Measuring Ridership with Bus Stop Distances Map

cond <- c("OBJECTID_12", "Route", "Stop_ID", "Avg_POPDENS_CY", "Avg_AVGHHSZ_CY", "Avg_MEDAGE_CY", "Avg_MALES_CY", 
    "Avg_FEMALES_CY", "Avg_UNEMPRT_CY", "Avg_WHITE_CY",
    "Avg_BLACK_CY", "Avg_ASIAN_CY", "Avg_HISPPOP_CY",
    "Avg_MEDHINC_CY", "Weekday_Bo", "Weekday_Le", "Weekday_To", "Distance", "Avg_TOTPOP_CY")


 c1 <- c %>% 
  dplyr::select(.,cond) %>%
   cleanup.import()  ##cleans data and converts to integer when needed 

cn <- c1 %>%
  dplyr::rename(`ID`= OBJECTID_12,
             `Route` = Route,
             `Stop Number` = Stop_ID,
             `Population Density` = Avg_POPDENS_CY,
             `Household Size` = Avg_AVGHHSZ_CY,
             `Age` = Avg_MEDAGE_CY,
             `Male Population` = Avg_MALES_CY,
             `Female Population` = Avg_FEMALES_CY,
             `Unemployment Rate` = Avg_UNEMPRT_CY,
             `White Population` = Avg_WHITE_CY,
             `Black Population` = Avg_BLACK_CY,
             `Asian Population` = Avg_ASIAN_CY,
             `Hispanic Population` = Avg_HISPPOP_CY,
             `Median HH Income` = Avg_MEDHINC_CY,
             `Boardings` = Weekday_Bo,
             `Offsets` = Weekday_Le,
             `Total Riders` = Weekday_To,
             `Distance` = Distance,
             `Total Population` = Avg_TOTPOP_CY)
  
  cn <- cn %>%
    mutate(
      Black= (`Black Population` / `Total Population`* 100),
      Asian= (`Asian Population` / `Total Population`* 100),
      Hispanic= (`Hispanic Population` / `Total Population`* 100),
      White= (`White Population` / `Total Population`* 100),
      Female = (`Female Population` / `Total Population` * 100),
      `City Hall` = ifelse( `Stop Number` == 6115|`Stop Number`== 130|`Stop Number`== 17261|`Stop Number`== 5131, 1, 0)) 
               

exp_vars <- c("Population Density", "Household Size", "Age", "Female", 
     "Unemployment Rate", "White",
    "Black", "Asian", "Hispanic", "City Hall",
    "Median HH Income", "Boardings", "Distance")

mpd <- c("OBJECTID_12", "Weekday_Bo", "Route", "Latitude", "Longitude")



c1_16 <- cn %>%
  mutate(
    ID = ifelse(Route == 16, ID, NA)) %>%
    filter(!is.na(ID)
  )

c1_21 <- cn %>%
  mutate(
    ID = ifelse(Route == 21, ID, NA),
    Boardings = ifelse(Boardings == 0, 1, Boardings)) %>%
    filter(!is.na(ID)
  )

c2_21 <- c1 %>%
  mutate(
    ID = ifelse(Route == 21, OBJECTID_12, NA)) %>%
    filter(!is.na(OBJECTID_12)
  )
c2_16 <- c1 %>%
  mutate(
    ID = ifelse(Route == 16, OBJECTID_12, NA)) %>%
    filter(!is.na(OBJECTID_12)
  )

kable(head(c1_21 %>% dplyr::select(exp_vars), 10), 
      col.names = c("Population Density", "Household Size", "Median Age", "Male Population", 
                    "Female Population", "Unemployment Rate",
                    "White Population", "Black Population", "Asian Population",
              "Hispanic Population", "Median Household Income", "Ridership",
              "Distance")) %>% 
  kable_styling(bootstrap_options = "striped",position = "left") %>%
  scroll_box(width = "100%", height = "100%")

map1 <- tm_shape(dat_sf, unit = "mi", bbox = boundingBox) + 
  tm_dots(title.size = "Bus Stops", alpha = 0.5, size = "Weekday_Bo", col = "Weekday_Bo", title = "Ridership") +
  tm_shape(busroutes) +
  tm_lines(col = "#CE8F98", scale = .35)+
  tm_layout(main.title = "Bus Lines",
            asp = 0, legend.outside = TRUE, legend.outside.position = "bottom", 
            title.snap.to.legend = FALSE, title.position = c("center", "top"),
            outer.margins = c(0, 0, 0, 0),
            inner.margins = c(0, 0, 0, 0)) +
  tm_shape(boundingBox) +
  tm_borders() +
  tm_layout(main.title = "Route 21 and 16 Bus Routes",
            asp = 0, legend.outside = TRUE, legend.outside.position = "bottom", 
            title.snap.to.legend = FALSE, title.position = c("center", "top"),
            outer.margins = c(0, 0, 0, 0),
            inner.margins = c(0, 0, 0, 0))

map1