Overview

Dataset statistics

Number of variables30
Number of observations500
Missing cells500
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory129.0 KiB
Average record size in memory264.3 B

Variable types

Text3
Categorical13
Numeric12
Unsupported1
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 재물안전관리사이버보안결과정보에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092944/fileData.do

Alerts

작성일자 has constant value ""Constant
인가인원수 has constant value ""Constant
보유소화기수 has constant value ""Constant
인가증외부인원수 has constant value ""Constant
인가증전월보유수 has constant value ""Constant
인가증퇴사직원반납건수 has constant value ""Constant
인가증분실건수 has constant value ""Constant
인가증추가건수 has constant value ""Constant
사원증퇴사직원반납건수 is highly imbalanced (88.2%)Imbalance
사원증분실건수 is highly imbalanced (97.9%)Imbalance
사원증감소건수 is highly imbalanced (75.8%)Imbalance
보안업무향상안건내용 has 500 (100.0%) missing valuesMissing
사이버보안결과ID has unique valuesUnique
보안업무향상안건내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
예비군인원수 has 157 (31.4%) zerosZeros
민방위인원수 has 94 (18.8%) zerosZeros
비대원인원수 has 27 (5.4%) zerosZeros
남자인원수 has 13 (2.6%) zerosZeros
여자인원수 has 27 (5.4%) zerosZeros
사원증직원수 has 15 (3.0%) zerosZeros
사원증전월보유수 has 14 (2.8%) zerosZeros
사원증추가건수 has 367 (73.4%) zerosZeros

Reproduction

Analysis started2023-12-12 14:43:51.254858
Analysis finished2023-12-12 14:43:51.595132
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사이버보안결과ID
Text

UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T23:43:51.841876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5000
Distinct characters62
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique500 ?
Unique (%)100.0%

Sample

1st row9dnOBw5NBS
2nd row9dnOA9IaRS
3rd row9dngBHX7qe
4th row9dngFFysG0
5th row9dm2393bDi
ValueCountFrequency (%)
9dnobw5nbs 1
 
0.2%
9dm2ymoolu 1
 
0.2%
9dm2yueq48 1
 
0.2%
9dm2x7ac1z 1
 
0.2%
9dm2yr5kyt 1
 
0.2%
9dm2xlhjum 1
 
0.2%
9dm2x4eync 1
 
0.2%
9dm2ypmvdq 1
 
0.2%
9dm2yievfo 1
 
0.2%
9dm2yfrofi 1
 
0.2%
Other values (490) 490
98.0%
2023-12-12T23:43:52.273750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 583
 
11.7%
9 545
 
10.9%
d 538
 
10.8%
2 230
 
4.6%
3 124
 
2.5%
4 105
 
2.1%
n 99
 
2.0%
Y 87
 
1.7%
0 83
 
1.7%
5 82
 
1.6%
Other values (52) 2524
50.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2403
48.1%
Decimal Number 1381
27.6%
Uppercase Letter 1216
24.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 583
24.3%
d 538
22.4%
n 99
 
4.1%
u 72
 
3.0%
o 69
 
2.9%
v 68
 
2.8%
f 61
 
2.5%
j 59
 
2.5%
t 56
 
2.3%
r 56
 
2.3%
Other values (16) 742
30.9%
Uppercase Letter
ValueCountFrequency (%)
Y 87
 
7.2%
X 67
 
5.5%
Z 58
 
4.8%
B 56
 
4.6%
Q 55
 
4.5%
T 52
 
4.3%
D 50
 
4.1%
I 49
 
4.0%
R 49
 
4.0%
S 49
 
4.0%
Other values (16) 644
53.0%
Decimal Number
ValueCountFrequency (%)
9 545
39.5%
2 230
16.7%
3 124
 
9.0%
4 105
 
7.6%
0 83
 
6.0%
5 82
 
5.9%
1 59
 
4.3%
6 58
 
4.2%
8 48
 
3.5%
7 47
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 3619
72.4%
Common 1381
 
27.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 583
 
16.1%
d 538
 
14.9%
n 99
 
2.7%
Y 87
 
2.4%
u 72
 
2.0%
o 69
 
1.9%
v 68
 
1.9%
X 67
 
1.9%
f 61
 
1.7%
j 59
 
1.6%
Other values (42) 1916
52.9%
Common
ValueCountFrequency (%)
9 545
39.5%
2 230
16.7%
3 124
 
