A terrifying number of people have taken me up on the javascript business, and powered on through with material that we haven’t covered in class. OK, that is awesome, but if that’s the path we’ve gone down, I should almost certainly be taking questions on that theme…

For example, if you followed the link through to the google spreadsheet map maker from the last post in this series, then you might have found that it made you some horrible javascript that it is NOT obvious how to do nice stuff with, and how to attach javascript widgets to. If anyone wants to follow through a step-by-step rebuild of that into some nicer javascript, then we can do that.

We can also look at other things – Google Apps for Your Domain (or What Does Google Apps for Your Domain Actually Do?)… BBpress installation as an example alternate app install. It’s up to you.

Project Scheduling Tools for Google Spreadsheets

http://www.viewpath.com/

Now, last time when we left off, the site was in what you’d call a colossal mess. Trashed wordpress install, and still no interesting visualisation. So, how to improve things?

We’ll start by doing what I suggested last time – mapping off with a less ambitious dataset, based on LGAs (Local Government Areas) instead of suburbs. Here it is:

I even made a little chart. And look, since I am no longer quite as bored of CDATA as I was last week, I made another other spreadsheet based on percentage of people doing volunteer labour, by LGA.

Now, I’m keen to graph these data sets against each other. And I can, using google spreadsheets “Chart” function.

But first I need to tidy up those names. What’s with the ABS sticking “(C)” and “(A)” all over the place? FFS. Right, a new spreadsheet formula to trim off that crap. This one is a bit ugly:

But it works.

Now… about that chart… Well, we could do one in google spreadsheets, but that’s basically like doing it in excel and about as much fun. So let’s not.

Instead, let’s upload it to ManyEyes. Have you seen this thing? Fun, collaborative mashup, and you do it by copying and pasting. There are a couple of tricks. Like I can’t have dollar signs in the spreadsheet values, but I have to put the dollar sign in the column header. Then I have to select just the rows I want. Here a screenshot fo the spreadsheet after I’ve done that:

Note that I don’t know that I have to do that just because I’m some kind of web genius, in case you were wondering. In fact, I just read those instructions off the manyeyes upload page: (click through to see it yourself – you’ll have to sign on, mind)

Wham. There it is. I did the same for the volunteers doohickey. And then I made a merged version of those two and uploaded it, because it’s more interesting that way. (“Interest” is also why I spelled it “voolunteerism, ok?)

Now this ain’t a statistics class, but, er, there you go, a possibly informative data visualisation. Well, it might be if you click through to a less microscopic version. So it turns out that rich local government areas tend to volunteer an amount close to average, and poor ones volunteer over a wider range. Hm. Damn those rich people, and their… lack of variability? That could have been more interesting. Messing around with statistics until a more fascinating one pops out is left as an exercise, however. Let’s power on through and work out what we can do with the tools at hand.

We’re gonna map this thing.

Now, first I try that yahoo pipes idea the obvious way, and repeat last time – i just send the output of my spreadsheet into the yahoo pipe, and hope the location extractor will do something useful:

Look at that. Dang, no location information in the output. Lame! I might have to read the manual.

Location Extractor can glean location data from some URLs, such as those from maps.yahoo.com, maps.google.com, and mapquest.com.

A wide range of location mark-up is recognized, including GML (Geography Markup Language), Abbreviated GML, W3C Basic Geo, Abbreviated W3C Basic Geo, Simple GeoRSS, Yahoo! Local format, and KML LookAt and Point tags.

Right. Well, clearly, our feed doesn’t look like yahoo local or whatever the crap that is. But I reckon getting our data format in google maps link format should be fine, because it’s easy. I know from playing around, that you can get google maps to link to, say, Armidale, by using a URL like this:

http://maps.google.com/?q=Armidale, New South Wales

I guess that might be documented somewhere, but I just figured it out by typing things into the URL bar until it worked.

Anyway, we could use Google Spreadsheets to turn all those “Armidale”-type cells into “http://maps.google.com/?q=Armidale, New South Wales” type cells, but it’s late in the day, so I’ll show you a little hack to do it without using Yahoo Pipes to save more fiddling around:

Woo! It worked! What does it do? Well, I’m not going into too much detail with this one, since, as I said, you can do it all in google spreadsheets… but the regex tool is a handy thingy for doing translation of strings of letters into other strings of letters (in this case, into strings of letters with “New South Wales” stuck on the end, and the URL builder just shoves stuff into a URL – in this case, the google maps one. Feel free to play around with it. The only trick with this one was I noticed that Yahoo Pipes was occasionally breaking when I tried to use “Local Government Area” as a field name in the CSV import thingy, so I renamed it to “LGA” in the CSV import widget, and then it worked OK. I guess it doesn’t like spaces in the name. Anyway, watch out for that.

