Overview

Dataset statistics

Number of variables9
Number of observations125
Missing cells121
Missing cells (%)10.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory73.1 B

Variable types

Categorical3
DateTime2
Text4

Dataset

Description화물운송("일반화물", "이사화물", "일반이사화물") 주선사업 허가업체 현황(시군명, 인허가일자, 인허가번호, 영업상태, 업종구분, 업체명, 도로명주소, 지번주소, 데이터기준일자) 입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15114730/fileData.do

Alerts

시군명 has constant value ""Constant
영업상태 has constant value ""Constant
업종구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
지번주소 has 121 (96.8%) missing valuesMissing
인허가번호 has unique valuesUnique

Reproduction

Analysis started2024-04-18 07:57:01.211270
Analysis finished2024-04-18 07:57:01.757082
Duration0.55 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
안양시
125 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안양시 125
100.0%

Length

2024-04-18T16:57:01.830102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:57:01.935437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안양시 125
100.0%

인허가일자
Date

Distinct121
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1984-06-23 00:00:00
Maximum2021-09-28 00:00:00
2024-04-18T16:57:02.037938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:57:02.177196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가번호
Text

UNIQUE 

Distinct125
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-18T16:57:02.364841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters2625
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

Unique125 ?
Unique (%)100.0%

Sample

1st row3830000-2023-03-00002
2nd row3830000-2023-03-00001
3rd row3830000-2022-03-00004
4th row3830000-2022-03-00003
5th row3830000-2022-03-00002
ValueCountFrequency (%)
3830000-2023-03-00002 1
 
0.8%
3830000-2002-03-00010 1
 
0.8%
3830000-1998-03-00003 1
 
0.8%
3830000-1998-03-00005 1
 
0.8%
3830000-1999-03-00005 1
 
0.8%
3830000-1999-03-00008 1
 
0.8%
3830000-1999-03-00010 1
 
0.8%
3830000-1999-03-00014 1
 
0.8%
3830000-1999-03-00021 1
 
0.8%
3830000-1999-03-00027 1
 
0.8%
Other values (115) 115
92.0%
2024-04-18T16:57:02.703912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1229
46.8%
3 412
 
15.7%
- 375
 
14.3%
2 145
 
5.5%
8 140
 
5.3%
1 123
 
4.7%
9 102
 
3.9%
5 26
 
1.0%
6 25
 
1.0%
4 24
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2250
85.7%
Dash Punctuation 375
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1229
54.6%
3 412
 
18.3%
2 145
 
6.4%
8 140
 
6.2%
1 123
 
5.5%
9 102
 
4.5%
5 26
 
1.2%
6 25
 
1.1%
4 24
 
1.1%
7 24
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 375
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1229
46.8%
3 412
 
15.7%
- 375
 
14.3%
2 145
 
5.5%
8 140
 
5.3%
1 123
 
4.7%
9 102
 
3.9%
5 26
 
1.0%
6 25
 
1.0%
4 24
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1229
46.8%
3 412
 
15.7%
- 375
 
14.3%
2 145
 
5.5%
8 140
 
5.3%
1 123
 
4.7%
9 102
 
3.9%
5 26
 
1.0%
6 25
 
1.0%
4 24
 
0.9%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
신규
125 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 125
100.0%

Length

2024-04-18T16:57:02.836496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:57:02.927137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 125
100.0%

업종구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
화물운송주선업
125 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화물운송주선업 125
100.0%

Length

2024-04-18T16:57:03.015003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:57:03.118578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화물운송주선업 125
100.0%

업체명
Text

Distinct124
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-18T16:57:03.350578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length13
Mean length7.12
Min length2

Characters and Unicode

Total characters890
Distinct characters193
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

Unique123 ?
Unique (%)98.4%

Sample

1st row진환로지스(주)
2nd row기양산업(주)
3rd row(주)서진로지스
4th row(주)원팀운수
5th row(주)전국물류콜센터
ValueCountFrequency (%)
주식회사 3
 
