This repository takes data from the California Pesticide Use Reporting system and calculates crop acreage to at the 1-square-mile resolution. This data is then aggregated to larger regions, either county or irrigation district.

Dependencies: numpy tqdm pandas

Order of Operations

Downloading, processing, and plotting the California pesticide data to understand historical crop acreage

Part 1: Will be converted to a simple datascraper to do all this nonsense for you. Stay tuned. For now: Download data at ftp://transfer.cdpr.ca.gov/pub/outgoing/pur_archives/

1. Unzip each folder from 1974-2016 (e.g. pur1978.zip)
2. save each folder as pur_data_raw/pur ( e.g.pur_data_raw/pur1975)

Part 2: Download .py files from crop_acreages_CA_DPR_reports and place in same folder (which should also contain the pur_data_raw folder)

Part 3: Clean the data - Cleans up bad data by removing any non-alphanumeric characters from the comtrs (COunty, Meridian, Township, Range, Section) indices and compiles data columns to create a comtrs value for each permit. I.e. places each permit, or data row, into a 1-square-mile geographic location as labeled with the comtrs alpanumeric string.

clean_calPIP_data.py

Part 4: Compile and normalize the data by 1-mile section

compile_normalize_data_by_comtrs.py

Part 5: Create graphs comparing County Commissioner data with calPUR dataset

calPUR_county_comparison.py

Part 6, option a: Create several graphs for a chosen irrigation district or county within Tulare Lake Basin

acreage_calc_plots_single_irrigation_district.py

Part 6, option b: Create a specific graph for all irrigation districts within the Tulare Lake Basin