Overview

Dataset statistics

Number of variables60
Number of observations90
Missing cells2373
Missing cells (%)43.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.6 KiB
Average record size in memory518.5 B

Variable types

Categorical21
Text10
DateTime4
Unsupported16
Numeric9

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
Author광진구
URLhttps://data.seoul.go.kr/dataList/OA-17556/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영문상호주소 has constant value ""Constant
주변환경명 is highly imbalanced (73.8%)Imbalance
건물용도명 is highly imbalanced (69.8%)Imbalance
지하층수 is highly imbalanced (71.2%)Imbalance
객실수 is highly imbalanced (91.2%)Imbalance
건축연면적 is highly imbalanced (91.2%)Imbalance
선박총톤수 is highly imbalanced (91.2%)Imbalance
선박척수 is highly imbalanced (91.2%)Imbalance
무대면적 is highly imbalanced (91.2%)Imbalance
좌석수 is highly imbalanced (91.2%)Imbalance
회의실별동시수용인원 is highly imbalanced (91.2%)Imbalance
놀이시설수 is highly imbalanced (91.2%)Imbalance
인허가취소일자 has 82 (91.1%) missing valuesMissing
폐업일자 has 21 (23.3%) missing valuesMissing
휴업시작일자 has 90 (100.0%) missing valuesMissing
휴업종료일자 has 90 (100.0%) missing valuesMissing
재개업일자 has 90 (100.0%) missing valuesMissing
전화번호 has 28 (31.1%) missing valuesMissing
소재지면적 has 90 (100.0%) missing valuesMissing
소재지우편번호 has 39 (43.3%) missing valuesMissing
도로명주소 has 5 (5.6%) missing valuesMissing
도로명우편번호 has 28 (31.1%) missing valuesMissing
업태구분명 has 90 (100.0%) missing valuesMissing
좌표정보(X) has 2 (2.2%) missing valuesMissing
좌표정보(Y) has 2 (2.2%) missing valuesMissing
지역구분명 has 82 (91.1%) missing valuesMissing
총층수 has 77 (85.6%) missing valuesMissing
제작취급품목내용 has 90 (100.0%) missing valuesMissing
지상층수 has 77 (85.6%) missing valuesMissing
영문상호명 has 88 (97.8%) missing valuesMissing
영문상호주소 has 88 (97.8%) missing valuesMissing
선박제원 has 90 (100.0%) missing valuesMissing
기념품종류 has 90 (100.0%) missing valuesMissing
시설면적 has 73 (81.1%) missing valuesMissing
놀이기구수내역 has 90 (100.0%) missing valuesMissing
방송시설유무 has 90 (100.0%) missing valuesMissing
발전시설유무 has 90 (100.0%) missing valuesMissing
의무실유무 has 90 (100.0%) missing valuesMissing
안내소유무 has 90 (100.0%) missing valuesMissing
기획여행보험시작일자 has 90 (100.0%) missing valuesMissing
기획여행보험종료일자 has 90 (100.0%) missing valuesMissing
자본금 has 52 (57.8%) missing valuesMissing
보험시작일자 has 58 (64.4%) missing valuesMissing
보험종료일자 has 58 (64.4%) missing valuesMissing
부대시설내역 has 90 (100.0%) missing valuesMissing
시설규모 has 73 (81.1%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 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
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
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 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 3 (3.3%) zerosZeros
지상층수 has 3 (3.3%) zerosZeros
시설면적 has 3 (3.3%) zerosZeros
시설규모 has 3 (3.3%) zerosZeros

Reproduction

Analysis started2024-04-06 10:40:38.703098
Analysis finished2024-04-06 10:40:40.199410
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
3040000
90 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3040000
2nd row3040000
3rd row3040000
4th row3040000
5th row3040000

Common Values

ValueCountFrequency (%)
3040000 90
100.0%

Length

2024-04-06T19:40:40.394089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:40.569016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3040000 90
100.0%

관리번호
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-06T19:40:40.867569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1800
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

Unique90 ?
Unique (%)100.0%

Sample

1st rowCDFI2260011993000001
2nd rowCDFI2260011994000001
3rd rowCDFI2260011997000001
4th rowCDFI2260011997000002
5th rowCDFI2260011998000001
ValueCountFrequency (%)
cdfi2260011993000001 1
 
1.1%
cdfi2260012016000011 1
 
1.1%
cdfi2260012016000007 1
 
1.1%
cdfi2260012016000006 1
 
1.1%
cdfi2260012016000005 1
 
1.1%
cdfi2260012016000002 1
 
1.1%
cdfi2260012016000001 1
 
1.1%
cdfi2260012015000008 1
 
1.1%
cdfi2260012015000007 1
 
1.1%
cdfi2260012015000005 1
 
1.1%
Other values (80) 80
88.9%
2024-04-06T19:40:41.508911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 745
41.4%
2 308
17.1%
1 177
 
9.8%
6 107
 
5.9%
C 90
 
5.0%
D 90
 
5.0%
F 90
 
5.0%
I 90
 
5.0%
9 23
 
1.3%
3 22
 
1.2%
Other values (4) 58
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1440
80.0%
Uppercase Letter 360
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 745
51.7%
2 308
21.4%
1 177
 
12.3%
6 107
 
7.4%
9 23
 
1.6%
3 22
 
1.5%
4 21
 
1.5%
7 14
 
1.0%
5 14
 
1.0%
8 9
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 90
25.0%
D 90
25.0%
F 90
25.0%
I 90
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1440
80.0%
Latin 360
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 745
51.7%
2 308
21.4%
1 177
 
12.3%
6 107
 
7.4%
9 23
 
1.6%
3 22
 
1.5%
4 21
 
1.5%
7 14
 
1.0%
5 14
 
1.0%
8 9
 
0.6%
Latin
ValueCountFrequency (%)
C 90
25.0%
D 90
25.0%
F 90
25.0%
I 90
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 745
41.4%
2 308
17.1%
1 177
 
9.8%
6 107
 
5.9%
C 90
 
5.0%
D 90
 
5.0%
F 90
 
5.0%
I 90
 
5.0%
9 23
 
1.3%
3 22
 
1.2%
Other values (4) 58
 
3.2%

인허가일자
Date

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum1993-04-13 00:00:00
Maximum2023-05-03 00:00:00
2024-04-06T19:40:41.770345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:40:42.072818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct4
Distinct (%)50.0%
Missing82
Missing (%)91.1%
Memory size852.0 B
Minimum2013-04-10 00:00:00
Maximum2023-07-18 00:00:00
2024-04-06T19:40:42.300919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:40:42.622535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
3
65 
4
11 
1
10 
5
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 65
72.2%
4 11
 
12.2%
1 10
 
11.1%
5 4
 
4.4%

Length

2024-04-06T19:40:42.924958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:43.227382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 65
72.2%
4 11
 
12.2%
1 10
 
11.1%
5 4
 
4.4%

영업상태명
Categorical

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
폐업
65 
취소/말소/만료/정지/중지
11 
영업/정상
10 
제외/삭제/전출
 
4

Length

Max length14
Median length2
Mean length4.0666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 65
72.2%
취소/말소/만료/정지/중지 11
 
12.2%
영업/정상 10
 
11.1%
제외/삭제/전출 4
 
4.4%

Length

2024-04-06T19:40:43.559703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:43.841126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 65
72.2%
취소/말소/만료/정지/중지 11
 
