Data Visualization - Matplotlib and Seaborn: Two Marks Important Questions and Answers

Python for Data Science

Chapter 6: Data Visualization – Matplotlib and Seaborn

Two Marks Questions with Answers

1. What is visualization ?

Answer: Visualization means representing data or information in the form of graph instead of just numbers or text.

For example ‒ a bar chart or histogram makes it easy to see who scored high, low, and how scores are spread.

2. What is the difference between matlab and matplotlib ?

Answer:

Matlab

1.It is a commercial software and programming language mainly used for mathematics, engineering, signal processing, and scientific research.

2.It is developed by MathWorks and it is a paid software. We need license to use it.

Matplotlib

1.It is a Python library for data visualization.

2.It is community driven open source library and we can freely download and use it.

3. Is a histogram always a bar chart? Justify your answer.

Answer: A histogram looks like a bar chart, but it is not the same because it is meant for continuous data and shows frequency distribution, while a bar chart is for categorical data and shows comparisons. There is no gaps in histogram but there are gaps between bars of bar chart.

4. What is the use of Matplotlib?

Answer: Matplotlib is a Python library used to create visualizations (charts and graphs).

It helps turn numbers (data) into pictures, so patterns and trends are easier to understand.

5. What command is used to verify that Matplotlib is installed?

Answer: The command like

pip show matplotlib

This will display details like version, location, and dependencies if Matplotlib is installed.

6. Enlist data visualization libraries in Python.

Answer: The libraries are ‒

1) Matplotlib

2) Plotly

3) ggplot

4) Seaborn

5) Geoplotlib

7. What is matplotlib library? Enlist the features of it.

Answer: Matplotlib is an open source drawing library. We can generate plots, histograms, bar charts and other types of charts with few lines of codes.

Features are ‒

1) It is a powerful tool for data analysis.

2) It is flexible and supports various forms of data representations.

3) It is easy to access large amount of data using Matplotlib.

4) It is customizable.

5) It can run on different platforms.

6) It is useful in creating advanced visualizations.

8. What is the purpose of bar graph?

Answer: The bar graph makes use of bars to represent the data. The bar() function is used for this purpose.

9. Explain the purpose histogram in data science.

Answer: The histogram is used to understand the distribution of a continuous numerical variable. A histogram is a graph showing frequency distributions. It is a graph showing the number of observations within each given interval. For example ‒ To represent the weights of 1000 people we may use histogram. Using Matplotlib, we can draw the histogram using the function hist() function. The hist() function will use an array of numbers as data to create a histogram.

10. What is the use of marker in graph plotting ?

Answer: The marker parameter can be used to create "markers" in a plot. You can specify the shape of the marker by passing a value to the parameter. For example ‒

from matplotlib import pyplot as plt

import numpy as np

y = np.array([5,2,10,8])

plt.plot(y,marker = 'D')

plt.show()

11. Why do we use seaborn library in Python ?

Answer: Seaborn is a Python data visualization library based on matplotlib. It provides a high level interface for drawing attractive and informative statistical graphics. Seaborn is built on top of matplotlib and integrates closely with Pandas data structures. Seaborn is particularly well suited for working with complex data sets.

12. How will you import seaborn library in your python program ?

Answer: For importing the seaborn library following code must be written at the beginning of your import seaborn as sns

13. What is heatmap?

Answer: Heatmap allows us to represent the data in matrix‒like form. In this Heatmap, more common values or higher activities brighter colors, basically reddish colors are used and to represent less common or activity values, darker colors are preferred.

14. Can we show multiple graph plots in the same figure? Justify.

Answer: Subplot is used for displaying multiple plots in the same plot. Using the subplot() method one can draw multiple plots in one figure.

Python program

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]

y = [10, 20,30, 40,50]

plt.plot(x, y, label='Sample Line')

plt.xticks([1, 2, 3, 4, 5], ['A', 'B', 'C', 'D', 'E'],color='red')

plt.yticks([10, 20, 30, 40, 50], ['Ten', 'Twenty', 'Thirty', 'Forty', 'fifty'])

plt.xlabel('X‒axis Label')

plt.ylabel('Y‒axis Label')

plt.title('Customized Ticks Demo')

plt.show()

Output

This code creates a simple line plot with customized x‒tick and y‒tick labels., The xticks are red colored ticks.

15. How to set titles to the graph, X‒axis and Y‒axis labels.

 Answer: For setting title to the graph the set_title() method is used. Similarly we can set the labels to the x‒axis and y‒axis using the methods set_xlabel and set_ylabel.

Example code

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

# read dataset

titanic = pd.read_csv("d:/titanic.csv")

print(titanic.head())

# create plot

res=sns.countplot(x = 'Pclass',hue='Sex', data = titanic)

res.set_title("Titanic Survivors', fontdict={'size': 20, 'weight': 'bold'})

res.set_xlabel('Class', fontdict={'size': 10})

res.set_ylabel('count of Persons', fontdict={'size': 10})

plt.show()

16. Write Python program using plot function for simple line plot omitting X‒axis values.

Answer:

import matplotlib.pyplot as plt

# Only Y values are given

y = [3, 5, 7, 9, 11, 13]

# Plot without specifying X values

plt.plot(y)

# Show plot

plt.show()

17. What are scatter plots?

Answer: A scatter plot is a type of graph that shows the relationship between two numerical variables. Each point on the plot represents one observation.

18. What is a subplot in Matplotlib?

Answer: Subplot is a function in matplotlib which is used for displaying multiple plots in the same plot. Using the subplot() method one can draw multiple plots in one figure.

19. What is the difference between plot and subplot.

Answer:

Plot

1.It is used to create a single plot in a figure.

2.The simple plt.plot(x,y) function is used.

3.We can modify the title, labels, colors, etc., for a single plot.

4.It is simple and straightforward.

Subplot

1.It is used to create multiple plots within the single figure.

2.In order to arrange multiple plots in rows and columns plt.subplot(rows, cols, index)  function is used.

3.Each subplot can have its own title, labels, and formatting.

4.It is more complex as it involves managing agongwans ( the layout and appearance of multiple plots.

20. Explain the use of seaborn library?

Answer: Seaborn is a Python library built on top of Matplotlib. It is mainly used for making statistical data visualizations that look more attractive and easier to understand than plain Matplotlib plots.