Overview

Dataset statistics

Number of variables39
Number of observations1216
Missing cells11255
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory397.9 KiB
Average record size in memory335.1 B

Variable types

Numeric10
Categorical11
Text7
DateTime4
Unsupported7

Dataset

Description2023-07-01
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 (65.3%)Imbalance
표본렌즈수 is highly imbalanced (57.5%)Imbalance
조제용연마기수 is highly imbalanced (53.6%)Imbalance
렌즈절단기수 is highly imbalanced (55.1%)Imbalance
인허가취소일자 has 1216 (100.0%) missing valuesMissing
폐업일자 has 782 (64.3%) missing valuesMissing
휴업시작일자 has 1216 (100.0%) missing valuesMissing
휴업종료일자 has 1216 (100.0%) missing valuesMissing
재개업일자 has 1216 (100.0%) missing valuesMissing
소재지전화 has 190 (15.6%) missing valuesMissing
소재지면적 has 1216 (100.0%) missing valuesMissing
소재지우편번호 has 552 (45.4%) missing valuesMissing
소재지전체주소 has 106 (8.7%) missing valuesMissing
도로명전체주소 has 82 (6.7%) missing valuesMissing
도로명우편번호 has 255 (21.0%) missing valuesMissing
업태구분명 has 1216 (100.0%) missing valuesMissing
좌표정보(x) has 92 (7.6%) missing valuesMissing
좌표정보(y) has 92 (7.6%) missing valuesMissing
측정의자수 has 38 (3.1%) missing valuesMissing
가열기수 has 39 (3.2%) missing valuesMissing
안경세척기수 has 38 (3.1%) missing valuesMissing
총면적 has 467 (38.4%) missing valuesMissing
Unnamed: 38 has 1216 (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 243 (20.0%) zerosZeros
동공거리측정기수 has 172 (14.1%) zerosZeros
정점굴절계기수 has 170 (14.0%) zerosZeros
가열기수 has 247 (20.3%) zerosZeros
안경세척기수 has 246 (20.2%) zerosZeros
총면적 has 105 (8.6%) zerosZeros

Reproduction

Analysis started2024-04-21 10:34:50.595150
Analysis finished2024-04-21 10:34:52.247499
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1216
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean608.5
Minimum1
Maximum1216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:34:52.440871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile61.75
Q1304.75
median608.5
Q3912.25
95-th percentile1155.25
Maximum1216
Range1215
Interquartile range (IQR)607.5

Descriptive statistics

Standard deviation351.17327
Coefficient of variation (CV)0.57711302
Kurtosis-1.2
Mean608.5
Median Absolute Deviation (MAD)304
Skewness0
Sum739936
Variance123322.67
MonotonicityStrictly increasing
2024-04-21T19:34:52.885933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
810 1
 
0.1%
817 1
 
0.1%
816 1
 
0.1%
815 1
 
0.1%
814 1
 
0.1%
813 1
 
0.1%
812 1
 
0.1%
811 1
 
0.1%
809 1
 
0.1%
Other values (1206) 1206
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 (%)
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%
1209 1
0.1%
1208 1
0.1%
1207 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
안경업
1216 

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 1216
100.0%

Length

2024-04-21T19:34:53.295123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:53.594256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1216
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
01_02_01_P
1216 

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 1216
100.0%

Length

2024-04-21T19:34:53.903189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:54.203878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1216
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325156.2
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:34:54.486968image/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 deviation39942.039
Coefficient of variation (CV)0.012012079
Kurtosis-0.73673745
Mean3325156.2
Median Absolute Deviation (MAD)30000
Skewness-0.04103578
Sum4.04339 × 109
Variance1.5953665 × 109
MonotonicityIncreasing
2024-04-21T19:34:54.870046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 177
14.6%
3290000 150
12.3%
3310000 117
9.6%
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 117
9.6%
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 177
14.6%
3340000 94
7.7%
3330000 105
8.6%
3320000 71
5.8%
3310000 117
9.6%

관리번호
Text

UNIQUE 

Distinct1216
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:34:55.610470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters30400
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

Unique1216 ?
Unique (%)100.0%

Sample

1st rowPHMB220233250021082200001
2nd rowPHMB220183250021082200001
3rd rowPHMB220103250021082200001
4th rowPHMB219933250021082200001
5th rowPHMB220103250021082200006
ValueCountFrequency (%)
phmb220233250021082200001 1
 
0.1%
phmb220053350024082200005 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%
phmb220073350024082200002 1
 
0.1%
phmb220183250021082200001 1
 
0.1%
Other values (1206) 1206
99.2%
2024-04-21T19:34:56.728894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9941
32.7%
2 6583
21.7%
3 2672
 
8.8%
1 1651
 
5.4%
8 1553
 
5.1%
P 1216
 
4.0%
H 1216
 
4.0%
M 1216
 
4.0%
B 1216
 
4.0%
4 1080
 
3.6%
Other values (4) 2056
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25536
84.0%
Uppercase Letter 4864
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9941
38.9%
2 6583
25.8%
3 2672
 
10.5%
1 1651
 
6.5%
8 1553
 
6.1%
4 1080
 
4.2%
9 980
 
3.8%
5 603
 
2.4%
7 256
 
1.0%
6 217
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 1216
25.0%
H 1216
25.0%
M 1216
25.0%
B 1216
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25536
84.0%
Latin 4864
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9941
38.9%
2 6583
25.8%
3 2672
 
10.5%
1 1651
 
6.5%
8 1553
 
6.1%
4 1080
 
4.2%
9 980
 
3.8%
5 603
 
2.4%
7 256
 
1.0%
6 217
 
0.8%
Latin
ValueCountFrequency (%)
P 1216
25.0%
H 1216
25.0%
M 1216
25.0%
B 1216
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9941
32.7%
2 6583
21.7%
3 2672
 
8.8%
1 1651
 
5.4%
8 1553
 
5.1%
P 1216
 
4.0%
H 1216
 
4.0%
M 1216
 
4.0%
B 1216
 
4.0%
4 1080
 
3.6%
Other values (4) 2056
 
6.8%
Distinct1114
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum1971-05-18 00:00:00
Maximum2023-05-30 00:00:00
2024-04-21T19:34:57.020787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:34:57.272986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
762 
3
446 
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 (%)
1 762
62.7%
3 446
36.7%
4 8
 
0.7%

Length

2024-04-21T19:34:57.507070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:57.679294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 762
62.7%
3 446
36.7%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업/정상
762 
폐업
446 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length3.9588816
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 762
62.7%
폐업 446
36.7%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:34:57.869251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:58.053454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 762
62.7%
폐업 446
36.7%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
13
762 
3
446 
24
 
8

Length

Max length2
Median length2
Mean length1.6332237
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 762
62.7%
3 446
36.7%
24 8
 
0.7%

Length

2024-04-21T19:34:58.235691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:58.410002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 762
62.7%
3 446
36.7%
24 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업중
762 
폐업
446 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6398026
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 762
62.7%
폐업 446
36.7%
직권폐업 8
 
0.7%

Length

2024-04-21T19:34:58.607139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:34:58.798816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 762
62.7%
폐업 446
36.7%
직권폐업 8
 
0.7%

폐업일자
Date

MISSING 

Distinct403
Distinct (%)92.9%
Missing782
Missing (%)64.3%
Memory size9.6 KiB
Minimum1985-11-28 00:00:00
Maximum2023-05-31 00:00:00
2024-04-21T19:34:58.996495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:34:59.241401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB

소재지전화
Text

MISSING 

Distinct966
Distinct (%)94.2%
Missing190
Missing (%)15.6%
Memory size9.6 KiB
2024-04-21T19:35:00.012477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.309942
Min length7

Characters and Unicode

Total characters11604
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%
2024-04-21T19:35:01.007708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1812
15.6%
0 1759
15.2%
5 1625
14.0%
1 1613
13.9%
2 876
7.5%
8 712
 
6.1%
7 712
 
6.1%
3 706
 
6.1%
6 700
 
6.0%
4 642
 
5.5%
Other values (4) 447
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9749
84.0%
Dash Punctuation 1812
 
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 1759
18.0%
5 1625
16.7%
1 1613
16.5%
2 876
9.0%
8 712
7.3%
7 712
7.3%
3 706
7.2%
6 700
 
7.2%
4 642
 
6.6%
9 404
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1812
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 11604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1812
15.6%
0 1759
15.2%
5 1625
14.0%
1 1613
13.9%
2 876
7.5%
8 712
 
