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phd day workshop.Rmd
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phd day workshop.Rmd
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---
title: "Beyond barcharts"
output: html_notebook
---
# Bar chart alternatives
Let's meet the iris dataset!
Read more about it in the R help page for iris
```{r}
head(iris)
```
## ggplot basics
Let's do ggplot basics now!
Make a jitterplot with `geom_jitter()` Set the `x aesthetic` to `Species` and the `y aesthetic` to `Sepal.Length`
```{r}
```
## Barchart in ggplot
Let's make the same plot, but as a barchart.
Do you already know `stat_summary()`?
It's ggplot's best kept secret.
Replace `geom_jitter()` with `stat_summary(geom = 'bar')` and make a barchart.
Second, add `stat_summary(geom = 'errorbar')`
```{r}
```
That's your barchart right there!
Is it a beauty, no not quite, but we can fine-tune that in a later stage.
## Density alternatives
Let's make a couple alternatives.
### try `geom_violin()`
```{r}
```
### try `geom_density`
Replace the `x` aesthetic for `col = Species` , and maybe swap x and y axes.
You can add the `linetype` aesthetic as well!
that way it works in greyscale print.
```{r}
```
-------====== Wait here please, we'll plenary get up to speed in a second ===========------
## point/count alternatives
### dotplot
Similar to a violin plot, but shows the actual data points.
Use `geom_dotplot(binaxis = 'y',stackdir = 'center')`
```{r}
```
### histogram
```{r}
```
### boxplot
```{r}
```
-------====== Wait here please, we'll plenary get up to speed in a second ===========------
# Combining shapes!
ggplot can layer shapes on top of one another.
We can use this to our advantage, and add more data in our figure.
### Boxplot with jitter
Make a boxplot like before, but add the datapoints with `geom_jitter`.
Make the datapoints transparent and grey if you know how.
```{r}
```
### dotplot with median
Was that too easy, then here is a hard one!
Next, make a dotplot, but add a red line that displays the median.
Use stat summary and the cheatsheet.
*hint: `stat_summary()` has a `fun=` argument for determining what function you want used to summarise the data.*
```{r}
```
# Extension packages
## GGdist
ggdist, deals with displaying distributions, perfect!
Have a look at their cheatsheet.
[ggdist cheatsheet](https://github.com/mjskay/ggdist/blob/master/figures-source/cheat_sheet-slabinterval.pdf){.uri}
Try a ggdist visualisation on the iris dataset.
```{r}
```
# A figure of your own?
Do you have a (barchart?) figure of your own at hand?
Maybe play with that!
I'll be around to help out.
```{r}
```
## Alternative:
Formatting your data into the right shape is as hard as working ggplot itself.
I'd like you to try to make a boxplot of the irisdataset.
On the x axis, should be the different lengths that were measured.
The fill colour should be the Species, and on the y axis the actual measured length.
Can you manage?
Now make your favourite alternative, maybe a dotplot with a crossbar?
Or some other shape you may have found in the ggdist package.
```{r}
```
## Challenge!
Feeling up to a challenge, try to re-create this:
```{r}
```