Exploded code

# Exploded code
## Using flipbookr and xaringan
### Me

---

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---

```r
*library(tidyverse)
```
]
 
.panel2-setup-auto[

]

---
count: false

```r
library(tidyverse)
*knitr::opts_chunk$set(echo = TRUE)
```
]
 
.panel2-setup-auto[

]

---

```r
*datasets::anscombe
```
]
 
.panel2-anscombe-auto[

```
   x1 x2 x3 x4    y1   y2    y3    y4
1  10 10 10  8  8.04 9.14  7.46  6.58
2   8  8  8  8  6.95 8.14  6.77  5.76
3  13 13 13  8  7.58 8.74 12.74  7.71
4   9  9  9  8  8.81 8.77  7.11  8.84
5  11 11 11  8  8.33 9.26  7.81  8.47
6  14 14 14  8  9.96 8.10  8.84  7.04
7   6  6  6  8  7.24 6.13  6.08  5.25
8   4  4  4 19  4.26 3.10  5.39 12.50
9  12 12 12  8 10.84 9.13  8.15  5.56
10  7  7  7  8  4.82 7.26  6.42  7.91
11  5  5  5  8  5.68 4.74  5.73  6.89
```
]

---
count: false

```r
datasets::anscombe %>%
* pivot_longer(cols = 1:8)
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 88 x 2
   name  value
   <chr> <dbl>
 1 x1    10   
 2 x2    10   
 3 x3    10   
 4 x4     8   
 5 y1     8.04
 6 y2     9.14
 7 y3     7.46
 8 y4     6.58
 9 x1     8   
10 x2     8   
11 x3     8   
12 x4     8   
13 y1     6.95
14 y2     8.14
15 y3     6.77
16 y4     5.76
17 x1    13   
18 x2    13   
19 x3    13   
20 x4     8   
21 y1     7.58
22 y2     8.74
23 y3    12.7 
24 y4     7.71
25 x1     9   
26 x2     9   
27 x3     9   
28 x4     8   
29 y1     8.81
30 y2     8.77
31 y3     7.11
32 y4     8.84
33 x1    11   
34 x2    11   
35 x3    11   
36 x4     8   
37 y1     8.33
38 y2     9.26
39 y3     7.81
40 y4     8.47
41 x1    14   
42 x2    14   
43 x3    14   
44 x4     8   
45 y1     9.96
46 y2     8.1 
47 y3     8.84
48 y4     7.04
49 x1     6   
50 x2     6   
51 x3     6   
52 x4     8   
53 y1     7.24
54 y2     6.13
55 y3     6.08
# … with 33 more rows
```
]

---
count: false

```r
datasets::anscombe %>%
  pivot_longer(cols = 1:8) %>%
* mutate(group = str_extract(name, "\\d"))
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 88 x 3
   name  value group
   <chr> <dbl> <chr>
 1 x1    10    1    
 2 x2    10    2    
 3 x3    10    3    
 4 x4     8    4    
 5 y1     8.04 1    
 6 y2     9.14 2    
 7 y3     7.46 3    
 8 y4     6.58 4    
 9 x1     8    1    
10 x2     8    2    
11 x3     8    3    
12 x4     8    4    
13 y1     6.95 1    
14 y2     8.14 2    
15 y3     6.77 3    
16 y4     5.76 4    
17 x1    13    1    
18 x2    13    2    
19 x3    13    3    
20 x4     8    4    
21 y1     7.58 1    
22 y2     8.74 2    
23 y3    12.7  3    
24 y4     7.71 4    
25 x1     9    1    
26 x2     9    2    
27 x3     9    3    
28 x4     8    4    
29 y1     8.81 1    
30 y2     8.77 2    
31 y3     7.11 3    
32 y4     8.84 4    
33 x1    11    1    
34 x2    11    2    
35 x3    11    3    
36 x4     8    4    
37 y1     8.33 1    
38 y2     9.26 2    
39 y3     7.81 3    
40 y4     8.47 4    
41 x1    14    1    
42 x2    14    2    
43 x3    14    3    
44 x4     8    4    
45 y1     9.96 1    
46 y2     8.1  2    
47 y3     8.84 3    
48 y4     7.04 4    
49 x1     6    1    
50 x2     6    2    
51 x3     6    3    
52 x4     8    4    
53 y1     7.24 1    
54 y2     6.13 2    
55 y3     6.08 3    
# … with 33 more rows
```
]

---
count: false

```r
datasets::anscombe %>%
  pivot_longer(cols = 1:8) %>%
  mutate(group = str_extract(name, "\\d")) %>%
* mutate(var = str_extract(name, "\\w"))
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 88 x 4
   name  value group var  
   <chr> <dbl> <chr> <chr>
 1 x1    10    1     x    
 2 x2    10    2     x    
 3 x3    10    3     x    
 4 x4     8    4     x    
 5 y1     8.04 1     y    
 6 y2     9.14 2     y    
 7 y3     7.46 3     y    
 8 y4     6.58 4     y    
 9 x1     8    1     x    
10 x2     8    2     x    
11 x3     8    3     x    
12 x4     8    4     x    
13 y1     6.95 1     y    
14 y2     8.14 2     y    
15 y3     6.77 3     y    
16 y4     5.76 4     y    
17 x1    13    1     x    
18 x2    13    2     x    
19 x3    13    3     x    
20 x4     8    4     x    
21 y1     7.58 1     y    
22 y2     8.74 2     y    
23 y3    12.7  3     y    
24 y4     7.71 4     y    
25 x1     9    1     x    
26 x2     9    2     x    
27 x3     9    3     x    
28 x4     8    4     x    
29 y1     8.81 1     y    
30 y2     8.77 2     y    
31 y3     7.11 3     y    
32 y4     8.84 4     y    
33 x1    11    1     x    
34 x2    11    2     x    
35 x3    11    3     x    
36 x4     8    4     x    
37 y1     8.33 1     y    
38 y2     9.26 2     y    
39 y3     7.81 3     y    
40 y4     8.47 4     y    
41 x1    14    1     x    
42 x2    14    2     x    
43 x3    14    3     x    
44 x4     8    4     x    
45 y1     9.96 1     y    
46 y2     8.1  2     y    
47 y3     8.84 3     y    
48 y4     7.04 4     y    
49 x1     6    1     x    
50 x2     6    2     x    
51 x3     6    3     x    
52 x4     8    4     x    
53 y1     7.24 1     y    
54 y2     6.13 2     y    
55 y3     6.08 3     y    
# … with 33 more rows
```
]

---
count: false

```r
datasets::anscombe %>%
  pivot_longer(cols = 1:8) %>%
  mutate(group = str_extract(name, "\\d")) %>%
  mutate(var = str_extract(name, "\\w")) %>%
* select(-name)
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 88 x 3
   value group var  
   <dbl> <chr> <chr>
 1 10    1     x    
 2 10    2     x    
 3 10    3     x    
 4  8    4     x    
 5  8.04 1     y    
 6  9.14 2     y    
 7  7.46 3     y    
 8  6.58 4     y    
 9  8    1     x    
10  8    2     x    
11  8    3     x    
12  8    4     x    
13  6.95 1     y    
14  8.14 2     y    
15  6.77 3     y    
16  5.76 4     y    
17 13    1     x    
18 13    2     x    
19 13    3     x    
20  8    4     x    
21  7.58 1     y    
22  8.74 2     y    
23 12.7  3     y    
24  7.71 4     y    
25  9    1     x    
26  9    2     x    
27  9    3     x    
28  8    4     x    
29  8.81 1     y    
30  8.77 2     y    
31  7.11 3     y    
32  8.84 4     y    
33 11    1     x    
34 11    2     x    
35 11    3     x    
36  8    4     x    
37  8.33 1     y    
38  9.26 2     y    
39  7.81 3     y    
40  8.47 4     y    
41 14    1     x    
42 14    2     x    
43 14    3     x    
44  8    4     x    
45  9.96 1     y    
46  8.1  2     y    
47  8.84 3     y    
48  7.04 4     y    
49  6    1     x    
50  6    2     x    
51  6    3     x    
52  8    4     x    
53  7.24 1     y    
54  6.13 2     y    
55  6.08 3     y    
# … with 33 more rows
```
]

