Overview

Dataset statistics

Number of variables8
Number of observations68
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory66.9 B

Variable types

Numeric1
Categorical2
Text4
DateTime1

Dataset

Description인천광역시 계양구 관내 대부업 등록 현황에 대한 데이터로, 순번, 시군구명, 등록신청사업, 등록증번호, 상호, 대표자, 소재지(도로명주소), 등록일자 등을 제공합니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078047&srcSe=7661IVAWM27C61E190

Alerts

시군구명 has constant value ""Constant
순번 has unique valuesUnique
등록증번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 02:05:43.422416
Analysis finished2024-03-18 02:05:45.687823
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-03-18T11:05:45.753967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-03-18T11:05:45.887862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
인천광역시 계양구
68 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 계양구
2nd row인천광역시 계양구
3rd row인천광역시 계양구
4th row인천광역시 계양구
5th row인천광역시 계양구

Common Values

ValueCountFrequency (%)
인천광역시 계양구 68
100.0%

Length

2024-03-18T11:05:46.013683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:05:46.105210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 68
50.0%
계양구 68
50.0%

등록신청사업
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
대부업
43 
대부중개업
25 

Length

Max length5
Median length3
Mean length3.7352941
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대부중개업
2nd row대부업
3rd row대부업
4th row대부중개업
5th row대부중개업

Common Values

ValueCountFrequency (%)
대부업 43
63.2%
대부중개업 25
36.8%

Length

2024-03-18T11:05:46.208585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:05:46.289274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 43
63.2%
대부중개업 25
36.8%

등록증번호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-18T11:05:46.472789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length13.897059
Min length11

Characters and Unicode

Total characters945
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)100.0%

Sample

1st row2023-인천계양-0022
2nd row2023-인천계양-0020
3rd row2023-인천계양-0021
4th row2023-인천계양-0019
5th row2023-인천계양-0018
ValueCountFrequency (%)
계양구 9
 
10.5%
인천 9
 
10.5%
2023-인천계양-0020 1
 
1.2%
2021-인천계양-0010 1
 
1.2%
2021-인천계양-0009 1
 
1.2%
2021-인천계양-0007 1
 
1.2%
2021-인천계양-0002 1
 
1.2%
2020-인천계양-0016 1
 
1.2%
2020-인천계양-0014 1
 
1.2%
2020-인천계양-0011 1
 
1.2%
Other values (60) 60
69.8%
2024-03-18T11:05:46.816517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 219
23.2%
2 130
13.8%
- 127
13.4%
인 68
 
7.2%
천 68
 
7.2%
계 68
 
7.2%
양 68
 
7.2%
1 68
 
7.2%
3 30
 
3.2%
18
 
1.9%
Other values (14) 81
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 507
53.7%
Other Letter 289
30.6%
Dash Punctuation 127
 
13.4%
Space Separator 18
 
1.9%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 219
43.2%
2 130
25.6%
1 68
 
13.4%
3 30
 
5.9%
8 17
 
3.4%
5 13
 
2.6%
4 10
 
2.0%
9 8
 
1.6%
6 7
 
1.4%
7 5
 
1.0%
Other Letter
ValueCountFrequency (%)
인 68
23.5%
천 68
23.5%
계 68
23.5%
양 68
23.5%
구 9
 
3.1%
대 2
 
0.7%
부 2
 
0.7%
업 2
 
0.7%
중 1
 
0.3%
개 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 127
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 656
69.4%
Hangul 289
30.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 219
33.4%
2 130
19.8%
- 127
19.4%
1 68
 
10.4%
3 30
 
4.6%
18
 
2.7%
8 17
 
2.6%
5 13
 
2.0%
4 10
 
1.5%
9 8
 
1.2%
Other values (4) 16
 
2.4%
Hangul
ValueCountFrequency (%)
인 68
23.5%
천 68
23.5%
계 68
23.5%
양 68
23.5%
구 9
 
3.1%
대 2
 
0.7%
부 2
 
0.7%
업 2
 
0.7%
중 1
 
0.3%
개 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 656
69.4%
Hangul 289
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 219
33.4%
2 130
19.8%
- 127
19.4%
1 68
 
10.4%
3 30
 
4.6%
18
 
2.7%
8 17
 
2.6%
5 13
 
2.0%
4 10
 
1.5%
9 8
 
1.2%
Other values (4) 16
 
2.4%
Hangul
ValueCountFrequency (%)
인 68
23.5%
천 68
23.5%
계 68
23.5%
양 68
23.5%
구 9
 
3.1%
대 2
 
0.7%
부 2
 
0.7%
업 2
 
0.7%
중 1
 
0.3%
개 1
 
0.3%

상호
Text

Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-18T11:05:47.090224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length8.2058824
Min length3

Characters and Unicode

Total characters558
Distinct characters124
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)97.1%

Sample

1st row정다운대부중개
2nd row24시여성전용대부
3rd rowMC대부
4th row플러스 대부중개
5th row더페스트대부중개
ValueCountFrequency (%)
주식회사 13
 
14.6%
대부 3
 
3.4%
우리모기지론대부 2
 
2.2%
이상준아카데미대부 2
 
2.2%
더희망대부 1
 
1.1%
유베리에셋대부 1
 
1.1%
코리아페이대부 1
 
1.1%
제이에스금융대부중개 1
 
1.1%
한샘파이낸셜대부 1
 
1.1%
주)동행자산관리대부 1
 
1.1%
Other values (63) 63
70.8%
2024-03-18T11:05:47.512146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 70
 
12.5%
부 69
 
12.4%
개 24
 
4.3%
중 24
 
4.3%
21
 
3.8%
주 20
 
3.6%
사 18
 
3.2%
스 16
 
2.9%
식 15
 
2.7%
회 15
 
2.7%
Other values (114) 266
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 514
92.1%
Space Separator 21
 
3.8%
Open Punctuation 8
 
1.4%
Close Punctuation 8
 
1.4%
Uppercase Letter 5
 
0.9%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 70
 
13.6%
부 69
 
13.4%
개 24
 
4.7%
중 24
 
4.7%
주 20
 
3.9%
사 18
 
3.5%
스 16
 
3.1%
식 15
 
2.9%
회 15
 
2.9%
이 13
 
2.5%
Other values (105) 230
44.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
M 1
20.0%
J 1
20.0%
C 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 514
92.1%
Common 39
 
7.0%
Latin 5
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 70
 
13.6%
부 69
 
13.4%
개 24
 
4.7%
중 24
 
4.7%
주 20
 
3.9%
사 18
 
3.5%
스 16
 
3.1%
식 15
 
2.9%
회 15
 
2.9%
이 13
 
2.5%
Other values (105) 230
44.7%
Common
ValueCountFrequency (%)
21
53.8%
( 8
 
20.5%
) 8
 
20.5%
2 1
 
2.6%
4 1
 
2.6%
Latin
ValueCountFrequency (%)
K 2
40.0%
M 1
20.0%
J 1
20.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 514
92.1%
ASCII 44
 
7.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 70
 
13.6%
부 69
 
13.4%
개 24
 
4.7%
중 24
 
4.7%
주 20
 
3.9%
사 18
 
3.5%
스 16
 
3.1%
식 15
 
2.9%
회 15
 
2.9%
이 13
 
2.5%
Other values (105) 230
44.7%
ASCII
ValueCountFrequency (%)
21
47.7%
( 8
 
18.2%
) 8
 
18.2%
K 2
 
4.5%
M 1
 
2.3%
J 1
 
2.3%
C 1
 
2.3%
2 1
 
2.3%
4 1
 
2.3%

대표자
Text

Distinct58
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-18T11:05:47.716491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9558824
Min length2

Characters and Unicode

Total characters201
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)70.6%

Sample

1st row이대한
2nd row강솔
3rd row선용
4th row정준영
5th row박현아
ValueCountFrequency (%)
박금옥 2
 
2.9%
최현주 2
 
2.9%
고근호 2
 
2.9%
노경미 2
 
2.9%
황예빈 2
 
2.9%
이재승 2
 
2.9%
이상준 2
 
2.9%
배성환 2
 
2.9%
곽형웅 2
 
2.9%
하성만 2
 
2.9%
Other values (48) 48
70.6%
2024-03-18T11:05:48.042318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 10
 
5.0%
성 10
 
5.0%
김 8
 
4.0%
현 7
 
3.5%
정 7
 
3.5%
민 6
 
3.0%
준 6
 
3.0%
박 6
 
3.0%
최 6
 
3.0%
경 5
 
2.5%
Other values (67) 130
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
 
5.0%
성 10
 
5.0%
김 8
 
4.0%
현 7
 
3.5%
정 7
 
3.5%
민 6
 
3.0%
준 6
 
3.0%
박 6
 
3.0%
최 6
 
3.0%
경 5
 
2.5%
Other values (67) 130
64.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
 
5.0%
성 10
 
5.0%
김 8
 
4.0%
현 7
 
3.5%
정 7
 
3.5%
민 6
 
3.0%
준 6
 
3.0%
박 6
 
3.0%
최 6
 
3.0%
경 5
 
2.5%
Other values (67) 130
64.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 10
 
5.0%
성 10
 
5.0%
김 8
 
4.0%
현 7
 
3.5%
정 7
 
3.5%
민 6
 
3.0%
준 6
 
3.0%
박 6
 
3.0%
최 6
 
3.0%
경 5
 
2.5%
Other values (67) 130
64.7%

소재지(도로명)
Text

Distinct58
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-03-18T11:05:48.299743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41.5
Mean length38.191176
Min length26

Characters and Unicode

Total characters2597
Distinct characters105
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)70.6%

Sample

1st row인천광역시 계양구 오조산로57번길 7-1, 미래사랑빌딩 7층 스페이스드림 D43호 (계산동)
2nd row인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 186-1호 (계산동)
3rd row인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 192-1호 (계산동)
4th row인천광역시 계양구 오조산로57번길 15, 명동빌딩 768호 (계산동)
5th row인천광역시 계양구 계양대로 40, 401호 (작전동)
ValueCountFrequency (%)
인천광역시 68
 
13.9%
계양구 68
 
13.9%
계산동 48
 
9.8%
계양문화로 15
 
3.1%
오조산로57번길 13
 
2.7%
명동빌딩 12
 
2.4%
15 12
 
2.4%
작전동 11
 
2.2%
54 11
 
2.2%
대산월드프라자 11
 
2.2%
Other values (124) 221
45.1%
2024-03-18T11:05:48.690644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
422
 
16.2%
계 150
 
5.8%
동 92
 
3.5%
양 90
 
3.5%
1 89
 
3.4%
산 88
 
3.4%
, 74
 
2.8%
0 73
 
2.8%
천 72
 
2.8%
( 70
 
2.7%
Other values (95) 1377
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1470
56.6%
Decimal Number 465
 
17.9%
Space Separator 422
 
16.2%
Other Punctuation 74
 
2.8%
Open Punctuation 70
 
2.7%
Close Punctuation 70
 
2.7%
Dash Punctuation 20
 
0.8%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 150
 
10.2%
동 92
 
6.3%
양 90
 
6.1%
산 88
 
6.0%
천 72
 
4.9%
시 69
 
4.7%
인 68
 
4.6%
구 68
 
4.6%
역 68
 
4.6%
광 68
 
4.6%
Other values (77) 637
43.3%
Decimal Number
ValueCountFrequency (%)
1 89
19.1%
0 73
15.7%
5 62
13.3%
7 60
12.9%
3 39
8.4%
4 35
 
7.5%
2 35
 
7.5%
6 29
 
6.2%
8 23
 
4.9%
9 20
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
C 2
33.3%
D 1
 
16.7%
Space Separator
ValueCountFrequency (%)
422
100.0%
Other Punctuation
ValueCountFrequency (%)
, 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1470
56.6%
Common 1121
43.2%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 150
 
10.2%
동 92
 
6.3%
양 90
 
6.1%
산 88
 
6.0%
천 72
 
4.9%
시 69
 
4.7%
인 68
 
4.6%
구 68
 
4.6%
역 68
 
4.6%
광 68
 
4.6%
Other values (77) 637
43.3%
Common
ValueCountFrequency (%)
422
37.6%
1 89
 
7.9%
, 74
 
6.6%
0 73
 
6.5%
( 70
 
6.2%
) 70
 
6.2%
5 62
 
5.5%
7 60
 
5.4%
3 39
 
3.5%
4 35
 
3.1%
Other values (5) 127
 
11.3%
Latin
ValueCountFrequency (%)
B 3
50.0%
C 2
33.3%
D 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1470
56.6%
ASCII 1127
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
422
37.4%
1 89
 
7.9%
, 74
 
6.6%
0 73
 
6.5%
( 70
 
6.2%
) 70
 
6.2%
5 62
 
5.5%
7 60
 
5.3%
3 39
 
3.5%
4 35
 
3.1%
Other values (8) 133
 
11.8%
Hangul
ValueCountFrequency (%)
계 150
 
10.2%
동 92
 
6.3%
양 90
 
6.1%
산 88
 
6.0%
천 72
 
4.9%
시 69
 
4.7%
인 68
 
4.6%
구 68
 
4.6%
역 68
 
4.6%
광 68
 
4.6%
Other values (77) 637
43.3%

등록일자
Date

Distinct52
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2020-11-30 00:00:00
Maximum2023-11-02 00:00:00
2024-03-18T11:05:48.803807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:05:48.914462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-18T11:05:45.366004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:05:48.989911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업등록증번호상호대표자소재지(도로명)등록일자
순번1.0000.1551.0001.0000.9800.9800.975
등록신청사업0.1551.0001.0000.0000.0000.0000.000
등록증번호1.0001.0001.0001.0001.0001.0001.000
상호1.0000.0001.0001.0001.0001.0001.000
대표자0.9800.0001.0001.0001.0001.0000.999
소재지(도로명)0.9800.0001.0001.0001.0001.0000.999
등록일자0.9750.0001.0001.0000.9990.9991.000
2024-03-18T11:05:49.082109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업
순번1.0000.102
등록신청사업0.1021.000

Missing values

2024-03-18T11:05:45.518718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:05:45.635994image/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

순번시군구명등록신청사업등록증번호상호대표자소재지(도로명)등록일자
01인천광역시 계양구대부중개업2023-인천계양-0022정다운대부중개이대한인천광역시 계양구 오조산로57번길 7-1, 미래사랑빌딩 7층 스페이스드림 D43호 (계산동)2023-11-02
12인천광역시 계양구대부업2023-인천계양-002024시여성전용대부강솔인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 186-1호 (계산동)2023-10-20
23인천광역시 계양구대부업2023-인천계양-0021MC대부선용인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 192-1호 (계산동)2023-10-20
34인천광역시 계양구대부중개업2023-인천계양-0019플러스 대부중개정준영인천광역시 계양구 오조산로57번길 15, 명동빌딩 768호 (계산동)2023-10-16
45인천광역시 계양구대부중개업2023-인천계양-0018더페스트대부중개박현아인천광역시 계양구 계양대로 40, 401호 (작전동)2021-09-28
56인천광역시 계양구대부업2023-인천계양-0017새희망론대부최형준인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 73-2호 (계산동)2023-09-21
67인천광역시 계양구대부업2023-인천계양-0016시크릿 대부송대호인천광역시 계양구 오조산로57번길 15, 명동빌딩 750호 (계산동)2023-09-05
78인천광역시 계양구대부업2023-인천계양-0015스마트대부최우성인천광역시 계양구 계양문화로 44, 라이즈빌 307호 (계산동)2022-04-20
89인천광역시 계양구대부업2023-인천계양-0014여성전용대부김소민인천광역시 계양구 계양문화로 54, 대산월드프라자 10층 86-1호 (계산동)2023-02-14
910인천광역시 계양구대부업2023-인천계양-0013제이에스플러스대부이재승인천광역시 계양구 아나지로299번길 22, 4층 403호 (작전동)2023-06-30
순번시군구명등록신청사업등록증번호상호대표자소재지(도로명)등록일자
5859인천광역시 계양구대부업2017-인천계양-0024JK대부주유하인천광역시 계양구 계양문화로 48, 뉴월드프라자 902호 (계산동)2023-07-06
5960인천광역시 계양구대부업인천 계양구 16-18(주) 행복자산관리대부이강훈인천광역시 계양구 장제로 899, 5층 (임학동)2022-08-18
6061인천광역시 계양구대부업인천 계양구 15-35(주)서울캐피탈대부곽형웅인천광역시 계양구 계산천동로 6-1, 302호 (계산동, 용궁오피스텔)2020-12-14
6162인천광역시 계양구대부중개업인천 계양구 15-34(주)서울캐피탈대부중개곽형웅인천광역시 계양구 계산천동로 6-1, 302호 (계산동, 용궁오피스텔)2020-12-14
6263인천광역시 계양구대부업인천 계양구 15-33열린캐피탈대부 주식회사윤열인천광역시 계양구 장제로756번길 5, 한별프라자 301-2호 (계산동)2021-09-06
6364인천광역시 계양구대부중개업인천 계양구 15-03영신대부중개송남규인천광역시 계양구 경명대로 1037, 603호 (계산동)2020-11-30
6465인천광역시 계양구대부업인천 계양구 14-2디에스대부주식회사유규성인천광역시 계양구 주부토로 467, 303호 (작전동)2022-11-03
6566인천광역시 계양구대부업인천 계양구 08-55경인사 전당포대부김순자인천광역시 계양구 계양대로 182-1 (계산동)2023-05-10
6667인천광역시 계양구대부업인천 계양구 08-16병방사(대부업)김성애인천광역시 계양구 계양산로 219, 2층 (병방동)2022-11-24
6768인천광역시 계양구대부업인천 계양구 08-11대우사 전당포(대부)김남현인천광역시 계양구 경명대로 1075, 3층 (계산동)2022-11-03