update file to current version

DataINCITE · Sep 16, 2021 · f0611ce · f0611ce
1 parent 444f802
commit f0611ce
Showing 1 changed file with 18 additions and 9 deletions.
diff --git a/read_wapData.R b/read_wapData.R
@@ -6,7 +6,7 @@
 ################################################################################################################
 #load the packages if they are not already loaded
 packages <- c("shiny", "shinydashboard", "shinyjs", "ggplot2", "shinyWidgets", "tidyverse",  "tidyr",
-               "lubridate", "plyr", "scales", "zoo", "ggalt", "leaflet", "plotly", "wesanderson", "reactable")
+              "lubridate", "plyr", "scales", "zoo", "ggalt", "leaflet", "plotly", "wesanderson", "reactable")
 new.packages <- packages[!(packages %in% installed.packages()[,"Package"])]
 if (length(new.packages) > 0) {
   install.packages(new.packages)
@@ -49,6 +49,9 @@ rpi_wap_stats <- readRDS("../COVID_RPI_WiFi_Data/rpi_wifi_semester_day_summary.r
 #buildinginfo: Building, latitude, longitude, buildingType, abbrev
 #buildinginfo <- readRDS("../COVID_RPI_WiFi_Data/buildinginfo.rds")
 
+#user_prediction: Building, weekday, Hour, users, Mean_Usercount, latitude, longitude, buildingType
+user_predictions <- readRDS("../COVID_RPI_WiFi_Data/rpi_user_predictions.rds")
+
 ################################################################################################################
 ###CLEANING DATA
 ################################################################################################################
@@ -78,6 +81,13 @@ hits_per_wap_semester_by_building_max <- hits_per_wap_semester_by_building_max %
 hits_per_wap_semester_by_building_max <- hits_per_wap_semester_by_building_max %>% group_by(Building) %>% summarise_all(funs(max)) %>% ungroup() %>% select(Building, usercount_max)
 colnames(hits_per_wap_semester_by_building_max) <- c('Building', 'capacity')
 
+
+#user_predictions <- user_predictions %>% mutate(Hour = hour(as.POSIXct(time))) %>% select(Building, Median_Usercount, Mean_Usercount, Hour, latitude, longitude, buildingType, weekday)
+user_predictions <- user_predictions %>% group_by(Building, Hour, latitude, longitude, buildingType, weekday) %>% ungroup() 
+colnames(user_predictions) <- c('Building', 'weekday', 'Hour','users', 'Mean_Usercount' ,'lat','lng', 'BuildingType')
+user_predictions <- user_predictions %>% filter(BuildingType != "housing" & BuildingType != "greek") %>%
+  filter(!(Building %in% remove_list))
+
 ################################################################################################################
 ## DEFININING LISTS AND DATA FRAMES FOR CONVENIENCE
 ################################################################################################################
@@ -198,10 +208,10 @@ Other <- c("City Station South",
            "Old Bumstead Garage, behind Colonie Apts",
            # "SAE, 12 Myrtle Ave off Pawling Ave",
            "Rensselaer at Hartford")
-           # "Peoples Ave #1002",
-           # "Peoples Ave #1516",
-           # "Peoples Ave #901", 
-           # "Peoples Ave #907")
+# "Peoples Ave #1002",
+# "Peoples Ave #1516",
+# "Peoples Ave #901", 
+# "Peoples Ave #907")
 
 #Sleep: Housing
 # Sleep <- unique((rpi_wap_last7 %>% filter(BuildingType %in% c('housing')) %>% select(Building))$Building)
@@ -216,7 +226,7 @@ byCat_single <- list(
   "Other Off Campus" =  as.vector(unique((rpi_wap_last7 %>% filter(BuildingType=='otherOffCampus') %>% select(Building))$Building))
   # "Greek" = as.vector(unique((rpi_wap_last7 %>% filter(BuildingType=='greek') %>% select(Building))$Building)),
   # "Housing" = as.vector(unique((rpi_wap_last7 %>% filter(BuildingType=='housing') %>% select(Building))$Building))
-  )
+)
 
 byCat_multi <- list(
   "Nothing Selected" = as.vector('None'),
@@ -225,7 +235,7 @@ byCat_multi <- list(
   "Other Off Campus" =  as.vector(unique(rpi_wap_last7 %>% filter(BuildingType=='otherOffCampus') %>% select(Building))$Building)
   # "Greek" = as.vector(unique(rpi_wap_last7 %>% filter(BuildingType=='greek') %>% select(Building))$Building),
   # "Housing" = as.vector(unique(rpi_wap_last7 %>% filter(BuildingType=='housing') %>% select(Building))$Building)
-  )
+)
 
 byAct_single <- list(
   "Common Favorites" = as.vector(Favorites),
@@ -334,5 +344,4 @@ make_plot <- function(dat, time_now, building_select, hits_per_wap_semester_by_b
           legend.position="none")
 }
 
-icon <- awesomeIcons(icon = 'ios-close', iconColor="black", library='ion', markerColor="green")
-
+icon <- awesomeIcons(icon = 'ios-close', iconColor="black", library='ion', markerColor="green")