Overview

Dataset statistics

Number of variables56
Number of observations618
Missing cells16812
Missing cells (%)48.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory292.8 KiB
Average record size in memory485.2 B

Variable types

Numeric9
Text7
DateTime4
Categorical15
Unsupported21

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-16058/S/1/datasetView.do

Alerts

인허가취소일자 is highly imbalanced (97.8%)Imbalance
상세영업상태명 is highly imbalanced (59.0%)Imbalance
주변환경명 is highly imbalanced (89.1%)Imbalance
건물용도명 is highly imbalanced (86.2%)Imbalance
통로너비 is highly imbalanced (51.5%)Imbalance
조명시설조도 is highly imbalanced (51.5%)Imbalance
노래방실수 is highly imbalanced (51.5%)Imbalance
청소년실수 is highly imbalanced (51.5%)Imbalance
총게임기수 is highly imbalanced (51.5%)Imbalance
지역구분명 is highly imbalanced (85.9%)Imbalance
폐업일자 has 456 (73.8%) missing valuesMissing
휴업시작일자 has 618 (100.0%) missing valuesMissing
휴업종료일자 has 618 (100.0%) missing valuesMissing
재개업일자 has 618 (100.0%) missing valuesMissing
전화번호 has 321 (51.9%) missing valuesMissing
소재지면적 has 618 (100.0%) missing valuesMissing
소재지우편번호 has 507 (82.0%) missing valuesMissing
도로명주소 has 14 (2.3%) missing valuesMissing
도로명우편번호 has 177 (28.6%) missing valuesMissing
업태구분명 has 618 (100.0%) missing valuesMissing
좌표정보(X) has 7 (1.1%) missing valuesMissing
좌표정보(Y) has 7 (1.1%) missing valuesMissing
총층수 has 526 (85.1%) missing valuesMissing
제작취급품목내용 has 301 (48.7%) missing valuesMissing
시설면적 has 466 (75.4%) missing valuesMissing
지상층수 has 521 (84.3%) missing valuesMissing
지하층수 has 531 (85.9%) missing valuesMissing
비상계단여부 has 618 (100.0%) missing valuesMissing
비상구여부 has 618 (100.0%) missing valuesMissing
자동환기여부 has 618 (100.0%) missing valuesMissing
청소년실여부 has 618 (100.0%) missing valuesMissing
특수조명여부 has 618 (100.0%) missing valuesMissing
방음시설여부 has 618 (100.0%) missing valuesMissing
비디오재생기명 has 618 (100.0%) missing valuesMissing
조명시설유무 has 618 (100.0%) missing valuesMissing
음향시설여부 has 618 (100.0%) missing valuesMissing
편의시설여부 has 618 (100.0%) missing valuesMissing
소방시설여부 has 618 (100.0%) missing valuesMissing
기존게임업외업종명 has 618 (100.0%) missing valuesMissing
제공게임물명 has 618 (100.0%) missing valuesMissing
공연장형태구분명 has 618 (100.0%) missing valuesMissing
품목명 has 618 (100.0%) missing valuesMissing
최초등록시점 has 618 (100.0%) missing valuesMissing
최종수정일자 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
제공게임물명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공연장형태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
품목명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
최초등록시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 62 (10.0%) zerosZeros
시설면적 has 50 (8.1%) zerosZeros
지상층수 has 61 (9.9%) zerosZeros
지하층수 has 62 (10.0%) zerosZeros

Reproduction

Analysis started2024-04-06 11:25:35.490082
Analysis finished2024-04-06 11:25:37.162542
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3147653.7
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:37.278609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13110000
median3180000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)110000

Descriptive statistics

Standard deviation77270.053
Coefficient of variation (CV)0.02454846
Kurtosis-0.88585492
Mean3147653.7
Median Absolute Deviation (MAD)40000
Skewness-0.72446317
Sum1.94525 × 109
Variance5.9706611 × 109
MonotonicityNot monotonic
2024-04-06T20:25:37.511256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 127
20.6%
3210000 77
12.5%
3130000 65
10.5%
3180000 38
 
6.1%
3000000 38
 
6.1%
3020000 26
 
4.2%
3230000 25
 
4.0%
3010000 21
 
3.4%
3040000 21
 
3.4%
3160000 18
 
2.9%
Other values (15) 162
26.2%
ValueCountFrequency (%)
3000000 38
6.1%
3010000 21
3.4%
3020000 26
4.2%
3030000 16
2.6%
3040000 21
3.4%
3050000 6
 
1.0%
3060000 2
 
0.3%
3070000 11
 
1.8%
3080000 3
 
0.5%
3090000 6
 
1.0%
ValueCountFrequency (%)
3240000 10
 
1.6%
3230000 25
 
4.0%
3220000 127
20.6%
3210000 77
12.5%
3200000 15
 
2.4%
3190000 18
 
2.9%
3180000 38
 
6.1%
3170000 15
 
2.4%
3160000 18
 
2.9%
3150000 17
 
2.8%
Distinct185
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-06T20:25:37.870038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters12360
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

Unique94 ?
Unique (%)15.2%

Sample

1st rowCDFF3241102023000003
2nd rowCDFF3241102017000002
3rd rowCDFF3241102012000002
4th rowCDFF3241102016000002
5th rowCDFF3241102023000003
ValueCountFrequency (%)
cdff3241102021000001 19
 
3.1%
cdff3241102023000001 18
 
2.9%
cdff3241102012000001 17
 
2.8%
cdff3241102007000001 13
 
2.1%
cdff3241102006000001 13
 
2.1%
cdff3241102018000001 13
 
2.1%
cdff3241102022000001 13
 
2.1%
cdff3241102020000001 13
 
2.1%
cdff3241102013000001 11
 
1.8%
cdff3241102012000002 11
 
1.8%
Other values (175) 477
77.2%
2024-04-06T20:25:38.476983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4547
36.8%
1 1854
15.0%
2 1654
 
13.4%
F 1236
 
10.0%
3 780
 
6.3%
4 705
 
5.7%
C 618
 
5.0%
D 618
 
5.0%
9 78
 
0.6%
6 73
 
0.6%
Other values (3) 197
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9888
80.0%
Uppercase Letter 2472
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4547
46.0%
1 1854
18.8%
2 1654
 
16.7%
3 780
 
7.9%
4 705
 
7.1%
9 78
 
0.8%
6 73
 
0.7%
8 69
 
0.7%
7 65
 
0.7%
5 63
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
F 1236
50.0%
C 618
25.0%
D 618
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9888
80.0%
Latin 2472
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4547
46.0%
1 1854
18.8%
2 1654
 
16.7%
3 780
 
7.9%
4 705
 
7.1%
9 78
 
0.8%
6 73
 
0.7%
8 69
 
0.7%
7 65
 
0.7%
5 63
 
0.6%
Latin
ValueCountFrequency (%)
F 1236
50.0%
C 618
25.0%
D 618
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4547
36.8%
1 1854
15.0%
2 1654
 
13.4%
F 1236
 
10.0%
3 780
 
6.3%
4 705
 
5.7%
C 618
 
5.0%
D 618
 
5.0%
9 78
 
0.6%
6 73
 
0.6%
Other values (3) 197
 
1.6%
Distinct564
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum1998-09-29 00:00:00
Maximum2024-03-25 00:00:00
2024-04-06T20:25:38.749016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:39.004105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
616 
20101231
 
1
20220119
 
1

Length

Max length8
Median length4
Mean length4.012945
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 616
99.7%
20101231 1
 
0.2%
20220119 1
 
0.2%

Length

2024-04-06T20:25:39.364057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:39.596288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 616
99.7%
20101231 1
 
0.2%
20220119 1
 
0.2%
Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
1
451 
3
140 
5
 
23
4
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 451
73.0%
3 140
 
22.7%
5 23
 
3.7%
4 4
 
0.6%

Length

2024-04-06T20:25:39.900507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:40.139381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 451
73.0%
3 140
 
22.7%
5 23
 
3.7%
4 4
 
0.6%

영업상태명
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
영업/정상
451 
폐업
140 
제외/삭제/전출
 
23
취소/말소/만료/정지/중지
 
4

Length

Max length14
Median length5
Mean length4.4902913
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 451
73.0%
폐업 140
 
22.7%
제외/삭제/전출 23
 
3.7%
취소/말소/만료/정지/중지 4
 
0.6%

Length

2024-04-06T20:25:40.378837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:40.563488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 451
73.0%
폐업 140
 
22.7%
제외/삭제/전출 23
 
3.7%
취소/말소/만료/정지/중지 4
 
0.6%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.988673
Minimum3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:40.734743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q113
median13
Q313
95-th percentile13
Maximum35
Range32
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.6860808
Coefficient of variation (CV)0.42644646
Kurtosis3.2484137
Mean10.988673
Median Absolute Deviation (MAD)0
Skewness-0.15505199
Sum6791
Variance21.959353
MonotonicityNot monotonic
2024-04-06T20:25:40.930999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 451
73.0%
3 139
 
22.5%
15 23
 
3.7%
31 2
 
0.3%
35 2
 
0.3%
34 1
 
0.2%
ValueCountFrequency (%)
3 139
 
22.5%
13 451
73.0%
15 23
 
3.7%
31 2
 
0.3%
34 1
 
0.2%
35 2
 
0.3%
ValueCountFrequency (%)
35 2
 
0.3%
34 1
 
0.2%
31 2
 
0.3%
15 23
 
3.7%
13 451
73.0%
3 139
 
22.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
영업중
451 
폐업
139 
전출
 
23
등록취소
 
2
직권말소
 
2

Length

Max length5
Median length3
Mean length2.7475728
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 451
73.0%
폐업 139
 
22.5%
전출 23
 
3.7%
등록취소 2
 
0.3%
직권말소 2
 
0.3%
영업장폐쇄 1
 
0.2%

Length

2024-04-06T20:25:41.189895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:41.376673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 451
73.0%
폐업 139
 
22.5%
전출 23
 
3.7%
등록취소 2
 
0.3%
직권말소 2
 
0.3%
영업장폐쇄 1
 
0.2%

폐업일자
Date

MISSING 

Distinct157
Distinct (%)96.9%
Missing456
Missing (%)73.8%
Memory size5.0 KiB
Minimum2000-01-01 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T20:25:41.570692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:41.870539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

전화번호
Text

MISSING 

Distinct286
Distinct (%)96.3%
Missing321
Missing (%)51.9%
Memory size5.0 KiB
2024-04-06T20:25:42.293272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.632997
Min length8

Characters and Unicode

Total characters3158
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

Unique275 ?
Unique (%)92.6%

Sample

1st row070-7580-5470
2nd row02-482-9114
3rd row1644-8080
4th row02-545-8517
5th row070-8802-9719
ValueCountFrequency (%)
02 5
 
1.6%
02-3490-9300 2
 
0.6%
070-8862-7686 2
 
0.6%
02-568-8609 2
 
0.6%
070-4304-6643 2
 
0.6%
02-539-2088 2
 
0.6%
02-573-7474 2
 
0.6%
070-8860-7080 2
 
0.6%
02-3450-5433 2
 
0.6%
02-562-7188 2
 
0.6%
Other values (284) 286
92.6%
2024-04-06T20:25:42.970437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 510
16.1%
- 460
14.6%
2 422
13.4%
3 258
8.2%
7 244
7.7%
5 235
7.4%
8 226
7.2%
4 223
7.1%
6 210
6.6%
1 209
6.6%
Other values (4) 161
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2682
84.9%
Dash Punctuation 460
 
14.6%
Space Separator 12
 
0.4%
Close Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 510
19.0%
2 422
15.7%
3 258
9.6%
7 244
9.1%
5 235
8.8%
8 226
8.4%
4 223
8.3%
6 210
7.8%
1 209
7.8%
9 145
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 460
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3158
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 510
16.1%
- 460
14.6%
2 422
13.4%
3 258
8.2%
7 244
7.7%
5 235
7.4%
8 226
7.2%
4 223
7.1%
6 210
6.6%
1 209
6.6%
Other values (4) 161
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3158
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 510
16.1%
- 460
14.6%
2 422
13.4%
3 258
8.2%
7 244
7.7%
5 235
7.4%
8 226
7.2%
4 223
7.1%
6 210
6.6%
1 209
6.6%
Other values (4) 161
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

소재지우편번호
Text

MISSING 

Distinct99
Distinct (%)89.2%
Missing507
Missing (%)82.0%
Memory size5.0 KiB
2024-04-06T20:25:43.490960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.027027
Min length6

Characters and Unicode

Total characters669
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

Unique90 ?
Unique (%)81.1%

Sample

1st row120-818
2nd row110702
3rd row110855
4th row135-830
5th row110824
ValueCountFrequency (%)
137876 3
 
2.7%
152848 3
 
2.7%
135517 3
 
2.7%
137894 2
 
1.8%
110054 2
 
1.8%
137878 2
 
1.8%
137856 2
 
1.8%
140848 2
 
1.8%
100250 2
 
1.8%
137871 1
 
0.9%
Other values (89) 89
80.2%
2024-04-06T20:25:44.302804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 149
22.3%
8 94
14.1%
0 80
12.0%
5 76
11.4%
3 71
10.6%
7 59
 
8.8%
2 42
 
6.3%
9 38
 
5.7%
4 34
 
5.1%
6 23
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 666
99.6%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 149
22.4%
8 94
14.1%
0 80
12.0%
5 76
11.4%
3 71
10.7%
7 59
 
8.9%
2 42
 
6.3%
9 38
 
5.7%
4 34
 
5.1%
6 23
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 669
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 149
22.3%
8 94
14.1%
0 80
12.0%
5 76
11.4%
3 71
10.6%
7 59
 
8.8%
2 42
 
6.3%
9 38
 
5.7%
4 34
 
5.1%
6 23
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 149
22.3%
8 94
14.1%
0 80
12.0%
5 76
11.4%
3 71
10.6%
7 59
 
8.8%
2 42
 
6.3%
9 38
 
5.7%
4 34
 
5.1%
6 23
 
3.4%
Distinct569
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-06T20:25:44.828962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length26.938511
Min length14

Characters and Unicode

Total characters16648
Distinct characters370
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

Unique532 ?
Unique (%)86.1%

Sample

1st row서울특별시 강남구 역삼동 ***-**
2nd row서울특별시 금천구 가산동 ***-** 대륭테크노타운**차
3rd row서울특별시 강남구 도곡동 ***-* 수경빌딩
4th row서울특별시 성동구 마장동 ***-*
5th row서울특별시 마포구 상암동 **** 팬엔터테인먼트 사옥
ValueCountFrequency (%)
서울특별시 618
19.8%
번지 385
 
12.3%
230
 
7.4%
강남구 127
 
4.1%
106
 
3.4%
105
 
3.4%
서초구 77
 
2.5%
마포구 64
 
2.0%
영등포구 39
 
1.2%
서초동 39
 
1.2%
Other values (567) 1336
42.7%
2024-04-06T20:25:45.591026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 3205
19.3%
2882
17.3%
804
 
4.8%
710
 
4.3%
658
 
4.0%
630
 
3.8%
623
 
3.7%
618
 
3.7%
618
 
3.7%
- 510
 
3.1%
Other values (360) 5390
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9890
59.4%
Other Punctuation 3214
 
19.3%
Space Separator 2882
 
17.3%
Dash Punctuation 510
 
3.1%
Uppercase Letter 86
 
0.5%
Lowercase Letter 27
 
0.2%
Decimal Number 23
 
0.1%
Open Punctuation 8
 
< 0.1%
Close Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
804
 
8.1%
710
 
7.2%
658
 
6.7%
630
 
6.4%
623
 
6.3%
618
 
6.2%
618
 
6.2%
437
 
4.4%
392
 
4.0%
171
 
1.7%
Other values (313) 4229
42.8%
Uppercase Letter
ValueCountFrequency (%)
B 11
12.8%
A 8
 
9.3%
S 7
 
8.1%
T 7
 
8.1%
C 6
 
7.0%
E 6
 
7.0%
N 6
 
7.0%
M 6
 
7.0%
I 4
 
4.7%
K 4
 
4.7%
Other values (10) 21
24.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
25.9%
l 3
11.1%
c 3
11.1%
r 3
11.1%
w 3
11.1%
o 3
11.1%
a 2
 
7.4%
k 1
 
3.7%
n 1
 
3.7%
t 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
0 3
13.0%
3 3
13.0%
1 3
13.0%
6 3
13.0%
2 3
13.0%
9 2
8.7%
8 2
8.7%
5 2
8.7%
4 1
 
4.3%
7 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
* 3205
99.7%
, 8
 
0.2%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2882
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 510
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9890
59.4%
Common 6645
39.9%
Latin 113
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
804
 
8.1%
710
 
7.2%
658
 
6.7%
630
 
6.4%
623
 
6.3%
618
 
6.2%
618
 
6.2%
437
 
4.4%
392
 
4.0%
171
 
1.7%
Other values (313) 4229
42.8%
Latin
ValueCountFrequency (%)
B 11
 
9.7%
A 8
 
7.1%
e 7
 
6.2%
S 7
 
6.2%
T 7
 
6.2%
C 6
 
5.3%
E 6
 
5.3%
N 6
 
5.3%
M 6
 
5.3%
I 4
 
3.5%
Other values (20) 45
39.8%
Common
ValueCountFrequency (%)
* 3205
48.2%
2882
43.4%
- 510
 
7.7%
( 8
 
0.1%
) 8
 
0.1%
, 8
 
0.1%
0 3
 
< 0.1%
3 3
 
< 0.1%
1 3
 
< 0.1%
6 3
 
< 0.1%
Other values (7) 12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9890
59.4%
ASCII 6758
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 3205
47.4%
2882
42.6%
- 510
 
7.5%
B 11
 
0.2%
A 8
 
0.1%
( 8
 
0.1%
) 8
 
0.1%
, 8
 
0.1%
e 7
 
0.1%
S 7
 
0.1%
Other values (37) 104
 
1.5%
Hangul
ValueCountFrequency (%)
804
 
8.1%
710
 
7.2%
658
 
6.7%
630
 
6.4%
623
 
6.3%
618
 
6.2%
618
 
6.2%
437
 
4.4%
392
 
4.0%
171
 
1.7%
Other values (313) 4229
42.8%

도로명주소
Text

MISSING 

Distinct581
Distinct (%)96.2%
Missing14
Missing (%)2.3%
Memory size5.0 KiB
2024-04-06T20:25:46.033924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length47
Mean length34.235099
Min length22

Characters and Unicode

Total characters20678
Distinct characters414
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

Unique559 ?
Unique (%)92.5%

Sample

1st row서울특별시 강남구 역삼로*길 ** (역삼동)
2nd row서울특별시 금천구 가산디지털*로 **, 대륭테크노타운**차 ****호 (가산동)
3rd row서울특별시 강남구 강남대로**길 **, 수경빌딩 *층 (도곡동)
4th row서울특별시 성동구 마장로 ***, *층 (마장동)
5th row서울특별시 마포구 월드컵북로**길 **, 더팬빌딩 *층 (상암동)
ValueCountFrequency (%)
서울특별시 604
 
15.7%
602
 
15.6%
240
 
6.2%
201
 
5.2%
강남구 127
 
3.3%
서초구 75
 
1.9%
마포구 64
 
1.7%
종로구 37
 
1.0%
영등포구 37
 
1.0%
역삼동 28
 
0.7%
Other values (945) 1840
47.7%
2024-04-06T20:25:46.840849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3405
 
16.5%
* 3271
 
15.8%
816
 
3.9%
765
 
3.7%
680
 
3.3%
653
 
3.2%
, 647
 
3.1%
614
 
3.0%
) 611
 
3.0%
( 611
 
3.0%
Other values (404) 8605
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11885
57.5%
Other Punctuation 3919
 
19.0%
Space Separator 3405
 
16.5%
Close Punctuation 611
 
3.0%
Open Punctuation 611
 
3.0%
Uppercase Letter 101
 
0.5%
Dash Punctuation 86
 
0.4%
Decimal Number 33
 
0.2%
Lowercase Letter 23
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
816
 
6.9%
765
 
6.4%
680
 
5.7%
653
 
5.5%
614
 
5.2%
611
 
5.1%
604
 
5.1%
604
 
5.1%
330
 
2.8%
321
 
2.7%
Other values (354) 5887
49.5%
Uppercase Letter
ValueCountFrequency (%)
B 22
21.8%
A 10
9.9%
S 8
 
7.9%
T 7
 
6.9%
C 7
 
6.9%
M 7
 
6.9%
E 6
 
5.9%
N 6
 
5.9%
I 5
 
5.0%
R 3
 
3.0%
Other values (12) 20
19.8%
Decimal Number
ValueCountFrequency (%)
1 7
21.2%
4 6
18.2%
3 5
15.2%
5 4
12.1%
0 3
9.1%
7 2
 
6.1%
6 2
 
6.1%
9 2
 
6.1%
2 1
 
3.0%
8 1
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
e 7
30.4%
w 3
13.0%
r 3
13.0%
l 3
13.0%
o 2
 
8.7%
d 1
 
4.3%
t 1
 
4.3%
n 1
 
4.3%
a 1
 
4.3%
c 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
* 3271
83.5%
, 647
 
16.5%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3405
100.0%
Close Punctuation
ValueCountFrequency (%)
) 611
100.0%
Open Punctuation
ValueCountFrequency (%)
( 611
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11885
57.5%
Common 8669
41.9%
Latin 124
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
816
 
6.9%
765
 
6.4%
680
 
5.7%
653
 
5.5%
614
 
5.2%
611
 
5.1%
604
 
5.1%
604
 
5.1%
330
 
2.8%
321
 
2.7%
Other values (354) 5887
49.5%
Latin
ValueCountFrequency (%)
B 22
17.7%
A 10
 
8.1%
S 8
 
6.5%
T 7
 
5.6%
e 7
 
5.6%
C 7
 
5.6%
M 7
 
5.6%
E 6
 
4.8%
N 6
 
4.8%
I 5
 
4.0%
Other values (22) 39
31.5%
Common
ValueCountFrequency (%)
3405
39.3%
* 3271
37.7%
, 647
 
7.5%
) 611
 
7.0%
( 611
 
7.0%
- 86
 
1.0%
1 7
 
0.1%
4 6
 
0.1%
3 5
 
0.1%
5 4
 
< 0.1%
Other values (8) 16
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11885
57.5%
ASCII 8793
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3405
38.7%
* 3271
37.2%
, 647
 
7.4%
) 611
 
6.9%
( 611
 
6.9%
- 86
 
1.0%
B 22
 
0.3%
A 10
 
0.1%
S 8
 
0.1%
1 7
 
0.1%
Other values (40) 115
 
1.3%
Hangul
ValueCountFrequency (%)
816
 
6.9%
765
 
6.4%
680
 
5.7%
653
 
5.5%
614
 
5.2%
611
 
5.1%
604
 
5.1%
604
 
5.1%
330
 
2.8%
321
 
2.7%
Other values (354) 5887
49.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct370
Distinct (%)83.9%
Missing177
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean9999.6372
Minimum1094
Maximum158860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:47.197685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1094
5-th percentile3054
Q14056
median6018
Q36724
95-th percentile8708
Maximum158860
Range157766
Interquartile range (IQR)2668

Descriptive statistics

Standard deviation24267.311
Coefficient of variation (CV)2.4268192
Kurtosis26.493665
Mean9999.6372
Median Absolute Deviation (MAD)1392
Skewness5.269911
Sum4409840
Variance5.8890241 × 108
MonotonicityNot monotonic
2024-04-06T20:25:47.619043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3925 6
 
1.0%
8501 4
 
0.6%
3923 4
 
0.6%
6724 4
 
0.6%
4799 3
 
0.5%
8289 3
 
0.5%
2725 3
 
0.5%
8589 3
 
0.5%
6018 2
 
0.3%
6053 2
 
0.3%
Other values (360) 407
65.9%
(Missing) 177
28.6%
ValueCountFrequency (%)
1094 1
0.2%
1127 1
0.2%
1337 1
0.2%
1381 1
0.2%
1411 1
0.2%
1413 1
0.2%
1849 1
0.2%
2152 1
0.2%
2224 1
0.2%
2586 1
0.2%
ValueCountFrequency (%)
158860 1
0.2%
157930 1
0.2%
157812 1
0.2%
152838 1
0.2%
151080 1
0.2%
150102 1
0.2%
142876 1
0.2%
138812 1
0.2%
137927 1
0.2%
135925 1
0.2%
Distinct594
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-04-06T20:25:48.123222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length9.3495146
Min length1

Characters and Unicode

Total characters5778
Distinct characters486
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique571 ?
Unique (%)92.4%

Sample

1st row제이제이뮤직그룹
2nd row주식회사 시샵코리아
3rd row(주)알레스뮤직
4th row마장뮤직앤픽처스(주)
5th row주식회사 펑키스튜디오
ValueCountFrequency (%)
주식회사 115
 
13.1%
엔터테인먼트 10
 
1.1%
뮤직 7
 
0.8%
music 6
 
0.7%
스튜디오 6
 
0.7%
entertainment 5
 
0.6%
4
 
0.5%
프로덕션 4
 
0.5%
유한회사 4
 
0.5%
코리아 4
 
0.5%
Other values (682) 716
81.3%
2024-04-06T20:25:48.936074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
 
6.2%
) 280
 
4.8%
( 279
 
4.8%
263
 
4.6%
196
 
3.4%
157
 
2.7%
151
 
2.6%
129
 
2.2%
121
 
2.1%
110
 
1.9%
Other values (476) 3732
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4317
74.7%
Lowercase Letter 308
 
5.3%
Uppercase Letter 295
 
5.1%
Close Punctuation 281
 
4.9%
Open Punctuation 280
 
4.8%
Space Separator 263
 
4.6%
Other Punctuation 15
 
0.3%
Decimal Number 14
 
0.2%
Dash Punctuation 4
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
360
 
