How to make a new list by comparing pandas Dataframe Columns with Set

Question:

I have already a set named "bad_outcomes" and a dataframe where a column name is "Outcome".

Using the "Outcome", I want to create a list where the element is 0 if the corresponding row in Outcome is in the set bad_outcomes; otherwise, it’s 1.

Then I want to assign it to the variable ‘landing_class’.

I have written this one:

landing_class = []

if df['Outcome'].isin(set(bad_outcomes)):
  landing_class.append(0)
else:
  landing_class.append(1)

It’s not working. I have got an error.

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
Asked By: Sumiya Akter Nisher

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Source

Answers:

Try using this one-liner with isin, eq and astype:

landing_class = df['Outcome'].isin(bad_outcomes).eq(False).astype(int)
Answered By: U12-Forward

First, the return of this condition is df['Outcome'].isin(set(bad_outcomes)) is a series of true and false values like that if {true, true, false,....} and that is invalid input to if-statement. In order to solve this problem, you need to use one of the functions such as all() or any().

But adding any or all only solves the error but it does not achieve your goal.

You have three solutions:

First Solution:

for i in df['Outcome']:
    if i in set(bad_outcomes):
        landing_class.append(0)
    else:
        landing_class.append(1)

Second Solution:

landing_class = np.where(df['Outcome'].isin(set(bad_outcomes)), 0, 1)

Third Solution:

landing_class  = list(~df['Outcome'].isin(set(bad_outcomes))*1)
Answered By: user16310106

This simple code works:

landing_class = np.where(df['Outcome'].isin(bad_outcomes), 0, 1)
Answered By: Nag