Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells108454
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical18
Text8
DateTime4
Unsupported7
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18660/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (58.6%)Imbalance
총인원 is highly imbalanced (79.3%)Imbalance
본사종업원수 is highly imbalanced (79.3%)Imbalance
공장사무직종업원수 is highly imbalanced (79.3%)Imbalance
공장판매직종업원수 is highly imbalanced (79.3%)Imbalance
공장생산직종업원수 is highly imbalanced (79.3%)Imbalance
보증액 is highly imbalanced (79.3%)Imbalance
월세액 is highly imbalanced (79.3%)Imbalance
다중이용업소여부 is highly imbalanced (96.7%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2091 (20.9%) 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 3004 (30.0%) missing valuesMissing
소재지면적 has 536 (5.4%) missing valuesMissing
도로명주소 has 5502 (55.0%) missing valuesMissing
도로명우편번호 has 5558 (55.6%) missing valuesMissing
좌표정보(X) has 493 (4.9%) missing valuesMissing
좌표정보(Y) has 493 (4.9%) missing valuesMissing
남성종사자수 has 4041 (40.4%) missing valuesMissing
여성종사자수 has 3946 (39.5%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1398 (14.0%) missing valuesMissing
시설총규모 has 1398 (14.0%) missing valuesMissing
전통업소지정번호 has 9994 (99.9%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 52.22788374)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4755 (47.5%) zerosZeros
여성종사자수 has 3625 (36.2%) zerosZeros
시설총규모 has 543 (5.4%) zerosZeros

Reproduction

Analysis started2024-05-11 08:29:55.574093
Analysis finished2024-05-11 08:29:57.585761
Duration2.01 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
3080000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 10000
100.0%

Length

2024-05-11T17:29:57.636516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:29:57.720140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:29:57.878140image/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 row3080000-101-2013-00212
2nd row3080000-101-1986-05216
3rd row3080000-101-2023-00216
4th row3080000-101-2021-00043
5th row3080000-101-2022-00148
ValueCountFrequency (%)
3080000-101-2013-00212 1
 
< 0.1%
3080000-101-1993-04457 1
 
< 0.1%
3080000-101-1991-04391 1
 
< 0.1%
3080000-101-1995-06563 1
 
< 0.1%
3080000-101-2000-08806 1
 
< 0.1%
3080000-101-2005-00302 1
 
< 0.1%
3080000-101-2017-00029 1
 
< 0.1%
3080000-101-2002-00411 1
 
< 0.1%
3080000-101-2019-00277 1
 
< 0.1%
3080000-101-1995-04793 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T17:29:58.196049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89617
40.7%
1 31414
 
14.3%
- 30000
 
13.6%
8 14945
 
6.8%
3 14854
 
6.8%
2 12013
 
5.5%
9 10868
 
4.9%
4 4318
 
2.0%
6 3999
 
1.8%
7 3996
 
1.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 89617
47.2%
1 31414
 
16.5%
8 14945
 
7.9%
3 14854
 
7.8%
2 12013
 
6.3%
9 10868
 
5.7%
4 4318
 
2.3%
6 3999
 
2.1%
7 3996
 
2.1%
5 3976
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89617
40.7%
1 31414
 
14.3%
- 30000
 
13.6%
8 14945
 
6.8%
3 14854
 
6.8%
2 12013
 
5.5%
9 10868
 
4.9%
4 4318
 
2.0%
6 3999
 
1.8%
7 3996
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89617
40.7%
1 31414
 
14.3%
- 30000
 
13.6%
8 14945
 
6.8%
3 14854
 
6.8%
2 12013
 
5.5%
9 10868
 
4.9%
4 4318
 
2.0%
6 3999
 
1.8%
7 3996
 
1.8%
Distinct6250
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T17:29:58.336131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:29:58.466149image/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
7909 
1
2091 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7909
79.1%
1 2091
 
20.9%

Length

2024-05-11T17:29:58.583483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:29:58.663675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7909
79.1%
1 2091
 
20.9%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7909 
영업/정상
2091 

Length

Max length5
Median length2
Mean length2.6273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7909
79.1%
영업/정상 2091
 
20.9%

Length

2024-05-11T17:29:58.759199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:29:58.853156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7909
79.1%
영업/정상 2091
 
20.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7909 
1
2091 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7909
79.1%
1 2091
 
20.9%

Length

2024-05-11T17:29:58.953193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:29:59.035966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7909
79.1%
1 2091
 
20.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7909 
영업
2091 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7909
79.1%
영업 2091
 
20.9%

Length

2024-05-11T17:29:59.121000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:29:59.201871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7909
79.1%
영업 2091
 
20.9%

폐업일자
Date

MISSING 

Distinct4467
Distinct (%)56.5%
Missing2091
Missing (%)20.9%
Memory size156.2 KiB
Minimum1987-05-14 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T17:29:59.292354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:29:59.413596image/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 

Distinct5797
Distinct (%)82.9%
Missing3004
Missing (%)30.0%
Memory size156.2 KiB
2024-05-11T17:29:59.735587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8532018
Min length2

Characters and Unicode

Total characters68933
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5559 ?
Unique (%)79.5%

Sample

1st row0200000000
2nd row02 9940582
3rd row02 9080111
4th row02 9875651
5th row02 9818075
ValueCountFrequency (%)
02 6131
45.1%
00000 291
 
2.1%
0200000000 210
 
1.5%
988 51
 
0.4%
9057110 48
 
0.4%
980 45
 
0.3%
945 44
 
0.3%
987 39
 
0.3%
0209057110 35
 
0.3%
989 35
 
0.3%
Other values (5822) 6665
49.0%
2024-05-11T17:30:00.152381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15603
22.6%
2 10257
14.9%
9 10037
14.6%
8156
11.8%
8 5780
 
8.4%
5 3585
 
5.2%
1 3194
 
4.6%
3 3193
 
4.6%
7 3152
 
4.6%
4 3132
 
4.5%
Other values (4) 2844
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60772
88.2%
Space Separator 8156
 
11.8%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15603
25.7%
2 10257
16.9%
9 10037
16.5%
8 5780
 
