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Function that calculates, mean, variance and skewness at the same time in a dataframe

Applying functions to dataframe or multiple listsCalculating mean of a subset within a dataframe in rR cut with open interval to right puts some values in the wrong intervalHow to calculate daily means, medians, from weather variables data collected hourly in R?Calculate summary statistics of different columns from separate data.framesMean(or other function) of corresponding elements of a list in Rr - Length and sum of runs of negative valuesFunction to perform similar calculations on variables with similar namesR: Change order of several dataframes in a list depending on mean of a specific columnLooping so that it extracts data and then calculates mean

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2

I have this dataframe

um dois tres
1.2 1.9 0.1
1.2 1.1 2
2.2 1.2 0.4
3.0 1.8 2.6

and I need to calculate in the same function the mean, variance and skewness of the dataframe. I have the functions separate.
Any suggestions?

mean <- function(x)
 sum(x)/length(x)


variance <- function(x)
 n <- length(x)
 m <- mean(x)
 (1/(n-1))*sum((x-m)^2)


skewness <- function(x) 
 n <- length(x)
 v <- var(x)
 m <- mean(x)
 third.moment <- (1/(n - 2))*sum((x - m)^3)
 third.moment/(var(x)^(3/2))

r function

share|improve this question

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What does "of the dataframe" mean? Calculate values for each column, or for all numbers in all columns combined?
  
  – neilfws
  Mar 8 at 0:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  See the moments package for the skewness function.
  
  – Dave2e
  Mar 8 at 0:35
  

  
  
  
  

add a comment | 

2

I have this dataframe

um dois tres
1.2 1.9 0.1
1.2 1.1 2
2.2 1.2 0.4
3.0 1.8 2.6

and I need to calculate in the same function the mean, variance and skewness of the dataframe. I have the functions separate.
Any suggestions?

mean <- function(x)
 sum(x)/length(x)


variance <- function(x)
 n <- length(x)
 m <- mean(x)
 (1/(n-1))*sum((x-m)^2)


skewness <- function(x) 
 n <- length(x)
 v <- var(x)
 m <- mean(x)
 third.moment <- (1/(n - 2))*sum((x - m)^3)
 third.moment/(var(x)^(3/2))

r function

share|improve this question

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What does "of the dataframe" mean? Calculate values for each column, or for all numbers in all columns combined?
  
  – neilfws
  Mar 8 at 0:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  See the moments package for the skewness function.
  
  – Dave2e
  Mar 8 at 0:35
  

  
  
  
  

add a comment | 

I have this dataframe

um dois tres
1.2 1.9 0.1
1.2 1.1 2
2.2 1.2 0.4
3.0 1.8 2.6

and I need to calculate in the same function the mean, variance and skewness of the dataframe. I have the functions separate.
Any suggestions?

mean <- function(x)
 sum(x)/length(x)


variance <- function(x)
 n <- length(x)
 m <- mean(x)
 (1/(n-1))*sum((x-m)^2)


skewness <- function(x) 
 n <- length(x)
 v <- var(x)
 m <- mean(x)
 third.moment <- (1/(n - 2))*sum((x - m)^3)
 third.moment/(var(x)^(3/2))

r function

share|improve this question

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

um dois tres
1.2 1.9 0.1
1.2 1.1 2
2.2 1.2 0.4
3.0 1.8 2.6

mean <- function(x)
 sum(x)/length(x)


variance <- function(x)
 n <- length(x)
 m <- mean(x)
 (1/(n-1))*sum((x-m)^2)


skewness <- function(x) 
 n <- length(x)
 v <- var(x)
 m <- mean(x)
 third.moment <- (1/(n - 2))*sum((x - m)^3)
 third.moment/(var(x)^(3/2))

share|improve this question

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

share|improve this question

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

edited Mar 8 at 0:32

d.b

20.5k41949

edited Mar 8 at 0:32

d.b

20.5k41949

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

asked Mar 8 at 0:10

Frank TerraFrank Terra

1111

2 Answers
2

active

oldest

votes

1

dput(data)
structure(list(um = c(1.2, 1.2, 2.2, 3), dois = c(1.9, 1.1, 1.2, 1.8), tres = c(0.1, 2, 0.4, 2.6)), class = "data.frame", row.names = c(NA,-4L))


# to use the function skewnewss install and load the package e1071
library(e1071)
sapply(data, function(x) c(means = mean(x), vars = var(x), skews = skewness(x)))

The output generates the required calculations in one go, for each of the input columns:

 um dois tres
 means 1.9000000 1.5000000 1.27500000
 vars 0.7600000 0.1666667 1.47583333
 skews 0.2535648 0.0000000 0.05788459

share|improve this answer

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Note that e1071::skewness takes the option type = from 1-3. Whilst 3 is the default, 1 is the "typical" definition. See also moments::skewness, which returns values as for type = 1.
  
