R ggplot //在X軸上的多個分組

Question

我正試圖在Excel中將圖表1實現爲Shiny。到目前爲止，我得到了結果圖2的代碼。

ggplot(filteredData(), aes(x=interaction(month, year), y=sum)) 
+ geom_bar(stat="identity") + facet_grid(. ~ X) + theme(legend.position="none") 

我想組個月，像今年在Excel的例子，這樣的帽子你的傳說和第一排（「1」，「2」，...），在只有一個月計數器第二年（「2016」，「2017」，...）。月數可能會有所不同。

數據集的樣子：

X year month sum 
10 2016 1  450 
10 2016 2  670 
... ... ... ... 
10 2017 1  200 
11 2016 1  460 

Answer 1

我稍微改變了數據集，這是我給你的規格最接近：

df <- read.table(text = "X year month sum 
10 2016 1  450 
10 2016 2  670 
10 2017 1  200 
11 2016 1  460 
11 2017 2  500", header = T) 

# Notice the variable type for month and year 
df$month <- as.factor(df$month) 
df$year <- as.factor(df$year) 
df$X <- as.factor(df$X) 

ggplot(df, aes(x = month, y = sum)) + geom_bar(stat = "identity") + 
    facet_grid(.~X + year, 
      switch = "x", # Moves the labels from the top to the bottom 
      labeller = label_both # Adds the labels to the year and X variables 
      ) + 
    xlab("") # Removes the month label 

結果：

或者如果你想刪除未使用的級別：

ggplot(df, aes(x = month, y = sum)) + geom_bar(stat = "identity") + 
    facet_grid(.~X + year, 
      switch = "x", # Moves the labels from the top to the bottom 
      labeller = label_both, # Adds the labels to the year and X variables 
      scales = "free_x") + 
    xlab("") # Removes the month legend 

Answer 2

你可以得到一個稍微複雜一點，用cowplot的情節融合在一起。您可以使用lapply來自動執行此操作，以循環使用您的唯一值，儘管這對於兩個組來說可能是過度的。

library(ggplot2) 
library(cowplot) 
library(dplyr) 

# Return to default theme, as cowplot sets its own 
theme_set(theme_gray()) 

# Save y limits to get same scale 
myYlims <- c(0, ceiling(max(df$sum)/100)*100) 


# Generate each plot 
x10 <- 
    ggplot(df %>% 
      filter(X == 10) 
     , aes(x = month, y = sum)) + geom_bar(stat = "identity") + 
    facet_grid(~ year, 
      switch = "x") + 
    panel_border() + 
    coord_cartesian(ylim = myYlims) + 
    xlab("X = 10") 


x11 <- 
    ggplot(df %>% 
      filter(X == 11) 
     , aes(x = month, y = sum)) + geom_bar(stat = "identity") + 
    facet_grid(~ year, 
      switch = "x") + 
    panel_border() + 
    coord_cartesian(ylim = myYlims) + 
    xlab("X = 11") 


# Put the plots together 
plot_grid(x10 
      , x11 + 
      theme(axis.title.y = element_blank() 
        , axis.text.y = element_blank() 
        , axis.ticks.y = element_blank()) 
      , rel_widths = c(1.1,1) 
     ) 

下面是自動執行此，包括更復雜的數據來證明的自動化的方法。請注意，您將需要與rel_widths選擇你的輸出和寬高比發揮，使它看起來體面：

df <- 
    data.frame(
    X = rep(1:6, each = 9) 
    , year = rep(rep(2016:2018, each = 3),3) 
    , month = rep(1:3, 6) 
    , sum = rnorm(9*6, 700, 100) 
) 


# Notice the variable type for month and year 
df$month <- as.factor(df$month) 
df$year <- as.factor(df$year) 
df$X <- as.factor(df$X) 


# Save y limits to get same scale 
myYlims <- c(0, ceiling(max(df$sum)/100)*100) 


# Generate each plot 
eachPlot <- lapply(levels(df$X), function(thisX){ 
    ggplot(df %>% 
      filter(X == thisX) 
     , aes(x = month, y = sum)) + 
    geom_bar(stat = "identity") + 
    facet_grid(~ year, 
       switch = "x") + 
    panel_border() + 
    coord_cartesian(ylim = myYlims) + 
    xlab(paste("X =", thisX)) 
}) 


# Remove axes from all but the first 
eachPlot[-1] <- lapply(eachPlot[-1], function(x){ 
    x + 
    theme(axis.title.y = element_blank() 
      , axis.text.y = element_blank() 
      , axis.ticks.y = element_blank() 
    ) 
}) 

# Put the plots together 
plot_grid(plotlist = eachPlot 
      , rel_widths = c(1.4, rep(1, length(eachPlot)-1)) 
      , nrow = 1 
)