pointing at updated data url, adding explicit NA handling to factor, cutting unnecess...
authoraaronshaw <aaron.d.shaw@gmail.com>
Wed, 1 Apr 2020 21:52:22 +0000 (16:52 -0500)
committeraaronshaw <aaron.d.shaw@gmail.com>
Wed, 1 Apr 2020 21:52:22 +0000 (16:52 -0500)
wikipedia_views/analysis/output/top10_views_by_project_date.csv
wikipedia_views/analysis/pageview_example.R

index 796af100ab76b8d29b5e733b537fd6c2830ac0df..ce7eb5ef135eba3ee5405ef3b1f4b401dc3ed277 100644 (file)
@@ -1,11 +1,11 @@
 "article","project","timestamp","views"
-"2019–20_coronavirus_pandemic","en.wikipedia","2020032600",1148284
-"2020_coronavirus_pandemic_in_India","en.wikipedia","2020032600",513901
-"Coronavirus","en.wikipedia","2020032600",397959
-"2020_coronavirus_pandemic_in_the_United_States","en.wikipedia","2020032600",337676
-"2019–20_coronavirus_pandemic_by_country_and_territory","en.wikipedia","2020032600",298603
-"2020_coronavirus_pandemic_in_Italy","en.wikipedia","2020032600",297687
-"Coronavirus_disease_2019","en.wikipedia","2020032600",292272
-"2020_coronavirus_pandemic_in_Spain","en.wikipedia","2020032600",114732
-"2020_coronavirus_pandemic_in_the_United_Kingdom","en.wikipedia","2020032600",111856
-"Anthony_Fauci","en.wikipedia","2020032600",103205
+"2019–20_coronavirus_pandemic","en.wikipedia","2020033100",831879
+"2020_coronavirus_pandemic_in_India","en.wikipedia","2020033100",323123
+"2019–20_coronavirus_pandemic_by_country_and_territory","en.wikipedia","2020033100",315572
+"2020_coronavirus_pandemic_in_the_United_States","en.wikipedia","2020033100",290535
+"Coronavirus_disease_2019","en.wikipedia","2020033100",211391
+"2020_coronavirus_pandemic_in_Italy","en.wikipedia","2020033100",209908
+"Coronavirus","en.wikipedia","2020033100",188921
+"USNS_Comfort_(T-AH-20)","en.wikipedia","2020033100",150422
+"USNS_Comfort_(T-AH-20)","en.wikipedia","2020033100",150422
+"WrestleMania_36","en.wikipedia","2020033100",137637
index 8a7aba35dfe6f5827a7a1debc0192730658e3214..fb5359aa64c856bec978b1a5bcfc9712de82c907 100644 (file)
@@ -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=",",

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