TypeError: 'Series' object is not callable using pandas apply() with custom function

Question

Tying to use Pandas dataframe Apply() function for updating all rows with a function. Result is a TypeError

----> 1 df_usnews['AvgMathSAT_IQR'].apply(interquartile(df_usnews))

/anaconda/lib/python3.5/site-packages/pandas/core/series.py in apply(self, func, convert_dtype, args, **kwds)
   2235             values = lib.map_infer(values, boxer)
   2236 
-> 2237         mapped = lib.map_infer(values, f, convert=convert_dtype)
   2238         if len(mapped) and isinstance(mapped[0], Series):
   2239             from pandas.core.frame import DataFrame

pandas/src/inference.pyx in pandas.lib.map_infer (pandas/lib.c:63043)()

TypeError: 'Series' object is not callable

def interquartile(df):
        return pd.to_numeric(df.ThirdQuartileMathSAT) - pd.to_numeric(df.FirstQuartileMathSAT)


q75_upper = np.percentile(df_usnews.AvgMathSAT, q=75, interpolation='higher', axis=0)
q25_lower = np.percentile(df_usnews.AvgMathSAT, q=25, interpolation='lower', axis=0)
interquartile = q75_upper - q25_lower
df_usnews['AvgMathSAT_IQR'] = 0
df_usnews['AvgMathSAT_IQR'].apply(interquartile(df_usnews))

The output of interquartile(df) is a Series object.You are trying to apply a Series as a function. Hence the error. — Vishnu Kunchur
– Vishnu Kunchur, Commented Oct 22, 2018 at 19:51
Can you share same input data, including desired output, so we can show you how apply works? — jpp
– jpp, Commented Oct 22, 2018 at 19:51
Sample data : -1 -1 138 26 38 144 -1 22 116 47 -1 2 -1 156 156 81 -1 Name: AvgMathSAT — Data Science Analytics Manager
– Data Science Analytics Manager, Commented Oct 22, 2018 at 20:32

cs95 · Accepted Answer · 2018-10-22 19:55:59Z

2

Fixing your code, since interquartile operates on the DataFrame, apply must as well. You'd need to do

df_usnews['AvgMathSAT_IQR'] = df_usnews.apply(interquartile)

Note that when passing the function to apply, it is passed without arguments (i.e., it is not called).

Thankfully, pd.to_numeric is vectorised, so you don't need to apply the function here.

df_usnews['AvgMathSAT_IQR'] = interquartile(df_usnews)

Or,

df_usnews['AvgMathSAT_IQR'] = df_usnews.pipe(interquartile)

Is going to be a lot faster.

edited Oct 22, 2018 at 19:55

answered Oct 22, 2018 at 19:52

cs95

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