Jse 06jan2023

.rcsignore

@@ -0,0 +1 @@
+dataset_generator.R

.rscignore

@@ -1 +1,5 @@
+state_reservoirs_spatial_ny.Rds
+points_in_state_ny.Rds
+tab20_tract20_tract10_natl.tsv
+debug.R
 dataset_generator.R

app.R

@@ -1,3 +1,4 @@
+# See: https://github.rpi.edu/RensselaerIDEA/CohoesPVApp
 library(usmap)
 library(ggplot2)
 library(plotly)
@@ -40,12 +41,14 @@ transformed <- usmap_transform(transformed)
 
 # Helper functions =====
 # Load states data
-state_choices <- data.frame(state.name, state.abb)
-names(state_choices) <- c('State', 'Abbreviation')
-# Format state names
-state_choices$Adjusted_Name <- tolower(state_choices$State)
-state_choices$Adjusted_Name <- sub(' ', '_', state_choices$Adjusted_Name)
+# state_choices <- data.frame(state.name, state.abb)
+# names(state_choices) <- c('State', 'Abbreviation')
+# # Format state names
+# state_choices$Adjusted_Name <- tolower(state_choices$State)
+# state_choices$Adjusted_Name <- sub(' ', '_', state_choices$Adjusted_Name)
 
+state_choices <- readRDS("data/general/state_choices.Rds")
+
 # Linear regression model for determining zoom level
 # Data
 long_data <- c(0.972210, 0.100498, 3.206336, 3.723576, 0.410752, 7.002313, 0.628595, 0.111407,
@@ -190,6 +193,9 @@ ui <- fluidPage(
               "Select a congressional district (left) to highlight census tracts 
               in that district."
             ), 
+            tags$li(
+              "NEW (Jan 2023): Congressional district boundaries for the ", tags$b("118th Congress")," are shown."
+            ), 
           ),
           tags$br(),
           leafletOutput('reservoir_map', height = '700'),

data/cd118_shapes/congress.prj

@@ -0,0 +1 @@
+GEOGCS["WGS84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["degree",0.017453292519943295]]