Overview

Dataset statistics

Number of variables60
Number of observations120
Missing cells4169
Missing cells (%)57.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.9 KiB
Average record size in memory520.1 B

Variable types

Categorical12
Text10
DateTime4
Unsupported24
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-17582/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (84.6%)Imbalance
주변환경명 is highly imbalanced (67.9%)Imbalance
건물용도명 is highly imbalanced (67.4%)Imbalance
지하층수 is highly imbalanced (72.7%)Imbalance
폐업일자 has 54 (45.0%) missing valuesMissing
휴업시작일자 has 120 (100.0%) missing valuesMissing
휴업종료일자 has 120 (100.0%) missing valuesMissing
재개업일자 has 120 (100.0%) missing valuesMissing
전화번호 has 35 (29.2%) missing valuesMissing
소재지면적 has 120 (100.0%) missing valuesMissing
소재지우편번호 has 63 (52.5%) missing valuesMissing
도로명우편번호 has 27 (22.5%) missing valuesMissing
업태구분명 has 120 (100.0%) missing valuesMissing
지역구분명 has 113 (94.2%) missing valuesMissing
총층수 has 108 (90.0%) missing valuesMissing
제작취급품목내용 has 120 (100.0%) missing valuesMissing
보험기관명 has 91 (75.8%) missing valuesMissing
지상층수 has 106 (88.3%) missing valuesMissing
객실수 has 120 (100.0%) missing valuesMissing
건축연면적 has 120 (100.0%) missing valuesMissing
영문상호명 has 116 (96.7%) missing valuesMissing
영문상호주소 has 116 (96.7%) missing valuesMissing
선박총톤수 has 120 (100.0%) missing valuesMissing
선박척수 has 120 (100.0%) missing valuesMissing
선박제원 has 120 (100.0%) missing valuesMissing
무대면적 has 120 (100.0%) missing valuesMissing
좌석수 has 120 (100.0%) missing valuesMissing
기념품종류 has 120 (100.0%) missing valuesMissing
회의실별동시수용인원 has 120 (100.0%) missing valuesMissing
시설면적 has 97 (80.8%) missing valuesMissing
놀이기구수내역 has 120 (100.0%) missing valuesMissing
놀이시설수 has 120 (100.0%) missing valuesMissing
방송시설유무 has 120 (100.0%) missing valuesMissing
발전시설유무 has 120 (100.0%) missing valuesMissing
의무실유무 has 120 (100.0%) missing valuesMissing
안내소유무 has 120 (100.0%) missing valuesMissing
기획여행보험시작일자 has 120 (100.0%) missing valuesMissing
기획여행보험종료일자 has 120 (100.0%) missing valuesMissing
자본금 has 87 (72.5%) missing valuesMissing
보험시작일자 has 88 (73.3%) missing valuesMissing
보험종료일자 has 88 (73.3%) missing valuesMissing
부대시설내역 has 120 (100.0%) missing valuesMissing
시설규모 has 97 (80.8%) 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
객실수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건축연면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박총톤수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박척수 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
무대면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
좌석수 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
회의실별동시수용인원 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
놀이시설수 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 5 (4.2%) zerosZeros
지상층수 has 5 (4.2%) zerosZeros
시설면적 has 9 (7.5%) zerosZeros
시설규모 has 9 (7.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:38:59.458592
Analysis finished2024-05-11 06:39:00.449114
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3050000
120 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 120
100.0%

Length

2024-05-11T15:39:00.536458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:00.686437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 120
100.0%

관리번호
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:39:00.916272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2400
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

Unique120 ?
Unique (%)100.0%

Sample

1st rowCDFI2260021994000001
2nd rowCDFI2260021996000001
3rd rowCDFI2260021996000003
4th rowCDFI2260021997000001
5th rowCDFI2260021997000002
ValueCountFrequency (%)
cdfi2260021994000001 1
 
0.8%
cdfi2260021996000001 1
 
0.8%
cdfi2260022019000006 1
 
0.8%
cdfi2260022019000005 1
 
0.8%
cdfi2260022019000002 1
 
0.8%
cdfi2260022019000001 1
 
0.8%
cdfi2260022018000011 1
 
0.8%
cdfi2260022018000009 1
 
0.8%
cdfi2260022018000008 1
 
0.8%
cdfi2260022018000007 1
 
0.8%
Other values (110) 110
91.7%
2024-05-11T15:39:01.404225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 985
41.0%
2 533
22.2%
6 144
 
6.0%
C 120
 
5.0%
D 120
 
5.0%
F 120
 
5.0%
I 120
 
5.0%
1 110
 
4.6%
9 33
 
1.4%
8 28
 
1.2%
Other values (4) 87
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1920
80.0%
Uppercase Letter 480
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 985
51.3%
2 533
27.8%
6 144
 
7.5%
1 110
 
5.7%
9 33
 
1.7%
8 28
 
1.5%
3 26
 
1.4%
4 25
 
1.3%
7 24
 
1.2%
5 12
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
C 120
25.0%
D 120
25.0%
F 120
25.0%
I 120
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1920
80.0%
Latin 480
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 985
51.3%
2 533
27.8%
6 144
 
7.5%
1 110
 
5.7%
9 33
 
1.7%
8 28
 
1.5%
3 26
 
1.4%
4 25
 
1.3%
7 24
 
1.2%
5 12
 
0.6%
Latin
ValueCountFrequency (%)
C 120
25.0%
D 120
25.0%
F 120
25.0%
I 120
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 985
41.0%
2 533
22.2%
6 144
 
6.0%
C 120
 
5.0%
D 120
 
5.0%
F 120
 
5.0%
I 120
 
5.0%
1 110
 
4.6%
9 33
 
1.4%
8 28
 
1.2%
Other values (4) 87
 
3.6%
Distinct116
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1992-03-03 00:00:00
Maximum2024-03-05 00:00:00
2024-05-11T15:39:01.689597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:01.874698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
115 
20091102
 
3
20021227
 
1
20021130
 
1

Length

Max length8
Median length4
Mean length4.1666667
Min length4

Unique

Unique2 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 115
95.8%
20091102 3
 
2.5%
20021227 1
 
0.8%
20021130 1
 
0.8%

Length

2024-05-11T15:39:02.078846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:02.274254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 115
95.8%
20091102 3
 
2.5%
20021227 1
 
0.8%
20021130 1
 
0.8%
Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
61 
1
45 
4
5
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 61
50.8%
1 45
37.5%
4 9
 
7.5%
5 5
 
4.2%

Length

2024-05-11T15:39:02.464238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:02.635720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
50.8%
1 45
37.5%
4 9
 
7.5%
5 5
 
4.2%

영업상태명
Categorical

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
61 
영업/정상
45 
취소/말소/만료/정지/중지
제외/삭제/전출
 
5

Length

Max length14
Median length2
Mean length4.275
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
50.8%
영업/정상 45
37.5%
취소/말소/만료/정지/중지 9
 
7.5%
제외/삭제/전출 5
 
4.2%

Length

2024-05-11T15:39:02.811105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:02.989694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
50.8%
영업/정상 45
37.5%
취소/말소/만료/정지/중지 9
 
