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# Splitting DataFrame into multiple DataFrames based on value in Pandas

schedule Aug 11, 2023
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local_offer
PythonPandas
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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.

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