Pricing

Pay per event

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Time Series Forecasting (Chronos-2): Sales, Demand, Traffic

Try for free

Forecast sales, demand, traffic, prices or any time series with Amazon's Chronos-2 model: prediction intervals, backtest accuracy, seasonality, a plain-language summary and a chart per series. From values, CSV, Excel, Google Sheets or an Apify dataset. For AI agents.

Pricing

Pay per event

Rating

0.0

(0)

Developer

Jumble Mog

Actor stats

Bookmarked

Total users

Monthly active users

2 days ago

Last modified

Categories

E-commerce

Developer tools

You can access the Time Series Forecasting (Chronos-2): Sales, Demand, Traffic programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = { "data": [
9        {
10            "month": "2021-09",
11            "co2_ppm": 413.26,
12        },
13        {
14            "month": "2021-10",
15            "co2_ppm": 413.9,
16        },
17        {
18            "month": "2021-11",
19            "co2_ppm": 414.97,
20        },
21        {
22            "month": "2021-12",
23            "co2_ppm": 416.67,
24        },
25        {
26            "month": "2022-01",
27            "co2_ppm": 418.13,
28        },
29        {
30            "month": "2022-02",
31            "co2_ppm": 419.24,
32        },
33        {
34            "month": "2022-03",
35            "co2_ppm": 418.76,
36        },
37        {
38            "month": "2022-04",
39            "co2_ppm": 420.19,
40        },
41        {
42            "month": "2022-05",
43            "co2_ppm": 420.97,
44        },
45        {
46            "month": "2022-06",
47            "co2_ppm": 420.94,
48        },
49        {
50            "month": "2022-07",
51            "co2_ppm": 418.85,
52        },
53        {
54            "month": "2022-08",
55            "co2_ppm": 417.15,
56        },
57        {
58            "month": "2022-09",
59            "co2_ppm": 415.91,
60        },
61        {
62            "month": "2022-10",
63            "co2_ppm": 415.74,
64        },
65        {
66            "month": "2022-11",
67            "co2_ppm": 417.47,
68        },
69        {
70            "month": "2022-12",
71            "co2_ppm": 418.99,
72        },
73        {
74            "month": "2023-01",
75            "co2_ppm": 419.48,
76        },
77        {
78            "month": "2023-02",
79            "co2_ppm": 420.31,
80        },
81        {
82            "month": "2023-03",
83            "co2_ppm": 420.99,
84        },
85        {
86            "month": "2023-04",
87            "co2_ppm": 423.35,
88        },
89        {
90            "month": "2023-05",
91            "co2_ppm": 424,
92        },
93        {
94            "month": "2023-06",
95            "co2_ppm": 423.68,
96        },
97        {
98            "month": "2023-07",
99            "co2_ppm": 421.83,
100        },
101        {
102            "month": "2023-08",
103            "co2_ppm": 419.68,
104        },
105        {
106            "month": "2023-09",
107            "co2_ppm": 418.5,
108        },
109        {
110            "month": "2023-10",
111            "co2_ppm": 418.82,
112        },
113        {
114            "month": "2023-11",
115            "co2_ppm": 420.46,
116        },
117        {
118            "month": "2023-12",
119            "co2_ppm": 421.86,
120        },
121        {
122            "month": "2024-01",
123            "co2_ppm": 422.8,
124        },
125        {
126            "month": "2024-02",
127            "co2_ppm": 424.55,
128        },
129        {
130            "month": "2024-03",
131            "co2_ppm": 425.38,
132        },
133        {
134            "month": "2024-04",
135            "co2_ppm": 426.51,
136        },
137        {
138            "month": "2024-05",
139            "co2_ppm": 426.9,
140        },
141        {
142            "month": "2024-06",
143            "co2_ppm": 426.91,
144        },
145        {
146            "month": "2024-07",
147            "co2_ppm": 425.55,
148        },
149        {
150            "month": "2024-08",
151            "co2_ppm": 422.99,
152        },
153        {
154            "month": "2024-09",
155            "co2_ppm": 422.03,
156        },
157        {
158            "month": "2024-10",
159            "co2_ppm": 422.38,
160        },
161        {
162            "month": "2024-11",
163            "co2_ppm": 423.85,
164        },
165        {
166            "month": "2024-12",
167            "co2_ppm": 425.4,
168        },
169        {
170            "month": "2025-01",
171            "co2_ppm": 426.65,
172        },
173        {
174            "month": "2025-02",
175            "co2_ppm": 427.09,
176        },
177        {
178            "month": "2025-03",
179            "co2_ppm": 428.15,
180        },
181        {
182            "month": "2025-04",
183            "co2_ppm": 429.64,
184        },
185        {
186            "month": "2025-05",
187            "co2_ppm": 430.51,
188        },
189        {
190            "month": "2025-06",
191            "co2_ppm": 429.61,
192        },
193        {
194            "month": "2025-07",
195            "co2_ppm": 427.87,
196        },
197        {
198            "month": "2025-08",
199            "co2_ppm": 425.48,
200        },
201        {
202            "month": "2025-09",
203            "co2_ppm": 424.37,
204        },
205        {
206            "month": "2025-10",
207            "co2_ppm": 424.87,
208        },
209        {
210            "month": "2025-11",
211            "co2_ppm": 426.46,
212        },
213        {
214            "month": "2025-12",
215            "co2_ppm": 427.49,
216        },
217        {
218            "month": "2026-01",
219            "co2_ppm": 428.62,
220        },
221        {
222            "month": "2026-02",
223            "co2_ppm": 429.35,
224        },
225        {
226            "month": "2026-03",
227            "co2_ppm": 430.15,
228        },
229        {
230            "month": "2026-04",
231            "co2_ppm": 431.12,
232        },
233        {
234            "month": "2026-05",
235            "co2_ppm": 432.34,
236        },
237        {
238            "month": "2026-06",
239            "co2_ppm": 431.43,
240        },
241        {
242            "month": "2026-07",
243            "co2_ppm": 429.13,
244        },
245        {
246            "month": "2026-08",
247            "co2_ppm": 427.55,
248        },
249    ] }
250
251# Run the Actor and wait for it to finish
252run = client.actor("jumblemog/time-series-forecasting").call(run_input=run_input)
253
254# Fetch and print Actor results from the run's dataset (if there are any)
255print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
256for item in client.dataset(run.default_dataset_id).iterate_items():
257    print(item)
258
259# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Time Series Forecasting API: Sales & Demand with Chronos-2 API in Python

The Apify API client for Python is the official library that allows you to use Time Series Forecasting (Chronos-2): Sales, Demand, Traffic API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Time Series Forecasting (Chronos-2): Sales, Demand, Traffic API in JavaScript

Time Series Forecasting (Chronos-2): Sales, Demand, Traffic API through CLI

Time Series Forecasting (Chronos-2): Sales, Demand, Traffic OpenAPI definition

Time Series Forecasting (Chronos-2): Sales, Demand, Traffic API

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