Pandas assign - passing column in a user defined function

Question

Given an input dataframe and string:

df = pd.DataFrame({"A" : [10, 20, 30], "B" : [0, 1, 8]})
colour = "green" #or "red", "blue" etc.

I want to add a new column df["C"] conditional on the values in df["A"], df["B"] and colour so it looks like:

df = pd.DataFrame({"A" : [4, 2, 10], "B" : [1, 4, 3], "C" : [True, True, False]})

So far, I have a function that works for just the input values alone:

def check_passing(colour, A, B):
    if colour == "red":
        if B < 5:
            return True
        else:
            return False
    if colour == "blue":
        if B < 10:
            return True
        else:
            return False
    if colour == "green":
        if B < 5:
            if A < 5:
                return True
            else:
                return False
        else:
            return False

How would you go about using this function in df.assign() so that it calculates this for each row? Specifically, how do you pass each column to check_passing()?

df.assign() allows you to refer to the columns directly or in a lambda, but doesn't work within a function as you're passing in the entire column:

df = df.assign(C = check_passing(colour, df["A"], df["B"]))

Is there a way to avoid a long and incomprehensible lambda? Open to any other approaches or suggestions!

user17242583 · Accepted Answer · 2022-01-27 23:43:13Z

4

Applying a function like that can be inefficient, especially when dealing with dataframes with many rows. Here is a one-liner:

colour = "green" #or "red", "blue" etc.

df['C'] = ((colour == 'red') & df['B'].lt(5)) | ((colour == 'blue') & df['B'].lt(5)) | ((colour == 'green') & df['B'].lt(5) & df['A'].lt(5))

answered Jan 27, 2022 at 23:43

user17242583

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