Table Of Contents
Table Of Contents

Notebooks Coverage

Report on last executions.

75% 2018-10-16

_images/nbcov-2018-10-16.png
index coverage exe time last execution name title success time nb cells nb runs nb valid
0 100% 1.020 2018-10-16 cheat_sheets/chsh_dates.ipynb Cheat Sheet on dates True 3.095 9 9 9
1 100% 15.814 2018-10-09 cheat_sheets/chsh_files.ipynb Cheat Sheet on files True 18.434 21 21 21
2 100% 7.014 2018-10-16 cheat_sheets/chsh_geo.ipynb Cheat sheet on Geocoordinates True 9.094 10 10 10
3 100% 6.966 2018-10-16 cheat_sheets/chsh_graphs.ipynb Cheat Sheet on Graphs True 13.095 8 8 8
4 100% 2.267 2018-10-16 cheat_sheets/chsh_html.ipynb Cheat Sheet on HTML True 6.083 12 12 12
5 100% 2.116 2018-10-16 cheat_sheets/chsh_images.ipynb Images and matrices True 5.089 16 16 16
6 100% 4.917 2018-10-16 cheat_sheets/chsh_pandas.ipynb Uncommon operation with dataframes True 7.092 10 10 10
7 100% 14.019 2018-10-16 cheat_sheets/chsh_pip_install.ipynb Pip install from a notebook True 16.179 8 8 8
8 100% 4.619 2018-10-16 cheat_sheets/image_features.ipynb Image to features True 7.087 5 5 5
9 100% 215.128 2018-10-09 city_bike/bike_chicago.ipynb Chicago True 217.675 18 18 18
10 100% 46.153 2018-10-16 city_bike/bike_seatle.ipynb Seattle True 52.197 16 16 16
11 100% 12.735 2018-10-16 city_bike/business_chicago.ipynb Chicago True 18.109 8 8 8
12 100% 35.300 2018-10-16 city_bike/city_bike_challenge.ipynb City Bike Challenge True 41.457 7 7 7
13 100% 267.364 2018-10-09 city_bike/city_bike_solution.ipynb Ideas on City Bike Challenge True 270.158 25 25 25
14 100% 372.794 2018-10-09 city_bike/city_bike_solution_cluster.ipynb Bike Pattern True 376.278 30 30 30
15 100% 854.309 2018-10-09 city_bike/city_bike_solution_cluster_start.ipynb Bike Pattern 2 True 857.314 36 36 36
16 100% 820.036 2018-10-09 city_bike/city_bike_views.ipynb City Bike Views True 823.905 23 23 23
17 100% 28.164 2018-10-09 city_tour/city_tour_1.ipynb Shortest city tour True 31.242 15 15 15
18 100% 28.410 2018-10-09 city_tour/city_tour_1_solution.ipynb Shortest city tour (solution) True 31.126 7 7 7
19 100% 28.835 2018-10-09 city_tour/city_tour_data_preparation.ipynb Walk through all streets in a city True 31.242 18 18 18
20 100% 190.435 2018-10-09 city_tour/city_tour_long.ipynb Longer city tours True 193.364 6 6 6
21 100% 262.703 2018-10-09 city_tour/city_tour_long_solution.ipynb Longer city tours (solution) True 265.608 12 12 12
22 100% 0.201 2018-10-16 coding_problems/dices_sequence.ipynb Dés en séquences True 5.075 2 2 2
23 0% nan   hackathon_2015/database_schemas.ipynb Database Schemas   nan 58 0  
24 60% 5.361 2018-10-16 hackathon_2015/download_data_azure.ipynb Download data from Azure True 8.190 10 6 6
25 0% nan   hackathon_2015/process_clean_files.ipynb Clean, process dates in text files   nan 13 0  
26 0% nan   hackathon_2015/times_series.ipynb Times Series   nan 27 0  
27 0% nan   hackathon_2015/upload_donnees.ipynb Upload data   nan 23 0  
28 100% 152.384 2018-10-16 knn_kdtree/nearest_neighbours_sparse_features.ipynb Nearest Neighbours and Sparse Features True 156.837 12 12 12
29 100% 11.302 2018-10-09 mlexamples/PCA.ipynb PCA (Principal Component Analysis) True 17.114 31 31 31
30 100% 1055.683 2018-10-09 mlexamples/online_news_popylarity.ipynb OnlineNewPopularity (data from UCI) True 1060.912 42 42 42
31 0% nan   velib/velib_trajectories.ipynb 2A.ml - Déterminer la vitesse moyenne des vélib   nan 14 0  
_images/nbcov.png