6.1%
7 712
 
6.1%
3 706
 
6.1%
6 700
 
6.0%
4 642
 
5.5%
Other values (4) 447
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1812
15.6%
0 1759
15.2%
5 1625
14.0%
1 1613
13.9%
2 876
7.5%
8 712
 
6.1%
7 712
 
6.1%
3 706
 
6.1%
6 700
 
6.0%
4 642
 
5.5%
Other values (4) 447
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB

소재지우편번호
Text

MISSING 

Distinct339
Distinct (%)51.1%
Missing552
Missing (%)45.4%
Memory size9.6 KiB
2024-04-21T19:35:01.834439image/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%
2024-04-21T19:35:02.902194image/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 

Distinct1054
Distinct (%)95.0%
Missing106
Missing (%)8.7%
Memory size9.6 KiB
2024-04-21T19:35:04.184496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.072973
Min length3

Characters and Unicode

Total characters26721
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

Unique1003 ?
Unique (%)90.4%

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 1081
 
19.4%
금정구 171
 
3.1%
부산진구 145
 
2.6%
1호 117
 
2.1%
남구 105
 
1.9%
사하구 87
 
1.6%
동래구 84
 
1.5%
중구 78
 
1.4%
해운대구 75
 
1.3%
북구 69
 
1.2%
Other values (1452) 3572
64.0%
2024-04-21T19:35:05.935579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4489
 
16.8%
1 1409
 
5.3%
1394
 
5.2%
1332
 
5.0%
1232
 
4.6%
1128
 
4.2%
1117
 
4.2%
1109
 
4.2%
1086
 
4.1%
2 935
 
3.5%
Other values (314) 11490
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15923
59.6%
Decimal Number 5811
 
21.7%
Space Separator 4489
 
16.8%
Dash Punctuation 329
 
1.2%
Uppercase Letter 64
 
0.2%
Other Punctuation 41
 
0.2%
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 (%)
1394
 
8.8%
1332
 
8.4%
1232
 
7.7%
1128
 
7.1%
1117
 
7.0%
1109
 
7.0%
1086
 
6.8%
811
 
5.1%
771
 
4.8%
755
 
4.7%
Other values (280) 5188
32.6%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.2%
K 10
15.6%
B 7
10.9%
E 6
9.4%
A 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 1409
24.2%
2 935
16.1%
3 641
11.0%
4 553
 
9.5%
5 487
 
8.4%
0 404
 
7.0%
6 377
 
6.5%
7 357
 
6.1%
8 332
 
5.7%
9 316
 
5.4%
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 (%)
4489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 329
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 15923
59.6%
Common 10732
40.2%
Latin 66
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1394
 
8.8%
1332
 
8.4%
1232
 
7.7%
1128
 
7.1%
1117
 
7.0%
1109
 
7.0%
1086
 
6.8%
811
 
5.1%
771
 
4.8%
755
 
4.7%
Other values (280) 5188
32.6%
Common
ValueCountFrequency (%)
4489
41.8%
1 1409
 
13.1%
2 935
 
8.7%
3 641
 
6.0%
4 553
 
5.2%
5 487
 
4.5%
0 404
 
3.8%
6 377
 
3.5%
7 357
 
3.3%
8 332
 
3.1%
Other values (9) 748
 
7.0%
Latin
ValueCountFrequency (%)
S 11
16.7%
K 10
15.2%
B 7
10.6%
E 6
9.1%
A 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 15923
59.6%
ASCII 10798
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4489
41.6%
1 1409
 
13.0%
2 935
 
8.7%
3 641
 
5.9%
4 553
 
5.1%
5 487
 
4.5%
0 404
 
3.7%
6 377
 
3.5%
7 357
 
3.3%
8 332
 
3.1%
Other values (24) 814
 
7.5%
Hangul
ValueCountFrequency (%)
1394
 
8.8%
1332
 
8.4%
1232
 
7.7%
1128
 
7.1%
1117
 
7.0%
1109
 
7.0%
1086
 
6.8%
811
 
5.1%
771
 
4.8%
755
 
4.7%
Other values (280) 5188
32.6%

도로명전체주소
Text

MISSING 

Distinct1060
Distinct (%)93.5%
Missing82
Missing (%)6.7%
Memory size9.6 KiB
2024-04-21T19:35:07.103646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length28.319224
Min length20

Characters and Unicode

Total characters32114
Distinct characters369
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

