Notebooks Coverage

Report on last executions.

26% 2021-09-26

index	coverage	exe time	last execution	name	title	success	time	nb cells	nb runs	nb valid
0	0%	nan		centrale/azure_pig.ipynb	HDInsight, PIG		nan	35	0
1	0%	nan		centrale/centrale_201606.ipynb	Big Data, Azure, Machine Learning, Python		nan	11	0
2	0%	nan		centrale/centrale_201606_sysrec.ipynb	Recommandations sur le web		nan	17	0
3	0%	nan		ensae/2017_1a_ensae_nocture.ipynb	ENSAE 1A : nocturne		nan	35	0
4	0%	nan		ensae/introcode.ipynb	Leçon de code		nan	90	0
5	0%	nan		ensae/kaggle_review_2016.ipynb	Revue de compétitions Kaggle (2016)		nan	21	0
6	0%	nan		ensae/kaggle_review_2017.ipynb	Revue de compétitions Kaggle (2017)		nan	19	0
7	0%	nan		ensae_api/sklearn_api.ipynb	API de sciki-learn et modèles customisés		nan	78	0
8	0%	nan		meshs/automation_finance_trading.ipynb	Les algorithmes, outils de décision automatique.		nan	42	0
9	0%	nan		msexp/onnx_deploy.ipynb	Deploy machine learned models with ONNX		nan	130	0
10	0%	nan		pydata/10_plotting_libraries.ipynb	10 plotting libraries		nan	84	0
11	0%	nan		pydata/big_datashader.ipynb	datashader		nan	35	0
12	0%	nan		pydata/gui_geoplotlib.ipynb	geoplotlib		nan	8	0
13	100%	2.130	2021-09-26	pydata/im_biopython.ipynb	biopython	True	4.561	6	6	6
14	100%	17.514	2021-09-26	pydata/im_cartopy.ipynb	cartopy	True	19.943	4	4	4
15	0%	nan		pydata/im_ete3.ipynb	ete3		nan	14	0
16	100%	9.417	2021-09-26	pydata/im_lifelines.ipynb	lifelines	True	11.860	7	7	7
17	90%	4.904	2021-09-26	pydata/im_matplotlib.ipynb	matplotlib	True	7.331	11	10	10
18	100%	25.561	2021-09-26	pydata/im_missingno.ipynb	missingno	True	28.030	13	13	13
19	100%	23.910	2021-09-26	pydata/im_mpl_scatter_density.ipynb	mpl-scatter-density	True	26.353	5	5	5
20	100%	3.158	2021-09-26	pydata/im_networkx.ipynb	networkx	True	5.638	4	4	4
21	100%	20.440	2021-09-26	pydata/im_plotnine.ipynb	plotnine	True	22.885	9	9	9
22	100%	1.091	2021-09-26	pydata/im_reportlab.ipynb	reportlab	True	3.539	4	4	4
23	100%	4.171	2021-09-26	pydata/im_scikit_plot.ipynb	scikit-plot	True	6.605	5	5	5
24	100%	20.539	2021-09-26	pydata/im_seaborn.ipynb	seaborn	True	23.205	5	5	5
25	100%	6.192	2021-09-26	pydata/js_bokeh.ipynb	bokeh	True	8.667	7	7	7
26	0%	nan		pydata/js_lightning_python.ipynb	lightning-python		nan	9	0
27	0%	nan		pydata/js_mpld3.ipynb	mpld3		nan	17	0
28	100%	8.617	2021-09-26	pydata/js_plotly.ipynb	plotly	True	11.305	9	9	9
29	100%	9.024	2021-09-26	pydata/js_pydy_mass_spring_damper.ipynb	pydy	True	11.561	32	32	32
30	85%	2.307	2021-09-26	pydata/js_pyecharts.ipynb	pyecharts	True	4.782	7	6	6
31	100%	3.084	2021-09-26	pydata/js_pygal.ipynb	pygal	True	5.648	7	7	7
32	100%	3.502	2021-09-26	pydata/js_pythreejs.ipynb	pythreejs	True	6.729	5	5	5
33	100%	1.350	2021-09-26	pydata/js_vega.ipynb	vega	True	3.804	6	6	6
34	100%	0.759	2021-09-26	pydata/jsonly_treant.ipynb	treant-js	True	3.490	7	7	7
35	100%	5.791	2021-09-26	pydata/pyjs_bqplot.ipynb	bqplot	True	11.271	19	19	19
36	100%	2.013	2021-09-26	pydata/pyjs_brython.ipynb	brython, brythonmagic	True	4.574	18	18	18
37	0%	nan		pydata/pyjsc_vispy.ipynb	vispy		nan	11	0
38	0%	nan		pyparis/onnx_deploy_pyparis.ipynb	Deploy machine learned models with ONNX		nan	70	0
39	100%	56.418	2021-09-26	sklearn/onnx_sklearn_consortium.ipynb	ONNX, scikit-learn, persistence, deployment	True	59.003	47	47	47
40	100%	9.809	2021-09-26	sklearn/onnx_sklearn_custom.ipynb	Convert custom transformer into ONNX	True	12.306	17	17	17

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