fix linting

econml/sklearn_extensions/linear_model.py

@@ -1684,7 +1684,7 @@ def _check_input(self, X, y, sample_weight, freq_weight, sample_var):
         """Check dimensions and other assertions."""
 
         X, y, sample_weight, freq_weight, sample_var = check_input_arrays(
-            X, y, sample_weight, freq_weight, sample_var, dtype = 'numeric') 
+            X, y, sample_weight, freq_weight, sample_var, dtype='numeric')
         if X is None:
             X = np.empty((y.shape[0], 0))
         if self.fit_intercept:

econml/tests/test_statsmodels.py

@@ -333,7 +333,7 @@ def test_o_dtype(self):
         np.random.seed(123)
         n = 1000
         d = 3
-        
+
         X = np.random.normal(size=(n, d)).astype('O')
         y = np.random.normal(size=n).astype('O')
 

econml/utilities.py

@@ -532,7 +532,7 @@ def check_input_arrays(*args, validate_len=True, force_all_finite=True, dtype=No
         Whether to allow inf and nan in input arrays.
 
     dtype : 'numeric', type, list of type or None (default=None)
-        Argument passed to sklearn.utils.check_array. 
+        Argument passed to sklearn.utils.check_array.
         Specifies data type of result. If None, the dtype of the input is preserved.
         If "numeric", dtype is preserved unless array.dtype is object.
         If dtype is a list of types, conversion on the first type is only