Based on the data, one can see the relationship between various college branches or majors and the salaries of the graduates. Read on to find out % of women, STEM etc:- have any correlation on the salries of the gradutes.
I have used pandas and ebay car sales data of Germany to analyse resale values of major car brands. Read on to find out the costliest car brand, best value for money car brand etc:-
What do all profitable apps have in common ? From a DataScience perspective, have a look at the profiles of the most profitable apps on Appstore and Playstore. Read on to find out which category of apps have more chance to succeed
In this post, using a real case dataset of the exit surveys, let’s find out why the employees are leaving.
In this post, using pandas I will try to analyse New York city’s high school SAT scores, and will try to look at any possible correlation between scores and gender, race, financial background, geographical location of schools.
