ValueError: cannot convert float NaN to integer

Client SDKs
1

Hi there,

When querying data with python influxDB client to pandas dataframe I get the error message ValueError: cannot convert float NaN to integer.

.venv\Lib\site-packages\influxdb_client\client\flux_csv_parser.py", line 288, in _to_value

  • return int(str_val)*
  •       ^^^^^^^^^^^^*

ValueError: cannot convert float NaN to integer.

Is there a solution or workaround for this problem?

Best regards,
Jan

2

Hello @JanD,
Can you share your python script? (including the flux query?)
As well as the python client version you’re using?
Thank you!

3

Hello Anaisdg,

Thanks for your interest. Attached you find the python script and below the query.
I use the latest release of the python influxdb_client.

Best regards,

The query i run is:

import “experimental/date/boundaries”
import “influxdata/influxdb/schema”
lastWeek = boundaries.week(week_offset: -1)
from(bucket: “claire-test-data”)

Outlook-logo TUe.png

(Attachment download_data.py is missing)

4

Hello Anaisdg,

Thanks for your interest. Below you find the python script and below the query.
I use the latest release of the python influxdb_client.

Best regards,
Jan

The python script:

import os
import time
from dotenv import load_dotenv
from influxdb_client import InfluxDBClient
import pandas as pd
import matplotlib
import certifi
import re

For windows ssh certification keys

fh = open(certifi.where(), “r”)
cert = fh.read()
fh.close()

load secret data from .env file

load_dotenv()
token = os.getenv(‘TOKEN’)
org = os.getenv(‘ORG’)
bucket = os.getenv(‘BUCKET’)
host = os.getenv(‘INFLUXDB_HOST’)

Init influxDB client

client = InfluxDBClient(url=host, org=org, token=token)
query_api = client.query_api()

read excel with MAC adresses in pandas dataframe

location_data = pd.read_excel(‘./sensor_locations.xlsx’)
mac_adresses_to_filter = ‘’
for i in range(1,location_data.shape[0]):
if location_data.Active[i] == True:
mac_adresses_to_filter += f’|{location_data.MAC_adresses[i]}’

print( f’MACS {mac_adresses_to_filter}')

query in flux language

start_time = ‘2023-12-20T00:00:00’
stop_time = ‘2023-12-20T23:59:59’

filter_string =“AM232X_RH|AM232X_TEMP|ENS210_RH|ENS210_TEMP|NDIR_CO2|NUMPM0|NUMPM1|NUMPM2|NUMPM4|NUMPM10|PM1|PM2.5|PM4|PM10|IAQ|TVOC”
keep_column_string = ‘[“_time”, “MAC”, "’ + re.sub(‘[|]’, ‘", "’, filter_string) + ‘"]’

query = f’‘’
// Flux query to download data from last week for sensor with MAC adress … /

from(bucket: “claire-test-data”)

range(start: {start_time}Z, stop: {stop_time}Z)
filter(fn: (r) => r._measurement == “environment”)
filter(fn: (r) => r.MAC =~ /^({mac_adresses_to_filter})$/)
filter(fn: (r) => r._field =~ /^({filter_string})$/)
pivot(rowKey:[“_time”], columnKey: [“_field”], valueColumn: “_value”)
group()
keep(columns: {keep_column_string})
‘’’
print(query)

Run query and return data as pandas data frame

data = query_api.query_data_frame(query=query)

print(data.head())

close client

client.close()

csv_filename = f’AC_data_{start_time}{stop_time}.csv’
pk1_filename = f’…/Data_archive/AC_data{start_time}{stop_time}.pk1.zip’.replace(‘:’,'‘)
zip_archive_filename = f’…/Data_archive/AC_data_{start_time}_{stop_time}all.zip’.replace(‘:’,'')

print(zip_archive_filename)
print(csv_filename)

save data as compressed csv

data.to_csv(zip_archive_filename, sep=‘,’, compression={‘method’: ‘zip’, ‘archive_name’: f’{csv_filename}'}, mode=‘a’)

save data as pickle file format

data.to_pickle(pk1_filename, compression=‘zip’)

The query i run is:

import “experimental/date/boundaries”
import “influxdata/influxdb/schema”
lastWeek = boundaries.week(week_offset: -1)
from(bucket: “claire-test-data”)

5

Any news about this ?

6

Hi,
Not Yet. I made a workaround by saving data first in csv file and then read the CSV in a pandas dataframe.

Best regards,
Jan