---
count: false

```r
datasets::anscombe %>%
  pivot_longer(cols = 1:8) %>%
  mutate(group = str_extract(name, "\\d")) %>%
  mutate(var = str_extract(name, "\\w")) %>%
  select(-name) %>%
* pivot_wider(names_from = var,
*             values_from = value)
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 4 x 3
  group x          y         
  <chr> <list>     <list>    
1 1     <dbl [11]> <dbl [11]>
2 2     <dbl [11]> <dbl [11]>
3 3     <dbl [11]> <dbl [11]>
4 4     <dbl [11]> <dbl [11]>
```
]

---
count: false

```r
datasets::anscombe %>%
  pivot_longer(cols = 1:8) %>%
  mutate(group = str_extract(name, "\\d")) %>%
  mutate(var = str_extract(name, "\\w")) %>%
  select(-name) %>%
  pivot_wider(names_from = var,
              values_from = value) %>%
* unnest()
```
]
 
.panel2-anscombe-auto[

```
# A tibble: 44 x 3
   group     x     y
   <chr> <dbl> <dbl>
 1 1        10  8.04
 2 1         8  6.95
 3 1        13  7.58
 4 1         9  8.81
 5 1        11  8.33
 6 1        14  9.96
 7 1         6  7.24
 8 1         4  4.26
 9 1        12 10.8 
10 1         7  4.82
11 1         5  5.68
12 2        10  9.14
13 2         8  8.14
14 2        13  8.74
15 2         9  8.77
16 2        11  9.26
17 2        14  8.1 
18 2         6  6.13
19 2         4  3.1 
20 2        12  9.13
21 2         7  7.26
22 2         5  4.74
23 3        10  7.46
24 3         8  6.77
25 3        13 12.7 
26 3         9  7.11
27 3        11  7.81
28 3        14  8.84
29 3         6  6.08
30 3         4  5.39
31 3        12  8.15
32 3         7  6.42
33 3         5  5.73
34 4         8  6.58
35 4         8  5.76
36 4         8  7.71
37 4         8  8.84
38 4         8  8.47
39 4         8  7.04
40 4         8  5.25
41 4        19 12.5 
42 4         8  5.56
43 4         8  7.91
44 4         8  6.89
```
]

---
count: false

]

---

```r
*tidy_anscombe
```
]
 
.panel2-anscombe_plot-auto[

---
count: false

```r
tidy_anscombe %>%
* ggplot()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_02_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
* aes(x = x, y = y)
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_03_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
* geom_point()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_04_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
* aes(color = group)
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_05_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
* facet_wrap(facets = vars(group))
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_06_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
* ggxmean::geom_x_mean()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_07_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
* ggxmean::geom_y_mean()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_08_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
  ggxmean::geom_y_mean() +
# mean of y
* ggxmean:::geom_x1sd(linetype = "dashed")
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_09_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
  ggxmean::geom_y_mean() +
# mean of y
  ggxmean:::geom_x1sd(linetype = "dashed") +
* ggxmean:::geom_y1sd(linetype = "dashed")
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_10_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
  ggxmean::geom_y_mean() +
# mean of y
  ggxmean:::geom_x1sd(linetype = "dashed") +
  ggxmean:::geom_y1sd(linetype = "dashed") +
# linear model
* ggxmean::geom_lm()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_11_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
  ggxmean::geom_y_mean() +
# mean of y
  ggxmean:::geom_x1sd(linetype = "dashed") +
  ggxmean:::geom_y1sd(linetype = "dashed") +
# linear model
  ggxmean::geom_lm() +
* ggxmean::geom_lm_formula()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_12_output-1.png)
]

---
count: false

```r
tidy_anscombe %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(color = group) +
  facet_wrap(facets = vars(group)) +
# mean of x
  ggxmean::geom_x_mean() +
  ggxmean::geom_y_mean() +
# mean of y
  ggxmean:::geom_x1sd(linetype = "dashed") +
  ggxmean:::geom_y1sd(linetype = "dashed") +
# linear model
  ggxmean::geom_lm() +
  ggxmean::geom_lm_formula() +
# Pearson correlation
* ggxmean:::geom_corrlabel()
```
]
 
.panel2-anscombe_plot-auto[
![](anscombes_exploded_files/figure-html/anscombe_plot_auto_13_output-1.png)
]