Why customization matters in Matplotlib - See It in Action

Why customization matters

📖 Scenario: You are working on a simple sales report for your small business. You want to show a clear and colorful bar chart of monthly sales to your team. Customizing the chart colors and labels will help everyone understand the data better.

🎯 Goal: Create a bar chart of monthly sales data and customize the colors and labels to make the chart clear and visually appealing.

📋 What You'll Learn

Create a dictionary called monthly_sales with exact keys and values for sales data

Create a list called colors with specific colors for each month

Use a matplotlib bar chart to plot the sales with the custom colors

Add a title and labels for the x-axis and y-axis

Display the customized bar chart

💡 Why This Matters

🌍 Real World

Customizing charts helps make data easier to understand for presentations and reports.

💼 Career

Data scientists and analysts often customize visualizations to communicate insights clearly to stakeholders.

1

DATA SETUP: Create the sales data dictionary

Create a dictionary called monthly_sales with these exact entries: 'Jan': 150, 'Feb': 200, 'Mar': 170, 'Apr': 220, 'May': 190.

Matplotlib

# Your code here

Need a hint?

Use curly braces {} to create the dictionary with month names as keys and sales numbers as values.

2

CONFIGURATION: Create a list of colors for the bars

Create a list called colors with these exact color names in order: 'red', 'blue', 'green', 'orange', 'purple'.

Matplotlib

monthly_sales = {'Jan': 150, 'Feb': 200, 'Mar': 170, 'Apr': 220, 'May': 190}
# Your code here

Need a hint?

Use square brackets [] to create the list of colors in the same order as the months.

3

CORE LOGIC: Plot the bar chart with customization

Import matplotlib.pyplot as plt. Use plt.bar() to plot the sales with months as x-axis labels, sales values as heights, and the colors list for bar colors. Add a title 'Monthly Sales', x-axis label 'Month', and y-axis label 'Sales'.

Matplotlib

monthly_sales = {'Jan': 150, 'Feb': 200, 'Mar': 170, 'Apr': 220, 'May': 190}
colors = ['red', 'blue', 'green', 'orange', 'purple']
# Your code here

Need a hint?

Use list() to get keys and values from the dictionary. Pass them to plt.bar() with the color parameter.

4

OUTPUT: Show the customized bar chart

Use plt.show() to display the bar chart with your custom colors and labels.

Matplotlib

import matplotlib.pyplot as plt

monthly_sales = {'Jan': 150, 'Feb': 200, 'Mar': 170, 'Apr': 220, 'May': 190}
colors = ['red', 'blue', 'green', 'orange', 'purple']

months = list(monthly_sales.keys())
sales = list(monthly_sales.values())

plt.bar(months, sales, color=colors)
plt.title('Monthly Sales')
plt.xlabel('Month')
plt.ylabel('Sales')
# Your code here

Need a hint?

Call plt.show() to open the window with your bar chart.