Overview

Dataset statistics

Number of variables60
Number of observations365
Missing cells8126
Missing cells (%)37.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory184.8 KiB
Average record size in memory518.4 B

Variable types

Categorical23
Text8
DateTime4
Numeric11
Unsupported14

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),문화체육업종명,문화사업자구분명,지역구분명,총층수,주변환경명,제작취급품목내용,보험기관명,건물용도명,지상층수,지하층수,객실수,건축연면적,영문상호명,영문상호주소,선박총톤수,선박척수,선박제원,무대면적,좌석수,기념품종류,회의실별동시수용인원,시설면적,놀이기구수내역,놀이시설수,방송시설유무,발전시설유무,의무실유무,안내소유무,기획여행보험시작일자,기획여행보험종료일자,자본금,보험시작일자,보험종료일자,부대시설내역,시설규모
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-17565/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
지역구분명 is highly imbalanced (90.1%)Imbalance
주변환경명 is highly imbalanced (91.3%)Imbalance
보험기관명 is highly imbalanced (55.8%)Imbalance
건물용도명 is highly imbalanced (62.2%)Imbalance
지하층수 is highly imbalanced (70.3%)Imbalance
객실수 is highly imbalanced (70.5%)Imbalance
건축연면적 is highly imbalanced (70.5%)Imbalance
영문상호주소 is highly imbalanced (88.7%)Imbalance
선박총톤수 is highly imbalanced (70.5%)Imbalance
선박척수 is highly imbalanced (70.5%)Imbalance
무대면적 is highly imbalanced (70.5%)Imbalance
좌석수 is highly imbalanced (70.5%)Imbalance
회의실별동시수용인원 is highly imbalanced (70.5%)Imbalance
놀이시설수 is highly imbalanced (70.5%)Imbalance
기획여행보험시작일자 is highly imbalanced (96.6%)Imbalance
기획여행보험종료일자 is highly imbalanced (96.6%)Imbalance
인허가취소일자 has 317 (86.8%) missing valuesMissing
폐업일자 has 135 (37.0%) missing valuesMissing
휴업시작일자 has 365 (100.0%) missing valuesMissing
휴업종료일자 has 365 (100.0%) missing valuesMissing
재개업일자 has 365 (100.0%) missing valuesMissing
전화번호 has 81 (22.2%) missing valuesMissing
소재지면적 has 365 (100.0%) missing valuesMissing
소재지우편번호 has 134 (36.7%) missing valuesMissing
도로명주소 has 17 (4.7%) missing valuesMissing
도로명우편번호 has 146 (40.0%) missing valuesMissing
업태구분명 has 365 (100.0%) missing valuesMissing
좌표정보(X) has 8 (2.2%) missing valuesMissing
좌표정보(Y) has 8 (2.2%) missing valuesMissing
총층수 has 302 (82.7%) missing valuesMissing
제작취급품목내용 has 365 (100.0%) missing valuesMissing
지상층수 has 302 (82.7%) missing valuesMissing
영문상호명 has 354 (97.0%) missing valuesMissing
선박제원 has 365 (100.0%) missing valuesMissing
기념품종류 has 365 (100.0%) missing valuesMissing
시설면적 has 264 (72.3%) missing valuesMissing
놀이기구수내역 has 365 (100.0%) missing valuesMissing
방송시설유무 has 365 (100.0%) missing valuesMissing
발전시설유무 has 365 (100.0%) missing valuesMissing
의무실유무 has 365 (100.0%) missing valuesMissing
안내소유무 has 365 (100.0%) missing valuesMissing
자본금 has 211 (57.8%) missing valuesMissing
보험시작일자 has 236 (64.7%) missing valuesMissing
보험종료일자 has 237 (64.9%) missing valuesMissing
부대시설내역 has 365 (100.0%) missing valuesMissing
시설규모 has 264 (72.3%) 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 54 (14.8%) zerosZeros
지상층수 has 54 (14.8%) zerosZeros
시설면적 has 85 (23.3%) zerosZeros
자본금 has 4 (1.1%) zerosZeros
시설규모 has 85 (23.3%) zerosZeros

Reproduction

Analysis started2024-05-11 05:38:09.011105
Analysis finished2024-05-11 05:38:10.417803
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3130000
365 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 365
100.0%

Length

2024-05-11T14:38:10.519298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:10.696542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 365
100.0%

관리번호
Text

UNIQUE 

Distinct365
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T14:38:10.953072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7300
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

Unique365 ?
Unique (%)100.0%

Sample

1st rowCDFI2260011972000001
2nd rowCDFI2260011983000001
3rd rowCDFI2260011991000001
4th rowCDFI2260011991000002
5th rowCDFI2260011992000001
ValueCountFrequency (%)
cdfi2260011972000001 1
 
0.3%
cdfi2260012014000014 1
 
0.3%
cdfi2260012015000013 1
 
0.3%
cdfi2260012015000011 1
 
0.3%
cdfi2260012015000009 1
 
0.3%
cdfi2260012015000008 1
 
0.3%
cdfi2260012015000007 1
 
0.3%
cdfi2260012015000006 1
 
0.3%
cdfi2260012015000005 1
 
0.3%
cdfi2260012015000004 1
 
0.3%
Other values (355) 355
97.3%
2024-05-11T14:38:11.516127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2881
39.5%
2 1239
17.0%
1 779
 
10.7%
6 428
 
5.9%
C 365
 
5.0%
D 365
 
5.0%
F 365
 
5.0%
I 365
 
5.0%
9 132
 
1.8%
3 96
 
1.3%
Other values (4) 285
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5840
80.0%
Uppercase Letter 1460
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2881
49.3%
2 1239
21.2%
1 779
 
13.3%
6 428
 
7.3%
9 132
 
2.3%
3 96
 
1.6%
5 79
 
1.4%
8 73
 
1.2%
4 73
 
1.2%
7 60
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 365
25.0%
D 365
25.0%
F 365
25.0%
I 365
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5840
80.0%
Latin 1460
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2881
49.3%
2 1239
21.2%
1 779
 
13.3%
6 428
 
7.3%
9 132
 
2.3%
3 96
 
1.6%
5 79
 
1.4%
8 73
 
1.2%
4 73
 
1.2%
7 60
 
1.0%
Latin
ValueCountFrequency (%)
C 365
25.0%
D 365
25.0%
F 365
25.0%
I 365
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2881
39.5%
2 1239
17.0%
1 779
 
10.7%
6 428
 
5.9%
C 365
 
5.0%
D 365
 
5.0%
F 365
 
5.0%
I 365
 
5.0%
9 132
 
1.8%
3 96
 
1.3%
Other values (4) 285
 
3.9%
Distinct349
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum1972-11-13 00:00:00
Maximum2024-02-16 00:00:00
2024-05-11T14:38:11.747190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:11.986524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)14.6%
Missing317
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean20125779
Minimum20071005
Maximum20170601
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:12.193081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071005
5-th percentile20120409
Q120121207
median20121207
Q320130826
95-th percentile20131004
Maximum20170601
Range99596
Interquartile range (IQR)9619

Descriptive statistics

Standard deviation13113.575
Coefficient of variation (CV)0.00065158099
Kurtosis10.776846
Mean20125779
Median Absolute Deviation (MAD)798
Skewness0.15092356
Sum9.660374 × 108
Variance1.7196585 × 108
MonotonicityNot monotonic
2024-05-11T14:38:12.397954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20121207 23
 
