Xtykutl

Something weird happened to me today. I needed to create a list based on a sequence of if statements. My dataframe looks something like this:

prom_lect4b_rbd    prom_lect2m_rbd   prom_lect8b_rbd   prom_lect6b_rbd

     100                np.nan            80                200

     np.nan             np.nan            40                1000

     np.nan             np.nan           np.nan              90

     230                 100              80                100

Columns are orderer according to their priority. The list (or column) I'm trying to create takes the first value from those rows that is not nan. So, in this case I want a column that looks like this:

simce_final_lect

     100

     40

     90

     230

I tried the following:

cols=[simces.prom_lect4b_rbd, simces.prom_lect2m_rbd, simces.prom_lect8b_rbd, simces.prom_lect6b_rbd]



simce_final_lect=[j if np.isnan(j)==False else k if np.isnan(k)==False

                  else l if np.isnan(l)==False else m if np.isnan(m)==False 

                  else np.nan for j,k,l,m in zip(cols[0],cols[1],cols[2],cols[3])]

And that just copies two values (out of 8752) to the list. But if I limit my zip to just j,k,l, it works perfectly:

simce_final_lect=[j if np.isnan(j)==False else k if np.isnan(k)==False

                  else l if np.isnan(l)==False  

                  else np.nan for j,k,l in zip(cols[0],cols[1],cols[2])]

Do you know what is happening? Else, is there a more efficient solution to my problem?

You can use bfill(axis=1) and select the first col.

df.bfill(axis=1).iloc[:,0]



0    100.0

1     40.0

2     90.0

3    230.0

Name: prom_lect4b_rbd, dtype: float64



## For list

df.bfill(axis=1).iloc[:,0].tolist()

['100', '40', 90, '230']

Use first_valid_index():

df.apply(lambda x: x[x.first_valid_index()], axis=1)

Yields:

0    100.0

1     40.0

2     90.0

3    230.0

dtype: float64