Overview

Dataset statistics

Number of variables56
Number of observations2190
Missing cells61779
Missing cells (%)50.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory485.1 B

Variable types

Categorical16
Text9
DateTime4
Unsupported21
Numeric6

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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-17389/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
주변환경명 has constant value ""Constant
인허가취소일자 is highly imbalanced (99.4%)Imbalance
영업상태코드 is highly imbalanced (57.0%)Imbalance
영업상태명 is highly imbalanced (57.0%)Imbalance
상세영업상태코드 is highly imbalanced (57.0%)Imbalance
상세영업상태명 is highly imbalanced (57.0%)Imbalance
문화사업자구분명 is highly imbalanced (61.1%)Imbalance
지하층수 is highly imbalanced (84.7%)Imbalance
건물용도명 is highly imbalanced (98.0%)Imbalance
통로너비 is highly imbalanced (70.3%)Imbalance
조명시설조도 is highly imbalanced (70.3%)Imbalance
노래방실수 is highly imbalanced (70.3%)Imbalance
청소년실수 is highly imbalanced (70.3%)Imbalance
총게임기수 is highly imbalanced (70.3%)Imbalance
폐업일자 has 1781 (81.3%) missing valuesMissing
휴업시작일자 has 2190 (100.0%) missing valuesMissing
휴업종료일자 has 2190 (100.0%) missing valuesMissing
재개업일자 has 2190 (100.0%) missing valuesMissing
전화번호 has 1313 (60.0%) missing valuesMissing
소재지면적 has 2190 (100.0%) missing valuesMissing
소재지우편번호 has 2040 (93.2%) missing valuesMissing
도로명우편번호 has 395 (18.0%) missing valuesMissing
업태구분명 has 2190 (100.0%) missing valuesMissing
총층수 has 2062 (94.2%) missing valuesMissing
주변환경명 has 2189 (> 99.9%) missing valuesMissing
제작취급품목내용 has 745 (34.0%) missing valuesMissing
시설면적 has 1020 (46.6%) missing valuesMissing
지상층수 has 2053 (93.7%) missing valuesMissing
비상계단여부 has 2190 (100.0%) missing valuesMissing
비상구여부 has 2190 (100.0%) missing valuesMissing
자동환기여부 has 2190 (100.0%) missing valuesMissing
청소년실여부 has 2190 (100.0%) missing valuesMissing
특수조명여부 has 2190 (100.0%) missing valuesMissing
방음시설여부 has 2190 (100.0%) missing valuesMissing
비디오재생기명 has 2190 (100.0%) missing valuesMissing
조명시설유무 has 2190 (100.0%) missing valuesMissing
음향시설여부 has 2190 (100.0%) missing valuesMissing
편의시설여부 has 2190 (100.0%) missing valuesMissing
소방시설여부 has 2190 (100.0%) missing valuesMissing
기존게임업외업종명 has 2190 (100.0%) missing valuesMissing
제공게임물명 has 2190 (100.0%) missing valuesMissing
공연장형태구분명 has 2190 (100.0%) missing valuesMissing
품목명 has 2190 (100.0%) missing valuesMissing
최초등록시점 has 2190 (100.0%) missing valuesMissing
지역구분명 has 2184 (99.7%) missing valuesMissing
시설면적 is highly skewed (γ1 = 26.08348995)Skewed
관리번호 has unique valuesUnique
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 114 (5.2%) zerosZeros
시설면적 has 122 (5.6%) zerosZeros
지상층수 has 113 (5.2%) zerosZeros

Reproduction

Analysis started2024-05-11 07:50:33.530217
Analysis finished2024-05-11 07:50:37.605876
Duration4.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
3220000
2190 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 2190
100.0%

Length

2024-05-11T07:50:37.817991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:38.336908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 2190
100.0%

관리번호
Text

UNIQUE 

Distinct2190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-05-11T07:50:39.047228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters43800
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

Unique2190 ?
Unique (%)100.0%

Sample

1st rowCDFF1241071989000001
2nd rowCDFF1241071995000001
3rd rowCDFF1241071999000001
4th rowCDFF1241071999000002
5th rowCDFF1241071999000004
ValueCountFrequency (%)
cdff1241071989000001 1
 
< 0.1%
cdff1241072021000011 1
 
< 0.1%
cdff1241072021000018 1
 
< 0.1%
cdff1241072021000017 1
 
< 0.1%
cdff1241072021000016 1
 
< 0.1%
cdff1241072021000015 1
 
< 0.1%
cdff1241072021000014 1
 
< 0.1%
cdff1241072021000012 1
 
< 0.1%
cdff1241072021000057 1
 
< 0.1%
cdff1241072021000056 1
 
< 0.1%
Other values (2180) 2180
99.5%
2024-05-11T07:50:40.311262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13661
31.2%
1 6663
15.2%
2 6190
14.1%
F 4380
 
10.0%
4 2787
 
6.4%
7 2748
 
6.3%
C 2190
 
5.0%
D 2190
 
5.0%
3 740
 
1.7%
9 630
 
1.4%
Other values (3) 1621
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35040
80.0%
Uppercase Letter 8760
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13661
39.0%
1 6663
19.0%
2 6190
17.7%
4 2787
 
8.0%
7 2748
 
7.8%
3 740
 
2.1%
9 630
 
1.8%
6 570
 
1.6%
8 532
 
1.5%
5 519
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
F 4380
50.0%
C 2190
25.0%
D 2190
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 35040
80.0%
Latin 8760
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13661
39.0%
1 6663
19.0%
2 6190
17.7%
4 2787
 
8.0%
7 2748
 
7.8%
3 740
 
2.1%
9 630
 
1.8%
6 570
 
1.6%
8 532
 
1.5%
5 519
 
1.5%
Latin
ValueCountFrequency (%)
F 4380
50.0%
C 2190
25.0%
D 2190
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13661
31.2%
1 6663
15.2%
2 6190
14.1%
F 4380
 
