Fundamental

In Taiwan stock fundamental data, we have 12 datasets, as follows:

• Income Statement TaiwanStockFinancialStatements
• Balance Sheet TaiwanStockBalanceSheet
• Cash Flows Statement TaiwanStockCashFlowsStatement
• Dividend Policy Table TaiwanStockDividend
• Ex-Dividend/Ex-Right Result Table TaiwanStockDividendResult
• Monthly Revenue Table TaiwanStockMonthRevenue
• Capital Reduction Resumption Reference Price TaiwanStockCapitalReductionReferencePrice
• Taiwan Stock Market Value Table TaiwanStockMarketValue
• Taiwan Stock Delisting Table TaiwanStockDelisting
• Taiwan Stock Market Value Weight Table TaiwanStockMarketValueWeight
• Taiwan Stock Post-Split Reference Price TaiwanStockSplitPrice
• Taiwan Stock Par Value Change Resumption Reference Price TaiwanStockParValueChange

---

Income Statement TaiwanStockFinancialStatements

• Data range: 1990-03-01 ~ now
• Coverage: listed (TWSE), OTC (TPEx) and emerging market companies, distinguished by stock_id (use TaiwanStockInfo to look up market type)

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_financial_statement(
    stock_id="2330",
    start_date='2019-01-01',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockFinancialStatements",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockFinancialStatements",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_financial_statement(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	2330	CostOfGoodsSold	1.28352e+11	營業成本
1	2019-03-31	2330	EPS	2.37	基本每股盈餘（元）
2	2019-03-31	2330	EquityAttributableToOwnersOfParent	6.60098e+10	綜合損益總額歸屬於母公司業主
3	2019-03-31	2330	GrossProfit	9.03576e+10	營業毛利（毛損）淨額
4	2019-03-31	2330	IncomeAfterTaxes	6.13873e+10	本期淨利（淨損）

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_financial_statement(
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockFinancialStatements",
    "start_date": "2019-03-31",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data)

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockFinancialStatements",
        start_date= "2019-03-31"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	000116	EPS	0.24	基本每股盈餘（元）
1	2019-03-31	000116	EquityAttributableToOwnersOfParent	4.65569e+08	綜合損益總額歸屬於母公司業主
2	2019-03-31	000116	Expense	8.95498e+08	支出及費用
3	2019-03-31	000116	Income	1.07791e+09	收益
4	2019-03-31	000116	IncomeAfterTaxes	2.74322e+08	本期淨利（淨損）

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

---

Balance Sheet TaiwanStockBalanceSheet

• Data range: 2011-12-01 ~ now
• Coverage: listed (TWSE), OTC (TPEx) and emerging market companies, distinguished by stock_id (use TaiwanStockInfo to look up market type)

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_balance_sheet(
    stock_id="2330",
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockBalanceSheet",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockBalanceSheet",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_balance_sheet(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	2330	AccountsPayable	2.71009e+10	應付帳款
1	2019-03-31	2330	AccountsPayable_per	1.24	應付帳款
2	2019-03-31	2330	AccountsPayableToRelatedParties	5.60941e+08	應付帳款－關係人
3	2019-03-31	2330	AccountsPayableToRelatedParties_per	0.03	應付帳款－關係人
4	2019-03-31	2330	AccountsReceivableDuefromRelatedPartiesNet	3.09821e+08	應收帳款－關係人淨額

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_balance_sheet(
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockBalanceSheet",
    "start_date": "2019-03-31",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockBalanceSheet",
        start_date= "2019-03-31"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	1101	AccountsPayable	7.84411e+09	應付帳款
1	2019-03-31	1101	AccountsPayable_per	2.15	應付帳款
2	2019-03-31	1101	AccountsReceivableDuefromRelatedPartiesNet	2.64638e+08	應收帳款－關係人淨額
3	2019-03-31	1101	AccountsReceivableDuefromRelatedPartiesNet_per	0.07	應收帳款－關係人淨額
4	2019-03-31	1101	AccountsReceivableNet	8.3396e+09	應收帳款淨額

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

---

Cash Flows Statement TaiwanStockCashFlowsStatement

• Data range: 2008-06-01 ~ now
• Coverage: listed (TWSE), OTC (TPEx) and emerging market companies, distinguished by stock_id (use TaiwanStockInfo to look up market type)