8.3%
196
 
4.5%
157
 
3.6%
151
 
3.5%
129
 
3.0%
121
 
2.8%
110
 
2.5%
97
 
2.2%
97
 
2.2%
92
 
2.1%
Other values (409) 2807
65.0%
Uppercase Letter
ValueCountFrequency (%)
S 32
 
10.8%
E 28
 
9.5%
M 27
 
9.2%
I 23
 
7.8%
A 18
 
6.1%
N 18
 
6.1%
O 18
 
6.1%
C 16
 
5.4%
L 14
 
4.7%
U 14
 
4.7%
Other values (15) 87
29.5%
Lowercase Letter
ValueCountFrequency (%)
n 34
11.0%
e 33
10.7%
o 30
9.7%
t 29
 
9.4%
i 25
 
8.1%
a 22
 
7.1%
r 19
 
6.2%
u 15
 
4.9%
d 15
 
4.9%
m 12
 
3.9%
Other values (14) 74
24.0%
Decimal Number
ValueCountFrequency (%)
1 4
28.6%
2 4
28.6%
0 2
14.3%
9 1
 
7.1%
3 1
 
7.1%
7 1
 
7.1%
8 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 8
53.3%
& 4
26.7%
, 2
 
13.3%
? 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 280
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 279
99.6%
[ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
263
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4318
74.7%
Common 857
 
14.8%
Latin 603
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
360
 
8.3%
196
 
4.5%
157
 
3.6%
151
 
3.5%
129
 
3.0%
121
 
2.8%
110
 
2.5%
97
 
2.2%
97
 
2.2%
92
 
2.1%
Other values (410) 2808
65.0%
Latin
ValueCountFrequency (%)
n 34
 
5.6%
e 33
 
5.5%
S 32
 
5.3%
o 30
 
5.0%
t 29
 
4.8%
E 28
 
4.6%
M 27
 
4.5%
i 25
 
4.1%
I 23
 
3.8%
a 22
 
3.6%
Other values (39) 320
53.1%
Common
ValueCountFrequency (%)
) 280
32.7%
( 279
32.6%
263
30.7%
. 8
 
0.9%
- 4
 
0.5%
& 4
 
0.5%
1 4
 
0.5%
2 4
 
0.5%
0 2
 
0.2%
, 2
 
0.2%
Other values (7) 7
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4317
74.7%
ASCII 1460
 
25.3%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
360
 
8.3%
196
 
4.5%
157
 
3.6%
151
 
3.5%
129
 
3.0%
121
 
2.8%
110
 
2.5%
97
 
2.2%
97
 
2.2%
92
 
2.1%
Other values (409) 2807
65.0%
ASCII
ValueCountFrequency (%)
) 280
19.2%
( 279
19.1%
263
18.0%
n 34
 
2.3%
e 33
 
2.3%
S 32
 
2.2%
o 30
 
2.1%
t 29
 
2.0%
E 28
 
1.9%
M 27
 
1.8%
Other values (56) 425
29.1%
None
ValueCountFrequency (%)
1
100.0%

최종수정일자
Date

UNIQUE 

Distinct618
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2006-02-20 10:05:55
Maximum2024-04-04 17:46:59
2024-04-06T20:25:49.270263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:49.629155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
I
467 
U
148 
D
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 467
75.6%
U 148
 
23.9%
D 3
 
0.5%

Length

2024-04-06T20:25:49.905654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:50.473335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 467
75.6%
u 148
 
23.9%
d 3
 
0.5%
Distinct261
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T20:25:50.682785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:25:50.919327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct567
Distinct (%)92.8%
Missing7
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean198820.57
Minimum182735.79
Maximum213048.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:51.140371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182735.79
5-th percentile188585.1
Q1193327.11
median200175
Q3203507.58
95-th percentile209104.08
Maximum213048.69
Range30312.905
Interquartile range (IQR)10180.465

Descriptive statistics

Standard deviation6378.3556
Coefficient of variation (CV)0.032080964
Kurtosis-0.66181617
Mean198820.57
Median Absolute Deviation (MAD)4428.6333
Skewness-0.20099298
Sum1.2147937 × 108
Variance40683421
MonotonicityNot monotonic
2024-04-06T20:25:51.426162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189954.316212248 4
 
0.6%
193282.654266684 4
 
0.6%
201990.741998075 3
 
0.5%
189504.258704224 3
 
0.5%
190349.885855531 3
 
0.5%
189089.927764903 3
 
0.5%
190459.967586857 2
 
0.3%
203808.126310759 2
 
0.3%
205784.445648184 2
 
0.3%
198563.350432385 2
 
0.3%
Other values (557) 583
94.3%
(Missing) 7
 
1.1%
ValueCountFrequency (%)
182735.786874703 1
0.2%
182941.05762285 1
0.2%
183172.231545973 1
0.2%
183342.868967294 1
0.2%
183661.654363086 1
0.2%
183937.7403014 1
0.2%
184655.264279055 1
0.2%
185115.903576225 1
0.2%
185365.565 1
0.2%
185455.0 1
0.2%
ValueCountFrequency (%)
213048.692179757 1
0.2%
212811.975075042 1
0.2%
212755.661843784 1
0.2%
212590.465473593 1
0.2%
211834.106255522 1
0.2%
211735.079601952 1
0.2%
211368.226711282 1
0.2%
211260.202994668 1
0.2%
211118.67780737 1
0.2%
211080.396769483 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct567
Distinct (%)92.8%
Missing7
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean447485.8
Minimum438200.73
Maximum462521.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:51.702886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438200.73
5-th percentile441765.77
Q1444289.26
median446797.34
Q3450548.18
95-th percentile454489.24
Maximum462521.72
Range24320.994
Interquartile range (IQR)6258.9252

Descriptive statistics

Standard deviation4208.4776
Coefficient of variation (CV)0.0094047175
Kurtosis0.10523654
Mean447485.8
Median Absolute Deviation (MAD)3166.8913
Skewness0.59715766
Sum2.7341382 × 108
Variance17711283
MonotonicityNot monotonic
2024-04-06T20:25:51.957342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453263.335891345 4
 
0.6%
447611.552045596 4
 
0.6%
442433.148687375 3
 
0.5%
441390.738560411 3
 
0.5%
444836.673561831 3
 
0.5%
442569.300676147 3
 
0.5%
453050.376274362 2
 
0.3%
445512.704269021 2
 
0.3%
449451.98622544 2
 
0.3%
451062.298492966 2
 
0.3%
Other values (557) 583
94.3%
(Missing) 7
 
1.1%
ValueCountFrequency (%)
438200.726855847 1
0.2%
440050.890713983 1
0.2%
440538.798020288 1
0.2%
440634.624615443 1
0.2%
440694.901050366 1
0.2%
440726.19 1
0.2%
440732.569663101 1
0.2%
440753.993971457 1
0.2%
440804.189450368 1
0.2%
441036.050850249 1
0.2%
ValueCountFrequency (%)
462521.720396049 1
0.2%
461439.392577545 2
0.3%
461008.914009807 1
0.2%
460581.59670577 2
0.3%
459731.831648811 1
0.2%
459252.431495024 1
0.2%
459096.21304272 1
0.2%
458084.679952437 1
0.2%
458077.6402941 1
0.2%
457447.793737463 1
0.2%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
음반.음악영상물배급업
458 
<NA>
160 

Length

Max length11
Median length11
Mean length9.1877023
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 (%)
음반.음악영상물배급업 458
74.1%
<NA> 160
 
25.9%

Length

2024-04-06T20:25:52.162995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:52.337454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음반.음악영상물배급업 458
74.1%
na 160
 
25.9%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
유통관련업
458 
<NA>
160 

Length

Max length5
Median length5
Mean length4.7411003
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 458
74.1%
<NA> 160
 
25.9%

Length

2024-04-06T20:25:52.552044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:52.762502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통관련업 458
74.1%
na 160
 
25.9%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)16.3%
Missing526
Missing (%)85.1%
Infinite0
Infinite (%)0.0%
Mean2.8695652
Minimum0
Maximum41
Zeros62
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:52.951755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile16
Maximum41
Range41
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.1950306
Coefficient of variation (CV)2.1588743
Kurtosis15.935982
Mean2.8695652
Median Absolute Deviation (MAD)0
Skewness3.4700415
Sum264
Variance38.378404
MonotonicityNot monotonic
2024-04-06T20:25:53.173936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 62
 
10.0%
5 5
 
0.8%
6 4
 
0.6%
4 3
 
0.5%
3 3
 
0.5%
1 3
 
0.5%
19 2
 
0.3%
16 2
 
0.3%
10 2
 
0.3%
9 1
 
0.2%
Other values (5) 5
 
0.8%
(Missing) 526
85.1%
ValueCountFrequency (%)
0 62
10.0%
1 3
 
0.5%
3 3
 
0.5%
4 3
 
0.5%
5 5
 
0.8%
6 4
 
0.6%
7 1
 
0.2%
9 1
 
0.2%
10 2
 
0.3%
12 1
 
0.2%
ValueCountFrequency (%)
41 1
 
0.2%
19 2
0.3%
17 1
 
0.2%
16 2
0.3%
15 1
 
0.2%
12 1
 
0.2%
10 2
0.3%
9 1
 
0.2%
7 1
 
0.2%
6 4
0.6%

주변환경명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
598 
기타
 
10
주택가주변
 
8
학교정화(절대)
 
1
아파트지역
 
1

Length

Max length8
Median length4
Mean length3.9886731
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 598
96.8%
기타 10
 
1.6%
주택가주변 8
 
1.3%
학교정화(절대) 1
 
0.2%
아파트지역 1
 
0.2%

Length

2024-04-06T20:25:53.370118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:53.564251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 598
96.8%
기타 10
 
1.6%
주택가주변 8
 
1.3%
학교정화(절대 1
 
0.2%
아파트지역 1
 
0.2%
Distinct164
Distinct (%)51.7%
Missing301
Missing (%)48.7%
Memory size5.0 KiB
2024-04-06T20:25:53.984042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26
Mean length7.7381703
Min length2

Characters and Unicode

Total characters2453
Distinct characters149
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)43.5%

Sample

1st row불경음반(테이프,CD)
2nd row음원, 음반 유통
3rd row음반, 음악영상물
4th row음원,CD,DVD
5th row해외 뮤직비디오
ValueCountFrequency (%)
음반 133
24.8%
음악영상물 41
 
7.6%
음반,음악영상물 25
 
4.7%
cd 22
 
4.1%
영상물 21
 
3.9%
19
 
3.5%
음원 19
 
3.5%
음악 17
 
3.2%
뮤직비디오 12
 
2.2%
음반음악영상물 11
 
2.0%
Other values (143) 217
40.4%
2024-04-06T20:25:54.654737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
424
17.3%
241
 
9.8%
220
 
9.0%
, 185
 
7.5%
160
 
6.5%
155
 
6.3%
140
 
5.7%
138
 
5.6%
D 60
 
2.4%
41
 
1.7%
Other values (139) 689
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1862
75.9%
Space Separator 220
 
9.0%
Other Punctuation 208
 
8.5%
Uppercase Letter 137
 
5.6%
Close Punctuation 13
 
0.5%
Open Punctuation 13
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
424
22.8%
241
12.9%
160
 
8.6%
155
 
8.3%
140
 
7.5%
138
 
7.4%
41
 
2.2%
40
 
2.1%
34
 
1.8%
29
 
1.6%
Other values (119) 460
24.7%
Uppercase Letter
ValueCountFrequency (%)
D 60
43.8%
C 36
26.3%
V 12
 
8.8%
T 5
 
3.6%
P 5
 
3.6%
S 5
 
3.6%
A 4
 
2.9%
E 3
 
2.2%
B 2
 
1.5%
U 2
 
1.5%
Other values (3) 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 185
88.9%
. 15
 
7.2%
? 7
 
3.4%
/ 1
 
0.5%
Space Separator
ValueCountFrequency (%)
220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1862
75.9%
Common 454
 
18.5%
Latin 137
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
424
22.8%
241
12.9%
160
 
8.6%
155
 
8.3%
140
 
7.5%
138
 
7.4%
41
 
2.2%
40
 
2.1%
34
 
1.8%
29
 
1.6%
Other values (119) 460
24.7%
Latin
ValueCountFrequency (%)
D 60
43.8%
C 36
26.3%
V 12
 
8.8%
T 5
 
3.6%
P 5
 
3.6%
S 5
 
3.6%
A 4
 
2.9%
E 3
 
2.2%
B 2
 
1.5%
U 2
 
1.5%
Other values (3) 3
 
2.2%
Common
ValueCountFrequency (%)
220
48.5%
, 185
40.7%
. 15
 
3.3%
) 13
 
2.9%
( 13
 
2.9%
? 7
 
1.5%
/ 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1862
75.9%
ASCII 591
 
24.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
424
22.8%
241
12.9%
160
 
8.6%
155
 
8.3%
140
 
7.5%
138
 
7.4%
41
 
2.2%
40
 
2.1%
34
 
1.8%
29
 
1.6%
Other values (119) 460
24.7%
ASCII
ValueCountFrequency (%)
220
37.2%
, 185
31.3%
D 60
 
10.2%
C 36
 
6.1%
. 15
 
2.5%
) 13
 
2.2%
( 13
 
2.2%
V 12
 
2.0%
? 7
 
1.2%
T 5
 
0.8%
Other values (10) 25
 
4.2%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct97
Distinct (%)63.8%
Missing466
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean84.902368
Minimum0
Maximum2355.2
Zeros50
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:54.983825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median33
Q393.045
95-th percentile264.6415
Maximum2355.2
Range2355.2
Interquartile range (IQR)93.045

Descriptive statistics

Standard deviation223.04686
Coefficient of variation (CV)2.6270982
Kurtosis73.361467
Mean84.902368
Median Absolute Deviation (MAD)33
Skewness7.7617294
Sum12905.16
Variance49749.902
MonotonicityNot monotonic
2024-04-06T20:25:55.240669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 50
 
8.1%
20.0 4
 
0.6%
33.0 3
 
0.5%
16.5 2
 
0.3%
184.71 1
 
0.2%
26.82 1
 
0.2%
99.79 1
 
0.2%
80.0 1
 
0.2%
79.52 1
 
0.2%
100.74 1
 
0.2%
Other values (87) 87
 
14.1%
(Missing) 466
75.4%
ValueCountFrequency (%)
0.0 50
8.1%
1.0 1
 
0.2%
1.65 1
 
0.2%
4.0 1
 
0.2%
5.0 1
 
0.2%
5.67 1
 
0.2%
6.0 1
 
0.2%
10.0 1
 
0.2%
11.4 1
 
0.2%
16.0 1
 
0.2%
ValueCountFrequency (%)
2355.2 1
0.2%
975.21 1
0.2%
677.6 1
0.2%
667.59 1
0.2%
338.8 1
0.2%
320.98 1
0.2%
280.7 1
0.2%
265.56 1
0.2%
263.89 1
0.2%
214.31 1
0.2%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)14.4%
Missing521
Missing (%)84.3%
Infinite0
Infinite (%)0.0%
Mean2.5463918
Minimum0
Maximum35
Zeros61
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:55.523861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile15
Maximum35
Range35
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.9721936
Coefficient of variation (CV)2.3453554
Kurtosis16.331494
Mean2.5463918
Median Absolute Deviation (MAD)0
Skewness3.7663673
Sum247
Variance35.667096
MonotonicityNot monotonic
2024-04-06T20:25:55.782455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 61
 
9.9%
4 8
 
1.3%
1 7
 
1.1%
2 5
 
0.8%
15 3
 
0.5%
5 3
 
0.5%
3 2
 
0.3%
8 2
 
0.3%
34 1
 
0.2%
14 1
 
0.2%
Other values (4) 4
 
0.6%
(Missing) 521
84.3%
ValueCountFrequency (%)
0 61
9.9%
1 7
 
1.1%
2 5
 
0.8%
3 2
 
0.3%
4 8
 
1.3%
5 3
 
0.5%
6 1
 
0.2%
8 2
 
0.3%
10 1
 
0.2%
14 1
 
0.2%
ValueCountFrequency (%)
35 1
 
0.2%
34 1
 
0.2%
17 1
 
0.2%
15 3
 
0.5%
14 1
 
0.2%
10 1
 
0.2%
8 2
 
0.3%
6 1
 
0.2%
5 3
 
0.5%
4 8
1.3%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)6.9%
Missing531
Missing (%)85.9%
Infinite0
Infinite (%)0.0%
Mean0.45977011
Minimum0
Maximum6
Zeros62
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-04-06T20:25:55.976012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.020768
Coefficient of variation (CV)2.2201705
Kurtosis14.640069
Mean0.45977011
Median Absolute Deviation (MAD)0
Skewness3.5353544
Sum40
Variance1.0419674
MonotonicityNot monotonic
2024-04-06T20:25:56.162791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 62
 
10.0%
1 19
 
3.1%
2 3
 
0.5%
5 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
(Missing) 531
85.9%
ValueCountFrequency (%)
0 62
10.0%
1 19
 
3.1%
2 3
 
0.5%
4 1
 
0.2%
5 1
 
0.2%
6 1
 
0.2%
ValueCountFrequency (%)
6 1
 
0.2%
5 1
 
0.2%
4 1
 
0.2%
2 3
 
0.5%
1 19
 
3.1%
0 62
10.0%

건물용도명
Categorical

IMBALANCE 

Distinct8
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
582 
근린생활시설
 
25
사무실
 
4
단독주택
 
2
아파트
 
2
Other values (3)
 
3

Length

Max length6
Median length4
Mean length4.0728155
Min length2

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 582
94.2%
근린생활시설 25
 
4.0%
사무실 4
 
0.6%
단독주택 2
 
0.3%
아파트 2
 
0.3%
다세대주택 1
 
0.2%
기타 1
 
0.2%
교육연구시설 1
 
0.2%

Length

2024-04-06T20:25:56.445970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:56.689692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.2%
근린생활시설 25
 
4.0%
사무실 4
 
0.6%
단독주택 2
 
0.3%
아파트 2
 
0.3%
다세대주택 1
 
0.2%
기타 1
 
0.2%
교육연구시설 1
 
0.2%

통로너비
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
553 
0
65 

Length

Max length4
Median length4
Mean length3.684466
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> 553
89.5%
0 65
 
10.5%

Length

2024-04-06T20:25:56.904804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:57.071521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
89.5%
0 65
 
10.5%

조명시설조도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
553 
0
65 

Length

Max length4
Median length4
Mean length3.684466
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> 553
89.5%
0 65
 
10.5%

Length

2024-04-06T20:25:57.295681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:57.502096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
89.5%
0 65
 
10.5%

노래방실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
553 
0
65 

Length

Max length4
Median length4
Mean length3.684466
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> 553
89.5%
0 65
 
10.5%

Length

2024-04-06T20:25:57.686450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:57.868807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
89.5%
0 65
 
10.5%

청소년실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
553 
0
65 

Length

Max length4
Median length4
Mean length3.684466
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> 553
89.5%
0 65
 
10.5%

Length

2024-04-06T20:25:58.208689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:58.460692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
89.5%
0 65
 
10.5%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

총게임기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
553 
0
65 

Length

Max length4
Median length4
Mean length3.684466
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> 553
89.5%
0 65
 
10.5%

Length

2024-04-06T20:25:58.737429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:58.953787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
89.5%
0 65
 
10.5%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

제공게임물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing618
Missing (%)100.0%
Memory size5.6 KiB

지역구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
588 
일반주거지역
 
17
일반상업지역
 
6
주거지역
 
4
준공업지역
 
2

Length

Max length6
Median length4
Mean length4.0776699
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 588
95.1%
일반주거지역 17
 
2.8%
일반상업지역 6
 
1.0%
주거지역 4
 
0.6%
준공업지역 2
 
0.3%
상업지역 1
 
0.2%

Length

2024-04-06T20:25:59.178626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:25:59.415511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 588
95.1%
일반주거지역 17
 
2.8%
일반상업지역 6
 
1.0%
주거지역 4
 
0.6%
준공업지역 2
 
0.3%
상업지역 1
 
0.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03220000CDFF32411020230000032023-03-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 ***-**서울특별시 강남구 역삼로*길 ** (역삼동)6243제이제이뮤직그룹2023-03-06 17:52:45I2022-12-03 00:08:00.0<NA>202776.71097443697.332836<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>
13170000CDFF32411020170000022015-11-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 ***-** 대륭테크노타운**차서울특별시 금천구 가산디지털*로 **, 대륭테크노타운**차 ****호 (가산동)8589주식회사 시샵코리아2023-06-26 16:09:05U2022-12-05 22:08:00.0<NA>189504.258704441390.73856<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>
23220000CDFF32411020120000022008-04-17<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7580-5470<NA><NA>서울특별시 강남구 도곡동 ***-* 수경빌딩서울특별시 강남구 강남대로**길 **, 수경빌딩 *층 (도곡동)6259(주)알레스뮤직2023-03-21 13:55:05U2022-12-02 22:03:00.0<NA>203004.869657443095.281905<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>
33030000CDFF32411020160000022016-07-18<NA>5제외/삭제/전출15전출2023-04-27<NA><NA><NA><NA><NA><NA>서울특별시 성동구 마장동 ***-*서울특별시 성동구 마장로 ***, *층 (마장동)4758마장뮤직앤픽처스(주)2023-04-27 10:51:08U2022-12-03 22:09:00.0<NA>203737.8358451507.016073<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>
43130000CDFF32411020230000032023-03-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 **** 팬엔터테인먼트 사옥서울특별시 마포구 월드컵북로**길 **, 더팬빌딩 *층 (상암동)3923주식회사 펑키스튜디오2023-03-28 13:26:51D2022-12-02 21:00:00.0<NA>189954.316212453263.335891<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>
53090000CDFF32411020230000022023-04-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 도봉구 창동 *-* 창동 아우르네 *호서울특별시 도봉구 마들로**길 **, 창동 아우르네 *층 *호 (창동)1411주식회사 비트썸원2023-04-04 14:05:08I2022-12-04 00:06:00.0<NA>204167.266664461439.392578<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>
63130000CDFF32411020230000012023-02-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 ***-**서울특별시 마포구 잔다리로 **, 우신빌딩 *층 (서교동)4043주식회사 두세븐엔터테인먼트2023-02-03 11:23:33I2022-12-02 00:05:00.0<NA>192866.453646449849.09236<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>
73130000CDFF32411020230000022023-03-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 **** 팬엔터테인먼트 사옥서울특별시 마포구 월드컵북로**길 **, 더팬빌딩 *층 (상암동)3923주식회사 펑키스튜디오2023-03-24 17:37:45I2022-12-02 22:06:00.0<NA>189954.316212453263.335891<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>
83240000CDFF32411020230000012023-04-06<NA>1영업/정상13영업중<NA><NA><NA><NA>02-482-9114<NA><NA>서울특별시 강동구 길동 ***-* 대우빌딩 *층서울특별시 강동구 천중로**길 *, 대우빌딩 *층 (길동)5304주식회사 나인프로젝트2023-04-06 13:48:17I2022-12-04 00:08:00.0<NA>212755.661844448788.663652<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>
93120000CDFF32411020230000012023-03-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 *-***서울특별시 서대문구 포방터길 ***-* (홍은동)3601새벽숨의 예술인들2023-03-28 18:22:27I2022-12-02 21:00:00.0<NA>195522.604375455526.470899<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
6083140000CDFF324110202200000120220822<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 ***-**서울특별시 양천구 중앙로**길 ** (신월동)7934하모니카2022-08-22 16:14:21I2021-12-07 22:04:00.0<NA>186399.630008446925.645126<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>
6093030000CDFF324110201900000120120330<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 성동구 성수동*가 ***-** 우리큐브서울특별시 성동구 연무장**길 **, 우리큐브 *층 ***호 (성수동*가)4783블루보이2022-08-25 14:50:09U2021-12-07 22:07:00.0<NA>205014.436192448961.20833<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>
6103220000CDFF324110202200001020220829<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 ***-** 세명빌딩서울특별시 강남구 역삼로 ***, 세명빌딩 *층 (역삼동)6227주식회사 빅스톤스튜디오2022-08-29 10:06:43I2021-12-07 21:01:00.0<NA>203641.076839443854.896864<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>
6113220000CDFF324110202200001120200629<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4304-6643<NA><NA>서울특별시 강남구 역삼동 ***-* 삼익 라비돌 빌딩서울특별시 강남구 테헤란로 ***, 삼익 라비돌 빌딩 **층 (역삼동)6221컬쳐띵크 주식회사2022-09-22 10:02:33U2021-12-08 22:04:00.0<NA>203628.379146444413.806441<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>
6123220000CDFF324110202200001220220926<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 ***-* HJ타워서울특별시 강남구 테헤란로 ***, HJ타워 **(공부상**층)층 (역삼동)6212주식회사 바이포엠스튜디오2022-09-26 14:30:41I2021-12-08 22:08:00.0<NA>204180.425444622.13<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>
6133220000CDFF324110202200001320221004<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 대치동 **** 엠디엠타워서울특별시 강남구 테헤란로***길 **, 엠디엠타워 *층 (대치동)6176주식회사 하이브아이엠2022-10-04 16:06:00I2021-10-31 00:06:00.0<NA>205788.064366444961.39426<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>
6143120000CDFF324110201900000120190116<NA>3폐업3폐업20221004<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 **-**서울특별시 서대문구 연세로*다길 **, *층 ***호 (창천동)3787주식회사 블루멜론프로덕션2022-10-04 13:45:36U2021-10-31 00:06:00.0<NA>194033.037823450514.653917<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>
6153040000CDFF324110202200000120220923<NA>3폐업3폐업20220928<NA><NA><NA>07041688661<NA><NA>서울특별시 광진구 자양동 **-*서울특별시 광진구 자양강변길 ***, 본빌딩 *층 (자양동)5086(주)케이디지털미디어2022-09-28 18:27:22U2021-12-08 21:00:00.0<NA>205692.272635447791.471988<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>
6163040000CDFF324110201800000120180202<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 광진구 자양동 **-*서울특별시 광진구 자양강변길 ***, 본빌딩 *층 (자양동)5086(주)케이디지털미디어2022-09-28 18:24:11U2021-12-08 21:00:00.0<NA>205692.272635447791.471988<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>
6173220000CDFF324110202200001420221011<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 삼성동 ***-**서울특별시 강남구 선릉로**길 **, *층, *층 (삼성동)6160주식회사 팬딩2022-10-11 15:53:24I2021-10-30 23:03:00.0<NA>204496.322722444864.380973<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>