How to Unpack a List-Like Column into Separate Rows in a DataFrame?

Unpacking a List-Like Column into Separate Rows in a DataFrame

Question:

How can we transform a DataFrame cell containing a list into individual rows for each value within that list?

Example:

Consider the following DataFrame:

name	opponent	nearest_neighbors
A.J. Price	76ers	['Zach LaVine', 'Jeremy Lin', 'Nate Robinson', 'Isaia']

Our goal is to "explode" the nearest_neighbors column, creating a new row for each value in the list.

Answer:

In pandas version 0.25 and later, the explode() method makes this operation straightforward:

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})
      .set_index(['name', 'opponent']))

df.explode('nearest_neighbors')

Output:

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

The explode() method effectively unrolls each list in the nearest_neighbors column, creating a new row for each value.

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