Long story short: It works.

But lets get that stuff off the pipes page, by getting the KML export URL:

Now we’ve copied that url, we paste it in to google spreadsheets, right there in the search box.

And the result?

Win. we have a google map of the yahoo pipe of the google spreadsheet of the ABS data.

Not that it’s perfect. I meant, as far as visualisations go, this could be way more interesting – this is more a map of where local governments are than it is of the stats that started the whole thing off. We could pup pop-up speech bubble with the ABS stats into the yahoo pipe output if we wanted, which might be fun. Or we could try to import THIS data set into wordpress. Or maybe we could try to map it differently. If you’re not afraid to get your feet wet in javascript, the handy javascript mapping library Openlayers javascript examples page includes on of resizable map markers. So we could build a map that had, maybe, big markers for really rich LGAs, and really small ones for poor ones. Or colourise them. Or… Lots of options. However, there are a few steps along that path that were a little hairy, so I’m going to give you an alternative geocoding method instead – since more of you seem to want to map specific locations rather than census statistics, it might pay to stick to close to what the class needs.

Basically, it was too much work to get it to geocode properly (it might have been a bit more fun if we controlled the source of data, and say, had a wordpress blog outputting GeoRSS or something).

Fortunately, Pamela Fox has blogged a nice way to geocode your spreadsheets. (She also has some awesome tips for designing maps.) Let’s follow her instructions. First, we add “New South Wales” to the end of all our LGA names, so that google can find ‘em better.

Nice. The rest is all following Pamela’s instructions.

You whack her gadget in there:

set it up:

Then you press the go button (small correction – up above I showed myself geocoding 150 records at once, but it only for 99. If you find it stops half-way through, that’s why. But it’s easy enough to restart.)

And then it goes. Not completely smoothly – it Turn out google has no idea where “Greater Hume Shire” is. And nor do I. I could have fixed that manually (possibly using the plain old paper street directory), but decided to be lazy. I copy and paste and then:

From the same blog post, Pamela also gives links to a handy spreadsheet mapping tool or two. There are, as always, too many alternatives. You might want to reverse geocode, or try this other hand bulk geocoder, or the GeoCommons open source geographic database, and there are semi-commerical services to automate part of it for you, such as umapper. Bah!

The real idea that I’m trying to get across here is that none of this is magical secret powers (well, except regexs), but there is a lot of muddling through. The list of tools out there is really large, and they change. No-one is a ninja at most of them, but be being happy to just try things and see if they work you can get a long way with a lot of them. There are bugs and annoyances. But then you usually get something at the end of the day.

Here are some links for lists of other directions to explore with mashups. I’ve mentioned some before, and some are new.

1. HackU
2. ToyChest
3. Simon Willison’s roundup for the Guardian
4. Freebase appears to have a general purpose mashup engine too.
5. YQL is hot right now, if you want to get just a shade geekier. It supports a massive number of the services we are looking at here and more I haven’t heard of, and if those aren’t enough, you can turn anything, almost, into a YQL data source with a little bit of code. Very handy.
6. google has a Javascript playground! (although I reckon the Openlayers examples page, mentioned above, is cooler)

Now, that’s enough writing from me for now. I’m may have time to do another walk-through of things for this semester… If anyone wants to suggest the topic in the comments, fire away.

by vingt deux, licensed under CC BY-NC-ND 2.0

I’ve had a number of questions about how to get some different types of data mashed up, and for some worked examples. Good! We didn’t have as much time as I was hoping to cover that, so I’ll whack it in this blog post so that those of you going down a mashup path have  some better examples. This isn’t a comprehensive overview, since we’ve already had one of those, but simple and detailed worked examples of what to do. I’ll show some of the false starts that I might make in a mashup project, as well as the successes.

Before we get started, be sure you’ve read ProgrammableWeb’s mashup guide and our own previous class notes on mashups. They give more “why” that I will give here. This here is all about “how”.

First decision – am I doing an Australian mashup, or an international one? Australia’s a bit of a backwater in data access, and doesn’t have nearly as many easy datasets, but it’s probably a lot more relevant for a lot of us. International mashups, for example, have lots more handy mapping tools (e.g. google’s charts or mapsgeek) Let’s give Australia a go anyway. I’ll start with some Australian census data.

