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Python library to programatically access geospatially aggregated spatio temporal socioeconomic datasets produced by the Australian Bureau of Statistics

License: Apache License 2.0

Shell 0.01% Jupyter Notebook 98.50% Python 1.32% TeX 0.18%

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seifa's Issues

Shapely GEO warning

konstantinstadler's review comment from ausdex: rbturnbull/ausdex#5

When installing in a fresh conda environment (Python 3.9) I get the following warning

UserWarning: The Shapely GEOS version (3.10.2-CAPI-1.16.0) is incompatible with the GEOS version PyGEOS was compiled with (3.9.1-CAPI-1.14.2). Conversions between both will be slow.
Downloading https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/consumer-price-index-australia/mar-2022/640101.xls to /home/konstans/.cache/ausdex/640101-mar-2022.xls
CPI data for 2022-04-11 15:24:00.144389 not available.

Problem with the CLI usage

From konstantinstadler's review comment: rbturnbull/ausdex#2

Hi,

This is connected to the JOSS review.
I tested all examples given in the README and most work. However, if I do

$ ausdex seifa-vic 2020 footscray ier_score

I receive NaN. Full output:

UserWarning: The Shapely GEOS version (3.10.2-CAPI-1.16.0) is incompatible with the GEOS version PyGEOS was compiled with (3.9.1-CAPI-1.14.2). Conversions between both will be slow.
nan
One other oberservations: The interpolate_vic_suburb_seifa values given in the README for the interactive use are 2 units above the values I currently get. Probably due to updates in the upstream db.

Magic numbers in the code

From konstantinstadler's review comment in ausdex: rbturnbull/ausdex#6
The function (in data_io.py)

def download_from_aurin(
    wfs_aurin, dataset, links, local_path, bbox=(96.81, -43.75, 159.11, -9.14)
):

has these 4 magic numbers which should be explained in a docstring or stored in a meaningful variable name.

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