R中的数据汇总

Question

我相信这真的很容易，但作为一个R新手，我正在撕扯我的头发。

我有一个数据框架：

df <- data.frame("Factor_1" = c(1,2,1,1,2,1,1,2,1,2,1,2),
                 "Factor_2" = c("M", "F", "M", "F","M", "F","M", "F","M", "F","M", "F"),
                 "Denominator" = c(1,1,1,1,1,1,1,1,1,1,1,1),
                 "Numerator" = c(0,0,1,0,0,0,1,0,0,0,1,1))

我想要创建一些图表：

(1) Sum(Denominator) - split by Factor_1
(2) Sum(Numerator)/Sum(Denominator) - split by Factor_1

(so Factor_1 appears on the horizontal axis)

(and then repeat for Factor_2)

理想情况下，(1)和(2)具有不同的垂直轴线和(1)作为列和(2)作为线。

看起来有点像附加的图片(来自Excel枢轴表/图表)：

枢轴图

Answer 1

不要把这个问题看作是Excel中的一个支点，而要把它看作是使用tidyverse的最佳机会！

让我们建立我们的环境：

library(tidyverse)   # This will load dplyr and tidyverse to make visualization easier!

df <- data.frame("Factor_1" = c(1,2,1,1,2,1,1,2,1,2,1,2),   
             "Factor_2" = c("M", "F", "M", "F","M", "F","M", "F","M", "F","M", "F"),   
             "Denominator" = c(1,1,1,1,1,1,1,1,1,1,1,1),   
             "Numerator" = c(0,0,1,0,0,0,1,0,0,0,1,1))   

首先，让我们使用Factor_1。首先，我们要得到每个Factor_1群的分子和分母和分子/分母比。我们需要告诉R，我们想要按Factor_1分组，然后我们可以使用dplyr包中的summarize()函数来完成大部分的繁重工作。

summaryFactor1 <- df %>%                     # Save as new object: summaryFactor1
group_by(Factor_1) %>%                       # Group data by Factor_1, and for each:
summarize(sum_num = sum(Numerator),          # sum Numerator
        sum_den = sum(Denominator)) %>%      # sum Denominator
mutate(ratio = sum_num/sum_den)              # and create new column for num/den

这将使我们：

summaryFactor1
#  A tibble: 2 x 4
  Factor_1 sum_num sum_den ratio
     <dbl>   <dbl>   <dbl> <dbl>
1        1       3       7 0.429
2        2       1       5 0.2  

为了再现您要寻找的图形，我们使用我们的summaryFactor1 tibble并使用ggplot：

summaryFactor1 %>%                        # Use our summary table
ggplot(aes(x = Factor_1)) +               # plot Factor_1 on x-axis, 
geom_col(aes(y = sum_den)) +              # sum_den as columns, 
geom_line(aes(y = ratio))                 # and ratio as a line

​

​

请注意，这里只有一个y轴，因此绘制该比率的直线很难解释。虽然您希望从Excel中共享的地块看起来更好，但是要小心对该比率的误解。

我们可以对Factor_2使用与上面相同的逻辑：

summaryFactor2 <- df %>%                     # Save as new object: summaryFactor1                    
group_by(Factor_2) %>%                       # Group data by Factor2, and for each:    
summarize(sum_num = sum(Numerator),          # sum Numerator
        sum_den = sum(Denominator)) %>%      # sum Denominator
mutate(ratio = sum_num/sum_den)              # and create new column for num/den

# Let's view the result
summaryFactor2
# A tibble: 2 x 4
 Factor_2 sum_num sum_den ratio
  <fct>      <dbl>   <dbl> <dbl>
1 F              1       6 0.167
2 M              3       6 0.5  

在我们继续之前，请注意，每个组的分母之和是相同的。当我们比较因子1组中的比率时，注意这两个组有一个不同的分母和，所以这是一个更容易的1:1比较。

因为在两组之间策划sum_den并不是很有见地.

summaryFactor2
ggplot(aes(x = Factor_2)) + 
geom_col(aes(y = sum_den)) 

​

​

相反，让我们画出这个比率：

summaryFactor2 %>% 
ggplot(aes(x = Factor_2)) + 
geom_col(aes(y = ratio)) 

​

​

Answer 2

library(tidyverse)

df <- data.frame("Factor_1" = c(1,2,1,1,2,1,1,2,1,2,1,2),
             "Factor_2" = c("M", "F", "M", "F","M", "F","M", "F","M", "F","M", "F"),
             "Denominator" = c(1,1,1,1,1,1,1,1,1,1,1,1),
             "Numerator" = c(0,0,1,0,0,0,1,0,0,0,1,1))




df %>% group_by(Factor_1) %>% summarize(sum_num=sum(Numerator),sum_dem=sum(Denominator)) %>% mutate(ratio=sum_num/sum_dem)

A tibble: 2 x 4
Factor_1 sum_num sum_dem ratio
   <dbl>   <dbl>   <dbl> <dbl>
       1       3       7 0.429
       2       1       5 0.2 

这个有用吗？