Say that I want to mashup, er, the average income of individuals in a suburb versus… geez, whatever, i can get away with that looks interesting. Remember, this is an experiment… There’s a few data types listed at at the Australian Bureau of Statistics site. The ABS data descriptions are unspeakably confusing and geeky, so it takes me a bit of poking around to realise that the “CDATA” seems to do what i want. I have to register to use it, but it’s free. Sweet. I can choose a ridiculous number of data types, and aggregate them, however i want, including by suburb, as long as I’m prepared to tolerate their opaque jargon:

And best of all, it lets me export to a CSV file!

CDATA also has some other features: graphs and maps.

But graphs don’t work for spreadsheets this big, and the maps are amazingly ugly and don’t seem to export too well. Feel free to use them in your own mashups, mind… but this is not what I’m going for in my mashup.

So let’s get out data out of there and into something more useful. You will recall that I can upload CSV  to a google spreadsheet, and google spreadsheets are wicked easy to mashup.So, I’ll do that. (here it is)

Now, we can start mapping average income. First obstacle: There is no spreadsheet telling me average income, just how many people are in each income bracket, what you call a histogram. Now we have two options: We could change plans and choose a different data set, or if we are feeling a bit more confident we can process this data set to give us what we need.  That won’t be too hard in this case (although it will mean remembering high school maths) so I’m going to run with it.

Fortunately, the internet can help here, even if we’ve forgotten our high school mathematics – we can approximate the mean income from a histogram using instructions online. And we are already using a spreadsheet, so this part is kinda easy. It won’t be completely accurate, but hey, it will be a good start, and if the sites gets enough web traffic, maybe we can get some funding to get more accurate data. So we make up a “central” income for each income category:

So, now I modify the spreadsheet to include a mean-income estimation according to those instructions.

then this is the formula to calculate the mean from the histogram

Next step, I’ve noticed that there is way to0 much crap in the spreadsheet. I can probably get rid of most of it. let’s delete the columns that are about income by sex – we just want to know about average income over all (unless you are doing a map of sex-based income gaps by suburb, which would be pretty interesting – I’ll leave that one as an exercise.)

Now, at this point, I want to create some nice interactive coloured map of income levels, a choropleth. But, as I intimated above, that’s a bit tricky in Australia. I know from helping with the AboutNSW ones that it was annoying to get them working, and we had to roll our own tools. Rolling your own tools isn’t impossible – you can get the suburb outlines from the ABS and follow google’s handy instructions for banging them on a map, but that’s going to involve a fair bit of software wrangling… so let’s see what else we can do that might be a bit simpler before we resort to that.

Well, how about importing the spreadsheet into wordpress?

(What? Well it turns out that google spreadsheets can export RSS and wordpress can import RSS, and vice versa. Remember me banging in week 3 about the importance of standards like RSS to make things talk to each other?)

Great, so now I import my list of suburbs into my blog… Bam! It works!

Well, it kind of works. There are a few problems. Firstly, the import process takes so long that eventually dreamhost gives up the ghost, and my import script stops after 1294 suburbs have been imported. I could work around this by only exporting part of the spreadsheet at a time… but then let’s look at the next problem THEN there’s the problem that a lot of these imported articles are frankly, ugly. I should possibly have put more care into which columns of the spreadsheet I exported.

There’s another problem too, which I’ve glossed over – it turns out that when I copy and past the RSS URL into my browser, both firefox and safari refuse to download the RSS properly for me to upload into wordpress. I end up having to install an extension into firefox called DownThemAll just to get the RSS file to download without getting all mangled. watch out for that!

On the plus side, I now have a blog with a reasonable chunk of all the suburbs in New South Wales in it, and each of those even lists the approximate average personal income in the suburb. I could go places with that. Maybe I could have each suburb post show a little map of the suburb, using jQuery. Or maybe I could put extra suburb info up there in the blog.

Did you know the suburb of “Airds” has an average weekly income of approximately $370 dollars, and that its name means… etc

But for now, it’s a mess. I’m going to nuke my wordpress blog and start again, rather than deleting 1295 entries by hand.

And I’m going to do it a bit differently… I think I’m being overambitious. You know what? This is a one-semester project.

Why am i trying to deal with all two-and-a-half-thousand suburbs in New South Wales? Forget it. I’m going to run with a smaller data set. I’m going to go back to the ABS, and I’m going to grab the personal income statistics again, but this time I’m going to grab them, not per suburb, but per Local Government Area. There’s only a few hundred of those, which might fit into wordpress a bit better, and might be easier to manually edit if there are a few mistakes. Also, it looks like LGA is a more common thing to classify data by than suburb (e.g. the NSW crimes map, and stap isi’s fantastic council contact info). And I’m going to use Yahoo pipes to make my job easier, and present the result using jQuery to keep it a bit simpler.

At least, that’s the plan. However, banging out this detailed tutorial with screen shots and all that it taking an amazingly long time (16 hours and counting!) and I know some of you are wanting to get your hands on this info ASAP. So I’ll continue in a blog post part 2 over the weekend, and put this blog post out there, eh?

For now, here are some interesting follow up readings:

1. the mashup australia contest is open! If your mashup is good enough, you might want to enter it and win $$
2. mashupaustralia has also graced us with a handy list of data sources that you might want to use
3. There is a nice blog post here about how to make your life mashing stuff up a lot easier which also walks through the same technologies I’m covering here.

Introduction

I began to seriously contemplate the idea of going freelance back in May, and realised I wasn’t very prepared. For one thing, I didn’t really know how much money I spent each month or what I spent it on. Nor did I have a good handle on how I spent my time. I wanted to see how I was behaving financially, so as to know how much I’d need to earn as a freelancer to maintain my lifestyle. I also wanted to know what made up this lifestyle to see how much time I’d have available for doing this freelance thing. I did go freelance at the end of June and carried on measuring things for a while so I’d have enough data for a meaningful result.

On the 6th June, I started keeping a record of my spending; on the 1st July, I began to keep a diary of what I was doing all day. At the end of August, I stopped measuring. This means I have four months of records of how I’ve spent money and three of how I’ve spent time.

Having this information is very useful, I think, so I’ve published all the data and analysis spreadsheets for you to play with. If you wanted to do something similar, they might be helpful. (The data are all published as Google Spreadsheets – see the links at the bottom of this post.)

Of course, it would be remiss of me, as a one-time scientist, if I were to look at data and deduce hypotheses after the fact. So, without prejudicing my judgement too much by figuring out a collection of perhaps-useful things in advance, I’ve written down some questions that I want answering and hypotheses to test for each.

Money

1. How much money do I spend in a month?
   • Hypothesis: I think I spend £2400 a month
2. What am I spending most of my money on?
   • I think the majority is being spent on rent, dining and boozing
3. How much do I spend on booze?
   • I think I spend £400 a month on booze

Time

1. How much time do I spend sleeping?
   • I think I spend 1/3 of my time sleeping
2. How much time do I have free in a week after I’ve done all the habitual activities?
   • I estimated I have 31 hours a week to use (estimate recorded in Habits)
3. What is the most expensive activity per time spent on it?
   • I think it is boozing (although dining will be a close second)

This post is going to cover the questions about spending money.

Constraints

1. The Hawthorne effect – will I change my behaviour by measuring it?
2. Not splitting money and time spending when on holiday – it just goes down as ‘holiday’

Measuring money

Answering the questions

How much money do I spend in a month?

Hypothesis: I think I spend £2400 a month
The data shows: Between May and August 2009, I spent an average of £2492.65 each month

What am I spending most of my money on?

Hypothesis: I think the majority is being spent on rent, dining and boozing
The data shows: rent 21.7%, holiday 20.6%, dining 10%, boozing 7.7%

How much do I spend on booze?

Hypothesis: I think I spend £100 a week or £400 a month on booze
The data shows: Between May and August 2009, I spent an average of £191.20 on booze each month

The data illuminates

The images below are generated from the summary spreadsheet, which contains live graphs you can play with – clicking on pie segments, for example, reveals the percentage and value attached to each.

Methods

Collecting data – iPod Touch & Notes

Online banking is a boon to the would-be data collector, as you can generally download a transaction history in csv format. Unfortunately, plenty of entries for “cash” creates a big unknown in the results. I decided to keep a record of when I spent cash during the day, what I spent it on and how much I spent. I didn’t start monitoring expenditure until the 6th May, so approximately £140 cash is unaccounted for over the four month period (I haven’t been worried sufficiently to alter any calculations to take this into account, as my monthly spending has a standard deviation of more than this).

I’d done something like this before, when I was having a crisis about where all my money was going shortly after I started working for BT in 2005. Back then, I used a pencil and notepad, and the prospect of copying all the records into a computer was so daunting that I never did. This time, I had the benefit of an iPod Touch (thanks Dad) and its “Notes” application. You can mail yourself a note, which I did every month or so.

