Fixes #374. Thanks to @sstevens2

Author: albhasan

episodes/07-vector-shapefile-attributes-in-r.Rmd

@@ -32,10 +32,11 @@ library(sf)
 
 ```{r load-data, echo=FALSE, results="hide"}
 # learners will have this data loaded from previous episodes
-point_HARV <- st_read("data/NEON-DS-Site-Layout-Files/HARV/HARVtower_UTM18N.shp")
+point_HARV <-
+    st_read("data/NEON-DS-Site-Layout-Files/HARV/HARVtower_UTM18N.shp")
 lines_HARV <- st_read("data/NEON-DS-Site-Layout-Files/HARV/HARV_roads.shp")
-aoi_boundary_HARV <- st_read(
-  "data/NEON-DS-Site-Layout-Files/HARV/HarClip_UTMZ18.shp")
+aoi_boundary_HARV <-
+    st_read("data/NEON-DS-Site-Layout-Files/HARV/HarClip_UTMZ18.shp")
 ```
 
 ::::::::::::::::::::::::::::::::::::::::::  prereq
@@ -490,33 +491,29 @@ other lines can be black.
 
 ## Answers
 
-First we need to make sure that the `BicyclesHo` attribute is a factor and
-check how many levels it has.
+First we explore the `BicyclesHo` attribute to learn the values that correspond
+to the roads we need.
 
 ```{r}
-lines_HARV$BicyclesHo <- as.factor(lines_HARV$BicyclesHo)
-class(lines_HARV$BicyclesHo)
-levels(lines_HARV$BicyclesHo)
+lines_HARV %>%
+  pull(BicyclesHo) %>%
+  unique()
 ```
 
-Next, we will create a new object `lines_removeNA` that removes missing values.
+Now, we can create a data frame with only those roads where bicycles and horses 
+are allowed.
 
 ```{r}
-lines_removeNA <- lines_HARV[!is.na(lines_HARV$BicyclesHo),]
+lines_showHarv <-
+  lines_HARV %>%
+  filter(BicyclesHo == "Bicycles and Horses Allowed")
+
 ```
 
-In our plot, we will set colors so that only the allowed roads are magenta, and
-we will set line width so that the first factor level is thicker than the
-others.
+Finally, we plot the needed roads after setting them to magenta and a thicker 
+line width.
 
 ```{r harv-paths-bike-horses, fig.cap="Roads and trails in the area highlighting paths where horses and bikes are allowed."}
-# First, create a data frame with only those roads where bicycles and horses
-# are allowed
-lines_showHarv <-
-  lines_removeNA %>%
-  filter(BicyclesHo == "Bicycles and Horses Allowed")
-
-# Next, visualise using ggplot
 ggplot() +
   geom_sf(data = lines_HARV) +
   geom_sf(data = lines_showHarv, aes(color = BicyclesHo), size = 2) +