CSV Schema Profiler

Store Positioning

Store title: CSV Schema Profiler

Short description: Profile CSV columns for inferred types, null rates, uniqueness, sample values, duplicates, and drift risks.

SEO title: CSV Schema Profiler — data QA, validation, and cleanup utility

SEO description: Profile CSV columns for inferred types, null rates, uniqueness, sample values, duplicates, and drift risks. Use it to validate rows, schemas, duplicates, field quality, and delivery-readiness before handing data to clients or automations.

Categories: SEO_TOOLS, DEVELOPER_TOOLS

Keywords: csv, schema, profiler, csv qa, data/schema qa utility

Pricing

This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model.

• Tier: U2 — Data/schema QA utility
• Primary event: row-checked at $0.00390 base
• Default max charge: $5.00
• Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount

Event set:

• actor-start: base $0.00500, GOLD $0.00400. CSV Schema Profiler: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• row-checked: base $0.00390, GOLD $0.00312. CSV Schema Profiler: charged when row checked is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• issue-detected: base $0.00372, GOLD $0.00298. CSV Schema Profiler: charged when issue detected is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• qa-report-generated: base $0.05000, GOLD $0.04000. CSV Schema Profiler: charged when qa report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.

Public Task Concepts

• Extract CSV Schema rows from supplied public inputs
• Inventory CSV Schema fields across a bounded input
• Normalize CSV Schema evidence for delivery
• Flag missing CSV Schema data before delivery
• Export CSV column profiles with warnings

What It Does

Profile CSV columns for inferred types, null rates, uniqueness, sample values, duplicates, and drift risks.

Use it to inspect type consistency, missing values, uniqueness, and representative values before importing or delivering a CSV dataset.

What It Does Not Do

• It does not modify, enrich, or upload the supplied CSV to external services.
• It does not infer business meaning or guarantee that a value is correct.
• It does not replace a full data contract or warehouse constraint suite.
• It processes only the bounded CSV content supplied in the run input.

Input Fields

Provide csvText, choose the delimiter and header behavior, and set bounded item and charge limits.

Output Fields

• columnName
• columnIndex
• inferredType
• nonEmptyCount
• blankCount
• nullRate
• uniqueCount
• sampleValues
• warnings

Public Task Examples

Profile CSV column types in a customer export

• Input: A capped CSV customer export with its delimiter and header setting.
• Output: Column rows with inferred type, fill rate, uniqueness, samples, and warnings.
• Use case: Identify schema drift before loading a customer export.

Find blank values before importing a spreadsheet

• Input: A spreadsheet export containing optional and required columns.
• Output: Per-column blank counts, null rates, and warning labels.
• Use case: Find incomplete fields before a bulk import.

Summarize unique values for feed cleanup

• Input: A product or partner feed with repeated category and status values.
• Output: Unique counts and representative values for each column.
• Use case: Spot inconsistent enumerations before feed cleanup.

Detect numeric columns with malformed values

• Input: A CSV containing expected numeric columns and malformed entries.
• Output: Inferred types and warning evidence for mixed-value columns.
• Use case: Catch malformed price or quantity fields before delivery.

Create a CSV data-quality table for operations

• Input: A bounded operational export with headers enabled.
• Output: A normalized column-quality table and optional summary artifact.
• Use case: Attach consistent profiling evidence to a data delivery.

Tests

• Actor-specific tests live in test/csv-schema-profiler.test.ts.
• The suite validates output artifacts, issue/no-result cases, report billing, and max-charge stops.

FAQ

Does the actor change my CSV?

No. It returns profile rows and report artifacts without rewriting the supplied content.

How should I choose a sample?

Use a representative bounded extract that includes headers and known edge values.