Dealing with the data after it fell into my inbox was a matter of some search-and-replace in a text editor, to make the fields tab-separated so that they could be copy-and-pasted into Google Spreadsheets.

Analysing data – Google Spreadsheet

The first thing to do was enhance the data by tagging each expense with a chunky category like “rent” or “boozing”.

Using Google Spreadsheets to analyse an amount of information is a task with a fairly steep learning curve, since the examples for using the more complicated functions are not always that enlightening (I imagine if you are already an Excel functions master, it won’t be so hard). Nevertheless, the Google Docs forum is replete with the writings of two characters in particular – Otávio Alves Ribeiro, the Spreadsheet Ninja from Brazil, and “ahab“, the mysterious Google Docs Guru.

The performance of a Google Spreadsheet is generally quite good, although there is often slowdown in processing. I found, mainly through trial and error, that a good way to understand what is going on and get decent performance out of Google Spreadsheets is to separate worksheets between data collection and analysis; then perform any inter-spreadsheet aggregation by importing the plain data from each spreadsheet into a single worksheet and make all your calculations based on that.

Further work

I ended up with just over 20 different tags; if I were to do this again, I would split the ‘holiday’ tag into its constituent parts and I would split “dining” into “breakfast”, “lunch” and “dinner”.

It will be interesting to compare my monthly spend (which is the simplest data to measure) to the relatively steady pattern I have discovered over these four months to see how much effect measuring my spending had on dampening it; indeed, I could measure the historical monthly spends and perhaps see an effect that way.

Data

All the data for this experiment is published on various Google Spreadsheets. See the links below.

• Spending summary May-August 2009
• Spending May 2009
• Spending June 2009
• Spending July 2009
• Spending August 2009

Rather than asking people to edit a whole spreadsheet, you can make it easier by creating a form for them to add particular information by answering questions.

To do this, open your spreadsheet in Google Docs and click on Form > Create a form.

A new window will appear containing a form that you can edit, with some information automatically added.

If you roll over any of the questions you will see buttons for you to edit, duplicate or delete it. You can also edit the form title and description and there are various extra options across the top.

Along the bottom of the form you will see a web address (URL) for the form that you can send to people or copy and paste into an investigation update. When a person clicks on this they will be able to fill in the form and the information will be added to your spreadsheet.

Once you’ve finished, just close the window. 

If you need the address of your form again open your spreadsheet and go to Form > Go to live form… this will open the form – copy the URL from the web address bar as you would with any other webpage.

If you want to edit the form again just open your spreadsheet, click on Form > Edit form…

Following on from the previous post on creating and publishing a spreadsheet online, here’s how you allow others to add to that, and how you track what happens:

To allow others to edit your spreadsheet, open it and click on Share (in the top right area) then click See who has access…

This last option is best if you want to allow others to add information to your spreadsheet

But what if someone deletes all my data? Setting up alerts

On the same window you can set up the spreadsheet so you are alerted whenever anyone makes changes.

Click on My notification settings.

You will be presented with a number of options for when you are notified of any changes

If a change is made that you don’t like (e.g. someone deletes all data) go to File > Revision history

The spreadsheet will now have the latest change highlighted and above the top row of cells will be a number of new buttons – click on Older to see how the spreadsheet looked before the last change that was made.

Then click Revert to this one to change the spreadsheet back to how it looked then (You will be asked to confirm – click OK).

If this isn’t the version you want to revert to you can keep clicking Older to go back in the spreadsheet’s history. The Newer button will take you in the other direction, to more recent versions.

Making it really easy – allowing updates by form

There’s a better way to allow users to add data to your spreadsheet – creating a form. I explain how to do this here.

For some investigations it will be useful to create a public spreadsheet of information. There are 3 main reasons why:

• It’s a better way of displaying data than using a sentence of text
• It means people can easily see where the gaps are – and fill them in
• It also allows people to do interesting things with the data, like visualise it, or mix it up (‘mashup’) with information from elsewhere, e.g. maps

One of the most popular tools for creating public spreadsheets of data is Google Spreadsheets, part of Google Docs.

Creating or uploading a spreadsheet

Creating a spreadsheet in Google Docs is pretty much the same as in any other spreadsheet software. Click on New > Spreadsheet to start creating one. Name it by clicking where it says ‘Unsaved spreadsheet‘ and add your data.

You can also upload a spreadsheet from your computer into Google Docs by going to File > Import.

Publishing your spreadsheet online

To publish the spreadsheet click on ‘Share‘ (in the top right area) and select Publish as a web page.

A new window will appear where you can select whether to publish an individual sheet or the whole spreadsheet (if it has more than one). Change this if you want to, then click Start publishing.

