pandas :当DataFrame为空时,为什么DataFrame.apply(f,axis = 1)调用f? [英] Pandas: why does DataFrame.apply(f, axis=1) call f when the DataFrame is empty?
问题描述
为什么当DataFrame
为空时,熊猫的DataFrame.apply
方法调用正在应用的函数?
Why does Pandas' DataFrame.apply
method call the function being applied when the DataFrame
is empty?
例如:
>>> import pandas as pd
>>> df = pd.DataFrame({"foo": []})
>>> df
Empty DataFrame
Columns: [foo]
Index: []
>>> x = []
>>> df.apply(x.append, axis=1)
Series([], dtype: float64)
>>> x
[Series([], dtype: float64)] # <<< why was the apply callback called with an empty row?
推荐答案
深入研究Pandas源代码,似乎是罪魁祸首:
Digging into the Pandas source, it looks like this is the culprit:
if not all(self.shape):
# How to determine this better?
is_reduction = False
try:
is_reduction = not isinstance(f(_EMPTY_SERIES), Series)
except Exception:
pass
if is_reduction:
return Series(NA, index=self._get_agg_axis(axis))
else:
return self.copy()
Pandas似乎在不带参数的情况下调用该函数,以试图猜测结果是Series
还是DataFrame
.
It looks like Pandas is calling the function with no arguments in an attempt to guess whether the result should be a Series
or a DataFrame
.
我想有个补丁.
编辑:此问题已得到修复,现已记录在案,并允许使用reduce
选项来避免此问题:
Edit: this issue has been patched, and is now both documented and allows the reduce
option to be used to avoid it: http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.apply.html
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