Notebooks Coverage

Report on last executions.

78% 2020-06-28

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	100%	0.096	2020-06-28	centrale/centrale_201606.ipynb	Big Data, Azure, Machine Learning, Python	True	0.954	2	2	2
2	100%	0.100	2020-06-28	centrale/centrale_201606_sysrec.ipynb	Recommandations sur le web	True	0.968	1	1	1
3	100%	0.959	2020-06-28	ensae/2017_1a_ensae_nocture.ipynb	ENSAE 1A : nocturne	True	1.836	10	10	10
4	100%	0.373	2020-06-28	ensae/kaggle_review_2016.ipynb	Revue de compétitions Kaggle (2016)	True	1.301	2	2	2
5	100%	0.368	2020-06-28	ensae/kaggle_review_2017.ipynb	Revue de compétitions Kaggle (2017)	True	1.233	2	2	2
6	0%	nan		ensae_api/sklearn_api.ipynb	API de sciki-learn et modèles customisés		nan	78	0
7	100%	3.423	2020-06-28	meshs/automation_finance_trading.ipynb	Les algorithmes, outils de décision automatique.	True	4.314	10	10	10
8	100%	108.828	2020-06-21	msexp/onnx_deploy.ipynb	Deploy machine learned models with ONNX	True	110.164	82	82	82
9	100%	14.995	2020-06-28	pydata/10_plotting_libraries.ipynb	10 plotting libraries	True	15.989	16	16	16
10	100%	14.327	2020-06-21	pydata/big_datashader.ipynb	datashader	True	15.728	28	28	28
11	80%	1.237	2020-06-21	pydata/gui_geoplotlib.ipynb	geoplotlib	True	3.557	5	4	4
12	100%	1.375	2020-06-28	pydata/im_biopython.ipynb	biopython	True	2.269	6	6	6
13	100%	8.293	2020-06-28	pydata/im_cartopy.ipynb	cartopy	True	9.146	4	4	4
14	100%	2.376	2020-06-21	pydata/im_ete3.ipynb	ete3	True	3.562	11	11	11
15	100%	2.440	2020-06-28	pydata/im_lifelines.ipynb	lifelines	True	3.266	7	7	7
16	90%	1.247	2020-06-28	pydata/im_matplotlib.ipynb	matplotlib	True	2.214	11	10	10
17	100%	4.136	2020-06-28	pydata/im_missingno.ipynb	missingno	True	4.990	13	13	13
18	100%	23.267	2020-06-28	pydata/im_mpl_scatter_density.ipynb	mpl-scatter-density	True	24.125	6	6	6
19	100%	0.884	2020-06-28	pydata/im_networkx.ipynb	networkx	True	1.826	4	4	4
20	100%	6.991	2020-06-28	pydata/im_plotnine.ipynb	plotnine	True	7.860	9	9	9
21	100%	0.680	2020-06-28	pydata/im_reportlab.ipynb	reportlab	True	1.488	4	4	4
22	100%	1.209	2020-06-28	pydata/im_scikit_plot.ipynb	scikit-plot	True	2.065	5	5	5
23	100%	4.730	2020-06-28	pydata/im_seaborn.ipynb	seaborn	True	5.644	5	5	5
24	100%	1.397	2020-06-28	pydata/js_bokeh.ipynb	bokeh	True	2.720	7	7	7
25	50%	0.105	2020-06-28	pydata/js_lightning_python.ipynb	lightning-python	True	1.024	4	2	2
26	0%	nan		pydata/js_mpld3.ipynb	mpld3		nan	17	0
27	100%	6.291	2020-06-28	pydata/js_plotly.ipynb	plotly	True	7.232	9	9	9
28	100%	4.132	2020-06-28	pydata/js_pydy_mass_spring_damper.ipynb	pydy	True	5.532	32	32	32
29	85%	0.763	2020-06-28	pydata/js_pyecharts.ipynb	pyecharts	True	1.659	7	6	6
30	100%	1.210	2020-06-28	pydata/js_pygal.ipynb	pygal	True	2.159	7	7	7
31	100%	1.507	2020-06-28	pydata/js_pythreejs.ipynb	pythreejs	True	2.481	5	5	5
32	100%	0.703	2020-06-28	pydata/js_vega.ipynb	vega	True	1.586	6	6	6
33	100%	0.569	2020-06-28	pydata/jsonly_treant.ipynb	treant-js	True	1.949	7	7	7
34	100%	2.527	2020-06-28	pydata/pyjs_bqplot.ipynb	bqplot	True	4.017	19	19	19
35	100%	1.529	2020-06-28	pydata/pyjs_brython.ipynb	brython, brythonmagic	True	2.506	18	18	18
36	100%	1.092	2020-06-28	pydata/pyjsc_vispy.ipynb	vispy	True	2.034	8	8	8
37	100%	52.416	2020-06-21	pyparis/onnx_deploy_pyparis.ipynb	Deploy machine learned models with ONNX	True	53.794	38	38	38
38	100%	29.761	2020-06-28	sklearn/onnx_sklearn_consortium.ipynb	ONNX, scikit-learn, persistence, deployment	True	30.972	47	47	47
39	100%	2.927	2020-06-28	sklearn/onnx_sklearn_custom.ipynb	Convert custom transformer into ONNX	True	3.911	17	17	17