Last updated: 2021-07-19

Purpose

This code creates keys to relate USDA acreage data to USGS crop categories for pesticide data for California. The USGS pesticide data is derived from a different dataset than the rest of the country (CA Pesticide Use Reporting), in which a greater range of crops are included than in the main dataset used by USGS (survey data from Kynetec). Because the CA-PUR data is reported in the form of use rate, USGS did not need to estimate crop acreage for this state. So, I am attempting to match CA-PUR crops to USDA crops to the best extent possible.

Data sources

Data sources for USDA crop acreage data are described in the data extraction code. Information on which crops are included in the CA-PUR dataset is from USGS metadata, Baker & Stone (2015) Appendix 1, and personal communication with Nancy Baker.

Libraries & functions

library(tidyverse)
library(data.table)
library(stringr)

Load data

# Acreage data
crop_data <- read.csv("../output_big/nass_survey/qs.crops.ac.nat_20200404.csv")
str(crop_data)
# Load keys created for the rest of the continental US
harv_key <- read.csv("../keys/crop_key_harv.csv", stringsAsFactors=FALSE)
str(harv_key)

plant_key <- read.csv("../keys/crop_key_plant.csv", stringsAsFactors=FALSE)
str(plant_key)

Subset data

Select crop acreage that meets the following conditions:

  • Annual estimate
  • 1992 or later
crop_data_sub <- crop_data %>%
  filter(FREQ_DESC=="ANNUAL"&
          REFERENCE_PERIOD_DESC=="YEAR" &
          (YEAR>1991))

Extract crop names

crop_names <- crop_data_sub %>%
  group_by(SOURCE_DESC, SHORT_DESC, YEAR) %>%
  summarise(n = length(VALUE)) %>%
  spread(key = SOURCE_DESC, value = n)

Data items for major crops

The goal here is to create keys to relate USDA crop data to USGS surveyed crops. There are two keys because of slightly different types of acreage data - only those acres that were harvested, and all acres in the ground (planted). Availability of these items can vary across crops, years, and datasets (Census vs. Survey).

Notes

  • Acreage categories for California appear to be similar to the rest of the country for major crops (corn, soybean, cotton, alfalfa, rice, wheat), so this part of the table was left as-is

Data items for minor crops

Orchards and grapes

This category includes tree crops (fruits, nuts) and grapes. According to the metadata associated with the USGS dataset, in addition to those crops represented in the rest of the country, in California this category includes chestnuts, dates, figs, kiwifruit, kumquats, limes, mangoes, olives, citrus, other; nut trees, other; pome fruit, other; stone fruit, papayas, and persimmons

# look for all data items with orchard crops or grapes in the short description
chestnut_names <- filter(crop_names, str_detect(SHORT_DESC, "CHESTNUT"))
date_names <- filter(crop_names, str_detect(SHORT_DESC, "DATE"))
fig_names <- filter(crop_names, str_detect(SHORT_DESC, "FIG"))
kiwi_names <- filter(crop_names, str_detect(SHORT_DESC, "KIWI"))
kumquat_names <- filter(crop_names, str_detect(SHORT_DESC, "KUMQUAT"))
lime_names <- filter(crop_names, str_detect(SHORT_DESC, "LIME"))
mango_names <- filter(crop_names, str_detect(SHORT_DESC, "MANGO"))
olive_names <- filter(crop_names, str_detect(SHORT_DESC, "OLIVE"))
papaya_names <- filter(crop_names, str_detect(SHORT_DESC, "PAPAYA"))
persimmon_names <- filter(crop_names, str_detect(SHORT_DESC, "PERSIMMON"))
citrus_names <- filter(crop_names, str_detect(SHORT_DESC, "CITRUS, OTHER"))
nut_names <- filter(crop_names, str_detect(SHORT_DESC, "TREE NUTS, OTHER"))
stone_names <- filter(crop_names, str_detect(SHORT_DESC, "STONE"))

Notes

  • ACRES BEARING treated as harvested acres
    • This item starts in 2002 for most crops in Census; 2007 in Survey
  • ACRES BEARING & NON-BEARING treated as planted acres
    • This item goes back to 1997 for Census; not included in Survey
  • STONE FRUITS, OTHER does not appear to be a data item in the Census or Survey.
# add to list of data items for harvested acres
harv_key_CA <- rbind(harv_key,
                         c("CHESTNUTS - ACRES BEARING",
                           "Chestnuts",
                           "Orchards_and_grapes"),
                         c("CITRUS, OTHER - ACRES BEARING",
                           "OtherCitrusFruit",
                           "Orchards_and_grapes"),
                         c("DATES - ACRES BEARING",
                           "Dates",
                           "Orchards_and_grapes"),
                         c("FIGS - ACRES BEARING",
                           "Figs",
                           "Orchards_and_grapes"),
                         c("KIWIFRUIT - ACRES BEARING",
                           "Kiwifruit",
                           "Orchards_and_grapes"),
                         c("KUMQUATS - ACRES BEARING",
                           "Kumquats",
                           "Orchards_and_grapes"),
                         c("LIMES - ACRES BEARING",
                           "Limes",
                           "Orchards_and_grapes"),
                         c("MANGOES - ACRES BEARING",
                           "Mangoes",
                           "Orchards_and_grapes"),
                          c("TREE NUTS, OTHER - ACRES BEARING",
                           "OtherNuts",
                           "Orchards_and_grapes"),
                         c("OLIVES - ACRES BEARING",
                           "Olives",
                           "Orchards_and_grapes"),
                         c("PAPAYAS - ACRES BEARING",
                           "Papayas",
                           "Orchards_and_grapes"),
                         c("PERSIMMONS - ACRES BEARING",
                           "Persimmons",
                           "Orchards_and_grapes"))

# add to list of data items for planted acres
plant_key_CA <- rbind(plant_key,
                         c("CHESTNUTS - ACRES BEARING & NON-BEARING",
                           "Chestnuts",
                           "Orchards_and_grapes"),
                         c("CITRUS, OTHER - ACRES BEARING & NON-BEARING",
                           "OtherCitrusFruit",
                           "Orchards_and_grapes"),
                         c("DATES - ACRES BEARING & NON-BEARING",
                           "Dates",
                           "Orchards_and_grapes"),
                         c("FIGS - ACRES BEARING & NON-BEARING",
                           "Figs",
                           "Orchards_and_grapes"),
                         c("KIWIFRUIT - ACRES BEARING & NON-BEARING",
                           "Kiwifruit",
                           "Orchards_and_grapes"),
                         c("KUMQUATS - ACRES BEARING & NON-BEARING",
                           "Kumquats",
                           "Orchards_and_grapes"),
                         c("LIMES - ACRES BEARING & NON-BEARING",
                           "Limes",
                           "Orchards_and_grapes"),
                         c("MANGOES - ACRES BEARING & NON-BEARING",
                           "Mangoes",
                           "Orchards_and_grapes"),
                          c("TREE NUTS, OTHER - ACRES BEARING & NON-BEARING",
                           "OtherNuts",
                           "Orchards_and_grapes"),
                         c("OLIVES - ACRES BEARING & NON-BEARING",
                           "Olives",
                           "Orchards_and_grapes"),
                         c("PAPAYAS - ACRES BEARING & NON-BEARING",
                           "Papayas",
                           "Orchards_and_grapes"),
                         c("PERSIMMONS - ACRES BEARING & NON-BEARING",
                           "Persimmons",
                           "Orchards_and_grapes"))

Vegetables and fruit

This category includes vegetables, melons, and berries. According to the metadata associated with the USGS dataset, in addition to those crops represented in the rest of the country, in California this category includes avocados, beets, blueberries; tame, brussels sprouts, bulb crops, chicory, cole crops, collards, cranberries, currants, daikon, eggplant, escarole or endive, ginger root, guavas, herbs, horseradish, kale, mustard greens, okra, other; non-citrus fruit, other; leafy vegetables, other; roots or tubers, other; vegetables, parsley, pineapples, radishes, rhubarb, sweet potatoes, and turnips.

