X-Git-Url: https://code.communitydata.science/covid19.git/blobdiff_plain/09d171608f699eafe6528325938a892937a65302..98b07b8098611287eaa775b09622d1f3514303c8:/keywords/analysis/related_searches_example.R

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+### COVID-19 Digital Observatory
+### 2020-03-28
+### 
+### Minimal example analysis file using trending search data
+
+### Import and cleanup data
+
+DataURL <-
+    url("https://github.com/CommunityDataScienceCollective/COVID-19_Digital_Observatory/blob/master/transliterations/data/output/related_searches_top.csv")
+
+related.searches.top <- read.table(DataURL,
+                           sep=",", header=TRUE,
+                           stringsAsFactors=FALSE) 
+
+### Alternatively, uncomment and run if working locally with full git tree
+### Identify data source directory and file
+## DataDir <- ("../data/output/")
+## DataFile <- ("related_searches_top.csv")
+
+## related.searches.top <- read.table(paste(DataDir,DataFile, sep=""),
+##                                   sep=",", header=TRUE,
+##                                   stringsAsFactors=FALSE)
+
+### Aggregate top 5 search queries by term/day
+top5.per.term.date <- aggregate(query ~ term + date,
+                                data=related.searches.top,
+                                head, 5)
+
+## Might cleanup a bit for further analysis or visualization...
+top5.per.term.date$date <- as.Date(top5.per.term.date$date)
+
+### Export
+write.table(top5.per.term.date,
+            file="output/top5_queries_per_term_per_date.csv", sep=",",
+            row.names=FALSE)
+