Overview

Dataset statistics

Number of variables60
Number of observations153
Missing cells3340
Missing cells (%)36.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.5 KiB
Average record size in memory518.9 B

Variable types

Categorical24
Text9
DateTime4
Numeric9
Unsupported14

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-17567/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영문상호주소 has constant value ""Constant
인허가취소일자 is highly imbalanced (76.1%)Imbalance
휴업시작일자 is highly imbalanced (94.3%)Imbalance
휴업종료일자 is highly imbalanced (94.3%)Imbalance
지역구분명 is highly imbalanced (83.0%)Imbalance
총층수 is highly imbalanced (85.7%)Imbalance
주변환경명 is highly imbalanced (83.3%)Imbalance
건물용도명 is highly imbalanced (77.1%)Imbalance
지하층수 is highly imbalanced (85.2%)Imbalance
객실수 is highly imbalanced (94.3%)Imbalance
건축연면적 is highly imbalanced (94.3%)Imbalance
선박총톤수 is highly imbalanced (94.3%)Imbalance
선박척수 is highly imbalanced (94.3%)Imbalance
무대면적 is highly imbalanced (94.3%)Imbalance
좌석수 is highly imbalanced (94.3%)Imbalance
회의실별동시수용인원 is highly imbalanced (94.3%)Imbalance
놀이시설수 is highly imbalanced (94.3%)Imbalance
폐업일자 has 69 (45.1%) missing valuesMissing
재개업일자 has 153 (100.0%) missing valuesMissing
전화번호 has 39 (25.5%) missing valuesMissing
소재지면적 has 153 (100.0%) missing valuesMissing
소재지우편번호 has 85 (55.6%) missing valuesMissing
도로명주소 has 3 (2.0%) missing valuesMissing
도로명우편번호 has 44 (28.8%) missing valuesMissing
업태구분명 has 153 (100.0%) missing valuesMissing
좌표정보(X) has 23 (15.0%) missing valuesMissing
좌표정보(Y) has 23 (15.0%) missing valuesMissing
제작취급품목내용 has 153 (100.0%) missing valuesMissing
지상층수 has 146 (95.4%) missing valuesMissing
영문상호명 has 151 (98.7%) missing valuesMissing
영문상호주소 has 151 (98.7%) missing valuesMissing
선박제원 has 153 (100.0%) missing valuesMissing
기념품종류 has 153 (100.0%) missing valuesMissing
시설면적 has 127 (83.0%) missing valuesMissing
놀이기구수내역 has 153 (100.0%) missing valuesMissing
방송시설유무 has 153 (100.0%) missing valuesMissing
발전시설유무 has 153 (100.0%) missing valuesMissing
의무실유무 has 153 (100.0%) missing valuesMissing
안내소유무 has 153 (100.0%) missing valuesMissing
기획여행보험시작일자 has 153 (100.0%) missing valuesMissing
기획여행보험종료일자 has 153 (100.0%) missing valuesMissing
자본금 has 50 (32.7%) missing valuesMissing
보험시작일자 has 80 (52.3%) missing valuesMissing
보험종료일자 has 80 (52.3%) missing valuesMissing
부대시설내역 has 153 (100.0%) missing valuesMissing
시설규모 has 127 (83.0%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
최종수정일자 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
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
지상층수 has 2 (1.3%) zerosZeros
시설면적 has 2 (1.3%) zerosZeros
시설규모 has 2 (1.3%) zerosZeros

Reproduction

Analysis started2024-04-29 19:21:21.601434
Analysis finished2024-04-29 19:21:22.631263
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3150000
153 

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 153
100.0%

Length

2024-04-30T04:21:22.694342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:22.770108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 153
100.0%

관리번호
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:21:22.920577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters3060
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

Unique153 ?
Unique (%)100.0%

Sample

1st rowCDFI2260011991000001
2nd rowCDFI2260011992000001
3rd rowCDFI2260011993000001
4th rowCDFI2260011994000001
5th rowCDFI2260011997000001
ValueCountFrequency (%)
cdfi2260011991000001 1
 
0.7%
cdfi2260012018000008 1
 
0.7%
cdfi2260012019000002 1
 
0.7%
cdfi2260012018000002 1
 
0.7%
cdfi2260012018000003 1
 
0.7%
cdfi2260012018000004 1
 
0.7%
cdfi2260012018000005 1
 
0.7%
cdfi2260012018000006 1
 
0.7%
cdfi2260012018000007 1
 
0.7%
cdfi2260012018000010 1
 
0.7%
Other values (143) 143
93.5%
2024-04-30T04:21:23.186494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1242
40.6%
2 509
16.6%
1 326
 
10.7%
6 175
 
5.7%
C 153
 
5.0%
D 153
 
5.0%
F 153
 
5.0%
I 153
 
5.0%
9 49
 
1.6%
4 34
 
1.1%
Other values (4) 113
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2448
80.0%
Uppercase Letter 612
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1242
50.7%
2 509
20.8%
1 326
 
13.3%
6 175
 
7.1%
9 49
 
2.0%
4 34
 
1.4%
5 29
 
1.2%
8 29
 
1.2%
7 28
 
1.1%
3 27
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 153
25.0%
D 153
25.0%
F 153
25.0%
I 153
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2448
80.0%
Latin 612
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1242
50.7%
2 509
20.8%
1 326
 
13.3%
6 175
 
7.1%
9 49
 
2.0%
4 34
 
1.4%
5 29
 
1.2%
8 29
 
1.2%
7 28
 
1.1%
3 27
 
1.1%
Latin
ValueCountFrequency (%)
C 153
25.0%
D 153
25.0%
F 153
25.0%
I 153
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1242
40.6%
2 509
16.6%
1 326
 
10.7%
6 175
 
5.7%
C 153
 
5.0%
D 153
 
5.0%
F 153
 
5.0%
I 153
 
5.0%
9 49
 
1.6%
4 34
 
1.1%
Other values (4) 113
 
3.7%

인허가일자
Date

Distinct151
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum1991-03-18 00:00:00
Maximum2024-01-03 00:00:00
2024-04-30T04:21:23.312485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:23.443296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
20070907
 
6

Length

Max length8
Median length4
Mean length4.1568627
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> 147
96.1%
20070907 6
 
3.9%

Length

2024-04-30T04:21:23.560991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:23.649614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
96.1%
20070907 6
 
3.9%

영업상태코드
Categorical

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
79 
1
59 
4
8 
5
 
6
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
3 79
51.6%
1 59
38.6%
4 8
 
5.2%
5 6
 
3.9%
2 1
 
0.7%

Length

2024-04-30T04:21:23.732052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:23.832677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 79
51.6%
1 59
38.6%
4 8
 
5.2%
5 6
 
3.9%
2 1
 
0.7%

영업상태명
Categorical

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
79 
영업/정상
59 
취소/말소/만료/정지/중지
8 
제외/삭제/전출
 
6
휴업
 
1

Length

Max length14
Median length2
Mean length4.0196078
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 79
51.6%
영업/정상 59
38.6%
취소/말소/만료/정지/중지 8
 
5.2%
제외/삭제/전출 6
 
3.9%
휴업 1
 
0.7%

Length

2024-04-30T04:21:23.939665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:24.033587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 79
51.6%
영업/정상 59
38.6%
취소/말소/만료/정지/중지 8
 
5.2%
제외/삭제/전출 6
 
3.9%
휴업 1
 
0.7%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.7712418
Minimum2
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:24.111862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q13
median3
Q313
95-th percentile21
Maximum31
Range29
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.1777221
Coefficient of variation (CV)0.8183245
Kurtosis2.0676865
Mean8.7712418
Median Absolute Deviation (MAD)0
Skewness1.3601169
Sum1342
Variance51.519694
MonotonicityNot monotonic
2024-04-30T04:21:24.185948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 79
51.6%
13 59
38.6%
31 6
 
3.9%
15 6
 
3.9%
30 2
 
1.3%
2 1
 
0.7%
ValueCountFrequency (%)
2 1
 
0.7%
3 79
51.6%
13 59
38.6%
15 6
 
3.9%
30 2
 
1.3%
31 6
 
3.9%
ValueCountFrequency (%)
31 6
 
3.9%
30 2
 
1.3%
15 6
 
3.9%
13 59
38.6%
3 79
51.6%
2 1
 
0.7%

상세영업상태명
Categorical

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
79 
영업중
59 
등록취소
 
6
전출
 
6
허가취소
 
2

Length

Max length4
Median length2
Mean length2.4901961
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 79
51.6%
영업중 59
38.6%
등록취소 6
 
3.9%
전출 6
 
3.9%
허가취소 2
 
1.3%
휴업 1
 
0.7%

Length

2024-04-30T04:21:24.287987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:24.383692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 79
51.6%
영업중 59
38.6%
등록취소 6
 
3.9%
전출 6
 
3.9%
허가취소 2
 
1.3%
휴업 1
 
0.7%

폐업일자
Date

MISSING 

Distinct79
Distinct (%)94.0%
Missing69
Missing (%)45.1%
Memory size1.3 KiB
Minimum2001-09-10 00:00:00
Maximum2024-04-03 00:00:00
2024-04-30T04:21:24.489235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:24.622867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
20191224
 
1

Length

Max length8
Median length4
Mean length4.0261438
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
20191224 1
 
0.7%

Length

2024-04-30T04:21:24.738109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:24.835944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
20191224 1
 
0.7%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
20251231
 
1

Length

Max length8
Median length4
Mean length4.0261438
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
20251231 1
 
0.7%

Length

2024-04-30T04:21:24.934781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:25.027349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
20251231 1
 
0.7%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

전화번호
Text

MISSING 

Distinct109
Distinct (%)95.6%
Missing39
Missing (%)25.5%
Memory size1.3 KiB
2024-04-30T04:21:25.233579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.754386
Min length8

Characters and Unicode

Total characters1226
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

Unique105 ?
Unique (%)92.1%

Sample

1st row2694-7262
2nd row02-2692-0083
3rd row2661-6200
4th row02-3663-1245
5th row654-3045
ValueCountFrequency (%)
3665-8733 3
 
2.6%
02 3
 
2.6%
2668-1999 2
 
1.7%
02-3663-1245 2
 
1.7%
02-312-9988 2
 
1.7%
02-3662-0522 1
 
0.9%
33944920 1
 
0.9%
02-3665-3650 1
 
0.9%
000226588883 1
 
0.9%
02-540-1208 1
 
0.9%
Other values (100) 100
85.5%
2024-04-30T04:21:25.601097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 200
16.3%
0 172
14.0%
- 171
13.9%
6 135
11.0%
5 93
7.6%
3 87
7.1%
8 81
6.6%
7 79
 
6.4%
9 69
 
5.6%
1 65
 
5.3%
Other values (3) 74
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1043
85.1%
Dash Punctuation 171
 
13.9%
Close Punctuation 6
 
0.5%
Space Separator 6
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 200
19.2%
0 172
16.5%
6 135
12.9%
5 93
8.9%
3 87
8.3%
8 81
7.8%
7 79
 
7.6%
9 69
 
6.6%
1 65
 
6.2%
4 62
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1226
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 200
16.3%
0 172
14.0%
- 171
13.9%
6 135
11.0%
5 93
7.6%
3 87
7.1%
8 81
6.6%
7 79
 
6.4%
9 69
 
5.6%
1 65
 
5.3%
Other values (3) 74
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 200
16.3%
0 172
14.0%
- 171
13.9%
6 135
11.0%
5 93
7.6%
3 87
7.1%
8 81
6.6%
7 79
 
6.4%
9 69
 
5.6%
1 65
 
5.3%
Other values (3) 74
 
6.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Text

MISSING 

Distinct44
Distinct (%)64.7%
Missing85
Missing (%)55.6%
Memory size1.3 KiB
2024-04-30T04:21:25.804467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0147059
Min length6

Characters and Unicode

Total characters409
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

Unique30 ?
Unique (%)44.1%

Sample

1st row157928
2nd row157846
3rd row157866
4th row157897
5th row157030
ValueCountFrequency (%)
157801 4
 
5.9%
157030 4
 
5.9%
157840 4
 
5.9%
157928 4
 
5.9%
157846 4
 
5.9%
157862 2
 
2.9%
157861 2
 
2.9%
157221 2
 
2.9%
157873 2
 
2.9%
157925 2
 
2.9%
Other values (34) 38
55.9%
2024-04-30T04:21:26.119423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 89
21.8%
5 80
19.6%
7 77
18.8%
8 51
12.5%
0 33
 
8.1%
2 22
 
5.4%
4 15
 
3.7%
9 15
 
3.7%
6 14
 
3.4%
3 12
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 89
21.8%
5 80
19.6%
7 77
18.9%
8 51
12.5%
0 33
 
8.1%
2 22
 
5.4%
4 15
 
3.7%
9 15
 
3.7%
6 14
 
3.4%
3 12
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 409
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 89
21.8%
5 80
19.6%
7 77
18.8%
8 51
12.5%
0 33
 
8.1%
2 22
 
5.4%
4 15
 
3.7%
9 15
 
3.7%
6 14
 
3.4%
3 12
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 409
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 89
21.8%
5 80
19.6%
7 77
18.8%
8 51
12.5%
0 33
 
8.1%
2 22
 
5.4%
4 15
 
3.7%
9 15
 
3.7%
6 14
 
3.4%
3 12
 
2.9%

지번주소
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:21:26.365776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length30.620915
Min length19

Characters and Unicode

Total characters4685
Distinct characters183
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

Unique153 ?
Unique (%)100.0%

Sample

1st row서울특별시 강서구 화곡동 1117-18번지
2nd row서울특별시 강서구 내발산동 681-15번지
3rd row서울특별시 강서구 방화동 247-110번지
4th row서울특별시 강서구 화곡동 24-571번지 천일빌딩 201호
5th row서울특별시 강서구 화곡동 796-16번지
ValueCountFrequency (%)
서울특별시 153
 
17.6%
강서구 153
 
17.6%
마곡동 50
 
5.8%
화곡동 28
 
3.2%
방화동 21
 
2.4%
등촌동 16
 
1.8%
가양동 16
 
1.8%
염창동 10
 
1.2%
b동 7
 
0.8%
공항동 7
 
0.8%
Other values (325) 407
46.9%
2024-04-30T04:21:26.727615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
774
 
16.5%
서 306
 
6.5%
1 217
 
4.6%
동 180
 
3.8%
시 155
 
3.3%
울 155
 
3.3%
별 154
 
3.3%
특 153
 
3.3%
강 153
 
3.3%
구 153
 
3.3%
Other values (173) 2285
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2696
57.5%
Decimal Number 1043
 
22.3%
Space Separator 774
 
16.5%
Dash Punctuation 140
 
3.0%
Uppercase Letter 22
 
0.5%
Letter Number 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 306
 
11.4%
동 180
 
6.7%
시 155
 
5.7%
울 155
 
5.7%
별 154
 
5.7%
특 153
 
5.7%
강 153
 
5.7%
구 153
 
5.7%
지 104
 
3.9%
호 99
 
3.7%
Other values (148) 1084
40.2%
Decimal Number
ValueCountFrequency (%)
1 217
20.8%
7 131
12.6%
2 129
12.4%
0 121
11.6%
9 91
8.7%
4 83
 
8.0%
5 75
 
7.2%
3 74
 
7.1%
8 66
 
6.3%
6 56
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 10
45.5%
A 6
27.3%
D 1
 
4.5%
C 1
 
4.5%
W 1
 
4.5%
V 1
 
4.5%
I 1
 
4.5%
P 1
 
4.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅰ 3
42.9%
Space Separator
ValueCountFrequency (%)
774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2696
57.5%
Common 1960
41.8%
Latin 29
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 306
 
11.4%
동 180
 
6.7%
시 155
 
5.7%
울 155
 
5.7%
별 154
 
5.7%
특 153
 
5.7%
강 153
 
5.7%
구 153
 
5.7%
지 104
 
3.9%
호 99
 
3.7%
Other values (148) 1084
40.2%
Common
ValueCountFrequency (%)
774
39.5%
1 217
 
11.1%
- 140
 
7.1%
7 131
 
6.7%
2 129
 
6.6%
0 121
 
6.2%
9 91
 
4.6%
4 83
 
4.2%
5 75
 
3.8%
3 74
 
3.8%
Other values (5) 125
 
6.4%
Latin
ValueCountFrequency (%)
B 10
34.5%
A 6
20.7%
Ⅱ 4
 
13.8%
Ⅰ 3
 
10.3%
D 1
 
3.4%
C 1
 
3.4%
W 1
 
3.4%
V 1
 
3.4%
I 1
 
3.4%
P 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2696
57.5%
ASCII 1982
42.3%
Number Forms 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
774
39.1%
1 217
 
10.9%
- 140
 
7.1%
7 131
 
6.6%
2 129
 
6.5%
0 121
 
6.1%
9 91
 
4.6%
4 83
 
4.2%
5 75
 
3.8%
3 74
 
3.7%
Other values (13) 147
 
7.4%
Hangul
ValueCountFrequency (%)
서 306
 
11.4%
동 180
 
6.7%
시 155
 
5.7%
울 155
 
5.7%
별 154
 
5.7%
특 153
 
5.7%
강 153
 
5.7%
구 153
 
5.7%
지 104
 
3.9%
호 99
 
3.7%
Other values (148) 1084
40.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅰ 3
42.9%

도로명주소
Text

MISSING 

Distinct148
Distinct (%)98.7%
Missing3
Missing (%)2.0%
Memory size1.3 KiB
2024-04-30T04:21:27.006111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length36.12
Min length23

Characters and Unicode

Total characters5418
Distinct characters189
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

Unique146 ?
Unique (%)97.3%

Sample

1st row서울특별시 강서구 화곡로 326 (화곡동)
2nd row서울특별시 강서구 강서로47길 40, 1층 (내발산동)
3rd row서울특별시 강서구 초원로 75 (방화동)
4th row서울특별시 강서구 화곡로 266, 201호 (화곡동, 천일빌딩)
5th row서울특별시 강서구 곰달래로 256 (화곡동)
ValueCountFrequency (%)
서울특별시 150
 
15.0%
강서구 150
 
15.0%
마곡동 49
 
4.9%
공항대로 29
 
2.9%
양천로 20
 
2.0%
화곡동 18
 
1.8%
방화동 16
 
1.6%
가양동 14
 
1.4%
마곡중앙6로 12
 
1.2%
등촌동 11
 
1.1%
Other values (351) 530
53.1%
2024-04-30T04:21:27.500573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
876
 
16.2%
서 316
 
5.8%
1 190
 
3.5%
동 182
 
3.4%
, 173
 
3.2%
강 164
 
3.0%
로 158
 
2.9%
시 153
 
2.8%
울 152
 
2.8%
별 151
 
2.8%
Other values (179) 2903
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3105
57.3%
Decimal Number 896
 
16.5%
Space Separator 876
 
16.2%
Other Punctuation 173
 
3.2%
Open Punctuation 150
 
2.8%
Close Punctuation 150
 
2.8%
Uppercase Letter 35
 
0.6%
Dash Punctuation 26
 
0.5%
Letter Number 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 316
 
10.2%
동 182
 
5.9%
강 164
 
5.3%
로 158
 
5.1%
시 153
 
4.9%
울 152
 
4.9%
별 151
 
4.9%
특 150
 
4.8%
구 150
 
4.8%
곡 140
 
4.5%
Other values (153) 1389
44.7%
Decimal Number
ValueCountFrequency (%)
1 190
21.2%
2 131
14.6%
0 93
10.4%
3 90
10.0%
6 87
9.7%
5 86
9.6%
4 71
 
7.9%
8 52
 
5.8%
7 50
 
5.6%
9 46
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 10
28.6%
A 6
17.1%
I 6
17.1%
V 4
 
11.4%
P 4
 
11.4%
D 2
 
5.7%
H 1
 
2.9%
C 1
 
2.9%
W 1
 
2.9%
Letter Number
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅰ 3
42.9%
Space Separator
ValueCountFrequency (%)
876
100.0%
Other Punctuation
ValueCountFrequency (%)
, 173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3105
57.3%
Common 2271
41.9%
Latin 42
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 316
 
10.2%
동 182
 
5.9%
강 164
 
5.3%
로 158
 
5.1%
시 153
 
4.9%
울 152
 
4.9%
별 151
 
4.9%
특 150
 
4.8%
구 150
 
4.8%
곡 140
 
4.5%
Other values (153) 1389
44.7%
Common
ValueCountFrequency (%)
876
38.6%
1 190
 
8.4%
, 173
 
7.6%
( 150
 
6.6%
) 150
 
6.6%
2 131
 
5.8%
0 93
 
4.1%
3 90
 
4.0%
6 87
 
3.8%
5 86
 
3.8%
Other values (5) 245
 
10.8%
Latin
ValueCountFrequency (%)
B 10
23.8%
A 6
14.3%
I 6
14.3%
Ⅱ 4
 
9.5%
V 4
 
9.5%
P 4
 
9.5%
Ⅰ 3
 
7.1%
D 2
 
4.8%
H 1
 
2.4%
C 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3105
57.3%
ASCII 2306
42.6%
Number Forms 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
876
38.0%
1 190
 
8.2%
, 173
 
7.5%
( 150
 
6.5%
) 150
 
6.5%
2 131
 
5.7%
0 93
 
4.0%
3 90
 
3.9%
6 87
 
3.8%
5 86
 
3.7%
Other values (14) 280
 
12.1%
Hangul
ValueCountFrequency (%)
서 316
 
10.2%
동 182
 
5.9%
강 164
 
5.3%
로 158
 
5.1%
시 153
 
4.9%
울 152
 
4.9%
별 151
 
4.9%
특 150
 
4.8%
구 150
 
4.8%
곡 140
 
4.5%
Other values (153) 1389
44.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 4
57.1%
Ⅰ 3
42.9%

도로명우편번호
Text

MISSING 

Distinct56
Distinct (%)51.4%
Missing44
Missing (%)28.8%
Memory size1.3 KiB
2024-04-30T04:21:27.706430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1651376
Min length5

Characters and Unicode

Total characters563
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

Unique43 ?
Unique (%)39.4%

Sample

1st row07633
2nd row157866
3rd row07777
4th row07802
5th row07632
ValueCountFrequency (%)
07802 13
 
11.9%
07788 9
 
8.3%
07631 7
 
6.4%
07803 7
 
6.4%
07532 6
 
5.5%
07806 6
 
5.5%
07807 3
 
2.8%
07801 3
 
2.8%
07654 3
 
2.8%
07526 3
 
2.8%
Other values (46) 49
45.0%
2024-04-30T04:21:28.307462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 143
25.4%
7 140
24.9%
8 65
11.5%
5 53
 
9.4%
2 42
 
7.5%
6 36
 
6.4%
1 35
 
6.2%
3 32
 
5.7%
4 11
 
2.0%
9 5
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 562
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 143
25.4%
7 140
24.9%
8 65
11.6%
5 53
 
9.4%
2 42
 
7.5%
6 36
 
6.4%
1 35
 
6.2%
3 32
 
5.7%
4 11
 
2.0%
9 5
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 143
25.4%
7 140
24.9%
8 65
11.5%
5 53
 
9.4%
2 42
 
7.5%
6 36
 
6.4%
1 35
 
6.2%
3 32
 
5.7%
4 11
 
2.0%
9 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 143
25.4%
7 140
24.9%
8 65
11.5%
5 53
 
9.4%
2 42
 
7.5%
6 36
 
6.4%
1 35
 
6.2%
3 32
 
5.7%
4 11
 
2.0%
9 5
 
0.9%

사업장명
Text

Distinct152
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-30T04:21:28.558710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.3137255
Min length2

Characters and Unicode

Total characters1272
Distinct characters235
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

Unique151 ?
Unique (%)98.7%

Sample

1st row(주)나진관광여행사
2nd row(주)삼다도관광
3rd row(주)케이제이 여행사
4th row(주)강서관광여행사
5th row(주)기독교놀이문화여행사
ValueCountFrequency (%)
주식회사 25
 
13.2%
브이아이피관광여행사 2
 
1.1%
여행사 2
 
1.1%
투어 2
 
1.1%
주)모두모아투어 1
 
0.5%
주)청실홍실 1
 
0.5%
여행의 1
 
0.5%
온도 1
 
0.5%
주)윤투어 1
 
0.5%
주)투어윈도우글로벌 1
 
0.5%
Other values (153) 153
80.5%
2024-04-30T04:21:28.955189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 120
 
9.4%
) 93
 
7.3%
( 93
 
7.3%
사 58
 
4.6%
행 45
 
3.5%
여 44
 
3.5%
투 39
 
3.1%
어 38
 
3.0%
37
 
2.9%
이 36
 
2.8%
Other values (225) 669
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1038
81.6%
Close Punctuation 93
 
7.3%
Open Punctuation 93
 
7.3%
Space Separator 37
 
2.9%
Uppercase Letter 9
 
0.7%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 120
 
11.6%
사 58
 
5.6%
행 45
 
4.3%
여 44
 
4.2%
투 39
 
3.8%
어 38
 
3.7%
이 36
 
3.5%
스 28
 
2.7%
식 25
 
2.4%
회 25
 
2.4%
Other values (212) 580
55.9%
Uppercase Letter
ValueCountFrequency (%)
O 2
22.2%
K 1
11.1%
R 1
11.1%
S 1
11.1%
U 1
11.1%
T 1
11.1%
C 1
11.1%
M 1
11.1%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1038
81.6%
Common 225
 
17.7%
Latin 9
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 120
 
11.6%
사 58
 
5.6%
행 45
 
4.3%
여 44
 
4.2%
투 39
 
3.8%
어 38
 
3.7%
이 36
 
3.5%
스 28
 
2.7%
식 25
 
2.4%
회 25
 
2.4%
Other values (212) 580
55.9%
Latin
ValueCountFrequency (%)
O 2
22.2%
K 1
11.1%
R 1
11.1%
S 1
11.1%
U 1
11.1%
T 1
11.1%
C 1
11.1%
M 1
11.1%
Common
ValueCountFrequency (%)
) 93
41.3%
( 93
41.3%
37
 
16.4%
& 1
 
0.4%
- 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1038
81.6%
ASCII 234
 
18.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 120
 
11.6%
사 58
 
5.6%
행 45
 
4.3%
여 44
 
4.2%
투 39
 
3.8%
어 38
 
3.7%
이 36
 
3.5%
스 28
 
2.7%
식 25
 
2.4%
회 25
 
2.4%
Other values (212) 580
55.9%
ASCII
ValueCountFrequency (%)
) 93
39.7%
( 93
39.7%
37
 
15.8%
O 2
 
0.9%
& 1
 
0.4%
K 1
 
0.4%
R 1
 
0.4%
- 1
 
0.4%
S 1
 
0.4%
U 1
 
0.4%
Other values (3) 3
 
1.3%

최종수정일자
Date

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2003-04-18 11:50:59
Maximum2024-04-03 14:58:06
2024-04-30T04:21:29.069752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:29.195382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
79 
U
74 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 79
51.6%
U 74
48.4%

Length

2024-04-30T04:21:29.310294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:29.394857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 79
51.6%
u 74
48.4%

데이터갱신일자
Date

Distinct72
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-30T04:21:29.497491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:21:29.618600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)80.8%
Missing23
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean185698.36
Minimum182524.82
Maximum188954.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:29.755091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182524.82
5-th percentile183034.82
Q1184712.44
median185740.63
Q3187052.32
95-th percentile188216.91
Maximum188954.19
Range6429.3633
Interquartile range (IQR)2339.8859

Descriptive statistics

Standard deviation1614.8022
Coefficient of variation (CV)0.0086958344
Kurtosis-0.82959918
Mean185698.36
Median Absolute Deviation (MAD)1117.8618
Skewness-0.057322918
Sum24140787
Variance2607586.1
MonotonicityNot monotonic
2024-04-30T04:21:29.877580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187052.323132425 5
 
3.3%
185144.0 4
 
2.6%
187733.160920858 3
 
2.0%
185960.440336998 3
 
2.0%
187952.560027898 2
 
1.3%
182876.367858149 2
 
1.3%
185078.0 2
 
1.3%
184971.522700042 2
 
1.3%
188245.686899069 2
 
1.3%
185163.0 2
 
1.3%
Other values (95) 103
67.3%
(Missing) 23
 
15.0%
ValueCountFrequency (%)
182524.823835629 1
0.7%
182876.367858149 2
1.3%
182895.668483962 1
0.7%
182914.598086861 1
0.7%
182929.561795629 1
0.7%
183007.220061564 1
0.7%
183068.55405978 1
0.7%
183225.996378678 1
0.7%
183237.425943428 1
0.7%
183275.424160871 1
0.7%
ValueCountFrequency (%)
188954.187154407 1
0.7%
188843.428976776 1
0.7%
188791.250134373 1
0.7%
188692.033242329 1
0.7%
188459.993404231 1
0.7%
188245.686899069 2
1.3%
188181.747875314 1
0.7%
187999.32555627 1
0.7%
187952.560027898 2
1.3%
187926.077711687 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)80.8%
Missing23
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean450619.71
Minimum447353.95
Maximum452915.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:30.045242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447353.95
5-th percentile448323.84
Q1450075.82
median450782.43
Q3451331.22
95-th percentile452272.73
Maximum452915.96
Range5562.0141
Interquartile range (IQR)1255.4014

Descriptive statistics

Standard deviation1150.4409
Coefficient of variation (CV)0.0025530196
Kurtosis0.63456914
Mean450619.71
Median Absolute Deviation (MAD)647.18941
Skewness-0.69126294
Sum58580562
Variance1323514.4
MonotonicityNot monotonic
2024-04-30T04:21:30.230782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450291.97922408 5
 
3.3%
450938.0 4
 
2.6%
450747.952249309 3
 
2.0%
451800.33453706 3
 
2.0%
450562.020225978 2
 
1.3%
452247.393831256 2
 
1.3%
450896.0 2
 
1.3%
450643.056387457 2
 
1.3%
449758.746455637 2
 
1.3%
450826.0 2
 
1.3%
Other values (95) 103
67.3%
(Missing) 23
 
15.0%
ValueCountFrequency (%)
447353.94960188 1
0.7%
447532.962112156 1
0.7%
447558.097935801 1
0.7%
447634.784556281 1
0.7%
447752.517105171 1
0.7%
447998.061398387 1
0.7%
448300.451846753 1
0.7%
448352.42561757 1
0.7%
448712.576195721 1
0.7%
448770.058159662 1
0.7%
ValueCountFrequency (%)
452915.963722565 1
0.7%
452899.475862536 1
0.7%
452713.505241493 1
0.7%
452526.699106933 1
0.7%
452514.491608298 1
0.7%
452327.871674126 1
0.7%
452293.455519022 1
0.7%
452247.393831256 2
1.3%
452204.165533971 1
0.7%
452099.765683138 1
0.7%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
국내여행업
118 
<NA>
35 

Length

Max length5
Median length5
Mean length4.7712418
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 118
77.1%
<NA> 35
 
22.9%

Length

2024-04-30T04:21:30.423609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:30.538170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 118
77.1%
na 35
 
22.9%

문화사업자구분명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
109 
관광사업
44 

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> 109
71.2%
관광사업 44
28.8%

Length

2024-04-30T04:21:30.680062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:30.793594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 109
71.2%
관광사업 44
28.8%

지역구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
146 
일반상업지역
 
3
주거지역
 
2
상업지역
 
2

Length

Max length6
Median length4
Mean length4.0392157
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> 146
95.4%
일반상업지역 3
 
2.0%
주거지역 2
 
1.3%
상업지역 2
 
1.3%

Length

2024-04-30T04:21:30.912105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:31.006935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
95.4%
일반상업지역 3
 
2.0%
주거지역 2
 
1.3%
상업지역 2
 
1.3%

총층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
146 
0
 
2
7
 
2
5
 
1
17
 
1

Length

Max length4
Median length4
Mean length3.869281
Min length1

Unique

Unique3 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 146
95.4%
0 2
 
1.3%
7 2
 
1.3%
5 1
 
0.7%
17 1
 
0.7%
4 1
 
0.7%

Length

2024-04-30T04:21:31.114017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:31.218451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
95.4%
0 2
 
1.3%
7 2
 
1.3%
5 1
 
0.7%
17 1
 
0.7%
4 1
 
0.7%

주변환경명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
기타
 
5
주택가주변
 
1

Length

Max length5
Median length4
Mean length3.9411765
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
96.1%
기타 5
 
3.3%
주택가주변 1
 
0.7%

Length

2024-04-30T04:21:31.319692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:31.407235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
96.1%
기타 5
 
3.3%
주택가주변 1
 
0.7%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

보험기관명
Categorical

Distinct18
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
80 
서울보증보험
37 
한국관광협회중앙회 여행공제회
9 
한국관광협회 여행공제회
 
6
서울보증보험주식회사
 
4
Other values (13)
17 

Length

Max length18
Median length4
Mean length6.5163399
Min length4

Unique

Unique11 ?
Unique (%)7.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 80
52.3%
서울보증보험 37
24.2%
한국관광협회중앙회 여행공제회 9
 
5.9%
한국관광협회 여행공제회 6
 
3.9%
서울보증보험주식회사 4
 
2.6%
서울보증보험(2천만원) 4
 
2.6%
한국관광협회 2
 
1.3%
서울보증보험(주) 1
 
0.7%
한국관광협회 여행공제 1
 
0.7%
서울보증보험(14천만원) 1
 
0.7%
Other values (8) 8
 
5.2%

Length

2024-04-30T04:21:31.497715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 80
47.3%
서울보증보험 37
21.9%
여행공제회 15
 
8.9%
한국관광협회중앙회 9
 
5.3%
한국관광협회 9
 
5.3%
서울보증보험주식회사 4
 
2.4%
서울보증보험(2천만원 4
 
2.4%
서울보증보험(3천만원 1
 
0.6%
서울보증보험(85,000,000 1
 
0.6%
관광공제회(2천만원 1
 
0.6%
Other values (8) 8
 
4.7%

건물용도명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
141 
근린생활시설
 
6
사무실
 
3
유통시설
 
2
아파트
 
1

Length

Max length6
Median length4
Mean length4.0522876
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 141
92.2%
근린생활시설 6
 
3.9%
사무실 3
 
2.0%
유통시설 2
 
1.3%
아파트 1
 
0.7%

Length

2024-04-30T04:21:31.615167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:31.727977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
92.2%
근린생활시설 6
 
3.9%
사무실 3
 
2.0%
유통시설 2
 
1.3%
아파트 1
 
0.7%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)85.7%
Missing146
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean46.285714
Minimum0
Maximum299
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:31.803374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median4
Q39
95-th percentile212.9
Maximum299
Range299
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation111.5119
Coefficient of variation (CV)2.4092078
Kurtosis6.9695851
Mean46.285714
Median Absolute Deviation (MAD)4
Skewness2.6383029
Sum324
Variance12434.905
MonotonicityNot monotonic
2024-04-30T04:21:31.888955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 2
 
1.3%
4 1
 
0.7%
12 1
 
0.7%
3 1
 
0.7%
6 1
 
0.7%
299 1
 
0.7%
(Missing) 146
95.4%
ValueCountFrequency (%)
0 2
1.3%
3 1
0.7%
4 1
0.7%
6 1
0.7%
12 1
0.7%
299 1
0.7%
ValueCountFrequency (%)
299 1
0.7%
12 1
0.7%
6 1
0.7%
4 1
0.7%
3 1
0.7%
0 2
1.3%

지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
147 
1
 
3
0
 
2
5
 
1

Length

Max length4
Median length4
Mean length3.8823529
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 147
96.1%
1 3
 
2.0%
0 2
 
1.3%
5 1
 
0.7%

Length

2024-04-30T04:21:31.993615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:32.080329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 147
96.1%
1 3
 
2.0%
0 2
 
1.3%
5 1
 
0.7%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:32.179230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:32.282054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:32.370587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:32.459025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

영문상호명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing151
Missing (%)98.7%
Memory size1.3 KiB
2024-04-30T04:21:32.573879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20.5
Mean length20.5
Min length19

Characters and Unicode

Total characters41
Distinct characters23
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 rowONNURI GOLF CO.,LTD
2nd rowTHE WAY KOREA Co.Ltd.,
ValueCountFrequency (%)
onnuri 1
14.3%
golf 1
14.3%
co.,ltd 1
14.3%
the 1
14.3%
way 1
14.3%
korea 1
14.3%
co.ltd 1
14.3%
2024-04-30T04:21:32.844148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
12.2%
O 4
 
9.8%
L 3
 
7.3%
. 3
 
7.3%
C 2
 
4.9%
A 2
 
4.9%
E 2
 
4.9%
T 2
 
4.9%
N 2
 
4.9%
, 2
 
4.9%
Other values (13) 14
34.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 28
68.3%
Space Separator 5
 
12.2%
Other Punctuation 5
 
12.2%
Lowercase Letter 3
 
7.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 4
14.3%
L 3
10.7%
C 2
 
7.1%
A 2
 
7.1%
E 2
 
7.1%
T 2
 
7.1%
N 2
 
7.1%
R 2
 
7.1%
F 1
 
3.6%
G 1
 
3.6%
Other values (7) 7
25.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
t 1
33.3%
d 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 4
 
12.9%
L 3
 
9.7%
C 2
 
6.5%
A 2
 
6.5%
E 2
 
6.5%
T 2
 
6.5%
N 2
 
6.5%
R 2
 
6.5%
F 1
 
3.2%
G 1
 
3.2%
Other values (10) 10
32.3%
Common
ValueCountFrequency (%)
5
50.0%
. 3
30.0%
, 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
 
12.2%
O 4
 
9.8%
L 3
 
7.3%
. 3
 
7.3%
C 2
 
4.9%
A 2
 
4.9%
E 2
 
4.9%
T 2
 
4.9%
N 2
 
4.9%
, 2
 
4.9%
Other values (13) 14
34.1%

영문상호주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing151
Missing (%)98.7%
Memory size1.3 KiB
2024-04-30T04:21:32.962911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters48
Distinct characters16
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%
2024-04-30T04:21:33.195011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8
16.7%
e 6
12.5%
t 4
 
8.3%
i 4
 
8.3%
4
 
8.3%
D 2
 
4.2%
o 2
 
4.2%
m 2
 
4.2%
c 2
 
4.2%
r 2
 
4.2%
Other values (6) 12
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 42
87.5%
Space Separator 4
 
8.3%
Uppercase Letter 2
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 8
19.0%
e 6
14.3%
t 4
9.5%
i 4
9.5%
o 2
 
4.8%
m 2
 
4.8%
c 2
 
4.8%
r 2
 
4.8%
a 2
 
4.8%
v 2
 
4.8%
Other values (4) 8
19.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 2
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%
t 4
 
9.1%
i 4
 
9.1%
D 2
 
4.5%
o 2
 
4.5%
m 2
 
4.5%
c 2
 
4.5%
r 2
 
4.5%
a 2
 
4.5%
Other values (5) 10
22.7%
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%
t 4
 
8.3%
i 4
 
8.3%
4
 
8.3%
D 2
 
4.2%
o 2
 
4.2%
m 2
 
4.2%
c 2
 
4.2%
r 2
 
4.2%
Other values (6) 12
25.0%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:33.309871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:33.392434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:33.484024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:33.565984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:33.874845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:33.985597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:34.077930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:34.163592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:34.252432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:34.349252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)88.5%
Missing127
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean53.665
Minimum0
Maximum138.14
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:34.429273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.875
Q117.375
median45.58
Q370.575
95-th percentile130.7
Maximum138.14
Range138.14
Interquartile range (IQR)53.2

Descriptive statistics

Standard deviation41.637899
Coefficient of variation (CV)0.77588557
Kurtosis-0.55233508
Mean53.665
Median Absolute Deviation (MAD)27.33
Skewness0.62882903
Sum1395.29
Variance1733.7146
MonotonicityNot monotonic
2024-04-30T04:21:34.536848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
66.0 2
 
1.3%
10.0 2
 
1.3%
0.0 2
 
1.3%
125.0 1
 
0.7%
40.0 1
 
0.7%
71.0 1
 
0.7%
112.2 1
 
0.7%
99.47 1
 
0.7%
20.0 1
 
0.7%
40.4 1
 
0.7%
Other values (13) 13
 
8.5%
(Missing) 127
83.0%
ValueCountFrequency (%)
0.0 2
1.3%
7.5 1
0.7%
10.0 2
1.3%
13.36 1
0.7%
16.5 1
0.7%
20.0 1
0.7%
28.86 1
0.7%
35.69 1
0.7%
39.76 1
0.7%
40.0 1
0.7%
ValueCountFrequency (%)
138.14 1
0.7%
132.6 1
0.7%
125.0 1
0.7%
112.2 1
0.7%
99.47 1
0.7%
87.25 1
0.7%
71.0 1
0.7%
69.3 1
0.7%
66.0 2
1.3%
59.5 1
0.7%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
152 
0
 
1

Length

Max length4
Median length4
Mean length3.9803922
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
99.3%
0 1
 
0.7%

Length

2024-04-30T04:21:34.664008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:21:34.750280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
99.3%
0 1
 
0.7%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

자본금
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)23.3%
Missing50
Missing (%)32.7%
Infinite0
Infinite (%)0.0%
Mean81136417
Minimum15000000
Maximum1.5 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:34.828587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15000000
5-th percentile15000000
Q131763240
median50000000
Q393000000
95-th percentile1.97 × 108
Maximum1.5 × 109
Range1.485 × 109
Interquartile range (IQR)61236760

