Python 数据类型转换错误：ValueError：无法将非有限值（NA 或 inf）转换为整数
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时间：2020-08-19 18:44:28 来源:igfitidea点击:
Data type conversion error: ValueError: Cannot convert non-finite values (NA or inf) to integer
提问by Aravind Yarram
I've the following dataframe
我有以下数据框
df1 = df[['tripduration','starttime','stoptime','start station name','end station name','bikeid','usertype','birth year','gender']]
print(df1.head(2))
which prints the following
打印以下内容
tripduration starttime stoptime start station name \
0 364 2017-09-01 00:02:01 2017-09-01 00:08:05 Exchange Place
1 357 2017-09-01 00:08:12 2017-09-01 00:14:09 Warren St
end station name bikeid usertype birth year gender
0 Marin Light Rail 29670 Subscriber 1989.0 1
1 Newport Pkwy 26163 Subscriber 1980.0 1
I am using the following code to convert "birth year" column type from float to int.
我正在使用以下代码将“出生年份”列类型从 float 转换为 int。
df1[['birth year']] = df1[['birth year']].astype(int)
print df1.head(2)
But I get the following error. How to fix this?
但我收到以下错误。如何解决这个问题？
ValueErrorTraceback (most recent call last)
<ipython-input-25-0fe766e4d4a7> in <module>()
----> 1 df1[['birth year']] = df1[['birth year']].astype(int)
2 print df1.head(2)
3 __zeppelin__._displayhook()
/usr/miniconda2/lib/python2.7/site-packages/pandas/util/_decorators.pyc in wrapper(*args, **kwargs)
116 else:
117 kwargs[new_arg_name] = new_arg_value
--> 118 return func(*args, **kwargs)
119 return wrapper
120 return _deprecate_kwarg
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/generic.pyc in astype(self, dtype, copy, errors, **kwargs)
4002 # else, only a single dtype is given
4003 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 4004 **kwargs)
4005 return self._constructor(new_data).__finalize__(self)
4006
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/internals.pyc in astype(self, dtype, **kwargs)
3460
3461 def astype(self, dtype, **kwargs):
-> 3462 return self.apply('astype', dtype=dtype, **kwargs)
3463
3464 def convert(self, **kwargs):
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/internals.pyc in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
3327
3328 kwargs['mgr'] = self
-> 3329 applied = getattr(b, f)(**kwargs)
3330 result_blocks = _extend_blocks(applied, result_blocks)
3331
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/internals.pyc in astype(self, dtype, copy, errors, values, **kwargs)
542 def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
543 return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 544 **kwargs)
545
546 def _astype(self, dtype, copy=False, errors='raise', values=None,
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/internals.pyc in _astype(self, dtype, copy, errors, values, klass, mgr, **kwargs)
623
624 # _astype_nansafe works fine with 1-d only
--> 625 values = astype_nansafe(values.ravel(), dtype, copy=True)
626 values = values.reshape(self.shape)
627
/usr/miniconda2/lib/python2.7/site-packages/pandas/core/dtypes/cast.pyc in astype_nansafe(arr, dtype, copy)
685
686 if not np.isfinite(arr).all():
--> 687 raise ValueError('Cannot convert non-finite values (NA or inf) to '
688 'integer')
689
ValueError: Cannot convert non-finite values (NA or inf) to integer
回答by Orenshi
If your DF is big, you're probably not seeing the missing numbers. But you can use the fillnafunction to help
如果您的 DF 很大，您可能看不到丢失的数字。但是您可以使用该fillna功能来帮助
>>> df = pd.DataFrame(data=data, columns=['id', 'birth_year'])
>>> df
id birth_year
0 1 1989.0
1 2 1990.0
2 3 NaN
>>> df.birth_year
0 1989.0
1 1990.0
2 NaN
Name: birth_year, dtype: float64
>>> df.birth_year.astype(int)
ERROR |2018.01.29T18:14:04|default:183: Unhandled Terminal Exception
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/util/_decorators.py", line 91, in wrapper
return func(*args, **kwargs)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/generic.py", line 3410, in astype
**kwargs)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/internals.py", line 3224, in astype
return self.apply('astype', dtype=dtype, **kwargs)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/internals.py", line 3091, in apply
applied = getattr(b, f)(**kwargs)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/internals.py", line 471, in astype
**kwargs)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/internals.py", line 521, in _astype
values = astype_nansafe(values.ravel(), dtype, copy=True)
File "/usr/local/devtools/uat/anaconda4321/lib/python3.6/site-
packages/pandas/core/dtypes/cast.py", line 620, in astype_nansafe
raise ValueError('Cannot convert non-finite values (NA or inf) to '
ValueError: Cannot convert non-finite values (NA or inf) to integer
>>> df = df.fillna(0)
>>> df.birth_year.astype(int)
0 1989
1 1990
2 0
Name: birth_year, dtype: int64
