Reputation: 1801
I caught up with this scenario and don't know how can I solve this. I have the data frame where I am trying to add "week_of_year" and "year" column based in the "date" column of the pandas' data frame which is working fine.
import pandas as pd
df = pd.DataFrame({'date': ['2018-12-31', '2019-01-01', '2019-12-31', '2020-01-01']})
df['date'] = pd.to_datetime(df['date'])
df['week_of_year'] = df['date'].apply(lambda x: x.weekofyear)
df['year'] = df['date'].apply(lambda x: x.year)
print(df)
Current Output
date week_of_year year
0 2018-12-31 1 2018
1 2019-01-01 1 2019
2 2019-12-31 1 2019
3 2020-01-01 1 2020
Expected Output
So here what I am expecting is for 2018 and 2019 the last date was the first week of the new year which is 2019 and 2020 respectively so I want to add logic in the year, where the week is 1 but the date belongs for the previous year so the year column would track that as in the expected output.
date week_of_year year
0 2018-12-31 1 2019
1 2019-01-01 1 2019
2 2019-12-31 1 2020
3 2020-01-01 1 2020
Upvotes: 1
Views: 7318
Reputation: 514
To get the week number as a series
df['DATE'].dt.isocalendar().week
To set a new column to the week use same function and set series returned to a column:
df['WEEK'] = df['DATE'].dt.isocalendar().week
Use the pd.series.dt.isocalendar().week
to get the the week for a given series object.
Note:
Upvotes: 1
Reputation: 13387
Try:
df['date'] = pd.to_datetime(df['date'])
df['week_of_year'] = df['date'].dt.weekofyear
df['year']=(df['date']+pd.to_timedelta(6-df['date'].dt.weekday, unit='d')).dt.year
Outputs:
date week_of_year year
0 2018-12-31 1 2019
1 2019-01-01 1 2019
2 2019-12-31 1 2020
3 2020-01-01 1 2020
Few things - generally avoid .apply(..)
.
For datetime
columns you can just interact with the date through df[col].dt
variable.
Then to get the last day of the week just add to date 6-weekday
where weekday
is between 0 (Monday) and 6 to the date
Upvotes: 3