9.5%
5 3585
 
5.9%
1 3194
 
5.3%
3 3193
 
5.3%
7 3152
 
5.2%
4 3132
 
5.2%
6 2839
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
8156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15603
22.6%
2 10257
14.9%
9 10037
14.6%
8156
11.8%
8 5780
 
8.4%
5 3585
 
5.2%
1 3194
 
4.6%
3 3193
 
4.6%
7 3152
 
4.6%
4 3132
 
4.5%
Other values (4) 2844
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15603
22.6%
2 10257
14.9%
9 10037
14.6%
8156
11.8%
8 5780
 
8.4%
5 3585
 
5.2%
1 3194
 
4.6%
3 3193
 
4.6%
7 3152
 
4.6%
4 3132
 
4.5%
Other values (4) 2844
 
4.1%

소재지면적
Text

MISSING 

Distinct4448
Distinct (%)47.0%
Missing536
Missing (%)5.4%
Memory size156.2 KiB
2024-05-11T17:30:00.503083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0861158
Min length3

Characters and Unicode

Total characters48135
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

Unique2889 ?
Unique (%)30.5%

Sample

1st row19.72
2nd row40.32
3rd row31.96
4th row33.00
5th row49.50
ValueCountFrequency (%)
33.00 103
 
1.1%
26.40 80
 
0.8%
30.00 79
 
0.8%
24.00 73
 
0.8%
20.00 53
 
0.6%
27.00 49
 
0.5%
23.10 48
 
0.5%
18.00 47
 
0.5%
19.80 47
 
0.5%
21.00 44
 
0.5%
Other values (4438) 8841
93.4%
2024-05-11T17:30:00.963744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9464
19.7%
0 7289
15.1%
2 5394
11.2%
1 4209
8.7%
3 3668
 
7.6%
4 3520
 
7.3%
6 3277
 
6.8%
5 3178
 
6.6%
8 2955
 
6.1%
9 2587
 
5.4%
Other values (2) 2594
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38661
80.3%
Other Punctuation 9474
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7289
18.9%
2 5394
14.0%
1 4209
10.9%
3 3668
9.5%
4 3520
9.1%
6 3277
8.5%
5 3178
8.2%
8 2955
7.6%
9 2587
 
6.7%
7 2584
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 9464
99.9%
, 10
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 48135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9464
19.7%
0 7289
15.1%
2 5394
11.2%
1 4209
8.7%
3 3668
 
7.6%
4 3520
 
7.3%
6 3277
 
6.8%
5 3178
 
6.6%
8 2955
 
6.1%
9 2587
 
5.4%
Other values (2) 2594
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9464
19.7%
0 7289
15.1%
2 5394
11.2%
1 4209
8.7%
3 3668
 
7.6%
4 3520
 
7.3%
6 3277
 
6.8%
5 3178
 
6.6%
8 2955
 
6.1%
9 2587
 
5.4%
Other values (2) 2594
 
5.4%
Distinct140
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:30:01.271858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0968
Min length6

Characters and Unicode

Total characters60968
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

Unique16 ?
Unique (%)0.2%

Sample

1st row142807
2nd row142827
3rd row142-870
4th row142-885
5th row142-804
ValueCountFrequency (%)
142804 715
 
7.1%
142878 611
 
6.1%
142876 543
 
5.4%
142070 505
 
5.1%
142803 323
 
3.2%
142874 319
 
3.2%
142805 314
 
3.1%
142864 280
 
2.8%
142815 255
 
2.5%
142872 244
 
2.4%
Other values (130) 5891
58.9%
2024-05-11T17:30:01.653131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12479
20.5%
4 11702
19.2%
2 11374
18.7%
8 10771
17.7%
0 4424
 
7.3%
7 4294
 
7.0%
6 2471
 
4.1%
- 968
 
1.6%
5 916
 
1.5%
9 825
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
98.4%
Dash Punctuation 968
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12479
20.8%
4 11702
19.5%
2 11374
19.0%
8 10771
18.0%
0 4424
 
7.4%
7 4294
 
7.2%
6 2471
 
4.1%
5 916
 
1.5%
9 825
 
1.4%
3 744
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 968
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60968
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12479
20.5%
4 11702
19.2%
2 11374
18.7%
8 10771
17.7%
0 4424
 
7.3%
7 4294
 
7.0%
6 2471
 
4.1%
- 968
 
1.6%
5 916
 
1.5%
9 825
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12479
20.5%
4 11702
19.2%
2 11374
18.7%
8 10771
17.7%
0 4424
 
7.3%
7 4294
 
7.0%
6 2471
 
4.1%
- 968
 
1.6%
5 916
 
1.5%
9 825
 
1.4%
Distinct7084
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:30:01.929358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length50
Mean length24.6611
Min length14

Characters and Unicode

Total characters246611
Distinct characters345
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

Unique5545 ?
Unique (%)55.5%

Sample

1st row서울특별시 강북구 미아동 121-38번지
2nd row서울특별시 강북구 미아동 688-5번지
3rd row서울특별시 강북구 수유동 402-8
4th row서울특별시 강북구 수유동 451-172
5th row서울특별시 강북구 미아동 55-20
ValueCountFrequency (%)
서울특별시 10000
22.2%
강북구 9997
22.2%
미아동 4197
 
9.3%
수유동 4015
 
8.9%
번동 1383
 
3.1%
지상1층 926
 
2.1%
1층 430
 
1.0%
우이동 417
 
0.9%
지상2층 111
 
0.2%
지하1층 105
 
0.2%
Other values (6347) 13410
29.8%
2024-05-11T17:30:02.338866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43441
 
17.6%
1 11235
 
4.6%
10254
 
4.2%
10087
 
4.1%
10044
 
4.1%
10044
 
4.1%
10026
 
4.1%
10019
 
4.1%
10013
 
4.1%
10001
 
4.1%
Other values (335) 111447
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136296
55.3%
Decimal Number 52134
 
21.1%
Space Separator 43441
 
17.6%
Dash Punctuation 9925
 
4.0%
Open Punctuation 2291
 
0.9%
Close Punctuation 2288
 
0.9%
Other Punctuation 149
 
0.1%
Uppercase Letter 60
 
< 0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10254
 
7.5%
10087
 
7.4%
10044
 
7.4%
10044
 
7.4%
10026
 
7.4%
10019
 
7.4%
10013
 
7.3%
10001
 
7.3%
10000
 
7.3%
9095
 
6.7%
Other values (296) 36713
26.9%
Uppercase Letter
ValueCountFrequency (%)
B 28
46.7%
K 9
 
15.0%
S 8
 
13.3%
A 5
 
8.3%
O 2
 
3.3%
J 2
 
3.3%
H 2
 
3.3%
M 1
 
1.7%
D 1
 
1.7%
T 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 11235
21.6%
2 6730
12.9%
4 6015
11.5%
3 5198
10.0%
5 4513
8.7%
6 4369
 
8.4%
7 4191
 
8.0%
0 3490
 
6.7%
8 3366
 
6.5%
9 3027
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
b 2
14.3%
k 2
14.3%
s 2
14.3%
a 2
14.3%
p 2
14.3%
e 1
7.1%
m 1
7.1%
i 1
7.1%
y 1
7.1%
Other Punctuation
ValueCountFrequency (%)
, 108
72.5%
. 37
 
24.8%
@ 4
 
2.7%
Space Separator
ValueCountFrequency (%)
43441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9925
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2291
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2288
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136296
55.3%
Common 110240
44.7%
Latin 75
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10254
 
7.5%
10087
 
7.4%
10044
 
7.4%
10044
 
7.4%
10026
 
7.4%
10019
 
7.4%
10013
 
7.3%
10001
 
7.3%
10000
 
7.3%
9095
 
6.7%
Other values (296) 36713
26.9%
Latin
ValueCountFrequency (%)
B 28
37.3%
K 9
 
12.0%
S 8
 
10.7%
A 5
 
6.7%
O 2
 
2.7%
J 2
 
2.7%
b 2
 
2.7%
k 2
 
2.7%
s 2
 
2.7%
a 2
 
2.7%
Other values (11) 13
17.3%
Common
ValueCountFrequency (%)
43441
39.4%
1 11235
 
10.2%
- 9925
 
9.0%
2 6730
 
6.1%
4 6015
 
5.5%
3 5198
 
4.7%
5 4513
 
4.1%
6 4369
 
4.0%
7 4191
 
3.8%
0 3490
 
3.2%
Other values (8) 11133
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136296
55.3%
ASCII 110314
44.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43441
39.4%
1 11235
 
10.2%
- 9925
 
9.0%
2 6730
 
6.1%
4 6015
 
5.5%
3 5198
 
4.7%
5 4513
 
4.1%
6 4369
 
4.0%
7 4191
 
3.8%
0 3490
 
3.2%
Other values (28) 11207
 
10.2%
Hangul
ValueCountFrequency (%)
10254
 
7.5%
10087
 
7.4%
10044
 
7.4%
10044
 
7.4%
10026
 
7.4%
10019
 
7.4%
10013
 
7.3%
10001
 
7.3%
10000
 
7.3%
9095
 
6.7%
Other values (296) 36713
26.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3850
Distinct (%)85.6%
Missing5502
Missing (%)55.0%
Memory size156.2 KiB
2024-05-11T17:30:02.637200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length56
Mean length29.825923
Min length21

Characters and Unicode

Total characters134157
Distinct characters349
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

Unique3350 ?
Unique (%)74.5%

Sample

1st row서울특별시 강북구 도봉로50길 15 (미아동)
2nd row서울특별시 강북구 삼양로 362, 1층 (수유동)
3rd row서울특별시 강북구 덕릉로 27, 1층 (수유동)
4th row서울특별시 강북구 도봉로10가길 15, 1층 (미아동)
5th row서울특별시 강북구 오패산로30길 25, 1층 (미아동)
ValueCountFrequency (%)
서울특별시 4498
 
17.3%
강북구 4496
 
17.2%
수유동 1522
 
5.8%
미아동 1431
 
5.5%
1층 1389
 
5.3%
번동 411
 
1.6%
삼양로 369
 
1.4%
도봉로 318
 
1.2%
한천로 207
 
0.8%
2층 187
 
0.7%
Other values (2163) 11245
43.1%
2024-05-11T17:30:03.264170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21577
 
16.1%
1 6497
 
4.8%
( 5649
 
4.2%
) 5648
 
4.2%
4668
 
3.5%
4661
 
3.5%
4549
 
3.4%
4533
 
3.4%
4527
 
3.4%
4521
 
3.4%
Other values (339) 67327
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75156
56.0%
Decimal Number 22114
 
16.5%
Space Separator 21577
 
16.1%
Open Punctuation 5649
 
4.2%
Close Punctuation 5648
 
4.2%
Other Punctuation 3316
 
2.5%
Dash Punctuation 595
 
0.4%
Uppercase Letter 72
 
0.1%
Math Symbol 16
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4668
 
6.2%
4661
 
6.2%
4549
 
6.1%
4533
 
6.0%
4527
 
6.0%
4521
 
6.0%
4510
 
6.0%
4508
 
6.0%
4498
 
6.0%
4498
 
6.0%
Other values (299) 29683
39.5%
Uppercase Letter
ValueCountFrequency (%)
B 26
36.1%
R 13
18.1%
K 9
 
12.5%
S 8
 
11.1%
A 7
 
9.7%
J 2
 
2.8%
H 2
 
2.8%
O 2
 
2.8%
M 1
 
1.4%
T 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 6497
29.4%
2 2785
12.6%
3 2261
 
10.2%
4 1850
 
8.4%
7 1731
 
7.8%
0 1636
 
7.4%
5 1441
 
6.5%
9 1382
 
6.2%
6 1271
 
5.7%
8 1260
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
a 2
15.4%
p 2
15.4%
k 2
15.4%
s 2
15.4%
b 1
7.7%
e 1
7.7%
m 1
7.7%
i 1
7.7%
y 1
7.7%
Other Punctuation
ValueCountFrequency (%)
, 3185
96.0%
. 129
 
3.9%
? 1
 
< 0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
21577
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5649
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5648
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 595
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75156
56.0%
Common 58915
43.9%
Latin 86
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4668
 
6.2%
4661
 
6.2%
4549
 
6.1%
4533
 
6.0%
4527
 
6.0%
4521
 
6.0%
4510
 
6.0%
4508
 
6.0%
4498
 
6.0%
4498
 
6.0%
Other values (299) 29683
39.5%
Latin
ValueCountFrequency (%)
B 26
30.2%
R 13
15.1%
K 9
 
10.5%
S 8
 
9.3%
A 7
 
8.1%
J 2
 
2.3%
H 2
 
2.3%
a 2
 
2.3%
p 2
 
2.3%
O 2
 
2.3%
Other values (11) 13
15.1%
Common
ValueCountFrequency (%)
21577
36.6%
1 6497
 
11.0%
( 5649
 
9.6%
) 5648
 
9.6%
, 3185
 
5.4%
2 2785
 
4.7%
3 2261
 
3.8%
4 1850
 
3.1%
7 1731
 
2.9%
0 1636
 
2.8%
Other values (9) 6096
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75156
56.0%
ASCII 59000
44.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21577
36.6%
1 6497
 
11.0%
( 5649
 
9.6%
) 5648
 
9.6%
, 3185
 
5.4%
2 2785
 
4.7%
3 2261
 
3.8%
4 1850
 
3.1%
7 1731
 
2.9%
0 1636
 
2.8%
Other values (29) 6181
 
10.5%
Hangul
ValueCountFrequency (%)
4668
 
6.2%
4661
 
6.2%
4549
 
6.1%
4533
 
6.0%
4527
 
6.0%
4521
 
6.0%
4510
 
6.0%
4508
 
6.0%
4498
 
6.0%
4498
 
6.0%
Other values (299) 29683
39.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct215
Distinct (%)4.8%
Missing5558
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean1116.7618
Minimum1000
Maximum1442
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:03.400005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1014
Q11061
median1112
Q31179
95-th percentile1221
Maximum1442
Range442
Interquartile range (IQR)118

Descriptive statistics

Standard deviation67.98045
Coefficient of variation (CV)0.060872828
Kurtosis-1.1249556
Mean1116.7618
Median Absolute Deviation (MAD)58
Skewness0.2349362
Sum4960656
Variance4621.3416
MonotonicityNot monotonic
2024-05-11T17:30:03.529510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1072 166
 
1.7%
1219 161
 
1.6%
1054 159
 
1.6%
1073 78
 
0.8%
1126 71
 
0.7%
1074 64
 
0.6%
1114 63
 
0.6%
1221 62
 
0.6%
1077 60
 
0.6%
1170 60
 
0.6%
Other values (205) 3498
35.0%
(Missing) 5558
55.6%
ValueCountFrequency (%)
1000 21
0.2%
1001 4
 
< 0.1%
1002 43
0.4%
1004 17
 
0.2%
1005 22
0.2%
1006 20
0.2%
1009 13
 
0.1%
1010 18
0.2%
1011 44
0.4%
1012 17
 
0.2%
ValueCountFrequency (%)
1442 1
 
< 0.1%
1378 1
 
< 0.1%
1237 14
0.1%
1236 6
 
0.1%
1234 4
 
< 0.1%
1233 28
0.3%
1232 2
 
< 0.1%
1231 8
 
0.1%
1230 11
 
0.1%
1229 2
 
< 0.1%
Distinct8347
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T17:30:03.802570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length5.2324
Min length1

Characters and Unicode

Total characters52324
Distinct characters1073
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7412 ?
Unique (%)74.1%

Sample

1st row행복한 요리사
2nd row달라스레스토랑
3rd row다진닭발
4th row은영이네부대랑삼겹살이랑
5th row토리아에즈 미아사거리점
ValueCountFrequency (%)
수유점 122
 
1.0%
미아점 59
 
0.5%
전주식당 29
 
0.2%
미아사거리점 28
 
0.2%
실내포장마차 27
 
0.2%
포차 22
 
0.2%
치킨 22
 
0.2%
수유역점 22
 
0.2%
순대국 18
 
0.2%
18
 
0.2%
Other values (8861) 11475
96.9%
2024-05-11T17:30:04.232244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1843
 
3.5%
1355
 
2.6%
1064
 
2.0%
994
 
1.9%
860
 
1.6%
839
 
1.6%
738
 
1.4%
686
 
1.3%
667
 
1.3%
592
 
1.1%
Other values (1063) 42686
81.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47617
91.0%
Space Separator 1843
 
3.5%
Lowercase Letter 738
 
1.4%
Uppercase Letter 657
 
1.3%
Decimal Number 547
 
1.0%
Close Punctuation 352
 
0.7%
Open Punctuation 352
 
0.7%
Other Punctuation 202
 
0.4%
Letter Number 10
 
< 0.1%
Dash Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1355
 
2.8%
1064
 
2.2%
994
 
2.1%
860
 
1.8%
839
 
1.8%
738
 
1.5%
686
 
1.4%
667
 
1.4%
592
 
1.2%
585
 
1.2%
Other values (984) 39237
82.4%
Uppercase Letter
ValueCountFrequency (%)
B 67
 
10.2%
O 64
 
9.7%
A 50
 
7.6%
C 44
 
6.7%
E 37
 
5.6%
S 36
 
5.5%
T 30
 
4.6%
H 29
 
4.4%
K 28
 
4.3%
M 28
 
4.3%
Other values (16) 244
37.1%
Lowercase Letter
ValueCountFrequency (%)
e 105
14.2%
o 75
 
10.2%
a 68
 
9.2%
n 51
 
6.9%
i 47
 
6.4%
t 43
 
5.8%
r 41
 
5.6%
c 37
 
5.0%
l 33
 
4.5%
m 33
 
4.5%
Other values (15) 205
27.8%
Decimal Number
ValueCountFrequency (%)
2 108
19.7%
1 92
16.8%
0 86
15.7%
9 60
11.0%
5 48
8.8%
8 41
 
7.5%
4 37
 
6.8%
3 31
 
5.7%
7 27
 
4.9%
6 17
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 70
34.7%
& 61
30.2%
, 23
 
11.4%
? 20
 
9.9%
' 9
 
4.5%
! 7
 
3.5%
/ 6
 
3.0%
3
 
1.5%
* 2
 
1.0%
: 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 351
99.7%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 351
99.7%
[ 1
 
