Applying a function inside a dplyr pipe command

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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"))

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

df %>% group_by(Country) %>% mutate_at(vars(OfferPrice), funs(Trim(x = ., trim = 0.1, na.rm = TRUE)))) ?
– Andre Elrico
Nov 19 at 15:39

Or just df %>% group_by(Country) %>% mutate(OfferPrice = Trim(OfferPrice, trim=0.1, na.rm=TRUE)), since it's only one column.
– r2evans
Nov 19 at 15:41

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up vote
0
down vote

favorite

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"))

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

df %>% group_by(Country) %>% mutate_at(vars(OfferPrice), funs(Trim(x = ., trim = 0.1, na.rm = TRUE)))) ?
– Andre Elrico
Nov 19 at 15:39

Or just df %>% group_by(Country) %>% mutate(OfferPrice = Trim(OfferPrice, trim=0.1, na.rm=TRUE)), since it's only one column.
– r2evans
Nov 19 at 15:41

add a comment |

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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"))

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

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"))

r dplyr

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

edited Nov 19 at 22:07

Stedy

5,067144767

edited Nov 19 at 22:07

Stedy

5,067144767

edited Nov 19 at 22:07

Stedy

5,067144767

asked Nov 19 at 15:27

user113156

775417

asked Nov 19 at 15:27

user113156

775417

asked Nov 19 at 15:27

user113156

775417

df %>% group_by(Country) %>% mutate_at(vars(OfferPrice), funs(Trim(x = ., trim = 0.1, na.rm = TRUE)))) ?
– Andre Elrico
Nov 19 at 15:39

Or just df %>% group_by(Country) %>% mutate(OfferPrice = Trim(OfferPrice, trim=0.1, na.rm=TRUE)), since it's only one column.
– r2evans
Nov 19 at 15:41

add a comment |

df %>% group_by(Country) %>% mutate_at(vars(OfferPrice), funs(Trim(x = ., trim = 0.1, na.rm = TRUE)))) ?
– Andre Elrico
Nov 19 at 15:39

Or just df %>% group_by(Country) %>% mutate(OfferPrice = Trim(OfferPrice, trim=0.1, na.rm=TRUE)), since it's only one column.
– r2evans
Nov 19 at 15:41

df %>% group_by(Country) %>% mutate_at(vars(OfferPrice), funs(Trim(x = ., trim = 0.1, na.rm = TRUE)))) ?
– Andre Elrico
Nov 19 at 15:39

Or just df %>% group_by(Country) %>% mutate(OfferPrice = Trim(OfferPrice, trim=0.1, na.rm=TRUE)), since it's only one column.
– r2evans
Nov 19 at 15:41

add a comment |

2 Answers
2

active

oldest

votes

up vote
1
down vote

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".

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

add a comment |

up vote
1
down vote

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

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

1

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

add a comment |

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2 Answers
2

active

oldest

votes

2 Answers
2

active

oldest

votes

up vote
1
down vote

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)

  )

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".

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

add a comment |

up vote
1
down vote

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)

  )

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".

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

add a comment |

up vote
1
down vote

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)

  )

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".

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

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)

  )

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".

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

edited Nov 19 at 21:47

answered Nov 19 at 15:33

mikeck

1,9621022

answered Nov 19 at 15:33

mikeck

1,9621022

answered Nov 19 at 15:33

mikeck

1,9621022

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

add a comment |

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

Thanks! I will try it out now. Regarding the mutate_all ignore that, I just wanted to trim the end points of the OfferPrice column. I will let you know how it works.
– user113156
Nov 19 at 15:41

@user113156 see my edit based on your actual end goal.
– mikeck
Nov 19 at 15:49

Did you use a package for the attribute part? I get this: could not find function "attribute"
– user113156
Nov 19 at 15:51

@user113156 sorry it should be attr, not attribute.
– mikeck
Nov 19 at 16:56

add a comment |

up vote
1
down vote

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

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

1

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

add a comment |

up vote
1
down vote

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

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

1

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

add a comment |

up vote
1
down vote

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

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

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

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

edited Nov 19 at 22:48

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

answered Nov 19 at 16:05

G. Grothendieck

143k9125230

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

1

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

add a comment |

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

1

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

Right forgot about slice... this accomplishes the same thing as my answer with do, but using slice is a bit cleaner.
– mikeck
Nov 19 at 16:59

@mikek, The code in your EDIT would give the same result if it added a minus.
– G. Grothendieck
Nov 19 at 17:05

add a comment |

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