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time-series-cookbook/ch1/1.03_resampling_a_time_series.py

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1	import pandas as pd
2	import matplotlib.pyplot as plt
3	import numpy as np
4
5
6	# Create fake sales data
7	n_sales = 1000
8	start = pd.Timestamp('2023-01-01 09:00')
9	end = pd.Timestamp('2023-04-01')
10	n_days = (end-start).days + 1 # pyright: ignore[reportOperatorIssue]
11
12	# random times from start
13	irregular_series = pd.to_timedelta(np.random.rand(n_sales) * n_days, unit='D')+start
14
15	# fake sales all = 0, resampled to daily
16	ts_sales = pd.Series(0, index=irregular_series)
17	tot_sales = ts_sales.resample('D').count() # daily sales
18
19	tot_sales.plot()
20	plt.show()