基本面
在台股基本面，我們擁有 9 種資料集，如下:
- 綜合損益表 TaiwanStockFinancialStatements
- 資產負債表 TaiwanStockBalanceSheet
- 現金流量表 TaiwanStockCashFlowsStatement
- 股利政策表 TaiwanStockDividend
- 除權除息結果表 TaiwanStockDividendResult
- 月營收表 TaiwanStockMonthRevenue
- 減資恢復買賣參考價格 TaiwanStockCapitalReductionReferencePrice
- 台灣股價市值表 TaiwanStockMarketValue
- 台灣股票下市櫃表 TaiwanStockDelisting
綜合損益表 TaiwanStockFinancialStatements¶
- 資料區間：1990-03-01 ~ now
Example
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_financial_statement(
stock_id="2330",
start_date='2019-01-01',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockFinancialStatements",
"data_id": "2330",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockFinancialStatements",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | type | value | origin_name | |
|---|---|---|---|---|---|
| 0 | 2019-03-31 | 2330 | CostOfGoodsSold | 1.28352e+11 | 營業成本 |
| 1 | 2019-03-31 | 2330 | EPS | 2.37 | 基本每股盈餘（元） |
| 2 | 2019-03-31 | 2330 | EquityAttributableToOwnersOfParent | 6.60098e+10 | 綜合損益總額歸屬於母公司業主 |
| 3 | 2019-03-31 | 2330 | GrossProfit | 9.03576e+10 | 營業毛利（毛損）淨額 |
| 4 | 2019-03-31 | 2330 | IncomeAfterTaxes | 6.13873e+10 | 本期淨利（淨損） |
{
date: str,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)¶
Example
from FinMind.data import DataLoader
api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_financial_statement(
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockFinancialStatements",
"start_date": "2019-03-31",
"token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data)
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockFinancialStatements",
start_date= "2019-03-31",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
資產負債表 TaiwanStockBalanceSheet¶
- 資料區間：2011-12-01 ~ now
Example
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_balance_sheet(
stock_id="2330",
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockBalanceSheet",
"data_id": "2330",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockBalanceSheet",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | type | value | origin_name | |
|---|---|---|---|---|---|
| 0 | 2019-03-31 | 2330 | AccountsPayable | 2.71009e+10 | 應付帳款 |
| 1 | 2019-03-31 | 2330 | AccountsPayable_per | 1.24 | 應付帳款 |
| 2 | 2019-03-31 | 2330 | AccountsPayableToRelatedParties | 5.60941e+08 | 應付帳款－關係人 |
| 3 | 2019-03-31 | 2330 | AccountsPayableToRelatedParties_per | 0.03 | 應付帳款－關係人 |
| 4 | 2019-03-31 | 2330 | AccountsReceivableDuefromRelatedPartiesNet | 3.09821e+08 | 應收帳款－關係人淨額 |
{
date: str,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)¶
Example
from FinMind.data import DataLoader
api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_balance_sheet(
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockBalanceSheet",
"start_date": "2019-03-31",
"token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockBalanceSheet",
start_date= "2019-03-31",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
現金流量表 TaiwanStockCashFlowsStatement¶
- 資料區間：2008-06-01 ~ now
Example
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_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"
parameter = {
"dataset": "TaiwanStockCashFlowsStatement",
"data_id": "2330",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockCashFlowsStatement",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | type | value | origin_name | |
|---|---|---|---|---|---|
| 0 | 2019-03-31 | 2330 | HedgingFinancialLiabilities | -2.27383e+08 | 除列避險之金融負債 |
| 1 | 2019-03-31 | 2330 | CashFlowsFromOperatingActivities | 1.5267e+11 | 營業活動之淨現金流入（流出） |
| 2 | 2019-03-31 | 2330 | CashProvidedByInvestingActivities | -6.41885e+10 | 投資活動之淨現金流入(流出) |
| 3 | 2019-03-31 | 2330 | CashBalancesIncrease | 6.78559e+10 | 本期現金及約當現金增加（減少）數 |
| 4 | 2019-03-31 | 2330 | NetIncomeBeforeTax | 6.81817e+10 | 本期稅前淨利（淨損） |
{
date: str,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)¶
Example
from FinMind.data import DataLoader
api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_cash_flows_statement(
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockCashFlowsStatement",
"start_date": "2019-03-31",
"token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockCashFlowsStatement",
start_date= "2019-03-31",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
type: str,
value: float64,
origin_name: str
}
股利政策表 TaiwanStockDividend¶
- 資料區間：2005-05-01 ~ now
Example
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_dividend(
stock_id="2330",
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockDividend",
"data_id": "2330",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockStockDividend",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
year: str,
StockEarningsDistribution: float64,
StockStatutorySurplus: float64,
StockExDividendTradingDate: str,
TotalEmployeeStockDividend: float64,
TotalEmployeeStockDividendAmount: float64,
RatioOfEmployeeStockDividendOfTotal: float64,
RatioOfEmployeeStockDividend: float64,
CashEarningsDistribution: float64,
CashStatutorySurplus: float64,
CashExDividendTradingDate: str,
CashDividendPaymentDate: str,
TotalEmployeeCashDividend: float64,
TotalNumberOfCashCapitalIncrease: float64,
CashIncreaseSubscriptionRate: float64,
CashIncreaseSubscriptionpRrice: float64,
RemunerationOfDirectorsAndSupervisors: float64,
ParticipateDistributionOfTotalShares: float64,
AnnouncementDate: str,
AnnouncementTime: str
}
除權除息結果表 TaiwanStockDividendResult¶
- 資料區間：2003-05-01 ~ now
Example
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_dividend_result(
stock_id="2330",
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockDividendResult",
"data_id": "2330",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockDividendResult",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
before_price: float32,
after_price: float32,
stock_and_cache_dividend: float32,
stock_or_cache_dividend: float32,
max_price: float32,
min_price: float32,
open_price: float32,
reference_price: float32
}
一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)¶
Example
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_dividend_result(
start_date='2019-06-24',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockDividendResult",
"start_date": "2019-06-24",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockDividendResult",
start_date= "2019-06-24",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | before_price | after_price | stock_and_cache_dividend | stock_or_cache_dividend | max_price | min_price | open_price | reference_price | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2019-06-24 | 00697B | 42.48 | 42.21 | 0.27 | 除息 | 9999.95 | 0.01 | 42.21 | 42.21 |
| 1 | 2019-06-24 | 00751B | 46.05 | 45.46 | 0.59 | 除息 | 9999.95 | 0.01 | 45.46 | 45.46 |
| 2 | 2019-06-24 | 1707 | 220 | 213.5 | 6.5 | 息 | 234.5 | 192.5 | 213.5 | 213.5 |
| 3 | 2019-06-24 | 1711 | 17 | 16.5 | 0.5 | 息 | 18.15 | 14.85 | 16.5 | 16.5 |
| 4 | 2019-06-24 | 1906 | 13.55 | 13.05 | 0.5 | 息 | 14.35 | 11.75 | 13.05 | 13.05 |
{
date: str,
stock_id: str,
before_price: float32,
after_price: float32,
stock_and_cache_dividend: float32,
stock_or_cache_dividend: float32,
max_price: float32,
min_price: float32,
open_price: float32,
reference_price: float32
}
月營收表 TaiwanStockMonthRevenue¶
- 資料區間：2002-02-01 ~ now
Example
from FinMind.data import DataLoader
api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_month_revenue(
stock_id="2330",
start_date='2019-03-31',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockMonthRevenue",
"data_id": "2330",
"start_date": "2019-01-01",
"token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockMonthRevenue",
data_id="2330",
start_date= "2019-01-02",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
country: str,
revenue: int64,
revenue_month: int64,
revenue_year: int64
