How to Use describe() Function in R

Renesh Bedre    2 minute read

The describe() is a helpful function for summarising the descriptive statistics for a data frame or matrix.

In contrast to the summary() function, the describe() function produces additional descriptive statistics such as sample count, range, standard error (se), standard deviation (sd), trimmed mean, and skew.

The describe() function is available in the psych R package and the basic syntax for the describe() function is,

describe(df)

In the above syntax, the df could be a data frame or matrix.

The following two examples illustrate how to use a describe() function to summarise the results for a data frame or matrix.

1. Summary statistics for the data frame

The following example shows how to use the describe() function on a data frame to summarise the statistical results.

# load package
library(psych)

# load example dataset
df <- read.table("https://reneshbedre.github.io/assets/posts/anova/onewayanova.txt", 
                 header = TRUE)

# view data frame
df
   A  B  C  D
1 25 45 30 54
2 30 55 29 60
3 28 29 33 51
4 36 56 37 62
5 29 40 27 73

# get descriptive statistics
describe(df)

  vars n mean    sd median trimmed   mad min max range  skew kurtosis   se
A    1 5 29.6  4.04     29    29.6  1.48  25  36    11  0.49    -1.39 1.81
B    2 5 45.0 11.20     45    45.0 14.83  29  56    27 -0.27    -1.85 5.01
C    3 5 31.2  3.90     30    31.2  4.45  27  37    10  0.39    -1.72 1.74
D    4 5 60.0  8.51     60    60.0  8.90  51  73    22  0.41    -1.61 3.81

If there are character variable in a data frame, the describe() function convert them into a numeric variable and summarise the descriptive statistic.

Note: By default, the describe() function drops NA values while providing a descriptive statistical summary of a data frame.

2. Summary statistics for matrix

The describe() function returns descriptive summary statistics for each column of the matrix (similar to a data frame).

If you convert a data frame to the matrix, the factor columns (characters) are converted to integer values.

# load package
library(psych)

# load example dataset
df <- read.table("https://reneshbedre.github.io/assets/posts/anova/onewayanova.txt", header = TRUE)

# convert to matrix
df_mat = data.matrix(df)

# get summary statistics
describe(df_mat)

  vars n mean    sd median trimmed   mad min max range  skew kurtosis   se
A    1 5 29.6  4.04     29    29.6  1.48  25  36    11  0.49    -1.39 1.81
B    2 5 45.0 11.20     45    45.0 14.83  29  56    27 -0.27    -1.85 5.01
C    3 5 31.2  3.90     30    31.2  4.45  27  37    10  0.39    -1.72 1.74
D    4 5 60.0  8.51     60    60.0  8.90  51  73    22  0.41    -1.61 3.81

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