基本面
在台股基本面，我們擁有 6 種資料集，如下:
- 綜合損益表 FinancialStatements
- 資產負債表 BalanceSheet
- 現金流量表 TaiwanCashFlowsStatement
- 股利政策表 StockDividend
- 除權除息結果表 StockDividendResult
- 月營收表 TaiwanStockMonthRevenue
綜合損益表 FinancialStatements¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "FinancialStatements",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id type value origin_name
0 2019-03-31 2330 ASSO 433491000.0 採用權益法認列之關聯企業及合資損益之份額淨額
1 2019-03-31 2330 CostOfGoodsSold 128352000000.0 營業成本合計
2 2019-03-31 2330 EPS 2.37 基本每股盈餘
3 2019-03-31 2330 EXDF 3218080000.0 國外營運機構財務報表換算之兌換差額
4 2019-03-31 2330 FinancialCost 899065000.0 財務成本淨額
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="FinancialStatements",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id type value origin_name
1: 2019-03-31 2330 ASSO 433491000.0 採用權益法認列之關聯企業及合資損益之份額淨額
2: 2019-03-31 2330 CostOfGoodsSold 128352000000.0 營業成本合計
3: 2019-03-31 2330 EPS 2.37 基本每股盈餘
4: 2019-03-31 2330 EXDF 3218080000.0 國外營運機構財務報表換算之兌換差額
5: 2019-03-31 2330 FinancialCost 899065000.0 財務成本淨額
6: 2019-03-31 2330 GrossProfit 90352100000.0 營業毛利(毛損)
資產負債表 BalanceSheet¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "BalanceSheet",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id type value origin_name
0 2019-03-31 2330 AccountsPayable 27100909000.0 應付帳款
1 2019-03-31 2330 AccountsPayable_per 1.0 應付帳款
2 2019-03-31 2330 AccountsPayableToRelatedParties 560941000.0 應付帳款－關係人
3 2019-03-31 2330 AccountsPayableToRelatedParties_per 0.0 應付帳款－關係人
4 2019-03-31 2330 AccountsReceivableDuefromRelatedPartiesNet 309821000.0 應收帳款－關係人淨額
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="BalanceSheet",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id type value origin_name
1: 2019-03-31 2330 AccountsPayable 27100909000.0 應付帳款
2: 2019-03-31 2330 AccountsPayable_per 1.0 應付帳款
3: 2019-03-31 2330 AccountsPayableToRelatedParties 560941000.0 應付帳款－關係人
4: 2019-03-31 2330 AccountsPayableToRelatedParties_per 0.0 應付帳款－關係人
5: 2019-03-31 2330 AccountsReceivableDuefromRelatedPartiesNet 309821000.0 應收帳款－關係人淨額
6: 2019-03-31 2330 AccountsReceivableDuefromRelatedPartiesNet_per 0.0 應收帳款－關係人淨額
現金流量表 TaiwanCashFlowsStatement¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanCashFlowsStatement",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id type value origin_name
0 2019-03-31 2330 AccountsPayable 6105110000.0 應付帳款增加(減少)
1 2019-03-31 2330 AmortizationExpense 1355340000.0 攤銷費用
2 2019-03-31 2330 AmountDueToRelatedParties 815558000.0 應付帳款-關係人增加(減少)
3 2019-03-31 2330 CashBalancesBeginningOfPeriod 577815000000.0 期初現金及約當現金餘額
4 2019-03-31 2330 CashBalancesEndOfPeriod 645671000000.0 期末現金及約當現金餘額
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanCashFlowsStatement",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id type value origin_name
1: 2019-03-31 2330 AccountsPayable 6105110000.0 應付帳款增加(減少)
2: 2019-03-31 2330 AmortizationExpense 1355340000.0 攤銷費用
3: 2019-03-31 2330 AmountDueToRelatedParties 815558000.0 應付帳款-關係人增加(減少)
4: 2019-03-31 2330 CashBalancesBeginningOfPeriod 577815000000.0 期初現金及約當現金餘額
5: 2019-03-31 2330 CashBalancesEndOfPeriod 645671000000.0 期末現金及約當現金餘額
6: 2019-03-31 2330 CashBalancesIncrease 67855900000.0 本期現金及約當現金增加（減少）數
股利政策表 StockDividend¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "StockDividend",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id year StockEarningsDistribution ... RemunerationOfDirectorsAndSupervisors ParticipateDistributionOfTotalShares AnnouncementDate AnnouncementTime
0 2019-06-30 2330 107年 None ... None 25930380458 2019-06-06 15:47:30.000000000
1 2019-09-25 2330 108年第1季 None ... None 25930380458 2019-07-09 18:33:02.000000000
2 2019-12-25 2330 108年第2季 None ... None 25930380458 2019-08-14 15:27:02.000000000
3 2020-03-25 2330 108年第3季 None ... None 25930380458 2019-11-14 17:01:07.000000000
4 2020-06-24 2330 108年第4季 None ... None 25930380458 2020-02-14 15:10:50.000000000
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="StockDividend",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id year StockEarningsDistribution StockStatutorySurplus
1: 2019-06-30 2330 107年 None None
2: 2019-09-25 2330 108年第1季 None None
3: 2019-12-25 2330 108年第2季 None None
4: 2020-03-25 2330 108年第3季 None None
5: 2020-06-24 2330 108年第4季 None None
6: 2020-09-23 2330 109年第1季 None None
StockExDividendTradingDate TotalEmployeeStockDividend TotalEmployeeStockDividendAmount
1: None None None
2: None None None
3: None None None
4: None None None
5: None None None
6: None None None
RatioOfEmployeeStockDividendOfTotal RatioOfEmployeeStockDividend CashEarningsDistribution
1: None None 8.0
2: None None 2.0
3: None None 2.5
4: None None 2.5
5: None None 2.5
6: None None 2.5
CashStatutorySurplus CashExDividendTradingDate CashDividendPaymentDate TotalEmployeeCashDividend
1: None 2019-06-24 2019-07-18 None
2: None 2019-09-19 2019-10-17 None
3: None 2019-12-19 2020-01-16 None
4: None 2020-03-19 2020-04-16 None
5: None 2020-06-18 2020-07-16 None
6: None 2020-09-17 2020-10-15 None
TotalNumberOfCashCapitalIncrease CashIncreaseSubscriptionRate CashIncreaseSubscriptionpRrice
1: None None None
2: None None None
3: None None None
4: None None None
5: None None None
6: None None None
RemunerationOfDirectorsAndSupervisors ParticipateDistributionOfTotalShares AnnouncementDate
1: None 25930380458 2019-06-06
2: None 25930380458 2019-07-09
3: None 25930380458 2019-08-14
4: None 25930380458 2019-11-14
5: None 25930380458 2020-02-14
6: None 25930380458 2020-05-14
AnnouncementTime
1: 15:47:30.000000000
2: 18:33:02.000000000
3: 15:27:02.000000000
4: 17:01:07.000000000
5: 15:10:50.000000000
6: 10:51:55.000000000
除權除息結果表 StockDividendResult¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "StockDividendResult",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id type value
0 2019-06-24 2330 after_price 240.50
1 2019-06-24 2330 before_price 248.50
2 2019-06-24 2330 max_price 264.50
3 2019-06-24 2330 min_price 216.50
4 2019-06-24 2330 open_price 240.50
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="StockDividendResult",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id type value
1: 2019-06-24 2330 after_price 240.50
2: 2019-06-24 2330 before_price 248.50
3: 2019-06-24 2330 max_price 264.50
4: 2019-06-24 2330 min_price 216.50
5: 2019-06-24 2330 open_price 240.50
6: 2019-06-24 2330 reference_price 240.50
月營收表 TaiwanStockMonthRevenue¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockMonthRevenue",
"stock_id": "2330",
"date": "2019-01-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id country revenue revenue_month revenue_year
0 2019-01-01 2330 Taiwan 89830598000 12 2018
1 2019-02-01 2330 Taiwan 78093827000 1 2019
2 2019-03-01 2330 Taiwan 60889055000 2 2019
3 2019-04-01 2330 Taiwan 79721587000 3 2019
4 2019-05-01 2330 Taiwan 74693615000 4 2019
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="StockDividendResult",
stock_id="2330",
date= "2019-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id country revenue revenue_month revenue_year
1: 2019-02-01 2330 Taiwan 78093827000 1 2019
2: 2019-03-01 2330 Taiwan 60889055000 2 2019
3: 2019-04-01 2330 Taiwan 79721587000 3 2019
4: 2019-05-01 2330 Taiwan 74693615000 4 2019
5: 2019-06-01 2330 Taiwan 80436931000 5 2019
6: 2019-07-01 2330 Taiwan 85867929000 6 2019