Data Prep Toolbox

(Geo) DataMerger

Mon, 01 Jan 0001 00:00:00 +0000

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.

Features

Load geographic and attribute data…Read GeoJSON/TopoJSON, CSV, and JSON files, and preview their contents.
Key-based join…Join geographic data (Feature properties) with attribute data using a common key column (left join basis).
Remove unnecessary columns…After merging, select and remove unwanted columns from the output via the UI.
Output format selection…Save and download the merged data as GeoJSON/TopoJSON/CSV.

How to use

1. Load geographic and attribute data…Load GeoJSON/TopoJSON on the left side and CSV/JSON on the right side.
1. Specify the join key…Select the column (key) used for joining from each data preview, and verify that they match correctly.
1. Remove unnecessary columns…Select and delete unneeded attribute columns after merging.
1. Export and save…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.

Choosing the Right Data Wrangling Tool

Mon, 01 Jan 0001 00:00:00 +0000

Here is a guide to the data wrangling tools available, organized by purpose.

Visually cleanse your data

dataviz.jp

OpenRefine

Data cleansing and transformation tool for tabular data

open-refine.dataprep.jp

Easily merge map data with thematic data

dataprep.jp

(Geo) DataMerger

Easily merge geographic data with thematic data

geo-data-merger.dataprep.jp

Quickly understand JSON structure

dataprep.jp

JSON Crack

Visually understand JSON data structures in your browser

jsoncrack.dataprep.jp

Fix character encoding issues

dataprep.jp

Shift JIS ⇄ UTF-8 Converter

Convert character encoding between Shift JIS and UTF-8

change-character-encoding.dataprep.jp

Easily convert addresses to latitude/longitude

dataprep.jp

Address to Lat/Lon Converter

Geocoding tool

address-to-latlon.dataprep.jp

Extract table data from PDFs

dataprep.jp

Tabula PDF

Extract table data from PDFs

tabula-pdf.dataprep.jp

Remove furigana from Aozora Bunko texts

dataprep.jp

Aozora Furigana Remover

Remove furigana and metadata from Aozora Bunko novels

aozora-furigana.dataprep.jp

Use Mapbox Studio base maps in Foursquare Studio or Kepler.gl

dataprep.jp

Mapbox Classic Styles

Mapbox map tiles for use with Kepler.gl and Foursquare Studio

classic-mapbox-styles.dataprep.jp

Reduce map data file size

dataprep.jp

Mapshaper

Process and convert map data

mapshaper.dataprep.jp

Quickly create buffer zones around POIs

dataprep.jp

Turf Buffer

Easily create radius buffers in your browser

turf-buffer.dataprep.jp

Create custom map data

dataprep.jp

GeoJSON.io

Trace map tiles to create GeoJSON

geojson.dataprep.jp

Format and convert map data

dataprep.jp

Lat/Lon Formatter

Easily convert latitude/longitude decimal places

latlon-formatter.dataprep.jp

dataprep.jp

Transform Coordinates

Convert coordinates of geographic feature files

transform-coordinates.dataprep.jp

Convert bus route data to network data

dataprep.jp

GTFS to Network

Convert GTFS transit data to network data

gtfs-to-network.dataprep.jp

Convert SVG for use in graphic tools

dataprep.jp

SVG ⇄ GeoJSON Converter

Convert between GeoJSON and SVG formats

geojson-and-svg.dataprep.jp

GeoJSON.io

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

GeoJSON.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.

Features

Draw and edit data on a map…Draw markers (points), polylines (lines), and polygons (areas) on the map and freely edit them.
Real-time code editing and preview…Drawn shapes are instantly updated and displayed as GeoJSON code, and attribute editing is also supported.
Multi-format import…Import and edit spatial data including GeoJSON, TopoJSON, CSV, KML, and more (historically supported by the tool).
Simple attribute editing…Edit and delete field values in table view to adjust Feature properties.

How to use

Load data or create new drawings…Upload existing GeoJSON, or draw points, lines, and polygons on the map.
Edit attributes and code…Interactively edit drawings and attribute information.
Save and share…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

GTFSネットワークデータ変換

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

GTFS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.

Features

Uses stop information (stops.txt) and stop time information (stop_times.txt) to generate network data in CSV format.

1. 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_id`s traversing the same segment (source to target).
`avg_duration_sec`	Average travel time (seconds)	Average travel time for the same segment.

