Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells109033
Missing cells (%)24.8%
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18661/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소주된음식 has constant value ""Constant
영업장주변구분명 is highly imbalanced (50.6%)Imbalance
총인원 is highly imbalanced (80.1%)Imbalance
본사종업원수 is highly imbalanced (80.0%)Imbalance
공장사무직종업원수 is highly imbalanced (80.0%)Imbalance
공장판매직종업원수 is highly imbalanced (80.0%)Imbalance
공장생산직종업원수 is highly imbalanced (80.0%)Imbalance
보증액 is highly imbalanced (80.0%)Imbalance
월세액 is highly imbalanced (80.0%)Imbalance
다중이용업소여부 is highly imbalanced (89.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2015 (20.2%) 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 2833 (28.3%) missing valuesMissing
소재지면적 has 560 (5.6%) missing valuesMissing
도로명주소 has 5521 (55.2%) missing valuesMissing
도로명우편번호 has 5581 (55.8%) missing valuesMissing
좌표정보(X) has 376 (3.8%) missing valuesMissing
좌표정보(Y) has 376 (3.8%) missing valuesMissing
남성종사자수 has 4638 (46.4%) missing valuesMissing
여성종사자수 has 4556 (45.6%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1290 (12.9%) missing valuesMissing
시설총규모 has 1290 (12.9%) missing valuesMissing
전통업소지정번호 has 9998 (> 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 4506 (45.1%) zerosZeros
여성종사자수 has 3905 (39.1%) zerosZeros
시설총규모 has 581 (5.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:30:15.851528
Analysis finished2024-05-11 05:30:21.583549
Duration5.73 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
3090000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 10000
100.0%

Length

2024-05-11T05:30:21.894960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:22.285497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T05:30:22.807532image/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 row3090000-101-1995-02631
2nd row3090000-101-1992-01169
3rd row3090000-101-2005-00218
4th row3090000-101-1999-04494
5th row3090000-101-2006-00040
ValueCountFrequency (%)
3090000-101-1995-02631 1
 
< 0.1%
3090000-101-1997-00261 1
 
< 0.1%
3090000-101-1999-01220 1
 
< 0.1%
3090000-101-1999-04449 1
 
< 0.1%
3090000-101-1996-02271 1
 
< 0.1%
3090000-101-2011-00147 1
 
< 0.1%
3090000-101-1990-02363 1
 
< 0.1%
3090000-101-1988-04169 1
 
< 0.1%
3090000-101-2014-00037 1
 
< 0.1%
3090000-101-2018-00046 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T05:30:24.282725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90388
41.1%
1 32028
 
14.6%
- 30000
 
13.6%
9 20509
 
9.3%
3 14602
 
6.6%
2 12356
 
5.6%
5 4632
 
2.1%
4 4607
 
2.1%
8 3842
 
1.7%
6 3599
 
1.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90388
47.6%
1 32028
 
16.9%
9 20509
 
10.8%
3 14602
 
7.7%
2 12356
 
6.5%
5 4632
 
2.4%
4 4607
 
2.4%
8 3842
 
2.0%
6 3599
 
1.9%
7 3437
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90388
41.1%
1 32028
 
14.6%
- 30000
 
13.6%
9 20509
 
9.3%
3 14602
 
6.6%
2 12356
 
5.6%
5 4632
 
2.1%
4 4607
 
2.1%
8 3842
 
1.7%
6 3599
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90388
41.1%
1 32028
 
14.6%
- 30000
 
13.6%
9 20509
 
9.3%
3 14602
 
6.6%
2 12356
 
5.6%
5 4632
 
2.1%
4 4607
 
2.1%
8 3842
 
1.7%
6 3599
 
1.6%
Distinct6004
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1907-05-09 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T05:30:25.012789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:25.683500image/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
7985 
1
2015 

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 7985
79.8%
1 2015
 
20.2%

Length

2024-05-11T05:30:26.326932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:26.726829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7985
79.8%
1 2015
 
20.2%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7985 
영업/정상
2015 

Length

Max length5
Median length2
Mean length2.6045
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7985
79.8%
영업/정상 2015
 
20.2%

Length

2024-05-11T05:30:27.082886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:27.491553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7985
79.8%
영업/정상 2015
 
20.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7985 
1
2015 

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 7985
79.8%
1 2015
 
20.2%

Length

2024-05-11T05:30:27.934815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:28.492899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7985
79.8%
1 2015
 
20.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7985 
영업
2015 

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 7985
79.8%
영업 2015
 
20.2%

Length

2024-05-11T05:30:29.151605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:29.778066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7985
79.8%
영업 2015
 
20.2%

폐업일자
Date

MISSING 

Distinct4516
Distinct (%)56.6%
Missing2015
Missing (%)20.2%
Memory size156.2 KiB
Minimum1983-06-11 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T05:30:30.465899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:31.311492image/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 

Distinct6227
Distinct (%)86.9%
Missing2833
Missing (%)28.3%
Memory size156.2 KiB
2024-05-11T05:30:33.592645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9991628
Min length2

Characters and Unicode

Total characters71664
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5919 ?
Unique (%)82.6%

Sample

1st row02 9057314
2nd row0209028622
3rd row0234928831
4th row02 9939885
5th row02906 0309
ValueCountFrequency (%)
02 4996
38.5%
0200000000 244
 
1.9%
954 133
 
1.0%
955 115
 
0.9%
956 111
 
0.9%
900 74
 
0.6%
999 47
 
0.4%
990 42
 
0.3%
070 40
 
0.3%
902 37
 
0.3%
Other values (6187) 7123
55.0%
2024-05-11T05:30:35.314097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15223
21.2%
9 11412
15.9%
2 10677
14.9%
7127
9.9%
5 5333
 
7.4%
3 4658
 
6.5%
4 4574
 
6.4%
8 3303
 
4.6%
1 3121
 
4.4%
7 3119
 
4.4%
Other values (2) 3117
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64532
90.0%
Space Separator 7127
 
9.9%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15223
23.6%
9 11412
17.7%
2 10677
16.5%
5 5333
 
