Overview

Dataset statistics

Number of variables56
Number of observations1766
Missing cells49314
Missing cells (%)49.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory843.5 KiB
Average record size in memory489.1 B

Variable types

Numeric5
Text9
Categorical15
Unsupported25
DateTime2

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),문화체육업종명,문화사업자구분명,총층수,주변환경명,제작취급품목내용,시설면적,지상층수,지하층수,건물용도명,통로너비,조명시설조도,노래방실수,청소년실수,비상계단여부,비상구여부,자동환기여부,청소년실여부,특수조명여부,방음시설여부,비디오재생기명,조명시설유무,음향시설여부,편의시설여부,소방시설여부,총게임기수,기존게임업외업종명,제공게임물명,공연장형태구분명,품목명,최초등록시점,지역구분명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16052/S/1/datasetView.do

Alerts

인허가취소일자 is highly imbalanced (99.0%)Imbalance
영업상태코드 is highly imbalanced (53.8%)Imbalance
영업상태명 is highly imbalanced (53.8%)Imbalance
상세영업상태명 is highly imbalanced (64.1%)Imbalance
폐업일자 has 1409 (79.8%) missing valuesMissing
휴업시작일자 has 1766 (100.0%) missing valuesMissing
휴업종료일자 has 1766 (100.0%) missing valuesMissing
재개업일자 has 1766 (100.0%) missing valuesMissing
전화번호 has 1115 (63.1%) missing valuesMissing
소재지면적 has 1766 (100.0%) missing valuesMissing
소재지우편번호 has 1683 (95.3%) missing valuesMissing
도로명주소 has 30 (1.7%) missing valuesMissing
도로명우편번호 has 361 (20.4%) missing valuesMissing
업태구분명 has 1766 (100.0%) missing valuesMissing
좌표정보(X) has 24 (1.4%) missing valuesMissing
좌표정보(Y) has 24 (1.4%) missing valuesMissing
문화사업자구분명 has 1766 (100.0%) missing valuesMissing
주변환경명 has 1766 (100.0%) missing valuesMissing
제작취급품목내용 has 1766 (100.0%) missing valuesMissing
건물용도명 has 1766 (100.0%) missing valuesMissing
비상계단여부 has 1766 (100.0%) missing valuesMissing
비상구여부 has 1766 (100.0%) missing valuesMissing
자동환기여부 has 1766 (100.0%) missing valuesMissing
청소년실여부 has 1766 (100.0%) missing valuesMissing
특수조명여부 has 1766 (100.0%) missing valuesMissing
방음시설여부 has 1766 (100.0%) missing valuesMissing
비디오재생기명 has 1766 (100.0%) missing valuesMissing
조명시설유무 has 1766 (100.0%) missing valuesMissing
음향시설여부 has 1766 (100.0%) missing valuesMissing
편의시설여부 has 1766 (100.0%) missing valuesMissing
소방시설여부 has 1766 (100.0%) missing valuesMissing
기존게임업외업종명 has 1766 (100.0%) missing valuesMissing
제공게임물명 has 1766 (100.0%) missing valuesMissing
공연장형태구분명 has 1766 (100.0%) missing valuesMissing
품목명 has 1766 (100.0%) missing valuesMissing
최초등록시점 has 518 (29.3%) missing valuesMissing
지역구분명 has 1766 (100.0%) missing valuesMissing
최초등록시점 is highly skewed (γ1 = -24.74391303)Skewed
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
문화사업자구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주변환경명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물용도명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비상계단여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비상구여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자동환기여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
청소년실여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
특수조명여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방음시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
비디오재생기명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조명시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
음향시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
편의시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소방시설여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기존게임업외업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제공게임물명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공연장형태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
품목명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지역구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:09:27.949885
Analysis finished2024-05-11 06:09:30.216069
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3147106.5
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2024-05-11T15:09:30.311809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13080000
median3180000
Q33220000
95-th percentile3220000
Maximum3240000
Range240000
Interquartile range (IQR)140000

Descriptive statistics

Standard deviation82194.801
Coefficient of variation (CV)0.026117579
Kurtosis-1.0911187
Mean3147106.5
Median Absolute Deviation (MAD)40000
Skewness-0.68070592
Sum5.55779 × 109
Variance6.7559853 × 109
MonotonicityNot monotonic
2024-05-11T15:09:30.493400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 569
32.2%
3130000 206
 
11.7%
3210000 165
 
9.3%
3010000 138
 
7.8%
3000000 94
 
5.3%
3020000 85
 
4.8%
3180000 69
 
3.9%
3230000 60
 
3.4%
3030000 53
 
3.0%
3120000 38
 
2.2%
Other values (15) 289
16.4%
ValueCountFrequency (%)
3000000 94
5.3%
3010000 138
7.8%
3020000 85
4.8%
3030000 53
 
3.0%
3040000 25
 
1.4%
3050000 9
 
0.5%
3060000 8
 
0.5%
3070000 28
 
1.6%
3080000 9
 
0.5%
3090000 7
 
0.4%
ValueCountFrequency (%)
3240000 14
 
0.8%
3230000 60
 
3.4%
3220000 569
32.2%
3210000 165
 
9.3%
3200000 12
 
0.7%
3190000 25
 
1.4%
3180000 69
 
3.9%
3170000 34
 
1.9%
3160000 25
 
1.4%
3150000 37
 
2.1%
Distinct655
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
2024-05-11T15:09:30.794122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters35320
Distinct characters13
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

Unique390 ?
Unique (%)22.1%

Sample

1st rowCDFF5211032023000003
2nd rowCDFF5211032022000005
3rd rowCDFF5211032014000034
4th rowCDFF5211032023000002
5th rowCDFF5211032022000002
ValueCountFrequency (%)
cdff5211032022000001 21
 
1.2%
cdff5211032023000001 21
 
1.2%
cdff5211032019000001 21
 
1.2%
cdff5211032021000001 20
 
1.1%
cdff5211032020000001 20
 
1.1%
cdff5211032018000001 19
 
1.1%
cdff5211032022000002 17
 
1.0%
cdff5211032024000001 17
 
1.0%
cdff5211032012000001 16
 
0.9%
cdff5211032020000002 16
 
0.9%
Other values (645) 1578
89.4%
2024-05-11T15:09:31.303049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12289
34.8%
1 5382
15.2%
2 4697
 
13.3%
F 3532
 
10.0%
3 2327
 
6.6%
5 2024
 
5.7%
C 1766
 
5.0%
D 1766
 
5.0%
9 387
 
1.1%
4 364
 
1.0%
Other values (3) 786
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28256
80.0%
Uppercase Letter 7064
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12289
43.5%
1 5382
19.0%
2 4697
 
16.6%
3 2327
 
8.2%
5 2024
 
7.2%
9 387
 
1.4%
4 364
 
1.3%
8 280
 
1.0%
7 265
 
0.9%
6 241
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
F 3532
50.0%
C 1766
25.0%
D 1766
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28256
80.0%
Latin 7064
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12289
43.5%
1 5382
19.0%
2 4697
 
16.6%
3 2327
 
8.2%
5 2024
 
7.2%
9 387
 
1.4%
4 364
 
1.3%
8 280
 
1.0%
7 265
 
0.9%
6 241
 
0.9%
Latin
ValueCountFrequency (%)
F 3532
50.0%
C 1766
25.0%
D 1766
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12289
34.8%
1 5382
15.2%
2 4697
 
13.3%
F 3532
 
10.0%
3 2327
 
6.6%
5 2024
 
5.7%
C 1766
 
5.0%
D 1766
 
5.0%
9 387
 
1.1%
4 364
 
1.0%
Other values (3) 786
 
2.2%
Distinct1408
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
2024-05-11T15:09:31.806286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3884485
Min length8

Characters and Unicode

Total characters14814
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

Unique1118 ?
Unique (%)63.3%

Sample

1st row2023-03-17
2nd row2021-07-21
3rd row2014-09-23
4th row2018-08-27
5th row2023-03-13
ValueCountFrequency (%)
2024-02-27 5
 
0.3%
2018-08-07 4
 
0.2%
20091217 4
 
0.2%
20090610 4
 
0.2%
20080122 4
 
0.2%
20090423 4
 
0.2%
20090211 4
 
0.2%
2016-10-17 4
 
0.2%
20090910 4
 
0.2%
2023-03-27 4
 
0.2%
Other values (1398) 1725
97.7%
2024-05-11T15:09:32.649021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4405
29.7%
2 3415
23.1%
1 2669
18.0%
- 686
 
4.6%
3 659
 
4.4%
9 612
 
4.1%
4 514
 
3.5%
7 498
 
3.4%
8 484
 
3.3%
6 440
 
3.0%
Other values (2) 432
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14126
95.4%
Dash Punctuation 686
 
4.6%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4405
31.2%
2 3415
24.2%
1 2669
18.9%
3 659
 
4.7%
9 612
 
4.3%
4 514
 
3.6%
7 498
 
3.5%
8 484
 
3.4%
6 440
 
3.1%
5 430
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 686
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14814
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4405
29.7%
2 3415
23.1%
1 2669
18.0%
- 686
 
4.6%
3 659
 
4.4%
9 612
 
4.1%
4 514
 
3.5%
7 498
 
3.4%
8 484
 
3.3%
6 440
 
3.0%
Other values (2) 432
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4405
29.7%
2 3415
23.1%
1 2669
18.0%
- 686
 
4.6%
3 659
 
4.4%
9 612
 
4.1%
4 514
 
3.5%
7 498
 
3.4%
8 484
 
3.3%
6 440
 
3.0%
Other values (2) 432
 
2.9%

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1763 
20230113
 
1
20141230
 
1
20190119
 
1

Length

Max length8
Median length4
Mean length4.006795
Min length4

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1763
99.8%
20230113 1
 
0.1%
20141230 1
 
0.1%
20190119 1
 
0.1%

Length

2024-05-11T15:09:32.896870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:33.084120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1763
99.8%
20230113 1
 
0.1%
20141230 1
 
0.1%
20190119 1
 
0.1%

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
1
1399 
3
270 
5
 
93
4
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row5
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1399
79.2%
3 270
 
15.3%
5 93
 
5.3%
4 4
 
0.2%

Length

2024-05-11T15:09:33.270632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:33.462645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1399
79.2%
3 270
 
15.3%
5 93
 
5.3%
4 4
 
0.2%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
영업/정상
1399 
폐업
270 
제외/삭제/전출
 
93
취소/말소/만료/정지/중지
 
4

Length

Max length14
Median length5
Mean length4.7197055
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row제외/삭제/전출
3rd row폐업
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 1399
79.2%
폐업 270
 
15.3%
제외/삭제/전출 93
 
5.3%
취소/말소/만료/정지/중지 4
 
0.2%

Length

2024-05-11T15:09:33.694764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:33.915298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 1399
79.2%
폐업 270
 
15.3%
제외/삭제/전출 93
 
5.3%
취소/말소/만료/정지/중지 4
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.620612
Minimum3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2024-05-11T15:09:34.083509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q113
median13
Q313
95-th percentile15
Maximum35
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.8041136
Coefficient of variation (CV)0.32735916
Kurtosis3.2199664
Mean11.620612
Median Absolute Deviation (MAD)0
Skewness-1.3263429
Sum20522
Variance14.47128
MonotonicityNot monotonic
2024-05-11T15:09:34.283653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 1399
79.2%
3 270
 
15.3%
15 93
 
5.3%
32 2
 
0.1%
35 1
 
0.1%
31 1
 
0.1%
ValueCountFrequency (%)
3 270
 
15.3%
13 1399
79.2%
15 93
 
5.3%
31 1
 
0.1%
32 2
 
0.1%
35 1
 
0.1%
ValueCountFrequency (%)
35 1
 
0.1%
32 2
 
0.1%
31 1
 
0.1%
15 93
 
5.3%
13 1399
79.2%
3 270
 
15.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
영업중
1399 
폐업
270 
전출
 
93
신고취소
 
2
직권말소
 
1

Length

Max length4
Median length3
Mean length2.7967157
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 1399
79.2%
폐업 270
 
15.3%
전출 93
 
5.3%
신고취소 2
 
0.1%
직권말소 1
 
0.1%
등록취소 1
 
0.1%

Length

2024-05-11T15:09:34.615186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:34.885335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 1399
79.2%
폐업 270
 
15.3%
전출 93
 
5.3%
신고취소 2
 
0.1%
직권말소 1
 
0.1%
등록취소 1
 
0.1%

폐업일자
Text

MISSING 

Distinct316
Distinct (%)88.5%
Missing1409
Missing (%)79.8%
Memory size13.9 KiB
2024-05-11T15:09:35.379689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4985994
Min length8

Characters and Unicode

Total characters3034
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

Unique279 ?
Unique (%)78.2%

Sample

1st row2023-03-08
2nd row2023-03-07
3rd row2024-02-23
4th row2023-03-14
5th row2023-03-10
ValueCountFrequency (%)
20211231 4
 
1.1%
20191230 3
 
0.8%
20161231 3
 
0.8%
20221207 2
 
0.6%
20220401 2
 
0.6%
20221228 2
 
0.6%
20220407 2
 
0.6%
20220421 2
 
0.6%
20221006 2
 
0.6%
20200205 2
 
0.6%
Other values (306) 333
93.3%
2024-05-11T15:09:36.091590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 863
28.4%
0 772
25.4%
1 525
17.3%
3 194
 
6.4%
- 178
 
5.9%
4 117
 
3.9%
6 89
 
2.9%
7 83
 
2.7%
9 79
 
2.6%
5 70
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2856
94.1%
Dash Punctuation 178
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 863
30.2%
0 772
27.0%
1 525
18.4%
3 194
 
6.8%
4 117
 
4.1%
6 89
 
3.1%
7 83
 
2.9%
9 79
 
2.8%
5 70
 
2.5%
8 64
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3034
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 863
28.4%
0 772
25.4%
1 525
17.3%
3 194
 
6.4%
- 178
 
5.9%
4 117
 
3.9%
6 89
 
2.9%
7 83
 
2.7%
9 79
 
2.6%
5 70
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3034
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 863
28.4%
0 772
25.4%
1 525
17.3%
3 194
 
6.4%
- 178
 
5.9%
4 117
 
3.9%
6 89
 
2.9%
7 83
 
2.7%
9 79
 
2.6%
5 70
 
2.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

전화번호
Text

MISSING 

Distinct609
Distinct (%)93.5%
Missing1115
Missing (%)63.1%
Memory size13.9 KiB
2024-05-11T15:09:36.502884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length10.807988
Min length7

Characters and Unicode

Total characters7036
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)88.2%

Sample

1st row02-2272-2945
2nd row02-511-0821
3rd row02-2027-2300
4th row02-6013-8074
5th row070-7500-8671
ValueCountFrequency (%)
02-3490-9300 4
 
0.6%
070-8670-2618 3
 
0.5%
02-566-7901 3
 
0.5%
02-515-9234 3
 
0.5%
02-338-1007 3
 
0.5%
02-324-0469 3
 
0.5%
02-3445-1393 2
 
0.3%
02-540-2026 2
 
0.3%
744-4248 2
 
0.3%
02-564-8471 2
 
0.3%
Other values (599) 624
95.9%
2024-05-11T15:09:37.218105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1180
16.8%
- 1057
15.0%
2 953
13.5%
7 615
8.7%
3 547
7.8%
4 519
7.4%
5 513
7.3%
6 456
 
6.5%
1 456
 
6.5%
8 416
 
5.9%
Other values (3) 324
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5972
84.9%
Dash Punctuation 1057
 
15.0%
Close Punctuation 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1180
19.8%
2 953
16.0%
7 615
10.3%
3 547
9.2%
4 519
8.7%
5 513
8.6%
6 456
 
7.6%
1 456
 
7.6%
8 416
 
7.0%
9 317
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 1057
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7036
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1180
16.8%
- 1057
15.0%
2 953
13.5%
7 615
8.7%
3 547
7.8%
4 519
7.4%
5 513
7.3%
6 456
 
6.5%
1 456
 
6.5%
8 416
 
5.9%
Other values (3) 324
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1180
16.8%
- 1057
15.0%
2 953
13.5%
7 615
8.7%
3 547
7.8%
4 519
7.4%
5 513
7.3%
6 456
 
6.5%
1 456
 
6.5%
8 416
 
5.9%
Other values (3) 324
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

소재지우편번호
Text

MISSING 

Distinct71
Distinct (%)85.5%
Missing1683
Missing (%)95.3%
Memory size13.9 KiB
2024-05-11T15:09:37.640555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0240964
Min length6

Characters and Unicode

Total characters500
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

Unique61 ?
Unique (%)73.5%

Sample

1st row110848
2nd row110510
3rd row110803
4th row110126
5th row110800
ValueCountFrequency (%)
110350 3
 
3.6%
135120 3
 
3.6%
138051 2
 
2.4%
110040 2
 
2.4%
140190 2
 
2.4%
158715 2
 
2.4%
135011 2
 
2.4%
135881 2
 
2.4%
138180 2
 
2.4%
100300 2
 
2.4%
Other values (61) 61
73.5%
2024-05-11T15:09:38.306988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 139
27.8%
0 112
22.4%
8 47
 
9.4%
3 46
 
9.2%
5 45
 
9.0%
2 33
 
6.6%
7 24
 
4.8%
4 20
 
4.0%
6 19
 
3.8%
9 13
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 498
99.6%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 139
27.9%
0 112
22.5%
8 47
 
9.4%
3 46
 
9.2%
5 45
 
9.0%
2 33
 
6.6%
7 24
 
4.8%
4 20
 
4.0%
6 19
 
3.8%
9 13
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 500
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 139
27.8%
0 112
22.4%
8 47
 
9.4%
3 46
 
9.2%
5 45
 
9.0%
2 33
 
6.6%
7 24
 
4.8%
4 20
 
4.0%
6 19
 
3.8%
9 13
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 139
27.8%
0 112
22.4%
8 47
 
9.4%
3 46
 
9.2%
5 45
 
9.0%
2 33
 
6.6%
7 24
 
4.8%
4 20
 
4.0%
6 19
 
3.8%
9 13
 
2.6%
Distinct1394
Distinct (%)78.9%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
2024-05-11T15:09:38.720056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length26.110985
Min length13

Characters and Unicode

Total characters46112
Distinct characters468
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1213 ?
Unique (%)68.7%

Sample

1st row서울특별시 영등포구 여의도동 **-* 삼보빌딩
2nd row서울특별시 마포구 신수동 **-** 광성빌딩
3rd row서울특별시 강남구 신사동 ***-* 대원빌딩지하*층
4th row서울특별시 서초구 방배동 ***-* 용진빌딩
5th row서울특별시 동작구 상도동 ***-***
ValueCountFrequency (%)
서울특별시 1764
20.2%
번지 977
 
11.2%
751
 
8.6%
강남구 568
 
6.5%
290
 
3.3%
마포구 206
 
2.4%
논현동 198
 
2.3%
195
 
2.2%
서초구 166
 
1.9%
중구 138
 
1.6%
Other values (1148) 3499
40.0%
2024-05-11T15:09:39.644001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 8624
18.7%
8055
17.5%
2157
 
4.7%
1939
 
4.2%
1844
 
4.0%
1794
 
3.9%
1784
 
3.9%
1765
 
3.8%
1764
 
3.8%
- 1403
 
3.0%
Other values (458) 14983
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27493
59.6%
Other Punctuation 8647
 
18.8%
Space Separator 8055
 
17.5%
Dash Punctuation 1403
 
3.0%
Uppercase Letter 312
 
0.7%
Decimal Number 93
 
0.2%
Lowercase Letter 79
 
0.2%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2157
 
7.8%
1939
 
7.1%
1844
 
6.7%
1794
 
6.5%
1784
 
6.5%
1765
 
6.4%
1764
 
6.4%
1076
 
3.9%
981
 
3.6%
679
 
2.5%
Other values (397) 11710
42.6%
Uppercase Letter
ValueCountFrequency (%)
C 39
12.5%
B 29
 
9.3%
M 28
 
9.0%
D 26
 
8.3%
S 24
 
7.7%
T 19
 
6.1%
A 18
 
5.8%
K 18
 
5.8%
E 17
 
5.4%
L 12
 
3.8%
Other values (14) 82
26.3%
Lowercase Letter
ValueCountFrequency (%)
e 15
19.0%
r 11
13.9%
o 10
12.7%
i 7
8.9%
w 7
8.9%
n 6
 
7.6%
t 6
 
7.6%
l 4
 
5.1%
a 3
 
3.8%
c 2
 
2.5%
Other values (6) 8
10.1%
Decimal Number
ValueCountFrequency (%)
8 17
18.3%
2 16
17.2%
1 16
17.2%
6 10
10.8%
3 9
9.7%
7 9
9.7%
4 6
 
6.5%
9 5
 
5.4%
0 3
 
3.2%
5 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
* 8624
99.7%
, 16
 
0.2%
. 3
 
< 0.1%
/ 2
 
< 0.1%
? 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
8055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1403
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27490
59.6%
Common 18226
39.5%
Latin 393
 
0.9%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2157
 
7.8%
1939
 
7.1%
1844
 
6.7%
1794
 
6.5%
1784
 
6.5%
1765
 
6.4%
1764
 
6.4%
1076
 
3.9%
981
 
3.6%
679
 
2.5%
Other values (394) 11707
42.6%
Latin
ValueCountFrequency (%)
C 39
 
9.9%
B 29
 
7.4%
M 28
 
7.1%
D 26
 
6.6%
S 24
 
6.1%
T 19
 
4.8%
A 18
 
4.6%
K 18
 
4.6%
E 17
 
4.3%
e 15
 
3.8%
Other values (32) 160
40.7%
Common
ValueCountFrequency (%)
* 8624
47.3%
8055
44.2%
- 1403
 
7.7%
8 17
 
0.1%
2 16
 
0.1%
, 16
 
0.1%
1 16
 
0.1%
( 14
 
0.1%
) 14
 
0.1%
6 10
 
0.1%
Other values (9) 41
 
0.2%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27490
59.6%
ASCII 18617
40.4%
CJK 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 8624
46.3%
8055
43.3%
- 1403
 
7.5%
C 39
 
0.2%
B 29
 
0.2%
M 28
 
0.2%
D 26
 
0.1%
S 24
 
0.1%
T 19
 
0.1%
A 18
 
0.1%
Other values (49) 352
 
1.9%
Hangul
ValueCountFrequency (%)
2157
 
7.8%
1939
 
7.1%
1844
 
6.7%
1794
 
6.5%
1784
 
6.5%
1765
 
6.4%
1764
 
6.4%
1076
 
3.9%
981
 
3.6%
679
 
2.5%
Other values (394) 11707
42.6%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

도로명주소
Text

MISSING 

Distinct1579
Distinct (%)91.0%
Missing30
Missing (%)1.7%
Memory size13.9 KiB
2024-05-11T15:09:40.198823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length52
Mean length35.320853
Min length22

Characters and Unicode

Total characters61317
Distinct characters510
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1458 ?
Unique (%)84.0%

Sample

1st row서울특별시 영등포구 국회대로**길 *, 삼보빌딩 ***호 (여의도동)
2nd row서울특별시 마포구 독막로**길 **, 광성빌딩 ***호 (신수동)
3rd row서울특별시 강남구 압구정로**길 *, 지하*층층 (신사동, 대원빌딩)
4th row서울특별시 서초구 동작대로 **, 용진빌딩 *층 ***호 (방배동)
5th row서울특별시 동작구 국사봉*길 *** (상도동)
ValueCountFrequency (%)
서울특별시 1736
 
15.1%
1735
 
15.1%
744
 
6.5%
696
 
6.1%
강남구 565
 
4.9%
마포구 201
 
1.7%
서초구 165
 
1.4%
논현동 142
 
1.2%
중구 128
 
1.1%
102
 
0.9%
Other values (1891) 5277
45.9%
2024-05-11T15:09:40.925269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 10352
16.9%
10038
 
16.4%
2192
 
3.6%
2182
 
3.6%
, 1974
 
3.2%
1909
 
3.1%
1847
 
3.0%
1774
 
2.9%
1762
 
2.9%
) 1753
 
2.9%
Other values (500) 25534
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34516
56.3%
Other Punctuation 12338
 
20.1%
Space Separator 10038
 
16.4%
Close Punctuation 1753
 
2.9%
Open Punctuation 1753
 
2.9%
Uppercase Letter 371
 
0.6%
Dash Punctuation 324
 
0.5%
Decimal Number 136
 
0.2%
Lowercase Letter 79
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2192
 
6.4%
2182
 
6.3%
1909
 
5.5%
1847
 
5.4%
1774
 
5.1%
1762
 
5.1%
1737
 
5.0%
1736
 
5.0%
979
 
2.8%
878
 
2.5%
Other values (437) 17520
50.8%
Uppercase Letter
ValueCountFrequency (%)
B 48
12.9%
C 46
12.4%
S 27
 
7.3%
M 26
 
7.0%
T 25
 
6.7%
A 24
 
6.5%
D 24
 
6.5%
E 18
 
4.9%
K 17
 
4.6%
I 15
 
4.0%
Other values (14) 101
27.2%
Lowercase Letter
ValueCountFrequency (%)
e 16
20.3%
r 11
13.9%
o 10
12.7%
w 7
8.9%
i 6
 
7.6%
n 6
 
7.6%
t 5
 
6.3%
l 4
 
5.1%
c 3
 
3.8%
a 3
 
3.8%
Other values (7) 8
10.1%
Decimal Number
ValueCountFrequency (%)
1 39
28.7%
0 19
14.0%
2 18
13.2%
6 13
 
9.6%
3 10
 
7.4%
7 10
 
7.4%
4 9
 
6.6%
5 8
 
5.9%
8 7
 
5.1%
9 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
* 10352
83.9%
, 1974
 
16.0%
. 8
 
0.1%
? 2
 
< 0.1%
/ 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
10038
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1753
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1753
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 324
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34513
56.3%
Common 26349
43.0%
Latin 452
 
0.7%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2192
 
6.4%
2182
 
6.3%
1909
 
5.5%
1847
 
5.4%
1774
 
5.1%
1762
 
5.1%
1737
 
5.0%
1736
 
5.0%
979
 
2.8%
878
 
2.5%
Other values (434) 17517
50.8%
Latin
ValueCountFrequency (%)
B 48
 
10.6%
C 46
 
10.2%
S 27
 
6.0%
M 26
 
5.8%
T 25
 
5.5%
A 24
 
5.3%
D 24
 
5.3%
E 18
 
4.0%
K 17
 
3.8%
e 16
 
3.5%
Other values (33) 181
40.0%
Common
ValueCountFrequency (%)
* 10352
39.3%
10038
38.1%
, 1974
 
7.5%
) 1753
 
6.7%
( 1753
 
6.7%
- 324
 
1.2%
1 39
 
0.1%
0 19
 
0.1%
2 18
 
0.1%
6 13
 
< 0.1%
Other values (10) 66
 
0.3%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34513
56.3%
ASCII 26799
43.7%
CJK 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 10352
38.6%
10038
37.5%
, 1974
 
7.4%
) 1753
 
6.5%
( 1753
 
6.5%
- 324
 
1.2%
B 48
 
0.2%
C 46
 
0.2%
1 39
 
0.1%
S 27
 
0.1%
Other values (51) 445
 
1.7%
Hangul
ValueCountFrequency (%)
2192
 
6.4%
2182
 
6.3%
1909
 
5.5%
1847
 
5.4%
1774
 
5.1%
1762
 
5.1%
1737
 
5.0%
1736
 
5.0%
979
 
2.8%
878
 
2.5%
Other values (434) 17517
50.8%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

도로명우편번호
Text

MISSING 

Distinct881
Distinct (%)62.7%
Missing361
Missing (%)20.4%
Memory size13.9 KiB
2024-05-11T15:09:41.456480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2241993
Min length5

Characters and Unicode

Total characters7340
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

Unique624 ?
Unique (%)44.4%

Sample

1st row07238
2nd row04096
3rd row135-888
4th row06677
5th row07050
ValueCountFrequency (%)
06097 10
 
0.7%
05854 9
 
0.6%
06103 9
 
0.6%
06017 8
 
0.6%
03908 8
 
0.6%
04417 8
 
0.6%
06040 8
 
0.6%
04029 7
 
0.5%
06036 7
 
0.5%
06524 7
 
0.5%
Other values (871) 1324
94.2%
2024-05-11T15:09:42.387332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1869
25.5%
1 871
11.9%
6 765
10.4%
3 751
10.2%
5 632
 
8.6%
4 557
 
7.6%
7 505
 
6.9%
2 502
 
6.8%
9 443
 
6.0%
8 434
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7329
99.9%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1869
25.5%
1 871
11.9%
6 765
10.4%
3 751
10.2%
5 632
 
8.6%
4 557
 
7.6%
7 505
 
6.9%
2 502
 
6.8%
9 443
 
6.0%
8 434
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7340
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1869
25.5%
1 871
11.9%
6 765
10.4%
3 751
10.2%
5 632
 
8.6%
4 557
 
7.6%
7 505
 
6.9%
2 502
 
6.8%
9 443
 
6.0%
8 434
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1869
25.5%
1 871
11.9%
6 765
10.4%
3 751
10.2%
5 632
 
8.6%
4 557
 
7.6%
7 505
 
6.9%
2 502
 
6.8%
9 443
 
6.0%
8 434
 
5.9%
Distinct1670
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
2024-05-11T15:09:42.811691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length9.4892412
Min length2

Characters and Unicode

Total characters16758
Distinct characters642
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1582 ?
Unique (%)89.6%

Sample

1st row뉴크마그 주식회사
2nd row(주)캐스팅라인
3rd row(유)조이앤시네마
4th row주식회사 브라더미디어
5th row풋인라이트
ValueCountFrequency (%)
주식회사 446
 
18.0%
25
 
1.0%
유한회사 19
 
0.8%
영화사 16
 
0.6%
픽쳐스 14
 
0.6%
엔터테인먼트 10
 
0.4%
필름 10
 
0.4%
pictures 7
 
0.3%
스튜디오 6
 
0.2%
미디어 6
 
0.2%
Other values (1778) 1918
77.4%
2024-05-11T15:09:43.498333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1227
 
7.3%
) 842
 
5.0%
( 841
 
5.0%
714
 
4.3%
673
 
4.0%
599
 
3.6%
548
 
3.3%
485
 
2.9%
461
 
2.8%
385
 
2.3%
Other values (632) 9983
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13547
80.8%
Close Punctuation 842
 
5.0%
Open Punctuation 841
 
5.0%
Space Separator 714
 
4.3%
Uppercase Letter 324
 
1.9%
Lowercase Letter 283
 
1.7%
Other Symbol 134
 
0.8%
Decimal Number 38
 
0.2%
Other Punctuation 32
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1227
 
9.1%
673
 
5.0%
599
 
4.4%
548
 
4.0%
485
 
3.6%
461
 
3.4%
385
 
2.8%
309
 
2.3%
281
 
2.1%
261
 
1.9%
Other values (563) 8318
61.4%
Uppercase Letter
ValueCountFrequency (%)
C 29
 
9.0%
E 25
 
7.7%
A 25
 
7.7%
L 25
 
7.7%
M 23
 
7.1%
S 19
 
5.9%
O 19
 
5.9%
I 18
 
5.6%
D 16
 
4.9%
T 15
 
4.6%
Other values (15) 110
34.0%
Lowercase Letter
ValueCountFrequency (%)
e 36
12.7%
t 31
11.0%
o 28
9.9%
i 24
8.5%
r 24
8.5%
n 23
 
8.1%
s 18
 
6.4%
a 15
 
5.3%
d 13
 
4.6%
m 13
 
4.6%
Other values (14) 58
20.5%
Decimal Number
ValueCountFrequency (%)
5 6
15.8%
3 6
15.8%
1 6
15.8%
2 5
13.2%
4 4
10.5%
8 3
7.9%
6 3
7.9%
9 2
 
5.3%
7 2
 
5.3%
0 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 20
62.5%
& 6
 
18.8%
, 6
 
18.8%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 842
100.0%
Open Punctuation
ValueCountFrequency (%)
( 841
100.0%
Space Separator
ValueCountFrequency (%)
714
100.0%
Other Symbol
ValueCountFrequency (%)
134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13681
81.6%
Common 2470
 
14.7%
Latin 607
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1227
 
9.0%
673
 
4.9%
599
 
4.4%
548
 
4.0%
485
 
3.5%
461
 
3.4%
385
 
2.8%
309
 
2.3%
281
 
2.1%
261
 
1.9%
Other values (564) 8452
61.8%
Latin
ValueCountFrequency (%)
e 36
 
5.9%
t 31
 
5.1%
C 29
 
4.8%
o 28
 
4.6%
E 25
 
4.1%
A 25
 
4.1%
L 25
 
4.1%
i 24
 
4.0%
r 24
 
4.0%
M 23
 
3.8%
Other values (39) 337
55.5%
Common
ValueCountFrequency (%)
) 842
34.1%
( 841
34.0%
714
28.9%
. 20
 
0.8%
& 6
 
0.2%
5 6
 
0.2%
, 6
 
0.2%
3 6
 
0.2%
1 6
 
0.2%
2 5
 
0.2%
Other values (9) 18
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13547
80.8%
ASCII 3077
 
18.4%
None 134
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1227
 
9.1%
673
 
5.0%
599
 
4.4%
548
 
4.0%
485
 
3.6%
461
 
3.4%
385
 
2.8%
309
 
2.3%
281
 
2.1%
261
 
1.9%
Other values (563) 8318
61.4%
ASCII
ValueCountFrequency (%)
) 842
27.4%
( 841
27.3%
714
23.2%
e 36
 
1.2%
t 31
 
1.0%
C 29
 
0.9%
o 28
 
0.9%
E 25
 
0.8%
A 25
 
0.8%
L 25
 
0.8%
Other values (58) 481
15.6%
None
ValueCountFrequency (%)
134
100.0%
Distinct1674
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
Minimum2010-04-26 14:06:22
Maximum2024-05-09 14:25:01
2024-05-11T15:09:43.786890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:44.137873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
I
1255 
U
510 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 1255
71.1%
U 510
28.9%
D 1
 
0.1%

Length

2024-05-11T15:09:44.352086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:44.519836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1255
71.1%
u 510
28.9%
d 1
 
0.1%
Distinct669
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:09:44.704690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:44.930686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1402
Distinct (%)80.5%
Missing24
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean199626.25
Minimum183147.51
Maximum215496.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2024-05-11T15:09:45.153140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183147.51
5-th percentile189855.43
Q1195454.38
median201415.95
Q3203350.03
95-th percentile207745.67
Maximum215496.15
Range32348.644
Interquartile range (IQR)7895.6519

Descriptive statistics

Standard deviation5616.3436
Coefficient of variation (CV)0.028134294
Kurtosis-0.25928867
Mean199626.25
Median Absolute Deviation (MAD)2871.7644
Skewness-0.45905231
Sum3.4774893 × 108
Variance31543316
MonotonicityNot monotonic
2024-05-11T15:09:45.710675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190335.496775957 7
 
0.4%
210627.0 6
 
0.3%
189855.433985731 6
 
0.3%
199829.423596734 5
 
0.3%
190680.536850936 5
 
0.3%
210986.460698452 5
 
0.3%
202494.429240138 5
 
0.3%
199279.677406441 5
 
0.3%
200319.06075632 5
 
0.3%
193326.931018911 5
 
0.3%
Other values (1392) 1688
95.6%
(Missing) 24
 
1.4%
ValueCountFrequency (%)
183147.50519545 1
0.1%
183413.187725047 1
0.1%
183593.440428788 1
0.1%
183758.0 1
0.1%
183807.118188697 1
0.1%
184290.893400642 1
0.1%
184333.781102949 1
0.1%
184343.983714681 1
0.1%
184383.220247235 1
0.1%
184655.264279055 1
0.1%
ValueCountFrequency (%)
215496.149626989 1
0.1%
215278.711932608 1
0.1%
213749.851091244 1
0.1%
213671.045593053 1
0.1%
213092.929228694 1
0.1%
212965.180856621 1
0.1%
212711.714410254 1
0.1%
212626.759844797 1
0.1%
212394.393188708 1
0.1%
211986.297245596 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1402
Distinct (%)80.5%
Missing24
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean447789.05
Minimum438507.91
Maximum464814.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2024-05-11T15:09:45.965170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438507.91
5-th percentile442140.29
Q1444934.28
median446764.84
Q3450749.68
95-th percentile454379.99
Maximum464814.72
Range26306.81
Interquartile range (IQR)5815.3929

Descriptive statistics

Standard deviation3957.2075
Coefficient of variation (CV)0.0088372135
Kurtosis0.54140931
Mean447789.05
Median Absolute Deviation (MAD)2803.7669
Skewness0.68391766
Sum7.8004853 × 108
Variance15659491
MonotonicityNot monotonic
2024-05-11T15:09:46.227481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452758.642764785 7
 
0.4%
442875.0 6
 
0.3%
453614.583448105 6
 
0.3%
451140.199847659 5
 
0.3%
442392.645303533 5
 
0.3%
441725.293491662 5
 
0.3%
445871.873786171 5
 
0.3%
451120.517700578 5
 
0.3%
448640.981454745 5
 
0.3%
446973.914570276 5
 
0.3%
Other values (1392) 1688
95.6%
(Missing) 24
 
1.4%
ValueCountFrequency (%)
438507.907687757 1
0.1%
440040.309820942 1
0.1%
440445.175674836 1
0.1%
440521.85524888 1
0.1%
440569.5817534 1
0.1%
440603.367544216 1
0.1%
440693.311634096 1
0.1%
440753.993971457 1
0.1%
440764.426277932 1
0.1%
440963.759050916 1
0.1%
ValueCountFrequency (%)
464814.717432497 1
0.1%
463579.872056086 1
0.1%
463226.07845947 1
0.1%
462960.615197443 1
0.1%
462643.124805593 1
0.1%
462168.440616166 1
0.1%
462123.008334776 1
0.1%
461736.71535014 1
0.1%
461600.903305995 1
0.1%
460821.487931542 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
영화배급업
1248 
<NA>
518 

Length

Max length5
Median length5
Mean length4.7066818
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영화배급업 1248
70.7%
<NA> 518
29.3%

Length

2024-05-11T15:09:46.483048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:46.676179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영화배급업 1248
70.7%
na 518
29.3%

문화사업자구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

총층수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1444 
0
322 

Length

Max length4
Median length4
Mean length3.4530011
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 (%)
<NA> 1444
81.8%
0 322
 
18.2%

Length

2024-05-11T15:09:46.852624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:47.035338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1444
81.8%
0 322
 
18.2%

주변환경명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

시설면적
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1444 
0
322 

Length

Max length4
Median length4
Mean length3.4530011
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 (%)
<NA> 1444
81.8%
0 322
 
18.2%

Length

2024-05-11T15:09:47.214226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:47.394478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1444
81.8%
0 322
 
18.2%

지상층수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1444 
0
322 

Length

Max length4
Median length4
Mean length3.4530011
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 (%)
<NA> 1444
81.8%
0 322
 
18.2%

Length

2024-05-11T15:09:47.579327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:47.770952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1444
81.8%
0 322
 
18.2%

지하층수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1444 
0
322 

Length

Max length4
Median length4
Mean length3.4530011
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 (%)
<NA> 1444
81.8%
0 322
 
18.2%

Length

2024-05-11T15:09:47.989775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:48.162009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1444
81.8%
0 322
 
18.2%

건물용도명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

통로너비
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1545 
0
221 

Length

Max length4
Median length4
Mean length3.6245753
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 (%)
<NA> 1545
87.5%
0 221
 
12.5%

Length

2024-05-11T15:09:48.338656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:48.560052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1545
87.5%
0 221
 
12.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1545 
0
221 

Length

Max length4
Median length4
Mean length3.6245753
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 (%)
<NA> 1545
87.5%
0 221
 
12.5%

Length

2024-05-11T15:09:48.785403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:48.966365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1545
87.5%
0 221
 
12.5%

노래방실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1545 
0
221 

Length

Max length4
Median length4
Mean length3.6245753
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 (%)
<NA> 1545
87.5%
0 221
 
12.5%

Length

2024-05-11T15:09:49.156986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:49.322229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1545
87.5%
0 221
 
12.5%

청소년실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1545 
0
221 

Length

Max length4
Median length4
Mean length3.6245753
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 (%)
<NA> 1545
87.5%
0 221
 
12.5%

Length

2024-05-11T15:09:49.489584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:49.649447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1545
87.5%
0 221
 
12.5%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

총게임기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.9 KiB
<NA>
1545 
0
221 

Length

Max length4
Median length4
Mean length3.6245753
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 (%)
<NA> 1545
87.5%
0 221
 
12.5%

Length

2024-05-11T15:09:49.805477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:49.978107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1545
87.5%
0 221
 
12.5%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

제공게임물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

최초등록시점
Real number (ℝ)

MISSING  SKEWED 

Distinct1025
Distinct (%)82.1%
Missing518
Missing (%)29.3%
Infinite0
Infinite (%)0.0%
Mean20101487
Minimum2007073
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2024-05-11T15:09:50.136145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007073
5-th percentile20010331
Q120091084
median20131111
Q320170814
95-th percentile20210276
Maximum20220325
Range18213252
Interquartile range (IQR)79729.25

Descriptive statistics

Standard deviation727191.94
Coefficient of variation (CV)0.036176026
Kurtosis614.64226
Mean20101487
Median Absolute Deviation (MAD)39906.5
Skewness-24.743913
Sum2.5086656 × 1010
Variance5.2880812 × 1011
MonotonicityNot monotonic
2024-05-11T15:09:50.346724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080122 4
 
0.2%
20090211 4
 
0.2%
20090610 4
 
0.2%
20090910 4
 
0.2%
20090423 4
 
0.2%
20121025 3
 
0.2%
20090604 3
 
0.2%
20110114 3
 
0.2%
20070716 3
 
0.2%
19990904 3
 
0.2%
Other values (1015) 1213
68.7%
(Missing) 518
29.3%
ValueCountFrequency (%)
2007073 1
0.1%
2009012 1
0.1%
19990517 2
0.1%
19990519 2
0.1%
19990528 2
0.1%
19990531 1
0.1%
19990629 1
0.1%
19990702 1
0.1%
19990703 1
0.1%
19990708 1
0.1%
ValueCountFrequency (%)
20220325 1
0.1%
20220307 1
0.1%
20220223 1
0.1%
20220207 1
0.1%
20220125 1
0.1%
20220121 1
0.1%
20220119 1
0.1%
20220118 1
0.1%
20220112 1
0.1%
20220111 1
0.1%

지역구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1766
Missing (%)100.0%
Memory size15.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03180000CDFF52110320230000032023-03-17<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 **-* 삼보빌딩서울특별시 영등포구 국회대로**길 *, 삼보빌딩 ***호 (여의도동)07238뉴크마그 주식회사2023-03-17 12:41:11I2022-12-02 23:09:00.0<NA>192974.136279447585.389405<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13130000CDFF52110320220000052021-07-21<NA>5제외/삭제/전출15전출2023-03-08<NA><NA><NA><NA><NA><NA>서울특별시 마포구 신수동 **-** 광성빌딩서울특별시 마포구 독막로**길 **, 광성빌딩 ***호 (신수동)04096(주)캐스팅라인2023-03-08 16:55:40U2022-12-02 23:00:00.0<NA>194495.426419449611.210113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23220000CDFF52110320140000342014-09-23<NA>3폐업3폐업2023-03-07<NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 ***-* 대원빌딩지하*층서울특별시 강남구 압구정로**길 *, 지하*층층 (신사동, 대원빌딩)135-888(유)조이앤시네마2023-03-08 16:43:50U2022-12-02 23:00:00.0<NA>201876.763775446752.450887<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33210000CDFF52110320230000022018-08-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서초구 방배동 ***-* 용진빌딩서울특별시 서초구 동작대로 **, 용진빌딩 *층 ***호 (방배동)06677주식회사 브라더미디어2023-03-08 13:51:32I2022-12-02 23:01:00.0<NA>198363.705517442198.239121<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43190000CDFF52110320220000022023-03-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동작구 상도동 ***-***서울특별시 동작구 국사봉*길 *** (상도동)07050풋인라이트2023-03-13 15:54:19I2022-12-02 23:05:00.0<NA>194119.753513443676.004156<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53230000CDFF52110320230000022015-08-20<NA>5제외/삭제/전출15전출2024-02-23<NA><NA><NA><NA><NA><NA>서울특별시 송파구 문정동 *** 파크하비오서울특별시 송파구 송파대로 ***, ***동 *층 A***호 (문정동, 파크하비오)05837(주)영화사 안다미로2024-02-23 15:03:51U2023-12-01 22:05:00.0<NA>210868.397497442053.227933<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63120000CDFF52110320200000062002-05-07<NA>3폐업3폐업2023-03-14<NA><NA><NA>02-2272-2945<NA><NA>서울특별시 서대문구 홍제동 ***-*서울특별시 서대문구 간호대로*길 ** (홍제동)03619(주)씨네월드2023-03-14 15:55:45U2022-12-02 23:06:00.0<NA>195314.09396454854.831582<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73210000CDFF52110320220000122015-08-20<NA>5제외/삭제/전출15전출2023-03-10<NA><NA><NA><NA><NA><NA>서울특별시 서초구 잠원동 **-*서울특별시 서초구 강남대로***안길 *, *층 (잠원동)06524(주)영화사 안다미로2023-03-10 13:43:54U2022-12-02 23:02:00.0<NA>201541.893869446065.753966<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83220000CDFF52110320230000132023-02-28<NA>1영업/정상13영업중<NA><NA><NA><NA>02-511-0821<NA><NA>서울특별시 강남구 논현동 **-** 넥서스빌딩서울특별시 강남구 언주로***길 **-*, 넥서스빌딩 *층 (논현동)06049쇼트케이크 주식회사2023-03-17 09:45:03U2022-12-02 23:09:00.0<NA>202760.753884446321.701565<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93130000CDFF52110320180000172014-11-10<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 ***-**서울특별시 마포구 독막로*길 *-*, *층 (서교동)04048(주)영화사오원2023-03-16 15:21:25U2022-12-02 23:08:00.0<NA>192802.178308449599.372382<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
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