使用group_by时mutate_at评估错误 [英] mutate_at evaluation error when using group_by
问题描述
mutate_at()与group_by()一起使用以及将列位置的数值向量作为第一个(.vars)参数插入时,显示评估错误.
mutate_at() shows an evaluation error when used with group_by() and when imputing a numerical vector for column position as the first (.vars) argument.
- 使用
R
3.4.2和dplyr
0.7.4版本时出现问题 - 使用
R
3.3.2和dplyr
0.5.0 时工作正常
- 如果.vars是字符向量(列名),效果很好
- Issue shows up when using
R
3.4.2 anddplyr
0.7.4 version - Works fine when using
R
3.3.2 anddplyr
0.5.0 - Works fine if .vars is character vector (column name)
示例:
# Create example dataframe
Id <- c('10_1', '10_2', '11_1', '11_2', '11_3', '12_1')
Month <- c(2, 3, 4, 6, 7, 8)
RWA <- c(0, 0, 0, 1.579, NA, 0.379)
dftest = data.frame(Id, Month, RWA)
# Define column to fill NAs
nacol = c('RWA')
# Fill NAs with last period
dftest_2 <- dftest %>%
group_by(Id) %>%
mutate_at(which(names(dftest) %in% nacol),
funs(ifelse(is.na(.),0,.)))
Error in mutate_impl(.data, dots) :
Evaluation error: object 'NA' not found.
展示问题的更明智的示例:
More sensible example demonstrating issue:
# Create example dataframe
Id <- c('10_1', '10_2', '11_1', '11_3', '11_3', '12_1')
Month <- c(2, 3, 4, 6, 7, 8)
RWA <- c(0, 0, 0, 1.579, NA, 0.379)
dftest = data.frame(Id, Month, RWA)
# Define column to fill NAs
nacol = c('RWA')
# Fill NAs with last period
dftest_2 <- dftest %>%
group_by(Id) %>%
mutate_at(which(names(dftest) %in% nacol),
funs(na.locf(., na.rm=F)))
推荐答案
我们获得NA值的原因是,我们从which
获得的输出为3,但是我们按"Id"分组,所以只有2之后的专栏.
The reason we are getting NA values is that the output we get from which
is 3, but we grouped by 'Id' and so there are only 2 columns after that.
dftest %>%
group_by(Id) %>%
mutate_at(which(names(dftest) %in% nacol)-1, funs(ifelse(is.na(.),0,.)))
# A tibble: 6 x 3
# Groups: Id [6]
# Id Month RWA
# <fctr> <dbl> <dbl>
#1 10_1 2 0.000
#2 10_2 3 0.000
#3 11_1 4 0.000
#4 11_2 6 1.579
#5 11_3 7 0.000
#6 12_1 8 0.379
此处不需要group_by
部分,因为我们将其他列中的NA值更改为0
The group_by
is part is not needed here as we are changing NA values in other columns to 0
dftest %>%
mutate_at(which(names(dftest) %in% nacol), funs(ifelse(is.na(.),0,.)))
这可能是一个错误,使用基于职位的方法有时会带来风险.更好的选择是使用names
It could be a bug and using the position based approach is sometimes risky. Better option would be to go with names
dftest %>%
group_by(Id) %>%
mutate_at(intersect(names(.), nacol), funs(replace(., is.na(.), 0)))
注意:在所有这些情况下,都不需要group_by
NOTE: In all these cases, the group_by
is not needed
另一个选项是tidyr
中的replace_na
dftest %>%
tidyr::replace_na(as.list(setNames(0, nacol)))
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