02_Pandas_annotations.ipynb

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      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/OmarFloresPTY/my-google-colabs/blob/master/02_Pandas_annotations.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "source": [
        "# 10 minutes to pandas 🐼📚🐍"
      ],
      "metadata": {
        "id": "y2YJ-0-EtSWt"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "a5piwFfAbW6e"
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      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Object Creation"
      ],
      "metadata": {
        "id": "xCFEzpOz3gNd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "s = pd.Series([1,3,4,np.nan,6,8])\n",
        "s"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "huToMScX258d",
        "outputId": "c3740d7e-9f1e-40c2-9d7b-da4414a30fda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1.0\n",
              "1    3.0\n",
              "2    4.0\n",
              "3    NaN\n",
              "4    6.0\n",
              "5    8.0\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dates = pd.date_range('20130101',periods=6)\n",
        "dates"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cq9zOH_E3kvv",
        "outputId": "25eff5bb-4476-43e9-9655-42dfcdf0e1b4"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',\n",
              "               '2013-01-05', '2013-01-06'],\n",
              "              dtype='datetime64[ns]', freq='D')"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(np.random.randn(6,4),index=dates,columns=list('ABCD')) #np.random.randn(fila,columna) genera una matriz fila x columna de 0 y una desviación estándar de 1"
      ],
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              "                   A         B         C         D\n",
              "2013-01-01  0.494200 -0.025161  2.316596  0.055902\n",
              "2013-01-02 -1.143214  0.456303 -1.134004  0.530386\n",
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              "2013-01-04 -0.143476  0.605036 -1.119808  1.443138\n",
              "2013-01-05 -0.519936  1.152605  1.139425  1.568212\n",
              "2013-01-06  1.119840  1.447411  0.460106  0.406254"
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              "    A   B   C   D   E\n",
              "5  15  11  17  12   9\n",
              "6   5  19   7   1  18\n",
              "7  14   7   8   1   7\n",
              "8  17   5  18   1  10\n",
              "9  18   7  10  14   8"
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              "      <th>5</th>\n",
              "      <td>15</td>\n",
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              "      <td>9</td>\n",
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              "      <th>6</th>\n",
              "      <td>5</td>\n",
              "      <td>19</td>\n",
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              "      <td>1</td>\n",
              "      <td>18</td>\n",
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              "      <th>7</th>\n",
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              "    domScope.querySelector('#df-6b9a2a32-ede4-4b70-8a78-091470691fcf button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a723df2c-62f3-49c4-bc31-4b1436fd324b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a723df2c-62f3-49c4-bc31-4b1436fd324b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = pd.DataFrame(\n",
        "    {\n",
        "        \"A\": 1.0,\n",
        "        \"B\": pd.Timestamp(\"20130102\"),\n",
        "        \"C\": pd.Series(1, index=list(range(4)), dtype=\"float32\"),\n",
        "        \"D\": np.array([3] * 4, dtype=\"int32\"),\n",
        "        \"E\": pd.Categorical([\"test\", \"train\", \"test\", \"train\"]),\n",
        "        \"F\": \"foo\",\n",
        "    }\n",
        ")\n",
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "kzFvlQBgBBZB",
        "outputId": "3b0f514d-67b3-41a8-c13a-c7a071842a5d"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     A          B    C  D      E    F\n",
              "0  1.0 2013-01-02  1.0  3   test  foo\n",
              "1  1.0 2013-01-02  1.0  3  train  foo\n",
              "2  1.0 2013-01-02  1.0  3   test  foo\n",
              "3  1.0 2013-01-02  1.0  3  train  foo"
            ],
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              "\n",
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              "    <tr>\n",
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              "      <td>1.0</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ea8553d3-701c-495a-8b8a-ca9dce43836e')\"\n",
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              "              style=\"display:none;\">\n",
              "\n",
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              "\n",
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              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e44f6826-4428-46ba-86af-61f28016327e')\"\n",
              "              title=\"Suggest charts.\"\n",
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              "\n",
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              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-e44f6826-4428-46ba-86af-61f28016327e button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ea8553d3-701c-495a-8b8a-ca9dce43836e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ea8553d3-701c-495a-8b8a-ca9dce43836e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Viewing Data"
      ],
      "metadata": {
        "id": "zKMjYenqkuBu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "index = pd.date_range(\"1/1/2000\", periods=8)\n",
        "df = pd.DataFrame(np.random.randn(8, 3), index=index, columns=[\"A\", \"B\", \"C\"])\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "1hDs0l_Jkw8t",
        "outputId": "aeb6266d-dbdc-4cff-d78c-3ade8f3d225f"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.966314  0.931645  0.303348\n",
              "2000-01-02 -2.205841  0.202679  1.066221\n",
              "2000-01-03 -1.185118  0.649188 -0.422109\n",
              "2000-01-04 -0.567090 -0.104624 -0.856980\n",
              "2000-01-05 -0.000358 -1.666904  0.364500\n",
              "2000-01-06  0.438707 -1.157793 -0.086172\n",
              "2000-01-07  0.821727  1.138478 -0.723475\n",
              "2000-01-08 -0.896600 -1.694298  1.776689"
            ],
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              "\n",
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              "      <th>2000-01-01</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
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              "      <th>2000-01-05</th>\n",
              "      <td>-0.000358</td>\n",
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              "      <td>-0.086172</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>0.821727</td>\n",
              "      <td>1.138478</td>\n",
              "      <td>-0.723475</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>-0.896600</td>\n",
              "      <td>-1.694298</td>\n",
              "      <td>1.776689</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-77d6f0c9-a3c5-4398-8993-de9a411d7905')\"\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
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              "\n",
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              "    background-color: #E2EBFA;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
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              "\n",
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              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-dc0e1336-4260-4382-b47f-0b5acd787156 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        displayQuickchartButton(document);\n",
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              "\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-77d6f0c9-a3c5-4398-8993-de9a411d7905 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-77d6f0c9-a3c5-4398-8993-de9a411d7905');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "hHJDk7GHlBtp",
        "outputId": "a40a30bc-9c49-4506-e12a-f62c27733185"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
              "2000-01-03 -0.656894  0.370821  0.250454\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362\n",
              "2000-01-05  0.097053 -0.033579 -0.465060"
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              "\n",
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              "          document.querySelector('#df-371e6145-bea4-493f-8f83-614deb3ee2fe button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-371e6145-bea4-493f-8f83-614deb3ee2fe');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.tail(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
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        "id": "53hhzrmplGAw",
        "outputId": "917078b1-db3b-4fb1-fbee-8eb653d94b53"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-06  0.462307  0.545508  0.839077\n",
              "2000-01-07 -0.607997  0.210907 -0.563551\n",
              "2000-01-08  0.239716  1.017750 -0.481969"
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-2f3f9a58-c508-4daf-81e1-94e202fcbcf2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2f3f9a58-c508-4daf-81e1-94e202fcbcf2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.index"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rm0x8P8hlPVv",
        "outputId": "7e11fe13-49a2-40ef-c996-5b628f18b8f0"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03', '2000-01-04',\n",
              "               '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-08'],\n",
              "              dtype='datetime64[ns]', freq='D')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qWk1NqdXlRDk",
        "outputId": "2c6b11a5-5d20-4645-84fc-f45b120bb097"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['A', 'B', 'C'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "¡IMPORTANTE! 🚨 La conversión de un dataFrame a un objeto numpy, NO incluye los índices o columnas."
      ],
      "metadata": {
        "id": "WnLABrzampXI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_numpy()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mKVU5--fmKnR",
        "outputId": "633cd6c1-84e9-4e86-8792-d3ea282c7446"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 0.74865878, -1.15096065,  1.3409273 ],\n",
              "       [ 1.75377906,  0.05424516, -0.17420374],\n",
              "       [-0.65689382,  0.37082057,  0.25045367],\n",
              "       [-0.46413663, -1.97061271, -0.47336161],\n",
              "       [ 0.09705327, -0.03357883, -0.46506048],\n",
              "       [ 0.46230739,  0.5455077 ,  0.83907677],\n",
              "       [-0.60799694,  0.21090727, -0.5635506 ],\n",
              "       [ 0.23971553,  1.01774995, -0.48196859]])"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(type(df))\n",
        "print(type(df.to_numpy()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tg4IyL3FmO1-",
        "outputId": "c81f83a3-7852-4a40-e5ce-8c534c7d4b8a"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "<class 'numpy.ndarray'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.to_numpy()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0Kd93IDUmcWv",
        "outputId": "76eafef7-7bf6-43af-d699-bd13ade4c9d5"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'test', 'foo'],\n",
              "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'train', 'foo'],\n",
              "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'test', 'foo'],\n",
              "       [1.0, Timestamp('2013-01-02 00:00:00'), 1.0, 3, 'train', 'foo']],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "id": "73jpe45x2XMS",
        "outputId": "b26eb819-e6b8-43d0-d9dd-747d085be507",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              A         B         C\n",
              "count  8.000000  8.000000  8.000000\n",
              "mean   0.196561 -0.119490  0.034039\n",
              "std    0.812786  0.971983  0.714760\n",
              "min   -0.656894 -1.970613 -0.563551\n",
              "25%   -0.500102 -0.312924 -0.475513\n",
              "50%    0.168384  0.132576 -0.319632\n",
              "75%    0.533895  0.414492  0.397609\n",
              "max    1.753779  1.017750  1.340927"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-269a500c-0994-4f8a-af8a-9a16b6fea7bf\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>8.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.196561</td>\n",
              "      <td>-0.119490</td>\n",
              "      <td>0.034039</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.812786</td>\n",
              "      <td>0.971983</td>\n",
              "      <td>0.714760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-0.656894</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.563551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.500102</td>\n",
              "      <td>-0.312924</td>\n",
              "      <td>-0.475513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.168384</td>\n",
              "      <td>0.132576</td>\n",
              "      <td>-0.319632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.533895</td>\n",
              "      <td>0.414492</td>\n",
              "      <td>0.397609</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.753779</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>1.340927</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-269a500c-0994-4f8a-af8a-9a16b6fea7bf')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-c0dfcb57-30e3-4cc3-a8b0-2f5ebfebd217\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c0dfcb57-30e3-4cc3-a8b0-2f5ebfebd217')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-c0dfcb57-30e3-4cc3-a8b0-2f5ebfebd217 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-269a500c-0994-4f8a-af8a-9a16b6fea7bf button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-269a500c-0994-4f8a-af8a-9a16b6fea7bf');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.T"
      ],
      "metadata": {
        "id": "5vEsuwjg2hyI",
        "outputId": "c89a4f1a-da17-44bb-8860-3dd52282c9ae",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        }
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   2000-01-01  2000-01-02  2000-01-03  2000-01-04  2000-01-05  2000-01-06  \\\n",
              "A    0.748659    1.753779   -0.656894   -0.464137    0.097053    0.462307   \n",
              "B   -1.150961    0.054245    0.370821   -1.970613   -0.033579    0.545508   \n",
              "C    1.340927   -0.174204    0.250454   -0.473362   -0.465060    0.839077   \n",
              "\n",
              "   2000-01-07  2000-01-08  \n",
              "A   -0.607997    0.239716  \n",
              "B    0.210907    1.017750  \n",
              "C   -0.563551   -0.481969  "
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-967072ea-847c-4996-a684-6720800bd14c\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>2000-01-01</th>\n",
              "      <th>2000-01-02</th>\n",
              "      <th>2000-01-03</th>\n",
              "      <th>2000-01-04</th>\n",
              "      <th>2000-01-05</th>\n",
              "      <th>2000-01-06</th>\n",
              "      <th>2000-01-07</th>\n",
              "      <th>2000-01-08</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <td>0.748659</td>\n",
              "      <td>1.753779</td>\n",
              "      <td>-0.656894</td>\n",
              "      <td>-0.464137</td>\n",
              "      <td>0.097053</td>\n",
              "      <td>0.462307</td>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.239716</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>B</th>\n",
              "      <td>-1.150961</td>\n",
              "      <td>0.054245</td>\n",
              "      <td>0.370821</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>1.017750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>C</th>\n",
              "      <td>1.340927</td>\n",
              "      <td>-0.174204</td>\n",
              "      <td>0.250454</td>\n",
              "      <td>-0.473362</td>\n",
              "      <td>-0.465060</td>\n",
              "      <td>0.839077</td>\n",
              "      <td>-0.563551</td>\n",
              "      <td>-0.481969</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-967072ea-847c-4996-a684-6720800bd14c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-c310d567-8e6c-4710-a791-019e5445fb98 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
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              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-967072ea-847c-4996-a684-6720800bd14c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-967072ea-847c-4996-a684-6720800bd14c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "id": "KMLd-2JY3RMZ",
        "outputId": "eea84049-718e-4b86-a3fc-49562be7318d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
              "2000-01-03 -0.656894  0.370821  0.250454\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362\n",
              "2000-01-05  0.097053 -0.033579 -0.465060\n",
              "2000-01-06  0.462307  0.545508  0.839077\n",
              "2000-01-07 -0.607997  0.210907 -0.563551\n",
              "2000-01-08  0.239716  1.017750 -0.481969"
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              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
              "      <td>-0.174204</td>\n",
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              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
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              "      <td>-0.464137</td>\n",
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              "      <th>2000-01-06</th>\n",
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              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>-0.481969</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f27f3e77-34fa-41b8-9e56-22df767c6d86')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "    display: none;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-bb4ee497-a496-4669-9ec7-1a9a2ca13243 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f27f3e77-34fa-41b8-9e56-22df767c6d86 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f27f3e77-34fa-41b8-9e56-22df767c6d86');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.sort_index(axis=1,ascending=False)"
      ],
      "metadata": {
        "id": "_s5oSu2q2sHR",
        "outputId": "fdfcd772-b2e4-4dab-aac3-e2c07d82e1e9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   C         B         A\n",
              "2000-01-01  1.340927 -1.150961  0.748659\n",
              "2000-01-02 -0.174204  0.054245  1.753779\n",
              "2000-01-03  0.250454  0.370821 -0.656894\n",
              "2000-01-04 -0.473362 -1.970613 -0.464137\n",
              "2000-01-05 -0.465060 -0.033579  0.097053\n",
              "2000-01-06  0.839077  0.545508  0.462307\n",
              "2000-01-07 -0.563551  0.210907 -0.607997\n",
              "2000-01-08 -0.481969  1.017750  0.239716"
            ],
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              "      <div>\n",
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              "      <td>-1.150961</td>\n",
              "      <td>0.748659</td>\n",
              "    </tr>\n",
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              "      <th>2000-01-02</th>\n",
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              "      <td>0.250454</td>\n",
              "      <td>0.370821</td>\n",
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              "    </tr>\n",
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              "      <td>-0.473362</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>-0.465060</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>0.097053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.839077</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.462307</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.563551</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.607997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>-0.481969</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>0.239716</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d9c4ca95-d7e0-489f-aa63-9c4aac077f8c')\"\n",
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              "              title=\"Suggest charts.\"\n",
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              "\n",
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              "\n",
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              "    background-color: #3B4455;\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "\n",
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              "\n",
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              "}\n",
              "\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d9c4ca95-d7e0-489f-aa63-9c4aac077f8c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d9c4ca95-d7e0-489f-aa63-9c4aac077f8c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.sort_values(by=\"B\")"
      ],
      "metadata": {
        "id": "eQPIpEKR3wl9",
        "outputId": "59bea9c8-2213-48e0-8cc0-913478dfc866",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-05  0.097053 -0.033579 -0.465060\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
              "2000-01-07 -0.607997  0.210907 -0.563551\n",
              "2000-01-03 -0.656894  0.370821  0.250454\n",
              "2000-01-06  0.462307  0.545508  0.839077\n",
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              "      <td>0.748659</td>\n",
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              "\n",
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              "\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a047f396-490b-42dc-99a3-c9cfdd2d041d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a047f396-490b-42dc-99a3-c9cfdd2d041d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Getting\n",
        "Selecting a single column, which yields a Series."
      ],
      "metadata": {
        "id": "fF8WCtpD382F"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "rPLP8UpxS1BH",
        "outputId": "4c7c5476-c9d3-443c-fa48-c0d2fedd6450"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
              "2000-01-03 -0.656894  0.370821  0.250454\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362\n",
              "2000-01-05  0.097053 -0.033579 -0.465060\n",
              "2000-01-06  0.462307  0.545508  0.839077\n",
              "2000-01-07 -0.607997  0.210907 -0.563551\n",
              "2000-01-08  0.239716  1.017750 -0.481969"
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              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2000-01-01</th>\n",
              "      <td>0.748659</td>\n",
              "      <td>-1.150961</td>\n",
              "      <td>1.340927</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
              "      <td>-0.174204</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
              "      <td>0.370821</td>\n",
              "      <td>0.250454</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.473362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>0.097053</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>-0.465060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.839077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>-0.481969</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4c5e1847-9401-4b1d-9b0c-b58f66192f74')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-6e040370-cd6c-4eca-acc3-df61b88a8f26\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6e040370-cd6c-4eca-acc3-df61b88a8f26')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-6e040370-cd6c-4eca-acc3-df61b88a8f26 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4c5e1847-9401-4b1d-9b0c-b58f66192f74 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4c5e1847-9401-4b1d-9b0c-b58f66192f74');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['A']"
      ],
      "metadata": {
        "id": "_gaABm1u3-YA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d5667e69-f120-410c-cd96-336837bb5a83"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2000-01-01    0.748659\n",
              "2000-01-02    1.753779\n",
              "2000-01-03   -0.656894\n",
              "2000-01-04   -0.464137\n",
              "2000-01-05    0.097053\n",
              "2000-01-06    0.462307\n",
              "2000-01-07   -0.607997\n",
              "2000-01-08    0.239716\n",
              "Freq: D, Name: A, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[0:3]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "KEwzoQkbSayq",
        "outputId": "27381300-844c-4792-f1e6-480d0d859df2"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
              "2000-01-03 -0.656894  0.370821  0.250454"
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              "      <th>2000-01-01</th>\n",
              "      <td>0.748659</td>\n",
              "      <td>-1.150961</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
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              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5f5cad33-fa1e-4db7-a40a-3a59ffd03be5')\"\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
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              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-86d5fe8b-0821-41b5-bf15-aa43e772fefa button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5f5cad33-fa1e-4db7-a40a-3a59ffd03be5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5f5cad33-fa1e-4db7-a40a-3a59ffd03be5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Selection by label"
      ],
      "metadata": {
        "id": "kqGTTxbsS7s7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[:,['A','B']]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "ZgcuydysWGBi",
        "outputId": "c7b34001-93c5-47b4-aa70-1b5b12b68547"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B\n",
              "2000-01-01  0.748659 -1.150961\n",
              "2000-01-02  1.753779  0.054245\n",
              "2000-01-03 -0.656894  0.370821\n",
              "2000-01-04 -0.464137 -1.970613\n",
              "2000-01-05  0.097053 -0.033579\n",
              "2000-01-06  0.462307  0.545508\n",
              "2000-01-07 -0.607997  0.210907\n",
              "2000-01-08  0.239716  1.017750"
            ],
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              "      <div>\n",
              "<style scoped>\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2000-01-01</th>\n",
              "      <td>0.748659</td>\n",
              "      <td>-1.150961</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
              "      <td>0.370821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>0.097053</td>\n",
              "      <td>-0.033579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
              "      <td>0.545508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cd2a2674-4e9f-4155-b73a-ba23253febf4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
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              "              title=\"Suggest charts.\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-8fb9efe9-bc7a-4ea2-bff5-dd8e2ff7993a button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-cd2a2674-4e9f-4155-b73a-ba23253febf4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cd2a2674-4e9f-4155-b73a-ba23253febf4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[\"20000101\":\"20000104\", [\"A\", \"B\"]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "6z604kOoWSOi",
        "outputId": "572b01be-ae7c-484f-d2cd-34e0f356101d"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B\n",
              "2000-01-01  0.748659 -1.150961\n",
              "2000-01-02  1.753779  0.054245\n",
              "2000-01-03 -0.656894  0.370821\n",
              "2000-01-04 -0.464137 -1.970613"
            ],
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              "\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "      <td>-0.656894</td>\n",
              "      <td>0.370821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a6b8e9d2-9df3-458a-a6e3-2332672e39ef')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
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              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-9cf3a512-4191-4a1c-975e-ccbbbd259f5a button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a6b8e9d2-9df3-458a-a6e3-2332672e39ef button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a6b8e9d2-9df3-458a-a6e3-2332672e39ef');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "index[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DRY2P_69Wkrq",
        "outputId": "ee0b02b3-cc9a-4f6f-f1cb-0e3e42a8e65d"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2000-01-01 00:00:00', freq='D')"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[index[0],\"A\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MAqsa4LJWdFf",
        "outputId": "ef4843b5-82e6-4e94-a5d0-cf786cca5d3f"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.748658778023008"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.at[index[0],\"A\"] #Exactamente igual pero más rápido en memoria."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9yVIV8iHXe7b",
        "outputId": "de7e7f46-cc39-408e-c54c-1ee4467d4acd"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.748658778023008"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Selection by position"
      ],
      "metadata": {
        "id": "N1HSUJx1YR-W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "ziN0LIWhYaIq",
        "outputId": "3a56e189-4745-4e26-c95c-35b71dd7465e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
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              "                                                     [key], {});\n",
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            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[3] ##Accede al registro de la posición 3 en el dataFrame"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q47bJQadYUym",
        "outputId": "b42e510e-6f03-491f-824f-8d8bd4f9e95f"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "A   -0.464137\n",
              "B   -1.970613\n",
              "C   -0.473362\n",
              "Name: 2000-01-04 00:00:00, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[3:5, 0:2] #Primer slice son filas, segundo slice son columnas"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 112
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        "id": "9wSalJIWYo1d",
        "outputId": "97187a18-bb28-4820-fc12-b4e3a7fedfaa"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B\n",
              "2000-01-04 -0.464137 -1.970613\n",
              "2000-01-05  0.097053 -0.033579"
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "          dataTable['output_type'] = 'display_data';\n",
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          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[[1,2,4],[0,2]] #Filtrando por índices específicos"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "DWdNq5XmkYB3",
        "outputId": "02028377-8f5c-464b-cce6-95ee2d306e6f"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         C\n",
              "2000-01-02  1.753779 -0.174204\n",
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              "2000-01-05  0.097053 -0.465060"
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              "\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ]
          },
          "metadata": {},
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        }
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    },
    {
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          "height": 112
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        "id": "wGUpNot0lSS6",
        "outputId": "95a6f5c3-d1ec-413a-ebe7-690c4ed24066"
      },
      "execution_count": 31,
      "outputs": [
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          "data": {
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              "                   A         B         C\n",
              "2000-01-02  1.753779  0.054245 -0.174204\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
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    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[:, 1:3]"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "sp_0ly2mlYLb",
        "outputId": "6597ff23-5496-438f-88d9-a0469c0a1003"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                   B         C\n",
              "2000-01-01 -1.150961  1.340927\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "\n",
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              "      display:flex;\n",
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              "\n",
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              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c048f537-0ad1-47c1-95a8-980ffc56d10c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c048f537-0ad1-47c1-95a8-980ffc56d10c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[1,1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lc6TjA9mlt3k",
        "outputId": "66257dd4-fefa-48aa-f2f2-0d710cb35fb3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.4935545440006357"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iat[1,1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V7seLjlzlv81",
        "outputId": "2eb0bbd3-1971-4346-aa9b-55f0d714aaf2"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0542451607868941"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Boolean indexing"
      ],
      "metadata": {
        "id": "Usj7aCcloqaw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['A'] > 0.5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "x2RSKNTNoszq",
        "outputId": "19d5cf97-0e9e-4c66-e559-189e05bad72c"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659 -1.150961  1.340927\n",
              "2000-01-02  1.753779  0.054245 -0.174204"
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              "\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[df > 0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "zayTy-0rpn3I",
        "outputId": "7a04bf4d-a3f0-4156-d926-ad265c83b4b7"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01  0.748659       NaN  1.340927\n",
              "2000-01-02  1.753779  0.054245       NaN\n",
              "2000-01-03       NaN  0.370821  0.250454\n",
              "2000-01-04       NaN       NaN       NaN\n",
              "2000-01-05  0.097053       NaN       NaN\n",
              "2000-01-06  0.462307  0.545508  0.839077\n",
              "2000-01-07       NaN  0.210907       NaN\n",
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              "      <td>NaN</td>\n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c6ab6819-6f9d-457c-8001-8b56323e5ce9')\"\n",
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              "\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-c6ab6819-6f9d-457c-8001-8b56323e5ce9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c6ab6819-6f9d-457c-8001-8b56323e5ce9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = df.copy()\n",
        "df2[\"E\"] = [\"one\", \"one\", \"two\", \"three\", \"four\", \"three\",\"four\", \"three\"]\n",
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "_X-AE3Otq56D",
        "outputId": "a64cc151-c238-4731-fcfb-ae868b39e697"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C      E\n",
              "2000-01-01  0.748659 -1.150961  1.340927    one\n",
              "2000-01-02  1.753779  0.054245 -0.174204    one\n",
              "2000-01-03 -0.656894  0.370821  0.250454    two\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  three\n",
              "2000-01-05  0.097053 -0.033579 -0.465060   four\n",
              "2000-01-06  0.462307  0.545508  0.839077  three\n",
              "2000-01-07 -0.607997  0.210907 -0.563551   four\n",
              "2000-01-08  0.239716  1.017750 -0.481969  three"
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              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
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              "      <td>three</td>\n",
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              "\n",
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              "\n",
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              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7b2e509a-5dc4-4651-9fd6-ef0357fffb2b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7b2e509a-5dc4-4651-9fd6-ef0357fffb2b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2[df2[\"E\"].isin([\"two\",\"four\"])] #El método isin() funciona para filtrar también."
