Overview

Dataset statistics

Number of variables9
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory80.0 B

Variable types

Text4
Categorical2
Numeric2
DateTime1

Dataset

Description영광군의 벙커C유 사용업소 자료로 업소명, 소재지, 전화번호, 업종, 위도, 경도, 데이터기준일자가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15076956/fileData.do

Alerts

사용유종 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
위도 is highly overall correlated with 업종 및 생산품High correlation
경도 is highly overall correlated with 업종 및 생산품High correlation
업종 및 생산품 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
업소명 has unique valuesUnique
소재지 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:25:37.662854
Analysis finished2023-12-12 22:25:38.594626
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T07:25:38.721148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.0909091
Min length3

Characters and Unicode

Total characters112
Distinct characters53
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

Unique22 ?
Unique (%)100.0%

Sample

1st row중앙목욕탕
2nd row해광양만장
3rd row만정양식장
4th row호산양만장
5th row홍농탕
ValueCountFrequency (%)
중앙목욕탕 1
 
4.3%
화천양만장 1
 
4.3%
아세아물산 1
 
4.3%
대성양만 1
 
4.3%
용덕수산 1
 
4.3%
청산양만영어조합법인 1
 
4.3%
신흥수산 1
 
4.3%
태호양만장 1
 
4.3%
금호양만장 1
 
4.3%
승희양만 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T07:25:39.047314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 11
 
9.8%
만 11
 
9.8%
장 7
 
6.2%
산 7
 
6.2%
성 5
 
4.5%
농 5
 
4.5%
호 3
 
2.7%
탕 3
 
2.7%
영 3
 
2.7%
아 3
 
2.7%
Other values (43) 54
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
99.1%
Space Separator 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 11
 
9.9%
만 11
 
9.9%
장 7
 
6.3%
산 7
 
6.3%
성 5
 
4.5%
농 5
 
4.5%
호 3
 
2.7%
탕 3
 
2.7%
영 3
 
2.7%
아 3
 
2.7%
Other values (42) 53
47.7%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
99.1%
Common 1
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 11
 
9.9%
만 11
 
9.9%
장 7
 
6.3%
산 7
 
6.3%
성 5
 
4.5%
농 5
 
4.5%
호 3
 
2.7%
탕 3
 
2.7%
영 3
 
2.7%
아 3
 
2.7%
Other values (42) 53
47.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
99.1%
ASCII 1
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 11
 
9.9%
만 11
 
9.9%
장 7
 
6.3%
산 7
 
6.3%
성 5
 
4.5%
농 5
 
4.5%
호 3
 
2.7%
탕 3
 
2.7%
영 3
 
2.7%
아 3
 
2.7%
Other values (42) 53
47.7%
ASCII
ValueCountFrequency (%)
1
100.0%

소재지
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T07:25:39.271940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24.5
Mean length21.5
Min length17

Characters and Unicode

Total characters473
Distinct characters56
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

Unique22 ?
Unique (%)100.0%

Sample

1st row전남 영광군 법성면 법성리 706-2
2nd row전남 영광군 법성면 화천길 69
3rd row전남 영광군 군서면 만곡리 440-25
4th row전남 영광군 백수읍 상사리 염백로3길 16-1
5th row전남 영광군 홍농읍 상하리 214-12
ValueCountFrequency (%)
전남 22
18.8%
영광군 22
18.8%
법성면 10
 
8.5%
백수읍 3
 
2.6%
법성리 3
 
2.6%
용덕리 3
 
2.6%
염산면 3
 
2.6%
와룡로 2
 
1.7%
145-23 2
 
1.7%
영광읍 2
 
1.7%
Other values (42) 45
38.5%
2023-12-13T07:25:39.585876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
20.3%
영 24
 
5.1%
광 24
 
5.1%
남 24
 
5.1%
1 23
 
4.9%
군 23
 
4.9%
전 22
 
4.7%
리 20
 
4.2%
면 15
 
3.2%
4 15
 
3.2%
Other values (46) 187
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 273
57.7%
Space Separator 96
 
20.3%
Decimal Number 91
 
19.2%
Dash Punctuation 13
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 24
 
8.8%
광 24
 
8.8%
남 24
 
8.8%
군 23
 
8.4%
전 22
 
8.1%
리 20
 
7.3%
면 15
 
5.5%
성 14
 
5.1%
법 13
 
4.8%
로 7
 
2.6%
Other values (34) 87
31.9%
Decimal Number
ValueCountFrequency (%)
1 23
25.3%
4 15
16.5%
3 11
12.1%
2 11
12.1%
5 10
11.0%
7 5
 
5.5%
8 4
 
4.4%
0 4
 
4.4%
6 4
 
4.4%
9 4
 
4.4%
Space Separator
ValueCountFrequency (%)
96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 273
57.7%
Common 200
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 24
 
8.8%
광 24
 
8.8%
남 24
 
8.8%
군 23
 
8.4%
전 22
 
8.1%
리 20
 
7.3%
면 15
 
5.5%
성 14
 
5.1%
법 13
 
4.8%
로 7
 
2.6%
Other values (34) 87
31.9%
Common
ValueCountFrequency (%)
96
48.0%
1 23
 
11.5%
4 15
 
7.5%
- 13
 
6.5%
3 11
 
5.5%
2 11
 
5.5%
5 10
 
5.0%
7 5
 
2.5%
8 4
 
2.0%
0 4
 
2.0%
Other values (2) 8
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 273
57.7%
ASCII 200
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
48.0%
1 23
 
11.5%
4 15
 
7.5%
- 13
 
6.5%
3 11
 
5.5%
2 11
 
5.5%
5 10
 
5.0%
7 5
 
2.5%
8 4
 
2.0%
0 4
 
2.0%
Other values (2) 8
 
4.0%
Hangul
ValueCountFrequency (%)
영 24
 
8.8%
광 24
 
8.8%
남 24
 
8.8%
군 23
 
8.4%
전 22
 
8.1%
리 20
 
7.3%
면 15
 
5.5%
성 14
 
5.1%
법 13
 
4.8%
로 7
 
2.6%
Other values (34) 87
31.9%

전화번호
Text

Distinct16
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T07:25:39.741230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length9.7727273
Min length5

Characters and Unicode

Total characters215
Distinct characters16
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

Unique15 ?
Unique (%)68.2%

Sample

1st row061-356-4077
2nd row담당자문의
3rd row담당자문의
4th row담당자문의
5th row061-356-5174
ValueCountFrequency (%)
담당자문의 7
31.8%
061-356-4077 1
 
4.5%
061-356-5174 1
 
4.5%
061-351-0350 1
 
4.5%
061-352-9805 1
 
4.5%
061-356-5090 1
 
4.5%
061-352-1911 1
 
4.5%
061-351-1917 1
 
4.5%
061-356-6354 1
 
4.5%
061-356-2011 1
 
4.5%
Other values (6) 6
27.3%
2023-12-13T07:25:40.290613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30
14.0%
5 29
13.5%
1 28
13.0%
0 25
11.6%
6 23
10.7%
3 18
8.4%
담 7
 
3.3%
당 7
 
3.3%
자 7
 
3.3%
문 7
 
3.3%
Other values (6) 34
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
69.8%
Other Letter 35
 
16.3%
Dash Punctuation 30
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 29
19.3%
1 28
18.7%
0 25
16.7%
6 23
15.3%
3 18
12.0%
2 7
 
4.7%
9 7
 
4.7%
4 6
 
4.0%
7 6
 
4.0%
8 1
 
0.7%
Other Letter
ValueCountFrequency (%)
담 7
20.0%
당 7
20.0%
자 7
20.0%
문 7
20.0%
의 7
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 180
83.7%
Hangul 35
 
