Overview

Dataset statistics

Number of variables44
Number of observations58
Missing cells446
Missing cells (%)17.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.4 KiB
Average record size in memory377.3 B

Variable types

Categorical22
Text7
DateTime4
Unsupported6
Numeric4
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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18314/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (87.4%)Imbalance
등급구분명 is highly imbalanced (53.1%)Imbalance
총인원 is highly imbalanced (57.6%)Imbalance
보증액 is highly imbalanced (55.8%)Imbalance
월세액 is highly imbalanced (58.9%)Imbalance
홈페이지 is highly imbalanced (87.4%)Imbalance
인허가취소일자 has 58 (100.0%) missing valuesMissing
폐업일자 has 21 (36.2%) missing valuesMissing
휴업시작일자 has 58 (100.0%) missing valuesMissing
휴업종료일자 has 58 (100.0%) missing valuesMissing
재개업일자 has 58 (100.0%) missing valuesMissing
전화번호 has 11 (19.0%) missing valuesMissing
소재지면적 has 2 (3.4%) missing valuesMissing
도로명주소 has 17 (29.3%) missing valuesMissing
도로명우편번호 has 17 (29.3%) missing valuesMissing
좌표정보(X) has 1 (1.7%) missing valuesMissing
좌표정보(Y) has 1 (1.7%) missing valuesMissing
다중이용업소여부 has 14 (24.1%) missing valuesMissing
시설총규모 has 14 (24.1%) missing valuesMissing
전통업소지정번호 has 58 (100.0%) missing valuesMissing
전통업소주된음식 has 58 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
시설총규모 has 37 (63.8%) zerosZeros

Reproduction

Analysis started2024-05-11 01:22:13.529082
Analysis finished2024-05-11 01:22:15.177275
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size596.0 B
3120000
58 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 58
100.0%

Length

2024-05-11T01:22:15.440349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:15.788624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 58
100.0%

관리번호
Text

UNIQUE 

Distinct58
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size596.0 B
2024-05-11T01:22:16.380907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1276
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

Unique58 ?
Unique (%)100.0%

Sample

1st row3120000-114-1996-00056
2nd row3120000-114-1996-00065
3rd row3120000-114-1997-00055
4th row3120000-114-1997-00057
5th row3120000-114-1997-00058
ValueCountFrequency (%)
3120000-114-1996-00056 1
 
1.7%
3120000-114-2016-00001 1
 
1.7%
3120000-114-2023-00002 1
 
1.7%
3120000-114-2010-00001 1
 
1.7%
3120000-114-2010-00002 1
 
1.7%
3120000-114-2010-00003 1
 
1.7%
3120000-114-2011-00001 1
 
1.7%
3120000-114-2012-00001 1
 
1.7%
3120000-114-2012-00002 1
 
1.7%
3120000-114-2013-00001 1
 
1.7%
Other values (48) 48
82.8%
2024-05-11T01:22:17.278820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 523
41.0%
1 227
17.8%
- 174
 
13.6%
2 142
 
11.1%
3 75
 
5.9%
4 65
 
5.1%
9 26
 
2.0%
5 16
 
1.3%
7 12
 
0.9%
6 8
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1102
86.4%
Dash Punctuation 174
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 523
47.5%
1 227
20.6%
2 142
 
12.9%
3 75
 
6.8%
4 65
 
5.9%
9 26
 
2.4%
5 16
 
1.5%
7 12
 
1.1%
6 8
 
0.7%
8 8
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 523
41.0%
1 227
17.8%
- 174
 
13.6%
2 142
 
11.1%
3 75
 
5.9%
4 65
 
5.1%
9 26
 
2.0%
5 16
 
1.3%
7 12
 
0.9%
6 8
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 523
41.0%
1 227
17.8%
- 174
 
13.6%
2 142
 
11.1%
3 75
 
5.9%
4 65
 
5.1%
9 26
 
2.0%
5 16
 
1.3%
7 12
 
0.9%
6 8
 
0.6%

인허가일자
Date

Distinct56
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size596.0 B
Minimum1992-12-11 00:00:00
Maximum2023-08-16 00:00:00
2024-05-11T01:22:17.720967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:18.165715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
3
37 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 37
63.8%
1 21
36.2%

Length

2024-05-11T01:22:18.461279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:18.860803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 37
63.8%
1 21
36.2%

영업상태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
폐업
37 
영업/정상
21 

Length

Max length5
Median length2
Mean length3.0862069
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 37
63.8%
영업/정상 21
36.2%

Length

2024-05-11T01:22:19.346748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:19.673784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 37
63.8%
영업/정상 21
36.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
2
37 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 37
63.8%
1 21
36.2%

Length

2024-05-11T01:22:20.034399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:20.432838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 37
63.8%
1 21
36.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
폐업
37 
영업
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 37
63.8%
영업 21
36.2%

Length

2024-05-11T01:22:20.685099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:21.002428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 37
63.8%
영업 21
36.2%

폐업일자
Date

MISSING 

Distinct36
Distinct (%)97.3%
Missing21
Missing (%)36.2%
Memory size596.0 B
Minimum2001-07-10 00:00:00
Maximum2024-01-23 00:00:00
2024-05-11T01:22:21.337664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:21.757854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

전화번호
Text

MISSING 

Distinct46
Distinct (%)97.9%
Missing11
Missing (%)19.0%
Memory size596.0 B
2024-05-11T01:22:22.250664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.297872
Min length7

