import pandas as pd
import matplotlib.pyplot as plt
import numpy as np


# Create fake sales data
n_sales = 1000
start = pd.Timestamp('2023-01-01 09:00')
end = pd.Timestamp('2023-04-01')
n_days = (end-start).days + 1  # pyright: ignore[reportOperatorIssue]

# random times from start
irregular_series = pd.to_timedelta(np.random.rand(n_sales) * n_days, unit='D')+start

# fake sales all = 0, resampled to daily
ts_sales = pd.Series(0, index=irregular_series)
tot_sales = ts_sales.resample('D').count() # daily sales

tot_sales.plot()
plt.show()