Overview

Dataset statistics

Number of variables39
Number of observations1222
Missing cells11297
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory399.9 KiB
Average record size in memory335.1 B

Variable types

Numeric10
Categorical11
Text7
DateTime4
Unsupported7

Dataset

Description2023-09-01
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 (65.7%)Imbalance
표본렌즈수 is highly imbalanced (57.4%)Imbalance
조제용연마기수 is highly imbalanced (53.4%)Imbalance
렌즈절단기수 is highly imbalanced (55.0%)Imbalance
인허가취소일자 has 1222 (100.0%) missing valuesMissing
폐업일자 has 784 (64.2%) missing valuesMissing
휴업시작일자 has 1222 (100.0%) missing valuesMissing
휴업종료일자 has 1222 (100.0%) missing valuesMissing
재개업일자 has 1222 (100.0%) missing valuesMissing
소재지전화 has 194 (15.9%) missing valuesMissing
소재지면적 has 1222 (100.0%) missing valuesMissing
소재지우편번호 has 560 (45.8%) missing valuesMissing
소재지전체주소 has 105 (8.6%) missing valuesMissing
도로명전체주소 has 82 (6.7%) missing valuesMissing
도로명우편번호 has 254 (20.8%) missing valuesMissing
업태구분명 has 1222 (100.0%) missing valuesMissing
좌표정보(x) has 91 (7.4%) missing valuesMissing
좌표정보(y) has 91 (7.4%) 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 462 (37.8%) missing valuesMissing
Unnamed: 38 has 1222 (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 250 (20.5%) zerosZeros
동공거리측정기수 has 172 (14.1%) zerosZeros
정점굴절계기수 has 170 (13.9%) zerosZeros
가열기수 has 254 (20.8%) zerosZeros
안경세척기수 has 253 (20.7%) zerosZeros
총면적 has 108 (8.8%) zerosZeros

Reproduction

Analysis started2024-04-21 10:36:40.475713
Analysis finished2024-04-21 10:36:42.016987
Duration1.54 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1222
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean611.5
Minimum1
Maximum1222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:36:42.212241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile62.05
Q1306.25
median611.5
Q3916.75
95-th percentile1160.95
Maximum1222
Range1221
Interquartile range (IQR)610.5

Descriptive statistics

Standard deviation352.90532
Coefficient of variation (CV)0.57711418
Kurtosis-1.2
Mean611.5
Median Absolute Deviation (MAD)305.5
Skewness0
Sum747253
Variance124542.17
MonotonicityStrictly increasing
2024-04-21T19:36:42.660047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
814 1
 
0.1%
821 1
 
0.1%
820 1
 
0.1%
819 1
 
0.1%
818 1
 
0.1%
817 1
 
0.1%
816 1
 
0.1%
815 1
 
0.1%
813 1
 
0.1%
Other values (1212) 1212
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 (%)
1222 1
0.1%
1221 1
0.1%
1220 1
0.1%
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%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
안경업
1222 

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 1222
100.0%

Length

2024-04-21T19:36:43.073103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:43.370690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1222
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
01_02_01_P
1222 

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 1222
100.0%

Length

2024-04-21T19:36:43.679350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:43.979515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1222
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325163.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:36:44.263072image/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 deviation39890.485
Coefficient of variation (CV)0.011996548
Kurtosis-0.73480947
Mean3325163.7
Median Absolute Deviation (MAD)30000
Skewness-0.041420213
Sum4.06335 × 109
Variance1.5912508 × 109
MonotonicityIncreasing
2024-04-21T19:36:44.646833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 179
14.6%
3290000 151
12.4%
3310000 118
9.7%
3330000 105
8.6%
3340000 94
7.7%
3300000 94
7.7%
3250000 82
6.7%
3320000 71
 
5.8%
3390000 69
 
5.6%
3370000 66
 
5.4%
Other values (6) 193
15.8%
ValueCountFrequency (%)
3250000 82
6.7%
3260000 23
 
1.9%
3270000 29
 
2.4%
3280000 28
 
2.3%
3290000 151
12.4%
3300000 94
7.7%
3310000 118
9.7%
3320000 71
5.8%
3330000 105
8.6%
3340000 94
7.7%
ValueCountFrequency (%)
3400000 39
 
