Python / fbprophet-如何根据季节进行调整

Question

数据集：

def replace_inside_parentheses(string, find_string, replace_string):
    bracket_count = 0
    return_string = ""
    for a in string:
        if a == "(":
            bracket_count += 1
        elif a == ")":
            bracket_count -= 1
        if bracket_count > 0:
            return_string += a.replace(find_string, replace_string)
        else:
            return_string += a
    return return_string


my_str = "Hello (This . will be replaced, this one. too, (even this one . inside nested parentheses!))."
print(my_str)
print(replace_inside_parentheses(my_str, ".", ";"))

使用df = {'date': {0: '01/01/2017', 1: '02/01/2017', 2: '03/01/2017', 3: '04/01/2017', 4: '05/01/2017', 5: '06/01/2017', 6: '07/01/2017', 7: '08/01/2017', 8: '09/01/2017', 9: '10/01/2017', 10: '11/01/2017', 11: '12/01/2017', 12: '13/01/2017', 13: '14/01/2017', 14: '15/01/2017', 15: '16/01/2017', 16: '17/01/2017', 17: '18/01/2017', 18: '19/01/2017', 19: '20/01/2017', 20: '21/01/2017', 21: '22/01/2017', 22: '23/01/2017', 23: '24/01/2017', 24: '25/01/2017', 25: '26/01/2017', 26: '27/01/2017', 27: '28/01/2017', 28: '29/01/2017', 29: '30/01/2017', 30: '31/01/2017', 31: '01/02/2017', 32: '02/02/2017', 33: '03/02/2017', 34: '04/02/2017', 35: '05/02/2017', 36: '06/02/2017', 37: '07/02/2017', 38: '08/02/2017', 39: '09/02/2017', 40: '10/02/2017', 41: '11/02/2017', 42: '12/02/2017', 43: '13/02/2017', 44: '14/02/2017', 45: '15/02/2017', 46: '16/02/2017', 47: '17/02/2017', 48: '18/02/2017', 49: '19/02/2017', 50: '20/02/2017', 51: '21/02/2017', 52: '22/02/2017', 53: '23/02/2017', 54: '24/02/2017', 55: 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3289, 250: 1936, 251: 1706, 252: 1856, 253: 3307, 254: 2228, 255: 3591, 256: 3367, 257: 1934, 258: 1992, 259: 2378, 260: 2062, 261: 1879, 262: 1598, 263: 1353, 264: 3018, 265: 892, 266: 1188, 267: 3407, 268: 2440, 269: 1613, 270: 1171, 271: 2144, 272: 1253, 273: 2583, 274: 2607, 275: 1620, 276: 2517, 277: 2056, 278: 2048, 279: 986, 280: 1621, 281: 2404, 282: 1955, 283: 2130, 284: 1566, 285: 1102, 286: 704, 287: 1213, 288: 1151, 289: 1646, 290: 1810, 291: 2229, 292: 1653, 293: 1779, 294: 1951, 295: 2525, 296: 1351, 297: 2146, 298: 1929, 299: 2244, 300: 730, 301: 2306, 302: 2464, 303: 1115, 304: 2007, 305: 1475, 306: 1759, 307: 1624, 308: 1172, 309: 2347, 310: 1201, 311: 1731, 312: 933, 313: 2023, 314: 1044, 315: 1876, 316: 1871, 317: 861, 318: 1604, 319: 1294, 320: 1942, 321: 847, 322: 2130, 323: 1293, 324: 1016, 325: 2143, 326: 1120, 327: 2530, 328: 1692, 329: 1980, 330: 2270, 331: 1279, 332: 2136, 333: 1733, 334: 1752, 335: 1406, 336: 852, 337: 1992, 338: 1500, 339: 1780, 340: 1065, 341: 705, 342: 796, 343: 1300, 344: 2061, 345: 1723, 346: 1490, 347: 1084, 348: 1113, 349: 735, 350: 825, 351: 1607, 352: 998, 353: 796, 354: 1020, 355: 1062, 356: 1345, 357: 661, 358: 660, 359: 1168, 360: 2567, 361: 1090, 362: 943, 363: 1068, 364: 1084, 365: 744, 366: 1488, 367: 1799, 368: 1495, 369: 1667, 370: 1502, 371: 2026, 372: 2519, 373: 1758, 374: 1280, 375: 1417, 376: 1624, 377: 2505, 378: 4017, 379: 2159, 380: 1811, 381: 3177, 382: 1401, 383: 1472, 384: 2824, 385: 3620, 386: 2914, 387: 3280, 388: 1346, 389: 1983, 390: 2816, 391: 1688, 392: 2623, 393: 1696, 394: 3269, 395: 2460, 396: 2750, 397: 3107, 398: 2704, 399: 4018, 400: 1267, 401: 3166, 402: 2545, 403: 2364, 404: 2543, 405: 2455, 406: 4592, 407: 3344, 408: 2117, 409: 1650, 410: 1485, 411: 1711, 412: 2032, 413: 4209, 414: 2958, 415: 1578, 416: 