- Data science Tasks, including creation of datasets by web scraping(Pandas)
- SQL Topics on SuperDataScience with multiple challenges to gain insight on data. Additionally, loading data into a database. Database design principles to handle a large amount of data.
- MP4 to AVI : Use this to convert an mp4 file to AVI. Usage : python script convert.py [path to mp4 file/ directory] convert.exe in distributions folder - On systems without python ---> convert.exe [path]
- Geospatial Analysis : Interesting way to visualize spatial information
- Geopandas(Marker, Circle), Folium(Choropleth plots, heatmaps), etc.
- Full course available on Kaggle
- All the data for this project was downloaded from here
- Analysis tasks completed on the Child mortality rates:
- Highest and lowest child mortality rates in the years 1990 and 2016
- Plot the child moratlity rates on a map of the world using Choropleths
- Plot the change in child mortality rates in the world on a map using a time slider choropleth
- Analysis tasks completed on heathcare expenditure:
- Plot countries which have a health expenditure less than 5% of their GDP
- Plot top 40 countries which have highest health expenditure
- Make these plots interactive, so that you can check the values for each country individually
- Compare values of Child mortality and health expenditure percentage. Try to correlate these values
As shown, most of these countries have the same correlation between child mortality and health expenditure. There are a few exceptions though, for example:- AFG: High Child mortality in-spite of having a higher health expenditure compared to other countries. Maybe because of the war
- BRN: Brunei has same child mortality as Bulgaria (BGR), but the expenditure is much lesser. Maybe populations are not comparable
