Data Wrangling with R: Day 1

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.item.center[

# <span style="text-shadow: 2px 2px 30px white;">Data Wrangling with R: Day 1</span>

]

.center.shade_black.animated.bounceInUp.slower[
<br><br>
## <span style="color: #ccf2ff; text-shadow: 10px 10px 100px white;">Data manipulation with `dplyr`</span>

<br>

Presented by Emi Tanaka

Department of Econometrics and Business Statistics

<img src="images/monash-one-line-reversed.png" style="width:500px"><br>
<span><i class="fas  fa-envelope faa-float animated "></i></span>  emi.tanaka@monash.edu
<span><i class="fab  fa-twitter faa-float animated faa-fast "></i></span>  @statsgen

.bottom_abs.width100.bg-black[
1st December 2020 @ Statistical Society of Australia | Zoom
]

]

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---

# Grammar of data manipulation

```r
library(dplyr) # or library(tidyverse)
```
* `dplyr` is a core package in `tidyverse` 
* The earlier concept of `dplyr` (first on CRAN in 2014-01-29) was implemented in `plyr` (first on CRAN in 2008-10-08)
* The functions in `dplyr` has been evolving frequently but `dplyr` v1.0.0 was released on CRAN in 2020-05-29
* This new version contained new "verbs"
* The major release suggests that functions in `dplyr` are maturing and thus the user interface is unlikely to change

.footnote[
Hadley Wickham, Romain François, Lionel Henry and Kirill Müller
  (2020). dplyr: A Grammar of Data Manipulation. R package version
  1.0.2. 
  
Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data
  Analysis. Journal of Statistical Software, 40(1), 1-29.
]

---

# Lifecycle

.grid[
.item[
<br>
<img src="https://raw.githubusercontent.com/r-lib/lifecycle/master/vignettes/figures/lifecycle.svg" width = "550px">
]
.item[

* Functions (and sometimes arguments of functions) in `tidyverse` packages often are labelled with a badge like above
* Find definitions of badges [here](https://lifecycle.r-lib.org/articles/lifecycle.html)
* Check out documentations below

```r
help(mutate, package = "dplyr")
help(mutate_each, package = "dplyr")
```

]

.footnote[
Lionel Henry (2020). lifecycle: Manage the Life Cycle of your
  Package Functions. R package version 0.2.0.
]

---

# `dplyr` "verbs"

* The main functions of `dplyr` include: 
<center>
<table style="width:60%">
  <tr>
    <td><code>arrange</code></td>
    <td><code>select</code></td>
    <td><code>mutate</code></td>
  </tr>
  <tr>
    <td><code>rename</code></td>
    <td><code>group_by</code></td>
    <td><code>summarise</code></td>
  </tr>
</table>
</center>
--

* Notice that these functions are _verbs_
--

* Functions in `dplyr` generally have the form:

* I.e., the first argument `data` is a `data.frame` object
--

* What do you think the following will do?

{{content}}
]
--

`arrange(mtcars, wt)`

---

# Pipe operator %>%

* Almost all tidyverse packages import the `magrittr` package to use `%>%`

.footnote[
Stefan Milton Bache and Hadley Wickham (2020). magrittr: A
  Forward-Pipe Operator for R. R package version 2.0.1.
]
--

* `x %>% f(y)` is the same as `f(x, y)`
--

* `x %>% f(y) %>% g(z)` is the same as `g(f(x, y), z)`
--

* When you see the pipe operator `%>%`, read it as "and then"
--

```r
mtcars %>%                          # take mtcars data, and then
 rename(miles_per_gallon = mpg) %>% # rename mpg as miles_per_gallon, and then
 arrange(wt)                        # arrange row by wt
```

```
##                     miles_per_gallon cyl  disp  hp drat    wt  qsec vs am gear
## Lotus Europa                    30.4   4  95.1 113 3.77 1.513 16.90  1  1    5
## Honda Civic                     30.4   4  75.7  52 4.93 1.615 18.52  1  1    4
## Toyota Corolla                  33.9   4  71.1  65 4.22 1.835 19.90  1  1    4
## Fiat X1-9                       27.3   4  79.0  66 4.08 1.935 18.90  1  1    4
## Porsche 914-2                   26.0   4 120.3  91 4.43 2.140 16.70  0  1    5
## Fiat 128                        32.4   4  78.7  66 4.08 2.200 19.47  1  1    4
## Datsun 710                      22.8   4 108.0  93 3.85 2.320 18.61  1  1    4
## Toyota Corona                   21.5   4 120.1  97 3.70 2.465 20.01  1  0    3
## Mazda RX4                       21.0   6 160.0 110 3.90 2.620 16.46  0  1    4
## Ferrari Dino                    19.7   6 145.0 175 3.62 2.770 15.50  0  1    5
## Volvo 142E                      21.4   4 121.0 109 4.11 2.780 18.60  1  1    4
## Mazda RX4 Wag                   21.0   6 160.0 110 3.90 2.875 17.02  0  1    4
## Merc 230                        22.8   4 140.8  95 3.92 3.150 22.90  1  0    4
## Ford Pantera L                  15.8   8 351.0 264 4.22 3.170 14.50  0  1    5
## Merc 240D                       24.4   4 146.7  62 3.69 3.190 20.00  1  0    4
## Hornet 4 Drive                  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3
## AMC Javelin                     15.2   8 304.0 150 3.15 3.435 17.30  0  0    3
## Hornet Sportabout               18.7   8 360.0 175 3.15 3.440 17.02  0  0    3
## Merc 280                        19.2   6 167.6 123 3.92 3.440 18.30  1  0    4
## Merc 280C                       17.8   6 167.6 123 3.92 3.440 18.90  1  0    4
## Valiant                         18.1   6 225.0 105 2.76 3.460 20.22  1  0    3
## Dodge Challenger                15.5   8 318.0 150 2.76 3.520 16.87  0  0    3
## Duster 360                      14.3   8 360.0 245 3.21 3.570 15.84  0  0    3
## Maserati Bora                   15.0   8 301.0 335 3.54 3.570 14.60  0  1    5
## Merc 450SL                      17.3   8 275.8 180 3.07 3.730 17.60  0  0    3
## Merc 450SLC                     15.2   8 275.8 180 3.07 3.780 18.00  0  0    3
## Camaro Z28                      13.3   8 350.0 245 3.73 3.840 15.41  0  0    3
## Pontiac Firebird                19.2   8 400.0 175 3.08 3.845 17.05  0  0    3
## Merc 450SE                      16.4   8 275.8 180 3.07 4.070 17.40  0  0    3
## Cadillac Fleetwood              10.4   8 472.0 205 2.93 5.250 17.98  0  0    3
## Chrysler Imperial               14.7   8 440.0 230 3.23 5.345 17.42  0  0    3
## Lincoln Continental             10.4   8 460.0 215 3.00 5.424 17.82  0  0    3
##                     carb
## Lotus Europa           2
## Honda Civic            2
## Toyota Corolla         1
## Fiat X1-9              1
## Porsche 914-2          2
## Fiat 128               1
## Datsun 710             1
## Toyota Corona          1
## Mazda RX4              4
## Ferrari Dino           6
## Volvo 142E             2
## Mazda RX4 Wag          4
## Merc 230               2
## Ford Pantera L         4
## Merc 240D              2
## Hornet 4 Drive         1
## AMC Javelin            2
## Hornet Sportabout      2
## Merc 280               4
## Merc 280C              4
## Valiant                1
## Dodge Challenger       2
## Duster 360             4
## Maserati Bora          8
## Merc 450SL             3
## Merc 450SLC            3
## Camaro Z28             4
## Pontiac Firebird       2
## Merc 450SE             3
## Cadillac Fleetwood     4
## Chrysler Imperial      4
## Lincoln Continental    4
```

---

# Lazy and non-standard evaluation

* Remember in Base R:

```r
subset(mtcars, mpg > 31)
```

```
##                 mpg cyl disp hp drat    wt  qsec vs am gear carb
## Fiat 128       32.4   4 78.7 66 4.08 2.200 19.47  1  1    4    1
## Toyota Corolla 33.9   4 71.1 65 4.22 1.835 19.90  1  1    4    1
```
--

* But the second argument cannot be evaluated:

```r
mpg > 31
```

```
## Error in eval(expr, envir, enclos): object 'mpg' not found
```
--

* R employs what is called **lazy evaluation** for function inputs 
--

* **Non-standard evaluation** uses this feature to capture the input expression within the function and evaluate only when requested

---

# Tidy evaluation .font_small[.font_small[Part] 1]

* Tidy evaluation builds on the lazy and non-standard evaluation and is implemented in `rlang`
* All core tidyverse packages import `rlang`
* So what does it do?
* Let's consider `filter`, the Tidyverse version of `subset`

```r
filter(mtcars, mpg > 31)
```

```
##                 mpg cyl disp hp drat    wt  qsec vs am gear carb
## Fiat 128       32.4   4 78.7 66 4.08 2.200 19.47  1  1    4    1
## Toyota Corolla 33.9   4 71.1 65 4.22 1.835 19.90  1  1    4    1
```

* <i class="fas fa-exclamation-triangle animated flash red"></i> If you get an error using `filter`, replace it with `dplyr::filter`<br> .font_small[for those interested, `dplyr::filter` is a conflict with `stats::filter` and it may be using `stats::filter` instead... I've fallen into this trap so many times!]

.footnote[
Lionel Henry and Hadley Wickham (2020). rlang: Functions for Base
  Types and Core R and 'Tidyverse' Features. R package version
  0.4.8.
]

---

# Tidy evaluation .font_small[.font_small[Part] 2]

* Suppose we have a silly function that subsets `mtcars` for a given condition

```r
myCarSubset <- function(cond) subset(mtcars, cond)
myCarFilter <- function(cond) filter(mtcars, cond)
```

* This causes an issue because `cond` is evaluated before it is parsed into `subset` or `filter`

```r
myCarSubset(mpg > 31)
```

```
## Error in eval(e, x, parent.frame()): object 'mpg' not found
```

```r
myCarFilter(mpg > 31)
```

```
## Error: Problem with `filter()` input `..1`.
## x object 'mpg' not found
## ℹ Input `..1` is `cond`.
```

---

# Tidy evaluation .font_small[.font_small[Part] 3]

* Functions that use non-standard evaluation is problematic

<code class ='r hljs remark-code'>myCarSubsetNew <- function(cond) subset(mtcars, <span style="background-color:#ffff7f">{{</span> cond <span style="background-color:#ffff7f">}}</span>)<br>myCarFilterNew <- function(cond) filter(mtcars, <span style="background-color:#ffff7f">{{</span> cond <span style="background-color:#ffff7f">}}</span>)<br><br>myCarSubsetNew(mpg > 31)</code>

```

## Error in eval(e, x, parent.frame()): object 'mpg' not found

```

<code class ='r hljs remark-code'>myCarFilterNew(mpg > 31)</code>

```

##                 mpg cyl disp hp drat    wt  qsec vs am gear carb
## Fiat 128       32.4   4 78.7 66 4.08 2.200 19.47  1  1    4    1
## Toyota Corolla 33.9   4 71.1 65 4.22 1.835 19.90  1  1    4    1

```

* .monash-blue[`{{ }}`] only works if the underlying function implements `rlang`

---

# Data masking .font_small[.font_small[Part] 1]

```r
ind <- 1:nrow(cars) # nrow(cars) = 50
subset(cars, ind > 49)
```

```
##    speed dist
## 50    25   85
```

```r
filter(cars, ind > 49)
```

```
##   speed dist
## 1    25   85
```
* For any variables that don't exist in the data, R searches the parental environment for evaluation.
]
.item[

{{content}}
]

]

```r
speed <- c(40, 51)
subset(cars, speed > 24)
```
{{content}}
--

```
##    speed dist
## 50    25   85
```
{{content}}
--

```r
filter(cars, speed > 24)
```
{{content}}
--

```
##   speed dist
## 1    25   85
```
{{content}}
--

* The variables in data take priority for reference over those in parental environment

---

# Data masking .font_small[.font_small[Part] 2]

<code class ='r hljs remark-code'>speed <- 1:nrow(cars)<br>filter(cars, <span style="background-color:#ffff7f">.data</span>$speed > 24)</code>

```

##   speed dist
## 1    25   85

```

<code class ='r hljs remark-code'>filter(cars, <span style="background-color:#ffff7f">.env</span>$speed > 24)</code>

```

##    speed dist
## 1     15   26
## 2     15   54
## 3     16   32
## 4     16   40
## 5     17   32
## 6     17   40
## 7     17   50
## 8     18   42
## 9     18   56
## 10    18   76
## 11    18   84
## 12    19   36
## 13    19   46
## 14    19   68
## 15    20   32
## 16    20   48
## 17    20   52
## 18    20   56
## 19    20   64
## 20    22   66
## 21    23   54
## 22    24   70
## 23    24   92
## 24    24   93
## 25    24  120
## 26    25   85

```

]
.item[

* In Tidyverse, you can be explicit whether the variable is in the data or in the parental environment
* .monash-blue[`.data`] is a special pronoun referring to variables in the data parsed in the first argument
* .monash-blue[`.env`] is a special pronoun referring to variables in the environment (i.e. _not_ in the data parsed in the first argument)

]

---

# Tidy select .font_small[.font_small[Part] 1]

* Tidyverse packages generally use syntax from the `tidyselect` package for variable/column selection

```r
data(frog_signal, package = "dwexercise")
str(frog_signal) 
```

```
## 'data.frame':	535 obs. of  22 variables:
##  $ FrogID            : chr  "13196" "13197" "13198" "13206" ...
##  $ AlternativeCD     : num  28 27 31 33 26 31 33 28 29 34 ...
##  $ AlternativeCR     : num  12 15 13 15 11 6 15 12 14 12 ...
##  $ AlternativeDF     : num  2315 2304 2646 2281 2789 ...
##  $ AlternativeRA     : num  -10 -8 -12 -7 -8 -6 -12 -16 -12 -10 ...
##  $ AlternativePR     : num  46 49 43 50 57 51 46 55 56 45 ...
##  $ Standard1         : num  47 69 139 112 101 90 79 262 123 47 ...
##  $ Standard2         : num  46 44 102 112 101 68 41 237 106 62 ...
##  $ Standard3         : num  42 36 85 117 80 73 46 166 95 63 ...
##  $ Alternative1      : num  28 33 227 101 126 143 50 123 76 53 ...
##  $ Alternative2      : num  48 27 111 81 60 103 36 122 80 48 ...
##  $ Alternative3      : num  43 37 126 61 76 113 29 188 84 57 ...
##  $ TwoChoiceLatency  : num  134 47 273 281 110 107 187 113 70 63 ...
##  $ TwoChoice         : chr  "Standard" "Alternative" "Alternative" "Standard" ...
##  $ ChoiceBinary      : num  0 1 1 0 1 0 1 1 1 0 ...
##  $ StandardAverage   : num  45 50 109 114 94 77 55 222 108 57 ...
##  $ AlternativeAverage: num  40 32 155 81 87 120 38 144 80 53 ...
##  $ PhonotaxisScore   : num  0.0588 0.2195 -0.1742 0.1692 0.0387 ...
##  $ ScorePreference   : num  1 1 0 1 1 0 1 1 1 1 ...
##  $ Mismatch          : num  1 0 1 1 0 0 0 0 0 1 ...
##  $ SpeakerPosition   : chr  "left" "left" "left" "left" ...
##  $ FirstPresented    : chr  "Alternative" "Alternative" "Alternative" "Standard" ...
```

---

# Tidy select .font_small[.font_small[Part] 2]

<code class ='r hljs remark-code'>frog_signal %>% <br>&nbsp;<span style="background-color:#ffff7f">select</span>(Standard1, Standard2, Standard3)</code>

```

##     Standard1 Standard2 Standard3
## 1          47        46        42
## 2          69        44        36
## 3         139       102        85
## 4         112       112       117
## 5         101       101        80
## 6          90        68        73
## 7          79        41        46
## 8         262       237       166
## 9         123       106        95
## 10         47        62        63
## 11         95       117        84
## 12         56        52        41
## 13         41        51        57
## 14         57        41        30
## 15        144       128       166
## 16         68        41        52
## 17         62        68        84
## 18         52        89        63
## 19        101        80       106
## 20         69        80        57
## 21        134       112       102
## 22        167       118       123
## 23         51        52        62
## 24         73        84       136
## 25         89       106        90
## 26         55        78        63
## 27         74        77        83
## 28         69        70        95
## 29        117        73       111
## 30        244       242        85
## 31        208       102       124
## 32         95        42        45
## 33         62        46        57
## 34        148       134       112
## 35         96        57        67
## 36         28        36        39
## 37        101        52        95
## 38         58        68        62
## 39         73        63        62
## 40        173        69        38
## 41         84        90        87
## 42         51        62        50
## 43         95        95       104
## 44         52        57        69
## 45         74       107        82
## 46         47        52        69
## 47         68        60        41
## 48         58        52        52
## 49         47        40        47
## 50         51        52        41
## 51         96        99        79
## 52         63        41        24
## 53        102       129        52
## 54         80        57        62
## 55         62        52        56
## 56         46        57        98
## 57         87        82        83
## 58        100        59        62
## 59        111       101       111
## 60         96        79        68
## 61        177       156       145
## 62        150       131       134
## 63        172       107       116
## 64        133        95       117
## 65         68       100        79
## 66        112        69        79
## 67        112       125        90
## 68         68        56        57
## 69         90       215       117
## 70         90       200        89
## 71        113       127        95
## 72         47        47        48
## 73         50        97        91
## 74         96       112        80
## 75         80        38        74
## 76         78        63        59
## 77         29        48        47
## 78        105        63       151
## 79         42        41        53
## 80         59        68       155
## 81         91       101        74
## 82         68        86        91
## 83         53        47        47
## 84         64        73        62
## 85         83        57        90
## 86         52        36        55
## 87        117       106       101
## 88         84       100        86
## 89         57        57        33
## 90        101        61        69
## 91         51        70        57
## 92         63        68        84
## 93         41        52        48
## 94         67        95        90
## 95         53        47        75
## 96         75       103        86
## 97         53        79        47
## 98        155       129       139
## 99         79       128       107
## 100        95       120       112
## 101       120        41       134
## 102        41        52        80
## 103       150        90        86
## 104        63        96        97
## 105       130       100       102
## 106        83        53        39
## 107       118        64       102
## 108        80        79        53
## 109        96        85       118
## 110        58        47        62
## 111        70        81        59
## 112        31        67        64
## 113        65        75        89
## 114       113        88       102
## 115        58        85        70
## 116       129       117        90
## 117        69        80       117
## 118        95        69        63
## 119        69        63        68
## 120       168        79        56
## 121       171       188       139
## 122       106        90       101
## 123       136       129        79
## 124        73        80        80
## 125        79        47        51
## 126        47        41        35
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## 128        90        96        68
## 129        50        58        35
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## 131        57        36        63
## 132        68        52        52
## 133       154       161        79
## 134        68        76        53
## 135        53        32        46
## 136        62        86        61
## 137        89        68        54
## 138       113        53        53
## 139        58       268        96
## 140        58        52        53
## 141        53        92        58
## 142        32        74        90
## 143        47        57        75
## 144       155       136        96
## 145        62        41        50
## 146        41        37        74
## 147        79        41        52
## 148       112        86        89
## 149        88        57        85
## 150        57        30        53
## 151        96       123       158
## 152        63        84        89
## 153        72        90       100
## 154       107        74        52
## 155        79        52        68
## 156        52        42        45
## 157        26        57        74
## 158       106        95       255
## 159        34        52        45
## 160        73        89        62
## 161        41        45        39
## 162        29        51        47
## 163        58        68        67
## 164       119        68        30
## 165        51        63        56
## 166        62        77        78
## 167        35       106        82
## 168       133        90       172
## 169       139        91        68
## 170        85        51        55
## 171        57        34        67
## 172        25        66        56
## 173        69        73        75
## 174        78        79        49
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## 178        46        61        63
## 179        62        35        63
## 180        63        45        79
## 181        63        57       105
## 182       105        87        53
## 183        52        57        41
## 184        79        52       101
## 185       162        90        62
## 186        35        24        25
## 187        90        57        79
## 188        62       101        89
## 189        43        41        41
## 190        58        46        45
## 191       133        83        90
## 192        68        79        64
## 193        35        35        51
## 194        55        91        51
## 195        13        16        30
## 196        24        41        46
## 197        41        85        90
## 198        68       112        47
## 199        46       265        65
## 200        85        89       107
## 201        57        40        30
## 202        36        31        41
## 203        41        72        61
## 204        74        62        84
## 205        59        52        57
## 206        66        47        46
## 207       118        46        62
## 208        75        39       112
## 209        36        63        68
## 210        36        59        41
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## 212        69        63        57
## 213        62        52        67
## 214        64        57        52
## 215        53        46        39
## 216        74        57        73
## 217        74        84        80
## 218        35        19        34
## 219        38        46        68
## 220       106        91       102
## 221       107        46        83
## 222        89        73        78
## 223        25        69        41
## 224        51        63        37
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## 246        86        79       224
## 247        79        86        56
## 248        46        57        35
## 249        84        63        63
## 250        36        53       173
## 251        84        69        90
## 252        52        29        30
## 253        73        69        69
## 254        36        45        62
## 255        51        30        36
## 256       166        88        62
## 257        46        40        58
## 258        30        30        49
## 259        90        46        45
## 260        85        41        48
## 261        72        74       100
## 262       128        56        46
## 263        51        36        46
## 264        68        78        89
## 265       101       158        68
## 266        57        63        73
## 267        94        63        69
## 268        95        71        73
## 269       107        74        57
## 270        86        52        42
## 271        74       106        79
## 272        68        74        63
## 273        95        73        79
## 274        84        73        63
## 275        36        42        47
## 276        90       105       123
## 277        46        52        65
## 278        79        88        75
## 279       112        85        85
## 280       107       112       132
## 281        80       165        NA
## 282       177        85       100
## 283        58        53        57
## 284        63        84        69
## 285        79        68        90
## 286        63        79        57
## 287        62        80        74
## 288        84        58        79
## 289        94       102        79
## 290       117        95       102
## 291        56       107        52
## 292       135       101        79
## 293       200       167       199
## 294        96        58        98
## 295        80        58        73
## 296        52        47        60
## 297        52        46        54
## 298       150       134        92
## 299        74        75        83
## 300       106       116       139
## 301        99        74        90
## 302        78        46        29
## 303        52        41        56
## 304        61        46        60
## 305       117       260        79
## 306       117       100        94
## 307       148        90       139
## 308        86        81        79
## 309       112        80        93
## 310        52        57        57
## 311        74        73        62
## 312        68        83        78
## 313        40        41        58
## 314        62        54        56
## 315        40        46        40
## 316        46        57        57
## 317       106        89        40
## 318        63        46        73
## 319        62        94        79
## 320        84        69        68
## 321        56        62        52
## 322        38        64        72
## 323        68        60        61
## 324        46        46        73
## 325       117       168        73
## 326       150        79        67
## 327        79        62        63
## 328        88        78        73
## 329        84        63        79
## 330        51        53        90
## 331        84        78        67
## 332        89        84        73
## 333       101        45        52
## 334        90       104        78
## 335        84        93        89
## 336        40        68        47
## 337        84       118       112
## 338        61       106        68
## 339        74        61        74
## 340        51        52        47
## 341        89        77        90
## 342        62        57        57
## 343        43        52        38
## 344        68        56        53
## 345        80        79        73
## 346        80        52        63
## 347        30        35        45
## 348        95        72        57
## 349        67       123        80
## 350        74        74        80
## 351        62        94       133
## 352        25        52        65
## 353       111        58        52
## 354        59        55        50
## 355        44        61        47
## 356        46        46        40
## 357        68        72        55
## 358       100        61       167
## 359        68       112        86
## 360        63        74       123
## 361        79        52        56
## 362        58        41        53
## 363        52        42        47
## 364        53        67        88
## 365        33        47        63
## 366        69        74        91
## 367        86        85        74
## 368        64        52        91
## 369        64        73        52
## 370       166        77        69
## 371        68        62        58
## 372        73        64        57
## 373        78       100        80
## 374        79        63        52
## 375        30        56        62
## 376        57        52        46
## 377        30        29        31
## 378        42        46        57
## 379        56        58        57
## 380       172       128        79
## 381        52        46        57
## 382        41        52        52
## 383       112        57        57
## 384        79        90        90
## 385        68        85        68
## 386        57        68        79
## 387        95       107       111
## 388        74        63        74
## 389        66        74        74
## 390        73        48        50
## 391        52        69        30
## 392        58        37        68
## 393        90       107        69
## 394        57        63       117
## 395        62        94        79
## 396        68        67        46
## 397       139       122       106
## 398       106        62        62
## 399        68        57        57
## 400        36        64        75
## 401        74        59        47
## 402        70        85        96
## 403        53        52        63
## 404        80        85       118
## 405        74        47        63
## 406        79        42        58
## 407        75        72       106
## 408        52        90        78
## 409        47        53        63
## 410        46        46        28
## 411       118       150       160
## 412       165        79        67
## 413        78        57        57
## 414        95        76        57
## 415        94        51        59
## 416        66        57        45
## 417        74        62        46
## 418        39        54        40
## 419        95        85       145
## 420        73        58       182
## 421       182       139       106
## 422        62        51        62
## 423       139        75       113
## 424        89       106       259
## 425        99        57        69
## 426        58        91        59
## 427        42        36        54
## 428        57        85        64
## 429        64        72       183
## 430        85        75        70
## 431       185        69        52
## 432        91        58       102
## 433       127       123       106
## 434        85        52        90
## 435        67        96        62
## 436        85        57       135
## 437       123        73        84
## 438       100        40        39
## 439       160       134        83
## 440        58        51        52
## 441        62        46        57
## 442        73        84        63
## 443        89        63        62
## 444        44        57        74
## 445        68        74        63
## 446       100        63        52
## 447       151       100       106
## 448        68        68        73
## 449        62        47        56
## 450        58        62        46
## 451        67        46        84
## 452       107        95       101
## 453        47        37        31
## 454        90        95        73
## 455       149        85        74
## 456        84        84        62
## 457        79        60        68
## 458        63        85        58
## 459        95       119        84
## 460        75        51        66
## 461        75        51        66
## 462        89        95       154
## 463        79        85       101
## 464       151       117       128
## 465       139       123       101
## 466        63        79        68
## 467        52        85        63
## 468        80        85        83
## 469       101        76        73
## 470       171       168       135
## 471        69        69        69
## 472        98       119        97
## 473        90        93       111
## 474        35        38        38
## 475        62        46        51
## 476        62        79        52
## 477       117        79        63
## 478       112        91        98
## 479        96        81        64
## 480       145       129       124
## 481        69        53        74
## 482       212        96       101
## 483        68        85        75
## 484        95        93        86
## 485       291       118       119
## 486        91        83        64
## 487       102        86        NA
## 488        59        97        75
## 489        58        51        97
## 490        69        75       195
## 491       140        85        80
## 492        48        70        97
## 493        47        58        69
## 494       134       101        75
## 495       129        70        58
## 496        46        40        41
## 497        52        63        89
## 498        95        79        84
## 499        74       100        80
## 500       145       101        84
## 501        79        62        41
## 502        74        68        63
## 503        79        65        63
## 504        63        74        69
## 505        90        90        96
## 506        89        63        63
## 507        80        84       101
## 508        62        90       149
## 509        40        42        36
## 510       101        71        46
## 511        29        35        38
## 512       114        36       101
## 513        60        63        85
## 514        68        47        46
## 515        24        42        41
## 516       106       183        96
## 517        90        79        47
## 518       146       106        96
## 519        37        42        48
## 520        70        69       112
## 521        48        37        80
## 522       112        90       122
## 523        85       220        52
## 524       128       110       128
## 525        63        40        46
## 526       100        73        85
## 527        73        68        61
## 528        51        84        52
## 529       172        52        40
## 530        62        84        79
## 531       139        73        86
## 532        89        95        90
## 533       112       134       123
## 534       117        79        49
## 535        51        29        41

