list comprehension in pandas

Question

I'm giving a toy example but it will help me understand what's going on for something else I'm trying to do. Let's say I want a new column in a dataframe 'optimal_fruit' that is apples * orange - bananas.

I can do something like this to get it.

df2['optimal_fruit'] = df2['apples'] * df2['oranges'] - df2['bananas'] 


apples  oranges bananas optimal_fruit
1       6       11      -5
2       7       12      2
3       8       13      11
4       9       14      22
5       10      15      35

What is happening if I try to do something like this? And how could I do this in a list comprehension?

df2['optimal_fruit'] = [x * y - z for x in df2['apples'] for y in df2['oranges'] for z in df2['bananas']]

I get an error of:

ValueError: Length of values does not match length of index

As always, thank you all so much for your help!

Answer 1

Essentially your list comprehension statement is a set of 3 nested loops. In code:

l = []
for x in df2['apples']:
    for y in df2['oranges']:
        for z in df2['bananas']:
            l.extend([x * y - z])

The length of your resultant list will be 3 times the length of your DataFrame. Hence the error. To fix, you need the equivalent of:

for x, y, z in zip(df2['apples'], df2['oranges'], df2['bananas']):
    l.extend([x * y - z])

In terms of list comprehension:

[x * y - z for x, y, z in zip(df2['apples'], df2['oranges'], df2['bananas'])]

Answer 2

The reason why your new method doesn't work is because the list comprehension produces data that is longer than the number of indices in your dataframe. A quick fix for that would be something like:

[x * y - z for x,y,z in zip(df2['apples'], df2['oranges'], df2['bananas'])]

Answer 3

You can get all the values of the row as a list using the np.array() function inside your list of comprehension.

The following code solves your problem:

df2['optimal_fruit'] = [x[0] * x[1] - x[2] for x in np.array(df2)]

It is going to avoid the need of typing each column name in your list of comprehension.