How to remove numbers from string terms in a pandas dataframe

Question

I have a data frame similar to the one below:

Name    Volume  Value May21   23      21321 James   12      12311 Adi22   11      4435 Hello   34      32454 Girl90  56      654654 

I want the output to be in the format:

Name    Volume  Value May     23      21321 James   12      12311 Adi     11      4435 Hello   34      32454 Girl    56      654654 

Want to remove all the numbers from the Name column.

Closest I have come is doing it at a cell level with the following code:

result = ''.join([i for i in df['Name'][1] if not i.isdigit()]) 

Any idea how to do it in a better way at the series/dataframe level.

Answer 1

You can apply str.replace to the Name column in combination with regular expressions:

import pandas as pd  # Example DataFrame df = pd.DataFrame.from_dict({'Name'  : ['May21', 'James', 'Adi22', 'Hello', 'Girl90'],                              'Volume': [23, 12, 11, 34, 56],                              'Value' : [21321, 12311, 4435, 32454, 654654]})  df['Name'] = df['Name'].str.replace('\d+', '')  print(df) 

Output:

    Name   Value  Volume 0    May   21321      23 1  James   12311      12 2    Adi    4435      11 3  Hello   32454      34 4   Girl  654654      56 

In the regular expression \d stands for "any digit" and + stands for "one or more".

Thus, str.replace('\d+', '') means: "Replace all occurring digits in the strings with nothing".