Deviations from type average-CodePudding

I have a df like this:

structure(list(Date = structure(c(18605, 18604, 18598, 18597, 
18590, 18584, 18583, 18578, 18570, 18569, 18563, 18562, 18557, 
18549, 18548, 18542, 18541, 18536, 18534, 18529, 18521, 18520, 
18515, 18508, 18500, 18499, 18493, 18492, 18486, 18485, 18479, 
18478, 18472, 18471, 18465, 18464, 18458, 18457, 18450, 18445, 
18444, 18437, 18436, 18430, 18429, 18424, 18416, 18415, 18410, 
18409, 18403, 18402, 18396, 18388, 18387, 18381, 18380, 18374, 
18373, 18368, 18367, 18360, 18359, 18354, 18340, 18338, 18331, 
18325, 18317, 18312, 18289, 18282, 18275, 18268), class = "Date"), 
    `Type 1` = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, 0.3, NA, NA, NA, NA, 0.4, NA, NA, 
    NA, NA, 0.2, NA, NA, NA, NA, 0.7, NA, NA, NA, NA, NA, 0.5, 
    NA, NA, NA, NA, 0.3, NA, NA, NA, NA, NA, 0.4, NA, NA, NA, 
    0.3, NA, NA, NA, NA, NA, NA, NA, NA, 0.6, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA), `Type 2` = c(NA, NA, 0.1, NA, 
    NA, 0.1, NA, 0.2, NA, 0.2, 0.1, NA, 0.2, 0.2, NA, 0.1, NA, 
    NA, 0.1, NA, 0.2, NA, NA, 0.4, 0.2, NA, 0.3, NA, 0.2, NA, 
    0.3, NA, 0.6, NA, 0.4, NA, NA, 0.2, NA, 0.4, 0.6, NA, 0.3, 
    NA, 0.2, 0.7, NA, 0.1, 0.3, NA, 0.2, NA, NA, NA, 0.3, NA, 
    0.1, 0.3, NA, NA, 0.3, 0.2, NA, NA, NA, NA, 0.6, NA, 0.4, 
    NA, 0.2, NA, NA, 0.2), `Type 3` = c(NA, 0.3, NA, 0.3, 0.4, 
    NA, 0.2, NA, 0.3, NA, NA, 0.2, NA, NA, 0.2, NA, 0.2, NA, 
    NA, 0.1, NA, 0.2, NA, NA, NA, 0.3, NA, NA, NA, 0.4, NA, 0.3, 
    NA, 0.7, NA, 0.2, 0.5, 0.4, NA, 0.4, NA, 0.8, 0.4, NA, 0.2, 
    0.6, 0.3, 0.2, NA, NA, NA, 0.4, 0.4, NA, 0.2, 0.3, NA, 0.2, 
    0.3, 0.4, NA, 0.7, NA, NA, 1.4, NA, NA, 1.4, NA, 1, NA, NA, 
    0.3, NA), `Type 4` = c(NA, 0.4, NA, 0.1, 0.1, NA, 0.1, NA, 
    NA, 0.1, NA, 0.1, 0.2, NA, 0.2, NA, 0.2, 0.3, NA, NA, NA, 
    0.2, 0.3, 0.3, NA, NA, NA, 0.5, NA, 0.6, NA, 0.7, NA, NA, 
    NA, 1.2, 1, NA, 0.3, NA, 1.1, NA, NA, 0.4, NA, NA, NA, NA, 
    0.2, 0.2, NA, NA, 0.2, NA, NA, 0.1, NA, NA, NA, 0.2, 0.3, 
    NA, 0.2, 0.3, NA, 1.8, NA, NA, NA, NA, NA, 0.2, NA, NA)), row.names = c(NA, 
-74L), class = c("tbl_df", "tbl", "data.frame"))

I'd like to be able to work out the deviation from the 'Type' average, and display it instead of the original data. So for example, the df currently shows 0.3 on 2020-10-01 for 'Type 1'. Instead of that, I would like it to show the deviation from the 'Type 1' average from across the dataset. Is this possible? Any help is appreciated.

CodePudding user response：

library(tidyverse)

df %>%  
  mutate(across(2:5, ~ mean(., na.rm = T) - .x ))

# A tibble: 74 × 5
   Date       `Type 1` `Type 2` `Type 3` `Type 4`
   <date>        <dbl>    <dbl>    <dbl>    <dbl>
 1 2020-12-09       NA  NA       NA      NA      
 2 2020-12-08       NA  NA        0.119  -0.00968
 3 2020-12-02       NA   0.171   NA      NA      
 4 2020-12-01       NA  NA        0.119   0.290  
 5 2020-11-24       NA  NA        0.0194  0.290  
 6 2020-11-18       NA   0.171   NA      NA      
 7 2020-11-17       NA  NA        0.219   0.290  
 8 2020-11-12       NA   0.0714  NA      NA      
 9 2020-11-04       NA  NA        0.119  NA      
10 2020-11-03       NA   0.0714  NA       0.290  
# … with 64 more rows
# ℹ Use `print(n = ...)` to see more rows