How to change entire row if NaN present if a single column has NaN

What I will do reindex

df.dropna().reindex(df.index)

mask:

df.mask(df.gauge.isna())

---

                        gauge  satellite
1979-06-23 18:00:00  6.700000   2.484378
1979-06-27 03:00:00       NaN        NaN
1979-06-27 06:00:00  1.833333   4.053460
1979-06-27 09:00:00       NaN        NaN
1979-07-31 18:00:00  6.066667   1.438324

use np.where to add nan

import numpy as np
df['satellite'] = np.where(df['gauge'].isnull(),np.nan,df['satellite'])

Second solution

use .loc and isnull

df.loc[df['guage'].isnull(),'satellite'] = np.nan