Prettiness with ggplot2

# Prettiness with ggplot2
## Amy Perfors
### adapted from Danielle Navarro: <a href="https://djnavarro.github.io/chdss2018/day2/ggplot-slides.html" class="uri">https://djnavarro.github.io/chdss2018/day2/ggplot-slides.html</a> <a href="https://djnavarro.github.io/satrdayjoburg/" class="uri">https://djnavarro.github.io/satrdayjoburg/</a>
### 18 December 2019

---

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# Data visualisation

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[@allison_horst](https://twitter.com/allison_horst)

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.font4[A plot of the frames data]
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```r
# load data
frames <- read_csv(here("data","frames_ex2.csv"))

# show data
frames
```

```
## # A tibble: 4,725 x 8
## id gender age condition sample_size n_obs test_item response
## <dbl> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 1 male 36 category small 2 1 8
## 2 1 male 36 category small 2 2 7
## 3 1 male 36 category small 2 3 6
## 4 1 male 36 category small 2 4 6
## 5 1 male 36 category small 2 5 5
## 6 1 male 36 category small 2 6 6
## 7 1 male 36 category small 2 7 3
## 8 1 male 36 category medium 6 1 9
## 9 1 male 36 category medium 6 2 7
## 10 1 male 36 category medium 6 3 5
## # … with 4,715 more rows
```
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# Summarise frames data

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```r
frames_small <- frames %>%
 group_by(
 age, condition, sample_size
 ) %>%
 summarise(
 response = mean(response)
 ) %>%
 ungroup()

frames_small
```
]]]
]]

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```
## # A tibble: 231 x 4
## age condition sample_size response
## <dbl> <chr> <chr> <dbl>
## 1 20 category large 3.86
## 2 20 category medium 4.21
## 3 20 category small 4.93
## 4 20 property large 4.37
## 5 20 property medium 4.31
## 6 20 property small 3.74
## 7 21 category large 5.5 
## 8 21 category medium 5.04
## 9 21 category small 5.46
## 10 21 property large 3.71
## # … with 221 more rows
```
]]]
]]

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A simple plot

```r
ggplot(
  frames_small, 
  aes(age, response)
) + 
geom_point()
```

- A little verbose?
- Not the prettiest plot?
- Why is it like this?

]]]
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![](ggplot-slides_files/figure-html/introplot-1.png)

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.font4[Painting a Picture]
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## A grammar...

- grammars compose & reuse small parts
- complex structures from simpler units

## ...of graphics

- uses the "painters model"
- a plot is built in layers
- each layer is drawn on top of the last

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[Image credit: Trinity Treft](https://unsplash.com/photos/waYWz3vAYJQ)

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A blank canvas

```r
ggplot()
```

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![](ggplot-slides_files/figure-html/blankcanvas-1.png)

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Specify the .orange[data]

```r
ggplot(
* data = frames_small
)
```

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.pad1[.font2[
![](ggplot-slides_files/figure-html/stillblankcanvas-1.png)

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A .orange[mapping] from data onto plot .orange[aesthetics]

```r
ggplot(
  data = frames_small,
* mapping = aes(
*   x = age,
*   y = response
* )
)
```

- .orange[x]-axis location
- .orange[y]-axis location
- .orange[colour] of marker
- .orange[fill] of a marker
- .orange[shape] of a marker, etc.
]]]
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![](ggplot-slides_files/figure-html/aesthetics-1.png)

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Add a plot .orange[layer]

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response
  ) 
) + 
*geom_point()
```

- the .orange[points]
- the .orange[lines]
- the .orange[histograms]
- etc

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/add_layer-1.png)

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Add layer-specific parameters

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response
  ) 
) + 
*geom_point(size = 3)
```

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/add_fixedaesthetic-1.png)

]]
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.pull.left[.pad1[.font2[
Add layer-specific mappings

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
*geom_point(size = 3)
```

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/add_layeraesthetic-1.png)

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Add more layers to the plotcake

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
geom_point(size = 3) +
*geom_rug()
```

]]]
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.pad1[.font2[
![](ggplot-slides_files/figure-html/two_layers-1.png)

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Split into .orange[facets]

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
geom_point(size = 3) +
geom_rug() + 
*facet_wrap(vars(sample_size))
```

]]]
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![](ggplot-slides_files/figure-html/add_facets-1.png)

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.pull.left[.pad1[.font2[
Modify the .orange[theme]

