Notebooks Coverage

Report on last executions.

30% 2022-05-19

_images/nbcov-2022-05-19.png

index

coverage

exe time

last execution

name

title

success

time

nb cells

nb runs

nb valid

0

100%

21.544

2022-04-23

api_rest/rest_api_search_images.ipynb

Search engines for images through a REST API

True

25.899

14

14

14

1

100%

0.813

2022-05-19

cheat_sheets/chsh_dates.ipynb

Cheat Sheet on dates

True

4.714

9

9

9

2

100%

12.265

2022-04-23

cheat_sheets/chsh_files.ipynb

Cheat Sheet on files

True

17.531

21

21

21

3

100%

4.361

2022-05-19

cheat_sheets/chsh_geo.ipynb

Cheat sheet on Geocoordinates

True

8.327

10

10

10

4

100%

6.264

2022-05-19

cheat_sheets/chsh_graphs.ipynb

Cheat Sheet on Graphs

True

10.225

8

8

8

5

100%

2.110

2022-05-19

cheat_sheets/chsh_html.ipynb

Cheat Sheet on HTML

True

6.040

12

12

12

6

100%

2.152

2022-05-19

cheat_sheets/chsh_images.ipynb

Images and matrices

True

6.073

18

18

18

7

100%

3.738

2022-05-19

cheat_sheets/chsh_pandas.ipynb

Uncommon operation with dataframes

True

7.653

10

10

10

8

100%

18.070

2022-05-19

cheat_sheets/chsh_pip_install.ipynb

Pip install from a notebook

True

22.353

8

8

8

9

100%

4.123

2022-05-19

cheat_sheets/image_features.ipynb

Image to features

True

7.998

5

5

5

10

0%

nan

city_bike/bike_chicago.ipynb

Chicago

nan

22

0

11

100%

31.012

2022-05-19

city_bike/bike_seatle.ipynb

Seattle

True

34.971

16

16

16

12

100%

31.416

2022-05-19

city_bike/business_chicago.ipynb

Chicago

True

35.203

8

8

8

13

100%

25.954

2022-05-19

city_bike/city_bike_challenge.ipynb

City Bike Challenge

True

29.927

7

7

7

14

0%

nan

city_bike/city_bike_solution.ipynb

Ideas on City Bike Challenge

nan

36

0

15

0%

nan

city_bike/city_bike_solution_cluster.ipynb

Bike Pattern

nan

44

0

16

0%

nan

city_bike/city_bike_solution_cluster_start.ipynb

Bike Pattern 2

nan

51

0

17

0%

nan

city_bike/city_bike_views.ipynb

City Bike Views

nan

31

0

18

0%

nan

city_tour/city_tour_1.ipynb

Shortest city tour

nan

27

0

19

0%

nan

city_tour/city_tour_1_solution.ipynb

Shortest city tour (solution)

nan

11

0

20

0%

nan

city_tour/city_tour_data_preparation.ipynb

Walk through all streets in a city

nan

26

0

21

0%

nan

city_tour/city_tour_long.ipynb

Longer city tours

nan

10

0

22

0%

nan

city_tour/city_tour_long_solution.ipynb

Longer city tours (solution)

nan

16

0

23

100%

0.196

2022-05-19

coding_problems/dices_sequence.ipynb

Dés en séquences

True

5.077

2

2

2

24

0%

nan

hackathon_2015/database_schemas.ipynb

Database Schemas

nan

58

0

25

60%

5.593

2022-05-19

hackathon_2015/download_data_azure.ipynb

Download data from Azure

True

10.183

10

6

6

26

0%

nan

hackathon_2015/process_clean_files.ipynb

Clean, process dates in text files

nan

13

0

27

0%

nan

hackathon_2015/times_series.ipynb

Times Series

nan

27

0

28

0%

nan

hackathon_2015/upload_donnees.ipynb

Upload data

nan

23

0

29

0%

nan

hackathon_2018/baseline_images_keras.ipynb

Exemple pour reconnaissance des inondations

nan

23

0

30

0%

nan

hackathon_2018/donnees_insee.ipynb

Données INSEE

nan

26

0

31

0%

nan

hackathon_2018/images_dups.ipynb

Image et doublons

nan

40

0

32

0%

nan

hackathon_2018/images_gets.ipynb

Récupération d’images avec Bing

nan

28

0

33

0%

nan

hackathon_2022/traitement_du_son.ipynb

Son

nan

25

0

34

100%

31.522

2022-05-19

knn_kdtree/nearest_neighbours_sparse_features.ipynb

Nearest Neighbours and Sparse Features

True

35.811

12

12

12

35

100%

17.087

2022-04-23

mlexamples/PCA.ipynb

PCA (Principal Component Analysis)

True

23.676

31

31

31

36

100%

986.719

2022-04-23

mlexamples/online_news_popylarity.ipynb

OnlineNewPopularity (data from UCI)

True

992.701

44

44

44

37

0%

nan

velib/velib_trajectories.ipynb

2A.ml - Déterminer la vitesse moyenne des vélib

nan

14

0

_images/nbcov.png