Overview

Dataset statistics

Number of variables60
Number of observations130
Missing cells3140
Missing cells (%)40.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.9 KiB
Average record size in memory519.0 B

Variable types

Categorical23
Text9
DateTime4
Unsupported15
Numeric9

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,문화사업자구분명,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-17591/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (91.8%)Imbalance
휴업종료일자 is highly imbalanced (91.8%)Imbalance
주변환경명 is highly imbalanced (81.2%)Imbalance
건물용도명 is highly imbalanced (72.3%)Imbalance
지하층수 is highly imbalanced (78.7%)Imbalance
객실수 is highly imbalanced (84.2%)Imbalance
건축연면적 is highly imbalanced (84.2%)Imbalance
선박총톤수 is highly imbalanced (84.2%)Imbalance
선박척수 is highly imbalanced (84.2%)Imbalance
무대면적 is highly imbalanced (84.2%)Imbalance
좌석수 is highly imbalanced (84.2%)Imbalance
회의실별동시수용인원 is highly imbalanced (84.2%)Imbalance
놀이시설수 is highly imbalanced (84.2%)Imbalance
인허가취소일자 has 130 (100.0%) missing valuesMissing
폐업일자 has 76 (58.5%) missing valuesMissing
재개업일자 has 130 (100.0%) missing valuesMissing
전화번호 has 69 (53.1%) missing valuesMissing
소재지면적 has 130 (100.0%) missing valuesMissing
도로명주소 has 2 (1.5%) missing valuesMissing
도로명우편번호 has 22 (16.9%) missing valuesMissing
업태구분명 has 130 (100.0%) missing valuesMissing
좌표정보(X) has 2 (1.5%) missing valuesMissing
좌표정보(Y) has 2 (1.5%) missing valuesMissing
지역구분명 has 125 (96.2%) missing valuesMissing
총층수 has 121 (93.1%) missing valuesMissing
제작취급품목내용 has 130 (100.0%) missing valuesMissing
지상층수 has 119 (91.5%) missing valuesMissing
영문상호명 has 126 (96.9%) missing valuesMissing
영문상호주소 has 126 (96.9%) missing valuesMissing
선박제원 has 130 (100.0%) missing valuesMissing
기념품종류 has 130 (100.0%) missing valuesMissing
시설면적 has 90 (69.2%) missing valuesMissing
놀이기구수내역 has 130 (100.0%) missing valuesMissing
방송시설유무 has 130 (100.0%) missing valuesMissing
발전시설유무 has 130 (100.0%) missing valuesMissing
의무실유무 has 130 (100.0%) missing valuesMissing
안내소유무 has 130 (100.0%) missing valuesMissing
기획여행보험시작일자 has 130 (100.0%) missing valuesMissing
기획여행보험종료일자 has 130 (100.0%) missing valuesMissing
자본금 has 66 (50.8%) missing valuesMissing
보험시작일자 has 77 (59.2%) missing valuesMissing
보험종료일자 has 77 (59.2%) missing valuesMissing
부대시설내역 has 130 (100.0%) missing valuesMissing
시설규모 has 90 (69.2%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 3 (2.3%) zerosZeros
지상층수 has 3 (2.3%) zerosZeros
시설면적 has 6 (4.6%) zerosZeros
시설규모 has 6 (4.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:29:49.333570
Analysis finished2024-05-11 06:29:51.008168
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3140000
130 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 130
100.0%

Length

2024-05-11T15:29:51.131624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:51.334062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 130
100.0%

관리번호
Text

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:29:51.612371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2600
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

Unique130 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021993000001
2nd rowCDFI2260021996000001
3rd rowCDFI2260021996000003
4th rowCDFI2260021997000001
5th rowCDFI2260021998000001
ValueCountFrequency (%)
cdfi2260021993000001 1
 
0.8%
cdfi2260022017000005 1
 
0.8%
cdfi2260022017000003 1
 
0.8%
cdfi2260022017000002 1
 
0.8%
cdfi2260022017000001 1
 
0.8%
cdfi2260022016000005 1
 
0.8%
cdfi2260022016000003 1
 
0.8%
cdfi2260022016000002 1
 
0.8%
cdfi2260022016000001 1
 
0.8%
cdfi2260022015000008 1
 
0.8%
Other values (120) 120
92.3%
2024-05-11T15:29:52.103940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1077
41.4%
2 567
21.8%
6 156
 
6.0%
C 130
 
5.0%
D 130
 
5.0%
F 130
 
5.0%
I 130
 
5.0%
1 120
 
4.6%
4 33
 
1.3%
7 29
 
1.1%
Other values (4) 98
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2080
80.0%
Uppercase Letter 520
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1077
51.8%
2 567
27.3%
6 156
 
7.5%
1 120
 
5.8%
4 33
 
1.6%
7 29
 
1.4%
5 28
 
1.3%
3 25
 
1.2%
9 24
 
1.2%
8 21
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 130
25.0%
D 130
25.0%
F 130
25.0%
I 130
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2080
80.0%
Latin 520
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1077
51.8%
2 567
27.3%
6 156
 
7.5%
1 120
 
5.8%
4 33
 
1.6%
7 29
 
1.4%
5 28
 
1.3%
3 25
 
1.2%
9 24
 
1.2%
8 21
 
1.0%
Latin
ValueCountFrequency (%)
C 130
25.0%
D 130
25.0%
F 130
25.0%
I 130
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1077
41.4%
2 567
21.8%
6 156
 
6.0%
C 130
 
5.0%
D 130
 
5.0%
F 130
 
5.0%
I 130
 
5.0%
1 120
 
4.6%
4 33
 
1.3%
7 29
 
1.1%
Other values (4) 98
 
3.8%

인허가일자
Date

Distinct127
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1991-10-10 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T15:29:52.334448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:52.590018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

영업상태코드
Categorical

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
1
72 
3
50 
5
 
4
4
 
2
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 72
55.4%
3 50
38.5%
5 4
 
3.1%
4 2
 
1.5%
2 2
 
1.5%

Length

2024-05-11T15:29:52.791855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:52.970809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 72
55.4%
3 50
38.5%
5 4
 
3.1%
4 2
 
1.5%
2 2
 
1.5%

영업상태명
Categorical

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업/정상
72 
폐업
50 
제외/삭제/전출
 
4
취소/말소/만료/정지/중지
 
2
휴업
 
2

Length

Max length14
Median length5
Mean length4.0307692
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 72
55.4%
폐업 50
38.5%
제외/삭제/전출 4
 
3.1%
취소/말소/만료/정지/중지 2
 
1.5%
휴업 2
 
1.5%

Length

2024-05-11T15:29:53.222812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:53.449740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 72
55.4%
폐업 50
38.5%
제외/삭제/전출 4
 
3.1%
취소/말소/만료/정지/중지 2
 
1.5%
휴업 2
 
1.5%

상세영업상태코드
Categorical

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
13
72 
3
50 
15
 
4
31
 
2
2
 
2

Length

Max length2
Median length2
Mean length1.6
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row31
4th row3
5th row13

Common Values

ValueCountFrequency (%)
13 72
55.4%
3 50
38.5%
15 4
 
3.1%
31 2
 
1.5%
2 2
 
1.5%

Length

2024-05-11T15:29:53.704526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:53.859966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 72
55.4%
3 50
38.5%
15 4
 
3.1%
31 2
 
1.5%
2 2
 
1.5%

상세영업상태명
Categorical

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업중
72 
폐업
50 
전출
 
4
등록취소
 
2
휴업
 
2

Length

Max length4
Median length3
Mean length2.5846154
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 72
55.4%
폐업 50
38.5%
전출 4
 
3.1%
등록취소 2
 
1.5%
휴업 2
 
1.5%

Length

2024-05-11T15:29:54.059117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:54.229979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 72
55.4%
폐업 50
38.5%
전출 4
 
3.1%
등록취소 2
 
1.5%
휴업 2
 
1.5%

폐업일자
Date

MISSING 

Distinct53
Distinct (%)98.1%
Missing76
Missing (%)58.5%
Memory size1.1 KiB
Minimum1996-03-02 00:00:00
Maximum2024-03-27 00:00:00
2024-05-11T15:29:54.408800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:54.583259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
128 
20050803
 
1
20081031
 
1

Length

Max length8
Median length4
Mean length4.0615385
Min length4

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
98.5%
20050803 1
 
0.8%
20081031 1
 
0.8%

Length

2024-05-11T15:29:54.787745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:54.964515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
98.5%
20050803 1
 
0.8%
20081031 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
128 
20060630
 
1
20090430
 
1

Length

Max length8
Median length4
Mean length4.0615385
Min length4

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
98.5%
20060630 1
 
0.8%
20090430 1
 
0.8%

Length

2024-05-11T15:29:55.159435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:55.359388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
98.5%
20060630 1
 
0.8%
20090430 1
 
0.8%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Text

MISSING 

Distinct61
Distinct (%)100.0%
Missing69
Missing (%)53.1%
Memory size1.1 KiB
2024-05-11T15:29:55.676601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9
Mean length10.180328
Min length7

Characters and Unicode

Total characters621
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

Unique61 ?
Unique (%)100.0%

Sample

1st row02-2652-3361
2nd row02-2645-7441
3rd row2168-3001
4th row6739-3636
5th row02-2168-3453
ValueCountFrequency (%)
2648-7114 1
 
1.6%
02-538-2733 1
 
1.6%
02-2643-1179 1
 
1.6%
2652-0530 1
 
1.6%
2668-8888 1
 
1.6%
070-4384-1244 1
 
1.6%
2644-4700 1
 
1.6%
02-2647-4044 1
 
1.6%
0226915333 1
 
1.6%
02-2646-5773 1
 
1.6%
Other values (52) 52
83.9%
2024-05-11T15:29:56.172688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 98
15.8%
6 76
12.2%
- 76
12.2%
0 76
12.2%
4 53
8.5%
3 47
7.6%
1 45
7.2%
8 44
7.1%
5 43
6.9%
7 37
 
6.0%
Other values (3) 26
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 542
87.3%
Dash Punctuation 76
 
12.2%
Space Separator 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 98
18.1%
6 76
14.0%
0 76
14.0%
4 53
9.8%
3 47
8.7%
1 45
8.3%
8 44
8.1%
5 43
7.9%
7 37
 
6.8%
9 23
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 621
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 98
15.8%
6 76
12.2%
- 76
12.2%
0 76
12.2%
4 53
8.5%
3 47
7.6%
1 45
7.2%
8 44
7.1%
5 43
6.9%
7 37
 
6.0%
Other values (3) 26
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 621
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 98
15.8%
6 76
12.2%
- 76
12.2%
0 76
12.2%
4 53
8.5%
3 47
7.6%
1 45
7.2%
8 44
7.1%
5 43
6.9%
7 37
 
6.0%
Other values (3) 26
 
4.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

소재지우편번호
Categorical

Distinct37
Distinct (%)28.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
54 
158050
15 
158852
6 
158806
6 
158811
 
4
Other values (32)
45 

Length

Max length7
Median length6
Mean length5.2
Min length4

Unique

Unique24 ?
Unique (%)18.5%

Sample

1st row158811
2nd row158864
3rd row158050
4th row158050
5th row158-808

Common Values

ValueCountFrequency (%)
<NA> 54
41.5%
158050 15
 
11.5%
158852 6
 
4.6%
158806 6
 
4.6%
158811 4
 
3.1%
158857 4
 
3.1%
158735 3
 
2.3%
158742 3
 
2.3%
158723 3
 
2.3%
158808 2
 
1.5%
Other values (27) 30
23.1%

Length

2024-05-11T15:29:56.386702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 54
41.5%
158050 15
 
11.5%
158852 6
 
4.6%
158806 6
 
4.6%
158811 4
 
3.1%
158857 4
 
3.1%
158735 3
 
2.3%
158742 3
 
2.3%
158723 3
 
2.3%
158070 2
 
1.5%
Other values (27) 30
23.1%

지번주소
Text

Distinct126
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:29:56.679941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length27.223077
Min length16

Characters and Unicode

Total characters3539
Distinct characters130
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)93.8%

Sample

1st row서울특별시 양천구 목동 606-15번지 1층
2nd row서울특별시 양천구 신정동 1190-5번지
3rd row서울특별시 양천구 목동 917-1번지
4th row서울특별시 양천구 목동 909-6번지 우방B/D403호
5th row서울특별시 양천구 목동 515-1 홍조빌딩2층
ValueCountFrequency (%)
서울특별시 130
19.0%
양천구 129
18.9%
목동 66
 
9.6%
신정동 50
 
7.3%
신월동 13
 
1.9%
1층 9
 
1.3%
2층 7
 
1.0%
현대41타워 6
 
0.9%
923-14번지 5
 
0.7%
현대월드타워 5
 
0.7%
Other values (214) 264
38.6%
2024-05-11T15:29:57.235226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
610
 
17.2%
1 182
 
5.1%
동 150
 
4.2%
시 134
 
3.8%
양 134
 
3.8%
천 133
 
3.8%
서 131
 
3.7%
구 131
 
3.7%
특 130
 
3.7%
별 130
 
3.7%
Other values (120) 1674
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2014
56.9%
Decimal Number 788
 
22.3%
Space Separator 610
 
17.2%
Dash Punctuation 114
 
3.2%
Uppercase Letter 10
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 150
 
7.4%
시 134
 
6.7%
양 134
 
6.7%
천 133
 
6.6%
서 131
 
6.5%
구 131
 
6.5%
특 130
 
6.5%
별 130
 
6.5%
울 130
 
6.5%
지 84
 
4.2%
Other values (96) 727
36.1%
Decimal Number
ValueCountFrequency (%)
1 182
23.1%
9 101
12.8%
2 99
12.6%
0 94
11.9%
4 65
 
8.2%
3 65
 
8.2%
6 56
 
7.1%
7 49
 
6.2%
5 47
 
6.0%
8 30
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 2
20.0%
O 1
10.0%
M 1
10.0%
U 1
10.0%
Y 1
10.0%
E 1
10.0%
D 1
10.0%
K 1
10.0%
T 1
10.0%
Other Punctuation
ValueCountFrequency (%)
& 1
33.3%
/ 1
33.3%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2014
56.9%
Common 1515
42.8%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 150
 
7.4%
시 134
 
6.7%
양 134
 
6.7%
천 133
 
6.6%
서 131
 
6.5%
구 131
 
6.5%
특 130
 
6.5%
별 130
 
6.5%
울 130
 
6.5%
지 84
 
4.2%
Other values (96) 727
36.1%
Common
ValueCountFrequency (%)
610
40.3%
1 182
 
12.0%
- 114
 
7.5%
9 101
 
6.7%
2 99
 
6.5%
0 94
 
6.2%
4 65
 
4.3%
3 65
 
4.3%
6 56
 
3.7%
7 49
 
3.2%
Other values (5) 80
 
5.3%
Latin
ValueCountFrequency (%)
B 2
20.0%
O 1
10.0%
M 1
10.0%
U 1
10.0%
Y 1
10.0%
E 1
10.0%
D 1
10.0%
K 1
10.0%
T 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2014
56.9%
ASCII 1525
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
610
40.0%
1 182
 
11.9%
- 114
 
7.5%
9 101
 
6.6%
2 99
 
6.5%
0 94
 
6.2%
4 65
 
4.3%
3 65
 
4.3%
6 56
 
3.7%
7 49
 
3.2%
Other values (14) 90
 
5.9%
Hangul
ValueCountFrequency (%)
동 150
 
7.4%
시 134
 
6.7%
양 134
 
6.7%
천 133
 
6.6%
서 131
 
6.5%
구 131
 
6.5%
특 130
 
6.5%
별 130
 
6.5%
울 130
 
6.5%
지 84
 
4.2%
Other values (96) 727
36.1%

도로명주소
Text

MISSING 

Distinct123
Distinct (%)96.1%
Missing2
Missing (%)1.5%
Memory size1.1 KiB
2024-05-11T15:29:57.539870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length33.390625
Min length22

Characters and Unicode

Total characters4274
Distinct characters152
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)92.2%

Sample

1st row서울특별시 양천구 등촌로 232 (목동,1층)
2nd row서울특별시 양천구 중앙로 273 (신정동)
3rd row서울특별시 양천구 목동서로 159-1 (목동)
4th row서울특별시 양천구 목동동로 431 (목동,우방B/D403호)
5th row서울특별시 양천구 공항대로 636 (목동,홍조빌딩2층)
ValueCountFrequency (%)
서울특별시 128
 
15.8%
양천구 127
 
15.6%
목동 41
 
5.0%
신정동 37
 
4.6%
목동서로 21
 
2.6%
목동동로 21
 
2.6%
1층 14
 
1.7%
오목로 11
 
1.4%
2층 9
 
1.1%
신월동 9
 
1.1%
Other values (262) 394
48.5%
2024-05-11T15:29:57.978561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
715
 
16.7%
동 242
 
5.7%
1 165
 
3.9%
목 161
 
3.8%
서 152
 
3.6%
, 147
 
3.4%
양 134
 
3.1%
시 132
 
3.1%
천 131
 
3.1%
로 130
 
3.0%
Other values (142) 2165
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2427
56.8%
Space Separator 715
 
16.7%
Decimal Number 694
 
16.2%
Other Punctuation 149
 
3.5%
Open Punctuation 128
 
3.0%
Close Punctuation 128
 
3.0%
Dash Punctuation 21
 
0.5%
Uppercase Letter 12
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 242
 
10.0%
목 161
 
6.6%
서 152
 
6.3%
양 134
 
5.5%
시 132
 
5.4%
천 131
 
5.4%
로 130
 
5.4%
구 129
 
5.3%
울 128
 
5.3%
별 128
 
5.3%
Other values (116) 960
39.6%
Decimal Number
ValueCountFrequency (%)
1 165
23.8%
2 127
18.3%
3 94
13.5%
0 82
11.8%
4 45
 
6.5%
7 45
 
6.5%
9 43
 
6.2%
6 38
 
5.5%
5 37
 
5.3%
8 18
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
K 2
16.7%
T 2
16.7%
B 2
16.7%
M 1
8.3%
Y 1
8.3%
O 1
8.3%
U 1
8.3%
E 1
8.3%
D 1
8.3%
Other Punctuation
ValueCountFrequency (%)
, 147
98.7%
& 1
 
0.7%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
715
100.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2427
56.8%
Common 1835
42.9%
Latin 12
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 242
 
10.0%
목 161
 
6.6%
서 152
 
6.3%
양 134
 
5.5%
시 132
 
5.4%
천 131
 
5.4%
로 130
 
5.4%
구 129
 
5.3%
울 128
 
5.3%
별 128
 
5.3%
Other values (116) 960
39.6%
Common
ValueCountFrequency (%)
715
39.0%
1 165
 
9.0%
, 147
 
8.0%
( 128
 
7.0%
) 128
 
7.0%
2 127
 
6.9%
3 94
 
5.1%
0 82
 
4.5%
4 45
 
2.5%
7 45
 
2.5%
Other values (7) 159
 
8.7%
Latin
ValueCountFrequency (%)
K 2
16.7%
T 2
16.7%
B 2
16.7%
M 1
8.3%
Y 1
8.3%
O 1
8.3%
U 1
8.3%
E 1
8.3%
D 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2427
56.8%
ASCII 1847
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
715
38.7%
1 165
 
8.9%
, 147
 
8.0%
( 128
 
6.9%
) 128
 
6.9%
2 127
 
6.9%
3 94
 
5.1%
0 82
 
4.4%
4 45
 
2.4%
7 45
 
2.4%
Other values (16) 171
 
9.3%
Hangul
ValueCountFrequency (%)
동 242
 
10.0%
목 161
 
6.6%
서 152
 
6.3%
양 134
 
5.5%
시 132
 
5.4%
천 131
 
5.4%
로 130
 
5.4%
구 129
 
5.3%
울 128
 
5.3%
별 128
 
5.3%
Other values (116) 960
39.6%

도로명우편번호
Text

MISSING 

Distinct55
Distinct (%)50.9%
Missing22
Missing (%)16.9%
Memory size1.1 KiB
2024-05-11T15:29:58.233288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0555556
Min length5

Characters and Unicode

Total characters546
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

Unique36 ?
Unique (%)33.3%

Sample

1st row07968
2nd row07997
3rd row07962
4th row08014
5th row07997
ValueCountFrequency (%)
07997 7
 
6.5%
07983 6
 
5.6%
07995 6
 
5.6%
08014 5
 
4.6%
07945 5
 
4.6%
07968 5
 
4.6%
08026 4
 
3.7%
08006 4
 
3.7%
08023 4
 
3.7%
07946 4
 
3.7%
Other values (45) 58
53.7%
2024-05-11T15:29:58.667385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 166
30.4%
9 82
15.0%
7 78
14.3%
8 77
14.1%
5 30
 
5.5%
6 26
 
4.8%
1 24
 
4.4%
4 24
 
4.4%
2 24
 
4.4%
3 14
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 545
99.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 166
30.5%
9 82
15.0%
7 78
14.3%
8 77
14.1%
5 30
 
5.5%
6 26
 
4.8%
1 24
 
4.4%
4 24
 
4.4%
2 24
 
4.4%
3 14
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 166
30.4%
9 82
15.0%
7 78
14.3%
8 77
14.1%
5 30
 
