https://github.com/clhenrick/census-lehd-lodes-od

analysis of U.S. Census LEHD LODES Origin Destination data (https://lehd.ces.census.gov/data/#lodes)
https://github.com/clhenrick/census-lehd-lodes-od

Last synced: about 2 months ago
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analysis of U.S. Census LEHD LODES Origin Destination data (https://lehd.ces.census.gov/data/#lodes)

• Host: GitHub
• URL: https://github.com/clhenrick/census-lehd-lodes-od
• Owner: clhenrick
• License: mit
• Created: 2018-09-21T00:41:48.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-10-01T00:12:40.000Z (over 6 years ago)
• Last Synced: 2024-11-09T12:48:33.517Z (3 months ago)
• Language: Jupyter Notebook
• Size: 943 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# Analysis of Census LEHD LODES Origin Destination data

Part 1: determine census tracts with the highest number of workers living outside of the tract's county.

## Running

Running `make` will download the LEHD data, run the Jupyter notebook, and join the processed data to 2010 census tract geometries.

This assumes you have an python environment setup called `jobs_map_env` and have the `mapshaper` cli tool available globally. See [Environment Setup](#environment-setup) for more.

## Notebooks

To run the notebooks locally first activate the `conda` environment:

```

source activate jobs_map_env

```

Then do:

```

jupyter notebook

```

## Data

Data sourced from:

https://lehd.ces.census.gov/data/lodes/LODES7/ca/od/ca_od_main_JT00_2015.csv.gz

https://lehd.ces.census.gov/data/lodes/LODES7/ca/ca_xwalk.csv.gz

The LEHD origin destination data is very large so is not checked into this repo.

## Environment Setup

For using Python Pandas and GeoPandas for data processing.

First, install [Miniconda3](https://conda.io/miniconda.html) and set up a Python virtual environment with dependencies.

```bash

# install miniconda, for more see: https://pandas.pydata.org/pandas-docs/stable/install.html

bash Miniconda3-latest-MacOSX-x86_64.sh

# make sure to add conda to your PATH

export PATH="/Users/chrishenrick/miniconda3/bin":$PATH

# create virtual env

conda create -n jobs_map_env python

# activate env

source activate jobs_map_env

# install pandas

conda install pandas

# install pip

conda install pip

# install shapely, geos, gdal

conda install shapely

conda install gdal

# install geopandas

conda install -c conda-forge geopandas

# install jupyter

python -m pip install --upgrade pip

python -m pip install jupyter

# to deactivate the virtual env

source deactivate

```