```

]
.item50[
{{content}}
]

]
--

<code class ='r hljs remark-code'>frog_signal %>% <br>&nbsp;&nbsp;select(Standard1<span style="background-color:#ffff7f">:</span>Standard3)</code>

```

<div class="info-box pad20" style="position:absolute;right:10px;bottom:10px;">
The <code>tidyselect</code> syntax <code class="monash-blue">:</code> can be used to select contiguous columns in the data
</div>

---

# Tidy select .font_small[.font_small[Part] 3]

```r
frog_signal %>% 
  select(starts_with("Standard"))
```

```
##     Standard1 Standard2 Standard3 StandardAverage
## 1          47        46        42              45
## 2          69        44        36              50
## 3         139       102        85             109
## 4         112       112       117             114
## 5         101       101        80              94
## 6          90        68        73              77
## 7          79        41        46              55
## 8         262       237       166             222
## 9         123       106        95             108
## 10         47        62        63              57
## 11         95       117        84              99
## 12         56        52        41              50
## 13         41        51        57              50
## 14         57        41        30              43
## 15        144       128       166             146
## 16         68        41        52              54
## 17         62        68        84              71
## 18         52        89        63              68
## 19        101        80       106              96
## 20         69        80        57              69
## 21        134       112       102             116
## 22        167       118       123             136
## 23         51        52        62              55
## 24         73        84       136              98
## 25         89       106        90              95
## 26         55        78        63              65
## 27         74        77        83              78
## 28         69        70        95              78
## 29        117        73       111             100
## 30        244       242        85             190
## 31        208       102       124             145
## 32         95        42        45              61
## 33         62        46        57              55
## 34        148       134       112             131
## 35         96        57        67              73
## 36         28        36        39              34
## 37        101        52        95              83
## 38         58        68        62              63
## 39         73        63        62              66
## 40        173        69        38              93
## 41         84        90        87              87
## 42         51        62        50              54
## 43         95        95       104              98
## 44         52        57        69              59
## 45         74       107        82              88
## 46         47        52        69              56
## 47         68        60        41              56
## 48         58        52        52              54
## 49         47        40        47              45
## 50         51        52        41              48
## 51         96        99        79              91
## 52         63        41        24              43
## 53        102       129        52              94
## 54         80        57        62              66
## 55         62        52        56              57
## 56         46        57        98              67
## 57         87        82        83              84
## 58        100        59        62              74
## 59        111       101       111             108
## 60         96        79        68              81
## 61        177       156       145             159
## 62        150       131       134             138
## 63        172       107       116             132
## 64        133        95       117             115
## 65         68       100        79              82
## 66        112        69        79              87
## 67        112       125        90             109
## 68         68        56        57              60
## 69         90       215       117             141
## 70         90       200        89             126
## 71        113       127        95             112
## 72         47        47        48              47
## 73         50        97        91              79
## 74         96       112        80              96
## 75         80        38        74              64
## 76         78        63        59              67
## 77         29        48        47              41
## 78        105        63       151             106
## 79         42        41        53              45
## 80         59        68       155              94
## 81         91       101        74              89
## 82         68        86        91              82
## 83         53        47        47              49
## 84         64        73        62              66
## 85         83        57        90              77
## 86         52        36        55              48
## 87        117       106       101             108
## 88         84       100        86              90
## 89         57        57        33              49
## 90        101        61        69              77
## 91         51        70        57              59
## 92         63        68        84              72
## 93         41        52        48              47
## 94         67        95        90              84
## 95         53        47        75              58
## 96         75       103        86              88
## 97         53        79        47              60
## 98        155       129       139             141
## 99         79       128       107             105
## 100        95       120       112             109
## 101       120        41       134              98
## 102        41        52        80              58
## 103       150        90        86             109
## 104        63        96        97              85
## 105       130       100       102             111
## 106        83        53        39              58
## 107       118        64       102              95
## 108        80        79        53              71
## 109        96        85       118             100
## 110        58        47        62              56
## 111        70        81        59              70
## 112        31        67        64              54
## 113        65        75        89              76
## 114       113        88       102             101
## 115        58        85        70              71
## 116       129       117        90             112
## 117        69        80       117              89
## 118        95        69        63              76
## 119        69        63        68              67
## 120       168        79        56             101
## 121       171       188       139             166
## 122       106        90       101              99
## 123       136       129        79             115
## 124        73        80        80              78
## 125        79        47        51              59
## 126        47        41        35              41
## 127        52        49        57              53
## 128        90        96        68              85
## 129        50        58        35              48
## 130       106        84        95              95
## 131        57        36        63              52
## 132        68        52        52              57
## 133       154       161        79             131
## 134        68        76        53              66
## 135        53        32        46              44
## 136        62        86        61              70
## 137        89        68        54              70
## 138       113        53        53              73
## 139        58       268        96             141
## 140        58        52        53              54
## 141        53        92        58              68
## 142        32        74        90              65
## 143        47        57        75              60
## 144       155       136        96             129
## 145        62        41        50              51
## 146        41        37        74              51
## 147        79        41        52              57
## 148       112        86        89              96
## 149        88        57        85              77
## 150        57        30        53              47
## 151        96       123       158             126
## 152        63        84        89              79
## 153        72        90       100              87
## 154       107        74        52              78
## 155        79        52        68              66
## 156        52        42        45              46
## 157        26        57        74              52
## 158       106        95       255             152
## 159        34        52        45              44
## 160        73        89        62              75
## 161        41        45        39              42
## 162        29        51        47              42
## 163        58        68        67              64
## 164       119        68        30              72
## 165        51        63        56              57
## 166        62        77        78              72
## 167        35       106        82              74
## 168       133        90       172             132
## 169       139        91        68              99
## 170        85        51        55              64
## 171        57        34        67              53
## 172        25        66        56              49
## 173        69        73        75              72
## 174        78        79        49              69
## 175        56        73        68              66
## 176        70        56        73              66
## 177       112        74        73              86
## 178        46        61        63              57
## 179        62        35        63              53
## 180        63        45        79              62
## 181        63        57       105              75
## 182       105        87        53              82
## 183        52        57        41              50
## 184        79        52       101              77
## 185       162        90        62             105
## 186        35        24        25              28
## 187        90        57        79              75
## 188        62       101        89              84
## 189        43        41        41              42
## 190        58        46        45              50
## 191       133        83        90             102
## 192        68        79        64              70
## 193        35        35        51              40
## 194        55        91        51              66
## 195        13        16        30              20
## 196        24        41        46              37
## 197        41        85        90              72
## 198        68       112        47              76
## 199        46       265        65             125
## 200        85        89       107              94
## 201        57        40        30              42
## 202        36        31        41              36
## 203        41        72        61              58
## 204        74        62        84              73
## 205        59        52        57              56
## 206        66        47        46              53
## 207       118        46        62              75
## 208        75        39       112              75
## 209        36        63        68              56
## 210        36        59        41              45
## 211        90        74        50              71
## 212        69        63        57              63
## 213        62        52        67              60
## 214        64        57        52              58
## 215        53        46        39              46
## 216        74        57        73              68
## 217        74        84        80              79
## 218        35        19        34              29
## 219        38        46        68              51
## 220       106        91       102             100
## 221       107        46        83              79
## 222        89        73        78              80
## 223        25        69        41              45
## 224        51        63        37              50
## 225        61        78        50              63
## 226        24        30        41              32
## 227       102        69        47              73
## 228        25        30        25              27
## 229        68        47        90              68
## 230        63        73        30              55
## 231       107       104        74              95
## 232        35        41        44              40
## 233        96        67        67              77
## 234        67        52        96              72
## 235        58        36        36              43
## 236        35        34        29              33
## 237        62        44        45              50
## 238        62        48        52              54
## 239        63        79        35              59
## 240        83        89        63              78
## 241        50        49        56              52
## 242        79        94        57              77
## 243       100        58        63              74
## 244        70        83        79              77
## 245       123        74        61              86
## 246        86        79       224             130
## 247        79        86        56              74
## 248        46        57        35              46
## 249        84        63        63              70
## 250        36        53       173              87
## 251        84        69        90              81
## 252        52        29        30              37
## 253        73        69        69              70
## 254        36        45        62              48
## 255        51        30        36              39
## 256       166        88        62             105
## 257        46        40        58              48
## 258        30        30        49              36
## 259        90        46        45              60
## 260        85        41        48              58
## 261        72        74       100              82
## 262       128        56        46              77
## 263        51        36        46              44
## 264        68        78        89              78
## 265       101       158        68             109
## 266        57        63        73              64
## 267        94        63        69              75
## 268        95        71        73              80
## 269       107        74        57              79
## 270        86        52        42              60
## 271        74       106        79              86
## 272        68        74        63              68
## 273        95        73        79              82
## 274        84        73        63              73
## 275        36        42        47              42
## 276        90       105       123             106
## 277        46        52        65              54
## 278        79        88        75              81
## 279       112        85        85              94
## 280       107       112       132             117
## 281        80       165        NA              82
## 282       177        85       100             121
## 283        58        53        57              56
## 284        63        84        69              72
## 285        79        68        90              79
## 286        63        79        57              66
## 287        62        80        74              72
## 288        84        58        79              74
## 289        94       102        79              92
## 290       117        95       102             105
## 291        56       107        52              72
## 292       135       101        79             105
## 293       200       167       199             189
## 294        96        58        98              84
## 295        80        58        73              70
## 296        52        47        60              53
## 297        52        46        54              51
## 298       150       134        92             125
## 299        74        75        83              77
## 300       106       116       139             120
## 301        99        74        90              88
## 302        78        46        29              51
## 303        52        41        56              50
## 304        61        46        60              56
## 305       117       260        79             152
## 306       117       100        94             104
## 307       148        90       139             126
## 308        86        81        79              82
## 309       112        80        93              95
## 310        52        57        57              55
## 311        74        73        62              70
## 312        68        83        78              76
## 313        40        41        58              46
## 314        62        54        56              57
## 315        40        46        40              42
## 316        46        57        57              53
## 317       106        89        40              78
## 318        63        46        73              61
## 319        62        94        79              78
## 320        84        69        68              74
## 321        56        62        52              57
## 322        38        64        72              58
## 323        68        60        61              63
## 324        46        46        73              55
## 325       117       168        73             119
## 326       150        79        67              99
## 327        79        62        63              68
## 328        88        78        73              80
## 329        84        63        79              75
## 330        51        53        90              65
## 331        84        78        67              76
## 332        89        84        73              82
## 333       101        45        52              66
## 334        90       104        78              91
## 335        84        93        89              89
## 336        40        68        47              52
## 337        84       118       112             105
## 338        61       106        68              78
## 339        74        61        74              70
## 340        51        52        47              50
## 341        89        77        90              85
## 342        62        57        57              59
## 343        43        52        38              44
## 344        68        56        53              59
## 345        80        79        73              77
## 346        80        52        63              65
## 347        30        35        45              37
## 348        95        72        57              75
## 349        67       123        80              90
## 350        74        74        80              76
## 351        62        94       133              96
## 352        25        52        65              47
## 353       111        58        52              74
## 354        59        55        50              55
## 355        44        61        47              51
## 356        46        46        40              44
## 357        68        72        55              65
## 358       100        61       167             109
## 359        68       112        86              89
## 360        63        74       123              87
## 361        79        52        56              62
## 362        58        41        53              51
## 363        52        42        47              47
## 364        53        67        88              69
## 365        33        47        63              48
## 366        69        74        91              78
## 367        86        85        74              82
## 368        64        52        91              69
## 369        64        73        52              63
## 370       166        77        69             104
## 371        68        62        58              63
## 372        73        64        57              65
## 373        78       100        80              86
## 374        79        63        52              65
## 375        30        56        62              49
## 376        57        52        46              52
## 377        30        29        31              30
## 378        42        46        57              48
## 379        56        58        57              57
## 380       172       128        79             126
## 381        52        46        57              52
## 382        41        52        52              48
## 383       112        57        57              75
## 384        79        90        90              86
## 385        68        85        68              74
## 386        57        68        79              68
## 387        95       107       111             104
## 388        74        63        74              70
## 389        66        74        74              71
## 390        73        48        50              57
## 391        52        69        30              50
## 392        58        37        68              54
## 393        90       107        69              89
## 394        57        63       117              79
## 395        62        94        79              78
## 396        68        67        46              60
## 397       139       122       106             122
## 398       106        62        62              77
## 399        68        57        57              61
## 400        36        64        75              58
## 401        74        59        47              60
## 402        70        85        96              84
## 403        53        52        63              56
## 404        80        85       118              94
## 405        74        47        63              61
## 406        79        42        58              60
## 407        75        72       106              84
## 408        52        90        78              73
## 409        47        53        63              54
## 410        46        46        28              40
## 411       118       150       160             143
## 412       165        79        67             104
## 413        78        57        57              64
## 414        95        76        57              76
## 415        94        51        59              68
## 416        66        57        45              56
## 417        74        62        46              61
## 418        39        54        40              44
## 419        95        85       145             108
## 420        73        58       182             104
## 421       182       139       106             142
## 422        62        51        62              58
## 423       139        75       113             109
## 424        89       106       259             151
## 425        99        57        69              75
## 426        58        91        59              69
## 427        42        36        54              44
## 428        57        85        64              69
## 429        64        72       183             106
## 430        85        75        70              77
## 431       185        69        52             102
## 432        91        58       102              84
## 433       127       123       106             119
## 434        85        52        90              76
## 435        67        96        62              75
## 436        85        57       135              92
## 437       123        73        84              93
## 438       100        40        39              60
## 439       160       134        83             126
## 440        58        51        52              54
## 441        62        46        57              55
## 442        73        84        63              73
## 443        89        63        62              71
## 444        44        57        74              58
## 445        68        74        63              68
## 446       100        63        52              72
## 447       151       100       106             119
## 448        68        68        73              70
## 449        62        47        56              55
## 450        58        62        46              55
## 451        67        46        84              66
## 452       107        95       101             101
## 453        47        37        31              38
## 454        90        95        73              86
## 455       149        85        74             103
## 456        84        84        62              77
## 457        79        60        68              69
## 458        63        85        58              69
## 459        95       119        84              99
## 460        75        51        66              64
## 461        75        51        66              64
## 462        89        95       154             113
## 463        79        85       101              88
## 464       151       117       128             132
## 465       139       123       101             121
## 466        63        79        68              70
## 467        52        85        63              67
## 468        80        85        83              83
## 469       101        76        73              83
## 470       171       168       135             158
## 471        69        69        69              69
## 472        98       119        97             105
## 473        90        93       111              98
## 474        35        38        38              37
## 475        62        46        51              53
## 476        62        79        52              64
## 477       117        79        63              86
## 478       112        91        98             100
## 479        96        81        64              80
## 480       145       129       124             133
## 481        69        53        74              65
## 482       212        96       101             136
## 483        68        85        75              76
## 484        95        93        86              91
## 485       291       118       119             176
## 486        91        83        64              79
## 487       102        86        NA              94
## 488        59        97        75              77
## 489        58        51        97              69
## 490        69        75       195             113
## 491       140        85        80             102
## 492        48        70        97              72
## 493        47        58        69              58
## 494       134       101        75             103
## 495       129        70        58              86
## 496        46        40        41              42
## 497        52        63        89              68
## 498        95        79        84              86
## 499        74       100        80              85
## 500       145       101        84             110
## 501        79        62        41              61
## 502        74        68        63              68
## 503        79        65        63              69
## 504        63        74        69              69
## 505        90        90        96              92
## 506        89        63        63              72
## 507        80        84       101              88
## 508        62        90       149             100
## 509        40        42        36              39
## 510       101        71        46              73
## 511        29        35        38              34
## 512       114        36       101              84
## 513        60        63        85              69
## 514        68        47        46              54
## 515        24        42        41              36
## 516       106       183        96             128
## 517        90        79        47              72
## 518       146       106        96             116
## 519        37        42        48              42
## 520        70        69       112              84
## 521        48        37        80              55
## 522       112        90       122             108
## 523        85       220        52             119
## 524       128       110       128             122
## 525        63        40        46              50
## 526       100        73        85              86
## 527        73        68        61              67
## 528        51        84        52              62
## 529       172        52        40              88
## 530        62        84        79              75
## 531       139        73        86              99
## 532        89        95        90              91
## 533       112       134       123             123
## 534       117        79        49              82
## 535        51        29        41              40
```
]
.item[
{{content}}
]

]

