diff --git a/.gitignore b/.gitignore
index 4ff5907..0e958ce 100644
--- a/.gitignore
+++ b/.gitignore
@@ -8,6 +8,9 @@
 # Session Data files
 .RData
 
+# Environment with secret values
+.Renviron
+
 # Example code in package build process
 *-Ex.R
 
diff --git a/ipd.Rproj b/ipd.Rproj
new file mode 100644
index 0000000..8e3c2eb
--- /dev/null
+++ b/ipd.Rproj
@@ -0,0 +1,13 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
diff --git a/script-2017.R b/script-2017.R
index 4b38b83..f9cd70b 100755
--- a/script-2017.R
+++ b/script-2017.R
@@ -40,8 +40,8 @@ ipd_states <- c("NJ", "PA")
 ipd_counties <- c("34005", "34007", "34015", "34021",
                   "42017", "42029", "42045", "42091", "42101")
 # Census API Key
-# census_api_key("YOUR API KEY GOES HERE", install = TRUE)
-census_api_key("Insert API Key Here", overwrite = TRUE)
+census_api_key(Sys.getenv("CENSUS_API_KEY"), overwrite = TRUE)
+
 
 # Functions
 min <- function(i, ..., na.rm = TRUE) {
@@ -429,10 +429,17 @@ export_counts$Classification <- factor(export_counts$Classification,
                                                   "Well Above Average",
                                                   "NoData"))
 export_counts <- arrange(export_counts, Variable, Classification)
+
+# 2022-04-27 # replacing mutate_all with across, which supercedes it in dplyr
+# was causing issues because replace_na was trying to apply to "Variable" column, 
+# a character data type
+# across + where allows us to apply the function replace_na to just numeric columns
 export_counts <- export_counts %>%
   spread(Classification, Count) %>%
-  mutate_all(~(replace_na(., 0))) %>%
+  # mutate_all(~(replace_na(., 0))) %>%
+  mutate(across(where(is.numeric), ~replace_na(., 0))) %>%
   mutate(TOTAL = rowSums(.[2:7], na.rm = TRUE))
+
 # Bin break points
 breaks <- ipd_summary %>% select(ends_with("PctEst"))
 export_breaks <- round(mapply(st_dev_breaks, x = breaks, i = 5, na.rm = TRUE), digits = 3)
diff --git a/script-2018.R b/script-2018.R
index a3eb0a5..75673e1 100755
--- a/script-2018.R
+++ b/script-2018.R
@@ -7,8 +7,8 @@ library(plyr); library(here); library(sf); library(summarytools);
 library(tidycensus); library(tidyverse); library(tigris)
 
 # Census API Key
-# census_api_key("YOUR API KEY GOES HERE", install = TRUE)
-census_api_key("Insert API Key Here", overwrite = TRUE)
+census_api_key(Sys.getenv("CENSUS_API_KEY"), overwrite = TRUE)
+
 
 # Fields
 
@@ -520,9 +520,15 @@ export_counts$Classification <- factor(export_counts$Classification,
                                                   "Well Above Average",
                                                   "NoData"))
 export_counts <- arrange(export_counts, Variable, Classification)
+
+# 2022-04-27 # replacing mutate_all with across, which supercedes it in dplyr
+# was causing issues because replace_na was trying to apply to "Variable" column, 
+# a character data type
+# across + where allows us to apply the function replace_na to just numeric columns
 export_counts <- export_counts %>%
   spread(Classification, Count) %>%
-  mutate_all(~(replace_na(., 0))) %>%
+  # mutate_all(~(replace_na(., 0))) %>%
+  mutate(across(where(is.numeric), ~replace_na(., 0))) %>%
   mutate(TOTAL = rowSums(.[2:7], na.rm = TRUE))
 
 # Bin break points
diff --git a/script-2019-PhilaOnly.r b/script-2019-PhilaOnly.r
index e192f54..acfe64a 100644
--- a/script-2019-PhilaOnly.r
+++ b/script-2019-PhilaOnly.r
@@ -8,8 +8,7 @@ library(plyr); library(here); library(sf); library(summarytools);
 library(tidycensus); library(tidyverse); library(tigris); library(dplyr); library(descr)
 