10.0%
4 2787
 
6.4%
7 2748
 
6.3%
C 2190
 
5.0%
D 2190
 
5.0%
3 740
 
1.7%
9 630
 
1.4%
Other values (3) 1621
 
3.7%
Distinct1629
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
Minimum1989-11-03 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T07:50:40.937752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:50:41.491074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2189 
20170714
 
1

Length

Max length8
Median length4
Mean length4.0018265
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2189
> 99.9%
20170714 1
 
< 0.1%

Length

2024-05-11T07:50:41.928624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:42.633646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2189
> 99.9%
20170714 1
 
< 0.1%

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
1
1779 
3
296 
5
 
114
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1779
81.2%
3 296
 
13.5%
5 114
 
5.2%
4 1
 
< 0.1%

Length

2024-05-11T07:50:43.135605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:43.555416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1779
81.2%
3 296
 
13.5%
5 114
 
5.2%
4 1
 
< 0.1%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
영업/정상
1779 
폐업
296 
제외/삭제/전출
 
114
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length4.7547945
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 1779
81.2%
폐업 296
 
13.5%
제외/삭제/전출 114
 
5.2%
취소/말소/만료/정지/중지 1
 
< 0.1%

Length

2024-05-11T07:50:44.043776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:44.478442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 1779
81.2%
폐업 296
 
13.5%
제외/삭제/전출 114
 
5.2%
취소/말소/만료/정지/중지 1
 
< 0.1%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
13
1779 
3
296 
15
 
114
32
 
1

Length

Max length2
Median length2
Mean length1.8648402
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
13 1779
81.2%
3 296
 
13.5%
15 114
 
5.2%
32 1
 
< 0.1%

Length

2024-05-11T07:50:45.082629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:45.482912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 1779
81.2%
3 296
 
13.5%
15 114
 
5.2%
32 1
 
< 0.1%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
영업중
1779 
폐업
296 
전출
 
114
신고취소
 
1

Length

Max length4
Median length3
Mean length2.813242
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 1779
81.2%
폐업 296
 
13.5%
전출 114
 
5.2%
신고취소 1
 
< 0.1%

Length

2024-05-11T07:50:46.177984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:50:46.713943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 1779
81.2%
폐업 296
 
13.5%
전출 114
 
5.2%
신고취소 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct364
Distinct (%)89.0%
Missing1781
Missing (%)81.3%
Memory size17.2 KiB
Minimum2006-01-18 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T07:50:47.125932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:50:47.844546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

전화번호
Text

MISSING 

Distinct855
Distinct (%)97.5%
Missing1313
Missing (%)60.0%
Memory size17.2 KiB
2024-05-11T07:50:48.787519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length11.021665
Min length7

Characters and Unicode

Total characters9666
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique834 ?
Unique (%)95.1%

Sample

1st row3467-9400
2nd row3218-8280
3rd row02-3019-3400
4th row02-3445-3319
5th row563-4822
ValueCountFrequency (%)
02-2017-1690 3
 
0.3%
02-552-1281 2
 
0.2%
02-542-9048 2
 
0.2%
02-3444-4460 2
 
0.2%
02-517-2671 2
 
0.2%
02-516-1797 2
 
0.2%
02-501-0251 2
 
0.2%
3444-5588 2
 
0.2%
02-2135-2567 2
 
0.2%
02-512-9579 2
 
0.2%
Other values (845) 856
97.6%
2024-05-11T07:50:50.205236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1555
16.1%
0 1520
15.7%
2 1315
13.6%
5 1061
11.0%
4 830
8.6%
1 644
6.7%
3 615
 
6.4%
7 598
 
6.2%
6 574
 
5.9%
8 540
 
5.6%
Other values (2) 414
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8110
83.9%
Dash Punctuation 1555
 
16.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1520
18.7%
2 1315
16.2%
5 1061
13.1%
4 830
10.2%
1 644
7.9%
3 615
7.6%
7 598
 
7.4%
6 574
 
7.1%
8 540
 
6.7%
9 413
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1555
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1555
16.1%
0 1520
15.7%
2 1315
13.6%
5 1061
11.0%
4 830
8.6%
1 644
6.7%
3 615
 
6.4%
7 598
 
6.2%
6 574
 
5.9%
8 540
 
5.6%
Other values (2) 414
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1555
16.1%
0 1520
15.7%
2 1315
13.6%
5 1061
11.0%
4 830
8.6%
1 644
6.7%
3 615
 
6.4%
7 598
 
6.2%
6 574
 
5.9%
8 540
 
5.6%
Other values (2) 414
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)56.7%
Missing2040
Missing (%)93.2%
Infinite0
Infinite (%)0.0%
Mean135679.99
Minimum110310
Maximum137855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:50:50.759320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110310
5-th percentile135517
Q1135818.5
median135867
Q3135908
95-th percentile135956.55
Maximum137855
Range27545
Interquartile range (IQR)89.5

Descriptive statistics

Standard deviation2095.3003
Coefficient of variation (CV)0.015442958
Kurtosis147.12224
Mean135679.99
Median Absolute Deviation (MAD)46.5
Skewness-12.065947
Sum20351998
Variance4390283.2
MonotonicityNot monotonic
2024-05-11T07:50:51.183795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135891 5
 
0.2%
135517 5
 
0.2%
135815 5
 
0.2%
135818 4
 
0.2%
135812 4
 
0.2%
135895 4
 
0.2%
135908 4
 
0.2%
135816 4
 
0.2%
135513 3
 
0.1%
135832 3
 
0.1%
Other values (75) 109
 
5.0%
(Missing) 2040
93.2%
ValueCountFrequency (%)
110310 1
 
< 0.1%
135502 1
 
< 0.1%
135509 2
 
0.1%
135513 3
0.1%
135517 5
0.2%
135526 1
 
< 0.1%
135541 2
 
0.1%
135545 1
 
< 0.1%
135555 1
 
< 0.1%
135722 1
 
< 0.1%
ValueCountFrequency (%)
137855 1
 
< 0.1%
135995 2
0.1%
135963 1
 
< 0.1%
135962 3
0.1%
135957 1
 
< 0.1%
135956 1
 
< 0.1%
135954 2
0.1%
135953 1
 
< 0.1%
135952 2
0.1%
135951 2
0.1%
Distinct1165
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-05-11T07:50:51.858847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length24.792694
Min length14

Characters and Unicode

Total characters54296
Distinct characters438
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

Unique983 ?
Unique (%)44.9%

Sample

1st row서울특별시 강남구 신사동 ***-*번지
2nd row서울특별시 강남구 신사동 ***-**번지
3rd row서울특별시 강남구 논현동 ***-**번지 진영빌딩 *층
4th row서울특별시 강남구 청담동 **번지 키네마빌딩 *층
5th row서울특별시 강남구 도곡동 ***-**번지
ValueCountFrequency (%)
서울특별시 2189
21.0%
강남구 2185
20.9%
1105
10.6%
번지 1089
10.4%
논현동 764
 
7.3%
역삼동 486
 
4.7%
신사동 317
 
3.0%
282
 
2.7%
삼성동 256
 
2.5%
181
 
1.7%
Other values (875) 1585
15.2%
2024-05-11T07:50:53.064409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 10393
19.1%
9652
17.8%
2269
 
4.2%
2241
 
4.1%
2223
 
4.1%
2216
 
4.1%
2198
 
4.0%
2196
 
4.0%
2193
 
4.0%
2189
 
4.0%
Other values (428) 16526
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31842
58.6%
Other Punctuation 10432
 
19.2%
Space Separator 9652
 
17.8%
Dash Punctuation 1991
 
3.7%
Uppercase Letter 213
 
0.4%
Lowercase Letter 79
 
0.1%
Decimal Number 72
 
0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2269
 
7.1%
2241
 
7.0%
2223
 
7.0%
2216
 
7.0%
2198
 
6.9%
2196
 
6.9%
2193
 
6.9%
2189
 
6.9%
2189
 
6.9%
1162
 
3.6%
Other values (364) 10766
33.8%
Uppercase Letter
ValueCountFrequency (%)
S 23
 
10.8%
B 19
 
8.9%
E 17
 
8.0%
W 16
 
7.5%
T 14
 
6.6%
O 13
 
6.1%
I 11
 
5.2%
C 9
 
4.2%
A 9
 
4.2%
R 9
 
4.2%
Other values (15) 73
34.3%
Lowercase Letter
ValueCountFrequency (%)
e 13
16.5%
o 11
13.9%
r 10
12.7%
i 6
7.6%
k 5
 
6.3%
w 5
 
6.3%
l 5
 
6.3%
n 4
 
5.1%
s 3
 
3.8%
a 3
 
3.8%
Other values (9) 14
17.7%
Decimal Number
ValueCountFrequency (%)
1 15
20.8%
4 10
13.9%
3 10
13.9%
2 9
12.5%
7 7
9.7%
6 7
9.7%
0 6
 
8.3%
5 4
 
5.6%
8 3
 
4.2%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
* 10393
99.6%
, 27
 
0.3%
. 6
 
0.1%
& 5
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
9652
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1991
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31842
58.6%
Common 22162
40.8%
Latin 292
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2269
 
7.1%
2241
 
7.0%
2223
 
7.0%
2216
 
7.0%
2198
 
6.9%
2196
 
6.9%
2193
 
6.9%
2189
 
6.9%
2189
 
6.9%
1162
 
3.6%
Other values (364) 10766
33.8%
Latin
ValueCountFrequency (%)
S 23
 
7.9%
B 19
 
6.5%
E 17
 
5.8%
W 16
 
5.5%
T 14
 
4.8%
O 13
 
4.5%
e 13
 
4.5%
o 11
 
3.8%
I 11
 
3.8%
r 10
 
3.4%
Other values (34) 145
49.7%
Common
ValueCountFrequency (%)
* 10393
46.9%
9652
43.6%
- 1991
 
9.0%
, 27
 
0.1%
1 15
 
0.1%
4 10
 
< 0.1%
3 10
 
< 0.1%
2 9
 
< 0.1%
) 7
 
< 0.1%
7 7
 
< 0.1%
Other values (10) 41
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31842
58.6%
ASCII 22454
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 10393
46.3%
9652
43.0%
- 1991
 
8.9%
, 27
 
0.1%
S 23
 
0.1%
B 19
 
0.1%
E 17
 
0.1%
W 16
 
0.1%
1 15
 
0.1%
T 14
 
0.1%
Other values (54) 287
 
1.3%
Hangul
ValueCountFrequency (%)
2269
 
7.1%
2241
 
7.0%
2223
 
7.0%
2216
 
7.0%
2198
 
6.9%
2196
 
6.9%
2193
 
6.9%
2189
 
6.9%
2189
 
6.9%
1162
 
3.6%
Other values (364) 10766
33.8%
Distinct1646
Distinct (%)75.2%
Missing1
Missing (%)< 0.1%
Memory size17.2 KiB
2024-05-11T07:50:53.910316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length33.211512
Min length23

Characters and Unicode

Total characters72700
Distinct characters451
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

Unique1420 ?
Unique (%)64.9%

Sample

1st row서울특별시 강남구 강남대로 ***, *층 (신사동, ICT TOWER)
2nd row서울특별시 강남구 도산대로**길 ** (신사동)
3rd row서울특별시 강남구 선릉로 *** (논현동,진영빌딩 *층)
4th row서울특별시 강남구 선릉로 *** (청담동,키네마빌딩 *층)
5th row서울특별시 강남구 언주로 *** (도곡동)
ValueCountFrequency (%)
2200
15.9%
서울특별시 2188
15.8%
강남구 2184
15.8%
1082
 
7.8%
논현동 655
 
4.7%
572
 
4.1%
역삼동 424
 
3.1%
신사동 258
 
1.9%
논현로***길 221
 
1.6%
삼성동 221
 
1.6%
Other values (1126) 3859
27.8%
2024-05-11T07:50:55.184552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 12378
17.0%
12044
16.6%
2557
 
3.5%
2447
 
3.4%
2421
 
3.3%
2257
 
3.1%
, 2236
 
3.1%
2215
 
3.0%
2204
 
3.0%
2199
 
3.0%
Other values (441) 29742
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40917
56.3%
Other Punctuation 14627
 
20.1%
Space Separator 12044
 
16.6%
Close Punctuation 2195
 
3.0%
Open Punctuation 2195
 
3.0%
Dash Punctuation 282
 
0.4%
Uppercase Letter 260
 
0.4%
Decimal Number 94
 
0.1%
Lowercase Letter 79
 
0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2557
 
6.2%
2447
 
6.0%
2421
 
5.9%
2257
 
5.5%
2215
 
5.4%
2204
 
5.4%
2199
 
5.4%
2192
 
5.4%
2191
 
5.4%
2188
 
5.3%
Other values (378) 18046
44.1%
Uppercase Letter
ValueCountFrequency (%)
B 48
18.5%
S 26
 
10.0%
E 18
 
6.9%
W 16
 
6.2%
O 15
 
5.8%
T 14
 
5.4%
C 13
 
5.0%
A 12
 
4.6%
I 12
 
4.6%
R 10
 
3.8%
Other values (15) 76
29.2%
Lowercase Letter
ValueCountFrequency (%)
e 12
15.2%
o 10
12.7%
r 9
11.4%
i 6
 
7.6%
k 5
 
6.3%
l 5
 
6.3%
s 4
 
5.1%
w 4
 
5.1%
n 4
 
5.1%
b 3
 
3.8%
Other values (9) 17
21.5%
Decimal Number
ValueCountFrequency (%)
1 20
21.3%
3 15
16.0%
2 13
13.8%
4 12
12.8%
5 10
10.6%
6 7
 
7.4%
0 7
 
7.4%
7 5
 
5.3%
9 5
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 12378
84.6%
, 2236
 
15.3%
. 7
 
< 0.1%
& 5
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12044
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2195
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 282
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40917
56.3%
Common 31444
43.3%
Latin 339
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2557
 
6.2%
2447
 
6.0%
2421
 
5.9%
2257
 
5.5%
2215
 
5.4%
2204
 
5.4%
2199
 
5.4%
2192
 
5.4%
2191
 
5.4%
2188
 
5.3%
Other values (378) 18046
44.1%
Latin
ValueCountFrequency (%)
B 48
 
14.2%
S 26
 
7.7%
E 18
 
5.3%
W 16
 
4.7%
O 15
 
4.4%
T 14
 
4.1%
C 13
 
3.8%
A 12
 
3.5%
I 12
 
3.5%
e 12
 
3.5%
Other values (34) 153
45.1%
Common
ValueCountFrequency (%)
* 12378
39.4%
12044
38.3%
, 2236
 
7.1%
) 2195
 
7.0%
( 2195
 
7.0%
- 282
 
0.9%
1 20
 
0.1%
3 15
 
< 0.1%
2 13
 
< 0.1%
4 12
 
< 0.1%
Other values (9) 54
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40917
56.3%
ASCII 31783
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 12378
38.9%
12044
37.9%
, 2236
 
7.0%
) 2195
 
6.9%
( 2195
 
6.9%
- 282
 
0.9%
B 48
 
0.2%
S 26
 
0.1%
1 20
 
0.1%
E 18
 
0.1%
Other values (53) 341
 
1.1%
Hangul
ValueCountFrequency (%)
2557
 
6.2%
2447
 
6.0%
2421
 
5.9%
2257
 
5.5%
2215
 
5.4%
2204
 
5.4%
2199
 
5.4%
2192
 
5.4%
2191
 
5.4%
2188
 
5.3%
Other values (378) 18046
44.1%

도로명우편번호
Text

MISSING 

Distinct294
Distinct (%)16.4%
Missing395
Missing (%)18.0%
Memory size17.2 KiB
2024-05-11T07:50:56.069049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0206128
Min length5

Characters and Unicode

Total characters9012
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

Unique71 ?
Unique (%)4.0%

Sample

1st row06035
2nd row135919
3rd row06028
4th row06151
5th row06106
ValueCountFrequency (%)
06049 48
 
2.7%
06028 36
 
2.0%
06103 30
 
1.7%
06035 29
 
1.6%
06039 27
 
1.5%
06097 25
 
1.4%
06040 23
 
1.3%
06100 20
 
1.1%
06121 20
 
1.1%
06034 19
 
1.1%
Other values (284) 1518
84.6%
2024-05-11T07:50:57.296475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2879
31.9%
6 2037
22.6%
1 998
 
11.1%
2 686
 
7.6%
3 619
 
6.9%
4 486
 
5.4%
5 424
 
4.7%
9 344
 
3.8%
7 288
 
3.2%
8 246
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9007
99.9%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2879
32.0%
6 2037
22.6%
1 998
 
11.1%
2 686
 
7.6%
3 619
 
6.9%
4 486
 
5.4%
5 424
 
4.7%
9 344
 
3.8%
7 288
 
3.2%
8 246
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2879
31.9%
6 2037
22.6%
1 998
 
11.1%
2 686
 
7.6%
3 619
 
6.9%
4 486
 
5.4%
5 424
 
4.7%
9 344
 
3.8%
7 288
 
3.2%
8 246
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2879
31.9%
6 2037
22.6%
1 998
 
11.1%
2 686
 
7.6%
3 619
 
6.9%
4 486
 
5.4%
5 424
 
4.7%
9 344
 
3.8%
7 288
 
3.2%
8 246
 
2.7%
Distinct2152
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
2024-05-11T07:50:58.021268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length30
Mean length8.809589
Min length1

Characters and Unicode

Total characters19293
Distinct characters701
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

Unique2116 ?
Unique (%)96.6%

Sample

1st row작은별프로덕션
2nd row(주)오토오
3rd row이엠아이뮤직코리아(주)
4th row지오인터랙티브(주)
5th row(주)우정티엔씨
ValueCountFrequency (%)
주식회사 470
 
