How to Split a Pandas DataFrame into Multiple DataFrames Based on Column Values?

Splitting a Pandas DataFrame by Column Values Using GroupBy

You want to segment a Pandas DataFrame based on distinct values in the 'ZZ' column. The goal is to create a new DataFrame with the 'N0_YLDF' column partitioned into four new columns, each for a unique 'ZZ' value. While groupby is an essential function, the article addresses how to proceed with the grouped object to achieve the desired outcome.

To accomplish this, follow these steps:

1. Group the DataFrame by the 'ZZ' column using the .groupby() method:

   gb = df.groupby('ZZ')

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2. Retrieve groups of rows corresponding to each unique 'ZZ' value:

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

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As a result, groups will be a list containing four separate DataFrames, each representing a distinct 'ZZ' value and its corresponding 'N0_YLDF' data.

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