Overview

Dataset statistics

Number of variables60
Number of observations231
Missing cells5228
Missing cells (%)37.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.8 KiB
Average record size in memory517.6 B

Variable types

Categorical24
Text8
DateTime4
Unsupported14
Numeric10

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,문화사업자구분명,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-17589/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (92.2%)Imbalance
지역구분명 is highly imbalanced (80.8%)Imbalance
주변환경명 is highly imbalanced (79.2%)Imbalance
건물용도명 is highly imbalanced (69.0%)Imbalance
기획여행보험시작일자 is highly imbalanced (96.0%)Imbalance
기획여행보험종료일자 is highly imbalanced (96.0%)Imbalance
폐업일자 has 91 (39.4%) missing valuesMissing
휴업시작일자 has 231 (100.0%) missing valuesMissing
휴업종료일자 has 231 (100.0%) missing valuesMissing
재개업일자 has 231 (100.0%) missing valuesMissing
전화번호 has 101 (43.7%) missing valuesMissing
소재지면적 has 231 (100.0%) missing valuesMissing
도로명주소 has 5 (2.2%) missing valuesMissing
도로명우편번호 has 71 (30.7%) missing valuesMissing
업태구분명 has 231 (100.0%) missing valuesMissing
좌표정보(X) has 4 (1.7%) missing valuesMissing
좌표정보(Y) has 4 (1.7%) missing valuesMissing
총층수 has 180 (77.9%) missing valuesMissing
제작취급품목내용 has 231 (100.0%) missing valuesMissing
지상층수 has 179 (77.5%) missing valuesMissing
지하층수 has 182 (78.8%) missing valuesMissing
영문상호명 has 229 (99.1%) missing valuesMissing
영문상호주소 has 229 (99.1%) missing valuesMissing
선박제원 has 231 (100.0%) missing valuesMissing
기념품종류 has 231 (100.0%) missing valuesMissing
시설면적 has 171 (74.0%) missing valuesMissing
놀이기구수내역 has 231 (100.0%) missing valuesMissing
방송시설유무 has 231 (100.0%) missing valuesMissing
발전시설유무 has 231 (100.0%) missing valuesMissing
의무실유무 has 231 (100.0%) missing valuesMissing
안내소유무 has 231 (100.0%) missing valuesMissing
자본금 has 125 (54.1%) missing valuesMissing
보험시작일자 has 126 (54.5%) missing valuesMissing
보험종료일자 has 126 (54.5%) missing valuesMissing
부대시설내역 has 231 (100.0%) missing valuesMissing
시설규모 has 171 (74.0%) missing valuesMissing
관리번호 has unique valuesUnique
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 33 (14.3%) zerosZeros
지상층수 has 33 (14.3%) zerosZeros
지하층수 has 33 (14.3%) zerosZeros
시설면적 has 30 (13.0%) zerosZeros
자본금 has 7 (3.0%) zerosZeros
시설규모 has 30 (13.0%) zerosZeros

Reproduction

Analysis started2024-05-11 06:13:27.839033
Analysis finished2024-05-11 06:13:31.542653
Duration3.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3120000
231 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 231
100.0%

Length

2024-05-11T06:13:31.732463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:32.054549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 231
100.0%

관리번호
Text

UNIQUE 

Distinct231
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T06:13:32.542109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters4620
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

Unique231 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021996000001
2nd rowCDFI2260021996000003
3rd rowCDFI2260021997000001
4th rowCDFI2260021998000001
5th rowCDFI2260021999000002
ValueCountFrequency (%)
cdfi2260021996000001 1
 
0.4%
cdfi2260022020000013 1
 
0.4%
cdfi2260022017000015 1
 
0.4%
cdfi2260022017000016 1
 
0.4%
cdfi2260022017000017 1
 
0.4%
cdfi2260022018000001 1
 
0.4%
cdfi2260022018000003 1
 
0.4%
cdfi2260022018000004 1
 
0.4%
cdfi2260022018000005 1
 
0.4%
cdfi2260022018000006 1
 
0.4%
Other values (221) 221
95.7%
2024-05-11T06:13:33.647213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1840
39.8%
2 1057
22.9%
6 269
 
5.8%
1 248
 
5.4%
C 231
 
5.0%
D 231
 
5.0%
F 231
 
5.0%
I 231
 
5.0%
3 70
 
1.5%
9 54
 
1.2%
Other values (4) 158
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3696
80.0%
Uppercase Letter 924
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1840
49.8%
2 1057
28.6%
6 269
 
7.3%
1 248
 
6.7%
3 70
 
1.9%
9 54
 
1.5%
4 48
 
1.3%
8 40
 
1.1%
7 37
 
1.0%
5 33
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 231
25.0%
D 231
25.0%
F 231
25.0%
I 231
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3696
80.0%
Latin 924
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1840
49.8%
2 1057
28.6%
6 269
 
7.3%
1 248
 
6.7%
3 70
 
1.9%
9 54
 
1.5%
4 48
 
1.3%
8 40
 
1.1%
7 37
 
1.0%
5 33
 
0.9%
Latin
ValueCountFrequency (%)
C 231
25.0%
D 231
25.0%
F 231
25.0%
I 231
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1840
39.8%
2 1057
22.9%
6 269
 
5.8%
1 248
 
5.4%
C 231
 
5.0%
D 231
 
5.0%
F 231
 
5.0%
I 231
 
5.0%
3 70
 
1.5%
9 54
 
1.2%
Other values (4) 158
 
3.4%
Distinct227
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1995-09-12 00:00:00
Maximum2024-02-26 00:00:00
2024-05-11T06:13:34.290238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:13:35.136820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
226 
20100426
 
1
20091111
 
1
20100705
 
1
20111128
 
1

Length

Max length8
Median length4
Mean length4.0865801
Min length4

Unique

Unique5 ?
Unique (%)2.2%

Sample

1st row<NA>
2nd row20100426
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 226
97.8%
20100426 1
 
0.4%
20091111 1
 
0.4%
20100705 1
 
0.4%
20111128 1
 
0.4%
20140811 1
 
0.4%

Length

2024-05-11T06:13:35.745524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:36.107837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 226
97.8%
20100426 1
 
0.4%
20091111 1
 
0.4%
20100705 1
 
0.4%
20111128 1
 
0.4%
20140811 1
 
0.4%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
93 
1
85 
4
40 
5
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 93
40.3%
1 85
36.8%
4 40
17.3%
5 13
 
5.6%

Length

2024-05-11T06:13:36.432635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:36.754879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 93
40.3%
1 85
36.8%
4 40
17.3%
5 13
 
5.6%

영업상태명
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
93 
영업/정상
85 
취소/말소/만료/정지/중지
40 
제외/삭제/전출
13 

Length

Max length14
Median length8
Mean length5.5194805
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 93
40.3%
영업/정상 85
36.8%
취소/말소/만료/정지/중지 40
17.3%
제외/삭제/전출 13
 
5.6%

Length

2024-05-11T06:13:37.152064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:37.497082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 93
40.3%
영업/정상 85
36.8%
취소/말소/만료/정지/중지 40
17.3%
제외/삭제/전출 13
 
5.6%
Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
03
93 
13
84 
35
35 
15
13 
31
 
5

Length

Max length4
Median length2
Mean length2.008658
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row03
2nd row31
3rd row13
4th row03
5th row03

Common Values

ValueCountFrequency (%)
03 93
40.3%
13 84
36.4%
35 35
 
15.2%
15 13
 
5.6%
31 5
 
2.2%
BBBB 1
 
0.4%

Length

2024-05-11T06:13:38.074050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:38.401597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03 93
40.3%
13 84
36.4%
35 35
 
15.2%
15 13
 
5.6%
31 5
 
2.2%
bbbb 1
 
0.4%
Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
폐업
93 
영업중
84 
직권말소
35 
전출
13 
등록취소
 
5

Length

Max length4
Median length3
Mean length2.7186147
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 93
40.3%
영업중 84
36.4%
직권말소 35
 
15.2%
전출 13
 
5.6%
등록취소 5
 
2.2%
<NA> 1
 
0.4%

Length

2024-05-11T06:13:39.034096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:39.460979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 93
40.3%
영업중 84
36.4%
직권말소 35
 
15.2%
전출 13
 
5.6%
등록취소 5
 
2.2%
na 1
 
0.4%

폐업일자
Date

MISSING 

Distinct102
Distinct (%)72.9%
Missing91
Missing (%)39.4%
Memory size1.9 KiB
Minimum1999-02-25 00:00:00
Maximum2024-04-08 00:00:00
2024-05-11T06:13:39.911464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:13:40.550756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct130
Distinct (%)100.0%
Missing101
Missing (%)43.7%
Memory size1.9 KiB
2024-05-11T06:13:41.448756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length9.7076923
Min length7

Characters and Unicode

Total characters1262
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)100.0%

Sample

1st row392-1984
2nd row313-3103
3rd row3147-0584
4th row313-7226
5th row393-0071
ValueCountFrequency (%)
777-9131 1
 
0.8%
6748-3651 1
 
0.8%
7360712 1
 
0.8%
02-452-9595 1
 
0.8%
02-730-9355 1
 
0.8%
02-304-1232 1
 
0.8%
4327800 1
 
0.8%
02-546-3316 1
 
0.8%
3640903 1
 
0.8%
02 1
 
0.8%
Other values (121) 121
92.4%
2024-05-11T06:13:43.107025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 184
14.6%
3 158
12.5%
2 157
12.4%
7 138
10.9%
- 138
10.9%
1 115
9.1%
5 87
6.9%
4 74
5.9%
6 74
5.9%
8 73
 
5.8%
Other values (5) 64
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1118
88.6%
Dash Punctuation 138
 
10.9%
Other Punctuation 3
 
0.2%
Math Symbol 2
 
0.2%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 184
16.5%
3 158
14.1%
2 157
14.0%
7 138
12.3%
1 115
10.3%
5 87
7.8%
4 74
6.6%
6 74
6.6%
8 73
 
6.5%
9 58
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1262
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 184
14.6%
3 158
12.5%
2 157
12.4%
7 138
10.9%
- 138
10.9%
1 115
9.1%
5 87
6.9%
4 74
5.9%
6 74
5.9%
8 73
 
5.8%
Other values (5) 64
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 184
14.6%
3 158
12.5%
2 157
12.4%
7 138
10.9%
- 138
10.9%
1 115
9.1%
5 87
6.9%
4 74
5.9%
6 74
5.9%
8 73
 
5.8%
Other values (5) 64
 
5.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB
Distinct50
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
113 
120030
17 
120012
13 
120013
 
6
120833
 
5
Other values (45)
77 

Length

Max length7
Median length6
Mean length5.0909091
Min length4

Unique

Unique29 ?
Unique (%)12.6%

Sample

1st row120070
2nd row120012
3rd row120-722
4th row120834
5th row120822

Common Values

ValueCountFrequency (%)
<NA> 113
48.9%
120030 17
 
7.4%
120012 13
 
5.6%
120013 6
 
2.6%
120833 5
 
2.2%
120809 5
 
2.2%
120-012 5
 
2.2%
120722 4
 
1.7%
120-013 4
 
1.7%
120110 4
 
1.7%
Other values (40) 55
23.8%

Length

2024-05-11T06:13:43.687772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 113
48.9%
120030 17
 
7.4%
120012 13
 
5.6%
120013 6
 
2.6%
120833 5
 
2.2%
120809 5
 
2.2%
120-012 5
 
2.2%
120110 4
 
1.7%
120-013 4
 
1.7%
120722 4
 
1.7%
Other values (40) 55
23.8%
Distinct202
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T06:13:44.497808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length27.922078
Min length17

Characters and Unicode

Total characters6450
Distinct characters177
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)80.5%

Sample

1st row서울특별시 서대문구 영천동 277-1번지
2nd row서울특별시 서대문구 충정로2가 191번지 골든타워 1405호
3rd row서울특별시 서대문구 충정로2가 191 골든타워빌딩 1203호
4th row서울특별시 서대문구 창천동 33-18번지
5th row서울특별시 서대문구 북아현동 251-39번지 3층
ValueCountFrequency (%)
서울특별시 231
18.9%
서대문구 230
18.8%
충정로2가 42
 
3.4%
합동 36
 
2.9%
창천동 35
 
2.9%
충정로3가 23
 
1.9%
연희동 20
 
1.6%
191 18
 
1.5%
골든타워빌딩 16
 
1.3%
홍은동 15
 
1.2%
Other values (310) 556
45.5%
2024-05-11T06:13:45.992131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1070
 
16.6%
463
 
7.2%
1 335
 
5.2%
268
 
4.2%
244
 
3.8%
232
 
3.6%
232
 
3.6%
231
 
3.6%
231
 
3.6%
231
 
3.6%
Other values (167) 2913
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3924
60.8%
Decimal Number 1283
 
19.9%
Space Separator 1070
 
16.6%
Dash Punctuation 136
 
2.1%
Uppercase Letter 28
 
0.4%
Other Punctuation 4
 
0.1%
Lowercase Letter 3
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
463
 
11.8%
268
 
6.8%
244
 
6.2%
232
 
5.9%
232
 
5.9%
231
 
5.9%
231
 
5.9%
231
 
5.9%
175
 
4.5%
93
 
2.4%
Other values (142) 1524
38.8%
Decimal Number
ValueCountFrequency (%)
1 335
26.1%
2 206
16.1%
3 147
11.5%
4 112
 
8.7%
0 111
 
8.7%
5 88
 
6.9%
6 80
 
6.2%
7 80
 
6.2%
9 68
 
5.3%
8 56
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 8
28.6%
K 7
25.0%
S 7
25.0%
A 3
 
10.7%
D 2
 
7.1%
M 1
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
b 1
33.3%
s 1
33.3%
k 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1070
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3924
60.8%
Common 2495
38.7%
Latin 31
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
463
 
11.8%
268
 
6.8%
244
 
6.2%
232
 
5.9%
232
 
5.9%
231
 
5.9%
231
 
5.9%
231
 
5.9%
175
 
4.5%
93
 
2.4%
Other values (142) 1524
38.8%
Common
ValueCountFrequency (%)
1070
42.9%
1 335
 
13.4%
2 206
 
8.3%
3 147
 
5.9%
- 136
 
5.5%
4 112
 
4.5%
0 111
 
4.4%
5 88
 
3.5%
6 80
 
3.2%
7 80
 
3.2%
Other values (6) 130
 
5.2%
Latin
ValueCountFrequency (%)
B 8
25.8%
K 7
22.6%
S 7
22.6%
A 3
 
9.7%
D 2
 
6.5%
M 1
 
3.2%
b 1
 
3.2%
s 1
 
3.2%
k 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3924
60.8%
ASCII 2526
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1070
42.4%
1 335
 
13.3%
2 206
 
8.2%
3 147
 
5.8%
- 136
 
5.4%
4 112
 
4.4%
0 111
 
4.4%
5 88
 
3.5%
6 80
 
3.2%
7 80
 
3.2%
Other values (15) 161
 
6.4%
Hangul
ValueCountFrequency (%)
463
 
11.8%
268
 
6.8%
244
 
6.2%
232
 
5.9%
232
 
5.9%
231
 
5.9%
231
 
5.9%
231
 
5.9%
175
 
4.5%
93
 
2.4%
Other values (142) 1524
38.8%

도로명주소
Text

MISSING 

Distinct212
Distinct (%)93.8%
Missing5
Missing (%)2.2%
Memory size1.9 KiB
2024-05-11T06:13:46.698966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length35.424779
Min length23

Characters and Unicode

Total characters8006
Distinct characters197
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)88.9%

Sample

1st row서울특별시 서대문구 충정로 53, 1405호 (충정로2가,골든타워)
2nd row서울특별시 서대문구 충정로 53, 1203호 (충정로2가)
3rd row서울특별시 서대문구 연세로7안길 10-4 (창천동)
4th row서울특별시 서대문구 신촌로 205 (북아현동,3층)
5th row서울특별시 서대문구 충정로 53 (충정로2가,골든타워1601)
ValueCountFrequency (%)
서울특별시 226
 
15.2%
서대문구 225
 
15.2%
서소문로 52
 
3.5%
2층 38
 
2.6%
충정로 37
 
2.5%
신촌로 34
 
2.3%
53 30
 
2.0%
창천동 29
 
2.0%
합동 29
 
2.0%
충정로2가 26
 
1.8%
Other values (370) 758
51.1%
2024-05-11T06:13:48.088470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1305
 
16.3%
507
 
6.3%
288
 
3.6%
281
 
3.5%
275
 
3.4%
, 272
 
3.4%
2 249
 
3.1%
240
 
3.0%
1 240
 
3.0%
( 227
 
2.8%
Other values (187) 4122
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4665
58.3%
Space Separator 1305
 
16.3%
Decimal Number 1249
 
15.6%
Other Punctuation 273
 
3.4%
Open Punctuation 227
 
2.8%
Close Punctuation 227
 
2.8%
Dash Punctuation 31
 
0.4%
Uppercase Letter 26
 
0.3%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
507
 
10.9%
288
 
6.2%
281
 
6.0%
275
 
5.9%
240
 
5.1%
227
 
4.9%
227
 
4.9%
226
 
4.8%
226
 
4.8%
170
 
3.6%
Other values (163) 1998
42.8%
Decimal Number
ValueCountFrequency (%)
2 249
19.9%
1 240
19.2%
3 197
15.8%
0 119
9.5%
5 112
9.0%
4 102
8.2%
7 95
 
7.6%
9 55
 
4.4%
6 42
 
3.4%
8 38
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 8
30.8%
K 7
26.9%
S 7
26.9%
D 2
 
7.7%
A 1
 
3.8%
M 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 272
99.6%
/ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
1305
100.0%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4665
58.3%
Common 3312
41.4%
Latin 29
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
507
 
10.9%
288
 
6.2%
281
 
6.0%
275
 
5.9%
240
 
5.1%
227
 
4.9%
227
 
4.9%
226
 
4.8%
226
 
4.8%
170
 
3.6%
Other values (163) 1998
42.8%
Common
ValueCountFrequency (%)
1305
39.4%
, 272
 
8.2%
2 249
 
7.5%
1 240
 
7.2%
( 227
 
6.9%
) 227
 
6.9%
3 197
 
5.9%
0 119
 
3.6%
5 112
 
3.4%
4 102
 
3.1%
Other values (6) 262
 
7.9%
Latin
ValueCountFrequency (%)
B 8
27.6%
K 7
24.1%
S 7
24.1%
e 2
 
6.9%
D 2
 
6.9%
b 1
 
3.4%
A 1
 
3.4%
M 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4665
58.3%
ASCII 3341
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1305
39.1%
, 272
 
8.1%
2 249
 
7.5%
1 240
 
7.2%
( 227
 
6.8%
) 227
 
6.8%
3 197
 
5.9%
0 119
 
3.6%
5 112
 
3.4%
4 102
 
3.1%
Other values (14) 291
 
8.7%
Hangul
ValueCountFrequency (%)
507
 
10.9%
288
 
6.2%
281
 
6.0%
275
 
5.9%
240
 
5.1%
227
 
4.9%
227
 
4.9%
226
 
4.8%
226
 
4.8%
170
 
3.6%
Other values (163) 1998
42.8%

도로명우편번호
Text

MISSING 

Distinct59
Distinct (%)36.9%
Missing71
Missing (%)30.7%
Memory size1.9 KiB
2024-05-11T06:13:48.840173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.125
Min length5

Characters and Unicode

Total characters820
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)21.2%

Sample

1st row03736
2nd row03735
3rd row03640
4th row03741
5th row03737
ValueCountFrequency (%)
03741 32
20.0%
03736 22
 
13.8%
03785 16
 
10.0%
120030 6
 
3.8%
03735 4
 
2.5%
03663 4
 
2.5%
03737 4
 
2.5%
03730 3
 
1.9%
03789 3
 
1.9%
03611 2
 
1.2%
Other values (49) 64
40.0%
2024-05-11T06:13:50.220709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 197
24.0%
0 196
23.9%
7 129
15.7%
6 73
 
8.9%
1 70
 
8.5%
4 45
 
5.5%
8 37
 
4.5%
2 34
 
4.1%
5 31
 
3.8%
9 7
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 819
99.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 197
24.1%
0 196
23.9%
7 129
15.8%
6 73
 
8.9%
1 70
 
8.5%
4 45
 
5.5%
8 37
 
4.5%
2 34
 
4.2%
5 31
 
3.8%
9 7
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 820
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 197
24.0%
0 196
23.9%
7 129
15.7%
6 73
 
8.9%
1 70
 
8.5%
4 45
 
5.5%
8 37
 
4.5%
2 34
 
4.1%
5 31
 
3.8%
9 7
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 197
24.0%
0 196
23.9%
7 129
15.7%
6 73
 
8.9%
1 70
 
8.5%
4 45
 
5.5%
8 37
 
4.5%
2 34
 
4.1%
5 31
 
3.8%
9 7
 
0.9%
Distinct228
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-05-11T06:13:51.099001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length21
Mean length8.4935065
Min length3

Characters and Unicode

Total characters1962
Distinct characters312
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

Unique225 ?
Unique (%)97.4%

Sample

1st row(주)거산세계여행
2nd row(주)알펜투어
3rd row(주)한사랑여행
4th row월즈오브런던
5th row(주)여행천하
ValueCountFrequency (%)
주식회사 32
 
