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DATE
stringdate 2025-08-19 19:15:00
2025-09-03 05:15:00
| open
float64 0.58
149
| high
float64 0.58
149
| low
float64 0.58
149
| close
float64 0.58
149
| tick_volume
int64 13
2.57k
| spread
int64 0
184
|
---|---|---|---|---|---|---|
2025-08-19 19:30:00
| 0.64574 | 0.64582 | 0.64554 | 0.64559 | 520 | 18 |
2025-08-19 19:45:00
| 0.64559 | 0.6458 | 0.64549 | 0.64559 | 454 | 18 |
2025-08-19 20:00:00
| 0.64559 | 0.64566 | 0.64546 | 0.64555 | 477 | 18 |
2025-08-19 20:15:00
| 0.64555 | 0.64562 | 0.64544 | 0.64556 | 421 | 18 |
2025-08-19 20:30:00
| 0.64555 | 0.64591 | 0.64554 | 0.6458 | 400 | 18 |
2025-08-19 20:45:00
| 0.6458 | 0.64581 | 0.64564 | 0.64574 | 391 | 18 |
2025-08-19 21:00:00
| 0.64573 | 0.64573 | 0.64529 | 0.64529 | 437 | 18 |
2025-08-19 21:15:00
| 0.64529 | 0.64533 | 0.64521 | 0.64527 | 380 | 18 |
2025-08-19 21:30:00
| 0.64526 | 0.64534 | 0.64495 | 0.64496 | 358 | 18 |
2025-08-19 21:45:00
| 0.64495 | 0.6452 | 0.64492 | 0.64511 | 522 | 18 |
2025-08-19 22:00:00
| 0.64511 | 0.64513 | 0.64489 | 0.64501 | 451 | 18 |
2025-08-19 22:15:00
| 0.64501 | 0.64532 | 0.645 | 0.64531 | 392 | 18 |
2025-08-19 22:30:00
| 0.64532 | 0.64535 | 0.64512 | 0.64516 | 312 | 18 |
2025-08-19 22:45:00
| 0.64516 | 0.64524 | 0.64506 | 0.64522 | 309 | 18 |
2025-08-19 23:00:00
| 0.64523 | 0.64528 | 0.64517 | 0.64522 | 339 | 18 |
2025-08-19 23:15:00
| 0.64522 | 0.64535 | 0.64522 | 0.64532 | 193 | 18 |
2025-08-19 23:30:00
| 0.64532 | 0.64535 | 0.64525 | 0.64526 | 251 | 18 |
2025-08-19 23:45:00
| 0.64525 | 0.64532 | 0.64513 | 0.64531 | 240 | 18 |
2025-08-20 00:00:00
| 0.6448 | 0.64552 | 0.6448 | 0.64521 | 50 | 76 |
2025-08-20 00:15:00
| 0.64521 | 0.64538 | 0.6452 | 0.64537 | 122 | 51 |
2025-08-20 00:30:00
| 0.64537 | 0.64537 | 0.64523 | 0.64524 | 97 | 42 |
2025-08-20 00:45:00
| 0.64523 | 0.64534 | 0.6452 | 0.64524 | 95 | 33 |
2025-08-20 01:00:00
| 0.6453 | 0.64543 | 0.64516 | 0.64543 | 170 | 18 |
2025-08-20 01:15:00
| 0.64543 | 0.64543 | 0.64534 | 0.64536 | 88 | 18 |
2025-08-20 01:30:00
| 0.64536 | 0.64543 | 0.64534 | 0.64537 | 159 | 18 |
2025-08-20 01:45:00
| 0.64537 | 0.64547 | 0.64536 | 0.64537 | 152 | 18 |
2025-08-20 02:00:00
| 0.64537 | 0.64538 | 0.6452 | 0.64523 | 192 | 18 |
2025-08-20 02:15:00
| 0.64523 | 0.64524 | 0.64496 | 0.64512 | 138 | 18 |
2025-08-20 02:30:00
| 0.64512 | 0.64533 | 0.64502 | 0.64532 | 176 | 18 |
2025-08-20 02:45:00
| 0.64532 | 0.64539 | 0.64519 | 0.64527 | 305 | 18 |
2025-08-20 03:00:00
| 0.64527 | 0.64543 | 0.64473 | 0.64481 | 604 | 18 |
2025-08-20 03:15:00
| 0.6448 | 0.64505 | 0.64449 | 0.64482 | 387 | 18 |
2025-08-20 03:30:00
| 0.64482 | 0.64496 | 0.64473 | 0.64482 | 335 | 18 |
2025-08-20 03:45:00
| 0.64482 | 0.64515 | 0.6448 | 0.64503 | 508 | 18 |
2025-08-20 04:00:00
| 0.64503 | 0.64537 | 0.64494 | 0.64503 | 486 | 18 |
2025-08-20 04:15:00
| 0.64503 | 0.6451 | 0.64433 | 0.64439 | 432 | 18 |
2025-08-20 04:30:00
| 0.64439 | 0.64483 | 0.64427 | 0.64479 | 501 | 18 |
2025-08-20 04:45:00
