Extending Pandas Dataframe with string/datetime column values.

[Dastaan Sharma]

Hi BT community,
I need help regarding extending Pandas Datafeed:

My dataframe looks like this :

 	open 	high 	low 	close 	volume 	expiry
time_stamp 						
2015-04-01 09:15:00 	18250.00 	18315.00 	18226.15 	18295.00 	222650 	2015-04-30
2015-04-01 09:30:00 	18295.00 	18299.50 	18261.55 	18278.00 	66875 	2015-04-30
2015-04-01 09:45:00 	18275.20 	18358.95 	18266.95 	18345.05 	162800 	2015-04-30
2015-04-01 10:00:00 	18345.05 	18390.00 	18332.60 	18374.95 	146525 	2015-04-30
2015-04-01 10:15:00 	18375.00 	18411.65 	18361.35 	18383.20 	119875 	2015-04-30

I have tried to figure this out by myself but would love help .

class custom(bt.feeds.PandasData):
    
    lines = ('open', 'high', 'low', 'close', 'volume',
             'expiry',
            )
    
    params = (
        ('open', -1),
        ('high', -1),
        ('low', -1),
        ('close', -1),
        ('volume', -1),
        ('expiry', -1),
    )

How can I use string/datetime as lines ?

[backtrader]

@Dastaan-Sharma said in Extending Pandas Dataframe with string/datetime column values.:

How can I use string/datetime as lines ?

You cannot. It it's a timestamp, encode it to be a float (for a date the integral part of the number should be enough for most practical uses)

[Dastaan Sharma]

Ah Alright.
It is better to apply

date2num

Solved my problem though.

[tianjixuetu]

@Dastaan-Sharma maybe using PandasDirectData is a better way.

[Dastaan Sharma]

@tianjixuetu
Thanks. Your analysis is really helpful for me.