如何获得除一栏以外的所有栏的均值? [英] How to get the means of all columns but one?

问题描述

我有如下数据:

> dplyr::tbl_df(sbp)

Country X1980       X1981       X1982       X1983       X1984       X1985
Albania 132.9270    133.0296    133.1459    133.1868    133.2048    133.2577        
Algeria 132.4093    132.1710    131.9649    131.7835    131.6161    131.4345        
Andorra 140.8585    140.1076    139.3727    138.6457    137.9525    137.3192    

我想获取所有国家/地区每年的平均值，并在数据框的末尾添加一个类似World的行，以便我可以以这种格式绘制平均值在多年内的变化.

I want to get mean of values for each year for all countries and add a row like World to the end of the dataframe, so that I can plot the change of the mean value through years, in that format.

我尝试使用gather()，这样我的数据只有三列，例如Country-year-value.但是我想不出一种方法来计算世界平均值.

I tried using gather() so that I have a data with three columns only, like Country-year-value. However I can not think of a way to calculate the mean for the world.

Country year    sbp
Albania X1980   132.9270        
Algeria X1980   132.4093        
Andorra X1980   140.8585    

可以请教吗?

推荐答案

以R为底的可能解决方案:

A possible solution with base R:

rbind(mydf, cbind(Country = 'World', as.data.frame.list(colMeans(mydf[,-1]))))

给出:

  Country    X1980    X1981    X1982    X1983    X1984    X1985
1 Albania 132.9270 133.0296 133.1459 133.1868 133.2048 133.2577
2 Algeria 132.4093 132.1710 131.9649 131.7835 131.6161 131.4345
3 Andorra 140.8585 140.1076 139.3727 138.6457 137.9525 137.3192
4   World 135.3983 135.1027 134.8278 134.5387 134.2578 134.0038

和tidyverse解决方案:

mydf %>% 
  gather(year, sbp, -1) %>% 
  bind_rows(., mydf %>% 
              gather(year, sbp, -1) %>%
              group_by(year) %>%
              summarise(Country = 'World', sbp = mean(sbp)))

格式较长的结果:

   Country  year      sbp
1  Albania X1980 132.9270
2  Algeria X1980 132.4093
3  Andorra X1980 140.8585
4  Albania X1981 133.0296
5  Algeria X1981 132.1710
6  Andorra X1981 140.1076
7  Albania X1982 133.1459
8  Algeria X1982 131.9649
9  Andorra X1982 139.3727
10 Albania X1983 133.1868
11 Algeria X1983 131.7835
12 Andorra X1983 138.6457
13 Albania X1984 133.2048
14 Algeria X1984 131.6161
15 Andorra X1984 137.9525
16 Albania X1985 133.2577
17 Algeria X1985 131.4345
18 Andorra X1985 137.3192
19   World X1980 135.3983
20   World X1981 135.1027
21   World X1982 134.8278
22   World X1983 134.5387
23   World X1984 134.2578
24   World X1985 134.0038

---

使用的数据:

---

Used data:

mydf <- read.table(text="Country X1980       X1981       X1982       X1983       X1984       X1985
Albania 132.9270    133.0296    133.1459    133.1868    133.2048    133.2577        
Algeria 132.4093    132.1710    131.9649    131.7835    131.6161    131.4345        
Andorra 140.8585    140.1076    139.3727    138.6457    137.9525    137.3192", header=TRUE, stringsAsFactors=FALSE)

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