技術面
在台股技術面，我們擁有 6 種資料集，如下:
- 台灣股價資料表 TaiwanStockPrice
- 台灣股價及時資料表 TaiwanStockPriceMinute
- 台灣即時最佳五檔 TaiwanStockPriceMinuteBidAsk
- 台灣個股PER、PBR資料表 TaiwanStockPER
- 每5秒委託成交統計 StatisticsOfOrderBookAndTrade
- 台股加權指數 TaiwanVariousIndicators5Seconds
根據上述資料表逐一說明怎麼使用，另外具體資料表 schemas 請參考 finmindapi
台股總覽 TaiwanStockInfo¶
- 這張資料表主要是列出台灣所有上市上櫃的股票名稱，代碼和產業類別
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockInfo",
}
resp = requests.get(url, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
industry_category stock_id stock_name type
0 ETF 0050 元大台灣50 twse
1 ETF 0051 元大中型100 twse
2 ETF 0052 富邦科技 twse
3 ETF 0053 元大電子 twse
4 ETF 0054 元大台商50 twse
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(dataset = "TaiwanStockInfo")
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
industry_category stock_id stock_name type
1: ETF 0050 元大台灣50 twse
2: ETF 0051 元大中型100 twse
3: ETF 0052 富邦科技 twse
4: ETF 0053 元大電子 twse
5: ETF 0054 元大台商50 twse
6: ETF 0055 元大MSCI金融 twse
股價日成交資訊 TaiwanStockPrice¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockPrice",
"stock_id": "2330",
"date": "2020-04-02",
"end_date": "2020-04-12",
}
resp = requests.get(url, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
date stock_id Trading_Volume Trading_money open max min close spread Trading_turnover
0 2020-04-06 2330 59712754 16324198154 273.0 275.5 270.0 275.5 4.0 19971
1 2020-04-07 2330 48887346 13817936851 283.5 284.0 280.5 283.0 8.5 24281
2 2020-04-08 2330 38698826 11016972354 285.0 285.5 283.0 285.0 2.0 19126
3 2020-04-09 2330 29276430 8346209654 287.5 288.0 282.5 283.0 -2.0 15271
4 2020-04-10 2330 28206858 7894277586 280.0 282.0 279.0 279.5 -3.5 15833
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockPrice",
stock_id= "2330",
date= "2020-04-02",
end_date= "2020-04-08"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id Trading_Volume Trading_money open max min close spread Trading_turnover
1: 2020-04-06 2330 59712754 16324198154 273.0 275.5 270.0 275.5 4.0 19971
2: 2020-04-07 2330 48887346 13817936851 283.5 284.0 280.5 283.0 7.5 24281
3: 2020-04-08 2330 38698826 11016972354 285.0 285.5 283.0 285.0 2.0 19126
即時股價 TaiwanStockPriceMinute¶
- 輸入 dataset、stock_id 參數，會回傳當天最近 100 筆即時資料。
- 輸入 dataset、stock_id、date，會回傳 date 當天 data。
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockPriceMinute",
"stock_id": "2330"
}
resp = requests.get(url, params=parameter)
data = resp.json()
data = pd.DataFrame(data["data"])
print(data.head())
date stock_id deal_price volume
0 2020-01-02 09:00:00 2330 332.5 520
1 2020-01-02 09:00:05 2330 333.0 45
2 2020-01-02 09:00:10 2330 333.0 22
3 2020-01-02 09:00:15 2330 333.0 15
4 2020-01-02 09:00:20 2330 333.5 3
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanStockPriceMinute",
stock_id= "2330"
)
)
data = content(response)
df = do.call('cbind',data$data) %>%
data.table
head(df)
date stock_id deal_price volume Time
1: 2020-01-02 2330 332.5 520 09:00:00.000000000
2: 2020-01-02 2330 333.0 45 09:00:05.000000000
3: 2020-01-02 2330 333.0 22 09:00:10.000000000
4: 2020-01-02 2330 333.0 15 09:00:15.000000000
5: 2020-01-02 2330 333.5 3 09:00:20.000000000
6: 2020-01-02 2330 333.0 20 09:00:25.000000000
