I have a pandas data from with the following indices
print(df.index)
MultiIndex(levels=[[u'Day 3', u'Day 4', u'Day 5', u'Day 7', u'Day 9'], [u'D1', u'D10', u'D11', u'D12', u'D2', u'D3', u'D4', u'D5', u'D6', u'D7', u'D8', u'D9'], [1.0, 2.0, 3.0]],
labels=[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4], [0, 0, 0, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 1, 1, 1, 2, 2, 2, 3, 3, 3, 0, 0, 0, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 1, 1, 1, 2, 2, 2, 3, 3, 3, 0, 0, 0, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 1, 1, 1, 2, 2, 2, 3, 3, 3, 0, 0, 0, 4, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 1, 1, 1, 2, 2, 2, 3, 3, 3, 0, 0, 0, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 1, 1, 1, 2, 2, 2, 3, 3, 3], [1, 2, 0, 1, 2, 0, 0, 2, 1, 0, 1, 2, 2, 0, 1, 0, 2, 1, 1, 2, 0, 1, 0, 2, 2, 0, 1, 0, 1, 2, 2, 1, 0, 1, 2, 0, 0, 2, 1, 0, 2, 1, 2, 0, 1, 0, 2, 1, 1, 0, 2, 0, 1, 2, 0, 2, 1, 2, 0, 1, 0, 2, 1, 0, 2, 1, 2, 0, 1, 0, 2, 1, 2, 1, 0, 0, 2, 1, 1, 2, 0, 0, 2, 1, 0, 1, 2, 0, 1, 2, 2, 1, 0, 1, 0, 2, 1, 0, 2, 0, 1, 2, 2, 0, 1, 1, 0, 2, 1, 2, 0, 1, 1, 2, 0, 2, 1, 0, 1, 2, 0, 0, 1, 2, 0, 1, 2, 2, 1, 0, 1, 0, 2, 2, 0, 1, 0, 1, 2, 0, 2, 1, 2, 0, 1, 1, 2, 0, 0, 2, 1, 0, 2, 1, 0, 2, 1, 2, 1, 0, 0, 2, 1, 2, 0, 1, 2, 0, 1, 2, 1, 0, 1, 2, 0, 2, 1, 0, 1, 2, 0]],
names=[u'Interval', u'Device', u'Well'])
I am sorting with the following
df = df.reindex(index=natsorted(df.index))
With this particular df, however, it returns the follow error.
raise Exception("cannot handle a non-unique multi-index!")
Exception: cannot handle a non-unique multi-index!
Any help would be greatly appreciated.
I made a minimal example and could reproduce your error. It seems it happens, because of the same levels tuple Day 3, D1 and 1.0 in arrays. If you remove one of them it works fine.
import pandas as pd
import numpy as np
from natsort import natsorted
arrays = [[u'Day 3', u'Day 3', u'Day 4', u'Day 5', u'Day 7', u'Day 9', u'Day 3', u'Day 4', u'Day 5', u'Day 7', u'Day 9'],
[u'D1', u'D1', u'D10', u'D11', u'D12', u'D2', u'D3', u'D4', u'D5', u'D6', u'D7'],
[1.0, 1.0, 2.0, 3.0, 1.0, 2.0, 1.0, 2.0, 3.0, 1.0, 2.0]]
tuples = list(zip(*arrays))
index = pd.MultiIndex.from_tuples(tuples, names=[u'Interval', u'Device', u'Well'])
df = pd.Series(np.random.randn(len(arrays[0])), index=index)
print df.index
df = df.reindex(index=natsorted(df.index))
As you mentioned you use several excel files, this may be helpful: Merging multiple dataframes with non unique indexes