 # Census API Key
-
-census_api_key("", overwrite = TRUE)
+census_api_key(Sys.getenv("CENSUS_API_KEY"), overwrite = TRUE)
 
 # Fields
 
@@ -529,9 +528,15 @@ export_counts$Classification <- factor(export_counts$Classification,
                                                   "Well Above Average",
                                                   "NoData"))
 export_counts <- arrange(export_counts, Variable, Classification)
+
+# 2022-04-27 # replacing mutate_all with across, which supercedes it in dplyr
+# was causing issues because replace_na was trying to apply to "Variable" column, 
+# a character data type
+# across + where allows us to apply the function replace_na to just numeric columns
 export_counts <- export_counts %>%
   spread(Classification, Count) %>%
-  mutate_all(~(replace_na(., 0))) %>%
+  # mutate_all(~(replace_na(., 0))) %>%
+  mutate(across(where(is.numeric), ~replace_na(., 0))) %>%
   mutate(TOTAL = rowSums(.[2:7], na.rm = TRUE))
 
 # Bin break points
diff --git a/script-2019.R b/script-2019.R
index 98956e9..325ed63 100644
--- a/script-2019.R
+++ b/script-2019.R
@@ -8,8 +8,7 @@ library(plyr); library(here); library(sf); library(summarytools);
 library(tidycensus); library(tidyverse); library(tigris); library(dplyr); library(descr)
 
 # Census API Key
-
-census_api_key("API_Key_Goes_Here", overwrite = TRUE)
+census_api_key(Sys.getenv("CENSUS_API_KEY"), overwrite = TRUE)
 
 # Fields
 
@@ -524,9 +523,15 @@ export_counts$Classification <- factor(export_counts$Classification,
                                                   "Well Above Average",
                                                   "NoData"))
 export_counts <- arrange(export_counts, Variable, Classification)
+
+# 2022-04-27 # replacing mutate_all with across, which supercedes it in dplyr
+# was causing issues because replace_na was trying to apply to "Variable" column, 
+# a character data type
+# across + where allows us to apply the function replace_na to just numeric columns
 export_counts <- export_counts %>%
   spread(Classification, Count) %>%
-  mutate_all(~(replace_na(., 0))) %>%
+  # mutate_all(~(replace_na(., 0))) %>%
+  mutate(across(where(is.numeric), ~replace_na(., 0))) %>%
   mutate(TOTAL = rowSums(.[2:7], na.rm = TRUE))
 
 # Bin break points
diff --git a/script-2020.R b/script-2020.R
index 927419c..3356a5d 100644
--- a/script-2020.R
+++ b/script-2020.R
@@ -8,8 +8,7 @@ library(plyr); library(here); library(sf); library(summarytools);
 library(tidycensus); library(tidyverse); library(tigris); library(dplyr); library(descr)
 
 # Census API Key
-
-census_api_key("insert_api_key_here", overwrite = TRUE)
+census_api_key(Sys.getenv("CENSUS_API_KEY"), overwrite = TRUE)
 
 # Fields
 
@@ -532,9 +531,15 @@ export_counts$Classification <- factor(export_counts$Classification,
                                                   "Well Above Average",
                                                   "NoData"))
 export_counts <- arrange(export_counts, Variable, Classification)
+
+# 2022-04-27 # replacing mutate_all with across, which supercedes it in dplyr
+# was causing issues because replace_na was trying to apply to "Variable" column, 
+# a character data type
+# across + where allows us to apply the function replace_na to just numeric columns
 export_counts <- export_counts %>%
   spread(Classification, Count) %>%
-  mutate_all(~(replace_na(., 0))) %>%
+  # mutate_all(~(replace_na(., 0))) %>%
+  mutate(across(where(is.numeric), ~replace_na(., 0))) %>%
   mutate(TOTAL = rowSums(.[2:7], na.rm = TRUE))
 
 # Bin break points