Question 1

What is the purpose of the Matplotlib library?

Accepted Answer

Matplotlib is a Python library used for creating static, animated, and interactive visualizations in Python. Its purpose is to provide an easy way to plot data and visualize it in various types of graphs and charts. — Matplotlib provides functions and tools to create a wide range of plots such as line plots, bar charts, histograms, scatter plots, etc., which help in data analysis and presentation.

Question 2

What are some of the major components of any graphs or plot?

Accepted Answer

The major components of any graph or plot include:
- Title: Describes what the graph is about.
- Axes: X-axis and Y-axis which represent variables.
- Labels: Labels for the axes to indicate what they represent.
- Legend: Explains the symbols, colors, or lines used in the plot.
- Grid: Helps in better visualization of data points.
- Data points or lines: The actual representation of data. — These components help in understanding the data being presented and make the graph informative and readable.

Question 3

Name the function which is used to save the plot.

Accepted Answer

The function used to save the plot in Matplotlib is savefig(). — After creating a plot, savefig() can be called with a filename to save the current figure to a file in various formats such as PNG, JPG, PDF, etc.

Question 4

Write short notes on different customisation options available with any plot.

Accepted Answer

Customization options in plots include:
- Changing colors of lines, bars, or points.
- Adding titles and labels to axes.
- Setting limits for axes.
- Adding grid lines.
- Changing line styles and markers.
- Adding legends to explain plot elements.
- Adjusting font sizes and styles.
- Annotating points or areas in the plot. — These options help in making the plot more informative, visually appealing, and easier to interpret.

Question 5

What is the purpose of a legend?

Accepted Answer

The purpose of a legend in a plot is to explain the meaning of different colors, symbols, or line styles used in the graph. It helps the viewer understand what each element in the plot represents. — Legends provide clarity when multiple datasets or categories are plotted together, making the graph easier to interpret.

Question 6

Define Pandas visualisation.

Accepted Answer

Pandas visualization refers to the built-in plotting capabilities of the Pandas library in Python, which allows easy and quick plotting of data stored in Pandas DataFrames and Series using Matplotlib as the backend. — Pandas provides methods like plot(), hist(), boxplot(), etc., which simplify the process of creating various types of plots directly from data structures.

Question 7

What is open data? Name any two websites from which we can download open data.

Accepted Answer

Open data is data that is freely available for anyone to use, reuse, and redistribute without restrictions. Two websites from which open data can be downloaded are:
- data.gov.in (Government of India Open Data)
- Kaggle (https://www.kaggle.com/datasets) — Open data promotes transparency, innovation, and research by making datasets accessible to the public.

Question 8

Give an example of data comparison where we can use the scatter plot.

Accepted Answer

An example where a scatter plot can be used is to compare the relationship between students' study hours and their exam scores. Each point represents a student with coordinates (study hours, exam score). — Scatter plots are useful to observe correlations or patterns between two numerical variables.

Question 9

Name the plot which displays the statistical summary.

Accepted Answer

The plot which displays the statistical summary is the boxplot (or box-and-whisker plot). — Boxplots show median, quartiles, minimum, maximum, and outliers of a dataset, providing a concise summary of its distribution.

Question 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

- Before displaying the plot display “Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday” in place of Day 1, 2, 3, 4, 5, 6, 7
- Change the color of the line to ‘Magenta’.

Accepted Answer

To plot the given data using a line plot with the specified requirements, follow these steps:

1. Import matplotlib.pyplot as plt.
2. Define the days as ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'].
3. Define tickets_sold as [2000, 2800, 3000, 2500, 2300, 2500, 1000].
4. Use plt.plot(days, tickets_sold, color='magenta') to plot the line.
5. Set the title, xlabel, and ylabel appropriately.
6. Display the plot using plt.show().

Example code:

```python
import matplotlib.pyplot as plt

days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
tickets_sold = [2000, 2800, 3000, 2500, 2300, 2500, 1000]

plt.plot(days, tickets_sold, color='magenta')
plt.title('Tickets Sold Over a Week')
plt.xlabel('Day')
plt.ylabel('Tickets Sold')
plt.show()
``` — Replacing numeric day labels with day names improves readability. Changing line color to magenta is done via the color parameter in plt.plot(). Setting title and axis labels makes the plot informative.

Question 11

Collect data about colleges in Delhi University or any other university of your choice and number of courses they run for Science, Commerce and Humanities, store it in a CSV file and present it using a bar plot.