How to use

1. Upload GTFS files…Load the target files via drag-and-drop or file selection.
1. Specify the current format…Select whether it is 1 file or 2 files.
1. Press the convert button…
1. 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

Japanese-Western Calendar Converter

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Japanese-Western Calendar Converter

Convert between Japanese era dates and Western dates

calendar-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.

Features

Real-time conversion — Type in either the Japanese era or Western date field, and the other field updates instantly
CSV batch conversion — Drag & 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’s language setting

How to use

Manual conversion

Enter a date in either the “Japanese era” or “Western” input field at the top of the page
The converted result appears automatically in the other field

Batch file conversion

Drag & 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 “Convert and Download” 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

JSON Crack

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

JSON 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.

Features

Visualizes JSON and structured data as node-and-edge graphs or trees, with expand and collapse capabilities.

How to use

1. Input data…Paste JSON or upload from a file.
1. An interactive node diagram or tree is rendered based on the input content.
1. Expand/collapse, search, zoom, and other operations as needed.

Data formats

JSON

Mapbox Classic スタイル生成

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Mapbox 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.

Features

Mapbox Classic style generation…Generate and reference Classic style JSON files (e.g., Streets, Light, Dark, etc.).
Compatible with Kepler.gl and similar tools…Use the generated styles as base maps in map visualization tools like Kepler.gl.
Template management…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…Choose a Classic style (e.g., Light / Dark / Streets, etc.).
Generate JSON…Generate the Mapbox Classic style JSON based on your selection and edits.
Import…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

Mapshaper

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Mapshaper

mapshaper.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.

Features

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

1. Load and display data…Imported geographic data is displayed in map view, where you can review attributes and shapes.
1. 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.
1. Export…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’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)

OpenRefine

Mon, 01 Jan 0001 00:00:00 +0000

dataviz.jp

OpenRefine

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.

It can save the state of your cleansing work on the server side, and also record cleansing procedures for reapplication to similar files.

Features

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

1. Load data in CSV / TSV / Excel / JSON or other formats
1. Use Facets and filters to identify problematic values
1. Clean up data using transformations, replacements, and clustering
1. 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.jp

OpenRefineの公式解説サイト

OpenRefine解説

open-refine-doc.dataviz.jp

Shift JIS ⇄ UTF-8 文字コード変換ツール

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Shift 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.

Files 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.

Features

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

1. Enter or upload the text you want to convert.
1. Copy or download the converted text.

The tool automatically detects whether the file is Shift JIS or UTF-8.

Data formats

Tabular data (CSV, TSV, DSV)
JSON

SVG ⇄ GeoJSON 変換ツール

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

SVG ⇄ 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).

It 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.

GeoJSON is a standard JSON-based format for location data, widely used for web mapping and GIS integration.

Features

Bi-directional conversion between geospatial data (GeoJSON) and SVG (vector image format)

How to use

1. Load a file
1. Download

No special operations are required.

Data formats

SVG
GeoJSON

Tabula PDF

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Tabula PDF

PDF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.

You 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 “you have the PDF but not the original data.”

Features

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

1. Upload a PDF file
1. Open the target page and select the table area to extract
1. Choose the extraction mode and review the preview
1. 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.

Text Entity Extraction Tool

Mon, 01 Jan 0001 00:00:00 +0000

dataprep.jp

Text Entity Extraction Tool

text-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.

Features

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 & 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 & extract — Select the target column and entity type (hashtag / mention / URL / email / phone number), then click “Extract”
Review & download — Check the extraction count and click “Download CSV” 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 “Column 1, Column 2, …”)
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

Visually cleanse your data

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

OpenRefine

Data cleansing and transformation tool for tabular data

open-refine.dataprep.jp

Good fit for

Cleaning public datasets
Preparing files before record matching
Reducing manual find-and-replace work

バッファ生成ツール

Mon, 01 Jan 0001 00:00:00 +0000

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 “buffers (buffer zones)” at a specified distance around geospatial data (points, lines, polygons).

A buffer is a polygon area that expands a specified distance around a given feature, and is a technique commonly used in GIS spatial analysis.

When creating data maps with buffers such as “within a 10-minute walk from a certain point,” using the desktop application QGIS requires the following steps:

1. Convert the data file from a geographic coordinate system to a projected coordinate system that varies by region
1. Perform the buffering operation
1. 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.

Features

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

1. Upload CSV data…Select a CSV file containing latitude and longitude columns.
1. Specify buffer parameters…Enter the buffer radius (in meters).
1. Generate and review the buffer…Press the create button, and the buffer areas are drawn on the map.
1. Download…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.

住所 → 緯度経度変換ツール

Mon, 01 Jan 0001 00:00:00 +0000

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.

Features

Batch conversion (CSV support)…Upload a CSV file containing multiple addresses, and retrieve latitude and longitude for each address.
High-accuracy geocoding…Uses Geolonia’s community geocoder (based on the Ministry of Land, Infrastructure, Transport and Tourism’s Address Reference Information), achieving conversion accuracy specialized for Japanese addresses.
Character encoding support…You can specify the character encoding of the input file (UTF-8 / Shift_JIS).
Browser-only processing…Data is processed entirely within the browser and is never sent to a server (privacy protection).

How to use

1. Upload a CSV file…Load address data by clicking or drag-and-dropping a CSV file.
1. Specify the character encoding…Select the appropriate encoding from UTF-8 / Shift_JIS.
1. Run the conversion…A CSV file with automatically added latitude and longitude columns is generated.
1. Download / Use…Download the output CSV and import it into map rendering or analysis tools.

Data formats

Tabular data (CSV)

座標系変換ツール

Mon, 01 Jan 0001 00:00:00 +0000

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

緯度経度フォーマッター

Mon, 01 Jan 0001 00:00:00 +0000

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.

Features

Format conversion
Bi-directional conversion between single-column format (latitude and longitude in one cell, e.g., “35.6762,139.6503”) 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

1. Upload a CSV…Load the target CSV via drag-and-drop or file selection.
1. Specify the current format…Select whether latitude and longitude are in single-column or two-column format.
1. Choose the output format…Select the desired single-column or two-column format.
1. Adjust precision (optional)…Set the number of decimal places for latitude and longitude.
1. Convert and download…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 “latitude,longitude”.
- CSV (two-column format): Standard format with separate latitude and longitude columns.

青空文庫ルビ削除ツール

Mon, 01 Jan 0001 00:00:00 +0000

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

Easily merge map data with thematic data

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

(Geo) DataMerger

Easily merge geographic data with thematic data

geo-data-merger.dataprep.jp

Good fit for

Mapping statistics by municipality
Testing multiple boundary datasets
Checking join errors before visualization

Quickly understand JSON structure

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

JSON Crack

Visually understand JSON data structures in your browser

jsoncrack.dataprep.jp

Good fit for

Inspecting API responses
Understanding third-party data structures
Preparing JSON for tabular conversion

Fix character encoding issues

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

Shift JIS ⇄ UTF-8 Converter

Convert character encoding between Shift JIS and UTF-8

change-character-encoding.dataprep.jp

Good fit for

Preparing CSV files for distribution
Fixing import errors in Japanese datasets
Moving files between different systems

Easily convert addresses to latitude/longitude

Mon, 01 Jan 0001 00:00:00 +0000

Use this pattern when you have addresses for stores or facilities, but need latitude and longitude before you can map or analyze them.

Solution

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.

Tool

dataprep.jp

Address to Lat/Lon Converter

Geocoding tool for converting address lists into coordinates

address-to-latlon.dataprep.jp

Good fit for

Mapping store or facility locations
Running spatial analysis on address-based data
Avoiding manual coordinate lookup

Extract table data from PDFs

Mon, 01 Jan 0001 00:00:00 +0000

Use this pattern when a report or government document includes tables in PDF form and you want to extract them without manual re-entry.

Solution

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.

Tool

dataprep.jp

Tabula PDF

Extract table data from PDFs

tabula-pdf.dataprep.jp

Good fit for

Reusing tables from public documents
Extracting figures from survey reports
Reducing manual data entry

Reduce map data file size

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

Mapshaper

Process and convert map data

mapshaper.dataprep.jp

Good fit for

Making GeoJSON faster to render
Preparing smaller map files for sharing
Cleaning attributes while simplifying geometry

Format and convert map data

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tools

dataprep.jp

Lat/Lon Formatter

Standardize latitude/longitude format and precision

latlon-formatter.dataprep.jp

dataprep.jp

Transform Coordinates

Convert the coordinate system of geographic files

transform-coordinates.dataprep.jp

Good fit for

Mixing map data from different coordinate systems
Normalizing latitude/longitude precision
Troubleshooting positional offsets

Create custom map data

Mon, 01 Jan 0001 00:00:00 +0000

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.

Solution

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.

Tool

dataprep.jp

GeoJSON.io

Create GeoJSON while tracing over map tiles

geojson.dataprep.jp

Good fit for

Creating a small custom map dataset
Drawing survey points or movement paths
Building GeoJSON without a full GIS workflow