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "J7pRPgQ0rMny",
        "outputId": "20d06fd8-4ff7-4948-f915-c9cd0762d9aa"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C     E\n",
              "2000-01-03 -0.656894  0.370821  0.250454   two\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  four\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  four"
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              "      <td>0.097053</td>\n",
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              "      <td>-0.465060</td>\n",
              "      <td>four</td>\n",
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              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "      <td>four</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-085bd8a0-8e77-4b63-9843-1a19c706aad6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-b8587df0-0a4d-4465-835c-6e1abe5eaa43\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b8587df0-0a4d-4465-835c-6e1abe5eaa43')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-b8587df0-0a4d-4465-835c-6e1abe5eaa43 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-085bd8a0-8e77-4b63-9843-1a19c706aad6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-085bd8a0-8e77-4b63-9843-1a19c706aad6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Setting"
      ],
      "metadata": {
        "id": "6e8TeX-irczp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "s1 = pd.Series([1,2,3,4,5,6,7,8],index=pd.date_range(\"2000-01-01\", periods=8))\n",
        "s1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CYnEIwlDrfAW",
        "outputId": "7e3477b8-14ba-49da-9843-f389836829d8"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2000-01-01    1\n",
              "2000-01-02    2\n",
              "2000-01-03    3\n",
              "2000-01-04    4\n",
              "2000-01-05    5\n",
              "2000-01-06    6\n",
              "2000-01-07    7\n",
              "2000-01-08    8\n",
              "Freq: D, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[\"F\"] = s1\n",
        "df"
      ],
      "metadata": {
        "id": "Ceu6G_REsxwZ",
        "outputId": "0053463e-2fa7-49a7-ce37-9de43138a598",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F\n",
              "2000-01-01  0.748659 -1.150961  1.340927  1\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7\n",
              "2000-01-08  0.239716  1.017750 -0.481969  8"
            ],
            "text/html": [
              "\n",
              "\n",
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              "<style scoped>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>F</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2000-01-01</th>\n",
              "      <td>0.748659</td>\n",
              "      <td>-1.150961</td>\n",
              "      <td>1.340927</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
              "      <td>-0.174204</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
              "      <td>0.370821</td>\n",
              "      <td>0.250454</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.473362</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>0.097053</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>-0.465060</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.839077</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>-0.481969</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-73c2a610-bcca-48b0-a968-9c12dd5c3f87')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-2a4843d0-5b1a-4e1e-b800-1c338effed20\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2a4843d0-5b1a-4e1e-b800-1c338effed20')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-2a4843d0-5b1a-4e1e-b800-1c338effed20 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-73c2a610-bcca-48b0-a968-9c12dd5c3f87 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-73c2a610-bcca-48b0-a968-9c12dd5c3f87');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.at[index[0],\"A\"] = 0\n",
        "df"
      ],
      "metadata": {
        "id": "hURUSvpZtEQ3",
        "outputId": "4e9af84d-95b8-4a11-875a-9deb8af7c181",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F\n",
              "2000-01-01  0.000000 -1.150961  1.340927  1\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7\n",
              "2000-01-08  0.239716  1.017750 -0.481969  8"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-4d6f331d-e611-4888-88e2-7a3a8193009a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "    }\n",
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>F</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2000-01-01</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>-1.150961</td>\n",
              "      <td>1.340927</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
              "      <td>-0.174204</td>\n",
              "      <td>2</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
              "      <td>0.370821</td>\n",
              "      <td>0.250454</td>\n",
              "      <td>3</td>\n",
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              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.473362</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>0.097053</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>-0.465060</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.839077</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>-0.481969</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4d6f331d-e611-4888-88e2-7a3a8193009a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
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              "\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
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              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-377c0c97-84d9-4084-a327-7b47fc1c156b button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4d6f331d-e611-4888-88e2-7a3a8193009a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4d6f331d-e611-4888-88e2-7a3a8193009a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iat[0, 1] = 0\n",
        "df"
      ],
      "metadata": {
        "id": "utaFgqiAtZxT",
        "outputId": "6ae808f4-66a7-4749-80bb-d66f51294867",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F\n",
              "2000-01-01  0.000000  0.000000  1.340927  1\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7\n",
              "2000-01-08  0.239716  1.017750 -0.481969  8"
            ],
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              "\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-78432dfe-6f4a-45a6-a35f-a570d3bc96ee button.colab-df-convert');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.loc[:, \"D\"] = np.array([5] * len(df))\n",
        "df"
      ],
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        "id": "HipFq2kEuFDE",
        "outputId": "b5345451-a9db-43f2-df0a-cded3c92425f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                   A         B         C  F  D\n",
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              "2000-01-05  0.097053 -0.033579 -0.465060  5  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6  5\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7  5\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c63e4774-9667-47f2-9561-84ef6e630e5e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = df.copy()\n",
        "df2[df2 > 0] = -df2\n",
        "df2"
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      "metadata": {
        "id": "IWkv7sdSupXH",
        "outputId": "f83a1668-a865-46c2-f322-ba3ac6172d12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F  D\n",
              "2000-01-01  0.000000  0.000000 -1.340927 -1 -5\n",
              "2000-01-02 -1.753779 -0.054245 -0.174204 -2 -5\n",
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              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f5c945d2-b407-49d6-93c0-bb206b7228e0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f5c945d2-b407-49d6-93c0-bb206b7228e0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Missing data"
