How to Group Pandas DataFrame Rows and Convert Column Values to Lists?

How to Convert Dataframe Rows to Lists in Pandas GroupBy

When manipulating dataframes in Pandas, it can be necessary to transform data into a specific format for further analysis. One way to do this is to group rows by a specified column and create lists from another column within each group.

In this scenario, we are given a dataframe containing two columns: 'a' (column name) and 'b' (column values). The task is to transform this dataframe into a new dataframe where each unique value in column 'a' has its corresponding values from column 'b' grouped into a list.

To achieve this:

df1 = df.groupby('a')['b'].apply(list).reset_index(name='new')

In this code:

• df.groupby('a'): Groups the dataframe by the column 'a'.
• ['b'].apply(list): Applies the list function to each group, converting the 'b' column values into a list.
• reset_index(name='new'): Resets the index of the resulting dataframe and sets the name of the new column to 'new'.

The final result is a new dataframe, df1, with the unique values from column 'a' in the 'a' column, and the corresponding lists from column 'b' in the 'new' column.

Here's an example to illustrate:

Given the following dataframe:

Applying the aforementioned code will transform it into:

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