Overview

Dataset statistics

Number of variables39
Number of observations1209
Missing cells11219
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory395.6 KiB
Average record size in memory335.1 B

Variable types

Numeric10
Categorical11
Text7
DateTime4
Unsupported7

Dataset

Description2023-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123010

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
시력표수 is highly imbalanced (65.2%)Imbalance
표본렌즈수 is highly imbalanced (57.8%)Imbalance
조제용연마기수 is highly imbalanced (53.9%)Imbalance
렌즈절단기수 is highly imbalanced (55.5%)Imbalance
인허가취소일자 has 1209 (100.0%) missing valuesMissing
폐업일자 has 785 (64.9%) missing valuesMissing
휴업시작일자 has 1209 (100.0%) missing valuesMissing
휴업종료일자 has 1209 (100.0%) missing valuesMissing
재개업일자 has 1209 (100.0%) missing valuesMissing
소재지전화 has 188 (15.6%) missing valuesMissing
소재지면적 has 1209 (100.0%) missing valuesMissing
소재지우편번호 has 542 (44.8%) missing valuesMissing
소재지전체주소 has 106 (8.8%) missing valuesMissing
도로명전체주소 has 82 (6.8%) missing valuesMissing
도로명우편번호 has 256 (21.2%) missing valuesMissing
업태구분명 has 1209 (100.0%) missing valuesMissing
좌표정보(x) has 100 (8.3%) missing valuesMissing
좌표정보(y) has 100 (8.3%) missing valuesMissing
측정의자수 has 38 (3.1%) missing valuesMissing
가열기수 has 39 (3.2%) missing valuesMissing
안경세척기수 has 38 (3.1%) missing valuesMissing
총면적 has 472 (39.0%) missing valuesMissing
Unnamed: 38 has 1209 (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 236 (19.5%) zerosZeros
동공거리측정기수 has 172 (14.2%) zerosZeros
정점굴절계기수 has 170 (14.1%) zerosZeros
가열기수 has 240 (19.9%) zerosZeros
안경세척기수 has 239 (19.8%) zerosZeros
총면적 has 99 (8.2%) zerosZeros

Reproduction

Analysis started2024-04-21 10:32:01.474867
Analysis finished2024-04-21 10:32:03.054433
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1209
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean605
Minimum1
Maximum1209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:03.248214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile61.4
Q1303
median605
Q3907
95-th percentile1148.6
Maximum1209
Range1208
Interquartile range (IQR)604

Descriptive statistics

Standard deviation349.15255
Coefficient of variation (CV)0.57711165
Kurtosis-1.2
Mean605
Median Absolute Deviation (MAD)302
Skewness0
Sum731445
Variance121907.5
MonotonicityStrictly increasing
2024-04-21T19:32:03.694865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
813 1
 
0.1%
811 1
 
0.1%
810 1
 
0.1%
809 1
 
0.1%
808 1
 
0.1%
807 1
 
0.1%
806 1
 
0.1%
805 1
 
0.1%
804 1
 
0.1%
Other values (1199) 1199
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1209 1
0.1%
1208 1
0.1%
1207 1
0.1%
1206 1
0.1%
1205 1
0.1%
1204 1
0.1%
1203 1
0.1%
1202 1
0.1%
1201 1
0.1%
1200 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
안경업
1209 

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 1209
100.0%

Length

2024-04-21T19:32:04.104317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:04.401928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안경업 1209
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
01_02_01_P
1209 

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 1209
100.0%

Length

2024-04-21T19:32:04.716130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:05.014471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01_02_01_p 1209
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3325103.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:05.300692image/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 deviation39933.845
Coefficient of variation (CV)0.012009806
Kurtosis-0.73863114
Mean3325103.4
Median Absolute Deviation (MAD)30000
Skewness-0.045511948
Sum4.02005 × 109
Variance1.594712 × 109
MonotonicityIncreasing
2024-04-21T19:32:05.682218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 177
14.6%
3290000 149
12.3%
3310000 116
9.6%
3330000 104
8.6%
3340000 94
7.8%
3300000 92
7.6%
3250000 82
6.8%
3320000 70
 
5.8%
3390000 68
 
5.6%
3370000 66
 
5.5%
Other values (6) 191
15.8%
ValueCountFrequency (%)
3250000 82
6.8%
3260000 23
 
1.9%
3270000 29
 
2.4%
3280000 28
 
2.3%
3290000 149
12.3%
3300000 92
7.6%
3310000 116
9.6%
3320000 70
5.8%
3330000 104
8.6%
3340000 94
7.8%
ValueCountFrequency (%)
3400000 38
 
3.1%
3390000 68
 
5.6%
3380000 54
 
4.5%
3370000 66
 
5.5%
3360000 19
 
1.6%
3350000 177
14.6%
3340000 94
7.8%
3330000 104
8.6%
3320000 70
 
5.8%
3310000 116
9.6%

관리번호
Text

UNIQUE 

Distinct1209
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:32:06.426369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters30225
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

Unique1209 ?
Unique (%)100.0%

Sample

1st rowPHMB220233250021082200001
2nd rowPHMB220183250021082200001
3rd rowPHMB220103250021082200001
4th rowPHMB219933250021082200001
5th rowPHMB220103250021082200006
ValueCountFrequency (%)
phmb220233250021082200001 1
 
0.1%
phmb219913350024082200005 1
 
0.1%
phmb219863350024082200004 1
 
0.1%
phmb219863350024082200003 1
 
0.1%
phmb219883350024082200002 1
 
0.1%
phmb219853350024082200002 1
 
0.1%
phmb220083350024082200001 1
 
0.1%
phmb220073350024082200002 1
 
0.1%
phmb220053350024082200006 1
 
0.1%
phmb220053350024082200005 1
 
0.1%
Other values (1199) 1199
99.2%
2024-04-21T19:32:07.539911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9883
32.7%
2 6541
21.6%
3 2650
 
8.8%
1 1642
 
5.4%
8 1546
 
5.1%
P 1209
 
4.0%
H 1209
 
4.0%
M 1209
 
4.0%
B 1209
 
4.0%
4 1074
 
3.6%
Other values (4) 2053
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25389
84.0%
Uppercase Letter 4836
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9883
38.9%
2 6541
25.8%
3 2650
 
10.4%
1 1642
 
6.5%
8 1546
 
6.1%
4 1074
 
4.2%
9 978
 
3.9%
5 602
 
2.4%
7 256
 
1.0%
6 217
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 1209
25.0%
H 1209
25.0%
M 1209
25.0%
B 1209
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25389
84.0%
Latin 4836
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9883
38.9%
2 6541
25.8%
3 2650
 
10.4%
1 1642
 
6.5%
8 1546
 
6.1%
4 1074
 
4.2%
9 978
 
3.9%
5 602
 
2.4%
7 256
 
1.0%
6 217
 
0.9%
Latin
ValueCountFrequency (%)
P 1209
25.0%
H 1209
25.0%
M 1209
25.0%
B 1209
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9883
32.7%
2 6541
21.6%
3 2650
 
8.8%
1 1642
 
5.4%
8 1546
 
5.1%
P 1209
 
4.0%
H 1209
 
4.0%
M 1209
 
4.0%
B 1209
 
4.0%
4 1074
 
3.6%
Other values (4) 2053
 
6.8%
Distinct1107
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum1971-05-18 00:00:00
Maximum2023-01-31 00:00:00
2024-04-21T19:32:07.939986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:32:08.578936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
765 
3
436 
4
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 765
63.3%
3 436
36.1%
4 8
 
0.7%

Length

2024-04-21T19:32:09.005406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:09.318733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 765
63.3%
3 436
36.1%
4 8
 
0.7%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업/정상
765 
폐업
436 
취소/말소/만료/정지/중지
 
8

Length

Max length14
Median length5
Mean length3.9776675
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 765
63.3%
폐업 436
36.1%
취소/말소/만료/정지/중지 8
 
0.7%

Length

2024-04-21T19:32:09.684603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:09.961744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 765
63.3%
폐업 436
36.1%
취소/말소/만료/정지/중지 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
13
765 
3
436 
24
 
8

Length

Max length2
Median length2
Mean length1.6393714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
13 765
63.3%
3 436
36.1%
24 8
 
0.7%

Length

2024-04-21T19:32:10.149620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:10.459756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 765
63.3%
3 436
36.1%
24 8
 
0.7%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
영업중
765 
폐업
436 
직권폐업
 
8

Length

Max length4
Median length3
Mean length2.6459884
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 765
63.3%
폐업 436
36.1%
직권폐업 8
 
0.7%

Length

2024-04-21T19:32:10.836460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:11.175376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 765
63.3%
폐업 436
36.1%
직권폐업 8
 
0.7%

폐업일자
Date

MISSING 

Distinct395
Distinct (%)93.2%
Missing785
Missing (%)64.9%
Memory size9.6 KiB
Minimum1985-11-28 00:00:00
Maximum2023-01-31 00:00:00
2024-04-21T19:32:11.514808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:32:11.945952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

소재지전화
Text

MISSING 

Distinct963
Distinct (%)94.3%
Missing188
Missing (%)15.6%
Memory size9.6 KiB
2024-04-21T19:32:12.814723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.306562
Min length7

Characters and Unicode

Total characters11544
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

Unique913 ?
Unique (%)89.4%

Sample

1st row051-243-3991
2nd row2531216
3rd row070-4116-2770
4th row051-253-1216
5th row051-246-0006
ValueCountFrequency (%)
051-808-7088 4
 
0.4%
051-623-7778 3
 
0.3%
261-6700 3
 
0.3%
051-647-5766 3
 
0.3%
051-816-4500 3
 
0.3%
051-625-8471 3
 
0.3%
051-337-7111 3
 
0.3%
051-465-2120 2
 
0.2%
264-2133 2
 
0.2%
051-361-1335 2
 
0.2%
Other values (953) 993
97.3%
2024-04-21T19:32:14.088905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1802
15.6%
0 1752
15.2%
5 1616
14.0%
1 1600
13.9%
2 870
7.5%
8 710
 
6.2%
7 707
 
6.1%
3 704
 
6.1%
6 697
 
6.0%
4 639
 
5.5%
Other values (4) 447
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9699
84.0%
Dash Punctuation 1802
 
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 1752
18.1%
5 1616
16.7%
1 1600
16.5%
2 870
9.0%
8 710
7.3%
7 707
7.3%
3 704
7.3%
6 697
 
7.2%
4 639
 
6.6%
9 404
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 1802
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 11544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1802
15.6%
0 1752
15.2%
5 1616
14.0%
1 1600
13.9%
2 870
7.5%
8 710
 
6.2%
7 707
 
6.1%
3 704
 
6.1%
6 697
 
6.0%
4 639
 
5.5%
Other values (4) 447
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1802
15.6%
0 1752
15.2%
5 1616
14.0%
1 1600
13.9%
2 870
7.5%
8 710
 
6.2%
7 707
 
6.1%
3 704
 
6.1%
6 697
 
6.0%
4 639
 
5.5%
Other values (4) 447
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

소재지우편번호
Text

MISSING 

Distinct339
Distinct (%)50.8%
Missing542
Missing (%)44.8%
Memory size9.6 KiB
2024-04-21T19:32:15.018294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9910045
Min length5

Characters and Unicode

Total characters4663
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190 ?
Unique (%)28.5%

Sample

1st row600-042
2nd row600-819
3rd row600-063
4th row600-063
5th row600-031
ValueCountFrequency (%)
609-839 33
 
4.9%
609-834 8
 
1.2%
609-822 7
 
1.0%
614-030 7
 
1.0%
609-800 7
 
1.0%
608-805 7
 
1.0%
616-852 7
 
1.0%
614-845 7
 
1.0%
604-851 6
 
0.9%
612-022 6
 
0.9%
Other values (329) 572
85.8%
2024-04-21T19:32:16.403019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 776
16.6%
0 725
15.5%
- 664
14.2%
1 612
13.1%
8 520
11.2%
4 291
 
6.2%
2 282
 
6.0%
9 276
 
5.9%
3 257
 
5.5%
7 164
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3999
85.8%
Dash Punctuation 664
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 776
19.4%
0 725
18.1%
1 612
15.3%
8 520
13.0%
4 291
 
7.3%
2 282
 
7.1%
9 276
 
6.9%
3 257
 
6.4%
7 164
 
4.1%
5 96
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 664
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4663
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 776
16.6%
0 725
15.5%
- 664
14.2%
1 612
13.1%
8 520
11.2%
4 291
 
6.2%
2 282
 
6.0%
9 276
 
5.9%
3 257
 
5.5%
7 164
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 776
16.6%
0 725
15.5%
- 664
14.2%
1 612
13.1%
8 520
11.2%
4 291
 
6.2%
2 282
 
6.0%
9 276
 
5.9%
3 257
 
5.5%
7 164
 
3.5%

소재지전체주소
Text

MISSING 

Distinct1048
Distinct (%)95.0%
Missing106
Missing (%)8.8%
Memory size9.6 KiB
2024-04-21T19:32:17.652296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length24.085222
Min length3

Characters and Unicode

Total characters26566
Distinct characters320
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

Unique998 ?
Unique (%)90.5%

Sample

1st row부산광역시 중구 부평동1가 35-20
2nd row부산광역시 중구 창선동2가 24번지 4호
3rd row부산광역시 중구 남포동2가 24번지 8호
4th row부산광역시 중구 창선동2가 24번지 4호
5th row부산광역시 중구 남포동4가 2번지 5호
ValueCountFrequency (%)
부산광역시 1074
 
19.3%
금정구 171
 
3.1%
부산진구 144
 
2.6%
1호 119
 
2.1%
남구 105
 
1.9%
사하구 87
 
1.6%
동래구 83
 
1.5%
중구 78
 
1.4%
해운대구 74
 
1.3%
북구 68
 
1.2%
Other values (1439) 3552
63.9%
2024-04-21T19:32:19.337440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4467
 
16.8%
1 1406
 
5.3%
1386
 
5.2%
1323
 
5.0%
1225
 
4.6%
1120
 
4.2%
1110
 
4.2%
1103
 
4.2%
1079
 
4.1%
2 930
 
3.5%
Other values (310) 11417
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15815
59.5%
Decimal Number 5793
 
21.8%
Space Separator 4467
 
16.8%
Dash Punctuation 321
 
1.2%
Uppercase Letter 64
 
0.2%
Other Punctuation 42
 
0.2%
Open Punctuation 30
 
0.1%
Close Punctuation 30
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1386
 
8.8%
1323
 
8.4%
1225
 
7.7%
1120
 
7.1%
1110
 
7.0%
1103
 
7.0%
1079
 
6.8%
815
 
5.2%
775
 
4.9%
759
 
4.8%
Other values (276) 5120
32.4%
Uppercase Letter
ValueCountFrequency (%)
S 11
17.2%
K 10
15.6%
B 7
10.9%
E 6
9.4%
A 6
9.4%
H 5
7.8%
C 5
7.8%
U 4
 
6.2%
Y 4
 
6.2%
L 2
 
3.1%
Other values (3) 4
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 1406
24.3%
2 930
16.1%
3 644
11.1%
4 553
 
9.5%
5 484
 
8.4%
0 404
 
7.0%
6 374
 
6.5%
7 356
 
6.1%
8 328
 
5.7%
9 314
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 34
81.0%
. 5
 
11.9%
@ 2
 
4.8%
/ 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
4467
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15815
59.5%
Common 10685
40.2%
Latin 66
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1386
 
8.8%
1323
 
8.4%
1225
 
7.7%
1120
 
7.1%
1110
 
7.0%
1103
 
7.0%
1079
 
6.8%
815
 
5.2%
775
 
4.9%
759
 
4.8%
Other values (276) 5120
32.4%
Common
ValueCountFrequency (%)
4467
41.8%
1 1406
 
13.2%
2 930
 
8.7%
3 644
 
6.0%
4 553
 
5.2%
5 484
 
4.5%
0 404
 
3.8%
6 374
 
3.5%
7 356
 
3.3%
8 328
 
3.1%
Other values (9) 739
 
6.9%
Latin
ValueCountFrequency (%)
S 11
16.7%
K 10
15.2%
B 7
10.6%
E 6
9.1%
A 6
9.1%
H 5
7.6%
C 5
7.6%
U 4
 
6.1%
Y 4
 
6.1%
L 2
 
3.0%
Other values (5) 6
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15815
59.5%
ASCII 10751
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4467
41.5%
1 1406
 
13.1%
2 930
 
8.7%
3 644
 
6.0%
4 553
 
5.1%
5 484
 
4.5%
0 404
 
3.8%
6 374
 
3.5%
7 356
 
3.3%
8 328
 
3.1%
Other values (24) 805
 
7.5%
Hangul
ValueCountFrequency (%)
1386
 
8.8%
1323
 
8.4%
1225
 
7.7%
1120
 
7.1%
1110
 
7.0%
1103
 
7.0%
1079
 
6.8%
815
 
5.2%
775
 
4.9%
759
 
4.8%
Other values (276) 5120
32.4%

도로명전체주소
Text

MISSING 

Distinct1053
Distinct (%)93.4%
Missing82
Missing (%)6.8%
Memory size9.6 KiB
2024-04-21T19:32:20.742107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length50
Mean length28.245785
Min length20

Characters and Unicode

Total characters31833
Distinct characters360
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

Unique992 ?
Unique (%)88.0%

Sample

1st row부산광역시 중구 광복로 19-1(부평동1가)
2nd row부산광역시 중구 국제시장2길 6-1 (창선동2가)
3rd row부산광역시 중구 구덕로34번길 3-1 (남포동2가)
4th row부산광역시 중구 국제시장2길 6-1 (창선동2가)
5th row부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)
ValueCountFrequency (%)
부산광역시 1128
 
17.6%
1층 195
 
3.1%
금정구 155
 
2.4%
부산진구 143
 
2.2%
해운대구 103
 
1.6%
남구 93
 
1.5%
동래구 91
 
1.4%
사하구 90
 
1.4%
중구 78
 
1.2%
부전동 71
 
1.1%
Other values (1387) 4245
66.4%
2024-04-21T19:32:22.602443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5269
 