即時最佳五檔 TaiwanStockPriceMinuteBidAsk¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockPriceMinuteBidAsk",
"stock_id": "2330",
}
resp = requests.get(url, params=parameter)
data = resp.json()["data"]
if data['date'] == []:
data.pop('date', None)
data = pd.DataFrame(data)
print(data.head())
stock_id AskPrice AskVolume BidPrice BidVolume Time
0 2330 [292.5, 293.0, 293.5, 294.0, 294.5] [174, 452, 245, 602, 291] [292.0, 291.5, 291.0, 290.5, 290.0] [67, 236, 1109, 1505, 7097] 13:24:54.559711
1 2330 [292.5, 293.0, 293.5, 294.0, 294.5] [174, 452, 245, 602, 291] [292.0, 291.5, 291.0, 290.5, 290.0] [67, 236, 1112, 1505, 7097] 13:24:54.568170
2 2330 [292.5, 293.0, 293.5, 294.0, 294.5] [174, 452, 245, 602, 291] [292.0, 291.5, 291.0, 290.5, 290.0] [67, 236, 1114, 1505, 7097] 13:24:54.592893
3 2330 [292.5, 293.0, 293.5, 294.0, 294.5] [174, 452, 245, 602, 291] [292.0, 291.5, 291.0, 290.5, 290.0] [67, 236, 1114, 1506, 7097] 13:24:54.598656
4 2330 [292.5, 293.0, 293.5, 294.0, 294.5] [174, 452, 245, 602, 291] [292.0, 291.5, 291.0, 290.5, 290.0] [67, 236, 1116, 1506, 7097] 13:24:54.907709
個股PER、PBR資料表 TaiwanStockPER¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanStockPER",
"stock_id": "2330",
"date": "2020-04-01",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date stock_id dividend_yield PER PBR
0 2020-04-01 2330 3.5 20.38 4.34
1 2020-04-06 2330 3.45 20.68 4.41
2 2020-04-07 2330 3.36 21.25 4.53
3 2020-04-08 2330 3.33 21.4 4.56
4 2020-04-09 2330 3.36 21.25 4.53
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(url = url,
query = list(
dataset="TaiwanStockPER",
stock_id= "2330",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
date stock_id dividend_yield PER PBR
1: 2020-01-02 2330 2.36 26.69 5.54
2: 2020-01-03 2330 2.36 26.73 5.55
3: 2020-01-06 2330 2.41 26.14 5.42
4: 2020-01-07 2330 2.43 25.94 5.38
5: 2020-01-08 2330 2.43 25.94 5.38
6: 2020-01-09 2330 2.37 26.57 5.51
每5秒委託成交統計 StatisticsOfOrderBookAndTrade¶
(由於資料量過大，只提供 date 當天 data)
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "StatisticsOfOrderBookAndTrade",
"date": "2020-04-01",
}
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/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="StatisticsOfOrderBookAndTrade",
date= "2020-01-02"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)
加權指數 TaiwanVariousIndicators5Seconds¶
Example
import requests
import pandas as pd
url = "https://api.finmindtrade.com/api/v3/data"
parameter = {
"dataset": "TaiwanVariousIndicators5Seconds",
"date": "2020-07-01",
"end_date": "2020-07-27",
}
data = requests.get(url, params=parameter)
data = data.json()
data = pd.DataFrame(data['data'])
print(data.head())
date TAIEX
0 2020-07-01 09:00:00 11621.2
1 2020-07-01 09:00:05 11622.6
2 2020-07-01 09:00:10 11632.4
3 2020-07-01 09:00:15 11643.5
4 2020-07-01 09:00:20 11644.2
library(httr)
library(data.table)
library(dplyr)
url = 'https://api.finmindtrade.com/api/v3/data'
response = httr::GET(
url = url,
query = list(
dataset="TaiwanVariousIndicators5Seconds",
date="2020-07-01",
end_date= "2020-07-27"
)
)
data = content(response)
df = data$data %>%
do.call('rbind',.) %>%
data.table
head(df)