我在Jupyter NoteBook中使用标签编码器编码数据帧时收到错误消息

如何解决我在Jupyter NoteBook中使用标签编码器编码数据帧时收到错误消息

代码段显示以下错误消息

CODE
l1=LabelEncoder()
df_con_enc=df_con.apply(l1.fit_transform)

---

ERROR MESSAGE
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~\anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode(values,uniques,encode,check_unknown)
    112         try:
--> 113             res = _encode_python(values,encode)
    114         except TypeError:

~\anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode_python(values,encode)
     60     if uniques is None:
---> 61         uniques = sorted(set(values))
     62         uniques = np.array(uniques,dtype=values.dtype)

TypeError: '<' not supported between instances of 'str' and 'float'

During handling of the above exception,another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-236-2a15c97ba0b0> in <module>
----> 1 df_con_enc=df_con.apply(l1.fit_transform)

~\anaconda3\lib\site-packages\pandas\core\frame.py in apply(self,func,axis,raw,result_type,args,**kwds)
   6876             kwds=kwds,6877         )
-> 6878         return op.get_result()
   6879 
   6880     def applymap(self,func) -> "DataFrame":

~\anaconda3\lib\site-packages\pandas\core\apply.py in get_result(self)
    184             return self.apply_raw()
    185 
--> 186         return self.apply_standard()
    187 
    188     def apply_empty_result(self):

~\anaconda3\lib\site-packages\pandas\core\apply.py in apply_standard(self)
    311 
    312         # compute the result using the series generator
--> 313         results,res_index = self.apply_series_generator()
    314 
    315         # wrap results

~\anaconda3\lib\site-packages\pandas\core\apply.py in apply_series_generator(self)
    339         else:
    340             for i,v in enumerate(series_gen):
--> 341                 results[i] = self.f(v)
    342                 keys.append(v.name)
    343 

~\anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in fit_transform(self,y)
    254         """
    255         y = column_or_1d(y,warn=True)
--> 256         self.classes_,y = _encode(y,encode=True)
    257         return y
    258 

~\anaconda3\lib\site-packages\sklearn\preprocessing\_label.py in _encode(values,check_unknown)
    115             types = sorted(t.__qualname__
    116                            for t in set(type(v) for v in values))
--> 117             raise TypeError("Encoders require their input to be uniformly "
    118                             f"strings or numbers. Got {types}")
    119         return res

TypeError: Encoders require their input to be uniformly strings or numbers. Got ['float','str']