Publishing a Google Docs spreadsheet

The bottom half of that window will now become active and you should now have a web address (URL) where the spreadsheet is published. Copy that web address and paste it into a new window to see how the spreadsheet looks in its published form.

You can also paste that address anywhere you want to show people the spreadsheet – including in investigation updates.

Allowing others to edit your spreadsheet – and tracking what is changed

There’s a lot more you can do with a Google Docs spreadsheet when you allow others to collaborate on it. To find out more read: how to allow others to edit your spreadsheet – and how to track the changes they make.

If you have any questions or comments please post them and I’ll try to answer.

Lunch Time!

If there are two things software engineers like to discuss and optimize the most during their work day, they are the commute and where to go for lunch. The latter is the topic of discussion today.

A few weeks ago I decided to put a makeshift lunch-chart on my whiteboard. I listed all the lunch places along one axis and all the people I generally go to lunch with on the other and had everyone rate their choices from 0 to 10. Later on I back-ported a meaning onto this 0-10 scale: multiply by ten to get the percentage chance I could get you to go to this place if I proposed we go there.

Eventually everyone got annoyed that we couldn’t fiddle with the numbers to generate cool statistics. One person even proposed doing an “affinity” chart to see who generally likes the same places as others. All this was too tough to do on a whiteboard, so I ported the numbers over to a Google Spreadsheet (in my spare time, of course). The image above is a slightly dated version of that Spreadsheet.

I think Google Spreadsheet is really awesome and I hope that maybe if you live or work in Silver Spring, this chart will be somewhat beneficial to you, too. And if not, maybe you can make your own chart for the places near you!

View the whole spreadsheet here!

*Mixed media: You know how I love mixed media. Unless you accidentally came here through some who-knows-how-relevant search terms. Check out these book covers made for films.

*Coinage: Peakniks = people who believe the best has come and gone. Peak oil, peak carbon, peak debt, peak beer…

*Toys: Your child needs a BlackBerry just as badly as you do. [rob t]

*Topography: Look over this hot dog map of West Virginia. I have never been to West Virginia. And I hate relish. HATE IT.

*Ink: Tattoos of food. FOOD. DELICIOUS, DELICIOUS FOOD. [murketing]

*Twitter: Waxy points out this Google spreadsheet of musicians on Twitter. (Most of them are very bad. I’m just saying.) Wait. Willie Nelson?

*Directory: New Yorker music writer Sasha Frere-Jones offers a directory of people on Twitter. I was unable to identify myself among them. Sad.

*Language: GOOD magazine points to the 100 most beautiful words in the English language. I was going to be pissed if mellifluous wasn’t on there. But then it was.

*Music: This generator allows you to create music from any text file. Is this utter fucking bullshit?

This weekend, I casually collaborated with a fellow twitterer while figuring out how to use a very cool feature in google docs. It is explained on this website:
http://mespandt.blogspot.com/2008/11/googlespreadsheet-demo-using-jing-to.html

So my friend Maureen and I tried out all sorts of different words to have google spreadsheets expand upon. You really have to play with it yourself. If you put in Sarah Palin and then drag down (hold down control key for PC, option for Mac) you get some fairly amusing results. You can put in famous actors, kinds of trees, etc.

Here is another link for the rest of the functionality.
http://www.googletutor.com/2007/01/09/google-spreadsheets-trick-google-lookup/

And one more: http://documents.google.com/support/bin/answer.py?hl=en&answer=54199

Have fun!

We have been using Microsoft Office over 15 years, some of us even longer. Very few of us question why, even though it slows down our computers and the majority of us only use about 10 per cent of the available features, even though we pay for them all. Maybe it’s time we take a look at what else is out there.

The most common reason people stick with Microsoft Office is because we’re familiar with it. Let’s face it, we don’t like change, even if that change may be better and more efficient. Another reason is that people are comfortable with it, and of course because everyone else seems to use it.

The best competitor right now is ‘Open Office’. It’s called that because it is developed by a very large community of people who donate their time to the worthwhile cause. It’s completely compatible with Microsoft Office, and it’s free. You can get it from http://www.openoffice.org. Their goal right now is simply to get people to use it.

Consumer perspective seems to be encouraging, albeit sceptical. People don’t want to take the time to learn something new, but considering the lack of a price tag and compatibility with Microsoft Office, consumers seem more than willing to take a look.

“I’d definitely check it out, I would,” says Steph Norris, a first-year nursing student at the college, but says

sticking with a new product would “depend on how much I like it. Free stuff would be nice.”

