US Population Data Analysis by County and Year
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
Introduction
The data study of population over time is a very important topic that can have regular meaning in our everyday lives. Beyond the fact that this year is a census year where we can get a more accurate count of our populations, county population can be very interesting and reveal a lot of patterns in our society today. Where are jobs moving towards? If I am buying a house, where are house prices likely rising? How have things changed since I've been to an area? These are all things that we can study by looking at population over counties over time.
Data was obtained using the US Census data, which was then filtered and adjusted as required. Code was written using Shiny, R, dplyr, ggplot2, and plotly.
Using a slider and drop down, users can select which state they are interested in and what time period from 1970-2019. The resulting graphs and charts will show population trends by their self, compared to the US average, and raw data. If a state has too many counties, users can use the tools provided by plotly to adjust the default display to make it more readable.
The GitHub for the project is here: https://github.com/bacover/CountyPopulationShinyApp
The running Shiny App can be found here: https://bacover.shinyapps.io/CountyPopulation/
Data
Some examples of the resulting output are below:
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