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voting_capstone

Measuring the effect of polling place closures on voter turnout

Project Organization

├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── results        <- CSV data of results from different model specifications.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. 
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- PDF version of final reports
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── src                <- Source code for use in this project.
    ├── __init__.py    <- Makes src a Python module
    │
    ├── data           <- Scripts for data cleaning and processing.
    │   │                 
    │   ├── cleaning_functions.py     <- Functions used in cleaning and formatting raw NC voter data. 
    │   └── clean_data.py             <- Transforms raw data into intermediate data that can be geocoded. Writes to CSVs. 
    │   └── combine_CSVs.py           <- Script for combining Dask CSVs into a single file
    │   └── here_geocode.py           <- Geocode CSVs of data written from Dask into latitude/longitude coords using Here API.
    │   └── find_poll_distance.py     <- Takes geocoded data, adds distance from each voter to their polling place.
    │   └── query_census.py           <- Script for getting some descriptive stats on NC from the census. Deprecated. 
    │
    ├── models         <- Scripts for running our model over the finalized data set
    │   │                 
    │   ├── nearest_neighbors.py      <- Takes geocoded data, finds each voter's neighbors within given caliper width
    │   └── make_blocked_df.py        <- Takes geocoded data, makes CSV formatted for running our regression model
    │
    └── visualization  <- Scripts to create exploratory and results oriented visualizations
        └── visualize.py

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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MIMS capstone project investigating the causal impact of polling place changes on voter turnout using a novel geographical matching method

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