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
geom_point(size = 3) +
geom_rug() + 
facet_wrap(vars(sample_size)) +
*theme_bw()
```

]]]
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.pad1[.font2[
![](ggplot-slides_files/figure-html/add_theme-1.png)

]]
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(Nothing to see here...)

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition)) + 
geom_point(size = 3) +
geom_rug() + 
facet_wrap(vars(sample_size)) +
theme_bw()
```

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/add_theme2-1.png)

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Make nicer titles

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
geom_point(size = 3) +
geom_rug() + 
facet_wrap(vars(sample_size)) +
theme_bw() +
*labs(
* title = "Response by age",
* subtitle = "Varying condition and sample size",
* x = "Age (years)",
* y = "Response (1=no, 9=yes)"
*) 
```

]]]
]]

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![](ggplot-slides_files/figure-html/add_titles-1.png)

]]
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---
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.column.bg-main1[.content.vtop.center[
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Done! Our plotcake is baked.

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = age, 
    y = response,
    colour = condition
  ) 
) + 
geom_point(size = 3) +
geom_rug() + 
facet_wrap(vars(sample_size)) +
theme_bw() +
labs(
  title = "Response by age",
  subtitle = "Varying condition and sample size",
  x = "Age (years)",
  y = "Response (1=no, 9=yes)"
)
```
]]]
]]

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![](ggplot-slides_files/figure-html/done-1.png)

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---
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All the ingredients are needed!

- Data
- Aesthetics
- Layers
- Facets
- Theme
- (Coordinates)
- (Scales)

]]]
]]

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So when I type this...

```r
ggplot(
  frames_small, 
  aes(age, response)
) + 
geom_point()
```

]]]
]]

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.column.bg-main1[.content.vtop.center[
.pull.left[.pad1[.font2[
All the ingredients are needed!

- Data
- Aesthetics
- Layers
- Facets
- Theme
- (Coordinates)
- (Scales)

]]]
]]

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What I get is this...

```r
ggplot(
  data = frames_small, 
  mapping = aes(
    x = age, y = response)) + 
layer(
  geom = "point",
  stat = "identity",
  position = "identity") + 
facet_null() +
theme_grey() + 
coord_cartesian() + 
scale_x_continuous() + 
scale_y_continuous()
```

]]]
]]

---

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# New summary of data

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```r
frames_test <- frames %>%
 group_by(
 test_item, condition, sample_size
 ) %>%
 summarise(
 response = mean(response)
 ) %>%
 ungroup()

frames_test
```
]]]
]]

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```
## # A tibble: 42 x 4
## test_item condition sample_size response
## <dbl> <chr> <chr> <dbl>
## 1 1 category large 7.60
## 2 1 category medium 7.32
## 3 1 category small 6.07
## 4 1 property large 7.16
## 5 1 property medium 6.66
## 6 1 property small 5.78
## 7 2 category large 7.51
## 8 2 category medium 7.17
## 9 2 category small 6.26
## 10 2 property large 7.20
## # … with 32 more rows
```
]]]
]]

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.pull.left[.pad1[.font2[
Locations (.orange[x] and .orange[y]) are aesthetics

```r
ggplot(
  data = frames_test,
  mapping = aes(
*   x = test_item,
*   y = response
  ) 
) + 
geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-19-1.png)

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.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
The .orange[colour] can be an aesthetic

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
*   colour = condition
  ) 
) + 
geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-21-1.png)

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.column.bg-main1[.content.vtop.center[

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The .orange[group] can matter!

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = condition,
*   group = sample_size
  ) 
) + 
geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-23-1.png)

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.pull.left[.pad1[.font2[
But maybe we want to colour by sample size

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
*   group = sample_size
  ) 
) + 
geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-25-1.png)

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The .orange[fill] can be an aesthetic

```r
ggplot(
  data = frames,
  mapping = aes(
    x = response,
*   fill = sample_size
  ) 
) + 
geom_histogram() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-27-1.png)

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These are terrible colours. Use palettes instead!

```r
# install.packages("RColorBrewer")
library(RColorBrewer)
display.brewer.all()
```

]]]
]]

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Can do fills...

```r
ggplot(
  data = frames,
  mapping = aes(
    x = response,
    fill = sample_size
  ) 
) + 
geom_histogram() +
*scale_fill_brewer(palette = "Dark2") +
facet_wrap(vars(condition))
```

]]]
]]

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.pull.left[.pad1[.font2[
And colours...