```r
frog_signal %>% 
  select(num_range("Standard", 1:3))
```

```
##     Standard1 Standard2 Standard3
## 1          47        46        42
## 2          69        44        36
## 3         139       102        85
## 4         112       112       117
## 5         101       101        80
## 6          90        68        73
## 7          79        41        46
## 8         262       237       166
## 9         123       106        95
## 10         47        62        63
## 11         95       117        84
## 12         56        52        41
## 13         41        51        57
## 14         57        41        30
## 15        144       128       166
## 16         68        41        52
## 17         62        68        84
## 18         52        89        63
## 19        101        80       106
## 20         69        80        57
## 21        134       112       102
## 22        167       118       123
## 23         51        52        62
## 24         73        84       136
## 25         89       106        90
## 26         55        78        63
## 27         74        77        83
## 28         69        70        95
## 29        117        73       111
## 30        244       242        85
## 31        208       102       124
## 32         95        42        45
## 33         62        46        57
## 34        148       134       112
## 35         96        57        67
## 36         28        36        39
## 37        101        52        95
## 38         58        68        62
## 39         73        63        62
## 40        173        69        38
## 41         84        90        87
## 42         51        62        50
## 43         95        95       104
## 44         52        57        69
## 45         74       107        82
## 46         47        52        69
## 47         68        60        41
## 48         58        52        52
## 49         47        40        47
## 50         51        52        41
## 51         96        99        79
## 52         63        41        24
## 53        102       129        52
## 54         80        57        62
## 55         62        52        56
## 56         46        57        98
## 57         87        82        83
## 58        100        59        62
## 59        111       101       111
## 60         96        79        68
## 61        177       156       145
## 62        150       131       134
## 63        172       107       116
## 64        133        95       117
## 65         68       100        79
## 66        112        69        79
## 67        112       125        90
## 68         68        56        57
## 69         90       215       117
## 70         90       200        89
## 71        113       127        95
## 72         47        47        48
## 73         50        97        91
## 74         96       112        80
## 75         80        38        74
## 76         78        63        59
## 77         29        48        47
## 78        105        63       151
## 79         42        41        53
## 80         59        68       155
## 81         91       101        74
## 82         68        86        91
## 83         53        47        47
## 84         64        73        62
## 85         83        57        90
## 86         52        36        55
## 87        117       106       101
## 88         84       100        86
## 89         57        57        33
## 90        101        61        69
## 91         51        70        57
## 92         63        68        84
## 93         41        52        48
## 94         67        95        90
## 95         53        47        75
## 96         75       103        86
## 97         53        79        47
## 98        155       129       139
## 99         79       128       107
## 100        95       120       112
## 101       120        41       134
## 102        41        52        80
## 103       150        90        86
## 104        63        96        97
## 105       130       100       102
## 106        83        53        39
## 107       118        64       102
## 108        80        79        53
## 109        96        85       118
## 110        58        47        62
## 111        70        81        59
## 112        31        67        64
## 113        65        75        89
## 114       113        88       102
## 115        58        85        70
## 116       129       117        90
## 117        69        80       117
## 118        95        69        63
## 119        69        63        68
## 120       168        79        56
## 121       171       188       139
## 122       106        90       101
## 123       136       129        79
## 124        73        80        80
## 125        79        47        51
## 126        47        41        35
## 127        52        49        57
## 128        90        96        68
## 129        50        58        35
## 130       106        84        95
## 131        57        36        63
## 132        68        52        52
## 133       154       161        79
## 134        68        76        53
## 135        53        32        46
## 136        62        86        61
## 137        89        68        54
## 138       113        53        53
## 139        58       268        96
## 140        58        52        53
## 141        53        92        58
## 142        32        74        90
## 143        47        57        75
## 144       155       136        96
## 145        62        41        50
## 146        41        37        74
## 147        79        41        52
## 148       112        86        89
## 149        88        57        85
## 150        57        30        53
## 151        96       123       158
## 152        63        84        89
## 153        72        90       100
## 154       107        74        52
## 155        79        52        68
## 156        52        42        45
## 157        26        57        74
## 158       106        95       255
## 159        34        52        45
## 160        73        89        62
## 161        41        45        39
## 162        29        51        47
## 163        58        68        67
## 164       119        68        30
## 165        51        63        56
## 166        62        77        78
## 167        35       106        82
## 168       133        90       172
## 169       139        91        68
## 170        85        51        55
## 171        57        34        67
## 172        25        66        56
## 173        69        73        75
## 174        78        79        49
## 175        56        73        68
## 176        70        56        73
## 177       112        74        73
## 178        46        61        63
## 179        62        35        63
## 180        63        45        79
## 181        63        57       105
## 182       105        87        53
## 183        52        57        41
## 184        79        52       101
## 185       162        90        62
## 186        35        24        25
## 187        90        57        79
## 188        62       101        89
## 189        43        41        41
## 190        58        46        45
## 191       133        83        90
## 192        68        79        64
## 193        35        35        51
## 194        55        91        51
## 195        13        16        30
## 196        24        41        46
## 197        41        85        90
## 198        68       112        47
## 199        46       265        65
## 200        85        89       107
## 201        57        40        30
## 202        36        31        41
## 203        41        72        61
## 204        74        62        84
## 205        59        52        57
## 206        66        47        46
## 207       118        46        62
## 208        75        39       112
## 209        36        63        68
## 210        36        59        41
## 211        90        74        50
## 212        69        63        57
## 213        62        52        67
## 214        64        57        52
## 215        53        46        39
## 216        74        57        73
## 217        74        84        80
## 218        35        19        34
## 219        38        46        68
## 220       106        91       102
## 221       107        46        83
## 222        89        73        78
## 223        25        69        41
## 224        51        63        37
## 225        61        78        50
## 226        24        30        41
## 227       102        69        47
## 228        25        30        25
## 229        68        47        90
## 230        63        73        30
## 231       107       104        74
## 232        35        41        44
## 233        96        67        67
## 234        67        52        96
## 235        58        36        36
## 236        35        34        29
## 237        62        44        45
## 238        62        48        52
## 239        63        79        35
## 240        83        89        63
## 241        50        49        56
## 242        79        94        57
## 243       100        58        63
## 244        70        83        79
## 245       123        74        61
## 246        86        79       224
## 247        79        86        56
## 248        46        57        35
## 249        84        63        63
## 250        36        53       173
## 251        84        69        90
## 252        52        29        30
## 253        73        69        69
## 254        36        45        62
## 255        51        30        36
## 256       166        88        62
## 257        46        40        58
## 258        30        30        49
## 259        90        46        45
## 260        85        41        48
## 261        72        74       100
## 262       128        56        46
## 263        51        36        46
## 264        68        78        89
## 265       101       158        68
## 266        57        63        73
## 267        94        63        69
## 268        95        71        73
## 269       107        74        57
## 270        86        52        42
## 271        74       106        79
## 272        68        74        63
## 273        95        73        79
## 274        84        73        63
## 275        36        42        47
## 276        90       105       123
## 277        46        52        65
## 278        79        88        75
## 279       112        85        85
## 280       107       112       132
## 281        80       165        NA
## 282       177        85       100
## 283        58        53        57
## 284        63        84        69
## 285        79        68        90
## 286        63        79        57
## 287        62        80        74
## 288        84        58        79
## 289        94       102        79
## 290       117        95       102
## 291        56       107        52
## 292       135       101        79
## 293       200       167       199
## 294        96        58        98
## 295        80        58        73
## 296        52        47        60
## 297        52        46        54
## 298       150       134        92
## 299        74        75        83
## 300       106       116       139
## 301        99        74        90
## 302        78        46        29
## 303        52        41        56
## 304        61        46        60
## 305       117       260        79
## 306       117       100        94
## 307       148        90       139
## 308        86        81        79
## 309       112        80        93
## 310        52        57        57
## 311        74        73        62
## 312        68        83        78
## 313        40        41        58
## 314        62        54        56
## 315        40        46        40
## 316        46        57        57
## 317       106        89        40
## 318        63        46        73
## 319        62        94        79
## 320        84        69        68
## 321        56        62        52
## 322        38        64        72
## 323        68        60        61
## 324        46        46        73
## 325       117       168        73
## 326       150        79        67
## 327        79        62        63
## 328        88        78        73
## 329        84        63        79
## 330        51        53        90
## 331        84        78        67
## 332        89        84        73
## 333       101        45        52
## 334        90       104        78
## 335        84        93        89
## 336        40        68        47
## 337        84       118       112
## 338        61       106        68
## 339        74        61        74
## 340        51        52        47
## 341        89        77        90
## 342        62        57        57
## 343        43        52        38
## 344        68        56        53
## 345        80        79        73
## 346        80        52        63
## 347        30        35        45
## 348        95        72        57
## 349        67       123        80
## 350        74        74        80
## 351        62        94       133
## 352        25        52        65
## 353       111        58        52
## 354        59        55        50
## 355        44        61        47
## 356        46        46        40
## 357        68        72        55
## 358       100        61       167
## 359        68       112        86
## 360        63        74       123
## 361        79        52        56
## 362        58        41        53
## 363        52        42        47
## 364        53        67        88
## 365        33        47        63
## 366        69        74        91
## 367        86        85        74
## 368        64        52        91
## 369        64        73        52
## 370       166        77        69
## 371        68        62        58
## 372        73        64        57
## 373        78       100        80
## 374        79        63        52
## 375        30        56        62
## 376        57        52        46
## 377        30        29        31
## 378        42        46        57
## 379        56        58        57
## 380       172       128        79
## 381        52        46        57
## 382        41        52        52
## 383       112        57        57
## 384        79        90        90
## 385        68        85        68
## 386        57        68        79
## 387        95       107       111
## 388        74        63        74
## 389        66        74        74
## 390        73        48        50
## 391        52        69        30
## 392        58        37        68
## 393        90       107        69
## 394        57        63       117
## 395        62        94        79
## 396        68        67        46
## 397       139       122       106
## 398       106        62        62
## 399        68        57        57
## 400        36        64        75
## 401        74        59        47
## 402        70        85        96
## 403        53        52        63
## 404        80        85       118
## 405        74        47        63
## 406        79        42        58
## 407        75        72       106
## 408        52        90        78
## 409        47        53        63
## 410        46        46        28
## 411       118       150       160
## 412       165        79        67
## 413        78        57        57
## 414        95        76        57
## 415        94        51        59
## 416        66        57        45
## 417        74        62        46
## 418        39        54        40
## 419        95        85       145
## 420        73        58       182
## 421       182       139       106
## 422        62        51        62
## 423       139        75       113
## 424        89       106       259
## 425        99        57        69
## 426        58        91        59
## 427        42        36        54
## 428        57        85        64
## 429        64        72       183
## 430        85        75        70
## 431       185        69        52
## 432        91        58       102
## 433       127       123       106
## 434        85        52        90
## 435        67        96        62
## 436        85        57       135
## 437       123        73        84
## 438       100        40        39
## 439       160       134        83
## 440        58        51        52
## 441        62        46        57
## 442        73        84        63
## 443        89        63        62
## 444        44        57        74
## 445        68        74        63
## 446       100        63        52
## 447       151       100       106
## 448        68        68        73
## 449        62        47        56
## 450        58        62        46
## 451        67        46        84
## 452       107        95       101
## 453        47        37        31
## 454        90        95        73
## 455       149        85        74
## 456        84        84        62
## 457        79        60        68
## 458        63        85        58
## 459        95       119        84
## 460        75        51        66
## 461        75        51        66
## 462        89        95       154
## 463        79        85       101
## 464       151       117       128
## 465       139       123       101
## 466        63        79        68
## 467        52        85        63
## 468        80        85        83
## 469       101        76        73
## 470       171       168       135
## 471        69        69        69
## 472        98       119        97
## 473        90        93       111
## 474        35        38        38
## 475        62        46        51
## 476        62        79        52
## 477       117        79        63
## 478       112        91        98
## 479        96        81        64
## 480       145       129       124
## 481        69        53        74
## 482       212        96       101
## 483        68        85        75
## 484        95        93        86
## 485       291       118       119
## 486        91        83        64
## 487       102        86        NA
## 488        59        97        75
## 489        58        51        97
## 490        69        75       195
## 491       140        85        80
## 492        48        70        97
## 493        47        58        69
## 494       134       101        75
## 495       129        70        58
## 496        46        40        41
## 497        52        63        89
## 498        95        79        84
## 499        74       100        80
## 500       145       101        84
## 501        79        62        41
## 502        74        68        63
## 503        79        65        63
## 504        63        74        69
## 505        90        90        96
## 506        89        63        63
## 507        80        84       101
## 508        62        90       149
## 509        40        42        36
## 510       101        71        46
## 511        29        35        38
## 512       114        36       101
## 513        60        63        85
## 514        68        47        46
## 515        24        42        41
## 516       106       183        96
## 517        90        79        47
## 518       146       106        96
## 519        37        42        48
## 520        70        69       112
## 521        48        37        80
## 522       112        90       122
## 523        85       220        52
## 524       128       110       128
## 525        63        40        46
## 526       100        73        85
## 527        73        68        61
## 528        51        84        52
## 529       172        52        40
## 530        62        84        79
## 531       139        73        86
## 532        89        95        90
## 533       112       134       123
## 534       117        79        49
## 535        51        29        41
```

---

# Selection language .font_small[.font_small[Part] 1]

* `:` for selecting contiguous variables
* `!` for taking complement set of variables
* `&` or `|` for selecting intersection or union of two sets of variables, e.g.

