How to transpose rows into single column based on time-stamp index in python?
Assuming you have the following source DF:

In [21]: df
Out[21]:
         Time  val1  val2  val3
0  2017-11-17    11    12    13
1  2017-11-18    24    25     0
2  2017-11-19    37     0     0


Solution:

In [22]: (df.replace(0, np.nan)
            .set_index('Time', append=True)
            .stack()
            .reset_index()
            .rename(columns={0:'val'})
            .drop('level_2',1))
Out[22]:
   level_0        Time   val
0        0  2017-11-17  11.0
1        0  2017-11-17  12.0
2        0  2017-11-17  13.0
3        1  2017-11-18  24.0
4        1  2017-11-18  25.0
5        2  2017-11-19  37.0