Overview

Dataset statistics

Number of variables35
Number of observations4622
Missing cells40849
Missing cells (%)25.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory302.0 B

Variable types

Numeric14
Text6
DateTime4
Categorical8
Unsupported3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),시력표수,표본렌즈수,측정의자수,동공거리측정기수,정점굴절계기수,조제용연마기수,렌즈절단기수,가열기수,안경세척기수,총면적
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16490/S/1/datasetView.do

Alerts

상세영업상태코드 is highly imbalanced (51.9%)Imbalance
상세영업상태명 is highly imbalanced (51.9%)Imbalance
휴업종료일자 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 4557 (98.6%) missing valuesMissing
폐업일자 has 2715 (58.7%) missing valuesMissing
휴업시작일자 has 4406 (95.3%) missing valuesMissing
재개업일자 has 4622 (100.0%) missing valuesMissing
전화번호 has 844 (18.3%) missing valuesMissing
소재지면적 has 4622 (100.0%) missing valuesMissing
소재지우편번호 has 2103 (45.5%) missing valuesMissing
지번주소 has 232 (5.0%) missing valuesMissing
도로명주소 has 902 (19.5%) missing valuesMissing
도로명우편번호 has 1112 (24.1%) missing valuesMissing
업태구분명 has 4622 (100.0%) missing valuesMissing
좌표정보(X) has 899 (19.5%) missing valuesMissing
좌표정보(Y) has 899 (19.5%) missing valuesMissing
표본렌즈수 has 886 (19.2%) missing valuesMissing
측정의자수 has 885 (19.1%) missing valuesMissing
동공거리측정기수 has 824 (17.8%) missing valuesMissing
정점굴절계기수 has 816 (17.7%) missing valuesMissing
렌즈절단기수 has 914 (19.8%) missing valuesMissing
가열기수 has 912 (19.7%) missing valuesMissing
안경세척기수 has 904 (19.6%) missing valuesMissing
총면적 has 2173 (47.0%) missing valuesMissing
표본렌즈수 is highly skewed (γ1 = 60.13440356)Skewed
총면적 is highly skewed (γ1 = 38.41322833)Skewed
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
표본렌즈수 has 1023 (22.1%) zerosZeros
측정의자수 has 1031 (22.3%) zerosZeros
동공거리측정기수 has 962 (20.8%) zerosZeros
정점굴절계기수 has 957 (20.7%) zerosZeros
렌즈절단기수 has 1054 (22.8%) zerosZeros
가열기수 has 1051 (22.7%) zerosZeros
안경세척기수 has 1047 (22.7%) zerosZeros
총면적 has 463 (10.0%) zerosZeros

Reproduction

Analysis started2024-05-18 03:20:02.310518
Analysis finished2024-05-18 03:20:07.100901
Duration4.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3125928.2
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:07.386111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13060000
median3130000
Q33200000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)140000

Descriptive statistics

Standard deviation76651.362
Coefficient of variation (CV)0.024521153
Kurtosis-1.2702041
Mean3125928.2
Median Absolute Deviation (MAD)70000
Skewness-0.15101098
Sum1.444804 × 1010
Variance5.8754313 × 109
MonotonicityNot monotonic
2024-05-18T12:20:07.967813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3010000 542
 
11.7%
3220000 359
 
7.8%
3180000 305
 
6.6%
3100000 299
 
6.5%
3230000 233
 
5.0%
3240000 220
 
4.8%
3130000 213
 
4.6%
3110000 212
 
4.6%
3210000 201
 
4.3%
3150000 179
 
3.9%
Other values (15) 1859
40.2%
ValueCountFrequency (%)
3000000 118
 
2.6%
3010000 542
11.7%
3020000 93
 
2.0%
3030000 87
 
1.9%
3040000 118
 
2.6%
3050000 149
 
3.2%
3060000 127
 
2.7%
3070000 153
 
3.3%
3080000 92
 
2.0%
3090000 86
 
1.9%
ValueCountFrequency (%)
3240000 220
4.8%
3230000 233
5.0%
3220000 359
7.8%
3210000 201
4.3%
3200000 168
3.6%
3190000 134
 
2.9%
3180000 305
6.6%
3170000 91
 
2.0%
3160000 141
 
3.1%
3150000 179
3.9%
Distinct4621
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
2024-05-18T12:20:08.912322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters115550
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

Unique4620 ?
Unique (%)> 99.9%

Sample

1st rowPHMB220223220033082200004
2nd rowPHMB219903130033082200002
3rd rowPHMB220173010033082200015
4th rowPHMB220183040033082200005
5th rowPHMB220203140033082200005
ValueCountFrequency (%)
phmb220183010033082200001 2
 
< 0.1%
phmb220113180034082200007 1
 
< 0.1%
phmb220133170035082200003 1
 
< 0.1%
phmb219993170035082200001 1
 
< 0.1%
phmb219983170035082200002 1
 
< 0.1%
phmb220173170035082200003 1
 
< 0.1%
phmb220173170035082200002 1
 
< 0.1%
phmb220173170035082200001 1
 
< 0.1%
phmb219993170035082200002 1
 
< 0.1%
phmb220003170035082200001 1
 
< 0.1%
Other values (4611) 4611
99.8%
2024-05-18T12:20:10.377909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38945
33.7%
2 20858
18.1%
3 13362
 
11.6%
1 8014
 
6.9%
8 5716
 
4.9%
P 4622
 
4.0%
H 4622
 
4.0%
M 4622
 
4.0%
B 4622
 
4.0%
9 3493
 
3.0%
Other values (4) 6674
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97062
84.0%
Uppercase Letter 18488
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38945
40.1%
2 20858
21.5%
3 13362
 
13.8%
1 8014
 
8.3%
8 5716
 
5.9%
9 3493
 
3.6%
4 3237
 
3.3%
5 1281
 
1.3%
7 1116
 
1.1%
6 1040
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
P 4622
25.0%
H 4622
25.0%
M 4622
25.0%
B 4622
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97062
84.0%
Latin 18488
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38945
40.1%
2 20858
21.5%
3 13362
 
13.8%
1 8014
 
8.3%
8 5716
 
5.9%
9 3493
 
3.6%
4 3237
 
3.3%
5 1281
 
1.3%
7 1116
 
1.1%
6 1040
 
1.1%
Latin
ValueCountFrequency (%)
P 4622
25.0%
H 4622
25.0%
M 4622
25.0%
B 4622
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115550
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38945
33.7%
2 20858
18.1%
3 13362
 
11.6%
1 8014
 
6.9%
8 5716
 
4.9%
P 4622
 
4.0%
H 4622
 
4.0%
M 4622
 
4.0%
B 4622
 
4.0%
9 3493
 
3.0%
Other values (4) 6674
 
5.8%
Distinct3409
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
Minimum1900-01-01 00:00:00
Maximum2024-05-13 00:00:00
2024-05-18T12:20:10.847349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:20:11.443377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)95.4%
Missing4557
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean20139299
Minimum20090128
Maximum20181005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:12.096498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090128
5-th percentile20090423
Q120110128
median20140728
Q320170620
95-th percentile20180867
Maximum20181005
Range90877
Interquartile range (IQR)60492

Descriptive statistics

Standard deviation32777.191
Coefficient of variation (CV)0.0016275239
Kurtosis-1.4110171
Mean20139299
Median Absolute Deviation (MAD)29982
Skewness-0.21895971
Sum1.3090544 × 109
Variance1.0743443 × 109
MonotonicityNot monotonic
2024-05-18T12:20:12.787807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131121 2
 
< 0.1%
20170710 2
 
< 0.1%
20090423 2
 
< 0.1%
20160108 1
 
< 0.1%
20180611 1
 
< 0.1%
20170620 1
 
< 0.1%
20161014 1
 
< 0.1%
20171012 1
 
< 0.1%
20180720 1
 
< 0.1%
20180608 1
 
< 0.1%
Other values (52) 52
 
1.1%
(Missing) 4557
98.6%
ValueCountFrequency (%)
20090128 1
< 0.1%
20090204 1
< 0.1%
20090209 1
< 0.1%
20090423 2
< 0.1%
20090515 1
< 0.1%
20090604 1
< 0.1%
20090717 1
< 0.1%
20090810 1
< 0.1%
20090812 1
< 0.1%
20091231 1
< 0.1%
ValueCountFrequency (%)
20181005 1
< 0.1%
20180918 1
< 0.1%
20180912 1
< 0.1%
20180904 1
< 0.1%
20180720 1
< 0.1%
20180702 1
< 0.1%
20180614 1
< 0.1%
20180611 1
< 0.1%
20180608 1
< 0.1%
20180601 1
< 0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
1
2298 
3
2239 
4
 
84
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 2298
49.7%
3 2239
48.4%
4 84
 
1.8%
2 1
 
< 0.1%

Length

2024-05-18T12:20:13.361006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:13.726367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2298
49.7%
3 2239
48.4%
4 84
 
1.8%
2 1
 
< 0.1%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
영업/정상
2298 
폐업
2239 
취소/말소/만료/정지/중지
 
84
휴업
 
1

Length

Max length14
Median length5
Mean length3.7096495
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 2298
49.7%
폐업 2239
48.4%
취소/말소/만료/정지/중지 84
 
1.8%
휴업 1
 
< 0.1%

Length

2024-05-18T12:20:14.085797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:14.456235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 2298
49.7%
폐업 2239
48.4%
취소/말소/만료/정지/중지 84
 
1.8%
휴업 1
 
< 0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
13
2298 
3
2239 
24
 
83
2
 
1
25
 
1

Length

Max length2
Median length2
Mean length1.5153613
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 2298
49.7%
3 2239
48.4%
24 83
 
1.8%
2 1
 
< 0.1%
25 1
 
< 0.1%

Length

2024-05-18T12:20:14.918455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:15.320378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 2298
49.7%
3 2239
48.4%
24 83
 
1.8%
2 1
 
< 0.1%
25 1
 
< 0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
영업중
2298 
폐업
2239 
직권폐업
 
83
휴업
 
1
영업정지
 
1

Length

Max length4
Median length3
Mean length2.5335353
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2298
49.7%
폐업 2239
48.4%
직권폐업 83
 
1.8%
휴업 1
 
< 0.1%
영업정지 1
 
< 0.1%

Length

2024-05-18T12:20:15.757863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:16.097698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2298
49.7%
폐업 2239
48.4%
직권폐업 83
 
1.8%
휴업 1
 
< 0.1%
영업정지 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1480
Distinct (%)77.6%
Missing2715
Missing (%)58.7%
Memory size36.2 KiB
Minimum1998-04-07 00:00:00
Maximum2024-05-27 00:00:00
2024-05-18T12:20:16.466193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:20:16.904522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)62.0%
Missing4406
Missing (%)95.3%
Infinite0
Infinite (%)0.0%
Mean20050464
Minimum19980407
Maximum20210114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:17.293311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980407
5-th percentile19990188
Q120050711
median20060317
Q320060828
95-th percentile20080619
Maximum20210114
Range229707
Interquartile range (IQR)10117.5

Descriptive statistics

Standard deviation31032.198
Coefficient of variation (CV)0.0015477047
Kurtosis4.7293023
Mean20050464
Median Absolute Deviation (MAD)9514
Skewness0.028840774
Sum4.3309003 × 109
Variance9.6299733 × 108
MonotonicityNot monotonic
2024-05-18T12:20:17.718136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060317 64
 
1.4%
20071016 5
 
0.1%
20050801 4
 
0.1%
20050727 3
 
0.1%
19990713 3
 
0.1%
20061013 3
 
0.1%
20051129 2
 
< 0.1%
20050803 2
 
< 0.1%
20060224 2
 
< 0.1%
20060721 2
 
< 0.1%
Other values (124) 126
 
2.7%
(Missing) 4406
95.3%
ValueCountFrequency (%)
19980407 1
< 0.1%
19980427 1
< 0.1%
19980601 1
< 0.1%
19980623 1
< 0.1%
19980716 1
< 0.1%
19980817 1
< 0.1%
19980826 1
< 0.1%
19980903 1
< 0.1%
19980917 1
< 0.1%
19981204 1
< 0.1%
ValueCountFrequency (%)
20210114 1
< 0.1%
20190228 1
< 0.1%
20081021 1
< 0.1%
20081009 1
< 0.1%
20080910 1
< 0.1%
20080827 1
< 0.1%
20080821 1
< 0.1%
20080820 1
< 0.1%
20080624 1
< 0.1%
20080623 1
< 0.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
<NA>
4620 
20200228
 
1
20210731
 
1

Length

Max length8
Median length4
Mean length4.0017309
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4620
> 99.9%
20200228 1
 
< 0.1%
20210731 1
 
< 0.1%

Length

2024-05-18T12:20:18.160694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:18.492655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4620
> 99.9%
20200228 1
 
< 0.1%
20210731 1
 
< 0.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4622
Missing (%)100.0%
Memory size40.8 KiB

전화번호
Text

MISSING 

Distinct3557
Distinct (%)94.2%
Missing844
Missing (%)18.3%
Memory size36.2 KiB
2024-05-18T12:20:19.121376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length10.09423
Min length3

Characters and Unicode

Total characters38136
Distinct characters15
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

Unique3364 ?
Unique (%)89.0%

Sample

1st row07077125546
2nd row02-308-6662
3rd row02-499-9333
4th row02-2651-1002
5th row02-387-8854
ValueCountFrequency (%)
02-354-6741 6
 
0.2%
02-932-3005 5
 
0.1%
3482-2203 4
 
0.1%
02-309-1333 4
 
0.1%
02-930-7468 4
 
0.1%
02-780-7478 3
 
0.1%
02-373-3389 3
 
0.1%
02-6406-0595 3
 
0.1%
517-5308 3
 
0.1%
02 3
 
0.1%
Other values (3546) 3740
99.0%
2024-05-18T12:20:20.039614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 5990
15.7%
0 5587
14.7%
2 5295
13.9%
3 3194
8.4%
5 2733
7.2%
7 2733
7.2%
1 2682
7.0%
4 2570
6.7%
8 2478
6.5%
6 2450
6.4%
Other values (5) 2424
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32136
84.3%
Dash Punctuation 5990
 
