Overview

Dataset statistics

Number of variables39
Number of observations1154
Missing cells10731
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory383.3 KiB
Average record size in memory340.1 B

Variable types

Numeric14
Categorical12
Text5
Unsupported7
DateTime1

Dataset

Description2021-07-01
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 (64.3%)Imbalance
표본렌즈수 is highly imbalanced (59.8%)Imbalance
정점굴절계기수 is highly imbalanced (51.4%)Imbalance
조제용연마기수 is highly imbalanced (56.0%)Imbalance
렌즈절단기수 is highly imbalanced (57.8%)Imbalance
인허가취소일자 has 1154 (100.0%) missing valuesMissing
폐업일자 has 762 (66.0%) missing valuesMissing
휴업시작일자 has 1154 (100.0%) missing valuesMissing
휴업종료일자 has 1154 (100.0%) missing valuesMissing
재개업일자 has 1154 (100.0%) missing valuesMissing
소재지전화 has 171 (14.8%) missing valuesMissing
소재지면적 has 1154 (100.0%) missing valuesMissing
소재지우편번호 has 469 (40.6%) missing valuesMissing
소재지전체주소 has 96 (8.3%) missing valuesMissing
도로명전체주소 has 82 (7.1%) missing valuesMissing
도로명우편번호 has 256 (22.2%) missing valuesMissing
업태구분명 has 1154 (100.0%) missing valuesMissing
좌표정보(x) has 76 (6.6%) missing valuesMissing
좌표정보(y) has 76 (6.6%) missing valuesMissing
측정의자수 has 46 (4.0%) missing valuesMissing
가열기수 has 50 (4.3%) missing valuesMissing
안경세척기수 has 49 (4.2%) missing valuesMissing
총면적 has 515 (44.6%) missing valuesMissing
Unnamed: 38 has 1154 (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 172 (14.9%) zerosZeros
동공거리측정기수 has 174 (15.1%) zerosZeros
가열기수 has 173 (15.0%) zerosZeros
안경세척기수 has 172 (14.9%) zerosZeros
총면적 has 66 (5.7%) zerosZeros

Reproduction

Analysis started2024-04-21 10:37:11.124064
Analysis finished2024-04-21 10:37:12.603027
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1154
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean577.5
Minimum1
Maximum1154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:12.730895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile58.65
Q1289.25
median577.5
Q3865.75
95-th percentile1096.35
Maximum1154
Range1153
Interquartile range (IQR)576.5

Descriptive statistics

Standard deviation333.27541
Coefficient of variation (CV)0.57710028
Kurtosis-1.2
Mean577.5
Median Absolute Deviation (MAD)288.5
Skewness0
Sum666435
Variance111072.5
MonotonicityStrictly increasing
2024-04-21T19:37:12.985327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
867 1
 
0.1%
775 1
 
0.1%
774 1
 
0.1%
773 1
 
0.1%
772 1
 
0.1%
771 1
 
0.1%
770 1
 
0.1%
769 1
 
0.1%
768 1
 
0.1%
Other values (1144) 1144
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 (%)
1154 1
0.1%
1153 1
0.1%
1152 1
0.1%
1151 1
0.1%
1150 1
0.1%
1149 1
0.1%
1148 1
0.1%
1147 1
0.1%
1146 1
0.1%
1145 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
안경업
1154 

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 1154
100.0%

Length

2024-04-21T19:37:13.218637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:13.377849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1154
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
01_02_01_P
1154 

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 1154
100.0%

Length

2024-04-21T19:37:13.542353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:13.700443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1154
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325156
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:13.859537image/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 deviation39667.109
Coefficient of variation (CV)0.011929398
Kurtosis-0.73123507
Mean3325156
Median Absolute Deviation (MAD)30000
Skewness-0.06023711
Sum3.83723 × 109
Variance1.5734796 × 109
MonotonicityNot monotonic
2024-04-21T19:37:14.069475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 176
15.3%
3290000 142
12.3%
3310000 115
10.0%
3330000 99
8.6%
3340000 90
7.8%
3300000 85
7.4%
3250000 77
6.7%
3390000 66
 
5.7%
3320000 64
 
5.5%
3370000 63
 
5.5%
Other values (6) 177
15.3%
ValueCountFrequency (%)
3250000 77
6.7%
3260000 22
 
1.9%
3270000 27
 
2.3%
3280000 27
 
2.3%
3290000 142
12.3%
3300000 85
7.4%
3310000 115
10.0%
3320000 64
5.5%
3330000 99
8.6%
3340000 90
7.8%
ValueCountFrequency (%)
3400000 32
 
2.8%
3390000 66
 
5.7%
3380000 52
 
4.5%
3370000 63
 
5.5%
3360000 17
 
1.5%
3350000 176
15.3%
3340000 90
7.8%
3330000 99
8.6%
3320000 64
 
5.5%
3310000 115
10.0%

관리번호
Text

UNIQUE 

Distinct1154
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
2024-04-21T19:37:14.715384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters28850
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

Unique1154 ?
Unique (%)100.0%

Sample

1st rowPHMB219843250021082200001
2nd rowPHMB220123370022082200002
3rd rowPHMB219953290024082200001
4th rowPHMB220153290024082200006
5th rowPHMB220103390023082200001
ValueCountFrequency (%)
phmb219843250021082200001 1
 
