Overview

Dataset statistics

Number of variables60
Number of observations100
Missing cells2406
Missing cells (%)40.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.8 KiB
Average record size in memory520.3 B

Variable types

Categorical22
Text7
DateTime4
Unsupported17
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-17597/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
지역구분명 is highly imbalanced (62.1%)Imbalance
주변환경명 is highly imbalanced (67.1%)Imbalance
건물용도명 is highly imbalanced (59.3%)Imbalance
지하층수 is highly imbalanced (65.7%)Imbalance
객실수 is highly imbalanced (71.4%)Imbalance
건축연면적 is highly imbalanced (76.9%)Imbalance
영문상호주소 is highly imbalanced (75.6%)Imbalance
선박총톤수 is highly imbalanced (71.4%)Imbalance
선박척수 is highly imbalanced (71.4%)Imbalance
무대면적 is highly imbalanced (71.4%)Imbalance
좌석수 is highly imbalanced (71.4%)Imbalance
회의실별동시수용인원 is highly imbalanced (71.4%)Imbalance
놀이시설수 is highly imbalanced (71.4%)Imbalance
인허가취소일자 has 100 (100.0%) missing valuesMissing
폐업일자 has 42 (42.0%) missing valuesMissing
휴업시작일자 has 100 (100.0%) missing valuesMissing
휴업종료일자 has 100 (100.0%) missing valuesMissing
재개업일자 has 100 (100.0%) missing valuesMissing
전화번호 has 43 (43.0%) missing valuesMissing
소재지면적 has 100 (100.0%) missing valuesMissing
소재지우편번호 has 43 (43.0%) missing valuesMissing
도로명우편번호 has 38 (38.0%) missing valuesMissing
업태구분명 has 100 (100.0%) missing valuesMissing
총층수 has 84 (84.0%) missing valuesMissing
제작취급품목내용 has 100 (100.0%) missing valuesMissing
지상층수 has 80 (80.0%) missing valuesMissing
영문상호명 has 92 (92.0%) missing valuesMissing
선박제원 has 100 (100.0%) missing valuesMissing
기념품종류 has 100 (100.0%) missing valuesMissing
시설면적 has 72 (72.0%) missing valuesMissing
놀이기구수내역 has 100 (100.0%) missing valuesMissing
방송시설유무 has 100 (100.0%) missing valuesMissing
발전시설유무 has 100 (100.0%) missing valuesMissing
의무실유무 has 100 (100.0%) missing valuesMissing
안내소유무 has 100 (100.0%) missing valuesMissing
기획여행보험시작일자 has 100 (100.0%) missing valuesMissing
기획여행보험종료일자 has 100 (100.0%) missing valuesMissing
자본금 has 45 (45.0%) missing valuesMissing
보험시작일자 has 49 (49.0%) missing valuesMissing
보험종료일자 has 45 (45.0%) missing valuesMissing
부대시설내역 has 100 (100.0%) missing valuesMissing
시설규모 has 72 (72.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 6 (6.0%) zerosZeros
지상층수 has 6 (6.0%) zerosZeros
시설면적 has 10 (10.0%) zerosZeros
시설규모 has 10 (10.0%) zerosZeros

Reproduction

Analysis started2024-04-06 12:22:59.164452
Analysis finished2024-04-06 12:23:00.379858
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3200000
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 100
100.0%

Length

2024-04-06T21:23:00.564893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:01.192603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 100
100.0%

관리번호
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T21:23:01.468455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2000
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

Unique100 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021994000001
2nd rowCDFI2260021997000001
3rd rowCDFI2260021997000002
4th rowCDFI2260021998000001
5th rowCDFI2260021998000005
ValueCountFrequency (%)
cdfi2260021994000001 1
 
1.0%
cdfi2260022016000001 1
 
1.0%
cdfi2260022018000004 1
 
1.0%
cdfi2260022018000003 1
 
1.0%
cdfi2260022018000002 1
 
1.0%
cdfi2260022017000008 1
 
1.0%
cdfi2260022017000007 1
 
1.0%
cdfi2260022017000003 1
 
1.0%
cdfi2260022017000002 1
 
1.0%
cdfi2260022017000001 1
 
1.0%
Other values (90) 90
90.0%
2024-04-06T21:23:02.085626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 821
41.0%
2 446
22.3%
6 110
 
5.5%
1 109
 
5.5%
C 100
 
5.0%
D 100
 
5.0%
F 100
 
5.0%
I 100
 
5.0%
9 29
 
1.5%
3 25
 
1.2%
Other values (4) 60
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
80.0%
Uppercase Letter 400
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 821
51.3%
2 446
27.9%
6 110
 
6.9%
1 109
 
6.8%
9 29
 
1.8%
3 25
 
1.6%
7 18
 
1.1%
4 17
 
1.1%
8 13
 
0.8%
5 12
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 100
25.0%
D 100
25.0%
F 100
25.0%
I 100
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1600
80.0%
Latin 400
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 821
51.3%
2 446
27.9%
6 110
 
6.9%
1 109
 
6.8%
9 29
 
1.8%
3 25
 
1.6%
7 18
 
1.1%
4 17
 
1.1%
8 13
 
0.8%
5 12
 
0.8%
Latin
ValueCountFrequency (%)
C 100
25.0%
D 100
25.0%
F 100
25.0%
I 100
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 821
41.0%
2 446
22.3%
6 110
 
5.5%
1 109
 
5.5%
C 100
 
5.0%
D 100
 
5.0%
F 100
 
5.0%
I 100
 
5.0%
9 29
 
1.5%
3 25
 
1.2%
Other values (4) 60
 
3.0%
Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum1994-05-11 00:00:00
Maximum2023-08-31 00:00:00
2024-04-06T21:23:02.420424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:02.691669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB
Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
54 
1
40 
5
 
4
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 54
54.0%
1 40
40.0%
5 4
 
4.0%
4 2
 
2.0%

Length

2024-04-06T21:23:02.937926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:03.163226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 54
54.0%
1 40
40.0%
5 4
 
4.0%
4 2
 
2.0%

영업상태명
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
폐업
54 
영업/정상
40 
제외/삭제/전출
 
4
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length2
Mean length3.68
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 54
54.0%
영업/정상 40
40.0%
제외/삭제/전출 4
 
4.0%
취소/말소/만료/정지/중지 2
 
2.0%

Length

2024-04-06T21:23:03.477652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:03.759699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 54
54.0%
영업/정상 40
40.0%
제외/삭제/전출 4
 
4.0%
취소/말소/만료/정지/중지 2
 
2.0%
Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
3
54 
13
40 
15
 
4
30
 
2

Length

Max length2
Median length1
Mean length1.46
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row30
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 54
54.0%
13 40
40.0%
15 4
 
4.0%
30 2
 
2.0%

Length

2024-04-06T21:23:04.004597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:04.234494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 54
54.0%
13 40
40.0%
15 4
 
4.0%
30 2
 
2.0%
Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
폐업
54 
영업중
40 
전출
 
4
허가취소
 
2

Length

Max length4
Median length2
Mean length2.44
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 54
54.0%
영업중 40
40.0%
전출 4
 
4.0%
허가취소 2
 
2.0%

Length

2024-04-06T21:23:04.462999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:04.674163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 54
54.0%
영업중 40
40.0%
전출 4
 
4.0%
허가취소 2
 
2.0%

폐업일자
Date

MISSING 

Distinct58
Distinct (%)100.0%
Missing42
Missing (%)42.0%
Memory size932.0 B
Minimum1997-11-17 00:00:00
Maximum2024-02-19 00:00:00
2024-04-06T21:23:04.918653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:05.160540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

전화번호
Text

MISSING 

Distinct57
Distinct (%)100.0%
Missing43
Missing (%)43.0%
Memory size932.0 B
2024-04-06T21:23:05.609683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length10.087719
Min length8

Characters and Unicode

Total characters575
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row873-5688
2nd row882-0080
3rd row874-5656
4th row02-874-5151
5th row872-7788
ValueCountFrequency (%)
773-5545,885-8678 1
 
1.7%
02-6959-9881 1
 
1.7%
02-565-8816 1
 
1.7%
02-888-8287 1
 
1.7%
02-3289-8777 1
 
1.7%
02-730-8691 1
 
1.7%
02-871-1131 1
 
1.7%
02-725-0770 1
 
1.7%
02-588-3499 1
 
1.7%
02-852-8880 1
 
1.7%
Other values (49) 49
83.1%
2024-04-06T21:23:06.426219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 87
15.1%
8 79
13.7%
0 73
12.7%
7 68
11.8%
2 65
11.3%
5 49
8.5%
3 36
6.3%
6 36
6.3%
9 36
6.3%
1 27
 
4.7%
Other values (3) 19
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 485
84.3%
Dash Punctuation 87
 
15.1%
Space Separator 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 79
16.3%
0 73
15.1%
7 68
14.0%
2 65
13.4%
5 49
10.1%
3 36
7.4%
6 36
7.4%
9 36
7.4%
1 27
 
5.6%
4 16
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 87
15.1%
8 79
13.7%
0 73
12.7%
7 68
11.8%
2 65
11.3%
5 49
8.5%
3 36
6.3%
6 36
6.3%
9 36
6.3%
1 27
 
4.7%
Other values (3) 19
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 87
15.1%
8 79
13.7%
0 73
12.7%
7 68
11.8%
2 65
11.3%
5 49
8.5%
3 36
6.3%
6 36
6.3%
9 36
6.3%
1 27
 
4.7%
Other values (3) 19
 
3.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

소재지우편번호
Text

MISSING 

Distinct37
Distinct (%)64.9%
Missing43
Missing (%)43.0%
Memory size932.0 B
2024-04-06T21:23:06.947382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1052632
Min length6

Characters and Unicode

Total characters348
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

Unique28 ?
Unique (%)49.1%

Sample

1st row151832
2nd row151015
3rd row151822
4th row151015
5th row151840
ValueCountFrequency (%)
151015 6
 
10.5%
151050 5
 
8.8%
151836 4
 
7.0%
151800 3
 
5.3%
151903 3
 
5.3%
151840 2
 
3.5%
151834 2
 
3.5%
151849 2
 
3.5%
151801 2
 
3.5%
151-835 1
 
1.8%
Other values (27) 27
47.4%
2024-04-06T21:23:07.507617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 124
35.6%
5 71
20.4%
8 39
 
11.2%
0 37
 
10.6%
3 17
 
4.9%
9 17
 
4.9%
4 11
 
3.2%
2 9
 
2.6%
7 9
 
2.6%
6 8
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
98.3%
Dash Punctuation 6
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 124
36.3%
5 71
20.8%
8 39
 
11.4%
0 37
 
10.8%
3 17
 
5.0%
9 17
 
5.0%
4 11
 
3.2%
2 9
 
2.6%
7 9
 
2.6%
6 8
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 124
35.6%
5 71
20.4%
8 39
 
11.2%
0 37
 
10.6%
3 17
 
4.9%
9 17
 
4.9%
4 11
 
3.2%
2 9
 
2.6%
7 9
 
2.6%
6 8
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 124
35.6%
5 71
20.4%
8 39
 
11.2%
0 37
 
10.6%
3 17
 
4.9%
9 17
 
4.9%
4 11
 
3.2%
2 9
 
2.6%
7 9
 
2.6%
6 8
 
2.3%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T21:23:08.018566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length28.39
Min length18

Characters and Unicode

Total characters2839
Distinct characters131
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row서울특별시 관악구 봉천동 1632-1번지
2nd row서울특별시 관악구 신림동 1655-19번지 ,29
3rd row서울특별시 관악구 봉천동 871-67번지 2층
4th row서울특별시 관악구 신림동 1422-38
5th row서울특별시 관악구 봉천동 910-20번지
ValueCountFrequency (%)
서울특별시 100
18.9%
관악구 99
18.7%
봉천동 45
 
8.5%
신림동 43
 
8.1%
1층 11
 
2.1%
남현동 11
 
2.1%
남현프라자 4
 
0.8%
관악센츄리타워 4
 
0.8%
612-51 4
 
0.8%
869-10번지 4
 
0.8%
Other values (178) 204
38.6%
2024-04-06T21:23:08.748232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
471
 
16.6%
1 180
 
6.3%
109
 
3.8%
107
 
3.8%
106
 
3.7%
102
 
3.6%
101
 
3.6%
101
 
3.6%
100
 
3.5%
100
 
3.5%
Other values (121) 1362
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1589
56.0%
Decimal Number 671
23.6%
Space Separator 471
 
16.6%
Dash Punctuation 93
 
3.3%
Uppercase Letter 10
 
0.4%
Other Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
109
 
6.9%
107
 
6.7%
106
 
6.7%
102
 
6.4%
101
 
6.4%
101
 
6.4%
100
 
6.3%
100
 
6.3%
100
 
6.3%
63
 
4.0%
Other values (100) 600
37.8%
Decimal Number
ValueCountFrequency (%)
1 180
26.8%
2 88
13.1%
6 81
12.1%
0 69
 
10.3%
5 54
 
8.0%
3 50
 
7.5%
8 40
 
6.0%
9 38
 
5.7%
7 36
 
5.4%
4 35
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 6
60.0%
Q 1
 
10.0%
K 1
 
10.0%
S 1
 
10.0%
E 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
50.0%
( 1
50.0%
Space Separator
ValueCountFrequency (%)
471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1589
56.0%
Common 1240
43.7%
Latin 10
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
109
 
