dplyr_Basics.rmd

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# dplyr Basics

dplyr is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges:

* mutate() adds new variables that are functions of existing variables
* select() picks variables based on their names.
* filter() picks cases based on their values.
* summarise() reduces multiple values down to a single summary.
* arrange() changes the ordering of the rows.

## Loading Packages and Data
```{r LibraryData}
library(tidyverse)
data("starwars")
help("starwars")
```

## Filter
filters information based on a value (remember to use ==)

```{r FilterExample}
filter(starwars,films=="The Force Awakens")
ForceAwakens <- filter(starwars,films=="The Force Awakens")
```

## Arrange
changes the ordering of the rows

```{r ArrangeExample}
arrange(ForceAwakens,name)
ForceAwakens <- arrange(ForceAwakens,name)
```

## Mutate
adds new variables that are functions of existing variables

```{r MutateExample}
Droid <- filter(starwars,species=="Droid")

mutate(Droid,mass_lbs = mass*2.2)
Droid <- mutate(Droid,mass_lbs = mass*2.2)
```

# Select
picks variables based on their names

```{r SelectExample}
Droid2 <- select(Droid,name,height,mass_lbs,homeworld)
Droid3 <- select(Droid,name,height,mass_lbs,homeworld,everything())
```

# Summarize
reduces multiple values down to a single summary

```{r SummarizeExample}
summarize(starwars,mass=mean(mass,na.rm=TRUE))

starwars_summary <- group_by(starwars,species)
summarize(starwars_summary,mass=mean(mass,na.rm=TRUE))
```