Python – Strip whitespace from a Pandas DataFrame

To strip whitespace from a Pandas DataFrame, use the str.strip() method on string columns. This removes both leading and trailing whitespace characters from text data.

Importing Pandas

First, let us import the required Pandas library with an alias ?

import pandas as pd

Creating a DataFrame with Whitespace

Let's create a DataFrame with 3 columns where the first column has leading and trailing whitespaces ?

import pandas as pd

dataFrame = pd.DataFrame({
    'Product Category': [' Computer', ' Mobile Phone', 'Electronics ', 'Appliances', ' Furniture', 'Stationery'],
    'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Refrigerators', 'Chairs', 'Diaries'],
    'Quantity': [10, 50, 10, 20, 25, 50]
})

print("Original DataFrame:")
print(dataFrame)

Original DataFrame:
  Product Category   Product Name  Quantity
0        Computer       Keyboard        10
1    Mobile Phone        Charger        50
2   Electronics         SmartTV        10
3      Appliances  Refrigerators        20
4       Furniture         Chairs        25
5       Stationery        Diaries        50

Stripping Whitespace from a Single Column

To remove whitespace from a single column "Product Category" ?

import pandas as pd

dataFrame = pd.DataFrame({
    'Product Category': [' Computer', ' Mobile Phone', 'Electronics ', 'Appliances', ' Furniture', 'Stationery'],
    'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Refrigerators', 'Chairs', 'Diaries'],
    'Quantity': [10, 50, 10, 20, 25, 50]
})

# Strip whitespace from a single column
dataFrame['Product Category'] = dataFrame['Product Category'].str.strip()

print("DataFrame after removing whitespaces:")
print(dataFrame)

DataFrame after removing whitespaces:
  Product Category   Product Name  Quantity
0         Computer       Keyboard        10
1     Mobile Phone        Charger        50
2      Electronics        SmartTV        10
3       Appliances  Refrigerators        20
4        Furniture         Chairs        25
5       Stationery        Diaries        50

Stripping Whitespace from All String Columns

To strip whitespace from all string columns in the DataFrame ?

import pandas as pd

dataFrame = pd.DataFrame({
    'Product Category': [' Computer', ' Mobile Phone', 'Electronics ', 'Appliances', ' Furniture', 'Stationery'],
    'Product Name': [' Keyboard ', 'Charger', 'SmartTV ', 'Refrigerators', ' Chairs', 'Diaries'],
    'Quantity': [10, 50, 10, 20, 25, 50]
})

# Strip whitespace from all object/string columns
string_columns = dataFrame.select_dtypes(include=['object']).columns
dataFrame[string_columns] = dataFrame[string_columns].apply(lambda x: x.str.strip())

print("DataFrame after stripping all string columns:")
print(dataFrame)

DataFrame after stripping all string columns:
  Product Category   Product Name  Quantity
0         Computer       Keyboard        10
1     Mobile Phone        Charger        50
2      Electronics        SmartTV        10
3       Appliances  Refrigerators        20
4        Furniture         Chairs        25
5       Stationery        Diaries        50

Conclusion

Use str.strip() to remove leading and trailing whitespace from pandas DataFrame columns. Apply it to single columns or use select_dtypes() to strip all string columns at once.