Why built-in plotting matters in Pandas - See It in Action

Why built-in plotting matters

📖 Scenario: You work in a small business that tracks monthly sales data. You want to quickly see how sales change over the months without writing complex code. Using built-in plotting in pandas helps you create simple charts fast, just like drawing on paper to understand your data better.

🎯 Goal: Build a small program that creates a pandas DataFrame with monthly sales data, then uses pandas built-in plotting to show a line chart of sales over months.

📋 What You'll Learn

Create a pandas DataFrame with exact months and sales values

Create a variable for the plot title

Use pandas built-in plotting to create a line chart of sales

Print the plot title before showing the plot

💡 Why This Matters

🌍 Real World

Quickly visualizing data helps businesses understand trends without complex coding.

💼 Career

Data analysts and scientists often use pandas built-in plotting for fast data exploration and reporting.

1

Create the sales data DataFrame

Create a pandas DataFrame called sales_data with two columns: 'Month' and 'Sales'. Use these exact values: Months are 'Jan', 'Feb', 'Mar', 'Apr', 'May'. Sales are 250, 300, 280, 350, 400.

Pandas

import pandas as pd
# Create the sales_data DataFrame with Month and Sales columns
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary containing the exact keys and lists of values.

2

Create a plot title variable

Create a variable called plot_title and set it to the string 'Monthly Sales Data'.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Sales': [250, 300, 280, 350, 400]
})
# Create the plot_title variable
# Your code here

Need a hint?

Assign the exact string to the variable plot_title.

3

Create a line plot using pandas built-in plotting

Use the pandas built-in plotting to create a line plot of Sales over Month from the sales_data DataFrame. Use sales_data.plot(x='Month', y='Sales', kind='line').

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Sales': [250, 300, 280, 350, 400]
})
plot_title = 'Monthly Sales Data'
# Create the line plot using pandas built-in plotting
# Your code here

Need a hint?

Use sales_data.plot with x='Month', y='Sales', and kind='line'.

4

Print the plot title and show the plot

Write two lines: first, print the plot_title variable; second, call import matplotlib.pyplot as plt and then plt.show() to display the plot.

Pandas

import pandas as pd
sales_data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May'],
    'Sales': [250, 300, 280, 350, 400]
})
plot_title = 'Monthly Sales Data'
sales_data.plot(x='Month', y='Sales', kind='line')
# Print the plot_title and show the plot
# Your code here

Need a hint?

Use print(plot_title) and then plt.show() after importing matplotlib.pyplot as plt.