To remove spaces from column names in Pandas DataFrame, the most efficient way is to use the “.columns” attribute with the “str.replace()” method. It directly operates on the index of the columns (which is a string index) and performs string replacement.

import pandas as pd

# Sample DataFrame
data = {'Col 1': [1, 2, 3], 'Col 2': [
    4, 5, 6], 'Col 3': [7, 8, 9]}

df = pd.DataFrame(data)
print(df)

# Remove all spaces
df.columns = df.columns.str.replace(' ', '')
print(df)

Output

You can see from the above figure that we removed space between column names.

Replacing spaces with underscores

We can also replace spaces with underscores if we have that kind of requirement. In that case, we must replace ” “ with “_”.

import pandas as pd

data = {'Col 1': [1, 2, 3], 'Col 2': [
    4, 5, 6], 'Col 3': [7, 8, 9]}

df = pd.DataFrame(data)
print(df)

# Replace space with underscore (_)
df.columns = df.columns.str.replace(' ', '_')
print(df)

Output

Remove leading/trailing spaces from column names

You can also remove leading/trailing spaces from column names using the “.strip()” method.

import pandas as pd

data = {' Col 1 ': [1, 2, 3], ' Col 2 ': [
    4, 5, 6], ' Col 3 ': [7, 8, 9]}

df = pd.DataFrame(data)
print(df)

# Remove leading and trailing whitespaces
df.columns = df.columns.str.strip()
print(df)

Output

That’s all!