3.2%
3390000 69
 
5.6%
3380000 54
 
4.4%
3370000 66
 
5.4%
3360000 20
 
1.6%
3350000 179
14.6%
3340000 94
7.7%
3330000 105
8.6%
3320000 71
 
5.8%
3310000 118
9.7%

관리번호
Text

UNIQUE 

Distinct1222
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-04-21T19:36:45.387349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters30550
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

Unique1222 ?
Unique (%)100.0%

Sample

1st rowPHMB220233250021082200001
2nd rowPHMB220183250021082200001
3rd rowPHMB220103250021082200001
4th rowPHMB219933250021082200001
5th rowPHMB220103250021082200006
ValueCountFrequency (%)
phmb220233250021082200001 1
 
0.1%
phmb220113340025082200001 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%
phmb220053350024082200006 1
 
0.1%
phmb220053350024082200005 1
 
0.1%
Other values (1212) 1212
99.2%
2024-04-21T19:36:46.236356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9990
32.7%
2 6624
21.7%
3 2689
 
8.8%
1 1654
 
5.4%
8 1559
 
5.1%
P 1222
 
4.0%
H 1222
 
4.0%
M 1222
 
4.0%
B 1222
 
4.0%
4 1086
 
3.6%
Other values (4) 2060
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25662
84.0%
Uppercase Letter 4888
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9990
38.9%
2 6624
25.8%
3 2689
 
10.5%
1 1654
 
6.4%
8 1559
 
6.1%
4 1086
 
4.2%
9 981
 
3.8%
5 605
 
2.4%
7 256
 
1.0%
6 218
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 1222
25.0%
H 1222
25.0%
M 1222
25.0%
B 1222
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25662
84.0%
Latin 4888
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9990
38.9%
2 6624
25.8%
3 2689
 
10.5%
1 1654
 
6.4%
8 1559
 
6.1%
4 1086
 
4.2%
9 981
 
3.8%
5 605
 
2.4%
7 256
 
1.0%
6 218
 
0.8%
Latin
ValueCountFrequency (%)
P 1222
25.0%
H 1222
25.0%
M 1222
25.0%
B 1222
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9990
32.7%
2 6624
21.7%
3 2689
 
8.8%
1 1654
 
5.4%
8 1559
 
5.1%
P 1222
 
4.0%
H 1222
 
4.0%
M 1222
 
4.0%
B 1222
 
4.0%
4 1086
 
3.6%
Other values (4) 2060
 
6.7%
Distinct1120
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
Minimum1971-05-18 00:00:00
Maximum2023-07-31 00:00:00
2024-04-21T19:36:46.476728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:36:46.725983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
1
764 
3
450 
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 (%)
1 764
62.5%
3 450
36.8%
4 8
 
0.7%

Length

2024-04-21T19:36:46.964676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:47.138418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 764
62.5%
3 450
36.8%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
영업/정상
764 
폐업
450 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length3.9541735
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 764
62.5%
폐업 450
36.8%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:36:47.331014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:47.513828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 764
62.5%
폐업 450
36.8%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
13
764 
3
450 
24
 
8

Length

Max length2
Median length2
Mean length1.6317512
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 764
62.5%
3 450
36.8%
24 8
 
0.7%

Length

2024-04-21T19:36:47.697430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:48.071635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 764
62.5%
3 450
36.8%
24 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
영업중
764 
폐업
450 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6382979
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 764
62.5%
폐업 450
36.8%
직권폐업 8
 
0.7%

Length

2024-04-21T19:36:48.269707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:36:48.460541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 764
62.5%
폐업 450
36.8%
직권폐업 8
 
0.7%

폐업일자
Date

MISSING 

Distinct406
Distinct (%)92.7%
Missing784
Missing (%)64.2%
Memory size9.7 KiB
Minimum1985-11-28 00:00:00
Maximum2023-07-14 00:00:00
2024-04-21T19:36:48.658952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:36:48.905344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB

소재지전화
Text

MISSING 

Distinct968
Distinct (%)94.2%
Missing194
Missing (%)15.9%
Memory size9.7 KiB
2024-04-21T19:36:49.685500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.314202
Min length7

Characters and Unicode

Total characters11631
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

Unique916 ?
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%
051-647-5766 3
 
0.3%
051-337-7111 3
 
0.3%
051-816-4500 3
 
0.3%
051-625-8471 3
 
0.3%
261-6700 3
 
0.3%
051-623-7778 3
 
0.3%
524-4100 2
 
0.2%
051-257-7090 2
 
0.2%
051-312-2809 2
 
0.2%
Other values (958) 1000
97.3%
2024-04-21T19:36:50.701001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1817
15.6%
0 1762
15.1%
5 1631
14.0%
1 1623
14.0%
2 876
7.5%
8 717
 
6.2%
7 712
 
6.1%
3 704
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 448
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9771
84.0%
Dash Punctuation 1817
 
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 1762
18.0%
5 1631
16.7%
1 1623
16.6%
2 876
9.0%
8 717
7.3%
7 712
7.3%
3 704
 
7.2%
6 700
 
7.2%
4 641
 
6.6%
9 405
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1817
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 11631
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1817
15.6%
0 1762
15.1%
5 1631
14.0%
1 1623
14.0%
2 876
7.5%
8 717
 
6.2%
7 712
 
6.1%
3 704
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 448
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1817
15.6%
0 1762
15.1%
5 1631
14.0%
1 1623
14.0%
2 876
7.5%
8 717
 
6.2%
7 712
 
6.1%
3 704
 
6.1%
6 700
 
6.0%
4 641
 
5.5%
Other values (4) 448
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB

소재지우편번호
Text

MISSING 

Distinct339
Distinct (%)51.2%
Missing560
Missing (%)45.8%
Memory size9.7 KiB
2024-04-21T19:36:51.517785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9909366
Min length5

Characters and Unicode

Total characters4628
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 (%)28.9%

Sample

1st row600-042
2nd row600-819
3rd row600-063
4th row600-045
5th row600-063
ValueCountFrequency (%)
609-839 33
 
5.0%
609-834 8
 
1.2%
609-800 7
 
1.1%
616-852 7
 
1.1%
614-845 7
 
1.1%
614-030 7
 
1.1%
609-822 7
 
1.1%
608-805 7
 
1.1%
619-963 6
 
0.9%
611-082 6
 
0.9%
Other values (329) 567
85.6%
2024-04-21T19:36:52.592421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 770
16.6%
0 723
15.6%
- 659
14.2%
1 606
13.1%
8 516
11.1%
4 288
 
6.2%
9 276
 
6.0%
2 276
 
6.0%
3 256
 
5.5%
7 164
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3969
85.8%
Dash Punctuation 659
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 770
19.4%
0 723
18.2%
1 606
15.3%
8 516
13.0%
4 288
 
7.3%
9 276
 
7.0%
2 276
 
7.0%
3 256
 
6.4%
7 164
 
4.1%
5 94
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 659
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 770
16.6%
0 723
15.6%
- 659
14.2%
1 606
13.1%
8 516
11.1%
4 288
 
6.2%
9 276
 
6.0%
2 276
 
6.0%
3 256
 
5.5%
7 164
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 770
16.6%
0 723
15.6%
- 659
14.2%
1 606
13.1%
8 516
11.1%
4 288
 
6.2%
9 276
 
6.0%
2 276
 
6.0%
3 256
 
5.5%
7 164
 
3.5%

소재지전체주소
Text

MISSING 

Distinct1060
Distinct (%)94.9%
Missing105
Missing (%)8.6%
Memory size9.7 KiB
2024-04-21T19:36:53.804429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.047449
Min length3

Characters and Unicode

Total characters26861
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

Unique1009 ?
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 1088
 
19.4%
금정구 173
 
3.1%
부산진구 146
 
2.6%
1호 117
 
2.1%
남구 106
 
1.9%
사하구 87
 
1.6%
동래구 85
 
1.5%
중구 78
 
1.4%
해운대구 76
 
1.4%
북구 69
 
1.2%
Other values (1458) 3586
63.9%
2024-04-21T19:36:55.277483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4509
 
16.8%
1 1411
 
5.3%
1404
 
5.2%
1341
 
5.0%
1240
 
4.6%
1135
 
4.2%
1124
 
4.2%
1116
 
4.2%
1093
 
4.1%
2 938
 
3.5%
Other values (314) 11550
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16008
59.6%
Decimal Number 5839
 
