Applying a function inside a dplyr pipe command

Question

I am trying to apply a Trim function from the DescTools package to a data frame in R using the dplyr package.

What I have so far is the following:

x <- df %>%
  group_by(Country) %>%
  mutate_all(OfferPrice, Trim(trim = 0.1, na.rm = TRUE))

Which returns the following error:

Error in Trim(trim = 0.1, na.rm = TRUE) : 
  argument "x" is missing, with no default

I know its a problem with the characteristics inside the Trim() part of the mutate but I cannot seem to apply this function inside dplyr.

The function trims the top and bottom 10% of the observations, hopefully removing any extreme values.

Data:

df <- structure(list(Country = c("AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", "AU", 
"AU", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", 
"CA", "CA", "CA", "CA", "CA", "CA", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", "GB", 
"GB", "GB", "GB", "GB", "GB", "GB"), OfferPrice = c(0.25, 0.55, 
0.065, 0.075, 0.019, 0.0114, 0.18, 0.015, 2.8, 3.62, 0.025, 0.07, 
0.6, 0.9, 0.12, 2.72, 0.015, 0.015, 0.32, 0.2, 0.063, 0.01, 1.42, 
0.0045, 0.02, 1.15, 0.2, 17.05, 0.009, 1.8, 3.22, 0.135, 0.35, 
5, 0.37, 0.023, 0.014, 0.023, 0.35, 1.25, 0.05, 0.059, 0.2, 0.025, 
5.45, 0.05, 0.3, 0.22, 0.04, 0.035, 2, 0.32, 0.2, 0.2, 0.02, 
0.34, 0.04, 0.025, 0.03, 0.0125, 1.6, 0.03, 0.15, 13.5, 0.1, 
0.3, 0.13, 0.115, 0.35, 0.2, 0.6, 0.7, 8, 14, 25, 15.75, 3.8, 
2, 0.5, 35.2, 1.75, 0.12, 0.48, 0.15, 0.7, 0.075, 0.15, 14.5, 
0.29, 0.58, 1.75, 9, 11.5, 0.5, 0.075, 0.12, 1.1, 0.6, 0.75, 
0.26, 0.2, 0.12, 0.49, 12, 6.85, 0.55, 0.25, 1.6, 0.36, 0.06, 
2, 0.272, 41, 0.15, 1.1, 4.1, 0.6, 0.08, 1.4, 3, 0.09, 0.15, 
0.2, 0.3, 0.8, 0.21, 0.1, 0.05, 0.17, 0.1, 0.15, 0.05, 0.3, 0.6, 
0.2, 0.5, 3.45, 3, 0.07, 0.1, 0.3, 7.2, 0.4, 0.1, 12.5, 0.07, 
0.375, 0.25, 0.3, 1.15, 0.2, 3, 1, 0.3, 0.25, 530, 262, 20, 37.5, 
3422, 295, 100, 0.085, 1925, 0.3, 107.5, 10, 2.1, 3, 15, 300, 
690, 50, 410, 100, 120, 225, 40, 100, 100, 51, 10, 82, 9.58, 
269, 0.5, 271, 100, 108, 0.3, 4.5, 0.5, 0.55, 50, 0.95, 275, 
100, 170, 0.7), OfferTo1stOpen = c(18, -2.727274895, 9.230772972, 
6.666662216, -15.78947067, 5.263155937, -2.777781725, 13.33333588, 
5.000001907, -3.591157198, -0.000001490116119, 1.428570986, -4.166670322, 
0.00000264909545, -34.16666412, -0.000001051846652, 26.66666985, 
26.66666985, 9.375002861, 2.499998569, 6.34920454, 0.000002235174179, 
-0.7042223215, -11.11110687, 15.00000286, 1.304349899, -0.000001490116119, 
6.217013359, 11.11111546, 25.00000381, 0.9316761494, -0.000003973642833, 
-15.71428394, 17.20000076, -0.000001288749104, 4.347826004, 14.28571033, 
13.04347801, 4.285716057, 43.20000076, 1.99999845, 10.16949081, 
2.499998569, -4.000001431, -0.1834827513, 11.99999809, -1.666670561, 
95.45454407, -12.49999809, 25.7142849, -0.5, 18.75000191, -0.000001490116119, 
-17.50000191, -9.999998093, 44.11764526, 15.00000286, 19.99999809, 
0.000002235174179, 35.99999619, 10.62499809, 76.66667175, 6.666662216, 
-0.3703703582, -10.00000095, -100, 146.1538544, 65.21739197, 
-11.42856979, 14.99999809, -5.000003815, -11.42856979, 1.625, 
6.785714149, NA, 3.492063522, -3.684209347, -2.5, 10, -1.420456648, 
1.142857194, -12.49999809, -1.041664481, -0.000003973642833, 
-14.2857132, 39.99999619, 36.66666031, -0.3448275924, -15.51723862, 
-12.06896305, -18.2857151, 0.555555582, -5.434782505, 590, -6.666670322, 
0.000002235174179, 1.818179607, 36.66666031, -6.666666508, 0.000003667978262, 
-10.00000095, 20.83333588, -20.40816498, -2.916666746, -29.1970787, 
-0.000002167441608, -10, -18.80635834, -100, 8.333335876, -3.5, 
10.29411125, 2.097560883, -6.666670322, 7.272725105, 0.7317096591, 
19.99999619, 81.25000763, 45.00000381, -20, -11.1111145, -0.000003973642833, 
-7.500001431, -0.000003973642833, -1.250001431, -14.28571129, 
