Link to dataset : https://www.kaggle.com/nsharan/h-1b-visa

Link to visualisations: http://edlab-www.cs.umass.edu/~nmundra

The H1B visa is an employment-based, nonimmigrant visa category for temporary workers. For such a visa, an employer must offer a job and apply for your H1B visa petition with the US Immigration Department.

This dataset contains H-1B Visa Petitions for the period of 2011 till 2016. It contains information like job type, job title, work location, wage, etc and the case status which was provided by the Office of Foreign Labor Certification (OFLC).

I am interested in finding out which locations, employers, job titles and salary range makes H1B petition certification more favourable. I am also interested to analyze the cases of Full time and Part time employees separately. And, for my analysis, I have used data of only the year 2016. This is because of the extremely large size of the data and my analysis did not require the data of all the years.

1. Finding out the job positions which are more likely to for getting an H1B.
2. Finding out jobs which make certification unfavourable.
3. Analysing regions in the US which file the maximum number of petitions and the general distribution of case status in each region.
4. Effect of wage and employer on visa case status.
5. Impact of full time status on H1B petitions.
6. Impact of Employer in a state for H1B approval.
7. States filing maximum petitions.

1. Geospatial Heatmap
2. Sunburst with line plot
3. Pie Chart
4. Scatter Plot
5. Row Chart
6. Bubble Chart