otp.LoadTicksFromDataFrame#

class LoadTicksFromDataFrame(dataframe=None, timestamp_column=utils.adaptive, symbol_name_field=None, symbol=utils.adaptive, db=utils.adaptive_to_default, tick_type=utils.adaptive)#

Bases:

Load pandas.DataFrame as data source

Relies on otp.Ticks. So unlike onetick.py.ReadFromDataFrame() filtering by symbols via symbols parameter in otp.run don’t affect output.

Also, it can be used in older OneTick versions.

Parameters:

dataframe (pandas.DataFrame) – Pandas DataFrame to load.
timestamp_column (str, optional) –
Column containing time info.

If parameter not set and DataFrame has one of columns TIME or Timestamp (case-insensitive), it will be automatically used as timestamp_column. To disable this, set timestamp_column=None.

Timestamp column dtype should be either datetime related or string.
symbol_name_field (str, optional) – Column containing symbol name.
symbol (str) –
Symbol(s) from which data should be taken.

If both symbol_name_field and symbol are omitted otp.config.default_symbol value will be used.
db (str) – Custom database name for the node of the graph.
tick_type (str) – Tick type. Default: ANY.

Examples

All examples for onetick.py.ReadFromDataFrame() suitable for this data source.

Let’s look at differences. Here’s onetick.py.ReadFromDataFrame() output with symbols parameter in otp.run:

>>> src = otp.ReadFromDataFrame(dataframe, symbol_name_field='SYMBOL_NAME')  
>>> otp.run(data, date=otp.dt(2024, 1, 1), symbols=['AAA'])  
                     Time SYMBOL_NAME  PRICE
0 2024-01-01 12:00:00.001         AAA  50.05
1 2024-01-01 12:00:02.000         AAA  50.05
2 2024-01-01 12:00:03.100         AAA  49.98

Same example for LoadTicksFromDataFrame. As you can see, ticks weren’t filtered by symbol name:

>>> dataframe['_SYMBOL'] = dataframe['SYMBOL_NAME']  
>>> src = otp.LoadTicksFromDataFrame(dataframe)  
>>> otp.run(src, date=otp.date(2024, 1, 1))  
                     Time  PRICE _SYMBOL
0 2024-01-01 12:00:00.001  50.05     AAA
1 2024-01-01 12:00:02.000  50.05     AAA
2 2024-01-01 12:00:02.500  49.95     BBB
3 2024-01-01 12:00:03.100  49.98     AAA
4 2024-01-01 12:00:03.250  50.02     BBB