I've been using R for a few years now and have found it fantastic for all the data manipulation and visualisation I was doing, plus you can even use it to build web apps! So to help people get going with R I've put together a pre-tutorial to show off a little of what it can do and help you work out if it is for you. Why use R? Overview and case studies One thing I missed in the video was to explain what R actually is, so here's my super brief definition... R is an open source data analysis scripting (or programming) language which was originally developed for statistical analysis but is now used more broadly in many scientific and business fields. It is my second ever video tutorial so please be kind but I do welcome suggestions for improving them or requests for topics/questions you are interested in. Also, what do you think of the new logo?

I'm big believer in beauty in simplicity... most of the time.  But regardless this is a great presentation that walks through some table formatting options that produce a much more readable table.  Interestingly the starting point is quite similar to the Microsoft defaults... Clear Off the Table

For years now I've been recommending QGIS to friend and colleagues with the caveat that there is bit of a learning curve, but that it's really great!  So to help these people along I've created a video tutorial that will get you up and running with QGIS. Intro to QGIS: Installing and Importing - Quickstart guide It is my first ever video tutorial so please be kind but I do welcome suggestions for improving them or requests for topics/questions you are interested in.  In future I probably won't record on quite so little sleep with a sleeping baby in the next room...

While delving into some data science communities I had hear of Kaggle many times over and had even created an account, but it wasn't until I got an email about a dataset of Kiva loans that I actually got interested. First of all, what is Kaggle? Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. - Wikipedia Essentially it is a data science playground where you can access data, do analysis, look at other peoples analysis and enter competitions. If you submit an analysis then all your code is available for others to see which means you can 'be inspired' techniques you see others using and also makes it easier assist others when they need help. So what about Kiva? Kiva Microfunds is a 501 non-profit organization that allows people to lend money via the Internet to low-income entrepreneurs ...

 KML is a really common format, it is not usually one that GIS professionals use for a number of reasons but it is really handy for passing GIS data to online mapping systems, portable devices and it can even be created with a text editor.  If you want more information on it then the wiki page on Keyhole Markup Language (yes, that is the actual name) and Google Developers KML page are good places to start. Using KML with QGIS is super simple however there are a few tricks, particularly with KMZ files .  Here is a brief tutorial on opening KML files in QGIS. So getting them into QGIS is fine but sometimes I need to use the data within a KML file and QGIS doesn't deal with that very well as all the descriptive fields are groups in an HTML table in a single field.  While I'm sure it is possible to parse this in QGIS, here is a script in R since that was where I needed the data anyway. Save the KML file as a .csv file Open the file in R with read.csv ...

Region around Tidal River Wilsons Promontory is a beautiful national park in Victoria, Australia and actually contains the southern most point of the mainland. It is know for its beaches, camping, hiking and generally just being a nice place to visit.  While it is almost impossible to get lost there, I do love a good map and they do come in handy... Background I started making maps when I discovered there was a wealth of data on the data.vic.gov.au site and a friend mentioned needing some maps to go fly fishing. So I downloaded some data and set about putting something together. The first maps were not great, it was rather hard developing layer styles that work well together but it was a good starting point and a proof of concept. Tidal River looking towards Mt Ramsay Not long after that I decided to put together some maps to do the Coast to Coast in England based on UK Ordinance Survey data .  One of the really nice thing about this data is that they also off...

I had been looking for a good coding project for a while, to try and build some confidence before I attempted a hackathon, when a friend posted a link to a great map based representation of the  Australian Marriage Law Postal Survey results.  It was a nice clean map that provided a mouse-over pop-up of the yes/no percentage for each electorate which I found it really interesting, but I also wanted some more information.  Information on things like the number of voters, the member holding that seat, the party they are from, what suburbs where in each electorate, and maybe even some census data.  Thus the project was formed. As always, the 80:20 rule was proved true when I got the map up with the basic info the following day, but being a perfectionist (with a small child and a few other project on the go), it has taken me quite a bit longer to show it off but here it is: 2017 Australian Marriage Law Postal Survey - Results Map (The site is hosted on shinyapps.i...