Overview

Dataset statistics

Number of variables56
Number of observations1340
Missing cells33308
Missing cells (%)44.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory632.2 KiB
Average record size in memory483.1 B

Variable types

Numeric8
Text7
DateTime4
Categorical17
Unsupported20

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-16038/S/1/datasetView.do

Alerts

제공게임물명 has constant value ""Constant
인허가취소일자 is highly imbalanced (98.7%)Imbalance
상세영업상태코드 is highly imbalanced (58.5%)Imbalance
상세영업상태명 is highly imbalanced (58.5%)Imbalance
데이터갱신구분 is highly imbalanced (54.8%)Imbalance
문화체육업종명 is highly imbalanced (81.0%)Imbalance
주변환경명 is highly imbalanced (56.2%)Imbalance
건물용도명 is highly imbalanced (63.3%)Imbalance
통로너비 is highly imbalanced (66.7%)Imbalance
조명시설조도 is highly imbalanced (55.0%)Imbalance
노래방실수 is highly imbalanced (55.0%)Imbalance
청소년실수 is highly imbalanced (55.0%)Imbalance
총게임기수 is highly imbalanced (55.0%)Imbalance
지역구분명 is highly imbalanced (61.9%)Imbalance
폐업일자 has 129 (9.6%) missing valuesMissing
휴업시작일자 has 1340 (100.0%) missing valuesMissing
휴업종료일자 has 1340 (100.0%) missing valuesMissing
재개업일자 has 1340 (100.0%) missing valuesMissing
전화번호 has 527 (39.3%) missing valuesMissing
소재지면적 has 1340 (100.0%) missing valuesMissing
소재지우편번호 has 449 (33.5%) missing valuesMissing
도로명주소 has 147 (11.0%) missing valuesMissing
도로명우편번호 has 1214 (90.6%) missing valuesMissing
업태구분명 has 1340 (100.0%) missing valuesMissing
좌표정보(X) has 49 (3.7%) missing valuesMissing
좌표정보(Y) has 49 (3.7%) missing valuesMissing
총층수 has 704 (52.5%) missing valuesMissing
제작취급품목내용 has 1340 (100.0%) missing valuesMissing
시설면적 has 412 (30.7%) missing valuesMissing
지상층수 has 692 (51.6%) missing valuesMissing
지하층수 has 797 (59.5%) missing valuesMissing
비상계단여부 has 1340 (100.0%) missing valuesMissing
비상구여부 has 1340 (100.0%) missing valuesMissing
자동환기여부 has 1340 (100.0%) missing valuesMissing
청소년실여부 has 1340 (100.0%) missing valuesMissing
특수조명여부 has 1340 (100.0%) missing valuesMissing
방음시설여부 has 1340 (100.0%) missing valuesMissing
조명시설유무 has 1340 (100.0%) missing valuesMissing
음향시설여부 has 1340 (100.0%) missing valuesMissing
편의시설여부 has 1340 (100.0%) missing valuesMissing
소방시설여부 has 1340 (100.0%) missing valuesMissing
기존게임업외업종명 has 1340 (100.0%) missing valuesMissing
제공게임물명 has 1339 (99.9%) missing valuesMissing
공연장형태구분명 has 1340 (100.0%) missing valuesMissing
품목명 has 1340 (100.0%) missing valuesMissing
최초등록시점 has 1340 (100.0%) missing valuesMissing
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
제작취급품목내용 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
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
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
최초등록시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 306 (22.8%) zerosZeros
시설면적 has 487 (36.3%) zerosZeros
지상층수 has 291 (21.7%) zerosZeros
지하층수 has 312 (23.3%) zerosZeros

Reproduction

Analysis started2024-05-11 08:50:05.180775
Analysis finished2024-05-11 08:50:07.975834
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3123962.7
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:08.291461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13050000
median3120000
Q33200000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)150000

Descriptive statistics

Standard deviation78600.806
Coefficient of variation (CV)0.02516061
Kurtosis-1.3471382
Mean3123962.7
Median Absolute Deviation (MAD)70000
Skewness-0.16591086
Sum4.18611 × 109
Variance6.1780867 × 109
MonotonicityNot monotonic
2024-05-11T08:50:08.879919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3000000 131
 
9.8%
3120000 108
 
8.1%
3200000 101
 
7.5%
3230000 91
 
6.8%
3220000 88
 
6.6%
3040000 76
 
5.7%
3180000 70
 
5.2%
3190000 67
 
5.0%
3050000 62
 
4.6%
3070000 60
 
4.5%
Other values (15) 486
36.3%
ValueCountFrequency (%)
3000000 131
9.8%
3010000 58
4.3%
3020000 16
 
1.2%
3030000 20
 
1.5%
3040000 76
5.7%
3050000 62
4.6%
3060000 26
 
1.9%
3070000 60
4.5%
3080000 33
 
2.5%
3090000 13
 
1.0%
ValueCountFrequency (%)
3240000 36
 
2.7%
3230000 91
6.8%
3220000 88
6.6%
3210000 46
3.4%
3200000 101
7.5%
3190000 67
5.0%
3180000 70
5.2%
3170000 20
 
1.5%
3160000 43
3.2%
3150000 35
 
2.6%
Distinct187
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
2024-05-11T08:50:09.671733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters26800
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

Unique47 ?
Unique (%)3.5%

Sample

1st rowCDFF1242012010000002
2nd rowCDFF1242012010000001
3rd rowCDFF1242011999000002
4th rowCDFF1242012009000002
5th rowCDFF1242012007000002
ValueCountFrequency (%)
cdff1242011996000001 25
 
1.9%
cdff1242012001000001 24
 
1.8%
cdff1242011996000003 23
 
1.7%
cdff1242011996000004 23
 
1.7%
cdff1242011996000008 22
 
1.6%
cdff1242012002000001 22
 
1.6%
cdff1242012001000002 22
 
1.6%
cdff1242011996000005 22
 
1.6%
cdff1242011996000009 21
 
1.6%
cdff1242011996000006 21
 
1.6%
Other values (177) 1115
83.2%
2024-05-11T08:50:11.048265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8952
33.4%
1 4128
15.4%
2 3768
14.1%
F 2680
 
10.0%
9 1631
 
6.1%
4 1542
 
5.8%
C 1340
 
5.0%
D 1340
 
5.0%
6 639
 
2.4%
3 284
 
1.1%
Other values (3) 496
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21440
80.0%
Uppercase Letter 5360
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8952
41.8%
1 4128
19.3%
2 3768
17.6%
9 1631
 
