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primarykey
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6817194
data
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0
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0
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2011-07-25T13:52:49.863
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2011-07-25T14:07:27.833
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2011-07-25T14:07:27.833
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652155
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652155
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6294436
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2
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2
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You can try explicitly casting to a data.frame in your yahooImport function. The following worked for me: <pre><code>>>> yahooImport = robjects.r('function(x) as.data.frame(yahooImport(x)@data)') >>> print type(qqq) <class 'rpy2.robjects.vectors.DataFrame'> >>> qqq <DataFrame - Python:0x102412680 / R:0x103c2b310> [Float..., Float..., Float..., Float..., Float..., Float...] Open: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241a638 / R:0x1048f1c00> [58.970000, 58.660000, 59.180000, ..., 102.250000, 102.870000, 102.250000] High: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241acf8 / R:0x104916000> [59.700000, 59.320000, 59.190000, ..., 102.310000, 103.470000, 102.310000] Low: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241add0 / R:0x10491c200> [58.920000, 58.340000, 58.500000, ..., 99.310000, 100.620000, 100.560000] Close: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241aef0 / R:0x10486f800> [59.600000, 58.990000, 58.600000, ..., 100.120000, 102.620000, 102.120000] Volume: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241d050 / R:0x104875a00> [43540100.000000, 70148800.000000, 57085500.000000, ..., 8743600.000000, 9688600.000000, 5232000.000000] Adj.Close: <class 'rpy2.robjects.vectors.FloatVector'> <FloatVector - Python:0x10241d170 / R:0x10485a000> [59.600000, 58.990000, 58.600000, ..., 48.110000, 49.320000, 49.080000] </code></pre> yahooImport returns a timeSeries object which is represented internally as a matrix, which is what is causing your return values in rpy2 to be a matrix.
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