12.2%
영업/정상 10
 
11.1%
제외/삭제/전출 4
 
4.4%
Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
3
65 
31
10 
13
10 
15
 
4
30
 
1

Length

Max length2
Median length1
Mean length1.2777778
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row31
2nd row31
3rd row3
4th row30
5th row3

Common Values

ValueCountFrequency (%)
3 65
72.2%
31 10
 
11.1%
13 10
 
11.1%
15 4
 
4.4%
30 1
 
1.1%

Length

2024-04-06T19:40:44.193445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:44.498327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 65
72.2%
31 10
 
11.1%
13 10
 
11.1%
15 4
 
4.4%
30 1
 
1.1%
Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
폐업
65 
등록취소
10 
영업중
10 
전출
 
4
허가취소
 
1

Length

Max length4
Median length2
Mean length2.3555556
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 65
72.2%
등록취소 10
 
11.1%
영업중 10
 
11.1%
전출 4
 
4.4%
허가취소 1
 
1.1%

Length

2024-04-06T19:40:44.768443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:45.231276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 65
72.2%
등록취소 10
 
11.1%
영업중 10
 
11.1%
전출 4
 
4.4%
허가취소 1
 
1.1%

폐업일자
Date

MISSING 

Distinct66
Distinct (%)95.7%
Missing21
Missing (%)23.3%
Memory size852.0 B
Minimum2002-08-12 00:00:00
Maximum2024-03-27 00:00:00
2024-04-06T19:40:45.722516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:40:46.143072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

전화번호
Text

MISSING 

Distinct59
Distinct (%)95.2%
Missing28
Missing (%)31.1%
Memory size852.0 B
2024-04-06T19:40:46.703819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.548387
Min length8

Characters and Unicode

Total characters654
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)91.9%

Sample

1st row453-3031
2nd row453-5458
3rd row497-4334
4th row447-0367
5th row3436-0888
ValueCountFrequency (%)
02-2201-0773 3
 
4.5%
02 2
 
3.0%
02-447-7010 2
 
3.0%
432 1
 
1.5%
02-455-8546 1
 
1.5%
070-8959-4671 1
 
1.5%
02-557-0243 1
 
1.5%
02-6395-1113 1
 
1.5%
02-446-5034 1
 
1.5%
02-6232-0008 1
 
1.5%
Other values (52) 52
78.8%
2024-04-06T19:40:47.440885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 101
15.4%
0 95
14.5%
4 84
12.8%
2 77
11.8%
7 55
8.4%
3 54
8.3%
5 45
6.9%
6 39
 
6.0%
1 34
 
5.2%
8 34
 
5.2%
Other values (3) 36
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 546
83.5%
Dash Punctuation 101
 
15.4%
Space Separator 6
 
0.9%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 95
17.4%
4 84
15.4%
2 77
14.1%
7 55
10.1%
3 54
9.9%
5 45
8.2%
6 39
7.1%
1 34
 
6.2%
8 34
 
6.2%
9 29
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 654
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 101
15.4%
0 95
14.5%
4 84
12.8%
2 77
11.8%
7 55
8.4%
3 54
8.3%
5 45
6.9%
6 39
 
6.0%
1 34
 
5.2%
8 34
 
5.2%
Other values (3) 36
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 654
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 101
15.4%
0 95
14.5%
4 84
12.8%
2 77
11.8%
7 55
8.4%
3 54
8.3%
5 45
6.9%
6 39
 
6.0%
1 34
 
5.2%
8 34
 
5.2%
Other values (3) 36
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

소재지우편번호
Text

MISSING 

Distinct40
Distinct (%)78.4%
Missing39
Missing (%)43.3%
Memory size852.0 B
2024-04-06T19:40:48.230866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0980392
Min length6

Characters and Unicode

Total characters311
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

Unique34 ?
Unique (%)66.7%

Sample

1st row143-827
2nd row143883
3rd row143838
4th row143866
5th row143826
ValueCountFrequency (%)
143802 4
 
7.8%
143915 4
 
7.8%
143831 3
 
5.9%
143841 2
 
3.9%
143846 2
 
3.9%
143875 2
 
3.9%
143821 1
 
2.0%
143-827 1
 
2.0%
143200 1
 
2.0%
143-220 1
 
2.0%
Other values (30) 30
58.8%
2024-04-06T19:40:49.009859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 71
22.8%
4 58
18.6%
3 58
18.6%
8 44
14.1%
2 16
 
5.1%
9 16
 
5.1%
0 13
 
4.2%
5 13
 
4.2%
6 9
 
2.9%
7 8
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
98.4%
Dash Punctuation 5
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 71
23.2%
4 58
19.0%
3 58
19.0%
8 44
14.4%
2 16
 
5.2%
9 16
 
5.2%
0 13
 
4.2%
5 13
 
4.2%
6 9
 
2.9%
7 8
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 311
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 71
22.8%
4 58
18.6%
3 58
18.6%
8 44
14.1%
2 16
 
5.1%
9 16
 
5.1%
0 13
 
4.2%
5 13
 
4.2%
6 9
 
2.9%
7 8
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 311
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 71
22.8%
4 58
18.6%
3 58
18.6%
8 44
14.1%
2 16
 
5.1%
9 16
 
5.1%
0 13
 
4.2%
5 13
 
4.2%
6 9
 
2.9%
7 8
 
2.6%
Distinct87
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-06T19:40:49.521701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length31.5
Mean length27.988889
Min length17

Characters and Unicode

Total characters2519
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)93.3%

Sample

1st row서울특별시 광진구 구의동 254-114
2nd row서울특별시 광진구 중곡동 20-2번지 서암빌딩1층
3rd row서울특별시 광진구 군자동 473-19번지
4th row서울특별시 광진구 자양동 619-24번지
5th row서울특별시 광진구 구의동 252-16번지 동일빌딩 302호
ValueCountFrequency (%)
서울특별시 91
18.7%
광진구 90
18.5%
구의동 28
 
5.7%
자양동 20
 
4.1%
중곡동 18
 
3.7%
광장동 9
 
1.8%
화양동 7
 
1.4%
군자동 6
 
1.2%
301호 5
 
1.0%
4층 4
 
0.8%
Other values (173) 209
42.9%
2024-04-06T19:40:50.447285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
436
 
17.3%
118
 
4.7%
1 115
 
4.6%
107
 
4.2%
2 99
 
3.9%
98
 
3.9%
95
 
3.8%
93
 
3.7%
92
 
3.7%
92
 
3.7%
Other values (125) 1174
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1446
57.4%
Decimal Number 535
 
21.2%
Space Separator 436
 
17.3%
Dash Punctuation 84
 
3.3%
Uppercase Letter 13
 
0.5%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
118
 
8.2%
107
 
7.4%
98
 
6.8%
95
 
6.6%
93
 
6.4%
92
 
6.4%
92
 
6.4%
91
 
6.3%
91
 
6.3%
56
 
3.9%
Other values (103) 513
35.5%
Decimal Number
ValueCountFrequency (%)
1 115
21.5%
2 99
18.5%
3 59
11.0%
0 55
10.3%
4 48
9.0%
6 44
 
8.2%
5 37
 
6.9%
7 33
 
6.2%
9 27
 
5.0%
8 18
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
S 4
30.8%
Y 2
15.4%
B 2
15.4%
K 2
15.4%
U 1
 
7.7%
N 1
 
7.7%
J 1
 
7.7%
Space Separator
ValueCountFrequency (%)
436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1446
57.4%
Common 1060
42.1%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
118
 
8.2%
107
 
7.4%
98
 
6.8%
95
 
6.6%
93
 
6.4%
92
 
6.4%
92
 
6.4%
91
 
6.3%
91
 
6.3%
56
 
3.9%
Other values (103) 513
35.5%
Common
ValueCountFrequency (%)
436
41.1%
1 115
 
10.8%
2 99
 
9.3%
- 84
 
7.9%
3 59
 
5.6%
0 55
 
5.2%
4 48
 
4.5%
6 44
 
4.2%
5 37
 
3.5%
7 33
 
3.1%
Other values (5) 50
 
4.7%
Latin
ValueCountFrequency (%)
S 4
30.8%
Y 2
15.4%
B 2
15.4%
K 2
15.4%
U 1
 
7.7%
N 1
 
7.7%
J 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1446
57.4%
ASCII 1073
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
436
40.6%
1 115
 
10.7%
2 99
 
9.2%
- 84
 
7.8%
3 59
 
5.5%
0 55
 
5.1%
4 48
 
4.5%
6 44
 
4.1%
5 37
 
3.4%
7 33
 
3.1%
Other values (12) 63
 
5.9%
Hangul
ValueCountFrequency (%)
118
 
8.2%
107
 
7.4%
98
 
6.8%
95
 
6.6%
93
 
6.4%
92
 
6.4%
92
 
6.4%
91
 
6.3%
91
 
6.3%
56
 
3.9%
Other values (103) 513
35.5%

도로명주소
Text

MISSING 

Distinct84
Distinct (%)98.8%
Missing5
Missing (%)5.6%
Memory size852.0 B
2024-04-06T19:40:51.014769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length33.929412
Min length22

Characters and Unicode

Total characters2884
Distinct characters141
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

Unique83 ?
Unique (%)97.6%

Sample

1st row서울특별시 광진구 자양로 165 (구의동)
2nd row서울특별시 광진구 용마산로22길 28 (중곡동,서암빌딩1층)
3rd row서울특별시 광진구 천호대로 540 (군자동)
4th row서울특별시 광진구 뚝섬로49길 11-1 (자양동)
5th row서울특별시 광진구 자양로 116 (구의동,동일빌딩 302호)
ValueCountFrequency (%)
서울특별시 86
 
15.6%
광진구 85
 
15.4%
구의동 18
 
3.3%
중곡동 15
 
2.7%
자양동 14
 
2.5%
아차산로 12
 
2.2%
천호대로 10
 
1.8%
자양로 9
 
1.6%
광장동 7
 
1.3%
2층 7
 
1.3%
Other values (196) 288
52.3%
2024-04-06T19:40:51.872243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
484
 
16.8%
115
 
4.0%
109
 
3.8%
108
 
3.7%
, 97
 
3.4%
1 91
 
3.2%
90
 
3.1%
88
 
3.1%
87
 
3.0%
86
 
3.0%
Other values (131) 1529
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1623
56.3%
Space Separator 484
 
16.8%
Decimal Number 477
 
16.5%
Other Punctuation 97
 
3.4%
Close Punctuation 86
 
3.0%
Open Punctuation 86
 
3.0%
Uppercase Letter 18
 
0.6%
Dash Punctuation 10
 
0.3%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
115
 
7.1%
109
 
6.7%
108
 
6.7%
90
 
5.5%
88
 
5.4%
87
 
5.4%
86
 
5.3%
86
 
5.3%
86
 
5.3%
84
 
5.2%
Other values (106) 684
42.1%
Decimal Number
ValueCountFrequency (%)
1 91
19.1%
3 70
14.7%
0 65
13.6%
2 58
12.2%
6 39
8.2%
4 38
8.0%
7 37
7.8%
8 28
 
5.9%
9 26
 
5.5%
5 25
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
S 7
38.9%
K 3
16.7%
N 2
 
11.1%
B 2
 
11.1%
U 2
 
11.1%
Y 1
 
5.6%
L 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
n 1
33.3%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
484
100.0%
Other Punctuation
ValueCountFrequency (%)
, 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1623
56.3%
Common 1240
43.0%
Latin 21
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
115
 
7.1%
109
 
6.7%
108
 
6.7%
90
 
5.5%
88
 
5.4%
87
 
5.4%
86
 
5.3%
86
 
5.3%
86
 
5.3%
84
 
5.2%
Other values (106) 684
42.1%
Common
ValueCountFrequency (%)
484
39.0%
, 97
 
7.8%
1 91
 
7.3%
) 86
 
6.9%
( 86
 
6.9%
3 70
 
5.6%
0 65
 
5.2%
2 58
 
4.7%
6 39
 
3.1%
4 38
 
3.1%
Other values (5) 126
 
10.2%
Latin
ValueCountFrequency (%)
S 7
33.3%
K 3
14.3%
N 2
 
9.5%
B 2
 
9.5%
U 2
 
9.5%
e 1
 
4.8%
n 1
 
4.8%
Y 1
 
4.8%
L 1
 
4.8%
i 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1623
56.3%
ASCII 1261
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
484
38.4%
, 97
 
7.7%
1 91
 
7.2%
) 86
 
6.8%
( 86
 
6.8%
3 70
 
5.6%
0 65
 
5.2%
2 58
 
4.6%
6 39
 
3.1%
4 38
 
3.0%
Other values (15) 147
 
11.7%
Hangul
ValueCountFrequency (%)
115
 
7.1%
109
 
6.7%
108
 
6.7%
90
 
5.5%
88
 
5.4%
87
 
5.4%
86
 
5.3%
86
 
5.3%
86
 
5.3%
84
 
5.2%
Other values (106) 684
42.1%

도로명우편번호
Text

MISSING 

Distinct45
Distinct (%)72.6%
Missing28
Missing (%)31.1%
Memory size852.0 B
2024-04-06T19:40:52.245343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1612903
Min length5

Characters and Unicode

Total characters320
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

Unique37 ?
Unique (%)59.7%

Sample

1st row143-827
2nd row143760
3rd row143912
4th row05007
5th row05044
ValueCountFrequency (%)
04969 6
 
9.7%
05044 5
 
8.1%
04930 3
 
4.8%
05055 3
 
4.8%
05072 2
 
3.2%
04929 2
 
3.2%
05043 2
 
3.2%
05022 2
 
3.2%
04947 1
 
1.6%
143-827 1
 
1.6%
Other values (35) 35
56.5%
2024-04-06T19:40:53.070473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 93
29.1%
4 50
15.6%
9 42
13.1%
5 42
13.1%
3 22
 
6.9%
1 19
 
5.9%
2 16
 
5.0%
6 14
 
4.4%
7 11
 
3.4%
8 10
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319
99.7%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 93
29.2%
4 50
15.7%
9 42
13.2%
5 42
13.2%
3 22
 
6.9%
1 19
 
6.0%
2 16
 
5.0%
6 14
 
4.4%
7 11
 
3.4%
8 10
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 93
29.1%
4 50
15.6%
9 42
13.1%
5 42
13.1%
3 22
 
