Feature Request: make working with pandas dataframe timestamps easier

[Anaisdg]

Currently users have to do a bit of timestamp manipulation in order to write pandas DataFrames, for example:

The following features could make working pandas DataFrames easier:

• The ability to specify the timestamp column/not set the timestamp column as an index
• The ability to specify the timestamp type and automatic conversation (like from ISO or rfc3339 timestamps to datetime objects).

[bednar]

Hi @Anaisdg,

thanks for the suggestion, we'll take a look. Do you have a sample data?

Regards

[rslippert]

In order to use a wider variety of time and date formats,
there should also be a timezone parameter specified.
It would help if the InfluxDb could generate a json template like what my software uses,
it could generate this json data like it does when generating a token, see below:
{
"influx_bucket": "rslippert's Bucket",
"influx_org": "d9ae8eef6f1bd6da",
"influx_token": "E3zGsMqgMrDYthxjfT921FXhipsOfGOIOxpcfvn61SnBE4D1mdgYKF5aYefaCbroy0UpBIsOEEMZr2XM96dtFg==",
"influx_url": "https://us-east-1-1.aws.cloud2.influxdata.com",
"timezone": "EST",
"influx_version": "1.0"
}

[rslippert]

Attached is some sample data as requested:
1dSCCOPLMCOPX.csv

[bednar]

@rslippert thanks for sharing your data

[bednar]

Hi @rslippert,

with upcoming #440 you will be able to use the following code:

import pandas as pd

from influxdb_client import InfluxDBClient
from influxdb_client.client.write_api import SYNCHRONOUS

url = "http://localhost:8086"
token = "my-token"
org = "my-org"

with InfluxDBClient(url=url, token=token, org=org) as client:

    data_frame = pd.read_csv("path/to/1dSCCOPLMCOPX.csv")
    client \
        .write_api(write_options=SYNCHRONOUS) \
        .write(bucket="my-bucket",
               record=data_frame,
               data_frame_measurement_name="scco",
               data_frame_timestamp_column="Date",
               data_frame_timestamp_timezone="EST")

Regards

[rslippert]

I’m impressed by the speed and completeness of this pandas timestamp change. Great job Influx!

[Anaisdg]

Same thanks @bednar and @rhajek!!!