Find maximum value of a column and return the corresponding row values using Pandas
Assuming df has a unique index, this gives the row with the maximum value:
In [34]: df.loc[df['Value'].idxmax()]Out[34]: Country USPlace KansasValue 894Name: 7Note 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()
I think the easiest way to return a row with the maximum value is by getting its index. argmax() can be used to return the index of the row with the largest value.
index = df.Value.argmax()Now the index could be used to get the features for that particular row:
df.iloc[df.Value.argmax(), 0:2]