App.js

@@ -44,14 +44,6 @@ const styles = StyleSheet.create({
   },
   scrollView:{
 	  marginHorizontal: 20
-  },
-  data: {
-	  color: "white",
-	  fontSize: 20
-  },
-  graph: {
-	  borderColor: "blue",
-	  height: 200
   }
 });
 
@@ -166,4 +158,4 @@ setNews = () => this.setState({ current: states.newsView })
 }
 
 
-export default App
+export default App

R.R

@@ -1,52 +0,0 @@
-library(tidycensus)
-library(tidyverse)
-
-tableYear = 2020
-
-#log on with API
-census_api_key("7a853acf81fd5758228680556ac831138c40b83e")
-
-#load variables
-pueblos = 78
-variables = load_variables(2020,"acs5/profile")
-codes = variables$name
-label0 = variables$label
-
-#view variables
-#varTable = table(variables$concept)
-#write.table(varTable, file = "cat.txt", sep = ",", quote = FALSE, row.names = F)
-
-#pull all tables with every variable
-  
-test = get_acs(geography = "county",
-               state = "PR",
-               year = tableYear,
-               variables = codes)
-
-#add label column
-#create empty vector 
-labelCol = c()
-
-#amount of GEOIDS
-for (x in 1:pueblos){
-  labelCol = c(labelCol, label0)
-}
-
-#combine test and cols
-test["label"] = labelCol
-
-#rearrange cols
-test = test[c("NAME","label","variable","estimate","moe","GEOID")]
-
-GEOIDS = table(test$GEOID)
-
-#omit NA rows
-noNA = na.omit(test)
-
-DP02table = noNA %>% filter(startsWith(variable,"DP02"))
-
-DP03table = noNA %>% filter(startsWith(variable,"DP03"))
-
-DP04table = noNA %>% filter(startsWith(variable,"DP04"))
-
-DP05table = noNA %>% filter(startsWith(variable,"DP05"))

fetchTables.py

@@ -1,66 +0,0 @@
-import pandas as pd
-import rpy2.robjects as robjects
-
-#hellooo
-
-robjects.r('''
-        library(tidycensus)
-library(tidyverse)
-
-tableYear = 2020
-
-#log on with API
-census_api_key("7a853acf81fd5758228680556ac831138c40b83e")
-
-#load variables
-pueblos = 78
-variables = load_variables(2020,"acs5/profile")
-codes = variables$name
-label0 = variables$label
-
-#view variables
-#varTable = table(variables$concept)
-#write.table(varTable, file = "cat.txt", sep = ",", quote = FALSE, row.names = F)
-
-#pull all tables with every variable
-  
-test = get_acs(geography = "county",
-               state = "PR",
-               year = tableYear,
-               variables = codes)
-
-#add label column
-#create empty vector 
-labelCol = c()
-
-#amount of GEOIDS
-for (x in 1:pueblos){
-  labelCol = c(labelCol, label0)
-}
-
-#combine test and cols
-test["label"] = labelCol
-
-#rearrange cols
-test = test[c("NAME","label","variable","estimate","moe","GEOID")]
-
-GEOIDS = table(test$GEOID)
-
-#omit NA rows
-noNA = na.omit(test)
-
-DP02table = noNA %>% filter(startsWith(variable,"DP02"))
-
-DP03table = noNA %>% filter(startsWith(variable,"DP03"))
-
-DP04table = noNA %>% filter(startsWith(variable,"DP04"))
-
-DP05table = noNA %>% filter(startsWith(variable,"DP05"))
-        ''')
-        
-table02 = robjects.r('''DP02table''')
-table03 = robjects.r('''DP03table''')
-table04 = robjects.r('''DP04table''')
-table05 = robjects.r('''DP05table''')
-
-print(table02)