Technical Analysis Library in Python’s documentation! import pandas as pd from ta import add_all_ta_features from ta.utils import dropna # Load datas df = pd.read_csv('ta/tests/data/datas.csv', sep=',') # Clean NaN values df = dropna(df) # Add ta features filling NaN values df = add_all_ta_features( df, open="Open", high="High", low="Low", close="Close", volume="Volume_BTC", fillna=True)