Example: obtaining all ticks in csv files starting with bu1601 in the directory /tick2016/bu/
from IOUtils import *
df_reader('bu1601*', topdir='../tick2016/bu/').get_tick(raw=True)
Results:
| Time | InstrumentID | Date | TimeStamp | LastPrice | HighPrice | LowPrice | Volume | Turnover | AccVolume | AccTurnover | SettlePrice | OpenInterest | AskPrice1 | AskPrice2 | AskPrice3 | AskPrice4 | AskPrice5 | AskVolume1 | AskVolume2 | AskVolume3 | AskVolume4 | AskVolume5 | BidPrice1 | BidPrice2 | BidPrice3 | BidPrice4 | BidPrice5 | BidVolume1 | BidVolume2 | BidVolume3 | BidVolume4 | BidVolume5 | Type | AveragePrice | UpperLimitPrice | LowerLimitPrice | UpdateTime |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-01-04 18:33:30.967000 | bu1601 | 20160104 | 1.4519e+12 | 1630 | 1630 | 1630 | 0 | -1 | 0 | 0 | -1 | 20284 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | -1 | 0 | 1734 | 1536 | 18:33:30.967 |
| 2016-01-04 18:33:31.500000 | bu1601 | 20160104 | 1.4519e+12 | 1630 | 1630 | 1630 | 0 | 0 | 0 | 0 | -1 | 20284 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | -1 | 0 | 1734 | 1536 | 18:33:31.500 |
Note: It doesn't work for night market ticks yet.
Line 91: In df_reader.f_fill, the sampling index is hard-coded for day markets.
from IOUtils import *
df_reader('bu1601*', topdir='../tick2016/bu/day/').get_tick(raw=false)
| InstrumentID | Date | TimeStamp | LastPrice | HighPrice | LowPrice | Volume | Turnover | AccVolume | AccTurnover | SettlePrice | OpenInterest | AskPrice1 | AskPrice2 | AskPrice3 | AskPrice4 | AskPrice5 | AskVolume1 | AskVolume2 | AskVolume3 | AskVolume4 | AskVolume5 | BidPrice1 | BidPrice2 | BidPrice3 | BidPrice4 | BidPrice5 | BidVolume1 | BidVolume2 | BidVolume3 | BidVolume4 | BidVolume5 | Type | AveragePrice | UpperLimitPrice | LowerLimitPrice | UpdateTime | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-01-04 09:00:00 | bu1601 | 2.01601e+07 | 1.45187e+12 | 1702 | 1702 | 1702 | 4 | 68080 | 4 | 68080 | -1 | 22640 | 1718 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 0 | 1700 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | -1 | 1702 | 1812 | 1606 | 08:59:00.500 |
| 2016-01-04 09:00:30 | bu1601 | 2.01601e+07 | 1.45187e+12 | 1706 | 1724 | 1702 | 0 | 0 | 70 | 1.2012e+06 | -1 | 22666 | 1708 | 0 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 1706 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | -1 | 1716 | 1812 | 1606 | 09:00:30.000 |
use_case: df_reader(filepat='ag1712*', topdir='../ag/day', offset=5, freq='30S'), where offset is in minutes (offset=5 means that it starts 5 minutes after opening 9 AM) and frequency is in 30 seconds.
use_case: df_reader(filepat='ag1712*', topdir='../ag/night', offset=5, freq='30S', session = 'Night'), default value for session is 'Day'
use_case: IOUtils_v1.df_reader(filepat='rb1712*', topdir='../rb/day', offset=1./60., freq='2T', day=True, symbol='rb').get_tick(), where the start time is 09:00:01 AM. The night trade is implemented for all four symbols.
- Automatically extract symbol from csv files
- Automatically extract day/night trading from csv files
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent