I have a dataframe that looks something like this:

date-time                   val 1   val 2   val 3
sample date-time 1          92      81      100
sample date-time 2          84      78      96
sample date-time 3          79              100
sample date-time 4          84      83  
sample date-time 5                  80      100
sample date-time 6          84      83      95

(note the missing values in multiple columns)

I’m trying to remove all rows that have atleast 1 missing value in columns val 1 or val 3 using dropna but it doesn’t do anything.

Here’s what I tried:

dftest = df.dropna(subset=['val 1', 'val 3'], how='all')
dftest

but this makes no changes in the dataframe. I suspect the values might not be being considered as empty or nans but I’ve no idea as to how or why that could happen. Any ideas would be appreciated, thanks!