Distance calculation between rows in Pandas Dataframe using a distance matrix

Question

I have the following Pandas DataFrame:

In [31]:
import pandas as pd
sample = pd.DataFrame({\'Sym1\': [\'a\',\'a\',\'a\',\'d\'],\'Sym2\':[\'a\',\'c\',\'b\',\'         


        

Answer 1

this is doing twice as much work as needed, but technically works for non-symmetric distance matrices as well ( whatever that is supposed to mean )

pd.DataFrame ( { idx1: { idx2:sum( DistMatrix[ x ][ y ]
                                  for (x, y) in zip( row1, row2 ) ) 
                         for (idx2, row2) in sample.iterrows( ) } 
                 for (idx1, row1 ) in sample.iterrows( ) } )

you can make it more readable by writing it in pieces:

# a helper function to compute distance of two items
dist = lambda xs, ys: sum( DistMatrix[ x ][ y ] for ( x, y ) in zip( xs, ys ) )

# a second helper function to compute distances from a given item
xdist = lambda x: { idx: dist( x, y ) for (idx, y) in sample.iterrows( ) }

# the pairwise distance matrix
pd.DataFrame( { idx: xdist( x ) for ( idx, x ) in sample.iterrows( ) } )