籌碼面

在台股籌碼面，我們擁有 13 種資料集，如下:

• 個股融資融劵表 TaiwanStockMarginPurchaseShortSale
• 整體市場融資融劵表 TaiwanStockTotalMarginPurchaseShortSale
• 個股三大法人買賣表 TaiwanStockInstitutionalInvestorsBuySell
• 整體市場三大法人買賣表 TaiwanStockTotalInstitutionalInvestors
• 外資持股表 TaiwanStockShareholding
• 股權持股分級表 TaiwanStockHoldingSharesPer
• 借券成交明細 TaiwanStockSecuritiesLending
• 暫停融券賣出表(融券回補日) TaiwanStockMarginShortSaleSuspension
• 信用額度總量管制餘額表 TaiwanDailyShortSaleBalances
• 證券商資訊表 TaiwanSecuritiesTraderInfo
• 台股分點資料表(query by 股票代碼) TaiwanStockTradingDailyReport
• 台股分點資料表(query by 券商代碼) TaiwanStockTradingDailyReport
• 台股權證分點資料表(query by 股票代碼) TaiwanStockWarrantTradingDailyReport
• 台股權證分點資料表(query by 券商代碼) TaiwanStockWarrantTradingDailyReport
• 台股八大行庫賣賣表 TaiwanstockGovernmentBankBuySell

---

融資融劵表 TaiwanStockMarginPurchaseShortSale

• 資料區間：2001-01-01 ~ now
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_margin_purchase_short_sale(
    stock_id="2330",
    start_date='2020-04-02',
    end_date='2020-04-12'
)

Python

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockMarginPurchaseShortSale",
    "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'])

R

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
    dataset="TaiwanStockMarginPurchaseShortSale",
    data_id= "2330",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table

Output

DataFrame

	date	stock_id	MarginPurchaseBuy	MarginPurchaseCashRepayment	MarginPurchaseLimit	MarginPurchaseSell	MarginPurchaseTodayBalance	MarginPurchaseYesterdayBalance	Note	OffsetLoanAndShort	ShortSaleBuy	ShortSaleCashRepayment	ShortSaleLimit	ShortSaleSell	ShortSaleTodayBalance	ShortSaleYesterdayBalance
0	2020-04-06	2330	1914	8	6482595	1269	26285	25648	X	0	0	24	6482595	0	0	24
1	2020-04-07	2330	1049	13	6482595	2655	24666	26285	X	0	0	0	6482595	0	0	0
2	2020-04-08	2330	1192	3	6482595	1569	24286	24666		0	0	0	6482595	0	0	0
3	2020-04-09	2330	499	28	6482595	1362	23395	24286		209	0	0	6482595	398	398	0
4	2020-04-10	2330	1227	24	6482595	794	23804	23395		53	156	0	6482595	156	398	398

Schema

{
    date: str,
    stock_id: str,
    MarginPurchaseBuy: int64,
    MarginPurchaseCashRepayment: int64,
    MarginPurchaseLimit: int64,
    MarginPurchaseSell: int64,
    MarginPurchaseTodayBalance: int64,
    MarginPurchaseYesterdayBalance: int64,
    Note: str,
    OffsetLoanAndShort: int64,
    ShortSaleBuy: int64,
    ShortSaleCashRepayment: int64,
    ShortSaleLimit: int64,
    ShortSaleSell: int64,
    ShortSaleTodayBalance: int64,
    ShortSaleYesterdayBalance: int64
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_margin_purchase_short_sale(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockMarginPurchaseShortSale",
    "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="TaiwanStockMarginPurchaseShortSale",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	MarginPurchaseBuy	MarginPurchaseCashRepayment	MarginPurchaseLimit	MarginPurchaseSell	MarginPurchaseTodayBalance	MarginPurchaseYesterdayBalance	Note	OffsetLoanAndShort	ShortSaleBuy	ShortSaleCashRepayment	ShortSaleLimit	ShortSaleSell	ShortSaleTodayBalance	ShortSaleYesterdayBalance
0	2020-04-01	0050	193	15	263750	163	3189	3174		0	65	1	263750	13	2283	2336
1	2020-04-01	0051	0	0	2375	0	5	5		0	0	0	2375	0	0	0
2	2020-04-01	0052	0	0	7500	0	128	128		0	0	0	7500	0	0	0
3	2020-04-01	0053	0	0	1622	0	1	1		0	0	0	1622	0	0	0
4	2020-04-01	0054	0	0	2531	0	0	0	X	0	0	0	2531	0	0	0

