Explode and regroup lists into rows in a pandas DataFrame

Setup

# Import libraries
import pandas as pd

# Create sample dataframe
df = pd.DataFrame(
    {'zip_codes':["75002, 75005, 75007, 75019, 75020", "13000, 13001, 13005", "69001, 69003, 69004"]}, 
    index=['Paris', 'Marseille', 'Lyon']
)
df

	zip_codes
Paris	75002, 75005, 75007, 75019, 75020
Marseille	13000, 13001, 13005
Lyon	69001, 69003, 69004

Split values and expand into multiple rows

Use explode() to break down a list into multiple rows

# Split values on commas, and expand into multiple rows
df = (
    df
    .assign(zip_codes=lambda x: x['zip_codes'].str.split(','))
    .explode('zip_codes')
)
df

	zip_codes
Paris	75002
Paris	75005
Paris	75007
Paris	75019
Paris	75020
Marseille	13000
Marseille	13001
Marseille	13005
Lyon	69001
Lyon	69003
Lyon	69004

Regroup rows into a list

The inverse operation, regrouping multiple rows into a list, is achieved with a grouby() followed by agg(list).

# Regroup rows with the same index into a list
(
    df
    .groupby(df.index)
    .agg(list)
)

	zip_codes
Lyon	[69001, 69003, 69004]
Marseille	[13000, 13001, 13005]
Paris	[75002, 75005, 75007, 75019, 75020]

##Setup

##Split values and expand into multiple rows

###Regroup rows into a list

Setup

Split values and expand into multiple rows

Regroup rows into a list