6.9%
107
 
6.7%
106
 
6.7%
102
 
6.4%
101
 
6.4%
101
 
6.4%
100
 
6.3%
100
 
6.3%
100
 
6.3%
63
 
4.0%
Other values (100) 600
37.8%
Common
ValueCountFrequency (%)
471
38.0%
1 180
 
14.5%
- 93
 
7.5%
2 88
 
7.1%
6 81
 
6.5%
0 69
 
5.6%
5 54
 
4.4%
3 50
 
4.0%
8 40
 
3.2%
9 38
 
3.1%
Other values (6) 76
 
6.1%
Latin
ValueCountFrequency (%)
B 6
60.0%
Q 1
 
10.0%
K 1
 
10.0%
S 1
 
10.0%
E 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1588
55.9%
ASCII 1250
44.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
471
37.7%
1 180
 
14.4%
- 93
 
7.4%
2 88
 
7.0%
6 81
 
6.5%
0 69
 
5.5%
5 54
 
4.3%
3 50
 
4.0%
8 40
 
3.2%
9 38
 
3.0%
Other values (11) 86
 
6.9%
Hangul
ValueCountFrequency (%)
109
 
6.9%
107
 
6.7%
106
 
6.7%
102
 
6.4%
101
 
6.4%
101
 
6.4%
100
 
6.3%
100
 
6.3%
100
 
6.3%
63
 
4.0%
Other values (99) 599
37.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct99
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Memory size932.0 B
2024-04-06T21:23:09.363449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length42
Mean length34.232323
Min length23

Characters and Unicode

Total characters3389
Distinct characters156
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row서울특별시 관악구 봉천로 594 (봉천동)
2nd row서울특별시 관악구 봉천로 461-1 (봉천동,2층)
3rd row서울특별시 관악구 남부순환로 1617 (신림동)
4th row서울특별시 관악구 양녕로 17 (봉천동)
5th row서울특별시 관악구 남부순환로 1872 (봉천동)
ValueCountFrequency (%)
서울특별시 99
 
15.8%
관악구 98
 
15.6%
봉천동 33
 
5.3%
신림동 32
 
5.1%
남부순환로 28
 
4.5%
과천대로 9
 
1.4%
봉천로 8
 
1.3%
1층 8
 
1.3%
2층 6
 
1.0%
남현동 6
 
1.0%
Other values (234) 301
47.9%
2024-04-06T21:23:10.267506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
552
 
16.3%
1 138
 
4.1%
, 117
 
3.5%
113
 
3.3%
112
 
3.3%
110
 
3.2%
103
 
3.0%
101
 
3.0%
100
 
3.0%
( 100
 
3.0%
Other values (146) 1843
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1947
57.5%
Space Separator 552
 
16.3%
Decimal Number 546
 
16.1%
Other Punctuation 117
 
3.5%
Open Punctuation 100
 
3.0%
Close Punctuation 100
 
3.0%
Uppercase Letter 16
 
0.5%
Dash Punctuation 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
113
 
5.8%
112
 
5.8%
110
 
5.6%
103
 
5.3%
101
 
5.2%
100
 
5.1%
100
 
5.1%
99
 
5.1%
99
 
5.1%
94
 
4.8%
Other values (125) 916
47.0%
Decimal Number
ValueCountFrequency (%)
1 138
25.3%
2 74
13.6%
0 68
12.5%
3 57
10.4%
9 47
 
8.6%
5 37
 
6.8%
8 35
 
6.4%
4 34
 
6.2%
6 31
 
5.7%
7 25
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 9
56.2%
E 2
 
12.5%
F 2
 
12.5%
Q 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%
Space Separator
ValueCountFrequency (%)
552
100.0%
Other Punctuation
ValueCountFrequency (%)
, 117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1947
57.5%
Common 1426
42.1%
Latin 16
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
113
 
5.8%
112
 
5.8%
110
 
5.6%
103
 
5.3%
101
 
5.2%
100
 
5.1%
100
 
5.1%
99
 
5.1%
99
 
5.1%
94
 
4.8%
Other values (125) 916
47.0%
Common
ValueCountFrequency (%)
552
38.7%
1 138
 
9.7%
, 117
 
8.2%
( 100
 
7.0%
) 100
 
7.0%
2 74
 
5.2%
0 68
 
4.8%
3 57
 
4.0%
9 47
 
3.3%
5 37
 
2.6%
Other values (5) 136
 
9.5%
Latin
ValueCountFrequency (%)
B 9
56.2%
E 2
 
12.5%
F 2
 
12.5%
Q 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1947
57.5%
ASCII 1442
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
552
38.3%
1 138
 
9.6%
, 117
 
8.1%
( 100
 
6.9%
) 100
 
6.9%
2 74
 
5.1%
0 68
 
4.7%
3 57
 
4.0%
9 47
 
3.3%
5 37
 
2.6%
Other values (11) 152
 
10.5%
Hangul
ValueCountFrequency (%)
113
 
5.8%
112
 
5.8%
110
 
5.6%
103
 
5.3%
101
 
5.2%
100
 
5.1%
100
 
5.1%
99
 
5.1%
99
 
5.1%
94
 
4.8%
Other values (125) 916
47.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)72.6%
Missing38
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean24929.435
Minimum8702
Maximum151903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:10.540937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8702
5-th percentile8708
Q18754
median8786.5
Q38818
95-th percentile151835.9
Maximum151903
Range143201
Interquartile range (IQR)64

Descriptive statistics

Standard deviation45641.449
Coefficient of variation (CV)1.8308256
Kurtosis4.4288391
Mean24929.435
Median Absolute Deviation (MAD)32.5
Skewness2.5073783
Sum1545625
Variance2.0831419 × 109
MonotonicityNot monotonic
2024-04-06T21:23:10.790575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
8808 4
 
4.0%
8787 3
 
3.0%
8754 3
 
3.0%
8770 3
 
3.0%
8767 2
 
2.0%
8702 2
 
2.0%
8807 2
 
2.0%
8720 2
 
2.0%
8768 2
 
2.0%
8738 2
 
2.0%
Other values (35) 37
37.0%
(Missing) 38
38.0%
ValueCountFrequency (%)
8702 2
2.0%
8705 1
1.0%
8708 2
2.0%
8720 2
2.0%
8731 1
1.0%
8738 2
2.0%
8742 1
1.0%
8744 1
1.0%
8750 1
1.0%
8752 1
1.0%
ValueCountFrequency (%)
151903 1
1.0%
151877 1
1.0%
151846 1
1.0%
151836 1
1.0%
151834 1
1.0%
151778 1
1.0%
151730 1
1.0%
8863 1
1.0%
8860 1
1.0%
8858 1
1.0%
Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T21:23:11.224387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18
Mean length8.79
Min length2

Characters and Unicode

Total characters879
Distinct characters202
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row(주)서경기계설비
2nd row(주)동서항공여행사
3rd row(주)여행하는 사람들
4th row(주)천보관광여행사
5th row개벽관광
ValueCountFrequency (%)
주식회사 14
 
10.5%
주)루카스여행사 2
 
1.5%
여행사 2
 
1.5%
투어 2
 
1.5%
tour 2
 
1.5%
주)세우여행사 1
 
0.8%
에버프로덕션 1
 
0.8%
만들기 1
 
0.8%
주)서경기계설비 1
 
0.8%
풍경 1
 
0.8%
Other values (106) 106
79.7%
2024-04-06T21:23:11.877293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
7.5%
) 55
 
6.3%
( 54
 
6.1%
43
 
4.9%
34
 
3.9%
33
 
3.8%
33
 
3.8%
29
 
3.3%
27
 
3.1%
20
 
2.3%
Other values (192) 485
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 679
77.2%
Close Punctuation 55
 
6.3%
Open Punctuation 54
 
6.1%
Space Separator 33
 
3.8%
Lowercase Letter 30
 
3.4%
Uppercase Letter 23
 
2.6%
Decimal Number 3
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
66
 
9.7%
43
 
6.3%
34
 
5.0%
33
 
4.9%
29
 
4.3%
27
 
4.0%
20
 
2.9%
20
 
2.9%
15
 
2.2%
14
 
2.1%
Other values (163) 378
55.7%
Lowercase Letter
ValueCountFrequency (%)
u 6
20.0%
o 4
13.3%
r 4
13.3%
a 3
10.0%
h 3
10.0%
c 2
 
6.7%
t 2
 
6.7%
e 2
 
6.7%
d 1
 
3.3%
n 1
 
3.3%
Other values (2) 2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
C 4
17.4%
L 3
13.0%
N 3
13.0%
T 3
13.0%
I 2
8.7%
O 2
8.7%
M 2
8.7%
A 2
8.7%
U 1
 
4.3%
R 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
1 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 679
77.2%
Common 147
 
16.7%
Latin 53
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
66
 
9.7%
43
 
6.3%
34
 
5.0%
33
 
4.9%
29
 
4.3%
27
 
4.0%
20
 
2.9%
20
 
2.9%
15
 
2.2%
14
 
2.1%
Other values (163) 378
55.7%
Latin
ValueCountFrequency (%)
u 6
 
11.3%
C 4
 
7.5%
o 4
 
7.5%
r 4
 
7.5%
L 3
 
5.7%
N 3
 
5.7%
a 3
 
5.7%
h 3
 
5.7%
T 3
 
5.7%
c 2
 
3.8%
Other values (12) 18
34.0%
Common
ValueCountFrequency (%)
) 55
37.4%
( 54
36.7%
33
22.4%
2 2
 
1.4%
. 1
 
0.7%
, 1
 
0.7%
1 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 679
77.2%
ASCII 200
 
22.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
66
 
9.7%
43
 
6.3%
34
 
5.0%
33
 
4.9%
29
 
4.3%
27
 
4.0%
20
 
2.9%
20
 
2.9%
15
 
2.2%
14
 
2.1%
Other values (163) 378
55.7%
ASCII
ValueCountFrequency (%)
) 55
27.5%
( 54
27.0%
33
16.5%
u 6
 
3.0%
C 4
 
2.0%
o 4
 
2.0%
r 4
 
2.0%
L 3
 
1.5%
N 3
 
1.5%
a 3
 
1.5%
Other values (19) 31
15.5%
Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2003-02-06 10:46:07
Maximum2024-03-21 17:12:14
2024-04-06T21:23:12.146202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:12.476717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
U
56 
I
44 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 56
56.0%
I 44
44.0%

Length

2024-04-06T21:23:12.730178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:12.927508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 56
56.0%
i 44
44.0%
Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:03:00
2024-04-06T21:23:13.124769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:23:13.418914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

좌표정보(X)
Real number (ℝ)

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194720.34
Minimum191131.05
Maximum203963.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:13.680926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191131.05
5-th percentile191374.51
Q1193305.15
median194807.41
Q3195894.22
95-th percentile198315.16
Maximum203963.69
Range12832.64
Interquartile range (IQR)2589.0701

Descriptive statistics

Standard deviation2236.2023
Coefficient of variation (CV)0.011484174
Kurtosis1.6448384
Mean194720.34
Median Absolute Deviation (MAD)1332.0413
Skewness0.73709773
Sum19472034
Variance5000600.6
MonotonicityNot monotonic
2024-04-06T21:23:13.936032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
195588.796492288 5
 
5.0%
198284.078546351 4
 
4.0%
198374.473281221 4
 
4.0%
193764.761470624 2
 
2.0%
195537.269534163 2
 
2.0%
196409.202870272 2
 
2.0%
192012.500669524 2
 
2.0%
193746.833837509 2
 
2.0%
192429.160875861 2
 
2.0%
193306.240555398 2
 
2.0%
Other values (73) 73
73.0%
ValueCountFrequency (%)
191131.049995846 1
1.0%
191144.418041034 1
1.0%
191210.00657717 1
1.0%
191244.186952943 1
1.0%
191334.658955208 1
1.0%
191376.602183978 1
1.0%
191463.822484719 1
1.0%
191529.880223043 1
1.0%
191530.692912889 1
1.0%
191592.154183574 1
1.0%
ValueCountFrequency (%)
203963.6898334 1
 
1.0%
198374.473281221 4
4.0%
198312.042719052 1
 
1.0%
198295.195735536 1
 
1.0%
198284.078546351 4
4.0%
198234.65096107 1
 
1.0%
197104.582735832 1
 
1.0%
196890.42502367 1
 
1.0%
196671.427602648 1
 
1.0%
196631.023343907 1
 
1.0%

좌표정보(Y)
Real number (ℝ)

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean442162.8
Minimum439023.17
Maximum453178.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:14.205612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile441033.51
Q1441699.89
median442129.07
Q3442458.43
95-th percentile443155.05
Maximum453178.08
Range14154.914
Interquartile range (IQR)758.53909

Descriptive statistics

Standard deviation1301.7955
Coefficient of variation (CV)0.0029441543
Kurtosis52.451141
Mean442162.8
Median Absolute Deviation (MAD)361.40492
Skewness6.0320072
Sum44216280
Variance1694671.5
MonotonicityNot monotonic
2024-04-06T21:23:14.491713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442098.372819317 5
 
5.0%
441368.909286824 4
 
4.0%
441033.513044892 4
 
4.0%
442488.438980658 2
 
2.0%
442122.202180318 2
 
2.0%
441837.788616059 2
 
2.0%
441885.529640794 2
 
2.0%
442510.775085572 2
 
2.0%
442856.622644707 2
 
2.0%
443221.321009043 2
 
2.0%
Other values (73) 73
73.0%
ValueCountFrequency (%)
439023.167125842 1
 
1.0%
440355.648657087 1
 
1.0%
440698.444186102 1
 
1.0%
440757.239746434 1
 
1.0%
441033.513044892 4
4.0%
441173.69301173 1
 
1.0%
441268.270440207 1
 
1.0%
441276.34100034 1
 
1.0%
441281.894518334 1
 
1.0%
441304.24922842 1
 
1.0%
ValueCountFrequency (%)
453178.08122361 1
1.0%
443547.049696825 1
1.0%
443291.231245754 1
1.0%
443221.321009043 2
2.0%
443151.561302292 1
1.0%
443014.695103526 1
1.0%
443011.455007816 1
1.0%
442957.711891203 1
1.0%
442920.76209914 1
1.0%
442856.622644707 2
2.0%
Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
국내외여행업
66 
<NA>
34 

Length

Max length6
Median length6
Mean length5.32
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 66
66.0%
<NA> 34
34.0%

Length

2024-04-06T21:23:14.824745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:15.178491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 66
66.0%
na 34
34.0%
Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
71 
관광사업
29 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
71.0%
관광사업 29
29.0%

Length

2024-04-06T21:23:15.425216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:15.607386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
71.0%
관광사업 29
29.0%

지역구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
84 
일반상업지역
 
6
일반주거지역
 
4
주거지역
 
2
준주거지역
 
2

Length

Max length6
Median length4
Mean length4.26
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
84.0%
일반상업지역 6
 
6.0%
일반주거지역 4
 
4.0%
주거지역 2
 
2.0%
준주거지역 2
 
2.0%
근린상업지역 2
 
2.0%

Length

2024-04-06T21:23:15.834707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:16.054245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
84.0%
일반상업지역 6
 
6.0%
일반주거지역 4
 
4.0%
주거지역 2
 
2.0%
준주거지역 2
 
2.0%
근린상업지역 2
 
2.0%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)56.2%
Missing84
Missing (%)84.0%
Infinite0
Infinite (%)0.0%
Mean5.375
Minimum0
Maximum23
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:16.338123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q35.25
95-th percentile22.25
Maximum23
Range23
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation7.6757193
Coefficient of variation (CV)1.4280408
Kurtosis1.6503386
Mean5.375
Median Absolute Deviation (MAD)3
Skewness1.676178
Sum86
Variance58.916667
MonotonicityNot monotonic
2024-04-06T21:23:16.828982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 6
 
6.0%
3 3
 
3.0%
5 1
 
1.0%
22 1
 
1.0%
4 1
 
1.0%
15 1
 
1.0%
2 1
 
1.0%
23 1
 
1.0%
6 1
 
1.0%
(Missing) 84
84.0%
ValueCountFrequency (%)
0 6
6.0%
2 1
 
1.0%
3 3
3.0%
4 1
 
1.0%
5 1
 
1.0%
6 1
 
1.0%
15 1
 
1.0%
22 1
 
1.0%
23 1
 
1.0%
ValueCountFrequency (%)
23 1
 
1.0%
22 1
 
1.0%
15 1
 
1.0%
6 1
 
1.0%
5 1
 
1.0%
4 1
 
1.0%
3 3
3.0%
2 1
 
1.0%
0 6
6.0%

주변환경명
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
89 
기타
 
6
주택가주변
 
3
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.99
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 89
89.0%
기타 6
 
6.0%
주택가주변 3
 
3.0%
유흥업소밀집지역 2
 
2.0%

Length

2024-04-06T21:23:17.085427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:17.934772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
89.0%
기타 6
 
6.0%
주택가주변 3
 
3.0%
유흥업소밀집지역 2
 
2.0%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

보험기관명
Categorical

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
51 
서울보증보험주식회사
한국관광협회중앙회
서울보증보험
 
4
한국관광협회
 
3
Other values (20)
28 

Length

Max length31
Median length4
Mean length6.89
Min length4

Unique

Unique14 ?
Unique (%)14.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
51.0%
서울보증보험주식회사 8
 
8.0%
한국관광협회중앙회 6
 
6.0%
서울보증보험 4
 
4.0%
한국관광협회 3
 
3.0%
한국관광협회중앙회(3,000만) 3
 
3.0%
여행공제회 3
 
3.0%
서울특별시관광협회 2
 
2.0%
서울보증보험(3000만) 2
 
2.0%
서울보증(3천만) 2
 
2.0%
Other values (15) 16
 
16.0%

Length

2024-04-06T21:23:18.238935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 51
48.6%
서울보증보험주식회사 8
 
7.6%
한국관광협회중앙회 6
 
5.7%
한국관광협회 6
 
5.7%
서울보증보험 4
 
3.8%
한국관광협회중앙회(3,000만 3
 
2.9%
여행공제회 3
 
2.9%
중앙회 2
 
1.9%
서울보증(3천만 2
 
1.9%
서울보증보험(3000만 2
 
1.9%
Other values (17) 18
 
17.1%

건물용도명
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
84 
근린생활시설
11 
사무실
 
4
시장(재래시장)
 
1

Length

Max length8
Median length4
Mean length4.22
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
84.0%
근린생활시설 11
 
11.0%
사무실 4
 
4.0%
시장(재래시장) 1
 
1.0%

Length

2024-04-06T21:23:18.478834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:18.660675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
84.0%
근린생활시설 11
 
11.0%
사무실 4
 
4.0%
시장(재래시장 1
 
1.0%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)40.0%
Missing80
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean4.15
Minimum0
Maximum20
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:18.828682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q34.25
95-th percentile15.25
Maximum20
Range20
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation5.7149389
Coefficient of variation (CV)1.3770937
Kurtosis2.7440183
Mean4.15
Median Absolute Deviation (MAD)2.5
Skewness1.8928979
Sum83
Variance32.660526
MonotonicityNot monotonic
2024-04-06T21:23:19.025177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 6
 
6.0%
3 4
 
4.0%
2 3
 
3.0%
5 2
 
2.0%
15 2
 
2.0%
1 1
 
1.0%
4 1
 
1.0%
20 1
 
1.0%
(Missing) 80
80.0%
ValueCountFrequency (%)
0 6
6.0%
1 1
 
1.0%
2 3
3.0%
3 4
4.0%
4 1
 
1.0%
5 2
 
2.0%
15 2
 
2.0%
20 1
 
1.0%
ValueCountFrequency (%)
20 1
 
1.0%
15 2
 
2.0%
5 2
 
2.0%
4 1
 
1.0%
3 4
4.0%
2 3
3.0%
1 1
 
1.0%
0 6
6.0%

지하층수
Categorical

IMBALANCE 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
85 
0
 
6
1
 
6
7
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.55
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
85.0%
0 6
 
6.0%
1 6
 
6.0%
7 1
 
1.0%
5 1
 
1.0%
3 1
 
1.0%

Length

2024-04-06T21:23:19.245555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:19.432762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
85.0%
0 6
 
6.0%
1 6
 
6.0%
7 1
 
1.0%
5 1
 
1.0%
3 1
 
1.0%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:19.620151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:19.787065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

건축연면적
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
94 
0
 
5
23
 
1

Length

Max length4
Median length4
Mean length3.83
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 94
94.0%
0 5
 
5.0%
23 1
 
1.0%

Length

2024-04-06T21:23:19.992245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:20.185749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 94
94.0%
0 5
 
5.0%
23 1
 
1.0%

영문상호명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing92
Missing (%)92.0%
Memory size932.0 B
2024-04-06T21:23:20.389645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14.5
Mean length12.875
Min length6

Characters and Unicode

Total characters103
Distinct characters38
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

Unique8 ?
Unique (%)100.0%

Sample

1st rowLovely Tour Network
2nd rowCreating a LAANDSCAPE
3rd rowEUREVEL Co.,Ltd
4th rowAKIMAI
5th rowCLASS TOUR
ValueCountFrequency (%)
tour 4
22.2%
lovely 1
 
5.6%
network 1
 
5.6%
creating 1
 
5.6%
a 1
 
5.6%
laandscape 1
 
5.6%
eurevel 1
 
5.6%
co.,ltd 1
 
5.6%
akimai 1
 
5.6%
class 1
 
5.6%
Other values (5) 5
27.8%
2024-04-06T21:23:20.924404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
9.7%
L 7
 
6.8%
E 6
 
5.8%
o 6
 
5.8%
A 6
 
5.8%
O 5
 
4.9%
T 4
 
3.9%
r 4
 
3.9%
C 4
 
3.9%
M 4
 
3.9%
Other values (28) 47
45.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 57
55.3%
Lowercase Letter 33
32.0%
Space Separator 10
 
9.7%
Other Punctuation 3
 
2.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
L 7
12.3%
E 6
10.5%
A 6
10.5%
O 5
8.8%
T 4
 
7.0%
C 4
 
7.0%
M 4
 
7.0%
S 3
 
5.3%
R 3
 
5.3%
U 3
 
5.3%
Other values (8) 12
21.1%
Lowercase Letter
ValueCountFrequency (%)
o 6
18.2%
r 4
12.1%
e 3
9.1%
t 3
9.1%
i 2
 
6.1%
n 2
 
6.1%
a 2
 
6.1%
u 2
 
6.1%
d 1
 
3.0%
s 1
 
3.0%
Other values (7) 7
21.2%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 90
87.4%
Common 13
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
L 7
 
7.8%
E 6
 
6.7%
o 6
 
6.7%
A 6
 
6.7%
O 5
 
5.6%
T 4
 
4.4%
r 4
 
4.4%
C 4
 
4.4%
M 4
 
4.4%
S 3
 
3.3%
Other values (25) 41
45.6%
Common
ValueCountFrequency (%)
10
76.9%
. 2
 
15.4%
, 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 103
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
 
9.7%
L 7
 
6.8%
E 6
 
5.8%
o 6
 
5.8%
A 6
 
5.8%
O 5
 
4.9%
T 4
 
3.9%
r 4
 
3.9%
C 4
 
3.9%
M 4
 
3.9%
Other values (28) 47
45.6%

영문상호주소
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
92 
OVERSEAS TRAVEL BUSINESS
 
6
Overseas Travel Business
 
1
OVERSEAs TRAVAL BUSINESS
 
1

Length

Max length24
Median length4
Mean length5.6
Min length4

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
92.0%
OVERSEAS TRAVEL BUSINESS 6
 
6.0%
Overseas Travel Business 1
 
1.0%
OVERSEAs TRAVAL BUSINESS 1
 
1.0%

Length

2024-04-06T21:23:21.182768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:21.386697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
79.3%
overseas 8
 
6.9%
business 8
 
6.9%
travel 7
 
6.0%
traval 1
 
0.9%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:21.608144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:21.785029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:21.964815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:22.151320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:22.317730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:22.486773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:22.724277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:22.895597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:23.063105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:23.258116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)67.9%
Missing72
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean25.025
Minimum0
Maximum138.8
Zeros10
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:23.435848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17.765
Q333.5
95-th percentile61.56
Maximum138.8
Range138.8
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation30.544088
Coefficient of variation (CV)1.220543
Kurtosis6.0487124
Mean25.025
Median Absolute Deviation (MAD)17.765
Skewness2.0606214
Sum700.7
Variance932.94132
MonotonicityNot monotonic
2024-04-06T21:23:23.699595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 10
 
10.0%
26.07 1
 
1.0%
52.9 1
 
1.0%
30.1 1
 
1.0%
62.4 1
 
1.0%
25.09 1
 
1.0%
31.74 1
 
1.0%
18.0 1
 
1.0%
8.0 1
 
1.0%
33.0 1
 
1.0%
Other values (9) 9
 
9.0%
(Missing) 72
72.0%
ValueCountFrequency (%)
0.0 10
10.0%
8.0 1
 
1.0%
12.5 1
 
1.0%
12.61 1
 
1.0%
17.53 1
 
1.0%
18.0 1
 
1.0%
25.09 1
 
1.0%
26.07 1
 
1.0%
30.1 1
 
1.0%
30.6 1
 
1.0%
ValueCountFrequency (%)
138.8 1
1.0%
62.4 1
1.0%
60.0 1
1.0%
56.86 1
1.0%
52.9 1
1.0%
49.5 1
1.0%
35.0 1
1.0%
33.0 1
1.0%
31.74 1
1.0%
30.6 1
1.0%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
95 
0
 
5

Length

Max length4
Median length4
Mean length3.85
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> 95
95.0%
0 5
 
5.0%

Length

2024-04-06T21:23:23.940696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:23:24.101004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
95.0%
0 5
 
5.0%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

자본금
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)36.4%
Missing45
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean1.0281333 × 108
Minimum0
Maximum7 × 108
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:24.266172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32362465
Q160000000
median1 × 108
Q31 × 108
95-th percentile1.94 × 108
Maximum7 × 108
Range7 × 108
Interquartile range (IQR)40000000

Descriptive statistics

Standard deviation1.100005 × 108
Coefficient of variation (CV)1.0699051
Kurtosis20.568065
Mean1.0281333 × 108
Median Absolute Deviation (MAD)35000000
Skewness4.3569202
Sum5.654733 × 109
Variance1.210011 × 1016
MonotonicityNot monotonic
2024-04-06T21:23:24.512689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
100000000 22
22.0%
60000000 13
 
