###
### 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=""),
+
+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$date <- asDate(top5.per.term.date$date)
+top5.per.term.date$date <- as.Date(top5.per.term.date$date)
### Export
write.table(top5.per.term.date,