12-stock-analysis.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stock Market Analysis using Python\n",
    "[Link](https://thecleverprogrammer.com/2022/07/12/stock-market-analysis-using-python/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "import datetime\n",
    "from datetime import date, timedelta\n",
    "import plotly.graph_objects as go\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "today = date.today()\n",
    "\n",
    "d1 = today.strftime(\"%Y-%m-%d\")\n",
    "end_date = d1\n",
    "\n",
    "d2 = date.today() - timedelta(days=365)\n",
    "d2 = d2.strftime(\"%Y-%m-%d\")\n",
    "start_date = d2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        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>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-05-20</td>\n",
       "      <td>112.085503</td>\n",
       "      <td>112.550003</td>\n",
       "      <td>106.373001</td>\n",
       "      <td>109.313004</td>\n",
       "      <td>109.313004</td>\n",
       "      <td>37586000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-05-23</td>\n",
       "      <td>110.103996</td>\n",
       "      <td>112.005501</td>\n",
       "      <td>109.154251</td>\n",
       "      <td>111.666496</td>\n",
       "      <td>111.666496</td>\n",
       "      <td>31558000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-05-24</td>\n",
       "      <td>106.377502</td>\n",
       "      <td>106.394997</td>\n",
       "      <td>102.208000</td>\n",
       "      <td>105.926003</td>\n",
       "      <td>105.926003</td>\n",
       "      <td>60386000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>105.141998</td>\n",
       "      <td>106.544701</td>\n",
       "      <td>104.211250</td>\n",
       "      <td>105.839500</td>\n",
       "      <td>105.839500</td>\n",
       "      <td>37900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>106.050499</td>\n",
       "      <td>108.955254</td>\n",
       "      <td>105.487999</td>\n",
       "      <td>108.295998</td>\n",
       "      <td>108.295998</td>\n",
       "      <td>30288000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date        Open        High         Low       Close   Adj Close  \\\n",
       "0 2022-05-20  112.085503  112.550003  106.373001  109.313004  109.313004   \n",
       "1 2022-05-23  110.103996  112.005501  109.154251  111.666496  111.666496   \n",
       "2 2022-05-24  106.377502  106.394997  102.208000  105.926003  105.926003   \n",
       "3 2022-05-25  105.141998  106.544701  104.211250  105.839500  105.839500   \n",
       "4 2022-05-26  106.050499  108.955254  105.487999  108.295998  108.295998   \n",
       "\n",
       "     Volume  \n",
       "0  37586000  \n",
       "1  31558000  \n",
       "2  60386000  \n",
       "3  37900000  \n",
       "4  30288000  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = yf.download(\n",
    "    'GOOG',\n",
    "    start=start_date,\n",
    "    end=end_date,\n",
    "    progress=False\n",
    ")\n",
    "\n",
    "data[\"Date\"] = data.index\n",
    "df1 = data[[\"Date\", \"Open\", \"High\", \"Low\", \"Close\", \"Adj Close\", \"Volume\"]]\n",
    "df1.reset_index(drop=True, inplace=True)\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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            "ticks": ""
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           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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          },
          "title": {
           "x": 0.05
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          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
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           "zerolinewidth": 2
          },
          "yaxis": {
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        },
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     },
     "metadata": {},
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   ],
   "source": [
    "figure = go.Figure(data=[go.Candlestick(\n",
    "    x=df1[\"Date\"],\n",
    "    open=df1[\"Open\"],\n",
    "    high=df1[\"High\"],\n",
    "    low=df1[\"Low\"],\n",
    "    close=df1[\"Close\"]\n",
    ")])\n",
    "\n",
    "figure.update_layout(title = \"Google Stock Price Analysis\", xaxis_rangeslider_visible=True)\n",
    "figure.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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     "data": {
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   "cell_type": "code",
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   "metadata": {},
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   ],
   "source": [
    "figure = px.line(\n",
    "    df1, \n",
    "    x='Date', y='Close',\n",
    "    title='Stock Market Analysis with Rangeslider'\n",
    "    )\n",
    "\n",
    "figure.update_xaxes(rangeslider_visible=True)\n",
    "figure.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
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          },
          "title": {
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           "ticks": "",
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        },
        "title": {
         "text": "Stock Market Analysis with Time Period Selectors"
        },
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         "anchor": "y",
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          0,
          1
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   "source": [
    "figure = px.line(\n",
    "    df1,\n",
    "    x='Date', y='Close',\n",
    "    title='Stock Market Analysis with Time Period Selectors'\n",
    ")\n",
    "\n",
    "figure.update_xaxes(\n",
    "    rangeselector=dict(\n",
    "        buttons=list([\n",
    "            dict(count=1, label=\"1m\", step=\"month\", stepmode=\"backward\"),\n",
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        },
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          "2022-05-20",
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     },
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   "source": [
    "figure = px.scatter(\n",
    "    data,\n",
    "    x='Date', y='Close',\n",
    "    range_x=[d2, d1],\n",
    "    title='Stock Market Analysis by Hiding Weekend Gaps'\n",
    ")\n",
    "\n",
    "figure.update_xaxes(\n",
    "    rangebreaks=[\n",
    "        dict(bounds=[\"sat\", \"mon\"])\n",
    "    ]\n",
    ")\n",
    "figure.update_xaxes(rangeslider_visible=True)\n",
    "\n",
    "figure.show()"
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