7.5%
제외/삭제/전출 5
 
4.2%
Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
3
61 
13
45 
31
15
 
5
35
 
2

Length

Max length2
Median length1
Mean length1.4916667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 61
50.8%
13 45
37.5%
31 7
 
5.8%
15 5
 
4.2%
35 2
 
1.7%

Length

2024-05-11T15:39:03.180245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:03.340989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
50.8%
13 45
37.5%
31 7
 
5.8%
15 5
 
4.2%
35 2
 
1.7%
Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
폐업
61 
영업중
45 
등록취소
전출
 
5
직권말소
 
2

Length

Max length4
Median length2
Mean length2.525
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 61
50.8%
영업중 45
37.5%
등록취소 7
 
5.8%
전출 5
 
4.2%
직권말소 2
 
1.7%

Length

2024-05-11T15:39:03.522960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:03.715828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
50.8%
영업중 45
37.5%
등록취소 7
 
5.8%
전출 5
 
4.2%
직권말소 2
 
1.7%

폐업일자
Date

MISSING 

Distinct62
Distinct (%)93.9%
Missing54
Missing (%)45.0%
Memory size1.1 KiB
Minimum1999-02-10 00:00:00
Maximum2024-04-15 00:00:00
2024-05-11T15:39:03.913951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:04.121665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

전화번호
Text

MISSING 

Distinct84
Distinct (%)98.8%
Missing35
Missing (%)29.2%
Memory size1.1 KiB
2024-05-11T15:39:04.504924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.517647
Min length8

Characters and Unicode

Total characters894
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

Unique83 ?
Unique (%)97.6%

Sample

1st row926-9054
2nd row2247-5906
3rd row277-0171
4th row741-4163
5th row967-2929
ValueCountFrequency (%)
02-2212-8909 2
 
2.4%
6959-9388 1
 
1.2%
926-9054 1
 
1.2%
02-966-5353 1
 
1.2%
02-722-3771 1
 
1.2%
02-753-8181 1
 
1.2%
070-7794-5442 1
 
1.2%
736-4577 1
 
1.2%
02-318-1950 1
 
1.2%
02-733-1212 1
 
1.2%
Other values (74) 74
87.1%
2024-05-11T15:39:05.077480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 161
18.0%
- 136
15.2%
0 111
12.4%
3 79
8.8%
7 70
7.8%
1 65
7.3%
5 57
 
6.4%
9 55
 
6.2%
4 54
 
6.0%
6 54
 
6.0%
Other values (3) 52
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 755
84.5%
Dash Punctuation 136
 
15.2%
Close Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 161
21.3%
0 111
14.7%
3 79
10.5%
7 70
9.3%
1 65
8.6%
5 57
 
7.5%
9 55
 
7.3%
4 54
 
7.2%
6 54
 
7.2%
8 49
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 161
18.0%
- 136
15.2%
0 111
12.4%
3 79
8.8%
7 70
7.8%
1 65
7.3%
5 57
 
6.4%
9 55
 
6.2%
4 54
 
6.0%
6 54
 
6.0%
Other values (3) 52
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 161
18.0%
- 136
15.2%
0 111
12.4%
3 79
8.8%
7 70
7.8%
1 65
7.3%
5 57
 
6.4%
9 55
 
6.2%
4 54
 
6.0%
6 54
 
6.0%
Other values (3) 52
 
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

소재지우편번호
Text

MISSING 

Distinct42
Distinct (%)73.7%
Missing63
Missing (%)52.5%
Memory size1.1 KiB
2024-05-11T15:39:05.378284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2105263
Min length6

Characters and Unicode

Total characters354
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

Unique35 ?
Unique (%)61.4%

Sample

1st row130-823
2nd row130-846
3rd row130812
4th row130817
5th row130867
ValueCountFrequency (%)
130812 5
 
8.8%
130811 5
 
8.8%
130817 3
 
5.3%
130814 3
 
5.3%
130-823 2
 
3.5%
130805 2
 
3.5%
130787 2
 
3.5%
130832 1
 
1.8%
130-703 1
 
1.8%
130842 1
 
1.8%
Other values (32) 32
56.1%
2024-05-11T15:39:05.822850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 87
24.6%
0 73
20.6%
3 66
18.6%
8 50
14.1%
7 19
 
5.4%
2 15
 
4.2%
4 15
 
4.2%
- 12
 
3.4%
5 8
 
2.3%
6 6
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
96.6%
Dash Punctuation 12
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 87
25.4%
0 73
21.3%
3 66
19.3%
8 50
14.6%
7 19
 
5.6%
2 15
 
4.4%
4 15
 
4.4%
5 8
 
2.3%
6 6
 
1.8%
9 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 87
24.6%
0 73
20.6%
3 66
18.6%
8 50
14.1%
7 19
 
5.4%
2 15
 
4.2%
4 15
 
4.2%
- 12
 
3.4%
5 8
 
2.3%
6 6
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 87
24.6%
0 73
20.6%
3 66
18.6%
8 50
14.1%
7 19
 
5.4%
2 15
 
4.2%
4 15
 
4.2%
- 12
 
3.4%
5 8
 
2.3%
6 6
 
1.7%
Distinct113
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:39:06.346853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length35
Mean length27.875
Min length18

Characters and Unicode

Total characters3345
Distinct characters147
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)90.0%

Sample

1st row서울특별시 동대문구 용두동 233-19
2nd row서울특별시 동대문구 장안동 464-8
3rd row서울특별시 동대문구 신설동 102-37번지
4th row서울특별시 동대문구 용두동 23-7번지
5th row서울특별시 동대문구 청량리동 281번지
ValueCountFrequency (%)
서울특별시 118
18.7%
동대문구 118
18.7%
용두동 33
 
5.2%
장안동 24
 
3.8%
신설동 21
 
3.3%
전농동 14
 
2.2%
답십리동 8
 
1.3%
청량리동 6
 
0.9%
휘경동 4
 
0.6%
이문동 4
 
0.6%
Other values (225) 282
44.6%
2024-05-11T15:39:07.067566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
556
 
16.6%
265
 
7.9%
134
 
4.0%
133
 
4.0%
1 132
 
3.9%
121
 
3.6%
120
 
3.6%
118
 
3.5%
118
 
3.5%
118
 
3.5%
Other values (137) 1530
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2027
60.6%
Decimal Number 652
 
19.5%
Space Separator 556
 
16.6%
Dash Punctuation 105
 
3.1%
Uppercase Letter 4
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
265
 
13.1%
134
 
6.6%
133
 
6.6%
121
 
6.0%
120
 
5.9%
118
 
5.8%
118
 
5.8%
118
 
5.8%
118
 
5.8%
51
 
2.5%
Other values (121) 731
36.1%
Decimal Number
ValueCountFrequency (%)
1 132
20.2%
3 100
15.3%
4 68
10.4%
0 62
9.5%
2 60
9.2%
7 56
8.6%
8 47
 
7.2%
5 45
 
6.9%
6 43
 
6.6%
9 39
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
Y 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2027
60.6%
Common 1314
39.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
265
 
13.1%
134
 
6.6%
133
 
6.6%
121
 
6.0%
120
 
5.9%
118
 
5.8%
118
 
5.8%
118
 
5.8%
118
 
5.8%
51
 
2.5%
Other values (121) 731
36.1%
Common
ValueCountFrequency (%)
556
42.3%
1 132
 
10.0%
- 105
 
8.0%
3 100
 
7.6%
4 68
 
5.2%
0 62
 
4.7%
2 60
 
4.6%
7 56
 
4.3%
8 47
 
3.6%
5 45
 
3.4%
Other values (3) 83
 
6.3%
Latin
ValueCountFrequency (%)
B 2
50.0%
Y 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2027
60.6%
ASCII 1318
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
556
42.2%
1 132
 
10.0%
- 105
 
8.0%
3 100
 
7.6%
4 68
 
5.2%
0 62
 
4.7%
2 60
 
4.6%
7 56
 
4.2%
8 47
 
3.6%
5 45
 
3.4%
Other values (6) 87
 
6.6%
Hangul
ValueCountFrequency (%)
265
 
13.1%
134
 
6.6%
133
 
6.6%
121
 
6.0%
120
 
5.9%
118
 
5.8%
118
 
5.8%
118
 
5.8%
118
 
5.8%
51
 
2.5%
Other values (121) 731
36.1%
Distinct115
Distinct (%)96.6%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-05-11T15:39:07.485598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length44
Mean length35.915966
Min length24

Characters and Unicode

Total characters4274
Distinct characters176
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

Unique111 ?
Unique (%)93.3%

Sample

1st row서울특별시 동대문구 왕산로9길 20 (용두동)
2nd row서울특별시 동대문구 천호대로 425 (장안동)
3rd row서울특별시 동대문구 왕산로2길 32 (신설동)
4th row서울특별시 동대문구 왕산로 140 (용두동)
5th row서울특별시 동대문구 홍릉로 8 (청량리동)
ValueCountFrequency (%)
서울특별시 117
 
14.4%
동대문구 117
 
14.4%
용두동 30
 
3.7%
왕산로 23
 
2.8%
장안동 22
 
2.7%
천호대로 19
 
2.3%
전농동 14
 
1.7%
신설동 12
 
1.5%
장한로 9
 
1.1%
3층 9
 
1.1%
Other values (282) 439
54.1%
2024-05-11T15:39:08.439023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
718
 
16.8%
271
 
6.3%
166
 
3.9%
1 147
 
3.4%
, 141
 
3.3%
135
 
3.2%
128
 
3.0%
125
 
2.9%
125
 
2.9%
121
 
2.8%
Other values (166) 2197
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2509
58.7%
Space Separator 718
 
16.8%
Decimal Number 643
 
15.0%
Other Punctuation 141
 
3.3%
Close Punctuation 120
 
2.8%
Open Punctuation 120
 
2.8%
Dash Punctuation 12
 
0.3%
Uppercase Letter 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
271
 
10.8%
166
 
6.6%
135
 
5.4%
128
 
5.1%
125
 
5.0%
125
 
5.0%
121
 
4.8%
120
 
4.8%
117
 
4.7%
117
 
4.7%
Other values (147) 1084
43.2%
Decimal Number
ValueCountFrequency (%)
1 147
22.9%
2 100
15.6%
3 95
14.8%
0 79
12.3%
4 71
11.0%
5 41
 
6.4%
7 34
 
5.3%
8 29
 
4.5%
9 28
 
4.4%
6 19
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
45.5%
C 2
 
18.2%
Y 2
 
18.2%
A 2
 
18.2%
Space Separator
ValueCountFrequency (%)
718
100.0%
Other Punctuation
ValueCountFrequency (%)
, 141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2509
58.7%
Common 1754
41.0%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
271
 
10.8%
166
 
6.6%
135
 
5.4%
128
 
5.1%
125
 
5.0%
125
 
5.0%
121
 
4.8%
120
 
4.8%
117
 
4.7%
117
 
4.7%
Other values (147) 1084
43.2%
Common
ValueCountFrequency (%)
718
40.9%
1 147
 
8.4%
, 141
 
8.0%
) 120
 
6.8%
( 120
 
6.8%
2 100
 
5.7%
3 95
 
5.4%
0 79
 
4.5%
4 71
 
4.0%
5 41
 
2.3%
Other values (5) 122
 
7.0%
Latin
ValueCountFrequency (%)
B 5
45.5%
C 2
 
18.2%
Y 2
 
18.2%
A 2
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2509
58.7%
ASCII 1765
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
718
40.7%
1 147
 
8.3%
, 141
 
8.0%
) 120
 
6.8%
( 120
 
6.8%
2 100
 
5.7%
3 95
 
5.4%
0 79
 
4.5%
4 71
 
4.0%
5 41
 
2.3%
Other values (9) 133
 
7.5%
Hangul
ValueCountFrequency (%)
271
 
10.8%
166
 
6.6%
135
 
5.4%
128
 
5.1%
125
 
5.0%
125
 
5.0%
121
 
4.8%
120
 
4.8%
117
 
4.7%
117
 
4.7%
Other values (147) 1084
43.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct53
Distinct (%)57.0%
Missing27
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean11252.602
Minimum2419
Maximum130851
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:08.744952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2419
5-th percentile2448
Q12560
median2585
Q32622
95-th percentile130322.4
Maximum130851
Range128432
Interquartile range (IQR)62

Descriptive statistics

Standard deviation31654.365
Coefficient of variation (CV)2.8130707
Kurtosis11.000044
Mean11252.602
Median Absolute Deviation (MAD)26
Skewness3.5588253
Sum1046492
Variance1.0019988 × 109
MonotonicityNot monotonic
2024-05-11T15:39:08.971477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2560 6
 
5.0%
2624 5
 
4.2%
2586 5
 
4.2%
2565 5
 
4.2%
2585 4
 
3.3%
2577 3
 
2.5%
2594 3
 
2.5%
2591 3
 
2.5%
2622 3
 
2.5%
2582 3
 
2.5%
Other values (43) 53
44.2%
(Missing) 27
22.5%
ValueCountFrequency (%)
2419 1
0.8%
2420 1
0.8%
2435 1
0.8%
2440 1
0.8%
2445 1
0.8%
2450 1
0.8%
2483 1
0.8%
2489 1
0.8%
2490 1
0.8%
2496 1
0.8%
ValueCountFrequency (%)
130851 1
0.8%
130810 1
0.8%
130787 1
0.8%
130723 1
0.8%
130701 1
0.8%
130070 1
0.8%
22020 2
1.7%
2645 2
1.7%
2640 1
0.8%
2636 1
0.8%
Distinct118
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-05-11T15:39:09.296763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length8.8166667
Min length2

Characters and Unicode

Total characters1058
Distinct characters225
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)97.5%

Sample

1st row태경조이
2nd row(주)월드레스포여행사
3rd row알라스카관광공사지사
4th row(주)징검다리여행사(국외)
5th rowGUAM한마음투어지사
ValueCountFrequency (%)
주식회사 20
 
12.3%
가람티앤씨(t&c 3
 
1.9%
투어 2
 
1.2%
아람투어 2
 
1.2%
동대문 1
 
0.6%
세훈여행 1
 
0.6%
커피를만드는사람들 1
 
0.6%
주)투어프라자 1
 
0.6%
주)데니스여행사 1
 
0.6%
주)더투어샵 1
 
0.6%
Other values (129) 129
79.6%
2024-05-11T15:39:09.808877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
7.8%
( 68
 
6.4%
) 68
 
6.4%
50
 
4.7%
42
 
4.0%
39
 
3.7%
37
 
3.5%
27
 
2.6%
27
 
2.6%
27
 
2.6%
Other values (215) 591
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 847
80.1%
Open Punctuation 68
 
6.4%
Close Punctuation 68
 
6.4%
Space Separator 42
 
4.0%
Uppercase Letter 15
 
1.4%
Lowercase Letter 14
 
1.3%
Other Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
82
 
9.7%
50
 
5.9%
39
 
4.6%
37
 
4.4%
27
 
3.2%
27
 
3.2%
27
 
3.2%
23
 
2.7%
23
 
2.7%
20
 
2.4%
Other values (190) 492
58.1%
Lowercase Letter
ValueCountFrequency (%)
u 3
21.4%
e 1
 
7.1%
l 1
 
7.1%
f 1
 
7.1%
i 1
 
7.1%
n 1
 
7.1%
o 1
 
7.1%
p 1
 
7.1%
r 1
 
7.1%
c 1
 
7.1%
Other values (2) 2
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 4
26.7%
T 3
20.0%
G 2
13.3%
B 1
 
6.7%
F 1
 
6.7%
W 1
 
6.7%
M 1
 
6.7%
A 1
 
6.7%
U 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Other Punctuation
ValueCountFrequency (%)
& 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 847
80.1%
Common 182
 
17.2%
Latin 29
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
82
 
9.7%
50
 
5.9%
39
 
4.6%
37
 
4.4%
27
 
3.2%
27
 
3.2%
27
 
3.2%
23
 
2.7%
23
 
2.7%
20
 
2.4%
Other values (190) 492
58.1%
Latin
ValueCountFrequency (%)
C 4
 
13.8%
u 3
 
10.3%
T 3
 
10.3%
G 2
 
6.9%
e 1
 
3.4%
B 1
 
3.4%
l 1
 
3.4%
f 1
 
3.4%
i 1
 
3.4%
n 1
 
3.4%
Other values (11) 11
37.9%
Common
ValueCountFrequency (%)
( 68
37.4%
) 68
37.4%
42
23.1%
& 4
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 847
80.1%
ASCII 211
 
19.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
82
 
9.7%
50
 
5.9%
39
 
4.6%
37
 
4.4%
27
 
3.2%
27
 
3.2%
27
 
3.2%
23
 
2.7%
23
 
2.7%
20
 
2.4%
Other values (190) 492
58.1%
ASCII
ValueCountFrequency (%)
( 68
32.2%
) 68
32.2%
42
19.9%
& 4
 
1.9%
C 4
 
1.9%
u 3
 
1.4%
T 3
 
1.4%
G 2
 
0.9%
e 1
 
0.5%
B 1
 
0.5%
Other values (15) 15
 
7.1%
Distinct115
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2003-04-18 15:38:35
Maximum2024-05-02 15:35:40
2024-05-11T15:39:10.050598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:10.297487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
U
72 
I
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 72
60.0%
I 48
40.0%

Length

2024-05-11T15:39:10.496878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:10.626409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 72
60.0%
i 48
40.0%
Distinct59
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:39:10.815634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:11.011279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

좌표정보(X)
Real number (ℝ)

Distinct90
Distinct (%)75.6%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean203337.2
Minimum166870.89
Maximum206590.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:11.187597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166870.89
5-th percentile202044.35
Q1202740.91
median203803.38
Q3205206.99
95-th percentile206101.91
Maximum206590.05
Range39719.159
Interquartile range (IQR)2466.0785

Descriptive statistics

Standard deviation4980.3605
Coefficient of variation (CV)0.02449311
Kurtosis48.200954
Mean203337.2
Median Absolute Deviation (MAD)1196.023
Skewness-6.731008
Sum24197127
Variance24803990
MonotonicityNot monotonic
2024-05-11T15:39:11.378056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203356.957362754 4
 
3.3%
206101.9138443 4
 
3.3%
202897.628746121 3
 
2.5%
203967.783536236 3
 
2.5%
204048.508433109 3
 
2.5%
202792.678699836 3
 
2.5%
203188.427527295 2
 
1.7%
205742.110580377 2
 
1.7%
204884.796367996 2
 
1.7%
205858.614104173 2
 
1.7%
Other values (80) 91
75.8%
ValueCountFrequency (%)
166870.887070091 2
1.7%
202022.650035503 2
1.7%
202023.921749857 1
0.8%
202033.22548938 1
0.8%
202045.581261433 1
0.8%
202056.089579192 1
0.8%
202076.619577636 1
0.8%
202078.855745629 1
0.8%
202081.516316998 1
0.8%
202116.938316772 1
0.8%
ValueCountFrequency (%)
206590.046202018 1
 
0.8%
206484.233644024 1
 
0.8%
206317.625784018 1
 
0.8%
206296.915447815 1
 
0.8%
206101.9138443 4
3.3%
206090.434292925 1
 
0.8%
206057.985138022 1
 
0.8%
206053.014794545 2
1.7%
206039.648371834 1
 
0.8%
205904.610819986 1
 
0.8%

좌표정보(Y)
Real number (ℝ)

Distinct90
Distinct (%)75.6%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean452312.74
Minimum434329.26
Maximum455033.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:11.593718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum434329.26
5-th percentile451116.95
Q1452225.55
median452524.17
Q3452915.13
95-th percentile454231.95
Maximum455033.43
Range20704.17
Interquartile range (IQR)689.58187

Descriptive statistics

Standard deviation2496.3209
Coefficient of variation (CV)0.0055190152
Kurtosis45.027675
Mean452312.74
Median Absolute Deviation (MAD)368.47582
Skewness-6.3797516
Sum53825216
Variance6231617.9
MonotonicityNot monotonic
2024-05-11T15:39:11.791627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452469.300221465 4
 
3.3%
452155.691148899 4
 
3.3%
452834.682253792 3
 
2.5%
452510.849293451 3
 
2.5%
452452.733089156 3
 
2.5%
452915.127892459 3
 
2.5%
452835.044818809 2
 
1.7%
451664.212631043 2
 
1.7%
451394.889425203 2
 
1.7%
451494.590428778 2
 
1.7%
Other values (80) 91
75.8%
ValueCountFrequency (%)
434329.255701773 2
1.7%
451038.454241239 1
0.8%
451059.346901649 1
0.8%
451094.412855942 1
0.8%
451103.146980087 1
0.8%
451118.479199016 1
0.8%
451135.637561446 1
0.8%
451284.080255576 1
0.8%
451290.385714542 1
0.8%
451394.889425203 2
1.7%
ValueCountFrequency (%)
455033.426085375 1
0.8%
454935.013985935 1
0.8%
454934.047367752 1
0.8%
454874.254865697 1
0.8%
454833.337679973 1
0.8%
454406.655078623 1
0.8%
454212.542182175 1
0.8%
454149.049376394 1
0.8%
454074.991324664 1
0.8%
453510.992949524 1
0.8%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
62 
국내외여행업
58 

Length

Max length6
Median length4
Mean length4.9666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 62
51.7%
국내외여행업 58
48.3%

Length

2024-05-11T15:39:11.988025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:12.170624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 62
51.7%
국내외여행업 58
48.3%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
85 
관광사업
35 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
70.8%
관광사업 35
29.2%

Length

2024-05-11T15:39:12.364235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:12.523361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
70.8%
관광사업 35
29.2%

지역구분명
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing113
Missing (%)94.2%
Memory size1.1 KiB
2024-05-11T15:39:12.696418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.7142857
Min length4

Characters and Unicode

Total characters33
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)71.4%

Sample

1st row공업지역
2nd row상업지역
3rd row준주거지역
4th row일반상업지역
5th row상업지역
ValueCountFrequency (%)
상업지역 2
28.6%
공업지역 1
14.3%
준주거지역 1
14.3%
일반상업지역 1
14.3%
근린상업지역 1
14.3%
주거지역 1
14.3%
2024-05-11T15:39:13.462368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
21.2%
7
21.2%
5
15.2%
4
12.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (2) 2
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7
21.2%
7
21.2%
5
15.2%
4
12.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (2) 2
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7
21.2%
7
21.2%
5
15.2%
4
12.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (2) 2
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
7
21.2%
7
21.2%
5
15.2%
4
12.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (2) 2
 
6.1%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)66.7%
Missing108
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean5.1666667
Minimum0
Maximum35
Zeros5
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:13.671199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.5
Q35.25
95-th percentile19.6
Maximum35
Range35
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation9.7405743
Coefficient of variation (CV)1.8852724
Kurtosis9.8976453
Mean5.1666667
Median Absolute Deviation (MAD)2.5
Skewness3.0485539
Sum62
Variance94.878788
MonotonicityNot monotonic
2024-05-11T15:39:13.903282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 5
 
4.2%
4 1
 
0.8%
2 1
 
0.8%
3 1
 
0.8%
5 1
 
0.8%
35 1
 
0.8%
7 1
 
0.8%
6 1
 
0.8%
(Missing) 108
90.0%
ValueCountFrequency (%)
0 5
4.2%
2 1
 
0.8%
3 1
 
0.8%
4 1
 
0.8%
5 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
35 1
 
0.8%
ValueCountFrequency (%)
35 1
 
0.8%
7 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
4 1
 
0.8%
3 1
 
0.8%
2 1
 
0.8%
0 5
4.2%

주변환경명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
113 
기타
 
7

Length

Max length4
Median length4
Mean length3.8833333
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> 113
94.2%
기타 7
 
5.8%

Length

2024-05-11T15:39:14.193214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:14.411401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
94.2%
기타 7
 
5.8%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

보험기관명
Text

MISSING 

Distinct15
Distinct (%)51.7%
Missing91
Missing (%)75.8%
Memory size1.1 KiB
2024-05-11T15:39:14.710427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.862069
Min length4

Characters and Unicode

Total characters257
Distinct characters36
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)37.9%

Sample

1st row서울보증보험-주
2nd row서울보증보험
3rd row한국관광협회중앙회 여행공제회
4th row서울보증보험
5th row한국관광협회중앙회
ValueCountFrequency (%)
서울보증보험 11
35.5%
한국관광협회중앙회 5
16.1%
여행공제회 3
 
9.7%
서울보증보험주식회사 2
 
6.5%
서울보증보험-주 1
 
3.2%
관광공제회 1
 
3.2%
서울시관광협회 1
 
3.2%
서울보증 1
 
3.2%
서울보증보험(30,000,000 1
 
3.2%
서울보증보험(주 1
 
3.2%
Other values (4) 4
 
12.9%
2024-05-11T15:39:15.247361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
14.4%
20
 
7.8%
20
 
7.8%
19
 
7.4%
19
 
7.4%
18
 
7.0%
0 17
 
6.6%
8
 
3.1%
8
 
3.1%
7
 
2.7%
Other values (26) 84
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
82.5%
Decimal Number 26
 
10.1%
Close Punctuation 5
 
1.9%
Open Punctuation 5
 
1.9%
Other Punctuation 4
 
1.6%
Dash Punctuation 3
 
1.2%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
17.5%
20
 
9.4%
20
 
9.4%
19
 
9.0%
19
 
9.0%
18
 
8.5%
8
 
3.8%
8
 
3.8%
7
 
3.3%
6
 
2.8%
Other values (16) 50
23.6%
Decimal Number
ValueCountFrequency (%)
0 17
65.4%
3 4
 
15.4%
2 3
 
11.5%
1 1
 
3.8%
9 1
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
82.5%
Common 45
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
17.5%
20
 
9.4%
20
 
9.4%
19
 
9.0%
19
 
9.0%
18
 
8.5%
8
 
3.8%
8
 
3.8%
7
 
3.3%
6
 
2.8%
Other values (16) 50
23.6%
Common
ValueCountFrequency (%)
0 17
37.8%
) 5
 
11.1%
( 5
 
11.1%
3 4
 
8.9%
, 4
 
8.9%
2 3
 
6.7%
- 3
 
6.7%
2
 
4.4%
1 1
 
2.2%
9 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
82.5%
ASCII 45
 
17.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
37
17.5%
20
 
9.4%
20
 
9.4%
19
 
9.0%
19
 
9.0%
18
 
8.5%
8
 
3.8%
8
 
3.8%
7
 
3.3%
6
 
2.8%
Other values (16) 50
23.6%
ASCII
ValueCountFrequency (%)
0 17
37.8%
) 5
 
11.1%
( 5
 
11.1%
3 4
 
8.9%
, 4
 
8.9%
2 3
 
6.7%
- 3
 
6.7%
2
 
4.4%
1 1
 
2.2%
9 1
 
2.2%

건물용도명
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
104 
근린생활시설
 
10
사무실
 
4
다가구용 주택(공동주택적용)
 
1
단독주택
 
1

Length

Max length15
Median length4
Mean length4.225
Min length3

Unique

Unique2 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 104
86.7%
근린생활시설 10
 
8.3%
사무실 4
 
3.3%
다가구용 주택(공동주택적용) 1
 
0.8%
단독주택 1
 
0.8%

Length

2024-05-11T15:39:15.489012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:15.765606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 104
86.0%
근린생활시설 10
 
8.3%
사무실 4
 
3.3%
다가구용 1
 
0.8%
주택(공동주택적용 1
 
0.8%
단독주택 1
 
0.8%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)42.9%
Missing106
Missing (%)88.3%
Infinite0
Infinite (%)0.0%
Mean4.0714286
Minimum0
Maximum30
Zeros5
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:15.970910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34.5
95-th percentile14.4
Maximum30
Range30
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation7.7604945
Coefficient of variation (CV)1.9060864
Kurtosis11.461714
Mean4.0714286
Median Absolute Deviation (MAD)2
Skewness3.2721714
Sum57
Variance60.225275
MonotonicityNot monotonic
2024-05-11T15:39:16.185248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 5
 
