英文:
How to Summarize multiple columns in R while removing NAs
问题
我试图总结一个数据集，以便列出所有具有数字值的列的均值、中位数、标准差、第25个和第5个百分位数，其中NA已被移除。到目前为止，我有以下代码，但似乎无法将其整理成合适的结构。
mtcars %>%summarize(across(where(is.numeric), list(Mean = mean, Median = median, Q90 = quantile(., 0.9), SD = sd, Q5 = quantile(., 0.05), N = sum(!is.na(.))), na.rm = TRUE))
我正在寻找类似下面的输出：
> 均值 中位数 90%百分位数 标准差 5%百分位数 N> MPG # # # # # #> CYL #> DISP #> HP #> DRAT #> 等等 #
还类似下面的输出：
> 均值 中位数 Q90 标准差 Q5 N> MPG # # # # # #> CYL #> DISP #> HP #> DRAT #> 等等 #
是否可以将数据整理成这种方式？感谢您帮助R中的新手。
英文:
I am trying to use summarize a dataset so that it would list out the mean, median, SD, 25th, 5th percentile for all columns with numeric values with NA removed. I have the below so far, but cannot seem to get it into the appropriate structure.
mtcars %>% summarize(across(where(is.numeric), list(mean = mean, sd = sd), na.rm = TRUE))
I am looking for something like the below:
> MPG CYL DISP HP DRAT etc
> Mean # # # # #
> Median #
> 90% Percentile(q90) #
> SD #
> 5% Percentile (q5) #
> N #
and also like the below
> Mean Median Q90 SD Q5 N
> MPG # # # # # #
> CYL #
> DISP #
> HP #
> DRAT #
> etc #
Is it possible to shape the data this way? Thanks for helping a novice in R.
答案1
得分: 1
这是一个处理数据的一种方法：
mtcars %>% summarize(across(where(is.numeric), list(mean = mean, sd = sd), na.rm = TRUE)) %>%pivot_longer(everything(), names_to = "var", values_to = "val") %>%separate(var, c("var", "stat"), sep = "_") %>%pivot_wider(names_from = "stat", values_from = "val")
输出结果：
# A tibble: 11 x 3var mean sd<chr> <dbl> <dbl>1 mpg 20.1 6.032 cyl 6.19 1.793 disp 231. 124.4 hp 147. 68.65 drat 3.60 0.5356 wt 3.22 0.9787 qsec 17.8 1.798 vs 0.438 0.5049 am 0.406 0.49910 gear 3.69 0.73811 carb 2.81 1.62
或者将 names_from = "stat" 更改为 names_from = "var"：
输出结果：
# A tibble: 2 x 12stat mpg cyl disp hp drat wt qsec vs am gear carb<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>1 mean 20.1 6.19 231. 147. 3.60 3.22 17.8 0.438 0.406 3.69 2.812 sd 6.03 1.79 124. 68.6 0.535 0.978 1.79 0.504 0.499 0.738 1.62
请注意，这只是代码的翻译部分。
英文:
Here is one of way of doing this :
mtcars %>% summarize(across(where(is.numeric), list(mean = mean, sd = sd), na.rm = TRUE)) %>%pivot_longer(everything(),names_to = "var", values_to = "val" ) %>%separate(var, c("var", "stat"), sep = "_") %>%pivot_wider(names_from = "stat", values_from = "val")
output:
# A tibble: 11 x 3var mean sd<chr> <dbl> <dbl>1 mpg 20.1 6.032 cyl 6.19 1.793 disp 231. 124.4 hp 147. 68.65 drat 3.60 0.5356 wt 3.22 0.9787 qsec 17.8 1.798 vs 0.438 0.5049 am 0.406 0.49910 gear 3.69 0.73811 carb 2.81 1.62
or change names_from = "stat" to names_from = "var" :
output
# A tibble: 2 x 12stat mpg cyl disp hp drat wt qsec vs am gear carb<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>1 mean 20.1 6.19 231. 147. 3.60 3.22 17.8 0.438 0.406 3.69 2.812 sd 6.03 1.79 124. 68.6 0.535 0.978 1.79 0.504 0.499 0.738 1.62
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