With students, learning new programs in addition to their course load isn’t appealing, so alternative programs need to be easy to use and not require much of a learning curve. They don’t need every feature known to man built-in, they just want something that works.

“You have to go with something that you know, you don’t have time during the school year to learn something new [in addition to everything else],” says Norris.

With the internet gaining strength over the past decade, many companies, such as Google, are taking their applications online instead of selling their boxed software in stores. Google has ‘Docs’ and ‘Google Spreadsheets’. Another company is Zoho Office, which is also free.

Even with the convenience, some are not yet comfortable with storing their documents online, and consumers don’t fully trust the internet, so companies need to do more to gain customer trust.

“I don’t know if I’d trust the online programs,” says Mike Campon, an Environment Sciences student at the college, “I don’t believe they are as secure as they say they are.”

As for whether online applications are beginning to makes a dent in boxed software sales, the answer seems to be no.

“[There isn’t] an awareness and people are set in their ways, and it’s brand loyalty,” says Julian Clement, an Entertainment Associate at the Future Shop in Medicine Hat, “[there is a]lack of information out there about online software.”

Unless you’re “in-the-know”, customers only seem to be aware of the software on the shelves and don’t seem to trust anything else. With the vast amount of features, Microsoft Office seems more targeted toward business, while the alternatives are aimed at home users.

“If people were more aware [of the alternatives], they might definitely second guess that decision [to buy Microsoft Office],” says Candace Knelsen, the department manager for Electronics at the Lethbridge south Wal-Mart location, though she says that “sales seem to be as strong as ever.”

One solution to bloated software that includes features most people never use is called ‘modular software’. Microsoft is a perfect example, with many experts predicting Windows 7 will be sold as a basic operating system, and customers can buy or subscribe to add-ons and other features.

“I want the computer to come with the basics with the option to expand, but I want them to make it easy to find and download the add-ons,” says Paul Sywanyk, a third-year Conservation Enforcement student.

Sywanyk brings up a valid point. Companies will need to make it easy to obtain the additional features, and the lack of doing so will only bring confusion and hassle to the already complex software industry.

Customers are tired of bloated software that is difficult to use and that slows down our computers. We are becoming more aware of other choices in the software market, and we’re making it clear through the internet and our spending habits that we just want something that works and that isn’t a hassle to use.

Fact: “Google Docs Struggles to Gain Foothold.” “Google Docs Use: Just a Blip.” “Study: Office Fights Off Google Docs Threat.” “OpenOffice Five Times More Popular than Google Docs.”  These are news articles covering the release of a new ClickStream study of typical use of “productivity software” like the Microsoft Office suite (Word, Excel), Google Docs, Google Spreadsheets, OpenOffice, etc. The study “among adult U.S. internet users showed that use of free productivity applications such as Google Docs and OpenOffice remains low, while Microsoft Office is in use by over 50% of adult U.S. internet users and shows no signs of declining popularity.”

Analysis: Well, yesterday I gave Google some nice words because of our joint work with DoD on improving military health IT. So I’m itching to tweak the Big G now, and we have some numbers to examine.  And I wasn’t cherry-picking the titles above either, they were the “most relevant” results on a Google News query this morning for <”Google Docs” OpenOffice Microsoft>.

But there’s more to the story, if you read closely. Let’s start with the basic findings. The ClickStream summary of the study says:

Of all free productivity applications observed, OpenOffice (a client application) was the most popular, in use by 5% of all users. OpenOffice also had the heaviest and highest frequency of use among free apps, with an average of 548 clicks performed and 8.7 days of use per user.

Google Docs (a web-based application) was the 2nd most popular free productivity app, used by 1% of users. Google docs also had the lightest use of all productivity apps, with an average of 40 actions performed in the app (compare with 548 in OpenOffice and 1,797 in Microsoft Word), and the fewest average days used during the 6-month period [emphasis added]. Although 1% of users had Gears installed on their machine, there was no evidence of its use in conjunction with Google Docs, nor did any user click on “Offline” or “Get Google Gears now” in their Docs account.

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Using Google Spreadsheets, it’s trivial to create a spreadsheet with updating (but delayed) market data – like this. The formula for each cell follows the format =GoogleFinance(symbol,attribute), so to retrieve the quote for Microsoft, enter =GoogleFinance(“MSFT”,”quote”). Although the quotes are delayed by 20 minutes, you can then use the Google Gadget graphing capabilities to see the composition of your portfolio. And, of course, you can share with your friends in real time, as always with Google Spreadsheets.