16.6%
1440
 
4.5%
1424
 
4.5%
1377
 
4.3%
1216
 
3.8%
1215
 
3.8%
1162
 
3.7%
1 1137
 
3.6%
1132
 
3.6%
1111
 
3.5%
Other values (350) 15350
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19022
59.8%
Space Separator 5269
 
16.6%
Decimal Number 4490
 
14.1%
Close Punctuation 1109
 
3.5%
Open Punctuation 1109
 
3.5%
Other Punctuation 580
 
1.8%
Dash Punctuation 169
 
0.5%
Uppercase Letter 72
 
0.2%
Math Symbol 8
 
< 0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1440
 
7.6%
1424
 
7.5%
1377
 
7.2%
1216
 
6.4%
1215
 
6.4%
1162
 
6.1%
1132
 
6.0%
1111
 
5.8%
594
 
3.1%
301
 
1.6%
Other values (315) 8050
42.3%
Uppercase Letter
ValueCountFrequency (%)
S 14
19.4%
K 12
16.7%
B 11
15.3%
A 5
 
6.9%
H 5
 
6.9%
C 5
 
6.9%
G 4
 
5.6%
E 4
 
5.6%
U 4
 
5.6%
Y 4
 
5.6%
Other values (4) 4
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 1137
25.3%
2 686
15.3%
3 419
 
9.3%
0 400
 
8.9%
4 387
 
8.6%
5 332
 
7.4%
7 325
 
7.2%
6 304
 
6.8%
9 259
 
5.8%
8 241
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
b 1
20.0%
h 1
20.0%
k 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 576
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5269
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19022
59.8%
Common 12734
40.0%
Latin 77
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1440
 
7.6%
1424
 
7.5%
1377
 
7.2%
1216
 
6.4%
1215
 
6.4%
1162
 
6.1%
1132
 
6.0%
1111
 
5.8%
594
 
3.1%
301
 
1.6%
Other values (315) 8050
42.3%
Latin
ValueCountFrequency (%)
S 14
18.2%
K 12
15.6%
B 11
14.3%
A 5
 
6.5%
H 5
 
6.5%
C 5
 
6.5%
G 4
 
5.2%
E 4
 
5.2%
U 4
 
5.2%
Y 4
 
5.2%
Other values (8) 9
11.7%
Common
ValueCountFrequency (%)
5269
41.4%
1 1137
 
8.9%
) 1109
 
8.7%
( 1109
 
8.7%
2 686
 
5.4%
, 576
 
4.5%
3 419
 
3.3%
0 400
 
3.1%
4 387
 
3.0%
5 332
 
2.6%
Other values (7) 1310
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19022
59.8%
ASCII 12811
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5269
41.1%
1 1137
 
8.9%
) 1109
 
8.7%
( 1109
 
8.7%
2 686
 
5.4%
, 576
 
4.5%
3 419
 
3.3%
0 400
 
3.1%
4 387
 
3.0%
5 332
 
2.6%
Other values (25) 1387
 
10.8%
Hangul
ValueCountFrequency (%)
1440
 
7.6%
1424
 
7.5%
1377
 
7.2%
1216
 
6.4%
1215
 
6.4%
1162
 
6.1%
1132
 
6.0%
1111
 
5.8%
594
 
3.1%
301
 
1.6%
Other values (315) 8050
42.3%

도로명우편번호
Text

MISSING 

Distinct548
Distinct (%)57.5%
Missing256
Missing (%)21.2%
Memory size9.6 KiB
2024-04-21T19:32:23.573429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1217209
Min length5

Characters and Unicode

Total characters4881
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique350 ?
Unique (%)36.7%

Sample

1st row48979
2nd row48946
3rd row48946
4th row48953
5th row48947
ValueCountFrequency (%)
48946 21
 
2.2%
48953 13
 
1.4%
46291 11
 
1.2%
48945 10
 
1.0%
47295 8
 
0.8%
47254 8
 
0.8%
46576 8
 
0.8%
47296 7
 
0.7%
47286 7
 
0.7%
47289 7
 
0.7%
Other values (538) 853
89.5%
2024-04-21T19:32:24.967841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1202
24.6%
8 543
11.1%
7 517
10.6%
6 488
10.0%
9 434
 
8.9%
2 378
 
7.7%
5 366
 
7.5%
0 328
 
6.7%
1 306
 
6.3%
3 261
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4823
98.8%
Dash Punctuation 58
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1202
24.9%
8 543
11.3%
7 517
10.7%
6 488
10.1%
9 434
 
9.0%
2 378
 
7.8%
5 366
 
7.6%
0 328
 
6.8%
1 306
 
6.3%
3 261
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4881
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1202
24.6%
8 543
11.1%
7 517
10.6%
6 488
10.0%
9 434
 
8.9%
2 378
 
7.7%
5 366
 
7.5%
0 328
 
6.7%
1 306
 
6.3%
3 261
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1202
24.6%
8 543
11.1%
7 517
10.6%
6 488
10.0%
9 434
 
8.9%
2 378
 
7.7%
5 366
 
7.5%
0 328
 
6.7%
1 306
 
6.3%
3 261
 
5.3%
Distinct965
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T19:32:25.857637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length6.917287
Min length2

Characters and Unicode

Total characters8363
Distinct characters415
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

Unique849 ?
Unique (%)70.2%

Sample

1st row서울광학
2nd row국전안경
3rd row아이샵(eye#)안경
4th row국전안경
5th row눈사랑안경남포
ValueCountFrequency (%)
안경원 69
 
4.5%
안경 44
 
2.9%
갤러리안경 30
 
1.9%
눈사랑안경 22
 
1.4%
안경나라 22
 
1.4%
갤러리안경원 13
 
0.8%
으뜸플러스안경 12
 
0.8%
초이스안경 12
 
0.8%
오렌즈 12
 
0.8%
세컨페이스 11
 
0.7%
Other values (964) 1295
84.0%
2024-04-21T19:32:27.183292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1094
 
13.1%
1092
 
13.1%
405
 
4.8%
333
 
4.0%
292
 
3.5%
275
 
3.3%
219
 
2.6%
198
 
2.4%
127
 
1.5%
0 95
 
1.1%
Other values (405) 4233
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7509
89.8%
Space Separator 333
 
4.0%
Decimal Number 192
 
2.3%
Lowercase Letter 90
 
1.1%
Uppercase Letter 90
 
1.1%
Close Punctuation 60
 
0.7%
Open Punctuation 60
 
0.7%
Other Punctuation 23
 
0.3%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1094
 
14.6%
1092
 
14.5%
405
 
5.4%
292
 
3.9%
275
 
3.7%
219
 
2.9%
198
 
2.6%
127
 
1.7%
88
 
1.2%
84
 
1.1%
Other values (347) 3635
48.4%
Uppercase Letter
ValueCountFrequency (%)
O 14
15.6%
E 9
 
10.0%
S 8
 
8.9%
L 6
 
6.7%
G 5
 
5.6%
K 5
 
5.6%
N 5
 
5.6%
M 4
 
4.4%
I 4
 
4.4%
C 4
 
4.4%
Other values (12) 26
28.9%
Lowercase Letter
ValueCountFrequency (%)
e 16
17.8%
n 11
12.2%
a 9
10.0%
c 9
10.0%
l 7
7.8%
i 6
 
6.7%
o 6
 
6.7%
h 5
 
5.6%
s 5
 
5.6%
t 5
 
5.6%
Other values (8) 11
12.2%
Decimal Number
ValueCountFrequency (%)
0 95
49.5%
1 43
22.4%
5 23
 
12.0%
8 22
 
11.5%
2 5
 
2.6%
3 3
 
1.6%
6 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 14
60.9%
· 4
 
17.4%
& 3
 
13.0%
# 2
 
8.7%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
333
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7509
89.8%
Common 673
 
8.0%
Latin 180
 
2.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1094
 
14.6%
1092
 
14.5%
405
 
5.4%
292
 
3.9%
275
 
3.7%
219
 
2.9%
198
 
2.6%
127
 
1.7%
88
 
1.2%
84
 
1.1%
Other values (347) 3635
48.4%
Latin
ValueCountFrequency (%)
e 16
 
8.9%
O 14
 
7.8%
n 11
 
6.1%
a 9
 
5.0%
c 9
 
5.0%
E 9
 
5.0%
S 8
 
4.4%
l 7
 
3.9%
i 6
 
3.3%
L 6
 
3.3%
Other values (30) 85
47.2%
Common
ValueCountFrequency (%)
333
49.5%
0 95
 
14.1%
) 60
 
8.9%
( 60
 
8.9%
1 43
 
6.4%
5 23
 
3.4%
8 22
 
3.3%
. 14
 
2.1%
2 5
 
0.7%
· 4
 
0.6%
Other values (7) 14
 
2.1%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7508
89.8%
ASCII 848
 
10.1%
None 5
 
0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1094
 
14.6%
1092
 
14.5%
405
 
5.4%
292
 
3.9%
275
 
3.7%
219
 
2.9%
198
 
2.6%
127
 
1.7%
88
 
1.2%
84
 
1.1%
Other values (346) 3634
48.4%
ASCII
ValueCountFrequency (%)
333
39.3%
0 95
 
11.2%
) 60
 
7.1%
( 60
 
7.1%
1 43
 
5.1%
5 23
 
2.7%
8 22
 
2.6%
e 16
 
1.9%
O 14
 
1.7%
. 14
 
1.7%
Other values (45) 168
19.8%
None
ValueCountFrequency (%)
· 4
80.0%
1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1183
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2008-11-20 14:16:39
Maximum2023-01-31 16:22:29
2024-04-21T19:32:27.575347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:32:27.979698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
I
908 
U
301 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 908
75.1%
U 301
 
24.9%

Length

2024-04-21T19:32:28.362824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:28.668541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 908
75.1%
u 301
 
24.9%
Distinct339
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-02-02 00:40:52
2024-04-21T19:32:28.980364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T19:32:29.402302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct942
Distinct (%)84.9%
Missing100
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean388091.08
Minimum367108.19
Maximum403214.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:29.816798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum367108.19
5-th percentile379703.83
Q1384870.65
median388422.63
Q3391283.63
95-th percentile397554.2
Maximum403214.46
Range36106.271
Interquartile range (IQR)6412.9831

Descriptive statistics

Standard deviation5318.463
Coefficient of variation (CV)0.013704162
Kurtosis0.44320502
Mean388091.08
Median Absolute Deviation (MAD)3215.1027
Skewness0.019622711
Sum4.30393 × 108
Variance28286049
MonotonicityNot monotonic
2024-04-21T19:32:30.258331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
387618.822819678 7
 
0.6%
387271.299492377 7
 
0.6%
389314.662086382 5
 
0.4%
387920.292113406 5
 
0.4%
389816.233000769 5
 
0.4%
398237.363461482 5
 
0.4%
384874.515689472 4
 
0.3%
389097.800933845 4
 
0.3%
385590.814676765 4
 
0.3%
384903.52410762 4
 
0.3%
Other values (932) 1059
87.6%
(Missing) 100
 
8.3%
ValueCountFrequency (%)
367108.187127244 1
0.1%
371179.513984489 1
0.1%
371180.376049706 1
0.1%
373495.794543247 1
0.1%
373508.720158694 1
0.1%
373510.894533028 1
0.1%
373567.668846554 1
0.1%
373576.028819345 1
0.1%
373735.179019114 1
0.1%
374819.186712212 1
0.1%
ValueCountFrequency (%)
403214.458027912 1
 
0.1%
402521.177512697 2
0.2%
402510.10889131 1
 
0.1%
402168.69425719 3
0.2%
401739.341804489 1
 
0.1%
401727.549646357 1
 
0.1%
401723.705430156 1
 
0.1%
401721.440535713 1
 
0.1%
401709.204864151 1
 
0.1%
401700.978437423 1
 
0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct942
Distinct (%)84.9%
Missing100
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean187357.44
Minimum174016.55
Maximum206209.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:30.664784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174016.55
5-th percentile178648.38
Q1183505.93
median187141.15
Q3191882.36
95-th percentile196260.36
Maximum206209.45
Range32192.899
Interquartile range (IQR)8376.4301

Descriptive statistics

Standard deviation5865.1354
Coefficient of variation (CV)0.031304524
Kurtosis-0.23241057
Mean187357.44
Median Absolute Deviation (MAD)4393.2899
Skewness0.1572937
Sum2.077794 × 108
Variance34399813
MonotonicityNot monotonic
2024-04-21T19:32:31.297986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186273.478853335 7
 
0.6%
186099.137533193 7
 
0.6%
194669.898821674 5
 
0.4%
186157.316240541 5
 
0.4%
193329.605871168 5
 
0.4%
187720.511056894 5
 
0.4%
179978.235223733 4
 
0.3%
192260.811648263 4
 
0.3%
179553.867031936 4
 
0.3%
179742.031632526 4
 
0.3%
Other values (932) 1059
87.6%
(Missing) 100
 
8.3%
ValueCountFrequency (%)
174016.551235181 1
 
0.1%
174289.976688419 2
0.2%
174820.944129501 1
 
0.1%
174883.742734168 2
0.2%
174910.857552639 1
 
0.1%
174915.765704636 1
 
0.1%
174922.72397246 1
 
0.1%
175057.154813015 1
 
0.1%
175314.286676535 1
 
0.1%
175382.738615908 3
0.2%
ValueCountFrequency (%)
206209.450536273 1
0.1%
206070.223360046 1
0.1%
205529.184735321 1
0.1%
205422.192069209 1
0.1%
205159.486624298 1
0.1%
205068.689054296 1
0.1%
204878.049675429 1
0.1%
204747.503833689 1
0.1%
204727.131165848 1
0.1%
204683.186892293 1
0.1%

시력표수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
1000 
0
170 
2
 
33
<NA>
 
4
3
 
2

Length

Max length4
Median length1
Mean length1.0099256
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 1000
82.7%
0 170
 
14.1%
2 33
 
2.7%
<NA> 4
 
0.3%
3 2
 
0.2%

Length

2024-04-21T19:32:31.729474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:32.067273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1000
82.7%
0 170
 
14.1%
2 33
 
2.7%
na 4
 
0.3%
3 2
 
0.2%

표본렌즈수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
904 
0
236 
2
 
33
<NA>
 
29
3
 
6

Length

Max length4
Median length1
Mean length1.0736146
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 904
74.8%
0 236
 
19.5%
2 33
 
2.7%
<NA> 29
 
2.4%
3 6
 
0.5%
266 1
 
0.1%

Length

2024-04-21T19:32:32.409627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:32.606022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 904
74.8%
0 236
 
19.5%
2 33
 
2.7%
na 29
 
2.4%
3 6
 
0.5%
266 1
 
0.1%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing38
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.8616567
Minimum0
Maximum11
Zeros236
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:32.784088image/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 deviation0.59598972
Coefficient of variation (CV)0.69167885
Kurtosis74.857327
Mean0.8616567
Median Absolute Deviation (MAD)0
Skewness4.6896638
Sum1009
Variance0.35520375
MonotonicityNot monotonic
2024-04-21T19:32:32.960859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 883
73.0%
0 236
 
19.5%
2 43
 
3.6%
3 4
 
0.3%
4 3
 
0.2%
5 1
 
0.1%
11 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 236
 
19.5%
1 883
73.0%
2 43
 
3.6%
3 4
 
0.3%
4 3
 
0.2%
5 1
 
0.1%
11 1
 
0.1%
ValueCountFrequency (%)
11 1
 
0.1%
5 1
 
0.1%
4 3
 
0.2%
3 4
 
0.3%
2 43
 
3.6%
1 883
73.0%
0 236
 
19.5%

동공거리측정기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.6%
Missing4
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean0.93029046
Minimum0
Maximum10
Zeros172
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:33.145362image/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 deviation0.59213028
Coefficient of variation (CV)0.63650044
Kurtosis56.340491
Mean0.93029046
Median Absolute Deviation (MAD)0
Skewness4.6110699
Sum1121
Variance0.35061827
MonotonicityNot monotonic
2024-04-21T19:32:33.331754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 983
81.3%
0 172
 
14.2%
2 32
 
2.6%
3 9
 
0.7%
5 5
 
0.4%
4 3
 
0.2%
10 1
 
0.1%
(Missing) 4
 
0.3%
ValueCountFrequency (%)
0 172
 
14.2%
1 983
81.3%
2 32
 
2.6%
3 9
 
0.7%
4 3
 
0.2%
5 5
 
0.4%
10 1
 
0.1%
ValueCountFrequency (%)
10 1
 
0.1%
5 5
 
0.4%
4 3
 
0.2%
3 9
 
0.7%
2 32
 
2.6%
1 983
81.3%
0 172
 
14.2%

정점굴절계기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.5%
Missing6
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean1.0199501
Minimum0
Maximum5
Zeros170
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:33.514362image/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 deviation0.62632302
Coefficient of variation (CV)0.61407221
Kurtosis4.9935158
Mean1.0199501
Median Absolute Deviation (MAD)0
Skewness1.2880816
Sum1227
Variance0.39228053
MonotonicityNot monotonic
2024-04-21T19:32:33.693239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 884
73.1%
0 170
 
14.1%
2 112
 
9.3%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
(Missing) 6
 
0.5%
ValueCountFrequency (%)
0 170
 
14.1%
1 884
73.1%
2 112
 
9.3%
3 30
 
2.5%
4 6
 
0.5%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 6
 
0.5%
3 30
 
2.5%
2 112
 
9.3%
1 884
73.1%
0 170
 
14.1%

조제용연마기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
901 
0
241 
<NA>
 
39
2
 
27
3
 
1

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 901
74.5%
0 241
 
19.9%
<NA> 39
 
3.2%
2 27
 
2.2%
3 1
 
0.1%

Length

2024-04-21T19:32:33.903831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:34.152957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 901
74.5%
0 241
 
19.9%
na 39
 
3.2%
2 27
 
2.2%
3 1
 
0.1%

렌즈절단기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
1
910 
0
240 
<NA>
 
39
2
 
19
3
 
1

Length

Max length4
Median length1
Mean length1.0967742
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 910
75.3%
0 240
 
19.9%
<NA> 39
 
3.2%
2 19
 
1.6%
3 1
 
0.1%

Length

2024-04-21T19:32:34.538737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T19:32:34.878732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 910
75.3%
0 240
 