21.7%
Space Separator 4509
 
16.8%
Dash Punctuation 337
 
1.3%
Uppercase Letter 64
 
0.2%
Other Punctuation 40
 
0.1%
Open Punctuation 30
 
0.1%
Close Punctuation 30
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1404
 
8.8%
1341
 
8.4%
1240
 
7.7%
1135
 
7.1%
1124
 
7.0%
1116
 
7.0%
1093
 
6.8%
810
 
5.1%
770
 
4.8%
753
 
4.7%
Other values (280) 5222
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%
C 5
7.8%
H 5
7.8%
U 4
 
6.2%
Y 4
 
6.2%
L 2
 
3.1%
Other values (3) 4
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 1411
24.2%
2 938
16.1%
3 644
11.0%
4 557
 
9.5%
5 492
 
8.4%
0 404
 
6.9%
6 381
 
6.5%
7 358
 
6.1%
8 333
 
5.7%
9 321
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 32
80.0%
. 5
 
12.5%
@ 2
 
5.0%
/ 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
4509
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 337
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16008
59.6%
Common 10787
40.2%
Latin 66
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1404
 
8.8%
1341
 
8.4%
1240
 
7.7%
1135
 
7.1%
1124
 
7.0%
1116
 
7.0%
1093
 
6.8%
810
 
5.1%
770
 
4.8%
753
 
4.7%
Other values (280) 5222
32.6%
Common
ValueCountFrequency (%)
4509
41.8%
1 1411
 
13.1%
2 938
 
8.7%
3 644
 
6.0%
4 557
 
5.2%
5 492
 
4.6%
0 404
 
3.7%
6 381
 
3.5%
7 358
 
3.3%
- 337
 
3.1%
Other values (9) 756
 
7.0%
Latin
ValueCountFrequency (%)
S 11
16.7%
K 10
15.2%
B 7
10.6%
A 6
9.1%
E 6
9.1%
C 5
7.6%
H 5
7.6%
U 4
 
6.1%
Y 4
 
6.1%
L 2
 
3.0%
Other values (5) 6
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16008
59.6%
ASCII 10853
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4509
41.5%
1 1411
 
13.0%
2 938
 
8.6%
3 644
 
5.9%
4 557
 
5.1%
5 492
 
4.5%
0 404
 
3.7%
6 381
 
3.5%
7 358
 
3.3%
- 337
 
3.1%
Other values (24) 822
 
7.6%
Hangul
ValueCountFrequency (%)
1404
 
8.8%
1341
 
8.4%
1240
 
7.7%
1135
 
7.1%
1124
 
7.0%
1116
 
7.0%
1093
 
6.8%
810
 
5.1%
770
 
4.8%
753
 
4.7%
Other values (280) 5222
32.6%

도로명전체주소
Text

MISSING 

Distinct1066
Distinct (%)93.5%
Missing82
Missing (%)6.7%
Memory size9.7 KiB
2024-04-21T19:36:56.503052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length28.357018
Min length20

Characters and Unicode

Total characters32327
Distinct characters367
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

Unique1005 ?
Unique (%)88.2%

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 1141
 
17.6%
1층 202
 
3.1%
금정구 157
 
2.4%
부산진구 145
 
2.2%
해운대구 104
 
1.6%
남구 95
 
1.5%
동래구 93
 
1.4%
사하구 90
 
1.4%
중구 78
 
1.2%
부전동 71
 
1.1%
Other values (1407) 4317
66.5%
2024-04-21T19:36:58.000519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5357
 
16.6%
1459
 
4.5%
1442
 
4.5%
1392
 
4.3%
1230
 
3.8%
1229
 
3.8%
1174
 
3.6%
1 1157
 
3.6%
1145
 
3.5%
1125
 
3.5%
Other values (357) 15617
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19299
59.7%
Space Separator 5357
 
16.6%
Decimal Number 4569
 
14.1%
Close Punctuation 1121
 
3.5%
Open Punctuation 1121
 
3.5%
Other Punctuation 595
 
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 (%)
1459
 
7.6%
1442
 
7.5%
1392
 
7.2%
1230
 
6.4%
1229
 
6.4%
1174
 
6.1%
1145
 
5.9%
1125
 
5.8%
600
 
3.1%
311
 
1.6%
Other values (316) 8192
42.4%
Uppercase Letter
ValueCountFrequency (%)
S 14
17.7%
K 12
15.2%
B 12
15.2%
A 6
7.6%
H 6
7.6%
E 5
 
6.3%
C 5
 
6.3%
U 4
 
5.1%
Y 4
 
5.1%
G 4
 
5.1%
Other values (7) 7
8.9%
Decimal Number
ValueCountFrequency (%)
1 1157
25.3%
2 701
15.3%
3 430
 
9.4%
0 409
 
9.0%
4 392
 
8.6%
5 336
 
7.4%
7 331
 
7.2%
6 309
 
6.8%
9 263
 
5.8%
8 241
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
l 2
22.2%
s 1
11.1%
b 1
11.1%
i 1
11.1%
h 1
11.1%
k 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 591
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5357
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19299
59.7%
Common 12940
40.0%
Latin 88
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1459
 
7.6%
1442
 
7.5%
1392
 
7.2%
1230
 
6.4%
1229
 
6.4%
1174
 
6.1%
1145
 
5.9%
1125
 
5.8%
600
 
3.1%
311
 
1.6%
Other values (316) 8192
42.4%
Latin
ValueCountFrequency (%)
S 14
15.9%
K 12
13.6%
B 12
13.6%
A 6
 
6.8%
H 6
 
6.8%
E 5
 
5.7%
C 5
 
5.7%
U 4
 
4.5%
Y 4
 
4.5%
G 4
 
4.5%
Other values (14) 16
18.2%
Common
ValueCountFrequency (%)
5357
41.4%
1 1157
 
8.9%
) 1121
 
8.7%
( 1121
 
8.7%
2 701
 
5.4%
, 591
 
4.6%
3 430
 
3.3%
0 409
 
3.2%
4 392
 
3.0%
5 336
 
2.6%
Other values (7) 1325
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19299
59.7%
ASCII 13028
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5357
41.1%
1 1157
 
8.9%
) 1121
 
8.6%
( 1121
 
8.6%
2 701
 
5.4%
, 591
 
4.5%
3 430
 
3.3%
0 409
 
3.1%
4 392
 
3.0%
5 336
 
2.6%
Other values (31) 1413
 
10.8%
Hangul
ValueCountFrequency (%)
1459
 
7.6%
1442
 
7.5%
1392
 
7.2%
1230
 
6.4%
1229
 
6.4%
1174
 
6.1%
1145
 
5.9%
1125
 
5.8%
600
 
3.1%
311
 
1.6%
Other values (316) 8192
42.4%

도로명우편번호
Text

MISSING 

Distinct551
Distinct (%)56.9%
Missing254
Missing (%)20.8%
Memory size9.7 KiB
2024-04-21T19:36:59.111507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1198347
Min length5

Characters and Unicode

Total characters4956
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

Unique349 ?
Unique (%)36.1%

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%
47254 8
 
0.8%
46576 8
 
0.8%
47286 7
 
0.7%
47296 7
 
0.7%
46726 7
 
0.7%
Other values (541) 868
89.7%
2024-04-21T19:37:00.470489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1221
24.6%
8 551
11.1%
7 526
10.6%
6 496
10.0%
9 434
 
8.8%
2 384
 
7.7%
5 373
 
7.5%
0 331
 
6.7%
1 314
 
6.3%
3 268
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4898
98.8%
Dash Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1221
24.9%
8 551
11.2%
7 526
10.7%
6 496
10.1%
9 434
 
8.9%
2 384
 
7.8%
5 373
 
7.6%
0 331
 
6.8%
1 314
 
6.4%
3 268
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4956
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1221
24.6%
8 551
11.1%
7 526
10.6%
6 496
10.0%
9 434
 
8.8%
2 384
 
7.7%
5 373
 
7.5%
0 331
 
6.7%
1 314
 
6.3%
3 268
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1221
24.6%
8 551
11.1%
7 526
10.6%
6 496
10.0%
9 434
 
