Reputation: 31
So i have a dataset from a genechip, where 16 chips measure 1 tissue sample. I would like to subtract from each gene in each chip the mean of this gene over all the chips. Therefore I grouped by gene and calculated the mean. Now I want to take the original PM intensity value and subtract the Mean from this gene. Thus i need to match the gene column with the the index from the table where i stored the mean value for this gene group and then subtract this value from the PM column.
totalgene = genedata.groupby(genedata['GENE']).mean()[['PM','LOGPM']]
genedata['MEANNORM'] = genedata['PM'] - totalgene.ix[genedata['GENE']]['AVGPM']
genedata['MEANNORM'] = genedata['LOGPM'] - totalgene.ix[genedata['GENE']]['AVGLOGPM']
results in the error:
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-18-08c1bb979f9c> in <module>()
----> 1 genedata['MEANNORM'] = genedata['PM'] - totalgene.ix[genedata['GENE'],'AVGPM']
2 genedata['MEANNORM'] = genedata['LOGPM'] - totalgene.ix[genedata['GENE'],'AVGLOGPM']
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\frame.py in __setitem__(self, key, value)
2417 else:
2418 # set column
-> 2419 self._set_item(key, value)
2420
2421 def _setitem_slice(self, key, value):
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\frame.py in _set_item(self, key, value)
2483
2484 self._ensure_valid_index(value)
-> 2485 value = self._sanitize_column(key, value)
2486 NDFrame._set_item(self, key, value)
2487
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\frame.py in _sanitize_column(self, key, value, broadcast)
2633
2634 if isinstance(value, Series):
-> 2635 value = reindexer(value)
2636
2637 elif isinstance(value, DataFrame):
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\frame.py in reindexer(value)
2625 # duplicate axis
2626 if not value.index.is_unique:
-> 2627 raise e
2628
2629 # other
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\frame.py in reindexer(value)
2620 # GH 4107
2621 try:
-> 2622 value = value.reindex(self.index)._values
2623 except Exception as e:
2624
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\series.py in reindex(self, index, **kwargs)
2360 @Appender(generic._shared_docs['reindex'] % _shared_doc_kwargs)
2361 def reindex(self, index=None, **kwargs):
-> 2362 return super(Series, self).reindex(index=index, **kwargs)
2363
2364 @Appender(generic._shared_docs['fillna'] % _shared_doc_kwargs)
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\generic.py in reindex(self, *args, **kwargs)
2257 # perform the reindex on the axes
2258 return self._reindex_axes(axes, level, limit, tolerance, method,
-> 2259 fill_value, copy).__finalize__(self)
2260
2261 def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\generic.py in _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
2275 obj = obj._reindex_with_indexers({axis: [new_index, indexer]},
2276 fill_value=fill_value,
-> 2277 copy=copy, allow_dups=False)
2278
2279 return obj
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\generic.py in _reindex_with_indexers(self, reindexers, fill_value, copy, allow_dups)
2369 fill_value=fill_value,
2370 allow_dups=allow_dups,
-> 2371 copy=copy)
2372
2373 if copy and new_data is self._data:
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\core\internals.py in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups, copy)
3837 # some axes don't allow reindexing with dups
3838 if not allow_dups:
-> 3839 self.axes[axis]._can_reindex(indexer)
3840
3841 if axis >= self.ndim:
C:\Users\timothy\Anaconda3\lib\site-packages\pandas\indexes\base.py in _can_reindex(self, indexer)
2492 # trying to reindex on an axis with duplicates
2493 if not self.is_unique and len(indexer):
-> 2494 raise ValueError("cannot reindex from a duplicate axis")
2495
2496 def reindex(self, target, method=None, level=None, limit=None,
ValueError: cannot reindex from a duplicate axis
And i have no clue why? Could somebody help?
Upvotes: 0
Views: 1218
Reputation: 107687
Consider transform
for an inline aggregate which returns a series that can be subtracted from original columns, PM and LOGPM:
genedata['MEANNORM_PM'] = genedata['PM'] - \
genedata.groupby(['GENE'])['PM'].transform('mean')
genedata['MEANNORM_LOGPM'] = genedata['LOGPM'] - \
genedata.groupby(['GENE'])['LOGPM'].transform('mean')
Upvotes: 1