README.md
In cursory: A Cursory Look at Variables

cursory

The goal of cursory is to make it easier to summarize data and look at your variables. It builds off dplyr and purrr. It is also compatible with dbplyr and remote data.

You can install the released version of cursory from CRAN with:

install.packages("cursory")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("halpo/cursory")

This is a basic example which shows you how to solve a common problem:

library(dplyr)
library(cursory)
data(iris)

## basic summary statistics for each variable in a data frame.
cursory_all(group_by(iris, Species), lst(mean, median)) %>% ungroup()

| Variable | Species | mean | median | | :----------- | :--------- | ----: | -----: | | Sepal.Length | setosa | 5.006 | 5.00 | | Sepal.Length | versicolor | 5.936 | 5.90 | | Sepal.Length | virginica | 6.588 | 6.50 | | Sepal.Width | setosa | 3.428 | 3.40 | | Sepal.Width | versicolor | 2.770 | 2.80 | | Sepal.Width | virginica | 2.974 | 3.00 | | Petal.Length | setosa | 1.462 | 1.50 | | Petal.Length | versicolor | 4.260 | 4.35 | | Petal.Length | virginica | 5.552 | 5.55 | | Petal.Width | setosa | 0.246 | 0.20 | | Petal.Width | versicolor | 1.326 | 1.30 | | Petal.Width | virginica | 2.026 | 2.00 |


## summary statistics for only numeric variables. 
cursory_if(iris, is.numeric, lst(Mean = mean, 'Std. Deviation' = sd))

| Variable | Mean | Std. Deviation | | :----------- | -------: | -------------: | | Sepal.Length | 5.843333 | 0.8280661 | | Sepal.Width | 3.057333 | 0.4358663 | | Petal.Length | 3.758000 | 1.7652982 | | Petal.Width | 1.199333 | 0.7622377 |


## summary statistics for specific variables. 
cursory_at(iris, vars(ends_with("Length")), var)

| Variable | var | | :----------- | --------: | | Sepal.Length | 0.6856935 | | Petal.Length | 3.1162779 |

`table_1`

The cursory package also provides a table_1 function that allows for describing variables of a dataset for different subsets automatically. This is useful in creating the very common demographics “table 1”.

table_1(iris, Species)

| Variable | Level | (All) | setosa | versicolor | virginica | | :----------- | :----- | :---- | :----- | :--------- | :-------- | | Sepal.Length | Min | 4.300 | 4.300 | 4.900 | 4.900 | | | Median | 5.800 | 5.000 | 5.900 | 6.500 | | | Mean | 5.843 | 5.006 | 5.936 | 6.588 | | | Max | 7.900 | 5.800 | 7.000 | 7.900 | | | SD | 0.828 | 0.352 | 0.516 | 0.636 | | Sepal.Width | Min | 2.000 | 2.300 | 2.000 | 2.200 | | | Median | 3.000 | 3.400 | 2.800 | 3.000 | | | Mean | 3.057 | 3.428 | 2.770 | 2.974 | | | Max | 4.400 | 4.400 | 3.400 | 3.800 | | | SD | 0.436 | 0.379 | 0.314 | 0.322 | | Petal.Length | Min | 1.000 | 1.000 | 3.000 | 4.500 | | | Median | 4.300 | 1.500 | 4.300 | 5.500 | | | Mean | 3.758 | 1.462 | 4.260 | 5.552 | | | Max | 6.900 | 1.900 | 5.100 | 6.900 | | | SD | 1.765 | 0.174 | 0.470 | 0.552 | | Petal.Width | Min | 0.100 | 0.100 | 1.000 | 1.400 | | | Median | 1.300 | 0.200 | 1.300 | 2.000 | | | Mean | 1.199 | 0.246 | 1.326 | 2.026 | | | Max | 2.500 | 0.600 | 1.800 | 2.500 | | | SD | 0.762 | 0.105 | 0.198 | 0.275 |

The table_1() function also tags the Variable column as a dontrepeat class column which make repeating values in columns not appear when formatted, so that tables are easier to read.