TypeError when using Python 3.9 with pandas apply method on DataFrame with custom function
This might be a silly question, but I'm working with a `TypeError` when trying to apply a custom function to a pandas DataFrame in Python 3.9. My DataFrame has a column of strings, and I want to convert each string to its length. Here’s a simplified version of my code: ```python import pandas as pd data = {'text_column': ['hello', 'world', 'python', 'stackover']} df = pd.DataFrame(data) def string_length(s): return len(s) # Attempting to apply the function to the DataFrame try: df['length'] = df['text_column'].apply(string_length) except TypeError as e: print(f'TypeError: {e}') ``` When I run this, I get the following behavior: ``` TypeError: string_lengths() missing 1 required positional argument: 's' ``` I've double-checked that `string_length` is defined correctly and that `text_column` contains strings. I've also tried passing a lambda function as an alternative: ```python # Trying with a lambda function try: df['length'] = df['text_column'].apply(lambda x: len(x)) except TypeError as e: print(f'TypeError: {e}') ``` This also produces the same behavior. I've used pandas version 1.1.5 with Python 3.9. I’m not sure why I'm getting this `TypeError`, as it seems like the function should be correctly applied to each element in the Series. Any guidance on what might be going wrong here would be greatly appreciated! Is there a better approach?