0.3%
Letter Number
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
Space Separator
ValueCountFrequency (%)
1843
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47596
91.0%
Common 3302
 
6.3%
Latin 1405
 
2.7%
Han 19
 
< 0.1%
Katakana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1355
 
2.8%
1064
 
2.2%
994
 
2.1%
860
 
1.8%
839
 
1.8%
738
 
1.6%
686
 
1.4%
667
 
1.4%
592
 
1.2%
585
 
1.2%
Other values (964) 39216
82.4%
Latin
ValueCountFrequency (%)
e 105
 
7.5%
o 75
 
5.3%
a 68
 
4.8%
B 67
 
4.8%
O 64
 
4.6%
n 51
 
3.6%
A 50
 
3.6%
i 47
 
3.3%
C 44
 
3.1%
t 43
 
3.1%
Other values (43) 791
56.3%
Common
ValueCountFrequency (%)
1843
55.8%
) 351
 
10.6%
( 351
 
10.6%
2 108
 
3.3%
1 92
 
2.8%
0 86
 
2.6%
. 70
 
2.1%
& 61
 
1.8%
9 60
 
1.8%
5 48
 
1.5%
Other values (16) 232
 
7.0%
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%
Katakana
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47593
91.0%
ASCII 4694
 
9.0%
CJK 17
 
< 0.1%
Number Forms 10
 
< 0.1%
None 3
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Katakana 2
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1843
39.3%
) 351
 
7.5%
( 351
 
7.5%
2 108
 
2.3%
e 105
 
2.2%
1 92
 
2.0%
0 86
 
1.8%
o 75
 
1.6%
. 70
 
1.5%
a 68
 
1.4%
Other values (66) 1545
32.9%
Hangul
ValueCountFrequency (%)
1355
 
2.8%
1064
 
2.2%
994
 
2.1%
860
 
1.8%
839
 
1.8%
738
 
1.6%
686
 
1.4%
667
 
1.4%
592
 
1.2%
585
 
1.2%
Other values (962) 39213
82.4%
Number Forms
ValueCountFrequency (%)
8
80.0%
2
 
20.0%
None
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
2
 
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (6) 6
35.3%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Katakana
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6222
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-01-08 00:00:00
Maximum2024-05-09 17:03:10
2024-05-11T17:30:04.372275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:04.507885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7329 
U
2670 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 7329
73.3%
U 2670
 
26.7%
D 1
 
< 0.1%

Length

2024-05-11T17:30:04.622035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:04.699336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7329
73.3%
u 2670
 
26.7%
d 1
 
< 0.1%
Distinct1163
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T17:30:04.790827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:30:04.907111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4545 
분식
1671 
기타
854 
호프/통닭
829 
경양식
507 
Other values (20)
1594 

Length

Max length15
Median length2
Mean length2.7914
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 4545
45.5%
분식 1671
 
16.7%
기타 854
 
8.5%
호프/통닭 829
 
8.3%
경양식 507
 
5.1%
정종/대포집/소주방 366
 
3.7%
중국식 250
 
2.5%
까페 231
 
2.3%
일식 228
 
2.3%
통닭(치킨) 219
 
2.2%
Other values (15) 300
 
3.0%

Length

2024-05-11T17:30:05.038385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4545
45.5%
분식 1671
 
16.7%
기타 854
 
8.5%
호프/통닭 829
 
8.3%
경양식 507
 
5.1%
정종/대포집/소주방 366
 
3.7%
중국식 250
 
2.5%
까페 231
 
2.3%
일식 228
 
2.3%
통닭(치킨 219
 
2.2%
Other values (15) 300
 
3.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3598
Distinct (%)37.8%
Missing493
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean202036.23
Minimum199759.38
Maximum204089.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:05.150332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199759.38
5-th percentile201039.8
Q1201645.53
median202071.31
Q3202425.5
95-th percentile202975.42
Maximum204089.67
Range4330.2918
Interquartile range (IQR)779.97384

Descriptive statistics

Standard deviation610.2016
Coefficient of variation (CV)0.0030202583
Kurtosis0.26417851
Mean202036.23
Median Absolute Deviation (MAD)377.97733
Skewness0.019464231
Sum1.9207584 × 109
Variance372345.99
MonotonicityNot monotonic
2024-05-11T17:30:05.275741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203093.488566 37
 
0.4%
202128.41823526 29
 
0.3%
202155.401317068 28
 
0.3%
202066.032206268 28
 
0.3%
202536.541879297 23
 
0.2%
202071.310518981 21
 
0.2%
201962.440539943 21
 
0.2%
202625.646264572 20
 
0.2%
202158.404849077 20
 
0.2%
201956.180985499 19
 
0.2%
Other values (3588) 9261
92.6%
(Missing) 493
 
4.9%
ValueCountFrequency (%)
199759.381379394 1
 
< 0.1%
199973.0134989 3
< 0.1%
200020.571943402 2
< 0.1%
200148.731152578 1
 
< 0.1%
200249.394326119 2
< 0.1%
200268.349747275 1
 
< 0.1%
200277.166817564 1
 
< 0.1%
200293.660373936 3
< 0.1%
200308.506805323 1
 
< 0.1%
200332.489971482 2
< 0.1%
ValueCountFrequency (%)
204089.673173372 1
 
< 0.1%
204083.177112537 11
0.1%
203999.650902849 2
 
< 0.1%
203982.734025835 1
 
< 0.1%
203981.35 5
0.1%
203975.790220599 1
 
< 0.1%
203960.532350205 1
 
< 0.1%
203932.991517795 7
0.1%
203920.882629874 3
 
< 0.1%
203895.660018622 2
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3598
Distinct (%)37.8%
Missing493
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean458833.81
Minimum451188.65
Maximum463555.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:05.424877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451188.65
5-th percentile456688.2
Q1457717.29
median459054.65
Q3459814.56
95-th percentile460649.25
Maximum463555.21
Range12366.56
Interquartile range (IQR)2097.2753

Descriptive statistics

Standard deviation1311.9935
Coefficient of variation (CV)0.002859409
Kurtosis-0.37031795
Mean458833.81
Median Absolute Deviation (MAD)909.70112
Skewness0.011104013
Sum4.362133 × 109
Variance1721327
MonotonicityNot monotonic
2024-05-11T17:30:05.559747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457274.600204 37
 
0.4%
459616.005143063 29
 
0.3%
459411.940883021 28
 
0.3%
459574.807943486 28
 
0.3%
456758.813670659 23
 
0.2%
459514.711297656 21
 
0.2%
460122.255687427 21
 
0.2%
456875.973976242 20
 
0.2%
459633.960977278 20
 
0.2%
458714.365820521 19
 
0.2%
Other values (3588) 9261
92.6%
(Missing) 493
 
4.9%
ValueCountFrequency (%)
451188.653527441 1
 
< 0.1%
456377.651999255 6
0.1%
456395.665910768 4
< 0.1%
456402.681578677 2
 
< 0.1%
456417.052514595 1
 
< 0.1%
456419.111212319 3
< 0.1%
456422.95319709 1
 
< 0.1%
456434.500687631 1
 
< 0.1%
456442.951197483 1
 
< 0.1%
456449.379330053 2
 
< 0.1%
ValueCountFrequency (%)
463555.213506333 2
< 0.1%
463314.308416652 1
< 0.1%
463273.034935381 2
< 0.1%
463271.784511597 1
< 0.1%
463264.336677193 1
< 0.1%
463240.16478942 2
< 0.1%
463229.806464406 1
< 0.1%
463204.601384724 1
< 0.1%
463204.449254807 1
< 0.1%
463160.587334505 1
< 0.1%

위생업태명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3984 
분식
1600 
<NA>
1398 
호프/통닭
699 
경양식
473 
Other values (21)
1846 

Length

Max length15
Median length2
Mean length2.9823
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 3984
39.8%
분식 1600
16.0%
<NA> 1398
 
14.0%
호프/통닭 699
 
7.0%
경양식 473
 
4.7%
기타 416
 
4.2%
정종/대포집/소주방 345
 
3.5%
중국식 219
 
2.2%
까페 217
 
2.2%
통닭(치킨) 196
 
2.0%
Other values (16) 453
 
4.5%

Length

2024-05-11T17:30:05.697946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3984
39.8%
분식 1600
16.0%
na 1398
 
14.0%
호프/통닭 699
 
7.0%
경양식 473
 
4.7%
기타 416
 
4.2%
정종/대포집/소주방 345
 
3.5%
중국식 219
 
2.2%
까페 217
 
2.2%
통닭(치킨 196
 
2.0%
Other values (16) 453
 
4.5%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct13
Distinct (%)0.2%
Missing4041
Missing (%)40.4%
Infinite0
Infinite (%)0.0%
Mean0.27538178
Minimum0
Maximum93
Zeros4755
Zeros (%)47.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:05.793651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3761442
Coefficient of variation (CV)4.9972232
Kurtosis3467.1874
Mean0.27538178
Median Absolute Deviation (MAD)0
Skewness52.227884
Sum1641
Variance1.8937728
MonotonicityNot monotonic
2024-05-11T17:30:05.877838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 4755
47.5%
1 983
 
9.8%
2 165
 
1.7%
3 35
 
0.4%
4 11
 
0.1%
8 2
 
< 0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
10 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 4041
40.4%
ValueCountFrequency (%)
0 4755
47.5%
1 983
 
9.8%
2 165
 
1.7%
3 35
 
0.4%
4 11
 
0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
12 1
 
< 0.1%
10 1
 
< 0.1%
8 2
 
< 0.1%
7 1
 
< 0.1%
5 2
 
< 0.1%
4 11
 
0.1%
3 35
0.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.2%
Missing3946
Missing (%)39.5%
Infinite0
Infinite (%)0.0%
Mean0.54063429
Minimum0
Maximum32
Zeros3625
Zeros (%)36.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:05.966552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum32
Range32
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.94272664
Coefficient of variation (CV)1.7437418
Kurtosis250.71056
Mean0.54063429
Median Absolute Deviation (MAD)0
Skewness9.7684399
Sum3273
Variance0.88873351
MonotonicityNot monotonic
2024-05-11T17:30:06.054336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 3625
36.2%
1 1814
18.1%
2 518
 
5.2%
3 66
 
0.7%
4 15
 
0.1%
6 4
 
< 0.1%
8 2
 
< 0.1%
5 2
 
< 0.1%
10 2
 
< 0.1%
12 1
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 3946
39.5%
ValueCountFrequency (%)
0 3625
36.2%
1 1814
18.1%
2 518
 
5.2%
3 66
 
0.7%
4 15
 
0.1%
5 2
 
< 0.1%
6 4
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
32 1
 
< 0.1%
20 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
11 1
 
< 0.1%
10 2
< 0.1%
8 2
< 0.1%
7 1
 
< 0.1%
6 4
< 0.1%
5 2
< 0.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4966 
주택가주변
3342 
기타
1241 
유흥업소밀집지역
 
324
아파트지역
 
73
Other values (3)
 
54

Length

Max length8
Median length7
Mean length4.2429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4966
49.7%
주택가주변 3342
33.4%
기타 1241
 
12.4%
유흥업소밀집지역 324
 
3.2%
아파트지역 73
 
0.7%
학교정화(상대) 32
 
0.3%
결혼예식장주변 16
 
0.2%
학교정화(절대) 6
 
0.1%

Length

2024-05-11T17:30:06.164224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:06.265399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4966
49.7%
주택가주변 3342
33.4%
기타 1241
 
12.4%
유흥업소밀집지역 324
 
3.2%
아파트지역 73
 
0.7%
학교정화(상대 32
 
0.3%
결혼예식장주변 16
 
0.2%
학교정화(절대 6
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5004 
기타
3183 
지도
1046 
자율
575 
 
136
Other values (3)
 
56

Length

Max length4
Median length4
Mean length2.9844
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5004
50.0%
기타 3183
31.8%
지도 1046
 
10.5%
자율 575
 
5.8%
136
 
1.4%
28
 
0.3%
관리 23
 
0.2%
우수 5
 
0.1%

Length

2024-05-11T17:30:06.393076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:06.490668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5004
50.0%
기타 3183
31.8%
지도 1046
 
