Question

我有一个数据框如下：

vdate=c("12-04-2015","13-04-2015","14-04-2015","15-04-2015","12-05-2015","13-05-2015","14-05-2015"
    ,"15-05-2015","12-06-2015","13-06-2015","14-06-2015","15-06-2015")
month=c(4,4,4,4,5,5,5,5,6,6,6,6)
col1=c(12,12.4,14.3,3,5.3,1.8,7.6,4.5,7.6,10.7,12,15.7)

df=data.frame(vdate,month,col1)

下面是包含基于某些计算的值的列：

pvar=c(8.4,2.4,12,14.4,2.3,3.5,7.8,5,16,5.4,18,18.4)

现在我想替换pvar值，如果它的值小于该特定月份的平均值。

For example,
for month 4,
Average value of pvar is 9.3 ((8.4+2.4+12+14.4)/4).

然后替换pvar中的所有值，该值小于第4个月的平均值（8.4＆amp; 2.4）。 Pvar值为9.3,9.3,12,14.4

我需要为pvar中的所有值执行此操作。

Answer 1

基础R解决方案是使用ave。请注意，我们首先需要将日期列转换为实际日期以提取月份（strsplit或正则表达式也可以这样做但我更喜欢将其设置为正确的日期），即

df$vdate <- as.POSIXct(df$vdate, format = '%d-%m-%Y')
with(df, ave(pvar, format(vdate, '%m'), FUN = function(i) replace(i, i < mean(i), mean(i))))
 #[1]  9.30  9.30 12.00 14.40  4.65  4.65  7.80  5.00 16.00 14.45 18.00 18.40

根据您的编辑，我将使用dplyr来解决它，因为它可能更具可读性。实际上我提出了两种方法。

首先：创建一个额外的分组变量，它将把你需要的所有月份改为同一组中的值并从那里替换，即

library(dplyr)

cbind(df, pvar) %>% 
 group_by(grp = cumsum(!month %in% c(4, 5))+1, month) %>% 
 mutate(pvar = replace(pvar, pvar < mean(pvar), mean(pvar))) %>% 
 ungroup() %>% 
 select(-grp)

第二：过滤所需的月份，进行计算。然后过滤掉你不需要的月份，再次创建pvar但不改变任何东西（绑定行所必需的）并绑定行，即

bind_rows(
  cbind(df, pvar) %>%
    filter(month %in% c(4, 5)) %>%
    group_by(month) %>%
    mutate(pvar = replace(pvar, pvar < mean(pvar), mean(pvar))),
  cbind(df, pvar) %>%
    filter(!month %in% c(4, 5))
)

以上两者都给出了

   vdate      month  col1  pvar
   <fct>      <dbl> <dbl> <dbl>
 1 12-04-2015    4. 12.0  12.0 
 2 13-04-2015    4. 12.4  12.4 
 3 14-04-2015    4. 14.3  14.3 
 4 15-04-2015    4.  3.00 10.4 
 5 12-05-2015    5.  5.30  5.30
 6 13-05-2015    5.  1.80  4.80
 7 14-05-2015    5.  7.60  7.60
 8 15-05-2015    5.  4.50  4.80
 9 12-06-2015    6.  7.60  7.60
10 13-06-2015    6. 10.7  10.7 
11 14-06-2015    6. 12.0  12.0 
12 15-06-2015    6. 15.7  15.7

Answer 2

基于dplyr的解决方案可以是：

  #Additional condition has been added to check if month != 6
  cbind(df, pvar) %>%
  group_by(month) %>%
  mutate(pvar = ifelse(pvar < mean(pvar) & month != 6, mean(pvar), pvar))  %>% 
  as.data.frame()

# vdate month col1  pvar
# 1  12-04-2015     4 12.0  9.30
# 2  13-04-2015     4 12.4  9.30
# 3  14-04-2015     4 14.3 12.00
# 4  15-04-2015     4  3.0 14.40
# 5  12-05-2015     5  5.3  4.65
# 6  13-05-2015     5  1.8  4.65
# 7  14-05-2015     5  7.6  7.80
# 8  15-05-2015     5  4.5  5.00
# 9  12-06-2015     6  7.6 16.00
# 10 13-06-2015     6 10.7  5.40
# 11 14-06-2015     6 12.0 18.00
# 12 15-06-2015     6 15.7 18.40

数据

vdate=c("12-04-2015","13-04-2015","14-04-2015","15-04-2015","12-05-2015", "13-05-2015","14-05-2015","15-05-2015","12-06-2015","13-06-2015", "14-06-2015","15-06-2015") month=c(4,4,4,4,5,5,5,5,6,6,6,6) col1=c(12,12.4,14.3,3,5.3,1.8,7.6,4.5,7.6,10.7,12,15.7) df=data.frame(vdate,month,col1) pvar=c(8.4,2.4,12,14.4,2.3,3.5,7.8,5,16,5.4,18,18.4)

计算月平均值并替换其他列的值

2 个答案: