# glancedata

Whenever I start working on a dataset, I need to take a glance at the data to see how the data are or it the format is the one that I am expecting. I found myself coding similar lines over and over again with each data set I put my hands on. I decided to put that lines together in an R package so I and others can use them. I called it `glancedata`

.

There are already some cool R packages to summarize dataframes. The ones that I use more often are `skimr`

and `GGally`

.

## Installation

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

`install.packages("glancedata")`

## Functions

These are the main functions in the package. You can see their documentation with `help`

, e.g., `help("glance_data")`

.

`glance_data` |
Alternative to `summary` . Emphasizes missing data and binary variables. |

`glance_data_in_workbook` |
Similar to `glance_data` . Creates list of dataframes instead and saves XLSX file. |

`plot_numerical_vars` |
Creates a plot per numerical variable. It might be histogram, density plot, qqplot, violin plot or scatterplot. |

`plot_discrete_vars` |
Creates a plot per numerical variable. It might be histogram, density plot, qqplot, violin plot or scatterplot. |

## Example

You can copy and paste the code and use your own dataset. I am using the `mtcars`

dataframe.

```
library(glancedata)
## This will generate a dataframe
glance_data(mtcars)
## Create a list of dataframes. If you provide the `filename`
## parameter to be equal to, say, "myglance.xlsx", then it will create
## an Excel workbook and place the content of each dataframe in a
## separate sheet.
glance_data_in_workbook(mtcars)
## These are the types of plots for numerical variables
plot_numerical_vars(mtcars, plot_type = "density")
plot_numerical_vars(mtcars, plot_type = "pairwise")
plot_numerical_vars(mtcars, plot_type = "histogram")
plot_numerical_vars(mtcars, plot_type = "violin")
plot_numerical_vars(mtcars, plot_type = "boxplot")
plot_numerical_vars(mtcars, plot_type = "qqplot")
## ... And here are barplots for variables with only a few different
## values
plot_discrete_vars(mtcars)
plot_discrete_vars(mtcars, sort_by_frequency = TRUE)
```