Schema

{
    date: str,
    stock_id: str,
    MarginPurchaseBuy: int64,
    MarginPurchaseCashRepayment: int64,
    MarginPurchaseLimit: int64,
    MarginPurchaseSell: int64,
    MarginPurchaseTodayBalance: int64,
    MarginPurchaseYesterdayBalance: int64,
    Note: str,
    OffsetLoanAndShort: int64,
    ShortSaleBuy: int64,
    ShortSaleCashRepayment: int64,
    ShortSaleLimit: int64,
    ShortSaleSell: int64,
    ShortSaleTodayBalance: int64,
    ShortSaleYesterdayBalance: int64
}

---

台灣市場整體融資融劵表 TaiwanStockTotalMarginPurchaseShortSale

• 資料區間：2001-01-01 ~ now
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_margin_purchase_short_sale_total(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockTotalMarginPurchaseShortSale",
    "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="TaiwanStockTotalMarginPurchaseShortSale",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	TodayBalance	YesBalance	buy	date	name	Return	sell
0	5463820	5471770	236127	2020-04-01	MarginPurchase	10986	233091
1	91965082000	91898116000	4046643000	2020-04-01	MarginPurchaseMoney	196619000	3783058000
2	541704	556742	57266	2020-04-01	ShortSale	6151	48379
3	535401	541704	50779	2020-04-06	ShortSale	3700	48176
4	93198509000	91965082000	6440842000	2020-04-06	MarginPurchaseMoney	71638000	5135777000

Schema

{
    TodayBalance: int64,
    YesBalance: int64,
    buy: int64,
    date: str,
    name: str,
    Return: int64,
    sell: int64
}

---

法人買賣表 TaiwanStockInstitutionalInvestorsBuySell

• 資料區間：2005-01-01 ~ now
• 資料更新時間 星期一至五 20:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_institutional_investors(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockInstitutionalInvestorsBuySell",
    "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="TaiwanStockInstitutionalInvestorsBuySell",
    data_id= "2330",
    start_date= "2020-04-01",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	buy	name	sell
0	2020-04-01	2330	31304729	Foreign_Investor	29057663
1	2020-04-01	2330	0	Foreign_Dealer_Self	0
2	2020-04-01	2330	900000	Investment_Trust	239000
3	2020-04-01	2330	79000	Dealer_self	807000
4	2020-04-01	2330	189000	Dealer_Hedging	493500

Schema

{
    date: str,
    stock_id: str,
    buy: int64,
    name: str,
    sell: int64
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_institutional_investors(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockInstitutionalInvestorsBuySell",
    "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)

R

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
    dataset="TaiwanStockInstitutionalInvestorsBuySell",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	buy	name	sell
0	2020-04-01	0050	458249	Foreign_Investor	4492000
1	2020-04-01	0050	0	Foreign_Dealer_Self	0
2	2020-04-01	0050	54000	Investment_Trust	0
3	2020-04-01	0050	0	Dealer_self	0
4	2020-04-01	0050	2050000	Dealer_Hedging	905000

Schema

{
    date: str,
    stock_id: str,
    buy: int64,
    name: str,
    sell: int64
}

---

台灣市場整體法人買賣表 TaiwanStockTotalInstitutionalInvestors

• 資料區間：2004-04-01 ~ now
• 資料更新時間 星期一至五 15:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_institutional_investors_total(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockTotalInstitutionalInvestors",
    "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="TaiwanStockTotalInstitutionalInvestors",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	buy	date	name	sell
0	123150	2020-04-01	Foreign_Dealer_Self	266220
1	3681729831	2020-04-01	Dealer_Hedging	5539788946
2	33759089839	2020-04-01	Foreign_Investor	38466572585
3	3039112340	2020-04-01	Investment_Trust	853138940
4	789316840	2020-04-01	Dealer_self	912143500

Schema

{
    buy: int64,
    date: str,
    name: str,
    sell: int64
}

---

外資持股表 TaiwanStockShareholding

• 資料區間：2004-02-01 ~ now
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_shareholding(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockShareholding",
    "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="TaiwanStockShareholding",
    data_id= "2330",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	stock_name	InternationalCode	ForeignInvestmentRemainingShares	ForeignInvestmentShares	ForeignInvestmentRemainRatio	ForeignInvestmentSharesRatio	ForeignInvestmentUpperLimitRatio	ChineseInvestmentUpperLimitRatio	NumberOfSharesIssued	RecentlyDeclareDate	note
0	2020-04-01	2330	台積電	TW0002330008	6309042842	19621337616	24.33	75.66	100	100	25930380458	2019-05-27
1	2020-04-06	2330	台積電	TW0002330008	6304552683	19625827775	24.31	75.68	100	100	25930380458	2019-05-27
2	2020-04-07	2330	台積電	TW0002330008	6283562246	19646818212	24.23	75.76	100	100	25930380458	2019-05-27
3	2020-04-08	2330	台積電	TW0002330008	6273338931	19657041527	24.19	75.8	100	100	25930380458	2019-05-27
4	2020-04-09	2330	台積電	TW0002330008	6267988722	19662391736	24.17	75.82	100	100	25930380458	2019-05-27

Schema

{
    date: str,
    stock_id: str,
    stock_name: str,
    InternationalCode: str,
    ForeignInvestmentRemainingShares: int64,
    ForeignInvestmentShares: int64,
    ForeignInvestmentRemainRatio: float64,
    ForeignInvestmentSharesRatio: float64,
    ForeignInvestmentUpperLimitRatio: float64,
    ChineseInvestmentUpperLimitRatio: float64,
    NumberOfSharesIssued: int64,
    RecentlyDeclareDate: str,
    note: str
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_shareholding(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockShareholding",
    "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="TaiwanStockShareholding",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	stock_name	InternationalCode	ForeignInvestmentRemainingShares	ForeignInvestmentShares	ForeignInvestmentRemainRatio	ForeignInvestmentSharesRatio	ForeignInvestmentUpperLimitRatio	ChineseInvestmentUpperLimitRatio	NumberOfSharesIssued	RecentlyDeclareDate	note
0	2020-04-01	0050	元大台灣50	TW0000050004	960256795	94743205	91.01	8.98	100	100	1055000000	2019-07-18
1	2020-04-01	0051	元大中型100	TW0000051002	9471000	29000	99.69	0.3	100	100	9500000	2019-07-18
2	2020-04-01	0052	富邦科技	TW0000052000	29957000	43000	99.85	0.14	100	100	30000000	2019-07-18
3	2020-04-01	0053	元大電子	TW0000053008	6466950	21050	99.67	0.32	100	100	6488000	2019-07-18
4	2020-04-01	0054	元大台商50	TW0000054006	9955000	169000	98.33	1.66	100	100	10124000	2019-07-18

Schema

{
    date: str,
    stock_id: str,
    stock_name: str,
    InternationalCode: str,
    ForeignInvestmentRemainingShares: int64,
    ForeignInvestmentShares: int64,
    ForeignInvestmentRemainRatio: float64,
    ForeignInvestmentSharesRatio: float64,
    ForeignInvestmentUpperLimitRatio: float64,
    ChineseInvestmentUpperLimitRatio: float64,
    NumberOfSharesIssued: int64,
    RecentlyDeclareDate: str,
    note: str
}

---

股東持股分級表 TaiwanStockHoldingSharesPer

• 資料區間：2001-01-01 ~ now

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_holding_shares_per(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockHoldingSharesPer",
    "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="TaiwanStockHoldingSharesPer",
    data_id= "2330",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	HoldingSharesLevel	people	percent	unit
0	2020-04-01	2330	1-999	165122	0.12	33289900
1	2020-04-01	2330	1,000-5,000	227692	1.69	440404454
2	2020-04-01	2330	10,001-15,000	10408	0.49	128127693
3	2020-04-01	2330	100,001-200,000	1628	0.86	225202876
4	2020-04-01	2330	15,001-20,000	5068	0.34	89929303

Schema

{
    date: str,
    stock_id: str,
    HoldingSharesLevel: str,
    people: int64,
    percent: float64,
    unit: int64
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_holding_shares_per(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockHoldingSharesPer",
    "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)

R

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

Output

DataFrame

	date	stock_id	HoldingSharesLevel	people	percent	unit
0	2020-04-01	0050	1-999	44173	1.02	10834763
1	2020-04-01	0050	1,000-5,000	96465	17.7	186791648
2	2020-04-01	0050	5,001-10,000	10364	7.57	79902735
3	2020-04-01	0050	10,001-15,000	2819	3.41	36075583
4	2020-04-01	0050	15,001-20,000	1557	2.69	28426726

Schema

{
    date: str,
    stock_id: str,
    HoldingSharesLevel: str,
    people: int64,
    percent: float64,
    unit: int64
}

---

借券成交明細 TaiwanStockSecuritiesLending

• 資料區間：2001-05-01 ~ now
• 資料更新時間 星期一至五 15:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_securities_lending(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockSecuritiesLending",
    "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="TaiwanStockSecuritiesLending",
    data_id="2330",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	transaction_type	volume	fee_rate	close	original_return_date	original_lending_period
0	2020-04-01	2330	議借	1330	1.36	271.5	2020-09-30	182
1	2020-04-01	2330	議借	800	0.41	271.5	2020-09-30	182
2	2020-04-01	2330	議借	850	0.41	271.5	2020-09-30	182
3	2020-04-01	2330	議借	500	0.5	271.5	2020-09-30	182
4	2020-04-01	2330	議借	160	0.36	271.5	2020-09-30	182

Schema

{
    date: str,
    stock_id: str,
    transaction_type: str,
    volume: int64,
    fee_rate: float64,
    close: float64,
    original_return_date: str,
    original_lending_period: int64
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_securities_lending(
    start_date='2020-04-01',
)

Python

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockSecuritiesLending",
    "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)

R

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
    dataset="TaiwanStockSecuritiesLending",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	transaction_type	volume	fee_rate	close	original_return_date	original_lending_period
0	2020-04-01	1101	議借	760	0.25	39	2020-09-30	182
1	2020-04-01	1101	議借	397	0.25	39	2020-09-30	182
2	2020-04-01	1101	競價	436	0.7	39	2020-09-30	182
3	2020-04-01	1102	議借	150	0.25	38.6	2020-09-30	182
4	2020-04-01	1102	議借	770	1.05	38.6	2020-09-30	182

Schema

{
    date: str,
    stock_id: str,
    transaction_type: str,
    volume: int64,
    fee_rate: float64,
    close: float64,
    original_return_date: str,
    original_lending_period: int64
}

---

暫停融券賣出表(融券回補日) TaiwanStockMarginShortSaleSuspension

• 資料區間：2005-01-01 ~ now
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockMarginShortSaleSuspension",
    "data_id": "0050",
    "start_date": "2015-01-01",
    "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="TaiwanStockMarginShortSaleSuspension",
    data_id="0050",
    start_date= "2015-01-01",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	stock_id	date	end_date	reason
0	0050	2015-10-20	2015-10-23	分配收益
1	0050	2016-07-22	2016-07-27	分配收益
2	0050	2017-02-02	2017-02-07	分配收益
3	0050	2017-07-25	2017-07-28	分配收益
4	0050	2018-01-23	2018-01-26	分配收益

Schema

{
    stock_id: str,
    date: str, # 開始日期
    end_date: str,
    reason: str
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockMarginShortSaleSuspension",
    "start_date": "2015-10-20",
    "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)

