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Description
First draft for a data health checker as discussed in #854. The checker receives a path to the data in CSV or qlib format (not implemented yet). It will convert the data to a DataFrame and perform basic checks for data completeness and correctness.
I am not too familiar with the qlib data handling yet, so I am hoping to get some first feedback on whether this goes in the right direction.
Motivation and Context
See #854. This was an issue where a user would get a non-meaningful error message when his data did not adhere to the format (specifically the "volume" column was named "vol"). When checking the data of #854 with this checker, the user would get:
Note: the large step change uses two configurable thresholds (one for price and one for volume) and checks only step changes in OHLCV columns.
How Has This Been Tested?
No tests yet as this is only a first draft
pytest qlib/tests/test_all_pipeline.py
under upper directory ofqlib
.Screenshots of Test Results (if appropriate):
Types of changes