Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells11
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory78.3 B

Variable types

Numeric3
Text3
DateTime1
Categorical2

Dataset

Description서울특별시 관악구 화물자동차운송주선사업허가업체 현황(업체명/인허가일자/영업상태명/업체소재지주소/위도/경도/구분/업체전화번호)
URLhttps://www.data.go.kr/data/15080952/fileData.do

Alerts

영업상태명 has constant value ""Constant
전화번호 has 11 (27.5%) missing valuesMissing
연번 has unique valuesUnique
업체명 has unique valuesUnique
인허가일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:40:42.441057
Analysis finished2023-12-12 12:40:44.158502
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:40:44.261344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T21:40:44.480318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

업체명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T21:40:44.791572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.55
Min length4

Characters and Unicode

Total characters262
Distinct characters86
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row서울익스프레스
2nd row아름다운이사
3rd row알뜰익스프레스
4th row보보디앤에스
5th row대동익스프레스
ValueCountFrequency (%)
주식회사 2
 
4.7%
서울익스프레스 1
 
2.3%
대신익스프레스 1
 
2.3%
월드익스프레스 1
 
2.3%
닥터익스프레스 1
 
2.3%
대일통운 1
 
2.3%
대리고 1
 
2.3%
화물전국 1
 
2.3%
라온퀵물류 1
 
2.3%
논스톱화물 1
 
2.3%
Other values (32) 32
74.4%
2023-12-12T21:40:45.247950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 38
 
14.5%
익 17
 
6.5%
프 16
 
6.1%
레 16
 
6.1%
사 10
 
3.8%
운 8
 
3.1%
주 7
 
2.7%
물 6
 
2.3%
이 6
 
2.3%
( 5
 
1.9%
Other values (76) 133
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
92.4%
Open Punctuation 5
 
1.9%
Close Punctuation 5
 
1.9%
Space Separator 3
 
1.1%
Uppercase Letter 3
 
1.1%
Other Punctuation 2
 
0.8%
Decimal Number 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 38
 
15.7%
익 17
 
7.0%
프 16
 
6.6%
레 16
 
6.6%
사 10
 
4.1%
운 8
 
3.3%
주 7
 
2.9%
물 6
 
2.5%
이 6
 
2.5%
대 5
 
2.1%
Other values (67) 113
46.7%
Uppercase Letter
ValueCountFrequency (%)
R 1
33.3%
O 1
33.3%
K 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
92.4%
Common 17
 
6.5%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 38
 
15.7%
익 17
 
7.0%
프 16
 
6.6%
레 16
 
6.6%
사 10
 
4.1%
운 8
 
3.3%
주 7
 
2.9%
물 6
 
2.5%
이 6
 
2.5%
대 5
 
2.1%
Other values (67) 113
46.7%
Common
ValueCountFrequency (%)
( 5
29.4%
) 5
29.4%
3
17.6%
. 2
 
11.8%
2 1
 
5.9%
4 1
 
5.9%
Latin
ValueCountFrequency (%)
R 1
33.3%
O 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
92.4%
ASCII 20
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 38
 
15.7%
익 17
 
7.0%
프 16
 
6.6%
레 16
 
6.6%
사 10
 
4.1%
운 8
 
3.3%
주 7
 
2.9%
물 6
 
2.5%
이 6
 
2.5%
대 5
 
2.1%
Other values (67) 113
46.7%
ASCII
ValueCountFrequency (%)
( 5
25.0%
) 5
25.0%
3
15.0%
. 2
 
10.0%
2 1
 
5.0%
4 1
 
5.0%
R 1
 
5.0%
O 1
 
5.0%
K 1
 
5.0%

인허가일자
Date

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum1984-06-23 00:00:00
Maximum2022-12-14 00:00:00
2023-12-12T21:40:45.432052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:45.619609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
영업중
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 40
100.0%

Length

2023-12-12T21:40:45.760360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:45.878094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 40
100.0%

소재지주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T21:40:46.052263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length19.85
Min length18

Characters and Unicode

Total characters794
Distinct characters29
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

Unique38 ?
Unique (%)95.0%

Sample

1st row서울특별시 관악구 봉천동 41-227
2nd row서울특별시 관악구 신림동 544-24
3rd row서울특별시 관악구 신림동 1577-15
4th row서울특별시 관악구 신림동 1422-5
5th row서울특별시 관악구 신림동 1657-20
ValueCountFrequency (%)
서울특별시 40
25.0%
관악구 39
24.4%
신림동 22
13.8%
봉천동 15
 
9.4%
1577-15 2
 
1.2%
남현동 2
 
1.2%
1646-2 1
 
0.6%
592-10 1
 
0.6%
602-39 1
 
0.6%
950-26 1
 
0.6%
Other values (36) 36
22.5%
2023-12-12T21:40:46.365430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
15.1%
시 41
 
5.2%
서 40
 
5.0%
울 40
 
5.0%
특 40
 
5.0%
별 40
 
5.0%
구 40
 
5.0%
동 40
 
5.0%
관 39
 
4.9%
악 39
 
4.9%
Other values (19) 315
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
55.4%
Decimal Number 196
24.7%
Space Separator 120
 
15.1%
Dash Punctuation 38
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 41
9.3%
서 40
9.1%
울 40
9.1%
특 40
9.1%
별 40
9.1%
구 40
9.1%
동 40
9.1%
관 39
8.9%
악 39
8.9%
림 22
 
5.0%
Other values (7) 59
13.4%
Decimal Number
ValueCountFrequency (%)
5 29
14.8%
2 27
13.8%
1 27
13.8%
6 24
12.2%
4 23
11.7%
7 17
8.7%
3 17
8.7%
0 15
7.7%
9 13
6.6%
8 4
 
2.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
55.4%
Common 354
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 41
9.3%
서 40
9.1%
울 40
9.1%
특 40
9.1%
별 40
9.1%
구 40
9.1%
동 40
9.1%
관 39
8.9%
악 39
8.9%
림 22
 
5.0%
Other values (7) 59
13.4%
Common
ValueCountFrequency (%)
120
33.9%
- 38
 
10.7%
5 29
 
8.2%
2 27
 
7.6%
1 27
 
7.6%
6 24
 
6.8%
4 23
 
6.5%
7 17
 
4.8%
3 17
 
4.8%
0 15
 
4.2%
Other values (2) 17
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
55.4%
ASCII 354
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
33.9%
- 38
 
10.7%
5 29
 
8.2%
2 27
 
7.6%
1 27
 
7.6%
6 24
 
6.8%
4 23
 
6.5%
7 17
 
4.8%
3 17
 
4.8%
0 15
 
4.2%
Other values (2) 17
 
4.8%
Hangul
ValueCountFrequency (%)
시 41
9.3%
서 40
9.1%
울 40
9.1%
특 40
9.1%
별 40
9.1%
구 40
9.1%
동 40
9.1%
관 39
8.9%
악 39
8.9%
림 22
 
5.0%
Other values (7) 59
13.4%

위도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.479059
Minimum37.451193
Maximum37.489503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:40:46.501414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.451193
5-th percentile37.46576
Q137.474749
median37.482084
Q337.48486
95-th percentile37.487205
Maximum37.489503
Range0.03830958
Interquartile range (IQR)0.010110668

Descriptive statistics

Standard deviation0.0079807816
Coefficient of variation (CV)0.00021293975
Kurtosis2.5085752
Mean37.479059
Median Absolute Deviation (MAD)0.003768045
Skewness-1.438199
Sum1499.1624
Variance6.3692876 × 10-5
MonotonicityNot monotonic
2023-12-12T21:40:46.649737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
37.48531965 2
 
5.0%
37.48276568 2
 
5.0%
37.4755685 1
 
2.5%
37.47735463 1
 
2.5%
37.47502817 1
 
2.5%
37.451193 1
 
2.5%
37.48950258 1
 
2.5%
37.4725907 1
 
2.5%
37.47389975 1
 
2.5%
37.48294889 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
37.451193 1
2.5%
37.46286021 1
2.5%
37.46591313 1
2.5%
37.46823784 1
2.5%
37.46869859 1
2.5%
37.46941606 1
2.5%
37.4725907 1
2.5%
37.47313656 1
2.5%
37.47389975 1
2.5%
37.47391334 1
2.5%
ValueCountFrequency (%)
37.48950258 1
2.5%
37.48788448 1
2.5%
37.48716946 1
2.5%
37.48631547 1
2.5%
37.48602025 1
2.5%
37.48568342 1
2.5%
37.48535443 1
2.5%
37.48531965 2
5.0%
37.4851529 1
2.5%
37.48476254 1
2.5%

경도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93472
Minimum126.90463
Maximum126.98042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T21:40:46.782833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90463
5-th percentile126.90727
Q1126.9143
median126.93165
Q3126.95157
95-th percentile126.9693
Maximum126.98042
Range0.0757945
Interquartile range (IQR)0.037278325

Descriptive statistics

Standard deviation0.02211322
Coefficient of variation (CV)0.00017420939
Kurtosis-0.9085357
Mean126.93472
Median Absolute Deviation (MAD)0.018737
Skewness0.3958743
Sum5077.3887
Variance0.00048899448
MonotonicityNot monotonic
2023-12-12T21:40:46.929329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
126.937872 2
 
5.0%
126.9230662 2
 
5.0%
126.9328111 1
 
2.5%
126.9174082 1
 
2.5%
126.980422 1
 
2.5%
126.9073684 1
 
2.5%
126.9477376 1
 
2.5%
126.9674833 1
 
2.5%
126.9687157 1
 
2.5%
126.9077686 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
126.9046275 1
2.5%
126.9054466 1
2.5%
126.9073684 1
2.5%
126.9077557 1
2.5%
126.9077686 1
2.5%
126.9099467 1
2.5%
126.9104146 1
2.5%
126.9111595 1
2.5%
126.9126695 1
2.5%
126.9131612 1
2.5%
ValueCountFrequency (%)
126.980422 1
2.5%
126.9804068 1
2.5%
126.9687157 1
2.5%
126.9674833 1
2.5%
126.9659928 1
2.5%
126.9591692 1
2.5%
126.9583876 1
2.5%
126.9564135 1
2.5%
126.9558026 1
2.5%
126.9536241 1
2.5%

구분
Categorical

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
이사
27 
일반
12 
일반/이사
 
1

Length

Max length5
Median length2
Mean length2.075
Min length2

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
이사 27
67.5%
일반 12
30.0%
일반/이사 1
 
2.5%

Length

2023-12-12T21:40:47.063259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:40:47.165166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이사 27
67.5%
일반 12
30.0%
일반/이사 1
 
2.5%

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing11
Missing (%)27.5%
Memory size452.0 B
2023-12-12T21:40:47.372481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.241379
Min length9

Characters and Unicode

Total characters326
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

Unique29 ?
Unique (%)100.0%

Sample

1st row02-875-2404
2nd row02-843-2400
3rd row02-886-2409
4th row1644-8710
5th row02-854-0024
ValueCountFrequency (%)
02-875-2404 1
 
3.4%
080-2420-080 1
 
3.4%
02-843-2400 1
 
3.4%
0507-1455-2423 1
 
3.4%
02-875-9924 1
 
3.4%
02-882-8000 1
 
3.4%
02-873-8224 1
 
3.4%
02-893-2424 1
 
3.4%
02-857-2311 1
 
3.4%
1588-7007 1
 
3.4%
Other values (19) 19
65.5%
2023-12-12T21:40:47.755637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 64
19.6%
0 58
17.8%
- 56
17.2%
4 39
12.0%
8 37
11.3%
5 20
 
6.1%
7 16
 
4.9%
1 11
 
3.4%
3 11
 
3.4%
6 8
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
82.8%
Dash Punctuation 56
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 64
23.7%
0 58
21.5%
4 39
14.4%
8 37
13.7%
5 20
 
7.4%
7 16
 
5.9%
1 11
 
4.1%
3 11
 
4.1%
6 8
 
3.0%
9 6
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 326
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 64
19.6%
0 58
17.8%
- 56
17.2%
4 39
12.0%
8 37
11.3%
5 20
 
6.1%
7 16
 
4.9%
1 11
 
3.4%
3 11
 
3.4%
6 8
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 326
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 64
19.6%
0 58
17.8%
- 56
17.2%
4 39
12.0%
8 37
11.3%
5 20
 
6.1%
7 16
 
4.9%
1 11
 
3.4%
3 11
 
3.4%
6 8
 
2.5%

Interactions

2023-12-12T21:40:43.567517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:42.786392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.187226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.691704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:42.932509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.310451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.813844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.069789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:40:43.440734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:40:47.873717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명인허가일자소재지주소위도경도구분전화번호
연번1.0001.0001.0000.9320.0000.0000.5421.000
업체명1.0001.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0001.0001.0001.0001.0001.0001.000
소재지주소0.9321.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0001.0000.6140.2791.000
경도0.0001.0001.0001.0000.6141.0000.4481.000
구분0.5421.0001.0001.0000.2790.4481.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T21:40:48.008896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도구분
연번1.000-0.2350.2220.340
위도-0.2351.000-0.0310.157
경도0.222-0.0311.0000.262
구분0.3400.1570.2621.000

Missing values

2023-12-12T21:40:43.950970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:40:44.103022image/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

연번업체명인허가일자영업상태명소재지주소위도경도구분전화번호
01서울익스프레스1995-03-07영업중서울특별시 관악구 봉천동 41-22737.486315126.953624이사02-875-2404
12아름다운이사1996-07-19영업중서울특별시 관악구 신림동 544-2437.481832126.910415이사02-843-2400
23알뜰익스프레스2001-05-14영업중서울특별시 관악구 신림동 1577-1537.482766126.923066이사02-886-2409
34보보디앤에스1984-06-23영업중서울특별시 관악구 신림동 1422-537.484763126.930097일반1644-8710
45대동익스프레스1993-07-03영업중서울특별시 관악구 신림동 1657-2037.481735126.904628이사02-854-0024
56삼일운송사1992-08-26영업중서울특별시 관악구 신림동 170637.468238126.944343이사02-884-2424
67미광운수알선사1992-11-24영업중서울특별시 관악구 봉천동 50-17737.485354126.950892이사02-877-2424
78전국아름다운이사1994-06-09영업중서울특별시 관악구 신림동 535-1337.484457126.911159이사02-854-1234
89한미익스프레스1995-06-21영업중서울특별시 관악구 신림동 480-1537.48602126.919605이사02-858-4000
910효성익스프레스1996-03-26영업중서울특별시 관악구 신림동 362-5737.469416126.930494이사02-556-2000
연번업체명인허가일자영업상태명소재지주소위도경도구분전화번호
3031(주)바른물류2006-09-22영업중서울특별시 관악구 신림동 569-3437.482949126.907769일반<NA>
3132상지통운1992-09-26영업중서울특별시 관악구 신림동 169437.475569126.932811이사02-882-8000
3233(주)아이무빙1992-08-05영업중서울특별시 관악구 신림동 1602-237.481577126.928063이사02-875-9924
3334전국24익스프레스2021-07-19영업중서울특별시 관악구 신림동 537-237.482891126.91267이사0507-1455-2423
3435한국익스프레스2001-02-13영업중서울특별시 관악구 남현동 602-4037.475229126.980407이사02-583-2400
3536사무실이사2020-06-02영업중서울특별시 관악구 봉천동 181-737.473137126.965993일반/이사<NA>
3637(주)다다익스2021-05-13영업중서울특별시 관악구 봉천동 1624-2437.476296126.958388일반<NA>
3738주식회사 공간씨엔에스2022-12-14영업중서울특별시 관악구 봉천동 34-737.484674126.955803이사<NA>
3839로젠스마트이사2022-06-28영업중서울특별시 관악구 신림동 545-537.482148126.909947이사<NA>
3940곳간로지스(주)2022-07-25 0:00영업중서울특별시 관악구 신림동 1555-437.468699126.934444일반<NA>