R

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
    dataset="TaiwanStockMarginShortSaleSuspension",
    start_date= "2015-10-20",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	stock_id	date	end_date	reason
0	0050	2015-10-20	2015-10-23	分配收益
1	0056	2015-10-20	2015-10-23	分配收益

Schema

{
    stock_id: str,
    date: str, # 開始日期
    end_date: str,
    reason: str
}

---

信用額度總量管制餘額表 TaiwanDailyShortSaleBalances

• 資料區間：2005-07-01 ~ now
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_daily_short_sale_balances(
    stock_id="2330",
    start_date='2020-04-01',
    end_date='2020-04-12'
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanDailyShortSaleBalances",
    "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="TaiwanDailyShortSaleBalances",
    data_id="2330",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	stock_id	MarginShortSalesPreviousDayBalance	MarginShortSalesShortSales	MarginShortSalesShortCovering	MarginShortSalesStockRedemption	MarginShortSalesCurrentDayBalance	MarginShortSalesQuota	SBLShortSalesPreviousDayBalance	SBLShortSalesShortSales	SBLShortSalesReturns	SBLShortSalesAdjustments	SBLShortSalesCurrentDayBalance	SBLShortSalesQuota	SBLShortSalesShortCovering	date
0	2330	1975000	0	1573000	378000	24000	-2107339478	47947858	487000	0	0	48434858	7526895	0	2020-04-01
1	2330	24000	0	0	24000	0	-2107339478	48434858	44000	60000	0	48418858	7563083	0	2020-04-06
2	2330	0	0	0	0	0	-2107339478	48418858	62000	0	0	48480858	7635835	0	2020-04-07
3	2330	0	0	0	0	0	-2107339478	48480858	933000	7345000	0	42068858	7688249	0	2020-04-08
4	2330	0	398000	0	0	398000	-2107339478	42068858	46000	2000	0	42112858	7642682	0	2020-04-09

Schema

{
    stock_id: str,
    MarginShortSalesPreviousDayBalance: int32,
    MarginShortSalesShortSales: int32,
    MarginShortSalesShortCovering: int32,
    MarginShortSalesStockRedemption: int32,
    MarginShortSalesCurrentDayBalance: int32,
    MarginShortSalesQuota: int32,
    SBLShortSalesPreviousDayBalance: int32,
    SBLShortSalesShortSales: int32,
    SBLShortSalesReturns: int32,
    SBLShortSalesAdjustments: int32,
    SBLShortSalesCurrentDayBalance: int32,
    SBLShortSalesQuota: int32,
    SBLShortSalesShortCovering: int32,
    date: str
}

一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_daily_short_sale_balances(
    start_date='2020-04-01',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanDailyShortSaleBalances",
    "start_date": "2021-05-20",
    "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)

R

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
    dataset="TaiwanDailyShortSaleBalances",
    start_date= "2020-01-02",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	stock_id	MarginShortSalesPreviousDayBalance	MarginShortSalesShortSales	MarginShortSalesShortCovering	MarginShortSalesStockRedemption	MarginShortSalesCurrentDayBalance	MarginShortSalesQuota	SBLShortSalesPreviousDayBalance	SBLShortSalesShortSales	SBLShortSalesReturns	SBLShortSalesAdjustments	SBLShortSalesCurrentDayBalance	SBLShortSalesQuota	SBLShortSalesShortCovering	date
0	0050	2336000	13000	65000	1000	2283000	263750000	25527000	0	0	0	25527000	2397551	0	2020-04-01
1	0051	0	0	0	0	0	2375000	1000	0	0	0	1000	4053	0	2020-04-01
2	0052	0	0	0	0	0	7500000	34000	0	0	0	34000	17168	0	2020-04-01
3	0053	0	0	0	0	0	1622000	0	0	0	0	0	3158	0	2020-04-01
4	0054	0	0	0	0	0	2531000	0	0	0	0	0	1357	0	2020-04-01

