This course is all about learning to use python and jupyter notebooks by exploring fun, real-world data projects.

teach yourself data analytics in 30 days.png

Jupyter.tar.gz

jupitor

code

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

## Storing of the data

We'll generate data in CSV and JSON files while collecting and cleaning data sets. We'll also store our Python scripts in `.ipynb` notebook files. Thankfully, Jupyter will regularly autosave your notebooks. These files are live in a **Docker** container, as shown in the following figure.

## Protecting the data

If the host is shut down for the last time and decommissioned (or corrupted beyond repair), our CSV and `.ipynb` files go with it. To preserve all
that data, make sure up-to-date copies exist in reliable places.
After all, data doesn’t back itself up.

<p>These files live in a Docker container.</p>


<p>Where are the live CSV and JSON files?</p>


# Storing of the data

We'll generate data in CSV and JSON files while collecting and cleaning data sets. We'll also store our Python scripts in `.ipynb` notebook files. Thankfully, Jupyter will regularly autosave your notebooks. These files are live in a **Docker** container, as shown in the following figure.

# Protecting the data

If the host is shut down for the last time and decommissioned (or corrupted beyond repair), our CSV and `.ipynb` files go with it. To preserve all
that data, make sure up-to-date copies exist in reliable places.
After all, data doesn’t back itself up.

Learn to see where we store and protect data for later use.

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

Storing and Protecting Data

Storing of the data

Protecting the data