Unit – V
UNIT V DATA VISUALIZATION
Introduction to Matplotlib, Importing Matplotlib – SciPy - Line plots – Scatter plots – visualizing errors –
density and contour plots – Histograms – legends – colors – subplots – text and annotation – customization
– three-dimensional plotting - Geographic Data with Basemap - Visualization with Seaborn, Data
Visualization Tools.
Sl. No. Part – A (2 MARKS) K-Level CO
Questions with Answers
1. What is the purpose of matplotlib? K1 CO5
Matplotlib is a cross-platform, data visualization and graphical plotting library
for Python and its numerical extension NumPy.
One of Matplotlib’s most important features is its ability to play well with many
operating systems and graphics backends.
2. Write the dual interface of matplotlib? K1 CO5
The dual interfaces of matplotlib are: a convenient MATLAB-style state-based
interface, and a more powerful object-oriented interface.
3. How to draw a simple line plot using matplotlib? K2 CO5
import matplotlib.pyplot as plt
plt.style.use('seaborn- whitegrid')
import numpy as np
fig = plt.figure()
ax = plt.axes()
x = np.linspace(0, 10, 1000)
ax.plot(x, np.sin(x))
4. What functions can be used to draw the scatterplot? K2 CO5
plt.plot are the functions used to draw the scatter plots.
Example:
x = np.linspace(0, 10, 30)
y = np.sin(x)
plt.plot(x, y, 'o', color='black');
Output:
A second, more powerful method of creating scatter plots is the plt.scatter
function, which can be used very similarly to the plt.plot function.
Example:
plt.scatter(x, y, marker='o')
5. Write the difference between plot and scatter functions? K2 CO5
The primary difference of plt.scatter from plt.plot is that it can be used to create
scatter plots where the properties of each individual point (size, face color, edge
color, etc.) can be individually controlled or mapped to data.
6. Define contour plot? K1 CO5
Contour plot used to plot three dimensional data into two dimensional data. A
contour plot can be created with the plt.contour function. It takes three arguments:
a grid of x values, a grid of y values, and a grid of z values.
7. What are the functions can be used to draw the contour plots? K1 CO5
plt.contour, plt.contourf, and plt.imshow are the functions used to draw the
contour plots.
Example:
x = np.linspace(0, 5, 50)
y = np.linspace(0, 5, 40)
X, Y = np.meshgrid(x, y)
Z=f(X,Y)
plt.contour(X, Y, Z, colors='black')
Output:
8. What is the purpose of using histogram? K1 CO5
A simple histogram is very useful in understanding a dataset. It is used to
specify the frequency distributions between two varibales.
Example:
plt.style.use('seaborn-white')
data = np.random.randn(1000)
plt.hist(data)
9. Write the source code to draw a simple histogram? K2 CO5
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('seaborn-white')
data = np.random.randn(1000)
plt.hist(data)
Output:
10. How to create a three-dimensional wireframe plot? K2 CO5
The three-dimensional plots that work on gridded data are wireframes. It take a
grid of values and project it onto the specified three dimensional surface, and can
make the resulting three-dimensional forms quite easy to visualize.
Example:
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.plot_wireframe(X, Y, Z, color='black')
ax.set_title('wireframe')
Output:
11. Define surface plot? K1 CO5
A surface plot is like a wireframe plot, but each face of the wireframe is a filled
polygon. Adding a colormap to the filled polygons can aid perception of the
topology of the surface being visualized.
Example:
ax = plt.axes(projection='3d')
ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='viridis', edgecolor='none')
ax.set_title('surface')
Output:
12. What is Seaborn and why is it used? K1 CO5
Seaborn is a open-source Python library built on top of matplotlib. It is used for
data visualization and exploratory data analysis. Seaborn works easily with
dataframes and the Pandas library. The graphs created can also be customized
easily.
Benefits of Data Visualization:
Graphs can help us find data trends that are useful in any machine learning
or forecasting project. Graphs make it easier to explain your data to non-
technical people.
Visually attractive graphs can make presentations and reports much more
appealing to the reader.
13. What is SciPy? K1 CO5
SciPy is an open-source Python library used for scientific and technical
computing, built on top of NumPy.
14. What is the purpose of error bars in data visualization? K1 CO5
Error bars show variability or uncertainty in the data, often representing standard
deviation or confidence intervals.
15. What is a heatmap in Seaborn? K1 CO5
A heatmap is a 2D data visualization where individual values are represented as
colors, commonly used for correlation matrices or density data.
16. What is the use of colors in data visualization? K1 CO5
Colors enhance clarity, highlight patterns, and differentiate data groups or variables
in a plot.
17. What is text annotation in a Matplotlib plot? K1 CO5
Text annotation adds descriptive text to plots to highlight or explain specific data
points.
18. Write a command to create subplots in Matplotlib. K2 CO5
plt.subplot(rows, cols, index)
19. How do you add a legend to a plot in Matplotlib? K2 CO5
plt.legend()
20. How do you import the Matplotlib library? K2 CO5
import matplotlib.pyplot as plt
21. write a command to create a basic scatter plot and display a plot on a screen K2 CO5
using Matplotlib.
To create scatter plot
plt.scatter(x, y)
display a plot on a screen
plt.show()
22. What is Basemap in Matplotlib? K1 CO5
Basemap is a toolkit for plotting 2D geographic data, allowing map projections,
coastlines, and location plotting.
Part – B (13 MARKS)
Sl. No. Questions K-Level CO
1. What is Matplotlib? Explain its significance in data visualization. Describe the two K3 CO5
main interfaces used in Matplotlib with examples.
2. Briefly explain about the line plot and scatter plot. K3 CO5
3. Explain contour plot and histogram. K3 CO5
4. Explain in detail about 3D plotting in Matplotlib with example. K3 CO5
5. How graphical data can be projected using matplotlib? Explain with example. K3 CO5
6. Explain the different types of joins in python K3 CO5
7. Briefly explain about the visualization with seaborn. Give an example working K3 CO5
code segment that represents a 2D Kernal density data for any data.
Part – C (15 MARKS)
Sl. No. Questions K-Level CO
1. Explain the key features of the Matplotlib library used for data visualization in K4 CO5
Python. Demonstrate its usage with relevant plot types (e.g., line, scatter,
histogram, subplot). Analyze the strength and limitations of using Matplotlib in
comparison with other visualization tools."
2. How can data be visually represented using scatter plots, line plots, and K3 CO5
histograms in Matplotlib? Use appropriate examples and explain how
customization (colors, labels, titles, etc.) enhances readability.
3. Discuss various data visualization tools available in Python, including K3 CO5
Matplotlib, Seaborn, and Basemap. Highlight the applications of Basemap in
plotting geographic data. Provide examples and real-world use cases.
4. What is error visualization in Matplotlib? Illustrate the use of error bars in K3 CO5
scientific and statistical graphs. Explain how they help in data interpretation with
example code.