10.8%
여행사 3
 
1.0%
트래블 2
 
0.7%
tour 2
 
0.7%
global 2
 
0.7%
글로벌 2
 
0.7%
co 2
 
0.7%
ltd 2
 
0.7%
주)씨앤비다보여행 2
 
0.7%
투어 2
 
0.7%
Other values (243) 245
82.8%
2024-05-11T06:13:52.192799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
8.3%
( 134
 
6.8%
) 134
 
6.8%
81
 
4.1%
76
 
3.9%
65
 
3.3%
62
 
3.2%
53
 
2.7%
52
 
2.7%
52
 
2.7%
Other values (302) 1090
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1507
76.8%
Open Punctuation 134
 
6.8%
Close Punctuation 134
 
6.8%
Lowercase Letter 66
 
3.4%
Space Separator 65
 
3.3%
Uppercase Letter 49
 
2.5%
Other Punctuation 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
 
10.8%
81
 
5.4%
76
 
5.0%
62
 
4.1%
53
 
3.5%
52
 
3.5%
52
 
3.5%
46
 
3.1%
33
 
2.2%
32
 
2.1%
Other values (261) 857
56.9%
Lowercase Letter
ValueCountFrequency (%)
o 10
15.2%
i 7
10.6%
l 7
10.6%
a 6
9.1%
r 6
9.1%
e 5
7.6%
d 5
7.6%
c 4
 
6.1%
t 3
 
4.5%
n 3
 
4.5%
Other values (8) 10
15.2%
Uppercase Letter
ValueCountFrequency (%)
T 8
16.3%
A 6
12.2%
O 5
10.2%
R 4
8.2%
E 4
8.2%
U 3
 
6.1%
L 3
 
6.1%
C 3
 
6.1%
G 3
 
6.1%
S 2
 
4.1%
Other values (7) 8
16.3%
Other Punctuation
ValueCountFrequency (%)
. 3
42.9%
& 2
28.6%
, 2
28.6%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Space Separator
ValueCountFrequency (%)
65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1507
76.8%
Common 340
 
17.3%
Latin 115
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
 
10.8%
81
 
5.4%
76
 
5.0%
62
 
4.1%
53
 
3.5%
52
 
3.5%
52
 
3.5%
46
 
3.1%
33
 
2.2%
32
 
2.1%
Other values (261) 857
56.9%
Latin
ValueCountFrequency (%)
o 10
 
8.7%
T 8
 
7.0%
i 7
 
6.1%
l 7
 
6.1%
a 6
 
5.2%
r 6
 
5.2%
A 6
 
5.2%
e 5
 
4.3%
O 5
 
4.3%
d 5
 
4.3%
Other values (25) 50
43.5%
Common
ValueCountFrequency (%)
( 134
39.4%
) 134
39.4%
65
19.1%
. 3
 
0.9%
& 2
 
0.6%
, 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1507
76.8%
ASCII 455
 
23.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
163
 
10.8%
81
 
5.4%
76
 
5.0%
62
 
4.1%
53
 
3.5%
52
 
3.5%
52
 
3.5%
46
 
3.1%
33
 
2.2%
32
 
2.1%
Other values (261) 857
56.9%
ASCII
ValueCountFrequency (%)
( 134
29.5%
) 134
29.5%
65
14.3%
o 10
 
2.2%
T 8
 
1.8%
i 7
 
1.5%
l 7
 
1.5%
a 6
 
1.3%
r 6
 
1.3%
A 6
 
1.3%
Other values (31) 72
15.8%
Distinct230
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2003-02-07 11:05:59
Maximum2024-05-09 09:08:02
2024-05-11T06:13:52.858991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:13:53.311811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
U
152 
I
78 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
U 152
65.8%
I 78
33.8%
D 1
 
0.4%

Length

2024-05-11T06:13:53.748284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:54.031516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 152
65.8%
i 78
33.8%
d 1
 
0.4%
Distinct91
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:01:00
2024-05-11T06:13:54.343346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:13:54.837152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)50.7%
Missing4
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean195446.5
Minimum191543.28
Maximum197567.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:13:55.504590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191543.28
5-th percentile193133.34
Q1194062.49
median195626.48
Q3196824.07
95-th percentile196942.2
Maximum197567.94
Range6024.658
Interquartile range (IQR)2761.5796

Descriptive statistics

Standard deviation1489.2668
Coefficient of variation (CV)0.0076198181
Kurtosis-1.0803828
Mean195446.5
Median Absolute Deviation (MAD)1223.7384
Skewness-0.48871951
Sum44366355
Variance2217915.5
MonotonicityNot monotonic
2024-05-11T06:13:55.916583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196801.661639204 28
 
12.1%
196892.09236853 20
 
8.7%
196824.072701729 16
 
6.9%
193712.476983727 14
 
6.1%
196945.454641052 8
 
3.5%
196829.272845892 6
 
2.6%
193582.818617191 4
 
1.7%
196862.481903369 4
 
1.7%
196850.221876572 3
 
1.3%
194770.272306267 3
 
1.3%
Other values (105) 121
52.4%
(Missing) 4
 
1.7%
ValueCountFrequency (%)
191543.28 1
0.4%
191778.716247587 1
0.4%
192150.038113118 1
0.4%
192219.454539817 1
0.4%
192285.636936533 1
0.4%
192415.907205 1
0.4%
192456.366937727 1
0.4%
192552.192063652 1
0.4%
192616.804543873 2
0.9%
192934.20130876 1
0.4%
ValueCountFrequency (%)
197567.93800572 1
 
0.4%
197053.685372291 1
 
0.4%
197028.132153511 2
 
0.9%
196945.454641052 8
 
3.5%
196934.602353655 2
 
0.9%
196921.265890833 1
 
0.4%
196920.634153795 1
 
0.4%
196892.09236853 20
8.7%
196876.322759587 1
 
0.4%
196863.328815216 1
 
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct115
Distinct (%)50.7%
Missing4
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean451564.78
Minimum450378.21
Maximum455939.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:13:56.302465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450378.21
5-th percentile450525.83
Q1450890.66
median451238.07
Q3451846.98
95-th percentile454272.01
Maximum455939.17
Range5560.9589
Interquartile range (IQR)956.3164

Descriptive statistics

Standard deviation1161.0915
Coefficient of variation (CV)0.0025712624
Kurtosis1.7604005
Mean451564.78
Median Absolute Deviation (MAD)466.36737
Skewness1.5657361
Sum1.025052 × 108
Variance1348133.5
MonotonicityNot monotonic
2024-05-11T06:13:56.692526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451267.809661546 28
 
12.1%
450948.915518467 20
 
8.7%
450890.664072337 16
 
6.9%
450637.010875398 14
 
6.1%
451003.162676008 8
 
3.5%
451317.18963079 6
 
2.6%
453077.774347174 4
 
1.7%
450971.304599585 4
 
1.7%
451623.734611949 3
 
1.3%
450529.307302535 3
 
1.3%
Other values (105) 121
52.4%
(Missing) 4
 
1.7%
ValueCountFrequency (%)
450378.207939919 1
0.4%
450400.49762862 1
0.4%
450415.649392505 1
0.4%
450422.374151297 1
0.4%
450433.691021245 1
0.4%
450443.357241716 2
0.9%
450469.610782261 2
0.9%
450484.124763157 1
0.4%
450503.286604315 1
0.4%
450525.834024158 2
0.9%
ValueCountFrequency (%)
455939.166820505 1
0.4%
455477.476234474 1
0.4%
454979.71556714 1
0.4%
454863.906333334 1
0.4%
454786.019433577 1
0.4%
454683.237327927 2
0.9%
454564.34581261 1
0.4%
454560.084990316 1
0.4%
454495.012463392 1
0.4%
454485.120954321 1
0.4%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
국내외여행업
128 
<NA>
103 

Length

Max length6
Median length6
Mean length5.1082251
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 128
55.4%
<NA> 103
44.6%

Length

2024-05-11T06:13:57.162488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:57.542979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 128
55.4%
na 103
44.6%
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
160 
관광사업
71 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 160
69.3%
관광사업 71
30.7%

Length

2024-05-11T06:13:57.895456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:58.363340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 160
69.3%
관광사업 71
30.7%

지역구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
215 
준주거지역
 
7
일반주거지역
 
5
상업지역
 
2
근린상업지역
 
1

Length

Max length6
Median length4
Mean length4.0822511
Min length4

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 215
93.1%
준주거지역 7
 
3.0%
일반주거지역 5
 
2.2%
상업지역 2
 
0.9%
근린상업지역 1
 
0.4%
주거지역 1
 
0.4%

Length

2024-05-11T06:13:58.816605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:13:59.174729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 215
93.1%
준주거지역 7
 
3.0%
일반주거지역 5
 
2.2%
상업지역 2
 
0.9%
근린상업지역 1
 
0.4%
주거지역 1
 
0.4%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)23.5%
Missing180
Missing (%)77.9%
Infinite0
Infinite (%)0.0%
Mean4.3137255
Minimum0
Maximum27
Zeros33
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:13:59.513887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.5
95-th percentile22.5
Maximum27
Range27
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation8.0261826
Coefficient of variation (CV)1.8606151
Kurtosis2.3227924
Mean4.3137255
Median Absolute Deviation (MAD)0
Skewness1.9177958
Sum220
Variance64.419608
MonotonicityNot monotonic
2024-05-11T06:13:59.892544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 33
 
14.3%
6 4
 
1.7%
22 2
 
0.9%
27 2
 
0.9%
5 2
 
0.9%
21 2
 
0.9%
7 1
 
0.4%
3 1
 
0.4%
23 1
 
0.4%
4 1
 
0.4%
Other values (2) 2
 
0.9%
(Missing) 180
77.9%
ValueCountFrequency (%)
0 33
14.3%
1 1
 
0.4%
3 1
 
0.4%
4 1
 
0.4%
5 2
 
0.9%
6 4
 
1.7%
7 1
 
0.4%
8 1
 
0.4%
21 2
 
0.9%
22 2
 
0.9%
ValueCountFrequency (%)
27 2
0.9%
23 1
 
0.4%
22 2
0.9%
21 2
0.9%
8 1
 
0.4%
7 1
 
0.4%
6 4
1.7%
5 2
0.9%
4 1
 
0.4%
3 1
 
0.4%

주변환경명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
216 
기타
 
11
주택가주변
 
3
학교정화(상대)
 
1

Length

Max length8
Median length4
Mean length3.9350649
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 216
93.5%
기타 11
 
4.8%
주택가주변 3
 
1.3%
학교정화(상대) 1
 
0.4%

Length

2024-05-11T06:14:00.515238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:01.056304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 216
93.5%
기타 11
 
4.8%
주택가주변 3
 
1.3%
학교정화(상대 1
 
0.4%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

보험기관명
Categorical

Distinct23
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
132 
서울보증보험
19 
서울보증보험주식회사
19 
한국관광협회중앙회 여행공제회
16 
서울특별시관광협회
 
10
Other values (18)
35 

Length

Max length19
Median length4
Mean length7.1125541
Min length4

Unique

Unique11 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
57.1%
서울보증보험 19
 
8.2%
서울보증보험주식회사 19
 
8.2%
한국관광협회중앙회 여행공제회 16
 
6.9%
서울특별시관광협회 10
 
4.3%
서울보증보험주식회사(삼천만원) 7
 
3.0%
서울보증보험주식회사(3천만원) 6
 
2.6%
서울시관광협회 3
 
1.3%
여행공제회 2
 
0.9%
서울보증보험주식회사(삼천만) 2
 
0.9%
Other values (13) 15
 
6.5%

Length

2024-05-11T06:14:01.623891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 132
53.4%
서울보증보험주식회사 19
 
7.7%
서울보증보험 19
 
7.7%
여행공제회 18
 
7.3%
한국관광협회중앙회 17
 
6.9%
서울특별시관광협회 10
 
4.0%
서울보증보험주식회사(삼천만원 7
 
2.8%
서울보증보험주식회사(3천만원 6
 
2.4%
서울시관광협회 3
 
1.2%
서울보증보험(30,000,000원 2
 
0.8%
Other values (12) 14
 
5.7%

건물용도명
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
199 
근린생활시설
25 
사무실
 
5
다중주택(공동주택적용)
 
1
아파트
 
1

Length

Max length12
Median length4
Mean length4.2251082
Min length3

Unique

Unique2 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
86.1%
근린생활시설 25
 
10.8%
사무실 5
 
2.2%
다중주택(공동주택적용) 1
 
0.4%
아파트 1
 
0.4%

Length

2024-05-11T06:14:02.567421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:03.061106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 199
86.1%
근린생활시설 25
 
10.8%
사무실 5
 
2.2%
다중주택(공동주택적용 1
 
0.4%
아파트 1
 
0.4%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)19.2%
Missing179
Missing (%)77.5%
Infinite0
Infinite (%)0.0%
Mean3.1538462
Minimum0
Maximum21
Zeros33
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:04.009288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.25
95-th percentile16.8
Maximum21
Range21
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation5.7509918
Coefficient of variation (CV)1.8234852
Kurtosis3.4421785
Mean3.1538462
Median Absolute Deviation (MAD)0
Skewness2.0825848
Sum164
Variance33.073906
MonotonicityNot monotonic
2024-05-11T06:14:04.586353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 33
 
14.3%
5 4
 
1.7%
15 3
 
1.3%
4 3
 
1.3%
21 2
 
0.9%
2 2
 
0.9%
6 2
 
0.9%
3 1
 
0.4%
7 1
 
0.4%
19 1
 
0.4%
(Missing) 179
77.5%
ValueCountFrequency (%)
0 33
14.3%
2 2
 
0.9%
3 1
 
0.4%
4 3
 
1.3%
5 4
 
1.7%
6 2
 
0.9%
7 1
 
0.4%
15 3
 
1.3%
19 1
 
0.4%
21 2
 
0.9%
ValueCountFrequency (%)
21 2
 
0.9%
19 1
 
0.4%
15 3
 
1.3%
7 1
 
0.4%
6 2
 
0.9%
5 4
 
1.7%
4 3
 
1.3%
3 1
 
0.4%
2 2
 
0.9%
0 33
14.3%

지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)14.3%
Missing182
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean1.244898
Minimum0
Maximum17
Zeros33
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:04.969057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum17
Range17
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9828022
Coefficient of variation (CV)2.3960214
Kurtosis16.142851
Mean1.244898
Median Absolute Deviation (MAD)0
Skewness3.6612814
Sum61
Variance8.8971088
MonotonicityNot monotonic
2024-05-11T06:14:05.969461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 33
 
14.3%
1 8
 
3.5%
6 4
 
1.7%
7 1
 
0.4%
2 1
 
0.4%
17 1
 
0.4%
3 1
 
0.4%
(Missing) 182
78.8%
ValueCountFrequency (%)
0 33
14.3%
1 8
 
3.5%
2 1
 
0.4%
3 1
 
0.4%
6 4
 
1.7%
7 1
 
0.4%
17 1
 
0.4%
ValueCountFrequency (%)
17 1
 
0.4%
7 1
 
0.4%
6 4
 
1.7%
3 1
 
0.4%
2 1
 
0.4%
1 8
 
3.5%
0 33
14.3%

객실수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:06.640238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:07.021471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

건축연면적
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:07.396869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:07.766201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

영문상호명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing229
Missing (%)99.1%
Memory size1.9 KiB
2024-05-11T06:14:08.288723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22.5
Mean length22.5
Min length17

Characters and Unicode

Total characters45
Distinct characters24
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 rowDo as I like Tour
2nd rowGood Feeling Korea Co., Ltd.
ValueCountFrequency (%)
do 1
10.0%
as 1
10.0%
i 1
10.0%
like 1
10.0%
tour 1
10.0%
good 1
10.0%
feeling 1
10.0%
korea 1
10.0%
co 1
10.0%
ltd 1
10.0%
2024-05-11T06:14:09.493669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
17.8%
o 6
13.3%
e 4
 
8.9%
r 2
 
4.4%
a 2
 
4.4%
l 2
 
4.4%
i 2
 
4.4%
. 2
 
4.4%
d 2
 
4.4%
n 1
 
2.2%
Other values (14) 14
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26
57.8%
Space Separator 8
 
17.8%
Uppercase Letter 8
 
17.8%
Other Punctuation 3
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
23.1%
e 4
15.4%
r 2
 
7.7%
a 2
 
7.7%
l 2
 
7.7%
i 2
 
7.7%
d 2
 
7.7%
n 1
 
3.8%
g 1
 
3.8%
u 1
 
3.8%
Other values (3) 3
11.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
12.5%
C 1
12.5%
K 1
12.5%
D 1
12.5%
F 1
12.5%
G 1
12.5%
T 1
12.5%
I 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
75.6%
Common 11
 
24.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
17.6%
e 4
 
11.8%
r 2
 
5.9%
a 2
 
5.9%
l 2
 
5.9%
i 2
 
5.9%
d 2
 
5.9%
n 1
 
2.9%
L 1
 
2.9%
C 1
 
2.9%
Other values (11) 11
32.4%
Common
ValueCountFrequency (%)
8
72.7%
. 2
 
18.2%
, 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
17.8%
o 6
13.3%
e 4
 
8.9%
r 2
 
4.4%
a 2
 
4.4%
l 2
 
4.4%
i 2
 
4.4%
. 2
 
4.4%
d 2
 
4.4%
n 1
 
2.2%
Other values (14) 14
31.1%

영문상호주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing229
Missing (%)99.1%
Memory size1.9 KiB
2024-05-11T06:14:09.946005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23.5
Mean length23.5
Min length23

Characters and Unicode

Total characters47
Distinct characters26
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

Unique2 ?
Unique (%)100.0%

Sample

1st rowFOREIGN TRAVEL BUSINESS
2nd rowOverseas travel business
ValueCountFrequency (%)
travel 2
33.3%
business 2
33.3%
foreign 1
16.7%
overseas 1
16.7%
2024-05-11T06:14:10.998402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 5
 
10.6%
e 4
 
8.5%
4
 
8.5%
E 3
 
6.4%
S 3
 
6.4%
r 2
 
4.3%
a 2
 
4.3%
R 2
 
4.3%
I 2
 
4.3%
N 2
 
4.3%
Other values (16) 18
38.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 22
46.8%
Lowercase Letter 21
44.7%
Space Separator 4
 
8.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3
13.6%
S 3
13.6%
R 2
9.1%
I 2
9.1%
N 2
9.1%
O 2
9.1%
F 1
 
4.5%
U 1
 
4.5%
B 1
 
4.5%
L 1
 
4.5%
Other values (4) 4
18.2%
Lowercase Letter
ValueCountFrequency (%)
s 5
23.8%
e 4
19.0%
r 2
 
9.5%
a 2
 
9.5%
v 2
 
9.5%
t 1
 
4.8%
l 1
 
4.8%
u 1
 
4.8%
i 1
 
4.8%
b 1
 
4.8%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43
91.5%
Common 4
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 5
 
11.6%
e 4
 
9.3%
E 3
 
7.0%
S 3
 
7.0%
r 2
 
4.7%
a 2
 
4.7%
R 2
 
4.7%
I 2
 
4.7%
N 2
 
4.7%
v 2
 
4.7%
Other values (15) 16
37.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 5
 
10.6%
e 4
 
8.5%
4
 
8.5%
E 3
 
6.4%
S 3
 
6.4%
r 2
 
4.3%
a 2
 
4.3%
R 2
 
4.3%
I 2
 
4.3%
N 2
 
4.3%
Other values (16) 18
38.3%

선박총톤수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:11.522420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:11.920685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

선박척수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:12.363910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:12.727664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

무대면적
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:13.092868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:13.483065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

좌석수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:13.984700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:14.325154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:14.712152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:15.081508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)48.3%
Missing171
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean31.049333
Minimum0
Maximum178.15
Zeros30
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:15.655662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10.985
Q352.515
95-th percentile114.504
Maximum178.15
Range178.15
Interquartile range (IQR)52.515

Descriptive statistics

Standard deviation41.699422
Coefficient of variation (CV)1.3430054
Kurtosis2.6404932
Mean31.049333
Median Absolute Deviation (MAD)10.985
Skewness1.6038605
Sum1862.96
Variance1738.8418
MonotonicityNot monotonic
2024-05-11T06:14:16.140395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 30
 
13.0%
38.33 2
 
0.9%
25.35 2
 
0.9%
32.0 1
 
0.4%
82.64 1
 
0.4%
58.93 1
 
0.4%
25.0 1
 
0.4%
63.2 1
 
0.4%
70.0 1
 
0.4%
52.74 1
 
0.4%
Other values (19) 19
 
8.2%
(Missing) 171
74.0%
ValueCountFrequency (%)
0.0 30
13.0%
21.97 1
 
0.4%
23.14 1
 
0.4%
24.75 1
 
0.4%
25.0 1
 
0.4%
25.35 2
 
0.9%
27.0 1
 
0.4%
32.0 1
 
0.4%
38.33 2
 
0.9%
39.6 1
 
0.4%
ValueCountFrequency (%)
178.15 1
0.4%
162.0 1
0.4%
115.53 1
0.4%
114.45 1
0.4%
91.25 1
0.4%
85.0 1
0.4%
82.64 1
0.4%
81.25 1
0.4%
76.0 1
0.4%
70.0 1
0.4%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

놀이시설수
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
197 
0
34 

Length

Max length4
Median length4
Mean length3.5584416
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> 197
85.3%
0 34
 
14.7%

Length

2024-05-11T06:14:16.698841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:17.110257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
85.3%
0 34
 
14.7%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
230 
20140702
 
1

Length

Max length8
Median length4
Mean length4.017316
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
99.6%
20140702 1
 
0.4%

Length

2024-05-11T06:14:17.533487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:17.958179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
99.6%
20140702 1
 
0.4%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
230 
20150702
 
1

Length

Max length8
Median length4
Mean length4.017316
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 230
99.6%
20150702 1
 
0.4%

Length

2024-05-11T06:14:18.371171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:14:18.835891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 230
99.6%
20150702 1
 
0.4%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)13.2%
Missing125
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean91271781
Minimum0
Maximum6.7 × 108
Zeros7
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:19.489160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q160000000
median1 × 108
Q31 × 108
95-th percentile1.5 × 108
Maximum6.7 × 108
Range6.7 × 108
Interquartile range (IQR)40000000

Descriptive statistics

Standard deviation69886646
Coefficient of variation (CV)0.76569828
Kurtosis44.957046
Mean91271781
Median Absolute Deviation (MAD)0
Skewness5.4912524
Sum9.6748088 × 109
Variance4.8841433 × 1015
MonotonicityNot monotonic
2024-05-11T06:14:19.937697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
100000000 54
23.4%
60000000 20
 
8.7%
150000000 8
 
3.5%
0 7
 
3.0%
30000000 7
 
3.0%
50000000 2
 
0.9%
120000000 1
 
0.4%
670000000 1
 
0.4%
90200000 1
 
0.4%
70000000 1
 
0.4%
Other values (4) 4
 
1.7%
(Missing) 125
54.1%
ValueCountFrequency (%)
0 7
 
3.0%
30000000 7
 
3.0%
50000000 2
 
0.9%
60000000 20
 
8.7%
70000000 1
 
0.4%
72608798 1
 
0.4%
90200000 1
 
0.4%
92000000 1
 
0.4%
100000000 54
23.4%
120000000 1
 
0.4%
ValueCountFrequency (%)
670000000 1
 
0.4%
250000000 1
 
0.4%
200000000 1
 
0.4%
150000000 8
 
3.5%
120000000 1
 
0.4%
100000000 54
23.4%
92000000 1
 
0.4%
90200000 1
 
0.4%
72608798 1
 
0.4%
70000000 1
 
0.4%

보험시작일자
Real number (ℝ)

MISSING 

Distinct104
Distinct (%)99.0%
Missing126
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean20125073
Minimum20040419
Maximum20210811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:20.364768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040419
5-th percentile20060629
Q120090923
median20120813
Q320150425
95-th percentile20200812
Maximum20210811
Range170392
Interquartile range (IQR)59502

Descriptive statistics

Standard deviation44485.812
Coefficient of variation (CV)0.0022104671
Kurtosis-0.71966749
Mean20125073
Median Absolute Deviation (MAD)29890
Skewness0.19833532
Sum2.1131326 × 109
Variance1.9789874 × 109
MonotonicityNot monotonic
2024-05-11T06:14:20.932617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111209 2
 
0.9%
20141207 1
 
0.4%
20140911 1
 
0.4%
20180110 1
 
0.4%
20131222 1
 
0.4%
20130103 1
 
0.4%
20200912 1
 
0.4%
20130617 1
 
0.4%
20110817 1
 
0.4%
20190404 1
 
0.4%
Other values (94) 94
40.7%
(Missing) 126
54.5%
ValueCountFrequency (%)
20040419 1
0.4%
20041029 1
0.4%
20050907 1
0.4%
20060203 1
0.4%
20060328 1
0.4%
20060610 1
0.4%
20060706 1
0.4%
20060801 1
0.4%
20060812 1
0.4%
20060901 1
0.4%
ValueCountFrequency (%)
20210811 1
0.4%
20210529 1
0.4%
20210419 1
0.4%
20210215 1
0.4%
20210104 1
0.4%
20200912 1
0.4%
20200413 1
0.4%
20190820 1
0.4%
20190704 1
0.4%
20190619 1
0.4%

보험종료일자
Real number (ℝ)

MISSING 

Distinct104
Distinct (%)99.0%
Missing126
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean20136013
Minimum20050418
Maximum20220811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:21.434836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20050418
5-th percentile20070629
Q120100923
median20130813
Q320170424
95-th percentile20210811
Maximum20220811
Range170393
Interquartile range (IQR)69501

Descriptive statistics

Standard deviation44901.221
Coefficient of variation (CV)0.0022298963
Kurtosis-0.80828547
Mean20136013
Median Absolute Deviation (MAD)39511
Skewness0.14392956
Sum2.1142814 × 109
Variance2.0161196 × 109
MonotonicityNot monotonic
2024-05-11T06:14:22.102899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090422 2
 
0.9%
20150506 1
 
0.4%
20150910 1
 
0.4%
20190109 1
 
0.4%
20141221 1
 
0.4%
20140103 1
 
0.4%
20210911 1
 
0.4%
20140616 1
 
0.4%
20120817 1
 
0.4%
20200403 1
 
0.4%
Other values (94) 94
40.7%
(Missing) 126
54.5%
ValueCountFrequency (%)
20050418 1
0.4%
20051029 1
0.4%
20060907 1
0.4%
20070203 1
0.4%
20070327 1
0.4%
20070610 1
0.4%
20070706 1
0.4%
20070731 1
0.4%
20070811 1
0.4%
20070831 1
0.4%
ValueCountFrequency (%)
20220811 1
0.4%
20220529 1
0.4%
20220419 1
0.4%
20220214 1
0.4%
20220103 1
0.4%
20210911 1
0.4%
20210412 1
0.4%
20200819 1
0.4%
20200703 1
0.4%
20200618 1
0.4%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing231
Missing (%)100.0%
Memory size2.2 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)43.3%
Missing171
Missing (%)74.0%
Infinite0
Infinite (%)0.0%
Mean31.033333
Minimum0
Maximum178
Zeros30
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-11T06:14:22.607274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q352.25
95-th percentile114.1
Maximum178
Range178
Interquartile range (IQR)52.25

Descriptive statistics

Standard deviation41.690127
Coefficient of variation (CV)1.3433983
Kurtosis2.6363248
Mean31.033333
Median Absolute Deviation (MAD)11
Skewness1.6036105
Sum1862
Variance1738.0667
MonotonicityNot monotonic
2024-05-11T06:14:23.079934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 30
 
