IntCastingNaNError：无法将非有限值（NA 或 inf）转换为整数

Question

在执行此特定代码行时，我收到错误。需要将具有字符串数据类型的特定列转换为数值

data['sex'] = data['sex'].map( {'male': 1, 'female': 0} ).astype("int64")

错误信息

IntCastingNaNError                        Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_8608/2590375292.py in <module>
      2 #Male=1, Female=0
      3 #Converting sex to numerical variable in data
----> 4 data['sex'] = data['sex'].map( {'male': 1, 'female': 0} ).astype("int64")
      5 
      6 #Converting resting_ecg to numerical variable in data

~\anaconda3\lib\site-packages\pandas\core\generic.py in astype(self, dtype, copy, errors)
   5813         else:
   5814             # else, only a single dtype is given
-> 5815             new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
   5816             return self._constructor(new_data).__finalize__(self, method="astype")
   5817 

~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in astype(self, dtype, copy, errors)
    416 
    417     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
--> 418         return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
    419 
    420     def convert(

~\anaconda3\lib\site-packages\pandas\core\internals\managers.py in apply(self, f, align_keys, ignore_failures, **kwargs)
    325                     applied = b.apply(f, **kwargs)
    326                 else:
--> 327                     applied = getattr(b, f)(**kwargs)
    328             except (TypeError, NotImplementedError):
    329                 if not ignore_failures:

~\anaconda3\lib\site-packages\pandas\core\internals\blocks.py in astype(self, dtype, copy, errors)
    589         values = self.values
    590 
--> 591         new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
    592 
    593         new_values = maybe_coerce_values(new_values)

~\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_array_safe(values, dtype, copy, errors)
   1307 
   1308     try:
-> 1309         new_values = astype_array(values, dtype, copy=copy)
   1310     except (ValueError, TypeError):
   1311         # e.g. astype_nansafe can fail on object-dtype of strings

~\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_array(values, dtype, copy)
   1255 
   1256     else:
-> 1257         values = astype_nansafe(values, dtype, copy=copy)
   1258 
   1259     # in pandas we don't store numpy str dtypes, so convert to object

~\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_nansafe(arr, dtype, copy, skipna)
   1166 
   1167     elif np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer):
-> 1168         return astype_float_to_int_nansafe(arr, dtype, copy)
   1169 
   1170     elif is_object_dtype(arr):

~\anaconda3\lib\site-packages\pandas\core\dtypes\cast.py in astype_float_to_int_nansafe(values, dtype, copy)
   1211     """
   1212     if not np.isfinite(values).all():
-> 1213         raise IntCastingNaNError(
   1214             "Cannot convert non-finite values (NA or inf) to integer"
   1215         )

IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer

我需要将其转换为分类值 有谁知道解决办法请帮帮我

Answer 1

用“####”或未知填充值，然后进行转换 有时，如果缺失的数据很多，我们无法在填充或删除之前进行转换