pandas – Python: create a new column from existing columns

pandas – Python: create a new column from existing columns

You can use apply with option axis=1. Then your solution is pretty concise.

df[z] = df.apply(lambda row: row.y if pd.notnull(row.y) else row.x, axis=1)

The new column z get its values from column y using df[z] = df[y]. This brings over the missing values so fill them in using fillna using column x. Chain these two actions:

>>> df[z] = df[y].fillna(df[x])
>>> df
   x   y   z
0  1 NaN   1
1  2   8   8
2  4  10  10
3  8 NaN   8

pandas – Python: create a new column from existing columns

Use np.where:

In [3]:

df[z] = np.where(df[y].isnull(), df[x], df[y])
df
Out[3]:
   x   y   z
0  1 NaN   1
1  2   8   8
2  4  10  10
3  8 NaN   8

Here it uses the boolean condition and if true returns df[x] else df[y]