Overview

Dataset statistics

Number of variables19
Number of observations60
Missing cells29
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory162.2 B

Variable types

Numeric5
Categorical7
Text5
DateTime2

Dataset

Description전라남도 고흥군 약국 현황에 대한 데이터로 관리번호, 상세영업상태명, 소재지전체주소, 사업장명, 약국영업면적, 지정일자 등을 제공합니다.
Author전라남도 고흥군
URLhttps://www.data.go.kr/data/15090515/fileData.do

Alerts

개방서비스명 has constant value ""Constant
개방서비스 아이디 has constant value ""Constant
개방자치단체코드 has constant value ""Constant
상세영업상태명 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
영업상태명 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
영업상태구분코드 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
상세영업상태코드 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
번호 is highly overall correlated with 도로명우편번호 and 4 other fieldsHigh correlation
도로명우편번호 is highly overall correlated with 번호 and 6 other fieldsHigh correlation
좌표정보(x) is highly overall correlated with 도로명우편번호 and 1 other fieldsHigh correlation
좌표정보(y) is highly overall correlated with 도로명우편번호 and 1 other fieldsHigh correlation
소재지전화 has 3 (5.0%) missing valuesMissing
소재지전체주소 has 23 (38.3%) missing valuesMissing
도로명우편번호 has 3 (5.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:22:23.789075
Analysis finished2023-12-12 20:22:27.978834
Duration4.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T05:22:28.069667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2023-12-13T05:22:28.219193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
약국
60 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
약국 60
100.0%

Length

2023-12-13T05:22:28.358330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:28.452328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
약국 60
100.0%

개방서비스 아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
01_01_06_P
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_01_06_P
2nd row01_01_06_P
3rd row01_01_06_P
4th row01_01_06_P
5th row01_01_06_P

Common Values

ValueCountFrequency (%)
01_01_06_P 60
100.0%

Length

2023-12-13T05:22:28.580236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:28.697811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_01_06_p 60
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
4880000
60 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4880000
2nd row4880000
3rd row4880000
4th row4880000
5th row4880000

Common Values

ValueCountFrequency (%)
4880000 60
100.0%

Length

2023-12-13T05:22:28.825303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:28.937007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4880000 60
100.0%

관리번호
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T05:22:29.151334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1500
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st rowPHMD120194880017084000001
2nd rowPHMD120194880017084000002
3rd rowPHMD120194880017084000003
4th rowPHMD119664880017084000001
5th rowPHMD119714880017084000001
ValueCountFrequency (%)
phmd120194880017084000001 1
 
1.7%
phmd120194880017084000002 1
 
1.7%
phmd120104880017084000005 1
 
1.7%
phmd120204880017084000001 1
 
1.7%
phmd120184880017084000001 1
 
1.7%
phmd119654880017084000001 1
 
1.7%
phmd119714880017084000002 1
 
1.7%
phmd120054880017084000001 1
 
1.7%
phmd120064880017084000001 1
 
1.7%
phmd120074880017084000004 1
 
1.7%
Other values (50) 50
83.3%
2023-12-13T05:22:29.578777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 558
37.2%
1 192
 
12.8%
8 186
 
12.4%
4 128
 
8.5%
2 71
 
4.7%
7 69
 
4.6%
P 60
 
4.0%
H 60
 
4.0%
M 60
 
4.0%
D 60
 
4.0%
Other values (4) 56
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1260
84.0%
Uppercase Letter 240
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 558
44.3%
1 192
 
15.2%
8 186
 
14.8%
4 128
 
10.2%
2 71
 
5.6%
7 69
 
5.5%
9 18
 
1.4%
3 14
 
1.1%
5 14
 
1.1%
6 10
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 60
25.0%
H 60
25.0%
M 60
25.0%
D 60
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1260
84.0%
Latin 240
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 558
44.3%
1 192
 
15.2%
8 186
 
14.8%
4 128
 
10.2%
2 71
 
5.6%
7 69
 
5.5%
9 18
 
1.4%
3 14
 
1.1%
5 14
 
1.1%
6 10
 
0.8%
Latin
ValueCountFrequency (%)
P 60
25.0%
H 60
25.0%
M 60
25.0%
D 60
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 558
37.2%
1 192
 
12.8%
8 186
 
12.4%
4 128
 
8.5%
2 71
 
4.7%
7 69
 
4.6%
P 60
 
4.0%
H 60
 
4.0%
M 60
 
4.0%
D 60
 
4.0%
Other values (4) 56
 
3.7%

인허가일자
Date

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum1965-08-26 00:00:00
Maximum2020-12-30 00:00:00
2023-12-13T05:22:29.747725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:29.895857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
1
33 
3
27 

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 33
55.0%
3 27
45.0%

Length

2023-12-13T05:22:30.028497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:30.127883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 33
55.0%
3 27
45.0%

영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
영업/정상
33 
폐업
27 

Length

Max length5
Median length5
Mean length3.65
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 33
55.0%
폐업 27
45.0%

Length

2023-12-13T05:22:30.231541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:30.342134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 33
55.0%
폐업 27
45.0%

상세영업상태코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
13
33 
3
27 

Length

Max length2
Median length2
Mean length1.55
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 33
55.0%
3 27
45.0%

Length

2023-12-13T05:22:30.483094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:30.590299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 33
55.0%
3 27
45.0%

상세영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
영업중
33 
폐업
27 

Length

Max length3
Median length3
Mean length2.55
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 33
55.0%
폐업 27
45.0%

Length

2023-12-13T05:22:30.686806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:31.057357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 33
55.0%
폐업 27
45.0%

소재지전화
Text

MISSING 

Distinct40
Distinct (%)70.2%
Missing3
Missing (%)5.0%
Memory size612.0 B
2023-12-13T05:22:31.261073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters684
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

Unique28 ?
Unique (%)49.1%

Sample

1st row061-835-5506
2nd row061-835-8850
3rd row061-834-1994
4th row061-843-1012
5th row061-842-2370
ValueCountFrequency (%)
061-834-3543 4
 
7.0%
061-835-5506 3
 
5.3%
061-842-0572 3
 
5.3%
061-844-3031 3
 
5.3%
061-843-1110 2
 
3.5%
061-832-3070 2
 
3.5%
061-832-0404 2
 
3.5%
061-833-5552 2
 
3.5%
061-833-7733 2
 
3.5%
061-842-8111 2
 
3.5%
Other values (30) 32
56.1%
2023-12-13T05:22:31.587697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 114
16.7%
0 94
13.7%
3 86
12.6%
1 85
12.4%
8 70
10.2%
6 63
9.2%
4 51
7.5%
2 47
6.9%
5 43
 
6.3%
7 18
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 570
83.3%
Dash Punctuation 114
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
16.5%
3 86
15.1%
1 85
14.9%
8 70
12.3%
6 63
11.1%
4 51
8.9%
2 47
8.2%
5 43
7.5%
7 18
 
3.2%
9 13
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 684
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 114
16.7%
0 94
13.7%
3 86
12.6%
1 85
12.4%
8 70
10.2%
6 63
9.2%
4 51
7.5%
2 47
6.9%
5 43
 
6.3%
7 18
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 114
16.7%
0 94
13.7%
3 86
12.6%
1 85
12.4%
8 70
10.2%
6 63
9.2%
4 51
7.5%
2 47
6.9%
5 43
 
6.3%
7 18
 
2.6%

소재지전체주소
Text

MISSING 

Distinct35
Distinct (%)94.6%
Missing23
Missing (%)38.3%
Memory size612.0 B
2023-12-13T05:22:31.824816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length23.432432
Min length16

Characters and Unicode

Total characters867
Distinct characters58
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

Unique33 ?
Unique (%)89.2%

Sample

1st row전라남도 고흥군 도덕면 도덕리 52
2nd row전라남도 고흥군 도양읍 봉암리 2072-6
3rd row전라남도 고흥군 고흥읍 남계리 969-9
4th row전라남도 고흥군 도화면 당오리 522-1
5th row전라남도 고흥군 포두면 길두리 1342-44
ValueCountFrequency (%)
전라남도 37
18.5%
고흥군 37
18.5%
고흥읍 15
 