4.2%
3 3
 
2.5%
1 2
 
1.7%
5 2
 
1.7%
30 1
 
0.8%
6 1
 
0.8%
(Missing) 106
88.3%
ValueCountFrequency (%)
0 5
4.2%
1 2
 
1.7%
3 3
2.5%
5 2
 
1.7%
6 1
 
0.8%
30 1
 
0.8%
ValueCountFrequency (%)
30 1
 
0.8%
6 1
 
0.8%
5 2
 
1.7%
3 3
2.5%
1 2
 
1.7%
0 5
4.2%

지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
<NA>
108 
0
 
5
1
 
5
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7
Min length1

Unique

Unique2 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 108
90.0%
0 5
 
4.2%
1 5
 
4.2%
4 1
 
0.8%
5 1
 
0.8%

Length

2024-05-11T15:39:16.422764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:16.596975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
90.0%
0 5
 
4.2%
1 5
 
4.2%
4 1
 
0.8%
5 1
 
0.8%

객실수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

건축연면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

영문상호명
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing116
Missing (%)96.7%
Memory size1.1 KiB
2024-05-11T15:39:16.805617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length16.25
Min length13

Characters and Unicode

Total characters65
Distinct characters29
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

Unique4 ?
Unique (%)100.0%

Sample

1st rowASA TOUR co.,ltd
2nd rowE-RUM co.,ltd
3rd rowDennis Travel Services
4th rowWE TOURS, INC.
ValueCountFrequency (%)
co.,ltd 2
18.2%
asa 1
9.1%
tour 1
9.1%
e-rum 1
9.1%
dennis 1
9.1%
travel 1
9.1%
services 1
9.1%
we 1
9.1%
tours 1
9.1%
inc 1
9.1%
2024-05-11T15:39:17.208469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
10.8%
e 4
 
6.2%
T 3
 
4.6%
U 3
 
4.6%
R 3
 
4.6%
c 3
 
4.6%
. 3
 
4.6%
, 3
 
4.6%
l 3
 
4.6%
S 3
 
4.6%
Other values (19) 30
46.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
41.5%
Uppercase Letter 24
36.9%
Space Separator 7
 
10.8%
Other Punctuation 6
 
9.2%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 3
12.5%
U 3
12.5%
R 3
12.5%
S 3
12.5%
A 2
8.3%
E 2
8.3%
O 2
8.3%
D 1
 
4.2%
M 1
 
4.2%
W 1
 
4.2%
Other values (3) 3
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
c 3
11.1%
l 3
11.1%
v 2
7.4%
r 2
7.4%
s 2
7.4%
i 2
7.4%
n 2
7.4%
d 2
7.4%
t 2
7.4%
Other values (2) 3
11.1%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
, 3
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 51
78.5%
Common 14
 
21.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4
 
7.8%
T 3
 
5.9%
U 3
 
5.9%
R 3
 
5.9%
c 3
 
5.9%
l 3
 
5.9%
S 3
 
5.9%
A 2
 
3.9%
v 2
 
3.9%
r 2
 
3.9%
Other values (15) 23
45.1%
Common
ValueCountFrequency (%)
7
50.0%
. 3
21.4%
, 3
21.4%
- 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
 
10.8%
e 4
 
6.2%
T 3
 
4.6%
U 3
 
4.6%
R 3
 
4.6%
c 3
 
4.6%
. 3
 
4.6%
, 3
 
4.6%
l 3
 
4.6%
S 3
 
4.6%
Other values (19) 30
46.2%

영문상호주소
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing116
Missing (%)96.7%
Memory size1.1 KiB
2024-05-11T15:39:17.430035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.25
Min length21

Characters and Unicode

Total characters93
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowInbound Travel Agency
2nd rowOverseas Travel Business
3rd rowOVERSEAS TRAVEL BUSINESS
4th rowOVERSEAS TRAVEL BUSINESS
ValueCountFrequency (%)
travel 4
33.3%
overseas 3
25.0%
business 3
25.0%
inbound 1
 
8.3%
agency 1
 
8.3%
2024-05-11T15:39:17.866055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 10
 
10.8%
E 8
 
8.6%
8
 
8.6%
e 6
 
6.5%
A 5
 
5.4%
s 5
 
5.4%
V 4
 
4.3%
R 4
 
4.3%
T 4
 
4.3%
n 4
 
4.3%
Other values (18) 35
37.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 50
53.8%
Lowercase Letter 35
37.6%
Space Separator 8
 
8.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6
17.1%
s 5
14.3%
n 4
11.4%
v 3
8.6%
a 3
8.6%
r 3
8.6%
u 2
 
5.7%
l 2
 
5.7%
y 1
 
2.9%
c 1
 
2.9%
Other values (5) 5
14.3%
Uppercase Letter
ValueCountFrequency (%)
S 10
20.0%
E 8
16.0%
A 5
10.0%
V 4
 
8.0%
R 4
 
8.0%
T 4
 
8.0%
O 3
 
6.0%
I 3
 
6.0%
B 3
 
6.0%
N 2
 
4.0%
Other values (2) 4
 
8.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85
91.4%
Common 8
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 10
 
11.8%
E 8
 
9.4%
e 6
 
7.1%
A 5
 
5.9%
s 5
 
5.9%
V 4
 
4.7%
R 4
 
4.7%
T 4
 
4.7%
n 4
 
4.7%
O 3
 
3.5%
Other values (17) 32
37.6%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 10
 
10.8%
E 8
 
8.6%
8
 
8.6%
e 6
 
6.5%
A 5
 
5.4%
s 5
 
5.4%
V 4
 
4.3%
R 4
 
4.3%
T 4
 
4.3%
n 4
 
4.3%
Other values (18) 35
37.6%

선박총톤수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

선박척수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

무대면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

좌석수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

회의실별동시수용인원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)65.2%
Missing97
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean51.596522
Minimum0
Maximum262.44
Zeros9
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:18.135072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25.67
Q372.26
95-th percentile221.476
Maximum262.44
Range262.44
Interquartile range (IQR)72.26

Descriptive statistics

Standard deviation72.186056
Coefficient of variation (CV)1.3990489
Kurtosis3.5099576
Mean51.596522
Median Absolute Deviation (MAD)25.67
Skewness1.9251362
Sum1186.72
Variance5210.8266
MonotonicityNot monotonic
2024-05-11T15:39:18.371614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 9
 
7.5%
262.44 1
 
0.8%
233.64 1
 
0.8%
25.67 1
 
0.8%
100.0 1
 
0.8%
112.0 1
 
0.8%
46.42 1
 
0.8%
83.83 1
 
0.8%
99.63 1
 
0.8%
24.0 1
 
0.8%
Other values (5) 5
 
4.2%
(Missing) 97
80.8%
ValueCountFrequency (%)
0.0 9
7.5%
15.0 1
 
0.8%
24.0 1
 
0.8%
25.67 1
 
0.8%
31.0 1
 
0.8%
32.4 1
 
0.8%
46.42 1
 
0.8%
60.0 1
 
0.8%
60.69 1
 
0.8%
83.83 1
 
0.8%
ValueCountFrequency (%)
262.44 1
0.8%
233.64 1
0.8%
112.0 1
0.8%
100.0 1
0.8%
99.63 1
0.8%
83.83 1
0.8%
60.69 1
0.8%
60.0 1
0.8%
46.42 1
0.8%
32.4 1
0.8%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

놀이시설수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

자본금
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)27.3%
Missing87
Missing (%)72.5%
Infinite0
Infinite (%)0.0%
Mean83234642
Minimum10000000
Maximum3.15 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:18.593041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000000
5-th percentile22000000
Q160000000
median60000000
Q31 × 108
95-th percentile1.6172185 × 108
Maximum3.15 × 108
Range3.05 × 108
Interquartile range (IQR)40000000

Descriptive statistics

Standard deviation59946259
Coefficient of variation (CV)0.72020804
Kurtosis7.6635649
Mean83234642
Median Absolute Deviation (MAD)40000000
Skewness2.4019678
Sum2.7467432 × 109
Variance3.5935539 × 1015
MonotonicityNot monotonic
2024-05-11T15:39:18.768984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
100000000 13
 
10.8%
60000000 10
 
8.3%
30000000 3
 
2.5%
10000000 2
 
1.7%
250000000 1
 
0.8%
315000000 1
 
0.8%
38849895 1
 
0.8%
30023557 1
 
0.8%
102869744 1
 
0.8%
(Missing) 87
72.5%
ValueCountFrequency (%)
10000000 2
 
1.7%
30000000 3
 
2.5%
30023557 1
 
0.8%
38849895 1
 
0.8%
60000000 10
8.3%
100000000 13
10.8%
102869744 1
 
0.8%
250000000 1
 
0.8%
315000000 1
 
0.8%
ValueCountFrequency (%)
315000000 1
 
0.8%
250000000 1
 
0.8%
102869744 1
 
0.8%
100000000 13
10.8%
60000000 10
8.3%
38849895 1
 
0.8%
30023557 1
 
0.8%
30000000 3
 
2.5%
10000000 2
 
1.7%

보험시작일자
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)100.0%
Missing88
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean20151252
Minimum20080127
Maximum20201113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:18.985989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20080127
5-th percentile20080426
Q120127976
median20161056
Q320173390
95-th percentile20194900
Maximum20201113
Range120986
Interquartile range (IQR)45414.25

Descriptive statistics

Standard deviation35781.103
Coefficient of variation (CV)0.0017756268
Kurtosis-0.53855562
Mean20151252
Median Absolute Deviation (MAD)20450
Skewness-0.69207538
Sum6.4484007 × 108
Variance1.2802873 × 109
MonotonicityNot monotonic
2024-05-11T15:39:19.201208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20140128 1
 
0.8%
20200122 1
 
0.8%
20190627 1
 
0.8%
20190220 1
 
0.8%
20170308 1
 
0.8%
20190430 1
 
0.8%
20171120 1
 
0.8%
20180201 1
 
0.8%
20181028 1
 
0.8%
20170627 1
 
0.8%
Other values (22) 22
 
18.3%
(Missing) 88
73.3%
ValueCountFrequency (%)
20080127 1
0.8%
20080208 1
0.8%
20080605 1
0.8%
20100402 1
0.8%
20100621 1
0.8%
20110906 1
0.8%
20120625 1
0.8%
20121223 1
0.8%
20130227 1
0.8%
20130926 1
0.8%
ValueCountFrequency (%)
20201113 1
0.8%
20200122 1
0.8%
20190627 1
0.8%
20190430 1
0.8%
20190220 1
0.8%
20181028 1
0.8%
20180822 1
0.8%
20180201 1
0.8%
20171120 1
0.8%
20170828 1
0.8%

보험종료일자
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)100.0%
Missing88
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean20161249
Minimum20090126
Maximum20211113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:19.456510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20090126
5-th percentile20090426
Q120137975
median20171055
Q320183372
95-th percentile20204899
Maximum20211113
Range120987
Interquartile range (IQR)45397

Descriptive statistics

Standard deviation35779.237
Coefficient of variation (CV)0.0017746538
Kurtosis-0.53834473
Mean20161249
Median Absolute Deviation (MAD)20450
Skewness-0.69210679
Sum6.4515997 × 108
Variance1.2801538 × 109
MonotonicityNot monotonic
2024-05-11T15:39:19.680516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20150128 1
 
0.8%
20210121 1
 
0.8%
20200626 1
 
0.8%
20200219 1
 
0.8%
20180307 1
 
0.8%
20200429 1
 
0.8%
20181119 1
 
0.8%
20190131 1
 
0.8%
20191028 1
 
0.8%
20180626 1
 
0.8%
Other values (22) 22
 
18.3%
(Missing) 88
73.3%
ValueCountFrequency (%)
20090126 1
0.8%
20090207 1
0.8%
20090605 1
0.8%
20110402 1
0.8%
20110620 1
0.8%
20120906 1
0.8%
20130625 1
0.8%
20131222 1
0.8%
20140226 1
0.8%
20140925 1
0.8%
ValueCountFrequency (%)
20211113 1
0.8%
20210121 1
0.8%
20200626 1
0.8%
20200429 1
0.8%
20200219 1
0.8%
20191028 1
0.8%
20190822 1
0.8%
20190131 1
0.8%
20181119 1
0.8%
20180827 1
0.8%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)60.9%
Missing97
Missing (%)80.8%
Infinite0
Infinite (%)0.0%
Mean51.608696
Minimum0
Maximum262
Zeros9
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-05-11T15:39:19.873677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median26
Q372.5
95-th percentile221.8
Maximum262
Range262
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation72.186463
Coefficient of variation (CV)1.3987267
Kurtosis3.4916279
Mean51.608696
Median Absolute Deviation (MAD)26
Skewness1.9219906
Sum1187
Variance5210.8854
MonotonicityNot monotonic
2024-05-11T15:39:20.506420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 9
 
