one_to_hundred=pd.Series(np.arange(1,101,1))

This is the correct answer where you create a series using the numpy arange function which creates a range starting with 1 till 100 by incrementing 1.

import pandas as pd
from datetime import datetime
import numpy as np
date_rng = pd.date_range(start='1/1/2018', end='1/08/2018', freq='H')

This is generating a time stamp, hourly data

type(date_rng)

pandas.core.indexes.datetimes.DatetimeIndex

Create a dataframe and add random values for the corresponding date

df = pd.DataFrame(date_rng, columns=['date'])
df['data'] = np.random.randint(0,100,size=(len(date_rng)))

You have your self-generated time-series data. Hope this one helps.

>>> ','.join('{},{}'.format(i, i + 1) for i in range(1, 100, 4))
'1,2,5,6,9,10,13,14,17,18,21,22,25,26,29,30,33,34,37,38,41,42,45,46,49,50,53,54,57,58,61,62,65,66,69,70,73,74,77,78,81,82,85,86,89,90,93,94,97,98'

That was a quick and quite dirty solution.

Now, for a solution that is suitable for different kinds of progression problems:

def deltas():
    while True:
        yield 1
        yield 3
def numbers(start, deltas, max):
    i = start
    while i <= max:
        yield i
        i += next(deltas)
print(','.join(str(i) for i in numbers(1, deltas(), 100)))

And here are similar ideas implemented using itertools:

from itertools import cycle, takewhile, accumulate, chain

def numbers(start, deltas, max):
    deltas = cycle(deltas)
    numbers = accumulate(chain([start], deltas))
    return takewhile(lambda x: x <= max, numbers)

print(','.join(str(x) for x in numbers(1, [1, 3], 100)))