Stack Overflow Asked by Shadrack Kibet on December 11, 2021
How can I use multiple factor variables say cut,color,clarityas arguments of by parameter in zoo::na.aggregate() function and be able to append output back into the data frame. Below is a reproducible example using single factor i.e carat from diamonds dataset. If not possible any workaround using tidyverse?
library(ggplot2)
library(zoo)
diamonds$avg <- na.aggregate(object = diamonds$carat, by = diamonds$cut, mean)
View(diamonds)
If you're trying to get the mean of carat based on cut, color and clarity, then this is what you're looking for:
library(dplyr)
library(zoo)
diamonds %>%
group_by(cut,color,clarity) %>%
mutate(mean=na.aggregate(carat))
# A tibble: 53,940 x 11
# Groups: cut, color, clarity [276]
carat cut color clarity depth table price x y z mean
<dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl>
1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43 0.23
2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31 0.21
3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31 0.23
4 0.290 Premium I VS2 62.4 58 334 4.2 4.23 2.63 0.290
5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75 0.31
6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48 0.24
7 0.24 Very Good I VVS1 62.3 57 336 3.95 3.98 2.47 0.24
8 0.26 Very Good H SI1 61.9 55 337 4.07 4.11 2.53 0.26
9 0.22 Fair E VS2 65.1 61 337 3.87 3.78 2.49 0.22
10 0.23 Very Good H VS1 59.4 61 338 4 4.05 2.39 0.23
Answered by Maël on December 11, 2021
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