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Data Tools

Whether you're a developer, data analyst or a casual user, here are some tools that can help you whether you're using the Detail Data Portal, or working with your own data.

These tools are aimed at all levels of user, from the novice to the expert, and are all free to use (with at most a requirement to sign up).

Further suggestions on anything that would be useful or that demonstrate how you're using data are very welcome, please contact us.

​Contents
Clean Your Data
Visualise Your Data
Analyse Your Data
Get Help

Clean Your Data

Trifacta

We aim to provide our datasets in the useful, standarised and simple formats. Though we spend a lot of time cleaning, tidying and providing our data in various file types, users have individual needs that may require altering fields and values after downloading the data.

If you need to clean messy, real-world data before putting it to use (otherwise known as data 'wrangling') you could use basic software packages such as Excel or even a text editor, but specialist tools also exist to make this easy and straightforward.

Data Wrangler / Trifacta

Wrangler is an interactive and visual tool that can transform, correct and cross-tabulate irregularly-formatted datasets (e.g. multi-table data files). It's web-based and simple to use, so you don't need to install anything. It also makes predictive suggestions that can help to guide you through the process. There's now a downloadable and supported version called Trifacta.

Open Refine 

Originally developed by Google, Open Refine is a powerful tool for making messy datasets clean and useable. It's better than using 'Find & Replace All', helps you to quickly transform data en masse and helps to find and correct errors.

Convert CSV

Have you downloaded a dataset in a strange format and don't know where to start with it, or just want to get it into another format? Try Convert CSV to upload or paste in JSON, XML, SQL, HTML, KML and other types of popular data formats and convert to CSV or Excel formats.

PDF Tables

Ever download a dataset only to find it's been produced as a near-to-useless PDF? There's a number of 'data scraping' tools that allow you to get useful, tabulated data out, PDF Tables, from ScraperWiki, is one of the best.

More information

If you're a regular wrangler, acqaint yourself with Tidy Data Principles for working with data in the wild.

Visualise Your Data

There are a multitude of ways to visualise data, and alot of it is down to communication, flexibility, interactivity or just personal preference. Data visualisation is becoming an industry in itself, not just the last step in publication, and there is now a massive range of different providers of tools for chart making and presentation. 

We'll present some tools and guides for data visualisation, but alot has been done to create libraries and respositories of visualisation that you should check those out too.

Datawrapper

Starting at the small end of the scale, Datawrapper allows you to upload data and make a simple chart that you can embed in a website in seconds.

Google Sheets

Similiar to using Excel, Google Sheets allows you to define your x and y axes from your spreadsheet and create scatter, line, bar, histogram and pie charts (full list here). For the initiated who know Javascript, you can also access the graph library directly though the Charts API.

Plotly

Plotly is a web-based app that provides a number of different charts for making your data make sense. In the latest version you can also build and publish dashboards using a number charts to present information to others, and it integrates with popular programming packages (Python, R, Excel, MATLAB, Javascript).

Tableau Public

Tableau provides a data storing, analysis, visualisation and web-publication platform in one. You can create full data dashboards, and extend interactivity to other users. There's also the simple, lean version, Tableau Reader.

Raw

Built on top of the flexible D3.js charting library, Raw lets you upload and preview your visualisation through a number of innovative charts that you'll be hard-pressed to find anywhere else (dendograms, alluvial flow diagrams, voronoi tessellation charts).

More information

Check out some of the vast visualisation repositories: Visualising Data, DataVisualisation.ch and Open-Data Tools.

Analyse Your Data

Crunching through numbers to perform data manipulation and calculations is probably the trickiest part of working with data. From the beginner to the expert, here's a few of our favourites that aren't Microsoft Excel.

Google Fusion

Fusion Tables is the cousin to Google Sheets, letting you do much of what you can do in Sheets (such as visualisation and importing/exporting data), but also makes it easy to summarise, 

R

Along with Python, R is the programming language of choice for statisticians. It is a complex language with a huge library off extended packages, but R Studio makes it easier to use and there are a number of guides and a broad user and developer community out there.

Python Pandas

You can use basic Python functions for data in Python, but the Pandas library provides a fast, structured and easy-to-use approach to working with many different types of data. If you're using Python, you should also check out Bokeh for visualisation.

Get Help

Our purpose is to improve how the voluntary and community sector uses data. So, if you're stuck or want some advice, we're here to help.