Chicago 311 flooding data

.gitignore

.Rhistory
*.dbf
*.prj
*.shp*
*.shx
*.geojson

fetch_311_data.R

#install.packages("tidyverse","RSocrata","sf")
library(tidyverse)
library(RSocrata)
library(sf)
library(tmap)
setwd('~/Documents/GitHub/chi311-flooding-gist')  # Cloned from: <https://gist.github.com/nmpeterson/ca3dd388ae36196864fcd516dfa8e7e4>
tmap_mode("plot")


# Specify which complaint types to fetch ----------------------------------

#View(read_csv('sr_types.csv'))
fetch_codes = c('AAF', 'AAE')  # "Water in basement" and "water on street" complaints
#fetch_codes = c('WBJ')  # "No water" complaints


# Get 311 data --------------------------------------------------------------------------------

# Get complaints from Chicago data portal using Socrata API.
# Source/metadata: <https://data.cityofchicago.org/Service-Requests/311-Service-Requests/v6vf-nfxy>
API_URL <- "https://data.cityofchicago.org/resource/v6vf-nfxy.json"
API_FILTER <- paste0(
  "sr_short_code in('", paste0(fetch_codes, collapse="','"), "')",
  " AND duplicate=false AND location IS NOT NULL"
)
chi311_raw <- read.socrata(paste0(API_URL, "?$where=", API_FILTER))


# Drop unnecessary fields ---------------------------------------------------------------------

chi311 <- as_tibble(chi311_raw) %>%
  select(
    starts_with('sr_'), created_date, street_address, zip_code, community_area, ward,
    latitude, longitude
  )

# Apply any filters ---------------------------------------------------------------------------

#chi311 <- chi311 %>%
#  filter(created_date >= "2020-05-01 00:00:00")  # Dataset begins on 7/1/2018


# Create points from coordinates --------------------------------------------------------------

chi311_geo <- st_as_sf(chi311, coords=c("longitude", "latitude"), crs=4326)
tm_shape(chi311_geo) + tm_dots(col="sr_type", alpha=0.35, palette="Dark2")


# Export to GeoJSON ---------------------------------------------------------------------------

out_name = paste0("chi311_", paste0(sort(fetch_codes), collapse="_"))
st_write(chi311_geo, paste0(out_name, ".geojson"), driver="geojson", append=FALSE)


# Export to shapefile -----------------------------------------------------

chi311_shp <- chi311_geo %>%
  rename(
    sr_code = sr_short_code,
    address = street_address,
    cca = community_area,
    sr_date = created_date
  ) %>%
  st_transform(st_crs(26971))  # IL State Plane East NAD83

st_write(chi311_shp, paste0(out_name, ".shp"), append=FALSE)

sr_types.csv