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UBC-DSCI · Dec 28, 2023 · a2dc8fd · a2dc8fd
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diff --git a/pull341/_sources/classification2.md b/pull341/_sources/classification2.md
@@ -395,20 +395,20 @@ the `random_state` argument that is available in many `pandas` and `scikit-learn
 functions. Those functions will then use your `Generator` to generate random numbers instead of
 `numpy`'s default generator. For example, we can reproduce our earlier example by using a `Generator`
 object with the `seed` value set to 1; we get the same lists of numbers once again.
-```{code}
+```python
 from numpy.random import Generator, PCG64
 rng = Generator(PCG64(seed=1))
 random_numbers1_third = nums_0_to_9.sample(n=10, random_state=rng).to_list()
 random_numbers1_third
 ```
-```{code}
+```text
 array([2, 9, 6, 4, 0, 3, 1, 7, 8, 5])
 ```
-```{code}
+```python
 random_numbers2_third = nums_0_to_9.sample(n=10, random_state=rng).to_list()
 random_numbers2_third
 ```
-```{code}
+```text
 array([9, 5, 3, 0, 8, 4, 2, 1, 6, 7])
 ```
 

diff --git a/pull341/classification1.html b/pull341/classification1.html
diff --git a/pull341/classification2.html b/pull341/classification2.html
diff --git a/pull341/clustering.html b/pull341/clustering.html
diff --git a/pull341/inference.html b/pull341/inference.html
diff --git a/pull341/intro.html b/pull341/intro.html
diff --git a/pull341/regression1.html b/pull341/regression1.html
diff --git a/pull341/regression2.html b/pull341/regression2.html
diff --git a/pull341/searchindex.js b/pull341/searchindex.js
diff --git a/pull341/viz.html b/pull341/viz.html
diff --git a/pull341/wrangling.html b/pull341/wrangling.html
@@ -4792,7 +4792,7 @@ <h2><span class="section-number">3.9. </span>Performing operations on groups of
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;pandas.core.groupby.generic.DataFrameGroupBy object at 0x7effae1d4890&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;pandas.core.groupby.generic.DataFrameGroupBy object at 0x7f14bd16e9d0&gt;
 </pre></div>
 </div>
 </div>