Wizard is an app that makes data analysis easier than ever. No programming, no typing -- just click and explore. No programming, no typing -- just click and explore. Wizard makes statistics accessible to beginners, but beneath the surface lies a full set of tools for doing professional research. Hi all, I'm trying to find the QUICK ANALYSIS tool in my Excel on mac version 15.14. I can't seem to find it. I have the data analysis tool but this in NOT what i'm looking for.
If you are using a Mac and Excel 2004–2016 for Mac or Apple Numbers for daily analytical and statistical purposes, StatPlus:mac LE is exactly what you need to get started! Get a powerful statistical tool for free – now with a set of new essential features - without leaving Excel. Refer to the discussion at What happened to the Data Analysis Toolpak or Solver in Excel for Mac 2011? – answers.microsoft.com. Quote: Quote: The Data Analysis Toolpak was removed in Office for Mac 2008. Wizard Pro is a multivariate statistics program for data analysis and exploration. The software keeps all work (tables, results, predictions) in a single document with an iTunes-like navigator and provides interactive interfaces for querying data. The Real Statistics Resource Pack contains a variety of supplemental functions and data analysis tools not provided by Excel.These complement the standard Excel capabilities and make it easier for you to perform the statistical analyses described in the rest of this website.
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
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).
Free Data Analysis Tool
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
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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.
![Data Data](https://www.rocketdownload.com/pictures/large/navicat_data_modeler__mac_os_x__-_database_design_tool_-_creating_data_models_business_database_management-822062.png)
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While the paradigm of 'more data is better' might look good from the executive suite, there's a challenge that many front-line business managers are encountering once they dig into this trove of new information: how to turn all of those numbers into something useful. Data isn't worth much if you can't use it to affect your business decisions and, while spreadsheets have long served as an acceptable, if mediocre, way for rank-and-file business users to present data, the new data deluge is pushing this tool beyond its practical limits. What's needed is a way for everyday business people to build not only pleasing but informative data visualizations that they can present to their leadership and co-workers quickly and easily, or showcase on their company websites, which are supported by web hosting services that can reliably store large data visualization files on their servers. While heavy-duty data analysis can still be the purview of hardcore business intelligence (BI) analysts, the ability to visualize large gobs of data in new ways needs to be democratized. And for small to midsize businesses (SMBs), the road to this new visualization vernacular needs to start with some free tools so they can touch, learn, and understand this new discipline before they have to invest in it.
Before we go any further, let's understand what we're talking about here. The term 'data visualization' doesn't necessarily refer to an arcane melding of SQL and PC graphics modeling. It's really just a general term that applies to any graphic that explains the significance of a new insight or data set visually rather than simply numerically. Technically, that simple pie chart you can one-click using Microsoft Excel is a data visualization. But, as technology has suddenly begun evolving in leaps and bounds over the traditional databases and spreadsheets to which we're accustomed, new kinds of data visualizations have become possible using a host of new tools and tech. And that's created a mystique around them that's kept many users from trying them, even though the basic tools to do so are already in their hands.
Even if you don't have access to one of the new breed of self-service BI tools that have fairly advanced data visualization baked in, you can still experiment with the concept because there are a host of third-party visualization tools available to anyone with a web browser. I've listed 10 of them below.
1. Tableau Public. This is right at the top because it's essentially the same platform as our self-service BI tool Editors' Choice winner Tableau Desktop. The company chose not to make its free version feature-poor. Instead, this is the full version of Tableau that's available for free download, with only one caveat: Everything you create with it is public, which means you'll automatically be making it available on the web via Tableau's visualization gallery.
2. Tableau Gallery. Tableau's gallery is cool enough to warrant a mention all its own because you don't need to download the tool nor use it to benefit from the gallery. Every visualization here can be downloaded into documents and email, or embedded into webpages with code snippets provided by Tableau. Other folks have done tremendous work on some truly impressive data visualizations and Tableau has curated that content and made it available for download. This is a great resource, not only for business people but also for researchers, students, and journalists looking for ways not just to flesh out and beautify their content but to keep it current, too.
Tableau Public
3. Microsoft Power BI. This is the last shameless plug for one of our reviews but I have to include it because, just like Tableau, Microsoft Power BI can be downloaded for free. And also just like Tableau, Microsoft has a visualization gallery that can be accessed by both Power BI users and folks simply looking for freely available visualizations.
4. Google Data Studio. Part of the Google Marketing Platform, Google Data Studio lets users build multiple views of their data as well as dashboards rather than one-time, publication-ready visualizations. While it follows the Google tradition of requiring somewhat of a learning curve, it's nevertheless not that difficult to use. It's also well integrated with Google Analytics, which can make for quite a powerful pairing—especially since both tools are available in free-to-play versions.
5. Openheatmap. This one purports to transform your spreadsheet, presumably encumbered with some kind of geographical data, into a functioning heat map with just one click. It works with Google Spreadsheets so you'll have to import your Microsoft Excel spreadsheet there if you want to use Openheatmap. But that's a relatively trivial requirement considering the possible results.
Openheatmap
![Free Data Analysis Tool For Mac Free Data Analysis Tool For Mac](https://tr1.cbsistatic.com/hub/i/2010/01/14/a3bcf8ed-c3b1-11e2-bc00-02911874f8c8/a_main.png)
6. Leaflet. This is definitely not a tool for complete newbies because it's just a JavaScript library that you'll need to incorporate into your data visualization framework on your own. But it's well-known because it's super lightweight (only 33 KB), and it's aces for building not just maps but interactive mapping visuals aimed specifically for mobile devices. That can be a tall order even for some of the commercial BI tools we've reviewed. So, if you're not scared of the command line or making an application programming interface (API) call, then check it out.
7. Datawrapper. Backed by Berlin, Germany-based company Datawrapper GmbH, Datawrapper is nevertheless multinational, having been built by a team of designers, developers, and journalists from a number of European countries as well as the United States. The tool is specifically built for journalists looking to create fast, easily digestible visualizations to accompany their articles; however, it's useful for anyone requiring similiar data views. While there is a paid version that supports the company, there's also a free plan that tops out at 10,000 charts, which should keep many SMB operators happy for quite some time. The tool is entirely web-based, and the website includes not only access mechanics but also an Academy area in which you can take online learning classes on how to use Datawrapper. There's a Gallery area, too, called the River, in which users can upload data and their visualizations for sharing.
Free Online Data Analysis Tool
Datawrapper
8. Chartbuilder. This is a well-known chart-creation tool that was made publicly available by financial news website Quartz in 2013. Quartz had developed the tool in-house so its journalists could quickly render numerical data visually to make their stories stand out. Ironically, Chartbuilder isn't very pretty itself and also is not the easiest tool for rank beginners to use. You'll need to understand how to download the tool and activate a Python script to get it running.
But after that, it's simply a matter of cutting and pasting data into the tool (also not pretty but very easy), and then generating a graphic that you can tweak via the tool or via style sheets. The only downside to the tool (aside from a little upfront complexity) is that it doesn't generate interactive visualizations like most of the other tools on this list do. Chartbuilder creates only static charts, though these are very polished, as befits something intended to go from numbers to slick published content in just a few steps.
Excel Data Analysis Tool
9. Information is Beautiful. This is simply a growing library of striking, prebuilt visualizations that other people have created by using a variety of tools. The gallery is fun and everything is downloadable, though you'll need to pay attention to the licensing agreements. These agreements give free access to individuals (especially students and academics) but, if you're looking to use these visualizations for commercial work, then you'll need to fork over some dough. Exactly how much depends on who you are and on an email exchange with the website's owner. Just to warn you: We had asked to pay for a visualization for this story, and two weeks after the request, we still hadn't heard back. So, if fast turnaround is part of your agenda, then look elsewhere.
10. Open Refine. There's an oft-overlooked underpinning to a successful data visualization: data transformation. That's especially true today when big data is trying to provide insights across different data sources, maybe a spreadsheet, maybe a long transaction log gleaned from a machine learning (ML) algorithm.
Transforming data generally refers to the painful (for normal people) process of taking a whole bunch of disparate numbers and turning them into a sleek set of relatable data. That means cleaning data (formatting and error checking), transforming it (changing from one format such as native Microsoft Excel to another, such as XML), and then making it available to external services such as webpages and those BI tools you're using. If you're thinking this can be a painstaking, eye-watering, brain-bending task, then you'd be right…unless you use a data transformation tool such as Open Refine. This tool began life under Google's flag but was rebranded to stand on its own. It's still both free and easy to use so, if you're banging your head against a mountain of mismatched data, then check it out.