feat(ds): r2

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

ds/25-1/r2/2.R

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+df = read.csv("./zipIncome.txt", sep = "|")
+colnames(df) <- c("zipCode", "income")
+
+summary(df)
+mean(df$income)
+if (any(is.na(df[,2]))) {
+  na = which(is.na(df[,2]))
+  df = df[-na,]
+}
+
+mean(df$income)
+median(df$income, na.rm=TRUE)
+
+plot(x=df$income, y=df$zipCode, xlab="income", ylab="zipCode")
+df$incomelog = log10(df$income)
+hist(df$incomelog, breaks=80)
+print(min_incomelog <- log10(7e3))
+print(max_incomelog <- log10(2e5))
+print(avg_incomelog <- median(df$incomelog))
+
+df <- subset(df, 7e3 < df$income & df$income < 2e5)
+hist(df$incomelog, breaks=80)
+summary(df)
+
+boxplot(incomelog ~ zipCode, data=df, main="boxplot", xlab="zipCode", ylab="incomelog")
+
+library(ggplot2)
+
+ggplot(df, aes(x=zipCode, y=income, color=zipCode)) +
+  geom_point(
+    position = position_jitter(width = 0.2),
+    alpha = 0.2,
+  ) +
+  geom_boxplot(
+    alpha = 0.5,
+    outlier.shape = NA,
+    width = 0.6,
+    fill = "white",
+    color = "black"
+  ) +
+  scale_y_log10(
+    breaks = c(1e4, 25e3, 5e4, 1e5, 2e5, 5e5)
+  ) +
+  labs(
+    title = "Распределение доходов по почтовым индексам",
+    subtitle = "Scatter plot jitter",
+  ) +
+  theme_minimal()
+  

ds/25-1/r2/r2.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX