Overview

Dataset statistics

Number of variables9
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.2 KiB
Average record size in memory76.3 B

Variable types

Categorical2
Text2
Numeric3
DateTime2

Dataset

Description해당 파일 데이터는 신용보증기금의 보험청약접수설계제안서관계에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093281/fileData.do

Alerts

업무구분코드 has constant value ""Constant
설계제안서원장역할관계코드 has constant value ""Constant
유효개시일자 has constant value ""Constant
유효종료일자 has constant value ""Constant

Reproduction

Analysis started2023-12-12 02:56:17.628875
Analysis finished2023-12-12 02:56:19.838852
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업무구분코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
A 500
100.0%

Length

2023-12-12T11:56:19.944039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:20.086699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 500
100.0%

설계제안서원장역할관계코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
1
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 500
100.0%

Length

2023-12-12T11:56:20.243737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:20.378264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 500
100.0%

설계제안서ID
Text

Distinct280
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T11:56:20.697661image/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

Unique150 ?
Unique (%)30.0%

Sample

1st row9dnN9Edyol
2nd row9dnN9Edyol
3rd row9dnOmKP9Wr
4th row9dnOmKP9Wr
5th row9dnlA02IZq
ValueCountFrequency (%)
9dncawhknj 13
 
2.6%
9dncg1lwvt 8
 
1.6%
9dnokglcuw 6
 
1.2%
9dng3mlbld 5
 
1.0%
9dnomkp9wr 5
 
1.0%
9dnjh3ejvf 5
 
1.0%
9dnk77wmrm 5
 
1.0%
9dnta06gki 4
 
0.8%
9dnmxiwt5u 4
 
0.8%
9dnaokwly0 4
 
0.8%
Other values (270) 441
88.2%
2023-12-12T11:56:21.248579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
d 546
 
10.9%
9 537
 
10.7%
n 533
 
10.7%
J 105
 
2.1%
C 104
 
2.1%
M 93
 
1.9%
h 93
 
1.9%
A 91
 
1.8%
z 91
 
1.8%
L 79
 
1.6%
Other values (52) 2728
54.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2481
49.6%
Uppercase Letter 1522
30.4%
Decimal Number 997
19.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 546
22.0%
n 533
21.5%
h 93
 
3.7%
z 91
 
3.7%
p 79
 
3.2%
m 75
 
3.0%
l 71
 
2.9%
y 69
 
2.8%
q 66
 
2.7%
k 66
 
2.7%
Other values (16) 792
31.9%
Uppercase Letter
ValueCountFrequency (%)
J 105
 
6.9%
C 104
 
6.8%
M 93
 
6.1%
A 91
 
6.0%
L 79
 
5.2%
D 79
 
5.2%
W 70
 
4.6%
O 65
 
4.3%
B 57
 
3.7%
I 56
 
3.7%
Other values (16) 723
47.5%
Decimal Number
ValueCountFrequency (%)
9 537
53.9%
7 61
 
6.1%
1 57
 
5.7%
0 53
 
5.3%
4 51
 
5.1%
6 51
 
5.1%
3 51
 
5.1%
2 49
 
4.9%
5 47
 
4.7%
8 40
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4003
80.1%
Common 997
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 546
 
13.6%
n 533
 
13.3%
J 105
 
2.6%
C 104
 
2.6%
M 93
 
2.3%
h 93
 
2.3%
A 91
 
2.3%
z 91
 
2.3%
L 79
 
2.0%
D 79
 
2.0%
Other values (42) 2189
54.7%
Common
ValueCountFrequency (%)
9 537
53.9%
7 61
 
6.1%
1 57
 
5.7%
0 53
 
5.3%
4 51
 
5.1%
6 51
 
5.1%
3 51
 
5.1%
2 49
 
4.9%
5 47
 
4.7%
8 40
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 546
 
10.9%
9 537
 
10.7%
n 533
 
10.7%
J 105
 
2.1%
C 104
 
2.1%
M 93
 
1.9%
h 93
 
1.9%
A 91
 
1.8%
z 91
 
1.8%
L 79
 
1.6%
Other values (52) 2728
54.6%

이력일련번호
Real number (ℝ)

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.72
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:56:21.454929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile7
Maximum25
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.977807
Coefficient of variation (CV)1.094782
Kurtosis16.400485
Mean2.72
Median Absolute Deviation (MAD)0
Skewness3.3795727
Sum1360
Variance8.8673347
MonotonicityNot monotonic
2023-12-12T11:56:21.629462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 281
56.2%
3 121
24.2%
5 52
 
10.4%
7 23
 
4.6%
9 10
 
2.0%
11 4
 
0.8%
15 2
 
0.4%
13 2
 
0.4%
25 1
 
0.2%
23 1
 
0.2%
Other values (3) 3
 
0.6%
ValueCountFrequency (%)
1 281
56.2%
3 121
24.2%
5 52
 
10.4%
7 23
 
4.6%
9 10
 
2.0%
11 4
 
0.8%
13 2
 
0.4%
15 2
 
0.4%
17 1
 
0.2%
19 1
 
0.2%
ValueCountFrequency (%)
25 1
 
0.2%
23 1
 
0.2%
21 1
 
0.2%
19 1
 
0.2%
17 1
 
0.2%
15 2
 
0.4%
13 2
 
0.4%
11 4
 
0.8%
9 10
2.0%
7 23
4.6%

유효개시일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T11:56:21.783466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:21.919138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

유효종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 00:00:00
2023-12-12T11:56:22.056529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:22.195073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종수정수
Real number (ℝ)

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.262
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:56:22.316522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile8
Maximum25
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0482683
Coefficient of variation (CV)0.93447834
Kurtosis15.286096
Mean3.262
Median Absolute Deviation (MAD)1
Skewness3.2247354
Sum1631
Variance9.2919399
MonotonicityNot monotonic
2023-12-12T11:56:22.494877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 140
28.0%
2 132
26.4%
3 67
13.4%
4 60
12.0%
5 28
 
5.6%
6 25
 
5.0%
7 13
 
2.6%
8 12
 
2.4%
9 6
 
1.2%
10 4
 
0.8%
Other values (10) 13
 
2.6%
ValueCountFrequency (%)
1 140
28.0%
2 132
26.4%
3 67
13.4%
4 60
12.0%
5 28
 
5.6%
6 25
 
5.0%
7 13
 
2.6%
8 12
 
2.4%
9 6
 
1.2%
10 4
 
0.8%
ValueCountFrequency (%)
25 1
 
0.2%
24 1
 
0.2%
22 1
 
0.2%
20 1
 
0.2%
18 1
 
0.2%
16 1
 
0.2%
15 1
 
0.2%
14 2
0.4%
12 3
0.6%
11 1
 
0.2%

처리시각
Text

Distinct491
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-12T11:56:22.991757image/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

Unique482 ?
Unique (%)96.4%

Sample

1st row52:26.0
2nd row52:25.1
3rd row29:46.3
4th row29:45.4
5th row26:05.6
ValueCountFrequency (%)
25:14.0 2
 
0.4%
42:09.4 2
 
0.4%
22:42.7 2
 
0.4%
35:15.8 2
 
0.4%
23:02.3 2
 
0.4%
18:26.6 2
 
0.4%
18:29.8 2
 
0.4%
38:35.5 2
 
0.4%
10:18.3 2
 
0.4%
11:54.2 1
 
0.2%
Other values (481) 481
96.2%
2023-12-12T11:56:23.785985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
1 339
9.7%
2 338
9.7%
0 311
8.9%
3 303
8.7%
5 301
8.6%
4 277
7.9%
9 177
 
5.1%
7 156
 
4.5%
Other values (2) 298
8.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 339
13.6%
2 338
13.5%
0 311
12.4%
3 303
12.1%
5 301
12.0%
4 277
11.1%
9 177
7.1%
7 156
6.2%
8 153
6.1%
6 145
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%
1 339
9.7%
2 338
9.7%
0 311
8.9%
3 303
8.7%
5 301
8.6%
4 277
7.9%
9 177
 
5.1%
7 156
 
4.5%
Other values (2) 298
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 500
14.3%
. 500
14.3%
1 339
9.7%
2 338
9.7%
0 311
8.9%
3 303
8.7%
5 301
8.6%
4 277
7.9%
9 177
 
5.1%
7 156
 
4.5%
Other values (2) 298
8.5%

처리직원번호
Real number (ℝ)

Distinct141
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5134.688
Minimum3168
Maximum6195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-12T11:56:24.030591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3168
5-th percentile3613
Q14679
median5190
Q35642
95-th percentile5938
Maximum6195
Range3027
Interquartile range (IQR)963

Descriptive statistics

Standard deviation671.65948
Coefficient of variation (CV)0.13080824
Kurtosis0.15677375
Mean5134.688
Median Absolute Deviation (MAD)506
Skewness-0.84267358
Sum2567344
Variance451126.46
MonotonicityNot monotonic
2023-12-12T11:56:24.242427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4607 13
 
2.6%
6013 13
 
2.6%
3590 13
 
2.6%
5256 13
 
2.6%
5074 11
 
2.2%
4565 11
 
2.2%
4621 11
 
2.2%
5001 10
 
2.0%
4561 10
 
2.0%
5190 9
 
1.8%
Other values (131) 386
77.2%
ValueCountFrequency (%)
3168 2
 
0.4%
3290 2
 
0.4%
3447 1
 
0.2%
3548 2
 
0.4%
3555 1
 
0.2%
3590 13
2.6%
3598 1
 
0.2%
3613 8
1.6%
3619 1
 
0.2%
3620 5
 
1.0%
ValueCountFrequency (%)
6195 1
 
0.2%
6147 1
 
0.2%
6138 2
 
0.4%
6120 2
 
0.4%
6013 13
2.6%
6008 1
 
0.2%
5942 1
 
0.2%
5938 5
 
1.0%
5927 7
1.4%
5916 4
 
0.8%

Interactions

2023-12-12T11:56:19.107587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.277776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.682856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:19.234613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.402071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.820862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:19.343301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.542760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:18.947617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:56:24.373690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이력일련번호최종수정수처리직원번호
이력일련번호1.0000.9760.271
최종수정수0.9761.0000.334
처리직원번호0.2710.3341.000
2023-12-12T11:56:24.495540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이력일련번호최종수정수처리직원번호
이력일련번호1.0000.4360.058
최종수정수0.4361.0000.054
처리직원번호0.0580.0541.000

Missing values

2023-12-12T11:56:19.501739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:56:19.751367image/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

업무구분코드설계제안서원장역할관계코드설계제안서ID이력일련번호유효개시일자유효종료일자최종수정수처리시각처리직원번호
0A19dnN9Edyol100:00.000:00.0352:26.04565
1A19dnN9Edyol300:00.000:00.0252:25.14565
2A19dnOmKP9Wr100:00.000:00.0929:46.35492
3A19dnOmKP9Wr900:00.000:00.0829:45.45492
4A19dnlA02IZq100:00.000:00.0326:05.65769
5A19dnlA02IZq300:00.000:00.0226:04.75769
6A19dnTbU3PvF100:00.000:00.0120:03.15900
7A19dnOcwsFBJ100:00.000:00.0302:52.55490
8A19dnOcwsFBJ300:00.000:00.0202:51.55490
9A19dnMG253mN100:00.000:00.0126:10.85074
업무구분코드설계제안서원장역할관계코드설계제안서ID이력일련번호유효개시일자유효종료일자최종수정수처리시각처리직원번호
490A19dny3zWpUy100:00.000:00.0127:32.25047
491A19dnp1KnRMC100:00.000:00.0329:21.05406
492A19dnp1KnRMC300:00.000:00.0229:20.15406
493A19dnpVZv4pM100:00.000:00.0326:32.84668
494A19dnpVZv4pM300:00.000:00.0226:32.04668
495A19dny2ZnXxx300:00.000:00.0226:27.33590
496A19dnoN3mq63100:00.000:00.0519:00.06138
497A19dnoN3mq63500:00.000:00.0418:59.26138
498A19dnmZXs73d100:00.000:00.0359:06.75626
499A19dnmZXs73d300:00.000:00.0259:05.75626