Overview

Dataset statistics

Number of variables6
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory51.8 B

Variable types

Categorical1
Text4
Numeric1

Dataset

Description경상남도 창녕군 산업단지 입주업체 현황에 대한 데이터를 포함하고 있습니다.(산업단지명, 회사명, 분양면적, 위치, 업종, 생산품)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15054909

Alerts

분양면적(㎡) is highly overall correlated with 산업단지명High correlation
산업단지명 is highly overall correlated with 분양면적(㎡)High correlation
산업단지명 is highly imbalanced (72.6%)Imbalance
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:26:45.520459
Analysis finished2023-12-10 23:26:46.252734
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산업단지명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
대합일반산업단지
43 
억만일반산업단지
 
2
하리일반산업단지
 
1
넥센일반산업단지
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique2 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
대합일반산업단지 43
91.5%
억만일반산업단지 2
 
4.3%
하리일반산업단지 1
 
2.1%
넥센일반산업단지 1
 
2.1%

Length

2023-12-11T08:26:46.316957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:26:46.405381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대합일반산업단지 43
91.5%
억만일반산업단지 2
 
4.3%
하리일반산업단지 1
 
2.1%
넥센일반산업단지 1
 
2.1%

회사명
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T08:26:46.628565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.1276596
Min length3

Characters and Unicode

Total characters288
Distinct characters108
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st row(주)세아베스틸
2nd row(주)대일금속자원
3rd row(주)다 우
4th row㈜시코텍
5th row㈜금경라이팅
ValueCountFrequency (%)
㈜화인베스틸 2
 
4.1%
㈜대산led전기조명 1
 
2.0%
㈜코아스틸 1
 
2.0%
주)티앤비우드 1
 
2.0%
대합이엔씨 1
 
2.0%
광희테크 1
 
2.0%
진성산업 1
 
2.0%
주)대림에프엔티 1
 
2.0%
윈스타 1
 
2.0%
패브릭 1
 
2.0%
Other values (38) 38
77.6%
2023-12-11T08:26:46.991522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 19
 
6.6%
주 15
 
5.2%
) 15
 
5.2%
( 15
 
5.2%
스 9
 
3.1%
우 9
 
3.1%
대 8
 
2.8%
이 7
 
2.4%
금 7
 
2.4%
속 6
 
2.1%
Other values (98) 178
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 230
79.9%
Other Symbol 19
 
6.6%
Close Punctuation 15
 
5.2%
Open Punctuation 15
 
5.2%
Uppercase Letter 6
 
2.1%
Space Separator 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 15
 
6.5%
스 9
 
3.9%
우 9
 
3.9%
대 8
 
3.5%
이 7
 
3.0%
금 7
 
3.0%
속 6
 
2.6%
틸 5
 
2.2%
엠 5
 
2.2%
크 5
 
2.2%
Other values (89) 154
67.0%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
L 1
16.7%
D 1
16.7%
P 1
16.7%
S 1
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 249
86.5%
Common 33
 
11.5%
Latin 6
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 19
 
7.6%
주 15
 
6.0%
스 9
 
3.6%
우 9
 
3.6%
대 8
 
3.2%
이 7
 
2.8%
금 7
 
2.8%
속 6
 
2.4%
틸 5
 
2.0%
엠 5
 
2.0%
Other values (90) 159
63.9%
Latin
ValueCountFrequency (%)
E 2
33.3%
L 1
16.7%
D 1
16.7%
P 1
16.7%
S 1
16.7%
Common
ValueCountFrequency (%)
) 15
45.5%
( 15
45.5%
3
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 230
79.9%
ASCII 39
 
13.5%
None 19
 
6.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 19
100.0%
Hangul
ValueCountFrequency (%)
주 15
 
6.5%
스 9
 
3.9%
우 9
 
3.9%
대 8
 
3.5%
이 7
 
3.0%
금 7
 
3.0%
속 6
 
2.6%
틸 5
 
2.2%
엠 5
 
2.2%
크 5
 
2.2%
Other values (89) 154
67.0%
ASCII
ValueCountFrequency (%)
) 15
38.5%
( 15
38.5%
3
 
7.7%
E 2
 
5.1%
L 1
 
2.6%
D 1
 
2.6%
P 1
 
2.6%
S 1
 
2.6%

분양면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26677.317
Minimum2004
Maximum411035.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-11T08:26:47.123094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2004
5-th percentile2532.9
Q14247.1
median10002
Q314726.25
95-th percentile122711.3
Maximum411035.6
Range409031.6
Interquartile range (IQR)10479.15

Descriptive statistics

Standard deviation67305.6
Coefficient of variation (CV)2.5229523
Kurtosis24.524077
Mean26677.317
Median Absolute Deviation (MAD)5674.8
Skewness4.742962
Sum1253833.9
Variance4.5300437 × 109
MonotonicityNot monotonic
2023-12-11T08:26:47.251582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
3311.0 2
 
4.3%
198480.0 1
 
2.1%
3970.0 1
 
2.1%
2404.0 1
 
2.1%
3487.0 1
 
2.1%
3487.1 1
 
2.1%
11054.9 1
 
2.1%
2648.0 1
 
2.1%
2502.0 1
 
2.1%
4877.0 1
 
2.1%
Other values (36) 36
76.6%
ValueCountFrequency (%)
2004.0 1
2.1%
2404.0 1
2.1%
2502.0 1
2.1%
2605.0 1
2.1%
2648.0 1
2.1%
3311.0 2
4.3%
3359.3 1
2.1%
3487.0 1
2.1%
3487.1 1
2.1%
3970.0 1
2.1%
ValueCountFrequency (%)
411035.6 1
2.1%
198480.0 1
2.1%
155108.0 1
2.1%
47119.0 1
2.1%
39112.5 1
2.1%
26378.0 1
2.1%
25234.3 1
2.1%
22466.0 1
2.1%
21610.0 1
2.1%
21350.0 1
2.1%

위치
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T08:26:47.484278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length20.702128
Min length20

Characters and Unicode

Total characters973
Distinct characters36
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

Unique47 ?
Unique (%)100.0%

Sample

1st row경상남도 창녕군 대합면 합리 1338
2nd row경상남도 창녕군 대합면 합리 1330
3rd row경상남도 창녕군 대합면 합리 1344
4th row경상남도 창녕군 대합면 합리 1332
5th row경상남도 창녕군 대합면 합리 1342
ValueCountFrequency (%)
경상남도 47
20.0%
창녕군 47
20.0%
대합면 44
18.7%
합리 43
18.3%
고암면 2
 
0.9%
1421-1 1
 
0.4%
1414 1
 
0.4%
1414-1 1
 
0.4%
1390 1
 
0.4%
1413-1 1
 
0.4%
Other values (47) 47
20.0%
2023-12-11T08:26:47.903780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
19.3%
합 87
 
8.9%
1 76
 
7.8%
창 49
 
5.0%
녕 48
 
4.9%
군 47
 
4.8%
상 47
 
4.8%
경 47
 
4.8%
도 47
 
4.8%
남 47
 
4.8%
Other values (26) 290
29.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 572
58.8%
Decimal Number 200
 
20.6%
Space Separator 188
 
19.3%
Dash Punctuation 13
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
합 87
15.2%
창 49
8.6%
녕 48
8.4%
군 47
8.2%
상 47
8.2%
경 47
8.2%
도 47
8.2%
남 47
8.2%
면 46
8.0%
대 45
7.9%
Other values (14) 62
10.8%
Decimal Number
ValueCountFrequency (%)
1 76
38.0%
3 33
16.5%
4 30
 
