Overview

Dataset statistics

Number of variables39
Number of observations1219
Missing cells11272
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory398.9 KiB
Average record size in memory335.1 B

Variable types

Numeric10
Categorical11
Text7
DateTime4
Unsupported7

Dataset

Description2023-08-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123010

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
시력표수 is highly imbalanced (65.5%)Imbalance
표본렌즈수 is highly imbalanced (57.5%)Imbalance
조제용연마기수 is highly imbalanced (53.5%)Imbalance
렌즈절단기수 is highly imbalanced (55.1%)Imbalance
인허가취소일자 has 1219 (100.0%) missing valuesMissing
폐업일자 has 783 (64.2%) missing valuesMissing
휴업시작일자 has 1219 (100.0%) missing valuesMissing
휴업종료일자 has 1219 (100.0%) missing valuesMissing
재개업일자 has 1219 (100.0%) missing valuesMissing
소재지전화 has 193 (15.8%) missing valuesMissing
소재지면적 has 1219 (100.0%) missing valuesMissing
소재지우편번호 has 555 (45.5%) missing valuesMissing
소재지전체주소 has 105 (8.6%) missing valuesMissing
도로명전체주소 has 82 (6.7%) missing valuesMissing
도로명우편번호 has 255 (20.9%) missing valuesMissing
업태구분명 has 1219 (100.0%) missing valuesMissing
좌표정보(x) has 91 (7.5%) missing valuesMissing
좌표정보(y) has 91 (7.5%) missing valuesMissing
측정의자수 has 37 (3.0%) missing valuesMissing
가열기수 has 38 (3.1%) missing valuesMissing
안경세척기수 has 37 (3.0%) missing valuesMissing
총면적 has 464 (38.1%) missing valuesMissing
Unnamed: 38 has 1219 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 38 is an unsupported type, check if it needs cleaning or further analysisUnsupported
측정의자수 has 247 (20.3%) zerosZeros
동공거리측정기수 has 173 (14.2%) zerosZeros
정점굴절계기수 has 171 (14.0%) zerosZeros
가열기수 has 251 (20.6%) zerosZeros
안경세척기수 has 250 (20.5%) zerosZeros
총면적 has 108 (8.9%) zerosZeros

Reproduction

Analysis started2024-04-21 10:35:24.047474
Analysis finished2024-04-21 10:35:25.634495
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean610
Minimum1
Maximum1219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:25.830595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile61.9
Q1305.5
median610
Q3914.5
95-th percentile1158.1
Maximum1219
Range1218
Interquartile range (IQR)609

Descriptive statistics

Standard deviation352.0393
Coefficient of variation (CV)0.5771136
Kurtosis-1.2
Mean610
Median Absolute Deviation (MAD)305
Skewness0
Sum743590
Variance123931.67
MonotonicityStrictly increasing
2024-04-21T19:35:26.276736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
812 1
 
0.1%
819 1
 
0.1%
818 1
 
0.1%
817 1
 
0.1%
816 1
 
0.1%
815 1
 
0.1%
814 1
 
0.1%
813 1
 
0.1%
811 1
 
0.1%
Other values (1209) 1209
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1219 1
0.1%
1218 1
0.1%
1217 1
0.1%
1216 1
0.1%
1215 1
0.1%
1214 1
0.1%
1213 1
0.1%
1212 1
0.1%
1211 1
0.1%
1210 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
안경업
1219 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안경업 1219
100.0%

Length

2024-04-21T19:35:26.693838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:26.993836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1219
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
01_02_01_P
1219 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01_02_01_P
2nd row01_02_01_P
3rd row01_02_01_P
4th row01_02_01_P
5th row01_02_01_P

Common Values

ValueCountFrequency (%)
01_02_01_P 1219
100.0%

Length

2024-04-21T19:35:27.311090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:27.611334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1219
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325184.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:27.898763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13290000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39907.873
Coefficient of variation (CV)0.012001702
Kurtosis-0.73418879
Mean3325184.6
Median Absolute Deviation (MAD)30000
Skewness-0.042820983
Sum4.0534 × 109
Variance1.5926383 × 109
MonotonicityIncreasing
2024-04-21T19:35:28.283437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 179
14.7%
3290000 150
12.3%
3310000 118
9.7%
3330000 105
8.6%
3340000 94
7.7%
3300000 93
7.6%
3250000 82
6.7%
3320000 71
 
5.8%
3390000 69
 
5.7%
3370000 66
 
5.4%
Other values (6) 192
15.8%
ValueCountFrequency (%)
3250000 82
6.7%
3260000 23
 
1.9%
3270000 29
 
2.4%
3280000 28
 
2.3%
3290000 150
12.3%
3300000 93
7.6%
3310000 118
9.7%
3320000 71
5.8%
3330000 105
8.6%
3340000 94
7.7%
ValueCountFrequency (%)
3400000 39
 
3.2%
3390000 69
 
5.7%
3380000 54
 
4.4%
3370000 66
 
5.4%
3360000 19
 
1.6%
3350000 179
14.7%
3340000 94
7.7%
3330000 105
8.6%
3320000 71
 
5.8%
3310000 118
9.7%

관리번호
Text

UNIQUE 

Distinct1219
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:35:29.019613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters30475
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

Unique1219 ?
Unique (%)100.0%

Sample

1st rowPHMB220233250021082200001
2nd rowPHMB220183250021082200001
3rd rowPHMB220103250021082200001
4th rowPHMB219933250021082200001
5th rowPHMB220103250021082200006
ValueCountFrequency (%)
phmb220233250021082200001 1
 
0.1%
phmb220053350024082200006 1
 
0.1%
phmb219913350024082200005 1
 
0.1%
phmb219783350024082200001 1
 
0.1%
phmb219863350024082200004 1
 
0.1%
phmb219863350024082200003 1
 
0.1%
phmb219883350024082200002 1
 
0.1%
phmb219853350024082200002 1
 
0.1%
phmb220083350024082200001 1
 
0.1%
phmb219873350024082200008 1
 
0.1%
Other values (1209) 1209
99.2%
2024-04-21T19:35:30.136854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9965
32.7%
2 6603
21.7%
3 2681
 
