Retain few NA's and drop rest of NA's during Stack operation in Python

Question

I have a dataframe like shown below

df2 = pd.DataFrame({\'person_id\':[1],\'H1_date\' : [\'2006-10-30 00:00:00\'], \'H1\':[2.3],\'H2_date\' : [\'2016-10-30          


        

Answer 1

try pd.DataFrame.melt

df = pd.melt(df2, id_vars='person_id', var_name='col', value_name='dates')
df['col2'] = df['col'].str.split("_").str[0]
df['count'] = df.groupby(['col2'])['dates'].transform(pd.Series.count)
df = df[df['count'] != 0]
df.drop(['col2', 'count'], axis=1, inplace=True)
print(df)

    person_id      col                dates
0           1  H1_date  2006-10-30 00:00:00
1           1       H1                  2.3
2           1  H2_date  2016-10-30 00:00:00
3           1       H2                 12.3
4           1  H3_date  2026-11-30 00:00:00
5           1       H3                 22.3
6           1  H4_date  2106-10-30 00:00:00
7           1       H4                 42.3
10          1  H6_date  2006-10-30 00:00:00
11          1       H6                  2.3
12          1  H7_date                  NaN
13          1       H7                  2.3
14          1  H8_date  2006-10-30 00:00:00
15          1       H8                  NaN