#‘stat_smooth’ featurette

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# .Large[#'ggplot::stat_smooth' featurette]
## .small[featuring [ggplot2::stat_smooth() ](https://github.com/tidyverse/ggplot2/) and mtcars]
#### .tiny[Gina Reynolds | 2023-10-25 |Image credit: Peter Broomfield, Upsplash]
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Title

---

count: false

.panel1-feature-auto[

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

]

---
count: false

.panel1-feature-auto[

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

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

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
* ggplot(aes(wt, mpg))
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_03_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
* geom_point()
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_04_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
  geom_point() +
* geom_smooth()
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_05_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
  geom_point() +
  geom_smooth() +
* stat_smooth(geom = "point",
*             color = "blue",
*             xseq = mtcars$wt)
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_06_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
  geom_point() +
  geom_smooth() +
  stat_smooth(geom = "point",
              color = "blue",
              xseq = mtcars$wt) +
* stat_smooth(geom = "segment",
*             color = "darkred",
*             xseq = mtcars$wt,
*             xend = mtcars$wt,
*             yend = mtcars$mpg)
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_07_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
  geom_point() +
  geom_smooth() +
  stat_smooth(geom = "point",
              color = "blue",
              xseq = mtcars$wt) +
  stat_smooth(geom = "segment",
              color = "darkred",
              xseq = mtcars$wt,
              xend = mtcars$wt,
              yend = mtcars$mpg) +
# intercept for linear model
* stat_smooth(geom = "point",
*            color = "green",
*            xseq = 0,
*            method = lm,
*            size = 7)
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_08_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)
mtcars %>%
  ggplot(aes(wt, mpg)) +
  geom_point() +
  geom_smooth() +
  stat_smooth(geom = "point",
              color = "blue",
              xseq = mtcars$wt) +
  stat_smooth(geom = "segment",
              color = "darkred",
              xseq = mtcars$wt,
              xend = mtcars$wt,
              yend = mtcars$mpg) +
# intercept for linear model
  stat_smooth(geom = "point",
             color = "green",
             xseq = 0,
             method = lm,
             size = 7) +
* stat_smooth(color = "green",
*             xseq = c(0, mtcars$wt),
*             method = lm)
```
]
 
.panel2-feature-auto[
![](stat-smooth-mtcars_files/figure-html/feature_auto_09_output-1.png)
]

---

### Check out {ggplot2} which does the computation in ggcirclepack

- https://github.com/tidyverse/ggplot2/

---

### Check out {ggsmoothfit} which explores more stat_smooth uses for educators

- https://github.com/EvaMaeRey/ggsmoothfit

---

### Check out flipbookr, used to build this featurette

- https://github.com/EvaMaeRey/flipbookr
- discussion: https://github.com/EvaMaeRey/flipbookr/blob/master/docs/draft_jasa_submission.pdf

---

### Check out more featurettes

- https://EvaMaeRey.github.io/featurette