CODEWITHSUNDEEP
pythonpandasdataframe
cbz
cbz

Reputation: 13

How to apply multiple condition in a single dataframe column with leap year logic

I am trying to create a column that is true if it is in leap year and false otherwise.

This is what I have tried so far and struggling to combined into one column:

df = pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/AirPassengers.csv")

"""
Here are the rules of leap years:
    A year may be a leap year if it is evenly divisible by 4.
    Years that are divisible by 100 (century years such as 1900 or 2000) cannot be leap years unless they are also divisible by 400. (For this reason, the years 1700, 1800, and 1900 were not leap years, but the years 1600 and 2000 were.)
condiction: 
1) divisible by 4
2) check century: divsible by 100 & 400

"""
df['year']=pd.to_datetime(df.date).dt.year

def filter_func(x):

    if x[2] % 4 ==0:
        return True
    else:
        return False

def filter_func1(x):

    if x[2] % 100 ==0 and x[2] %400 ==0:
        return True
    else:
        return False

df['multi_true'] = df.apply(filter_func1, axis=1)

Upvotes: 1

Views: 62

Answers (1)

U13-Forward
U13-Forward

Reputation: 71610

Pandas already has a function for this:

df['multi_true'] = pd.to_datetime(df['year'], format='%Y').dt.is_leap_year

It would give false for 1900 as well.

Upvotes: 4

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