Hi! I'm trying to add the Keltner Channels indicator as an extra filter for my universe selection, but I seem to be encountering some problems. Before trying to add the keltner indicator, I was only constructing EMAs and an RSI indicator to use for my universe selection, but I wasn't encountering this problem then with just these indicators. After trying to add the Keltner Channel, I encounter this error:

Runtime Error: TypeError : 'Timestamp' object does not support indexing
at <lambda> in FundamentalUniverseSelectionModel.py:46
TypeError : 'Timestamp' object does not support indexing (Open Stacktrace)

This is the class constructor:

class SelectionData():

def __init__(self, history):

self.slow = ExponentialMovingAverage(200)
self.fast = ExponentialMovingAverage(50)
self.keltner = KeltnerChannels(10, 2, MovingAverageType.Simple)

for bar in history.itertuples():

tradeBar = TradeBar(bar.Index[1], bar.Index[0], bar.open, bar.high, bar.low, bar.close, bar.volume, timedelta(1))

self.fast.Update(bar.Index[1], bar.close)
self.slow.Update(bar.Index[1], bar.close)

def is_ready(self):

return self.slow.IsReady and self.fast.IsReady and self.keltner.IsReady

def update(self, time, price):

self.fast.Update(time, price)
self.slow.Update(time, price)

And how I apply it to the symbols:


for security in sortedByDollarVolume:

symbol = security.Symbol
dollar = self.dollarVolumeBySymbol[symbol]
price = self.AdjustedPrice[symbol]

if symbol in history_symbols:

if not str(symbol) in history.index:

self.averages[symbol] = SelectionData(history.loc[symbol])

self.averages[symbol].update(algorithm.Time, price)
selected[symbol] = dollar


I'm stumped.. I followed the suggestion here: 


Thank you!