>>> from datetime import datetime
>>> from pandas import read_csv, DataFrame

>>> df = DataFrame(
...     [
...         {
...             "Date": datetime.strptime(date, "%Y-%m-%d"),
...             "Price": value
...         }
...         for date, value in read_csv(
...             "https://datahub.io/core/oil-prices/r/wti-daily.csv"
...         ).values.tolist()
...     ]
... )

>>> print(len(df))
9286

>>> df.plot(x="Date", y="Price")

>>> from swinging_door import swinging_door

>>> compress = DataFrame(
...      list(
...         {
...             "Date": datetime.fromtimestamp(date),
...             "Price": value
...         }
...         for date, value in swinging_door(
...             [
...                 (date.timestamp(), value)
...                 for date, value in df.values.tolist()
...             ], deviation=.5
...         )
...     )
... )

>>> print(len(compress))
2719

>>> compress.plot(x="Date", y="Price")