6.9%
1 19
 
5.9%
2 16
 
5.0%
6 14
 
4.4%
7 11
 
3.4%
8 10
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 93
29.1%
4 50
15.6%
9 42
13.1%
5 42
13.1%
3 22
 
6.9%
1 19
 
5.9%
2 16
 
5.0%
6 14
 
4.4%
7 11
 
3.4%
8 10
 
3.1%
Distinct89
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2024-04-06T19:40:53.515549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12.5
Mean length8.0666667
Min length4

Characters and Unicode

Total characters726
Distinct characters184
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)97.8%

Sample

1st row유아랑관광
2nd row(주)신우주관광
3rd row(주)강남고속
4th row(주)항공모함여행사
5th row(주)에스민여행사
ValueCountFrequency (%)
주식회사 14
 
13.0%
신세기여행사 2
 
1.9%
주)차이나드림컨설팅 1
 
0.9%
주)동서울여행사 1
 
0.9%
월드베이스볼투어 1
 
0.9%
데이아웃 1
 
0.9%
주)니즈엔터프라이즈 1
 
0.9%
링크관광개발 1
 
0.9%
주)클럽보드레저산업개발 1
 
0.9%
주)세정여행사 1
 
0.9%
Other values (84) 84
77.8%
2024-04-06T19:40:54.276870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
8.7%
( 47
 
6.5%
) 47
 
6.5%
34
 
4.7%
27
 
3.7%
25
 
3.4%
20
 
2.8%
20
 
2.8%
18
 
2.5%
18
 
2.5%
Other values (174) 407
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 603
83.1%
Open Punctuation 47
 
6.5%
Close Punctuation 47
 
6.5%
Space Separator 18
 
2.5%
Uppercase Letter 10
 
1.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
63
 
10.4%
34
 
5.6%
27
 
4.5%
25
 
4.1%
20
 
3.3%
20
 
3.3%
18
 
3.0%
17
 
2.8%
15
 
2.5%
10
 
1.7%
Other values (162) 354
58.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
M 2
20.0%
T 1
10.0%
W 1
10.0%
A 1
10.0%
I 1
10.0%
D 1
10.0%
E 1
10.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 603
83.1%
Common 113
 
15.6%
Latin 10
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
63
 
10.4%
34
 
5.6%
27
 
4.5%
25
 
4.1%
20
 
3.3%
20
 
3.3%
18
 
3.0%
17
 
2.8%
15
 
2.5%
10
 
1.7%
Other values (162) 354
58.7%
Latin
ValueCountFrequency (%)
C 2
20.0%
M 2
20.0%
T 1
10.0%
W 1
10.0%
A 1
10.0%
I 1
10.0%
D 1
10.0%
E 1
10.0%
Common
ValueCountFrequency (%)
( 47
41.6%
) 47
41.6%
18
 
15.9%
- 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 603
83.1%
ASCII 123
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
63
 
10.4%
34
 
5.6%
27
 
4.5%
25
 
4.1%
20
 
3.3%
20
 
3.3%
18
 
3.0%
17
 
2.8%
15
 
2.5%
10
 
1.7%
Other values (162) 354
58.7%
ASCII
ValueCountFrequency (%)
( 47
38.2%
) 47
38.2%
18
 
14.6%
C 2
 
1.6%
M 2
 
1.6%
T 1
 
0.8%
W 1
 
0.8%
A 1
 
0.8%
- 1
 
0.8%
I 1
 
0.8%
Other values (2) 2
 
1.6%

최종수정일자
Date

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2005-11-09 18:16:58
Maximum2024-03-27 09:15:46
2024-04-06T19:40:54.554455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:40:54.789244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
I
46 
U
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 46
51.1%
U 44
48.9%

Length

2024-04-06T19:40:55.042687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:55.211348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 46
51.1%
u 44
48.9%
Distinct36
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2018-08-31 23:59:59.0
46 
2022-10-31 23:09:00.0
2022-12-06 22:00:00.0
 
3
2021-11-27 02:40:00.0
 
2
2023-12-03 00:08:00.0
 
2
Other values (31)
31 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique31 ?
Unique (%)34.4%

Sample

1st row2022-12-06 22:00:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 46
51.1%
2022-10-31 23:09:00.0 6
 
6.7%
2022-12-06 22:00:00.0 3
 
3.3%
2021-11-27 02:40:00.0 2
 
2.2%
2023-12-03 00:08:00.0 2
 
2.2%
2021-12-04 02:40:00.0 1
 
1.1%
2021-10-29 02:40:00.0 1
 
1.1%
2022-12-03 22:09:00.0 1
 
1.1%
2022-12-02 22:03:00.0 1
 
1.1%
2022-10-31 22:05:00.0 1
 
1.1%
Other values (26) 26
28.9%

Length

2024-04-06T19:40:55.400280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 46
25.6%
23:59:59.0 46
25.6%
02:40:00.0 15
 
8.3%
2022-10-31 7
 
3.9%
23:09:00.0 6
 
3.3%
2022-12-06 4
 
2.2%
2022-12-02 4
 
2.2%
22:00:00.0 3
 
1.7%
2023-12-03 3
 
1.7%
22:09:00.0 2
 
1.1%
Other values (37) 44
24.4%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)83.0%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean207452.72
Minimum205828.25
Maximum209668.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:40:55.625492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205828.25
5-th percentile205891.41
Q1206940.48
median207359.32
Q3207902.03
95-th percentile209549.38
Maximum209668.9
Range3840.6477
Interquartile range (IQR)961.55697

Descriptive statistics

Standard deviation937.34272
Coefficient of variation (CV)0.0045183437
Kurtosis0.51823
Mean207452.72
Median Absolute Deviation (MAD)514.99559
Skewness0.54986915
Sum18255840
Variance878611.37
MonotonicityNot monotonic
2024-04-06T19:40:55.881735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209668.90120464 4
 
4.4%
208006.504810197 3
 
3.3%
207388.308848516 3
 
3.3%
207281.948699606 3
 
3.3%
207475.144909536 2
 
2.2%
207131.426666412 2
 
2.2%
207325.576921423 2
 
2.2%
205828.253476728 2
 
2.2%
205845.235477102 2
 
2.2%
209367.991933454 2
 
2.2%
Other values (63) 63
70.0%
(Missing) 2
 
2.2%
ValueCountFrequency (%)
205828.253476728 2
2.2%
205845.235477102 2
2.2%
205886.288968009 1
1.1%
205900.907866005 1
1.1%
205988.468227018 1
1.1%
206031.034219491 1
1.1%
206057.580556153 1
1.1%
206135.609362634 1
1.1%
206324.116092316 1
1.1%
206393.562375942 1
1.1%
ValueCountFrequency (%)
209668.90120464 4
4.4%
209637.078215509 1
 
1.1%
209386.519074531 1
 
1.1%
209367.991933454 2
2.2%
208776.911786206 1
 
1.1%
208338.31599039 1
 
1.1%
208201.993320839 1
 
1.1%
208189.434497483 1
 
1.1%
208163.482249441 1
 
1.1%
208126.413686279 1
 
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)83.0%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean449271.07
Minimum447314.06
Maximum452036.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:40:56.131302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447314.06
5-th percentile447905.36
Q1448364.72
median449323.87
Q3450126.62
95-th percentile450814.14
Maximum452036.14
Range4722.0831
Interquartile range (IQR)1761.8967