Descriptive statistics

Standard deviation1.5018298 × 108
Coefficient of variation (CV)1.8509934
Kurtosis79.823029
Mean81136417
Median Absolute Deviation (MAD)20000000
Skewness8.4705025
Sum8.3570509 × 109
Variance2.2554926 × 1016
MonotonicityNot monotonic
2024-04-30T04:21:34.934639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
50000000 38
24.8%
30000000 11
 
7.2%
100000000 9
 
5.9%
15000000 8
 
5.2%
150000000 7
 
4.6%
90000000 5
 
3.3%
200000000 4
 
2.6%
32000000 2
 
1.3%
60000000 2
 
1.3%
20000000 2
 
1.3%
Other values (14) 15
 
9.8%
(Missing) 50
32.7%
ValueCountFrequency (%)
15000000 8
5.2%
16000000 2
 
1.3%
18306241 1
 
0.7%
20000000 2
 
1.3%
30000000 11
7.2%
31163361 1
 
0.7%
31619171 1
 
0.7%
31907310 1
 
0.7%
32000000 2
 
1.3%
45000000 1
 
0.7%
ValueCountFrequency (%)
1500000000 1
 
0.7%
300000000 1
 
0.7%
200000000 4
2.6%
170000000 1
 
0.7%
150000000 7
4.6%
118916020 1
 
0.7%
100000000 9
5.9%
97338818 1
 
0.7%
96000000 1
 
0.7%
90000000 5
3.3%

보험시작일자
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)97.3%
Missing80
Missing (%)52.3%
Infinite0
Infinite (%)0.0%
Mean20145003
Minimum20020317
Maximum20210509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:35.054310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020317
5-th percentile20026608
Q120120906
median20161030
Q320190604
95-th percentile20210243
Maximum20210509
Range190192
Interquartile range (IQR)69698

Descriptive statistics

Standard deviation57056.241
Coefficient of variation (CV)0.0028322777
Kurtosis0.14378881
Mean20145003
Median Absolute Deviation (MAD)29927
Skewness-1.0913705
Sum1.4705852 × 109
Variance3.2554147 × 109
MonotonicityNot monotonic
2024-04-30T04:21:35.181216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030201 2
 
1.3%
20020317 2
 
1.3%
20170721 1
 
0.7%
20141201 1
 
0.7%
20161102 1
 
0.7%
20210422 1
 
0.7%
20161229 1
 
0.7%
20170618 1
 
0.7%
20170302 1
 
0.7%
20171102 1
 
0.7%
Other values (61) 61
39.9%
(Missing) 80
52.3%
ValueCountFrequency (%)
20020317 2
1.3%
20021025 1
0.7%
20021218 1
0.7%
20030201 2
1.3%
20030203 1
0.7%
20030217 1
0.7%
20030222 1
0.7%
20030226 1
0.7%
20050712 1
0.7%
20100507 1
0.7%
ValueCountFrequency (%)
20210509 1
0.7%
20210422 1
0.7%
20210415 1
0.7%
20210301 1
0.7%
20210204 1
0.7%
20200929 1
0.7%
20200730 1
0.7%
20200712 1
0.7%
20200527 1
0.7%
20200504 1
0.7%

보험종료일자
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)98.6%
Missing80
Missing (%)52.3%
Infinite0
Infinite (%)0.0%
Mean20155439
Minimum20030316
Maximum20220508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:35.303601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030316
5-th percentile20036607
Q120130906
median20171029
Q320200909
95-th percentile20220242
Maximum20220508
Range190192
Interquartile range (IQR)70003

Descriptive statistics

Standard deviation57576.235
Coefficient of variation (CV)0.0028566103
Kurtosis0.078968112
Mean20155439
Median Absolute Deviation (MAD)30072
Skewness-1.0752456
Sum1.4713471 × 109
Variance3.3150229 × 109
MonotonicityNot monotonic
2024-04-30T04:21:35.434279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040201 2
 
1.3%
20190115 1
 
0.7%
20151130 1
 
0.7%
20171101 1
 
0.7%
20220421 1
 
0.7%
20171229 1
 
0.7%
20180618 1
 
0.7%
20180301 1
 
0.7%
20190720 1
 
0.7%
20201101 1
 
0.7%
Other values (62) 62
40.5%
(Missing) 80
52.3%
ValueCountFrequency (%)
20030316 1
0.7%
20030317 1
0.7%
20031025 1
0.7%
20031217 1
0.7%
20040201 2
1.3%
20040203 1
0.7%
20040217 1
0.7%
20040222 1
0.7%
20040226 1
0.7%
20060712 1
0.7%
ValueCountFrequency (%)
20220508 1
0.7%
20220421 1
0.7%
20220415 1
0.7%
20220301 1
0.7%
20220203 1
0.7%
20210928 1
0.7%
20210729 1
0.7%
20210712 1
0.7%
20210603 1
0.7%
20210526 1
0.7%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing153
Missing (%)100.0%
Memory size1.5 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)80.8%
Missing127
Missing (%)83.0%
Infinite0
Infinite (%)0.0%
Mean53.692308
Minimum0
Maximum138
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-30T04:21:35.564109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q117.75
median45.5
Q370.5
95-th percentile131
Maximum138
Range138
Interquartile range (IQR)52.75

Descriptive statistics

Standard deviation41.582467
Coefficient of variation (CV)0.77445855
Kurtosis-0.54139305
Mean53.692308
Median Absolute Deviation (MAD)27
Skewness0.63069505
Sum1396
Variance1729.1015
MonotonicityNot monotonic
2024-04-30T04:21:35.661335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
40 3
 
2.0%
66 2
 
1.3%
10 2
 
1.3%
0 2
 
1.3%
125 1
 
0.7%
71 1
 
0.7%
112 1
 
0.7%
99 1
 
0.7%
20 1
 
0.7%
36 1
 
0.7%
Other values (11) 11
 
7.2%
(Missing) 127
83.0%
ValueCountFrequency (%)
0 2
1.3%
8 1
 
0.7%
10 2
1.3%
13 1
 
0.7%
17 1
 
0.7%
20 1
 
0.7%
29 1
 
0.7%
36 1
 
0.7%
40 3
2.0%
51 1
 
0.7%
ValueCountFrequency (%)
138 1
0.7%
133 1
0.7%
125 1
0.7%
112 1
0.7%
99 1
0.7%
87 1
0.7%
71 1
0.7%
69 1
0.7%
66 2
1.3%
60 1
0.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03150000CDFI226001199100000119910318<NA>3폐업3폐업20070220<NA><NA><NA>2694-7262<NA>157928서울특별시 강서구 화곡동 1117-18번지서울특별시 강서구 화곡로 326 (화곡동)<NA>(주)나진관광여행사2007-02-20 16:05:19I2018-08-31 23:59:59.0<NA>186748.439905450068.277077국내여행업관광사업<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>500000002003021720040217<NA><NA>
13150000CDFI226001199200000119920801<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2692-0083<NA><NA>서울특별시 강서구 내발산동 681-15번지서울특별시 강서구 강서로47길 40, 1층 (내발산동)07633(주)삼다도관광2020-06-16 10:49:01U2020-06-18 02:40:00.0<NA>185257.256014450098.16499국내여행업관광사업<NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>500000002020050420210503<NA><NA>
23150000CDFI226001199300000119930812<NA>3폐업3폐업20080506<NA><NA><NA>2661-6200<NA>157846서울특별시 강서구 방화동 247-110번지서울특별시 강서구 초원로 75 (방화동)<NA>(주)케이제이 여행사2008-05-06 15:26:02I2018-08-31 23:59:59.0<NA>183484.777904451729.553009국내여행업관광사업<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>500000002003020320040203<NA><NA>
33150000CDFI226001199400000119940305<NA>3폐업3폐업20140226<NA><NA><NA>02-3663-1245<NA>157866서울특별시 강서구 화곡동 24-571번지 천일빌딩 201호서울특별시 강서구 화곡로 266, 201호 (화곡동, 천일빌딩)157866(주)강서관광여행사2014-02-26 11:03:33I2018-08-31 23:59:59.0<NA>186412.970138449581.397185국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>200000000<NA><NA><NA><NA>
43150000CDFI226001199700000119970523<NA>3폐업3폐업20011228<NA><NA><NA>654-3045<NA>157897서울특별시 강서구 화곡동 796-16번지서울특별시 강서구 곰달래로 256 (화곡동)<NA>(주)기독교놀이문화여행사2003-04-28 13:41:38I2018-08-31 23:59:59.0<NA>187685.860829447752.517105국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53150000CDFI226001199700000219970904<NA>1영업/정상13영업중<NA><NA><NA><NA>3663-6252<NA>157030서울특별시 강서구 등촌동 698-1번지서울특별시 강서구 공항대로41길 66 (등촌동)<NA>(주)수호항공여행사2003-04-28 13:45:32I2018-08-31 23:59:59.0<NA>186378.231818450937.877207국내여행업관광사업<NA><NA><NA><NA>서울보증보험<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>500000002003020120040201<NA><NA>
63150000CDFI226001199700000319970930200709074취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>664-7777<NA>157846서울특별시 강서구 방화동 249-293번지서울특별시 강서구 방화대로33길 63 (방화동)<NA>케니종합물류(주)2009-05-28 11:26:12I2018-08-31 23:59:59.0<NA>183418.22833451775.118175국내여행업관광사업<NA><NA><NA><NA>한국관광협회 여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>69.3<NA><NA><NA><NA><NA><NA><NA><NA>500000002003020120040201<NA>69
73150000CDFI226001199700000419971024<NA>3폐업3폐업20100331<NA><NA><NA><NA><NA>157811서울특별시 강서구 공항동 22-53번지서울특별시 강서구 방화동로 36-1 (공항동)<NA>공항국제관광(주)2010-03-31 15:28:30I2018-08-31 23:59:59.0<NA>183237.425943451296.552424국내여행업관광사업<NA><NA><NA><NA>한국관광협회 여행공제<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>500000002002031720030317<NA><NA>
83150000CDFI226001199700000519970611<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 11:11:09I2018-08-31 23:59:59.0<NA>188954.187154449657.109279국내여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93150000CDFI226001199800000119980620<NA>3폐업3폐업20060127<NA><NA><NA><NA><NA>157836서울특별시 강서구 등촌동 507-6번지서울특별시 강서구 등촌로 225 (등촌동)<NA>주식회사 범아관광정보2006-01-27 14:40:10I2018-08-31 23:59:59.0<NA>187864.213666449738.795162국내여행업관광사업<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>500000002003022220040222<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
1433150000CDFI226001202100000520191018<NA>5제외/삭제/전출15전출20221121<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 798-5 에이스타워Ⅱ 504호서울특별시 강서구 마곡중앙로 59-21, 에이스타워Ⅱ 504호 (마곡동)07807주식회사 호랑뽀랑2022-11-21 16:05:31U2021-10-31 22:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1443150000CDFI226001202100000620190918<NA>3폐업3폐업20221124<NA><NA><NA>1877-2509<NA><NA>서울특별시 강서구 마곡동 774-2 보타닉파크타워2 314호서울특별시 강서구 공항대로 213, 보타닉파크타워2 314호 (마곡동)07802직투어2022-11-24 16:06:32U2021-10-31 22:06:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1453150000CDFI226001202100000720200113<NA>5제외/삭제/전출15전출20230106<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 757-5 프라이빗타워타워1차 1003호서울특별시 강서구 마곡중앙로 165, 프라이빗타워타워1차 1003호 (마곡동)07788주식회사 바바그라운드2023-01-06 10:11:50U2022-12-01 00:08:00.0<NA>184708.916316451822.756998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1463150000CDFI22600120210000082021-08-25<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2289-3978<NA><NA>서울특별시 강서구 마곡동 799-6 메트로비즈타워 403호서울특별시 강서구 마곡중앙2로 5, 메트로비즈타워 403호 (마곡동)07631펜션다나와2024-03-12 16:46:36U2023-12-02 23:04:00.0<NA>184685.391571450700.800441<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1473150000CDFI22600120220000012008-07-07<NA>3폐업3폐업2023-06-29<NA><NA><NA>02-3153-0181<NA><NA>서울특별시 강서구 공항동 1373-5 D동서울특별시 강서구 하늘길 233, D동 (공항동)07505(주)그린웍스2023-06-30 09:00:40U2022-12-07 00:02:00.0<NA>183007.220062450515.642036<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1483150000CDFI226001202200000220110201<NA>1영업/정상13영업중<NA><NA><NA><NA>2668-1999<NA><NA>서울특별시 강서구 염창동 275-2 주영빌딩 302호서울특별시 강서구 공항대로65길 12, 주영빌딩 3층 302호 (염창동)07560주식회사 브이아이피관광여행사2022-06-24 18:01:57I2021-12-05 22:06:00.0<NA>188245.686899449758.746456<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1493150000CDFI226001202200000320220713<NA>3폐업3폐업20221223<NA><NA><NA><NA><NA><NA>서울특별시 강서구 내발산동 750-11 신원메디칼프라자 9-80호서울특별시 강서구 강서로47길 165, 신원메디칼프라자 9층 80호 (내발산동)07635트래블랜드2022-12-26 11:07:19U2021-11-01 22:08:00.0<NA>184636.533441450143.872075<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1503150000CDFI22600120220000042022-09-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 194-2 양천향교지웰에스테이트 B101호서울특별시 강서구 양천로49길 54, 양천향교지웰에스테이트 B101호 (가양동)07523(주)카이로스2023-03-27 09:02:10U2022-12-02 22:09:00.0<NA>185867.499971452099.765683<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1513150000CDFI226001202300000120230118<NA>1영업/정상13영업중<NA><NA><NA><NA>1533-6559<NA><NA>서울특별시 강서구 마곡동 771-1서울특별시 강서구 마곡중앙8로 14, 613호 (마곡동)07801주식회사 얼롱2023-01-18 08:54:40I2022-11-30 22:01:00.0<NA>184811.597727451026.459719<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1523150000CDFI22600120240000012024-01-03<NA>3폐업3폐업2024-03-18<NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 648-6 비원오피스텔서울특별시 강서구 공항대로 525, 비원오피스텔 1501가-96호 (등촌동)07563스마트투어2024-03-18 13:17:24U2023-12-02 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>