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
    group = sample_size 
  ) 
) + 
geom_line() +
*scale_color_brewer(palette = "Set1") +
facet_wrap(vars(condition))
```

]]]
]]

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---

---

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.font4[Geoms]
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Points and lines are "simple" geoms

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
    group = sample_size 
  ) 
) + 
*geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-35-1.png)
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.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Points and lines are "simple" geoms

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
    group = sample_size 
  ) 
) + 
*geom_point() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-37-1.png)
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Geoms can be layered and take parameters

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
    group = sample_size 
  ) 
) + 
*geom_point(size=4) +
*geom_line() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-39-1.png)
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.pull.left[.pad1[.font2[
The order of geoms matters

```r
ggplot(
  data = frames_test,
  mapping = aes(
    x = test_item,
    y = response,
    colour = sample_size,
    group = sample_size 
  ) 
) + 
*geom_line() +
*geom_point(size=4) +
facet_wrap(vars(condition))
```

]]]
]]

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Geoms come in many varieties...

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = sample_size,
    y = response
  ) 
) + 
*geom_boxplot() +
facet_wrap(vars(condition))
```

]]]
]]

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![](ggplot-slides_files/figure-html/unnamed-chunk-43-1.png)
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Geoms come in many varieties...

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = sample_size,
    y = response
  ) 
) + 
*geom_violin() +
facet_wrap(vars(condition))
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-45-1.png)
]]
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class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = sample_size,
    y = response
  ) 
) + 
geom_violin() +
*geom_jitter() +
facet_wrap(vars(condition))
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-47-1.png)
]]
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---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames_small,
  mapping = aes(
    x = sample_size,
    y = response
  ) 
) + 
geom_violin() +
*geom_jitter(alpha=0.5,size=3) +
facet_wrap(vars(condition))
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-49-1.png)
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.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames,
  mapping = aes(
    x = test_item,
    y = response
  ) 
) + 
*geom_count()
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-51-1.png)
]]
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class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames,
  mapping = aes(
    x = test_item,
    y = response
  ) 
) + 
geom_count() + 
*facet_grid(condition ~ sample_size)
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-53-1.png)
]]
]]

---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames,
  mapping = aes(
    x = test_item,
    y = response
  ) 
) + 
*geom_count(aes(colour = ..n..)) +
facet_grid(condition ~ sample_size)
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-55-1.png)
]]
]]

---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Geoms come in many varieties...

```r
ggplot(
  data = frames,
  mapping = aes(
    x = test_item,
    y = response
  ) 
) + 
geom_point(size=4) +
*geom_smooth() +
facet_wrap(sample_size ~ condition)
```

]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-57-1.png)
]]
]]

---

.reveal-text.bg-main2[.pad1[
.font4[Error bars, contours]
]]

---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Summarise with errors

```r
library(lsr)

frames_mean <- frames %>%
 group_by(
 condition, sample_size, test_item
 ) %>%
 summarise(
 resp = mean(response),
 lower = ciMean(response)[1],
 upper = ciMean(response)[2]
 )

frames_mean
```
]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[

```
## # A tibble: 42 x 6
## # Groups: condition, sample_size [6]
## condition sample_size test_item resp lower upper
## <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 category large 1 7.60 7.16 8.04
## 2 category large 2 7.51 7.14 7.88
## 3 category large 3 6.39 5.95 6.84
## 4 category large 4 5.39 4.86 5.93
## 5 category large 5 4.72 4.13 5.30
## 6 category large 6 4.43 3.79 5.07
## 7 category large 7 4.18 3.53 4.82
## 8 category medium 1 7.32 6.85 7.78
## 9 category medium 2 7.17 6.80 7.54
## 10 category medium 3 5.98 5.54 6.42
## # … with 32 more rows
```
]]
]]

---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Plot the error bars

```r
frames_mean %>%
  ggplot(aes(
    x = test_item, y = resp, colour = condition
  )) +
  geom_point() +
  geom_line() +
  geom_errorbar(aes(
    ymin = lower, ymax = upper
  )) +
  facet_wrap(~sample_size)
```
]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-61-1.png)
]]
]]

---
class: split-50 bg-main1

.column.bg-main1[.content.vtop.center[

.pull.left[.pad1[.font2[
Let's also make contours

```r
frames_test %>% 
  ggplot(mapping = aes(
    x = test_item, 
    y = response, 
    colour = condition)) +
  geom_point() + 
  theme_bw() +
  geom_density_2d() +
  facet_wrap(~condition) +
  ylim(0,9)
```
]]]
]]

.column.bg-main3[.content.vtop.center[
.pad1[.font2[
![](ggplot-slides_files/figure-html/unnamed-chunk-63-1.png)
]]
]]

---