Overview

Dataset statistics

Number of variables60
Number of observations72
Missing cells1736
Missing cells (%)40.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.6 KiB
Average record size in memory520.8 B

Variable types

Categorical23
Text8
DateTime4
Unsupported15
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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-17566/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (89.4%)Imbalance
휴업종료일자 is highly imbalanced (89.4%)Imbalance
주변환경명 is highly imbalanced (70.0%)Imbalance
건물용도명 is highly imbalanced (50.6%)Imbalance
지하층수 is highly imbalanced (80.4%)Imbalance
객실수 is highly imbalanced (89.4%)Imbalance
건축연면적 is highly imbalanced (89.4%)Imbalance
선박총톤수 is highly imbalanced (89.4%)Imbalance
선박척수 is highly imbalanced (89.4%)Imbalance
무대면적 is highly imbalanced (89.4%)Imbalance
좌석수 is highly imbalanced (89.4%)Imbalance
회의실별동시수용인원 is highly imbalanced (89.4%)Imbalance
놀이시설수 is highly imbalanced (89.4%)Imbalance
인허가취소일자 has 72 (100.0%) missing valuesMissing
폐업일자 has 33 (45.8%) missing valuesMissing
재개업일자 has 72 (100.0%) missing valuesMissing
전화번호 has 36 (50.0%) missing valuesMissing
소재지면적 has 72 (100.0%) missing valuesMissing
도로명주소 has 3 (4.2%) missing valuesMissing
도로명우편번호 has 19 (26.4%) missing valuesMissing
업태구분명 has 72 (100.0%) missing valuesMissing
좌표정보(X) has 2 (2.8%) missing valuesMissing
좌표정보(Y) has 2 (2.8%) missing valuesMissing
지역구분명 has 68 (94.4%) missing valuesMissing
총층수 has 66 (91.7%) missing valuesMissing
제작취급품목내용 has 72 (100.0%) missing valuesMissing
지상층수 has 63 (87.5%) missing valuesMissing
영문상호명 has 70 (97.2%) missing valuesMissing
영문상호주소 has 70 (97.2%) missing valuesMissing
선박제원 has 72 (100.0%) missing valuesMissing
기념품종류 has 72 (100.0%) missing valuesMissing
시설면적 has 51 (70.8%) missing valuesMissing
놀이기구수내역 has 72 (100.0%) missing valuesMissing
방송시설유무 has 72 (100.0%) missing valuesMissing
발전시설유무 has 72 (100.0%) missing valuesMissing
의무실유무 has 72 (100.0%) missing valuesMissing
안내소유무 has 72 (100.0%) missing valuesMissing
기획여행보험시작일자 has 72 (100.0%) missing valuesMissing
기획여행보험종료일자 has 72 (100.0%) missing valuesMissing
자본금 has 36 (50.0%) missing valuesMissing
보험시작일자 has 43 (59.7%) missing valuesMissing
보험종료일자 has 43 (59.7%) missing valuesMissing
부대시설내역 has 72 (100.0%) missing valuesMissing
시설규모 has 51 (70.8%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
사업장명 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
제작취급품목내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선박제원 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기념품종류 is an unsupported type, check if it needs cleaning or further analysisUnsupported
놀이기구수내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방송시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
발전시설유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
의무실유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안내소유무 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
기획여행보험종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설내역 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총층수 has 1 (1.4%) zerosZeros
지상층수 has 1 (1.4%) zerosZeros
시설면적 has 7 (9.7%) zerosZeros
자본금 has 1 (1.4%) zerosZeros
시설규모 has 7 (9.7%) zerosZeros

Reproduction

Analysis started2024-05-11 08:04:58.515259
Analysis finished2024-05-11 08:04:59.931532
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
3140000
72 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3140000 72
100.0%

Length

2024-05-11T08:05:00.079498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:00.285124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 72
100.0%

관리번호
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-05-11T08:05:00.755949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1440
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

Unique72 ?
Unique (%)100.0%

Sample

1st rowCDFI2260011993000001
2nd rowCDFI2260011996000001
3rd rowCDFI2260011998000001
4th rowCDFI2260011998000002
5th rowCDFI2260011998000004
ValueCountFrequency (%)
cdfi2260011993000001 1
 
1.4%
cdfi2260011996000001 1
 
1.4%
cdfi2260012015000001 1
 
1.4%
cdfi2260012014000005 1
 
1.4%
cdfi2260012014000004 1
 
1.4%
cdfi2260012014000003 1
 
1.4%
cdfi2260012014000002 1
 
1.4%
cdfi2260012014000001 1
 
1.4%
cdfi2260012015000002 1
 
1.4%
cdfi2260012013000007 1
 
1.4%
Other values (62) 62
86.1%
2024-05-11T08:05:01.642277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 606
42.1%
2 231
 
16.0%
1 134
 
9.3%
6 81
 
5.6%
C 72
 
5.0%
D 72
 
5.0%
F 72
 
5.0%
I 72
 
5.0%
9 23
 
1.6%
4 21
 
1.5%
Other values (4) 56
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1152
80.0%
Uppercase Letter 288
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 606
52.6%
2 231
 
20.1%
1 134
 
11.6%
6 81
 
7.0%
9 23
 
2.0%
4 21
 
1.8%
5 21
 
1.8%
7 14
 
1.2%
3 13
 
1.1%
8 8
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C 72
25.0%
D 72
25.0%
F 72
25.0%
I 72
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1152
80.0%
Latin 288
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 606
52.6%
2 231
 
20.1%
1 134
 
11.6%
6 81
 
7.0%
9 23
 
2.0%
4 21
 
1.8%
5 21
 
1.8%
7 14
 
1.2%
3 13
 
1.1%
8 8
 
0.7%
Latin
ValueCountFrequency (%)
C 72
25.0%
D 72
25.0%
F 72
25.0%
I 72
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 606
42.1%
2 231
 
16.0%
1 134
 
9.3%
6 81
 
5.6%
C 72
 
5.0%
D 72
 
5.0%
F 72
 
5.0%
I 72
 
5.0%
9 23
 
1.6%
4 21
 
1.5%
Other values (4) 56
 
3.9%

인허가일자
Date

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum1993-05-15 00:00:00
Maximum2021-04-15 00:00:00
2024-05-11T08:05:02.074797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:05:02.522912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

영업상태코드
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
3
39 
1
30 
4
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
3 39
54.2%
1 30
41.7%
4 2
 
2.8%
2 1
 
1.4%

Length

2024-05-11T08:05:02.857043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:03.145289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 39
54.2%
1 30
41.7%
4 2
 
2.8%
2 1
 
1.4%

영업상태명
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
폐업
39 
영업/정상
30 
취소/말소/만료/정지/중지
 
2
휴업
 
1

Length

Max length14
Median length2
Mean length3.5833333
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 39
54.2%
영업/정상 30
41.7%
취소/말소/만료/정지/중지 2
 
