Overview

Dataset statistics

Number of variables14
Number of observations49
Missing cells20
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory121.7 B

Variable types

Categorical2
Text7
Numeric5

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=86f242f0-176d-11eb-a877-a5b67dc5814b

Alerts

자료생성년월(자격마감일) has constant value ""Constant
사업장형태구분코드 has constant value ""Constant
우편번호 is highly overall correlated with 웹검색 X좌표High correlation
웹검색 X좌표 is highly overall correlated with 우편번호High correlation
웹검색 전화번호 has 20 (40.8%) missing valuesMissing
사업장명 has unique valuesUnique
우편번호 has unique valuesUnique
사업장도로명상세주소 has unique valuesUnique
웹검색 대표자명 has unique valuesUnique
웹검색 주소 has unique valuesUnique
웹검색 X좌표 has unique valuesUnique
웹검색 Y좌표 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:18:38.071249
Analysis finished2023-12-10 13:18:46.092459
Duration8.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자료생성년월(자격마감일)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
202006
49 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202006
2nd row202006
3rd row202006
4th row202006
5th row202006

Common Values

ValueCountFrequency (%)
202006 49
100.0%

Length

2023-12-10T22:18:46.205280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:18:46.344264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202006 49
100.0%

사업장명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:46.634265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length7.7959184
Min length5

Characters and Unicode

Total characters382
Distinct characters118
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

Unique49 ?
Unique (%)100.0%

Sample

1st row(주)프리존
2nd row주식회사 세진씰
3rd row주식회사데이터원
4th row케이이엔씨주식회사
5th row진영기업(주)
ValueCountFrequency (%)
주식회사 4
 
7.5%
주)프리존 1
 
1.9%
주)서연침대 1
 
1.9%
이화텍주식회사 1
 
1.9%
진양솔루션 1
 
1.9%
주식회사원키 1
 
1.9%
라온이엔지(주 1
 
1.9%
주식회사한도 1
 
1.9%
주)케이알아스콘 1
 
1.9%
주식회사엠엠에스 1
 
1.9%
Other values (40) 40
75.5%
2023-12-10T22:18:47.471140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 46
 
12.0%
( 28
 
7.3%
) 28
 
7.3%
사 21
 
5.5%
식 19
 
5.0%
회 19
 
5.0%
이 15
 
3.9%
성 7
 
1.8%
진 6
 
1.6%
아 6
 
1.6%
Other values (108) 187
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 322
84.3%
Open Punctuation 28
 
7.3%
Close Punctuation 28
 
7.3%
Space Separator 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 46
 
14.3%
사 21
 
6.5%
식 19
 
5.9%
회 19
 
5.9%
이 15
 
4.7%
성 7
 
2.2%
진 6
 
1.9%
아 6
 
1.9%
업 6
 
1.9%
스 5
 
1.6%
Other values (105) 172
53.4%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
84.3%
Common 60
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 46
 
14.3%
사 21
 
6.5%
식 19
 
5.9%
회 19
 
5.9%
이 15
 
4.7%
성 7
 
2.2%
진 6
 
1.9%
아 6
 
1.9%
업 6
 
1.9%
스 5
 
1.6%
Other values (105) 172
53.4%
Common
ValueCountFrequency (%)
( 28
46.7%
) 28
46.7%
4
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 322
84.3%
ASCII 60
 
15.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 46
 
14.3%
사 21
 
6.5%
식 19
 
5.9%
회 19
 
5.9%
이 15
 
4.7%
성 7
 
2.2%
진 6
 
1.9%
아 6
 
1.9%
업 6
 
1.9%
스 5
 
1.6%
Other values (105) 172
53.4%
ASCII
ValueCountFrequency (%)
( 28
46.7%
) 28
46.7%
4
 
6.7%

사업자등록번호
Real number (ℝ)

Distinct44
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean439025.49
Minimum110880
Maximum895870
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T22:18:47.796094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110880
5-th percentile127012
Q1232880
median411810
Q3654880
95-th percentile823072
Maximum895870
Range784990
Interquartile range (IQR)422000

Descriptive statistics

Standard deviation237283.84
Coefficient of variation (CV)0.54047851
Kurtosis-1.031007
Mean439025.49
Median Absolute Deviation (MAD)214060
Skewness0.27492696
Sum21512249
Variance5.6303623 × 1010
MonotonicityNot monotonic
2023-12-10T22:18:48.067192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
136811 3
 
