library(tidyverse)
# we shouldn't need to run this script again, for future updates start from the file output by this script and add new rows
# XW by Alexa and Zoe based on
mapc_xw1 <- readxl::read_xlsx("C:/Users/aderosa/OneDrive - Metropolitan Area Planning Council/Shared Documents - Data Services/_Datasets (Final datasets only!)/_Crosswalks/Archive/Neighborhood-Muni Crosswalk.xlsx")
# first and second sheet of zipcode csv from Conor
mapc_zip1 <- readxl::read_xlsx("C:/Users/aderosa/Downloads/Zipcode_Neighborhood_Suburb_Town_crosswalk.xlsx", sheet = 1) |>
mutate(
neighborhood = str_to_title(SuburbName),
muni = str_to_title(ExciseGarageCity),
state = "MA"
) |>
select(neighborhood, muni, state)
mapc_zip2 <- readxl::read_xlsx("C:/Users/aderosa/Downloads/Zipcode_Neighborhood_Suburb_Town_crosswalk.xlsx", sheet = 2) |>
janitor::clean_names() |>
filter(pc_type != "UNIQUE ORGANIZATION") |>
mutate(
neighborhood = str_to_title(pa_name),
muni = str_to_title(city_town),
state = "MA"
) |>
select(neighborhood, muni, state)
# Mass GIS published xw
massgis_xw <- readxl::read_xlsx("C:/Users/aderosa/Downloads/TOWNNAME_LOOKUP(1)/TOWNNAME_LOOKUP/TOWNNAME_LOOKUP.xlsx") |>
janitor::clean_names() |>
select(alt_name, town) |>
rename(neighborhood = alt_name, muni = town) |>
mutate(state = "MA") |>
distinct()
# Join all tables
updated_xw <- mapc_xw1 |>
select(-c(ma_muni)) |>
rbind(massgis_xw, mapc_zip1, mapc_zip2) |>
distinct() |>
mutate(
ma_muni = ifelse(state == "MA", TRUE, FALSE)
) |>
group_by(neighborhood) |>
#identifying and flagging duplicates
mutate(
dup_count = n(),
duplicate = ifelse(dup_count > 1, TRUE, FALSE)
) |>
select(-c(dup_count))
# write .csv to folder
write.csv(updated_xw, "data-raw/neighborhood_muni_xw.csv")
# write .csv to DS sharepoint
writexl::write_xlsx(updated_xw, "C:/Users/aderosa/OneDrive - Metropolitan Area Planning Council/Shared Documents - Data Services/_Datasets (Final datasets only!)/_Crosswalks/neighborhood_muni_xw.xlsx")
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