How to Concatenate Columns in pandas: Simple Guide

To concatenate columns in pandas, you can use the + operator for string columns or the .str.cat() method for more control. These methods combine values from two or more columns into a single column easily.

Syntax

Here are two common ways to concatenate columns in pandas:

• df['new_col'] = df['col1'] + df['col2']: Adds string columns directly.
• df['new_col'] = df['col1'].str.cat(df['col2'], sep=' '): Concatenates with a separator and handles missing values.

python

df['new_col'] = df['col1'] + df['col2']
df['new_col'] = df['col1'].str.cat(df['col2'], sep=' ')

Example

This example shows how to combine two text columns into one with a space between the values.

python

import pandas as pd

data = {'first_name': ['John', 'Jane', 'Alice'],
        'last_name': ['Doe', 'Smith', 'Johnson']}
df = pd.DataFrame(data)

df['full_name'] = df['first_name'].str.cat(df['last_name'], sep=' ')
print(df)

Output

  first_name last_name   full_name
0       John       Doe    John Doe
1       Jane     Smith  Jane Smith
2      Alice   Johnson Alice Johnson

Common Pitfalls

Common mistakes include:

• Trying to add non-string columns directly, which causes errors.
• Not handling missing values, which can result in NaN in the output.

Use .astype(str) to convert non-string columns before concatenation and .str.cat() with na_rep='' to handle missing data.

python

import pandas as pd

data = {'A': ['foo', None, 'bar'], 'B': [1, 2, 3]}
df = pd.DataFrame(data)

# Wrong: adding string and int columns directly causes error
# df['concat'] = df['A'] + df['B']  # This will raise TypeError

# Right: convert int to string first
s1 = df['A'].fillna('')
s2 = df['B'].astype(str)
df['concat'] = s1.str.cat(s2, na_rep='')
print(df)

Output

     A  B concat
0  foo  1  foo1
1  NaN  2    2
2  bar  3  bar3

Quick Reference

Method	Description	Example
+ operator	Concatenate string columns directly	df['new'] = df['col1'] + df['col2']
.str.cat()	Concatenate with separator and handle missing values	df['new'] = df['col1'].str.cat(df['col2'], sep=' ')
.astype(str)	Convert non-string columns before concatenation	df['col2'].astype(str)
fillna('')	Replace missing values to avoid NaN in output	df['col1'].fillna('')

Key Takeaways

Use the + operator or .str.cat() to concatenate string columns in pandas.

Convert non-string columns to string with .astype(str) before concatenation.

Handle missing values with fillna('') or na_rep parameter to avoid NaN results.

.str.cat() allows adding separators between concatenated columns easily.

Direct addition of non-string columns causes errors; always convert types first.