49.99999619, -10.00000095, -5.882353783, NA, 23.33332825, 19.99999809, 
18.33332825, -13.33333683, 34.99999619, -34, -19.71014595, -32.33333206, 
-21.4285717, -20.00000191, -100, 0.1388915479, 7.499998569, -20.00000191, 
-0.2399999946, 257.1428528, -16, 54, NA, -4.347824097, -100, 
6, 1, 4.999995708, -8, 8.301886559, 3.511450291, 25, 16, -1.461133838, 
-1.694915295, 1, 17.64705849, 3.376623392, 24.99999428, 3.255813837, 
34, 0.00000454130668, -3.333333254, 10.33333302, 1.666666627, 
16.231884, 9, 1.829268336, 3, 11.66666698, 4.888888836, 14.25, 
3.5, 3.5, -4.411764622, 0.200000003, 1.829268336, 53.96659851, 
9.665427208, 5, -1.586715817, 2, 1.111111164, 4.999995708, -10, 
5, -4.545456409, NA, 7.894738197, 5.454545498, 1, 11.17647076, 
25.00000191), OfferTo1stClose = c(8, -7.272729397, 9.230772972, 
7.999995708, -21.05262947, -3.508773565, -2.777781725, 0.000002235174179, 
3.571430445, -3.867400169, -0.000001490116119, 1.428570986, -6.666670322, 
-1.666664004, -35.83333206, -3.308824539, 13.33333588, 26.66666985, 
10.93750286, -0.000001490116119, 6.34920454, -9.999998093, -0.3521096706, 
11.11111546, 5.000002384, -0.4347805381, -2.500001431, 3.519066334, 
11.11111546, 27.22222519, 4.34782505, -7.407411098, -17.1428566, 
15.39999962, 4.05405283, -0.0000001943629684, 7.142853737, 13.04347801, 
2.857144594, 43.20000076, 3.999998569, 10.16949081, -7.500001431, 
3.999998569, -0.5504552126, 19.99999809, -1.666670561, 170.4545441, 
-14.99999809, 31.4285717, -0.5, 18.75000191, -20.00000191, -17.50000191, 
0.000002235174179, 44.11764526, 12.50000286, 15.99999809, 3.333335638, 
35.99999619, 10.62499809, 123.3333359, 13.3333292, -1.481481433, 
-10.00000095, -100, 138.4615479, 47.82608414, -12.85714149, 32.49999619, 
-13.33333683, -24.2857132, 1.75, -0.3571428657, NA, 3.93650794, 
-7.894735813, -7, 20, -0.9375021458, 1.714285731, -8.333331108, 
-1.041664481, 3.333329201, -19.99999809, 33.33332825, 33.33332825, 
-0.06896551698, -16.3793087, -16.3793087, -18.2857151, 2.666666746, 
2.173913002, 590, -6.666670322, -16.66666412, 2.727270603, 44.99999237, 
-10.66666698, 1.923080683, -12.50000095, 16.66666985, -22.44898033, 
-4.166666508, -39.85401535, -3.636365652, -12, -16.8959198, -100, 
0.000002235174179, -3.5, 13.97058201, 2.707317114, -8.066670418, 
5.454543114, 0.4878072143, 19.99999619, 87.50000763, 45.7142868, 
-25.66666603, -5.555559158, 16.66666222, -2.500001431, 3.333329201, 
-0.000001490116119, -14.28571129, 49.99999619, -10.00000095, 
-5.882353783, NA, 39.99999619, 19.99999809, 13.3333292, -10.00000381, 
65, -26, -19.71014595, -31.66666603, -21.4285717, -20.00000191, 
-100, -0.1388862431, 11.24999809, -20.00000191, -1.679999948, 
228.5714264, -22.66666603, 42, NA, -7.826085091, -100, 6.666666508, 
0, 4.999995708, -8, 8.301886559, 3.969465733, 26, 16, -5.084745884, 
1.322033882, 1.5, 17.64705849, 2.077922106, 24.99999428, 3.255813837, 
43, 0.00000454130668, -4.166666508, 10.33333302, 1.333333373, 
18.69565201, 9, 1.829268336, 3, 11.66666698, 3.111111164, 15, 
3.5, 3.5, -4.411764622, 0.6000000238, 50.60975647, 53.96659851, 
37.54646683, 0, -0.1476014704, 3, 1.296296239, 4.999995708, -11.11111069, 
5, -0.000002167441608, NA, 7.894738197, 4.181818008, 0.5, 10.88235283, 
25.00000191)), row.names = c(NA, -199L), vars = "Country", drop = TRUE, indices = list(
    0:61, 62:154, 155:198), group_sizes = c(62L, 93L, 44L), biggest_group_size = 93L, labels = structure(list(
    Country = c("AU", "CA", "GB")), row.names = c(NA, -3L), class = "data.frame", vars = "Country", drop = TRUE, indices = list(
    0:61, 62:154, 155:198), group_sizes = c(62L, 93L, 44L), biggest_group_size = 93L, labels = structure(list(
    Country = c("AU", "CA", "GB")), row.names = c(NA, -3L), class = "data.frame", vars = "Country", drop = TRUE)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

