Overview

Dataset statistics

Number of variables13
Number of observations141
Missing cells136
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.0 KiB
Average record size in memory108.9 B

Variable types

Numeric4
Text7
Categorical2

Dataset

Description경상남도 거제시 공장등록현황(회사명, 단지명, 설립구분, 전화번호, 생산품, 우편번호, 공장주소, 업종명, 위도, 경도, 기준일자)에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://www.data.go.kr/data/15034978/fileData.do

Alerts

기준일자 has constant value ""Constant
공장우편번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 공장우편번호High correlation
경도 is highly overall correlated with 공장우편번호High correlation
설립구분 is highly imbalanced (61.9%)Imbalance
단지명 has 131 (92.9%) missing valuesMissing
전화번호 has 3 (2.1%) missing valuesMissing
업종명 has 2 (1.4%) missing valuesMissing
순번 has unique valuesUnique
회사명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:01:16.224830
Analysis finished2023-12-12 17:01:18.930601
Duration2.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:01:18.999843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q136
median71
Q3106
95-th percentile134
Maximum141
Range140
Interquartile range (IQR)70

Descriptive statistics

Standard deviation40.847277
Coefficient of variation (CV)0.57531375
Kurtosis-1.2
Mean71
Median Absolute Deviation (MAD)35
Skewness0
Sum10011
Variance1668.5
MonotonicityStrictly increasing
2023-12-13T02:01:19.167349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
98 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
99 1
 
0.7%
90 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%

회사명
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:01:19.482874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.3758865
Min length2

Characters and Unicode

Total characters1181
Distinct characters203
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

Unique141 ?
Unique (%)100.0%

Sample

1st row(주)거제전통메주
2nd row(주)건화
3rd row(주)광성산업
4th row(주)금하네이벌텍
5th row(주)금화
ValueCountFrequency (%)
주식회사 15
 
8.4%
제2공장 3
 
1.7%
삼삼해물씨푸드 3
 
1.7%
신화기업(주 2
 
1.1%
주)삼녹 2
 
1.1%
광신기계산업(주 2
 
1.1%
2공장 2
 
1.1%
삼녹eng 2
 
1.1%
건화공업(주 2
 
1.1%
제1공장 2
 
1.1%
Other values (140) 143
80.3%
2023-12-13T02:01:19.948634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 106
 
9.0%
( 83
 
7.0%
) 83
 
7.0%
업 37
 
3.1%
37
 
3.1%
공 35
 
3.0%
식 28
 
2.4%
제 28
 
2.4%
산 27
 
2.3%
사 26
 
2.2%
Other values (193) 691
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 950
80.4%
Open Punctuation 83
 
7.0%
Close Punctuation 83
 
7.0%
Space Separator 37
 
3.1%
Uppercase Letter 14
 
1.2%
Decimal Number 13
 
1.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 106
 
11.2%
업 37
 
3.9%
공 35
 
3.7%
식 28
 
2.9%
제 28
 
2.9%
산 27
 
2.8%
사 26
 
2.7%
장 24
 
2.5%
회 23
 
2.4%
기 18
 
1.9%
Other values (177) 598
62.9%
Uppercase Letter
ValueCountFrequency (%)
G 3
21.4%
N 2
14.3%
E 2
14.3%
F 2
14.3%
A 1
 
7.1%
B 1
 
7.1%
S 1
 
7.1%
M 1
 
7.1%
P 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 7
53.8%
1 4
30.8%
3 2
 
15.4%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 950
80.4%
Common 217
 
18.4%
Latin 14
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 106
 
11.2%
업 37
 
3.9%
공 35
 
3.7%
식 28
 
2.9%
제 28
 
2.9%
산 27
 
2.8%
사 26
 
2.7%
장 24
 
2.5%
회 23
 
2.4%
기 18
 
1.9%
Other values (177) 598
62.9%
Latin
ValueCountFrequency (%)
G 3
21.4%
N 2
14.3%
E 2
14.3%
F 2
14.3%
A 1
 
7.1%
B 1
 
7.1%
S 1
 
7.1%
M 1
 
7.1%
P 1
 
7.1%
Common
ValueCountFrequency (%)
( 83
38.2%
) 83
38.2%
37
17.1%
2 7
 
3.2%
1 4
 
1.8%
3 2
 
0.9%
& 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 950
80.4%
ASCII 231
 
19.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 106
 
11.2%
업 37
 
3.9%
공 35
 
3.7%
식 28
 
2.9%
제 28
 
2.9%
산 27
 
2.8%
사 26
 
2.7%
장 24
 
2.5%
회 23
 
2.4%
기 18
 
1.9%
Other values (177) 598
62.9%
ASCII
ValueCountFrequency (%)
( 83
35.9%
) 83
35.9%
37
16.0%
2 7
 
3.0%
1 4
 
1.7%
G 3
 
1.3%
N 2
 
0.9%
E 2
 
0.9%
F 2
 
0.9%
3 2
 
0.9%
Other values (6) 6
 
2.6%

단지명
Text

MISSING 

Distinct5
Distinct (%)50.0%
Missing131
Missing (%)92.9%
Memory size1.2 KiB
2023-12-13T02:01:20.156664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8
Min length8

Characters and Unicode

Total characters98
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)40.0%

Sample

1st row거제모사일반산업단지
2nd row거제오비일반산업단지
3rd row거제오비일반산업단지
4th row거제오비일반산업단지
5th row거제오비일반산업단지
ValueCountFrequency (%)
거제오비일반산업단지 6
60.0%
거제모사일반산업단지 1
 
10.0%
옥포국가산업단지 1
 
10.0%
죽도국가산업단지 1
 
10.0%
거제한내조선특화농공단지 1
 
10.0%
2023-12-13T02:01:20.503342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 10
10.2%
단 10
10.2%
산 9
9.2%
업 9
9.2%
제 8
8.2%
거 8
8.2%
반 7
 
7.1%
일 7
 
7.1%
비 6
 
6.1%
오 6
 
6.1%
Other values (16) 18
18.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 10
10.2%
단 10
10.2%
산 9
9.2%
업 9
9.2%
제 8
8.2%
거 8
8.2%
반 7
 
7.1%
일 7
 
7.1%
비 6
 
6.1%
오 6
 
6.1%
Other values (16) 18
18.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 10
10.2%
단 10
10.2%
산 9
9.2%
업 9
9.2%
제 8
8.2%
거 8
8.2%
반 7
 
7.1%
일 7
 
7.1%
비 6
 
6.1%
오 6
 
6.1%
Other values (16) 18
18.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 98
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 10
10.2%
단 10
10.2%
산 9
9.2%
업 9
9.2%
제 8
8.2%
거 8
8.2%
반 7
 
7.1%
일 7
 
7.1%
비 6
 
6.1%
오 6
 
6.1%
Other values (16) 18
18.4%

설립구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일반
118 
창업
13 
일반산업단지
 
7
국가산업단지
 
2
농공단지
 
1

Length

Max length6
Median length2
Mean length2.2695035
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row일반
2nd row일반산업단지
3rd row일반
4th row일반
5th row창업

Common Values

ValueCountFrequency (%)
일반 118
83.7%
창업 13
 
9.2%
일반산업단지 7
 
5.0%
국가산업단지 2
 
1.4%
농공단지 1
 
0.7%

Length

2023-12-13T02:01:20.685915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:01:20.832405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 118
83.7%
창업 13
 
9.2%
일반산업단지 7
 
5.0%
국가산업단지 2
 
1.4%
농공단지 1
 
0.7%

전화번호
Text

MISSING 

Distinct121
Distinct (%)87.7%
Missing3
Missing (%)2.1%
Memory size1.2 KiB
2023-12-13T02:01:21.096684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.014493
Min length12

Characters and Unicode

Total characters1658
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

Unique105 ?
Unique (%)76.1%

Sample

1st row055-633-2270
2nd row055-639-5300
3rd row055-632-7333
4th row051-664-8200
5th row055-638-2974
ValueCountFrequency (%)
055-687-0039 3
 
2.2%
055-633-0034 2
 
1.4%
055-633-5104 2
 
1.4%
055-636-6121 2
 
1.4%
055-638-3227 2
 
1.4%
055-633-8200 2
 
1.4%
055-633-4960 2
 
1.4%
055-633-3340 2
 
1.4%
055-636-6434 2
 
1.4%
055-636-4733 2
 
1.4%
Other values (111) 117
84.8%
2023-12-13T02:01:21.530503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 343
20.7%
- 276
16.6%
0 245
14.8%
6 202
12.2%
3 202
12.2%
2 93
 
5.6%
4 70
 
4.2%
1 68
 
4.1%
7 60
 
3.6%
8 55
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1382
83.4%
Dash Punctuation 276
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 343
24.8%
0 245
17.7%
6 202
14.6%
3 202
14.6%
2 93
 
6.7%
4 70
 
5.1%
1 68
 
4.9%
7 60
 
4.3%
8 55
 
4.0%
9 44
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1658
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 343
20.7%
- 276
16.6%
0 245
14.8%
6 202
12.2%
3 202
12.2%
2 93
 
5.6%
4 70
 
4.2%
1 68
 
4.1%
7 60
 
3.6%
8 55
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 343
20.7%
- 276
16.6%
0 245
14.8%
6 202
12.2%
3 202
12.2%
2 93
 
5.6%
4 70
 
4.2%
1 68
 
4.1%
7 60
 
3.6%
8 55
 
3.3%

생산품
Text

Distinct103
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:01:21.741452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length22
Mean length8.3191489
Min length2

Characters and Unicode

Total characters1173
Distinct characters240
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)63.8%

Sample

1st row메주 두부 장류
2nd row선박구성부분품도장및기타피막처리업
3rd row금속공작물
4th row복합센서마스트 여객용 선박 등
5th row선박구성부분품(계측관)
ValueCountFrequency (%)
철의장품 14
 
5.9%
선박구성부분품 12
 
5.0%
등 9
 
3.8%
레미콘 5
 
2.1%
강선 5
 
2.1%
굴가공류 4
 
1.7%
및 4
 
1.7%
pipe 3
 
1.3%
액젖류 3
 
1.3%
유자차 3
 
1.3%
Other values (158) 176
73.9%
2023-12-13T02:01:22.422342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
8.3%
품 59
 
5.0%
선 47
 
4.0%
박 33
 
2.8%
구 31
 
2.6%
부 31
 
2.6%
조 30
 
2.6%
분 23
 
2.0%
성 22
 
1.9%
장 21
 
1.8%
Other values (230) 779
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 951
81.1%
Space Separator 97
 
8.3%
Uppercase Letter 93
 
7.9%
Close Punctuation 14
 
1.2%
Open Punctuation 14
 
1.2%
Other Punctuation 3
 
0.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 59
 
6.2%
선 47
 
4.9%
박 33
 
3.5%
구 31
 
3.3%
부 31
 
3.3%
조 30
 
3.2%
분 23
 
2.4%
성 22
 
2.3%
장 21
 
2.2%
의 18
 
1.9%
Other values (206) 636
66.9%
Uppercase Letter
ValueCountFrequency (%)
E 11
11.8%
P 11
11.8%
O 11
11.8%
L 8
8.6%
C 8
8.6%
S 8
8.6%
B 5
 
5.4%
I 4
 
4.3%
A 4
 
4.3%
K 4
 
4.3%
Other values (9) 19
20.4%
Space Separator
ValueCountFrequency (%)
97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
， 3
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 951
81.1%
Common 129
 
11.0%
Latin 93
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 59
 
6.2%
선 47
 
4.9%
박 33
 
3.5%
구 31
 
3.3%
부 31
 
3.3%
조 30
 
3.2%
분 23
 
2.4%
성 22
 
2.3%
장 21
 
2.2%
의 18
 
1.9%
Other values (206) 636
66.9%
Latin
ValueCountFrequency (%)
E 11
11.8%
P 11
11.8%
O 11
11.8%
L 8
8.6%
C 8
8.6%
S 8
8.6%
B 5
 
5.4%
I 4
 
4.3%
A 4
 
4.3%
K 4
 
4.3%
Other values (9) 19
20.4%
Common
ValueCountFrequency (%)
97
75.2%
) 14
 
10.9%
( 14
 
10.9%
， 3
 
2.3%
5 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 951
81.1%
ASCII 219
 
18.7%
None 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
44.3%
) 14
 
6.4%
( 14
 
6.4%
E 11
 
5.0%
P 11
 
5.0%
O 11
 
5.0%
L 8
 
3.7%
C 8
 
3.7%
S 8
 
3.7%
B 5
 
2.3%
Other values (13) 32
 
14.6%
Hangul
ValueCountFrequency (%)
품 59
 
6.2%
선 47
 
4.9%
박 33
 
3.5%
구 31
 
3.3%
부 31
 
3.3%
조 30
 
3.2%
분 23
 
2.4%
성 22
 
2.3%
장 21
 
2.2%
의 18
 
1.9%
Other values (206) 636
66.9%
None
ValueCountFrequency (%)
， 3
100.0%

공장우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53246.865
Minimum53201
Maximum53332
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:01:22.557447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53201
5-th percentile53202
Q153207
median53261
Q353278
95-th percentile53308
Maximum53332
Range131
Interquartile range (IQR)71

Descriptive statistics

Standard deviation39.572758
Coefficient of variation (CV)0.00074319413
Kurtosis-1.2245686
Mean53246.865
Median Absolute Deviation (MAD)40
Skewness0.24660197
Sum7507808
Variance1566.0031
MonotonicityNot monotonic
2023-12-13T02:01:22.697852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
53207 21
14.9%
53206 16
 