Unique999 ?
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 1135
 
17.6%
1층 199
 
3.1%
금정구 155
 
2.4%
부산진구 144
 
2.2%
해운대구 104
 
1.6%
남구 94
 
1.5%
동래구 92
 
1.4%
사하구 90
 
1.4%
중구 78
 
1.2%
부전동 71
 
1.1%
Other values (1401) 4286
66.5%
2024-04-21T19:35:08.539876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5318
 
16.6%
1449
 
4.5%
1434
 
4.5%
1384
 
4.3%
1224
 
3.8%
1223
 
3.8%
1168
 
3.6%
1 1148
 
3.6%
1139
 
3.5%
1119
 
3.5%
Other values (359) 15508
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19185
59.7%
Space Separator 5318
 
16.6%
Decimal Number 4528
 
14.1%
Close Punctuation 1115
 
3.5%
Open Punctuation 1115
 
3.5%
Other Punctuation 588
 
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 (%)
1449
 
7.6%
1434
 
7.5%
1384
 
7.2%
1224
 
6.4%
1223
 
6.4%
1168
 
6.1%
1139
 
5.9%
1119
 
5.8%
600
 
3.1%
304
 
1.6%
Other values (318) 8141
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%
Y 4
 
5.1%
G 4
 
5.1%
U 4
 
5.1%
Other values (7) 7
8.9%
Decimal Number
ValueCountFrequency (%)
1 1148
25.4%
2 695
15.3%
3 424
 
9.4%
0 405
 
8.9%
4 389
 
8.6%
5 333
 
7.4%
7 329
 
7.3%
6 305
 
6.7%
9 261
 
5.8%
8 239
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
l 2
22.2%
e 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 (%)
, 584
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5318
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19185
59.7%
Common 12841
40.0%
Latin 88
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1449
 
7.6%
1434
 
7.5%
1384
 
7.2%
1224
 
6.4%
1223
 
6.4%
1168
 
6.1%
1139
 
5.9%
1119
 
5.8%
600
 
3.1%
304
 
1.6%
Other values (318) 8141
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%
Y 4
 
4.5%
G 4
 
4.5%
U 4
 
4.5%
Other values (14) 16
18.2%
Common
ValueCountFrequency (%)
5318
41.4%
1 1148
 
8.9%
) 1115
 
8.7%
( 1115
 
8.7%
2 695
 
5.4%
, 584
 
4.5%
3 424
 
3.3%
0 405
 
3.2%
4 389
 
3.0%
5 333
 
2.6%
Other values (7) 1315
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19185
59.7%
ASCII 12929
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5318
41.1%
1 1148
 
8.9%
) 1115
 
8.6%
( 1115
 
8.6%
2 695
 
5.4%
, 584
 
4.5%
3 424
 
3.3%
0 405
 
3.1%
4 389
 
3.0%
5 333
 
2.6%
Other values (31) 1403
 
10.9%
Hangul
ValueCountFrequency (%)
1449
 
7.6%
1434
 
7.5%
1384
 
7.2%
1224
 
6.4%
1223
 
6.4%
1168
 
6.1%
1139
 
5.9%
1119
 
5.8%
600
 
3.1%
304
 
1.6%
Other values (318) 8141
42.4%

도로명우편번호
Text

MISSING 

Distinct551
Distinct (%)57.3%
Missing255
Missing (%)21.0%
Memory size9.6 KiB
2024-04-21T19:35:09.654632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1207076
Min length5

Characters and Unicode

Total characters4921
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 (%)36.5%

Sample

1st row48979
2nd row48946
3rd row48946
4th row48953
5th row48947
ValueCountFrequency (%)
48946 21
 
2.2%
48953 13
 
1.4%
46291 11
 
1.1%
48945 10
 
1.0%
46576 8
 
0.8%
47254 8
 
0.8%
47295 8
 
0.8%
47296 7
 
0.7%
47286 7
 
0.7%
47289 7
 
0.7%
Other values (541) 861
89.6%
2024-04-21T19:35:11.012444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1213
24.6%
8 549
11.2%
7 519
10.5%
6 491
10.0%
9 435
 
8.8%
2 379
 
7.7%
5 371
 
7.5%
0 330
 
6.7%
1 312
 
6.3%
3 264
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4863
98.8%
Dash Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1213
24.9%
8 549
11.3%
7 519
10.7%
6 491
10.1%
9 435
 
