# e-Stat Japan Statistics Scraper (`jungle_synthesizer/e-stat-japan-statistics-scraper`) Actor Extract official Japanese government statistics from the e-Stat API (api.e-stat.go.jp). Search 6,000+ datasets covering population, GDP, trade, employment, and more. Returns bilingual JP/EN labels with automatic wareki-to-Gregorian date conversion. Requires a free appId from e-stat.go.jp/api/. - **URL**: https://apify.com/jungle\_synthesizer/e-stat-japan-statistics-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## e-Stat Japan Statistics Scraper Extract official Japanese government statistics from the e-Stat API. Search 6,000+ datasets covering population, GDP, trade, employment, and more. Returns bilingual JP/EN labels with automatic wareki-to-Gregorian date conversion. ### What is e-Stat? [e-Stat](https://www.e-stat.go.jp/) is Japan's unified government statistics portal, operated by the Ministry of Internal Affairs and Communications. It aggregates statistical data from all major Japanese ministries and agencies. The [e-Stat API v3](https://api.e-stat.go.jp/rest/3.0/app/) provides programmatic access to 6,000+ survey tables covering: - **Population**: Census, vital statistics, household surveys - **Economy**: GDP, industrial production, corporate statistics - **Labour**: Employment, wages, working hours - **Agriculture**: Crop production, livestock, fisheries - **Trade**: Import/export by commodity and country - **Health & Education**: Medical facilities, school enrollment ### Getting Started 1. **Register for a free API key** at [https://www.e-stat.go.jp/api/](https://www.e-stat.go.jp/api/) 2. Enter your `appId` in the actor input 3. Choose a mode: `catalog` to search tables, `data` to fetch records ### Modes #### Catalog Mode (`mode: "catalog"`) Search the statistical table index by keyword, subject area, or publishing ministry. Returns metadata for matching tables — use this to discover `statsDataId` values for data mode. **Input example:** ```json { "appId": "YOUR_APP_ID", "mode": "catalog", "searchWord": "population", "lang": "E", "maxItems": 50 } ```` **Output fields:** | Field | Description | |-------|-------------| | `stats_data_id` | Unique e-Stat table ID (use in data mode) | | `stats_name` | Survey series name | | `statistics_name` | Specific table name within the survey | | `title` | Full table title | | `government_org` | Publishing ministry or agency | | `cycle` | Survey frequency (annual/monthly/etc.) | | `survey_date` | Survey period code | | `open_date` | Publication date (YYYY-MM-DD) | | `small_area` | True if municipality-level data is available | | `overall_total` | Total number of data cells in the table | #### Data Mode (`mode: "data"`) Fetch actual data cells from one or more specific table IDs. Supports multi-dimensional data with area, time, and category axes. **Input example:** ```json { "appId": "YOUR_APP_ID", "mode": "data", "statsDataIds": ["0003448237"], "lang": "E", "maxItems": 1000 } ``` **Output fields:** | Field | Description | |-------|-------------| | `stats_data_id` | Source table ID | | `area_code` | JIS prefecture/municipality code | | `area_label` | Area name (Japanese) | | `area_label_en` | Area name (English) | | `time_code` | Time dimension code | | `time_label` | Time label as reported (may include wareki) | | `time_gregorian` | ISO 8601 normalized year (wareki converted) | | `cat01_code` | Category dimension 1 code | | `cat01_label` | Category dimension 1 label | | `value` | Numeric data value | | `unit` | Measurement unit | | `annotation` | Suppression flag (\* or -) | ### Filtering Options #### Catalog Mode Filters | Input | Description | Example | |-------|-------------|---------| | `searchWord` | Keyword search across JP and EN metadata | `"population"` | | `statsField` | Subject area code | `"02"` (Population) | | `governmentOrg` | Ministry code | `"00200"` (Statistics Bureau) | | `lang` | Label language: `"E"` (English) or `"J"` (Japanese) | `"E"` | #### Common `statsField` Codes | Code | Subject Area | |------|-------------| | `02` | Population / Households | | `03` | Labour / Wages | | `04` | Agriculture / Forestry / Fisheries | | `05` | Mining / Industry / Construction | | `07` | Trade | | `08` | Finance / Insurance | | `09` | Government Finance | | `13` | Health / Social Security | | `14` | Education / Culture | ### Wareki Date Conversion Japanese government data frequently uses imperial era years (令和, 平成, 昭和, 大正). This actor automatically converts them to Gregorian years in the `time_gregorian` field: | Japanese | Gregorian Offset | Example | |----------|-----------------|---------| | 令和 (Reiwa) | +2018 | 令和6 → 2024 | | 平成 (Heisei) | +1988 | 平成30 → 2018 | | 昭和 (Showa) | +1925 | 昭和50 → 1975 | | 大正 (Taisho) | +1911 | 大正5 → 1916 | ### Rate Limits The e-Stat API free tier allows up to **100,000 requests per day** with no monthly limit. The actor uses a conservative 200ms delay between requests to stay well within limits. ### Large Tables Some e-Stat tables contain millions of data cells. Use `maxItems` to limit output: - Catalog mode: up to 100,000 table entries per search - Data mode: no hard per-table cap, but use `maxItems` for manageable runs ### Output Format All records are flat JSON objects. Unused dimension fields (e.g. `cat02_*` when a table only has one category dimension) are omitted from output. ### Example Use Cases - Track Japan's annual population by prefecture over time - Monitor labour market statistics (unemployment, wages) by industry - Analyze agricultural production trends - Research bilateral trade flows by commodity - Study historical demographic data with wareki-to-Gregorian conversion # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `appId` (type: `string`): Your free e-Stat API application ID. Register at https://www.e-stat.go.jp/api/ to get your own key. Required for all API calls. ## `mode` (type: `string`): Operation mode: "catalog" (search for statistical tables), "data" (fetch data cells for specific table IDs). ## `searchWord` (type: `string`): Keyword to search for (used in catalog mode). Searches both Japanese and English metadata. ## `statsDataIds` (type: `array`): One or more e-Stat table IDs (statsDataId) to fetch data cells for. Used in data mode. Example: \["0003448237"]. ## `lang` (type: `string`): Language for labels — "E" for English, "J" for Japanese. ## `statsField` (type: `string`): Filter by subject area code (catalog mode only). E.g. "02" for Population/Households, "03" for Labour/Wages, "04" for Agriculture. ## `governmentOrg` (type: `string`): Filter by publishing ministry code (catalog mode only). E.g. "00200" for Statistics Bureau. ## `maxItems` (type: `integer`): Maximum number of records to return. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "appId": "e58d90215db770e17b638605c0912b8ba0222b09", "mode": "catalog", "searchWord": "population", "statsDataIds": [ "0003448237" ], "lang": "E", "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "appId": "e58d90215db770e17b638605c0912b8ba0222b09", "mode": "catalog", "searchWord": "population", "statsDataIds": [ "0003448237" ], "lang": "E", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/e-stat-japan-statistics-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "appId": "e58d90215db770e17b638605c0912b8ba0222b09", "mode": "catalog", "searchWord": "population", "statsDataIds": ["0003448237"], "lang": "E", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/e-stat-japan-statistics-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "appId": "e58d90215db770e17b638605c0912b8ba0222b09", "mode": "catalog", "searchWord": "population", "statsDataIds": [ "0003448237" ], "lang": "E", "maxItems": 10 }' | apify call jungle_synthesizer/e-stat-japan-statistics-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/e-stat-japan-statistics-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "e-Stat Japan Statistics Scraper", "description": "Extract official Japanese government statistics from the e-Stat API (api.e-stat.go.jp). Search 6,000+ datasets covering population, GDP, trade, employment, and more. Returns bilingual JP/EN labels with automatic wareki-to-Gregorian date conversion. Requires a free appId from e-stat.go.jp/api/.", "version": "0.1", "x-build-id": "qaiMb5Szqz6jdAwXW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~e-stat-japan-statistics-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-e-stat-japan-statistics-scraper", "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/jungle_synthesizer~e-stat-japan-statistics-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-e-stat-japan-statistics-scraper", "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/jungle_synthesizer~e-stat-japan-statistics-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-e-stat-japan-statistics-scraper", "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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "appId": { "title": "e-Stat Application ID", "type": "string", "description": "Your free e-Stat API application ID. Register at https://www.e-stat.go.jp/api/ to get your own key. Required for all API calls.\n" }, "mode": { "title": "Mode", "enum": [ "catalog", "data" ], "type": "string", "description": "Operation mode: \"catalog\" (search for statistical tables), \"data\" (fetch data cells for specific table IDs).\n" }, "searchWord": { "title": "Search Keyword", "type": "string", "description": "Keyword to search for (used in catalog mode). Searches both Japanese and English metadata.\n" }, "statsDataIds": { "title": "Stats Data IDs", "type": "array", "description": "One or more e-Stat table IDs (statsDataId) to fetch data cells for. Used in data mode. Example: [\"0003448237\"].\n", "items": { "type": "string" } }, "lang": { "title": "Language", "enum": [ "E", "J" ], "type": "string", "description": "Language for labels — \"E\" for English, \"J\" for Japanese." }, "statsField": { "title": "Statistics Field Code", "type": "string", "description": "Filter by subject area code (catalog mode only). E.g. \"02\" for Population/Households, \"03\" for Labour/Wages, \"04\" for Agriculture.\n" }, "governmentOrg": { "title": "Government Organization Code", "type": "string", "description": "Filter by publishing ministry code (catalog mode only). E.g. \"00200\" for Statistics Bureau.\n" }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return." } } }, "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 } } }, "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 } } } } } } } } } } ```