13.0%
30000000 2
 
2.0%
90000000 2
 
2.0%
103890000 1
 
1.0%
60300000 1
 
1.0%
34760000 1
 
1.0%
33374950 1
 
1.0%
34796000 1
 
1.0%
50000000 1
 
1.0%
Other values (10) 10
 
10.0%
(Missing) 45
45.0%
ValueCountFrequency (%)
0 1
 
1.0%
30000000 2
 
2.0%
33374950 1
 
1.0%
34760000 1
 
1.0%
34796000 1
 
1.0%
50000000 1
 
1.0%
60000000 13
13.0%
60300000 1
 
1.0%
60610000 1
 
1.0%
65000000 1
 
1.0%
ValueCountFrequency (%)
700000000 1
 
1.0%
550000000 1
 
1.0%
250000000 1
 
1.0%
170000000 1
 
1.0%
150000000 1
 
1.0%
103890000 1
 
1.0%
100745502 1
 
1.0%
100000000 22
22.0%
90000000 2
 
2.0%
71256595 1
 
1.0%

보험시작일자
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)98.0%
Missing49
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean20136677
Minimum20020730
Maximum20220216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:24.773983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020730
5-th percentile20040710
Q120110558
median20140303
Q320180374
95-th percentile20200624
Maximum20220216
Range199486
Interquartile range (IQR)69816.5

Descriptive statistics

Standard deviation52429.281
Coefficient of variation (CV)0.002603671
Kurtosis-0.57266295
Mean20136677
Median Absolute Deviation (MAD)40018
Skewness-0.56262718
Sum1.0269705 × 109
Variance2.7488295 × 109
MonotonicityNot monotonic
2024-04-06T21:23:25.057285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140303 2
 
2.0%
20200822 1
 
1.0%
20170101 1
 
1.0%
20120724 1
 
1.0%
20130902 1
 
1.0%
20131008 1
 
1.0%
20100208 1
 
1.0%
20180427 1
 
1.0%
20110404 1
 
1.0%
20141204 1
 
1.0%
Other values (40) 40
40.0%
(Missing) 49
49.0%
ValueCountFrequency (%)
20020730 1
1.0%
20020902 1
1.0%
20030806 1
1.0%
20050615 1
1.0%
20051122 1
1.0%
20060522 1
1.0%
20070921 1
1.0%
20080325 1
1.0%
20080515 1
1.0%
20080922 1
1.0%
ValueCountFrequency (%)
20220216 1
1.0%
20210101 1
1.0%
20200822 1
1.0%
20200426 1
1.0%
20190708 1
1.0%
20190705 1
1.0%
20190508 1
1.0%
20190501 1
1.0%
20190420 1
1.0%
20190202 1
1.0%

보험종료일자
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)98.2%
Missing45
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean20137728
Minimum20010503
Maximum20230215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:25.339754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010503
5-th percentile20027775
Q120095720
median20141008
Q320190376
95-th percentile20210544
Maximum20230215
Range219712
Interquartile range (IQR)94655

Descriptive statistics

Standard deviation59938.551
Coefficient of variation (CV)0.0029764306
Kurtosis-0.69384756
Mean20137728
Median Absolute Deviation (MAD)49522
Skewness-0.59003244
Sum1.1075751 × 109
Variance3.5926299 × 109
MonotonicityNot monotonic
2024-04-06T21:23:25.600088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150302 2
 
2.0%
20130712 1
 
1.0%
20210821 1
 
1.0%
20200320 1
 
1.0%
20171231 1
 
1.0%
20130724 1
 
1.0%
20140901 1
 
1.0%
20141008 1
 
1.0%
20110208 1
 
1.0%
20200326 1
 
1.0%
Other values (44) 44
44.0%
(Missing) 45
45.0%
ValueCountFrequency (%)
20010503 1
1.0%
20020112 1
1.0%
20021119 1
1.0%
20030628 1
1.0%
20030730 1
1.0%
20030902 1
1.0%
20040805 1
1.0%
20061122 1
1.0%
20070521 1
1.0%
20070614 1
1.0%
ValueCountFrequency (%)
20230215 1
1.0%
20211231 1
1.0%
20210821 1
1.0%
20210426 1
1.0%
20200707 1
1.0%
20200704 1
1.0%
20200430 1
1.0%
20200419 1
1.0%
20200326 1
1.0%
20200320 1
1.0%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)60.7%
Missing72
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean25.107143
Minimum0
Maximum139
Zeros10
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T21:23:25.809208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median18
Q333.5
95-th percentile61.3
Maximum139
Range139
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation30.564248
Coefficient of variation (CV)1.2173527
Kurtosis6.0591149
Mean25.107143
Median Absolute Deviation (MAD)18
Skewness2.0593808
Sum703
Variance934.17328
MonotonicityNot monotonic
2024-04-06T21:23:26.004827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 10
 
10.0%
13 2
 
2.0%
18 2
 
2.0%
26 1
 
1.0%
53 1
 
1.0%
139 1
 
1.0%
31 1
 
1.0%
50 1
 
1.0%
60 1
 
1.0%
35 1
 
1.0%
Other values (7) 7
 
7.0%
(Missing) 72
72.0%
ValueCountFrequency (%)
0 10
10.0%
8 1
 
1.0%
13 2
 
2.0%
18 2
 
2.0%
25 1
 
1.0%
26 1
 
1.0%
30 1
 
1.0%
31 1
 
1.0%
32 1
 
1.0%
33 1
 
1.0%
ValueCountFrequency (%)
139 1
1.0%
62 1
1.0%
60 1
1.0%
57 1
1.0%
53 1
1.0%
50 1
1.0%
35 1
1.0%
33 1
1.0%
32 1
1.0%
31 1
1.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03200000CDFI226002199400000119940511<NA>3폐업3폐업19971117<NA><NA><NA><NA><NA>151832서울특별시 관악구 봉천동 1632-1번지서울특별시 관악구 봉천로 594 (봉천동)<NA>(주)서경기계설비2003-02-06 10:46:07I2018-08-31 23:59:59.0<NA>196671.427603441562.289883국내외여행업관광사업<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
13200000CDFI226002199700000119970116<NA>3폐업3폐업20010710<NA><NA><NA><NA><NA>151015서울특별시 관악구 신림동 1655-19번지 ,29<NA><NA>(주)동서항공여행사2003-02-06 10:46:07I2018-08-31 23:59:59.0<NA>191244.186953442274.238534국내외여행업관광사업<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
23200000CDFI226002199700000219970822<NA>4취소/말소/만료/정지/중지30허가취소<NA><NA><NA><NA>873-5688<NA>151822서울특별시 관악구 봉천동 871-67번지 2층서울특별시 관악구 봉천로 461-1 (봉천동,2층)<NA>(주)여행하는 사람들2005-04-19 13:07:35I2018-08-31 23:59:59.0<NA>195629.63209442265.436122국내외여행업관광사업<NA><NA><NA><NA>서울보증보험회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1000000002003080620040805<NA><NA>
33200000CDFI226002199800000119980708<NA>3폐업3폐업20220502<NA><NA><NA>882-0080<NA>151015서울특별시 관악구 신림동 1422-38서울특별시 관악구 남부순환로 1617 (신림동)<NA>(주)천보관광여행사2022-05-02 10:16:13U2021-12-05 00:04:00.0<NA>193764.761471442488.438981<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43200000CDFI226002199800000519981106<NA>3폐업3폐업19991203<NA><NA><NA><NA><NA>151840서울특별시 관악구 봉천동 910-20번지서울특별시 관악구 양녕로 17 (봉천동)<NA>개벽관광2003-02-06 10:47:14I2018-08-31 23:59:59.0<NA>195187.953488442390.648691국내외여행업관광사업<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
53200000CDFI226002199900000119990113<NA>3폐업3폐업20030617<NA><NA><NA>874-5656<NA>151848서울특별시 관악구 봉천동 1663-1번지서울특별시 관악구 남부순환로 1872 (봉천동)<NA>(주)선명여행사2003-06-17 10:47:59I2018-08-31 23:59:59.0<NA>196175.137922441879.759178국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>100000000<NA>20020112<NA><NA>
63200000CDFI226002199900000219991004<NA>3폐업3폐업20000221<NA><NA><NA><NA><NA>151840서울특별시 관악구 봉천동 912-11번지서울특별시 관악구 봉천로 408 (봉천동)<NA>월드남부관광클럽2003-02-06 10:46:07I2018-08-31 23:59:59.0<NA>195081.689722442275.730544국내외여행업관광사업<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
73200000CDFI226002200000000220000427<NA>1영업/정상13영업중<NA><NA><NA><NA>02-874-5151<NA>151834서울특별시 관악구 봉천동 1666-37 1층서울특별시 관악구 남부순환로 1835, 1층 (봉천동)8738(주)다원관광여행사2021-11-23 13:14:59U2021-11-25 02:40:00.0<NA>195890.981812442083.343115국내외여행업관광사업<NA><NA><NA><NA>한국관광협회중앙회(3,000만)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1000000002020042620210426<NA><NA>
83200000CDFI226002200100000120010216<NA>3폐업3폐업20110831<NA><NA><NA>872-7788<NA>151892서울특별시 관악구 신림동 1433-102번지 11통1반 2층서울특별시 관악구 남부순환로 1591 (신림동,2층)<NA>(주)신림여행사2011-08-31 18:17:40I2018-08-31 23:59:59.0<NA>193506.453614442451.538878국내외여행업관광사업<NA><NA><NA><NA>서울보증보험주식회사<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>1000000002008032520090324<NA><NA>
93200000CDFI226002200100000320010308<NA>3폐업3폐업20030213<NA><NA><NA><NA><NA>130867서울특별시 동대문구 청량리동 268번지 동광빌딩 1층서울특별시 동대문구 왕산로 205 (청량리동,동광빌딩 1층)<NA>(주)세기투어2003-02-13 10:38:46I2018-08-31 23:59:59.0<NA>203963.689833453178.081224국내외여행업관광사업주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>100000000<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
903200000CDFI22600220200000072017-08-24<NA>1영업/정상13영업중<NA><NA><NA><NA>02-730-3220<NA><NA>서울특별시 관악구 신림동 493-12 1층서울특별시 관악구 신사로14길 67, 1층 (신림동)8705(주)목동여행사2023-11-03 15:25:03U2022-11-01 00:05:00.0<NA>192604.812541442611.744286<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
913200000CDFI22600220210000012013-08-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1661-9서울특별시 관악구 봉천로 563, 501호 (봉천동)8792주식회사 탑투어2023-11-03 15:23:36U2022-11-01 00:05:00.0<NA>196417.878091441738.631456<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
923200000CDFI22600220210000022005-02-17<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 905-1 해국빌 101호서울특별시 관악구 봉천로29길 64, 해국빌 101호 (봉천동)8750(주)넥서스투어2023-08-02 15:59:49U2022-12-08 00:04:00.0<NA>194872.649617442604.546058<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
933200000CDFI22600220210000032009-06-26<NA>1영업/정상13영업중<NA><NA><NA><NA>02-3476-2655<NA><NA>서울특별시 관악구 신림동 1422-5 르네상스 복합쇼핑몰 7층 B704호서울특별시 관악구 신림로 340, 르네상스 복합쇼핑몰 7층 B704호 (신림동)8754(주)하나트레블서비스2023-11-03 15:22:52U2022-11-01 00:05:00.0<NA>193746.833838442510.775086<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
943200000CDFI22600220210000042019-08-19<NA>5제외/삭제/전출15전출2023-03-23<NA><NA><NA>070-7793-9030<NA><NA>서울특별시 관악구 신림동 1694 신림현대아파트 쇼핑센타 B동 207호서울특별시 관악구 신림로29길 8, B동 207호 (신림동, 신림현대아파트)8845노른자여행사2023-03-23 13:05:37U2022-12-02 22:05:00.0<NA>193957.944324441437.774867<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
953200000CDFI22600220210000052019-03-28<NA>3폐업3폐업2023-05-04<NA><NA><NA>02-565-8816<NA><NA>서울특별시 관악구 신림동 663-1 대운빌딩서울특별시 관악구 난곡로 112, 대운빌딩 지하층 (신림동)8860고스 투어2023-05-04 17:52:13U2022-12-05 00:07:00.0<NA>192852.58596440355.648657<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
963200000CDFI22600220220000012022-06-30<NA>1영업/정상13영업중<NA><NA><NA><NA>02-878-7651<NA><NA>서울특별시 관악구 봉천동 1659-2서울특별시 관악구 남부순환로 1922, 5층 (봉천동)8793주식회사 아워스포츠네이션2023-11-03 15:21:29U2022-11-01 00:05:00.0<NA>196631.023344441655.970495<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
973200000CDFI22600220230000012016-06-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 1666-50서울특별시 관악구 시흥대로 540, F1층 (신림동)8768(주)아트앤트래블2023-11-24 13:56:38U2022-10-31 22:06:00.0<NA>191144.418041442139.911784<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
983200000CDFI22600220230000022023-08-31<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 908-68서울특별시 관악구 양녕로1길 46, 1동 지하층 F02호 (봉천동)8752시선 여행사2023-11-23 17:30:46U2022-10-31 22:05:00.0<NA>194976.841269442395.711297<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
993200000CDFI22600220240000012002-06-25<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 607-137서울특별시 관악구 난곡로40길 16 (신림동)8849(주)루카스여행사2024-03-21 17:12:14I2023-12-02 22:03:00.0<NA>192649.525659441458.986264<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>