19.9%
na 39
 
3.2%
2 19
 
1.6%
3 1
 
0.1%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing39
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean0.90598291
Minimum0
Maximum5
Zeros240
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:35.194219image/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 deviation0.59052841
Coefficient of variation (CV)0.65180966
Kurtosis5.0031041
Mean0.90598291
Median Absolute Deviation (MAD)0
Skewness0.84866408
Sum1060
Variance0.3487238
MonotonicityNot monotonic
2024-04-21T19:32:35.533729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 817
67.6%
0 240
 
19.9%
2 101
 
8.4%
3 9
 
0.7%
5 2
 
0.2%
4 1
 
0.1%
(Missing) 39
 
3.2%
ValueCountFrequency (%)
0 240
 
19.9%
1 817
67.6%
2 101
 
8.4%
3 9
 
0.7%
4 1
 
0.1%
5 2
 
0.2%
ValueCountFrequency (%)
5 2
 
0.2%
4 1
 
0.1%
3 9
 
0.7%
2 101
 
8.4%
1 817
67.6%
0 240
 
19.9%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing38
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.93851409
Minimum0
Maximum5
Zeros239
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:35.863111image/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 deviation0.62945711
Coefficient of variation (CV)0.67069543
Kurtosis3.1621723
Mean0.93851409
Median Absolute Deviation (MAD)0
Skewness0.80940972
Sum1099
Variance0.39621625
MonotonicityNot monotonic
2024-04-21T19:32:36.201657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 791
65.4%
0 239
 
19.8%
2 119
 
9.8%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
(Missing) 38
 
3.1%
ValueCountFrequency (%)
0 239
 
19.8%
1 791
65.4%
2 119
 
9.8%
3 19
 
1.6%
4 2
 
0.2%
5 1
 
0.1%
ValueCountFrequency (%)
5 1
 
0.1%
4 2
 
0.2%
3 19
 
1.6%
2 119
 
9.8%
1 791
65.4%
0 239
 
19.8%

총면적
Real number (ℝ)

MISSING  ZEROS 

Distinct529
Distinct (%)71.8%
Missing472
Missing (%)39.0%
Infinite0
Infinite (%)0.0%
Mean74.237408
Minimum0
Maximum723.02
Zeros99
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size10.8 KiB
2024-04-21T19:32:36.569524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q130.75
median57.75
Q397.38
95-th percentile210
Maximum723.02
Range723.02
Interquartile range (IQR)66.63

Descriptive statistics

Standard deviation71.857052
Coefficient of variation (CV)0.96793589
Kurtosis17.642892
Mean74.237408
Median Absolute Deviation (MAD)31.75
Skewness2.9342954
Sum54712.97
Variance5163.4359
MonotonicityNot monotonic
2024-04-21T19:32:37.013588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 99
 
8.2%
33.0 10
 
0.8%
60.0 5
 
0.4%
66.0 5
 
0.4%
49.5 5
 
0.4%
99.0 4
 
0.3%
105.0 4
 
0.3%
56.0 4
 
0.3%
57.6 4
 
0.3%
46.2 4
 
0.3%
Other values (519) 593
49.0%
(Missing) 472
39.0%
ValueCountFrequency (%)
0.0 99
8.2%
1.0 1
 
0.1%
2.0 1
 
0.1%
5.56 1
 
0.1%
5.6 1
 
0.1%
7.5 1
 
0.1%
8.5 1
 
0.1%
9.7 1
 
0.1%
10.23 1
 
0.1%
11.22 1
 
0.1%
ValueCountFrequency (%)
723.02 1
0.1%
700.0 1
0.1%
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%
310.68 1
0.1%
304.5 1
0.1%
304.12 1
0.1%

Unnamed: 38
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1209
Missing (%)100.0%
Memory size10.8 KiB

