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 is a dataframe:
import pandas as pd
d = {
'Report Number':['8761234567', '8679876543','8994434555'],
'Name' :['George', 'Bill', 'Sally']
}
d = pd.DataFrame(d)
I would like to remove the first three characters from each field in the Report Number column of dataframe d.
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.