Overview

Dataset statistics

Number of variables10
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory88.3 B

Variable types

Numeric7
Categorical2
DateTime1

Alerts

게이트웨이ID has constant value ""Constant
ID is highly overall correlated with 위도 값 and 2 other fieldsHigh correlation
위도 값 is highly overall correlated with ID and 1 other fieldsHigh correlation
속도 is highly overall correlated with ID and 1 other fieldsHigh correlation
노드ID is highly overall correlated with IDHigh correlation
노드ID is highly imbalanced (56.4%)Imbalance
ID has unique valuesUnique
시간 has unique valuesUnique
진동 값(y) has 6 (6.0%) zerosZeros
속도 has 33 (33.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:03:59.796830
Analysis finished2023-12-10 13:04:05.592199
Duration5.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61571607
Minimum60307011
Maximum62866002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:04:05.662943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60307011
5-th percentile60307018
Q161286958
median61478858
Q362534773
95-th percentile62833822
Maximum62866002
Range2558991
Interquartile range (IQR)1247815.5

Descriptive statistics

Standard deviation842133.35
Coefficient of variation (CV)0.0136773
Kurtosis-1.0805872
Mean61571607
Median Absolute Deviation (MAD)1055906.5
Skewness-0.084382967
Sum6.1571607 × 109
Variance7.0918858 × 1011
MonotonicityStrictly increasing
2023-12-10T22:04:06.039611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60307011 1
 
1.0%
61753921 1
 
1.0%
62534770 1
 
1.0%
62534767 1
 
1.0%
62534766 1
 
1.0%
62534765 1
 
1.0%
62534764 1
 
1.0%
62534763 1
 
1.0%
61813298 1
 
1.0%
61813297 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
60307011 1
1.0%
60307012 1
1.0%
60307013 1
1.0%
60307014 1
1.0%
60307015 1
1.0%
60307018 1
1.0%
60307029 1
1.0%
60307040 1
1.0%
60307051 1
1.0%
60307062 1
1.0%
ValueCountFrequency (%)
62866002 1
1.0%
62866001 1
1.0%
62866000 1
1.0%
62865999 1
1.0%
62865998 1
1.0%
62832129 1
1.0%
62769109 1
1.0%
62769108 1
1.0%
62651694 1
1.0%
62597945 1
1.0%

게이트웨이ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
SERVER
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
SERVER 100
100.0%

Length

2023-12-10T22:04:06.155448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:04:06.240269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
server 100
100.0%

시간
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2019-01-01 10:04:46
Maximum2019-01-23 09:09:34
2023-12-10T22:04:06.334893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:06.488262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

노드ID
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
IK1012
91 
IK1032
 
9

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIK1012
2nd rowIK1012
3rd rowIK1012
4th rowIK1012
5th rowIK1012

Common Values

ValueCountFrequency (%)
IK1012 91
91.0%
IK1032 9
 
9.0%

Length

2023-12-10T22:04:06.618022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:04:06.715749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ik1012 91
91.0%
ik1032 9
 
9.0%

진동 값(x)
Real number (ℝ)

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.011364746
Minimum-0.074707031
Maximum0.1105957
Zeros0
Zeros (%)0.0%
Negative86
Negative (%)86.0%
Memory size1.0 KiB
2023-12-10T22:04:06.817326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.074707031
5-th percentile-0.028076172
Q1-0.018615723
median-0.014038086
Q3-0.0094604492
95-th percentile0.020056152
Maximum0.1105957
Range0.18530273
Interquartile range (IQR)0.0091552734

Descriptive statistics

Standard deviation0.021401219
Coefficient of variation (CV)-1.8831234
Kurtosis13.049125
Mean-0.011364746
Median Absolute Deviation (MAD)0.0046386719
Skewness2.3446016
Sum-1.1364746
Variance0.00045801218
MonotonicityNot monotonic
2023-12-10T22:04:06.945305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.01416015625 6
 
6.0%
-0.012939453125 3
 
3.0%
-0.017333984375 3
 
3.0%
-0.013671875 3
 
3.0%
-0.014892578125 3
 
3.0%
-0.013916015625 3
 
3.0%
-0.019287109375 3
 
3.0%
-0.013427734375 3
 
3.0%
-0.011962890625 3
 
3.0%
-0.0166015625 3
 
3.0%
Other values (61) 67
67.0%
ValueCountFrequency (%)
-0.07470703125 1
1.0%
-0.06640625 1
1.0%
-0.050048828125 1
1.0%
-0.041259765625 1
1.0%
-0.03271484375 1
1.0%
-0.02783203125 1
1.0%
-0.027587890625 2
2.0%
-0.027099609375 1
1.0%
-0.026611328125 1
1.0%
-0.025146484375 1
1.0%
ValueCountFrequency (%)
0.110595703125 1
1.0%
0.068359375 1
1.0%
0.055419921875 1
1.0%
0.026123046875 1
1.0%
0.020751953125 1
1.0%
0.02001953125 1
1.0%
0.01123046875 1
1.0%
0.01025390625 1
1.0%
0.0078125 1
1.0%
0.0068359375 1
1.0%

진동 값(y)
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0038867187
Minimum-0.082763672
Maximum0.10644531
Zeros6
Zeros (%)6.0%
Negative24
Negative (%)24.0%
Memory size1.0 KiB
2023-12-10T22:04:07.078131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.082763672
5-th percentile-0.0069335937
Q10
median0.0032958984
Q30.0068969727
95-th percentile0.017810059
Maximum0.10644531
Range0.18920898
Interquartile range (IQR)0.0068969727

Descriptive statistics

Standard deviation0.01626937
Coefficient of variation (CV)4.1858882
Kurtosis23.59573
Mean0.0038867187
Median Absolute Deviation (MAD)0.0035400391
Skewness0.86006174
Sum0.38867188
Variance0.0002646924
MonotonicityNot monotonic
2023-12-10T22:04:07.205211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6
 
6.0%
0.00439453125 5
 
5.0%
0.001708984375 5
 
5.0%
-0.0009765625 4
 
4.0%
0.002685546875 3
 
3.0%
0.003662109375 3
 
3.0%
0.00244140625 3
 
3.0%
-0.002197265625 3
 
3.0%
0.004638671875 3
 
3.0%
0.003173828125 3
 
3.0%
Other values (54) 62
62.0%
ValueCountFrequency (%)
-0.082763671875 1
1.0%
-0.0380859375 1
1.0%
-0.034423828125 1
1.0%
-0.0107421875 1
1.0%
-0.0087890625 1
1.0%
-0.0068359375 1
1.0%
-0.00537109375 1
1.0%
-0.00439453125 1
1.0%
-0.004150390625 1
1.0%
-0.00390625 1
1.0%
ValueCountFrequency (%)
0.1064453125 1
1.0%
0.03759765625 1
1.0%
0.024169921875 1
1.0%
0.022705078125 1
1.0%
0.022216796875 1
1.0%
0.017578125 1
1.0%
0.0166015625 1
1.0%
0.014892578125 1
1.0%
0.0146484375 2
2.0%
0.014404296875 1
1.0%

진동 값(z)
Real number (ℝ)

Distinct54
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24880371
Minimum0.22949219
Maximum0.27026367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:04:07.342625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.22949219
5-th percentile0.24189453
Q10.24560547
median0.24841309
Q30.25195312
95-th percentile0.25689697
Maximum0.27026367
Range0.040771484
Interquartile range (IQR)0.0063476562

Descriptive statistics

Standard deviation0.0057774738
Coefficient of variation (CV)0.023221011
Kurtosis3.4486426
Mean0.24880371
Median Absolute Deviation (MAD)0.0030517578
Skewness0.10500024
Sum24.880371
Variance3.3379203 × 10-5
MonotonicityNot monotonic
2023-12-10T22:04:07.487332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.24951171875 5
 
5.0%
0.245361328125 5
 
5.0%
0.24560546875 5
 
5.0%
0.242919921875 4
 
4.0%
0.248046875 4
 
4.0%
0.250244140625 3
 
3.0%
0.2529296875 3
 
3.0%
0.2470703125 3
 
3.0%
0.247314453125 3
 
3.0%
0.252685546875 3
 
3.0%
Other values (44) 62
62.0%
ValueCountFrequency (%)
0.2294921875 1
 
1.0%
0.229736328125 1
 
1.0%
0.236572265625 1
 
1.0%
0.23779296875 1
 
1.0%
0.240966796875 1
 
1.0%
0.241943359375 1
 
1.0%
0.242919921875 4
4.0%
0.2431640625 1
 
1.0%
0.24365234375 1
 
1.0%
0.244140625 2
2.0%
ValueCountFrequency (%)
0.270263671875 1
1.0%
0.263916015625 1
1.0%
0.263427734375 1
1.0%
0.26025390625 1
1.0%
0.258056640625 1
1.0%
0.2568359375 1
1.0%
0.25634765625 1
1.0%
0.255859375 1
1.0%
0.255615234375 2
2.0%
0.2548828125 1
1.0%

위도 값
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.864065
Minimum35.837625
Maximum35.898918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:04:07.610411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.837625
5-th percentile35.83776
Q135.84041
median35.873324
Q335.874995
95-th percentile35.898918
Maximum35.898918
Range0.061293
Interquartile range (IQR)0.034585

Descriptive statistics

Standard deviation0.022062261
Coefficient of variation (CV)0.00061516341
Kurtosis-1.2695597
Mean35.864065
Median Absolute Deviation (MAD)0.025594
Skewness0.28065029
Sum3586.4065
Variance0.00048674336
MonotonicityNot monotonic
2023-12-10T22:04:07.712691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
35.898918 18
18.0%
35.84041 16
16.0%
35.874995 13
13.0%
35.873552 8
8.0%
35.873324 7
 
7.0%
35.859626 7
 
7.0%
35.83776 5
 
5.0%
35.840143 5
 
5.0%
35.847437 3
 
3.0%
35.8471 3
 
3.0%
Other values (10) 15
15.0%
ValueCountFrequency (%)
35.837625 2
 
2.0%
35.83763 1
 
1.0%
35.83776 5
 
5.0%
35.83927 3
 
3.0%
35.840143 5
 
5.0%
35.840152 1
 
1.0%
35.84041 16
16.0%
35.844306 1
 
1.0%
35.8471 3
 
3.0%
35.847437 3
 
3.0%
ValueCountFrequency (%)
35.898918 18
18.0%
35.893028 1
 
1.0%
35.874995 13
13.0%
35.873552 8
8.0%
35.87351 3
 
3.0%
35.873423 1
 
1.0%
35.873324 7
 
7.0%
35.861664 1
 
1.0%
35.859626 7
 
7.0%
35.848541 1
 
1.0%

경도 값
Real number (ℝ)

Distinct20
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59695
Minimum128.54618
Maximum128.61685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:04:07.834345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54618
5-th percentile128.56844
Q1128.59114
median128.59681
Q3128.61184
95-th percentile128.61356
Maximum128.61685
Range0.07067
Interquartile range (IQR)0.020695

Descriptive statistics

Standard deviation0.014335667
Coefficient of variation (CV)0.0001114775
Kurtosis0.83414813
Mean128.59695
Median Absolute Deviation (MAD)0.00567
Skewness-0.83351279
Sum12859.695
Variance0.00020551135
MonotonicityNot monotonic
2023-12-10T22:04:08.014818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
128.611835 18
18.0%
128.59681 16
16.0%
128.59114 13
13.0%
128.592509 8
8.0%
128.592487 7
 
7.0%
128.568436 7
 
7.0%
128.613563 5
 
5.0%
128.5983 5
 
5.0%
128.614852 3
 
3.0%
128.613427 3
 
3.0%
Other values (10) 15
15.0%
ValueCountFrequency (%)
128.546179 1
 
1.0%
128.568436 7
7.0%
128.569971 1
 
1.0%
128.570607 3
 
3.0%
128.588553 1
 
1.0%
128.59114 13
13.0%
128.592487 7
7.0%
128.592509 8
8.0%
128.592753 1
 
1.0%
128.592775 3
 
3.0%
ValueCountFrequency (%)
128.616849 1
 
1.0%
128.614852 3
 
3.0%
128.613583 1
 
1.0%
128.613563 5
 
5.0%
128.613504 2
 
2.0%
128.613427 3
 
3.0%
128.611835 18
18.0%
128.5983 5
 
5.0%
128.59681 16
16.0%
128.592916 1
 
1.0%

속도
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.52
Minimum0
Maximum43
Zeros33
Zeros (%)33.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:04:08.131163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314
95-th percentile36
Maximum43
Range43
Interquartile range (IQR)14

Descriptive statistics

Standard deviation14.002511
Coefficient of variation (CV)1.3310371
Kurtosis-0.2428318
Mean10.52
Median Absolute Deviation (MAD)3
Skewness1.202641
Sum1052
Variance196.0703
MonotonicityNot monotonic
2023-12-10T22:04:08.228345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 33
33.0%
36 18
18.0%
3 16
16.0%
7 13
 