      ],
      "metadata": {
        "id": "IH-ubSNNu_bh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "id": "KJvUcbZhvBsJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "outputId": "bf9a896a-df2b-4e2e-9fc6-9e9b32aac92c"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F  D\n",
              "2000-01-01  0.000000  0.000000  1.340927  1  5\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2  5\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3  5\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4  5\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  5  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6  5\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7  5\n",
              "2000-01-08  0.239716  1.017750 -0.481969  8  5"
            ],
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              "\n",
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              "      <td>1.753779</td>\n",
              "      <td>0.054245</td>\n",
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              "      <td>2</td>\n",
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              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
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              "      <td>3</td>\n",
              "      <td>5</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>-0.464137</td>\n",
              "      <td>-1.970613</td>\n",
              "      <td>-0.473362</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>0.097053</td>\n",
              "      <td>-0.033579</td>\n",
              "      <td>-0.465060</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
              "      <td>0.545508</td>\n",
              "      <td>0.839077</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>-0.607997</td>\n",
              "      <td>0.210907</td>\n",
              "      <td>-0.563551</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-08</th>\n",
              "      <td>0.239716</td>\n",
              "      <td>1.017750</td>\n",
              "      <td>-0.481969</td>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-23d92c65-19a3-47cb-8b38-b10dfd4cb6ff')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
              "\n",
              "\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
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              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-70e9ea25-a543-40a6-a006-2963d844575a button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-23d92c65-19a3-47cb-8b38-b10dfd4cb6ff button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-23d92c65-19a3-47cb-8b38-b10dfd4cb6ff');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1 = df.reindex(index=index[0:4],columns=list(df.columns)+[\"E\"])\n",
        "df1.loc[index[0] : index[1], \"E\"] = 1\n",
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "X6RZlqkvlw70",
        "outputId": "72ca7284-5bea-4c54-f2fb-59abb889dcaa"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F  D    E\n",
              "2000-01-01  0.000000  0.000000  1.340927  1  5  1.0\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2  5  1.0\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3  5  NaN\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4  5  NaN"
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              "\n",
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              "      <th>2000-01-01</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>2000-01-02</th>\n",
              "      <td>1.753779</td>\n",
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              "      <th>2000-01-03</th>\n",
              "      <td>-0.656894</td>\n",
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              "              title=\"Suggest charts.\"\n",
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              "\n",
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              "\n",
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              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
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              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
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              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-73a1d82d-462f-4bf6-a176-7253dde4e7f4 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
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              "      display:flex;\n",
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              "      display: none;\n",
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              "\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0a3835f9-fb31-4d36-8b37-3118f1fa017b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0a3835f9-fb31-4d36-8b37-3118f1fa017b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.dropna(how=\"any\")"
      ],
      "metadata": {
        "colab": {
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          "height": 112
        },
        "id": "8EZVIogDm1hE",
        "outputId": "373e9b60-6c4a-4129-cc8b-11b265236145"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                   A         B         C  F  D    E\n",
              "2000-01-01  0.000000  0.000000  1.340927  1  5  1.0\n",
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              "\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
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              "\n",
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              "    domScope.querySelector('#df-d6619bd6-5165-4b43-b81e-709109d793f4 button.colab-df-quickchart');\n",
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              "      background-color: #E8F0FE;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "          document.querySelector('#df-06fe6109-e692-4aa1-92e8-2a8f0951d5c7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-06fe6109-e692-4aa1-92e8-2a8f0951d5c7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df1.fillna(value=5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "sxCP4u9znSTM",
        "outputId": "abe48a98-38d9-434f-cc26-21f918296c9c"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F  D    E\n",
              "2000-01-01  0.000000  0.000000  1.340927  1  5  1.0\n",
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              "2000-01-03 -0.656894  0.370821  0.250454  3  5  5.0\n",
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              "\n",
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              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "    .colab-df-container {\n",
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              "\n",
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              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0c546092-b705-45b9-b1c4-c9eb7c2d50a3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0c546092-b705-45b9-b1c4-c9eb7c2d50a3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.isna(df1)"
      ],
      "metadata": {
        "id": "yeiokogjuSyD",
        "outputId": "f8f5b1ee-5054-456c-84db-2e513c5a7b9c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        }
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                A      B      C      F      D      E\n",
              "2000-01-01  False  False  False  False  False  False\n",
              "2000-01-02  False  False  False  False  False  False\n",
              "2000-01-03  False  False  False  False  False   True\n",
              "2000-01-04  False  False  False  False  False   True"
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              "      <th>2000-01-04</th>\n",
              "      <td>False</td>\n",