6.1%
512810 2
 
4.1%
136812 2
 
4.1%
416810 2
 
4.1%
654880 1
 
2.0%
427860 1
 
2.0%
232880 1
 
2.0%
895870 1
 
2.0%
361870 1
 
2.0%
680880 1
 
2.0%
Other values (34) 34
69.4%
ValueCountFrequency (%)
110880 1
 
2.0%
125810 1
 
2.0%
125812 1
 
2.0%
128812 1
 
2.0%
128813 1
 
2.0%
136811 3
6.1%
136812 2
4.1%
183860 1
 
2.0%
224820 1
 
2.0%
232880 1
 
2.0%
ValueCountFrequency (%)
895870 1
2.0%
889870 1
2.0%
825880 1
2.0%
818860 1
2.0%
814880 1
2.0%
746880 1
2.0%
731870 1
2.0%
712810 1
2.0%
701870 1
2.0%
680880 1
2.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40709.449
Minimum4799
Maximum415860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T22:18:48.487248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4799
5-th percentile8838.2
Q115600
median31713
Q352062
95-th percentile59561.4
Maximum415860
Range411061
Interquartile range (IQR)36462

Descriptive statistics

Standard deviation57665.312
Coefficient of variation (CV)1.4165093
Kurtosis39.121086
Mean40709.449
Median Absolute Deviation (MAD)18506
Skewness5.9393236
Sum1994763
Variance3.3252882 × 109
MonotonicityNot monotonic
2023-12-10T22:18:48.743579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
14319 1
 
2.0%
8055 1
 
2.0%
62464 1
 
2.0%
31035 1
 
2.0%
15600 1
 
2.0%
24207 1
 
2.0%
31706 1
 
2.0%
13207 1
 
2.0%
52612 1
 
2.0%
59000 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
4799 1
2.0%
7274 1
2.0%
8055 1
2.0%
10013 1
2.0%
10038 1
2.0%
10045 1
2.0%
10212 1
2.0%
10257 1
2.0%
10816 1
2.0%
13207 1
2.0%
ValueCountFrequency (%)
415860 1
2.0%
62464 1
2.0%
59657 1
2.0%
59418 1
2.0%
59000 1
2.0%
58558 1
2.0%
57812 1
2.0%
57714 1
2.0%
56167 1
2.0%
55727 1
2.0%

사업장지번상세주소
Text

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:49.374826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length12.571429
Min length10

Characters and Unicode

Total characters616
Distinct characters99
Distinct categories3 ?
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 (%)95.9%

Sample

1st row경기도 광명시 소하동
2nd row충청남도 당진시 송산면
3rd row경기도 김포시 양촌읍
4th row전라남도 여수시 화양면
5th row경기도 안성시 미양면
ValueCountFrequency (%)
경기도 14
 
9.1%
전라남도 6
 
3.9%
충청남도 6
 
3.9%
김포시 4
 
2.6%
대구광역시 4
 
2.6%
경상남도 4
 
2.6%
서울특별시 3
 
1.9%
강원도 3
 
1.9%
전라북도 3
 
1.9%
단원구 2
 
1.3%
Other values (92) 105
68.2%
2023-12-10T22:18:50.211420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
17.0%
시 43
 
7.0%
도 40
 
6.5%
동 23
 
3.7%
면 22
 
3.6%
남 22
 
3.6%
경 20
 
3.2%
구 19
 
3.1%
산 15
 
2.4%
기 14
 
2.3%
Other values (89) 293
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 509
82.6%
Space Separator 105
 
17.0%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 43
 
8.4%
도 40
 
7.9%
동 23
 
4.5%
면 22
 
4.3%
남 22
 
4.3%
경 20
 
3.9%
구 19
 
3.7%
산 15
 
2.9%
기 14
 
2.8%
광 13
 
2.6%
Other values (87) 278
54.6%
Space Separator
ValueCountFrequency (%)
105
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 509
82.6%
Common 107
 
17.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 43
 
8.4%
도 40
 
7.9%
동 23
 
4.5%
면 22
 
4.3%
남 22
 
4.3%
경 20
 
3.9%
구 19
 
3.7%
산 15
 
2.9%
기 14
 
2.8%
광 13
 
2.6%
Other values (87) 278
54.6%
Common
ValueCountFrequency (%)
105
98.1%
2 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 509
82.6%
ASCII 107
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
98.1%
2 2
 