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_cash_flows_statement(
    stock_id="2330",
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockCashFlowsStatement",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockCashFlowsStatement",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_cash_flows_statement(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	2330	HedgingFinancialLiabilities	-2.27383e+08	除列避險之金融負債
1	2019-03-31	2330	CashFlowsFromOperatingActivities	1.5267e+11	營業活動之淨現金流入（流出）
2	2019-03-31	2330	CashProvidedByInvestingActivities	-6.41885e+10	投資活動之淨現金流入(流出)
3	2019-03-31	2330	CashBalancesIncrease	6.78559e+10	本期現金及約當現金增加（減少）數
4	2019-03-31	2330	NetIncomeBeforeTax	6.81817e+10	本期稅前淨利（淨損）

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_cash_flows_statement(
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockCashFlowsStatement",
    "start_date": "2019-03-31",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockCashFlowsStatement",
        start_date= "2019-03-31"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	type	value	origin_name
0	2019-03-31	1101	DecreaseInShortTermLoans	7.59053e+09	短期借款減少
1	2019-03-31	1101	ReceivableIncrease	-1.15069e+08	應收帳款(增加)減少
2	2019-03-31	1101	PropertyAndPlantAndEquipment	-1.48367e+09	取得不動產、廠房及設備
3	2019-03-31	1101	NetIncomeBeforeTax	5.6035e+09	本期稅前淨利（淨損）
4	2019-03-31	1101	CashProvidedByInvestingActivities	-4.31058e+09	投資活動之淨現金流入(流出)

{
    date: str, # date
    stock_id: str, # stock code
    type: str, # category
    value: float64, # value
    origin_name: str # original name
}

---

Dividend Policy Table TaiwanStockDividend

• Data range: 2005-05-01 ~ now

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_dividend(
    stock_id="2330",
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockDividend",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockStockDividend",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_dividend(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	year	StockEarningsDistribution	StockStatutorySurplus	StockExDividendTradingDate	TotalEmployeeStockDividend	TotalEmployeeStockDividendAmount	RatioOfEmployeeStockDividendOfTotal	RatioOfEmployeeStockDividend	CashEarningsDistribution	CashStatutorySurplus	CashExDividendTradingDate	CashDividendPaymentDate	TotalEmployeeCashDividend	TotalNumberOfCashCapitalIncrease	CashIncreaseSubscriptionRate	CashIncreaseSubscriptionpRrice	RemunerationOfDirectorsAndSupervisors	ParticipateDistributionOfTotalShares	AnnouncementDate	AnnouncementTime
0	2019-06-30	2330	107年	0	0		0	0	0	0	8	0	2019-06-24	2019-07-18	0	0	0	0	0	2.59304e+10	2019-06-06	15:47:30
1	2019-09-25	2330	108年第1季	0	0		0	0	0	0	2	0	2019-09-19	2019-10-17	0	0	0	0	0	2.59304e+10	2019-07-09	18:33:02
2	2019-12-25	2330	108年第2季	0	0		0	0	0	0	2.5	0	2019-12-19	2020-01-16	0	0	0	0	0	2.59304e+10	2019-08-14	15:27:02
3	2020-03-25	2330	108年第3季	0	0		0	0	0	0	2.5	0	2020-03-19	2020-04-16	0	0	0	0	0	2.59304e+10	2019-11-14	17:01:07
4	2020-06-24	2330	108年第4季	0	0		0	0	0	0	2.5	0	2020-06-18	2020-07-16	0	0	0	0	0	2.59304e+10	2020-02-14	15:10:50

