First non-null value per row from a list of Pandas columns

Question

If I\'ve got a DataFrame in pandas which looks something like:

    A   B   C
0   1 NaN   2
1 NaN   3 NaN
2 NaN   4   5
3 NaN NaN NaN

How ca

Answer 1

groupby in axis=1

If we pass a callable that returns the same value, we group all columns together. This allows us to use groupby.agg which gives us the first method that makes this easy

df.groupby(lambda x: 'Z', 1).first()

     Z
0  1.0
1  3.0
2  4.0
3  NaN

This returns a dataframe with the column name of the thing I was returning in my callable

---

lookup, notna, and idxmax

df.lookup(df.index, df.notna().idxmax(1))

array([ 1.,  3.,  4., nan])

---

argmin and slicing

v = df.values
v[np.arange(len(df)), np.isnan(v).argmin(1)]

array([ 1.,  3.,  4., nan])