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FinMind 是超過 50 種金融開源數據 50 datasets。 包含

台股股價 daily、台股5秒交易資料 ( 2019-05-29 ~ now, 共超過 3 千萬筆 )、財報、資產負債表、現金流量表、月營收、外資持股、股權分散表、融資融券、三大法人買賣，台股期貨、選擇權交易明細。

美股股價 daily、minute ( 2019-06-01 ~ now, 共超過 8 千萬筆 )，G7 匯率、利率、債券期貨。
原物料期貨價格( 肉、穀物、金屬、能源、軟商品 )，國際原油價格、黃金價格，美債殖利率。

資料每天更新。你不需收集資料，就可進行分析。

FinMind is open source of more than 50 datasets , contain

Taiwan stock trade data daily, Taiwan stock trade data (5 seconds) ( 2019-05-29 ~ now, total more than 30 million data ), Financial Statements, Balance Sheet, Cash Flows Statement, Month Revenue, Holding Shares Per, Institutional Investors Buy Sell. Taiwan Futures Trade Detail, Taiwan Option Trade Detail.

US stock price daily, minute ( 2019-06-01 ~ now, total more than 80 million data ), oil price, gold price, G7 exchange rate, interest rate, government bonds futures.
Raw Material Futures Prices ( meats, grains, energies, softs, metals ), US Government Bonds Yield.

The datasets are automatically updated daily. You can analyze financial data without having to collect the data by yourself.

 pip3 install FinMind

• Python document

  import requests
  url = 'http://finmindapi.servebeer.com/api/data'
  form_data = {'dataset':'TaiwanStockInfo'}
  res = requests.post(url,verify = True,data = form_data)
  
  url = 'http://finmindapi.servebeer.com/api/data'
  form_data = {'dataset':'TaiwanStockPrice','stock_id':'2317','date':'2019-06-01'}
  res = requests.post(url,verify = True,data = form_data)
  

• R document

  library(httr) 
  library(jsonlite)
  library('data.table')
  library(dplyr)
  
  url = 'http://finmindapi.servebeer.com/api/data'
  
  # TaiwanStockInfo
  payload<-list( 'dataset' = 'TaiwanStockInfo')
  
  response = POST(url,body = payload,encode="json")
  data = response %>% content 
  data = do.call('cbind',data$data) %>%data.table
  head(data)	
  

	import requests
	url = 'http://finmindapi.servebeer.com/api/translation'
	dataset = 'RawMaterialFuturesPrices'
	# or 
	# dataset = 'FinancialStatements'
	# dataset = 'BalanceSheet'
	# dataset = 'StockDividend'
	# dataset = 'TaiwanStockMarginPurchaseShortSale'
	# dataset = 'InstitutionalInvestorsBuySell'
	parameter = {'dataset':dataset}

	res = requests.post(url,verify = True,data = parameter)
	#res.text
	data = res.json()
	data = pd.DataFrame( data['data'] )

• FinMind.Data

• 50 data sets

• Variable Document

  from FinMind.Data import Load
  TaiwanStockInfo = Load.FinData(dataset = 'TaiwanStockInfo')
  	data = Load.FinData(dataset = 'TaiwanStockPrice',select = '2317',
  				date = '2018-10-10')
  

• FinMind.Mind
• GRU_LSTM_demo

• The full version of this documentation is at https://linsamtw.github.io/FinMindDoc/.
• median

HistoryUpdate

At least five kinds of visualization tools for every data type. ( In development )
https://finmind.servebeer.com/ 開發中

Solicit partners who are interested in joint development.
徵求有興趣共同開發的夥伴。
email : [email protected]