Overview

Dataset statistics

Number of variables39
Number of observations1171
Missing cells10890
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory388.9 KiB
Average record size in memory340.1 B

Variable types

Numeric14
Categorical12
Text5
Unsupported7
DateTime1

Dataset

Description2021-11-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123010

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
시력표수 is highly imbalanced (63.7%)Imbalance
표본렌즈수 is highly imbalanced (58.8%)Imbalance
정점굴절계기수 is highly imbalanced (51.0%)Imbalance
조제용연마기수 is highly imbalanced (55.0%)Imbalance
렌즈절단기수 is highly imbalanced (56.8%)Imbalance
인허가취소일자 has 1171 (100.0%) missing valuesMissing
폐업일자 has 768 (65.6%) missing valuesMissing
휴업시작일자 has 1171 (100.0%) missing valuesMissing
휴업종료일자 has 1171 (100.0%) missing valuesMissing
재개업일자 has 1171 (100.0%) missing valuesMissing
소재지전화 has 175 (14.9%) missing valuesMissing
소재지면적 has 1171 (100.0%) missing valuesMissing
소재지우편번호 has 491 (41.9%) missing valuesMissing
소재지전체주소 has 100 (8.5%) missing valuesMissing
도로명전체주소 has 82 (7.0%) missing valuesMissing
도로명우편번호 has 256 (21.9%) missing valuesMissing
업태구분명 has 1171 (100.0%) missing valuesMissing
좌표정보(x) has 80 (6.8%) missing valuesMissing
좌표정보(y) has 80 (6.8%) missing valuesMissing
측정의자수 has 46 (3.9%) missing valuesMissing
가열기수 has 50 (4.3%) missing valuesMissing
안경세척기수 has 49 (4.2%) missing valuesMissing
총면적 has 511 (43.6%) missing valuesMissing
Unnamed: 38 has 1171 (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 189 (16.1%) zerosZeros
동공거리측정기수 has 175 (14.9%) zerosZeros
가열기수 has 190 (16.2%) zerosZeros
안경세척기수 has 189 (16.1%) zerosZeros
총면적 has 70 (6.0%) zerosZeros

Reproduction

Analysis started2024-04-21 10:39:05.421212
Analysis finished2024-04-21 10:39:06.816832
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean586
Minimum1
Maximum1171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:07.002406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile59.5
Q1293.5
median586
Q3878.5
95-th percentile1112.5
Maximum1171
Range1170
Interquartile range (IQR)585

Descriptive statistics

Standard deviation338.18289
Coefficient of variation (CV)0.57710391
Kurtosis-1.2
Mean586
Median Absolute Deviation (MAD)293
Skewness0
Sum686206
Variance114367.67
MonotonicityStrictly increasing
2024-04-21T19:39:07.440517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
771 1
 
0.1%
787 1
 
0.1%
786 1
 
0.1%
785 1
 
0.1%
784 1
 
0.1%
783 1
 
0.1%
782 1
 
0.1%
781 1
 
0.1%
780 1
 
0.1%
Other values (1161) 1161
99.1%
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 (%)
1171 1
0.1%
1170 1
0.1%
1169 1
0.1%
1168 1
0.1%
1167 1
0.1%
1166 1
0.1%
1165 1
0.1%
1164 1
0.1%
1163 1
0.1%
1162 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
안경업
1171 

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 1171
100.0%

Length

2024-04-21T19:39:07.852948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:08.142117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1171
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
01_02_01_P
1171 

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 1171
100.0%

Length

2024-04-21T19:39:08.449320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:08.739249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1171
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325089.7
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:09.019621image/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 deviation39900.149
Coefficient of variation (CV)0.011999721
Kurtosis-0.74122522
Mean3325089.7
Median Absolute Deviation (MAD)30000
Skewness-0.050589667
Sum3.89368 × 109
Variance1.5920219 × 109
MonotonicityNot monotonic
2024-04-21T19:39:09.401654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 175
14.9%
3290000 146
12.5%
3310000 115
9.8%
3330000 99
8.5%
3340000 91
7.8%
3300000 88
7.5%
3250000 80
6.8%
3390000 67
 
5.7%
3320000 65
 
5.6%
3370000 65
 
5.6%
Other values (6) 180
15.4%
ValueCountFrequency (%)
3250000 80
6.8%
3260000 22
 
1.9%
3270000 27
 
2.3%
3280000 27
 
2.3%
3290000 146
12.5%
3300000 88
7.5%
3310000 115
9.8%
3320000 65
5.6%
3330000 99
8.5%
3340000 91
7.8%
ValueCountFrequency (%)
3400000 35
 
3.0%
3390000 67
 
5.7%
3380000 52
 
4.4%
3370000 65
 
5.6%
3360000 17
 
1.5%
3350000 175
14.9%
3340000 91
7.8%
3330000 99
8.5%
3320000 65
 
5.6%
3310000 115
9.8%

관리번호
Text

UNIQUE 

Distinct1171
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2024-04-21T19:39:10.135011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters29275
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

Unique1171 ?
Unique (%)100.0%

Sample

1st rowPHMB220203330024082200004
2nd rowPHMB220213330024082200001
3rd rowPHMB220203330024082200003
4th rowPHMB219973330024082200001
5th rowPHMB220073330024082200001
ValueCountFrequency (%)
phmb220203330024082200004 1
 
0.1%
phmb220113330024082200001 1
 
0.1%
phmb220103400013082200005 1
 
0.1%
phmb220083400013082200001 1
 
0.1%
phmb220093400013082200001 1
 
0.1%
phmb219993400013082200001 1
 
0.1%
phmb220133400013082200004 1
 
0.1%
phmb220143400013082200002 1
 
0.1%
phmb220103400013082200004 1
 
0.1%
phmb220063330024082200007 1
 
0.1%
Other values (1161) 1161
99.1%
2024-04-21T19:39:11.009727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9572
32.7%
2 6261
21.4%
3 2563
 
8.8%
1 1612
 
5.5%
8 1507
 
5.1%
P 1171
 
4.0%
H 1171
 
4.0%
M 1171
 
4.0%
B 1171
 
4.0%
4 1044
 
3.6%
Other values (4) 2032
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24591
84.0%
Uppercase Letter 4684
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9572
38.9%
2 6261
25.5%
3 2563
 
10.4%
1 1612
 
6.6%
8 1507
 
6.1%
4 1044
 
4.2%
9 977
 
4.0%
5 591
 
2.4%
7 252
 
1.0%
6 212
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 1171
25.0%
H 1171
25.0%
M 1171
25.0%
B 1171
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24591
84.0%
Latin 4684
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9572
38.9%
2 6261
25.5%
3 2563
 
10.4%
1 1612
 
6.6%
8 1507
 
6.1%
4 1044
 
4.2%
9 977
 
4.0%
5 591
 
2.4%
7 252
 
1.0%
6 212
 
0.9%
Latin
ValueCountFrequency (%)
P 1171
25.0%
H 1171
25.0%
M 1171
25.0%
B 1171
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9572
32.7%
2 6261
21.4%
3 2563
 
8.8%
1 1612
 
5.5%
8 1507
 
5.1%
P 1171
 
4.0%
H 1171
 
4.0%
M 1171
 
4.0%
B 1171
 
4.0%
4 1044
 
3.6%
Other values (4) 2032
 
6.9%

인허가일자
Real number (ℝ)

Distinct1073
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20040154
Minimum19710518
Maximum20210923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:11.326241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19710518
5-th percentile19850615
Q119960316
median20060119
Q320130530
95-th percentile20200170
Maximum20210923
Range500405
Interquartile range (IQR)170214.5

Descriptive statistics

Standard deviation109765.42
Coefficient of variation (CV)0.0054772742
Kurtosis-0.75631486
Mean20040154
Median Absolute Deviation (MAD)80708
Skewness-0.40553689
Sum2.346702 × 1010
Variance1.2048447 × 1010
MonotonicityNot monotonic
2024-04-21T19:39:11.610994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19910628 12
 
1.0%
19901119 5
 
0.4%
20150731 3
 
0.3%
20000908 3
 
0.3%
19871223 2
 
0.2%
20030901 2
 
0.2%
20051202 2
 
0.2%
20140424 2
 
0.2%
20161219 2
 
0.2%
20001128 2
 
0.2%
Other values (1063) 1136
97.0%
ValueCountFrequency (%)
19710518 1
0.1%
19750813 1
0.1%
19751230 1
0.1%
19770602 1
0.1%
19780306 1
0.1%
19780419 1
0.1%
19780711 1
0.1%
19780812 1
0.1%
19780825 1
0.1%
19781027 1
0.1%
ValueCountFrequency (%)
20210923 1
0.1%
20210915 1
0.1%
20210906 1
0.1%
20210903 1
0.1%
20210831 1
0.1%
20210824 1
0.1%
20210823 2
0.2%
20210813 1
0.1%
20210809 1
0.1%
20210803 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
754 
3
409 
4
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 754
64.4%
3 409
34.9%
4 8
 
0.7%

Length

2024-04-21T19:39:11.843113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:12.009829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 754
64.4%
3 409
34.9%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
영업/정상
754 
폐업
409 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length4.0136635
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 754
64.4%
폐업 409
34.9%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:39:12.205909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:12.383004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 754
64.4%
폐업 409
34.9%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
13
754 
3
409 
24
 
8

Length

Max length2
Median length2
Mean length1.6507259
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 754
64.4%
3 409
34.9%
24 8
 
0.7%

Length

2024-04-21T19:39:12.562220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:12.731503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 754
64.4%
3 409
34.9%
24 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
영업중
754 
폐업
409 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6575576
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 754
64.4%
폐업 409
34.9%
직권폐업 8
 
0.7%

Length

2024-04-21T19:39:12.935686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:13.127187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 754
64.4%
폐업 409
34.9%
직권폐업 8
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct371
Distinct (%)92.1%
Missing768
Missing (%)65.6%
Infinite0
Infinite (%)0.0%
Mean20103669
Minimum19851128
Maximum20210825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:13.328758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19851128
5-th percentile19922015
Q120080959
median20120404
Q320171070
95-th percentile20210324
Maximum20210825
Range359697
Interquartile range (IQR)90111

Descriptive statistics

Standard deviation86860.14
Coefficient of variation (CV)0.0043206114
Kurtosis-0.22714852
Mean20103669
Median Absolute Deviation (MAD)50426
Skewness-0.87451184
Sum8.1017784 × 109
Variance7.5446839 × 109
MonotonicityNot monotonic
2024-04-21T19:39:13.592327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110303 3
 
0.3%
20111130 2
 
0.2%
19980512 2
 
0.2%
20140602 2
 
0.2%
19990205 2
 
0.2%
19990421 2
 
0.2%
20110418 2
 
0.2%
20210623 2
 
0.2%
20110131 2
 
0.2%
20150708 2
 
0.2%
Other values (361) 382
32.6%
(Missing) 768
65.6%
ValueCountFrequency (%)
19851128 1
0.1%
19900226 1
0.1%
19900507 1
0.1%
19900514 1
0.1%
19900927 1
0.1%
19901128 1
0.1%
19910122 1
0.1%
19910314 1
0.1%
19910406 2
0.2%
19910531 2
0.2%
ValueCountFrequency (%)
20210825 1
0.1%
20210820 1
0.1%
20210729 1
0.1%
20210726 1
0.1%
20210712 2
0.2%
20210701 1
0.1%
20210630 1
0.1%
20210625 1
0.1%
20210623 2
0.2%
20210531 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

소재지전화
Text

MISSING 

Distinct942
Distinct (%)94.6%
Missing175
Missing (%)14.9%
Memory size9.3 KiB
2024-04-21T19:39:14.332739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.295181
Min length7

Characters and Unicode

Total characters11250
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

Unique896 ?
Unique (%)90.0%

Sample

1st row051-900-5555
2nd row051-731-1536
3rd row731-3900
4th row784-4042
5th row528-0770
ValueCountFrequency (%)
051-808-7088 4
 
0.4%
051-623-7778 3
 
0.3%
051-337-7111 3
 
0.3%
051-625-8471 3
 
0.3%
051-816-4500 3
 
0.3%
261-6700 3
 
0.3%
051-647-5766 3
 
0.3%
524-4100 2
 
0.2%
051-625-8086 2
 
0.2%
051-759-9881 2
 
0.2%
Other values (932) 968
97.2%
2024-04-21T19:39:15.298115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1755
15.6%
0 1709
15.2%
5 1570
14.0%
1 1557
13.8%
2 846
7.5%
8 701
 
6.2%
6 691
 
6.1%
3 688
 
6.1%
7 687
 
6.1%
4 620
 
5.5%
Other values (4) 426
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9452
84.0%
Dash Punctuation 1755
 
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 1709
18.1%
5 1570
16.6%
1 1557
16.5%
2 846
9.0%
8 701
7.4%
6 691
7.3%
3 688
7.3%
7 687
7.3%
4 620
 
6.6%
9 383
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1755
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 11250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1755
15.6%
0 1709
15.2%
5 1570
14.0%
1 1557
13.8%
2 846
7.5%
8 701
 
6.2%
6 691
 
6.1%
3 688
 
6.1%
7 687
 
6.1%
4 620
 
5.5%
Other values (4) 426
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1755
15.6%
0 1709
15.2%
5 1570
14.0%
1 1557
13.8%
2 846
7.5%
8 701
 
6.2%
6 691
 
6.1%
3 688
 
6.1%
7 687
 
6.1%
4 620
 
5.5%
Other values (4) 426
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct340
Distinct (%)50.0%
Missing491
Missing (%)41.9%
Infinite0
Infinite (%)0.0%
Mean608176.49
Minimum48272
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:15.539290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48272
5-th percentile601812
Q1607832.5
median609839.5
Q3614049.75
95-th percentile617800.3
Maximum619963
Range571691
Interquartile range (IQR)6217.25

Descriptive statistics

Standard deviation37562.778
Coefficient of variation (CV)0.061762956
Kurtosis216.51176
Mean608176.49
Median Absolute Deviation (MAD)3967.5
Skewness-14.646806
Sum4.1356001 × 108
Variance1.4109623 × 109
MonotonicityNot monotonic
2024-04-21T19:39:15.965720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609839 33
 
2.8%
609834 8
 
0.7%
614845 8
 
0.7%
609822 7
 
0.6%
609800 7
 
0.6%
608805 7
 
0.6%
616852 7
 
0.6%
611089 7
 
0.6%
614030 7
 
0.6%
612022 6
 
0.5%
Other values (330) 583
49.8%
(Missing) 491
41.9%
ValueCountFrequency (%)
48272 1
 
0.1%
48296 1
 
0.1%
49247 1
 
0.1%
600016 1
 
0.1%
600017 1
 
0.1%
600031 2
0.2%
600032 3
0.3%
600042 1
 
0.1%
600045 1
 
0.1%
600052 1
 
0.1%
ValueCountFrequency (%)
619963 6
0.5%
619961 1
 
0.1%
619912 2
 
0.2%
619905 5
0.4%
619903 4
0.3%
618814 2
 
0.2%
618807 1
 
0.1%
617846 2
 
0.2%
617833 1
 
0.1%
617830 1
 
0.1%

소재지전체주소
Text

MISSING 

Distinct1019
Distinct (%)95.1%
Missing100
Missing (%)8.5%
Memory size9.3 KiB
2024-04-21T19:39:17.216511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.182073
Min length3

Characters and Unicode

Total characters25899
Distinct characters308
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

Unique973 ?
Unique (%)90.8%

Sample

1st row부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨
2nd row부산광역시 해운대구 반여동 1629-3 경희빌딩
3rd row부산광역시 해운대구 우동 539번지 10호 해운대 라뮤에뜨
4th row부산광역시 해운대구 중동 1378-18
5th row부산광역시 해운대구 반여동 1629번지 3호
ValueCountFrequency (%)
부산광역시 1042
 
19.2%
금정구 169
 
3.1%
부산진구 141
 
2.6%
1호 123
 
2.3%
남구 106
 
2.0%
사하구 84
 
1.5%
동래구 79
 
1.5%
중구 76
 
1.4%
해운대구 69
 
1.3%
1층 68
 
1.3%
Other values (1379) 3469
63.9%
2024-04-21T19:39:18.735522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4370
 
16.9%
1 1391
 
5.4%
1346
 
5.2%
1285
 
5.0%
1190
 
4.6%
1086
 
4.2%
1075
 
4.2%
1073
 
4.1%
1046
 
4.0%
2 911
 
3.5%
Other values (298) 11126
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15416
59.5%
Decimal Number 5664
 
21.9%
Space Separator 4370
 
16.9%
Dash Punctuation 276
 
1.1%
Uppercase Letter 63
 
0.2%
Other Punctuation 44
 
0.2%
Close Punctuation 31
 
0.1%
Open Punctuation 31
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1346
 
8.7%
1285
 
8.3%
1190
 
7.7%
1086
 
7.0%
1075
 
7.0%
1073
 
7.0%
1046
 
6.8%
834
 
5.4%
796
 
5.2%
783
 
5.1%
Other values (264) 4902
31.8%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.5%
K 10
15.9%
B 7
11.1%
A 6
9.5%
C 5
7.9%
E 5
7.9%
H 5
7.9%
U 4
 
6.3%
Y 4
 
6.3%
L 2
 
3.2%
Other values (3) 4
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 1391
24.6%
2 911
16.1%
3 637
11.2%
4 542
 
9.6%
5 467
 
8.2%
0 395
 
7.0%
6 358
 
6.3%
7 343
 
6.1%
8 320
 
5.6%
9 300
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 36
81.8%
. 5
 
11.4%
@ 2
 
4.5%
/ 1
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
4370
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15416
59.5%
Common 10418
40.2%
Latin 65
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1346
 
8.7%
1285
 
8.3%
1190
 
7.7%
1086
 
7.0%
1075
 
7.0%
1073
 
7.0%
1046
 
6.8%
834
 
5.4%
796
 
5.2%
783
 
5.1%
Other values (264) 4902
31.8%
Common
ValueCountFrequency (%)
4370
41.9%
1 1391
 
13.4%
2 911
 
8.7%
3 637
 
6.1%
4 542
 
5.2%
5 467
 
4.5%
0 395
 
3.8%
6 358
 
3.4%
7 343
 
3.3%
8 320
 
3.1%
Other values (9) 684
 
6.6%
Latin
ValueCountFrequency (%)
S 11
16.9%
K 10
15.4%
B 7
10.8%
A 6
9.2%
C 5
7.7%
E 5
7.7%
H 5
7.7%
U 4
 
6.2%
Y 4
 
6.2%
L 2
 
3.1%
Other values (5) 6
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15416
59.5%
ASCII 10483
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4370
41.7%
1 1391
 
13.3%
2 911
 
8.7%
3 637
 
6.1%
4 542
 
5.2%
5 467
 
4.5%
0 395
 
3.8%
6 358
 
3.4%
7 343
 
3.3%
8 320
 
3.1%
Other values (24) 749
 
7.1%
Hangul
ValueCountFrequency (%)
1346
 
8.7%
1285
 
8.3%
1190
 
7.7%
1086
 
7.0%
1075
 
7.0%
1073
 
7.0%
1046
 
6.8%
834
 
5.4%
796
 
5.2%
783
 
5.1%
Other values (264) 4902
31.8%

도로명전체주소
Text

MISSING 

Distinct1014
Distinct (%)93.1%
Missing82
Missing (%)7.0%
Memory size9.3 KiB
2024-04-21T19:39:20.000419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length28.036731
Min length20

Characters and Unicode

Total characters30532
Distinct characters351
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

Unique953 ?
Unique (%)87.5%

Sample

1st row부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 1층 121호 (우동)
2nd row부산광역시 해운대구 반여로 100, 경희빌딩 101,102호 (반여동)
3rd row부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 226호 (우동)
4th row부산광역시 해운대구 구남로29번길 16 (중동)
5th row부산광역시 해운대구 중동2로 16, 1층 (중동)
ValueCountFrequency (%)
부산광역시 1090
 
17.8%
1층 169
 
2.8%
금정구 153
 
2.5%
부산진구 140
 
2.3%
해운대구 98
 
1.6%
남구 92
 
1.5%
사하구 87
 
1.4%
동래구 87
 
1.4%
중구 76
 
1.2%
부전동 70
 
1.1%
Other values (1345) 4064
66.3%
2024-04-21T19:39:21.500991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5041
 
16.5%
1385
 
4.5%
1377
 
4.5%
1333
 
4.4%
1174
 
3.8%
1172
 
3.8%
1123
 
3.7%
1093
 
3.6%
1 1090
 
3.6%
( 1075
 
3.5%
Other values (341) 14669
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18257
59.8%
Space Separator 5041
 
16.5%
Decimal Number 4303
 
14.1%
Open Punctuation 1075
 
3.5%
Close Punctuation 1075
 
3.5%
Other Punctuation 533
 
1.7%
Dash Punctuation 165
 
0.5%
Uppercase Letter 71
 
0.2%
Math Symbol 7
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1385
 
7.6%
1377
 
7.5%
1333
 
7.3%
1174
 
6.4%
1172
 
6.4%
1123
 
6.2%
1093
 
6.0%
1072
 
5.9%
577
 
3.2%
260
 
1.4%
Other values (306) 7691
42.1%
Uppercase Letter
ValueCountFrequency (%)
S 14
19.7%
K 12
16.9%
B 11
15.5%
H 5
 
7.0%
A 5
 
7.0%
C 5
 
7.0%
G 4
 
5.6%
Y 4
 
5.6%
U 4
 
5.6%
E 3
 
4.2%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 1090
25.3%
2 651
15.1%
3 405
 
9.4%
0 376
 
8.7%
4 364
 
8.5%
7 317
 
7.4%
5 314
 
7.3%
6 298
 
6.9%
9 249
 
5.8%
8 239
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
b 1
20.0%
h 1
20.0%
k 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 529
99.2%
. 4
 
0.8%
Space Separator
ValueCountFrequency (%)
5041
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1075
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1075
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18257
59.8%
Common 12199
40.0%
Latin 76
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1385
 
7.6%
1377
 
7.5%
1333
 
7.3%
1174
 
6.4%
1172
 
6.4%
1123
 
6.2%
1093
 
6.0%
1072
 
5.9%
577
 
3.2%
260
 
1.4%
Other values (306) 7691
42.1%
Latin
ValueCountFrequency (%)
S 14
18.4%
K 12
15.8%
B 11
14.5%
H 5
 
6.6%
A 5
 
6.6%
C 5
 
6.6%
G 4
 
5.3%
Y 4
 
5.3%
U 4
 
5.3%
E 3
 
3.9%
Other values (8) 9
11.8%
Common
ValueCountFrequency (%)
5041
41.3%
1 1090
 
8.9%
( 1075
 
8.8%
) 1075
 
8.8%
2 651
 
5.3%
, 529
 
4.3%
3 405
 
3.3%
0 376
 
3.1%
4 364
 
3.0%
7 317
 
2.6%
Other values (7) 1276
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18257
59.8%
ASCII 12275
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5041
41.1%
1 1090
 
8.9%
( 1075
 
8.8%
) 1075
 
8.8%
2 651
 
5.3%
, 529
 
4.3%
3 405
 
3.3%
0 376
 
3.1%
4 364
 
3.0%
7 317
 
2.6%
Other values (25) 1352
 
11.0%
Hangul
ValueCountFrequency (%)
1385
 
7.6%
1377
 
7.5%
1333
 
7.3%
1174
 
6.4%
1172
 
6.4%
1123
 
6.2%
1093
 
6.0%
1072
 
5.9%
577
 
3.2%
260
 
1.4%
Other values (306) 7691
42.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct536
Distinct (%)58.6%
Missing256
Missing (%)21.9%
Infinite0
Infinite (%)0.0%
Mean83588.787
Minimum46004
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:21.740628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46243
Q147132
median47860
Q348945
95-th percentile608805
Maximum619963
Range573959
Interquartile range (IQR)1813

Descriptive statistics

Standard deviation137630.59
Coefficient of variation (CV)1.6465198
Kurtosis10.913537
Mean83588.787
Median Absolute Deviation (MAD)864
Skewness3.589907
Sum76483740
Variance1.894218 × 1010
MonotonicityNot monotonic
2024-04-21T19:39:21.973348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48946 21
 
1.8%
48953 13
 
1.1%
46291 11
 
0.9%
48945 10
 
0.9%
47295 9
 
0.8%
47296 8
 
0.7%
46576 8
 
0.7%
46726 7
 
0.6%
47289 7
 
0.6%
47254 7
 
0.6%
Other values (526) 814
69.5%
(Missing) 256
 
21.9%
ValueCountFrequency (%)
46004 1
 
0.1%
46008 2
 
0.2%
46010 1
 
0.1%
46015 5
0.4%
46017 1
 
0.1%
46029 1
 
0.1%
46048 3
0.3%
46055 1
 
0.1%
46056 2
 
0.2%
46061 1
 
0.1%
ValueCountFrequency (%)
619963 1
0.1%
619961 1
0.1%
619912 1
0.1%
619905 1
0.1%
619903 2
0.2%
618803 1
0.1%
617823 1
0.1%
617818 1
0.1%
617816 1
0.1%
617800 1
0.1%
Distinct922
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
2024-04-21T19:39:22.762216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.7779675
Min length2

Characters and Unicode

Total characters7937
Distinct characters413
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

Unique805 ?
Unique (%)68.7%

Sample

1st row오렌즈 해운대비치점
2nd row눈이랑안경
3rd row으뜸50안경 해운대역점
4th row아이비젼안경원
5th row비추미안경 렌즈미
ValueCountFrequency (%)
안경원 65
 
4.4%
안경 45
 
3.1%
갤러리안경 30
 
2.0%
안경나라 22
 
1.5%
눈사랑안경 18
 
1.2%
갤러리안경원 13
 
0.9%
초이스안경 13
 
0.9%
오렌즈 12
 
0.8%
세컨페이스 11
 
0.7%
제일안경원 10
 
0.7%
Other values (921) 1228
83.7%
2024-04-21T19:39:23.782578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1064
 
13.4%
1062
 
13.4%
402
 
5.1%
296
 
3.7%
273
 
3.4%
262
 
3.3%
206
 
2.6%
186
 
2.3%
125
 
1.6%
0 91
 
1.1%
Other values (403) 3970
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7159
90.2%
Space Separator 296
 
3.7%
Decimal Number 183
 
2.3%
Uppercase Letter 85
 
1.1%
Lowercase Letter 70
 
0.9%
Close Punctuation 58
 
0.7%
Open Punctuation 58
 
0.7%
Other Punctuation 22
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1064
 
14.9%
1062
 
14.8%
402
 
5.6%
273
 
3.8%
262
 
3.7%
206
 
2.9%
186
 
2.6%
125
 
1.7%
86
 
1.2%
80
 
1.1%
Other values (345) 3413
47.7%
Uppercase Letter
ValueCountFrequency (%)
O 13
15.3%
E 8
 
9.4%
S 7
 
8.2%
L 6
 
7.1%
K 5
 
5.9%
G 5
 
5.9%
I 4
 
4.7%
N 4
 
4.7%
M 4
 
4.7%
C 4
 
4.7%
Other values (12) 25
29.4%
Lowercase Letter
ValueCountFrequency (%)
e 10
14.3%
n 7
10.0%
a 7
10.0%
c 7
10.0%
o 6
8.6%
i 6
8.6%
t 5
7.1%
l 5
7.1%
p 3
 
4.3%
h 3
 
4.3%
Other values (8) 11
15.7%
Decimal Number
ValueCountFrequency (%)
0 91
49.7%
1 43
23.5%
8 23
 
12.6%
5 17
 
9.3%
2 5
 
2.7%
3 3
 
1.6%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 13
59.1%
· 4
 
18.2%
& 3
 
13.6%
# 2
 
9.1%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7159
90.2%
Common 622
 
7.8%
Latin 155
 
2.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1064
 
14.9%
1062
 
14.8%
402
 
5.6%
273
 
3.8%
262
 
3.7%
206
 
2.9%
186
 
2.6%
125
 
1.7%
86
 
1.2%
80
 
1.1%
Other values (345) 3413
47.7%
Latin
ValueCountFrequency (%)
O 13
 
8.4%
e 10
 
6.5%
E 8
 
5.2%
S 7
 
4.5%
n 7
 
4.5%
a 7
 
4.5%
c 7
 
4.5%
L 6
 
3.9%
o 6
 
3.9%
i 6
 
3.9%
Other values (30) 78
50.3%
Common
ValueCountFrequency (%)
296
47.6%
0 91
 
14.6%
) 58
 
9.3%
( 58
 
9.3%
1 43
 
6.9%
8 23
 
3.7%
5 17
 
2.7%
. 13
 
2.1%
2 5
 
0.8%
· 4
 
0.6%
Other values (7) 14
 
2.3%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7158
90.2%
ASCII 772
 
9.7%
None 5
 
0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1064
 
14.9%
1062
 
14.8%
402
 
5.6%
273
 
3.8%
262
 
3.7%
206
 
2.9%
186
 
2.6%
125
 
1.7%
86
 
1.2%
80
 
1.1%
Other values (344) 3412
47.7%
ASCII
ValueCountFrequency (%)
296
38.3%
0 91
 
11.8%
) 58
 
7.5%
( 58
 
7.5%
1 43
 
5.6%
8 23
 
3.0%
5 17
 
2.2%
. 13
 
1.7%
O 13
 
1.7%
e 10
 
1.3%
Other values (45) 150
19.4%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1145
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0148874 × 1013
Minimum2.008112 × 1013
Maximum2.0210924 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:24.029937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.008112 × 1013
5-th percentile2.0090209 × 1013
Q12.0120362 × 1013
median2.0150409 × 1013
Q32.0180957 × 1013
95-th percentile2.0210429 × 1013
Maximum2.0210924 × 1013
Range1.2980399 × 1011
Interquartile range (IQR)6.0595013 × 1010

Descriptive statistics

Standard deviation3.8759717 × 1010
Coefficient of variation (CV)0.0019236667
Kurtosis-1.1349661
Mean2.0148874 × 1013
Median Absolute Deviation (MAD)3.0193978 × 1010
Skewness-0.020760813
Sum2.3594331 × 1016
Variance1.5023157 × 1021
MonotonicityNot monotonic
2024-04-21T19:39:24.300125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20081201183150 18
 
1.5%
20081215160833 6
 
0.5%
20081215160832 4
 
0.3%
20081201183151 2
 
0.2%
20210528123513 1
 
0.1%
20200219153739 1
 
0.1%
20210825125858 1
 
0.1%
20100427150645 1
 
0.1%
20111102180815 1
 
0.1%
20101223144341 1
 
0.1%
Other values (1135) 1135
96.9%
ValueCountFrequency (%)
20081120141639 1
 
0.1%
20081126140756 1
 
0.1%
20081126141153 1
 
0.1%
20081201183150 18
1.5%
20081201183151 2
 
0.2%
20081206110426 1
 
0.1%
20081215160831 1
 
0.1%
20081215160832 4
 
0.3%
20081215160833 6
 
0.5%
20081226155323 1
 
0.1%
ValueCountFrequency (%)
20210924130622 1
0.1%
20210923144150 1
0.1%
20210923135503 1
0.1%
20210916152242 1
0.1%
20210909133631 1
0.1%
20210907133620 1
0.1%
20210906142236 1
0.1%
20210903161107 1
0.1%
20210831115932 1
0.1%
20210826165720 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
I
938 
U
233 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 938
80.1%
U 233
 
19.9%

Length

2024-04-21T19:39:24.541563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:24.704378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 938
80.1%
u 233
 
19.9%
Distinct260
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-09-26 00:22:48
2024-04-21T19:39:24.901943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:39:25.141724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct936
Distinct (%)85.8%
Missing80
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean388104.07
Minimum367108.19
Maximum403236.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:25.377556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379714.97
Q1384886.65
median388597.98
Q3391256.59
95-th percentile397376.04
Maximum403236.19
Range36128.006
Interquartile range (IQR)6369.9431

Descriptive statistics

Standard deviation5230.8603
Coefficient of variation (CV)0.013477983
Kurtosis0.46521926
Mean388104.07
Median Absolute Deviation (MAD)3205.6293
Skewness-0.022045733
Sum4.2342154 × 108
Variance27361899
MonotonicityNot monotonic
2024-04-21T19:39:25.635037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387618.822819234 8
 
0.7%
387271.299492377 7
 
0.6%
389314.662085919 5
 
0.4%
389097.800933845 5
 
0.4%
389816.233000769 5
 
0.4%
387920.292112964 5
 
0.4%
384903.52410762 4
 
0.3%
385590.814676765 4
 
0.3%
384874.515689472 4
 
0.3%
393952.264486105 4
 
0.3%
Other values (926) 1040
88.8%
(Missing) 80
 
6.8%
ValueCountFrequency (%)
367108.187126995 1
0.1%
371179.51398421 1
0.1%
371180.37604943 1
0.1%
373495.79454295 1
0.1%
373508.720158398 1
0.1%
373510.894532737 1
0.1%
373561.0 1
0.1%
373576.028819056 1
0.1%
373735.179018815 1
0.1%
374846.363500608 1
0.1%
ValueCountFrequency (%)
403236.192851 1
 
0.1%
402168.434114938 3
0.3%
401739.342184973 1
 
0.1%
401727.549967414 1
 
0.1%
401724.508448107 1
 
0.1%
401723.705169194 1
 
0.1%
401721.440535713 1
 
0.1%
401712.115666 1
 
0.1%
401709.206084507 1
 
0.1%
401700.977668733 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct937
Distinct (%)85.9%
Missing80
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean187341.86
Minimum174016.55
Maximum206377.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:25.887654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178668.61
Q1183609.25
median187073.01
Q3191812.71
95-th percentile196235.82
Maximum206377.97
Range32361.42
Interquartile range (IQR)8203.4624

Descriptive statistics

Standard deviation5853.9681
Coefficient of variation (CV)0.031247518
Kurtosis-0.15218717
Mean187341.86
Median Absolute Deviation (MAD)4354.544
Skewness0.1879112
Sum2.0438997 × 108
Variance34268942
MonotonicityNot monotonic
2024-04-21T19:39:26.129436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186273.478853367 8
 
0.7%
186099.137533193 7
 
0.6%
194669.898821687 5
 
0.4%
192260.811648263 5
 
0.4%
193329.605871168 5
 
0.4%
186157.316240551 5
 
0.4%
179742.031632526 4
 
0.3%
179553.867031936 4
 
0.3%
179978.235223733 4
 
0.3%
187602.933160728 4
 
0.3%
Other values (927) 1040
88.8%
(Missing) 80
 
6.8%
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%
175057.154813024 1
 
0.1%
175314.286676535 1
 
0.1%
175382.738615908 3
0.3%
ValueCountFrequency (%)
206377.970967 1
0.1%
206209.450536273 1
0.1%
205965.90747 1
0.1%
205730.304383 1
0.1%
205464.225232 1
0.1%
205376.57603 1
0.1%
205312.201457 1
0.1%
205109.080405 1
0.1%
205056.269216 1
0.1%
205035.508686 1
0.1%

시력표수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
957 
0
173 
2
 
34
<NA>
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.0128096
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 957
81.7%
0 173
 
14.8%
2 34
 
2.9%
<NA> 5
 
0.4%
3 2
 
0.2%

Length

2024-04-21T19:39:26.525961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:26.868906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 957
81.7%
0 173
 
14.8%
2 34
 
2.9%
na 5
 
0.4%
3 2
 
0.2%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
905 
0
188 
<NA>
 
38
2
 
33
3
 
6

Length

Max length4
Median length1
Mean length1.0990606
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 905
77.3%
0 188
 
16.1%
<NA> 38
 
3.2%
2 33
 
2.8%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:39:27.245509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:27.582172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 905
77.3%
0 188
 
16.1%
na 38
 
3.2%
2 33
 
2.8%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing46
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.89777778
Minimum0
Maximum11
Zeros189
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:27.903539image/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 deviation0.58086667
Coefficient of variation (CV)0.64700496
Kurtosis85.308081
Mean0.89777778
Median Absolute Deviation (MAD)0
Skewness5.2228714
Sum1010
Variance0.33740609
MonotonicityNot monotonic
2024-04-21T19:39:28.237946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 884
75.5%
0 189
 
16.1%
2 43
 
3.7%
3 4
 
0.3%
4 3
 
0.3%
5 1
 
0.1%
11 1
 
0.1%
(Missing) 46
 
3.9%
ValueCountFrequency (%)
0 189
 
16.1%
1 884
75.5%
2 43
 
3.7%
3 4
 
0.3%
4 3
 
0.3%
5 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
5 1
 
0.1%
4 3
 
0.3%
3 4
 
0.3%
2 43
 
3.7%
1 884
75.5%
0 189
 
16.1%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing5
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.92281304
Minimum0
Maximum10
Zeros175
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:28.574930image/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 deviation0.59975186
Coefficient of variation (CV)0.64991698
Kurtosis55.389734
Mean0.92281304
Median Absolute Deviation (MAD)0
Skewness4.5738822
Sum1076
Variance0.35970229
MonotonicityNot monotonic
2024-04-21T19:39:28.919456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 943
80.5%
0 175
 
14.9%
2 31
 
2.6%
3 8
 
0.7%
5 5
 
0.4%
4 3
 
0.3%
10 1
 
0.1%
(Missing) 5
 
0.4%
ValueCountFrequency (%)
0 175
 
14.9%
1 943
80.5%
2 31
 
2.6%
3 8
 
0.7%
4 3
 
0.3%
5 5
 
0.4%
10 1
 
0.1%
ValueCountFrequency (%)
10 1
 
0.1%
5 5
 
0.4%
4 3
 
0.3%
3 8
 
0.7%
2 31
 
2.6%
1 943
80.5%
0 175
 
14.9%

정점굴절계기수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
853 
0
173 
2
103 
3
 
28
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0179334
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 853
72.8%
0 173
 
14.8%
2 103
 
8.8%
3 28
 
2.4%
<NA> 7
 
0.6%
4 7
 
0.6%

Length

2024-04-21T19:39:29.316850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:29.658953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 853
72.8%
0 173
 
14.8%
2 103
 
8.8%
3 28
 
2.4%
na 7
 
0.6%
4 7
 
0.6%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
902 
0
191 
<NA>
 
50
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.1280956
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 902
77.0%
0 191
 
16.3%
<NA> 50
 
4.3%
2 27
 
2.3%
3 1
 
0.1%

Length

2024-04-21T19:39:30.047531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:30.378729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 902
77.0%
0 191
 
16.3%
na 50
 
4.3%
2 27
 
2.3%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.3 KiB
1
911 
0
192 
<NA>
 
48
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.1229718
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 911
77.8%
0 192
 
16.4%
<NA> 48
 
4.1%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:39:30.753750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:39:31.087653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 911
77.8%
0 192
 
16.4%
na 48
 
4.1%
2 19
 
1.6%
3 1
 
0.1%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing50
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean0.94647636
Minimum0
Maximum5
Zeros190
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:31.407868image/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 deviation0.57070491
Coefficient of variation (CV)0.60297851
Kurtosis5.9939602
Mean0.94647636
Median Absolute Deviation (MAD)0
Skewness0.94673692
Sum1061
Variance0.32570409
MonotonicityNot monotonic
2024-04-21T19:39:31.607515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 818
69.9%
0 190
 
16.2%
2 101
 
8.6%
3 9
 
0.8%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 50
 
4.3%
ValueCountFrequency (%)
0 190
 
16.2%
1 818
69.9%
2 101
 
8.6%
3 9
 
0.8%
4 1
 
0.1%
5 2
 
0.2%
ValueCountFrequency (%)
5 2
 
0.2%
4 1
 
0.1%
3 9
 
0.8%
2 101
 
8.6%
1 818
69.9%
0 190
 
16.2%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing49
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean0.98039216
Minimum0
Maximum5
Zeros189
Zeros (%)16.1%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:32.001555image/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 deviation0.61032495
Coefficient of variation (CV)0.62253145
Kurtosis3.7570805
Mean0.98039216
Median Absolute Deviation (MAD)0
Skewness0.8827549
Sum1100
Variance0.37249655
MonotonicityNot monotonic
2024-04-21T19:39:32.179996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 792
67.6%
0 189
 
16.1%
2 119
 
10.2%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 49
 
4.2%
ValueCountFrequency (%)
0 189
 
16.1%
1 792
67.6%
2 119
 
10.2%
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
 
10.2%
1 792
67.6%
0 189
 
16.1%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct495
Distinct (%)75.0%
Missing511
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean76.984727
Minimum0
Maximum723.02
Zeros70
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-04-21T19:39:32.394063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133.0375
median59.9
Q399
95-th percentile213.05
Maximum723.02
Range723.02
Interquartile range (IQR)65.9625

Descriptive statistics

Standard deviation72.995286
Coefficient of variation (CV)0.9481788
Kurtosis17.9664
Mean76.984727
Median Absolute Deviation (MAD)31.815
Skewness3.0006749
Sum50809.92
Variance5328.3118
MonotonicityNot monotonic
2024-04-21T19:39:32.642017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 70
 
6.0%
33.0 8
 
0.7%
66.0 5
 
0.4%
46.2 4
 
0.3%
49.5 4
 
0.3%
60.0 4
 
0.3%
57.6 4
 
0.3%
56.0 4
 
0.3%
92.4 3
 
0.3%
114.0 3
 
0.3%
Other values (485) 551
47.1%
(Missing) 511
43.6%
ValueCountFrequency (%)
0.0 70
6.0%
1.0 1
 
0.1%
2.0 1
 
0.1%
5.56 1
 
0.1%
7.5 1
 
0.1%
8.5 1
 
0.1%
10.23 1
 
0.1%
11.5 1
 
0.1%
12.2 1
 
0.1%
12.25 1
 
0.1%
ValueCountFrequency (%)
723.02 1
0.1%
700.0 1
0.1%
361.38 1
0.1%
336.9 1
0.1%
334.0 1
0.1%
329.12 1
0.1%
320.0 1
0.1%
304.5 1
0.1%
304.12 1
0.1%
299.14 1
0.1%

Unnamed: 38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1171
Missing (%)100.0%
Memory size10.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
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12안경업01_02_01_P3330000PHMB22021333002408220000120210504<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 반여동 1629-3 경희빌딩부산광역시 해운대구 반여로 100, 경희빌딩 101,102호 (반여동)48036눈이랑안경20210506125651I2021-05-08 00:22:56.0<NA>393314.100293191087.7106271<NA><NA>11<NA><NA><NA><NA>88.92<NA>
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56안경업01_02_01_P3330000PHMB22006333002408220000220060328<NA>1영업/정상13영업중<NA><NA><NA><NA>528-0770<NA>612060부산광역시 해운대구 반여동 1629번지 3호부산광역시 해운대구 반여로 100, 101-102호 (반여동, 경희빌딩)48036눈이랑 안경콘택트20150506142332I2018-08-31 23:59:59.0<NA>393314.100293191087.71062711111111188.92<NA>
67안경업01_02_01_P3330000PHMB22009333002408220000620090828<NA>1영업/정상13영업중<NA><NA><NA><NA>782-6000<NA>612062부산광역시 해운대구 반여2동 1291번지 201호부산광역시 해운대구 재반로 240 (반여동)<NA>SECOND FACE(세컨페이스)20171221141315I2018-08-31 23:59:59.0<NA>394047.328919190900.937133111111111115.5<NA>
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89안경업01_02_01_P3330000PHMB22008333002408220000720080430<NA>1영업/정상13영업중<NA><NA><NA><NA>543-6277<NA>612082부산광역시 해운대구 반송2동 40번지 1160호부산광역시 해운대구 반송로924번길 20 (반송동)<NA>크로바안경원20110922154631I2018-08-31 23:59:59.0<NA>396209.813911194626.75411811111111189.1<NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
11611162안경업01_02_01_P3250000PHMB22010325002108220000120100312<NA>3폐업3폐업20120406<NA><NA><NA>070-4116-2770<NA>600042부산광역시 중구 남포동2가 24번지 8호부산광역시 중구 구덕로34번길 3-1 (남포동2가)<NA>아이샵(eye#)안경20121026092051I2018-08-31 23:59:59.0<NA>385208.616221179585.320651111111111134.98<NA>
11621163안경업01_02_01_P3250000PHMB22018325002108220000120180814<NA>3폐업3폐업20210726<NA><NA><NA>2531216<NA><NA>부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경20210726152758U2021-07-28 02:40:00.0<NA>384903.524108179742.03163311111111193.22<NA>
11631164안경업01_02_01_P3320000PHMB22017332004508220000120170303<NA>4취소/말소/만료/정지/중지24직권폐업20190213<NA><NA><NA><NA><NA><NA><NA>부산광역시 북구 덕천로276번길 5 (만덕동, 동원맨션)46611안경하우스20190213105621U2019-02-15 02:40:00.0<NA>385250.135062191889.10297111111111166.0<NA>
11641165안경업01_02_01_P3340000PHMB22016334002508220000120160112<NA>4취소/말소/만료/정지/중지24직권폐업20190910<NA><NA><NA>051-264-2134<NA><NA>부산광역시 사하구 다대동 36번지부산광역시 사하구 다대로429번길 9, 1층 (다대동)49518지니스안경원20190910151902U2019-09-12 02:40:00.0<NA>380590.120985175688.173024111111111106.24<NA>
11651166안경업01_02_01_P3350000PHMB22018335002408220000120150731<NA>4취소/말소/만료/정지/중지24직권폐업20191016<NA><NA><NA>051-808-7088<NA><NA>부산광역시 금정구 장전동 651번지 12호 패밀리외과병원부산광역시 금정구 온천장로 136-1, 패밀리외과병원 1층 (장전동)46301패밀리룩(LOOK)안경원20191016100255U2019-10-18 02:40:00.0<NA>389817.647326193473.41186822111111150.74<NA>
11661167안경업01_02_01_P3390000PHMB22010339002308220000120100224<NA>4취소/말소/만료/정지/중지24직권폐업20160701<NA><NA><NA><NA><NA>617060부산광역시 사상구 괘법동 546번지 1호 (105호)부산광역시 사상구 사상로 200 (괘법동)46968갤러리 안경20180404161948I2018-08-31 23:59:59.0<NA>380748.884274186669.236718111111111119.62<NA>
11671168안경업01_02_01_P3290000PHMB22015329002408220000620150731<NA>4취소/말소/만료/정지/중지24직권폐업20180105<NA><NA><NA>051-808-7088<NA>614080부산광역시 부산진구 초읍동 271번지 1호부산광역시 부산진구 새싹로 237, 102호 (초읍동, 창곡종합시장)47108피카소안경원20180104133737I2018-08-31 23:59:59.0<NA>386481.395166188372.0918811111111155.0<NA>
11681169안경업01_02_01_P3290000PHMB21995329002408220000119950516<NA>4취소/말소/만료/정지/중지24직권폐업20100322<NA><NA><NA>051-805-3306<NA>614032부산광역시 부산진구 부전동 256번지 6호 14통부산광역시 부산진구 서면로 56 (부전동)<NA>제일안경콘택트20131021110309I2018-08-31 23:59:59.0<NA>387468.480136185990.346087111111111<NA><NA>
11691170안경업01_02_01_P3370000PHMB22012337002208220000220121213<NA>4취소/말소/만료/정지/중지24직권폐업20190114<NA><NA><NA>051-868-7488<NA>611800부산광역시 연제구 거제1동 2번지 60호부산광역시 연제구 거제천로 191 (거제동)47522산타클로스안경20190111150127U2019-01-13 02:40:00.0<NA>389268.286625189861.16137711113112297.37<NA>
11701171안경업01_02_01_P3250000PHMB21984325002108220000119841006<NA>4취소/말소/만료/정지/중지24직권폐업20090513<NA><NA><NA>051-463-0479<NA><NA>부산광역시 중구 영주1동 26-1<NA><NA>부산당안경점20121231102827I2018-08-31 23:59:59.0<NA><NA><NA>111111111<NA><NA>