16.5%
스튜디오 15
 
0.5%
미디어 13
 
0.5%
엔터테인먼트 10
 
0.4%
프로덕션 9
 
0.3%
9
 
0.3%
픽쳐스 7
 
0.2%
컴퍼니 5
 
0.2%
유한회사 4
 
0.1%
크리에이티브 4
 
0.1%
Other values (2241) 2306
80.9%
2024-05-11T07:50:59.210945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1658
 
8.6%
( 1228
 
6.4%
) 1228
 
6.4%
809
 
4.2%
734
 
3.8%
664
 
3.4%
525
 
2.7%
486
 
2.5%
481
 
2.5%
419
 
2.2%
Other values (691) 11061
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15503
80.4%
Open Punctuation 1228
 
6.4%
Close Punctuation 1228
 
6.4%
Space Separator 664
 
3.4%
Lowercase Letter 276
 
1.4%
Uppercase Letter 275
 
1.4%
Decimal Number 82
 
0.4%
Other Punctuation 22
 
0.1%
Other Symbol 11
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1658
 
10.7%
809
 
5.2%
734
 
4.7%
525
 
3.4%
486
 
3.1%
481
 
3.1%
419
 
2.7%
294
 
1.9%
277
 
1.8%
261
 
1.7%
Other values (621) 9559
61.7%
Uppercase Letter
ValueCountFrequency (%)
T 23
 
8.4%
E 22
 
8.0%
I 20
 
7.3%
M 20
 
7.3%
C 18
 
6.5%
A 18
 
6.5%
S 15
 
5.5%
O 14
 
5.1%
R 13
 
4.7%
P 13
 
4.7%
Other values (16) 99
36.0%
Lowercase Letter
ValueCountFrequency (%)
i 31
11.2%
t 29
10.5%
n 25
 
9.1%
o 24
 
8.7%
e 22
 
8.0%
a 22
 
8.0%
r 18
 
6.5%
m 16
 
5.8%
u 13
 
4.7%
s 13
 
4.7%
Other values (14) 63
22.8%
Decimal Number
ValueCountFrequency (%)
2 17
20.7%
1 14
17.1%
0 11
13.4%
4 7
8.5%
5 7
8.5%
6 7
8.5%
3 7
8.5%
7 7
8.5%
9 3
 
3.7%
8 2
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 14
63.6%
, 4
 
18.2%
? 2
 
9.1%
/ 1
 
4.5%
& 1
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 1228
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1228
100.0%
Space Separator
ValueCountFrequency (%)
664
100.0%
Other Symbol
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15514
80.4%
Common 3228
 
16.7%
Latin 551
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1658
 
10.7%
809
 
5.2%
734
 
4.7%
525
 
3.4%
486
 
3.1%
481
 
3.1%
419
 
2.7%
294
 
1.9%
277
 
1.8%
261
 
1.7%
Other values (622) 9570
61.7%
Latin
ValueCountFrequency (%)
i 31
 
5.6%
t 29
 
5.3%
n 25
 
4.5%
o 24
 
4.4%
T 23
 
4.2%
E 22
 
4.0%
e 22
 
4.0%
a 22
 
4.0%
I 20
 
3.6%
M 20
 
3.6%
Other values (40) 313
56.8%
Common
ValueCountFrequency (%)
( 1228
38.0%
) 1228
38.0%
664
20.6%
2 17
 
0.5%
. 14
 
0.4%
1 14
 
0.4%
0 11
 
0.3%
4 7
 
0.2%
5 7
 
0.2%
6 7
 
0.2%
Other values (9) 31
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15503
80.4%
ASCII 3779
 
19.6%
None 11
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1658
 
10.7%
809
 
5.2%
734
 
4.7%
525
 
3.4%
486
 
3.1%
481
 
3.1%
419
 
2.7%
294
 
1.9%
277
 
1.8%
261
 
1.7%
Other values (621) 9559
61.7%
ASCII
ValueCountFrequency (%)
( 1228
32.5%
) 1228
32.5%
664
17.6%
i 31
 
0.8%
t 29
 
0.8%
n 25
 
0.7%
o 24
 
0.6%
T 23
 
0.6%
E 22
 
0.6%
e 22
 
0.6%
Other values (59) 483
 
12.8%
None
ValueCountFrequency (%)
11
100.0%

최종수정일자
Date

UNIQUE 

Distinct2190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
Minimum2006-07-21 11:45:59
Maximum2024-05-08 19:08:24
2024-05-11T07:50:59.535597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:50:59.934946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
I
1604 
U
583 
D
 
3

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 1604
73.2%
U 583
 
26.6%
D 3
 
0.1%

Length

2024-05-11T07:51:00.311582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:00.554186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1604
73.2%
u 583
 
26.6%
d 3
 
0.1%
Distinct812
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T07:51:00.994044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T07:51:01.430818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

좌표정보(X)
Real number (ℝ)

Distinct1620
Distinct (%)74.1%
Missing3
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean203349.58
Minimum198589.4
Maximum218725.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:51:02.075294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198589.4
5-th percentile201846
Q1202502.31
median203107.23
Q3203892.88
95-th percentile205428.09
Maximum218725.21
Range20135.806
Interquartile range (IQR)1390.5707

Descriptive statistics

Standard deviation1286.3148
Coefficient of variation (CV)0.006325633
Kurtosis13.428918
Mean203349.58
Median Absolute Deviation (MAD)678.43721
Skewness2.262863
Sum4.4472553 × 108
Variance1654605.8
MonotonicityNot monotonic
2024-05-11T07:51:02.549375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202425.73 14
 
0.6%
205079.418138107 12
 
0.5%
205271.275273064 10
 
0.5%
205130.591678902 8
 
0.4%
203607.068430001 7
 
0.3%
202608.967825196 6
 
0.3%
204829.390807866 6
 
0.3%
203588.048190661 6
 
0.3%
203879.036781778 5
 
0.2%
202484.065140723 5
 
0.2%
Other values (1610) 2108
96.3%
ValueCountFrequency (%)
198589.402656993 1
 
< 0.1%
198640.079735013 1
 
< 0.1%
201609.62721933 4
0.2%
201646.385389914 1
 
< 0.1%
201657.313312924 2
0.1%
201660.523554193 1
 
< 0.1%
201663.485596684 1
 
< 0.1%
201668.810439729 2
0.1%
201670.69965165 1
 
< 0.1%
201677.281063901 2
0.1%
ValueCountFrequency (%)
218725.209081123 1
< 0.1%
210256.790282349 1
< 0.1%
210026.550356859 1
< 0.1%
209897.807021555 1
< 0.1%
209536.907907099 2
0.1%
209253.71833848 2
0.1%
209160.342515348 1
< 0.1%
209144.783150288 1
< 0.1%
209135.58142461 1
< 0.1%
209088.967130828 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

Distinct1620
Distinct (%)74.1%
Missing3
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean445273.45
Minimum440266.5
Maximum465483.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:51:03.129901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440266.5
5-th percentile442735.7
Q1444631.52
median445521.92
Q3446211.64
95-th percentile446813.76
Maximum465483.59
Range25217.097
Interquartile range (IQR)1580.1196

Descriptive statistics

Standard deviation1339.181
Coefficient of variation (CV)0.0030075473
Kurtosis24.312906
Mean445273.45
Median Absolute Deviation (MAD)760.30519
Skewness0.77518356
Sum9.7381304 × 108
Variance1793405.7
MonotonicityNot monotonic
2024-05-11T07:51:03.571270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444852.88 14
 
0.6%
444869.834721154 12
 
0.5%
445852.638814088 10
 
0.5%
445590.096837802 8
 
0.4%
445315.578728921 7
 
0.3%
446548.09314484 6
 
0.3%
446875.023189828 6
 
0.3%
446183.368328818 6
 
0.3%
446972.586732853 5
 
0.2%
445740.326734106 5
 
0.2%
Other values (1610) 2108
96.3%
ValueCountFrequency (%)
440266.497436245 1
< 0.1%
440518.109999999 1
< 0.1%
440614.372755433 2
0.1%
441154.085897918 2
0.1%
441163.795720684 2
0.1%
441205.716346342 1
< 0.1%
441214.041021633 1
< 0.1%
441229.833327751 2
0.1%
441251.451660388 2
0.1%
441255.220213825 1
< 0.1%
ValueCountFrequency (%)
465483.594316613 1
< 0.1%
452660.293046982 1
< 0.1%
447491.028995399 1
< 0.1%
447386.554980471 1
< 0.1%
447305.523058661 1
< 0.1%
447304.209942729 1
< 0.1%
447287.490354431 1
< 0.1%
447266.572303873 2
0.1%
447256.953163375 1
< 0.1%
447256.825467548 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
비디오물제작업
1455 
<NA>
735 

Length

Max length7
Median length7
Mean length5.9931507
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비디오물제작업 1455
66.4%
<NA> 735
33.6%

Length

2024-05-11T07:51:04.085911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:04.445858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비디오물제작업 1455
66.4%
na 735
33.6%

문화사업자구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2023 
유통관련업
 
167

Length

Max length5
Median length4
Mean length4.0762557
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2023
92.4%
유통관련업 167
 
7.6%

Length

2024-05-11T07:51:04.654741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:04.928541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2023
92.4%
유통관련업 167
 
7.6%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)7.0%
Missing2062
Missing (%)94.2%
Infinite0
Infinite (%)0.0%
Mean0.7421875
Minimum0
Maximum16
Zeros114
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:51:05.122342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.6568767
Coefficient of variation (CV)3.5797917
Kurtosis20.479544
Mean0.7421875
Median Absolute Deviation (MAD)0
Skewness4.389808
Sum95
Variance7.0589936
MonotonicityNot monotonic
2024-05-11T07:51:05.465758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 114
 
5.2%
5 4
 
0.2%
15 2
 
0.1%
1 2
 
0.1%
7 2
 
0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
16 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 2062
94.2%
ValueCountFrequency (%)
0 114
5.2%
1 2
 
0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 4
 
0.2%
6 1
 
< 0.1%
7 2
 
0.1%
15 2
 
0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
15 2
 
0.1%
7 2
 
0.1%
6 1
 
< 0.1%
5 4
 
0.2%
4 1
 
< 0.1%
3 1
 
< 0.1%
1 2
 
0.1%
0 114
5.2%

주변환경명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing2189
Missing (%)> 99.9%
Memory size17.2 KiB
2024-05-11T07:51:05.883596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row유흥업소밀집지역
ValueCountFrequency (%)
유흥업소밀집지역 1
100.0%
2024-05-11T07:51:06.665663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Distinct518
Distinct (%)35.8%
Missing745
Missing (%)34.0%
Memory size17.2 KiB
2024-05-11T07:51:07.246380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length44
Mean length8.3439446
Min length2

Characters and Unicode

Total characters12057
Distinct characters279
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

Unique458 ?
Unique (%)31.7%

Sample

1st row비디오물제작
2nd row비디오물
3rd row비디오물
4th row비디오물
5th row비디오물
ValueCountFrequency (%)
비디오물 573
22.5%
제작 162
 
6.4%
비디오물제작업 161
 
6.3%
영상물 146
 
5.7%
광고 129
 
5.1%
홍보 75
 
2.9%
74
 
2.9%
영상 62
 
2.4%
홍보영상 62
 
2.4%
48
 
1.9%
Other values (451) 1052
41.4%
2024-05-11T07:51:09.128275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1154
 
9.6%
1100
 
9.1%
925
 
7.7%
906
 
7.5%
898
 
7.4%
790
 
6.6%
, 727
 
6.0%
701
 
5.8%
529
 
4.4%
524
 
4.3%
Other values (269) 3803
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9863
81.8%
Space Separator 1100
 
9.1%
Other Punctuation 737
 
6.1%
Uppercase Letter 203
 
1.7%
Decimal Number 68
 
0.6%
Open Punctuation 28
 
0.2%
Close Punctuation 27
 
0.2%
Lowercase Letter 20
 
0.2%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1154
11.7%
925
 
9.4%
906
 
9.2%
898
 
9.1%
790
 
8.0%
701
 
7.1%
529
 
5.4%
524
 
5.3%
311
 
3.2%
310
 
3.1%
Other values (219) 2815
28.5%
Uppercase Letter
ValueCountFrequency (%)
D 42
20.7%
V 42
20.7%
C 39
19.2%
F 30
14.8%
T 18
8.9%
R 10
 
4.9%
S 4
 
2.0%
G 3
 
1.5%
U 2
 
1.0%
B 2
 
1.0%
Other values (9) 11
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
c 3
15.0%
m 2
10.0%
o 2
10.0%
r 2
10.0%
f 1
 
5.0%
y 1
 
5.0%
a 1
 
5.0%
u 1
 
5.0%
l 1
 
5.0%
Other values (3) 3
15.0%
Decimal Number
ValueCountFrequency (%)
3 15
22.1%
2 10
14.7%
1 8
11.8%
0 7
10.3%
5 7
10.3%
6 6
 
8.8%
8 6
 
8.8%
4 5
 
7.4%
9 3
 
4.4%
7 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 727
98.6%
: 5
 
0.7%
/ 3
 
0.4%
? 2
 
0.3%
Space Separator
ValueCountFrequency (%)
1100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9863
81.8%
Common 1971
 
16.3%
Latin 223
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1154
11.7%
925
 
9.4%
906
 
9.2%
898
 
9.1%
790
 
8.0%
701
 
7.1%
529
 
5.4%
524
 
5.3%
311
 
3.2%
310
 
3.1%
Other values (219) 2815
28.5%
Latin
ValueCountFrequency (%)
D 42
18.8%
V 42
18.8%
C 39
17.5%
F 30
13.5%
T 18
8.1%
R 10
 
4.5%
S 4
 
1.8%
e 3
 
1.3%
c 3
 
1.3%
G 3
 
1.3%
Other values (22) 29
13.0%
Common
ValueCountFrequency (%)
1100
55.8%
, 727
36.9%
( 28
 
1.4%
) 27
 
1.4%
3 15
 
0.8%
- 11
 
0.6%
2 10
 
0.5%
1 8
 
0.4%
0 7
 
0.4%
5 7
 
0.4%
Other values (8) 31
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9863
81.8%
ASCII 2194
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1154
11.7%
925
 
9.4%
906
 
9.2%
898
 
9.1%
790
 
8.0%
701
 
7.1%
529
 
5.4%
524
 
5.3%
311
 
3.2%
310
 
3.1%
Other values (219) 2815
28.5%
ASCII
ValueCountFrequency (%)
1100
50.1%
, 727
33.1%
D 42
 
1.9%
V 42
 
1.9%
C 39
 
1.8%
F 30
 
1.4%
( 28
 
1.3%
) 27
 
1.2%
T 18
 
0.8%
3 15
 
0.7%
Other values (40) 126
 
5.7%

시설면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct655
Distinct (%)56.0%
Missing1020
Missing (%)46.6%
Infinite0
Infinite (%)0.0%
Mean404.49309
Minimum0
Maximum178347
Zeros122
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:51:09.936652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median69.855
Q3163.315
95-th percentile516.619
Maximum178347
Range178347
Interquartile range (IQR)162.315

Descriptive statistics

Standard deviation6044.446
Coefficient of variation (CV)14.943261
Kurtosis714.55601
Mean404.49309
Median Absolute Deviation (MAD)68.855
Skewness26.08349
Sum473256.92
Variance36535327
MonotonicityNot monotonic
2024-05-11T07:51:11.154009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 215
 
9.8%
0.0 122
 
5.6%
100.0 16
 
0.7%
30.0 16
 
0.7%
10.0 15
 
0.7%
99.0 14
 
0.6%
90.0 13
 
0.6%
3.3 12
 
0.5%
66.0 12
 
0.5%
50.0 8
 
0.4%
Other values (645) 727
33.2%
(Missing) 1020
46.6%
ValueCountFrequency (%)
0.0 122
5.6%
1.0 215
9.8%
1.44 1
 
< 0.1%
1.65 1
 
< 0.1%
3.0 1
 
< 0.1%
3.1 1
 
< 0.1%
3.3 12
 
0.5%
3.31 1
 
< 0.1%
4.0 2
 
0.1%
4.4 1
 
< 0.1%
ValueCountFrequency (%)
178347.0 1
< 0.1%
103126.0 1
< 0.1%
13478.75 1
< 0.1%
11982.62 1
< 0.1%
4953.37 1
< 0.1%
3882.2 1
< 0.1%
3754.58 1
< 0.1%
2582.0 1
< 0.1%
2013.97 1
< 0.1%
1923.0 1
< 0.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)6.6%
Missing2053
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean0.8540146
Minimum0
Maximum14
Zeros113
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size19.4 KiB
2024-05-11T07:51:11.757501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.3280266
Coefficient of variation (CV)2.7259799
Kurtosis13.055672
Mean0.8540146
Median Absolute Deviation (MAD)0
Skewness3.461625
Sum117
Variance5.419708
MonotonicityNot monotonic
2024-05-11T07:51:12.227474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 113
 
5.2%
4 8
 
0.4%
2 6
 
0.3%
5 3
 
0.1%
11 2
 
0.1%
9 2
 
0.1%
1 1
 
< 0.1%
14 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 2053
93.7%
ValueCountFrequency (%)
0 113
5.2%
1 1
 
< 0.1%
2 6
 
0.3%
3 1
 
< 0.1%
4 8
 
0.4%
5 3
 
0.1%
9 2
 
0.1%
11 2
 
0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
14 1
 
< 0.1%
11 2
 
0.1%
9 2
 
0.1%
5 3
 
0.1%
4 8
 
0.4%
3 1
 
< 0.1%
2 6
 
0.3%
1 1
 
< 0.1%
0 113
5.2%

지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2062 
0
 
115
1
 
8
2
 
4
7
 
1

Length

Max length4
Median length4
Mean length3.8246575
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> 2062
94.2%
0 115
 
5.3%
1 8
 
0.4%
2 4
 
0.2%
7 1
 
< 0.1%

Length

2024-05-11T07:51:12.910847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:13.614159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2062
94.2%
0 115
 
5.3%
1 8
 
0.4%
2 4
 
0.2%
7 1
 
< 0.1%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2182 
근린생활시설
 
5
사무실
 
2
단독주택
 
1

Length

Max length6
Median length4
Mean length4.003653
Min length3

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> 2182
99.6%
근린생활시설 5
 
0.2%
사무실 2
 
0.1%
단독주택 1
 
< 0.1%

Length

2024-05-11T07:51:14.250463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:14.847626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2182
99.6%
근린생활시설 5
 
0.2%
사무실 2
 
0.1%
단독주택 1
 
< 0.1%

통로너비
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2075 
0
 
115

Length

Max length4
Median length4
Mean length3.8424658
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> 2075
94.7%
0 115
 
5.3%

Length

2024-05-11T07:51:15.348700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:15.899511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
94.7%
0 115
 
5.3%

조명시설조도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2075 
0
 
115

Length

Max length4
Median length4
Mean length3.8424658
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> 2075
94.7%
0 115
 
5.3%

Length

2024-05-11T07:51:16.404845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:16.875734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
94.7%
0 115
 
5.3%

노래방실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2075 
0
 
115

Length

Max length4
Median length4
Mean length3.8424658
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> 2075
94.7%
0 115
 
5.3%

Length

2024-05-11T07:51:17.228128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:17.614215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
94.7%
0 115
 
5.3%

청소년실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2075 
0
 
115

Length

Max length4
Median length4
Mean length3.8424658
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> 2075
94.7%
0 115
 
5.3%

Length

2024-05-11T07:51:18.126034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:18.492145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
94.7%
0 115
 
5.3%

비상계단여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

비상구여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

자동환기여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

청소년실여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

특수조명여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

방음시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

비디오재생기명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

조명시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

음향시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

편의시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

소방시설여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

총게임기수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.2 KiB
<NA>
2075 
0
 
115

Length

Max length4
Median length4
Mean length3.8424658
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> 2075
94.7%
0 115
 
5.3%

Length

2024-05-11T07:51:18.811496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T07:51:19.186645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2075
94.7%
0 115
 
5.3%

기존게임업외업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

제공게임물명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

공연장형태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

품목명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

최초등록시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2190
Missing (%)100.0%
Memory size19.4 KiB

지역구분명
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing2184
Missing (%)99.7%
Memory size17.2 KiB
2024-05-11T07:51:19.525875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.1666667
Min length4

Characters and Unicode

Total characters31
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row주거지역
2nd row주거지역
3rd row일반주거지역
4th row준공업지역
5th row일반주거지역
ValueCountFrequency (%)
주거지역 2
33.3%
일반주거지역 2
33.3%
준공업지역 1
16.7%
중심상업지역 1
16.7%
2024-05-11T07:51:20.671107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
19.4%
6
19.4%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (2) 2
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
19.4%
6
19.4%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (2) 2
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
19.4%
6
19.4%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (2) 2
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
19.4%
6
19.4%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
1
 
3.2%
1
 
3.2%
Other values (2) 2
 
6.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명총층수주변환경명제작취급품목내용시설면적지상층수지하층수건물용도명통로너비조명시설조도노래방실수청소년실수비상계단여부비상구여부자동환기여부청소년실여부특수조명여부방음시설여부비디오재생기명조명시설유무음향시설여부편의시설여부소방시설여부총게임기수기존게임업외업종명제공게임물명공연장형태구분명품목명최초등록시점지역구분명
03220000CDFF124107198900000119891103<NA>3폐업3폐업20160126<NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 ***-*번지서울특별시 강남구 강남대로 ***, *층 (신사동, ICT TOWER)06035작은별프로덕션2016-01-26 14:15:40I2018-08-31 23:59:59.0<NA>201657.313313446139.884099비디오물제작업<NA><NA><NA>비디오물제작<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13220000CDFF124107199500000119950308<NA>3폐업3폐업20100112<NA><NA><NA><NA><NA><NA>서울특별시 강남구 신사동 ***-**번지서울특별시 강남구 도산대로**길 ** (신사동)<NA>(주)오토오2010-01-12 10:04:16I2018-08-31 23:59:59.0<NA>202057.834995446536.454402비디오물제작업<NA><NA><NA>비디오물<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23220000CDFF124107199900000119991213<NA>3폐업3폐업20090227<NA><NA><NA>3467-9400<NA>135833서울특별시 강남구 논현동 ***-**번지 진영빌딩 *층서울특별시 강남구 선릉로 *** (논현동,진영빌딩 *층)<NA>이엠아이뮤직코리아(주)2009-02-27 17:13:58I2018-08-31 23:59:59.0<NA>203736.905005445476.2982비디오물제작업<NA><NA><NA>비디오물<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33220000CDFF124107199900000219990603<NA>3폐업3폐업20080314<NA><NA><NA>3218-8280<NA>135954서울특별시 강남구 청담동 **번지 키네마빌딩 *층서울특별시 강남구 선릉로 *** (청담동,키네마빌딩 *층)<NA>지오인터랙티브(주)2008-03-14 17:24:35I2018-08-31 23:59:59.0<NA>203432.518476446848.284082비디오물제작업유통관련업<NA><NA>비디오물<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43220000CDFF124107199900000419990608<NA>3폐업3폐업20080731<NA><NA><NA><NA><NA>135856서울특별시 강남구 도곡동 ***-**번지서울특별시 강남구 언주로 *** (도곡동)<NA>(주)우정티엔씨2008-07-31 18:17:34I2018-08-31 23:59:59.0<NA>204463.672146442729.658559비디오물제작업유통관련업<NA><NA>비디오물<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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