8.8%
1 1653
 
5.4%
8 1556
 
5.1%
P 1219
 
4.0%
H 1219
 
4.0%
M 1219
 
4.0%
B 1219
 
4.0%
4 1083
 
3.6%
Other values (4) 2058
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25599
84.0%
Uppercase Letter 4876
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9965
38.9%
2 6603
25.8%
3 2681
 
10.5%
1 1653
 
6.5%
8 1556
 
6.1%
4 1083
 
4.2%
9 980
 
3.8%
5 605
 
2.4%
7 256
 
1.0%
6 217
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 1219
25.0%
H 1219
25.0%
M 1219
25.0%
B 1219
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25599
84.0%
Latin 4876
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9965
38.9%
2 6603
25.8%
3 2681
 
10.5%
1 1653
 
6.5%
8 1556
 
6.1%
4 1083
 
4.2%
9 980
 
3.8%
5 605
 
2.4%
7 256
 
1.0%
6 217
 
0.8%
Latin
ValueCountFrequency (%)
P 1219
25.0%
H 1219
25.0%
M 1219
25.0%
B 1219
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9965
32.7%
2 6603
21.7%
3 2681
 
8.8%
1 1653
 
5.4%
8 1556
 
5.1%
P 1219
 
4.0%
H 1219
 
4.0%
M 1219
 
4.0%
B 1219
 
4.0%
4 1083
 
3.6%
Other values (4) 2058
 
6.8%
Distinct1117
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum1971-05-18 00:00:00
Maximum2023-07-05 00:00:00
2024-04-21T19:35:30.536040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:30.973846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
763 
3
448 
4
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 763
62.6%
3 448
36.8%
4 8
 
0.7%

Length

2024-04-21T19:35:31.392684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:31.705666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 763
62.6%
3 448
36.8%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업/정상
763 
폐업
448 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length3.9565217
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 763
62.6%
폐업 448
36.8%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:35:32.069484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:32.397542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 763
62.6%
폐업 448
36.8%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
13
763 
3
448 
24
 
8

Length

Max length2
Median length2
Mean length1.6324856
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
13 763
62.6%
3 448
36.8%
24 8
 
0.7%

Length

2024-04-21T19:35:32.750892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:33.064963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 763
62.6%
3 448
36.8%
24 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업중
763 
폐업
448 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6390484
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 763
62.6%
폐업 448
36.8%
직권폐업 8
 
0.7%

Length

2024-04-21T19:35:33.441489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:33.780995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 763
62.6%
폐업 448
36.8%
직권폐업 8
 
0.7%

폐업일자
Date

MISSING 

Distinct405
Distinct (%)92.9%
Missing783
Missing (%)64.2%
Memory size9.6 KiB
Minimum1985-11-28 00:00:00
Maximum2023-06-19 00:00:00
2024-04-21T19:35:34.121534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:34.553059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

소재지전화
Text

MISSING 

Distinct966
Distinct (%)94.2%
Missing193
Missing (%)15.8%
Memory size9.6 KiB
2024-04-21T19:35:35.423037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.31384
Min length7

Characters and Unicode

Total characters11608
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique914 ?
Unique (%)89.1%

Sample

1st row051-243-3991
2nd row2531216
3rd row070-4116-2770
4th row051-253-1216
5th row051-246-0006
ValueCountFrequency (%)
051-808-7088 4
 
0.4%
051-816-4500 3
 
0.3%
051-625-8471 3
 
0.3%
051-647-5766 3
 
0.3%
261-6700 3
 
0.3%
051-623-7778 3
 
0.3%
051-337-7111 3
 
0.3%
051-315-2208 2
 
0.2%
524-4100 2
 
0.2%
051-611-0079 2
 
0.2%
Other values (956) 998
97.3%
2024-04-21T19:35:36.889040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1813
15.6%
0 1761
15.2%
5 1627
14.0%
1 1615
13.9%
2 875
7.5%
8 713
 
6.1%
7 711
 
6.1%
3 705
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 447
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9752
84.0%
Dash Punctuation 1813
 
15.6%
Close Punctuation 39
 
0.3%
Math Symbol 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1761
18.1%
5 1627
16.7%
1 1615
16.6%
2 875
9.0%
8 713
7.3%
7 711
7.3%
3 705
7.2%
6 700
 
7.2%
4 641
 
6.6%
9 404
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1813
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11608
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1813
15.6%
0 1761
15.2%
5 1627
14.0%
1 1615
13.9%
2 875
7.5%
8 713
 
6.1%
7 711
 
6.1%
3 705
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 447
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11608
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1813
15.6%
0 1761
15.2%
5 1627
14.0%
1 1615
13.9%
2 875
7.5%
8 713
 
6.1%
7 711
 
6.1%
3 705
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 447
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

소재지우편번호
Text

MISSING 

Distinct339
Distinct (%)51.1%
Missing555
Missing (%)45.5%
Memory size9.6 KiB
2024-04-21T19:35:37.810379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9909639
Min length5

Characters and Unicode

Total characters4642
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

Unique191 ?
Unique (%)28.8%

Sample

1st row600-042
2nd row600-819
3rd row600-063
4th row600-063
5th row600-031
ValueCountFrequency (%)
609-839 33
 
5.0%
609-834 8
 
1.2%
614-030 7
 
1.1%
609-800 7
 
1.1%
608-805 7
 
1.1%
614-845 7
 
1.1%
616-852 7
 
1.1%
609-822 7
 
1.1%
619-963 6
 
0.9%
612-022 6
 
0.9%
Other values (329) 569
85.7%
2024-04-21T19:35:39.183113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 772
16.6%
0 725
15.6%
- 661
14.2%
1 608
13.1%
8 517
11.1%
4 289
 