5.5%
6 26
 
4.8%
1 24
 
4.4%
4 24
 
4.4%
2 24
 
4.4%
3 14
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 166
30.4%
9 82
15.0%
7 78
14.3%
8 77
14.1%
5 30
 
5.5%
6 26
 
4.8%
1 24
 
4.4%
4 24
 
4.4%
2 24
 
4.4%
3 14
 
2.6%

사업장명
Text

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:29:58.921154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length8.7307692
Min length3

Characters and Unicode

Total characters1135
Distinct characters239
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st row(주)예일항공여행사
2nd row(주)파란들문화여행
3rd row주)엘지홈쇼핑
4th row(주)파파항공여행사
5th row(주)출발세계여행
ValueCountFrequency (%)
주식회사 19
 
11.4%
여행사 4
 
2.4%
tour 2
 
1.2%
트래블 2
 
1.2%
주)예일항공여행사 1
 
0.6%
히든코리아 1
 
0.6%
하나웰서비스 1
 
0.6%
서울에어서비스(주 1
 
0.6%
일교기술정보시스템 1
 
0.6%
이편한통합라이프 1
 
0.6%
Other values (133) 133
80.1%
2024-05-11T15:29:59.325309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 92
 
8.1%
) 78
 
6.9%
( 71
 
6.3%
사 56
 
4.9%
행 48
 
4.2%
여 46
 
4.1%
36
 
3.2%
어 36
 
3.2%
투 35
 
3.1%
이 26
 
2.3%
Other values (229) 611
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 894
78.8%
Close Punctuation 78
 
6.9%
Open Punctuation 71
 
6.3%
Uppercase Letter 42
 
3.7%
Space Separator 36
 
3.2%
Lowercase Letter 8
 
0.7%
Decimal Number 5
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 92
 
10.3%
사 56
 
6.3%
행 48
 
5.4%
여 46
 
5.1%
어 36
 
4.0%
투 35
 
3.9%
이 26
 
2.9%
스 24
 
2.7%
회 19
 
2.1%
식 19
 
2.1%
Other values (198) 493
55.1%
Uppercase Letter
ValueCountFrequency (%)
R 6
14.3%
U 5
11.9%
T 5
11.9%
O 5
11.9%
A 4
9.5%
D 3
7.1%
E 3
7.1%
B 2
 
4.8%
C 2
 
4.8%
L 2
 
4.8%
Other values (5) 5
11.9%
Lowercase Letter
ValueCountFrequency (%)
g 1
12.5%
o 1
12.5%
u 1
12.5%
r 1
12.5%
e 1
12.5%
s 1
12.5%
i 1
12.5%
n 1
12.5%
Decimal Number
ValueCountFrequency (%)
0 2
40.0%
2 1
20.0%
4 1
20.0%
3 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 894
78.8%
Common 191
 
16.8%
Latin 50
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 92
 
10.3%
사 56
 
6.3%
행 48
 
5.4%
여 46
 
5.1%
어 36
 
4.0%
투 35
 
3.9%
이 26
 
2.9%
스 24
 
2.7%
회 19
 
2.1%
식 19
 
2.1%
Other values (198) 493
55.1%
Latin
ValueCountFrequency (%)
R 6
12.0%
U 5
 
10.0%
T 5
 
10.0%
O 5
 
10.0%
A 4
 
8.0%
D 3
 
6.0%
E 3
 
6.0%
B 2
 
4.0%
C 2
 
4.0%
L 2
 
4.0%
Other values (13) 13
26.0%
Common
ValueCountFrequency (%)
) 78
40.8%
( 71
37.2%
36
18.8%
0 2
 
1.0%
2 1
 
0.5%
& 1
 
0.5%
4 1
 
0.5%
3 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 894
78.8%
ASCII 241
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 92
 
10.3%
사 56
 
6.3%
행 48
 
5.4%
여 46
 
5.1%
어 36
 
4.0%
투 35
 
3.9%
이 26
 
2.9%
스 24
 
2.7%
회 19
 
2.1%
식 19
 
2.1%
Other values (198) 493
55.1%
ASCII
ValueCountFrequency (%)
) 78
32.4%
( 71
29.5%
36
14.9%
R 6
 
2.5%
U 5
 
2.1%
T 5
 
2.1%
O 5
 
2.1%
A 4
 
1.7%
D 3
 
1.2%
E 3
 
1.2%
Other values (21) 25
 
10.4%

최종수정일자
Date

Distinct127
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2002-10-22 17:51:16
Maximum2024-05-08 09:42:06
2024-05-11T15:29:59.477562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:59.644163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
U
74 
I
56 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 74
56.9%
I 56
43.1%

Length

2024-05-11T15:29:59.924646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:00.318777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 74
56.9%
i 56
43.1%

데이터갱신일자
Date

Distinct60
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T15:30:00.618351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:30:00.899852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)69.5%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean188020.06
Minimum184597.45
Maximum189709.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:01.218195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184597.45
5-th percentile185281
Q1187674.33
median188420.09
Q3188829.17
95-th percentile189151.21
Maximum189709.8
Range5112.3539
Interquartile range (IQR)1154.8466

Descriptive statistics

Standard deviation1125.7216
Coefficient of variation (CV)0.0059872417
Kurtosis1.1838452
Mean188020.06
Median Absolute Deviation (MAD)532.97602
Skewness-1.3088952
Sum24066568
Variance1267249
MonotonicityNot monotonic
2024-05-11T15:30:01.476743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188953.066831076 7
 
5.4%
188584.345447275 5
 
3.8%
189151.208015925 5
 
3.8%
186852.153851552 4
 
3.1%
188555.643850446 3
 
2.3%
188729.190478822 3
 
2.3%
187916.254332614 3
 
2.3%
188352.6433345 3
 
2.3%
188965.738829492 3
 
2.3%
188493.762740612 2
 
1.5%
Other values (79) 90
69.2%
ValueCountFrequency (%)
184597.4496425 1
0.8%
184817.116668717 1
0.8%
184952.58622774 1
0.8%
185023.275606938 1
0.8%
185179.050770965 1
0.8%
185221.95790954 1
0.8%
185231.4166243 1
0.8%
185373.088854834 1
0.8%
185562.527967436 1
0.8%
185809.765126281 1
0.8%
ValueCountFrequency (%)
189709.803505321 1
 
0.8%
189576.475334065 1
 
0.8%
189430.977860634 1
 
0.8%
189348.372526225 1
 
0.8%
189151.208015925 5
3.8%
189128.248867296 1
 
0.8%
189086.756192965 1
 
0.8%
189042.496526196 1
 
0.8%
189039.009553549 1
 
0.8%
189038.037681199 1
 
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)69.5%
Missing2
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean447355.66
Minimum445478.4
Maximum449789.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:01.703937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445478.4
5-th percentile446051.81
Q1446714.97
median447132.17
Q3447895.25
95-th percentile449638.84
Maximum449789.61
Range4311.2181
Interquartile range (IQR)1180.2777

Descriptive statistics

Standard deviation1074.8618
Coefficient of variation (CV)0.0024027007
Kurtosis-0.0469634
Mean447355.66
Median Absolute Deviation (MAD)536.40219
Skewness0.81284565
Sum57261525
Variance1155327.8
MonotonicityNot monotonic
2024-05-11T15:30:01.869475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447333.569187997 7
 
