How to Use str.split in pandas for Splitting Strings

Use pandas.Series.str.split() to split strings in a DataFrame column by a delimiter. It returns a Series of lists or can expand into multiple columns with expand=True.

Syntax

The basic syntax of str.split() in pandas is:

• Series.str.split(pat=None, n=-1, expand=False)

Where:

• pat is the delimiter string to split on (default splits on whitespace).
• n is the maximum number of splits (-1 means no limit).
• expand if True, returns a DataFrame with each split as a separate column; if False, returns a Series of lists.

python

Series.str.split(pat=None, n=-1, expand=False)

Example

This example shows how to split a column of full names into first and last names using str.split() with expand=True to get separate columns.

python

import pandas as pd

data = {'Name': ['Alice Smith', 'Bob Johnson', 'Charlie Lee']}
df = pd.DataFrame(data)

# Split 'Name' column by space into two columns
split_names = df['Name'].str.split(' ', n=1, expand=True)
split_names.columns = ['First Name', 'Last Name']

# Join back to original DataFrame
result = df.join(split_names)
print(result)

Output

           Name First Name Last Name
0   Alice Smith      Alice     Smith
1   Bob Johnson        Bob   Johnson
2  Charlie Lee    Charlie       Lee

Common Pitfalls

Common mistakes when using str.split() include:

• Not setting expand=True when you want separate columns, resulting in a Series of lists instead.
• Using the wrong delimiter pat, which causes unexpected splits or no splits.
• Forgetting that n limits the number of splits, so setting it too low may truncate results.

Example of wrong and right usage:

python

import pandas as pd

data = {'Code': ['A-1-2', 'B-3-4', 'C-5-6']}
df = pd.DataFrame(data)

# Wrong: returns lists, not separate columns
wrong = df['Code'].str.split('-')
print('Wrong output:')
print(wrong)

# Right: expand=True splits into columns
right = df['Code'].str.split('-', expand=True)
print('\nRight output:')
print(right)

Output

Wrong output:
0    [A, 1, 2]
1    [B, 3, 4]
2    [C, 5, 6]
Name: Code, dtype: object

Right output:
   0  1  2
0  A  1  2
1  B  3  4
2  C  5  6

Quick Reference

Parameter	Description	Default
pat	Delimiter string to split on	None (whitespace)
n	Maximum number of splits	-1 (no limit)
expand	Return DataFrame if True, else Series of lists	False

Key Takeaways

Use pandas Series.str.split() to split strings in DataFrame columns by a delimiter.

Set expand=True to get separate columns instead of lists.

Specify the delimiter with pat to control how strings are split.

Use n to limit the number of splits if needed.

Common mistake: forgetting expand=True when separate columns are desired.