Introduction
In the year 2020, nearly 167,000 Indian students applied to the US to pursue education and for almost a decade now, the USA remains the most preferred destination among young graduates making Indian Americans the second-largest immigrant group in the United States. Indian Americans are a continuous constituent of recent arrivals and long-term residents. With many of the recent arrivals being students, U.S. Immigration and Customs Enforcement estimates the total number of SEVIS records for active F-1 and M-1 students being 1,251,569 in the calendar year 2020. And, that is a huge influx of crowds that enter the nation and lets see where such huge population are hosted within the country and find any co-existent variables that might influence today’s Indian immigrant settlement pattern.
Materials
To conduct this analysis, 1 dataset: ACS 2020 (5-Year Estimates) and three main softwares were used, two visualisation software: Social explorer, Data wrapper and one spreadsheet software: MS Excel. The data from the Census or American Community Survey: ACS 2020 (5-Year Estimates) were mapped using Social Explorer and exported as csv to MS Excel, which were then modelled into chart visualisation using DataWrapper.
Method
The main focus of this report is to analyse what factors influence today’s Indian immigrant settlement pattern and to do that we needed two main datasets, one: Foreign-Born Population: India – Native/Foreign Born, 2020 ; ACS 2020 (5-Year Estimates). And two: Total Employed Civilian Population 16 Years and over: Information – Occupation 2020 ; ACS 2020 (5-Year Estimates) with an assumption that Occupation can play an important part in shaping a settlement pattern. Using Socialexplorer, both of these data were mapped by states to infer which states host most of the Indian immigrants and what is the dominant occupation in those states. To visualise and compare the data, we used Bubbles as a visualisation type. After comparing both the maps by states, we later zoomed into Counties to get more granular data (only mapped counties in California as it hosted most of the immigrants).
Limitation: (1) Note that the dataset Foreign-Born Population: India includes both recent arrivals and long-term residents (citizens and non-citizens), so reason for early arrival’s settlement pattern is not taken into consideration. (2) Employed in Information dataset is used for capturing technology opportunities with an assumption Information (Data) is predominantly used in tech companies. (3) Both maps are set in 2020 and impact of the pandemic, new law and other factors are not taken into consideration.
Post capturing both the dataset, the next step was to export the underlying data to MS Excel where it was cleaned and sorted, and visualised comparisons on DataWrapper by creating pie chart and bar chart visualisations of the variables mapped in social explorer.
Data visualisation and Insights
Data visualisation 1– Foreign-Born Population: India – Native/Foreign Born, 2020 ; ACS 2020 (5-Year Estimates).
In 2020, California,Texas, New Jersey, Illinois, New York and Washington hosted the largest number of Indian immigrants and together welcomed 59.2 percent (1,548,268) of all Indian immigrants.
California hosted 547,009 Indian immigrants, the largest percentage of Indian immigrants (21 percent) of any US state.
Data visualisation 2–Total Employed Civilian Population 16 Years and over: Information – Occupation 2020 ; ACS 2020 (5-Year Estimates)
In 2020, California, New York, Florida, New Jersey, Georgia and Illinois, hosted the largest number of Civilian work with Information, assumption more tech opportunities and together holding 51 percent (1,548,268) of all Civilian employed Information.
California again topped with 542,674 tech employees, the largest percentage of tech employees (18 percent) of any US state.
Used the same colour to mark the states with highest Indian immigrant population on both charts to create focus on latter’s effect on the former.
Data visualisation 3 – Tech Opportunities in the US vs Indian-born population in the US
By comparing both the dataset, we can clearly see that there is a pattern to understand the Indian immigrants’ settlement dispersion and observe how the new age of technological companies set up in such areas plays a major role in it, showcasing Tech opportunities in the US attract major Indian immigrants to the country. Especially towards Silicon Valley and the east coast for education and later for Job.
Silicon Valley, California, home to many Indian immigrants is also home to multiple Tech startups and big companies.
Interesting thing about the East coast to note: New York being a hub of many tech opportunities falls after New Jersey in terms of Indian Immigrant population might be because of the high living cost of the city.
Other states also show correspondence to each other as we can see the same states being popped in both maps.
Reflections
In an overview, we tested our assumption and found that Tech Opportunities is definitly one of the major players in how Indian Immigrants both long-term residents and recent arrivals being dispersed within the country.
The future direction of this experiment will be understanding how Indian immigrants’ substantially greater educational attainment, overall levels of poverty being lower than the American average, plays an effect on their settlement pattern would give us more clear insights on the matter.
References
ttps://www.socialexplorer.com/1981d32a2e/view
https://www.datawrapper.de/_/vP5P6/
https://www.datawrapper.de/_/tShVd/
https://www.datawrapper.de/_/RntQb/
https://www.ice.gov/doclib/sevis/pdf/sevisBTN2020.pdf
2019#:~:text=In%20the%202014%2D18%20period,of%20the%20Indian%20population%20collectively.