Overview

Dataset statistics

Number of variables7
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory61.6 B

Variable types

Numeric2
Categorical1
Text4

Dataset

Description양산시 주요기업으로 종업원수100명이상 본사가 양산이 기업현황입니다. 주요대용은 대기업, 중기업, 중견기업 구분과 기업명, 소재지, 전화번호, 주요생산품을 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15078478

Alerts

순번 is highly overall correlated with 종업원수 and 1 other fieldsHigh correlation
종업원수 is highly overall correlated with 순번High correlation
구분 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique
회사명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:55:39.640911
Analysis finished2023-12-10 23:55:40.981624
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T08:55:41.059932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-11T08:55:41.206381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
중기업
22 
대기업
8 
중견기업
5 
소기업
 
1
중소기업
 
1

Length

Max length4
Median length3
Mean length3.1621622
Min length3

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
중기업 22
59.5%
대기업 8
 
21.6%
중견기업 5
 
13.5%
소기업 1
 
2.7%
중소기업 1
 
2.7%

Length

2023-12-11T08:55:41.345973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:55:41.460246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중기업 22
59.5%
대기업 8
 
21.6%
중견기업 5
 
13.5%
소기업 1
 
2.7%
중소기업 1
 
2.7%

회사명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T08:55:41.693083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.2972973
Min length5

Characters and Unicode

Total characters270
Distinct characters94
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row넥센타이어(주)
2nd row(주)화승알앤에이
3rd row동아타이어공업(주)
4th row(주)흥아
5th row(주)디티알
ValueCountFrequency (%)
넥센타이어(주 1
 
2.7%
한일제관(주 1
 
2.7%
주)화승t&c 1
 
2.7%
주)진주햄 1
 
2.7%
제일e&s(주 1
 
2.7%
주)에이치씨글로벌 1
 
2.7%
송월(주 1
 
2.7%
포스텍전자(주 1
 
2.7%
주)대성사 1
 
2.7%
주)동희정공 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T08:55:42.118979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 38
 
14.1%
( 37
 
13.7%
) 37
 
13.7%
이 9
 
3.3%
스 6
 
2.2%
에 5
 
1.9%
한 4
 
1.5%
아 4
 
1.5%
제 4
 
1.5%
씨 3
 
1.1%
Other values (84) 123
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
69.3%
Open Punctuation 37
 
13.7%
Close Punctuation 37
 
13.7%
Uppercase Letter 7
 
2.6%
Other Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 38
 
20.3%
이 9
 
4.8%
스 6
 
3.2%
에 5
 
2.7%
한 4
 
2.1%
아 4
 
2.1%
제 4
 
2.1%
씨 3
 
1.6%
전 3
 
1.6%
티 3
 
1.6%
Other values (76) 108
57.8%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
S 2
28.6%
E 1
14.3%
T 1
14.3%
M 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
69.3%
Common 76
28.1%
Latin 7
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 38
 
20.3%
이 9
 
4.8%
스 6
 
3.2%
에 5
 
2.7%
한 4
 
2.1%
아 4
 
2.1%
제 4
 
2.1%
씨 3
 
1.6%
전 3
 
1.6%
티 3
 
1.6%
Other values (76) 108
57.8%
Latin
ValueCountFrequency (%)
C 2
28.6%
S 2
28.6%
E 1
14.3%
T 1
14.3%
M 1
14.3%
Common
ValueCountFrequency (%)
( 37
48.7%
) 37
48.7%
& 2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
69.3%
ASCII 83
30.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 38
 
20.3%
이 9
 
4.8%
스 6
 
3.2%
에 5
 
2.7%
한 4
 
2.1%
아 4
 
2.1%
제 4
 
2.1%
씨 3
 
1.6%
전 3
 
1.6%
티 3
 
1.6%
Other values (76) 108
57.8%
ASCII
ValueCountFrequency (%)
( 37
44.6%
) 37
44.6%
C 2
 
2.4%
& 2
 
2.4%
S 2
 
2.4%
E 1
 
1.2%
T 1
 
1.2%
M 1
 
1.2%

도로명주소
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T08:55:42.372185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length17.837838
Min length15

Characters and Unicode

Total characters660
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)94.6%

Sample

1st row경상남도 양산시 충렬로 355
2nd row경상남도 양산시 충렬로 61
3rd row경상남도 양산시 유산공단11길 11
4th row경상남도 양산시 어실로 77
5th row경상남도 양산시 산막공단북11길 103
ValueCountFrequency (%)
경상남도 37
24.7%
양산시 37
24.7%
충렬로 6
 