8.8%
2 384
 
7.7%
5 373
 
7.5%
0 331
 
6.7%
1 314
 
6.3%
3 268
 
5.4%
Distinct981
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-04-21T19:37:01.264368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.9689034
Min length2

Characters and Unicode

Total characters8516
Distinct characters418
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

Unique865 ?
Unique (%)70.8%

Sample

1st row서울광학
2nd row국전안경
3rd row아이샵(eye#)안경
4th row국전안경
5th row눈사랑안경남포
ValueCountFrequency (%)
안경원 69
 
4.4%
안경 46
 
2.9%
갤러리안경 29
 
1.8%
눈사랑안경 22
 
1.4%
안경나라 21
 
1.3%
갤러리안경원 13
 
0.8%
으뜸플러스안경 13
 
0.8%
세컨페이스 12
 
0.8%
오렌즈 12
 
0.8%
초이스안경 12
 
0.8%
Other values (980) 1321
84.1%
2024-04-21T19:37:02.318928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1107
 
13.0%
1105
 
13.0%
407
 
4.8%
348
 
4.1%
302
 
3.5%
283
 
3.3%
223
 
2.6%
200
 
2.3%
132
 
1.6%
0 94
 
1.1%
Other values (408) 4315
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7645
89.8%
Space Separator 348
 
4.1%
Decimal Number 190
 
2.2%
Uppercase Letter 91
 
1.1%
Lowercase Letter 90
 
1.1%
Open Punctuation 61
 
0.7%
Close 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 (%)
1107
 
14.5%
1105
 
14.5%
407
 
5.3%
302
 
4.0%
283
 
3.7%
223
 
2.9%
200
 
2.6%
132
 
1.7%
91
 
1.2%
84
 
1.1%
Other values (350) 3711
48.5%
Uppercase Letter
ValueCountFrequency (%)
O 14
15.4%
E 9
 
9.9%
S 8
 
8.8%
L 6
 
6.6%
G 5
 
5.5%
N 5
 
5.5%
K 5
 
5.5%
C 4
 
4.4%
M 4
 
4.4%
I 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%
s 5
 
5.6%
h 5
 
5.6%
t 5
 
5.6%
Other values (8) 11
12.2%
Decimal Number
ValueCountFrequency (%)
0 94
49.5%
1 42
22.1%
5 24
 
12.6%
8 21
 
11.1%
2 5
 
2.6%
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 (%)
348
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7645
89.8%
Common 689
 
8.1%
Latin 181
 
2.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1107
 
14.5%
1105
 
14.5%
407
 
5.3%
302
 
4.0%
283
 
3.7%
223
 
2.9%
200
 
2.6%
132
 
1.7%
91
 
1.2%
84
 
1.1%
Other values (350) 3711
48.5%
Latin
ValueCountFrequency (%)
e 16
 
8.8%
O 14
 
7.7%
n 11
 
6.1%
E 9
 
5.0%
c 9
 
5.0%
a 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 (%)
348
50.5%
0 94
 
13.6%
( 61
 
8.9%
) 61
 
8.9%
1 42
 
6.1%
5 24
 
3.5%
8 21
 
3.0%
. 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 7644
89.8%
ASCII 865
 
10.2%
None 5
 
0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1107
 
14.5%
1105
 
14.5%
407
 
5.3%
302
 
4.0%
283
 
3.7%
223
 
2.9%
200
 
2.6%
132
 
1.7%
91
 
1.2%
84
 
1.1%
Other values (349) 3710
48.5%
ASCII
ValueCountFrequency (%)
348
40.2%
0 94
 
10.9%
( 61
 
7.1%
) 61
 
7.1%
1 42
 
4.9%
5 24
 
2.8%
8 21
 
2.4%
e 16
 
1.8%
O 14
 
1.6%
. 14
 
1.6%
Other values (45) 170
19.7%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Distinct1196
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
Minimum2008-11-20 14:16:39
Maximum2023-07-31 15:16:13
2024-04-21T19:37:02.550882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:37:02.794569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
I
890 
U
332 

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 890
72.8%
U 332
 
27.2%

Length

2024-04-21T19:37:03.009010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:03.179380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 890
72.8%
u 332
 