6.3%
20130806 7
 
1.9%
20131004 6
 
1.6%
20130826 5
 
1.4%
20120409 4
 
1.1%
20170601 2
 
0.5%
20071005 1
 
0.3%
(Missing) 317
86.8%
ValueCountFrequency (%)
20071005 1
 
0.3%
20120409 4
 
1.1%
20121207 23
6.3%
20130806 7
 
1.9%
20130826 5
 
1.4%
20131004 6
 
1.6%
20170601 2
 
0.5%
ValueCountFrequency (%)
20170601 2
 
0.5%
20131004 6
 
1.6%
20130826 5
 
1.4%
20130806 7
 
1.9%
20121207 23
6.3%
20120409 4
 
1.1%
20071005 1
 
0.3%
Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3
216 
4
77 
1
66 
5
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 216
59.2%
4 77
 
21.1%
1 66
 
18.1%
5 6
 
1.6%

Length

2024-05-11T14:38:12.594790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:12.761148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 216
59.2%
4 77
 
21.1%
1 66
 
18.1%
5 6
 
1.6%

영업상태명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
폐업
216 
취소/말소/만료/정지/중지
77 
영업/정상
66 
제외/삭제/전출
 
6

Length

Max length14
Median length2
Mean length5.1726027
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 216
59.2%
취소/말소/만료/정지/중지 77
 
21.1%
영업/정상 66
 
18.1%
제외/삭제/전출 6
 
1.6%

Length

2024-05-11T14:38:12.929877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:13.090018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 216
59.2%
취소/말소/만료/정지/중지 77
 
21.1%
영업/정상 66
 
18.1%
제외/삭제/전출 6
 
1.6%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.068493
Minimum3
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:13.227143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q13
median3
Q313
95-th percentile32
Maximum35
Range32
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.416116
Coefficient of variation (CV)1.0314066
Kurtosis-0.50053054
Mean11.068493
Median Absolute Deviation (MAD)0
Skewness1.069892
Sum4040
Variance130.32771
MonotonicityNot monotonic
2024-05-11T14:38:13.383927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 216
59.2%
13 66
 
18.1%
31 50
 
13.7%
32 17
 
4.7%
35 10
 
2.7%
15 6
 
1.6%
ValueCountFrequency (%)
3 216
59.2%
13 66
 
18.1%
15 6
 
1.6%
31 50
 
13.7%
32 17
 
4.7%
35 10
 
2.7%
ValueCountFrequency (%)
35 10
 
2.7%
32 17
 
4.7%
31 50
 
13.7%
15 6
 
1.6%
13 66
 
18.1%
3 216
59.2%
Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
폐업
216 
영업중
66 
등록취소
50 
신고취소
 
17
직권말소
 
10

Length

Max length4
Median length2
Mean length2.6027397
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 216
59.2%
영업중 66
 
18.1%
등록취소 50
 
13.7%
신고취소 17
 
4.7%
직권말소 10
 
2.7%
전출 6
 
1.6%

Length

2024-05-11T14:38:13.551080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:13.716836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 216
59.2%
영업중 66
 
18.1%
등록취소 50
 
13.7%
신고취소 17
 
4.7%
직권말소 10
 
2.7%
전출 6
 
1.6%

폐업일자
Date

MISSING 

Distinct203
Distinct (%)88.3%
Missing135
Missing (%)37.0%
Memory size3.0 KiB
Minimum1997-10-20 00:00:00
Maximum2024-02-14 00:00:00
2024-05-11T14:38:13.907115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:14.104458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

전화번호
Text

MISSING 

Distinct265
Distinct (%)93.3%
Missing81
Missing (%)22.2%
Memory size3.0 KiB
2024-05-11T14:38:14.436697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.4964789
Min length3

Characters and Unicode

Total characters2697
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

Unique254 ?
Unique (%)89.4%

Sample

1st row02-324-3781
2nd row3141-3889
3rd row711-9900
4th row564-5666
5th row3274-5599
ValueCountFrequency (%)
6049-4051 9
 
3.2%
02-6049-4051 3
 
1.1%
02-363-5551 2
 
0.7%
02-322-6001 2
 
0.7%
3665-1424 2
 
0.7%
070-7423-2063 2
 
0.7%
2233-7633 2
 
0.7%
734-0300 2
 
0.7%
392-7772 2
 
0.7%
334-1335 2
 
0.7%
Other values (255) 256
90.1%
2024-05-11T14:38:14.946963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 384
14.2%
- 366
13.6%
3 328
12.2%
2 296
11.0%
7 274
10.2%
1 246
9.1%
4 187
6.9%
5 184
6.8%
6 183
6.8%
8 151
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2331
86.4%
Dash Punctuation 366
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 384
16.5%
3 328
14.1%
2 296
12.7%
7 274
11.8%
1 246
10.6%
4 187
8.0%
5 184
7.9%
6 183
7.9%
8 151
 
6.5%
9 98
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2697
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 384
14.2%
- 366
13.6%
3 328
12.2%
2 296
11.0%
7 274
10.2%
1 246
9.1%
4 187
6.9%
5 184
6.8%
6 183
6.8%
8 151
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2697
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 384
14.2%
- 366
13.6%
3 328
12.2%
2 296
11.0%
7 274
10.2%
1 246
9.1%
4 187
6.9%
5 184
6.8%
6 183
6.8%
8 151
 
5.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

소재지우편번호
Text

MISSING 

Distinct101
Distinct (%)43.7%
Missing134
Missing (%)36.7%
Memory size3.0 KiB
2024-05-11T14:38:15.377960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0822511
Min length6

Characters and Unicode

Total characters1405
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

Unique52 ?
Unique (%)22.5%

Sample

1st row121-838
2nd row121883
3rd row121715
4th row121859
5th row121806
ValueCountFrequency (%)
121805 10
 
4.3%
121812 9
 
3.9%
121898 9
 
3.9%
121050 7
 
3.0%
121838 7
 
3.0%
121210 7
 
3.0%
121817 6
 
2.6%
121819 6
 
2.6%
121883 6
 
2.6%
121200 6
 
2.6%
Other values (91) 158
68.4%
2024-05-11T14:38:16.140216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 524
37.3%
2 275
19.6%
8 201
 
14.3%
0 91
 
6.5%
7 71
 
5.1%
9 63
 
4.5%
5 49
 
3.5%
3 44
 
3.1%
4 41
 
2.9%
6 27
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1386
98.6%
Dash Punctuation 19
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 524
37.8%
2 275
19.8%
8 201
 
14.5%
0 91
 
6.6%
7 71
 
5.1%
9 63
 
4.5%
5 49
 
3.5%
3 44
 
3.2%
4 41
 
3.0%
6 27
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1405
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 524
37.3%
2 275
19.6%
8 201
 
14.3%
0 91
 
6.5%
7 71
 
5.1%
9 63
 
4.5%
5 49
 
3.5%
3 44
 
3.1%
4 41
 
2.9%
6 27
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1405
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 524
37.3%
2 275
19.6%
8 201
 
14.3%
0 91
 
6.5%
7 71
 
5.1%
9 63
 
4.5%
5 49
 
3.5%
3 44
 
3.1%
4 41
 
2.9%
6 27
 
1.9%
Distinct356
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T14:38:16.667566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length29.367123
Min length16

Characters and Unicode

Total characters10719
Distinct characters242
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)95.1%

Sample

1st row서울특별시 마포구 서교동 353-5
2nd row서울특별시 마포구 합정동 414-1번지 동성하우스 101호
3rd row서울특별시 마포구 도화동 51-1번지 성우빌딩 801동
4th row서울특별시 마포구 아현동 330-3번지 송림빌딩 302동
5th row서울특별시 마포구 노고산동 31-135번지 무송빌딩 2층호
ValueCountFrequency (%)
서울특별시 365
 
17.7%
마포구 365
 
17.7%
서교동 66
 
3.2%
동교동 56
 
2.7%
도화동 47
 
2.3%
공덕동 36
 
1.7%
3층 32
 
1.6%
2층 31
 
1.5%
합정동 25
 
1.2%
마포동 19
 
0.9%
Other values (646) 1016
49.4%
2024-05-11T14:38:17.426707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1838
 
17.1%
1 463
 
4.3%
450
 
4.2%
444
 
4.1%
408
 
3.8%
397
 
3.7%
370
 
3.5%
370
 
3.5%
367
 
3.4%
366
 
3.4%
Other values (232) 5246
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6231
58.1%
Decimal Number 2277
 
21.2%
Space Separator 1838
 
17.1%
Dash Punctuation 289
 
2.7%
Uppercase Letter 53
 
0.5%
Lowercase Letter 10
 
0.1%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 5
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
450
 
7.2%
444
 
7.1%
408
 
6.5%
397
 
6.4%
370
 
5.9%
370
 
5.9%
367
 
5.9%
366
 
5.9%
365
 
5.9%
255
 
4.1%
Other values (191) 2439
39.1%
Uppercase Letter
ValueCountFrequency (%)
L 8
15.1%
T 7
13.2%
G 6
11.3%
I 4
7.5%
P 4
7.5%
B 4
7.5%
S 3
 
5.7%
C 3
 
5.7%
V 3
 
5.7%
A 3
 
5.7%
Other values (7) 8
15.1%
Decimal Number
ValueCountFrequency (%)
1 463
20.3%
3 312
13.7%
2 271
11.9%
0 259
11.4%
5 227
10.0%
4 225
9.9%
6 164
 
7.2%
7 143
 
6.3%
8 109
 
4.8%
9 104
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
v 2
20.0%
p 2
20.0%
i 2
20.0%
e 1
10.0%
r 1
10.0%
w 1
10.0%
o 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1838
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6231
58.1%
Common 4423
41.3%
Latin 65
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
450
 
7.2%
444
 
7.1%
408
 
6.5%
397
 
6.4%
370
 
5.9%
370
 
5.9%
367
 
5.9%
366
 
5.9%
365
 
5.9%
255
 
4.1%
Other values (191) 2439
39.1%
Latin
ValueCountFrequency (%)
L 8
 
12.3%
T 7
 
10.8%
G 6
 
9.2%
I 4
 
6.2%
P 4
 
6.2%
B 4
 
6.2%
S 3
 
4.6%
C 3
 
4.6%
V 3
 
4.6%
A 3
 
4.6%
Other values (15) 20
30.8%
Common
ValueCountFrequency (%)
1838
41.6%
1 463
 
10.5%
3 312
 
7.1%
- 289
 
6.5%
2 271
 
6.1%
0 259
 
5.9%
5 227
 
5.1%
4 225
 
5.1%
6 164
 
3.7%
7 143
 
3.2%
Other values (6) 232
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6230
58.1%
ASCII 4486
41.9%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1838
41.0%
1 463
 
10.3%
3 312
 
7.0%
- 289
 
6.4%
2 271
 
6.0%
0 259
 
5.8%
5 227
 
5.1%
4 225
 
5.0%
6 164
 
3.7%
7 143
 
3.2%
Other values (30) 295
 
6.6%
Hangul
ValueCountFrequency (%)
450
 
7.2%
444
 
7.1%
408
 
6.5%
397
 
6.4%
370
 
5.9%
370
 
5.9%
367
 
5.9%
366
 
5.9%
365
 
5.9%
255
 
4.1%
Other values (190) 2438
39.1%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct339
Distinct (%)97.4%
Missing17
Missing (%)4.7%
Memory size3.0 KiB
2024-05-11T14:38:17.853776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length45
Mean length35.054598
Min length23

Characters and Unicode

Total characters12199
Distinct characters262
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique330 ?
Unique (%)94.8%

Sample

1st row서울특별시 마포구 양화로 125 (서교동)
2nd row서울특별시 마포구 양화로 50, 101호 (합정동,동성하우스)
3rd row서울특별시 마포구 마포대로 49, 801동 (도화동,성우빌딩)
4th row서울특별시 마포구 신촌로 266, 302동 (아현동,송림빌딩)
5th row서울특별시 마포구 신촌로 102-1, 2층호 (노고산동,무송빌딩)
ValueCountFrequency (%)
서울특별시 348
 
15.4%
마포구 348
 
15.4%
마포대로 65
 
2.9%
서교동 50
 
2.2%
동교동 39
 
1.7%
양화로 35
 
1.6%
3층 32
 
1.4%
2층 29
 
1.3%
도화동 25
 
1.1%
공덕동 23
 
1.0%
Other values (652) 1261
55.9%
2024-05-11T14:38:18.668464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2031
 
16.6%
, 469
 
3.8%
460
 
3.8%
455
 
3.7%
449
 
3.7%
1 446
 
3.7%
431
 
3.5%
) 356
 
2.9%
( 356
 
2.9%
353
 
2.9%
Other values (252) 6393
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6976
57.2%
Space Separator 2031
 
16.6%
Decimal Number 1893
 
15.5%
Other Punctuation 470
 
3.9%
Close Punctuation 356
 
2.9%
Open Punctuation 356
 
2.9%
Uppercase Letter 61
 
0.5%
Dash Punctuation 44
 
0.4%
Lowercase Letter 10
 
0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
460
 
6.6%
455
 
6.5%
449
 
6.4%
431
 
6.2%
353
 
5.1%
353
 
5.1%
350
 
5.0%
349
 
5.0%
348
 
5.0%
345
 
4.9%
Other values (211) 3083
44.2%
Uppercase Letter
ValueCountFrequency (%)
L 10
16.4%
T 7
11.5%
G 6
9.8%
B 5
8.2%
I 4
 
6.6%
C 4
 
6.6%
D 4
 
6.6%
V 3
 
4.9%
A 3
 
4.9%
P 3
 
4.9%
Other values (7) 12
19.7%
Decimal Number
ValueCountFrequency (%)
1 446
23.6%
2 280
14.8%
3 217
11.5%
0 198
10.5%
4 157
 
8.3%
7 151
 
8.0%
6 145
 
7.7%
5 140
 
7.4%
8 90
 
4.8%
9 69
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
p 2
20.0%
i 2
20.0%
v 2
20.0%
o 1
10.0%
r 1
10.0%
e 1
10.0%
w 1
10.0%
Other Punctuation
ValueCountFrequency (%)
, 469
99.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2031
100.0%
Close Punctuation
ValueCountFrequency (%)
) 356
100.0%
Open Punctuation
ValueCountFrequency (%)
( 356
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6976
57.2%
Common 5150
42.2%
Latin 73
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
460
 
6.6%
455
 
6.5%
449
 
6.4%
431
 
6.2%
353
 
5.1%
353
 
5.1%
350
 
5.0%
349
 
5.0%
348
 
5.0%
345
 
4.9%
Other values (211) 3083
44.2%
Latin
ValueCountFrequency (%)
L 10
13.7%
T 7
 
9.6%
G 6
 
8.2%
B 5
 
6.8%
I 4
 
5.5%
C 4
 
5.5%
D 4
 
5.5%
V 3
 
4.1%
A 3
 
4.1%
P 3
 
4.1%
Other values (15) 24
32.9%
Common
ValueCountFrequency (%)
2031
39.4%
, 469
 
9.1%
1 446
 
8.7%
) 356
 
6.9%
( 356
 
6.9%
2 280
 
5.4%
3 217
 
4.2%
0 198
 
3.8%
4 157
 
3.0%
7 151
 
2.9%
Other values (6) 489
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6975
57.2%
ASCII 5221
42.8%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2031
38.9%
, 469
 
9.0%
1 446
 
8.5%
) 356
 
6.8%
( 356
 
6.8%
2 280
 
5.4%
3 217
 
4.2%
0 198
 
3.8%
4 157
 
3.0%
7 151
 
2.9%
Other values (30) 560
 
10.7%
Hangul
ValueCountFrequency (%)
460
 
6.6%
455
 
6.5%
449
 
6.4%
431
 
6.2%
353
 
5.1%
353
 
5.1%
350
 
5.0%
349
 
5.0%
348
 
5.0%
345
 
4.9%
Other values (210) 3082
44.2%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Text

MISSING 

Distinct114
Distinct (%)52.1%
Missing146
Missing (%)40.0%
Memory size3.0 KiB
2024-05-11T14:38:19.227705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.1598174
Min length5

Characters and Unicode

Total characters1130
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

Unique74 ?
Unique (%)33.8%

Sample

1st row04032
2nd row04058
3rd row04212
4th row04168
5th row04158
ValueCountFrequency (%)
04144 10
 
4.6%
04043 9
 
4.1%
03992 8
 
3.7%
04050 7
 
3.2%
04158 7
 
3.2%
121898 7
 
3.2%
04157 6
 
2.7%
04056 5
 
2.3%
04083 4
 
1.8%
03993 4
 
1.8%
Other values (104) 152
69.4%
2024-05-11T14:38:20.018725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 302
26.7%
4 205
18.1%
1 169
15.0%
3 84
 
7.4%
9 84
 
7.4%
2 79
 
7.0%
5 63
 
5.6%
8 60
 
5.3%
7 42
 
3.7%
6 38
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1126
99.6%
Dash Punctuation 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 302
26.8%
4 205
18.2%
1 169
15.0%
3 84
 
7.5%
9 84
 
7.5%
2 79
 
7.0%
5 63
 
5.6%
8 60
 
5.3%
7 42
 
3.7%
6 38
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 302
26.7%
4 205
18.1%
1 169
15.0%
3 84
 
7.4%
9 84
 
7.4%
2 79
 
7.0%
5 63
 
5.6%
8 60
 
5.3%
7 42
 
3.7%
6 38
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 302
26.7%
4 205
18.1%
1 169
15.0%
3 84
 
7.4%
9 84
 
7.4%
2 79
 
7.0%
5 63
 
5.6%
8 60
 
5.3%
7 42
 
3.7%
6 38
 
3.4%
Distinct358
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T14:38:20.501127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.2931507
Min length3

Characters and Unicode

Total characters3027
Distinct characters354
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique351 ?
Unique (%)96.2%

Sample

1st row경남관광(주)
2nd row주-하이웨이여행사
3rd row주-썬코리아여행사
4th row주-삼호항공여행사
5th row주-서교여행사
ValueCountFrequency (%)
주식회사 52
 
12.1%
다솜투어 2
 
0.5%
씨월드 2
 
0.5%
여행사 2
 
0.5%
여행파트너(주 2
 
0.5%
주)이노캠프 2
 
0.5%
주)덕송라인 2
 
0.5%
주)차니항공여행사 2
 
0.5%
주)울릉씨투어 2
 
0.5%
주)주신에스알 2
 
0.5%
Other values (358) 358
83.6%
2024-05-11T14:38:21.188389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
9.6%
) 216
 
7.1%
( 215
 
7.1%
120
 
4.0%
102
 
3.4%
99
 
3.3%
97
 
3.2%
97
 
3.2%
90
 
3.0%
79
 
2.6%
Other values (344) 1622
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2481
82.0%
Close Punctuation 218
 
7.2%
Open Punctuation 217
 
7.2%
Space Separator 63
 
2.1%
Uppercase Letter 21
 
0.7%
Dash Punctuation 17
 
0.6%
Lowercase Letter 6
 
0.2%
Decimal Number 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
290
 
11.7%
120
 
4.8%
102
 
4.1%
99
 
4.0%
97
 
3.9%
97
 
3.9%
90
 
3.6%
79
 
3.2%
54
 
2.2%
54
 
2.2%
Other values (316) 1399
56.4%
Uppercase Letter
ValueCountFrequency (%)
T 4
19.0%
S 2
9.5%
R 2
9.5%
O 2
9.5%
E 2
9.5%
U 2
9.5%
C 1
 
4.8%
H 1
 
4.8%
L 1
 
4.8%
M 1
 
4.8%
Other values (3) 3
14.3%
Lowercase Letter
ValueCountFrequency (%)
i 2
33.3%
p 1
16.7%
n 1
16.7%
d 1
16.7%
r 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 216
99.1%
] 2
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 215
99.1%
[ 2
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 16
94.1%
1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2481
82.0%
Common 519
 
17.1%
Latin 27
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
290
 
11.7%
120
 
4.8%
102
 
4.1%
99
 
4.0%
97
 
3.9%
97
 
3.9%
90
 
3.6%
79
 
3.2%
54
 
2.2%
54
 
2.2%
Other values (316) 1399
56.4%
Latin
ValueCountFrequency (%)
T 4
14.8%
S 2
 
7.4%
R 2
 
7.4%
O 2
 
7.4%
E 2
 
7.4%
U 2
 
7.4%
i 2
 
7.4%
C 1
 
3.7%
H 1
 
3.7%
L 1
 
3.7%
Other values (8) 8
29.6%
Common
ValueCountFrequency (%)
) 216
41.6%
( 215
41.4%
63
 
12.1%
- 16
 
3.1%
[ 2
 
0.4%
] 2
 
0.4%
1 2
 
0.4%
& 1
 
0.2%
9 1
 
0.2%
1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2481
82.0%
ASCII 545
 
18.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
290
 
11.7%
120
 
4.8%
102
 
4.1%
99
 
4.0%
97
 
3.9%
97
 
3.9%
90
 
3.6%
79
 
3.2%
54
 
2.2%
54
 
2.2%
Other values (316) 1399
56.4%
ASCII
ValueCountFrequency (%)
) 216
39.6%
( 215
39.4%
63
 
11.6%
- 16
 
2.9%
T 4
 
0.7%
S 2
 
0.4%
[ 2
 
0.4%
R 2
 
0.4%
O 2
 
0.4%
E 2
 
0.4%
Other values (17) 21
 
3.9%
None
ValueCountFrequency (%)
1
100.0%
Distinct324
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2003-04-18 14:56:25
Maximum2024-03-26 09:40:45
2024-05-11T14:38:21.479002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:21.733542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
I
211 
U
152 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 211
57.8%
U 152
41.6%
D 2
 
0.5%

Length

2024-05-11T14:38:22.027084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:22.254632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 211
57.8%
u 152
41.6%
d 2
 
0.5%
Distinct110
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 23:04:00
2024-05-11T14:38:22.497004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:22.798677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct226
Distinct (%)63.3%
Missing8
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean193763.89
Minimum189392.98
Maximum196293.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:23.520771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189392.98
5-th percentile191438.09
Q1192668.15
median193383.42
Q3195237.64
95-th percentile195900.71
Maximum196293.23
Range6900.255
Interquartile range (IQR)2569.4914

Descriptive statistics

Standard deviation1528.9803
Coefficient of variation (CV)0.0078909454
Kurtosis-0.64011454
Mean193763.89
Median Absolute Deviation (MAD)1212.4984
Skewness-0.27028147
Sum69173709
Variance2337780.7
MonotonicityNot monotonic
2024-05-11T14:38:23.797269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195703.425296812 17
 
4.7%
193088.824663271 11
 
3.0%
193166.430144679 10
 
2.7%
195310.825031788 8
 
2.2%
195454.875715409 6
 
1.6%
195237.642733133 6
 
1.6%
194974.587674037 5
 
1.4%
194978.350112608 5
 
1.4%
195324.793653981 5
 
1.4%
193537.812453408 4
 
1.1%
Other values (216) 280
76.7%
(Missing) 8
 
2.2%
ValueCountFrequency (%)
189392.975995366 1
0.3%
189779.165991291 1
0.3%
189855.433985731 1
0.3%
189857.566447564 1
0.3%
190086.625449279 2
0.5%
190125.564768858 2
0.5%
190182.067334395 1
0.3%
190204.923593825 1
0.3%
190256.997348579 1
0.3%
190335.496775957 2
0.5%
ValueCountFrequency (%)
196293.231026739 1
 
0.3%
196147.981522304 1
 
0.3%
196073.348728269 1
 
0.3%
196069.938748134 2
0.5%
196057.949965838 3
0.8%
196043.165226453 1
 
0.3%
196032.486543817 1
 
0.3%
196031.099955729 1
 
0.3%
196025.308611352 2
0.5%
195981.419695746 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct226
Distinct (%)63.3%
Missing8
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean449947.16
Minimum448229.06
Maximum453614.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:24.086994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448229.06
5-th percentile448539.02
Q1449282.51
median449924.24
Q3450473.94
95-th percentile451529.83
Maximum453614.58
Range5385.5196
Interquartile range (IQR)1191.4251

Descriptive statistics

Standard deviation1006.463
Coefficient of variation (CV)0.0022368472
Kurtosis1.6174763
Mean449947.16
Median Absolute Deviation (MAD)593.44149
Skewness0.93297256
Sum1.6063114 × 108
Variance1012967.8
MonotonicityNot monotonic
2024-05-11T14:38:24.390249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449330.800717721 17
 
4.7%
450798.385203407 11
 
3.0%
450425.852790862 10
 
2.7%
448677.797932004 8
 
2.2%
448970.223733402 6
 
1.6%
448733.404817253 6
 
1.6%
448229.063825491 5
 
1.4%
448487.374314355 5
 
1.4%
448885.430093289 5
 
1.4%
450644.919295783 4
 
1.1%
Other values (216) 280
76.7%
(Missing) 8
 
2.2%
ValueCountFrequency (%)
448229.063825491 5
1.4%
448345.713688045 2
 
0.5%
448407.752664604 2
 
0.5%
448460.50414883 1
 
0.3%
448487.374314355 5
1.4%
448507.812256819 1
 
0.3%
448525.449037308 1
 
0.3%
448533.382459215 1
 
0.3%
448540.434893446 2
 
0.5%
448557.491625418 1
 
0.3%
ValueCountFrequency (%)
453614.583448105 1
0.3%
453360.240306636 1
0.3%
453271.198852486 1
0.3%
453231.427685063 2
0.5%
453141.676626027 1
0.3%
453114.7324935 1
0.3%
453090.149821248 2
0.5%
452758.642764785 2
0.5%
452647.977464275 1
0.3%
452434.679034834 1
0.3%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
국내여행업
265 
<NA>
100 

Length

Max length5
Median length5
Mean length4.7260274
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 265
72.6%
<NA> 100
 
27.4%

Length

2024-05-11T14:38:24.679211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:24.878315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 265
72.6%
na 100
 
27.4%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
217 
관광사업
148 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 217
59.5%
관광사업 148
40.5%

Length

2024-05-11T14:38:25.124949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:25.344744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 217
59.5%
관광사업 148
40.5%

지역구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
354 
근린상업지역
 
4
일반주거지역
 
4
일반공업지역
 
1
준공업지역
 
1

Length

Max length6
Median length4
Mean length4.0520548
Min length4

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
97.0%
근린상업지역 4
 
1.1%
일반주거지역 4
 
1.1%
일반공업지역 1
 
0.3%
준공업지역 1
 
0.3%
상업지역 1
 
0.3%

Length

2024-05-11T14:38:25.631881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:25.912843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 354
97.0%
근린상업지역 4
 
1.1%
일반주거지역 4
 
1.1%
일반공업지역 1
 
0.3%
준공업지역 1
 
0.3%
상업지역 1
 
0.3%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)11.1%
Missing302
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.93650794
Minimum0
Maximum16
Zeros54
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:26.099440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7642476
Coefficient of variation (CV)2.9516543
Kurtosis15.417414
Mean0.93650794
Median Absolute Deviation (MAD)0
Skewness3.6879602
Sum59
Variance7.641065
MonotonicityNot monotonic
2024-05-11T14:38:26.322590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 54
 
14.8%
6 4
 
1.1%
3 1
 
0.3%
16 1
 
0.3%
10 1
 
0.3%
2 1
 
0.3%
4 1
 
0.3%
(Missing) 302
82.7%
ValueCountFrequency (%)
0 54
14.8%
2 1
 
0.3%
3 1
 
0.3%
4 1
 
0.3%
6 4
 
1.1%
10 1
 
0.3%
16 1
 
0.3%
ValueCountFrequency (%)
16 1
 
0.3%
10 1
 
0.3%
6 4
 
1.1%
4 1
 
0.3%
3 1
 
0.3%
2 1
 
0.3%
0 54
14.8%

주변환경명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
361 
기타
 
4

Length

Max length4
Median length4
Mean length3.9780822
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 361
98.9%
기타 4
 
1.1%

Length

2024-05-11T14:38:26.621238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:26.824508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 361
98.9%
기타 4
 
1.1%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

보험기관명
Categorical

IMBALANCE 

Distinct25
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
241 
서울보증보험
51 
한국관광협회중앙회 여행공제회
 
14
서울보증보험주식회사
 
9
한국관광협회중앙회
 
6
Other values (20)
44 

Length

Max length18
Median length4
Mean length5.7123288
Min length4

Unique

Unique10 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 241
66.0%
서울보증보험 51
 
14.0%
한국관광협회중앙회 여행공제회 14
 
3.8%
서울보증보험주식회사 9
 
2.5%
한국관광협회중앙회 6
 
1.6%
서울보증보험(2천만원) 6
 
1.6%
한국관광협회 5
 
1.4%
서울보증보험(2천만) 4
 
1.1%
서울보증보험 2천 4
 
1.1%
여행공제회 3
 
0.8%
Other values (15) 22
 
6.0%

Length

2024-05-11T14:38:27.029435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 241
62.1%
서울보증보험 58
 
14.9%
한국관광협회중앙회 20
 
5.2%
여행공제회 19
 
4.9%
서울보증보험주식회사 9
 
2.3%
한국관광협회 7
 
1.8%
서울보증보험(2천만원 6
 
1.5%
서울보증보험(2천만 4
 
1.0%
2천 4
 
1.0%
서울보증보험(20,000,000 3
 
0.8%
Other values (13) 17
 
4.4%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
303 
근린생활시설
55 
사무실
 
6
기타
 
1

Length

Max length6
Median length4
Mean length4.2794521
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 303
83.0%
근린생활시설 55
 
15.1%
사무실 6
 
1.6%
기타 1
 
0.3%

Length

2024-05-11T14:38:27.194797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:27.338279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 303
83.0%
근린생활시설 55
 
15.1%
사무실 6
 
1.6%
기타 1
 
0.3%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)12.7%
Missing302
Missing (%)82.7%
Infinite0
Infinite (%)0.0%
Mean0.6984127
Minimum0
Maximum12
Zeros54
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:27.509337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.129932
Coefficient of variation (CV)3.0496754
Kurtosis14.701114
Mean0.6984127
Median Absolute Deviation (MAD)0
Skewness3.6878675
Sum44
Variance4.5366103
MonotonicityNot monotonic
2024-05-11T14:38:27.694938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 54
 
14.8%
5 2
 
0.5%
2 2
 
0.5%
6 1
 
0.3%
1 1
 
0.3%
12 1
 
0.3%
8 1
 
0.3%
3 1
 
0.3%
(Missing) 302
82.7%
ValueCountFrequency (%)
0 54
14.8%
1 1
 
0.3%
2 2
 
0.5%
3 1
 
0.3%
5 2
 
0.5%
6 1
 
0.3%
8 1
 
0.3%
12 1
 
0.3%
ValueCountFrequency (%)
12 1
 
0.3%
8 1
 
0.3%
6 1
 
0.3%
5 2
 
0.5%
3 1
 
0.3%
2 2
 
0.5%
1 1
 
0.3%
0 54
14.8%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
304 
0
54 
1
 
4
5
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.4986301
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 304
83.3%
0 54
 
14.8%
1 4
 
1.1%
5 1
 
0.3%
4 1
 
0.3%
2 1
 
0.3%

Length

2024-05-11T14:38:27.897231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:28.121552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 304
83.3%
0 54
 
14.8%
1 4
 
1.1%
5 1
 
0.3%
4 1
 
0.3%
2 1
 
0.3%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:28.358395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:28.540665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:28.723069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:28.836637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

영문상호명
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing354
Missing (%)97.0%
Memory size3.0 KiB
2024-05-11T14:38:29.030041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length15.545455
Min length8

Characters and Unicode

Total characters171
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowIRUM GLOBAL Co.,Ltd.
2nd rowSTL GTOUR Co., Ltd.
3rd rowSEAH TNS
4th rowSeoulHiking
5th rowTime Traveller
ValueCountFrequency (%)
co 4
 
12.9%
ltd 4
 
12.9%
tour 4
 
12.9%
irum 1
 
3.2%
da-all 1
 
3.2%
blanc 1
 
3.2%
theme 1
 
3.2%
deluxe 1
 
3.2%
gtsk 1
 
3.2%
freehan 1
 
3.2%
Other values (12) 12
38.7%
2024-05-11T14:38:29.433341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
11.7%
T 12
 
7.0%
L 11
 
6.4%
. 10
 
5.8%
o 9
 
5.3%
e 7
 
4.1%
r 6
 
3.5%
t 6
 
3.5%
E 5
 
2.9%
S 5
 
2.9%
Other values (29) 80
46.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 77
45.0%
Lowercase Letter 58
33.9%
Space Separator 20
 
11.7%
Other Punctuation 15
 
8.8%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 12
15.6%
L 11
14.3%
E 5
 
6.5%
S 5
 
6.5%
C 5
 
6.5%
U 5
 
6.5%
A 4
 
5.2%
O 4
 
5.2%
G 4
 
5.2%
R 4
 
5.2%
Other values (9) 18
23.4%
Lowercase Letter
ValueCountFrequency (%)
o 9
15.5%
e 7
12.1%
r 6
10.3%
t 6
10.3%
d 5
8.6%
n 4
6.9%
l 4
6.9%
a 3
 
5.2%
u 3
 
5.2%
i 3
 
5.2%
Other values (6) 8
13.8%
Other Punctuation
ValueCountFrequency (%)
. 10
66.7%
, 5
33.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 135
78.9%
Common 36
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 12
 
8.9%
L 11
 
8.1%
o 9
 
6.7%
e 7
 
5.2%
r 6
 
4.4%
t 6
 
4.4%
E 5
 
3.7%
S 5
 
3.7%
d 5
 
3.7%
C 5
 
3.7%
Other values (25) 64
47.4%
Common
ValueCountFrequency (%)
20
55.6%
. 10
27.8%
, 5
 
13.9%
- 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
 
11.7%
T 12
 
7.0%
L 11
 
6.4%
. 10
 
5.8%
o 9
 
5.3%
e 7
 
4.1%
r 6
 
3.5%
t 6
 
3.5%
E 5
 
2.9%
S 5
 
2.9%
Other values (29) 80
46.8%

영문상호주소
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
353 
Domestic travel business
 
5
Domestic Travel Business
 
5
General Travel Business
 
1
GENERAL TRAVEL BUSINESS
 
1

Length

Max length24
Median length4
Mean length4.6520548
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 353
96.7%
Domestic travel business 5
 
1.4%
Domestic Travel Business 5
 
1.4%
General Travel Business 1
 
0.3%
GENERAL TRAVEL BUSINESS 1
 
0.3%

Length

2024-05-11T14:38:29.697502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:29.933259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 353
90.7%
travel 12
 
3.1%
business 12
 
3.1%
domestic 10
 
2.6%
general 2
 
0.5%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:30.177235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:30.398008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:30.612967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:30.827977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:31.076133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:31.248278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:31.468889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:31.663263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:31.854506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:32.020791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)16.8%
Missing264
Missing (%)72.3%
Infinite0
Infinite (%)0.0%
Mean8.8081188
Minimum0
Maximum208.03
Zeros85
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:32.244704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41
Maximum208.03
Range208.03
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.192354
Coefficient of variation (CV)3.3142553
Kurtosis25.246671
Mean8.8081188
Median Absolute Deviation (MAD)0
Skewness4.6748802
Sum889.62
Variance852.19356
MonotonicityNot monotonic
2024-05-11T14:38:32.447392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 85
 
23.3%
122.81 1
 
0.3%
75.46 1
 
0.3%
73.46 1
 
0.3%
26.4 1
 
0.3%
15.0 1
 
0.3%
33.5 1
 
0.3%
30.02 1
 
0.3%
27.74 1
 
0.3%
208.03 1
 
0.3%
Other values (7) 7
 
1.9%
(Missing) 264
72.3%
ValueCountFrequency (%)
0.0 85
23.3%
4.0 1
 
0.3%
6.6 1
 
0.3%
15.0 1
 
0.3%
26.4 1
 
0.3%
27.74 1
 
0.3%
30.02 1
 
0.3%
30.89 1
 
0.3%
33.5 1
 
0.3%
35.71 1
 
0.3%
ValueCountFrequency (%)
208.03 1
0.3%
122.81 1
0.3%
120.0 1
0.3%
75.46 1
0.3%
73.46 1
0.3%
41.0 1
0.3%
39.0 1
0.3%
35.71 1
0.3%
33.5 1
0.3%
30.89 1
0.3%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
346 
0
 
19

Length

Max length4
Median length4
Mean length3.8438356
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> 346
94.8%
0 19
 
5.2%

Length

2024-05-11T14:38:32.682559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:32.926996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 346
94.8%
0 19
 
5.2%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

기획여행보험시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
363 
20220217
 
1
20130724
 
1

Length

Max length8
Median length4
Mean length4.0219178
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 363
99.5%
20220217 1
 
0.3%
20130724 1
 
0.3%

Length

2024-05-11T14:38:33.172756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:33.371778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
99.5%
20220217 1
 
0.3%
20130724 1
 
0.3%

기획여행보험종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
363 
20230216
 
1
20140723
 
1

Length

Max length8
Median length4
Mean length4.0219178
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 363
99.5%
20230216 1
 
0.3%
20140723 1
 
0.3%

Length

2024-05-11T14:38:33.599283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:33.817470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 363
99.5%
20230216 1
 
0.3%
20140723 1
 
0.3%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)17.5%
Missing211
Missing (%)57.8%
Infinite0
Infinite (%)0.0%
Mean75477798
Minimum0
Maximum1.1 × 109
Zeros4
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:34.028591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21451677
Q130000000
median50000000
Q390000000
95-th percentile1.705 × 108
Maximum1.1 × 109
Range1.1 × 109
Interquartile range (IQR)60000000

Descriptive statistics

Standard deviation1.0317132 × 108
Coefficient of variation (CV)1.3669095
Kurtosis64.668199
Mean75477798
Median Absolute Deviation (MAD)20000000
Skewness6.9933247
Sum1.1623581 × 1010
Variance1.0644321 × 1016
MonotonicityNot monotonic
2024-05-11T14:38:34.244409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
50000000 48
 
13.2%
30000000 43
 
11.8%
100000000 13
 
3.6%
150000000 13
 
3.6%
90000000 9
 
2.5%
0 4
 
1.1%
300000000 2
 
0.5%
200000000 2
 
0.5%
15000000 2
 
0.5%
93000000 1
 
0.3%
Other values (17) 17
 
4.7%
(Missing) 211
57.8%
ValueCountFrequency (%)
0 4
 
1.1%
15000000 2
 
0.5%
15128032 1
 
0.3%
18576219 1
 
0.3%
23000000 1
 
0.3%
25000000 1
 
0.3%
30000000 43
11.8%
35000000 1
 
0.3%
40000000 1
 
0.3%
43121390 1
 
0.3%
ValueCountFrequency (%)
1100000000 1
 
0.3%
450000000 1
 
0.3%
300000000 2
 
0.5%
246000000 1
 
0.3%
200000000 2
 
0.5%
190000000 1
 
0.3%
160000000 1
 
0.3%
157834068 1
 
0.3%
150000000 13
3.6%
100000000 13
3.6%

보험시작일자
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)93.8%
Missing236
Missing (%)64.7%
Infinite0
Infinite (%)0.0%
Mean20148916
Minimum20030313
Maximum20211027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:34.544932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030313
5-th percentile20060708
Q120120704
median20150711
Q320190312
95-th percentile20210601
Maximum20211027
Range180714
Interquartile range (IQR)69608

Descriptive statistics

Standard deviation44250.774
Coefficient of variation (CV)0.0021961864
Kurtosis-0.066734886
Mean20148916
Median Absolute Deviation (MAD)30291
Skewness-0.5558165
Sum2.5992101 × 109
Variance1.958131 × 109
MonotonicityNot monotonic
2024-05-11T14:38:35.236394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150330 3
 
0.8%
20160401 3
 
0.8%
20190603 2
 
0.5%
20150206 2
 
0.5%
20201001 2
 
0.5%
20210601 2
 
0.5%
20151021 1
 
0.3%
20150407 1
 
0.3%
20151126 1
 
0.3%
20150909 1
 
0.3%
Other values (111) 111
30.4%
(Missing) 236
64.7%
ValueCountFrequency (%)
20030313 1
0.3%
20031021 1
0.3%
20041210 1
0.3%
20050601 1
0.3%
20050706 1
0.3%
20051221 1
0.3%
20060627 1
0.3%
20060830 1
0.3%
20070913 1
0.3%
20080415 1
0.3%
ValueCountFrequency (%)
20211027 1
0.3%
20210823 1
0.3%
20210820 1
0.3%
20210806 1
0.3%
20210803 1
0.3%
20210714 1
0.3%
20210601 2
0.5%
20210528 1
0.3%
20210524 1
0.3%
20210513 1
0.3%

보험종료일자
Real number (ℝ)

MISSING 

Distinct120
Distinct (%)93.8%
Missing237
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean20159983
Minimum20040313
Maximum20221026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:35.497829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040313
5-th percentile20070698
Q120130714
median20160770
Q320200314
95-th percentile20220602
Maximum20221026
Range180713
Interquartile range (IQR)69600.5

Descriptive statistics

Standard deviation44383.339
Coefficient of variation (CV)0.0022015563
Kurtosis-0.040922137
Mean20159983
Median Absolute Deviation (MAD)30285.5
Skewness-0.5453594
Sum2.5804779 × 109
Variance1.9698808 × 109
MonotonicityNot monotonic
2024-05-11T14:38:35.726269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20170331 3
 
0.8%
20160330 3
 
0.8%
20210930 2
 
0.5%
20160205 2
 
0.5%
20220531 2
 
0.5%
20220602 2
 
0.5%
20200323 1
 
0.3%
20161125 1
 
0.3%
20161124 1
 
0.3%
20170222 1
 
0.3%
Other values (110) 110
30.1%
(Missing) 237
64.9%
ValueCountFrequency (%)
20040313 1
0.3%
20041021 1
0.3%
20051210 1
0.3%
20060531 1
0.3%
20060706 1
0.3%
20061221 1
0.3%
20070627 1
0.3%
20070830 1
0.3%
20090415 1
0.3%
20090711 1
0.3%
ValueCountFrequency (%)
20221026 1
0.3%
20220822 1
0.3%
20220819 1
0.3%
20220805 1
0.3%
20220802 1
0.3%
20220713 1
0.3%
20220602 2
0.5%
20220531 2
0.5%
20220528 1
0.3%
20220527 1
0.3%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing365
Missing (%)100.0%
Memory size3.3 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)16.8%
Missing264
Missing (%)72.3%
Infinite0
Infinite (%)0.0%
Mean8.8118812
Minimum0
Maximum208
Zeros85
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T14:38:35.964028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile41
Maximum208
Range208
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.183801
Coefficient of variation (CV)3.3118696
Kurtosis25.265772
Mean8.8118812
Median Absolute Deviation (MAD)0
Skewness4.675996
Sum890
Variance851.69426
MonotonicityNot monotonic
2024-05-11T14:38:36.133896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 85
 
