In [1]:
import os; os.sys.path.append(os.path.dirname(os.path.abspath('.'))) # for relative imports
from utils.nab_data import NABData
import numpy as np
import pandas as pd
In [2]:
data = NABData()
In [3]:
data.summary()
Out[3]:
file
length
features
period
periods_vary
min
max
mean
std
25th_percentile
50th_percentile
75th_percentile
0
Twitter_volume_IBM
15893
1
5m
1
0.00
1.390000e+02
4.39
5.50
1.00
3.00
6.00
1
Twitter_volume_CVS
15853
1
5m
1
0.00
5.000000e+01
0.36
1.09
0.00
0.00
0.00
2
Twitter_volume_AMZN
15831
1
5m
1
0.00
1.673000e+03
53.30
30.55
36.00
50.00
65.00
3
Twitter_volume_UPS
15866
1
5m
1
0.00
2.310000e+02
5.46
21.57
0.00
2.00
4.00
4
Twitter_volume_CRM
15902
1
5m
1
0.00
2.090000e+02
3.35
4.61
1.00
2.00
5.00
5
Twitter_volume_FB
15833
1
5m
1
0.00
1.258000e+03
17.81
19.74
9.00
14.00
22.00
6
Twitter_volume_AAPL
15902
1
5m
1
0.00
1.347900e+04
85.55
321.05
29.00
47.00
76.00
7
Twitter_volume_GOOG
15842
1
5m
1
0.00
4.650000e+02
20.74
18.56
11.00
16.00
26.00
8
Twitter_volume_PFE
15858
1
5m
1
0.00
3.600000e+01
0.87
1.46
0.00
0.00
1.00
9
Twitter_volume_KO
15851
1
5m
1
0.00
2.241000e+03
11.40
24.80
5.00
8.00
13.00
10
art_noisy
4032
1
5m
1
8.00
1.900000e+01
13.49
3.15
10.79
13.45
16.23
11
art_daily_small_noise
4032
1
5m
1
18.00
8.798000e+01
42.44
28.08
19.84
21.61
75.45
12
art_flatline
4032
1
5m
1
45.00
4.500000e+01
45.00
0.00
45.00
45.00
45.00
13
art_daily_perfect_square_wave
4032
1
5m
1
20.00
8.000000e+01
42.50
29.05
20.00
20.00
80.00
14
art_daily_no_noise
4032
1
5m
1
20.00
8.000000e+01
42.50
27.95
20.00
20.29
79.62
15
exchange-4_cpm_results
1643
1
1h
0
0.12
1.644000e+01
0.53
0.75
0.36
0.47
0.58
16
exchange-4_cpc_results
1643
1
1h
0
0.02
3.130000e+00
0.09
0.13
0.06
0.07
0.10
17
exchange-3_cpc_results
1538
1
1h
0
0.04
1.030000e+00
0.14
0.08
0.10
0.12
0.15
18
exchange-2_cpm_results
1624
1
1h
0
0.00
1.050000e+00
0.34
0.16
0.21
0.30
0.46
19
exchange-3_cpm_results
1538
1
1h
0
0.32
5.500000e+00
0.77
0.34
0.56
0.70
0.90
20
exchange-2_cpc_results
1624
1
1h
0
0.03
2.300000e-01
0.10
0.03
0.08
0.10
0.12
21
art_daily_nojump
4032
1
5m
1
18.00
8.797000e+01
40.82
27.64
19.70
21.38
74.79
22
art_load_balancer_spikes
4032
1
5m
1
0.00
3.220000e+00
0.11
0.44
0.00
0.00
0.00
23
art_daily_jumpsdown
4032
1
5m
1
18.00
8.800000e+01
41.51
27.51
19.99
21.64
74.86
24
art_daily_flatmiddle
4032
1
5m
1
-22.00
8.796000e+01
18.98
45.37
-19.93
-17.54
74.43
25
art_daily_jumpsup
4032
1
5m
1
18.00
1.649500e+02
44.49
32.43
19.99
21.65
76.44
26
art_increase_spike_density
4032
1
5m
1
0.00
2.000000e+01
0.42
2.87
0.00
0.00
0.00
27
TravelTime_451
2162
1
10m
0
22.00
5.578000e+03
327.22
444.74
146.00
203.00
332.00
28
occupancy_t4013
2500
1
5m
0
0.00
4.306000e+01
7.24
4.37
4.06
6.83
9.83
29
TravelTime_387
2500
1
14m
0
9.00
5.059000e+03
325.09
399.56
133.00
201.00
366.00
30
speed_t4013
2495
1
5m
0
11.00
7.700000e+01
62.93
5.19
61.00
63.00
65.00
31
speed_7578
1127
1
5m
0
1.00
9.000000e+01
64.05
9.24
63.00
66.00
68.00
32
speed_6005
2500
1
10m
0
20.00
1.090000e+02
81.91
8.75
77.00
82.00
88.00
33
occupancy_6005
2380
1
5m
0
0.00
2.228000e+01
4.50
3.40
1.94
3.83
6.17
34
rogue_agent_key_updown
5315
1
5m
0
0.00
2.882100e+02
0.49
5.37
0.00
0.00
0.00
35
ambient_temperature_system_failure
7267
1
1h
0
57.46
8.622000e+01
71.24
4.25
68.37
71.86
74.43
36
ec2_request_latency_system_failure
4032
1
5m
0
22.86
9.925000e+01
45.16
2.29
43.94
45.02
46.36
37
rogue_agent_key_hold
1882
1
5m
0
0.00
9.000000e-01
0.04
0.06
0.00
0.00
0.07
38
nyc_taxi
10320
1
30m
1
8.00
3.919700e+04
15137.57
6939.50
10262.00
16778.00
19838.75
39
machine_temperature_system_failure
22695
1
5m
0
2.08
1.085100e+02
85.93
13.75
83.08
89.41
94.02
40
cpu_utilization_asg_misconfiguration
18050
1
5m
1
11.53
1.000000e+02
38.28
15.64
30.79
32.00
35.66
41
ec2_disk_write_bytes_c0d644
4032
1
5m
1
0.00
8.639640e+08
17331273.32
79696644.73
0.00
0.00
0.00
42
iio_us-east-1_i-a2eb1cd9_NetworkIn
1243
1
5m
1
789781.00
6.151940e+07
4615221.91
4534241.67
2576003.70
3795175.80
5152488.80
43
rds_cpu_utilization_e47b3b
4032
1
5m
1
12.63
7.623000e+01
18.93
5.61
15.84
16.68
25.52
44
ec2_cpu_utilization_ac20cd
4032
1
5m
0
2.46
9.974000e+01
40.99
21.92
33.15
34.66
37.63
45
grok_asg_anomaly
4621
1
5m
1
0.00
4.562000e+01
27.68
13.14
33.33
33.44
33.56
46
ec2_cpu_utilization_c6585a
4032
1
5m
1
0.06
1.600000e+00
0.09
0.09
0.07
0.07
0.07
47
ec2_network_in_5abac7
4730
1
5m
0
42.00
8.285420e+06
118714.64
775718.73
42.00
68.40
108.00
48
ec2_cpu_utilization_5f5533
4032
1
5m
1
34.77
6.809000e+01
43.11
4.30
39.30
42.92
46.01
49
ec2_disk_write_bytes_1ef3de
4730
1
5m
0
0.00
5.474570e+08
6581560.77
40385680.18
0.00
0.00
0.00
50
ec2_cpu_utilization_53ea38
4032
1
5m
1
1.60
2.660000e+00
1.83
0.10
1.77
1.80
1.87
51
ec2_cpu_utilization_825cc2
4032
1
5m
0
18.72
9.912000e+01
89.79
12.08
89.08
92.45
94.30
52
ec2_cpu_utilization_fe7f93
4032
1
5m
1
1.80
9.967000e+01
5.78
11.81
2.18
2.58
3.43
53
ec2_cpu_utilization_77c1ca
4032
1
5m
1
0.06
9.990000e+01
10.52
26.93
0.10
0.10
0.10
54
rds_cpu_utilization_cc0c53
4032
1
5m
0
5.19
2.510000e+01
8.11
3.65
6.01
6.08
7.10
55
ec2_cpu_utilization_24ae8d
4032
1
5m
1
0.07
2.340000e+00
0.13
0.09
0.13
0.13
0.13
56
ec2_network_in_257a54
4032
1
5m
0
38516.60
2.451260e+08
570809.85
4607792.94
219341.75
234245.50
251774.75
57
elb_request_count_8c0756
4032
1
5m
0
1.00
6.560000e+02
61.84
56.66
15.00
48.00
89.00
In [4]:
data.summary().mean()
Out[4]:
length 6302.724138
features 1.000000
periods_vary 0.568966
min 14288.386552
max 29765940.068276
mean 504046.179310
std 2241530.442241
25th_percentile 48393.902414
50th_percentile 69788.306897
75th_percentile 93561.236034
dtype: float64
In [ ]:
Content source: jonathanstrong/NAB
Similar notebooks: