Filtering out characters from a string in a data frame [duplicate]

It seems like you are trying to change the data even though you only change the iteration of the data, meaning that the actual data frame is never changed. I think the only way to fix this is to keep track of where you are in the iteration and index the list at the point in which you are to change the data frame directly. You can see my solution below:

def clean_data(data, bad_values):
    for i in range(len(data["SalaryUSD"])):
        string = data["SalaryUSD"][i]
        for ele in string:
            if ele in bad_values:
                data["SalaryUSD"][i]=string.replace(ele, "")
    return data

Also, after going through the code you provided I found that the counter parameter never comes up in your code. I just wanted to make sure you put it back in if it is used in your full code.

The @Barmar approach can be extended so you can remove all the characters in your bad_value list using:

bad_value = ['\$',',', ' ', '\[']   # extend to include all 'bad' values
pattern = '|'.join(bad_value)
data['Salary'] = data['SalaryUSD'].str.replace(pattern, '', regex = True)

Note that characters that have a special meaning in regex have to be be 'escaped' by using backslash \. You can look these up. You should always using such an approach with Pandas DFs, not looping.