8.3%
3 4658
 
7.2%
4 4574
 
7.1%
8 3303
 
5.1%
1 3121
 
4.8%
7 3119
 
4.8%
6 3112
 
4.8%
Space Separator
ValueCountFrequency (%)
7127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71664
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15223
21.2%
9 11412
15.9%
2 10677
14.9%
7127
9.9%
5 5333
 
7.4%
3 4658
 
6.5%
4 4574
 
6.4%
8 3303
 
4.6%
1 3121
 
4.4%
7 3119
 
4.4%
Other values (2) 3117
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15223
21.2%
9 11412
15.9%
2 10677
14.9%
7127
9.9%
5 5333
 
7.4%
3 4658
 
6.5%
4 4574
 
6.4%
8 3303
 
4.6%
1 3121
 
4.4%
7 3119
 
4.4%
Other values (2) 3117
 
4.3%

소재지면적
Text

MISSING 

Distinct3564
Distinct (%)37.8%
Missing560
Missing (%)5.6%
Memory size156.2 KiB
2024-05-11T05:30:36.256083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0826271
Min length3

Characters and Unicode

Total characters47980
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

Unique2264 ?
Unique (%)24.0%

Sample

1st row45.90
2nd row48.11
3rd row26.40
4th row16.30
5th row23.10
ValueCountFrequency (%)
26.40 390
 
4.1%
23.10 272
 
2.9%
29.70 208
 
2.2%
19.80 155
 
1.6%
33.00 145
 
1.5%
66.00 119
 
1.3%
49.50 94
 
1.0%
30.00 88
 
0.9%
16.50 84
 
0.9%
59.40 79
 
0.8%
Other values (3554) 7806
82.7%
2024-05-11T05:30:37.567091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9440
19.7%
0 8322
17.3%
2 5411
11.3%
1 3972
8.3%
3 3578
 
7.5%
4 3387
 
7.1%
6 3321
 
6.9%
5 3042
 
6.3%
9 2769
 
5.8%
8 2576
 
5.4%
Other values (2) 2162
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38528
80.3%
Other Punctuation 9452
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8322
21.6%
2 5411
14.0%
1 3972
10.3%
3 3578
9.3%
4 3387
8.8%
6 3321
 
8.6%
5 3042
 
7.9%
9 2769
 
7.2%
8 2576
 
6.7%
7 2150
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 9440
99.9%
, 12
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 47980
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9440
19.7%
0 8322
17.3%
2 5411
11.3%
1 3972
8.3%
3 3578
 
7.5%
4 3387
 
7.1%
6 3321
 
6.9%
5 3042
 
6.3%
9 2769
 
5.8%
8 2576
 
5.4%
Other values (2) 2162
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9440
19.7%
0 8322
17.3%
2 5411
11.3%
1 3972
8.3%
3 3578
 
7.5%
4 3387
 
7.1%
6 3321
 
6.9%
5 3042
 
6.3%
9 2769
 
5.8%
8 2576
 
5.4%
Other values (2) 2162
 
4.5%
Distinct270
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T05:30:38.467055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0858
Min length6

Characters and Unicode

Total characters60858
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

Unique38 ?
Unique (%)0.4%

Sample

1st row132849
2nd row132893
3rd row132842
4th row132040
5th row132925
ValueCountFrequency (%)
132821 394
 
3.9%
132820 362
 
3.6%
132854 349
 
3.5%
132917 337
 
3.4%
132898 297
 
3.0%
132850 272
 
2.7%
132924 267
 
2.7%
132819 235
 
2.4%
132864 231
 
2.3%
132853 215
 
2.1%
Other values (260) 7041
70.4%
2024-05-11T05:30:39.729267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12803
21.0%
1 12798
21.0%
3 11146
18.3%
8 8339
13.7%
9 4503
 
7.4%
0 2911
 
4.8%
4 2572
 
4.2%
5 2231
 
3.7%
6 1636
 
2.7%
7 1061
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
98.6%
Dash Punctuation 858
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12803
21.3%
1 12798
21.3%
3 11146
18.6%
8 8339
13.9%
9 4503
 
7.5%
0 2911
 
4.9%
4 2572
 
4.3%
5 2231
 
3.7%
6 1636
 
2.7%
7 1061
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 858
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12803
21.0%
1 12798
21.0%
3 11146
18.3%
8 8339
13.7%
9 4503
 
7.4%
0 2911
 
4.8%
4 2572
 
4.2%
5 2231
 
3.7%
6 1636
 
2.7%
7 1061
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12803
21.0%
1 12798
21.0%
3 11146
18.3%
8 8339
13.7%
9 4503
 
7.4%
0 2911
 
4.8%
4 2572
 
4.2%
5 2231
 
3.7%
6 1636
 
2.7%
7 1061
 
1.7%
Distinct7551
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T05:30:40.633628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length49
Mean length25.1827
Min length14

Characters and Unicode

Total characters251827
Distinct characters333
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6124 ?
Unique (%)61.2%

Sample

1st row서울특별시 도봉구 방학동 673-20번지
2nd row서울특별시 도봉구 쌍문동 639-0번지
3rd row서울특별시 도봉구 방학동 632-48번지 (지상1층)
4th row서울특별시 도봉구 창동 808-0번지 동아청솔아파트상가 지층02호
5th row서울특별시 도봉구 창동 651-77번지 (지상1층)
ValueCountFrequency (%)
서울특별시 10000
21.2%
도봉구 9999
21.2%
창동 3147
 
6.7%
방학동 2741
 
5.8%
도봉동 2198
 
4.7%
쌍문동 1941
 
4.1%
지상1층 1667
 
3.5%
1층 1273
 
2.7%
지하1층 277
 
0.6%
지상 155
 
0.3%
Other values (5290) 13750
29.2%
2024-05-11T05:30:42.179513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45394
18.0%
12301
 
4.9%
12298
 
4.9%
1 11377
 
4.5%
10641
 
4.2%
10596
 
4.2%
10065
 
4.0%
10031
 
4.0%
10010
 
4.0%
10007
 
4.0%
Other values (323) 109107
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142176
56.5%
Decimal Number 52315
 
20.8%
Space Separator 45394
 
18.0%
Dash Punctuation 9218
 
3.7%
Close Punctuation 950
 
0.4%
Open Punctuation 950
 
0.4%
Uppercase Letter 450
 
0.2%
Other Punctuation 354
 
0.1%
Math Symbol 13
 
< 0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12301
 
8.7%
12298
 
8.6%
10641
 
7.5%
10596
 
7.5%
10065
 
7.1%
10031
 
7.1%
10010
 
7.0%
10007
 
7.0%
10000
 
7.0%
10000
 
7.0%
Other values (279) 36227
25.5%
Uppercase Letter
ValueCountFrequency (%)
A 136
30.2%
S 99
22.0%
E 97
21.6%
B 42
 
9.3%
R 15
 
3.3%
L 8
 
1.8%
D 8
 
1.8%
Q 8
 
1.8%
G 7
 
1.6%
P 6
 
1.3%
Other values (12) 24
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 11377
21.7%
6 7077
13.5%
2 6138
11.7%
5 5223
10.0%
3 5014
9.6%
0 4521
 
8.6%
7 3857
 
7.4%
4 3589
 
6.9%
8 3076
 
5.9%
9 2443
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 311
87.9%
@ 28
 
7.9%
. 8
 
2.3%
/ 6
 
1.7%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
45394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 950
100.0%
Open Punctuation
ValueCountFrequency (%)
( 950
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142181
56.5%
Common 109194
43.4%
Latin 452
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12301
 
8.7%
12298
 
8.6%
10641
 
7.5%
10596
 
7.5%
10065
 
7.1%
10031
 
7.1%
10010
 
7.0%
10007
 
7.0%
10000
 
7.0%
10000
 
7.0%
Other values (280) 36232
25.5%
Latin
ValueCountFrequency (%)
A 136
30.1%
S 99
21.9%
E 97
21.5%
B 42
 
9.3%
R 15
 
3.3%
L 8
 
1.8%
D 8
 
1.8%
Q 8
 
1.8%
G 7
 
1.5%
P 6
 
1.3%
Other values (13) 26
 
5.8%
Common
ValueCountFrequency (%)
45394
41.6%
1 11377
 
10.4%
- 9218
 
8.4%
6 7077
 
6.5%
2 6138
 
5.6%
5 5223
 
4.8%
3 5014
 
4.6%
0 4521
 
4.1%
7 3857
 
3.5%
4 3589
 
3.3%
Other values (10) 7786
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142175
56.5%
ASCII 109646
43.5%
None 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45394
41.4%
1 11377
 
10.4%
- 9218
 
8.4%
6 7077
 
6.5%
2 6138
 
5.6%
5 5223
 
4.8%
3 5014
 
4.6%
0 4521
 
4.1%
7 3857
 
3.5%
4 3589
 
3.3%
Other values (33) 8238
 
7.5%
Hangul
ValueCountFrequency (%)
12301
 
8.7%
12298
 
8.6%
10641
 
7.5%
10596
 
7.5%
10065
 
7.1%
10031
 
7.1%
10010
 
7.0%
10007
 
7.0%
10000
 
7.0%
10000
 
7.0%
Other values (278) 36226
25.5%
None
ValueCountFrequency (%)
5
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3755
Distinct (%)83.8%
Missing5521
Missing (%)55.2%
Memory size156.2 KiB
2024-05-11T05:30:42.852827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length56
Mean length31.569324
Min length22

Characters and Unicode

Total characters141399
Distinct characters317
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3239 ?
Unique (%)72.3%

Sample

1st row서울특별시 도봉구 도봉로181길 30 (도봉동,(2층))
2nd row서울특별시 도봉구 해등로 161, 지하1층 (쌍문동)
3rd row서울특별시 도봉구 도당로19길 20, 1층 (방학동)
4th row서울특별시 도봉구 해등로 172, 1층 (쌍문동)
5th row서울특별시 도봉구 방학로 176, 1층 (방학동)
ValueCountFrequency (%)
서울특별시 4479
 
16.2%
도봉구 4478
 
16.2%
1층 1913
 
6.9%
창동 1257
 
4.5%
방학동 1047
 
3.8%
쌍문동 790
 
2.9%
도봉동 788
 
2.8%
지상1층 457
 
1.7%
도봉로 261
 
0.9%
마들로 236
 
0.9%
Other values (1869) 11949
43.2%
2024-05-11T05:30:44.267709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23182
 
16.4%
1 8675
 
6.1%
7584
 
5.4%
7288
 
5.2%
4930
 
3.5%
) 4732
 
3.3%
( 4732
 
3.3%
4684
 
3.3%
, 4612
 
3.3%
4494
 
3.2%
Other values (307) 66486
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78456
55.5%
Decimal Number 24832
 
17.6%
Space Separator 23182
 
16.4%
Close Punctuation 4732
 
3.3%
Open Punctuation 4732
 
3.3%
Other Punctuation 4634
 
3.3%
Dash Punctuation 507
 
0.4%
Uppercase Letter 308
 
0.2%
Math Symbol 10
 
< 0.1%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7584
 
9.7%
7288
 
9.3%
4930
 
6.3%
4684
 
6.0%
4494
 
5.7%
4485
 
5.7%
4480
 
5.7%
4479
 
5.7%
4479
 
5.7%
4339
 
5.5%
Other values (264) 27214
34.7%
Uppercase Letter
ValueCountFrequency (%)
A 71
23.1%
E 66
21.4%
S 64
20.8%
B 46
14.9%
R 14
 
4.5%
D 7
 
2.3%
Q 6
 
1.9%
L 6
 
1.9%
I 4
 
1.3%
M 4
 
1.3%
Other values (11) 20
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 8675
34.9%
2 2761
 
11.1%
0 2160
 
8.7%
3 2148
 
8.7%
6 1989
 
8.0%
5 1988
 
8.0%
4 1785
 
7.2%
7 1244
 
5.0%
9 1063
 
4.3%
8 1019
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 4612
99.5%
@ 8
 
0.2%
. 6
 
0.1%
/ 6
 
0.1%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
23182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4732
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4732
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 507
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78461
55.5%
Common 62629
44.3%
Latin 309
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7584
 
