Where are Australian jobs growing or shrinking (2002 - 2014; over 100 regions; SA4 level)?
This data - count of employees by 100 regions within Australia (over 12 years; 2002 - 2014) - 8.5M 2002 -> 10.3M 2014.
Parent data - Employee $ DATA by detailed occupation, by location (SA4), by year;
See analysis in progress for:
=> Individual income by occupation / location
at: http://areff2000.net16.net
To recreate #datavis -
How To To view on National Map (data.gov.au mapping tool).
1. Save data as csv.
Data (loaded here), currently at: http://118.138.240.130/sa4_deltaHeadcountRaw_display.csv
2. Open http://nationalmap.gov.au.
3. Click 'Add Data'.
4. Drag csv file onto map.
5. Click Done.
6. Select Year in control panel (lower left of screen). Raw shows count of jobs. Year shows % change from four years earlier.
7. Click on region (SA4) to see data for that region.
Data format: Year | Occupation | Location (SA4) | Count of Workers | $ of Workers
* Year: [2002, 2006, 2010, 2014]
* Salary and Wages; 200,000 lines (summary only included here)
* Sole Proprietors; 100,000 lines (not included here)
* Occupation: Description at Australian Bureau of Statistics. (3,216 lines) (link below)
* SA4 Location descriptions at: http://stat.abs.gov.au/itt/r.jsp?databyregion#/.
#dataTotals - Salary and Wages
| Year | Workers (M) | Earnings ($B) | GDP USD($B) |
|---|---|---|---|
| 2002 | 8.5 | 285 | 400 |
| 2006 | 9.4 | 372 | 746 |
| 2010 | 10.2 | 481 | 1142 |
| 2014 | 10.3 | 584 | 1450 |
Table 1: Aust. Salary and Wages 2002 - 2014.
GDP info from: Trading Economics (link below).
#datavis
1. Three Chloro images made at aurin.org.au (AU researcher login required). eg Chloro12_2014 is 12 colour chloropeth, for 2010 - 2014, Chloro12_2010 is 2006 - 2010, Chloro12_2006 is 2002 - 2006.
Please cite images as: Ferrers, R., ATO - User uploaded data (2016) visualised in AURIN portal (map visualisation chloropeth) on 25.8.2016. Viewed online at: https://dx.doi.org/10.6084/m9.figshare.4056282.v2
2. Red/Orange (year.tiff) images made at nationalmap.org.au, where 2014.tiff is percent difference 2010 - 2014, 2010.tiff is 2006 - 2010, 2006.tiff is 2002 - 2006.
#usage
This #datavis was used in a University of Melbourne Library Hackathon - Hack for Good (25.8.16) - https://twitter.com/ValueMgmt/status/769041449862168577
Slides attached below: (see Canva link; Ferrers, Li, Kreunen and Lindsay (2016). L^2 Local Livability Index. Online at: https://www.canva.com/design/DAB8-48tlEw/view)
https://twitter.com/ValueMgmt/status/770144651953135616
