Notebooks Coverage

Report on last executions.

39% 2018-12-09

_images/nbcov-2018-12-09.png
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  
_images/nbcov.png