Descriptive statistics

Standard deviation1044.0729
Coefficient of variation (CV)0.0023239264
Kurtosis-0.70965073
Mean449271.07
Median Absolute Deviation (MAD)900.39132
Skewness0.38816491
Sum39535854
Variance1090088.2
MonotonicityNot monotonic
2024-04-06T19:40:56.377585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449767.964721034 4
 
4.4%
447998.924380413 3
 
3.3%
448313.517465433 3
 
3.3%
448219.671396301 3
 
3.3%
450340.862168452 2
 
2.2%
450569.212408341 2
 
2.2%
448526.049057258 2
 
2.2%
448575.453228821 2
 
2.2%
448487.468509742 2
 
2.2%
449464.138000765 2
 
2.2%
Other values (63) 63
70.0%
(Missing) 2
 
2.2%
ValueCountFrequency (%)
447314.058937118 1
 
1.1%
447750.838364027 1
 
1.1%
447810.832206499 1
 
1.1%
447869.510348339 1
 
1.1%
447873.626054109 1
 
1.1%
447964.288794784 1
 
1.1%
447967.299542306 1
 
1.1%
447998.924380413 3
3.3%
448129.166313052 1
 
1.1%
448167.472990408 1
 
1.1%
ValueCountFrequency (%)
452036.142053293 1
1.1%
451522.314560436 1
1.1%
451381.691441567 1
1.1%
451297.373903151 1
1.1%
450840.637116234 1
1.1%
450764.939696563 1
1.1%
450680.671703358 1
1.1%
450625.255482591 1
1.1%
450583.054957622 1
1.1%
450569.212408341 2
2.2%
Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
국내여행업
61 
<NA>
29 

Length

Max length5
Median length5
Mean length4.6777778
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 61
67.8%
<NA> 29
32.2%

Length

2024-04-06T19:40:56.595884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:56.756318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 61
67.8%
na 29
32.2%
Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
57 
관광사업
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 57
63.3%
관광사업 33
36.7%

Length

2024-04-06T19:40:56.952082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:57.134735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
63.3%
관광사업 33
36.7%

지역구분명
Text

MISSING 

Distinct6
Distinct (%)75.0%
Missing82
Missing (%)91.1%
Memory size852.0 B
2024-04-06T19:40:57.361769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.375
Min length4

Characters and Unicode

Total characters43
Distinct characters13
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

Unique5 ?
Unique (%)62.5%

Sample

1st row근린상업지역
2nd row준주거지역
3rd row일반상업지역
4th row근린상업지역
5th row일반주거지역
ValueCountFrequency (%)
근린상업지역 3
37.5%
준주거지역 1
 
12.5%
일반상업지역 1
 
12.5%
일반주거지역 1
 
12.5%
관리지역 1
 
12.5%
상업지역 1
 
12.5%
2024-04-06T19:40:57.969661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
18.6%
8
18.6%
5
11.6%
5
11.6%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (3) 3
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8
18.6%
8
18.6%
5
11.6%
5
11.6%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (3) 3
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8
18.6%
8
18.6%
5
11.6%
5
11.6%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (3) 3
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
8
18.6%
8
18.6%
5
11.6%
5
11.6%
3
 
7.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
Other values (3) 3
 
7.0%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)76.9%
Missing77
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean6.6923077
Minimum0
Maximum21
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:40:58.188837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q311
95-th percentile18
Maximum21
Range21
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.0045773
Coefficient of variation (CV)1.046661
Kurtosis-0.33622237
Mean6.6923077
Median Absolute Deviation (MAD)5
Skewness0.88716554
Sum87
Variance49.064103
MonotonicityNot monotonic
2024-04-06T19:40:58.402314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3
 
3.3%
1 2
 
2.2%
4 1
 
1.1%
6 1
 
1.1%
5 1
 
1.1%
21 1
 
1.1%
7 1
 
1.1%
15 1
 
1.1%
16 1
 
1.1%
11 1
 
1.1%
(Missing) 77
85.6%
ValueCountFrequency (%)
0 3
3.3%
1 2
2.2%
4 1
 
1.1%
5 1
 
1.1%
6 1
 
1.1%
7 1
 
1.1%
11 1
 
1.1%
15 1
 
1.1%
16 1
 
1.1%
21 1
 
1.1%
ValueCountFrequency (%)
21 1
 
1.1%
16 1
 
1.1%
15 1
 
1.1%
11 1
 
1.1%
7 1
 
1.1%
6 1
 
1.1%
5 1
 
1.1%
4 1
 
1.1%
1 2
2.2%
0 3
3.3%

주변환경명
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
84 
기타
 
4
주택가주변
 
2

Length

Max length5
Median length4
Mean length3.9333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
93.3%
기타 4
 
4.4%
주택가주변 2
 
2.2%

Length

2024-04-06T19:40:58.677076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:40:58.883176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
93.3%
기타 4
 
4.4%
주택가주변 2
 
2.2%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

보험기관명
Categorical

Distinct11
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
58 
서울보증보험
10 
서울특별시관광협회
한국관광협회중앙회 여행공제회
 
5
서울보증보험주식회사
 
4
Other values (6)

Length

Max length16
Median length4
Mean length5.9444444
Min length4

Unique

Unique5 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
64.4%
서울보증보험 10
 
11.1%
서울특별시관광협회 6
 
6.7%
한국관광협회중앙회 여행공제회 5
 
5.6%
서울보증보험주식회사 4
 
4.4%
서울시관광협회 2
 
2.2%
서울보증보험주식회사(삼천만원) 1
 
1.1%
서울보증보험(20,000천원) 1
 
1.1%
한국관광협회중앙회 1
 
1.1%
서울보증보험주식사 1
 
1.1%

Length

2024-04-06T19:40:59.156610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 58
60.4%
서울보증보험 11
 
11.5%
서울특별시관광협회 6
 
6.2%
한국관광협회중앙회 6
 
6.2%
여행공제회 5
 
5.2%
서울보증보험주식회사 4
 
4.2%
서울시관광협회 2
 
2.1%
서울보증보험주식회사(삼천만원 1
 
1.0%
서울보증보험(20,000천원 1
 
1.0%
서울보증보험주식사 1
 
1.0%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
81 
근린생활시설
 
5
사무실
 
3
기타
 
1

Length

Max length6
Median length4
Mean length4.0555556
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 81
90.0%
근린생활시설 5
 
5.6%
사무실 3
 
3.3%
기타 1
 
1.1%

Length

2024-04-06T19:40:59.556670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:00.002187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
90.0%
근린생활시설 5
 
5.6%
사무실 3
 
3.3%
기타 1
 
1.1%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)76.9%
Missing77
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean5.5384615
Minimum0
Maximum17
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:00.242666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q38
95-th percentile15.2
Maximum17
Range17
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.7389805
Coefficient of variation (CV)1.0362048
Kurtosis-0.38279897
Mean5.5384615
Median Absolute Deviation (MAD)4
Skewness0.87664869
Sum72
Variance32.935897
MonotonicityNot monotonic
2024-04-06T19:41:00.473931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3
 