# look for all data items with orchard crops or grapes in the short description
avocado_names <- filter(crop_names, str_detect(SHORT_DESC, "AVOCADO"))
beet_names <- filter(crop_names, str_detect(SHORT_DESC, "BEET"))
blueberry_names <- filter(crop_names, str_detect(SHORT_DESC, "BLUEBERR"))
brussel_names <- filter(crop_names, str_detect(SHORT_DESC, "BRUSSEL"))
bulb_names <- filter(crop_names, str_detect(SHORT_DESC, "BULB"))
chicory_names <- filter(crop_names, str_detect(SHORT_DESC, "CHICORY"))
cole_names <- filter(crop_names, str_detect(SHORT_DESC, "COLE"))
collard_names <- filter(crop_names, str_detect(SHORT_DESC, "COLLARD"))
cranberry_names <- filter(crop_names, str_detect(SHORT_DESC, "CRANBERR"))
currant_names <- filter(crop_names, str_detect(SHORT_DESC, "CURRANT"))
daikon_names <- filter(crop_names, str_detect(SHORT_DESC, "DAIKON"))
eggplant_names <- filter(crop_names, str_detect(SHORT_DESC, "EGGPLANT"))
escarole_names <- filter(crop_names, str_detect(SHORT_DESC, "ESCAROLE"))
endive_names <- filter(crop_names, str_detect(SHORT_DESC, "ENDIVE"))
ginger_names <- filter(crop_names, str_detect(SHORT_DESC, "GINGER"))
guava_names <- filter(crop_names, str_detect(SHORT_DESC, "GUAVA"))
herb_names <- filter(crop_names, str_detect(SHORT_DESC, "HERB"))
horseradish_names <- filter(crop_names, str_detect(SHORT_DESC, "HORSERADISH"))
kale_names <- filter(crop_names, str_detect(SHORT_DESC, "KALE"))
mustard_names <- filter(crop_names, str_detect(SHORT_DESC, "MUSTARD"))
okra_names <- filter(crop_names, str_detect(SHORT_DESC, "OKRA"))
non_citrus_names <- filter(crop_names, str_detect(SHORT_DESC, "NON-CITRUS"))
leafy_names <- filter(crop_names, str_detect(SHORT_DESC, "LEAFY"))
tuber_names <- filter(crop_names, str_detect(SHORT_DESC, "TUBER"))
vegetable <- filter(crop_names, str_detect(SHORT_DESC, "VEGETABLES, OTHER"))
parsley_names <- filter(crop_names, str_detect(SHORT_DESC, "PARSLEY"))
pineapple_names <- filter(crop_names, str_detect(SHORT_DESC, "PINEAPPLE"))
radish_names <- filter(crop_names, str_detect(SHORT_DESC, "RADISH"))
rhubarb_names <- filter(crop_names, str_detect(SHORT_DESC, "RHUBARB"))
sweet_potato <- filter(crop_names, str_detect(SHORT_DESC, "SWEET POTATO"))
turnip_names <- filter(crop_names, str_detect(SHORT_DESC, "TURNIP"))

Notes

  • For perennial crops (e.g. blueberry, cranberry) did not include ACRES PLANTED because it’s unclear what that would reflect
  • Note that avocado & guava are included here even thought they are tree crops; acres planted/harvested convention similar to what I did for other tree crops above.
  • Could not find data item corresponding to some of the crops listed in USGS metadata (other (vegetable) bulbs, other cole crops, other leafy vegetables)
  • For harvested acres, selected items based on categories used in the Census. Sometimes Census and Survey categories are different. The Census is more reliably available so I am using that.
  • Planted acres are only available in the Survey, so I used Survey categories for planted acres. I attempted to use the combination of Survey data items that most closely resemble the combination of Census data items for a given crop so that the summed acreage is as comparable as possible.
# add to list of data items for harvested acres
harv_key_CA <- rbind(harv_key_CA,
                         c("AVOCADOS - ACRES BEARING",
                           "Avocados",
                           "Vegetables_and_fruit"),
                  c("BEETS - ACRES HARVESTED",
                           "Beets",
                           "Vegetables_and_fruit"),
                  c("BLUEBERRIES, TAME - ACRES HARVESTED",
                           "BlueberriesTame",
                           "Vegetables_and_fruit"),
                  c("BRUSSELS SPROUTS - ACRES HARVESTED",
                           "BrusselsSprouts",
                           "Vegetables_and_fruit"),
                  c("CHICORY - ACRES HARVESTED",
                           "Chicory",
                           "Vegetables_and_fruit"),
                  c("GREENS, COLLARD - ACRES HARVESTED",
                           "Collards",
                           "Vegetables_and_fruit"),
                  c("CRANBERRIES - ACRES HARVESTED",
                           "Cranberries",
                           "Vegetables_and_fruit"),
                  c("CURRANTS - ACRES HARVESTED",
                           "Currants",
                           "Vegetables_and_fruit"),
                  c("DAIKON - ACRES HARVESTED",
                           "BeansSnapBushPoleString",
                           "Vegetables_and_fruit"),
                   c("EGGPLANT - ACRES HARVESTED",
                           "Eggplant",
                           "Vegetables_and_fruit"),
                  c("ESCAROLE & ENDIVE - ACRES HARVESTED",
                           "EscaroleAndEndive",
                           "Vegetables_and_fruit"),
                  c("GINGER ROOT - ACRES HARVESTED",
                           "GingerRoot",
                           "Vegetables_and_fruit"),
                  c("GUAVAS - ACRES BEARING",
                           "Guavas",
                           "Vegetables_and_fruit"),
                  c("HERBS, DRY - ACRES HARVESTED",
                           "Herbs",
                           "Vegetables_and_fruit"),
                  c("HERBS, FRESH CUT - ACRES HARVESTED",
                           "Herbs",
                           "Vegetables_and_fruit"),
                  c("HORSERADISH - ACRES HARVESTED",
                           "Horseradish",
                           "Vegetables_and_fruit"),
                  c("GREENS, KALE - ACRES HARVESTED",
                           "Kale",
                           "Vegetables_and_fruit"),
                  c("GREENS, MUSTARD - ACRES HARVESTED",
                           "MustardGreens",
                           "Vegetables_and_fruit"),
                  c("NON-CITRUS, OTHER, (EXCL BERRIES) - ACRES BEARING",
                           "OtherNonCitrusFruit",
                           "Vegetables_and_fruit"),
                  c("OKRA - ACRES HARVESTED",
                           "Okra",
                           "Vegetables_and_fruit"),
                  c("PARSLEY - ACRES HARVESTED",
                           "Parsley",
                           "Vegetables_and_fruit"),
                  c("PINEAPPLE - ACRES HARVESTED",
                           "Pineapple",
                           "Vegetables_and_fruit"),
                  c("RADISHES - ACRES HARVESTED",
                           "Radishes",
                           "Vegetables_and_fruit"),
                  c("RHUBARB - ACRES HARVESTED",
                           "Rhubarb",
                           "Vegetables_and_fruit"),
                  c("SWEET POTATOES - ACRES HARVESTED",
                           "SweetPotatoes",
                           "Vegetables_and_fruit"),
                  c("TURNIPS - ACRES HARVESTED",
                           "Turnips",
                           "Vegetables_and_fruit"))

# add to list of data items for planted acres
plant_key_CA <- rbind(plant_key_CA,
                   c("AVOCADOS - ACRES BEARING & NON-BEARING",
                           "Avocados",
                           "Vegetables_and_fruit"),
                   c("BEETS, PROCESSING - ACRES PLANTED",
                           "Beets",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "BlueberriesTame",
                           "Vegetables_and_fruit"),
                   c("BRUSSELS SPROUTS - ACRES PLANTED",
                           "BrusselsSprouts",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Chicory",
                           "Vegetables_and_fruit"),
                   c("GREENS, COLLARD - ACRES PLANTED",
                           "Collards",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Cranberries",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Currants",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Daikon",
                           "Vegetables_and_fruit"),
                   c("EGGPLANT, FRESH MARKET - ACRES PLANTED",
                           "Eggplant",
                           "Vegetables_and_fruit"),
                   c("ESCAROLE & ENDIVE, FRESH MARKET - ACRES PLANTED",
                           "EscaroleAndEndive",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "GingerRoot",
                           "Vegetables_and_fruit"),
                   c("GUAVAS - ACRES BEARING & NON-BEARING",
                           "Guavas",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Herbs",
                           "Vegetables_and_fruit"),
                   c(NA,
                           "Horseradish",
                           "Vegetables_and_fruit"),
                   c("GREENS, KALE - ACRES PLANTED",
                           "Kale",
                           "Vegetables_and_fruit"),
                   c("GREENS, MUSTARD - ACRES PLANTED",
                           "MustardGreens",
                           "Vegetables_and_fruit"),
                  c("NON-CITRUS, OTHER, (EXCL BERRIES) - ACRES BEARING & NON-BEARING",
                           "OtherNonCitrusFruit",
                           "Vegetables_and_fruit"),
                  c("OKRA - ACRES PLANTED",
                           "Okra",
                           "Vegetables_and_fruit"),
                  c(NA,
                           "Parsley",
                           "Vegetables_and_fruit"),
                  c(NA,
                           "Pineapple",
                           "Vegetables_and_fruit"),
                  c("RADISHES - ACRES PLANTED",
                           "Radishes",
                           "Vegetables_and_fruit"),
                  c(NA,
                           "Rhubarb",
                           "Vegetables_and_fruit"),
                  c("SWEET POTATOES - ACRES PLANTED",
                           "SweetPotatoes",
                           "Vegetables_and_fruit"),
                  c(NA,
                           "Turnips",
                           "Vegetables_and_fruit"))

Other crops

This category includes assorted crops that do not fit into other categories. According to the metadata, in addition to those crops included in the national dataset, this category includes flax or flaxseed, grass seed crops, hops, jojoba, mustard seed, oats or rye for grain, safflower, sesame, taro, triticale, wild rice, and woodland crops.

# look for all data items with other crops in the short description
flax_names <- filter(crop_names, str_detect(SHORT_DESC, "FLAX"))
grass_names <- filter(crop_names, str_detect(SHORT_DESC, "GRASS"))
hops_names <- filter(crop_names, str_detect(SHORT_DESC, "HOPS"))
jojoba_names <- filter(crop_names, str_detect(SHORT_DESC, "JOJOBA"))
mustard_names <- filter(crop_names, str_detect(SHORT_DESC, "MUSTARD"))
oats_names <- filter(crop_names, str_detect(SHORT_DESC, "OATS"))
rye_names <- filter(crop_names, str_detect(SHORT_DESC, "RYE"))
safflower_names <- filter(crop_names, str_detect(SHORT_DESC, "SAFFLOWER"))
sesame_names <- filter(crop_names, str_detect(SHORT_DESC, "SESAME"))
taro_names <- filter(crop_names, str_detect(SHORT_DESC, "TARO"))
triticale_names <- filter(crop_names, str_detect(SHORT_DESC, "TRITICALE"))
wild_rice_names <- filter(crop_names, str_detect(SHORT_DESC, "WILD"))
tree_names <- filter(crop_names, str_detect(SHORT_DESC, "TREE"))