}
一次拿特定日期，所有資料(只限 backer、sponsor 會員使用)¶
Example
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_month_revenue(
start_date='2019-04-01',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockMonthRevenue",
"start_date": "2019-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockMonthRevenue",
start_date= "2019-01-01",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | country | revenue | revenue_month | revenue_year | |
|---|---|---|---|---|---|---|
| 0 | 2019-05-01 | 1101 | Taiwan | 10596314000 | 4 | 2019 |
| 1 | 2019-05-01 | 1102 | Taiwan | 8434811000 | 4 | 2019 |
| 2 | 2019-05-01 | 1103 | Taiwan | 160751000 | 4 | 2019 |
| 3 | 2019-05-01 | 1104 | Taiwan | 418992000 | 4 | 2019 |
| 4 | 2019-05-01 | 1108 | Taiwan | 323834000 | 4 | 2019 |
{
date: str,
stock_id: str,
country: str,
revenue: int64,
revenue_month: int64,
revenue_year: int64
}
減資恢復買賣參考價格 TaiwanStockCapitalReductionReferencePrice¶
- 資料區間：2011-01-01 ~ now
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockCapitalReductionReferencePrice",
"data_id": "2327",
"start_date": "2010-01-01",
"token": "", # 參考登入，獲取金鑰
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id ClosingPriceonTheLastTradingDay PostReductionReferencePrice LimitUp LimitDown OpeningReferencePrice ExrightReferencePrice ReasonforCapitalReduction
0 2013-09-18 2327 10.20 10.28 10.95 9.57 10.3 -1.0 Cash refund
1 2014-10-09 2327 22.05 49.82 53.30 46.35 49.8 -1.0 Cash refund
2 2016-08-15 2327 54.80 65.96 72.50 59.40 66.0 -1.0 Cash refund
3 2017-08-18 2327 120.50 168.13 184.50 151.50 168.0 -1.0 Cash refund
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockCapitalReductionReferencePrice",
data_id="2327",
start_date= "2010-01-01",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$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
台灣股價市值表 TaiwanStockMarketValue (只限 backer、sponsor 會員使用)¶
- 資料區間：2004-01-01 ~ now
- 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
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_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"
parameter = {
"dataset": "TaiwanStockMarketValue",
"data_id": "2330",
"start_date": "2023-01-01",
"end_date": "2024-01-01",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockMarketValue",
data_id= "2330",
start_date= "2023-01-01",
end_date= "2024-01-01",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| date | stock_id | market_value | |
|---|---|---|---|
| 0 | 2023-01-03 | 2330 | 1.174646e+13 |
| 1 | 2023-01-04 | 2330 | 1.165571e+13 |
| 2 | 2023-01-05 | 2330 | 1.188908e+13 |
| 3 | 2023-01-06 | 2330 | 1.188908e+13 |
| 4 | 2023-01-09 | 2330 | 1.247251e+13 |
{
date: str,
stock_id: str,
market_value: int64
}
一次拿特定日期，所有資料(只限 backer、sponsor 使用)¶
Example
from FinMind.data import DataLoader
api = DataLoader()
# api.login_by_token(api_token='token')
# api.login(user_id='user_id',password='password')
df = api.taiwan_stock_daily(
start_date='2023-01-03',
)
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockMarketValue",
"start_date": "2023-01-03",
"token": "", # 參考登入，獲取金鑰
}
resp = requests.get(url, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockMarketValue",
start_date= "2023-01-03",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
market_value: int64
}
台灣股票下市櫃表 TaiwanStockDelisting¶
- 資料區間：2001-01-01 ~ now
- 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
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_delisting()
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v4/data"
parameter = {
"dataset": "TaiwanStockDelisting",
"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())
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v4/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockDelisting",
token = "" # 參考登入，獲取金鑰
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
Output
| 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,
stock_id: str,
stock_name: str
}