Generates a Pandas compatible Series of Timestamps using the Pendulum module. Addresses the issue where Pendulum Timestamps are not correctly converted to Pandas documented here: https://github.com/sdispater/pendulum/issues/246

generate_pd_timestamp_series.py

import pendulum
import pandas as pd

def generate_pd_timestamp_series(start_year,
                                 start_month,
                                 start_day,
                                 end_year,
                                 end_month,
                                 end_day,
                                 time_zone,
                                 interval,
                                 units=1):
    
    """
    Takes starting and ending dates and generates a Pandas friendly 
    Series of interval datetimes. Nanoseconds are not supported, 
    timezones are required.
    
    Parameters
    ----------
    start_year (Integer): The starting year; 2018 or 1921, etc. 
    start_month (Integer): The starting month; 1-12. 
    start_day (Integer): The starting day of the month; 1-31.
    end_year (Integer): The ending year; 2018 or 1921, etc. 
    end_month (Integer): The ending month; 1-12.
    end_day (Integer): The ending day of the month; 1-31.
    time_zone (String): The timezone for starting, ending and 
        resulting Series; "America/Denver", etc. 
    interval (String): The interval type; years, months, weeks, 
        days, hours, minutes, seconds. 
    units (Integer): The count of intervals between timestamps; 5, etc. 
    
    Returns
    -------
    result (Series): A pandas Series of datetimes between the 
        starting and ending dates in the designated interval units.
    
    Example
    -------
    pd_series = generate_pd_timestamp_series(2018,1,1,2018,1,2,"America/Denver",'hours',units=8) 
    
    print(type(pd_series))
    >  pandas.core.series.Series
    
    print(pd_series)
    >  0    2018-01-01 00:00:00 -0700
    >  1    2018-01-01 08:00:00 -0700
    >  2    2018-01-01 16:00:00 -0700
    >  3    2018-01-02 00:00:00 -0700
    >  dtype: object
    """
    
    start = pendulum.datetime(start_year,
                              start_month,
                              start_day).set(tz=time_zone)
                              
    end = pendulum.datetime(end_year,
                            end_month,
                            end_day).set(tz=time_zone)
    
    period = pendulum.period(start, end)
    return pd.Series([dt.strftime("%Y-%m-%d %H:%M:%S %z") for dt in period.range(interval,units)])