Notes

  • For grass seed, included only bermuda grass and sudan grass because those appeared to be the only species with acreage in California (based on search in QuickStats)
  • There is some discrepancy between the USGS metadata and Baker and Stone (2015), Appendix Table 1-2. The metadata lists a limited number of crops but there are a great many additional minor crops listed in the appendix table. I went by the metadata.
# add to list of data items for harvested acres
harv_key_CA <- rbind(harv_key_CA,
                         c("FLAXSEED - ACRES HARVESTED",
                           "Flaxseed",
                           "Other_crops"),
                         c("GRASSES, BERMUDA GRASS, SEED - ACRES HARVESTED",
                           "FieldAndGrassSeedCropsAll",
                           "Other_crops"),
                  c("GRASSES, SUDANGRASS, SEED - ACRES HARVESTED",
                           "FieldAndGrassSeedCropsAll",
                           "Other_crops"),
                        c("HOPS - ACRES HARVESTED",
                           "Hops",
                           "Other_crops"),
                  c("JOJOBA - ACRES HARVESTED",
                           "Jojoba",
                           "Other_crops"),
                  c("MUSTARD - ACRES HARVESTED",
                           "MustardSeed",
                           "Other_crops"),
                  c("OATS - ACRES HARVESTED",
                           "OatsForGrain",
                           "Other_crops"),
                  c("RYE - ACRES HARVESTED",
                           "RyeForGrain",
                           "Other_crops"),
                  c("SAFFLOWER - ACRES HARVESTED",
                           "Safflower",
                           "Other_crops"),
                  c("SUGARCANE, SUGAR - ACRES HARVESTED",
                           "Sugarcane",
                           "Other_crops"),
                  c("SUGARCANE, SEED - ACRES HARVESTED",
                           "Sugarcane",
                           "Other_crops"),
                  c("TARO - ACRES HARVESTED",
                           "Taro",
                           "Other_crops"),
                  c("TRITICALE - ACRES HARVESTED",
                           "Triticale",
                           "Other_crops"),
                  c("WILD RICE - ACRES HARVESTED",
                           "WildRice",
                           "Other_crops"),
                  c("CUT CHRISTMAS TREES - ACRES IN PRODUCTION",
                           "OtherCrops",
                           "Other_crops"))
                  
                   
# add to list of data items for planted acres
plant_key_CA <- rbind(plant_key_CA,
                         c("FLAXSEED - ACRES PLANTED",
                           "Flaxseed",
                           "Other_crops"),
                          c(NA,
                           "FieldAndGrassSeedCropsAll",
                           "Other_crops"),
                  c(NA,
                           "Hops",
                           "Other_crops"),
                          c(NA,
                           "Jojoba",
                           "Other_crops"),
                        c("MUSTARD - ACRES PLANTED",
                           "MustardSeed",
                           "Other_crops"),
                   c("OATS - ACRES PLANTED",
                           "OatsForGrain",
                           "Other_crops"),
                   c("RYE - ACRES PLANTED",
                           "RyeForGrain",
                           "Other_crops"),
                  c("SAFFLOWER - ACRES PLANTED",
                           "Safflower",
                           "Other_crops"),
                  c(NA,
                           "Taro",
                           "Other_crops"),
                  c(NA,
                           "Triticale",
                           "Other_crops"),
                  c(NA,
                           "WildRice",
                           "Other_crops"),
                  c(NA,
                           "OtherCrops",
                           "Other_crops"))

Pasture and hay

This category includes pasture and non-alfalfa hay crops.