3.3%
1 2
 
2.2%
3 1
 
1.1%
5 1
 
1.1%
4 1
 
1.1%
17 1
 
1.1%
12 1
 
1.1%
14 1
 
1.1%
8 1
 
1.1%
7 1
 
1.1%
(Missing) 77
85.6%
ValueCountFrequency (%)
0 3
3.3%
1 2
2.2%
3 1
 
1.1%
4 1
 
1.1%
5 1
 
1.1%
7 1
 
1.1%
8 1
 
1.1%
12 1
 
1.1%
14 1
 
1.1%
17 1
 
1.1%
ValueCountFrequency (%)
17 1
 
1.1%
14 1
 
1.1%
12 1
 
1.1%
8 1
 
1.1%
7 1
 
1.1%
5 1
 
1.1%
4 1
 
1.1%
3 1
 
1.1%
1 2
2.2%
0 3
3.3%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
80 
1
 
3
0
 
3
3
 
2
4
 
1

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique2 ?
Unique (%)2.2%

Sample

1st row<NA>
2nd row1
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 80
88.9%
1 3
 
3.3%
0 3
 
3.3%
3 2
 
2.2%
4 1
 
1.1%
2 1
 
1.1%

Length

2024-04-06T19:41:00.733135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:00.983821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 80
88.9%
1 3
 
3.3%
0 3
 
3.3%
3 2
 
2.2%
4 1
 
1.1%
2 1
 
1.1%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:01.235532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:01.430229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:01.675636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:01.915720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

영문상호명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing88
Missing (%)97.8%
Memory size852.0 B
2024-04-06T19:41:02.127734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length14
Min length13

Characters and Unicode

Total characters28
Distinct characters15
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

Unique2 ?
Unique (%)100.0%

Sample

1st rowCheerful Tour
2nd rowChounha Ace Co.
ValueCountFrequency (%)
cheerful 1
20.0%
tour 1
20.0%
chounha 1
20.0%
ace 1
20.0%
co 1
20.0%
2024-04-06T19:41:02.776743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 3
10.7%
h 3
10.7%
e 3
10.7%
u 3
10.7%
3
10.7%
o 3
10.7%
r 2
 
7.1%
f 1
 
3.6%
l 1
 
3.6%
T 1
 
3.6%
Other values (5) 5
17.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19
67.9%
Uppercase Letter 5
 
17.9%
Space Separator 3
 
10.7%
Other Punctuation 1
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
h 3
15.8%
e 3
15.8%
u 3
15.8%
o 3
15.8%
r 2
10.5%
f 1
 
5.3%
l 1
 
5.3%
n 1
 
5.3%
a 1
 
5.3%
c 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
60.0%
T 1
 
20.0%
A 1
 
20.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
85.7%
Common 4
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 3
12.5%
h 3
12.5%
e 3
12.5%
u 3
12.5%
o 3
12.5%
r 2
8.3%
f 1
 
4.2%
l 1
 
4.2%
T 1
 
4.2%
n 1
 
4.2%
Other values (3) 3
12.5%
Common
ValueCountFrequency (%)
3
75.0%
. 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 3
10.7%
h 3
10.7%
e 3
10.7%
u 3
10.7%
3
10.7%
o 3
10.7%
r 2
 
7.1%
f 1
 
3.6%
l 1
 
3.6%
T 1
 
3.6%
Other values (5) 5
17.9%

영문상호주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing88
Missing (%)97.8%
Memory size852.0 B
2024-04-06T19:41:03.075061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters48
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDomestic Travel Business
2nd rowDomestic Travel Business
ValueCountFrequency (%)
domestic 2
33.3%
travel 2
33.3%
business 2
33.3%
2024-04-06T19:41:03.526896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8
16.7%
e 6
12.5%
4
 
8.3%
i 4
 
8.3%
r 2
 
4.2%
u 2
 
4.2%
B 2
 
4.2%
l 2
 
4.2%
v 2
 
4.2%
a 2
 
4.2%
Other values (7) 14
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38
79.2%
Uppercase Letter 6
 
12.5%
Space Separator 4
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 8
21.1%
e 6
15.8%
i 4
10.5%
r 2
 
5.3%
u 2
 
5.3%
l 2
 
5.3%
v 2
 
5.3%
a 2
 
5.3%
o 2
 
5.3%
c 2
 
5.3%
Other values (3) 6
15.8%
Uppercase Letter
ValueCountFrequency (%)
B 2
33.3%
D 2
33.3%
T 2
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44
91.7%
Common 4
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 8
18.2%
e 6
13.6%
i 4
 
9.1%
r 2
 
4.5%
u 2
 
4.5%
B 2
 
4.5%
l 2
 
4.5%
v 2
 
4.5%
a 2
 
4.5%
D 2
 
4.5%
Other values (6) 12
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 8
16.7%
e 6
12.5%
4
 
8.3%
i 4
 
8.3%
r 2
 
4.2%
u 2
 
4.2%
B 2
 
4.2%
l 2
 
4.2%
v 2
 
4.2%
a 2
 
4.2%
Other values (7) 14
29.2%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:03.741546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:03.924054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:04.133680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:04.354460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:04.943781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:05.138043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:05.349509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:05.525723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:05.702278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:05.913184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)88.2%
Missing73
Missing (%)81.1%
Infinite0
Infinite (%)0.0%
Mean106.11824
Minimum0
Maximum634.5
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:06.088807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.94
median31.35
Q366
95-th percentile544.74
Maximum634.5
Range634.5
Interquartile range (IQR)43.06

Descriptive statistics

Standard deviation185.20421
Coefficient of variation (CV)1.7452628
Kurtosis4.7592942
Mean106.11824
Median Absolute Deviation (MAD)17.65
Skewness2.3769909
Sum1804.01
Variance34300.598
MonotonicityNot monotonic
2024-04-06T19:41:06.322127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 3
 
3.3%
634.5 1
 
1.1%
207.9 1
 
1.1%
41.73 1
 
1.1%
33.0 1
 
1.1%
31.35 1
 
1.1%
87.0 1
 
1.1%
22.0 1
 
1.1%
522.3 1
 
1.1%
66.0 1
 
1.1%
Other values (5) 5
 
5.6%
(Missing) 73
81.1%
ValueCountFrequency (%)
0.0 3
3.3%
22.0 1
 
1.1%
22.94 1
 
1.1%
26.69 1
 
1.1%
29.6 1
 
1.1%
30.0 1
 
1.1%
31.35 1
 
1.1%
33.0 1
 
1.1%
41.73 1
 
1.1%
49.0 1
 
1.1%
ValueCountFrequency (%)
634.5 1
1.1%
522.3 1
1.1%
207.9 1
1.1%
87.0 1
1.1%
66.0 1
1.1%
49.0 1
1.1%
41.73 1
1.1%
33.0 1
1.1%
31.35 1
1.1%
30.0 1
1.1%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
<NA>
89 
0
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
98.9%
0 1
 
1.1%

Length

2024-04-06T19:41:06.551411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:41:06.784241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
98.9%
0 1
 
1.1%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

자본금
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)50.0%
Missing52
Missing (%)57.8%
Infinite0
Infinite (%)0.0%
Mean76441960
Minimum10430000
Maximum5 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:07.022964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10430000
5-th percentile15000000
Q130132500
median50000000
Q31 × 108
95-th percentile1.65 × 108
Maximum5 × 108
Range4.8957 × 108
Interquartile range (IQR)69867500

