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)