With disaster comes opportunity Due to a computer disaster we recently had to reinstall everything, and we think we’re almost working to our old capacity. Some of the recovery has not been easy, but one thing that was simple was to re-install Anaconda/Python, Pyomo and the GLPK linear program solver. The reason it’s […]
Quarterly Gross State Product Australia, Quarterly GSP Australia, Quarterly State Accounts Australia. Economic growth. GSP growth. New South Wales (NSW), Victoria (Vic), Queensland (Qld), South Australia (SA), Western Australia (WA), Tasmania (Tas), Australian Capital Territory (ACT), Northern Territory (NT). Benchmarking. June quarter 2023, 2022/23. Australian Bureau of Statistics (ABS), Cat No. 5220.0, Cat No. 5206.0.
Python Pyomo Abstract Models, Results Viewing, Results Extraction, Results Saving, Python Dictionaries, Python Pandas DataFrames, Excel.xlsx CSV.csv. It’s been some time since we posted on installing Python and its associated linear programming package Pyomo, followed by a few basic operations – December 2019 to be exact. These were our first two real posts on
The ABS does not publish quarterly Australian state and territory GSP estimates, so Practical Economics generates quarterly GSP by benchmarking quarterly industry indicators to annual GSP benchmarks.
A few weeks ago the Australian Bureau of Statistics (ABS) published the September quarter 2021 Australian National Accounts: National Income, Expenditure and Product (Cat. No. 5206), which means we can update the Practical Economics quarterly Australian State and Territory Gross State Product (GSP) series. The ABS does not publish quarterly state and territory GSP. The Practical Economics quarterly GSP
Australian Quarterly Gross State Product (GSP): September Quarter 2020/21 Read More »
We hope you learned something from Part 1 of our post on stylised charting with Python/Matplotlib. You now know how to do straight line charts using point to point plotting. This post teaches you to do some curves, and some more straight lines, with equations. As with anything Python, there’s probably a thousand ways to
Stylised (Stylized) Economics Charts in Python/Matplotlib: Part 2 Read More »
Charts can be your best friend in understanding the world. They can also be your worst enemy. One of the Proprietor’s pet hates is ‘analysts’ putting a metaphorical magnifying glass over a chart and attempting to rationalize any little up or down that might occur. Or seeing relationships during part of the chart sample that
Stylised (Stylized) Economics Charts in Python/Matplotlib: Part 1 Read More »
As we write this, due to the Wuhan/Coronavirus the Australian Football League teams were playing matches in front of no spectators over a shortened season before the league was delayed entirely. The Western Australian Football League has been delayed until June, while junior training and games in Western Australia were also cancelled until June. We
You’ve now installed Anaconda/Python and Pyomo. What do you do now? This post gives you the very basics of running Python in terms of line by line code in the IPython Console and running a file from the Editor window. It is not a full tutorial on Python. There is so much excellent information available
Getting Started in Python/Anaconda Read More »
OK, maybe not the only software you’ll ever need, but only maybe. At least it’s all you need to implement any Practical Economics analysis provided on this blog. It’s what we use. If anything extra is required for anything we post we’ll let you know how to install it at the time. What is Python?
