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use mtcarz data
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‎R/ds-cross-table.R

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#' @section Deprecated Function:
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#' \code{ds_cross_table()} has been deprecated. Instead use \code{ds_cross_table()}.
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#' @examples
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#' k <- ds_cross_table(mtcars, cyl, am)
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#' k <- ds_cross_table(mtcarz, cyl, am)
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#' k
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#'
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#' # bar plots

‎R/ds-data-mtcarz.R

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#' mtcarz
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#'
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#' Copy of mtcars data set with modified variable types
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#'
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"mtcarz"

‎R/ds-describe.R

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#' @section Deprecated function:
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#' \code{tailobs()} has been deprecated. Instead use \code{ds_tailobs()}.
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#' @examples
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#' ds_tailobs(mtcars$mpg, 5)
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#' ds_tailobs(mtcars$mpg, 5, type = "high")
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#' ds_tailobs(mtcarz$mpg, 5)
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#' ds_tailobs(mtcarz$mpg, 5, type = "high")
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#' @export
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#' @seealso \code{\link[dplyr]{top_n}}
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#'

‎R/ds-freq-cont.R

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#' \code{freq_cont()} has been deprecated. Instead use \code{ds_freq_cont()}.
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#' @examples
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#' # frequency table
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#' ds_freq_cont(mtcars, mpg, 4)
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#' ds_freq_cont(mtcarz, mpg, 4)
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#'
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#' # histogram
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#' k <- ds_freq_cont(mtcars, mpg, 4)
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#' k <- ds_freq_cont(mtcarz, mpg, 4)
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#' hist(k)
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#' @seealso \code{link{ds_freq_table}} \code{link{ds_cross_table}}
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#' @export

‎R/ds-freq-table.R

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#' \code{freq_table()} has been deprecated. Instead use \code{ds_freq_table()}.
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#' @examples
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#' # frequency table
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#' mt <- mtcars
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#' mt$cyl <- as.factor(mt$cyl)
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#' ds_freq_table(mt, cyl)
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#' ds_freq_table(mtcarz, cyl)
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#'
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#' # barplot
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#' mt <- mtcars
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#' mt$cyl <- as.factor(mt$cyl)
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#' k <- ds_freq_table(mt, cyl)
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#' k <- ds_freq_table(mtcarz, cyl)
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#' barplot(k)
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#' @seealso \code{link{ds_freq_cont}} \code{link{ds_cross_table}}
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#' @export

‎R/ds-group-summary.R

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#' use \code{ds_group_summary()}.
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#' @examples
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#' # ds_group summary
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#' mt <- mtcars
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#' mt$cyl <- as.factor(mt$cyl)
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#' ds_group_summary(mt, cyl, mpg)
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#' ds_group_summary(mtcarz, cyl, mpg)
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#'
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#' # boxplot
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#' k <- ds_group_summary(mt, cyl, mpg)
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#' k <- ds_group_summary(mtcarz, cyl, mpg)
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#' boxplot(k)
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#' @seealso \code{link{ds_summary_stats}}
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#' @export

‎R/ds-mult-table.R

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#' \code{oway_tables()} and \code{tway_tables()} have been deprecated. Instead
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#' use \code{ds_oway_tables()} and \code{ds_tway_tables()}.
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#' @examples
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#' mt <- mtcars
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#' mt[, c(2, 8, 9)] <- lapply(mt[, c(2, 8, 9)], factor)
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#' # multiple one way tables
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#' ds_oway_tables(mt)
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#' ds_oway_tables(mtcarz)
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#'
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#' # multiple two way tables
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#' ds_tway_tables(mt)
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#' ds_tway_tables(mtcarz)
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#' @seealso \code{link{ds_freq_table}} \code{link{ds_cross_table}}
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#' @export
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#'

‎R/ds-multistats.R

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#' @section Deprecated Function:
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#' \code{multistats()} has been deprecated. Instead use \code{ds_multi_stats()}
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#' @examples
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#' ds_multi_stats(mtcars, mpg, disp, hp)
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#' ds_multi_stats(mtcarz, mpg, disp, hp)
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#' @export
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#'
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ds_multi_stats <- function(x, ...) {

‎R/ds-screener.R

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#' use \code{ds_screener()}.
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#' @examples
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#' # screen data
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#' mt <- mtcars
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#' mt[, c(2, 8:11)] <- lapply(mt[, c(2, 8:11)], factor)
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#' mt[sample(1:nrow(mt), 12), sample(1:ncol(mt), 6)] <- NA
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#' ds_screener(mt)
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#'
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#' # visualize missing data
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#' k <- ds_screener(mt)
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#' plot(k)
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#' ds_screener(mtcarz)
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#' @export
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#'
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ds_screener <- function(y) UseMethod('ds_screener')

