Overview

Dataset statistics

Number of variables60
Number of observations36
Missing cells1002
Missing cells (%)46.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.4 KiB
Average record size in memory524.7 B

Variable types

Categorical20
Text10
DateTime4
Unsupported21
Numeric5

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-17466/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
주변환경명 has constant value ""Constant
총층수 is highly imbalanced (57.1%)Imbalance
지상층수 is highly imbalanced (57.1%)Imbalance
지하층수 is highly imbalanced (57.0%)Imbalance
자본금 is highly imbalanced (61.4%)Imbalance
인허가취소일자 has 36 (100.0%) missing valuesMissing
폐업일자 has 17 (47.2%) missing valuesMissing
휴업시작일자 has 36 (100.0%) missing valuesMissing
휴업종료일자 has 36 (100.0%) missing valuesMissing
재개업일자 has 36 (100.0%) missing valuesMissing
전화번호 has 34 (94.4%) missing valuesMissing
소재지면적 has 36 (100.0%) missing valuesMissing
소재지우편번호 has 29 (80.6%) missing valuesMissing
도로명우편번호 has 12 (33.3%) missing valuesMissing
업태구분명 has 36 (100.0%) missing valuesMissing
좌표정보(X) has 1 (2.8%) missing valuesMissing
좌표정보(Y) has 1 (2.8%) missing valuesMissing
문화사업자구분명 has 36 (100.0%) missing valuesMissing
지역구분명 has 30 (83.3%) missing valuesMissing
주변환경명 has 34 (94.4%) missing valuesMissing
제작취급품목내용 has 36 (100.0%) missing valuesMissing
보험기관명 has 36 (100.0%) missing valuesMissing
영문상호명 has 31 (86.1%) missing valuesMissing
영문상호주소 has 31 (86.1%) missing valuesMissing
선박제원 has 36 (100.0%) missing valuesMissing
기념품종류 has 36 (100.0%) missing valuesMissing
시설면적 has 13 (36.1%) missing valuesMissing
놀이기구수내역 has 36 (100.0%) missing valuesMissing
방송시설유무 has 36 (100.0%) missing valuesMissing
발전시설유무 has 36 (100.0%) missing valuesMissing
의무실유무 has 36 (100.0%) missing valuesMissing
안내소유무 has 36 (100.0%) missing valuesMissing
기획여행보험시작일자 has 36 (100.0%) missing valuesMissing
기획여행보험종료일자 has 36 (100.0%) missing valuesMissing
보험시작일자 has 36 (100.0%) missing valuesMissing
보험종료일자 has 36 (100.0%) missing valuesMissing
부대시설내역 has 36 (100.0%) missing valuesMissing
시설규모 has 13 (36.1%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
도로명주소 has unique valuesUnique
사업장명 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
문화사업자구분명 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
보험기관명 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
보험시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
보험종료일자 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
시설면적 has 2 (5.6%) zerosZeros
시설규모 has 2 (5.6%) zerosZeros

Reproduction

Analysis started2024-04-29 19:20:14.364481
Analysis finished2024-04-29 19:20:15.211641
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
3140000
36 

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 36
100.0%

Length

2024-04-30T04:20:15.280340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:15.362664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 36
100.0%

관리번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-30T04:20:15.504934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters720
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

Unique36 ?
Unique (%)100.0%

Sample

1st rowCDFI2262212012000002
2nd rowCDFI2262212012000003
3rd rowCDFI2262212013000001
4th rowCDFI2262212013000002
5th rowCDFI2262212014000001
ValueCountFrequency (%)
cdfi2262212012000002 1
 
2.8%
cdfi2262212012000003 1
 
2.8%
cdfi2262212023000004 1
 
2.8%
cdfi2262212021000001 1
 
2.8%
cdfi2262212022000001 1
 
2.8%
cdfi2262212022000002 1
 
2.8%
cdfi2262212023000001 1
 
2.8%
cdfi2262212023000002 1
 
2.8%
cdfi2262212023000003 1
 
2.8%
cdfi2262212023000005 1
 
2.8%
Other values (26) 26
72.2%
2024-04-30T04:20:15.805845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
30.0%
2 209
29.0%
1 68
 
9.4%
6 41
 
5.7%
C 36
 
5.0%
D 36
 
5.0%
F 36
 
5.0%
I 36
 
5.0%
3 16
 
2.2%
4 13
 
1.8%
Other values (4) 13
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 576
80.0%
Uppercase Letter 144
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
37.5%
2 209
36.3%
1 68
 
11.8%
6 41
 
7.1%
3 16
 
2.8%
4 13
 
2.3%
5 6
 
1.0%
9 4
 
0.7%
7 2
 
0.3%
8 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
C 36
25.0%
D 36
25.0%
F 36
25.0%
I 36
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 576
80.0%
Latin 144
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
37.5%
2 209
36.3%
1 68
 
11.8%
6 41
 
7.1%
3 16
 
2.8%
4 13
 
2.3%
5 6
 
1.0%
9 4
 
0.7%
7 2
 
0.3%
8 1
 
0.2%
Latin
ValueCountFrequency (%)
C 36
25.0%
D 36
25.0%
F 36
25.0%
I 36
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
30.0%
2 209
29.0%
1 68
 
9.4%
6 41
 
5.7%
C 36
 
5.0%
D 36
 
5.0%
F 36
 
5.0%
I 36
 
5.0%
3 16
 
2.2%
4 13
 
1.8%
Other values (4) 13
 
1.8%

인허가일자
Date

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2012-07-25 00:00:00
Maximum2024-03-19 00:00:00
2024-04-30T04:20:15.952590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:20:16.083337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
3
19 
1
17 

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 19
52.8%
1 17
47.2%

Length

2024-04-30T04:20:16.222725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:16.326712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 19
52.8%
1 17
47.2%

영업상태명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
폐업
19 
영업/정상
17 

Length

Max length5
Median length2
Mean length3.4166667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 19
52.8%
영업/정상 17
47.2%

Length

2024-04-30T04:20:16.420350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:16.505940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
52.8%
영업/정상 17
47.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
3
19 
13
17 

Length

Max length2
Median length1
Mean length1.4722222
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 19
52.8%
13 17
47.2%

Length

2024-04-30T04:20:16.596312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:16.692132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 19
52.8%
13 17
47.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
폐업
19 
영업중
17 

Length

Max length3
Median length2
Mean length2.4722222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 19
52.8%
영업중 17
47.2%

Length

2024-04-30T04:20:16.778036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:16.857194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 19
52.8%
영업중 17
47.2%

폐업일자
Date

MISSING 

Distinct18
Distinct (%)94.7%
Missing17
Missing (%)47.2%
Memory size420.0 B
Minimum2016-11-01 00:00:00
Maximum2023-12-31 00:00:00
2024-04-30T04:20:16.941289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:20:17.048835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

전화번호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing34
Missing (%)94.4%
Memory size420.0 B
2024-04-30T04:20:17.179061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length10.5
Min length9

Characters and Unicode

Total characters21
Distinct characters10
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

Unique2 ?
Unique (%)100.0%

Sample

1st row2651-1133
2nd row02-6095-7899
ValueCountFrequency (%)
2651-1133 1
50.0%
02-6095-7899 1
50.0%
2024-04-30T04:20:17.404222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
14.3%
- 3
14.3%
9 3
14.3%
2 2
9.5%
6 2
9.5%
5 2
9.5%
3 2
9.5%
0 2
9.5%
7 1
 
4.8%
8 1
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
85.7%
Dash Punctuation 3
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
16.7%
9 3
16.7%
2 2
11.1%
6 2
11.1%
5 2
11.1%
3 2
11.1%
0 2
11.1%
7 1
 
5.6%
8 1
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
14.3%
- 3
14.3%
9 3
14.3%
2 2
9.5%
6 2
9.5%
5 2
9.5%
3 2
9.5%
0 2
9.5%
7 1
 
4.8%
8 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
14.3%
- 3
14.3%
9 3
14.3%
2 2
9.5%
6 2
9.5%
5 2
9.5%
3 2
9.5%
0 2
9.5%
7 1
 
4.8%
8 1
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

소재지우편번호
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing29
Missing (%)80.6%
Memory size420.0 B
2024-04-30T04:20:17.552619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters49
Distinct characters10
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

Unique7 ?
Unique (%)100.0%

Sample

1st row158-724
2nd row158-832
3rd row158-808
4th row158-773
5th row158-799
ValueCountFrequency (%)
158-724 1
14.3%
158-832 1
14.3%
158-808 1
14.3%
158-773 1
14.3%
158-799 1
14.3%
158-070 1
14.3%
158-798 1
14.3%
2024-04-30T04:20:17.791111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 11
22.4%
1 7
14.3%
5 7
14.3%
- 7
14.3%
7 6
12.2%
0 3
 
6.1%
9 3
 
6.1%
2 2
 
4.1%
3 2
 
4.1%
4 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42
85.7%
Dash Punctuation 7
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 11
26.2%
1 7
16.7%
5 7
16.7%
7 6
14.3%
0 3
 
7.1%
9 3
 
7.1%
2 2
 
4.8%
3 2
 
4.8%
4 1
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 11
22.4%
1 7
14.3%
5 7
14.3%
- 7
14.3%
7 6
12.2%
0 3
 
6.1%
9 3
 
6.1%
2 2
 
4.1%
3 2
 
4.1%
4 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 11
22.4%
1 7
14.3%
5 7
14.3%
- 7
14.3%
7 6
12.2%
0 3
 
6.1%
9 3
 
6.1%
2 2
 
4.1%
3 2
 
4.1%
4 1
 
2.0%

지번주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-30T04:20:17.992525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length26.722222
Min length18

Characters and Unicode

Total characters962
Distinct characters68
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동 916번지 목동현대하이페이온 102동 3807호
2nd row서울특별시 양천구 목동 925 목동신시가지아파트7단지 721동 802호
3rd row서울특별시 양천구 신월동 416-1번지 보람아파트 102동 701호
4th row서울특별시 양천구 목동 513-22번지 서영빌라 601호
5th row서울특별시 양천구 신정동 328번지 목동신시가지아파트 1324동 102호
ValueCountFrequency (%)
서울특별시 36
19.4%
양천구 36
19.4%
신정동 19
 
10.2%
목동 16
 
8.6%
102호 3
 
1.6%
102동 2
 
1.1%
925 2
 
1.1%
목동신시가지아파트7단지 2
 
1.1%
879-6 1
 
0.5%
534-2 1
 
0.5%
Other values (68) 68
36.6%
2024-04-30T04:20:18.306900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
 
15.6%
1 56
 
5.8%
동 53
 
5.5%
시 40
 
4.2%
양 37
 
3.8%
천 37
 
3.8%
서 37
 
3.8%
별 36
 
3.7%
울 36
 
3.7%
구 36
 
3.7%
Other values (58) 444
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 558
58.0%
Decimal Number 228
23.7%
Space Separator 150
 
15.6%
Dash Punctuation 25
 
2.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
 
9.5%
시 40
 
7.2%
양 37
 
6.6%
천 37
 
6.6%
서 37
 
6.6%
별 36
 
6.5%
울 36
 
6.5%
구 36
 
6.5%
특 36
 
6.5%
신 26
 
4.7%
Other values (45) 184
33.0%
Decimal Number
ValueCountFrequency (%)
1 56
24.6%
2 32
14.0%
3 26
11.4%
0 25
11.0%
5 18
 
7.9%
9 17
 
7.5%
7 15
 
6.6%
8 14
 
6.1%
4 14
 
6.1%
6 11
 
4.8%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 558
58.0%
Common 403
41.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
 
9.5%
시 40
 
7.2%
양 37
 
6.6%
천 37
 
6.6%
서 37
 
6.6%
별 36
 
6.5%
울 36
 
6.5%
구 36
 
6.5%
특 36
 
6.5%
신 26
 
4.7%
Other values (45) 184
33.0%
Common
ValueCountFrequency (%)
150
37.2%
1 56
 
13.9%
2 32
 
7.9%
3 26
 
6.5%
- 25
 
6.2%
0 25
 
6.2%
5 18
 
4.5%
9 17
 
4.2%
7 15
 
3.7%
8 14
 
3.5%
Other values (2) 25
 
6.2%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 558
58.0%
ASCII 404
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
37.1%
1 56
 
13.9%
2 32
 
7.9%
3 26
 
6.4%
- 25
 
6.2%
0 25
 
6.2%
5 18
 
4.5%
9 17
 
4.2%
7 15
 
3.7%
8 14
 
3.5%
Other values (3) 26
 
6.4%
Hangul
ValueCountFrequency (%)
동 53
 
9.5%
시 40
 
7.2%
양 37
 
6.6%
천 37
 
6.6%
서 37
 
6.6%
별 36
 
6.5%
울 36
 
6.5%
구 36
 
6.5%
특 36
 
6.5%
신 26
 
4.7%
Other values (45) 184
33.0%

도로명주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-30T04:20:18.553758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length38.222222
Min length26

Characters and Unicode

Total characters1376
Distinct characters82
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목동동로 257, 102동 3807호 (목동, 목동현대하이페리온)
2nd row서울특별시 양천구 목동로 186, 721동 802호 (목동, 목동신시가지아파트7단지)
3rd row서울특별시 양천구 남부순환로67길 15, 102동 7층 701호 (신월동, 보람아파트)
4th row서울특별시 양천구 목동중앙북로 83-1 (목동, 서영빌라 601호)
5th row서울특별시 양천구 목동동로 100, 1324동 102호 (신정동, 목동신시가지아파트)
ValueCountFrequency (%)
서울특별시 36
 
14.3%
양천구 36
 
14.3%
신정동 19
 
7.5%
목동 16
 
6.3%
2층 6
 
2.4%
102호 5
 
2.0%
목동동로 4
 
1.6%
목동중앙북로 3
 
1.2%
202호 3
 
1.2%
33-1 2
 
0.8%
Other values (109) 122
48.4%
2024-04-30T04:20:18.892378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216
 
15.7%
동 86
 
6.2%
1 58
 
4.2%
2 56
 
4.1%
, 50
 
3.6%
목 49
 
3.6%
0 47
 
3.4%
시 41
 
3.0%
서 38
 
2.8%
천 37
 
2.7%
Other values (72) 698
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 758
55.1%
Decimal Number 265
 
19.3%
Space Separator 216
 
15.7%
Other Punctuation 50
 
3.6%
Close Punctuation 36
 
2.6%
Open Punctuation 36
 
2.6%
Dash Punctuation 11
 
0.8%
Uppercase Letter 3
 
0.2%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 86
 
11.3%
목 49
 
6.5%
시 41
 
5.4%
서 38
 
5.0%
천 37
 
4.9%
양 37
 
4.9%
구 36
 
4.7%
로 36
 
4.7%
울 36
 
4.7%
별 36
 
4.7%
Other values (54) 326
43.0%
Decimal Number
ValueCountFrequency (%)
1 58
21.9%
2 56
21.1%
0 47
17.7%
3 29
10.9%
4 17
 
6.4%
7 17
 
6.4%
8 15
 
5.7%
5 13
 
4.9%
6 10
 
3.8%
9 3
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
216
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 758
55.1%
Common 614
44.6%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 86
 
11.3%
목 49
 
6.5%
시 41
 
5.4%
서 38
 
5.0%
천 37
 
4.9%
양 37
 
4.9%
구 36
 
4.7%
로 36
 
4.7%
울 36
 
4.7%
별 36
 
4.7%
Other values (54) 326
43.0%
Common
ValueCountFrequency (%)
216
35.2%
1 58
 
9.4%
2 56
 
9.1%
, 50
 
8.1%
0 47
 
7.7%
) 36
 
5.9%
( 36
 
5.9%
3 29
 
4.7%
4 17
 
2.8%
7 17
 
2.8%
Other values (5) 52
 
8.5%
Latin
ValueCountFrequency (%)
B 2
50.0%
D 1
25.0%
b 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 758
55.1%
ASCII 618
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
216
35.0%
1 58
 
9.4%
2 56
 
9.1%
, 50
 
8.1%
0 47
 
7.6%
) 36
 
5.8%
( 36
 
5.8%
3 29
 
4.7%
4 17
 
2.8%
7 17
 
2.8%
Other values (8) 56
 
9.1%
Hangul
ValueCountFrequency (%)
동 86
 
11.3%
목 49
 
6.5%
시 41
 
5.4%
서 38
 
5.0%
천 37
 
4.9%
양 37
 
4.9%
구 36
 
4.7%
로 36
 
4.7%
울 36
 
4.7%
별 36
 
4.7%
Other values (54) 326
43.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)83.3%
Missing12
Missing (%)33.3%
Infinite0
Infinite (%)0.0%
Mean7977.7917
Minimum7937
Maximum8058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-30T04:20:19.001876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7937
5-th percentile7938.15
Q17954.5
median7970.5
Q38003.5
95-th percentile8046.25
Maximum8058
Range121
Interquartile range (IQR)49

Descriptive statistics

Standard deviation34.752515
Coefficient of variation (CV)0.0043561573
Kurtosis0.042013573
Mean7977.7917
Median Absolute Deviation (MAD)26
Skewness0.8660546
Sum191467
Variance1207.7373
MonotonicityNot monotonic
2024-04-30T04:20:19.100626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
7973 2
 
5.6%
7971 2
 
5.6%
7955 2
 
5.6%
7939 2
 
5.6%
7993 1
 
2.8%
7941 1
 
2.8%
7953 1
 
2.8%
8058 1
 
2.8%
7958 1
 
2.8%
7968 1
 
2.8%
Other values (10) 10
27.8%
(Missing) 12
33.3%
ValueCountFrequency (%)
7937 1
2.8%
7938 1
2.8%
7939 2
5.6%
7941 1
2.8%
7953 1
2.8%
7955 2
5.6%
7958 1
2.8%
7968 1
2.8%
7969 1
2.8%
7970 1
2.8%
ValueCountFrequency (%)
8058 1
2.8%
8050 1
2.8%
8025 1
2.8%
8012 1
2.8%
8009 1
2.8%
8008 1
2.8%
8002 1
2.8%
7993 1
2.8%
7973 2
5.6%
7971 2
5.6%

사업장명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-30T04:20:19.274790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length16
Mean length9.4444444
Min length1

Characters and Unicode

Total characters340
Distinct characters114
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row현대하이페리온
2nd rowO.K. House
3rd row꿈을 이루는 집
4th rowSeoul 910
5th row스위트홈
ValueCountFrequency (%)
house 6
 
9.0%
스테이 3
 
4.5%
stay 3
 
4.5%
studio 2
 
3.0%
현대하이페리온 1
 
1.5%
목동 1
 
1.5%
전망좋은집 1
 
1.5%
레드판다커머스 1
 
1.5%
brick 1
 
1.5%
이레의집 1
 
1.5%
Other values (47) 47
70.1%
2024-04-30T04:20:19.576065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
9.1%
스 21
 
6.2%
이 13
 
3.8%
o 12
 
3.5%
e 12
 
3.5%
u 11
 
3.2%
s 11
 
3.2%
H 10
 
2.9%
S 9
 
2.6%
하 8
 
2.4%
Other values (104) 202
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148
43.5%
Lowercase Letter 85
25.0%
Uppercase Letter 58
 
17.1%
Space Separator 31
 
9.1%
Open Punctuation 5
 
1.5%
Close Punctuation 5
 
1.5%
Other Punctuation 5
 
1.5%
Decimal Number 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 21
 
14.2%
이 13
 
8.8%
하 8
 
5.4%
테 7
 
4.7%
우 6
 
4.1%
트 4
 
2.7%
게 4
 
2.7%
더 3
 
2.0%
레 3
 
2.0%
집 3
 
2.0%
Other values (62) 76
51.4%
Lowercase Letter
ValueCountFrequency (%)
o 12
14.1%
e 12
14.1%
u 11
12.9%
s 11
12.9%
a 6
 
7.1%
t 5
 
5.9%
r 4
 
4.7%
i 3
 
3.5%
n 3
 
3.5%
h 3
 
3.5%
Other values (7) 15
17.6%
Uppercase Letter
ValueCountFrequency (%)
H 10
17.2%
S 9
15.5%
O 7
12.1%
U 4
 
6.9%
I 3
 
5.2%
N 3
 
5.2%
Y 3
 
5.2%
E 3
 
5.2%
T 3
 
5.2%
J 3
 
5.2%
Other values (7) 10
17.2%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
0 1
33.3%
9 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
' 2
40.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
43.2%
Latin 143
42.1%
Common 49
 
14.4%
Han 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 21
 
14.3%
이 13
 
8.8%
하 8
 
5.4%
테 7
 
4.8%
우 6
 
4.1%
트 4
 
2.7%
게 4
 
2.7%
더 3
 
2.0%
레 3
 
2.0%
집 3
 
2.0%
Other values (61) 75
51.0%
Latin
ValueCountFrequency (%)
o 12
 
8.4%
e 12
 
8.4%
u 11
 
7.7%
s 11
 
7.7%
H 10
 
7.0%
S 9
 
6.3%
O 7
 
4.9%
a 6
 
4.2%
t 5
 
3.5%
U 4
 
2.8%
Other values (24) 56
39.2%
Common
ValueCountFrequency (%)
31
63.3%
( 5
 
10.2%
) 5
 
10.2%
. 3
 
6.1%
' 2
 
4.1%
1 1
 
2.0%
0 1
 
2.0%
9 1
 
2.0%
Han
ValueCountFrequency (%)
孝 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 192
56.5%
Hangul 147
43.2%
CJK 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
 
16.1%
o 12
 
6.2%
e 12
 
6.2%
u 11
 
5.7%
s 11
 
5.7%
H 10
 
5.2%
S 9
 
4.7%
O 7
 
3.6%
a 6
 
3.1%
( 5
 
2.6%
Other values (32) 78
40.6%
Hangul
ValueCountFrequency (%)
스 21
 
14.3%
이 13
 
8.8%
하 8
 
5.4%
테 7
 
4.8%
우 6
 
4.1%
트 4
 
2.7%
게 4
 
2.7%
더 3
 
2.0%
레 3
 
2.0%
집 3
 
2.0%
Other values (61) 75
51.0%
CJK
ValueCountFrequency (%)
孝 1
100.0%

최종수정일자
Date

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2016-11-01 00:00:00
Maximum2024-03-19 18:06:46
2024-04-30T04:20:19.683708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:20:19.794510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
I
19 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 19
52.8%
U 17
47.2%

Length

2024-04-30T04:20:19.892901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:19.981465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 19
52.8%
u 17
47.2%

데이터갱신일자
Date

Distinct22
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2018-08-31 23:59:00
Maximum2023-12-02 23:07:00
2024-04-30T04:20:20.072058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:20:20.186624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean187955.82
Minimum184971.29
Maximum189414.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-30T04:20:20.297048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184971.29
5-th percentile185672.46
Q1187392.11
median188231.07
Q3188799.65
95-th percentile189090.79
Maximum189414.09
Range4442.798
Interquartile range (IQR)1407.536

Descriptive statistics

Standard deviation1053.1952
Coefficient of variation (CV)0.0056034189
Kurtosis1.1662786
Mean187955.82
Median Absolute Deviation (MAD)674.5502
Skewness-1.129409
Sum6578453.6
Variance1109220.1
MonotonicityNot monotonic
2024-04-30T04:20:20.399148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
188884.0756 1
 
2.8%
188248.4543 1
 
2.8%
188023.126624766 1
 
2.8%
184971.290324023 1
 
2.8%
189414.0883 1
 
2.8%
187316.794328687 1
 
2.8%
188983.0511 1
 
2.8%
187426.99847239 1
 
2.8%
189033.127347553 1
 
2.8%
188248.45432693 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
184971.290324023 1
2.8%
185593.1935 1
2.8%
185706.4317 1
2.8%
186710.935819425 1
2.8%
186855.001383142 1
2.8%
187239.6278 1
2.8%
187240.623329909 1
2.8%
187316.794328687 1
2.8%
187357.2254 1
2.8%
187426.99847239 1
2.8%
ValueCountFrequency (%)
189414.0883 1
2.8%
189120.105 1
2.8%
189078.224808079 1
2.8%
189077.658 1
2.8%
189033.127347553 1
2.8%
188983.0511 1
2.8%
188905.616 1
2.8%
188884.0756 1
2.8%
188882.1441 1
2.8%
188717.1518 1
2.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)100.0%
Missing1
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean447521.6
Minimum444831.85
Maximum449371.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-30T04:20:20.713468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444831.85
5-th percentile445579.89
Q1446647.24
median447261.45
Q3448956.23
95-th percentile449337.3
Maximum449371.19
Range4539.3419
Interquartile range (IQR)2308.9914

Descriptive statistics

Standard deviation1303.9659
Coefficient of variation (CV)0.0029137497
Kurtosis-1.0034822
Mean447521.6
Median Absolute Deviation (MAD)792.43331
Skewness0.055482678
Sum15663256
Variance1700327.2
MonotonicityNot monotonic
2024-04-30T04:20:20.823920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
447186.8886 1
 
2.8%
447406.3013 1
 
2.8%
448784.723904545 1
 
2.8%
445601.995865959 1
 
2.8%
449292.3585 1
 
2.8%
446890.396275444 1
 
2.8%
449172.5074 1
 
2.8%
447284.783534476 1
 
2.8%
446507.431632047 1
 
2.8%
447406.301288366 1
 
2.8%
Other values (25) 25
69.4%
ValueCountFrequency (%)
444831.8478 1
2.8%
445528.3059 1
2.8%
445601.995865959 1
2.8%
445887.4577 1
2.8%
446003.9412 1
2.8%
446469.0194 1
2.8%
446497.899521869 1
2.8%
446507.431632047 1
2.8%
446607.6108 1
2.8%
446686.8762 1
2.8%
ValueCountFrequency (%)
449371.1897 1
2.8%
449363.193667633 1
2.8%
449326.206 1
2.8%
449292.3585 1
2.8%
449228.1227 1
2.8%
449225.3796 1
2.8%
449219.2473 1
2.8%
449172.5074 1
2.8%
449096.254852184 1
2.8%
448816.215 1
2.8%

문화체육업종명
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
외국인관광 도시민박업
23 
<NA>
13 

Length

Max length11
Median length11
Mean length8.4722222
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row외국인관광 도시민박업
2nd row외국인관광 도시민박업
3rd row외국인관광 도시민박업
4th row외국인관광 도시민박업
5th row외국인관광 도시민박업

Common Values

ValueCountFrequency (%)
외국인관광 도시민박업 23
63.9%
<NA> 13
36.1%

Length

2024-04-30T04:20:20.954201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:21.060854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인관광 23
39.0%
도시민박업 23
39.0%
na 13
22.0%

문화사업자구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

지역구분명
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing30
Missing (%)83.3%
Memory size420.0 B
2024-04-30T04:20:21.183339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.5
Min length4

Characters and Unicode

Total characters33
Distinct characters7
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 (%)33.3%

Sample

1st row일반주거지역
2nd row일반주거지역
3rd row일반주거지역
4th row주거지역
5th row일반주거지역
ValueCountFrequency (%)
일반주거지역 4
66.7%
주거지역 1
 
16.7%
준주거지역 1
 
16.7%
2024-04-30T04:20:21.411346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6
18.2%
거 6
18.2%
지 6
18.2%
역 6
18.2%
일 4
12.1%
반 4
12.1%
준 1
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6
18.2%
거 6
18.2%
지 6
18.2%
역 6
18.2%
일 4
12.1%
반 4
12.1%
준 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6
18.2%
거 6
18.2%
지 6
18.2%
역 6
18.2%
일 4
12.1%
반 4
12.1%
준 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6
18.2%
거 6
18.2%
지 6
18.2%
역 6
18.2%
일 4
12.1%
반 4
12.1%
준 1
 
3.0%

총층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
30 
0
4 
15
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.5277778
Min length1

Unique

Unique2 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
83.3%
0 4
 
11.1%
15 1
 
2.8%
3 1
 
2.8%

Length

2024-04-30T04:20:21.528582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:21.624721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
83.3%
0 4
 
11.1%
15 1
 
2.8%
3 1
 
2.8%

주변환경명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing34
Missing (%)94.4%
Memory size420.0 B
2024-04-30T04:20:21.714756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters5
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

Unique0 ?
Unique (%)0.0%

Sample

1st row아파트지역
2nd row아파트지역
ValueCountFrequency (%)
아파트지역 2
100.0%
2024-04-30T04:20:21.923097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2
20.0%
파 2
20.0%
트 2
20.0%
지 2
20.0%
역 2
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2
20.0%
파 2
20.0%
트 2
20.0%
지 2
20.0%
역 2
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2
20.0%
파 2
20.0%
트 2
20.0%
지 2
20.0%
역 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2
20.0%
파 2
20.0%
트 2
20.0%
지 2
20.0%
역 2
20.0%

제작취급품목내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

보험기관명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

건물용도명
Categorical

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
27 
아파트
6 
다세대주택
 
2
다가구용 주택(공동주택적용)
 
1

Length

Max length15
Median length4
Mean length4.1944444
Min length3

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
75.0%
아파트 6
 
16.7%
다세대주택 2
 
5.6%
다가구용 주택(공동주택적용) 1
 
2.8%

Length

2024-04-30T04:20:22.029822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:22.124200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
73.0%
아파트 6
 
16.2%
다세대주택 2
 
5.4%
다가구용 1
 
2.7%
주택(공동주택적용 1
 
2.7%

지상층수
Categorical

IMBALANCE 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
30 
0
4 
7
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.5277778
Min length1

Unique

Unique2 ?
Unique (%)5.6%

Sample

1st row<NA>
2nd row0
3rd row7
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
83.3%
0 4
 
11.1%
7 1
 
2.8%
15 1
 
2.8%

Length

2024-04-30T04:20:22.242929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:22.333245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
83.3%
0 4
 
11.1%
7 1
 
2.8%
15 1
 
2.8%

지하층수
Categorical

IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
31 
0
4 
2
 
1

Length

Max length4
Median length4
Mean length3.5833333
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
86.1%
0 4
 
11.1%
2 1
 
2.8%

Length

2024-04-30T04:20:22.435157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:22.523550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
86.1%
0 4
 
11.1%
2 1
 
2.8%

객실수
Categorical

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
26 
2
3 
1
3 
3
 
2
0
 
2

Length

Max length4
Median length4
Mean length3.1666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row2
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
72.2%
2 3
 
8.3%
1 3
 
8.3%
3 2
 
5.6%
0 2
 
5.6%

Length

2024-04-30T04:20:22.635489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:22.744780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
72.2%
2 3
 
8.3%
1 3
 
8.3%
3 2
 
5.6%
0 2
 
5.6%

건축연면적
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:22.842972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:22.948543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

영문상호명
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing31
Missing (%)86.1%
Memory size420.0 B
2024-04-30T04:20:23.057295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6
Min length9

Characters and Unicode

Total characters48
Distinct characters23
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

Unique5 ?
Unique (%)100.0%

Sample

1st rowO.K. House
2nd rowSeoul 910
3rd rowJay's Home
4th rowHyo House
5th rowHAN'S STAY
ValueCountFrequency (%)
house 2
20.0%
o.k 1
10.0%
seoul 1
10.0%
910 1
10.0%
jay's 1
10.0%
home 1
10.0%
hyo 1
10.0%
han's 1
10.0%
stay 1
10.0%
2024-04-30T04:20:23.301831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
10.4%
H 5
 
10.4%
o 5
 
10.4%
e 4
 
8.3%
u 3
 
6.2%
s 3
 
6.2%
S 3
 
6.2%
y 2
 
4.2%
. 2
 
4.2%
A 2
 
4.2%
Other values (13) 14
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20
41.7%
Uppercase Letter 16
33.3%
Space Separator 5
 
10.4%
Other Punctuation 4
 
8.3%
Decimal Number 3
 
6.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 5
31.2%
S 3
18.8%
A 2
 
12.5%
O 1
 
6.2%
T 1
 
6.2%
N 1
 
6.2%
J 1
 
6.2%
K 1
 
6.2%
Y 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
o 5
25.0%
e 4
20.0%
u 3
15.0%
s 3
15.0%
y 2
 
10.0%
m 1
 
5.0%
a 1
 
5.0%
l 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
9 1
33.3%
0 1
33.3%
1 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
' 2
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
75.0%
Common 12
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 5
13.9%
o 5
13.9%
e 4
11.1%
u 3
8.3%
s 3
8.3%
S 3
8.3%
y 2
 
5.6%
A 2
 
5.6%
O 1
 
2.8%
T 1
 
2.8%
Other values (7) 7
19.4%
Common
ValueCountFrequency (%)
5
41.7%
. 2
 
16.7%
' 2
 
16.7%
9 1
 
8.3%
0 1
 
8.3%
1 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
 
10.4%
H 5
 
10.4%
o 5
 
10.4%
e 4
 
8.3%
u 3
 
6.2%
s 3
 
6.2%
S 3
 
6.2%
y 2
 
4.2%
. 2
 
4.2%
A 2
 
4.2%
Other values (13) 14
29.2%

영문상호주소
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing31
Missing (%)86.1%
Memory size420.0 B
2024-04-30T04:20:23.447603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length43
Min length25

Characters and Unicode

Total characters215
Distinct characters34
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

Unique5 ?
Unique (%)100.0%

Sample

1st rowTOURISM SERVICE FACILITIES BUSINESS CERTIFICATE OF REGISTRATION
2nd rowCity accommodation business for foreign tourists
3rd rowTOURISM SERVICE FACLITIES
4th rowGuesthouse for foreign tourists
5th rowCity accommodation business for Foreign Tourists
ValueCountFrequency (%)
business 3
11.5%
for 3
11.5%
foreign 3
11.5%
tourists 3
11.5%
tourism 2
7.7%
service 2
7.7%
city 2
7.7%
accommodation 2
7.7%
facilities 1
 
3.8%
certificate 1
 
3.8%
Other values (4) 4
15.4%
2024-04-30T04:20:23.725004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
9.8%
o 16
 
7.4%
s 14
 
6.5%
I 14
 
6.5%
i 12
 
5.6%
t 10
 
4.7%
S 10
 
4.7%
E 10
 
4.7%
r 9
 
4.2%
T 9
 
4.2%
Other values (24) 90
41.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 109
50.7%
Uppercase Letter 85
39.5%
Space Separator 21
 
9.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 16
14.7%
s 14
12.8%
i 12
11.0%
t 10
9.2%
r 9
8.3%
n 7
 
6.4%
e 7
 
6.4%
u 7
 
6.4%
f 5
 
4.6%
a 4
 
3.7%
Other values (7) 18
16.5%
Uppercase Letter
ValueCountFrequency (%)
I 14
16.5%
S 10
11.8%
E 10
11.8%
T 9
10.6%
C 8
9.4%
R 7
8.2%
F 5
 
5.9%
A 4
 
4.7%
O 4
 
4.7%
U 3
 
3.5%
Other values (6) 11
12.9%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 194
90.2%
Common 21
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 16
 
8.2%
s 14
 
7.2%
I 14
 
7.2%
i 12
 
6.2%
t 10
 
5.2%
S 10
 
5.2%
E 10
 
5.2%
r 9
 
4.6%
T 9
 
4.6%
C 8
 
4.1%
Other values (23) 82
42.3%
Common
ValueCountFrequency (%)
21
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
 
9.8%
o 16
 
7.4%
s 14
 
6.5%
I 14
 
6.5%
i 12
 
5.6%
t 10
 
4.7%
S 10
 
4.7%
E 10
 
4.7%
r 9
 
4.2%
T 9
 
4.2%
Other values (24) 90
41.9%

선박총톤수
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:23.847936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:23.951535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

선박척수
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:24.060789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:24.164663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

선박제원
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

무대면적
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:24.274834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:24.388832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

좌석수
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:24.490333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:24.583638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

기념품종류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

회의실별동시수용인원
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:24.676690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:24.789467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

시설면적
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)87.0%
Missing13
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean84.474783
Minimum0
Maximum162
Zeros2
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-30T04:20:24.872820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.74
Q162.61
median83.37
Q3111.8
95-th percentile136.665
Maximum162
Range162
Interquartile range (IQR)49.19

Descriptive statistics

Standard deviation40.149009
Coefficient of variation (CV)0.47527803
Kurtosis0.29624269
Mean84.474783
Median Absolute Deviation (MAD)24.91
Skewness-0.39753808
Sum1942.92
Variance1611.9429
MonotonicityNot monotonic
2024-04-30T04:20:24.977511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 2
 
5.6%
115.32 2
 
5.6%
84.95 2
 
5.6%
79.71 1
 
2.8%
73.97 1
 
2.8%
66.74 1
 
2.8%
51.95 1
 
2.8%
105.35 1
 
2.8%
101.91 1
 
2.8%
82.35 1
 
2.8%
Other values (10) 10
27.8%
(Missing) 13
36.1%
ValueCountFrequency (%)
0.0 2
5.6%
37.4 1
2.8%
51.95 1
2.8%
55.92 1
2.8%
58.48 1
2.8%
66.74 1
2.8%
73.97 1
2.8%
79.71 1
2.8%
79.98 1
2.8%
82.35 1
2.8%
ValueCountFrequency (%)
162.0 1
2.8%
137.36 1
2.8%
130.41 1
2.8%
127.2 1
2.8%
115.32 2
5.6%
108.28 1
2.8%
105.35 1
2.8%
101.91 1
2.8%
84.95 2
5.6%
83.37 1
2.8%

놀이기구수내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

놀이시설수
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
32 
0
4 

Length

Max length4
Median length4
Mean length3.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
88.9%
0 4
 
11.1%

Length

2024-04-30T04:20:25.097008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:25.196727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
88.9%
0 4
 
11.1%

방송시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

발전시설유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

의무실유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

안내소유무
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

기획여행보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

기획여행보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

자본금
Categorical

IMBALANCE 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
31 
0
 
3
8000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.9444444
Min length1

Unique

Unique2 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 31
86.1%
0 3
 
8.3%
8000000 1
 
2.8%
10000000 1
 
2.8%

Length

2024-04-30T04:20:25.320538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:20:25.432154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
86.1%
0 3
 
8.3%
8000000 1
 
2.8%
10000000 1
 
2.8%

보험시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

보험종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

부대시설내역
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

시설규모
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)82.6%
Missing13
Missing (%)36.1%
Infinite0
Infinite (%)0.0%
Mean84.347826
Minimum0
Maximum162
Zeros2
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-30T04:20:25.552482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.7
Q162.5
median83
Q3111.5
95-th percentile136.3
Maximum162
Range162
Interquartile range (IQR)49

Descriptive statistics

Standard deviation40.085827
Coefficient of variation (CV)0.47524434
Kurtosis0.30583246
Mean84.347826
Median Absolute Deviation (MAD)25
Skewness-0.3985701
Sum1940
Variance1606.8735
MonotonicityNot monotonic
2024-04-30T04:20:25.715011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 2
 
5.6%
115 2
 
5.6%
80 2
 
5.6%
85 2
 
5.6%
82 1
 
2.8%
74 1
 
2.8%
67 1
 
2.8%
52 1
 
2.8%
105 1
 
2.8%
102 1
 
2.8%
Other values (9) 9
25.0%
(Missing) 13
36.1%
ValueCountFrequency (%)
0 2
5.6%
37 1
2.8%
52 1
2.8%
56 1
2.8%
58 1
2.8%
67 1
2.8%
74 1
2.8%
80 2
5.6%
82 1
2.8%
83 1
2.8%
ValueCountFrequency (%)
162 1
2.8%
137 1
2.8%
130 1
2.8%
127 1
2.8%
115 2
5.6%
108 1
2.8%
105 1
2.8%
102 1
2.8%
85 2
5.6%
83 1
2.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
03140000CDFI226221201200000220120809<NA>3폐업3폐업20170131<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916번지 목동현대하이페이온 102동 3807호서울특별시 양천구 목동동로 257, 102동 3807호 (목동, 목동현대하이페리온)<NA>현대하이페리온2017-01-31I2018-08-31 23:59:00.0<NA>188884.0756447186.8886외국인관광 도시민박업<NA>일반주거지역<NA>아파트지역<NA><NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>137.36<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>137
13140000CDFI226221201200000320120725<NA>3폐업3폐업20200320<NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 925 목동신시가지아파트7단지 721동 802호서울특별시 양천구 목동로 186, 721동 802호 (목동, 목동신시가지아파트7단지)8002O.K. House2023-07-24U2023-07-26 02:40:00.0<NA>188248.4543447406.3013외국인관광 도시민박업<NA>일반주거지역0<NA><NA><NA>아파트0020O.K. HouseTOURISM SERVICE FACILITIES BUSINESS CERTIFICATE OF REGISTRATION00<NA>00<NA>084.95<NA>0<NA><NA><NA><NA><NA><NA>0<NA><NA><NA>85
23140000CDFI226221201300000120130828<NA>3폐업3폐업20170124<NA><NA><NA><NA><NA>158-832서울특별시 양천구 신월동 416-1번지 보람아파트 102동 701호서울특별시 양천구 남부순환로67길 15, 102동 7층 701호 (신월동, 보람아파트)<NA>꿈을 이루는 집2017-01-24I2018-08-31 23:59:00.0<NA>185593.1935446956.5114외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>83.37<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>83
33140000CDFI226221201300000220130612<NA>3폐업3폐업20180601<NA><NA><NA>2651-1133<NA>158-808서울특별시 양천구 목동 513-22번지 서영빌라 601호서울특별시 양천구 목동중앙북로 83-1 (목동, 서영빌라 601호)<NA>Seoul 9102018-06-01I2018-08-31 23:59:00.0<NA>188670.7781449371.1897외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Seoul 910City accommodation business for foreign tourists<NA><NA><NA><NA><NA><NA><NA>127.2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>127
43140000CDFI226221201400000120140114<NA>3폐업3폐업20180420<NA><NA><NA><NA><NA>158-773서울특별시 양천구 신정동 328번지 목동신시가지아파트 1324동 102호서울특별시 양천구 목동동로 100, 1324동 102호 (신정동, 목동신시가지아파트)<NA>스위트홈2018-04-20I2018-08-31 23:59:00.0<NA>188234.648445887.4577외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>115.32<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>115
53140000CDFI226221201400000220141030<NA>3폐업3폐업20201207<NA><NA><NA><NA><NA>158-799서울특별시 양천구 신정동 1314 양천중앙하이츠아파트 103동 704호서울특별시 양천구 목동남로2길 60-7, 103동 704호 (신정동, 양천중앙하이츠아파트)<NA>진 아트하우스(Jin's Art House)2020-12-08U2020-12-10 02:40:00.0<NA>187879.6275444831.8478외국인관광 도시민박업<NA>일반주거지역15아파트지역<NA><NA>아파트1521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>162.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>162
63140000CDFI226221201400000320141202<NA>3폐업3폐업20170920<NA><NA><NA><NA><NA>158-070서울특별시 양천구 신정동 1297번지 길훈로즈빌 1201호서울특별시 양천구 목동동로 190, 1201호 (신정동)<NA>더브러2017-09-20I2018-08-31 23:59:00.0<NA>188554.9402446701.7451외국인관광 도시민박업<NA>주거지역<NA><NA><NA><NA>아파트<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>84.95<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>85
73140000CDFI226221201500000120150202<NA>3폐업3폐업20161101<NA><NA><NA><NA><NA>158-798서울특별시 양천구 신정동 1310번지서울특별시 양천구 신정로11길 20, 12층 1204호 (신정동)<NA>더그레이스(The Grace)2016-11-01I2018-08-31 23:59:00.0<NA>185706.4317445528.3059외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>115.32<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>115
83140000CDFI226221201500000220151120<NA>3폐업3폐업20161110<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 915-21번지 오성빌라 D동 102호서울특별시 양천구 중앙로52길 54, D동 102호 (신정동, 오성빌라)<NA>Jay's Home2016-11-11I2018-08-31 23:59:00.0<NA>187239.6278447091.0011외국인관광 도시민박업<NA>일반주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA>Jay's HomeTOURISM SERVICE FACLITIES<NA><NA><NA><NA><NA><NA><NA>37.4<NA><NA><NA><NA><NA><NA><NA><NA>8000000<NA><NA><NA>37
93140000CDFI226221201500000320151028<NA>3폐업3폐업20180501<NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 524-7번지서울특별시 양천구 목동중앙북로18길 25, 101동 401호 (목동, 디아인스1)<NA>코리안 프렌즈 게스트하우스2018-05-01I2018-08-31 23:59:00.0<NA>188905.616449219.2473외국인관광 도시민박업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>130.41<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>130
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)문화체육업종명문화사업자구분명지역구분명총층수주변환경명제작취급품목내용보험기관명건물용도명지상층수지하층수객실수건축연면적영문상호명영문상호주소선박총톤수선박척수선박제원무대면적좌석수기념품종류회의실별동시수용인원시설면적놀이기구수내역놀이시설수방송시설유무발전시설유무의무실유무안내소유무기획여행보험시작일자기획여행보험종료일자자본금보험시작일자보험종료일자부대시설내역시설규모
263140000CDFI22622120230000042023-08-02<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 879-6 상진아파트 102호서울특별시 양천구 은행정로 87, 102호 (신정동, 상진아파트)7939이레의집2023-09-26 11:00:21U2022-12-08 22:08:00.0<NA>187426.998472447284.783534<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
273140000CDFI22622120230000052023-09-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 127-32서울특별시 양천구 신목로2길 33-1 (신정동)8009STAY 유연하게2023-09-26 11:00:06U2022-12-08 22:08:00.0<NA>189033.127348446507.431632<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
283140000CDFI22622120230000062023-11-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 925 목동신시가지아파트7단지서울특별시 양천구 목동로 212, 706동 2층 206호 (목동, 목동신시가지아파트7단지)7993현2023-11-09 14:50:22I2022-10-31 23:01:00.0<NA>188248.454327447406.301288<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
293140000CDFI22622120230000072023-11-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 890-5서울특별시 양천구 목동로23길 14, 2층 202호 (신정동)7938M stay2024-01-04 11:18:01U2023-12-01 00:06:00.0<NA>187734.840273447261.452708<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
303140000CDFI22622120240000012024-01-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 516-9서울특별시 양천구 목동중앙북로 125-1, 3층 (목동)7968스테이 블리스2024-01-11 12:50:32I2023-11-30 23:03:00.0<NA>189078.224808449363.193668<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
313140000CDFI22622120240000022024-01-18<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 726-3서울특별시 양천구 목동중앙남로9가길 5, b01호 (목동)7958민어스하우스2024-01-18 16:51:50I2023-11-30 22:00:00.0<NA>188055.292889448401.782394<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
323140000CDFI22622120240000032024-01-30<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1190-13서울특별시 양천구 중앙로45길 2-8, B02호 (신정동)8058투게더스테이2024-01-30 14:20:53I2023-12-02 00:01:00.0<NA>186855.001383446497.899522<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
333140000CDFI22622120240000042024-02-23<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 875-5서울특별시 양천구 은행정로19가길 20, 지층 102호 (신정동)7939비밀공간2024-02-23 08:43:09I2023-12-01 22:05:00.0<NA>187240.62333447349.824391<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343140000CDFI22622120240000052024-03-15<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 553-26서울특별시 양천구 목동중앙본로27길 33-1, 1층 101호 (목동)7953달마을 스테이2024-03-15 17:26:11I2023-12-02 23:07:00.0<NA>188302.524537449096.254852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
353140000CDFI22622120240000062024-03-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 936-6서울특별시 양천구 은행정로17길 75-1, 102호 (신정동)7941무무스테이2024-03-19 18:06:46I2023-12-02 22:01:00.0<NA>186710.935819447247.841436<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>