Spaces:
Sleeping
Sleeping
from datetime import datetime, date | |
import numpy as np | |
import pandas as pd | |
def dk_calendar() -> pd.DataFrame: | |
""" | |
Fetches calendar for Denmark. | |
Returns: | |
- pd.DataFrame: DataFrame with danish calendar. | |
""" | |
df = pd.read_csv('https://raw.githubusercontent.com/Camillahannesbo/MLOPs-Assignment-/main/data/calendar_incl_holiday.csv', delimiter=';', usecols=['date', 'type']) | |
# Formatting the date column to 'YYYY-MM-DD' dateformat | |
df["date"] = df["date"].map(lambda x: datetime.strptime(x, '%d/%m/%Y').strftime("%Y-%m-%d")) | |
# Add features to the calendar dataframe | |
df['date_'] = pd.to_datetime(df['date']) | |
df['dayofweek'] = df['date_'].dt.dayofweek | |
df['day'] = df['date_'].dt.day | |
df['month'] = df['date_'].dt.month | |
df['year'] = df['date_'].dt.year | |
df['workday'] = np.where(df['type'] == 'Not a Workday', 0, 1) | |
# Drop the columns 'type' and 'date_' to finalize the calendar dataframe | |
calendar = df.drop(['type','date_'], axis=1) | |
# Return the DataFrame with calendar data | |
return calendar |