Use Values in column as String Slicer of another column pandas-CodePudding

I'm trying to use a cell value as the slice for a string in a new column. For example, if I create this table.

data = pd.DataFrame(data = {'Name':['This is a title'], 'Number':[-5]})

               Name Number
0   This is a title     -5

And create a new column like so:

data['Test'] = data.Name.str[:data.Number.item()]

It'll create the new column, as expected:

               Name Number       Test
0   This is a title     -5  This is a

The issue occurs when I have more than row, so if I create the following table:

 data = pd.DataFrame(data = {'Name':['This is a title', 'This is another title'], 'Number':[-5, -13]})

                     Name   Number
0   This is a title             -5
1   This is another title      -13

The creation of the 'Test' column yields:

can only convert an array of size 1 to a Python scalar

I understand why this is happening since the column now has more than one value, what I want to know is how can I do this with a dataframe that has more than one row? I've tried .items(), .values(), etc. and the new column just becomes NaN.

Any thoughts?

Thanks!

CodePudding user response：

You can use apply with axis=1 and move on dataframe row by row.

import pandas as pd
data = pd.DataFrame(data = {'Name':['This is a title', 'This is another title'], 'Number':[-5, -13]})

data['Test'] = data.apply(lambda row: row['Name'][:row['Number']], axis=1)
print(data)

Output:

                    Name  Number        Test
0        This is a title      -5  This is a 
1  This is another title     -13    This is

CodePudding user response：

Unfortunately, here, you need to loop. A list comprehension will be the most efficient:

data['Test'] = [s[:i] for s,i in zip(data['Name'], data['Number'])]

output:

                    Name  Number        Test
0        This is a title      -5  This is a 
1  This is another title     -13    This is