我经历R上的Kaggle教程，并试图替代magrittr的filter。但这似乎不起作用，但我不明白为什么。他们似乎做同样的事情。
我试过下面的代码。
f_countOfMen <- mutFoodData %>%
select(starts_with("gender")) %>%
filter(Gender == 1) %>%
rowSums(na.rm = T)
f_countOfWomen <- mutFoodData %>%
select(starts_with("gender")) %>%
filter(Gender == 2) %>%
rowSums(na.rm = T)
mutFoodData <- mutFoodData %>%
mutate(fMen = f_countOfMen, fWomen = f_countOfWomen) # add our new variables
# however it doesn't add the variables and produces an error
m_countOfMen <- mutFoodData %>%
select(starts_with("gender")) %>%
magrittr::equals(1) %>%
rowSums(na.rm = T)
m_countOfWomen <- mutFoodData %>%
select(starts_with("gender")) %>%
magrittr::equals(2) %>%
rowSums(na.rm = T)
mutFoodData <- mutFoodData %>%
mutate(mMen = m_countOfMen, mWomen = m_countOfWomen) # add our new variables
# this code does as expected
我希望添加新的列，但我不断收到此错误：
mutate_impl（.data，点）中的错误：错误的结果大小（76），预期为124或1
问题在于，这样做的同时filter减少了行数，并将其添加到具有完整行的原始数据集中。在这里，而不是filtering，创建一个逻辑矩阵，并获得rowSums“男人”和“女人”的
library(dplyr)
mutFoodData %>%
mutate(fMen = rowSums(select(., starts_with("gender")) == 1, na.rm= TRUE),
fFemale = rowSums(2*(select(., starts_with("gender")) ==2), na.rm = TRUE))
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