Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells108076
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical18
Text8
DateTime4
Unsupported7
Numeric6
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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-18671/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (61.5%)Imbalance
총인원 is highly imbalanced (77.1%)Imbalance
본사종업원수 is highly imbalanced (77.0%)Imbalance
공장사무직종업원수 is highly imbalanced (77.0%)Imbalance
공장판매직종업원수 is highly imbalanced (77.0%)Imbalance
공장생산직종업원수 is highly imbalanced (77.0%)Imbalance
보증액 is highly imbalanced (77.0%)Imbalance
월세액 is highly imbalanced (77.0%)Imbalance
다중이용업소여부 is highly imbalanced (85.8%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2309 (23.1%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 2872 (28.7%) missing valuesMissing
도로명주소 has 5272 (52.7%) missing valuesMissing
도로명우편번호 has 5383 (53.8%) missing valuesMissing
좌표정보(X) has 801 (8.0%) missing valuesMissing
좌표정보(Y) has 801 (8.0%) missing valuesMissing
남성종사자수 has 3893 (38.9%) missing valuesMissing
여성종사자수 has 3873 (38.7%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1378 (13.8%) missing valuesMissing
시설총규모 has 1378 (13.8%) missing valuesMissing
전통업소지정번호 has 9995 (> 99.9%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 42.23280899)Skewed
여성종사자수 is highly skewed (γ1 = 35.15370778)Skewed
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
건물소유구분명 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 4273 (42.7%) zerosZeros
여성종사자수 has 3208 (32.1%) zerosZeros

Reproduction

Analysis started2024-05-11 05:38:35.778952
Analysis finished2024-05-11 05:38:39.504126
Duration3.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3190000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 10000
100.0%

Length

2024-05-11T14:38:39.633214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:39.828747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:38:40.124239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3190000-101-1984-04828
2nd row3190000-101-1980-02442
3rd row3190000-101-1990-02659
4th row3190000-101-1993-05308
5th row3190000-101-2020-00024
ValueCountFrequency (%)
3190000-101-1984-04828 1
 
< 0.1%
3190000-101-2021-00224 1
 
< 0.1%
3190000-101-1984-02331 1
 
< 0.1%
3190000-101-2006-00176 1
 
< 0.1%
3190000-101-2018-00269 1
 
< 0.1%
3190000-101-1991-04094 1
 
< 0.1%
3190000-101-1989-01983 1
 
< 0.1%
3190000-101-1994-03893 1
 
< 0.1%
3190000-101-2021-00205 1
 
< 0.1%
3190000-101-2022-00076 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T14:38:40.719692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78700
35.8%
1 41832
19.0%
- 30000
 
13.6%
9 21037
 
9.6%
3 14905
 
6.8%
2 12083
 
5.5%
8 4722
 
2.1%
4 4495
 
2.0%
5 4105
 
1.9%
7 4062
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 78700
41.4%
1 41832
22.0%
9 21037
 
11.1%
3 14905
 
7.8%
2 12083
 
6.4%
8 4722
 
2.5%
4 4495
 
2.4%
5 4105
 
2.2%
7 4062
 
2.1%
6 4059
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 78700
35.8%
1 41832
19.0%
- 30000
 
13.6%
9 21037
 
9.6%
3 14905
 
6.8%
2 12083
 
5.5%
8 4722
 
2.1%
4 4495
 
2.0%
5 4105
 
1.9%
7 4062
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 78700
35.8%
1 41832
19.0%
- 30000
 
13.6%
9 21037
 
9.6%
3 14905
 
6.8%
2 12083
 
5.5%
8 4722
 
2.1%
4 4495
 
2.0%
5 4105
 
1.9%
7 4062
 
1.8%
Distinct6176
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:38:41.011003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:41.228531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
7691 
1
2309 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7691
76.9%
1 2309
 
23.1%

Length

2024-05-11T14:38:41.426620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:41.606293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7691
76.9%
1 2309
 
23.1%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7691 
영업/정상
2309 

Length

Max length5
Median length2
Mean length2.6927
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7691
76.9%
영업/정상 2309
 
23.1%

Length

2024-05-11T14:38:41.790310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:41.946587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7691
76.9%
영업/정상 2309
 
23.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7691 
1
2309 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7691
76.9%
1 2309
 
23.1%

Length

2024-05-11T14:38:42.112640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:42.285403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7691
76.9%
1 2309
 
23.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7691 
영업
2309 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7691
76.9%
영업 2309
 
23.1%

Length

2024-05-11T14:38:42.472404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:42.627404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7691
76.9%
영업 2309
 
23.1%

폐업일자
Date

MISSING 

Distinct4201
Distinct (%)54.6%
Missing2309
Missing (%)23.1%
Memory size156.2 KiB
Minimum1986-04-03 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:38:42.787208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:42.979453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct6586
Distinct (%)92.4%
Missing2872
Missing (%)28.7%
Memory size156.2 KiB
2024-05-11T14:38:43.288678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8612514
Min length2

Characters and Unicode

Total characters70291
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6344 ?
Unique (%)89.0%

Sample

1st row0208464034
2nd row0205854319
3rd row02 8179887
4th row02 8155425
5th row02 8138915
ValueCountFrequency (%)
02 4994
39.3%
0 47
 
0.4%
00000 43
 
0.3%
812 40
 
0.3%
822 32
 
0.3%
815 29
 
0.2%
823 28
 
0.2%
070 27
 
0.2%
0200000000 25
 
0.2%
813 24
 
0.2%
Other values (6640) 7431
58.4%
2024-05-11T14:38:43.780715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12847
18.3%
0 11936
17.0%
8 8230
11.7%
6464
9.2%
5 5800
8.3%
1 5491
7.8%
3 4877
 
6.9%
4 4167
 
5.9%
7 3550
 
5.1%
9 3500
 
5.0%
Other values (3) 3429
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63825
90.8%
Space Separator 6464
 
9.2%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12847
20.1%
0 11936
18.7%
8 8230
12.9%
5 5800
9.1%
1 5491
8.6%
3 4877
 
7.6%
4 4167
 
6.5%
7 3550
 
5.6%
9 3500
 
5.5%
6 3427
 
5.4%
Space Separator
ValueCountFrequency (%)
6464
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70291
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12847
18.3%
0 11936
17.0%
8 8230
11.7%
6464
9.2%
5 5800
8.3%
1 5491
7.8%
3 4877
 
6.9%
4 4167
 
5.9%
7 3550
 
5.1%
9 3500
 
5.0%
Other values (3) 3429
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70291
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12847
18.3%
0 11936
17.0%
8 8230
11.7%
6464
9.2%
5 5800
8.3%
1 5491
7.8%
3 4877
 
6.9%
4 4167
 
5.9%
7 3550
 
5.1%
9 3500
 
5.0%
Other values (3) 3429
 
4.9%
Distinct5106
Distinct (%)51.3%
Missing55
Missing (%)0.5%
Memory size156.2 KiB
2024-05-11T14:38:44.493134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0956259
Min length3

Characters and Unicode

Total characters50676
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

Unique3242 ?
Unique (%)32.6%

Sample

1st row17.15
2nd row18.40
3rd row26.40
4th row53.14
5th row35.00
ValueCountFrequency (%)
33.00 85
 
0.9%
30.00 55
 
0.6%
20.00 54
 
0.5%
26.40 41
 
0.4%
21.00 37
 
0.4%
19.80 34
 
0.3%
24.00 33
 
0.3%
16.50 33
 
0.3%
18.00 32
 
0.3%
28.00 30
 
0.3%
Other values (5096) 9511
95.6%
2024-05-11T14:38:45.659653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9945
19.6%
0 6491
12.8%
2 5470
10.8%
1 4827
9.5%
3 4088
8.1%
4 3816
 
7.5%
5 3633
 
7.2%
6 3567
 
7.0%
8 3115
 
6.1%
7 2909
 
5.7%
Other values (2) 2815
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40726
80.4%
Other Punctuation 9950
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6491
15.9%
2 5470
13.4%
1 4827
11.9%
3 4088
10.0%
4 3816
9.4%
5 3633
8.9%
6 3567
8.8%
8 3115
7.6%
7 2909
7.1%
9 2810
6.9%
Other Punctuation
ValueCountFrequency (%)
. 9945
99.9%
, 5
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9945
19.6%
0 6491
12.8%
2 5470
10.8%
1 4827
9.5%
3 4088
8.1%
4 3816
 
7.5%
5 3633
 
7.2%
6 3567
 
7.0%
8 3115
 
6.1%
7 2909
 
5.7%
Other values (2) 2815
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9945
19.6%
0 6491
12.8%
2 5470
10.8%
1 4827
9.5%
3 4088
8.1%
4 3816
 
7.5%
5 3633
 
7.2%
6 3567
 
7.0%
8 3115
 
6.1%
7 2909
 
5.7%
Other values (2) 2815
 
5.6%
Distinct173
Distinct (%)1.7%
Missing33
Missing (%)0.3%
Memory size156.2 KiB
2024-05-11T14:38:46.289619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0919033
Min length6

Characters and Unicode

Total characters60718
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

Unique23 ?
Unique (%)0.2%

Sample

1st row156844
2nd row156090
3rd row156832
4th row156831
5th row156839
ValueCountFrequency (%)
156030 657
 
6.6%
156816 601
 
6.0%
156800 535
 
5.4%
156824 388
 
3.9%
156801 365
 
3.7%
156861 310
 
3.1%
156832 277
 
2.8%
156811 266
 
2.7%
156815 243
 
2.4%
156826 212
 
2.1%
Other values (163) 6113
61.3%
2024-05-11T14:38:47.200608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13546
22.3%
6 11742
19.3%
5 11332
18.7%
8 9222
15.2%
0 5259
 
8.7%
3 2611
 
4.3%
2 1991
 
3.3%
4 1948
 
3.2%
7 1323
 
2.2%
- 916
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59802
98.5%
Dash Punctuation 916
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13546
22.7%
6 11742
19.6%
5 11332
18.9%
8 9222
15.4%
0 5259
 
8.8%
3 2611
 
4.4%
2 1991
 
3.3%
4 1948
 
3.3%
7 1323
 
2.2%
9 828
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 916
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60718
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13546
22.3%
6 11742
19.3%
5 11332
18.7%
8 9222
15.2%
0 5259
 
8.7%
3 2611
 
4.3%
2 1991
 
3.3%
4 1948
 
3.2%
7 1323
 
2.2%
- 916
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60718
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13546
22.3%
6 11742
19.3%
5 11332
18.7%
8 9222
15.2%
0 5259
 
8.7%
3 2611
 
4.3%
2 1991
 
3.3%
4 1948
 
3.2%
7 1323
 
2.2%
- 916
 
1.5%
Distinct6379
Distinct (%)64.0%
Missing33
Missing (%)0.3%
Memory size156.2 KiB
2024-05-11T14:38:47.670587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length58
Mean length23.555935
Min length14

Characters and Unicode

Total characters234782
Distinct characters341
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4579 ?
Unique (%)45.9%

Sample

1st row서울특별시 동작구 상도동 259-89번지
2nd row서울특별시 동작구 사당동 39-1번지
3rd row서울특별시 동작구 상도동 368-50번지
4th row서울특별시 동작구 상도동 32-16번지
5th row서울특별시 동작구 상도동 337-14번지
ValueCountFrequency (%)
서울특별시 9967
23.3%
동작구 9967
23.3%
사당동 2970
 
7.0%
상도동 2093
 
4.9%
노량진동 1596
 
3.7%
신대방동 1226
 
2.9%
흑석동 952
 
2.2%
대방동 618
 
1.4%
1층 474
 
1.1%
상도1동 308
 
0.7%
Other values (5660) 12521
29.3%
2024-05-11T14:38:48.444031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41176
17.5%
20271
 
8.6%
1 10795
 
4.6%
10052
 
4.3%
10003
 
4.3%
9981
 
4.3%
9973
 
4.2%
9971
 
4.2%
9967
 
4.2%
9967
 
4.2%
Other values (331) 92626
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135358
57.7%
Decimal Number 48036
 
20.5%
Space Separator 41176
 
17.5%
Dash Punctuation 9451
 
4.0%
Open Punctuation 242
 
0.1%
Close Punctuation 241
 
0.1%
Other Punctuation 168
 
0.1%
Uppercase Letter 96
 
< 0.1%
Math Symbol 8
 
< 0.1%
Lowercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20271
15.0%
10052
 
7.4%
10003
 
7.4%
9981
 
7.4%
9973
 
7.4%
9971
 
7.4%
9967
 
7.4%
9967
 
7.4%
7767
 
5.7%
7404
 
5.5%
Other values (292) 30002
22.2%
Uppercase Letter
ValueCountFrequency (%)
B 51
53.1%
A 23
24.0%
I 4
 
4.2%
D 3
 
3.1%
G 3
 
3.1%
P 2
 
2.1%
T 2
 
2.1%
S 2
 
2.1%
L 1
 
1.0%
M 1
 
1.0%
Other values (4) 4
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 10795
22.5%
2 5986
12.5%
3 5847
12.2%
0 4711
9.8%
4 4212
 
8.8%
5 3675
 
7.7%
6 3675
 
7.7%
7 3133
 
6.5%
9 3112
 
6.5%
8 2890
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 153
91.1%
@ 10
 
6.0%
. 3
 
1.8%
/ 1
 
0.6%
? 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
a 2
33.3%
e 1
16.7%
t 1
16.7%
p 1
16.7%
b 1
16.7%
Space Separator
ValueCountFrequency (%)
41176
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 242
100.0%
Close Punctuation
ValueCountFrequency (%)
) 241
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135358
57.7%
Common 99322
42.3%
Latin 102
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20271
15.0%
10052
 
7.4%
10003
 
7.4%
9981
 
7.4%
9973
 
7.4%
9971
 
7.4%
9967
 
7.4%
9967
 
7.4%
7767
 
5.7%
7404
 
5.5%
Other values (292) 30002
22.2%
Common
ValueCountFrequency (%)
41176
41.5%
1 10795
 
10.9%
- 9451
 
9.5%
2 5986
 
6.0%
3 5847
 
5.9%
0 4711
 
4.7%
4 4212
 
4.2%
5 3675
 
3.7%
6 3675
 
3.7%
7 3133
 
3.2%
Other values (10) 6661
 
6.7%
Latin
ValueCountFrequency (%)
B 51
50.0%
A 23
22.5%
I 4
 
3.9%
D 3
 
2.9%
G 3
 
2.9%
P 2
 
2.0%
T 2
 
2.0%
a 2
 
2.0%
S 2
 
2.0%
L 1
 
1.0%
Other values (9) 9
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135358
57.7%
ASCII 99424
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41176
41.4%
1 10795
 
10.9%
- 9451
 
9.5%
2 5986
 
6.0%
3 5847
 
5.9%
0 4711
 
4.7%
4 4212
 
4.2%
5 3675
 
3.7%
6 3675
 
3.7%
7 3133
 
3.2%
Other values (29) 6763
 
6.8%
Hangul
ValueCountFrequency (%)
20271
15.0%
10052
 
7.4%
10003
 
7.4%
9981
 
7.4%
9973
 
7.4%
9971
 
7.4%
9967
 
7.4%
9967
 
7.4%
7767
 
5.7%
7404
 
5.5%
Other values (292) 30002
22.2%

도로명주소
Text

MISSING 

Distinct4098
Distinct (%)86.7%
Missing5272
Missing (%)52.7%
Memory size156.2 KiB
2024-05-11T14:38:48.973847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length61
Mean length30.259518
Min length21

Characters and Unicode

Total characters143067
Distinct characters314
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

Unique3604 ?
Unique (%)76.2%

Sample

1st row서울특별시 동작구 상도로 99-6, 1층 (상도동)
2nd row서울특별시 동작구 흑석로 115-10 (흑석동)
3rd row서울특별시 동작구 사당로12길 10-1, 지하1층,지상1층 (사당동)
4th row서울특별시 동작구 상도로 304, 1층 (상도동)
5th row서울특별시 동작구 서달로 165-1 (흑석동, 2층)
ValueCountFrequency (%)
동작구 4728
 
16.9%
서울특별시 4727
 
16.8%
1층 1555
 
5.5%
사당동 1252
 
4.5%
상도동 944
 
3.4%
노량진동 690
 
2.5%
신대방동 479
 
1.7%
흑석동 448
 
1.6%
2층 338
 
1.2%
상도로 323
 
1.2%
Other values (1836) 12575
44.8%
2024-05-11T14:38:49.858596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23338
 
16.3%
10548
 
7.4%
1 7182
 
5.0%
5511
 
3.9%
4926
 
3.4%
( 4904
 
3.4%
) 4903
 
3.4%
4800
 
3.4%
4740
 
3.3%
4733
 
3.3%
Other values (304) 67482
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83731
58.5%
Space Separator 23338
 
16.3%
Decimal Number 21785
 
15.2%
Open Punctuation 4904
 
3.4%
Close Punctuation 4903
 
3.4%
Other Punctuation 3656
 
2.6%
Dash Punctuation 571
 
0.4%
Uppercase Letter 168
 
0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10548
 
12.6%
5511
 
6.6%
4926
 
5.9%
4800
 
5.7%
4740
 
5.7%
4733
 
5.7%
4728
 
5.6%
4728
 
5.6%
4493
 
5.4%
2968
 
3.5%
Other values (272) 31556
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 120
71.4%
A 24
 
14.3%
C 11
 
6.5%
D 5
 
3.0%
T 2
 
1.2%
G 1
 
0.6%
I 1
 
0.6%
R 1
 
0.6%
E 1
 
0.6%
S 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 7182
33.0%
2 3620
16.6%
3 1891
 
8.7%
0 1695
 
7.8%
4 1603
 
7.4%
6 1408
 
6.5%
5 1307
 
6.0%
7 1277
 
5.9%
8 948
 
4.4%
9 854
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 3644
99.7%
? 4
 
0.1%
@ 4
 
0.1%
. 2
 
0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
23338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4904
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4903
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 571
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83731
58.5%
Common 59168
41.4%
Latin 168
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10548
 
12.6%
5511
 
6.6%
4926
 
5.9%
4800
 
5.7%
4740
 
5.7%
4733
 
5.7%
4728
 
5.6%
4728
 
5.6%
4493
 
5.4%
2968
 
3.5%
Other values (272) 31556
37.7%
Common
ValueCountFrequency (%)
23338
39.4%
1 7182
 
12.1%
( 4904
 
8.3%
) 4903
 
8.3%
, 3644
 
6.2%
2 3620
 
6.1%
3 1891
 
3.2%
0 1695
 
2.9%
4 1603
 
2.7%
6 1408
 
2.4%
Other values (11) 4980
 
8.4%
Latin
ValueCountFrequency (%)
B 120
71.4%
A 24
 
14.3%
C 11
 
6.5%
D 5
 
3.0%
T 2
 
1.2%
G 1
 
0.6%
I 1
 
0.6%
R 1
 
0.6%
E 1
 
0.6%
S 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83731
58.5%
ASCII 59336
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23338
39.3%
1 7182
 
12.1%
( 4904
 
8.3%
) 4903
 
8.3%
, 3644
 
6.1%
2 3620
 
6.1%
3 1891
 
3.2%
0 1695
 
2.9%
4 1603
 
2.7%
6 1408
 
2.4%
Other values (22) 5148
 
8.7%
Hangul
ValueCountFrequency (%)
10548
 
12.6%
5511
 
6.6%
4926
 
5.9%
4800
 
5.7%
4740
 
5.7%
4733
 
5.7%
4728
 
5.6%
4728
 
5.6%
4493
 
5.4%
2968
 
3.5%
Other values (272) 31556
37.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)3.4%
Missing5383
Missing (%)53.8%
Infinite0
Infinite (%)0.0%
Mean6987.3154
Minimum6900
Maximum7075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:50.064147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6900
5-th percentile6910
Q16941
median6997
Q37025
95-th percentile7069
Maximum7075
Range175
Interquartile range (IQR)84

Descriptive statistics

Standard deviation50.583396
Coefficient of variation (CV)0.0072393178
Kurtosis-1.1538978
Mean6987.3154
Median Absolute Deviation (MAD)40
Skewness-0.078435918
Sum32260435
Variance2558.68
MonotonicityNot monotonic
2024-05-11T14:38:50.288103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7008 318
 
3.2%
6913 144
 
1.4%
6910 136
 
1.4%
7027 131
 
1.3%
7015 130
 
1.3%
7025 118
 
1.2%
6979 114
 
1.1%
7071 110
 
1.1%
6922 101
 
1.0%
7055 101
 
1.0%
Other values (148) 3214
32.1%
(Missing) 5383
53.8%
ValueCountFrequency (%)
6900 74
0.7%
6902 27
 
0.3%
6904 13
 
0.1%
6905 3
 
< 0.1%
6906 6
 
0.1%
6907 9
 
0.1%
6908 7
 
0.1%
6909 14
 
0.1%
6910 136
1.4%
6911 4
 
< 0.1%
ValueCountFrequency (%)
7075 1
 
< 0.1%
7074 14
 
0.1%
7073 7
 
0.1%
7072 37
 
0.4%
7071 110
1.1%
7070 43
 
0.4%
7069 51
0.5%
7068 26
 
0.3%
7067 29
 
0.3%
7066 2
 
< 0.1%
Distinct8522
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:38:50.799629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length5.3234
Min length1

Characters and Unicode

Total characters53234
Distinct characters1108
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7627 ?
Unique (%)76.3%

Sample

1st row혁이타운
2nd row북경
3rd row멕켄치킨
4th row어제
5th row숙성회전문주주총회
ValueCountFrequency (%)
노량진점 75
 
0.6%
상도점 52
 
0.4%
사당점 50
 
0.4%
중앙대점 44
 
0.4%
이수역점 33
 
0.3%
전주식당 30
 
0.3%
이수점 26
 
0.2%
실내포장마차 25
 
0.2%
숭실대점 23
 
0.2%
신대방점 22
 
0.2%
Other values (8952) 11249
96.7%
2024-05-11T14:38:51.522735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1635
 
3.1%
1283
 
2.4%
1133
 
2.1%
1027
 
1.9%
964
 
1.8%
766
 
1.4%
727
 
1.4%
678
 
1.3%
654
 
1.2%
580
 
1.1%
Other values (1098) 43787
82.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47603
89.4%
Space Separator 1635
 
3.1%
Lowercase Letter 1167
 
2.2%
Uppercase Letter 1011
 
1.9%
Decimal Number 649
 
1.2%
Close Punctuation 476
 
0.9%
Open Punctuation 476
 
0.9%
Other Punctuation 188
 
0.4%
Dash Punctuation 19
 
< 0.1%
Letter Number 4
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1283
 
2.7%
1133
 
2.4%
1027
 
2.2%
964
 
2.0%
766
 
1.6%
727
 
1.5%
678
 
1.4%
654
 
1.4%
580
 
1.2%
578
 
1.2%
Other values (1017) 39213
82.4%
Uppercase Letter
ValueCountFrequency (%)
O 97
 
9.6%
A 89
 
8.8%
B 72
 
7.1%
C 69
 
6.8%
E 59
 
5.8%
N 56
 
5.5%
L 54
 
5.3%
T 48
 
4.7%
R 47
 
4.6%
I 44
 
4.4%
Other values (16) 376
37.2%
Lowercase Letter
ValueCountFrequency (%)
e 172
14.7%
o 128
 
11.0%
a 121
 
10.4%
i 78
 
6.7%
f 68
 
5.8%
n 64
 
5.5%
r 57
 
4.9%
c 56
 
4.8%
s 52
 
4.5%
l 49
 
4.2%
Other values (15) 322
27.6%
Decimal Number
ValueCountFrequency (%)
1 118
18.2%
2 116
17.9%
0 104
16.0%
3 69
10.6%
9 59
9.1%
5 50
7.7%
4 43
 
6.6%
8 33
 
5.1%
7 29
 
4.5%
6 28
 
4.3%
Other Punctuation
ValueCountFrequency (%)
& 64
34.0%
. 63
33.5%
, 27
14.4%
' 10
 
5.3%
? 10
 
5.3%
! 7
 
3.7%
# 3
 
1.6%
: 2
 
1.1%
1
 
0.5%
; 1
 
0.5%
Other Symbol
ValueCountFrequency (%)
2
66.7%
1
33.3%
Letter Number
ValueCountFrequency (%)
2
50.0%
2
50.0%
Space Separator
ValueCountFrequency (%)
1635
100.0%
Close Punctuation
ValueCountFrequency (%)
) 476
100.0%
Open Punctuation
ValueCountFrequency (%)
( 476
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47543
89.3%
Common 3449
 
6.5%
Latin 2182
 
4.1%
Han 60
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1283
 
2.7%
1133
 
2.4%
1027
 
2.2%
964
 
2.0%
766
 
1.6%
727
 
1.5%
678
 
1.4%
654
 
1.4%
580
 
1.2%
578
 
1.2%
Other values (974) 39153
82.4%
Latin
ValueCountFrequency (%)
e 172
 
7.9%
o 128
 
5.9%
a 121
 
5.5%
O 97
 
4.4%
A 89
 
4.1%
i 78
 
3.6%
B 72
 
3.3%
C 69
 
3.2%
f 68
 
3.1%
n 64
 
2.9%
Other values (43) 1224
56.1%
Han
ValueCountFrequency (%)
5
 
8.3%
4
 
6.7%
4
 
6.7%
3
 
5.0%
3
 
5.0%
2
 
3.3%
2
 
3.3%
2
 
3.3%
1
 
1.7%
1
 
1.7%
Other values (33) 33
55.0%
Common
ValueCountFrequency (%)
1635
47.4%
) 476
 
13.8%
( 476
 
13.8%
1 118
 
3.4%
2 116
 
3.4%
0 104
 
3.0%
3 69
 
2.0%
& 64
 
1.9%
. 63
 
1.8%
9 59
 
1.7%
Other values (18) 269
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47543
89.3%
ASCII 5623
 
10.6%
CJK 58
 
0.1%
Number Forms 4
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
None 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1635
29.1%
) 476
 
8.5%
( 476
 
8.5%
e 172
 
3.1%
o 128
 
2.3%
a 121
 
2.2%
1 118
 
2.1%
2 116
 
2.1%
0 104
 
1.8%
O 97
 
1.7%
Other values (66) 2180
38.8%
Hangul
ValueCountFrequency (%)
1283
 
2.7%
1133
 
2.4%
1027
 
2.2%
964
 
2.0%
766
 
1.6%
727
 
1.5%
678
 
1.4%
654
 
1.4%
580
 
1.2%
578
 
1.2%
Other values (974) 39153
82.4%
CJK
ValueCountFrequency (%)
5
 
8.6%
4
 
6.9%
4
 
6.9%
3
 
5.2%
3
 
5.2%
2
 
3.4%
2
 
3.4%
2
 
3.4%
1
 
1.7%
1
 
1.7%
Other values (31) 31
53.4%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
2
50.0%
None
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
50.0%
1
50.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%
Distinct6513
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-08 00:00:00
Maximum2024-05-09 16:13:24
2024-05-11T14:38:51.763119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:52.006806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7326 
U
2674 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7326
73.3%
U 2674
 
26.7%

Length

2024-05-11T14:38:52.218417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:52.360843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7326
73.3%
u 2674
 
26.7%
Distinct1205
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:38:52.529494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:52.780902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3778 
분식
1849 
기타
874 
경양식
794 
정종/대포집/소주방
640 
Other values (21)
2065 

Length

Max length15
Median length2
Mean length3.0708
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row경양식
2nd row정종/대포집/소주방
3rd row분식
4th row경양식
5th row일식

Common Values

ValueCountFrequency (%)
한식 3778
37.8%
분식 1849
18.5%
기타 874
 
8.7%
경양식 794
 
7.9%
정종/대포집/소주방 640
 
6.4%
호프/통닭 609
 
6.1%
일식 309
 
3.1%
중국식 293
 
2.9%
통닭(치킨) 275
 
2.8%
전통찻집 171
 
1.7%
Other values (16) 408
 
4.1%

Length

2024-05-11T14:38:53.033288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3778
37.8%
분식 1849
18.5%
기타 874
 
8.7%
경양식 794
 
7.9%
정종/대포집/소주방 640
 
6.4%
호프/통닭 609
 
6.1%
일식 309
 
3.1%
중국식 293
 
2.9%
통닭(치킨 275
 
2.8%
전통찻집 171
 
1.7%
Other values (16) 408
 
4.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3419
Distinct (%)37.2%
Missing801
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean195598.25
Minimum191481.82
Maximum198428.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:53.279621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191481.82
5-th percentile192220.2
Q1194178.6
median195200.94
Q3197549.22
95-th percentile198266.48
Maximum198428.61
Range6946.7945
Interquartile range (IQR)3370.6227

Descriptive statistics

Standard deviation1920.4517
Coefficient of variation (CV)0.009818348
Kurtosis-1.1022727
Mean195598.25
Median Absolute Deviation (MAD)1521.9511
Skewness-0.064558457
Sum1.7993083 × 109
Variance3688134.8
MonotonicityNot monotonic
2024-05-11T14:38:53.562443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193218.36400997 70
 
0.7%
193279.599095483 51
 
0.5%
198303.527071078 36
 
0.4%
195079.265528912 35
 
0.4%
193140.052317678 33
 
0.3%
191691.678396263 33
 
0.3%
193273.484014052 32
 
0.3%
193810.01277159 30
 
0.3%
194812.59305916 29
 
0.3%
194346.156670595 29
 
0.3%
Other values (3409) 8821
88.2%
(Missing) 801
 
8.0%
ValueCountFrequency (%)
191481.81674639 4
 
< 0.1%
191484.231170935 3
 
< 0.1%
191548.535775618 4
 
< 0.1%
191555.354381759 3
 
< 0.1%
191625.827023746 2
 
< 0.1%
191647.259479634 1
 
< 0.1%
191673.025374635 2
 
< 0.1%
191677.374890384 2
 
< 0.1%
191688.979039976 6
 
0.1%
191691.678396263 33
0.3%
ValueCountFrequency (%)
198428.611275 2
 
< 0.1%
198369.267432933 2
 
< 0.1%
198364.235287192 6
0.1%
198358.52130279 1
 
< 0.1%
198357.541280509 1
 
< 0.1%
198354.350098982 8
0.1%
198353.622717679 1
 
< 0.1%
198351.814626867 1
 
< 0.1%
198347.013335361 3
 
< 0.1%
198345.602269773 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3419
Distinct (%)37.2%
Missing801
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean443936.64
Minimum441553.73
Maximum445956.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:53.829309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441553.73
5-th percentile441969.63
Q1442807.05
median444085.6
Q3445038.76
95-th percentile445643.8
Maximum445956.72
Range4402.9894
Interquartile range (IQR)2231.7051

Descriptive statistics

Standard deviation1222.3958
Coefficient of variation (CV)0.0027535367
Kurtosis-1.2749832
Mean443936.64
Median Absolute Deviation (MAD)1115.3418
Skewness-0.14980883
Sum4.0837732 × 109
Variance1494251.5
MonotonicityNot monotonic
2024-05-11T14:38:54.072101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443239.581054145 70
 
0.7%
443230.418234155 51
 
0.5%
442742.422887932 36
 
0.4%
445413.288375132 35
 
0.4%
443178.674686446 33
 
0.3%
442818.113681285 33
 
0.3%
445011.250115029 32
 
0.3%
445610.160717686 30
 
0.3%
445692.62623807 29
 
0.3%
445823.500892497 29
 
0.3%
Other values (3409) 8821
88.2%
(Missing) 801
 
8.0%
ValueCountFrequency (%)
441553.731052152 1
 
< 0.1%
441564.273638609 1
 
< 0.1%
441566.953618972 2
 
< 0.1%
441569.058208929 2
 
< 0.1%
441569.362995612 4
< 0.1%
441577.448324663 1
 
< 0.1%
441581.838470649 1
 
< 0.1%
441588.861462309 5
0.1%
441595.660481209 1
 
< 0.1%
441621.646831742 1
 
< 0.1%
ValueCountFrequency (%)
445956.720487001 1
 
< 0.1%
445930.454113113 1
 
< 0.1%
445901.413432497 24
0.2%
445881.266053 1
 
< 0.1%
445868.076456773 2
 
< 0.1%
445836.993606646 3
 
< 0.1%
445823.500892497 29
0.3%
445816.474374 1
 
< 0.1%
445790.549860682 23
0.2%
445764.748202257 3
 
< 0.1%

위생업태명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3280 
분식
1761 
<NA>
1378 
경양식
728 
정종/대포집/소주방
611 
Other values (21)
2242 

Length

Max length15
Median length2
Mean length3.2348
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row경양식
2nd row정종/대포집/소주방
3rd row분식
4th row경양식
5th row일식

Common Values

ValueCountFrequency (%)
한식 3280
32.8%
분식 1761
17.6%
<NA> 1378
13.8%
경양식 728
 
7.3%
정종/대포집/소주방 611
 
6.1%
기타 512
 
5.1%
호프/통닭 497
 
5.0%
통닭(치킨) 244
 
2.4%
일식 244
 
2.4%
중국식 238
 
2.4%
Other values (16) 507
 
5.1%

Length

2024-05-11T14:38:54.297138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3280
32.8%
분식 1761
17.6%
na 1378
13.8%
경양식 728
 
7.3%
정종/대포집/소주방 611
 
6.1%
기타 512
 
5.1%
호프/통닭 497
 
5.0%
통닭(치킨 244
 
2.4%
일식 244
 
2.4%
중국식 238
 
2.4%
Other values (16) 507
 
5.1%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct11
Distinct (%)0.2%
Missing3893
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean0.42410349
Minimum0
Maximum93
Zeros4273
Zeros (%)42.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:54.472619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8379115
Coefficient of variation (CV)4.3336393
Kurtosis2110.1002
Mean0.42410349
Median Absolute Deviation (MAD)0
Skewness42.232809
Sum2590
Variance3.3779188
MonotonicityNot monotonic
2024-05-11T14:38:54.647558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 4273
42.7%
1 1429
 
14.3%
2 307
 
3.1%
3 65
 
0.7%
4 20
 
0.2%
7 4
 
< 0.1%
5 3
 
< 0.1%
6 2
 
< 0.1%
93 2
 
< 0.1%
11 1
 
< 0.1%
(Missing) 3893
38.9%
ValueCountFrequency (%)
0 4273
42.7%
1 1429
 
14.3%
2 307
 
3.1%
3 65
 
0.7%
4 20
 
0.2%
5 3
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
11 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
93 2
 
< 0.1%
20 1
 
< 0.1%
11 1
 
< 0.1%
7 4
 
< 0.1%
6 2
 
< 0.1%
5 3
 
< 0.1%
4 20
 
0.2%
3 65
 
0.7%
2 307
 
3.1%
1 1429
14.3%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.2%
Missing3873
Missing (%)38.7%
Infinite0
Infinite (%)0.0%
Mean0.74832708
Minimum0
Maximum93
Zeros3208
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:54.833275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5495895
Coefficient of variation (CV)2.0707382
Kurtosis2052.8118
Mean0.74832708
Median Absolute Deviation (MAD)0
Skewness35.153708
Sum4585
Variance2.4012276
MonotonicityNot monotonic
2024-05-11T14:38:55.022167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 3208
32.1%
1 1812
18.1%
2 812
 
8.1%
3 219
 
2.2%
4 40
 
0.4%
5 17
 
0.2%
7 5
 
0.1%
10 4
 
< 0.1%
6 3
 
< 0.1%
8 2
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 3873
38.7%
ValueCountFrequency (%)
0 3208
32.1%
1 1812
18.1%
2 812
 
8.1%
3 219
 
2.2%
4 40
 
0.4%
5 17
 
0.2%
6 3
 
< 0.1%
7 5
 
0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
< 0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
7 5
 
0.1%
6 3
 
< 0.1%
5 17
0.2%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
3917 
주택가주변
3834 
기타
1765 
아파트지역
 
259
유흥업소밀집지역
 
139
Other values (3)
 
86

Length

Max length8
Median length7
Mean length4.1455
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3917
39.2%
주택가주변 3834
38.3%
기타 1765
17.6%
아파트지역 259
 
2.6%
유흥업소밀집지역 139
 
1.4%
학교정화(상대) 57
 
0.6%
학교정화(절대) 21
 
0.2%
결혼예식장주변 8
 
0.1%

Length

2024-05-11T14:38:55.256467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:55.472960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3917
39.2%
주택가주변 3834
38.3%
기타 1765
17.6%
아파트지역 259
 
2.6%
유흥업소밀집지역 139
 
1.4%
학교정화(상대 57
 
0.6%
학교정화(절대 21
 
0.2%
결혼예식장주변 8
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4738 
기타
3583 
지도
882 
관리
 
265
 
254
Other values (3)
 
278

Length

Max length4
Median length2
Mean length2.9173
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4738
47.4%
기타 3583
35.8%
지도 882
 
8.8%
관리 265
 
2.6%
254
 
2.5%
자율 220
 
2.2%
49
 
0.5%
우수 9
 
0.1%

Length

2024-05-11T14:38:55.737699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:55.946676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4738
47.4%
기타 3583
35.8%
지도 882
 
8.8%
관리 265
 
2.6%
254
 
2.5%
자율 220
 
2.2%
49
 
0.5%
우수 9
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
7257 
<NA>
2676 
상수도(음용)지하수(주방용)겸용
 
65
간이상수도
 
1
지하수전용
 
1

Length

Max length17
Median length5
Mean length4.8104
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 7257
72.6%
<NA> 2676
 
26.8%
상수도(음용)지하수(주방용)겸용 65
 
0.7%
간이상수도 1
 
< 0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T14:38:56.178888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:56.373697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 7257
72.6%
na 2676
 
26.8%
상수도(음용)지하수(주방용)겸용 65
 
0.7%
간이상수도 1
 
< 0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9629 
0
 
371

Length

Max length4
Median length4
Mean length3.8887
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> 9629
96.3%
0 371
 
3.7%

Length

2024-05-11T14:38:56.553809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:57.098198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9629
96.3%
0 371
 
3.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:57.271994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:57.437156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:57.618787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:57.801217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:57.991335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.157148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:58.341641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.516463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:58.716126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.898854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9627 
0
 
373

Length

Max length4
Median length4
Mean length3.8881
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> 9627
96.3%
0 373
 
3.7%

Length

2024-05-11T14:38:59.079269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:59.289609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9627
96.3%
0 373
 
3.7%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1378
Missing (%)13.8%
Memory size97.7 KiB
False
8448 
True
 
174
(Missing)
1378 
ValueCountFrequency (%)
False 8448
84.5%
True 174
 
1.7%
(Missing) 1378
 
13.8%
2024-05-11T14:38:59.472280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct4660
Distinct (%)54.0%
Missing1378
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean54.314145
Minimum0
Maximum1948.76
Zeros59
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:38:59.698136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.4805
Q122.3825
median34.025
Q363.6
95-th percentile144.6565
Maximum1948.76
Range1948.76
Interquartile range (IQR)41.2175

Descriptive statistics

Standard deviation73.075671
Coefficient of variation (CV)1.3454262
Kurtosis158.84315
Mean54.314145
Median Absolute Deviation (MAD)15.175
Skewness9.3969182
Sum468296.56
Variance5340.0537
MonotonicityNot monotonic
2024-05-11T14:38:59.953664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 59
 
0.6%
33.0 51
 
0.5%
20.0 45
 
0.4%
21.0 34
 
0.3%
26.4 33
 
0.3%
19.8 31
 
0.3%
16.5 30
 
0.3%
30.0 28
 
0.3%
24.0 26
 
0.3%
23.1 26
 
0.3%
Other values (4650) 8259
82.6%
(Missing) 1378
 
13.8%
ValueCountFrequency (%)
0.0 59
0.6%
3.03 1
 
< 0.1%
4.55 1
 
< 0.1%
5.0 1
 
< 0.1%
5.15 1
 
< 0.1%
5.16 1
 
< 0.1%
5.17 1
 
< 0.1%
5.39 1
 
< 0.1%
5.8 1
 
< 0.1%
6.0 1
 
< 0.1%
ValueCountFrequency (%)
1948.76 1
< 0.1%
1926.03 1
< 0.1%
1421.91 1
< 0.1%
1162.44 1
< 0.1%
1018.03 1
< 0.1%
974.05 1
< 0.1%
966.6 1
< 0.1%
956.11 1
< 0.1%
946.31 1
< 0.1%
927.13 1
< 0.1%
Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T14:39:00.183911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length2.2
Min length1

Characters and Unicode

Total characters11
Distinct characters6
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row1.1
2nd row`
3rd row
4th row-
5th row00000
ValueCountFrequency (%)
2
50.0%
1.1 1
25.0%
00000 1
25.0%
2024-05-11T14:39:00.675027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5
45.5%
1 2
 
18.2%
. 1
 
9.1%
` 1
 
9.1%
1
 
9.1%
- 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
63.6%
Other Punctuation 1
 
9.1%
Modifier Symbol 1
 
9.1%
Space Separator 1
 
9.1%
Dash Punctuation 1
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
71.4%
1 2
 
28.6%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5
45.5%
1 2
 
18.2%
. 1
 
9.1%
` 1
 
9.1%
1
 
9.1%
- 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5
45.5%
1 2
 
18.2%
. 1
 
9.1%
` 1
 
9.1%
1
 
9.1%
- 1
 
9.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
69431900003190000-101-1984-0482819840420<NA>3폐업2폐업19900824<NA><NA><NA>020846403417.15156844서울특별시 동작구 상도동 259-89번지<NA><NA>혁이타운2001-09-29 00:00:00I2018-08-31 23:59:59.0경양식194129.651017444001.815177경양식01주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N17.15<NA><NA><NA>
20731900003190000-101-1980-0244219801220<NA>3폐업2폐업19940117<NA><NA><NA>020585431918.40156090서울특별시 동작구 사당동 39-1번지<NA><NA>북경2002-01-15 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방198354.350099443206.101229정종/대포집/소주방12주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N18.4<NA><NA><NA>
189331900003190000-101-1990-0265919900524<NA>3폐업2폐업19951031<NA><NA><NA>02 817988726.40156832서울특별시 동작구 상도동 368-50번지<NA><NA>멕켄치킨2002-01-17 00:00:00I2018-08-31 23:59:59.0분식194574.597731444689.150327분식01주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.4<NA><NA><NA>
324931900003190000-101-1993-0530819930903<NA>3폐업2폐업19950728<NA><NA><NA>02 815542553.14156831서울특별시 동작구 상도동 32-16번지<NA><NA>어제2001-09-29 00:00:00I2018-08-31 23:59:59.0경양식195153.415292444726.029491경양식02주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.14<NA><NA><NA>
1256131900003190000-101-2020-0002420200207<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.00156839서울특별시 동작구 상도동 337-14번지서울특별시 동작구 상도로 99-6, 1층 (상도동)6952숙성회전문주주총회2020-02-07 15:40:51I2020-02-09 00:23:23.0일식193865.045329444264.948606일식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N35.0<NA><NA><NA>
33931900003190000-101-1982-0032819821023<NA>3폐업2폐업20160129<NA><NA><NA>02 813891559.86156860서울특별시 동작구 흑석동 164-6번지서울특별시 동작구 흑석로 115-10 (흑석동)<NA>부산회집2009-04-01 10:43:46I2018-08-31 23:59:59.0일식196504.721773445206.68902일식12주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N59.86<NA><NA><NA>
733631900003190000-101-2002-0037220021114<NA>3폐업2폐업20060314<NA><NA><NA>02 825450844.17156861서울특별시 동작구 흑석동 190-34번지<NA><NA>호박2005-07-06 00:00:00I2018-08-31 23:59:59.0호프/통닭196312.564849445008.441402호프/통닭00학교정화(절대)<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N44.17<NA><NA><NA>
568331900003190000-101-1999-0492419991023<NA>3폐업2폐업20000223<NA><NA><NA>02 522447297.49156827서울특별시 동작구 사당동 1039-4번지<NA><NA>유니코2000-02-24 00:00:00I2018-08-31 23:59:59.0경양식198022.393645441724.071649경양식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.49<NA><NA><NA>
63931900003190000-101-1984-0316519840926<NA>3폐업2폐업19951031<NA><NA><NA>02 583298114.00156815서울특별시 동작구 사당동 88-22번지<NA><NA>2002-02-01 00:00:00I2018-08-31 23:59:59.0분식198275.106271442932.979684분식11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N14.0<NA><NA><NA>
647431900003190000-101-2000-0795020001028<NA>3폐업2폐업20061025<NA><NA><NA>02 583601762.08156821서울특별시 동작구 사당동 269-25번지<NA><NA>쉼터호프2001-02-01 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방197382.830348442357.854263정종/대포집/소주방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.08<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
899431900003190000-101-2007-0010620070517<NA>3폐업2폐업20130205<NA><NA><NA><NA>35.15156819서울특별시 동작구 사당동 252-17번지 서림빌딩 105호서울특별시 동작구 사당로 215 (사당동,서림빌딩 105호)7004윤흥분삼삼국밥2007-05-17 00:00:00I2018-08-31 23:59:59.0한식197486.501626442493.781452한식22주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N35.15<NA><NA><NA>
1022031900003190000-101-2012-0000820120112<NA>3폐업2폐업20190425<NA><NA><NA>816889325.53156832서울특별시 동작구 상도동 360-67번지서울특별시 동작구 상도로15길 99, 1층 (상도동)6949고향칼국수2019-04-25 16:02:36U2019-04-27 02:40:00.0한식194290.674734444702.412347한식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.53<NA><NA><NA>
129031900003190000-101-1987-0523419940120<NA>3폐업2폐업20041001<NA><NA><NA>02 817508058.42156860서울특별시 동작구 흑석동 180-6번지<NA><NA>라이트라인2004-04-30 00:00:00I2018-08-31 23:59:59.0경양식196540.938516445164.579131경양식11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N58.42<NA><NA><NA>
492231900003190000-101-1997-0431719970814<NA>3폐업2폐업20071127<NA><NA><NA>02 845321489.60156855서울특별시 동작구 신대방동 708-0번지 해태보라매타워 2층<NA><NA>진지방순대국2006-04-10 00:00:00I2018-08-31 23:59:59.0한식193279.599095443230.418234한식00아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N89.6<NA><NA><NA>
108031900003190000-101-1986-0501919860901<NA>3폐업2폐업20050330<NA><NA><NA>02 8223600174.50156839서울특별시 동작구 상도동 324-1번지<NA><NA>타임벨2001-04-18 00:00:00I2018-08-31 23:59:59.0경양식193896.384766444196.484791경양식21주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N174.5<NA><NA><NA>
1264831900003190000-101-2020-0011120200529<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.20156815서울특별시 동작구 사당동 77-67번지서울특별시 동작구 동작대로29나길 32, 1층 102호 (사당동)6997인생닭강정2020-05-29 15:49:57I2020-05-31 00:23:29.0호프/통닭198234.406542443034.615249호프/통닭<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N21.2<NA><NA><NA>
1297831900003190000-101-2021-0016520210712<NA>1영업/정상1영업<NA><NA><NA><NA>02 811 775458.80156861서울특별시 동작구 흑석동 223-18서울특별시 동작구 흑석로 88, 2층 (흑석동)6973백채김치찌개 중앙대점2022-03-31 13:48:48U2021-12-04 00:02:00.0한식196340.622511444982.102029<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
849531900003190000-101-2005-0027520051020<NA>3폐업2폐업20091009<NA><NA><NA>023477370162.94156824서울특별시 동작구 사당동 708-446번지<NA><NA>홍메까 참치2008-08-20 13:07:20I2018-08-31 23:59:59.0한식198159.671808442573.837997한식21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N62.94<NA><NA><NA>
80231900003190000-101-1985-0205419850611<NA>3폐업2폐업19951031<NA><NA><NA>02 812551166.90156030서울특별시 동작구 상도동 755-0번지<NA><NA>미가도2001-09-29 00:00:00I2018-08-31 23:59:59.0전통찻집<NA><NA>전통찻집03주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N66.9<NA><NA><NA>
479431900003190000-101-1997-0226019970411<NA>3폐업2폐업20210917<NA><NA><NA>02 826863163.93156847서울특별시 동작구 신대방동 351-5서울특별시 동작구 보라매로 105 (신대방동)7056펀비어킹2021-09-17 10:18:26U2021-09-19 02:40:00.0정종/대포집/소주방193542.317495444054.924159정종/대포집/소주방00유흥업소밀집지역기타상수도전용00000<NA>00N63.93<NA><NA><NA>