Software Engineer Snippet

from pandas_datareader import data as web from mpl_finance import candlestick_ohlc from matplotlib import pyplot as plt from matplotlib import style import matplotlib.dates as mdates import yfinance as yf import datetime as dt import pandas as pd import numpy as np import time style.use('dark_background') yf.pdr_override() ma1 = 5 ma2 = 20 print('Stock Number:') stock_no = input() csv_file = '/users/jht/Desktop/python/stockData/'+stock_no+'.csv' start = dt.datetime(2020, 1, 1) end = dt.datetime.now() df = web.get_data_yahoo(stock_no + '.TW', start, end) df.to_csv(csv_file) time.sleep(2) data = pd.read_csv(csv_file, parse_dates=True, index_col='Date') data.head() close = data["Close"] avg = sum(close)/len(close) top = plt.subplot2grid((21, 9), (0, 0), rowspan=9, colspan=9)#整個畫面共有(21row,9col),其位於(0row,0col),此占各9row&col bottom = plt.subplot2grid((21, 9), (12, 0), rowspan=3, colspan=9, sharex=top) bottom1 = plt.subplot2gr...

  from matplotlib import pyplot as plt from matplotlib import style from pandas_datareader import data as web import yfinance as yf #需要yf.pdr_override() import pandas as pd import datetime as dt import csv yf.pdr_override() print ( 'Stock Number:' ) stock_no = input () csv_file = '/users/jht/Desktop/python/stockData/' +stock_no+ '.csv' start = dt.datetime( 2017 , 6 , 14 ) end = dt.datetime( 2020 , 9 , 1 ) get = web.get_data_yahoo(stock_no+ '.TW' , start , end) get.to_csv(csv_file) #得到的數據匯入csv檔 data = pd.read_csv(csv_file , parse_dates = True, index_col = 'Date' ) #以index_col對應依據 price = data[ 'Close' ] data = data.reset_index() #回到最初 plt.plot(price) plt.show()

from matplotlib import pyplot as plt from matplotlib import style import pandas as pd import csv #python內建 style.use( 'ggplot' ) #txt轉成csv #讀取數據 txtPath = '/users/jht/Desktop/python/stockData/2330.txt' readTxt = csv.reader( open (txtPath , 'r' ) , delimiter = ',' ) #以','符號定界分行delimiter #匯入並創建csv檔案 cvsPath = '/users/jht/Desktop/python/stockData/2330.csv' writeCsv = csv.writer( open (cvsPath , 'w' )) writeCsv.writerow([ 'NO' , 'price' ]) #設定row heaer writeCsv.writerows(readTxt) #匯入txt x=[] y=[] with open (txtPath , 'r' ) as txt2330: #以r唯讀，打開檔案，呼叫用txt2330 plots = csv.reader(txt2330 , delimiter = ',' ) for row in plots: x.append( float (row[ 0 ])) y.append( float (row[ 1 ])) plt.subplot( 211 ) plt.plot(x , y) plt.subplot( 212 ) data = pd.read_csv(cvsPath , parse_dates = True, index_col = 'NO' ) #以parse_dates判定x,y個數相等 print (data.head()) plt.plot(data[ 'price' ] , ...

from matplotlib import pyplot as plt from matplotlib import style style.use( 'ggplot' ) #設定背景 x = [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ] y = [ 18 , 21 , 4 , 3 , 45 , 17 , 16 , 5 , 6 ] x2 = [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ] y2 = [ 17 , 28 , 14 , 16 , 15 , 13 , 1 , 5 , 6 ] plt.subplot( 211 ) #有2個圖表，第1個顯示在第1位 plt.plot(x , y , linewidth = 3 , marker = 'o' , label = 'truthValue' ) plt.plot(x2 , y2 , color = 'y' , label = 'prediction' ) plt.legend() plt.subplot( 212 ) #有2個圖表，第1個顯示在第2位 plt.bar(x , y , align = 'center' , label = 'truthValue' ) plt.bar(x2 , y2 , align = 'center' , label = 'prediction' ) #marker轉折點符號 plt.legend() plt.ylabel( 'price' ) plt.xlabel( 'date' ) plt.show()

☝python upgrade 1.brew upgrade python 2.echo "alias python=/usr/local/bin/python3.8" >> ~/.zshrc 版本太多， 以為打python3 -m 就可以解決一切，但還是 有抓前版本的 package ， so最好將python全刪，再重新安裝: /usr/local/bin/下的 全部的python /Library/Python /Library/Frameworks/Python.framework ☝  pip 套件管理員 curl https : // bootstrap . pypa . io / get - pip . py - o get - pip . py python get - pip . py ☝venv環境工作管理員 ☝ conda 安裝  = pip + venv 在安裝時我自選習慣儲存的位置:/usr/local package安裝 ☝matplotlib //可產生多種不同繪圖類型,  嵌入繪圖， 其數值數學(數據分析)擴展包  NumPy 的可視化操作界面 ☝mpl_finance ☝numpy ☝pandas //python 的 Excel；pandas-datareader用來獲取資料 ☝pandas-datareader ☝yfinance yahoo股市資料 # import yfinance as yf