Is there a simple way to select a loop or cycle of data in pandas/Python?

Question

I would like to select a cycle of data in Python (in this case, pandas, but it's a flexible and recurring problem), such that the selected data circles back around to the start of the data for n of the beginning rows. I keep running into this problem, and while I have a variety of working solutions for it, I'm interested in whether there's some built-in method for this I don't know about?

Here's an example pandas DataFrame:

import pandas as pd
import numpy as np

df = pd.DataFrame([[0,1],[2,3],[5,6],[7,8]],columns = ['x','y'])

This DataFrame would, of course, look like this:

   x  y
0  0  1
1  2  3
2  5  6
3  7  8

A good-enough solution I've found is to create an index array:

n = 1     #how far through the start of the dataframe to select
select = np.concatenate((range(len(df)),range(n)))

The output of select would be:

array([0, 1, 2, 3, 0])

If I do df.x[select], I get what I'm looking for:

0    0
1    2
2    5
3    7
0    0
Name: x, dtype: int64

Is there some functionality in NumPy, pandas, or any other module of Python that would allow this kind of looping selection of data? Something like df.x[0:+1] that would work in a way analogous to df.x[0:-1] instead of how it currently works? Or a NumPy method that works the way I'm making np.arange() work by combining it with np.concatenate()? As I mentioned, I keep running into this problem, and for a language as convenient as Python has been, it sure seems like a feature that would or should exist. Am I missing or forgetting something?

Edit to clarify request:

A suggested method by avloss was to use np.tile, which is the right degree of simple and generalizable I'm looking for, only it's excessive for the applications I'm using. These are cases where you have to close the loop of cyclic data either for plotting, or for calculating (eg if you're matching slopes of the beginning and end of a closed curve using a finite difference method). In these cases you only need the first n data points in a series (where n is usually somewhere between 1 and 3) to be repeated for closing the calculation or plotting the cycle.

Answer 1

This is not exactly what you're asking for, but np.tile comes pretty close: https://numpy.org/doc/stable/reference/generated/numpy.tile.html

Or, if you want to do this through indices, you might use mod division

np.arange(5) % 4 == array([0, 1, 2, 3, 0])