15.7%
Other Punctuation 5
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5587
17.4%
2 5295
16.5%
3 3194
9.9%
5 2733
8.5%
7 2733
8.5%
1 2682
8.3%
4 2570
8.0%
8 2478
7.7%
6 2450
7.6%
9 2414
7.5%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 5990
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38136
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 5990
15.7%
0 5587
14.7%
2 5295
13.9%
3 3194
8.4%
5 2733
7.2%
7 2733
7.2%
1 2682
7.0%
4 2570
6.7%
8 2478
6.5%
6 2450
6.4%
Other values (5) 2424
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 5990
15.7%
0 5587
14.7%
2 5295
13.9%
3 3194
8.4%
5 2733
7.2%
7 2733
7.2%
1 2682
7.0%
4 2570
6.7%
8 2478
6.5%
6 2450
6.4%
Other values (5) 2424
6.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4622
Missing (%)100.0%
Memory size40.8 KiB

소재지우편번호
Text

MISSING 

Distinct1203
Distinct (%)47.8%
Missing2103
Missing (%)45.5%
Memory size36.2 KiB
2024-05-18T12:20:20.723136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0389043
Min length5

Characters and Unicode

Total characters15212
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique730 ?
Unique (%)29.0%

Sample

1st row121-250
2nd row100-805
3rd row133-823
4th row158-054
5th row136-817
ValueCountFrequency (%)
100804 67
 
2.7%
100094 29
 
1.2%
100011 24
 
1.0%
100092 19
 
0.8%
139205 16
 
0.6%
150010 15
 
0.6%
121210 15
 
0.6%
100802 15
 
0.6%
100762 14
 
0.6%
139200 14
 
0.6%
Other values (1193) 2291
90.9%
2024-05-18T12:20:21.703614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3663
24.1%
0 2742
18.0%
8 1671
11.0%
3 1630
10.7%
2 1417
 
9.3%
5 1246
 
8.2%
4 787
 
5.2%
9 763
 
5.0%
7 692
 
4.5%
6 499
 
3.3%
Other values (2) 102
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15110
99.3%
Dash Punctuation 100
 
0.7%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3663
24.2%
0 2742
18.1%
8 1671
11.1%
3 1630
10.8%
2 1417
 
9.4%
5 1246
 
8.2%
4 787
 
5.2%
9 763
 
5.0%
7 692
 
4.6%
6 499
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3663
24.1%
0 2742
18.0%
8 1671
11.0%
3 1630
10.7%
2 1417
 
9.3%
5 1246
 
8.2%
4 787
 
5.2%
9 763
 
5.0%
7 692
 
4.5%
6 499
 
3.3%
Other values (2) 102
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3663
24.1%
0 2742
18.0%
8 1671
11.0%
3 1630
10.7%
2 1417
 
9.3%
5 1246
 
8.2%
4 787
 
5.2%
9 763
 
5.0%
7 692
 
4.5%
6 499
 
3.3%
Other values (2) 102
 
0.7%

지번주소
Text

MISSING 

Distinct4177
Distinct (%)95.1%
Missing232
Missing (%)5.0%
Memory size36.2 KiB
2024-05-18T12:20:22.417810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length46
Mean length25.387927
Min length6

Characters and Unicode

Total characters111453
Distinct characters536
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4012 ?
Unique (%)91.4%

Sample

1st row서울특별시 강남구 신사동 532-2
2nd row서울특별시 마포구 성산2동200-364
3rd row서울특별시 광진구 화양동 6-1
4th row서울특별시 양천구 신정동 323번지 9호 이스타빌
5th row서울특별시 은평구 신사동 7-4
ValueCountFrequency (%)
서울특별시 4105
 
18.1%
1층 530
 
2.3%
중구 453
 
2.0%
1호 341
 
1.5%
강남구 303
 
1.3%
영등포구 297
 
1.3%
강동구 210
 
0.9%
송파구 207
 
0.9%
은평구 203
 
0.9%
마포구 198
 
0.9%
Other values (4785) 15838
69.8%
2024-05-18T12:20:23.742862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18520
 
16.6%
1 5697
 
5.1%
4909
 
4.4%
4908
 
4.4%
4526
 
4.1%
4350
 
3.9%
4274
 
3.8%
4243
 
3.8%
4240
 
3.8%
3484
 
3.1%
Other values (526) 52302
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67972
61.0%
Decimal Number 22814
 
20.5%
Space Separator 18520
 
16.6%
Dash Punctuation 1105
 
1.0%
Uppercase Letter 372
 
0.3%
Other Punctuation 214
 
0.2%
Close Punctuation 181
 
0.2%
Open Punctuation 181
 
0.2%
Lowercase Letter 66
 
0.1%
Math Symbol 24
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4909
 
7.2%
4908
 
7.2%
4526
 
6.7%
4350
 
6.4%
4274
 
6.3%
4243
 
6.2%
4240
 
6.2%
3484
 
5.1%
3340
 
4.9%
3112
 
4.6%
Other values (457) 26586
39.1%
Uppercase Letter
ValueCountFrequency (%)
B 72
19.4%
A 41
11.0%
S 28
 
7.5%
C 23
 
6.2%
K 22
 
5.9%
D 22
 
5.9%
G 20
 
5.4%
E 17
 
4.6%
L 16
 
4.3%
T 16
 
4.3%
Other values (16) 95
25.5%
Lowercase Letter
ValueCountFrequency (%)
e 13
19.7%
o 9
13.6%
a 7
10.6%
r 5
 
7.6%
i 4
 
6.1%
s 4
 
6.1%
u 4
 
6.1%
n 4
 
6.1%
b 2
 
3.0%
q 2
 
3.0%
Other values (8) 12
18.2%
Decimal Number
ValueCountFrequency (%)
1 5697
25.0%
2 3059
13.4%
3 2515
11.0%
4 2026
 
8.9%
5 1918
 
8.4%
0 1842
 
8.1%
6 1692
 
7.4%
7 1413
 
6.2%
8 1382
 
6.1%
9 1270
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 174
81.3%
. 16
 
7.5%
/ 14
 
6.5%
@ 7
 
3.3%
& 2
 
0.9%
? 1
 
0.5%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
18520
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Open Punctuation
ValueCountFrequency (%)
( 181
100.0%
Math Symbol
ValueCountFrequency (%)
~ 24
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67973
61.0%
Common 43040
38.6%
Latin 440
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4909
 
7.2%
4908
 
7.2%
4526
 
6.7%
4350
 
6.4%
4274
 
6.3%
4243
 
6.2%
4240
 
6.2%
3484
 
5.1%
3340
 
4.9%
3112
 
4.6%
Other values (458) 26587
39.1%
Latin
ValueCountFrequency (%)
B 72
16.4%
A 41
 
