#%%#先引入后面可能用到的包（package） import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns sns.set() %matplotlib inline #正常顯示畫圖時(shí)出現(xiàn)的中文和負(fù)號(hào) from pylab import mpl mpl.rcParams['font.sans-serif']=['SimHei'] mpl.rcParams['axes.unicode_minus']=False #使用tushare獲取交易數(shù)據(jù) #設(shè)置token import tushare as ts token='' ts.set_token(token) pro=ts.pro_api(token) #pro=ts.pro_api(token) index={'上證綜指': '000001.SH','深證成指': '399001.SZ','滬深300': '000300.SH','創(chuàng)業(yè)板指': '399006.SZ','上證50': '000016.SH','中證500': '000905.SH','中小板指': '399005.SZ','上證180': '000010.SH'} #獲取當(dāng)前交易的股票代碼和名稱 def get_code():df = pro.stock_basic(exchange='', list_status='L')codes=df.ts_code.valuesnames=df.name.valuesstock=dict(zip(names,codes))#合并指數(shù)和個(gè)股成一個(gè)字典stocks=dict(stock,**index)return stocks #獲取行情數(shù)據(jù) def get_data(stock,start='20151009',end=''):#如果代碼在字典index里，則取的是指數(shù)數(shù)據(jù)code=get_code()[stock]if code in index.values():df=ts.pro_bar(ts_code=code,asset='I',start_date=start, end_date=end)#否則取的是個(gè)股數(shù)據(jù)else:df=ts.pro_bar(ts_code=code, adj='qfq',start_date=start, end_date=end)#將交易日期設(shè)置為索引值df.index=pd.to_datetime(df.trade_date)df=df.sort_index()return df import tushare as ts import pandas as pd import timedef maintask():pro = ts.pro_api()#獲取基礎(chǔ)信息數(shù)據(jù)，包括股票代碼，名稱，上市日期，退市日期等pool = pro.stock_basic(exchange='',list_status = 'L',adj = 'qfq',fields = 'ts_code,symbol,name,area,industry,fullname,list_date,market,exchange,is_hs')#print(pool.head()) print('獲得上市股票總數(shù)：',len(pool)-1)j=1for i in pool.ts_code:print('正在獲取第%d家，股票代碼%s' %(j,i))#接口限制訪問(wèn)200次/分鐘，加一點(diǎn)微小的延時(shí)防止被bantime.sleep(0.301)j += 1df = pro.daily(ts_code=i,start_date = startdate,end_date = enddate,fields = 'ts_code,trade_date,open,high,low,close,pre_close,change,pct_chg,vol,amount')#print(df.head())writer = pd.ExcelWriter(i + '.xlsx')df.to_excel(writer,sheet_name= i + '',index=False)if __name__== '__main__':#設(shè)置起始日期startdate='19980101'enddate='20200224'#主程序maintask()

總結(jié)

以上是生活随笔為你收集整理的获取所有股票数据的全部?jī)?nèi)容，希望文章能夠幫你解決所遇到的問(wèn)題。

如果覺(jué)得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。