Shiny intergration

.gitignore

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+
+# History files
+.Rhistory
+.Rapp.history
+
+# Session Data files
+.RData
+
+# Example code in package build process
+*-Ex.R
+
+# Output files from R CMD build
+/*.tar.gz
+
+# Output files from R CMD check
+/*.Rcheck/
+
+# RStudio files
+.Rproj.user/
+
+# produced vignettes
+vignettes/*.html
+vignettes/*.pdf
+
+# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
+.httr-oauth
+
+# knitr and R markdown default cache directories
+/*_cache/
+/cache/
+
+# Temporary files created by R markdown
+*.utf8.md
+*.knit.md
+
+*.Rproj
+.Rhistory
+.RData
+.Ruserdata
+.Rproj.user

CalgaryCrime.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX

Shiny-Intergration/LoadData.R

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+#Fix for rjava issue in linux
+#https://stackoverflow.com/questions/28462302/libjvm-so-cannot-open-shared-object-file-no-such-file-or-directory
+
+library(xlsx)
+library(dplyr)
+library(tidyr)
+library(readr)
+library(rgdal)
+
+f_dowle3 = function(DT) {
+
+  # or by number (slightly faster than by name) :
+  for (j in seq_len(ncol(DT)))
+    set(DT,which(is.na(DT[[j]])),j,0)
+}
+
+xlsx_dir <- "Shiny-Intergration/RawData"
+working_dir <- getwd()
+
+list_file_xls <-
+  list.files(
+    path = working_dir,
+    pattern = "xls$",
+    recursive = TRUE,
+    full.names = TRUE
+  )
+list_file_csv <-
+  list.files(
+    path = paste0(working_dir, '/', 'RawData'),
+    pattern = "csv$",
+    recursive = TRUE,
+    full.names = TRUE
+  )
+list.files(
+  path = paste0(working_dir, '/', 'RawData'),
+  pattern = "shp$",
+  recursive = TRUE,
+  full.names = TRUE
+)
+shapefiles <-
+  list.files(
+    path = paste0(working_dir, '/', 'RawData'),
+    pattern = "shp$",
+    recursive = TRUE,
+    full.names = TRUE
+  )
+
+
+#for now just grab the first item in the list
+#but this could be migrated to grab the latest
+
+#this is really slow with na.strings
+#https://cran.r-project.org/web/packages/XLConnect/vignettes/XLConnect.pdf
+#might be a valid replacement
+CalgaryCrime <-
+  read.xlsx(
+    file = list_file_xls[1],
+    sheetIndex = 2,
+    startRow = 2,
+    na.strings = c(""),
+    stringsAsFactors = FALSE
+  )
+colnames(CalgaryCrime)[1:2] <- c("Category", "Community")
+CalgaryCrime[is.na(CalgaryCrime)] <- 0
+
+#run a for loop across the columnsize to fix the names
+names <- colnames(CalgaryCrime)
+names <- names[3:length(names)]
+
+intialYear <- 2012
+j <- 1
+
+
+for (i in 1:length(names)) {
+  if (j < 10) {
+    names[i] <-  paste0('0', j, '/01/', intialYear)
+
+  } else{
+    names[i]  <-   paste0(j, '/01/', intialYear)
+  }
+
+  if (j == 12) {
+    intialYear <- intialYear + 1
+    j <- 1
+  } else{
+    j <- (j + 1)
+  }
+
+}
+
+tmpnames <- colnames(CalgaryCrime)
+tmpnames[3:ncol(CalgaryCrime)] <- names
+colnames(CalgaryCrime) <- tmpnames
+
+
+#Applying data minp based on the work of Marc Boulet & Calgary R User Group
+CalgaryCrime <-
+  select(CalgaryCrime,-71:-75) # remove unused columns
+CalgaryCrimeTidy <-
+  CalgaryCrime %>% gather(Date, Cases, 3:70) # move data columns into one column
+CalgaryCrimeTidy$Date <-
+  as.Date(CalgaryCrimeTidy$Date, format = "%m/%d/%Y") # convert Date column to date format
+
+CalgaryCensus <- read_csv(list_file_csv[1])
+CalgaryCensus$AvgPop <-
+  rowMeans(subset(CalgaryCensus, select = c(2:6))) # calc 5 yr pop average
+CalgaryData <-
+  left_join(CalgaryCrimeTidy, CalgaryCensus, by = "Community") # add pop data to crime data
+
+#map to a  data.table and clean up
+CalgaryData <- data.table(CalgaryData)
+CalgaryData <- CalgaryData[Category != "0" | Community != "0"]
+# remove na's
+f_dowle3(CalgaryData)
+
+
+CatTotal <-   CalgaryData %>%
+  group_by(Category) %>%
+  summarise(TotalByCategory = sum(Cases)) %>%
+  arrange(desc(TotalByCategory))
+
+CatTotal <- data.table(CatTotal)
+
+CasesTotal <-   CalgaryData %>%
+  group_by(Community) %>%
+  summarise(TotalByCommunity = sum(Cases)) %>%
+  arrange(desc(TotalByCommunity))
+
+CasesTotal <- data.table(CasesTotal)
+
+
+boundries <-
+  readOGR(shapefiles[1],
+          layer = 'geo_export_48183217-cea2-47fe-bb74-c513d0cfd1fe',
+          GDAL1_integer64_policy = TRUE)
+
+community <- append(c(""), unique(CalgaryData$Community))
+crimeTypes <-  append(c("") , unique(CalgaryData$Category))
+dateRange <- append(c("") , unique(as.character(CalgaryData[,Date])))
+
+
+
+
+#clean up
+remove(list = c("i", "j", "intialYear", "names", "tmpnames"))
+
+
+