Use fixed seeds for reproducible pseudorandomness

Author: Rebecca N. Palmer <[email protected]>
Forwarded: no


Gbp-Pq: Name fix_random_seeds.patch

Author: Debian Science Team

doc/source/getting_started/comparison/comparison_with_r.rst

@@ -241,6 +241,7 @@ In pandas we may use :meth:`~pandas.pivot_table` method to handle this:
 
    import random
    import string
+   random.seed(123456) # for reproducibility
 
    baseball = pd.DataFrame(
        {

doc/source/user_guide/advanced.rst

@@ -595,6 +595,7 @@ they need to be sorted. As with any index, you can use :meth:`~DataFrame.sort_in
 
    import random
 
+   random.seed(123456) # for reproducibility
    random.shuffle(tuples)
    s = pd.Series(np.random.randn(8), index=pd.MultiIndex.from_tuples(tuples))
    s

doc/source/user_guide/visualization.rst

@@ -1019,6 +1019,7 @@ be passed, and when ``lag=1`` the plot is essentially ``data[:-1]`` vs.
    :suppress:
 
    np.random.seed(123456)
+   random.seed(123456) # for reproducibility - bootstrap_plot uses random.sample
 
 .. ipython:: python