Technical

In US stock data, we offer 2 datasets, as follows:

• US Stock Minute K Price Table USStockPriceMinute
• US Stock Price Table USStockPrice

In addition, the following list summarizes the available datasets:

• US Stock List USStockInfo

The usage of each dataset is explained one by one below. For the specific dataset schemas, please refer to finmindapi

US Stock List USStockInfo

• This dataset primarily lists the names, codes, and industry categories of all US listed and OTC stocks.

Example

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to the login page to obtain your API key
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "USStockInfo"
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

Output

DataFrameSchema

	date	stock_id	Country	IPOYear	MarketCap	Subsector	stock_name
0	2019-01-10	A	United States	1999	21610000000	Biotechnology:LaboratoryAnalyticalInstruments	Agilent Technologies, Inc.
1	2019-01-10	AA	n/a	2016	5270000000	Aluminum	Alcoa Corporation
2	2019-01-10	AABA	United States	0	36780000000	EDPServices	Altaba Inc.
3	2019-01-10	AAC	United States	2014	55360000	MedicalSpecialities	AAC Holdings, Inc.
4	2019-01-10	AAL	United States	0	14930000000	AirFreight/DeliveryServices	American Airlines Group, Inc.

{
    date: str,
    stock_id: str,
    Country: str,
    IPOYear: str,
    MarketCap: str,
    Subsector: str,
    stock_name: str
}

US Stock Minute K Price Table USStockPriceMinute (available only to backer, sponsor members)

• Data update time 08:00 daily. Actual update time is based on the API data.

Example

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to the login page to obtain your API key
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "USStockPriceMinute",
    "data_id": "^DJI",
    "start_date": "2022-06-16",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

Output

DataFrameSchema

	date	stock_id	close	high	low	open	volume
0	2022-06-16 13:31:00	^DJI	30082.5	30094.9	30076.6	30091.4	1686944
1	2022-06-16 13:32:00	^DJI	30075.6	30087.9	30069.2	30081.7	1939377
2	2022-06-16 13:33:00	^DJI	30039.5	30085.8	30036.4	30078.1	1589351
3	2022-06-16 13:34:00	^DJI	30001.6	30036.5	29995.9	30036.5	2127155
4	2022-06-16 13:35:00	^DJI	29996.7	30008	29984.3	30002.2	1917277

{
    date: str,
    stock_id: str,
    close: float64,
    high: float64,
    low: float64,
    open: float64,
    volume: int64
}

US Stock Price Table USStockPrice

• Data update time 08:00 daily. Actual update time is based on the API data.

Example

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to the login page to obtain your API key
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "USStockPrice",
    "data_id": "^DJI",
    "start_date": "2020-06-16",
    "end_date": "2021-06-16",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

Output

DataFrameSchema

	date	stock_id	Adj_Close	Close	High	Low	Open	Volume
0	2020-06-16	^DJI	26290	26290	26611	25811.7	26326.7	489500000
1	2020-06-17	^DJI	26119.6	26119.6	26400.1	26068.4	26330.5	328830000
2	2020-06-18	^DJI	26080.1	26080.1	26154.2	25848.5	26016.5	328390000
3	2020-06-19	^DJI	25871.5	25871.5	26451.4	25759.7	26213.1	669390000
4	2020-06-22	^DJI	26025	26025	26059.8	25667.7	25865.1	351780000

{
    date: str,
    stock_id: str,
    close: float64,
    high: float64,
    low: float64,
    open: float64,
    volume: int64
}