query_data_frame with many columns throws Pandas PerformanceWarning

[sjamesc]

Steps to reproduce:
List the minimal actions needed to reproduce the behavior.

1. Write a flux query with a pivot that results in many columns being returned (i.e. 100+)
2. Use client.query_api().query_data_frame(query, org=org) to query as a Pandas DataFrame

Expected behavior:
The code should run without issue, similar to how it runs fine without the pivot (so many rows, not many columns).

Actual behavior:
Pandas warning is thrown:

/opt/conda/envs/trading/lib/python3.9/site-packages/influxdb_client/client/flux_csv_parser.py:138: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling frame.insert many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use newframe = frame.copy()
self._data_frame[column.label] = column.default_value

Specifications:

• Client Version: 1.21.0
• Pandas Version: 1.3.3
• InfluxDB Version: 2.0.9
• Platform: Python 3.9

[bednar]

Hi @sjamesc,

thanks for using our client.

We will take a look.

Regards