{
    date: str, # rights distribution record date
    stock_id: str, # stock code
    year: str, # dividend fiscal year
    StockEarningsDistribution: float64, # stock dividend: capitalization of earnings
    StockStatutorySurplus: float64, # stock dividend: capitalization of statutory and capital surplus
    StockExDividendTradingDate: str, # ex-rights trading date
    TotalEmployeeStockDividend: float64, # employee stock dividend
    TotalEmployeeStockDividendAmount: float64, # employee stock dividend amount
    RatioOfEmployeeStockDividendOfTotal: float64, # ratio of employee stock dividend to total earnings dividend
    RatioOfEmployeeStockDividend: float64, # employee stock dividend ratio
    CashEarningsDistribution: float64, # cash dividend: capitalization of earnings
    CashStatutorySurplus: float64, # cash dividend: capitalization of statutory and capital surplus
    CashExDividendTradingDate: str, # ex-dividend trading date
    CashDividendPaymentDate: str, # cash dividend payment date
    TotalEmployeeCashDividend: float64, # total employee cash bonus
    TotalNumberOfCashCapitalIncrease: float64, # total shares of cash capital increase
    CashIncreaseSubscriptionRate: float64, # cash capital increase subscription ratio
    CashIncreaseSubscriptionpRrice: float64, # cash capital increase subscription price
    RemunerationOfDirectorsAndSupervisors: float64, # directors and supervisors remuneration
    ParticipateDistributionOfTotalShares: float64, # total shares participating in distribution
    AnnouncementDate: str, # announcement date
    AnnouncementTime: str # announcement time
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_dividend(
    start_date='2025-10-06',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockDividend",
    "start_date": "2025-10-06",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockStockDividend",
        start_date= "2025-10-06"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	year	StockEarningsDistribution	StockStatutorySurplus	StockExDividendTradingDate	TotalEmployeeStockDividend	TotalEmployeeStockDividendAmount	RatioOfEmployeeStockDividendOfTotal	RatioOfEmployeeStockDividend	CashEarningsDistribution	CashStatutorySurplus	CashExDividendTradingDate	CashDividendPaymentDate	TotalEmployeeCashDividend	TotalNumberOfCashCapitalIncrease	CashIncreaseSubscriptionRate	CashIncreaseSubscriptionpRrice	RemunerationOfDirectorsAndSupervisors	ParticipateDistributionOfTotalShares	AnnouncementDate	AnnouncementTime
0	2025-10-06	2540	113年	3	0.999999	2025-09-30	0	0	0	0	0.4	0.6	2025-09-30	2025-10-31	0	0	0	0	0	6.7491e+08	2025-09-12	17:35:32
1	2025-10-06	3312	不適用	0	0	2025-09-30	0	0	0	0	0	0			0	2e+07	9.84	39.8	0	1.62627e+08	2025-09-22	16:52:52

{
    date: str, # rights distribution record date
    stock_id: str, # stock code
    year: str, # dividend fiscal year
    StockEarningsDistribution: float64, # stock dividend: capitalization of earnings
    StockStatutorySurplus: float64, # stock dividend: capitalization of statutory and capital surplus
    StockExDividendTradingDate: str, # ex-rights trading date
    TotalEmployeeStockDividend: float64, # employee stock dividend
    TotalEmployeeStockDividendAmount: float64, # employee stock dividend amount
    RatioOfEmployeeStockDividendOfTotal: float64, # ratio of employee stock dividend to total earnings dividend
    RatioOfEmployeeStockDividend: float64, # employee stock dividend ratio
    CashEarningsDistribution: float64, # cash dividend: capitalization of earnings
    CashStatutorySurplus: float64, # cash dividend: capitalization of statutory and capital surplus
    CashExDividendTradingDate: str, # ex-dividend trading date
    CashDividendPaymentDate: str, # cash dividend payment date
    TotalEmployeeCashDividend: float64, # total employee cash bonus
    TotalNumberOfCashCapitalIncrease: float64, # total shares of cash capital increase
    CashIncreaseSubscriptionRate: float64, # cash capital increase subscription ratio
    CashIncreaseSubscriptionpRrice: float64, # cash capital increase subscription price
    RemunerationOfDirectorsAndSupervisors: float64, # directors and supervisors remuneration
    ParticipateDistributionOfTotalShares: float64, # total shares participating in distribution
    AnnouncementDate: str, # announcement date
    AnnouncementTime: str # announcement time
}

---

Ex-Dividend/Ex-Right Result Table TaiwanStockDividendResult

• Data range: 2003-05-01 ~ now

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_dividend_result(
    stock_id="2330",
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockDividendResult",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockDividendResult",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_dividend_result(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	before_price	after_price	stock_and_cache_dividend	stock_or_cache_dividend	max_price	min_price	open_price	reference_price
0	2019-06-24	2330	248.5	240.5	8	息	264.5	216.5	240.5	240.5
1	2019-09-19	2330	267	265	2	息	291.5	238.5	265	265
2	2019-12-19	2330	344.5	342	2.5	息	376	308	342	342
3	2020-03-19	2330	260	257.5	2.5	息	283	232	257.5	257.5
4	2020-06-18	2330	315	312.5	2.5	息	343.5	281.5	312.5	312.5

{
    date: str, # date
    stock_id: str, # stock code
    before_price: float32, # closing price before ex-dividend/ex-right
    after_price: float32, # closing price after ex-dividend/ex-right
    stock_and_cache_dividend: float32, # dividend value
    stock_or_cache_dividend: float32, # right/dividend
    max_price: float32, # limit-up price
    min_price: float32, # limit-down price
    open_price: float32, # open price
    reference_price: float32 # reference price after dividend deduction
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_dividend_result(
    start_date='2019-06-24',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockDividendResult",
    "start_date": "2019-06-24",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockDividendResult",
        start_date= "2019-06-24"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	before_price	after_price	stock_and_cache_dividend	stock_or_cache_dividend	max_price	min_price	open_price	reference_price
0	2019-06-24	00697B	42.48	42.21	0.27	除息	9999.95	0.01	42.21	42.21
1	2019-06-24	00751B	46.05	45.46	0.59	除息	9999.95	0.01	45.46	45.46
2	2019-06-24	1707	220	213.5	6.5	息	234.5	192.5	213.5	213.5
3	2019-06-24	1711	17	16.5	0.5	息	18.15	14.85	16.5	16.5
4	2019-06-24	1906	13.55	13.05	0.5	息	14.35	11.75	13.05	13.05

{
    date: str, # date
    stock_id: str, # stock code
    before_price: float32, # closing price before ex-dividend/ex-right
    after_price: float32, # closing price after ex-dividend/ex-right
    stock_and_cache_dividend: float32, # dividend value
    stock_or_cache_dividend: float32, # right/dividend
    max_price: float32, # limit-up price
    min_price: float32, # limit-down price
    open_price: float32, # open price
    reference_price: float32 # reference price after dividend deduction
}

---

Monthly Revenue Table TaiwanStockMonthRevenue

• Data range: 2002-02-01 ~ now
• Coverage: listed (TWSE), OTC (TPEx) and emerging market companies, distinguished by stock_id (use TaiwanStockInfo to look up market type)

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_month_revenue(
    stock_id="2330",
    start_date='2019-03-31',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMonthRevenue",
    "data_id": "2330",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMonthRevenue",
        data_id="2330",
        start_date= "2019-01-02"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_month_revenue(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	country	revenue	revenue_month	revenue_year
0	2019-04-01	2330	Taiwan	79721587000	3	2019
1	2019-05-01	2330	Taiwan	74693615000	4	2019
2	2019-06-01	2330	Taiwan	80436931000	5	2019
3	2019-07-01	2330	Taiwan	85867929000	6	2019
4	2019-08-01	2330	Taiwan	84757724000	7	2019

{
    date: str, # date
    stock_id: str, # stock code
    country: str, # country
    revenue: int64, # revenue
    revenue_month: int64, # revenue month
    revenue_year: int64 # revenue year
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_month_revenue(
    start_date='2019-04-01',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMonthRevenue",
    "start_date": "2019-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMonthRevenue",
        start_date= "2019-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	country	revenue	revenue_month	revenue_year
0	2019-05-01	1101	Taiwan	10596314000	4	2019
1	2019-05-01	1102	Taiwan	8434811000	4	2019
2	2019-05-01	1103	Taiwan	160751000	4	2019
3	2019-05-01	1104	Taiwan	418992000	4	2019
4	2019-05-01	1108	Taiwan	323834000	4	2019

{
    date: str, # date
    stock_id: str, # stock code
    country: str, # country
    revenue: int64, # revenue
    revenue_month: int64, # revenue month
    revenue_year: int64 # revenue year
}

---

Capital Reduction Resumption Reference Price TaiwanStockCapitalReductionReferencePrice

• Data range: 2011-01-01 ~ now

Example

PythonRPackage-Async

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockCapitalReductionReferencePrice",
    "data_id": "2327",
    "start_date": "2010-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

        date stock_id  ClosingPriceonTheLastTradingDay  PostReductionReferencePrice  LimitUp  LimitDown  OpeningReferencePrice  ExrightReferencePrice ReasonforCapitalReduction
0  2013-09-18     2327                            10.20                        10.28    10.95       9.57                   10.3                   -1.0               Cash refund
1  2014-10-09     2327                            22.05                        49.82    53.30      46.35                   49.8                   -1.0               Cash refund
2  2016-08-15     2327                            54.80                        65.96    72.50      59.40                   66.0                   -1.0               Cash refund
3  2017-08-18     2327                           120.50                       168.13   184.50     151.50                  168.0                   -1.0               Cash refund

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockCapitalReductionReferencePrice",
        data_id="2327",
        start_date= "2010-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

        date stock_id  ClosingPriceonTheLastTradingDay  PostReductionReferencePrice  LimitUp  LimitDown  OpeningReferencePrice  ExrightReferencePrice ReasonforCapitalReduction
1  2013-09-18     2327                            10.20                        10.28    10.95       9.57                   10.3                   -1.0               Cash refund
2  2014-10-09     2327                            22.05                        49.82    53.30      46.35                   49.8                   -1.0               Cash refund
3  2016-08-15     2327                            54.80                        65.96    72.50      59.40                   66.0                   -1.0               Cash refund
4  2017-08-18     2327                           120.50                       168.13   184.50     151.50                  168.0                   -1.0               Cash refund

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_capital_reduction_reference_price(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

---

Taiwan Stock Market Value Table TaiwanStockMarketValue (available only to backer, sponsor members)

• Data range: 2004-01-01 ~ now
• Data update time: Monday to Friday 23:30. The actual update time is based on the API data.

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_market_value(
    stock_id='2330',
    start_date='2023-01-01',
    end_date='2024-01-01'
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarketValue",
    "data_id": "2330",
    "start_date": "2023-01-01",
    "end_date": "2024-01-01",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
    response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarketValue",
        data_id= "2330",
        start_date= "2023-01-01",
        end_date= "2024-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	market_value
0	2023-01-03	2330	1.174646e+13
1	2023-01-04	2330	1.165571e+13
2	2023-01-05	2330	1.188908e+13
3	2023-01-06	2330	1.188908e+13
4	2023-01-09	2330	1.247251e+13

{
    date: str, # date
    stock_id: str, # stock code
    market_value: int64 # market value
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_daily(
    start_date='2023-01-03',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarketValue",
    "start_date": "2023-01-03",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarketValue",
        start_date= "2023-01-03"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	market_value
0	2023-01-03	0050	2.561094e+11
1	2023-01-03	0051	7.967000e+08
2	2023-01-03	0052	5.644650e+09
3	2023-01-03	0053	2.611218e+08
4	2023-01-03	0055	1.625804e+09

{
    date: str, # date
    stock_id: str, # stock code
    market_value: int64 # market value
}

---

Taiwan Stock Delisting Table TaiwanStockDelisting

• Data range: 2001-01-01 ~ now
• Data update time: Monday to Friday 23:30. The actual update time is based on the API data.

Example

PackagePython-requestRPackage-Async

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_delisting()

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockDelisting",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockDelisting"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

from FinMind.data import DataLoader
from loguru import logger
import datetime

api = DataLoader()
api.login_by_token(api_token='token')

start = datetime.datetime.now()
df = api.taiwan_stock_delisting(
    stock_id_list=['2330', '2317', '2454', '3008'],
    start_date='2024-01-01',
    end_date='2024-12-31',
    use_async=True,
)
cost = datetime.datetime.now() - start
logger.info(cost)

Output

DataFrameSchema

	date	stock_id	stock_name
0	2005-10-04	1204	津津
1	2001-11-01	1230	聯成食品
2	2005-10-04	1306	合發興業
3	2006-06-26	1408	中興紡織
4	2002-11-08	1431	新燕實業

{
    date: str, # date
    stock_id: str, # stock code
    stock_name: str # stock name
}

---

Taiwan Stock Market Value Weight Table TaiwanStockMarketValueWeight (available only to backer, sponsor members)

• Data range: 2024-10-30 ~ now
• Data update time: 23:45 on the 1st, 2nd, 3rd, 28th, 29th, 30th, and 31st of each month. The actual update time is based on the API data.

