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Thread: choropleth map datawrapper

  1. #1
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    choropleth map datawrapper

    Hello All,

    What free software do you use to create a population-based heat map - also known as a choropleth map - overlaying an Australian map? Remember the mention of the work "free". This is a map that shows different density of population within a specific local area. The differences in population are shown within a different scale of colours. For example, red could represent the highest population density of a particular cohort of people. Where yellow could be medium density. Down to white representing not many people at all.

    I have been tasked to provide a population-based heat map or choropleth to indicate the number of a specific group of people living in Queensland. I came across the Datawrapper website and followed the 'simple' tips and tricks. However, my map lacks colour. As in not showing any populations.

    I tried using the simple Youtube directions using the mapping feature of Microsoft Excel. However there must be different versions because the option of making a choropleth map is shown on YouTube - however, my version of Excel does not have that option to click on.

    I have my data in a spreadsheet that I have uploaded to the program.

    I started to search the internet and found Datawrapper and even Datawrapper's on how to YouTube clip - Accessed 14th November 2025 from, https://www.youtube.com/watch?v=-e7O69cgQ_M&t=309s

    Any help would be greatly appreciated - I identify as a semi-Luddite. I am on the very steep end of the learning curve regarding choropleth map constructions.

    The data range is between 1000 to 27000 - perhaps I need to adjust the scale in density to come up with the colour scale shown on the map. At the moment there is only the name of the location city/region/shire in Queensland labelled and zero colour shading or numbers appearing. I must have missed a couple of steps about how to refine things - like generating colour. Ignorance is unfortunately not causing bliss at the moment! Just frustration.

    Kind regards
    Lionel

  2. #2
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    Quote Originally Posted by Lionelgee View Post
    Hello All,

    What free software do you use to create a population-based heat map - also known as a choropleth map - overlaying an Australian map?

    Kind regards
    Lionel
    Hi Lionel.

    Not sure where the term 'heat map' comes from unless it is a colloquial term applied to maps that use varying shades of red to represent different temperatures in different regions. Choropleth is really about the use of the entire colour spectrum to represent data. In some situations shades of one colour might suffice. Choice is up to the user or dictated by the data.

    An AI search comes up with (apparently) free mapping programs like QGIS, SAGA GIS, ILWIS, DIVA GIS, FALCONVIEW - I haven't used any of them.

    I'm only familiar with linking spreadsheet data and map data together using a mapping program. I don't now if advances in Excel allow it to replace the mapping program.

    About 18 years ago, in a past life, I used MapInfo to 'join' map files and Excel spreadsheets together to create choropleth maps.

    To start with, simply put, you need (1) a map file, (2) an empty spreadsheet and (3) a mapping program aka a GIS program.. The first column of numbers, unique numbers, in your map file is copied to the first column in your spreadsheet. You load the remaining spreadsheet columns with your research data, as many columns as needed, arranged against the relevant unique number. The mapping program uses the list of numbers, unique numbers, to tie together each map region with the spreadsheet data that belongs to that map region.

    The data, now tied to a region, is colour coded by a choropleth process, then presented as a finished map. The choroplething, or colour coding, is done in the mapping program - the data breaks for scaling and colour arrangement is up to you. As you have indicated, if there is no data for a region then the region could be white unless you make instances of 'no data' the first pale shade from your scale.

    There will be as many lines in your spreadsheet as you have geographic regions, ie 20 regions = 20 lines.

    If you collected 5 types of data from 20 regions then the spreadsheet will be 20 lines deep by 6 columns wide.

    In your spreadsheet you will have your uniquely numbered geographic regions (column 1) number of sheep in each region (column 2) number of cattle in each region (column 3) weight of fish caught in each region (column 4) number of people in each region (column 5) number of barbecues in each region (column 6).

    To create a map you will see inside the mapping program all the data headings that were in your spreadsheet. In your first set of maps you might want to choropleth the population by geography first, so you choose column 1 and 5. Next set of maps, number of cattle by geography, so you choose 1 and 3. Barbecues by region 1 and 6 etc.. You could devise a map that has both number of people and number of cattle by geographic region, but you generally do not do that - such a map for example could be coloured to represent the cattle, with black numbers in each region representing the number of people. Usually a choropleth map represents all the geography regions against one data type at a time. If you want to compare more than two data types against geography you should resort to graphs and data tables. Choropleths are for simple visual representations, as are the frowned upon pie graphs.

    Again inside the mapping program, you set the data breaks and corresponding colour(s) that you want - this will be the scale on your map. Sometimes natural breaks in the data may dictate how the scale is devised. Usually keep the breaks to a small number ie less than 100 sheep, less than 500 sheep, less than 1000 sheep, less than 5000 sheep...less than 10000 sheep, greater than 20,000 sheep. If you had a zillion sheep and a zillion different shades of one colour or a zillion of all colours, then no one is going to be able to tell one subtle shade from another, the map would be unreadable. The fewer number of data breaks in your scale the better the colour contrast.

    May be wrong, but you may be able to get ABS map files from their website, like State/Local Area (SLA)/Collection Districts (CD)/sub-CD. Oherwise you need to buy a map file or you make your own in the mapping software. Organisations often have their own purpose built maps or they manipulate (redistrict) ABS maps to get an approximation of their geography that mainly meets their needs. Redistricting is often done on a consultancy basis by the organisation that owns the maps - not because the agency does not want to give you the map, but because many researchers don't know how to redistrict maps. Organisations often want to compare their own data with ABS data on population, income, occupation etc so it pays to use an ABS map or some manipulated version of an ABS map.

    If the 'specific group of people' you refer to are of Aboriginal or Torres Strait Islander descent then ABS has covered that in Indigenous Community Profiles, from memory free from their website. If you are talking about country of birth groupings then you may find ABS Census profiles for free on their website. Same with occupation groupings, income groupings etc. ABS usually releases the commonly demanded data as publications, for free. You will usually pay where you want something not commonly required, or you want a variation on an already released publication.

  3. #3
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    Going to need a lot more coffee this morning, apparently.
    ​JayTee

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  4. #4
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    Hello Workingonit,

    Thank you for your insightful post. It will take me a while to digest its contents.

    I found this link that explains what heat maps are Heatmaps | Visualise Demographic Concentrations (Accessed 15th November 2025). The term seems to cross over to being a type of choropleth map. The person I am working with is ex-military and they apparently use heat maps a lot. I used to know the dot to density and colour as being scatter-plot representations. The concepts of heat maps and choropleth are very new to me. As mentioned previously - I am at the steep part of the learning curve.

    It seems to be something that features strongly this week. I caught up with a former colleague yesterday, who is now a professor. They kept suggesting that I should become conversant with Artificial Intelligence to do things like convert my thesis, or chapters thereof into research papers. Online courses and the like. "oh, you can do that now with AI", was frequently mentioned. All from the comfort of my own home.

    Last week I had a meeting with an IT person and they said pretty much the same thing about how I should become more familiar with AI. It annoys the crap out of me when I write an email in Outlook and then I get rudely interrupted by Copilot asking me if I want it to take over writing the email. My response is that Copilot can do physically impossible things to itself.

    Looks like I will be disappearing down the AI rabbit hole over the next week or so - sigh!

    Can you pick up my level of enthusiasm towards AI? Sigh x 4..

    See-ya down the rabbit hole I go... sigh x 5

    Kind regards
    Lionel

  5. #5
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    Hello All,

    It could be that a dot density map might be more appropriate than a chloroplast map... more research to do on the two of them.

    I am looking at identifying on the map the density of where a specific group of people - say for example, the number of Land Rover Series vehicles per state government electorate in Queensland. By the way - did you know there are 78 Local Government Areas (LGA) in Queensland! I have been spending lots of time lately looking on the Australian Bureau of Statistics' Census 2021 results.

    It is even more fun when a chosen district does not follow LGA boundaries. Primary Health Network map makers in New South Wales seem to like drinking lots of red wine before and during making their health district maps. "Clear boundaries such as LGA's ... nah, I reckon we should cover over here too, and why not cover over there as well" ... sip .. sip.. scribble .. sip...

    Kind regards
    Lionel

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    Quote Originally Posted by Lionelgee View Post
    .

    It is even more fun when a chosen district does not follow LGA boundariesl
    Probably steer clear of 'home made geographies' that are partially based on national standards combined with 'something else' - in these cases it makes importing data from more disciplined sources difficult.

    Generally, but not always, the key is not to cut the lowest standard geography unit in half to match your border better - either incorporate it entirely in the geographic unit you are building, or hive it off in its entirety to another geographic unit.

    If creating your own geography, for example river drainage regions by economic activity, stick to modelling the catchments around national geography units. The units go down to very small amounts of surface area (CDs or now Statistical Level Areas) - you will get a very good approximation of your catchment area, a bit fuzzy around the edges to what you might really like - but again data from more disciplined sources will be easy to incorporate. I'm not sure if sub-CD units, very small units, are still in use and from memory were not available publicly - SAS was required to manipulate the massive collection of such small units.

    Not entirely sure, but you might be safer using Statistical Local Areas (SLA). Even then, things change and you should look at the Australian Statistical Geography Standard.

    It may still be the case that not all of Australia is covered by a council. Where the land is covered by a council the boundary it is called a Local Government Area (LGA). The rest is 'unincorporated'.

    To resolve this issue the Statistical Local Area (SLA) was created to cover both council land and unincorporated land. To start off, the majority of SLAs and LGAs had the same boundary.

    Dot densities are OK where there is little or no overlay of dots. I assume dot size is part of this and not just dots of the same size with increasing colour density? A really dense dot will be very large and run over the smaller surrounding dots. If you really just want a more densely coloured dot

    I've been reading up lately on SQL and NoSQL for which there seem to be very sophisticated data presentation programs ie Neo4j. Life is just not long enough.

  7. #7
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    Quote Originally Posted by workingonit View Post
    Not entirely sure, but you might be safer using Statistical Local Areas (SLA). Even then, things change and you should look at the Australian Statistical Geography Standard.

    It may still be the case that not all of Australia is covered by a council. Where the land is covered by a council the boundary it is called a Local Government Area (LGA). The rest is 'unincorporated'.

    To resolve this issue the Statistical Local Area (SLA) was created to cover both council land and unincorporated land. To start off, the majority of SLAs and LGAs had the same boundary.

    Dot densities are OK where there is little or no overlay of dots. A really dense dot will be very large and run over the smaller surrounding dots.

    I've been reading up on SQL and NoSQL for which there seem to be very sophisticated data presentation programs ie Neo4j. Life is just not long enough.
    Hello working on it,

    Fortunately for the Queensland-based task I could stick with Local Government Areas and finding the information in the Australian Bureau of Statistics via their LGA "Quick Stats." For example, Bundaberg 2021 Census All persons QuickStats - Geography type: Local Government Areas - Area code LGA31820. Accessed 15th November 2025 from, 2021 Bundaberg, Census All persons QuickStats | Australian Bureau of Statistics. I only needed to go down to a handful of smaller "Community Profiles" and downloading the data sets for SLAs within a single PHN area in NSW.

    I will read up on your tip about SQL. I also reached out to my old university via an email to one of their lecturers. According to their website the geography section is under their Bachelor of Science and Environment. Fingers crossed they get back to me.

    Kind regards
    Lionel

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