4.0%
유산공단7길 4
 
2.7%
어실로 3
 
2.0%
39 2
 
1.3%
45 2
 
1.3%
11 2
 
1.3%
유산공단4길 2
 
1.3%
77 2
 
1.3%
Other values (51) 53
35.3%
2023-12-11T08:55:42.706158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
109
16.5%
산 52
 
7.9%
상 42
 
6.4%
남 38
 
5.8%
양 38
 
5.8%
경 37
 
5.6%
도 37
 
5.6%
시 37
 
5.6%
1 30
 
4.5%
단 21
 
3.2%
Other values (36) 219
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 432
65.5%
Space Separator 113
 
17.1%
Decimal Number 112
 
17.0%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 52
12.0%
상 42
9.7%
남 38
8.8%
양 38
8.8%
경 37
8.6%
도 37
8.6%
시 37
8.6%
단 21
 
4.9%
공 21
 
4.9%
길 20
 
4.6%
Other values (23) 89
20.6%
Decimal Number
ValueCountFrequency (%)
1 30
26.8%
3 18
16.1%
4 14
12.5%
5 13
11.6%
7 10
 
8.9%
2 8
 
7.1%
6 6
 
5.4%
9 5
 
4.5%
8 4
 
3.6%
0 4
 
3.6%
Space Separator
ValueCountFrequency (%)
109
96.5%
  4
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 432
65.5%
Common 228
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 52
12.0%
상 42
9.7%
남 38
8.8%
양 38
8.8%
경 37
8.6%
도 37
8.6%
시 37
8.6%
단 21
 
4.9%
공 21
 
4.9%
길 20
 
4.6%
Other values (23) 89
20.6%
Common
ValueCountFrequency (%)
109
47.8%
1 30
 
13.2%
3 18
 
7.9%
4 14
 
6.1%
5 13
 
5.7%
7 10
 
4.4%
2 8
 
3.5%
6 6
 
2.6%
9 5
 
2.2%
  4
 
1.8%
Other values (3) 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 432
65.5%
ASCII 224
33.9%
None 4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
109
48.7%
1 30
 
13.4%
3 18
 
8.0%
4 14
 
6.2%
5 13
 
5.8%
7 10
 
4.5%
2 8
 
3.6%
6 6
 
2.7%
9 5
 
2.2%
8 4
 
1.8%
Other values (2) 7
 
3.1%
Hangul
ValueCountFrequency (%)
산 52
12.0%
상 42
9.7%
남 38
8.8%
양 38
8.8%
경 37
8.6%
도 37
8.6%
시 37
8.6%
단 21
 
4.9%
공 21
 
4.9%
길 20
 
4.6%
Other values (23) 89
20.6%
None
ValueCountFrequency (%)
  4
100.0%

전화번호
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T08:55:42.909861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027027
Min length12

Characters and Unicode

Total characters445
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

Unique37 ?
Unique (%)100.0%

Sample

1st row055-370-5114
2nd row055-370-3331
3rd row055-389-0011
4th row055-371-3700
5th row055-758-5166
ValueCountFrequency (%)
055-370-5114 1
 
2.7%
055-370-6600 1
 
2.7%
055-380-3600 1
 
2.7%
055-387-5001 1
 
2.7%
055-383-1301 1
 
2.7%
055-386-2161 1
 
2.7%
055-911-1040 1
 
2.7%
055-371-7000 1
 
2.7%
055-372-2007 1
 
2.7%
070-7093-6420 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T08:55:43.222324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 106
23.8%
5 83
18.7%
- 74
16.6%
3 51
11.5%
7 34
 
7.6%
1 31
 
7.0%
8 19
 
4.3%
6 15
 
3.4%
9 13
 
2.9%
2 10
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 371
83.4%
Dash Punctuation 74
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
28.6%
5 83
22.4%
3 51
13.7%
7 34
 
9.2%
1 31
 
8.4%
8 19
 
5.1%
6 15
 
4.0%
9 13
 
3.5%
2 10
 
2.7%
4 9
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 445
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 106
23.8%
5 83
18.7%
- 74
16.6%
3 51
11.5%
7 34
 
7.6%
1 31
 
7.0%
8 19
 
4.3%
6 15
 
3.4%
9 13
 
2.9%
2 10
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 445
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106
23.8%
5 83
18.7%
- 74
16.6%
3 51
11.5%
7 34
 
7.6%
1 31
 
7.0%
8 19
 
4.3%
6 15
 
3.4%
9 13
 
2.9%
2 10
 
2.2%

종업원수
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean379.91892
Minimum100
Maximum4149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-11T08:55:43.348206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile106.4
Q1128
median195
Q3300
95-th percentile897.6
Maximum4149
Range4049
Interquartile range (IQR)172

Descriptive statistics

Standard deviation677.66914
Coefficient of variation (CV)1.7837204
Kurtosis28.230018
Mean379.91892
Median Absolute Deviation (MAD)79
Skewness5.0877251
Sum14057
Variance459235.47
MonotonicityNot monotonic
2023-12-11T08:55:43.487650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
116 2
 
5.4%
4149 1
 
2.7%
138 1
 
2.7%
195 1
 
2.7%
187 1
 
2.7%
175 1
 
2.7%
168 1
 
2.7%
160 1
 
2.7%
144 1
 
2.7%
129 1
 
2.7%
Other values (26) 26
70.3%
ValueCountFrequency (%)
100 1
2.7%
104 1
2.7%
107 1
2.7%
108 1
2.7%
112 1
2.7%
116 2
5.4%
120 1
2.7%
126 1
2.7%
128 1
2.7%
129 1
2.7%
ValueCountFrequency (%)
4149 1
2.7%
1208 1
2.7%
820 1
2.7%
591 1
2.7%
587 1
2.7%
583 1
2.7%
529 1
2.7%
375 1
2.7%
329 1
2.7%
300 1
2.7%

생산품
Text

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-11T08:55:43.720180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length17
Mean length9.8378378
Min length2

Characters and Unicode

Total characters364
Distinct characters154
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

Unique35 ?
Unique (%)94.6%

Sample

1st row타이어
2nd row자동차용고무부품및산업용고무
3rd row타이어, 튜브
4th row타이어
5th row자동차용 소음 및 방진부품
ValueCountFrequency (%)
타이어 3
 
4.4%
자동차부품(자동차 1
 
1.5%
수지 1
 
1.5%
벨보아 1
 
1.5%
자동차고무부품외 1
 
1.5%
햄 1
 
1.5%
소시지 1
 
1.5%
맛살 1
 
1.5%
s.w.c 1
 
1.5%
joint 1
 
1.5%
Other values (56) 56
82.4%
2023-12-11T08:55:44.063560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
8.5%
, 16
 
4.4%
자 11
 
3.0%
동 10
 
2.7%
차 10
 
2.7%
부 9
 
2.5%
스 9
 
2.5%
품 9
 
2.5%
용 8
 
2.2%
라 8
 
2.2%
Other values (144) 243
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
70.9%
Space Separator 31
 
8.5%
Uppercase Letter 26
 
7.1%
Lowercase Letter 22
 
6.0%
Other Punctuation 21
 
5.8%
Open Punctuation 2
 
0.5%
Dash Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 11
 
4.3%
동 10
 
3.9%
차 10
 
3.9%
부 9
 
3.5%
스 9
 
3.5%
품 9
 
3.5%
용 8
 
3.1%
라 8
 
3.1%
지 5
 
1.9%
이 5
 
1.9%
Other values (116) 174
67.4%
Uppercase Letter
ValueCountFrequency (%)
S 5
19.2%
E 4
15.4%
T 3
11.5%
I 3
11.5%
N 2
 
7.7%
W 2
 
7.7%
H 1
 
3.8%
O 1
 
3.8%
J 1
 
3.8%
C 1
 
3.8%
Other values (3) 3
11.5%
Lowercase Letter
ValueCountFrequency (%)
o 5
22.7%
e 4
18.2%
r 3
13.6%
l 3
13.6%
i 2
 
9.1%
c 2
 
9.1%
p 2
 
9.1%
g 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 16
76.2%
. 3
 
14.3%
/ 2
 
9.5%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
70.9%
Common 58
 
15.9%
Latin 48
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 11
 
4.3%
동 10
 
3.9%
차 10
 
3.9%
부 9
 
3.5%
스 9
 
3.5%
품 9
 
3.5%
용 8
 
3.1%
라 8
 
3.1%
지 5
 
1.9%
이 5
 
1.9%
Other values (116) 174
67.4%
Latin
ValueCountFrequency (%)
S 5
 
10.4%
o 5
 
10.4%
e 4
 
8.3%
E 4
 
8.3%
T 3
 
6.2%
I 3
 
6.2%
r 3
 
6.2%
l 3
 
6.2%
i 2
 
4.2%
N 2
 
4.2%
Other values (11) 14
29.2%
Common
ValueCountFrequency (%)
31
53.4%
, 16
27.6%
. 3
 
5.2%
/ 2
 
3.4%
( 2
 
3.4%
- 2
 
3.4%
) 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
70.9%
ASCII 106
29.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
29.2%
, 16
15.1%
S 5
 
4.7%
o 5
 
4.7%
e 4
 
3.8%
E 4
 
3.8%
T 3
 
2.8%
I 3
 
2.8%
. 3
 
2.8%
r 3
 
2.8%
Other values (18) 29
27.4%
Hangul
ValueCountFrequency (%)
자 11
 
4.3%
동 10
 
3.9%
차 10
 
3.9%
부 9
 
3.5%
스 9
 
3.5%
품 9
 
3.5%
용 8
 
3.1%
라 8
 
3.1%
지 5
 
1.9%
이 5
 
1.9%
Other values (116) 174
67.4%

Interactions

2023-12-11T08:55:40.222517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:55:40.025352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:55:40.601777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:55:40.126203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:55:44.153280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분회사명도로명주소전화번호종업원수생산품
순번1.0000.9291.0001.0001.0000.5041.000
구분0.9291.0001.0001.0001.0000.3351.000
회사명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0000.994
전화번호1.0001.0001.0001.0001.0001.0001.000
종업원수0.5040.3351.0001.0001.0001.0000.000
생산품1.0001.0001.0000.9941.0000.0001.000
2023-12-11T08:55:44.272826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수구분
순번1.000-0.7700.589
종업원수-0.7701.0000.269
구분0.5890.2691.000

Missing values

2023-12-11T08:55:40.738864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:55:40.916383image/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

순번구분회사명도로명주소전화번호종업원수생산품
01대기업넥센타이어(주)경상남도 양산시 충렬로 355055-370-51144149타이어
12대기업(주)화승알앤에이경상남도 양산시 충렬로 61055-370-33311208자동차용고무부품및산업용고무
23대기업동아타이어공업(주)경상남도 양산시 유산공단11길 11055-389-0011820타이어, 튜브
34대기업(주)흥아경상남도 양산시 어실로 77055-371-3700587타이어
45대기업(주)디티알경상남도 양산시 산막공단북11길 103055-758-5166529자동차용 소음 및 방진부품
56대기업쿠쿠전자(주)경상남도 양산시 충렬로 143055-380-0700375전기압력밥솥
67대기업에스텍(주)경상남도 양산시 유산공단9길 22055-370-2200329스피커
78대기업(주)화승소재경상남도 양산시 유산공단2길 11055-780-3400300연고무
89소기업송우산업(주)경상남도 양산시 어곡공단3길 14-2055-367-5005100자동차부품용 고무호스
910중견기업(주)코렌스경상남도 양산시 어곡공단로 116055-371-6700591자동차부품(egr-cooler/oil-cooler/pipe)
순번구분회사명도로명주소전화번호종업원수생산품
2728중기업(주)대성사경상남도 양산시 대동로 53055-372-2007138자동차부품
2829중기업(주)동희정공경상남도 양산시 소주공단1길 41070-7093-6420129자동차부품(자동차 플라스틱 연료탱크)
2930중기업(주)케이프경상남도 양산시 상북면 양산대로 1303055-370-1234128대형선박 엔진용 실린더라이너
3031중기업(주)한성전장경상남도 양산시 상북면 소토로 23055-375-1197126전동식 조향장치 부분품
3132중기업한국제이에스티(주)경상남도 양산시 어곡공단1길 56055-371-5500120커넥터
3233중기업고려강선(주)경상남도 양산시 유산공단7길 15055-380-3307116스틸코드
3334중기업(주)파멕스경상남도 양산시 웅비공단길 118055-388-8490112자동제어장비, 주유기, 티켓발매기
3435중기업(주)대호피앤씨경상남도 양산시 산막공단북4길 13055-388-4001107냉간압조용선재
3536중기업조광아이엘아이(주)경상남도 양산시 산막공단북10길 37055-360-0200104밸브
3637중소기업디씨엠(주)경상남도 양산시 웅상농공단지길 55055-366-9991165라미네이팅강판