2.3%
통인익스프레스 2
 
1.5%
코로넷사람들(주 1
 
0.8%
기성화물 1
 
0.8%
전국신금화물 1
 
0.8%
지티인터네셔널(주 1
 
0.8%
다이아몬드특송(주 1
 
0.8%
대진운수(주 1
 
0.8%
주)씨아이에이플러스 1
 
0.8%
신세계익스프레스 1
 
0.8%
Other values (119) 119
90.2%
2024-04-18T16:57:03.740817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 76
 
8.5%
주 48
 
5.4%
( 47
 
5.3%
) 47
 
5.3%
물 45
 
5.1%
류 31
 
3.5%
레 24
 
2.7%
익 23
 
2.6%
프 23
 
2.6%
지 22
 
2.5%
Other values (183) 504
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 745
83.7%
Open Punctuation 47
 
5.3%
Close Punctuation 47
 
5.3%
Lowercase Letter 20
 
2.2%
Uppercase Letter 10
 
1.1%
Space Separator 7
 
0.8%
Other Punctuation 7
 
0.8%
Decimal Number 6
 
0.7%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 76
 
10.2%
주 48
 
6.4%
물 45
 
6.0%
류 31
 
4.2%
레 24
 
3.2%
익 23
 
3.1%
프 23
 
3.1%
지 22
 
3.0%
화 18
 
2.4%
로 18
 
2.4%
Other values (155) 417
56.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
20.0%
o 3
15.0%
t 2
10.0%
p 2
10.0%
a 2
10.0%
e 2
10.0%
d 1
 
5.0%
n 1
 
5.0%
i 1
 
5.0%
g 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
O 3
30.0%
L 2
20.0%
S 1
 
10.0%
R 1
 
10.0%
C 1
 
10.0%
N 1
 
10.0%
P 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
4 2
33.3%
1 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 3
42.9%
& 2
28.6%
, 2
28.6%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 746
83.8%
Common 114
 
12.8%
Latin 30
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 76
 
10.2%
주 48
 
6.4%
물 45
 
6.0%
류 31
 
4.2%
레 24
 
3.2%
익 23
 
3.1%
프 23
 
3.1%
지 22
 
2.9%
화 18
 
2.4%
로 18
 
2.4%
Other values (156) 418
56.0%
Latin
ValueCountFrequency (%)
s 4
13.3%
O 3
 
10.0%
o 3
 
10.0%
L 2
 
6.7%
t 2
 
6.7%
p 2
 
6.7%
a 2
 
6.7%
e 2
 
6.7%
S 1
 
3.3%
R 1
 
3.3%
Other values (8) 8
26.7%
Common
ValueCountFrequency (%)
( 47
41.2%
) 47
41.2%
7
 
6.1%
2 3
 
2.6%
. 3
 
2.6%
4 2
 
1.8%
& 2
 
1.8%
, 2
 
1.8%
1 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 745
83.7%
ASCII 144
 
16.2%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 76
 
10.2%
주 48
 
6.4%
물 45
 
6.0%
류 31
 
4.2%
레 24
 
3.2%
익 23
 
3.1%
프 23
 
3.1%
지 22
 
3.0%
화 18
 
2.4%
로 18
 
2.4%
Other values (155) 417
56.0%
ASCII
ValueCountFrequency (%)
( 47
32.6%
) 47
32.6%
7
 
4.9%
s 4
 
2.8%
2 3
 
2.1%
O 3
 
2.1%
o 3
 
2.1%
. 3
 
2.1%
L 2
 
1.4%
t 2
 
1.4%
Other values (17) 23
16.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

Distinct122
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-18T16:57:03.955782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length37.184
Min length22

Characters and Unicode

Total characters4648
Distinct characters186
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)95.2%

Sample

1st row경기도 안양시 동안구 인덕원로24번길 44, 5층 (관양동)
2nd row경기도 안양시 동안구 흥안대로145번길 127, 4층 (호계동)
3rd row경기도 안양시 만안구 문예로 50, 2층 203-2호 (안양동, 한림시티빌아파트)
4th row경기도 안양시 만안구 덕천로152번길 25, 안양아이에스BIZ타워센트럴 B동 1008호 (안양동)
5th row경기도 안양시 만안구 덕천로152번길 25, 안양아이에스BIZ타워센트럴 A동 1908A호 (안양동)
ValueCountFrequency (%)
경기도 124
 
12.9%
안양시 124
 
12.9%
동안구 83
 
8.6%
만안구 41
 
4.3%
호계동 34
 
3.5%
관양동 32
 
3.3%
안양동 24
 
2.5%
92 14
 
1.5%
엘에스로 14
 
1.5%
비산동 14
 
1.5%
Other values (304) 459
47.7%
2024-04-18T16:57:04.286582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
838
 
18.0%
안 310
 
6.7%
동 238
 
5.1%
양 204
 
4.4%
1 143
 
3.1%
시 135
 
2.9%
2 133
 
2.9%
경 132
 
2.8%
, 128
 
2.8%
호 127
 
2.7%
Other values (176) 2260
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2613
56.2%
Space Separator 838
 
18.0%
Decimal Number 774
 
16.7%
Other Punctuation 130
 
2.8%
Open Punctuation 114
 
2.5%
Close Punctuation 114
 
2.5%
Uppercase Letter 29
 
0.6%
Dash Punctuation 27
 
0.6%
Lowercase Letter 8
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 310
 
11.9%
동 238
 
9.1%
양 204
 
7.8%
시 135
 
5.2%
경 132
 
5.1%
호 127
 
4.9%
로 126
 
4.8%
구 125
 
4.8%
도 124
 
4.7%
기 124
 
4.7%
Other values (141) 968
37.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
20.7%
B 5
17.2%
I 4
13.8%
Z 3
10.3%
C 2
 
6.9%
S 2
 
6.9%
D 1
 
3.4%
L 1
 
3.4%
G 1
 
3.4%
E 1
 
3.4%
Other values (3) 3
10.3%
Decimal Number
ValueCountFrequency (%)
1 143
18.5%
2 133
17.2%
3 97
12.5%
0 83
10.7%
4 76
9.8%
5 64
8.3%
9 55
 
7.1%
7 46
 
5.9%
6 45
 
5.8%
8 32
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
t 1
 
12.5%
r 1
 
12.5%
n 1
 
12.5%
c 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 128
98.5%
. 2
 
1.5%
Space Separator
ValueCountFrequency (%)
838
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2613
56.2%
Common 1998
43.0%
Latin 37
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 310
 
11.9%
동 238
 
9.1%
양 204
 
7.8%
시 135
 
5.2%
경 132
 
5.1%
호 127
 
4.9%
로 126
 
4.8%
구 125
 
4.8%
도 124
 
4.7%
기 124
 
4.7%
Other values (141) 968
37.0%
Latin
ValueCountFrequency (%)
A 6
16.2%
B 5
13.5%
I 4
10.8%
e 4
10.8%
Z 3
 
8.1%
C 2
 
5.4%
S 2
 
5.4%
t 1
 
2.7%
D 1
 
2.7%
r 1
 
2.7%
Other values (8) 8
21.6%
Common
ValueCountFrequency (%)
838
41.9%
1 143
 
7.2%
2 133
 
6.7%
, 128
 
6.4%
( 114
 
5.7%
) 114
 
5.7%
3 97
 
4.9%
0 83
 
4.2%
4 76
 
3.8%
5 64
 
3.2%
Other values (7) 208
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2613
56.2%
ASCII 2035
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
838
41.2%
1 143
 
7.0%
2 133
 
6.5%
, 128
 
6.3%
( 114
 
5.6%
) 114
 
5.6%
3 97
 
4.8%
0 83
 
4.1%
4 76
 
3.7%
5 64
 
3.1%
Other values (25) 245
 
12.0%
Hangul
ValueCountFrequency (%)
안 310
 
11.9%
동 238
 
9.1%
양 204
 
7.8%
시 135
 
5.2%
경 132
 
5.1%
호 127
 
4.9%
로 126
 
4.8%
구 125
 
4.8%
도 124
 
4.7%
기 124
 
4.7%
Other values (141) 968
37.0%

지번주소
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing121
Missing (%)96.8%
Memory size1.1 KiB
2024-04-18T16:57:04.432168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length23.25
Min length22

Characters and Unicode

Total characters93
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row경기도 안양시 만안구 안양동 622-70
2nd row경기도 안양시 만안구 안양동 622-70
3rd row경기도 안양시 만안구 안양동 833-12 101호
4th row경기도 안양시 만안구 안양동 124-32
ValueCountFrequency (%)
경기도 4
19.0%
안양시 4
19.0%
만안구 4
19.0%
안양동 4
19.0%
622-70 2
9.5%
833-12 1
 
4.8%
101호 1
 
4.8%
124-32 1
 
4.8%
2024-04-18T16:57:04.693229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
18.3%
안 12
12.9%
양 8
 
8.6%
2 7
 
7.5%
경 4
 
4.3%
도 4
 
4.3%
시 4
 
4.3%
만 4
 
4.3%
구 4
 
4.3%
동 4
 
4.3%
Other values (10) 25
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
52.7%
Decimal Number 23
24.7%
Space Separator 17
 
18.3%
Dash Punctuation 4
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 12
24.5%
양 8
16.3%
경 4
 
8.2%
도 4
 
8.2%
시 4
 
8.2%
만 4
 
8.2%
구 4
 
8.2%
동 4
 
8.2%
기 4
 
8.2%
호 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 7
30.4%
1 4
17.4%
3 3
13.0%
0 3
13.0%
6 2
 
8.7%
7 2
 
8.7%
8 1
 
4.3%
4 1
 
4.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
52.7%
Common 44
47.3%

Most frequent character per script

Common
ValueCountFrequency (%)
17
38.6%
2 7
15.9%
- 4
 
9.1%
1 4
 
9.1%
3 3
 
6.8%
0 3
 
6.8%
6 2
 
4.5%
7 2
 
4.5%
8 1
 
2.3%
4 1
 
2.3%
Hangul
ValueCountFrequency (%)
안 12
24.5%
양 8
16.3%
경 4
 
8.2%
도 4
 
8.2%
시 4
 
8.2%
만 4
 
8.2%
구 4
 
8.2%
동 4
 
8.2%
기 4
 
8.2%
호 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
52.7%
ASCII 44
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
38.6%
2 7
15.9%
- 4
 
9.1%
1 4
 
9.1%
3 3
 
6.8%
0 3
 
6.8%
6 2
 
4.5%
7 2
 
4.5%
8 1
 
2.3%
4 1
 
2.3%
Hangul
ValueCountFrequency (%)
안 12
24.5%
양 8
16.3%
경 4
 
8.2%
도 4
 
8.2%
시 4
 
8.2%
만 4
 
8.2%
구 4
 
8.2%
동 4
 
8.2%
기 4
 
8.2%
호 1
 
2.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-06-19 00:00:00
Maximum2023-06-19 00:00:00
2024-04-18T16:57:04.819472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:57:04.907855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-04-18T16:57:01.705498image/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

시군명인허가일자인허가번호영업상태업종구분업체명도로명주소지번주소데이터기준일자
0안양시1993-06-163830000-2023-03-00002신규화물운송주선업진환로지스(주)경기도 안양시 동안구 인덕원로24번길 44, 5층 (관양동)<NA>2023-06-19
1안양시1998-10-093830000-2023-03-00001신규화물운송주선업기양산업(주)경기도 안양시 동안구 흥안대로145번길 127, 4층 (호계동)<NA>2023-06-19
2안양시2007-07-313830000-2022-03-00004신규화물운송주선업(주)서진로지스경기도 안양시 만안구 문예로 50, 2층 203-2호 (안양동, 한림시티빌아파트)<NA>2023-06-19
3안양시2004-01-263830000-2022-03-00003신규화물운송주선업(주)원팀운수경기도 안양시 만안구 덕천로152번길 25, 안양아이에스BIZ타워센트럴 B동 1008호 (안양동)<NA>2023-06-19
4안양시2002-12-093830000-2022-03-00002신규화물운송주선업(주)전국물류콜센터경기도 안양시 만안구 덕천로152번길 25, 안양아이에스BIZ타워센트럴 A동 1908A호 (안양동)<NA>2023-06-19
5안양시2001-08-303830000-2022-03-00001신규화물운송주선업(주)도양경기도 안양시 만안구 만안로 284, 1동 519호 (안양동, 마인빌)<NA>2023-06-19
6안양시2021-09-283830000-2021-03-00004신규화물운송주선업엔투엔로지스틱 주식회사경기도 안양시 만안구 덕천로152번길 25, 안양아이에스BIZ타워센트럴 446A호 (안양동)<NA>2023-06-19
7안양시2001-11-143830000-2021-03-00003신규화물운송주선업미래스마트운수경기도 안양시 동안구 전파로 88, 신원비젼타워 709호 (호계동)<NA>2023-06-19
8안양시2007-02-213830000-2021-03-00001신규화물운송주선업(주)한샘서비스경기도 안양시 동안구 시민대로365번길 51 (관양동)<NA>2023-06-19
9안양시2008-02-113830000-2020-03-00002신규화물운송주선업제승물류경기도 안양시 동안구 관평로305번길 41, 401호 (관양동)<NA>2023-06-19
시군명인허가일자인허가번호영업상태업종구분업체명도로명주소지번주소데이터기준일자
115안양시1992-02-113830000-1992-03-00007신규화물운송주선업씨큐에스티(주)경기도 안양시 동안구 경수대로 596, 701호 (호계동)<NA>2023-06-19
116안양시1992-10-163830000-1992-03-00001신규화물운송주선업효성익스프레스경기도 안양시 동안구 평촌대로374번길 9-3, 101호 (비산동)<NA>2023-06-19
117안양시1990-11-283830000-1990-03-00005신규화물운송주선업(주)짱짱물류경기도 안양시 만안구 덕천로 34, 명지e스페이스 7층 702호 (안양동)<NA>2023-06-19
118안양시1990-02-103830000-1990-03-00003신규화물운송주선업드림물류경기도 안양시 만안구 양화로148번길 15, 4층 (박달동)<NA>2023-06-19
119안양시1990-10-273830000-1990-03-00001신규화물운송주선업(주)반도물류경기도 안양시 동안구 평촌대로 239, 신안메트로칸 1336호 (비산동)<NA>2023-06-19
120안양시1989-11-293830000-1989-03-00004신규화물운송주선업경이물류경기도 안양시 동안구 벌말로 126, 평촌 오비즈타워 205호 (관양동)<NA>2023-06-19
121안양시1989-11-293830000-1989-03-00003신규화물운송주선업전국화물퀵경기도 안양시 동안구 경수대로 701, 314호 (호계동, 노블오피스텔)<NA>2023-06-19
122안양시1989-08-073830000-1989-03-00002신규화물운송주선업스마트물류경기도 안양시 동안구 관평로 329, 현대아파트상가 2층 30호 (관양동)<NA>2023-06-19
123안양시1989-12-123830000-1989-03-00001신규화물운송주선업신화화물운송경기도 안양시 동안구 동안로 98, 2층 204호 (호계동, 목련아파트상가동)<NA>2023-06-19
124안양시1984-06-233830000-1984-03-00001신규화물운송주선업영안물류경기도 안양시 동안구 엘에스로 92, 국제유통단지 28동 212호 (호계동)<NA>2023-06-19