22 free tools for data visualization and analysis

You may not think you’ve got much in common with an investigative journalist or an academic medical researcher. But if you’re trying to extract useful information from an ever-increasing inflow of data, you’ll likely find visualization useful — whether it’s to show patterns or trends with graphics instead of mountains of numbers, or to try to explain complex issues to a nontechnical audience.

There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge.

They range from easy enough for a beginner (i.e., anyone who can do rudimentary spreadsheet data entry) to expert (requiring hands-on coding). But they all share one important characteristic: They’re free. Your main investment: time.

Data cleaning

Before you can analyze and visualize data, it often needs to be cleaned. What does that mean? Perhaps some entries list “New York City” while others say “New York, NY” and you need to standardize them before you can see patterns. There might be some records with misspellings or numerical data-entry errors. “Cleaning” tools are designed to help get your data in shape to be analyzed for the period.

 DataWrangler (and subsequently Trifacta)

What they do: The DataWrangler web-based service from Stanford University’s Visualization Group is designed for cleaning and rearranging data so it’s in a form that other tools such as a spreadsheet app can use.

Click on a row or column, and DataWrangler will suggest changes. For example, if you click on a blank row, several suggestions pop up such as “delete row” or “delete empty rows.”

There’s also a history list that allows for easy undo — a feature that’s also available in Open Refine (reviewed next).

The team behind Data Wrangler later went to work on the Trifacta commercial product, although the service can still be used as is at the URL above. Trifacta is desktop software. The free version allows one user (without collaboration) and import of local CSV, JSON, text and Excel files.

What’s cool: Text editing is especially easy in DataWrangler. For example, when I selected “Alabama” in one row of sample data headlined “Reported crime in Alabama” and then selected “Alaska” in the next group of data, it led to a suggestion to extract every state name. Hover your mouse over a suggestion, and you can see affected rows highlighted in red.

Drawbacks: I found that unexpected changes occurred as I attempted to explore DataWrangler’s options; I constantly had to click “clear” to reset. And not all suggestions are useful (“promote row to header” seemed an odd suggestion when the row was blank) or easy to understand (“fold split 1 using 2 as key”).

Skill level: Advanced beginner

Runs on: Any web browser for Data Wrangler; Windows or macOS X for Trifacta

Learn more: There’s a screencast on the Data Wrangler home page. Also, see this post on using DataWrangler to format data (from Tableau Public’s blog). For more on Trifacta, see its resources page.

 OpenRefine (formerly Google Refine)

What it does: OpenRefine can be described as a spreadsheet on steroids for taking a first look at both text and numerical data. Like Excel, it can import and export data in a number of formats including tab- and comma-separated text files.

OpenRefine features several built-in algorithms that find text items that should be grouped together. After importing your data, you can select edit cells –> cluster and edit and choose which algorithm you want to use. After OpenRefine runs, you decide whether to accept or reject each suggestion. For example, you could say yes to combining Microsoft and Microsoft Corp., but no to combining Coach Inc. with CQG Inc. If it’s offering too few or too many suggestions, you can change the strength of the suggestion function.

There are also numerical options that offer quick and easy overviews of data distributions. This functionality can reveal anomalies that might be the result of data input errors — such as $800,000 instead of $80,000 for a salary entry — or it could expose inconsistencies, such as differences in the way compensation data is reported from entry to entry, with some showing, say, hourly wages and others showing weekly pay or yearly salaries.

Beyond data housekeeping, OpenRefine offers some useful analysis tools, such as sorting and filtering.

What’s cool: Once you get used to which commands do what, this is a powerful tool for data manipulation and analysis that strikes a good balance between functionality and ease of use. The undo/redo list of every action you’ve taken lets you roll back when needed. You can also store command histories to run again. And text functions handle Java-syntax regular expressions, allowing you to look for patterns (such as, say, three numbers followed by two digits) as well as specific text strings and numbers.

Finally, while this is a browser-based application, it works with files on your desktop, so your data remains local.

