Overview

Dataset statistics

Number of variables6
Number of observations566
Missing cells991
Missing cells (%)29.2%
Duplicate rows23
Duplicate rows (%)4.1%
Total size in memory28.3 KiB
Average record size in memory51.2 B

Variable types

Text2
Categorical1
Numeric3

Dataset

Description경상남도 창원시의 일반화물자동차 운송사업자의 사업현황을 표출합니다. 항목은 업체명, 허가종별, 보유차량대수, 직영/위수탁여부, 주소 등입니다.
Author경상남도 창원시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15115896

Alerts

Dataset has 23 (4.1%) duplicate rowsDuplicates
차량대수(직영) is highly overall correlated with 차량대수(확인불가)High correlation
차량대수(확인불가) is highly overall correlated with 차량대수(직영)High correlation
차량대수(직영) has 106 (18.7%) missing valuesMissing
차량대수(위수탁) has 421 (74.4%) missing valuesMissing
차량대수(확인불가) has 464 (82.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:29:22.450929
Analysis finished2023-12-10 23:29:23.758719
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct268
Distinct (%)47.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-11T08:29:24.097566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length9.6519435
Min length2

Characters and Unicode

Total characters5463
Distinct characters232
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique266 ?
Unique (%)47.0%

Sample

1st row개인사업자(업체명없음)
2nd row(주)해솔로지스
3rd row(주)창진로지스
4th row개인사업자(업체명없음)
5th row(주)우경특수
ValueCountFrequency (%)
개인사업자(업체명없음 298
50.9%
주식회사 11
 
1.9%
주)새로비스 2
 
0.3%
경남지사 2
 
0.3%
신우화물 1
 
0.2%
크레인 1
 
0.2%
스카이 1
 
0.2%
우성 1
 
0.2%
신라상사 1
 
0.2%
명진카고크레인 1
 
0.2%
Other values (267) 267
45.6%
2023-12-11T08:29:24.577846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 602
 
11.0%
( 456
 
8.3%
) 456
 
8.3%
사 319
 
5.8%
인 304
 
5.6%
자 301
 
5.5%
개 299
 
5.5%
명 299
 
5.5%
체 298
 
5.5%
없 298
 
5.5%
Other values (222) 1831
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4503
82.4%
Open Punctuation 456
 
8.3%
Close Punctuation 456
 
8.3%
Space Separator 20
 
0.4%
Uppercase Letter 14
 
0.3%
Other Symbol 9
 
0.2%
Lowercase Letter 4
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 602
13.4%
사 319
 
7.1%
인 304
 
6.8%
자 301
 
6.7%
개 299
 
6.6%
명 299
 
6.6%
체 298
 
6.6%
없 298
 
6.6%
음 298
 
6.6%
주 168
 
3.7%
Other values (204) 1317
29.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
M 2
14.3%
H 2
14.3%
J 2
14.3%
K 1
 
7.1%
F 1
 
7.1%
B 1
 
7.1%
G 1
 
7.1%
L 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
l 1
25.0%
i 1
25.0%
n 1
25.0%
a 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 456
100.0%
Close Punctuation
ValueCountFrequency (%)
) 456
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4512
82.6%
Common 933
 
17.1%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 602
13.3%
사 319
 
7.1%
인 304
 
6.7%
자 301
 
6.7%
개 299
 
6.6%
명 299
 
6.6%
체 298
 
6.6%
없 298
 
6.6%
음 298
 
6.6%
주 168
 
3.7%
Other values (205) 1326
29.4%
Latin
ValueCountFrequency (%)
S 3
16.7%
M 2
11.1%
H 2
11.1%
J 2
11.1%
K 1
 
5.6%
F 1
 
5.6%
B 1
 
5.6%
G 1
 
5.6%
L 1
 
5.6%
l 1
 
5.6%
Other values (3) 3
16.7%
Common
ValueCountFrequency (%)
( 456
48.9%
) 456
48.9%
20
 
2.1%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4503
82.4%
ASCII 951
 
17.4%
None 9
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 602
13.4%
사 319
 
7.1%
인 304
 
6.8%
자 301
 
6.7%
개 299
 
6.6%
명 299
 
6.6%
체 298
 
6.6%
없 298
 
6.6%
음 298
 
6.6%
주 168
 
3.7%
Other values (204) 1317
29.2%
ASCII
ValueCountFrequency (%)
( 456
47.9%
) 456
47.9%
20
 
2.1%
S 3
 
0.3%
M 2
 
0.2%
H 2
 
0.2%
J 2
 
0.2%
K 1
 
0.1%
F 1
 
0.1%
B 1
 
0.1%
Other values (7) 7
 
0.7%
None
ValueCountFrequency (%)
㈜ 9
100.0%

면허종류
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
(구)일반화물
474 
일반화물
92 

Length

Max length7
Median length7
Mean length6.5123675
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
(구)일반화물 474
83.7%
일반화물 92
 
16.3%

Length

2023-12-11T08:29:24.694366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:29:24.770631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구)일반화물 474
83.7%
일반화물 92
 
16.3%

차량대수(직영)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)3.3%
Missing106
Missing (%)18.7%
Infinite0
Infinite (%)0.0%
Mean2.1130435
Minimum1
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-11T08:29:24.840059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum54
Range53
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.4070674
Coefficient of variation (CV)1.6123982
Kurtosis135.62964
Mean2.1130435
Median Absolute Deviation (MAD)0
Skewness10.288308
Sum972
Variance11.608108
MonotonicityNot monotonic
2023-12-11T08:29:24.926045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 231
40.8%
2 166
29.3%
3 25
 
4.4%
4 13
 
2.3%
5 7
 
1.2%
8 4
 
0.7%
6 3
 
0.5%
12 2
 
0.4%
18 2
 
0.4%
9 2
 
0.4%
Other values (5) 5
 
0.9%
(Missing) 106
18.7%
ValueCountFrequency (%)
1 231
40.8%
2 166
29.3%
3 25
 
4.4%
4 13
 
2.3%
5 7
 
1.2%
6 3
 
0.5%
7 1
 
0.2%
8 4
 
0.7%
9 2
 
0.4%
10 1
 
0.2%
ValueCountFrequency (%)
54 1
 
0.2%
34 1
 
0.2%
18 2
0.4%
14 1
 
0.2%
12 2
0.4%
10 1
 
0.2%
9 2
0.4%
8 4
0.7%
7 1
 
0.2%
6 3
0.5%

차량대수(위수탁)
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)27.6%
Missing421
Missing (%)74.4%
Infinite0
Infinite (%)0.0%
Mean12.593103
Minimum1
Maximum137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-11T08:29:25.019367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q311
95-th percentile61.8
Maximum137
Range136
Interquartile range (IQR)9

Descriptive statistics

Standard deviation22.338773
Coefficient of variation (CV)1.7738894
Kurtosis11.385613
Mean12.593103
Median Absolute Deviation (MAD)2
Skewness3.1098773
Sum1826
Variance499.02079
MonotonicityNot monotonic
2023-12-11T08:29:25.131564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2 41
 
7.2%
1 30
 
5.3%
4 10
 
1.8%
6 7
 
1.2%
7 5
 
0.9%
3 4
 
0.7%
5 4
 
0.7%
8 3
 
0.5%
16 3
 
0.5%
25 3
 
0.5%
Other values (30) 35
 
6.2%
(Missing) 421
74.4%
ValueCountFrequency (%)
1 30
5.3%
2 41
7.2%
3 4
 
0.7%
4 10
 
1.8%
5 4
 
0.7%
6 7
 
1.2%
7 5
 
0.9%
8 3
 
0.5%
9 1
 
0.2%
10 3
 
0.5%
ValueCountFrequency (%)
137 1
0.2%
127 1
0.2%
77 1
0.2%
75 1
0.2%
70 1
0.2%
66 1
0.2%
64 1
0.2%
62 1
0.2%
61 1
0.2%
57 1
0.2%

차량대수(확인불가)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)21.6%
Missing464
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean6.8235294
Minimum1
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-11T08:29:25.243428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile21.8
Maximum67
Range66
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.7892766
Coefficient of variation (CV)1.4346354
Kurtosis16.737077
Mean6.8235294
Median Absolute Deviation (MAD)3
Skewness3.7057751
Sum696
Variance95.829936
MonotonicityNot monotonic
2023-12-11T08:29:25.335084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 21
 
3.7%
3 16
 
2.8%
2 13
 
2.3%
4 11
 
1.9%
10 7
 
1.2%
5 6
 
1.1%
6 4
 
0.7%
7 4
 
0.7%
9 3
 
0.5%
8 3
 
0.5%
Other values (12) 14
 
2.5%
(Missing) 464
82.0%
ValueCountFrequency (%)
1 21
3.7%
2 13
2.3%
3 16
2.8%
4 11
1.9%
5 6
 
1.1%
6 4
 
0.7%
7 4
 
0.7%
8 3
 
0.5%
9 3
 
0.5%
10 7
 
1.2%
ValueCountFrequency (%)
67 1
0.2%
42 1
0.2%
41 1
0.2%
38 1
0.2%
29 1
0.2%
22 1
0.2%
18 2
0.4%
16 1
0.2%
15 1
0.2%
13 1
0.2%

주소
Text

Distinct471
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-12-11T08:29:25.575721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length35.402827
Min length21

Characters and Unicode

Total characters20038
Distinct characters327
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique409 ?
Unique (%)72.3%

Sample

1st row경상남도 창원시 의창구 서곡길 133 (봉곡동,늘푸른마을 코오롱아파트)
2nd row경상남도 창원시 의창구 사림로 47, 사림프라자 504호 (사림동)
3rd row경상남도 창원시 의창구 차상로 58, 한신빌딩 2층 202호 (팔용동)
4th row경상남도 창원시 의창구 서상로 27 (동정동,동정오성아파트)
5th row경상남도 창원시 의창구 차룡로48번길 44, 창원스마트업타워 S1807호 (팔용동)
ValueCountFrequency (%)
경상남도 566
 
15.0%
창원시 566
 
15.0%
진해구 135
 
3.6%
의창구 134
 
3.6%
마산회원구 121
 
3.2%
성산구 103
 
2.7%
마산합포구 73
 
1.9%
내서읍 57
 
1.5%
팔용동 40
 
1.1%
사랑으로 28
 
0.7%
Other values (994) 1950
51.7%
2023-12-11T08:29:25.949883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3207
 
16.0%
원 901
 
4.5%
창 773
 
3.9%
동 668
 
3.3%
남 650
 
3.2%
상 634
 
3.2%
시 591
 
2.9%
구 591
 
2.9%
경 583
 
2.9%
도 575
 
2.9%
Other values (317) 10865
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12923
64.5%
Space Separator 3207
 
16.0%
Decimal Number 2349
 
11.7%
Open Punctuation 528
 
2.6%
Close Punctuation 528
 
2.6%
Other Punctuation 363
 
1.8%
Dash Punctuation 101
 
0.5%
Uppercase Letter 37
 
0.2%
Lowercase Letter 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 901
 
7.0%
창 773
 
6.0%
동 668
 
5.2%
남 650
 
5.0%
상 634
 
4.9%
시 591
 
4.6%
구 591
 
4.6%
경 583
 
4.5%
도 575
 
4.4%
로 496
 
3.8%
Other values (283) 6461
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 9
24.3%
B 7
18.9%
O 4
10.8%
K 4
10.8%
N 3
 
8.1%
E 2
 
5.4%
T 2
 
5.4%
X 2
 
5.4%
I 1
 
2.7%
D 1
 
2.7%
Other values (2) 2
 
5.4%
Decimal Number
ValueCountFrequency (%)
1 518
22.1%
2 360
15.3%
3 271
11.5%
4 225
9.6%
0 199
 
8.5%
5 173
 
7.4%
7 163
 
6.9%
8 161
 
6.9%
6 147
 
6.3%
9 132
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 356
98.1%
· 4
 
1.1%
: 2
 
0.6%
* 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 527
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 527
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3207
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12924
64.5%
Common 7076
35.3%
Latin 38
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 901
 
7.0%
창 773
 
6.0%
동 668
 
5.2%
남 650
 
5.0%
상 634
 
4.9%
시 591
 
4.6%
구 591
 
4.6%
경 583
 
4.5%
도 575
 
4.4%
로 496
 
3.8%
Other values (284) 6462
50.0%
Common
ValueCountFrequency (%)
3207
45.3%
( 527
 
7.4%
) 527
 
7.4%
1 518
 
7.3%
2 360
 
5.1%
, 356
 
5.0%
3 271
 
3.8%
4 225
 
3.2%
0 199
 
2.8%
5 173
 
2.4%
Other values (10) 713
 
10.1%
Latin
ValueCountFrequency (%)
S 9
23.7%
B 7
18.4%
O 4
10.5%
K 4
10.5%
N 3
 
7.9%
E 2
 
5.3%
T 2
 
5.3%
X 2
 
5.3%
e 1
 
2.6%
I 1
 
2.6%
Other values (3) 3
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12923
64.5%
ASCII 7110
35.5%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3207
45.1%
( 527
 
7.4%
) 527
 
7.4%
1 518
 
7.3%
2 360
 
5.1%
, 356
 
5.0%
3 271
 
3.8%
4 225
 
3.2%
0 199
 
2.8%
5 173
 
2.4%
Other values (22) 747
 
10.5%
Hangul
ValueCountFrequency (%)
원 901
 
7.0%
창 773
 
6.0%
동 668
 
5.2%
남 650
 
5.0%
상 634
 
4.9%
시 591
 
4.6%
구 591
 
4.6%
경 583
 
4.5%
도 575
 
4.4%
로 496
 
3.8%
Other values (283) 6461
50.0%
None
ValueCountFrequency (%)
· 4
80.0%
㈜ 1
 
20.0%

Interactions

2023-12-11T08:29:23.236828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:22.780390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:23.010267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:23.308342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:22.861480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:23.078056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:23.384165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:22.936161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:29:23.156279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:29:26.030605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면허종류차량대수(직영)차량대수(위수탁)차량대수(확인불가)
면허종류1.0000.3070.0970.332
차량대수(직영)0.3071.0000.7320.887
차량대수(위수탁)0.0970.7321.0000.847
차량대수(확인불가)0.3320.8870.8471.000
2023-12-11T08:29:26.115051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차량대수(직영)차량대수(위수탁)차량대수(확인불가)면허종류
차량대수(직영)1.0000.3650.5830.220
차량대수(위수탁)0.3651.0000.3510.101
차량대수(확인불가)0.5830.3511.0000.240
면허종류0.2200.1010.2401.000

Missing values

2023-12-11T08:29:23.503159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:29:23.615884image/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.
2023-12-11T08:29:23.698849image/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

업체명면허종류차량대수(직영)차량대수(위수탁)차량대수(확인불가)주소
0개인사업자(업체명없음)일반화물1<NA><NA>경상남도 창원시 의창구 서곡길 133 (봉곡동,늘푸른마을 코오롱아파트)
1(주)해솔로지스일반화물<NA>2<NA>경상남도 창원시 의창구 사림로 47, 사림프라자 504호 (사림동)
2(주)창진로지스일반화물<NA>2<NA>경상남도 창원시 의창구 차상로 58, 한신빌딩 2층 202호 (팔용동)
3개인사업자(업체명없음)일반화물2<NA><NA>경상남도 창원시 의창구 서상로 27 (동정동,동정오성아파트)
4(주)우경특수일반화물<NA>2<NA>경상남도 창원시 의창구 차룡로48번길 44, 창원스마트업타워 S1807호 (팔용동)
5동서(주)일반화물<NA>21경상남도 창원시 의창구 용동로 45, 현대썬앤빌더스퀘어 C동 411호 (사림동)
6북면북창원레카일반화물31<NA>경상남도 창원시 의창구 북면 동전로45번길 28, 1층
7창원레카(문준호)일반화물13<NA>경상남도 창원시 의창구 무역로503번길 5 (팔용동)
8우진통운일반화물6<NA><NA>경상남도 창원시 의창구 무역로581번길 2-1, 2층 (사화동)
9㈜항도물류일반화물<NA>7<NA>경상남도 창원시 의창구 지귀로28번길 23 (봉곡동)
업체명면허종류차량대수(직영)차량대수(위수탁)차량대수(확인불가)주소
556(주)고려특운(구)일반화물2<NA>9경상남도 창원시 진해구 행암로 12, 엠에스빌딩 410호 (장천동)
557티앤티 주식회사(구)일반화물<NA>210경상남도 창원시 진해구 안골로 52 (안골동)
558씨제이대한통운(주)진해영업소(구)일반화물5121경상남도 창원시 진해구 천자로 278 (장천동)
559(주)보고대성로지스(구)일반화물<NA>613경상남도 창원시 진해구 신항3로 22, 보고씨엔에스 2층 (용원동)
560지알로지스틱(주)(구)일반화물<NA>163경상남도 창원시 진해구 신항8로 203 (남문동, KOSENKO국제물류센터)
561디앤디로직스(주)(구)일반화물4216경상남도 창원시 진해구 신항북로 320, 322호 (용원동, 내트럭(주) 부산신항 사업소)
562금륜물류(주)(구)일반화물4182경상남도 창원시 진해구 웅동로 72, 상가동 306호 (마천동, 남명프라자)
563선도특운(주)(구)일반화물<NA>25<NA>경상남도 창원시 진해구 충장로285번길 27-1, 103호 (경화동, 봉산하이츠빌라)
564(주)월드로지스텍(구)일반화물9<NA>18경상남도 창원시 진해구 신항8로 139, DNI로지스틱스 (남문동)
565㈜올웨이즈익스프레스(구)일반화물34<NA>42경상남도 창원시 진해구 신항5로 15-13, 엠에스디스트리파크 (용원동)

Duplicate rows

Most frequently occurring

업체명면허종류차량대수(직영)차량대수(위수탁)차량대수(확인불가)주소# duplicates
15개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 신항동로 136 (용원동,부산신항 사랑으로 부영 8단지)5
14개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 신항4로 75(용원동,부산신항 사랑으로 부영 13단지)4
3개인사업자(업체명없음)(구)일반화물1<NA><NA>경상남도 창원시 마산회원구 삼호로 80 (양덕동,메트로시티2단지)3
13개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 신항4로 75 (용원동,부산신항 사랑으로 부영 13단지)3
17개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 신항동로 225 (용원동,부산신항 사랑으로 부영 3단지)3
18개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 신항북로 202(용원동,부산신항만이지더원아파트2단지)3
19개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 안골로298번길 26 (안골동,창원마린2차푸르지오)3
20개인사업자(업체명없음)(구)일반화물2<NA><NA>경상남도 창원시 진해구 안청남로 13(청안동,부영아파트)3
0개인사업자(업체명없음)(구)일반화물1<NA><NA>경상남도 창원시 마산합포구 월영동11길 42 (해운동,두산아파트)2
1개인사업자(업체명없음)(구)일반화물1<NA><NA>경상남도 창원시 마산합포구 진동면 진북산업로 58 (한일유앤아이아파트)2