1.9%
Hangul
ValueCountFrequency (%)
시 43
 
8.4%
도 40
 
7.9%
동 23
 
4.5%
면 22
 
4.3%
남 22
 
4.3%
경 20
 
3.9%
구 19
 
3.7%
산 15
 
2.9%
기 14
 
2.8%
광 13
 
2.6%
Other values (87) 278
54.6%

사업장도로명상세주소
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:50.696317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length16.857143
Min length1

Characters and Unicode

Total characters826
Distinct characters128
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row경기도 광명시 하안로
2nd row충청남도 당진시 송산면 당산1로
3rd row경기도 김포시 양촌읍 대곶남로
4th row전라남도 여수시 화양면 영터길
5th row경기도 안성시 미양면 제2공단5길
ValueCountFrequency (%)
경기도 13
 
7.2%
전라남도 6
 
3.3%
충청남도 6
 
3.3%
대구광역시 4
 
2.2%
경상남도 4
 
2.2%
서울특별시 3
 
1.7%
강원도 3
 
1.7%
전라북도 3
 
1.7%
김포시 3
 
1.7%
고양시 2
 
1.1%
Other values (120) 133
73.9%
2023-12-10T22:18:51.431165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
16.1%
도 41
 
5.0%
시 41
 
5.0%
로 35
 
4.2%
산 28
 
3.4%
길 27
 
3.3%
남 25
 
3.0%
면 22
 
2.7%
구 20
 
2.4%
경 19
 
2.3%
Other values (118) 435
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 645
78.1%
Space Separator 133
 
16.1%
Decimal Number 48
 
5.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 41
 
6.4%
시 41
 
6.4%
로 35
 
5.4%
산 28
 
4.3%
길 27
 
4.2%
남 25
 
3.9%
면 22
 
3.4%
구 20
 
3.1%
경 19
 
2.9%
광 13
 
2.0%
Other values (107) 374
58.0%
Decimal Number
ValueCountFrequency (%)
1 9
18.8%
2 9
18.8%
3 6
12.5%
0 5
10.4%
4 4
8.3%
6 4
8.3%
8 4
8.3%
5 3
 
6.2%
9 3
 
6.2%
7 1
 
2.1%
Space Separator
ValueCountFrequency (%)
133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 645
78.1%
Common 181
 
21.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 41
 
6.4%
시 41
 
6.4%
로 35
 
5.4%
산 28
 
4.3%
길 27
 
4.2%
남 25
 
3.9%
면 22
 
3.4%
구 20
 
3.1%
경 19
 
2.9%
광 13
 
2.0%
Other values (107) 374
58.0%
Common
ValueCountFrequency (%)
133
73.5%
1 9
 
5.0%
2 9
 
5.0%
3 6
 
3.3%
0 5
 
2.8%
4 4
 
2.2%
6 4
 
2.2%
8 4
 
2.2%
5 3
 
1.7%
9 3
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 645
78.1%
ASCII 181
 
21.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
73.5%
1 9
 
5.0%
2 9
 
5.0%
3 6
 
3.3%
0 5
 
2.8%
4 4
 
2.2%
6 4
 
2.2%
8 4
 
2.2%
5 3
 
1.7%
9 3
 
1.7%
Hangul
ValueCountFrequency (%)
도 41
 
6.4%
시 41
 
6.4%
로 35
 
5.4%
산 28
 
4.3%
길 27
 
4.2%
남 25
 
3.9%
면 22
 
3.4%
구 20
 
3.1%
경 19
 
2.9%
광 13
 
2.0%
Other values (107) 374
58.0%

사업장형태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
1
49 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 49
100.0%

Length

2023-12-10T22:18:51.681102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:18:51.825421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
100.0%

사업장업종코드
Real number (ℝ)

Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean280707.88
Minimum141003
Maximum900101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T22:18:51.994419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum141003
5-th percentile176061
Q1252400
median281100
Q3291902
95-th percentile327821.8
Maximum900101
Range759098
Interquartile range (IQR)39502

Descriptive statistics

Standard deviation98699.864
Coefficient of variation (CV)0.35161059
Kurtosis33.630067
Mean280707.88
Median Absolute Deviation (MAD)11801
Skewness5.2240046
Sum13754686
Variance9.7416631 × 109
MonotonicityNot monotonic
2023-12-10T22:18:52.282057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
281100 5
 
10.2%
291902 4
 
8.2%
252901 3
 
6.1%
291200 3
 
6.1%
292902 2
 
4.1%
269903 2
 
4.1%
292903 2
 
4.1%
241200 2
 
4.1%
292100 2
 
4.1%
182001 1
 
2.0%
Other values (23) 23
46.9%
ValueCountFrequency (%)
141003 1
2.0%
171109 1
2.0%
172101 1
2.0%
182001 1
2.0%
210200 1
2.0%
241106 1
2.0%
241200 2
4.1%
242204 1
2.0%
242901 1
2.0%
251901 1
2.0%
ValueCountFrequency (%)
900101 1
 
2.0%
351103 1
 
2.0%
351101 1
 
2.0%
292903 2
4.1%
292902 2
4.1%
292901 1
 
2.0%
292202 1
 
2.0%
292100 2
4.1%
291902 4
8.2%
291200 3
6.1%

사업장업종코드명
Text

Distinct33
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:52.808293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length18
Mean length14.55102
Min length3

Characters and Unicode

Total characters713
Distinct characters105
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)49.0%

Sample

1st row인쇄 및 제책용 기계 제조업
2nd row볼트 및 너트류 제조업
3rd row산업용 냉장 및 냉동장비 제조업
4th row산업용 냉장 및 냉동장비 제조업
5th row금속 문 창 셔터 및 관련제품 제조업
ValueCountFrequency (%)
제조업 41
19.2%
및 27
 
12.7%
관련제품 7
 
3.3%
금속 6
 
2.8%
플라스틱 6
 
2.8%
산업용 6
 
2.8%
창 5
 
2.3%
셔터 5
 
2.3%
문 5
 
2.3%
기타 5
 
2.3%
Other values (67) 100
46.9%
2023-12-10T22:18:53.397478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
24.7%
제 61
 
8.6%
업 59
 
8.3%
조 44
 
6.2%
및 27
 
3.8%
기 23
 
3.2%
용 19
 
2.7%
품 15
 
2.1%
장 12
 
1.7%
금 9
 
1.3%
Other values (95) 268
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
75.3%
Space Separator 176
 
24.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 61
 
11.4%
업 59
 
11.0%
조 44
 
8.2%
및 27
 
5.0%
기 23
 
4.3%
용 19
 
3.5%
품 15
 
2.8%
장 12
 
2.2%
금 9
 
1.7%
스 9
 
1.7%
Other values (94) 259
48.2%
Space Separator
ValueCountFrequency (%)
176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
75.3%
Common 176
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 61
 
11.4%
업 59
 
11.0%
조 44
 
8.2%
및 27
 
5.0%
기 23
 
4.3%
용 19
 
3.5%
품 15
 
2.8%
장 12
 
2.2%
금 9
 
1.7%
스 9
 
1.7%
Other values (94) 259
48.2%
Common
ValueCountFrequency (%)
176
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
75.3%
ASCII 176
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
100.0%
Hangul
ValueCountFrequency (%)
제 61
 
11.4%
업 59
 
11.0%
조 44
 
8.2%
및 27
 
5.0%
기 23
 
4.3%
용 19
 
3.5%
품 15
 
2.8%
장 12
 
2.2%
금 9
 
1.7%
스 9
 
1.7%
Other values (94) 259
48.2%

웹검색 대표자명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:53.774469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0612245
Min length2

Characters and Unicode

Total characters150
Distinct characters75
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row김소영
2nd row강수진
3rd row고은아
4th row고영선
5th row오상영
ValueCountFrequency (%)
김소영 1
 
2.0%
송승훈 1
 
2.0%
이두형 1
 
2.0%
조원기 1
 
2.0%
이종구 1
 
2.0%
전순란 1
 
2.0%
정경록 1
 
2.0%
이종섭 1
 
2.0%
최원혁 1
 
2.0%
고창회/정삼옥 1
 
2.0%
Other values (39) 39
79.6%
2023-12-10T22:18:54.359798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
7.3%
정 8
 
5.3%
김 6
 
4.0%
영 6
 
4.0%
경 4
 
2.7%
진 4
 
2.7%
성 4
 
2.7%
철 4
 
2.7%
원 4
 
2.7%
석 4
 
2.7%
Other values (65) 95
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149
99.3%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
7.4%
정 8
 
5.4%
김 6
 
4.0%
영 6
 
4.0%
경 4
 
2.7%
진 4
 
2.7%
성 4
 
2.7%
철 4
 
2.7%
원 4
 
2.7%
석 4
 
2.7%
Other values (64) 94
63.1%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
7.4%
정 8
 
5.4%
김 6
 
4.0%
영 6
 
4.0%
경 4
 
2.7%
진 4
 
2.7%
성 4
 
2.7%
철 4
 
2.7%
원 4
 
2.7%
석 4
 
2.7%
Other values (64) 94
63.1%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
7.4%
정 8
 
5.4%
김 6
 
4.0%
영 6
 
4.0%
경 4
 
2.7%
진 4
 
2.7%
성 4
 
2.7%
철 4
 
2.7%
원 4
 
2.7%
석 4
 
2.7%
Other values (64) 94
63.1%
ASCII
ValueCountFrequency (%)
/ 1
100.0%

웹검색 주소
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T22:18:54.882216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23
Mean length17.897959
Min length13

Characters and Unicode

Total characters877
Distinct characters118
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

Unique49 ?
Unique (%)100.0%

Sample

1st row경기 광명시 하안로 108, 705호
2nd row충남 당진시 당산1로 1
3rd row경기 김포시 대곶남로 632-54, B동
4th row전남 여수시 영터길 35-31
5th row경기 안성시 제2공단5길 16-37
ValueCountFrequency (%)
경기 14
 
6.5%
충남 6
 
2.8%
전남 6
 
2.8%
대구 4
 
1.9%
김포시 4
 
1.9%
경남 4
 
1.9%
전북 3
 
1.4%
서울 3
 
1.4%
강원 3
 
1.4%
춘천시 2
 
0.9%
Other values (151) 165
77.1%
2023-12-10T22:18:55.910398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
165
 
18.8%
1 45
 
5.1%
로 35
 
4.0%
시 32
 
3.6%
2 29
 
3.3%
길 27
 
3.1%
산 24
 
2.7%
남 23
 
2.6%
구 21
 
2.4%
3 21
 
2.4%
Other values (108) 455
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
56.0%
Decimal Number 202
23.0%
Space Separator 165
 
18.8%
Dash Punctuation 8
 
0.9%
Other Punctuation 8
 
0.9%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 35
 
7.1%
시 32
 
6.5%
길 27
 
5.5%
산 24
 
4.9%
남 23
 
4.7%
구 21
 
4.3%
경 20
 
4.1%
기 14
 
2.9%
서 13
 
2.6%
단 12
 
2.4%
Other values (93) 270
55.0%
Decimal Number
ValueCountFrequency (%)
1 45
22.3%
2 29
14.4%
3 21
10.4%
4 18
 
8.9%
0 18
 
8.9%
7 17
 
8.4%
5 16
 
7.9%
6 16
 
7.9%
8 13
 
6.4%
9 9
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
56.0%
Common 383
43.7%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 35
 
7.1%
시 32
 
6.5%
길 27
 
5.5%
산 24
 
4.9%
남 23
 
4.7%
구 21
 
4.3%
경 20
 
4.1%
기 14
 
2.9%
서 13
 
2.6%
단 12
 
2.4%
Other values (93) 270
55.0%
Common
ValueCountFrequency (%)
165
43.1%
1 45
 
11.7%
2 29
 
7.6%
3 21
 
5.5%
4 18
 
4.7%
0 18
 
4.7%
7 17
 
4.4%
5 16
 
4.2%
6 16
 
4.2%
8 13
 
3.4%
Other values (3) 25
 
6.5%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
56.0%
ASCII 386
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
165
42.7%
1 45
 
11.7%
2 29
 
7.5%
3 21
 
5.4%
4 18
 
4.7%
0 18
 
4.7%
7 17
 
4.4%
5 16
 
4.1%
6 16
 
4.1%
8 13
 
3.4%
Other values (5) 28
 
7.3%
Hangul
ValueCountFrequency (%)
로 35
 
7.1%
시 32
 
6.5%
길 27
 
5.5%
산 24
 
4.9%
남 23
 
4.7%
구 21
 
4.3%
경 20
 
4.1%
기 14
 
2.9%
서 13
 
2.6%
단 12
 
2.4%
Other values (93) 270
55.0%

웹검색 전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing20
Missing (%)40.8%
Memory size524.0 B
2023-12-10T22:18:56.302997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length15.896552
Min length13

