计算和绘制超越概率的Python方法？

Question

我的销售预测时间序列如下：

   Date        Sales
Jan 2020    1270.5835
Feb 2020    1298.713662
Mar 2020    1303.249137
Apr 2020    1338.529632
May 2020    1471.54609
Jun 2020    1572.235056
Jul 2020    1612.89844
Aug 2020    1610.461128
Sep 2020    1531.651765
Oct 2020    1448.489179
Nov 2020    1318.591714
Dec 2020    1296.853276
Jan 2021    1329.845902
Feb 2021    1336.795806
Mar 2021    1342.587392
Apr 2021    1377.867888
May 2021    1510.884345
Jun 2021    1611.573311
Jul 2021    1652.236695
Aug 2021    1649.799383
Sep 2021    1570.990021
Oct 2021    1487.827434
Nov 2021    1357.929969
Dec 2021    1336.191531
Jan 2022    1369.184158
Feb 2022    1376.134061
Mar 2022    1381.925647
Apr 2022    1417.206143
May 2022    1550.2226
Jun 2022    1650.911566
Jul 2022    1691.57495
Aug 2022    1689.137638
Sep 2022    1610.328276
Oct 2022    1527.165689
Nov 2022    1397.268224
Dec 2022    1375.529786
Jan 2023    1408.522413
Feb 2023    1415.472316
Mar 2023    1421.263902
Apr 2023    1456.544398
May 2023    1589.560855
Jun 2023    1690.249821
Jul 2023    1730.913205
Aug 2023    1728.475894
Sep 2023    1649.666531
Oct 2023    1566.503944
Nov 2023    1436.606479
Dec 2023    1414.868042
Jan 2024    1447.860668
Feb 2024    1454.810571
Mar 2024    1460.602157
Apr 2024    1495.882653
May 2024    1628.899111
Jun 2024    1729.588076
Jul 2024    1770.25146
Aug 2024    1767.814149
Sep 2024    1689.004786
Oct 2024    1605.842199
Nov 2024    1475.944734
Dec 2024    1454.206297
Jan 2025    1487.198923
Feb 2025    1494.148826
Mar 2025    1499.940413
Apr 2025    1535.220908
May 2025    1668.237366
Jun 2025    1768.926331
Jul 2025    1809.589715
Aug 2025    1807.152404
Sep 2025    1728.343041
Oct 2025    1645.180455
Nov 2025    1515.282989
Dec 2025    1493.544552
Jan 2026    1526.537178
Feb 2026    1533.487082
Mar 2026    1539.278668
Apr 2026    1574.559163
May 2026    1707.575621
Jun 2026    1808.264587
Jul 2026    1848.927971
Aug 2026    1846.490659
Sep 2026    1767.681297
Oct 2026    1684.51871
Nov 2026    1554.621245
Dec 2026    1532.882807
Jan 2027    1565.875433
Feb 2027    1572.825337
Mar 2027    1578.616923
Apr 2027    1613.897419
May 2027    1746.913876
Jun 2027    1847.602842
Jul 2027    1888.266226
Aug 2027    1885.828914
Sep 2027    1807.019552
Oct 2027    1723.856965
Nov 2027    1593.9595
Dec 2027    1572.221062
Jan 2028    1605.213689
Feb 2028    1612.163592
Mar 2028    1617.955178
Apr 2028    1653.235674
May 2028    1786.252131
Jun 2028    1886.941097
Jul 2028    1927.604481
Aug 2028    1925.167169
Sep 2028    1846.357807
Oct 2028    1763.19522
Nov 2028    1633.297755
Dec 2028    1611.559317
Jan 2029    1644.551944
Feb 2029    1651.501847
Mar 2029    1657.293433
Apr 2029    1692.573929
May 2029    1825.590387
Jun 2029    1926.279352
Jul 2029    1966.942736
Aug 2029    1964.505425
Sep 2029    1885.696062
Oct 2029    1802.533475
Nov 2029    1672.63601
Dec 2029    1650.897573
Jan 2030    1683.890199
Feb 2030    1690.840102
Mar 2030    1696.631689
Apr 2030    1731.912184
May 2030    1864.928642
Jun 2030    1965.617607
Jul 2030    2006.280991
Aug 2030    2003.84368
Sep 2030    1925.034317
Oct 2030    1841.871731
Nov 2030    1711.974265
Dec 2030    1690.235828

我想要的是如何提取和绘制上述时间序列（销售额的1%、5%、10%、50%和90%）的超越概率（POE），使用pythonic方法。所需的输出如下所示：

该图显示了超出值的概率 未来几年。 高场景：虚线。 基本场景：实线。 低场景：虚线