/bikeshare_IOTND

bikeshare project as part of the first phase of IOT Nano degree

Primary LanguagePython

bikeshare_IOTND

bikeshare project as part of the first phase of IOT Nano degree Statistics Computed:

1 Popular times of travel (i.e., occurs most often in the start time)

  • most common month
  • most common day of week
  • most common hour of day

2 Popular stations and trip

  • most common start station
  • most common end station
  • most common trip from start to end (i.e., most frequent combination of start station and end station)

3 Trip duration

  • total travel time
  • average travel time

4 User info

  • counts of each user type
  • counts of each gender (only available for NYC and Chicago)
  • earliest, most recent, most common year of birth (only available for NYC and Chicago)

References:

http://pandas.pydata.org/pandas-docs/version/0.22/generated/pandas.Series.dt.hour.html https://docs.python.org/2/library/datetime.html#strftime-and-strptime-behavior https://stackoverflow.com/questions/22402548/default-values-on-empty-user-input-in-python?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa
https://stackoverflow.com/questions/29832455/merging-and-subtracting-dataframe-columns-in-pandas?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa