Book Image

Data Analysis Foundations with Python

By : Cuantum Technologies LLC
Book Image

Data Analysis Foundations with Python

By: Cuantum Technologies LLC

Overview of this book

Embark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently. Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling. To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.
Table of Contents (37 chapters)
Free Chapter
1
Code Blocks Resource
2
Premium Customer Support
4
Introduction
7
Acknowledgments
9
Quiz for Part I: Introduction to Data Analysis and Python
13
Quiz for Part II: Python Basics for Data Analysis
17
Quiz for Part III: Core Libraries for Data Analysis
21
Quiz for Part IV: Exploratory Data Analysis (EDA)
25
Quiz for Part V: Statistical Foundations
29
Quiz Part VI: Machine Learning Basics
33
Quiz Part VII: Case Studies
36
Conclusion
37
Know more about us

Practical Exercises Chapter 3

Exercise 1: Your First Script

1. Create a Python script named print_even_numbers.py.

2. Make the script print even numbers from 2 to 20.

# print_even_numbers.py

for i in range(2, 21, 2):

print(i)

 

3. Run your script from the terminal to verify it works.

Exercise 2: Command-Line Arguments

1.Create a Python script named greet_user.py.

2. Modify the script to accept a username as a command-line argument.

# greet_user.py

import sys

 

username = sys.argv[1]

print(f"Hello, {username}!")

 

3. Run the script from the terminal, passing in different usernames to make sure it works.

Exercise 3: CSV File Reader

1. Create a CSV file with columns Name, Age, and Email and populate it with sample data.

2. Write a Python script named read_csv.py.

# read_csv.py

import csv

 

with open('sample.csv', 'r') as file:

reader = csv.reader(file)

for row in reader:

print(row)

 

3. Run the script to make sure...