R Markdown

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When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

library(tidyverse)

filter(mpg, cty>=20) 
## # A tibble: 56 × 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 manu… f        21    29 p     comp…
##  2 audi         a4           2    2008     4 manu… f        20    31 p     comp…
##  3 audi         a4           2    2008     4 auto… f        21    30 p     comp…
##  4 audi         a4 quattro   2    2008     4 manu… 4        20    28 p     comp…
##  5 chevrolet    malibu       2.4  2008     4 auto… f        22    30 r     mids…
##  6 honda        civic        1.6  1999     4 manu… f        28    33 r     subc…
##  7 honda        civic        1.6  1999     4 auto… f        24    32 r     subc…
##  8 honda        civic        1.6  1999     4 manu… f        25    32 r     subc…
##  9 honda        civic        1.6  1999     4 manu… f        23    29 p     subc…
## 10 honda        civic        1.6  1999     4 auto… f        24    32 r     subc…
## # ℹ 46 more rows
mpg_eff <- filter(mpg, cty>=20) 
view(mpg_eff)

mpg_ford <- filter(mpg,manufacturer =="ford" ) 
view(mpg_ford)

mpg_metric <- mutate(mpg, cty_metric = 0.42144 * cty)
glimpse(mpg_metric)
## Rows: 234
## Columns: 12
## $ 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…
## $ cty_metric   <dbl> 7.58592, 8.85024, 8.42880, 8.85024, 6.74304, 7.58592, 7.5…
#redoing the above function but with a pipe

mpg_metric <- mpg %>%
  mutate(cty_metric = 0.42144 * cty) 

view(mpg)

#takes mpg, groups it by class, then summarizes based on the mean

mpg %>% 
  group_by(class) %>% 
  summarise(mean(cty),
            mean(hwy),
            median(cty))
## # A tibble: 7 × 4
##   class      `mean(cty)` `mean(hwy)` `median(cty)`
##   <chr>            <dbl>       <dbl>         <dbl>
## 1 2seater           15.4        24.8            15
## 2 compact           20.1        28.3            20
## 3 midsize           18.8        27.3            18
## 4 minivan           15.8        22.4            16
## 5 pickup            13          16.9            13
## 6 subcompact        20.4        28.1            19
## 7 suv               13.5        18.1            13
ggplot(mpg, aes(x=cty))+
         geom_histogram() + 
          labs (x="City Milage")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(mpg, aes(x=cty))+
  geom_freqpoly() + 
  labs (x="City Milage")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(mpg, aes(x=cty))+
  geom_histogram() + 
  geom_freqpoly()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

  labs (x="City Milage")
## $x
## [1] "City Milage"
## 
## attr(,"class")
## [1] "labels"
ggplot(mpg, aes(x=cty,
                y=hwy))+
  geom_point() + 
  geom_smooth (method="lm")
## `geom_smooth()` using formula = 'y ~ x'

ggplot(mpg, aes(x=cty,
                y=hwy,
                colour = class))+
  geom_point()

ggplot(mpg, aes(x=cty,
                y=hwy,
                colour = class))+
  geom_point() + 
  scale_color_brewer(palette = "Dark2")

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.