[Python]利用ricequant获取上证指数以及所有股票历史价格数据 |
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[Python]利用ricequant获取上证指数以及所有股票历史价格数据
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1、准备工作 网址：https://www.ricequant.com 点击“研究”，点击右上方的“新建”，选择Python3.
2、代码 1)获取所有股票从起始记录时间至今的全部价格数据。详细api可以参考：https://www.ricequant.com/api/research/chn #ClosingPx import pandas as pd datas = all_instruments(type='CS', country='cn') list = datas['order_book_id'].tolist() df1 = pd.DataFrame(columns = list) df1.loc[0] = datas['symbol'].tolist() df2 = pd.DataFrame(columns = list) for id in list: df2[id] = get_price(id,start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['ClosingPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('stoneClosingPx_0809.csv') #PreClosingPx import pandas as pd datas = all_instruments(type='CS', country='cn') list = datas['order_book_id'].tolist() df1 = pd.DataFrame(columns = list) df1.loc[0] = datas['symbol'].tolist() df2 = pd.DataFrame(columns = list) for id in list: df2[id] = get_price(id,start_date='2013-01-04', end_date='2017-08-09', adjust_type='pre')['ClosingPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('stonePreClosingPx_0809.csv') #OpeningPx import pandas as pd datas = all_instruments(type='CS', country='cn') list = datas['order_book_id'].tolist() df1 = pd.DataFrame(columns = list) df1.loc[0] = datas['symbol'].tolist() df2 = pd.DataFrame(columns = list) for id in list: df2[id] = get_price(id, start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['OpeningPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('stoneOpeningPx_0809.csv') #HighPx import pandas as pd datas = all_instruments(type='CS', country='cn') list = datas['order_book_id'].tolist() df1 = pd.DataFrame(columns = list) df1.loc[0] = datas['symbol'].tolist() df2 = pd.DataFrame(columns = list) for id in list: df2[id] = get_price(id, start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['HighPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('stoneHighPx_0809.csv') #LowPx import pandas as pd datas = all_instruments(type='CS', country='cn') list = datas['order_book_id'].tolist() df1 = pd.DataFrame(columns = list) df1.loc[0] = datas['symbol'].tolist() df2 = pd.DataFrame(columns = list) for id in list: df2[id] = get_price(id,start_date='2013-01-04', end_date='2016-12-28', adjust_type='none')['LowPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('stoneLowPx_0809.csv')
2)获取上证指数 #shanghai import pandas as pd df1 = pd.DataFrame(columns = ['000001.XSHG']) df1.loc[0] = '上证指数' df2 = pd.DataFrame(columns = ['000001.XSHG']) df2['000001.XSHG'] = get_price('000001.XSHG', start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['HighPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('shanghaiHighPx_0809.csv') import pandas as pd df1 = pd.DataFrame(columns = ['000001.XSHG']) df1.loc[0] = '上证指数' df2 = pd.DataFrame(columns = ['000001.XSHG']) df2['000001.XSHG'] = get_price('000001.XSHG', start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['LowPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('shanghaiLowPx_0809.csv') import pandas as pd df1 = pd.DataFrame(columns = ['000001.XSHG']) df1.loc[0] = '上证指数' df2 = pd.DataFrame(columns = ['000001.XSHG']) df2['000001.XSHG'] = get_price('000001.XSHG', start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['ClosingPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('shanghaiClosingPx_0809.csv') import pandas as pd df1 = pd.DataFrame(columns = ['000001.XSHG']) df1.loc[0] = '上证指数' df2 = pd.DataFrame(columns = ['000001.XSHG']) df2['000001.XSHG'] = get_price('000001.XSHG', start_date='2013-01-04', end_date='2017-08-09', adjust_type='pre')['ClosingPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('shanghaiPreClosingPx_0809.csv') import pandas as pd df1 = pd.DataFrame(columns = ['000001.XSHG']) df1.loc[0] = '上证指数' df2 = pd.DataFrame(columns = ['000001.XSHG']) df2['000001.XSHG'] = get_price('000001.XSHG', start_date='2013-01-04', end_date='2017-08-09', adjust_type='none')['OpeningPx'] frames = [df1, df2] result = pd.concat(frames) result.to_csv('shanghaiOpeningPx_0809.csv') 3、运行选中所有代码，同时按住ctrl+enter即可。结果会生成在和代码相同的页面。
结果格式如下：
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