13.0%
14 7
 
7.0%
2 5
 
5.0%
10 3
 
3.0%
9 1
 
1.0%
35 1
 
1.0%
39 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
0 33
33.0%
1 1
 
1.0%
2 5
 
5.0%
3 16
16.0%
7 13
 
13.0%
9 1
 
1.0%
10 3
 
3.0%
14 7
 
7.0%
35 1
 
1.0%
36 18
18.0%
ValueCountFrequency (%)
43 1
 
1.0%
39 1
 
1.0%
36 18
18.0%
35 1
 
1.0%
14 7
 
7.0%
10 3
 
3.0%
9 1
 
1.0%
7 13
13.0%
3 16
16.0%
2 5
 
5.0%

Interactions

2023-12-10T22:04:04.719157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.107491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.158176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.958097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.676297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.355925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.010337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.808902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.198559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.263005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.069175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.792028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.442458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.091483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.910784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.283754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.372095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.180990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.887985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.539914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.205634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:05.007387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.426415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.502981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.273579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.998723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.635525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.304884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:05.096141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.876047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.646460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.374224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.091712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.750983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.429523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:05.169127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:00.974247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.757995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.465785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.182676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.840767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.541276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:05.258792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.064726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:01.856578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:02.576517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.273981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:03.931193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:04:04.642049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:04:08.301735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID시간노드ID진동 값(x)진동 값(y)진동 값(z)위도 값경도 값속도
ID1.0001.0001.0000.3340.2260.0000.9450.7690.897
시간1.0001.0001.0001.0001.0001.0001.0001.0001.000
노드ID1.0001.0001.0000.5240.4310.0000.4570.3920.332
진동 값(x)0.3341.0000.5241.0000.7880.5160.1660.3060.000
진동 값(y)0.2261.0000.4310.7881.0000.5700.0810.3010.000
진동 값(z)0.0001.0000.0000.5160.5701.0000.2750.3060.325
위도 값0.9451.0000.4570.1660.0810.2751.0000.8320.979
경도 값0.7691.0000.3920.3060.3010.3060.8321.0000.781
속도0.8971.0000.3320.0000.0000.3250.9790.7811.000
2023-12-10T22:04:08.416721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ID진동 값(x)진동 값(y)진동 값(z)위도 값경도 값속도노드ID
ID1.0000.292-0.1450.067-0.7830.227-0.5050.979
진동 값(x)0.2921.000-0.0920.075-0.2660.136-0.1940.382
진동 값(y)-0.145-0.0921.0000.0500.036-0.060-0.0010.450
진동 값(z)0.0670.0750.0501.0000.0540.1240.0250.000
위도 값-0.783-0.2660.0360.0541.000-0.1160.5790.322
경도 값0.2270.136-0.0600.124-0.1161.0000.0150.460
속도-0.505-0.194-0.0010.0250.5790.0151.0000.233
노드ID0.9790.3820.4500.0000.3220.4600.2331.000

Missing values

2023-12-10T22:04:05.387826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:04:05.542312image/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

ID게이트웨이ID시간노드ID진동 값(x)진동 값(y)진동 값(z)위도 값경도 값속도
060307011SERVER2019-01-01 10:04:46IK1012-0.0209960.0021970.2429235.898918128.61183536
160307012SERVER2019-01-01 10:04:56IK1012-0.017090.0024410.24951235.898918128.61183536
260307013SERVER2019-01-01 10:05:06IK1012-0.0126950.0036620.24975635.898918128.61183536
360307014SERVER2019-01-01 10:05:15IK1012-0.014160.0026860.25073235.898918128.61183536
460307015SERVER2019-01-01 10:05:25IK1012-0.014160.0061040.2458535.898918128.61183536
560307018SERVER2019-01-01 10:05:34IK1012-0.0136720.0031740.25048835.898918128.61183536
660307029SERVER2019-01-01 10:05:45IK1012-0.0148930.0046390.24853535.898918128.61183536
760307040SERVER2019-01-01 10:05:55IK1012-0.0139160.0043950.2535.898918128.61183536
860307051SERVER2019-01-01 10:06:06IK1012-0.0192870.0034180.24560535.898918128.61183536
960307062SERVER2019-01-01 10:06:15IK1012-0.0187990.0014650.24853535.898918128.61183536
ID게이트웨이ID시간노드ID진동 값(x)진동 값(y)진동 값(z)위도 값경도 값속도
9062597945SERVER2019-01-05 23:18:51IK1012-0.0039060.0085450.25219735.873423128.5927531
9162651694SERVER2019-01-14 03:50:46IK1032-0.0109860.00.25146535.844306128.58855343
9262769108SERVER2019-01-17 13:56:12IK1032-0.041260.1064450.24560535.837625128.6135040
9362769109SERVER2019-01-17 13:56:22IK10320.05542-0.0827640.26025435.837625128.6135040
9462832129SERVER2019-01-23 00:15:58IK10320.110596-0.0380860.2529335.83763128.6135830
9562865998SERVER2019-01-23 09:08:54IK1032-0.0024410.010010.24731435.83776128.6135632
9662865999SERVER2019-01-23 09:09:04IK1032-0.0097660.0056150.25219735.83776128.6135632
9762866000SERVER2019-01-23 09:09:13IK1032-0.00708-0.0009770.24780335.83776128.6135632
9862866001SERVER2019-01-23 09:09:24IK1032-0.0104980.0043950.24414135.83776128.6135632
9962866002SERVER2019-01-23 09:09:34IK1032-0.0073240.0026860.24194335.83776128.6135632