Creating my dataframe:
from pandas import *
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
tuples = zip(*arrays)
index = MultiIndex.from_tuples(tuples, names=['first','second'])
data = DataFrame(randn(8,2),index=index,columns=['c1','c2'])
data
Out[68]:
c1 c2
first second
bar one 0.833816 -1.529639
two 0.340150 -1.818052
baz one -1.605051 -0.917619
two -0.021386 -0.222951
foo one 0.143949 -0.406376
two 1.208358 -2.469746
qux one -0.345265 -0.505282
two 0.158928 1.088826
I would like to rename the "first" index values, such as "bar"->"cat", "baz"->"dog", etc. However, every example I have read either operates on a single-level index and/or loops through the entire index to effectively re-create it from scratch. I was thinking something like:
data = data.reindex(index={'bar':'cat','baz':'dog'})
but this does not work, nor do I really expect it to work on multiple indexes. Can I do such a replacement without looping through the entire dataframe index?
Begin edit
I am hesitant to update to 0.13 until release, so I used the following workaround:
index = data.index.tolist()
for r in xrange( len(index) ):
index[r] = (codes[index[r][0]],index[r][1])
index = pd.MultiIndex.from_tuples(index,names=data.index.names)
data.index = index
Where is a previous defined dictionary of code:string pairs. This actually isn't as big of a performance his as I was expecting (takes a couple seconds to operate over ~1.1 million rows). It is not as pretty as a one-liner, but it does work.
End Edit