Overview

Dataset statistics

Number of variables14
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.4%
Total size in memory56.3 KiB
Average record size in memory115.3 B

Variable types

DateTime4
Categorical6
Text1
Numeric1
Boolean2

Dataset

Description해당 파일 데이터는 신용보증기금의 사후관리기일내역에 대한 정보를 확인하실 수 있는 자료이니 데이터 활용에 참고하여 주시기 바랍니다.
Author신용보증기금
URLhttps://www.data.go.kr/data/15092842/fileData.do

Alerts

기준일자 has constant value ""Constant
업무구분코드 has constant value ""Constant
사후관리기록표종류코드 has constant value ""Constant
취급일자 has constant value ""Constant
사후관리기한 has constant value ""Constant
이메일전송여부 has constant value ""Constant
삭제여부 has constant value ""Constant
최종수정수 has constant value ""Constant
처리직원번호 has constant value ""Constant
최초처리시각 has constant value ""Constant
최초처리직원번호 has constant value ""Constant
Dataset has 2 (0.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 23:21:29.615418
Analysis finished2023-12-12 23:21:30.227196
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:21:30.269340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:30.361377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

업무구분코드
Categorical

CONSTANT 

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

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 500
100.0%

Length

2023-12-13T08:21:30.457320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:30.534923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 500
100.0%

사후관리기록표종류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
5
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 500
100.0%

Length

2023-12-13T08:21:30.616725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:30.697206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 500
100.0%

기업고객ID
Text

Distinct498
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-13T08:21:30.927812image/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

Unique496 ?
Unique (%)99.2%

Sample

1st row9cgEaxTZ42
2nd row9ck5ITzBw4
3rd row9ckQsUV429
4th row9ckIWzPTcF
5th row9ckTmjyixv
ValueCountFrequency (%)
9cep4vkmvg 2
 
0.4%
9ciutkvlok 2
 
0.4%
9b0hs1sjzf 1
 
0.2%
9ciy0qhbb8 1
 
0.2%
9cgeaxtz42 1
 
0.2%
9cimdhtmbv 1
 
0.2%
9ciuoykdim 1
 
0.2%
9ci0aq8uox 1
 
0.2%
9ciiunmxij 1
 
0.2%
9ci408cqql 1
 
0.2%
Other values (488) 488
97.6%
2023-12-13T08:21:31.305392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 569
 
11.4%
c 507
 
10.1%
j 201
 
4.0%
i 191
 
3.8%
b 118
 
2.4%
k 117
 
2.3%
h 116
 
2.3%
a 90
 
1.8%
f 76
 
1.5%
Q 71
 
1.4%
Other values (52) 2944
58.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2454
49.1%
Uppercase Letter 1451
29.0%
Decimal Number 1095
21.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 507
20.7%
j 201
 
8.2%
i 191
 
7.8%
b 118
 
4.8%
k 117
 
4.8%
h 116
 
4.7%
a 90
 
3.7%
f 76
 
3.1%
l 69
 
2.8%
n 67
 
2.7%
Other values (16) 902
36.8%
Uppercase Letter
ValueCountFrequency (%)
Q 71
 
4.9%
Y 68
 
4.7%
A 66
 
4.5%
T 66
 
4.5%
H 64
 
4.4%
O 63
 
4.3%
I 60
 
4.1%
M 60
 
4.1%
L 57
 
3.9%
S 57
 
3.9%
Other values (16) 819
56.4%
Decimal Number
ValueCountFrequency (%)
9 569
52.0%
5 68
 
6.2%
4 67
 
6.1%
7 66
 
6.0%
8 66
 
6.0%
0 65
 
5.9%
3 55
 
5.0%
2 49
 
4.5%
6 48
 
4.4%
1 42
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 3905
78.1%
Common 1095
 
21.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 507
 
13.0%
j 201
 
5.1%
i 191
 
4.9%
b 118
 
3.0%
k 117
 
3.0%
h 116
 
3.0%
a 90
 
2.3%
f 76
 
1.9%
Q 71
 
1.8%
l 69
 
1.8%
Other values (42) 2349
60.2%
Common
ValueCountFrequency (%)
9 569
52.0%
5 68
 
6.2%
4 67
 
6.1%
7 66
 
6.0%
8 66
 
6.0%
0 65
 
5.9%
3 55
 
5.0%
2 49
 
4.5%
6 48
 
4.4%
1 42
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 569
 
11.4%
c 507
 
10.1%
j 201
 
4.0%
i 191
 
3.8%
b 118
 
2.4%
k 117
 
2.3%
h 116
 
2.3%
a 90
 
1.8%
f 76
 
1.5%
Q 71
 
1.4%
Other values (52) 2944
58.9%

취급일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:21:31.415465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:31.492641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

사후관리기한
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:00:00
Maximum2023-12-13 00:00:00
2023-12-13T08:21:31.570290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:31.649301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

담당자직원번호
Real number (ℝ)

Distinct327
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4325.112
Minimum1378
Maximum5273
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-13T08:21:31.759133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1378
5-th percentile2979.1
Q13790
median4528
Q34978
95-th percentile5151.05
Maximum5273
Range3895
Interquartile range (IQR)1188

Descriptive statistics

Standard deviation734.75428
Coefficient of variation (CV)0.16988098
Kurtosis0.43772786
Mean4325.112
Median Absolute Deviation (MAD)505
Skewness-0.92048295
Sum2162556
Variance539863.85
MonotonicityNot monotonic
2023-12-13T08:21:31.896878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4753 6
 
1.2%
5015 6
 
1.2%
3790 5
 
1.0%
4804 5
 
1.0%
3464 5
 
1.0%
4135 4
 
0.8%
4537 4
 
0.8%
4902 4
 
0.8%
3475 4
 
0.8%
4086 4
 
0.8%
Other values (317) 453
90.6%
ValueCountFrequency (%)
1378 1
 
0.2%
1803 1
 
0.2%
1940 2
0.4%
2398 3
0.6%
2450 3
0.6%
2458 1
 
0.2%
2510 2
0.4%
2522 3
0.6%
2687 1
 
0.2%
2712 1
 
0.2%
ValueCountFrequency (%)
5273 1
 
0.2%
5260 3
0.6%
5252 1
 
0.2%
5239 3
0.6%
5238 1
 
0.2%
5236 1
 
0.2%
5235 1
 
0.2%
5233 1
 
0.2%
5231 2
0.4%
5206 1
 
0.2%

이메일전송여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
True
500 
ValueCountFrequency (%)
True 500
100.0%
2023-12-13T08:21:31.994837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size632.0 B
False
500 
ValueCountFrequency (%)
False 500
100.0%
2023-12-13T08:21:32.054487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

최종수정수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 500
100.0%

Length

2023-12-13T08:21:32.137007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:32.251613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 500
100.0%

처리시각
Date

Distinct59
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
Minimum2023-12-13 00:07:12
Maximum2023-12-13 00:49:42
2023-12-13T08:21:32.343595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:21:32.528364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

처리직원번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
AAR01
500 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAAR01
2nd rowAAR01
3rd rowAAR01
4th rowAAR01
5th rowAAR01

Common Values

ValueCountFrequency (%)
AAR01 500
100.0%

Length

2023-12-13T08:21:32.640627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:32.728456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
aar01 500
100.0%

최초처리시각
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0001-01-01 00:00:00.000000
500 

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 500
100.0%

Length

2023-12-13T08:21:32.810681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:32.892721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0001-01-01 500
50.0%
00:00:00.000000 500
50.0%

최초처리직원번호
Categorical

CONSTANT 

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

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 500
100.0%

Length

2023-12-13T08:21:32.976515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:21:33.052224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
batch 500
100.0%

Interactions

2023-12-13T08:21:29.860652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:21:33.122355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
담당자직원번호처리시각
담당자직원번호1.0000.339
처리시각0.3391.000

Missing values

2023-12-13T08:21:29.992551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:21:30.162390image/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

기준일자업무구분코드사후관리기록표종류코드기업고객ID취급일자사후관리기한담당자직원번호이메일전송여부삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
000:00.0G59cgEaxTZ4200:00.000:00.04361YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
100:00.0G59ck5ITzBw400:00.000:00.04903YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
200:00.0G59ckQsUV42900:00.000:00.03443YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
300:00.0G59ckIWzPTcF00:00.000:00.04123YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
400:00.0G59ckTmjyixv00:00.000:00.04470YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
500:00.0G59ckFCNJrij00:00.000:00.05187YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
600:00.0G59ckQgZQPHb00:00.000:00.05084YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
700:00.0G59cfoYYkKzt00:00.000:00.03973YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
800:00.0G59cktPvBHSB00:00.000:00.04496YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
900:00.0G59ckbqHR4FC00:00.000:00.04258YN200:19.7AAR010001-01-01 00:00:00.000000BATCH
기준일자업무구분코드사후관리기록표종류코드기업고객ID취급일자사후관리기한담당자직원번호이메일전송여부삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호
49000:00.0G59cgOPc0LGB00:00.000:00.03491YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49100:00.0G59b7M7mZ02k00:00.000:00.04613YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49200:00.0G59chHvQQrDR00:00.000:00.03291YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49300:00.0G59chzYLw8Ox00:00.000:00.04869YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49400:00.0G59cbcEl8M2B00:00.000:00.04999YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49500:00.0G59b2FidIAUQ00:00.000:00.03931YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49600:00.0G59chpFVRjot00:00.000:00.05009YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49700:00.0G59chgprUwvq00:00.000:00.04086YN200:14.9AAR010001-01-01 00:00:00.000000BATCH
49800:00.0G59cf90N5bwm00:00.000:00.04753YN200:22.4AAR010001-01-01 00:00:00.000000BATCH
49900:00.0G59chmilDxng00:00.000:00.02450YN200:22.4AAR010001-01-01 00:00:00.000000BATCH

Duplicate rows

Most frequently occurring

기준일자업무구분코드사후관리기록표종류코드기업고객ID취급일자사후관리기한담당자직원번호이메일전송여부삭제여부최종수정수처리시각처리직원번호최초처리시각최초처리직원번호# duplicates
000:00.0G59cep4VKMvG00:00.000:00.05061YN200:22.9AAR010001-01-01 00:00:00.000000BATCH2
100:00.0G59ciutKvLOK00:00.000:00.04770YN200:10.4AAR010001-01-01 00:00:00.000000BATCH2