23.3%
123 1
 
0.3%
75 1
 
0.3%
73 1
 
0.3%
26 1
 
0.3%
15 1
 
0.3%
34 1
 
0.3%
30 1
 
0.3%
28 1
 
0.3%
208 1
 
0.3%
Other values (7) 7
 
1.9%
(Missing) 264
72.3%
ValueCountFrequency (%)
0 85
23.3%
4 1
 
0.3%
7 1
 
0.3%
15 1
 
0.3%
26 1
 
0.3%
28 1
 
0.3%
30 1
 
0.3%
31 1
 
0.3%
34 1
 
0.3%
36 1
 
0.3%
ValueCountFrequency (%)
208 1
0.3%
123 1
0.3%
120 1
0.3%
75 1
0.3%
73 1
0.3%
41 1
0.3%
39 1
0.3%
36 1
0.3%
34 1
0.3%
31 1
0.3%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03130000CDFI22600119720000011972-11-13<NA>1영업/정상13영업중<NA><NA><NA><NA>02-324-3781<NA>121-838서울특별시 마포구 서교동 353-5서울특별시 마포구 양화로 125 (서교동)04032경남관광(주)2023-07-24 13:21:06U2022-12-06 22:06:00.0<NA>192887.159606450276.024385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13130000CDFI226001198300000119830907<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>3141-3889<NA>121883서울특별시 마포구 합정동 414-1번지 동성하우스 101호서울특별시 마포구 양화로 50, 101호 (합정동,동성하우스)<NA>주-하이웨이여행사2003-04-18 14:56:25I2018-08-31 23:59:59.0<NA>192377.277695449695.089965국내여행업관광사업<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
23130000CDFI226001199100000119910426<NA>3폐업3폐업19980328<NA><NA><NA><NA><NA>121715서울특별시 마포구 도화동 51-1번지 성우빌딩 801동서울특별시 마포구 마포대로 49, 801동 (도화동,성우빌딩)<NA>주-썬코리아여행사2003-04-18 14:56:41I2018-08-31 23:59:59.0<NA>195237.642733448733.404817국내여행업관광사업<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
33130000CDFI226001199100000219911210<NA>3폐업3폐업19971223<NA><NA><NA><NA><NA>121859서울특별시 마포구 아현동 330-3번지 송림빌딩 302동서울특별시 마포구 신촌로 266, 302동 (아현동,송림빌딩)<NA>주-삼호항공여행사2003-04-18 14:56:41I2018-08-31 23:59:59.0<NA>195963.808713450536.468632국내여행업관광사업<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
43130000CDFI226001199200000119921117<NA>3폐업3폐업20040224<NA><NA><NA>711-9900<NA>121806서울특별시 마포구 노고산동 31-135번지 무송빌딩 2층호서울특별시 마포구 신촌로 102-1, 2층호 (노고산동,무송빌딩)<NA>주-서교여행사2004-02-25 14:52:06I2018-08-31 23:59:59.0<NA>194397.553053450261.16041국내여행업관광사업<NA><NA>기타<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
53130000CDFI226001199300000119930209<NA>4취소/말소/만료/정지/중지32신고취소<NA><NA><NA><NA>564-5666<NA>121050서울특별시 마포구 마포동 35-1번지서울특별시 마포구 마포대로 15 (마포동)<NA>(주)인터컨티넨탈여행사2003-04-18 14:56:41I2018-08-31 23:59:59.0<NA>194978.350113448487.374314국내여행업관광사업<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
63130000CDFI226001199300000219930729<NA>3폐업3폐업19971020<NA><NA><NA><NA><NA>121815서울특별시 마포구 도화동 544-0번지서울특별시 마포구 큰우물로 76 (도화동)<NA>주-세진여행사2003-04-18 14:56:41I2018-08-31 23:59:59.0<NA>195153.205994448725.077064국내여행업관광사업<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
73130000CDFI226001199500000119950603<NA>3폐업3폐업19980202<NA><NA><NA>3274-5599<NA>121812서울특별시 마포구 도화동 173-0번지 삼창프라자 9층호서울특별시 마포구 마포대로 63-8, 9층호 (도화동,삼창프라자)<NA>주-신원2003-04-18 14:56:25I2018-08-31 23:59:59.0<NA>195324.793654448885.430093국내여행업관광사업<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
83130000CDFI226001199500000219950705<NA>3폐업3폐업20140226<NA><NA><NA>3141-6354<NA>121711서울특별시 마포구 성산동 370번지 마포구청 본관 지하1층<NA><NA>(주)삼주여행사2014-02-26 13:53:34I2018-08-31 23:59:59.0<NA>191267.19524451555.668041국내여행업관광사업<NA>0<NA><NA>한국관광협회중앙회 여행공제회근린생활시설00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA>2011053120120531<NA>0
93130000CDFI226001199600000119960510<NA>3폐업3폐업20001228<NA><NA><NA>322-2344<NA>121896서울특별시 마포구 서교동 440-5번지 2층호서울특별시 마포구 월드컵로 94, 2층호 (서교동)<NA>주-샘국제여행사2003-04-18 14:56:41I2018-08-31 23:59:59.0<NA>191939.262193450547.752162국내여행업관광사업<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
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
3553130000CDFI22600120230000032015-01-20<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 471-2 프리마빌딩서울특별시 마포구 방울내로11길 37, 프리마빌딩 2층 2190호 (망원동)03961화산여행사2023-09-01 14:09:25U2022-12-09 00:03:00.0<NA>191397.589464451116.947316<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3563130000CDFI22600120230000042005-10-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>121-718서울특별시 마포구 공덕동 404 풍림빌딩 912호<NA><NA>(주)크레디투어2023-11-23 18:04:05D2022-10-31 22:05:00.0<NA>195703.425297449330.800718<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3573130000CDFI22600120230000052007-02-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-711-5025<NA>121-809서울특별시 마포구 대흥동 163-1 골드빌딩 1층<NA><NA>(주)주신에스알2023-11-23 18:03:04D2022-10-31 22:05:00.0<NA>194901.295478449580.543628<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3583130000CDFI22600120230000072013-08-19<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4112-4339<NA><NA>서울특별시 마포구 서교동 459-7 잔다리빌딩 304호서울특별시 마포구 동교로 125, 잔다리빌딩 304호 (서교동)04002(주)맛조이코리아2023-08-03 13:59:36U2022-12-08 00:05:00.0<NA>192508.796598450322.734455<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3593130000CDFI22600120230000082023-09-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 동교동 203-4 5층서울특별시 마포구 월드컵북로6길 36, 5층 (동교동)03992주식회사 여행너머2023-10-16 17:27:57U2022-10-30 23:08:00.0<NA>192907.931093450699.914173<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3603130000CDFI22600120230000092023-12-28<NA>1영업/정상13영업중<NA><NA><NA><NA>070-4035-0523<NA><NA>서울특별시 마포구 상수동 146-9서울특별시 마포구 와우산로 41-1, 5층 (상수동)04049누비고2023-12-28 13:14:49I2022-11-01 21:00:00.0<NA>193106.578305449556.820963<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3613130000CDFI22600120240000012018-07-30<NA>1영업/정상13영업중<NA><NA><NA><NA>070-7575-2351<NA><NA>서울특별시 마포구 서교동 394-44 서교제일빌딩서울특별시 마포구 양화로 64, 서교제일빌딩 9층 902호 (서교동)04045주식회사 필더필2024-01-24 09:16:28I2023-11-30 22:06:00.0<NA>192488.985145449787.214169<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3623130000CDFI22600120240000022021-09-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 도화동 51-1 성우빌딩서울특별시 마포구 마포대로 49, 성우빌딩 502호 (도화동)04158주식회사 프랜딧2024-01-24 09:26:00I2023-11-30 22:06:00.0<NA>195237.642733448733.404817<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3633130000CDFI22600120240000032024-02-16<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 서교동 351-24 203호서울특별시 마포구 동교로 162, 203호 (서교동)04031밸류체인코리아2024-02-16 13:46:33I2023-12-01 23:08:00.0<NA>192853.826977450374.220949<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3643130000CDFI22600120240000042007-02-27<NA>1영업/정상13영업중<NA><NA><NA><NA>3665-1424<NA>121-784서울특별시 마포구 도화동 559 마포트라팰리스 에이동 3007호<NA><NA>(주)이노캠프2024-03-21 13:13:36I2023-12-02 22:03:00.0<NA>195266.073146448799.641804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>