Merge pull request #1296 from cmu-delphi/combine-filter

Combine `summarize_*` filter in surveys aggregation

Author: krivard

facebook/delphiFacebook/R/aggregate.R

@@ -181,7 +181,10 @@ summarize_indicators_day <- function(day_df, indicators, target_day, geo_level,
 
       # Copy only columns we're using.
       select_cols <- c(metric, var_weight, "weight_in_location")
-      ind_df <- sub_df[, select_cols, with=FALSE][!is.na(sub_df[[var_weight]]) & !is.na(sub_df[[metric]]), ]
+      # This filter uses `x[, cols, with=FALSE]` rather than the newer
+      # recommended `x[, ..cols]` format to take advantage of better
+      # performance. Switch to using `..` if `with` is deprecated in the future.
+      ind_df <- sub_df[!is.na(sub_df[[var_weight]]) & !is.na(sub_df[[metric]]), select_cols, with=FALSE]
 
       if (nrow(ind_df) > 0)
       {

facebook/delphiFacebook/R/contingency_aggregate.R

@@ -336,7 +336,10 @@ summarize_aggregations_group <- function(group_df, aggregations, target_group, g
 
     # Copy only columns we're using.
     select_cols <- c(metric, var_weight, "weight_in_location")
-    agg_df <- group_df[, select_cols, with=FALSE][!is.na(eval(as.name(metric))), ]
+    # This filter uses `x[, cols, with=FALSE]` rather than the newer recommended
+    # `x[, ..cols]` format to take advantage of better performance. Switch to
+    # using `..` if `with` is deprecated in the future.
+    agg_df <- group_df[!is.na(eval(as.name(metric))), select_cols, with=FALSE]
 
     if (nrow(agg_df) > 0) {
       s_mix_coef <- params$s_mix_coef