Overview

Dataset statistics

Number of variables60
Number of observations294
Missing cells6310
Missing cells (%)35.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory148.9 KiB
Average record size in memory518.4 B

Variable types

Categorical25
Text9
DateTime4
Numeric10
Unsupported12

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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-17592/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (82.1%)Imbalance
휴업시작일자 is highly imbalanced (95.9%)Imbalance
휴업종료일자 is highly imbalanced (95.9%)Imbalance
지역구분명 is highly imbalanced (80.4%)Imbalance
주변환경명 is highly imbalanced (78.4%)Imbalance
보험기관명 is highly imbalanced (54.3%)Imbalance
건물용도명 is highly imbalanced (77.0%)Imbalance
지하층수 is highly imbalanced (81.4%)Imbalance
객실수 is highly imbalanced (89.6%)Imbalance
건축연면적 is highly imbalanced (89.6%)Imbalance
선박총톤수 is highly imbalanced (89.6%)Imbalance
선박척수 is highly imbalanced (89.6%)Imbalance
무대면적 is highly imbalanced (89.6%)Imbalance
좌석수 is highly imbalanced (89.6%)Imbalance
회의실별동시수용인원 is highly imbalanced (89.6%)Imbalance
놀이시설수 is highly imbalanced (89.6%)Imbalance
기획여행보험시작일자 is highly imbalanced (96.7%)Imbalance
기획여행보험종료일자 is highly imbalanced (96.7%)Imbalance
폐업일자 has 195 (66.3%) missing valuesMissing
재개업일자 has 294 (100.0%) missing valuesMissing
전화번호 has 118 (40.1%) missing valuesMissing
소재지면적 has 294 (100.0%) missing valuesMissing
소재지우편번호 has 201 (68.4%) missing valuesMissing
도로명주소 has 7 (2.4%) missing valuesMissing
도로명우편번호 has 64 (21.8%) missing valuesMissing
업태구분명 has 294 (100.0%) missing valuesMissing
좌표정보(X) has 35 (11.9%) missing valuesMissing
좌표정보(Y) has 35 (11.9%) missing valuesMissing
총층수 has 267 (90.8%) missing valuesMissing
제작취급품목내용 has 294 (100.0%) missing valuesMissing
지상층수 has 268 (91.2%) missing valuesMissing
영문상호명 has 290 (98.6%) missing valuesMissing
영문상호주소 has 290 (98.6%) missing valuesMissing
선박제원 has 294 (100.0%) missing valuesMissing
기념품종류 has 294 (100.0%) missing valuesMissing
시설면적 has 250 (85.0%) missing valuesMissing
놀이기구수내역 has 294 (100.0%) missing valuesMissing
방송시설유무 has 294 (100.0%) missing valuesMissing
발전시설유무 has 294 (100.0%) missing valuesMissing
의무실유무 has 294 (100.0%) missing valuesMissing
안내소유무 has 294 (100.0%) missing valuesMissing
자본금 has 152 (51.7%) missing valuesMissing
보험시작일자 has 180 (61.2%) missing valuesMissing
보험종료일자 has 180 (61.2%) missing valuesMissing
부대시설내역 has 294 (100.0%) missing valuesMissing
시설규모 has 250 (85.0%) missing valuesMissing
관리번호 has unique valuesUnique
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
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 9 (3.1%) zerosZeros
지상층수 has 9 (3.1%) zerosZeros
시설면적 has 9 (3.1%) zerosZeros
시설규모 has 9 (3.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:53:07.870208
Analysis finished2024-05-11 06:53:09.284065
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
3150000
294 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 294
100.0%

Length

2024-05-11T15:53:09.404958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:09.611988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 294
100.0%

관리번호
Text

UNIQUE 

Distinct294
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T15:53:09.876487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters5880
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

Unique294 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021997000001
2nd rowCDFI2260021997000002
3rd rowCDFI2260021997000003
4th rowCDFI2260021997000004
5th rowCDFI2260021997000005
ValueCountFrequency (%)
cdfi2260021997000001 1
 
0.3%
cdfi2260022019000028 1
 
0.3%
cdfi2260022020000016 1
 
0.3%
cdfi2260022020000015 1
 
0.3%
cdfi2260022020000014 1
 
0.3%
cdfi2260022020000012 1
 
0.3%
cdfi2260022020000011 1
 
0.3%
cdfi2260022020000010 1
 
0.3%
cdfi2260022020000009 1
 
0.3%
cdfi2260022020000008 1
 
0.3%
Other values (284) 284
96.6%
2024-05-11T15:53:10.312614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2323
39.5%
2 1388
23.6%
6 337
 
5.7%
C 294
 
5.0%
D 294
 
5.0%
F 294
 
5.0%
I 294
 
5.0%
1 283
 
4.8%
9 88
 
1.5%
3 73
 
1.2%
Other values (4) 212
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4704
80.0%
Uppercase Letter 1176
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2323
49.4%
2 1388
29.5%
6 337
 
7.2%
1 283
 
6.0%
9 88
 
1.9%
3 73
 
1.6%
8 63
 
1.3%
4 57
 
1.2%
5 49
 
1.0%
7 43
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 294
25.0%
D 294
25.0%
F 294
25.0%
I 294
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4704
80.0%
Latin 1176
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2323
49.4%
2 1388
29.5%
6 337
 
7.2%
1 283
 
6.0%
9 88
 
1.9%
3 73
 
1.6%
8 63
 
1.3%
4 57
 
1.2%
5 49
 
1.0%
7 43
 
0.9%
Latin
ValueCountFrequency (%)
C 294
25.0%
D 294
25.0%
F 294
25.0%
I 294
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5880
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2323
39.5%
2 1388
23.6%
6 337
 
5.7%
C 294
 
5.0%
D 294
 
5.0%
F 294
 
5.0%
I 294
 
5.0%
1 283
 
4.8%
9 88
 
1.5%
3 73
 
1.2%
Other values (4) 212
 
3.6%
Distinct273
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1997-05-23 00:00:00
Maximum2024-03-28 00:00:00
2024-05-11T15:53:10.493808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:53:10.661542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
282 
20070907
 
8
20090424
 
4

Length

Max length8
Median length4
Mean length4.1632653
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row20070907
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 282
95.9%
20070907 8
 
2.7%
20090424 4
 
1.4%

Length

2024-05-11T15:53:10.905198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:11.130543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 282
95.9%
20070907 8
 
2.7%
20090424 4
 
1.4%
Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
1
178 
3
79 
5
22 
4
 
13
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 178
60.5%
3 79
26.9%
5 22
 
7.5%
4 13
 
4.4%
2 2
 
0.7%

Length

2024-05-11T15:53:11.296789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:11.435039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 178
60.5%
3 79
26.9%
5 22
 
7.5%
4 13
 
4.4%
2 2
 
0.7%

영업상태명
Categorical

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
영업/정상
178 
폐업
79 
제외/삭제/전출
22 
취소/말소/만료/정지/중지
 
13
휴업
 
2

Length

Max length14
Median length5
Mean length4.7959184
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 178
60.5%
폐업 79
26.9%
제외/삭제/전출 22
 
7.5%
취소/말소/만료/정지/중지 13
 
4.4%
휴업 2
 
0.7%

Length

2024-05-11T15:53:11.580501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:11.712515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 178
60.5%
폐업 79
26.9%
제외/삭제/전출 22
 
7.5%
취소/말소/만료/정지/중지 13
 
4.4%
휴업 2
 
0.7%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.180272
Minimum2
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:11.818150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median13
Q313
95-th percentile15
Maximum31
Range29
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.246759
Coefficient of variation (CV)0.5587305
Kurtosis2.3492152
Mean11.180272
Median Absolute Deviation (MAD)0
Skewness0.81199658
Sum3287
Variance39.021999
MonotonicityNot monotonic
2024-05-11T15:53:11.926997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
13 178
60.5%
3 79
26.9%
15 22
 
7.5%
31 12
 
4.1%
2 2
 
0.7%
30 1
 
0.3%
ValueCountFrequency (%)
2 2
 
0.7%
3 79
26.9%
13 178
60.5%
15 22
 
7.5%
30 1
 
0.3%
31 12
 
4.1%
ValueCountFrequency (%)
31 12
 
4.1%
30 1
 
0.3%
15 22
 
7.5%
13 178
60.5%
3 79
26.9%
2 2
 
0.7%
Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
영업중
178 
폐업
79 
전출
22 
등록취소
 
12
휴업
 
2

Length

Max length4
Median length3
Mean length2.6938776
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 178
60.5%
폐업 79
26.9%
전출 22
 
7.5%
등록취소 12
 
4.1%
휴업 2
 
0.7%
허가취소 1
 
0.3%

Length

2024-05-11T15:53:12.083048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:12.216986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 178
60.5%
폐업 79
26.9%
전출 22
 
7.5%
등록취소 12
 
4.1%
휴업 2
 
0.7%
허가취소 1
 
0.3%

폐업일자
Date

MISSING 

Distinct94
Distinct (%)94.9%
Missing195
Missing (%)66.3%
Memory size2.4 KiB
Minimum2000-02-29 00:00:00
Maximum2024-04-03 00:00:00
2024-05-11T15:53:12.397977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:53:12.937272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
292 
20080919
 
1
20210401
 
1

Length

Max length8
Median length4
Mean length4.0272109
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 292
99.3%
20080919 1
 
0.3%
20210401 1
 
0.3%

Length

2024-05-11T15:53:13.195732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:13.390485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 292
99.3%
20080919 1
 
0.3%
20210401 1
 
0.3%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
292 
20090820
 
1
20230331
 
1

Length

Max length8
Median length4
Mean length4.0272109
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 292
99.3%
20090820 1
 
0.3%
20230331 1
 
0.3%

Length

2024-05-11T15:53:13.528368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:13.682492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 292
99.3%
20090820 1
 
0.3%
20230331 1
 
0.3%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

전화번호
Text

MISSING 

Distinct175
Distinct (%)99.4%
Missing118
Missing (%)40.1%
Memory size2.4 KiB
2024-05-11T15:53:13.963639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.943182
Min length6

Characters and Unicode

Total characters1926
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)98.9%

Sample

1st row654-3045
2nd row2664-7777
3rd row02-2665-2222
4th row3661-8200
5th row666-3871
ValueCountFrequency (%)
02 4
 
2.2%
2668-1999 2
 
1.1%
02-6326-5111 1
 
0.6%
654-3045 1
 
0.6%
02-335-6944 1
 
0.6%
02-736-7880 1
 
0.6%
02-761-7557 1
 
0.6%
02-3210-2200 1
 
0.6%
02-6014-5760 1
 
0.6%
02-512-5369 1
 
0.6%
Other values (166) 166
92.2%
2024-05-11T15:53:14.569558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 308
16.0%
0 300
15.6%
- 279
14.5%
6 201
10.4%
7 151
7.8%
3 140
7.3%
5 121
 
6.3%
1 118
 
6.1%
8 111
 
5.8%
4 104
 
5.4%
Other values (4) 93
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1632
84.7%
Dash Punctuation 279
 
14.5%
Space Separator 7
 
0.4%
Close Punctuation 6
 
0.3%
Math Symbol 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 308
18.9%
0 300
18.4%
6 201
12.3%
7 151
9.3%
3 140
8.6%
5 121
 
7.4%
1 118
 
7.2%
8 111
 
6.8%
4 104
 
6.4%
9 78
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1926
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 308
16.0%
0 300
15.6%
- 279
14.5%
6 201
10.4%
7 151
7.8%
3 140
7.3%
5 121
 
6.3%
1 118
 
6.1%
8 111
 
5.8%
4 104
 
5.4%
Other values (4) 93
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 308
16.0%
0 300
15.6%
- 279
14.5%
6 201
10.4%
7 151
7.8%
3 140
7.3%
5 121
 
6.3%
1 118
 
6.1%
8 111
 
5.8%
4 104
 
5.4%
Other values (4) 93
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

소재지우편번호
Text

MISSING 

Distinct57
Distinct (%)61.3%
Missing201
Missing (%)68.4%
Memory size2.4 KiB
2024-05-11T15:53:14.935085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0107527
Min length6

Characters and Unicode

Total characters559
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

Unique40 ?
Unique (%)43.0%

Sample

1st row157897
2nd row157846
3rd row157863
4th row157864
5th row157862
ValueCountFrequency (%)
157863 5
 
5.4%
157840 5
 
5.4%
157812 5
 
5.4%
157030 5
 
5.4%
157924 4
 
4.3%
157031 3
 
3.2%
157857 3
 
3.2%
157925 3
 
3.2%
157853 3
 
3.2%
157847 3
 
3.2%
Other values (47) 54
58.1%
2024-05-11T15:53:15.577121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 118
21.1%
5 112
20.0%
7 110
19.7%
8 69
12.3%
0 39
 
7.0%
2 28
 
5.0%
4 24
 
4.3%
3 23
 
4.1%
9 21
 
3.8%
6 14
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 118
21.1%
5 112
20.1%
7 110
19.7%
8 69
12.4%
0 39
 
7.0%
2 28
 
5.0%
4 24
 
4.3%
3 23
 
4.1%
9 21
 
3.8%
6 14
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 559
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 118
21.1%
5 112
20.0%
7 110
19.7%
8 69
12.3%
0 39
 
7.0%
2 28
 
5.0%
4 24
 
4.3%
3 23
 
4.1%
9 21
 
3.8%
6 14
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 118
21.1%
5 112
20.0%
7 110
19.7%
8 69
12.3%
0 39
 
7.0%
2 28
 
5.0%
4 24
 
4.3%
3 23
 
4.1%
9 21
 
3.8%
6 14
 
2.5%
Distinct275
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T15:53:15.919063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length30.323129
Min length17

Characters and Unicode

Total characters8915
Distinct characters209
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)89.8%

Sample

1st row서울특별시 강서구 화곡동 796-16번지
2nd row서울특별시 강서구 방화동 249-293번지
3rd row서울특별시 강서구 방화동 621-15번지 1층
4th row서울특별시 강서구 염창동 273-4번지
5th row서울특별시 강서구 염창동 283-11번지
ValueCountFrequency (%)
서울특별시 294
 
17.7%
강서구 294
 
17.7%
마곡동 107
 
6.4%
화곡동 43
 
2.6%
등촌동 40
 
2.4%
방화동 35
 
2.1%
염창동 23
 
1.4%
가양동 18
 
1.1%
공항동 18
 
1.1%
b동 13
 
0.8%
Other values (502) 774
46.7%
2024-05-11T15:53:16.422598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1445
 
16.2%
596
 
6.7%
1 365
 
4.1%
340
 
3.8%
303
 
3.4%
298
 
3.3%
295
 
3.3%
294
 
3.3%
294
 
3.3%
294
 
3.3%
Other values (199) 4391
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5215
58.5%
Decimal Number 1917
 
21.5%
Space Separator 1445
 
16.2%
Dash Punctuation 277
 
3.1%
Uppercase Letter 43
 
0.5%
Letter Number 10
 
0.1%
Other Punctuation 4
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
596
 
11.4%
340
 
6.5%
303
 
5.8%
298
 
5.7%
295
 
5.7%
294
 
5.6%
294
 
5.6%
294
 
5.6%
177
 
3.4%
176
 
3.4%
Other values (171) 2148
41.2%
Decimal Number
ValueCountFrequency (%)
1 365
19.0%
7 270
14.1%
2 222
11.6%
0 220
11.5%
9 158
8.2%
3 158
8.2%
4 150
7.8%
5 134
 
7.0%
6 132
 
6.9%
8 108
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 18
41.9%
A 12
27.9%
C 4
 
9.3%
W 3
 
7.0%
D 2
 
4.7%
F 1
 
2.3%
V 1
 
2.3%
I 1
 
2.3%
P 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
/ 1
25.0%
. 1
25.0%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Space Separator
ValueCountFrequency (%)
1445
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 277
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5215
58.5%
Common 3647
40.9%
Latin 53
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
596
 
11.4%
340
 
6.5%
303
 
5.8%
298
 
5.7%
295
 
5.7%
294
 
5.6%
294
 
5.6%
294
 
5.6%
177
 
3.4%
176
 
3.4%
Other values (171) 2148
41.2%
Common
ValueCountFrequency (%)
1445
39.6%
1 365
 
10.0%
- 277
 
7.6%
7 270
 
7.4%
2 222
 
6.1%
0 220
 
6.0%
9 158
 
4.3%
3 158
 
4.3%
4 150
 
4.1%
5 134
 
3.7%
Other values (7) 248
 
6.8%
Latin
ValueCountFrequency (%)
B 18
34.0%
A 12
22.6%
6
 
11.3%
C 4
 
7.5%
4
 
7.5%
W 3
 
5.7%
D 2
 
3.8%
F 1
 
1.9%
V 1
 
1.9%
I 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5215
58.5%
ASCII 3690
41.4%
Number Forms 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1445
39.2%
1 365
 
9.9%
- 277
 
7.5%
7 270
 
7.3%
2 222
 
6.0%
0 220
 
6.0%
9 158
 
4.3%
3 158
 
4.3%
4 150
 
4.1%
5 134
 
3.6%
Other values (16) 291
 
7.9%
Hangul
ValueCountFrequency (%)
596
 
11.4%
340
 
6.5%
303
 
5.8%
298
 
5.7%
295
 
5.7%
294
 
5.6%
294
 
5.6%
294
 
5.6%
177
 
3.4%
176
 
3.4%
Other values (171) 2148
41.2%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%

도로명주소
Text

MISSING 

Distinct277
Distinct (%)96.5%
Missing7
Missing (%)2.4%
Memory size2.4 KiB
2024-05-11T15:53:16.833963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length37.278746
Min length23

Characters and Unicode

Total characters10699
Distinct characters225
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique268 ?
Unique (%)93.4%

Sample

1st row서울특별시 강서구 곰달래로 256 (화곡동)
2nd row서울특별시 강서구 방화대로33길 63 (방화동)
3rd row서울특별시 강서구 방화동로 1, 1층 (방화동)
4th row서울특별시 강서구 공항대로63길 41 (염창동)
5th row서울특별시 강서구 공항대로 649-7 (염창동)
ValueCountFrequency (%)
서울특별시 287
 
14.6%
강서구 287
 
14.6%
마곡동 107
 
5.5%
공항대로 64
 
3.3%
양천로 32
 
1.6%
등촌동 31
 
1.6%
화곡동 28
 
1.4%
방화동 26
 
1.3%
마곡중앙6로 24
 
1.2%
화곡로 23
 
1.2%
Other values (556) 1054
53.7%
2024-05-11T15:53:17.483767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1714
 
16.0%
621
 
5.8%
1 411
 
3.8%
351
 
3.3%
329
 
3.1%
, 315
 
2.9%
298
 
2.8%
291
 
2.7%
( 290
 
2.7%
) 290
 
2.7%
Other values (215) 5789
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6128
57.3%
Decimal Number 1826
 
17.1%
Space Separator 1714
 
16.0%
Other Punctuation 316
 
3.0%
Open Punctuation 290
 
2.7%
Close Punctuation 290
 
2.7%
Uppercase Letter 63
 
0.6%
Dash Punctuation 62
 
0.6%
Letter Number 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
621
 
10.1%
351
 
5.7%
329
 
5.4%
298
 
4.9%
291
 
4.7%
288
 
4.7%
287
 
4.7%
287
 
4.7%
287
 
4.7%
264
 
4.3%
Other values (187) 2825
46.1%
Decimal Number
ValueCountFrequency (%)
1 411
22.5%
2 244
13.4%
0 217
11.9%
6 177
9.7%
5 161
 
8.8%
3 158
 
8.7%
4 149
 
8.2%
7 114
 
6.2%
9 99
 
5.4%
8 96
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 20
31.7%
B 20
31.7%
C 7
 
11.1%
I 4
 
6.3%
W 3
 
4.8%
D 3
 
4.8%
V 2
 
3.2%
P 2
 
3.2%
E 1
 
1.6%
F 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 315
99.7%
/ 1
 
0.3%
Letter Number
ValueCountFrequency (%)
6
60.0%
4
40.0%
Space Separator
ValueCountFrequency (%)
1714
100.0%
Open Punctuation
ValueCountFrequency (%)
( 290
100.0%
Close Punctuation
ValueCountFrequency (%)
) 290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6128
57.3%
Common 4498
42.0%
Latin 73
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
621
 
10.1%
351
 
5.7%
329
 
5.4%
298
 
4.9%
291
 
4.7%
288
 
4.7%
287
 
4.7%
287
 
4.7%
287
 
4.7%
264
 
4.3%
Other values (187) 2825
46.1%
Common
ValueCountFrequency (%)
1714
38.1%
1 411
 
9.1%
, 315
 
7.0%
( 290
 
6.4%
) 290
 
6.4%
2 244
 
5.4%
0 217
 
4.8%
6 177
 
3.9%
5 161
 
3.6%
3 158
 
3.5%
Other values (6) 521
 
11.6%
Latin
ValueCountFrequency (%)
A 20
27.4%
B 20
27.4%
C 7
 
9.6%
6
 
8.2%
I 4
 
5.5%
4
 
5.5%
W 3
 
4.1%
D 3
 
4.1%
V 2
 
2.7%
P 2
 
2.7%
Other values (2) 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6128
57.3%
ASCII 4561
42.6%
Number Forms 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1714
37.6%
1 411
 
9.0%
, 315
 
6.9%
( 290
 
6.4%
) 290
 
6.4%
2 244
 
5.3%
0 217
 
4.8%
6 177
 
3.9%
5 161
 
3.5%
3 158
 
3.5%
Other values (16) 584
 
12.8%
Hangul
ValueCountFrequency (%)
621
 
10.1%
351
 
5.7%
329
 
5.4%
298
 
4.9%
291
 
4.7%
288
 
4.7%
287
 
4.7%
287
 
4.7%
287
 
4.7%
264
 
4.3%
Other values (187) 2825
46.1%
Number Forms
ValueCountFrequency (%)
6
60.0%
4
40.0%

도로명우편번호
Text

MISSING 

Distinct87
Distinct (%)37.8%
Missing64
Missing (%)21.8%
Memory size2.4 KiB
2024-05-11T15:53:17.940394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1
Min length5