9.0%
4 105
 
7.6%
0 83
 
6.0%
5 82
 
5.9%
1 59
 
4.3%
6 58
 
4.2%
8 48
 
3.5%
7 47
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 583
 
11.7%
9 545
 
10.9%
d 538
 
10.8%
2 230
 
4.6%
3 124
 
2.5%
4 105
 
2.1%
n 99
 
2.0%
Y 87
 
1.7%
0 83
 
1.7%
5 82
 
1.6%
Other values (52) 2524
50.5%

작성일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
500 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row00:00.0
2nd row00:00.0
3rd row00:00.0
4th row00:00.0
5th row00:00.0

Common Values

ValueCountFrequency (%)
00:00.0 500
100.0%

Length

2023-12-12T23:43:52.431336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:52.529091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 500
100.0%

작성자직원번호
Real number (ℝ)

Distinct194
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4688.55
Minimum2443
Maximum6077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:52.642081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2443
5-th percentile3352
Q14397.25
median4829
Q35212.25
95-th percentile5454
Maximum6077
Range3634
Interquartile range (IQR)815

Descriptive statistics

Standard deviation670.10067
Coefficient of variation (CV)0.14292279
Kurtosis0.2847736
Mean4688.55
Median Absolute Deviation (MAD)392.5
Skewness-0.81236377
Sum2344275
Variance449034.91
MonotonicityNot monotonic
2023-12-12T23:43:52.793714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4259 11
 
2.2%
5256 9
 
1.8%
5326 9
 
1.8%
3619 9
 
1.8%
4699 8
 
1.6%
5320 8
 
1.6%
3604 7
 
1.4%
3603 7
 
1.4%
4877 7
 
1.4%
4046 7
 
1.4%
Other values (184) 418
83.6%
ValueCountFrequency (%)
2443 1
 
0.2%
2711 1
 
0.2%
2869 5
1.0%
2876 3
0.6%
3074 3
0.6%
3191 2
 
0.4%
3283 2
 
0.4%
3290 2
 
0.4%
3291 1
 
0.2%
3294 2
 
0.4%
ValueCountFrequency (%)
6077 1
 
0.2%
6019 3
0.6%
5930 1
 
0.2%
5903 1
 
0.2%
5869 1
 
0.2%
5851 3
0.6%
5839 1
 
0.2%
5719 2
0.4%
5639 1
 
0.2%
5593 2
0.4%

예비군인원수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.256
Minimum0
Maximum16
Zeros157
Zeros (%)31.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:52.911550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum16
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4815039
Coefficient of variation (CV)1.1795413
Kurtosis29.189494
Mean1.256
Median Absolute Deviation (MAD)1
Skewness3.945593
Sum628
Variance2.1948537
MonotonicityNot monotonic
2023-12-12T23:43:53.027740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 181
36.2%
0 157
31.4%
2 93
18.6%
3 52
 
10.4%
4 9
 
1.8%
5 4
 
0.8%
11 3
 
0.6%
16 1
 
0.2%
ValueCountFrequency (%)
0 157
31.4%
1 181
36.2%
2 93
18.6%
3 52
 
10.4%
4 9
 
1.8%
5 4
 
0.8%
11 3
 
0.6%
16 1
 
0.2%
ValueCountFrequency (%)
16 1
 
0.2%
11 3
 
0.6%
5 4
 
0.8%
4 9
 
1.8%
3 52
 
10.4%
2 93
18.6%
1 181
36.2%
0 157
31.4%

민방위인원수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.752
Minimum0
Maximum15
Zeros94
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:53.138902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile5
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7170885
Coefficient of variation (CV)0.98007332
Kurtosis9.288488
Mean1.752
Median Absolute Deviation (MAD)1
Skewness2.2678366
Sum876
Variance2.9483928
MonotonicityNot monotonic
2023-12-12T23:43:53.238503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 184
36.8%
2 118
23.6%
0 94
18.8%
3 44
 
8.8%
5 22
 
4.4%
4 20
 
4.0%
6 9
 
1.8%
8 4
 
0.8%
7 2
 
0.4%
15 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
0 94
18.8%
1 184
36.8%
2 118
23.6%
3 44
 
8.8%
4 20
 
4.0%
5 22
 
4.4%
6 9
 
1.8%
7 2
 
0.4%
8 4
 
0.8%
9 1
 
0.2%
ValueCountFrequency (%)
15 1
 
0.2%
10 1
 
0.2%
9 1
 
0.2%
8 4
 
0.8%
7 2
 
0.4%
6 9
 
1.8%
5 22
 
4.4%
4 20
 
4.0%
3 44
 
8.8%
2 118
23.6%

비대원인원수
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.16
Minimum0
Maximum33
Zeros27
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:53.368522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median9
Q314
95-th percentile20.05
Maximum33
Range33
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.7654906
Coefficient of variation (CV)0.56746955
Kurtosis0.74518866
Mean10.16
Median Absolute Deviation (MAD)3
Skewness0.72106573
Sum5080
Variance33.240882
MonotonicityNot monotonic
2023-12-12T23:43:53.499426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
6 58
 
11.6%
10 48
 
9.6%
8 39
 
7.8%
7 39
 
7.8%
5 37
 
7.4%
18 34
 
6.8%
0 27
 
5.4%
9 26
 
5.2%
11 25
 
5.0%
16 22
 
4.4%
Other values (18) 145
29.0%
ValueCountFrequency (%)
0 27
5.4%
2 1
 
0.2%
3 6
 
1.2%
4 22
 
4.4%
5 37
7.4%
6 58
11.6%
7 39
7.8%
8 39
7.8%
9 26
5.2%
10 48
9.6%
ValueCountFrequency (%)
33 2
 
0.4%
30 2
 
0.4%
27 1
 
0.2%
25 1
 
0.2%
24 2
 
0.4%
23 8
1.6%
22 2
 
0.4%
21 7
1.4%
20 3
 
0.6%
19 7
1.4%

남자인원수
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.622
Minimum0
Maximum228
Zeros13
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:53.631121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q16
median8
Q312
95-th percentile20
Maximum228
Range228
Interquartile range (IQR)6

Descriptive statistics

Standard deviation17.79732
Coefficient of variation (CV)1.675515
Kurtosis132.50561
Mean10.622
Median Absolute Deviation (MAD)3
Skewness11.034618
Sum5311
Variance316.74461
MonotonicityNot monotonic
2023-12-12T23:43:53.812163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
6 67
13.4%
5 62
12.4%
11 47
9.4%
7 43
 
8.6%
8 39
 
7.8%
9 30
 
6.0%
13 29
 
5.8%
4 27
 
5.4%
12 22
 
4.4%
20 19
 
3.8%
Other values (18) 115
23.0%
ValueCountFrequency (%)
0 13
 
2.6%
2 1
 
0.2%
3 19
 
3.8%
4 27
5.4%
5 62
12.4%
6 67
13.4%
7 43
8.6%
8 39
7.8%
9 30
6.0%
10 16
 
3.2%
ValueCountFrequency (%)
228 3
 
0.6%
55 1
 
0.2%
29 1
 
0.2%
27 1
 
0.2%
26 4
 
0.8%
24 2
 
0.4%
22 6
 
1.2%
21 1
 
0.2%
20 19
3.8%
19 8
1.6%

여자인원수
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.124
Minimum0
Maximum18
Zeros27
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:53.962047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q35
95-th percentile9
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0684613
Coefficient of variation (CV)0.74404979
Kurtosis6.5686108
Mean4.124
Median Absolute Deviation (MAD)2
Skewness1.9897924
Sum2062
Variance9.4154549
MonotonicityNot monotonic
2023-12-12T23:43:54.082824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 94
18.8%
5 78
15.6%
3 70
14.0%
4 68
13.6%
6 46
9.2%
1 46
9.2%
0 27
 
5.4%
7 24
 
4.8%
8 18
 
3.6%
18 10
 
2.0%
Other values (5) 19
 
3.8%
ValueCountFrequency (%)
0 27
 
5.4%
1 46
9.2%
2 94
18.8%
3 70
14.0%
4 68
13.6%
5 78
15.6%
6 46
9.2%
7 24
 
4.8%
8 18
 
3.6%
9 10
 
2.0%
ValueCountFrequency (%)
18 10
 
2.0%
13 1
 
0.2%
12 2
 
0.4%
11 1
 
0.2%
10 5
 
1.0%
9 10
 
2.0%
8 18
 
3.6%
7 24
 
4.8%
6 46
9.2%
5 78
15.6%

인가인원수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:54.214939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:54.320342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

보유소화기수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:54.426955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:54.522893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

보안업무향상안건내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing500
Missing (%)100.0%
Memory size4.5 KiB

사원증직원수
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.512
Minimum0
Maximum67
Zeros15
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:54.619698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median12
Q318
95-th percentile27.05
Maximum67
Range67
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.5453111
Coefficient of variation (CV)0.55841556
Kurtosis8.3713602
Mean13.512
Median Absolute Deviation (MAD)4
Skewness1.7419596
Sum6756
Variance56.931719
MonotonicityNot monotonic
2023-12-12T23:43:54.747072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
8 49
 
9.8%
12 42
 
8.4%
13 37
 
7.4%
11 35
 
7.0%
18 32
 
6.4%
7 29
 
5.8%
6 26
 
5.2%
19 25
 
5.0%
10 25
 
5.0%
16 23
 
4.6%
Other values (23) 177
35.4%
ValueCountFrequency (%)
0 15
 
3.0%
4 6
 
1.2%
5 17
 
3.4%
6 26
5.2%
7 29
5.8%
8 49
9.8%
9 20
4.0%
10 25
5.0%
11 35
7.0%
12 42
8.4%
ValueCountFrequency (%)
67 1
 
0.2%
64 1
 
0.2%
39 1
 
0.2%
38 1
 
0.2%
31 4
0.8%
30 3
0.6%
29 7
1.4%
28 7
1.4%
27 3
0.6%
26 1
 
0.2%

사원증전월보유수
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.228
Minimum0
Maximum64
Zeros14
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:54.900989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median12
Q317
95-th percentile27
Maximum64
Range64
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.9789273
Coefficient of variation (CV)0.52758749
Kurtosis5.4994841
Mean13.228
Median Absolute Deviation (MAD)4
Skewness1.349376
Sum6614
Variance48.705427
MonotonicityNot monotonic
2023-12-12T23:43:55.041019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
11 46
 
9.2%
8 43
 
8.6%
12 39
 
7.8%
7 37
 
7.4%
13 37
 
7.4%
10 31
 
6.2%
18 25
 
5.0%
6 24
 
4.8%
14 21
 
4.2%
19 20
 
4.0%
Other values (21) 177
35.4%
ValueCountFrequency (%)
0 14
 
2.8%
4 7
 
1.4%
5 15
 
3.0%
6 24
4.8%
7 37
7.4%
8 43
8.6%
9 13
 
2.6%
10 31
6.2%
11 46
9.2%
12 39
7.8%
ValueCountFrequency (%)
64 1
 
0.2%
39 1
 
0.2%
36 1
 
0.2%
31 5
1.0%
29 3
 
0.6%
28 8
1.6%
27 9
1.8%
26 3
 
0.6%
25 11
2.2%
24 2
 
0.4%

사원증퇴사직원반납건수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
492 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 492
98.4%
1 8
 
1.6%

Length

2023-12-12T23:43:55.186570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:55.341417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 492
98.4%
1 8
 
1.6%

사원증분실건수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
499 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 499
99.8%
1 1
 
0.2%

Length

2023-12-12T23:43:55.487391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:55.599147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 499
99.8%
1 1
 
0.2%

사원증추가건수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.392
Minimum0
Maximum7
Zeros367
Zeros (%)73.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:55.692289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.77945564
Coefficient of variation (CV)1.9884073
Kurtosis12.753543
Mean0.392
Median Absolute Deviation (MAD)0
Skewness2.8354608
Sum196
Variance0.6075511
MonotonicityNot monotonic
2023-12-12T23:43:55.819308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 367
73.4%
1 87
 
17.4%
2 35
 
7.0%
3 8
 
1.6%
4 2
 
0.4%
7 1
 
0.2%
ValueCountFrequency (%)
0 367
73.4%
1 87
 
17.4%
2 35
 
7.0%
3 8
 
1.6%
4 2
 
0.4%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
4 2
 
0.4%
3 8
 
1.6%
2 35
 
7.0%
1 87
 
17.4%
0 367
73.4%

인가증외부인원수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:55.952888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:56.063847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

