[{"content":" dataprep.jp(Geo) DataMerger地理データとテーマデータを手軽に結合geo-data-merger.dataprep.jp What is this tool? A web-based tool for easily merging geographic data (GeoJSON/TopoJSON) with attribute data (CSV/JSON). It is a convenient data processing tool for when you want to link thematic data (e.g., population, attribute values) to map data.\nFeatures Load geographic and attribute data\u0026hellip;Read GeoJSON/TopoJSON, CSV, and JSON files, and preview their contents. Key-based join\u0026hellip;Join geographic data (Feature properties) with attribute data using a common key column (left join basis). Remove unnecessary columns\u0026hellip;After merging, select and remove unwanted columns from the output via the UI. Output format selection\u0026hellip;Save and download the merged data as GeoJSON/TopoJSON/CSV. How to use Load geographic and attribute data\u0026hellip;Load GeoJSON/TopoJSON on the left side and CSV/JSON on the right side. Specify the join key\u0026hellip;Select the column (key) used for joining from each data preview, and verify that they match correctly. Remove unnecessary columns\u0026hellip;Select and delete unneeded attribute columns after merging. Export and save\u0026hellip;Export the merged data as GeoJSON/TopoJSON/CSV. Data formats Input formats GeoJSON: Geographic Features (points/lines/polygons) + attributes. TopoJSON: A geographic data format that preserves topology (an extension of GeoJSON). CSV/JSON: Thematic data to merge (tabular data containing region codes or key-value pairs). Output formats GeoJSON/TopoJSON: Merged geospatial data. CSV: Merged tabular data. ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/geo-data-merger/images/cover_geo-data-merger_hu_e4dca32cd2b34c8e.jpg","permalink":"https://www.dataprep.jp/en/geo-data-merger/","title":"(Geo) DataMerger"},{"content":"Here is a guide to the data wrangling tools available, organized by purpose.\nVisually cleanse your data Easily merge map data with thematic data Quickly understand JSON structure Fix character encoding issues Easily convert addresses to latitude/longitude Extract table data from PDFs Remove furigana from Aozora Bunko texts Use Mapbox Studio base maps in Foursquare Studio or Kepler.gl Reduce map data file size Quickly create buffer zones around POIs Create custom map data Format and convert map data Convert bus route data to network data Convert SVG for use in graphic tools Visually cleanse your data dataviz.jpOpenRefineData cleansing and transformation tool for tabular dataopen-refine.dataprep.jp Easily merge map data with thematic data dataprep.jp(Geo) DataMergerEasily merge geographic data with thematic datageo-data-merger.dataprep.jp Quickly understand JSON structure dataprep.jpJSON CrackVisually understand JSON data structures in your browserjsoncrack.dataprep.jp Fix character encoding issues dataprep.jpShift JIS ⇄ UTF-8 ConverterConvert character encoding between Shift JIS and UTF-8change-character-encoding.dataprep.jp Easily convert addresses to latitude/longitude dataprep.jpAddress to Lat/Lon ConverterGeocoding tooladdress-to-latlon.dataprep.jp Extract table data from PDFs dataprep.jpTabula PDFExtract table data from PDFstabula-pdf.dataprep.jp Remove furigana from Aozora Bunko texts dataprep.jpAozora Furigana RemoverRemove furigana and metadata from Aozora Bunko novelsaozora-furigana.dataprep.jp Use Mapbox Studio base maps in Foursquare Studio or Kepler.gl dataprep.jpMapbox Classic StylesMapbox map tiles for use with Kepler.gl and Foursquare Studioclassic-mapbox-styles.dataprep.jp Reduce map data file size dataprep.jpMapshaperProcess and convert map datamapshaper.dataprep.jp Quickly create buffer zones around POIs dataprep.jpTurf BufferEasily create radius buffers in your browserturf-buffer.dataprep.jp Create custom map data dataprep.jpGeoJSON.ioTrace map tiles to create GeoJSONgeojson.dataprep.jp Format and convert map data dataprep.jpLat/Lon FormatterEasily convert latitude/longitude decimal placeslatlon-formatter.dataprep.jp dataprep.jpTransform CoordinatesConvert coordinates of geographic feature filestransform-coordinates.dataprep.jp Convert bus route data to network data dataprep.jpGTFS to NetworkConvert GTFS transit data to network datagtfs-to-network.dataprep.jp Convert SVG for use in graphic tools dataprep.jpSVG ⇄ GeoJSON ConverterConvert between GeoJSON and SVG formatsgeojson-and-svg.dataprep.jp ","date":"0001-01-01T00:00:00Z","permalink":"https://www.dataprep.jp/en/how-to-use-data-wrangling/","title":"Choosing the Right Data Wrangling Tool"},{"content":" dataprep.jpGeoJSON.io地図タイルをトレースしてGeoJSON作成geojson.dataprep.jp What is this tool? A simple browser-based tool for creating, viewing, and sharing spatial data (such as GeoJSON). You can draw and edit geographic data on a map, and the corresponding GeoJSON is generated instantly, making it ideal for prototyping and verifying spatial data.