Highlight Pandas DataFrame\'s Specific Columns using Apply()

While presenting or explaining data using Pandas DataFrames, we might need to highlight important rows and columns to make them more appealing, explainable and visually stunning. One way of highlighting specific columns is by using the built-in apply() method with Pandas styling.

Understanding apply() with Pandas Styling

The apply() method is used to apply a user-defined function to each column or row of the Pandas DataFrame. To highlight specific columns, we first define a custom function that sets the required conditions for highlighting, then use the apply() method along with the style module.

Syntax

df.style.apply(function_name)

Highlighting Specific Columns

Let's start with a basic example of highlighting specific columns by name ?

import pandas as pd

# Create a sample DataFrame
data = {
    'Name': ['Ram', 'Shyam', 'Mohan', 'Shrey'],
    'Age': [25, 30, 35, 40],
    'Score': [80, 90, 85, 95]
}
df = pd.DataFrame(data)

# Function to highlight specific columns
def highlight_columns(col):
    color = 'lightblue' if col.name in ['Age', 'Score'] else 'white'
    return ['background-color: {}'.format(color) for _ in col]

# Apply highlighting
styled_df = df.style.apply(highlight_columns)
print("DataFrame with highlighted columns created successfully!")
print(df)

DataFrame with highlighted columns created successfully!
    Name  Age  Score
0    Ram   25     80
1  Shyam   30     90
2  Mohan   35     85
3  Shrey   40     95

Highlighting All Columns

To highlight all columns with the same color, we can modify our function ?

import pandas as pd

data = {
    'Name': ['Ram', 'Shyam', 'Mohan', 'Shrey'],
    'Age': [25, 30, 35, 40],
    'Score': [80, 90, 85, 95]
}
df = pd.DataFrame(data)

# Function to highlight all columns
def highlight_all_columns(col):
    color = 'lightgreen'
    return ['background-color: {}'.format(color) for _ in col]

styled_df = df.style.apply(highlight_all_columns)
print("All columns highlighted with light green!")
print(df)

All columns highlighted with light green!
    Name  Age  Score
0    Ram   25     80
1  Shyam   30     90
2  Mohan   35     85
3  Shrey   40     95

Conditional Highlighting

We can also highlight specific values within columns based on conditions ?

import pandas as pd

data = {
    'Name': ['Ram', 'Shyam', 'Mohan', 'Shrey'],
    'Age': [25, 30, 35, 40],
    'Score': [80, 90, 85, 95]
}
df = pd.DataFrame(data)

# Function for conditional highlighting
def highlight_conditions(col):
    if col.name == 'Age':
        return ['background-color: lightblue' if val > 30 else '' for val in col]
    elif col.name == 'Score':
        return ['background-color: lightgreen' if val >= 90 else '' for val in col]
    else:
        return ['' for _ in col]

styled_df = df.style.apply(highlight_conditions)
print("Conditional highlighting applied:")
print("- Age > 30: Light blue background")
print("- Score >= 90: Light green background")
print(df)

Conditional highlighting applied:
- Age > 30: Light blue background
- Score >= 90: Light green background
    Name  Age  Score
0    Ram   25     80
1  Shyam   30     90
2  Mohan   35     85
3  Shrey   40     95

Key Features

Conclusion

The apply() method with Pandas styling provides a powerful way to highlight DataFrame columns based on various conditions. Use it to make your data presentations more visually appealing and easier to understand.