10.5%
자율 575
 
5.8%
136
 
1.4%
28
 
0.3%
관리 23
 
0.2%
우수 5
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
6562 
<NA>
3402 
상수도(음용)지하수(주방용)겸용
 
25
간이상수도
 
6
지하수전용
 
5

Length

Max length17
Median length5
Mean length4.6898
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 6562
65.6%
<NA> 3402
34.0%
상수도(음용)지하수(주방용)겸용 25
 
0.2%
간이상수도 6
 
0.1%
지하수전용 5
 
0.1%

Length

2024-05-11T17:30:06.613083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:06.706805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 6562
65.6%
na 3402
34.0%
상수도(음용)지하수(주방용)겸용 25
 
0.2%
간이상수도 6
 
0.1%
지하수전용 5
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9675 
0
 
325

Length

Max length4
Median length4
Mean length3.9025
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> 9675
96.8%
0 325
 
3.2%

Length

2024-05-11T17:30:06.815907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:06.912127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9675
96.8%
0 325
 
3.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.003628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:07.101027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.211766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:07.294552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.378832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:07.465258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.562227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:07.645568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

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>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.733057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:07.818394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9674 
0
 
326

Length

Max length4
Median length4
Mean length3.9022
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> 9674
96.7%
0 326
 
3.3%

Length

2024-05-11T17:30:07.916961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:30:08.007595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9674
96.7%
0 326
 
3.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1398
Missing (%)14.0%
Memory size97.7 KiB
False
8573 
True
 
29
(Missing)
1398 
ValueCountFrequency (%)
False 8573
85.7%
True 29
 
0.3%
(Missing) 1398
 
14.0%
2024-05-11T17:30:08.080072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct4044
Distinct (%)47.0%
Missing1398
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean50.481616
Minimum0
Maximum3417.21
Zeros543
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T17:30:08.179655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q121.4925
median30.255
Q357.8075
95-th percentile134.217
Maximum3417.21
Range3417.21
Interquartile range (IQR)36.315

Descriptive statistics

Standard deviation91.282297
Coefficient of variation (CV)1.8082285
Kurtosis445.93567
Mean50.481616
Median Absolute Deviation (MAD)12.745
Skewness16.75906
Sum434242.86
Variance8332.4577
MonotonicityNot monotonic
2024-05-11T17:30:08.559050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 543
 
5.4%
26.4 70
 
0.7%
33.0 69
 
0.7%
24.0 63
 
0.6%
30.0 53
 
0.5%
23.1 42
 
0.4%
20.0 38
 
0.4%
19.8 38
 
0.4%
27.0 38
 
0.4%
23.0 37
 
0.4%
Other values (4034) 7611
76.1%
(Missing) 1398
 
14.0%
ValueCountFrequency (%)
0.0 543
5.4%
3.24 1
 
< 0.1%
3.48 1
 
< 0.1%
4.12 1
 
< 0.1%
4.29 1
 
< 0.1%
4.48 1
 
< 0.1%
4.5 1
 
< 0.1%
4.8 1
 
< 0.1%
4.86 1
 
< 0.1%
5.52 1
 
< 0.1%
ValueCountFrequency (%)
3417.21 1
< 0.1%
2863.38 1
< 0.1%
2166.54 1
< 0.1%
1982.23 1
< 0.1%
1968.02 1
< 0.1%
1928.3 1
< 0.1%
1570.14 1
< 0.1%
1182.35 1
< 0.1%
1168.6 1
< 0.1%
1159.53 1
< 0.1%
Distinct5
Distinct (%)83.3%
Missing9994
Missing (%)99.9%
Memory size156.2 KiB
2024-05-11T17:30:08.670415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length1
Mean length1.8333333
Min length1

Characters and Unicode

Total characters11
Distinct characters7
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row]
2nd row1
3rd row
4th row1022
5th row
ValueCountFrequency (%)
2
50.0%
1 1
25.0%
1022 1
25.0%
2024-05-11T17:30:08.859901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
18.2%
1 2
18.2%
2 2
18.2%
- 2
18.2%
] 1
9.1%
0 1
9.1%
= 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
45.5%
Space Separator 2
 
18.2%
Dash Punctuation 2
 
18.2%
Close Punctuation 1
 
9.1%
Math Symbol 1
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
0 1
20.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2
18.2%
1 2
18.2%
2 2
18.2%
- 2
18.2%
] 1
9.1%
0 1
9.1%
= 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
18.2%
1 2
18.2%
2 2
18.2%
- 2
18.2%
] 1
9.1%
0 1
9.1%
= 1
9.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1287530800003080000-101-2013-0021220130911<NA>3폐업2폐업20140527<NA><NA><NA><NA>19.72142807서울특별시 강북구 미아동 121-38번지서울특별시 강북구 도봉로50길 15 (미아동)1157행복한 요리사2013-09-30 19:32:48I2018-08-31 23:59:59.0분식202357.22753458145.010247분식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N19.72<NA><NA><NA>
95930800003080000-101-1986-0521619860812<NA>3폐업2폐업19890120<NA><NA><NA>020000000040.32142827서울특별시 강북구 미아동 688-5번지<NA><NA>달라스레스토랑2001-10-17 00:00:00I2018-08-31 23:59:59.0경양식201762.419935457441.24407경양식12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.32<NA><NA><NA>
1593430800003080000-101-2023-002162023-08-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.96142-870서울특별시 강북구 수유동 402-8서울특별시 강북구 삼양로 362, 1층 (수유동)1082다진닭발2023-08-23 11:36:37I2022-12-07 22:05:00.0한식201476.627105459271.440379<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1511330800003080000-101-2021-000432021-02-23<NA>3폐업2폐업2023-03-22<NA><NA><NA><NA>33.00142-885서울특별시 강북구 수유동 451-172서울특별시 강북구 덕릉로 27, 1층 (수유동)1094은영이네부대랑삼겹살이랑2023-03-22 08:52:12U2022-12-02 22:04:00.0한식201387.203165459100.595625<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1555630800003080000-101-2022-001482022-06-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.50142-804서울특별시 강북구 미아동 55-20서울특별시 강북구 도봉로10가길 15, 1층 (미아동)1219토리아에즈 미아사거리점2023-07-03 13:32:51U2022-12-07 00:05:00.0기타202697.718009456737.851762<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1552330800003080000-101-2022-0011520220512<NA>1영업/정상1영업<NA><NA><NA><NA><NA>81.00142800서울특별시 강북구 미아동 83-2서울특별시 강북구 오패산로30길 25, 1층 (미아동)1233일번지 통닭2022-05-12 10:38:38I2021-12-04 23:04:00.0호프/통닭203001.034778456887.862437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9430800003080000-101-1977-0103719771107<NA>3폐업2폐업19970509<NA><NA><NA>02 994058220.10142876서울특별시 강북구 수유동 173-19번지<NA><NA>골목집2001-09-26 00:00:00I2018-08-31 23:59:59.0한식202475.346618459892.093585한식01유흥업소밀집지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N20.1<NA><NA><NA>
1179430800003080000-101-2010-0008820100507<NA>3폐업2폐업20180207<NA><NA><NA>02 9080111670.83142864서울특별시 강북구 번동 418-1번지 (도봉로 356)(지상 11층) 1101호서울특별시 강북구 도봉로 358, 1101호 (번동,(도봉로 356)(지상 11층))1063라 파밀리아2018-02-07 10:40:29I2018-08-31 23:59:59.0뷔페식202343.387489459654.425207뷔페식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N670.83<NA><NA><NA>
853030800003080000-101-2002-0027820020524<NA>3폐업2폐업20191004<NA><NA><NA>02 987565125.80142874서울특별시 강북구 수유동 50-16번지 1층서울특별시 강북구 삼양로80나길 74, 1층 (수유동)1114에스에이치(SH)푸드2019-10-04 09:21:39U2019-10-06 02:40:00.0호프/통닭201794.984116459068.630775호프/통닭00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.8<NA><NA><NA>
360230800003080000-101-1994-0325819941123<NA>3폐업2폐업20081208<NA><NA><NA>02 9818075117.37142805서울특별시 강북구 미아동 484-4번지<NA><NA>오 바(O BAR)2007-03-08 00:00:00I2018-08-31 23:59:59.0호프/통닭202477.627412456690.622279호프/통닭00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N117.37<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
514230800003080000-101-1997-0258319970605<NA>3폐업2폐업20050110<NA><NA><NA>02 9076800167.31142867서울특별시 강북구 번동 449-1번지<NA><NA>대포항횟집2000-03-15 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방202032.757632459259.443979정종/대포집/소주방00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N167.31<NA><NA><NA>
120430800003080000-101-1987-0515619870619<NA>3폐업2폐업19940324<NA><NA><NA>020980679050.44142803서울특별시 강북구 미아동 189-5번지<NA><NA>레몬트리2001-10-17 00:00:00I2018-08-31 23:59:59.0경양식202092.262517458857.879708경양식21주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.44<NA><NA><NA>
116430800003080000-101-1987-0436319871112<NA>3폐업2폐업19970509<NA><NA><NA>020983791318.56142819서울특별시 강북구 미아동 1345-1번지<NA><NA>장터국수2001-10-17 00:00:00I2018-08-31 23:59:59.0분식201595.001552457491.283644분식02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N18.56<NA><NA><NA>
1336830800003080000-101-2015-0011120150604<NA>3폐업2폐업20170515<NA><NA><NA><NA><NA>142878서울특별시 강북구 수유동 192-33번지서울특별시 강북구 도봉로87길 32-6, 1층 (수유동)1072신세계2017-05-15 13:58:27I2018-08-31 23:59:59.0한식202078.958516459649.759047한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1330230800003080000-101-2015-0004520150324<NA>3폐업2폐업20170515<NA><NA><NA><NA>16.26142815서울특별시 강북구 미아동 329-32번지서울특별시 강북구 도봉로23길 49 (미아동)1179차군 떡볶이 치킨2017-05-15 15:34:31I2018-08-31 23:59:59.0통닭(치킨)202235.336066457356.104826통닭(치킨)<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.26<NA><NA><NA>
1097330800003080000-101-2007-002872007-11-08<NA>3폐업2폐업2023-08-04<NA><NA><NA><NA>24.00142-811서울특별시 강북구 미아동 211-38 (지상1층)서울특별시 강북구 도봉로53길 27 (미아동,(지상1층))1126옛날호프2023-08-04 14:54:56U2022-12-08 00:06:00.0호프/통닭202071.348092458240.266582<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1316030800003080000-101-2014-0019720140915<NA>3폐업2폐업20150518<NA><NA><NA><NA><NA>142805서울특별시 강북구 미아동 469-42번지서울특별시 강북구 도봉로13길 55, 1층 (미아동)1206라온푸드2014-09-15 11:36:14I2018-08-31 23:59:59.0한식202340.696645456961.129368한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
213430800003080000-101-1990-0734519900624<NA>3폐업2폐업20170616<NA><NA><NA>02 9926993106.47142878서울특별시 강북구 수유동 191-78번지서울특별시 강북구 한천로139길 39 (수유동)1074봉숭아학당2017-06-16 13:39:08I2018-08-31 23:59:59.0호프/통닭202157.645758459585.806247호프/통닭00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N106.47<NA><NA><NA>
1455130800003080000-101-2019-0015820190619<NA>3폐업2폐업20211203<NA><NA><NA><NA>56.20142867서울특별시 강북구 번동 445-3 금성약국서울특별시 강북구 오패산로 405-1, 금성약국 1층 (번동)1065수유회관2021-12-03 16:47:19U2021-12-07 02:40:00.0기타202291.073793459402.71983기타00<NA><NA>상수도전용00000<NA>00N56.2<NA><NA><NA>
924830800003080000-101-2003-0034820030819<NA>3폐업2폐업20081024<NA><NA><NA><NA>77.03142877서울특별시 강북구 수유동 219-2번지<NA><NA>홍천칼국수2003-08-19 00:00:00I2018-08-31 23:59:59.0분식201782.904277459968.040246분식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N77.03<NA><NA><NA>