9.7%
7288
 
9.3%
4930
 
6.3%
4684
 
6.0%
4494
 
5.7%
4485
 
5.7%
4480
 
5.7%
4479
 
5.7%
4479
 
5.7%
4339
 
5.5%
Other values (265) 27219
34.7%
Latin
ValueCountFrequency (%)
A 71
23.0%
E 66
21.4%
S 64
20.7%
B 46
14.9%
R 14
 
4.5%
D 7
 
2.3%
Q 6
 
1.9%
L 6
 
1.9%
I 4
 
1.3%
M 4
 
1.3%
Other values (12) 21
 
6.8%
Common
ValueCountFrequency (%)
23182
37.0%
1 8675
 
13.9%
) 4732
 
7.6%
( 4732
 
7.6%
, 4612
 
7.4%
2 2761
 
4.4%
0 2160
 
3.4%
3 2148
 
3.4%
6 1989
 
3.2%
5 1988
 
3.2%
Other values (10) 5650
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78456
55.5%
ASCII 62938
44.5%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23182
36.8%
1 8675
 
13.8%
) 4732
 
7.5%
( 4732
 
7.5%
, 4612
 
7.3%
2 2761
 
4.4%
0 2160
 
3.4%
3 2148
 
3.4%
6 1989
 
3.2%
5 1988
 
3.2%
Other values (32) 5959
 
9.5%
Hangul
ValueCountFrequency (%)
7584
 
9.7%
7288
 
9.3%
4930
 
6.3%
4684
 
6.0%
4494
 
5.7%
4485
 
5.7%
4480
 
5.7%
4479
 
5.7%
4479
 
5.7%
4339
 
5.5%
Other values (264) 27214
34.7%
None
ValueCountFrequency (%)
5
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct179
Distinct (%)4.1%
Missing5581
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean1386.313
Minimum1300
Maximum4183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T05:30:44.788246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1300
5-th percentile1304
Q11340
median1387
Q31437
95-th percentile1474
Maximum4183
Range2883
Interquartile range (IQR)97

Descriptive statistics

Standard deviation69.384261
Coefficient of variation (CV)0.050049493
Kurtosis595.97008
Mean1386.313
Median Absolute Deviation (MAD)48
Skewness14.905572
Sum6126117
Variance4814.1757
MonotonicityNot monotonic
2024-05-11T05:30:45.230475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1414 158
 
1.6%
1332 136
 
1.4%
1340 103
 
1.0%
1455 102
 
1.0%
1405 92
 
0.9%
1349 92
 
0.9%
1394 82
 
0.8%
1399 79
 
0.8%
1473 78
 
0.8%
1390 77
 
0.8%
Other values (169) 3420
34.2%
(Missing) 5581
55.8%
ValueCountFrequency (%)
1300 12
 
0.1%
1301 66
0.7%
1302 37
0.4%
1303 73
0.7%
1304 60
0.6%
1305 13
 
0.1%
1306 10
 
0.1%
1307 67
0.7%
1308 17
 
0.2%
1309 28
 
0.3%
ValueCountFrequency (%)
4183 1
 
< 0.1%
1489 12
0.1%
1488 7
 
0.1%
1487 5
 
0.1%
1486 9
0.1%
1485 1
 
< 0.1%
1484 10
0.1%
1483 1
 
< 0.1%
1482 17
0.2%
1481 18
0.2%
Distinct8242
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T05:30:46.000256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length5.2294
Min length1

Characters and Unicode

Total characters52294
Distinct characters1041
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
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 row국도식당
2nd row람바다
3rd row짱나라 24시 해장국
4th row짱가네분식
5th row토스트 다우
ValueCountFrequency (%)
창동점 63
 
0.6%
방학점 40
 
0.4%
쌍문점 38
 
0.3%
전주식당 32
 
0.3%
실내포장마차 32
 
0.3%
김밥천국 22
 
0.2%
도봉점 21
 
0.2%
멕시칸치킨 20
 
0.2%
고향식당 18
 
0.2%
진미식당 17
 
0.2%
Other values (8636) 10958
97.3%
2024-05-11T05:30:47.595109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1264
 
2.4%
1170
 
2.2%
1011
 
1.9%
861
 
1.6%
811
 
1.6%
792
 
1.5%
742
 
1.4%
691
 
1.3%
649
 
1.2%
634
 
1.2%
Other values (1031) 43669
83.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48728
93.2%
Space Separator 1264
 
2.4%
Decimal Number 547
 
1.0%
Uppercase Letter 472
 
0.9%
Lowercase Letter 471
 
0.9%
Open Punctuation 315
 
0.6%
Close Punctuation 314
 
0.6%
Other Punctuation 173
 
0.3%
Dash Punctuation 7
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1170
 
2.4%
1011
 
2.1%
861
 
1.8%
811
 
1.7%
792
 
1.6%
742
 
1.5%
691
 
1.4%
649
 
1.3%
634
 
1.3%
606
 
1.2%
Other values (955) 40761
83.7%
Uppercase Letter
ValueCountFrequency (%)
B 76
16.1%
O 36
 
7.6%
C 34
 
7.2%
H 27
 
5.7%
T 24
 
5.1%
A 23
 
4.9%
M 21
 
4.4%
E 20
 
4.2%
G 19
 
4.0%
Q 18
 
3.8%
Other values (16) 174
36.9%
Lowercase Letter
ValueCountFrequency (%)
e 66
14.0%
a 51
10.8%
o 49
 
10.4%
i 31
 
6.6%
r 29
 
6.2%
n 26
 
5.5%
l 24
 
5.1%
s 24
 
5.1%
t 24
 
5.1%
f 23
 
4.9%
Other values (12) 124
26.3%
Other Punctuation
ValueCountFrequency (%)
& 64
37.0%
. 56
32.4%
? 17
 
