Repository for Project 1: Charlotte income vs commute analysis
Team:
Bandana Deo
Catlin Smith
Hunter Johnson
John Falcone
Charlotte Census block groups analysis:
With charlotte being one of the largest growing metro areas in the united states at the moment our team felt it would be a good idea to take a look at some population metrics and find a correlation between household income and commuting to work. Hoping to find a large correlation between higher paying jobs in the Charlotte metro area, and single person commuting. Along with more people in poverty having a diverse set of ways to get to work.
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Do people with higher paying jobs tend to commute alone more?
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Do people with lower paying jobs tend to use a more varied array of ways to get to work?
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Where is the area with the lowest average income and their preferred method of commuting?
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Where is the area with the highest average income and their preferred method of commuting?
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Where is an area with the closest to city wide average income and their preferred method of commuting?
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What do these metrics tell us about the city of Charlotte?
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Are there more people that live and work in the same area when that area is closer to uptown/ do more people walk to work the closer they live to uptown?
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Do rural areas have more single occupancy commuters?
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Where is the biggest change in commuting style in the blocks?
Data Sources:
https://data.charlottenc.gov/datasets/census-commuting-block-groups
Charlotte NC has its own API’s available for free to use by anyone, these data sets are both for years 2011-2015, so while not a current analysis it should be enough data to see trends and analyze for the future.
Tools used:
Python
Pandas
MatPlotlib
Jupyter Notebook
Python API’s
Products:
Data visualizations using MatPlotlib
Git Hub repository
PowerPoint presentation