2.8%
휴업 1
 
1.4%

Length

2024-05-11T08:05:03.527981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:03.869242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 39
54.2%
영업/정상 30
41.7%
취소/말소/만료/정지/중지 2
 
2.8%
휴업 1
 
1.4%

상세영업상태코드
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
3
39 
13
30 
31
 
2
2
 
1

Length

Max length2
Median length1
Mean length1.4444444
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
3 39
54.2%
13 30
41.7%
31 2
 
2.8%
2 1
 
1.4%

Length

2024-05-11T08:05:04.239481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:04.575366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 39
54.2%
13 30
41.7%
31 2
 
2.8%
2 1
 
1.4%

상세영업상태명
Categorical

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
폐업
39 
영업중
30 
등록취소
 
2
휴업
 
1

Length

Max length4
Median length2
Mean length2.4722222
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 39
54.2%
영업중 30
41.7%
등록취소 2
 
2.8%
휴업 1
 
1.4%

Length

2024-05-11T08:05:04.891042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:05.112297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 39
54.2%
영업중 30
41.7%
등록취소 2
 
2.8%
휴업 1
 
1.4%

폐업일자
Date

MISSING 

Distinct34
Distinct (%)87.2%
Missing33
Missing (%)45.8%
Memory size708.0 B
Minimum1998-03-26 00:00:00
Maximum2023-05-31 00:00:00
2024-05-11T08:05:05.321825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:05:05.621900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
20050803
 
1

Length

Max length8
Median length4
Mean length4.0555556
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
20050803 1
 
1.4%

Length

2024-05-11T08:05:05.961192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:06.192213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
20050803 1
 
1.4%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
20060630
 
1

Length

Max length8
Median length4
Mean length4.0555556
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
20060630 1
 
1.4%

Length

2024-05-11T08:05:06.425826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:06.706637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
20060630 1
 
1.4%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

전화번호
Text

MISSING 

Distinct34
Distinct (%)94.4%
Missing36
Missing (%)50.0%
Memory size708.0 B
2024-05-11T08:05:07.082418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length10.583333
Min length8

Characters and Unicode

Total characters381
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)91.7%

Sample

1st row02-2652-3361
2nd row2608-7788
3rd row02-2168-3001
4th row02-2168-3453
5th row02-2655-2133
ValueCountFrequency (%)
15883340 3
 
8.3%
02-2652-3361 1
 
2.8%
02-2637-3095 1
 
2.8%
02-364-1212 1
 
2.8%
07046815290 1
 
2.8%
02-599-0779 1
 
2.8%
02-2652-1235 1
 
2.8%
2616-4321 1
 
2.8%
02-780-9161 1
 
2.8%
2608-7788 1
 
2.8%
Other values (24) 24
66.7%
2024-05-11T08:05:07.874137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 59
15.5%
0 53
13.9%
- 49
12.9%
6 44
11.5%
1 34
8.9%
3 32
8.4%
5 27
7.1%
8 27
7.1%
4 22
 
5.8%
7 20
 
5.2%
Other values (2) 14
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 331
86.9%
Dash Punctuation 49
 
12.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 59
17.8%
0 53
16.0%
6 44
13.3%
1 34
10.3%
3 32
9.7%
5 27
8.2%
8 27
8.2%
4 22
 
6.6%
7 20
 
6.0%
9 13
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 381
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 59
15.5%
0 53
13.9%
- 49
12.9%
6 44
11.5%
1 34
8.9%
3 32
8.4%
5 27
7.1%
8 27
7.1%
4 22
 
5.8%
7 20
 
5.2%
Other values (2) 14
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 59
15.5%
0 53
13.9%
- 49
12.9%
6 44
11.5%
1 34
8.9%
3 32
8.4%
5 27
7.1%
8 27
7.1%
4 22
 
5.8%
7 20
 
5.2%
Other values (2) 14
 
3.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

소재지우편번호
Categorical

Distinct23
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
26 
158050
9 
158857
5 
158811
4 
158070
4 
Other values (18)
24 

Length

Max length7
Median length6
Mean length5.3055556
Min length4

Unique

Unique13 ?
Unique (%)18.1%

Sample

1st row158811
2nd row158050
3rd row158846
4th row158050
5th row158856

Common Values

ValueCountFrequency (%)
<NA> 26
36.1%
158050 9
 
12.5%
158857 5
 
6.9%
158811 4
 
5.6%
158070 4
 
5.6%
158846 3
 
4.2%
158856 2
 
2.8%
158724 2
 
2.8%
158806 2
 
2.8%
158808 2
 
2.8%
Other values (13) 13
18.1%

Length

2024-05-11T08:05:08.192746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 26
36.1%
158050 9
 
12.5%
158857 5
 
6.9%
158811 4
 
5.6%
158070 4
 
5.6%
158846 3
 
4.2%
158856 2
 
2.8%
158724 2
 
2.8%
158806 2
 
2.8%
158808 2
 
2.8%
Other values (13) 13
18.1%

지번주소
Text

Distinct65
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-05-11T08:05:08.724460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length26.75
Min length15

Characters and Unicode

Total characters1926
Distinct characters90
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)83.3%

Sample

1st row서울특별시 양천구 목동 606-15번지 한강빌딩 1층
2nd row서울특별시 양천구 목동 909-6번지 우방빌딩 403
3rd row서울특별시 양천구 신월동 961-6번지 3층
4th row서울특별시 양천구 목동 917-1번지
5th row서울특별시 양천구 신정동 878-19번지 3층
ValueCountFrequency (%)
서울특별시 71
19.0%
양천구 71
19.0%
목동 34
 
9.1%
신정동 25
 
6.7%
신월동 12
 
3.2%
2층 9
 
2.4%
917-9 7
 
1.9%
현대41타워 7
 
1.9%
1층 4
 
1.1%
302호 3
 
0.8%
Other values (111) 130
34.9%
2024-05-11T08:05:09.589577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
342
 
17.8%
1 99
 
5.1%
동 78
 
4.0%
구 73
 
3.8%
양 73
 
3.8%
서 73
 
3.8%
시 72
 
3.7%
천 72
 
3.7%
별 71
 
3.7%
특 71
 
3.7%
Other values (80) 902
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1079
56.0%
Decimal Number 436
22.6%
Space Separator 342
 
17.8%
Dash Punctuation 67
 
3.5%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 78
 
7.2%
구 73
 
6.8%
양 73
 
6.8%
서 73
 
6.8%
시 72
 
6.7%
천 72
 
6.7%
별 71
 
6.6%
특 71
 
6.6%
울 71
 
6.6%
지 42
 
3.9%
Other values (66) 383
35.5%
Decimal Number
ValueCountFrequency (%)
1 99
22.7%
9 60
13.8%
2 55
12.6%
0 40
9.2%
7 36
 
8.3%
4 36
 
8.3%
6 31
 
7.1%
3 30
 
6.9%
5 27
 
6.2%
8 22
 
5.0%
Space Separator
ValueCountFrequency (%)
342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1079
56.0%
Common 847
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 78
 
7.2%
구 73
 
6.8%
양 73
 
6.8%
서 73
 
6.8%
시 72
 
6.7%
천 72
 
6.7%
별 71
 
6.6%
특 71
 
6.6%
울 71
 
6.6%
지 42
 
3.9%
Other values (66) 383
35.5%
Common
ValueCountFrequency (%)
342
40.4%
1 99
 
11.7%
- 67
 
7.9%
9 60
 
7.1%
2 55
 
6.5%
0 40
 
4.7%
7 36
 
4.3%
4 36
 
4.3%
6 31
 
3.7%
3 30
 
3.5%
Other values (4) 51
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1079
56.0%
ASCII 847
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
342
40.4%
1 99
 
11.7%
- 67
 
7.9%
9 60
 
7.1%
2 55
 
6.5%
0 40
 
4.7%
7 36
 
4.3%
4 36
 
4.3%
6 31
 
3.7%
3 30
 
3.5%
Other values (4) 51
 
6.0%
Hangul
ValueCountFrequency (%)
동 78
 
7.2%
구 73
 
6.8%
양 73
 
6.8%
서 73
 
6.8%
시 72
 
6.7%
천 72
 
6.7%
별 71
 
6.6%
특 71
 
6.6%
울 71
 
6.6%
지 42
 
3.9%
Other values (66) 383
35.5%

도로명주소
Text

MISSING 

Distinct66
Distinct (%)95.7%
Missing3
Missing (%)4.2%
Memory size708.0 B
2024-05-11T08:05:10.146097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length38
Mean length32.449275
Min length23

Characters and Unicode

Total characters2239
Distinct characters112
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

Unique63 ?
Unique (%)91.3%

Sample

1st row서울특별시 양천구 등촌로 232 (목동,한강빌딩 1층)
2nd row서울특별시 양천구 목동동로 431 (목동,우방빌딩 403)
3rd row서울특별시 양천구 남부순환로66길 23 (신월동,3층)
4th row서울특별시 양천구 목동서로 159-1 (목동)
5th row서울특별시 양천구 신정중앙로 51 (신정동,3층)
ValueCountFrequency (%)
서울특별시 69
 
16.4%
양천구 69
 
16.4%
목동 18
 
4.3%
목동동로 18
 
4.3%
신정동 16
 
3.8%
293 10
 
2.4%
신월동 8
 
1.9%
1층 7
 
1.7%
목동서로 6
 
1.4%
중앙로 6
 
1.4%
Other values (141) 194
46.1%
2024-05-11T08:05:11.263631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
372
 
16.6%
동 122
 
5.4%
서 77
 
3.4%
2 77
 
3.4%
, 74
 
3.3%
양 72
 
3.2%
1 71
 
3.2%
) 70
 
3.1%
( 70
 
3.1%
로 70
 
3.1%
Other values (102) 1164
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1272
56.8%
Space Separator 372
 
16.6%
Decimal Number 371
 
16.6%
Other Punctuation 74
 
3.3%
Close Punctuation 70
 
3.1%
Open Punctuation 70
 
3.1%
Dash Punctuation 9
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 122
 
9.6%
서 77
 
6.1%
양 72
 
5.7%
로 70
 
5.5%
목 70
 
5.5%
구 70
 
5.5%
천 70
 
5.5%
시 70
 
5.5%
울 69
 
5.4%
별 69
 
5.4%
Other values (86) 513
40.3%
Decimal Number
ValueCountFrequency (%)
2 77
20.8%
1 71
19.1%
3 52
14.0%
0 42
11.3%
9 28
 
7.5%
4 27
 
7.3%
5 25
 
6.7%
8 19
 
5.1%
7 15
 
4.0%
6 15
 
4.0%
Space Separator
ValueCountFrequency (%)
372
100.0%
Other Punctuation
ValueCountFrequency (%)
, 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1272
56.8%
Common 966
43.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 122
 
9.6%
서 77
 
6.1%
양 72
 
5.7%
로 70
 
5.5%
목 70
 
5.5%
구 70
 
5.5%
천 70
 
5.5%
시 70
 
5.5%
울 69
 
5.4%
별 69
 
5.4%
Other values (86) 513
40.3%
Common
ValueCountFrequency (%)
372
38.5%
2 77
 
8.0%
, 74
 
7.7%
1 71
 
7.3%
) 70
 
7.2%
( 70
 
7.2%
3 52
 
5.4%
0 42
 
4.3%
9 28
 
2.9%
4 27
 
2.8%
Other values (5) 83
 
8.6%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1272
56.8%
ASCII 967
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
372
38.5%
2 77
 
8.0%
, 74
 
7.7%
1 71
 
7.3%
) 70
 
7.2%
( 70
 
7.2%
3 52
 
5.4%
0 42
 
4.3%
9 28
 
2.9%
4 27
 
2.8%
Other values (6) 84
 
8.7%
Hangul
ValueCountFrequency (%)
동 122
 
9.6%
서 77
 
6.1%
양 72
 
5.7%
로 70
 
5.5%
목 70
 
5.5%
구 70
 
5.5%
천 70
 
5.5%
시 70
 
5.5%
울 69
 
5.4%
별 69
 
5.4%
Other values (86) 513
40.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)64.2%
Missing19
Missing (%)26.4%
Infinite0
Infinite (%)0.0%
Mean16537.906
Minimum7903
Maximum158852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:11.648744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7903
5-th percentile7930.2
Q17968
median7997
Q38039
95-th percentile68379.4
Maximum158852
Range150949
Interquartile range (IQR)71

Descriptive statistics

Standard deviation35185.899
Coefficient of variation (CV)2.127591
Kurtosis14.136597
Mean16537.906
Median Absolute Deviation (MAD)37
Skewness3.9502111
Sum876509
Variance1.2380475 × 109
MonotonicityNot monotonic
2024-05-11T08:05:12.068191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
7997 10
13.9%
8026 3
 
4.2%
8077 3
 
4.2%
7995 2
 
2.8%
8095 2
 
2.8%
7946 2
 
2.8%
7937 2
 
2.8%
7945 2
 
2.8%
8039 2
 
2.8%
8087 1
 
1.4%
Other values (24) 24
33.3%
(Missing) 19
26.4%
ValueCountFrequency (%)
7903 1
1.4%
7909 1
1.4%
7920 1
1.4%
7937 2
2.8%
7938 1
1.4%
7944 1
1.4%
7945 2
2.8%
7946 2
2.8%
7962 1
1.4%
7965 1
1.4%
ValueCountFrequency (%)
158852 1
 
1.4%
158808 1
 
1.4%
158806 1
 
1.4%
8095 2
2.8%
8087 1
 
1.4%
8077 3
4.2%
8065 1
 
1.4%
8062 1
 
1.4%
8058 1
 
1.4%
8044 1
 
1.4%

사업장명
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2024-05-11T08:05:12.542593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length11.5
Mean length8.6111111
Min length3

Characters and Unicode

Total characters620
Distinct characters168
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

Unique72 ?
Unique (%)100.0%

Sample

1st row(주)예일항공여행사
2nd row(주)파파항공여행사
3rd row(주)다인여행사
4th row주)승우여행사
5th row태성항공여행사
ValueCountFrequency (%)
주식회사 12
 
13.3%
케이시스코 1
 
1.1%
주)버스조인(bus 1
 
1.1%
개미여행사 1
 
1.1%
주)해누리관광여행사 1
 
1.1%
우리관광 1
 
1.1%
주)여행즐겨찾기 1
 
1.1%
주)최고여행사 1
 
1.1%
주)대신항공여행사 1
 
1.1%
주)예일항공여행사 1
 
1.1%
Other values (69) 69
76.7%
2024-05-11T08:05:13.376240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 60
 
9.7%
) 46
 
7.4%
( 44
 
7.1%
사 33
 
5.3%
투 25
 
4.0%
행 23
 
3.7%
어 22
 
3.5%
여 22
 
3.5%
18
 
2.9%
스 18
 
2.9%
Other values (158) 309
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494
79.7%
Close Punctuation 46
 
7.4%
Open Punctuation 44
 
7.1%
Space Separator 18
 
2.9%
Uppercase Letter 13
 
2.1%
Other Punctuation 3
 
0.5%
Lowercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 60
 
12.1%
사 33
 
6.7%
투 25
 
5.1%
행 23
 
4.7%
어 22
 
4.5%
여 22
 
4.5%
스 18
 
3.6%
이 14
 
2.8%
식 12
 
2.4%
회 12
 
2.4%
Other values (141) 253
51.2%
Uppercase Letter
ValueCountFrequency (%)
O 2
15.4%
B 2
15.4%
S 2
15.4%
U 1
7.7%
J 1
7.7%
I 1
7.7%
N 1
7.7%
L 1
7.7%
C 1
7.7%
T 1
7.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
d 1
50.0%
t 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 494
79.7%
Common 111
 
17.9%
Latin 15
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 60
 
12.1%
사 33
 
6.7%
투 25
 
5.1%
행 23
 
4.7%
어 22
 
4.5%
여 22
 
4.5%
스 18
 
3.6%
이 14
 
2.8%
식 12
 
2.4%
회 12
 
2.4%
Other values (141) 253
51.2%
Latin
ValueCountFrequency (%)
O 2
13.3%
B 2
13.3%
S 2
13.3%
U 1
6.7%
J 1
6.7%
I 1
6.7%
N 1
6.7%
d 1
6.7%
t 1
6.7%
L 1
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
) 46
41.4%
( 44
39.6%
18
 
16.2%
. 2
 
1.8%
, 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 494
79.7%
ASCII 126
 
20.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 60
 
12.1%
사 33
 
6.7%
투 25
 
5.1%
행 23
 
4.7%
어 22
 
4.5%
여 22
 
4.5%
스 18
 
3.6%
이 14
 
2.8%
식 12
 
2.4%
회 12
 
2.4%
Other values (141) 253
51.2%
ASCII
ValueCountFrequency (%)
) 46
36.5%
( 44
34.9%
18
 
14.3%
. 2
 
1.6%
O 2
 
1.6%
B 2
 
1.6%
S 2
 
1.6%
U 1
 
0.8%
J 1
 
0.8%
I 1
 
0.8%
Other values (7) 7
 
5.6%

최종수정일자
Date

Distinct67
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum2002-10-22 17:51:16
Maximum2024-03-08 16:23:11
2024-05-11T08:05:13.752300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:05:14.016519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
U
44 
I
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 44
61.1%
I 28
38.9%

Length

2024-05-11T08:05:14.271148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:14.461432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 44
61.1%
i 28
38.9%

데이터갱신일자
Date

Distinct28
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size708.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 23:00:00
2024-05-11T08:05:14.649689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:05:15.024308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)67.1%
Missing2
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean187707.73
Minimum184242.73
Maximum189709.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:15.329250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184242.73
5-th percentile185120.1
Q1186982.39
median187995.29
Q3188880.93
95-th percentile188953.07
Maximum189709.8
Range5467.0735
Interquartile range (IQR)1898.5483

Descriptive statistics

Standard deviation1333.6722
Coefficient of variation (CV)0.0071050471
Kurtosis-0.029201101
Mean187707.73
Median Absolute Deviation (MAD)948.43389
Skewness-0.97005485
Sum13139541
Variance1778681.7
MonotonicityNot monotonic
2024-05-11T08:05:15.586231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
188953.066831076 10
 
13.9%
186852.153851552 3
 
4.2%
187700.179587787 3
 
4.2%
187934.622082601 2
 
2.8%
188884.075622342 2
 
2.8%
187007.685 2
 
2.8%
188943.727308753 2
 
2.8%
185313.848748186 2
 
2.8%
187823.500716444 2
 
2.8%
188584.345447275 2
 
2.8%
Other values (37) 40
55.6%
ValueCountFrequency (%)
184242.730019702 1
1.4%
184643.617436929 1
1.4%
185023.275606938 1
1.4%
185039.127935307 1
1.4%
185219.063117975 1
1.4%
185221.95790954 1
1.4%
185248.796504661 1
1.4%
185313.848748186 2
2.8%
185566.058732924 1
1.4%
185809.765126281 1
1.4%
ValueCountFrequency (%)
189709.803505321 1
 
1.4%
189151.208015925 1
 
1.4%
188977.171050288 1
 
1.4%
188953.066831076 10
13.9%
188943.727308753 2
 
2.8%
188885.699738662 1
 
1.4%
188884.075622342 2
 
2.8%
188871.512837973 2
 
2.8%
188774.341755793 1
 
1.4%
188729.190478822 1
 
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)67.1%
Missing2
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean447416.45
Minimum446070.26
Maximum449789.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:15.892684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446070.26
5-th percentile446110.15
Q1446648.17
median447261.13
Q3447855.47
95-th percentile449683.22
Maximum449789.61
Range3719.3509
Interquartile range (IQR)1207.2985

Descriptive statistics

Standard deviation1045.4268
Coefficient of variation (CV)0.0023365855
Kurtosis0.13860423
Mean447416.45
Median Absolute Deviation (MAD)636.92247
Skewness0.94766425
Sum31319152
Variance1092917.2
MonotonicityNot monotonic
2024-05-11T08:05:16.264365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
447333.569187997 10
 