Descriptive statistics

Standard deviation85173695
Coefficient of variation (CV)1.114227
Kurtosis16.836555
Mean76441960
Median Absolute Deviation (MAD)30000000
Skewness3.6899106
Sum2.9047945 × 109
Variance7.2545584 × 1015
MonotonicityNot monotonic
2024-04-06T19:41:07.239070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
50000000 7
 
7.8%
100000000 7
 
7.8%
30000000 4
 
4.4%
15000000 3
 
3.3%
20000000 2
 
2.2%
150000000 2
 
2.2%
30530000 1
 
1.1%
33500000 1
 
1.1%
35000000 1
 
1.1%
500000000 1
 
1.1%
Other values (9) 9
 
10.0%
(Missing) 52
57.8%
ValueCountFrequency (%)
10430000 1
 
1.1%
15000000 3
3.3%
20000000 2
 
2.2%
30000000 4
4.4%
30530000 1
 
1.1%
33500000 1
 
1.1%
35000000 1
 
1.1%
38348504 1
 
1.1%
50000000 7
7.8%
54703617 1
 
1.1%
ValueCountFrequency (%)
500000000 1
 
1.1%
250000000 1
 
1.1%
150000000 2
 
2.2%
100000000 7
7.8%
92191151 1
 
1.1%
90091206 1
 
1.1%
90000000 1
 
1.1%
65000000 1
 
1.1%
60000000 1
 
1.1%
54703617 1
 
1.1%

보험시작일자
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)100.0%
Missing58
Missing (%)64.4%
Infinite0
Infinite (%)0.0%
Mean20154401
Minimum20031020
Maximum20210615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:07.467971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031020
5-th percentile20046486
Q120140738
median20160514
Q320200344
95-th percentile20210504
Maximum20210615
Range179595
Interquartile range (IQR)59605.5

Descriptive statistics

Standard deviation53096.955
Coefficient of variation (CV)0.0026345092
Kurtosis0.11109321
Mean20154401
Median Absolute Deviation (MAD)30491.5
Skewness-1.0159511
Sum6.4494084 × 108
Variance2.8192867 × 109
MonotonicityNot monotonic
2024-04-06T19:41:07.741219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20160414 1
 
1.1%
20210309 1
 
1.1%
20201216 1
 
1.1%
20200318 1
 
1.1%
20190318 1
 
1.1%
20191201 1
 
1.1%
20201103 1
 
1.1%
20130927 1
 
1.1%
20160216 1
 
1.1%
20161201 1
 
1.1%
Other values (22) 22
 
24.4%
(Missing) 58
64.4%
ValueCountFrequency (%)
20031020 1
1.1%
20041206 1
1.1%
20050806 1
1.1%
20070601 1
1.1%
20080122 1
1.1%
20080213 1
1.1%
20130927 1
1.1%
20140521 1
1.1%
20140811 1
1.1%
20140904 1
1.1%
ValueCountFrequency (%)
20210615 1
1.1%
20210507 1
1.1%
20210502 1
1.1%
20210423 1
1.1%
20210309 1
1.1%
20201216 1
1.1%
20201103 1
1.1%
20200422 1
1.1%
20200318 1
1.1%
20191201 1
1.1%

보험종료일자
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)100.0%
Missing58
Missing (%)64.4%
Infinite0
Infinite (%)0.0%
Mean20165332
Minimum20041020
Maximum20230501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:08.015662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20041020
5-th percentile20056486
Q120150738
median20170514
Q320210343
95-th percentile20220555
Maximum20230501
Range189481
Interquartile range (IQR)59605.25

Descriptive statistics

Standard deviation52930.116
Coefficient of variation (CV)0.0026248076
Kurtosis0.18131316
Mean20165332
Median Absolute Deviation (MAD)30456
Skewness-1.0123055
Sum6.4529061 × 108
Variance2.8015972 × 109
MonotonicityNot monotonic
2024-04-06T19:41:08.274070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20170414 1
 
1.1%
20220308 1
 
1.1%
20211215 1
 
1.1%
20210317 1
 
1.1%
20200318 1
 
1.1%
20201130 1
 
1.1%
20211103 1
 
1.1%
20140926 1
 
1.1%
20170216 1
 
1.1%
20171130 1
 
1.1%
Other values (22) 22
 
24.4%
(Missing) 58
64.4%
ValueCountFrequency (%)
20041020 1
1.1%
20051206 1
1.1%
20060806 1
1.1%
20090122 1
1.1%
20090213 1
1.1%
20090531 1
1.1%
20140926 1
1.1%
20150521 1
1.1%
20150810 1
1.1%
20160517 1
1.1%
ValueCountFrequency (%)
20230501 1
1.1%
20220614 1
1.1%
20220506 1
1.1%
20220422 1
1.1%
20220308 1
1.1%
20211215 1
1.1%
20211103 1
1.1%
20210421 1
1.1%
20210317 1
1.1%
20201130 1
1.1%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)82.4%
Missing73
Missing (%)81.1%
Infinite0
Infinite (%)0.0%
Mean106.17647
Minimum0
Maximum635
Zeros3
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size942.0 B
2024-04-06T19:41:08.570686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123
median31
Q366
95-th percentile544.6
Maximum635
Range635
Interquartile range (IQR)43

Descriptive statistics

Standard deviation185.23743
Coefficient of variation (CV)1.7446184
Kurtosis4.7655254
Mean106.17647
Median Absolute Deviation (MAD)18
Skewness2.3777419
Sum1805
Variance34312.904
MonotonicityNot monotonic
2024-04-06T19:41:08.835098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 3
 
