pointing at updated data url, adding explicit NA handling to factor, cutting unnecessary call to ggplot2, and updated corresponding output from new data file. May not work while kibo urls are getting resolved

wikipedia_views/analysis/pageview_example.R

@@ -4,13 +4,12 @@
 ### Minimal example analysis file using pageview data
 
 library(tidyverse)
-library(ggplot2)
 library(scales)
 
-### Import and cleanup data
+### Import and cleanup one datafile from the observatory
 
 DataURL <-
-    url("https://github.com/CommunityDataScienceCollective/COVID-19_Digital_Observatory/raw/master/wikipedia_views/data/dailyviews2020032600.tsv")
+    url("https://covid19.communitydata.science/datasets/wikipedia/digobs_covid19-wikipedia-enwiki_dailyviews-20200401.tsv")
 
 views <-
     read.table(DataURL, sep="\t", header=TRUE, stringsAsFactors=FALSE) 
@@ -30,12 +29,14 @@ views <-
 ### (see https://www.tidyverse.org for more info)
 
 views <- views[,c("article", "project", "timestamp", "views")]
-views$timestamp <- factor(views$timestamp)
+views$timestamp <- fct_explicit_na(views$timestamp)
+
 
 ### Sorts and groups at the same time
 views.by.proj.date <- arrange(group_by(views, project, timestamp),
                         desc(views))
 
+
 ### Export just the top 10 by pageviews
 write.table(head(views.by.proj.date, 10),
             file="output/top10_views_by_project_date.csv", sep=",",