5.4%
447255.070457495 5
 
3.8%
448200.067716589 5
 
3.8%
446714.974104065 4
 
3.1%
446305.287756674 3
 
2.3%
447572.610039376 3
 
2.3%
449683.219205227 3
 
2.3%
445478.395298097 3
 
2.3%
448365.713974147 3
 
2.3%
447213.539278579 2
 
1.5%
Other values (79) 90
69.2%
ValueCountFrequency (%)
445478.395298097 3
2.3%
445825.399064037 1
 
0.8%
445984.041714478 1
 
0.8%
446003.941216623 1
 
0.8%
446030.714521005 1
 
0.8%
446090.979359781 1
 
0.8%
446099.600366308 1
 
0.8%
446115.838905266 1
 
0.8%
446116.629313272 1
 
0.8%
446123.034540646 1
 
0.8%
ValueCountFrequency (%)
449789.613381329 1
 
0.8%
449785.227427003 2
1.5%
449701.802558519 1
 
0.8%
449683.219205227 3
2.3%
449556.4108025 1
 
0.8%
449554.442166594 1
 
0.8%
449399.489126654 1
 
0.8%
449394.675249633 1
 
0.8%
449389.208595744 1
 
0.8%
449383.141430143 1
 
0.8%

문화체육업종명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
국내외여행업
85 
<NA>
45 

Length

Max length6
Median length6
Mean length5.3076923
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 85
65.4%
<NA> 45
34.6%

Length

2024-05-11T15:30:02.460125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:02.628856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 85
65.4%
na 45
34.6%

문화사업자구분명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
88 
관광사업
42 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 88
67.7%
관광사업 42
32.3%

Length

2024-05-11T15:30:02.819093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:02.993869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 88
67.7%
관광사업 42
32.3%

지역구분명
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing125
Missing (%)96.2%
Memory size1.1 KiB
2024-05-11T15:30:03.160257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.8
Min length4

Characters and Unicode

Total characters24
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row상업지역
2nd row상업지역
3rd row일반주거지역
4th row주거지역
5th row일반상업지역
ValueCountFrequency (%)
상업지역 2
40.0%
일반주거지역 1
20.0%
주거지역 1
20.0%
일반상업지역 1
20.0%
2024-05-11T15:30:03.616141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 5
20.8%
역 5
20.8%
상 3
12.5%
업 3
12.5%
일 2
 
8.3%
반 2
 
8.3%
주 2
 
8.3%
거 2
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 5
20.8%
역 5
20.8%
상 3
12.5%
업 3
12.5%
일 2
 
8.3%
반 2
 
8.3%
주 2
 
8.3%
거 2
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 5
20.8%
역 5
20.8%
상 3
12.5%
업 3
12.5%
일 2
 
8.3%
반 2
 
8.3%
주 2
 
8.3%
거 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 5
20.8%
역 5
20.8%
상 3
12.5%
업 3
12.5%
일 2
 
8.3%
반 2
 
8.3%
주 2
 
8.3%
거 2
 
8.3%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)77.8%
Missing121
Missing (%)93.1%
Infinite0
Infinite (%)0.0%
Mean11.777778
Minimum0
Maximum46
Zeros3
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:03.785814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q316
95-th percentile37.6
Maximum46
Range46
Interquartile range (IQR)16

Descriptive statistics

Standard deviation15.368619
Coefficient of variation (CV)1.3048827
Kurtosis2.4673852
Mean11.777778
Median Absolute Deviation (MAD)5
Skewness1.6283049
Sum106
Variance236.19444
MonotonicityNot monotonic
2024-05-11T15:30:03.943189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3
 
2.3%
46 1
 
0.8%
5 1
 
0.8%
25 1
 
0.8%
10 1
 
0.8%
4 1
 
0.8%
16 1
 
0.8%
(Missing) 121
93.1%
ValueCountFrequency (%)
0 3
2.3%
4 1
 
0.8%
5 1
 
0.8%
10 1
 
0.8%
16 1
 
0.8%
25 1
 
0.8%
46 1
 
0.8%
ValueCountFrequency (%)
46 1
 
0.8%
25 1
 
0.8%
16 1
 
0.8%
10 1
 
0.8%
5 1
 
0.8%
4 1
 
0.8%
0 3
2.3%

주변환경명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
123 
주택가주변
 
4
아파트지역
 
2
기타
 
1

Length

Max length5
Median length4
Mean length4.0307692
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 123
94.6%
주택가주변 4
 
3.1%
아파트지역 2
 
1.5%
기타 1
 
0.8%

Length

2024-05-11T15:30:04.123702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:04.311075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 123
94.6%
주택가주변 4
 
3.1%
아파트지역 2
 
1.5%
기타 1
 
0.8%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

보험기관명
Categorical

Distinct23
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
81 
서울보증보험주식회사
9 
서울보증보험
 
8
한국관광협회중앙회
 
4
서울보증보험(3천만원)
 
4
Other values (18)
24 

Length

Max length16
Median length4
Mean length6.2230769
Min length4

Unique

Unique13 ?
Unique (%)10.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 81
62.3%
서울보증보험주식회사 9
 
6.9%
서울보증보험 8
 
6.2%
한국관광협회중앙회 4
 
3.1%
서울보증보험(3천만원) 4
 
3.1%
서울보증보험(삼천만원) 3
 
2.3%
한국관광협회중앙회 여행공제회 2
 
1.5%
한국관광협회 2
 
1.5%
서울시관광협회 2
 
1.5%
서울보증보험(사천만원) 2
 
1.5%
Other values (13) 13
 
10.0%

Length

2024-05-11T15:30:04.508771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 81
60.4%
서울보증보험주식회사 9
 
6.7%
서울보증보험 8
 
6.0%
한국관광협회중앙회 7
 
5.2%
서울보증보험(3천만원 4
 
3.0%
서울보증보험(삼천만원 3
 
2.2%
여행공제회 2
 
1.5%
한국관광협회 2
 
1.5%
서울시관광협회 2
 
1.5%
서울보증보험(사천만원 2
 
1.5%
Other values (14) 14
 
10.4%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
118 
근린생활시설
 
8
사무실
 
3
아파트
 
1

Length

Max length6
Median length4
Mean length4.0923077
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 118
90.8%
근린생활시설 8
 
6.2%
사무실 3
 
2.3%
아파트 1
 
0.8%

Length

2024-05-11T15:30:04.706626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:04.866669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 118
90.8%
근린생활시설 8
 
6.2%
사무실 3
 
2.3%
아파트 1
 
0.8%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)72.7%
Missing119
Missing (%)91.5%
Infinite0
Infinite (%)0.0%
Mean8.9090909
Minimum0
Maximum41
Zeros3
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:05.050349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q312
95-th percentile30.5
Maximum41
Range41
Interquartile range (IQR)11

Descriptive statistics

Standard deviation12.485628
Coefficient of variation (CV)1.4014481
Kurtosis4.136293
Mean8.9090909
Median Absolute Deviation (MAD)4
Skewness1.993347
Sum98
Variance155.89091
MonotonicityNot monotonic
2024-05-11T15:30:05.245471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 3
 
