Adding a column to a data frame with a repeating sequence

Question

I am trying to add a column to a data frame and have it pre populated with a repeating sequence.

For example:

new_column
1
2
3
4
5
1
2
3
4
5
.
.
.

Is there a way to achieve this using pandas functions and not having to run a loop?

Welcome to StackOverflow. To make your question fit the format of this site, it is necessary, that you include also what you have researched so far, and where exactly you are stuck. See also: stackoverflow.com/help/how-to-ask. The easiest way is to include an MVCE showing how you populate your dataframe and where in the script you are missing bits. — NOhs
– NOhs, Commented Aug 7, 2019 at 20:31

rafaelc · Accepted Answer · 2019-08-07 20:26:09Z

3

Use np.tile

N = 2
np.tile([1,2,3,4,5], N)

where N is the number of repetitions

answered Aug 7, 2019 at 20:26

rafaelc

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Comments

piRSquared · Accepted Answer · 2019-08-07 20:35:34Z

2

`itertools`, `islice` and `cycle`

This keeps going through the pattern and doesn't matter if the length of the dataframe is a multiple of the length of the pattern.

from itertools import islice, cycle

pat = [1, 2, 3, 4, 5]
df.assign(new_column=[*islice(cycle(pat), len(df))])

   old_column  new_column
0           A           1
1           B           2
2           C           3
3           D           4
4           E           5
5           F           1
6           G           2
7           H           3
8           I           4
9           J           5
10          K           1

Setup

df = pd.DataFrame(dict(old_column=[*'ABCDEFGHIJK']))

edited Aug 7, 2019 at 20:35

answered Aug 7, 2019 at 20:26

piRSquared

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2 Comments

rxtechsbay Over a year ago

This is exactly what I need, but when I try to run this code, I am getting a syntax error - df = pd.DataFrame(dict(old_column=[*'ABCDEFGHIJK'])) ^ SyntaxError: invalid syntax

piRSquared Over a year ago

You're probably using an older version of Python that doesn't allow for my "slick" use of [*...] so use the list callable instead df.assign(new_column=list(islice(cycle(pat), len(df))))

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