7.5%
100 2
 
1.7%
262 1
 
0.8%
234 1
 
0.8%
26 1
 
0.8%
112 1
 
0.8%
46 1
 
0.8%
84 1
 
0.8%
24 1
 
0.8%
61 1
 
0.8%
Other values (4) 4
 
3.3%
(Missing) 97
80.8%
ValueCountFrequency (%)
0 9
7.5%
15 1
 
0.8%
24 1
 
0.8%
26 1
 
0.8%
31 1
 
0.8%
32 1
 
0.8%
46 1
 
0.8%
60 1
 
0.8%
61 1
 
0.8%
84 1
 
0.8%
ValueCountFrequency (%)
262 1
0.8%
234 1
0.8%
112 1
0.8%
100 2
1.7%
84 1
0.8%
61 1
0.8%
60 1
0.8%
46 1
0.8%
32 1
0.8%
31 1
0.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03050000CDFI22600219940000011994-10-12<NA>3폐업3폐업2009-04-10<NA><NA><NA>926-9054<NA>130-823서울특별시 동대문구 용두동 233-19서울특별시 동대문구 왕산로9길 20 (용두동)<NA>태경조이2023-03-21 14:42:46U2022-12-02 22:03:00.0<NA>202396.724538452859.954606<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13050000CDFI22600219960000011996-02-23<NA>3폐업3폐업2023-06-02<NA><NA><NA>2247-5906<NA>130-846서울특별시 동대문구 장안동 464-8서울특별시 동대문구 천호대로 425 (장안동)2645(주)월드레스포여행사2023-06-02 15:31:45U2022-12-06 00:04:00.0<NA>205790.19945451038.454241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23050000CDFI226002199600000319960314<NA>3폐업3폐업20080305<NA><NA><NA>277-0171<NA>130812서울특별시 동대문구 신설동 102-37번지서울특별시 동대문구 왕산로2길 32 (신설동)<NA>알라스카관광공사지사2008-03-05 13:20:33I2018-08-31 23:59:59.0<NA>202215.070568452524.166969국내외여행업관광사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33050000CDFI226002199700000119970226<NA>3폐업3폐업20000315<NA><NA><NA>741-4163<NA>130817서울특별시 동대문구 용두동 23-7번지서울특별시 동대문구 왕산로 140 (용두동)<NA>(주)징검다리여행사(국외)2003-04-18 15:38:35I2018-08-31 23:59:59.0<NA>203376.17869452862.182347국내외여행업관광사업<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
43050000CDFI226002199700000219970416<NA>3폐업3폐업20090624<NA><NA><NA>967-2929<NA>130867서울특별시 동대문구 청량리동 281번지서울특별시 동대문구 홍릉로 8 (청량리동)<NA>GUAM한마음투어지사2009-07-07 14:35:26I2018-08-31 23:59:59.0<NA>203922.763128453192.813687국내외여행업관광사업<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
53050000CDFI226002199700000319970708<NA>3폐업3폐업19990210<NA><NA><NA>2254-3765<NA>130812서울특별시 동대문구 신설동 103-6번지서울특별시 동대문구 천호대로 14 (신설동)<NA>(주)차세대여행사2003-04-18 15:38:35I2018-08-31 23:59:59.0<NA>202123.025511452472.988294국내외여행업관광사업<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
63050000CDFI226002199800000119980122<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>557-0078<NA>130845서울특별시 동대문구 장안동 433-8번지서울특별시 동대문구 장한로2길 7 (장안동)<NA>(주)세계를 나의 품에 여행사2003-04-18 15:38:35I2018-08-31 23:59:59.0<NA>205746.038399451118.479199국내외여행업관광사업<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
73050000CDFI226002199800000519981102<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>522-6678<NA>130812서울특별시 동대문구 신설동 103-6번지 아세아빌딩2층서울특별시 동대문구 천호대로 14 (신설동,아세아빌딩2층)<NA>아시아드림투어(주)2003-04-18 15:38:35I2018-08-31 23:59:59.0<NA>202123.025511452472.988294국내외여행업관광사업<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
83050000CDFI226002200100000120010122<NA>3폐업3폐업20050628<NA><NA><NA>2233-3888<NA>130814서울특별시 동대문구 신설동 114-26번지 남양빌딩 302호서울특별시 동대문구 난계로28길 8 (신설동,남양빌딩 302호)<NA>(주)삼성항공여행2007-06-28 12:00:08I2018-08-31 23:59:59.0<NA>202033.225489452271.363467국내외여행업관광사업공업지역<NA>기타<NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93050000CDFI226002200100000220010417200212274취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA>964-9354<NA>130842서울특별시 동대문구 장안동 373-6번지 황금오피스텔 403호서울특별시 동대문구 장한로21길 11-11 (장안동,황금오피스텔 403호)<NA>(주)그린피아항공2010-11-25 10:48:33I2018-08-31 23:59:59.0<NA>206039.648372451902.608513국내외여행업관광사업<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
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
1103050000CDFI22600220220000072021-06-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 33-1 홈플러스 동대문점서울특별시 동대문구 천호대로 133, 홈플러스 동대문점 B1층 (용두동)2565가람티앤씨(T&C)2023-02-27 09:56:14U2022-12-03 00:01:00.0<NA>203356.957363452469.300221<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1113050000CDFI22600220220000082017-07-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 597-6 410호서울특별시 동대문구 왕산로 248, 410호 (전농동)2554시너지 투어2023-07-10 13:44:34U2022-12-06 23:03:00.0<NA>204286.367631453421.056688<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1123050000CDFI22600220230000012022-05-06<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 11-1 청량리역 해링턴플레이스서울특별시 동대문구 고산자로34길 70, 청량리역 해링턴플레이스 A동 415호 (용두동)2560하나인터내셔널 주식회사2024-04-25 12:23:57U2023-12-03 22:07:00.0<NA>203658.734006452878.997692<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1133050000CDFI22600220230000022023-04-27<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 청량리동 235-6서울특별시 동대문구 왕산로 239, 힐스테이트 청량리역 101동 718호 (청량리동)2489서던퍼시픽투어2023-06-02 15:17:51U2022-12-06 00:04:00.0<NA>204190.108783453415.795068<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1143050000CDFI22600220230000032011-03-28<NA>5제외/삭제/전출15전출2024-04-15<NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 787 동의보감타워서울특별시 동대문구 왕산로 128, 동의보감타워 1227호 (용두동)2566(주)트렌유럽2024-04-15 17:47:17U2023-12-03 23:07:00.0<NA>203258.377206452834.064125<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1153050000CDFI22600220230000042023-02-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 용두동 797 청량리역 해링턴플레이스 528호서울특별시 동대문구 고산자로34길 70, 청량리역 해링턴플레이스 528호 (용두동)2560고투어로 주식회사2024-03-13 15:08:00U2023-12-02 23:06:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1163050000CDFI22600220230000052023-08-11<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2212-8882<NA><NA>서울특별시 동대문구 전농동 26-13 3층 423호서울특별시 동대문구 전농로 124, 3층 423호 (전농동)2531티제이트래블2023-08-17 09:59:38U2022-12-07 23:09:00.0<NA>205045.11379452623.143799<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1173050000CDFI22600220230000062023-11-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 전농동 620-69 1418호서울특별시 동대문구 왕산로 200, 1418호 (전농동)2559주식회사 아람투어2023-11-15 16:41:18U2022-10-31 23:07:00.0<NA>203996.013918453058.665829<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1183050000CDFI22600220240000012024-03-05<NA>1영업/정상13영업중<NA><NA><NA><NA>02-778-5100<NA><NA>서울특별시 동대문구 답십리동 488-46 4층 13호서울특별시 동대문구 전농로 24, 4층 13호 (답십리동)2621트래블 이음2024-03-05 19:04:09I2023-12-03 00:07:00.0<NA>204960.697867451636.873332<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1193050000CDFI22600220240000022023-07-26<NA>1영업/정상13영업중<NA><NA><NA><NA>02-953-1848<NA><NA>서울특별시 동대문구 전농동 620-69 1022호서울특별시 동대문구 왕산로 200, 1022호 (전농동)2559비와이트래블2024-03-19 16:46:01I2023-12-02 22:01:00.0<NA>203996.013918453058.665829<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>