Answer 1

Assuming that what you want is that for any element of OfferPrice excluded by Trim(OfferPrice, ...) that entire row of df should be dropped, get the trim attribute of the result of Trim(...) and remove those rows using slice doing it all by Country.

library(dplyr)
library(DescTools)

df %>%
  group_by(Country) %>%
  slice(-attr(Trim(OfferPrice, trim = 0.1, na.rm = TRUE), "trim")) %>%
  ungroup

This could also be written:

df %>%
  group_by(Country) %>%
  slice(OfferPrice %>% 
          Trim(trim = 0.1, na.rm = TRUE) %>% 
          attr("trim") %>% 
          `-`) %>%
  ungroup

Answer 2

I think you'll need to do this with do since the action of Trim is to return essentially a subset of observations. Try:

x <- df %>%
  group_by(Country) %>% 
  do(
    Trim(.$OfferPrice, trim = 0.1, na.rm = TRUE)
  )

You could then use lapply or map inside the do statement to Trim each column of data, but I'm not sure if this is actually what you want. It's unclear since you have not provided any sample data. The attempt to use mutate_all suggests you want to Trim each column of data separately, but this doesn't make sense to me.

EDIT based on your comment you really want to filter the dataframe by the Trimmed column OfferPrice, so

x <- df %>%
  group_by(Country) %>% 
  do(
    .[attr(Trim(.$OfferPrice, trim = 0.1, na.rm = TRUE), "trim"), ]
  )

See the documentation of Trim for details, specifically

The indices of the trimmed values will be attached as attribute named "trim".