Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells100331
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical19
Text7
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18667/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (60.9%)Imbalance
총인원 is highly imbalanced (73.7%)Imbalance
본사종업원수 is highly imbalanced (73.7%)Imbalance
공장사무직종업원수 is highly imbalanced (73.7%)Imbalance
공장판매직종업원수 is highly imbalanced (73.7%)Imbalance
공장생산직종업원수 is highly imbalanced (73.7%)Imbalance
보증액 is highly imbalanced (73.7%)Imbalance
월세액 is highly imbalanced (73.7%)Imbalance
다중이용업소여부 is highly imbalanced (84.8%)Imbalance
전통업소주된음식 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2854 (28.5%) 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 2788 (27.9%) missing valuesMissing
소재지면적 has 267 (2.7%) missing valuesMissing
도로명주소 has 4417 (44.2%) missing valuesMissing
도로명우편번호 has 4491 (44.9%) missing valuesMissing
좌표정보(X) has 602 (6.0%) missing valuesMissing
좌표정보(Y) has 602 (6.0%) missing valuesMissing
남성종사자수 has 5272 (52.7%) missing valuesMissing
여성종사자수 has 5058 (50.6%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1990 (19.9%) missing valuesMissing
시설총규모 has 1990 (19.9%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
여성종사자수 is highly skewed (γ1 = 24.03488914)Skewed
시설총규모 is highly skewed (γ1 = 88.08899919)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
전통업소지정번호 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 2987 (29.9%) zerosZeros
여성종사자수 has 1861 (18.6%) zerosZeros
시설총규모 has 270 (2.7%) zerosZeros

Reproduction

Analysis started2024-05-11 05:35:44.483625
Analysis finished2024-05-11 05:35:48.579557
Duration4.1 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
3150000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 10000
100.0%

Length

2024-05-11T14:35:48.672283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:48.809873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:35:49.071229image/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 row3150000-101-2005-00426
2nd row3150000-101-2008-00102
3rd row3150000-101-2023-00451
4th row3150000-101-2003-00694
5th row3150000-101-2003-00287
ValueCountFrequency (%)
3150000-101-2005-00426 1
 
< 0.1%
3150000-101-2001-09810 1
 
< 0.1%
3150000-101-2001-09737 1
 
< 0.1%
3150000-101-1995-01263 1
 
< 0.1%
3150000-101-2006-00425 1
 
< 0.1%
3150000-101-2000-09315 1
 
< 0.1%
3150000-101-1995-01296 1
 
< 0.1%
3150000-101-1996-04631 1
 
< 0.1%
3150000-101-1993-06309 1
 
< 0.1%
3150000-101-2000-09283 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T14:35:49.608965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80051
36.4%
1 40659
18.5%
- 30000
 
13.6%
3 15197
 
6.9%
5 14077
 
6.4%
2 13316
 
6.1%
9 9832
 
4.5%
4 4596
 
2.1%
8 4271
 
1.9%
6 4019
 
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 80051
42.1%
1 40659
21.4%
3 15197
 
8.0%
5 14077
 
7.4%
2 13316
 
7.0%
9 9832
 
5.2%
4 4596
 
2.4%
8 4271
 
2.2%
6 4019
 
2.1%
7 3982
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80051
36.4%
1 40659
18.5%
- 30000
 
13.6%
3 15197
 
6.9%
5 14077
 
6.4%
2 13316
 
6.1%
9 9832
 
4.5%
4 4596
 
2.1%
8 4271
 
1.9%
6 4019
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80051
36.4%
1 40659
18.5%
- 30000
 
13.6%
3 15197
 
6.9%
5 14077
 
6.4%
2 13316
 
6.1%
9 9832
 
4.5%
4 4596
 
2.1%
8 4271
 
1.9%
6 4019
 
1.8%
Distinct6071
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:35:49.855047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:50.327565image/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
7146 
1
2854 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7146
71.5%
1 2854
 
28.5%

Length

2024-05-11T14:35:50.572714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:50.793253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7146
71.5%
1 2854
 
28.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7146 
영업/정상
2854 

Length

Max length5
Median length2
Mean length2.8562
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7146
71.5%
영업/정상 2854
 
28.5%

Length

2024-05-11T14:35:50.979449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:51.133836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7146
71.5%
영업/정상 2854
 
28.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7146 
1
2854 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7146
71.5%
1 2854
 
28.5%

Length

2024-05-11T14:35:51.280902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:51.428048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7146
71.5%
1 2854
 
28.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7146 
영업
2854 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7146
71.5%
영업 2854
 
28.5%

Length

2024-05-11T14:35:51.593777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:35:51.743870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7146
71.5%
영업 2854
 
28.5%

폐업일자
Date

MISSING 

Distinct4283
Distinct (%)59.9%
Missing2854
Missing (%)28.5%
Memory size156.2 KiB
Minimum1976-09-13 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:35:51.900660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:35:52.116701image/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 

Distinct6701
Distinct (%)92.9%
Missing2788
Missing (%)27.9%
Memory size156.2 KiB
2024-05-11T14:35:52.540920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8535774
Min length2

Characters and Unicode

Total characters71064
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

Unique6482 ?
Unique (%)89.9%

Sample

1st row26425990
2nd row0226519982
3rd row0226651723
4th row0226661662
5th row02 00000
ValueCountFrequency (%)
02 2396
 
25.3%
0200000000 54
 
0.6%
00000 42
 
0.4%
0 23
 
0.2%
6905151 7
 
0.1%
6699000 6
 
0.1%
032 4
 
< 0.1%
031 4
 
< 0.1%
6614588 4
 
< 0.1%
0226628942 3
 
< 0.1%
Other values (6713) 6934
73.2%
2024-05-11T14:35:53.143348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14022
19.7%
0 13271
18.7%
6 12593
17.7%
9 4922
 
6.9%
3 4789
 
6.7%
5 4339
 
6.1%
8 3862
 
5.4%
4 3738
 
5.3%
1 3628
 
5.1%
7 3359
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68523
96.4%
Space Separator 2541
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14022
20.5%
0 13271
19.4%
6 12593
18.4%
9 4922
 
7.2%
3 4789
 
7.0%
5 4339
 
6.3%
8 3862
 
5.6%
4 3738
 
5.5%
1 3628
 
5.3%
7 3359
 
4.9%
Space Separator
ValueCountFrequency (%)
2541
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71064
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14022
19.7%
0 13271
18.7%
6 12593
17.7%
9 4922
 
6.9%
3 4789
 
6.7%
5 4339
 
6.1%
8 3862
 
5.4%
4 3738
 
5.3%
1 3628
 
5.1%
7 3359
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71064
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14022
19.7%
0 13271
18.7%
6 12593
17.7%
9 4922
 
6.9%
3 4789
 
6.7%
5 4339
 
6.1%
8 3862
 
5.4%
4 3738
 
5.3%
1 3628
 
5.1%
7 3359
 
4.7%

소재지면적
Text

MISSING 

Distinct4983
Distinct (%)51.2%
Missing267
Missing (%)2.7%
Memory size156.2 KiB
2024-05-11T14:35:53.693869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.147642
Min length3

Characters and Unicode

Total characters50102
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

Unique3258 ?
Unique (%)33.5%

Sample

1st row88.88
2nd row39.64
3rd row401.70
4th row95.37
5th row50.36
ValueCountFrequency (%)
33.00 157
 
1.6%
30.00 78
 
0.8%
26.40 58
 
0.6%
40.00 55
 
0.6%
26.00 48
 
0.5%
25.00 46
 
0.5%
66.00 45
 
0.5%
20.00 42
 
0.4%
23.10 38
 
0.4%
24.00 32
 
0.3%
Other values (4973) 9134
93.8%
2024-05-11T14:35:54.393591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9733
19.4%
0 6695
13.4%
2 5340
10.7%
3 4245
8.5%
1 4195
8.4%
4 3922
7.8%
6 3553
 
7.1%
5 3531
 
7.0%
8 3320
 
6.6%
9 2802
 
5.6%
Other values (2) 2766
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40360
80.6%
Other Punctuation 9742
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6695
16.6%
2 5340
13.2%
3 4245
10.5%
1 4195
10.4%
4 3922
9.7%
6 3553
8.8%
5 3531
8.7%
8 3320
8.2%
9 2802
6.9%
7 2757
6.8%
Other Punctuation
ValueCountFrequency (%)
. 9733
99.9%
, 9
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9733
19.4%
0 6695
13.4%
2 5340
10.7%
3 4245
8.5%
1 4195
8.4%
4 3922
7.8%
6 3553
 
7.1%
5 3531
 
7.0%
8 3320
 
6.6%
9 2802
 
5.6%
Other values (2) 2766
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9733
19.4%
0 6695
13.4%
2 5340
10.7%
3 4245
8.5%
1 4195
8.4%
4 3922
7.8%
6 3553
 
7.1%
5 3531
 
7.0%
8 3320
 
6.6%
9 2802
 
5.6%
Other values (2) 2766
 
5.5%
Distinct243
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:35:54.994493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1357
Min length6

Characters and Unicode

Total characters61357
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

Unique27 ?
Unique (%)0.3%

Sample

1st row157836
2nd row157836
3rd row157-030
4th row157812
5th row157857
ValueCountFrequency (%)
157210 762
 
7.6%
157-210 456
 
4.6%
157930 382
 
3.8%
157928 349
 
3.5%
157897 245
 
2.5%
157910 237
 
2.4%
157280 234
 
2.3%
157884 228
 
2.3%
157812 222
 
2.2%
157916 212
 
2.1%
Other values (233) 6673
66.7%
2024-05-11T14:35:55.827099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13498
22.0%
5 11358
18.5%
7 11349
18.5%
8 7358
12.0%
0 4296
 