Characters and Unicode

Total characters461
Distinct characters13
Distinct categories4 ?
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 row+82 02-2678-5957
2nd row+82 02-704-5609
3rd row+82 031-677-0091
4th row+82 055-585-6827
5th row+82 031-677-7311
ValueCountFrequency (%)
82 29
50.0%
02-2678-5957 1
 
1.7%
053-588-8994 1
 
1.7%
061-792-5095 1
 
1.7%
061-281-8032 1
 
1.7%
063-536-0250 1
 
1.7%
070-8667-3775 1
 
1.7%
054-552-3931 1
 
1.7%
1577-5077 1
 
1.7%
031-732-9014 1
 
1.7%
Other values (20) 20
34.5%
2023-12-10T22:18:56.916382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
12.6%
0 56
12.1%
2 54
11.7%
8 50
10.8%
3 41
8.9%
5 33
7.2%
+ 29
6.3%
29
6.3%
1 28
6.1%
7 25
5.4%
Other values (3) 58
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
74.8%
Dash Punctuation 58
 
12.6%
Math Symbol 29
 
6.3%
Space Separator 29
 
6.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 56
16.2%
2 54
15.7%
8 50
14.5%
3 41
11.9%
5 33
9.6%
1 28
8.1%
7 25
7.2%
6 22
 
6.4%
4 19
 
5.5%
9 17
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
+ 29
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
12.6%
0 56
12.1%
2 54
11.7%
8 50
10.8%
3 41
8.9%
5 33
7.2%
+ 29
6.3%
29
6.3%
1 28
6.1%
7 25
5.4%
Other values (3) 58
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
12.6%
0 56
12.1%
2 54
11.7%
8 50
10.8%
3 41
8.9%
5 33
7.2%
+ 29
6.3%
29
6.3%
1 28
6.1%
7 25
5.4%
Other values (3) 58
12.6%

웹검색 X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1833829.1
Minimum1636911.3
Maximum1991544.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T22:18:57.177102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1636911.3
5-th percentile1652486.9
Q11716202.4
median1876196.1
Q31939784.4
95-th percentile1969404.6
Maximum1991544.6
Range354633.37
Interquartile range (IQR)223582.02

Descriptive statistics

Standard deviation118164.98
Coefficient of variation (CV)0.064436202
Kurtosis-1.4647748
Mean1833829.1
Median Absolute Deviation (MAD)90617.166
Skewness-0.31622061
Sum89857627
Variance1.3962963 × 1010
MonotonicityNot monotonic
2023-12-10T22:18:57.438003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1938903.40779391 1
 
2.0%
1945767.55841556 1
 
2.0%
1689966.14776365 1
 
2.0%
1876196.10709966 1
 
2.0%
1923076.14023309 1
 
2.0%
1991544.64743336 1
 
2.0%
1890823.92397997 1
 
2.0%
1937742.98854157 1
 
2.0%
1683027.38394126 1
 
2.0%
1639427.86360503 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1636911.28142483 1
2.0%
1639427.86360503 1
2.0%
1652301.89501356 1
2.0%
1652764.45686196 1
2.0%
1659414.92318368 1
2.0%
1663422.15695067 1
2.0%
1677821.37423001 1
2.0%
1683027.38394126 1
2.0%
1689966.14776365 1
2.0%
1695302.65058249 1
2.0%
ValueCountFrequency (%)
1991544.64743336 1
2.0%
1985807.66663271 1
2.0%
1970455.41281955 1
2.0%
1967828.48785428 1
2.0%
1967390.52229823 1
2.0%
1966813.2735808 1
2.0%
1966179.96096555 1
2.0%
1963486.19799486 1
2.0%
1960396.94866292 1
2.0%
1949847.56591552 1
2.0%

웹검색 Y좌표
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean987834.79
Minimum891689.3
Maximum1136092.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T22:18:57.734044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum891689.3
5-th percentile909199.99
Q1934699.84
median971518.37
Q31024301.6
95-th percentile1105392.3
Maximum1136092.7
Range244403.39
Interquartile range (IQR)89601.716

Descriptive statistics

Standard deviation67155.837
Coefficient of variation (CV)0.067982862
Kurtosis-0.74199008
Mean987834.79
Median Absolute Deviation (MAD)45737.669
Skewness0.65654588
Sum48403905
Variance4.5099064 × 109
MonotonicityNot monotonic
2023-12-10T22:18:58.017191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
946241.899671075 1
 
2.0%
941870.861338171 1
 
2.0%
934699.838375066 1
 
2.0%
969547.293987085 1
 
2.0%
936472.730785763 1
 
2.0%
1020833.52150209 1
 
2.0%
916373.565735682 1
 
2.0%
971518.373074858 1
 
2.0%
1092277.5453946 1
 
2.0%
891689.30155763 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
891689.30155763 1
2.0%
900998.452073571 1
2.0%
904417.61381904 1
2.0%
916373.565735682 1
2.0%
920260.869241746 1
2.0%
921452.081018082 1
2.0%
921568.780936184 1
2.0%
923274.549402508 1
2.0%
924783.702596831 1
2.0%
929052.808002056 1
2.0%
ValueCountFrequency (%)
1136092.69575844 1
2.0%
1122950.66459965 1
2.0%
1114135.47345206 1
2.0%
1092277.5453946 1
2.0%
1090440.34677276 1
2.0%
1090054.76414021 1
2.0%
1086703.37588494 1
2.0%
1085308.10154906 1
2.0%
1076675.92689789 1
2.0%
1067403.4393173 1
2.0%

Interactions

2023-12-10T22:18:44.800644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:39.287853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:40.179425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:41.387501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:42.378277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:44.996904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:39.492308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:40.482528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:41.577765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:42.570314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:45.167814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:39.638643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:40.730591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:41.844870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:42.808487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:45.308754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:39.787125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:40.990991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:42.067250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:43.222826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:45.447730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:39.984227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:41.202518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:42.241137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:18:43.693068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:18:58.180592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명사업자등록번호우편번호사업장지번상세주소사업장도로명상세주소사업장업종코드사업장업종코드명웹검색 대표자명웹검색 주소웹검색 전화번호웹검색 X좌표웹검색 Y좌표
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업자등록번호1.0001.0000.5511.0001.0000.5010.6251.0001.0001.0000.7920.660
우편번호1.0000.5511.0001.0001.0000.0000.9011.0001.0001.0000.7480.000
사업장지번상세주소1.0001.0001.0001.0001.0001.0000.9951.0001.0001.0000.8961.000
사업장도로명상세주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사업장업종코드1.0000.5010.0001.0001.0001.0001.0001.0001.0001.0000.0000.418
사업장업종코드명1.0000.6250.9010.9951.0001.0001.0001.0001.0001.0000.0000.821
웹검색 대표자명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
웹검색 주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
웹검색 전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
웹검색 X좌표1.0000.7920.7480.8961.0000.0000.0001.0001.0001.0001.0000.865
웹검색 Y좌표1.0000.6600.0001.0001.0000.4180.8211.0001.0001.0000.8651.000
2023-12-10T22:18:58.520390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업자등록번호우편번호사업장업종코드웹검색 X좌표웹검색 Y좌표
사업자등록번호1.0000.2500.124-0.3580.100
우편번호0.2501.0000.024-0.8290.293
사업장업종코드0.1240.0241.000-0.143-0.148
웹검색 X좌표-0.358-0.829-0.1431.000-0.376
웹검색 Y좌표0.1000.293-0.148-0.3761.000

Missing values

2023-12-10T22:18:45.646466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:18:45.979401image/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

