A repo to demonstrate and practice data visualization. Use Jupyter Notebooks, Python Pandas, Seaborn, and Matplotlib
This project is part of the Foundations of Data Science curriculum at Codecademy. The purpose is to demonstrate data visualization skills using some common tools. Namely: Python Pandas, Matplotlib, and Seaborn. I will be using Jupyter Notebooks as my working environment.
The repository has 4 CSV files. They are:
- all_data.csv = This is the file that Codecademy provides for students to use. It is small, and I've chosen to use other bigger datasets.
- gdp_Data.csv = GDP in current USD for 12 selected countries over a span of 20 years
- adolescent_Data.csv = Adolescent Fertility rates for the same 12 countries over the same span of years. This statistic captures the number of births to mothers between the ages of 15 and 19, per 1000 women between the ages of 15 and 19.
- life_expectancy_Data.csv = Life expectancy from birth for the same countries over the same years
I will conduct a series of univariate descriptive data visualizations, and then move on to bivariate and multivariate analyses. Some of the final analysis will visualize the smilarity of the 6 Latin American countries and their differences with the other 6, mostly European, countries.