  – neilfws
  Mar 8 at 1:19
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have to create one function that calculates mean, variance and skewness for each column. I have an error when I execute sappy: "Error in var(x) : is.atomic(x) is not TRUE"
  
  – Frank Terra
  Mar 8 at 15:40
  

  
  
  
  

add a comment | 

1

You don't explain whether "of the dataframe" means "by column". Let's assume it does and use tidyr::gather() to reshape the data from wide to long, then dplyr::summarise() for the calculations. Assume the dataframe is named data1 and using moments::skewness:

library(tidyr)
library(dplyr)
library(moments)

data1 %>%
 gather(Var, Val) %>% 
 group_by(Var) %>% 
 summarise(Mean = mean(Val), 
 Vari = var(Val), 
 Skew = skewness(Val))

# A tibble: 3 x 4
 Var Mean Vari Skew
 <chr> <dbl> <dbl> <dbl>
1 dois 1.5 0.167 0 
2 tres 1.28 1.48 0.0891
3 um 1.9 0.76 0.390

If you want values for all numbers, not by column, just omit the group_by.

If you want to use your own function - no need since R supplies them in this case - but you could just substitute their names.

share|improve this answer

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

add a comment | 

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1

dput(data)
structure(list(um = c(1.2, 1.2, 2.2, 3), dois = c(1.9, 1.1, 1.2, 1.8), tres = c(0.1, 2, 0.4, 2.6)), class = "data.frame", row.names = c(NA,-4L))


# to use the function skewnewss install and load the package e1071
library(e1071)
sapply(data, function(x) c(means = mean(x), vars = var(x), skews = skewness(x)))

The output generates the required calculations in one go, for each of the input columns:

 um dois tres
 means 1.9000000 1.5000000 1.27500000
 vars 0.7600000 0.1666667 1.47583333
 skews 0.2535648 0.0000000 0.05788459

share|improve this answer

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Note that e1071::skewness takes the option type = from 1-3. Whilst 3 is the default, 1 is the "typical" definition. See also moments::skewness, which returns values as for type = 1.
  
  – neilfws
  Mar 8 at 1:19
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have to create one function that calculates mean, variance and skewness for each column. I have an error when I execute sappy: "Error in var(x) : is.atomic(x) is not TRUE"
  
  – Frank Terra
  Mar 8 at 15:40
  

  
  
  
  

add a comment | 

1

dput(data)
structure(list(um = c(1.2, 1.2, 2.2, 3), dois = c(1.9, 1.1, 1.2, 1.8), tres = c(0.1, 2, 0.4, 2.6)), class = "data.frame", row.names = c(NA,-4L))


# to use the function skewnewss install and load the package e1071
library(e1071)
sapply(data, function(x) c(means = mean(x), vars = var(x), skews = skewness(x)))

The output generates the required calculations in one go, for each of the input columns:

 um dois tres
 means 1.9000000 1.5000000 1.27500000
 vars 0.7600000 0.1666667 1.47583333
 skews 0.2535648 0.0000000 0.05788459

share|improve this answer

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Note that e1071::skewness takes the option type = from 1-3. Whilst 3 is the default, 1 is the "typical" definition. See also moments::skewness, which returns values as for type = 1.
  
  – neilfws
  Mar 8 at 1:19
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I have to create one function that calculates mean, variance and skewness for each column. I have an error when I execute sappy: "Error in var(x) : is.atomic(x) is not TRUE"
  
  – Frank Terra
  Mar 8 at 15:40
  

  
  
  
  

add a comment | 

dput(data)
structure(list(um = c(1.2, 1.2, 2.2, 3), dois = c(1.9, 1.1, 1.2, 1.8), tres = c(0.1, 2, 0.4, 2.6)), class = "data.frame", row.names = c(NA,-4L))


# to use the function skewnewss install and load the package e1071
library(e1071)
sapply(data, function(x) c(means = mean(x), vars = var(x), skews = skewness(x)))

