Using split() function on a pandas dataframe

Question

I have the following dataframe:

I'm trying to get rid of the percentage signs. In order to do this I decided to apply a function to the Democrat and Republican column and try to split() by the percentage sign. The following code tries to do that:

gallup_2012[['Democrat/Lean Democratic', 'Republican/Lean 
Republican']].apply(lambda x: x.split('%')[0])

However, when I try to do this, I get the following error:

("'Series' object has no attribute 'split'", u'occurred at index Democrat/Lean > Democratic')

I'm not quite sure why this error occurs, as I can apply other functions to this series. It's just that the split() function doesn't work.

Any help would be appreciated!

ksai · Accepted Answer · 2017-07-25 02:28:43Z

15

df[[ ]] returns a dataframe, so if you use df.apply() then it would be applied on pd.Series. And Series doesn't have split() method, But if you use df[ ] and use df.apply() then you would be able to achieve what you want. The drawback is only that you can apply only on one column.

gallup_2012['Democrat/Lean Democratic'].apply(lambda x: x.split('%')[0])

answered Jul 25, 2017 at 2:28

ksai

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2 Comments

bugsyb Over a year ago

How come when I do an operation like apply(lambda x: x+'s') this still works on every individual element even if I'm applying it to a dataframe?

ksai Over a year ago

see the output of df.apply(lambda x : type(x) and df['column'].apply(lambda x : type(x))

Henrique Coura · Accepted Answer · 2017-07-25 02:23:37Z

2

You could use the str.replace method on the desired columns

df["column"] = df["column"].str.replace("%", "")

answered Jul 25, 2017 at 2:23

Henrique Coura

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2 Comments

bugsyb Over a year ago

Yeah I could, although I'm curious as to why the other method doesn't work

Hrvoje Over a year ago

This doesn't work in pandas 0.25 AttributeError: Can only use .str accessor with string values!

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