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armgilles / vcub_keeper

Analyse de l'activité des stations Vcub dans la métropole de Bordeaux afin de détecter en amont les stations hors service
https://vcubwatcher.herokuapp.com/
MIT License
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Graphique de type map afin de visualiser les station HS ou non ainsi que le nombre de vélo dispo #49

Closed armgilles closed 3 years ago

armgilles commented 3 years ago

Création d'une map afin de pouvoir :

station_id mean_activity is_anomaly is_inactive last_date_anomaly anomaly_since
0 181 0 0 0 NaT NaT
144 6 0.4 0 0 2021-04-07 11:40:00+02:00 NaT
174 102 0.63 0 0 NaT NaT
armgilles commented 3 years ago

Avec l'update de https://github.com/armgilles/vcub_keeper/commit/54b5c28fd67acb64d763255edb5158e3bb040c9b

Notebook : notebooks/02_Features/07_visualisation_map_stations #49.ipynb

Warning

Attention les données de station_control sont simulées et provienne du projet vcub_watcher.

Résultats :

plot_map_station_with_plotly(station_control=station_control, offline_plot=False)

image

# Focus sur une station particulière : 
plot_map_station_with_plotly(station_control=station_control, offline_plot=False, station_id=6)

image

plot_map_station_with_kepler(station_control=station_control)

image

plot_map_station_with_kepler(station_control=station_control, station_id=6)

image

armgilles commented 3 years ago

Prendre en compte dans le preprocess des données des graphiques les stations qui ne sont pas monitorer par les algos afin de pouvoir les afficher d'une certaine couleur (stations avec trop peu d'activités)

Faire attention pour les graphiques liés à KeplerGL, car les couleurs sont liées à l'ordre dans le DataFrame. De plus s’il n'y a pas de station en anomalie ET/OU inactive, cela peut changer les couleurs de l'état de fonctionnement de la station sur le graphique.

armgilles commented 3 years ago

Données de station_control avec l'ajout des vélos dispo sur les stations en provenance du Back de `Vcub_watcher``

Sans anomalie :


simulated_data="""station_id,mean_activity,is_anomaly,is_inactive,last_date_anomaly,anomaly_since,available_bikes
181,0.0,0,0,,,9
160,0.0,0,0,,,4
161,0.01,0,0,,,7
180,0.01,0,0,,,11
92,0.01,0,0,,,7
167,0.01,0,0,,,10
168,0.01,0,0,,,8
183,0.01,0,0,,,9
81,0.02,0,0,,,3
150,0.02,0,0,,,4
72,0.02,0,0,,,0
71,0.02,0,0,,,8
91,0.02,0,0,,,8
80,0.02,0,0,,,3
165,0.02,0,0,,,6
156,0.02,0,0,,,10
157,0.03,0,0,,,6
87,0.03,0,0,,,9
182,0.03,0,0,,,9
93,0.03,0,0,,,9
94,0.03,0,0,,,8
149,0.04,0,0,,,4
82,0.04,0,0,,,2
88,0.05,0,0,,,3
164,0.05,0,0,,,5
76,0.05,0,0,,,12
77,0.05,0,0,,,13
158,0.05,0,0,,,10
148,0.05,0,0,,,11
79,0.05,0,0,,,9
95,0.05,0,0,,,8
151,0.05,0,0,,,8
86,0.06,0,0,,,8
153,0.06,0,0,,,7
159,0.06,0,0,,,11
85,0.06,0,0,,,8
162,0.06,0,0,,,10
169,0.07,0,0,,,7
177,0.07,0,0,,,11
78,0.07,0,0,,,10
147,0.07,0,0,,,11
97,0.07,0,0,,,6
84,0.08,0,0,,,14
163,0.08,0,0,,,6
63,0.09,0,0,,,10
146,0.09,0,0,,,14
166,0.1,0,0,,,13
89,0.1,0,0,,,5
152,0.1,0,0,,,12
143,0.1,0,0,,,8
115,0.1,0,0,,,13
142,0.11,0,0,,,5
64,0.11,0,0,,,4
74,0.12,0,0,,,8
144,0.12,0,0,,,10
51,0.12,0,0,,,6
114,0.13,0,0,,,15
145,0.13,0,0,,,10
83,0.13,0,0,,,6
113,0.13,0,0,,,12
251,0.13,0,0,,,21
38,0.13,0,0,,,13
70,0.14,0,0,,,15
75,0.14,0,0,,,8
175,0.14,0,0,,,14
178,0.16,0,0,,,17
32,0.16,0,0,,,8
12,0.17,0,0,,,10
90,0.17,0,0,,,2
50,0.17,0,0,,,13
49,0.18,0,0,,,10
155,0.18,0,0,,,5
129,0.18,0,0,,,9
52,0.18,0,0,,,12
26,0.18,0,0,,,12
31,0.18,0,0,,,7
29,0.19,0,0,,,7
53,0.2,0,0,,,8
30,0.2,0,0,,,10
154,0.2,0,0,,,11
35,0.2,0,0,,,6
126,0.2,0,0,,,4
176,0.21,0,0,,,6
25,0.21,0,0,,,6
117,0.21,0,0,,,17
122,0.21,0,0,,,4
137,0.21,0,0,,,10
96,0.22,0,0,,,16
73,0.23,0,0,,,12
141,0.23,0,0,,,10
27,0.23,0,0,,,7
69,0.23,0,0,,,11
14,0.23,0,0,,,23
179,0.23,0,0,,,3
47,0.24,0,0,,,6
13,0.24,0,0,,,9
46,0.24,0,0,,,9
116,0.24,0,0,,,22
48,0.24,0,0,,,13
67,0.25,0,0,,,12
121,0.25,0,0,,,5
173,0.25,0,0,,,10
17,0.26,0,0,,,6
140,0.27,0,0,,,2
107,0.27,0,0,,,4
171,0.27,0,0,,,1
33,0.27,0,0,,,0
61,0.27,0,0,,,16
34,0.27,0,0,,,5
170,0.28,0,0,,,0
132,0.28,0,0,,,7
128,0.28,0,0,,,1
119,0.28,0,0,,,16
15,0.29,0,0,,,4
18,0.29,0,0,,,9
124,0.3,0,0,,,3
118,0.3,0,0,2021-04-09 06:50:00+02:00,,14
111,0.31,0,0,,,12
10,0.31,0,0,2021-04-08 07:50:00+02:00,,8
62,0.32,0,0,2021-04-09 07:10:00+02:00,,23
66,0.32,0,0,2021-04-09 07:50:00+02:00,,8
105,0.32,0,0,2021-04-09 05:50:00+02:00,,1
130,0.32,0,0,,,8
112,0.32,0,0,2021-04-08 10:50:00+02:00,,26
2,0.32,0,0,2021-04-09 10:40:00+02:00,,7
68,0.32,0,0,2021-04-08 11:50:00+02:00,,2
23,0.34,0,0,2021-04-08 07:40:00+02:00,,18
11,0.34,0,0,2021-04-08 08:20:00+02:00,,18
60,0.34,0,0,2021-04-08 13:20:00+02:00,,11
120,0.34,0,0,2021-04-08 07:20:00+02:00,,6
9,0.34,0,0,,,8
3,0.35,0,0,,,7
45,0.35,0,0,,,8
136,0.36,0,0,2021-04-08 07:50:00+02:00,,6
24,0.36,0,0,,,7
138,0.36,0,1,,,0
21,0.36,0,0,2021-04-09 08:10:00+02:00,,3
108,0.37,0,0,,,10
16,0.37,0,1,,,0
131,0.37,0,0,,,6
36,0.38,0,0,2021-04-08 07:20:00+02:00,,4
20,0.39,0,0,,,11
110,0.39,0,0,,,14
139,0.39,0,0,,,14
6,0.4,0,0,2021-04-09 08:30:00+02:00,,18
42,0.4,0,0,2021-04-09 07:40:00+02:00,,8
125,0.4,0,0,2021-04-09 09:50:00+02:00,,18
19,0.41,0,0,2021-04-09 09:40:00+02:00,,16
135,0.41,0,0,,,16
59,0.42,0,0,2021-04-09 09:50:00+02:00,,14
41,0.43,0,0,,,5
28,0.44,0,0,,,9
7,0.44,0,0,,,6
109,0.44,0,0,,,10
4,0.44,0,0,,,13
57,0.44,0,0,2021-04-09 08:20:00+02:00,,8
55,0.44,0,0,,,10
37,0.45,0,0,2021-04-09 09:30:00+02:00,,21
8,0.46,0,0,2021-04-08 07:40:00+02:00,,6
58,0.47,0,0,,,9
99,0.48,0,1,,,0
134,0.48,0,0,,,16
104,0.49,0,0,,,7
40,0.49,0,0,2021-04-08 05:40:00+02:00,,19
98,0.49,0,0,,,17
172,0.5,0,0,2021-04-08 10:50:00+02:00,,13
1,0.51,0,0,2021-04-08 10:00:00+02:00,,10
56,0.51,0,0,,,10
43,0.51,0,0,,,8
44,0.53,0,0,,,7
100,0.54,0,0,2021-04-08 08:10:00+02:00,,26
133,0.55,0,0,2021-04-08 07:50:00+02:00,,14
103,0.58,0,0,2021-04-09 08:50:00+02:00,,9
101,0.6,0,0,2021-04-09 08:50:00+02:00,,12
102,0.63,0,0,2021-04-09 07:30:00+02:00,,9
5,0.64,0,0,,,20
65,0.65,0,0,,,11
174,0.67,0,0,,,34
123,0.74,0,0,,,25
54,0.74,0,0,,,9
39,0.82,0,0,2021-04-09 07:30:00+02:00,,22
22,0.82,0,0,2021-04-08 07:30:00+02:00,,23
127,0.9,0,0,2021-04-08 07:20:00+02:00,,2
106,1.03,0,0,,,26
"""
armgilles commented 3 years ago