9.3%
S 28
 
6.4%
C 23
 
5.2%
K 22
 
5.0%
D 22
 
5.0%
G 20
 
4.5%
E 17
 
3.9%
L 16
 
3.6%
T 16
 
3.6%
Other values (36) 163
37.0%
Common
ValueCountFrequency (%)
18520
43.0%
1 5697
 
13.2%
2 3059
 
7.1%
3 2515
 
5.8%
4 2026
 
4.7%
5 1918
 
4.5%
0 1842
 
4.3%
6 1692
 
3.9%
7 1413
 
3.3%
8 1382
 
3.2%
Other values (12) 2976
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67972
61.0%
ASCII 43478
39.0%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18520
42.6%
1 5697
 
13.1%
2 3059
 
7.0%
3 2515
 
5.8%
4 2026
 
4.7%
5 1918
 
4.4%
0 1842
 
4.2%
6 1692
 
3.9%
7 1413
 
3.2%
8 1382
 
3.2%
Other values (56) 3414
 
7.9%
Hangul
ValueCountFrequency (%)
4909
 
7.2%
4908
 
7.2%
4526
 
6.7%
4350
 
6.4%
4274
 
6.3%
4243
 
6.2%
4240
 
6.2%
3484
 
5.1%
3340
 
4.9%
3112
 
4.6%
Other values (457) 26586
39.1%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3591
Distinct (%)96.5%
Missing902
Missing (%)19.5%
Memory size36.2 KiB
2024-05-18T12:20:24.527642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length54
Mean length31.324731
Min length12

Characters and Unicode

Total characters116528
Distinct characters555
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3478 ?
Unique (%)93.5%

Sample

1st row서울특별시 강남구 압구정로10길 11, 1층 (신사동)
2nd row서울특별시 마포구 월드컵북로 188 (성산동)
3rd row서울특별시 중구 장충단로13길 20, 현대시티타워 지하1층 (을지로6가)
4th row서울특별시 광진구 능동로 103, 1층 2-2호 (화양동)
5th row서울특별시 양천구 목동서로 377, 이스타빌 A동 2층 209호 (신정동)
ValueCountFrequency (%)
서울특별시 3718
 
16.1%
1층 954
 
4.1%
중구 361
 
1.6%
강남구 325
 
1.4%
영등포구 228
 
1.0%
송파구 211
 
0.9%
마포구 196
 
0.8%
서초구 189
 
0.8%
2층 174
 
0.8%
강서구 163
 
0.7%
Other values (4139) 16570
71.8%
2024-05-18T12:20:25.720900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19386
 
16.6%
1 4884
 
4.2%
4586
 
3.9%
4552
 
3.9%
4051
 
3.5%
4026
 
3.5%
3989
 
3.4%
3790
 
3.3%
) 3751
 
3.2%
( 3750
 
3.2%
Other values (545) 59763
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68472
58.8%
Space Separator 19386
 
16.6%
Decimal Number 16882
 
14.5%
Close Punctuation 3751
 
3.2%
Open Punctuation 3750
 
3.2%
Other Punctuation 3307
 
2.8%
Uppercase Letter 430
 
0.4%
Dash Punctuation 419
 
0.4%
Lowercase Letter 95
 
0.1%
Math Symbol 33
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4586
 
6.7%
4552
 
6.6%
4051
 
5.9%
4026
 
5.9%
3989
 
5.8%
3790
 
5.5%
3720
 
5.4%
3719
 
5.4%
1606
 
2.3%
1250
 
1.8%
Other values (482) 33183
48.5%
Uppercase Letter
ValueCountFrequency (%)
B 91
21.2%
A 49
11.4%
S 35
 
8.1%
C 31
 
7.2%
E 22
 
5.1%
G 19
 
4.4%
L 18
 
4.2%
D 18
 
4.2%
N 17
 
4.0%
T 16
 
3.7%
Other values (15) 114
26.5%
Lowercase Letter
ValueCountFrequency (%)
e 19
20.0%
o 13
13.7%
n 10
10.5%
i 9
9.5%
a 8
8.4%
u 7
 
7.4%
r 7
 
7.4%
s 6
 
6.3%
q 4
 
4.2%
g 3
 
3.2%
Other values (5) 9
9.5%
Decimal Number
ValueCountFrequency (%)
1 4884
28.9%
2 2492
14.8%
3 1731
 
10.3%
0 1550
 
9.2%
4 1369
 
8.1%
5 1223
 
7.2%
6 1110
 
6.6%
7 916
 
5.4%
8 857
 
5.1%
9 750
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 3300
99.8%
@ 2
 
0.1%
? 2
 
0.1%
& 2
 
0.1%
. 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
19386
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3751
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3750
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 419
100.0%
Math Symbol
ValueCountFrequency (%)
~ 33
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68473
58.8%
Common 47528
40.8%
Latin 527
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4586
 
6.7%
4552
 
6.6%
4051
 
5.9%
4026
 
5.9%
3989
 
5.8%
3790
 
5.5%
3720
 
5.4%
3719
 
5.4%
1606
 
2.3%
1250
 
1.8%
Other values (483) 33184
48.5%
Latin
ValueCountFrequency (%)
B 91
17.3%
A 49
 
9.3%
S 35
 
6.6%
C 31
 
5.9%
E 22
 
4.2%
e 19
 
3.6%
G 19
 
3.6%
L 18
 
3.4%
D 18
 
3.4%
N 17
 
3.2%
Other values (32) 208
39.5%
Common
ValueCountFrequency (%)
19386
40.8%
1 4884
 
10.3%
) 3751
 
7.9%
( 3750
 
7.9%
, 3300
 
6.9%
2 2492
 
5.2%
3 1731
 
3.6%
0 1550
 
3.3%
4 1369
 
2.9%
5 1223
 
2.6%
Other values (10) 4092
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68472
58.8%
ASCII 48053
41.2%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19386
40.3%
1 4884
 
10.2%
) 3751
 
7.8%
( 3750
 
7.8%
, 3300
 
6.9%
2 2492
 
5.2%
3 1731
 
3.6%
0 1550
 
3.2%
4 1369
 
2.8%
5 1223
 
2.5%
Other values (50) 4617
 
9.6%
Hangul
ValueCountFrequency (%)
4586
 
6.7%
4552
 
6.6%
4051
 
5.9%
4026
 
5.9%
3989
 
5.8%
3790
 
5.5%
3720
 
5.4%
3719
 
5.4%
1606
 
2.3%
1250
 
1.8%
Other values (482) 33183
48.5%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1953
Distinct (%)55.6%
Missing1112
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean17411.763
Minimum1006
Maximum158839
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:26.236689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1006
5-th percentile1686.5
Q13925
median5558
Q37599
95-th percentile135926.95
Maximum158839
Range157833
Interquartile range (IQR)3674

Descriptive statistics

Standard deviation38217.504
Coefficient of variation (CV)2.1949244
Kurtosis6.3689242
Mean17411.763
Median Absolute Deviation (MAD)1848
Skewness2.8540131
Sum61115289
Variance1.4605776 × 109
MonotonicityNot monotonic
2024-05-18T12:20:26.756566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4528 76
 