Characters and Unicode

Total characters1173
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

Unique57 ?
Unique (%)24.8%

Sample

1st row07620
2nd row07802
3rd row07777
4th row07802
5th row157815
ValueCountFrequency (%)
07802 23
 
10.0%
07788 21
 
9.1%
07803 16
 
7.0%
07631 14
 
6.1%
07806 12
 
5.2%
07807 9
 
3.9%
07547 7
 
3.0%
07801 7
 
3.0%
07635 6
 
2.6%
07532 6
 
2.6%
Other values (77) 109
47.4%
2024-05-11T15:53:18.527268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 311
26.5%
0 309
26.3%
8 129
11.0%
5 111
 
9.5%
6 72
 
6.1%
2 68
 
5.8%
1 68
 
5.8%
3 62
 
5.3%
4 24
 
2.0%
9 18
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1172
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 311
26.5%
0 309
26.4%
8 129
11.0%
5 111
 
9.5%
6 72
 
6.1%
2 68
 
5.8%
1 68
 
5.8%
3 62
 
5.3%
4 24
 
2.0%
9 18
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 311
26.5%
0 309
26.3%
8 129
11.0%
5 111
 
9.5%
6 72
 
6.1%
2 68
 
5.8%
1 68
 
5.8%
3 62
 
5.3%
4 24
 
2.0%
9 18
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 311
26.5%
0 309
26.3%
8 129
11.0%
5 111
 
9.5%
6 72
 
6.1%
2 68
 
5.8%
1 68
 
5.8%
3 62
 
5.3%
4 24
 
2.0%
9 18
 
1.5%
Distinct291
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-05-11T15:53:18.941469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.1156463
Min length3

Characters and Unicode

Total characters2386
Distinct characters317
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

Unique288 ?
Unique (%)98.0%

Sample

1st row(주)기독교놀이문화
2nd row케니종합물류(주)
3rd row공항국제관광(주)
4th row(주)동그라미항공여행사
5th row주)팩에어시스템
ValueCountFrequency (%)
주식회사 35
 
9.7%
투어 5
 
1.4%
여행사 3
 
0.8%
3
 
0.8%
주)투어라인 2
 
0.6%
제이투어 2
 
0.6%
travel 2
 
0.6%
주)트래블스토어 2
 
0.6%
브이아이피관광여행사 2
 
0.6%
발리투어 1
 
0.3%
Other values (305) 305
84.3%
2024-05-11T15:53:19.529841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
197
 
8.3%
) 161
 
6.7%
( 158
 
6.6%
95
 
4.0%
90
 
3.8%
87
 
3.6%
79
 
3.3%
72
 
3.0%
69
 
2.9%
68
 
2.8%
Other values (307) 1310
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1925
80.7%
Close Punctuation 161
 
6.7%
Open Punctuation 158
 
6.6%
Space Separator 68
 
2.8%
Uppercase Letter 58
 
2.4%
Lowercase Letter 12
 
0.5%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
197
 
10.2%
95
 
4.9%
90
 
4.7%
87
 
4.5%
79
 
4.1%
72
 
3.7%
69
 
3.6%
52
 
2.7%
41
 
2.1%
38
 
2.0%
Other values (273) 1105
57.4%
Uppercase Letter
ValueCountFrequency (%)
A 6
 
10.3%
T 6
 
10.3%
R 4
 
6.9%
S 4
 
6.9%
L 4
 
6.9%
J 4
 
6.9%
I 3
 
5.2%
N 3
 
5.2%
D 3
 
5.2%
M 3
 
5.2%
Other values (9) 18
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
t 2
16.7%
p 2
16.7%
u 1
8.3%
s 1
8.3%
o 1
8.3%
n 1
8.3%
r 1
8.3%
i 1
8.3%
Other Punctuation
ValueCountFrequency (%)
& 2
50.0%
, 1
25.0%
. 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1925
80.7%
Common 391
 
16.4%
Latin 70
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
197
 
10.2%
95
 
4.9%
90
 
4.7%
87
 
4.5%
79
 
4.1%
72
 
3.7%
69
 
3.6%
52
 
2.7%
41
 
2.1%
38
 
2.0%
Other values (273) 1105
57.4%
Latin
ValueCountFrequency (%)
A 6
 
8.6%
T 6
 
8.6%
R 4
 
5.7%
S 4
 
5.7%
L 4
 
5.7%
J 4
 
5.7%
I 3
 
4.3%
N 3
 
4.3%
D 3
 
4.3%
M 3
 
4.3%
Other values (18) 30
42.9%
Common
ValueCountFrequency (%)
) 161
41.2%
( 158
40.4%
68
17.4%
& 2
 
0.5%
, 1
 
0.3%
. 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1925
80.7%
ASCII 461
 
19.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
197
 
10.2%
95
 
4.9%
90
 
4.7%
87
 
4.5%
79
 
4.1%
72
 
3.7%
69
 
3.6%
52
 
2.7%
41
 
2.1%
38
 
2.0%
Other values (273) 1105
57.4%
ASCII
ValueCountFrequency (%)
) 161
34.9%
( 158
34.3%
68
14.8%
A 6
 
1.3%
T 6
 
1.3%
R 4
 
0.9%
S 4
 
0.9%
L 4
 
0.9%
J 4
 
0.9%
I 3
 
0.7%
Other values (24) 43
 
9.3%
Distinct291
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2003-04-18 11:50:44
Maximum2024-05-07 09:05:22
2024-05-11T15:53:19.711716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:53:19.902350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
U
168 
I
126 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 168
57.1%
I 126
42.9%

Length

2024-05-11T15:53:20.145775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:20.296263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 168
57.1%
i 126
42.9%
Distinct145
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:53:20.452892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:53:20.651502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct175
Distinct (%)67.6%
Missing35
Missing (%)11.9%
Infinite0
Infinite (%)0.0%
Mean185514.96
Minimum182524.82
Maximum189058.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:20.843591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182524.82
5-th percentile182936.44
Q1184636.53
median185371.3
Q3186514.13
95-th percentile187999.33
Maximum189058.63
Range6533.8041
Interquartile range (IQR)1877.6005

Descriptive statistics

Standard deviation1593.416
Coefficient of variation (CV)0.0085891509
Kurtosis-0.70517249
Mean185514.96
Median Absolute Deviation (MAD)1010.7677
Skewness0.109493
Sum48048376
Variance2538974.6
MonotonicityNot monotonic
2024-05-11T15:53:21.070984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187952.560027898 9
 
3.1%
184636.53344075 6
 
2.0%
185127.285385035 6
 
2.0%
184655.264279055 5
 
1.7%
187125.882786229 4
 
1.4%
185365.0 4
 
1.4%
185292.76664368 4
 
1.4%
186324.832095725 3
 
1.0%
185032.421148111 3
 
1.0%
186480.475282452 3
 
1.0%
Other values (165) 212
72.1%
(Missing) 35
 
11.9%
ValueCountFrequency (%)
182524.823835629 1
0.3%
182794.441839414 2
0.7%
182859.059692916 1
0.3%
182876.367858149 2
0.7%
182879.610355768 1
0.3%
182895.668483962 2
0.7%
182914.598086861 1
0.3%
182914.770762913 2
0.7%
182929.561795629 1
0.3%
182937.208431243 1
0.3%
ValueCountFrequency (%)
189058.62791549 1
0.3%
189029.460526202 1
0.3%
188954.187154407 1
0.3%
188953.293071222 1
0.3%
188843.428976776 1
0.3%
188791.250134373 1
0.3%
188646.810503675 1
0.3%
188518.776948398 1
0.3%
188245.686899069 2
0.7%
188182.789386066 1
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct175
Distinct (%)67.6%
Missing35
Missing (%)11.9%
Infinite0
Infinite (%)0.0%
Mean450649.1
Minimum447473.84
Maximum452915.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:21.278206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447473.84
5-th percentile448665.28
Q1450207.06
median450792.7
Q3451129.04
95-th percentile452293.65
Maximum452915.96
Range5442.1189
Interquartile range (IQR)921.9815

Descriptive statistics

Standard deviation1078.7695
Coefficient of variation (CV)0.0023938127
Kurtosis0.7718515
Mean450649.1
Median Absolute Deviation (MAD)455.10426
Skewness-0.69620103
Sum1.1671812 × 108
Variance1163743.7
MonotonicityNot monotonic
2024-05-11T15:53:21.530213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450562.020225978 9
 
3.1%
450143.872075084 6
 
2.0%
450939.221091497 6
 
2.0%
451864.298152252 5
 
1.7%
451038.464052645 4
 
1.4%
450789.0 4
 
1.4%
450863.026923918 4
 
1.4%
450838.384642533 3
 
1.0%
450836.071292455 3
 
1.0%
449665.415630585 3
 
1.0%
Other values (165) 212
72.1%
(Missing) 35
 
11.9%
ValueCountFrequency (%)
447473.844844863 1
0.3%
447532.962112156 1
0.3%
447558.097935801 1
0.3%
447634.784556281 1
0.3%
447752.517105171 1
0.3%
447812.923942238 1
0.3%
447816.998701898 1
0.3%
447957.117594405 1
0.3%
448184.110703559 1
0.3%
448299.045454744 1
0.3%
ValueCountFrequency (%)
452915.963722565 1
0.3%
452885.190156723 2
0.7%
452801.707821111 1
0.3%
452796.68880421 2
0.7%
452713.505241493 1
0.3%
452526.699106933 1
0.3%
452504.78048233 1
0.3%
452362.041759725 1
0.3%
452343.174444214 1
0.3%
452295.430545244 2
0.7%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
국내외여행업
167 
<NA>
127 

Length

Max length6
Median length6
Mean length5.1360544
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 167
56.8%
<NA> 127
43.2%

Length

2024-05-11T15:53:21.742824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:21.864398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 167
56.8%
na 127
43.2%
Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
220 
관광사업
74 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 220
74.8%
관광사업 74
 
25.2%

Length

2024-05-11T15:53:21.981559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:22.107513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 220
74.8%
관광사업 74
 
25.2%

지역구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
274 
상업지역
 
7
일반주거지역
 
5
준주거지역
 
4
주거지역
 
2

Length

Max length6
Median length4
Mean length4.0612245
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> 274
93.2%
상업지역 7
 
2.4%
일반주거지역 5
 
1.7%
준주거지역 4
 
1.4%
주거지역 2
 
0.7%
일반상업지역 2
 
0.7%

Length

2024-05-11T15:53:22.289603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:22.500001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 274
93.2%
상업지역 7
 
2.4%
일반주거지역 5
 
1.7%
준주거지역 4
 
1.4%
주거지역 2
 
0.7%
일반상업지역 2
 
0.7%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)33.3%
Missing267
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean3.4444444
Minimum0
Maximum21
Zeros9
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:22.622396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile14.3
Maximum21
Range21
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.9717149
Coefficient of variation (CV)1.4434011
Kurtosis6.9724545
Mean3.4444444
Median Absolute Deviation (MAD)2
Skewness2.5711676
Sum93
Variance24.717949
MonotonicityNot monotonic
2024-05-11T15:53:22.744931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 9
 
3.1%
2 5
 
1.7%
4 5
 
1.7%
3 2
 
0.7%
5 2
 
0.7%
8 1
 
0.3%
1 1
 
0.3%
21 1
 
0.3%
17 1
 
0.3%
(Missing) 267
90.8%
ValueCountFrequency (%)
0 9
3.1%
1 1
 
0.3%
2 5
1.7%
3 2
 
0.7%
4 5
1.7%
5 2
 
0.7%
8 1
 
0.3%
17 1
 
0.3%
21 1
 
0.3%
ValueCountFrequency (%)
21 1
 
0.3%
17 1
 
0.3%
8 1
 
0.3%
5 2
 
0.7%
4 5
1.7%
3 2
 
0.7%
2 5
1.7%
1 1
 
0.3%
0 9
3.1%

주변환경명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
272 
기타
 
13
주택가주변
 
5
아파트지역
 
2
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.962585
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> 272
92.5%
기타 13
 
4.4%
주택가주변 5
 
1.7%
아파트지역 2
 
0.7%
유흥업소밀집지역 2
 
0.7%

Length

2024-05-11T15:53:22.896337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:23.059808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 272
92.5%
기타 13
 
4.4%
주택가주변 5
 
1.7%
아파트지역 2
 
0.7%
유흥업소밀집지역 2
 
0.7%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

보험기관명
Categorical

IMBALANCE 

Distinct22
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
183 
서울보증보험
54 
한국관광협회중앙회 여행공제회
 
16
서울보증보험(3천만원)
 
7
한국관광협회 여행공제회
 
4
Other values (17)
30 

Length

Max length20
Median length4
Mean length6.0578231
Min length4

Unique

Unique12 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 183
62.2%
서울보증보험 54
 
18.4%
한국관광협회중앙회 여행공제회 16
 
5.4%
서울보증보험(3천만원) 7
 
2.4%
한국관광협회 여행공제회 4
 
1.4%
한국관광협회중앙회 4
 
1.4%
서울보증보험주식회사 4
 
1.4%
서울보증보험(주) 4
 
1.4%
한국관광협회 3
 
1.0%
서울보증보험(30,000,000) 3
 
1.0%
Other values (12) 12
 
4.1%

Length

2024-05-11T15:53:23.203328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 183
58.1%
서울보증보험 55
 
17.5%
한국관광협회중앙회 20
 
6.3%
여행공제회 20
 
6.3%
서울보증보험(3천만원 7
 
2.2%
한국관광협회 7
 
2.2%
서울보증보험주식회사 4
 
1.3%
서울보증보험(주 4
 
1.3%
서울보증보험(30,000,000 3
 
1.0%
서울보증보험(100,000,000 1
 
0.3%
Other values (11) 11
 
3.5%

건물용도명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
267 
사무실
 
14
근린생활시설
 
9
기타
 
2
유통시설
 
1

Length

Max length6
Median length4
Mean length3.9965986
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 267
90.8%
사무실 14
 
4.8%
근린생활시설 9
 
3.1%
기타 2
 
0.7%
유통시설 1
 
0.3%
아파트 1
 
0.3%

Length

2024-05-11T15:53:23.383345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:23.529435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 267
90.8%
사무실 14
 
4.8%
근린생활시설 9
 
3.1%
기타 2
 
0.7%
유통시설 1
 
0.3%
아파트 1
 
0.3%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)30.8%
Missing268
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean2.9230769
Minimum0
Maximum17
Zeros9
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:23.650975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile12.75
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.2040274
Coefficient of variation (CV)1.4382199
Kurtosis6.58748
Mean2.9230769
Median Absolute Deviation (MAD)2
Skewness2.5357864
Sum76
Variance17.673846
MonotonicityNot monotonic
2024-05-11T15:53:23.780343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 9
 
