How can I "unpivot" specific columns from a pandas DataFrame?

Question

I have a pandas DataFrame, eg:

x = DataFrame.from_dict({'farm' : ['A','B','A','B'],                           'fruit':['apple','apple','pear','pear'],                           '2014':[10,12,6,8],                           '2015':[11,13,7,9]}) 

ie:

   2014  2015 farm  fruit 0    10    11    A  apple 1    12    13    B  apple 2     6     7    A   pear 3     8     9    B   pear 

How can I convert it to this: ?

  farm  fruit  value  year 0    A  apple     10  2014 1    B  apple     12  2014 2    A   pear      6  2014 3    B   pear      8  2014 4    A  apple     11  2015 5    B  apple     13  2015 6    A   pear      7  2015 7    B   pear      9  2015 

I have tried stack and unstack but haven't been able to make it work.

Thanks!

Answer 1

This can be done with pd.melt():

# value_name is 'value' by default, but setting it here to make it clear pd.melt(x, id_vars=['farm', 'fruit'], var_name='year', value_name='value') 

Result:

  farm  fruit  year  value 0    A  apple  2014     10 1    B  apple  2014     12 2    A   pear  2014      6 3    B   pear  2014      8 4    A  apple  2015     11 5    B  apple  2015     13 6    A   pear  2015      7 7    B   pear  2015      9  [8 rows x 4 columns] 

I'm not sure how common "melt" is as the name for this kind of operation, but that's what it's called in R's reshape2 package, which probably inspired the name here.