CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Haalanam
Haalanam

Reputation: 89

Adding business days to python

Wonking on pandas dataframes -

I have a date format like this: datetime64[ns] and a column with a int64 format.

the dataframe looks like this:

           date    days        
0    2019-07-04       1 
1    2019-10-17       1 
2    2019-10-17       2

i want to use this function to add n business days:

def add_business_days(from_date,ndays):
    business_days_to_add = abs(ndays)
    current_date = from_date
    sign = ndays/abs(ndays)
    while business_days_to_add > 0:
        current_date += datetime.timedelta(sign * 1)
        weekday = current_date.weekday()
        if weekday >= 5: # sunday = 6
            continue
        business_days_to_add -= 1
    return current_date

But i somehow get this error:

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

Could you help on that ?

Upvotes: 1

Views: 2043

Answers (2)

JE_Muc
JE_Muc

Reputation: 5774

pandas has an implemented support for business days. I am not absolutely sure what your output is supposed to like like (since you did not include an expected output, could you please add it?), but I guess this is what you want:

pd.to_datetime(from_date) + pd.offsets.BDay(ndays)

Assuming your dataframe looks like this:

dates = [pd.to_datetime('2019-07-04'), pd.to_datetime('2019-10-17'), pd.to_datetime('2019-10-17')]
df = pd.DataFrame(data={'date': dates, 'days': [1, 1, 2]})

The conversion to a timestamp with pd.to_datetime() can be omitted.

Upvotes: 2

jezrael
jezrael

Reputation: 862661

Use lambda function with offsets.BDay:

def add_business_days(from_date,ndays):
    return from_date + pd.offsets.BDay(ndays)

df['date'] = pd.to_datetime(df['date'])
df['new'] = df.apply(lambda x: add_business_days(x['date'], x['days']), axis=1)

Or:

df['new'] = df.apply(lambda x: x['date'] +  pd.offsets.BDay(x['days']), axis=1)

print (df)
        date  days        new
0 2019-07-04     1 2019-07-05
1 2019-10-17     1 2019-10-18
2 2019-10-17     2 2019-10-21

Upvotes: 1

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