Notebooks Coverage

Report on last executions.

77% 2020-02-24

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%	0.079	2020-02-24	centrale/centrale_201606.ipynb	Big Data, Azure, Machine Learning, Python	True	1.806	2	2	2
2	100%	0.083	2020-02-24	centrale/centrale_201606_sysrec.ipynb	Recommandations sur le web	True	0.884	1	1	1
3	100%	0.784	2020-02-24	ensae/2017_1a_ensae_nocture.ipynb	ENSAE 1A : nocturne	True	2.645	10	10	10
4	100%	0.337	2020-02-24	ensae/kaggle_review_2016.ipynb	Revue de compétitions Kaggle (2016)	True	2.251	2	2	2
5	100%	0.329	2020-02-24	ensae/kaggle_review_2017.ipynb	Revue de compétitions Kaggle (2017)	True	2.046	2	2	2
6	0%	nan		ensae_api/sklearn_api.ipynb	API de sciki-learn et modèles customisés		nan	78	0
7	100%	3.316	2020-02-24	meshs/automation_finance_trading.ipynb	Les algorithmes, outils de décision automatique.	True	5.333	10	10	10
8	100%	186.828	2020-02-17	msexp/onnx_deploy.ipynb	Deploy machine learned models with ONNX	True	187.871	77	77	77
9	100%	13.111	2020-02-24	pydata/10_plotting_libraries.ipynb	10 plotting libraries	True	13.957	16	16	16
10	100%	18.493	2020-02-17	pydata/big_datashader.ipynb	datashader	True	19.498	28	28	28
11	80%	1.404	2020-02-17	pydata/gui_geoplotlib.ipynb	geoplotlib	True	2.268	5	4	4
12	100%	1.225	2020-02-24	pydata/im_biopython.ipynb	biopython	True	2.027	6	6	6
13	100%	0.820	2020-02-24	pydata/im_cartopy.ipynb	cartopy	True	1.591	4	4	4
14	100%	4.778	2020-02-17	pydata/im_ete3.ipynb	ete3	True	5.691	11	11	11
15	100%	2.886	2020-02-24	pydata/im_lifelines.ipynb	lifelines	True	3.802	7	7	7
16	90%	1.126	2020-02-24	pydata/im_matplotlib.ipynb	matplotlib	True	1.926	11	10	10
17	100%	4.856	2020-02-24	pydata/im_missingno.ipynb	missingno	True	5.684	13	13	13
18	100%	9.017	2020-02-24	pydata/im_mpl_scatter_density.ipynb	mpl-scatter-density	True	9.869	6	6	6
19	100%	0.850	2020-02-24	pydata/im_networkx.ipynb	networkx	True	2.547	4	4	4
20	100%	6.605	2020-02-24	pydata/im_plotnine.ipynb	plotnine	True	7.406	9	9	9
21	100%	0.524	2020-02-24	pydata/im_reportlab.ipynb	reportlab	True	1.387	4	4	4
22	100%	1.023	2020-02-24	pydata/im_scikit_plot.ipynb	scikit-plot	True	1.794	5	5	5
23	100%	4.655	2020-02-24	pydata/im_seaborn.ipynb	seaborn	True	5.475	5	5	5
24	100%	1.632	2020-02-24	pydata/js_bokeh.ipynb	bokeh	True	3.650	7	7	7
25	50%	0.075	2020-02-24	pydata/js_lightning_python.ipynb	lightning-python	True	1.773	4	2	2
26	0%	nan		pydata/js_mpld3.ipynb	mpld3		nan	17	0
27	100%	9.823	2020-02-24	pydata/js_plotly.ipynb	plotly	True	10.675	9	9	9
28	100%	4.681	2020-02-24	pydata/js_pydy_mass_spring_damper.ipynb	pydy	True	6.469	32	32	32
29	85%	0.822	2020-02-24	pydata/js_pyecharts.ipynb	pyecharts	True	1.600	7	6	6
30	100%	1.006	2020-02-24	pydata/js_pygal.ipynb	pygal	True	1.806	7	7	7
31	100%	1.403	2020-02-24	pydata/js_pythreejs.ipynb	pythreejs	True	2.321	5	5	5
32	100%	0.682	2020-02-24	pydata/js_vega.ipynb	vega	True	1.442	6	6	6
33	100%	0.524	2020-02-24	pydata/jsonly_treant.ipynb	treant-js	True	2.546	7	7	7
34	100%	2.192	2020-02-24	pydata/pyjs_bqplot.ipynb	bqplot	True	3.507	19	19	19
35	100%	1.459	2020-02-24	pydata/pyjs_brython.ipynb	brython, brythonmagic	True	3.288	18	18	18
36	100%	0.925	2020-02-24	pydata/pyjsc_vispy.ipynb	vispy	True	2.636	8	8	8
37	100%	111.583	2020-02-17	pyparis/onnx_deploy_pyparis.ipynb	Deploy machine learned models with ONNX	True	113.164	38	38	38
38	100%	55.212	2020-02-24	sklearn/onnx_sklearn_consortium.ipynb	ONNX, scikit-learn, persistence, deployment	True	57.028	47	47	47
39	100%	2.745	2020-02-24	sklearn/onnx_sklearn_custom.ipynb	Convert custom transformer into ONNX	True	3.589	17	17	17