Overview

Dataset statistics

Number of variables60
Number of observations79
Missing cells2059
Missing cells (%)43.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.2 KiB
Average record size in memory521.7 B

Variable types

Categorical21
Text9
DateTime4
Unsupported16
Numeric10

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,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-17622/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
지역구분명 is highly imbalanced (67.9%)Imbalance
주변환경명 is highly imbalanced (71.5%)Imbalance
지하층수 is highly imbalanced (78.2%)Imbalance
객실수 is highly imbalanced (90.2%)Imbalance
건축연면적 is highly imbalanced (90.2%)Imbalance
영문상호주소 is highly imbalanced (54.3%)Imbalance
선박총톤수 is highly imbalanced (90.2%)Imbalance
선박척수 is highly imbalanced (90.2%)Imbalance
무대면적 is highly imbalanced (90.2%)Imbalance
좌석수 is highly imbalanced (90.2%)Imbalance
회의실별동시수용인원 is highly imbalanced (90.2%)Imbalance
놀이시설수 is highly imbalanced (90.2%)Imbalance
기획여행보험시작일자 is highly imbalanced (90.2%)Imbalance
기획여행보험종료일자 is highly imbalanced (90.2%)Imbalance
인허가취소일자 has 79 (100.0%) missing valuesMissing
폐업일자 has 53 (67.1%) missing valuesMissing
휴업시작일자 has 79 (100.0%) missing valuesMissing
휴업종료일자 has 79 (100.0%) missing valuesMissing
재개업일자 has 79 (100.0%) missing valuesMissing
전화번호 has 46 (58.2%) missing valuesMissing
소재지면적 has 79 (100.0%) missing valuesMissing
소재지우편번호 has 69 (87.3%) missing valuesMissing
도로명우편번호 has 1 (1.3%) missing valuesMissing
업태구분명 has 79 (100.0%) missing valuesMissing
문화사업자구분명 has 79 (100.0%) missing valuesMissing
총층수 has 69 (87.3%) missing valuesMissing
제작취급품목내용 has 79 (100.0%) missing valuesMissing
보험기관명 has 58 (73.4%) missing valuesMissing
건물용도명 has 70 (88.6%) missing valuesMissing
지상층수 has 69 (87.3%) missing valuesMissing
영문상호명 has 63 (79.7%) missing valuesMissing
선박제원 has 79 (100.0%) missing valuesMissing
기념품종류 has 79 (100.0%) missing valuesMissing
시설면적 has 65 (82.3%) missing valuesMissing
놀이기구수내역 has 79 (100.0%) missing valuesMissing
방송시설유무 has 79 (100.0%) missing valuesMissing
발전시설유무 has 79 (100.0%) missing valuesMissing
의무실유무 has 79 (100.0%) missing valuesMissing
안내소유무 has 79 (100.0%) missing valuesMissing
자본금 has 55 (69.6%) missing valuesMissing
보험시작일자 has 56 (70.9%) missing valuesMissing
보험종료일자 has 56 (70.9%) missing valuesMissing
부대시설내역 has 79 (100.0%) missing valuesMissing
시설규모 has 65 (82.3%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
문화사업자구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 1 (1.3%) zerosZeros
지상층수 has 1 (1.3%) zerosZeros
시설면적 has 1 (1.3%) zerosZeros
자본금 has 1 (1.3%) zerosZeros
시설규모 has 1 (1.3%) zerosZeros

Reproduction

Analysis started2024-05-11 06:38:47.190119
Analysis finished2024-05-11 06:38:48.393130
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
3200000
79 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 79
100.0%

Length

2024-05-11T15:38:48.495492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:48.644280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 79
100.0%

관리번호
Text

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-05-11T15:38:48.925227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1580
Distinct characters14
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

Unique79 ?
Unique (%)100.0%

Sample

1st rowCDFI2260042010000001
2nd rowCDFI2260042012000001
3rd rowCDFI2260042013000002
4th rowCDFI2260042013000006
5th rowCDFI2260042014000002
ValueCountFrequency (%)
cdfi2260042010000001 1
 
1.3%
cdfi2260042022000009 1
 
1.3%
cdfi2260042022000006 1
 
1.3%
cdfi2260042022000005 1
 
1.3%
cdfi2260042022000004 1
 
1.3%
cdfi2260042022000003 1
 
1.3%
cdfi2260042022000002 1
 
1.3%
cdfi2260042022000001 1
 
1.3%
cdfi2260042021000009 1
 
1.3%
cdfi2260042021000007 1
 
1.3%
Other values (69) 69
87.3%
2024-05-11T15:38:49.459925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 639
40.4%
2 306
19.4%
4 95
 
6.0%
6 92
 
5.8%
C 79
 
5.0%
D 79
 
5.0%
F 79
 
5.0%
I 79
 
5.0%
1 62
 
3.9%
3 20
 
1.3%
Other values (4) 50
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1264
80.0%
Uppercase Letter 316
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 639
50.6%
2 306
24.2%
4 95
 
7.5%
6 92
 
7.3%
1 62
 
4.9%
3 20
 
1.6%
8 15
 
1.2%
7 13
 
1.0%
5 11
 
0.9%
9 11
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 79
25.0%
D 79
25.0%
F 79
25.0%
I 79
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1264
80.0%
Latin 316
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 639
50.6%
2 306
24.2%
4 95
 
7.5%
6 92
 
7.3%
1 62
 
4.9%
3 20
 
1.6%
8 15
 
1.2%
7 13
 
1.0%
5 11
 
0.9%
9 11
 
0.9%
Latin
ValueCountFrequency (%)
C 79
25.0%
D 79
25.0%
F 79
25.0%
I 79
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 639
40.4%
2 306
19.4%
4 95
 
6.0%
6 92
 
5.8%
C 79
 
5.0%
D 79
 
5.0%
F 79
 
5.0%
I 79
 
5.0%
1 62
 
3.9%
3 20
 
1.3%
Other values (4) 50
 
3.2%
Distinct75
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum1988-12-19 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:38:49.703285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:38:49.980980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B
Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
1
53 
3
15 
5
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 53
67.1%
3 15
 
19.0%
5 11
 
13.9%

Length

2024-05-11T15:38:50.182354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:50.350659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 53
67.1%
3 15
 
19.0%
5 11
 
13.9%

영업상태명
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
영업/정상
53 
폐업
15 
제외/삭제/전출
11 

Length

Max length8
Median length5
Mean length4.8481013
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 53
67.1%
폐업 15
 
19.0%
제외/삭제/전출 11
 
13.9%

Length

2024-05-11T15:38:50.540331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:50.745955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 53
67.1%
폐업 15
 
19.0%
제외/삭제/전출 11
 
13.9%
Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
13
53 
3
15 
15
11 

Length

Max length2
Median length2
Mean length1.8101266
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row3

Common Values

ValueCountFrequency (%)
13 53
67.1%
3 15
 
19.0%
15 11
 
13.9%

Length

2024-05-11T15:38:50.948349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:51.141416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 53
67.1%
3 15
 
19.0%
15 11
 
13.9%
Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
영업중
53 
폐업
15 
전출
11 

Length

Max length3
Median length3
Mean length2.6708861
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 53
67.1%
폐업 15
 
