Overview

Dataset statistics

Number of variables19
Number of observations191
Missing cells230
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.7 KiB
Average record size in memory164.7 B

Variable types

Text4
DateTime1
Categorical11
Numeric3

Dataset

Description전북특별자치도 전주시 내 안경업을 제공하며, 사업장명, 인허가일자, 상세영업상태, 소재지전화번호, 도로명주소, 지번주소 등을 제공합니다.눈을 보호하거나 시력의 교정을 요하는 대상에게 시력의 교정 및 안경을 판매 또는 수리하는 업소항목 : 사업장명, 인허가일자, 상세영업상태, 소재지전화번호, 도로명주소, 지번주소, 위도, 경도 등담당부서 : 보건행정과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15053260/fileData.do

Alerts

상세영업상태명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
표본렌즈수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
측정의자수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
시력표수 is highly overall correlated with 표본렌즈수 and 7 other fieldsHigh correlation
동공거리측정기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
정점굴절계기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
조제용연마기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
렌즈절단기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
가열기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
안경세척기수 is highly overall correlated with 시력표수 and 7 other fieldsHigh correlation
소재지전화 has 139 (72.8%) missing valuesMissing
총면적 has 91 (47.6%) missing valuesMissing
총면적 has 9 (4.7%) zerosZeros

Reproduction

Analysis started2024-03-14 21:13:38.650254
Analysis finished2024-03-14 21:13:44.189850
Duration5.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct189
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T06:13:45.012329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.6649215
Min length3

Characters and Unicode

Total characters1655
Distinct characters216
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)97.9%

Sample

1st row1001안경동산점
2nd row1001안경원오거리점
3rd row1001안경콘택트 서부신시가지점
4th row1001안경콘택트삼천점
5th row1001안경콘택트아중점
ValueCountFrequency (%)
안경나라 5
 
2.1%
안경콘택트 4
 
1.7%
다비치안경 3
 
1.3%
으뜸플러스안경 3
 
1.3%
전북대점 3
 
1.3%
렌즈타운 2
 
0.8%
아중점 2
 
0.8%
채플린안경콘택트 2
 
0.8%
호성점 2
 
0.8%
평화점 2
 
0.8%
Other values (205) 211
88.3%
2024-03-15T06:13:46.419348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 163
 
9.8%
안 161
 
9.7%
점 101
 
6.1%
원 49
 
3.0%
트 48
 
2.9%
48
 
2.9%
아 42
 
2.5%
택 41
 
2.5%
콘 41
 
2.5%
전 37
 
2.2%
Other values (206) 924
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1519
91.8%
Space Separator 48
 
2.9%
Decimal Number 47
 
2.8%
Uppercase Letter 12
 
0.7%
Open Punctuation 10
 
0.6%
Close Punctuation 10
 
0.6%
Lowercase Letter 6
 
0.4%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 163
 
10.7%
안 161
 
10.6%
점 101
 
6.6%
원 49
 
3.2%
트 48
 
3.2%
아 42
 
2.8%
택 41
 
2.7%
콘 41
 
2.7%
전 37
 
2.4%
이 35
 
2.3%
Other values (182) 801
52.7%
Uppercase Letter
ValueCountFrequency (%)
O 2
16.7%
E 2
16.7%
J 2
16.7%
K 2
16.7%
T 1
8.3%
C 1
8.3%
N 1
8.3%
Y 1
8.3%
Decimal Number
ValueCountFrequency (%)
0 22
46.8%
1 18
38.3%
5 4
 
8.5%
9 1
 
2.1%
6 1
 
2.1%
3 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
b 2
33.3%
y 2
33.3%
e 1
16.7%
h 1
16.7%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1519
91.8%
Common 118
 
7.1%
Latin 18
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 163
 
10.7%
안 161
 
10.6%
점 101
 
6.6%
원 49
 
3.2%
트 48
 
3.2%
아 42
 
2.8%
택 41
 
2.7%
콘 41
 
2.7%
전 37
 
2.4%
이 35
 
2.3%
Other values (182) 801
52.7%
Common
ValueCountFrequency (%)
48
40.7%
0 22
18.6%
1 18
 