1.6%
4529 36
 
0.8%
4536 21
 
0.5%
4563 18
 
0.4%
4527 16
 
0.3%
4535 14
 
0.3%
6018 13
 
0.3%
4532 13
 
0.3%
8776 12
 
0.3%
4049 11
 
0.2%
Other values (1943) 3280
71.0%
(Missing) 1112
 
24.1%
ValueCountFrequency (%)
1006 1
< 0.1%
1009 1
< 0.1%
1011 1
< 0.1%
1036 1
< 0.1%
1038 1
< 0.1%
1039 1
< 0.1%
1040 1
< 0.1%
1043 1
< 0.1%
1044 1
< 0.1%
1051 2
< 0.1%
ValueCountFrequency (%)
158839 1
< 0.1%
158093 1
< 0.1%
158077 1
< 0.1%
158074 2
< 0.1%
158072 1
< 0.1%
158054 1
< 0.1%
158053 1
< 0.1%
158051 2
< 0.1%
157924 1
< 0.1%
157879 1
< 0.1%
Distinct3636
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
2024-05-18T12:20:27.482548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length7.0646906
Min length2

Characters and Unicode

Total characters32653
Distinct characters672
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3127 ?
Unique (%)67.7%

Sample

1st row씨샵 가로수길 플래그쉽
2nd row안경상회 마포성산점
3rd row룩옵티컬 현대아울렛동대문점
4th row오렌즈 건대입구점
5th row으뜸플러스안경 목동점
ValueCountFrequency (%)
안경원 72
 
1.3%
안경 70
 
1.3%
오렌즈 62
 
1.1%
으뜸50안경 56
 
1.0%
렌즈미 30
 
0.5%
안경콘택트 25
 
0.5%
룩옵티컬 24
 
0.4%
안경박사 22
 
0.4%
으뜸플러스안경 22
 
0.4%
안경나라 19
 
0.3%
Other values (3643) 5095
92.7%
2024-05-18T12:20:28.560595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3883
 
11.9%
3860
 
11.8%
1303
 
4.0%
1054
 
3.2%
910
 
2.8%
878
 
2.7%
831
 
2.5%
745
 
2.3%
587
 
1.8%
467
 
1.4%
Other values (662) 18135
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29233
89.5%
Space Separator 878
 
2.7%
Uppercase Letter 709
 
2.2%
Decimal Number 536
 
1.6%
Close Punctuation 414
 
1.3%
Open Punctuation 414
 
1.3%
Lowercase Letter 384
 
1.2%
Other Punctuation 65
 
0.2%
Dash Punctuation 14
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3883
 
13.3%
3860
 
13.2%
1303
 
4.5%
1054
 
3.6%
910
 
3.1%
831
 
2.8%
745
 
2.5%
587
 
2.0%
467
 
1.6%
364
 
1.2%
Other values (586) 15229
52.1%
Uppercase Letter
ValueCountFrequency (%)
E 85
 
12.0%
O 79
 
11.1%
A 68
 
9.6%
S 53
 
7.5%
L 51
 
7.2%
C 40
 
5.6%
M 32
 
4.5%
T 31
 
4.4%
I 29
 
4.1%
N 25
 
3.5%
Other values (15) 216
30.5%
Lowercase Letter
ValueCountFrequency (%)
e 68
17.7%
o 57
14.8%
y 31
 
8.1%
n 27
 
7.0%
r 24
 
6.2%
a 22
 
5.7%
s 22
 
5.7%
i 18
 
4.7%
t 17
 
4.4%
d 16
 
4.2%
Other values (13) 82
21.4%
Decimal Number
ValueCountFrequency (%)
0 227
42.4%
1 117
21.8%
5 104
19.4%
2 41
 
7.6%
9 17
 
3.2%
3 10
 
1.9%
4 7
 
1.3%
7 6
 
1.1%
8 5
 
0.9%
6 2
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 36
55.4%
? 9
 
13.8%
, 8
 
12.3%
& 7
 
10.8%
1
 
1.5%
/ 1
 
1.5%
# 1
 
1.5%
1
 
1.5%
: 1
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 413
99.8%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 413
99.8%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
878
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Currency Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29233
89.5%
Common 2324
 
7.1%
Latin 1093
 
3.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3883
 
13.3%
3860
 
13.2%
1303
 
4.5%
1054
 
3.6%
910
 
3.1%
831
 
2.8%
745
 
2.5%
587
 
2.0%
467
 
1.6%
364
 
1.2%
Other values (585) 15229
52.1%
Latin
ValueCountFrequency (%)
E 85
 
7.8%
O 79
 
7.2%
A 68
 
6.2%
e 68
 
6.2%
o 57
 
5.2%
S 53
 
4.8%
L 51
 
4.7%
C 40
 
3.7%
M 32
 
2.9%
y 31
 
2.8%
Other values (38) 529
48.4%
Common
ValueCountFrequency (%)
878
37.8%
) 413
17.8%
( 413
17.8%
0 227
 
9.8%
1 117
 
5.0%
5 104
 
4.5%
2 41
 
1.8%
. 36
 
1.5%
9 17
 
0.7%
- 14
 
0.6%
Other values (17) 64
 
2.8%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29230
89.5%
ASCII 3414
 
10.5%
None 6
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3883
 
13.3%
3860
 
13.2%
1303
 
4.5%
1054
 
3.6%
910
 
3.1%
831
 
2.8%
745
 
2.5%
587
 
2.0%
467
 
1.6%
364
 
1.2%
Other values (584) 15226
52.1%
ASCII
ValueCountFrequency (%)
878
25.7%
) 413
12.1%
( 413
12.1%
0 227
 
6.6%
1 117
 
3.4%
5 104
 
3.0%
E 85
 
2.5%
O 79
 
2.3%
A 68
 
2.0%
e 68
 
2.0%
Other values (62) 962
28.2%
None
ValueCountFrequency (%)
3
50.0%
1
 
16.7%
1
 
16.7%
1
 
16.7%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%
Distinct4204
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
Minimum2008-12-06 09:08:23
Maximum2024-05-16 16:44:49
2024-05-18T12:20:28.967428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:20:29.435598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
I
2933 
U
1689 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2933
63.5%
U 1689
36.5%

Length

2024-05-18T12:20:29.753856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:30.000931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2933
63.5%
u 1689
36.5%
Distinct1036
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-18T12:20:30.326447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T12:20:30.762124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4622
Missing (%)100.0%
Memory size40.8 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3061
Distinct (%)82.2%
Missing899
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean198998.95
Minimum182028.31
Maximum215426.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:31.390907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182028.31
5-th percentile186930.09
Q1193090.78
median199050.53
Q3204520.31
95-th percentile210889.62
Maximum215426.03
Range33397.722
Interquartile range (IQR)11429.531

Descriptive statistics

Standard deviation7182.0193
Coefficient of variation (CV)0.036090739
Kurtosis-0.81197733
Mean198998.95
Median Absolute Deviation (MAD)5772.8281
Skewness-0.090023442
Sum7.408731 × 108
Variance51581402
MonotonicityNot monotonic
2024-05-18T12:20:31.779352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197864.564761519 22
 
0.5%
197902.146082898 15
 
0.3%
198315.532747026 12
 
0.3%
198354.121882082 12
 
0.3%
200703.625559248 11
 
0.2%
208589.363343145 11
 
0.2%
190232.524534335 9
 
0.2%
200664.582936542 9
 
0.2%
208937.760652081 8
 
0.2%
182524.823835629 7
 
0.2%
Other values (3051) 3607
78.0%
(Missing) 899
 
19.5%
ValueCountFrequency (%)
182028.306204 1
 
< 0.1%
182524.823835629 7
0.2%
182876.367858149 2
 
< 0.1%
182940.995178251 1
 
< 0.1%
183030.868557234 1
 
< 0.1%
183129.098346591 1
 
< 0.1%
183130.915788053 1
 
< 0.1%
183166.343309141 1
 
< 0.1%
183211.887600153 1
 
< 0.1%
183236.659082702 1
 
< 0.1%
ValueCountFrequency (%)
215426.028109 1
< 0.1%
215400.574803 1
< 0.1%
215384.844269 1
< 0.1%
215361.163713829 1
< 0.1%
215289.815449411 1
< 0.1%
215214.453823181 1
< 0.1%
215194.400879055 1
< 0.1%
215101.359476309 1
< 0.1%
214987.563823481 1
< 0.1%
214973.882389563 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3059
Distinct (%)82.2%
Missing899
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean449229.09
Minimum410746.74
Maximum464638.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:32.207368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum410746.74
5-th percentile441953.8
Q1444905.46
median449188.97
Q3452092.35
95-th percentile459608.54
Maximum464638.13
Range53891.39
Interquartile range (IQR)7186.8919

Descriptive statistics

Standard deviation5400.3746
Coefficient of variation (CV)0.012021427
Kurtosis1.0612334
Mean449229.09
Median Absolute Deviation (MAD)3737.3854
Skewness0.27897798
Sum1.6724799 × 109
Variance29164046
MonotonicityNot monotonic
2024-05-18T12:20:32.671275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450776.970697936 22
 
0.5%
450720.711316548 15
 
0.3%
451248.141599825 12
 
0.3%
451309.736293852 12
 
0.3%
445455.90405262 11
 
0.2%
451836.458256618 11
 
0.2%
451781.8683954 9
 
0.2%
444978.682746138 9
 
0.2%
442873.588039887 8
 
0.2%
445963.384875409 7
 
0.2%
Other values (3049) 3607
78.0%
(Missing) 899
 
19.5%
ValueCountFrequency (%)
410746.743609205 1
< 0.1%
412876.819130805 1
< 0.1%
421245.44916551 1
< 0.1%
437689.38449215 1
< 0.1%
437777.824339474 1
< 0.1%
437914.06299827 1
< 0.1%
438365.613175801 1
< 0.1%
438518.811960006 1
< 0.1%
438520.182013694 1
< 0.1%
438636.970338125 1
< 0.1%
ValueCountFrequency (%)
464638.133327247 1
< 0.1%
464625.423162623 1
< 0.1%
464474.910004698 1
< 0.1%
464174.850719823 1
< 0.1%
464092.187505065 1
< 0.1%
464080.593904719 1
< 0.1%
463911.244365486 1
< 0.1%
463898.141439795 1
< 0.1%
463871.943605684 1
< 0.1%
463857.044652327 1
< 0.1%

시력표수
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
1
2759 
0
956 
<NA>
812 
2
 
86
3
 
8

Length

Max length4
Median length1
Mean length1.5270446
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 2759
59.7%
0 956
 
20.7%
<NA> 812
 
17.6%
2 86
 
1.9%
3 8
 
0.2%
5 1
 
< 0.1%

Length

2024-05-18T12:20:33.313099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:33.627539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2759
59.7%
0 956
 
20.7%
na 812
 
17.6%
2 86
 
1.9%
3 8
 
0.2%
5 1
 
< 0.1%

표본렌즈수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.3%
Missing886
Missing (%)19.2%
Infinite0
Infinite (%)0.0%
Mean1.0711991
Minimum0
Maximum1000
Zeros1023
Zeros (%)22.1%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:33.949087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1000
Range1000
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.441785
Coefficient of variation (CV)15.348952
Kurtosis3651.1882
Mean1.0711991
Median Absolute Deviation (MAD)0
Skewness60.134404
Sum4002
Variance270.33228
MonotonicityNot monotonic
2024-05-18T12:20:34.335038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 2608
56.4%
0 1023
 
22.1%
2 77
 
1.7%
3 15
 
0.3%
10 6
 
0.1%
5 2
 
< 0.1%
15 1
 
< 0.1%
100 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 886
 
19.2%
ValueCountFrequency (%)
0 1023
 
22.1%
1 2608
56.4%
2 77
 
1.7%
3 15
 
0.3%
4 1
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
10 6
 
0.1%
15 1
 
< 0.1%
100 1
 
< 0.1%
ValueCountFrequency (%)
1000 1
 
< 0.1%
100 1
 
< 0.1%
15 1
 
< 0.1%
10 6
 
0.1%
6 1
 
< 0.1%
5 2
 
< 0.1%
4 1
 
< 0.1%
3 15
 
0.3%
2 77
 
1.7%
1 2608
56.4%

측정의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.2%
Missing885
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean0.76264383
Minimum0
Maximum8
Zeros1031
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:34.672029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.53126679
Coefficient of variation (CV)0.69661193
Kurtosis11.081171
Mean0.76264383
Median Absolute Deviation (MAD)0
Skewness0.76767502
Sum2850
Variance0.2822444
MonotonicityNot monotonic
2024-05-18T12:20:35.096597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2587
56.0%
0 1031
 
22.3%
2 103
 
2.2%
3 12
 
0.3%
4 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 885
 
19.1%
ValueCountFrequency (%)
0 1031
 
22.3%
1 2587
56.0%
2 103
 
2.2%
3 12
 
0.3%
4 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
< 0.1%
3 12
 
0.3%
2 103
 
2.2%
1 2587
56.0%
0 1031
 
22.3%

동공거리측정기수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.3%
Missing824
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean0.83070037
Minimum0
Maximum20
Zeros962
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:35.544040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.80819811
Coefficient of variation (CV)0.9729117
Kurtosis187.31262
Mean0.83070037
Median Absolute Deviation (MAD)0
Skewness9.4095997
Sum3155
Variance0.65318418
MonotonicityNot monotonic
2024-05-18T12:20:35.942029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 2682
58.0%
0 962
 
20.8%
2 94
 
2.0%
3 32
 
0.7%
5 13
 
0.3%
4 6
 
0.1%
10 4
 
0.1%
7 2
 
< 0.1%
20 2
 
< 0.1%
6 1
 
< 0.1%
(Missing) 824
 
17.8%
ValueCountFrequency (%)
0 962
 
20.8%
1 2682
58.0%
2 94
 
2.0%
3 32
 
0.7%
4 6
 
0.1%
5 13
 
0.3%
6 1
 
< 0.1%
7 2
 
< 0.1%
10 4
 
0.1%
20 2
 
< 0.1%
ValueCountFrequency (%)
20 2
 
< 0.1%
10 4
 
0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
5 13
 
0.3%
4 6
 
0.1%
3 32
 
0.7%
2 94
 
2.0%
1 2682
58.0%
0 962
 
20.8%

정점굴절계기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.2%
Missing816
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean0.88439306
Minimum0
Maximum6
Zeros957
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:36.310263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.66627664
Coefficient of variation (CV)0.75337162
Kurtosis4.1667141
Mean0.88439306
Median Absolute Deviation (MAD)0
Skewness1.0523352
Sum3366
Variance0.44392456
MonotonicityNot monotonic
2024-05-18T12:20:36.620383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2434
52.7%
0 957
 
20.7%
2 337
 
7.3%
3 60
 
1.3%
4 13
 
0.3%
5 4
 
0.1%
6 1
 
< 0.1%
(Missing) 816
 
17.7%
ValueCountFrequency (%)
0 957
 
20.7%
1 2434
52.7%
2 337
 
7.3%
3 60
 
1.3%
4 13
 
0.3%
5 4
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 4
 
0.1%
4 13
 
0.3%
3 60
 
1.3%
2 337
 
7.3%
1 2434
52.7%
0 957
 
20.7%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size36.2 KiB
1
2586 
0
1054 
<NA>
911 
2
 
71

Length

Max length4
Median length1
Mean length1.5913025
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2586
55.9%
0 1054
22.8%
<NA> 911
 
19.7%
2 71
 
1.5%

Length

2024-05-18T12:20:37.065372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T12:20:37.398301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2586
55.9%
0 1054
22.8%
na 911
 
19.7%
2 71
 
1.5%

렌즈절단기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.2%
Missing914
Missing (%)19.8%
Infinite0
Infinite (%)0.0%
Mean0.73166127
Minimum0
Maximum11
Zeros1054
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:37.723008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5046327
Coefficient of variation (CV)0.68970809
Kurtosis45.693751
Mean0.73166127
Median Absolute Deviation (MAD)0
Skewness1.7990995
Sum2713
Variance0.25465416
MonotonicityNot monotonic
2024-05-18T12:20:38.047835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 2607
56.4%
0 1054
22.8%
2 44
 
1.0%
4 1
 
< 0.1%
3 1
 
< 0.1%
11 1
 
< 0.1%
(Missing) 914
 
19.8%
ValueCountFrequency (%)
0 1054
22.8%
1 2607
56.4%
2 44
 
1.0%
3 1
 
< 0.1%
4 1
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
2 44
 
1.0%
1 2607
56.4%
0 1054
22.8%

가열기수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.2%
Missing912
Missing (%)19.7%
Infinite0
Infinite (%)0.0%
Mean0.85175202
Minimum0
Maximum11
Zeros1051
Zeros (%)22.7%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:38.481479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.75146368
Coefficient of variation (CV)0.88225641
Kurtosis45.530319
Mean0.85175202
Median Absolute Deviation (MAD)0
Skewness3.8279335
Sum3160
Variance0.56469766
MonotonicityNot monotonic
2024-05-18T12:20:38.843957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2274
49.2%
0 1051
22.7%
2 319
 
6.9%
3 54
 
1.2%
4 6
 
0.1%
11 5
 
0.1%
7 1
 
< 0.1%
(Missing) 912
19.7%
ValueCountFrequency (%)
0 1051
22.7%
1 2274
49.2%
2 319
 
6.9%
3 54
 
1.2%
4 6
 
0.1%
7 1
 
< 0.1%
11 5
 
0.1%
ValueCountFrequency (%)
11 5
 
0.1%
7 1
 
< 0.1%
4 6
 
0.1%
3 54
 
1.2%
2 319
 
6.9%
1 2274
49.2%
0 1051
22.7%

안경세척기수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.2%
Missing904
Missing (%)19.6%
Infinite0
Infinite (%)0.0%
Mean0.85207101
Minimum0
Maximum7
Zeros1047
Zeros (%)22.7%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:39.194898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.67041702
Coefficient of variation (CV)0.78680887
Kurtosis3.4203654
Mean0.85207101
Median Absolute Deviation (MAD)0
Skewness0.89996728
Sum3168
Variance0.44945899
MonotonicityNot monotonic
2024-05-18T12:20:39.665023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 2258
48.9%
0 1047
22.7%
2 343
 
7.4%
3 59
 
1.3%
4 10
 
0.2%
7 1
 
< 0.1%
(Missing) 904
19.6%
ValueCountFrequency (%)
0 1047
22.7%
1 2258
48.9%
2 343
 
7.4%
3 59
 
1.3%
4 10
 
0.2%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
4 10
 
0.2%
3 59
 
1.3%
2 343
 
7.4%
1 2258
48.9%
0 1047
22.7%

총면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1270
Distinct (%)51.9%
Missing2173
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean48.177383
Minimum0
Maximum6032
Zeros463
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size40.8 KiB
2024-05-18T12:20:40.242695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q117.02
median35.4
Q360.6
95-th percentile126.364
Maximum6032
Range6032
Interquartile range (IQR)43.58

Descriptive statistics

Standard deviation131.98011
Coefficient of variation (CV)2.7394621
Kurtosis1728.7805
Mean48.177383
Median Absolute Deviation (MAD)21.6
Skewness38.413228
Sum117986.41
Variance17418.75
MonotonicityNot monotonic
2024-05-18T12:20:40.736404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 463
 
10.0%
1.0 29
 
0.6%
33.0 28
 
0.6%
66.0 23
 
0.5%
49.5 20
 
0.4%
30.0 16
 
0.3%
25.0 13
 
0.3%
50.0 13
 
0.3%
45.0 12
 
0.3%
26.4 12
 
0.3%
Other values (1260) 1820
39.4%
(Missing) 2173
47.0%
ValueCountFrequency (%)
0.0 463
10.0%
1.0 29
 
