Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells100647
Missing cells (%)22.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory382.0 B

Variable types

Categorical18
Text9
DateTime4
Unsupported6
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18674/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소주된음식 has constant value ""Constant
데이터갱신구분 is highly imbalanced (52.7%)Imbalance
급수시설구분명 is highly imbalanced (83.9%)Imbalance
총인원 is highly imbalanced (92.9%)Imbalance
본사종업원수 is highly imbalanced (92.5%)Imbalance
공장사무직종업원수 is highly imbalanced (92.5%)Imbalance
공장판매직종업원수 is highly imbalanced (92.5%)Imbalance
공장생산직종업원수 is highly imbalanced (92.5%)Imbalance
보증액 is highly imbalanced (92.5%)Imbalance
월세액 is highly imbalanced (92.5%)Imbalance
다중이용업소여부 is highly imbalanced (95.4%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1131 (11.3%) 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 1055 (10.5%) missing valuesMissing
도로명주소 has 7523 (75.2%) missing valuesMissing
도로명우편번호 has 7565 (75.6%) missing valuesMissing
좌표정보(X) has 461 (4.6%) missing valuesMissing
좌표정보(Y) has 461 (4.6%) missing valuesMissing
남성종사자수 has 798 (8.0%) missing valuesMissing
여성종사자수 has 798 (8.0%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 422 (4.2%) missing valuesMissing
시설총규모 has 422 (4.2%) missing valuesMissing
전통업소지정번호 has 9995 (> 99.9%) missing valuesMissing
전통업소주된음식 has 9999 (> 99.9%) missing valuesMissing
홈페이지 has 10000 (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
건물소유구분명 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 7541 (75.4%) zerosZeros
여성종사자수 has 7240 (72.4%) zerosZeros

Reproduction

Analysis started2024-05-11 08:53:14.346988
Analysis finished2024-05-11 08:53:20.702409
Duration6.36 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
3220000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 10000
100.0%

Length

2024-05-11T08:53:21.003978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:21.368393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:53:21.970343image/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 row3220000-101-2000-22562
2nd row3220000-101-2006-00617
3rd row3220000-101-1984-12041
4th row3220000-101-1994-14789
5th row3220000-101-1992-08891
ValueCountFrequency (%)
3220000-101-2000-22562 1
 
< 0.1%
3220000-101-1998-07230 1
 
< 0.1%
3220000-101-2003-00772 1
 
< 0.1%
3220000-101-1998-04815 1
 
< 0.1%
3220000-101-1989-10820 1
 
< 0.1%
3220000-101-1996-09003 1
 
< 0.1%
3220000-101-1989-15490 1
 
< 0.1%
3220000-101-1998-08184 1
 
< 0.1%
3220000-101-1996-14045 1
 
< 0.1%
3220000-101-1992-16059 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T08:53:23.116256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 69284
31.5%
1 35074
15.9%
- 30000
13.6%
2 29976
13.6%
9 15401
 
7.0%
3 14906
 
6.8%
8 6192
 
2.8%
4 5176
 
2.4%
5 4827
 
2.2%
6 4609
 
2.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 69284
36.5%
1 35074
18.5%
2 29976
15.8%
9 15401
 
8.1%
3 14906
 
7.8%
8 6192
 
3.3%
4 5176
 
2.7%
5 4827
 
2.5%
6 4609
 
2.4%
7 4555
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 69284
31.5%
1 35074
15.9%
- 30000
13.6%
2 29976
13.6%
9 15401
 
7.0%
3 14906
 
6.8%
8 6192
 
2.8%
4 5176
 
2.4%
5 4827
 
2.2%
6 4609
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 69284
31.5%
1 35074
15.9%
- 30000
13.6%
2 29976
13.6%
9 15401
 
7.0%
3 14906
 
6.8%
8 6192
 
2.8%
4 5176
 
2.4%
5 4827
 
2.2%
6 4609
 
2.1%
Distinct5022
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1909-05-28 00:00:00
Maximum2007-08-21 00:00:00
2024-05-11T08:53:23.572560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:24.138825image/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
8869 
1
1131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 8869
88.7%
1 1131
 
11.3%

Length

2024-05-11T08:53:24.628407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:24.976340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8869
88.7%
1 1131
 
11.3%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8869 
영업/정상
1131 

Length

Max length5
Median length2
Mean length2.3393
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8869
88.7%
영업/정상 1131
 
11.3%

Length

2024-05-11T08:53:25.508781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:25.926250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8869
88.7%
영업/정상 1131
 
11.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8869 
1
1131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 8869
88.7%
1 1131
 
11.3%

Length

2024-05-11T08:53:26.429048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:27.053945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8869
88.7%
1 1131
 
11.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8869 
영업
1131 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8869
88.7%
영업 1131
 
11.3%

Length

2024-05-11T08:53:27.687765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:28.125323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8869
88.7%
영업 1131
 
11.3%

폐업일자
Date

MISSING 

Distinct4515
Distinct (%)50.9%
Missing1131
Missing (%)11.3%
Memory size156.2 KiB
Minimum1985-04-01 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T08:53:28.788717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:29.526918image/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 

Distinct7746
Distinct (%)86.6%
Missing1055
Missing (%)10.5%
Memory size156.2 KiB
2024-05-11T08:53:30.788885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.4642817
Min length2

Characters and Unicode

Total characters84658
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

Unique7518 ?
Unique (%)84.0%

Sample

1st row02 4593195
2nd row02
3rd row0205437494
4th row0205496460
5th row5385381
ValueCountFrequency (%)
02 5317
37.8%
0200000000 370
 
2.6%
00000 209
 
1.5%
0 64
 
0.5%
0000000 9
 
0.1%
517 8
 
0.1%
031 7
 
< 0.1%
5413111 6
 
< 0.1%
070 5
 
< 0.1%
555 5
 
< 0.1%
Other values (7769) 8081
57.4%
2024-05-11T08:53:32.791588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18040
21.3%
2 12763
15.1%
5 12411
14.7%
4 7293
8.6%
5790
 
6.8%
6 5666
 
6.7%
1 5314
 
6.3%
3 4809
 
5.7%
7 4708
 
5.6%
8 4162
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78868
93.2%
Space Separator 5790
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18040
22.9%
2 12763
16.2%
5 12411
15.7%
4 7293
9.2%
6 5666
 
