In this lab you can use the interactive console to explore but please record your commands here. Remember anything you type here can be “sent” to the console with Cmd-Enter (OS-X) or Cntr-Enter (Windows/Linux) (But only in side the {r} areas).

Part 1

Check to see if you have the mpg dataset [hint: it’s in the ggplot2 package].

mpg

## # A tibble: 234 × 11
##    manufacturer model      displ  year   cyl trans drv     cty   hwy fl    class
##    <chr>        <chr>      <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
##  1 audi         a4           1.8  1999     4 auto… f        18    29 p     comp…
##  2 audi         a4           1.8  1999     4 manu… f        21    29 p     comp…
##  3 audi         a4           2    2008     4 manu… f        20    31 p     comp…
##  4 audi         a4           2    2008     4 auto… f        21    30 p     comp…
##  5 audi         a4           2.8  1999     6 auto… f        16    26 p     comp…
##  6 audi         a4           2.8  1999     6 manu… f        18    26 p     comp…
##  7 audi         a4           3.1  2008     6 auto… f        18    27 p     comp…
##  8 audi         a4 quattro   1.8  1999     4 manu… 4        18    26 p     comp…
##  9 audi         a4 quattro   1.8  1999     4 auto… 4        16    25 p     comp…
## 10 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
## # … with 224 more rows

What data class is mpg?

class(mpg)

## [1] "tbl_df"     "tbl"        "data.frame"

How many observations (rows) and variables (columns) are in the mpg dataset?

dim(mpg)

## [1] 234  11

nrow(mpg)

## [1] 234

ncol(mpg)

## [1] 11

glimpse(mpg)

## Rows: 234
## Columns: 11
## $ manufacturer <chr> "audi", "audi", "audi", "audi", "audi", "audi", "audi", "…
## $ model        <chr> "a4", "a4", "a4", "a4", "a4", "a4", "a4", "a4 quattro", "…
## $ displ        <dbl> 1.8, 1.8, 2.0, 2.0, 2.8, 2.8, 3.1, 1.8, 1.8, 2.0, 2.0, 2.…
## $ year         <int> 1999, 1999, 2008, 2008, 1999, 1999, 2008, 1999, 1999, 200…
## $ cyl          <int> 4, 4, 4, 4, 6, 6, 6, 4, 4, 4, 4, 6, 6, 6, 6, 6, 6, 8, 8, …
## $ trans        <chr> "auto(l5)", "manual(m5)", "manual(m6)", "auto(av)", "auto…
## $ drv          <chr> "f", "f", "f", "f", "f", "f", "f", "4", "4", "4", "4", "4…
## $ cty          <int> 18, 21, 20, 21, 16, 18, 18, 18, 16, 20, 19, 15, 17, 17, 1…
## $ hwy          <int> 29, 29, 31, 30, 26, 26, 27, 26, 25, 28, 27, 25, 25, 25, 2…
## $ fl           <chr> "p", "p", "p", "p", "p", "p", "p", "p", "p", "p", "p", "p…
## $ class        <chr> "compact", "compact", "compact", "compact", "compact", "c…

Select the manufacturer, model and year columns from the mpg dataset.

select(mpg, manufacturer, model, year)

## # A tibble: 234 × 3
##    manufacturer model       year
##    <chr>        <chr>      <int>
##  1 audi         a4          1999
##  2 audi         a4          1999
##  3 audi         a4          2008
##  4 audi         a4          2008
##  5 audi         a4          1999
##  6 audi         a4          1999
##  7 audi         a4          2008
##  8 audi         a4 quattro  1999
##  9 audi         a4 quattro  1999
## 10 audi         a4 quattro  2008
## # … with 224 more rows

Identify the subset of cars/rows where city fuel economy (cty) is greater than 20 and highway fuel economy (hwy) is greater than 30. Assign this output to an object called eff. How many cars/rows are present?

eff <- mpg %>% filter(cty > 20, hwy > 30)
dim(eff)

## [1] 21 11

How many fuel efficient cars (in the eff dataset) were manufactured in the year 1999?

eff %>% filter(year == 1999) %>% nrow()

## [1] 9

Filter cars from the overall mpg dataset that do not have 4 cylinder engines. How many cars/rows are there?

mpg %>% filter(cyl != 4) %>% nrow()

## [1] 153

Filter cars to only those in the “suv” or “minivan” class. How many cars/rows are there?

# both give same result
mpg %>% filter(class %in% c("suv", "minivan")) %>% nrow()

## [1] 73

mpg %>% filter(class =="suv" | class == "minivan") %>% nrow()

## [1] 73

Filter cars with displacements (displ) greater than 4 and that are all 4 wheel drive (drv). How many cars/rows are there.

mpg %>% filter(displ > 4, drv == "4") %>% nrow()

## [1] 49

Data Subsetting, Part 1 - Lab

Part 1