I have a dataframe that looks like the following:
df
0 1 2 3 4
0 0.0 NaN NaN NaN NaN
1 NaN 0.0 0.0 NaN 4.0
2 NaN 2.0 0.0 NaN 5.0
3 NaN NaN NaN 0.0 NaN
4 NaN 0.0 3.0 NaN 0.0
I would like to have a dataframe of all the couples of values different from NaN. The dataframe should be like the following
df
i j val
0 0 0 0.0
1 1 1 0.0
2 1 2 0.0
3 1 4 5.0
4 3 3 0.0
5 4 1 0.0
6 4 2 3.0
7 4 4 0.0
Use DataFrame.stack with DataFrame.rename_axis and DataFrame.reset_index:
df = df.stack().rename_axis(('i','j')).reset_index(name='val')
print (df)
i j val
0 0 0 0.0
1 1 1 0.0
2 1 2 0.0
3 1 4 4.0
4 2 1 2.0
5 2 2 0.0
6 2 4 5.0
7 3 3 0.0
8 4 1 0.0
9 4 2 3.0
10 4 4 0.0
Like this:
In [379]: df.stack().reset_index(name='val').rename(columns={'level_0':'i', 'level_1':'j'})
Out[379]:
i j val
0 0 0 0.0
1 1 1 0.0
2 1 2 0.0
3 1 4 4.0
4 2 1 2.0
5 2 2 0.0
6 2 4 5.0
7 3 3 0.0
8 4 1 0.0
9 4 2 3.0
10 4 4 0.0