3.1%
2 5
 
1.7%
3 5
 
1.7%
4 3
 
1.0%
6 1
 
0.3%
1 1
 
0.3%
15 1
 
0.3%
17 1
 
0.3%
(Missing) 268
91.2%
ValueCountFrequency (%)
0 9
3.1%
1 1
 
0.3%
2 5
1.7%
3 5
1.7%
4 3
 
1.0%
6 1
 
0.3%
15 1
 
0.3%
17 1
 
0.3%
ValueCountFrequency (%)
17 1
 
0.3%
15 1
 
0.3%
6 1
 
0.3%
4 3
 
1.0%
3 5
1.7%
2 5
1.7%
1 1
 
0.3%
0 9
3.1%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
274 
0
 
9
1
 
7
2
 
2
12
 
1

Length

Max length4
Median length4
Mean length3.7993197
Min length1

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 274
93.2%
0 9
 
3.1%
1 7
 
2.4%
2 2
 
0.7%
12 1
 
0.3%
6 1
 
0.3%

Length

2024-05-11T15:53:23.958217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:24.101862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 274
93.2%
0 9
 
3.1%
1 7
 
2.4%
2 2
 
0.7%
12 1
 
0.3%
6 1
 
0.3%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:24.249736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:24.372018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:24.507436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:24.664931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

영문상호명
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing290
Missing (%)98.6%
Memory size2.4 KiB
2024-05-11T15:53:24.827883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21.5
Mean length21.25
Min length15

Characters and Unicode

Total characters85
Distinct characters32
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

Unique4 ?
Unique (%)100.0%

Sample

1st rowTHE WAY KOREA Co.Ltd.,
2nd rowP.G.S Korea Co., Ltd.
3rd rowSpecial Travel Service Inc.
4th rowSTAR TOUR & AIR
ValueCountFrequency (%)
korea 2
 
12.5%
the 1
 
6.2%
way 1
 
6.2%
co.ltd 1
 
6.2%
p.g.s 1
 
6.2%
co 1
 
6.2%
ltd 1
 
6.2%
special 1
 
6.2%
travel 1
 
6.2%
service 1
 
6.2%
Other values (5) 5
31.2%
2024-05-11T15:53:25.143917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
14.1%
. 7
 
8.2%
e 5
 
5.9%
T 4
 
4.7%
S 4
 
4.7%
A 4
 
4.7%
R 4
 
4.7%
c 3
 
3.5%
a 3
 
3.5%
o 3
 
3.5%
Other values (22) 36
42.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 34
40.0%
Lowercase Letter 29
34.1%
Space Separator 12
 
14.1%
Other Punctuation 10
 
11.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 4
11.8%
S 4
11.8%
A 4
11.8%
R 4
11.8%
I 2
 
5.9%
L 2
 
5.9%
C 2
 
5.9%
O 2
 
5.9%
K 2
 
5.9%
E 2
 
5.9%
Other values (6) 6
17.6%
Lowercase Letter
ValueCountFrequency (%)
e 5
17.2%
c 3
10.3%
a 3
10.3%
o 3
10.3%
r 3
10.3%
v 2
 
6.9%
l 2
 
6.9%
i 2
 
6.9%
d 2
 
6.9%
t 2
 
6.9%
Other values (2) 2
 
6.9%
Other Punctuation
ValueCountFrequency (%)
. 7
70.0%
, 2
 
20.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
74.1%
Common 22
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
 
7.9%
T 4
 
6.3%
S 4
 
6.3%
A 4
 
6.3%
R 4
 
6.3%
c 3
 
4.8%
a 3
 
4.8%
o 3
 
4.8%
r 3
 
4.8%
I 2
 
3.2%
Other values (18) 28
44.4%
Common
ValueCountFrequency (%)
12
54.5%
. 7
31.8%
, 2
 
9.1%
& 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
 
14.1%
. 7
 
8.2%
e 5
 
5.9%
T 4
 
4.7%
S 4
 
4.7%
A 4
 
4.7%
R 4
 
4.7%
c 3
 
3.5%
a 3
 
3.5%
o 3
 
3.5%
Other values (22) 36
42.4%

영문상호주소
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing290
Missing (%)98.6%
Memory size2.4 KiB
2024-05-11T15:53:25.590161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters96
Distinct characters24
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 rowOverseas travel business
2nd rowOverseas travel business
3rd rowOVERSEAS TRAVEL BUSINESS
4th rowOVERSEAS TRAVEL BUSINESS
ValueCountFrequency (%)
overseas 4
33.3%
travel 4
33.3%
business 4
33.3%
2024-05-11T15:53:25.964453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 10
 
10.4%
s 10
 
10.4%
e 8
 
8.3%
E 8
 
8.3%
8
 
8.3%
v 4
 
4.2%
R 4
 
4.2%
V 4
 
4.2%
O 4
 
4.2%
A 4
 
4.2%
Other values (14) 32
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 46
47.9%
Lowercase Letter 42
43.8%
Space Separator 8
 
8.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 10
21.7%
E 8
17.4%
R 4
 
8.7%
V 4
 
8.7%
O 4
 
8.7%
A 4
 
8.7%
B 2
 
4.3%
L 2
 
4.3%
T 2
 
4.3%
I 2
 
4.3%
Other values (2) 4
 
8.7%
Lowercase Letter
ValueCountFrequency (%)
s 10
23.8%
e 8
19.0%
v 4
 
9.5%
a 4
 
9.5%
r 4
 
9.5%
n 2
 
4.8%
i 2
 
4.8%
u 2
 
4.8%
b 2
 
4.8%
l 2
 
4.8%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 88
91.7%
Common 8
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 10
 
11.4%
s 10
 
11.4%
e 8
 
9.1%
E 8
 
9.1%
v 4
 
4.5%
R 4
 
4.5%
V 4
 
4.5%
O 4
 
4.5%
A 4
 
4.5%
a 4
 
4.5%
Other values (13) 28
31.8%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 10
 
10.4%
s 10
 
10.4%
e 8
 
8.3%
E 8
 
8.3%
8
 
8.3%
v 4
 
4.2%
R 4
 
4.2%
V 4
 
4.2%
O 4
 
4.2%
A 4
 
4.2%
Other values (14) 32
33.3%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:26.150526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:26.256127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:26.377949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:26.497897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:26.658561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:26.830257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:27.008288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:27.127472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:27.248917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:27.380469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)79.5%
Missing250
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean48.935682
Minimum0
Maximum190.8
Zeros9
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:27.558728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.49
median34
Q375.3225
95-th percentile137.19
Maximum190.8
Range190.8
Interquartile range (IQR)67.8325

Descriptive statistics

Standard deviation48.310098
Coefficient of variation (CV)0.98721621
Kurtosis0.73989337
Mean48.935682
Median Absolute Deviation (MAD)31
Skewness1.1311175
Sum2153.17
Variance2333.8656
MonotonicityNot monotonic
2024-05-11T15:53:27.765119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 9
 
3.1%
33.0 2
 
0.7%
8.0 1
 
0.3%
74.7 1
 
0.3%
30.32 1
 
0.3%
5.96 1
 
0.3%
26.4 1
 
0.3%
106.86 1
 
0.3%
35.49 1
 
0.3%
19.0 1
 
0.3%
Other values (25) 25
 
8.5%
(Missing) 250
85.0%
ValueCountFrequency (%)
0.0 9
3.1%
4.5 1
 
0.3%
5.96 1
 
0.3%
8.0 1
 
0.3%
16.53 1
 
0.3%
19.0 1
 
0.3%
21.45 1
 
0.3%
26.4 1
 
0.3%
28.45 1
 
0.3%
29.7 1
 
0.3%
ValueCountFrequency (%)
190.8 1
0.3%
160.0 1
0.3%
138.0 1
0.3%
132.6 1
0.3%
126.28 1
0.3%
112.2 1
0.3%
106.86 1
0.3%
99.0 1
0.3%
82.5 1
0.3%
77.28 1
0.3%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
290 
0
 
