X-Git-Url: https://code.communitydata.science/covid19.git/blobdiff_plain/18118328ccb35d65a30d826129ef6f58c954fc9c..98b07b8098611287eaa775b09622d1f3514303c8:/transliterations/analysis/related_searches_example.R diff --git a/transliterations/analysis/related_searches_example.R b/transliterations/analysis/related_searches_example.R deleted file mode 100644 index 19ddfc7..0000000 --- a/transliterations/analysis/related_searches_example.R +++ /dev/null @@ -1,28 +0,0 @@ -### COVID-19 Digital Observatory -### 2020-03-28 -### -### Minimal example analysis file using trending search data - -### Identify data source directory and file -DataDir <- ("../data/output/") -DataFile <- ("related_searches_top.csv") - -### Import and cleanup data -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$date <- asDate(top5.per.term.date$date) - -### Export -write.table(top5.per.term.date, - file="output/top5_queries_per_term_per_date.csv", sep=",", - row.names=FALSE) -