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Splitting DataFrame into multiple DataFrames based on value in Pandas
schedule Aug 11, 2023
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Tags Python●Pandas
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Consider the following DataFrame:
df = pd.DataFrame({"A":["a","a","b"],"B":[6,7,8]})df
A B0 a 61 a 72 b 8
Solution
To split a DataFrame into dictionary containing multiple DataFrames based on values in column A:
dict_dfs = dict(tuple(df.groupby("A")))dict_dfs
{'a': A B 0 a 6 1 a 7, 'b': A B 2 b 8}
Note the following:
the key of the dictionary is the value of the group, while the value is the corresponding DataFrame.
if you just wanted a tuple representation instead, then simply leave out the
dict(~)
Explanation
Here, we first partition the DataFrame into groups split by values in column A using groupby("A"). We then create a tuple (of size two) containing the two groups:
tuple(df.groupby("A"))
(('a', A B 0 a 6 1 a 7), ('b', A B 2 b 8))
We then call dict(~) to convert this tuple into a dictionary.
Published by Isshin Inada
Edited by 0 others
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