```r
frog_signal %>% 
  select(starts_with("Alt") & ends_with("1")) %>% 
  str()
```

```
## 'data.frame':	535 obs. of  1 variable:
##  $ Alternative1: num  28 33 227 101 126 143 50 123 76 53 ...
```

* `c()` for combining selections
* `everything()` to select all variables
* `last_col()` to select last variable, with option of an offset

---

# Selection language .font_small[.font_small[Part] 2]

* `starts_with()` selects columns with the given prefix
* `ends_with()` selects columns with the given suffix
* `contains()` selects columns with a literal string
* `matches()` selects columns that match the regular expression .font_small[we'll learn this next!]
* `num_range()` selects columns with a numerical range
* `all_of()` for selecting columns based on a character vector
* `any_of()` is the same as `all_of()` but no error when variables do not exist
* `where()` selects based on where given function return TRUE

```r
help(language, package = "tidyselect")
```

---

# Subsetting by column .font_small[Tidyverse]

```r
select(mtcars, c(mpg, cyl))
select(mtcars, c("mpg", "cyl"))
select(mtcars, mpg, cyl)
select(mtcars, "mpg", "cyl")
```
All the same result as below

```r
mtcars %>% 
  select(mpg, cyl)
```

```
##                      mpg cyl
## Mazda RX4           21.0   6
## Mazda RX4 Wag       21.0   6
## Datsun 710          22.8   4
## Hornet 4 Drive      21.4   6
## Hornet Sportabout   18.7   8
## Valiant             18.1   6
## Duster 360          14.3   8
## Merc 240D           24.4   4
## Merc 230            22.8   4
## Merc 280            19.2   6
## Merc 280C           17.8   6
## Merc 450SE          16.4   8
## Merc 450SL          17.3   8
## Merc 450SLC         15.2   8
## Cadillac Fleetwood  10.4   8
## Lincoln Continental 10.4   8
## Chrysler Imperial   14.7   8
## Fiat 128            32.4   4
## Honda Civic         30.4   4
## Toyota Corolla      33.9   4
## Toyota Corona       21.5   4
## Dodge Challenger    15.5   8
## AMC Javelin         15.2   8
## Camaro Z28          13.3   8
## Pontiac Firebird    19.2   8
## Fiat X1-9           27.3   4
## Porsche 914-2       26.0   4
## Lotus Europa        30.4   4
## Ford Pantera L      15.8   8
## Ferrari Dino        19.7   6
## Maserati Bora       15.0   8
## Volvo 142E          21.4   4
```

]
.item[
{{content}}
]

]

```r
mtcars %>% select(mpg)
```

```
##                      mpg
## Mazda RX4           21.0
## Mazda RX4 Wag       21.0
## Datsun 710          22.8
## Hornet 4 Drive      21.4
## Hornet Sportabout   18.7
## Valiant             18.1
## Duster 360          14.3
## Merc 240D           24.4
## Merc 230            22.8
## Merc 280            19.2
## Merc 280C           17.8
## Merc 450SE          16.4
## Merc 450SL          17.3
## Merc 450SLC         15.2
## Cadillac Fleetwood  10.4
## Lincoln Continental 10.4
## Chrysler Imperial   14.7
## Fiat 128            32.4
## Honda Civic         30.4
## Toyota Corolla      33.9
## Toyota Corona       21.5
## Dodge Challenger    15.5
## AMC Javelin         15.2
## Camaro Z28          13.3
## Pontiac Firebird    19.2
## Fiat X1-9           27.3
## Porsche 914-2       26.0
## Lotus Europa        30.4
## Ford Pantera L      15.8
## Ferrari Dino        19.7
## Maserati Bora       15.0
## Volvo 142E          21.4
```

<div class="info-box" style="position:absolute;right:20px;margin-right:0px!important;bottom:0px;margin-left:0;width:650px;">
<ul>
<li>Selecting one column doesn't "drop" it to a vector.</li> <li>If you really want the vector then use <code class="monash-blue">pull(mpg)</code>.</li>
</ul>
</div>

---

# Subsetting by row .font_small[Tidyverse]

```r
mtcars %>% 
  slice(3:1)
```

```
##                mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Datsun 710    22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Mazda RX4 Wag 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Mazda RX4     21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
```
--

```r
mtcars %>% 
  filter(rownames(.) %in% c("Datsun 710", "Mazda RX4"))
```

```
##             mpg cyl disp  hp drat   wt  qsec vs am gear carb
## Mazda RX4  21.0   6  160 110 3.90 2.62 16.46  0  1    4    4
## Datsun 710 22.8   4  108  93 3.85 2.32 18.61  1  1    4    1
```
* Use .monash-blue[`slice`] to subset by *index* and .monash-blue[`filter`] by *logical vector*

<div class="info-box" style="position:absolute;right:20px;margin-right:0px!important;top:50px;margin-left:0;width:900px;font-size: 20pt;">
<ul>
<li>Placeholder binding</li>
<ul>
<li><code>x %>% f(y, g(.))</code> is the same as <code>f(x, y, g(x))</code></li>
<li><code>x %>% f(y, .)</code> is the same as <code>f(y, x)</code></li>
</ul>
{{content}}
</ul>
</div>

--
<i class="fas fa-exclamation-triangle red"></i> Note: row names do not follow tidy data principles<br>
{{content}}
--
<li>Use <code class="monash-blue">tibble::rownames_to_column()</code> to convert rownames to a column to make into a tidy data</li>

---

# Adding or modifying a column .font_small[Tidyverse]

<code class ='r hljs remark-code'>mtcars %>% <br>&nbsp;&nbsp;<span style="background-color:#ffff7f">mutate</span>(gpm = 1 / mpg,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;wt = gpm^2,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;wt = if_else(cyl==6, 10, wt),<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;hp = case_when(cyl==6 ~ 11,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cyl==4 ~ 10,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;TRUE ~ 3))</code>

```

##     mpg cyl  disp hp drat           wt  qsec vs am gear carb        gpm
## 1  21.0   6 160.0 11 3.90 1.000000e+01 16.46  0  1    4    4 0.04761905
## 2  21.0   6 160.0 11 3.90 1.000000e+01 17.02  0  1    4    4 0.04761905
## 3  22.8   4 108.0 10 3.85 1.923669e-03 18.61  1  1    4    1 0.04385965
## 4  21.4   6 258.0 11 3.08 1.000000e+01 19.44  1  0    3    1 0.04672897
## 5  18.7   8 360.0  3 3.15 2.859676e-03 17.02  0  0    3    2 0.05347594
## 6  18.1   6 225.0 11 2.76 1.000000e+01 20.22  1  0    3    1 0.05524862
## 7  14.3   8 360.0  3 3.21 4.890215e-03 15.84  0  0    3    4 0.06993007
## 8  24.4   4 146.7 10 3.69 1.679656e-03 20.00  1  0    4    2 0.04098361
## 9  22.8   4 140.8 10 3.92 1.923669e-03 22.90  1  0    4    2 0.04385965
## 10 19.2   6 167.6 11 3.92 1.000000e+01 18.30  1  0    4    4 0.05208333
## 11 17.8   6 167.6 11 3.92 1.000000e+01 18.90  1  0    4    4 0.05617978
## 12 16.4   8 275.8  3 3.07 3.718025e-03 17.40  0  0    3    3 0.06097561
## 13 17.3   8 275.8  3 3.07 3.341241e-03 17.60  0  0    3    3 0.05780347
## 14 15.2   8 275.8  3 3.07 4.328255e-03 18.00  0  0    3    3 0.06578947
## 15 10.4   8 472.0  3 2.93 9.245562e-03 17.98  0  0    3    4 0.09615385
## 16 10.4   8 460.0  3 3.00 9.245562e-03 17.82  0  0    3    4 0.09615385
## 17 14.7   8 440.0  3 3.23 4.627701e-03 17.42  0  0    3    4 0.06802721
## 18 32.4   4  78.7 10 4.08 9.525987e-04 19.47  1  1    4    1 0.03086420
## 19 30.4   4  75.7 10 4.93 1.082064e-03 18.52  1  1    4    2 0.03289474
## 20 33.9   4  71.1 10 4.22 8.701630e-04 19.90  1  1    4    1 0.02949853
## 21 21.5   4 120.1 10 3.70 2.163332e-03 20.01  1  0    3    1 0.04651163
## 22 15.5   8 318.0  3 2.76 4.162331e-03 16.87  0  0    3    2 0.06451613
## 23 15.2   8 304.0  3 3.15 4.328255e-03 17.30  0  0    3    2 0.06578947
## 24 13.3   8 350.0  3 3.73 5.653231e-03 15.41  0  0    3    4 0.07518797
## 25 19.2   8 400.0  3 3.08 2.712674e-03 17.05  0  0    3    2 0.05208333
## 26 27.3   4  79.0 10 4.08 1.341760e-03 18.90  1  1    4    1 0.03663004
## 27 26.0   4 120.3 10 4.43 1.479290e-03 16.70  0  1    5    2 0.03846154
## 28 30.4   4  95.1 10 3.77 1.082064e-03 16.90  1  1    5    2 0.03289474
## 29 15.8   8 351.0  3 4.22 4.005768e-03 14.50  0  1    5    4 0.06329114
## 30 19.7   6 145.0 11 3.62 1.000000e+01 15.50  0  1    5    6 0.05076142
## 31 15.0   8 301.0  3 3.54 4.444444e-03 14.60  0  1    5    8 0.06666667
## 32 21.4   4 121.0 10 4.11 2.183597e-03 18.60  1  1    4    2 0.04672897

```
--

<div class="info-box" style="position:absolute;right:20px;margin-right:0px!important;top:50px;margin-left:0;width:550px;font-size: 20pt;">
<ul>
<li>Evaluation in <code>mutate</code> is done sequentially based on input order</li>
{{content}}
</ul>
</div>

<li>So you refer to the newly created variable in later input</li>
{{content}}
--
<li>You can call multiple <code>mutate</code> but computational performance is usually better if done within the same <code>mutate</code> call</li>
<pre>
<code>mtcars %>%
  mutate(gpm = 1 / mpg) %>% 
  mutate(wt = gpm^2)
</code></pre>

---

# Sorting columns .font_small[Tidyverse]

```r
mtcars %>% 
  select(sort(names(.)))
```

```
##                     am carb cyl  disp drat gear  hp  mpg  qsec vs    wt
## Mazda RX4            1    4   6 160.0 3.90    4 110 21.0 16.46  0 2.620
## Mazda RX4 Wag        1    4   6 160.0 3.90    4 110 21.0 17.02  0 2.875
## Datsun 710           1    1   4 108.0 3.85    4  93 22.8 18.61  1 2.320
## Hornet 4 Drive       0    1   6 258.0 3.08    3 110 21.4 19.44  1 3.215
## Hornet Sportabout    0    2   8 360.0 3.15    3 175 18.7 17.02  0 3.440
## Valiant              0    1   6 225.0 2.76    3 105 18.1 20.22  1 3.460
## Duster 360           0    4   8 360.0 3.21    3 245 14.3 15.84  0 3.570
## Merc 240D            0    2   4 146.7 3.69    4  62 24.4 20.00  1 3.190
## Merc 230             0    2   4 140.8 3.92    4  95 22.8 22.90  1 3.150
## Merc 280             0    4   6 167.6 3.92    4 123 19.2 18.30  1 3.440
## Merc 280C            0    4   6 167.6 3.92    4 123 17.8 18.90  1 3.440
## Merc 450SE           0    3   8 275.8 3.07    3 180 16.4 17.40  0 4.070
## Merc 450SL           0    3   8 275.8 3.07    3 180 17.3 17.60  0 3.730
## Merc 450SLC          0    3   8 275.8 3.07    3 180 15.2 18.00  0 3.780
## Cadillac Fleetwood   0    4   8 472.0 2.93    3 205 10.4 17.98  0 5.250
## Lincoln Continental  0    4   8 460.0 3.00    3 215 10.4 17.82  0 5.424
## Chrysler Imperial    0    4   8 440.0 3.23    3 230 14.7 17.42  0 5.345
## Fiat 128             1    1   4  78.7 4.08    4  66 32.4 19.47  1 2.200
## Honda Civic          1    2   4  75.7 4.93    4  52 30.4 18.52  1 1.615
## Toyota Corolla       1    1   4  71.1 4.22    4  65 33.9 19.90  1 1.835
## Toyota Corona        0    1   4 120.1 3.70    3  97 21.5 20.01  1 2.465
## Dodge Challenger     0    2   8 318.0 2.76    3 150 15.5 16.87  0 3.520
## AMC Javelin          0    2   8 304.0 3.15    3 150 15.2 17.30  0 3.435
## Camaro Z28           0    4   8 350.0 3.73    3 245 13.3 15.41  0 3.840
## Pontiac Firebird     0    2   8 400.0 3.08    3 175 19.2 17.05  0 3.845
## Fiat X1-9            1    1   4  79.0 4.08    4  66 27.3 18.90  1 1.935
## Porsche 914-2        1    2   4 120.3 4.43    5  91 26.0 16.70  0 2.140
## Lotus Europa         1    2   4  95.1 3.77    5 113 30.4 16.90  1 1.513
## Ford Pantera L       1    4   8 351.0 4.22    5 264 15.8 14.50  0 3.170
## Ferrari Dino         1    6   6 145.0 3.62    5 175 19.7 15.50  0 2.770
## Maserati Bora        1    8   8 301.0 3.54    5 335 15.0 14.60  0 3.570
## Volvo 142E           1    2   4 121.0 4.11    4 109 21.4 18.60  1 2.780
```
]
.s300[