0.1%
phmb220033350024082200003 1
 
0.1%
phmb219823390023082200003 1
 
0.1%
phmb219983390023082200001 1
 
0.1%
phmb219963390023082200001 1
 
0.1%
phmb220173390023082200002 1
 
0.1%
phmb220173390023082200001 1
 
0.1%
phmb219853390023082200002 1
 
0.1%
phmb220143390023082200001 1
 
0.1%
phmb220163390023082200003 1
 
0.1%
Other values (1144) 1144
99.1%
2024-04-21T19:37:15.570000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9431
32.7%
2 6148
21.3%
3 2531
 
8.8%
1 1588
 
5.5%
8 1490
 
5.2%
P 1154
 
4.0%
H 1154
 
4.0%
M 1154
 
4.0%
B 1154
 
4.0%
4 1030
 
3.6%
Other values (4) 2016
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24234
84.0%
Uppercase Letter 4616
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9431
38.9%
2 6148
25.4%
3 2531
 
10.4%
1 1588
 
6.6%
8 1490
 
6.1%
4 1030
 
4.3%
9 972
 
4.0%
5 583
 
2.4%
7 250
 
1.0%
6 211
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 1154
25.0%
H 1154
25.0%
M 1154
25.0%
B 1154
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24234
84.0%
Latin 4616
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9431
38.9%
2 6148
25.4%
3 2531
 
10.4%
1 1588
 
6.6%
8 1490
 
6.1%
4 1030
 
4.3%
9 972
 
4.0%
5 583
 
2.4%
7 250
 
1.0%
6 211
 
0.9%
Latin
ValueCountFrequency (%)
P 1154
25.0%
H 1154
25.0%
M 1154
25.0%
B 1154
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28850
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9431
32.7%
2 6148
21.3%
3 2531
 
8.8%
1 1588
 
5.5%
8 1490
 
5.2%
P 1154
 
4.0%
H 1154
 
4.0%
M 1154
 
4.0%
B 1154
 
4.0%
4 1030
 
3.6%
Other values (4) 2016
 
7.0%

인허가일자
Real number (ℝ)

Distinct1057
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20037632
Minimum19710518
Maximum20210528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:15.825378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19710518
5-th percentile19850575
Q119951229
median20051068
Q320130226
95-th percentile20190579
Maximum20210528
Range500010
Interquartile range (IQR)178996.75

Descriptive statistics

Standard deviation108570.79
Coefficient of variation (CV)0.0054183444
Kurtosis-0.75417487
Mean20037632
Median Absolute Deviation (MAD)84996
Skewness-0.41332153
Sum2.3123427 × 1010
Variance1.1787617 × 1010
MonotonicityNot monotonic
2024-04-21T19:37:16.087278image/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%
20150617 2
 
0.2%
20111024 2
 
0.2%
20101029 2
 
0.2%
20110304 2
 
0.2%
20161124 2
 
0.2%
19880525 2
 
0.2%
Other values (1047) 1119
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 (%)
20210528 1
0.1%
20210512 1
0.1%
20210504 1
0.1%
20210423 1
0.1%
20210409 1
0.1%
20210311 1
0.1%
20210310 1
0.1%
20210302 1
0.1%
20210219 1
0.1%
20210215 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
1
747 
3
399 
4
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
1 747
64.7%
3 399
34.6%
4 8
 
0.7%

Length

2024-04-21T19:37:16.326499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:16.493668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 747
64.7%
3 399
34.6%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
영업/정상
747 
폐업
399 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length4.02513
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row취소/말소/만료/정지/중지
3rd row취소/말소/만료/정지/중지
4th row취소/말소/만료/정지/중지
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
영업/정상 747
64.7%
폐업 399
34.6%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:37:16.683085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:16.860712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 747
64.7%
폐업 399
34.6%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
13
747 
3
399 
24
 
8

Length

Max length2
Median length2
Mean length1.6542461
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row24
2nd row24
3rd row24
4th row24
5th row24

Common Values

ValueCountFrequency (%)
13 747
64.7%
3 399
34.6%
24 8
 
0.7%

Length

2024-04-21T19:37:17.255915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:17.438109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 747
64.7%
3 399
34.6%
24 8
 
0.7%
Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
영업중
747 
폐업
399 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6611785
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 747
64.7%
폐업 399
34.6%
직권폐업 8
 
0.7%

Length

2024-04-21T19:37:17.643507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:17.836705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 747
64.7%
폐업 399
34.6%
직권폐업 8
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct362
Distinct (%)92.3%
Missing762
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean20100665
Minimum19851128
Maximum20210531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:18.040539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19851128
5-th percentile19920936
Q120080108
median20111220
Q320170533
95-th percentile20201230
Maximum20210531
Range359403
Interquartile range (IQR)90425.5

Descriptive statistics

Standard deviation86171.897
Coefficient of variation (CV)0.0042870172
Kurtosis-0.25291926
Mean20100665
Median Absolute Deviation (MAD)59053
Skewness-0.87000417
Sum7.8794607 × 109
Variance7.4255958 × 109
MonotonicityNot monotonic
2024-04-21T19:37:18.305409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110303 3
 
0.3%
20170222 2
 
0.2%
20100803 2
 
0.2%
20091028 2
 
0.2%
20110131 2
 
0.2%
20110211 2
 
0.2%
20110216 2
 
0.2%
20110418 2
 
0.2%
20181112 2
 
0.2%
20120508 2
 
0.2%
Other values (352) 371
32.1%
(Missing) 762
66.0%
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 (%)
20210531 1
0.1%
20210529 1
0.1%
20210528 1
0.1%
20210527 1
0.1%
20210520 1
0.1%
20210503 1
0.1%
20210426 1
0.1%
20210413 1
0.1%
20210329 1
0.1%
20210324 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

소재지전화
Text

MISSING 

Distinct932
Distinct (%)94.8%
Missing171
Missing (%)14.8%
Memory size9.1 KiB
2024-04-21T19:37:19.188351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.276704
Min length7

Characters and Unicode

Total characters11085
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

Unique889 ?
Unique (%)90.4%

Sample

1st row051-463-0479
2nd row051-868-7488
3rd row051-805-3306
4th row051-808-7088
5th row051-808-7088
ValueCountFrequency (%)
051-808-7088 4
 
0.4%
051-816-4500 3
 
0.3%
051-337-7111 3
 
0.3%
261-6700 3
 
0.3%
051-623-7778 3
 
0.3%
051-625-8471 3
 
0.3%
051-647-5766 3
 
0.3%
051-257-7090 2
 
0.2%
051-804-4009 2
 
0.2%
051-761-0603 2
 
0.2%
Other values (922) 955
97.2%
2024-04-21T19:37:20.290198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1727
15.6%
0 1684
15.2%
5 1536
13.9%
1 1530
13.8%
2 829
7.5%
8 694
6.3%
6 689
 
6.2%
7 681
 
6.1%
3 680
 
6.1%
4 615
 
5.5%
Other values (4) 420
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9315
84.0%
Dash Punctuation 1727
 
15.6%
Close Punctuation 39
 
0.4%
Math Symbol 3
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1684
18.1%
5 1536
16.5%
1 1530
16.4%
2 829
8.9%
8 694
7.5%
6 689
7.4%
7 681
7.3%
3 680
7.3%
4 615
 
6.6%
9 377
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1727
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 11085
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1727
15.6%
0 1684
15.2%
5 1536
13.9%
1 1530
13.8%
2 829
7.5%
8 694
6.3%
6 689
 
6.2%
7 681
 
6.1%
3 680
 
6.1%
4 615
 
5.5%
Other values (4) 420
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11085
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1727
15.6%
0 1684
15.2%
5 1536
13.9%
1 1530
13.8%
2 829
7.5%
8 694
6.3%
6 689
 
6.2%
7 681
 
6.1%
3 680
 
6.1%
4 615
 
5.5%
Other values (4) 420
 
3.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct342
Distinct (%)49.9%
Missing469
Missing (%)40.6%
Infinite0
Infinite (%)0.0%
Mean608176.72
Minimum48272
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:20.533419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48272
5-th percentile601812
Q1607831
median609839
Q3614042
95-th percentile617656.2
Maximum619963
Range571691
Interquartile range (IQR)6211

Descriptive statistics

Standard deviation37427.267
Coefficient of variation (CV)0.061540119
Kurtosis218.06645
Mean608176.72
Median Absolute Deviation (MAD)3968
Skewness-14.697943
Sum4.1660105 × 108
Variance1.4008003 × 109
MonotonicityNot monotonic
2024-04-21T19:37:20.927741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609839 33
 
2.9%
614845 8
 
0.7%
609834 8
 
0.7%
611089 7
 
0.6%
608805 7
 
0.6%
614030 7
 
0.6%
609800 7
 
0.6%
616852 7
 
0.6%
609822 7
 
0.6%
619963 6
 
0.5%
Other values (332) 588
51.0%
(Missing) 469
40.6%
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 

Distinct1007
Distinct (%)95.2%
Missing96
Missing (%)8.3%
Memory size9.1 KiB
2024-04-21T19:37:22.232665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.198488
Min length3

Characters and Unicode

Total characters25602
Distinct characters302
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

Unique962 ?
Unique (%)90.9%

Sample

1st row부산광역시 중구 영주1동 26-1
2nd row부산광역시 연제구 거제1동 2번지 60호
3rd row부산광역시 부산진구 부전동 256번지 6호 14통
4th row부산광역시 부산진구 초읍동 271번지 1호
5th row부산광역시 사상구 괘법동 546번지 1호 (105호)
ValueCountFrequency (%)
부산광역시 1028
 
19.2%
금정구 170
 
3.2%
부산진구 137
 
2.6%
1호 123
 
2.3%
남구 106
 
2.0%
사하구 83
 
1.5%
동래구 80
 
1.5%
중구 73
 
1.4%
해운대구 69
 
1.3%
1층 67
 
1.2%
Other values (1360) 3429
63.9%
2024-04-21T19:37:23.969647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4322
 
16.9%
1 1376
 
5.4%
1326
 
5.2%
1266
 
4.9%
1181
 
4.6%
1068
 
4.2%
1065
 
4.2%
1058
 
4.1%
1031
 
4.0%
2 905
 
3.5%
Other values (292) 11004
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15221
59.5%
Decimal Number 5621
 
22.0%
Space Separator 4322
 
16.9%
Dash Punctuation 262
 
1.0%
Uppercase Letter 63
 
0.2%
Other Punctuation 47
 
0.2%
Open Punctuation 31
 
0.1%
Close Punctuation 31
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1326
 
