Scatter for all variables with percentages

BivariateAnalysis.R

@@ -77,14 +77,14 @@ scatterForCorr <- function(datos, variableX, variableY, season) {
   X <- paste(variableX, ".", season, sep = "")
   Y <- paste(variableY, ".", season, sep = "")
   medianX <- median(eval(parse(text = paste("datos$",X, sep = ""))))
-  maxY <- min(eval(parse(text = paste("datos$",Y, sep = ""))))
+  maxY <- max(eval(parse(text = paste("datos$",Y, sep = ""))))
   
   sp <- ggscatter(datos, x = X, y = Y,
                   add = "reg.line",  # Add regressin line
-                  add.params = list(color = "#B23AEE", fill = "lightgray"), # Customize reg. line
+                  add.params = list(color = "#40E0D0", fill = "lightgray"), # Customize reg. line
                   conf.int = TRUE # Add confidence interval
   )
-  sp + stat_cor(method = "pearson", label.x = medianX, label.y = maxY)
+  sp + stat_cor(method = "pearson", label.x = medianX, label.y = maxY-0.1)
 }
 # 500x406
 scatterForCorr(trainStudy, "passes","passes_completed", "1819")
@@ -92,24 +92,28 @@ scatterForCorr(trainStudy, "passes_completed", "passes_pct", "1819")
 scatterForCorr(trainStudy, "passes", "passes_pct", "1819")
 
 scatterForCorr(trainStudy, "pass_targets", "passes_received", "1819")
-scatterForCorr(trainStudyStand, "passes_received", "passes_received_pct", "1819")
-scatterForCorr(trainStudyStand, "pass_targets", "passes_received_pct", "1819")
+scatterForCorr(trainStudy, "passes_received", "passes_received_pct", "1819")
+scatterForCorr(trainStudy, "pass_targets", "passes_received_pct", "1819")
 
+#CDC673
 scatterForCorr(trainStudy, "shots_total", "shots_on_target", "1819")
-scatterForCorr(trainStudyStand, "shots_on_target", "shots_on_target_pct", "1819")
-scatterForCorr(trainStudyStand, "shots_total", "shots_on_target_pct", "1819")
+scatterForCorr(trainStudy, "shots_on_target", "shots_on_target_pct", "1819")
+scatterForCorr(trainStudy, "shots_total", "shots_on_target_pct", "1819")
 
+#00688B
 scatterForCorr(trainStudy, "aerials_lost", "aerials_won", "1819")
-scatterForCorr(trainStudyStand, "aerials_won", "aerials_won_pct", "1819")
-scatterForCorr(trainStudyStand, "aerials_lost", "aerials_won_pct", "1819")
+scatterForCorr(trainStudy, "aerials_won", "aerials_won_pct", "1819")
+scatterForCorr(trainStudy, "aerials_lost", "aerials_won_pct", "1819")
 
+#CD5555
 scatterForCorr(trainStudy, "dribbles", "dribbles_completed", "1819")
-scatterForCorr(trainStudyStand, "dribbles_completed", "dribbles_completed_pct", "1819")
-scatterForCorr(trainStudyStand, "dribbles", "dribbles_completed_pct", "1819")
+scatterForCorr(trainStudy, "dribbles_completed", "dribbles_completed_pct", "1819")
+scatterForCorr(trainStudy, "dribbles", "dribbles_completed_pct", "1819")
 
+#40E0D0
 scatterForCorr(trainStudy, "shots_on_target_against", "saves", "1819")
-scatterForCorr(trainStudyStand, "saves", "save_pct", "1819")
-scatterForCorr(trainStudyStand, "shots_on_target_against", "save_pct", "1819")
+scatterForCorr(trainStudy, "saves", "save_pct", "1819")
+scatterForCorr(trainStudy, "shots_on_target_against", "save_pct", "1819")
 
 # Add correlation coefficient
 sp + stat_cor(method = "pearson", label.x = , label.y = 30)