2.3%
4 2
 
1.5%
41 1
 
0.8%
20 1
 
0.8%
9 1
 
0.8%
15 1
 
0.8%
2 1
 
0.8%
3 1
 
0.8%
(Missing) 119
91.5%
ValueCountFrequency (%)
0 3
2.3%
2 1
 
0.8%
3 1
 
0.8%
4 2
1.5%
9 1
 
0.8%
15 1
 
0.8%
20 1
 
0.8%
41 1
 
0.8%
ValueCountFrequency (%)
41 1
 
0.8%
20 1
 
0.8%
15 1
 
0.8%
9 1
 
0.8%
4 2
1.5%
3 1
 
0.8%
2 1
 
0.8%
0 3
2.3%

지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
121 
1
 
3
0
 
3
5
 
2
2
 
1

Length

Max length4
Median length4
Mean length3.7923077
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
93.1%
1 3
 
2.3%
0 3
 
2.3%
5 2
 
1.5%
2 1
 
0.8%

Length

2024-05-11T15:30:05.454293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:05.650321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
93.1%
1 3
 
2.3%
0 3
 
2.3%
5 2
 
1.5%
2 1
 
0.8%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:05.871299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:06.068310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:06.426381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:06.622879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

영문상호명
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing126
Missing (%)96.9%
Memory size1.1 KiB
2024-05-11T15:30:06.832104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21.5
Mean length20.25
Min length15

Characters and Unicode

Total characters81
Distinct characters31
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 rowSABYUL TRAVEL Co., Ltd.
2nd rowSeoulAirService.Co.,Ltd
3rd rowNawago.Co.,Ltd.
4th rowROYAL MILE Co., Ltd.
ValueCountFrequency (%)
co 2
20.0%
ltd 2
20.0%
sabyul 1
10.0%
travel 1
10.0%
seoulairservice.co.,ltd 1
10.0%
nawago.co.,ltd 1
10.0%
royal 1
10.0%
mile 1
10.0%
2024-05-11T15:30:07.394726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9
 
11.1%
L 8
 
9.9%
6
 
7.4%
o 6
 
7.4%
t 4
 
4.9%
C 4
 
4.9%
d 4
 
4.9%
A 4
 
4.9%
, 4
 
4.9%
e 3
 
3.7%
Other values (21) 29
35.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 33
40.7%
Lowercase Letter 29
35.8%
Other Punctuation 13
 
16.0%
Space Separator 6
 
7.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 8
24.2%
C 4
12.1%
A 4
12.1%
S 3
 
9.1%
E 2
 
6.1%
Y 2
 
6.1%
R 2
 
6.1%
U 1
 
3.0%
B 1
 
3.0%
T 1
 
3.0%
Other values (5) 5
15.2%
Lowercase Letter
ValueCountFrequency (%)
o 6
20.7%
t 4
13.8%
d 4
13.8%
e 3
10.3%
a 2
 
6.9%
i 2
 
6.9%
r 2
 
6.9%
u 1
 
3.4%
l 1
 
3.4%
v 1
 
3.4%
Other values (3) 3
10.3%
Other Punctuation
ValueCountFrequency (%)
. 9
69.2%
, 4
30.8%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62
76.5%
Common 19
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 8
 
12.9%
o 6
 
9.7%
t 4
 
6.5%
C 4
 
6.5%
d 4
 
6.5%
A 4
 
6.5%
e 3
 
4.8%
S 3
 
4.8%
E 2
 
3.2%
Y 2
 
3.2%
Other values (18) 22
35.5%
Common
ValueCountFrequency (%)
. 9
47.4%
6
31.6%
, 4
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9
 
11.1%
L 8
 
9.9%
6
 
7.4%
o 6
 
7.4%
t 4
 
4.9%
C 4
 
4.9%
d 4
 
4.9%
A 4
 
4.9%
, 4
 
4.9%
e 3
 
3.7%
Other values (21) 29
35.8%

영문상호주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing126
Missing (%)96.9%
Memory size1.1 KiB
2024-05-11T15:30:07.625712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters96
Distinct characters25
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

Unique4 ?
Unique (%)100.0%

Sample

1st rowOUTBOUND TRAVEL BUSINESS
2nd rowOverseas travel business
3rd rowOverseas travle business
4th rowOVERSEAS TRAVEL BUSINESS
ValueCountFrequency (%)
business 4
33.3%
travel 3
25.0%
overseas 3
25.0%
outbound 1
 
8.3%
travle 1
 
8.3%
2024-05-11T15:30:08.126441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 10
 
10.4%
S 8
 
8.3%
8
 
8.3%
e 8
 
8.3%
E 6
 
6.2%
O 5
 
5.2%
U 4
 
4.2%
v 4
 
4.2%
r 4
 
4.2%
a 4
 
4.2%
Other values (15) 35
36.5%

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 8
17.4%
E 6
13.0%
O 5
10.9%
U 4
8.7%
B 3
 
6.5%
A 3
 
6.5%
V 3
 
6.5%
N 3
 
6.5%
R 3
 
6.5%
T 3
 
6.5%
Other values (3) 5
10.9%
Lowercase Letter
ValueCountFrequency (%)
s 10
23.8%
e 8
19.0%
v 4
 
9.5%
r 4
 
9.5%
a 4
 
9.5%
l 2
 
4.8%
i 2
 
4.8%
u 2
 
4.8%
b 2
 
4.8%
n 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 8
 
9.1%
e 8
 
9.1%
E 6
 
6.8%
O 5
 
5.7%
U 4
 
4.5%
v 4
 
4.5%
r 4
 
4.5%
a 4
 
4.5%
B 3
 
3.4%
Other values (14) 32
36.4%
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 8
 
8.3%
8
 
8.3%
e 8
 
8.3%
E 6
 
6.2%
O 5
 
5.2%
U 4
 
4.2%
v 4
 
4.2%
r 4
 
4.2%
a 4
 
4.2%
Other values (15) 35
36.5%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:08.419551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:08.638631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:08.836723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:09.022697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:09.247724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:09.414446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:09.565157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:09.746551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:09.977023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:10.162871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)77.5%
Missing90
Missing (%)69.2%
Infinite0
Infinite (%)0.0%
Mean61.65125
Minimum0
Maximum555
Zeros6
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:10.321591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median38.875
Q367.35
95-th percentile198.1
Maximum555
Range555
Interquartile range (IQR)47.35

Descriptive statistics

Standard deviation92.374169
Coefficient of variation (CV)1.4983341
Kurtosis21.439715
Mean61.65125
Median Absolute Deviation (MAD)22.455
Skewness4.2285803
Sum2466.05
Variance8532.987
MonotonicityNot monotonic
2024-05-11T15:30:10.529461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 6
 
4.6%
33.0 2
 
1.5%
20.0 2
 
1.5%
66.0 2
 
1.5%
30.0 2
 
1.5%
38.22 1
 
0.8%
16.34 1
 
0.8%
71.4 1
 
0.8%
91.0 1
 
0.8%
555.0 1
 
0.8%
Other values (21) 21
 
16.2%
(Missing) 90
69.2%
ValueCountFrequency (%)
0.0 6
4.6%
7.0 1
 
0.8%
16.34 1
 
0.8%
16.5 1
 
0.8%
20.0 2
 
1.5%
21.81 1
 
0.8%
30.0 2
 
1.5%
31.0 1
 
0.8%
31.4 1
 
0.8%
33.0 2
 
1.5%
ValueCountFrequency (%)
555.0 1
0.8%
200.0 1
0.8%
198.0 1
0.8%
128.76 1
0.8%
104.0 1
0.8%
91.0 1
0.8%
83.0 1
0.8%
79.34 1
0.8%
74.0 1
0.8%
71.4 1
0.8%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
127 
0
 
3

Length

Max length4
Median length4
Mean length3.9307692
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> 127
97.7%
0 3
 
2.3%

Length

2024-05-11T15:30:10.751194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:30:10.952629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 127
97.7%
0 3
 
2.3%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

자본금
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)46.9%
Missing66
Missing (%)50.8%
Infinite0
Infinite (%)0.0%
Mean96546494
Minimum0
Maximum3.0319704 × 108
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:11.149877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13000000
Q160000000
median1 × 108
Q31.0125 × 108
95-th percentile2.2975 × 108
Maximum3.0319704 × 108
Range3.0319704 × 108
Interquartile range (IQR)41250000

Descriptive statistics

Standard deviation64000802
Coefficient of variation (CV)0.66290136
Kurtosis3.2926841
Mean96546494
Median Absolute Deviation (MAD)40000000
Skewness1.5764595
Sum6.1789756 × 109
Variance4.0961026 × 1015
MonotonicityNot monotonic
2024-05-11T15:30:11.382295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100000000 18
 
13.8%
60000000 9
 
6.9%
150000000 6
 
4.6%
30000000 3
 
2.3%
10000000 2
 
1.5%
300000000 2
 
1.5%
235000000 1
 
0.8%
90000000 1
 
0.8%
45000000 1
 
0.8%
60320326 1
 
0.8%
Other values (20) 20
 
15.4%
(Missing) 66
50.8%
ValueCountFrequency (%)
0 1
 
0.8%
6000000 1
 
0.8%
10000000 2
 
1.5%
30000000 3
 
2.3%
30008034 1
 
0.8%
32000000 1
 
0.8%
45000000 1
 
0.8%
50000000 1
 
0.8%
60000000 9
6.9%
60068945 1
 
0.8%
ValueCountFrequency (%)
303197040 1
 
0.8%
300000000 2
 
1.5%
235000000 1
 
0.8%
200000000 1
 
0.8%
150000000 6
4.6%
140661820 1
 
0.8%
140000000 1
 
0.8%
130000000 1
 
0.8%
120000000 1
 
0.8%
105000000 1
 
0.8%

보험시작일자
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)100.0%
Missing77
Missing (%)59.2%
Infinite0
Infinite (%)0.0%
Mean20121744
Minimum20030124
Maximum20211218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:11.620763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030124
5-th percentile20046484
Q120080210
median20140116
Q320160920
95-th percentile20204671
Maximum20211218
Range181094
Interquartile range (IQR)80710

Descriptive statistics

Standard deviation54752.895
Coefficient of variation (CV)0.002721081
Kurtosis-1.3683647
Mean20121744
Median Absolute Deviation (MAD)49587
Skewness-0.069754631
Sum1.0664524 × 109
Variance2.9978795 × 109
MonotonicityNot monotonic
2024-05-11T15:30:11.866843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150323 1
 
0.8%
20160426 1
 
0.8%
20150711 1
 
0.8%
20150409 1
 
0.8%
20211218 1
 
0.8%
20160824 1
 
0.8%
20130801 1
 
0.8%
20160920 1
 
0.8%
20200218 1
 
0.8%
20131202 1
 
0.8%
Other values (43) 43
33.1%
(Missing) 77
59.2%
ValueCountFrequency (%)
20030124 1
0.8%
20030421 1
0.8%
20041021 1
0.8%
20050126 1
0.8%
20050223 1
0.8%
20050302 1
0.8%
20050509 1
0.8%
20051025 1
0.8%
20051214 1
0.8%
20060504 1
0.8%
ValueCountFrequency (%)
20211218 1
0.8%
20210610 1
0.8%
20210325 1
0.8%
20200901 1
0.8%
20200218 1
0.8%
20181113 1
0.8%
20180910 1
0.8%
20180512 1
0.8%
20180316 1
0.8%
20180106 1
0.8%

보험종료일자
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)100.0%
Missing77
Missing (%)59.2%
Infinite0
Infinite (%)0.0%
Mean20131915
Minimum20040124
Maximum20221217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:12.155375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040124
5-th percentile20056484
Q120090209
median20150115
Q320170920
95-th percentile20214266
Maximum20221217
Range181093
Interquartile range (IQR)80711

Descriptive statistics

Standard deviation54852.303
Coefficient of variation (CV)0.002724644
Kurtosis-1.3799004
Mean20131915
Median Absolute Deviation (MAD)49586
Skewness-0.076531462
Sum1.0669915 × 109
Variance3.0087752 × 109
MonotonicityNot monotonic
2024-05-11T15:30:12.433655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160323 1
 
0.8%
20170425 1
 
0.8%
20160711 1
 
0.8%
20160408 1
 
0.8%
20221217 1
 
0.8%
20170823 1
 
0.8%
20140731 1
 
0.8%
20170920 1
 
0.8%
20210218 1
 
0.8%
20141201 1
 
0.8%
Other values (43) 43
33.1%
(Missing) 77
59.2%
ValueCountFrequency (%)
20040124 1
0.8%
20040421 1
0.8%
20051021 1
0.8%
20060126 1
0.8%
20060222 1
0.8%
20060302 1
0.8%
20060509 1
0.8%
20061025 1
0.8%
20061214 1
0.8%
20070504 1
0.8%
ValueCountFrequency (%)
20221217 1
0.8%
20220609 1
0.8%
20220324 1
0.8%
20210228 1
0.8%
20210218 1
0.8%
20191112 1
0.8%
20190909 1
0.8%
20190511 1
0.8%
20190315 1
0.8%
20190105 1
0.8%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing130
Missing (%)100.0%
Memory size1.3 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)70.0%
Missing90
Missing (%)69.2%
Infinite0
Infinite (%)0.0%
Mean61.65
Minimum0
Maximum555
Zeros6
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:30:12.675586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median39
Q367.25
95-th percentile198.1
Maximum555
Range555
Interquartile range (IQR)47.25

Descriptive statistics

Standard deviation92.373142
Coefficient of variation (CV)1.4983478
Kurtosis21.441156
Mean61.65
Median Absolute Deviation (MAD)22.5
Skewness4.2288981
Sum2466
Variance8532.7974
MonotonicityNot monotonic
2024-05-11T15:30:12.855612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 6
 
