Overview

Dataset statistics

Number of variables8
Number of observations62
Missing cells27
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory67.1 B

Variable types

Numeric1
Categorical2
DateTime1
Text4

Dataset

Description인천광역시 계양구 관내 화물자동차운송주선사업 허가업체에 대한 데이터로, 허가일자, 등록업체명, 주소, 구분, 대표자, 전화번호 등을 제공합니다.
URLhttps://www.data.go.kr/data/15081058/fileData.do

Alerts

군구명 has constant value ""Constant
전화번호 has 27 (43.5%) missing valuesMissing
연번 has unique valuesUnique
허가일자 has unique valuesUnique
등록업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:09:38.210073
Analysis finished2023-12-12 12:09:39.022251
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.5
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-12T21:09:39.096925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.05
Q116.25
median31.5
Q346.75
95-th percentile58.95
Maximum62
Range61
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation18.041619
Coefficient of variation (CV)0.5727498
Kurtosis-1.2
Mean31.5
Median Absolute Deviation (MAD)15.5
Skewness0
Sum1953
Variance325.5
MonotonicityStrictly increasing
2023-12-12T21:09:39.297909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
48 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (52) 52
83.9%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%

군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
계양구
62 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계양구 62
100.0%

Length

2023-12-12T21:09:39.465188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:09:39.569573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계양구 62
100.0%

허가일자
Date

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum1984-06-27 00:00:00
Maximum2008-11-04 00:00:00
2023-12-12T21:09:39.728811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:09:39.920528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록업체명
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T21:09:40.241436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11.5
Mean length6.9677419
Min length2

Characters and Unicode

Total characters432
Distinct characters136
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st row유공익스프레스
2nd row신우익스프레스
3rd row이사친구 명성이사몰
4th row(주)이원물류
5th row(주)효성화물
ValueCountFrequency (%)
유공익스프레스 1
 
1.5%
이사모아익스프레스 1
 
1.5%
주)한도운수 1
 
1.5%
모든이사 1
 
1.5%
극동익스프레스 1
 
1.5%
sk명품이사몰 1
 
1.5%
㈜에이원로지스틱스 1
 
1.5%
대박이사 1
 
1.5%
유티엘 1
 
1.5%
뉴-이사몰 1
 
1.5%
Other values (58) 58
85.3%
2023-12-12T21:09:41.008186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 40
 
9.3%
이 29
 
6.7%
물 20
 
4.6%
사 17
 
3.9%
익 13
 
3.0%
프 13
 
3.0%
레 13
 
3.0%
류 11
 
2.5%
화 9
 
2.1%
㈜ 9
 
2.1%
Other values (126) 258
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 389
90.0%
Other Symbol 9
 
2.1%
Uppercase Letter 7
 
1.6%
Space Separator 6
 
1.4%
Open Punctuation 6
 
1.4%
Close Punctuation 6
 
1.4%
Other Punctuation 4
 
0.9%
Decimal Number 4
 
0.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 40
 
10.3%
이 29
 
7.5%
물 20
 
5.1%
사 17
 
4.4%
익 13
 
3.3%
프 13
 
3.3%
레 13
 
3.3%
류 11
 
2.8%
화 9
 
2.3%
로 8
 
2.1%
Other values (111) 216
55.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
S 1
14.3%
B 1
14.3%
G 1
14.3%
J 1
14.3%
C 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Decimal Number
ValueCountFrequency (%)
4 3
75.0%
3 1
 
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
91.9%
Common 27
 
6.2%
Latin 7
 
1.6%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 40
 
10.1%
이 29
 
7.3%
물 20
 
5.0%
사 17
 
4.3%
익 13
 
3.3%
프 13
 
3.3%
레 13
 
3.3%
류 11
 
2.8%
화 9
 
2.3%
㈜ 9
 
2.3%
Other values (111) 223
56.2%
Common
ValueCountFrequency (%)
6
22.2%
( 6
22.2%
) 6
22.2%
. 3
11.1%
4 3
11.1%
- 1
 
3.7%
3 1
 
3.7%
/ 1
 
3.7%
Latin
ValueCountFrequency (%)
K 2
28.6%
S 1
14.3%
B 1
14.3%
G 1
14.3%
J 1
14.3%
C 1
14.3%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
89.8%
ASCII 34
 
