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Return self._combine_series(other, na_op, fill_value, axis, level)įile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/frame.py", line 3500, in _combine_seriesįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/frame.py", line 3528, in _combine_match_columnsįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/frame.py", line 2730, in alignįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/generic.py", line 4152, in alignįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/generic.py", line 4234, in _align_seriesįdata = fdata.reindex_indexer(join_index, lidx, axis=0)įile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/internals.py", line 3528, in reindex_indexerįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/internals.py", line 3591, in _slice_take_blocks_ax0įile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/internals.py", line 3621, in _make_na_blockīlock_values = np.empty(block_shape, dtype=dtype)įile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/sklearn/decomposition/kernel_pca.py", line 202, in fitįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/sklearn/decomposition/kernel_pca.py", line 135, in _get_kernelįile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/sklearn/metrics/pairwise.py", line 1347, in pairwise_kernels Update: adding the traceback errors: Traceback (most recent call last):įile "/home/ec2-user/anaconda2/lib/python2.7/site-packages/pandas/core/ops.py", line 1057, in f I've also verified that I'm using 64-bit Python. I've rebooted the notebook, the kernel, and the instance, but the same calls keep giving the MemoryError. Most perplexingly, I can do this and it finishes in a few seconds: huge = range(1000000000) Meanwhile, these work fine: Z = X.copy(deep=True) Pca = decomposition.KernelPCA(n_components=5) Certain Pandas and Scikit-learn (v0.17) calls will trigger a MemoryError instantly, e.g.: #X is a subset of the original df with 60 columns instead of the 3000 I've loaded a Pandas (v0.18) dataframe that is large (150K rows, ~30KB per row), but is nowhere near the memory capacity of the instance, even if many many copies are made. I'm working in Python2.7 (Anaconda 4.0) on a Jupyter notebook on a EC2 instance with plenty of memory (60GB, 48GB free according to free).