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plt.title(): This function is used to set the title for the plot. It takes a string as an argument thatdenotes the title
of the graph.
Some other common functions used for plotting graphs through Matplotlib:
Functions Purpose
xlabel() to write label name for x-axis
ylabel() to write label name for y-axis
title() to write title for the plot
legend() to show legends
show() to view the plot
savefig() To save the plot as .png or .pdf at the desired location
5. What is the purpose of a legend?
Ans. The purpose of a legend in Matplotlib is to provide an explanation or key for the different elements (e.g., lines, markers,
colors) present in a plot. It helps users understand the meaning of each component in the graph, making the visualization
more informative.
6. Define Pandas visualisation.
Ans. Pandas visualization refers to the built-in data visualization capabilities provided by the Pandas library in Python. It allows
users to create various types of plots, charts, and graphs directly from Pandas data structures, such as DataFrames and
Series, making it convenient for data analysis and exploration.
7. What is open data? Name any two websites from which we can download open data.
Ans. Refer to 8.6 Open Data
8. Give an example of data comparison where we can use the scatter plot.
Ans. Refer to 3.1.3 Scatter Plot
9. Name the plot which displays the statistical summary.
Ans. The plot that displays the statistical summary in Matplotlib is called a "box plot" or "box-and-whisker plot."
Note: Give appropriate title, set xlabel and ylabel while attempting the following questions.
10. Plot the following data using a line plot:
Day 1 2 3 4 5 6 7
Tickets sold 2000 2800 3000 2500 2300 2500 1000
a. Before displaying the plot display "Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday" inplace of Day 1,
2, 3, 4, 5, 6, 7
b. Change the color of the line to 'Magenta'.
Ans. import matplotlib.pyplot as plt
# Data
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
tickets_sold = [2000, 2800, 3000, 2500, 2300, 2500, 1000]
# Plotting
plt.plot(days, tickets_sold, color='magenta', marker='o', linestyle='-', linewidth=2,
markersize=8)
# Adding labels and title
plt.xlabel('Day')
plt.ylabel('Tickets Sold')
plt.title('Tickets Sold Each Day')
118 Touchpad Informatics Practices-XII

