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descstatsr
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Download and install descstatsr package within the R console
Install from CRAN:
install.packages("descstatsr")
Install from Github:
library("remotes")
install_github("cran/descstatsr")
Install by package version:
library("remotes")
install_version("descstatsr", "0.1.0")
Attach the package and use:
library("descstatsr")
Maintained by
Harish Kumar
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-10-12
Latest Update: 2018-10-12
Description:
It generates summary statistics on the input dataset using different descriptive univariate
statistical measures on entire data or at a group level. Though there are other packages which does
similar job but each of these are deficient in one form or other, in the measures generated, in
treating numeric, character and date variables alike, no functionality to view these measures on a
group level or the way the output is represented. Given the foremost role of the descriptive statistics
in any of the exploratory data analysis or solution development, there is a need for a more constructive,
structured and refined version over these packages. This is the idea behind the package and it brings
together all the required descriptive measures to give an initial understanding of the data quality,
distribution in a faster,easier and elaborative way.The function brings an additional capability to be
able to generate these statistical measures on the entire dataset or at a group level. It calculates measures
of central tendency (mean, median), distribution (count, proportion), dispersion (min, max, quantile,
standard deviation, variance) and shape (skewness, kurtosis). Addition to these measures, it provides information on
the data type, count on no. of rows, unique entries and percentage of missing entries. More importantly the measures
are generated based on the data types as required by them,rather than applying numerical measures on character and
data variables and vice versa. Output as a dataframe object gives a very neat representation, which often is useful
when working with a large number of columns. It can easily be exported as csv and analyzed further or presented as a
summary report for the data.
How to cite:
Harish Kumar (2018). descstatsr: Descriptive Univariate Statistics. R package version 0.1.0, https://cran.r-project.org/web/packages/descstatsr. Accessed 18 Feb. 2025.
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Complete documentation for descstatsr
Functions, R codes and Examples using
the descstatsr R package
Some associated functions: desc_stats .
Some associated R codes: desc_stats.R . Full descstatsr package functions and examples
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