How to fill in rows with repeating data in pandas?

Question

In R, when adding new data of unequal length to a data frame, the values repeat to fill the data frame:

df <- data.frame(first=c(1,2,3,4,5,6))
df$second &         


        

Answer 1

import pandas as pd
import numpy as np

def put(df, column, values):
    df[column] = 0
    np.put(df[column], np.arange(len(df)), values)

df = pd.DataFrame({'first':range(1, 8)})    
put(df, 'second', [1,2,3])

yields

   first  second
0      1       1
1      2       2
2      3       3
3      4       1
4      5       2
5      6       3
6      7       1

Not particularly beautiful, but one "feature" it possesses is that you do not have to worry if the length of the DataFrame is a multiple of the length of the repeated values. np.put repeats the values as necessary.

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My first answer was:

import itertools as IT
df['second'] = list(IT.islice(IT.cycle([1,2,3]), len(df)))

but it turns out this is significantly slower:

In [312]: df = pd.DataFrame({'first':range(10**6)})

In [313]: %timeit df['second'] = list(IT.islice(IT.cycle([1,2,3]), len(df)))
10 loops, best of 3: 143 ms per loop

In [316]: %timeit df['second'] = 0; np.put(df['second'], np.arange(N), [1,2,3])
10 loops, best of 3: 27.9 ms per loop