Add VT2-examples: all 6 chapters of 'Visualize This' (110 files) — data scraping, ETL, trends, categorical, multivariate, spatial, distribution analysis

VT2-examples/vt2-ch6-codedata-dir/make-heatmap-multivariate.R

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+
+#
+# Load data
+#
+
+players <- read.csv("data/nba-top50scorers-2022-23.csv")
+head(players)
+
+play20 <- players[1:20,]
+
+#
+# Heatmap
+#
+
+# Four columns
+heatmap(as.matrix(play20[,c("MP", "FG", "FGpct", "PTS")]),
+        scale = "column",
+        Rowv = NA, Colv = NA)
+
+# Names
+heatmap(as.matrix(play20[,c("MP", "FG", "FGpct", "PTS")]),
+        scale = "column",
+        labRow = play20$Player,
+        Rowv = NA, Colv = NA)
+
+# Change order
+playrev <- play20[order(play20$PTS, decreasing = FALSE),]
+heatmap(as.matrix(playrev[,c("MP", "FG", "FGpct", "PTS")]),
+        scale = "column",
+        labRow = playrev$Player,
+        Rowv = NA, Colv = NA)
+
+
+# Color
+playrev <- play20[order(play20$PTS, decreasing = FALSE),]
+heatmap(as.matrix(playrev[,c("MP", "FG", "FGpct", "X2Ppct", "X3Ppct", "FTpct", "PTS")]),
+        scale = "column",
+        labRow = playrev$Player, 
+        cexCol = 1,
+        col = rev(hcl.colors(20, palette = "Blues 3")),
+        Rowv = NA, Colv = NA)
+