9.8%
, 14
 
8.1%
' 6
 
3.5%
# 5
 
2.9%
! 5
 
2.9%
/ 3
 
1.7%
% 1
 
0.6%
: 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 107
19.6%
1 103
18.8%
0 72
13.2%
5 50
9.1%
8 45
8.2%
4 44
8.0%
9 43
7.9%
3 41
 
7.5%
7 25
 
4.6%
6 17
 
3.1%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1264
100.0%
Open Punctuation
ValueCountFrequency (%)
( 315
100.0%
Close Punctuation
ValueCountFrequency (%)
) 314
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48710
93.1%
Common 2622
 
5.0%
Latin 943
 
1.8%
Han 19
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1170
 
2.4%
1011
 
2.1%
861
 
1.8%
811
 
1.7%
792
 
1.6%
742
 
1.5%
691
 
1.4%
649
 
1.3%
634
 
1.3%
606
 
1.2%
Other values (938) 40743
83.6%
Latin
ValueCountFrequency (%)
B 76
 
8.1%
e 66
 
7.0%
a 51
 
5.4%
o 49
 
5.2%
O 36
 
3.8%
C 34
 
3.6%
i 31
 
3.3%
r 29
 
3.1%
H 27
 
2.9%
n 26
 
2.8%
Other values (38) 518
54.9%
Common
ValueCountFrequency (%)
1264
48.2%
( 315
 
12.0%
) 314
 
12.0%
2 107
 
4.1%
1 103
 
3.9%
0 72
 
2.7%
& 64
 
2.4%
. 56
 
2.1%
5 50
 
1.9%
8 45
 
1.7%
Other values (17) 232
 
8.8%
Han
ValueCountFrequency (%)
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48708
93.1%
ASCII 3562
 
6.8%
CJK 19
 
< 0.1%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1264
35.5%
( 315
 
8.8%
) 314
 
8.8%
2 107
 
3.0%
1 103
 
2.9%
B 76
 
2.1%
0 72
 
2.0%
e 66
 
1.9%
& 64
 
1.8%
. 56
 
1.6%
Other values (62) 1125
31.6%
Hangul
ValueCountFrequency (%)
1170
 
2.4%
1011
 
2.1%
861
 
1.8%
811
 
1.7%
792
 
1.6%
742
 
1.5%
691
 
1.4%
649
 
1.3%
634
 
1.3%
606
 
1.2%
Other values (936) 40741
83.6%
CJK
ValueCountFrequency (%)
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (8) 8
42.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6950
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-06 00:00:00
Maximum2024-05-09 10:47:51
2024-05-11T05:30:48.254010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:48.761891image/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
7855 
U
2145 

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 7855
78.5%
U 2145
 
21.4%

Length

2024-05-11T05:30:49.659123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:50.096481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7855
78.5%
u 2145
 
21.4%
Distinct1206
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T05:30:50.492948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:51.329442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4352 
분식
1852 
호프/통닭
979 
경양식
555 
통닭(치킨)
 
381
Other values (19)
1881 

Length

Max length15
Median length2
Mean length2.8786
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row중국식
3rd row한식
4th row분식
5th row분식

Common Values

ValueCountFrequency (%)
한식 4352
43.5%
분식 1852
18.5%
호프/통닭 979
 
9.8%
경양식 555
 
5.5%
통닭(치킨) 381
 
3.8%
일식 359
 
3.6%
기타 351
 
3.5%
중국식 314
 
3.1%
까페 191
 
1.9%
정종/대포집/소주방 178
 
1.8%
Other values (14) 488
 
4.9%

Length

2024-05-11T05:30:52.178206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4352
43.5%
분식 1852
18.5%
호프/통닭 979
 
9.8%
경양식 555
 
5.5%
통닭(치킨 381
 
3.8%
일식 359
 
3.6%
기타 351
 
3.5%
중국식 314
 
3.1%
까페 191
 
1.9%
정종/대포집/소주방 178
 
1.8%
Other values (14) 488
 
4.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2922
Distinct (%)30.4%
Missing376
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean203385.99
Minimum196602.92
Maximum204719.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T05:30:52.765635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196602.92
5-th percentile202199.68
Q1203079.4
median203457.06
Q3203811.42
95-th percentile204260.19
Maximum204719.28
Range8116.3556
Interquartile range (IQR)732.02041

Descriptive statistics

Standard deviation631.64221
Coefficient of variation (CV)0.0031056328
Kurtosis3.7370483
Mean203385.99
Median Absolute Deviation (MAD)371.45917
Skewness-1.3094893
Sum1.9573868 × 109
Variance398971.88
MonotonicityNot monotonic
2024-05-11T05:30:53.535438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203946.218925234 56
 
0.6%
204083.769271308 45
 
0.4%
204169.847670316 42
 
0.4%
203220.374977448 31
 
0.3%
203984.137173444 31
 
0.3%
204317.264907404 30
 
0.3%
204279.415 30
 
0.3%
203242.968498731 29
 
0.3%
203890.492709829 28
 
0.3%
203953.833720651 27
 
0.3%
Other values (2912) 9275
92.8%
(Missing) 376
 
3.8%
ValueCountFrequency (%)
196602.921764405 1
 
< 0.1%
201065.929648946 2
 
< 0.1%
201076.85313831 5
0.1%
201080.934192453 3
< 0.1%
201081.915285607 7
0.1%
201085.925925578 1
 
< 0.1%
201094.369420008 3
< 0.1%
201095.903057318 7
0.1%
201096.680640152 2
 
< 0.1%
201098.761383515 3
< 0.1%
ValueCountFrequency (%)
204719.277363253 3
 
< 0.1%
204641.872260793 2
 
< 0.1%
204623.018873403 12
0.1%
204582.338677684 1
 
< 0.1%
204569.769384803 2
 
< 0.1%
204534.405989157 1
 
< 0.1%
204510.908809878 1
 
< 0.1%
204506.921108086 12
0.1%
204502.118604099 6
0.1%
204488.650732578 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2922
Distinct (%)30.4%
Missing376
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean461924.4
Minimum449882.49
Maximum465478.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T05:30:54.324795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449882.49
5-th percentile459563.52
Q1460908.62
median461960.78
Q3462850.68
95-th percentile464625.42
Maximum465478.52
Range15596.027
Interquartile range (IQR)1942.0652

Descriptive statistics

Standard deviation1424.3603
Coefficient of variation (CV)0.0030835355
Kurtosis-0.061277446
Mean461924.4
Median Absolute Deviation (MAD)969.17022
Skewness0.049458689
Sum4.4455604 × 109
Variance2028802.3
MonotonicityNot monotonic
2024-05-11T05:30:54.906182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462919.219463289 56
 
0.6%
462849.020752258 45
 
0.4%
464814.717432497 42
 
0.4%
464866.74995962 31
 
0.3%
461008.914009807 31
 
0.3%
461224.014056627 30
 
0.3%
461140.88 30
 
0.3%
460001.081136921 29
 
0.3%
462686.077387621 28
 
0.3%
462675.950480622 27
 
0.3%
Other values (2912) 9275
92.8%
(Missing) 376
 
3.8%
ValueCountFrequency (%)
449882.493878941 1
< 0.1%
458893.791471245 1
< 0.1%
458929.963006728 1
< 0.1%
458940.711388052 1
< 0.1%
458949.910542727 1
< 0.1%
458954.54912126 2
< 0.1%
458959.625639951 1
< 0.1%
458968.625259996 2
< 0.1%
458980.656746745 1
< 0.1%
458981.076989217 1
< 0.1%
ValueCountFrequency (%)
465478.520742432 1
< 0.1%
465406.9671209 1
< 0.1%
465314.409287091 2
< 0.1%
465277.522479657 1
< 0.1%
465275.378864957 1
< 0.1%
465272.877451705 1
< 0.1%
465266.234116323 1
< 0.1%
465256.803814673 1
< 0.1%
465240.855556 1
< 0.1%
465166.726281001 1
< 0.1%

위생업태명
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3774 
분식
1779 
<NA>
1290 
호프/통닭
832 
경양식
497 
Other values (18)
1828 

Length

Max length15
Median length2
Mean length3.0217
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한식
2nd row중국식
3rd row한식
4th row분식
5th row분식

Common Values

ValueCountFrequency (%)
한식 3774
37.7%
분식 1779
17.8%
<NA> 1290
 
12.9%
호프/통닭 832
 
8.3%
경양식 497
 
5.0%
통닭(치킨) 350
 
3.5%
일식 283
 
2.8%
중국식 266
 
2.7%
까페 184
 
1.8%
정종/대포집/소주방 170
 
1.7%
Other values (13) 575
 
5.8%

Length

2024-05-11T05:30:55.451421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3774
37.7%
분식 1779
17.8%
na 1290
 
12.9%
호프/통닭 832
 
8.3%
경양식 497
 
5.0%
통닭(치킨 350
 
3.5%
일식 283
 
2.8%
중국식 266
 
2.7%
까페 184
 
1.8%
정종/대포집/소주방 170
 
1.7%
Other values (13) 575
 
5.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.1%
Missing4638
Missing (%)46.4%
Infinite0
Infinite (%)0.0%
Mean0.19339799
Minimum-1
Maximum11
Zeros4506
Zeros (%)45.1%
Negative14
Negative (%)0.1%
Memory size166.0 KiB
2024-05-11T05:30:55.945496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum11
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.52727267
Coefficient of variation (CV)2.7263607
Kurtosis44.852628
Mean0.19339799
Median Absolute Deviation (MAD)0
Skewness4.4393597
Sum1037
Variance0.27801647
MonotonicityNot monotonic
2024-05-11T05:30:56.476307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 4506
45.1%
1 683
 
6.8%
2 131
 
1.3%
3 17
 
0.2%
-1 14
 
0.1%
4 6
 
0.1%
5 4
 
< 0.1%
11 1
 
< 0.1%
(Missing) 4638
46.4%
ValueCountFrequency (%)
-1 14
 
0.1%
0 4506
45.1%
1 683
 
6.8%
2 131
 
1.3%
3 17
 
0.2%
4 6
 
0.1%
5 4
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
5 4
 
< 0.1%
4 6
 
0.1%
3 17
 
0.2%
2 131
 
1.3%
1 683
 
6.8%
0 4506
45.1%
-1 14
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.2%
Missing4556
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean0.36333578
Minimum-1
Maximum10
Zeros3905
Zeros (%)39.1%
Negative10
Negative (%)0.1%
Memory size166.0 KiB
2024-05-11T05:30:57.081163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum10
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.68249171
Coefficient of variation (CV)1.8784049
Kurtosis18.34605
Mean0.36333578
Median Absolute Deviation (MAD)0
Skewness2.8706468
Sum1978
Variance0.46579493
MonotonicityNot monotonic
2024-05-11T05:30:57.666010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 3905
39.1%
1 1149
 
11.5%
2 337
 
3.4%
3 29
 
0.3%
-1 10
 
0.1%
4 7
 
0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 4556
45.6%
ValueCountFrequency (%)
-1 10
 
0.1%
0 3905
39.1%
1 1149
 
11.5%
2 337
 
3.4%
3 29
 
0.3%
4 7
 
0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
8 2
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 1
 
< 0.1%
4 7
 
0.1%
3 29
 
0.3%
2 337
 
3.4%
1 1149
 
11.5%
0 3905
39.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6163 
주택가주변
2528 
기타
903 
아파트지역
 
307
유흥업소밀집지역
 
52
Other values (3)
 
47

Length

Max length8
Median length4
Mean length4.1415
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6163
61.6%
주택가주변 2528
25.3%
기타 903
 
9.0%
아파트지역 307
 
3.1%
유흥업소밀집지역 52
 
0.5%
학교정화(상대) 22
 
0.2%
학교정화(절대) 15
 
0.1%
결혼예식장주변 10
 
0.1%

Length

2024-05-11T05:30:58.146114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:58.605513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6163
61.6%
주택가주변 2528
25.3%
기타 903
 