‎R/ds-summary-stats.R

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#' \code{summary_stats()} has been deprecated. Instead use
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#' \code{ds_summary_stats()}.
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#' @examples
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#' ds_summary_stats(mtcars, mpg)
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#' ds_summary_stats(mtcarz, mpg)
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#' @seealso \code{\link[base]{summary}} \code{\link{ds_freq_cont}}
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#' \code{\link{ds_freq_table}} \code{\link{ds_cross_table}}
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#' @export
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summary_stats <- function(data) {
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.Deprecated("ds_summary_stats()")
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# ds_summary_stats(data)
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}
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‎README.Rmd

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## Usage
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##### Summary Statistics
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We will use a modified version of the `mtcars` data set in the below examples. The only difference between the data sets is related to the
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variable types.
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```{r load, eval=TRUE, echo=FALSE}
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library(descriptr)
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mtcars$cyl <- as.factor(mtcars$cyl)
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```
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```{r egdata}
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str(mtcarz)
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```
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##### Summary Statistics
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```{r descript1}
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ds_summary_stats(mtcars, mpg)
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ds_summary_stats(mtcarz, mpg)
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```
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##### Two Way Table
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```{r descript2}
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ds_cross_table(mtcars, cyl, gear)
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ds_cross_table(mtcarz, cyl, gear)
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```
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##### One Way Table
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```{r descript3}
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mt <- mtcars
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mt$cyl <- as.factor(mt$cyl)
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ds_freq_table(mt, cyl)
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ds_freq_table(mtcarz, cyl)
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```
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##### One Way Table (Continuous Data)
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```{r descript4}
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ds_freq_cont(mtcars, mpg)
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ds_freq_cont(mtcarz, mpg)
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```
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##### Group Summary
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```{r descript5}
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mt <- mtcars
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mt$cyl <- as.factor(mt$cyl)
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ds_group_summary(mt, cyl, mpg)
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ds_group_summary(mtcarz, cyl, mpg)
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```
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##### Multiple Variable Statistics
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```{r descriptr6}
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ds_multi_stats(mtcars, mpg, disp, hp)
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ds_multi_stats(mtcarz, mpg, disp, hp)
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```
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‎README.md

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## Usage
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We will use a modified version of the `mtcars` data set in the below
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examples. The only difference between the data sets is related to the
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variable types.
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``` r
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str(mtcarz)
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#> 'data.frame': 32 obs. of 11 variables:
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#> $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
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#> $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
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#> $ disp: num 160 160 108 258 360 ...
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#> $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
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#> $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
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#> $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
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#> $ qsec: num 16.5 17 18.6 19.4 17 ...
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#> $ vs : Factor w/ 2 levels "0","1": 1 1 2 2 1 2 1 2 2 2 ...
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#> $ am : Factor w/ 2 levels "0","1": 2 2 2 1 1 1 1 1 1 1 ...
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#> $ gear: Factor w/ 3 levels "3","4","5": 2 2 2 1 1 1 1 2 2 2 ...
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#> $ carb: Factor w/ 6 levels "1","2","3","4",..: 4 4 1 1 2 1 4 2 2 4 ...
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```
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##### Summary Statistics
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``` r
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ds_summary_stats(mtcars, mpg)
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ds_summary_stats(mtcarz, mpg)
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#> Univariate Analysis
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#>
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#> N 32.00 Variance 36.32
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##### Two Way Table
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``` r
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ds_cross_table(mtcars, cyl, gear)
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ds_cross_table(mtcarz, cyl, gear)
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#> Cell Contents
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#> |---------------|
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#> | Frequency |
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##### One Way Table
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``` r
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mt <- mtcars
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mt$cyl <- as.factor(mt$cyl)
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ds_freq_table(mt, cyl)
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ds_freq_table(mtcarz, cyl)
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#> Variable: cyl
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#> |--------------------------------------------------------------------------|
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#> | Cumulative Cumulative |
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##### One Way Table (Continuous Data)
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``` r
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ds_freq_cont(mtcars, mpg)
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ds_freq_cont(mtcarz, mpg)
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#> Variable: mpg
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#> |-----------------------------------------------------------------------|
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#> | Bins | Frequency | Cum Frequency | Percent | Cum Percent |
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##### Group Summary
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``` r
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mt <- mtcars
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mt$cyl <- as.factor(mt$cyl)
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ds_group_summary(mt, cyl, mpg)
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ds_group_summary(mtcarz, cyl, mpg)
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#> mpg by cyl
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#> -----------------------------------------------------------------------------------------
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#> | Statistic/Levels| 4| 6| 8|
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##### Multiple Variable Statistics
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``` r
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ds_multi_stats(mtcars, mpg, disp, hp)
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ds_multi_stats(mtcarz, mpg, disp, hp)
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#> # A tibble: 3 x 16
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#> vars min max mean t_mean median mode range variance stdev skew
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#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>

‎_pkgdown.yml

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illustrate the functions as well as for running tests.
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contents:
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- hsb
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- mtcarz

‎data/mtcarz.rda

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