python – How to address data inconsistency in the Binance klines API?

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I see a discrepancy in the values ​​returned from the klines API call.

Here is an example:

API call delivered to the BTC / USDT market.

Candle data appearing on the exchange for open time 2020-12-20 21:26:00:

open = 23832.00

high = 23844.58

low = 23783.86

close = 23788.65

A snapshot of the Binance exchange scene: https://imgur.com/a/DShL7lN

Candle data returned from the API calls for this candle:

open = 23832.00

high = 23844.58

low = 23783.86

close = 23799.72

The near values ​​do not match.

This led to the calculation of an invalid signal. I find there are random differences in the proximity value.

How do I apply for support?

Code to apply kline for the following problematic and valid candle:

    from datetime import datetime, timedelta
import time
from datetime import timezone

from binance.client import Client
import pandas as pd
import numpy as np
from pandas_datareader import data


client = Client("", "")

klines = client.get_klines(
    symbol = "BTCUSDT",
    interval = "1m",
    startTime = 1608499560000,
    limit = 2
)

labels = ['open_time', 'open', 'high', 'low', 'close', 'volume', 'close_time', '1', '2', '3', '4', '5']
df = pd.DataFrame(klines, columns=labels)

for j in range(0, (df.shape[0])):
    print(int(str(df.iloc[j]['open_time'])))          
    str_open_time = datetime.utcfromtimestamp(int(str(df.iloc[j]['open_time'])[:-3])).strftime('%Y-%m-%d %H:%M:%S')
    print("open time: " + str_open_time + "; open: " + str(df.iloc[j]['open']) + "; low: " + str(df.iloc[j]['low']) + "; high: " + str(df.iloc[j]['high']) + "; close: " + str(df.iloc[j]['close']))

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