Overview

Dataset statistics

Number of variables44
Number of observations62
Missing cells630
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 KiB
Average record size in memory377.1 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

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),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18315/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업장주변구분명 is highly imbalanced (63.9%)Imbalance
등급구분명 is highly imbalanced (58.4%)Imbalance
급수시설구분명 is highly imbalanced (72.0%)Imbalance
총인원 is highly imbalanced (88.1%)Imbalance
보증액 is highly imbalanced (70.8%)Imbalance
월세액 is highly imbalanced (70.8%)Imbalance
인허가취소일자 has 62 (100.0%) missing valuesMissing
폐업일자 has 26 (41.9%) missing valuesMissing
휴업시작일자 has 62 (100.0%) missing valuesMissing
휴업종료일자 has 62 (100.0%) missing valuesMissing
재개업일자 has 62 (100.0%) missing valuesMissing
전화번호 has 9 (14.5%) missing valuesMissing
소재지면적 has 2 (3.2%) missing valuesMissing
도로명주소 has 14 (22.6%) missing valuesMissing
도로명우편번호 has 15 (24.2%) missing valuesMissing
좌표정보(X) has 3 (4.8%) missing valuesMissing
좌표정보(Y) has 3 (4.8%) missing valuesMissing
남성종사자수 has 53 (85.5%) missing valuesMissing
여성종사자수 has 53 (85.5%) missing valuesMissing
다중이용업소여부 has 18 (29.0%) missing valuesMissing
전통업소지정번호 has 62 (100.0%) missing valuesMissing
전통업소주된음식 has 62 (100.0%) missing valuesMissing
홈페이지 has 62 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 has unique valuesUnique
최종수정일자 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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 2 (3.2%) zerosZeros
여성종사자수 has 2 (3.2%) zerosZeros

Reproduction

Analysis started2024-05-18 02:35:30.492205
Analysis finished2024-05-18 02:35:31.871509
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
3130000
62 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3130000 62
100.0%

Length

2024-05-18T11:35:32.065499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:32.429648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 62
100.0%

관리번호
Text

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-05-18T11:35:32.866188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1364
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)100.0%

Sample

1st row3130000-114-1995-00786
2nd row3130000-114-1996-00787
3rd row3130000-114-1996-00788
4th row3130000-114-1996-00789
5th row3130000-114-1996-00790
ValueCountFrequency (%)
3130000-114-1995-00786 1
 
1.6%
3130000-114-2015-00003 1
 
1.6%
3130000-114-2023-00001 1
 
1.6%
3130000-114-2010-00002 1
 
1.6%
3130000-114-2011-00001 1
 
1.6%
3130000-114-2012-00001 1
 
1.6%
3130000-114-2012-00002 1
 
1.6%
3130000-114-2012-00003 1
 
1.6%
3130000-114-2013-00001 1
 
1.6%
3130000-114-2013-00002 1
 
1.6%
Other values (52) 52
83.9%
2024-05-18T11:35:34.062629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 558
40.9%
1 246
18.0%
- 186
 
13.6%
3 143
 
10.5%
2 82
 
6.0%
4 69
 
5.1%
9 32
 
2.3%
7 16
 
1.2%
6 13
 
1.0%
8 11
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1178
86.4%
Dash Punctuation 186
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 558
47.4%
1 246
20.9%
3 143
 
12.1%
2 82
 
7.0%
4 69
 
5.9%
9 32
 
2.7%
7 16
 
1.4%
6 13
 
1.1%
8 11
 
0.9%
5 8
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 558
40.9%
1 246
18.0%
- 186
 
13.6%
3 143
 
10.5%
2 82
 
6.0%
4 69
 
5.1%
9 32
 
2.3%
7 16
 
1.2%
6 13
 
1.0%
8 11
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 558
40.9%
1 246
18.0%
- 186
 
13.6%
3 143
 
10.5%
2 82
 
6.0%
4 69
 
5.1%
9 32
 
2.3%
7 16
 
1.2%
6 13
 
1.0%
8 11
 
0.8%

인허가일자
Date

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum1995-09-23 00:00:00
Maximum2023-06-23 00:00:00
2024-05-18T11:35:34.584967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:35:35.132774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
3
36 
1
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 36
58.1%
1 26
41.9%

Length

2024-05-18T11:35:35.847701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:36.368691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 36
58.1%
1 26
41.9%

영업상태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
폐업
36 
영업/정상
26 

Length

Max length5
Median length2
Mean length3.2580645
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row영업/정상
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 36
58.1%
영업/정상 26
41.9%

Length

2024-05-18T11:35:37.133552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:37.679508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 36
58.1%
영업/정상 26
41.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
2
36 
1
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 36
58.1%
1 26
41.9%

Length

2024-05-18T11:35:38.210408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:38.794927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 36
58.1%
1 26
41.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
폐업
36 
영업
26 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 36
58.1%
영업 26
41.9%

Length

2024-05-18T11:35:39.342846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:39.993439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 36
58.1%
영업 26
41.9%

폐업일자
Date

MISSING 

Distinct35
Distinct (%)97.2%
Missing26
Missing (%)41.9%
Memory size628.0 B
Minimum2001-03-12 00:00:00
Maximum2024-04-16 00:00:00
2024-05-18T11:35:40.307607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:35:40.894057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

전화번호
Text

MISSING 

Distinct51
Distinct (%)96.2%
Missing9
Missing (%)14.5%
Memory size628.0 B
2024-05-18T11:35:41.564461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.358491
Min length7

Characters and Unicode

Total characters549
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)92.5%

Sample

1st row02 3202622
2nd row02 3043448
3rd row02 7180084
4th row02 3237541
5th row02 3760037
ValueCountFrequency (%)
02 42
40.4%
3237541 2
 
1.9%
0232751480 2
 
1.9%
335 1
 
1.0%
31440826 1
 
1.0%
3372678 1
 
1.0%
7014482 1
 
1.0%
373 1
 
1.0%
2233 1
 
1.0%
701 1
 
1.0%
Other values (51) 51
49.0%
2024-05-18T11:35:42.617148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 103
18.8%
0 94
17.1%
67
12.2%
3 56
10.2%
7 55
10.0%
1 45
8.2%
4 33
 
6.0%
8 32
 
5.8%
5 24
 
4.4%
6 23
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 482
87.8%
Space Separator 67
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 103
21.4%
0 94
19.5%
3 56
11.6%
7 55
11.4%
1 45
9.3%
4 33
 
6.8%
8 32
 
6.6%
5 24
 
5.0%
6 23
 
4.8%
9 17
 
3.5%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 103
18.8%
0 94
17.1%
67
12.2%
3 56
10.2%
7 55
10.0%
1 45
8.2%
4 33
 
6.0%
8 32
 
5.8%
5 24
 
4.4%
6 23
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 103
18.8%
0 94
17.1%
67
12.2%
3 56
10.2%
7 55
10.0%
1 45
8.2%
4 33
 
6.0%
8 32
 
5.8%
5 24
 
4.4%
6 23
 
4.2%

소재지면적
Text

MISSING 

Distinct59
Distinct (%)98.3%
Missing2
Missing (%)3.2%
Memory size628.0 B
2024-05-18T11:35:43.161254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2666667
Min length6

Characters and Unicode

Total characters376
Distinct characters12
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

Unique58 ?
Unique (%)96.7%

Sample

1st row1,423.51
2nd row616.45
3rd row505.44
4th row376.02
5th row400.45
ValueCountFrequency (%)
477.69 2
 
3.3%
441.87 1
 
1.7%
1,423.51 1
 
1.7%
1131.66 1
 
1.7%
5910.77 1
 
1.7%
330.00 1
 
1.7%
382.70 1
 
1.7%
7177.00 1
 
1.7%
478.70 1
 
1.7%
596.00 1
 
1.7%
Other values (49) 49
81.7%
2024-05-18T11:35:44.401568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 67
17.8%
. 60
16.0%
6 40
10.6%
4 36
9.6%
7 34
9.0%
5 26
 
6.9%
3 26
 
6.9%
1 24
 
6.4%
8 22
 
5.9%
9 20
 
5.3%
Other values (2) 21
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 312
83.0%
Other Punctuation 64
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
21.5%
6 40
12.8%
4 36
11.5%
7 34
10.9%
5 26
 
8.3%
3 26
 
8.3%
1 24
 
7.7%
8 22
 
7.1%
9 20
 
6.4%
2 17
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 60
93.8%
, 4
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 67
17.8%
. 60
16.0%
6 40
10.6%
4 36
9.6%
7 34
9.0%
5 26
 
6.9%
3 26
 
6.9%
1 24
 
6.4%
8 22
 
5.9%
9 20
 
5.3%
Other values (2) 21
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 67
17.8%
. 60
16.0%
6 40
10.6%
4 36
9.6%
7 34
9.0%
5 26
 
6.9%
3 26
 
6.9%
1 24
 
6.4%
8 22
 
5.9%
9 20
 
5.3%
Other values (2) 21
 
5.6%

소재지우편번호
Text

Distinct46
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-05-18T11:35:45.168903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2580645
Min length6

Characters and Unicode

Total characters388
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)58.1%

Sample

1st row121807
2nd row121-850
3rd row121813
4th row121827
5th row121877
ValueCountFrequency (%)
121827 5
 
8.1%
121010 3
 
4.8%
121-849 3
 
4.8%
121875 3
 
4.8%
121849 2
 
3.2%
121830 2
 
3.2%
121-807 2
 
3.2%
121811 2
 
3.2%
121814 2
 
3.2%
121876 2
 
3.2%
Other values (36) 36
58.1%
2024-05-18T11:35:46.220912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 146
37.6%
2 75
19.3%
8 53
 
13.7%
0 23
 
5.9%
7 22
 
5.7%
- 16
 
4.1%
4 15
 
3.9%
9 13
 
3.4%
5 11
 
2.8%
6 8
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 372
95.9%
Dash Punctuation 16
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 146
39.2%
2 75
20.2%
8 53
 
14.2%
0 23
 
6.2%
7 22
 
5.9%
4 15
 
4.0%
9 13
 
3.5%
5 11
 
3.0%
6 8
 
2.2%
3 6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 388
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 146
37.6%
2 75
19.3%
8 53
 
13.7%
0 23
 
5.9%
7 22
 
5.7%
- 16
 
4.1%
4 15
 
3.9%
9 13
 
3.4%
5 11
 
2.8%
6 8
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 146
37.6%
2 75
19.3%
8 53
 
13.7%
0 23
 
5.9%
7 22
 
5.7%
- 16
 
4.1%
4 15
 
3.9%
9 13
 
3.4%
5 11
 
2.8%
6 8
 
2.1%

지번주소
Text

Distinct60
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-05-18T11:35:47.040960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length25.112903
Min length17

Characters and Unicode

Total characters1557
Distinct characters123
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

Unique58 ?
Unique (%)93.5%

Sample

1st row서울특별시 마포구 노고산동 57-1 지하1.2층
2nd row서울특별시 마포구 성산동 446 제1상가 001호
3rd row서울특별시 마포구 도화동 251-1 1층
4th row서울특별시 마포구 망원동 478-11 지층1층
5th row서울특별시 마포구 중동 64-25 지층9-46호.51호
ValueCountFrequency (%)
서울특별시 62
19.8%
마포구 62
19.8%
성산동 9
 
2.9%
도화동 8
 
2.6%
1층 8
 
2.6%
망원동 6
 
1.9%
아현동 5
 
1.6%
용강동 5
 
1.6%
상암동 5
 
1.6%
서교동 4
 
1.3%
Other values (111) 139
44.4%
2024-05-18T11:35:48.088230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
295
18.9%
1 90
 
5.8%
동 69
 
4.4%
서 67
 
4.3%
마 65
 
4.2%
포 64
 
4.1%
구 63
 
4.0%
특 62
 
4.0%
별 62
 
4.0%
시 62
 
4.0%
Other values (113) 658
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 906
58.2%
Space Separator 295
 
18.9%
Decimal Number 294
 
18.9%
Dash Punctuation 42
 
2.7%
Other Punctuation 7
 
0.4%
Uppercase Letter 7
 
0.4%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 69
 
7.6%
서 67
 
7.4%
마 65
 
7.2%
포 64
 
7.1%
구 63
 
7.0%
특 62
 
6.8%
별 62
 
6.8%
시 62
 
6.8%
울 62
 
6.8%
층 22
 
2.4%
Other values (93) 308
34.0%
Decimal Number
ValueCountFrequency (%)
1 90
30.6%
3 33
 
11.2%
2 27
 
9.2%
0 24
 
8.2%
5 24
 
8.2%
7 24
 
8.2%
4 21
 
7.1%
8 21
 
7.1%
9 16
 
5.4%
6 14
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
P 1
 
14.3%
T 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 5
71.4%
. 2
 
28.6%
Space Separator
ValueCountFrequency (%)
295
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 906
58.2%
Common 644
41.4%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 69
 
7.6%
서 67
 
7.4%
마 65
 
7.2%
포 64
 
7.1%
구 63
 
7.0%
특 62
 
6.8%
별 62
 
6.8%
시 62
 
6.8%
울 62
 
6.8%
층 22
 
2.4%
Other values (93) 308
34.0%
Common
ValueCountFrequency (%)
295
45.8%
1 90
 
14.0%
- 42
 
6.5%
3 33
 
5.1%
2 27
 
4.2%
0 24
 
3.7%
5 24
 
3.7%
7 24
 
3.7%
4 21
 
3.3%
8 21
 
3.3%
Other values (6) 43
 
6.7%
Latin
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
P 1
 
14.3%
T 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 906
58.2%
ASCII 651
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
295
45.3%
1 90
 
13.8%
- 42
 
6.5%
3 33
 
5.1%
2 27
 
4.1%
0 24
 
3.7%
5 24
 
3.7%
7 24
 
3.7%
4 21
 
3.2%
8 21
 
3.2%
Other values (10) 50
 
7.7%
Hangul
ValueCountFrequency (%)
동 69
 
7.6%
서 67
 
7.4%
마 65
 
7.2%
포 64
 
7.1%
구 63
 
7.0%
특 62
 
6.8%
별 62
 
6.8%
시 62
 
6.8%
울 62
 
6.8%
층 22
 
2.4%
Other values (93) 308
34.0%

도로명주소
Text

MISSING 

Distinct48
Distinct (%)100.0%
Missing14
Missing (%)22.6%
Memory size628.0 B
2024-05-18T11:35:48.672058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length48.5
Mean length35.625
Min length22

Characters and Unicode

Total characters1710
Distinct characters148
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

Unique48 ?
Unique (%)100.0%

Sample

1st row서울특별시 마포구 신촌로 94 (노고산동, 지하1.2층)
2nd row서울특별시 마포구 월드컵북로 233 (성산동, 제1상가 001호)
3rd row서울특별시 마포구 삼개로 20 (도화동, 1층)
4th row서울특별시 마포구 월드컵북로 230 (중동, 지층9-46호.51호)
5th row서울특별시 마포구 신촌로 66 (노고산동)
ValueCountFrequency (%)
서울특별시 48
 
15.0%
마포구 48
 
15.0%
1층 17
 
5.3%
월드컵북로 9
 
2.8%
성산동 8
 
2.5%
상암동 5
 
1.6%
아현동 5
 
1.6%
큰우물로 4
 
1.2%
서교동 4
 
1.2%
용강동 4
 
1.2%
Other values (130) 169
52.6%
2024-05-18T11:35:49.685951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
 
16.1%
1 80
 
4.7%
, 67
 
3.9%
동 56
 
3.3%
마 55
 
3.2%
포 54
 
3.2%
서 53
 
3.1%
( 50
 
2.9%
) 50
 
2.9%
구 49
 
2.9%
Other values (138) 921
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 973
56.9%
Space Separator 275
 
16.1%
Decimal Number 269
 
15.7%
Other Punctuation 69
 
4.0%
Open Punctuation 50
 
2.9%
Close Punctuation 50
 
2.9%
Uppercase Letter 10
 
0.6%
Dash Punctuation 8
 
0.5%
Math Symbol 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 56
 
5.8%
마 55
 
5.7%
포 54
 
5.5%
서 53
 
5.4%
구 49
 
5.0%
시 49
 
5.0%
울 48
 
4.9%
별 48
 
4.9%
특 48
 
4.9%
로 45
 
4.6%
Other values (117) 468
48.1%
Decimal Number
ValueCountFrequency (%)
1 80
29.7%
2 45
16.7%
0 28
 
10.4%
3 26
 
9.7%
5 20
 
7.4%
4 18
 
6.7%
6 16
 
5.9%
9 12
 
4.5%
7 12
 
4.5%
8 12
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 6
60.0%
A 2
 
20.0%
P 1
 
10.0%
T 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 67
97.1%
. 2
 
2.9%
Space Separator
ValueCountFrequency (%)
275
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 973
56.9%
Common 727
42.5%
Latin 10
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 56
 
5.8%
마 55
 
5.7%
포 54
 
5.5%
서 53
 
5.4%
구 49
 
5.0%
시 49
 
5.0%
울 48
 
4.9%
별 48
 
4.9%
특 48
 
4.9%
로 45
 
4.6%
Other values (117) 468
48.1%
Common
ValueCountFrequency (%)
275
37.8%
1 80
 
11.0%
, 67
 
9.2%
( 50
 
6.9%
) 50
 
6.9%
2 45
 
6.2%
0 28
 
3.9%
3 26
 
3.6%
5 20
 
2.8%
4 18
 
2.5%
Other values (7) 68
 
9.4%
Latin
ValueCountFrequency (%)
B 6
60.0%
A 2
 
20.0%
P 1
 
10.0%
T 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 973
56.9%
ASCII 737
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
37.3%
1 80
 
10.9%
, 67
 
9.1%
( 50
 
6.8%
) 50
 
6.8%
2 45
 
6.1%
0 28
 
3.8%
3 26
 
3.5%
5 20
 
2.7%
4 18
 
2.4%
Other values (11) 78
 
10.6%
Hangul
ValueCountFrequency (%)
동 56
 
5.8%
마 55
 
5.7%
포 54
 
5.5%
서 53
 
5.4%
구 49
 
5.0%
시 49
 
5.0%
울 48
 
4.9%
별 48
 
4.9%
특 48
 
4.9%
로 45
 
4.6%
Other values (117) 468
48.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)78.7%
Missing15
Missing (%)24.2%
Infinite0
Infinite (%)0.0%
Mean4054.2766
Minimum3901
Maximum4209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-05-18T11:35:50.165039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3901
5-th percentile3920.7
Q13964
median4058
Q34148
95-th percentile4195.4
Maximum4209
Range308
Interquartile range (IQR)184

Descriptive statistics

Standard deviation96.888708
Coefficient of variation (CV)0.023897903
Kurtosis-1.4280969
Mean4054.2766
Median Absolute Deviation (MAD)94
Skewness0.0061233855
Sum190551
Variance9387.4218
MonotonicityNot monotonic
2024-05-18T11:35:50.579365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
4166 3
 
4.8%
3949 2
 
3.2%
4117 2
 
3.2%
4088 2
 
3.2%
3918 2
 
3.2%
3930 2
 
3.2%
3964 2
 
3.2%
4002 2
 
3.2%
4058 2
 
3.2%
4087 1
 
1.6%
Other values (27) 27
43.5%
(Missing) 15
24.2%
ValueCountFrequency (%)
3901 1
1.6%
3918 2
3.2%
3927 1
1.6%
3930 2
3.2%
3932 1
1.6%
3936 1
1.6%
3941 1
1.6%
3949 2
3.2%
3964 2
3.2%
3966 1
1.6%
ValueCountFrequency (%)
4209 1
 
1.6%
4203 1
 
1.6%
4196 1
 
1.6%
4194 1
 
1.6%
4180 1
 
1.6%
4173 1
 
1.6%
4166 3
4.8%
4163 1
 
1.6%
4152 1
 
1.6%
4150 1
 
1.6%

사업장명
Text

Distinct60
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
2024-05-18T11:35:51.232645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.516129
Min length3

Characters and Unicode

Total characters528
Distinct characters133
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

Unique58 ?
Unique (%)93.5%

Sample

1st row그랜드백화점(주)마트신촌점
2nd row(주)농협유통 하나로마트 성산점
3rd row에스 마트(S Mart)
4th row(주)페트라마켓
5th row성산마트( K-super )
ValueCountFrequency (%)
하나로마트 4
 
4.3%
마포점 4
 
4.3%
서서울농협 2
 
2.2%
홈플러스익스프레스 2
 
2.2%
주식회사 2
 
2.2%
신촌점 2
 
2.2%
시티식자재마트 2
 
2.2%
주)퍼브릭마트 2
 
2.2%
상암점 2
 
2.2%
홈플러스 2
 
2.2%
Other values (67) 68
73.9%
2024-05-18T11:35:52.170555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 57
 
10.8%
트 46
 
8.7%
30
 
5.7%
) 21
 
4.0%
( 21
 
4.0%
점 19
 
3.6%
주 19
 
3.6%
스 16
 
3.0%
서 8
 
1.5%
농 8
 
1.5%
Other values (123) 283
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 439
83.1%
Space Separator 30
 
5.7%
Close Punctuation 21
 
4.0%
Open Punctuation 21
 
4.0%
Lowercase Letter 8
 
1.5%
Uppercase Letter 7
 
1.3%
Dash Punctuation 1
 
0.2%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 57
 
13.0%
트 46
 
10.5%
점 19
 
4.3%
주 19
 
4.3%
스 16
 
3.6%
서 8
 
1.8%
농 8
 
1.8%
포 8
 
1.8%
로 7
 
1.6%
인 7
 
1.6%
Other values (106) 244
55.6%
Lowercase Letter
ValueCountFrequency (%)
r 2
25.0%
a 1
12.5%
t 1
12.5%
s 1
12.5%
u 1
12.5%
p 1
12.5%
e 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
K 2
28.6%
I 1
14.3%
G 1
14.3%
M 1
14.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 439
83.1%
Common 74
 
14.0%
Latin 15
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 57
 
13.0%
트 46
 
10.5%
점 19
 
4.3%
주 19
 
4.3%
스 16
 
3.6%
서 8
 
1.8%
농 8
 
1.8%
포 8
 
1.8%
로 7
 
1.6%
인 7
 
1.6%
Other values (106) 244
55.6%
Latin
ValueCountFrequency (%)
S 2
13.3%
r 2
13.3%
K 2
13.3%
I 1
6.7%
G 1
6.7%
M 1
6.7%
a 1
6.7%
t 1
6.7%
s 1
6.7%
u 1
6.7%
Other values (2) 2
13.3%
Common
ValueCountFrequency (%)
30
40.5%
) 21
28.4%
( 21
28.4%
- 1
 
1.4%
2 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 439
83.1%
ASCII 89
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 57
 
13.0%
트 46
 
10.5%
점 19
 
4.3%
주 19
 
4.3%
스 16
 
3.6%
서 8
 
1.8%
농 8
 
1.8%
포 8
 
1.8%
로 7
 
1.6%
인 7
 
1.6%
Other values (106) 244
55.6%
ASCII
ValueCountFrequency (%)
30
33.7%
) 21
23.6%
( 21
23.6%
S 2
 
2.2%
r 2
 
2.2%
K 2
 
2.2%
I 1
 
1.1%
G 1
 
1.1%
M 1
 
1.1%
a 1
 
1.1%
Other values (7) 7
 
7.9%

최종수정일자
Date

UNIQUE 

Distinct62
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum1999-09-10 00:00:00
Maximum2024-04-16 17:20:52
2024-05-18T11:35:52.580297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:35:53.028710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
I
32 
U
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 32
51.6%
U 30
48.4%

Length

2024-05-18T11:35:53.464221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:53.698984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 32
51.6%
u 30
48.4%

데이터갱신일자
Date

Distinct31
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size628.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-18T11:35:54.006226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:35:54.406640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size628.0 B
기타식품판매업
62 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 62
100.0%

Length

2024-05-18T11:35:54.805096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:55.109980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 62
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)74.6%
Missing3
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean193622.87
Minimum189315.31
Maximum196362.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-05-18T11:35:55.421335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189315.31
5-th percentile190683.6
Q1192032.83
median194236.73
Q3195243.88
95-th percentile196007.23
Maximum196362.55
Range7047.2367
Interquartile range (IQR)3211.0514

Descriptive statistics

Standard deviation1935.7616
Coefficient of variation (CV)0.0099975876
Kurtosis-1.0004494
Mean193622.87
Median Absolute Deviation (MAD)1615.7896
Skewness-0.42795574
Sum11423749
Variance3747172.8
MonotonicityNot monotonic
2024-05-18T11:35:55.857930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
191685.792779705 3
 
4.8%
195012.011289058 2
 
3.2%
192207.639914367 2
 
3.2%
196043.165226453 2
 
3.2%
194236.734674521 2
 
3.2%
190707.026133738 2
 
3.2%
191651.529315787 2
 
3.2%
192577.990805265 2
 
3.2%
194648.759340948 2
 
3.2%
195669.217619713 2
 
3.2%
Other values (34) 38
61.3%
(Missing) 3
 
4.8%
ValueCountFrequency (%)
189315.310470024 1
 
1.6%
189343.04418441 1
 
1.6%
190472.811962108 1
 
1.6%
190707.026133738 2
3.2%
190931.000875925 2
3.2%
191263.451931121 1
 
1.6%
191435.876990887 1
 
1.6%
191651.529315787 2
3.2%
191685.792779705 3
4.8%
191858.011461839 1
 
1.6%
ValueCountFrequency (%)
196362.54713488 1
1.6%
196043.165226453 2
3.2%
196003.236176187 1
1.6%
196002.238594738 1
1.6%
195874.639172861 1
1.6%
195852.524254164 1
1.6%
195829.955210361 1
1.6%
195808.904523588 1
1.6%
195669.217619713 2
3.2%
195564.375757848 1
1.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)74.6%
Missing3
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean450138.99
Minimum448236.66
Maximum453647.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-05-18T11:35:56.464500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448236.66
5-th percentile448468.54
Q1449133.5
median449860.58
Q3450778.22
95-th percentile452629.45
Maximum453647.19
Range5410.5354
Interquartile range (IQR)1644.7248

Descriptive statistics

Standard deviation1343.3892
Coefficient of variation (CV)0.0029843875
Kurtosis0.08382775
Mean450138.99
Median Absolute Deviation (MAD)917.64601
Skewness0.79693812
Sum26558200
Variance1804694.5
MonotonicityNot monotonic
2024-05-18T11:35:56.960274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
450778.221420561 3
 
4.8%
448867.238362701 2
 
3.2%
451600.397676312 2
 
3.2%
450175.069333285 2
 
3.2%
449243.162717684 2
 
3.2%
452612.042328463 2
 
3.2%
450694.803472189 2
 
3.2%
450569.670545853 2
 
3.2%
449239.314703653 2
 
3.2%
448393.658663222 2
 
3.2%
Other values (34) 38
61.3%
(Missing) 3
 
4.8%
ValueCountFrequency (%)
448236.655548283 1
1.6%
448393.658663222 2
3.2%
448476.859046692 1
1.6%
448575.779442887 1
1.6%
448644.311298762 1
1.6%
448652.176751796 1
1.6%
448757.883381233 2
3.2%
448802.592741882 1
1.6%
448867.238362701 2
3.2%
448910.741283532 1
1.6%
ValueCountFrequency (%)
453647.190988422 1
1.6%
453624.945221014 1
1.6%
452786.073622541 1
1.6%
452612.042328463 2
3.2%
452207.500653521 1
1.6%
451990.707795053 1
1.6%
451600.397676312 2
3.2%
451427.722144609 2
3.2%
451124.615897058 1
1.6%
451088.79724231 1
1.6%

위생업태명
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
기타식품판매업
44 
<NA>
18 

Length

Max length7
Median length7
Mean length6.1290323
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 44
71.0%
<NA> 18
29.0%

Length

2024-05-18T11:35:57.385899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:57.627292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 44
71.0%
na 18
29.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)66.7%
Missing53
Missing (%)85.5%
Infinite0
Infinite (%)0.0%
Mean4
Minimum0
Maximum12
Zeros2
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-05-18T11:35:57.923586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q35
95-th percentile9.6
Maximum12
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.7080992
Coefficient of variation (CV)0.92702481
Kurtosis2.0958678
Mean4
Median Absolute Deviation (MAD)2
Skewness1.1536698
Sum36
Variance13.75
MonotonicityNot monotonic
2024-05-18T11:35:58.125809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 3
 
4.8%
0 2
 
3.2%
12 1
 
1.6%
1 1
 
1.6%
6 1
 
1.6%
5 1
 
1.6%
(Missing) 53
85.5%
ValueCountFrequency (%)
0 2
3.2%
1 1
 
1.6%
4 3
4.8%
5 1
 
1.6%
6 1
 
1.6%
12 1
 
1.6%
ValueCountFrequency (%)
12 1
 
1.6%
6 1
 
1.6%
5 1
 
1.6%
4 3
4.8%
1 1
 
1.6%
0 2
3.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)77.8%
Missing53
Missing (%)85.5%
Infinite0
Infinite (%)0.0%
Mean11.555556
Minimum0
Maximum41
Zeros2
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size690.0 B
2024-05-18T11:35:58.343184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median8
Q313
95-th percentile31.4
Maximum41
Range41
Interquartile range (IQR)6

Descriptive statistics

Standard deviation12.350214
Coefficient of variation (CV)1.0687685
Kurtosis4.5151154
Mean11.555556
Median Absolute Deviation (MAD)5
Skewness1.908671
Sum104
Variance152.52778
MonotonicityNot monotonic
2024-05-18T11:35:58.561823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
7 2
 
3.2%
0 2
 
3.2%
13 1
 
1.6%
8 1
 
1.6%
17 1
 
1.6%
11 1
 
1.6%
41 1
 
1.6%
(Missing) 53
85.5%
ValueCountFrequency (%)
0 2
3.2%
7 2
3.2%
8 1
1.6%
11 1
1.6%
13 1
1.6%
17 1
1.6%
41 1
1.6%
ValueCountFrequency (%)
41 1
1.6%
17 1
1.6%
13 1
1.6%
11 1
1.6%
8 1
1.6%
7 2
3.2%
0 2
3.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
54 
기타
 
5
주택가주변
 
2
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9354839
Min length2

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 54
87.1%
기타 5
 
8.1%
주택가주변 2
 
3.2%
유흥업소밀집지역 1
 
1.6%

Length

2024-05-18T11:35:58.913867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:59.130840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
87.1%
기타 5
 
8.1%
주택가주변 2
 
3.2%
유흥업소밀집지역 1
 
1.6%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
54 
기타
6 
우수
 
2

Length

Max length4
Median length4
Mean length3.7419355
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 54
87.1%
기타 6
 
9.7%
우수 2
 
3.2%

Length

2024-05-18T11:35:59.526661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:35:59.804698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
87.1%
기타 6
 
9.7%
우수 2
 
3.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
59 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.0483871
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
95.2%
상수도전용 3
 
4.8%

Length

2024-05-18T11:36:00.217917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:00.425253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
95.2%
상수도전용 3
 
4.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
61 
0
 
1

Length

Max length4
Median length4
Mean length3.9516129
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 61
98.4%
0 1
 
1.6%

Length

2024-05-18T11:36:00.733794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:01.059700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
98.4%
0 1
 
1.6%

본사종업원수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
46 
0
16 

Length

Max length4
Median length4
Mean length3.2258065
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
74.2%
0 16
 
25.8%

Length

2024-05-18T11:36:01.422175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:01.747135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
74.2%
0 16
 
25.8%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
46 
0
16 

Length

Max length4
Median length4
Mean length3.2258065
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
74.2%
0 16
 
25.8%

Length

2024-05-18T11:36:02.113801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:02.444322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
74.2%
0 16
 
25.8%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
46 
0
16 

Length

Max length4
Median length4
Mean length3.2258065
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
74.2%
0 16
 
25.8%

Length

2024-05-18T11:36:02.769959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:03.083539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
74.2%
0 16
 
25.8%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
46 
0
16 

Length

Max length4
Median length4
Mean length3.2258065
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
74.2%
0 16
 
25.8%

Length

2024-05-18T11:36:03.474478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:03.841164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
74.2%
0 16
 
25.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
37 
임대
19 
자가
6 

Length

Max length4
Median length4
Mean length3.1935484
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 37
59.7%
임대 19
30.6%
자가 6
 
9.7%

Length

2024-05-18T11:36:04.396479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:04.806211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 37
59.7%
임대 19
30.6%
자가 6
 
9.7%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
57 
0
 
4
500000000
 
1

Length

Max length9
Median length4
Mean length3.8870968
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 57
91.9%
0 4
 
6.5%
500000000 1
 
1.6%

Length

2024-05-18T11:36:05.182214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:05.633562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
91.9%
0 4
 
6.5%
500000000 1
 
1.6%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
<NA>
57 
0
 
4
18000000
 
1

Length

Max length8
Median length4
Mean length3.8709677
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 57
91.9%
0 4
 
6.5%
18000000 1
 
1.6%

Length

2024-05-18T11:36:06.122058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:06.509088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
91.9%
0 4
 
6.5%
18000000 1
 
1.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.3%
Missing18
Missing (%)29.0%
Memory size256.0 B
False
44 
(Missing)
18 
ValueCountFrequency (%)
False 44
71.0%
(Missing) 18
29.0%
2024-05-18T11:36:06.828964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size628.0 B
0
43 
<NA>
18 
370
 
1

Length

Max length4
Median length1
Mean length1.9032258
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 43
69.4%
<NA> 18
29.0%
370 1
 
1.6%

Length

2024-05-18T11:36:07.308518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:36:07.921713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 43
69.4%
na 18
29.0%
370 1
 
1.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing62
Missing (%)100.0%
Memory size690.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031300003130000-114-1995-0078619950923<NA>3폐업2폐업20180927<NA><NA><NA>02 32026221,423.51121807서울특별시 마포구 노고산동 57-1 지하1.2층서울특별시 마포구 신촌로 94 (노고산동, 지하1.2층)4058그랜드백화점(주)마트신촌점2018-09-27 13:38:12I2018-08-31 23:59:59.0기타식품판매업194273.598099450318.72413기타식품판매업1213유흥업소밀집지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
131300003130000-114-1996-007871996-06-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 3043448616.45121-850서울특별시 마포구 성산동 446 제1상가 001호서울특별시 마포구 월드컵북로 233 (성산동, 제1상가 001호)3936(주)농협유통 하나로마트 성산점2024-04-08 15:26:43U2023-12-03 23:02:00.0기타식품판매업191263.451931452207.500654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231300003130000-114-1996-0078819960711<NA>1영업/정상1영업<NA><NA><NA><NA>02 7180084505.44121813서울특별시 마포구 도화동 251-1 1층서울특별시 마포구 삼개로 20 (도화동, 1층)4173에스 마트(S Mart)2021-07-21 13:21:45U2021-07-23 02:40:00.0기타식품판매업195254.758705448476.859047기타식품판매업17기타기타<NA><NA>0000<NA><NA><NA>N0<NA><NA><NA>
331300003130000-114-1996-0078919960725<NA>3폐업2폐업20030404<NA><NA><NA>02 3237541376.02121827서울특별시 마포구 망원동 478-11 지층1층<NA><NA>(주)페트라마켓2001-10-05 00:00:00I2018-08-31 23:59:59.0기타식품판매업191685.79278450778.221421기타식품판매업68기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
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531300003130000-114-1996-007911996-09-20<NA>1영업/정상1영업<NA><NA><NA><NA>02213112121825.29121-807서울특별시 마포구 노고산동 49-31서울특별시 마포구 신촌로 66 (노고산동)4057(주)농협하나로유통 하나로마트 신촌점2024-04-03 17:38:26U2023-12-04 00:05:00.0기타식품판매업194020.023177450426.583344<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
631300003130000-114-1998-0079219980915<NA>3폐업2폐업20020307<NA><NA><NA>02 37602901,679.82121849서울특별시 마포구 성산동 533-1 1층<NA><NA>마포마트1999-12-02 00:00:00I2018-08-31 23:59:59.0기타식품판매업190931.000876451427.722145기타식품판매업417기타우수<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
731300003130000-114-1998-0079319981116<NA>3폐업2폐업20010312<NA><NA><NA>02 7151717436.53121815서울특별시 마포구 도화동 550-0 삼성(아)상가동 지층101<NA><NA>(주)장선하우징2001-03-19 00:00:00I2018-08-31 23:59:59.0기타식품판매업195542.119523448652.176752기타식품판매업47주택가주변우수<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
831300003130000-114-1999-0075019990910<NA>3폐업2폐업20091013<NA><NA><NA>02 3372677414.83121827서울특별시 마포구 망원동 480-1 (1층)<NA><NA>(주)퍼브릭마트1999-09-10 00:00:00I2018-08-31 23:59:59.0기타식품판매업<NA><NA>기타식품판매업411주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
931300003130000-114-2000-0096720001123<NA>3폐업2폐업20201105<NA><NA><NA>02 3221001561.18121816서울특별시 마포구 동교동 113-3서울특별시 마포구 연희로 25-1 (동교동)3985서아통상(주)2020-11-05 16:45:49U2020-11-07 02:40:00.0기타식품판매업193438.005329451002.268909기타식품판매업541기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
5231300003130000-114-2018-0000120180321<NA>3폐업2폐업20200107<NA><NA><NA><NA>396.40121830서울특별시 마포구 상암동 31-6 2층서울특별시 마포구 월드컵북로 328, 세움테크사옥 (상암동)3930(주)한국유통농축산물센터2020-01-07 09:35:22U2020-01-09 02:40:00.0기타식품판매업190707.026134452612.042328기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N370<NA><NA><NA>
5331300003130000-114-2019-0000120190214<NA>3폐업2폐업20200701<NA><NA><NA><NA>716.20121010서울특별시 마포구 아현동 780 애오개아이파크서울특별시 마포구 굴레방로1길 25, 지하2층 101호~102호 (아현동, 애오개아이파크)4117한울마트2020-07-06 10:43:35U2020-07-08 02:40:00.0기타식품판매업196043.165226450175.069333기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0<NA><NA><NA>
5431300003130000-114-2019-000022019-10-10<NA>3폐업2폐업2023-08-03<NA><NA><NA>0232751480333.00121-856서울특별시 마포구 신수동 288-1서울특별시 마포구 토정로17길 17, 1층 (신수동)4088신수할인마트2023-08-03 13:12:57U2022-12-08 00:05:00.0기타식품판매업194236.734675449243.162718<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5531300003130000-114-2019-0000320191025<NA>3폐업2폐업20201211<NA><NA><NA><NA>676.94121843서울특별시 마포구 성산동 41-7서울특별시 마포구 월드컵북로 97, 지하2층~3층 (성산동)3966주식회사 천해마2020-12-11 16:49:29U2020-12-13 02:40:00.0기타식품판매업192366.166346451088.797242기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0<NA><NA><NA>
5631300003130000-114-2020-000012020-06-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2530.16121-807서울특별시 마포구 노고산동 57-1 그랜드플라자서울특별시 마포구 신촌로 94, 지하1~3층 (노고산동)4058이마트 신촌점2024-04-15 15:18:31U2023-12-03 23:07:00.0기타식품판매업194273.598099450318.72413<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5731300003130000-114-2020-000022020-07-02<NA>3폐업2폐업2023-03-31<NA><NA><NA>02 31440826554.88121-841서울특별시 마포구 서교동 487 서교동 대우미래사랑서울특별시 마포구 월드컵북로5나길 18, 1층 113~126,136~137호 (서교동, 서교동 대우미래사랑)4002(주)대우농수산마트2023-03-31 15:07:33U2022-12-04 00:02:00.0기타식품판매업192577.990805450569.670546<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5831300003130000-114-2021-0000120210122<NA>3폐업2폐업20211001<NA><NA><NA>02 61065914449.00121844서울특별시 마포구 성산동 114-3 성산동 성일 APT서울특별시 마포구 월드컵북로 98, 1층 (성산동, 성산동 성일 APT)3978요마트 마포점2021-10-01 13:35:49U2021-10-03 02:40:00.0기타식품판매업192403.199513451124.615897기타식품판매업00<NA><NA><NA>00000임대00N0<NA><NA><NA>
5931300003130000-114-2021-0000220210720<NA>1영업/정상1영업<NA><NA><NA><NA>02 335 1158700.00121886서울특별시 마포구 합정동 395-3서울특별시 마포구 월드컵로3길 76, 1층 (합정동)4020주식회사 윈플러스마트서부 마포점2022-10-14 10:30:09U2021-10-30 23:06:00.0기타식품판매업191858.011462449691.888105<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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6131300003130000-114-2023-000022023-06-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>365.95121-849서울특별시 마포구 성산동 99-1서울특별시 마포구 모래내로 87, B동 1층 (성산동)3949시티식자재마트2023-06-23 14:29:55I2022-12-05 22:05:00.0기타식품판매업192207.639914451600.397676<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>