Binance_Get_Data.py

# https://python-binance.readthedocs.io/en/latest/
# https://www.youtube.com/watch?v=_gNIWHh539A

import pandas as pd
from binance.client import Client
import ta

klinesT = Client().get_historical_klines("BTCUSDT", Client.KLINE_INTERVAL_15MINUTE, "01 December 2021")

df = pd.DataFrame(klinesT, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time', 'quote_av', 'trades', 'tb_base_av', 'tb_quote_av', 'ignore'])

# [[
#    1499040000000,      // Open time
#    "0.01634790",       // Open
#    "0.80000000",       // High
#    "0.01575800",       // Low
#    "0.01577100",       // Close
#    "148976.11427815",  // Volume
#    1499644799999,      // Close time
#    "2434.19055334",    // Quote asset volume
#    308,                // Number of trades
#    "1756.87402397",    // Taker buy base asset volume
#    "28.46694368",      // Taker buy quote asset volume
#    "17928899.62484339" // Ignore.
#  ]]

del df['ignore']
del df['close_time']
del df['quote_av']
del df['trades']
del df['tb_base_av']
del df['tb_quote_av']

df['close'] = pd.to_numeric(df['close'])
df['high'] = pd.to_numeric(df['high'])
df['low'] = pd.to_numeric(df['low'])
df['open'] = pd.to_numeric(df['open'])

df = df.set_index(df['timestamp'])
df.index = pd.to_datetime(df.index, unit='ms')

print(df)