16.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 30
16.7%
5 29
16.1%
1 28
15.6%
0 25
13.9%
6 23
12.8%
3 18
10.0%
2 7
 
3.9%
9 7
 
3.9%
4 6
 
3.3%
7 6
 
3.3%
Hangul
ValueCountFrequency (%)
담 7
20.0%
당 7
20.0%
자 7
20.0%
문 7
20.0%
의 7
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
83.7%
Hangul 35
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30
16.7%
5 29
16.1%
1 28
15.6%
0 25
13.9%
6 23
12.8%
3 18
10.0%
2 7
 
3.9%
9 7
 
3.9%
4 6
 
3.3%
7 6
 
3.3%
Hangul
ValueCountFrequency (%)
담 7
20.0%
당 7
20.0%
자 7
20.0%
문 7
20.0%
의 7
20.0%

업종 및 생산품
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
내수면양식어업
16 
목욕탕
4 
공통시설
2 

Length

Max length7
Median length7
Mean length6
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row목욕탕
2nd row내수면양식어업
3rd row내수면양식어업
4th row내수면양식어업
5th row목욕탕

Common Values

ValueCountFrequency (%)
내수면양식어업 16
72.7%
목욕탕 4
 
18.2%
공통시설 2
 
9.1%

Length

2023-12-13T07:25:40.448540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:25:40.568819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내수면양식어업 16
72.7%
목욕탕 4
 
18.2%
공통시설 2
 
9.1%

사용유종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
벙커C유
22 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
벙커C유 22
100.0%

Length

2023-12-13T07:25:40.665299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:25:40.753522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
벙커c유 22
100.0%

연간사용량
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T07:25:40.887077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.6363636
Min length3

Characters and Unicode

Total characters102
Distinct characters19
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row96톤
2nd row30.3ℓ/hr
3rd row171톤
4th row274톤
5th row96톤
ValueCountFrequency (%)
96톤 2
 
9.1%
129톤 1
 
4.5%
84.9kℓ 1
 
4.5%
62.5ℓ/hr 1
 
4.5%
112톤 1
 
4.5%
194톤 1
 
4.5%
2400l 1
 
4.5%
202톤 1
 
4.5%
167톤 1
 
4.5%
167.0톤 1
 
4.5%
Other values (11) 11
50.0%
2023-12-13T07:25:41.176653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
톤 16
15.7%
6 12
11.8%
1 11
10.8%
2 10
9.8%
0 9
8.8%
7 6
 
5.9%
9 5
 
4.9%
5 5
 
4.9%
. 4
 
3.9%
ℓ 4
 
3.9%
Other values (9) 20
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
66.7%
Other Letter 16
 
15.7%
Lowercase Letter 9
 
8.8%
Other Punctuation 7
 
6.9%
Uppercase Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 12
17.6%
1 11
16.2%
2 10
14.7%
0 9
13.2%
7 6
8.8%
9 5
7.4%
5 5
7.4%
4 4
 
5.9%
3 3
 
4.4%
8 3
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
ℓ 4
44.4%
r 2
22.2%
h 2
22.2%
k 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 4
57.1%
/ 2
28.6%
, 1
 
14.3%
Other Letter
ValueCountFrequency (%)
톤 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 79
77.5%
Hangul 16
 
15.7%
Latin 7
 
6.9%

Most frequent character per script

Common
ValueCountFrequency (%)
6 12
15.2%
1 11
13.9%
2 10
12.7%
0 9
11.4%
7 6
7.6%
9 5
6.3%
5 5
6.3%
. 4
 
5.1%
ℓ 4
 
5.1%
4 4
 
5.1%
Other values (4) 9
11.4%
Latin
ValueCountFrequency (%)
L 2
28.6%
r 2
28.6%
h 2
28.6%
k 1
14.3%
Hangul
ValueCountFrequency (%)
톤 16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
80.4%
Hangul 16
 
15.7%
Letterlike Symbols 4
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
톤 16
100.0%
ASCII
ValueCountFrequency (%)
6 12
14.6%
1 11
13.4%
2 10
12.2%
0 9
11.0%
7 6
7.3%
9 5
 
6.1%
5 5
 
6.1%
. 4
 
4.9%
4 4
 
4.9%
3 3
 
3.7%
Other values (7) 13
15.9%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 4
100.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.31824
Minimum35.20727
Maximum35.39785
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T07:25:41.297861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.20727
5-th percentile35.214
Q135.27384
median35.357105
Q335.366185
95-th percentile35.390707
Maximum35.39785
Range0.19058
Interquartile range (IQR)0.092345

Descriptive statistics

Standard deviation0.063446712
Coefficient of variation (CV)0.0017964291
Kurtosis-1.1237991
Mean35.31824
Median Absolute Deviation (MAD)0.03768
Skewness-0.59512274
Sum777.00127
Variance0.0040254853
MonotonicityNot monotonic
2023-12-13T07:25:41.453051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35.36279 1
 
4.5%
35.3644 1
 
4.5%
35.21495 1
 
4.5%
35.21395 1
 
4.5%
35.36974 1
 
4.5%
35.36737 1
 
4.5%
35.35283 1
 
4.5%
35.22297 1
 
4.5%
35.29524 1
 
4.5%
35.36464 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
35.20727 1
4.5%
35.21395 1
4.5%
35.21495 1
4.5%
35.22297 1
4.5%
35.26111 1
4.5%
35.27043 1
4.5%
35.28407 1
4.5%
35.29521 1
4.5%
35.29524 1
4.5%
35.30018 1
4.5%
ValueCountFrequency (%)
35.39785 1
4.5%
35.39172 1
4.5%
35.37145 1
4.5%
35.36974 1
4.5%
35.36737 1
4.5%
35.36651 1
4.5%
35.36521 1
4.5%
35.36464 1
4.5%
35.3644 1
4.5%
35.36279 1
4.5%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.44166
Minimum126.33546
Maximum126.50555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T07:25:41.569900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.33546
5-th percentile126.33973
Q1126.43827
median126.45404
Q3126.4802
95-th percentile126.50507
Maximum126.50555
Range0.17009
Interquartile range (IQR)0.04193

Descriptive statistics

Standard deviation0.054749597
Coefficient of variation (CV)0.00043300282
Kurtosis-0.29499404
Mean126.44166
Median Absolute Deviation (MAD)0.02607
Skewness-0.9435881
Sum2781.7166
Variance0.0029975183
MonotonicityNot monotonic
2023-12-13T07:25:41.678288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
126.44453 1
 
4.5%
126.48271 1
 
4.5%
126.33968 1
 
4.5%
126.34064 1
 
4.5%
126.44212 1
 
4.5%
126.49553 1
 
4.5%
126.46045 1
 
4.5%
126.49622 1
 
4.5%
126.50555 1
 
4.5%
126.4803 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
126.33546 1
4.5%
126.33968 1
4.5%
126.34064 1
4.5%
126.36692 1
4.5%
126.37329 1
4.5%
126.43708 1
4.5%
126.44185 1
4.5%
126.44212 1
4.5%
126.44453 1
4.5%
126.44568 1
4.5%
ValueCountFrequency (%)
126.50555 1
4.5%
126.50554 1
4.5%
126.49622 1
4.5%
126.49553 1
4.5%
126.48271 1
4.5%
126.4803 1
4.5%
126.47991 1
4.5%
126.46736 1
4.5%
126.46732 1
4.5%
126.46085 1
4.5%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2023-08-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-13T07:25:41.803267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:25:41.910151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T07:25:38.176827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:25:37.978283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:25:38.301911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:25:38.075998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:25:41.991500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지전화번호업종 및 생산품연간사용량위도경도
업소명1.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0000.8810.8850.0000.732
업종 및 생산품1.0001.0000.8811.0001.0000.6990.808
연간사용량1.0001.0000.8851.0001.0000.9361.000
위도1.0001.0000.0000.6990.9361.0000.845
경도1.0001.0000.7320.8081.0000.8451.000
2023-12-13T07:25:42.106920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종 및 생산품
위도1.0000.3160.536
경도0.3161.0000.626
업종 및 생산품0.5360.6261.000

Missing values

2023-12-13T07:25:38.419671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:25:38.547023image/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

업소명소재지전화번호업종 및 생산품사용유종연간사용량위도경도데이터 기준일자
0중앙목욕탕전남 영광군 법성면 법성리 706-2061-356-4077목욕탕벙커C유96톤35.36279126.444532023-08-01
1해광양만장전남 영광군 법성면 화천길 69담당자문의내수면양식어업벙커C유30.3ℓ/hr35.36651126.460852023-08-01
2만정양식장전남 영광군 군서면 만곡리 440-25담당자문의내수면양식어업벙커C유171톤35.28407126.467362023-08-01
3호산양만장전남 영광군 백수읍 상사리 염백로3길 16-1담당자문의내수면양식어업벙커C유274톤35.26111126.373292023-08-01
4홍농탕전남 영광군 홍농읍 상하리 214-12061-356-5174목욕탕벙커C유96톤35.39785126.447622023-08-01
5무등목욕탕전남 영광군 법성면 법성리 648-12담당자문의목욕탕벙커C유62톤35.36138126.445682023-08-01
6오성농산전남 영광군 백수읍 천정리 산159-2061-351-0350내수면양식어업벙커C유562톤35.30018126.437082023-08-01
7거성농산전남 영광군 염산면 야월리 칠산로5길 345061-352-9805공통시설벙커C유176톤35.20727126.335462023-08-01
8지마트 홍농점전남 영광군 홍농읍 홍농로 398061-356-5090목욕탕벙커C유6000L35.39172126.441852023-08-01
9중촌위탁영농전남 영광군 백수읍 하사리 백수로 477061-352-1911공통시설벙커C유851톤35.27043126.366922023-08-01
업소명소재지전화번호업종 및 생산품사용유종연간사용량위도경도데이터 기준일자
12신성양만전남 영광군 법성면 용덕리 479-4061-356-2011내수면양식어업벙커C유129톤35.3644126.482712023-08-01
13승희양만전남 영광군 법성면 용덕리 450-4외1담당자문의내수면양식어업벙커C유167.0톤35.36521126.479912023-08-01
14금호양만장전남 영광군 법성면 용성리 843-1외1061-356-4550내수면양식어업벙커C유167톤35.36464126.48032023-08-01
15태호양만장전남 영광군 영광읍 월평리 와룡로 145-23061-353-9922내수면양식어업벙커C유202톤35.29524126.505552023-08-01
16신흥수산전남 영광군 불갑면 부춘리 357-1061-351-0502내수면양식어업벙커C유2400L35.22297126.496222023-08-01
17청산양만영어조합법인전남 영광군 법성면 대덕리 211-1외2담당자문의내수면양식어업벙커C유194톤35.35283126.460452023-08-01
18용덕수산전남 영광군 법성면 용덕리 45외1담당자문의내수면양식어업벙커C유112톤35.36737126.495532023-08-01
19대성양만전남 영광군 법성면 법성리 연우로 84061-356-1449내수면양식어업벙커C유62.5ℓ/hr35.36974126.442122023-08-01
20아세아물산전남 영광군 염산면 봉남리 1135외3061-352-7555내수면양식어업벙커C유84.9kℓ35.21395126.340642023-08-01
21아삼영어조합법인전남 영광군 염산면 봉남리 1132외1061-351-7555내수면양식어업벙커C유67,536ℓ35.21495126.339682023-08-01