adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Split parse_ticker_dataframe some logic to clean_ohlcv_dataframe.

Browse Source
This commit is contained in:
Matthias 2019-12-25 13:24:09 +01:00
parent 1b90ec58b9
commit d9e7d64f33
1 changed files with 24 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
freqtrade/data/converter.py
View File

@ -37,9 +37,29 @@ def parse_ticker_dataframe(ticker: list, timeframe: str, pair: str, *,
# and fail with exception...
frame = frame.astype(dtype={'open': 'float', 'high': 'float', 'low': 'float', 'close': 'float',
'volume': 'float'})
return clean_ohlcv_dataframe(frame, timeframe, pair,
fill_missing=fill_missing,
drop_incomplete=drop_incomplete)
def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *,
fill_missing: bool = True,
drop_incomplete: bool = True) -> DataFrame:
"""
Clense a ohlcv dataframe by
* Grouping it by date (removes duplicate tics)
* dropping last candles if requested
* Filling up missing data (if requested)
:param data: DataFrame containing ohlcv data.
:param timeframe: timeframe (e.g. 5m). Used to fill up eventual missing data
:param pair: Pair this data is for (used to warn if fillup was necessary)
:param fill_missing: fill up missing candles with 0 candles
(see ohlcv_fill_up_missing_data for details)
:param drop_incomplete: Drop the last candle of the dataframe, assuming it's incomplete
:return: DataFrame
"""
# group by index and aggregate results to eliminate duplicate ticks
frame = frame.groupby(by='date', as_index=False, sort=True).agg({
data = data.groupby(by='date', as_index=False, sort=True).agg({
'open': 'first',
'high': 'max',
'low': 'min',
@ -48,13 +68,13 @@ def parse_ticker_dataframe(ticker: list, timeframe: str, pair: str, *,
})
# eliminate partial candle
if drop_incomplete:
frame.drop(frame.tail(1).index, inplace=True)
data.drop(data.tail(1).index, inplace=True)
logger.debug('Dropping last candle')
if fill_missing:
return ohlcv_fill_up_missing_data(frame, timeframe, pair)
return ohlcv_fill_up_missing_data(data, timeframe, pair)
else:
return frame
return data
def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) -> DataFrame: