GDP and life expectancy

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For this project, you will analyze data on GDP and life expectancy from the World Health Organization and the World Bank to try and identify the relationship between the GDP and life expectancy of six countries.

During this project, you will analyze, prepare, and plot data in order to answer questions in a meaningful way.

After you perform your analysis, you’ll be creating a blog post to share your findings on the World Health Organization website.

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Project Objectives:

Complete a project to add to your portfolio
Use seaborn and Matplotlib to create visualizations
Become familiar with presenting and sharing data visualizations
Preprocess, explore, and analyze data

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Prerequisites:

Data Acquisition
Data Visualization
Hypothesis Testing
Summarizing Quantitative Data
Data Wrangling and Tidying
Data Manipulation with Pandas

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Necessary Files:

Click this link to download a zip file with the necessary starter code and design assets. Note that life_expectancy_gdp.ipynb is a blank file and should be used to create your project. Going off platform:

For this particular project, you will be using Jupyter Notebook and Git version control. If you need help with your setup, read our articles about getting started off platform:

[Command Line Interface Setup](https://www.codecademy.com/articles/command-line-setup)
[Introducing Jupyter Notebook](https://www.codecademy.com/articles/introducing-jupyter-notebook)
[Setting up Jupyter Notebook](https://www.codecademy.com/articles/setting-up-jupyter-notebook)
[Getting Started with Jupyter](https://www.codecademy.com/articles/getting-started-with-jupyter)
[Getting More out of Jupyter Notebook](https://www.codecademy.com/articles/getting-more-out-of-jupyter-notebook)

If you need a refresher on how to work with Git for version control, review the GitHub Desktop article and additional help on this Git cheat sheet.

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Debugging Tips + Helpful Resources

Feeling stuck? Try the following:

Google your question: oftentimes, someone has had the same question as you! Check out websites like [StackOverflow](https://stackoverflow.com/) and [Dev.to](https://dev.to/) to see how other folks have found solutions.
Read the documentation: make sure to carefully read through the documentation for any languages and libraries that you are using. Oftentimes they’ll have examples of what you’re looking for!
Rubber ducking: try to explain a problem to a friend or co-worker. Oftentimes you’ll figure out the solution as you’re trying to explain it. And if not, getting another pair of eyes on your code can be helpful.

Check out these helpful resources:

[Matplotlib tutorial](https://matplotlib.org/tutorials/introductory/pyplot.html)
[seaborn examples](https://seaborn.pydata.org/examples/index.html)
[numPy tutorial](https://numpy.org/doc/stable/user/quickstart.html)
[pandas user guide](https://pandas.pydata.org/docs/user_guide/10min.html)

Example Code

What to see an example of how someone else has completed this project? Click this link to download a zip file containing one example solution to this project. Remember: your project doesn’t have to look anything like this! It should be unique to your vision.