Notes

  • Acreage categories for California appear to be similar to the rest of the country for this category, so this part of the table was left as-is

Summary

  • USGS and USDA crop names were matched based on information in Baker & Stone (2015), Appendix 1, Table 2, USGS metadata, and conversations with Nancy Baker, as well as USDA documentation
  • Harvested acreage:
    • Available every 5 years in the Census for all crops
    • Available more frequently from the Survey for major crops (corn, soy, wheat, cotton, rice, alfalfa)
  • Planted/total acreage:
    • Not attempted for perennial crops, except orchards (no data or too complicated)
    • For annual crops, planted acreage is only reported in the Survey
    • For orchard crops, total acreage is considered bearing + non-bearing acreage, which is reported in the Census. Harvested acreage (bearing) is only consistently available 2002 onward.
  • There are some cases for which Census and Survey data do not match exactly because different crop categories are used - tried to match them as well as possible
  • These keys should cover everything except the USGS category Pasture_and_hay
    • This category requires some items from the crop data (non-alfalfa hay) and other items from the economic/land data (pastureland, fallow)
  • The ‘summary’ key tries to match as well as possible methods in Baker & Stone (2015), as well as maximizing data coverage
    • Harvested acreage used, with priority to Census data
    • For orchard crops, used bearing + non-bearing to maximize coverage

Create summary key

summary_key_CA <- harv_key_CA %>%
  filter(!str_detect(SHORT_DESC,"BEARING")) %>%
  rbind(filter(plant_key_CA, str_detect(SHORT_DESC,"BEARING")))

# Add remaining data items from the 'economic' part of the Census for pastureland category
summary_key_CA <- rbind(summary_key_CA,
                         c("AG LAND, PASTURELAND - ACRES",
                           "Pasture",
                           "Pasture_and_hay"),
                         c("AG LAND, CROPLAND, (EXCL HARVESTED & PASTURED), CULTIVATED SUMMER FALLOW - ACRES",
                           "Fallow",
                           "Pasture_and_hay"))

Check keys

# make sure all data items were entered correctly by joining back to original data item names (only ones that shouldn't match are items from 'economic' dataset, not crops)
crop_names_short <- as.data.frame(unique(crop_names$SHORT_DESC))
crop_names_short$test <- "test"
names(crop_names_short) <- c("SHORT_DESC", "test")
harv_check <- left_join(harv_key_CA, crop_names_short, by="SHORT_DESC")
plant_check <- left_join(plant_key_CA, crop_names_short, by="SHORT_DESC")
summary_check <- left_join(summary_key_CA, crop_names_short, by="SHORT_DESC")

Export keys

write.csv(harv_key_CA, "../keys/crop_key_harv_CA.csv", row.names=FALSE)
write.csv(plant_key_CA, "../keys/crop_key_plant_CA.csv", row.names=FALSE)
write.csv(summary_key_CA, "../keys/crop_key_summary_CA.csv", row.names=FALSE)

Session information

sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] data.table_1.14.0 forcats_0.4.0     stringr_1.4.0    
 [4] dplyr_0.8.3       purrr_0.3.2       readr_1.3.1      
 [7] tidyr_1.1.0       tibble_2.1.3      ggplot2_3.2.0    
[10] tidyverse_1.2.1  

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.6       cellranger_1.1.0 pillar_1.4.2     compiler_3.6.1  
 [5] tools_3.6.1      digest_0.6.20    lubridate_1.7.4  jsonlite_1.6    
 [9] evaluate_0.14    lifecycle_0.2.0  nlme_3.1-140     gtable_0.3.0    
[13] lattice_0.20-38  pkgconfig_2.0.2  rlang_0.4.7      cli_1.1.0       
[17] rstudioapi_0.10  yaml_2.2.0       haven_2.1.1      xfun_0.8        
[21] withr_2.1.2      xml2_1.2.0       httr_1.4.2       knitr_1.23      
[25] hms_0.5.0        generics_0.0.2   vctrs_0.3.2      grid_3.6.1      
[29] tidyselect_1.1.0 glue_1.3.1       R6_2.4.0         readxl_1.3.1    
[33] rmarkdown_1.14   modelr_0.1.4     magrittr_1.5     backports_1.1.4 
[37] scales_1.0.0     htmltools_0.3.6  rvest_0.3.4      assertthat_0.2.1
[41] colorspace_1.4-1 stringi_1.4.3    lazyeval_0.2.2   munsell_0.5.0   
[45] broom_0.5.2      crayon_1.3.4

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