Right now I have a DF like this
Word Word2 Word3
Hello NaN NaN
My My Name NaN
Yellow Yellow Bee Yel
import numpy as np
import pandas as pd
import functools
def drop_and_roll(col, na_position='last', fillvalue=np.nan):
result = np.full(len(col), fillvalue, dtype=col.dtype)
mask = col.notnull()
N = mask.sum()
if na_position == 'last':
result[:N] = col.loc[mask]
elif na_position == 'first':
result[-N:] = col.loc[mask]
else:
raise ValueError('na_position {!r} unrecognized'.format(na_position))
return result
df = pd.read_table('data', sep='\s{2,}')
print(df.apply(functools.partial(drop_and_roll, fillvalue='')))
yields
Word Word2 Word3
0 Hello My Name Yellow Bee Hive
1 My Yellow Bee
2 Yellow Golden Gates
3 Golden
4 Yellow