4.6%
33 2
 
1.5%
20 2
 
1.5%
30 2
 
1.5%
40 2
 
1.5%
66 2
 
1.5%
31 2
 
1.5%
53 2
 
1.5%
74 1
 
0.8%
7 1
 
0.8%
Other values (18) 18
 
13.8%
(Missing) 90
69.2%
ValueCountFrequency (%)
0 6
4.6%
7 1
 
0.8%
16 1
 
0.8%
17 1
 
0.8%
20 2
 
1.5%
22 1
 
0.8%
30 2
 
1.5%
31 2
 
1.5%
33 2
 
1.5%
37 1
 
0.8%
ValueCountFrequency (%)
555 1
0.8%
200 1
0.8%
198 1
0.8%
129 1
0.8%
104 1
0.8%
91 1
0.8%
83 1
0.8%
79 1
0.8%
74 1
0.8%
71 1
0.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03140000CDFI226002199300000119930309<NA>3폐업3폐업20060203<NA><NA><NA>02-2652-3361<NA>158811서울특별시 양천구 목동 606-15번지 1층서울특별시 양천구 등촌로 232 (목동,1층)<NA>(주)예일항공여행사2006-03-08 08:54:51I2018-08-31 23:59:59.0<NA>187934.622083449785.227427국내외여행업관광사업<NA><NA><NA><NA>한국관광협회중앙회여행공제회근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2005012620060126<NA><NA>
13140000CDFI226002199600000119960229<NA>3폐업3폐업19960302<NA><NA><NA><NA><NA>158864서울특별시 양천구 신정동 1190-5번지서울특별시 양천구 중앙로 273 (신정동)<NA>(주)파란들문화여행2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>186876.287617446502.706604국내외여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><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
23140000CDFI226002199600000319960803<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 917-1번지서울특별시 양천구 목동서로 159-1 (목동)<NA>주)엘지홈쇼핑2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>188871.512838447348.132133국내외여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><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
33140000CDFI226002199700000119970926<NA>3폐업3폐업19990619<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 909-6번지 우방B/D403호서울특별시 양천구 목동동로 431 (목동,우방B/D403호)<NA>(주)파파항공여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>189709.803505448328.288936국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><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
43140000CDFI22600219980000011998-04-03<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2645-7441<NA>158-808서울특별시 양천구 목동 515-1 홍조빌딩2층서울특별시 양천구 공항대로 636 (목동,홍조빌딩2층)07968(주)출발세계여행2023-03-08 13:25:58U2022-12-02 23:01:00.0<NA>188918.535367449389.208596<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53140000CDFI226002199900000119990430<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158859서울특별시 양천구 신정동 955-8번지서울특별시 양천구 은행정로 49 (신정동)<NA>(주)어드밴스여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>187477.353085446894.478512국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><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
63140000CDFI226002200100000420010808<NA>3폐업3폐업20030410<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 917-9번지서울특별시 양천구 목동동로 293 (목동)<NA>(주)월드징기스칸2003-10-09 16:29:08I2018-08-31 23:59:59.0<NA>188953.066831447333.569188국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73140000CDFI226002200100000720011012<NA>3폐업3폐업20030228<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 923-14번지 드리타워15층19호서울특별시 양천구 목동동로 233-1 (목동,드리타워15층19호)<NA>(주)스피드투어2003-02-28 09:50:42I2018-08-31 23:59:59.0<NA>188584.345447447255.070457국내외여행업관광사업<NA><NA>주택가주변<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
83140000CDFI226002200100000920011224<NA>3폐업3폐업20030211<NA><NA><NA><NA><NA>158811서울특별시 양천구 목동 613-2번지 정원빌딩413호서울특별시 양천구 등촌로 220 (목동,정원빌딩413호)<NA>(주)다님여행사2003-10-09 16:38:33I2018-08-31 23:59:59.0<NA>187916.254333449683.219205국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93140000CDFI226002200100001020010612<NA>3폐업3폐업20210226<NA><NA><NA>2168-3001<NA>158723서울특별시 양천구 목동 917-9 현대41타워서울특별시 양천구 목동동로 293 (목동, 현대41타워)07997(주)투투항공여행사2021-02-26 15:50:09U2021-02-28 02:40:00.0<NA>188953.066831447333.569188국내외여행업<NA><NA><NA><NA><NA>서울보증보험주식회사(4천만원)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2020090120210228<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
1203140000CDFI226002202200000120220203<NA>5제외/삭제/전출15전출20220610<NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 405 목동대림아파트 상가동 지하3호서울특별시 양천구 목동동로12길 23, 상가동 지하3호 (목동, 목동대림아파트)08006(주)킹투어2022-06-10 09:49:16U2021-12-05 23:04:00.0<NA>188815.060184446814.889014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1213140000CDFI226002202200000320111207<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2666-1848<NA><NA>서울특별시 양천구 신정동 911-7서울특별시 양천구 신정중앙로 62, 1층 (신정동)07944주식회사 브이아이피여행사2022-08-10 18:29:06U2021-12-07 23:02:00.0<NA>187436.998527447184.745108<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1223140000CDFI226002202200000420020917<NA>1영업/정상13영업중<NA><NA><NA><NA>027156020<NA><NA>서울특별시 양천구 목동 404-5 오목빌딩서울특별시 양천구 신목로2길 68, 오목빌딩 1층 102호 (목동)08007(주)오즈여행2022-11-17 16:56:47I2021-10-31 22:00:00.0<NA>189086.756193446851.320186<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1233140000CDFI22600220220000052004-09-02<NA>1영업/정상13영업중<NA><NA><NA><NA>02-735-1415<NA><NA>서울특별시 양천구 신정동 1009-6 남부빌딩 203호서울특별시 양천구 신월로 389, 남부빌딩 203호 (신정동)08023(주)석원여행2023-09-05 16:35:09U2022-12-09 00:07:00.0<NA>187925.667554446739.797763<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1243140000CDFI22600220230000012023-02-03<NA>1영업/정상13영업중<NA><NA><NA><NA>02-745-7333<NA><NA>서울특별시 양천구 신정동 1009-4 YOU&ME법조빌딩서울특별시 양천구 신월로 387, YOU&ME법조빌딩 5층 (신정동)08023(주)에듀인애스크2023-02-16 10:57:10U2022-12-01 23:08:00.0<NA>187907.215246446728.591968<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1253140000CDFI22600220230000032023-09-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 996-1서울특별시 양천구 목동로19길 11, 한농빌딩 4층 70호 (신정동)08022(주)헵시바투어2023-11-28 15:02:54U2022-10-31 21:00:00.0<NA>187838.825896446966.459279<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1263140000CDFI22600220240000012024-01-08<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 617-13 목3동시장 고객지원센터서울특별시 양천구 목동중앙북로6길 5, 목3동시장 고객지원센터 3층 (목동)07950놀이문화공동체협동조합(PLAY CULTURE)2024-01-31 15:33:23U2023-12-02 00:02:00.0<NA>188019.68584449554.442167<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1273140000CDFI22600220240000022024-02-28<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 28-6서울특별시 양천구 화곡로 41 (신월동)07900티엔비2024-02-28 13:23:36I2023-12-03 00:01:00.0<NA>184597.449642448604.977024<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1283140000CDFI22600220240000032024-03-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1014-3 법정빌딩서울특별시 양천구 신월로 376, 법정빌딩 801호 (신정동)08087(주)커뮤니케이션애드게이트2024-04-05 10:28:16U2023-12-04 00:07:00.0<NA>187791.46182446647.027913<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1293140000CDFI22600220240000042024-04-25<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 971-20 명성빌딩서울특별시 양천구 중앙로 294, 명성빌딩 616호 (신정동)08026(주)신철마여행사2024-04-29 10:28:40U2023-12-05 00:01:00.0<NA>186852.153852446714.974104<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>