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This repository was archived by the owner on Oct 29, 2024. It is now read-only.
As continuation of #811
The solution for the rounding error seems not to be merged.
This gives particular problems when merging data from different sources to a database : timestamps must be CORRECT! This is an essential point in a timeseries database. (my thoughts...)
python 3 makes floats if you divide with '/' --> please change to '//'
Example : line 375 fro _dataframe_client.py
time = ((dataframe.index.to_timestamp().values.astype(np.int64) /
precision_factor).astype(np.int64).astype(str))
to
time = ((dataframe.index.to_timestamp().values.astype(np.int64) //
precision_factor).astype(np.int64).astype(str))
The text was updated successfully, but these errors were encountered:
@svhb1000 which version of pandas are you using? I am on 1.2.4 and using the code I posted in #811 I've been testing this without success. Even with the '//' if I have timestamps that are within a few nanoseconds of each other they are combined into one datapoint upon writing to influx.
Edit: my mistake, it is working once I change to '//'. Do you also change the line below line 375 to '//' or should that be left as a single '/'?
As continuation of #811
The solution for the rounding error seems not to be merged.
This gives particular problems when merging data from different sources to a database : timestamps must be CORRECT! This is an essential point in a timeseries database. (my thoughts...)
python 3 makes floats if you divide with '/' --> please change to '//'
Example : line 375 fro _dataframe_client.py
to
The text was updated successfully, but these errors were encountered: