其他

在台灣股票新聞面，我們擁有 2 種資料集，如下:

相關新聞表 TaiwanStockNews¶

(由於資料量過大，單次請求只提供一天資料)

Example

Python

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockNews",
    "data_id":"2330",
    "start_date": "2020-04-01",
    "token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

R

library(httr)
library(data.table)
library(dplyr)

url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(url = url,
                    query = list(
                    dataset="TaiwanStockNews",
                    data_id="2330",
                    start_date= "2020-04-01",
                    token = "" # 參考登入，獲取金鑰
                    )
)
data = response %>% content
df = do.call('cbind',data$data) %>%data.table
head(df)

Output

DataFrame

date	stock_id	description	link	source	title
0	2020-04-01 00:00:00	2330	<a href="https://tw.news.yahoo.com/%E9%9B%B...	https://tw.news.yahoo.com/%E9%9B%BB%E5%AD%90%E...	Yahoo奇摩新聞
1	2020-04-01 00:57:33	2330	<a href="https://udn.com/news/story/6850/44...	https://udn.com/news/story/6850/4458587	udn 聯合新聞網
2	2020-04-01 00:58:42	2330	<a href="https://finance.technews.tw/2020/0...	https://finance.technews.tw/2020/04/01/tsmc-wa...	科技新報 TechNews
3	2020-04-01 00:59:38	2330	<a href="https://tw.news.yahoo.com/%E5%8F%B...	https://tw.news.yahoo.com/%E5%8F%B0%E7%A9%8D%E...	Yahoo奇摩股市
4	2020-04-01 02:40:00	2330	<a href="https://fnc.ebc.net.tw/FncNews/Con...	https://fnc.ebc.net.tw/FncNews/Content/117374	東森財經新聞

Schema

{
    date: str,
    stock_id: str,
    description: str,
    link: str,
    source: str,
    title: str
}

台灣每月景氣對策信號表 TaiwanBusinessIndicator (只限 backer、sponsor 會員使用)¶

資料區間：1982-01-01 ~ now

Example

Python

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanBusinessIndicator",
    "start_date": "2024-04-01",
    "end_date": "2025-01-01",
    "token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

R

library(httr)
library(data.table)
library(dplyr)

url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(url = url,
                    query = list(
                    dataset="TaiwanBusinessIndicator",
                    start_date= "2020-04-01",
                    "end_date": "2025-01-01",
                    token = "" # 參考登入，獲取金鑰
                    )
)
data = response %>% content
df = do.call('cbind',data$data) %>%data.table
head(df)

Output

DataFrame

	date	leading	leading_notrend	coincident	coincident_notrend	lagging	lagging_notrend	monitoring	monitoring_color
0	2024-01-01	92.32	99.85	90.8	98.21	91.82	99.31	27	G
1	2024-02-01	92.71	100.35	91.45	98.99	91.68	99.25	29	G
2	2024-03-01	93.19	100.95	92.28	99.97	91.6	99.23	31	G
3	2024-04-01	93.75	101.63	93.23	101.07	91.52	99.22	35	YR
4	2024-05-01	94.29	102.28	94.21	102.19	91.41	99.16	36	YR

Schema

{
    date: str,
    leading: float32,
    leading_notrend: float32,
    coincident: float32,
    coincident_notrend: float32,
    lagging: float32,
    lagging_notrend: float32,
    monitoring: float32,
    monitoring_color: str
}