_notes_to_myself.Rmd

---
title: "_notes_to_myself"
author: "Martin Monkman"
date: "02/01/2022"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## publishing

a two-step process:

1. render

```{r}
bookdown::render_book()
```

2. publish to bookdown.org

```{r}

bookdown::publish_book(name = "DataAnalyticsCodingFundamentals", account = "martin_monkman")

```


## data cleaning resources

https://twitter.com/CDelawalla/status/1516026363484033027


Simultaneous use of multiple imputation for missing data and disclosure limitation
https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X20040027755




## Tangent: Arguments within functions

Virtually every function we use has default arguments, and options to change those. This allows us to use one function for a variety of circumstances. Instead of having separate functions to split a variable into its quartiles (four parts), quintiles (five parts), deciles (ten parts), and so on, there is one function that uses the generic name for this process: quantile. 

The default setting of the `quantile()` function splits the distribution into four parts, known as _quartiles_. This is the most common quantile used to summarize a distribution.

```{r}

quantile(gapminder$lifeExp)

```


If you want other groupings, the function has arguments that allow you define those. For example, if you want deciles—10 groups, each with 10% of the cases—the second example shows how to do that.


```{r}


# deciles
quantile(gapminder$lifeExp, probs = seq(0, 1, 0.10))

```