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.

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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.

Data Analytics in Python

# Brief description

The **Bureau of Labor Statistics (BLS)** is a US government department. They collect and publish huge amounts of employment and economics-related data and have done for decades now.

## Admiration for BLS

Admiration for BLS jumped to a new level when we discovered their well-supported application programming interface (API). This opens up all that amazing data to intelligent retrieval through our Python scripts. It also gives us some rich data for discovery, as shown in the following figure.

Learn what BLS is and why it's great. We'll also look at an example to understand how to retrieve data through python scripts.

Before We Begin

Comparing Wages With Consumer Price Index Data

Wages and CPI: Reality Check

Working With Major US Storm Data

Property Rights and Economic Development

How Representative Is Your Government?

Does Wealth Influence The Prevalence Of Mental Illness?

Do Birthdays Make Elite Athletes?

Does Literacy Impact The Income of People

Conclusion

Appendix

Introduction

Brief description

Admiration for BLS