Pandas Melt with Multiple Value Vars

Question

I have a data set which is in wide format like this

   Index Country     Variable 2000 2001 2002 2003 2004 2005
   0     Argentina   var1     12   15   18            


        

Answer 1

numpy

years = df.drop(['Country', 'Variable'], 1)
y = years.values
m = y.shape[1]
c = df.Country.values
v = df.Variable.values

f0, u0 = pd.factorize(df.Country.values)
f1, u1 = pd.factorize(df.Variable.values)

w = np.empty((u1.size, u0.size, m), dtype=y.dtype)
w[f1, f0] = y

results = pd.DataFrame(dict(
        Country=u0.repeat(m),
        Year=np.tile(years.columns.values, u0.size),
    )).join(pd.DataFrame(w.reshape(-1, m * u1.size).T, columns=u1))

results

      Country  Year  var1  var2
0   Argentina  2000    12     1
1   Argentina  2001    15     3
2   Argentina  2002    18     2
3   Argentina  2003    17     5
4   Argentina  2004    23     7
5   Argentina  2005    29     5
6      Brazil  2000    20     0
7      Brazil  2001    23     1
8      Brazil  2002    25     2
9      Brazil  2003    29     2
10     Brazil  2004    31     3
11     Brazil  2005    32     3