In ColoradoDemography/ProfileDashboard: State Demography Office Community Profile Dashboard

knitr::opts_chunk$set(fig.pos = 'H')
# invalidate cache when the tufte version changes
memory.limit(size=100000)

library(tidyverse, quietly=TRUE)
library(scales, quietly=TRUE)
library(codemogAPI, quietly=TRUE)
library(codemogProfile, quietly=TRUE)
library(knitr, quietly=TRUE)
library(kableExtra, quietly=TRUE)
library(RPostgreSQL, quietly=TRUE)
library(rmarkdown)
library(tinytex)
library(VennDiagram)
library(gridExtra)
library(coProfileDashboard)

#text Functions
baseText<- function(place){
  outTest <- paste0("Information for ",place," is compiled by the State Demography Office and the U.S. Bureau of the Census (NEED TEXT)")
 return(outTest)
}

# Creating the conditional display vars
#Basic Stats
if("stats" %in% params$outChk) {
  outStats <- TRUE
} else {
  outStats <- FALSE
}

#Population Forecast
if("popf" %in% params$outChk) {
  outPopf <- TRUE
} else {
  outPopf <- FALSE
}

#Population Characteristics: Age
if("pop" %in% params$outChk) {
  outPop <- TRUE
} else {
  outPop <- FALSE
}

#Population Characteristics: Income, Education and Race
if("popc" %in% params$outChk) {
  outPopC <- TRUE
} else {
  outPopC <- FALSE
}

#Housing
if("housing" %in% params$outChk) {
  outHouse <- TRUE
} else {
  outHouse <- FALSE
}

#Commuting
if("comm" %in% params$outChk) {
  outComm <- TRUE
} else {
  outComm <- FALSE
}

#Employment by Industry
if("emplind" %in% params$outChk) {
  outEmply <- TRUE
} else {
  outEmply <- FALSE
}

#Employment and Demographic Forecast
if("emply" %in% params$outChk) {
  outEmplind <- TRUE
} else {
  outEmplind <- FALSE
}
oYr <- params$curYr
oACS <- params$curACS
placeName <- params$ctyName
fips5 <- params$fips
fips3 <- substr(params$fips,3,5)
fipsN <- as.numeric(fips3)

Demographic and Economic Profile for r placeName

r if(outStats) '## Basic Statistics'

\bminione

    if(outStats) {
      cat(baseText(placeName))

#`r colFmt(paste0(placeName," Demographic and Economic Profile"),"dolagreen")`
    } 

\emini \bminitwo

if(outStats){
   y <- cp_countymap(substr(fips5,3,5))
   print(y)
   }

\emini \FloatBarrier

if(outStats){
  x <-  statsTable1(cty=fips5, 
                             place="",
                             sYr=2010,
                             eYr= oYr,
                             ACS=oACS,
                             oType="latex")
   print(x)
   }

\newpage

r if(outPopf) '## Population Forecasts'

 #Population, Migration and Natural Increase
   if(outPopf){  
      # Population Change Table
      popTab <- popTable(cty=fips3,ctyname=placeName,sYr=1990,eYr=oYr,oType="latex")
      cat(popTab$text)
      print(popTab$table)
   }

      #County forecast
    if(outPopf) {
      popf1 <- county_timeseries(fips=fips3,endYear=oYr)
       popf2 <- popForecast(fips=fipsN, ctyname = placeName)
       popf3 <- cocPlot(fips=fipsN,ctyname=placeName,lYr=oYr)
       print(popf1$plot)
       print(popf2$plot)
       print(popf3$plot)
    }

\newpage

r if(outPop) '## Population by Age'

r if(outPop) "Age Text (NEED TEXT)"

 #Population, Migration and Natural Increase
   if(outPop){
      # Age Plot
      popa1 <- agePlotPRO(fips=fipsN, ctyname=placeName, yrs=2016)
      print(popa1$plot)

   }

 #Population, Migration and Natural Increase
   if(outPop){
      popa3 <- ageForecastPRO(fips=fipsN,stYr=2010,mYr=2015,eYr=2025)
      print(popa3$plot)
   }

