Overview

Dataset statistics

Number of variables8
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory70.7 B

Variable types

Categorical4
Numeric3
Boolean1

Dataset

Description해당 파일 데이터는 신용보증기금의 보증고객 창업기업 성과공유금 유예 상세 내용에 대해 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15093267/fileData.do

Alerts

업무구분코드 has constant value ""Constant
삭제여부 has constant value ""Constant
최초처리시각 has constant value ""Constant
최초처리직원번호 has constant value ""Constant

Reproduction

Analysis started2023-12-12 09:48:44.409076
Analysis finished2023-12-12 09:48:45.491694
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업무구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
G
49 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
G 49
100.0%

Length

2023-12-12T18:48:45.551373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:45.636517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 49
100.0%

전자결재상태코드
Categorical

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
13
42 
11
7 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 42
85.7%
11 7
 
14.3%

Length

2023-12-12T18:48:45.724577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:45.820799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 42
85.7%
11 7
 
14.3%

유예대상금액
Real number (ℝ)

Distinct35
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3757530.6
Minimum1000000
Maximum7992000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T18:48:45.918384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000000
5-th percentile1192400
Q12000000
median3600000
Q35040000
95-th percentile6000000
Maximum7992000
Range6992000
Interquartile range (IQR)3040000

Descriptive statistics

Standard deviation1880882.9
Coefficient of variation (CV)0.50056355
Kurtosis-0.88311269
Mean3757530.6
Median Absolute Deviation (MAD)1600000
Skewness0.22725854
Sum1.84119 × 108
Variance3.5377203 × 1012
MonotonicityNot monotonic
2023-12-12T18:48:46.041072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5900000 4
 
8.2%
4000000 3
 
6.1%
6000000 3
 
6.1%
2000000 3
 
6.1%
1800000 2
 
4.1%
3300000 2
 
4.1%
5940000 2
 
4.1%
5000000 2
 
4.1%
1000000 2
 
4.1%
3600000 1
 
2.0%
Other values (25) 25
51.0%
ValueCountFrequency (%)
1000000 2
4.1%
1190000 1
 
2.0%
1196000 1
 
2.0%
1200000 1
 
2.0%
1230000 1
 
2.0%
1304000 1
 
2.0%
1400000 1
 
2.0%
1800000 2
4.1%
1860000 1
 
2.0%
2000000 3
6.1%
ValueCountFrequency (%)
7992000 1
 
2.0%
7660000 1
 
2.0%
6000000 3
6.1%
5995000 1
 
2.0%
5940000 2
4.1%
5900000 4
8.2%
5040000 1
 
2.0%
5000000 2
4.1%
4940000 1
 
2.0%
4880000 1
 
2.0%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size181.0 B
False
49 
ValueCountFrequency (%)
False 49
100.0%
2023-12-12T18:48:46.140387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Real number (ℝ)

Distinct21
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.244898
Minimum2
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T18:48:46.215495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.4
Q14
median9
Q313
95-th percentile27.8
Maximum37
Range35
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.885986
Coefficient of variation (CV)0.76974764
Kurtosis2.4052701
Mean10.244898
Median Absolute Deviation (MAD)5
Skewness1.6133418
Sum502
Variance62.188776
MonotonicityNot monotonic
2023-12-12T18:48:46.329250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4 12
24.5%
9 7
14.3%
10 3
 
6.1%
7 3
 
6.1%
5 3
 
6.1%
2 2
 
4.1%
8 2
 
4.1%
15 2
 
4.1%
29 2
 
4.1%
17 2
 
4.1%
Other values (11) 11
22.4%
ValueCountFrequency (%)
2 2
 
4.1%
3 1
 
2.0%
4 12
24.5%
5 3
 
6.1%
6 1
 
2.0%
7 3
 
6.1%
8 2
 
4.1%
9 7
14.3%
10 3
 
6.1%
11 1
 
2.0%
ValueCountFrequency (%)
37 1
2.0%
29 2
4.1%
26 1
2.0%
25 1
2.0%
20 1
2.0%
17 2
4.1%
16 1
2.0%
15 2
4.1%
14 1
2.0%
13 1
2.0%

처리직원번호
Real number (ℝ)

Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4026.6327
Minimum2458
Maximum5076
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T18:48:46.490788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2458
5-th percentile2712
Q13487
median4252
Q34528
95-th percentile5035.6
Maximum5076
Range2618
Interquartile range (IQR)1041

Descriptive statistics

Standard deviation727.80523
Coefficient of variation (CV)0.18074786
Kurtosis-0.6756475
Mean4026.6327
Median Absolute Deviation (MAD)485
Skewness-0.53061162
Sum197305
Variance529700.45
MonotonicityNot monotonic
2023-12-12T18:48:46.713442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
4528 3
 
6.1%
4496 3
 
6.1%
2458 2
 
4.1%
4601 2
 
4.1%
3553 2
 
4.1%
2712 2
 
4.1%
4656 2
 
4.1%
4999 1
 
2.0%
3419 1
 
2.0%
3326 1
 
2.0%
Other values (30) 30
61.2%
ValueCountFrequency (%)
2458 2
4.1%
2712 2
4.1%
2895 1
2.0%
3059 1
2.0%
3117 1
2.0%
3224 1
2.0%
3290 1
2.0%
3326 1
2.0%
3398 1
2.0%
3419 1
2.0%
ValueCountFrequency (%)
5076 1
 
2.0%
5062 1
 
2.0%
5060 1
 
2.0%
4999 1
 
2.0%
4994 1
 
2.0%
4876 1
 
2.0%
4792 1
 
2.0%
4656 2
4.1%
4601 2
4.1%
4528 3
6.1%

최초처리시각
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
0001-01-01 00:00:00.000000
49 

Length

Max length26
Median length26
Mean length26
Min length26

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0001-01-01 00:00:00.000000 49
100.0%

Length

2023-12-12T18:48:46.879876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:47.083247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 49
50.0%
00:00:00.000000 49
50.0%

최초처리직원번호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
BATCH
49 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BATCH 49
100.0%

Length

2023-12-12T18:48:47.201672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:48:47.302211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
batch 49
100.0%

Interactions

2023-12-12T18:48:45.064484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.572020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.832341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:45.140217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.668455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.916193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:45.217396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.756580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:48:44.990225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:48:47.373343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전자결재상태코드유예대상금액최종수정수처리직원번호
전자결재상태코드1.0000.0000.2320.000
유예대상금액0.0001.0000.4420.466
최종수정수0.2320.4421.0000.000
처리직원번호0.0000.4660.0001.000
2023-12-12T18:48:47.485316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유예대상금액최종수정수처리직원번호전자결재상태코드
유예대상금액1.0000.0250.0660.000
최종수정수0.0251.0000.0270.181
처리직원번호0.0660.0271.0000.000
전자결재상태코드0.0000.1810.0001.000

Missing values

2023-12-12T18:48:45.325127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:48:45.444153image/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

업무구분코드전자결재상태코드유예대상금액삭제여부최종수정수처리직원번호최초처리시각최초처리직원번호
0G115040000N945280001-01-01 00:00:00.000000BATCH
1G117992000N750760001-01-01 00:00:00.000000BATCH
2G134000000N1744960001-01-01 00:00:00.000000BATCH
3G115900000N739000001-01-01 00:00:00.000000BATCH
4G131400000N2933980001-01-01 00:00:00.000000BATCH
5G134000000N1735120001-01-01 00:00:00.000000BATCH
6G133300000N1249940001-01-01 00:00:00.000000BATCH
7G131860000N445280001-01-01 00:00:00.000000BATCH
8G134000000N1649990001-01-01 00:00:00.000000BATCH
9G135000000N948760001-01-01 00:00:00.000000BATCH
업무구분코드전자결재상태코드유예대상금액삭제여부최종수정수처리직원번호최초처리시각최초처리직원번호
39G134560000N431170001-01-01 00:00:00.000000BATCH
40G134520000N434190001-01-01 00:00:00.000000BATCH
41G134140000N1524580001-01-01 00:00:00.000000BATCH
42G132650000N3745150001-01-01 00:00:00.000000BATCH
43G135940000N942900001-01-01 00:00:00.000000BATCH
44G133000000N428950001-01-01 00:00:00.000000BATCH
45G131190000N937320001-01-01 00:00:00.000000BATCH
46G135995000N1144210001-01-01 00:00:00.000000BATCH
47G132000000N2940860001-01-01 00:00:00.000000BATCH
48G136000000N642690001-01-01 00:00:00.000000BATCH