How to Remove Unwanted Characters from String Columns in a DataFrame?

Eliminating Unwanted Characters from Strings in DataFrame Columns

When dealing with datasets containing string data, it is often necessary to extract meaningful information from within strings. However, unwanted characters or formatting can obscure the desired data. In this scenario, the goal is to remove these unwanted parts efficiently.

Suppose we have a DataFrame column with the following data:

time	result
09:00	52A
10:00	62B
11:00	44a
12:00	30b
13:00	-110a

Our objective is to trim the data to remove the ' ' or '-' prefix and the 'a' or 'b' suffix. The desired output is:

time	result
09:00	52
10:00	62
11:00	44
12:00	30
13:00	110

To achieve this, we employ the lambda function within the map method. The following code snippet accomplishes the task:

data['result'] = data['result'].map(lambda x: x.lstrip('+-').rstrip('aAbBcC'))

The lstrip function removes any leading ' ' or '-' characters, while the rstrip function removes any trailing 'a', 'A', 'b', 'B', or 'c' characters. The output is a DataFrame with the desired trimmed data.

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