Find maximum value of a column and return the corresponding row values using Pandas

Structure of data;

Using Python Pandas I am trying to find the 'Country' & 'Place' with the maximum value.

This returns the maximum value:

    data.groupby(['Country','Place'])['Value'].max()

But how do I get the corresponding 'Country' and 'Place' name?

Assuming df has a unique index, this gives the row with the maximum value:

    In [34]: df.loc[df['Value'].idxmax()]
    Out[34]: 
    Country        US
    Place      Kansas
    Value         894
    Name: 7

Note that idxmax returns index labels. So if the DataFrame has duplicates in the index, the label may not uniquely identify the row, so df.loc may return more than one row.

Therefore, if df does not have a unique index, you must make the index unique before proceeding as above. Depending on the DataFrame, sometimes you can use stack or set_index to make the index unique. Or, you can simply reset the index (so the rows become renumbered, starting at 0):

    df = df.reset_index()

From: stackoverflow.com/q/15741759

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