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I have found that 'right' joins on index values raise TypeEerror: Argument 'left' has incorrect type (expected numpy.ndarray, got Int64Index).
Both index types are the same Int64Index index. This works in pandas 0.13.1.
Pandas: 0.17.0 Numpy: 1.9.2
import pandas as pd import numpy as np df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'], 'B' : ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'], 'C' : np.random.randn(8), 'D' : np.random.randn(8)}) s = pd.Series(np.repeat(np.arange(8),2), index=np.repeat(np.arange(8),2), name='TEST') In []: s.head() Out[]: 0 0 0 0 1 1 1 1 2 2 dtype: int32 # The following all work as expected df.join(s, how='inner') df.join(s, how='outer') df.join(s, how='left') # Right Joins Type Error df.join(s, how='right') --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-80-26e8bf54fd8f> in <module>() ----> 1 df.join(s, how='right') D:\Python27\lib\site-packages\pandas\core\frame.pyc in join(self, other, on, how, lsuffix, rsuffix, sort) 4218 # For SparseDataFrame's benefit 4219 return self._join_compat(other, on=on, how=how, lsuffix=lsuffix, -> 4220 rsuffix=rsuffix, sort=sort) 4221 4222 def _join_compat(self, other, on=None, how='left', lsuffix='', rsuffix='', D:\Python27\lib\site-packages\pandas\core\frame.pyc in _join_compat(self, other, on, how, lsuffix, rsuffix, sort) 4232 return merge(self, other, left_on=on, how=how, 4233 left_index=on is None, right_index=True, -> 4234 suffixes=(lsuffix, rsuffix), sort=sort) 4235 else: 4236 if on is not None: D:\Python27\lib\site-packages\pandas\tools\merge.pyc in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator) 33 right_index=right_index, sort=sort, suffixes=suffixes, 34 copy=copy, indicator=indicator) ---> 35 return op.get_result() 36 if __debug__: 37 merge.__doc__ = _merge_doc % '\nleft : DataFrame' D:\Python27\lib\site-packages\pandas\tools\merge.pyc in get_result(self) 194 self.left, self.right = self._indicator_pre_merge(self.left, self.right) 195 --> 196 join_index, left_indexer, right_indexer = self._get_join_info() 197 198 ldata, rdata = self.left._data, self.right._data D:\Python27\lib\site-packages\pandas\tools\merge.pyc in _get_join_info(self) 309 if self.left_index and self.right_index: 310 join_index, left_indexer, right_indexer = \ --> 311 left_ax.join(right_ax, how=self.how, return_indexers=True) 312 elif self.right_index and self.how == 'left': 313 join_index, left_indexer, right_indexer = \ D:\Python27\lib\site-packages\pandas\core\index.pyc in join(self, other, how, level, return_indexers) 2212 if self.is_monotonic and other.is_monotonic: 2213 return self._join_monotonic(other, how=how, -> 2214 return_indexers=return_indexers) 2215 else: 2216 return self._join_non_unique(other, how=how, D:\Python27\lib\site-packages\pandas\core\index.pyc in _join_monotonic(self, other, how, return_indexers) 2463 join_index, lidx, ridx = self._left_indexer(sv, ov) 2464 elif how == 'right': -> 2465 join_index, ridx, lidx = self._left_indexer(other, self) 2466 elif how == 'inner': 2467 join_index, lidx, ridx = self._inner_indexer(sv, ov) TypeError: Argument 'left' has incorrect type (expected numpy.ndarray, got Int64Index)
The text was updated successfully, but these errors were encountered:
Seems this was already broken in 0.15.2
Sorry, something went wrong.
BUG: df.join(df2, how='right') TypeError: Argument 'left' has incorre…
d78266e
…ct type (issue #11519)
closed by #11545
No branches or pull requests
I have found that 'right' joins on index values raise TypeEerror: Argument 'left' has incorrect type (expected numpy.ndarray, got Int64Index).
Both index types are the same Int64Index index. This works in pandas 0.13.1.
Pandas: 0.17.0
Numpy: 1.9.2
The text was updated successfully, but these errors were encountered: