Please help me.

[snippsat]

Not sure what you try do.
It was just a quick function demo.
Can write it more useful like this,now is much flexible and can take different argument in.

import krakenex
import pandas as pd

api = krakenex.API()

def calc_max(pair: str, interval: int, col_index: str) -> None:
    # make the API request for OHLC data
    ohlc_data = api.query_public('OHLC', {'pair': pair, 'interval': interval})
    # Convert the data to a pandas dataframe
    df = pd.DataFrame(ohlc_data['result'][pair], columns=['time', 'open', 'high', 'low', 'close', 'vwap', 'volume', 'count'])
    df['time'] = pd.to_datetime(df['time'], unit='s')
    df.set_index('time', inplace=True)
    print(f'{df.head()}\n')
    max_price = df[col_index].max()
    print(f"Maximum price in the <{col_index}>: {max_price}")

if __name__ == '__main__':
    pair = 'XRPGBP'
    interval = 60
    col_index = 'open'
    calc_max(pair, interval, col_index)

Output:
(dl_env) G:\div_code\dl_env
λ python calc_max.py
                        open     high      low    close     vwap         volume  count
time
2023-04-08 14:00:00  0.41009  0.41067  0.41003  0.41049  0.41031  2498.49848700     17
2023-04-08 15:00:00  0.41087  0.41087  0.41001  0.41002  0.41035  2470.63201500     19
2023-04-08 16:00:00  0.40983  0.40992  0.40913  0.40950  0.40945  5611.68209685     19
2023-04-08 17:00:00  0.40953  0.41037  0.40767  0.40767  0.40918  2416.04309153     15
2023-04-08 18:00:00  0.40755  0.40811  0.40507  0.40585  0.40658  5555.67721549     33

Maximum price in the <open>: 0.42970

Now it check max in XRPGBP open column.
Let say now want to check max in BTC/USD high column with interval 15.

import krakenex
import pandas as pd

api = krakenex.API()

def calc_max(pair: str, interval: int, col_index: str) -> None:
    # make the API request for OHLC data
    ohlc_data = api.query_public('OHLC', {'pair': pair, 'interval': interval})
    # Convert the data to a pandas dataframe
    df = pd.DataFrame(ohlc_data['result'][pair], columns=['time', 'open', 'high', 'low', 'close', 'vwap', 'volume', 'count'])
    df['time'] = pd.to_datetime(df['time'], unit='s')
    df.set_index('time', inplace=True)
    print(f'{df.head()}\n')
    max_price = df[col_index].max()
    print(f"Maximum price in the <{col_index}>: {max_price}")

if __name__ == '__main__':
    pair = 'BTC/USD'
    interval = 15
    col_index = 'high'
    calc_max(pair, interval, col_index)

Output:
G:\div_code\dl_env
λ python calc_max.py
                        open     high      low    close     vwap       volume  count
time
2023-05-01 02:15:00  28650.2  28678.1  28568.0  28600.0  28635.1  74.45265240    541
2023-05-01 02:30:00  28599.9  28652.7  28586.8  28589.4  28615.1  30.90120898    432
2023-05-01 02:45:00  28598.0  28623.1  28536.0  28555.3  28580.7  20.00984895    350
2023-05-01 03:00:00  28564.2  28565.1  28477.4  28491.9  28537.1  41.99185887    436
2023-05-01 03:15:00  28489.1  28605.7  28450.0  28595.8  28537.2  42.52158371    402

Maximum price in the <high>: 29868.1