Pandas explode()

import pandas as pd

# sample DataFrame
data = {'A': [[1, 2], [3, 4], [5]],
        'B': ['X', 'Y', 'Z']}
df = pd.DataFrame(data)

# use explode on column A
exploded_df = df.explode('A')

print(exploded_df)

'''
Output

   A  B
0  1  X
0  2  X
1  3  Y
1  4  Y
2  5  Z
'''

explode() Syntax

The syntax of the explode() method in Pandas is:

df.explode(column, ignore_index=False)

explode() Arguments

The explode() method has the following arguments:

• column : specifies the column to explode
• ignore_index (optional): if True, the resulting index will reset.

explode() Return Value

The explode() method returns a DataFrame with the same columns as the input DataFrame, but rows are expanded as per list-like entries in the specified column.

Example 1: Basic Explode

import pandas as pd

data = {'Names': [['Alice', 'Bob'], ['Cindy', 'Dan']]}
df = pd.DataFrame(data)

# explode the 'Names' column
exploded_names = df.explode('Names')

print(exploded_names)

Output

   Names
0  Alice
0    Bob
1  Cindy
1    Dan

In this example, we exploded the Names column to separate each list into individual rows.

Example 2: Explode with Index Reset

import pandas as pd

data = {'Names': [['Alice', 'Bob'], ['Cindy', 'Dan']]}
df = pd.DataFrame(data)

# explode the 'Names' column
exploded_names = df.explode('Names', ignore_index=True)

print(exploded_names)

Output

   Names
0  Alice
1    Bob
2  Cindy
3    Dan

In this example, we exploded the Names column and reset the index using ignore_index=True.