Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) Plots

In [96]:
from verticapy.datasets import load_amazon
amazon = load_amazon()

amazon.acf(ts = "date", 
           column = "number", 
           p = 48,
           by = ["state"],
           unit = "month",
           method = "spearman")
Out[96]:
value
confidence
010.024396841824873748
10.865436803960170.03856205308291557
20.6419226395188780.04656468707262692
30.399389293501420.052519441106804815
40.1856557998465230.057377036550587374
50.04593831992307460.061640765754674524
6-0.00936843359205180.0655069183976806
70.01961680762547270.06894501806026314
80.1274682155781890.07161118776156336
90.2968285113930740.07416885585834694
100.4946634714209210.07659027318891991
110.6691836237218030.07887501028576362
120.7562407777512270.08070972531360529
130.7036564223473670.08246563028583806
140.5450777941470880.08399101248988675
150.3430925972778070.08547965236320183
160.1549755025880190.0868462967771087
170.02299789765094970.08794223779603168
18-0.04000857870921030.08899807709603456
19-0.0236632170873690.08984615265637208
200.06719192786413140.09063193558306873
210.2150560317811250.09126725326056165
220.3943265409909520.0918613330687679
230.5601743884140020.0924395780522622
240.652326944993960.09293318667622075
250.622365647619640.09323727861686824
260.4892417595855530.09351085391986542
270.309344145287620.09373816688889977
280.1308898017281710.09389849041590317
29-0.001318022324472980.09401990717406696
30-0.0699827488438810.09413611707174371
31-0.07002694235129020.09424661024229615
320.004700656819557680.09433115129623874
330.1339146158898730.09440975398732615
340.299992244046420.0944787937500136
350.4603782179492140.09451720691829557
360.5586703377890430.0945555772769078
370.5526916713993490.09459152125235575
380.4431660805403540.09461816517092184
390.2747133912120480.09464457943128332
400.1060217277695310.09466530944697167
41-0.02299823035817310.09468281718440483
42-0.09867643412226680.0946937428701469
43-0.1103174908213920.09470447438051062
44-0.0548538766306620.09471520792593062
450.05518489194382320.09472503189708015
460.2039932854459050.09473297816528793
470.354973986800270.09474051064208233
480.4588208532206820.09474791601815644
Rows: 1-49 | Columns: 3