tidysummary: Create a tidy summary of a data frame

In peterdalle/tidysummary: Show Summaries of Data Frames

Create a tidy summary of a data frame

Description

Create a summary (small, medium or large) of a data frame.

Usage

tidysummary(x, size = "small", digits = 2)

Arguments

x	a data.frame to generate a summary for. Can also be an atomic vector (numeric, factor, boolean etc.).
size	how large the summary should be. Either small, medium or large (or simply s, m or l).
digits	the number of decimal places for rounding. Can be an integer or NULL (no rounding).

Details

The returned data frame has the following columns:

column	Name of the column
n	Number of observations
class	Data type
min	Minimum value
max	Maximum value
mean	Mean value
sd	Standard deviation
unique	Number of unique values (includes NA)
median	Median value
na	Number of NAs (missing values)
mode	Most frequent value
quant25	25 percent quantile
quant75	75 percent quantile
levels	Number of factor levels (only relevant for factors)
head	Top (first) value of the data frame
tail	Bottom (last) value of the data frame
se	Standard error
skewness	Skewness
kurtosis	Kurtosis
bytes	Size in bytes of the memory usage of the column

Note:

• For character vectors, the text length will be used to calculate the statistics.

• Missing values will be automatically removed before any statistical summaries are calculated

• Statistical summaries are produced using base R functions with defaults. Kurtosis and skewness is produced using code adapted from the moments package (https://cran.r-project.org/web/packages/moments/index.html).

Value

A data frame with one row per column.

See Also

to_markdown(), to_latex(), to_html(), to_json(), to_csv(), to_excel()

Examples

# Summary for data frame
tidysummary(iris)
tidysummary(iris, "medium")
tidysummary(iris, digits=2)

# Summary for atomic vector
tidysummary(iris$Sepal.Length, "large")

# Convert summary to Markdown
output <- tidysummary(iris)
to_markdown(output)

peterdalle/tidysummary documentation built on March 27, 2022, 4:30 p.m.