Data Toolbox

Visualize 3D data of row × column × value as a color-mapped surface resembling a topographic map

3D Surface Chart

3d-surface-chart.dataviz.jp

What is this tool?

A visualization tool that generates interactive 3D surface charts simply by loading CSV data. It lets you view data with a “row × column × value” structure — such as interest rate yield curves and regional statistics — as a three-dimensional landscape. Rotate and zoom freely with your mouse to intuitively grasp overall trends and local variations in your data.

Features

3D surface rendering — Automatically generates a color-mapped 3D surface from CSV data
Camera presets — Switch between four viewpoints (overview, front, top, side) with one click
Color schemes — Choose from 21 palettes (sequential and diverging). Diverging schemes support a zero-baseline mode
Axis labels — Toggle between horizontal and vertical text. Supports many categories such as Japanese prefecture names
CSV import — Load any CSV via file picker or drag-and-drop
Sample data — Preloaded datasets including Japan Ministry of Finance interest rates (from 1974), U.S. Treasury bonds, and births by prefecture
PNG export — Download high-resolution images with axis labels
Share — Share the current view (data, color scheme, camera position) via URL. OGP images for social media are generated automatically
Project save/load — Save your work to the cloud and restore it anytime

How to use

Open the page to see Japan Ministry of Finance interest rate data (last 5 years) displayed by default
Switch sample datasets from the dropdown, or load your own CSV
Drag to rotate, scroll to zoom, and right-drag to pan
Adjust the color scheme and camera position to create the best view
Click “Export” to download a PNG image, or “Share” to generate a shareable URL
Shared URLs are viewable by anyone

Data format

Use a pivot table (cross-tabulation) CSV file. Values are placed at the intersection of rows and columns — the same structure as an Excel pivot table.

        col1   col2   col3   ...
row1    5.53   5.47   5.36   ...
row2    5.42   5.38   5.25   ...

In CSV format:

label,col1,col2,col3,...
row1,5.53,5.47,5.36,...
row2,5.42,5.38,5.25,...

First column: Row labels (dates in YYYY-MM-DD format, fiscal years, category names, etc.) — mapped to the depth axis
Remaining columns: Numeric data columns — mapped to the horizontal axis. If column names use duration formats like 1Y or 10M, axis spacing is calculated automatically; otherwise, columns are evenly spaced
Cell values: Numbers — mapped to the height (vertical axis) and color map

Example: Births by prefecture

Year,Hokkaido,Aomori,Iwate,...,Okinawa
2011,39292,9532,9310,...,16918
2012,38686,9168,9277,...,17074

If your data is in long format, convert it to a pivot table using Excel or Python’s pivot() before loading.

References

The idea of using a 3D surface chart for time-series yield curves originated from The New York Times.

A 3-D View of a Chart That Predicts The Economic Future: The Yield Curve - The New York Times https://www.nytimes.com/interactive/2015/03/19/upshot/3d-yield-curve-economic-growth.html

Choosing the Right Data Visualization Tool

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

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

Create various charts

Exploratory data visualization

A visualization tool for Exploratory Data Analysis (EDA)

Voyager2

voyager2.dataviz.jp

parallel-coordinates.dataviz.jp

Parallel Coordinates

3D visualization

Display 3D data (row × column × value) as a colored surface, like a topographic map

3D Surface Chart

3d-surface-chart.dataviz.jp

3D map visualization

Visualization and exploration tool for large-scale geospatial data

kepler.gl

kepler-gl.dataviz.jp

Create data maps by prefecture or municipality

Easily create choropleth maps of Japan

Japan Choropleth Map

choropleth-japan.dataviz.jp

Easily create cartograms of Japan

Japan Cartogram

cartogram-japan.dataviz.jp

Prefecture Choropleth Map

Easily create choropleth maps of prefectures

choropleth-prefectures.dataviz.jp

Easily create cartograms of prefectures

Prefecture Cartogram

cartogram-prefectures.dataviz.jp

Create world data maps

Network visualization

Create Sankey diagrams with ease

Sankeymatic

sankeymatic.dataviz.jp

Cytoscape

Web version of Cytoscape

cytoscape.dataviz.jp

Create network graphs with ease

Gephi Lite

Text visualization

Word Cloud specialized for Japanese

Code-based quick visualization

Write visualization specs in JSON to render interactive graphs and charts in real time

Generate chart images with just a URL

QuickChart UI

quickchart.dataviz.jp

Design gradients for your charts

SVG Gradient Editor

svg-gradient.dataviz.jp

Design textures for your charts

SVG Texture Editor

svg-tectures.dataviz.jp

Easing Functions Cheat Sheet

Visualize parameter changes over time

easings.dataviz.jp

Animate aircraft and ship trajectories

ADS-B / AIS Visualization

Easily animate aircraft and ship movement data

bbts.dataviz.jp

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

Data cleansing and transformation tool for tabular data

OpenRefine

open-refine.dataviz.jp

Easily merge map data with thematic data

Easily merge geographic data with thematic data

(Geo) DataMerger

geo-data-merger.dataviz.jp

Quickly understand JSON structure

Visually understand JSON data structures in your browser

JSON Crack

jsoncrack.dataviz.jp

Fix character encoding issues

Shift JIS ⇄ UTF-8 Converter

Convert character encoding between Shift JIS and UTF-8

change-character-encoding.dataviz.jp

Easily convert addresses to latitude/longitude

Address to Lat/Lon Converter

Geocoding tool

address-to-latlon.dataviz.jp

Extract table data from PDFs

Extract table data from PDFs

Tabula PDF

tabula-pdf.dataviz.jp

Remove furigana from Aozora Bunko texts

Remove furigana and metadata from Aozora Bunko novels

Aozora Furigana Remover

aozora-furigana.dataviz.jp

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

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

Mapbox Classic Styles

classic-mapbox-styles.dataviz.jp

Reduce map data file size

Process and convert map data

Mapshaper

mapshaper.dataviz.jp

Quickly create buffer zones around POIs

Easily create radius buffers in your browser

Turf Buffer

turf-buffer.dataviz.jp

Create custom map data

Trace map tiles to create GeoJSON

GeoJSON.io

geojson.dataviz.jp

Format and convert map data

Easily convert latitude/longitude decimal places

Lat/Lon Formatter

latlon-formatter.dataviz.jp

Convert coordinates of geographic feature files

Transform Coordinates

transform-coordinates.dataviz.jp

Convert bus route data to network data

Convert GTFS transit data to network data

GTFS to Network

gtfs-to-network.dataviz.jp

Convert SVG for use in graphic tools

Convert between GeoJSON and SVG formats

SVG ⇄ GeoJSON Converter

geojson-and-svg.dataviz.jp

Easily identify map tile locations

Browse multiple open map tile types and check XYZ tile coordinates

Map Tile Browser

what-the-tile.dataviz.jp

Coloring Administrative District Maps with Data

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

Coloring administrative district maps — commonly known as blank maps — with data is called a “choropleth map.” Although sometimes referred to as a “classified area map,” that term actually describes a data processing technique, not a visualization type.

Using our “Japan Choropleth Map” and “Prefecture Choropleth Map” tools, you can easily create high-quality choropleth maps.

Here we introduce how to create one using our tools.

Fukushima Prefecture: Population Change Rate 2011–2024

choropleth-prefectures.dataviz.jp

Paid subscribers can open the link above as an editable project file to learn the process and examine the data structure.

Visualizing with Sample Data

Here is what it looks like when you visualize pre-loaded population data on a Fukushima Prefecture map. By turning on the “Divide by area (/km²)” checkbox, the data becomes population density.

Incidentally, using a technique called a cartogram — which distorts area to reflect data (also available as a tool) — produces a warped map like this:

Visualizing with Your Own Data

You can of course prepare and visualize your own data.

In that case, download the sample data and keep only the place names to see what geographic names you need to prepare data for.

Population Comparison Data Between 2011 and 2024

Download the “Fukushima Prefecture Current Population Survey Annual Report: Reference Materials” published by Fukushima Prefecture. This dataset compares population between 2011 and 2024.

Keep only the sheet and table you need.

Once you have this, load it into OpenRefine for cleansing.

Remove unnecessary spaces and commas. The minus sign is represented as “△”, so replace it with the minus symbol “-”.

Also load the file with only municipality names from the sample data into OpenRefine as a separate project.

Use the “Add column based on this column” operation to perform a VLOOKUP-like join — merging two tables horizontally.

Join using an OpenRefine-specific script:

cell.cross('PROJECT_NAME','KEY_COLUMN_NAME').cells['COLUMN_NAME_TO_GET'].value[0]

PROJECT_NAME — the project name of your original data
KEY_COLUMN_NAME — the name of the column to use as the key
COLUMN_NAME_TO_GET — the name of the column you want to join

You can see that the join was successful for all municipalities except Futaba, Namie, Okuma, and Tomioka, where no data exists.

Municipalities with higher population change rates are displayed in darker colors.

Draw-to-Answer Line Chart

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

Draw-to-Answer Line Chart

drawing-line-chart.dataviz.jp

What is this tool?

“Draw-to-Answer Line Chart” is an interactive quiz builder based on time-series data. Quiz creators upload their data, and respondents predict upcoming trends by drawing directly on the chart. After submitting, the prediction is compared against the actual data and a score is displayed.

Features

CSV upload: Create quizzes from your own time-series data
Sample data: Try it instantly with built-in datasets — U.S. unemployment rate, Japan’s population, inbound tourists to Japan, and USD/JPY exchange rate
Date range selection: Select a portion of the data to define the quiz scope
Period annotations: Overlay contextual labels on the chart, such as political transitions or economic events
Hand-drawn style: Choose between a standard style and a hand-drawn sketch style
Publish & share: Share your quiz via URL or on social media
Project save & load: Save work-in-progress quizzes and resume editing later

How to use

Upload data — Drag & drop a CSV file or select a sample dataset
Set the date range — Specify the start and end of the data range
Configure the quiz — Enter a title (question), the prediction start point, units, and style
Add annotations (optional) — Set period labels to display as background context
Preview — Check the chart in real time on the right panel
Publish — Generate a URL and share it with respondents

Data format

CSV files with a header row are supported.

Column	Content	Example
X-axis (time series)	Year or year-month	`2000`, `2020/04`
Y-axis (numeric)	Any numeric value	`4.9`, `12615`, `105.21`

date,value
2000,4.0
2001,4.7
2002,5.8

X-axis supports YYYY (year) or YYYY/MM (year-month) formats
For multi-column CSVs, you can select the X-axis and Y-axis columns after uploading
JSON format is also supported ([{“x”: 2000, “y”: 4.0}, …])

Exploring Two Variables at Once with a Mekko Chart

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

Every year, Dentsu publishes “Advertising Expenditures in Japan.” We visualized the advertising expenditure by industry across four traditional media (excluding the internet).

Normally, using bar charts or pie charts would require creating as many charts as there are industries (21) or media types (4). With a Mekko chart, however, you can represent both dimensions as vertical and horizontal proportions within a single chart.

Here we introduce how to create one using the tools provided by this service.

Advertising Expenditure by Industry and Mass Media (2025)

Paid users can open the link above as an editable project file to learn how it was made and examine the data structure.

The data is sourced from Dentsu’s PDF report.

2025 Advertising Expenditures in Japan - Dentsu

Extracting Table Data from a PDF

The published materials are available as a PDF. As-is, this data cannot be processed by a computer. Manual data entry would be tedious.

In cases like this, Tabula makes it easy to extract table data from PDFs.

Extract table data from PDFs

Tabula PDF

tabula-pdf.dataviz.jp

Cleansing the Data

To transform the data into a tidy format that computers can process, OpenRefine is very useful. It allows you to cleanse data with visual confirmation.

We removed unnecessary columns, as well as unnecessary spaces and commas.

The data is still in a cross-tabulation (matrix) format, so we need to perform the reverse of a pivot table in Excel. OpenRefine lets you do this visually as well.

Data cleansing is now complete. Choose your favorite visualization tool. In this case, we’ll use RawGraphs, which makes it easy to create Mekko charts.

Visualizing Data with RawGraphs

RawGraphs is a single-page tool where each step appears as you scroll down.

Completed

Export as PNG to include in slides or publish on the web.

Export as SVG to edit in design tools such as PowerPoint, Adobe Illustrator, or Figma. Some axis labels were too close together, so we adjusted them.

Editing in PowerPoint

Editing in Adobe Illustrator

Finding the Ideal Yogurt with Parallel Coordinates

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

Let’s find the “ideal yogurt” — high in protein, low in sugar.

With a Parallel Coordinates chart, you can easily filter data by applying multiple conditions simultaneously.

Here we show how to create this using our tools.

Finding the Ideal Yogurt with Parallel Coordinates

parallel-coordinates.dataviz.jp

Paid subscribers can open the link above as an editable project file to learn the process and examine the data structure.

Collecting the Data

First, we gathered nutritional information for yogurts sold at convenience stores, collecting data from each manufacturer’s website.

Visualizing with Parallel Coordinates

After loading nutritional data for 70 yogurt products and switching to Min-Max scale, metrics with different units are normalized to the same 0–1 axis.

Filtering Across Multiple Axes

By brushing the upper range on the protein axis and the lower range on the carbohydrate axis, only products meeting the “high protein, low sugar” criteria remain as blue lines.

The standout result is PARTHENO Plain, a rich Greek yogurt — 10.9g of protein with just 4.6g of carbohydrates.

Reordering Axes

Try dragging axes to rearrange them, and hover over table rows to highlight the corresponding lines. Experience how the “feel” of the data changes with different arrangements.

GeoJSON.io

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

GeoJSON.io

地図タイルをトレースしてGeoJSON作成

geojson.dataviz.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

交通データGTFSをネットワーク・データに変換します

GTFSネットワークデータ変換

gtfs-to-network.dataviz.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

i want hue

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

What is this tool?

A web tool for generating and adjusting distinguishable color palettes for data visualization. It creates highly distinguishable color sets by taking human color perception (hue, saturation, lightness, etc.) into account.

Features

Color palette generation…Automatically generates easy-to-distinguish color combinations based on the specified number of colors.
Color property adjustments…Design custom palettes by specifying ranges for hue, chroma (saturation), and lightness.
Color vision deficiency support…Capable of generating palettes that accommodate color vision diversity (color vision deficiency).
Diverse output formats…Retrieve generated palettes as JSON, CSS, RGB/HEX lists, JavaScript code, and more.

How to use

1. Set generation parameters…Specify the number of colors, hue range, and saturation/lightness constraints for the palette.
1. Generate the palette…Colors are listed based on your settings.
1. Customize and adjust…Fine-tune individual colors or overall distribution to optimize visibility and color balance.
1. Export and use…Export in JSON, CSS, JavaScript, and other formats for use in data visualizations.

Japanese-Western Calendar Converter

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

Japanese-Western Calendar Converter

Convert between Japanese era dates and Western dates

calendar-converter.dataviz.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

ブラウザ上で JSON データ構造を視覚的に理解する

JSON Crack

jsoncrack.dataviz.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

kepler.gl

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

大規模地理空間データの可視化・探索ツール

kepler-gl.dataviz.jp

What is this tool?

A browser-based tool for visualizing and exploring large-scale geospatial data. It leverages WebGL to produce high-performance map visualizations that enable intuitive analysis of location data. Originally developed by Uber as an open-source GIS tool, it allows data exploration without any programming.

Features

Diverse layer types: Supports multiple layers including points, lines, polygons, heatmaps, hexbin aggregation, arcs, and more.
Interactive operations: Explore data through filtering, zooming, panning, and time-axis animations.
High-performance rendering: Uses WebGL to smoothly render millions of data points at high speed.
Style settings and customization: Adjust color coding, scale settings, 3D representation (height/extrude), and many other display options.
Export: Save and share completed maps as PNG images or interactive HTML, as well as CSV file output.
Save and load created projects

How to use

1. Add data: Drag and drop CSV or GeoJSON files to load them.
1. Configure layers: Select a type (point/polygon, etc.) from the layer panel and assign columns such as latitude and longitude.
1. Customize: Adjust colors, sizes, filters, and scales to optimize the visualization.
1. Save and share: Save settings and maps (locally/export) for reuse.

Data formats

CSV
Json
GeoJSON
Arrow
Parquet

Leonardo

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

Adobe がオープンソースとして提供しているツール

Leonardo

leonardo.dataviz.jp

What is this tool?

Leonardo is a web-based color tool that generates and designs colors based on target contrast ratios. It functions as a support tool for building accessible (visibility- and color-vision-friendly) color schemes for design systems and data visualization, and for managing overall color systems for themes. It is fundamentally built on a color module that Adobe provides as open source.

Features

Contrast ratio-based color generation…Automatically generates colors that match a specified target contrast ratio, producing palettes that meet accessibility standards (WCAG) requirements.
Color theme design and management…Create and adjust color scales and overall theme structures to build accessible themes for design systems.
Visual evaluation and export…Visually evaluate contrast between colors, color differences, and positions in color space, with export options as SVG or code (CSS custom properties, design tokens) as needed.
Adaptive (dark/light) theme support…Generate color schemes that adapt to light mode and dark mode by adjusting brightness, saturation, and contrast.

How to use

1. Set base colors…Specify the base color, background color, and target contrast ratio.
1. Generate and adjust palettes…Review the automatically generated color swatches, and adjust the color space and ratios as needed.
1. Export results…Export in your preferred format such as SVG, color code lists, CSS/JS/design tokens, and use them in your project.

Mapbox Classic スタイル生成

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

Kepler.gl や Foursquare Studio で利用可能な Mapbox 地図タイル

Mapbox Classic スタイル生成

classic-mapbox-styles.dataviz.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

Mapshaper

mapshaper.dataviz.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

OpenRefine

表データのクレンジング・ツール

open-refine.dataviz.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

open-refine-doc.dataviz.jp

OpenRefineの公式解説サイト

OpenRefine解説

RAWGraphs2

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

What is this tool?

A tool that lets you create a wide variety of charts with an intuitive interface. While it is not designed for fine-tuning charts on its own, it excels as a drafting tool for exporting in SVG format and refining in graphic tools (such as Figma or Adobe Illustrator) or PowerPoint.

A missing link tool that bridges the gap between Excel and graphic applications like Adobe Illustrator.

Features

32 diverse chart templates across 8 categories
Export as PNG, JPEG, or SVG images
Style adjustments
No interactive content creation capabilities
Save and load created projects

How to use

1. Load your data
1. Choose a chart
1. Map the data
1. Customize

Data formats

Tabular data (CSV, TSV, DSV)
JSON

Note

Drag operations may not work properly when using Microsoft Edge. In that case, please use another browser such as Chrome.

Sankeymatic

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

Sankeymatic

sankeymatic.dataviz.jp

What is this tool?

A tool specialized for creating Sankey diagrams. Because the data format is simple, anyone can easily create Sankey diagrams using data prepared in spreadsheet tools.

Features

Create beautiful Sankey diagrams
Export as PNG or SVG images

How to use

Load data from the “Input” section
Adjust styles
Export the result

Data formats

Proprietary notation for this tool
source [value] target

Shift JIS ⇄ UTF-8 文字コード変換ツール

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

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.dataviz.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

geojson-and-svg.dataviz.jp

SVG ⇄ GeoJSON 変換ツール

GeoJSON と SVG の相互変換を支援

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

Tabula PDF

PDFから表データを取り出す

tabula-pdf.dataviz.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

Text Entity Extraction Tool

text-entity.dataviz.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

Visualizing Japan's Temperature Changes with a Spiral Chart

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

We visualized the annual mean temperature anomaly in Japan from 1898 to the present using a spiral chart.

With RawGraphs’ spiral chart, you can arrange long-term time series data in a spiral layout, making it easy to grasp trends over time at a glance.

Here we introduce how to create this using our service’s tools.

Visualizing Japan's Temperature Changes with a Spiral Chart

Data Source

This visualization uses the “Annual Mean Temperature Anomaly in Japan” data published by the Japan Meteorological Agency (JMA).

Annual Mean Temperature Anomaly in Japan — Japan Meteorological Agency

This dataset records the temperature anomaly (°C) for each year from 1898 to 2025, calculated against the 30-year average from 1991 to 2020 as the baseline. In recent years, positive anomalies exceeding +1°C have continued, clearly showing a long-term warming trend.

Visualization with RawGraphs

Load the CSV data into RawGraphs and select “Spiral Plot” from the chart types.

By assigning the year to the time axis and the temperature anomaly to the value, a spiral chart is drawn with the timeline progressing from the center outward. The closer to the outer edge, the more recent the data, and the warming trend becomes visually apparent through changes in color and position.

Advantages of Spiral Charts

While bar charts or line charts can represent the same data, they become too wide for long-term data spanning over 100 years. Spiral charts can fit long time series into a compact area, making it easier to get an overview of the overall trend.

By comparing the inner part of the spiral (past) with the outer part (present), you can intuitively grasp how the temperature anomaly has been growing larger year by year.

イージング関数チートシート

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

イージング関数チートシート

時間の経過に伴うパラメーターの変化を可視化

easings.dataviz.jp

What is this tool?

A reference site that catalogs “easing functions” – which describe how values change over time in animations and transitions. You can visually compare and select various easing behaviors (acceleration, deceleration, bounce, etc.). Easing functions define the rate of change that gives animations a natural feel.

Features

Easing function catalog…Browse a wide range of easing functions (e.g., easeInSine, easeOutBounce) in a list view.
Visual comparison with graphs…See how each function changes over time (t) displayed as a graph.
CSS and code examples…Includes information showing how to use each function as CSS Transition / Animation or in code.
Real-time preview…A UI that lets you visually confirm the motion of your selected function.

How to use

1. Select a function…Click or select the desired easing function from the list.
1. Review the behavior…Compare how values change using the graph and preview of the selected function.
1. Apply to your project…Copy the function name or code and paste it into your animation library or CSS Timing Function.

バッファ生成ツール

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

バッファ生成ツール

turf-buffer.dataviz.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

address-to-latlon.dataviz.jp

住所 → 緯度経度変換ツール

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)

地図タイル・ブラウザー

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

地図タイル・ブラウザー

what-the-tile.dataviz.jp

座標系変換ツール

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

transform-coordinates.dataviz.jp

座標系変換ツール

地物ファイルの座標を変換

日本地図カルトグラム

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

cartogram-japan.dataviz.jp

日本地図カルトグラム

日本地図カルトグラムを手軽に作成できるツール

What is this tool?

A web-based tool that lets you easily create cartograms reflecting statistical data for each prefecture of Japan. A cartogram is a type of thematic map that distorts the area and shape of regions on a map according to statistical values (such as population, votes, or other indicators). It visually highlights regional differences and disparities that are hard to see on a standard map.

Features

Japan map cartogram generation: Displays regions such as prefectures with their areas distorted according to statistical values.
Data value reflection: Map shapes change based on the data you input.
Ranking mode: Automatically generates ranking data sorted by value in descending order. Ranking data can be used for color coding.
Interactive display: Browse and interact with the map on the web.
Export as PNG or SVG images

How to use

1. Specify your data…Upload or enter numerical data by region in CSV format (e.g., population, GDP, vote counts).
1. Generate the cartogram…Based on the specified statistical values, a distorted cartogram of the Japan map is generated and displayed on screen.

Adjust and review…Adjust parameters (color, degree of distortion, region label display, etc.) as needed and review the results.

Data formats

Tabular data (CSV)

日本地図コロプレス

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

choropleth-japan.dataviz.jp

日本地図コロプレス

日本地図コロプレスを手軽に作成できるツール

What is this tool?

Features

How to use

Data formats

緯度経度フォーマッター

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

latlon-formatter.dataviz.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

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.

都道府県地図カルトグラム

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

cartogram-prefectures.dataviz.jp

都道府県地図カルトグラム

都道府県地図カルトグラムを手軽に作成できるツール

What is this tool?

A web-based tool that lets you easily create cartograms reflecting statistical data for each municipality within a selected prefecture. A cartogram is a type of thematic map that distorts the area and shape of regions on a map according to statistical values (such as population, votes, or other indicators). It visually highlights regional differences and disparities that are hard to see on a standard map.

Features

Prefecture map cartogram generation: Displays regions such as municipalities with their areas distorted according to statistical values.
Data value reflection: Map shapes change based on the data you input.
Ranking mode: Automatically generates ranking data sorted by value in descending order. Ranking data can be used for color coding.
Interactive display: Browse and interact with the map on the web.
Export as PNG or SVG images

How to use

1. Specify your data…Upload or enter numerical data by region in CSV format (e.g., population, GDP, vote counts).
1. Generate the cartogram…Based on the specified statistical values, a distorted cartogram of the prefecture map is generated and displayed on screen.

Adjust and review…Adjust parameters (color, degree of distortion, region label display, etc.) as needed and review the results.

Data formats

Tabular data (CSV)

都道府県地図コロプレス

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

choropleth-prefectures.dataviz.jp

都道府県地図コロプレス

都道府県地図コロプレスを手軽に作成できるツール

What is this tool?

Features

How to use

Data formats

青空文庫ルビ削除ツール

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

aozora-furigana.dataviz.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

Color Brewer

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

Color Brewer

カラースキーム選びを地図上でシミュレーション

colorbrewer.dataviz.jp

What is this tool?

ColorBrewer is an online tool for selecting optimal color palettes for data visualization and maps. Its purpose is to suggest color schemes suited to color visibility and the nature of categorical or numerical data.

Features

Color scheme selection assistance…Presents color schemes for sequential data, diverging data, qualitative data, and more based on data characteristics.
Usage considerations…Filter options for colorblind safety, print friendliness, and photocopy safety.
Number of classes…Adjust the number of colors (e.g., 3 to 12) to select the optimal palette.
Color output formats…Export selected palettes in HEX/RGB/CMYK formats, CSS, JavaScript arrays, and more.
Save and load created projects.

How to use

1. Select data nature…Choose from sequential (ordered), diverging (bipolar around a center value), or categorical (unordered).
1. Specify number of colors (classes)…Select the desired number of data classes (e.g., 3, 4, …).
1. Review and adjust the palette…Check how the selected palette looks on maps or charts.
1. Export…Export as CSS, JavaScript, Adobe Swatch, etc. as needed.

Cytoscape

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

Cytoscape

cytoscape.dataviz.jp

What is this tool?

A browser-based implementation of Cytoscape, which is popular as a desktop application.

It is a tool for interactively visualizing network (graph) data in your browser. You can load relationship data composed of nodes (points) and edges (lines), and intuitively change layouts, apply styling based on attributes, and more.

Cytoscape is an open-source platform for visualizing and analyzing network (graph) data. Originally developed for visualizing and analyzing biological networks (molecular interaction networks), it is also widely used for social network analysis and general complex network visualization.

Features

Data Import — Upload and visualize files in GEXF, GraphML, and CSV formats
Sample Datasets — Load one of 9 sample datasets with a single click, including Les Misérables, Game of Thrones, and Marvel Universe
Layout Switching — 6 layout types: Grid, Circle, Concentric, Breadthfirst, Cose (physics simulation), and Random
Node Styling — Dynamically change colors (qualitative color scheme), sizes, and labels based on attributes
Edge Styling — Dynamically change colors (quantitative color scheme), thickness, and labels based on attributes
SVG Export — Download the current graph in SVG format
Project Save/Load — Save projects to the server and restore them later

How to use

Select a file from the “Load Data File” button, or choose from “Load Sample Data”
Adjust the graph arrangement by changing the layout and easing in the control panel
Select the attribute to use for node color, size, and label from the dropdowns in the “Node” row
Select the attribute to use for edge color, thickness, and label from the dropdowns in the “Edge” row
If needed, save as an SVG image using “Export”

Data formats

GEXF / GraphML

XML formats designed for graphs. They can richly describe node and edge attributes (categories, weights, coordinates, etc.). They can be exported from many tools such as Gephi and NetworkX.

CSV (Edge List Format)

A format that can be easily created from spreadsheets or Excel.

A header row is required
Specify the endpoints of edges using source and target columns (or from and to) — case-insensitive
All other columns are imported as edge attributes
Nodes are automatically generated from the edge information

source,target,weight,type
Alice,Bob,1.0,friends
Bob,Carol,2.5,colleagues
Alice,Dave,0.8,family

Tilegrams

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

What is this tool?

A web-based map creation tool that generates “tilegrams (tiled cartograms)” – representations of geographic regions using hexagonal tiles, with region sizes visually adjusted according to data values. Region areas are expressed proportionally to population or other indicators through the number of tiles, while maintaining an approximate resemblance to the original geographic shape.

Features

Hexagonal tile cartogram generation…Represents geographic areas as uniform hexagonal tiles, varying the number of tiles per region according to data values.
Built-in maps and custom data support…In addition to standard map templates for the United States, Europe, and other regions, you can load custom data to generate tilegrams.
Interactive adjustment…Drag tiles to adjust placement, or change the resolution (the value each tile represents) to optimize the appearance.
Export…Export the created tilegram in SVG or TopoJSON format for use and further editing in other tools.

How to use

1. Select a base map…Start from a prepared geographic region (e.g., US states, French regions, etc.).
1. Specify and load data…Upload regional values (such as population or vote counts) in CSV format.
1. Set resolution and adjust…Set the value each tile represents (e.g., 1 tile = 1 million people), and optionally drag tiles for fine-tuning.
1. Generate and export…Download the completed tilegram as PNG / SVG / TopoJSON for analysis and sharing.

Data formats

CSV (comma-separated) format containing geographic identifiers (Geo ID, etc.) and values (e.g., population, vote counts).

SVGグラデーションエディタ

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

SVGグラデーションエディタ

チャートのグラデーションをデザイン

svg-gradient.dataviz.jp

What is this tool?

A web-based tool for visually creating and adjusting gradients (smooth color transitions) in SVG (Scalable Vector Graphics). It can be used to design color gradients for chart and shape backgrounds and fills.

Features

Gradient design…Visually edit linear and radial gradients for use in SVG.
Color stop settings…Add and adjust colors (stops) and positions along the gradient to create custom color schemes.
Real-time preview…Instantly review editing results and make adjustments while seeing the final appearance.
SVG generation…Output the completed gradient definition directly as SVG code.

How to use

1. Create a gradient…Design the gradient by manipulating color stops, angles, and positions.
1. Preview…Check how the configured gradient renders in real time.
1. Retrieve the generated SVG…Copy or save the final gradient definition as SVG code and incorporate it into your designs or visualizations.

SVGテクスチャエディタ

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

SVGテクスチャエディタ

チャートのテクスチャをデザイン

svg-tectures.dataviz.jp

What is this tool?

A web-based editor for designing texture patterns and surface effects used in SVG (Scalable Vector Graphics). You can visually edit and create repeating patterns (textures) for chart and shape backgrounds and fills, and use them as SVG. This tool is primarily intended to support the design of texture expressions in data visualization and graphic design.

Features

Texture pattern generation and editing…Visually create and adjust repeating patterns (stripes, dots, etc.) and texture patterns for embedding in SVG.
Preview display…Evaluate the appearance of patterns in real time as you edit.
SVG output…Retrieve the designed textures as SVG code or pattern definitions.

How to use

1. Design a texture…Create a texture by configuring pattern type, spacing, direction, color, and other settings (via GUI).
1. Real-time preview…Review the appearance of the edited texture on the spot.
1. Retrieve as SVG…Copy or save the finished pattern as SVG XML (such as <pattern>) and apply it to other SVG shapes or charts.

ADS-B / AIS Visualization

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

ADS-B / AIS Visualization

Easily create videos from aircraft and ship movement data

bbts.dataviz.jp

What is this tool?

A web tool that visualizes tracks on a map with animation simply by uploading a CSV file containing latitude and longitude data. It supports visualization of broadcast-type positioning data such as ADS-B (aircraft tracking) and AIS (ship tracking).

Features

CSV Upload: Load CSV files via drag & drop or file selection
Track Visualization: Animate movement paths on a map based on time-series data
Multiple Track Support: Automatically groups and displays multiple aircraft or vessels from a single CSV
Auto Column Detection: Automatically recognizes column names like lat/lon, latitude/longitude regardless of case
Sample Data: Ready-to-use sample data available for quick testing

How to use

Prepare a CSV file (containing latitude, longitude, and timestamp)
Drag & drop or click to select a file from the sidebar on the left
Sample data is also available
Tracks are automatically drawn on the map
Export as GIF animation, sequential still images, or video files
Customize base map style, date/time display, and other options

Data formats

Include the following variables in your CSV:

Position (required): lat / lon, latitude / longitude, or Position (“lat,lon” combined format)
Time (required): Timestamp (Unix epoch seconds), etc.
Identifier: Callsign (aircraft), MMSI / VesselName (vessel)
Optional: Altitude, Speed, Direction / Course

Supported position data formats

Column names are case-insensitive (e.g., LAT, Lat, lat are all accepted).

Column Name	Description
`lat` / `lon`	Latitude / Longitude (abbreviated)
`latitude` / `longitude`	Latitude / Longitude (full name)
`Position`	Combined lat/lon format (`"35.68,139.76"`)

Supported time data formats

Time data is automatically detected in the following formats. Supported column names include timestamp, time, datetime, date, etc.

Format	Example
ISO 8601	`2023-05-20T10:30:00Z`
Date-time string	`2023-05-20 10:30:00`
Compact format	`20230520_103000`
Unix timestamp (seconds)	`1684567890`
Unix timestamp (milliseconds)	`1684567890123`

When a single CSV contains multiple aircraft or vessels, they are automatically grouped and displayed.

Reference

Data Illustrator

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

What is this tool?

Data Illustrator is a web application that lets you create data visualizations visually without programming. It aims to generate charts with the feel of drawing graphics using vector design operations, similar to Figma or Adobe Illustrator.

Features

An intuitive, vector-design-like interface for drawing, selecting, and manipulating.
Supports data binding (linking data to graphics).
Automatic visual encoding: Assign data columns to visual attributes such as color, shape, and position for instant rendering.
UI components including Canvas, Data Panel, Layers Panel, and Property Inspector enable editing and structuring.

How to use

1. Import data and display the data table.
1. Draw, select, and edit shapes.
1. Bind data columns to shape attributes such as position, color, and size. Updates are reflected immediately.
1. Export or save the created visualization.

Data formats

Tabular data (CSV)

Gephi Lite

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

Gephi Lite

Write visualization specs in JSON to render interactive graphs and charts in real time

What is this tool?

Gephi Lite is a web application that allows you to easily create network graphs (relationship visualizations) in your browser. You can load data composed of nodes (points) and edges (lines), and intuitively perform layout calculations, color coding, filtering, and more.

Features

Graph Visualization: Interactively display relationships between nodes and edges. Zoom, pan, and node selection are supported
Layout Calculation: Multiple layout algorithms including ForceAtlas2, Force Directed, Circular, and CirclePack
Appearance Settings: Automatically assign colors, sizes, and labels to nodes and edges based on attribute values
Filtering: Narrow down the display of nodes and edges by attribute values or range specifications
Metrics Calculation: Compute network analysis metrics such as degree, PageRank, betweenness centrality, and Louvain community detection
Data Table: View and edit node and edge attributes in a list format
Export: Export as graph images (PNG) or graph data (GEXF)
Japanese/English Auto-Switch: The UI automatically switches based on your browser’s language settings

How to use

When you access the page, a sample graph or an empty workspace will be displayed
Load data using the “Open Data File” button at the top of the screen, or by dragging and dropping a file
Select “Layout” from the left side menu and run an algorithm to automatically arrange the nodes
In the “Appearance” menu, set colors and sizes based on attributes to make the graph easier to read
Deepen your analysis using “Filters” and “Metrics”
The completed graph can be exported as an image (PNG) or data file (GEXF)

Data formats

The following file formats are supported.

Format	Extension	Description
CSV	`.csv`	Edge list format. The first row contains headers (Source, Target, etc.), and subsequent rows contain the data for each edge. The simplest format
GEXF	`.gexf`	Gephi’s standard XML format. Retains rich node/edge attributes and visual information
GraphML	`.graphml`	A standard XML-based graph description format
Graphology JSON	`.json`	JSON format for the Graphology library

CSV file format example:

Source,Target,Weight
Alice,Bob,1.0
Bob,Charlie,2.0
Alice,Charlie,1.5

The first row is the header (required)
The Source (or From, Src) and Target (or To, Dst) columns are automatically detected
Other columns (such as Weight) are imported as edge attributes
Nodes are automatically generated from the Source / Target values
Character encoding supports both UTF-8 and Shift_JIS

Histogram

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

Tools that can create this chart…

A data variable is sorted in ascending order to show its distribution. A data width called a “bin” is specified, and the count of data points within each bin is displayed. The bin width and the resulting counts determine the appearance of the histogram.

If there are too few bins, the appearance becomes too coarse and fine differences go unnoticed. Conversely, if there are too many bins, the appearance becomes too detailed, making it difficult to grasp overall trends. The process of adjusting the bin width itself helps in understanding the characteristics of the data.

Parallel Coordinates

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

parallel-coordinates.dataviz.jp

Parallel Coordinates

What is this tool?

An interactive chart specialized for comparing and exploring multidimensional data. Simply upload a CSV file, and numeric columns are displayed as parallel axes with each row drawn as a polyline crossing them. Brushing on each axis lets you filter data matching specific conditions, making it easy to discover patterns and outliers intuitively.

Features

Brushing: Drag vertically on each axis to specify a range and filter data matching the conditions
Axis reordering: Drag column names horizontally to rearrange axis order. Place related metrics side by side for comparison
Scale switching: Toggle between three modes — Original (raw values), Min-Max (0–1 normalization), and Z-Score (standardization)
Table synchronization: The data table below syncs with brushing results. Hovering over a row highlights the corresponding line on the chart
Export: Export filtered results as CSV and chart images as SVG/PNG
Share — Share the current view via URL. OGP images for social media are generated automatically
Project saving: Save and restore data and settings (scale, axis order, brush ranges) to the cloud with thumbnails

How to use

Click “CSV Upload” to load your data (or try “Sample” to use yogurt nutrition data)
Drag vertically on an axis to narrow down a range of interest
Switch the Scale to Min-Max or Z-Score as needed to compare metrics with different units
Drag axis names horizontally to place items you want to compare next to each other
Hover over a table row to highlight the corresponding line on the chart
Export results as CSV/SVG/PNG, or save as a project to the cloud

Data format

File format: CSV (comma-separated, UTF-8)
Structure: First row as header (column names), subsequent rows as data
Numeric columns: Automatically detected and displayed as chart axes
String columns: Shown in the table but not included as chart axes
Missing values: Empty cells are treated as missing

Vega Editor

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

JSON 形式で可視化仕様を書くことで、インタラクティブなグラフやチャートをリアルタイムにレンダリング

What is this tool?

Vega Editor is a web-based IDE (editor) for writing, editing, and previewing Vega and Vega-Lite visualization specifications. By writing visualization specifications in JSON format, you can render interactive graphs and charts in real time. Vega and Vega-Lite are declarative visualization grammars that generate charts by defining data and display rules in JSON.

Features

Text editor / code view…Provides an editor for entering and editing Vega/Vega-Lite JSON.
Real-time preview…Instantly displays the edited specification as a visualization in the browser.
Samples and templates…Load example specs for learning and experimentation (a feature of the official version).
Vega / Vega-Lite mode switching…Edit and preview in both specification formats (a standard feature of the official tool).
Sharing / Export…Save and share specifications via GitHub Gist and other backend integrations (an official version feature).

How to use

1. Write specifications in JSON format…Enter Vega or Vega-Lite specifications into the editor.
1. View the preview…The specification is rendered in real time so you can review the results.
1. Save and share as needed…Save specifications to Gist or similar services for sharing with others (when backend integration is available).

Data formats

JSON (Vega / Vega-Lite specification)…Describes the visualization definition (data references, transforms, encodings, marks, etc.) in JSON.
Tabular data as data sources…Vega/Vega-Lite can load external data either by embedding it directly within the JSON or by referencing CSV/TSV file URLs (as part of the specification standard).

Voyager2

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

データ探索（Exploratory Data Analysis, EDA）を支援するビジュアライゼーションツール

Voyager2

voyager2.dataviz.jp

What is this tool?

Voyager 2 is a visualization tool that supports Exploratory Data Analysis (EDA). It lets you load data in the browser and interactively explore and generate visualizations. The original project is a fork/derivative of Voyager developed on the Vega ecosystem, characterized by its combination of manual chart specification and automatic recommendations for exploration support.

Features

Data exploration interface…Load data and interact through panels for field lists, chart encodings, filtering, and more.
Visualization recommendation…Automatically generate related charts (related views) and multiple chart candidates using wildcards, displaying them alongside the current visualization (focus view).
Partial specification with multiple chart generation…Use wildcards to simultaneously generate and compare multiple visualization specifications.
Interactive operations…Drag and drop fields onto encoding channels and update visualizations in real time.

How to use

1. Load data…Load tabular data such as CSV and review the field list.
1. Specify the visualization…Drag fields to encoding channels (e.g., x-axis, y-axis, color) to create a visualization.
1. Use exploration support…Simultaneously generate multiple views using wildcards, or use recommended views to broadly explore data.
1. Adjust and compare results…Compare recommended visualizations and generated charts while deepening your analysis.

Data formats

Tabular data (CSV, TSV)
JSON

Word Cloud

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

日本語に特化したWord Cloud

Write visualization specs in JSON to render interactive graphs and charts in real time

What is this tool?

Word Cloud is a web tool that visualizes word frequency in text data by displaying more frequent words in larger sizes, creating a “word cloud” directly in the browser.

Word clouds are a visualization technique used to intuitively grasp key words in text data at a glance. Word size and color represent frequency trends.

Features

Text input / upload…Enter text files or text data to generate a word cloud.
Frequency analysis…Counts word occurrences and adjusts word sizes according to their frequency.
Word cloud display…Renders the word cloud with sizes and arrangements corresponding to word frequency.
Customization…Adjust maximum/minimum font sizes, colors, layout, and more.
Export / save…Provides an interface to save generated results as images or SVG.

How to use

1. Input / upload text data…Load text data using the text area or file upload.
1. Generate the word cloud…Click the “Generate” button, and a word cloud based on word frequency within the text is displayed.
1. Customize…Adjust parameters for font size, color, layout settings, etc.
1. Save results…Download the generated word cloud as PNG / SVG or CSV.

Data formats

Input formats
- Text (TXT) or copy-and-paste strings: Input directly into the tool.
- CSV / TXT files: Upload files containing word lists or text data.
Output formats
- Images (PNG / SVG): Save the visualized word cloud as an image.
- CSV: Save the morphologically analyzed tokens (words) and their frequency data.

Box-And‐Whisker Plot

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

You can create this chart with…

This chart uses a box and lines (whiskers) to display five summary statistics. The positions of the box indicate the first quartile (25th percentile), the second quartile (50th percentile), and the third quartile (75th percentile), while the endpoints of the whiskers indicate the minimum and maximum values.

QuickChart UI

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

Write visualization specs in JSON to render interactive graphs and charts in real time

QuickChart UI

URLだけでチャート画像生成

quickchart.dataviz.jp

What is this tool?

QuickChart is a tool that instantly generates static chart images (PNG, etc.) from specified data and chart definitions (Chart.js format) using only a URL.

Its distinctive feature is the ability to create embeddable chart images for server-side applications, emails, reports, documents, and other environments where JavaScript cannot be executed.

This tool provides a GUI for conveniently configuring those URL parameters.

Features

Chart image generation…Generate static chart images such as bar charts, line charts, and pie charts from settings specified via URL parameters or query strings.
URL-only workflow…Create charts using just the URL query, with no need to install complex libraries.
Usable as images…Generated charts are output as PNG or other image formats, making them easy to embed in web pages, reports, and emails.

How to use

1. Specify the chart configuration in JSON format via URL query parameters.
1. Use the generated image URL directly or download it.

Data formats

Tabular data (CSV)

Density Plot

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

You can create this chart with…

This chart depicts a probability distribution as a smooth curve. When kernel density estimation is used to draw the curve, it is sometimes referred to as a kernel density plot.

Violin Plot

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

You can create this chart with…

A density plot is mirrored and placed back-to-back, with the equivalent of a box plot drawn inside. The bottom end represents the minimum value, and the top end represents the maximum value. It allows for a more detailed understanding of the data than a box plot.

Ridgeline Plot

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Density plots are displayed in a staggered, overlapping arrangement to compare multiple variables or groups.

Dot Plot

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

A frequency distribution is shown with one dot representing one data point. It uses a single variable, with axes arranged in parallel. The horizontal axis represents data values or data classes, while the vertical axis represents frequency, with the number of dots indicating the count.

Beeswarm Plot

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

You can create this chart with…

This chart displays the distribution of a single data variable using one dot per data point. When showing multiple variables, they can be color-coded within a single chart or arranged side by side. Instead of stacking dots along an axis, dots are drawn as an evenly spaced cluster, so even when data points are concentrated in a particular range, the degree of concentration is visible as a wider area, and individual data points remain distinguishable.

Strip Chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

A one-dimensional scatterplot where each data point is plotted along a single line. Each data point is represented as one dot, showing the distribution of a single variable. Unlike a bee swarm plot, which spreads points organically to avoid overlap, data points are plotted within a pre-defined axis range.

Pie Chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

The angle within the circle represents the proportional size of data values. In recent years, there have been many negative opinions about its use, but it is perfectly fine as long as inappropriate practices are avoided, such as including too many items or distorting the appearance of proportions with 3D rendering.

The maximum number of items should be around six; if more are needed, consider using a different chart type.

There is also a variant called a donut chart, which has its center hollowed out. Since this makes it impossible to visually read angles, it is best avoided unless precise reading of values by angle is not critical or when it is used for effective presentation purposes.

Mekko Chart

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

Tools that can create this chart…

This chart is similar to a 100% stacked bar chart but with two axes. Its key feature is the ability to simultaneously show the proportions of two variables. Although it appears simple, it can be surprisingly difficult to interpret, so it is important to supplement it with legends and annotations to aid understanding.

Waffle Chart

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

Named after the grid-patterned pastry it resembles, this chart arranges 100 squares in a 10x10 grid for a single category and uses color coding to show the proportion of each segment relative to the whole.

Stacked Densities

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

Multiple variables are displayed simultaneously using density plots, with the full display area representing 100% to show proportions. Unlike a 100% stacked bar chart, this chart can handle continuous variables on the horizontal axis. The vertical axis shows the results of kernel density estimation in relative terms.

Gauge Chart

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

A semicircle is used to show proportional composition. Beyond simply displaying percentages, it can also represent each individual with a symbol such as a circle, showing both the number of seats and their proportions simultaneously. A well-known use case is displaying the number of seats won in a parliament.

Bar Chart

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

A bar chart represents the magnitude of one measure against one dimension (category) using the length of bars. For example, this is useful when you want to see the population (measure) for each prefecture (dimension). Since most people know how to read bar charts and they convey numerical values accurately through length, they can be used effectively in many situations.

Because bar charts communicate values through length while also implying area, avoid using triangles instead of rectangles. Length and area do not scale proportionally, making it unclear which encoding the reader should use, which can lead to misinterpretation.

There is no fundamental difference between a vertical bar chart (where bars extend vertically) and a horizontal bar chart (where bars extend horizontally). By convention, the independent variable is often placed on the horizontal axis and the dependent variable on the vertical axis, leading to more frequent use of vertical bar charts. However, this convention does not need to be strictly followed.

Vertical bar charts are preferable when:

You want to display a bar chart alongside a line chart in the same space
The display space is wider than it is tall and there are many dimension categories

Horizontal bar charts are preferable when:

The dimension labels contain long text strings
You want to include annotations
The display space is taller than it is wide and there are many dimension categories

Stacked Bar Chart

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

For a single dimension, multiple measures are displayed simultaneously as stacked heights. Each measure is differentiated by color or texture. The measure values are treated as absolute numbers.

Since proportions are conveyed through length, they are easier to perceive accurately than angles in a pie chart. For more precise communication of values, this chart is preferable to a pie chart.

A chart that shows measure values as proportions is distinguished by the name “100% stacked bar chart.” The entire chart display area represents 100%, and each measure is shown as a proportion of the whole.

Grouped Bar Chart

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

Tools that can create this chart…

A single measure is shown as the bar height across multiple dimensions (categories). Bars are positioned so that groups are visually identifiable. Avoid combining grouped bar chart grouping with stacked bar chart stacking (stacking measures) at the same time.

Heatmap

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

Data values are represented by color within a grid of tiled rectangles. This chart is not for examining correlations; rather, it displays colors in a sequential order, such as from top-left to bottom-right like a calendar. Although it looks similar, the chart used for examining correlations is called a correlogram.

Bullet Graph

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

You can create this chart with…

Displayed alongside a bar chart, this graph shows the difference from a target and qualitative evaluations (such as good, average, or poor) inside the bar. A thin rule line running in the same direction as the bar may be used to indicate specific quantities, or to mark the target value as a reference point.

Symbol Chart

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

Data values are represented using symbols (such as circles or squares), with their area or color encoding the values. The arrangement order is not fixed; symbols may be placed from the center outward in descending order of size, or arranged from left to right.

Isotype Chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Pictograms are used to represent quantities by lining up the corresponding number of icons. By using different types of pictograms, categories can be indicated. However, it is preferable that the pictograms are relevant to the theme being addressed.

Radar Chart

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

You can create this chart with…

This is one of the best charts for comparing groups with multiple variables in a polar coordinate system. Typically, the variables are evenly spaced at angles determined by dividing the full circle (360 degrees) by the number of variables. It can be thought of as parallel coordinates mapped onto a polar coordinate system.

Polar Area Chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

A chart in a polar coordinate system with equal angles, where qualitative data is assigned to the angle and quantitative data is compared by the distance from the origin. It can be thought of as a bar chart arranged in polar coordinates.

Parallel Coordinates

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

Tools that can create this chart…

The chart name itself describes the coordinate system, with multiple axes arranged in parallel. Compared to radar charts, the key differences are: the ability to compare more variables simultaneously, the ability to find correlated variables by reordering the axes, and the ability to perform “brushing” – filtering data along specific axes (depending on the tool’s capabilities).

Parallel Sets

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

Inspired by parallel coordinates, but with key differences: it represents the frequency of categorical data and uses areas instead of lines. The chart is often colored according to the values of the highest-priority axis, allowing users to explore the chart using color as a guide.

Scatterplot

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

Used to examine the correlation between two measure variables. To explore correlations among variables within a dataset, use a scatterplot matrix.

Bubble Chart

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

You can create this chart with…

Similar to a scatter plot, but with two additional visual attributes – circle size and color – to which two more variables can be assigned. This makes it effective for examining correlation trends while simultaneously checking whether characteristics differ across groups. In this context, a chart that adds two visual variables to a scatter plot is referred to as a bubble chart, distinguishing it from a symbol chart that uses circles.

Scatterplot Matrix

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

To exhaustively explore correlations among variables within a dataset, variables are arranged in a matrix and a scatterplot is drawn at each intersection using the corresponding pair of variables, enabling more efficient exploration.

When the two intersecting variables are the same, there is no need to examine correlation, so a histogram is displayed instead. Since the order of two intersecting variables does not matter, the same pair of variables appears in two locations. Rather than displaying the same scatterplot twice, one of the locations may show the correlation coefficient instead.

Correlogram

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

You can create this chart with…

Used when you want to identify correlations more concisely than with a scatter plot matrix. Variables are arranged in a matrix in the same manner, and the correlation coefficient for each pair of variables is displayed – primarily through color – at their intersection. Redundant combinations (identical variable pairs and previously shown pairs) are omitted.

Word Crowd

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

You can create this chart with…

日本語に特化したWord Cloud

Words appearing in a document, paragraph, or text are sized based on their frequency and arranged around the center of the chart drawing area. However, since the original character length of words affects their visual size, this chart is not well suited for reading precise numerical values.

Text color can encode an additional variable, but many word clouds in the wild use meaningless random coloring, which is inappropriate as a visual expression (it becomes noise). If there is no suitable variable to map, there is no need to force colorful styling.

Word Bubbie

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

You can create this chart with…

日本語に特化したWord Cloud

Write visualization specs in JSON to render interactive graphs and charts in real time

This representation addresses a shortcoming of word clouds – that the original character length of words affects their visual size, making accurate numerical reading difficult. Circles are placed behind each word, and the area of each circle represents the numerical value. While word font size does not encode the value, words may be drawn at several different sizes for classified grouping. The circles are typically distributed evenly around the center point.

Venn Diagram, Euler Diagram

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

Visualizes textual data belonging to multiple attributes (more like tags than categories, in the sense that items can belong to multiple attributes simultaneously). It is known as a diagram that uses closed curves (closed shapes formed by closed lines) to represent set-theoretic relationships.

A Venn diagram is used in mathematics, logic, and other fields when “all intersections of sets must be shown.” A chart that only needs to show the assumed combinations is called an Euler diagram.

While the name “Venn diagram” is more widely recognized, in practice Euler diagrams are used more frequently. It is worth noting this discrepancy.

Stem and Leaf PIot

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

The basic structure displays data values split into two parts. The stem represents the leading portion of the data and is usually arranged vertically. The leaf represents the detailed portion and is arranged horizontally. It resembles a histogram, but instead of showing the distribution with bars (area), the actual data values are written directly. A train station timetable is a perfect example of this chart.

Typographic Scatterpiots

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

Instead of dots in a scatterplot, the actual typefaces or words representing data values are displayed directly. Variations include bubble chart adaptations, where additional variables are assigned to color or size.

Line Chart with River Labei

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

Text representing data values is displayed directly inside or in place of the lines in a line chart.

Parallel Coordinates with River Label

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

Text representing data values is displayed directly inside or in place of the lines in a parallel coordinates chart.

Typographic Graph

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

A network graph diagram where related words are connected as links. The nodes display the actual typefaces or words directly, and the links are represented as lines.

Typographic Mekko chart

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

The corresponding data values are displayed directly as text inside the rectangles of a standard Mekko chart.

Typographic Stacked Bar Chart

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

The corresponding data values are displayed directly as text inside the rectangles of a standard stacked bar chart.

Text Skimming

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

The paragraph of text takes center stage, with internal data applied to it. To improve the readability of the text, inherent characteristics are processed as internal data and used for visual representation.

Spark words

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

The paragraph of text takes center stage, with external data applied to it. Data related to the text is rendered as charts or other visualizations, and the colors used in those visualizations are applied to the corresponding words or sentences within the text, enhancing the cross-referenceability between the text and external data.

Line Chart

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

Tools that can create this chart…

A commonly used chart type. The horizontal axis represents time, and a non-time variable is assigned to the vertical axis. By connecting data points with lines, the slope of the lines visually conveys the magnitude of change.

Area chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

An area chart has nearly the same structure as a line chart, with the difference being that the area enclosed between the line and the axis is filled with color. When displaying multiple items in a single chart, be aware that overlapping areas may obscure the data. In such cases, consider using semi-transparent fills, re-aggregating the data so that layers stack without overlapping along the Z-axis, or using a stream graph instead.

Stream graph

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

Similar to a stacked area chart, but without an explicit horizontal axis. Instead, it uses both upward and downward directions from the baseline to display quantities as areas. Depending on the tool used, the shape of the graph may vary based on the order of columns in the input data file.

Connected Scatterplot

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

Like a standard scatter plot, variables are assigned to two axes. The plotted points are then connected in chronological order. Neither axis uses a time scale. This chart can effectively represent temporal differences between two variables as loop-shaped patterns, and distinctive features of the shape lend themselves well to annotations. However, there is a trade-off between its novelty and the difficulty of interpretation.

Diverging Bar Chart

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

This chart uses bar graphs to show changes over time for divergent data – data that deals with opposing sides or increases and decreases.

Diverging Stacked Bar Chart

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

Similar to a diverging bar chart, but with the ability to handle multiple numerical variables simultaneously.

Candlestick Chart

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

You can create this chart with…

For each unit of time in a time series, this chart simultaneously displays data such as the maximum value, minimum value, opening value, and closing value. It is commonly used for social activities such as stock market price movements, and is also sometimes applied to natural phenomena such as temperature.

Gantt Chart

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Write visualization specs in JSON to render interactive graphs and charts in real time

The horizontal axis represents time, showing the duration for each category. It is used to compare the active periods of people or services, or to show the timeline breakdown of a single project.

Bump chart

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

This chart shows how the ranking of items changes over time. It can be thought of as a simplified line chart focused specifically on changes in rank order. Even when the underlying data is numerical, values are converted to rankings for display.

Time―Distance Diagram

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

Used in railway timetable diagrams. It has two axes: time and travel distance (marked by stations or place names), and uses lines to show when and where moving objects such as trains are located.

Calendar Heat Map

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

You can create this chart with…

Data values are displayed primarily through color in cells arranged like a calendar. The calendar layout allows data values to be shown along cyclical time periods such as weeks and months. Rather than discovering periodicity in data without preconceptions, this chart is better suited for examining distributions and cyclical patterns in a format aligned with familiar social conventions.

Circular Chart

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

You can create this chart with…

Typically starting from the 12 o’clock position, the passage of time is represented along the circumference of a circle, with values shown using lines, areas, or bars. The layout is arranged so that one complete revolution around the circle represents one full time cycle.

Polar Area Chart

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

Equal angles represent the passage of fixed time intervals, and the distance from the origin indicates the magnitude of another data variable. Florence Nightingale’s coxcomb chart is a famous example of using this chart as a time-series visualization, but in modern practice, it is rarely used for time-series purposes.

Spiral Chart

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

You can create this chart with…

Typically, time progression is represented along the circumference starting from the 12 o’clock position. Unlike circular charts or polar area charts, which complete in a single revolution, this chart represents data in a spiral pattern to highlight periodicity. However, a drawback is that as the spiral extends to two or three revolutions, comparisons become more difficult.

Dot Map

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

Each dot represents one data point (1 dot = 1 data item), showing the distribution of data using dots (circles). No variable is assigned to the size of the dots (maps that do assign a variable to dot size are called symbol maps). Since each dot corresponds one-to-one with individual data, it is possible to search for specific items in space.

Dot Density Map

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

You can create this chart with…

Write visualization specs in JSON to render interactive graphs and charts in real time

Unlike a dot map, in a dot density map each dot represents multiple data points, showing the distribution of density through dots (circles). No variable is assigned to the size of the dots. Rather than focusing on individual data points, this map is used to understand continuous phenomena across large-scale datasets.

Graduated Symbol Map

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

A symbol map uses shapes such as circles, squares, stars, or theme-specific figures, with variables assigned to both their size and color. A graduated symbol map is a type of symbol map that uses classified (graduated) data.

Proportional Symbol Map

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

A type of symbol map that uses unclassified (proportional) data.

3D Bar Chart Map

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

When data points are distributed continuously, this chart represents data using 3D bars arranged in a grid pattern, encoding values through the area (height), color, and direction (upward or downward) of each bar.

Graduated Flow Map

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

A flow map is a map that represents the flow or movement between locations, and this type uses classified (graduated) data. Compared to proportional flow maps, it makes it easier to quickly grasp overall general trends.

Proportional Flow Map

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

A flow map is a map that represents the flow or movement between locations, and this type uses unclassified (proportional) data. Compared to graduated flow maps, it allows for more accurate and detailed analysis.

Choropleth Map

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

You can create this chart with…

Data values are represented by coloring geographic shapes defined by administrative boundaries such as national or prefectural borders. Ensure that the geographic enumeration units are consistent. While the familiarity of seeing a recognizable map colored in is an advantage, the varying sizes of administrative areas can distort the perceived magnitude of data values. Some choropleth maps classify data into discrete classes, while others do not.

Dasymetric Map

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

You can create this chart with…

Nearly identical to a choropleth map, but instead of using administrative boundaries, it increases geographic precision by strictly distinguishing uninhabitable areas such as mountains and lakes.

Continuous Cartogram

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

You can create this chart with…

A map that assigns data values to area is called a cartogram. In a continuous cartogram, the administrative boundaries such as national or prefectural borders are preserved, and data values are assigned not only to color but also to area. Because the boundaries remain intact, adjacent regions influence each other through their distorted areas, resulting in an overall warped shape. There is an engaging quality to seeing a familiar map become distorted.

Non‐Continuous Cartogram

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

A type of cartogram in which regions are displayed separated at national or prefectural borders, with data values applied to their areas. As a result, regions are not affected by the distortion of adjacent areas.

Pseudo-Continuous Cartogram

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

Regions such as prefectures are all represented using identical geometric shapes such as circles, squares, or hexagons, with data values expressed through area and coloring. Since geometric shapes are used instead of actual terrain, a key advantage is that it is easier to compare data values by area.

Gridded Cartogram

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

Regions such as prefectures or municipalities are all represented using identical shapes such as circles, squares, or hexagons, where the number of shapes represents area and coloring represents data values.

Isolines Map

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

Unclassified data is used to divide regions with isolines. Rather than splitting the data into discrete categories, the placement of isolines is determined based on the natural patterns of change in the data. The spacing between isolines is adjusted according to the magnitude of data variation. Where data changes rapidly, isolines are densely packed; where changes are gradual, they are spaced further apart.

Isopleths Map

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

Classified data is used to color regions delineated by isopleths (contour lines). Data values are categorized into defined classes, with each class assigned a corresponding color or texture. By dividing data into discrete categories, characteristics can be clearly and distinctly revealed. Although colloquially referred to as a “heat map,” this is not its formal name. To distinguish it from the non-map-based chart of the same name, it is recommended to use the proper term.

Chartmaps

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

You can create this chart with…

Statistical charts reflecting regional data are drawn on a map. In the case of pie charts, a variable can also be assigned to the overall area of each pie. This can be thought of as small multiples arranged according to geographic positions on a map.

A drawback is that in densely packed areas – such as the southern Kanto region where prefectures are clustered together – charts may not fit in their proper locations and need to be repositioned (for example, placing Tokyo’s chart over Tokyo Bay), which diminishes the effectiveness of the geographic layout.

If making charts smaller allows them to fit but compromises readability, consider using standard small multiples instead of this map-based approach.

Vector Field Map

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

Tools that can create this chart…

Write visualization specs in JSON to render interactive graphs and charts in real time

When continuously distributed data indicates direction and energy, such as wind direction, lines are drawn from each point of origin to visualize the continuous data. This technique is also used in weather data services to represent air currents and ocean currents.

3D Choropleth Map

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

A choropleth map extended into 3D by adding height. In addition to the color used in a 2D choropleth, data variables can be assigned to the height dimension. This allows for an integrated dimension where the same data variable is mapped to both color and height, or a separated dimension where different data variables are assigned to color and height independently.

Vertical Trees, Horizontal Trees

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

A connection-based chart that arranges parent, child, and grandchild data in a single direction. When arranged vertically, it is called a vertical tree; when arranged horizontally, it is called a horizontal tree. A connection-based chart that arranges data in multiple directions is called a multi-directional tree.

Radial Trees

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

This is a connection-based chart that uses a polar coordinate layout, placing the parent at the center, its children on the surrounding ring, and grandchildren on the next outer ring.

Icicle Plots

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

An area-based chart that arranges parent, child, and grandchild data in a single direction. The data values themselves are represented by length (area), showing the relative proportions at each hierarchical level.

Sunburst

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

You can create this chart with…

An area-based chart that uses a polar coordinate layout, placing the parent at the center, its children on the surrounding ring, and grandchildren on the next outer ring. Data values are represented by angles showing relative proportions within each hierarchical level. It is called a “sunburst” because its appearance resembles an exploding sun.

Treemaps

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

You can create this chart with…

An area-based, nested chart where each data item is represented as a rectangle. A well-known example is the chart showing market capitalization and stock price changes in the stock market.

Circle Packing

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

You can create this chart with…

An area-based, nested chart type in which individual data points are represented as circles.

Force Directed Diagram

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

Tools that can create this chart…

This chart simulates magnetic and elastic forces on nodes to position them at even intervals. Since the absolute positions often change each time the simulation is run, it is not well suited for comparing multiple datasets.

Arc Diagram

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

You can create this chart with…

Nodes are arranged in a single row, and links are shown as arc-shaped lines. Variables are represented through the thickness and color of the link lines.

Bio Fabric

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

Nodes are represented as horizontal lines rather than points, and links are shown as vertical lines. This approach solves a notable drawback of connection-type network diagrams, where the visibility of link lines deteriorates significantly when the number of links is large.

Circular Layout

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

You can create this chart with…

Nodes are evenly distributed around the full circumference of a circle, and links are displayed inside the circle.

Chord Diagram

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

You can create this chart with…

Similar to a circular layout, nodes are distributed around the full circumference of a circle. However, in a chord diagram, data values are assigned to the arc angle of each node. Links are then displayed inside the circle.

Geography Based Connection

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

Nodes are displayed on a map, and their relationships are represented by connecting lines. A geographic coordinate system is used for spatial transformation.

Alluvial Diagram

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

You can create this chart with…

https://stripe.com/jp/privacy

This chart shows how a set of categorical data variables are grouped across various dimensions (such as year, country of origin, research category, document type, publishing journal, etc.). It is well suited for illustrating how multiple categorical variables in a dataset are interrelated.

Sankey Diagram

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

You can create this chart with…

sankeymatic.dataviz.jp

A visual summary of the flow volume and direction of quantitative data variables as they pass through stages of a process or system. It can make complex systems easier to understand. It can also be used as a marketing conversion funnel.

Adiacency Matrix

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

A matrix-based network diagram. In connection-type network diagrams, the visibility of links can deteriorate significantly as the number of nodes increases (known as the hairball problem), but adjacency matrices do not suffer from this issue. However, they tend to require more display space compared to other chart types. Sorting the rows and columns by a particular data value can also make exploration more efficient.

Changelog

Tue, 10 Mar 2026 00:00:00 +0000

Roadmap

AI-powered automatic chart selection and visualization tool
Project sharing within organizations

And more. This list will be updated as needed.

✅ Public sharing feature for created interactive visualization content
✅ CSV support for data used in Cytoscape, Gephi, and similar tools

Changelog

April 12, 2026

Localized checkout and sign-up flows for English users. The entire subscription experience — from pricing to payment — is now available in English.
Introduced USD pricing for international users. Plans now start at $17/month for individuals and $72/month for small teams.
Renamed “Enterprise Plan” to “Group Plan” for consistency across billing and pricing pages.

April 9, 2026

Launched multi-user plans for teams and departments. Choose from plans for 5, 10, or 30 members.

April 8, 2026

Fixed a display issue around the common header that occurred in some tools.

April 5, 2026

Added new tool: “Japanese-Western Calendar Converter”

April 3, 2026

Launched the “Data Library” page. Accessible from the navigation bar, it lets you browse and search sample datasets available across tools, then launch a compatible tool with the selected data.
Added a “Sample Data” button to each tool’s toolbar. You can now browse and load compatible sample datasets directly from within the tool.

April 2, 2026

The account dashboard domain has been changed from auth.dataviz.jp to app.dataviz.jp. You will be redirected automatically, but please update your bookmarks.
The tools listing page has been moved from the public site https://www.dataviz.jp/ to the members-only page https://app.dataviz.jp/.

March 31, 2026

Added a corporate number database that can be called from OpenRefine’s “Reconciliation” feature

March 24, 2026

Added new tool: “Draw-to-Answer Line Chart”

March 23, 2026

Added new tool: “3D Surface Chart”
Added public sharing feature to Parallel Coordinates

March 18, 2026

Added CSV format and Shift JIS data file support for Gephi and Cytoscape
Added a spiral chart example using RawGraphs to the showcase

March 17, 2026

Added Shift JIS data file support for RawGraphs, Parallel Coordinates, Voyager, Word Cloud, and Data Illustrator

March 14, 2026

Added new tool: “Parallel Coordinates”

March 12, 2026

Removed unnecessary line breaks within cells in Tabula
Added new tool: “Text Entity Extraction Tool”

March 11, 2026

The service was officially launched.

Privacy Policy

Tue, 10 Mar 2026 00:00:00 +0000

Version 1 - Enacted: March 10, 2026

“Data Toolbox” (hereinafter referred to as “the Service”) considers the protection of users’ personal information to be an important responsibility, and hereby establishes the following Privacy Policy.

This Policy describes how personal information is handled within the Service.

1. Information We Collect

The Service may collect the following information.

Data That Users Visualize and Analyze

The Service provides tools primarily intended for data visualization and analysis.

Basic Operation Data uploaded or entered by users (file contents such as CSV, Excel, JSON, manually entered data, etc.) is processed on the client side (within the user’s browser) for most features. This data is not sent to or stored on the Service’s servers.
When the Save Feature Is Used In certain visualization tools, only when the user explicitly selects “Save”, the following data is stored on the server:
- Chart and configuration data that the user has instructed to save
- Data processing via OpenRefine (temporary storage to prevent loss of work data)
Saved data is handled as follows:
- It is linked to the user’s account and accessible only by the user.
- Purpose of storage: Re-display, editing, and sharing (when permitted by the user) of saved content
- Retention period: Until the user deletes it (or all data is deleted upon account deletion)
- Upon request for deletion, data will be promptly removed.
Note Regarding Data Containing Personal Information The Service does not review or screen the content of data entered or uploaded by users in advance. If you upload data containing personal information to the server using the save feature, please handle it under your own responsibility. Unless you use the save feature, no data, including any personal information, will remain on the server.

Unless the save feature is used, no data that has been entered or uploaded (including data containing personal information) will remain on the server. However, OpenRefine performs temporary storage to prevent loss of work state.

Retention Period

Data stored on the server using the save feature (charts, settings, source data, etc.) is retained until the user instructs its deletion.
If an account deletion request is made, all associated saved data will be completely deleted without delay (typically within 7 days).

Information Provided by Users

Name
Email address
Account information
Inquiry details

Information Collected During Service Use

Service usage history
IP address
Browser information
Information obtained through cookies and similar technologies

The Service uses the external payment service Stripe, Inc. for processing payments for paid services.

Credit card information entered by users is sent directly to Stripe’s system and is not stored on the Service’s servers.

The payment-related information that the Service may obtain is limited to non-sensitive information such as the following:

Payment status
Card brand
Last 4 digits of the card number
Payment date and time
Subscription status

2. Purpose of Use of Personal Information

The information collected is used for the following purposes:

Provision and operation of the Service
Management of user accounts
Improvement and development of the Service
Responding to inquiries
Prevention of unauthorized use
Addressing violations of the Terms of Service
Payment processing and contract management for paid services
Notification of important announcements

3. Provision of Personal Information to Third Parties

The Service will not provide users’ personal information to third parties except in the following cases:

When the user has given consent
When required by law
When necessary for the protection of life, body, or property
When requested by a public authority

4. Use of External Services

The Service may use the following external services for its operation.

Stripe (Payment Processing)

Payment processing for paid services is handled by Stripe, Inc. Credit card information entered by users is securely processed by Stripe, and the Service does not obtain or store sensitive information such as card numbers. For information on how Stripe handles personal information, please refer to the following:

5. Cookies and Analytics

The Service may use cookies and similar technologies for the purpose of improving the Service and analyzing usage patterns. Cookies are small pieces of data stored in the user’s browser and do not contain information that directly identifies an individual. Users may refuse cookies through their browser settings; however, doing so may result in some features of the Service becoming unavailable.

6. Security of Personal Information

The Service implements reasonable security measures to prevent leakage, loss, and alteration of personal information. Regarding credit card information, the Service is designed not to retain card information on its side by using a PCI-DSS compliant payment service (Stripe).

7. Disclosure, Correction, and Deletion of Personal Information

Users may request the disclosure, correction, or deletion of their personal information.

If you wish to make such a request, please contact us at the address provided below. After verifying your identity, we will respond within a reasonable scope.

8. Use by Minors

If a minor wishes to use the Service, please obtain the consent of a parent or guardian before doing so.

9. Changes to the Privacy Policy

The contents of this Policy may be changed as necessary.

In the event of significant changes, users will be notified through the Service.

10. Contact Us

For inquiries regarding this Privacy Policy, please contact us at the following:

Data Toolbox Operator: Yuichi Yazaki

Google Forms

Pre-Contract Inquiry about 'Data Toolbox'

forms.gle

Version 1 - Enacted: March 5, 2026

FAQ

Sat, 07 Mar 2026 00:00:00 +0000

About This Service

What is Data Toolbox?

We provide a wide range of nimble data visualization (charts, data maps, network diagrams) and data wrangling tools — more diverse than Excel and easier than BI tools. Everything runs in your browser, and you can use all tools as much as you want with a flat-rate subscription.

Who is this service for?

This service is for anyone who works with data.

People who want to create charts that Excel can’t make
People who want to visualize data without programming languages like Python
People who want specialized visualizations such as maps, networks, or text
People who want to streamline data formatting and cleansing
It can be used for a wide range of purposes including general documentation, marketing, government, research, and data journalism.

What kinds of data visualizations can I create?

Create various charts
Exploratory data visualization
3D map visualization
Create data maps by prefecture or municipality
Network visualization
Text visualization

and more.

See the Choosing the Right Data Visualization Tool page for details.

What kinds of data wrangling can I do?

Visually cleanse 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
Quickly create buffer zones around POIs

and more.

See the Choosing the Right Data Wrangling Tool page for details.

Who owns the copyright of outputs (charts, etc.) created with these tools?

The copyright of visualizations you create belongs to you. You are free to publish and use them as you wish.

Can I use outputs (charts, etc.) created with these tools commercially?

Yes. You can freely use them in reports, presentations, papers, books, websites, and more.

Can I save my work?

For data visualization tools, we provide the ability to save your work as a project. These are listed on your dashboard and can be opened with a single click. Other tools (data wrangling, color design) do not have a save function — please download the output for your use.

What is a project?

We call the combination of “your data” and “your work in a tool” a “project.”

Can I start using it right away?

We are currently building and testing the service. We plan to launch around March 2026.

How to Use

Do I need to install anything?

No installation is required. All tools run in your browser. You don’t need any special software — just an internet connection and a web browser.

Do I need programming skills?

No programming is required. You can create charts and process data simply by uploading or entering your data. We’ve designed professional tools to be as simple to use as possible.

What data formats are supported?

Most tools accept data in CSV format. Some tools also support specific formats such as GeoJSON. Each tool’s page lists supported data formats and provides sample data.

Since Excel files can contain various data structures, we don’t support direct Excel uploads. Instead, we provide the versatile data cleansing tool OpenRefine.

Is sample data available?

We offer two types of data portals: sample data bundled with each tool, and original datasets curated based on popular requests.

Pricing & Subscriptions

How much does it cost?

The most basic Standard Plan is $20/month. Annual billing ($200/year) saves you $40 compared to monthly.

See the Pricing page for details.

Are subscriptions auto-renewed?

Yes. Using Stripe’s subscription system, your subscription is automatically renewed one month or one year after your payment date, depending on your plan.

Can I cancel at any time?

Yes, you can cancel at any time. After cancellation, automatic payments will stop, and you can continue using the service until the end of your current billing period.

Data Security

Can I use personal or confidential data?

Data used in our tools is generally not stored on our servers, but processing methods vary by tool. Some data visualization tools have a feature to save your work-in-progress, and in those cases data is stored on the server. For all other tools, data is not retained on the server side.

Future Plans

Will more tools be added?

We continuously add and improve tools in this service. We plan to add new data visualization and data wrangling tools on an ongoing basis. Some tools may be modified or discontinued. We welcome requests for tools and datasets, and will accommodate them as much as possible.

Adoption & Organizational Use

Can teams or companies use this?

Yes, teams and companies can use this service. As a suite of tools for streamlining data visualization and data wrangling, it can be used by people in various roles such as analysts and planners. It can also be adopted as a common data tool within a team.

However, a license is required for each user. We offer bulk account registration and volume discounts — please contact us via the Contact page.

Can it be used for corporate training or educational purposes?

Yes, it can be used for educational purposes. It can serve as a tool for learning data visualization and data literacy in university courses or corporate training. Since many of the tools are single-function, they are well-suited as teaching materials for understanding data structures and visualization mechanisms.

However, a license is required for each user. We offer bulk account registration and volume discounts — please contact us via the Contact page.

License

Wed, 04 Mar 2026 00:00:00 +0000

A list of licenses and credits for the tools provided by this service.

Open Source Software

The following tools are based on original open source projects. We are grateful to the developers of each project.

Color Brewer — Apache-2.0 License (Cynthia Brewer, Mark Harrower, The Pennsylvania State University)
Cytoscape — MIT License (Cytoscape Consortium)
D3.js — ISC License (Mike Bostock)
Data Illustrator — MIT License (Georgia Tech)
(Geo) Data Merger — MIT License (Fabio Berta)
GeoJSON.io — ISC License (Mapbox)
Gephi Lite — GPL-3.0 License (Gephi / OuestWare)
iwanthue — MIT License (Sciences Po médialab)
JSON Crack — Apache-2.0 License (Aykut Saraç)
kepler.gl — MIT License (Urban Computing Foundation)
Leonardo — Apache-2.0 License (Adobe)
Mapshaper — Mozilla Public License 2.0 (Matthew Bloch)
OpenRefine — BSD-3-Clause License (OpenRefine contributors)
Parallel Coordinates — BSD-3-Clause License (Kai Chang)
RAWGraphs — Apache-2.0 License (DensityDesign Lab, Politecnico di Milano)
Sankeymatic — ISC License (Steve Bogart)
Tabula PDF — MIT License (Manuel Aristarán, Mike Tigas, Jeremy B. Merrill)
Tilegrams — ISC License (Pitch Interactive)
Vega Editor — BSD-3-Clause License (UW Interactive Data Lab)
Voyager 2 — BSD-3-Clause License (UW Interactive Data Lab)
Easings Cheat Sheet — GPL-3.0 License (Andrey Sitnik, Ivan Solovev)
Map Tile Browser — MIT License

dataviz.jp Original Tools

The following tools are originally developed by dataviz.jp.

ADS-B / AIS Visualization
Aozora Bunko Ruby Remover
Address to Lat/Lon Converter
Buffer Generator
Cartogram Japan
Cartogram Prefectures
Choropleth Japan
Choropleth Prefectures
Coordinate System Converter
GTFS Network Data Converter
Lat/Lon Formatter
Mapbox Classic Style Generator
QuickChart UI
Shift JIS / UTF-8 Encoding Converter
SVG / GeoJSON Converter
SVG Gradient Editor
SVG Texture Editor
Word Cloud

Specified Commercial Transaction Act

Mon, 02 Mar 2026 00:00:00 +0000

Business Operator

Notation LLC

Business Location

N&E BLD. 7F, 1-12-4 Ginza, Chuo-ku, Tokyo 104-0061, Japan

Contact

info@notation.co.jp

Pricing

All prices are displayed inclusive of consumption tax.

Payment Method

We use Stripe for payment processing.

Handling of Personal Information

Please refer to our Privacy Policy.

Cancellations

No returns, refunds, or cancellations are accepted at the customer’s convenience. Please be aware of this before purchasing.

Supported Browsers

Latest versions of Chrome, Firefox, Safari, and Edge on desktop computers. Tablets and smartphones are not guaranteed to be supported.

Delivery of Products

Upon purchasing paid content, access will be available immediately after the payment process is completed.

Terms of Service

Mon, 02 Mar 2026 00:00:00 +0000

Version 1 - Enacted: March 10, 2026

These Terms of Service (hereinafter referred to as “these Terms”) set forth the conditions for using the data visualization and data processing tool suite service “Data Toolbox” (https://www.dataviz.jp/) (hereinafter referred to as “the Service”) provided by Notation LLC (hereinafter referred to as “the Company”). Users shall use the Service upon agreeing to these Terms.

Article 1: Scope of Application

These Terms apply to all aspects of the relationship between users and the Company regarding the use of the Service.
Any individual rules or guidelines posted by the Company within the Service shall constitute a part of these Terms.

Article 2: Definitions

The terms used in these Terms are defined as follows:

“User” An individual or legal entity who uses the Service upon agreeing to these Terms.
“Account” The identification information assigned to a user in order to use the Service.
“Content” All information provided through the Service, including software, tools, programs, text, images, data, UI, and any other materials.

Article 3: Service Description

The Service is an online service that provides various tools for data visualization and data processing.
The Service includes multiple tools, but the features and content of each tool are subject to change.
The Company may add, modify, or remove features of the Service.
The Company may impose reasonable limitations on usage volume, processing frequency, data size, access frequency, and other usage methods in order to ensure the stable provision of the Service.
The Company may add, modify, or discontinue any tools, features, or content included in the Service.

Article 4: Account Registration

Users may be required to register an account in order to use the Service.
Users shall keep their registration information accurate and up to date.
Users shall manage their account information at their own responsibility.
The Company shall not be liable for any damages arising from unauthorized use of an account.

Article 5: Subscription

Part or all of the Service may be provided in a paid subscription format.
Subscriptions will automatically renew unless cancelled by the user.
Usage fees, payment methods, renewal cycles, and other details shall be in accordance with the information displayed on the Service.
Payments may be processed through third-party payment services such as Stripe.
Users shall also comply with the terms of service of the payment service.
The Company may change the features, content, usage fees, or pricing structure of the Service. Such changes will be communicated by posting on the Service or by other means the Company deems appropriate.

Article 6: Cancellation

Users may cancel their subscription through the prescribed method.
Once the cancellation procedure is completed, no charges will be incurred from the next renewal date onward.
Fees already paid will not be refunded, except as required by law or as otherwise determined by the Company.

Article 7: Handling of Data

Users shall be responsible for the content, legality, and right to use any data entered or uploaded to the Service (hereinafter referred to as “User Data”).
The Company has no obligation to monitor or guarantee the content of User Data.
When handling personal information or confidential information, users shall manage it appropriately at their own responsibility.
Even if User Data is stored or retained within the Service, the Company does not guarantee its storage, integrity, or continued retention. Users shall back up their data at their own responsibility as needed.

Article 8: Visualization and Analysis Results

Visualization results, analysis results, processed data, and other outputs generated by the Service are provided as reference information.
The Company does not guarantee the accuracy, completeness, or usefulness of such results.
Users shall use the results at their own responsibility.

Article 9: Prohibited Activities

Users shall not engage in the following activities when using the Service:

Activities that violate laws, regulations, or public order and morals
Activities that infringe upon the rights of the Company or third parties
Activities that interfere with the operation of the Service
Unauthorized access or attempts thereof
Using bots, scraping tools, automation tools, or similar means to extract content from the Service
Copying, reverse-engineering, or redistributing the software or features of the Service
Using the Service for the purpose of developing a competing service
Developing or providing a service that competes with the Company by utilizing the features of the Service
Any other activities deemed inappropriate by the Company

Article 10: Intellectual Property Rights

Intellectual property rights related to the software, tools, designs, text, images, UI, programs, and other elements of the Service belong to the Company or their rightful owners.
The copyright of visualizations, images, charts, processed data, and other outputs created by users using the Service (hereinafter referred to as “Generated Content”) belongs to the respective user, provided that such use does not infringe upon the rights of the Company or third parties, including software, templates, and design elements included in the Service.
Users may use, publish, and distribute Generated Content at their own responsibility.
Users hereby grant the Company a free-of-charge license to store, copy, process, display, distribute, embed, and otherwise handle Generated Content to the extent necessary for the provision and operation of the Service.
The Company may introduce Generated Content created by users for the purpose of promoting or publicizing the Service, provided that such use does not unreasonably harm the rights of the user.

Article 11: Third-Party Software

The Service may include open-source software or third-party software. The use of such software may be subject to their respective license terms.

Article 12: Changes and Suspension of Service

The Company may change, add, or remove the content of the Service without prior notice.
The Company may suspend all or part of the Service in the following cases:

System maintenance
Incident response
Force majeure
Other cases deemed necessary for operational purposes

Article 13: Suspension of Use

The Company may suspend or delete a user’s account without prior notice if the Company determines that the user falls under any of the following:

Violation of these Terms
Unauthorized use
Extended period of non-use
Other cases deemed inappropriate by the Company

Article 14: Disclaimer

The Company shall not be liable for any damages caused by system failures, data loss, service interruptions, or similar events in the course of providing the Service.
Even if the Company is found to be liable, such liability shall be limited to the total amount of usage fees paid by the user to the Company.

Article 15: Changes to the Terms

The Company may change these Terms when deemed necessary. The revised Terms shall take effect upon being posted on the Service.

Article 16: Governing Law and Jurisdiction

These Terms shall be governed by the laws of Japan.
In the event of any dispute arising in connection with the Service, the court having jurisdiction over the location of the Company’s head office shall have exclusive agreed jurisdiction as the court of first instance.

End of Terms

About Us

Mon, 23 Feb 2026 00:00:00 +0000

Operating Company

Notation LLC

Based on the belief that “data visualization is the intersection of expressive communication and problem-solving,” we provide new forms of notation to the world.

notation.co.jp

合同会社ノーテーション

notation.co.jp

About the Representative

Yuichi Yazaki

After seven years of experience as a user interface designer and art director at Business Architects Inc., Yuichi Yazaki went independent. He is engaged in a wide range of activities related to the practice and promotion of data visualization, including lectures at corporations and educational institutions, information dissemination through the website Visualizing.JP, and community activities through Data Visualization Japan.

He is the sole author of “The Complete Guide to Data Visualization Fundamentals” and co-author of “The RESAS Textbook” (Nikkei BP, 2016). He holds a Master’s degree in Design Science from Chiba Institute of Technology. He is the founder of Data Visualization Japan and a Yahoo! News Expert.