Indrouction to Python Libraries

1. Python Libraries
Presented By
Nellaiammal S
Junior Engineer

2. Agenda
1. Python
2. Introduction to Python Libraries
3. Features of Python Libraries
4. Popular Python Libraries
5. Matplotlib
6. Numpy
7. How to install and import Python Libraries?
8. Conclusion and Resources

3. Python
Python is a high-level programming language known for its simplicity and
readability.
Features of python:
1. Easy to learn syntax
2. Interpreted language
3. High level language
4. Dynamic typing
5. Large standard library
6. Versatility

4. Introduction to Python
libraries
Python libraries are collections of pre-written code that provide a wide
range of functionality, from data analysis to web development and
machine learning.

5. Features of Python libraries
1 Extensive
Functionality
Python libraries offer
extensive functionality to
perform various tasks,
making it a versatile
programming language.
2 Reusability
They allow for code
reuse, enabling
developers to save time
and effort in writing
programs by using
existing modules and
libraries.
3 Community
Contributions
Contributions from a
supportive community
ensure a broad array of
high-quality libraries
available for various
purposes.

6. Popular Python libraries for Data
Analysis
Pandas
A powerful data manipulation and analysis
library, widely used for handling structured data.
NumPy
An essential library for scientific computing and
numerical operations, including support for large,
multi-dimensional arrays.

7. Popular Python libraries for Web
Development
Django
A high-level web framework known for its clean
design and efficient handling of web
development tasks.
Matplotlib
A comprehensive library for creating static,
animated, and interactive visualizations in
Python.

8. Popular Python libraries for Machine
Learning
TensorFlow
An open-source software library for dataflow and
differentiable programming across a range of
tasks.
Scikit-learn
It provides tools for machine learning, including
algorithms, models, and preprocessing
techniques.

9. Matplotlib
Matplotlib is a popular Python library used for creating static, interactive, and animated visualizations in
Python. It provides a wide variety of plotting functions and customization options, making it suitable for a
broad range of data visualization tasks.
Features:
• Plotting
• Customization
• Multiple plotting styles
• Animation
• Wide adoption and community support

10. Example:
import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5] y = [2, 3, 5, 7, 11]
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_title('Simple Line Plot') ax.set_xlabel('X-axis') ax.set_ylabel('Y-
axis')
plt.show()

11. Output:
The plt.subplots() function is used to create a new figure (fig) and axis (ax). A figure represents the
entire window or page where the plot is drawn, while an axis represents an individual plot within the
figure.
The ax.plot() method is called to plot the data x against y.
The ax.set_title(), ax.set_xlabel(), and ax.set_ylabel() methods are used to customize the
plot by setting a title, x-axis label, and y-axis label, respectively.
Finally, the plt.show() function is called to display the plot on the screen.

12. Numpy
NumPy is a powerful library for numerical computing in Python, providing essential data structures and
functions for performing a wide range of numerical computations efficiently. It is widely used in various
fields such as scientific computing, engineering, machine learning, data analysis, and more.
Features:
• Multi dimensional arrays
• Efficient numerical operations
• Indexing and slicing
• Random number generation
• Memory efficiency and performance

13. Example:
import numpy as np
arr1 = np.array( [1, 2, 3, 4, 5] )
result_addition = arr1 + 10
result_subtraction = arr1 - 3
result_multiplication = arr1 * 2
result_division = arr1 / 2
print(arr1)
print(result_addition)
print(result_subtraction)
print(result_multiplication)
print(result_division)

14. Output:
• We first import NumPy as np.
• We create a NumPy array, arr1 , using the np.array() function.
• We perform basic arithmetic operations (addition, subtraction, multiplication, and division) on
arr1.

15. How to install and import Python
libraries
Install Using pip
Python libraries can be installed using the pip package manager, with simple commands
like pip install library-name.
Import in Python Code
After installation, libraries can be imported into Python code using the import statement,
such as import library-name.

16. Conclusion
Python libraries play a crucial role in enabling developers to efficiently tackle a wide range of tasks
across different domains. Throughout this presentation, we've explored several essential Python libraries
and their applications.
Whether you're analyzing data, building machine learning models, creating visualizations, or developing
web applications, Python libraries provide the tools you need to succeed.
Python continues to empower developers worldwide to innovate and solve real-world problems. Embrace
Python libraries, and unlock the full potential of your projects.