Avec des stations suspectes :

13/04/21 9H30 : 

station_id,mean_activity,is_anomaly,is_inactive,last_date_anomaly,anomaly_since,available_bikes
181,0.0,0,0,,,9
160,0.0,0,0,,,4
161,0.01,0,0,,,7
180,0.01,0,0,,,11
92,0.01,0,0,,,7
167,0.01,0,0,,,10
168,0.01,0,0,,,8
183,0.01,0,0,,,9
81,0.02,0,0,,,3
150,0.02,0,0,,,4
72,0.02,0,0,,,0
71,0.02,0,0,,,8
91,0.02,0,0,,,8
80,0.02,0,0,,,3
165,0.02,0,0,,,6
156,0.02,0,0,,,10
157,0.03,0,0,,,6
87,0.03,0,0,,,9
182,0.03,0,0,,,9
93,0.03,0,0,,,9
94,0.03,0,0,,,8
149,0.04,0,0,,,4
82,0.04,0,0,,,2
88,0.05,0,0,,,3
164,0.05,0,0,,,5
76,0.05,0,0,,,12
77,0.05,0,0,,,13
158,0.05,0,0,,,10
148,0.05,0,0,,,11
79,0.05,0,0,,,9
95,0.05,0,0,,,8
151,0.05,0,0,,,8
86,0.06,0,0,,,8
153,0.06,0,0,,,7
159,0.06,0,0,,,11
85,0.06,0,0,,,8
162,0.06,0,0,,,10
169,0.07,0,0,,,7
177,0.07,0,0,,,11
78,0.07,0,0,,,10
147,0.07,0,0,,,11
97,0.07,0,0,,,6
84,0.08,0,0,,,14
163,0.08,0,0,,,6
63,0.09,0,0,,,10
146,0.09,0,0,,,14
166,0.1,0,0,,,13
89,0.1,0,0,,,5
152,0.1,0,0,,,12
143,0.1,0,0,,,8
115,0.1,0,0,,,13
142,0.11,0,0,,,5
64,0.11,0,0,,,4
74,0.12,0,0,,,8
144,0.12,0,0,,,10
51,0.12,0,0,,,6
114,0.13,0,0,,,15
145,0.13,0,0,,,10
83,0.13,0,0,,,6
113,0.13,0,0,,,12
251,0.13,0,0,,,21
38,0.13,0,0,,,13
70,0.14,0,0,,,15
75,0.14,0,0,,,8
175,0.14,0,0,,,14
178,0.16,0,0,,,17
32,0.16,0,0,,,8
12,0.17,0,0,,,10
90,0.17,0,0,,,2
50,0.17,0,0,,,13
49,0.18,0,0,,,10
155,0.18,0,0,,,5
129,0.18,0,0,,,9
52,0.18,0,0,,,12
26,0.18,0,0,,,12
31,0.18,0,0,,,7
29,0.19,0,0,,,7
53,0.2,0,0,,,8
30,0.2,0,0,,,10
154,0.2,0,0,,,11
35,0.2,0,0,,,6
126,0.2,0,0,,,4
176,0.21,0,0,,,6
25,0.21,0,0,,,6
117,0.21,0,0,,,17
122,0.21,0,0,,,4
137,0.21,0,0,,,10
96,0.22,0,0,,,16
73,0.23,0,0,,,12
141,0.23,0,0,,,10
27,0.23,0,0,,,7
69,0.23,0,0,,,11
14,0.23,0,0,,,23
179,0.23,0,0,,,3
47,0.24,0,0,,,6
13,0.24,0,0,,,9
46,0.24,0,0,,,9
116,0.24,0,0,,,22
48,0.24,0,0,,,13
67,0.25,0,0,,,12
121,0.25,0,0,,,5
173,0.25,0,0,,,10
17,0.26,0,0,,,6
140,0.27,0,0,,,2
107,0.27,0,0,,,4
171,0.27,0,0,,,1
33,0.27,0,0,,,0
61,0.27,0,0,,,16
34,0.27,0,0,,,5
170,0.28,0,0,,,0
132,0.28,0,0,,,7
128,0.28,0,0,,,1
119,0.28,0,0,,,16
15,0.29,0,0,,,4
18,0.29,0,0,,,9
124,0.3,0,0,2021-04-11 11:30:00+02:00,,3
118,0.3,0,0,2021-04-13 07:50:00+02:00,,14
111,0.31,0,0,2021-04-11 13:10:00+02:00,,12
10,0.31,0,0,2021-04-10 11:50:00+02:00,,8
62,0.32,0,0,2021-04-13 08:10:00+02:00,,23
66,0.32,0,0,2021-04-12 08:20:00+02:00,,8
105,0.32,0,0,2021-04-13 08:30:00+02:00,,1
130,0.32,0,0,,,8
112,0.32,0,0,2021-04-13 08:10:00+02:00,,26
2,0.32,0,0,2021-04-13 07:20:00+02:00,,7
68,0.32,1,0,2021-04-13 09:20:00+02:00,2021-04-13 07:50:00+02:00,2
23,0.34,0,0,2021-04-12 07:30:00+02:00,,18
11,0.34,0,0,2021-04-12 08:20:00+02:00,,18
60,0.34,0,0,2021-04-10 10:30:00+02:00,,11
120,0.34,0,0,2021-04-11 05:50:00+02:00,,6
9,0.34,0,0,2021-04-12 07:40:00+02:00,,8
3,0.35,0,0,2021-04-11 11:10:00+02:00,,7
45,0.35,1,0,2021-04-13 09:20:00+02:00,2021-04-13 06:20:00+02:00,8
136,0.36,0,0,2021-04-11 11:50:00+02:00,,6
