Microsoft flow as a last resort in place of cron and windows scheduler

You know the situation: while you are not the biggest fan of MS out there, your employer's IT department are. Of course you don't really have proper access to a Linux system to set up a cronjob to do your data fetching for you, and you don't even have an 'always on' windows machine to be able to do this via Task Scheduler.

Well, you have to make do with what you have, and in this case, that is Office 365, a lesser known component of it called Flow. There is an upside to this to rescue your pride somewhat: while it is a humble office app it uses the same language as azure logic apps, so think of it as cloud training!

Using Post code Sector GeoJson from TableauMapping.bi

Ok, so this time I'm using https://www.tableaumapping.bi/ properly. I connect using the web connector from tableau Public to https://www.tableaumapping.bi/wdc and chose the Post code Sector table. I then blend in my own data with post code addresses. I use a calculated field to generate the sector from the full post code in my data:

left([postcode],len([postcode])-2) 

and voila! a much more detailed map than the one I got before using only the first half of the postcode.

Strange maps courtesy of Tableau mapping BI

While fooling around with the otherwise worthwhile https://www.tableaumapping.bi website last night, I managed to get it into a state producing some rather interesting maps. The one below shows the UK ceremonial counties trampling over Iceland (cod wars all over again!). 

Another one shows the Bristol channel housing the whole of the EU and a few fellow travellers broken down to NUTS 2!

I'm having trouble reproducing the behaviour today, they might have fixed it!

British MEPs go NUTS

I know what you are thinking, the European Parliament has more than its fair share of nutcases but this is about NUTS as in Nomenclature des unités territoriales statistiques  which are defined across Europe, but we'll take the UK as a case study.

A year and a half ago I looked into grouping counties and unitary authorities together in Tableau to form the European election constituencies in England. This takes a fair amount of work, and I had a dodgy solution with dual axis to avoid having to also group all Scottish, Welsh and Northern Irish counties in a similar way.

A much simpler solution using the latest Tableau functionality is to use NUTS as geographic role. This avoids needing a source to define the constituencies at all, so the data source of the MEPs of each region is enough to also generate maps.

Splitting the prefix out of a british postcode with no spaces

I came across a dataset this week that had postcodes in this format

Tableau only understands the first half of the postcode, but how do we split it out? Wikipedia as always has a fairly comprehensive description: The outward code (i.e first half) can be from 2 to four characters, but the inward code (second half) is always three characters. Therefore we can isolate the outward code with a calculation:

left([Post Code],len([Post Code])-3)

This now gives the outward code alone in a field that can be given a post code geographic role and  used with the filled map mark type.

And if you do spatial analysis, that little anomaly on the river Thames would have caught your attention. Lets add place names and streets in the map layers and zoom in:

Simultaneous gantt objects (2018.1 update of using pivot with contracts)

My second post more than a year ago looked at how we find simultaneous gantt type objects. While the method for data preparation still stands, the final plot can be refined a bit thanks to the latest tableau update, the step line type

This now gives a more realistic depiction of the number of concurrent objects and how they change, as it is going to be a step change through integer values rather than a ramp up.

Layering filled maps and polygons on map (2018.1 update)

I wrote about this technique more than a year ago and it was one of my more popular posts, thanks to a tweet by zen master Chris Love. It is time to update the particular example as version 2018.1 finally brings generated Latitude and Longitude closer to Latitude and Longitude already in the dataset.

We start by UNIONing our two sources, the polygon source having latitude and longitude, the mark source having a field that can be interpreted as a filled map.

 We then use the new trick of putting generated latitude and longitude on the axis, with source latitude longitude in the level of detail for the polygon layer. In the past I would import the filled map source, generate the latitudes longitudes, export crosstab to excel, save as csv, and do a union with the polygon csv. No longer necessary as of 2018.1.

Now all that is required is dual axis to overlay the polygon over the filled map.