자료생성년월(자격마감일)사업장명사업자등록번호우편번호사업장지번상세주소사업장도로명상세주소사업장형태구분코드사업장업종코드사업장업종코드명웹검색 대표자명웹검색 주소웹검색 전화번호웹검색 X좌표웹검색 Y좌표
0202006(주)프리존65488014319경기도 광명시 소하동경기도 광명시 하안로1292902인쇄 및 제책용 기계 제조업김소영경기 광명시 하안로 108, 705호<NA>1938903.407794946241.899671
1202006주식회사 세진씰12881331713충청남도 당진시 송산면충청남도 당진시 송산면 당산1로1289908볼트 및 너트류 제조업강수진충남 당진시 당산1로 1+82 02-2678-59571883550.9064923274.549403
2202006주식회사데이터원81886010045경기도 김포시 양촌읍경기도 김포시 양촌읍 대곶남로1291902산업용 냉장 및 냉동장비 제조업고은아경기 김포시 대곶남로 632-54, B동+82 02-704-56091960396.948663921452.081018
3202006케이이엔씨주식회사40186059657전라남도 여수시 화양면전라남도 여수시 화양면 영터길1291902산업용 냉장 및 냉동장비 제조업고영선전남 여수시 영터길 35-31<NA>1636911.2814251011583.065294
4202006진영기업(주)12581017599경기도 안성시 미양면경기도 안성시 미양면 제2공단5길1281100금속 문 창 셔터 및 관련제품 제조업오상영경기 안성시 제2공단5길 16-37+82 031-677-00911886176.039323978932.852682
5202006주식회사남성하이테크73187052062경상남도 함안군 군북면경상남도 함안군 군북면 유전2길1271101제철업남권희경남 함안군 유전2길 23+82 055-585-68271701317.5163871076675.926898
6202006안성공업(주)12581217604경기도 안성시 미양면경기도 안성시 미양면 협동단지길1292100농업 및 임업용 기계 제조업임경석경기 안성시 협동단지길 15+82 031-677-73111884610.249058977169.680081
7202006대영파워펌프(주)13681118544경기도 화성시 마도면경기도 화성시 마도면 마도로1291200유압 기기 제조업송경희경기 화성시 마도로 421-13+82 031-357-50001910513.68504933434.249208
8202006아이엠아이크리티컬엔지니어링코리아13681110816경기도 파주시 문산읍경기도 파주시 문산읍 당동2로1291200유압 기기 제조업서정덕경기 파주시 당동2로 14+82 031-980-98001985807.666633937026.981809
9202006금산(주)31081031933충청남도 서산시 성연면충청남도 서산시 성연면 일호리2길1141003건설용 석재 채굴 및 쇄석 생산업윤석권충남 서산시 일호리2길 113+82 041-663-14961868612.100551904417.613819
자료생성년월(자격마감일)사업장명사업자등록번호우편번호사업장지번상세주소사업장도로명상세주소사업장형태구분코드사업장업종코드사업장업종코드명웹검색 대표자명웹검색 주소웹검색 전화번호웹검색 X좌표웹검색 Y좌표
39202006선양이엔지(주)67887050855경상남도 김해시 진영읍경상남도 김해시 진영읍 본산로269번길1351103선박 구성 부분품 제조업나종원경남 김해시 본산로269번길 20+82 070-8667-37751703145.9594651114135.473452
40202006주식회사진원테크4058117274서울특별시 영등포구 양평동2가서울특별시 영등포구 영등포로3길1292903주형 및 금형 제조업김진영서울 영등포구 영등포로3길 26<NA>1947559.705532945591.66345
41202006영신(유)40481056167전라북도 정읍시 하북동전라북도 정읍시 서부산업도로1292100농업 및 임업용 기계 제조업성준태전북 정읍시 서부산업도로 580+82 063-536-02501732931.945264942612.28328
42202006백산기계(주)41181058558전라남도 무안군 삼향읍전라남도 무안군 삼향읍 삼향공단길1291100내연기관 제조업강철원전남 무안군 삼향공단길 70+82 061-281-80321652764.456862900998.452074
43202006주식회사안산후렉스62287015431경기도 안산시 단원구 원곡동경기도 안산시 단원구 산단로1289901금속선 가공제품 제조업홍성철경기 안산시 단원구 산단로 326, 22동 112호,113호<NA>1925155.374222936955.367838
44202006(주)신진기업41681057812전라남도 광양시 금호동전라남도 광양시 제철로1271102제강업김윤철전남 광양시 제철로 2148-33+82 061-792-50951659414.9231841024301.554274
45202006주식회사금덕18386042902대구광역시 달성군 하빈면대구광역시 달성군 하빈면 하빈로1292202금속 절삭기계 제조업이승섭대구 달성군 하빈로 458+82 053-588-89941767954.5389441085308.101549
46202006주식회사동원텍스타일74688042702대구광역시 달서구 신당동대구광역시 달서구 달구벌대로240길1171109화학섬유직물 직조업신성철대구 달서구 달구벌대로240길 30<NA>1761841.2904221090054.76414
47202006(주)삼호유비40581054333전라북도 김제시 용지면전라북도 김제시 용지면 금백로1241200복합비료 및 기타 화학비료 제조업김영태전북 김제시 금백로 875+82 063-545-35331761317.517409954030.761419
48202006(주)열린문66686050808경상남도 김해시 대동면경상남도 김해시 대동면 동남로117번길1252400플라스틱 창호 제조업한정섭경남 김해시 동남로117번길 7<NA>1695302.6505821136092.695758