Accepted Answer

Steps to solve:

1. Collect data about colleges and the number of courses offered in Science, Commerce, and Humanities.
2. Create a CSV file with columns like College Name, Science, Commerce, Humanities.
3. Load the CSV file using pandas.
4. Use matplotlib or pandas plotting to create a bar plot showing the number of courses for each college.
5. Set appropriate title, xlabel (Colleges), ylabel (Number of Courses), and legend.

Example code snippet:

```python
import pandas as pd
import matplotlib.pyplot as plt

data = pd.read_csv('colleges_courses.csv')

# Plotting
ax = data.plot(x='College Name', kind='bar', stacked=False)
plt.title('Number of Courses in Different Streams per College')
plt.xlabel('College Name')
plt.ylabel('Number of Courses')
plt.show()
``` — Bar plots effectively compare categorical data such as number of courses across colleges. Storing data in CSV allows easy data management and plotting.

Question 12

Collect and store data related to the screen time of students in your class separately for boys and girls and present it using a boxplot.

Accepted Answer

Steps to solve:

1. Collect screen time data (in hours) for boys and girls separately.
2. Store the data in a CSV or directly in lists.
3. Use matplotlib or pandas to create a boxplot comparing screen time distributions.
4. Set title, xlabel (Gender), ylabel (Screen Time in hours).

Example code:

```python
import matplotlib.pyplot as plt

boys_screen_time = [2, 3, 4, 5, 3, 2, 4]
girls_screen_time = [1, 2, 2, 3, 2, 1, 3]

plt.boxplot([boys_screen_time, girls_screen_time], labels=['Boys', 'Girls'])
plt.title('Screen Time Comparison')
plt.ylabel('Screen Time (hours)')
plt.show()
``` — Boxplots show the distribution, median, quartiles, and outliers of screen time for boys and girls, allowing comparison of their screen usage patterns.

Question 13

Explain the findings of the boxplot of Figure 4.18 by filling the following blanks:

a) The median for the five subjects is ____, ____, ____, ____, ____

b) The highest value for the five subjects is : ____, ____, ____, ____, ____

c) The lowest value for the five subjects is : ____, ____, ____, ____, ____

d) _________ subject has two outliers with the value ______ and ______

e) _________ subject shows minimum variation

Accepted Answer

As the figure 4.18 is not provided here, the answers depend on the boxplot data shown in that figure. Generally:

a) The median values are the middle lines inside each box for the five subjects.

b) The highest values correspond to the top whiskers or maximum data points.

c) The lowest values correspond to the bottom whiskers or minimum data points.

d) The subject with two outliers will have points plotted outside the whiskers; their values are the outlier data points.

e) The subject with the smallest interquartile range (IQR) shows minimum variation. — Boxplots visually summarize data distribution. Medians, extremes, outliers, and variation can be identified from the plot. The exact values must be read from Figure 4.18.

Question 14

Collect the minimum and maximum temperature of your city for a month and present it using a histogram plot.

Accepted Answer

Steps to solve:

1. Collect daily minimum and maximum temperature data for a month.
2. Store the data in two lists or a CSV file.
3. Use matplotlib to plot histograms for minimum and maximum temperatures.
4. Use different colors and add legend to distinguish between min and max temperatures.
5. Set title, xlabel (Temperature), ylabel (Frequency).

Example code:

```python
import matplotlib.pyplot as plt

min_temps = [list of min temps]
max_temps = [list of max temps]

plt.hist(min_temps, alpha=0.5, label='Min Temp')
plt.hist(max_temps, alpha=0.5, label='Max Temp')
plt.title('Temperature Distribution for a Month')
plt.xlabel('Temperature (°C)')
plt.ylabel('Frequency')
plt.legend()
plt.show()
``` — Histograms show the frequency distribution of temperature values, helping to understand the range and common temperature values in the city.

Question 15

Conduct a class census by preparing a questionnaire. The questionnaire should contain a minimum of five questions.

Accepted Answer

To conduct a class census:

1. Prepare a questionnaire with at least five questions related to student demographics, preferences, or habits. For example:
   - What is your age?
   - What is your favorite subject?
   - How many hours do you study daily?
   - Do you participate in extracurricular activities?
   - What is your preferred mode of learning?
2. Collect responses from all classmates.
3. Organize and analyze the data.
4. Optionally, visualize the data using appropriate plots. — A class census helps gather information about students which can be used for analysis or planning. Preparing a good questionnaire is the first step.

Plotting Data using

Plotting Data using — Study Notes

4.1 INTRODUCTION

4.2 PLOTTING USING MATPLOTLIB

4.3 CUSTOMISATION OF PLOTS

Practice Questions — Plotting Data using

All 7 Chapters in Informatics Practices