2336, 417: 2178, 418: 1538, 419: 1243, 420: 3055, 421: 1461, 422: 2204, 423: 1549, 424: 2165, 425: 2378, 426: 2302, 427: 4959, 428: 2098, 429: 3720, 430: 2600, 431: 1960, 432: 1809, 433: 2249, 434: 3443, 435: 4136, 436: 3995, 437: 3971, 438: 3638, 439: 3618, 440: 1965, 441: 4234, 442: 4466, 443: 1800, 444: 3112, 445: 3845, 446: 1829, 447: 2142, 448: 3678, 449: 2345, 450: 2341, 451: 2577, 452: 3043, 453: 2292, 454: 3665, 455: 2001, 456: 4137, 457: 2589, 458: 2891, 459: 4068, 460: 4476, 461: 1991, 462: 2503, 463: 4070, 464: 3028, 465: 2360, 466: 4522, 467: 3604, 468: 1828, 469: 5575, 470: 3126, 471: 2040, 472: 2423, 473: 2037, 474: 3521, 475: 2631, 476: 6056, 477: 3930, 478: 1976, 479: 4781, 480: 3594, 481: 3728, 482: 3081, 483: 3578, 484: 3661, 485: 5168, 486: 4970, 487: 5661, 488: 1909, 489: 3595, 490: 4857, 491: 4428, 492: 3438, 493: 5195, 494: 2705, 495: 5214, 496: 3698, 497: 4641, 498: 2668, 499: 5697, 500: 5343, 501: 3455, 502: 4285, 503: 3045, 504: 4246, 505: 7447, 506: 5278, 507: 5044, 508: 3152, 509: 4094, 510: 4439, 511: 6518, 512: 5619, 513: 5687, 514: 5881, 515: 6972, 516: 3180, 517: 2569, 518: 3769, 519: 6369, 520: 7647, 521: 6467, 522: 5384, 523: 5448, 524: 4072, 525: 5603, 526: 7134, 527: 5781, 528: 6482, 529: 3097, 530: 4521, 531: 5614, 532: 4019, 533: 5905, 534: 4993, 535: 6241, 536: 4025, 537: 4956, 538: 4568, 539: 7849, 540: 5183, 541: 7267, 542: 6525, 543: 8567, 544: 4406, 545: 7138, 546: 7716, 547: 7897, 548: 6124, 549: 9031, 550: 9882, 551: 8223, 552: 8084, 553: 7118, 554: 7512, 555: 7330, 556: 5230, 557: 9010, 558: 5061, 559: 3768, 560: 8035, 561: 9365, 562: 5510, 563: 9968, 564: 10214, 565: 5277, 566: 5582, 567: 7743, 568: 4839, 569: 6697, 570: 4830, 571: 5707, 572: 5337, 573: 4359, 574: 8244, 575: 6158, 576: 7791, 577: 4158, 578: 6553, 579: 5652, 580: 7704, 581: 7254, 582: 6902, 583: 10189, 584: 4496, 585: 9339, 586: 6260, 587: 5464, 588: 3512, 589: 5536, 590: 4418, 591: 3674, 592: 6667, 593: 6959, 594: 2898, 595: 2733, 596: 3395, 597: 3602, 598: 6680, 599: 5758, 600: 3332, 601: 3802, 602: 5524, 603: 2718, 604: 2893, 605: 4764, 606: 5732, 607: 3746, 608: 4310, 609: 3332, 610: 2367, 611: 4762, 612: 2391, 613: 4453, 614: 3727, 615: 3722, 616: 2707, 617: 5423, 618: 2059, 619: 3134, 620: 2983, 621: 1555, 622: 2544, 623: 4125, 624: 3496, 625: 1489, 626: 2426, 627: 1744, 628: 2015, 629: 1411, 630: 1741, 631: 4087, 632: 3784, 633: 2350, 634: 2032, 635: 2818, 636: 1310, 637: 2639, 638: 3260, 639: 1482, 640: 2637, 641: 2112, 642: 2423, 643: 1330, 644: 1664, 645: 1158, 646: 2284, 647: 2004, 648: 1416, 649: 2059, 650: 958, 651: 2055, 652: 1126, 653: 1728, 654: 2447, 655: 1261, 656: 1429, 657: 825, 658: 1774, 659: 2144, 660: 2406, 661: 1002, 662: 1903, 663: 2245, 664: 1738, 665: 1027, 666: 1468, 667: 1422, 668: 2128, 669: 2607, 670: 1631, 671: 1872, 672: 1650, 673: 1614, 674: 1769, 675: 913, 676: 1482, 677: 1450, 678: 1780, 679: 846, 680: 1144, 681: 1841, 682: 1115, 683: 1214, 684: 1195, 685: 1254, 686: 1346, 687: 2273, 688: 1235, 689: 854, 690: 1866, 691: 1026, 692: 1681, 693: 2853, 694: 2219, 695: 2283, 696: 1355, 697: 1512, 698: 1008, 699: 862, 700: 1383}} 可以进行预测，我唯一的问题是在10月至1月/ 2月左右的年末拥有预测帐户。

结果：

将结果导出到Tableau中，得到以下图：

如您所见，从八月到二月的这段时间似乎过高了预测。

代码：

fbprophet

关于我做错了什么以及如何调整模型以更准确地说明这些期间的任何想法？

Answer 1

由于您确实具有可乘的季节性，因此季节性的影响实际上会逐周期增加，如果您觉得预测过度，则可以减少季节性的傅立叶阶数。

https://facebook.github.io/prophet/docs/seasonality,_holiday_effects,_and_regressors.html#prior-scale-for-holidays-and-seasonality

检查此页面并降低傅立叶顺序，可能是因为它可以帮助您显示较小的值