README.md

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