Overview

Dataset statistics

Number of variables56
Number of observations812
Missing cells20866
Missing cells (%)45.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory383.1 KiB
Average record size in memory483.2 B

Variable types

Categorical18
Text6
DateTime4
Unsupported20
Numeric8

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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-16781/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (74.6%)Imbalance
문화체육업종명 is highly imbalanced (57.6%)Imbalance
문화사업자구분명 is highly imbalanced (57.6%)Imbalance
주변환경명 is highly imbalanced (66.9%)Imbalance
지하층수 is highly imbalanced (51.9%)Imbalance
건물용도명 is highly imbalanced (66.0%)Imbalance
통로너비 is highly imbalanced (56.8%)Imbalance
조명시설조도 is highly imbalanced (56.8%)Imbalance
노래방실수 is highly imbalanced (56.8%)Imbalance
청소년실수 is highly imbalanced (56.8%)Imbalance
제공게임물명 is highly imbalanced (70.2%)Imbalance
지역구분명 is highly imbalanced (85.6%)Imbalance
폐업일자 has 333 (41.0%) missing valuesMissing
휴업시작일자 has 812 (100.0%) missing valuesMissing
휴업종료일자 has 812 (100.0%) missing valuesMissing
재개업일자 has 812 (100.0%) missing valuesMissing
전화번호 has 758 (93.3%) missing valuesMissing
소재지면적 has 812 (100.0%) missing valuesMissing
소재지우편번호 has 516 (63.5%) missing valuesMissing
도로명주소 has 12 (1.5%) missing valuesMissing
도로명우편번호 has 482 (59.4%) missing valuesMissing
업태구분명 has 812 (100.0%) missing valuesMissing
좌표정보(X) has 9 (1.1%) missing valuesMissing
좌표정보(Y) has 9 (1.1%) missing valuesMissing
총층수 has 550 (67.7%) missing valuesMissing
제작취급품목내용 has 810 (99.8%) missing valuesMissing
시설면적 has 277 (34.1%) missing valuesMissing
지상층수 has 516 (63.5%) missing valuesMissing
비상계단여부 has 812 (100.0%) missing valuesMissing
비상구여부 has 812 (100.0%) missing valuesMissing
자동환기여부 has 812 (100.0%) missing valuesMissing
청소년실여부 has 812 (100.0%) missing valuesMissing
특수조명여부 has 812 (100.0%) missing valuesMissing
방음시설여부 has 812 (100.0%) missing valuesMissing
비디오재생기명 has 812 (100.0%) missing valuesMissing
조명시설유무 has 812 (100.0%) missing valuesMissing
음향시설여부 has 812 (100.0%) missing valuesMissing
편의시설여부 has 812 (100.0%) missing valuesMissing
소방시설여부 has 812 (100.0%) missing valuesMissing
총게임기수 has 354 (43.6%) missing valuesMissing
기존게임업외업종명 has 812 (100.0%) missing valuesMissing
공연장형태구분명 has 812 (100.0%) missing valuesMissing
품목명 has 812 (100.0%) missing valuesMissing
최초등록시점 has 812 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
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
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
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 66 (8.1%) zerosZeros
시설면적 has 45 (5.5%) zerosZeros
지상층수 has 59 (7.3%) zerosZeros

Reproduction

Analysis started2024-05-11 04:16:00.630108
Analysis finished2024-05-11 04:16:03.051079
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3140000
812 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 812
100.0%

Length

2024-05-11T04:16:03.249367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:03.586213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 812
100.0%

관리번호
Text

UNIQUE 

Distinct812
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-05-11T04:16:04.221513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters16240
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

Unique812 ?
Unique (%)100.0%

Sample

1st rowCDFF2241021999000001
2nd rowCDFF2241021999000002
3rd rowCDFF2241021999000003
4th rowCDFF2241021999000004
5th rowCDFF2241021999000005
ValueCountFrequency (%)
cdff2241021999000001 1
 
0.1%
cdff2241022010000015 1
 
0.1%
cdff2241022010000006 1
 
0.1%
cdff2241022010000028 1
 
0.1%
cdff2241022010000007 1
 
0.1%
cdff2241022010000008 1
 
0.1%
cdff2241022010000009 1
 
0.1%
cdff2241022010000010 1
 
0.1%
cdff2241022010000011 1
 
0.1%
cdff2241022010000012 1
 
0.1%
Other values (802) 802
98.8%
2024-05-11T04:16:05.421735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5642
34.7%
2 3469
21.4%
F 1624
 
10.0%
1 1571
 
9.7%
4 999
 
6.2%
C 812
 
5.0%
D 812
 
5.0%
9 347
 
2.1%
8 262
 
1.6%
3 200
 
1.2%
Other values (3) 502
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12992
80.0%
Uppercase Letter 3248
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5642
43.4%
2 3469
26.7%
1 1571
 
12.1%
4 999
 
7.7%
9 347
 
2.7%
8 262
 
2.0%
3 200
 
1.5%
7 195
 
1.5%
5 163
 
1.3%
6 144
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
F 1624
50.0%
C 812
25.0%
D 812
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12992
80.0%
Latin 3248
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5642
43.4%
2 3469
26.7%
1 1571
 
12.1%
4 999
 
7.7%
9 347
 
2.7%
8 262
 
2.0%
3 200
 
1.5%
7 195
 
1.5%
5 163
 
1.3%
6 144
 
1.1%
Latin
ValueCountFrequency (%)
F 1624
50.0%
C 812
25.0%
D 812
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16240
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5642
34.7%
2 3469
21.4%
F 1624
 
10.0%
1 1571
 
9.7%
4 999
 
6.2%
C 812
 
5.0%
D 812
 
5.0%
9 347
 
2.1%
8 262
 
1.6%
3 200
 
1.2%
Other values (3) 502
 
3.1%

인허가일자
Date

Distinct597
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum1999-07-12 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T04:16:05.897346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:16:06.396080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct45
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
564 
20070402
203 
20101005
 
2
20090302
 
2
20111123
 
1
Other values (40)
 
40

Length

Max length10
Median length4
Mean length5.2241379
Min length4

Unique

Unique41 ?
Unique (%)5.0%

Sample

1st row20070402
2nd row20070402
3rd row20070402
4th row<NA>
5th row20070402

Common Values

ValueCountFrequency (%)
<NA> 564
69.5%
20070402 203
 
25.0%
20101005 2
 
0.2%
20090302 2
 
0.2%
20111123 1
 
0.1%
20100927 1
 
0.1%
20080717 1
 
0.1%
20090306 1
 
0.1%
20090501 1
 
0.1%
20090301 1
 
0.1%
Other values (35) 35
 
4.3%

Length

2024-05-11T04:16:06.850754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 564
69.5%
20070402 203
 
25.0%
20101005 2
 
0.2%
20090302 2
 
0.2%
20141118 1
 
0.1%
20200110 1
 
0.1%
20161005 1
 
0.1%
20120110 1
 
0.1%
20170111 1
 
0.1%
20190212 1
 
0.1%
Other values (35) 35
 
4.3%

영업상태코드
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3
373 
4
356 
1
83 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 373
45.9%
4 356
43.8%
1 83
 
10.2%

Length

2024-05-11T04:16:07.192170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:07.496670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 373
45.9%
4 356
43.8%
1 83
 
10.2%

영업상태명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
373 
취소/말소/만료/정지/중지
356 
영업/정상
83 

Length

Max length14
Median length5
Mean length7.567734
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 373
45.9%
취소/말소/만료/정지/중지 356
43.8%
영업/정상 83
 
10.2%

Length

2024-05-11T04:16:07.988408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:08.363086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 373
45.9%
취소/말소/만료/정지/중지 356
43.8%
영업/정상 83
 
10.2%

상세영업상태코드
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
03
373 
31
249 
35
106 
13
80 
BBBB
 
3

Length

Max length4
Median length2
Mean length2.0073892
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row31
2nd row31
3rd row31
4th row03
5th row31

Common Values

ValueCountFrequency (%)
03 373
45.9%
31 249
30.7%
35 106
 
13.1%
13 80
 
9.9%
BBBB 3
 
0.4%
30 1
 
0.1%

Length

2024-05-11T04:16:08.844320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:09.316023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03 373
45.9%
31 249
30.7%
35 106
 
13.1%
13 80
 
9.9%
bbbb 3
 
0.4%
30 1
 
0.1%

상세영업상태명
Categorical

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
373 
등록취소
249 
직권말소
106 
영업중
80 
<NA>
 
3

Length

Max length4
Median length3
Mean length2.9827586
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 373
45.9%
등록취소 249
30.7%
직권말소 106
 
13.1%
영업중 80
 
9.9%
<NA> 3
 
0.4%
허가취소 1
 
0.1%

Length

2024-05-11T04:16:09.943615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:10.441318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 373
45.9%
등록취소 249
30.7%
직권말소 106
 
13.1%
영업중 80
 
9.9%
na 3
 
0.4%
허가취소 1
 
0.1%

폐업일자
Date

MISSING 

Distinct362
Distinct (%)75.6%
Missing333
Missing (%)41.0%
Memory size6.5 KiB
Minimum2000-02-28 00:00:00
Maximum2024-02-22 00:00:00
2024-05-11T04:16:10.962220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:16:11.574849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

전화번호
Text

MISSING 

Distinct54
Distinct (%)100.0%
Missing758
Missing (%)93.3%
Memory size6.5 KiB
2024-05-11T04:16:12.294854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9.6111111
Min length9

Characters and Unicode

Total characters519
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

Unique54 ?
Unique (%)100.0%

Sample

1st row2647-7544
2nd row2694-9193
3rd row2036-2921
4th row2607-2242
5th row2648-8002
ValueCountFrequency (%)
02-2605-0584 1
 
1.9%
3142-2940 1
 
1.9%
2646-8545 1
 
1.9%
2647-0190 1
 
1.9%
2651-2823 1
 
1.9%
2646-0072 1
 
1.9%
2644-3396 1
 
1.9%
2646-6909 1
 
1.9%
2646-0814 1
 
1.9%
2065-9871 1
 
1.9%
Other values (44) 44
81.5%
2024-05-11T04:16:13.720288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 87
16.8%
6 73
14.1%
0 66
12.7%
- 59
11.4%
4 44
8.5%
5 37
7.1%
8 35
6.7%
1 31
 
6.0%
7 31
 
6.0%
9 28
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
88.6%
Dash Punctuation 59
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 87
18.9%
6 73
15.9%
0 66
14.3%
4 44
9.6%
5 37
8.0%
8 35
7.6%
1 31
 
6.7%
7 31
 
6.7%
9 28
 
6.1%
3 28
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 519
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 87
16.8%
6 73
14.1%
0 66
12.7%
- 59
11.4%
4 44
8.5%
5 37
7.1%
8 35
6.7%
1 31
 
6.0%
7 31
 
6.0%
9 28
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 519
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 87
16.8%
6 73
14.1%
0 66
12.7%
- 59
11.4%
4 44
8.5%
5 37
7.1%
8 35
6.7%
1 31
 
6.0%
7 31
 
6.0%
9 28
 
5.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)16.9%
Missing516
Missing (%)63.5%
Infinite0
Infinite (%)0.0%
Mean158789.21
Minimum158050
Maximum158868
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:14.381695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum158050
5-th percentile158070
Q1158816.75
median158838
Q3158852
95-th percentile158864
Maximum158868
Range818
Interquartile range (IQR)35.25

Descriptive statistics

Standard deviation187.20217
Coefficient of variation (CV)0.0011789351
Kurtosis11.417271
Mean158789.21
Median Absolute Deviation (MAD)19
Skewness-3.6266448
Sum47001605
Variance35044.652
MonotonicityNot monotonic
2024-05-11T04:16:14.912460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
158864 19
 
2.3%
158819 16
 
2.0%
158845 14
 
1.7%
158806 14
 
1.7%
158849 13
 
1.6%
158859 11
 
1.4%
158840 11
 
1.4%
158811 10
 
1.2%
158050 10
 
1.2%
158831 9
 
1.1%
Other values (40) 169
 
20.8%
(Missing) 516
63.5%
ValueCountFrequency (%)
158050 10
1.2%
158070 8
1.0%
158724 1
 
0.1%
158803 2
 
0.2%
158806 14
1.7%
158807 4
 
0.5%
158808 9
1.1%
158809 1
 
0.1%
158811 10
1.2%
158812 2
 
0.2%
ValueCountFrequency (%)
158868 1
 
0.1%
158864 19
2.3%
158863 6
 
0.7%
158862 1
 
0.1%
158861 9
1.1%
158860 7
 
0.9%
158859 11
1.4%
158858 5
 
0.6%
158857 6
 
0.7%
158856 7
 
0.9%

지번주소
Text

Distinct751
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-05-11T04:16:15.563850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length25.112069
Min length18

Characters and Unicode

Total characters20391
Distinct characters149
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

Unique696 ?
Unique (%)85.7%

Sample

1st row서울특별시 양천구 신월동 145-5번지 지상2층
2nd row서울특별시 양천구 신정동 114-12번지 3층
3rd row서울특별시 양천구 신월동 147-3번지
4th row서울특별시 양천구 신정동 1031-2번지
5th row서울특별시 양천구 신정동 202-10번지
ValueCountFrequency (%)
서울특별시 812
20.8%
양천구 812
20.8%
신월동 313
 
8.0%
신정동 288
 
7.4%
목동 213
 
5.5%
2층 117
 
3.0%
1층 117
 
3.0%
지하1층 74
 
1.9%
3층 57
 
1.5%
지층 27
 
0.7%
Other values (766) 1076
27.5%
2024-05-11T04:16:16.957992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3791
18.6%
1 1193
 
5.9%
동 847
 
4.2%
양 813
 
4.0%
서 813
 
4.0%
시 813
 
4.0%
별 812
 
4.0%
천 812
 
4.0%
구 812
 
4.0%
울 812
 
4.0%
Other values (139) 8873
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11311
55.5%
Decimal Number 4445
 
21.8%
Space Separator 3791
 
18.6%
Dash Punctuation 798
 
3.9%
Uppercase Letter 14
 
0.1%
Other Punctuation 13
 
0.1%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 847
 
7.5%
양 813
 
7.2%
서 813
 
7.2%
시 813
 
7.2%
별 812
 
7.2%
천 812
 
7.2%
구 812
 
7.2%
울 812
 
7.2%
특 812
 
7.2%
지 767
 
6.8%
Other values (115) 3198
28.3%
Decimal Number
ValueCountFrequency (%)
1 1193
26.8%
2 660
14.8%
3 426
 
9.6%
9 387
 
8.7%
0 347
 
7.8%
7 320
 
7.2%
5 307
 
6.9%
4 301
 
6.8%
6 255
 
5.7%
8 249
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 9
64.3%
A 1
 
7.1%
C 1
 
7.1%
P 1
 
7.1%
D 1
 
7.1%
W 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 7
53.8%
. 5
38.5%
/ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
3791
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11311
55.5%
Common 9066
44.5%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 847
 
7.5%
양 813
 
7.2%
서 813
 
7.2%
시 813
 
7.2%
별 812
 
7.2%
천 812
 
7.2%
구 812
 
7.2%
울 812
 
7.2%
특 812
 
7.2%
지 767
 
6.8%
Other values (115) 3198
28.3%
Common
ValueCountFrequency (%)
3791
41.8%
1 1193
 
13.2%
- 798
 
8.8%
2 660
 
7.3%
3 426
 
4.7%
9 387
 
4.3%
0 347
 
3.8%
7 320
 
3.5%
5 307
 
3.4%
4 301
 
3.3%
Other values (8) 536
 
5.9%
Latin
ValueCountFrequency (%)
B 9
64.3%
A 1
 
7.1%
C 1
 
7.1%
P 1
 
7.1%
D 1
 
7.1%
W 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11311
55.5%
ASCII 9080
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3791
41.8%
1 1193
 
13.1%
- 798
 
8.8%
2 660
 
7.3%
3 426
 
4.7%
9 387
 
4.3%
0 347
 
3.8%
7 320
 
3.5%
5 307
 
3.4%
4 301
 
3.3%
Other values (14) 550
 
6.1%
Hangul
ValueCountFrequency (%)
동 847
 
7.5%
양 813
 
7.2%
서 813
 
7.2%
시 813
 
7.2%
별 812
 
7.2%
천 812
 
7.2%
구 812
 
7.2%
울 812
 
7.2%
특 812
 
7.2%
지 767
 
6.8%
Other values (115) 3198
28.3%

도로명주소
Text

MISSING 

Distinct744
Distinct (%)93.0%
Missing12
Missing (%)1.5%
Memory size6.5 KiB
2024-05-11T04:16:17.669888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length28.49
Min length22

Characters and Unicode

Total characters22792
Distinct characters164
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

Unique694 ?
Unique (%)86.8%

Sample

1st row서울특별시 양천구 곰달래로5길 81 (신월동,지상2층)
2nd row서울특별시 양천구 신목로 33 (신정동,3층)
3rd row서울특별시 양천구 남부순환로 354 (신월동)
4th row서울특별시 양천구 중앙로 274 (신정동)
5th row서울특별시 양천구 목동남로2길 29 (신정동)
ValueCountFrequency (%)
서울특별시 800
 
18.4%
양천구 800
 
18.4%
신월동 174
 
4.0%
신정동 163
 
3.7%
목동 119
 
2.7%
오목로 63
 
1.4%
1층 59
 
1.4%
지양로 56
 
1.3%
신월로 55
 
1.3%
중앙로 50
 
1.1%
Other values (566) 2011
46.2%
2024-05-11T04:16:19.200064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4024
 
17.7%
동 1031
 
4.5%
양 866
 
3.8%
1 844
 
3.7%
서 842
 
3.7%
로 819
 
3.6%
( 807
 
3.5%
) 807
 
3.5%
시 802
 
3.5%
구 800
 
3.5%
Other values (154) 11150
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13321
58.4%
Space Separator 4024
 
17.7%
Decimal Number 3136
 
13.8%
Open Punctuation 807
 
3.5%
Close Punctuation 807
 
3.5%
Other Punctuation 598
 
2.6%
Dash Punctuation 80
 
0.4%
Uppercase Letter 14
 
0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1031
 
7.7%
양 866
 
6.5%
서 842
 
6.3%
로 819
 
6.1%
시 802
 
6.0%
구 800
 
6.0%
특 800
 
6.0%
울 800
 
6.0%
천 800
 
6.0%
별 800
 
6.0%
Other values (130) 4961
37.2%
Decimal Number
ValueCountFrequency (%)
1 844
26.9%
2 545
17.4%
3 356
11.4%
0 284
 
9.1%
6 223
 
7.1%
4 210
 
6.7%
5 209
 
6.7%
7 183
 
5.8%
9 146
 
4.7%
8 136
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 10
71.4%
A 2
 
14.3%
W 1
 
7.1%
D 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 594
99.3%
. 3
 
0.5%
/ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
4024
100.0%
Open Punctuation
ValueCountFrequency (%)
( 807
100.0%
Close Punctuation
ValueCountFrequency (%)
) 807
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13321
58.4%
Common 9455
41.5%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1031
 
7.7%
양 866
 
6.5%
서 842
 
6.3%
로 819
 
6.1%
시 802
 
6.0%
구 800
 
6.0%
특 800
 
6.0%
울 800
 
6.0%
천 800
 
6.0%
별 800
 
6.0%
Other values (130) 4961
37.2%
Common
ValueCountFrequency (%)
4024
42.6%
1 844
 
8.9%
( 807
 
8.5%
) 807
 
8.5%
, 594
 
6.3%
2 545
 
5.8%
3 356
 
3.8%
0 284
 
3.0%
6 223
 
2.4%
4 210
 
2.2%
Other values (8) 761
 
8.0%
Latin
ValueCountFrequency (%)
B 10
62.5%
A 2
 
12.5%
s 1
 
6.2%
k 1
 
6.2%
W 1
 
6.2%
D 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13321
58.4%
ASCII 9471
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4024
42.5%
1 844
 
8.9%
( 807
 
8.5%
) 807
 
8.5%
, 594
 
6.3%
2 545
 
5.8%
3 356
 
3.8%
0 284
 
3.0%
6 223
 
2.4%
4 210
 
2.2%
Other values (14) 777
 
8.2%
Hangul
ValueCountFrequency (%)
동 1031
 
7.7%
양 866
 
6.5%
서 842
 
6.3%
로 819
 
6.1%
시 802
 
6.0%
구 800
 
6.0%
특 800
 
6.0%
울 800
 
6.0%
천 800
 
6.0%
별 800
 
6.0%
Other values (130) 4961
37.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct99
Distinct (%)30.0%
Missing482
Missing (%)59.4%
Infinite0
Infinite (%)0.0%
Mean29007.064
Minimum7903
Maximum158864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:19.859262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7903
5-th percentile7908.35
Q17940
median7983
Q38073
95-th percentile158853.4
Maximum158864
Range150961
Interquartile range (IQR)133

Descriptive statistics

Standard deviation52316.601
Coefficient of variation (CV)1.8035814
Kurtosis2.3900964
Mean29007.064
Median Absolute Deviation (MAD)58
Skewness2.0918
Sum9572331
Variance2.7370267 × 109
MonotonicityNot monotonic
2024-05-11T04:16:20.395048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7923 13
 
1.6%
8082 12
 
1.5%
7938 12
 
1.5%
8073 11
 
1.4%
7925 11
 
1.4%
7945 10
 
1.2%
7965 9
 
1.1%
7968 9
 
1.1%
8007 8
 
1.0%
7943 8
 
1.0%
Other values (89) 227
28.0%
(Missing) 482
59.4%
ValueCountFrequency (%)
7903 2
 
0.2%
7905 3
0.4%
7906 5
0.6%
7907 7
0.9%
7910 4
0.5%
7911 4
0.5%
7917 5
0.6%
7920 5
0.6%
7921 3
0.4%
7922 2
 
0.2%
ValueCountFrequency (%)
158864 2
0.2%
158861 3
0.4%
158860 4
0.5%
158859 3
0.4%
158858 1
 
0.1%
158857 4
0.5%
158849 1
 
0.1%
158846 1
 
0.1%
158845 2
0.2%
158844 1
 
0.1%

사업장명
Text

Distinct721
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-05-11T04:16:21.970349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.3423645
Min length2

Characters and Unicode

Total characters5150
Distinct characters427
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique661 ?
Unique (%)81.4%

Sample

1st rowCH-1328
2nd rowTHE.TEAM
3rd row원오원 인터넷 PC방
4th row아라크네
5th rowPC마을
ValueCountFrequency (%)
pc방 98
 
8.6%
pc 86
 
7.5%
인터넷 26
 
2.3%
대박pc 13
 
1.1%
pc클럽 11
 
1.0%
jj 8
 
0.7%
zone 7
 
0.6%
vj 6
 
0.5%
목동점 6
 
0.5%
인터넷pc방 5
 
0.4%
Other values (736) 874
76.7%
2024-05-11T04:16:23.728824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 562
 
10.9%
C 560
 
10.9%
330
 
6.4%
방 302
 
5.9%
이 149
 
2.9%
스 104
 
2.0%
넷 103
 
2.0%
인 94
 
1.8%
아 86
 
1.7%
터 86
 
1.7%
Other values (417) 2774
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3049
59.2%
Uppercase Letter 1466
28.5%
Space Separator 330
 
6.4%
Lowercase Letter 152
 
3.0%
Decimal Number 47
 
0.9%
Open Punctuation 32
 
0.6%
Close Punctuation 32
 
0.6%
Other Punctuation 27
 
0.5%
Dash Punctuation 15
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 302
 
9.9%
이 149
 
4.9%
스 104
 
3.4%
넷 103
 
3.4%
인 94
 
3.1%
아 86
 
2.8%
터 86
 
2.8%
점 62
 
2.0%
리 60
 
2.0%
피 59
 
1.9%
Other values (353) 1944
63.8%
Uppercase Letter
ValueCountFrequency (%)
P 562
38.3%
C 560
38.2%
E 41
 
2.8%
J 34
 
2.3%
N 31
 
2.1%
O 28
 
1.9%
T 26
 
1.8%
A 23
 
1.6%
Z 19
 
1.3%
I 17
 
1.2%
Other values (15) 125
 
8.5%
Lowercase Letter
ValueCountFrequency (%)
p 40
26.3%
c 35
23.0%
e 15
 
9.9%
n 11
 
7.2%
o 10
 
6.6%
a 7
 
4.6%
i 6
 
3.9%
u 5
 
3.3%
x 4
 
2.6%
l 4
 
2.6%
Other values (10) 15
 
9.9%
Decimal Number
ValueCountFrequency (%)
2 15
31.9%
1 13
27.7%
3 7
14.9%
0 4
 
8.5%
7 3
 
6.4%
9 2
 
4.3%
4 1
 
2.1%
8 1
 
2.1%
5 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 22
81.5%
& 2
 
7.4%
! 2
 
7.4%
% 1
 
3.7%
Open Punctuation
ValueCountFrequency (%)
( 31
96.9%
[ 1
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 31
96.9%
] 1
 
3.1%
Space Separator
ValueCountFrequency (%)
330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3047
59.2%
Latin 1618
31.4%
Common 483
 
9.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 302
 
9.9%
이 149
 
4.9%
스 104
 
3.4%
넷 103
 
3.4%
인 94
 
3.1%
아 86
 
2.8%
터 86
 
2.8%
점 62
 
2.0%
리 60
 
2.0%
피 59
 
1.9%
Other values (351) 1942
63.7%
Latin
ValueCountFrequency (%)
P 562
34.7%
C 560
34.6%
E 41
 
2.5%
p 40
 
2.5%
c 35
 
2.2%
J 34
 
2.1%
N 31
 
1.9%
O 28
 
1.7%
T 26
 
1.6%
A 23
 
1.4%
Other values (35) 238
14.7%
Common
ValueCountFrequency (%)
330
68.3%
( 31
 
6.4%
) 31
 
6.4%
. 22
 
4.6%
- 15
 
3.1%
2 15
 
3.1%
1 13
 
2.7%
3 7
 
1.4%
0 4
 
0.8%
7 3
 
0.6%
Other values (9) 12
 
2.5%
Han
ValueCountFrequency (%)
生 1
50.0%
死 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3047
59.2%
ASCII 2101
40.8%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 562
26.7%
C 560
26.7%
330
15.7%
E 41
 
2.0%
p 40
 
1.9%
c 35
 
1.7%
J 34
 
1.6%
N 31
 
1.5%
( 31
 
1.5%
) 31
 
1.5%
Other values (54) 406
19.3%
Hangul
ValueCountFrequency (%)
방 302
 
9.9%
이 149
 
4.9%
스 104
 
3.4%
넷 103
 
3.4%
인 94
 
3.1%
아 86
 
2.8%
터 86
 
2.8%
점 62
 
2.0%
리 60
 
2.0%
피 59
 
1.9%
Other values (351) 1942
63.7%
CJK
ValueCountFrequency (%)
生 1
50.0%
死 1
50.0%

최종수정일자
Date

Distinct763
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2002-10-22 17:41:01
Maximum2024-05-02 09:20:45
2024-05-11T04:16:24.322783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:16:24.817035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
I
602 
U
210 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 602
74.1%
U 210
 
25.9%

Length

2024-05-11T04:16:25.261746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:25.576129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 602
74.1%
u 210
 
25.9%

데이터갱신일자
Date

Distinct129
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T04:16:25.910675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:16:26.347174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct518
Distinct (%)64.5%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean186886.79
Minimum184457.85
Maximum189709.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:26.850525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184457.85
5-th percentile184985.79
Q1185581.01
median186978.08
Q3187968.5
95-th percentile188918.36
Maximum189709.8
Range5251.9513
Interquartile range (IQR)2387.4833

Descriptive statistics

Standard deviation1332.815
Coefficient of variation (CV)0.0071316703
Kurtosis-1.253135
Mean186886.79
Median Absolute Deviation (MAD)1111.676
Skewness-0.013336315
Sum1.500701 × 108
Variance1776395.8
MonotonicityNot monotonic
2024-05-11T04:16:27.282138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185692.551545586 14
 
1.7%
186009.348428578 8
 
1.0%
187923.919592336 7
 
0.9%
186953.199757922 7
 
0.9%
185164.274611167 5
 
0.6%
187219.776938727 5
 
0.6%
188780.516711776 5
 
0.6%
186925.884838357 4
 
0.5%
185152.306258581 4
 
0.5%
186943.28186023 4
 
0.5%
Other values (508) 740
91.1%
(Missing) 9
 
1.1%
ValueCountFrequency (%)
184457.852171363 1
0.1%
184490.797137375 1
0.1%
184537.639604228 1
0.1%
184571.315447564 1
0.1%
184574.628915728 1
0.1%
184582.382083153 1
0.1%
184585.101058153 2
0.2%
184607.541032125 1
0.1%
184625.70334445 1
0.1%
184647.036987491 1
0.1%
ValueCountFrequency (%)
189709.803505321 1
 
0.1%
189643.735000001 1
 
0.1%
189512.045139098 1
 
0.1%
189348.372526225 4
0.5%
189332.773428473 1
 
0.1%
189280.689807363 1
 
0.1%
189251.065 2
0.2%
189151.208015925 4
0.5%
189092.945269213 1
 
0.1%
189084.518748788 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct518
Distinct (%)64.5%
Missing9
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean447309.72
Minimum445021.4
Maximum449843.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:27.715662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445021.4
5-th percentile446103.28
Q1446549.19
median447039.65
Q3447951.52
95-th percentile449375.44
Maximum449843.2
Range4821.799
Interquartile range (IQR)1402.3264

Descriptive statistics

Standard deviation1034.5025
Coefficient of variation (CV)0.0023127208
Kurtosis-0.28659725
Mean447309.72
Median Absolute Deviation (MAD)668.79839
Skewness0.5408292
Sum3.591897 × 108
Variance1070195.4
MonotonicityNot monotonic
2024-05-11T04:16:28.166775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447374.522041433 14
 
1.7%
446302.275471851 8
 
1.0%
447850.891096367 7
 
0.9%
446282.381840537 7
 
0.9%
446701.013450812 5
 
0.6%
447006.977030483 5
 
0.6%
449375.975876165 5
 
0.6%
446522.764708979 4
 
0.5%
447932.268189185 4
 
0.5%
446311.109320231 4
 
0.5%
Other values (508) 740
91.1%
(Missing) 9
 
1.1%
ValueCountFrequency (%)
445021.404026362 1
 
0.1%
445039.928375227 1
 
0.1%
445081.396522145 1
 
0.1%
445113.109971419 3
0.4%
445124.131588947 1
 
0.1%
445142.765 1
 
0.1%
445155.081213627 1
 
0.1%
445166.926423154 1
 
0.1%
445180.40867328 3
0.4%
445180.546993674 1
 
0.1%
ValueCountFrequency (%)
449843.203005652 2
0.2%
449833.140237863 2
0.2%
449804.270313845 1
0.1%
449785.227427003 1
0.1%
449783.451870726 1
0.1%
449763.347390512 1
0.1%
449753.158413664 2
0.2%
449673.074674822 1
0.1%
449635.632611714 1
0.1%
449627.820984369 1
0.1%

문화체육업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
인터넷컴퓨터게임시설제공업
742 
<NA>
 
70

Length

Max length13
Median length13
Mean length12.224138
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인터넷컴퓨터게임시설제공업 742
91.4%
<NA> 70
 
8.6%

Length

2024-05-11T04:16:28.605148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:28.928580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인터넷컴퓨터게임시설제공업 742
91.4%
na 70
 
8.6%

문화사업자구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
유통관련업
742 
<NA>
 
70

Length

Max length5
Median length5
Mean length4.9137931
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통관련업 742
91.4%
<NA> 70
 
8.6%

Length

2024-05-11T04:16:29.225361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:29.558872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 742
91.4%
na 70
 
8.6%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)5.0%
Missing550
Missing (%)67.7%
Infinite0
Infinite (%)0.0%
Mean3.5267176
Minimum0
Maximum30
Zeros66
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:29.933478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median4
Q35
95-th percentile6
Maximum30
Range30
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.2479366
Coefficient of variation (CV)0.92095171
Kurtosis30.232444
Mean3.5267176
Median Absolute Deviation (MAD)1
Skewness3.9210951
Sum924
Variance10.549092
MonotonicityNot monotonic
2024-05-11T04:16:30.329595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4 80
 
9.9%
0 66
 
8.1%
5 55
 
6.8%
3 23
 
2.8%
6 16
 
2.0%
7 6
 
0.7%
2 5
 
0.6%
1 4
 
0.5%
9 2
 
0.2%
8 2
 
0.2%
Other values (3) 3
 
0.4%
(Missing) 550
67.7%
ValueCountFrequency (%)
0 66
8.1%
1 4
 
0.5%
2 5
 
0.6%
3 23
 
2.8%
4 80
9.9%
5 55
6.8%
6 16
 
2.0%
7 6
 
0.7%
8 2
 
0.2%
9 2
 
0.2%
ValueCountFrequency (%)
30 1
 
0.1%
29 1
 
0.1%
15 1
 
0.1%
9 2
 
0.2%
8 2
 
0.2%
7 6
 
0.7%
6 16
 
2.0%
5 55
6.8%
4 80
9.9%
3 23
 
2.8%

주변환경명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
684 
학교정화(상대)
 
53
주택가주변
 
41
기타
 
23
아파트지역
 
6
Other values (2)
 
5

Length

Max length8
Median length4
Mean length4.2869458
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row학교정화(상대)
3rd row기타
4th row기타
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 684
84.2%
학교정화(상대) 53
 
6.5%
주택가주변 41
 
5.0%
기타 23
 
2.8%
아파트지역 6
 
0.7%
학교정화(절대) 4
 
0.5%
유흥업소밀집지역 1
 
0.1%

Length

2024-05-11T04:16:30.766739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:31.270546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 684
84.2%
학교정화(상대 53
 
6.5%
주택가주변 41
 
5.0%
기타 23
 
2.8%
아파트지역 6
 
0.7%
학교정화(절대 4
 
0.5%
유흥업소밀집지역 1
 
0.1%

제작취급품목내용
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing810
Missing (%)99.8%
Memory size6.5 KiB
2024-05-11T04:16:31.626734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5
Min length3

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row도나크
2nd row고스톱,바둑이
ValueCountFrequency (%)
도나크 1
50.0%
고스톱,바둑이 1
50.0%
2024-05-11T04:16:32.711746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 1
10.0%
나 1
10.0%
크 1
10.0%
고 1
10.0%
스 1
10.0%
톱 1
10.0%
, 1
10.0%
바 1
10.0%
둑 1
10.0%
이 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
90.0%
Other Punctuation 1
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1
11.1%
나 1
11.1%
크 1
11.1%
고 1
11.1%
스 1
11.1%
톱 1
11.1%
바 1
11.1%
둑 1
11.1%
이 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
90.0%
Common 1
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1
11.1%
나 1
11.1%
크 1
11.1%
고 1
11.1%
스 1
11.1%
톱 1
11.1%
바 1
11.1%
둑 1
11.1%
이 1
11.1%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
90.0%
ASCII 1
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 1
11.1%
나 1
11.1%
크 1
11.1%
고 1
11.1%
스 1
11.1%
톱 1
11.1%
바 1
11.1%
둑 1
11.1%
이 1
11.1%
ASCII
ValueCountFrequency (%)
, 1
100.0%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct384
Distinct (%)71.8%
Missing277
Missing (%)34.1%
Infinite0
Infinite (%)0.0%
Mean106.68673
Minimum0
Maximum499.68
Zeros45
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:33.140989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131.7
median97.17
Q3156.555
95-th percentile261.253
Maximum499.68
Range499.68
Interquartile range (IQR)124.855

Descriptive statistics

Standard deviation88.729462
Coefficient of variation (CV)0.83168228
Kurtosis2.234218
Mean106.68673
Median Absolute Deviation (MAD)64.17
Skewness1.2002949
Sum57077.4
Variance7872.9175
MonotonicityNot monotonic
2024-05-11T04:16:33.671524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 45
 
5.5%
33.0 12
 
1.5%
30.0 7
 
0.9%
24.0 5
 
0.6%
26.0 5
 
0.6%
80.73 4
 
0.5%
28.0 4
 
0.5%
168.3 4
 
0.5%
20.0 3
 
0.4%
115.37 3
 
0.4%
Other values (374) 443
54.6%
(Missing) 277
34.1%
ValueCountFrequency (%)
0.0 45
5.5%
7.87 1
 
0.1%
10.4 1
 
0.1%
13.2 1
 
0.1%
15.0 2
 
0.2%
15.07 1
 
0.1%
16.53 1
 
0.1%
16.8 1
 
0.1%
18.0 3
 
0.4%
18.15 1
 
0.1%
ValueCountFrequency (%)
499.68 1
0.1%
498.0 1
0.1%
496.0 1
0.1%
484.81 1
0.1%
431.32 1
0.1%
396.83 1
0.1%
373.65 1
0.1%
362.4 1
0.1%
346.66 1
0.1%
343.14 1
0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)3.4%
Missing516
Missing (%)63.5%
Infinite0
Infinite (%)0.0%
Mean2.6824324
Minimum0
Maximum24
Zeros59
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:34.112275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile5
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4245556
Coefficient of variation (CV)0.90386457
Kurtosis35.365547
Mean2.6824324
Median Absolute Deviation (MAD)1
Skewness4.2574356
Sum794
Variance5.87847
MonotonicityNot monotonic
2024-05-11T04:16:34.517249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 89
 
11.0%
0 59
 
7.3%
4 57
 
7.0%
2 36
 
4.4%
1 25
 
3.1%
5 17
 
2.1%
6 9
 
1.1%
8 2
 
0.2%
24 1
 
0.1%
23 1
 
0.1%
(Missing) 516
63.5%
ValueCountFrequency (%)
0 59
7.3%
1 25
 
3.1%
2 36
4.4%
3 89
11.0%
4 57
7.0%
5 17
 
2.1%
6 9
 
1.1%
8 2
 
0.2%
23 1
 
0.1%
24 1
 
0.1%
ValueCountFrequency (%)
24 1
 
0.1%
23 1
 
0.1%
8 2
 
0.2%
6 9
 
1.1%
5 17
 
2.1%
4 57
7.0%
3 89
11.0%
2 36
4.4%
1 25
 
3.1%
0 59
7.3%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
546 
1
193 
0
66 
2
 
4
6
 
2

Length

Max length4
Median length4
Mean length3.0172414
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 546
67.2%
1 193
 
23.8%
0 66
 
8.1%
2 4
 
0.5%
6 2
 
0.2%
4 1
 
0.1%

Length

2024-05-11T04:16:35.172189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:35.561412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 546
67.2%
1 193
 
23.8%
0 66
 
8.1%
2 4
 
0.5%
6 2
 
0.2%
4 1
 
0.1%

건물용도명
Categorical

IMBALANCE 

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
536 
근린생활시설
267 
연립주택
 
4
기타
 
1
유통시설
 
1
Other values (3)
 
3

Length

Max length6
Median length4
Mean length4.6551724
Min length2

Unique

Unique5 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 536
66.0%
근린생활시설 267
32.9%
연립주택 4
 
0.5%
기타 1
 
0.1%
유통시설 1
 
0.1%
문화시설 1
 
0.1%
단독주택 1
 
0.1%
판매시설 1
 
0.1%

Length

2024-05-11T04:16:36.096880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:36.618951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 536
66.0%
근린생활시설 267
32.9%
연립주택 4
 
0.5%
기타 1
 
0.1%
유통시설 1
 
0.1%
문화시설 1
 
0.1%
단독주택 1
 
0.1%
판매시설 1
 
0.1%

통로너비
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
740 
0
 
72

Length

Max length4
Median length4
Mean length3.7339901
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> 740
91.1%
0 72
 
8.9%

Length

2024-05-11T04:16:37.314828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:37.711931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 740
91.1%
0 72
 
8.9%

조명시설조도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
740 
0
 
72

Length

Max length4
Median length4
Mean length3.7339901
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> 740
91.1%
0 72
 
8.9%

Length

2024-05-11T04:16:38.119725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:38.605255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 740
91.1%
0 72
 
8.9%

노래방실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
740 
0
 
72

Length

Max length4
Median length4
Mean length3.7339901
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> 740
91.1%
0 72
 
8.9%

Length

2024-05-11T04:16:39.083265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:39.449321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 740
91.1%
0 72
 
8.9%

청소년실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
740 
0
 
72

Length

Max length4
Median length4
Mean length3.7339901
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> 740
91.1%
0 72
 
8.9%

Length

2024-05-11T04:16:39.856859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:40.229361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 740
91.1%
0 72
 
8.9%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

총게임기수
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)20.3%
Missing354
Missing (%)43.6%
Infinite0
Infinite (%)0.0%
Mean38.655022
Minimum0
Maximum289
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-05-11T04:16:40.604431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median40
Q355
95-th percentile97.15
Maximum289
Range289
Interquartile range (IQR)47

Descriptive statistics

Standard deviation36.407717
Coefficient of variation (CV)0.94186254
Kurtosis9.014559
Mean38.655022
Median Absolute Deviation (MAD)30
Skewness2.1653287
Sum17704
Variance1325.5219
MonotonicityNot monotonic
2024-05-11T04:16:41.200147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 41
 
5.0%
6 39
 
4.8%
50 33
 
4.1%
8 30
 
3.7%
9 22
 
2.7%
5 20
 
2.5%
10 19
 
2.3%
53 13
 
1.6%
51 12
 
1.5%
56 11
 
1.4%
Other values (83) 218
26.8%
(Missing) 354
43.6%
ValueCountFrequency (%)
0 2
 
0.2%
4 2
 
0.2%
5 20
2.5%
6 39
4.8%
7 41
5.0%
8 30
3.7%
9 22
2.7%
10 19
2.3%
11 5
 
0.6%
12 3
 
0.4%
ValueCountFrequency (%)
289 1
0.1%
238 1
0.1%
237 1
0.1%
199 1
0.1%
169 1
0.1%
165 1
0.1%
153 1
0.1%
143 2
0.2%
140 2
0.2%
135 1
0.1%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

제공게임물명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
739 
전체이용가
 
67
청소년이용불가
 
6

Length

Max length7
Median length4
Mean length4.1046798
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 (%)
<NA> 739
91.0%
전체이용가 67
 
8.3%
청소년이용불가 6
 
0.7%

Length

2024-05-11T04:16:41.678732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:42.061689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 739
91.0%
전체이용가 67
 
8.3%
청소년이용불가 6
 
0.7%

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing812
Missing (%)100.0%
Memory size7.3 KiB

지역구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
767 
일반주거지역
 
24
주거지역
 
14
준주거지역
 
3
상업지역
 
2
Other values (2)
 
2

Length

Max length6
Median length4
Mean length4.0652709
Min length4

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 767
94.5%
일반주거지역 24
 
3.0%
주거지역 14
 
1.7%
준주거지역 3
 
0.4%
상업지역 2
 
0.2%
일반상업지역 1
 
0.1%
관리지역 1
 
0.1%

Length

2024-05-11T04:16:42.589491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:16:43.236023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 767
94.5%
일반주거지역 24
 
3.0%
주거지역 14
 
1.7%
준주거지역 3
 
0.4%
상업지역 2
 
0.2%
일반상업지역 1
 
0.1%
관리지역 1
 
0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03140000CDFF224102199900000119990712200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158828서울특별시 양천구 신월동 145-5번지 지상2층서울특별시 양천구 곰달래로5길 81 (신월동,지상2층)<NA>CH-13282008-04-02 11:32:30I2018-08-31 23:59:59.0<NA>184849.094398448131.515051인터넷컴퓨터게임시설제공업유통관련업<NA><NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13140000CDFF224102199900000219990716200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158849서울특별시 양천구 신정동 114-12번지 3층서울특별시 양천구 신목로 33 (신정동,3층)<NA>THE.TEAM2008-04-02 11:33:02I2018-08-31 23:59:59.0<NA>188746.764802446254.72628인터넷컴퓨터게임시설제공업유통관련업<NA>학교정화(상대)<NA><NA><NA><NA>연립주택<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23140000CDFF224102199900000319990816200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158829서울특별시 양천구 신월동 147-3번지서울특별시 양천구 남부순환로 354 (신월동)<NA>원오원 인터넷 PC방2008-04-02 11:33:20I2018-08-31 23:59:59.0<NA>184748.571713448142.580281인터넷컴퓨터게임시설제공업유통관련업<NA>기타<NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33140000CDFF224102199900000419990904<NA>3폐업03폐업20010312<NA><NA><NA><NA><NA>158070서울특별시 양천구 신정동 1031-2번지서울특별시 양천구 중앙로 274 (신정동)<NA>아라크네2002-10-22 17:41:01I2018-08-31 23:59:59.0<NA>186936.178192446507.437323인터넷컴퓨터게임시설제공업유통관련업<NA>기타<NA>0.0<NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43140000CDFF224102199900000519990917200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158851서울특별시 양천구 신정동 202-10번지서울특별시 양천구 목동남로2길 29 (신정동)<NA>PC마을2008-04-02 11:33:44I2018-08-31 23:59:59.0<NA>187961.25482445021.404026인터넷컴퓨터게임시설제공업유통관련업<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>
53140000CDFF224102199900000619990921<NA>3폐업03폐업20011228<NA><NA><NA><NA><NA>158838서울특별시 양천구 신월동 492-16번지 2층서울특별시 양천구 오목로 75 (신월동,2층)<NA>퍼팩트PC방2002-10-22 17:41:01I2018-08-31 23:59:59.0<NA>186302.868074446772.054243인터넷컴퓨터게임시설제공업유통관련업<NA>학교정화(상대)<NA>0.0<NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63140000CDFF224102199900000719990929200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158857서울특별시 양천구 신정동 902-13번지서울특별시 양천구 오목로 227 (신정동)<NA>클릭!!PC방2008-04-02 11:34:07I2018-08-31 23:59:59.0<NA>187796.641104447102.058469인터넷컴퓨터게임시설제공업유통관련업<NA><NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>주거지역
73140000CDFF224102199900000819991018200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158811서울특별시 양천구 목동 616-2번지서울특별시 양천구 목동중앙북로 12 (목동)<NA>인터넷참피언2008-04-02 11:34:24I2018-08-31 23:59:59.0<NA>187988.189388449573.933274인터넷컴퓨터게임시설제공업유통관련업<NA><NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83140000CDFF224102199900000919991021200704024취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158840서울특별시 양천구 신월동 534-25번지서울특별시 양천구 신월로 191 (신월동)<NA>싸이버 스페이스2008-04-02 11:34:45I2018-08-31 23:59:59.0<NA>186129.6508446424.10743인터넷컴퓨터게임시설제공업유통관련업4<NA><NA><NA>31근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93140000CDFF224102199900001019991106<NA>3폐업03폐업20000816<NA><NA><NA><NA><NA>158806서울특별시 양천구 목동 406-5번지 2층<NA><NA>시샵2002-10-22 17:41:01I2018-08-31 23:59:59.0<NA><NA><NA>인터넷컴퓨터게임시설제공업유통관련업5<NA><NA>0.032근린생활시설<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
8023140000CDFF22410220230000012023-01-17<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1182-2 401호서울특별시 양천구 중앙로 251, 4층 401호 (신정동)8073칠성PC2023-08-29 13:25:28U2022-12-07 21:01:00.0<NA>186953.199758446282.381841<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>
8033140000CDFF22410220230000022023-02-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 175-1서울특별시 양천구 목동남로4길 32 (신정동)8104제로100 PC 신정점2023-02-08 17:23:54I2022-12-01 23:00:00.0<NA>188090.288494445188.515421<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>
8043140000CDFF22410220230000032023-02-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 911-7서울특별시 양천구 신정중앙로 62, 1층 3호 (신정동)7944킹덤PC2024-04-23 08:49:56U2023-12-03 22:05:00.0<NA>187436.998527447184.745108<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>
8053140000CDFF22410220230000042023-05-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 98-39서울특별시 양천구 곰달래로5길 62, 1층 (신월동)7917스타PC2024-04-08 13:34:17U2023-12-03 23:00:00.0<NA>185067.588089448085.036955<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>
8063140000CDFF22410220230000052023-08-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 932-1서울특별시 양천구 지양로 79, 2층층 (신월동)8037행운PC2023-11-09 18:00:33U2022-10-31 23:01:00.0<NA>185164.274611446701.013451<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>
8073140000CDFF22410220230000062023-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 137-19서울특별시 양천구 곰달래로5길 49-1, 1층 (신월동)7920콩이PC2023-11-02 16:58:19I2022-11-01 00:04:00.0<NA>185094.060623447968.452541<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>
8083140000CDFF22410220230000072023-11-14<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 497-4 대명이튼캐슬서울특별시 양천구 목동중앙본로 107, 1층 104호 (목동, 대명이튼캐슬)7948대박pc2024-03-13 09:05:18U2023-12-02 23:06:00.0<NA>188509.227318449220.428989<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>
8093140000CDFF22410220240000012024-02-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 68-14서울특별시 양천구 월정로 220, 1층 (신월동)7907망고PC2024-02-02 09:14:14I2023-12-02 00:04:00.0<NA>185225.007214448427.7556<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>
8103140000CDFF22410220240000022024-03-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 68-12서울특별시 양천구 월정로 218, 1층 (신월동)7907유이PC2024-03-08 14:01:08I2023-12-02 23:00:00.0<NA>185233.53248448410.511726<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>
8113140000CDFF22410220240000032024-03-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 972-2 목동미르웰한올림서울특별시 양천구 중앙로 286, 지하1층 B02호 (신정동, 목동미르웰한올림)8026경동성인PC2024-03-28 14:22:16I2023-12-02 21:00:00.0<NA>186890.0602446630.638222<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>