\nFeatures Draw and edit data on a map\u0026hellip;Draw markers (points), polylines (lines), and polygons (areas) on the map and freely edit them. Real-time code editing and preview\u0026hellip;Drawn shapes are instantly updated and displayed as GeoJSON code, and attribute editing is also supported. Multi-format import\u0026hellip;Import and edit spatial data including GeoJSON, TopoJSON, CSV, KML, and more (historically supported by the tool). Simple attribute editing\u0026hellip;Edit and delete field values in table view to adjust Feature properties. How to use Load data or create new drawings\u0026hellip;Upload existing GeoJSON, or draw points, lines, and polygons on the map. Edit attributes and code\u0026hellip;Interactively edit drawings and attribute information. Save and share\u0026hellip;Download the completed GeoJSON as a file or share via URL parameters. Data formats Input formats GeoJSON: A JSON format centered on geographic Features (points, lines, areas). TopoJSON / CSV / KML / GPX, etc.: Multiple geographic data formats can be loaded and converted to GeoJSON for editing. Output formats GeoJSON, TopoJSON, CSV, KML, WKT, Shapefile ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/geojson/images/cover_geojson_hu_ae87efc44c887c27.jpg","permalink":"https://www.dataprep.jp/en/geojson/","title":"GeoJSON.io"},{"content":" dataprep.jpGTFSネットワークデータ変換交通データGTFSをネットワーク・データに変換しますgtfs-to-network.dataprep.jp What is this tool? Converts GTFS data, a common format for transit information, into network data.\nFeatures Uses stop information (stops.txt) and stop time information (stop_times.txt) to generate network data in CSV format.\n1. stops.txt (used as node information) Variable Description Required Usage stop_id Stop ID Yes Used as node ID (source/target). stop_name Stop name Yes Node name attribute. Also assigned as origin/destination names for links. stop_lat Latitude Yes Node coordinates. stop_lon Longitude Yes Node coordinates. 2. stop_times.txt (used for link aggregation) Variable Description Required Usage trip_id Trip ID Yes Used for grouping to identify movements (A to B) within the same trip. stop_id Stop ID Yes Identifies the source and target of each link. stop_sequence Stop sequence Yes Determines travel order within a trip (used for sorting). arrival_time Arrival time Yes Calculates link travel time (next stop arrival - current stop departure). departure_time Departure time Yes Calculates link travel time. Output data attributes (aggregated/calculated values) CSV Header Description Calculation Method frequency Number of trips Count of trip_ids traversing the same segment (source to target). avg_duration_sec Average travel time (seconds) Average travel time for the same segment. How to use Upload GTFS files\u0026hellip;Load the target files via drag-and-drop or file selection. Specify the current format\u0026hellip;Select whether it is 1 file or 2 files. Press the convert button\u0026hellip; After conversion, the file is automatically downloaded. Data formats Input formats GTFS: Stop information (stops.txt) GTFS: Stop time information (stop_times.txt) Output formats CSV (single-file format): Nodes and links combined in a single file CSV (two-file format): Nodes and links in separate files ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/gtfs-to-network/images/gtfs-to-network_hu_a77a17226dc49fbb.png","permalink":"https://www.dataprep.jp/en/gtfs-to-network/","title":"GTFSネットワークデータ変換"},{"content":" dataprep.jpJapanese-Western Calendar ConverterConvert between Japanese era dates and Western datescalendar-converter.dataprep.jp What is this tool? A browser-based tool for converting between Japanese era dates (Showa, Heisei, Reiwa) and Western calendar dates. You can type a date and see the conversion in real time, or drop a CSV file to auto-detect date columns and batch-convert them for download. All processing runs entirely in your browser — no data is ever sent to a server.