Extract daily trip counts for all stations

bike_daily_trips(bikedb, city, station, member, birth_year, gender,
  standardise = FALSE)

Arguments

bikedb

A string containing the path to the SQLite3 database. If no directory specified, it is presumed to be in tempdir().

city

City for which trips are to be counted - mandatory if database contains data for more than one city

station

Optional argument specifying bike station for which trips are to be counted

member

If given, extract only trips by registered members (member = 1 or TRUE) or not (member = 0 or FALSE).

birth_year

If given, extract only trips by registered members whose declared birth years equal or lie within the specified value or values.

gender

If given, extract only records for trips by registered users declaring the specified genders (f/m/. or 2/1/0).

standardise

If TRUE, daily trip counts are standardised to the relative numbers of bike stations in operation for each day, so daily trip counts are increased during (generally early) periods with relatively fewer stations, and decreased during (generally later) periods with more stations.

Value

A data.frame containing daily dates and total numbers of trips

Examples

# NOT RUN {
bike_write_test_data () # by default in tempdir ()
# dl_bikedata (city = 'la', data_dir = data_dir) # or download some real data!
store_bikedata (data_dir = tempdir (), bikedb = 'testdb')
# create database indexes for quicker access:
index_bikedata_db (bikedb = 'testdb')

bike_daily_trips (bikedb = 'testdb', city = 'ny')
bike_daily_trips (bikedb = 'testdb', city = 'ny', member = TRUE)
bike_daily_trips (bikedb = 'testdb', city = 'ny', gender = 'f')
bike_daily_trips (bikedb = 'testdb', city = 'ny', station = '173',
                  gender = 1)

bike_rm_test_data ()
bike_rm_db ('testdb')
# don't forget to remove real data!
# file.remove (list.files ('.', pattern = '.zip'))
# }