suggestion: Consider using a dynamic range for patient iteration.

The loop iterates over a hardcoded range from 1 to 10. Consider using a dynamic range based on the actual number of patients in the dataset to make the code more flexible.

suggestion (bug_risk): Check for key existence in dictionary access.

When accessing dictionary keys using formatted strings, ensure that the keys exist to avoid potential KeyErrors. Consider using a safer method like dict.get() with a default value.

suggestion (performance): Optimize null check to specific columns.

Checking for nulls across all columns might be inefficient for large datasets. Consider checking specific columns that are critical for your analysis to improve performance.

time_series.select(
 pl.col('date'),
 pl.any_horizontal(
 pl.col(['critical_column1', 'critical_column2', 'critical_column3']).is_null()
 ).alias('has_null')
)

suggestion (performance): Optimize date filtering by converting column type.

If date filtering is a frequent operation, consider converting the date column to a datetime type once and using direct comparisons to improve performance.

suggestion: Specify interpolation method and handle edge cases.

The suggestion to use linear interpolation is vague. Specify the method of interpolation and consider handling edge cases where interpolation might not be appropriate, such as at the boundaries of the dataset.

issue (documentation): Fix typo in 'Kllustrations'

The word 'Kllustrations' should be 'Illustrations'.