README.Rmd

---
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(hitchr)
library(tidyverse)
library(cowplot)
random_sample <- iidr(10)
random_NAs <- iidr(10, na_prob = 0.2)
```

<!-- README.md is generated by README.Rmd. Please edit .Rmd file. -->

# hitchr <img src="./README_files/thumb.jpg" align="right" height="139" />

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Random sample generator based on Douglas Adams' The Hitchhiker's Guide to the Galaxy. It also allows random insertion of NAs in a dataset (inspired by the
[wakefield](https://github.com/trinker/wakefield) package).

:warning: Currently in development. No warranty for deprecated functions as I 
come up with names I like better.

To install:

```{r eval=FALSE}
devtools::install_github("bbartholdy/hitchr")
```

## :exclamation:Important Note:exclamation:

This package deals with the concept of 'race' in a strictly biological sense;
i.e., there is no way to biologically distinguish discrete races within the 
*Homo sapiens* species (despite claims to the contrary).

This should not distract from the very real concept of social 'race', and the social
injustice that currently persists across the globe.

[BlackLivesMatter](https://blacklivesmatter.com/)

[StopAsianHate](https://www.stopasianhate.info/)

## Examples

```{r eval=FALSE}
hitchr::infinite_improbability_drive(10) # generates a random sample of 10 individuals
# or
hitchr::iidr(10)
```

```{r echo=FALSE}
knitr::kable(random_sample)
```

Missing values can be inserted symmetrically (symm = T): equal number of NAs in 
each column, or asymmetrically (symm = F): random distribution in the columns.
To insert missing values, specify the desired proportion of missing values (0 to 1).

```{r eval=FALSE}
hitchr::iidr(10, na_prob = 0.2, symm = T)
```

```{r echo=FALSE}
knitr::kable(random_NAs)
```

Races currently available:

```{r race-index}
hitchr:::race_index()
```

Stats currently available:

```{r stats-index}
hitchr:::stats_index()
```


Sexual dimorphism in the height of males and females of different races:

```{r sex-dim}
hitchr_sample <- hitchr::iidr(1000)
hitchr_sample %>%
  filter(sex == "male" | sex == "female") %>%
  group_by(race) %>%
  ggplot(aes(x = sex, y = height, fill = race)) +
    geom_violin() +
    theme_minimal() +
    scale_fill_viridis_d() +
    facet_wrap(~ race) +
    theme(legend.position = "none")
```