Using the apply function to pandas dataframe with arguments

Question

I created a function to take a column of a string datatype and ensure the first item in the string is always capitalized. Here is my function:

def myfunc(df, col):
     transformed_df = df[col][0].capitalize() + df[col][1:]
     return transformed_df

Using my function in my column of interest in my pandas dataframe:

df["mycol"].apply(myfunc)

I don't know why I get this error: TypeError: myfunc() missing 1 required positional argument: 'col'

Even adding axis to indicate that it should treat it column wise. I believe I am already passing my arguments why do I still need to specify col again? Correct me if I am wrong?

Your input is highly appreciated

jezrael · Accepted Answer · 2020-05-19 06:30:44Z

1

If use Series.apply then each value of Series is processing separately, so need:

def myfunc(val):
     return val[0].capitalize() + val[1:]

If want use pandas strings functions:

df["mycol"].str[0].str.capitalize() + df["mycol"].str[1:]

If want pass to function:

def myfunc(col):
    return col.str[0].str.capitalize() + col.str[1:]

Then use Series.pipe for processing Series:

df["mycol"].pipe(myfunc)

Or:

myfunc(df["mycol"])

edited May 19, 2020 at 6:30

answered May 19, 2020 at 6:28

jezrael

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1 Comment

JA-pythonista Over a year ago

Excellent! Thanks for the insights. Silly me.

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