Data Visualisation with R Workshop Part 1

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# <span style="text-shadow: 2px 2px 30px white;">Data Visualisation with R<br>Workshop Part 1</span>

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<br><br>
## Jazzing up your plots <i class='fas fa-paint-brush'></i>

<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[
6th Dec 2021 @ Statistical Society of Australia NSW Branch | Zoom
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# .circle-big[5]
# Publication-ready plots

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# The `ggplot` object

* .monash-blue[**Modifiable**]: `ggplot` object can be modified
* .monash-blue[**Generalisable**]: `ggplot2` uses a cohesive and complex system under the hood to make many kinds of plots
* .monash-blue[**Extensible**]: the system can be extended to make specialised plots or add more features if the same "grammar" is adopted

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# Motor Trend Car Road Tests

The `mtcars` is from the `datasets` 📦 (loaded by default)

```r
mtcars_df <- mtcars %>% rownames_to_column("car")
glimpse(mtcars_df)
```

```
## Rows: 32
## Columns: 12
## $ car  <chr> "Mazda RX4", "Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Ho…
## $ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8,…
## $ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8,…
## $ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 16…
## $ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180…
## $ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,…
## $ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.…
## $ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18…
## $ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0,…
## $ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0,…
## $ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3,…
## $ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2,…
```
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# `ggrepel` 📦 .font_small[one of my favorites!]

```r
ggplot(mtcars_df, aes(wt, mpg)) + 
  geom_point(size = 2, color = "red") + 
  geom_text(aes(label = car)) +
  ggtitle("geom_text()")
```

<img src="images/part1-session4/unnamed-chunk-5-1.png" style="display: block; margin: auto;" />
{{content}}
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```r
library(ggrepel)
set.seed(1)
ggplot(mtcars_df, aes(wt, mpg)) + 
  geom_point(size = 2, color = "red") + 
  geom_text_repel(aes(label = car))+
  ggtitle("geom_text_repel()")
```

<img src="images/part1-session4/unnamed-chunk-6-1.png" style="display: block; margin: auto;" />
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.footnote[
Kamil Slowikowski (2020). ggrepel: Automatically Position
  Non-Overlapping Text Labels with 'ggplot2'. R package version 0.8.2.
  https://CRAN.R-project.org/package=ggrepel
]

There are many [extension packages](https://exts.ggplot2.tidyverse.org/)!

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# Themes

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# `theme`: modify the *look* of texts

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# `element_text()`

```r
ggplot(diamonds, aes(carat, price)) + 
  geom_hex() +
 labs(title = "Diamond") +
 theme(axis.title.x = element_text(size = 30,
                                 color = "red",
                                 face = "bold",
                                 angle = 10,
                                 family = "Fira Code"),
       legend.title = element_text(size = 25,
                                   color = "#ef42eb", 
                                   margin = margin(b = 5)),
       plot.title = element_text(size = 35,
                                 face = "bold",
                                 family = "Nunito",
                                 color = "blue"
                                ))
```

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# `theme`: modify the *look* of the lines

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# `element_line()`

```r
ggplot(penguins, aes(bill_length_mm, bill_depth_mm)) + 
  geom_point() +
  theme(axis.line.y = element_line(color = "black",
                                  size = 1.2,
                                  arrow = grid::arrow()),
       axis.line.x = element_line(linetype = "dashed", 
                                  color = "brown",
                                  size = 1.2),
       axis.ticks = element_line(color = "red", size = 1.1),
       axis.ticks.length = unit(3, "mm"),
       panel.grid.major = element_line(color = "blue", 
                                       size = 1.2),
       panel.grid.minor = element_line(color = "#0080ff",
                                       size = 1.2,
                                       linetype = "dotted"))
```

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# `theme`: modify the *look* of the <br>rectangular regions

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# `element_rect()`

```r
ggplot(penguins, aes(bill_length_mm, bill_depth_mm)) + 
 geom_point(aes(color = species)) +
 theme(
  legend.background = element_rect(fill = "#fff6c2", 
                                  color = "black",
                               linetype = "dashed"),
  legend.key = element_rect(fill = "grey", color = "brown"),
  panel.background = element_rect(fill = "#005F59",
                          color = "red", size = 3),
  panel.border = element_rect(color = "black", 
                              fill = "transparent",
                    linetype = "dashed", size = 3),
  plot.background = element_rect(fill = "#a1dce9",
                                color = "black",
                                 size = 1.3),
  legend.position = "bottom")
```

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