15.0%
2 23
 
11.5%
0 11
 
5.5%
9 9
 
4.5%
8 7
 
3.5%
5 5
 
2.5%
6 4
 
2.0%
7 2
 
1.0%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 572
58.8%
Common 401
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
합 87
15.2%
창 49
8.6%
녕 48
8.4%
군 47
8.2%
상 47
8.2%
경 47
8.2%
도 47
8.2%
남 47
8.2%
면 46
8.0%
대 45
7.9%
Other values (14) 62
10.8%
Common
ValueCountFrequency (%)
188
46.9%
1 76
19.0%
3 33
 
8.2%
4 30
 
7.5%
2 23
 
5.7%
- 13
 
3.2%
0 11
 
2.7%
9 9
 
2.2%
8 7
 
1.7%
5 5
 
1.2%
Other values (2) 6
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 572
58.8%
ASCII 401
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
46.9%
1 76
19.0%
3 33
 
8.2%
4 30
 
7.5%
2 23
 
5.7%
- 13
 
3.2%
0 11
 
2.7%
9 9
 
2.2%
8 7
 
1.7%
5 5
 
1.2%
Other values (2) 6
 
1.5%
Hangul
ValueCountFrequency (%)
합 87
15.2%
창 49
8.6%
녕 48
8.4%
군 47
8.2%
상 47
8.2%
경 47
8.2%
도 47
8.2%
남 47
8.2%
면 46
8.0%
대 45
7.9%
Other values (14) 62
10.8%

업종
Text

Distinct35
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T08:26:48.150405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length13.914894
Min length7

Characters and Unicode

Total characters654
Distinct characters94
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

Unique26 ?
Unique (%)55.3%

Sample

1st row강열간 압연 및 압출제품 제조업, 제강업
2nd row볼베어링및롤러베어링 제조업
3rd row알루미늄 제련,정련 및 합금 제조업
4th row알루미늄 제련,정련 및 합금 제조업
5th row알루미늄주물 주조업
ValueCountFrequency (%)
제조업 34
 
20.4%
및 16
 
9.6%
금속 6
 
3.6%
부품 5
 
3.0%
구조재 4
 
2.4%
자동차 4
 
2.4%
배전반 3
 
1.8%
그 3
 
1.8%
주조업 3
 
1.8%
합금 3
 
1.8%
Other values (61) 86
51.5%
2023-12-11T08:26:48.639956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
18.3%
조 59
 
9.0%
제 55
 
8.4%
업 48
 
7.3%
품 21
 
3.2%
및 17
 
2.6%
차 17
 
2.6%
자 14
 
2.1%
동 14
 
2.1%
금 14
 
2.1%
Other values (84) 275
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 524
80.1%
Space Separator 120
 
18.3%
Other Punctuation 8
 
1.2%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 59
 
11.3%
제 55
 
10.5%
업 48
 
9.2%
품 21
 
4.0%
및 17
 
3.2%
차 17
 
3.2%
자 14
 
2.7%
동 14
 
2.7%
금 14
 
2.7%
기 13
 
2.5%
Other values (81) 252
48.1%
Space Separator
ValueCountFrequency (%)
120
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 524
80.1%
Common 130
 
19.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 59
 
11.3%
제 55
 
10.5%
업 48
 
9.2%
품 21
 
4.0%
및 17
 
3.2%
차 17
 
3.2%
자 14
 
2.7%
동 14
 
2.7%
금 14
 
2.7%
기 13
 
2.5%
Other values (81) 252
48.1%
Common
ValueCountFrequency (%)
120
92.3%
, 8
 
6.2%
1 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 524
80.1%
ASCII 130
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
92.3%
, 8
 
6.2%
1 2
 
1.5%
Hangul
ValueCountFrequency (%)
조 59
 
11.3%
제 55
 
10.5%
업 48
 
9.2%
품 21
 
4.0%
및 17
 
3.2%
차 17
 
3.2%
자 14
 
2.7%
동 14
 
2.7%
금 14
 
2.7%
기 13
 
2.5%
Other values (81) 252
48.1%

생산품
Text

Distinct40
Distinct (%)85.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-11T08:26:48.925147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.2340426
Min length3

Characters and Unicode

Total characters340
Distinct characters137
Distinct categories6 ?
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 (%)78.7%

Sample

1st row특수강봉
2nd row베어링
3rd row알루미늄 튜브
4th row산업용로 및 알루미늄 합금
5th rowLED조명기구
ValueCountFrequency (%)
자동차 9
 
10.0%
부품 7
 
7.8%
부품류 5
 
5.6%
배전반 3
 
3.3%
및 3
 
3.3%
알루미늄 2
 
2.2%
로봇 1
 
1.1%
산업용 1
 
1.1%
자동화 1
 
1.1%
기계 1
 
1.1%
Other values (57) 57
63.3%
2023-12-11T08:26:49.386648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43
 
12.6%
품 16
 
4.7%
부 14
 
4.1%
차 12
 
3.5%
자 11
 
3.2%
동 11
 
3.2%
기 6
 
1.8%
류 6
 
1.8%
이 5
 
1.5%
, 5
 
1.5%
Other values (127) 211
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
77.4%
Space Separator 43
 
12.6%
Lowercase Letter 15
 
4.4%
Uppercase Letter 13
 
3.8%
Other Punctuation 5
 
1.5%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 16
 
6.1%
부 14
 
5.3%
차 12
 
4.6%
자 11
 
4.2%
동 11
 
4.2%
기 6
 
2.3%
류 6
 
2.3%
이 5
 
1.9%
금 5
 
1.9%
공 5
 
1.9%
Other values (103) 172
65.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
13.3%
e 2
13.3%
s 2
13.3%
l 1
6.7%
b 1
6.7%
m 1
6.7%
t 1
6.7%
k 1
6.7%
c 1
6.7%
o 1
6.7%
Other values (2) 2
13.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
D 2
15.4%
E 2
15.4%
L 2
15.4%
H 1
7.7%
S 1
7.7%
P 1
7.7%
B 1
7.7%
I 1
7.7%
Space Separator
ValueCountFrequency (%)
43
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
77.4%
Common 49
 
14.4%
Latin 28
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 16
 
6.1%
부 14
 
5.3%
차 12
 
4.6%
자 11
 
4.2%
동 11
 
4.2%
기 6
 
2.3%
류 6
 
2.3%
이 5
 
1.9%
금 5
 
1.9%
공 5
 
1.9%
Other values (103) 172
65.4%
Latin
ValueCountFrequency (%)
a 2
 
7.1%
e 2
 
7.1%
s 2
 
7.1%
C 2
 
7.1%
D 2
 
7.1%
E 2
 
7.1%
L 2
 
7.1%
H 1
 
3.6%
S 1
 
3.6%
P 1
 
3.6%
Other values (11) 11
39.3%
Common
ValueCountFrequency (%)
43
87.8%
, 5
 
10.2%
- 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
77.4%
ASCII 77
 
22.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43
55.8%
, 5
 
6.5%
a 2
 
2.6%
e 2
 
2.6%
s 2
 
2.6%
C 2
 
2.6%
D 2
 
2.6%
E 2
 
2.6%
L 2
 
2.6%
H 1
 
1.3%
Other values (14) 14
 
18.2%
Hangul
ValueCountFrequency (%)
품 16
 
6.1%
부 14
 
5.3%
차 12
 
4.6%
자 11
 
4.2%
동 11
 
4.2%
기 6
 
2.3%
류 6
 
2.3%
이 5
 
1.9%
금 5
 
1.9%
공 5
 
1.9%
Other values (103) 172
65.4%

Interactions

2023-12-11T08:26:45.957112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:26:49.491558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
산업단지명회사명분양면적(㎡)위치업종생산품
산업단지명1.0000.0000.8281.0001.0001.000
회사명0.0001.0000.0001.0000.9850.980
분양면적(㎡)0.8280.0001.0001.0000.9391.000
위치1.0001.0001.0001.0001.0001.000
업종1.0000.9850.9391.0001.0000.972
생산품1.0000.9801.0001.0000.9721.000
2023-12-11T08:26:49.593927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분양면적(㎡)산업단지명
분양면적(㎡)1.0000.788
산업단지명0.7881.000

