This repository contains all of the data and code used for analyzing preferential sampling in personal weather stations.
- preprocessed_data: this folder contains the preprocessed data with weather underground and census data combined into .shp files, organized by location / time period.
- notebooks: this folder contains .ipynb notebooks used for conducting analysis.
Please consult the notebooks to see the code used in the analysis.
The following requirements are needed to run the code in this repository.
- PyMC - for running models.
- Arviz - for visualizing PyMC results.
- GDAL - must be installed for data preprocessing steps.
- PySAL - for geographic data manipulation.
- Geopandas - for working with .shp files.
- Statsmodels - for some basic statistical analysis.
- Numpy and Pandas - for basic data manipulation.
If you would like to understand how to pull Weather Underground data, or better understand any of the questions, please make an issue, or send me a note! I would love to hear your questions.