How can I unpack lists in pandas DataFrames into individual rows?

Unpacking Lists in DataFrames into Individual Rows

In data manipulation scenarios, you may encounter the challenge of transforming a pandas cell containing a list into individual rows. To achieve this, you can leverage the functionality of pandas' explode() method.

Prior to pandas 0.25, handling this operation required more cumbersome approaches. However, the introduction of explode() has streamlined the process.

Consider the following example:

import pandas as pd

df = pd.DataFrame({'name': ['A.J. Price'] * 3, 
                    'opponent': ['76ers', 'blazers', 'bobcats'], 
                    'nearest_neighbors': [['Zach LaVine', 'Jeremy Lin', 'Nate Robinson', 'Isaia']] * 3})
df.set_index(['name', 'opponent'])

With the DataFrame above, you aim to unpack and stack the values in the nearest_neighbors column, resulting in each value becoming a row within each corresponding opponent.

Here's how you can accomplish this using the explode() method:

df.explode('nearest_neighbors')

The output will appear as follows:

                    nearest_neighbors
name       opponent                  
A.J. Price 76ers          Zach LaVine
           76ers           Jeremy Lin
           76ers        Nate Robinson
           76ers                Isaia
           blazers        Zach LaVine
           blazers         Jeremy Lin
           blazers      Nate Robinson
           blazers              Isaia
           bobcats        Zach LaVine
           bobcats         Jeremy Lin
           bobcats      Nate Robinson
           bobcats              Isaia

By utilizing the explode() method, you effectively transform the original list-like column into rows, providing a more structured and manageable representation of your data.

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