인가증전월보유수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:56.191111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:56.305665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

인가증퇴사직원반납건수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:56.426691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:56.532220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

인가증분실건수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:56.642951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:56.744520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

인가증추가건수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-12T23:43:56.848069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:56.948804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

전자결재상태코드
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
13
262 
11
238 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row13
4th row13
5th row11

Common Values

ValueCountFrequency (%)
13 262
52.4%
11 238
47.6%

Length

2023-12-12T23:43:57.063710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:57.185023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 262
52.4%
11 238
47.6%

결재일자
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
00:00.0
262 
0001-01-01 00:00:00.000000
238 

Length

Max length26
Median length7
Mean length16.044
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0001-01-01 00:00:00.000000
2nd row0001-01-01 00:00:00.000000
3rd row00:00.0
4th row00:00.0
5th row0001-01-01 00:00:00.000000

Common Values

ValueCountFrequency (%)
00:00.0 262
52.4%
0001-01-01 00:00:00.000000 238
47.6%

Length

2023-12-12T23:43:57.329435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:43:57.462910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
00:00.0 262
35.5%
0001-01-01 238
32.2%
00:00:00.000000 238
32.2%

삭제여부
Boolean

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
263 
True
237 
ValueCountFrequency (%)
False 263
52.6%
True 237
47.4%
2023-12-12T23:43:57.559858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct9
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.382
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:57.937520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median4
Q34
95-th percentile5
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2974756
Coefficient of variation (CV)0.38364151
Kurtosis3.8925482
Mean3.382
Median Absolute Deviation (MAD)0
Skewness1.1592491
Sum1691
Variance1.6834429
MonotonicityNot monotonic
2023-12-12T23:43:58.032519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 282
56.4%
2 189
37.8%
7 8
 
1.6%
6 8
 
1.6%
5 4
 
0.8%
8 3
 
0.6%
10 3
 
0.6%
3 2
 
0.4%
1 1
 
0.2%
ValueCountFrequency (%)
1 1
 
0.2%
2 189
37.8%
3 2
 
0.4%
4 282
56.4%
5 4
 
0.8%
6 8
 
1.6%
7 8
 
1.6%
8 3
 
0.6%
10 3
 
0.6%
ValueCountFrequency (%)
10 3
 
0.6%
8 3
 
0.6%
7 8
 
1.6%
6 8
 
1.6%
5 4
 
0.8%
4 282
56.4%
3 2
 
0.4%
2 189
37.8%
1 1
 
0.2%

처리시각
Text

Distinct498
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T23:43:58.383072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)99.2%

Sample

1st row06:30.3
2nd row06:30.3
3rd row27:00.0
4th row05:05.9
5th row42:52.0
ValueCountFrequency (%)
06:30.3 2
 
0.4%
17:54.0 2
 
0.4%
24:16.3 1
 
0.2%
37:04.6 1
 
0.2%
45:47.5 1
 
0.2%
37:39.7 1
 
0.2%
38:30.8 1
 
0.2%
39:26.5 1
 
0.2%
39:39.8 1
 
0.2%
40:21.0 1
 
0.2%
Other values (488) 488
97.6%
2023-12-12T23:43:58.876822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 347
9.9%
3 324
9.3%
0 314
9.0%
1 301
8.6%
4 299
8.5%
2 290
8.3%
6 173
 
4.9%
8 156
 
4.5%
Other values (2) 296
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 347
13.9%
3 324
13.0%
0 314
12.6%
1 301
12.0%
4 299
12.0%
2 290
11.6%
6 173
6.9%
8 156
6.2%
7 148
5.9%
9 148
5.9%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 347
9.9%
3 324
9.3%
0 314
9.0%
1 301
8.6%
4 299
8.5%
2 290
8.3%
6 173
 
4.9%
8 156
 
4.5%
Other values (2) 296
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 347
9.9%
3 324
9.3%
0 314
9.0%
1 301
8.6%
4 299
8.5%
2 290
8.3%
6 173
 
4.9%
8 156
 
4.5%
Other values (2) 296
8.5%

처리직원번호
Real number (ℝ)

Distinct304
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4208.682
Minimum1886
Maximum6030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:43:59.026076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1886
5-th percentile3149
Q13644.75
median4150.5
Q34691.5
95-th percentile5336.95
Maximum6030
Range4144
Interquartile range (IQR)1046.75

Descriptive statistics

Standard deviation693.53116
Coefficient of variation (CV)0.16478583
Kurtosis-0.44443849
Mean4208.682
Median Absolute Deviation (MAD)508
Skewness0.11866992
Sum2104341
Variance480985.46
MonotonicityNot monotonic
2023-12-12T23:43:59.208851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4259 9
 
1.8%
3619 8
 
1.6%
5256 7
 
1.4%
5326 7
 
1.4%
4046 7
 
1.4%
5320 6
 
1.2%
4456 5
 
1.0%
4985 5
 
1.0%
3604 5
 
1.0%
3603 5
 
1.0%
Other values (294) 436
87.2%
ValueCountFrequency (%)
1886 1
 
0.2%
2458 2
0.4%
2689 1
 
0.2%
2869 3
0.6%
2876 1
 
0.2%
2895 1
 
0.2%
2957 1
 
0.2%
2966 1
 
0.2%
2994 2
0.4%
3023 1
 
0.2%
ValueCountFrequency (%)
6030 2
0.4%
6019 1
 
0.2%
5851 1
 
0.2%
5593 1
 
0.2%
5572 1
 
0.2%
5478 3
0.6%
5450 2
0.4%
5448 1
 
0.2%
5442 2
0.4%
5438 1
 
0.2%

최초처리시각
Text

Distinct498
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T23:43:59.554345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3500
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique496 ?
Unique (%)99.2%

Sample

1st row06:30.3
2nd row00:45.0
3rd row42:23.1
4th row42:52.0
5th row03:26.5
ValueCountFrequency (%)
24:23.4 2
 
0.4%
14:55.4 2
 
0.4%
59:13.3 1
 
0.2%
36:48.0 1
 
0.2%
06:30.3 1
 
0.2%
34:23.2 1
 
0.2%
31:13.3 1
 
0.2%
36:16.3 1
 
0.2%
25:43.8 1
 
0.2%
30:23.8 1
 
0.2%
Other values (488) 488
97.6%
2023-12-12T23:44:00.035131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 348
9.9%
3 327
9.3%
0 327
9.3%
2 299
8.5%
4 297
8.5%
1 294
8.4%
6 165
 
4.7%
7 150
 
4.3%
Other values (2) 293
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2500
71.4%
Other Punctuation 1000
 
28.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 348
13.9%
3 327
13.1%
0 327
13.1%
2 299
12.0%
4 297
11.9%
1 294
11.8%
6 165
6.6%
7 150
6.0%
9 148
5.9%
8 145
5.8%
Other Punctuation
ValueCountFrequency (%)
: 500
50.0%
. 500
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 348
9.9%
3 327
9.3%
0 327
9.3%
2 299
8.5%
4 297
8.5%
1 294
8.4%
6 165
 
4.7%
7 150
 
4.3%
Other values (2) 293
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
5 348
9.9%
3 327
9.3%
0 327
9.3%
2 299
8.5%
4 297
8.5%
1 294
8.4%
6 165
 
4.7%
7 150
 
4.3%
Other values (2) 293
8.4%

최초처리직원번호
Real number (ℝ)

Distinct198
Distinct (%)39.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4695.542
Minimum2443
Maximum6077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T23:44:00.227880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2443
5-th percentile3352
Q14397.25
median4837
Q35214
95-th percentile5478
Maximum6077
Range3634
Interquartile range (IQR)816.75

Descriptive statistics

Standard deviation677.11519
Coefficient of variation (CV)0.14420384
Kurtosis0.26499919
Mean4695.542
Median Absolute Deviation (MAD)393
Skewness-0.77720149
Sum2347771
Variance458484.99
MonotonicityNot monotonic
2023-12-12T23:44:00.381970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4259 11
 
2.2%
5326 9
 
1.8%
5256 9
 
1.8%
3619 9
 
1.8%
5320 8
 
1.6%
3604 7
 
1.4%
4046 7
 
1.4%
4992 7
 
1.4%
4877 7
 
1.4%
3603 7
 
1.4%
Other values (188) 419
83.8%
ValueCountFrequency (%)
2443 1
 
0.2%
2711 1
 
0.2%
2869 5
1.0%
2876 3
0.6%
3074 3
0.6%
3191 2
 
0.4%
3283 2
 
0.4%
3290 2
 
0.4%
3291 1
 
0.2%
3294 2
 
0.4%
ValueCountFrequency (%)
6077 1
 
0.2%
6030 2
0.4%
6019 3
0.6%
6011 1
 
0.2%
5930 1
 
0.2%
5903 1
 
0.2%
5869 1
 
0.2%
5851 3
0.6%
5839 1
 
0.2%
5719 1
 
0.2%

사원증감소건수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
456 
1
 
39
2
 
3
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 456
91.2%
1 39
 
7.8%
2 3
 
0.6%
4 2
 
0.4%

Length

2023-12-12T23:44:00.533188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:44:00.631978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 456
91.2%
1 39
 
7.8%
2 3
 
0.6%
4 2
 
0.4%

Sample

사이버보안결과ID작성일자작성자직원번호예비군인원수민방위인원수비대원인원수남자인원수여자인원수인가인원수보유소화기수보안업무향상안건내용사원증직원수사원증전월보유수사원증퇴사직원반납건수사원증분실건수사원증추가건수인가증외부인원수인가증전월보유수인가증퇴사직원반납건수인가증분실건수인가증추가건수전자결재상태코드결재일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호사원증감소건수
09dnOBw5NBS00:00.042592518201800<NA>252500000000110001-01-01 00:00:00.000000N106:30.3425906:30.342590
19dnOA9IaRS00:00.042592518201800<NA>252500000000110001-01-01 00:00:00.000000Y206:30.3425900:45.042590
29dngBHX7qe00:00.05238011816300<NA>1919000000001300:00.0N427:00.0415942:23.152380
39dngFFysG000:00.053361379200<NA>1111000000001300:00.0N405:05.9414242:52.053360
49dm2393bDi00:00.053361379200<NA>111100000000110001-01-01 00:00:00.000000Y842:52.0533603:26.553360
59dm2YTYu4800:00.05238011816300<NA>191900000000110001-01-01 00:00:00.000000Y742:23.1523843:08.352380
69dnfurLyvv00:00.05449211415200<NA>017000000001300:00.0N426:25.8399104:50.654490
79dnfq6vLXt00:00.059030488400<NA>1211001000001300:00.0N415:31.9364413:48.159030
89dnfqaxw8f00:00.055722186500<NA>1110001000001300:00.0N412:49.2354559:31.455720
99dnfqiuuL900:00.0484101127600<NA>1312001000001300:00.0N402:37.1455401:29.048410
사이버보안결과ID작성일자작성자직원번호예비군인원수민방위인원수비대원인원수남자인원수여자인원수인가인원수보유소화기수보안업무향상안건내용사원증직원수사원증전월보유수사원증퇴사직원반납건수사원증분실건수사원증추가건수인가증외부인원수인가증전월보유수인가증퇴사직원반납건수인가증분실건수인가증추가건수전자결재상태코드결재일자삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호사원증감소건수
4909dmnSEsDb900:00.033520030300<NA>212300000000110001-01-01 00:00:00.000000Y217:18.7335214:12.633522
4919dmnR48shm00:00.033520030300<NA>212300000000110001-01-01 00:00:00.000000Y214:12.6335205:30.633522
4929dmmq8ikvL00:00.04493001614200<NA>1615001000001300:00.0N407:16.0365927:21.544930
4939dmmBKBRad00:00.051911405000<NA>1818000000001300:00.0N405:15.2443009:29.051910
4949dmnQOKhD400:00.05230121512600<NA>181700100000110001-01-01 00:00:00.000000Y254:12.6523046:12.352300
4959dmmVxqZxP00:00.05230121512600<NA>181700100000110001-01-01 00:00:00.000000Y246:12.3523011:36.952300
4969dmnQwJPXX00:00.054780075200<NA>6600000000110001-01-01 00:00:00.000000Y242:08.2547841:46.254780
4979dmnQhkpgL00:00.054780064200<NA>6600000000110001-01-01 00:00:00.000000Y441:46.2547837:58.554780
4989dmmVsYcrT00:00.054511066100<NA>77000000001300:00.0N412:15.7376710:31.054510
4999dmmUtRqEl00:00.05230121512600<NA>181700100000110001-01-01 00:00:00.000000Y211:36.9523055:28.052300