Question

我有一个带有一些nan的字符串系列，我想要替换一些字符，然后将其转换为int（float是可以的）但是nan仍然是nan。喜欢

In[1]:df = pd.DataFrame(["type 12", None, "type13"], columns=['A'])
Out[1]: 
  A
0 12
1 NaN
2 13

有没有好办法呢？

Answer 1

不，不幸的是。你将不得不接受floats。

>>> s = pd.Series(['1', '2', '3', '4', '5'], index=list('abcde'))
>>> s
a    1
b    2
c    3
d    4
e    5
dtype: object
>>> s = s.reindex(['a','b','c','f','u'])
>>> s
a      1
b      2
c      3
f    NaN
u    NaN
dtype: object
>>> s.astype(int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/generic.py", line 2947, in astype
    raise_on_error=raise_on_error, **kwargs)
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/internals.py", line 2873, in astype
    return self.apply('astype', dtype=dtype, **kwargs)
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/internals.py", line 2832, in apply
    applied = getattr(b, f)(**kwargs)
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/internals.py", line 422, in astype
    values=values, **kwargs)
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/internals.py", line 465, in _astype
    values = com._astype_nansafe(values.ravel(), dtype, copy=True)
  File "/home/juan/anaconda3/lib/python3.5/site-packages/pandas/core/common.py", line 2628, in _astype_nansafe
    return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
  File "pandas/lib.pyx", line 937, in pandas.lib.astype_intsafe (pandas/lib.c:16620)
  File "pandas/src/util.pxd", line 60, in util.set_value_at (pandas/lib.c:67979)
ValueError: cannot convert float NaN to integer

来自熊猫Caveats and Gotchas：

特殊值NaN（非-A-Number）在任何地方都用作NA   值，并且有API函数isnull和notnull可以   在dtypes中使用来检测NA值。

然而，它最后还有几个权衡取舍   肯定没有被忽视......在没有高性能NA的情况下   支持从头开始构建NumPy，主要   伤亡是指在整数数组中表示NA的能力。

这样做：

>>> s.astype(float)
a    1.0
b    2.0
c    3.0
f    NaN
u    NaN
dtype: float64

如何在不影响nan的情况下处理大熊猫数据？

1 个答案: