Overview

Dataset statistics

Number of variables15
Number of observations642
Missing cells646
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory83.5 KiB
Average record size in memory133.2 B

Variable types

Numeric12
Unsupported1
Categorical2

Alerts

inspec_area has constant value ""Constant
last_load_dttm has constant value ""Constant
skey is highly overall correlated with inspec_ym and 2 other fieldsHigh correlation
inspec_ym is highly overall correlated with skey and 3 other fieldsHigh correlation
virus02 is highly overall correlated with inspec_ym and 4 other fieldsHigh correlation
virus03 is highly overall correlated with skey and 3 other fieldsHigh correlation
virus04 is highly overall correlated with virus02 and 1 other fieldsHigh correlation
virus07 is highly overall correlated with skey and 2 other fieldsHigh correlation
virus08 is highly overall correlated with virus02 and 1 other fieldsHigh correlation
virus09 is highly overall correlated with virus02High correlation
virus10 has 642 (100.0%) missing valuesMissing
virus06 is highly skewed (γ1 = 21.92658212)Skewed
skey has unique valuesUnique
virus10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
virus01 has 88 (13.7%) zerosZeros
virus02 has 305 (47.5%) zerosZeros
virus03 has 408 (63.6%) zerosZeros
virus04 has 160 (24.9%) zerosZeros
virus05 has 389 (60.6%) zerosZeros
virus06 has 471 (73.4%) zerosZeros
virus07 has 446 (69.5%) zerosZeros
virus08 has 198 (30.8%) zerosZeros
virus09 has 475 (74.0%) zerosZeros

Reproduction

Analysis started2024-04-17 00:57:27.184263
Analysis finished2024-04-17 00:57:40.299020
Duration13.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

skey
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct642
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean329600.5
Minimum329280
Maximum329921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:40.359777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum329280
5-th percentile329312.05
Q1329440.25
median329600.5
Q3329760.75
95-th percentile329888.95
Maximum329921
Range641
Interquartile range (IQR)320.5

Descriptive statistics

Standard deviation185.47372
Coefficient of variation (CV)0.0005627228
Kurtosis-1.2
Mean329600.5
Median Absolute Deviation (MAD)160.5
Skewness0
Sum2.1160352 × 108
Variance34400.5
MonotonicityNot monotonic
2024-04-17T09:57:40.733008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
329777 1
 
0.2%
329522 1
 
0.2%
329464 1
 
0.2%
329465 1
 
0.2%
329466 1
 
0.2%
329467 1
 
0.2%
329468 1
 
0.2%
329469 1
 
0.2%
329470 1
 
0.2%
329471 1
 
0.2%
Other values (632) 632
98.4%
ValueCountFrequency (%)
329280 1
0.2%
329281 1
0.2%
329282 1
0.2%
329283 1
0.2%
329284 1
0.2%
329285 1
0.2%
329286 1
0.2%
329287 1
0.2%
329288 1
0.2%
329289 1
0.2%
ValueCountFrequency (%)
329921 1
0.2%
329920 1
0.2%
329919 1
0.2%
329918 1
0.2%
329917 1
0.2%
329916 1
0.2%
329915 1
0.2%
329914 1
0.2%
329913 1
0.2%
329912 1
0.2%

inspec_ym
Real number (ℝ)

HIGH CORRELATION 

Distinct148
Distinct (%)23.2%
Missing4
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean201136.51
Minimum200204
Maximum202011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:40.846431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200204
5-th percentile200305
Q1200706
median201111
Q3201605.75
95-th percentile202004
Maximum202011
Range1807
Interquartile range (IQR)899.75

Descriptive statistics

Standard deviation533.37371
Coefficient of variation (CV)0.0026517995
Kurtosis-1.1353235
Mean201136.51
Median Absolute Deviation (MAD)450
Skewness-0.059695916
Sum1.283251 × 108
Variance284487.52
MonotonicityNot monotonic
2024-04-17T09:57:40.963079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201405 8
 
1.2%
201404 7
 
1.1%
200908 5
 
0.8%
200209 5
 
0.8%
201407 5
 
0.8%
200208 5
 
0.8%
201409 5
 
0.8%
201504 5
 
0.8%
201507 5
 
0.8%
201509 5
 
0.8%
Other values (138) 583
90.8%
ValueCountFrequency (%)
200204 2
 
0.3%
200205 5
0.8%
200206 4
0.6%
200207 4
0.6%
200208 5
0.8%
200209 5
0.8%
200210 4
0.6%
200304 2
 
0.3%
200305 4
0.6%
200306 4
0.6%
ValueCountFrequency (%)
202011 4
0.6%
202010 4
0.6%
202009 4
0.6%
202008 5
0.8%
202007 4
0.6%
202006 5
0.8%
202005 4
0.6%
202004 4
0.6%
201911 4
0.6%
201910 5
0.8%

inspec_wk
Real number (ℝ)

Distinct9
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.758567
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:41.061409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3391838
Coefficient of variation (CV)0.48546358
Kurtosis0.036033066
Mean2.758567
Median Absolute Deviation (MAD)1
Skewness0.41224543
Sum1771
Variance1.7934132
MonotonicityNot monotonic
2024-04-17T09:57:41.151588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3 148
23.1%
4 148
23.1%
1 144
22.4%
2 144
22.4%
5 52
 
8.1%
6 2
 
0.3%
7 2
 
0.3%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
1 144
22.4%
2 144
22.4%
3 148
23.1%
4 148
23.1%
5 52
 
8.1%
6 2
 
0.3%
7 2
 
0.3%
8 1
 
0.2%
9 1
 
0.2%
ValueCountFrequency (%)
9 1
 
0.2%
8 1
 
0.2%
7 2
 
0.3%
6 2
 
0.3%
5 52
 
8.1%
4 148
23.1%
3 148
23.1%
2 144
22.4%
1 144
22.4%

virus01
Real number (ℝ)

ZEROS 

Distinct341
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean363.40966
Minimum0
Maximum7022
Zeros88
Zeros (%)13.7%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:41.267282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.5
median44
Q3254.75
95-th percentile1959.95
Maximum7022
Range7022
Interquartile range (IQR)252.25

Descriptive statistics

Standard deviation865.99646
Coefficient of variation (CV)2.3829759
Kurtosis18.837943
Mean363.40966
Median Absolute Deviation (MAD)44
Skewness4.0041514
Sum233309
Variance749949.87
MonotonicityNot monotonic
2024-04-17T09:57:41.383438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 88
 
13.7%
1.0 25
 
3.9%
0.5 18
 
2.8%
2.0 14
 
2.2%
2.5 11
 
1.7%
4.5 10
 
1.6%
3.0 9
 
1.4%
4.0 8
 
1.2%
1.5 8
 
1.2%
7.5 7
 
1.1%
Other values (331) 444
69.2%
ValueCountFrequency (%)
0.0 88
13.7%
0.5 18
 
2.8%
1.0 25
 
3.9%
1.5 8
 
1.2%
2.0 14
 
2.2%
2.5 11
 
1.7%
3.0 9
 
1.4%
3.5 4
 
0.6%
4.0 8
 
1.2%
4.5 10
 
1.6%
ValueCountFrequency (%)
7022.0 1
0.2%
6613.0 1
0.2%
5708.0 1
0.2%
5351.0 1
0.2%
4696.0 1
0.2%
4563.0 1
0.2%
4338.0 1
0.2%
4271.0 2
0.3%
4193.0 1
0.2%
4056.0 1
0.2%

virus02
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct112
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.562305
Minimum0
Maximum259.5
Zeros305
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:41.495903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q39
95-th percentile68.35
Maximum259.5
Range259.5
Interquartile range (IQR)9

Descriptive statistics

Standard deviation32.288699
Coefficient of variation (CV)2.5702845
Kurtosis21.77212
Mean12.562305
Median Absolute Deviation (MAD)0.5
Skewness4.3488175
Sum8065
Variance1042.5601
MonotonicityNot monotonic
2024-04-17T09:57:41.608050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 305
47.5%
1.0 33
 
5.1%
0.5 23
 
3.6%
2.0 19
 
3.0%
3.0 16
 
2.5%
1.5 11
 
1.7%
3.5 10
 
1.6%
4.5 8
 
1.2%
2.5 8
 
1.2%
6.0 7
 
1.1%
Other values (102) 202
31.5%
ValueCountFrequency (%)
0.0 305
47.5%
0.5 23
 
3.6%
1.0 33
 
5.1%
1.5 11
 
1.7%
2.0 19
 
3.0%
2.5 8
 
1.2%
3.0 16
 
2.5%
3.5 10
 
1.6%
4.0 7
 
1.1%
4.5 8
 
1.2%
ValueCountFrequency (%)
259.5 1
0.2%
227.0 1
0.2%
224.0 2
0.3%
206.0 1
0.2%
180.0 1
0.2%
178.0 1
0.2%
175.0 1
0.2%
172.0 1
0.2%
168.0 1
0.2%
160.0 1
0.2%

virus03
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct176
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean387.96028
Minimum0
Maximum9718
Zeros408
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:41.732877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318.375
95-th percentile2672.55
Maximum9718
Range9718
Interquartile range (IQR)18.375

Descriptive statistics

Standard deviation1213.0599
Coefficient of variation (CV)3.126763
Kurtosis24.203536
Mean387.96028
Median Absolute Deviation (MAD)0
Skewness4.5302219
Sum249070.5
Variance1471514.2
MonotonicityNot monotonic
2024-04-17T09:57:41.862273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 408
63.6%
0.5 14
 
2.2%
1.0 8
 
1.2%
5.0 7
 
1.1%
2.0 5
 
0.8%
7.0 4
 
0.6%
3.0 4
 
0.6%
12.0 4
 
0.6%
17.0 3
 
0.5%
4.0 3
 
0.5%
Other values (166) 182
28.3%
ValueCountFrequency (%)
0.0 408
63.6%
0.5 14
 
2.2%
1.0 8
 
1.2%
1.5 1
 
0.2%
2.0 5
 
0.8%
3.0 4
 
0.6%
3.5 2
 
0.3%
4.0 3
 
0.5%
4.5 2
 
0.3%
5.0 7
 
1.1%
ValueCountFrequency (%)
9718.0 1
0.2%
9207.0 1
0.2%
9036.0 1
0.2%
8808.0 1
0.2%
8541.0 1
0.2%
7024.0 1
0.2%
7003.0 1
0.2%
5282.0 1
0.2%
5075.0 1
0.2%
5064.0 1
0.2%

virus04
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct225
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187.35156
Minimum0
Maximum4765.5
Zeros160
Zeros (%)24.9%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:41.984620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.275
median3.75
Q365
95-th percentile1199.225
Maximum4765.5
Range4765.5
Interquartile range (IQR)64.725

Descriptive statistics

Standard deviation535.97115
Coefficient of variation (CV)2.8607777
Kurtosis27.066752
Mean187.35156
Median Absolute Deviation (MAD)3.75
Skewness4.6826533
Sum120279.7
Variance287265.08
MonotonicityNot monotonic
2024-04-17T09:57:42.119619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 160
24.9%
2.0 41
 
6.4%
1.0 35
 
5.5%
0.5 33
 
5.1%
4.0 18
 
2.8%
1.5 17
 
2.6%
2.5 16
 
2.5%
5.0 11
 
1.7%
9.0 11
 
1.7%
3.0 11
 
1.7%
Other values (215) 289
45.0%
ValueCountFrequency (%)
0.0 160
24.9%
0.2 1
 
0.2%
0.5 33
 
5.1%
1.0 35
 
5.5%
1.5 17
 
2.6%
2.0 41
 
6.4%
2.5 16
 
2.5%
3.0 11
 
1.7%
3.5 7
 
1.1%
4.0 18
 
2.8%
ValueCountFrequency (%)
4765.5 2
0.3%
3833.5 1
0.2%
3747.0 1
0.2%
2839.0 1
0.2%
2646.0 1
0.2%
2621.0 2
0.3%
2604.0 1
0.2%
2538.0 1
0.2%
2429.5 1
0.2%
2154.0 1
0.2%

virus05
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0412773
Minimum0
Maximum112
Zeros389
Zeros (%)60.6%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:42.240209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.5
95-th percentile18
Maximum112
Range112
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation9.694447
Coefficient of variation (CV)3.1876236
Kurtosis41.072366
Mean3.0412773
Median Absolute Deviation (MAD)0
Skewness5.6546627
Sum1952.5
Variance93.982303
MonotonicityNot monotonic
2024-04-17T09:57:42.352276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 389
60.6%
1.0 44
 
6.9%
0.5 41
 
6.4%
2.0 28
 
4.4%
1.5 19
 
3.0%
3.0 15
 
2.3%
4.0 14
 
2.2%
2.5 9
 
1.4%
8.0 9
 
1.4%
6.0 7
 
1.1%
Other values (38) 67
 
10.4%
ValueCountFrequency (%)
0.0 389
60.6%
0.5 41
 
6.4%
1.0 44
 
6.9%
1.5 19
 
3.0%
2.0 28
 
4.4%
2.5 9
 
1.4%
3.0 15
 
2.3%
3.5 6
 
0.9%
4.0 14
 
2.2%
4.5 3
 
0.5%
ValueCountFrequency (%)
112.0 1
0.2%
77.0 1
0.2%
68.0 1
0.2%
64.0 1
0.2%
55.0 1
0.2%
50.0 1
0.2%
49.0 2
0.3%
48.0 2
0.3%
47.0 1
0.2%
45.0 1
0.2%

virus06
Real number (ℝ)

SKEWED  ZEROS 

Distinct35
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0584112
Minimum0
Maximum396
Zeros471
Zeros (%)73.4%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:42.455092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile9
Maximum396
Range396
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation16.381902
Coefficient of variation (CV)7.9585176
Kurtosis523.96105
Mean2.0584112
Median Absolute Deviation (MAD)0
Skewness21.926582
Sum1321.5
Variance268.36671
MonotonicityNot monotonic
2024-04-17T09:57:42.568897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 471
73.4%
0.5 32
 
5.0%
1.0 31
 
4.8%
2.0 19
 
3.0%
1.5 12
 
1.9%
2.5 10
 
1.6%
3.0 9
 
1.4%
4.0 8
 
1.2%
5.0 6
 
0.9%
10.0 4
 
0.6%
Other values (25) 40
 
6.2%
ValueCountFrequency (%)
0.0 471
73.4%
0.5 32
 
5.0%
1.0 31
 
4.8%
1.5 12
 
1.9%
2.0 19
 
3.0%
2.5 10
 
1.6%
3.0 9
 
1.4%
4.0 8
 
1.2%
4.5 3
 
0.5%
5.0 6
 
0.9%
ValueCountFrequency (%)
396.0 1
0.2%
48.5 1
0.2%
47.0 1
0.2%
44.0 1
0.2%
41.0 1
0.2%
32.0 1
0.2%
31.0 1
0.2%
28.0 1
0.2%
25.0 1
0.2%
22.0 2
0.3%

virus07
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.602804
Minimum0
Maximum1308
Zeros446
Zeros (%)69.5%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:42.688794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile87.95
Maximum1308
Range1308
Interquartile range (IQR)3

Descriptive statistics

Standard deviation73.061764
Coefficient of variation (CV)4.1505754
Kurtosis162.75528
Mean17.602804
Median Absolute Deviation (MAD)0
Skewness10.779124
Sum11301
Variance5338.0214
MonotonicityNot monotonic
2024-04-17T09:57:42.802518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 446
69.5%
1.0 16
 
2.5%
0.5 9
 
1.4%
4.0 9
 
1.4%
2.0 7
 
1.1%
8.0 6
 
0.9%
9.0 5
 
0.8%
13.0 5
 
0.8%
33.0 5
 
0.8%
7.0 4
 
0.6%
Other values (90) 130
 
20.2%
ValueCountFrequency (%)
0.0 446
69.5%
0.5 9
 
1.4%
1.0 16
 
2.5%
1.5 1
 
0.2%
2.0 7
 
1.1%
2.5 1
 
0.2%
3.0 3
 
0.5%
3.5 2
 
0.3%
4.0 9
 
1.4%
5.0 4
 
0.6%
ValueCountFrequency (%)
1308.0 1
0.2%
566.0 1
0.2%
537.5 1
0.2%
364.5 1
0.2%
344.0 1
0.2%
342.0 1
0.2%
294.0 1
0.2%
291.0 1
0.2%
282.0 1
0.2%
258.0 1
0.2%

virus08
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct249
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.44081
Minimum0
Maximum1214
Zeros198
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:42.915169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14
Q374.75
95-th percentile439.7
Maximum1214
Range1214
Interquartile range (IQR)74.75

Descriptive statistics

Standard deviation186.99071
Coefficient of variation (CV)2.1632225
Kurtosis13.986653
Mean86.44081
Median Absolute Deviation (MAD)14
Skewness3.5901852
Sum55495
Variance34965.525
MonotonicityNot monotonic
2024-04-17T09:57:43.035740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 198
30.8%
1.0 15
 
2.3%
0.5 13
 
2.0%
7.5 10
 
1.6%
2.0 10
 
1.6%
6.0 8
 
1.2%
7.0 6
 
0.9%
2.5 6
 
0.9%
5.5 5
 
0.8%
11.0 5
 
0.8%
Other values (239) 366
57.0%
ValueCountFrequency (%)
0.0 198
30.8%
0.5 13
 
2.0%
1.0 15
 
2.3%
1.5 5
 
0.8%
2.0 10
 
1.6%
2.5 6
 
0.9%
3.0 3
 
0.5%
3.5 2
 
0.3%
4.0 4
 
0.6%
4.5 2
 
0.3%
ValueCountFrequency (%)
1214.0 1
0.2%
1196.0 1
0.2%
1114.0 1
0.2%
1076.0 1
0.2%
1069.0 1
0.2%
1054.0 1
0.2%
1004.0 1
0.2%
1000.0 1
0.2%
969.0 1
0.2%
959.0 1
0.2%

virus09
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct43
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3255452
Minimum0
Maximum168
Zeros475
Zeros (%)74.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2024-04-17T09:57:43.153098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.5
95-th percentile14
Maximum168
Range168
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation9.2913461
Coefficient of variation (CV)3.9953411
Kurtosis169.7992
Mean2.3255452
Median Absolute Deviation (MAD)0
Skewness10.957948
Sum1493
Variance86.329112
MonotonicityNot monotonic
2024-04-17T09:57:43.265207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 475
74.0%
0.5 23
 
3.6%
1.0 18
 
2.8%
6.0 10
 
1.6%
1.5 9
 
1.4%
2.5 9
 
1.4%
4.5 9
 
1.4%
2.0 9
 
1.4%
3.0 8
 
1.2%
14.5 5
 
0.8%
Other values (33) 67
 
10.4%
ValueCountFrequency (%)
0.0 475
74.0%
0.5 23
 
3.6%
1.0 18
 
2.8%
1.5 9
 
1.4%
2.0 9
 
1.4%
2.5 9
 
1.4%
3.0 8
 
1.2%
3.5 4
 
0.6%
4.0 5
 
0.8%
4.5 9
 
1.4%
ValueCountFrequency (%)
168.0 1
0.2%
86.0 1
0.2%
47.0 1
0.2%
38.0 2
0.3%
37.5 2
0.3%
36.0 1
0.2%
33.0 1
0.2%
28.0 1
0.2%
27.5 2
0.3%
24.5 1
0.2%

virus10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing642
Missing (%)100.0%
Memory size5.8 KiB

inspec_area
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
부산지역축사
642 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산지역축사 642
100.0%

Length

2024-04-17T09:57:43.370588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T09:57:43.445025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산지역축사 642
100.0%

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2021-02-01 06:09:03
642 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-02-01 06:09:03
2nd row2021-02-01 06:09:03
3rd row2021-02-01 06:09:03
4th row2021-02-01 06:09:03
5th row2021-02-01 06:09:03

Common Values

ValueCountFrequency (%)
2021-02-01 06:09:03 642
100.0%

Length

2024-04-17T09:57:43.523962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T09:57:43.600079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-02-01 642
50.0%
06:09:03 642
50.0%

Interactions

2024-04-17T09:57:39.028288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:27.633490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.613857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.705729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.690450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.044758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.014107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.927932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.830384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.027287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.034361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.986223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.116449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:27.707905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.712132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.785884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.092574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.141023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.088336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.007120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.912720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.106033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.123316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.068819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.203463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:27.787023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.815425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.868759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.184141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.245466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.168527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.084190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.999191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.191049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.205421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.150512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.294704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:27.867443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.925370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.954609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.281679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.333080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.247062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.166167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.104041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.278190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.287992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.232392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.384947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:27.953384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.011156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.036599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.362276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.409004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.323477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.243021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.185406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.362962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.370180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.323752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.465598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.028496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.087536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.118086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.438883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.479918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.389588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.318028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.255713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.445164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.444781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.405946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.547137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.109434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.164373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.199376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.517807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.549500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.459586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.388337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.326627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.522524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.518228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.478287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.627417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.184064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.237381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.292455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.614180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.621601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.532618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.455946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.400626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.608985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.590024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.551153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.700479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.257178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.324966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.366577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.696106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.697301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.602107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.526651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.469836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.701710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.661711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.643620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.788081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.341794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.435076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.452062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.792285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.780102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.693246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.603854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.549650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.790441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.744491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.764497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.864667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.420487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.521283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.530171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.882797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.861905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.771363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.680818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.625081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.871540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.820454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.856225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:39.945266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:28.515437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:29.615391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:30.610211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:31.962076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:32.938484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:33.852159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:34.755547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:35.699331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:36.951563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:37.899403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T09:57:38.941969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T09:57:43.660120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeyinspec_yminspec_wkvirus01virus02virus03virus04virus05virus06virus07virus08virus09
skey1.0000.9950.0000.3290.3120.3610.2320.3990.0700.3680.3840.432
inspec_ym0.9951.0000.0000.3620.3030.3840.2330.4200.0000.3540.3700.473
inspec_wk0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
virus010.3290.3620.0001.0000.5900.6940.5690.3400.4290.2620.3490.602
virus020.3120.3030.0000.5901.0000.0000.7180.0000.6130.0000.6230.746
virus030.3610.3840.0000.6940.0001.0000.0000.5030.3260.6010.0000.000
virus040.2320.2330.0000.5690.7180.0001.0000.0000.6020.0000.5000.767
virus050.3990.4200.0000.3400.0000.5030.0001.0000.0960.3720.2390.000
virus060.0700.0000.0000.4290.6130.3260.6020.0961.0000.1540.2590.000
virus070.3680.3540.0000.2620.0000.6010.0000.3720.1541.0000.0000.000
virus080.3840.3700.0000.3490.6230.0000.5000.2390.2590.0001.0000.522
virus090.4320.4730.0000.6020.7460.0000.7670.0000.0000.0000.5221.000
2024-04-17T09:57:43.783156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
skeyinspec_yminspec_wkvirus01virus02virus03virus04virus05virus06virus07virus08virus09
skey1.0001.000-0.004-0.3370.495-0.7500.329-0.0220.195-0.5450.3550.200
inspec_ym1.0001.000-0.005-0.3260.522-0.7660.353-0.0070.198-0.5580.3680.229
inspec_wk-0.004-0.0051.000-0.0050.003-0.020-0.024-0.027-0.025-0.020-0.023-0.007
virus01-0.337-0.326-0.0051.0000.2100.4110.4910.4380.2360.3730.3880.157
virus020.4950.5220.0030.2101.000-0.5890.7400.2140.340-0.4670.6830.559
virus03-0.750-0.766-0.0200.411-0.5891.000-0.3120.135-0.0480.822-0.271-0.381
virus040.3290.353-0.0240.4910.740-0.3121.0000.3430.418-0.1700.7340.471
virus05-0.022-0.007-0.0270.4380.2140.1350.3431.0000.1920.2340.2990.075
virus060.1950.198-0.0250.2360.340-0.0480.4180.1921.000-0.0180.233-0.012
virus07-0.545-0.558-0.0200.373-0.4670.822-0.1700.234-0.0181.000-0.103-0.306
virus080.3550.368-0.0230.3880.683-0.2710.7340.2990.233-0.1031.0000.418
virus090.2000.229-0.0070.1570.559-0.3810.4710.075-0.012-0.3060.4181.000

Missing values

2024-04-17T09:57:40.061928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T09:57:40.236205image/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

skeyinspec_yminspec_wkvirus01virus02virus03virus04virus05virus06virus07virus08virus09virus10inspec_arealast_load_dttm
03297772016093161.010.50.530.50.00.50.034.00.0<NA>부산지역축사2021-02-01 06:09:03
13297782016094139.51.50.021.52.50.51.0136.00.0<NA>부산지역축사2021-02-01 06:09:03
2329779201610159.00.50.05.00.00.00.092.50.0<NA>부산지역축사2021-02-01 06:09:03
332978020161027.51.50.09.01.00.00.093.00.0<NA>부산지역축사2021-02-01 06:09:03
432978120161034.00.50.01.51.50.50.036.50.0<NA>부산지역축사2021-02-01 06:09:03
532978220161043.51.50.01.00.00.00.022.50.0<NA>부산지역축사2021-02-01 06:09:03
632978320161110.00.00.00.00.00.00.00.00.0<NA>부산지역축사2021-02-01 06:09:03
732978420161120.00.00.00.00.00.00.00.00.0<NA>부산지역축사2021-02-01 06:09:03
832978520161130.00.00.00.00.00.00.00.00.0<NA>부산지역축사2021-02-01 06:09:03
932978620161140.01.00.00.00.00.00.00.00.0<NA>부산지역축사2021-02-01 06:09:03
skeyinspec_yminspec_wkvirus01virus02virus03virus04virus05virus06virus07virus08virus09virus10inspec_arealast_load_dttm
6323293972005104116.00.029.04.00.01.00.016.00.0<NA>부산지역축사2021-02-01 06:09:03
633329398200604111.51.03.50.00.00.00.00.00.0<NA>부산지역축사2021-02-01 06:09:03
63432939920060423.00.07.50.00.00.00.00.50.0<NA>부산지역축사2021-02-01 06:09:03
63532940020060436.50.54.50.00.50.00.00.50.0<NA>부산지역축사2021-02-01 06:09:03
63632940120060444.52.50.00.01.00.00.00.50.0<NA>부산지역축사2021-02-01 06:09:03
63732940220060512.54.01.50.00.00.00.01.00.0<NA>부산지역축사2021-02-01 06:09:03
63832940320060527.00.57.00.00.50.05.54.50.0<NA>부산지역축사2021-02-01 06:09:03
63932940420060537.57.014.50.50.00.04.08.00.0<NA>부산지역축사2021-02-01 06:09:03
640329405200605411.03.016.03.50.00.09.510.00.0<NA>부산지역축사2021-02-01 06:09:03
641329406200605525.03.016.51.51.50.08.517.50.0<NA>부산지역축사2021-02-01 06:09:03