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Description:

pydplace 3.2.0

pydplace
A Python library to curate D-PLACE data.

To install pydplace run
pip install pydplace

Usage
Bootstrapping a pydplace-curated dataset
pydplace provides a cldfbench dataset template to create the skeleton of files and directories for a
D-PLACE dataset, to be run with cldfbench new.
Running
cldfbench new --template dplace_dataset

will create a dataset skeleton looking as follows
$ tree testtree/

Implementing CLDF creation
Implementing CLDF creation means - as for any other cldfbench-curated dataset - filling in the
cmd_makecldf method of the Dataset subclass in cldfbench_<id>.py.
Running CLDF creation
With cmd_makecldf implemented, CLDF creation can be triggered running
cldfbench makecldf cldfbench_<id>.py

The resulting CLDF dataset can be validated running
pytest

Release workflow
cldfbench makecldf --glottolog-version v5.0 --with-cldfreadme cldfbench_<id>.py
pytest

Now inspect the changes and add a corresponding section to CHANGELOG.md.
cldfbench zenodo --communities dplace cldfbench_<id>.py
cldfbench cldfviz.map cldf --pacific-centered --format png --width 20 --output map.png --with-ocean --no-legend
cldfbench readme cldfbench_<id>.py
dplace check cldfbench_<id>.py
git commit -a -m"release v3.1"
git push origin
dplace release cldfbench_<id>.py v3.1

Then create a release on GitHub, thereby pushing the repos to Zenodo.
Using the datasets
$ csvgrep -c Var_ID -m AnnualMeanTemperature cldf/data.csv | csvstat -c Value
4. "Value"

Type of data: Number
Contains null values: False
Unique values: 1649
Smallest value: -19,45
Largest value: 29,153
Sum: 32.700,717
Mean: 16,449
Median: 19,721
StDev: 9,684
Most common values: 14,392 (9x)
21,66 (6x)
6,96 (6x)
23,335 (5x)
21,619 (5x)

Row count: 1988