Labeling time series data

class: left, top
background-image: url(https://images.unsplash.com/photo-1454944338482-a69bb95894af?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=1504&q=80)
background-size: 170%

# .right.large[Labeling time series in {ggplot2}]

#### Edited: Gina Reynolds Photo Credit: Lauren Mancke

---

Viz and Code Inspirations:

- [Jenny Bryan](https://twitter.com/JennyBryan/status/1244499728831672320)  
- [John Burn-Murdoch](https://gist.githubusercontent.com/johnburnmurdoch/34bd7470dca92e470fd5f12a488923ce/raw/c7a66c8a718299ecfdb9b7c922daca5d33eb8aa0/coronavirus_cases_trajectories.R)
- [Allison Horst](https://twitter.com/allison_horst/status/1248765119334498305)
- [Hiroaki Yutani](https://yutani.rbind.io/post/gghighlight-0-2-0/)
- [Malcolm Barrett](https://designing-ggplots.netlify.com/#1)
- [Taming Themes in ggplot2](https://evamaerey.github.io/little_flipbooks_library/taming_themes_in_ggplot/taming_ggplot_themes.html)

---
class: inverse, center, middle

# Legend, ordered legend, or direct label

---

```r
*dat
```
]]
.column[.content[

```
# A tibble: 9 x 5
 year fruit price fruit_ABCD fruit_sane
 <int> <chr> <dbl> <fct> <fct> 
1 2016 Oranges 4.25 Oranges Oranges 
2 2016 Lemons 4 Lemons Lemons 
3 2016 Grapes 3.25 Grapes Grapes 
4 2017 Oranges 4 Oranges Oranges 
5 2017 Lemons 4.75 Lemons Lemons 
6 2017 Grapes 3.75 Grapes Grapes 
7 2018 Oranges 5.55 Oranges Oranges 
8 2018 Lemons NA Lemons Lemons 
9 2018 Grapes 4.85 Grapes Grapes 
```
]]
---
class: split-40
count: false

```r
dat %>% 
* ggplot()
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_2_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
* aes(x = year, y = price)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_3_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
* geom_line(size = 1.5)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_4_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
* aes(colour = fruit)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_5_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
* theme_minimal(base_size = 25)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_6_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
* scale_x_continuous(breaks = 2016:2018)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_7_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
* labs(title = "Price of produce: Edible?")
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_8_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
* scale_x_continuous(breaks = 2016:2018,
* expand = c(0.1,0),
* limits = c(2016,2018.2))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_17_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
* scale_y_continuous(labels = scales::dollar_format(),
* expand = c(0,.15))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_18_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
* labs(x = NULL, y = NULL)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_19_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
* theme(panel.grid.minor.x = element_blank())
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_20_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
* theme(panel.grid.major.x = element_blank())
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_21_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
 theme(panel.grid.major.x = element_blank()) + 
* theme(plot.title.position = "plot")
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_22_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
 theme(panel.grid.major.x = element_blank()) + 
 theme(plot.title.position = "plot") + 
* theme(plot.background = element_rect(fill = "grey98"))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_23_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
 theme(panel.grid.major.x = element_blank()) + 
 theme(plot.title.position = "plot") + 
 theme(plot.background = element_rect(fill = "grey98")) + 
* theme(axis.line.x = element_line(color = "grey20"))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_24_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
 theme(panel.grid.major.x = element_blank()) + 
 theme(plot.title.position = "plot") + 
 theme(plot.background = element_rect(fill = "grey98")) + 
 theme(axis.line.x = element_line(color = "grey20")) + 
* theme(axis.ticks.x = element_line(color = "grey20"))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_25_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
 scale_x_continuous(breaks = 2016:2018) + 
 labs(title = "Price of produce: Edible?") + 
# overwrite with a more appropriate factor ordering
 aes(colour = fct_reorder2(fruit, year, price)) + 
# put the key near the data
 theme(legend.justification = c(1, 0.85)) + 
 labs(colour = NULL) + 
 labs(title = "Price of produce: Fancy") + 
# but you might directly label the series
 theme(legend.position = "none") + 
 aes(color = fruit) + 
 geom_text(data = . %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(label = fruit), 
 nudge_x = .1, 
 nudge_y = .12, 
 color = "black", 
 size = 7) + 
# give them a cute little end point
 geom_point(data = dat %>% 
 group_by(fruit) %>% 
 drop_na() %>% 
 filter(year == max(year)), 
 aes(fill = fruit), 
 shape = 21, 
 size = 6, 
 color = "white") + 
# but probably wider x axis
 scale_x_continuous(breaks = 2016:2018, 
 expand = c(0.1,0), 
 limits = c(2016,2018.2)) + 
 scale_y_continuous(labels = scales::dollar_format(), 
 expand = c(0,.15)) + 
 labs(x = NULL, y = NULL) + 
 theme(panel.grid.minor.x = element_blank()) + 
 theme(panel.grid.major.x = element_blank()) + 
 theme(plot.title.position = "plot") + 
 theme(plot.background = element_rect(fill = "grey98")) + 
 theme(axis.line.x = element_line(color = "grey20")) + 
 theme(axis.ticks.x = element_line(color = "grey20")) + 
* labs(title = "Price of produce: Extra Fancy")
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/plots_auto_26_output-1.png" width="576" />
]]

---
class: inverse, center, middle

# Faceting

---

```r
*library(gghighlight)
```
]]
.column[.content[

]]
---
class: split-40
count: false

```r
library(gghighlight)  
*dat
```
]]
.column[.content[

```r
library(gghighlight) 
dat %>% 
* ggplot()
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_3_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
* aes(x = year)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_4_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
* aes(y = price)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_5_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
* facet_wrap(~fruit)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_6_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
* geom_line(data = . %>%
* mutate(fruit_grey = fruit) %>%
* select(-fruit),
* aes(group = fruit_grey),
* color = "grey")
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_7_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
* geom_line(size = 1.5,
* color = "steelblue")
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_8_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
 geom_line(size = 1.5, 
 color = "steelblue") + 
 theme_minimal(base_size = 18) + 
 scale_x_continuous(breaks = 2016:2018) + 
 theme(legend.position = "none") + 
* theme(strip.text =
* element_text(color = "steelblue",
* size = 20,
* face = "bold"))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_12_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
 geom_line(size = 1.5, 
 color = "steelblue") + 
 theme_minimal(base_size = 18) + 
 scale_x_continuous(breaks = 2016:2018) + 
 theme(legend.position = "none") + 
 theme(strip.text = 
 element_text(color = "steelblue", 
 size = 20, 
 face = "bold")) + 
* theme(panel.spacing.x =
* unit(2, "lines"))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_13_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
 geom_line(size = 1.5, 
 color = "steelblue") + 
 theme_minimal(base_size = 18) + 
 scale_x_continuous(breaks = 2016:2018) + 
 theme(legend.position = "none") + 
 theme(strip.text = 
 element_text(color = "steelblue", 
 size = 20, 
 face = "bold")) + 
 theme(panel.spacing.x = 
 unit(2, "lines")) + 
# beyond alphabetical for faceting too
* facet_wrap(~fct_reorder2(fruit, year, price))
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_14_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
 geom_line(size = 1.5, 
 color = "steelblue") + 
 theme_minimal(base_size = 18) + 
 scale_x_continuous(breaks = 2016:2018) + 
 theme(legend.position = "none") + 
 theme(strip.text = 
 element_text(color = "steelblue", 
 size = 20, 
 face = "bold")) + 
 theme(panel.spacing.x = 
 unit(2, "lines")) + 
# beyond alphabetical for faceting too
 facet_wrap(~fct_reorder2(fruit, year, price)) + 
* labs(x = NULL, y = NULL)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_15_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year) + 
 aes(y = price) + 
 facet_wrap(~fruit) + 
 geom_line(data = . %>% 
 mutate(fruit_grey = fruit) %>% 
 select(-fruit), 
 aes(group = fruit_grey), 
 color = "grey") + 
 geom_line(size = 1.5, 
 color = "steelblue") + 
 theme_minimal(base_size = 18) + 
 scale_x_continuous(breaks = 2016:2018) + 
 theme(legend.position = "none") + 
 theme(strip.text = 
 element_text(color = "steelblue", 
 size = 20, 
 face = "bold")) + 
 theme(panel.spacing.x = 
 unit(2, "lines")) + 
# beyond alphabetical for faceting too
 facet_wrap(~fct_reorder2(fruit, year, price)) + 
 labs(x = NULL, y = NULL) + 
* scale_y_continuous(labels = scales::dollar_format())
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/faceting_auto_16_output-1.png" width="576" />
]]

---
class: inverse, center, middle

# gghighlight

---

```r
*library(gghighlight)
```
]]
.column[.content[

]]
---
class: split-40
count: false

```r
library(gghighlight)  
*dat
```
]]
.column[.content[

```r
library(gghighlight) 
dat %>% 
* ggplot()
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_3_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
* aes(x = year, y = price)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_4_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
* geom_line(size = 1.5)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_5_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
* aes(colour = fruit)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_6_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
* theme_minimal(base_size = 25)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_7_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight) 
dat %>% 
 ggplot() + 
 aes(x = year, y = price) + 
 geom_line(size = 1.5) + 
 aes(colour = fruit) + 
 theme_minimal(base_size = 25) + 
* scale_x_continuous(breaks = 2016:2018)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_8_output-1.png" width="576" />
]]
---
class: split-40
count: false

```r
library(gghighlight)  
dat %>%  
  ggplot() +  
  aes(x = year, y = price) +  
  geom_line(size = 1.5) +  
  aes(colour = fruit) +  
  theme_minimal(base_size = 25) +  
  scale_x_continuous(breaks = 2016:2018) ->  
*g 
```
]]
.column[.content[

]]
---
class: split-40
count: false

*g 
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_10_output-1.png" width="576" />
]]
---
class: split-40
count: false

g + 
* gghighlight(max(price, na.rm = T) > 5,
* keep_scales = TRUE)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_11_output-1.png" width="576" />
]]
---
class: split-40
count: false

g +  
  gghighlight(max(price, na.rm = T) > 5,  
              keep_scales = TRUE) ->  
*g2
```
]]
.column[.content[

]]
---
class: split-40
count: false

g +  
  gghighlight(max(price, na.rm = T) > 5,  
              keep_scales = TRUE) ->  
g2

*g 
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_13_output-1.png" width="576" />
]]
---
class: split-40
count: false

g +  
  gghighlight(max(price, na.rm = T) > 5,  
              keep_scales = TRUE) ->  
g2

g + 
* gghighlight(max(price, na.rm = T) > 3,
* keep_scales = TRUE)
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_14_output-1.png" width="576" />
]]
---
class: split-40
count: false

g +  
  gghighlight(max(price, na.rm = T) > 5,  
              keep_scales = TRUE) ->  
g2

g + 
 gghighlight(max(price, na.rm = T) > 3, 
 keep_scales = TRUE) 
```
]]
.column[.content[
<img src="labeling_time_series_files/figure-html/gghighlight_auto_15_output-1.png" width="576" />
]]

---
class: inverse, center, middle

# Interested in the toy data prep?
--

## Uses the newish pivot_longer()!

--
### This is basically [Jenny Bryan's set up](https://gist.github.com/jennybc/847c6b43c4e35cec2e5bb30a3f38af73)

---

```r
*library(tidyverse)
```
]]
.column[.content[

]]
---
class: split-40
count: false

```r
library(tidyverse)  
*library(patchwork)
```
]]
.column[.content[

]]
---
class: split-40
count: false

```r
library(tidyverse)  
library(patchwork)

*tibble(
* year = 2016:2018,
* Oranges = c(4.25, 4, 5.55),
* Lemons = c(4, 4.75, NA),
* Grapes = c(3.25, 3.75, 4.85)
*) 
```
]]
.column[.content[

```
# A tibble: 3 x 4
 year Oranges Lemons Grapes
 <int> <dbl> <dbl> <dbl>
1 2016 4.25 4 3.25
2 2017 4 4.75 3.75
3 2018 5.55 NA 4.85
```
]]
---
class: split-40
count: false

```r
library(tidyverse)  
library(patchwork)

tibble(  
  year = 2016:2018,  
  Oranges = c(4.25, 4, 5.55),  
  Lemons = c(4, 4.75, NA),  
  Grapes = c(3.25, 3.75, 4.85)  
)  ->  
*dat_wide
```
]]
.column[.content[

]]
---
class: split-40
count: false

```r
library(tidyverse)  
library(patchwork)

tibble(  
  year = 2016:2018,  
  Oranges = c(4.25, 4, 5.55),  
  Lemons = c(4, 4.75, NA),  
  Grapes = c(3.25, 3.75, 4.85)  
)  ->  
dat_wide

*dat_wide
```
]]
.column[.content[

```r
library(tidyverse)  
library(patchwork)

tibble(  
  year = 2016:2018,  
  Oranges = c(4.25, 4, 5.55),  
  Lemons = c(4, 4.75, NA),  
  Grapes = c(3.25, 3.75, 4.85)  
)  ->  
dat_wide

dat_wide %>%  
* pivot_longer(
*   cols = c(Oranges, Lemons, Grapes),
*   names_to = "fruit",
*   values_to = "price")
```
]]
.column[.content[

```
# A tibble: 9 x 3
 year fruit price
 <int> <chr> <dbl>
1 2016 Oranges 4.25
2 2016 Lemons 4 
3 2016 Grapes 3.25
4 2017 Oranges 4 
5 2017 Lemons 4.75
6 2017 Grapes 3.75
7 2018 Oranges 5.55
8 2018 Lemons NA 
9 2018 Grapes 4.85
```
]]
---
class: split-40
count: false

```r
library(tidyverse)  
library(patchwork)

tibble(  
  year = 2016:2018,  
  Oranges = c(4.25, 4, 5.55),  
  Lemons = c(4, 4.75, NA),  
  Grapes = c(3.25, 3.75, 4.85)  
)  ->  
dat_wide

dat_wide %>%  
  pivot_longer(  
    cols = c(Oranges, Lemons, Grapes),  
    names_to = "fruit",  
    values_to = "price") %>%  
* mutate(
*   fruit_ABCD = factor(fruit),
*   fruit_sane = fct_reorder2(fruit, year, price)
* )
```
]]
.column[.content[

```r
library(tidyverse)  
library(patchwork)

tibble(  
  year = 2016:2018,  
  Oranges = c(4.25, 4, 5.55),  
  Lemons = c(4, 4.75, NA),  
  Grapes = c(3.25, 3.75, 4.85)  
)  ->  
dat_wide

dat_wide %>%  
  pivot_longer(  
    cols = c(Oranges, Lemons, Grapes),  
    names_to = "fruit",  
    values_to = "price") %>%  
  mutate(  
    fruit_ABCD = factor(fruit),  
    fruit_sane = fct_reorder2(fruit, year, price)  
  ) ->  
*dat
```
]]
.column[.content[

]]

---