4

Length

Max length4
Median length4
Mean length3.9591837
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 290
98.6%
0 4
 
1.4%

Length

2024-05-11T15:53:27.980644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:28.100003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 290
98.6%
0 4
 
1.4%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
293 
20161020
 
1

Length

Max length8
Median length4
Mean length4.0136054
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 293
99.7%
20161020 1
 
0.3%

Length

2024-05-11T15:53:28.215562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:28.324030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 293
99.7%
20161020 1
 
0.3%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
<NA>
293 
20171019
 
1

Length

Max length8
Median length4
Mean length4.0136054
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 293
99.7%
20171019 1
 
0.3%

Length

2024-05-11T15:53:28.441579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:53:28.562689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 293
99.7%
20171019 1
 
0.3%

자본금
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)20.4%
Missing152
Missing (%)51.7%
Infinite0
Infinite (%)0.0%
Mean95974723
Minimum30000000
Maximum4 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:28.667936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30000000
5-th percentile30000000
Q160000000
median1 × 108
Q31 × 108
95-th percentile1.985 × 108
Maximum4 × 108
Range3.7 × 108
Interquartile range (IQR)40000000

Descriptive statistics

Standard deviation57279109
Coefficient of variation (CV)0.59681452
Kurtosis7.194595
Mean95974723
Median Absolute Deviation (MAD)40000000
Skewness2.0692778
Sum1.3628411 × 1010
Variance3.2808963 × 1015
MonotonicityNot monotonic
2024-05-11T15:53:28.832075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
100000000 49
 
16.7%
60000000 20
 
6.8%
30000000 19
 
6.5%
150000000 16
 
5.4%
50000000 5
 
1.7%
200000000 4
 
1.4%
90000000 3
 
1.0%
300000000 2
 
0.7%
37000000 2
 
0.7%
80000000 2
 
0.7%
Other values (19) 20
 
6.8%
(Missing) 152
51.7%
ValueCountFrequency (%)
30000000 19
6.5%
30982950 1
 
0.3%
37000000 2
 
0.7%
50000000 5
 
1.7%
57000000 1
 
0.3%
60000000 20
6.8%
62000000 1
 
0.3%
65292858 1
 
0.3%
68400000 1
 
0.3%
70000000 1
 
0.3%
ValueCountFrequency (%)
400000000 1
 
0.3%
301000000 1
 
0.3%
300000000 2
 
0.7%
200000000 4
 
1.4%
170000000 2
 
0.7%
160000000 1
 
0.3%
150000000 16
5.4%
118949781 1
 
0.3%
118916020 1
 
0.3%
106483646 1
 
0.3%

보험시작일자
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)93.9%
Missing180
Missing (%)61.2%
Infinite0
Infinite (%)0.0%
Mean20152315
Minimum20020227
Maximum20220211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:29.055026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020227
5-th percentile20030267
Q120130230
median20170328
Q320190688
95-th percentile20200788
Maximum20220211
Range199984
Interquartile range (IQR)60457.5

Descriptive statistics

Standard deviation50441.026
Coefficient of variation (CV)0.0025029892
Kurtosis0.73650419
Mean20152315
Median Absolute Deviation (MAD)20583.5
Skewness-1.2218429
Sum2.2973639 × 109
Variance2.5442971 × 109
MonotonicityNot monotonic
2024-05-11T15:53:29.322810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151022 2
 
0.7%
20190910 2
 
0.7%
20161125 2
 
0.7%
20190904 2
 
0.7%
20191001 2
 
0.7%
20190730 2
 
0.7%
20170328 2
 
0.7%
20190614 1
 
0.3%
20190112 1
 
0.3%
20190712 1
 
0.3%
Other values (97) 97
33.0%
(Missing) 180
61.2%
ValueCountFrequency (%)
20020227 1
0.3%
20020430 1
0.3%
20021004 1
0.3%
20021116 1
0.3%
20021229 1
0.3%
20030201 1
0.3%
20030302 1
0.3%
20031126 1
0.3%
20050603 1
0.3%
20070412 1
0.3%
ValueCountFrequency (%)
20220211 1
0.3%
20211224 1
0.3%
20210730 1
0.3%
20210422 1
0.3%
20201101 1
0.3%
20200929 1
0.3%
20200712 1
0.3%
20200609 1
0.3%
20200516 1
0.3%
20200406 1
0.3%

보험종료일자
Real number (ℝ)

MISSING 

Distinct108
Distinct (%)94.7%
Missing180
Missing (%)61.2%
Infinite0
Infinite (%)0.0%
Mean20162320
Minimum20030227
Maximum20230211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:29.523940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030227
5-th percentile20040267
Q120133577
median20180327
Q320200686
95-th percentile20210788
Maximum20230211
Range199984
Interquartile range (IQR)67109.25

Descriptive statistics

Standard deviation50487.619
Coefficient of variation (CV)0.002504058
Kurtosis0.72393024
Mean20162320
Median Absolute Deviation (MAD)20584
Skewness-1.2202469
Sum2.2985045 × 109
Variance2.5489997 × 109
MonotonicityNot monotonic
2024-05-11T15:53:29.748428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180327 3
 
1.0%
20171124 2
 
0.7%
20200909 2
 
0.7%
20200930 2
 
0.7%
20200729 2
 
0.7%
20210515 1
 
0.3%
20170927 1
 
0.3%
20200111 1
 
0.3%
20200903 1
 
0.3%
20200711 1
 
0.3%
Other values (98) 98
33.3%
(Missing) 180
61.2%
ValueCountFrequency (%)
20030227 1
0.3%
20030429 1
0.3%
20031004 1
0.3%
20031116 1
0.3%
20031228 1
0.3%
20040201 1
0.3%
20040302 1
0.3%
20041126 1
0.3%
20060602 1
0.3%
20080411 1
0.3%
ValueCountFrequency (%)
20230211 1
0.3%
20221223 1
0.3%
20220729 1
0.3%
20220421 1
0.3%
20211031 1
0.3%
20210928 1
0.3%
20210712 1
0.3%
20210609 1
0.3%
20210515 1
0.3%
20210406 1
0.3%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing294
Missing (%)100.0%
Memory size2.7 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)68.2%
Missing250
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean48.931818
Minimum0
Maximum191
Zeros9
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-05-11T15:53:29.954656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.5
median34
Q375.5
95-th percentile137.25
Maximum191
Range191
Interquartile range (IQR)68

Descriptive statistics

Standard deviation48.335262
Coefficient of variation (CV)0.98780842
Kurtosis0.74436669
Mean48.931818
Median Absolute Deviation (MAD)31
Skewness1.133481
Sum2153
Variance2336.2976
MonotonicityNot monotonic
2024-05-11T15:53:30.127149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 9
 
