Need to write a function that joins two values from two separate columns together of different lengths
If I'm not mistaken about what you want, you can simply use print(df[["Y","M"]].dropna()).
If you wish to remove the NaN from the data altogether, pass an inplace=True argument in the dropna method (df.dropna(inplace=True)).
I have a .pkl file that has looks something like this but has at least 300 rows:




X
Y
Z
M




-0.522
3
0.55
Yes


0.44
5
NaN
No


NaN
NaN
0.241
Maybe


0.325
3
Nan
Yes




I want to get a list of values for Y and M [3 = Yes, 5 = No, 3 = Yes ] but in some of the rows there are NaNs.
Currently I am able to get Y without the NaNs
But there are no NaNs in M. I need to remove the M values that do not have a Y value. (Y = NaN)
Then print(Y_no_nans together with M_no_Y_nans)