melb_walk_fast() to be compatible with the data
API change.melb_walk_fast() to be compatible with the data
API change.Fixed a typo in melb_weather().
Added a new set of functions to scrape Melbourne microclimate data. (@sa-lee)
melb_walk().melb_walk_directional().melb_walk_directional() to access minute
by minute directional pedestrian counts for the last hour from
pedestrian sensor devices located across the city.pull_sensor() due to the Socrata API URL
change.lookup_sensor(), walk_melb(),
run_melb() and shine_melb() in favour of
suffixed function names.melb_walk_fast() (previously
run_melb()) due to Socrata API changes.walk_melb(), run_melb() and
shine_melb() in favour of suffixed function names.tweak in
walk_melb(), as the sensor names from the data source match
with run_melb().match column in the data frame called from
lookup_sensor().tbl_ts) instead of data.frame.run_melb(na.rm = FALSE).walk_melb(tweak = TRUE).lookup_sensor().run_melb(),
pull_sensor(), and lookup_sensor() using
Socrata.shine_melb() to use
walk_melb(tweak = TRUE).run_melb() pulls Melbourne pedestrian data using
Socrata, which is faster than walk_melb().pull_sensor() pulls Melbourne pedestrian sensor
locations using Socrata.lookup_sensor() provides a dictionary for sensor names
used in walk_melb() and run_melb().na.rm = FALSE and
tweak = FALSE to the function walk_melb(). If
na.rm = TRUE, it removes NAs from the data. If
tweak = TRUE, it ensures the consistency of sensor names to
run_melb().shine_melb() to launch a shiny app.
It provides two basic plots to take a glimpse at the data: one is an
overlaying time series plot and the other showing a dot plot of missing
values.NEWS.md file to track changes to the
package.walk_melb() to scrape Melbourne
pedestrian data.