27.2%
Distinct361
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-08-02 00:18:52
2024-04-21T19:37:03.359276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:37:03.602785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1222
Missing (%)100.0%
Memory size10.9 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct955
Distinct (%)84.4%
Missing91
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean388122.15
Minimum367108.19
Maximum407446.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:03.858898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379705.01
Q1384874.52
median388524.94
Q3391306.95
95-th percentile397573.08
Maximum407446.39
Range40338.198
Interquartile range (IQR)6432.4331

Descriptive statistics

Standard deviation5341.9891
Coefficient of variation (CV)0.01376368
Kurtosis0.5359329
Mean388122.15
Median Absolute Deviation (MAD)3274.8065
Skewness0.031367827
Sum4.3896615 × 108
Variance28536847
MonotonicityNot monotonic
2024-04-21T19:37:04.117292image/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%
393952.264486105 5
 
0.4%
389314.662086382 5
 
0.4%
389097.800933845 5
 
0.4%
389816.233000769 5
 
0.4%
387920.292113406 5
 
0.4%
398237.363461482 5
 
0.4%
395388.715069604 4
 
0.3%
384903.52410762 4
 
0.3%
Other values (945) 1079
88.3%
(Missing) 91
 
7.4%
ValueCountFrequency (%)
367108.187127244 1
0.1%
371179.513984489 1
0.1%
371180.376049706 1
0.1%
373401.811505138 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%
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 

Distinct955
Distinct (%)84.4%
Missing91
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean187388.93
Minimum174016.55
Maximum206209.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:04.372040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178695.17
Q1183544.39
median187141.15
Q3191889.01
95-th percentile196320.68
Maximum206209.45
Range32192.899
Interquartile range (IQR)8344.628

Descriptive statistics

Standard deviation5887.4041
Coefficient of variation (CV)0.0314181
Kurtosis-0.16676764
Mean187388.93
Median Absolute Deviation (MAD)4393.2899
Skewness0.18840203
Sum2.1193688 × 108
Variance34661527
MonotonicityNot monotonic
2024-04-21T19:37:04.611059image/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%
187602.933160728 5
 
0.4%
194669.898821674 5
 
0.4%
192260.811648263 5
 
0.4%
193329.605871168 5
 
0.4%
186157.316240541 5
 
0.4%
187720.511056894 5
 
0.4%
186268.853282623 4
 
0.3%
179742.031632526 4
 
0.3%
Other values (945) 1079
88.3%
(Missing) 91
 
7.4%
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 size9.7 KiB
1
1013 
0
170 
2
 
35
<NA>
 
3
3
 
1

Length

Max length4
Median length1
Mean length1.007365
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1013
82.9%
0 170
 
13.9%
2 35
 
2.9%
<NA> 3
 
0.2%
3 1
 
0.1%

Length

2024-04-21T19:37:04.855076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:05.049297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1013
82.9%
0 170
 
13.9%
2 35
 
2.9%
na 3
 
0.2%
3 1
 
0.1%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
1
904 
0
250 
2
 
33
<NA>
 
28
3
 
6

Length

Max length4
Median length1
Mean length1.0703764
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 904
74.0%
0 250
 
20.5%
2 33
 
2.7%
<NA> 28
 
2.3%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:37:05.255655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:05.455604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 904
74.0%
0 250
 
20.5%
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%
Mean0.85147679
Minimum0
Maximum11
Zeros250
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:05.846642image/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 deviation0.59973243
Coefficient of variation (CV)0.70434383
Kurtosis72.389164
Mean0.85147679
Median Absolute Deviation (MAD)0
Skewness4.5637853
Sum1009
Variance0.35967898
MonotonicityNot monotonic
2024-04-21T19:37:06.025552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 883
72.3%
0 250
 
20.5%
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 (%)
0 250
 
20.5%
1 883
72.3%
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
72.3%
0 250
 
20.5%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing3
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.93027071
Minimum0
Maximum10
Zeros172
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:06.206726image/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 deviation0.58657183
Coefficient of variation (CV)0.63053885
Kurtosis57.792309
Mean0.93027071
Median Absolute Deviation (MAD)0
Skewness4.6577717
Sum1134
Variance0.34406651
MonotonicityNot monotonic
2024-04-21T19:37:06.395278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 997
81.6%
0 172
 
14.1%
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 (%)
0 172
 
14.1%
1 997
81.6%
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%
1 997
81.6%
0 172
 
14.1%

정점굴절계기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.5%
Missing5
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.0221857
Minimum0
Maximum5
Zeros170
Zeros (%)13.9%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:06.575044image/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 deviation0.62460579
Coefficient of variation (CV)0.61104923
Kurtosis4.9848896
Mean1.0221857
Median Absolute Deviation (MAD)0
Skewness1.2825483
Sum1244
Variance0.39013239
MonotonicityNot monotonic
2024-04-21T19:37:06.757460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 895
73.2%
0 170
 
13.9%
2 115
 
9.4%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
(Missing) 5
 
0.4%
ValueCountFrequency (%)
0 170
 
13.9%
1 895
73.2%
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%
1 895
73.2%
0 170
 
13.9%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
1
901 
0
255 
<NA>
 
38
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.0932897
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 901
73.7%
0 255
 
20.9%
<NA> 38
 
3.1%
2 27
 
2.2%
3 1
 
0.1%

Length

2024-04-21T19:37:06.968189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:07.163420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 901
73.7%
0 255
 
20.9%
na 38
 
3.1%
2 27
 
2.2%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
1
910 
0
254 
<NA>
 
38
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.0932897
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 910
74.5%
0 254
 
20.8%
<NA> 38
 
3.1%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:37:07.371732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:07.565615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 910
74.5%
0 254
 
20.8%
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%
Mean0.89527027
Minimum0
Maximum5
Zeros254
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:07.739400image/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 deviation0.59514343
Coefficient of variation (CV)0.66476398
Kurtosis4.7872252
Mean0.89527027
Median Absolute Deviation (MAD)0
Skewness0.83152443
Sum1060
Variance0.3541957
MonotonicityNot monotonic
2024-04-21T19:37:07.922244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 817
66.9%
0 254
 
20.8%
2 101
 
8.3%
3 9
 
0.7%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 254
 
20.8%
1 817
66.9%
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
66.9%
0 254
 
20.8%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing37
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.92742616
Minimum0
Maximum5
Zeros253
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:08.097893image/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 deviation0.63389525
Coefficient of variation (CV)0.68349942
Kurtosis3.0312176
Mean0.92742616
Median Absolute Deviation (MAD)0
Skewness0.79727021
Sum1099
Variance0.40182318
MonotonicityNot monotonic
2024-04-21T19:37:08.279575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 791
64.7%
0 253
 
20.7%
2 119
 
9.7%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 37
 
3.0%
ValueCountFrequency (%)
0 253
 
20.7%
1 791
64.7%
2 119
 
9.7%
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
 
9.7%
1 791
64.7%
0 253
 
20.7%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct540
Distinct (%)71.1%
Missing462
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean73.311921
Minimum0
Maximum723.02
Zeros108
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-04-21T19:37:08.494551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q129.85
median57.6
Q396.82
95-th percentile210
Maximum723.02
Range723.02
Interquartile range (IQR)66.97

Descriptive statistics

Standard deviation71.558414
Coefficient of variation (CV)0.97608156
Kurtosis17.467609
Mean73.311921
Median Absolute Deviation (MAD)31.88
Skewness2.910531
Sum55717.06
Variance5120.6066
MonotonicityNot monotonic
2024-04-21T19:37:08.749361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 108
 
8.8%
33.0 10
 
0.8%
66.0 6
 
0.5%
60.0 5
 
0.4%
49.5 5
 
0.4%
57.6 4
 
0.3%
56.0 4
 
0.3%
105.0 4
 
0.3%
99.0 4
 
0.3%
46.2 4
 
0.3%
Other values (530) 606
49.6%
(Missing) 462
37.8%
ValueCountFrequency (%)
0.0 108
8.8%
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 

Missing1222
Missing (%)100.0%
Memory size10.9 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
12121213안경업01_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>
12131214안경업01_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>
12141215안경업01_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>
12151216안경업01_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>
12161217안경업01_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>
12171218안경업01_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>
12181219안경업01_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>
12191220안경업01_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>
12201221안경업01_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>
12211222안경업01_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>