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Sample input dataset is:

enter image description here

Sample output dataset what i want:

0   2017-11-17 10:23:28.691 788
0   2017-11-17 10:23:28.691 756
0   2017-11-17 10:23:28.691 789
0   2017-11-17 10:23:28.691 780
1   2017-11-17 10:23:29.731 788
1   2017-11-17 10:23:29.731 783
2   2017-11-17 10:23:30.655 747
3   2017-11-17 10:23:31.627 766
4   2017-11-17 10:23:32.606 807

How can I do this by pandas? or is there any other technique to do this?

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3
  • 1
    $\begingroup$ This is probably best suited for StackOverflow I think? It's a purely programming question. $\endgroup$
    – Mephy
    Nov 22, 2017 at 13:56
  • $\begingroup$ I think this is fine. It's a data wrangling question. $\endgroup$
    – Louis T
    Nov 22, 2017 at 20:57
  • $\begingroup$ Thanks, everyone. I posted to Stackoverflow and got the answer stackoverflow.com/questions/47437966/… $\endgroup$
    – An0mn
    Nov 23, 2017 at 9:26

1 Answer 1

Reset to default
2
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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
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