UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U26'), dtype('int64')) -> None

[SSMK-wq]

thanks a lot for this package. It is very useful for me,

I am trying to follow a tutorial in hackernoon to select features from a dataset

When I execute the below code, I get an error like as shown below

from featurewiz import featurewiz
features, train = featurewiz(ord_train_t,y_train, corr_limit=0.7, verbose=2)

UFuncTypeError: ufunc 'add' did not contain a loop with signature
matching types (dtype('<U26'), dtype('int64')) -> None

However, I verified the dtypes for all my train data (ord_train_t) and target (y_train)

They all are of int64 and float64 types (as shown below) Don't understand why there is still an error. Even after converting float64 to int64, I get the same error. I also tried ord_train_t.isna().sum(), there are no NA's

[![enter image description here][5]][5]

Find below the full error

---------------------------------------------------------------------------
UFuncTypeError                            Traceback (most recent call last)
C:\Users\abcde1\AppData\Local\Temp/ipykernel_1888/1114387036.py in <module>
      1 from featurewiz import featurewiz
      2 
----> 3 features, train = featurewiz(ord_train_t,y_train, corr_limit=0.7, verbose=2)

~\Anaconda3\lib\site-packages\featurewiz\featurewiz.py in featurewiz(dataname, target, corr_limit, verbose, sep, header, test_data, feature_engg, category_encoders, dask_xgboost_flag, nrows, **kwargs)
   1027     ##################    L O A D    T E S T   D A T A      ######################
   1028     dataname = remove_duplicate_cols_in_dataset(dataname)
-> 1029     dataname = remove_special_chars_in_names(dataname, target, verbose=1)
   1030     if dask_xgboost_flag:
   1031         train = remove_special_chars_in_names(train, target)

~\Anaconda3\lib\site-packages\featurewiz\featurewiz.py in remove_special_chars_in_names(df, target, verbose)
   3581     else:
   3582         sel_preds = [x for x in list(df) if x not in target]
-> 3583         df = df[sel_preds+target]
   3584     orig_preds = copy.deepcopy(sel_preds)
   3585     #####   column names must not have any special characters #####

~\Anaconda3\lib\site-packages\pandas\core\ops\common.py in new_method(self, other)
     67         other = item_from_zerodim(other)
     68 
---> 69         return method(self, other)
     70 
     71     return new_method

~\Anaconda3\lib\site-packages\pandas\core\arraylike.py in __radd__(self, other)
     94     @unpack_zerodim_and_defer("__radd__")
     95     def __radd__(self, other):
---> 96         return self._arith_method(other, roperator.radd)
     97 
     98     @unpack_zerodim_and_defer("__sub__")

~\Anaconda3\lib\site-packages\pandas\core\series.py in _arith_method(self, other, op)
   5524 
   5525         with np.errstate(all="ignore"):
-> 5526             result = ops.arithmetic_op(lvalues, rvalues, op)
   5527 
   5528         return self._construct_result(result, name=res_name)

~\Anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in arithmetic_op(left, right, op)
    222         _bool_arith_check(op, left, right)
    223 
--> 224         res_values = _na_arithmetic_op(left, right, op)
    225 
    226     return res_values

~\Anaconda3\lib\site-packages\pandas\core\ops\array_ops.py in _na_arithmetic_op(left, right, op, is_cmp)
    164 
    165     try:
--> 166         result = func(left, right)
    167     except TypeError:
    168         if is_object_dtype(left) or is_object_dtype(right) and not is_cmp:

~\Anaconda3\lib\site-packages\pandas\core\computation\expressions.py in evaluate(op, a, b, use_numexpr)
    237         if use_numexpr:
    238             # error: "None" not callable
--> 239             return _evaluate(op, op_str, a, b)  # type: ignore[misc]
    240     return _evaluate_standard(op, op_str, a, b)
    241 

~\Anaconda3\lib\site-packages\pandas\core\computation\expressions.py in _evaluate_standard(op, op_str, a, b)
     67     if _TEST_MODE:
     68         _store_test_result(False)
---> 69     return op(a, b)
     70 
     71 

~\Anaconda3\lib\site-packages\pandas\core\roperator.py in radd(left, right)
      7 
      8 def radd(left, right):
----> 9     return right + left
     10 
     11 

UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U26'), dtype('int64')) -> None

[AutoViML]

You have made an error in your input: your code should be modified as follows:

from featurewiz import featurewiz
features, trainm = featurewiz(train,target, corr_limit=0.7, verbose=2)

The entire train dataframe should be sent in as-is. Then you should send the target column.

Please read the documentation right,
Ram

[SSMK-wq]

@AutoViML - Yes, I did send the entire dataframe as is...and sent target column seperately as well...Should I change it to 'trainm' instead of 'train'? Is this what you meant?

[AutoViML]

Your mistake was sending the target as a dataframe and not as the name of the column in the code snippet below:

features, trainm = featurewiz(train,target, corr_limit=0.7, verbose=2)

Hope you can see the examples in the examples folder here and use that notebook to form your own pipeline.

https://github.com/AutoViML/featurewiz/tree/main/examples

AutoViML