Notebooks Coverage

Report on last executions.

39% 2018-12-09

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%	0.141	2018-12-09	centrale/centrale_201606.ipynb	Big Data, Azure, Machine Learning, Python	True	3.080	2	2	2
2	100%	0.148	2018-12-09	centrale/centrale_201606_sysrec.ipynb	Recommandations sur le web	True	4.079	1	1	1
3	100%	1.708	2018-12-09	ensae/2017_1a_ensae_nocture.ipynb	ENSAE 1A : nocturne	True	7.095	11	11	11
4	100%	0.960	2018-12-09	ensae/kaggle_review_2016.ipynb	Revue de compétitions Kaggle (2016)	True	7.174	2	2	2
5	100%	0.937	2018-12-09	ensae/kaggle_review_2017.ipynb	Revue de compétitions Kaggle (2017)	True	7.275	2	2	2
6	100%	14.563	2018-12-09	meshs/automation_finance_trading.ipynb	Les algorithmes, outils de décision automatique.	True	17.105	10	10	10
7	0%	nan		msexp/onnx_deploy.ipynb	Deploy machine learned models with ONNX		nan	169	0
8	100%	20.612	2018-12-09	pydata/10_plotting_libraries.ipynb	10 plotting libraries	True	23.135	16	16	16
9	100%	41.057	2018-11-18	pydata/big_datashader.ipynb	datashader	True	44.516	28	28	28
10	80%	2.101	2018-12-09	pydata/gui_geoplotlib.ipynb	geoplotlib	True	4.205	5	4	4
11	100%	1.458	2018-12-09	pydata/im_biopython.ipynb	biopython	True	4.086	6	6	6
12	100%	4.513	2018-12-09	pydata/im_cartopy.ipynb	cartopy	True	7.093	4	4	4
13	0%	nan		pydata/im_ete3.ipynb	ete3		nan	14	0
14	100%	2.466	2018-12-09	pydata/im_ggplot.ipynb	ggplot	True	9.094	3	3	3
15	100%	7.262	2018-12-09	pydata/im_lifelines.ipynb	lifelines	True	10.100	7	7	7
16	90%	3.700	2018-12-09	pydata/im_matplotlib.ipynb	matplotlib	True	6.093	11	10	10
17	100%	18.521	2018-12-09	pydata/im_missingno.ipynb	missingno	True	21.118	13	13	13
18	100%	49.848	2018-12-09	pydata/im_mpl_scatter_density.ipynb	mpl-scatter-density	True	52.336	6	6	6
19	100%	3.828	2018-12-09	pydata/im_networkx.ipynb	networkx	True	7.094	4	4	4
20	100%	16.287	2018-12-09	pydata/im_plotnine.ipynb	plotnine	True	19.117	9	9	9
21	100%	1.454	2018-12-09	pydata/im_reportlab.ipynb	reportlab	True	4.087	4	4	4
22	100%	5.244	2018-12-09	pydata/im_scikit_plot.ipynb	scikit-plot	True	8.098	5	5	5
23	100%	13.449	2018-12-09	pydata/im_seaborn.ipynb	seaborn	True	16.110	5	5	5
24	100%	6.180	2018-12-09	pydata/js_bokeh.ipynb	bokeh	True	10.196	7	7	7
25	50%	0.150	2018-12-09	pydata/js_lightning_python.ipynb	lightning-python	True	5.237	4	2	2
26	0%	nan		pydata/js_mpld3.ipynb	mpld3		nan	17	0
27	100%	12.484	2018-12-09	pydata/js_plotly.ipynb	plotly	True	15.123	13	13	13
28	0%	nan		pydata/js_pydy_mass_spring_damper.ipynb	pydy		nan	60	0
29	80%	1.648	2018-12-09	pydata/js_pyecharts.ipynb	pyecharts	True	4.148	5	4	4
30	100%	3.132	2018-12-09	pydata/js_pygal.ipynb	pygal	True	6.107	7	7	7
31	100%	4.976	2018-12-09	pydata/js_pythreejs.ipynb	pythreejs	True	8.102	5	5	5
32	100%	2.188	2018-12-09	pydata/js_vega.ipynb	vega	True	5.216	6	6	6
33	100%	1.214	2018-12-09	pydata/jsonly_treant.ipynb	treant-js	True	4.085	7	7	7
34	100%	5.861	2018-12-09	pydata/pyjs_bqplot.ipynb	bqplot	True	11.133	19	19	19
35	100%	2.223	2018-12-09	pydata/pyjs_brython.ipynb	brython, brythonmagic	True	9.257	18	18	18
36	100%	1.492	2018-12-09	pydata/pyjsc_vispy.ipynb	vispy	True	4.078	8	8	8
37	0%	nan		pyparis/onnx_deploy_pyparis.ipynb	Deploy machine learned models with ONNX		nan	80	0