动态行添加

Question

我有一个如下数据框，我需要创建一个列总和。对于每一行，总和将来自行动月份。

Apr May Jun Jul Aug Sep Oct Nov Action On
4.0 2.0 3.0 2.0 1.5 1.0 0.5 4   July
3.0 4.0 1.0 7.0 2.0 3.0 1.0 2   August
3.0 3.0 1.0 0.5 0.5 1.0 1.0 6.0 September
1.0 1.0 0.5 0.3 0.3 0.5 0.5 2.0 October
0.5 1.0 0.4 0.1 0.1 0.3 0.3 3.0 July
0.4 3.0 0.0 0.2 0.2 0.1 0.1 9.0 September
1.3 5.0 0.3 0.4 0.4 0.2 0.2 7.0 November
2.2 7.0 0.6 1.0 0.6 0.4 0.4 1.2 July

请告诉我最好的代码。我创建了一个将月份转换为数字的列，并使用了一个 for 循环，如下所示：

for(rowidx in 1: nrow(conshead)) {
   startcol=conshead[rowidx,"b"]
   conshead[rowidx,"sum"]=sum(conshead[rowidx,startcol:8], na.rm = TRUE)
}

还是有这个错误

startcol:8 中的错误：NA/NaN 参数。

请分享更好的代码。

Answer 1

这是你的追求吗？

> m1 <- data.frame(Jul = c(1,4,6),
+                  Aug = c(3,5,9),
+                  ActionOn = c("July", "August", "July"))
> 
> m1
  Jul Aug ActionOn
1   1   3     July
2   4   5   August
3   6   9     July
> 
> m1$sumofinterest <- colSums(m1[,match(substr(m1$ActionOn, 1, 3), colnames(m1))])

> m1
  Jul Aug ActionOn sumofinterest
1   1   3     July            11
2   4   5   August            17
3   6   9     July            11

Answer 2

你也可以试试dplyr

library(tidyverse)

# reading your data
df <- read_table("Apr May Jun Jul Aug Sep Oct Nov Action On
4.0 2.0 3.0 2.0 1.5 1.0 0.5 4   July
3.0 4.0 1.0 7.0 2.0 3.0 1.0 2   August
3.0 3.0 1.0 0.5 0.5 1.0 1.0 6.0 September
1.0 1.0 0.5 0.3 0.3 0.5 0.5 2.0 October
0.5 1.0 0.4 0.1 0.1 0.3 0.3 3.0 July
0.4 3.0 0.0 0.2 0.2 0.1 0.1 9.0 September
1.3 5.0 0.3 0.4 0.4 0.2 0.2 7.0 November
2.2 7.0 0.6 1.0 0.6 0.4 0.4 1.2 July")

代码是：

df %>% 
  select_if(is.numeric) %>% 
  mutate(SUM=colSums(.)) %>% 
  bind_cols(df %>% select_if(is.character))

输出：

  # A tibble: 8 x 10
  #  Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   SUM `Action On`
  #  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>      
  # 1 4.00     2. 3.00  2.00  1.50  1.00  0.500  4.00 15.4  July       
  # 2 3.00     4. 1.00  7.00  2.00  3.00  1.00   2.00 26.0  August     
  # 3 3.00     3. 1.00  0.500 0.500 1.00  1.00   6.00  6.80 September  
  # 4 1.00     1. 0.500 0.300 0.300 0.500 0.500  2.00 11.5  October    
  # 5 0.500    1. 0.400 0.100 0.100 0.300 0.300  3.00  5.60 July       
  # 6 0.400    3. 0.    0.200 0.200 0.100 0.100  9.00  6.50 September  
  # 7 1.30     5. 0.300 0.400 0.400 0.200 0.200  7.00  4.00 November   
  # 8 2.20     7. 0.600 1.00  0.600 0.400 0.400  1.20 34.2  July     

按月分组：

df %>% 
  select_if(is.numeric) %>% 
  mutate(SUM=colSums(.)) %>% 
  bind_cols(df %>% select_if(is.character)) %>% 
  group_by(`Action On`) %>% 
  summarise(SUM_per_month=sum(SUM))

输出：

# A tibble: 5 x 2
#   `Action On` SUM_per_month
#   <chr>               <dbl>
# 1 August              26.0 
# 2 July                55.2 
# 3 November             4.00
# 4 October             11.5 
# 5 September           13.3