Notebooks Coverage

Report on last executions.

89% 2019-06-23

_images/nbcov-2019-06-23.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%

0.076

2019-06-16

centrale/centrale_201606.ipynb

Big Data, Azure, Machine Learning, Python

True

2.027

2

2

2

2

100%

0.093

2019-06-16

centrale/centrale_201606_sysrec.ipynb

Recommandations sur le web

True

2.406

1

1

1

3

100%

1.151

2019-06-16

ensae/2017_1a_ensae_nocture.ipynb

ENSAE 1A : nocturne

True

3.030

10

10

10

4

100%

0.316

2019-06-16

ensae/kaggle_review_2016.ipynb

Revue de compétitions Kaggle (2016)

True

2.047

2

2

2

5

100%

0.320

2019-06-16

ensae/kaggle_review_2017.ipynb

Revue de compétitions Kaggle (2017)

True

2.748

2

2

2

6

100%

3.836

2019-06-16

meshs/automation_finance_trading.ipynb

Les algorithmes, outils de décision automatique.

True

6.036

10

10

10

7

100%

136.313

2019-06-16

msexp/onnx_deploy.ipynb

Deploy machine learned models with ONNX

True

138.311

77

77

77

8

100%

5.796

2019-06-16

pydata/10_plotting_libraries.ipynb

10 plotting libraries

True

8.048

16

16

16

9

100%

15.665

2019-06-16

pydata/big_datashader.ipynb

datashader

True

18.495

28

28

28

10

80%

1.348

2019-06-16

pydata/gui_geoplotlib.ipynb

geoplotlib

True

3.067

5

4

4

11

100%

0.666

2019-06-16

pydata/im_biopython.ipynb

biopython

True

3.063

6

6

6

12

100%

0.793

2019-06-16

pydata/im_cartopy.ipynb

cartopy

True

3.070

4

4

4

13

100%

2.803

2019-06-16

pydata/im_ete3.ipynb

ete3

True

5.277

11

11

11

14

100%

2.265

2019-06-16

pydata/im_lifelines.ipynb

lifelines

True

4.057

7

7

7

15

90%

1.167

2019-06-16

pydata/im_matplotlib.ipynb

matplotlib

True

3.064

11

10

10

16

100%

5.187

2019-06-16

pydata/im_missingno.ipynb

missingno

True

7.083

13

13

13

17

100%

10.521

2019-06-16

pydata/im_mpl_scatter_density.ipynb

mpl-scatter-density

True

13.074

6

6

6

18

100%

0.887

2019-06-16

pydata/im_networkx.ipynb

networkx

True

3.592

4

4

4

19

100%

4.829

2019-06-16

pydata/im_plotnine.ipynb

plotnine

True

7.065

9

9

9

20

100%

0.326

2019-06-16

pydata/im_reportlab.ipynb

reportlab

True

2.060

4

4

4

21

100%

1.059

2019-06-16

pydata/im_scikit_plot.ipynb

scikit-plot

True

3.068

5

5

5

22

100%

5.253

2019-06-16

pydata/im_seaborn.ipynb

seaborn

True

7.078

5

5

5

23

100%

1.048

2019-06-16

pydata/js_bokeh.ipynb

bokeh

True

3.352

7

7

7

24

50%

0.199

2019-06-16

pydata/js_lightning_python.ipynb

lightning-python

True

3.229

4

2

2

25

0%

nan

pydata/js_mpld3.ipynb

mpld3

nan

17

0

26

100%

2.876

2019-06-16

pydata/js_plotly.ipynb

plotly

True

5.154

9

9

9

27

100%

3.701

2019-06-16

pydata/js_pydy_mass_spring_damper.ipynb

pydy

True

6.686

32

32

32

28

85%

0.458

2019-06-16

pydata/js_pyecharts.ipynb

pyecharts

True

3.066

7

6

6

29

100%

0.974

2019-06-16

pydata/js_pygal.ipynb

pygal

True

3.077

7

7

7

30

100%

1.743

2019-06-16

pydata/js_pythreejs.ipynb

pythreejs

True

4.073

5

5

5

31

100%

0.634

2019-06-16

pydata/js_vega.ipynb

vega

True

3.050

6

6

6

32

100%

2.554

2019-06-16

pydata/jsonly_treant.ipynb

treant-js

True

5.049

7

7

7

33

100%

4.527

2019-06-16

pydata/pyjs_bqplot.ipynb

bqplot

True

7.042

19

19

19

34

100%

2.406

2019-06-16

pydata/pyjs_brython.ipynb

brython, brythonmagic

True

6.688

18

18

18

35

100%

0.692

2019-06-16

pydata/pyjsc_vispy.ipynb

vispy

True

3.350

8

8

8

36

100%

71.715

2019-06-16

pyparis/onnx_deploy_pyparis.ipynb

Deploy machine learned models with ONNX

True

74.461

38

38

38

37

100%

24.857

2019-06-16

sklearn/onnx_sklearn_consortium.ipynb

ONNX, scikit-learn, persistence, deployment

True

27.662

46

46

46

38

100%

2.695

2019-06-16

sklearn/onnx_sklearn_custom.ipynb

Convert custom transformer into ONNX

True

5.082

17

17

17

_images/nbcov.png