15.3%
( 10
 
8.5%
) 10
 
8.5%
5 4
 
3.4%
· 1
 
0.8%
9 1
 
0.8%
6 1
 
0.8%
3 1
 
0.8%
Other values (2) 2
 
1.7%
Latin
ValueCountFrequency (%)
O 2
11.1%
E 2
11.1%
J 2
11.1%
K 2
11.1%
b 2
11.1%
y 2
11.1%
e 1
5.6%
h 1
5.6%
T 1
5.6%
C 1
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1519
91.8%
ASCII 135
 
8.2%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 163
 
10.7%
안 161
 
10.6%
점 101
 
6.6%
원 49
 
3.2%
트 48
 
3.2%
아 42
 
2.8%
택 41
 
2.7%
콘 41
 
2.7%
전 37
 
2.4%
이 35
 
2.3%
Other values (182) 801
52.7%
ASCII
ValueCountFrequency (%)
48
35.6%
0 22
16.3%
1 18
 
13.3%
( 10
 
7.4%
) 10
 
7.4%
5 4
 
3.0%
O 2
 
1.5%
E 2
 
1.5%
J 2
 
1.5%
K 2
 
1.5%
Other values (13) 15
 
11.1%
None
ValueCountFrequency (%)
· 1
100.0%

인허가일자
Date

Distinct182
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1979-12-10 00:00:00
Maximum2022-06-15 00:00:00
2024-03-15T06:13:46.688338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:46.949479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
영업중
191 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 191
100.0%

Length

2024-03-15T06:13:47.174959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:13:47.499758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 191
100.0%

소재지전화
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing139
Missing (%)72.8%
Memory size1.6 KiB
2024-03-15T06:13:48.375105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters624
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

Unique52 ?
Unique (%)100.0%

Sample

1st row063-222-1771
2nd row063-252-1007
3rd row063-226-8119
4th row063-902-6969
5th row063-221-4004
ValueCountFrequency (%)
063-222-1771 1
 
1.9%
063-252-1007 1
 
1.9%
063-273-1567 1
 
1.9%
063-241-1351 1
 
1.9%
063-242-8338 1
 
1.9%
063-714-2229 1
 
1.9%
063-287-8101 1
 
1.9%
063-288-3734 1
 
1.9%
063-274-7179 1
 
1.9%
063-276-5005 1
 
1.9%
Other values (42) 42
80.8%
2024-03-15T06:13:49.710006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.7%
2 99
15.9%
0 97
15.5%
3 82
13.1%
6 80
12.8%
1 38
 
6.1%
5 35
 
5.6%
7 32
 
5.1%
8 21
 
3.4%
9 19
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 99
19.0%
0 97
18.7%
3 82
15.8%
6 80
15.4%
1 38
 
7.3%
5 35
 
6.7%
7 32
 
6.2%
8 21
 
4.0%
9 19
 
3.7%
4 17
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.7%
2 99
15.9%
0 97
15.5%
3 82
13.1%
6 80
12.8%
1 38
 
6.1%
5 35
 
5.6%
7 32
 
5.1%
8 21
 
3.4%
9 19
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.7%
2 99
15.9%
0 97
15.5%
3 82
13.1%
6 80
12.8%
1 38
 
6.1%
5 35
 
5.6%
7 32
 
5.1%
8 21
 
3.4%
9 19
 
3.0%

도로명주소
Text

Distinct189
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T06:13:50.923554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length53
Mean length34.465969
Min length27

Characters and Unicode

Total characters6583
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)97.9%

Sample

1st row전북특별자치도 전주시 덕진구 편운로 7 (동산동)
2nd row전북특별자치도 전주시 완산구 전주객사5길 73-24 (고사동)
3rd row전북특별자치도 전주시 완산구 홍산남로 11-8 (효자동2가)
4th row전북특별자치도 전주시 완산구 거마평로 11 (삼천동1가)
5th row전북특별자치도 전주시 덕진구 정언신로 86 (인후동1가)
ValueCountFrequency (%)
전북특별자치도 191
 
15.2%
전주시 191
 
15.2%
완산구 113
 
9.0%
덕진구 78
 
6.2%
1층 21
 
1.7%
효자동2가 19
 
1.5%
서신동 15
 
1.2%
백제대로 13
 
1.0%
송천동1가 12
 
1.0%
팔달로 12
 
1.0%
Other values (331) 593
47.1%
2024-03-15T06:13:52.352992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1068
 
16.2%
전 403
 
6.1%
자 237
 
3.6%
1 234
 
3.6%
동 208
 
3.2%
주 206
 
3.1%
구 196
 
3.0%
북 196
 
3.0%
시 194
 
2.9%
도 193
 
2.9%
Other values (199) 3448
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4204
63.9%
Space Separator 1069
 
16.2%
Decimal Number 783
 
11.9%
Close Punctuation 193
 
2.9%
Open Punctuation 193
 
2.9%
Other Punctuation 83
 
1.3%
Dash Punctuation 27
 
0.4%
Uppercase Letter 19
 
0.3%
Lowercase Letter 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 403
 
9.6%
자 237
 
5.6%
동 208
 
4.9%
주 206
 
4.9%
구 196
 
4.7%
북 196
 
4.7%
시 194
 
4.6%
도 193
 
4.6%
치 192
 
4.6%
특 191
 
4.5%
Other values (168) 1988
47.3%
Decimal Number
ValueCountFrequency (%)
1 234
29.9%
2 134
17.1%
3 79
 
10.1%
6 62
 
7.9%
4 61
 
7.8%
5 60
 
7.7%
0 56
 
7.2%
7 42
 
5.4%
8 31
 
4.0%
9 24
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
L 4
21.1%
E 2
10.5%
W 2
10.5%
I 2
10.5%
V 2
10.5%
A 2
10.5%
K 2
10.5%
S 2
10.5%
B 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
s 2
16.7%
r 2
16.7%
a 2
16.7%
d 2
16.7%
Space Separator
ValueCountFrequency (%)
1068
99.9%
　 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 82
98.8%
@ 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 193
100.0%
Open Punctuation
ValueCountFrequency (%)
( 193
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4204
63.9%
Common 2348
35.7%
Latin 31
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 403
 
9.6%
자 237
 
5.6%
동 208
 
4.9%
주 206
 
4.9%
구 196
 
4.7%
북 196
 
4.7%
시 194
 
4.6%
도 193
 
4.6%
치 192
 
4.6%
특 191
 
4.5%
Other values (168) 1988
47.3%
Common
ValueCountFrequency (%)
1068
45.5%
1 234
 
10.0%
) 193
 
8.2%
( 193
 
8.2%
2 134
 
5.7%
, 82
 
3.5%
3 79
 
3.4%
6 62
 
2.6%
4 61
 
2.6%
5 60
 
2.6%
Other values (7) 182
 
7.8%
Latin
ValueCountFrequency (%)
L 4
12.9%
e 4
12.9%
E 2
 
6.5%
W 2
 
6.5%
I 2
 
6.5%
V 2
 
6.5%
s 2
 
6.5%
r 2
 
6.5%
A 2
 
6.5%
a 2
 
6.5%
Other values (4) 7
22.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4204
63.9%
ASCII 2378
36.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1068
44.9%
1 234
 
9.8%
) 193
 
8.1%
( 193
 
8.1%
2 134
 
5.6%
, 82
 
3.4%
3 79
 
3.3%
6 62
 
2.6%
4 61
 
2.6%
5 60
 
2.5%
Other values (20) 212
 
8.9%
Hangul
ValueCountFrequency (%)
전 403
 
9.6%
자 237
 
5.6%
동 208
 
4.9%
주 206
 
4.9%
구 196
 
4.7%
북 196
 
4.7%
시 194
 
4.6%
도 193
 
4.6%
치 192
 
4.6%
특 191
 
4.5%
Other values (168) 1988
47.3%
None
ValueCountFrequency (%)
　 1
100.0%

지번주소
Text

Distinct182
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-15T06:13:54.353675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length26.732984
Min length22

Characters and Unicode

Total characters5106
Distinct characters60
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

Unique173 ?
Unique (%)90.6%

Sample

1st row전북특별자치도 전주시 덕진구 동산동 694
2nd row전북특별자치도 전주시 완산구 고사동 232-6
3rd row전북특별자치도 전주시 완산구 효자동2가 1238-1
4th row전북특별자치도 전주시 완산구 삼천동1가 767-2
5th row전북특별자치도 전주시 덕진구 인후동1가 868-3
ValueCountFrequency (%)
전북특별자치도 191
20.0%
전주시 191
20.0%
완산구 113
 
11.8%
덕진구 78
 
8.2%
효자동2가 19
 
2.0%
서신동 14
 
1.5%
인후동1가 13
 
1.4%
송천동1가 12
 
1.3%
효자동1가 11
 
1.1%
덕진동1가 11
 
1.1%
Other values (210) 304
31.8%
2024-03-15T06:13:57.072574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
766
 
15.0%
전 384
 
7.5%
1 247
 
4.8%
자 229
 
4.5%
동 195
 
3.8%
북 194
 
3.8%
특 191
 
3.7%
별 191
 
3.7%
치 191
 
3.7%
도 191
 
3.7%
Other values (50) 2327
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3206
62.8%
Decimal Number 956
 
18.7%
Space Separator 766
 
15.0%
Dash Punctuation 178
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 384
 
12.0%
자 229
 
7.1%
동 195
 
6.1%
북 194
 
6.1%
특 191
 
6.0%
별 191
 
6.0%
치 191
 
6.0%
도 191
 
6.0%
주 191
 
6.0%
시 191
 
6.0%
Other values (38) 1058
33.0%
Decimal Number
ValueCountFrequency (%)
1 247
25.8%
2 162
16.9%
3 96
 
10.0%
6 84
 
8.8%
4 77
 
8.1%
5 72
 
7.5%
7 64
 
6.7%
9 61
 
6.4%
8 61
 
6.4%
0 32
 
3.3%
Space Separator
ValueCountFrequency (%)
766
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3206
62.8%
Common 1900
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 384
 
12.0%
자 229
 
7.1%
동 195
 
6.1%
북 194
 
6.1%
특 191
 
6.0%
별 191
 
6.0%
치 191
 
6.0%
도 191
 
6.0%
주 191
 
6.0%
시 191
 
6.0%
Other values (38) 1058
33.0%
Common
ValueCountFrequency (%)
766
40.3%
1 247
 
13.0%
- 178
 
9.4%
2 162
 
8.5%
3 96
 
5.1%
6 84
 
4.4%
4 77
 
4.1%
5 72
 
3.8%
7 64
 
3.4%
9 61
 
3.2%
Other values (2) 93
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3206
62.8%
ASCII 1900
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
766
40.3%
1 247
 
13.0%
- 178
 
9.4%
2 162
 
8.5%
3 96
 
5.1%
6 84
 
4.4%
4 77
 
4.1%
5 72
 
3.8%
7 64
 
3.4%
9 61
 
3.2%
Other values (2) 93
 
4.9%
Hangul
ValueCountFrequency (%)
전 384
 
12.0%
자 229
 
7.1%
동 195
 
6.1%
북 194
 
6.1%
특 191
 
6.0%
별 191
 
6.0%
치 191
 
6.0%
도 191
 
6.0%
주 191
 
6.0%
시 191
 
6.0%
Other values (38) 1058
33.0%

위도
Real number (ℝ)

Distinct183
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.828246
Minimum35.786767
Maximum35.874165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-15T06:13:57.315007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.786767
5-th percentile35.795617
Q135.815558
median35.826618
Q335.841791
95-th percentile35.868975
Maximum35.874165
Range0.08739778
Interquartile range (IQR)0.0262321

Descriptive statistics

Standard deviation0.021265637
Coefficient of variation (CV)0.00059354392
Kurtosis-0.46053252
Mean35.828246
Median Absolute Deviation (MAD)0.01258508
Skewness0.30061847
Sum6843.1949
Variance0.00045222733
MonotonicityNot monotonic
2024-03-15T06:13:57.806823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.80551485 2
 
1.0%
35.81554362 2
 
1.0%
35.83807321 2
 
1.0%
35.80638391 2
 
1.0%
35.84347653 2
 
1.0%
35.83249005 2
 
1.0%
35.8140433 2
 
1.0%
35.85457451 2
 
1.0%
35.87136799 1
 
0.5%
35.84114928 1
 
0.5%
Other values (173) 173
90.6%
ValueCountFrequency (%)
35.78676726 1
0.5%
35.7868638 1
0.5%
35.78702954 1
0.5%
35.7871307 1
0.5%
35.78860452 1
0.5%
35.79351993 1
0.5%
35.79356312 1
0.5%
35.79480615 1
0.5%
35.7948209 1
0.5%
35.79541614 1
0.5%
ValueCountFrequency (%)
35.87416504 1
0.5%
35.87378753 1
0.5%
35.8735992 1
0.5%
35.87309321 1
0.5%
35.87253391 1
0.5%
35.87196114 1
0.5%
35.87136799 1
0.5%
35.8712105 1
0.5%
35.87082881 1
0.5%
35.87004561 1
0.5%

경도
Real number (ℝ)

Distinct183
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12494
Minimum127.05901
Maximum127.16717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-15T06:13:58.058409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05901
5-th percentile127.07753
Q1127.11307
median127.12503
Q3127.14425
95-th percentile127.15536
Maximum127.16717
Range0.1081544
Interquartile range (IQR)0.03118375

Descriptive statistics

Standard deviation0.021836314
Coefficient of variation (CV)0.0001717705
Kurtosis0.42841474
Mean127.12494
Median Absolute Deviation (MAD)0.0163526
Skewness-0.53192488
Sum24280.864
Variance0.00047682462
MonotonicityNot monotonic
2024-03-15T06:13:58.325997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1144693 2
 
1.0%
127.1064504 2
 
1.0%
127.0599762 2
 
1.0%
127.1164665 2
 
1.0%
127.1272027 2
 
1.0%
127.1100031 2
 
1.0%
127.1086523 2
 
1.0%
127.12046 2
 
1.0%
127.0773708 1
 
0.5%
127.1512581 1
 
0.5%
Other values (173) 173
90.6%
ValueCountFrequency (%)
127.0590138 1
0.5%
127.0599762 2
1.0%
127.0721458 1
0.5%
127.0723962 1
0.5%
127.0764793 1
0.5%
127.0767309 1
0.5%
127.0770367 1
0.5%
127.0771191 1
0.5%
127.0773708 1
0.5%
127.0776864 1
0.5%
ValueCountFrequency (%)
127.1671682 1
0.5%
127.1640791 1
0.5%
127.1636583 1
0.5%
127.1632902 1
0.5%
127.1630901 1
0.5%
127.1629026 1
0.5%
127.1625961 1
0.5%
127.1625712 1
0.5%
127.1615685 1
0.5%
127.155434 1
0.5%

시력표수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
100 
0
46 
<NA>
36 
2
 
7
3
 
2

Length

Max length4
Median length1
Mean length1.565445
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 100
52.4%
0 46
24.1%
<NA> 36
 
18.8%
2 7
 
3.7%
3 2
 
1.0%

Length

2024-03-15T06:13:58.693769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:13:59.028129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
52.4%
0 46
24.1%
na 36
 
18.8%
2 7
 
3.7%
3 2
 
1.0%

표본렌즈수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
91 
0
52 
<NA>
45 
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.7068063
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 91
47.6%
0 52
27.2%
<NA> 45
23.6%
2 2
 
1.0%
3 1
 
0.5%

Length

2024-03-15T06:13:59.294010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:13:59.654853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 91
47.6%
0 52
27.2%
na 45
23.6%
2 2
 
1.0%
3 1
 
0.5%

측정의자수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
92 
0
52 
<NA>
43 
2
 
3
3
 
1

Length

Max length4
Median length1
Mean length1.6753927
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 92
48.2%
0 52
27.2%
<NA> 43
22.5%
2 3
 
1.6%
3 1
 
0.5%

Length

2024-03-15T06:14:00.190404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:00.455698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 92
48.2%
0 52
27.2%
na 43
22.5%
2 3
 
1.6%
3 1
 
0.5%

동공거리측정기수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
105 
0
46 
<NA>
37 
2
 
2
3
 
1

Length

Max length4
Median length1
Mean length1.5811518
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 105
55.0%
0 46
24.1%
<NA> 37
 
19.4%
2 2
 
1.0%
3 1
 
0.5%

Length

2024-03-15T06:14:00.855567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:01.207317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 105
55.0%
0 46
24.1%
na 37
 
19.4%
2 2
 
1.0%
3 1
 
0.5%

정점굴절계기수
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
79 
0
46 
<NA>
37 
2
22 
3
 
6

Length

Max length4
Median length1
Mean length1.5811518
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 79
41.4%
0 46
24.1%
<NA> 37
19.4%
2 22
 
11.5%
3 6
 
3.1%
4 1
 
0.5%

Length

2024-03-15T06:14:01.608567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:01.965712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 79
41.4%
0 46
24.1%
na 37
19.4%
2 22
 
11.5%
3 6
 
3.1%
4 1
 
0.5%

조제용연마기수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
86 
0
53 
<NA>
45 
2
 
7

Length

Max length4
Median length1
Mean length1.7068063
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 86
45.0%
0 53
27.7%
<NA> 45
23.6%
2 7
 
3.7%

Length

2024-03-15T06:14:02.360382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:02.655379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 86
45.0%
0 53
27.7%
na 45
23.6%
2 7
 
3.7%

렌즈절단기수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
93 
0
53 
<NA>
44 
2
 
1

Length

Max length4
Median length1
Mean length1.6910995
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row1
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 93
48.7%
0 53
27.7%
<NA> 44
23.0%
2 1
 
0.5%

Length

2024-03-15T06:14:03.038063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:03.385882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 93
48.7%
0 53
27.7%
na 44
23.0%
2 1
 
0.5%

가열기수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
65 
0
52 
<NA>
44 
2
29 
3
 
1

Length

Max length4
Median length1
Mean length1.6910995
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row0
3rd row2
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 65
34.0%
0 52
27.2%
<NA> 44
23.0%
2 29
15.2%
3 1
 
0.5%

Length

2024-03-15T06:14:03.802393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:04.304442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
34.0%
0 52
27.2%
na 44
23.0%
2 29
15.2%
3 1
 
0.5%

안경세척기수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
63 
0
52 
<NA>
44 
2
29 
3
 
3

Length

Max length4
Median length1
Mean length1.6910995
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row2
4th row0
5th row<NA>

Common Values

ValueCountFrequency (%)
1 63
33.0%
0 52
27.2%
<NA> 44
23.0%
2 29
15.2%
3 3
 
1.6%

Length

2024-03-15T06:14:04.561631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:04.921195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 63
33.0%
0 52
27.2%
na 44
23.0%
2 29
15.2%
3 3
 
1.6%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct89
Distinct (%)89.0%
Missing91
Missing (%)47.6%
Infinite0
Infinite (%)0.0%
Mean90.8652
Minimum0
Maximum490.55
Zeros9
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-15T06:14:05.212312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141.1375
median68.465
Q3107.1375
95-th percentile261.0095
Maximum490.55
Range490.55
Interquartile range (IQR)66

Descriptive statistics

Standard deviation85.340083
Coefficient of variation (CV)0.93919435
Kurtosis4.9793773
Mean90.8652
Median Absolute Deviation (MAD)33.675
Skewness1.954823
Sum9086.52
Variance7282.9297
MonotonicityNot monotonic
2024-03-15T06:14:05.469563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
4.7%
99.0 3
 
1.6%
1.0 2
 
1.0%
66.4 1
 
0.5%
62.76 1
 
0.5%
44.74 1
 
0.5%
34.68 1
 
0.5%
40.95 1
 
0.5%
112.41 1
 
0.5%
260.17 1
 
0.5%
Other values (79) 79
41.4%
(Missing) 91
47.6%
ValueCountFrequency (%)
0.0 9
4.7%
1.0 2
 
1.0%
14.0 1
 
0.5%
17.3 1
 
0.5%
18.02 1
 
0.5%
19.8 1
 
0.5%
21.15 1
 
0.5%
25.26 1
 
0.5%
25.65 1
 
0.5%
29.8 1
 
0.5%
ValueCountFrequency (%)
490.55 1
0.5%
354.0 1
0.5%
300.0 1
0.5%
297.34 1
0.5%
276.96 1
0.5%
260.17 1
0.5%
258.0 1
0.5%
251.99 1
0.5%
242.45 1
0.5%
234.0 1
0.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-11-20
191 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-20
2nd row2023-11-20
3rd row2023-11-20
4th row2023-11-20
5th row2023-11-20

Common Values

ValueCountFrequency (%)
2023-11-20 191
100.0%

Length

2024-03-15T06:14:05.856542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:14:06.182047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-20 191
100.0%

Interactions

2024-03-15T06:13:41.858912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:40.478147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:41.168420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:41.993238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:40.689470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:41.405366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:42.137767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:40.931666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:13:41.664473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:14:06.384065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지전화위도경도시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
소재지전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0000.7500.0000.1300.1400.1100.0000.0590.2940.0000.0000.186
경도1.0000.7501.0000.0000.0000.0000.1750.3160.2310.3920.1190.1070.270
시력표수1.0000.0000.0001.0000.9880.9830.9500.7180.6180.6140.9750.9180.679
표본렌즈수1.0000.1300.0000.9881.0000.9980.6180.6680.6780.6620.9830.9380.797
측정의자수1.0000.1400.0000.9830.9981.0000.6660.6680.6710.6620.9820.9410.692
동공거리측정기수1.0000.1100.1750.9500.6180.6661.0000.6930.9080.9070.6210.6190.558
정점굴절계기수1.0000.0000.3160.7180.6680.6680.6931.0000.6570.6560.6740.7560.164
조제용연마기수1.0000.0590.2310.6180.6780.6710.9080.6571.0000.9580.6690.6800.311
렌즈절단기수1.0000.2940.3920.6140.6620.6620.9070.6560.9581.0000.6630.6630.051
가열기수1.0000.0000.1190.9750.9830.9820.6210.6740.6690.6631.0000.9860.416
안경세척기수1.0000.0000.1070.9180.9380.9410.6190.7560.6800.6630.9861.0000.237
총면적1.0000.1860.2700.6790.7970.6920.5580.1640.3110.0510.4160.2371.000
2024-03-15T06:14:06.733406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시력표수정점굴절계기수표본렌즈수가열기수렌즈절단기수측정의자수동공거리측정기수안경세척기수조제용연마기수
시력표수1.0000.6550.8490.7850.6290.8250.6990.6220.634
정점굴절계기수0.6551.0000.5980.6050.6200.5980.6260.7010.621
표본렌즈수0.8490.5981.0000.8220.6870.9400.6330.6680.707
가열기수0.7850.6050.8221.0000.6880.8160.6370.8380.696
렌즈절단기수0.6290.6200.6870.6881.0000.6870.6290.6890.749
측정의자수0.8250.5980.9400.8160.6871.0000.6920.6750.698
동공거리측정기수0.6990.6260.6330.6370.6290.6921.0000.6350.630
안경세척기수0.6220.7010.6680.8380.6890.6750.6351.0000.709
조제용연마기수0.6340.6210.7070.6960.7490.6980.6300.7091.000
2024-03-15T06:14:07.054486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도총면적시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수
위도1.0000.056-0.0490.0000.0730.0800.0610.0000.0270.1790.0000.000
경도0.0561.0000.0170.0000.0000.0000.1010.1330.1360.2490.0660.060
총면적-0.0490.0171.0000.4970.4860.3860.3820.0880.1360.0000.1930.146
시력표수0.0000.0000.4971.0000.8490.8250.6990.6550.6340.6290.7850.622
표본렌즈수0.0730.0000.4860.8491.0000.9400.6330.5980.7070.6870.8220.668
측정의자수0.0800.0000.3860.8250.9401.0000.6920.5980.6980.6870.8160.675
동공거리측정기수0.0610.1010.3820.6990.6330.6921.0000.6260.6300.6290.6370.635
정점굴절계기수0.0000.1330.0880.6550.5980.5980.6261.0000.6210.6200.6050.701
조제용연마기수0.0270.1360.1360.6340.7070.6980.6300.6211.0000.7490.6960.709
렌즈절단기수0.1790.2490.0000.6290.6870.6870.6290.6200.7491.0000.6880.689
가열기수0.0000.0660.1930.7850.8220.8160.6370.6050.6960.6881.0000.838
안경세척기수0.0000.0600.1460.6220.6680.6750.6350.7010.7090.6890.8381.000

Missing values

2024-03-15T06:13:42.393341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:13:43.382562image/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.
2024-03-15T06:13:43.879123image/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

사업장명인허가일자상세영업상태명소재지전화도로명주소지번주소위도경도시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적데이터기준일자
01001안경동산점1998-04-03영업중<NA>전북특별자치도 전주시 덕진구 편운로 7 (동산동)전북특별자치도 전주시 덕진구 동산동 69435.871368127.077371<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
11001안경원오거리점1991-06-24영업중<NA>전북특별자치도 전주시 완산구 전주객사5길 73-24 (고사동)전북특별자치도 전주시 완산구 고사동 232-635.821396127.1440910000000000.02023-11-20
21001안경콘택트 서부신시가지점2008-12-16영업중063-222-1771전북특별자치도 전주시 완산구 홍산남로 11-8 (효자동2가)전북특별자치도 전주시 완산구 효자동2가 1238-135.81604127.10326111111122<NA>2023-11-20
31001안경콘택트삼천점2001-09-13영업중<NA>전북특별자치도 전주시 완산구 거마평로 11 (삼천동1가)전북특별자치도 전주시 완산구 삼천동1가 767-235.79352127.116631000000000<NA>2023-11-20
41001안경콘택트아중점1998-03-18영업중<NA>전북특별자치도 전주시 덕진구 정언신로 86 (인후동1가)전북특별자치도 전주시 덕진구 인후동1가 868-335.830807127.16329<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
51001안경콘택트이마트앞점2005-03-04영업중<NA>전북특별자치도 전주시 완산구 당산로 100 (서신동)전북특별자치도 전주시 완산구 서신동 785-135.831985127.119467000000000<NA>2023-11-20
61001안경콘택트팔복동점2002-06-15영업중<NA>전북특별자치도 전주시 덕진구 기린대로 699 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 250-1835.853246127.104959<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
71001안경콘택트혁신도시점2022-02-23영업중<NA>전북특별자치도 전주시 덕진구 기지로 66, 103호 (중동)전북특별자치도 전주시 덕진구 중동 774-435.838049127.059014100120000182.592023-11-20
81001안경하가지구점2021-05-26영업중063-252-1007전북특별자치도 전주시 덕진구 가련산로 10, 1층 (덕진동2가)전북특별자치도 전주시 덕진구 덕진동2가 695-235.840668127.1105541<NA><NA>11<NA><NA><NA><NA>66.42023-11-20
9369 안경콘택트 전북대점2007-01-05영업중<NA>전북특별자치도 전주시 덕진구 명륜5길 10-2 (덕진동1가)전북특별자치도 전주시 덕진구 덕진동1가 1262-435.843174127.125512111111111<NA>2023-11-20
사업장명인허가일자상세영업상태명소재지전화도로명주소지번주소위도경도시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적데이터기준일자
181투아이스안경 렌즈미서신점1999-09-18영업중<NA>전북특별자치도 전주시 완산구 서신로 103 (서신동)전북특별자치도 전주시 완산구 서신동 963-635.83462127.115599000000000<NA>2023-11-20
182트론by카프카2011-02-24영업중<NA>전북특별자치도 전주시 완산구 홍산북로 11-3 (효자동2가, 104호)전북특별자치도 전주시 완산구 효자동2가 1227-235.817721127.10279811111212295.232023-11-20
183팰리스 안경콘택트2011-08-18영업중063-286-3333전북특별자치도 전주시 완산구 용호로 75 (효자동2가, 101호)전북특별자치도 전주시 완산구 효자동2가 1313-235.809776127.09753211111111164.02023-11-20
184푸른안경원금암점2004-11-06영업중<NA>전북특별자치도 전주시 덕진구 백제대로 660 (금암동)전북특별자치도 전주시 덕진구 금암동 1588-635.842913127.141386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
185풍경이 있는 안경원2012-08-24영업중063-255-6667전북특별자치도 전주시 덕진구 추탄로 6 (덕진동2가)전북특별자치도 전주시 덕진구 덕진동2가 680-335.841793127.110301111121122171.592023-11-20
186한빛안경원1997-05-13영업중<NA>전북특별자치도 전주시 완산구 백제대로 259 (중화산동2가)전북특별자치도 전주시 완산구 중화산동2가 629-535.81623127.122589<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
187한양안경원1991-06-03영업중<NA>전북특별자치도 전주시 완산구 팔달로 172-1 (경원동1가)전북특별자치도 전주시 완산구 경원동1가 30-535.81785127.147383000000000<NA>2023-11-20
188현대중앙안경원2018-06-04영업중063-282-9009전북특별자치도 전주시 덕진구 기린대로 272, 중앙안과 (진북동)전북특별자치도 전주시 덕진구 진북동 329-135.829982127.142558<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2023-11-20
189화니안경원2003-06-14영업중<NA>전북특별자치도 전주시 완산구 장승배기로 245 (평화동1가)전북특별자치도 전주시 완산구 평화동1가 438-535.798164127.13907411111111146.442023-11-20
190황박사안경원 반월점2004-08-07영업중<NA>전북특별자치도 전주시 덕진구 쪽구름로 120 (반월동)전북특별자치도 전주시 덕진구 반월동 422-2235.874165127.07214611111111149.822023-11-20