Excel & CSV Merger: Consolidate, Pivot & Batch Convert
Pricing
from $20.00 / 1,000 processed files
Combine, pivot, and batch convert, rename, or format many Excel and CSV files in one run.
You can access the Excel & CSV Merger: Consolidate, Pivot & Batch Convert programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.1", "x-build-id": "Q2cgu3Bu8y2etHcsa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dws_build~excel-csv-merger-consolidate-pivot-batch-convert/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dws_build-excel-csv-merger-consolidate-pivot-batch-convert", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dws_build~excel-csv-merger-consolidate-pivot-batch-convert/runs": { "post": { "operationId": "runs-sync-dws_build-excel-csv-merger-consolidate-pivot-batch-convert", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dws_build~excel-csv-merger-consolidate-pivot-batch-convert/run-sync": { "post": { "operationId": "run-sync-dws_build-excel-csv-merger-consolidate-pivot-batch-convert", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "operation" ], "properties": { "operation": { "title": "Operation", "enum": [ "consolidate", "pivot", "convert", "rename_columns", "format" ], "type": "string", "description": "What to do with the files. consolidate: combine sheets into one. pivot: group and aggregate across all sheets. convert, rename_columns, format: apply to each file separately; in any of these three, Rename columns and Format options both apply when filled in (rename first, then format)." }, "files": { "title": "Files (URL or base64)", "type": "array", "description": "Files to process (.xlsx, .xlsm, .xls, .csv), as direct-download links. Each item is {\"url\": \"https://...\", \"name\": \"optional label\"} or {\"base64\": \"...\", \"name\": \"jan.csv\"}. Up to 50 files and 30 MB in total. Base64 is limited to 5 MB per file and 10 MB per run. Example: [{\"url\": \"https://example.com/jan.xlsx\"}, {\"url\": \"https://example.com/feb.csv\", \"name\": \"February\"}]." }, "sheets": { "title": "Sheets", "type": "array", "description": "Sheet names to read from each workbook. Leave empty to read all sheets. A CSV is one sheet named after the file.", "items": { "type": "string" } }, "outputFormat": { "title": "Output format", "enum": [ "xlsx", "csv", "json" ], "type": "string", "description": "File format of every output, for all operations (convert uses it as the target format). json is an array of row objects per sheet. The format operation requires xlsx.", "default": "xlsx" }, "consolidate": { "title": "Consolidate options", "type": "object", "description": "Used when operation is consolidate. stack_rows appends rows and aligns columns by header name. merge_on_key joins sheets side by side on a key column." }, "pivot": { "title": "Pivot options", "type": "object", "description": "Used when operation is pivot. groupBy: key columns. values: numeric columns to aggregate. aggregations: any of sum, count, mean, min, max." }, "renameColumns": { "title": "Rename columns", "type": "object", "description": "A map of old header name to new header name, applied to every file, such as {\"Cust ID\": \"customer_id\"}. Required for rename_columns. Also applies in convert and format runs when filled in." }, "format": { "title": "Format options", "type": "object", "description": "Excel formatting applied to every file: boldHeader, freezeHeader, autoWidth (true or false, all default to true), and columnFormats, a map of column name to Excel number format, such as {\"Revenue\": \"#,##0.00\", \"Date\": \"yyyy-mm-dd\"}. Used by the format operation, and also by convert and rename_columns when filled in. Needs xlsx output." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Excel & CSV Merger: Consolidate, Pivot & Batch Convert from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: