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Randomly splitting DataFrame into multiple DataFrames of equal size in Pandas
schedule Aug 10, 2023
Last updated local_offer
Tags Python●Pandas
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Consider the following DataFrame:
df = pd.DataFrame({"A":[1,2,3,4],"B":[5,6,7,8],"C":[9,10,11,12]})df
A B C0 1 5 91 2 6 102 3 7 113 4 8 12
Solution
To randomly split df into two DataFrames of equal size:
df_shuffled = df.sample(frac=1)df_splits = np.array_split(df_shuffled, 2)for df in df_splits: display(df)
A B C2 3 7 111 2 6 10 A B C0 1 5 93 4 8 12
Note the following:
we first use DataFrame's
sample(~)method to randomly shuffle the rows. Thefrac=1means we want all rows returned.we then use NumPy's
array_split(~,2)method to split the DataFrame into 2 equally sized sub-DataFrames. The return type is a list of DataFrames.
Case when equally-sized DataFrame is not possible
When the number of splits do not evenly divide the number of rows, then the resulting DataFrames will not all be of equal size:
df_shuffled = df.sample(frac=1)df_splits = np.array_split(df_shuffled, 3)for df in df_splits: display(df)
A B C2 3 7 111 2 6 10 A B C3 4 8 12 A B C0 1 5 9
Published by Isshin Inada
Edited by 0 others
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