9.0%
아파트지역 307
 
3.1%
유흥업소밀집지역 52
 
0.5%
학교정화(상대 22
 
0.2%
학교정화(절대 15
 
0.1%
결혼예식장주변 10
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6190 
기타
1428 
자율
1251 
지도
 
469
우수
 
453
Other values (3)
 
209

Length

Max length4
Median length4
Mean length3.2188
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6190
61.9%
기타 1428
 
14.3%
자율 1251
 
12.5%
지도 469
 
4.7%
우수 453
 
4.5%
159
 
1.6%
33
 
0.3%
관리 17
 
0.2%

Length

2024-05-11T05:30:59.019439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:59.422837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6190
61.9%
기타 1428
 
14.3%
자율 1251
 
12.5%
지도 469
 
4.7%
우수 453
 
4.5%
159
 
1.6%
33
 
0.3%
관리 17
 
0.2%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
5892 
<NA>
4076 
지하수전용
 
21
상수도(음용)지하수(주방용)겸용
 
11

Length

Max length17
Median length5
Mean length4.6056
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 5892
58.9%
<NA> 4076
40.8%
지하수전용 21
 
0.2%
상수도(음용)지하수(주방용)겸용 11
 
0.1%

Length

2024-05-11T05:31:00.086535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:00.532839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 5892
58.9%
na 4076
40.8%
지하수전용 21
 
0.2%
상수도(음용)지하수(주방용)겸용 11
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9691 
0
 
309

Length

Max length4
Median length4
Mean length3.9073
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> 9691
96.9%
0 309
 
3.1%

Length

2024-05-11T05:31:01.352432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:01.754126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9691
96.9%
0 309
 
3.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:02.205993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:02.654331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:03.048651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:03.452630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:03.899155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:04.544731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:05.019580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:05.540601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

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>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:06.076295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:06.518537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9689 
0
 
311

Length

Max length4
Median length4
Mean length3.9067
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> 9689
96.9%
0 311
 
3.1%

Length

2024-05-11T05:31:06.913804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:07.655663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9689
96.9%
0 311
 
3.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1290
Missing (%)12.9%
Memory size97.7 KiB
False
8585 
True
 
125
(Missing)
1290 
ValueCountFrequency (%)
False 8585
85.9%
True 125
 
1.2%
(Missing) 1290
 
12.9%
2024-05-11T05:31:08.020329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct3227
Distinct (%)37.0%
Missing1290
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean48.941459
Minimum0
Maximum2176.95
Zeros581
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T05:31:08.522153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q122.325
median30
Q357.99
95-th percentile128.0605
Maximum2176.95
Range2176.95
Interquartile range (IQR)35.665

Descriptive statistics

Standard deviation73.163569
Coefficient of variation (CV)1.4949201
Kurtosis207.58742
Mean48.941459
Median Absolute Deviation (MAD)12.44
Skewness11.273114
Sum426280.11
Variance5352.9078
MonotonicityNot monotonic
2024-05-11T05:31:09.110197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 581
 
5.8%
26.4 371
 
3.7%
23.1 257
 
2.6%
29.7 197
 
2.0%
19.8 146
 
1.5%
33.0 117
 
1.2%
66.0 102
 
1.0%
49.5 88
 
0.9%
16.5 78
 
0.8%
59.4 73
 
0.7%
Other values (3217) 6700
67.0%
(Missing) 1290
 
12.9%
ValueCountFrequency (%)
0.0 581
5.8%
1.0 1
 
< 0.1%
1.5 1
 
< 0.1%
3.3 1
 
< 0.1%
4.7 1
 
< 0.1%
4.9 1
 
< 0.1%
6.6 6
 
0.1%
6.64 1
 
< 0.1%
6.7 1
 
< 0.1%
6.95 1
 
< 0.1%
ValueCountFrequency (%)
2176.95 1
< 0.1%
1561.0 2
< 0.1%
1545.66 1
< 0.1%
1235.07 1
< 0.1%
1223.27 1
< 0.1%
1204.5 1
< 0.1%
1191.32 1
< 0.1%
1143.38 1
< 0.1%
1134.14 1
< 0.1%
1087.2 1
< 0.1%
Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T05:31:09.552740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row0032
2nd row
ValueCountFrequency (%)
0032 1
100.0%
2024-05-11T05:31:10.402503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
55.6%
0 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 5
55.6%
Decimal Number 4
44.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
50.0%
3 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5
55.6%
0 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
55.6%
0 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