\nFeatures Real-time conversion — Type in either the Japanese era or Western date field, and the other field updates instantly CSV batch conversion — Drag \u0026amp; drop a CSV file to auto-detect date columns and batch-convert them. Preview the results before downloading Auto character encoding detection — Automatically detects UTF-8 and Shift_JIS, so CSV files created in Excel can be loaded as-is Multiple date formats supported — Accepts commonly used formats such as R6.3.22, 令和6年3月22日, 2024/03/22, 2024-03-22, and more Output format options — When converting to Japanese era dates, choose between alphabetic notation (R6.3.22) or kanji notation (令和6年3月22日) Bilingual UI — The interface displays in Japanese or English based on your browser\u0026rsquo;s language setting How to use Manual conversion Enter a date in either the \u0026ldquo;Japanese era\u0026rdquo; or \u0026ldquo;Western\u0026rdquo; input field at the top of the page The converted result appears automatically in the other field Batch file conversion Drag \u0026amp; drop a CSV file onto the drop area (or click to select a file) Date columns are auto-detected and a before/after preview is displayed Select the conversion direction (Japanese era → Western / Western → Japanese era) and format as needed Click \u0026ldquo;Convert and Download\u0026rdquo; to download the converted CSV Data formats Supported input formats Type Example formats Japanese era (alphabetic) S49.9.24, H1-1-8, R6/3/22 Japanese era (kanji) 昭和49年9月24日, 令和元年5月1日 Western 2024/03/22, 2024-03-22, 2024.3.22 Supported eras Era Abbreviation Period Showa (昭和) S 1926/12/25 – 1989/01/07 Heisei (平成) H 1989/01/08 – 2019/04/30 Reiwa (令和) R 2019/05/01 – Batch file conversion Supported file formats: CSV, TSV, TXT Delimiters (comma, tab) are auto-detected Character encoding (UTF-8, Shift_JIS) is auto-detected Output is UTF-8 (with BOM) CSV, which opens directly in Excel ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/calendar-converter/images/cover_calendar-converter_hu_7e2df5b673914b7b.png","permalink":"https://www.dataprep.jp/en/calendar-converter/","title":"Japanese-Western Calendar Converter"},{"content":" dataprep.jpJSON Crackブラウザ上で JSON データ構造を視覚的に理解するjsoncrack.dataprep.jp What is this tool? JSON Crack is a web-based data visualization tool. It is designed to help you visually understand JSON data structures in your browser.\nFeatures Visualizes JSON and structured data as node-and-edge graphs or trees, with expand and collapse capabilities. How to use Input data\u0026hellip;Paste JSON or upload from a file. An interactive node diagram or tree is rendered based on the input content. Expand/collapse, search, zoom, and other operations as needed. Data formats JSON ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/jsoncrack/images/cover_jsoncrack_hu_37733359dd5c8324.png","permalink":"https://www.dataprep.jp/en/jsoncrack/","title":"JSON Crack"},{"content":" dataprep.jpMapbox Classic スタイル生成Kepler.gl や Foursquare Studio で利用可能な Mapbox 地図タイルclassic-mapbox-styles.dataprep.jp What is this tool? A web tool for generating and managing style definitions (JSON) for legacy Mapbox Classic styles. Mapbox Classic was a set of classic map style templates provided by Mapbox, used to generate and serve map styles compatible with map tools such as Kepler.gl and Foursquare Studio.\nFeatures Mapbox Classic style generation\u0026hellip;Generate and reference Classic style JSON files (e.g., Streets, Light, Dark, etc.). Compatible with Kepler.gl and similar tools\u0026hellip;Use the generated styles as base maps in map visualization tools like Kepler.gl. Template management\u0026hellip;Organizes Mapbox Classic standard templates for easy access, with features to retrieve and edit JSON as needed. How to use Obtain a Mapbox token Enter your Mapbox token Select a style template\u0026hellip;Choose a Classic style (e.g., Light / Dark / Streets, etc.). Generate JSON\u0026hellip;Generate the Mapbox Classic style JSON based on your selection and edits. Import\u0026hellip;Import the generated style JSON into Mapbox Studio. Base maps created in Mapbox Studio can be used in Kepler.gl and Foursquare Studio. Data formats Mapbox token\n","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/classic-mapbox-styles/images/cover_classic-mapbox-styles_hu_eaa1546adb32feee.png","permalink":"https://www.dataprep.jp/en/classic-mapbox-styles/","title":"Mapbox Classic スタイル生成"},{"content":" dataprep.jpMapshapermapshaper.dataprep.jp What is this tool? A web-based tool for editing, converting, and simplifying geospatial vector data (GIS). It loads map data and lets you intuitively perform operations such as shape simplification, attribute editing, and format conversion. Its key advantage is the ability to process data in the browser without relying on desktop GIS software.