CODEWITHSUNDEEP
pythonpandas
Hedrack
Hedrack

Reputation: 774

AttributeError: 'Series' object has no attribute 'upper'

I'm new to python and pandas but I have a problem I cannot wrap my head around.

I'm trying to add a new column to my DataFrame. To achieve that I use the assign() function.

Most of the examples on the internet are painfully trivial and I cannot find a solution for my problem.

What works:

my_dataset.assign(new_col=lambda x: my_custom_long_function(x['long_column']))

def my_custom_long_function(input)
  return input * 2

What doesn't work:

my_dataset.assign(new_col=lambda x: my_custom_string_function(x['string_column'])

def my_custom_string_function(input)
  return input.upper()

What confuses me is that in the debug I can see that even for my_custom_long_function the parameter is a Series, not a long.

I just want to use the lambda function and pass a value of the column to do my already written complicated functions. How do I do this?

Edit: The example here is just for demonstrative purpose, the real code is basically an existing complex function that does not care about panda's types and needs a str as a parameter.

Upvotes: 5

Views: 16043

Answers (1)

U13-Forward
U13-Forward

Reputation: 71580

Because the column doesn't have a upper method, in order to use it, you need to do str.upper:

my_dataset.assign(new_col=lambda x: my_custom_string_function(x['string_column'])

def my_custom_string_function(input)
  return input.str.upper()

That said, I would use:

my_dataset['new column'] = my_dataset['string_column'].str.upper()

For efficiency.

Edit:

my_dataset['new column'] = my_dataset['string_column'].apply(lambda x: my_custom_string_function(x))
def my_custom_string_function(input):
    return input.upper()

Upvotes: 6

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