Files
drift/run_fetch_data_5min.py
2022-03-15 14:12:05 +01:00

65 lines
1.6 KiB
Python

from binance_historical_data import BinanceDataDumper
import datetime
data_dumper = BinanceDataDumper(
path_dir_where_to_dump="./data/5min_crypto/",
data_frequency="5m",
)
assets = [
"TRXUSDT",
"XRPUSDT",
"ADAUSDT",
"SOLUSDT",
"AVAXUSDT",
"DOTUSDT",
"ETHUSDT",
"LTCUSDT",
"BNBUSDT",
"BTCUSDT",
"ETCUSDT",
]
data_dumper.dump_data(
list_tickers=assets,
date_start=datetime.date(2018, 1, 1),
date_end=datetime.date(2022, 1, 1),
is_to_update_existing=False,
)
import os
from tqdm import tqdm
import pandas as pd
for asset in tqdm(assets):
path = f"./data/5min_crypto/spot/monthly/klines/{asset}/5m/"
files = os.listdir(path)
def load_df(path):
df = pd.read_csv(
path,
names=[
"timestamp",
"open",
"low",
"high",
"close",
"volume",
"Closetime",
"Quote asset volume",
"Number of trades",
"Taker buy base asset volume",
"Taker buy quote asset volume",
"Ignore",
],
)
df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
df = df[["timestamp", "open", "high", "low", "close", "volume"]]
df.set_index("timestamp", inplace=True)
df.sort_index(inplace=True)
return df
dfs = pd.concat([load_df(path + file) for file in files], axis=0)
dfs.sort_index(inplace=True)
dfs.to_parquet(f"./data/5min_crypto/{asset}.parquet")