使用Tushare库下载股票数据

# -*- coding: utf-8 -*-
 
import tushare as ts
import matplotlib.pyplot as plt
import pandas as pd
#mytoken密令
tushareToken = 'd96c42438ba6bf1141f15b4adcfb59732baad32ca5a59d635e98f240'
#设定Token
ts.set_token(tushareToken)
#设定接口对象
pro = ts.pro_api()
# 读取Tushare的版本
vs = ts.__version__
print('当前tushare版本号为：%s'%vs)
#获取对应股票代码(xxxxxx.SH)
ts_code='601988'
# 获取历史复权数据(rehabilitation)：get_stock_basics
ret = ts.get_stock_basics()
# 公开上市首日：timeToMarket
tm = ret.ix[ts_code]['timeToMarket']
print('当前股票上市时间为：%s'%tm)

#hf = pro.index_basic('SSE',start='20060101')     ## 上证指数
#sf = ts.get_hist_data('399001',start='20060101')     ## 深证成指
sf = pro.daily(ts_code='399001.XSHG',start_date='20060101',end_date='20190519')
hs = ts.get_hist_data('399300',start='20060101')     ## 沪深300
#当前股票历史交易数据
df = pro.daily(ts_code=ts_code+'.SH',start_date='20060101',end_date='20190519')
# 显示最近的30笔交易数据,df.head()读取pandas DataFrame对象前N行数据
print('获取当前股票历史交易数据:\n%s'%df)
#保存当前股票历史交易数据
swingdata = []
for i in range(len(df)):
    swing_data = (df.iloc[i]['high'] - df.iloc[i]['low'])/df.iloc[i]['low']
    swingdata.append(swing_data)
    #保存当前股票历史交易数据
obj_series_list = pd.Series(swingdata)  # 通过列表创建series
df['swing'] = obj_series_list
data2csv = pd.DataFrame(sf)
data2csv.to_csv(r'C:\Users\28715\Desktop\predict/'+ts_code + '.csv',index = False)