Python查股價

請使用 Colab 練習

條件篩選股票

import requests

from io import StringIO

import pandas as pd

import numpy as np

#查詢日期

datestr = '20220819'

r = requests.post('http://www.twse.com.tw/exchangeReport/MI_INDEX?response=csv&date=' + datestr + '&type=ALL')

df = pd.read_csv(StringIO("\n".join([i.translate({ord(c): None for c in ' '})

for i in r.text.split('\n')

if len(i.split('",')) == 17 and i[0] != '='])), header=0 , thousands=",")

#條件篩選，5<本益比<15 且 收盤價<300 且 (成交股數/1000）>10000張

df.loc[(pd.to_numeric(df['本益比'], errors='coerce') < 15) & (pd.to_numeric(df['本益比'], errors='coerce') > 5) & (pd.to_numeric(df['收盤價'], errors='coerce') < 300) & (pd.to_numeric(df['成交股數'], errors='coerce')/1000 > 10000)]

畫個股1，5，20，60日平均線

#先安裝yfinance套件，只要裝一次即可

!pip install yfinance

#導入套件

import datetime

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

#設定爬蟲股票代號

sid = '2330'

#設定爬蟲時間，以日為單位

start = datetime.datetime.now() - datetime.timedelta(days=180)

end = datetime.date.today()

#導入pandas_datareader

from pandas_datareader import data

#導入fix_yahoo_finance

import yfinance as yf

#把資料抓到本機

yf.pdr_override()

# 取得股票資料，上櫃就改成.TWO

stock_yf = yf.download(sid+'.TW', start, end)

stock_yf.tail(10)

#如果加上如下這段就會畫出圖形

#線型圖，收盤價、5日均線、20日均線、60日均線

stock_yf['Adj Close'].plot(figsize=(16, 8))

stock_yf['Adj Close'].rolling(window=5).mean().plot(figsize=(16, 8), label='5_Day_Mean')

stock_yf['Adj Close'].rolling(window=20).mean().plot(figsize=(16, 8), label='20_Day_Mean')

stock_yf['Adj Close'].rolling(window=60).mean().plot(figsize=(16, 8), label='60_Day_Mean')

#顯示側標

plt.legend(loc='upper right', shadow=True, fontsize='x-large')

#顯示標題

plt.title(sid)

畫個股收盤價及成交量

#先安裝twstock套件，只要裝一次即可

!pip install twstock

import twstock as t

import pandas as p

import plotly.express as e


#在('')裡面 打股票代碼

stockID = '2330'

stock = t.Stock(stockID)

date = stock.date #日期

price = stock.price #收盤價

amount = stock.capacity #成交量


data = p.DataFrame({'日期':date, '收盤價':price})

result = e.line(data, x='日期', y='收盤價', title=stockID+'股價')

result.show()


data = p.DataFrame({'日期':date, '成交量':amount})

result = e.bar(data, x='日期', y='成交量', title=stockID+'成交量')

result.show()

畫個股K線圖

#先安裝twstock套件，只要裝一次即可

!pip install twstock

#m分鐘: 1m

#h小時: 1h

#d天: 1d

#wk週: 1wk

#mo月: 1mo

#y年: 1y


#period期間

#選項: 1d 5d 1mo 3mo 6mo 1y 2y 5y 10y


#interval間隔多久

#選項: 1m 2m 5m 15m 30m 60m 90m

import yfinance as y

import pandas as p

import plotly.graph_objects as g


#上市股: '股票代碼.tw'

#上櫃股: '股票代碼.two'

stockID = '2330.tw'

stock = y.download(stockID, period='1d', interval='1m')


data = stock.reset_index()

data.columns = ['現在時間', '開盤價', '最高價', '最低價', '收盤價', '調整後收盤價', '成交量']

data['現在時間'] = p.to_datetime(data['現在時間'].dt.strftime('%Y-%m-%d %H:%M'))

data['成交量'] //= 1000 #把單位從成交股數換成成交張數


result = g.Figure()


#成交量的圖

result.add_trace(

g.Bar(

name = '成交量',

x = data['現在時間'],

y = data['成交量'],

yaxis = 'y2',

marker_color = '#99ccff'

)

)


#k線圖

result.add_trace(

g.Candlestick(

name = '',

x = data['現在時間'],

open = data['開盤價'],

high = data['最高價'],

low = data['最低價'],

close = data['收盤價'],

increasing_line_color = '#fd5047',

increasing_fillcolor = '#f29696',

decreasing_line_color = '#3d9970',

decreasing_fillcolor = '#91c2b3'

)

)


result.update_layout(

title = stockID,

hovermode = 'x unified', #滑鼠停在圖上的時候會有資訊卡

#xaxis_rangeslider_visible = False, #x軸座標的小圖，可以用來滑動上面的圖


yaxis = dict(

title = '股價'

),


yaxis2 = dict(

overlaying = 'y',

visible = False

),


font = dict(

size = 10

)

)


result.show()

畫個股K，D線

Python wrapper for TA-Lib (http://ta-lib.org/)
https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html

#Colab安裝Talib的解法

!wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz

!tar -xzvf ta-lib-0.4.0-src.tar.gz

%cd ta-lib

!./configure --prefix=/usr

!make

!make install

!pip install Ta-Lib

import talib

#先安裝yfinance套件，只要裝一次即可

!pip install yfinance

#導入套件

import datetime

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

#設定爬蟲股票代號

sid = '2330'

#設定爬蟲時間，以日為單位

start = datetime.datetime.now() - datetime.timedelta(days=180)

end = datetime.date.today()

#導入pandas_datareader

from pandas_datareader import data

#導入fix_yahoo_finance

import yfinance as yf

#finance

import talib

#把資料抓到本機

yf.pdr_override()

# 取得股票資料，上櫃就改成.TWO

stock_yf = yf.download(sid+'.TW', start, end)

#算出K，D值

stock_yf['k'], stock_yf['d'] = talib.STOCH(stock_yf['High'],

stock_yf['Low'],

stock_yf['Close'],

fastk_period=5,

slowk_period=3,

slowk_matype=0,

slowd_period=3,

slowd_matype=0)

#算出RSI值

stock_yf['rsi5']=talib.RSI(stock_yf['Close'], timeperiod=5)

stock_yf['rsi10']=talib.RSI(stock_yf['Close'], timeperiod=10)


stock_yf["upper"],stock_yf["middle"],stock_yf["lower"] = talib.BBANDS(stock_yf["Close"], timeperiod=20, nbdevup=2.1, nbdevdn=2.1, matype=0)

stock_yf

#畫出KD線

stock_yf['k'].rolling(window=1).mean().plot(figsize=(16, 8), label='k')

stock_yf['d'].rolling(window=1).mean().plot(figsize=(16, 8), label='d')
#畫出rsi5及rsi10線

stock_yf['rsi5'].rolling(window=1).mean().plot(figsize=(16, 8), label='rsi5')

stock_yf['rsi10'].rolling(window=1).mean().plot(figsize=(16, 8), label='rsi10')


#顯示側標

plt.legend(loc='upper left', shadow=True, fontsize='x-large')

#顯示標題

plt.title(sid)