As a dev, I want the information extracted by the performance_assessment.py script to be aggregated in a human readable report.

[Endlessflow]

Description

Context
Our initial performance_assessment script currently generates raw data on the system's performance and compiles it into a CSV report. To be useful to our team, this information needs to be transformed into a human-readable format.

Problem Statement
To derive meaningful insights from the raw data generated by our performance_assessment script, we need to compile the results in the CSV report into an aggregated and understandable format. For now, we will implement a basic aggregation method.

For each label, we will have:

• The average Levenshtein distance score for each field.
• The ratio of fields that are considered to have a passing score.
• The ratio of missing fields from the pipeline output compared to expected results.

Acceptance Criteria
To consider this issue resolved, the following criteria need to be met:

1. Data Aggregation:

   • The performance_assessment script must aggregate raw data and calculate the average Levenshtein distance score for each field across all labels.
   • The script must calculate and include in the report the ratio of fields that meet or exceed a predefined passing score threshold.
   • The script should also calculate and provide the ratio of missing fields from the pipeline's output compared to expected results.

2. Report Generation:

   • The aggregated results should include simple visualizations (e.g., bar charts or pie charts) for better comprehension.
   • The aggregated data must be compiled into a user-friendly, human-readable report format (e.g., PDF or web dashboard).
   • Ensure that there is a clear definition at the beginning of the report explaining what constitutes a 'passing score' for field accuracy.