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()
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