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Repository to evaluate data from the Chicago Transit Authority. This repository also serves as an introduction to using GitHub for ensuring reproducible research.

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CTAnalyze

Objective

This repository hosts data and code to evaluate the Chicago Transit Authority's ridership trends from 2019 - 2023.

Perform the Analysis

This respository can be copied and run locally.

Clone this repository to your local system by pasting the following into your terminal/shell:

git clone https://github.com/meghutch/CTAnalyze.git

Alternatively, follow these instructions for setting up git in Rstudio.

Directory Structure

├── README.md                         <- You are here
|
├── data/
│   ├── README.txt                    <- README documenting raw data extraction process
|
├── processed_data/                   <- Folder containing the pre-processed data files
|   ├── 2019_2023_cta_ridership_data.csv   <- Pre-processed data to be used for analysis 
|
├── R/                                <- Scripts to perform the analysis
|   ├── 00_pre_process_data.R         <- Script to pre-process the raw dataset by date to reduce the file size to the subset of data we want to analyze
|   ├── 01_cta_ridership_analysis.R   <- Script to perform the primary analysis of the ridership trends in the top 3 most frequently visted CTA Stations
|
├── results/figures/                  <- Folder to store analysis results and figures
|   ├── 2019_2023_top_3_stations.png  <- Figure depicting the ridership trends from pre and post pandemic.
    

Run Analysis

To reproduce the analysis:

  1. Review the data/README.txt and download the raw data from the Chicago Data Portal

  2. Pre-process the raw data using R/00_pre_process_data.R

  3. Next, run R/01_cta_ridership_analysis.R to run the analysis

Results / Output

The output of the analysis will identify the CTA stations with the most riders from August 2019 - October 2023.

The resulting figure will output to results/figures/2019_2023_top_3_stations.png

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Repository to evaluate data from the Chicago Transit Authority. This repository also serves as an introduction to using GitHub for ensuring reproducible research.

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