From a021cd3ae2755f889c0fd47af25b202cc0326ce9 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 30 Dec 2018 16:07:47 +0100
Subject: [PATCH] Add ohlcv data interpolator

---
 freqtrade/data/converter.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py
index ee915ec19..71a7e35a4 100644
--- a/freqtrade/data/converter.py
+++ b/freqtrade/data/converter.py
@@ -5,6 +5,8 @@ import logging
 import pandas as pd
 from pandas import DataFrame, to_datetime
 
+from freqtrade.constants import TICKER_INTERVAL_MINUTES
+
 logger = logging.getLogger(__name__)
 
 
@@ -36,6 +38,35 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
     return frame
 
 
+def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str) -> DataFrame:
+    """
+    Fills up missing data with 0 volume rows,
+    using the previous close as price for "open", "high" "low" and "close", volume is set to 0
+
+    """
+    ohlc_dict = {
+        'open': 'first',
+        'high': 'max',
+        'low': 'min',
+        'close': 'last',
+        'volume': 'sum'
+    }
+    tick_mins = TICKER_INTERVAL_MINUTES[ticker_interval]
+    # Resample to create "NAN" values
+    df = dataframe.resample(f'{tick_mins}min', on='date').agg(ohlc_dict)
+
+    # Forwardfill close for missing columns
+    df['close'] = df['close'].fillna(method='ffill')
+    # Use close for "open, high, low"
+    df.loc[:, ['open', 'high', 'low']] = df[['open', 'high', 'low']].fillna(
+        value={'open': df['close'],
+               'high': df['close'],
+               'low': df['close'],
+               })
+    df.reset_index(inplace=True)
+    return df
+
+
 def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
     """
     Gets order book list, returns dataframe with below format per suggested by creslin