19.0%
전출 11
 
13.9%

Length

2024-05-11T15:38:51.341357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:51.529501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 53
67.1%
폐업 15
 
19.0%
전출 11
 
13.9%

폐업일자
Date

MISSING 

Distinct26
Distinct (%)100.0%
Missing53
Missing (%)67.1%
Memory size764.0 B
Minimum2015-02-17 00:00:00
Maximum2024-04-12 00:00:00
2024-05-11T15:38:51.676498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:38:51.837388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

전화번호
Text

MISSING 

Distinct32
Distinct (%)97.0%
Missing46
Missing (%)58.2%
Memory size764.0 B
2024-05-11T15:38:52.240966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length11.454545
Min length8

Characters and Unicode

Total characters378
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st row1661-1924
2nd row02-888-3353
3rd row02-829-0922,0917
4th row02-6912-4890
5th row02-3141-6666
ValueCountFrequency (%)
02-3141-6666 2
 
5.9%
1833-9858 1
 
2.9%
02-468-1178 1
 
2.9%
02-877-7200 1
 
2.9%
02-888-2666 1
 
2.9%
02-776-5088 1
 
2.9%
02-757-7789 1
 
2.9%
02-829-1511 1
 
2.9%
02-1800-5248 1
 
2.9%
858-3580 1
 
2.9%
Other values (23) 23
67.6%
2024-05-11T15:38:52.821620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 55
14.6%
- 55
14.6%
8 53
14.0%
2 51
13.5%
6 30
7.9%
1 28
7.4%
3 27
7.1%
7 22
 
5.8%
5 18
 
4.8%
4 17
 
4.5%
Other values (5) 22
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 317
83.9%
Dash Punctuation 55
 
14.6%
Space Separator 3
 
0.8%
Other Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
17.4%
8 53
16.7%
2 51
16.1%
6 30
9.5%
1 28
8.8%
3 27
8.5%
7 22
 
6.9%
5 18
 
5.7%
4 17
 
5.4%
9 16
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 55
14.6%
- 55
14.6%
8 53
14.0%
2 51
13.5%
6 30
7.9%
1 28
7.4%
3 27
7.1%
7 22
 
5.8%
5 18
 
4.8%
4 17
 
4.5%
Other values (5) 22
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 55
14.6%
- 55
14.6%
8 53
14.0%
2 51
13.5%
6 30
7.9%
1 28
7.4%
3 27
7.1%
7 22
 
5.8%
5 18
 
4.8%
4 17
 
4.5%
Other values (5) 22
 
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

소재지우편번호
Text

MISSING 

Distinct7
Distinct (%)70.0%
Missing69
Missing (%)87.3%
Memory size764.0 B
2024-05-11T15:38:53.076003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1
Min length6

Characters and Unicode

Total characters61
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

Unique5 ?
Unique (%)50.0%

Sample

1st row151836
2nd row151800
3rd row151-844
4th row151706
5th row151827
ValueCountFrequency (%)
151706 3
30.0%
151015 2
20.0%
151836 1
 
10.0%
151800 1
 
10.0%
151-844 1
 
10.0%
151827 1
 
10.0%
151891 1
 
10.0%
2024-05-11T15:38:53.518986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
37.7%
5 12
19.7%
0 7
 
11.5%
8 5
 
8.2%
7 4
 
6.6%
6 4
 
6.6%
4 2
 
3.3%
3 1
 
1.6%
- 1
 
1.6%
2 1
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
98.4%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
38.3%
5 12
20.0%
0 7
 
11.7%
8 5
 
8.3%
7 4
 
6.7%
6 4
 
6.7%
4 2
 
3.3%
3 1
 
1.7%
2 1
 
1.7%
9 1
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
37.7%
5 12
19.7%
0 7
 
11.5%
8 5
 
8.2%
7 4
 
6.6%
6 4
 
6.6%
4 2
 
3.3%
3 1
 
1.6%
- 1
 
1.6%
2 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
37.7%
5 12
19.7%
0 7
 
11.5%
8 5
 
8.2%
7 4
 
6.6%
6 4
 
6.6%
4 2
 
3.3%
3 1
 
1.6%
- 1
 
1.6%
2 1
 
1.6%
Distinct77
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-05-11T15:38:54.008785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length26.822785
Min length19

Characters and Unicode

Total characters2119
Distinct characters139
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

Unique75 ?
Unique (%)94.9%

Sample

1st row서울특별시 관악구 봉천동 865-2번지 세종빌딩 217호
2nd row서울특별시 관악구 남현동 1061-18번지 르메에르간남타운2, 1-지-2호
3rd row서울특별시 관악구 봉천동 930-20 1층
4th row서울특별시 관악구 봉천동 729-21 대교타워, 6층
5th row서울특별시 관악구 봉천동 949-18번지 B09호
ValueCountFrequency (%)
서울특별시 79
19.2%
관악구 79
19.2%
신림동 34
 
8.3%
봉천동 34
 
8.3%
남현동 11
 
2.7%
대교타워 5
 
1.2%
1층 5
 
1.2%
2층 4
 
1.0%
729-21 4
 
1.0%
3층 4
 
1.0%
Other values (131) 152
37.0%
2024-05-11T15:38:54.762513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
 
16.3%
1 108
 
5.1%
83
 
3.9%
83
 
3.9%
82
 
3.9%
- 81
 
3.8%
80
 
3.8%
80
 
3.8%
80
 
3.8%
79
 
3.7%
Other values (129) 1017
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1186
56.0%
Decimal Number 486
22.9%
Space Separator 346
 
16.3%
Dash Punctuation 81
 
3.8%
Uppercase Letter 8
 
0.4%
Lowercase Letter 6
 
0.3%
Other Punctuation 4
 
0.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
83
 
7.0%
83
 
7.0%
82
 
6.9%
80
 
6.7%
80
 
6.7%
80
 
6.7%
79
 
6.7%
79
 
6.7%
79
 
6.7%
37
 
3.1%
Other values (100) 424
35.8%
Decimal Number
ValueCountFrequency (%)
1 108
22.2%
2 67
13.8%
0 53
10.9%
6 43
 
8.8%
8 41
 
8.4%
4 39
 
8.0%
7 35
 
7.2%
3 35
 
7.2%
9 33
 
6.8%
5 32
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
A 1
12.5%
C 1
12.5%
M 1
12.5%
B 1
12.5%
T 1
12.5%
L 1
12.5%
W 1
12.5%
G 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
16.7%
r 1
16.7%
w 1
16.7%
o 1
16.7%
z 1
16.7%
i 1
16.7%
Space Separator
ValueCountFrequency (%)
346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1186
56.0%
Common 919
43.4%
Latin 14
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
83
 
7.0%
83
 
7.0%
82
 
6.9%
80
 
6.7%
80
 
6.7%
80
 
6.7%
79
 
6.7%
79
 
6.7%
79
 
6.7%
37
 
3.1%
Other values (100) 424
35.8%
Common
ValueCountFrequency (%)
346
37.6%
1 108
 
11.8%
- 81
 
8.8%
2 67
 
7.3%
0 53
 
5.8%
6 43
 
4.7%
8 41
 
4.5%
4 39
 
4.2%
7 35
 
3.8%
3 35
 
3.8%
Other values (5) 71
 
7.7%
Latin
ValueCountFrequency (%)
A 1
 
7.1%
e 1
 
7.1%
r 1
 
7.1%
w 1
 
7.1%
C 1
 
7.1%
M 1
 
7.1%
o 1
 
7.1%
B 1
 
7.1%
T 1
 
7.1%
L 1
 
7.1%
Other values (4) 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1186
56.0%
ASCII 933
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
346
37.1%
1 108
 
11.6%
- 81
 
8.7%
2 67
 
7.2%
0 53
 
5.7%
6 43
 
4.6%
8 41
 
4.4%
4 39
 
4.2%
7 35
 
3.8%
3 35
 
3.8%
Other values (19) 85
 
9.1%
Hangul
ValueCountFrequency (%)
83
 
7.0%
83
 
7.0%
82
 
6.9%
80
 
6.7%
80
 
6.7%
80
 
6.7%
79
 
6.7%
79
 
6.7%
79
 
6.7%
37
 
3.1%
Other values (100) 424
35.8%
Distinct78
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-05-11T15:38:55.281367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length34.379747
Min length24

Characters and Unicode

Total characters2716
Distinct characters163
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

Unique77 ?
Unique (%)97.5%

Sample

1st row서울특별시 관악구 관악로13길 25, 217호 (봉천동,세종빌딩)
2nd row서울특별시 관악구 과천대로 939 (남현동)
3rd row서울특별시 관악구 장군봉1길 13, 1층 (봉천동)
4th row서울특별시 관악구 보라매로3길 23, 6층 (봉천동, 대교타워)
5th row서울특별시 관악구 남부순환로 1679, B09호 (봉천동)
ValueCountFrequency (%)
서울특별시 79
 
14.6%
관악구 79
 
14.6%
신림동 34
 
6.3%
봉천동 33
 
6.1%
남부순환로 14
 
2.6%
남현동 11
 
2.0%
1층 11
 
2.0%
2층 11
 
2.0%
23 8
 
1.5%
3층 8
 
1.5%
Other values (183) 254
46.9%
2024-05-11T15:38:55.953661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
463
 
17.0%
1 104
 
3.8%
92
 
3.4%
, 92
 
3.4%
88
 
3.2%
86
 
3.2%
80
 
2.9%
80
 
2.9%
( 80
 
2.9%
) 80
 
2.9%
Other values (153) 1471
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1536
56.6%
Space Separator 463
 
17.0%
Decimal Number 443
 
16.3%
Other Punctuation 92
 
3.4%
Open Punctuation 80
 
2.9%
Close Punctuation 80
 
2.9%
Uppercase Letter 10
 
0.4%
Dash Punctuation 6
 
0.2%
Lowercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
92
 
6.0%
88
 
5.7%
86
 
5.6%
80
 
5.2%
80
 
5.2%
80
 
5.2%
79
 
5.1%
79
 
5.1%
79
 
5.1%
67
 
4.4%
Other values (124) 726
47.3%
Decimal Number
ValueCountFrequency (%)
1 104
23.5%
2 65
14.7%
3 54
12.2%
0 50
11.3%
4 36
 
8.1%
7 31
 
7.0%
8 29
 
6.5%
5 27
 
6.1%
9 27
 
6.1%
6 20
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
20.0%
B 2
20.0%
C 1
10.0%
M 1
10.0%
T 1
10.0%
L 1
10.0%
W 1
10.0%
G 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
16.7%
r 1
16.7%
e 1
16.7%
o 1
16.7%
z 1
16.7%
i 1
16.7%
Space Separator
ValueCountFrequency (%)
463
100.0%
Other Punctuation
ValueCountFrequency (%)
, 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1536
56.6%
Common 1164
42.9%
Latin 16
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
92
 
6.0%
88
 
5.7%
86
 
5.6%
80
 
5.2%
80
 
5.2%
80
 
5.2%
79
 
5.1%
79
 
5.1%
79
 
5.1%
67
 
4.4%
Other values (124) 726
47.3%
Common
ValueCountFrequency (%)
463
39.8%
1 104
 
8.9%
, 92
 
7.9%
( 80
 
6.9%
) 80
 
6.9%
2 65
 
5.6%
3 54
 
4.6%
0 50
 
4.3%
4 36
 
3.1%
7 31
 
2.7%
Other values (5) 109
 
9.4%
Latin
ValueCountFrequency (%)
A 2
12.5%
B 2
12.5%
w 1
 
6.2%
r 1
 
6.2%
e 1
 
6.2%
o 1
 
6.2%
C 1
 
6.2%
M 1
 
6.2%
T 1
 
6.2%
L 1
 
6.2%
Other values (4) 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1536
56.6%
ASCII 1180
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
463
39.2%
1 104
 
8.8%
, 92
 
7.8%
( 80
 
6.8%
) 80
 
6.8%
2 65
 
5.5%
3 54
 
4.6%
0 50
 
4.2%
4 36
 
3.1%
7 31
 
2.6%
Other values (19) 125
 
10.6%
Hangul
ValueCountFrequency (%)
92
 
6.0%
88
 
5.7%
86
 
5.6%
80
 
5.2%
80
 
5.2%
80
 
5.2%
79
 
5.1%
79
 
5.1%
79
 
5.1%
67
 
4.4%
Other values (124) 726
47.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)53.8%
Missing1
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean10605.449
Minimum8702
Maximum151891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:38:56.216711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8702
5-th percentile8705
Q18754
median8773
Q38805
95-th percentile8839.05
Maximum151891
Range143189
Interquartile range (IQR)51

Descriptive statistics

Standard deviation16205.242
Coefficient of variation (CV)1.528011
Kurtosis77.999105
Mean10605.449
Median Absolute Deviation (MAD)21
Skewness8.8316858
Sum827225
Variance2.6260987 × 108
MonotonicityNot monotonic
2024-05-11T15:38:56.436101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
8807 6
 
7.6%
8708 6
 
7.6%
8806 5
 
6.3%
8787 4
 
5.1%
8758 4
 
5.1%
8752 3
 
3.8%
8705 3
 
3.8%
8813 2
 
2.5%
8737 2
 
2.5%
8754 2
 
2.5%
Other values (32) 41
51.9%
ValueCountFrequency (%)
8702 2
 
2.5%
8705 3
3.8%
8706 1
 
1.3%
8708 6
7.6%
8715 1
 
1.3%
8729 1
 
1.3%
8737 2
 
2.5%
8752 3
3.8%
8754 2
 
2.5%
8756 2
 
2.5%
ValueCountFrequency (%)
151891 1
 
1.3%
8856 1
 
1.3%
8849 1
 
1.3%
8845 1
 
1.3%
8838 1
 
1.3%
8826 1
 
1.3%
8816 1
 
1.3%
8813 2
 
2.5%
8807 6
7.6%
8806 5
6.3%
Distinct77
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
2024-05-11T15:38:56.936944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length17
Mean length9.3924051
Min length2

Characters and Unicode

Total characters742
Distinct characters189
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)94.9%

Sample

1st row초록별여행사
2nd row주식회사 세계정복
3rd row(주)아세아상사
4th row(주)대교
5th row신세계 국제교류중심
ValueCountFrequency (%)
주식회사 28
 
21.2%
여행사 3
 
2.3%
나우여행 2
 
1.5%
대교에듀캠프 2
 
1.5%
주)부미 1
 
0.8%
예가드림코리아(yega 1
 
0.8%
컴퍼니 1
 
0.8%
휴먼스 1
 
0.8%
1
 
0.8%
초록별여행사 1
 
0.8%
Other values (91) 91
68.9%
2024-05-11T15:38:57.807547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53
 
7.1%
50
 
6.7%
45
 
6.1%
30
 
4.0%
30
 
4.0%
( 27
 
3.6%
) 27
 
3.6%
25
 
3.4%
22
 
3.0%
17
 
2.3%
Other values (179) 416
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 542
73.0%
Space Separator 53
 
7.1%
Uppercase Letter 50
 
6.7%
Lowercase Letter 39
 
5.3%
Open Punctuation 27
 
3.6%
Close Punctuation 27
 
3.6%
Other Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
9.2%
45
 
8.3%
30
 
5.5%
30
 
5.5%
25
 
4.6%
22
 
4.1%
17
 
3.1%
15
 
2.8%
14
 
2.6%
13
 
2.4%
Other values (137) 281
51.8%
Uppercase Letter
ValueCountFrequency (%)
A 5
 
10.0%
T 5
 
10.0%
S 4
 
8.0%
O 4
 
8.0%
K 3
 
6.0%
I 3
 
6.0%
R 3
 
6.0%
E 3
 
6.0%
L 3
 
6.0%
F 2
 
4.0%
Other values (11) 15
30.0%
Lowercase Letter
ValueCountFrequency (%)
n 7
17.9%
a 5
12.8%
l 5
12.8%
e 4
10.3%
g 3
7.7%
s 2
 
5.1%
r 2
 
5.1%
i 2
 
5.1%
d 2
 
5.1%
h 1
 
2.6%
Other values (6) 6
15.4%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 542
73.0%
Common 111
 
15.0%
Latin 89
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
9.2%
45
 
8.3%
30
 
5.5%
30
 
5.5%
25
 
4.6%
22
 
4.1%
17
 
3.1%
15
 
2.8%
14
 
2.6%
13
 
2.4%
Other values (137) 281
51.8%
Latin
ValueCountFrequency (%)
n 7
 
7.9%
a 5
 
5.6%
A 5
 
5.6%
T 5
 
5.6%
l 5
 
5.6%
S 4
 
4.5%
O 4
 
4.5%
e 4
 
4.5%
K 3
 
3.4%
I 3
 
3.4%
Other values (27) 44
49.4%
Common
ValueCountFrequency (%)
53
47.7%
( 27
24.3%
) 27
24.3%
. 3
 
2.7%
, 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 542
73.0%
ASCII 200
 
27.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53
26.5%
( 27
13.5%
) 27
13.5%
n 7
 
3.5%
a 5
 
2.5%
A 5
 
2.5%
T 5
 
2.5%
l 5
 
2.5%
S 4
 
2.0%
O 4
 
2.0%
Other values (32) 58
29.0%
Hangul
ValueCountFrequency (%)
50
 
9.2%
45
 
8.3%
30
 
5.5%
30
 
5.5%
25
 
4.6%
22
 
4.1%
17
 
3.1%
15
 
2.8%
14
 
2.6%
13
 
2.4%
Other values (137) 281
51.8%

최종수정일자
Date

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum2012-10-22 20:47:11
Maximum2024-05-09 13:55:25
2024-05-11T15:38:58.005954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:38:58.214778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
U
66 
I
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 66
83.5%
I 13
 
16.5%

Length

2024-05-11T15:38:58.395768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:38:58.526254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 66
83.5%
i 13
 
16.5%
Distinct65
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:38:58.692853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:38:58.893662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

좌표정보(X)
Real number (ℝ)

Distinct63
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194714.18
Minimum191470.7
Maximum198284.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:38:59.156730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191470.7
5-th percentile192221.04
Q1193350.03
median194390.84
Q3195588.8
95-th percentile198222.01
Maximum198284.08
Range6813.3764
Interquartile range (IQR)2238.7695

Descriptive statistics

Standard deviation1896.1934
Coefficient of variation (CV)0.0097383429
Kurtosis-0.60551151
Mean194714.18
Median Absolute Deviation (MAD)1191.9747
Skewness0.46681329
Sum15382420
Variance3595549.5
MonotonicityNot monotonic
2024-05-11T15:38:59.424114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193350.027022729 5
 
6.3%
195588.796492288 3
 
3.8%
198284.078546351 3
 
3.8%
198194.309937956 3
 
3.8%
193746.833837509 2
 
2.5%
193610.797201552 2
 
2.5%
194386.133620309 2
 
2.5%
192221.040621527 2
 
2.5%
193089.988362527 2
 
2.5%
194390.838261699 2
 
2.5%
Other values (53) 53
67.1%
ValueCountFrequency (%)
191470.702188116 1
1.3%
191593.381855287 1
1.3%
191764.756977979 1
1.3%
192221.040621527 2
2.5%
192317.743639315 1
1.3%
192366.666934944 1
1.3%
192382.291075756 1
1.3%
192452.838619924 1
1.3%
192522.425662279 1
1.3%
192552.888456548 1
1.3%
ValueCountFrequency (%)
198284.078546351 3
3.8%
198234.65096107 1
 
1.3%
198220.60746417 1
 
1.3%
198194.309937956 3
3.8%
198185.514552993 1
 
1.3%
198142.028597565 1
 
1.3%
198038.813567583 1
 
1.3%
197195.570801758 1
 
1.3%
196345.098973971 1
 
1.3%
196139.864969792 1
 
1.3%

좌표정보(Y)
Real number (ℝ)

Distinct63
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442094.06
Minimum439023.17
Maximum443291.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:38:59.628152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440930.55
Q1441583.74
median442195.73
Q3442489.88
95-th percentile443216.75
Maximum443291.23
Range4268.0641
Interquartile range (IQR)906.13315

Descriptive statistics

Standard deviation699.78294
Coefficient of variation (CV)0.0015828825
Kurtosis3.6189442
Mean442094.06
Median Absolute Deviation (MAD)406.43901
Skewness-1.1489483
Sum34925431
Variance489696.16
MonotonicityNot monotonic
2024-05-11T15:38:59.829963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443216.750634836 5
 
6.3%
442098.372819317 3
 
3.8%
441368.909286824 3
 
3.8%
441535.941765974 3
 
3.8%
442510.775085572 2
 
2.5%
442281.285348422 2
 
2.5%
442492.51105354 2
 
2.5%
442089.535619866 2
 
2.5%
442376.611736067 2
 
2.5%
440930.551467844 2
 
2.5%
Other values (53) 53
67.1%
ValueCountFrequency (%)
439023.167125842 1
 
1.3%
440553.71626053 1
 
1.3%
440902.894980435 1
 
1.3%
440930.551467844 2
2.5%
441131.353181979 1
 
1.3%
441274.672747921 1
 
1.3%
441368.909286824 3
3.8%
441380.969363018 1
 
1.3%
441396.873039668 1
 
1.3%
441437.774867372 1
 
1.3%
ValueCountFrequency (%)
443291.231245754 1
 
1.3%
443216.750634836 5
6.3%
442960.64361526 1
 
1.3%
442904.541727979 1
 
1.3%
442829.750853917 1
 
1.3%
442775.501498729 1
 
1.3%
442765.416591107 1
 
1.3%
442757.363039063 1
 
1.3%
442730.736291767 1
 
1.3%
442726.678503845 1
 
1.3%
Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
54 
종합여행업
25 

Length

Max length5
Median length4
Mean length4.3164557
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 54
68.4%
종합여행업 25
31.6%

