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import numpy as np
# Define the getDateFeatures() function
def getDateFeatures(df):
df['holiday_type'] = 'Workday'
df['is_holiday'] = False
df['year'] = df['date'].dt.year
df['month'] = df['date'].dt.month
df['dayofmonth'] = df['date'].dt.day
df['dayofweek'] = df['date'].dt.dayofweek
df['weekofyear'] = df['date'].dt.weekofyear
df['quarter'] = df['date'].dt.quarter
df['is_month_start'] = df['date'].dt.is_month_start.astype(int)
df['is_month_end'] = df['date'].dt.is_month_end.astype(int)
df['is_quarter_start'] = df['date'].dt.is_quarter_start.astype(int)
df['is_quarter_end'] = df['date'].dt.is_quarter_end.astype(int)
df['is_year_start'] = df['date'].dt.is_year_start.astype(int)
df['is_year_end'] = df['date'].dt.is_year_end.astype(int)
# Extract the 'year' and 'weekofyear' components from the 'date' column
df['year_weekofyear'] = df['date'].dt.year * 100 + df['date'].dt.weekofyear
# create new coolumns to represent the cyclic nature of a year
df['dayofyear'] = df['date'].dt.dayofyear
df["sin(dayofyear)"] = np.sin(df["dayofyear"])
df["cos(dayofyear)"] = np.cos(df["dayofyear"])
df["is_weekend"] = np.where(df['dayofweek'] > 4, 1, 0)
# Define the criteria for each season
seasons = {'Winter': [12, 1, 2], 'Spring': [3, 4, 5], 'Summer': [6, 7, 8], 'Autumn': [9, 10, 11]}
# Create the 'season' column based on the 'date' column
df['season'] = df['month'].map({month: season for season, months in seasons.items() for month in months})
return df |