Schema

{
    stock_id: str,
    MarginShortSalesPreviousDayBalance: int32,
    MarginShortSalesShortSales: int32,
    MarginShortSalesShortCovering: int32,
    MarginShortSalesStockRedemption: int32,
    MarginShortSalesCurrentDayBalance: int32,
    MarginShortSalesQuota: int32,
    SBLShortSalesPreviousDayBalance: int32,
    SBLShortSalesShortSales: int32,
    SBLShortSalesReturns: int32,
    SBLShortSalesAdjustments: int32,
    SBLShortSalesCurrentDayBalance: int32,
    SBLShortSalesQuota: int32,
    SBLShortSalesShortCovering: int32,
    date: str
}

---

證券商資訊表 TaiwanSecuritiesTraderInfo

• 提供證券商相關資訊，用於台股分點資料表(TaiwanStockTradingDailyReport )，使用卷商代碼，查詢特定卷商所有股票進出。

Example

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanSecuritiesTraderInfo",
    "token": "", # 參考登入，獲取金鑰
}
resp = requests.get(url, params=parameter)
data = resp.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 = "TaiwanSecuritiesTraderInfo",
    token = "" # 參考登入，獲取金鑰
    )
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	securities_trader_id	securities_trader	date	address	phone
0	1020	合庫	2011-12-02	台北市大安區忠孝東路四段325號2樓(部分)、經紀部複委託科地址：台北市松山區長安東路二段225號5樓	02-27528000
1	1021	合庫- 台中	2011-12-02	台中市西區民權路91號6樓	04-22255141
2	1022	合庫-台南	2011-12-02	台南市北區成功路48號3樓	06-2260148
3	1023	合庫-高雄	2011-12-02	高雄市大勇路97號5樓	07-5319755
4	1024	合庫-嘉義	2011-12-02	嘉義市國華街279號2樓	05-2220016

Schema

{
    securities_trader_id: str,
    securities_trader: str,
    date: str,
    address: str,
    phone: str
}

---

台股分點資料表(query by 股票代碼) TaiwanStockTradingDailyReport (只限 sponsor 會員使用)

• 資料區間：2021-06-30 ~ now
• 由於資料量過大，單次請求只提供一天資料)
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Python-request

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/taiwan_stock_trading_daily_report'
parameter = {
    "data_id": "2330",
    "date": "2022-06-16",
    "token": 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/taiwan_stock_trading_daily_report'
response = httr::GET(
url = url,
query = list(
    data_id="2330",
    start_date= "2022-06-16",
    token = token # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	securities_trader	price	buy	sell	securities_trader_id	stock_id	date
0	合庫	508	4000	2000	1020	2330	2022-06-16
1	合庫	509	3480	0	1020	2330	2022-06-16
2	合庫	510	2310	50	1020	2330	2022-06-16
3	合庫	511	1169	0	1020	2330	2022-06-16
4	合庫	512	1300	10000	1020	2330	2022-06-16

Schema

{
    securities_trader: str,
    price: float64,
    buy: int32,
    sell: int32,
    securities_trader_id: str,
    stock_id: str,
    date: str
}

---

台股分點資料表(query by 券商代碼) TaiwanStockTradingDailyReport (只限 sponsor 會員使用)

• 資料區間：2021-06-30 ~ now
• 由於資料量過大，單次請求只提供一天資料)
• 資料更新時間 星期一至五 21:00，實際更新時間以 API 資料為主

Example

Python-request

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/taiwan_stock_trading_daily_report'
parameter = {
    "securities_trader_id": "1020",
    "date": "2022-06-16",
    "token": 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/taiwan_stock_trading_daily_report'
response = httr::GET(
url = url,
query = list(
    securities_trader_id="1020",
    start_date= "2022-06-16",
    token = token # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	securities_trader	price	buy	sell	securities_trader_id	stock_id	date
0	合庫	122.25	19000	0	1020	0050	2022-06-16
1	合庫	122.3	80000	0	1020	0050	2022-06-16
2	合庫	122.35	10000	0	1020	0050	2022-06-16
3	合庫	122.5	1300	0	1020	0050	2022-06-16
4	合庫	122.55	20000	0	1020	0050	2022-06-16
...	...	...	...	...	...	...	...
3211	合庫	107	1000	50000	1020	9958	2022-06-16
3212	合庫	107.5	0	32000	1020	9958	2022-06-16
3213	合庫	108	0	2000	1020	9958	2022-06-16
3214	合庫	108.5	150	0	1020	9958	2022-06-16
3215	合庫	16.05	1000	0	1020	9962	2022-06-16

Schema

{
    securities_trader: str,
    price: float64,
    buy: int32,
    sell: int32,
    securities_trader_id: str,
    stock_id: str,
    date: str
}

---

台股權證分點資料表(query by 股票代碼) TaiwanStockWarrantTradingDailyReport (只限 sponsor 會員使用)

• 資料區間：2023-06-21 ~ now
• 由於資料量過大，單次請求只提供一天資料)
• 資料更新時間 星期一至五 23:00，實際更新時間以 API 資料為主

Example

Python-request

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/taiwan_stock_warrant_trading_daily_report'
parameter = {
    "data_id": "084655",
    "date": "2023-06-21",
    "token": 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/taiwan_stock_warrant_trading_daily_report'
response = httr::GET(
url = url,
query = list(
    data_id="084655",
    start_date= "2023-06-21",
    token = token # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	securities_trader	price	buy	sell	securities_trader_id	stock_id	date
0	元富	2.48	0	4000	5920	084655	2023-06-21
1	凱基	2.48	4000	0	9200	084655	2023-06-21

Schema

{
    securities_trader: str,
    price: float64,
    buy: int32,
    sell: int32,
    securities_trader_id: str,
    stock_id: str,
    date: str
}

---

台股權證分點資料表(query by 券商代碼) TaiwanStockWarrantTradingDailyReport (只限 sponsor 會員使用)

• 資料區間：2023-06-21 ~ now
• 由於資料量過大，單次請求只提供一天資料)
• 資料更新時間 星期一至五 23:00，實際更新時間以 API 資料為主

Example

Python-request

import requests
import pandas as pd

url = 'https://api.finmindtrade.com/api/v4/taiwan_stock_warrant_trading_daily_report'
parameter = {
    "securities_trader_id": "5920",
    "date": "2023-06-21",
    "token": 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/taiwan_stock_warrant_trading_daily_report'
response = httr::GET(
url = url,
query = list(
    securities_trader_id="5920",
    start_date= "2023-06-21",
    token = token # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	securities_trader	price	buy	sell	securities_trader_id	stock_id	date
0	元富	0.97	50000	0	5920	07741U	2023-06-21
1	元富	0.98	50000	0	5920	07741U	2023-06-21
2	元富	1.52	100000	0	5920	07742U	2023-06-21
3	元富	1.56	49000	0	5920	07742U	2023-06-21

Schema

{
    securities_trader: str,
    price: float64,
    buy: int32,
    sell: int32,
    securities_trader_id: str,
    stock_id: str,
    date: str
}

---

台股八大行庫買賣表 TaiwanStockGovernmentBankBuySell (只限 sponsor 會員使用)

• 資料區間：2021-06-30 ~ now
• 由於資料量過大，單次請求只提供一天資料
• 資料更新時間 星期一至五 23:30，實際更新時間以 API 資料為主

Example

Package

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_government_bank_buy_sell(
    start_date='2023-01-17',
)

Python-request

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
    "dataset": "TaiwanStockGovernmentBankBuySell",
    "start_date": "2023-01-17",
    "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="TaiwanStockGovernmentBankBuySell",
    start_date= "2023-01-17",
    token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrame

	date	stock_id	buy_amount	sell_amount	buy	sell	bank_name
0	2023-01-17	0050	43992298.6	53309904.25	372595	451744	兆豐
1	2023-01-17	5202	288.0	303.50	20	20	第一
2	2023-01-17	5202	0.0	59.45	0	4	華南
3	2023-01-17	5203	82800.0	0.00	1000	0	兆豐
4	2023-01-17	5203	249000.0	583600.00	3000	7000	臺銀

Schema

{
    date: str,
    stock_id: str,
    buy_amount: float64,
    sell_amount: float64,
    buy: int64,
    sell: int64,
    bank_name: str
}