```r
mtcars %>% 
  relocate(am, carb, .before = cyl)
```

```
##                      mpg am carb cyl  disp  hp drat    wt  qsec vs gear
## Mazda RX4           21.0  1    4   6 160.0 110 3.90 2.620 16.46  0    4
## Mazda RX4 Wag       21.0  1    4   6 160.0 110 3.90 2.875 17.02  0    4
## Datsun 710          22.8  1    1   4 108.0  93 3.85 2.320 18.61  1    4
## Hornet 4 Drive      21.4  0    1   6 258.0 110 3.08 3.215 19.44  1    3
## Hornet Sportabout   18.7  0    2   8 360.0 175 3.15 3.440 17.02  0    3
## Valiant             18.1  0    1   6 225.0 105 2.76 3.460 20.22  1    3
## Duster 360          14.3  0    4   8 360.0 245 3.21 3.570 15.84  0    3
## Merc 240D           24.4  0    2   4 146.7  62 3.69 3.190 20.00  1    4
## Merc 230            22.8  0    2   4 140.8  95 3.92 3.150 22.90  1    4
## Merc 280            19.2  0    4   6 167.6 123 3.92 3.440 18.30  1    4
## Merc 280C           17.8  0    4   6 167.6 123 3.92 3.440 18.90  1    4
## Merc 450SE          16.4  0    3   8 275.8 180 3.07 4.070 17.40  0    3
## Merc 450SL          17.3  0    3   8 275.8 180 3.07 3.730 17.60  0    3
## Merc 450SLC         15.2  0    3   8 275.8 180 3.07 3.780 18.00  0    3
## Cadillac Fleetwood  10.4  0    4   8 472.0 205 2.93 5.250 17.98  0    3
## Lincoln Continental 10.4  0    4   8 460.0 215 3.00 5.424 17.82  0    3
## Chrysler Imperial   14.7  0    4   8 440.0 230 3.23 5.345 17.42  0    3
## Fiat 128            32.4  1    1   4  78.7  66 4.08 2.200 19.47  1    4
## Honda Civic         30.4  1    2   4  75.7  52 4.93 1.615 18.52  1    4
## Toyota Corolla      33.9  1    1   4  71.1  65 4.22 1.835 19.90  1    4
## Toyota Corona       21.5  0    1   4 120.1  97 3.70 2.465 20.01  1    3
## Dodge Challenger    15.5  0    2   8 318.0 150 2.76 3.520 16.87  0    3
## AMC Javelin         15.2  0    2   8 304.0 150 3.15 3.435 17.30  0    3
## Camaro Z28          13.3  0    4   8 350.0 245 3.73 3.840 15.41  0    3
## Pontiac Firebird    19.2  0    2   8 400.0 175 3.08 3.845 17.05  0    3
## Fiat X1-9           27.3  1    1   4  79.0  66 4.08 1.935 18.90  1    4
## Porsche 914-2       26.0  1    2   4 120.3  91 4.43 2.140 16.70  0    5
## Lotus Europa        30.4  1    2   4  95.1 113 3.77 1.513 16.90  1    5
## Ford Pantera L      15.8  1    4   8 351.0 264 4.22 3.170 14.50  0    5
## Ferrari Dino        19.7  1    6   6 145.0 175 3.62 2.770 15.50  0    5
## Maserati Bora       15.0  1    8   8 301.0 335 3.54 3.570 14.60  0    5
## Volvo 142E          21.4  1    2   4 121.0 109 4.11 2.780 18.60  1    4
```
]
]
.item50[
.s300[

```r
mtcars %>% 
  select(wt, gear, everything())
```

```
##                        wt gear  mpg cyl  disp  hp drat  qsec vs am carb
## Mazda RX4           2.620    4 21.0   6 160.0 110 3.90 16.46  0  1    4
## Mazda RX4 Wag       2.875    4 21.0   6 160.0 110 3.90 17.02  0  1    4
## Datsun 710          2.320    4 22.8   4 108.0  93 3.85 18.61  1  1    1
## Hornet 4 Drive      3.215    3 21.4   6 258.0 110 3.08 19.44  1  0    1
## Hornet Sportabout   3.440    3 18.7   8 360.0 175 3.15 17.02  0  0    2
## Valiant             3.460    3 18.1   6 225.0 105 2.76 20.22  1  0    1
## Duster 360          3.570    3 14.3   8 360.0 245 3.21 15.84  0  0    4
## Merc 240D           3.190    4 24.4   4 146.7  62 3.69 20.00  1  0    2
## Merc 230            3.150    4 22.8   4 140.8  95 3.92 22.90  1  0    2
## Merc 280            3.440    4 19.2   6 167.6 123 3.92 18.30  1  0    4
## Merc 280C           3.440    4 17.8   6 167.6 123 3.92 18.90  1  0    4
## Merc 450SE          4.070    3 16.4   8 275.8 180 3.07 17.40  0  0    3
## Merc 450SL          3.730    3 17.3   8 275.8 180 3.07 17.60  0  0    3
## Merc 450SLC         3.780    3 15.2   8 275.8 180 3.07 18.00  0  0    3
## Cadillac Fleetwood  5.250    3 10.4   8 472.0 205 2.93 17.98  0  0    4
## Lincoln Continental 5.424    3 10.4   8 460.0 215 3.00 17.82  0  0    4
## Chrysler Imperial   5.345    3 14.7   8 440.0 230 3.23 17.42  0  0    4
## Fiat 128            2.200    4 32.4   4  78.7  66 4.08 19.47  1  1    1
## Honda Civic         1.615    4 30.4   4  75.7  52 4.93 18.52  1  1    2
## Toyota Corolla      1.835    4 33.9   4  71.1  65 4.22 19.90  1  1    1
## Toyota Corona       2.465    3 21.5   4 120.1  97 3.70 20.01  1  0    1
## Dodge Challenger    3.520    3 15.5   8 318.0 150 2.76 16.87  0  0    2
## AMC Javelin         3.435    3 15.2   8 304.0 150 3.15 17.30  0  0    2
## Camaro Z28          3.840    3 13.3   8 350.0 245 3.73 15.41  0  0    4
## Pontiac Firebird    3.845    3 19.2   8 400.0 175 3.08 17.05  0  0    2
## Fiat X1-9           1.935    4 27.3   4  79.0  66 4.08 18.90  1  1    1
## Porsche 914-2       2.140    5 26.0   4 120.3  91 4.43 16.70  0  1    2
## Lotus Europa        1.513    5 30.4   4  95.1 113 3.77 16.90  1  1    2
## Ford Pantera L      3.170    5 15.8   8 351.0 264 4.22 14.50  0  1    4
## Ferrari Dino        2.770    5 19.7   6 145.0 175 3.62 15.50  0  1    6
## Maserati Bora       3.570    5 15.0   8 301.0 335 3.54 14.60  0  1    8
## Volvo 142E          2.780    4 21.4   4 121.0 109 4.11 18.60  1  1    2
```
]
.s300[

```r
mtcars %>% 
  relocate(wt, gear, .after = mpg)
```

```
##                      mpg    wt gear cyl  disp  hp drat  qsec vs am carb
## Mazda RX4           21.0 2.620    4   6 160.0 110 3.90 16.46  0  1    4
## Mazda RX4 Wag       21.0 2.875    4   6 160.0 110 3.90 17.02  0  1    4
## Datsun 710          22.8 2.320    4   4 108.0  93 3.85 18.61  1  1    1
## Hornet 4 Drive      21.4 3.215    3   6 258.0 110 3.08 19.44  1  0    1
## Hornet Sportabout   18.7 3.440    3   8 360.0 175 3.15 17.02  0  0    2
## Valiant             18.1 3.460    3   6 225.0 105 2.76 20.22  1  0    1
## Duster 360          14.3 3.570    3   8 360.0 245 3.21 15.84  0  0    4
## Merc 240D           24.4 3.190    4   4 146.7  62 3.69 20.00  1  0    2
## Merc 230            22.8 3.150    4   4 140.8  95 3.92 22.90  1  0    2
## Merc 280            19.2 3.440    4   6 167.6 123 3.92 18.30  1  0    4
## Merc 280C           17.8 3.440    4   6 167.6 123 3.92 18.90  1  0    4
## Merc 450SE          16.4 4.070    3   8 275.8 180 3.07 17.40  0  0    3
## Merc 450SL          17.3 3.730    3   8 275.8 180 3.07 17.60  0  0    3
## Merc 450SLC         15.2 3.780    3   8 275.8 180 3.07 18.00  0  0    3
## Cadillac Fleetwood  10.4 5.250    3   8 472.0 205 2.93 17.98  0  0    4
## Lincoln Continental 10.4 5.424    3   8 460.0 215 3.00 17.82  0  0    4
## Chrysler Imperial   14.7 5.345    3   8 440.0 230 3.23 17.42  0  0    4
## Fiat 128            32.4 2.200    4   4  78.7  66 4.08 19.47  1  1    1
## Honda Civic         30.4 1.615    4   4  75.7  52 4.93 18.52  1  1    2
## Toyota Corolla      33.9 1.835    4   4  71.1  65 4.22 19.90  1  1    1
## Toyota Corona       21.5 2.465    3   4 120.1  97 3.70 20.01  1  0    1
## Dodge Challenger    15.5 3.520    3   8 318.0 150 2.76 16.87  0  0    2
## AMC Javelin         15.2 3.435    3   8 304.0 150 3.15 17.30  0  0    2
## Camaro Z28          13.3 3.840    3   8 350.0 245 3.73 15.41  0  0    4
## Pontiac Firebird    19.2 3.845    3   8 400.0 175 3.08 17.05  0  0    2
## Fiat X1-9           27.3 1.935    4   4  79.0  66 4.08 18.90  1  1    1
## Porsche 914-2       26.0 2.140    5   4 120.3  91 4.43 16.70  0  1    2
## Lotus Europa        30.4 1.513    5   4  95.1 113 3.77 16.90  1  1    2
## Ford Pantera L      15.8 3.170    5   8 351.0 264 4.22 14.50  0  1    4
## Ferrari Dino        19.7 2.770    5   6 145.0 175 3.62 15.50  0  1    6
## Maserati Bora       15.0 3.570    5   8 301.0 335 3.54 14.60  0  1    8
## Volvo 142E          21.4 2.780    4   4 121.0 109 4.11 18.60  1  1    2
```
]
]

]

---

# Calculating statistical summaries by group .font_small[Tidyverse]

🎯 Calculate the _average_ weight (`wt`) of a car for each gear type in (`gear`)  `mtcars`

```r
mtcars %>% 
  group_by(gear) %>% 
  summarise(avg_wt = mean(wt))
```

```
## `summarise()` ungrouping output (override with `.groups` argument)
```

```
## # A tibble: 3 x 2
##    gear avg_wt
##   <dbl>  <dbl>
## 1     3   3.89
## 2     4   2.62
## 3     5   2.63
```

]
.item[
{{content}}
]
]
--

🎯 Calculate the _median_ weight (`wt`) of a car for each gear (`gear`) and engine (`vs`) type in  `mtcars`

```r
mtcars %>% 
  group_by(gear, vs) %>% 
  summarise(avg_wt = mean(wt),
            med_wt = median(wt))
```

```
## `summarise()` regrouping output by 'gear' (override with `.groups` argument)
```

