A Look at Visa Applications Through the Years

Posted on Oct 16, 2017

Introduction

The United States is one of the most culturally diverse countries in the world. People from all backgrounds immigrate to the U.S. in search of new opportunities and the chance for a better life. As a country, the United States welcomes these individuals through the H-1B Visa application. This visa allows people to apply for work in the United States through a “specialty occupation.” A “specialty occupation” is any profession that requires a minimum of a bachelor’s degree within numerous fields like architecture, engineering, education, etc.

The H-1B Visa also aids people in applying for a green card an eventually citizenship. In some instances, companies have sponsored green card applications for the employees who have demonstrated profound understanding in their respective fields. The H-1B Visa is an important first step in attaining the long-sought after “American dream.”

A dataset consisting of all Visa applications between 2011 and 2016 was acquired from Kaggle (https://www.kaggle.com/nsharan/h-1b-visa). The goal of this Shiny app was to be exploratory. It allows users to see trends in the visa status for the careers they wish to pursue.

Data Summary

The raw dataset includes the following categories:

  • Case Status
  • Employer Name
  • SOC Name
  • Job Title
  • Prevailing Wage
  • Year
  • Location

Observations

The first step was to look at the changing number of applicants each year. After applying this data to a line graph, you can see that the number of applicants drastically increases each year. Between 2011 and 2016, the number of applicants more than doubled from 200K to 424K in only five years.

       

Furthermore, using another line graph, we can also visualize the status of applicants as they changed over the years. In 2011, there we approximately 191K certified applicants, while in 2016 there are approximately 371K certified applicants. Surprisingly, the number of denied applicants has decreased over the years but the number of certified-withdrawn applicants have increased. Finally, we took a look at the relative frequency of the applicants by their case status. This showed that no matter the number, there is always an approximate 86% acceptance rate.

Specific Jobs

The second page in the application allows us to see information about specific jobs whether it be through a standard occupation classification (SOC) or through an actual job title. The data shows that the most numerous visa applications for SOC was a database administrator shown below. The graph also depicts the minimum, maximum, average, and median salary in addition to the total number of awarded full time positions. The final tab allows users to search for a specific job title and see the same information.

 

Locations

The last page shows a google map with markers indicating where the applicants, selected via the SOC title in the second page, who were certified and given a full-time position currently work. Based on a few sample entries, one can see that the most positions applied to and given were located on the east and west coast.

Conclusion

This app is intended to be exploratory in order to help individuals search for particular positions. When complementary datasets are acquired, we can improve the app by creating better visualizations on the google map as well as establishing a numerical analysis on specific job acceptance percentages.

About Author

Related Articles

Leave a Comment

No comments found.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp