How Can I Split a Pandas DataFrame into Multiple DataFrames Based on Column Values Using Groupby?

Splitting a Pandas DataFrame Based on Column Values Using Groupby

Pandas offers the powerful groupby function to manipulate data based on common values in a specified column. One practical application of this function is splitting a DataFrame into multiple smaller DataFrames based on unique values in a column.

Consider the DataFrame df below:

df = 
        N0_YLDF  ZZ        MAT
    0  6.286333   2  11.669069
    1  6.317000   6  11.669069
    2  6.324889   6  11.516454
    3  6.320667   5  11.516454
    4  6.325556   5  11.516454
    5  6.359000   6  11.516454
    6  6.359000   6  11.516454
    7  6.361111   7  11.516454
    8  6.360778   7  11.516454
    9  6.361111   6  11.516454

To split this DataFrame into four DataFrames based on the unique values of column ZZ, follow these steps:

1. Group the DataFrame by column ZZ:

   gb = df.groupby('ZZ')

2. Obtain a list of grouped objects:

   grouped_objects = [gb.get_group(x) for x in gb.groups]

The result will be a list of four DataFrames, each representing a different group based on the unique values in column ZZ.

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