3.1%
35 3
 
1.0%
60 2
 
0.7%
33 2
 
0.7%
30 2
 
0.7%
77 2
 
0.7%
17 1
 
0.3%
8 1
 
0.3%
5 1
 
0.3%
126 1
 
0.3%
Other values (20) 20
 
6.8%
(Missing) 250
85.0%
ValueCountFrequency (%)
0 9
3.1%
5 1
 
0.3%
6 1
 
0.3%
8 1
 
0.3%
17 1
 
0.3%
19 1
 
0.3%
21 1
 
0.3%
26 1
 
0.3%
28 1
 
0.3%
30 2
 
0.7%
ValueCountFrequency (%)
191 1
0.3%
160 1
0.3%
138 1
0.3%
133 1
0.3%
126 1
0.3%
112 1
0.3%
107 1
0.3%
99 1
0.3%
83 1
0.3%
77 2
0.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03150000CDFI226002199700000119970523<NA>3폐업3폐업20051229<NA><NA><NA>654-3045<NA>157897서울특별시 강서구 화곡동 796-16번지서울특별시 강서구 곰달래로 256 (화곡동)<NA>(주)기독교놀이문화2005-12-29 15:48:28I2018-08-31 23:59:59.0<NA>187685.860829447752.517105국내외여행업관광사업<NA><NA><NA><NA>한국관광협회 여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1000000002002022720030227<NA><NA>
13150000CDFI226002199700000219970930200709074취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>2664-7777<NA>157846서울특별시 강서구 방화동 249-293번지서울특별시 강서구 방화대로33길 63 (방화동)<NA>케니종합물류(주)2009-05-28 11:43:36I2018-08-31 23:59:59.0<NA>183418.22833451775.118175국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1000000002003020120040201<NA><NA>
23150000CDFI226002199700000319971024<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2665-2222<NA><NA>서울특별시 강서구 방화동 621-15번지 1층서울특별시 강서구 방화동로 1, 1층 (방화동)07620공항국제관광(주)2017-03-21 14:11:31I2018-08-31 23:59:59.0<NA>182952.663773451103.634438국내외여행업관광사업<NA><NA><NA><NA>한국관광협회중앙회 여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>35.04<NA><NA><NA><NA><NA><NA><NA><NA>1500000002017032720180327<NA>35
33150000CDFI226002199700000419971105<NA>3폐업3폐업20020215<NA><NA><NA><NA><NA>157863서울특별시 강서구 염창동 273-4번지서울특별시 강서구 공항대로63길 41 (염창동)<NA>(주)동그라미항공여행사2003-04-18 11:50:59I2018-08-31 23:59:59.0<NA>188116.099268449983.152403국내외여행업관광사업<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
43150000CDFI226002199700000519971121<NA>3폐업3폐업20000322<NA><NA><NA><NA><NA>157864서울특별시 강서구 염창동 283-11번지서울특별시 강서구 공항대로 649-7 (염창동)<NA>주)팩에어시스템2003-04-18 11:50:59I2018-08-31 23:59:59.0<NA>189058.627915449482.632252국내외여행업관광사업<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
53150000CDFI226002199700000619970611<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>3661-8200<NA>157862서울특별시 강서구 염창동 263-8번지서울특별시 강서구 양천로 720 (염창동)<NA>(주)비호여행사2006-04-18 11:20:47I2018-08-31 23:59:59.0<NA>188954.187154449657.109279국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63150000CDFI226002199800000519981224<NA>3폐업3폐업20000229<NA><NA><NA><NA><NA>157818서울특별시 강서구 공항동 693-9번지서울특별시 강서구 송정로 14 (공항동)<NA>(주)함지여행사2003-04-18 11:50:59I2018-08-31 23:59:59.0<NA>183348.230345450479.502677국내외여행업관광사업<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
73150000CDFI226002199900000519990927<NA>3폐업3폐업20010330<NA><NA><NA><NA><NA>157863서울특별시 강서구 염창동 267-190번지 대아빌딩 3층동<NA><NA>(주)네오비즈2006-04-18 11:26:17I2018-08-31 23:59:59.0<NA><NA><NA>국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83150000CDFI226002199900000619991124<NA>3폐업3폐업20010910<NA><NA><NA>666-3871<NA>157847서울특별시 강서구 방화동 273-5번지<NA><NA>(주)이오스로지스틱스2003-04-18 11:50:59I2018-08-31 23:59:59.0<NA><NA><NA>국내외여행업관광사업<NA>0<NA><NA><NA>근린생활시설00<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
93150000CDFI226002199900000819991230<NA>3폐업3폐업20040228<NA><NA><NA>707-0212<NA>157840서울특별시 강서구 등촌동 647-24번지 신아빌딩 2층 647동 24호서울특별시 강서구 공항대로59길 32, 647동 24호 (등촌동,신아빌딩 2층)<NA>(주)신아티엔에스2004-03-06 11:24:58I2018-08-31 23:59:59.0<NA>187899.961112450091.119183국내외여행업관광사업<NA><NA><NA><NA>서울보증보험(주)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1500000002002122920031228<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
2843150000CDFI22600220230000192014-10-13<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3444-7107<NA><NA>서울특별시 강서구 마곡동 759-3 보타닉파크타워Ⅰ서울특별시 강서구 마곡중앙로 161-17, 보타닉파크타워Ⅰ 1119호 (마곡동)07788케이투어 마케팅2023-11-22 17:20:49U2022-10-31 22:04:00.0<NA>184555.689189451767.833497<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2853150000CDFI22600220240000012022-02-07<NA>1영업/정상13영업중<NA><NA><NA><NA>02-6264-8288<NA><NA>서울특별시 강서구 공항동 34-35서울특별시 강서구 공항대로 38-9, 302호 (공항동)07623월드펫투어2024-01-08 17:36:23I2023-11-30 23:00:00.0<NA>183319.900586450973.131005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2863150000CDFI22600220240000022024-02-05<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 498-4 라테라스서울특별시 강서구 양천로 19, 라테라스 502호 (방화동)07516명품여행공장2024-02-05 13:29:21I2023-12-02 00:07:00.0<NA>182794.441839452295.430545<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2873150000CDFI22600220240000032024-02-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 648-6 비원오피스텔서울특별시 강서구 공항대로 525, 비원오피스텔 1501 가-112호 (등촌동)07563로나투어2024-03-18 16:01:46U2023-12-02 22:00:00.0<NA>187999.325556449920.361169<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2883150000CDFI22600220240000041999-02-10<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2273-7511<NA><NA>서울특별시 강서구 마곡동 784-11 마곡오드카운티1차서울특별시 강서구 강서로 429, 마곡오드카운티1차 227호 (마곡동)07792(주)세계여행클럽2024-02-28 10:26:12I2023-12-03 00:01:00.0<NA>185750.839364451301.705383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2893150000CDFI22600220240000052021-07-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 613-26서울특별시 강서구 개화동로27가길 1, 1층 (방화동)07620(주)우리투어2024-03-05 15:02:27I2023-12-03 00:07:00.0<NA>182879.610356451328.537479<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2903150000CDFI22600220240000062023-01-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 34-35서울특별시 강서구 공항대로 38-9, 302호 (공항동)07623(주) 남다른여행2024-03-13 09:39:32U2023-12-02 23:06:00.0<NA>183319.900586450973.131005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2913150000CDFI22600220240000072024-03-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 534-9 양서빌딩서울특별시 강서구 양천로 34, 양서빌딩 322호 (방화동)07602제이투어2024-03-11 15:45:50I2023-12-02 23:03:00.0<NA>182941.057623452258.458332<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2923150000CDFI22600220240000082024-03-20<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 34-35서울특별시 강서구 공항대로 38-9, 302호 (공항동)07623에스엠항공여행 주식회사2024-03-20 15:35:55I2023-12-02 22:02:00.0<NA>183319.900586450973.131005<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2933150000CDFI22600220240000092024-03-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 830-5 방화샤르망2오피스텔서울특별시 강서구 방화대로47가길 41, 방화샤르망2오피스텔 713호 (방화동)07511주식회사 오키투어2024-04-23 17:01:19U2023-12-03 22:05:00.0<NA>183466.507671452885.190157<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>