24,0.36,0,0,2021-04-12 07:10:00+02:00,,7
138,0.36,0,1,,,0
21,0.36,0,0,2021-04-09 08:10:00+02:00,,3
108,0.37,0,0,,,10
16,0.37,0,0,2021-04-12 05:50:00+02:00,,0
131,0.37,0,0,2021-04-12 07:10:00+02:00,,6
36,0.38,0,0,2021-04-11 11:10:00+02:00,,4
20,0.39,0,0,2021-04-10 10:50:00+02:00,,11
110,0.39,0,0,2021-04-13 08:10:00+02:00,,14
139,0.39,0,0,,,14
6,0.4,0,0,2021-04-12 09:30:00+02:00,,18
42,0.4,0,0,2021-04-12 08:50:00+02:00,,8
125,0.4,0,0,2021-04-12 10:10:00+02:00,,18
19,0.41,0,0,2021-04-09 09:40:00+02:00,,16
135,0.41,0,0,,,16
59,0.42,1,0,2021-04-13 09:20:00+02:00,2021-04-13 08:40:00+02:00,14
41,0.43,0,0,,,5
28,0.44,0,0,2021-04-12 09:00:00+02:00,,9
7,0.44,0,0,,,6
109,0.44,0,0,,,10
4,0.44,0,0,,,13
57,0.44,0,0,2021-04-09 08:20:00+02:00,,8
55,0.44,0,0,,,10
37,0.45,0,0,2021-04-12 08:30:00+02:00,,21
8,0.46,1,0,2021-04-13 09:20:00+02:00,2021-04-13 08:00:00+02:00,6
58,0.47,0,0,2021-04-13 08:40:00+02:00,,9
99,0.48,0,0,2021-04-10 13:20:00+02:00,,0
134,0.48,0,0,2021-04-12 09:30:00+02:00,,16
104,0.49,0,0,,,7
40,0.49,0,0,2021-04-12 05:50:00+02:00,,19
98,0.49,0,0,2021-04-13 06:50:00+02:00,,17
172,0.5,0,0,2021-04-10 10:30:00+02:00,,13
1,0.51,0,0,2021-04-11 10:40:00+02:00,,10
56,0.51,0,0,,,10
43,0.51,0,0,2021-04-12 06:30:00+02:00,,8
44,0.53,0,0,2021-04-12 09:00:00+02:00,,7
100,0.54,0,0,2021-04-12 08:20:00+02:00,,26
133,0.55,0,0,2021-04-13 07:50:00+02:00,,14
103,0.58,0,0,2021-04-11 10:20:00+02:00,,9
101,0.6,0,0,2021-04-12 08:50:00+02:00,,12
102,0.63,0,0,2021-04-12 08:30:00+02:00,,9
5,0.64,0,0,2021-04-10 09:30:00+02:00,,20
65,0.65,0,0,,,11
174,0.67,0,0,2021-04-12 06:20:00+02:00,,34
123,0.74,0,0,,,25
54,0.74,0,0,2021-04-11 09:50:00+02:00,,9
39,0.82,0,0,2021-04-12 06:50:00+02:00,,22
22,0.82,0,0,2021-04-08 07:30:00+02:00,,23
127,0.9,0,0,2021-04-12 06:50:00+02:00,,2
106,1.03,0,0,,,26
armgilles commented 3 years ago

Avec plusieurs types de données simulées, les graphiques réagissent correctement.

armgilles commented 3 years ago

Pour l'intégration des graphique dans vcub_watcher (Cf https://github.com/armgilles/vcub_watcher/issues/35):

Erreur dans la vue global : 

    # Transform date to string
    station_control['anomaly_since_str'] = \
        station_control['anomaly_since'].dt.strftime(date_format='%Y-%m-%d %H:%M')
    station_control['anomaly_since_str'] = station_control['anomaly_since_str'].fillna('-')

station_control est modifié en amont (aide à l'affichage) pour le résultat suivant :

image

Solution :

Si anomaly_since est absent du DataFrame, utilisé la colonne En anomalie depuis.

armgilles commented 3 years ago

Permettre de retourner le graphique (de type Plotly) afin de pouvoir l'afficher dans le front (https://github.com/armgilles/vcub_watcher/issues/35).

armgilles commented 3 years ago

Permettre d'augmenter la taille du graphique à partir de la fonction :

armgilles commented 3 years ago

Done with previous commit.