# import necessary libraries
import pandas as pd
from datetime import datetime

# create a time series
time_series = pd.Series(["2022-01-10", "2022-02-15", "2022-03-23",
                         "2022-04-09", "2022-05-19","2022-06-30"])

# define function to extract date components
def extract_date_components(date_str):
    date_obj = datetime.strptime(date_str, "%Y-%m-%d")
    day_of_month = date_obj.day
    week_number = date_obj.isocalendar()[1]
    day_of_year = date_obj.timetuple().tm_yday
    return pd.Series({'day_of_month': day_of_month,
                      'week_number': week_number,
                      'day_of_year': day_of_year})

# create dataframe
df = pd.DataFrame({"date": time_series})

# apply function to dataframe using the apply() method
df = df["date"].apply(extract_date_components).join(df)

# print results
print(df.sort_index(axis = 1))