Speedtest Open Data - Four International cities - MEL, BKK, SHG, LAX plus ALC - 2020, 2022

This dataset compares four cities FIXED-line broadband internet speeds:

- Melbourne, AU

- Bangkok, TH

- Shanghai, CN

- Los Angeles, US

- Alice Springs, AU

ERRATA:

1.Data is for Q3 2020, but some files are labelled incorrectly as 02-20 of June 20. They all should read Sept 20, or 09-20 as Q3 20, rather than Q2. Will rename and reload.

Amended in v7.

2. LAX file named 0320, when should be Q320.

Amended in v8.

*lines of data for each geojson file; a line equates to a 600m^2 location, inc total tests, devices used, and average upload and download speed

- MEL 16181 locations/lines => 0.85M speedtests (16.7 tests per 100people)

- SHG 31745 lines => 0.65M speedtests (2.5/100pp)

- BKK 29296 lines => 1.5M speedtests (14.3/100pp)

- LAX 15899 lines => 1.3M speedtests (10.4/100pp)

- ALC 76 lines => 500 speedtests (2/100pp)

Geojsons of these 2* by 2* extracts for MEL, BKK, SHG now added, and LAX added v6. Alice Springs added v15.

This dataset unpacks, geospatially, data summaries provided in Speedtest Global Index (linked below). See Jupyter Notebook (*.ipynb) to interrogate geo data. See link to install Jupyter.

** To Do

Will add Google Map versions so everyone can see without installing Jupyter.

- Link to Google Map (BKK) added below. Key:Green > 100Mbps(Superfast). Black > 500Mbps (Ultrafast). CSV provided. Code in Speedtestv1.1.ipynb Jupyter Notebook.

- Community (Whirlpool) surprised [Link: https://whrl.pl/RgAPTl] that Melb has 20% at or above 100Mbps. Suggest plot Top 20% on map for community. Google Map link - now added (and tweet). 

** Python

melb = au_tiles.cx[144:146 , -39:-37] #Lat/Lon extract

shg = tiles.cx[120:122 , 30:32] #Lat/Lon extract

bkk = tiles.cx[100:102 , 13:15] #Lat/Lon extract

lax = tiles.cx[-118:-120, 33:35] #lat/Lon extract

ALC=tiles.cx[132:134, -22:-24] #Lat/Lon extract

Histograms (v9), and data visualisations (v3,5,9,11) will be provided.

Data Sourced from - This is an extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).

**VERSIONS

v.24 Add tweet and google map of Top 20% (over 100Mbps locations) in Mel Q322. Add v.1.5 MEL-Superfast notebook, and CSV of results (now on Google Map; link below).

v23. Add graph of 2022 Broadband distribution, and compare 2020 - 2022. Updated v1.4 Jupyter notebook.

v22. Add Import ipynb; workflow-import-4cities.

v21. Add Q3 2022 data; five cities inc ALC. Geojson files.  (2020; 4.3M tests 2022; 2.9M tests)

#Melb 14784 lines Avg download speed 69.4M Tests 0.39M

#SHG 31207 lines Avg 233.7M Tests 0.56M

#ALC 113 lines Avg 51.5M Test 1092

#BKK 29684 lines Avg 215.9M Tests 1.2M

#LAX 15505 lines Avg 218.5M Tests 0.74M

v20. Speedtest - Five Cities inc ALC.

v19. Add ALC2.ipynb.

v18. Add ALC line graph.

v17. Added ipynb for ALC. Added ALC to title.v16. Load Alice Springs Data Q221 - csv. Added Google Map link of ALC.

v15. Load Melb Q1 2021 data - csv.

V14. Added Melb Q1 2021 data - geojson.

v13. Added Twitter link to pics.

v12 Add Line-Compare pic (fastest 1000 locations) inc Jupyter (nbn-intl-v1.2.ipynb).

v11 Add Line-Compare pic, plotting Four Cities on a graph.

v10 Add Four Histograms in one pic.

v9 Add Histogram for Four Cities. Add NBN-Intl.v1.1.ipynb (Jupyter Notebook).

v8 Renamed LAX file to Q3, rather than 03.

v7 Amended file names of BKK files to correctly label as Q3, not Q2 or 06.

v6 Added LAX file.

v5 Add screenshot of BKK Google Map.

v4 Add BKK Google map(link below), and BKK csv mapping files.

v3 replaced MEL map with big key version. Prev key was very tiny in top right corner.

v2 Uploaded MEL, SHG, BKK data and Jupyter Notebook

v1 Metadata record

** LICENCE

AWS data licence on Speedtest data is "CC BY-NC-SA 4.0", so use of this data must be:

- non-commercial (NC)

- reuse must be share-alike (SA)(add same licence).

This restricts the standard CC-BY Figshare licence.

** Other uses of Speedtest Open Data;

- see link at Speedtest below.