| 0.6448 | 0.64483 | 0.64459 | 0.64471 | 471 | 18 |
2025-08-20 05:00:00
| 0.64471 | 0.64473 | 0.64336 | 0.64356 | 1,210 | 18 |
2025-08-20 05:15:00
| 0.64356 | 0.64359 | 0.64307 | 0.64334 | 708 | 18 |
2025-08-20 05:30:00
| 0.64334 | 0.64388 | 0.64304 | 0.64309 | 581 | 18 |
2025-08-20 05:45:00
| 0.64309 | 0.64366 | 0.64283 | 0.64344 | 571 | 18 |
2025-08-20 06:00:00
| 0.64343 | 0.6441 | 0.64341 | 0.64359 | 754 | 18 |
2025-08-20 06:15:00
| 0.64356 | 0.64402 | 0.64353 | 0.64377 | 466 | 18 |
2025-08-20 06:30:00
| 0.64378 | 0.64407 | 0.64356 | 0.64378 | 432 | 18 |
2025-08-20 06:45:00
| 0.64378 | 0.64381 | 0.64315 | 0.64321 | 458 | 18 |
2025-08-20 07:00:00
| 0.6432 | 0.64375 | 0.64318 | 0.64368 | 323 | 18 |
2025-08-20 07:15:00
| 0.64368 | 0.6441 | 0.64358 | 0.64405 | 333 | 18 |
2025-08-20 07:30:00
| 0.64405 | 0.64429 | 0.64396 | 0.64419 | 280 | 18 |
2025-08-20 07:45:00
| 0.64419 | 0.64443 | 0.6441 | 0.64429 | 317 | 18 |
2025-08-20 08:00:00
| 0.6443 | 0.64432 | 0.64399 | 0.64416 | 340 | 18 |
2025-08-20 08:15:00
| 0.64415 | 0.64446 | 0.64406 | 0.64445 | 290 | 18 |
2025-08-20 08:30:00
| 0.64445 | 0.6447 | 0.64433 | 0.64435 | 347 | 18 |
2025-08-20 08:45:00
| 0.64436 | 0.64478 | 0.64423 | 0.64476 | 348 | 18 |
2025-08-20 09:00:00
| 0.64474 | 0.64484 | 0.64378 | 0.64406 | 830 | 18 |
2025-08-20 09:15:00
| 0.64405 | 0.64443 | 0.64366 | 0.64394 | 698 | 18 |
2025-08-20 09:30:00
| 0.64393 | 0.64455 | 0.64393 | 0.64449 | 568 | 18 |
2025-08-20 09:45:00
| 0.64449 | 0.64458 | 0.64417 | 0.64423 | 480 | 18 |
2025-08-20 10:00:00
| 0.64422 | 0.64458 | 0.64422 | 0.64432 | 668 | 18 |
2025-08-20 10:15:00
| 0.64432 | 0.64434 | 0.64405 | 0.64428 | 472 | 18 |
2025-08-20 10:30:00
| 0.64428 | 0.64428 | 0.64375 | 0.64391 | 470 | 18 |
2025-08-20 10:45:00
| 0.64391 | 0.64408 | 0.64347 | 0.64406 | 525 | 18 |
2025-08-20 11:00:00
| 0.64406 | 0.64412 | 0.643 | 0.64303 | 528 | 18 |
2025-08-20 11:15:00
| 0.64303 | 0.64333 | 0.64262 | 0.64262 | 489 | 18 |
2025-08-20 11:30:00
| 0.64261 | 0.64338 | 0.64248 | 0.64314 | 499 | 18 |
2025-08-20 11:45:00
| 0.64313 | 0.64344 | 0.64306 | 0.6433 | 309 | 18 |
2025-08-20 12:00:00
| 0.6433 | 0.64362 | 0.64326 | 0.6435 | 442 | 18 |
2025-08-20 12:15:00
| 0.64347 | 0.64357 | 0.64309 | 0.64326 | 355 | 18 |
2025-08-20 12:30:00
| 0.64326 | 0.64355 | 0.64315 | 0.64348 | 363 | 18 |
2025-08-20 12:45:00
| 0.64348 | 0.64359 | 0.64339 | 0.64358 | 388 | 18 |
2025-08-20 13:00:00
| 0.64358 | 0.64366 | 0.64326 | 0.64361 | 332 | 18 |
2025-08-20 13:15:00
| 0.64361 | 0.64362 | 0.64325 | 0.64347 | 405 | 18 |
2025-08-20 13:30:00
| 0.64347 | 0.64353 | 0.64324 | 0.64333 | 335 | 18 |
2025-08-20 13:45:00
| 0.64333 | 0.64351 | 0.64315 | 0.64334 | 306 | 18 |
2025-08-20 14:00:00
| 0.64334 | 0.64353 | 0.64325 | 0.64342 | 294 | 18 |
2025-08-20 14:15:00
| 0.64342 | 0.64359 | 0.64329 | 0.64336 | 273 | 18 |
2025-08-20 14:30:00
| 0.64336 | 0.64346 | 0.64308 | 0.64309 | 291 | 18 |
2025-08-20 14:45:00
| 0.64309 | 0.64332 | 0.643 | 0.64302 | 426 | 18 |
2025-08-20 15:00:00
