0.13.1: DataFrame.xs() ValueError: Cannot retrieve view (copy=False)

[bluefir]

I have python 2.7.6 and pandas 0.13.1 on Windows 7.

>>>portfolio_data_all.index.names
FrozenList([u'date', u'stock_id'])
>>>portfolio_data_all.xs(cusip_etf, level=field_stock_id, copy=False)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-69-5300763cc7b7> in <module>()
----> 1 portfolio_data_all.xs(cusip_etf, level=field_stock_id, copy=False)

C:\Python27\lib\site-packages\pandas\core\generic.pyc in xs(self, key, axis, level, copy, drop_level)
   1261 
   1262             if not copy and not isinstance(loc, slice):
-> 1263                 raise ValueError('Cannot retrieve view (copy=False)')
   1264 
   1265             # level = 0

ValueError: Cannot retrieve view (copy=False)

[cpcloud]

numpy always returns a copy of non-contiguous indices. It's more than likely that you'll have to copy when calling xs, because you're often taking a non contiguous chunk of the array out. Why can't you pass copy=True?

[bluefir]

I am bending over backwards trying to assign something to a column for rows where the second level in the MultiIndex has a particular value. For the first level, I can do it easily with .loc. How can I do it for the second level?

[jreback]

in reality this option shouldn't exist at all
xs by definition is a copy except in very rare cases and is just confusing
don't pass the copy flag

I think maybe I'll take it out

[bluefir]

@jreback no "may be". Take it out, please.

[jreback]

in master do this: http://pandas.pydata.org/pandas-docs/dev/

you can swap levels assign then swap back in other versions

[bluefir]

Got it. How expensive is swaplevel? Does it create a copy of everything?

[jreback]

swap level is cheap
if the underlying is already a copy (eg not a view) then this overall should be pretty cheap

[bluefir]

Thanks!

[jreback]

ok going to leave open to remove the copy option from xs

[bluefir]

Why doesn't this work?

>>>portfolio_data_all.loc[cusip_etf, [field_benchmark_weight, '_temp']]
            weight_benchmark     _temp
date                                  
2014-01-01               NaN  0.074489
2014-01-02               NaN  0.074486
2014-01-03               NaN  0.075367
2014-01-06               NaN  0.075428
2014-01-07               NaN  0.075089

[5 rows x 2 columns]
>>>portfolio_data_all.loc[cusip_etf, field_benchmark_weight] = portfolio_data_all.loc[cusip_etf, '_temp']
>>>>>>portfolio_data_all.loc[cusip_etf, [field_benchmark_weight, '_temp']]
            weight_benchmark     _temp
date                                  
2014-01-01               NaN  0.074489
2014-01-02               NaN  0.074486
2014-01-03               NaN  0.075367
2014-01-06               NaN  0.075428
2014-01-07               NaN  0.075089

[5 rows x 2 columns]

[bluefir]

Never mind, somehow this worked:

>>>portfolio_data_all.loc[cusip_etf, field_benchmark_weight] = portfolio_data_all['_temp']
            weight_benchmark     _temp
date                                  
2014-01-01          0.074489  0.074489
2014-01-02          0.074486  0.074486
2014-01-03          0.075367  0.075367
2014-01-06          0.075428  0.075428
2014-01-07          0.075089  0.075089

[5 rows x 2 columns]

The funny thing is that if I use a row indexer like

rows_au = portfolio_data_all[field_country] = 'AU'

I would have to do

portfolio_data_all.loc[rows_au, field_benchmark_weight] = portfolio_data_all.loc[rows_au, '_temp']

Why the disconnect?

[jreback]

can u make an example that can be easily copy-pasted

thanks