Redefining index values in Pandas DataFrame

Question

There seem to be plenty of other questions about indexing Pandas DataFrames, but I have not found a way to do the type of changes I want. If I have a DF which looks likes

                Value
 Index1 Index2
 0      1       1.1
 1      2       1.2
 2      3       2.4
 3      1       1.3
 4      2       2.2
 5      3       3.1

I don't need all of index1 to be unique. I would rather have something like

                Value
 Index1 Index2
 0      1       1.1
 0      2       1.2
 0      3       2.4
 1      1       1.3
 1      2       2.2
 1      3       3.1

Is there a way to do this? I think the easiest way is to apply a function of dividing by index1 values by 3, but not sure how you apply a function to an index. Perhaps though pandas has it's own methods for redefining index values to have groupings like this which are still unique when you consider both indexes?

unutbu · Accepted Answer · 2013-05-27 20:57:57Z

5

import io
import pandas as pd
text = '''\
 Index1 Index2 Value
 0      1       1.1
 1      2       1.2
 2      3       2.4
 3      1       1.3
 4      2       2.2
 5      3       3.1'''

df = pd.read_table(io.BytesIO(text), sep='\s+', index_col=[0, 1])
df.index = pd.MultiIndex.from_tuples(
    [(item[0] // 3, item[1]) for item in df.index],
    names=df.index.names)    
print(df)

yields

               Value
Index1 Index2       
0      1         1.1
       2         1.2
       3         2.4
1      1         1.3
       2         2.2
       3         3.1

edited May 27, 2013 at 20:57

answered May 27, 2013 at 20:19

unutbu

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