7.5%
남계리 7
 
3.5%
도양읍 7
 
3.5%
서문리 7
 
3.5%
봉암리 6
 
3.0%
유둔리 4
 
2.0%
동강면 4
 
2.0%
과역리 3
 
1.5%
Other values (65) 73
36.5%
2023-12-13T05:22:32.143876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
18.8%
흥 53
 
6.1%
고 52
 
6.0%
도 47
 
5.4%
남 44
 
5.1%
전 37
 
4.3%
군 37
 
4.3%
라 37
 
4.3%
리 37
 
4.3%
2 35
 
4.0%
Other values (48) 325
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 532
61.4%
Space Separator 163
 
18.8%
Decimal Number 157
 
18.1%
Dash Punctuation 15
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
흥 53
 
10.0%
고 52
 
9.8%
도 47
 
8.8%
남 44
 
8.3%
전 37
 
7.0%
군 37
 
7.0%
라 37
 
7.0%
리 37
 
7.0%
읍 22
 
4.1%
호 17
 
3.2%
Other values (36) 149
28.0%
Decimal Number
ValueCountFrequency (%)
2 35
22.3%
1 32
20.4%
9 16
10.2%
6 15
9.6%
8 14
 
8.9%
5 12
 
7.6%
3 10
 
6.4%
4 10
 
6.4%
7 9
 
5.7%
0 4
 
2.5%
Space Separator
ValueCountFrequency (%)
163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 532
61.4%
Common 335
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
흥 53
 
10.0%
고 52
 
9.8%
도 47
 
8.8%
남 44
 
8.3%
전 37
 
7.0%
군 37
 
7.0%
라 37
 
7.0%
리 37
 
7.0%
읍 22
 
4.1%
호 17
 
3.2%
Other values (36) 149
28.0%
Common
ValueCountFrequency (%)
163
48.7%
2 35
 
10.4%
1 32
 
9.6%
9 16
 
4.8%
6 15
 
4.5%
- 15
 
4.5%
8 14
 
4.2%
5 12
 
3.6%
3 10
 
3.0%
4 10
 
3.0%
Other values (2) 13
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 532
61.4%
ASCII 335
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
48.7%
2 35
 
10.4%
1 32
 
9.6%
9 16
 
4.8%
6 15
 
4.5%
- 15
 
4.5%
8 14
 
4.2%
5 12
 
3.6%
3 10
 
3.0%
4 10
 
3.0%
Other values (2) 13
 
3.9%
Hangul
ValueCountFrequency (%)
흥 53
 
10.0%
고 52
 
9.8%
도 47
 
8.8%
남 44
 
8.3%
전 37
 
7.0%
군 37
 
7.0%
라 37
 
7.0%
리 37
 
7.0%
읍 22
 
4.1%
호 17
 
3.2%
Other values (36) 149
28.0%

도로명전체주소
Text

Distinct42
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T05:22:32.347187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length21.366667
Min length19

Characters and Unicode

Total characters1282
Distinct characters82
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)53.3%

Sample

1st row전라남도 고흥군 동강면 고흥로 4265, 기타일반업무시설
2nd row전라남도 고흥군 고흥읍 서문여산길 76
3rd row전라남도 고흥군 고흥읍 터미널길 3
4th row전라남도 고흥군 도덕면 학동2길 6
5th row전라남도 고흥군 도양읍 비봉로 153
ValueCountFrequency (%)
전라남도 60
19.9%
고흥군 60
19.9%
고흥읍 26
 
8.6%
도양읍 15
 
5.0%
여산당촌길 13
 
4.3%
고흥로 9
 
3.0%
13-1 5
 
1.7%
금산면 5
 
1.7%
동강면 5
 
1.7%
거금중앙길 4
 
1.3%
Other values (66) 99
32.9%
2023-12-13T05:22:32.658580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
241
18.8%
고 95
 
7.4%
흥 95
 
7.4%
도 77
 
6.0%
남 66
 
5.1%
전 60
 
4.7%
군 60
 
4.7%
라 60
 
4.7%
길 46
 
3.6%
1 43
 
3.4%
Other values (72) 439
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 861
67.2%
Space Separator 241
 
18.8%
Decimal Number 163
 
12.7%
Dash Punctuation 16
 
1.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 95
 
11.0%
흥 95
 
11.0%
도 77
 
8.9%
남 66
 
7.7%
전 60
 
7.0%
군 60
 
7.0%
라 60
 
7.0%
길 46
 
5.3%
읍 41
 
4.8%
동 19
 
2.2%
Other values (59) 242
28.1%
Decimal Number
ValueCountFrequency (%)
1 43
26.4%
2 29
17.8%
3 20
12.3%
7 14
 
8.6%
8 13
 
8.0%
5 12
 
7.4%
4 12
 
7.4%
9 11
 
6.7%
6 7
 
4.3%
0 2
 
1.2%
Space Separator
ValueCountFrequency (%)
241
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 861
67.2%
Common 421
32.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 95
 
11.0%
흥 95
 
11.0%
도 77
 
8.9%
남 66
 
7.7%
전 60
 
7.0%
군 60
 
7.0%
라 60
 
7.0%
길 46
 
5.3%
읍 41
 
4.8%
동 19
 
2.2%
Other values (59) 242
28.1%
Common
ValueCountFrequency (%)
241
57.2%
1 43
 
10.2%
2 29
 
6.9%
3 20
 
4.8%
- 16
 
3.8%
7 14
 
3.3%
8 13
 
3.1%
5 12
 
2.9%
4 12
 
2.9%
9 11
 
2.6%
Other values (3) 10
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 861
67.2%
ASCII 421
32.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
241
57.2%
1 43
 
10.2%
2 29
 
6.9%
3 20
 
4.8%
- 16
 
3.8%
7 14
 
3.3%
8 13
 
3.1%
5 12
 
2.9%
4 12
 
2.9%
9 11
 
2.6%
Other values (3) 10
 
2.4%
Hangul
ValueCountFrequency (%)
고 95
 
11.0%
흥 95
 
11.0%
도 77
 
8.9%
남 66
 
7.7%
전 60
 
7.0%
군 60
 
7.0%
라 60
 
7.0%
길 46
 
5.3%
읍 41
 
4.8%
동 19
 
2.2%
Other values (59) 242
28.1%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct24
Distinct (%)42.1%
Missing3
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean188308.46
Minimum59502
Maximum548936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T05:22:32.768976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59502
5-th percentile59502
Q159540
median59546
Q3548802
95-th percentile548907
Maximum548936
Range489434
Interquartile range (IQR)489262

Descriptive statistics

Standard deviation217385.41
Coefficient of variation (CV)1.1544113
Kurtosis-0.80861932
Mean188308.46
Median Absolute Deviation (MAD)12
Skewness1.1049999
Sum10733582
Variance4.7256418 × 1010
MonotonicityNot monotonic
2023-12-13T05:22:32.863853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
59540 11
18.3%
59543 5
 
8.3%
59502 4
 
6.7%
548805 4
 
6.7%
59558 4
 
6.7%
59557 3
 
5.0%
548905 3
 
5.0%
59564 3
 
5.0%
59537 2
 
3.3%
548802 2
 
3.3%
Other values (14) 16
26.7%
(Missing) 3
 
5.0%
ValueCountFrequency (%)
59502 4
 
6.7%
59507 1
 
1.7%
59511 1
 
1.7%
59524 1
 
1.7%
59529 1
 
1.7%
59535 2
 
3.3%
59537 2
 
3.3%
59540 11
18.3%
59543 5
8.3%
59546 1
 
1.7%
ValueCountFrequency (%)
548936 1
 
1.7%
548931 1
 
1.7%
548907 2
3.3%
548905 3
5.0%
548851 1
 
1.7%
548812 1
 
1.7%
548805 4
6.7%
548802 2
3.3%
59569 1
 
1.7%
59564 3
5.0%

사업장명
Text

Distinct43
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-13T05:22:33.036423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.5
Min length3

Characters and Unicode

Total characters270
Distinct characters81
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

Unique30 ?
Unique (%)50.0%

Sample

1st row고흥약국
2nd row우리약국
3rd row길약국
4th row대성약국
5th row신약국
ValueCountFrequency (%)
광주약국 4
 
6.6%
고흥약국 3
 
4.9%
서울약국 3
 
4.9%
장수약국 3
 
4.9%
국도약국 2
 
3.3%
태광약국 2
 
3.3%
우리약국 2
 
3.3%
백화당약국 2
 
3.3%
온누리대성약국 2
 
3.3%
금산약국 2
 
3.3%
Other values (33) 36
59.0%
2023-12-13T05:22:33.365325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 62
23.0%
약 60
22.2%
광 6
 
2.2%
리 6
 
2.2%
화 6
 
2.2%
서 4
 
1.5%
울 4
 
1.5%
주 4
 
1.5%
성 4
 
1.5%
누 4
 
1.5%
Other values (71) 110
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 269
99.6%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 62
23.0%
약 60
22.3%
광 6
 
2.2%
리 6
 
2.2%
화 6
 
2.2%
서 4
 
1.5%
울 4
 
1.5%
주 4
 
1.5%
성 4
 
1.5%
누 4
 
1.5%
Other values (70) 109
40.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 269
99.6%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 62
23.0%
약 60
22.3%
광 6
 
2.2%
리 6
 
2.2%
화 6
 
2.2%
서 4
 
1.5%
울 4
 
1.5%
주 4
 
1.5%
성 4
 
1.5%
누 4
 
1.5%
Other values (70) 109
40.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 269
99.6%
ASCII 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 62
23.0%
약 60
22.3%
광 6
 
2.2%
리 6
 
2.2%
화 6
 
2.2%
서 4
 
1.5%
울 4
 
1.5%
주 4
 
1.5%
성 4
 
1.5%
누 4
 
1.5%
Other values (70) 109
40.5%
ASCII
ValueCountFrequency (%)
1
100.0%

좌표정보(x)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean222654.42
Minimum211306.42
Maximum242136.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T05:22:33.479236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum211306.42
5-th percentile211306.42
Q1212638.41
median225751.11
Q3226522.24
95-th percentile233034.52
Maximum242136.79
Range30830.372
Interquartile range (IQR)13883.823

Descriptive statistics

Standard deviation7887.0947
Coefficient of variation (CV)0.035423033
Kurtosis-0.95608924
Mean222654.42
Median Absolute Deviation (MAD)4643.8532
Skewness-0.17025597
Sum13359265
Variance62206262
MonotonicityNot monotonic
2023-12-13T05:22:33.604188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
225751.1137 6
 
10.0%
211306.4181 4
 
6.7%
225696.7427 4
 
6.7%
212388.6886 3
 
5.0%
212317.1703 3
 
5.0%
230394.9669 2
 
3.3%
213286.7488 2
 
3.3%
226955.1953 2
 
3.3%
233032.1705 2
 
3.3%
226065.1479 2
 
3.3%
Other values (30) 30
50.0%
ValueCountFrequency (%)
211306.4181 4
6.7%
212317.1703 3
5.0%
212332.0055 1
 
1.7%
212337.4927 1
 
1.7%
212358.092 1
 
1.7%
212367.2492 1
 
1.7%
212388.6886 3
5.0%
212605.7073 1
 
1.7%
212649.3172 1
 
1.7%
213285.4703 1
 
1.7%
ValueCountFrequency (%)
242136.7898 1
1.7%
234834.9447 1
1.7%
233079.227 1
1.7%
233032.1705 2
3.3%
231106.564 1
1.7%
230462.7735 1
1.7%
230421.1706 1
1.7%
230394.9669 2
3.3%
230389.7262 1
1.7%
229220.3706 1
1.7%

좌표정보(y)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121587.89
Minimum104077.86
Maximum142442.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T05:22:33.717854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104077.86
5-th percentile106735.03
Q1114422.11
median123257.59
Q3123360.65
95-th percentile142416.17
Maximum142442.4
Range38364.547
Interquartile range (IQR)8938.5353

Descriptive statistics

Standard deviation9367.7101
Coefficient of variation (CV)0.077044765
Kurtosis0.49572504
Mean121587.89
Median Absolute Deviation (MAD)6809.9657
Skewness0.62704947
Sum7295273.2
Variance87753993
MonotonicityNot monotonic
2023-12-13T05:22:33.838168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
123265.5629 6
 
10.0%
106735.0266 4
 
6.7%
123257.5906 4
 
6.7%
114210.5685 3
 
5.0%
114422.1114 3
 
5.0%
142419.3273 2
 
3.3%
116447.6249 2
 
3.3%
124881.3159 2
 
3.3%
131307.4815 2
 
3.3%
123366.1137 2
 
3.3%
Other values (30) 30
50.0%
ValueCountFrequency (%)
104077.8566 1
 
1.7%
106735.0266 4
6.7%
107460.6267 1
 
1.7%
112474.2228 1
 
1.7%
114210.5685 3
5.0%
114362.8015 1
 
1.7%
114408.2442 1
 
1.7%
114419.7781 1
 
1.7%
114420.5443 1
 
1.7%
114422.1114 3
5.0%
ValueCountFrequency (%)
142442.4033 1
1.7%
142419.3273 2
3.3%
142416.0029 1
1.7%
142372.29 1
1.7%
141590.8191 1
1.7%
131307.4815 2
3.3%
131143.9299 1
1.7%
128566.5554 1
1.7%
124881.3159 2
3.3%
123395.5183 1
1.7%

약국영업면적
Real number (ℝ)

Distinct35
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.849833
Minimum14
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T05:22:33.967694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile19.8265
Q133
median45.13
Q359.25
95-th percentile147.9725
Maximum193
Range179
Interquartile range (IQR)26.25

Descriptive statistics

Standard deviation37.376035
Coefficient of variation (CV)0.66922375
Kurtosis3.3532425
Mean55.849833
Median Absolute Deviation (MAD)12.13
Skewness1.8402376
Sum3350.99
Variance1396.968
MonotonicityNot monotonic
2023-12-13T05:22:34.091321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
33.0 7
 
11.7%
49.6 4
 
6.7%
99.2 3
 
5.0%
52.0 3
 
5.0%
29.75 3
 
5.0%
39.7 3
 
5.0%
43.84 2
 
3.3%
86.55 2
 
3.3%
36.37 2
 
3.3%
26.44 2
 
3.3%
Other values (25) 29
48.3%
ValueCountFrequency (%)
14.0 1
 
1.7%
16.5 1
 
1.7%
16.53 1
 
1.7%
20.0 2
 
3.3%
20.7 1
 
1.7%
26.44 2
 
3.3%
29.75 3
5.0%
33.0 7
11.7%
36.0 1
 
1.7%
36.37 2
 
3.3%
ValueCountFrequency (%)
193.0 1
 
1.7%
156.0 2
3.3%
147.55 1
 
1.7%
115.7 1
 
1.7%
106.82 1
 
1.7%
99.2 3
5.0%
86.55 2
3.3%
84.78 1
 
1.7%
82.5 1
 
1.7%
66.0 1
 
1.7%

지정일자
Date

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum1965-08-26 00:00:00
Maximum2020-12-30 00:00:00
2023-12-13T05:22:34.244231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:34.374660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T05:22:26.754649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:24.776535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.267988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.709008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.258701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.871678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:24.874224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.350288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.819463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.363676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.967468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:24.964517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.426057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.923856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.455168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:27.082543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.075314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.513658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.023274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.550810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:27.202776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.178314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:25.611263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.125013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:26.650480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:22:34.477285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호관리번호인허가일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명소재지전화소재지전체주소도로명전체주소도로명우편번호사업장명좌표정보(x)좌표정보(y)약국영업면적지정일자
번호1.0001.0001.0000.9950.9950.9950.9950.0000.9290.0000.8530.3080.0000.0000.4751.000
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0001.0001.0001.0001.0001.0000.9940.9800.9951.0000.9950.9160.7840.8051.000
영업상태구분코드0.9951.0001.0001.0000.9990.9990.9990.0001.0000.0000.8210.0000.0000.0000.2591.000
영업상태명0.9951.0001.0000.9991.0000.9990.9990.0001.0000.0000.8210.0000.0000.0000.2591.000
상세영업상태코드0.9951.0001.0000.9990.9991.0000.9990.0001.0000.0000.8210.0000.0000.0000.2591.000
상세영업상태명0.9951.0001.0000.9990.9990.9991.0000.0001.0000.0000.8210.0000.0000.0000.2591.000
소재지전화0.0001.0000.9940.0000.0000.0000.0001.0000.9890.9970.0000.9961.0000.9960.9200.994
소재지전체주소0.9291.0000.9801.0001.0001.0001.0000.9891.0000.9971.0000.9771.0001.0001.0000.980
도로명전체주소0.0001.0000.9950.0000.0000.0000.0000.9970.9971.0000.0000.9871.0001.0000.9020.995
도로명우편번호0.8531.0001.0000.8210.8210.8210.8210.0001.0000.0001.0000.0000.0000.0000.3321.000
사업장명0.3081.0000.9950.0000.0000.0000.0000.9960.9770.9870.0001.0000.9860.9580.9080.995
좌표정보(x)0.0001.0000.9160.0000.0000.0000.0001.0001.0001.0000.0000.9861.0000.9000.4480.916
좌표정보(y)0.0001.0000.7840.0000.0000.0000.0000.9961.0001.0000.0000.9580.9001.0000.4760.784
약국영업면적0.4751.0000.8050.2590.2590.2590.2590.9201.0000.9020.3320.9080.4480.4761.0000.805
지정일자1.0001.0001.0001.0001.0001.0001.0000.9940.9800.9951.0000.9950.9160.7840.8051.000
2023-12-13T05:22:34.628793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세영업상태명영업상태명영업상태구분코드상세영업상태코드
상세영업상태명1.0000.9660.9660.966
영업상태명0.9661.0000.9660.966
영업상태구분코드0.9660.9661.0000.966
상세영업상태코드0.9660.9660.9661.000
2023-12-13T05:22:34.738178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호도로명우편번호좌표정보(x)좌표정보(y)약국영업면적영업상태구분코드영업상태명상세영업상태코드상세영업상태명
번호1.0000.514-0.291-0.1260.0930.8710.8710.8710.871
도로명우편번호0.5141.000-0.573-0.5700.1880.6030.6030.6030.603
좌표정보(x)-0.291-0.5731.0000.764-0.2960.0000.0000.0000.000
좌표정보(y)-0.126-0.5700.7641.000-0.2580.0000.0000.0000.000
약국영업면적0.0930.188-0.296-0.2581.0000.1790.1790.1790.179
영업상태구분코드0.8710.6030.0000.0000.1791.0000.9660.9660.966
영업상태명0.8710.6030.0000.0000.1790.9661.0000.9660.966
상세영업상태코드0.8710.6030.0000.0000.1790.9660.9661.0000.966
상세영업상태명0.8710.6030.0000.0000.1790.9660.9660.9661.000

Missing values

2023-12-13T05:22:27.407330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:22:27.749645image/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.
2023-12-13T05:22:27.909519image/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

