Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory78.3 B

Variable types

DateTime1
Categorical2
Text1
Numeric5

Alerts

장치아이디 is highly overall correlated with 전류값 and 4 other fieldsHigh correlation
장치번호 is highly overall correlated with 전류값 and 4 other fieldsHigh correlation
전류값 is highly overall correlated with 전력값 and 4 other fieldsHigh correlation
전력값 is highly overall correlated with 전류값 and 4 other fieldsHigh correlation
파워팩터값 is highly overall correlated with 전류값 and 4 other fieldsHigh correlation
전원여부 is highly overall correlated with 전류값 and 4 other fieldsHigh correlation
로그일 has unique valuesUnique
전압값 has unique valuesUnique
파워팩터값 has unique valuesUnique
전력값 has 18 (18.0%) zerosZeros
전원여부 has 35 (35.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:20:16.251233
Analysis finished2023-12-10 13:20:21.375308
Duration5.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

로그일
Date

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2021-04-01 00:00:04
Maximum2021-04-01 08:10:05
2023-12-10T22:20:21.497362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:21.803660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

장치아이디
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5f042d3eef45e344565af9cc
50 
5f042e68ef45e344565af9d6
50 

Length

Max length24
Median length24
Mean length24
Min length24

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5f042d3eef45e344565af9cc
2nd row5f042e68ef45e344565af9d6
3rd row5f042d3eef45e344565af9cc
4th row5f042e68ef45e344565af9d6
5th row5f042d3eef45e344565af9cc

Common Values

ValueCountFrequency (%)
5f042d3eef45e344565af9cc 50
50.0%
5f042e68ef45e344565af9d6 50
50.0%

Length

2023-12-10T22:20:22.029056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:20:22.185115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5f042d3eef45e344565af9cc 50
50.0%
5f042e68ef45e344565af9d6 50
50.0%

장치번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Dawon-B540-2ef43250f6c6
50 
Dawon-B540-2ef432510196
50 

Length

Max length23
Median length23
Mean length23
Min length23

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDawon-B540-2ef43250f6c6
2nd rowDawon-B540-2ef432510196
3rd rowDawon-B540-2ef43250f6c6
4th rowDawon-B540-2ef432510196
5th rowDawon-B540-2ef43250f6c6

Common Values

ValueCountFrequency (%)
Dawon-B540-2ef43250f6c6 50
50.0%
Dawon-B540-2ef432510196 50
50.0%

Length

2023-12-10T22:20:22.380031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:20:22.544240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dawon-b540-2ef43250f6c6 50
50.0%
dawon-b540-2ef432510196 50
50.0%

로그 아이디
Text

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:20:22.975889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters2400
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)81.0%

Sample

1st row60648e818253773fcfc6b5cf
2nd row60648ec38253773fcfc6b73e
3rd row606490e88253773fcfc6c359
4th row606490c38253773fcfc6c288
5th row6064934f8253773fcfc6d0e3
ValueCountFrequency (%)
6064ca908253773fcfc807bd 13
 
13.0%
6064c61b8253773fcfc7eeca 6
 
6.0%
606501588253773fcfc93be7 1
 
1.0%
6064ff338253773fcfc93004 1
 
1.0%
6064e79b8253773fcfc8ab4b 1
 
1.0%
6064e5348253773fcfc89dbd 1
 
1.0%
6064e3018253773fcfc89188 1
 
1.0%
6064e0c48253773fcfc884dc 1
 
1.0%
6064de5d8253773fcfc8774c 1
 
1.0%
6064dbf68253773fcfc869ba 1
 
1.0%
Other values (73) 73
73.0%
2023-12-10T22:20:23.889942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 286
11.9%
c 269
11.2%
f 251
10.5%
6 250
10.4%
3 245
10.2%
8 181
7.5%
0 161
6.7%
5 134
 
5.6%
4 131
 
5.5%
2 125
 
5.2%
Other values (6) 367
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1628
67.8%
Lowercase Letter 772
32.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 286
17.6%
6 250
15.4%
3 245
15.0%
8 181
11.1%
0 161
9.9%
5 134
8.2%
4 131
8.0%
2 125
7.7%
9 68
 
4.2%
1 47
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
c 269
34.8%
f 251
32.5%
b 68
 
8.8%
a 66
 
8.5%
e 63
 
8.2%
d 55
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1628
67.8%
Latin 772
32.2%

Most frequent character per script

Common
ValueCountFrequency (%)
7 286
17.6%
6 250
15.4%
3 245
15.0%
8 181
11.1%
0 161
9.9%
5 134
8.2%
4 131
8.0%
2 125
7.7%
9 68
 
4.2%
1 47
 
2.9%
Latin
ValueCountFrequency (%)
c 269
34.8%
f 251
32.5%
b 68
 
8.8%
a 66
 
8.5%
e 63
 
8.2%
d 55
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 286
11.9%
c 269
11.2%
f 251
10.5%
6 250
10.4%
3 245
10.2%
8 181
7.5%
0 161
6.7%
5 134
 
5.6%
4 131
 
5.5%
2 125
 
5.2%
Other values (6) 367
15.3%

전류값
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18349083
Minimum0.0065437292
Maximum0.88325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:20:24.181747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0065437292
5-th percentile0.026474152
Q10.026616667
median0.026891667
Q30.3533533
95-th percentile0.66668917
Maximum0.88325
Range0.87670627
Interquartile range (IQR)0.32673664

Descriptive statistics

Standard deviation0.22395673
Coefficient of variation (CV)1.2205336
Kurtosis0.27592119
Mean0.18349083
Median Absolute Deviation (MAD)0.00046583437
Skewness1.2003185
Sum18.349083
Variance0.050156616
MonotonicityNot monotonic
2023-12-10T22:20:24.439837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0266166666666666 6
 
6.0%
0.0264833333333333 4
 
4.0%
0.0267666666666666 3
 
3.0%
0.0266499999999999 3
 
3.0%
0.0265166666666666 2
 
2.0%
0.0267166666666666 2
 
2.0%
0.0266 2
 
2.0%
0.0266666666666666 2
 
2.0%
0.02675 1
 
1.0%
0.0266999999999999 1
 
1.0%
Other values (74) 74
74.0%
ValueCountFrequency (%)
0.0065437291666666 1
 
1.0%
0.0106165604166666 1
 
1.0%
0.01698395 1
 
1.0%
0.02625 1
 
1.0%
0.0264183312499999 1
 
1.0%
0.0264770895833332 1
 
1.0%
0.0264833333333333 4
4.0%
0.0265166666666666 2
2.0%
0.0265329336805555 1
 
1.0%
0.0265333333333333 1
 
1.0%
ValueCountFrequency (%)
0.8832500000000001 1
1.0%
0.7333166666666665 1
1.0%
0.690149558333333 1
1.0%
0.6885752770833334 1
1.0%
0.6702833333333335 1
1.0%
0.6665 1
1.0%
0.6541999999999999 1
1.0%
0.5635500000000004 1
1.0%
0.5455333333333334 1
1.0%
0.5415521059027778 1
1.0%

전압값
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219.26711
Minimum215.82173
Maximum221.08233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:20:24.680511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum215.82173
5-th percentile216.5654
Q1218.57462
median219.53142
Q3220.27388
95-th percentile220.94136
Maximum221.08233
Range5.2606031
Interquartile range (IQR)1.6992556

Descriptive statistics

Standard deviation1.3186707
Coefficient of variation (CV)0.0060139923
Kurtosis-0.088768152
Mean219.26711
Median Absolute Deviation (MAD)0.83625
Skewness-0.82360245
Sum21926.711
Variance1.7388925
MonotonicityNot monotonic
2023-12-10T22:20:24.938217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
219.67200000000005 1
 
1.0%
219.9256666666667 1
 
1.0%
219.2176666666667 1
 
1.0%
217.3747045723626 1
 
1.0%
219.24016666666665 1
 
1.0%
216.51921287666215 1
 
1.0%
219.38958333333335 1
 
1.0%
217.2534136548833 1
 
1.0%
219.29216666666665 1
 
1.0%
217.70251862577567 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
215.82173018750004 1
1.0%
215.892 1
1.0%
215.930210375 1
1.0%
216.34716666666677 1
1.0%
216.51921287666215 1
1.0%
216.56783333333337 1
1.0%
217.1755054479167 1
1.0%
217.24935418029696 1
1.0%
217.2534136548833 1
1.0%
217.3747045723626 1
1.0%
ValueCountFrequency (%)
221.0823333333334 1
1.0%
220.99466666666663 1
1.0%
220.97749999999996 1
1.0%
220.94733333333332 1
1.0%
220.9450833333333 1
1.0%
220.94116666666665 1
1.0%
220.8658333333333 1
1.0%
220.79683333333327 1
1.0%
220.795 1
1.0%
220.73333333333335 1
1.0%

전력값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.431562
Minimum0
Maximum156.69967
Zeros18
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:20:25.527036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.010458333
median0.039488344
Q363.723639
95-th percentile120.82372
Maximum156.69967
Range156.69967
Interquartile range (IQR)63.71318

Descriptive statistics

Standard deviation43.191282
Coefficient of variation (CV)1.4192923
Kurtosis-0.010919559
Mean30.431562
Median Absolute Deviation (MAD)0.039488344
Skewness1.1593498
Sum3043.1562
Variance1865.4868
MonotonicityNot monotonic
2023-12-10T22:20:25.773986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 18
 
18.0%
0.0126666666666666 8
 
8.0%
0.0253333333333333 6
 
6.0%
0.0226666666666666 2
 
2.0%
0.01 2
 
2.0%
47.91039797717198 1
 
1.0%
71.31520041666666 1
 
1.0%
15.07705316666667 1
 
1.0%
120.94199977083332 1
 
1.0%
0.1359791458333345 1
 
1.0%
Other values (59) 59
59.0%
ValueCountFrequency (%)
0.0 18
18.0%
3.587499999999675e-05 1
 
1.0%
7.966666666665009e-05 1
 
1.0%
0.0001874999999999 1
 
1.0%
0.01 2
 
2.0%
0.0101666666666666 1
 
1.0%
0.0103333333333333 1
 
1.0%
0.0105 1
 
1.0%
0.0111666666666666 1
 
1.0%
0.0113333333333333 1
 
1.0%
ValueCountFrequency (%)
156.69966666666667 1
1.0%
132.43633333333335 1
1.0%
126.12883333333336 1
1.0%
123.4469570833334 1
1.0%
120.94199977083332 1
1.0%
120.8175 1
1.0%
114.0655 1
1.0%
106.99083333333334 1
1.0%
106.6921666666667 1
1.0%
102.16766666666663 1
1.0%

파워팩터값
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.25772646
Minimum0.10660833
Maximum0.7035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:20:26.039277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.10660833
5-th percentile0.11156295
Q10.13339167
median0.17526141
Q30.36295833
95-th percentile0.58026907
Maximum0.7035
Range0.59689167
Interquartile range (IQR)0.22956667

Descriptive statistics

Standard deviation0.15777552
Coefficient of variation (CV)0.61218209
Kurtosis-0.22654055
Mean0.25772646
Median Absolute Deviation (MAD)0.059436412
Skewness0.98631782
Sum25.772646
Variance0.024893115
MonotonicityNot monotonic
2023-12-10T22:20:26.272480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1077999999999999 1
 
1.0%
0.1525833333333333 1
 
1.0%
0.1271666666666666 1
 
1.0%
0.4789594750997339 1
 
1.0%
0.1328666666666666 1
 
1.0%
0.180485661639332 1
 
1.0%
0.1654250000000001 1
 
1.0%
0.3260537467457152 1
 
1.0%
0.1110999999999999 1
 
1.0%
0.4814789012522165 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
0.1066083333333332 1
1.0%
0.1068666666666666 1
1.0%
0.1077999999999999 1
1.0%
0.1094499999999999 1
1.0%
0.1110999999999999 1
1.0%
0.1115873145833332 1
1.0%
0.1154333333333333 1
1.0%
0.1157166666666666 1
1.0%
0.1159333333333333 1
1.0%
0.1177833333333332 1
1.0%
ValueCountFrequency (%)
0.7035000000000003 1
1.0%
0.6185333333333334 1
1.0%
0.6131188895833334 1
1.0%
0.6058833333333334 1
1.0%
0.5884333333333335 1
1.0%
0.5798393690972223 1
1.0%
0.5589554583333333 1
1.0%
0.5211499999999999 1
1.0%
0.5119500000000001 1
1.0%
0.5087666666666667 1
1.0%

전원여부
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.37183333
Minimum0
Maximum1
Zeros35
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:20:26.569045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.016666667
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.46829739
Coefficient of variation (CV)1.2594282
Kurtosis-1.7112496
Mean0.37183333
Median Absolute Deviation (MAD)0.016666667
Skewness0.53826327
Sum37.183333
Variance0.21930244
MonotonicityNot monotonic
2023-12-10T22:20:26.775857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 35
35.0%
1.0 29
29.0%
0.0166666666666666 18
18.0%
0.0333333333333333 8
 
8.0%
0.8166666666666667 3
 
3.0%
0.9666666666666668 2
 
2.0%
0.85 1
 
1.0%
0.05 1
 
1.0%
0.9833333333333332 1
 
1.0%
0.5166666666666667 1
 
1.0%
ValueCountFrequency (%)
0.0 35
35.0%
0.0166666666666666 18
18.0%
0.0333333333333333 8
 
8.0%
0.05 1
 
1.0%
0.5166666666666667 1
 
1.0%
0.8166666666666667 3
 
3.0%
0.8333333333333334 1
 
1.0%
0.85 1
 
1.0%
0.9666666666666668 2
 
2.0%
0.9833333333333332 1
 
1.0%
ValueCountFrequency (%)
1.0 29
29.0%
0.9833333333333332 1
 
1.0%
0.9666666666666668 2
 
2.0%
0.85 1
 
1.0%
0.8333333333333334 1
 
1.0%
0.8166666666666667 3
 
3.0%
0.5166666666666667 1
 
1.0%
0.05 1
 
1.0%
0.0333333333333333 8
 
8.0%
0.0166666666666666 18
18.0%

Interactions

2023-12-10T22:20:20.308510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.044996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.785684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:18.517483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.612849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.449129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.259016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.904215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:18.719293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.751801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.594537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.388517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:18.025026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.005198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.885525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.760749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.519607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:18.205667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.233445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.039034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.917882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:17.666841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:18.367550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:19.450355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:20:20.173517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:20:26.925864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
로그일장치아이디장치번호로그 아이디전류값전압값전력값파워팩터값전원여부
로그일1.0001.0001.0001.0001.0001.0001.0001.0001.000
장치아이디1.0001.0000.9991.0000.9530.3760.9420.9980.938
장치번호1.0000.9991.0001.0000.9530.3760.9420.9980.938
로그 아이디1.0001.0001.0001.0000.7860.0000.8170.0000.996
전류값1.0000.9530.9530.7861.0000.5660.9810.9600.692
전압값1.0000.3760.3760.0000.5661.0000.2200.1940.544
전력값1.0000.9420.9420.8170.9810.2201.0000.9640.682
파워팩터값1.0000.9980.9980.0000.9600.1940.9641.0000.776
전원여부1.0000.9380.9380.9960.6920.5440.6820.7761.000
2023-12-10T22:20:27.142181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장치아이디장치번호
장치아이디1.0000.980
장치번호0.9801.000
2023-12-10T22:20:27.315976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전류값전압값전력값파워팩터값전원여부장치아이디장치번호
전류값1.000-0.1620.8300.8170.5630.7810.781
전압값-0.1621.000-0.294-0.2690.1710.2920.292
전력값0.830-0.2941.0000.8490.6450.7630.763
파워팩터값0.817-0.2690.8491.0000.5180.9240.924
전원여부0.5630.1710.6450.5181.0000.7670.767
장치아이디0.7810.2920.7630.9240.7671.0000.980
장치번호0.7810.2920.7630.9240.7670.9801.000

Missing values

2023-12-10T22:20:21.100813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:20:21.298898image/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

로그일장치아이디장치번호로그 아이디전류값전압값전력값파워팩터값전원여부
02021-04-01 00:00:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c660648e818253773fcfc6b5cf0.026567219.6720.00.10780.0
12021-04-01 00:00:055f042e68ef45e344565af9d6Dawon-B540-2ef43251019660648ec38253773fcfc6b73e0.336062219.22666766.6952080.3319710.85
22021-04-01 00:10:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c6606490e88253773fcfc6c3590.026483219.8311670.0408330.13080.05
32021-04-01 00:10:055f042e68ef45e344565af9d6Dawon-B540-2ef432510196606490c38253773fcfc6c2880.147479219.16127.7668750.2508870.966667
42021-04-01 00:20:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064934f8253773fcfc6d0e30.026717220.23050.00.139250.0
52021-04-01 00:20:055f042e68ef45e344565af9d6Dawon-B540-2ef432510196606493348253773fcfc6d0430.451067219.517580.6750.4620331.0
62021-04-01 00:30:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c6606495b68253773fcfc6de730.026617220.27650.0111670.1365670.016667
72021-04-01 00:30:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966064959b8253773fcfc6ddd90.158067219.87420.0526670.3036671.0
82021-04-01 00:40:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064981d8253773fcfc6ec090.0266220.1926670.00.1198330.0
92021-04-01 00:40:055f042e68ef45e344565af9d6Dawon-B540-2ef432510196606498028253773fcfc6eb6e0.3875219.55616780.6240.3626331.0
로그일장치아이디장치번호로그 아이디전류값전압값전력값파워팩터값전원여부
902021-04-01 07:30:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064f8198253773fcfc908160.026817219.3158330.0126670.1583670.016667
912021-04-01 07:30:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966064f7fe8253773fcfc9077e0.310517219.01083342.5730.42541.0
922021-04-01 07:40:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064fa808253773fcfc915760.026617219.3281670.0253330.1701670.033333
932021-04-01 07:40:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966064fa658253773fcfc914df0.46345218.79516791.9210.4200171.0
942021-04-01 07:50:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064fce78253773fcfc9230a0.026517218.6530.0253330.1369170.033333
952021-04-01 07:50:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966064fccc8253773fcfc922710.02735218.3538331.2253330.204051.0
962021-04-01 08:00:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c66064ff4e8253773fcfc9309e0.026558217.61850.0126670.15220.016667
972021-04-01 08:00:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966064ff338253773fcfc930040.733317216.347167132.4363330.6058831.0
982021-04-01 08:10:045f042d3eef45e344565af9ccDawon-B540-2ef43250f6c6606501588253773fcfc93be70.026767216.5678330.0253330.109450.033333
992021-04-01 08:10:055f042e68ef45e344565af9d6Dawon-B540-2ef4325101966065019a8253773fcfc93d5d0.145283215.89226.80850.246951.0