Data Wrangling Problems on Data Prep Toolbox

Visually cleanse your data

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

Use this pattern when you want to clean inconsistent labels, blanks, duplicate rows, or unnecessary columns in CSV or Excel data while visually checking the result.

Solution

Choose a tool that lets you inspect value distributions, filter problem rows, and apply replacements step by step. If you also want to reuse the same preparation flow on other files, a tool with saved transformation history is a strong fit.

Tool

dataprep.jp

OpenRefine

Data cleansing and transformation tool for tabular data

open-refine.dataprep.jp

Good fit for

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

Easily merge map data with thematic data

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

Use this pattern when you have geographic boundaries in one file and statistics in CSV or Excel, and want to combine them quickly for mapping.

Solution

First align a shared key such as municipality code or place name. Then use a tool that accepts both geographic data and tabular data and lets you inspect the join result before exporting.

Tool

dataprep.jp

(Geo) DataMerger

Easily merge geographic data with thematic data

geo-data-merger.dataprep.jp

Good fit for

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

Quickly understand JSON structure

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

Use this pattern when an API response or configuration JSON is complex and you need to quickly see where the fields you need actually live.

Solution

Instead of reading raw text, visualize the JSON as connected nodes. That makes parent-child relationships and nested arrays much easier to understand before you extract or transform anything.

Tool

dataprep.jp

JSON Crack

Visually understand JSON data structures in your browser

jsoncrack.dataprep.jp

Good fit for

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

Fix character encoding issues

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

Use this pattern when Japanese text becomes garbled after opening a CSV, or when a GIS or spreadsheet app fails to read the file correctly.

Solution

Identify the original encoding first, then convert the file into the encoding expected by the next tool. A fast converter makes it easy to validate both directions before sharing or importing the data.

Tool

dataprep.jp

Shift JIS ⇄ UTF-8 Converter

Convert character encoding between Shift JIS and UTF-8

change-character-encoding.dataprep.jp

Good fit for

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

Easily convert addresses to latitude/longitude

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

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

Solution

Convert addresses into coordinate columns first, then move on to visualization or spatial analysis. Batch geocoding is much more reliable and efficient than checking each point manually.

Tool

dataprep.jp

Address to Lat/Lon Converter

Geocoding tool for converting address lists into coordinates

address-to-latlon.dataprep.jp

Good fit for

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

Extract table data from PDFs

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

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

Solution

Select the tabular region first, then extract it while preserving rows and columns. Once the table is out, you can clean headers and blanks in a separate step.

Tool

dataprep.jp

Tabula PDF

Extract table data from PDFs

tabula-pdf.dataprep.jp

Good fit for

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

Reduce map data file size

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

Use this pattern when your map data is too heavy to load comfortably in the browser, share with others, or import into a visualization tool.

Solution

Simplify geometry while preserving shape, and remove attributes you do not need. A tool that also handles conversion and merging helps keep the whole preprocessing flow in one place.

Tool

dataprep.jp

Mapshaper

Process and convert map data

mapshaper.dataprep.jp

Good fit for

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

Format and convert map data

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

Use this pattern when decimal precision or coordinate reference systems are inconsistent and your map data does not line up correctly in the next tool.

Solution

Standardize latitude/longitude formatting first, then convert the coordinate system if needed. Splitting the work into formatting and projection changes makes it easier to isolate the source of location errors.

Tools

dataprep.jp

Lat/Lon Formatter

Standardize latitude/longitude format and precision

latlon-formatter.dataprep.jp

dataprep.jp

Transform Coordinates

Convert the coordinate system of geographic files

transform-coordinates.dataprep.jp

Good fit for

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

Create custom map data

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

Use this pattern when the points, lines, or polygons you need are not available as ready-made data and you have to create them yourself.

Solution

Use a tool that lets you draw points, lines, and polygons directly on top of a base map and export GeoJSON. Start with the minimum area or features you need, then add attributes afterward.

Tool

dataprep.jp

GeoJSON.io

Create GeoJSON while tracing over map tiles

geojson.dataprep.jp

Good fit for

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