8.7%
1266
 
8.3%
1181
 
7.8%
1068
 
7.0%
1065
 
7.0%
1058
 
7.0%
1031
 
6.8%
837
 
5.5%
800
 
5.3%
788
 
5.2%
Other values (258) 4801
31.5%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.5%
K 10
15.9%
B 7
11.1%
A 6
9.5%
E 5
7.9%
H 5
7.9%
C 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 1376
24.5%
2 905
16.1%
3 633
11.3%
4 536
 
9.5%
5 467
 
8.3%
0 395
 
7.0%
6 359
 
6.4%
7 336
 
6.0%
8 316
 
5.6%
9 298
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 39
83.0%
. 5
 
10.6%
@ 2
 
4.3%
/ 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
4322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 262
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15221
59.5%
Common 10316
40.3%
Latin 65
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1326
 
8.7%
1266
 
8.3%
1181
 
7.8%
1068
 
7.0%
1065
 
7.0%
1058
 
7.0%
1031
 
6.8%
837
 
5.5%
800
 
5.3%
788
 
5.2%
Other values (258) 4801
31.5%
Common
ValueCountFrequency (%)
4322
41.9%
1 1376
 
13.3%
2 905
 
8.8%
3 633
 
6.1%
4 536
 
5.2%
5 467
 
4.5%
0 395
 
3.8%
6 359
 
3.5%
7 336
 
3.3%
8 316
 
3.1%
Other values (9) 671
 
6.5%
Latin
ValueCountFrequency (%)
S 11
16.9%
K 10
15.4%
B 7
10.8%
A 6
9.2%
E 5
7.7%
H 5
7.7%
C 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 15221
59.5%
ASCII 10381
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4322
41.6%
1 1376
 
13.3%
2 905
 
8.7%
3 633
 
6.1%
4 536
 
5.2%
5 467
 
4.5%
0 395
 
3.8%
6 359
 
3.5%
7 336
 
3.2%
8 316
 
3.0%
Other values (24) 736
 
7.1%
Hangul
ValueCountFrequency (%)
1326
 
8.7%
1266
 
8.3%
1181
 
7.8%
1068
 
7.0%
1065
 
7.0%
1058
 
7.0%
1031
 
6.8%
837
 
5.5%
800
 
5.3%
788
 
5.2%
Other values (258) 4801
31.5%

도로명전체주소
Text

MISSING 

Distinct998
Distinct (%)93.1%
Missing82
Missing (%)7.1%
Memory size9.1 KiB
2024-04-21T19:37:25.279055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length27.939366
Min length20

Characters and Unicode

Total characters29951
Distinct characters343
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

Unique938 ?
Unique (%)87.5%

Sample

1st row부산광역시 연제구 거제천로 191 (거제동)
2nd row부산광역시 부산진구 서면로 56 (부전동)
3rd row부산광역시 부산진구 새싹로 237, 102호 (초읍동, 창곡종합시장)
4th row부산광역시 사상구 사상로 200 (괘법동)
5th row부산광역시 금정구 온천장로 136-1, 패밀리외과병원 1층 (장전동)
ValueCountFrequency (%)
부산광역시 1072
 
17.8%
1층 156
 
2.6%
금정구 154
 
2.6%
부산진구 136
 
2.3%
해운대구 98
 
1.6%
남구 92
 
1.5%
사하구 85
 
1.4%
동래구 84
 
1.4%
중구 73
 
1.2%
부전동 68
 
1.1%
Other values (1324) 3992
66.4%
2024-04-21T19:37:26.710841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4942
 
16.5%
1360
 
4.5%
1355
 
4.5%
1309
 
4.4%
1153
 
3.8%
1151
 
3.8%
1106
 
3.7%
1074
 
3.6%
) 1060
 
3.5%
( 1060
 
3.5%
Other values (333) 14381
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17912
59.8%
Space Separator 4942
 
16.5%
Decimal Number 4218
 
14.1%
Close Punctuation 1060
 
3.5%
Open Punctuation 1060
 
3.5%
Other Punctuation 513
 
1.7%
Dash Punctuation 163
 
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 (%)
1360
 
7.6%
1355
 
7.6%
1309
 
7.3%
1153
 
6.4%
1151
 
6.4%
1106
 
6.2%
1074
 
6.0%
1056
 
5.9%
573
 
3.2%
255
 
1.4%
Other values (298) 7520
42.0%
Uppercase Letter
ValueCountFrequency (%)
S 14
19.7%
K 12
16.9%
B 11
15.5%
A 5
 
7.0%
H 5
 
7.0%
C 5
 
7.0%
U 4
 
5.6%
Y 4
 
5.6%
G 4
 
5.6%
E 3
 
4.2%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 1051
24.9%
2 647
15.3%
3 397
 
9.4%
0 367
 
8.7%
4 359
 
8.5%
7 313
 
7.4%
5 313
 
7.4%
6 289
 
6.9%
9 243
 
5.8%
8 239
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
h 1
20.0%
k 1
20.0%
b 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 509
99.2%
. 4
 
0.8%
Space Separator
ValueCountFrequency (%)
4942
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1060
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1060
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17912
59.8%
Common 11963
39.9%
Latin 76
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1360
 
7.6%
1355
 
7.6%
1309
 
7.3%
1153
 
6.4%
1151
 
6.4%
1106
 
6.2%
1074
 
6.0%
1056
 
5.9%
573
 
3.2%
255
 
1.4%
Other values (298) 7520
42.0%
Latin
ValueCountFrequency (%)
S 14
18.4%
K 12
15.8%
B 11
14.5%
A 5
 
6.6%
H 5
 
6.6%
C 5
 
6.6%
U 4
 
5.3%
Y 4
 
5.3%
G 4
 
5.3%
E 3
 
3.9%
Other values (8) 9
11.8%
Common
ValueCountFrequency (%)
4942
41.3%
) 1060
 
8.9%
( 1060
 
8.9%
1 1051
 
8.8%
2 647
 
5.4%
, 509
 
4.3%
3 397
 
3.3%
0 367
 
3.1%
4 359
 
3.0%
7 313
 
2.6%
Other values (7) 1258
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17912
59.8%
ASCII 12039
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4942
41.0%
) 1060
 
8.8%
( 1060
 
8.8%
1 1051
 
8.7%
2 647
 
5.4%
, 509
 
4.2%
3 397
 
3.3%
0 367
 
3.0%
4 359
 
3.0%
7 313
 
2.6%
Other values (25) 1334
 
11.1%
Hangul
ValueCountFrequency (%)
1360
 
7.6%
1355
 
7.6%
1309
 
7.3%
1153
 
6.4%
1151
 
6.4%
1106
 
6.2%
1074
 
6.0%
1056
 
5.9%
573
 
3.2%
255
 
1.4%
Other values (298) 7520
42.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct532
Distinct (%)59.2%
Missing256
Missing (%)22.2%
Infinite0
Infinite (%)0.0%
Mean84270.371
Minimum46004
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:26.947892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46004
5-th percentile46260.85
Q147134.5
median47864.5
Q348945
95-th percentile608805
Maximum619963
Range573959
Interquartile range (IQR)1810.5

Descriptive statistics

Standard deviation138838.48
Coefficient of variation (CV)1.6475361
Kurtosis10.621388
Mean84270.371
Median Absolute Deviation (MAD)867
Skewness3.5490189
Sum75674793
Variance1.9276123 × 1010
MonotonicityNot monotonic
2024-04-21T19:37:27.181893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48946 20
 
1.7%
48953 12
 
1.0%
46291 11
 
1.0%
48945 10
 
0.9%
47296 8
 
0.7%
46576 8
 
0.7%
47295 8
 
0.7%
48095 7
 
0.6%
47254 7
 
0.6%
46726 7
 
0.6%
Other values (522) 800
69.3%
(Missing) 256
 
22.2%
ValueCountFrequency (%)
46004 1
 
0.1%
46008 2
0.2%
46010 1
 
0.1%
46015 4
0.3%
46017 1
 
0.1%
46029 1
 
0.1%
46048 2
0.2%
46055 1
 
0.1%
46056 1
 
0.1%
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%
Distinct904
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
2024-04-21T19:37:27.908273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.7105719
Min length2

Characters and Unicode

Total characters7744
Distinct characters411
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

Unique787 ?
Unique (%)68.2%

Sample

1st row부산당안경점
2nd row산타클로스안경
3rd row제일안경콘택트
4th row피카소안경원
5th row갤러리 안경
ValueCountFrequency (%)
안경원 64
 
4.5%
안경 43
 
3.0%
갤러리안경 30
 
2.1%
안경나라 21
 
1.5%
눈사랑안경 18
 
1.3%
갤러리안경원 13
 
0.9%
초이스안경 13
 
0.9%
오렌즈 12
 
0.8%
제일안경원 11
 
0.8%
세컨페이스 10
 
0.7%
Other values (910) 1195
83.6%
2024-04-21T19:37:28.887946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1049
 
13.5%
1047
 
13.5%
399
 
5.2%
276
 
3.6%
261
 
3.4%
257
 
3.3%
200
 
2.6%
177
 
2.3%
123
 
1.6%
0 88
 
1.1%
Other values (401) 3867
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7008
90.5%
Space Separator 276
 
3.6%
Decimal Number 177
 
2.3%
Uppercase Letter 85
 
1.1%
Lowercase Letter 58
 
0.7%
Close Punctuation 56
 
0.7%
Open Punctuation 56
 
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 (%)
1049
 
15.0%
1047
 
14.9%
399
 
5.7%
261
 
3.7%
257
 
3.7%
200
 
2.9%
177
 
2.5%
123
 
1.8%
84
 
1.2%
80
 
1.1%
Other values (344) 3331
47.5%
Uppercase Letter
ValueCountFrequency (%)
O 13
15.3%
E 8
 
9.4%
S 7
 
8.2%
L 6
 
7.1%
G 5
 
5.9%
K 5
 
5.9%
I 4
 
4.7%
M 4
 
4.7%
N 4
 
4.7%
C 4
 
4.7%
Other values (12) 25
29.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
12.1%
c 6
10.3%
o 6
10.3%
i 6
10.3%
a 6
10.3%
t 5
8.6%
n 5
8.6%
l 4
6.9%
p 3
 
5.2%
s 2
 
3.4%
Other values (7) 8
13.8%
Decimal Number
ValueCountFrequency (%)
0 88
49.7%
1 43
24.3%
8 22
 
12.4%
5 16
 
9.0%
2 4
 
2.3%
3 3
 
1.7%
6 1
 
0.6%
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 (%)
276
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7008
90.5%
Common 592
 
7.6%
Latin 143
 
1.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1049
 
15.0%
1047
 
14.9%
399
 
5.7%
261
 
3.7%
257
 
3.7%
200
 
2.9%
177
 
2.5%
123
 
1.8%
84
 
1.2%
80
 
1.1%
Other values (344) 3331
47.5%
Latin
ValueCountFrequency (%)
O 13
 
9.1%
E 8
 
5.6%
e 7
 
4.9%
S 7
 
4.9%
c 6
 
4.2%
o 6
 
4.2%
i 6
 
4.2%
L 6
 
4.2%
a 6
 
4.2%
G 5
 
3.5%
Other values (29) 73
51.0%
Common
ValueCountFrequency (%)
276
46.6%
0 88
 
14.9%
) 56
 
9.5%
( 56
 
9.5%
1 43
 
7.3%
8 22
 
3.7%
5 16
 
2.7%
. 13
 
2.2%
· 4
 
0.7%
2 4
 
0.7%
Other values (7) 14
 
2.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7007
90.5%
ASCII 730
 
9.4%
None 5
 
0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1049
 
15.0%
1047
 
14.9%
399
 
5.7%
261
 
3.7%
257
 
3.7%
200
 
2.9%
177
 
2.5%
123
 
1.8%
84
 
1.2%
80
 
1.1%
Other values (343) 3330
47.5%
ASCII
ValueCountFrequency (%)
276
37.8%
0 88
 
12.1%
) 56
 
7.7%
( 56
 
7.7%
1 43
 
5.9%
8 22
 
3.0%
5 16
 
2.2%
. 13
 
1.8%
O 13
 
1.8%
E 8
 
1.1%
Other values (44) 139
19.0%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct1128
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0146971 × 1013
Minimum2.008112 × 1013
Maximum2.0210531 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:29.134675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.008112 × 1013
5-th percentile2.0090209 × 1013
Q12.0120248 × 1013
median2.015012 × 1013
Q32.0180406 × 1013
95-th percentile2.0201211 × 1013
Maximum2.0210531 × 1013
Range1.29411 × 1011
Interquartile range (IQR)6.0157742 × 1010

Descriptive statistics

Standard deviation3.7390184 × 1010
Coefficient of variation (CV)0.0018558713
Kurtosis-1.102901
Mean2.0146971 × 1013
Median Absolute Deviation (MAD)2.9999008 × 1010
Skewness-0.027932858
Sum2.3249604 × 1016
Variance1.3980259 × 1021
MonotonicityNot monotonic
2024-04-21T19:37:29.407684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20081201183150 18
 
1.6%
20081215160833 6
 
0.5%
20081215160832 4
 
0.3%
20081201183151 2
 
0.2%
20111123154300 1
 
0.1%
20121220160844 1
 
0.1%
20200919164037 1
 
0.1%
20111124091836 1
 
0.1%
20181126120152 1
 
0.1%
20111123153919 1
 
0.1%
Other values (1118) 1118
96.9%
ValueCountFrequency (%)
20081120141639 1
 
0.1%
20081126140756 1
 
0.1%
20081126141153 1
 
0.1%
20081201183150 18
1.6%
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 (%)
20210531144811 1
0.1%
20210528150712 1
0.1%
20210528123513 1
0.1%
20210528103317 1
0.1%
20210527170349 1
0.1%
20210525101728 1
0.1%
20210524094207 1
0.1%
20210513093457 1
0.1%
20210511114253 1
0.1%
20210506125651 1
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
I
941 
U
213 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 941
81.5%
U 213
 
18.5%

Length

2024-04-21T19:37:29.647703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:29.812246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 941
81.5%
u 213
 
18.5%
Distinct230
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
Minimum2018-08-31 23:59:59
Maximum2021-06-02 02:40:00
2024-04-21T19:37:30.002937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:37:30.235623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct921
Distinct (%)85.4%
Missing76
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean388108.13
Minimum367108.19
Maximum403236.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:30.468725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379709.15
Q1384884.88
median388667.4
Q3391258.9
95-th percentile397330.57
Maximum403236.19
Range36128.006
Interquartile range (IQR)6374.0155

Descriptive statistics

Standard deviation5223.5917
Coefficient of variation (CV)0.013459114
Kurtosis0.46145707
Mean388108.13
Median Absolute Deviation (MAD)3206.6854
Skewness-0.044209921
Sum4.1838057 × 108
Variance27285910
MonotonicityNot monotonic
2024-04-21T19:37:30.726845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387618.822819234 8
 
0.7%
387271.299492377 6
 
0.5%
389816.233000769 5
 
0.4%
387920.292112964 5
 
0.4%
389097.800933845 5
 
0.4%
389314.662085919 5
 
0.4%
384874.515689472 4
 
0.3%
385590.814676765 4
 
0.3%
398237.363461482 4
 
0.3%
393952.264486105 4
 
0.3%
Other values (911) 1028
89.1%
(Missing) 76
 
6.6%
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%
401723.705169194 1
 
0.1%
401721.440535713 1
 
0.1%
401712.115666 1
 
0.1%
401709.206084507 1
 
0.1%
401687.081587248 1
 
0.1%
401678.104349687 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct921
Distinct (%)85.4%
Missing76
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean187339.83
Minimum174016.55
Maximum206377.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:30.978319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178578.16
Q1183620.89
median187084.15
Q3191825.83
95-th percentile196235.82
Maximum206377.97
Range32361.42
Interquartile range (IQR)8204.9344

Descriptive statistics

Standard deviation5835.4027
Coefficient of variation (CV)0.031148757
Kurtosis-0.17371093
Mean187339.83
Median Absolute Deviation (MAD)4361.4273
Skewness0.17111876
Sum2.0195233 × 108
Variance34051925
MonotonicityNot monotonic
2024-04-21T19:37:31.429697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186273.478853367 8
 
0.7%
186099.137533193 6
 
0.5%
193329.605871168 5
 
0.4%
186157.316240551 5
 
0.4%
192260.811648263 5
 
0.4%
194669.898821687 5
 
0.4%
179978.235223733 4
 
0.3%
179553.867031936 4
 
0.3%
187720.511056894 4
 
0.3%
187602.933160728 4
 
0.3%
Other values (911) 1028
89.1%
(Missing) 76
 
6.6%
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%
175057.154813024 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 size9.1 KiB
1
946 
0
172 
2
 
29
<NA>
 
5
3
 
2

Length

Max length4
Median length1
Mean length1.0129983
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 946
82.0%
0 172
 
14.9%
2 29
 
2.5%
<NA> 5
 
0.4%
3 2
 
0.2%

Length

2024-04-21T19:37:31.669859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:31.859959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 946
82.0%
0 172
 
14.9%
2 29
 
2.5%
na 5
 
0.4%
3 2
 
0.2%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
1
905 
0
172 
<NA>
 
37
2
 
33
3
 
6

Length

Max length4
Median length1
Mean length1.0979203
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 905
78.4%
0 172
 
14.9%
<NA> 37
 
3.2%
2 33
 
2.9%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:37:32.058608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:32.250574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 905
78.4%
0 172
 
14.9%
na 37
 
3.2%
2 33
 
2.9%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing46
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean0.91155235
Minimum0
Maximum11
Zeros172
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:32.423306image/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 deviation0.57447366
Coefficient of variation (CV)0.63021467
Kurtosis90.108692
Mean0.91155235
Median Absolute Deviation (MAD)0
Skewness5.4688931
Sum1010
Variance0.33001999
MonotonicityNot monotonic
2024-04-21T19:37:32.603574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 884
76.6%
0 172
 
14.9%
2 43
 
3.7%
3 4
 
0.3%
4 3
 
0.3%
11 1
 
0.1%
5 1
 
0.1%
(Missing) 46
 
4.0%
ValueCountFrequency (%)
0 172
 
14.9%
1 884
76.6%
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
76.6%
0 172
 
14.9%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing5
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.9208007
Minimum0
Maximum10
Zeros174
Zeros (%)15.1%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:32.785716image/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 deviation0.60037217
Coefficient of variation (CV)0.65201099
Kurtosis55.945866
Mean0.9208007
Median Absolute Deviation (MAD)0
Skewness4.6044338
Sum1058
Variance0.36044675
MonotonicityNot monotonic
2024-04-21T19:37:32.969589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 928
80.4%
0 174
 
15.1%
2 31
 
2.7%
3 7
 
0.6%
5 5
 
0.4%
4 3
 
0.3%
10 1
 
0.1%
(Missing) 5
 
0.4%
ValueCountFrequency (%)
0 174
 
15.1%
1 928
80.4%
2 31
 
2.7%
3 7
 
0.6%
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 7
 
0.6%
2 31
 
2.7%
1 928
80.4%
0 174
 
15.1%

정점굴절계기수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
1
842 
0
172 
2
101 
3
 
26
<NA>
 
7

Length

Max length4
Median length1
Mean length1.0181976
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 842
73.0%
0 172
 
14.9%
2 101
 
8.8%
3 26
 
2.3%
<NA> 7
 
0.6%
4 6
 
0.5%

Length

2024-04-21T19:37:33.181441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:33.377545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 842
73.0%
0 172
 
14.9%
2 101
 
8.8%
3 26
 
2.3%
na 7
 
0.6%
4 6
 
0.5%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
1
902 
0
174 
<NA>
 
50
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.1299827
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 902
78.2%
0 174
 
15.1%
<NA> 50
 
4.3%
2 27
 
2.3%
3 1
 
0.1%

Length

2024-04-21T19:37:33.587336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:33.772403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 902
78.2%
0 174
 
15.1%
na 50
 
4.3%
2 27
 
2.3%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.1 KiB
1
911 
0
175 
<NA>
 
48
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.1247834
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 911
78.9%
0 175
 
15.2%
<NA> 48
 
4.2%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:37:33.973774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:37:34.158454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 911
78.9%
0 175
 
15.2%
na 48
 
4.2%
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%
Mean0.96105072
Minimum0
Maximum5
Zeros173
Zeros (%)15.0%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:34.322663image/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 deviation0.56276514
Coefficient of variation (CV)0.58557278
Kurtosis6.4284331
Mean0.96105072
Median Absolute Deviation (MAD)0
Skewness0.99822263
Sum1061
Variance0.31670461
MonotonicityNot monotonic
2024-04-21T19:37:34.505664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 818
70.9%
0 173
 
15.0%
2 101
 
8.8%
3 9
 
0.8%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 50
 
4.3%
ValueCountFrequency (%)
0 173
 
15.0%
1 818
70.9%
2 101
 
8.8%
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
 
8.8%
1 818
70.9%
0 173
 
15.0%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing49
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean0.99547511
Minimum0
Maximum5
Zeros172
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:34.679948image/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 deviation0.60266421
Coefficient of variation (CV)0.60540359
Kurtosis4.0128586
Mean0.99547511
Median Absolute Deviation (MAD)0
Skewness0.92216938
Sum1100
Variance0.36320414
MonotonicityNot monotonic
2024-04-21T19:37:34.862952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 792
68.6%
0 172
 
14.9%
2 119
 
10.3%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 49
 
4.2%
ValueCountFrequency (%)
0 172
 
14.9%
1 792
68.6%
2 119
 
10.3%
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
 
10.3%
1 792
68.6%
0 172
 
14.9%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct477
Distinct (%)74.6%
Missing515
Missing (%)44.6%
Infinite0
Infinite (%)0.0%
Mean76.173521
Minimum0
Maximum723.02
Zeros66
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size10.3 KiB
2024-04-21T19:37:35.079221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133
median59
Q398.675
95-th percentile211.704
Maximum723.02
Range723.02
Interquartile range (IQR)65.675

Descriptive statistics

Standard deviation72.395683
Coefficient of variation (CV)0.95040483
Kurtosis19.151747
Mean76.173521
Median Absolute Deviation (MAD)31
Skewness3.0977799
Sum48674.88
Variance5241.1349
MonotonicityNot monotonic
2024-04-21T19:37:35.327026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 66
 
5.7%
33.0 8
 
0.7%
66.0 5
 
0.4%
57.6 4
 
0.3%
60.0 4
 
0.3%
56.0 4
 
0.3%
46.2 4
 
0.3%
49.5 4
 
0.3%
50.0 3
 
0.3%
114.0 3
 
0.3%
Other values (467) 534
46.3%
(Missing) 515
44.6%
ValueCountFrequency (%)
0.0 66
5.7%
1.0 1
 
0.1%
2.0 1
 
0.1%
5.56 1
 
0.1%
5.61 2
 
0.2%
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%
334.0 1
0.1%
329.12 1
0.1%
320.0 1
0.1%
304.5 1
0.1%
299.14 2
0.2%
295.0 1
0.1%
294.88 1
0.1%

Unnamed: 38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1154
Missing (%)100.0%
Memory size10.3 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
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12안경업01_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>
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56안경업01_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>
67안경업01_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>
78안경업01_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>
89안경업01_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>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
11441145안경업01_02_01_P3330000PHMB22009333002408220000820091012<NA>1영업/정상13영업중<NA><NA><NA><NA>701-3579<NA>612031부산광역시 해운대구 좌1동 395번지 3호 동우빌딩 1층부산광역시 해운대구 좌동로 104 (좌동,동우빌딩 1층)<NA>다비치안경20190215140531U2019-02-17 02:40:00.0<NA>398202.092657188114.588575111111111227.42<NA>
11451146안경업01_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>
11461147안경업01_02_01_P3330000PHMB22001333002408220000120011204<NA>1영업/정상13영업중<NA><NA><NA><NA>543-2025<NA>612800부산광역시 해운대구 반송2동 62번지 450호부산광역시 해운대구 윗반송로 77 (반송동)<NA>이노티안경20091111154029I2018-08-31 23:59:59.0<NA>396318.990499194529.864217111111111<NA><NA>
11471148안경업01_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>
11481149안경업01_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>
11491150안경업01_02_01_P3330000PHMB22007333002408220000120071203<NA>1영업/정상13영업중<NA><NA><NA><NA>784-4042<NA>612729부산광역시 해운대구 우동 1433번지부산광역시 해운대구 마린시티1로 167, 116호 (우동, 현대까멜리아상가)48092비추미안경20200622154557U2020-06-24 02:40:00.0<NA>395812.483825186378.36755311111111168.93<NA>
11501151안경업01_02_01_P3330000PHMB21997333002408220000119970903<NA>1영업/정상13영업중<NA><NA><NA><NA>731-3900<NA><NA><NA>부산광역시 해운대구 구남로29번길 16 (중동)48095아이비젼안경원20160226163853I2018-08-31 23:59:59.0<NA>396895.429733186886.749218111111111<NA><NA>
11511152안경업01_02_01_P3330000PHMB22020333002408220000320200424<NA>1영업/정상13영업중<NA><NA><NA><NA>051-731-1536<NA><NA>부산광역시 해운대구 우동 539번지 10호 해운대 라뮤에뜨부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 226호 (우동)48094으뜸50안경 해운대역점20200427153754I2020-04-29 00:23:20.0<NA>396596.443478186999.88452711111111166.5<NA>
11521153안경업01_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>
11531154안경업01_02_01_P3330000PHMB22020333002408220000420201207<NA>1영업/정상13영업중<NA><NA><NA><NA>051-900-5555<NA><NA>부산광역시 해운대구 우동 539-10 해운대 라뮤에뜨부산광역시 해운대구 해운대로 620, 해운대 라뮤에뜨 1층 121호 (우동)48094오렌즈 해운대비치점20201208165741I2020-12-10 00:23:07.0<NA>396596.443478186999.8845271<NA><NA>11<NA><NA><NA><NA>48.3<NA>