\nFeatures Load and display geographic data: Import and display vector data such as Shapefile, GeoJSON, and TopoJSON. Shape simplification: Reduce polygon/line vertices to shrink file size while preserving topology. Attribute data editing: Modify and join attribute table contents, or delete unnecessary fields. Conversion and export: Convert and export to multiple formats (Shapefile, GeoJSON, TopoJSON, CSV, TSV, SVG, etc.). Clipping and dissolving: GIS processing such as clipping, merging, splitting, and dropping data. How to use Load and display data\u0026hellip;Imported geographic data is displayed in map view, where you can review attributes and shapes. Edit and process Simplification: Run tools for vertex reduction and topology preservation. Attribute editing: Add, delete, or join fields. Merge and clip: Merge multiple datasets or clip to a specified area. Export\u0026hellip;Save and download in the desired format from the Export menu. Data formats Mapshaper handles the following major GIS vector data formats for input and output: Shapefile (ESRI\u0026rsquo;s standard GIS format; a set of .shp/.dbf/.shx files, etc.) GeoJSON (JSON-based geographic information format) TopoJSON (topology-compressed format based on GeoJSON) CSV / TSV (as tabular data containing coordinates and attributes) SVG (as vector image output for geographic shapes) ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/mapshaper/images/cover_mapshaper_hu_a8429bf9d44435c0.jpg","permalink":"https://www.dataprep.jp/en/mapshaper/","title":"Mapshaper"},{"content":" dataviz.jpOpenRefine表データのクレンジング・ツールopen-refine.dataprep.jp What is this tool? OpenRefine is a tool for cleaning (deduplication, inconsistency correction, formatting) and transforming tabular data in the browser. It can process large volumes of data in batch, significantly reducing the need for manual corrections.\nIt can save the state of your cleansing work on the server side, and also record cleansing procedures for reapplication to similar files.\nFeatures Filtering and faceting for narrowing down and reviewing values Column splitting/merging, value replacement, whitespace and symbol normalization Duplicate detection and clustering for inconsistency correction Batch transformation using expressions (GREL) Reconciliation with external data sources How to use Load data in CSV / TSV / Excel / JSON or other formats Use Facets and filters to identify problematic values Clean up data using transformations, replacements, and clustering Export in the desired format Data formats Input: CSV, TSV, Excel (xls/xlsx), Google Sheets, JSON, XML, OpenDocument, etc. Output: CSV, TSV, Excel, JSON, etc. Official documentation site dataviz.jpOpenRefineの公式解説サイトOpenRefine解説open-refine-doc.dataviz.jp ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/open-refine/images/cover_open-refine_hu_ec23e442c008b09a.jpg","permalink":"https://www.dataprep.jp/en/open-refine/","title":"OpenRefine"},{"content":" dataprep.jpShift JIS ⇄ UTF-8 文字コード変換ツール文字コードを、Shift JIS ⇄ UTF-8 間で相互に変換change-character-encoding.dataprep.jp What is this tool? A tool that converts text file character encodings between Shift JIS and UTF-8 in both directions.\nFiles intended for use with Excel are often distributed in Shift JIS encoding. Most modern tools assume UTF-8 encoding. This is a simple utility to bridge that gap.\nFeatures Shift JIS to UTF-8 conversion: Converts text in the Shift JIS character encoding, commonly used by legacy systems and Excel, to UTF-8. UTF-8 to Shift JIS conversion: Converts text in UTF-8 format to Shift JIS, making it usable with legacy software and older systems. How to use Enter or upload the text you want to convert. Copy or download the converted text. The tool automatically detects whether the file is Shift JIS or UTF-8.\nData formats Tabular data (CSV, TSV, DSV) JSON ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/change-character-encoding/images/cover-change-character-encoding_hu_8bdd74485d262c60.png","permalink":"https://www.dataprep.jp/en/change-character-encoding/","title":"Shift JIS ⇄ UTF-8 文字コード変換ツール"},{"content":" dataprep.jpSVG ⇄ GeoJSON 変換ツールGeoJSON と SVG の相互変換を支援geojson-and-svg.dataprep.jp What is this tool? A web-based tool that assists with converting and visualizing between geospatial data (GeoJSON) and SVG (vector image format).\nIt is designed to convert geographic information such as map data and polygons into the SVG format, which is convenient for web display and print use, or to help work with SVG as GeoJSON format.\nGeoJSON is a standard JSON-based format for location data, widely used for web mapping and GIS integration.\nFeatures Bi-directional conversion between geospatial data (GeoJSON) and SVG (vector image format)\nHow to use Load a file Download No special operations are required.\nData formats SVG GeoJSON ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/geojson-and-svg/images/cover_geojson-and-svg_hu_f219570676423a6.jpg","permalink":"https://www.dataprep.jp/en/geojson-and-svg/","title":"SVG ⇄ GeoJSON 変換ツール"},{"content":" dataprep.jpTabula PDFPDFから表データを取り出すtabula-pdf.dataprep.jp What is this tool? Tabula PDF is a tool for extracting tables from PDFs and converting them into reusable formats. It is useful when you want to use tables from PDFs published as government documents, survey reports, handouts, and similar materials as data.\nYou can specify the area of the table to extract on the page, and export it as CSV / JSON / Excel format. It helps you create a starting point for data processing in situations where \u0026ldquo;you have the PDF but not the original data.\u0026rdquo;\nFeatures Table extraction from PDF (page-by-page and multi-page support) Manual selection of table regions (drag) with extraction preview Switching extraction modes (rule-based / whitespace-based) Batch output of multiple tables Download in CSV / JSON / Excel formats How to use Upload a PDF file Open the target page and select the table area to extract Choose the extraction mode and review the preview If everything looks correct, export as CSV / JSON / Excel Data formats Input: PDF Output: CSV, JSON, Excel Notes This tool is intended for use with PDFs that contain text data. For PDFs consisting primarily of scanned images, running OCR beforehand will improve extraction accuracy. ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/tabula-pdf/images/cover_tabula-pdf_hu_c06dcf09899ec484.jpg","permalink":"https://www.dataprep.jp/en/tabula-pdf/","title":"Tabula PDF"},{"content":" dataprep.jpText Entity Extraction Tooltext-entity.dataprep.jp What is this tool? A browser-based tool that uses regular expressions to batch-extract hashtags, mentions, URLs, email addresses, and phone numbers from text in CSV/TSV tabular data. All data is processed in your browser and never sent to a server.\nFeatures 5 entity types: Hashtags (#), mentions (@), URLs, email addresses, phone numbers CSV/TSV support: Load data via file upload or paste into the text area Column selection: Choose the target column with sample values displayed Preview: Review loaded data before extraction CSV export: Download results as CSV with extracted columns appended to the original data (UTF-8 with BOM) Japanese/English support: Auto-switches based on browser language; manual switching also available How to use Input data — Drag \u0026amp; drop a CSV file, or paste CSV/TSV data into the text area Preview — Check the number of columns and rows (first 100 rows displayed) Configure \u0026amp; extract — Select the target column and entity type (hashtag / mention / URL / email / phone number), then click \u0026ldquo;Extract\u0026rdquo; Review \u0026amp; download — Check the extraction count and click \u0026ldquo;Download CSV\u0026rdquo; to save the results Data format Input: CSV (comma-separated), TSV (tab-separated), TXT Header: Option to treat the first row as column names (if no header, columns are auto-named \u0026ldquo;Column 1, Column 2, \u0026hellip;\u0026rdquo;) Output: CSV (UTF-8 with BOM) containing all original columns plus an appended extraction result column. Multiple entities in a single cell are joined with commas ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/text-entity/images/cover_text-entity_hu_5dd91ae87348b722.jpg","permalink":"https://www.dataprep.jp/en/text-entity/","title":"Text Entity Extraction Tool"},{"content":"Use this pattern when you want to clean inconsistent labels, blanks, duplicate rows, or unnecessary columns in CSV or Excel data while visually checking the result.