I have a Python dataframe with about 1,500 rows and 15 columns. With one specific column I would like to remove the first 3 characters of each row. As a simple example here
Use vectorised str methods to slice each string entry
In [11]:
d['Report Number'] = d['Report Number'].str[3:]
d
Out[11]:
Name Report Number
0 George 1234567
1 Bill 9876543
2 Sally 4434555
It is worth noting Pandas "vectorised" str
methods are no more than Python-level loops.
Assuming clean data, you will often find a list comprehension more efficient:
# Python 3.6.0, Pandas 0.19.2
d = pd.concat([d]*10000, ignore_index=True)
%timeit d['Report Number'].str[3:] # 12.1 ms per loop
%timeit [i[3:] for i in d['Report Number']] # 5.78 ms per loop
Note these aren't equivalent, since the list comprehension does not deal with null data and other edge cases. For these situations, you may prefer the Pandas solution.