Characters and Unicode

Total characters484
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

Unique45 ?
Unique (%)95.7%

Sample

1st row02 3246830
2nd row0203691739
3rd row0231453039
4th row02 3764397
5th row02 3746767
ValueCountFrequency (%)
02 39
41.5%
3373981 2
 
2.1%
3629560 1
 
1.1%
3087500 1
 
1.1%
3949582 1
 
1.1%
3246830 1
 
1.1%
3234557 1
 
1.1%
63737000 1
 
1.1%
22905734 1
 
1.1%
3915601 1
 
1.1%
Other values (45) 45
47.9%
2024-05-11T01:22:23.070107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89
18.4%
3 74
15.3%
2 68
14.0%
56
11.6%
5 38
7.9%
7 30
 
6.2%
9 30
 
6.2%
6 29
 
6.0%
1 24
 
5.0%
4 24
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 428
88.4%
Space Separator 56
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89
20.8%
3 74
17.3%
2 68
15.9%
5 38
8.9%
7 30
 
7.0%
9 30
 
7.0%
6 29
 
6.8%
1 24
 
5.6%
4 24
 
5.6%
8 22
 
5.1%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 484
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89
18.4%
3 74
15.3%
2 68
14.0%
56
11.6%
5 38
7.9%
7 30
 
6.2%
9 30
 
6.2%
6 29
 
6.0%
1 24
 
5.0%
4 24
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89
18.4%
3 74
15.3%
2 68
14.0%
56
11.6%
5 38
7.9%
7 30
 
6.2%
9 30
 
6.2%
6 29
 
6.0%
1 24
 
5.0%
4 24
 
5.0%

소재지면적
Text

MISSING 

Distinct51
Distinct (%)91.1%
Missing2
Missing (%)3.4%
Memory size596.0 B
2024-05-11T01:22:23.617782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2142857
Min length6

Characters and Unicode

Total characters348
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

Unique46 ?
Unique (%)82.1%

Sample

1st row2360.00
2nd row303.80
3rd row2192.46
4th row565.43
5th row382.52
ValueCountFrequency (%)
384.76 2
 
3.6%
330.00 2
 
3.6%
950.00 2
 
3.6%
400.00 2
 
3.6%
396.00 2
 
3.6%
780.00 1
 
1.8%
2360.00 1
 
1.8%
485.98 1
 
1.8%
756.48 1
 
1.8%
1,166.53 1
 
1.8%
Other values (41) 41
73.2%
2024-05-11T01:22:24.671302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 70
20.1%
. 56
16.1%
3 36
10.3%
4 28
 
8.0%
7 28
 
8.0%
9 26
 
7.5%
6 24
 
6.9%
5 22
 
6.3%
1 20
 
5.7%
8 19
 
5.5%
Other values (2) 19
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 289
83.0%
Other Punctuation 59
 
17.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 70
24.2%
3 36
12.5%
4 28
 
9.7%
7 28
 
9.7%
9 26
 
9.0%
6 24
 
8.3%
5 22
 
7.6%
1 20
 
6.9%
8 19
 
6.6%
2 16
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 56
94.9%
, 3
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 70
20.1%
. 56
16.1%
3 36
10.3%
4 28
 
8.0%
7 28
 
8.0%
9 26
 
7.5%
6 24
 
6.9%
5 22
 
6.3%
1 20
 
5.7%
8 19
 
5.5%
Other values (2) 19
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 70
20.1%
. 56
16.1%
3 36
10.3%
4 28
 
8.0%
7 28
 
8.0%
9 26
 
7.5%
6 24
 
6.9%
5 22
 
6.3%
1 20
 
5.7%
8 19
 
5.5%
Other values (2) 19
 
5.5%

소재지우편번호
Text

Distinct35
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Memory size596.0 B
2024-05-11T01:22:25.181381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2068966
Min length6

Characters and Unicode

Total characters360
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

Unique22 ?
Unique (%)37.9%

Sample

1st row120-825
2nd row120841
3rd row120-834
4th row120813
5th row120805
ValueCountFrequency (%)
120805 6
 
10.3%
120810 4
 
6.9%
120170 3
 
5.2%
120847 3
 
5.2%
120859 3
 
5.2%
120130 3
 
5.2%
120771 2
 
3.4%
120827 2
 
3.4%
120824 2
 
3.4%
120830 2
 
3.4%
Other values (25) 28
48.3%
2024-05-11T01:22:26.356152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86
23.9%
1 78
21.7%
2 67
18.6%
8 46
12.8%
5 19
 
5.3%
7 19
 
5.3%
3 13
 
3.6%
- 12
 
3.3%
4 10
 
2.8%
9 6
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 348
96.7%
Dash Punctuation 12
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86
24.7%
1 78
22.4%
2 67
19.3%
8 46
13.2%
5 19
 
5.5%
7 19
 
5.5%
3 13
 
3.7%
4 10
 
2.9%
9 6
 
1.7%
6 4
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86
23.9%
1 78
21.7%
2 67
18.6%
8 46
12.8%
5 19
 
5.3%
7 19
 
5.3%
3 13
 
3.6%
- 12
 
3.3%
4 10
 
2.8%
9 6
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86
23.9%
1 78
21.7%
2 67
18.6%
8 46
12.8%
5 19
 
5.3%
7 19
 
5.3%
3 13
 
3.6%
- 12
 
3.3%
4 10
 
2.8%
9 6
 
1.7%

지번주소
Text

Distinct57
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size596.0 B
2024-05-11T01:22:27.187025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length37
Mean length29.293103
Min length19

Characters and Unicode

Total characters1699
Distinct characters107
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

Unique56 ?
Unique (%)96.6%

Sample

1st row서울특별시 서대문구 연희동 131-1
2nd row서울특별시 서대문구 홍은동 9-77 79,81
3rd row서울특별시 서대문구 창천동 30-33
4th row서울특별시 서대문구 북가좌동 306-17 서부코아 지층
5th row서울특별시 서대문구 남가좌동 295-10
ValueCountFrequency (%)
서울특별시 58
18.8%
서대문구 58
18.8%
남가좌동 12
 
3.9%
홍제동 10
 
3.2%
홍은동 9
 
2.9%
연희동 9
 
2.9%
1층 9
 
2.9%
북가좌동 8
 
2.6%
지하1층 6
 
1.9%
101호 4
 
1.3%
Other values (99) 125
40.6%
2024-05-11T01:22:28.566236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
289
 
17.0%
서 118
 
6.9%
1 87
 
5.1%
대 66
 
3.9%
동 63
 
3.7%
시 60
 
3.5%
문 59
 
3.5%
구 58
 
3.4%
울 58
 
3.4%
별 58
 
3.4%
Other values (97) 783
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 962
56.6%
Decimal Number 343
 
20.2%
Space Separator 289
 
17.0%
Dash Punctuation 48
 
2.8%
Other Punctuation 18
 
1.1%
Open Punctuation 13
 
0.8%
Close Punctuation 13
 
0.8%
Uppercase Letter 11
 
0.6%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 118
 
12.3%
대 66
 
6.9%
동 63
 
6.5%
시 60
 
6.2%
문 59
 
6.1%
구 58
 
6.0%
울 58
 
6.0%
별 58
 
6.0%
특 58
 
6.0%
층 30
 
3.1%
Other values (76) 334
34.7%
Decimal Number
ValueCountFrequency (%)
1 87
25.4%
4 44
12.8%
3 40
11.7%
2 35
10.2%
0 28
 
8.2%
5 24
 
7.0%
9 23
 
6.7%
8 22
 
6.4%
7 20
 
5.8%
6 20
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 7
63.6%
D 1
 
9.1%
M 1
 
9.1%
C 1
 
9.1%
A 1
 
9.1%
Space Separator
ValueCountFrequency (%)
289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 962
56.6%
Common 726
42.7%
Latin 11
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 118
 
12.3%
대 66
 
6.9%
동 63
 
6.5%
시 60
 
6.2%
문 59
 
6.1%
구 58
 
6.0%
울 58
 
6.0%
별 58
 
6.0%
특 58
 
6.0%
층 30
 
3.1%
Other values (76) 334
34.7%
Common
ValueCountFrequency (%)
289
39.8%
1 87
 
12.0%
- 48
 
6.6%
4 44
 
6.1%
3 40
 
5.5%
2 35
 
4.8%
0 28
 
3.9%
5 24
 
3.3%
9 23
 
3.2%
8 22
 
3.0%
Other values (6) 86
 
11.8%
Latin
ValueCountFrequency (%)
B 7
63.6%
D 1
 
9.1%
M 1
 
9.1%
C 1
 
9.1%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 962
56.6%
ASCII 737
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
289
39.2%
1 87
 
11.8%
- 48
 
6.5%
4 44
 
6.0%
3 40
 
5.4%
2 35
 
4.7%
0 28
 
3.8%
5 24
 
3.3%
9 23
 
3.1%
8 22
 
3.0%
Other values (11) 97
 
13.2%
Hangul
ValueCountFrequency (%)
서 118
 
12.3%
대 66
 
6.9%
동 63
 
6.5%
시 60
 
6.2%
문 59
 
6.1%
구 58
 
6.0%
울 58
 
6.0%
별 58
 
6.0%
특 58
 
6.0%
층 30
 
3.1%
Other values (76) 334
34.7%

도로명주소
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing17
Missing (%)29.3%
Memory size596.0 B
2024-05-11T01:22:29.570633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length41
Mean length35.634146
Min length23

Characters and Unicode

Total characters1461
Distinct characters129
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

Unique41 ?
Unique (%)100.0%

Sample

1st row서울특별시 서대문구 연희맛로 23 (연희동)
2nd row서울특별시 서대문구 신촌로 83 (창천동)
3rd row서울특별시 서대문구 응암로 54 (북가좌동,서부코아 지층)
4th row서울특별시 서대문구 세검정로1길 93 (홍은동)
5th row서울특별시 서대문구 통일로25길 30 (홍제동)
ValueCountFrequency (%)
서울특별시 41
 
15.4%
서대문구 41
 
15.4%
1층 9
 
3.4%
홍은동 7
 
2.6%
연희로 7
 
2.6%
남가좌동 7
 
2.6%
지하1층 6
 
2.2%
통일로 6
 
2.2%
홍제동 5
 
1.9%
연희동 5
 
1.9%
Other values (109) 133
49.8%
2024-05-11T01:22:31.119833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
15.5%
서 84
 
5.7%
1 69
 
4.7%
, 50
 
3.4%
대 47
 
3.2%
동 47
 
3.2%
( 46
 
3.1%
) 46
 
3.1%
문 43
 
2.9%
시 42
 
2.9%
Other values (119) 761
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 854
58.5%
Space Separator 226
 
15.5%
Decimal Number 210
 
14.4%
Other Punctuation 50
 
3.4%
Open Punctuation 46
 
3.1%
Close Punctuation 46
 
3.1%
Uppercase Letter 19
 
1.3%
Dash Punctuation 5
 
0.3%
Math Symbol 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 84
 
9.8%
대 47
 
5.5%
동 47
 
5.5%
문 43
 
5.0%
시 42
 
4.9%
울 42
 
4.9%
특 41
 
4.8%
별 41
 
4.8%
구 41
 
4.8%
로 37
 
4.3%
Other values (98) 389
45.6%
Decimal Number
ValueCountFrequency (%)
1 69
32.9%
2 26
 
12.4%
3 24
 
11.4%
0 23
 
11.0%
4 17
 
8.1%
5 15
 
7.1%
6 10
 
4.8%
7 9
 
4.3%
9 9
 
4.3%
8 8
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
63.2%
C 3
 
15.8%
M 2
 
10.5%
D 1
 
5.3%
A 1
 
5.3%
Space Separator
ValueCountFrequency (%)
226
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 854
58.5%
Common 588
40.2%
Latin 19
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 84
 
9.8%
대 47
 
5.5%
동 47
 
5.5%
문 43
 
5.0%
시 42
 
4.9%
울 42
 
4.9%
특 41
 
4.8%
별 41
 
4.8%
구 41
 
4.8%
로 37
 
4.3%
Other values (98) 389
45.6%
Common
ValueCountFrequency (%)
226
38.4%
1 69
 
11.7%
, 50
 
8.5%
( 46
 
7.8%
) 46
 
7.8%
2 26
 
4.4%
3 24
 
4.1%
0 23
 
3.9%
4 17
 
2.9%
5 15
 
2.6%
Other values (6) 46
 
7.8%
Latin
ValueCountFrequency (%)
B 12
63.2%
C 3
 
15.8%
M 2
 
10.5%
D 1
 
5.3%
A 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 854
58.5%
ASCII 607
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
37.2%
1 69
 
11.4%
, 50
 
8.2%
( 46
 
7.6%
) 46
 
7.6%
2 26
 
4.3%
3 24
 
4.0%
0 23
 
3.8%
4 17
 
2.8%
5 15
 
2.5%
Other values (11) 65
 
10.7%
Hangul
ValueCountFrequency (%)
서 84
 
9.8%
대 47
 
5.5%
동 47
 
5.5%
문 43
 
5.0%
시 42
 
4.9%
울 42
 
4.9%
특 41
 
4.8%
별 41
 
4.8%
구 41
 
4.8%
로 37
 
4.3%
Other values (98) 389
45.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)70.7%
Missing17
Missing (%)29.3%
Infinite0
Infinite (%)0.0%
Mean3697.3902
Minimum3602
Maximum3789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-05-11T01:22:31.656016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3602
5-th percentile3612
Q13658
median3707
Q33726
95-th percentile3777
Maximum3789
Range187
Interquartile range (IQR)68

Descriptive statistics

Standard deviation49.565047
Coefficient of variation (CV)0.013405414
Kurtosis-0.44192124
Mean3697.3902
Median Absolute Deviation (MAD)23
Skewness-0.18996448
Sum151593
Variance2456.6939
MonotonicityNot monotonic
2024-05-11T01:22:32.222729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
3712 3
 
5.2%
3709 3
 
5.2%
3764 2
 
3.4%
3726 2
 
3.4%
3699 2
 
3.4%
3646 2
 
3.4%
3686 2
 
3.4%
3658 2
 
3.4%
3730 2
 
3.4%
3612 2
 
3.4%
Other values (19) 19
32.8%
(Missing) 17
29.3%
ValueCountFrequency (%)
3602 1
1.7%
3604 1
1.7%
3612 2
3.4%
3628 1
1.7%
3629 1
1.7%
3646 2
3.4%
3653 1
1.7%
3658 2
3.4%
3674 1
1.7%
3686 2
3.4%
ValueCountFrequency (%)
3789 1
1.7%
3785 1
1.7%
3777 1
1.7%
3772 1
1.7%
3764 2
3.4%
3738 1
1.7%
3731 1
1.7%
3730 2
3.4%
3726 2
3.4%
3718 1
1.7%

사업장명
Text

Distinct57
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size596.0 B
2024-05-11T01:22:33.031800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length8.5344828
Min length3

Characters and Unicode

Total characters495
Distinct characters152
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)96.6%

Sample

1st row(주)사러가
2nd row준마트
3rd row현대백화점신촌점(기타식품)
4th row(주)지에스리테일북가좌점
5th row(주)함지유통
ValueCountFrequency (%)
주)이마트에브리데이 3
 
4.2%
화창토산(주 2
 
2.8%
롯데슈퍼 2
 
2.8%
남가좌점 2
 
2.8%
럭키 1
 
1.4%
주식회사우리농민마트 1
 
1.4%
서울농산물유통센터 1
 
1.4%
하모니마트대현점 1
 
1.4%
마트 1
 
1.4%
할인 1
 
1.4%
Other values (56) 56
78.9%
2024-05-11T01:22:34.308626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 33
 
6.7%
트 32
 
6.5%
( 28
 
5.7%
) 28
 
5.7%
주 26
 
5.3%
점 16
 
3.2%
13
 
2.6%
유 11
 
2.2%
데 11
 
2.2%
이 10
 
2.0%
Other values (142) 287
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
85.1%
Open Punctuation 28
 
5.7%
Close Punctuation 28
 
5.7%
Space Separator 13
 
2.6%
Decimal Number 4
 
0.8%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 33
 
7.8%
트 32
 
7.6%
주 26
 
6.2%
점 16
 
3.8%
유 11
 
2.6%
데 11
 
2.6%
이 10
 
2.4%
리 8
 
1.9%
통 8
 
1.9%
에 8
 
1.9%
Other values (134) 258
61.3%
Decimal Number
ValueCountFrequency (%)
2 1
25.0%
3 1
25.0%
4 1
25.0%
0 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
85.1%
Common 73
 
14.7%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 33
 
7.8%
트 32
 
7.6%
주 26
 
6.2%
점 16
 
3.8%
유 11
 
2.6%
데 11
 
2.6%
이 10
 
2.4%
리 8
 
1.9%
통 8
 
1.9%
에 8
 
1.9%
Other values (134) 258
61.3%
Common
ValueCountFrequency (%)
( 28
38.4%
) 28
38.4%
13
17.8%
2 1
 
1.4%
3 1
 
1.4%
4 1
 
1.4%
0 1
 
1.4%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
85.1%
ASCII 74
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 33
 
7.8%
트 32
 
7.6%
주 26
 
6.2%
점 16
 
3.8%
유 11
 
2.6%
데 11
 
2.6%
이 10
 
2.4%
리 8
 
1.9%
통 8
 
1.9%
에 8
 
1.9%
Other values (134) 258
61.3%
ASCII
ValueCountFrequency (%)
( 28
37.8%
) 28
37.8%
13
17.6%
2 1
 
1.4%
e 1
 
1.4%
3 1
 
1.4%
4 1
 
1.4%
0 1
 
1.4%

최종수정일자
Date

Distinct56
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size596.0 B
Minimum1999-11-03 00:00:00
Maximum2024-05-02 16:07:54
2024-05-11T01:22:34.895617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:35.452436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
I
40 
U
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 40
69.0%
U 18
31.0%

Length

2024-05-11T01:22:36.271919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:36.728066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 40
69.0%
u 18
31.0%

데이터갱신일자
Date

Distinct22
Distinct (%)37.9%
Missing0
Missing (%)0.0%
Memory size596.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T01:22:37.179432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:22:37.888887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
기타식품판매업
57 
즉석판매제조가공업
 
1

Length

Max length9
Median length7
Mean length7.0344828
Min length7

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 57
98.3%
즉석판매제조가공업 1
 
1.7%

Length

2024-05-11T01:22:38.583546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:39.160356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 57
98.3%
즉석판매제조가공업 1
 
1.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)71.9%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean194021.41
Minimum192000.95
Maximum196961.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-05-11T01:22:39.725650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192000.95
5-th percentile192209.32
Q1192874.51
median194134.69
Q3195063.82
95-th percentile195453.28
Maximum196961.57
Range4960.6284
Interquartile range (IQR)2189.3063

Descriptive statistics

Standard deviation1213.9713
Coefficient of variation (CV)0.0062568934
Kurtosis-0.95191064
Mean194021.41
Median Absolute Deviation (MAD)1062.008
Skewness-0.014324413
Sum11059220
Variance1473726.3
MonotonicityNot monotonic
2024-05-11T01:22:40.313439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
192552.192063652 4
 
6.9%
195196.693652181 3
 
5.2%
192367.103746694 3
 
5.2%
195332.123380254 3
 
5.2%
192209.323632506 3
 
5.2%
193803.424181589 2
 
3.4%
193762.64108662 2
 
3.4%
195057.033841623 2
 
3.4%
194257.693128485 2
 
3.4%
194920.532436667 2
 
3.4%
Other values (31) 31
53.4%
ValueCountFrequency (%)
192000.945942229 1
 
1.7%
192209.323632506 3
5.2%
192367.103746694 3
5.2%
192482.416512858 1
 
1.7%
192491.640163882 1
 
1.7%
192494.780458561 1
 
1.7%
192552.192063652 4
6.9%
192874.514454351 1
 
1.7%
193041.359622943 1
 
1.7%
193112.624510173 1
 
1.7%
ValueCountFrequency (%)
196961.57430764 1
 
1.7%
195993.99464336 1
 
1.7%
195566.148571394 1
 
1.7%
195425.05807225 1
 
1.7%
195407.418330818 1
 
1.7%
195332.123380254 3
5.2%
195281.395461663 1
 
1.7%
195280.710219904 1
 
1.7%
195259.429272709 1
 
1.7%
195196.693652181 3
5.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)71.9%
Missing1
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean452652.95
Minimum450433.69
Maximum455381.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-05-11T01:22:40.854959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450433.69
5-th percentile450618.54
Q1451975.05
median452723.46
Q3453430.81
95-th percentile454867.42
Maximum455381.48
Range4947.7893
Interquartile range (IQR)1455.7604

Descriptive statistics

Standard deviation1290.7915
Coefficient of variation (CV)0.002851614
Kurtosis-0.54551689
Mean452652.95
Median Absolute Deviation (MAD)748.40622
Skewness0.12702817
Sum25801218
Variance1666142.6
MonotonicityNot monotonic
2024-05-11T01:22:41.447311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
453030.926927651 4
 
6.9%
453764.706268517 3
 
5.2%
451975.051135763 3
 
5.2%
450806.05844472 3
 
5.2%
452067.039429636 3
 
5.2%
452723.457356207 2
 
3.4%
451445.274814853 2
 
3.4%
454786.019433577 2
 
3.4%
453215.522072057 2
 
3.4%
454188.343575118 2
 
3.4%
Other values (31) 31
53.4%
ValueCountFrequency (%)
450433.691021245 1
 
1.7%
450597.874088644 1
 
1.7%
450618.352604271 1
 
1.7%
450618.592067302 1
 
1.7%
450631.151435874 1
 
1.7%
450646.576957423 1
 
1.7%
450806.05844472 3
5.2%
451394.163765874 1
 
1.7%
451445.274814853 2
3.4%
451653.563671802 1
 
1.7%
ValueCountFrequency (%)
455381.480302685 1
 
1.7%
455220.88305506 1
 
1.7%
455193.014698844 1
 
1.7%
454786.019433577 2
3.4%
454344.432517428 1
 
1.7%
454188.343575118 2
3.4%
454049.804041193 1
 
1.7%
453764.706268517 3
5.2%
453657.534811024 1
 
1.7%
453607.908883612 1
 
1.7%

위생업태명
Categorical

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
기타식품판매업
43 
<NA>
14 
즉석판매제조가공업
 
1

Length

Max length9
Median length7
Mean length6.3103448
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 43
74.1%
<NA> 14
 
24.1%
즉석판매제조가공업 1
 
1.7%

Length

2024-05-11T01:22:42.028253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:42.358236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 43
74.1%
na 14
 
24.1%
즉석판매제조가공업 1
 
1.7%

남성종사자수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
51 
0
7 

Length

Max length4
Median length4
Mean length3.637931
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> 51
87.9%
0 7
 
12.1%

Length

2024-05-11T01:22:42.820847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:43.226259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
87.9%
0 7
 
12.1%

여성종사자수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
51 
0
7 

Length

Max length4
Median length4
Mean length3.637931
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> 51
87.9%
0 7
 
12.1%

Length

2024-05-11T01:22:43.644279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:44.025084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
87.9%
0 7
 
12.1%

영업장주변구분명
Categorical

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
48 
기타
7 
주택가주변
 
3

Length

Max length5
Median length4
Mean length3.8103448
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 48
82.8%
기타 7
 
12.1%
주택가주변 3
 
5.2%

Length

2024-05-11T01:22:44.439712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:44.783029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 48
82.8%
기타 7
 
12.1%
주택가주변 3
 
5.2%

등급구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
48 
기타
9 
자율
 
1

Length

Max length4
Median length4
Mean length3.6551724
Min length2

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 48
82.8%
기타 9
 
15.5%
자율 1
 
1.7%

Length

2024-05-11T01:22:45.256535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:45.576820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 48
82.8%
기타 9
 
15.5%
자율 1
 
1.7%

급수시설구분명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
44 
상수도전용
14 

Length

Max length5
Median length4
Mean length4.2413793
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 44
75.9%
상수도전용 14
 
24.1%

Length

2024-05-11T01:22:45.994851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:46.411170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
75.9%
상수도전용 14
 
24.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
53 
0
 
5

Length

Max length4
Median length4
Mean length3.7413793
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 53
91.4%
0 5
 
8.6%

Length

2024-05-11T01:22:46.897098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:47.239754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
91.4%
0 5
 
8.6%

본사종업원수
Categorical

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
35 
0
22 
38
 
1

Length

Max length4
Median length4
Mean length2.8275862
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 35
60.3%
0 22
37.9%
38 1
 
1.7%

Length

2024-05-11T01:22:47.786474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:48.230918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
60.3%
0 22
37.9%
38 1
 
1.7%

공장사무직종업원수
Categorical

Distinct4
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
34 
0
22 
3
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.7586207
Min length1

Unique

Unique2 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
58.6%
0 22
37.9%
3 1
 
1.7%
2 1
 
1.7%

Length

2024-05-11T01:22:48.777187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:49.422405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
58.6%
0 22
37.9%
3 1
 
1.7%
2 1
 
1.7%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
34 
0
22 
10
 
1
5
 
1

Length

Max length4
Median length4
Mean length2.7758621
Min length1

Unique

Unique2 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 34
58.6%
0 22
37.9%
10 1
 
1.7%
5 1
 
1.7%

Length

2024-05-11T01:22:50.154073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:50.631669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 34
58.6%
0 22
37.9%
10 1
 
1.7%
5 1
 
1.7%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
35 
0
23 

Length

Max length4
Median length4
Mean length2.8103448
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 35
60.3%
0 23
39.7%

Length

2024-05-11T01:22:51.159739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:51.605778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 35
60.3%
0 23
39.7%

건물소유구분명
Categorical

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
30 
임대
19 
자가
9 

Length

Max length4
Median length4
Mean length3.0344828
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> 30
51.7%
임대 19
32.8%
자가 9
 
15.5%

Length

2024-05-11T01:22:52.031214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:52.485922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
51.7%
임대 19
32.8%
자가 9
 
15.5%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
49 
0
8 
150000000
 
1

Length

Max length9
Median length4
Mean length3.6724138
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 49
84.5%
0 8
 
13.8%
150000000 1
 
1.7%

Length

2024-05-11T01:22:52.937387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:53.384615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
84.5%
0 8
 
13.8%
150000000 1
 
1.7%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
48 
0
8 
10000000
 
1
23000000
 
1

Length

Max length8
Median length4
Mean length3.7241379
Min length1

Unique

Unique2 ?
Unique (%)3.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 48
82.8%
0 8
 
13.8%
10000000 1
 
1.7%
23000000 1
 
1.7%

Length

2024-05-11T01:22:53.984881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:54.480272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 48
82.8%
0 8
 
13.8%
10000000 1
 
1.7%
23000000 1
 
1.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.3%
Missing14
Missing (%)24.1%
Memory size248.0 B
False
44 
(Missing)
14 
ValueCountFrequency (%)
False 44
75.9%
(Missing) 14
 
24.1%
2024-05-11T01:22:54.792406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)18.2%
Missing14
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean125.73182
Minimum0
Maximum1192.23
Zeros37
Zeros (%)63.8%
Negative0
Negative (%)0.0%
Memory size654.0 B
2024-05-11T01:22:55.097035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile953.744
Maximum1192.23
Range1192.23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation331.1989
Coefficient of variation (CV)2.6341693
Kurtosis4.7471262
Mean125.73182
Median Absolute Deviation (MAD)0
Skewness2.478013
Sum5532.2
Variance109692.71
MonotonicityNot monotonic
2024-05-11T01:22:55.509887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 37
63.8%
949.46 1
 
1.7%
495.0 1
 
1.7%
756.48 1
 
1.7%
1166.53 1
 
1.7%
954.5 1
 
1.7%
18.0 1
 
1.7%
1192.23 1
 
1.7%
(Missing) 14
 
24.1%
ValueCountFrequency (%)
0.0 37
63.8%
18.0 1
 
1.7%
495.0 1
 
1.7%
756.48 1
 
1.7%
949.46 1
 
1.7%
954.5 1
 
1.7%
1166.53 1
 
1.7%
1192.23 1
 
1.7%
ValueCountFrequency (%)
1192.23 1
 
1.7%
1166.53 1
 
1.7%
954.5 1
 
1.7%
949.46 1
 
1.7%
756.48 1
 
1.7%
495.0 1
 
1.7%
18.0 1
 
1.7%
0.0 37
63.8%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing58
Missing (%)100.0%
Memory size654.0 B

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size596.0 B
<NA>
57 
2
 
1

Length

Max length4
Median length4
Mean length3.9482759
Min length1

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 57
98.3%
2 1
 
1.7%

Length

2024-05-11T01:22:55.968305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:22:56.244998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 57
98.3%
2 1
 
1.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031200003120000-114-1996-000561996-04-23<NA>1영업/정상1영업<NA><NA><NA><NA>02 32468302360.00120-825서울특별시 서대문구 연희동 131-1서울특별시 서대문구 연희맛로 23 (연희동)3707(주)사러가2023-08-08 09:45:48U2022-12-07 23:00:00.0기타식품판매업193716.339878451653.563672<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131200003120000-114-1996-0006519960627<NA>3폐업2폐업20010710<NA><NA><NA>0203691739303.80120841서울특별시 서대문구 홍은동 9-77 79,81<NA><NA>준마트2002-03-07 00:00:00I2018-08-31 23:59:59.0기타식품판매업195425.058072455220.883055기타식품판매업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231200003120000-114-1997-000551992-12-11<NA>1영업/정상1영업<NA><NA><NA><NA>02314530392192.46120-834서울특별시 서대문구 창천동 30-33서울특별시 서대문구 신촌로 83 (창천동)3789현대백화점신촌점(기타식품)2024-04-05 14:43:59U2023-12-04 00:07:00.0기타식품판매업194265.06764450433.691021<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331200003120000-114-1997-0005719970910<NA>1영업/정상1영업<NA><NA><NA><NA>02 3764397565.43120813서울특별시 서대문구 북가좌동 306-17 서부코아 지층서울특별시 서대문구 응암로 54 (북가좌동,서부코아 지층)3691(주)지에스리테일북가좌점2016-01-25 14:04:22I2018-08-31 23:59:59.0기타식품판매업192000.945942452848.009128기타식품판매업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431200003120000-114-1997-0005819971018<NA>3폐업2폐업20061030<NA><NA><NA>02 3746767382.52120805서울특별시 서대문구 남가좌동 295-10<NA><NA>(주)함지유통1999-11-03 00:00:00I2018-08-31 23:59:59.0기타식품판매업192367.103747451975.051136기타식품판매업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531200003120000-114-1998-0005919980731<NA>3폐업2폐업20211130<NA><NA><NA>02 3910108400.67120771서울특별시 서대문구 홍은동 455 벽산아파트상가 A동 B01호서울특별시 서대문구 세검정로1길 93 (홍은동)3612삼미유통(에스엠마트)2021-11-30 15:15:52U2021-12-02 02:40:00.0기타식품판매업195057.033842454786.019434기타식품판매업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
631200003120000-114-1998-0033919960627<NA>3폐업2폐업20070503<NA><NA><NA>02 3234492384.76120847서울특별시 서대문구 홍은동 274-83<NA><NA>서부농업협동조합하나로마트연희점2002-03-11 00:00:00I2018-08-31 23:59:59.0기타식품판매업194257.693128453215.522072기타식품판매업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731200003120000-114-1998-0034119981020<NA>3폐업2폐업20021226<NA><NA><NA>02 3733581397.60120120서울특별시 서대문구 남가좌동 2-4 ,19,20,1-2<NA><NA>빅마트충암점2002-03-11 00:00:00I2018-08-31 23:59:59.0기타식품판매업193112.62451453607.908884기타식품판매업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831200003120000-114-1999-0034019960629<NA>3폐업2폐업20150414<NA><NA><NA>02723 7570450.70120853서울특별시 서대문구 홍제동 82 한양아파트상가서울특별시 서대문구 통일로25길 30 (홍제동)3730상수유통2015-04-23 11:59:14I2018-08-31 23:59:59.0기타식품판매업195259.429273453430.811542기타식품판매업00주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931200003120000-114-2000-0052520001120<NA>3폐업2폐업20170906<NA><NA><NA>02 39588681,135.75120847서울특별시 서대문구 홍은동 277-165서울특별시 서대문구 모래내로 330, 1~3층 (홍은동)3658(주)신정고려인삼2017-09-06 15:12:25I2018-08-31 23:59:59.0기타식품판매업194078.365285453053.728524기타식품판매업<NA><NA>기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
4831200003120000-114-2019-0000120190425<NA>1영업/정상1영업<NA><NA><NA><NA><NA>700.00120807서울특별시 서대문구 남가좌동 349-1 1, 2층서울특별시 서대문구 증가로 141, 1, 2층 (남가좌동)3692(주) 시티마트2019-04-25 11:32:47I2019-04-27 02:20:31.0기타식품판매업193041.359623452790.96358기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
4931200003120000-114-2021-0000120210603<NA>1영업/정상1영업<NA><NA><NA><NA><NA>637.40120848서울특별시 서대문구 홍은동 426 연희127빌딩서울특별시 서대문구 연희로 286, 연희127빌딩 1~지1층 (홍은동)3653농민마트2022-12-12 11:44:14U2021-11-01 23:04:00.0기타식품판매업194321.960265453368.123327<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5031200003120000-114-2021-000022021-08-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>480.49120-842서울특별시 서대문구 홍은동 11-419 우리은행서울특별시 서대문구 홍은중앙로 89, 우리은행 1층 (홍은동)3604(주)이마트에브리데이홍은점2024-04-29 15:23:43U2023-12-05 00:01:00.0기타식품판매업195280.71022455193.014699<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5131200003120000-114-2021-0000320211202<NA>1영업/정상1영업<NA><NA><NA><NA><NA>608.00120771서울특별시 서대문구 홍은동 455 홍은동벽산아파트서울특별시 서대문구 세검정로1길 93, 상가A동 B01호 (홍은동, 홍은동벽산아파트)3612오마켓2021-12-02 15:05:41I2021-12-04 00:22:43.0기타식품판매업195057.033842454786.019434기타식품판매업00<NA><NA><NA>00000자가00N0.0<NA><NA><NA>
5231200003120000-114-2021-0000420211206<NA>1영업/정상1영업<NA><NA><NA><NA>02 3949582777.83120857서울특별시 서대문구 홍제동 301-2 홍제빌딩 지하1층서울특별시 서대문구 통일로 464, 홍제빌딩 지하1층 (홍제동)3629(주)세계로커머스2021-12-06 17:09:58I2021-12-08 00:22:43.0기타식품판매업194920.532437454188.343575기타식품판매업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
5331200003120000-114-2022-000012022-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>940.83120-801서울특별시 서대문구 남가좌동 50-3 명지대학교서울특별시 서대문구 거북골로 34, 명지대학교 인문캠퍼스 MCC관 B2층 (남가좌동)3674(주)이마트에브리데이 명지대점2024-05-02 16:07:54U2023-12-05 00:04:00.0기타식품판매업193139.523944453106.002592<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5431200003120000-114-2022-000022022-08-17<NA>1영업/정상1영업<NA><NA><NA><NA>02 38051231130.00120-805서울특별시 서대문구 남가좌동 286-1 DMC금호리첸시아서울특별시 서대문구 수색로2길 39, 지하1층 B105-1,B105-2호 (남가좌동, DMC금호리첸시아)3712(주)이마트에브리데이 남가좌점2024-04-29 14:44:53U2023-12-05 00:01:00.0기타식품판매업192482.416513452143.491541<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5531200003120000-114-2023-000012023-04-26<NA>1영업/정상1영업<NA><NA><NA><NA>023610000400.00120-020서울특별시 서대문구 미근동 332 웨스트게이트타워서울특별시 서대문구 충정로 70, 웨스트게이트타워 10,12,16층 (미근동)3738네슬레코리아 유한책임회사2023-04-26 11:13:27I2022-12-03 22:08:00.0기타식품판매업196961.574308451394.163766<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5631200003120000-114-2023-000022023-06-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>970.00120-859서울특별시 서대문구 홍제동 158-33 연세24시사우나서울특별시 서대문구 통일로 413, 1층 (홍제동)3646삼성식자재마트2023-06-05 12:12:01I2022-12-06 00:08:00.0기타식품판매업195196.693652453764.706269<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5731200003120000-114-2023-000032023-08-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>341.20120-853서울특별시 서대문구 홍제동 57-5 서대문푸르지오센트럴파크아파트서울특별시 서대문구 통일로 339, 101동 B201~207,B105호 (홍제동, 서대문푸르지오센트럴파크아파트)3731(주)이마트에브리데이 무악재점2024-04-29 11:58:36U2023-12-05 00:01:00.0기타식품판매업195566.148571453219.054422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>