\nSolution Choose a tool that lets you inspect value distributions, filter problem rows, and apply replacements step by step. If you also want to reuse the same preparation flow on other files, a tool with saved transformation history is a strong fit.\nTool dataprep.jpOpenRefineData cleansing and transformation tool for tabular dataopen-refine.dataprep.jp Good fit for Cleaning public datasets Preparing files before record matching Reducing manual find-and-replace work ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-visual-data-cleansing/","title":"Visually cleanse your data"},{"content":" dataprep.jpバッファ生成ツールturf-buffer.dataprep.jp What is this tool? A web-based spatial analysis tool that generates \u0026ldquo;buffers (buffer zones)\u0026rdquo; at a specified distance around geospatial data (points, lines, polygons).\nA buffer is a polygon area that expands a specified distance around a given feature, and is a technique commonly used in GIS spatial analysis.\nWhen creating data maps with buffers such as \u0026ldquo;within a 10-minute walk from a certain point,\u0026rdquo; using the desktop application QGIS requires the following steps:\nConvert the data file from a geographic coordinate system to a projected coordinate system that varies by region Perform the buffering operation Convert back to the geographic coordinate system for output This tool eliminates this complex workflow, enabling completion in just a few clicks within the browser.\nFeatures Buffer generation Creates a buffer zone at a specified distance (radius) around the input points, lines, or polygons. Map preview View the loaded data and generated buffer areas on a web map. Output format Download buffer results as GeoJSON or SVG. How to use Upload CSV data\u0026hellip;Select a CSV file containing latitude and longitude columns. Specify buffer parameters\u0026hellip;Enter the buffer radius (in meters). Generate and review the buffer\u0026hellip;Press the create button, and the buffer areas are drawn on the map. Download\u0026hellip;Download the results in GeoJSON or SVG format. Data formats Input formats CSV (tabular data containing latitude and longitude) is loaded for processing. Output formats GeoJSON: Retrieve the generated buffer areas in GeoJSON format. SVG: Download as an SVG vector image. ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/turf-buffer/images/cover_turf-buffer_hu_d61fd0b7791dab9f.png","permalink":"https://www.dataprep.jp/en/turf-buffer/","title":"バッファ生成ツール"},{"content":" dataprep.jp住所 → 緯度経度 変換ツールaddress-to-latlon.dataprep.jp What is this tool? A web-based tool that converts Japanese address data into latitude and longitude (coordinates) through geocoding. It can batch-convert multiple addresses into GPS coordinates for use in map creation and location analysis.\nFeatures Batch conversion (CSV support)\u0026hellip;Upload a CSV file containing multiple addresses, and retrieve latitude and longitude for each address. High-accuracy geocoding\u0026hellip;Uses Geolonia\u0026rsquo;s community geocoder (based on the Ministry of Land, Infrastructure, Transport and Tourism\u0026rsquo;s Address Reference Information), achieving conversion accuracy specialized for Japanese addresses. Character encoding support\u0026hellip;You can specify the character encoding of the input file (UTF-8 / Shift_JIS). Browser-only processing\u0026hellip;Data is processed entirely within the browser and is never sent to a server (privacy protection). How to use Upload a CSV file\u0026hellip;Load address data by clicking or drag-and-dropping a CSV file. Specify the character encoding\u0026hellip;Select the appropriate encoding from UTF-8 / Shift_JIS. Run the conversion\u0026hellip;A CSV file with automatically added latitude and longitude columns is generated. Download / Use\u0026hellip;Download the output CSV and import it into map rendering or analysis tools. Data formats Tabular data (CSV) ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/address-to-latlon/images/cover_address-to-latlon_hu_288ec926a34ea61c.jpg","permalink":"https://www.dataprep.jp/en/address-to-latlon/","title":"住所 → 緯度経度 変換ツール"},{"content":" dataprep.jp座標系 変換ツール地物ファイルの座標を変換transform-coordinates.dataprep.jp ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/transform-coordinates/images/cover_transform-coordinates_hu_9ae682531bcd5005.png","permalink":"https://www.dataprep.jp/en/transform-coordinates/","title":"座標系 変換ツール"},{"content":" dataprep.jp緯度経度フォーマッター緯度経度データの桁数を簡単に変換latlon-formatter.dataprep.jp What is this tool? A web tool for easily converting the format of latitude and longitude data within CSV files. It is useful when you need to organize and standardize coordinate notation formats when working with geographic data.\nFeatures Format conversion Bi-directional conversion between single-column format (latitude and longitude in one cell, e.g., \u0026ldquo;35.6762,139.6503\u0026rdquo;) and two-column format (separate latitude and longitude columns). Auto-detection Automatically detects latitude and longitude columns in the input CSV. Data preview View the CSV before and after conversion on the spot. Decimal precision adjustment Adjust the number of decimal places for latitude and longitude values. Download Download the converted CSV as a file. Browser-only processing All processing is completed within the browser with no server communication required. How to use Upload a CSV\u0026hellip;Load the target CSV via drag-and-drop or file selection. Specify the current format\u0026hellip;Select whether latitude and longitude are in single-column or two-column format. Choose the output format\u0026hellip;Select the desired single-column or two-column format. Adjust precision (optional)\u0026hellip;Set the number of decimal places for latitude and longitude. Convert and download\u0026hellip;After running the conversion, review the preview and download the CSV. Data formats Input formats CSV: Tabular data with latitude and longitude in either single-column or two-column notation. Output formats CSV (single-column format): Latitude and longitude combined in a single field as \u0026ldquo;latitude,longitude\u0026rdquo;. CSV (two-column format): Standard format with separate latitude and longitude columns. ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/latlon-formatter/images/cover_latlon-formatter_hu_773826b6b511e8b3.png","permalink":"https://www.dataprep.jp/en/latlon-formatter/","title":"緯度経度フォーマッター"},{"content":" dataprep.jp青空文庫ルビ削除ツール青空文庫の小説からルビとメタデータを削除aozora-furigana.dataprep.jp ","date":"0001-01-01T00:00:00Z","image":"https://www.dataprep.jp/aozora-furigana/images/cover_aozora-furigana_hu_ceb1533af962d02f.jpg","permalink":"https://www.dataprep.jp/en/aozora-furigana/","title":"青空文庫ルビ削除ツール"},{"content":"Use this pattern when you have geographic boundaries in one file and statistics in CSV or Excel, and want to combine them quickly for mapping.\nSolution First align a shared key such as municipality code or place name. Then use a tool that accepts both geographic data and tabular data and lets you inspect the join result before exporting.\nTool dataprep.jp(Geo) DataMergerEasily merge geographic data with thematic datageo-data-merger.dataprep.jp Good fit for Mapping statistics by municipality Testing multiple boundary datasets Checking join errors before visualization ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-merge-map-and-data/","title":"Easily merge map data with thematic data"},{"content":"Use this pattern when an API response or configuration JSON is complex and you need to quickly see where the fields you need actually live.\nSolution Instead of reading raw text, visualize the JSON as connected nodes. That makes parent-child relationships and nested arrays much easier to understand before you extract or transform anything.\nTool dataprep.jpJSON CrackVisually understand JSON data structures in your browserjsoncrack.dataprep.jp Good fit for Inspecting API responses Understanding third-party data structures Preparing JSON for tabular conversion ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-understand-json-structure/","title":"Quickly understand JSON structure"},{"content":"Use this pattern when Japanese text becomes garbled after opening a CSV, or when a GIS or spreadsheet app fails to read the file correctly.\nSolution Identify the original encoding first, then convert the file into the encoding expected by the next tool. A fast converter makes it easy to validate both directions before sharing or importing the data.\nTool dataprep.jpShift JIS ⇄ UTF-8 ConverterConvert character encoding between Shift JIS and UTF-8change-character-encoding.dataprep.jp Good fit for Preparing CSV files for distribution Fixing import errors in Japanese datasets Moving files between different systems ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-fix-character-encoding/","title":"Fix character encoding issues"},{"content":"Use this pattern when you have addresses for stores or facilities, but need latitude and longitude before you can map or analyze them.\nSolution Convert addresses into coordinate columns first, then move on to visualization or spatial analysis. Batch geocoding is much more reliable and efficient than checking each point manually.\nTool dataprep.jpAddress to Lat/Lon ConverterGeocoding tool for converting address lists into coordinatesaddress-to-latlon.dataprep.jp Good fit for Mapping store or facility locations Running spatial analysis on address-based data Avoiding manual coordinate lookup ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-address-to-latlon/","title":"Easily convert addresses to latitude/longitude"},{"content":"Use this pattern when a report or government document includes tables in PDF form and you want to extract them without manual re-entry.\nSolution Select the tabular region first, then extract it while preserving rows and columns. Once the table is out, you can clean headers and blanks in a separate step.\nTool dataprep.jpTabula PDFExtract table data from PDFstabula-pdf.dataprep.jp Good fit for Reusing tables from public documents Extracting figures from survey reports Reducing manual data entry ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-extract-tables-from-pdf/","title":"Extract table data from PDFs"},{"content":"Use this pattern when your map data is too heavy to load comfortably in the browser, share with others, or import into a visualization tool.\nSolution Simplify geometry while preserving shape, and remove attributes you do not need. A tool that also handles conversion and merging helps keep the whole preprocessing flow in one place.\nTool dataprep.jpMapshaperProcess and convert map datamapshaper.dataprep.jp Good fit for Making GeoJSON faster to render Preparing smaller map files for sharing Cleaning attributes while simplifying geometry ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-reduce-map-data-file-size/","title":"Reduce map data file size"},{"content":"Use this pattern when decimal precision or coordinate reference systems are inconsistent and your map data does not line up correctly in the next tool.\nSolution Standardize latitude/longitude formatting first, then convert the coordinate system if needed. Splitting the work into formatting and projection changes makes it easier to isolate the source of location errors.\nTools dataprep.jpLat/Lon FormatterStandardize latitude/longitude format and precisionlatlon-formatter.dataprep.jp dataprep.jpTransform CoordinatesConvert the coordinate system of geographic filestransform-coordinates.dataprep.jp Good fit for Mixing map data from different coordinate systems Normalizing latitude/longitude precision Troubleshooting positional offsets ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-format-map-data/","title":"Format and convert map data"},{"content":"Use this pattern when the points, lines, or polygons you need are not available as ready-made data and you have to create them yourself.\nSolution Use a tool that lets you draw points, lines, and polygons directly on top of a base map and export GeoJSON. Start with the minimum area or features you need, then add attributes afterward.\nTool dataprep.jpGeoJSON.ioCreate GeoJSON while tracing over map tilesgeojson.dataprep.jp Good fit for Creating a small custom map dataset Drawing survey points or movement paths Building GeoJSON without a full GIS workflow ","date":"0001-01-01T00:00:00Z","image":"https://visualizing.jp/gridded-cartogram/images/thumb_ph_vizjp_hu_982f6515b909acd4.png","permalink":"https://www.dataprep.jp/en/pattern-create-map-data/","title":"Create custom map data"}]