How can i read each row till the first occurence of NaN.?
While calling the pd.read_excel function, try setting keep_default_na = False. This will avoid default NaN values while reading.
From excel file i want to read each row and use it independently to process
here how the data looks like in excel file
12  32  45  67  89  54  23  56  78  98
34  76  34  89  34  3
76  34  54  12  43  78  56
76  56  45  23  43  45  67  76  67  8
87  9   9   0   89  90  6   89
23  90  90  32  23  34  56  9   56  87
23  56  34  3   5   8   7   6   98
32  23  34  6   65  78  67  87  89  87
12  23  34  32  43  67  45
343 76  56  7   8   9   4
but when i read it through pandas then the remaining columns are filled with NaN.
the data after reading from pandas looks like

0 12  32  45  67  89  54  23.0    56.0    78.0    98.0
1 34  76  34  89  34  3   NaN NaN NaN NaN
2 76  34  54  12  43  78  56.0    NaN NaN NaN
3 76  56  45  23  43  45  67.0    76.0    67.0    8.0
4 87  9   9   0   89  90  6.0 89.0    NaN NaN
5 23  90  90  32  23  34  56.0    9.0 56.0    87.0
6 23  56  34  3   5   8   7.0 6.0 98.0    NaN
7 32  23  34  6   65  78  67.0    87.0    89.0    87.0
8 12  23  34  32  43  67  45.0    NaN NaN NaN
9 343 76  56  7   8   9   4.0 5.0 8.0 68.0

Here it can be seen the remaining columns of each row is filled with NaN which i don't want.
Nor i wanted to replace it with some other value or drop the whole rows contains NaN .
How can i read columns of each row till the first occurence of NaN. ? 

For eg.The second row in pandas is 34 76  34  89  34  3   NaN NaN NaN NaN
so my desired output will be that it reads only 34    76  34  89  34  3

My preference is pandas but if not possible then is their any other way of doing it like with some other libraries
Any resource or reference will be helpful?
Thanks