python - Use sklearn's FunctionTransformer with string data? -

i'm using sklearn's functiontransformer preprocess of data, date strings such "2015-01-01 11:09:15".

my customized function takes string input, found out functiontransformer cannot deal strings in source code didn't implement fit_transform. therefore, call got routed parent class as:

     57     def fit(self, x, y=none):      58         if self.validate: ---> 59             check_array(x, self.accept_sparse)      60         return self 

the check_array seems working numeric ndarrays. of course can in pandas domain, wonder if there's better way of dealing in sklearn - esp. given possibly use pipeline in future?

thanks!

seems if validate parameter looking for: http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.functiontransformer.html

here example, may make sense leave string on converting float mentioned in comment. let's want add time zone info date string:

import pandas pd  def add_tz(df):     df['date'] = df['date'].astype(str) + "z"  data = {  'date' : ["2015-01-01 11:00:00", "2015-01-01 11:15:00", "2015-01-01 11:30:00"],         'value' : [4., 3., 2.]}  df = pd.dataframe(data) 

this fail noted due check:

ft = functiontransformer(func=add_tz) ft.fit_transform(df) 

output:

valueerror: not convert string float: '2015-01-01 11:30:00' 

this works:

ft = functiontransformer(func=add_tz, validate=false) ft.fit_transform(df) 

output:

    date                    value 0   2015-01-01 11:00:00z    4.0 1   2015-01-01 11:15:00z    3.0 2   2015-01-01 11:30:00z    2.0