8.9%
2 379
 
7.8%
5 371
 
7.6%
0 330
 
6.8%
1 312
 
6.4%
3 264
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4921
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1213
24.6%
8 549
11.2%
7 519
10.5%
6 491
10.0%
9 435
 
8.8%
2 379
 
7.7%
5 371
 
7.5%
0 330
 
6.7%
1 312
 
6.3%
3 264
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4921
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1213
24.6%
8 549
11.2%
7 519
10.5%
6 491
10.0%
9 435
 
8.8%
2 379
 
7.7%
5 371
 
7.5%
0 330
 
6.7%
1 312
 
6.3%
3 264
 
5.4%
Distinct973
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:35:11.719504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.9383224
Min length2

Characters and Unicode

Total characters8437
Distinct characters416
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

Unique857 ?
Unique (%)70.5%

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%
초이스안경 12
 
0.8%
오렌즈 12
 
0.8%
으뜸플러스안경 12
 
0.8%
이노티안경 11
 
0.7%
Other values (972) 1309
84.1%
2024-04-21T19:35:12.648728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1100
 
13.0%
1098
 
13.0%
406
 
4.8%
340
 
4.0%
297
 
3.5%
280
 
3.3%
223
 
2.6%
197
 
2.3%
131
 
1.6%
0 93
 
1.1%
Other values (406) 4272
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7578
89.8%
Space Separator 340
 
4.0%
Decimal Number 188
 
2.2%
Lowercase Letter 90
 
1.1%
Uppercase Letter 90
 
1.1%
Close Punctuation 61
 
0.7%
Open Punctuation 61
 
0.7%
Other Punctuation 23
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1100
 
14.5%
1098
 
14.5%
406
 
5.4%
297
 
3.9%
280
 
3.7%
223
 
2.9%
197
 
2.6%
131
 
1.7%
89
 
1.2%
83
 
1.1%
Other values (348) 3674
48.5%
Uppercase Letter
ValueCountFrequency (%)
O 14
15.6%
E 9
 
10.0%
S 8
 
8.9%
L 6
 
6.7%
K 5
 
5.6%
N 5
 
5.6%
G 5
 
5.6%
M 4
 
4.4%
I 4
 
4.4%
C 4
 
4.4%
Other values (12) 26
28.9%
Lowercase Letter
ValueCountFrequency (%)
e 16
17.8%
n 11
12.2%
c 9
10.0%
a 9
10.0%
l 7
7.8%
i 6
 
6.7%
o 6
 
6.7%
t 5
 
5.6%
s 5
 
5.6%
h 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
60.9%
· 4
 
17.4%
& 3
 
13.0%
# 2
 
8.7%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
340
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 7578
89.8%
Common 678
 
8.0%
Latin 180
 
2.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1100
 
14.5%
1098
 
14.5%
406
 
5.4%
297
 
3.9%
280
 
3.7%
223
 
2.9%
197
 
2.6%
131
 
1.7%
89
 
1.2%
83
 
1.1%
Other values (348) 3674
48.5%
Latin
ValueCountFrequency (%)
e 16
 
8.9%
O 14
 
7.8%
n 11
 
6.1%
c 9
 
5.0%
a 9
 
5.0%
E 9
 
5.0%
S 8
 
4.4%
l 7
 
3.9%
L 6
 
3.3%
i 6
 
3.3%
Other values (30) 85
47.2%
Common
ValueCountFrequency (%)
340
50.1%
0 93
 
13.7%
) 61
 
9.0%
( 61
 
9.0%
1 42
 
6.2%
5 23
 
3.4%
8 21
 
3.1%
. 14
 
2.1%
2 5
 
0.7%
· 4
 
0.6%
Other values (7) 14
 
2.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7577
89.8%
ASCII 853
 
10.1%
None 5
 
0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1100
 
14.5%
1098
 
14.5%
406
 
5.4%
297
 
3.9%
280
 
3.7%
223
 
2.9%
197
 
2.6%
131
 
1.7%
89
 
1.2%
83
 
1.1%
Other values (347) 3673
48.5%
ASCII
ValueCountFrequency (%)
340
39.9%
0 93
 
10.9%
) 61
 
7.2%
( 61
 
7.2%
1 42
 
4.9%
5 23
 
2.7%
8 21
 
2.5%
e 16
 
1.9%
O 14
 
1.6%
. 14
 
1.6%
Other values (45) 168
19.7%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
CJK
ValueCountFrequency (%)
1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Distinct1190
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2008-11-20 14:16:39
Maximum2023-05-31 13:41:27
2024-04-21T19:35:12.882313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:13.124597image/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
896 
U
320 

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 896
73.7%
U 320
 
26.3%

Length

2024-04-21T19:35:13.338656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:13.506723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 896
73.7%
u 320
 
26.3%
Distinct350
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-06-02 02:40:00
2024-04-21T19:35:13.689186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:35:13.929017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1216
Missing (%)100.0%
Memory size10.8 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct952
Distinct (%)84.7%
Missing92
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean388135.07
Minimum367108.19
Maximum407446.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:14.183584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379712.13
Q1384874.52
median388513.46
Q3391309.52
95-th percentile397583.14
Maximum407446.39
Range40338.198
Interquartile range (IQR)6435.0014

Descriptive statistics

Standard deviation5335.1025
Coefficient of variation (CV)0.013745479
Kurtosis0.52190217
Mean388135.07
Median Absolute Deviation (MAD)3269.5661
Skewness0.047125371
Sum4.3626382 × 108
Variance28463318
MonotonicityNot monotonic
2024-04-21T19:35:14.441233image/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%
389816.233000769 5
 
0.4%
393952.264486105 5
 
0.4%
389314.662086382 5
 
0.4%
398237.363461482 5
 
0.4%
384874.515689472 4
 
0.3%
384903.52410762 4
 
0.3%
385590.814676765 4
 
0.3%
Other values (942) 1073
88.2%
(Missing) 92
 
7.6%
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 

Distinct952
Distinct (%)84.7%
Missing92
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean187381.04
Minimum174016.55
Maximum206209.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:14.694936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178684.73
Q1183542.35
median187126.28
Q3191884
95-th percentile196359.03
Maximum206209.45
Range32192.899
Interquartile range (IQR)8341.6462

Descriptive statistics

Standard deviation5891.0536
Coefficient of variation (CV)0.031438899
Kurtosis-0.16153734
Mean187381.04
Median Absolute Deviation (MAD)4404.3768
Skewness0.19355474
Sum2.1061629 × 108
Variance34704512
MonotonicityNot monotonic
2024-04-21T19:35:14.938590image/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%
193329.605871168 5
 
0.4%
187602.933160728 5
 
0.4%
194669.898821674 5
 
0.4%
187720.511056894 5
 
0.4%
179978.235223733 4
 
0.3%
179742.031632526 4
 
0.3%
179553.867031936 4
 
0.3%
Other values (942) 1073
88.2%
(Missing) 92
 
7.6%
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
1006 
0
170 
2
 
35
<NA>
 
4
3
 
1

Length

Max length4
Median length1
Mean length1.0098684
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1006
82.7%
0 170
 
14.0%
2 35
 
2.9%
<NA> 4
 
0.3%
3 1
 
0.1%

Length

2024-04-21T19:35:15.221351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:15.415822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1006
82.7%
0 170
 
14.0%
2 35
 
2.9%
na 4
 
0.3%
3 1
 
0.1%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
904 
0
243 
2
 
33
<NA>
 
29
3
 
6

Length

Max length4
Median length1
Mean length1.0731908
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 904
74.3%
0 243
 
20.0%
2 33
 
2.7%
<NA> 29
 
2.4%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:35:15.621208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:15.819407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 904
74.3%
0 243
 
20.0%
2 33
 
2.7%
na 29
 
2.4%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing38
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.8565365
Minimum0
Maximum11
Zeros243
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:15.995218image/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 deviation0.59789682
Coefficient of variation (CV)0.69804009
Kurtosis73.593438
Mean0.8565365
Median Absolute Deviation (MAD)0
Skewness4.6251636
Sum1009
Variance0.3574806
MonotonicityNot monotonic
2024-04-21T19:35:16.174883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 883
72.6%
0 243
 
20.0%
2 43
 
3.5%
3 4
 
0.3%
4 3
 
0.2%
5 1
 
0.1%
11 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 243
 
20.0%
1 883
72.6%
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
72.6%
0 243
 
20.0%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing4
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean0.92986799
Minimum0
Maximum10
Zeros172
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:16.475842image/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 deviation0.58824065
Coefficient of variation (CV)0.63260663
Kurtosis57.467205
Mean0.92986799
Median Absolute Deviation (MAD)0
Skewness4.6470289
Sum1127
Variance0.34602707
MonotonicityNot monotonic
2024-04-21T19:35:16.827167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 990
81.4%
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) 4
 
0.3%
ValueCountFrequency (%)
0 172
 
14.1%
1 990
81.4%
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%
1 990
81.4%
0 172
 
14.1%

정점굴절계기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.5%
Missing6
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean1.0214876
Minimum0
Maximum5
Zeros170
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:17.155169image/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 deviation0.62577748
Coefficient of variation (CV)0.61261388
Kurtosis4.972094
Mean1.0214876
Median Absolute Deviation (MAD)0
Skewness1.2829456
Sum1236
Variance0.39159745
MonotonicityNot monotonic
2024-04-21T19:35:17.494485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 889
73.1%
0 170
 
14.0%
2 114
 
9.4%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
(Missing) 6
 
0.5%
ValueCountFrequency (%)
0 170
 
14.0%
1 889
73.1%
2 114
 
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%
2 114
 
9.4%
1 889
73.1%
0 170
 
14.0%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
901 
0
248 
<NA>
 
39
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.0962171
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 901
74.1%
0 248
 
20.4%
<NA> 39
 
3.2%
2 27
 
2.2%
3 1
 
0.1%

Length

2024-04-21T19:35:17.884338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:18.222775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 901
74.1%
0 248
 
20.4%
na 39
 
3.2%
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
247 
<NA>
 
39
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.0962171
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 910
74.8%
0 247
 
20.3%
<NA> 39
 
3.2%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:35:18.601768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:35:18.940719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 910
74.8%
0 247
 
20.3%
na 39
 
3.2%
2 19
 
1.6%
3 1
 
0.1%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing39
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean0.90059473
Minimum0
Maximum5
Zeros247
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:19.250890image/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 deviation0.59287836
Coefficient of variation (CV)0.65831871
Kurtosis4.8924764
Mean0.90059473
Median Absolute Deviation (MAD)0
Skewness0.83964793
Sum1060
Variance0.35150475
MonotonicityNot monotonic
2024-04-21T19:35:19.589813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 817
67.2%
0 247
 
20.3%
2 101
 
8.3%
3 9
 
0.7%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 39
 
3.2%
ValueCountFrequency (%)
0 247
 
20.3%
1 817
67.2%
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
67.2%
0 247
 
20.3%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing38
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.93293718
Minimum0
Maximum5
Zeros246
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:19.910526image/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 deviation0.63171762
Coefficient of variation (CV)0.67712771
Kurtosis3.0951256
Mean0.93293718
Median Absolute Deviation (MAD)0
Skewness0.80297653
Sum1099
Variance0.39906715
MonotonicityNot monotonic
2024-04-21T19:35:20.250321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 791
65.0%
0 246
 
20.2%
2 119
 
9.8%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 246
 
20.2%
1 791
65.0%
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
65.0%
0 246
 
20.2%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct533
Distinct (%)71.2%
Missing467
Missing (%)38.4%
Infinite0
Infinite (%)0.0%
Mean73.81984
Minimum0
Maximum723.02
Zeros105
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:35:20.827265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130
median57.67
Q397.38
95-th percentile210
Maximum723.02
Range723.02
Interquartile range (IQR)67.38

Descriptive statistics

Standard deviation71.855083
Coefficient of variation (CV)0.97338443
Kurtosis17.341864
Mean73.81984
Median Absolute Deviation (MAD)31.97
Skewness2.9012539
Sum55291.06
Variance5163.1529
MonotonicityNot monotonic
2024-04-21T19:35:21.098543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 105
 
8.6%
33.0 10
 
0.8%
66.0 6
 
0.5%
49.5 5
 
0.4%
60.0 5
 
0.4%
46.2 4
 
0.3%
56.0 4
 
0.3%
105.0 4
 
0.3%
99.0 4
 
0.3%
57.6 4
 
0.3%
Other values (523) 598
49.2%
(Missing) 467
38.4%
ValueCountFrequency (%)
0.0 105
8.6%
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 

Missing1216
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
12061207안경업01_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>
12071208안경업01_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>
12081209안경업01_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>
12091210안경업01_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>
12101211안경업01_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>
12111212안경업01_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>
12121213안경업01_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>
12131214안경업01_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>
12141215안경업01_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>
12151216안경업01_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>