 #Population, Migration and Natural Increase
    if(outPop){
      medAge <- medianAgeTab(fips=fips3, ACS=oACS, ctyname=placeName,oType ="latex")
      print(medAge)
    }

 #Population, Migration and Natural Increase
   if(outPop){
      # Age Plot
     popa4 <- migbyagePRO(fips=fipsN, ctyname = placeName)
      print(popa4$plot)
   }

\newpage

r if(outPopC) '## Population Characteristics: Income, Education and Race'

r if(outPopC) 'Population Characteristics: Income, Education and Race Text (NEED TEXT)'

 if(outPopC){
    # Population Chatacteristics 
       popc1 <- incomePRO(fips=fips3,ctyname=placeName, ACS=oACS)
             print(popc1$plot)
 }

   if(outPopC){
      popc2 <- educPRO(fips=fips3, ctyname=placeName, ACS=oACS)
      print(popc2$plot)
   }

\FloatBarrier

   if(outPopC){
     race1 <- raceTab1(fips=fips3,ctyname=placeName,ACS=oACS,oType="latex") 
      print(race1)
   }

   if(outPopC){      
       race2 <- raceTab2(fips=fips3,ctyname=placeName,ACS=oACS,oType="latex")
      print(race2)
       }

\newpage

r if(outHouse) '## Housing and Households'

r if(outHouse) 'Housing Text (NEED TEXT)'

 if(outHouse){
    # Housing
     poph1 <<- houseEstPRO(fips=fips3,ctyname=placeName,curYr=oYr)
     print(poph1$plot)
 }

 if(outHouse){
     hTab <- housePRO(fips=fips3, ctyname=placeName, ACS=oACS, oType="latex")
     print(hTab)
 }

 if(outHouse){
     OOTab <- OOHouse(fips=fips3,ctyname=placeName,ACS=oACS, oType="latex")
     print(OOTab)
 }

 if(outHouse){
     RTTab <- RTHouse(fips=fips3,ctyname=placeName,ACS=oACS, oType="latex")
     print(RTTab)
        }

\newpage r if(outComm) '## Commuting'

\bminione

   if(outComm){
     cat("Commuting Text (NEED TEXT)")
   }

\emini \bminitwo

 if(outComm){
    # Commuting 
      popt1 <<- GenerateVenn(fips=fips3,ctyname=placeName,oType="latex")
      grid.arrange(popt1$plot)
 }

\emini

\FloatBarrier

     if(outComm){
       print(popt1$workTab)
     }

    if(outComm){
      print(popt1$liveTab)
      }

 if(outComm){ 
      popt2 <<- jobMigration(fips=fips3,ctyname=placeName,maxyr = oYr)
      print(popt2$plot)
       }

\newpage r if(outEmply) '## Employment by Industry'

r if(outEmply) 'Employment by Industry text (NEED TEXT)'

 if(outEmply) {
       popei1 <<- coProfileDashboard::ms_jobs(fips=fips3,ctyname=placeName, maxyr = oYr)
       print(popei1$plot)
 }

 if(outEmply) {
       popei2 <<- jobsByIndustry(fips=fips3,ctyname=placeName, curyr = oYr)
       print(popei2$plot)
 }

 if(outEmply) {
       popei3 <<- baseIndustries(fips=fips3,ctyname=placeName, curyr = oYr, oType="latex")
       print(popei3$plot)
 }

 if(outEmply) {
       print(popei3$table)
 }

\newpage

r if(outEmplind) '## Employment and Demographic Forecast'

r if(outEmplind) 'Employment and Demographic Forecast text (NEED TEXT)'

 if(outEmplind) {
   #Employment and Demographic Forecast Materials
       popem1 <<- jobsPopForecast(fips=fips3,ctyname=placeName)
       print(popem1$plot)
 }

 if(outEmplind) {
      popem2 <<- weeklyWages(fips=fips3,ctyname=placeName)
      print(popem2$plot)
 }

 if(outEmplind) {
       popem3 <<- residentialLF(fips=fips3,ctyname=placeName)
       print(popem3$plot1)
 }

 if(outEmplind) {
       print(popem3$plot2)
 }

ColoradoDemography/ProfileDashboard documentation built on May 27, 2019, 1:08 a.m.