Fix dplyr::select() error when using .data

pvdmeulen · Nov 1, 2022 · cc1e2fa · cc1e2fa
1 parent b961407
commit cc1e2fa
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Showing 2 changed files with 25 additions and 25 deletions.
diff --git a/R/load_ots.R b/R/load_ots.R
@@ -288,11 +288,11 @@ load_ots <- function(month = NULL,
       dplyr::left_join(supp_lookup, by = "SuppressionIndex") %>%
       # Put data in an order that makes more sense:
       dplyr::select(
-        .data$MonthId,
-        .data$FlowTypeId,
-        .data$FlowTypeDescription,
-        .data$SuppressionIndex,
-        .data$SuppressionDesc,
+        dplyr::contains("MonthId"),
+        dplyr::contains("FlowTypeId"),
+        dplyr::contains("FlowTypeDescription"),
+        dplyr::contains("SuppressionIndex"),
+        dplyr::contains("SuppressionDesc"),
         dplyr::contains("Hs2"),
         dplyr::contains("Hs4"),
         dplyr::contains("Hs6"),
@@ -305,17 +305,17 @@ load_ots <- function(month = NULL,
         dplyr::contains("Area2"),
         dplyr::contains("Area3"),
         dplyr::contains("Area5a"),
-        .data$CountryId,
-        .data$CountryCodeNumeric,
-        .data$CountryCodeAlpha,
-        .data$CountryName,
-        .data$PortId,
-        .data$PortCodeNumeric,
-        .data$PortCodeAlpha,
-        .data$PortName,
-        .data$Value,
-        .data$NetMass,
-        .data$SuppUnit
+        dplyr::contains("CountryId"),
+        dplyr::contains("CountryCodeNumeric"),
+        dplyr::contains("CountryCodeAlpha"),
+        dplyr::contains("CountryName"),
+        dplyr::contains("PortId"),
+        dplyr::contains("PortCodeNumeric"),
+        dplyr::contains("PortCodeAlpha"),
+        dplyr::contains("PortName"),
+        dplyr::contains("Value"),
+        dplyr::contains("NetMass"),
+        dplyr::contains("SuppUnit")
       )
 
     ots_data <- if(output == "df") {

diff --git a/R/load_rts.R b/R/load_rts.R
@@ -225,22 +225,22 @@ load_rts <- function(month = NULL,
       dplyr::left_join(ukcountry_lookup, by = "GovRegionId") %>%
       # Put data in an order that makes more sense:
       dplyr::select(
-        .data$MonthId,
-        .data$FlowTypeId,
-        .data$FlowTypeDescription,
+        dplyr::contains("MonthId"),
+        dplyr::contains("FlowTypeId"),
+        dplyr::contains("FlowTypeDescription"),
         dplyr::contains("Sitc1"),
         dplyr::contains("Sitc2"),
         dplyr::contains("GovRegion"),
         dplyr::contains("Area1"),
         dplyr::contains("Area2"),
         dplyr::contains("Area3"),
         dplyr::contains("Area5a"),
-        .data$CountryId,
-        .data$CountryCodeNumeric,
-        .data$CountryCodeAlpha,
-        .data$CountryName,
-        .data$Value,
-        .data$NetMass
+        dplyr::contains("CountryId"),
+        dplyr::contains("CountryCodeNumeric"),
+        dplyr::contains("CountryCodeAlpha"),
+        dplyr::contains("CountryName"),
+        dplyr::contains("Value"),
+        dplyr::contains("NetMass")
       )
 
     rts_data <- if(output == "df") {