Share New Research 
import pandas as pd
qb = QuantBook()
symbol = qb.AddEquity("gsus",fillDataForward = False).Symbol
# Fetch history
history = qb.History([symbol], 75, Resolution.Daily)
# Fetch price
total_price = history.loc[symbol].low
pd.set_option('display.max_rows', total_price.shape[0]+1)
print (total_price.shape[0])
print (total_price)
No data is available on 5-6 Aug but fillDataForward = False returns the same results as fillDataForward = True, any reason for that?
Noticed that for both fillDataForward = True/False, OHLC of NaN data will return the following:
Close = Previous Close
Open = Previous Open
High = Max (Open, Close)
Low = Min (Open, Close)
I wish to get the fillforward below instead, can advise? Thanks.
Close = Previous Close
Open = Previous Close
High = Max (Open, Close)
Low = Min (Open, Close)
Zc Yong
anyone can help?
Shile Wen
Hi Zc,
The reason fillDataForward=True and fillDataForward=False give us the same results is because Lean doesn't support named arguments (sorry coming soon!). Instead of typing out the method with all of the arguments, we can instead address this using the built-in pandas DataFrame fillna or dropna (if you wanted to delete the rows altogether) methods:
import pandas as pd
qb = QuantBook()
symbol = qb.AddEquity("gsus", fillforward=True).Symbol
# Fetch history
history = qb.History([symbol], 75, Resolution.Daily)
history = history.fillna(method='ffill')
# history = history.dropna() # alternative
history.isna().any()
For the method that uses the full method constructor:
qb = QuantBook()
symbol = qb.AddEquity("gsus", Resolution.Daily, Market.USA, True, 1, False).Symbol
history = qb.History([symbol], 75, Resolution.Daily)
history.isna().any()
Please see the attached notebook for reference.
Best,
Shile Wen
Zc Yong
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