Count non-null values in each row with pandas

Question

I have dataframe

    site1   time1   site2   time2   site3   time3   site4   time4   site5   time5   ... time6   site7   time7   site8   time8   site9   time         


        

Answer 1

I'd do this with just count:

train_df[sites].count(axis=1)

count specifically counts non-null values. The issue with your current implementation is that notnull yields boolean values, and bools are certainly not-null, meaning they are always counted.

---

df

        one       two     three four   five
a -0.166778  0.501113 -0.355322  bar  False
b       NaN       NaN       NaN  NaN    NaN
c -0.337890  0.580967  0.983801  bar  False
d       NaN       NaN       NaN  NaN    NaN
e  0.057802  0.761948 -0.712964  bar   True
f -0.443160 -0.974602  1.047704  bar  False
g       NaN       NaN       NaN  NaN    NaN
h -0.717852 -1.053898 -0.019369  bar  False

df.count(axis=1)

a    5
b    0
c    5
d    0
e    5
f    5
g    0
h    5
dtype: int64

And...

df.notnull().count(axis=1)


a    5
b    5
c    5
d    5
e    5
f    5
g    5
h    5
dtype: int64

Answer 2

Also trading count(axis=1) for sum() should do the trick

train_df[sites].notnull().sum()