Exploring Immigration Patterns in Chicago
Data Analytics and Visualization | 2023 | Designed using Tableau, R, and Microsoft Excel | Role - Data Visualization Designer
This academic project was collaboratively undertaken by Nishanth Srikanth, Naomi Ito, and myself.
My role involved sourcing and cleaning the data, then designing dashboards in Tableau to present the insights clearly and effectively.
Chicago is a city of neighborhoods, each of which has a rich history and culture. From the Ukrainian Village to the Polish and Lithuanian Broadways, to the "Black Metropolis" of Bronzeville, immigrants and immigration has played a strong role in shaping the city. As an international student, I've had the enriching experience of delving into Chicago's rich past, while also observing the current political dialogue surrounding immigration laws and policies.
This project aims to delve deeper into the historical and current narratives of the immigrants who have shaped both Chicago and Cook County at large, exploring their profound impact.
The interactive dashboard presented below is designed as an exploratory tool for visualizing immigration patterns in Chicago. You are encouraged to engage with this dashboard, click around, and discover various trends and insights about immigration in the city.
Data Source: Steven Ruggles, Sarah Flood, Matthew Sobek, Daniel Backman, Annie Chen, Grace Cooper, Stephanie Richards, Renae Rogers, and Megan Schouweiler. IPUMS USA: Version 14.0 [dataset]. Minneapolis, MN: IPUMS, 2023.
https://doi.org/10.18128/D010.V14.
We primarily used data from the American census, including the Decennial Census, as well as the yearly American Community Surveys. Both datasets are collected by the Census Bureau, a Part of the US Dept. of Commerce.
Population and Birthplace datasets:
The Population and Birthplace were taken from IPUMS and NHGIS. IPUMS consists of microdata samples from United States census records. The records are converted into a consistent format and made available to researchers through a web-based data dissemination and analysis system.
IPUMS is housed at the Institute for Social Research and Data Innovation (ISRDI), an interdisciplinary research center at the University of Minnesota, under the direction of Professor Steven Ruggles.
The variable used was: Birthplace.
The data was filtered by county, using State ICP / County ICP. NHGIS was used to find the ICP codes for counties as these were different for years before 1950.
These variables were downloaded for 18 cases from 1870 to 2021.
Economic Datasets:
The economic datasets came from the American Community Survey tables:
B06010 Place of Birth by Individual Income in the past 12 months
B06011 Median Income in the Past 12 Months
B06012 Place of Birth by Poverty Status in the Past 12 months
B08511 Means of Transportation to Work by Citizenship Status
B27020 Health Insurance Coverage Status and Type by Citizen
Datasets
All datasets were filtered to Cook County. These were further cleaned and edited as some broke down the data by Citizenship (Naturalized Citizen vs. Not a Citizen), while others broke things down by place of birth. These were combined to compare just “Foreign Born” vs “Native Born” and were checked with the total population to ensure correctness.
In some cases, only data for Chicago was available, and some years did not include breakdowns by place of birth for Cook County. These had to be filtered out accordingly. R was used to decode the data.
The final visualization takes the form of 5 different exploratory dashboards, each focused on one topic or question to be answered. Each dashboard includes a range of interactivity, including parameters and filters to sort and explore different variables, and additional information/ charts in tooltips. To accomplish this, we used LOD, context filters.
Technical Complexity
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