6.2%
2 279
 
6.0%
9 276
 
5.9%
3 256
 
5.5%
7 164
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3981
85.8%
Dash Punctuation 661
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 772
19.4%
0 725
18.2%
1 608
15.3%
8 517
13.0%
4 289
 
7.3%
2 279
 
7.0%
9 276
 
6.9%
3 256
 
6.4%
7 164
 
4.1%
5 95
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 661
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4642
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 772
16.6%
0 725
15.6%
- 661
14.2%
1 608
13.1%
8 517
11.1%
4 289
 
6.2%
2 279
 
6.0%
9 276
 
5.9%
3 256
 
5.5%
7 164
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4642
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 772
16.6%
0 725
15.6%
- 661
14.2%
1 608
13.1%
8 517
11.1%
4 289
 
6.2%
2 279
 
6.0%
9 276
 
5.9%
3 256
 
5.5%
7 164
 
3.5%

소재지전체주소
Text

MISSING 

Distinct1057
Distinct (%)94.9%
Missing105
Missing (%)8.6%
Memory size9.6 KiB
2024-04-21T19:35:40.536533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.059246
Min length3

Characters and Unicode

Total characters26802
Distinct characters324
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1006 ?
Unique (%)90.3%

Sample

1st row부산광역시 중구 부평동1가 35-20
2nd row부산광역시 중구 창선동2가 24번지 4호
3rd row부산광역시 중구 남포동2가 24번지 8호
4th row부산광역시 중구 창선동2가 24번지 4호
5th row부산광역시 중구 남포동4가 2번지 5호
ValueCountFrequency (%)
부산광역시 1085
 
19.4%
금정구 173
 
3.1%
부산진구 145
 
2.6%
1호 117
 
2.1%
남구 106
 
1.9%
사하구 87
 
1.6%
동래구 84
 
1.5%
중구 78
 
1.4%
해운대구 76
 
1.4%
북구 69
 
1.2%
Other values (1455) 3581
63.9%
2024-04-21T19:35:42.324148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4502
 
16.8%
1 1412
 
5.3%
1399
 
5.2%
1336
 
5.0%
1236
 
4.6%
1132
 
4.2%
1121
 
4.2%
1113
 
4.2%
1090
 
4.1%
2 938
 
3.5%
Other values (314) 11523
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15969
59.6%
Decimal Number 5830
 
21.8%
Space Separator 4502
 
16.8%
Dash Punctuation 332
 
1.2%
Uppercase Letter 64
 
0.2%
Other Punctuation 41
 
0.2%
Close Punctuation 30
 
0.1%
Open Punctuation 30
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1399
 
8.8%
1336
 
8.4%
1236
 
7.7%
1132
 
7.1%
1121
 
7.0%
1113
 
7.0%
1090
 
6.8%
811
 
5.1%
772
 
4.8%
755
 
4.7%
Other values (280) 5204
32.6%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.2%
K 10
15.6%
B 7
10.9%
A 6
9.4%
E 6
9.4%
H 5
7.8%
C 5
7.8%
U 4
 
6.2%
Y 4
 
6.2%
G 2
 
3.1%
Other values (3) 4
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 1412
24.2%
2 938
16.1%
3 641
11.0%
4 556
 
9.5%
5 490
 
8.4%
0 405
 
6.9%
6 379
 
6.5%
7 358
 
6.1%
8 332
 
5.7%
9 319
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 33
80.5%
. 5
 
12.2%
@ 2
 
4.9%
/ 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
4502
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 332
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15969
59.6%
Common 10767
40.2%
Latin 66
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1399
 
8.8%
1336
 
8.4%
1236
 
7.7%
1132
 
7.1%
1121
 
7.0%
1113
 
7.0%
1090
 
6.8%
811
 
5.1%
772
 
4.8%
755
 
4.7%
Other values (280) 5204
32.6%
Common
ValueCountFrequency (%)
4502
41.8%
1 1412
 
13.1%
2 938
 
8.7%
3 641
 
6.0%
4 556
 
5.2%
5 490
 
4.6%
0 405
 
3.8%
6 379
 
3.5%
7 358
 
3.3%
- 332
 
3.1%
Other values (9) 754
 
7.0%
Latin
ValueCountFrequency (%)
S 11
16.7%
K 10
15.2%
B 7
10.6%
A 6
9.1%
E 6
9.1%
H 5
7.6%
C 5
7.6%
U 4
 
6.1%
Y 4
 
6.1%
G 2
 
3.0%
Other values (5) 6
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15969
59.6%
ASCII 10833
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4502
41.6%
1 1412
 
13.0%
2 938
 
8.7%
3 641
 
5.9%
4 556
 
5.1%
5 490
 
4.5%
0 405
 
3.7%
6 379
 
3.5%
7 358
 
3.3%
- 332
 
3.1%
Other values (24) 820
 
7.6%
Hangul
ValueCountFrequency (%)
1399
 
8.8%
1336
 
8.4%
1236
 
7.7%
1132
 
7.1%
1121
 
7.0%
1113
 
7.0%
1090
 
6.8%
811
 
5.1%
772
 
4.8%
755
 
4.7%
Other values (280) 5204
32.6%

도로명전체주소
Text

MISSING 

Distinct1063
Distinct (%)93.5%
Missing82
Missing (%)6.7%
Memory size9.6 KiB
2024-04-21T19:35:43.650024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length28.328936
Min length20

Characters and Unicode

Total characters32210
Distinct characters368
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1002 ?
Unique (%)88.1%

Sample

1st row부산광역시 중구 광복로 19-1(부평동1가)
2nd row부산광역시 중구 국제시장2길 6-1 (창선동2가)
3rd row부산광역시 중구 구덕로34번길 3-1 (남포동2가)
4th row부산광역시 중구 국제시장2길 6-1 (창선동2가)
5th row부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)
ValueCountFrequency (%)
부산광역시 1138
 
17.6%
1층 201
 
3.1%
금정구 157
 
2.4%
부산진구 144
 
2.2%
해운대구 104
 
1.6%
남구 95
 
1.5%
동래구 92
 
1.4%
사하구 90
 
1.4%
중구 78
 
1.2%
부전동 71
 
1.1%
Other values (1402) 4300
66.5%
2024-04-21T19:35:45.424261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5337
 
16.6%
1454
 
4.5%
1438
 
4.5%
1387
 
4.3%
1227
 
3.8%
1226
 
3.8%
1171
 
3.6%
1 1153
 
3.6%
1142
 
3.5%
1122
 
3.5%
Other values (358) 15553
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19232
59.7%
Space Separator 5337
 
16.6%
Decimal Number 4548
 
14.1%
Open Punctuation 1118
 
3.5%
Close Punctuation 1118
 
3.5%
Other Punctuation 592
 
1.8%
Dash Punctuation 169
 
0.5%
Uppercase Letter 79
 
0.2%
Lowercase Letter 9
 
< 0.1%
Math Symbol 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1454
 
7.6%
1438
 
7.5%
1387
 
7.2%
1227
 
6.4%
1226
 
6.4%
1171
 
6.1%
1142
 
5.9%
1122
 
5.8%
598
 
3.1%
308
 
1.6%
Other values (317) 8159
42.4%
Uppercase Letter
ValueCountFrequency (%)
S 14
17.7%
B 12
15.2%
K 12
15.2%
A 6
7.6%
H 6
7.6%
C 5
 
6.3%
E 5
 
6.3%
Y 4
 
5.1%
U 4
 
5.1%
G 4
 
5.1%
Other values (7) 7
8.9%
Decimal Number
ValueCountFrequency (%)
1 1153
25.4%
2 698
15.3%
3 427
 
9.4%
0 407
 
8.9%
4 390
 
8.6%
5 336
 
7.4%
7 330
 
7.3%
6 306
 
6.7%
9 261
 
5.7%
8 240
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
l 2
22.2%
b 1
11.1%
i 1
11.1%
h 1
11.1%
k 1
11.1%
s 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 588
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5337
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19232
59.7%
Common 12890
40.0%
Latin 88
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1454
 
7.6%
1438
 
7.5%
1387
 
7.2%
1227
 
6.4%
1226
 
6.4%
1171
 
6.1%
1142
 
5.9%
1122
 
5.8%
598
 
3.1%
308
 
1.6%
Other values (317) 8159
42.4%
Latin
ValueCountFrequency (%)
S 14
15.9%
B 12
13.6%
K 12
13.6%
A 6
 
6.8%
H 6
 
6.8%
C 5
 
5.7%
E 5
 
5.7%
Y 4
 
4.5%
U 4
 
4.5%
G 4
 
4.5%
Other values (14) 16
18.2%
Common
ValueCountFrequency (%)
5337
41.4%
1 1153
 
8.9%
( 1118
 
8.7%
) 1118
 
8.7%
2 698
 
5.4%
, 588
 
4.6%
3 427
 
3.3%
0 407
 
3.2%
4 390
 
3.0%
5 336
 
2.6%
Other values (7) 1318
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19232
59.7%
ASCII 12978
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5337
41.1%
1 1153
 
8.9%
( 1118
 
8.6%
) 1118
 
8.6%
2 698
 
5.4%
, 588
 
4.5%
3 427
 
3.3%
0 407
 
3.1%
4 390
 
3.0%
5 336
 
2.6%
Other values (31) 1406
 
10.8%
Hangul
ValueCountFrequency (%)
1454
 
7.6%
1438
 
7.5%
1387
 
7.2%
1227
 
6.4%
1226
 
6.4%
1171
 
6.1%
1142
 
5.9%
1122
 
5.8%
598
 
3.1%
308
 
1.6%
Other values (317) 8159
42.4%

도로명우편번호
Text

MISSING 

Distinct551
Distinct (%)57.2%
Missing255
Missing (%)20.9%
Memory size9.6 KiB
2024-04-21T19:35:46.621324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.120332
Min length5

Characters and Unicode

Total characters4936
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

Unique351 ?
Unique (%)36.4%

Sample

1st row48979
2nd row48946
3rd row48946
4th row48953
5th row48947
ValueCountFrequency (%)
48946 21
 
2.2%
48953 13
 
1.3%
46291 11
 
1.1%
48945 10
 
1.0%
47295 8
 
0.8%
46576 8
 
0.8%
47254 8
 
0.8%
48095 7
 
0.7%
47286 7
 
0.7%
47296 7
 
0.7%
Other values (541) 864
89.6%
2024-04-21T19:35:48.245850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1216
24.6%
8 550
11.1%
7 521
10.6%
6 493
10.0%
9 434
 
8.8%
2 381
 
7.7%
5 373
 
7.6%
0 330
 
6.7%
1 313
 
6.3%
3 267
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4878
98.8%
Dash Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1216
24.9%
8 550
11.3%
7 521
10.7%
6 493
10.1%
9 434
 
8.9%
2 381
 
7.8%
5 373
 
7.6%
0 330
 
6.8%
1 313
 
6.4%
3 267
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4936
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1216
24.6%
8 550
11.1%
7 521
10.6%
6 493
10.0%
9 434
 
8.8%
2 381
 
7.7%
5 373
 
7.6%
0 330
 
6.7%
1 313
 
6.3%
3 267
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1216
24.6%
8 550
11.1%
7 521
10.6%
6 493
10.0%
9 434
 
8.8%
2 381
 
7.7%
5 373
 
7.6%
0 330
 
6.7%
1 313
 
6.3%
3 267
 
5.4%
Distinct977
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:35:49.163694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.95242
Min length2

Characters and Unicode

Total characters8475
Distinct characters417
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique861 ?
Unique (%)70.6%

Sample

1st row서울광학
2nd row국전안경
3rd row아이샵(eye#)안경
4th row국전안경
5th row눈사랑안경남포
ValueCountFrequency (%)
안경원 69
 
4.4%
안경 45
 
2.9%
갤러리안경 29
 
1.9%
눈사랑안경 22
 
1.4%
안경나라 22
 
1.4%
갤러리안경원 13
 
0.8%
으뜸플러스안경 13
 
0.8%
오렌즈 12
 
0.8%
세컨페이스 12
 
0.8%
초이스안경 12
 
0.8%
Other values (976) 1314
84.1%
2024-04-21T19:35:50.516270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1103
 
13.0%
1101
 
13.0%
405
 
4.8%
344
 
4.1%
300
 
3.5%
281
 
3.3%
221
 
2.6%
201
 
2.4%
131
 
1.5%
0 93
 
1.1%
Other values (407) 4295
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7610
89.8%
Space Separator 344
 
4.1%
Decimal Number 188
 
2.2%
Uppercase Letter 91
 
1.1%
Lowercase Letter 90
 
1.1%
Close Punctuation 61
 
0.7%
Open Punctuation 61
 
0.7%
Other Punctuation 24
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1103
 
14.5%
1101
 
14.5%
405
 
5.3%
300
 
3.9%
281
 
3.7%
221
 
2.9%
201
 
2.6%
131
 
1.7%
89
 
1.2%
85
 
1.1%
Other values (349) 3693
48.5%
Uppercase Letter
ValueCountFrequency (%)
O 14
15.4%
E 9
 
9.9%
S 8
 
8.8%
L 6
 
6.6%
N 5
 
5.5%
G 5
 
5.5%
K 5
 
5.5%
M 4
 
4.4%
I 4
 
4.4%
C 4
 
4.4%
Other values (12) 27
29.7%
Lowercase Letter
ValueCountFrequency (%)
e 16
17.8%
n 11
12.2%
c 9
10.0%
a 9
10.0%
l 7
7.8%
o 6
 
6.7%
i 6
 
6.7%
h 5
 
5.6%
s 5
 
5.6%
t 5
 
5.6%
Other values (8) 11
12.2%
Decimal Number
ValueCountFrequency (%)
0 93
49.5%
1 42
22.3%
5 23
 
12.2%
8 21
 
11.2%
2 5
 
2.7%
3 3
 
1.6%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 14
58.3%
& 4
 
16.7%
· 4
 
16.7%
# 2
 
8.3%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7610
89.8%
Common 683
 
8.1%
Latin 181
 
2.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1103
 
14.5%
1101
 
14.5%
405
 
5.3%
300
 
3.9%
281
 
3.7%
221
 
2.9%
201
 
2.6%
131
 
1.7%
89
 
1.2%
85
 
1.1%
Other values (349) 3693
48.5%
Latin
ValueCountFrequency (%)
e 16
 
8.8%
O 14
 
7.7%
n 11
 
6.1%
c 9
 
5.0%
a 9
 
5.0%
E 9
 
5.0%
S 8
 
4.4%
l 7
 
3.9%
o 6
 
3.3%
L 6
 
3.3%
Other values (30) 86
47.5%
Common
ValueCountFrequency (%)
344
50.4%
0 93
 
13.6%
) 61
 
8.9%
( 61
 
8.9%
1 42
 
6.1%
5 23
 
3.4%
8 21
 
3.1%
. 14
 
2.0%
2 5
 
0.7%
& 4
 
0.6%
Other values (7) 15
 
2.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7609
89.8%
ASCII 859
 
10.1%
None 5
 
0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1103
 
14.5%
1101
 
14.5%
405
 
5.3%
300
 
3.9%
281
 
3.7%
221
 
2.9%
201
 
2.6%
131
 
1.7%
89
 
1.2%
85
 
1.1%
Other values (348) 3692
48.5%
ASCII
ValueCountFrequency (%)
344
40.0%
0 93
 
10.8%
) 61
 
7.1%
( 61
 
7.1%
1 42
 
4.9%
5 23
 
2.7%
8 21
 
2.4%
e 16
 
1.9%
O 14
 
1.6%
. 14
 
1.6%
Other values (45) 170
19.8%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Distinct1193
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2008-11-20 14:16:39
Maximum2023-07-06 17:34:26
2024-04-21T19:35:50.911040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:51.329863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
I
892 
U
327 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowU
3rd rowI
4th rowI
5th rowU

Common Values

ValueCountFrequency (%)
I 892
73.2%
U 327
 
26.8%

Length

2024-04-21T19:35:51.724070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:52.030342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 892
73.2%
u 327
 
26.8%
Distinct358
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-07-08 02:40:00
2024-04-21T19:35:52.343284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:52.765163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct953
Distinct (%)84.5%
Missing91
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean388134.04
Minimum367108.19
Maximum407446.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:53.177712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379713.76
Q1384874.52
median388525.18
Q3391309.52
95-th percentile397577.39
Maximum407446.39
Range40338.198
Interquartile range (IQR)6435.0014

Descriptive statistics

Standard deviation5331.0235
Coefficient of variation (CV)0.013735006
Kurtosis0.52251157
Mean388134.04
Median Absolute Deviation (MAD)3276.7366
Skewness0.043620561
Sum4.378152 × 108
Variance28419812
MonotonicityNot monotonic
2024-04-21T19:35:53.624190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387271.299492377 7
 
0.6%
387618.822819678 7
 
0.6%
387920.292113406 5
 
0.4%
389314.662086382 5
 
0.4%
393952.264486105 5
 
0.4%
389816.233000769 5
 
0.4%
398237.363461482 5
 
0.4%
389097.800933845 4
 
0.3%
395388.715069604 4
 
0.3%
384874.515689472 4
 
0.3%
Other values (943) 1077
88.4%
(Missing) 91
 
7.5%
ValueCountFrequency (%)
367108.187127244 1
0.1%
371179.513984489 1
0.1%
371180.376049706 1
0.1%
373495.794543247 1
0.1%
373508.720158694 1
0.1%
373510.894533028 1
0.1%
373567.668846554 1
0.1%
373576.028819345 1
0.1%
373735.179019114 1
0.1%
374819.186712212 1
0.1%
ValueCountFrequency (%)
407446.385190035 1
 
0.1%
403214.458027912 1
 
0.1%
402521.177512697 2
0.2%
402510.10889131 1
 
0.1%
402168.69425719 3
0.2%
401739.341804489 1
 
0.1%
401727.549646357 1
 
0.1%
401723.705430156 1
 
0.1%
401721.440535713 1
 
0.1%
401709.204864151 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct953
Distinct (%)84.5%
Missing91
Missing (%)7.5%
Infinite0
Infinite (%)0.0%
Mean187391.89
Minimum174016.55
Maximum206209.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:54.031699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178690.7
Q1183544.39
median187138.65
Q3191888.97
95-th percentile196337.12
Maximum206209.45
Range32192.899
Interquartile range (IQR)8344.5836

Descriptive statistics

Standard deviation5888.0094
Coefficient of variation (CV)0.031420833
Kurtosis-0.16499802
Mean187391.89
Median Absolute Deviation (MAD)4395.5663
Skewness0.18949188
Sum2.1137805 × 108
Variance34668654
MonotonicityNot monotonic
2024-04-21T19:35:54.450774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186099.137533193 7
 
0.6%
186273.478853335 7
 
0.6%
186157.316240541 5
 
0.4%
194669.898821674 5
 
0.4%
187602.933160728 5
 
0.4%
193329.605871168 5
 
0.4%
187720.511056894 5
 
0.4%
192260.811648263 4
 
0.3%
186268.853282623 4
 
0.3%
179978.235223733 4
 
0.3%
Other values (943) 1077
88.4%
(Missing) 91
 
7.5%
ValueCountFrequency (%)
174016.551235181 1
 
0.1%
174289.976688419 2
0.2%
174820.944129501 1
 
0.1%
174883.742734168 2
0.2%
174910.857552639 1
 
0.1%
174915.765704636 1
 
0.1%
174922.72397246 1
 
0.1%
175057.154813015 1
 
0.1%
175314.286676535 1
 
0.1%
175382.738615908 3
0.2%
ValueCountFrequency (%)
206209.450536273 1
0.1%
206070.223360046 1
0.1%
205750.743932475 1
0.1%
205529.184735321 1
0.1%
205422.192069209 1
0.1%
205159.486624298 1
0.1%
205068.689054296 1
0.1%
204878.049675429 1
0.1%
204802.042928644 1
0.1%
204747.503833689 1
0.1%

시력표수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
1009 
0
171 
2
 
35
<NA>
 
3
3
 
1

Length

Max length4
Median length1
Mean length1.0073831
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1009
82.8%
0 171
 
14.0%
2 35
 
2.9%
<NA> 3
 
0.2%
3 1
 
0.1%

Length

2024-04-21T19:35:54.880110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:55.217423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1009
82.8%
0 171
 
14.0%
2 35
 
2.9%
na 3
 
0.2%
3 1
 
0.1%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
904 
0
247 
2
 
33
<NA>
 
28
3
 
6

Length

Max length4
Median length1
Mean length1.0705496
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 904
74.2%
0 247
 
20.3%
2 33
 
2.7%
<NA> 28
 
2.3%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:35:55.597005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:55.939825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 904
74.2%
0 247
 
20.3%
2 33
 
2.7%
na 28
 
2.3%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.8536379
Minimum0
Maximum11
Zeros247
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:56.259548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.59895432
Coefficient of variation (CV)0.70164917
Kurtosis72.898229
Mean0.8536379
Median Absolute Deviation (MAD)0
Skewness4.5897206
Sum1009
Variance0.35874628
MonotonicityNot monotonic
2024-04-21T19:35:56.593524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 883
72.4%
0 247
 
20.3%
2 43
 
3.5%
3 4
 
0.3%
4 3
 
0.2%
5 1
 
0.1%
11 1
 
0.1%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
0 247
 
20.3%
1 883
72.4%
2 43
 
3.5%
3 4
 
0.3%
4 3
 
0.2%
5 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
5 1
 
0.1%
4 3
 
0.2%
3 4
 
0.3%
2 43
 
3.5%
1 883
72.4%
0 247
 
20.3%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing3
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.92927632
Minimum0
Maximum10
Zeros173
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:56.924380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58788717
Coefficient of variation (CV)0.63262903
Kurtosis57.436162
Mean0.92927632
Median Absolute Deviation (MAD)0
Skewness4.6398309
Sum1130
Variance0.34561133
MonotonicityNot monotonic
2024-04-21T19:35:57.272541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 993
81.5%
0 173
 
14.2%
2 33
 
2.7%
3 8
 
0.7%
5 5
 
0.4%
4 3
 
0.2%
10 1
 
0.1%
(Missing) 3
 
0.2%
ValueCountFrequency (%)
0 173
 
14.2%
1 993
81.5%
2 33
 
2.7%
3 8
 
0.7%
4 3
 
0.2%
5 5
 
0.4%
10 1
 
0.1%
ValueCountFrequency (%)
10 1
 
0.1%
5 5
 
0.4%
4 3
 
0.2%
3 8
 
0.7%
2 33
 
2.7%
1 993
81.5%
0 173
 
14.2%

정점굴절계기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.5%
Missing5
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.0214168
Minimum0
Maximum5
Zeros171
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:57.599079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.62606425
Coefficient of variation (CV)0.61293709
Kurtosis4.9425083
Mean1.0214168
Median Absolute Deviation (MAD)0
Skewness1.2768575
Sum1240
Variance0.39195644
MonotonicityNot monotonic
2024-04-21T19:35:57.936325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 891
73.1%
0 171
 
14.0%
2 115
 
9.4%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
(Missing) 5
 
0.4%
ValueCountFrequency (%)
0 171
 
14.0%
1 891
73.1%
2 115
 
9.4%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 6
 
0.5%
3 30
 
2.5%
2 115
 
9.4%
1 891
73.1%
0 171
 
14.0%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
901 
0
252 
<NA>
 
38
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.0935193
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 901
73.9%
0 252
 
20.7%
<NA> 38
 
3.1%
2 27
 
2.2%
3 1
 
0.1%

Length

2024-04-21T19:35:58.323668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:58.660139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 901
73.9%
0 252
 
20.7%
na 38
 
3.1%
2 27
 
2.2%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
910 
0
251 
<NA>
 
38
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.0935193
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 910
74.7%
0 251
 
20.6%
<NA> 38
 
3.1%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:35:59.036376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:59.373636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 910
74.7%
0 251
 
20.6%
na 38
 
3.1%
2 19
 
1.6%
3 1
 
0.1%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing38
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.89754445
Minimum0
Maximum5
Zeros251
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:59.684271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.59418287
Coefficient of variation (CV)0.66200941
Kurtosis4.8316963
Mean0.89754445
Median Absolute Deviation (MAD)0
Skewness0.834901
Sum1060
Variance0.35305329
MonotonicityNot monotonic
2024-04-21T19:36:00.234731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 817
67.0%
0 251
 
20.6%
2 101
 
8.3%
3 9
 
0.7%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 251
 
20.6%
1 817
67.0%
2 101
 
8.3%
3 9
 
0.7%
4 1
 
0.1%
5 2
 
0.2%
ValueCountFrequency (%)
5 2
 
0.2%
4 1
 
0.1%
3 9
 
0.7%
2 101
 
8.3%
1 817
67.0%
0 251
 
20.6%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.92978003
Minimum0
Maximum5
Zeros250
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:36:00.553161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.63297193
Coefficient of variation (CV)0.680776
Kurtosis3.0582338
Mean0.92978003
Median Absolute Deviation (MAD)0
Skewness0.79963025
Sum1099
Variance0.40065347
MonotonicityNot monotonic
2024-04-21T19:36:00.888976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 791
64.9%
0 250
 
20.5%
2 119
 
9.8%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
0 250
 
20.5%
1 791
64.9%
2 119
 
9.8%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.2%
3 19
 
1.6%
2 119
 
9.8%
1 791
64.9%
0 250
 
20.5%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct536
Distinct (%)71.0%
Missing464
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean73.542053
Minimum0
Maximum723.02
Zeros108
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:36:01.251042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129.945
median57.6
Q397.245
95-th percentile210
Maximum723.02
Range723.02
Interquartile range (IQR)67.3

Descriptive statistics

Standard deviation71.728344
Coefficient of variation (CV)0.97533779
Kurtosis17.371411
Mean73.542053
Median Absolute Deviation (MAD)32.11
Skewness2.9006658
Sum55524.25
Variance5144.9553
MonotonicityNot monotonic
2024-04-21T19:36:01.691267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 108
 
8.9%
33.0 10
 
0.8%
66.0 6
 
0.5%
60.0 5
 
0.4%
49.5 5
 
0.4%
46.2 4
 
0.3%
99.0 4
 
0.3%
57.6 4
 
0.3%
105.0 4
 
0.3%
56.0 4
 
0.3%
Other values (526) 601
49.3%
(Missing) 464
38.1%
ValueCountFrequency (%)
0.0 108
8.9%
1.0 1
 
0.1%
2.0 1
 
0.1%
5.56 1
 
0.1%
5.6 1
 
0.1%
7.5 1
 
0.1%
8.5 1
 
0.1%
9.7 1
 
0.1%
10.23 1
 
0.1%
11.22 1
 
0.1%
ValueCountFrequency (%)
723.02 1
0.1%
700.0 1
0.1%
336.9 1
0.1%
334.0 1
0.1%
329.12 1
0.1%
320.0 1
0.1%
317.0 1
0.1%
310.68 1
0.1%
304.5 1
0.1%
304.12 1
0.1%

