Plot customization (title, labels, figsize) in Pandas - Mini Project: Build & Apply

Plot customization (title, labels, figsize)

📖 Scenario: You are working with sales data for a small store. You want to create a clear and nice-looking bar chart to show the sales of different products.

🎯 Goal: Create a bar plot using pandas and customize it by adding a title, axis labels, and setting the figure size to make the chart easy to understand and visually appealing.

📋 What You'll Learn

Create a pandas DataFrame with product names and sales numbers.

Set a variable for figure size as a tuple.

Use the DataFrame's plot method to create a bar chart with the specified figure size.

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

Print the plot to display the customized chart.

💡 Why This Matters

🌍 Real World

Customizing plots helps make data charts clear and easy to understand for reports or presentations.

💼 Career

Data scientists and analysts often create visualizations with titles and labels to communicate insights effectively.

1

Create the sales data DataFrame

Create a pandas DataFrame called sales_data with two columns: 'Product' and 'Sales'. Use these exact values: 'Apples', 'Bananas', 'Cherries', 'Dates' for products and 30, 45, 15, 10 for sales.

Pandas

# Your code here

Need a hint?

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

2

Set the figure size for the plot

Create a variable called fig_size and set it to the tuple (8, 5) to define the width and height of the plot in inches.

Pandas

import pandas as pd

sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Sales': [30, 45, 15, 10]
})

# Your code here

Need a hint?

Use parentheses to create a tuple for figure size, like (width, height).

3

Create the bar plot with customization

Use sales_data.plot.bar() to create a bar chart. Set x='Product', y='Sales', and figsize=fig_size. Then add a title 'Sales by Product', x-axis label 'Product', and y-axis label 'Number of Sales' using the plot's set_title, set_xlabel, and set_ylabel methods.

Pandas

import pandas as pd

sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Sales': [30, 45, 15, 10]
})

fig_size = (8, 5)

# Your code here

Need a hint?

Assign the plot to a variable, then use set_title, set_xlabel, and set_ylabel to add text.

4

Display the customized plot

Write a print() statement to display the plot object.

Pandas

import pandas as pd

sales_data = pd.DataFrame({
    'Product': ['Apples', 'Bananas', 'Cherries', 'Dates'],
    'Sales': [30, 45, 15, 10]
})

fig_size = (8, 5)

plot = sales_data.plot.bar(x='Product', y='Sales', figsize=fig_size)
plot.set_title('Sales by Product')
plot.set_xlabel('Product')
plot.set_ylabel('Number of Sales')

# Your code here

Need a hint?

Use print(plot) to show the plot object in the output.