전통업소주된음식
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing9999
Missing (%)> 99.9%
Memory size156.2 KiB
2024-05-11T05:31:10.847874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
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 row갈비탕
ValueCountFrequency (%)
갈비탕 1
100.0%
2024-05-11T05:31:11.852025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
232930900003090000-101-1995-0263119950513<NA>3폐업2폐업19960802<NA><NA><NA>02 905731445.90132849서울특별시 도봉구 방학동 673-20번지<NA><NA>국도식당2002-01-18 00:00:00I2018-08-31 23:59:59.0한식203367.052093462251.653964한식12기타우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N45.9<NA><NA><NA>
118330900003090000-101-1992-0116919920611<NA>3폐업2폐업19930324<NA><NA><NA>020902862248.11132893서울특별시 도봉구 쌍문동 639-0번지<NA><NA>람바다2002-01-24 00:00:00I2018-08-31 23:59:59.0중국식203273.762286461602.908743중국식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N48.11<NA><NA><NA>
692430900003090000-101-2005-0021820050809<NA>3폐업2폐업20060605<NA><NA><NA>023492883126.40132842서울특별시 도봉구 방학동 632-48번지 (지상1층)<NA><NA>짱나라 24시 해장국2006-04-04 00:00:00I2018-08-31 23:59:59.0한식202970.112111462642.707495한식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.4<NA><NA><NA>
404230900003090000-101-1999-0449419990318<NA>3폐업2폐업19991207<NA><NA><NA>02 993988516.30132040서울특별시 도봉구 창동 808-0번지 동아청솔아파트상가 지층02호<NA><NA>짱가네분식1999-12-07 00:00:00I2018-08-31 23:59:59.0분식204192.915095461653.030005분식11아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.3<NA><NA><NA>
708230900003090000-101-2006-0004020060308<NA>3폐업2폐업20111128<NA><NA><NA>02906 030923.10132925서울특별시 도봉구 창동 651-77번지 (지상1층)<NA><NA>토스트 다우2011-11-02 16:37:50I2018-08-31 23:59:59.0분식203085.597263460485.042698분식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.1<NA><NA><NA>
525430900003090000-101-2001-0588920010704<NA>3폐업2폐업20021030<NA><NA><NA><NA><NA>132884서울특별시 도봉구 쌍문동 372-7번지 지상1층<NA><NA>사또치킨호프2002-01-29 00:00:00I2018-08-31 23:59:59.0분식202147.521446460565.733976분식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
585830900003090000-101-2003-0000920030111<NA>3폐업2폐업20221219<NA><NA><NA><NA>36.30132815서울특별시 도봉구 도봉동 568-40 (2층)서울특별시 도봉구 도봉로181길 30 (도봉동,(2층))1303마츠머츠2022-12-19 11:43:55U2021-11-01 22:01:00.0호프/통닭203832.632451464654.516412<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
545230900003090000-101-2002-0578720020406<NA>3폐업2폐업20210824<NA><NA><NA>02 903257899.00132893서울특별시 도봉구 쌍문동 638서울특별시 도봉구 해등로 161, 지하1층 (쌍문동)1432휘가로2021-08-24 18:42:20U2021-08-26 02:40:00.0경양식203322.667869461614.137377경양식00<NA><NA><NA>00000<NA>00N99.0<NA><NA><NA>
232830900003090000-101-1995-0261619950306<NA>3폐업2폐업19950829<NA><NA><NA>02 991075428.32132872서울특별시 도봉구 쌍문동 248-2번지<NA><NA>피노키오분식2002-01-24 00:00:00I2018-08-31 23:59:59.0분식202407.91742461818.574821분식00아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.32<NA><NA><NA>
1039230900003090000-101-2019-0009820190515<NA>1영업/정상1영업<NA><NA><NA><NA>02 955955583.74132845서울특별시 도봉구 방학동 648-3번지서울특별시 도봉구 도당로19길 20, 1층 (방학동)1352황금정2020-01-02 11:36:39U2020-01-04 02:40:00.0중국식203404.204721462836.332327중국식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N83.74<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
172630900003090000-101-1993-0399419930726<NA>3폐업2폐업20101227<NA><NA><NA>020954594469.20132822서울특별시 도봉구 도봉동 629-22번지<NA><NA>생오리숯불바베큐2010-12-20 14:58:21I2018-08-31 23:59:59.0한식204283.398201463913.603743한식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.2<NA><NA><NA>
323330900003090000-101-1997-0028519971001<NA>3폐업2폐업20111110<NA><NA><NA>02 908929229.75132866서울특별시 도봉구 쌍문동 88-38번지<NA><NA>다래분식2011-10-21 10:26:07I2018-08-31 23:59:59.0분식202894.781129460661.153936분식<NA>2기타우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.75<NA><NA><NA>
296330900003090000-101-1996-0237419960605<NA>3폐업2폐업19960605<NA><NA><NA>020904985123.76132904서울특별시 도봉구 창동 134-2번지<NA><NA>바이타임창동3점2002-01-18 00:00:00I2018-08-31 23:59:59.0분식204005.432345461250.759986분식00주택가주변우수상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.76<NA><NA><NA>
1128430900003090000-101-2023-000702023-04-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.00132-896서울특별시 도봉구 쌍문동 716서울특별시 도봉구 방학로3길 71, 1층 가운데호 (쌍문동)1392두번먹는 명인김치찜 쌍문점2023-04-11 15:24:33I2022-12-03 23:03:00.0한식203464.377667461930.116534<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
202330900003090000-101-1994-0325419940617<NA>3폐업2폐업19980330<NA><NA><NA>023491122572.26132806서울특별시 도봉구 도봉동 275-7번지 1층호<NA><NA>나도나건강외식2002-01-18 00:00:00I2018-08-31 23:59:59.0한식203848.982426465020.60065한식00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N72.26<NA><NA><NA>
843530900003090000-101-2011-000362011-03-11<NA>1영업/정상1영업<NA><NA><NA><NA>02 9210031118.48132-848서울특별시 도봉구 방학동 668-8 지하1층서울특별시 도봉구 방학로 184 (방학동, 지하1층)1357작은음악회(라이브)2023-11-07 09:36:20U2022-11-01 00:09:00.0라이브카페202731.100129462228.589039<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
566530900003090000-101-2002-0600520020829<NA>3폐업2폐업20081201<NA><NA><NA>02 993616719.80132952서울특별시 도봉구 쌍문동 315-78번지 (1층)<NA><NA>숭미한식분식2007-04-13 00:00:00I2018-08-31 23:59:59.0분식202436.664765460853.904106분식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N19.8<NA><NA><NA>
653630900003090000-101-2004-0021720040716<NA>3폐업2폐업20041227<NA><NA><NA>02 944128861.00132892서울특별시 도봉구 쌍문동 601번지 (지상2층)<NA><NA>솔죽2004-07-16 00:00:00I2018-08-31 23:59:59.0한식203394.40396461673.069002한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N61.0<NA><NA><NA>
205430900003090000-101-1994-0354719940202<NA>3폐업2폐업20060906<NA><NA><NA>020906484130.68132919서울특별시 도봉구 창동 609-13번지<NA><NA>뽀빠이치킨2002-01-25 00:00:00I2018-08-31 23:59:59.0분식203481.657578460154.625325분식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N30.68<NA><NA><NA>
299730900003090000-101-1996-0262419960615<NA>3폐업2폐업19990308<NA><NA><NA>023493933898.39132848서울특별시 도봉구 방학동 668-32번지<NA><NA>신토불이1999-03-08 00:00:00I2018-08-31 23:59:59.0한식202826.137551462242.989954한식00주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N98.39<NA><NA><NA>