Unnamed: 38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1219
Missing (%)100.0%
Memory size10.8 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
01안경업01_02_01_P3250000PHMB2202332500210822000012023-01-31<NA>3폐업3폐업2023-01-31<NA><NA><NA>051-243-3991<NA><NA>부산광역시 중구 부평동1가 35-20부산광역시 중구 광복로 19-1(부평동1가)48979서울광학2023-01-31 16:22:29I2023-02-02 00:40:52<NA>384781.953731179720.1183230000000000.0<NA>
12안경업01_02_01_P3250000PHMB2201832500210822000012018-08-14<NA>3폐업3폐업2021-07-26<NA><NA><NA>2531216<NA><NA>부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경2021-07-26 15:27:58U2021-07-28 02:40:00<NA>384903.524108179742.03163311111111193.22<NA>
23안경업01_02_01_P3250000PHMB2201032500210822000012010-03-12<NA>3폐업3폐업2012-04-06<NA><NA><NA>070-4116-2770<NA>600-042부산광역시 중구 남포동2가 24번지 8호부산광역시 중구 구덕로34번길 3-1 (남포동2가)<NA>아이샵(eye#)안경2012-10-26 09:20:51I2018-08-31 23:59:59<NA>385208.616221179585.320651111111111134.98<NA>
34안경업01_02_01_P3250000PHMB2199332500210822000011993-03-27<NA>3폐업3폐업2018-08-14<NA><NA><NA>051-253-1216<NA>600-819부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경2018-08-14 10:27:02I2018-08-31 23:59:59<NA>384903.524108179742.031633111111111<NA><NA>
45안경업01_02_01_P3250000PHMB2201032500210822000062010-12-27<NA>3폐업3폐업2019-04-16<NA><NA><NA><NA><NA><NA>부산광역시 중구 남포동4가 2번지 5호부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)48953눈사랑안경남포2019-04-16 15:19:24U2019-04-18 02:40:00<NA>385186.028117179577.535415111141144188.2<NA>
56안경업01_02_01_P3250000PHMB2201432500210822000012014-01-02<NA>3폐업3폐업2016-10-12<NA><NA><NA>051-246-0006<NA><NA><NA>부산광역시 중구 광복로 43 (창선동1가)48947갤러리안경원2016-10-12 16:25:24I2018-08-31 23:59:59<NA>385016.604749179699.072538111111111197.49<NA>
67안경업01_02_01_P3250000PHMB2200432500210822000012004-03-12<NA>3폐업3폐업2009-03-20<NA><NA><NA>051-245-1999<NA><NA>부산광역시 중구 남포동6가 85<NA><NA>남포프라자안경2012-03-20 13:58:00I2018-08-31 23:59:59<NA><NA><NA>111111111<NA><NA>
78안경업01_02_01_P3250000PHMB2200532500210822000012005-11-22<NA>3폐업3폐업2018-04-16<NA><NA><NA>051-245-7344<NA><NA>부산광역시 중구 부평동1가 23-27부산광역시 중구 중구로33번길 12 (부평동1가)48978마루안경2018-04-24 15:35:21I2018-08-31 23:59:59<NA>384779.424584179871.25352111111111<NA><NA>
89안경업01_02_01_P3250000PHMB2200632500210822000012006-12-28<NA>3폐업3폐업2021-06-23<NA><NA><NA>051-246-1341<NA><NA>부산광역시 중구 창선동2가 45-17부산광역시 중구 중구로 14 (창선동2가)48953080안경2021-06-23 11:40:02U2021-06-25 02:40:00<NA>384843.682071179657.801434111111111<NA><NA>
910안경업01_02_01_P3250000PHMB2201032500210822000052010-11-09<NA>3폐업3폐업2018-05-31<NA><NA><NA>242-4623<NA>600-063부산광역시 중구 신창동3가 16번지 7호부산광역시 중구 광복로35번길 16 (신창동3가)48946스마일안경2018-06-05 15:05:19I2018-08-31 23:59:59<NA>384931.528183179828.54383611111111149.0<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
12091210안경업01_02_01_P3400000PHMB2201434000130822000032014-08-27<NA>1영업/정상13영업중<NA><NA><NA><NA>728-7229<NA><NA><NA>부산광역시 기장군 정관면 정관로 389 (롯데타워 103호)46008우리동네 안경원2019-06-28 14:53:12U2019-06-30 02:40:00<NA>396839.499809206070.2233611122111272.6<NA>
12101211안경업01_02_01_P3400000PHMB2202334000130822000012023-02-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 장안읍 길천리 212-1 굿모닝빌딩부산광역시 기장군 장안읍 해맞이로 427, 굿모닝빌딩 1층46035데일리안경원 위드렌즈2023-03-13 14:06:26U2023-03-15 02:40:00<NA>407446.38519205750.74393210011000066.0<NA>
12111212안경업01_02_01_P3400000PHMB2202134000130822000022021-07-28<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7585-0909<NA><NA>부산광역시 기장군 정관읍 매학리 713-1 정관타워부산광역시 기장군 정관읍 정관로 561, 3층 303호46015으뜸플러스안경 부산정관점2021-07-29 10:53:16I2021-07-31 00:22:51<NA>397748.735322204683.186892100110000202.97<NA>
12121213안경업01_02_01_P3400000PHMB2202134000130822000032021-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-2233<NA><NA>부산광역시 기장군 일광면 삼성리 830부산광역시 기장군 일광면 해빛6로 107-3, 1층 105,106호46048바라본안경2021-09-06 14:22:36I2021-09-08 00:22:50<NA>402510.108891198551.86926410011000063.5<NA>
12131214안경업01_02_01_P3400000PHMB2202234000130822000042022-11-28<NA>1영업/정상13영업중<NA><NA><NA><NA>051-911-4806<NA><NA>부산광역시 기장군 일광읍 삼성리 825-2 일광제일프라자부산광역시 기장군 일광읍 해빛로 13, 일광제일프라자 1층 104호46048눈사랑 위드렌즈2022-11-28 16:13:26I2022-11-30 00:39:55<NA>402521.177513198590.0505110011000054.5<NA>
12141215안경업01_02_01_P3400000PHMB2202134000130822000012021-06-01<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-3180<NA><NA>부산광역시 기장군 기장읍 교리 342-1부산광역시 기장군 기장읍 차성로 430, 1층 110호46056기장성모안경2021-11-16 14:54:30U2021-11-18 02:40:00<NA>401700.978437197225.4284920011000062.73<NA>
12151216안경업01_02_01_P3400000PHMB2202034000130822000022011-07-28<NA>1영업/정상13영업중<NA><NA><NA><NA>051-545-1518<NA><NA>부산광역시 기장군 기장읍 교리 340-1 꼬마돈까스부산광역시 기장군 기장읍 차성로 424, 1층46056갤러리안경2020-09-14 13:29:24I2020-09-16 00:23:12<NA>401654.858504197228.25010311111112256.6<NA>
12161217안경업01_02_01_P3400000PHMB2202234000130822000032022-08-18<NA>1영업/정상13영업중<NA><NA><NA><NA>051-728-5008<NA><NA>부산광역시 기장군 정관읍 달산리 1221-6부산광역시 기장군 정관읍 정관로 70446021이노티안경 정관점2022-12-09 15:00:16U2022-12-11 02:40:00<NA>399070.084726204598.839584100110000160.0<NA>
12171218안경업01_02_01_P3400000PHMB2201834000130822000012018-11-22<NA>1영업/정상13영업중<NA><NA><NA><NA>051-724-6900<NA><NA>부산광역시 기장군 기장읍 동부리 362번지 1호부산광역시 기장군 기장읍 차성동로 10446063다비치안경 기장시장점2019-05-02 16:27:48U2019-05-04 02:40:00<NA>401723.70543196436.867371222221122213.0<NA>
12181219안경업01_02_01_P3400000PHMB2202234000130822000022022-05-24<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-7212<NA><NA>부산광역시 기장군 일광읍 삼성리 825-2 일광제일프라자부산광역시 기장군 일광읍 해빛로 13, 일광제일프라자 상가동 202호46048오늘 안경원(see channel)2022-12-09 15:01:05U2022-12-11 02:40:00<NA>402521.177513198590.05051100110000107.62<NA>