Styling and themes in Data Analysis Python - Mini Project: Build & Apply

Styling and themes

📖 Scenario: You work as a data analyst for a small company. You have sales data for different products and want to create a clear and attractive table to share with your team. You will learn how to style a pandas DataFrame to make it easier to read and visually appealing.

🎯 Goal: Create a pandas DataFrame with sales data, set a style theme, and highlight the highest sales values to make the table easy to understand.

📋 What You'll Learn

Create a pandas DataFrame with given sales data

Define a style theme using pandas styling options

Highlight the highest sales values in the DataFrame

Display the styled DataFrame as output

💡 Why This Matters

🌍 Real World

Styling tables helps make reports easier to read and understand for business teams.

💼 Career

Data analysts often need to present data clearly using styles and themes in tools like pandas.

1

Create the sales data DataFrame

Create a pandas DataFrame called sales_data with these exact values: columns 'Product', 'Region', and 'Sales'. The rows should be: 'Apples', 'North', 250, 'Bananas', 'South', 150, 'Cherries', 'East', 300, 'Dates', 'West', 200.

Data Analysis Python

import pandas as pd
# Create the sales_data DataFrame with the exact values
# Your code here

Hint

Use pd.DataFrame with a dictionary where keys are column names and values are lists of column data.

2

Set a style theme for the DataFrame

Create a variable called styled_sales that applies the background_gradient style with the coolwarm colormap to the sales_data DataFrame.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Region': ['North', 'South', 'East', 'West'],
    'Sales': [250, 150, 300, 200]
})
# Apply background_gradient style with 'coolwarm' colormap to sales_data
# Your code here

Hint

Use sales_data.style.background_gradient(cmap='coolwarm') to add color shading based on values.

3

Highlight the highest sales value

Update styled_sales to highlight the maximum value in the 'Sales' column using the highlight_max method with color='yellow'.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Region': ['North', 'South', 'East', 'West'],
    'Sales': [250, 150, 300, 200]
})
styled_sales = sales_data.style.background_gradient(cmap='coolwarm')
# Highlight the max value in 'Sales' column with yellow color
# Your code here

Hint

Chain highlight_max(subset=['Sales'], color='yellow') after background_gradient.

4

Display the styled DataFrame

Print the styled_sales variable to display the styled DataFrame.

Data Analysis Python

import pandas as pd
sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Region': ['North', 'South', 'East', 'West'],
    'Sales': [250, 150, 300, 200]
})
styled_sales = sales_data.style.background_gradient(cmap='coolwarm').highlight_max(subset=['Sales'], color='yellow')
# Print styled_sales to show the styled DataFrame
# Your code here

Hint

Use print(styled_sales) to display the styled DataFrame in the console.