Extract date-time limits from trip database
bike_datelimits(bikedb, city)
| bikedb | A string containing the path to the SQLite3 database.
If no directory specified, it is presumed to be in |
|---|---|
| city | If given, date limits are calculated only for trips in that city. |
A vector of 2 elements giving the date-time of the first and last trips
data_dir <- tempdir () bike_write_test_data (data_dir = data_dir) # dl_bikedata (city = 'la', data_dir = data_dir) # or download some real data! # Remove one London file that triggers an API call which may fail tests: file.remove (file.path (tempdir(), "01aJourneyDataExtract10Jan16-23Jan16.csv"))#> [1] TRUE#>#>#>#> reading file 1/3: /tmp/Rtmp88OwDl/hubway_Trips_2012.csv #> reading file 2/3: /tmp/Rtmp88OwDl/201701-hubway-tripdata.csv #> reading file 3/3: /tmp/Rtmp88OwDl/201801_hubway_tripdata.csv#>#>#>#> reading file 1/1: /tmp/Rtmp88OwDl/Divvy_Trips_sample.csv#>#>#>#> reading file 1/1: /tmp/Rtmp88OwDl/2017Q1-capitalbikeshare-tripdata-temp.csv#>#>#>#> reading file 1/1: /tmp/Rtmp88OwDl/la_metro_gbfs_trips_Q1_2017.csv#>#>#>#> reading file 1/1: /tmp/Rtmp88OwDl/Nice_Ride_trip_history_2012_season.csv#>#>#>#> reading file 1/1: /tmp/Rtmp88OwDl/201612-citibike-tripdata.csv#>#>#> [1] 1598# create database indexes for quicker access: index_bikedata_db (bikedb = bikedb) bike_datelimits ('testdb') # overall limits for all cities#> first last #> "2012-04-02 13:07:00" "2018-01-02 07:02:04"bike_datelimits ('testdb', city = 'NYC')#> first last #> "2016-12-01 00:00:04" "2016-12-01 01:33:37"bike_datelimits ('testdb', city = 'los angeles')#> first last #> "2017-01-01 00:15:00" "2017-01-01 16:55:00"#> [1] 12bike_rm_db (bikedb)#> [1] TRUE# don't forget to remove real data! # file.remove (list.files ('.', pattern = '.zip'))