R圖分類和定量變量

Question

所以我有看起來像這樣的數據-

            Neighborhood
Overall.Cond Blmngtn Blueste BrDale BrkSide ClearCr CollgCr Crawfor Edwards Gilbert Greens
           1       0       0      0       0       0       0       0       1       0      0
           2       0       0      0       0       0       0       0       0       0      0
           3       0       0      0       0       1       0       2      12       0      0
           4       0       0      0       1       2       0       3       6       0      0
           5      14       1      9      15      15     163      20      53      87      3
           6       0       7      3      21       6      15      19      32       8      2
           7       0       0      1      33       6       9      16      22       3      0
           8       0       0      0       7       3       5       8       7       1      0
           9       0       0      0       1       0       0       5       1       0      0

我想為每個鄰域生成一個頻率直方圖-因此對於Blmngtn，我想要一個直方圖來顯示所有條件的分布。

為此，我將上面的內容放在了一個數據框中

        Overall.Cond Neighborhood Freq
1              1      Blmngtn    0
2              2      Blmngtn    0
3              3      Blmngtn    0
4              4      Blmngtn    0
5              5      Blmngtn   14
6              6      Blmngtn    0
7              7      Blmngtn    0

如何為每個鄰域生成直方圖（使用兩種數據格式）？

Answer 1

# Your data
df <- read.table(text="Overall.Cond Blmngtn Blueste BrDale BrkSide ClearCr  
CollgCr         Crawfor Edwards Gilbert Greens
       1       0       0      0       0       0       0       0       1       0      0
       2       0       0      0       0       0       0       0       0       0      0
       3       0       0      0       0       1       0       2      12       0      0
       4       0       0      0       1       2       0       3       6       0      0
       5      14       1      9      15      15     163      20      53      87      3
       6       0       7      3      21       6      15      19      32       8      2
       7       0       0      1      33       6       9      16      22       3      0
       8       0       0      0       7       3       5       8       7       1      0
       9       0       0      0       1       0       0       5       1       0      0",    
header=T)


names(df) <- tolower(names(df))

# Get frequency for each neighbourhood
# I am assuming that overall.cond is the outcome and the neighbourhood frequencies
# indicate how many times these are observed
# i.e. for Blmngtn you want a histogram of c(5,5,5,5,5,5,5,5,5,5,5,5,5,5) [ie. 5, 14 times]
l <- lapply(df[,2:11] , function(i) rep(df$overall.cond , i))

# Plot histograms (the first nine neighbourhoods)
par(mfrow=c(3,3))
  for(i in 1:9) {
      hist(l[[i]] , main = names(l[i]))
   }

# Plot barplots
par(mfrow=c(3,3))
for(i in 1:9) {
  barplot(table(l[[i]]) , main = names(l[i]))
  }