번호개방서비스명개방서비스 아이디개방자치단체코드관리번호인허가일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명소재지전화소재지전체주소도로명전체주소도로명우편번호사업장명좌표정보(x)좌표정보(y)약국영업면적지정일자
01약국01_01_06_P4880000PHMD1201948800170840000012019-03-251영업/정상13영업중061-835-5506<NA>전라남도 고흥군 동강면 고흥로 4265, 기타일반업무시설59502고흥약국230462.7735142442.403320.02019-03-25
12약국01_01_06_P4880000PHMD1201948800170840000022019-09-201영업/정상13영업중061-835-8850<NA>전라남도 고흥군 고흥읍 서문여산길 7659540우리약국225753.193123245.1169193.02019-09-20
23약국01_01_06_P4880000PHMD1201948800170840000032019-11-121영업/정상13영업중061-834-1994<NA>전라남도 고흥군 고흥읍 터미널길 359543길약국225777.3091123358.824459.02019-11-12
34약국01_01_06_P4880000PHMD1196648800170840000011966-10-281영업/정상13영업중061-843-1012전라남도 고흥군 도덕면 도덕리 52전라남도 고흥군 도덕면 학동2길 659546대성약국216032.3274118675.621316.51966-10-28
45약국01_01_06_P4880000PHMD1197148800170840000011971-07-281영업/정상13영업중061-842-2370전라남도 고흥군 도양읍 봉암리 2072-6전라남도 고흥군 도양읍 비봉로 15359558신약국212332.0055114362.801549.61971-07-28
56약국01_01_06_P4880000PHMD1197348800170840000011973-09-271영업/정상13영업중061-832-2167전라남도 고흥군 고흥읍 남계리 969-9전라남도 고흥군 고흥읍 학교길 6659537중앙약국226395.887123395.518329.751973-09-27
67약국01_01_06_P4880000PHMD1199248800170840000011992-09-031영업/정상13영업중061-833-8942전라남도 고흥군 도화면 당오리 522-1전라남도 고흥군 도화면 중심길 2759529강약국229220.3706112474.222842.971992-09-03
78약국01_01_06_P4880000PHMD1199448800170840000011994-07-291영업/정상13영업중061-834-7575전라남도 고흥군 포두면 길두리 1342-44전라남도 고흥군 포두면 우주로 58759524포두약국231106.564119377.099946.281994-07-29
89약국01_01_06_P4880000PHMD1199748800170840000011997-04-031영업/정상13영업중061-832-1991전라남도 고흥군 봉래면 신금리 878번지 463호전라남도 고흥군 봉래면 축정1길 10-859569건강약국242136.7898107460.626716.531997-04-03
910약국01_01_06_P4880000PHMD1200348800170840000022003-12-081영업/정상13영업중061-833-2060전라남도 고흥군 동강면 유둔리전라남도 고흥군 동강면 고흥로 426159502인애약국230421.1706142416.002933.02003-12-08
번호개방서비스명개방서비스 아이디개방자치단체코드관리번호인허가일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명소재지전화소재지전체주소도로명전체주소도로명우편번호사업장명좌표정보(x)좌표정보(y)약국영업면적지정일자
5051약국01_01_06_P4880000PHMD1201448800170840000022014-05-013폐업3폐업061-843-1110<NA>전라남도 고흥군 도양읍 녹동남문길 8-23548905유킹스파머시평화약국212317.1703114422.111499.22014-05-01
5152약국01_01_06_P4880000PHMD1201548800170840000012015-02-133폐업3폐업061-844-3031<NA>전라남도 고흥군 도양읍 차경구렁목길 225548907장수약국213286.7488116447.624986.552015-02-13
5253약국01_01_06_P4880000PHMD1201548800170840000022015-01-023폐업3폐업061-834-3543<NA>전라남도 고흥군 고흥읍 여산당촌길 13-1548805광주약국225751.1137123265.562929.752015-01-02
5354약국01_01_06_P4880000PHMD1201548800170840000052015-04-273폐업3폐업061-842-0572<NA>전라남도 고흥군 금산면 거금중앙길 7159564태광약국211306.4181106735.026652.02015-04-27
5455약국01_01_06_P4880000PHMD1201548800170840000072015-05-063폐업3폐업061-834-3543<NA>전라남도 고흥군 고흥읍 여산당촌길 13-159540광주약국225751.1137123265.562936.372015-05-06
5556약국01_01_06_P4880000PHMD1201048800170840000012010-02-013폐업3폐업061-832-1234전라남도 고흥군 과역면 과역리 168번지 9호전라남도 고흥군 과역면 고흥로 2989<NA>온누리대성약국233032.1705131307.481543.842010-02-01
5657약국01_01_06_P4880000PHMD1201048800170840000022010-02-013폐업3폐업061-832-0404전라남도 고흥군 고흥읍 남계리 629번지 6호전라남도 고흥군 고흥읍 봉황길 29548802백화당약국226065.1479123366.1137156.02010-02-01
5758약국01_01_06_P4880000PHMD1201048800170840000032010-04-283폐업3폐업061-835-3034전라남도 고흥군 고흥읍 서문리 218번지 11호전라남도 고흥군 고흥읍 여산당촌길 23548805새서울약국225696.7427123257.590636.02010-04-28
5859약국01_01_06_P4880000PHMD1201648800170840000022016-03-213폐업3폐업061-842-8111<NA>전라남도 고흥군 도양읍 녹동중앙길 5359558한길약국212388.6886114210.568539.392016-03-21
5960약국01_01_06_P4880000PHMD1201548800170840000042015-02-233폐업3폐업061-833-7733<NA>전라남도 고흥군 고흥읍 여산당촌길 13-159540밝은약국225751.1137123265.562926.442015-02-23