pandas 与空 DataFrame 合并
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Merging with empty DataFrame
提问by orange
I'm trying to merge a dataframe (df1) with another dataframe (df2) for which df2can potentially be empty. The merge condition is df1.index=df2.z(df1is never empty), but I'm getting the following error.
我试图合并一个数据框（df1）与另一数据框（df2）用于这df2有可能是空的。合并条件是df1.index=df2.z(df1永远不会为空)，但我收到以下错误。
Is there any way to get this working?
有没有办法让这个工作？
In [31]:
import pandas as pd
In [32]:
df1 = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [1, 2, 3]})
df2 = pd.DataFrame({'x':[], 'y':[], 'z':[]})
dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-34-4e9943198dae> in <module>()
----> 1 dfmb = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy)
37 right_index=right_index, sort=sort, suffixes=suffixes,
38 copy=copy)
---> 39 return op.get_result()
40 if __debug__:
41 merge.__doc__ = _merge_doc % '\nleft : DataFrame'
/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in get_result(self)
185
186 def get_result(self):
--> 187 join_index, left_indexer, right_indexer = self._get_join_info()
188
189 ldata, rdata = self.left._data, self.right._data
/usr/local/lib/python2.7/dist-packages/pandas/tools/merge.pyc in _get_join_info(self)
277 join_index = self.left.index.take(left_indexer)
278 elif self.left_index:
--> 279 join_index = self.right.index.take(right_indexer)
280 else:
281 join_index = Index(np.arange(len(left_indexer)))
/usr/local/lib/python2.7/dist-packages/pandas/core/index.pyc in take(self, indexer, axis)
981
982 indexer = com._ensure_platform_int(indexer)
--> 983 taken = np.array(self).take(indexer)
984
985 # by definition cannot propogate freq
IndexError: cannot do a non-empty take from an empty axes.
采纳答案by Andy Hayden
Another alternative, similar to Joran's:
另一种选择，类似于乔兰的：
try:
dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
except IndexError:
dfm = df1.reindex_axis(df1.columns.union(df2.columns), axis=1)
I'm not sure which is clearer but both the following work:
我不确定哪个更清楚，但以下两个都有效：
In [11]: df1.reindex_axis(df1.columns.union(df2.columns), axis=1)
Out[11]:
a b c x y z
0 1 4 1 NaN NaN NaN
1 2 5 2 NaN NaN NaN
2 3 6 3 NaN NaN NaN
In [12]: df1.loc[:, df1.columns.union(df2.columns)]
Out[12]:
a b c x y z
0 1 4 1 NaN NaN NaN
1 2 5 2 NaN NaN NaN
2 3 6 3 NaN NaN NaN
(I prefer the former.)
（我更喜欢前者。）
回答by Joran Beasley
try:
dfm = pd.merge(df1, df2, how='outer', left_index=True, right_on='z')
except IndexError:
dfm = df1 if not df1.empty else df2
might be sufficient for your needs
可能足以满足您的需求
