Align timeline examples (#239)

vignettes/articles/r2dii-plot-X.Rmd

@@ -55,6 +55,18 @@ sda %>%
   plot_timelineX(extrapolate = TRUE) + labs(title = "Timeline plot")
 ```
 
+You can further customize your plot by adding a custom manual scale using 
+`ggplot` function `scale_colour_manual()` with custom legend labels. 
+
+```{r}
+sda %>% 
+  filter(sector == "cement") %>% 
+  plot_timelineX(extrapolate = TRUE) +
+  scale_color_manual(
+    values = c("#4a5e54", "#a63d57", "#78c4d6", "#f2e06e"),
+    labels = c("Proj.", "Corp. Economy", "Target (demo)", "Adj. Scenario (demo)"))
+```
+
 ### Techmix
 
 Use `plot_techmixX()` with `market_share`-like data. Again, learn which rows to

vignettes/articles/r2dii-plot-Y.Rmd

@@ -38,15 +38,32 @@ cement <- prep_timelineY(sda, sector_filter = "cement")
 cement <- prep_timelineY(filter(sda, sector == "cement"))
 
 cement
+
+# Default recoding
+plot_timelineY(cement)
+```
+
+You can further polish your plot. Your options are limitless but these are
+some typical things you may do:
+
+* Pick a narrower time range (by filtering your data using `dplyr`).
+* Extrapolate the timeline.
+* Add a title. 
+
+```{r}
+cement <- prep_timelineY(
+  filter(sda, sector == "cement", year >= 2020), 
+  extrapolate = TRUE)
+
+plot_timelineY(cement) + 
+  labs(title = "Timeline plot")
 ```
 
 * `plot_timelineY()` defaults to recoding `line_name` to title case, and allows
 custom recoding and colour setting via a data frame passed to the argument 
 `specs`.
 
 ```{r}
-# Default recoding
-plot_timelineY(cement)
 
 # Custom recoding
 custom <- tribble(