Overview

Dataset statistics

Number of variables13
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory116.3 B

Variable types

Numeric9
DateTime1
Categorical3

Alerts

진동 값(z) is highly overall correlated with 평균 제곱근 오차 값 and 2 other fieldsHigh correlation
평균 제곱근 오차 값 is highly overall correlated with 진동 값(z) and 2 other fieldsHigh correlation
평균 제곱근 편차 값 is highly overall correlated with 진동 값(z) and 2 other fieldsHigh correlation
소음 값 is highly overall correlated with 소음 인덱스 and 2 other fieldsHigh correlation
소음 인덱스 is highly overall correlated with 소음 값 and 2 other fieldsHigh correlation
통합값 is highly overall correlated with 소음 값 and 3 other fieldsHigh correlation
진동 인덱스 is highly overall correlated with 진동 값(z) and 3 other fieldsHigh correlation
통합 인덱스 is highly overall correlated with 소음 값 and 2 other fieldsHigh correlation
진동 인덱스 is highly imbalanced (78.9%)Imbalance
ID has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:17:11.024446
Analysis finished2023-12-10 11:17:29.045747
Duration18.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

ID
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65714225
Minimum64528539
Maximum66151786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:29.179642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum64528539
5-th percentile64602359
Q164676197
median66151736
Q366151761
95-th percentile66151781
Maximum66151786
Range1623247
Interquartile range (IQR)1475564.2

Descriptive statistics

Standard deviation667071.29
Coefficient of variation (CV)0.010151094
Kurtosis-1.0967314
Mean65714225
Median Absolute Deviation (MAD)31
Skewness-0.92148102
Sum6.5714225 × 109
Variance4.4498411 × 1011
MonotonicityStrictly increasing
2023-12-10T20:17:29.472206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64528539 1
 
1.0%
66151751 1
 
1.0%
66151761 1
 
1.0%
66151760 1
 
1.0%
66151759 1
 
1.0%
66151758 1
 
1.0%
66151757 1
 
1.0%
66151756 1
 
1.0%
66151755 1
 
1.0%
66151754 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
64528539 1
1.0%
64558149 1
1.0%
64602356 1
1.0%
64602357 1
1.0%
64602358 1
1.0%
64602359 1
1.0%
64602360 1
1.0%
64602363 1
1.0%
64640515 1
1.0%
64676065 1
1.0%
ValueCountFrequency (%)
66151786 1
1.0%
66151785 1
1.0%
66151784 1
1.0%
66151783 1
1.0%
66151782 1
1.0%
66151781 1
1.0%
66151780 1
1.0%
66151779 1
1.0%
66151778 1
1.0%
66151777 1
1.0%

등록시간
Date

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2019-02-01 00:00:02
Maximum2019-02-24 18:15:21
2023-12-10T20:17:29.801727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:30.105186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

택시 ID
Categorical

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
IK1032
43 
IK1024
12 
IK1043
12 
IK1026
11 
IK1012
11 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIK1032
2nd rowIK1032
3rd rowIK1032
4th rowIK1032
5th rowIK1032

Common Values

ValueCountFrequency (%)
IK1032 43
43.0%
IK1024 12
 
12.0%
IK1043 12
 
12.0%
IK1026 11
 
11.0%
IK1012 11
 
11.0%
IK1014 11
 
11.0%

Length

2023-12-10T20:17:30.365151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:17:30.557114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ik1032 43
43.0%
ik1024 12
 
12.0%
ik1043 12
 
12.0%
ik1026 11
 
11.0%
ik1012 11
 
11.0%
ik1014 11
 
11.0%

진동 값(x)
Real number (ℝ)

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0018310547
Minimum-0.079345703
Maximum0.25585938
Zeros0
Zeros (%)0.0%
Negative53
Negative (%)53.0%
Memory size1.0 KiB
2023-12-10T20:17:30.778896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.079345703
5-th percentile-0.048730469
Q1-0.0090942383
median-0.0029296875
Q30.014404297
95-th percentile0.032275391
Maximum0.25585938
Range0.33520508
Interquartile range (IQR)0.023498535

Descriptive statistics

Standard deviation0.035247539
Coefficient of variation (CV)19.249856
Kurtosis27.18228
Mean0.0018310547
Median Absolute Deviation (MAD)0.013549805
Skewness3.5046023
Sum0.18310547
Variance0.001242389
MonotonicityNot monotonic
2023-12-10T20:17:31.035084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.014404296875 11
 
11.0%
0.0166015625 3
 
3.0%
-0.006103515625 3
 
3.0%
0.004150390625 3
 
3.0%
-0.00927734375 3
 
3.0%
-0.008056640625 2
 
2.0%
-0.007080078125 2
 
2.0%
-0.008544921875 2
 
2.0%
-0.00537109375 2
 
2.0%
-0.0029296875 2
 
2.0%
Other values (65) 67
67.0%
ValueCountFrequency (%)
-0.079345703125 1
1.0%
-0.078857421875 1
1.0%
-0.06689453125 1
1.0%
-0.0625 1
1.0%
-0.060791015625 1
1.0%
-0.048095703125 1
1.0%
-0.034423828125 1
1.0%
-0.033935546875 1
1.0%
-0.031005859375 1
1.0%
-0.02294921875 1
1.0%
ValueCountFrequency (%)
0.255859375 1
1.0%
0.0703125 1
1.0%
0.049560546875 1
1.0%
0.045654296875 1
1.0%
0.033203125 1
1.0%
0.0322265625 1
1.0%
0.030517578125 1
1.0%
0.030029296875 1
1.0%
0.029052734375 1
1.0%
0.02783203125 1
1.0%

진동 값(y)
Real number (ℝ)

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.90625 × 10-5
Minimum-0.10864258
Maximum0.070068359
Zeros0
Zeros (%)0.0%
Negative33
Negative (%)33.0%
Memory size1.0 KiB
2023-12-10T20:17:31.271449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.10864258
5-th percentile-0.039147949
Q1-0.0029907227
median0.00390625
Q30.0068359375
95-th percentile0.024194336
Maximum0.070068359
Range0.17871094
Interquartile range (IQR)0.0098266602

Descriptive statistics

Standard deviation0.023171082
Coefficient of variation (CV)-593.1797
Kurtosis9.7223136
Mean-3.90625 × 10-5
Median Absolute Deviation (MAD)0.0050048828
Skewness-2.0916939
Sum-0.00390625
Variance0.00053689904
MonotonicityNot monotonic
2023-12-10T20:17:31.528963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00390625 13
 
13.0%
0.0068359375 5
 
5.0%
0.0009765625 3
 
3.0%
-0.003662109375 2
 
2.0%
0.005615234375 2
 
2.0%
0.0048828125 2
 
2.0%
-0.0029296875 2
 
2.0%
0.003662109375 2
 
2.0%
0.00830078125 2
 
2.0%
0.00634765625 2
 
2.0%
Other values (65) 65
65.0%
ValueCountFrequency (%)
-0.108642578125 1
1.0%
-0.108154296875 1
1.0%
-0.06884765625 1
1.0%
-0.041015625 1
1.0%
-0.040771484375 1
1.0%
-0.0390625 1
1.0%
-0.031494140625 1
1.0%
-0.02587890625 1
1.0%
-0.024658203125 1
1.0%
-0.022705078125 1
1.0%
ValueCountFrequency (%)
0.070068359375 1
1.0%
0.0537109375 1
1.0%
0.027099609375 1
1.0%
0.026123046875 1
1.0%
0.024658203125 1
1.0%
0.024169921875 1
1.0%
0.023193359375 1
1.0%
0.02197265625 1
1.0%
0.019775390625 1
1.0%
0.019287109375 1
1.0%

진동 값(z)
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24523193
Minimum0.17797852
Maximum0.34106445
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:31.786895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.17797852
5-th percentile0.21712646
Q10.23999023
median0.2442627
Q30.25195312
95-th percentile0.27979736
Maximum0.34106445
Range0.16308594
Interquartile range (IQR)0.011962891

Descriptive statistics

Standard deviation0.019702705
Coefficient of variation (CV)0.080343144
Kurtosis6.7154639
Mean0.24523193
Median Absolute Deviation (MAD)0.0062255859
Skewness0.84262731
Sum24.523193
Variance0.00038819657
MonotonicityNot monotonic
2023-12-10T20:17:32.057742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.24267578125 11
 
11.0%
0.24755859375 3
 
3.0%
0.255615234375 3
 
3.0%
0.2421875 3
 
3.0%
0.250732421875 2
 
2.0%
0.244384765625 2
 
2.0%
0.243896484375 2
 
2.0%
0.245361328125 2
 
2.0%
0.22216796875 2
 
2.0%
0.244140625 2
 
2.0%
Other values (63) 68
68.0%
ValueCountFrequency (%)
0.177978515625 1
1.0%
0.193115234375 1
1.0%
0.20654296875 1
1.0%
0.212158203125 1
1.0%
0.214111328125 1
1.0%
0.21728515625 1
1.0%
0.2177734375 1
1.0%
0.2216796875 1
1.0%
0.22216796875 2
2.0%
0.22265625 1
1.0%
ValueCountFrequency (%)
0.341064453125 1
1.0%
0.29736328125 1
1.0%
0.291015625 1
1.0%
0.28369140625 1
1.0%
0.280029296875 1
1.0%
0.27978515625 1
1.0%
0.2763671875 1
1.0%
0.263671875 1
1.0%
0.261474609375 1
1.0%
0.260498046875 1
1.0%

평균 제곱근 오차 값
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24840743
Minimum0.17925492
Maximum0.39356589
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:32.402848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.17925492
5-th percentile0.21812157
Q10.24145446
median0.24515936
Q30.25417455
95-th percentile0.28158527
Maximum0.39356589
Range0.21431097
Interquartile range (IQR)0.01272009

Descriptive statistics

Standard deviation0.024238131
Coefficient of variation (CV)0.097574096
Kurtosis14.852894
Mean0.24840743
Median Absolute Deviation (MAD)0.006043009
Skewness2.5636396
Sum24.840743
Variance0.00058748699
MonotonicityNot monotonic
2023-12-10T20:17:32.671590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2431342784611489 11
 
11.0%
0.2486570767461656 1
 
1.0%
0.244973919706496 1
 
1.0%
0.2244167663039496 1
 
1.0%
0.2410715294893245 1
 
1.0%
0.2446486413727346 1
 
1.0%
0.2242493771360459 1
 
1.0%
0.2437938210637696 1
 
1.0%
0.2359128724438422 1
 
1.0%
0.2409139805259927 1
 
1.0%
Other values (80) 80
80.0%
ValueCountFrequency (%)
0.1792549233817864 1
1.0%
0.1935040481794495 1
1.0%
0.2129608878281828 1
1.0%
0.2143724300130378 1
1.0%
0.2165252083161086 1
1.0%
0.2182055919602002 1
1.0%
0.2222115610134922 1
1.0%
0.2233379702537429 1
1.0%
0.2242493771360459 1
1.0%
0.2244167663039496 1
1.0%
ValueCountFrequency (%)
0.3935658947884705 1
1.0%
0.3420689834825052 1
1.0%
0.3062397468563257 1
1.0%
0.2843953261604358 1
1.0%
0.2817379639093208 1
1.0%
0.2815772378093725 1
1.0%
0.2798419249031535 1
1.0%
0.2781177519807525 1
1.0%
0.2661685991099638 1
1.0%
0.2653745704895367 1
1.0%

평균 제곱근 편차 값
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.39
Minimum17
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:32.863210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile21
Q124
median24
Q325
95-th percentile28
Maximum39
Range22
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.461399
Coefficient of variation (CV)0.10091837
Kurtosis14.534885
Mean24.39
Median Absolute Deviation (MAD)1
Skewness2.4739588
Sum2439
Variance6.0584848
MonotonicityNot monotonic
2023-12-10T20:17:33.112020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
24 44
44.0%
25 20
20.0%
23 10
 
10.0%
26 7
 
7.0%
22 5
 
5.0%
21 4
 
4.0%
28 3
 
3.0%
27 2
 
2.0%
30 1
 
1.0%
39 1
 
1.0%
Other values (3) 3
 
3.0%
ValueCountFrequency (%)
17 1
 
1.0%
19 1
 
1.0%
21 4
 
4.0%
22 5
 
5.0%
23 10
 
10.0%
24 44
44.0%
25 20
20.0%
26 7
 
7.0%
27 2
 
2.0%
28 3
 
3.0%
ValueCountFrequency (%)
39 1
 
1.0%
34 1
 
1.0%
30 1
 
1.0%
28 3
 
3.0%
27 2
 
2.0%
26 7
 
7.0%
25 20
20.0%
24 44
44.0%
23 10
 
10.0%
22 5
 
5.0%

진동 인덱스
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
95 
4
 
3
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 95
95.0%
4 3
 
3.0%
2 2
 
2.0%

Length

2023-12-10T20:17:33.326962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:17:33.543417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 95
95.0%
4 3
 
3.0%
2 2
 
2.0%

소음 값
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.835
Minimum54.6
Maximum84.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:33.748405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54.6
5-th percentile55.57
Q162.9
median70.3
Q380.6
95-th percentile84.505
Maximum84.6
Range30
Interquartile range (IQR)17.7

Descriptive statistics

Standard deviation9.4165165
Coefficient of variation (CV)0.13293593
Kurtosis-1.2654381
Mean70.835
Median Absolute Deviation (MAD)9
Skewness-0.10518586
Sum7083.5
Variance88.670783
MonotonicityNot monotonic
2023-12-10T20:17:33.992883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.6 12
 
12.0%
67.6 6
 
6.0%
84.6 5
 
5.0%
58.6 4
 
4.0%
63.6 3
 
3.0%
56.6 3
 
3.0%
68.6 3
 
3.0%
54.6 3
 
3.0%
81.0 3
 
3.0%
66.6 3
 
3.0%
Other values (46) 55
55.0%
ValueCountFrequency (%)
54.6 3
3.0%
55.0 2
2.0%
55.6 1
 
1.0%
56.5 1
 
1.0%
56.6 3
3.0%
58.6 4
4.0%
60.0 2
2.0%
60.3 1
 
1.0%
60.6 1
 
1.0%
60.7 1
 
1.0%
ValueCountFrequency (%)
84.6 5
5.0%
84.5 1
 
1.0%
84.3 1
 
1.0%
84.0 1
 
1.0%
83.6 3
 
3.0%
83.0 1
 
1.0%
82.6 1
 
1.0%
81.5 1
 
1.0%
81.0 3
 
3.0%
80.6 12
12.0%

소음 인덱스
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.72
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:34.194976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.8860466
Coefficient of variation (CV)0.39958614
Kurtosis-1.2750643
Mean4.72
Median Absolute Deviation (MAD)2
Skewness-0.15668982
Sum472
Variance3.5571717
MonotonicityNot monotonic
2023-12-10T20:17:34.380411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
7 29
29.0%
4 18
18.0%
3 17
17.0%
2 11
 
11.0%
6 11
 
11.0%
5 11
 
11.0%
1 3
 
3.0%
ValueCountFrequency (%)
1 3
 
3.0%
2 11
 
11.0%
3 17
17.0%
4 18
18.0%
5 11
 
11.0%
6 11
 
11.0%
7 29
29.0%
ValueCountFrequency (%)
7 29
29.0%
6 11
 
11.0%
5 11
 
11.0%
4 18
18.0%
3 17
17.0%
2 11
 
11.0%
1 3
 
3.0%

통합값
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.38
Minimum2
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:17:34.943020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q15
median7.5
Q311
95-th percentile11
Maximum12
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.9328512
Coefficient of variation (CV)0.39740531
Kurtosis-1.2730884
Mean7.38
Median Absolute Deviation (MAD)2.5
Skewness-0.074468628
Sum738
Variance8.6016162
MonotonicityNot monotonic
2023-12-10T20:17:35.168664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
11 28
28.0%
6 18
18.0%
5 17
17.0%
3 11
 
11.0%
8 11
 
11.0%
9 9
 
9.0%
2 3
 
3.0%
10 1
 
1.0%
7 1
 
1.0%
12 1
 
1.0%
ValueCountFrequency (%)
2 3
 
3.0%
3 11
 
11.0%
5 17
17.0%
6 18
18.0%
7 1
 
1.0%
8 11
 
11.0%
9 9
 
9.0%
10 1
 
1.0%
11 28
28.0%
12 1
 
1.0%
ValueCountFrequency (%)
12 1
 
1.0%
11 28
28.0%
10 1
 
1.0%
9 9
 
9.0%
8 11
 
11.0%
7 1
 
1.0%
6 18
18.0%
5 17
17.0%
3 11
 
11.0%
2 3
 
3.0%

통합 인덱스
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
35 
4
30 
3
21 
1
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row4
5th row2

Common Values

ValueCountFrequency (%)
2 35
35.0%
4 30
30.0%
3 21
21.0%
1 14
 
14.0%

Length

2023-12-10T20:17:35.386300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:17:35.570083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 35
35.0%
4 30
30.0%
3 21
21.0%
1 14
 
14.0%

Interactions

2023-12-10T20:17:27.010910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:13.919627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.627735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.595869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.101567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.594436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.112631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.604360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:25.065144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.168106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:14.175086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.819088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.806455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.269178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.763588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.276927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.784056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:25.257139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.319403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:14.347810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.992989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.952056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.419538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.919338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.428554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.964767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:25.438344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.498301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:14.528338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:16.570278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.131660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.594583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.088092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.580783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.126748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:25.746204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.681866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:14.713859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:16.742844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.324228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.779308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.369655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.754363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.304546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:25.921793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.832593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:14.884125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:16.887072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.477154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:19.926933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.510535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:22.911905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.438780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:26.073745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:27.970799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.072671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.032749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.639858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.070480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.650476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.052407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.572866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:26.563541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:28.130936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.250836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.233237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.807404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.242397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.820290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.256963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.730360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:26.709443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:28.289201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:15.418572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:17.417199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:18.953547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:20.425640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:21.975167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:23.446576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:24.913611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:17:26.854813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:17:35.745703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID등록시간택시 ID진동 값(x)진동 값(y)진동 값(z)평균 제곱근 오차 값평균 제곱근 편차 값진동 인덱스소음 값소음 인덱스통합값통합 인덱스
ID1.0001.0000.5570.5200.8020.7500.9290.6720.4330.4680.3290.0840.000
등록시간1.0001.0000.0000.7340.9000.0000.0000.0000.0000.6550.9040.5150.872
택시 ID0.5570.0001.0000.2160.1930.4890.3650.1060.0000.5920.3910.4830.448
진동 값(x)0.5200.7340.2161.0000.7560.5480.7230.7250.7050.0000.0000.0000.000
진동 값(y)0.8020.9000.1930.7561.0000.4960.8450.8300.5700.1950.2120.2330.465
진동 값(z)0.7500.0000.4890.5480.4961.0000.9420.8920.9960.4360.3290.8470.179
평균 제곱근 오차 값0.9290.0000.3650.7230.8450.9421.0000.9911.0000.4570.2630.7190.320
평균 제곱근 편차 값0.6720.0000.1060.7250.8300.8920.9911.0000.9280.2110.2050.7190.000
진동 인덱스0.4330.0000.0000.7050.5700.9961.0000.9281.0000.0000.0000.8910.000
소음 값0.4680.6550.5920.0000.1950.4360.4570.2110.0001.0000.9300.8810.956
소음 인덱스0.3290.9040.3910.0000.2120.3290.2630.2050.0000.9301.0000.9800.943
통합값0.0840.5150.4830.0000.2330.8470.7190.7190.8910.8810.9801.0001.000
통합 인덱스0.0000.8720.4480.0000.4650.1790.3200.0000.0000.9560.9431.0001.000
2023-12-10T20:17:35.985237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통합 인덱스택시 ID진동 인덱스
통합 인덱스1.0000.3000.000
택시 ID0.3001.0000.000
진동 인덱스0.0000.0001.000
2023-12-10T20:17:36.229786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID진동 값(x)진동 값(y)진동 값(z)평균 제곱근 오차 값평균 제곱근 편차 값소음 값소음 인덱스통합값택시 ID진동 인덱스통합 인덱스
ID1.0000.148-0.135-0.213-0.173-0.137-0.0510.005-0.0060.3910.4240.045
진동 값(x)0.1481.000-0.083-0.195-0.234-0.2410.0980.1380.1440.0760.3800.000
진동 값(y)-0.135-0.0831.000-0.115-0.187-0.141-0.133-0.131-0.1600.1040.4240.216
진동 값(z)-0.213-0.195-0.1151.0000.9380.898-0.160-0.155-0.0800.2620.8930.108
평균 제곱근 오차 값-0.173-0.234-0.1870.9381.0000.952-0.151-0.165-0.0900.2080.9740.142
평균 제곱근 편차 값-0.137-0.241-0.1410.8980.9521.000-0.125-0.120-0.0420.0480.9740.000
소음 값-0.0510.098-0.133-0.160-0.151-0.1251.0000.9810.9520.3500.0000.852
소음 인덱스0.0050.138-0.131-0.155-0.165-0.1200.9811.0000.9770.2430.0000.920
통합값-0.0060.144-0.160-0.080-0.090-0.0420.9520.9771.0000.2560.7300.974
택시 ID0.3910.0760.1040.2620.2080.0480.3500.2430.2561.0000.0000.300
진동 인덱스0.4240.3800.4240.8930.9740.9740.0000.0000.7300.0001.0000.000
통합 인덱스0.0450.0000.2160.1080.1420.0000.8520.9200.9740.3000.0001.000