Missing values

2023-12-11T08:26:46.089350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:26:46.204858image/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

산업단지명회사명분양면적(㎡)위치업종생산품
0대합일반산업단지(주)세아베스틸198480.0경상남도 창녕군 대합면 합리 1338강열간 압연 및 압출제품 제조업, 제강업특수강봉
1대합일반산업단지(주)대일금속자원4711.0경상남도 창녕군 대합면 합리 1330볼베어링및롤러베어링 제조업베어링
2대합일반산업단지(주)다 우18193.0경상남도 창녕군 대합면 합리 1344알루미늄 제련,정련 및 합금 제조업알루미늄 튜브
3대합일반산업단지㈜시코텍11306.0경상남도 창녕군 대합면 합리 1332알루미늄 제련,정련 및 합금 제조업산업용로 및 알루미늄 합금
4대합일반산업단지㈜금경라이팅26378.0경상남도 창녕군 대합면 합리 1342알루미늄주물 주조업LED조명기구
5대합일반산업단지현대금속(주)6610.0경상남도 창녕군 대합면 합리 1331알루미늄 제련,정련 및 합금 제조업알루미늄인고트
6대합일반산업단지㈜엘엠에이티22466.0경상남도 창녕군 대합면 합리 1333알루미늄주물 주조업자동차 부품
7대합일반산업단지㈜영화47119.0경상남도 창녕군 대합면 합리 1383기타구조용금속제품 제조업샌드위치 판넬
8대합일반산업단지㈜센트랄씨엠에스21350.0경상남도 창녕군 대합면 합리 1388기타자동차부품제조업자동차 터보차져
9대합일반산업단지신화열처리21610.0경상남도 창녕군 대합면 합리 1392자동차용 동력전달장치제조자동차 부품
산업단지명회사명분양면적(㎡)위치업종생산품
37대합일반산업단지(주)현대종합철강3359.3경상남도 창녕군 대합면 합리 1412육상 금속 골조 구조재 제조업H빔, C형강
38대합일반산업단지월드엔지니어링(주)7071.2경상남도 창녕군 대합면 합리 1421-1육상 금속 골조 구조재 제조업유원지 놀이기구
39대합일반산업단지(주)진명금속8265.8경상남도 창녕군 대합면 합리 1421육상 금속 골조 구조재 제조업철구조물
40대합일반산업단지평안테크4327.2경상남도 창녕군 대합면 합리 1413주형 및 금형 제조업금속금형제품
41대합일반산업단지케이유엠세현(주)6537.2경상남도 창녕군 대합면 합리 1420그외 자동차용 신품부품 제조업자동차용 밴드 케이블
42대합일반산업단지(주)우영공업8805.3경상남도 창녕군 대합면 합리 1420-1자동차 차체용 신품부품 제조업자동차 내장재
43억만일반산업단지㈜코아스틸25234.3경상남도 창녕군 고암면 억만리 16001차철강제조업전기강판
44억만일반산업단지㈜화인베스틸39112.5경상남도 창녕군 고암면 하리청학로 220-381차철강제조업slab절단가공
45하리일반산업단지㈜화인베스틸155108.0경상남도 창녕군 창녕읍 창밀로 259-33열간압연 압출 제품제조업앵글, I-Beam 등
46넥센일반산업단지넥센타이어㈜411035.6경상남도 창녕군 대합면 대동월포로 291타이어 및 튜브 제조업타이어