Tema and ema gives nan as output :(

I am getting nan values for tema and ema calculation where as i am getting the required values for sma calculation.Below is my code snippet in init method:
def __init__(self): self.datetime = self.datas[0].datetime self.dataclose = self.datas[0].close self.dataopen = self.datas[0].open self.datahigh = self.datas[0].high self.datalow = self.datas[0].low self.datavolume=self.datas[0].volume self.volsma20=bt.indicators.SMA(self.datavolume,period=20) self.volsma20talib=bt.talib.SMA(self.datavolume,timeperiod=20) self.rsi=bt.indicators.RSI(self.volsma20,period=14) self.rsitalib=bt.talib.RSI(self.volsma20talib,timeperiod=14) self.tema200=bt.indicators.TripleExponentialMovingAverage(self.dataclose,period=200) self.ema1=EMA(self.dataclose,period=200)

@runout
Apparently the file has ohlcv and it gives sma but no ema.
If i use another file which only has ohlc then it gives the ema details.What is the correlation of this volume thing?
Why does it not give the ema details if volume is introduced along with the ohlc? 
@bismoy said in Tema and ema gives nan as output :(:
I am getting nan values for tema and ema calculation where as i am getting the required values for sma calculation.Below is my code snippet in init method:
I don't see a formula for tema and ema. I see formulas for:
self.tema200=bt.indicators.TripleExponentialMovingAverage(self.dataclose,period=200) self.ema1=EMA(self.dataclose,period=200)
Are these what you are referring to? Can you be specific about what line you are referring to, if you are importing a library show the import statements, and if we are to compare two different data sets, please include the top few lines from each including the headers. Thanks.

@runout yes thats what i was referring to.However i am noticing certain issues with the file as well which may be leading to the issue
when i am sampling 1 min tf to 5 min tf,i notice empty rows are coming for saturday and sunday.
How can i remove those as i have already tried
df.dropna(inplace=True) without any luck.Here df=pandas dataframe