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Data Analytics in Python

Name: Data Analytics in Python
Price: 59 USD
Rating: 4.53 (22 reviews)
Author: David Clinton

Learn about Python-based data analytics, discover data manipulation and cleaning techniques, explore Jupyter for insights, and gain skills to plot and visualize data effectively.

4.5

51 lessons

1 project

2h 29min

Created by David Clinton

What's included

51 lessons across 11 modules
32 quizzes with instant feedback
1 project in preconfigured environments
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

An understanding of data extraction and preprocessing techniques
A Hands-on experience in analyzing datasets for different problems using Python
Develop skills to gather valuable insights from data
A working knowledge of filtering and refining datasets
The ability to generate different types of graphs for data visualization

Learning Roadmap

51 Lessons32 Quizzes

Before We Begin

Get familiar with Python data analytics, data management, interpretation, and secure storage.

What Is This Course About?

Storing and Protecting Data

Comparing Wages With Consumer Price Index Data

Look at analyzing wage trends alongside consumer prices using Python and BLS API data.

Introduction

Working with API

Working with CPI and Salary Data

Manipulating the CPI Data Series

Converting Percentages to CPI Values

Merge and Plot Our Data Frames

Quiz

Challenge 1 - Plot a Simple Bar Graph

Solution Review - Plot a Simple Bar Graph

Wages and CPI: Reality Check

5 Lessons

Work your way through data integrity, historical context, S&P 500 integration, and growth rate calculations.

Working With Major US Storm Data

10 Lessons

Apply your skills to clean, analyze, and visualize US storm data effectively.

Time Series Analysis and Visualization Using Python and Plotly

Project

Premium

Property Rights and Economic Development

8 Lessons

Take a closer look at analyzing GDP, visualizing datasets, and enhancing plots using Python.

How Representative Is Your Government?

4 Lessons

Tackle analyzing voting data to assess governmental representativeness and party line adherence.

Does Wealth Influence The Prevalence Of Mental Illness?

4 Lessons

Analyze relationships between wealth and mental illness prevalence, considering varied trends and data complexities.

Do Birthdays Make Elite Athletes?

3 Lessons

Try out scraping and visualizing NHL data to analyze birthdate trends among athletes.

Does Literacy Impact The Income of People

4 Lessons

Solve challenges with analyzing literacy’s impact on global and US state income levels.

10.

Conclusion

Explore the foundational data analytics techniques using Python and Pandas you mastered.

Wrap Up!

11.

Appendix

Grasp the fundamentals of installing Python, managing environments, and setting up necessary libraries.

Installations

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

About this course

WHY I WROTE THIS COURSE

In this course, you will get an introduction to Python-based data analytics. You will learn the inner workings of Python to the point where you can confidently find and manipulate data sources and use a Jupyter environment to derive insights from your data. By the end of this course, you will be able to find and clean data sources, plot your data, and use Python functionalities that show graphs of data. It’s your all-in-one guide to teaching yourself data analytics in 30 days.

ABOUT THE AUTHOR

David Clinton

Linux system administrator, AWS solutions architect, data analyst, book and courseware author

Learn more about David

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