11.3%
53275 9
 
6.4%
53276 9
 
6.4%
53202 7
 
5.0%
53277 7
 
5.0%
53279 7
 
5.0%
53278 6
 
4.3%
53281 5
 
3.5%
53244 5
 
3.5%
Other values (24) 49
34.8%
ValueCountFrequency (%)
53201 1
 
0.7%
53202 7
 
5.0%
53203 1
 
0.7%
53204 5
 
3.5%
53205 4
 
2.8%
53206 16
11.3%
53207 21
14.9%
53208 2
 
1.4%
53210 2
 
1.4%
53211 1
 
0.7%
ValueCountFrequency (%)
53332 1
 
0.7%
53331 4
2.8%
53330 1
 
0.7%
53329 1
 
0.7%
53308 1
 
0.7%
53302 1
 
0.7%
53286 1
 
0.7%
53285 3
2.1%
53284 2
1.4%
53283 3
2.1%

공장대표주소(도로명)
Text

Distinct136
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:01:23.080074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length46
Mean length29.326241
Min length18

Characters and Unicode

Total characters4135
Distinct characters168
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

Unique131 ?
Unique (%)92.9%

Sample

1st row경상남도 거제시 동부면 삼거림1길 20 (총 2 필지) 외 1필지
2nd row경상남도 거제시 연초면 연하해안로 841-54 (연초면)
3rd row경상남도 거제시 연초면 소오비길 11-10
4th row경상남도 거제시 하청면 실전해안길 78 (실천카페리터미널)
5th row경상남도 거제시 사등면 거제대로 6025-17 (㈜정화) 외 2필지
ValueCountFrequency (%)
경상남도 141
 
15.2%
거제시 141
 
15.2%
외 50
 
5.4%
연초면 46
 
4.9%
사등면 39
 
4.2%
연하해안로 27
 
2.9%
1필지 24
 
2.6%
둔덕면 14
 
1.5%
필지 13
 
1.4%
거제대로 13
 
1.4%
Other values (272) 422
45.4%
2023-12-13T02:01:23.665196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
789
 
19.1%
거 176
 
4.3%
제 176
 
4.3%
남 147
 
3.6%
상 143
 
3.5%
1 143
 
3.5%
도 142
 
3.4%
경 141
 
3.4%
시 141
 
3.4%
면 138
 
3.3%
Other values (158) 1999
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2445
59.1%
Space Separator 789
 
19.1%
Decimal Number 638
 
15.4%
Open Punctuation 91
 
2.2%
Close Punctuation 91
 
2.2%
Dash Punctuation 65
 
1.6%
Other Punctuation 6
 
0.1%
Other Symbol 6
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 176
 
7.2%
제 176
 
7.2%
남 147
 
6.0%
상 143
 
5.8%
도 142
 
5.8%
경 141
 
5.8%
시 141
 
5.8%
면 138
 
5.6%
로 93
 
3.8%
지 76
 
3.1%
Other values (138) 1072
43.8%
Decimal Number
ValueCountFrequency (%)
1 143
22.4%
2 88
13.8%
3 85
13.3%
4 66
10.3%
5 65
10.2%
0 52
 
8.2%
7 45
 
7.1%
9 37
 
5.8%
8 30
 
4.7%
6 27
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
G 1
25.0%
M 1
25.0%
P 1
25.0%
Space Separator
ValueCountFrequency (%)
789
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Other Punctuation
ValueCountFrequency (%)
: 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2451
59.3%
Common 1680
40.6%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 176
 
7.2%
제 176
 
7.2%
남 147
 
6.0%
상 143
 
5.8%
도 142
 
5.8%
경 141
 
5.8%
시 141
 
5.8%
면 138
 
5.6%
로 93
 
3.8%
지 76
 
3.1%
Other values (139) 1078
44.0%
Common
ValueCountFrequency (%)
789
47.0%
1 143
 
8.5%
( 91
 
5.4%
) 91
 
5.4%
2 88
 
5.2%
3 85
 
5.1%
4 66
 
3.9%
5 65
 
3.9%
- 65
 
3.9%
0 52
 
3.1%
Other values (5) 145
 
8.6%
Latin
ValueCountFrequency (%)
A 1
25.0%
G 1
25.0%
M 1
25.0%
P 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2445
59.1%
ASCII 1684
40.7%
None 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
789
46.9%
1 143
 
8.5%
( 91
 
5.4%
) 91
 
5.4%
2 88
 
5.2%
3 85
 
5.0%
4 66
 
3.9%
5 65
 
3.9%
- 65
 
3.9%
0 52
 
3.1%
Other values (9) 149
 
8.8%
Hangul
ValueCountFrequency (%)
거 176
 
7.2%
제 176
 
7.2%
남 147
 
6.0%
상 143
 
5.8%
도 142
 
5.8%
경 141
 
5.8%
시 141
 
5.8%
면 138
 
5.6%
로 93
 
3.8%
지 76
 
3.1%
Other values (138) 1072
43.8%
None
ValueCountFrequency (%)
㈜ 6
100.0%

공장대표주소(지번)
Text

Distinct138
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T02:01:24.130481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length24.382979
Min length16

Characters and Unicode

Total characters3438
Distinct characters125
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

Unique135 ?
Unique (%)95.7%

Sample

1st row경상남도 거제시 동부면 부춘리 781 외 1필지
2nd row경상남도 거제시 연초면 한내리 777
3rd row경상남도 거제시 연초면 오비리 1164-9
4th row경상남도 거제시 하청면 실전리 1052-1 실천카페리터미널
5th row경상남도 거제시 사등면 청곡리 204 외 2필지
ValueCountFrequency (%)
경상남도 141
17.1%
거제시 140
17.0%
외 48
 
5.8%
연초면 42
 
5.1%
사등면 37
 
4.5%
1필지 24
 
2.9%
오비리 23
 
2.8%
한내리 16
 
1.9%
둔덕면 14
 
1.7%
사등리 12
 
1.5%
Other values (213) 328
39.8%
2023-12-13T02:01:24.712843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
684
19.9%
1 161
 
4.7%
거 151
 
4.4%
제 151
 
4.4%
상 145
 
4.2%
시 142
 
4.1%
경 141
 
4.1%
남 141
 
4.1%
도 141
 
4.1%
리 134
 
3.9%
Other values (115) 1447
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2049
59.6%
Space Separator 684
 
19.9%
Decimal Number 591
 
17.2%
Dash Punctuation 83
 
2.4%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%
Other Punctuation 6
 
0.2%
Uppercase Letter 3
 
0.1%
Other Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 151
 
7.4%
제 151
 
7.4%
상 145
 
7.1%
시 142
 
6.9%
경 141
 
6.9%
남 141
 
6.9%
도 141
 
6.9%
리 134
 
6.5%
면 131
 
6.4%
지 60
 
2.9%
Other values (96) 712
34.7%
Decimal Number
ValueCountFrequency (%)
1 161
27.2%
2 73
12.4%
0 62
 
10.5%
7 58
 
9.8%
5 46
 
7.8%
4 46
 
7.8%
3 43
 
7.3%
6 38
 
6.4%
9 33
 
5.6%
8 31
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
M 1
33.3%
P 1
33.3%
Space Separator
ValueCountFrequency (%)
684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
: 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2051
59.7%
Common 1384
40.3%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 151
 
7.4%
제 151
 
7.4%
상 145
 
7.1%
시 142
 
6.9%
경 141
 
6.9%
남 141
 
6.9%
도 141
 
6.9%
리 134
 
6.5%
면 131
 
6.4%
지 60
 
2.9%
Other values (97) 714
34.8%
Common
ValueCountFrequency (%)
684
49.4%
1 161
 
11.6%
- 83
 
6.0%
2 73
 
5.3%
0 62
 
4.5%
7 58
 
4.2%
5 46
 
3.3%
4 46
 
3.3%
3 43
 
3.1%
6 38
 
2.7%
Other values (5) 90
 
6.5%
Latin
ValueCountFrequency (%)
G 1
33.3%
M 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2049
59.6%
ASCII 1387
40.3%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
684
49.3%
1 161
 
11.6%
- 83
 
6.0%
2 73
 
5.3%
0 62
 
4.5%
7 58
 
4.2%
5 46
 
3.3%
4 46
 
3.3%
3 43
 
3.1%
6 38
 
2.7%
Other values (8) 93
 
6.7%
Hangul
ValueCountFrequency (%)
거 151
 
7.4%
제 151
 
7.4%
상 145
 
7.1%
시 142
 
6.9%
경 141
 
6.9%
남 141
 
6.9%
도 141
 
6.9%
리 134
 
6.5%
면 131
 
6.4%
지 60
 
2.9%
Other values (96) 712
34.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

업종명
Text

MISSING 

Distinct69
Distinct (%)49.6%
Missing2
Missing (%)1.4%
Memory size1.2 KiB
2023-12-13T02:01:25.053143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length16.94964
Min length5

Characters and Unicode

Total characters2356
Distinct characters139
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)33.1%

Sample

1st row장류 제조업 외 1 종
2nd row선박 구성 부분품 제조업 외 1 종
3rd row구조용 금속 판제품 및 공작물 제조업 외 5 종
4th row선박 구성 부분품 제조업 외 3 종
5th row선박 구성 부분품 제조업
ValueCountFrequency (%)
제조업 114
 
15.0%
외 59
 
7.7%
종 54
 
7.1%
및 49
 
6.4%
선박 40
 
5.2%
부분품 38
 
5.0%
구성 38
 
5.0%
1 27
 
3.5%
기타 25
 
3.3%
수산동물 21
 
2.8%
Other values (108) 297
39.0%
2023-12-13T02:01:25.557647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
26.4%
조 169
 
7.2%
업 142
 
6.0%
제 142
 
6.0%
품 76
 
3.2%
외 60
 
2.5%
구 56
 
2.4%
종 54
 
2.3%
및 50
 
2.1%
선 46
 
2.0%
Other values (129) 938
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1675
71.1%
Space Separator 623
 
26.4%
Decimal Number 56
 
2.4%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 169
 
10.1%
업 142
 
8.5%
제 142
 
8.5%
품 76
 
4.5%
외 60
 
3.6%
구 56
 
3.3%
종 54
 
3.2%
및 50
 
3.0%
선 46
 
2.7%
분 40
 
2.4%
Other values (119) 840
50.1%
Decimal Number
ValueCountFrequency (%)
1 29
51.8%
3 11
 
19.6%
2 9
 
16.1%
7 3
 
5.4%
5 2
 
3.6%
8 1
 
1.8%
6 1
 
1.8%
Space Separator
ValueCountFrequency (%)
623
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1675
71.1%
Common 681
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 169
 
10.1%
업 142
 
8.5%
제 142
 
8.5%
품 76
 
4.5%
외 60
 
3.6%
구 56
 
3.3%
종 54
 
3.2%
및 50
 
3.0%
선 46
 
2.7%
분 40
 
2.4%
Other values (119) 840
50.1%
Common
ValueCountFrequency (%)
623
91.5%
1 29
 
4.3%
3 11
 
1.6%
2 9
 
1.3%
7 3
 
0.4%
5 2
 
0.3%
) 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
( 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1671
70.9%
ASCII 681
28.9%
Compat Jamo 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
91.5%
1 29
 
4.3%
3 11
 
1.6%
2 9
 
1.3%
7 3
 
0.4%
5 2
 
0.3%
) 1
 
0.1%
8 1
 
0.1%
6 1
 
0.1%
( 1
 
0.1%
Hangul
ValueCountFrequency (%)
조 169
 
10.1%
업 142
 
8.5%
제 142
 
8.5%
품 76
 
4.5%
외 60
 
3.6%
구 56
 
3.4%
종 54
 
3.2%
및 50
 
3.0%
선 46
 
2.8%
분 40
 
2.4%
Other values (118) 836
50.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.901156
Minimum34.783775
Maximum34.999753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:01:25.743695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.783775
5-th percentile34.819914
Q134.877295
median34.908224
Q334.925652
95-th percentile34.963573
Maximum34.999753
Range0.21597759
Interquartile range (IQR)0.04835682

Descriptive statistics

Standard deviation0.041099957
Coefficient of variation (CV)0.0011776102
Kurtosis0.20088598
Mean34.901156
Median Absolute Deviation (MAD)0.01942587
Skewness-0.46102725
Sum4921.0629
Variance0.0016892065
MonotonicityNot monotonic
2023-12-13T02:01:25.923710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.87328069 3
 
2.1%
34.91746914 3
 
2.1%
34.81991401 2
 
1.4%
34.85570586 2
 
1.4%
34.91946997 2
 
1.4%
34.92722426 2
 
1.4%
34.8590407 1
 
0.7%
34.8587564 1
 
0.7%
34.90822444 1
 
0.7%
34.88401301 1
 
0.7%
Other values (123) 123
87.2%
ValueCountFrequency (%)
34.78377528 1
0.7%
34.7999344 1
0.7%
34.80864982 1
0.7%
34.81005367 1
0.7%
34.81425697 1
0.7%
34.81735864 1
0.7%
34.81991401 2
1.4%
34.82817935 1
0.7%
34.82902218 1
0.7%
34.8315737 1
0.7%
ValueCountFrequency (%)
34.99975287 1
0.7%
34.98565421 1
0.7%
34.97896131 1
0.7%
34.97753518 1
0.7%
34.97585885 1
0.7%
34.97478963 1
0.7%
34.963822 1
0.7%
34.96357303 1
0.7%
34.9629654 1
0.7%
34.95930705 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59282
Minimum128.47478
Maximum128.71974
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T02:01:26.124181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.47478
5-th percentile128.48671
Q1128.54123
median128.60411
Q3128.61968
95-th percentile128.69545
Maximum128.71974
Range0.2449584
Interquartile range (IQR)0.0784539

Descriptive statistics

Standard deviation0.060626303
Coefficient of variation (CV)0.00047145946
Kurtosis-0.60868388
Mean128.59282
Median Absolute Deviation (MAD)0.0444139
Skewness-0.037836243
Sum18131.588
Variance0.0036755486
MonotonicityNot monotonic
2023-12-13T02:01:26.326765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.655838 3
 
2.1%
128.6188984 3
 
2.1%
128.5077669 2
 
1.4%
128.4841164 2
 
1.4%
128.6152415 2
 
1.4%
128.6034822 2
 
1.4%
128.5882232 1
 
0.7%
128.5879706 1
 
0.7%
128.6176248 1
 
0.7%
128.6250818 1
 
0.7%
Other values (123) 123
87.2%
ValueCountFrequency (%)
128.4747829 1
0.7%
128.4764793 1
0.7%
128.4791563 1
0.7%
128.4801867 1
0.7%
128.4840417 1
0.7%
128.4841164 2
1.4%
128.4867112 1
0.7%
128.4968415 1
0.7%
128.4984433 1
0.7%
128.4991092 1
0.7%
ValueCountFrequency (%)
128.7197413 1
0.7%
128.7146552 1
0.7%
128.7112469 1
0.7%
128.7112284 1
0.7%
128.7065641 1
0.7%
128.7050471 1
0.7%
128.696234 1
0.7%
128.6954533 1
0.7%
128.6950969 1
0.7%
128.6950604 1
0.7%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-09-05
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-05
2nd row2023-09-05
3rd row2023-09-05
4th row2023-09-05
5th row2023-09-05

Common Values

ValueCountFrequency (%)
2023-09-05 141
100.0%

Length

2023-12-13T02:01:26.481164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:01:26.612695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-05 141
100.0%

Interactions

2023-12-13T02:01:18.100166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:16.957768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.356119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.762122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:18.184071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.067984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.467910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.867443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:18.303617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.162907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.579045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.952116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:18.407881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.250028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:17.669777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:18.025343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:01:26.705258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명설립구분공장우편번호업종명위도경도
순번1.0000.4600.0000.2560.5390.2830.000
단지명0.4601.0001.0001.0001.0001.0001.000
설립구분0.0001.0001.0000.5860.8310.0000.000
공장우편번호0.2561.0000.5861.0000.8430.7340.736
업종명0.5391.0000.8310.8431.0000.7470.689
위도0.2831.0000.0000.7340.7471.0000.804
경도0.0001.0000.0000.7360.6890.8041.000
2023-12-13T02:01:26.853541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번공장우편번호위도경도설립구분
순번1.0000.086-0.1010.0190.000
공장우편번호0.0861.000-0.887-0.6020.382
위도-0.101-0.8871.0000.4610.000
경도0.019-0.6020.4611.0000.000
설립구분0.0000.3820.0000.0001.000

Missing values

2023-12-13T02:01:18.551914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:01:18.753708image/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.
2023-12-13T02:01:18.877752image/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

순번회사명단지명설립구분전화번호생산품공장우편번호공장대표주소(도로명)공장대표주소(지번)업종명위도경도기준일자
01(주)거제전통메주<NA>일반055-633-2270메주 두부 장류53331경상남도 거제시 동부면 삼거림1길 20 (총 2 필지) 외 1필지경상남도 거제시 동부면 부춘리 781 외 1필지장류 제조업 외 1 종34.810054128.5982732023-09-05
12(주)건화거제모사일반산업단지일반산업단지055-639-5300선박구성부분품도장및기타피막처리업53206경상남도 거제시 연초면 연하해안로 841-54 (연초면)경상남도 거제시 연초면 한내리 777선박 구성 부분품 제조업 외 1 종34.940563128.595892023-09-05
23(주)광성산업<NA>일반055-632-7333금속공작물53208경상남도 거제시 연초면 소오비길 11-10경상남도 거제시 연초면 오비리 1164-9구조용 금속 판제품 및 공작물 제조업 외 5 종34.899784128.6307942023-09-05
34(주)금하네이벌텍<NA>일반051-664-8200복합센서마스트 여객용 선박 등53204경상남도 거제시 하청면 실전해안길 78 (실천카페리터미널)경상남도 거제시 하청면 실전리 1052-1 실천카페리터미널선박 구성 부분품 제조업 외 3 종34.978961128.6519252023-09-05
45(주)금화<NA>창업055-638-2974선박구성부분품(계측관)53275경상남도 거제시 사등면 거제대로 6025-17 (㈜정화) 외 2필지경상남도 거제시 사등면 청곡리 204 외 2필지선박 구성 부분품 제조업34.896136128.5071522023-09-05
56(주)네오하이텍<NA>일반055-637-4622LED 조명53276경상남도 거제시 사등면 성포로 92-19 상가동 101호 (삼우비취맨션)경상남도 거제시 사등면 성포리 367-6 삼우비취맨션 상가동 101호일반용 전기 조명장치 제조업34.91909128.5229542023-09-05
67(주)대기공업<NA>일반055-636-1462선박구성부분품53277경상남도 거제시 사등면 거제대로 5330-20 외 2필지경상남도 거제시 사등면 사등리 1-3 외 2필지선박 구성 부분품 제조업34.90338128.5576062023-09-05
78(주)대성쏠라<NA>일반055-633-1009태양광 구조물53244경상남도 거제시 수양로 180 (양정동 아주상사)경상남도 거제시 양정동 100 아주상사육상 금속 골조 구조재 제조업 외 2 종34.8722128.6531792023-09-05
89(주)대아<NA>일반055-637-2059금속제 창(새시)53207경상남도 거제시 연초면 오비4길 11경상남도 거제시 연초면 오비리 1197금속 문 창 셔터 및 관련제품 제조업34.918708128.6196832023-09-05
910(주)대흥<NA>일반055-632-6141선박구성부분품53276경상남도 거제시 사등면 성포로 350 (사등면) 외 1필지경상남도 거제시 사등면 사등리 2074-1 외 1필지선박 구성 부분품 제조업34.915392128.5374672023-09-05
순번회사명단지명설립구분전화번호생산품공장우편번호공장대표주소(도로명)공장대표주소(지번)업종명위도경도기준일자
131132풍어영어조합법인<NA>일반055-224-1368굴가공류53279경상남도 거제시 둔덕면 내평1길 50경상남도 거제시 둔덕면 술역리 783-3기타 수산동물 가공 및 저장 처리업34.848848128.4791562023-09-05
132133하나단열<NA>일반055-634-5511암면제품53286경상남도 거제시 거제면 산촌명진길 72경상남도 거제시 거제면 명진리 267-1암면 및 유사제품 제조업 외 1 종34.838318128.6071122023-09-05
133134하이에어코리아(주)<NA>일반055-346-3500원형통풍관및연결부분품53275경상남도 거제시 사등면 지석로 26-1 (한국하이프레스거제공장)경상남도 거제시 사등면 지석리 628그 외 기타 일반목적용 기계 제조업 외 1 종34.901017128.5152772023-09-05
134135한미산업(주)<NA>일반055-635-4005광고물금속구조물53278경상남도 거제시 사등면 모래실길 58-21경상남도 거제시 사등면 사곡리 697구조용 금속 판제품 및 공작물 제조업 외 3 종34.900593128.5779612023-09-05
135136해금강수산식품<NA>일반055-633-0129멸치액젓53281경상남도 거제시 둔덕면 법동어구로 702 외 1필지경상남도 거제시 둔덕면 하둔리 580 외 1필지수산동물 건조 및 염장품 제조업34.831574128.5102512023-09-05
136137해원<NA>일반055-633-4960배관용 파이프53275경상남도 거제시 사등면 지석로 34 (청유식품)경상남도 거제시 사등면 지석리 651선박 구성 부분품 제조업34.901084128.516382023-09-05
137138행복앤거제천년초<NA>일반055-688-0757천년초 추출액 외 5종53308경상남도 거제시 아주1로2길 116 1층 (아주동)경상남도 거제시 아주동 1670-9 1층기타 과실ㆍ채소 가공 및 저장 처리업 외 1 종34.868991128.6800082023-09-05
138139호진산업(주)<NA>일반055-633-2708철의장품53206경상남도 거제시 연초면 연하해안로 725-2 (호진산업(주))경상남도 거제시 연초면 한내리 120-8선박 구성 부분품 제조업34.926575128.6052432023-09-05
139140홍근버섯영농조합법인<NA>일반055-636-0325건강기능식품53331경상남도 거제시 동부면 산촌리 412-1 외 4필지경상남도 거제시 동부면 산촌리 412-1 외 4필지건강기능식품 제조업34.836024128.607182023-09-05
140141효진수산<NA>일반055-636-6318수산물절임 젓갈53201경상남도 거제시 장목면 거제북로 1315-18 (구지번:장목리 368-17) 외 2필지경상남도 거제시 장목면 장목리 368-17 (구지번:장목리 368-17) 외 2필지수산동물 건조 및 염장품 제조업34.999753128.6798242023-09-05