| 0.64302 | 0.64385 | 0.64302 | 0.64384 | 488 | 18 |
2025-08-20 15:15:00
| 0.64383 | 0.64425 | 0.64377 | 0.64421 | 427 | 18 |
2025-08-20 15:30:00
| 0.64421 | 0.64476 | 0.64408 | 0.64452 | 711 | 4 |
2025-08-20 15:45:00
| 0.64452 | 0.64453 | 0.64411 | 0.64428 | 562 | 18 |
2025-08-20 16:00:00
| 0.64428 | 0.64436 | 0.6439 | 0.64398 | 523 | 18 |
2025-08-20 16:15:00
| 0.64399 | 0.64416 | 0.64384 | 0.64401 | 404 | 18 |
2025-08-20 16:30:00
| 0.64402 | 0.64432 | 0.64383 | 0.64432 | 691 | 18 |
2025-08-20 16:45:00
| 0.64432 | 0.64432 | 0.64263 | 0.64274 | 1,020 | 18 |
2025-08-20 17:00:00
| 0.64275 | 0.64322 | 0.64253 | 0.64254 | 917 | 18 |
2025-08-20 17:15:00
| 0.64254 | 0.64297 | 0.64233 | 0.64238 | 817 | 18 |
2025-08-20 17:30:00
| 0.64239 | 0.64271 | 0.64228 | 0.64251 | 702 | 18 |
2025-08-20 17:45:00
| 0.64252 | 0.64304 | 0.64234 | 0.64293 | 953 | 18 |
2025-08-20 18:00:00
| 0.64293 | 0.6434 | 0.64284 | 0.64317 | 645 | 18 |
2025-08-20 18:15:00
| 0.6432 | 0.64383 | 0.64315 | 0.64383 | 611 | 18 |
2025-08-20 18:30:00
| 0.64383 | 0.64384 | 0.64329 | 0.64332 | 560 | 18 |
2025-08-20 18:45:00
| 0.64332 | 0.64338 | 0.64257 | 0.64263 | 655 | 18 |
2025-08-20 19:00:00
| 0.64263 | 0.64321 | 0.64263 | 0.64316 | 532 | 18 |
2025-08-20 19:15:00
| 0.64315 | 0.64354 | 0.64315 | 0.64335 | 482 | 18 |
2025-08-20 19:30:00
| 0.64335 | 0.64347 | 0.64326 | 0.64339 | 425 | 18 |
2025-08-20 19:45:00
| 0.64339 | 0.64349 | 0.64325 | 0.64341 | 426 | 18 |
2025-08-20 20:00:00
| 0.6434 | 0.64367 | 0.64336 | 0.64349 | 465 | 18 |
2025-08-20 20:15:00
| 0.64349 | 0.64368 | 0.64338 | 0.64353 | 483 | 18 |
End of preview. Expand
in Data Studio
FOREX Algotrading M15 1000 Columns
Descrição
Este dataset contém dados históricos de Forex em intervalos de 15 minutos (M15), incluindo múltiplos pares de moedas. É voltado para análise de séries temporais e desenvolvimento de algoritmos de trading automatizados. Cada arquivo CSV contém 1000 colunas com dados de mercado, como preços de abertura, fechamento, máxima e mínima, volume e spread.
Estrutura do dataset
Cada arquivo CSV possui as seguintes colunas:
Coluna | Descrição |
---|---|
DATE | Data e hora do registro (timestamp) |
open | Preço de abertura |
high | Preço máximo |
low | Preço mínimo |
close | Preço de fechamento |
tick_volume | Volume de ticks |
spread | Diferença entre compra e venda |
Observação: para análise e modelagem, você pode descartar a coluna
DATE
se quiser apenas os valores numéricos.
Licença
Este dataset está disponível sob a licença CC BY 4.0, permitindo uso, compartilhamento e adaptação com atribuição ao autor.
Exemplo de uso em Python
Você pode carregar o dataset usando o pacote datasets
do Hugging Face:
from datasets import load_dataset
import pandas as pd
# Carregar o dataset do Hugging Face Hub
dataset = load_dataset("lukealvess/FOREX_ALGOTRADING_M15_1000_COLUMNS")
# Converter para pandas DataFrame
df = pd.DataFrame(dataset['train'])
print(df.head())
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