# H1B-visa-application

In this project I have used h1b-visa application dataset. It has 10 columns and 300K+ rows. 

** To process the data I have used different cleaning techniques that includes:
•	Convert categorial data 
•	Drop missing values 
•	Reformate values
•	Find outliers and replace with median
•	Change text into lowercase.

**After cleaning data, I tried to find out statistical relations among the columns. I used graphical representation to explain it. 

** Dataset:
Downloaded dataset from this site: https://www.kaggle.com/nsharan/h-1b-visa

** Requirements:
•	Python, Jupyter notebook
•	Library: matplotlib, numphy, panda

** Files: 
•	Coursework1_DP.ipynb: Python script with codes and graph for data analysis
•	CourseWork-2.ipynb: Python script with the implementation of different classification models on the available data and its evaluation