Length

2024-05-11T15:38:59.990196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:00.119973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
68.4%
종합여행업 25
31.6%

문화사업자구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

지역구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
72 
일반주거지역
 
5
일반상업지역
 
2

Length

Max length6
Median length4
Mean length4.1772152
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 72
91.1%
일반주거지역 5
 
6.3%
일반상업지역 2
 
2.5%

Length

2024-05-11T15:39:00.267926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:00.430668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 72
91.1%
일반주거지역 5
 
6.3%
일반상업지역 2
 
2.5%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)80.0%
Missing69
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean5.8
Minimum0
Maximum13
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:00.560084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q13
median5.5
Q37.75
95-th percentile12.55
Maximum13
Range13
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation4.3919118
Coefficient of variation (CV)0.75722617
Kurtosis-0.82637873
Mean5.8
Median Absolute Deviation (MAD)2.5
Skewness0.44305365
Sum58
Variance19.288889
MonotonicityNot monotonic
2024-05-11T15:39:00.713483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
7 2
 
2.5%
3 2
 
2.5%
13 1
 
1.3%
12 1
 
1.3%
4 1
 
1.3%
8 1
 
1.3%
1 1
 
1.3%
0 1
 
1.3%
(Missing) 69
87.3%
ValueCountFrequency (%)
0 1
1.3%
1 1
1.3%
3 2
2.5%
4 1
1.3%
7 2
2.5%
8 1
1.3%
12 1
1.3%
13 1
1.3%
ValueCountFrequency (%)
13 1
1.3%
12 1
1.3%
8 1
1.3%
7 2
2.5%
4 1
1.3%
3 2
2.5%
1 1
1.3%
0 1
1.3%

주변환경명
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
72 
주택가주변
 
3
기타
 
2
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length4.0886076
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 72
91.1%
주택가주변 3
 
3.8%
기타 2
 
2.5%
유흥업소밀집지역 2
 
2.5%

Length

2024-05-11T15:39:00.903443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:01.078014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 72
91.1%
주택가주변 3
 
3.8%
기타 2
 
2.5%
유흥업소밀집지역 2
 
2.5%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

보험기관명
Text

MISSING 

Distinct13
Distinct (%)61.9%
Missing58
Missing (%)73.4%
Memory size764.0 B
2024-05-11T15:39:01.298472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.952381
Min length4

Characters and Unicode

Total characters188
Distinct characters35
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st row서울보증보험(주)
2nd row서울보증보험
3rd row서울보증보험주식회사
4th row서울보증보험주식회사
5th row서울보증보험(5000만원)
ValueCountFrequency (%)
서울보증보험 3
13.6%
보증보험 3
13.6%
서울보증보험(주 2
9.1%
서울보증보험주식회사 2
9.1%
서울보증보험(5000만원 2
9.1%
한국관광협회 2
9.1%
여행공제회 1
 
4.5%
관광협회중앙회 1
 
4.5%
여행공제회(5천 1
 
4.5%
서울보증(팔천오백 1
 
4.5%
Other values (4) 4
18.2%
2024-05-11T15:39:01.829909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
16.0%
16
 
8.5%
14
 
7.4%
0 13
 
6.9%
12
 
6.4%
12
 
6.4%
) 10
 
5.3%
( 10
 
5.3%
9
 
4.8%
5 7
 
3.7%
Other values (25) 55
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
75.5%
Decimal Number 20
 
10.6%
Close Punctuation 10
 
5.3%
Open Punctuation 10
 
5.3%
Uppercase Letter 3
 
1.6%
Other Punctuation 2
 
1.1%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
21.1%
16
11.3%
14
9.9%
12
 
8.5%
12
 
8.5%
9
 
6.3%
5
 
3.5%
4
 
2.8%
4
 
2.8%
3
 
2.1%
Other values (16) 33
23.2%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%
Decimal Number
ValueCountFrequency (%)
0 13
65.0%
5 7
35.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
75.5%
Common 43
 
22.9%
Latin 3
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
21.1%
16
11.3%
14
9.9%
12
 
8.5%
12
 
8.5%
9
 
6.3%
5
 
3.5%
4
 
2.8%
4
 
2.8%
3
 
2.1%
Other values (16) 33
23.2%
Common
ValueCountFrequency (%)
0 13
30.2%
) 10
23.3%
( 10
23.3%
5 7
16.3%
, 2
 
4.7%
1
 
2.3%
Latin
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
75.5%
ASCII 46
 
24.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
30
21.1%
16
11.3%
14
9.9%
12
 
8.5%
12
 
8.5%
9
 
6.3%
5
 
3.5%
4
 
2.8%
4
 
2.8%
3
 
2.1%
Other values (16) 33
23.2%
ASCII
ValueCountFrequency (%)
0 13
28.3%
) 10
21.7%
( 10
21.7%
5 7
15.2%
, 2
 
4.3%
1
 
2.2%
S 1
 
2.2%
G 1
 
2.2%
I 1
 
2.2%

건물용도명
Text

MISSING 

Distinct6
Distinct (%)66.7%
Missing70
Missing (%)88.6%
Memory size764.0 B
2024-05-11T15:39:02.056546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length6
Mean length6.3333333
Min length3

Characters and Unicode

Total characters57
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)55.6%

Sample

1st row근린생활시설
2nd row근린생활시설
3rd row단독주택
4th row사무실
5th row교육연구시설
ValueCountFrequency (%)
근린생활시설 4
40.0%
단독주택 1
 
10.0%
사무실 1
 
10.0%
교육연구시설 1
 
10.0%
다가구용 1
 
10.0%
주택(공동주택적용 1
 
10.0%
다세대주택 1
 
10.0%
2024-05-11T15:39:02.477484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
8.8%
5
 
8.8%
4
 
7.0%
4
 
7.0%
4
 
7.0%
4
 
7.0%
4
 
7.0%
4
 
7.0%
2
 
3.5%
2
 
3.5%
Other values (18) 19
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
94.7%
Close Punctuation 1
 
1.8%
Open Punctuation 1
 
1.8%
Space Separator 1
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
2
 
3.7%
2
 
3.7%
Other values (15) 16
29.6%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
94.7%
Common 3
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
2
 
3.7%
2
 
3.7%
Other values (15) 16
29.6%
Common
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
94.7%
ASCII 3
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
4
 
7.4%
2
 
3.7%
2
 
3.7%
Other values (15) 16
29.6%
ASCII
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)80.0%
Missing69
Missing (%)87.3%
Infinite0
Infinite (%)0.0%
Mean5.8
Minimum0
Maximum13
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:02.654668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.45
Q13
median5
Q38
95-th percentile12.55
Maximum13
Range13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.4171383
Coefficient of variation (CV)0.76157558
Kurtosis-0.89489006
Mean5.8
Median Absolute Deviation (MAD)3
Skewness0.44710917
Sum58
Variance19.511111
MonotonicityNot monotonic
2024-05-11T15:39:02.813458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 2
 
