How to lowercase the column names in Pandas dataframe?

In this article, you'll learn how to convert column names and values to lowercase in a Pandas DataFrame. We'll explore three different methods: str.lower(), map(str.lower), and apply(lambda) functions.

Creating a Sample DataFrame

Let's start by creating a sample DataFrame to demonstrate the methods ?

import pandas as pd

# Create sample restaurant data
data = {
    'Restaurant Name': ['Pizza Palace', 'Burger King', 'Sushi Bar'],
    'Rating Color': ['Green', 'Yellow', 'Red'],
    'Rating Text': ['Excellent', 'Good', 'Average']
}

df = pd.DataFrame(data)
print("Original DataFrame:")
print(df)

Original DataFrame:
  Restaurant Name Rating Color Rating Text
0    Pizza Palace        Green   Excellent
1     Burger King       Yellow        Good
2       Sushi Bar          Red     Average

Method 1: Using str.lower() Function

The str.lower() method converts string values in a column to lowercase ?

import pandas as pd

data = {
    'Restaurant Name': ['Pizza Palace', 'Burger King', 'Sushi Bar'],
    'Rating Color': ['Green', 'Yellow', 'Red'],
    'Rating Text': ['Excellent', 'Good', 'Average']
}

df = pd.DataFrame(data)

# Convert Rating Color column to lowercase
print("Converting Rating Color to lowercase:")
df['Rating Color'] = df['Rating Color'].str.lower()
print(df['Rating Color'])

Converting Rating Color to lowercase:
0     green
1    yellow
2       red
Name: Rating Color, dtype: object

Method 2: Using map(str.lower) Function

The map(str.lower) method applies the lowercase function to each element in the column ?

import pandas as pd

data = {
    'Restaurant Name': ['Pizza Palace', 'Burger King', 'Sushi Bar'],
    'Rating Text': ['Excellent', 'Good', 'Average']
}

df = pd.DataFrame(data)

# Add a new column with lowercase values
df['Lowercase Rating Text'] = df['Rating Text'].map(str.lower)
print("DataFrame with new lowercase column:")
print(df)

DataFrame with new lowercase column:
  Restaurant Name Rating Text Lowercase Rating Text
0    Pizza Palace   Excellent            excellent
1     Burger King        Good                 good
2       Sushi Bar     Average              average

Method 3: Converting Column Names and Values

This method demonstrates converting both column values using apply(lambda) and column headers using map(str.lower) ?

import pandas as pd

data = {
    'Restaurant Name': ['Pizza Palace', 'Burger King', 'Sushi Bar'],
    'Rating Color': ['Green', 'Yellow', 'Red'],
    'Rating Text': ['Excellent', 'Good', 'Average']
}

df = pd.DataFrame(data)

# Convert column values to lowercase using apply(lambda)
df['Lowercase Rating Text'] = df['Rating Text'].apply(lambda x: x.lower())
df['Lowercase Rating Color'] = df['Rating Color'].apply(lambda x: x.lower())

print("DataFrame with lowercase value columns:")
print(df)

# Convert column headers to lowercase
df.columns = df.columns.map(str.lower)
print("\nDataFrame with lowercase column headers:")
print(df)

DataFrame with lowercase value columns:
  Restaurant Name Rating Color Rating Text Lowercase Rating Text Lowercase Rating Color
0    Pizza Palace        Green   Excellent            excellent              green
1     Burger King       Yellow        Good                 good             yellow
2       Sushi Bar          Red     Average              average                red

DataFrame with lowercase column headers:
  restaurant name rating color rating text lowercase rating text lowercase rating color
0    Pizza Palace        Green   Excellent            excellent              green
1     Burger King       Yellow        Good                 good             yellow
2       Sushi Bar          Red     Average              average                red

Comparison of Methods

Conclusion

Use str.lower() for simple column conversion, map(str.lower) for creating new lowercase columns, and apply(lambda) for more complex transformations. To convert column headers, use df.columns.map(str.lower).