ask question about field and value separate

version: influxdb v2.4

i have a question about ETL when i use ui filter search my data

I expected my result like this

filed,value

voltage:20
current:30

but result is

_filed,_value

_filed,voltage

_filed,_value

_value,20

How do I fix it

part of Code:

column_list=["Location","Service","RackName","PduSide"]
ip_to_mapping = {
        '192.168.20.100': ["room1","storage","A01","R"],
        '192.168.20.101': ["room2","CRM","A02","L"]
    }
drop_colummns=['table','_measurement','_start','_stop','_time','result']
#mapping
def mapping_function(num):
    feeback_dict={}
    for x in range(len(empty)):
        feeback_dict[f'{empty[x]}']=ip_to_mapping[empty[x]][num]

    return(feeback_dict)


#instance
client = InfluxDBClient(url=url, token=token, org=org)
write_api = client.write_api(write_options=SYNCHRONOUS)
query_api = client.query_api()

#query
query = ''' from(bucket: "delta_pdu")
|> range(start:-1m)
|> filter(fn: (r) => r["_measurement"] == "snmp")  '''
result = query_api.query_data_frame(org=org, query=query)

# for x in result:
#     print(x.columns)

#ETL
empty=[]
for table in result:
    a=list(set(table['agent_host']))
    for x in a:
        empty.append(x)
    for x in range(len(column_list)):
        table[f'{column_list[x]}']=table['agent_host'].map(mapping_function(x))
    table.set_index(table['_time'], inplace=True)
    # print(table)
    clear_data=table.drop(columns=drop_colummns)
    clear_data_columns=list(clear_data.columns)
    print(clear_data)
    print(clear_data_columns)
    print('=----')
    # print(clear_data_columns)
    for x in clear_data_columns:

        if x[0]=='_':
            clear_data_columns.remove(x)
    print(clear_data_columns)


    write_api.write(bucket=bucket2, org=org, record=clear_data, 
                        data_frame_measurement_name='SNMP',
                        data_frame_tag_columns=clear_data_columns,
                        data_frame_field_columns=["_filed","_value"])

Start with the Python client code using query_api.query_data_frame and write_api.write, and reproduce the transformation against InfluxDB v2.4. Inspect the dataframe columns before the write and compare them with the supplied field and value expectations. Done means the cause of the separate _field and _value output is identified and a clear correction or documented limitation is established.