equiticity-census-data/ReadMe.txt at master · NUstat/equiticity-census-data · GitHub

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# 2022-359 CensusTeam
STAT 359 Census Data Team


# Introduction

Hello!

This is a GitHub for a project we did for a non-profit interested in Chicago’s Divvy bikes.
We worked to create scripts focusing on
Census data and other related data for Chicago neighborhoods.

We hope some of these scripts or data can be helpful in exploring demographics in Chicago.

To give you a sense of how to look into our repository, here’s a brief description of most of the files.

# *Table of Contents*

# Folders

## data

Contains raw data files we used for our visualizations.
Most of the data is in .csv format, for easy importing into R
or viewing using spreadsheet software.

The files in the "Bike Routes" (Source: https://data.cityofchicago.org/Transportation/Bike-Routes/3w5d-sru8) and "tl_2019" folders are shape
files, which must be used with an appropriate package to be
added onto a visualization.

### ACS_Chicago_Agg.csv
The aggregated American Community Survey (ACS) from 2015-2019.
Source: https://datahub.cmap.illinois.gov/dataset/community-data-snapshots-raw-data

### CensusTractsTiger2010.csv
Geographic information of Census Tracts from the 2010 Census.
Source: https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Census-Tracts-2010/5jrd-6zik

### ChicagoWalkscore.csv
A table containing walk scores of Chicago neighborhoods form walkscore.com.
Source:  https://www.walkscore.com/IL/Chicago

### Divvy_Bicycle_Stations.csv
A more detailed dataset with information on Divvy bike stations, not included in the other datasets.
Source: https://data.cityofchicago.org/Transportation/Divvy-Bicycle-Stations-Historical/eq45-8inv

### Divvy_Trips_2020_Q1_data.csv
A sliver of Divvy trip info from Divvy itself, which we used to test some of our visualizations.
Source: https://divvy-tripdata.s3.amazonaws.com/index.html

### census_team_2015_2019.dat.csv
A combined dataset that we made by cleaning and collecting census tract-level data.
Source: https://usa.ipums.org/usa/

### comm_density_2021.csv
Community Areas in Chicago with the average amount of Divvy stations in a 2 mile radius (which was calculated by the Divvy Core Data Team).

### commute.csv
Specific data on methods of commuting by Chicago residents from the ACS
Source: https://usa.ipums.org/usa/

### population_fixed.csv
Community populations for Chicago.
Source: https://www.cmap.illinois.gov/documents/10180/126764/_Combined_AllCCAs.pdf/

### poverty_data.csv
More specific poverty data from the ACS 5-year 2015-2019.
Source: https://data2.nhgis.org/main

### poverty_data_codebook.txt

## curated_data

This folder contains data that we have processed in R
friendly .rds format, and in Excel .xlsx format, along with
a codebook, in .pdf format.

### codebook_for_viz_and_comm_data.pdf
A codebook for the data files meant for the Visualization and Communication Team.

### community_index.xlsx
Our marginalization & socioeconomic hardship index, with one row for every community in Chicago.  See index_creation.Rmd for more details.

### demographic_data_community_codebook.pdf
A codebook for our final demographic data files.

### final_demoographic_data_no_geometry_with_connection…
Chicago demographic and divvy data on the community area-level, cleaned and combined data from the ACS, the CMAP Community Data Snapshots, the Divvy Core Data Team's datasets, and the Divvy open data portal, without mapping information.

### final_demographic_data_with_geometry_and_connection…
Same data as in the previous file but with mapping information.

### for_viz_no_geometry.xlsx
Divvy and demographic data on the community area-level used the by Visualization and Communication team without mapping information.

### selected_data_for_viz_com.rds
Same data as in the previous file but with mapping information.

### snapshots_with_connectivity.xlsx
CMAP Community Data Snapshots with Divvy connectivity (from Divvy Core Data Team) added.

## census_data_automation

A census data automation tool, made in Python. Contains the needed “data”, code,
and an “output” folder.

# Scripts

## Main Page

### visualizations.R

Script that contains all of our visualizations from our presentation, as well as some additional ones.
The additional visualizations are helpful to understand the dataset.

### creating_datasets_and_index.R

Brings in ACS data, and outputs a combined dataset with other sources of data in the folder.
Latter half of the script creates our marginalization index.  This script outputs all the data
files in the curated_data folder.

### generic_matching_script.R

Script that allows you to switch between geographical areas, census tracts, and other types
of geographic areas and map points (like Divvy stations) within those areas using shape files.

### variable_distributions.R

A script that creates several histograms and scatter plots with certain variable distributions.
Mainly to get a grasp of the data.  Some explorations of variable correlations.

### bikeroutesandroads.R

Creates plots including bike route and roads in Chicago.


# R Markdown files

### index_creation.Rmd

A detailed breakdown of our Marginalization and Economic Hardship index.


## How to cite

IEEE:
Jung, B, Chalas Cuevas, E, Braud, I, Chandler-Holtz, L, Coble, M (2022) 2022-352CensusTeam [Source code]. INSERT LINK HERE

ACM:
Benedict Jung, Edwin Chalas Cuevas, Ian Braud, Lauren Chandler-Holtz, Mat Coble. 2022. 2022-352CensusTeam. INSERT LINK HERE

CSE:
Jung, B, Chalas Cuevas, E, Braud, I, Chandler-Holtz, L, Coble, M. 2022-352CensusTeam. San Francisco (CA); GitHub; INSERT LINK HERE