Overview

Dataset statistics

Number of variables9
Number of observations4364
Missing cells0
Missing cells (%)0.0%
Duplicate rows259
Duplicate rows (%)5.9%
Total size in memory315.5 KiB
Average record size in memory74.0 B

Variable types

Categorical5
DateTime2
Numeric1
Text1

Dataset

Description세외수입 체납액의 효율적인 징수를 위한 인천광역시 중구 전자예금압류시스템에 등록된 체납자구분, 제3채무자, 압류일자, 압류내역 발송결과, 해제금액, 체납처분비 포함여부, 금액, 채납내역 부서, 과목 등에 관한 정보입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15085957/fileData.do

Alerts

금액 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 259 (5.9%) duplicate rowsDuplicates
체납내역 부서 is highly overall correlated with 압류내역 발송결과High correlation
제3채무자 is highly overall correlated with 압류내역 발송결과High correlation
압류내역 발송결과 is highly overall correlated with 해제금액 and 3 other fieldsHigh correlation
체납자구분 is highly overall correlated with 압류내역 발송결과High correlation
해제금액 is highly overall correlated with 압류내역 발송결과High correlation
체납자구분 is highly imbalanced (94.4%)Imbalance
압류내역 발송결과 is highly imbalanced (93.9%)Imbalance
해제금액 has 1096 (25.1%) zerosZeros

Reproduction

Analysis started2024-04-17 16:11:38.121705
Analysis finished2024-04-17 16:11:38.857103
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

체납자구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
개인
4317 
법인
 
44
사업
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 4317
98.9%
법인 44
 
1.0%
사업 3
 
0.1%

Length

2024-04-18T01:11:38.901567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:11:38.981709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 4317
98.9%
법인 44
 
1.0%
사업 3
 
0.1%

제3채무자
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
농협은행
968 
신한은행
828 
국민은행
701 
우리은행
492 
기업은행
398 
Other values (15)
977 

Length

Max length8
Median length4
Mean length4.374198
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row기업은행
2nd row농협은행
3rd row우리은행
4th row경남은행
5th row신한은행

Common Values

ValueCountFrequency (%)
농협은행 968
22.2%
신한은행 828
19.0%
국민은행 701
16.1%
우리은행 492
11.3%
기업은행 398
9.1%
KEB하나은행 384
 
8.8%
수협은행 218
 
5.0%
카카오뱅크 93
 
2.1%
씨티은행 86
 
2.0%
하나(외환)은행 82
 
1.9%
Other values (10) 114
 
2.6%

Length

2024-04-18T01:11:39.071529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
농협은행 968
22.2%
신한은행 828
19.0%
국민은행 701
16.1%
우리은행 492
11.3%
기업은행 398
9.1%
keb하나은행 384
 
8.8%
수협은행 218
 
5.0%
카카오뱅크 93
 
2.1%
씨티은행 86
 
2.0%
하나(외환)은행 82
 
1.9%
Other values (10) 114
 
2.6%

압류일자
Date

Distinct112
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
Minimum2014-11-21 00:00:00
Maximum2023-07-25 00:00:00
2024-04-18T01:11:39.168370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:11:39.295114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

압류내역 발송결과
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
정상
4333 
<NA>
 
31

Length

Max length4
Median length2
Mean length2.0142071
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 4333
99.3%
<NA> 31
 
0.7%

Length

2024-04-18T01:11:39.425824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:11:39.508415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 4333
99.3%
na 31
 
0.7%

해제금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1180
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7118032.2
Minimum0
Maximum8.6019016 × 108
Zeros1096
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size38.5 KiB
2024-04-18T01:11:39.593868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1402200
Q32470000
95-th percentile13865000
Maximum8.6019016 × 108
Range8.6019016 × 108
Interquartile range (IQR)2470000

Descriptive statistics

Standard deviation45162629
Coefficient of variation (CV)6.3448194
Kurtosis210.94485
Mean7118032.2
Median Absolute Deviation (MAD)1145250
Skewness13.586366
Sum3.1063093 × 1010
Variance2.039663 × 1015
MonotonicityNot monotonic
2024-04-18T01:11:39.694727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1096
 
25.1%
1593000 33
 
0.8%
2124000 23
 
0.5%
397800 17
 
0.4%
1247400 13
 
0.3%
347400 13
 
0.3%
5000000 12
 
0.3%
351000 12
 
0.3%
1031400 10
 
0.2%
1085400 10
 
0.2%
Other values (1170) 3125
71.6%
ValueCountFrequency (%)
0 1096
25.1%
47560 3
 
0.1%
52590 1
 
< 0.1%
83700 4
 
0.1%
84640 3
 
0.1%
107610 5
 
0.1%
180000 5
 
0.1%
200000 2
 
< 0.1%
219600 6
 
0.1%
300000 6
 
0.1%
ValueCountFrequency (%)
860190160 4
 
0.1%
766902810 2
 
< 0.1%
573000000 10
0.2%
344734560 1
 
< 0.1%
314376840 1
 
< 0.1%
285493025 1
 
< 0.1%
283500340 1
 
< 0.1%
279849500 3
 
0.1%
245929970 1
 
< 0.1%
199130400 4
 
0.1%

금액
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
0
4364 

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 4364
100.0%

Length

2024-04-18T01:11:39.785399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T01:11:39.859456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 4364
100.0%

체납내역 부서
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
교통행정과
1741 
교통운수과
1228 
허가민원과
331 
건축과
 
155
환경관리과 등 2개 부서
 
151
Other values (42)
758 

Length

Max length13
Median length5
Mean length5.4530247
Min length3

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
교통행정과 1741
39.9%
교통운수과 1228
28.1%
허가민원과 331
 
7.6%
건축과 155
 
3.6%
환경관리과 등 2개 부서 151
 
3.5%
교통지적과 91
 
2.1%
지적과 88
 
2.0%
건설과 84
 
1.9%
용유개발과 77
 
1.8%
도시개발과 52
 
1.2%
Other values (37) 366
 
8.4%

Length

2024-04-18T01:11:39.935810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교통행정과 1741
32.7%
교통운수과 1232
23.1%
허가민원과 381
 
7.1%
등 317
 
5.9%
부서 317
 
5.9%
2개 307
 
5.8%
건축과 184
 
3.5%
환경관리과 153
 
2.9%
교통지적과 91
 
1.7%
지적과 88
 
1.7%
Other values (30) 520
 
9.8%

과목
Text

Distinct77
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
2024-04-18T01:11:40.069292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length15.74725
Min length4

Characters and Unicode

Total characters68721
Distinct characters139
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.4%

Sample

1st row부동산실권리자명의등기법과징금
2nd row부동산실권리자명의등기법과징금
3rd row부동산실권리자명의등기법과징금
4th row부동산실권리자명의등기법과징금
5th row부동산실권리자명의등기법과징금
ValueCountFrequency (%)
자동차의무보험미가입과태료 2934
26.5%
등 2233
20.2%
세목 2233
20.2%
2개 1968
17.8%
건축법이행강제금 602
 
5.4%
3개 250
 
2.3%
자동차검사지연과태료 189
 
1.7%
특정경유자동차검사위반과태료 72
 
0.7%
부동산실권리자명의등기법과징금 66
 
0.6%
그외수입 52
 
0.5%
Other values (47) 464
 
4.2%
2024-04-18T01:11:40.328156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6699
 
9.7%
과 3372
 
4.9%
료 3355
 
4.9%
태 3301
 
4.8%
동 3298
 
4.8%
자 3296
 
4.8%
차 3239
 
4.7%
입 3039
 
4.4%
의 3029
 
4.4%
무 2959
 
4.3%
Other values (129) 33134
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59711
86.9%
Space Separator 6699
 
9.7%
Decimal Number 2233
 
3.2%
Open Punctuation 39
 
0.1%
Close Punctuation 39
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 3372
 
5.6%
료 3355
 
5.6%
태 3301
 
5.5%
동 3298
 
5.5%
자 3296
 
5.5%
차 3239
 
5.4%
입 3039
 
5.1%
의 3029
 
5.1%
무 2959
 
5.0%
보 2949
 
4.9%
Other values (121) 27874
46.7%
Decimal Number
ValueCountFrequency (%)
2 1968
88.1%
3 250
 
11.2%
4 11
 
0.5%
5 3
 
0.1%
6 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
6699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59711
86.9%
Common 9010
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 3372
 
5.6%
료 3355
 
5.6%
태 3301
 
5.5%
동 3298
 
5.5%
자 3296
 
5.5%
차 3239
 
5.4%
입 3039
 
5.1%
의 3029
 
5.1%
무 2959
 
5.0%
보 2949
 
4.9%
Other values (121) 27874
46.7%
Common
ValueCountFrequency (%)
6699
74.4%
2 1968
 
21.8%
3 250
 
2.8%
( 39
 
0.4%
) 39
 
0.4%
4 11
 
0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59711
86.9%
ASCII 9010
 
13.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6699
74.4%
2 1968
 
21.8%
3 250
 
2.8%
( 39
 
0.4%
) 39
 
0.4%
4 11
 
0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
과 3372
 
5.6%
료 3355
 
5.6%
태 3301
 
5.5%
동 3298
 
5.5%
자 3296
 
5.5%
차 3239
 
5.4%
입 3039
 
5.1%
의 3029
 
5.1%
무 2959
 
5.0%
보 2949
 
4.9%
Other values (121) 27874
46.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
Minimum2023-08-08 00:00:00
Maximum2023-08-08 00:00:00
2024-04-18T01:11:40.422388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T01:11:40.496146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T01:11:38.618238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T01:11:40.556904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납자구분제3채무자해제금액체납내역 부서과목
체납자구분1.0000.2490.1100.6150.975
제3채무자0.2491.0000.2030.2200.137
해제금액0.1100.2031.0000.8230.926
체납내역 부서0.6150.2200.8231.0000.994
과목0.9750.1370.9260.9941.000
2024-04-18T01:11:40.641903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
체납내역 부서제3채무자압류내역 발송결과체납자구분
체납내역 부서1.0000.0561.0000.378
제3채무자0.0561.0001.0000.134
압류내역 발송결과1.0001.0001.0001.000
체납자구분0.3780.1341.0001.000
2024-04-18T01:11:40.713514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해제금액체납자구분제3채무자압류내역 발송결과체납내역 부서
해제금액1.0000.0700.0821.0000.482
체납자구분0.0701.0000.1341.0000.378
제3채무자0.0820.1341.0001.0000.056
압류내역 발송결과1.0001.0001.0001.0001.000
체납내역 부서0.4820.3780.0561.0001.000

Missing values

2024-04-18T01:11:38.709944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T01:11:38.811086image/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

체납자구분제3채무자압류일자압류내역 발송결과해제금액금액체납내역 부서과목데이터기준일
0개인기업은행2014-12-29정상5730000000지적과부동산실권리자명의등기법과징금2023-08-08
1개인농협은행2014-12-29정상5730000000지적과부동산실권리자명의등기법과징금2023-08-08
2개인우리은행2014-12-29정상5730000000지적과부동산실권리자명의등기법과징금2023-08-08
3개인경남은행2014-12-29정상5730000000지적과부동산실권리자명의등기법과징금2023-08-08
4개인신한은행2014-12-29정상5730000000지적과부동산실권리자명의등기법과징금2023-08-08
5개인국민은행2014-12-29정상653520000지적과부동산실권리자명의등기법과징금2023-08-08
6개인하나(외환)은행2014-12-29정상116000000지적과부동산실권리자명의등기법과징금2023-08-08
7개인신한은행2014-12-29정상116000000지적과부동산실권리자명의등기법과징금2023-08-08
8개인국민은행2014-12-29정상416000000지적과부동산실권리자명의등기법과징금2023-08-08
9개인하나(외환)은행2014-12-29정상416000000지적과부동산실권리자명의등기법과징금2023-08-08
체납자구분제3채무자압류일자압류내역 발송결과해제금액금액체납내역 부서과목데이터기준일
4354개인신한은행2023-07-25정상00환경보호과 등 2개 부서자동차의무보험미가입과태료 등 3개 세목2023-08-08
4355개인수협은행2023-07-25정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-08
4356개인농협은행2023-07-25정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-08
4357개인기업은행2023-07-25정상00교통운수과자동차의무보험미가입과태료2023-08-08
4358개인국민은행2023-07-25정상00교통운수과자동차의무보험미가입과태료2023-08-08
4359개인카카오뱅크2023-07-25정상00교통운수과자동차의무보험미가입과태료2023-08-08
4360개인농협은행2023-07-25정상00환경보호과 등 2개 부서자동차의무보험미가입과태료 등 3개 세목2023-08-08
4361개인우리은행2023-07-25정상00환경보호과 등 2개 부서자동차의무보험미가입과태료 등 3개 세목2023-08-08
4362개인농협은행2023-07-25정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-08
4363개인KEB하나은행2023-07-25정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-08

Duplicate rows

Most frequently occurring

체납자구분제3채무자압류일자압류내역 발송결과해제금액금액체납내역 부서과목데이터기준일# duplicates
123개인농협은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-0820
47개인국민은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-0817
195개인신한은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-0817
229개인우리은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-0811
128개인농협은행2019-09-27정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-0810
64개인기업은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-089
14개인KEB하나은행2018-11-12정상00교통운수과자동차의무보험미가입과태료 등 2개 세목2023-08-088
68개인농협은행2014-11-28정상00교통행정과자동차의무보험미가입과태료 등 2개 세목2023-08-088
97개인농협은행2017-05-30정상00교통지적과개발부담금2023-08-088
111개인농협은행2017-12-27정상00허가민원과건축법이행강제금2023-08-087