Here is my data frame. df
store_1 store_2 store_3 store_4
0 banana banana plum banana
1 orange ta
If you wish to estimate the similarity of the stores with regards to their products, then you could use:
One hot encoding
Then each stores can be described by a vector with length of n = number of all products among all stores such as:
banana orange apple pear plum tangerin raspberry tomato melon . . .
Store_1 then is described as 1 1 1 1 1 0 0 0 0 0 ... Store_2 1 0 0 1 0 1 1 1 0 ...
This leaves you with a numerical vector, where you can compute dissimilarity measure such as Euclidean Distance.