Q.(Program 4-12) Prayatna sells designer bags and wallets. During the sales season, he gave discounts ranging from 10% to 50% over a period of 5 weeks. He recorded his sales for each type of discount in an array. Draw a scatter plot to show a relationship between the discount offered and sales made, given: discount = [10, 20, 30, 40, 50] and saleInRs = [40000, 45000, 48000, 50000, 100000] (title 'Sales Vs Discount', x axis 'Discount offered', y axis 'Sales in Rs').

To draw a scatter plot showing the relationship between discount offered and sales made, we use the matplotlib.pyplot library in Python. A scatter plot is ideal for visualizing the correlation or pattern between two quantitative variables.

First, we import matplotlib.pyplot as plt. Then, we define the given discount and saleInRs data as lists. The plt.scatter() function is used to create the plot, taking the x-axis values (discount) and y-axis values (saleInRs) as arguments. We then set the plot title, x-axis label, and y-axis label using plt.title(), plt.xlabel(), and plt.ylabel() respectively, as specified in the question. Finally, plt.show() displays the generated plot.

import matplotlib.pyplot as plt

# Given data
discount = [10, 20, 30, 40, 50]
saleInRs = [40000, 45000, 48000, 50000, 100000]

# Create the scatter plot
plt.scatter(discount, saleInRs)
# Key line: plt.scatter() creates a scatter plot where each point represents a pair of (discount, saleInRs) values.

# Set the title and axis labels
plt.title('Sales Vs Discount')
# Key line: plt.title() sets the main title of the plot for clarity.
plt.xlabel('Discount offered')
# Key line: plt.xlabel() labels the horizontal axis, indicating what the x-values represent.
plt.ylabel('Sales in Rs')
# Key line: plt.ylabel() labels the vertical axis, indicating what the y-values represent.

# Display the plot
plt.show()
# Key line: plt.show() renders the plot and displays it to the user.

The expected output is a scatter plot with the following characteristics: …

When we want to understand the relationship or correlation between two numerical variables, a scatter plot is an excellent visualization tool. Each point on a scatter plot represents a pair of values for the two variables, allowing us to visually identify patterns, trends, or outliers. In this problem, we need to see how saleInRs changes with discount, making a scatter plot the perfect choice.

The matplotlib.pyplot library in Python is the standard for creating static, animated, and interactive visualizations. We will use its scatter() function to plot the individual data points and other functions to add a title and axis labels for clarity.

import matplotlib.pyplot as plt

# 1. Define the data for discount and sales
# The 'discount' list represents the independent variable (x-axis).
discount = [10, 20, 30, 40, 50]
# The 'saleInRs' list represents the dependent variable (y-axis).
saleInRs = [40000, 45000, 48000, 50000, 100000]

# 2. Create the scatter plot
# plt.scatter() takes two arguments: the x-coordinates and the y-coordinates of the points.
plt.scatter(discount, saleInRs)

# 3. Set the title and axis labels for better readability
# plt.title() sets the main title of the plot.
plt.title('Sales Vs Discount')
# plt.xlabel() sets the label for the x-axis.
plt.xlabel('Discount offered')
# plt.ylabel() sets the label for the y-axis.
plt.ylabel('Sales in Rs')

# 4. Display the plot
# plt.show() renders the plot window. Without this, the plot might not be displayed.
plt.show()

Explanation of Key Lines:

• import matplotlib.pyplot as plt: This line imports the pyplot module from the matplotlib library, which is essential for creating plots. We use plt as a common alias for convenience.
• discount = [10, 20, 30, 40, 50] and saleInRs = [40000, 45000, 48000, 50000, 100000]: These lines define the data points for our plot. discount will be plotted on the x-axis, and saleInRs on the y-axis. Each corresponding element from these lists forms a single point on the scatter plot (e.g., (10, 40000), (20, 45000), etc.).
• plt.scatter(discount, saleInRs): This is the core function call that generates the scatter plot. It takes the discount values as x-coordinates and saleInRs values as y-coordinates, plotting each pair as a distinct point.
• plt.title('Sales Vs Discount'): This function adds a descriptive title to the plot, making it clear what the plot represents. …