[FIXED] Is there a method to save not missing values in another data frame?

Issue

I have a data frame by 20441 rows and 158 columns. in each row, there are a lot of "NA" values. so I want to convert it to sth like this:

If a value is not NA, I save it's row name , column name and value in another data frame. for example my first data frame is :

row and column name	c1	c2	c3	c4	c5
r1	NA	NA	NA	5	6
r2	1	3	NA	NA	NA

row name	c1	c2
r1	c4	5
r1	c5	6
r2	c1	1
r2	c2	3

Solution

Use melt:

out = (df.melt('row and column name', var_name='C1', value_name='C2')
         .dropna().astype({'C2': int}))

Output:

row and column name	C1	C2
r2	c1	1
r2	c2	3
r1	c4	5
r1	c5	6

Answered By - Corralien