For detailed documentation about different market data attributes, as well as information on accessing historical data, click here.

If you’ve ever had a list of geographical data in a spreadsheet and wanted to show this visually on Google Maps, this post is for you. Traditionally, getting this to work from a Microsoft Excel spreadsheet involves some complex trickery and third-party plug-ins, but now Google Gadgets makes this very easy – and free.

Build the dataset and creating the map

If you haven’t signed up for a Google account, do this first to get access to Google Docs. Once there, click on New –> Spreadsheet to create a blank workbook.

In the first column, add the addresses you want to track, and in the second column, add the tracking data you would like displayed on the map (eg. person’s name, salesman’s revenue, etc.) Once complete, click on Insert –> Gadget –> Maps and select the Google Map. This will then appear on your workbook:

You need to define the range of data (eg. A1:B100 would take completed entries in the first 100 rows). And you can optionally add a title, and change some of the interaction options of the map. You can view the live page by signing into Google and clicking here.

Embedding the results in your webpage

Click the options arrow in the top right-hand corner of the map, and select ‘Publish’. This will show you the script needed to embed this map into any HTML page. The resulting embedded map will be linked to your underlying data in the spreadsheet.

Other Google Gadgets

Google has a range of existing gadgets that you can attach to your Google Docs, but they have also exposed the API to enable you to write your own. Although some of the gadgets are designed purely for fun, there is a growing range of gadgets that extends the basic spreadsheet functionality to include functions previously only available in Microsoft Excel. For example, pivot tables can now be achieved through a gadget and unlike their Excel counterpart, they update in realtime. You can access all of this functionality from the Insert –> Gadget options.

We expecting the functionality of custom gadgets to grow exponentially in the next few months, as Google Docs becomes a serious contender to replace Microsoft Excel.

If you’ve ever wanted to send a survey to your customers (or any type of form to a group), traditionally this would require you to design an email, and then parse each customer response into a spreadsheet. Or you could find a web programmer in your company to throw together an ASP page (presuming you don’t have complex firewalls and infrastructure) or pay for a service such as Survey Monkey.

But with the new features of Google Spreadsheets, you can create a form and collate its results in seconds, and today’s post will show you how.

Designing the form.

Create an account at http://docs.google.com/ if you don’t already have one, and click on New –> Form. The form designer opens, which is a simple interface for putting together your questions. Here you can specify the type of question and response (text, multiple choice, etc.) and if responses are compulsory. Once you have finished, it will look something like this:

At the bottom of this window, you can see the form’s URL that you can send to your survey group. In this example it’s https://spreadsheets.google.com/viewform?key=p7BlQgZBeja8TAfFx1ObCZg. Note this URL is also secure, so responses are encrypted between the recipient and the server. 

In the top right, you will see a button called ‘More Actions’, which provides the code for embedding the survey in an iFrame (which you would use if you wanted to show the survey as part of another webpage), and also let’s you change the confirmation text that your user will see when they have completed the survey:

Gathering the feedback

Back in your Google Docs dashboard, you’ll see your newly-created form:

Click this item to open its underlying spreadsheet, which will update in realtime as respondents complete the survey:

From here, click the ‘Share’ button in the upper right-hand side, and you can choose which people can view and edit the results. I’ve published the sheet with rights for everyone with a Google account to view here. You can publish as a webpage (https://spreadsheets.google.com/pub?key=p7BlQgZBeja8TAfFx1ObCZg) which opens the page to universal access (but does not automatically update).

Furthermore, clicking the ‘Analysis’ button provides realtime charting of the responses:

Benefits and Limitations

Pros:

• This is probably the fastest and simplest way to send forms out to groups, and could be used to gather information from your internal groups, external customers, or even just as a form of Evite for a gathering. 
• The Microsoft Office alternative would be through Infopath or the Email to Spreadsheet/Database option, which is a little similar but more complicated, and relies on more licensed software.
• There are no limitations on the number of forms or questions and it’s free.
• Integration with the spreadsheet and analytics makes data-gathering completely automated.
• There are no problems posed by corporate firewalls or security (unless your company policies prohibit its use).
• Everything happens over SSL and data is stored in the cloud.

Cons:

• You cannot remove the ‘Powered by Google Docs’ or Google Terms which appear on the survey.
• You cannot parse or validate the entries provided.
• You cannot collect IP addresses or leave cookies to prevent multiple responses from one recipient.

Next, let’s look at some of the Google gadgets that can be used to bring these spreadsheets to life.