0.6%
2.0 1
 
< 0.1%
3.6 1
 
< 0.1%
5.6 1
 
< 0.1%
5.72 1
 
< 0.1%
5.9 1
 
< 0.1%
6.0 1
 
< 0.1%
6.25 1
 
< 0.1%
6.6 3
 
0.1%
ValueCountFrequency (%)
6032.0 1
< 0.1%
952.51 1
< 0.1%
663.01 1
< 0.1%
552.99 1
< 0.1%
493.0 1
< 0.1%
398.6 1
< 0.1%
396.0 1
< 0.1%
366.67 1
< 0.1%
355.0 1
< 0.1%
354.37 1
< 0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
03220000PHMB2202232200330822000042022-09-05<NA>1영업/정상13영업중<NA><NA><NA><NA>07077125546<NA><NA>서울특별시 강남구 신사동 532-2서울특별시 강남구 압구정로10길 11, 1층 (신사동)6028씨샵 가로수길 플래그쉽2023-03-03 17:21:58U2022-12-03 00:05:00.0<NA>201874.279735446735.053982<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13130000PHMB2199031300330822000021990-10-31<NA>1영업/정상13영업중<NA><NA><NA><NA>02-308-6662<NA>121-250서울특별시 마포구 성산2동200-364서울특별시 마포구 월드컵북로 188 (성산동)3946안경상회 마포성산점2023-03-03 10:11:43U2022-12-03 00:05:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23010000PHMB2201730100330822000152017-09-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 중구 장충단로13길 20, 현대시티타워 지하1층 (을지로6가)4563룩옵티컬 현대아울렛동대문점2023-03-07 15:16:21U2022-12-03 00:09:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33040000PHMB2201830400330822000052018-11-29<NA>1영업/정상13영업중<NA><NA><NA><NA>02-499-9333<NA><NA>서울특별시 광진구 화양동 6-1서울특별시 광진구 능동로 103, 1층 2-2호 (화양동)5017오렌즈 건대입구점2023-07-11 10:33:28U2022-12-06 23:03:00.0<NA>206163.281974448682.578828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43140000PHMB2202031400330822000052020-06-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2651-1002<NA><NA>서울특별시 양천구 신정동 323번지 9호 이스타빌서울특별시 양천구 목동서로 377, 이스타빌 A동 2층 209호 (신정동)8093으뜸플러스안경 목동점2023-03-08 11:26:05U2022-12-02 23:00:00.0<NA>187734.983112446030.714521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53110000PHMB2200631100320822000042006-11-22<NA>1영업/정상13영업중<NA><NA><NA><NA>02-387-8854<NA><NA><NA>서울특별시 은평구 갈현로 8, 신창빌딩 101호 (신사동)3423트랜디카안경2023-03-08 16:06:43U2022-12-02 23:00:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63110000PHMB2202331100320822000042000-09-26<NA>1영업/정상13영업중<NA><NA><NA><NA>02-388-8968<NA><NA>서울특별시 은평구 신사동 7-4서울특별시 은평구 갈현로 44, 영암빌딩 (신사동)3422아이엔비안경원2023-03-08 16:03:44U2022-12-02 23:00:00.0<NA>192026.412014455494.559013<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73180000PHMB2201331800340822000042013-12-03<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2634-5030<NA><NA>서울특별시 영등포구 양평동4가 101-3서울특별시 영등포구 양평로21길 1, 1층 (양평동4가)7208아이앤코안경원2023-03-09 09:40:15U2022-12-02 23:01:00.0<NA>190558.055924448366.233224<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83010000PHMB2200930100330822000042009-03-13<NA>3폐업3폐업2023-03-09<NA><NA><NA>755-8225<NA>100-805서울특별시 중구 남창동 62번지 1호 1층서울특별시 중구 남대문시장4길 46 (남창동,1층)<NA>늘푸른안경원2023-03-09 13:31:17U2022-12-02 23:01:00.0<NA>197907.587678450655.841466<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93030000PHMB2201430300330822000032014-09-22<NA>1영업/정상13영업중<NA><NA><NA><NA>02-466-1116<NA>133-823서울특별시 성동구 성수동1가 656번지 387호서울특별시 성동구 상원길 51, 1층 (성수동1가)4789레이안경2023-03-10 10:43:24U2022-12-02 23:02:00.0<NA>204176.101885449601.234752<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)시력표수표본렌즈수측정의자수동공거리측정기수정점굴절계기수조제용연마기수렌즈절단기수가열기수안경세척기수총면적
46123110000PHMB22022311003208220000320220530<NA>1영업/정상13영업중<NA><NA><NA><NA>02-352-4845<NA><NA>서울특별시 은평구 역촌동 41-17 캐시아 103호서울특별시 은평구 진흥로1길 16, 1층 103호 (역촌동, 캐시아)3408룩스토어역촌점2022-05-31 17:57:42I2021-12-06 00:02:00.0<NA>192762.169651455492.75957<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46133160000PHMB2200031600340822000032000-10-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2068-3356<NA><NA>서울특별시 구로구 신도림동 644번지 신도림2차동아아파트서울특별시 구로구 경인로 643, 205동 101호 (신도림동, 신도림2차동아아파트)8208으뜸50 신도림점2023-09-21 14:47:44U2022-12-08 22:03:00.0<NA>189841.350197445153.610163<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46143220000PHMB22006322003308220000420060824<NA>3폐업3폐업20220520<NA><NA><NA>6242-7471<NA><NA>서울특별시 강남구 수서동 713번지 수서현대벤쳐빌 지하1층서울특별시 강남구 밤고개로1길 10, 지하1층 (수서동, 수서현대벤쳐빌)6349예스안경원2022-06-02 13:25:52U2021-12-06 00:04:00.0<NA>208937.760652442873.58804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46153110000PHMB22001311003208220000120010206<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3157-0001<NA>122847서울특별시 은평구 불광동 631번지 1호 106호서울특별시 은평구 불광로 90, 106호 (불광동)3364불광그랑프리안경2022-06-02 16:00:15U2021-12-06 00:04:00.0<NA>194002.701727456937.54251<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46163130000PHMB22022313003308220000320220520<NA>1영업/정상13영업중<NA><NA><NA><NA>070-8648-1718<NA><NA>서울특별시 마포구 상수동 311-8서울특별시 마포구 독막로15길 13-5, 지층 (상수동)4049안경진정성홍대점2022-06-23 14:54:42U2021-12-05 22:05:00.0<NA>193030.141867449565.338478<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46173060000PHMB22019306003408220000320190625<NA>1영업/정상13영업중<NA><NA><NA><NA>02-434-1008<NA><NA>서울특별시 중랑구 면목동 1092-21서울특별시 중랑구 용마산로 301, 1층 102호 (면목동)2250탑클래스 면목동점2022-06-07 10:17:14U2021-12-06 00:09:00.0<NA>208028.4563453008.512652<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46183130000PHMB22017313003308220001020170925<NA>3폐업3폐업20220529<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 어울마당로 36, RAWROW CENTER 지1층 (상수동)4049알디오랩 홍대점2022-06-07 10:44:57U2021-12-06 00:09:00.0<NA>192902.63684449559.001671<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46193230000PHMB22022323003408220000220220518<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 법원로 128, 문정에스케이브이원지엘메트로시티 1층 122호 (문정동)5854으뜸50안경 문정역점2022-07-15 14:47:10U2021-12-06 23:07:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46203190000PHMB22006319003308220000520061228<NA>3폐업3폐업20221014<NA><NA><NA><NA><NA><NA>서울특별시 동작구 신대방2동 708 (18,19,20호)서울특별시 동작구 보라매로3길 29 (신대방동)7071공일공 보라매 안경.콘택트2022-10-17 12:11:00U2021-10-30 23:09:00.0<NA>193279.599095443230.418234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46213220000PHMB22022322003308220000120220602<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 수서동 713 수서현대벤쳐빌서울특별시 강남구 밤고개로1길 10, 수서현대벤쳐빌 (수서동)6349예스안경2023-01-12 14:16:30U2022-11-30 23:04:00.0<NA>208937.760652442873.58804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>