I can compute this, but I need one clarification on the aggregation level.

The data has these columns (header starts with overall.operation_created_at):

• overall.operation_created_at
• project_name
• operation_status
• transaction_type
• final_integration_type
• initial_integration_type
• customer_country_code
• card_brand
• card_iin
• customer_metadata_group
• template_name
• operation_count

Possible interpretations:

• Option A (global rate): rate = number of rows where operation_status = "succeeded" divided by total number of rows in the entire file (one single number).
• Option B (per-group rate): rate for each unique combination of all columns except operation_status (i.e., group by overall.operation_created_at, project_name, transaction_type, final_integration_type, initial_integration_type, customer_country_code, card_brand, card_iin, customer_metadata_group, template_name, operation_count) and compute succeeded/total per group; output a CSV with the group keys and the rate.
• Option C (per date/project or other subset): rate grouped by a subset (e.g., by overall.operation_created_at and project_name), etc.

Please tell me which option you want:

• A single overall rate (Option A), or
• Per-group rate (Option B) with a CSV output, or
• Some other grouping (e.g., per date and project)?

If you choose Option B, confirm which columns to group by (I can group by all columns except operation_status and, typically, exclude operation_count to avoid per-row granularity unless you want that). Also confirm whether you want the output as:

• a CSV with columns: [group_key columns..., rate], or
• a wide/flat format with one row per group and a rate column.

Once you confirm, I’ll compute and return the result in proper CSV format.