7.9%
None 9
 
2.1%
CJK 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 40
 
10.3%
이 29
 
7.5%
물 20
 
5.2%
사 17
 
4.4%
익 13
 
3.4%
프 13
 
3.4%
레 13
 
3.4%
류 11
 
2.8%
화 9
 
2.3%
로 8
 
2.1%
Other values (110) 215
55.4%
None
ValueCountFrequency (%)
㈜ 9
100.0%
ASCII
ValueCountFrequency (%)
6
17.6%
( 6
17.6%
) 6
17.6%
. 3
8.8%
4 3
8.8%
K 2
 
5.9%
S 1
 
2.9%
- 1
 
2.9%
3 1
 
2.9%
B 1
 
2.9%
Other values (4) 4
11.8%
CJK
ValueCountFrequency (%)
舊 1
100.0%

주소
Text

Distinct60
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T21:09:41.318358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length33.112903
Min length19

Characters and Unicode

Total characters2053
Distinct characters134
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)93.5%

Sample

1st row인천광역시 계양구 계산새로19번길 20 (계산동)
2nd row인천광역시 계양구 봉오대로691번길 12(작전동)
3rd row인천광역시 계양구 당미길 9, 103호(동양동)
4th row인천광역시 계양구 아나지로 528(서운동)
5th row인천광역시 계양구 계양대로 188, 1515호(계산동, 대덕노바체)
ValueCountFrequency (%)
인천광역시 62
 
17.8%
계양구 62
 
17.8%
71 5
 
1.4%
계산새로 5
 
1.4%
아나지로 4
 
1.1%
효성동 4
 
1.1%
하이베라스 4
 
1.1%
계산동 4
 
1.1%
비동 3
 
0.9%
계양문화로 3
 
0.9%
Other values (160) 193
55.3%
2023-12-12T21:09:41.774350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
288
 
14.0%
계 101
 
4.9%
1 98
 
4.8%
동 74
 
3.6%
, 72
 
3.5%
양 72
 
3.5%
인 63
 
3.1%
시 63
 
3.1%
광 63
 
3.1%
역 63
 
3.1%
Other values (124) 1096
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1198
58.4%
Decimal Number 364
 
17.7%
Space Separator 288
 
14.0%
Other Punctuation 72
 
3.5%
Close Punctuation 58
 
2.8%
Open Punctuation 58
 
2.8%
Dash Punctuation 15
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 101
 
8.4%
동 74
 
6.2%
양 72
 
6.0%
인 63
 
5.3%
시 63
 
5.3%
광 63
 
5.3%
역 63
 
5.3%
구 62
 
5.2%
천 62
 
5.2%
로 61
 
5.1%
Other values (109) 514
42.9%
Decimal Number
ValueCountFrequency (%)
1 98
26.9%
2 47
12.9%
0 46
12.6%
5 39
 
10.7%
3 36
 
9.9%
9 23
 
6.3%
7 20
 
5.5%
8 19
 
5.2%
4 18
 
4.9%
6 18
 
4.9%
Space Separator
ValueCountFrequency (%)
288
100.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1198
58.4%
Common 855
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 101
 
8.4%
동 74
 
6.2%
양 72
 
6.0%
인 63
 
5.3%
시 63
 
5.3%
광 63
 
5.3%
역 63
 
5.3%
구 62
 
5.2%
천 62
 
5.2%
로 61
 
5.1%
Other values (109) 514
42.9%
Common
ValueCountFrequency (%)
288
33.7%
1 98
 
11.5%
, 72
 
8.4%
) 58
 
6.8%
( 58
 
6.8%
2 47
 
5.5%
0 46
 
5.4%
5 39
 
4.6%
3 36
 
4.2%
9 23
 
2.7%
Other values (5) 90
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1198
58.4%
ASCII 855
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
288
33.7%
1 98
 
11.5%
, 72
 
8.4%
) 58
 
6.8%
( 58
 
6.8%
2 47
 
5.5%
0 46
 
5.4%
5 39
 
4.6%
3 36
 
4.2%
9 23
 
2.7%
Other values (5) 90
 
10.5%
Hangul
ValueCountFrequency (%)
계 101
 
8.4%
동 74
 
6.2%
양 72
 
6.0%
인 63
 
5.3%
시 63
 
5.3%
광 63
 
5.3%
역 63
 
5.3%
구 62
 
5.2%
천 62
 
5.2%
로 61
 
5.1%
Other values (109) 514
42.9%

구분
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
일반
33 
이사
27 
일반/이사
 
2

Length

Max length5
Median length2
Mean length2.0967742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이사
2nd row이사
3rd row이사
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 33
53.2%
이사 27
43.5%
일반/이사 2
 
3.2%

Length

2023-12-12T21:09:41.923240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:09:42.035892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 33
53.2%
이사 27
43.5%
일반/이사 2
 
3.2%

대표자
Text

Distinct61
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size628.0 B
2023-12-12T21:09:42.278850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0645161
Min length3

Characters and Unicode

Total characters190
Distinct characters96
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)96.8%

Sample

1st row홍용운
2nd row신동섭
3rd row고익선
4th row박동만
5th row민인희
ValueCountFrequency (%)
김병율 2
 
3.2%
홍용운 1
 
1.6%
박치일 1
 
1.6%
김영주 1
 
1.6%
이만구 1
 
1.6%
주대현 1
 
1.6%
정정수 1
 
1.6%
하헌석 1
 
1.6%
한남희 1
 
1.6%
박애란 1
 
1.6%
Other values (51) 51
82.3%
2023-12-12T21:09:42.707735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 15
 
7.9%
정 9
 
4.7%
박 8
 
4.2%
영 7
 
3.7%
이 6
 
3.2%
성 5
 
2.6%
선 5
 
2.6%
동 5
 
2.6%
희 4
 
2.1%
순 4
 
2.1%
Other values (86) 122
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
99.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 15
 
7.9%
정 9
 
4.8%
박 8
 
4.2%
영 7
 
3.7%
이 6
 
3.2%
성 5
 
2.6%
선 5
 
2.6%
동 5
 
2.6%
희 4
 
2.1%
순 4
 
2.1%
Other values (85) 121
64.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 15
 
7.9%
정 9
 
4.8%
박 8
 
4.2%
영 7
 
3.7%
이 6
 
3.2%
성 5
 
2.6%
선 5
 
2.6%
동 5
 
2.6%
희 4
 
2.1%
순 4
 
2.1%
Other values (85) 121
64.0%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
99.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 15
 
7.9%
정 9
 
4.8%
박 8
 
4.2%
영 7
 
3.7%
이 6
 
3.2%
성 5
 
2.6%
선 5
 
2.6%
동 5
 
2.6%
희 4
 
2.1%
순 4
 
2.1%
Other values (85) 121
64.0%
ASCII
ValueCountFrequency (%)
, 1
100.0%

전화번호
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing27
Missing (%)43.5%
Memory size628.0 B
2023-12-12T21:09:42.906398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.971429
Min length9

Characters and Unicode

Total characters419
Distinct characters11
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

Unique33 ?
Unique (%)94.3%

Sample

1st row032-542-6666
2nd row032-556-0024
3rd row032-546-2424
4th row032-554-8871
5th row032-547-1234
ValueCountFrequency (%)
032-545-9322 2
 
5.7%
1899-9652 1
 
2.9%
032-888-3327 1
 
2.9%
032-522-9321 1
 
2.9%
032-553-2424 1
 
2.9%
070-4962-0088 1
 
2.9%
032-543-2381 1
 
2.9%
032-564-2224 1
 
2.9%
032-772-9673 1
 
2.9%
032-546-2424 1
 
2.9%
Other values (24) 24
68.6%
2023-12-12T21:09:43.231322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 77
18.4%
- 69
16.5%
0 54
12.9%
3 51
12.2%
5 51
12.2%
4 39
9.3%
6 17
 
4.1%
7 17
 
4.1%
1 16
 
3.8%
8 15
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.5%
Dash Punctuation 69
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 77
22.0%
0 54
15.4%
3 51
14.6%
5 51
14.6%
4 39
11.1%
6 17
 
4.9%
7 17
 
4.9%
1 16
 
4.6%
8 15
 
4.3%
9 13
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 77
18.4%
- 69
16.5%
0 54
12.9%
3 51
12.2%
5 51
12.2%
4 39
9.3%
6 17
 
4.1%
7 17
 
4.1%
1 16
 
3.8%
8 15
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 77
18.4%
- 69
16.5%
0 54
12.9%
3 51
12.2%
5 51
12.2%
4 39
9.3%
6 17
 
4.1%
7 17
 
4.1%
1 16
 
3.8%
8 15
 
3.6%

Interactions

2023-12-12T21:09:38.682353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:09:43.325842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번허가일자등록업체명주소구분대표자전화번호
연번1.0001.0001.0000.8810.5280.9420.000
허가일자1.0001.0001.0001.0001.0001.0001.000
등록업체명1.0001.0001.0001.0001.0001.0001.000
주소0.8811.0001.0001.0000.9601.0001.000
구분0.5281.0001.0000.9601.0001.0001.000
대표자0.9421.0001.0001.0001.0001.0001.000
전화번호0.0001.0001.0001.0001.0001.0001.000
2023-12-12T21:09:43.422821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분
연번1.0000.347
구분0.3471.000

Missing values

2023-12-12T21:09:38.812429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:09:38.970801image/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

연번군구명허가일자등록업체명주소구분대표자전화번호
01계양구1996-04-09유공익스프레스인천광역시 계양구 계산새로19번길 20 (계산동)이사홍용운032-542-6666
12계양구2000-12-19신우익스프레스인천광역시 계양구 봉오대로691번길 12(작전동)이사신동섭032-556-0024
23계양구2001-06-11이사친구 명성이사몰인천광역시 계양구 당미길 9, 103호(동양동)이사고익선032-546-2424
34계양구2001-11-29(주)이원물류인천광역시 계양구 아나지로 528(서운동)일반박동만032-554-8871
45계양구2002-02-06(주)효성화물인천광역시 계양구 계양대로 188, 1515호(계산동, 대덕노바체)일반민인희032-547-1234
56계양구2002-06-07인천화물인천광역시 계양구 아나지로 449, 3동 2층(서운동)일반김광복032-555-9624
67계양구2003-11-07바로이사트랜스인천광역시 계양구 계양산로 52 (계산동)이사김보영032-529-8524
78계양구2005-10-20새소망익스프레스인천광역시 계양구 봉오대로 651번길 12, 103호(작전동)이사신동수032-556-5555
89계양구1998-05-18로얄사다리차연합인천광역시 계양구 서운로 43-25이사최막례032-663-6500
910계양구2000-06-29덕수기업 이사나라인천광역시 계양구 임학안로6번길 19-1, 1층이사김덕수032-555-7474
연번군구명허가일자등록업체명주소구분대표자전화번호
5253계양구2005-02-28㈜제이케이물류인천광역시 계양구 장제로743번길 2, 상가동 지하115호(작전동)일반조성환<NA>
5354계양구1999-08-27우인종합물류인천광역시 계양구 계양문화로 86, 408호 일부(용종동, 대우프라자)일반안광모032-543-2380
5455계양구1996-03-22제이로지스인천광역시 계양구 계산새로 71, 비동 612호(계산동, 하이베라스)일반박상진032-719-3334
5556계양구1997-04-18맥트랜스인천광역시 계양구 길마로 13, 401-2(효성동, 삼성빌딩)일반박지영<NA>
5657계양구2003-05-22㈜인천물류인천광역시 계양구 계산새로 71, 디동 1203호(계산동, 하이베라스)일반김병율032-545-9322
5758계양구2000-01-17㈜디에이치무역인천광역시 계양구 아나지로248번길 5, 비동 801호(작전동, 비케이디센트)일반김정화,박성근<NA>
5859계양구1984-06-27나월퀵화물이사인천광역시 계양구 계양문화로 96, 강북프라자 110호(용종동)일반/이사박금비<NA>
5960계양구2001-04-21에이스이엔지코리아인천광역시 계양구 장제로 652, 102동1303호(작전동, 더뷰룩스)일반제소영<NA>
6061계양구2002-03-16제이케이로지스인천광역시 계양구 오조산로57번길 7-1, 701호내 729호실(계산동, 미래사랑빌딩)일반김은미<NA>
6162계양구1986-07-09하은물류인천광역시 계양구 장제로 933, 204호(방축동, 계양산대창센시티아파트상가동)일반강민주<NA>