Overview

Dataset statistics

Number of variables9
Number of observations123
Missing cells58
Missing cells (%)5.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory73.1 B

Variable types

Categorical3
DateTime2
Text4

Dataset

Description경기도 이천시 이사화물업체현황에 대한 정보로 인허가일자, 영업상태, 업종구분, 업체명, 도로명주소, 지번주소, 연락처 정보를 제공
Author경기도 이천시
URLhttps://www.data.go.kr/data/15080683/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
영업상태구분 is highly overall correlated with 업종구분High correlation
업종구분 is highly overall correlated with 영업상태구분High correlation
영업상태구분 is highly imbalanced (88.1%)Imbalance
업종구분 is highly imbalanced (93.2%)Imbalance
지번주소 has 4 (3.3%) missing valuesMissing
연락처 has 53 (43.1%) missing valuesMissing

Reproduction

Analysis started2024-04-21 01:54:35.991879
Analysis finished2024-04-21 01:54:37.996657
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
이천시
123 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이천시 123
100.0%

Length

2024-04-21T10:54:38.067028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:54:38.183343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이천시 123
100.0%

인허가일자
Date

Distinct119
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1989-06-30 00:00:00
Maximum2019-05-27 00:00:00
2024-04-21T10:54:38.347736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:54:38.492188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
운영중
120 
폐업
 
2
양도
 
1

Length

Max length3
Median length3
Mean length2.9756098
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 120
97.6%
폐업 2
 
1.6%
양도 1
 
0.8%

Length

2024-04-21T10:54:38.622191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:54:38.729777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 120
97.6%
폐업 2
 
1.6%
양도 1
 
0.8%

업종구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
화물운송주선
122 
화물운송사업
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
화물운송주선 122
99.2%
화물운송사업 1
 
0.8%

Length

2024-04-21T10:54:38.839624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:54:38.967478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화물운송주선 122
99.2%
화물운송사업 1
 
0.8%

업체명
Text

Distinct122
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-21T10:54:39.160850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.3577236
Min length3

Characters and Unicode

Total characters782
Distinct characters178
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)98.4%

Sample

1st row㈜2대운송
2nd row오천화물
3rd row㈜전국화물
4th row가나익스프레스
5th row이천가나화물
ValueCountFrequency (%)
3
 
2.3%
동해콜화물 2
 
1.5%
㈜이천냉장로지스 1
 
0.8%
주)티에프로지스 1
 
0.8%
㈜제국물류 1
 
0.8%
이안종합물류 1
 
0.8%
동광로지스㈜ 1
 
0.8%
㈜디앤비파트너스 1
 
0.8%
kgb익스프레스 1
 
0.8%
이천점 1
 
0.8%
Other values (118) 118
90.1%
2024-04-21T10:54:39.531983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 72
 
9.2%
㈜ 69
 
8.8%
물 54
 
6.9%
류 34
 
4.3%
로 34
 
4.3%
지 33
 
4.2%
이 25
 
3.2%
화 20
 
2.6%
프 14
 
1.8%
천 14
 
1.8%
Other values (168) 413
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 662
84.7%
Other Symbol 69
 
8.8%
Uppercase Letter 14
 
1.8%
Decimal Number 9
 
1.2%
Open Punctuation 8
 
1.0%
Close Punctuation 8
 
1.0%
Space Separator 8
 
1.0%
Math Symbol 3
 
0.4%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 72
 
10.9%
물 54
 
8.2%
류 34
 
5.1%
로 34
 
5.1%
지 33
 
5.0%
이 25
 
3.8%
화 20
 
3.0%
프 14
 
2.1%
천 14
 
2.1%
레 13
 
2.0%
Other values (150) 349
52.7%
Uppercase Letter
ValueCountFrequency (%)
K 5
35.7%
B 2
 
14.3%
G 2
 
14.3%
S 2
 
14.3%
T 1
 
7.1%
H 1
 
7.1%
M 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
6 2
22.2%
2 2
22.2%
3 1
 
11.1%
1 1
 
11.1%
Other Symbol
ValueCountFrequency (%)
㈜ 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
> 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 731
93.5%
Common 37
 
4.7%
Latin 14
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 72
 
9.8%
㈜ 69
 
9.4%
물 54
 
7.4%
류 34
 
4.7%
로 34
 
4.7%
지 33
 
4.5%
이 25
 
3.4%
화 20
 
2.7%
프 14
 
1.9%
천 14
 
1.9%
Other values (151) 362
49.5%
Common
ValueCountFrequency (%)
( 8
21.6%
) 8
21.6%
8
21.6%
> 3
 
8.1%
0 3
 
8.1%
6 2
 
5.4%
2 2
 
5.4%
3 1
 
2.7%
1 1
 
2.7%
_ 1
 
2.7%
Latin
ValueCountFrequency (%)
K 5
35.7%
B 2
 
14.3%
G 2
 
14.3%
S 2
 
14.3%
T 1
 
7.1%
H 1
 
7.1%
M 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 662
84.7%
None 69
 
8.8%
ASCII 51
 
6.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 72
 
10.9%
물 54
 
8.2%
류 34
 
5.1%
로 34
 
5.1%
지 33
 
5.0%
이 25
 
3.8%
화 20
 
3.0%
프 14
 
2.1%
천 14
 
2.1%
레 13
 
2.0%
Other values (150) 349
52.7%
None
ValueCountFrequency (%)
㈜ 69
100.0%
ASCII
ValueCountFrequency (%)
( 8
15.7%
) 8
15.7%
8
15.7%
K 5
9.8%
> 3
 
5.9%
0 3
 
5.9%
B 2
 
3.9%
G 2
 
3.9%
S 2
 
3.9%
6 2
 
3.9%
Other values (7) 8
15.7%

도로명주소
Text

Distinct118
Distinct (%)96.7%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-04-21T10:54:39.755512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length24.508197
Min length14

Characters and Unicode

Total characters2990
Distinct characters126
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

Unique114 ?
Unique (%)93.4%

Sample

1st row경기도 이천시 백사면 이여로 113
2nd row경기도 이천시 마장면 억만리로 19
3rd row경기도 이천시 부발읍 황무로 1839
4th row경기도 이천시 갈산로133번길 46
5th row경기도 이천시 중부대로 1210
ValueCountFrequency (%)
경기도 123
18.5%
이천시 123
18.5%
마장면 23
 
3.5%
부발읍 21
 
3.2%
호법면 18
 
2.7%
2층 15
 
2.3%
중부대로 13
 
2.0%
대월면 11
 
1.7%
신둔면 7
 
1.1%
경충대로 7
 
1.1%
Other values (220) 303
45.6%
2024-04-21T10:54:40.105411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
542
18.1%
이 148
 
4.9%
천 142
 
4.7%
경 134
 
4.5%
시 124
 
4.1%
기 123
 
4.1%
도 123
 
4.1%
로 119
 
4.0%
1 118
 
3.9%
2 92
 
3.1%
Other values (116) 1325
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1726
57.7%
Decimal Number 598
 
20.0%
Space Separator 542
 
18.1%
Dash Punctuation 43
 
1.4%
Other Punctuation 42
 
1.4%
Open Punctuation 19
 
0.6%
Close Punctuation 19
 
0.6%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 148
 
8.6%
천 142
 
8.2%
경 134
 
7.8%
시 124
 
7.2%
기 123
 
7.1%
도 123
 
7.1%
로 119
 
6.9%
면 74
 
4.3%
대 59
 
3.4%
호 44
 
2.5%
Other values (100) 636
36.8%
Decimal Number
ValueCountFrequency (%)
1 118
19.7%
2 92
15.4%
3 63
10.5%
4 53
8.9%
8 52
8.7%
0 51
8.5%
7 47
 
7.9%
6 44
 
7.4%
5 40
 
6.7%
9 38
 
6.4%
Space Separator
ValueCountFrequency (%)
542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1726
57.7%
Common 1263
42.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 148
 
8.6%
천 142
 
8.2%
경 134
 
7.8%
시 124
 
7.2%
기 123
 
7.1%
도 123
 
7.1%
로 119
 
6.9%
면 74
 
4.3%
대 59
 
3.4%
호 44
 
2.5%
Other values (100) 636
36.8%
Common
ValueCountFrequency (%)
542
42.9%
1 118
 
9.3%
2 92
 
7.3%
3 63
 
5.0%
4 53
 
4.2%
8 52
 
4.1%
0 51
 
4.0%
7 47
 
3.7%
6 44
 
3.5%
- 43
 
3.4%
Other values (5) 158
 
12.5%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1726
57.7%
ASCII 1264
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
542
42.9%
1 118
 
9.3%
2 92
 
7.3%
3 63
 
5.0%
4 53
 
4.2%
8 52
 
4.1%
0 51
 
4.0%
7 47
 
3.7%
6 44
 
3.5%
- 43
 
3.4%
Other values (6) 159
 
12.6%
Hangul
ValueCountFrequency (%)
이 148
 
8.6%
천 142
 
8.2%
경 134
 
7.8%
시 124
 
7.2%
기 123
 
7.1%
도 123
 
7.1%
로 119
 
6.9%
면 74
 
4.3%
대 59
 
3.4%
호 44
 
2.5%
Other values (100) 636
36.8%

지번주소
Text

MISSING 

Distinct108
Distinct (%)90.8%
Missing4
Missing (%)3.3%
Memory size1.1 KiB
2024-04-21T10:54:40.500750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length20.302521
Min length15

Characters and Unicode

Total characters2416
Distinct characters114
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

Unique99 ?
Unique (%)83.2%

Sample

1st row경기도 이천시 백사면 모전리 966-2
2nd row경기도 이천시 마장면 회억리 230-1
3rd row경기도 이천시 부발읍 송온리 141
4th row경기도 이천시 갈산동 221-2
5th row경기도 이천시 장록동 376-4
ValueCountFrequency (%)
경기도 120
20.7%
이천시 120
20.7%
마장면 23
 
4.0%
호법면 18
 
3.1%
부발읍 18
 
3.1%
대월면 12
 
2.1%
신둔면 7
 
1.2%
안평리 7
 
1.2%
표교리 6
 
1.0%
초지리 5
 
0.9%
Other values (177) 245
42.2%
2024-04-21T10:54:41.003532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
462
19.1%
이 125
 
5.2%
천 124
 
5.1%
경 122
 
5.0%
도 121
 
5.0%
시 120
 
5.0%
기 120
 
5.0%
리 92
 
3.8%
- 85
 
3.5%
1 85
 
3.5%
Other values (104) 960
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1400
57.9%
Space Separator 462
 
19.1%
Decimal Number 461
 
19.1%
Dash Punctuation 85
 
3.5%
Other Punctuation 4
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 125
 
8.9%
천 124
 
8.9%
경 122
 
8.7%
도 121
 
8.6%
시 120
 
8.6%
기 120
 
8.6%
리 92
 
6.6%
면 74
 
5.3%
장 33
 
2.4%
동 29
 
2.1%
Other values (89) 440
31.4%
Decimal Number
ValueCountFrequency (%)
1 85
18.4%
4 65
14.1%
5 52
11.3%
2 51
11.1%
6 47
10.2%
7 45
9.8%
9 33
 
7.2%
3 30
 
6.5%
8 28
 
6.1%
0 25
 
5.4%
Space Separator
ValueCountFrequency (%)
462
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1400
57.9%
Common 1016
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 125
 
8.9%
천 124
 
8.9%
경 122
 
8.7%
도 121
 
8.6%
시 120
 
8.6%
기 120
 
8.6%
리 92
 
6.6%
면 74
 
5.3%
장 33
 
2.4%
동 29
 
2.1%
Other values (89) 440
31.4%
Common
ValueCountFrequency (%)
462
45.5%
- 85
 
8.4%
1 85
 
8.4%
4 65
 
6.4%
5 52
 
5.1%
2 51
 
5.0%
6 47
 
4.6%
7 45
 
4.4%
9 33
 
3.2%
3 30
 
3.0%
Other values (5) 61
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1400
57.9%
ASCII 1016
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
462
45.5%
- 85
 
8.4%
1 85
 
8.4%
4 65
 
6.4%
5 52
 
5.1%
2 51
 
5.0%
6 47
 
4.6%
7 45
 
4.4%
9 33
 
3.2%
3 30
 
3.0%
Other values (5) 61
 
6.0%
Hangul
ValueCountFrequency (%)
이 125
 
8.9%
천 124
 
8.9%
경 122
 
8.7%
도 121
 
8.6%
시 120
 
8.6%
기 120
 
8.6%
리 92
 
6.6%
면 74
 
5.3%
장 33
 
2.4%
동 29
 
2.1%
Other values (89) 440
31.4%

연락처
Text

MISSING 

Distinct70
Distinct (%)100.0%
Missing53
Missing (%)43.1%
Memory size1.1 KiB
2024-04-21T10:54:41.266117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.971429
Min length9

Characters and Unicode

Total characters838
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

Unique70 ?
Unique (%)100.0%

Sample

1st row031-637-2222
2nd row031-634-6388
3rd row031-631-2488
4th row031-638-2481
5th row031-637-1001
ValueCountFrequency (%)
031-632-3163 1
 
1.4%
031-632-1971 1
 
1.4%
031-643-1088 1
 
1.4%
031-632-8856 1
 
1.4%
031-631-6071 1
 
1.4%
031-631-2692 1
 
1.4%
031-636-1024 1
 
1.4%
031-634-9309 1
 
1.4%
031-635-8500 1
 
1.4%
031-637-1677 1
 
1.4%
Other values (60) 60
85.7%
2024-04-21T10:54:41.659981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 153
18.3%
- 139
16.6%
0 115
13.7%
1 115
13.7%
6 96
11.5%
2 58
 
6.9%
4 47
 
5.6%
7 37
 
4.4%
8 34
 
4.1%
5 23
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 699
83.4%
Dash Punctuation 139
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 153
21.9%
0 115
16.5%
1 115
16.5%
6 96
13.7%
2 58
 
8.3%
4 47
 
6.7%
7 37
 
5.3%
8 34
 
4.9%
5 23
 
3.3%
9 21
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 838
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 153
18.3%
- 139
16.6%
0 115
13.7%
1 115
13.7%
6 96
11.5%
2 58
 
6.9%
4 47
 
5.6%
7 37
 
4.4%
8 34
 
4.1%
5 23
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 153
18.3%
- 139
16.6%
0 115
13.7%
1 115
13.7%
6 96
11.5%
2 58
 
6.9%
4 47
 
5.6%
7 37
 
4.4%
8 34
 
4.1%
5 23
 
2.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2024-03-22 00:00:00
Maximum2024-03-22 00:00:00
2024-04-21T10:54:41.770634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:54:41.852535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-04-21T10:54:41.920010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구분업종구분연락처
영업상태구분1.0000.450NaN
업종구분0.4501.000NaN
연락처NaNNaN1.000
2024-04-21T10:54:42.008518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구분업종구분
영업상태구분1.0000.695
업종구분0.6951.000
2024-04-21T10:54:42.091197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구분업종구분
영업상태구분1.0000.695
업종구분0.6951.000

Missing values

2024-04-21T10:54:37.662949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:54:37.835014image/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.
2024-04-21T10:54:37.944064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명인허가일자영업상태구분업종구분업체명도로명주소지번주소연락처데이터기준일자
0이천시1994-05-31운영중화물운송주선㈜2대운송경기도 이천시 백사면 이여로 113경기도 이천시 백사면 모전리 966-2031-637-22222024-03-22
1이천시1994-01-27운영중화물운송주선오천화물경기도 이천시 마장면 억만리로 19경기도 이천시 마장면 회억리 230-1031-634-63882024-03-22
2이천시1994-08-05운영중화물운송주선㈜전국화물경기도 이천시 부발읍 황무로 1839경기도 이천시 부발읍 송온리 141031-631-24882024-03-22
3이천시1996-04-16운영중화물운송주선가나익스프레스경기도 이천시 갈산로133번길 46경기도 이천시 갈산동 221-2031-638-24812024-03-22
4이천시1996-04-30운영중화물운송주선이천가나화물경기도 이천시 중부대로 1210경기도 이천시 장록동 376-4031-637-10012024-03-22
5이천시1998-01-17운영중화물운송주선무지개익스프레스경기도 이천시 호법면 중부대로 952-10경기도 이천시 호법면 유산리 517-12031-637-00042024-03-22
6이천시1999-12-24운영중화물운송주선㈜케이엠알경기도 이천시 설성면 설가로 307경기도 이천시 설성면 상봉리 170-3031-632-08792024-03-22
7이천시2000-05-24운영중화물운송주선이사트랜스경기도 이천시 이섭대천로 1304-14경기도 이천시 창전동 445-7031-631-12242024-03-22
8이천시2001-05-08운영중화물운송주선㈜명미인터내셔널경기도 이천시 부발읍 황무로1720번길 113-14경기도 이천시 부발읍 수정리 55-11031-632-31632024-03-22
9이천시2002-08-28운영중화물운송주선이십일세기통운㈜경기도 이천시 부발읍 경충대로 1896경기도 이천시 부발읍 가산리 491-19031-636-38512024-03-22
시군명인허가일자영업상태구분업종구분업체명도로명주소지번주소연락처데이터기준일자
113이천시2000-08-10운영중화물운송주선하빈로지스경기도 이천시 경기도 이천시 마장면 프리미엄아울렛로 33-27, 1동 440호(표교리)경기도 이천시 경기도 이천시 마장면 프리미엄아울렛로 33-27, 1동 440호(표교리)<NA>2024-03-22
114이천시1994-05-16운영중화물운송주선진환종합물류㈜경기도 이천시 설성면 노성로 458-16경기도 이천시 설성면 노성로 458-16<NA>2024-03-22
115이천시2002-06-10운영중화물운송주선진환통운㈜경기도 이천시 설성면 노성로 458-16경기도 이천시 설성면 노성로 458-16<NA>2024-03-22
116이천시2001-05-21운영중화물운송주선㈜서준물류경기도 이천시 장호원읍 설장로876번길 9경기도 이천시 장호원읍 설장로876번길 9<NA>2024-03-22
117이천시1996-02-14운영중화물운송주선㈜에스엠물류경기도 이천시 장호원읍 서동대로8829번길 31, 2층경기도 이천시 장호원읍 서동대로8829번길 31, 2층<NA>2024-03-22
118이천시1999-04-16운영중화물운송주선케이비화물경기도 이천시 마장면 서이천로 413경기도 이천시 마장면 목리 400-4<NA>2024-03-22
119이천시2009-12-03운영중화물운송주선(주)일죽종합물류경기도 이천시 호법면 중부대로 748경기도 이천시 호법면 중부대로 748070-4084-23562024-03-22
120이천시1993-03-24운영중화물운송주선아트로지스㈜경기도 이천시 신둔면 황무로 489-6, 2층경기도 이천시 신둔면 소정리 62-9031-637-26772024-03-22
121이천시2002-10-11운영중화물운송주선노아운수경기도 이천시 부발읍 경충대로 1848번길 4, 1층경기도 이천시 부발읍 경충대로 1848번길 4, 1층<NA>2024-03-22
122이천시2005-02-15운영중화물운송주선태평종합물류경기도 이천시 대월면 장평리 63-4경기도 이천시 대월면 장평리 63-4<NA>2024-03-22