13.9%
446714.974104065 3
 
4.2%
447132.165539967 3
 
4.2%
449785.227427003 2
 
2.8%
447186.888604306 2
 
2.8%
446135.935 2
 
2.8%
449380.074012936 2
 
2.8%
446617.177229847 2
 
2.8%
447457.457884414 2
 
2.8%
447255.070457495 2
 
2.8%
Other values (37) 40
55.6%
ValueCountFrequency (%)
446070.262510721 1
1.4%
446090.979359781 1
1.4%
446099.600366308 2
2.8%
446123.034540646 1
1.4%
446135.935 2
2.8%
446149.197185122 1
1.4%
446222.634037686 1
1.4%
446382.826748194 1
1.4%
446386.541360966 1
1.4%
446509.999701528 1
1.4%
ValueCountFrequency (%)
449789.613381329 1
1.4%
449785.227427003 2
2.8%
449683.219205227 2
2.8%
449556.4108025 1
1.4%
449380.074012936 2
2.8%
449193.458358754 1
1.4%
448660.569381106 1
1.4%
448537.930084122 1
1.4%
448328.28893557 1
1.4%
448276.441944257 1
1.4%

문화체육업종명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
국내여행업
55 
<NA>
17 

Length

Max length5
Median length5
Mean length4.7638889
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내여행업 55
76.4%
<NA> 17
 
23.6%

Length

2024-05-11T08:05:16.524855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:16.721888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내여행업 55
76.4%
na 17
 
23.6%

문화사업자구분명
Categorical

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
38 
관광사업
34 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 38
52.8%
관광사업 34
47.2%

Length

2024-05-11T08:05:17.057471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:17.297244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 38
52.8%
관광사업 34
47.2%

지역구분명
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing68
Missing (%)94.4%
Memory size708.0 B
2024-05-11T08:05:17.468976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.5
Min length4

Characters and Unicode

Total characters18
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row주거지역
2nd row상업지역
3rd row주거지역
4th row근린상업지역
ValueCountFrequency (%)
주거지역 2
50.0%
상업지역 1
25.0%
근린상업지역 1
25.0%
2024-05-11T08:05:18.056111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 4
22.2%
역 4
22.2%
주 2
11.1%
거 2
11.1%
상 2
11.1%
업 2
11.1%
근 1
 
5.6%
린 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4
22.2%
역 4
22.2%
주 2
11.1%
거 2
11.1%
상 2
11.1%
업 2
11.1%
근 1
 
5.6%
린 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4
22.2%
역 4
22.2%
주 2
11.1%
거 2
11.1%
상 2
11.1%
업 2
11.1%
근 1
 
5.6%
린 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 4
22.2%
역 4
22.2%
주 2
11.1%
거 2
11.1%
상 2
11.1%
업 2
11.1%
근 1
 
5.6%
린 1
 
5.6%

총층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)100.0%
Missing66
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean17.5
Minimum0
Maximum46
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:18.472264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q13
median8
Q333.25
95-th percentile44.75
Maximum46
Range46
Interquartile range (IQR)30.25

Descriptive statistics

Standard deviation20.491462
Coefficient of variation (CV)1.1709407
Kurtosis-1.7363693
Mean17.5
Median Absolute Deviation (MAD)7
Skewness0.8751721
Sum105
Variance419.9
MonotonicityNot monotonic
2024-05-11T08:05:18.726026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 1
 
1.4%
41 1
 
1.4%
46 1
 
1.4%
2 1
 
1.4%
10 1
 
1.4%
0 1
 
1.4%
(Missing) 66
91.7%
ValueCountFrequency (%)
0 1
1.4%
2 1
1.4%
6 1
1.4%
10 1
1.4%
41 1
1.4%
46 1
1.4%
ValueCountFrequency (%)
46 1
1.4%
41 1
1.4%
10 1
1.4%
6 1
1.4%
2 1
1.4%
0 1
1.4%

주변환경명
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
65 
주택가주변
 
3
기타
 
3
아파트지역
 
1

Length

Max length5
Median length4
Mean length3.9722222
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 65
90.3%
주택가주변 3
 
4.2%
기타 3
 
4.2%
아파트지역 1
 
1.4%

Length

2024-05-11T08:05:19.123800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:19.478467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
90.3%
주택가주변 3
 
4.2%
기타 3
 
4.2%
아파트지역 1
 
1.4%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

보험기관명
Categorical

Distinct13
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
46 
서울보증보험
5 
서울보증보험(2천만원)
5 
한국관광협회중앙회
 
3
서울보증보험주식회사
 
3
Other values (8)
10 

Length

Max length16
Median length4
Mean length6.0972222
Min length4

Unique

Unique7 ?
Unique (%)9.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
63.9%
서울보증보험 5
 
6.9%
서울보증보험(2천만원) 5
 
6.9%
한국관광협회중앙회 3
 
4.2%
서울보증보험주식회사 3
 
4.2%
한국관광협회 3
 
4.2%
한국관광협회중앙회여행공제회 1
 
1.4%
서울보증보험주식회사(3천만원) 1
 
1.4%
서울보증 1
 
1.4%
서울특별시관광협회(2천만원) 1
 
1.4%
Other values (3) 3
 
4.2%

Length

2024-05-11T08:05:19.838198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 46
63.9%
서울보증보험 5
 
6.9%
서울보증보험(2천만원 5
 
6.9%
한국관광협회중앙회 3
 
4.2%
서울보증보험주식회사 3
 
4.2%
한국관광협회 3
 
4.2%
한국관광협회중앙회여행공제회 1
 
1.4%
서울보증보험주식회사(3천만원 1
 
1.4%
서울보증 1
 
1.4%
서울특별시관광협회(2천만원 1
 
1.4%
Other values (3) 3
 
4.2%

건물용도명
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
58 
근린생활시설
13 
사무실
 
1

Length

Max length6
Median length4
Mean length4.3472222
Min length3

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
80.6%
근린생활시설 13
 
18.1%
사무실 1
 
1.4%

Length

2024-05-11T08:05:20.122644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:20.426053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
80.6%
근린생활시설 13
 
18.1%
사무실 1
 
1.4%

지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)66.7%
Missing63
Missing (%)87.5%
Infinite0
Infinite (%)0.0%
Mean15.333333
Minimum0
Maximum41
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:20.733046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q11
median3
Q341
95-th percentile41
Maximum41
Range41
Interquartile range (IQR)40

Descriptive statistics

Standard deviation19.384272
Coefficient of variation (CV)1.2641917
Kurtosis-1.7270245
Mean15.333333
Median Absolute Deviation (MAD)3
Skewness0.8073769
Sum138
Variance375.75
MonotonicityNot monotonic
2024-05-11T08:05:21.061507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
41 3
 
4.2%
1 2
 
2.8%
8 1
 
1.4%
2 1
 
1.4%
3 1
 
1.4%
0 1
 
1.4%
(Missing) 63
87.5%
ValueCountFrequency (%)
0 1
 
1.4%
1 2
2.8%
2 1
 
1.4%
3 1
 
1.4%
8 1
 
1.4%
41 3
4.2%
ValueCountFrequency (%)
41 3
4.2%
8 1
 
1.4%
3 1
 
1.4%
2 1
 
1.4%
1 2
2.8%
0 1
 
1.4%

지하층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
68 
5
 
2
2
 
1
0
 
1

Length

Max length4
Median length4
Mean length3.8333333
Min length1

Unique

Unique2 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 68
94.4%
5 2
 
2.8%
2 1
 
1.4%
0 1
 
1.4%

Length

2024-05-11T08:05:21.482443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:21.830228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 68
94.4%
5 2
 
2.8%
2 1
 
1.4%
0 1
 
1.4%

객실수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:22.191233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:22.510453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

건축연면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:22.844875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:23.187912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

영문상호명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing70
Missing (%)97.2%
Memory size708.0 B
2024-05-11T08:05:23.473257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length14
Min length13

Characters and Unicode

Total characters28
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowNawago.Co.,Ltd.
2nd rowDRAGONFLYTOUR
ValueCountFrequency (%)
nawago.co.,ltd 1
50.0%
dragonflytour 1
50.0%
2024-05-11T08:05:24.368243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3
 
10.7%
N 2
 
7.1%
R 2
 
7.1%
o 2
 
7.1%
O 2
 
7.1%
L 2
 
7.1%
a 2
 
7.1%
T 1
 
3.6%
Y 1
 
3.6%
F 1
 
3.6%
Other values (10) 10
35.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 16
57.1%
Lowercase Letter 8
28.6%
Other Punctuation 4
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2
12.5%
R 2
12.5%
O 2
12.5%
L 2
12.5%
T 1
6.2%
Y 1
6.2%
F 1
6.2%
G 1
6.2%
A 1
6.2%
D 1
6.2%
Other values (2) 2
12.5%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
a 2
25.0%
d 1
12.5%
t 1
12.5%
g 1
12.5%
w 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
85.7%
Common 4
 
14.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
 
8.3%
R 2
 
8.3%
o 2
 
8.3%
O 2
 
8.3%
L 2
 
8.3%
a 2
 
8.3%
T 1
 
4.2%
Y 1
 
4.2%
F 1
 
4.2%
G 1
 
4.2%
Other values (8) 8
33.3%
Common
ValueCountFrequency (%)
. 3
75.0%
, 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3
 
10.7%
N 2
 
7.1%
R 2
 
7.1%
o 2
 
7.1%
O 2
 
7.1%
L 2
 
7.1%
a 2
 
7.1%
T 1
 
3.6%
Y 1
 
3.6%
F 1
 
3.6%
Other values (10) 10
35.7%

영문상호주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing70
Missing (%)97.2%
Memory size708.0 B
2024-05-11T08:05:24.693365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters48
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDomestic travle business
2nd rowDomestic travel Business
ValueCountFrequency (%)
domestic 2
33.3%
business 2
33.3%
travle 1
16.7%
travel 1
16.7%
2024-05-11T08:05:25.557751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8
16.7%
e 6
12.5%
4
 
8.3%
t 4
 
8.3%
i 4
 
8.3%
a 2
 
4.2%
n 2
 
4.2%
u 2
 
4.2%
l 2
 
4.2%
v 2
 
4.2%
Other values (7) 12
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41
85.4%
Space Separator 4
 
8.3%
Uppercase Letter 3
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 8
19.5%
e 6
14.6%
t 4
9.8%
i 4
9.8%
a 2
 
4.9%
n 2
 
4.9%
u 2
 
4.9%
l 2
 
4.9%
v 2
 
4.9%
r 2
 
4.9%
Other values (4) 7
17.1%
Uppercase Letter
ValueCountFrequency (%)
D 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44
91.7%
Common 4
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 8
18.2%
e 6
13.6%
t 4
 
9.1%
i 4
 
9.1%
a 2
 
4.5%
n 2
 
4.5%
u 2
 
4.5%
l 2
 
4.5%
v 2
 
4.5%
D 2
 
4.5%
Other values (6) 10
22.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 8
16.7%
e 6
12.5%
4
 
8.3%
t 4
 
8.3%
i 4
 
8.3%
a 2
 
4.2%
n 2
 
4.2%
u 2
 
4.2%
l 2
 
4.2%
v 2
 
4.2%
Other values (7) 12
25.0%

선박총톤수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:26.164228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:26.526751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

선박척수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:27.004975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:27.385752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

무대면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:27.873984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:28.526403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

좌석수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:29.316054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:29.730577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

회의실별동시수용인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:30.259650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:31.087021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)71.4%
Missing51
Missing (%)70.8%
Infinite0
Infinite (%)0.0%
Mean44.9
Minimum0
Maximum200
Zeros7
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:31.553686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median38.38
Q374
95-th percentile92
Maximum200
Range200
Interquartile range (IQR)74

Descriptive statistics

Standard deviation49.666707
Coefficient of variation (CV)1.1061627
Kurtosis3.3912997
Mean44.9
Median Absolute Deviation (MAD)38.38
Skewness1.4879401
Sum942.9
Variance2466.7818
MonotonicityNot monotonic
2024-05-11T08:05:32.089858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 7
 
9.7%
79.34 1
 
1.4%
66.0 1
 
1.4%
74.0 1
 
1.4%
80.0 1
 
1.4%
10.0 1
 
1.4%
200.0 1
 
1.4%
53.3 1
 
1.4%
38.38 1
 
1.4%
82.0 1
 
1.4%
Other values (5) 5
 
6.9%
(Missing) 51
70.8%
ValueCountFrequency (%)
0.0 7
9.7%
8.76 1
 
1.4%
10.0 1
 
1.4%
27.72 1
 
1.4%
38.38 1
 
1.4%
53.3 1
 
1.4%
60.0 1
 
1.4%
66.0 1
 
1.4%
71.4 1
 
1.4%
74.0 1
 
1.4%
ValueCountFrequency (%)
200.0 1
1.4%
92.0 1
1.4%
82.0 1
1.4%
80.0 1
1.4%
79.34 1
1.4%
74.0 1
1.4%
71.4 1
1.4%
66.0 1
1.4%
60.0 1
1.4%
53.3 1
1.4%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

놀이시설수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
<NA>
71 
0
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length1

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
98.6%
0 1
 
1.4%

Length

2024-05-11T08:05:32.616241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:05:33.000899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
98.6%
0 1
 
1.4%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)36.1%
Missing36
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean66317276
Minimum0
Maximum2 × 108
Zeros1
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:33.330875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13750000
Q150000000
median50000000
Q360720750
95-th percentile1.625 × 108
Maximum2 × 108
Range2 × 108
Interquartile range (IQR)10720750

Descriptive statistics

Standard deviation48443935
Coefficient of variation (CV)0.73048741
Kurtosis1.8736247
Mean66317276
Median Absolute Deviation (MAD)480500
Skewness1.543445
Sum2.3874219 × 109
Variance2.3468148 × 1015
MonotonicityNot monotonic
2024-05-11T08:05:33.827800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
50000000 18
25.0%
30000000 4
 
5.6%
150000000 3
 
4.2%
200000000 2
 
2.8%
10000000 1
 
1.4%
50961000 1
 
1.4%
100200939 1
 
1.4%
105000000 1
 
1.4%
101260000 1
 
1.4%
90000000 1
 
1.4%
Other values (3) 3
 
4.2%
(Missing) 36
50.0%
ValueCountFrequency (%)
0 1
 
1.4%
10000000 1
 
1.4%
15000000 1
 
1.4%
30000000 4
 
5.6%
45000000 1
 
1.4%
50000000 18
25.0%
50961000 1
 
1.4%
90000000 1
 
1.4%
100200939 1
 
1.4%
101260000 1
 
1.4%
ValueCountFrequency (%)
200000000 2
 
2.8%
150000000 3
 
4.2%
105000000 1
 
1.4%
101260000 1
 
1.4%
100200939 1
 
1.4%
90000000 1
 
1.4%
50961000 1
 
1.4%
50000000 18
25.0%
45000000 1
 
1.4%
30000000 4
 
5.6%

보험시작일자
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing43
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean20129191
Minimum20030124
Maximum20210719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:34.307109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030124
5-th percentile20034278
Q120080310
median20160318
Q320181113
95-th percentile20210401
Maximum20210719
Range180595
Interquartile range (IQR)100803

Descriptive statistics

Standard deviation63896.644
Coefficient of variation (CV)0.0031743275
Kurtosis-1.5888847
Mean20129191
Median Absolute Deviation (MAD)50283
Skewness-0.22939981
Sum5.8374654 × 108
Variance4.0827811 × 109
MonotonicityNot monotonic
2024-05-11T08:05:34.746590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20030323 1
 
1.4%
20191022 1
 
1.4%
20181113 1
 
1.4%
20210719 1
 
1.4%
20170124 1
 
1.4%
20160402 1
 
1.4%
20180806 1
 
1.4%
20180512 1
 
1.4%
20160318 1
 
1.4%
20190104 1
 
1.4%
Other values (19) 19
26.4%
(Missing) 43
59.7%
ValueCountFrequency (%)
20030124 1
1.4%
20030323 1
1.4%
20040210 1
1.4%
20040819 1
1.4%
20050223 1
1.4%
20060105 1
1.4%
20060818 1
1.4%
20080310 1
1.4%
20080324 1
1.4%
20081125 1
1.4%
ValueCountFrequency (%)
20210719 1
1.4%
20210601 1
1.4%
20210101 1
1.4%
20201223 1
1.4%
20200901 1
1.4%
20191022 1
1.4%
20190104 1
1.4%
20181113 1
1.4%
20180806 1
1.4%
20180512 1
1.4%

보험종료일자
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing43
Missing (%)59.7%
Infinite0
Infinite (%)0.0%
Mean20139204
Minimum20040124
Maximum20220718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:35.161539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20040124
5-th percentile20044520
Q120090309
median20170317
Q320191112
95-th percentile20216811
Maximum20220718
Range180594
Interquartile range (IQR)100803

Descriptive statistics

Standard deviation63011.833
Coefficient of variation (CV)0.0031288145
Kurtosis-1.6022437
Mean20139204
Median Absolute Deviation (MAD)50214
Skewness-0.23308023
Sum5.8403691 × 108
Variance3.9704912 × 109
MonotonicityNot monotonic
2024-05-11T08:05:35.657385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20040322 1
 
1.4%
20201021 1
 
1.4%
20191112 1
 
1.4%
20220718 1
 
1.4%
20180124 1
 
1.4%
20170401 1
 
1.4%
20190805 1
 
1.4%
20190511 1
 
1.4%
20170317 1
 
1.4%
20200103 1
 
1.4%
Other values (19) 19
26.4%
(Missing) 43
59.7%
ValueCountFrequency (%)
20040124 1
1.4%
20040322 1
1.4%
20050818 1
1.4%
20060210 1
1.4%
20060222 1
1.4%
20070105 1
1.4%
20070818 1
1.4%
20090309 1
1.4%
20090323 1
1.4%
20091125 1
1.4%
ValueCountFrequency (%)
20220718 1
1.4%
20220531 1
1.4%
20211231 1
1.4%
20211222 1
1.4%
20210228 1
1.4%
20201021 1
1.4%
20200103 1
1.4%
20191112 1
1.4%
20190805 1
1.4%
20190511 1
1.4%

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing72
Missing (%)100.0%
Memory size780.0 B

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)71.4%
Missing51
Missing (%)70.8%
Infinite0
Infinite (%)0.0%
Mean44.857143
Minimum0
Maximum200
Zeros7
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size780.0 B
2024-05-11T08:05:36.069107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median38
Q374
95-th percentile92
Maximum200
Range200
Interquartile range (IQR)74

Descriptive statistics

Standard deviation49.630924
Coefficient of variation (CV)1.1064219
Kurtosis3.4160234
Mean44.857143
Median Absolute Deviation (MAD)38
Skewness1.4935889
Sum942
Variance2463.2286
MonotonicityNot monotonic
2024-05-11T08:05:36.488302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 7
 