13.0%
25 4
 
1.7%
38 2
 
0.9%
46 2
 
0.9%
83 1
 
0.4%
85 1
 
0.4%
59 1
 
0.4%
63 1
 
0.4%
70 1
 
0.4%
53 1
 
0.4%
Other values (16) 16
 
6.9%
(Missing) 171
74.0%
ValueCountFrequency (%)
0 30
13.0%
22 1
 
0.4%
23 1
 
0.4%
25 4
 
1.7%
27 1
 
0.4%
32 1
 
0.4%
38 2
 
0.9%
40 1
 
0.4%
46 2
 
0.9%
50 1
 
0.4%
ValueCountFrequency (%)
178 1
0.4%
162 1
0.4%
116 1
0.4%
114 1
0.4%
91 1
0.4%
85 1
0.4%
83 1
0.4%
81 1
0.4%
76 1
0.4%
70 1
0.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03120000CDFI226002199600000119961112<NA>3폐업03폐업20030605<NA><NA><NA><NA><NA>120070서울특별시 서대문구 영천동 277-1번지<NA><NA>(주)거산세계여행2003-06-05 10:35:19I2018-08-31 23:59:59.0<NA><NA><NA>국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
13120000CDFI226002199600000319961118201004264취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>120012서울특별시 서대문구 충정로2가 191번지 골든타워 1405호서울특별시 서대문구 충정로 53, 1405호 (충정로2가,골든타워)<NA>(주)알펜투어2010-04-20 14:47:54I2018-08-31 23:59:59.0<NA>196801.661639451267.809662국내외여행업관광사업<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>1000000002006111620071115<NA><NA>
23120000CDFI22600219970000011997-09-12<NA>1영업/정상13영업중<NA><NA><NA><NA>392-1984<NA>120-722서울특별시 서대문구 충정로2가 191 골든타워빌딩 1203호서울특별시 서대문구 충정로 53, 1203호 (충정로2가)03736(주)한사랑여행2024-02-21 10:24:44U2023-12-01 22:03:00.0<NA>196801.661639451267.809662<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33120000CDFI226002199800000119980417<NA>3폐업03폐업19990225<NA><NA><NA><NA><NA>120834서울특별시 서대문구 창천동 33-18번지서울특별시 서대문구 연세로7안길 10-4 (창천동)<NA>월즈오브런던2003-02-07 11:05:59I2018-08-31 23:59:59.0<NA>194316.218242450673.635639국내외여행업관광사업<NA>0<NA><NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
43120000CDFI226002199900000219990303<NA>3폐업03폐업20020119<NA><NA><NA><NA><NA>120822서울특별시 서대문구 북아현동 251-39번지 3층서울특별시 서대문구 신촌로 205 (북아현동,3층)<NA>(주)여행천하2003-02-07 11:06:58I2018-08-31 23:59:59.0<NA>195421.69856450551.570075국내외여행업관광사업<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
53120000CDFI226002199900000519990630<NA>3폐업03폐업20050303<NA><NA><NA><NA><NA>120012서울특별시 서대문구 충정로2가 191-0번지 골든타워1601서울특별시 서대문구 충정로 53 (충정로2가,골든타워1601)<NA>서울컨벤션서비스(주)2005-03-03 17:10:55I2018-08-31 23:59:59.0<NA>196801.661639451267.809662국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63120000CDFI226002199900000719990809<NA>3폐업03폐업20051117<NA><NA><NA><NA><NA>120822서울특별시 서대문구 북아현동 221-14번지 3층서울특별시 서대문구 신촌로 229 (북아현동,3층)<NA>POSH KOREA2005-11-17 10:11:10I2018-08-31 23:59:59.0<NA>195626.483507450565.120109국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
73120000CDFI226002200000000320000630<NA>1영업/정상BBBB<NA><NA><NA><NA><NA><NA><NA>120805서울특별시 서대문구 남가좌동 293-77번지<NA><NA>김민수2003-02-07 11:06:58I2018-08-31 23:59:59.0<NA>192415.907205451856.120833국내외여행업관광사업<NA>0<NA><NA><NA><NA>00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
83120000CDFI22600220000000092000-06-26<NA>1영업/정상13영업중<NA><NA><NA><NA>313-3103<NA>120-050서울특별시 서대문구 냉천동 169-1 충현빌딩 601호서울특별시 서대문구 통일로9안길 9-6, 601호 (냉천동,충현빌딩)<NA>ETC 네트워크(주)2024-02-23 16:02:56U2023-12-01 22:05:00.0<NA>196850.221877451623.734612<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93120000CDFI226002200100000320010615<NA>3폐업03폐업20090609<NA><NA><NA>3147-0584<NA>120170서울특별시 서대문구 대현동 40-17번지 제원빌딩 4층서울특별시 서대문구 이화여대1길 9 (대현동,제원빌딩 4층)<NA>Good Africa2009-06-11 16:42:14I2018-08-31 23:59:59.0<NA>195098.205922450549.583847국내외여행업관광사업<NA><NA><NA><NA>한국관광협회중앙회 여행공제회<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2008100220091002<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
2213120000CDFI22600220230000162022-08-04<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 316-1 가동 202호서울특별시 서대문구 통일로37길 42-4, 가동 2층 202호 (홍제동)03645주식회사 언더골프투어2024-03-12 16:02:22U2023-12-02 23:04:00.0<NA>194965.186276453794.473075<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2223120000CDFI22600220230000172023-10-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 북가좌동 351-2 202호서울특별시 서대문구 응암로 146, 2층 202호 (북가좌동)03667주식회사 노리여행2024-03-27 15:02:38U2023-12-02 22:09:00.0<NA>192456.366938453652.460124<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2233120000CDFI22600220230000182023-10-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 충정로3가 465 충정리시온 303호서울특별시 서대문구 서소문로 27, 3층 303호 (충정로3가, 충정리시온)03741주식회사 나라트래블2023-11-15 10:52:50U2022-10-31 23:07:00.0<NA>196824.072702450890.664072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2243120000CDFI22600220230000192023-10-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 503-8 2층 2481호서울특별시 서대문구 신촌로 25, 상록빌딩 2층 2481호 (창천동)03785주식회사 스윙플러스2023-11-15 11:18:28U2022-10-31 23:07:00.0<NA>193712.476984450637.010875<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2253120000CDFI22600220230000202014-07-23<NA>1영업/정상13영업중<NA><NA><NA><NA>02-745-8162<NA><NA>서울특별시 서대문구 충정로3가 465 충정리시온서울특별시 서대문구 서소문로 27, 3층 302호 (충정로3가, 충정리시온)03741제이오투어2023-11-02 15:23:33I2022-11-01 00:04:00.0<NA>196824.072702450890.664072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2263120000CDFI22600220230000212023-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 8-834서울특별시 서대문구 홍은중앙로 172-33 (홍은동)03600주식회사 와일드홀릭(Wildholic Co., Ltd.)2023-11-15 13:51:41U2022-10-31 23:07:00.0<NA>195609.52218455939.166821<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2273120000CDFI22600220240000012024-01-12<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 503-8 2층 289호서울특별시 서대문구 신촌로 25, 2층 289호 (창천동)03785트래블 빌더2024-01-25 13:50:02U2023-11-30 22:07:00.0<NA>193712.476984450637.010875<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2283120000CDFI22600220240000022024-02-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 506-10 산성빌딩, 3층서울특별시 서대문구 신촌로3길 15, 산성빌딩 3층 (창천동)03785(주)플랫폼구사삼2024-03-05 11:01:32U2023-12-03 00:07:00.0<NA>193664.950751450744.320812<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2293120000CDFI22600220240000032024-02-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-356-3579<NA><NA>서울특별시 서대문구 충정로2가 191 골든타워빌딩 1609호서울특별시 서대문구 충정로 53, 골든타워빌딩 1609호 (충정로2가)03736찬누리 여행사2024-03-14 16:44:41I2023-12-02 23:06:00.0<NA>196801.661639451267.809662<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2303120000CDFI22600220240000042012-03-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 충정로2가 191 골든타워빌딩 1307호서울특별시 서대문구 충정로 53, 골든타워빌딩 1307호 (충정로2가)03736(주)휴먼에듀2024-04-18 18:31:33I2023-12-03 22:00:00.0<NA>196801.661639451267.809662<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>