01_wrangle.Rmd

---
title: "Wrangle"
author: "Evangeline Reynolds"
date: "2/13/2019"
output: html_document
---





---
### Let's see these at work


---

```{r wrangle_01, eval=F, echo=F, comment = " "}
gapminder %>%
  rename(per_capita_gdp = gdpPercap) %>%
  mutate(gdp = per_capita_gdp * pop) %>%
  select(continent, year, gdp, country) %>%
  filter(year == 2007) %>%
  group_by(continent) %>%
  summarize(mean_gdp = mean(gdp)) 
  
```

`r paste(knitr::knit(text = partial_knit_chunks("wrangle_01")), collapse = "\n")`



### Let's see these in action

---

```{r wrangle_02, eval=F, echo=F, comment = " "}
gapminder %>%
  mutate(americas = continent == "Americas") %>%
  filter(year %in% c(1997, 2007)) %>%
  filter(lifeExp > 80 | lifeExp < 40) %>%
  mutate(large_pop = pop >= 10000000) %>%
  filter(gdpPercap > 20000 & pop > 1000000) 
```
`r paste(knitr::knit(text = partial_knit_chunks("wrangle_02")), collapse = "\n")`



---
## A few more manipulation functions


- distinct() *returning unique cases*
- case_when() *recoding variables, used with mutate*


---


```{r wrangle_03, eval=F, echo=F, comment = " "}
gapminder %>%
  select(year) %>%
  distinct()
```


`r paste(knitr::knit(text = partial_knit_chunks("wrangle_03")), collapse = "\n")`


---


```{r wrangle_04, eval=F, echo=F, comment = " "}
gapminder %>%
  filter(year == 2007) %>%
  select(country, lifeExp) %>% 
  mutate(life_exp_cat = case_when(lifeExp >= 70 ~ "long", lifeExp < 70 ~ "short")) %>% 
  arrange(lifeExp)
```

`r paste(knitr::knit(text = partial_knit_chunks("wrangle_04")), collapse = "\n")`

---


```{r wrangle_05, eval=F, echo=F, comment = " "}
gapminder %>%
  group_by(year) %>%
  tally()
```

`r paste(knitr::knit(text = partial_knit_chunks("wrangle_05")), collapse = "\n")`


---