9.7%
79 1
 
1.4%
66 1
 
1.4%
74 1
 
1.4%
80 1
 
1.4%
10 1
 
1.4%
200 1
 
1.4%
53 1
 
1.4%
38 1
 
1.4%
82 1
 
1.4%
Other values (5) 5
 
6.9%
(Missing) 51
70.8%
ValueCountFrequency (%)
0 7
9.7%
9 1
 
1.4%
10 1
 
1.4%
28 1
 
1.4%
38 1
 
1.4%
53 1
 
1.4%
60 1
 
1.4%
66 1
 
1.4%
71 1
 
1.4%
74 1
 
1.4%
ValueCountFrequency (%)
200 1
1.4%
92 1
1.4%
82 1
1.4%
80 1
1.4%
79 1
1.4%
74 1
1.4%
71 1
1.4%
66 1
1.4%
60 1
1.4%
53 1
1.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03140000CDFI226001199300000119930515<NA>3폐업3폐업20060203<NA><NA><NA>02-2652-3361<NA>158811서울특별시 양천구 목동 606-15번지 한강빌딩 1층서울특별시 양천구 등촌로 232 (목동,한강빌딩 1층)<NA>(주)예일항공여행사2006-03-08 08:54:39I2018-08-31 23:59:59.0<NA>187934.622083449785.227427국내여행업관광사업<NA><NA><NA><NA>한국관광협회중앙회여행공제회근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2004021020060210<NA><NA>
13140000CDFI226001199600000119960926<NA>3폐업3폐업19990619<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 909-6번지 우방빌딩 403서울특별시 양천구 목동동로 431 (목동,우방빌딩 403)<NA>(주)파파항공여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>189709.803505448328.288936국내여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
23140000CDFI226001199800000119980103<NA>3폐업3폐업20001122<NA><NA><NA><NA><NA>158846서울특별시 양천구 신월동 961-6번지 3층서울특별시 양천구 남부순환로66길 23 (신월동,3층)<NA>(주)다인여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>185248.796505446698.947826국내여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
33140000CDFI226001199800000219980109<NA>3폐업3폐업19980326<NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 917-1번지서울특별시 양천구 목동서로 159-1 (목동)<NA>주)승우여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>188871.512838447348.132133국내여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
43140000CDFI226001199800000419980310<NA>3폐업3폐업20020121<NA><NA><NA><NA><NA>158856서울특별시 양천구 신정동 878-19번지 3층서울특별시 양천구 신정중앙로 51 (신정동,3층)<NA>태성항공여행사2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>187331.288525447247.621503국내여행업관광사업<NA><NA><NA><NA><NA>근린생활시설<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0
53140000CDFI226001199800000519980603<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA>158050서울특별시 양천구 목동 917-1번지서울특별시 양천구 목동서로 159-1 (목동)<NA>(주)엘지홈쇼핑2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA>188871.512838447348.132133국내여행업관광사업<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
63140000CDFI226001199900000119990318<NA>4취소/말소/만료/정지/중지31등록취소<NA><NA><NA><NA><NA><NA><NA>강서구 등촌동 647-24<NA><NA>(주)신아티엔에스2002-10-22 17:51:16I2018-08-31 23:59:59.0<NA><NA><NA>국내여행업관광사업<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
73140000CDFI226001200000000220000412<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA>158860서울특별시 양천구 신정동 973-35번지서울특별시 양천구 신월로 291 (신정동)8027오진여행사2018-11-02 14:19:54U2018-11-04 02:35:48.0<NA>186986.032756446593.808609국내여행업관광사업<NA><NA>주택가주변<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>
83140000CDFI226001200000000520001130<NA>3폐업3폐업20030410<NA><NA><NA><NA><NA>158811서울특별시 양천구 목동 613-2번지 정원빌딩 411호서울특별시 양천구 등촌로 220 (목동,정원빌딩 411호)<NA>(주)훼밀리관광2003-10-09 16:07:05I2018-08-31 23:59:59.0<NA>187916.254333449683.219205국내여행업관광사업<NA>6주택가주변<NA><NA>근린생활시설15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
93140000CDFI22600120000000062000-12-01<NA>3폐업3폐업2023-03-24<NA><NA><NA><NA><NA>158-721서울특별시 양천구 목동 917-6 행복한세상백화점 1층서울특별시 양천구 목동동로 309 (목동,행복한세상백화점 1층)7997(주)미션투어2023-03-27 09:06:22U2022-12-02 22:09:00.0<NA>188977.17105447466.355031<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
623140000CDFI226001201700000620171117<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 971-20번지 명성빌딩 617호서울특별시 양천구 중앙로 294, 6층 17호 (신정동)8026주식회사 여행가그룹2017-11-17 16:37:36I2018-08-31 23:59:59.0<NA>186852.153852446714.974104국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>50000000<NA><NA><NA><NA>
633140000CDFI22600120170000072017-12-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 143-2서울특별시 양천구 곰달래로5길 63, 4층 (신월동)7920행복투어2023-11-01 18:04:55U2022-11-01 00:03:00.0<NA>185039.127935448077.855039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
643140000CDFI226001201800000120181114<NA>3폐업3폐업20201231<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 971-20 명성빌딩서울특별시 양천구 중앙로 294, 명성빌딩 6층 14-5호 (신정동)8026일몬도2020-12-31 15:28:07U2021-01-02 02:40:00.0<NA>186852.153852446714.974104국내여행업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>450000002018111320191112<NA><NA>
653140000CDFI22600120190000022015-07-24<NA>3폐업3폐업2023-05-31<NA><NA><NA>1588-3340<NA><NA>서울특별시 양천구 목동 917-9 현대41타워서울특별시 양천구 목동동로 293, 현대41타워 1803호 (목동)7997(주)제주스타오투오2023-06-01 09:28:04U2022-12-06 00:03:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
663140000CDFI22600120190000032014-03-27<NA>3폐업3폐업2023-05-31<NA><NA><NA>15883340<NA><NA>서울특별시 양천구 목동 917-9 현대41타워서울특별시 양천구 목동동로 293, 현대41타워 1804호 (목동)7997주식회사 제주스타투어2023-05-31 18:02:24U2022-12-06 00:02:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
673140000CDFI22600120190000042007-12-07<NA>3폐업3폐업2023-05-31<NA><NA><NA>15883340<NA><NA>서울특별시 양천구 목동 917-9 현대41타워서울특별시 양천구 목동동로 293, 현대41타워 1801호 (목동)7997(주)제주스타렌탈2023-06-01 09:28:31U2022-12-06 00:03:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
683140000CDFI226001202000000120191016<NA>3폐업3폐업20211220<NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 962 목동트라팰리스서울특별시 양천구 오목로 299, 목동트라팰리스 B2호 (목동)8001트래블락 주식회사2022-01-20 14:10:38U2022-01-22 02:40:00.0<NA>188472.759197447091.855964국내여행업<NA><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><NA>2019102220201021<NA><NA>
693140000CDFI22600120200000022020-02-25<NA>3폐업3폐업2023-05-31<NA><NA><NA>15883340<NA><NA>서울특별시 양천구 목동 917-9 현대41타워서울특별시 양천구 목동동로 293, 현대41타워 1802호 (목동)7997주식회사 스타투어제주2023-06-01 09:28:16U2022-12-06 00:03:00.0<NA>188953.066831447333.569188<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
703140000CDFI22600120210000012021-04-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 39-1 서부자동차매매시장 403호서울특별시 양천구 화곡로 6, 서부자동차매매시장 403호 (신월동)7909전둘모투어2024-03-08 16:23:11U2023-12-02 23:00:00.0<NA>184242.73002448537.930084<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
713140000CDFI226001202200000220111123<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2666-1848<NA><NA>서울특별시 양천구 신정동 911-7서울특별시 양천구 신정중앙로 62, 1층 (신정동)7944주식회사 브이아이피여행사2022-08-10 18:27:46U2021-12-07 23:02:00.0<NA>187436.998527447184.745108<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>