louvain_israel.R

library(tidyverse)
library(readxl)
library(sf)
library(igraph)
library(tidygraph)
library(mapview)
nat <- read_csv("C:/idos_shit/celular1819_v1/v_1/AvgDayHourlyTrips201819_1270_weekday_v1.csv")
# nat <- read_csv("C:/idos_shit/celular1819_v1/v_1/AvgDayHourlyTrips201819_1270_friday_v1.csv")
# nat <- read_csv("C:/idos_shit/celular1819_v1/v_1/AvgDayHourlyTrips201819_1270_saturday_v1.csv")
shp1 <- st_read("C:/idos_shit/celular1819_v1/v_1/Shape files/1270_02.09.2021.shp",options = "ENCODING=WINDOWS-1255")
clusv21 <- nat %>% 
  gather(hour,count,-fromZone,-ToZone) %>% 
  rename(from = fromZone,to = ToZone) %>% 
  # filter(hour == "h2") %>% 
  group_by(from,to) %>% 
  summarise(count = sum(count)) %>% 
  ungroup() %>% 
  as_tbl_graph(directed = F)

with_grps <- clusv21 %E>% 
  filter(count >= 0) %N>%
  mutate(grp = group_louvain(weights = count)) 
anal <- with_grps %E>% 
  as_tibble() %>% 
  left_join(with_grps %>% as_tibble() %>% mutate(rn = row_number()),by = c("from"="rn")) %>% 
  left_join(with_grps %>% as_tibble() %>% mutate(rn = row_number()),by = c("to"="rn")) %>% 
  group_by(grp.x,grp.y) %>% 
  summarise(count = sum(count)) %>% 
  mutate(perc = count/sum(count),
         same = grp.x==grp.y) %>% 
  filter(same)
  # ungroup() %>% 
  # group_by(same) %>% 
  # summarise(count = sum(count)) %>% 
  
with_grps %>% 
  as_tibble() %>% 
  group_by(grp) %>% 
  add_count() %>% 
  ungroup() %>% 
  filter(n>1) %>%
  left_join(shp1 %>%mutate(TAZ_1270 = as.character(TAZ_1270)) ,by = c("name" = "TAZ_1270")) %>% 
  left_join(anal,by = c("grp"="grp.x")) %>% 
  # filter(grp == 48) %>%
  st_sf() %>% 
  group_by(grp) %>% 
  # summarise(perc = mean(perc)) %>%
  mapview(zcol = "grp",col.regions = randomcoloR::randomColor(1000))

Raw data available here: https://data.gov.il/dataset/tripscelular_1819/resource/c2004caa-a9b2-4790-81e8-6b144ce227b8