I work with a multi-indexing data framework in pandas and wonder if I should specify rows or columns.
My data looks something like this:
the code:
import numpy as np
import pandas as pd
arrays = pd.tools.util.cartesian_product([['condition1', 'condition2'],
['patient1', 'patient2'],
['measure1', 'measure2', 'measure3']])
colidxs = pd.MultiIndex.from_arrays(arrays,
names=['condition', 'patient', 'measure'])
rowidxs = pd.Index([0,1,2,3], name='time')
data = pd.DataFrame(np.random.randn(len(rowidxs), len(colidxs)),
index=rowidxs, columns=colidxs)
Here I select a multiindex column with the rationale that the pandas dataframe consists of a series, and my data ultimately represents a bunch of time series (hence, it is indexed by time).
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