7.2%
1 5314
 
6.7%
3 4809
 
6.1%
7 4708
 
6.0%
8 4162
 
5.3%
9 3702
 
4.7%
Space Separator
ValueCountFrequency (%)
5790
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84658
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18040
21.3%
2 12763
15.1%
5 12411
14.7%
4 7293
8.6%
5790
 
6.8%
6 5666
 
6.7%
1 5314
 
6.3%
3 4809
 
5.7%
7 4708
 
5.6%
8 4162
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84658
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18040
21.3%
2 12763
15.1%
5 12411
14.7%
4 7293
8.6%
5790
 
6.8%
6 5666
 
6.7%
1 5314
 
6.3%
3 4809
 
5.7%
7 4708
 
5.6%
8 4162
 
4.9%
Distinct6164
Distinct (%)61.7%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T08:53:34.014807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.3637001
Min length3

Characters and Unicode

Total characters53578
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

Unique4696 ?
Unique (%)47.0%

Sample

1st row25.00
2nd row57.00
3rd row97.50
4th row102.36
5th row207.63
ValueCountFrequency (%)
26.44 82
 
0.8%
29.75 72
 
0.7%
49.58 52
 
0.5%
82.64 50
 
0.5%
23.14 48
 
0.5%
59.50 42
 
0.4%
66.11 42
 
0.4%
132.23 36
 
0.4%
99.17 31
 
0.3%
19.83 29
 
0.3%
Other values (6154) 9505
95.2%
2024-05-11T08:53:35.882292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9989
18.6%
0 6019
11.2%
1 5953
11.1%
2 5440
10.2%
4 4131
7.7%
6 4035
7.5%
3 4007
7.5%
5 3947
 
7.4%
9 3495
 
6.5%
8 3428
 
6.4%
Other values (2) 3134
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43555
81.3%
Other Punctuation 10023
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6019
13.8%
1 5953
13.7%
2 5440
12.5%
4 4131
9.5%
6 4035
9.3%
3 4007
9.2%
5 3947
9.1%
9 3495
8.0%
8 3428
7.9%
7 3100
7.1%
Other Punctuation
ValueCountFrequency (%)
. 9989
99.7%
, 34
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 53578
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9989
18.6%
0 6019
11.2%
1 5953
11.1%
2 5440
10.2%
4 4131
7.7%
6 4035
7.5%
3 4007
7.5%
5 3947
 
7.4%
9 3495
 
6.5%
8 3428
 
6.4%
Other values (2) 3134
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53578
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9989
18.6%
0 6019
11.2%
1 5953
11.1%
2 5440
10.2%
4 4131
7.7%
6 4035
7.5%
3 4007
7.5%
5 3947
 
7.4%
9 3495
 
6.5%
8 3428
 
6.4%
Other values (2) 3134
 
5.8%
Distinct331
Distinct (%)3.3%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T08:53:37.141849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0259078
Min length6

Characters and Unicode

Total characters60241
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

Unique77 ?
Unique (%)0.8%

Sample

1st row135516
2nd row135816
3rd row135931
4th row135815
5th row135889
ValueCountFrequency (%)
135897 422
 
4.2%
135896 189
 
1.9%
135240 173
 
1.7%
135090 165
 
1.7%
135825 159
 
1.6%
135840 159
 
1.6%
135891 159
 
1.6%
135936 156
 
1.6%
135830 148
 
1.5%
135954 142
 
1.4%
Other values (321) 8125
81.3%
2024-05-11T08:53:38.869017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12604
20.9%
5 12595
20.9%
3 11898
19.8%
8 6775
11.2%
9 6051
10.0%
0 2372
 
3.9%
2 2233
 
3.7%
4 2104
 
3.5%
7 1881
 
3.1%
6 1469
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59982
99.6%
Dash Punctuation 259
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12604
21.0%
5 12595
21.0%
3 11898
19.8%
8 6775
11.3%
9 6051
10.1%
0 2372
 
4.0%
2 2233
 
3.7%
4 2104
 
3.5%
7 1881
 
3.1%
6 1469
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 259
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60241
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12604
20.9%
5 12595
20.9%
3 11898
19.8%
8 6775
11.2%
9 6051
10.0%
0 2372
 
3.9%
2 2233
 
3.7%
4 2104
 
3.5%
7 1881
 
3.1%
6 1469
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12604
20.9%
5 12595
20.9%
3 11898
19.8%
8 6775
11.2%
9 6051
10.0%
0 2372
 
3.9%
2 2233
 
3.7%
4 2104
 
3.5%
7 1881
 
3.1%
6 1469
 
2.4%
Distinct7858
Distinct (%)78.6%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T08:53:40.284426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length55
Mean length25.169351
Min length14

Characters and Unicode

Total characters251618
Distinct characters397
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6583 ?
Unique (%)65.8%

Sample

1st row서울특별시 강남구 일원동 678-7번지 지상1층
2nd row서울특별시 강남구 논현동 67-4번지 지상1층
3rd row서울특별시 강남구 역삼동 813-2번지
4th row서울특별시 강남구 논현동 57-1번지
5th row서울특별시 강남구 신사동 540-11번지
ValueCountFrequency (%)
강남구 9997
22.2%
서울특별시 9996
22.2%
역삼동 2214
 
4.9%
신사동 1675
 
3.7%
논현동 1639
 
3.6%
대치동 1255
 
2.8%
지상1층 1242
 
2.8%
삼성동 977
 
2.2%
지하1층 726
 
1.6%
개포동 706
 
1.6%
Other values (6901) 14516
32.3%
2024-05-11T08:53:42.388357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44473
 
17.7%
12721
 
5.1%
1 12588
 
5.0%
10229
 
4.1%
10156
 
4.0%
10099
 
4.0%
10046
 
4.0%
10024
 
4.0%
10022
 
4.0%
10013
 
4.0%
Other values (387) 111247
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146125
58.1%
Decimal Number 50095
 
19.9%
Space Separator 44473
 
17.7%
Dash Punctuation 9815
 
3.9%
Other Punctuation 459
 
0.2%
Uppercase Letter 228
 
0.1%
Open Punctuation 189
 
0.1%
Close Punctuation 188
 
0.1%
Lowercase Letter 24
 
< 0.1%
Math Symbol 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12721
 
8.7%
10229
 
7.0%
10156
 
7.0%
10099
 
6.9%
10046
 
6.9%
10024
 
6.9%
10022
 
6.9%
10013
 
6.9%
10002
 
6.8%
9997
 
6.8%
Other values (334) 42816
29.3%
Uppercase Letter
ValueCountFrequency (%)
B 69
30.3%
A 41
18.0%
F 38
16.7%
L 21
 
9.2%
C 8
 
3.5%
S 7
 
3.1%
O 7
 
3.1%
T 6
 
2.6%
W 6
 
2.6%
K 5
 
2.2%
Other values (9) 20
 
8.8%
Lowercase Letter
ValueCountFrequency (%)
a 5
20.8%
h 3
12.5%
e 2
 
8.3%
b 2
 
8.3%
c 2
 
8.3%
n 2
 
8.3%
o 2
 
8.3%
i 1
 
4.2%
r 1
 
4.2%
w 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
1 12588
25.1%
2 5985
11.9%
6 5027
 
10.0%
0 4493
 
9.0%
5 3899
 
7.8%
3 3866
 
7.7%
7 3630
 
7.2%
4 3582
 
7.2%
9 3529
 
7.0%
8 3496
 
7.0%
Other Punctuation
ValueCountFrequency (%)
, 388
84.5%
. 63
 
13.7%
? 3
 
0.7%
/ 3
 
0.7%
& 1
 
0.2%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
44473
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9815
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146125
58.1%
Common 105241
41.8%
Latin 252
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12721
 
8.7%
10229
 
7.0%
10156
 
7.0%
10099
 
6.9%
10046
 
6.9%
10024
 
6.9%
10022
 
6.9%
10013
 
6.9%
10002
 
6.8%
9997
 
6.8%
Other values (334) 42816
29.3%
Latin
ValueCountFrequency (%)
B 69
27.4%
A 41
16.3%
F 38
15.1%
L 21
 
8.3%
C 8
 
3.2%
S 7
 
2.8%
O 7
 
2.8%
T 6
 
2.4%
W 6
 
2.4%
K 5
 
2.0%
Other values (22) 44
17.5%
Common
ValueCountFrequency (%)
44473
42.3%
1 12588
 
12.0%
- 9815
 
9.3%
2 5985
 
5.7%
6 5027
 
4.8%
0 4493
 
4.3%
5 3899
 
3.7%
3 3866
 
3.7%
7 3630
 
3.4%
4 3582
 
3.4%
Other values (11) 7883
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146124
58.1%
ASCII 105493
41.9%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44473
42.2%
1 12588
 
11.9%
- 9815
 
9.3%
2 5985
 
5.7%
6 5027
 
4.8%
0 4493
 
4.3%
5 3899
 
3.7%
3 3866
 
3.7%
7 3630
 
3.4%
4 3582
 
3.4%
Other values (43) 8135
 
7.7%
Hangul
ValueCountFrequency (%)
12721
 
8.7%
10229
 
7.0%
10156
 
7.0%
10099
 
6.9%
10046
 
6.9%
10024
 
6.9%
10022
 
6.9%
10013
 
6.9%
10002
 
6.8%
9997
 
6.8%
Other values (333) 42815
29.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2372
Distinct (%)95.8%
Missing7523
Missing (%)75.2%
Memory size156.2 KiB
2024-05-11T08:53:43.644160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length57
Mean length30.408155
Min length22

Characters and Unicode

Total characters75321
Distinct characters316
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

Unique2290 ?
Unique (%)92.5%

Sample

1st row서울특별시 강남구 압구정로72길 22 (청담동,지하1층지상1층)
2nd row서울특별시 강남구 봉은사로 108 (역삼동)
3rd row서울특별시 강남구 역삼로78길 3 (대치동,1층)
4th row서울특별시 강남구 언주로 728 (논현동)
5th row서울특별시 강남구 강남대로 280 (도곡동)
ValueCountFrequency (%)
서울특별시 2477
 
18.9%
강남구 2477
 
18.9%
역삼동 292
 
2.2%
신사동 173
 
1.3%
논현동 163
 
1.2%
대치동 141
 
1.1%
지상1층 140
 
1.1%
삼성동 132
 
1.0%
지하1층 112
 
0.9%
역삼동,지상1층 94
 
0.7%
Other values (1844) 6916
52.7%
2024-05-11T08:53:44.853834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10642
 
14.1%
1 3914
 
5.2%
2803
 
3.7%
2741
 
3.6%
2726
 
3.6%
2614
 
3.5%
2533
 
3.4%
) 2520
 
3.3%
( 2519
 
3.3%
2496
 
3.3%
Other values (306) 39813
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44683
59.3%
Decimal Number 12603
 
16.7%
Space Separator 10642
 
14.1%
Close Punctuation 2520
 
3.3%
Open Punctuation 2519
 
3.3%
Other Punctuation 2022
 
2.7%
Dash Punctuation 205
 
0.3%
Uppercase Letter 101
 
0.1%
Lowercase Letter 17
 
< 0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2803
 
6.3%
2741
 
6.1%
2726
 
6.1%
2614
 
5.9%
2533
 
5.7%
2496
 
5.6%
2484
 
5.6%
2484
 
5.6%
2482
 
5.6%
2478
 
5.5%
Other values (259) 18842
42.2%
Uppercase Letter
ValueCountFrequency (%)
B 36
35.6%
L 12
 
11.9%
A 12
 
11.9%
F 12
 
11.9%
C 6
 
5.9%
O 4
 
4.0%
S 3
 
3.0%
K 3
 
3.0%
G 3
 
3.0%
R 2
 
2.0%
Other values (6) 8
 
7.9%
Lowercase Letter
ValueCountFrequency (%)
a 3
17.6%
o 2
11.8%
n 2
11.8%
h 2
11.8%
i 1
 
5.9%
k 1
 
5.9%
c 1
 
5.9%
b 1
 
5.9%
m 1
 
5.9%
w 1
 
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
1 3914
31.1%
2 1834
14.6%
3 1126
 
8.9%
4 983
 
7.8%
5 939
 
7.5%
0 923
 
7.3%
6 802
 
6.4%
8 797
 
6.3%
7 697
 
5.5%
9 588
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 1995
98.7%
. 25
 
1.2%
/ 1
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
10642
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2520
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2519
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44683
59.3%
Common 30520
40.5%
Latin 118
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2803
 
6.3%
2741
 
6.1%
2726
 
6.1%
2614
 
5.9%
2533
 
5.7%
2496
 
5.6%
2484
 
5.6%
2484
 
5.6%
2482
 
5.6%
2478
 
5.5%
Other values (259) 18842
42.2%
Latin
ValueCountFrequency (%)
B 36
30.5%
L 12
 
10.2%
A 12
 
10.2%
F 12
 
10.2%
C 6
 
5.1%
O 4
 
3.4%
a 3
 
2.5%
S 3
 
2.5%
K 3
 
2.5%
G 3
 
2.5%
Other values (18) 24
20.3%
Common
ValueCountFrequency (%)
10642
34.9%
1 3914
 
12.8%
) 2520
 
8.3%
( 2519
 
8.3%
, 1995
 
6.5%
2 1834
 
6.0%
3 1126
 
3.7%
4 983
 
3.2%
5 939
 
3.1%
0 923
 
3.0%
Other values (9) 3125
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44683
59.3%
ASCII 30638
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10642
34.7%
1 3914
 
12.8%
) 2520
 
8.2%
( 2519
 
8.2%
, 1995
 
6.5%
2 1834
 
6.0%
3 1126
 
3.7%
4 983
 
3.2%
5 939
 
3.1%
0 923
 
3.0%
Other values (37) 3243
 
10.6%
Hangul
ValueCountFrequency (%)
2803
 
6.3%
2741
 
6.1%
2726
 
6.1%
2614
 
5.9%
2533
 
5.7%
2496
 
5.6%
2484
 
5.6%
2484
 
5.6%
2482
 
5.6%
2478
 
5.5%
Other values (259) 18842
42.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct309
Distinct (%)12.7%
Missing7565
Missing (%)75.6%
Infinite0
Infinite (%)0.0%
Mean6153.4181
Minimum6000
Maximum6378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:53:45.264869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile6018
Q16062
median6143
Q36228.5
95-th percentile6329
Maximum6378
Range378
Interquartile range (IQR)166.5

Descriptive statistics

Standard deviation98.08444
Coefficient of variation (CV)0.01593983
Kurtosis-0.90349217
Mean6153.4181
Median Absolute Deviation (MAD)83
Skewness0.29453236
Sum14983573
Variance9620.5573
MonotonicityNot monotonic
2024-05-11T08:53:45.700058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6035 54
 
0.5%
6129 52
 
0.5%
6018 48
 
0.5%
6164 38
 
0.4%
6296 32
 
0.3%
6114 31
 
0.3%
6131 30
 
0.3%
6197 28
 
0.3%
6120 28
 
0.3%
6140 27
 
0.3%
Other values (299) 2067
 
20.7%
(Missing) 7565
75.6%
ValueCountFrequency (%)
6000 1
 
< 0.1%
6001 4
 
< 0.1%
6002 2
 
< 0.1%
6004 1
 
< 0.1%
6005 1
 
< 0.1%
6008 1
 
< 0.1%
6010 5
0.1%
6011 6
0.1%
6012 5
0.1%
6013 10
0.1%
ValueCountFrequency (%)
6378 3
 
< 0.1%
6368 1
 
< 0.1%
6367 11
0.1%
6365 8
0.1%
6364 1
 
< 0.1%
6363 1
 
< 0.1%
6362 2
 
< 0.1%
6356 1
 
< 0.1%
6355 1
 
< 0.1%
6354 2
 
< 0.1%
Distinct8225
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T08:53:46.443100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length4.2666
Min length1

Characters and Unicode

Total characters42666
Distinct characters1034
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7221 ?
Unique (%)72.2%

Sample

1st row맛나감자탕
2nd row츠키지
3rd row센스
4th row오복
5th row서울레스토랑
ValueCountFrequency (%)
명동칼국수 23
 
0.2%
전주식당 22
 
0.2%
역삼점 15
 
0.1%
선릉점 12
 
0.1%
12
 
0.1%
압구정점 12
 
0.1%
영동식당 11
 
0.1%
강남식당 11
 
0.1%
영동분식 10
 
0.1%
페리카나치킨 10
 
0.1%
Other values (8456) 10414
98.7%
2024-05-11T08:53:47.415313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
986
 
2.3%
945
 
2.2%
944
 
2.2%
736
 
1.7%
654
 
1.5%
556
 
1.3%
542
 
1.3%
465
 
1.1%
464
 
1.1%
462
 
1.1%
Other values (1024) 35912
84.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41097
96.3%
Space Separator 556
 
1.3%
Decimal Number 251
 
0.6%
Close Punctuation 219
 
0.5%
Open Punctuation 217
 
0.5%
Lowercase Letter 161
 
0.4%
Uppercase Letter 115
 
0.3%
Other Punctuation 46
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
986
 
2.4%
945
 
2.3%
944
 
2.3%
736
 
1.8%
654
 
1.6%
542
 
1.3%
465
 
1.1%
464
 
1.1%
462
 
1.1%
462
 
1.1%
Other values (955) 34437
83.8%
Lowercase Letter
ValueCountFrequency (%)
e 24
14.9%
a 17
 
10.6%
o 11
 
6.8%
l 11
 
6.8%
t 11
 
6.8%
i 10
 
6.2%
s 9
 
5.6%
m 8
 
5.0%
c 8
 
5.0%
f 7
 
4.3%
Other values (14) 45
28.0%
Uppercase Letter
ValueCountFrequency (%)
O 12
 
10.4%
A 10
 
8.7%
C 9
 
7.8%
F 9
 
7.8%
E 8
 
7.0%
N 8
 
7.0%
L 7
 
6.1%
M 6
 
5.2%
J 5
 
4.3%
I 5
 
4.3%
Other values (14) 36
31.3%
Decimal Number
ValueCountFrequency (%)
2 68
27.1%
1 44
17.5%
0 33
13.1%
4 24
 
9.6%
3 19
 
7.6%
9 16
 
6.4%
5 15
 
6.0%
7 12
 
4.8%
8 10
 
4.0%
6 10
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 21
45.7%
& 7
 
15.2%
? 6
 
13.0%
, 6
 
13.0%
3
 
6.5%
' 2
 
4.3%
% 1
 
2.2%
Space Separator
ValueCountFrequency (%)
556
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 217
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41096
96.3%
Common 1293
 
3.0%
Latin 276
 
0.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
986
 
2.4%
945
 
2.3%
944
 
2.3%
736
 
1.8%
654
 
1.6%
542
 
1.3%
465
 
1.1%
464
 
1.1%
462
 
1.1%
462
 
1.1%
Other values (954) 34436
83.8%
Latin
ValueCountFrequency (%)
e 24
 
8.7%
a 17
 
6.2%
O 12
 
4.3%
o 11
 
4.0%
l 11
 
4.0%
t 11
 
4.0%
A 10
 
3.6%
i 10
 
3.6%
s 9
 
3.3%
C 9
 
3.3%
Other values (38) 152
55.1%
Common
ValueCountFrequency (%)
556
43.0%
) 219
 
16.9%
( 217
 
16.8%
2 68
 
5.3%
1 44
 
3.4%
0 33
 
2.6%
4 24
 
1.9%
. 21
 
1.6%
3 19
 
1.5%
9 16
 
1.2%
Other values (11) 76
 
5.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41096
96.3%
ASCII 1566
 
3.7%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
986
 
2.4%
945
 
2.3%
944
 
2.3%
736
 
1.8%
654
 
1.6%
542
 
1.3%
465
 
1.1%
464
 
1.1%
462
 
1.1%
462
 
1.1%
Other values (954) 34436
83.8%
ASCII
ValueCountFrequency (%)
556
35.5%
) 219
 
14.0%
( 217
 
13.9%
2 68
 
4.3%
1 44
 
2.8%
0 33
 
2.1%
e 24
 
1.5%
4 24
 
1.5%
. 21
 
1.3%
3 19
 
1.2%
Other values (58) 341
21.8%
None
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct4337
Distinct (%)43.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-21 00:00:00
Maximum2024-05-07 16:27:31
2024-05-11T08:53:47.781198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:48.247536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
8986 
U
1014 

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 8986
89.9%
U 1014
 
10.1%

Length

2024-05-11T08:53:48.683590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:48.987787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 8986
89.9%
u 1014
 
10.1%
Distinct681
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T08:53:49.469472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:53:49.970304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4193 
경양식
2949 
분식
1605 
일식
495 
중국식
 
305
Other values (13)
453 

Length

Max length15
Median length2
Mean length2.5138
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row경양식
3rd row경양식
4th row한식
5th row경양식

Common Values

ValueCountFrequency (%)
한식 4193
41.9%
경양식 2949
29.5%
분식 1605
 
16.1%
일식 495
 
5.0%
중국식 305
 
3.0%
정종/대포집/소주방 99
 
1.0%
통닭(치킨) 91
 
0.9%
패스트푸드 90
 
0.9%
호프/통닭 67
 
0.7%
전통찻집 41
 
0.4%
Other values (8) 65
 
0.7%

Length

2024-05-11T08:53:50.409551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4193
41.9%
경양식 2949
29.5%
분식 1605
 
16.1%
일식 495
 
5.0%
중국식 305
 
3.0%
정종/대포집/소주방 99
 
1.0%
통닭(치킨 91
 
0.9%
패스트푸드 90
 
0.9%
호프/통닭 67
 
0.7%
전통찻집 41
 
0.4%
Other values (8) 65
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4960
Distinct (%)52.0%
Missing461
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean203757.22
Minimum201509.71
Maximum210442.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:53:50.868926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201509.71
5-th percentile201972.44
Q1202770.41
median203467.51
Q3204598.73
95-th percentile205949.39
Maximum210442.41
Range8932.7008
Interquartile range (IQR)1828.3207

Descriptive statistics

Standard deviation1374.2767
Coefficient of variation (CV)0.0067446774
Kurtosis1.8577156
Mean203757.22
Median Absolute Deviation (MAD)863.83031
Skewness1.1195654
Sum1.9436401 × 109
Variance1888636.4
MonotonicityNot monotonic
2024-05-11T08:53:51.330247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205130.591678902 50
 
0.5%
205340.631121567 45
 
0.4%
205707.089399978 28
 
0.3%
208937.760652081 26
 
0.3%
204669.543366778 25
 
0.2%
203121.203642767 23
 
0.2%
205259.527550336 23
 
0.2%
206970.919291372 23
 
0.2%
205170.959716696 22
 
0.2%
203470.848439305 19
 
0.2%
Other values (4950) 9255
92.5%
(Missing) 461
 
4.6%
ValueCountFrequency (%)
201509.712645065 2
 
< 0.1%
201598.092444518 1
 
< 0.1%
201608.620537385 2
 
< 0.1%
201620.446225572 1
 
< 0.1%
201634.68108722 1
 
< 0.1%
201636.407849513 2
 
< 0.1%
201640.067533451 3
< 0.1%
201641.741382771 3
< 0.1%
201646.385389914 2
 
< 0.1%
201650.787158848 6
0.1%
ValueCountFrequency (%)
210442.413455881 2
 
< 0.1%
210399.618416566 1
 
< 0.1%
209590.56842333 1
 
< 0.1%
209536.939306073 1
 
< 0.1%
209428.428164038 4
< 0.1%
209423.649311203 7
0.1%
209309.263 1
 
< 0.1%
209246.406810922 1
 
< 0.1%
209229.482887777 3
< 0.1%
209144.783150288 5
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4960
Distinct (%)52.0%
Missing461
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean445027.58
Minimum440096.04
Maximum447864.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:53:51.772963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440096.04
5-th percentile442521.09
Q1444018.58
median445003.22
Q3446295.26
95-th percentile447181.31
Maximum447864.76
Range7768.7201
Interquartile range (IQR)2276.6755

Descriptive statistics

Standard deviation1479.2143
Coefficient of variation (CV)0.0033238711
Kurtosis-0.54936495
Mean445027.58
Median Absolute Deviation (MAD)1129.5945
Skewness-0.31412017
Sum4.2451181 × 109
Variance2188075
MonotonicityNot monotonic
2024-05-11T08:53:52.301217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445590.096837802 50
 
0.5%
445354.571117445 45
 
0.4%
443914.194133105 28
 
0.3%
442873.588039887 26
 
0.3%
443873.621189048 25
 
0.2%
446464.379990564 23
 
0.2%
445361.937086207 23
 
0.2%
443574.411625824 23
 
0.2%
445264.936337181 22
 
0.2%
447369.579851952 19
 
0.2%
Other values (4950) 9255
92.5%
(Missing) 461
 
4.6%
ValueCountFrequency (%)
440096.043666667 1
 
< 0.1%
440137.950597011 4
< 0.1%
440208.558412381 7
0.1%
440377.184328629 1
 
< 0.1%
440538.332371671 1
 
< 0.1%
440792.907332437 2
 
< 0.1%
441096.843331453 1
 
< 0.1%
441119.156988213 1
 
< 0.1%
441156.65317701 2
 
< 0.1%
441161.475 1
 
< 0.1%
ValueCountFrequency (%)
447864.763737276 5
0.1%
447782.51322707 2
 
< 0.1%
447748.161018109 1
 
< 0.1%
447701.012985942 3
< 0.1%
447663.86257666 1
 
< 0.1%
447649.978394541 2
 
< 0.1%
447521.520319158 1
 
< 0.1%
447400.303560123 7
0.1%
447396.0865784 2
 
< 0.1%
447393.51192286 3
< 0.1%

위생업태명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3972 
경양식
2862 
분식
1565 
일식
471 
<NA>
422 
Other values (14)
708 

Length

Max length15
Median length2
Mean length2.5775
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row경양식
3rd row경양식
4th row한식
5th row경양식

Common Values

ValueCountFrequency (%)
한식 3972
39.7%
경양식 2862
28.6%
분식 1565
 
15.7%
일식 471
 
4.7%
<NA> 422
 
4.2%
중국식 279
 
2.8%
정종/대포집/소주방 97
 
1.0%
패스트푸드 88
 
0.9%
통닭(치킨) 83
 
0.8%
호프/통닭 60
 
0.6%
Other values (9) 101
 
1.0%

Length

2024-05-11T08:53:52.838347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3972
39.7%
경양식 2862
28.6%
분식 1565
 
15.7%
일식 471
 
4.7%
na 422
 
4.2%
중국식 279
 
2.8%
정종/대포집/소주방 97
 
1.0%
패스트푸드 88
 
0.9%
통닭(치킨 83
 
0.8%
호프/통닭 60
 
0.6%
Other values (9) 101
 
1.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.2%
Missing798
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean0.45174962
Minimum0
Maximum35
Zeros7541
Zeros (%)75.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:53:53.313978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4436139
Coefficient of variation (CV)3.1956061
Kurtosis97.701724
Mean0.45174962
Median Absolute Deviation (MAD)0
Skewness7.3697117
Sum4157
Variance2.084021
MonotonicityNot monotonic
2024-05-11T08:53:53.794837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 7541
75.4%
1 746
 
7.5%
2 376
 
3.8%
3 202
 
2.0%
4 132
 
1.3%
5 84
 
0.8%
7 29
 
0.3%
8 28
 
0.3%
6 27
 
0.3%
10 16
 
0.2%
Other values (11) 21
 
0.2%
(Missing) 798
 
8.0%
ValueCountFrequency (%)
0 7541
75.4%
1 746
 
7.5%
2 376
 
3.8%
3 202
 
2.0%
4 132
 
1.3%
5 84
 
0.8%
6 27
 
0.3%
7 29
 
0.3%
8 28
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
35 1
 
< 0.1%
30 1
 
< 0.1%
23 1
 
< 0.1%
20 5
0.1%
19 1
 
< 0.1%
18 1
 
< 0.1%
16 1
 
< 0.1%
15 3
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)0.3%
Missing798
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean0.54031732
Minimum0
Maximum60
Zeros7240
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:53:54.216744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7634093
Coefficient of variation (CV)3.2636549
Kurtosis221.37602
Mean0.54031732
Median Absolute Deviation (MAD)0
Skewness10.665576
Sum4972
Variance3.1096122
MonotonicityNot monotonic
2024-05-11T08:53:54.622833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 7240
72.4%
1 784
 
7.8%
2 640
 
6.4%
3 232
 
2.3%
4 107
 
1.1%
5 59
 
0.6%
6 36
 
0.4%
8 21
 
0.2%
7 19
 
0.2%
10 19
 
0.2%
Other values (17) 45
 
0.4%
(Missing) 798
 
8.0%
ValueCountFrequency (%)
0 7240
72.4%
1 784
 
7.8%
2 640
 
6.4%
3 232
 
2.3%
4 107
 
1.1%
5 59
 
0.6%
6 36
 
0.4%
7 19
 
0.2%
8 21
 
0.2%
9 6
 
0.1%
ValueCountFrequency (%)
60 1
 
< 0.1%
42 1
 
< 0.1%
30 1
 
< 0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
21 1
 
< 0.1%
20 8
0.1%
19 1
 
< 0.1%
18 3
 
< 0.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기타
6573 
주택가주변
1743 
유흥업소밀집지역
658 
<NA>
 
558
아파트지역
 
410
Other values (3)
 
58

Length

Max length8
Median length2
Mean length3.1843
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row기타
3rd row유흥업소밀집지역
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
기타 6573
65.7%
주택가주변 1743
 
17.4%
유흥업소밀집지역 658
 
6.6%
<NA> 558
 
5.6%
아파트지역 410
 
4.1%
결혼예식장주변 28
 
0.3%
학교정화(상대) 22
 
0.2%
학교정화(절대) 8
 
0.1%

Length

2024-05-11T08:53:55.148775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:55.616749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 6573
65.7%
주택가주변 1743
 
17.4%
유흥업소밀집지역 658
 
6.6%
na 558
 
5.6%
아파트지역 410
 
4.1%
결혼예식장주변 28
 
0.3%
학교정화(상대 22
 
0.2%
학교정화(절대 8
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
자율
4684 
기타
2653 
지도
1092 
<NA>
634 
548 
Other values (3)
 
389

Length

Max length4
Median length2
Mean length2.0391
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row자율
3rd row자율
4th row기타
5th row자율

Common Values

ValueCountFrequency (%)
자율 4684
46.8%
기타 2653
26.5%
지도 1092
 
10.9%
<NA> 634
 
6.3%
548
 
5.5%
329
 
3.3%
관리 30
 
0.3%
우수 30
 
0.3%

Length

2024-05-11T08:53:56.145086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:56.817405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자율 4684
46.8%
기타 2653
26.5%
지도 1092
 
10.9%
na 634
 
6.3%
548
 
5.5%
329
 
3.3%
관리 30
 
0.3%
우수 30
 
0.3%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
9438 
<NA>
 
550
상수도(음용)지하수(주방용)겸용
 
11
지하수전용
 
1

Length

Max length17
Median length5
Mean length4.9582
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 9438
94.4%
<NA> 550
 
5.5%
상수도(음용)지하수(주방용)겸용 11
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T08:53:57.414548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:57.725512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 9438
94.4%
na 550
 
5.5%
상수도(음용)지하수(주방용)겸용 11
 
0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9914 
0
 
86

Length

Max length4
Median length4
Mean length3.9742
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> 9914
99.1%
0 86
 
0.9%

Length

2024-05-11T08:53:58.075538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:58.448785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9914
99.1%
0 86
 
0.9%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:53:58.811486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:53:59.226785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:53:59.892920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:54:00.404672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:54:00.928112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:54:01.418426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:54:01.891716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:54:02.503192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

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>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:54:03.068982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:54:03.616781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9908 
0
 
92

Length

Max length4
Median length4
Mean length3.9724
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> 9908
99.1%
0 92
 
0.9%

Length

2024-05-11T08:54:04.089748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:54:04.414002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9908
99.1%
0 92
 
0.9%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing422
Missing (%)4.2%
Memory size97.7 KiB
False
9530 
True
 
48
(Missing)
 
422
ValueCountFrequency (%)
False 9530
95.3%
True 48
 
0.5%
(Missing) 422
 
4.2%
2024-05-11T08:54:04.676088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct5952
Distinct (%)62.1%
Missing422
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean108.75474
Minimum0
Maximum4823.2
Zeros19
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T08:54:05.121997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.56
Q135.4
median74
Q3132.2
95-th percentile301.006
Maximum4823.2
Range4823.2
Interquartile range (IQR)96.8

Descriptive statistics

Standard deviation142.93387
Coefficient of variation (CV)1.3142771
Kurtosis195.58739
Mean108.75474
Median Absolute Deviation (MAD)43.2
Skewness9.4057242
Sum1041652.9
Variance20430.092
MonotonicityNot monotonic
2024-05-11T08:54:05.836185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.44 82
 
0.8%
29.75 69
 
0.7%
23.14 48
 
0.5%
49.58 48
 
0.5%
82.64 47
 
0.5%
66.11 40
 
0.4%
59.5 40
 
0.4%
132.23 33
 
0.3%
19.83 29
 
0.3%
42.97 28
 
0.3%
Other values (5942) 9114
91.1%
(Missing) 422
 
4.2%
ValueCountFrequency (%)
0.0 19
0.2%
2.28 1
 
< 0.1%
2.42 1
 
< 0.1%
2.66 1
 
< 0.1%
2.68 1
 
< 0.1%
2.88 1
 
< 0.1%
3.45 1
 
< 0.1%
3.75 1
 
< 0.1%
3.96 1
 
< 0.1%
4.2 1
 
< 0.1%
ValueCountFrequency (%)
4823.2 1
< 0.1%
3461.56 1
< 0.1%
2726.0 1
< 0.1%
2223.55 1
< 0.1%
1995.51 1
< 0.1%
1816.0 1
< 0.1%
1798.84 1
< 0.1%
1778.2 1
< 0.1%
1769.21 1
< 0.1%
1683.0 1
< 0.1%
Distinct4
Distinct (%)80.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T08:54:06.186851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.2
Min length1

Characters and Unicode

Total characters11
Distinct characters7
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

Unique3 ?
Unique (%)60.0%

Sample

1st row..
2nd row24834
3rd row0
4th row99
5th row0
ValueCountFrequency (%)
0 2
40.0%
1
20.0%
24834 1
20.0%
99 1
20.0%
2024-05-11T08:54:07.021937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
18.2%
. 2
18.2%
4 2
18.2%
9 2
18.2%
2 1
9.1%
8 1
9.1%
3 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
81.8%
Other Punctuation 2
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
22.2%
4 2
22.2%
9 2
22.2%
2 1
11.1%
8 1
11.1%
3 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
18.2%
. 2
18.2%
4 2
18.2%
9 2
18.2%
2 1
9.1%
8 1
9.1%
3 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
18.2%
. 2
18.2%
4 2
18.2%
9 2
18.2%
2 1
9.1%
8 1
9.1%
3 1
9.1%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T08:54:07.409698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row00000000000000
ValueCountFrequency (%)
00000000000000 1
100.0%
2024-05-11T08:54:08.348691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
100.0%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1771532200003220000-101-2000-2256220001010<NA>3폐업2폐업20051031<NA><NA><NA>02 459319525.00135516서울특별시 강남구 일원동 678-7번지 지상1층<NA><NA>맛나감자탕2002-02-27 00:00:00I2018-08-31 23:59:59.0한식207247.808893443212.072643한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.0<NA><NA><NA>
2493132200003220000-101-2006-0061720060908<NA>3폐업2폐업20100603<NA><NA><NA><NA>57.00135816서울특별시 강남구 논현동 67-4번지 지상1층<NA><NA>츠키지2008-03-13 17:11:53I2018-08-31 23:59:59.0경양식202650.484186446302.356583경양식00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N57.0<NA><NA><NA>
113332200003220000-101-1984-1204119841214<NA>3폐업2폐업19991231<NA><NA><NA>0297.50135931서울특별시 강남구 역삼동 813-2번지<NA><NA>센스2000-01-13 00:00:00I2018-08-31 23:59:59.0경양식202288.15981444521.37814경양식13유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.5<NA><NA><NA>
958332200003220000-101-1994-1478919941209<NA>3폐업2폐업20050201<NA><NA><NA>0205437494102.36135815서울특별시 강남구 논현동 57-1번지<NA><NA>오복2001-12-21 00:00:00I2018-08-31 23:59:59.0한식202286.153055445689.003837한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N102.36<NA><NA><NA>
639832200003220000-101-1992-0889119920413<NA>3폐업2폐업19931218<NA><NA><NA>0205496460207.63135889서울특별시 강남구 신사동 540-11번지<NA><NA>서울레스토랑2001-08-02 00:00:00I2018-08-31 23:59:59.0경양식202056.468409446318.036537경양식00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N207.63<NA><NA><NA>
2021932200003220000-101-2002-0090320021014<NA>3폐업2폐업20030818<NA><NA><NA>5385381197.80135934서울특별시 강남구 역삼동 824-12번지 메가씨티 지상1층<NA><NA>코알라2002-12-03 00:00:00I2018-08-31 23:59:59.0경양식202603.676064443910.083023경양식00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N197.8<NA><NA><NA>
88032200003220000-101-1984-0594419840118<NA>3폐업2폐업19980211<NA><NA><NA>02 462944219.62135834서울특별시 강남구 대치동 16-0번지 주공고층 16호<NA><NA>2001-08-02 00:00:00I2018-08-31 23:59:59.0분식<NA><NA>분식01주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N19.62<NA><NA><NA>
770832200003220000-101-1993-0712019931102<NA>3폐업2폐업19970910<NA><NA><NA>020000000016.15135913서울특별시 강남구 역삼동 656-34번지<NA><NA>성보분식2001-08-02 00:00:00I2018-08-31 23:59:59.0분식203401.76742444950.497585분식00주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.15<NA><NA><NA>
1659932200003220000-101-1999-2103919991229<NA>3폐업2폐업20140708<NA><NA><NA>02 5422222395.04135517서울특별시 강남구 청담동 95-15번지 지하1층지상1층서울특별시 강남구 압구정로72길 22 (청담동,지하1층지상1층)6015하루에2012-03-28 13:08:21I2018-08-31 23:59:59.0중국식203905.751504446976.719216중국식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N395.04<NA><NA><NA>
1532332200003220000-101-1999-1874719990316<NA>3폐업2폐업20160829<NA><NA><NA>02222.19135907서울특별시 강남구 역삼동 601-0번지서울특별시 강남구 봉은사로 108 (역삼동)6123송탄쑥고개부대찌개2016-08-29 15:46:03I2018-08-31 23:59:59.0한식202191.232126444703.407194한식00유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N222.19<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
936632200003220000-101-1994-1210019940525<NA>3폐업2폐업20030904<NA><NA><NA>020461228449.31135962서울특별시 강남구 개포동 1194-3번지<NA><NA>브란치패스토랑2001-08-02 00:00:00I2018-08-31 23:59:59.0경양식204186.178345441393.155052경양식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.31<NA><NA><NA>
1279932200003220000-101-1997-0858019970516<NA>3폐업2폐업19980916<NA><NA><NA>02 5123437190.71135887서울특별시 강남구 신사동 502-7번지<NA><NA>아이반2001-08-02 00:00:00I2018-08-31 23:59:59.0경양식201664.929815446119.202666경양식<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N190.71<NA><NA><NA>
1668032200003220000-101-2000-2113020000113<NA>3폐업2폐업20080215<NA><NA><NA>02 6961501131.50135897서울특별시 강남구 신사동 655-1번지 지상1,2층<NA><NA>탱자탱자2005-07-20 00:00:00I2018-08-31 23:59:59.0한식203300.993984447003.699354한식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N131.5<NA><NA><NA>
1533232200003220000-101-1999-1876019990318<NA>3폐업2폐업20000725<NA><NA><NA>02 5013139128.90135881서울특별시 강남구 삼성동 160-20번지<NA><NA>토종버섯마을2000-07-25 00:00:00I2018-08-31 23:59:59.0한식205404.52675445753.751656한식00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N128.9<NA><NA><NA>
333732200003220000-101-1988-0720619881210<NA>3폐업2폐업19970910<NA><NA><NA>020557182555.14135849서울특별시 강남구 대치동 988-0번지<NA><NA>산호세2001-08-02 00:00:00I2018-08-31 23:59:59.0뷔페식205293.268999444204.455251뷔페식10유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.14<NA><NA><NA>
528532200003220000-101-1991-0600719910101<NA>3폐업2폐업19970814<NA><NA><NA>02 0000033.25135870서울특별시 강남구 삼성동 58-3번지<NA><NA>소나무분식2001-08-02 00:00:00I2018-08-31 23:59:59.0분식204942.583021446373.260291분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.25<NA><NA><NA>
2557132200003220000-101-2007-0032620070504<NA>3폐업2폐업20171108<NA><NA><NA>0264095798181.72135919서울특별시 강남구 역삼동 708-20번지 금천빌딩 102~106호서울특별시 강남구 테헤란로52길 15 (역삼동,금천빌딩 102~106호)6212미하루2017-12-05 15:53:52I2018-08-31 23:59:59.0경양식204170.084609444548.397487경양식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N181.72<NA><NA><NA>
1537932200003220000-101-1999-188341999-03-29<NA>1영업/정상1영업<NA><NA><NA><NA>0234434033117.15135-996서울특별시 강남구 논현동 210-3 지상1층서울특별시 강남구 언주로129길 6 (논현동,지상1층)6104해장왕 양평해장국 강남학동역본점2024-04-26 16:36:24U2023-12-03 22:08:00.0한식203004.766682445822.606854<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1267932200003220000-101-1997-0840119970910<NA>3폐업2폐업19981012<NA><NA><NA>02 226895151.10135945서울특별시 강남구 일원동 666-1번지<NA><NA>지바고2001-08-02 00:00:00I2018-08-31 23:59:59.0경양식207317.408048443069.274274경양식<NA><NA>기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.1<NA><NA><NA>
1329532200003220000-101-1997-1959419971117<NA>3폐업2폐업19990629<NA><NA><NA>02 557266028.49135969서울특별시 강남구 대치동 316-0번지 은마상가 A-5동 호호<NA><NA>시골밥상1999-06-29 00:00:00I2018-08-31 23:59:59.0한식205707.0894443914.194133한식00아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.49<NA><NA><NA>