7.6%
4 1542
 
7.2%
6 639
 
3.0%
3 284
 
1.3%
7 196
 
0.9%
5 172
 
0.8%
8 128
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
F 2680
50.0%
C 1340
25.0%
D 1340
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21440
80.0%
Latin 5360
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8952
41.8%
1 4128
19.3%
2 3768
17.6%
9 1631
 
7.6%
4 1542
 
7.2%
6 639
 
3.0%
3 284
 
1.3%
7 196
 
0.9%
5 172
 
0.8%
8 128
 
0.6%
Latin
ValueCountFrequency (%)
F 2680
50.0%
C 1340
25.0%
D 1340
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8952
33.4%
1 4128
15.4%
2 3768
14.1%
F 2680
 
10.0%
9 1631
 
6.1%
4 1542
 
5.8%
C 1340
 
5.0%
D 1340
 
5.0%
6 639
 
2.4%
3 284
 
1.1%
Other values (3) 496
 
1.9%
Distinct743
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
Minimum1906-09-09 00:00:00
Maximum2023-07-29 00:00:00
2024-05-11T08:50:11.628671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:50:12.509900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1337 
20101231
 
1
20051219
 
1
20080407
 
1

Length

Max length8
Median length4
Mean length4.0089552
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> 1337
99.8%
20101231 1
 
0.1%
20051219 1
 
0.1%
20080407 1
 
0.1%

Length

2024-05-11T08:50:13.031930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:13.458930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1337
99.8%
20101231 1
 
0.1%
20051219 1
 
0.1%
20080407 1
 
0.1%
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
3
1035 
4
194 
1
111 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 1035
77.2%
4 194
 
14.5%
1 111
 
8.3%

Length

2024-05-11T08:50:14.027495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:14.454769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1035
77.2%
4 194
 
14.5%
1 111
 
8.3%

영업상태명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
폐업
1035 
취소/말소/만료/정지/중지
194 
영업/정상
111 

Length

Max length14
Median length2
Mean length3.9858209
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1035
77.2%
취소/말소/만료/정지/중지 194
 
14.5%
영업/정상 111
 
8.3%

Length

2024-05-11T08:50:15.251071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:15.739795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1035
77.2%
취소/말소/만료/정지/중지 194
 
14.5%
영업/정상 111
 
8.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
03
1035 
35
185 
13
 
100
BBBB
 
11
30
 
5

Length

Max length4
Median length2
Mean length2.0164179
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03
2nd row03
3rd row35
4th row35
5th row35

Common Values

ValueCountFrequency (%)
03 1035
77.2%
35 185
 
13.8%
13 100
 
7.5%
BBBB 11
 
0.8%
30 5
 
0.4%
31 4
 
0.3%

Length

2024-05-11T08:50:16.290394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:16.832197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03 1035
77.2%
35 185
 
13.8%
13 100
 
7.5%
bbbb 11
 
0.8%
30 5
 
0.4%
31 4
 
0.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
폐업
1035 
직권말소
185 
영업중
 
100
<NA>
 
11
허가취소
 
5

Length

Max length4
Median length2
Mean length2.380597
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1035
77.2%
직권말소 185
 
13.8%
영업중 100
 
7.5%
<NA> 11
 
0.8%
허가취소 5
 
0.4%
등록취소 4
 
0.3%

Length

2024-05-11T08:50:17.441611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:17.899707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1035
77.2%
직권말소 185
 
13.8%
영업중 100
 
7.5%
na 11
 
0.8%
허가취소 5
 
0.4%
등록취소 4
 
0.3%

폐업일자
Date

MISSING 

Distinct928
Distinct (%)76.6%
Missing129
Missing (%)9.6%
Memory size10.6 KiB
Minimum1996-12-19 00:00:00
Maximum2024-03-27 00:00:00
2024-05-11T08:50:18.344829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:50:18.825253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

전화번호
Text

MISSING 

Distinct799
Distinct (%)98.3%
Missing527
Missing (%)39.3%
Memory size10.6 KiB
2024-05-11T08:50:19.866778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length8
Mean length8.3628536
Min length5

Characters and Unicode

Total characters6799
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique785 ?
Unique (%)96.6%

Sample

1st row070-8119-8582
2nd row02-893-5415
3rd row473-1334
4th row02-745-1209
5th row565-2818
ValueCountFrequency (%)
697-8182 2
 
0.2%
1111-1111 2
 
0.2%
02-538-4348 2
 
0.2%
965-1829 2
 
0.2%
467-5164 2
 
0.2%
497-8083 2
 
0.2%
861-4586 2
 
0.2%
959-9111 2
 
0.2%
473-7685 2
 
0.2%
992-3178 2
 
0.2%
Other values (789) 793
97.5%
2024-05-11T08:50:21.241340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 864
12.7%
2 680
10.0%
8 665
9.8%
7 655
9.6%
6 642
9.4%
3 637
9.4%
4 621
9.1%
9 601
8.8%
5 534
7.9%
1 477
7.0%
Other values (4) 423
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5931
87.2%
Dash Punctuation 864
 
12.7%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 680
11.5%
8 665
11.2%
7 655
11.0%
6 642
10.8%
3 637
10.7%
4 621
10.5%
9 601
10.1%
5 534
9.0%
1 477
8.0%
0 419
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 864
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6799
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 864
12.7%
2 680
10.0%
8 665
9.8%
7 655
9.6%
6 642
9.4%
3 637
9.4%
4 621
9.1%
9 601
8.8%
5 534
7.9%
1 477
7.0%
Other values (4) 423
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6799
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 864
12.7%
2 680
10.0%
8 665
9.8%
7 655
9.6%
6 642
9.4%
3 637
9.4%
4 621
9.1%
9 601
8.8%
5 534
7.9%
1 477
7.0%
Other values (4) 423
6.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

소재지우편번호
Text

MISSING 

Distinct376
Distinct (%)42.2%
Missing449
Missing (%)33.5%
Memory size10.6 KiB
2024-05-11T08:50:21.970117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0011223
Min length6

Characters and Unicode

Total characters5347
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

Unique228 ?
Unique (%)25.6%

Sample

1st row122-809
2nd row110111
3rd row110100
4th row110410
5th row110827
ValueCountFrequency (%)
138861 31
 
3.5%
143914 26
 
2.9%
150033 24
 
2.7%
151895 19
 
2.1%
110111 18
 
2.0%
110522 16
 
1.8%
120834 13
 
1.5%
136075 13
 
1.5%
136051 13
 
1.5%
156801 12
 
1.3%
Other values (366) 706
79.2%
2024-05-11T08:50:23.088867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1418
26.5%
8 790
14.8%
3 621
11.6%
0 612
11.4%
5 512
 
9.6%
2 389
 
7.3%
4 297
 
5.6%
9 255
 
4.8%
6 251
 
4.7%
7 201
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5346
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1418
26.5%
8 790
14.8%
3 621
11.6%
0 612
11.4%
5 512
 
9.6%
2 389
 
7.3%
4 297
 
5.6%
9 255
 
4.8%
6 251
 
4.7%
7 201
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5347
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1418
26.5%
8 790
14.8%
3 621
11.6%
0 612
11.4%
5 512
 
9.6%
2 389
 
7.3%
4 297
 
5.6%
9 255
 
4.8%
6 251
 
4.7%
7 201
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1418
26.5%
8 790
14.8%
3 621
11.6%
0 612
11.4%
5 512
 
9.6%
2 389
 
7.3%
4 297
 
5.6%
9 255
 
4.8%
6 251
 
4.7%
7 201
 
3.8%
Distinct1298
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
2024-05-11T08:50:23.769112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length41
Mean length24.650746
Min length14

Characters and Unicode

Total characters33032
Distinct characters234
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1258 ?
Unique (%)93.9%

Sample

1st row서울특별시 강남구 역삼동 820-2 지상3층
2nd row서울특별시 금천구 시흥동 995-8
3rd row서울특별시 강동구 천호동 453-8 지1층
4th row서울특별시 종로구 명륜2가 184
5th row서울특별시 종로구 관철동 13-1 5층
ValueCountFrequency (%)
서울특별시 1340
 
22.1%
3층 169
 
2.8%
종로구 131
 
2.2%
서대문구 108
 
1.8%
관악구 101
 
1.7%
송파구 91
 
1.5%
강남구 88
 
1.5%
신림동 81
 
1.3%
광진구 76
 
1.3%
창천동 74
 
1.2%
Other values (1621) 3807
62.8%
2024-05-11T08:50:24.845880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6002
18.2%
1565
 
4.7%
1542
 
4.7%
1419
 
4.3%
1412
 
4.3%
1 1384
 
4.2%
1348
 
4.1%
1341
 
4.1%
1340
 
4.1%
1340
 
4.1%
Other values (224) 14339
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18891
57.2%
Decimal Number 6591
 
20.0%
Space Separator 6002
 
18.2%
Dash Punctuation 1266
 
3.8%
Close Punctuation 113
 
0.3%
Open Punctuation 113
 
0.3%
Other Punctuation 44
 
0.1%
Uppercase Letter 10
 
< 0.1%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1565
 
8.3%
1542
 
8.2%
1419
 
7.5%
1412
 
7.5%
1348
 
7.1%
1341
 
7.1%
1340
 
7.1%
1340
 
7.1%
1258
 
6.7%
511
 
2.7%
Other values (200) 5815
30.8%
Decimal Number
ValueCountFrequency (%)
1 1384
21.0%
3 907
13.8%
2 881
13.4%
4 662
10.0%
5 604
9.2%
6 516
 
7.8%
0 427
 
6.5%
8 418
 
6.3%
7 398
 
6.0%
9 394
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
40.0%
A 2
20.0%
W 1
 
10.0%
C 1
 
10.0%
M 1
 
10.0%
D 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 37
84.1%
. 7
 
15.9%
Space Separator
ValueCountFrequency (%)
6002
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18891
57.2%
Common 14130
42.8%
Latin 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1565
 
8.3%
1542
 
8.2%
1419
 
7.5%
1412
 
7.5%
1348
 
7.1%
1341
 
7.1%
1340
 
7.1%
1340
 
7.1%
1258
 
6.7%
511
 
2.7%
Other values (200) 5815
30.8%
Common
ValueCountFrequency (%)
6002
42.5%
1 1384
 
9.8%
- 1266
 
9.0%
3 907
 
6.4%
2 881
 
6.2%
4 662
 
4.7%
5 604
 
4.3%
6 516
 
3.7%
0 427
 
3.0%
8 418
 
3.0%
Other values (7) 1063
 
7.5%
Latin
ValueCountFrequency (%)
B 4
36.4%
A 2
18.2%
W 1
 
9.1%
C 1
 
9.1%
M 1
 
9.1%
D 1
 
9.1%
a 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18891
57.2%
ASCII 14141
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6002
42.4%
1 1384
 
9.8%
- 1266
 
9.0%
3 907
 
6.4%
2 881
 
6.2%
4 662
 
4.7%
5 604
 
4.3%
6 516
 
3.6%
0 427
 
3.0%
8 418
 
3.0%
Other values (14) 1074
 
7.6%
Hangul
ValueCountFrequency (%)
1565
 
8.3%
1542
 
8.2%
1419
 
7.5%
1412
 
7.5%
1348
 
7.1%
1341
 
7.1%
1340
 
7.1%
1340
 
7.1%
1258
 
6.7%
511
 
2.7%
Other values (200) 5815
30.8%

도로명주소
Text

MISSING 

Distinct1157
Distinct (%)97.0%
Missing147
Missing (%)11.0%
Memory size10.6 KiB
2024-05-11T08:50:25.862112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length28.008382
Min length20

Characters and Unicode

Total characters33414
Distinct characters282
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1124 ?
Unique (%)94.2%

Sample

1st row서울특별시 강남구 테헤란로1길 17, 3층 (역삼동)
2nd row서울특별시 금천구 시흥대로61길 16 (시흥동)
3rd row서울특별시 강동구 천호대로157길 18 (천호동,지1층)
4th row서울특별시 종로구 대명길 40 (명륜2가)
5th row서울특별시 종로구 삼일대로19길 15 (관철동,5층)
ValueCountFrequency (%)
서울특별시 1193
 
19.4%
종로구 119
 
1.9%
서대문구 103
 
1.7%
관악구 98
 
1.6%
강남구 88
 
1.4%
송파구 85
 
1.4%
신림동 74
 
1.2%
광진구 69
 
1.1%
영등포구 63
 
1.0%
동작구 62
 
1.0%
Other values (1453) 4192
68.2%
2024-05-11T08:50:27.822101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5888
 
17.6%
1446
 
4.3%
1441
 
4.3%
1327
 
4.0%
1295
 
3.9%
( 1284
 
3.8%
) 1284
 
3.8%
1223
 
3.7%
1197
 
3.6%
1193
 
3.6%
Other values (272) 15836
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19308
57.8%
Space Separator 5888
 
17.6%
Decimal Number 4877
 
14.6%
Open Punctuation 1284
 
3.8%
Close Punctuation 1284
 
3.8%
Other Punctuation 567
 
1.7%
Dash Punctuation 195
 
0.6%
Uppercase Letter 10
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1446
 
7.5%
1441
 
7.5%
1327
 
6.9%
1295
 
6.7%
1223
 
6.3%
1197
 
6.2%
1193
 
6.2%
1193
 
6.2%
751
 
3.9%
446
 
2.3%
Other values (247) 7796
40.4%
Decimal Number
ValueCountFrequency (%)
1 981
20.1%
2 853
17.5%
3 659
13.5%
4 485
9.9%
5 411
8.4%
7 332
 
6.8%
6 317
 
6.5%
0 311
 
6.4%
9 278
 
5.7%
8 250
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
W 1
 
10.0%
A 1
 
10.0%
Y 1
 
10.0%
K 1
 
10.0%
D 1
 
10.0%
M 1
 
10.0%
C 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 563
99.3%
. 4
 
0.7%
Space Separator
ValueCountFrequency (%)
5888
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1284
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19308
57.8%
Common 14096
42.2%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1446
 
7.5%
1441
 
7.5%
1327
 
6.9%
1295
 
6.7%
1223
 
6.3%
1197
 
6.2%
1193
 
6.2%
1193
 
6.2%
751
 
3.9%
446
 
2.3%
Other values (247) 7796
40.4%
Common
ValueCountFrequency (%)
5888
41.8%
( 1284
 
9.1%
) 1284
 
9.1%
1 981
 
7.0%
2 853
 
6.1%
3 659
 
4.7%
, 563
 
4.0%
4 485
 
3.4%
5 411
 
2.9%
7 332
 
2.4%
Other values (7) 1356
 
9.6%
Latin
ValueCountFrequency (%)
B 3
30.0%
W 1
 
10.0%
A 1
 
10.0%
Y 1
 
10.0%
K 1
 
10.0%
D 1
 
10.0%
M 1
 
10.0%
C 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19308
57.8%
ASCII 14106
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5888
41.7%
( 1284
 
9.1%
) 1284
 
9.1%
1 981
 
7.0%
2 853
 
6.0%
3 659
 
4.7%
, 563
 
4.0%
4 485
 
3.4%
5 411
 
2.9%
7 332
 
2.4%
Other values (15) 1366
 
9.7%
Hangul
ValueCountFrequency (%)
1446
 
7.5%
1441
 
7.5%
1327
 
6.9%
1295
 
6.7%
1223
 
6.3%
1197
 
6.2%
1193
 
6.2%
1193
 
6.2%
751
 
3.9%
446
 
2.3%
Other values (247) 7796
40.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)70.6%
Missing1214
Missing (%)90.6%
Infinite0
Infinite (%)0.0%
Mean21686.048
Minimum1073
Maximum151846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:28.462438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1073
5-th percentile1693
Q13092.5
median5445.5
Q37139
95-th percentile135642.75
Maximum151846
Range150773
Interquartile range (IQR)4046.5

Descriptive statistics

Standard deviation43640.575
Coefficient of variation (CV)2.0123803
Kurtosis3.1660996
Mean21686.048
Median Absolute Deviation (MAD)2256
Skewness2.2293644
Sum2732442
Variance1.9044998 × 109
MonotonicityNot monotonic
2024-05-11T08:50:29.093330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6129 8
 
0.6%
6018 6
 
0.4%
1693 5
 
0.4%
2845 4
 
0.3%
2855 3
 
0.2%
4041 3
 
0.2%
4050 3
 
0.2%
4760 2
 
0.1%
6019 2
 
0.1%
6017 2
 
0.1%
Other values (79) 88
 
6.6%
(Missing) 1214
90.6%
ValueCountFrequency (%)
1073 2
 
0.1%
1074 1
 
0.1%
1220 1
 
0.1%
1662 1
 
0.1%
1693 5
0.4%
1695 2
 
0.1%
1892 1
 
0.1%
1895 1
 
0.1%
1902 1
 
0.1%
2120 1
 
0.1%
ValueCountFrequency (%)
151846 1
0.1%
150850 1
0.1%
150031 1
0.1%
142878 1
0.1%
138803 1
0.1%
136051 1
0.1%
135897 1
0.1%
134880 1
0.1%
134872 2
0.1%
134870 1
0.1%
Distinct1070
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
2024-05-11T08:50:29.831317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length6.7097015
Min length1

Characters and Unicode

Total characters8991
Distinct characters487
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique919 ?
Unique (%)68.6%

Sample

1st row해피죤DVD방
2nd row챌린저DVD
3rd row스타비디오
4th row고구마 DVD 영화관
5th rowDVD 키네마
ValueCountFrequency (%)
dvd 78
 
4.7%
비디오방 67
 
4.0%
비디오감상실 51
 
3.1%
영화관 24
 
1.4%
시네마천국 13
 
0.8%
시네마 12
 
0.7%
감상실 12
 
0.7%
dvd방 11
 
0.7%
명화비디오방 8
 
0.5%
허리우드 8
 
0.5%
Other values (1037) 1384
83.0%
2024-05-11T08:50:31.383696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
734
 
8.2%
709
 
7.9%
682
 
7.6%
D 518
 
5.8%
391
 
4.3%
329
 
3.7%
325
 
3.6%
288
 
3.2%
286
 
3.2%
V 257
 
2.9%
Other values (477) 4472
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7293
81.1%
Uppercase Letter 1029
 
11.4%
Space Separator 329
 
3.7%
Decimal Number 176
 
2.0%
Lowercase Letter 65
 
0.7%
Close Punctuation 33
 
0.4%
Open Punctuation 33
 
0.4%
Dash Punctuation 17
 
0.2%
Other Punctuation 16
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
734
 
10.1%
709
 
9.7%
682
 
9.4%
391
 
5.4%
325
 
4.5%
288
 
3.9%
286
 
3.9%
184
 
2.5%
177
 
2.4%
169
 
2.3%
Other values (413) 3348
45.9%
Uppercase Letter
ValueCountFrequency (%)
D 518
50.3%
V 257
25.0%
O 29
 
2.8%
C 25
 
2.4%
A 21
 
2.0%
S 19
 
1.8%
M 18
 
1.7%
E 16
 
1.6%
P 14
 
1.4%
N 14
 
1.4%
Other values (16) 98
 
9.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
21.5%
d 9
13.8%
n 7
10.8%
v 5
 
7.7%
o 4
 
6.2%
a 3
 
4.6%
p 3
 
4.6%
t 3
 
4.6%
i 3
 
4.6%
s 3
 
4.6%
Other values (9) 11
16.9%
Decimal Number
ValueCountFrequency (%)
2 70
39.8%
1 37
21.0%
0 20
 
11.4%
5 19
 
10.8%
4 16
 
9.1%
7 4
 
2.3%
6 3
 
1.7%
8 3
 
1.7%
9 2
 
1.1%
3 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 6
37.5%
& 6
37.5%
' 2
 
12.5%
? 1
 
6.2%
@ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7291
81.1%
Latin 1094
 
12.2%
Common 604
 
6.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
734
 
10.1%
709
 
9.7%
682
 
9.4%
391
 
5.4%
325
 
4.5%
288
 
4.0%
286
 
3.9%
184
 
2.5%
177
 
2.4%
169
 
2.3%
Other values (411) 3346
45.9%
Latin
ValueCountFrequency (%)
D 518
47.3%
V 257
23.5%
O 29
 
2.7%
C 25
 
2.3%
A 21
 
1.9%
S 19
 
1.7%
M 18
 
1.6%
E 16
 
1.5%
P 14
 
1.3%
N 14
 
1.3%
Other values (35) 163
 
14.9%
Common
ValueCountFrequency (%)
329
54.5%
2 70
 
11.6%
1 37
 
6.1%
) 33
 
5.5%
( 33
 
5.5%
0 20
 
3.3%
5 19
 
3.1%
- 17
 
2.8%
4 16
 
2.6%
. 6
 
1.0%
Other values (9) 24
 
4.0%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7288
81.1%
ASCII 1698
 
18.9%
Compat Jamo 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
734
 
10.1%
709
 
9.7%
682
 
9.4%
391
 
5.4%
325
 
4.5%
288
 
4.0%
286
 
3.9%
184
 
2.5%
177
 
2.4%
169
 
2.3%
Other values (408) 3343
45.9%
ASCII
ValueCountFrequency (%)
D 518
30.5%
329
19.4%
V 257
15.1%
2 70
 
4.1%
1 37
 
2.2%
) 33
 
1.9%
( 33
 
1.9%
O 29
 
1.7%
C 25
 
1.5%
A 21
 
1.2%
Other values (54) 346
20.4%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Compat Jamo
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct1047
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
Minimum2002-10-22 17:41:01
Maximum2024-03-27 14:30:47
2024-05-11T08:50:31.972131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:50:32.539151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
I
1213 
U
127 

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 1213
90.5%
U 127
 
9.5%

Length

2024-05-11T08:50:33.063828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:33.407776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1213
90.5%
u 127
 
9.5%
Distinct80
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:09:00
2024-05-11T08:50:33.925437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:50:34.573748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1179
Distinct (%)91.3%
Missing49
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean199331.62
Minimum183205.51
Maximum213632.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:35.103135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183205.51
5-th percentile188905.64
Q1194316.02
median199782.54
Q3204558
95-th percentile209487.94
Maximum213632.14
Range30426.627
Interquartile range (IQR)10241.976

Descriptive statistics

Standard deviation6318.2443
Coefficient of variation (CV)0.031697151
Kurtosis-0.80660008
Mean199331.62
Median Absolute Deviation (MAD)5407.3866
Skewness-0.09880996
Sum2.5733712 × 108
Variance39920211
MonotonicityNot monotonic
2024-05-11T08:50:35.711392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194334.618853084 4
 
0.3%
211116.109777375 3
 
0.2%
200640.845642848 3
 
0.2%
207111.481365768 3
 
0.2%
206071.426952559 3
 
0.2%
209541.418807954 3
 
0.2%
193070.031498237 3
 
0.2%
207370.740384909 3
 
0.2%
199909.796584818 2
 
0.1%
209565.754258618 2
 
0.1%
Other values (1169) 1262
94.2%
(Missing) 49
 
3.7%
ValueCountFrequency (%)
183205.51413075 1
0.1%
183227.963853126 1
0.1%
183237.425943428 1
0.1%
185416.995235468 1
0.1%
185480.851084522 1
0.1%
185526.740191834 1
0.1%
185628.594608335 1
0.1%
185669.055133283 1
0.1%
185688.018511973 1
0.1%
185692.551545586 1
0.1%
ValueCountFrequency (%)
213632.141350282 1
0.1%
213148.581914117 1
0.1%
213032.020864518 2
0.1%
212897.43493232 1
0.1%
212679.486469466 1
0.1%
212655.919014923 1
0.1%
212544.588586695 1
0.1%
212501.057257566 1
0.1%
212320.780255548 1
0.1%
211986.914896269 1
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1179
Distinct (%)91.3%
Missing49
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean449151.08
Minimum438699.61
Maximum463005.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:36.196746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438699.61
5-th percentile441482.75
Q1445154.59
median449143.96
Q3452259.96
95-th percentile458649.82
Maximum463005.29
Range24305.678
Interquartile range (IQR)7105.3718

Descriptive statistics

Standard deviation5153.467
Coefficient of variation (CV)0.011473794
Kurtosis-0.37223288
Mean449151.08
Median Absolute Deviation (MAD)3778.8348
Skewness0.35465043
Sum5.7985405 × 108
Variance26558222
MonotonicityNot monotonic
2024-05-11T08:50:36.702521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450650.747799211 4
 
0.3%
448577.957250699 3
 
0.2%
451721.924344597 3
 
0.2%
445404.185488928 3
 
0.2%
448734.249359413 3
 
0.2%
444357.068661528 3
 
0.2%
449992.775315167 3
 
0.2%
445382.739697831 3
 
0.2%
453367.533676631 2
 
0.1%
444358.646160107 2
 
0.1%
Other values (1169) 1262
94.2%
(Missing) 49
 
3.7%
ValueCountFrequency (%)
438699.610131723 1
0.1%
438845.717500944 1
0.1%
439065.169432475 1
0.1%
439099.231875631 1
0.1%
439125.63991796 1
0.1%
439129.969918536 1
0.1%
439144.877856068 1
0.1%
439169.359799687 1
0.1%
439885.941303087 1
0.1%
440465.308720064 1
0.1%
ValueCountFrequency (%)
463005.288095194 1
0.1%
462553.507825344 1
0.1%
461993.090140302 1
0.1%
461688.042377267 1
0.1%
461670.756131859 1
0.1%
461648.715054062 2
0.1%
461643.199837271 2
0.1%
461626.673163609 1
0.1%
461615.887623852 1
0.1%
461592.348795203 2
0.1%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
비디오물감상실업
1301 
<NA>
 
39

Length

Max length8
Median length8
Mean length7.8835821
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 (%)
비디오물감상실업 1301
97.1%
<NA> 39
 
2.9%

Length

2024-05-11T08:50:37.341456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:37.783678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비디오물감상실업 1301
97.1%
na 39
 
2.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
유통관련업
908 
<NA>
432 

Length

Max length5
Median length5
Mean length4.6776119
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 (%)
유통관련업 908
67.8%
<NA> 432
32.2%

Length

2024-05-11T08:50:38.138924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:38.539371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 908
67.8%
na 432
32.2%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)2.7%
Missing704
Missing (%)52.5%
Infinite0
Infinite (%)0.0%
Mean2.591195
Minimum0
Maximum48
Zeros306
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:38.912673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q34
95-th percentile7
Maximum48
Range48
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.5648571
Coefficient of variation (CV)1.3757579
Kurtosis49.405899
Mean2.591195
Median Absolute Deviation (MAD)3
Skewness4.776118
Sum1648
Variance12.708206
MonotonicityNot monotonic
2024-05-11T08:50:39.312984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 306
22.8%
4 95
 
7.1%
3 75
 
5.6%
5 62
 
4.6%
6 44
 
3.3%
7 15
 
1.1%
2 9
 
0.7%
10 8
 
0.6%
9 7
 
0.5%
8 6
 
0.4%
Other values (7) 9
 
0.7%
(Missing) 704
52.5%
ValueCountFrequency (%)
0 306
22.8%
1 2
 
0.1%
2 9
 
0.7%
3 75
 
5.6%
4 95
 
7.1%
5 62
 
4.6%
6 44
 
3.3%
7 15
 
1.1%
8 6
 
0.4%
9 7
 
0.5%
ValueCountFrequency (%)
48 1
 
0.1%
33 1
 
0.1%
19 1
 
0.1%
18 1
 
0.1%
12 2
 
0.1%
11 1
 
0.1%
10 8
0.6%
9 7
0.5%
8 6
 
0.4%
7 15
1.1%

주변환경명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1027 
기타
148 
유흥업소밀집지역
 
77
주택가주변
 
42
학교정화(상대)
 
39
Other values (2)
 
7

Length

Max length8
Median length4
Mean length4.1634328
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1027
76.6%
기타 148
 
11.0%
유흥업소밀집지역 77
 
5.7%
주택가주변 42
 
3.1%
학교정화(상대) 39
 
2.9%
아파트지역 6
 
0.4%
결혼예식장주변 1
 
0.1%

Length

2024-05-11T08:50:39.846904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:40.378557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1027
76.6%
기타 148
 
11.0%
유흥업소밀집지역 77
 
5.7%
주택가주변 42
 
3.1%
학교정화(상대 39
 
2.9%
아파트지역 6
 
0.4%
결혼예식장주변 1
 
0.1%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct369
Distinct (%)39.8%
Missing412
Missing (%)30.7%
Infinite0
Infinite (%)0.0%
Mean73.066422
Minimum0
Maximum3022.33
Zeros487
Zeros (%)36.3%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:41.321874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3128.0675
95-th percentile201.834
Maximum3022.33
Range3022.33
Interquartile range (IQR)128.0675

Descriptive statistics

Standard deviation161.13046
Coefficient of variation (CV)2.20526
Kurtosis189.01269
Mean73.066422
Median Absolute Deviation (MAD)0
Skewness11.900486
Sum67805.64
Variance25963.024
MonotonicityNot monotonic
2024-05-11T08:50:41.788364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 487
36.3%
132.0 7
 
0.5%
99.0 6
 
0.4%
165.0 5
 
0.4%
198.0 4
 
0.3%
66.0 4
 
0.3%
90.0 4
 
0.3%
126.0 3
 
0.2%
162.0 3
 
0.2%
97.0 3
 
0.2%
Other values (359) 402
30.0%
(Missing) 412
30.7%
ValueCountFrequency (%)
0.0 487
36.3%
6.6 1
 
0.1%
22.5 1
 
0.1%
37.0 1
 
0.1%
40.83 1
 
0.1%
46.8 1
 
0.1%
47.94 1
 
0.1%
51.0 1
 
0.1%
51.21 1
 
0.1%
51.57 1
 
0.1%
ValueCountFrequency (%)
3022.33 1
0.1%
2398.69 1
0.1%
2008.08 1
0.1%
646.39 1
0.1%
633.12 1
0.1%
348.12 1
0.1%
333.0 1
0.1%
326.0 1
0.1%
304.8 1
0.1%
294.8 1
0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)2.3%
Missing692
Missing (%)51.6%
Infinite0
Infinite (%)0.0%
Mean2.1867284
Minimum0
Maximum41
Zeros291
Zeros (%)21.7%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:42.260907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile6
Maximum41
Range41
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.8258045
Coefficient of variation (CV)1.2922522
Kurtosis56.362431
Mean2.1867284
Median Absolute Deviation (MAD)2
Skewness4.8176243
Sum1417
Variance7.9851714
MonotonicityNot monotonic
2024-05-11T08:50:42.621505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 291
21.7%
3 116
 
8.7%
4 84
 
6.3%
5 54
 
4.0%
2 53
 
4.0%
7 16
 
1.2%
6 14
 
1.0%
1 9
 
0.7%
9 3
 
0.2%
10 3
 
0.2%
Other values (5) 5
 
0.4%
(Missing) 692
51.6%
ValueCountFrequency (%)
0 291
21.7%
1 9
 
0.7%
2 53
 
4.0%
3 116
 
8.7%
4 84
 
6.3%
5 54
 
4.0%
6 14
 
1.0%
7 16
 
1.2%
8 1
 
0.1%
9 3
 
0.2%
ValueCountFrequency (%)
41 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%
12 1
 
0.1%
10 3
 
0.2%
9 3
 
0.2%
8 1
 
0.1%
7 16
 
1.2%
6 14
 
1.0%
5 54
4.0%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.3%
Missing797
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean0.51197053
Minimum0
Maximum7
Zeros312
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size11.9 KiB
2024-05-11T08:50:43.020802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7607437
Coefficient of variation (CV)1.4859131
Kurtosis16.304517
Mean0.51197053
Median Absolute Deviation (MAD)0
Skewness2.975284
Sum278
Variance0.57873098
MonotonicityNot monotonic
2024-05-11T08:50:43.598874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 312
 
23.3%
1 206
 
15.4%
2 14
 
1.0%
3 6
 
0.4%
5 3
 
0.2%
7 1
 
0.1%
4 1
 
0.1%
(Missing) 797
59.5%
ValueCountFrequency (%)
0 312
23.3%
1 206
15.4%
2 14
 
1.0%
3 6
 
0.4%
4 1
 
0.1%
5 3
 
0.2%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
5 3
 
0.2%
4 1
 
0.1%
3 6
 
0.4%
2 14
 
1.0%
1 206
15.4%
0 312
23.3%

건물용도명
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
905 
근린생활시설
359 
기타
 
69
사무실
 
2
문화시설
 
1
Other values (4)
 
4

Length

Max length6
Median length4
Mean length4.430597
Min length2

Unique

Unique5 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 905
67.5%
근린생활시설 359
 
26.8%
기타 69
 
5.1%
사무실 2
 
0.1%
문화시설 1
 
0.1%
유통시설 1
 
0.1%
단독주택 1
 
0.1%
유기장 1
 
0.1%
운수시설 1
 
0.1%

Length

2024-05-11T08:50:44.143354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:44.591485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 905
67.5%
근린생활시설 359
 
26.8%
기타 69
 
5.1%
사무실 2
 
0.1%
문화시설 1
 
0.1%
유통시설 1
 
0.1%
단독주택 1
 
0.1%
유기장 1
 
0.1%
운수시설 1
 
0.1%

통로너비
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1113 
0.0
124 
1.0
 
95
1.2
 
6
1.05
 
1

Length

Max length4
Median length4
Mean length3.8313433
Min length3

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> 1113
83.1%
0.0 124
 
9.3%
1.0 95
 
7.1%
1.2 6
 
0.4%
1.05 1
 
0.1%
1.1 1
 
0.1%

Length

2024-05-11T08:50:45.219961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:45.728584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1113
83.1%
0.0 124
 
9.3%
1.0 95
 
7.1%
1.2 6
 
0.4%
1.05 1
 
0.1%
1.1 1
 
0.1%

조명시설조도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1214 
0
126 

Length

Max length4
Median length4
Mean length3.7179104
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> 1214
90.6%
0 126
 
9.4%

Length

2024-05-11T08:50:46.205024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:46.655183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1214
90.6%
0 126
 
9.4%

노래방실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1214 
0
126 

Length

Max length4
Median length4
Mean length3.7179104
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> 1214
90.6%
0 126
 
9.4%

Length

2024-05-11T08:50:47.135792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:47.521101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1214
90.6%
0 126
 
9.4%

청소년실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1214 
0
126 

Length

Max length4
Median length4
Mean length3.7179104
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> 1214
90.6%
0 126
 
9.4%

Length

2024-05-11T08:50:48.022536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:48.416391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1214
90.6%
0 126
 
9.4%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
672 
자동
666 
수동
 
2

Length

Max length4
Median length4
Mean length3.0029851
Min length2

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> 672
50.1%
자동 666
49.7%
수동 2
 
0.1%

Length

2024-05-11T08:50:48.851876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:49.404110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 672
50.1%
자동 666
49.7%
수동 2
 
0.1%

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

총게임기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1214 
0
126 

Length

Max length4
Median length4
Mean length3.7179104
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> 1214
90.6%
0 126
 
9.4%

Length

2024-05-11T08:50:49.895255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:50.247792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1214
90.6%
0 126
 
9.4%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

제공게임물명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1339
Missing (%)99.9%
Memory size10.6 KiB
2024-05-11T08:50:50.575407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row전체이용가
ValueCountFrequency (%)
전체이용가 1
100.0%
2024-05-11T08:50:51.461708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1340
Missing (%)100.0%
Memory size11.9 KiB

지역구분명
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size10.6 KiB
<NA>
1073 
근린상업지역
 
82
준주거지역
 
58
상업지역
 
52
일반주거지역
 
36
Other values (4)
 
39

Length

Max length6
Median length4
Mean length4.2597015
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1073
80.1%
근린상업지역 82
 
6.1%
준주거지역 58
 
4.3%
상업지역 52
 
3.9%
일반주거지역 36
 
2.7%
일반상업지역 26
 
1.9%
주거지역 9
 
0.7%
공업지역 3
 
0.2%
전용주거지역 1
 
0.1%

Length

2024-05-11T08:50:51.867019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:50:52.310790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1073
80.1%
근린상업지역 82
 
6.1%
준주거지역 58
 
4.3%
상업지역 52
 
3.9%
일반주거지역 36
 
2.7%
일반상업지역 26
 
1.9%
주거지역 9
 
0.7%
공업지역 3
 
0.2%
전용주거지역 1
 
0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03220000CDFF12420120100000022010-09-14<NA>3폐업03폐업2023-03-13<NA><NA><NA>070-8119-8582<NA><NA>서울특별시 강남구 역삼동 820-2 지상3층서울특별시 강남구 테헤란로1길 17, 3층 (역삼동)6134해피죤DVD방2023-03-14 11:01:29U2022-12-02 23:06:00.0<NA>202372.354139444139.628295<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>
13170000CDFF12420120100000012010-07-28<NA>3폐업03폐업2012-10-08<NA><NA><NA>02-893-5415<NA><NA>서울특별시 금천구 시흥동 995-8서울특별시 금천구 시흥대로61길 16 (시흥동)8632챌린저DVD2023-02-06 15:21:28U2022-12-02 00:08:00.0<NA>191056.830341439099.231876<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>
23240000CDFF12420119990000021999-07-12<NA>4취소/말소/만료/정지/중지35직권말소2023-02-27<NA><NA><NA>473-1334<NA><NA>서울특별시 강동구 천호동 453-8 지1층서울특별시 강동구 천호대로157길 18 (천호동,지1층)<NA>스타비디오2023-02-27 10:07:06U2022-12-03 00:01:00.0<NA>211218.957284448493.145289<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>
33000000CDFF124201200900000220091029<NA>4취소/말소/만료/정지/중지35직권말소20220412<NA><NA><NA>02-745-1209<NA><NA>서울특별시 종로구 명륜2가 184서울특별시 종로구 대명길 40 (명륜2가)3077고구마 DVD 영화관2022-04-13 13:52:50U2021-12-03 23:05:00.0<NA>199874.787633453425.076273<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>
43000000CDFF124201200700000220071211<NA>4취소/말소/만료/정지/중지35직권말소20220412<NA><NA><NA><NA><NA><NA>서울특별시 종로구 관철동 13-1 5층서울특별시 종로구 삼일대로19길 15 (관철동,5층)<NA>DVD 키네마2022-04-13 13:52:21U2021-12-03 23:05:00.0<NA>198757.128601451907.113718<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>
53220000CDFF12420119980000021998-12-03<NA>3폐업03폐업2023-03-13<NA><NA><NA>565-2818<NA><NA>서울특별시 강남구 역삼동 818-1 3층서울특별시 강남구 강남대로96길 12, 3층 (역삼동)6129무비죤2023-03-14 11:01:37U2022-12-02 23:06:00.0<NA>202405.477341444167.897179<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>
63040000CDFF124201199900001019991117<NA>3폐업03폐업20221118<NA><NA><NA>468-7729<NA><NA>서울특별시 광진구 화양동 7-11 3층서울특별시 광진구 동일로22길 102 (화양동,3층)<NA>베스트비디오방2022-11-18 18:27:52U2021-10-31 22:00:00.0<NA>206084.564569448732.7276<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>
73000000CDFF124201200300000720031217<NA>4취소/말소/만료/정지/중지35직권말소20220412<NA><NA><NA>732-7719<NA><NA>서울특별시 종로구 인사동 75-1서울특별시 종로구 삼일대로 405 (인사동)<NA>씨네월드DVD상영관2022-04-13 13:51:58U2021-12-03 23:05:00.0<NA>198817.599795452054.207891<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>
83000000CDFF124201200300000320030303<NA>4취소/말소/만료/정지/중지35직권말소20220412<NA><NA><NA><NA><NA><NA>서울특별시 종로구 묘동 197-1서울특별시 종로구 돈화문로 31, 4층 (묘동)3139테마2022-04-13 13:51:31U2021-12-03 23:05:00.0<NA>199202.506933452121.392389<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>
93000000CDFF124201200300000120030115<NA>4취소/말소/만료/정지/중지35직권말소20220412<NA><NA><NA>722-1894<NA><NA>서울특별시 종로구 관철동 12-12서울특별시 종로구 삼일대로15길 26 (관철동)<NA>심야비디오감상실2022-04-13 13:51:07U2021-12-03 23:05:00.0<NA>198698.015512451849.19628<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
13303240000CDFF124201199900000119990614<NA>1영업/정상13영업중<NA><NA><NA><NA>478-5602<NA><NA>서울특별시 강동구 성내동 429-18번지 (3층)서울특별시 강동구 양재대로89가길 10 (성내동,(3층))<NA>영화수첩비디오방2009-09-17 10:17:46I2018-08-31 23:59:59.0<NA>211833.212147447111.892156비디오물감상실업<NA><NA><NA><NA>105.9<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13313240000CDFF124201199600001219960909<NA>1영업/정상13영업중<NA><NA><NA><NA>486-9045<NA><NA>서울특별시 강동구 성내동 443-33번지서울특별시 강동구 양재대로85길 23 (성내동)<NA>디프2014-07-01 16:49:02I2018-08-31 23:59:59.0<NA>211716.731305446924.6137비디오물감상실업<NA><NA><NA><NA>137.99<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13323240000CDFF124201200000000120001223<NA>1영업/정상13영업중<NA><NA><NA><NA>475-0031<NA>134874서울특별시 강동구 천호동 454-65번지 5층서울특별시 강동구 천호대로157길 15 (천호동,5층)<NA>DVD시네마2007-12-03 09:40:33I2018-08-31 23:59:59.0<NA>211146.068506448479.444644비디오물감상실업유통관련업<NA><NA><NA>165.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13333240000CDFF124201200100000320010313<NA>1영업/정상13영업중<NA><NA><NA><NA>487-1398<NA><NA>서울특별시 강동구 천호동 456번지 신라빌딩B1서울특별시 강동구 천호대로 997 (천호동,신라빌딩B1)<NA>현대DVD방2009-09-21 18:16:32I2018-08-31 23:59:59.0<NA>210825.177288448573.814955비디오물감상실업<NA><NA><NA><NA>326.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13343240000CDFF124201200200000120020731<NA>1영업/정상13영업중<NA><NA><NA><NA>488-0789<NA>134814서울특별시 강동구 길동 447-1번지서울특별시 강동구 진황도로 92 (길동)<NA>씨엔에스디비디방2004-07-19 15:45:43I2018-08-31 23:59:59.0<NA>211986.914896448201.841636비디오물감상실업유통관련업<NA><NA><NA>157.58<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자동<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13353220000CDFF124201202200000120220630<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 541서울특별시 강남구 가로수길 22, 지하1층 (신사동)6036보이드2022-06-30 14:20:36I2021-12-07 00:02:00.0<NA>201991.408303446353.146737<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>
13363210000CDFF124201199700000719971125<NA>4취소/말소/만료/정지/중지35직권말소20220706<NA><NA><NA>591-8389<NA><NA>서울특별시 서초구 반포동 19-4 고속버스터미널 지하8-2서울특별시 서초구 신반포로 194 (반포동,고속버스터미널 지하8-2)<NA>씨티비디오감상실2022-07-06 15:43:22U2021-12-07 00:08:00.0<NA>200554.743958444811.364826<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>
13373140000CDFF124201200100000520010724<NA>4취소/말소/만료/정지/중지35직권말소20220711<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 900-21서울특별시 양천구 목동로 213 (신정동)7938규빅비디오감상실2022-08-04 10:36:11U2021-12-08 00:06:00.0<NA>187890.858025447260.880711<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>
13383190000CDFF124201199900000619990730<NA>3폐업03폐업20220831<NA><NA><NA><NA><NA><NA>서울특별시 동작구 노량진동 126-14 2층, 3층서울특별시 동작구 만양로18길 14 (노량진동,2층, 3층)<NA>로드쇼 무비 카페2022-09-01 16:36:42U2021-12-09 00:03:00.0<NA>195067.845312445650.010537<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>
13393110000CDFF124201200000000120000324<NA>3폐업03폐업20220901<NA><NA><NA>356-5888<NA><NA>서울특별시 은평구 갈현동 399-19 ,20,26.지층서울특별시 은평구 연서로29길 8-15 (갈현동)3330멀티비디오방2022-09-02 10:41:26U2021-12-09 00:04:00.0<NA>192835.107836457461.823531<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>