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              "        const containerElement = document.querySelector('#' + key);\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-6f1bc18b-6122-4fab-8ea7-8a7f162b409b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6f1bc18b-6122-4fab-8ea7-8a7f162b409b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Operations"
      ],
      "metadata": {
        "id": "VsZ-FWr3uhgu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df"
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        "id": "cZv_dl3uujR_",
        "outputId": "ea8b7b64-dca4-4aaf-912c-404d86549093",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C  F  D\n",
              "2000-01-01  0.000000  0.000000  1.340927  1  5\n",
              "2000-01-02  1.753779  0.054245 -0.174204  2  5\n",
              "2000-01-03 -0.656894  0.370821  0.250454  3  5\n",
              "2000-01-04 -0.464137 -1.970613 -0.473362  4  5\n",
              "2000-01-05  0.097053 -0.033579 -0.465060  5  5\n",
              "2000-01-06  0.462307  0.545508  0.839077  6  5\n",
              "2000-01-07 -0.607997  0.210907 -0.563551  7  5\n",
              "2000-01-08  0.239716  1.017750 -0.481969  8  5"
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              "      <th>2000-01-06</th>\n",
              "      <td>0.462307</td>\n",
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              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-47039464-7f30-493b-8d9b-e0e37ee646de button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-21d7cb48-4c52-4c16-935e-fc7e7432e3c3 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-21d7cb48-4c52-4c16-935e-fc7e7432e3c3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.mean()"
      ],
      "metadata": {
        "id": "k28t2-p5umZG",
        "outputId": "48a280b2-d9f0-4a16-d3d6-deb683189576",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "A    0.102978\n",
              "B    0.024380\n",
              "C    0.034039\n",
              "F    4.500000\n",
              "D    5.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.mean(axis=1)"
      ],
      "metadata": {
        "id": "oERwdZmguwQt",
        "outputId": "13e32d67-19aa-47b2-ffc8-565bd660d87b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2000-01-01    1.468185\n",
              "2000-01-02    1.726764\n",
              "2000-01-03    1.592876\n",
              "2000-01-04    1.218378\n",
              "2000-01-05    1.919683\n",
              "2000-01-06    2.569378\n",
              "2000-01-07    2.207872\n",
              "2000-01-08    2.755099\n",
              "Freq: D, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s = pd.Series([1, 3, 5, np.nan, 6, 8,8,1], index=index).shift(2)\n",
        "s"
      ],
      "metadata": {
        "id": "nPrm0y2qvu6M",
        "outputId": "bce03624-628b-451d-f180-7205a7206f9b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2000-01-01    NaN\n",
              "2000-01-02    NaN\n",
              "2000-01-03    1.0\n",
              "2000-01-04    3.0\n",
              "2000-01-05    5.0\n",
              "2000-01-06    NaN\n",
              "2000-01-07    6.0\n",
              "2000-01-08    8.0\n",
              "Freq: D, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.sub(s, axis=\"index\")"
      ],
      "metadata": {
        "id": "b0jnpz8swIiG",
        "outputId": "960c406d-eb97-48c2-edb9-82739c37c40e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        }
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   A         B         C\n",
              "2000-01-01       NaN       NaN       NaN\n",
              "2000-01-02       NaN       NaN       NaN\n",
              "2000-01-03 -2.185118 -0.350812 -1.422109\n",
              "2000-01-04 -3.567090 -3.104624 -3.856980\n",
              "2000-01-05 -5.000358 -6.666904 -4.635500\n",
              "2000-01-06       NaN       NaN       NaN\n",
              "2000-01-07 -5.178273 -4.861522 -6.723475\n",
              "2000-01-08 -8.896600 -9.694298 -6.223311"
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              "      <th>2000-01-01</th>\n",
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              "      <th>2000-01-03</th>\n",
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              "      <td>-3.567090</td>\n",
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              "      <th>2000-01-08</th>\n",
              "      <td>-8.896600</td>\n",
              "      <td>-9.694298</td>\n",
              "      <td>-6.223311</td>\n",
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              "  </tbody>\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d045e345-6ce7-4bf5-928b-d907f8a4400f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-fb6ad975-5de5-48d1-9715-22e346d0e9cf button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d045e345-6ce7-4bf5-928b-d907f8a4400f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d045e345-6ce7-4bf5-928b-d907f8a4400f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Plotting"
      ],
      "metadata": {
        "id": "eobbZolVw2de"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "4upR2e6Zw1x-"
      },
      "execution_count": 69,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.close(\"all\")"
      ],
      "metadata": {
        "id": "cmLLM-jOxAVl"
      },
      "execution_count": 70,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ts = pd.Series(np.random.randn(1000),index=pd.date_range(\"1/1/2000\",periods=1000))\n",
        "ts = ts.cumsum()\n",
        "ts.plot();"
      ],
      "metadata": {
        "id": "Wat36-CxxHCt",
        "outputId": "74bd92b7-4b85-425b-d2f8-8c27d12bbb65",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        }
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.show();"
      ],
      "metadata": {
        "id": "gwOn3bRPxlrD"
      },
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(\n",
        "    np.random.randn(1000,4), index=ts.index, columns=[\"A\",\"B\",\"C\",\"D\"]\n",
        ")"
      ],
      "metadata": {
        "id": "iGQG3oEFxuoJ"
      },
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = df.cumsum()"
      ],
      "metadata": {
        "id": "Wq5PUI3Rx9gS"
      },
      "execution_count": 75,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure();"
      ],
      "metadata": {
        "id": "x9P8SCmNyAPA",
        "outputId": "34bd47ff-21a7-4861-a441-5c1062f1c95c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.plot();\n",
        "plt.legend(loc='best');"
      ],
      "metadata": {
        "id": "OWS3jNYRyDP_",
        "outputId": "8da7f267-9eb2-4fbb-cc89-8e0f949f70d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        }
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Importing and exporting data"
      ],
      "metadata": {
        "id": "VqNdRsQOzQgc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_excel(\"example.xlsx\",sheet_name='Sheet1') #Sheet_name es el nombre de la hoja"
      ],
      "metadata": {
        "id": "Ls3otAihyMAP"
      },
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.read_excel(\"example.xlsx\",\"Sheet1\", na_values=[\"NA\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "4oIIeL95zTnc",
        "outputId": "5f7f9439-4235-4190-ff97-05eb98728502"
      },
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Unnamed: 0          A          B         C         D\n",
              "0   2000-01-01  -0.377764   0.885891 -0.713470  1.249645\n",
              "1   2000-01-02   0.001138   1.154538 -0.860546  3.466671\n",
              "2   2000-01-03  -1.218679   1.148843  0.332636  2.726691\n",
              "3   2000-01-04   0.282326   2.172439  1.461189  2.423054\n",
              "4   2000-01-05   1.834416   1.784595  2.049084  1.852457\n",
              "..         ...        ...        ...       ...       ...\n",
              "995 2002-09-22 -45.202124 -39.033138  2.136208 -5.849337\n",
              "996 2002-09-23 -45.329542 -39.229431  0.877395 -6.729654\n",
              "997 2002-09-24 -44.217607 -38.635954  0.961738 -7.450612\n",
              "998 2002-09-25 -43.988762 -38.016456  1.201730 -8.805636\n",
