Overview

Dataset statistics

Number of variables7
Number of observations149
Missing cells42
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory57.9 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description"담배 소매인 지정현황"은 특정 지역 내에서 담배 소매인이 지정되어 있는 상태를 보여주는 공공데이터입니다. 이 데이터셋은 해당 지역의 담배 소매인의 명칭, 위치, 업태, 등록일 등의 정보를 포함하고 있습니다. 이 데이터는 보건 및 규제 담당 기관이나 관련 당국에 의해 관리되며, 담배 소매인의 등록 및 인증 절차를 투명하게 제공함으로써 공공의 건강 및 안전을 유지하는 데 도움이 됩니다. 또한, 담배 소매인이 위치한 지역의 흡연 행태와 관련된 데이터를 분석하는 데 활용될 수 있습니다. 이 데이터셋은 공공정책 수립, 보건정책 개선, 담배 규제 강화 등 다양한 분야에서 유용하게 활용될 수 있습니다.
Author전라남도 구례군
URLhttps://www.data.go.kr/data/15021289/fileData.do

Alerts

시군 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연락처 has 42 (28.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:50:40.802335
Analysis finished2024-03-23 05:50:42.982826
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75
Minimum1
Maximum149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-23T05:50:43.241945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q138
median75
Q3112
95-th percentile141.6
Maximum149
Range148
Interquartile range (IQR)74

Descriptive statistics

Standard deviation43.156691
Coefficient of variation (CV)0.57542255
Kurtosis-1.2
Mean75
Median Absolute Deviation (MAD)37
Skewness0
Sum11175
Variance1862.5
MonotonicityStrictly increasing
2024-03-23T05:50:43.796666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
Other values (139) 139
93.3%
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 (%)
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
전라남도 구례군
149 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라남도 구례군
2nd row전라남도 구례군
3rd row전라남도 구례군
4th row전라남도 구례군
5th row전라남도 구례군

Common Values

ValueCountFrequency (%)
전라남도 구례군 149
100.0%

Length

2024-03-23T05:50:44.222977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:50:44.575783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 149
50.0%
구례군 149
50.0%

업소명
Text

Distinct148
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-23T05:50:45.458731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.9597315
Min length2

Characters and Unicode

Total characters888
Distinct characters227
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

Unique147 ?
Unique (%)98.7%

Sample

1st row평도슈퍼
2nd row세븐일레븐 구례봉동점
3rd row구례라임씨협동조합
4th row이마트24구례광의점
5th row동해국수
ValueCountFrequency (%)
세븐일레븐 7
 
4.0%
섬진강 3
 
1.7%
삼성마트 2
 
1.1%
이마트24 2
 
1.1%
지리산온천점 2
 
1.1%
하나로마트 2
 
1.1%
구례축협하나로마트 1
 
0.6%
제일수퍼 1
 
0.6%
이촌 1
 
0.6%
보배네슈퍼 1
 
0.6%
Other values (154) 154
87.5%
2024-03-23T05:50:46.858043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 35
 
3.9%
퍼 32
 
3.6%
슈 29
 
3.3%
점 28
 
3.2%
27
 
3.0%
마 24
 
2.7%
상 23
 
2.6%
례 23
 
2.6%
회 21
 
2.4%
트 20
 
2.3%
Other values (217) 626
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 823
92.7%
Space Separator 27
 
3.0%
Decimal Number 18
 
2.0%
Uppercase Letter 12
 
1.4%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 35
 
4.3%
퍼 32
 
3.9%
슈 29
 
3.5%
점 28
 
3.4%
마 24
 
2.9%
상 23
 
2.8%
례 23
 
2.8%
회 21
 
2.6%
트 20
 
2.4%
지 16
 
1.9%
Other values (205) 572
69.5%
Uppercase Letter
ValueCountFrequency (%)
G 4
33.3%
S 3
25.0%
C 2
16.7%
U 2
16.7%
R 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
4 5
27.8%
5 4
22.2%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 823
92.7%
Common 53
 
6.0%
Latin 12
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 35
 
4.3%
퍼 32
 
3.9%
슈 29
 
3.5%
점 28
 
3.4%
마 24
 
2.9%
상 23
 
2.8%
례 23
 
2.8%
회 21
 
2.6%
트 20
 
2.4%
지 16
 
1.9%
Other values (205) 572
69.5%
Common
ValueCountFrequency (%)
27
50.9%
2 9
 
17.0%
4 5
 
9.4%
5 4
 
7.5%
) 3
 
5.7%
( 3
 
5.7%
. 2
 
3.8%
Latin
ValueCountFrequency (%)
G 4
33.3%
S 3
25.0%
C 2
16.7%
U 2
16.7%
R 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 823
92.7%
ASCII 65
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 35
 
4.3%
퍼 32
 
3.9%
슈 29
 
3.5%
점 28
 
3.4%
마 24
 
2.9%
상 23
 
2.8%
례 23
 
2.8%
회 21
 
2.6%
트 20
 
2.4%
지 16
 
1.9%
Other values (205) 572
69.5%
ASCII
ValueCountFrequency (%)
27
41.5%
2 9
 
13.8%
4 5
 
7.7%
G 4
 
6.2%
5 4
 
6.2%
) 3
 
4.6%
S 3
 
4.6%
( 3
 
4.6%
. 2
 
3.1%
C 2
 
3.1%
Other values (2) 3
 
4.6%

대표자
Text

Distinct145
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-23T05:50:47.792031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.2684564
Min length2

Characters and Unicode

Total characters487
Distinct characters146
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

Unique141 ?
Unique (%)94.6%

Sample

1st row정금순
2nd row박미선
3rd row박선조
4th row정인자
5th row정태연
ValueCountFrequency (%)
이현옥 2
 
1.3%
김옥자 2
 
1.3%
노성원 2
 
1.3%
박민자 2
 
1.3%
이해순 1
 
0.7%
배일선 1
 
0.7%
김정아 1
 
0.7%
최인환 1
 
0.7%
정금순 1
 
0.7%
최화자 1
 
0.7%
Other values (138) 138
90.8%
2024-03-23T05:50:49.282993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 25
 
5.1%
이 22
 
4.5%
순 18
 
3.7%
박 16
 
3.3%
자 16
 
3.3%
정 15
 
3.1%
영 14
 
2.9%
옥 11
 
2.3%
최 11
 
2.3%
선 10
 
2.1%
Other values (136) 329
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 482
99.0%
Space Separator 3
 
0.6%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 25
 
5.2%
이 22
 
4.6%
순 18
 
3.7%
박 16
 
3.3%
자 16
 
3.3%
정 15
 
3.1%
영 14
 
2.9%
옥 11
 
2.3%
최 11
 
2.3%
선 10
 
2.1%
Other values (133) 324
67.2%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 482
99.0%
Common 5
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 25
 
5.2%
이 22
 
4.6%
순 18
 
3.7%
박 16
 
3.3%
자 16
 
3.3%
정 15
 
3.1%
영 14
 
2.9%
옥 11
 
2.3%
최 11
 
2.3%
선 10
 
2.1%
Other values (133) 324
67.2%
Common
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 482
99.0%
ASCII 5
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 25
 
5.2%
이 22
 
4.6%
순 18
 
3.7%
박 16
 
3.3%
자 16
 
3.3%
정 15
 
3.1%
영 14
 
2.9%
옥 11
 
2.3%
최 11
 
2.3%
선 10
 
2.1%
Other values (133) 324
67.2%
ASCII
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%

소재지
Text

Distinct147
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-23T05:50:50.284887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length34
Mean length22.013423
Min length18

Characters and Unicode

Total characters3280
Distinct characters148
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145 ?
Unique (%)97.3%

Sample

1st row전라남도 구례군 토지면 피아골로 668
2nd row전라남도 구례군 구례읍 봉성산길 2
3rd row전라남도 구례군 마산면 화엄사로 12. C동 1층
4th row전라남도 구례군 광의면 광의철쭉동산로 2
5th row전라남도 구례군 문척면 동해벚꽃로 383
ValueCountFrequency (%)
전라남도 149
19.3%
구례군 149
19.3%
구례읍 63
 
8.1%
산동면 26
 
3.4%
토지면 21
 
2.7%
마산면 15
 
1.9%
지리산온천로 9
 
1.2%
문척면 7
 
0.9%
중앙로 7
 
0.9%
26 7
 
0.9%
Other values (222) 321
41.5%
2024-03-23T05:50:51.795193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
672
20.5%
구 225
 
6.9%
례 221
 
6.7%
전 162
 
4.9%
남 150
 
4.6%
도 150
 
4.6%
군 150
 
4.6%
라 149
 
4.5%
1 89
 
2.7%
면 87
 
2.7%
Other values (138) 1225
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2148
65.5%
Space Separator 672
 
20.5%
Decimal Number 404
 
12.3%
Dash Punctuation 26
 
0.8%
Other Punctuation 18
 
0.5%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 225
 
10.5%
례 221
 
10.3%
전 162
 
7.5%
남 150
 
7.0%
도 150
 
7.0%
군 150
 
7.0%
라 149
 
6.9%
면 87
 
4.1%
산 70
 
3.3%
로 67
 
3.1%
Other values (120) 717
33.4%
Decimal Number
ValueCountFrequency (%)
1 89
22.0%
2 64
15.8%
3 43
10.6%
4 42
10.4%
6 37
9.2%
5 35
 
8.7%
7 29
 
7.2%
0 23
 
5.7%
9 21
 
5.2%
8 21
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
B 1
25.0%
U 1
25.0%
Space Separator
ValueCountFrequency (%)
672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
. 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2148
65.5%
Common 1128
34.4%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 225
 
10.5%
례 221
 
10.3%
전 162
 
7.5%
남 150
 
7.0%
도 150
 
7.0%
군 150
 
7.0%
라 149
 
6.9%
면 87
 
4.1%
산 70
 
3.3%
로 67
 
3.1%
Other values (120) 717
33.4%
Common
ValueCountFrequency (%)
672
59.6%
1 89
 
7.9%
2 64
 
5.7%
3 43
 
3.8%
4 42
 
3.7%
6 37
 
3.3%
5 35
 
3.1%
7 29
 
2.6%
- 26
 
2.3%
0 23
 
2.0%
Other values (5) 68
 
6.0%
Latin
ValueCountFrequency (%)
C 2
50.0%
B 1
25.0%
U 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2148
65.5%
ASCII 1132
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
672
59.4%
1 89
 
7.9%
2 64
 
5.7%
3 43
 
3.8%
4 42
 
3.7%
6 37
 
3.3%
5 35
 
3.1%
7 29
 
2.6%
- 26
 
2.3%
0 23
 
2.0%
Other values (8) 72
 
6.4%
Hangul
ValueCountFrequency (%)
구 225
 
10.5%
례 221
 
10.3%
전 162
 
7.5%
남 150
 
7.0%
도 150
 
7.0%
군 150
 
7.0%
라 149
 
6.9%
면 87
 
4.1%
산 70
 
3.3%
로 67
 
3.1%
Other values (120) 717
33.4%

연락처
Text

MISSING 

Distinct97
Distinct (%)90.7%
Missing42
Missing (%)28.2%
Memory size1.3 KiB
2024-03-23T05:50:52.745018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.962617
Min length1

Characters and Unicode

Total characters1173
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)88.8%

Sample

1st row061-937-9989
2nd row061-781-3232
3rd row061-896-6129
4th row061-390-4901
5th row061-782-2357
ValueCountFrequency (%)
061 7
 
6.7%
061-783-5522 2
 
1.9%
061-782-9148 1
 
1.0%
061-782-7259 1
 
1.0%
061-783-0807 1
 
1.0%
061-782-2609 1
 
1.0%
061-782-2043 1
 
1.0%
061-782-4788 1
 
1.0%
061-782-8515 1
 
1.0%
061-782-7490 1
 
1.0%
Other values (88) 88
83.8%
2024-03-23T05:50:54.118412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 184
15.7%
1 157
13.4%
0 151
12.9%
8 138
11.8%
6 131
11.2%
7 130
11.1%
2 89
7.6%
3 61
 
5.2%
5 44
 
3.8%
4 36
 
3.1%
Other values (2) 52
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 970
82.7%
Dash Punctuation 184
 
15.7%
Space Separator 19
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 157
16.2%
0 151
15.6%
8 138
14.2%
6 131
13.5%
7 130
13.4%
2 89
9.2%
3 61
 
6.3%
5 44
 
4.5%
4 36
 
3.7%
9 33
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 184
15.7%
1 157
13.4%
0 151
12.9%
8 138
11.8%
6 131
11.2%
7 130
11.1%
2 89
7.6%
3 61
 
5.2%
5 44
 
3.8%
4 36
 
3.1%
Other values (2) 52
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 184
15.7%
1 157
13.4%
0 151
12.9%
8 138
11.8%
6 131
11.2%
7 130
11.1%
2 89
7.6%
3 61
 
5.2%
5 44
 
3.8%
4 36
 
3.1%
Other values (2) 52
 
4.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-02-29
149 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-29
2nd row2024-02-29
3rd row2024-02-29
4th row2024-02-29
5th row2024-02-29

Common Values

ValueCountFrequency (%)
2024-02-29 149
100.0%

Length

2024-03-23T05:50:54.612397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:50:55.057365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-29 149
100.0%

Interactions

2024-03-23T05:50:41.881929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:50:55.356060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연락처
연번1.0000.966
연락처0.9661.000

Missing values

2024-03-23T05:50:42.339495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:50:42.843921image/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

연번시군업소명대표자소재지연락처데이터기준일자
01전라남도 구례군평도슈퍼정금순전라남도 구례군 토지면 피아골로 668<NA>2024-02-29
12전라남도 구례군세븐일레븐 구례봉동점박미선전라남도 구례군 구례읍 봉성산길 2<NA>2024-02-29
23전라남도 구례군구례라임씨협동조합박선조전라남도 구례군 마산면 화엄사로 12. C동 1층061-937-99892024-02-29
34전라남도 구례군이마트24구례광의점정인자전라남도 구례군 광의면 광의철쭉동산로 2<NA>2024-02-29
45전라남도 구례군동해국수정태연전라남도 구례군 문척면 동해벚꽃로 383<NA>2024-02-29
56전라남도 구례군하사슈퍼이경숙전라남도 구례군 마산면 당몰샘로 263<NA>2024-02-29
67전라남도 구례군함께혜윰장매화전라남도 구례군 용방면 용방로 117-53. 농협구례교육원<NA>2024-02-29
78전라남도 구례군한아름마트박상섭전라남도 구례군 광의면 구만제로 312. 한아름마트061-781-32322024-02-29
89전라남도 구례군이마트24 구례군청점김경식전라남도 구례군 구례읍 봉성로 12. 가동 1층<NA>2024-02-29
910전라남도 구례군오가닉메이커 구례자연드림파크점농업회사법인(주)해피푸르츠전라남도 구례군 용방면 용산로 107-73061-896-61292024-02-29
연번시군업소명대표자소재지연락처데이터기준일자
139140전라남도 구례군중앙농기구상회김중식전라남도 구례군 구례읍 봉동리 393-2호061-782-21642024-02-29
140141전라남도 구례군광신철물이민기전라남도 구례군 광의면 구만제로 342061-781-38012024-02-29
141142전라남도 구례군지리산온천주유소이성영전라남도 구례군 산동면 시상리 164-4호061-782-88382024-02-29
142143전라남도 구례군서종슈퍼박중귀전라남도 구례군 마산면 마산리 545호061-782-69082024-02-29
143144전라남도 구례군백련상회이영옥전라남도 구례군 구례읍 백련리 463호061-782-65242024-02-29
144145전라남도 구례군중동상회이양순전라남도 구례군 산동면 관산리 517호061-783-18532024-02-29
145146전라남도 구례군신촌슈퍼김효순전라남도 구례군 구례읍 신촌길 4061-782-57112024-02-29
146147전라남도 구례군중동구판장임병구전라남도 구례군 산동면 좌사리 8-6호061-783-13332024-02-29
147148전라남도 구례군반내골슈퍼전순례전라남도 구례군 문척면 중산리 329061-781-55812024-02-29
148149전라남도 구례군하신구판장박만도전라남도 구례군 산동면 신학리 90061-782-70472024-02-29