amunra
commented
1 year ago You end up in this situation when:
- Creating the table in advance with a designated timestamp column.
- Not telling the python client which column is the designated timestamp column.
To resolve, specify at='timestamp'.
See: https://py-questdb-client.readthedocs.io/en/latest/examples.html#pandas-basics
Also, here are the API docs: https://py-questdb-client.readthedocs.io/en/latest/api.html#questdb.ingress.Buffer.dataframe
Same matter, btw, if you use the .row API.
Why this happens: The Python client produces messages in the ILP protocol. In the protocol the designated timestamp is sent as a special field with nanosecond precision instead of microsecond precision.
Even this sample code provided in the docs is broken:
` df = pd.DataFrame({ 'id': pd.Categorical(['toronto1', 'paris3']), 'temperature': [20.0, 21.0], 'humidity': [0.5, 0.6], 'timestamp': pd.to_datetime(['2021-01-01', '2021-01-02']) })
with Sender('localhost', 9009) as sender: sender.dataframe(df, table_name='sensors') `
I've tried various things, including sending a UNIX timestamp, UNIX timestamp converted to microseconds, nanoseconds, etc.