当我想查看涉及缺失数据的数据时，我收到了 FloatingPointError。
import numpy as np
import pandas as pd
np.seterr(all='raise')
s = pd.Series([np.nan,np.nan,np.nan],index=[1,2,3]); print(s); print(s.head())
我正在使用最新版本的 pandas，通过
conda install -f pandas
在 pkill python 和 conda remove pandas 之后。
这是回溯:
Out[4]: ---------------------------------------------------------------------------
FloatingPointError Traceback (most recent call last)
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/IPython/core/formatters.pyc in __call__(self, obj)
695 type_pprinters=self.type_printers,
696 deferred_pprinters=self.deferred_printers)
--> 697 printer.pretty(obj)
698 printer.flush()
699 return stream.getvalue()
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/IPython/lib/pretty.pyc in pretty(self, obj)
381 if callable(meth):
382 return meth(obj, self, cycle)
--> 383 return _default_pprint(obj, self, cycle)
384 finally:
385 self.end_group()
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/IPython/lib/pretty.pyc in _default_pprint(obj, p, cycle)
501 if _safe_getattr(klass, '__repr__', None) not in _baseclass_reprs:
502 # A user-provided repr. Find newlines and replace them with p.break_()
--> 503 _repr_pprint(obj, p, cycle)
504 return
505 p.begin_group(1, '<')
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/IPython/lib/pretty.pyc in _repr_pprint(obj, p, cycle)
683 """A pprint that just redirects to the normal repr function."""
684 # Find newlines and replace them with p.break_()
--> 685 output = repr(obj)
686 for idx,output_line in enumerate(output.splitlines()):
687 if idx:
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/base.pyc in __repr__(self)
61 Yields Bytestring in Py2, Unicode String in py3.
62 """
---> 63 return str(self)
64
65
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/base.pyc in __str__(self)
41 if compat.PY3:
42 return self.__unicode__()
---> 43 return self.__bytes__()
44
45 def __bytes__(self):
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/base.pyc in __bytes__(self)
53
54 encoding = get_option("display.encoding")
---> 55 return self.__unicode__().encode(encoding, 'replace')
56
57 def __repr__(self):
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/series.pyc in __unicode__(self)
954
955 self.to_string(buf=buf, name=self.name, dtype=self.dtype,
--> 956 max_rows=max_rows)
957 result = buf.getvalue()
958
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/series.pyc in to_string(self, buf, na_rep, float_format, header, length, dtype, name, max_rows)
992 the_repr = self._get_repr(float_format=float_format, na_rep=na_rep,
993 header=header, length=length, dtype=dtype,
--> 994 name=name, max_rows=max_rows)
995
996 # catch contract violations
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/series.pyc in _get_repr(self, name, header, length, dtype, na_rep, float_format, max_rows)
1022 float_format=float_format,
1023 max_rows=max_rows)
-> 1024 result = formatter.to_string()
1025
1026 # TODO: following check prob. not neces.
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/format.pyc in to_string(self)
223
224 fmt_index, have_header = self._get_formatted_index()
--> 225 fmt_values = self._get_formatted_values()
226
227 maxlen = max(self.adj.len(x) for x in fmt_index) # max index len
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/format.pyc in _get_formatted_values(self)
213 return format_array(self.tr_series._values, None,
214 float_format=self.float_format,
--> 215 na_rep=self.na_rep)
216
217 def to_string(self):
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/format.pyc in format_array(values, formatter, float_format, na_rep, digits, space, justify)
1974 justify=justify)
1975
-> 1976 return fmt_obj.get_result()
1977
1978
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/format.pyc in get_result(self)
1990
1991 def get_result(self):
-> 1992 fmt_values = self._format_strings()
1993 return _make_fixed_width(fmt_values, self.justify)
1994
/home/xxx/.conda/envs/myenv2/lib/python2.7/site-packages/pandas/core/format.pyc in _format_strings(self)
2085
2086 # this is pretty arbitrary for now
-> 2087 has_large_values = (abs_vals > 1e8).any()
2088 has_small_values = ((abs_vals < 10 ** (-self.digits)) &
2089 (abs_vals > 0)).any()
FloatingPointError: invalid value encountered in greater
最佳答案
每当您导入 pandas 时，所有 numpy 错误都将被设置为忽略。这是目前未记录的行为。
这是在 pandas/compat/numpy_compat.py 中完成的
# TODO: HACK for NumPy 1.5.1 to suppress warnings
# is this necessary?
try:
np.seterr(all='ignore')
except Exception: # pragma: no cover
pass
结果是这样的
In [1]: import numpy as np
In [2]: np.geterr()
Out[2]: {'divide': 'warn', 'invalid': 'warn', 'over': 'warn', 'under': 'ignore'}
In [3]: import pandas as pd
In [4]: np.geterr()
Out[4]: {'divide': 'ignore', 'invalid': 'ignore', 'over': 'ignore', 'under': 'ignore'}
In [5]: s = pd.Series([np.nan,np.nan,np.nan],index=[1,2,3]); print(s); print(s.head())
1 NaN
2 NaN
3 NaN
dtype: float64
1 NaN
2 NaN
3 NaN
dtype: float64
In [6]: np.seterr(invalid='raise')
Out[6]: {'divide': 'ignore', 'invalid': 'ignore', 'over': 'ignore', 'under': 'ignore'}
In [7]: s = pd.Series([np.nan,np.nan,np.nan],index=[1,2,3]); print(s); print(s.head())
FloatingPointError: invalid value encountered in greater
“解决方案”因此不是 np.seterr(invalid'raise')，每当您使用 pandas 时(尤其是在处理缺失数据时)。
关于python - Pandas :带有 np.seterr(所有 ='raise')和缺失数据的 FloatingPointError，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/35657516/