```
## # A tibble: 6 x 4
## # Groups:   gear [3]
##    gear    vs avg_wt med_wt
##   <dbl> <dbl>  <dbl>  <dbl>
## 1     3     0   4.10   3.81
## 2     3     1   3.05   3.22
## 3     4     0   2.75   2.75
## 4     4     1   2.59   2.55
## 5     5     0   2.91   2.97
## 6     5     1   1.51   1.51
```

---

#  `across` .tag.flash.animated[NEW in `dplyr` v1.0.0]

* Using `across`, you can more easily apply a function to multiple columns

```r
mtcars %>% 
  group_by(gear, vs) %>% 
* summarise(across(everything(), mean))
```

```
## # A tibble: 6 x 11
## # Groups:   gear [3]
##    gear    vs   mpg   cyl  disp    hp  drat    wt  qsec    am  carb
##   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1     3     0  15.0  8    358.  194.   3.12  4.10  17.1   0    3.08
## 2     3     1  20.3  5.33 201.  104    3.18  3.05  19.9   0    1   
## 3     4     0  21    6    160   110    3.9   2.75  16.7   1    4   
## 4     4     1  25.2  4.4  116.   85.4  4.07  2.59  19.4   0.6  2   
## 5     5     0  19.1  6.5  229.  216.   3.95  2.91  15.3   1    5   
## 6     5     1  30.4  4     95.1 113    3.77  1.51  16.9   1    2
```

---

#  `where` .tag.flash.animated[NEW in `dplyr` v1.0.0]

* You can combine `across` with the selection helper `where`

```r
mtcars %>% 
  group_by(gear, vs) %>% 
* summarise(across(where(function(x) n_distinct(x) > 10), mean))
```

```
## # A tibble: 6 x 8
## # Groups:   gear [3]
##    gear    vs   mpg  disp    hp  drat    wt  qsec
##   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1     3     0  15.0 358.  194.   3.12  4.10  17.1
## 2     3     1  20.3 201.  104    3.18  3.05  19.9
## 3     4     0  21   160   110    3.9   2.75  16.7
## 4     4     1  25.2 116.   85.4  4.07  2.59  19.4
## 5     5     0  19.1 229.  216.   3.95  2.91  15.3
## 6     5     1  30.4  95.1 113    3.77  1.51  16.9
```

---

#  `c_across` .tag.flash.animated[NEW in `dplyr` v1.0.0]

* Remember tidy selection only works with functions that are compatible

```r
mtcars %>% 
  rowwise() %>% 
  summarise(disp = disp, hp = hp, drat = drat, wt = wt,
*           score = sum(c_across(disp:wt)))
```

```
## # A tibble: 32 x 5
##     disp    hp  drat    wt score
##    <dbl> <dbl> <dbl> <dbl> <dbl>
##  1  160    110  3.9   2.62  277.
##  2  160    110  3.9   2.88  277.
##  3  108     93  3.85  2.32  207.
##  4  258    110  3.08  3.22  374.
##  5  360    175  3.15  3.44  542.
##  6  225    105  2.76  3.46  336.
##  7  360    245  3.21  3.57  612.
##  8  147.    62  3.69  3.19  216.
##  9  141.    95  3.92  3.15  243.
## 10  168.   123  3.92  3.44  298.
## # … with 22 more rows
```
---

#  `rowwise`?

* What happens if you omit `rowwise`?

```r
mtcars %>% 
  #rowwise() %>% 
  summarise(disp = disp, hp = hp, drat = drat, wt = wt,
*           score = sum(c_across(disp:wt)))
```

```
##     disp  hp drat    wt    score
## 1  160.0 110 3.90 2.620 12295.14
## 2  160.0 110 3.90 2.875 12295.14
## 3  108.0  93 3.85 2.320 12295.14
## 4  258.0 110 3.08 3.215 12295.14
## 5  360.0 175 3.15 3.440 12295.14
## 6  225.0 105 2.76 3.460 12295.14
## 7  360.0 245 3.21 3.570 12295.14
## 8  146.7  62 3.69 3.190 12295.14
## 9  140.8  95 3.92 3.150 12295.14
## 10 167.6 123 3.92 3.440 12295.14
## 11 167.6 123 3.92 3.440 12295.14
## 12 275.8 180 3.07 4.070 12295.14
## 13 275.8 180 3.07 3.730 12295.14
## 14 275.8 180 3.07 3.780 12295.14
## 15 472.0 205 2.93 5.250 12295.14
## 16 460.0 215 3.00 5.424 12295.14
## 17 440.0 230 3.23 5.345 12295.14
## 18  78.7  66 4.08 2.200 12295.14
## 19  75.7  52 4.93 1.615 12295.14
## 20  71.1  65 4.22 1.835 12295.14
## 21 120.1  97 3.70 2.465 12295.14
## 22 318.0 150 2.76 3.520 12295.14
## 23 304.0 150 3.15 3.435 12295.14
## 24 350.0 245 3.73 3.840 12295.14
## 25 400.0 175 3.08 3.845 12295.14
## 26  79.0  66 4.08 1.935 12295.14
## 27 120.3  91 4.43 2.140 12295.14
## 28  95.1 113 3.77 1.513 12295.14
## 29 351.0 264 4.22 3.170 12295.14
## 30 145.0 175 3.62 2.770 12295.14
## 31 301.0 335 3.54 3.570 12295.14
## 32 121.0 109 4.11 2.780 12295.14
```

---

# <i class="fas fa-code"></i> If you installed the `dwexercise` package, <br> run below in your R console

```r
learnr::run_tutorial("day1-exercise-02", package = "dwexercise")
```

<br>

# <i class="fas fa-link"></i> If the above doesn't work for you, go [here](https://ebsmonash.shinyapps.io/dw-day1-exercise-02).

# <i class="fas fa-question"></i> Questions or issues, let us know!
<center>
<div class="countdown clock" id="timer_5fc4c5aa" style="right:0;bottom:0;" data-warnwhen="0">
<code class="countdown-time"><span class="countdown-digits minutes">15</span><span class="countdown-digits colon">:</span><span class="countdown-digits seconds">00</span></code>
</div>
</center>

---

# Session Information

```r
devtools::session_info()
```

```
## ─ Session info ───────────────────────────────────────────────────────────────
##  setting  value                       
##  version  R version 4.0.1 (2020-06-06)
##  os       macOS Catalina 10.15.7      
##  system   x86_64, darwin17.0          
##  ui       X11                         
##  language (EN)                        
##  collate  en_AU.UTF-8                 
##  ctype    en_AU.UTF-8                 
##  tz       Australia/Melbourne         
##  date     2020-11-30                  
## 
## ─ Packages ───────────────────────────────────────────────────────────────────
##  package     * version    date       lib source                              
##  anicon        0.1.0      2020-06-21 [1] Github (emitanaka/anicon@0b756df)   
##  assertthat    0.2.1      2019-03-21 [2] CRAN (R 4.0.0)                      
##  callr         3.5.1      2020-10-13 [1] CRAN (R 4.0.2)                      
##  cli           2.2.0      2020-11-20 [1] CRAN (R 4.0.1)                      
##  countdown     0.3.5      2020-07-20 [1] Github (gadenbuie/countdown@a544fa4)
##  crayon        1.3.4      2017-09-16 [2] CRAN (R 4.0.0)                      
##  desc          1.2.0      2018-05-01 [2] CRAN (R 4.0.0)                      
##  devtools      2.3.2      2020-09-18 [1] CRAN (R 4.0.2)                      
##  digest        0.6.27     2020-10-24 [1] CRAN (R 4.0.2)                      
##  dplyr       * 1.0.2      2020-08-18 [1] CRAN (R 4.0.2)                      
##  ellipsis      0.3.1      2020-05-15 [2] CRAN (R 4.0.0)                      
##  evaluate      0.14       2019-05-28 [2] CRAN (R 4.0.0)                      
##  fansi         0.4.1      2020-01-08 [2] CRAN (R 4.0.0)                      
##  flair       * 0.0.2      2020-11-21 [1] Github (kbodwin/flair@b3054f2)      
##  fs            1.5.0      2020-07-31 [1] CRAN (R 4.0.2)                      
##  generics      0.1.0      2020-10-31 [2] CRAN (R 4.0.2)                      
##  glue          1.4.2      2020-08-27 [1] CRAN (R 4.0.2)                      
##  htmltools     0.5.0      2020-06-16 [1] CRAN (R 4.0.2)                      
##  icon          0.1.0      2020-06-21 [1] Github (emitanaka/icon@8458546)     
##  knitr         1.30       2020-09-22 [1] CRAN (R 4.0.2)                      
##  lifecycle     0.2.0      2020-03-06 [1] CRAN (R 4.0.0)                      
##  magrittr      2.0.1      2020-11-17 [1] CRAN (R 4.0.2)                      
##  memoise       1.1.0      2017-04-21 [2] CRAN (R 4.0.0)                      
##  pillar        1.4.7      2020-11-20 [1] CRAN (R 4.0.1)                      
##  pkgbuild      1.1.0      2020-07-13 [2] CRAN (R 4.0.1)                      
##  pkgconfig     2.0.3      2019-09-22 [2] CRAN (R 4.0.0)                      
##  pkgload       1.1.0      2020-05-29 [2] CRAN (R 4.0.0)                      
##  prettyunits   1.1.1      2020-01-24 [2] CRAN (R 4.0.0)                      
##  processx      3.4.4      2020-09-03 [1] CRAN (R 4.0.2)                      
##  ps            1.4.0      2020-10-07 [1] CRAN (R 4.0.2)                      
##  purrr         0.3.4      2020-04-17 [2] CRAN (R 4.0.0)                      
##  R6            2.5.0      2020-10-28 [1] CRAN (R 4.0.2)                      
##  remotes       2.2.0      2020-07-21 [1] CRAN (R 4.0.2)                      
##  rlang         0.4.8      2020-10-08 [1] CRAN (R 4.0.2)                      
##  rmarkdown     2.5        2020-10-21 [1] CRAN (R 4.0.1)                      
##  rprojroot     2.0.2      2020-11-15 [1] CRAN (R 4.0.2)                      
##  rstudioapi    0.13       2020-11-12 [1] CRAN (R 4.0.1)                      
##  sessioninfo   1.1.1      2018-11-05 [2] CRAN (R 4.0.0)                      
##  stringi       1.5.3      2020-09-09 [2] CRAN (R 4.0.2)                      
##  stringr       1.4.0      2019-02-10 [2] CRAN (R 4.0.0)                      
##  testthat      3.0.0      2020-10-31 [1] CRAN (R 4.0.2)                      
##  tibble        3.0.4.9000 2020-11-26 [1] Github (tidyverse/tibble@9eeef4d)   
##  tidyselect    1.1.0      2020-05-11 [2] CRAN (R 4.0.0)                      
##  usethis       1.6.3      2020-09-17 [1] CRAN (R 4.0.2)                      
##  utf8          1.1.4      2018-05-24 [2] CRAN (R 4.0.0)                      
##  vctrs         0.3.5.9000 2020-11-26 [1] Github (r-lib/vctrs@957baf7)        
##  whisker       0.4        2019-08-28 [2] CRAN (R 4.0.0)                      
##  withr         2.3.0      2020-09-22 [1] CRAN (R 4.0.2)                      
##  xaringan      0.18       2020-10-21 [1] CRAN (R 4.0.2)                      
##  xfun          0.19       2020-10-30 [1] CRAN (R 4.0.2)                      
##  yaml          2.2.1      2020-02-01 [1] CRAN (R 4.0.2)                      
## 
## [1] /Users/etan0038/Library/R/4.0/library
## [2] /Library/Frameworks/R.framework/Versions/4.0/Resources/library
```
]

These slides are licensed under <br><center><a href="https://creativecommons.org/licenses/by-sa/3.0/au/"><img src="images/cc.svg" style="height:2em;"/><img src="images/by.svg" style="height:2em;"/><img src="images/sa.svg" style="height:2em;"/></a></center>