Plotting a categorical x and numeric y

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**Plotting a numerical y and a categorical x is hard**

This slideshow  works you through challenges and how to overcome them! These solutions include:

- Using jitter to avoid overplotting.  
- Using color to differentiate values.  
- Suppressing a redundant legend.  
- Showing means on a plot.

---

**Step 1: Basic ggplot setup**   
Setting up aesthetic mapping <br> <br>

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid))
```
]

---

**Step 1: Basic ggplot setup**  
Adding points <br> <br>

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid)) +
  geom_point()
```
]

---

**Step 1: Basic ggplot setup**  
OH NO those points are too small.  
Let's try bigger, somewhat transparent points.

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid)) +
  geom_point(size = 6, 
             alpha = .3)
```
]

---

# Try jitterplots

---

**Step 2: Try jitterplots**  
It's still tough to differentiate overlapping points. 
Let's switch to jitterplots to spread out our x.

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid)) +
  geom_jitter(size = 6,  
             alpha = .3, 
             height = 0)
# I set height equal to zero
# So the plot doesn't lie.
```
]

---

**Step 2: Try jitterplots**  
That helps - but now categories blend :(  
Lets redundantly map visited on to color.

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid,
             color = visited)) +
  geom_jitter(size = 6,  
             alpha = .3, 
             height = 0)
```
]

.right-column[
<img src="cat_cont_flipbook_files/figure-html/unnamed-chunk-11-1.png" width="576" />
]

---

**Step 2: Try jitterplots**  
Now the unnecessary legend takes up too much space.  
Let's remove it!

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid,
             color = visited)) +
  geom_jitter(size = 6,  
             alpha = .3, 
             height = 0)+
  theme(legend.position = "none")
```
]

.right-column[
<img src="cat_cont_flipbook_files/figure-html/unnamed-chunk-13-1.png" width="576" />
]

---

# Add summaries

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**Step 3: Add summaries**  
Now let's add each group's mean <br><br>

.right-column[
<img src="cat_cont_flipbook_files/figure-html/unnamed-chunk-15-1.png" width="576" />
]

---

**Step 3: Add summaries**  
Those points are tiny.   
Let's make them big and black

``` r
gc_rils|>
  ggplot(aes(x = visited,
             y = prop_hybrid,
             color = visited)) +
  geom_jitter(size = 6,  
             alpha = .3, 
             height = 0)+
  theme(legend.position = "none")+
  stat_summary(fun = "mean", 
               color = "black", 
               size = 4)
```
]

.right-column[
<img src="cat_cont_flipbook_files/figure-html/unnamed-chunk-17-1.png" width="576" />
]

---

**Step 3: Add summaries**  
Those points are tiny.   
Let's make them big and black

.right-column[
<img src="cat_cont_flipbook_files/figure-html/unnamed-chunk-19-1.png" width="576" />
]

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# *'Fin'*