3.3%
30 2
 
2.2%
635 1
 
1.1%
208 1
 
1.1%
42 1
 
1.1%
33 1
 
1.1%
31 1
 
1.1%
87 1
 
1.1%
22 1
 
1.1%
522 1
 
1.1%
Other values (4) 4
 
4.4%
(Missing) 73
81.1%
ValueCountFrequency (%)
0 3
3.3%
22 1
 
1.1%
23 1
 
1.1%
27 1
 
1.1%
30 2
2.2%
31 1
 
1.1%
33 1
 
1.1%
42 1
 
1.1%
49 1
 
1.1%
66 1
 
1.1%
ValueCountFrequency (%)
635 1
1.1%
522 1
1.1%
208 1
1.1%
87 1
1.1%
66 1
1.1%
49 1
1.1%
42 1
1.1%
33 1
1.1%
31 1
1.1%
30 2
2.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03040000CDFI22600119930000011993-04-132023-07-184취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>143-827서울특별시 광진구 구의동 254-114서울특별시 광진구 자양로 165 (구의동)143-827유아랑관광2023-07-18 17:08:48U2022-12-06 22:00:00.0<NA>207339.945214448905.562845<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13040000CDFI226001199400000119940527<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>453-3031<NA>143883서울특별시 광진구 중곡동 20-2번지 서암빌딩1층서울특별시 광진구 용마산로22길 28 (중곡동,서암빌딩1층)<NA>(주)신우주관광2008-04-16 16:04:06I2018-08-31 23:59:59.0<NA>207749.266943451297.373903국내여행업관광사업<NA>4주택가주변<NA><NA>근린생활시설31<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23040000CDFI226001199700000119970117<NA>3폐업3폐업20091231<NA><NA><NA>453-5458<NA>143838서울특별시 광진구 군자동 473-19번지서울특별시 광진구 천호대로 540 (군자동)<NA>(주)강남고속2010-06-09 17:53:28I2018-08-31 23:59:59.0<NA>206836.813489450561.267729국내여행업관광사업근린상업지역6주택가주변<NA><NA>근린생활시설51<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>634.5<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>635
33040000CDFI226001199700000219970802<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>497-4334<NA>143866서울특별시 광진구 자양동 619-24번지서울특별시 광진구 뚝섬로49길 11-1 (자양동)<NA>(주)항공모함여행사2007-07-02 15:41:39I2018-08-31 23:59:59.0<NA>206880.990498447869.510348국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43040000CDFI226001199800000119980525<NA>3폐업3폐업20061117<NA><NA><NA>447-0367<NA>143826서울특별시 광진구 구의동 252-16번지 동일빌딩 302호서울특별시 광진구 자양로 116 (구의동,동일빌딩 302호)<NA>(주)에스민여행사2006-11-20 13:53:38I2018-08-31 23:59:59.0<NA>207342.766107448444.754635국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53040000CDFI226001199800000219980813<NA>3폐업3폐업20061204<NA><NA><NA><NA><NA>143889서울특별시 광진구 중곡동 115-4번지 공원빌딩 3층동서울특별시 광진구 천호대로 647, 3층동 (중곡동,공원빌딩)<NA>(주)오로라관광여행사2006-12-05 11:08:05I2018-08-31 23:59:59.0<NA>207824.309885450114.867822국내여행업관광사업<NA>0<NA><NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
63040000CDFI226001199900000119990518<NA>3폐업3폐업20051206<NA><NA><NA>3436-0888<NA>143825서울특별시 광진구 구의동 246-3번지 민도빌딩 301호서울특별시 광진구 아차산로 395 (구의동,민도빌딩 301호)<NA>여행코리아주식회사2005-12-07 10:04:11I2018-08-31 23:59:59.0<NA>207564.476227448369.568917국내여행업관광사업<NA>5기타<NA><NA>근린생활시설41<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>207.9<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>208
73040000CDFI226001200000000220000520<NA>3폐업3폐업20051213<NA><NA><NA>464-2905<NA>143747서울특별시 광진구 군자동 98-0번지 세종대학교학생회관<NA><NA>세종관광정보(주)2005-12-14 10:09:30I2018-08-31 23:59:59.0<NA>206479.980834449827.630946국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83040000CDFI226001200000000420000724<NA>3폐업3폐업20150602<NA><NA><NA>02-3436-3006<NA>143760서울특별시 광진구 구의동 252-11번지 성지하이츠 910호서울특별시 광진구 자양로 126, 8층 910호 (구의동, 성지하이츠)143760주식회사 제이티씨여행사2015-06-09 17:23:02I2018-08-31 23:59:59.0<NA>207336.338043448547.289498국내여행업관광사업<NA><NA><NA><NA>서울특별시관광협회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2014052120150521<NA><NA>
93040000CDFI226001200000000520000814<NA>3폐업3폐업20061002<NA><NA><NA>444-7447<NA>143875서울특별시 광진구 자양동 682-28번지 고려빌딩2층서울특별시 광진구 뚝섬로 704 (자양동,고려빌딩2층)<NA>주식회사 미래정보넷2006-10-02 15:00:36I2018-08-31 23:59:59.0<NA>207655.703185447873.626054국내여행업관광사업<NA>0<NA><NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
803040000CDFI22600120210000012021-01-22<NA>1영업/정상13영업중<NA><NA><NA><NA>02-499-9188<NA><NA>서울특별시 광진구 자양동 4-9서울특별시 광진구 동일로18길 78, 1층 (자양동)05075신세기여행사2024-03-05 10:30:07U2023-12-03 00:07:00.0<NA>205845.235477448487.46851<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
813040000CDFI22600120210000022021-04-13<NA>3폐업3폐업2023-05-03<NA><NA><NA>02-338-8888<NA><NA>서울특별시 광진구 자양동 626-3 아스하임서울특별시 광진구 자양로13길 8, 9층 901호 (자양동, 아스하임)05056주식회사 비즈공감2023-05-03 14:43:24U2022-12-05 00:05:00.0<NA>207284.923326448167.47299<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
823040000CDFI22600120210000032021-08-05<NA>3폐업3폐업2024-01-22<NA><NA><NA><NA><NA><NA>서울특별시 광진구 중곡동 80-10서울특별시 광진구 용마산로 38, 2층 201-1호 (중곡동)04949(주)페니엔터테인먼트2024-01-23 08:50:09U2023-11-30 22:05:00.0<NA>207736.066611450524.089944<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
833040000CDFI22600120210000042021-09-07<NA>3폐업3폐업2023-03-24<NA><NA><NA><NA><NA><NA>서울특별시 광진구 구의동 252-14 성지하이츠서울특별시 광진구 자양로 126, 성지하이츠 7층 710호 (구의동)05043주식회사 투어커뮤니케이션2023-03-24 17:18:51U2022-12-02 22:06:00.0<NA>207325.576921448526.049057<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
843040000CDFI226001202100000520210923<NA>3폐업3폐업20220818<NA><NA><NA><NA><NA><NA>서울특별시 광진구 자양동 9-13 서울특별시 동부여성발전센타서울특별시 광진구 아차산로30길 36, 서울특별시 동부여성발전센타 2층 204호 (자양동)05072청춘라떼2022-08-19 13:30:19U2021-12-07 22:01:00.0<NA>205828.253477448575.453229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
853040000CDFI22600120210000062021-12-21<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7953-2963<NA><NA>서울특별시 광진구 군자동 473-23 서림빌딩서울특별시 광진구 천호대로 536, 서림빌딩 6층 (군자동)04996주식회사 뉴런즈2023-11-17 14:45:41U2022-10-31 23:09:00.0<NA>206792.027736450583.054958<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
863040000CDFI22600120220000012022-10-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6954-6956<NA><NA>서울특별시 광진구 중곡동 142-21 SUN S 빌딩서울특별시 광진구 능동로38길 27, SUN S 빌딩 3층 301호 (중곡동)04929교육상점 주식회사2024-03-06 10:01:22U2023-12-03 00:08:00.0<NA>207131.426666450569.212408<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
873040000CDFI22600120220000022022-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-438-0189<NA><NA>서울특별시 광진구 화양동 481-1 에듀킨빌딩서울특별시 광진구 광나루로 436, 에듀킨빌딩 6층 (화양동)05022오라이투어2023-11-17 15:10:15U2022-10-31 23:09:00.0<NA>206799.232291449257.591473<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
883040000CDFI22600120230000012023-05-03<NA>5제외/삭제/전출15전출2024-03-27<NA><NA><NA><NA><NA><NA>서울특별시 광진구 구의동 681 광진 경제허브센터 도약관 208호서울특별시 광진구 광나루로 478, 광진 경제허브센터 도약관 208호 (구의동)05022주식회사 빌리지하우징2024-03-27 09:15:46U2023-12-02 22:09:00.0<NA>207181.590734449188.899221<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
893040000CDFI22600120230000022019-08-13<NA>3폐업3폐업2023-09-11<NA><NA><NA><NA><NA><NA>서울특별시 광진구 구의동 72-30서울특별시 광진구 천호대로136길 28, 2층 (구의동)04975해랑여행사2023-09-11 11:21:21U2022-12-08 23:03:00.0<NA>207946.743084449566.594501<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>