In the DataFrame
import pandas as pd
df=pd.DataFrame({\'col1\':[1,2,3],\'col2\':[3,2,1],\'col3\':[1,1,1]},index= [\'row1\',\'row2\',\'row3\'])
print df
If not duplicates, you can use idxmax, but it return only first column of max
value:
print (df.idxmax(1))
row1 col2
row2 col1
row3 col1
dtype: object
def get_column_name_for_max_values_of(row):
return df.idxmax(1).ix[row]
print (get_column_name_for_max_values_of('row2'))
col1
But with duplicates use boolean indexing:
print (df.ix['row2'] == df.ix['row2'].max())
col1 True
col2 True
col3 False
Name: row2, dtype: bool
print (df.ix[:,df.ix['row2'] == df.ix['row2'].max()])
col1 col2
row1 1 3
row2 2 2
row3 3 1
print (df.ix[:,df.ix['row2'] == df.ix['row2'].max()].columns)
Index(['col1', 'col2'], dtype='object')
And function is:
def get_column_name_for_max_values_of(row):
return df.ix[:,df.ix[row] == df.ix[row].max()].columns.tolist()
print (get_column_name_for_max_values_of('row2'))
['col1', 'col2']