Drawbacks: If you’ve got a large data set, carve out some time in your day to go through all of Refine’s suggested changes, since it can take a while. And, depending on the data set, be prepared when looking for text items to merge: You’re likely to get either a lot of false positives or missed problems — or both.

Skill level: Advanced beginner. Knowledge of data analysis concepts is more important than technical prowess; power Excel users who understand data-cleaning needs should be comfortable with this.

Runs on: Windows, macOS X (if it appears to do nothing after loading on a Mac, point a browser manually to http://127.0.0.1:3333/ ), Linux

Learn more: These three screencasts give a good overview of why and how you’d use Refine; there’s also fairly detailed documentation on GitHub.

Statistical analysis

Sometimes you need to combine graphical representation of your data with heftier numerical analysis.

The R Project for Statistical Computing

What it does: R started off life as a statistical analysis language with built-in support for graphics and handling certain common data formats such as spreadsheet-like rows and columns. Thousands of add-on packages later, it’s also used for mapping, dashboards, interactive Web apps and more.

What’s cool: There is a great deal of functionality in R, including quite a number of visualization options as well as numerical and spatial analysis. And the R community is adding to the language all the time, as well as generally responsive and helpful. Disclosure: I’m a longtime fan.

Drawbacks: The fact that R runs on the command line means that users will have to take the time to learn which commands do what, and not all users will be comfortable with a text-only interface. Some still complain that the language is slow, although enthusiasts counter that this can usually be fixed with better code and enterprise-class big data tools such as Microsoft R Server.

Skill level: Intermediate to advanced. Comfort with command-line prompts and a knowledge of statistics are musts for the core application.

Runs on: Linux, macOS X, Unix, Windows

Learn more: Check out the Computerworld Beginner’s Guide to R and our list of .

Visualization applications and services

These tools offer a number of different visualization options. While some stick to conventional charts and graphs, many offer a range of other choices such as treemaps and word clouds. A few offer mapping as well, although if you’re interested in maps, our sections on GIS/mapping focus specifically on that.

 Google Fusion Tables

What it does: This is one of the simplest ways I’ve seen to turn data into a chart or map. You can upload a file in several different formats and then choose how to display it: table, map, line chart, bar graph, pie chart, scatter plot and more. It’s customizable, allowing you to change map icons and style info windows.

There are some data editing functions within Fusion Tables, although changing more than a few individual cell entries can quickly become tedious. You can also join tables (which is important when the data you want to map is in multiple tables), and filter, sort and add columns and so on.

Mapping goes beyond just placing points, as many of us are accustomed to with Google Maps. Fusion tables can also map multiple polygons with variations in color based on underlying data.

Google lets you designate your data as private or unlisted as well as public, although your data still resides on Google’s servers — a benefit or drawback, depending on whether server bandwidth costs or data privacy is more important to you.

What’s cool: Fusion Tables offers relatively quick charting and mapping, including geographic information system (GIS) functions to analyze data by geography. The service also automatically geocodes addresses, which is useful when trying to place numerous points on a map. This is an excellent tool for beginners and advanced beginners to use to get comfortable with visualizing data; it’s also a good fit for people who don’t program. For more advanced users, there’s an API.

Drawbacks: Functionality, customization and data capacity are all limited compared with desktop applications or custom code, and interacting with large data sets on the site can be sluggish. And, while Fusion Tables has been around for years, Google still considers it an experimental product.

Skill level: Beginner

Runs on: Any web browser

Learn more: See Google’s three-minute tutorial on How to make a map in Google Fusion Tables. In addition, there are other how-tos in the Google Fusion Tables Help center, and several tutorials are available. Also see the Fusion Tables Example Gallery.

 Microsoft Power BI

What it does: This is Microsoft’s general BI platform, with data wrangling and visualization for many different data sources (without Excel’s row limits), as well as a web service that allows for streaming data and scheduled data updates.

Power BI was designed for robust data analysis that goes beyond Excel’s natural capabilities. Aimed to be simple, it offers drag-and-drop visualizations as well as the ability to create auto-updating reports and dashboards. There’s both free desktop software, which includes data-wrangling capabilities and is for Windows only, and a powerbi.com cloud service for visualizing data that can run in any modern browser. As of June 2017, private sharing on powerbi.com requires paid accounts, but free users can still post public visualizations as well as use the desktop software.

What’s cool: This is simple to use for basic visualizations and report creation and makes it fairly easy to do data exploration. It will handle files too large for Excel. Customization and filtering are also fairly straightforward. Runs R scripts within the desktop software and can generate many R visualizations.

Drawbacks: Customizing can be a little cumbersome and somewhat limited. Moving back and forth between the desktop and cloud service can be a bit confusing at the outset. Data filtering is also a tad limited at times, although Microsoft is adding new capabilities to the platform monthly.

Skill level: Beginner

Runs on: Windows for the desktop; any web browser for the service

Learn more: See Computerworld‘s Free data visualization with Microsoft Power BI: Your step-by-step guide as well as training resources from Microsoft.

 Tableau Public

What it does: This tool can turn data into any number of visualizations, from simple to complex. You can drag and drop fields onto the work area and ask the software to suggest a visualization type, then customize everything from labels and tool tips to size, interactive filters and legend display.

What’s cool: Tableau Public offers a variety of ways to display interactive data. You can combine multiple connected visualizations onto a single dashboard, where one search filter can act on numerous charts, graphs and maps; underlying data tables can also be joined. And once you get the hang of how the software works, its drag-and-drop interface is considerably quicker than manually coding in JavaScript or R for most users, making it more likely that you’ll try additional scenarios with your data set. In addition, you can easily perform calculations on data within the software. Tableau offers 10G of storage for public accounts and 15 million rows per workbook.

Drawbacks: In the free version of Tableau’s business intelligence software, your visualization and data must reside on Tableau’s site. Whenever you save your work, it gets sent up to the public website — which means you can’t save work in progress without running the risk that it will be seen before it’s ready (while Tableau’s site won’t deliberately expose your work, it relies on security by obscurity — so someone could see your work if he or she guesses your URL). And once your work is saved, viewers are invited to download your entire workbook with data. Upgrading to a single-user personal subscription costs $35/month; professional edition is $70/month.

Tableau’s learning curve is steeper than, say, Fusion Tables. Even with the drag-and-drop interface, it’ll take more than an hour or two to learn how to use the software’s true capabilities, although you can get up and running doing simple charts and maps before too long. And, some users have complained that making Tableau graphics mobile-friendly can be challenging.

Skill level: Advanced beginner to intermediate

Runs on: Windows; macOS X

Learn more: There are several short training videos on the Tableau site, where you can also find downloadable data files that you can use to follow along.

You can see a sample in our article “.”

 Google Data Studio

What it does: This service is designed to create dashboards and reports from multiple data sources. The focus is on Google sources such as Google Sheets, Google Analytics and BigQuery, but some other sources are supported as well, such as MySQL and PostgreSQL databases.

This is fairly easy to use, offering drag-and-drop visualizations such as time series, bar charts, tables, maps and “score cards” (a card that calls out one statistic). Styling includes a grid and alignment options, making it easy to ensure that multiple boxes aren’t slightly off in a row. You can also create your own calculated fields within Data Studio, including formulas with a few dozen available functions.

What’s cool: Relatively easy to use — I was up and running after watching a couple of tutorial videos. One of the easiest ways to create Google Analytics dashboards for multiple websites.

Drawbacks: It’s a beta product, meaning there’s a higher-than-average risk of it going away (or no longer being free). Limited number of available visualizations compared with some other options. Data has to reside in the cloud, which could be a deal-breaker for some sensitive information.

Skill level: Beginner

Runs on: Any web browser

Learn more: See Google’s Data Studio video tutorials.

 Plotly

What it does: The web service lets you create and host visualizations, from basic charts and scatter plots to statistical graphics such as histograms and box plots.

Plotly aims at statistical analysis along with charts and graphs you might see in your local newspaper. A free account includes one private file as well as unlimited public files and connections to seven types of data sources.

Plotly also open-sourced its JavaScript library, for those who want to work with their data locally and do more customizations; libraries for Python and R; and a client for MATLAB. There’s even a free Excel add-in.

What’s cool: It’s relatively easy to make interactive visualizations on the service, and the technology can be used across a wide variety of platforms.

Drawbacks: Even with customization, Plotly visualizations have a distinctive look that might not be for everyone. There’s limited free use of private data on the service.

Skill level: Beginner for web service; expert for most of the open-source libraries

Runs on: Modern web browsers

Learn more: Check resources at the Plotly Help Center.

 Qlik Sense Desktop

What it does: This multipurpose BI tool can wrangle data and create interactive data visualizations, reports and dashboards.

The free Qlik desktop app is designed for personal data exploration or sharing in small groups. If you want to collaborate or share, Qlik Sense Cloud is free for sharing with up to five other users.

You can prepare data before loading, create associations from multiple sources, edit within the application and create visualizations such as combo charts and tree maps.

What’s cool: This is a fairly robust application for free, and all data can be saved locally. Data sources can include Apache Hive, REST and Salesforce as well as other types, such as databases and spreadsheets.

Drawbacks: With power comes complexity: You’ll need to invest some time learning this application. Some of the latest intro tutorial videos assume knowledge of the product’s prior version instead of focusing on beginners to the platform.

Skill level: Advanced beginner to intermediate

Runs on: 64-bit Windows

Learn more: Qlik video tutorials

 VIDI

What it does: Although VIDI’s website bills this as a tool for the Drupal content management system, graphics created by the site’s visualization wizard can be used on any HTML page — no Drupal required.

Upload your data, select a visualization type, do a bit of customization selection, and your chart, timeline or map is ready to use via auto-generated embed code (using an iframe, not JavaScript or Flash).

What’s cool: This is easy to use, with mapping options and no need to make your visualization and data set public on its website. There are quick screencasts explaining each visualization type and several different color customization options.

Drawbacks: Surprisingly, the visualization wizard was easier to use than the embed code — my embedded iframe didn’t display while trying to preview it on the VIDI website; I needed to save the visualization and go to the “My VIDI” page to get embed code that actually worked. Also, as with any cloud service, if you’re using this for web publishing, you’ll want to feel confident that the host’s servers can handle your traffic and will be available longer than your need to display the data.

Skill level: Beginner

Runs on: Any web browser

Learn more: The VIDI home page features a link to a video tutorial.

It took me less than five minutes to create a sample: a map of earthquakes of 7.0 magnitude or more since Jan. 1, 2000.

 Zoho Reports

What it does: Zoho Reports can take data from various file formats or directly from a database and turn it into charts, tables and pivot tables — formats familiar to most spreadsheet users.

What’s cool: You can schedule data imports from sources on the web. Data can be queried using SQL and can be turned into visualizations, and the service is set up for web publishing and sharing (although if it’s accessed by more than two users, you will need a paid account).

Drawbacks: Visualization options are fairly basic and limited. Interacting live with the web-based data can be sluggish at times. Data files are limited to 100,000 rows in the free version. I found the navigation confusing at times.

Skill level: Advanced beginner

Runs on: Any web browser

Learn more: There are video demos and samples on Zoho’s website.

Code help: Wizards, libraries, APIs

Sometimes nothing can substitute for coding your own visualization — especially if the look and feel you’re after can’t be achieved without an existing desktop or web app. But that doesn’t mean you need to start from scratch, thanks to a wide range of available libraries and APIs.

 D3.js

What it does: One of the most popular JavaScript libraries for creating web visualizations, D3.js “combines powerful visualization components and a data-driven approach to DOM [Web document] manipulation,” according to the project’s website.

D3.js allows you to create data-based visualizations on a web page, allowing designers to create a wide range of interactive visualizations.

What’s cool: If you can imagine it, chances are good that you can implement it in D3.js. One oldie but goodie from The New York Times: Comparing Facebook’s initial stock offerings to other tech IPOs.

Drawbacks: This is not a trivial skill to learn. You’ll need a fair amount of knowledge about both this JavaScript library and web technologies in general in order to do anything compelling. For basic dataviz, this will be a lot of work for the uninitiated.

Skill level: Expert

Runs on: Most modern browsers

Learn more: See the D3 tutorials page, including links to some useful beginners’ how-tos by Scott Murray.

 Exhibit

What it does: This spin-off of the MIT Simile Project is designed to help users “easily create Web pages with advanced text search and filtering functionalities, with interactive maps, timelines and other visualization.” Billed as a publishing framework, the JavaScript library allows easy additions of filters, searches and more. The Easy Data Visualization for Journalists page offers examples of the code in use at a number of newspaper websites.

“Easy” is in the eye of the beholder — what’s easy for the professionals at MIT who created Exhibit might not be that simple for a user whose comfort level stops at Excel. Like most JavaScript libraries, Exhibit requires more hand-coding than services such as Google Fusion Tables. On the other hand, Exhibit has clear documentation for beginners, even those with no JavaScript experience.

What’s cool: For those who are comfortable coding, Exhibit offers a number of views — maps, charts, timeplots, calendars and more — as well as customized lenses (ways to format an individual record) and facets (properties that can be searched or sorted). You may be more likely to get the exact presentation you want with Exhibit than a web service with limited customization. And your data stays local unless and until you decide to publish.

Drawbacks: For newcomers unused to coding visualizations, it takes time to get familiar with coding and library syntax.

Skill level: Expert

Learn more: There are a number of examples you can look at, including U.S. Cities by Population and others.

 Google Chart Tools

What it does: Unlike Google Fusion Tables, which is a full-fledged, self-contained application for storing data and generating charts and maps, Chart Tools is designed to visualize data residing elsewhere, such as your own website or within Google Docs.

The Chart Tools API accesses a Google JavaScript library for creating interactive graphics. (Note: Google ended support for creating static image charts. The Chart Tools API is not affected.)

The visualization API includes various types of charts, maps, tables and other options.

What’s cool: The API lets you pull data in from a Google spreadsheet. You can create icons that mix text and images for visualizations, such as this weather forecast note, and what it calls a “Google-o-meter” graphic. The Visualization API also has some of the best documentation I’ve seen for a JavaScript library.

Drawbacks: The API, as with other JavaScript libraries, requires coding, making this more of a programming tool than an end-user business intelligence application. But unlike most other JavaScript libraries, you don’t have access to the underlying code and have to depend on Google to continue supporting the platform.

Skill level: Advanced beginner to expert

Runs on: Any web browser

Learn more: See the Quick Start. There are also samples in the Google Visualization API Gallery.

 JavaScript InfoVis Toolkit

What it does: InfoVis is probably not among the best-known JavaScript visualization libraries, but it could be worth a look if you’re interested in publishing interactive data visualizations on the web.

What sets this tool apart from many others is the highly polished graphics it creates from just basic code samples. InfoVis creator Nicolas García Belmonte, senior software architect at Sencha Inc., clearly cares as much about aesthetic design as he does about the code, and it shows.

What’s cool: The samples are gorgeous, and there’s no extra coding involved to get nifty fly-in effects. You can choose to download code for only the visualization types you want to use to minimize the weight of web pages.

Drawbacks: Since this is not an application but a code library, you must have coding expertise in order to use it. Therefore, this might not be a good fit for users who analyze data but don’t know how to program. Also, the choice of visualization types is somewhat limited. And it appears the code hasn’t been updated for several years.

Skill level: Expert

Runs on: JavaScript-enabled web browsers

Learn more: See demos with source code.

GIS/mapping on the desktop

There’s a wide range of business uses for geographic information systems (GIS), ranging from oil exploration to choosing sites for new retail stores. Or, as The Miami Herald did for its Pulitzer Prize-winning coverage of Hurricane Andrew, you can compare maximum wind speeds with damage reports and building information (and perhaps discover, for example, that the worst damage didn’t happen in the areas suffering the heaviest winds, but in areas with a lot of new, shoddy construction).

 Quantum GIS (QGIS) 

What it does: This is full-fledged GIS software, designed for creating maps that offer sophisticated, detailed, data-based analysis of a geographic regions.

The best-known desktop GIS software is probably Esri’s ArcGIS, a robust, well-supported application that costs quite a bit of money. The open-source QGIS is an alternative.

As OpenOffice is to Microsoft Office, QGIS is to ArcGIS. ArcGIS enthusiasts argue that Esri’s offering is a couple of iterations ahead of open-source alternatives, has a better-developed interface, enjoys commercial support and is better suited for print output. But QGIS users say the open-source alternative is an excellent program that does a great deal of useful GIS work — and there’s now a company called Boundless that aims to offer (paid) enterprise support.

What’s cool: QGIS has an enormous amount of GIS functionality, including the ability to create maps, overlay various types of data, do spatial analysis, publish to the web and more. It can also be enhanced with plug-ins that add support for numerous undertakings, including geocoding, managing underlying table data, exporting to MySQL and generating HTML image maps.

Drawbacks: As with any sophisticated GIS application, learning to use this software entails a serious commitment of time and training. Even in hour-long hands-on sessions with first ArcGIS and then QGIS, I noticed things that were easier to do in the commercial option, such as some calculated fields.

Runs on: Linux, Unix, macOS X, Windows. (This is one case where installation is more complicated on OS X, since it requires manual installation of several dependencies. There’s a one-click installer for Windows.)

Skill level: Intermediate to expert

Learn more: Timothy Barmann of The Providence Journal posted two very useful tutorials for the CAR conference that are still available: Introduction to QGIS and The Latest in Mapping With JavaScript and jQuery. Another resource to help you get started: QGIS Tutorial Labs, from Richard E. Plant, professor emeritus at the University of California, Davis.

Note: If you’re interested in GIS and want to consider other free software options, download this PDF listing of Open Source/Non-Commercial GIS Products. And if you’re looking for a free open-source desktop GIS program that might be fairly easy to use, Jacob Fenton, director of computer-assisted reporting at American University’s Investigative Reporting Workshop, recommends taking a look at the System for Automated Geoscientific Analyses (SAGA) site. Finally, if analyzing geographic data in a conventional database sounds interesting, PostGIS “spatially enables” the PostgreSQL relational database.

Web-based GIS/mapping

Most of us are familiar with mapping tools from major companies such as Google (which has a number of third-party front ends, such as Map A List, an add-on that adds info to a Google Map from a spreadsheet). There’s also Bing Maps with an API. But there are other options from smaller organizations or lone open-source enthusiasts that were designed from the ground up to map geographic data as well.

 OpenLayers

What it does: OpenLayers is a JavaScript library for displaying map information. It’s aimed at providing functionality similar to those big companies’ code libraries — but with open-source code. OpenLayers works with OpenStreetMap and other maps.

Other projects build on it to add functionality or ease of use, such as GeoExt, which adds more GIS capabilities. For users who are comfortable hand-coding JavaScript and prefer not to use a commercial platform such as Google or Bing, this can be a compelling option.

Drawbacks: OpenLayers is not as easy to use as, say, Google Maps.

Skill level: Expert

Runs on: Any web browser

Learn more: Try this OpenLayers Quick Start.

 OpenStreetMap

What it does: OpenStreetMap is somewhat like the Wikipedia of the mapping world, with various features such as roads and buildings contributed by users worldwide.

What’s cool: The main attraction of OpenStreetMap is its community nature, which has led to a number of interesting uses. For example, it is compatible with the Ushahidi mobile platform used to crowdsource information after disasters such as earthquakes. (While Ushahidi can use several different providers for the base map layer, including Google and Yahoo, some project creators feel most comfortable sticking with an open-source option.)

Drawbacks: As with any project accepting public input, there can be issues with contributors’ accuracy at times (such as the helicopter landing pad someone once placed in my neighborhood — it’s actually quite a few miles away). Although, to be fair, I’ve encountered more than one business listing on Google Maps that was out of date, too. In addition, the general look and feel of the maps isn’t quite as polished as some commercial alternatives.

Skill level: Advanced beginner to intermediate

Runs on: Any web browser

Learn more: See the Quick Tutorial on the OpenLayers site.

Temporal data analysis

If time is an important component of your data, traditional timeline visualizations may show patterns, but they don’t allow for sophisticated analysis or a great deal of interaction. That’s where this project comes in.

TimeFlow

What it does: This desktop software is for analyzing data points that involve a time component. In a demo I wrote about before its release, creators Fernanda Viégas and Martin Wattenberg — the pair behind IBM’s pioneering Many Eyes project who later left for Google — showed how TimeFlow can generate visual timelines from text files, with entries color- and size-coded for easy pattern spotting. It also allows the information to be sorted and filtered, and it gives some statistical summaries of the data.

What’s cool: TimeFlow makes it easy to interact with data in various ways, such as switching views or filtering by criteria such as date ranges or earthquakes of magnitude 8 or more. The timeline view offers a slider so you can zero in on a time period. While many applications can plot bar graphs, few also offer calendar views. And unlike web-based Google Fusion Tables, TimeFlow is a desktop application that makes it quick and painless to edit individual entries.

Drawbacks: There are no facilities for publishing or sharing results other than taking a screen snapshot, and the code hasn’t been updated in several years.

Skill level: Beginner

Runs on: Desktop systems running Java, including Windows and macOS X

Learn more: Check out Top tips.

Note: If you’re looking to publish visualized timelines, better options include Google Fusion Tables, VIDI or the SIMILE Timeline widget.

Text/word clouds

A lot of dataviz experts don’t think much of word clouds, considering them both unserious and unoriginal. You can think of them as the tiramisu of visualizations — long-ago trendy, now overused. But some still enjoy these graphics that display each word from a text file once, with the size of the words varying depending on how often each one appears in the source.

 IBM Word-Cloud Generator

What it does: Several tools mentioned previously can create word clouds, including Many Eyes and the Google Visualization API, as well as the website Wordle (which is a handy tool for making word clouds from websites instead of text files). But if you’re looking for easy desktop software dedicated to the task, IBM’s free Word-Cloud desktop application fits the bill.

What’s cool: This is a quick and easy way to find frequency of words in text.

Drawbacks: Because it’s trying to ignore words such as “a” and “the,” the basic configuration can miss some important terms. In early tests, it didn’t know the difference between “it” and “IT,” and completely missed “AT&T.”

Skill level: Advanced beginner. This app runs on the command line, so users should have the ability to find file paths and plug them into a sample command.

Runs on: Windows, macOS X and Linux running Java

Learn more: Check the examples that come with the download.

Social and other network analysis

These tools use a pre-Facebook/Twitter definition of “social network analysis” (SNA), referring to the discipline of finding connections between people based on various data sets. Investigative journalists have used such tools to, for example, find links between people who are involved in development projects or who are members of various boards of directors.

An understanding of statistical theories of network node analysis is necessary in order to use this category of software. Since I’ve only had a very basic introduction to that discipline, this is one category of tools I did not test hands-on. But if you’re seeking software to do such analysis, one of these might meet your needs.

 Gephi

What it does: Billed as a Photoshop for data, this open-source beta project is designed for visualizing statistical information, including relationships within networks of up to 50,000 nodes and half a million edges (connections or relationships) as well as network analyses of factors such as “betweenness,” closeness and clustering coefficient.

Runs on: Windows, Linux, Mac OS X running Java 1.6

Learn more: Try this Quick Start tutorial.

 NodeXL

What it does: This Excel plug-in displays network graphs from a given list of connections, helping you analyze and see patterns and relationships in the data.

NodeXL merges the older and current definitions of SNA. It’s “optimized for analyzing online social media — it includes built-in connections to query the APIs of Twitter, Flickr and YouTube, allowing you to draw networks of users and their activity,” according to Peter Aldhous, San Francisco bureau chief for New Scientist magazine.

It also handles email and conventional network analysis files (including data created by the popular — but not free — analysis tool UCINET).

Runs on: Excel on Windows

Learn more: Download this free NodeXL tutorial (PDF) by science journalist Peter Aldhous.

Want even more tools? See our searchable, sortable chart: .