Data transformer

A data transformer allow you to apply changes on data. It can be used to add financial indicators, remove indicators, or compress columns.

TaDataTransformer

class Hmile.DataTransformer.TaDataTransformer(dataprovider: DataProvider)

Add all technical analysis indicators to the data

Variables

dataprovider – The dataprovider to use to get the data

integrity_for_normalization(data: DataFrame) → DataFrame

drop columns with nans and check that std is not too low to avoid nan during normalizing

Parameters

data (pd.DataFrame) – data to check

Returns

data cleaned up

Return type

pd.DataFrame

transform() → Dict[str, DataFrame]

Apply transformation. Return a dict of dataframes with the key the pair and the value the corresponding dataframe. Every dataframe should have the same columns and the same index : The main columns are named be open, high, low, close, volume. In index is the date. The index name is’date’

Returns

The transformed data

Return type

Dict[str, pd.DataFrame]

Check the ta lib documentation for more information.

Examples :

from Hmile.DataProvider import YahooDataProvider
from Hmile.DataTransformer import TaDataTransformer

PAIR = "BTCUSD"
START = "2022-01-01"
END = "2022-01-03"
INTERVAL = "hour"

dp = YahooDataProvider([PAIR], START, END, interval=INTERVAL)

# We first need a source of data = a data provider
data_provider = YahooDataProvider()
# Create a data transformer
transformer = TaDataTransformer(data_provider)
# transform the data
data = transformer.transform()