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_market_value_weight(
    stock_id='2330',
    start_date='2024-01-01',
    end_date='2025-01-01'
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarketValueWeight",
    "data_id": "2330",
    "start_date": "2024-01-01",
    "end_date": "2025-01-01",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarketValueWeight",
        data_id= "2330",
        start_date= "2024-01-01",
        end_date= "2025-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	rank	stock_id	stock_name	weight_per	date	type
0	1	2330	台積電	36.8397	2024-10-30	twse

{
    rank: int64, # rank
    stock_id: str, # stock code
    stock_name: str, # stock name
    weight_per: float32, # weight percentage
    date: str, # date
    type: str # listed (twse) / OTC (tpex)
}

Fetch all data for a specific date at once (available only to backer, sponsor members)

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_market_value_weight(
    start_date='2024-10-30',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockMarketValueWeight",
    "start_date": "2024-10-30",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockMarketValueWeight",
        start_date= "2024-10-30"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	rank	stock_id	stock_name	weight_per	date	type
0	43	1101	台泥	0.3327	2024-10-30	twse
0	63	1102	亞泥	0.2282	2024-10-30	twse
0	394	1103	嘉泥	0.0192	2024-10-30	twse
0	305	1104	環泥	0.0286	2024-10-30	twse
0	651	1108	幸福	0.0082	2024-10-30	twse

{
    rank: int64, # rank
    stock_id: str, # stock code
    stock_name: str, # stock name
    weight_per: float32, # weight percentage
    date: str, # date
    type: str # listed (twse) / OTC (tpex)
}

---

Taiwan Stock Post-Split Reference Price TaiwanStockSplitPrice

• Provides Taiwan stock post-split reference prices.
• Data update time: Monday to Friday 18:00. The actual update time is based on the API data.

Example

Python-requestR

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockSplitPrice",
}
resp = requests.get(url, headers=headers, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockSplitPrice"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	type	before_price	after_price	max_price	min_price	open_price
0	2024-12-11	00632R	反分割	3.28	22.96	25.25	20.67	22.96
1	2025-02-19	00676R	反分割	2.04	12.23	13.45	11.01	12.23
2	2025-06-11	00663L	分割	170.15	24.3	29.16	19.44	24.3
3	2025-06-18	0050	分割	188.65	47.16	51.85	42.45	47.16

{
    date: str, # split date
    stock_id: str, # stock code
    type: str, # split type
    before_price: float, # pre-split price
    after_price: float, # post-split price
    max_price: float, # post-split max price
    min_price: float, # post-split min price
    open_price: float # post-split open price
}

---

Taiwan Stock Par Value Change Resumption Reference Price TaiwanStockParValueChange

• Data range: 2020-01-01 ~ now

Example

PackagePython-requestR

from FinMind.data import DataLoader

api = DataLoader()
# api.login_by_token(api_token='token')
df = api.taiwan_stock_par_value_change(
    start_date='2020-01-01',
)

import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
token = "" # Refer to login to obtain the token
headers = {"Authorization": f"Bearer {token}"}
parameter = {
    "dataset": "TaiwanStockParValueChange",
    "start_date": "2020-01-01",
}
data = requests.get(url, headers=headers, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())

library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
token = "" # Refer to login to obtain the token
response = httr::GET(
    url = url,
    query = list(
        dataset="TaiwanStockParValueChange",
        start_date= "2020-01-01"
    ),
    add_headers(Authorization = paste("Bearer", token))
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)

Output

DataFrameSchema

	date	stock_id	stock_name	before_close	after_ref_close	after_ref_max	after_ref_min	after_ref_open
0	2020-08-17	8070	長華	190	19	20.9	17.1	19
1	2021-10-18	6531	愛普	750	375	412.5	337.5	375
2	2022-07-13	6415	矽力-K	2485	621.25	683	560	621
3	2024-11-11	8476	台境	58.8	29.4	32.3	26.5	29.4
4	2025-06-30	4763	材料-KY	885	88.5	97.3	79.7	88.5

{
    date: str, # date
    stock_id: str, # stock code
    stock_name: str, # stock name
    before_close: float64, # closing price before suspension
    after_ref_close: float64, # resumption reference price
    after_ref_max: float64, # limit-up price
    after_ref_min: float64, # limit-down price
    after_ref_open: float64 # opening auction reference price
}