2.5%
8 2
 
2.5%
6 1
 
1.3%
13 1
 
1.3%
12 1
 
1.3%
4 1
 
1.3%
1 1
 
1.3%
0 1
 
1.3%
(Missing) 69
87.3%
ValueCountFrequency (%)
0 1
1.3%
1 1
1.3%
3 2
2.5%
4 1
1.3%
6 1
1.3%
8 2
2.5%
12 1
1.3%
13 1
1.3%
ValueCountFrequency (%)
13 1
1.3%
12 1
1.3%
8 2
2.5%
6 1
1.3%
4 1
1.3%
3 2
2.5%
1 1
1.3%
0 1
1.3%

지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
74 
1
 
2
2
 
2
0
 
1

Length

Max length4
Median length4
Mean length3.8101266
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
93.7%
1 2
 
2.5%
2 2
 
2.5%
0 1
 
1.3%

Length

2024-05-11T15:39:03.032370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:03.238438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
93.7%
1 2
 
2.5%
2 2
 
2.5%
0 1
 
1.3%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:03.403483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:03.561325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:03.726149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:03.925039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

영문상호명
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing63
Missing (%)79.7%
Memory size764.0 B
2024-05-11T15:39:04.146586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length22.5
Mean length20.4375
Min length4

Characters and Unicode

Total characters327
Distinct characters43
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st rowCristal one Co., Ltd
2nd rowTIME TOUR
3rd rowDaeKyoEducamp Co., Ltd
4th rowIUB,. Ltd.
5th rowXIN YUE INTERNATIONAL BUSINESS CO.,LTD
ValueCountFrequency (%)
ltd 6
 
12.2%
co 5
 
10.2%
tour 5
 
10.2%
international 4
 
8.2%
cristal 1
 
2.0%
gbg 1
 
2.0%
global 1
 
2.0%
chunwha 1
 
2.0%
travel 1
 
2.0%
agency 1
 
2.0%
Other values (23) 23
46.9%
2024-05-11T15:39:04.647851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
10.4%
o 18
 
5.5%
T 16
 
4.9%
I 16
 
4.9%
N 15
 
4.6%
. 13
 
4.0%
L 13
 
4.0%
O 13
 
4.0%
a 12
 
3.7%
n 12
 
3.7%
Other values (33) 165
50.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 147
45.0%
Lowercase Letter 126
38.5%
Space Separator 34
 
10.4%
Other Punctuation 20
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 18
14.3%
a 12
9.5%
n 12
9.5%
e 12
9.5%
t 11
 
8.7%
r 9
 
7.1%
d 8
 
6.3%
p 5
 
4.0%
l 5
 
4.0%
u 5
 
4.0%
Other values (10) 29
23.0%
Uppercase Letter
ValueCountFrequency (%)
T 16
10.9%
I 16
10.9%
N 15
10.2%
L 13
8.8%
O 13
8.8%
C 10
 
6.8%
E 9
 
6.1%
A 9
 
6.1%
U 8
 
5.4%
R 8
 
5.4%
Other values (10) 30
20.4%
Other Punctuation
ValueCountFrequency (%)
. 13
65.0%
, 7
35.0%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 273
83.5%
Common 54
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 18
 
6.6%
T 16
 
5.9%
I 16
 
5.9%
N 15
 
5.5%
L 13
 
4.8%
O 13
 
4.8%
a 12
 
4.4%
n 12
 
4.4%
e 12
 
4.4%
t 11
 
4.0%
Other values (30) 135
49.5%
Common
ValueCountFrequency (%)
34
63.0%
. 13
 
24.1%
, 7
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
 
10.4%
o 18
 
5.5%
T 16
 
4.9%
I 16
 
4.9%
N 15
 
4.6%
. 13
 
4.0%
L 13
 
4.0%
O 13
 
4.0%
a 12
 
3.7%
n 12
 
3.7%
Other values (33) 165
50.5%

영문상호주소
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
63 
GENERAL TRAVEL BUSINESS
GENENAL TRAVEL BUSINESS
 
5
General Travel Business
 
2
GENERAL TRAVAL BUSINESS
 
1

Length

Max length23
Median length4
Mean length7.8481013
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 63
79.7%
GENERAL TRAVEL BUSINESS 8
 
10.1%
GENENAL TRAVEL BUSINESS 5
 
6.3%
General Travel Business 2
 
2.5%
GENERAL TRAVAL BUSINESS 1
 
1.3%

Length

2024-05-11T15:39:04.873174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:05.068598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 63
56.8%
business 16
 
14.4%
travel 15
 
13.5%
general 11
 
9.9%
genenal 5
 
4.5%
traval 1
 
0.9%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:05.259216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:05.419882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:05.572848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:05.712825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:05.873426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:06.057297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:06.288090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:06.441734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:06.606774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:06.773575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)92.9%
Missing65
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean52.896429
Minimum0
Maximum210.75
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:06.917794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.75
Q118.4575
median26.695
Q341.1675
95-th percentile200.168
Maximum210.75
Range210.75
Interquartile range (IQR)22.71

Descriptive statistics

Standard deviation66.029303
Coefficient of variation (CV)1.2482753
Kurtosis2.8546124
Mean52.896429
Median Absolute Deviation (MAD)11.695
Skewness1.9853153
Sum740.55
Variance4359.8688
MonotonicityNot monotonic
2024-05-11T15:39:07.068326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
15.0 2
 
2.5%
34.22 1
 
1.3%
19.83 1
 
1.3%
20.0 1
 
1.3%
78.0 1
 
1.3%
210.75 1
 
1.3%
194.47 1
 
1.3%
41.39 1
 
1.3%
40.5 1
 
1.3%
18.0 1
 
1.3%
Other values (3) 3
 
3.8%
(Missing) 65
82.3%
ValueCountFrequency (%)
0.0 1
1.3%
15.0 2
2.5%
18.0 1
1.3%
19.83 1
1.3%
20.0 1
1.3%
23.89 1
1.3%
29.5 1
1.3%
34.22 1
1.3%
40.5 1
1.3%
41.39 1
1.3%
ValueCountFrequency (%)
210.75 1
1.3%
194.47 1
1.3%
78.0 1
1.3%
41.39 1
1.3%
40.5 1
1.3%
34.22 1
1.3%
29.5 1
1.3%
23.89 1
1.3%
20.0 1
1.3%
19.83 1
1.3%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
0
 
1

Length

Max length4
Median length4
Mean length3.9620253
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
0 1
 
1.3%

Length

2024-05-11T15:39:07.257305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:07.408360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
0 1
 
1.3%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
20180903
 
1

Length

Max length8
Median length4
Mean length4.0506329
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
20180903 1
 
1.3%

Length

2024-05-11T15:39:07.547626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:07.710848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
20180903 1
 
1.3%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
78 
20191002
 
1

Length

Max length8
Median length4
Mean length4.0506329
Min length4

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 78
98.7%
20191002 1
 
1.3%

Length

2024-05-11T15:39:08.213930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:08.372742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 78
98.7%
20191002 1
 
1.3%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)41.7%
Missing55
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean2.0729333 × 108
Minimum0
Maximum6.5 × 108
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:08.610619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1 × 108
Q11 × 108
median2 × 108
Q32.0410015 × 108
95-th percentile5.2 × 108
Maximum6.5 × 108
Range6.5 × 108
Interquartile range (IQR)1.0410015 × 108

Descriptive statistics

Standard deviation1.4518444 × 108
Coefficient of variation (CV)0.70038165
Kurtosis3.6354216
Mean2.0729333 × 108
Median Absolute Deviation (MAD)98565345
Skewness1.7515211
Sum4.9750399 × 109
Variance2.1078523 × 1016
MonotonicityNot monotonic
2024-05-11T15:39:08.788375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
200000000 9
 
11.4%
100000000 6
 
7.6%
300000000 2
 
2.5%
216400600 1
 
1.3%
650000000 1
 
1.3%
350000000 1
 
1.3%
102869310 1
 
1.3%
105770000 1
 
1.3%
550000000 1
 
1.3%
0 1
 
1.3%
(Missing) 55
69.6%
ValueCountFrequency (%)
0 1
 
1.3%
100000000 6
7.6%
102869310 1
 
1.3%
105770000 1
 
1.3%
200000000 9
11.4%
216400600 1
 
1.3%
300000000 2
 
2.5%
350000000 1
 
1.3%
550000000 1
 
1.3%
650000000 1
 
1.3%
ValueCountFrequency (%)
650000000 1
 
1.3%
550000000 1
 
1.3%
350000000 1
 
1.3%
300000000 2
 
2.5%
216400600 1
 
1.3%
200000000 9
11.4%
105770000 1
 
1.3%
102869310 1
 
1.3%
100000000 6
7.6%
0 1
 
1.3%

보험시작일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)100.0%
Missing56
Missing (%)70.9%
Infinite0
Infinite (%)0.0%
Mean20174217
Minimum20121010
Maximum20210917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:08.992526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20121010
5-th percentile20132038
Q120160554
median20180930
Q320190523
95-th percentile20208590
Maximum20210917
Range89907
Interquartile range (IQR)29968.5

Descriptive statistics

Standard deviation24715.216
Coefficient of variation (CV)0.0012250892
Kurtosis-0.34295924
Mean20174217
Median Absolute Deviation (MAD)10003
Skewness-0.70918327
Sum4.64007 × 108
Variance6.108419 × 108
MonotonicityNot monotonic
2024-05-11T15:39:09.170041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20121010 1
 
1.3%
20210531 1
 
1.3%
20210917 1
 
1.3%
20190515 1
 
1.3%
20190418 1
 
1.3%
20190307 1
 
1.3%
20180903 1
 
1.3%
20170914 1
 
1.3%
20190323 1
 
1.3%
20181101 1
 
1.3%
Other values (13) 13
 
16.5%
(Missing) 56
70.9%
ValueCountFrequency (%)
20121010 1
1.3%
20131118 1
1.3%
20140320 1
1.3%
20140716 1
1.3%
20141121 1
1.3%
20160408 1
1.3%
20160701 1
1.3%
20170914 1
1.3%
20170927 1
1.3%
20180725 1
1.3%
ValueCountFrequency (%)
20210917 1
1.3%
20210531 1
1.3%
20191122 1
1.3%
20190825 1
1.3%
20190618 1
1.3%
20190531 1
1.3%
20190515 1
1.3%
20190418 1
1.3%
20190323 1
1.3%
20190307 1
1.3%

보험종료일자
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)100.0%
Missing56
Missing (%)70.9%
Infinite0
Infinite (%)0.0%
Mean20185086
Minimum20131009
Maximum20220916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:09.348292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20131009
5-th percentile20142037
Q120170554
median20191101
Q320200720
95-th percentile20219528
Maximum20220916
Range89907
Interquartile range (IQR)30166.5

Descriptive statistics

Standard deviation25299.351
Coefficient of variation (CV)0.0012533685
Kurtosis-0.44105556
Mean20185086
Median Absolute Deviation (MAD)10174
Skewness-0.71816145
Sum4.6425699 × 108
Variance6.4005717 × 108
MonotonicityNot monotonic
2024-05-11T15:39:09.528643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20131009 1
 
1.3%
20220530 1
 
1.3%
20220916 1
 
1.3%
20210514 1
 
1.3%
20200417 1
 
1.3%
20200306 1
 
1.3%
20190902 1
 
1.3%
20180914 1
 
1.3%
20200322 1
 
1.3%
20191101 1
 
1.3%
Other values (13) 13
 
16.5%
(Missing) 56
70.9%
ValueCountFrequency (%)
20131009 1
1.3%
20141117 1
1.3%
20150319 1
1.3%
20150716 1
1.3%
20151121 1
1.3%
20170407 1
1.3%
20170701 1
1.3%
20180914 1
1.3%
20180927 1
1.3%
20190724 1
1.3%
ValueCountFrequency (%)
20220916 1
1.3%
20220530 1
1.3%
20210514 1
1.3%
20201122 1
1.3%
20200930 1
1.3%
20200824 1
1.3%
20200617 1
1.3%
20200531 1
1.3%
20200417 1
1.3%
20200322 1
1.3%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)78.6%
Missing65
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean52.928571
Minimum0
Maximum211
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size843.0 B
2024-05-11T15:39:09.709428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.75
Q118.5
median27
Q341
95-th percentile199.95
Maximum211
Range211
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation65.977227
Coefficient of variation (CV)1.2465333
Kurtosis2.8613227
Mean52.928571
Median Absolute Deviation (MAD)12
Skewness1.9858195
Sum741
Variance4352.9945
MonotonicityNot monotonic
2024-05-11T15:39:09.877179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
15 2
 