The output generates the required calculations in one go, for each of the input columns:

 um dois tres
 means 1.9000000 1.5000000 1.27500000
 vars 0.7600000 0.1666667 1.47583333
 skews 0.2535648 0.0000000 0.05788459

share|improve this answer

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

dput(data)
structure(list(um = c(1.2, 1.2, 2.2, 3), dois = c(1.9, 1.1, 1.2, 1.8), tres = c(0.1, 2, 0.4, 2.6)), class = "data.frame", row.names = c(NA,-4L))


# to use the function skewnewss install and load the package e1071
library(e1071)
sapply(data, function(x) c(means = mean(x), vars = var(x), skews = skewness(x)))

 um dois tres
 means 1.9000000 1.5000000 1.27500000
 vars 0.7600000 0.1666667 1.47583333
 skews 0.2535648 0.0000000 0.05788459

share|improve this answer

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

edited Mar 8 at 0:53

d.b

20.5k41949

edited Mar 8 at 0:53

d.b

20.5k41949

answered Mar 8 at 0:43

SadiazSadiaz

917

answered Mar 8 at 0:43

SadiazSadiaz

917

1

You don't explain whether "of the dataframe" means "by column". Let's assume it does and use tidyr::gather() to reshape the data from wide to long, then dplyr::summarise() for the calculations. Assume the dataframe is named data1 and using moments::skewness:

library(tidyr)
library(dplyr)
library(moments)

data1 %>%
 gather(Var, Val) %>% 
 group_by(Var) %>% 
 summarise(Mean = mean(Val), 
 Vari = var(Val), 
 Skew = skewness(Val))

# A tibble: 3 x 4
 Var Mean Vari Skew
 <chr> <dbl> <dbl> <dbl>
1 dois 1.5 0.167 0 
2 tres 1.28 1.48 0.0891
3 um 1.9 0.76 0.390

If you want values for all numbers, not by column, just omit the group_by.

If you want to use your own function - no need since R supplies them in this case - but you could just substitute their names.

share|improve this answer

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

add a comment | 

1

You don't explain whether "of the dataframe" means "by column". Let's assume it does and use tidyr::gather() to reshape the data from wide to long, then dplyr::summarise() for the calculations. Assume the dataframe is named data1 and using moments::skewness:

library(tidyr)
library(dplyr)
library(moments)

data1 %>%
 gather(Var, Val) %>% 
 group_by(Var) %>% 
 summarise(Mean = mean(Val), 
 Vari = var(Val), 
 Skew = skewness(Val))

# A tibble: 3 x 4
 Var Mean Vari Skew
 <chr> <dbl> <dbl> <dbl>
1 dois 1.5 0.167 0 
2 tres 1.28 1.48 0.0891
3 um 1.9 0.76 0.390

If you want values for all numbers, not by column, just omit the group_by.

If you want to use your own function - no need since R supplies them in this case - but you could just substitute their names.

share|improve this answer

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

add a comment | 

You don't explain whether "of the dataframe" means "by column". Let's assume it does and use tidyr::gather() to reshape the data from wide to long, then dplyr::summarise() for the calculations. Assume the dataframe is named data1 and using moments::skewness:

library(tidyr)
library(dplyr)
library(moments)

data1 %>%
 gather(Var, Val) %>% 
 group_by(Var) %>% 
 summarise(Mean = mean(Val), 
 Vari = var(Val), 
 Skew = skewness(Val))

# A tibble: 3 x 4
 Var Mean Vari Skew
 <chr> <dbl> <dbl> <dbl>
1 dois 1.5 0.167 0 
2 tres 1.28 1.48 0.0891
3 um 1.9 0.76 0.390

If you want values for all numbers, not by column, just omit the group_by.

If you want to use your own function - no need since R supplies them in this case - but you could just substitute their names.

share|improve this answer

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

library(tidyr)
library(dplyr)
library(moments)

data1 %>%
 gather(Var, Val) %>% 
 group_by(Var) %>% 
 summarise(Mean = mean(Val), 
 Vari = var(Val), 
 Skew = skewness(Val))

# A tibble: 3 x 4
 Var Mean Vari Skew
 <chr> <dbl> <dbl> <dbl>
1 dois 1.5 0.167 0 
2 tres 1.28 1.48 0.0891
3 um 1.9 0.76 0.390

share|improve this answer

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749

answered Mar 8 at 1:24

neilfwsneilfws

18.6k53749