              "999 2002-09-26 -42.417049 -37.708184  0.001456 -9.857482\n",
              "\n",
              "[1000 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-f47265de-49ee-4687-b7ee-c45f6abe5958\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>D</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2000-01-01</td>\n",
              "      <td>-0.377764</td>\n",
              "      <td>0.885891</td>\n",
              "      <td>-0.713470</td>\n",
              "      <td>1.249645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2000-01-02</td>\n",
              "      <td>0.001138</td>\n",
              "      <td>1.154538</td>\n",
              "      <td>-0.860546</td>\n",
              "      <td>3.466671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2000-01-03</td>\n",
              "      <td>-1.218679</td>\n",
              "      <td>1.148843</td>\n",
              "      <td>0.332636</td>\n",
              "      <td>2.726691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2000-01-04</td>\n",
              "      <td>0.282326</td>\n",
              "      <td>2.172439</td>\n",
              "      <td>1.461189</td>\n",
              "      <td>2.423054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2000-01-05</td>\n",
              "      <td>1.834416</td>\n",
              "      <td>1.784595</td>\n",
              "      <td>2.049084</td>\n",
              "      <td>1.852457</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>995</th>\n",
              "      <td>2002-09-22</td>\n",
              "      <td>-45.202124</td>\n",
              "      <td>-39.033138</td>\n",
              "      <td>2.136208</td>\n",
              "      <td>-5.849337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>996</th>\n",
              "      <td>2002-09-23</td>\n",
              "      <td>-45.329542</td>\n",
              "      <td>-39.229431</td>\n",
              "      <td>0.877395</td>\n",
              "      <td>-6.729654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>997</th>\n",
              "      <td>2002-09-24</td>\n",
              "      <td>-44.217607</td>\n",
              "      <td>-38.635954</td>\n",
              "      <td>0.961738</td>\n",
              "      <td>-7.450612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>998</th>\n",
              "      <td>2002-09-25</td>\n",
              "      <td>-43.988762</td>\n",
              "      <td>-38.016456</td>\n",
              "      <td>1.201730</td>\n",
              "      <td>-8.805636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999</th>\n",
              "      <td>2002-09-26</td>\n",
              "      <td>-42.417049</td>\n",
              "      <td>-37.708184</td>\n",
              "      <td>0.001456</td>\n",
              "      <td>-9.857482</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f47265de-49ee-4687-b7ee-c45f6abe5958')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-b3b5b532-e1ba-47e2-95e6-03a7e31c7b8a\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b3b5b532-e1ba-47e2-95e6-03a7e31c7b8a')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-b3b5b532-e1ba-47e2-95e6-03a7e31c7b8a button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f47265de-49ee-4687-b7ee-c45f6abe5958 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f47265de-49ee-4687-b7ee-c45f6abe5958');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv(\"foo.csv\")"
      ],
      "metadata": {
        "id": "v9pCd0Jtzx81"
      },
      "execution_count": 86,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.read_csv(\"foo.csv\")"
      ],
      "metadata": {
        "id": "_Jp1QeZizzJk",
        "outputId": "7baebf36-b1a6-4a98-98e0-f3e936051c91",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Unnamed: 0          A          B         C         D\n",
              "0    2000-01-01  -0.377764   0.885891 -0.713470  1.249645\n",
              "1    2000-01-02   0.001138   1.154538 -0.860546  3.466671\n",
              "2    2000-01-03  -1.218679   1.148843  0.332636  2.726691\n",
              "3    2000-01-04   0.282326   2.172439  1.461189  2.423054\n",
              "4    2000-01-05   1.834416   1.784595  2.049084  1.852457\n",
              "..          ...        ...        ...       ...       ...\n",
              "995  2002-09-22 -45.202124 -39.033138  2.136208 -5.849337\n",
              "996  2002-09-23 -45.329542 -39.229431  0.877395 -6.729654\n",
              "997  2002-09-24 -44.217607 -38.635954  0.961738 -7.450612\n",
              "998  2002-09-25 -43.988762 -38.016456  1.201730 -8.805636\n",
              "999  2002-09-26 -42.417049 -37.708184  0.001456 -9.857482\n",
              "\n",
              "[1000 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-35c38969-8cdd-44f9-928d-07745a01eef9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>D</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2000-01-01</td>\n",
              "      <td>-0.377764</td>\n",
              "      <td>0.885891</td>\n",
              "      <td>-0.713470</td>\n",
              "      <td>1.249645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2000-01-02</td>\n",
              "      <td>0.001138</td>\n",
              "      <td>1.154538</td>\n",
              "      <td>-0.860546</td>\n",
              "      <td>3.466671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2000-01-03</td>\n",
              "      <td>-1.218679</td>\n",
              "      <td>1.148843</td>\n",
              "      <td>0.332636</td>\n",
              "      <td>2.726691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2000-01-04</td>\n",
              "      <td>0.282326</td>\n",
              "      <td>2.172439</td>\n",
              "      <td>1.461189</td>\n",
              "      <td>2.423054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2000-01-05</td>\n",
              "      <td>1.834416</td>\n",
              "      <td>1.784595</td>\n",
              "      <td>2.049084</td>\n",
              "      <td>1.852457</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>995</th>\n",
              "      <td>2002-09-22</td>\n",
              "      <td>-45.202124</td>\n",
              "      <td>-39.033138</td>\n",
              "      <td>2.136208</td>\n",
              "      <td>-5.849337</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>996</th>\n",
              "      <td>2002-09-23</td>\n",
              "      <td>-45.329542</td>\n",
              "      <td>-39.229431</td>\n",
              "      <td>0.877395</td>\n",
              "      <td>-6.729654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>997</th>\n",
              "      <td>2002-09-24</td>\n",
              "      <td>-44.217607</td>\n",
              "      <td>-38.635954</td>\n",
              "      <td>0.961738</td>\n",
              "      <td>-7.450612</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>998</th>\n",
              "      <td>2002-09-25</td>\n",
              "      <td>-43.988762</td>\n",
              "      <td>-38.016456</td>\n",
              "      <td>1.201730</td>\n",
              "      <td>-8.805636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999</th>\n",
              "      <td>2002-09-26</td>\n",
              "      <td>-42.417049</td>\n",
              "      <td>-37.708184</td>\n",
              "      <td>0.001456</td>\n",
              "      <td>-9.857482</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1000 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-35c38969-8cdd-44f9-928d-07745a01eef9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-db00acae-585e-44a6-b573-548c33e84f4a\">\n",
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              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-db00acae-585e-44a6-b573-548c33e84f4a button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-35c38969-8cdd-44f9-928d-07745a01eef9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-35c38969-8cdd-44f9-928d-07745a01eef9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    }
  ]
}