2.5%
20 2
 
2.5%
41 2
 
2.5%
34 1
 
1.3%
78 1
 
1.3%
211 1
 
1.3%
194 1
 
1.3%
18 1
 
1.3%
30 1
 
1.3%
24 1
 
1.3%
(Missing) 65
82.3%
ValueCountFrequency (%)
0 1
1.3%
15 2
2.5%
18 1
1.3%
20 2
2.5%
24 1
1.3%
30 1
1.3%
34 1
1.3%
41 2
2.5%
78 1
1.3%
194 1
1.3%
ValueCountFrequency (%)
211 1
1.3%
194 1
1.3%
78 1
1.3%
41 2
2.5%
34 1
1.3%
30 1
1.3%
24 1
1.3%
20 2
2.5%
18 1
1.3%
15 2
2.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03200000CDFI226004201000000120101117<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>151836서울특별시 관악구 봉천동 865-2번지 세종빌딩 217호서울특별시 관악구 관악로13길 25, 217호 (봉천동,세종빌딩)<NA>초록별여행사2019-07-17 13:56:35U2019-07-19 02:40:00.0<NA>195582.81299441900.292747종합여행업<NA><NA><NA><NA><NA>서울보증보험(주)근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>34.22<NA><NA><NA><NA><NA><NA><NA><NA>2164006002013111820141117<NA>34
13200000CDFI226004201200000120120716<NA>1영업/정상13영업중<NA><NA><NA><NA>1661-1924<NA>151800서울특별시 관악구 남현동 1061-18번지 르메에르간남타운2, 1-지-2호서울특별시 관악구 과천대로 939 (남현동)8807주식회사 세계정복2012-10-22 20:47:11I2018-08-31 23:59:59.0<NA>198284.078546441368.909287종합여행업<NA><NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3000000002012101020131009<NA><NA>
23200000CDFI22600420130000022012-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-888-3353<NA>151-844서울특별시 관악구 봉천동 930-20 1층서울특별시 관악구 장군봉1길 13, 1층 (봉천동)8784(주)아세아상사2023-11-28 09:27:21U2022-10-31 21:00:00.0<NA>194706.666626442213.022512<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33200000CDFI226004201300000620120529<NA>1영업/정상13영업중<NA><NA><NA><NA>02-829-0922,0917<NA>151706서울특별시 관악구 봉천동 729-21 대교타워, 6층서울특별시 관악구 보라매로3길 23, 6층 (봉천동, 대교타워)8708(주)대교2022-09-01 15:23:45U2021-12-09 00:03:00.0<NA>193350.027023443216.750635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43200000CDFI226004201400000220140318<NA>3폐업3폐업20161017<NA><NA><NA><NA><NA>151827서울특별시 관악구 봉천동 949-18번지 B09호서울특별시 관악구 남부순환로 1679, B09호 (봉천동)8756신세계 국제교류중심2016-10-17 16:32:51I2018-08-31 23:59:59.0<NA>194386.13362442492.511054종합여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>15.0<NA><NA><NA><NA><NA><NA><NA><NA>2000000002016040820170407<NA>15
53200000CDFI226004201400000320140318<NA>3폐업3폐업20150217<NA><NA><NA><NA><NA>151891서울특별시 관악구 신림동 1426-13번지 704호서울특별시 관악구 신림로70길 16, 704호 (신림동)151891유케어 플러스2015-02-23 08:55:23I2018-08-31 23:59:59.0<NA>193720.681961442829.750854종합여행업<NA><NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>19.83<NA><NA><NA><NA><NA><NA><NA><NA>2000000002014032020150319<NA>20
63200000CDFI226004201400000619991228<NA>3폐업3폐업20190805<NA><NA><NA>02-6912-4890<NA>151706서울특별시 관악구 봉천동 729-21번지 대교타워, 18층서울특별시 관악구 보라매로3길 23, 18층호 (봉천동, 대교타워)8708(주)크리스탈원2019-08-06 09:00:11U2019-08-08 02:40:00.0<NA>193350.027023443216.750635종합여행업<NA><NA><NA><NA><NA>서울보증보험(5000만원)<NA><NA><NA><NA><NA>Cristal one Co., LtdGENERAL TRAVEL BUSINESS<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6500000002018072520190724<NA><NA>
73200000CDFI226004201400000720140618<NA>3폐업3폐업20170222<NA><NA><NA>02-3141-6666<NA>151015서울특별시 관악구 신림동 1474-8번지 2층호서울특별시 관악구 난곡로63길 30, 2층호 (신림동)8771(주)뉴타임투어2017-02-22 17:00:18I2018-08-31 23:59:59.0<NA>192221.040622442089.53562종합여행업<NA><NA><NA><NA><NA>여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2000000002014071620150716<NA><NA>
83200000CDFI226004201400000820111020<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3141-6666<NA>151015서울특별시 관악구 신림동 1474-8번지 2층호서울특별시 관악구 난곡로63길 30, 2층호 (신림동)8771타임투어2017-02-22 07:42:39I2018-08-31 23:59:59.0<NA>192221.040622442089.53562종합여행업<NA><NA><NA><NA><NA>관광협회중앙회 여행공제회(5천)<NA><NA><NA><NA><NA>TIME TOURGENERAL TRAVEL BUSINESS<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2000000002016070120170701<NA><NA>
93200000CDFI226004201500000420150618<NA>3폐업3폐업20210331<NA><NA><NA>028291336<NA>151706서울특별시 관악구 봉천동 729-21 대교타워 8층서울특별시 관악구 보라매로3길 23, 8층 (봉천동, 대교타워)8708주식회사 대교에듀캠프2021-03-31 14:26:06U2021-04-02 02:40:00.0<NA>193350.027023443216.750635종합여행업<NA><NA><NA><NA><NA>서울보증(팔천오백)<NA><NA><NA><NA><NA>DaeKyoEducamp Co., LtdGENERAL TRAVEL BUSINESS<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2000000002019061820200617<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
693200000CDFI22600420230000072023-09-20<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 남현동 1060-18 범평빌딩서울특별시 관악구 남현1길 51, 8층 (남현동)8806더인(The In)2023-09-20 11:07:50I2022-12-08 22:02:00.0<NA>198194.309938441535.941766<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
703200000CDFI22600420230000082023-09-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 1570-2서울특별시 관악구 남부순환로 1494, 203호 (신림동)8772돈키호테2023-11-24 13:56:05U2022-10-31 22:06:00.0<NA>192552.888457442196.637751<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
713200000CDFI22600420230000092021-03-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 908-68서울특별시 관악구 양녕로1길 46, 지하1층 전부호 (봉천동)8752주식회사 나우여행2024-04-23 17:44:14U2023-12-03 22:05:00.0<NA>194976.841269442395.711297<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
723200000CDFI22600420230000102023-12-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 남현동 1061-18서울특별시 관악구 과천대로 939, 2층 201,202호 (남현동)8807주식회사 하이랜드인터내셔널2023-12-04 10:04:04I2022-11-02 00:06:00.0<NA>198284.078546441368.909287<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
733200000CDFI22600420230000112019-07-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 587-111 신화아이서울특별시 관악구 난곡로48길 20-8 (신림동, 신화아이)8849탐조코리아2024-01-04 16:16:58U2023-12-01 00:06:00.0<NA>192522.425662441631.548183<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
743200000CDFI22600420240000012024-01-04<NA>5제외/삭제/전출15전출2024-04-12<NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 869-10 관악센츄리타워서울특별시 관악구 남부순환로 1808, 관악센츄리타워 8층 15호 (봉천동)8787주식회사 감탄여행2024-04-12 09:09:00U2023-12-03 23:04:00.0<NA>195588.796492442098.372819<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
753200000CDFI22600420240000022024-01-16<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 517-21서울특별시 관악구 신사로10길 14, 1층 (신림동)8702국제 행운 여행사2024-01-24 16:24:08U2023-11-30 22:06:00.0<NA>192382.291076442757.363039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
763200000CDFI22600420240000032024-03-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 870-12 에이스에이존서울특별시 관악구 남부순환로 1805, 1205호 (봉천동)8758트래블 어스2024-04-23 17:20:16U2023-12-03 22:05:00.0<NA>195582.349111442179.357454<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
773200000CDFI22600420240000042024-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 729-21 대교타워서울특별시 관악구 보라매로3길 23, 4층 (봉천동)8708주식회사 대교뉴이프2024-05-03 18:11:52I2023-12-05 00:05:00.0<NA>193350.027023443216.750635<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
783200000CDFI22600420240000052024-05-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 30-3 호삼빌딩서울특별시 관악구 관악로24길 14, 5층 32호 (봉천동)8737주식회사 지원행코리아2024-05-02 15:49:56I2023-12-05 00:04:00.0<NA>195999.663233442420.839864<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>