Missing values

2023-12-10T20:17:28.517020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:17:28.868507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

ID등록시간택시 ID진동 값(x)진동 값(y)진동 값(z)평균 제곱근 오차 값평균 제곱근 편차 값진동 인덱스소음 값소음 인덱스통합값통합 인덱스
0645285392019-02-09 08:52:10IK10320.0168460.0043950.2480470.24865724363.6352
1645581492019-02-09 18:59:25IK1032-0.0185550.0219730.2443850.24607124367.5462
2646023562019-02-10 04:40:36IK1032-0.0310060.0231930.2578120.26070426367.6462
3646023572019-02-10 04:40:46IK1032-0.0026860.0009770.2546390.25465525384.57114
4646023582019-02-10 04:40:55IK1032-0.0061040.0019530.2526860.25276725363.6352
5646023592019-02-10 04:41:05IK10320.0019530.0056150.2504880.25055925356.5231
6646023602019-02-10 04:41:16IK1032-0.007080.0039060.2539060.25403525366.6462
7646023632019-02-10 04:41:26IK1032-0.0085450.0012210.2465820.24673324383.67114
8646405152019-02-10 18:41:57IK10320.0703120.0700680.2636720.28173828367.6462
9646760652019-02-11 03:52:59IK1032-0.0090330.024170.2563480.25764325367.6462
ID등록시간택시 ID진동 값(x)진동 값(y)진동 값(z)평균 제곱근 오차 값평균 제곱근 편차 값진동 인덱스소음 값소음 인덱스통합값통합 인덱스
90661517772019-02-01 00:01:36IK10260.0144040.0039060.2426760.24313424380.67114
91661517782019-02-01 00:01:42IK1032-0.0153810.0034180.2575680.2580525355.6231
92661517792019-02-01 00:01:43IK1043-0.006104-0.0031740.2421880.24228524374.0583
93661517802019-02-01 00:01:44IK1024-0.0339360.0039060.2531740.25546825376.6693
94661517812019-02-01 00:01:45IK10140.025635-0.0036620.2475590.24890924381.07114
95661517822019-02-01 00:01:45IK1012-0.019043-0.0061040.2836910.28439528368.6462
96661517832019-02-01 00:01:46IK10260.0144040.0039060.2426760.24313424380.67114
97661517842019-02-01 00:01:52IK1032-0.0788570.0009770.2385250.25122525364.6352
98661517852019-02-01 00:01:53IK10430.012451-0.0097660.2556150.25610525355.0231
99661517862019-02-01 00:01:53IK10240.0056150.0053710.2465820.24670424356.6231