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
01안경업01_02_01_P3250000PHMB2202332500210822000012023-01-31<NA>3폐업3폐업2023-01-31<NA><NA><NA>051-243-3991<NA><NA>부산광역시 중구 부평동1가 35-20부산광역시 중구 광복로 19-1(부평동1가)48979서울광학2023-01-31 16:22:29I2023-02-02 00:40:52<NA>384781.953731179720.1183230000000000.0<NA>
12안경업01_02_01_P3250000PHMB2201832500210822000012018-08-14<NA>3폐업3폐업2021-07-26<NA><NA><NA>2531216<NA><NA>부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경2021-07-26 15:27:58U2021-07-28 02:40:00<NA>384903.524108179742.03163311111111193.22<NA>
23안경업01_02_01_P3250000PHMB2201032500210822000012010-03-12<NA>3폐업3폐업2012-04-06<NA><NA><NA>070-4116-2770<NA>600-042부산광역시 중구 남포동2가 24번지 8호부산광역시 중구 구덕로34번길 3-1 (남포동2가)<NA>아이샵(eye#)안경2012-10-26 09:20:51I2018-08-31 23:59:59<NA>385208.616221179585.320651111111111134.98<NA>
34안경업01_02_01_P3250000PHMB2199332500210822000011993-03-27<NA>3폐업3폐업2018-08-14<NA><NA><NA>051-253-1216<NA>600-819부산광역시 중구 창선동2가 24번지 4호부산광역시 중구 국제시장2길 6-1 (창선동2가)48946국전안경2018-08-14 10:27:02I2018-08-31 23:59:59<NA>384903.524108179742.031633111111111<NA><NA>
45안경업01_02_01_P3250000PHMB2201032500210822000062010-12-27<NA>3폐업3폐업2019-04-16<NA><NA><NA><NA><NA><NA>부산광역시 중구 남포동4가 2번지 5호부산광역시 중구 구덕로 38-1, 1,2층 (남포동4가)48953눈사랑안경남포2019-04-16 15:19:24U2019-04-18 02:40:00<NA>385186.028117179577.535415111141144188.2<NA>
56안경업01_02_01_P3250000PHMB2201432500210822000012014-01-02<NA>3폐업3폐업2016-10-12<NA><NA><NA>051-246-0006<NA><NA><NA>부산광역시 중구 광복로 43 (창선동1가)48947갤러리안경원2016-10-12 16:25:24I2018-08-31 23:59:59<NA>385016.604749179699.072538111111111197.49<NA>
67안경업01_02_01_P3250000PHMB2200432500210822000012004-03-12<NA>3폐업3폐업2009-03-20<NA><NA><NA>051-245-1999<NA><NA>부산광역시 중구 남포동6가 85<NA><NA>남포프라자안경2012-03-20 13:58:00I2018-08-31 23:59:59<NA><NA><NA>111111111<NA><NA>
78안경업01_02_01_P3250000PHMB2200532500210822000012005-11-22<NA>3폐업3폐업2018-04-16<NA><NA><NA>051-245-7344<NA><NA>부산광역시 중구 부평동1가 23-27부산광역시 중구 중구로33번길 12 (부평동1가)48978마루안경2018-04-24 15:35:21I2018-08-31 23:59:59<NA>384779.424584179871.25352111111111<NA><NA>
89안경업01_02_01_P3250000PHMB2200632500210822000012006-12-28<NA>3폐업3폐업2021-06-23<NA><NA><NA>051-246-1341<NA><NA>부산광역시 중구 창선동2가 45-17부산광역시 중구 중구로 14 (창선동2가)48953080안경2021-06-23 11:40:02U2021-06-25 02:40:00<NA>384843.682071179657.801434111111111<NA><NA>
910안경업01_02_01_P3250000PHMB2201032500210822000052010-11-09<NA>3폐업3폐업2018-05-31<NA><NA><NA>242-4623<NA>600-063부산광역시 중구 신창동3가 16번지 7호부산광역시 중구 광복로35번길 16 (신창동3가)48946스마일안경2018-06-05 15:05:19I2018-08-31 23:59:59<NA>384931.528183179828.54383611111111149.0<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적Unnamed: 38
11991200안경업01_02_01_P3400000PHMB2202034000130822000012020-02-21<NA>1영업/정상13영업중<NA><NA><NA><NA>0517215051<NA><NA>부산광역시 기장군 기장읍 동부리 280번지 11호 빠리바게트부산광역시 기장군 기장읍 차성동로 64, 2층46065으뜸50안경콘택트 기장점2020-02-21 16:32:10I2020-02-23 00:23:23<NA>401709.204864196053.98254111<NA>1<NA><NA><NA><NA><NA>100.42<NA>
12001201안경업01_02_01_P3400000PHMB2201434000130822000032014-08-27<NA>1영업/정상13영업중<NA><NA><NA><NA>728-7229<NA><NA><NA>부산광역시 기장군 정관면 정관로 389 (롯데타워 103호)46008우리동네 안경원2019-06-28 14:53:12U2019-06-30 02:40:00<NA>396839.499809206070.2233611122111272.6<NA>
12011202안경업01_02_01_P3400000PHMB2202134000130822000022021-07-28<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7585-0909<NA><NA>부산광역시 기장군 정관읍 매학리 713-1 정관타워부산광역시 기장군 정관읍 정관로 561, 3층 303호46015으뜸플러스안경 부산정관점2021-07-29 10:53:16I2021-07-31 00:22:51<NA>397748.735322204683.186892100110000202.97<NA>
12021203안경업01_02_01_P3400000PHMB2202134000130822000032021-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-2233<NA><NA>부산광역시 기장군 일광면 삼성리 830부산광역시 기장군 일광면 해빛6로 107-3, 1층 105,106호46048바라본안경2021-09-06 14:22:36I2021-09-08 00:22:50<NA>402510.108891198551.86926410011000063.5<NA>
12031204안경업01_02_01_P3400000PHMB2202234000130822000042022-11-28<NA>1영업/정상13영업중<NA><NA><NA><NA>051-911-4806<NA><NA>부산광역시 기장군 일광읍 삼성리 825-2 일광제일프라자부산광역시 기장군 일광읍 해빛로 13, 일광제일프라자 1층 104호46048눈사랑 위드렌즈2022-11-28 16:13:26I2022-11-30 00:39:55<NA>402521.177513198590.0505110011000054.5<NA>
12041205안경업01_02_01_P3400000PHMB2202134000130822000012021-06-01<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-3180<NA><NA>부산광역시 기장군 기장읍 교리 342-1부산광역시 기장군 기장읍 차성로 430, 1층 110호46056기장성모안경2021-11-16 14:54:30U2021-11-18 02:40:00<NA>401700.978437197225.4284920011000062.73<NA>
12051206안경업01_02_01_P3400000PHMB2202034000130822000022011-07-28<NA>1영업/정상13영업중<NA><NA><NA><NA>051-545-1518<NA><NA>부산광역시 기장군 기장읍 교리 340-1 꼬마돈까스부산광역시 기장군 기장읍 차성로 424, 1층46056갤러리안경2020-09-14 13:29:24I2020-09-16 00:23:12<NA>401654.858504197228.25010311111112256.6<NA>
12061207안경업01_02_01_P3400000PHMB2202234000130822000032022-08-18<NA>1영업/정상13영업중<NA><NA><NA><NA>051-728-5008<NA><NA>부산광역시 기장군 정관읍 달산리 1221-6부산광역시 기장군 정관읍 정관로 70446021이노티안경 정관점2022-12-09 15:00:16U2022-12-11 02:40:00<NA>399070.084726204598.839584100110000160.0<NA>
12071208안경업01_02_01_P3400000PHMB2201834000130822000012018-11-22<NA>1영업/정상13영업중<NA><NA><NA><NA>051-724-6900<NA><NA>부산광역시 기장군 기장읍 동부리 362번지 1호부산광역시 기장군 기장읍 차성동로 10446063다비치안경 기장시장점2019-05-02 16:27:48U2019-05-04 02:40:00<NA>401723.70543196436.867371222221122213.0<NA>
12081209안경업01_02_01_P3400000PHMB2202234000130822000022022-05-24<NA>1영업/정상13영업중<NA><NA><NA><NA>051-722-7212<NA><NA>부산광역시 기장군 일광읍 삼성리 825-2 일광제일프라자부산광역시 기장군 일광읍 해빛로 13, 일광제일프라자 상가동 202호46048오늘 안경원(see channel)2022-12-09 15:01:05U2022-12-11 02:40:00<NA>402521.177513198590.05051100110000107.62<NA>