7.0%
9 3875
 
6.3%
2 3546
 
5.8%
3 1761
 
2.9%
4 1571
 
2.6%
6 1388
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60000
97.8%
Dash Punctuation 1357
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13498
22.5%
5 11358
18.9%
7 11349
18.9%
8 7358
12.3%
0 4296
 
7.2%
9 3875
 
6.5%
2 3546
 
5.9%
3 1761
 
2.9%
4 1571
 
2.6%
6 1388
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1357
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61357
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13498
22.0%
5 11358
18.5%
7 11349
18.5%
8 7358
12.0%
0 4296
 
7.0%
9 3875
 
6.3%
2 3546
 
5.8%
3 1761
 
2.9%
4 1571
 
2.6%
6 1388
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61357
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13498
22.0%
5 11358
18.5%
7 11349
18.5%
8 7358
12.0%
0 4296
 
7.0%
9 3875
 
6.3%
2 3546
 
5.8%
3 1761
 
2.9%
4 1571
 
2.6%
6 1388
 
2.3%
Distinct8240
Distinct (%)82.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:35:56.303643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length59
Mean length28.9144
Min length16

Characters and Unicode

Total characters289144
Distinct characters452
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7126 ?
Unique (%)71.3%

Sample

1st row서울특별시 강서구 등촌동 510-14번지
2nd row서울특별시 강서구 등촌동 366-99 (지상 1층)
3rd row서울특별시 강서구 등촌동 14-7 가양역 데시앙플렉스 지식산업센터 102~110호
4th row서울특별시 강서구 공항동 60-25번지
5th row서울특별시 강서구 방화동 830-3번지 샤르망 (지상 2층) 205호
ValueCountFrequency (%)
서울특별시 10000
18.4%
강서구 10000
18.4%
화곡동 4311
 
7.9%
1층 3391
 
6.2%
지상 2719
 
5.0%
방화동 1334
 
2.4%
마곡동 1218
 
2.2%
등촌동 1212
 
2.2%
2층 607
 
1.1%
내발산동 543
 
1.0%
Other values (6933) 19143
35.1%
2024-05-11T14:35:57.170424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51353
 
17.8%
20201
 
7.0%
1 15660
 
5.4%
11140
 
3.9%
10684
 
3.7%
10189
 
3.5%
10186
 
3.5%
10060
 
3.5%
10009
 
3.5%
10002
 
3.5%
Other values (442) 129660
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159642
55.2%
Decimal Number 60069
 
20.8%
Space Separator 51353
 
17.8%
Dash Punctuation 9709
 
3.4%
Open Punctuation 3515
 
1.2%
Close Punctuation 3515
 
1.2%
Uppercase Letter 520
 
0.2%
Other Punctuation 413
 
0.1%
Math Symbol 295
 
0.1%
Letter Number 92
 
< 0.1%
Other values (2) 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20201
12.7%
11140
 
7.0%
10684
 
6.7%
10189
 
6.4%
10186
 
6.4%
10060
 
6.3%
10009
 
6.3%
10002
 
6.3%
10000
 
6.3%
6877
 
4.3%
Other values (377) 50294
31.5%
Uppercase Letter
ValueCountFrequency (%)
B 150
28.8%
A 148
28.5%
C 37
 
7.1%
N 34
 
6.5%
E 18
 
3.5%
D 15
 
2.9%
M 15
 
2.9%
S 13
 
2.5%
H 12
 
2.3%
I 11
 
2.1%
Other values (17) 67
12.9%
Lowercase Letter
ValueCountFrequency (%)
a 4
20.0%
e 3
15.0%
c 2
10.0%
t 2
10.0%
p 2
10.0%
y 1
 
5.0%
d 1
 
5.0%
b 1
 
5.0%
o 1
 
5.0%
m 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
1 15660
26.1%
2 6873
11.4%
0 6303
10.5%
7 5449
 
9.1%
3 4854
 
8.1%
6 4712
 
7.8%
5 4176
 
7.0%
4 4133
 
6.9%
9 4071
 
6.8%
8 3838
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 381
92.3%
. 25
 
6.1%
/ 4
 
1.0%
? 1
 
0.2%
: 1
 
0.2%
@ 1
 
0.2%
Letter Number
ValueCountFrequency (%)
61
66.3%
29
31.5%
2
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 3514
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
51353
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9709
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3515
100.0%
Math Symbol
ValueCountFrequency (%)
~ 295
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159642
55.2%
Common 128870
44.6%
Latin 631
 
0.2%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20201
12.7%
11140
 
7.0%
10684
 
6.7%
10189
 
6.4%
10186
 
6.4%
10060
 
6.3%
10009
 
6.3%
10002
 
6.3%
10000
 
6.3%
6877
 
4.3%
Other values (377) 50294
31.5%
Latin
ValueCountFrequency (%)
B 150
23.8%
A 148
23.5%
61
9.7%
C 37
 
5.9%
N 34
 
5.4%
29
 
4.6%
E 18
 
2.9%
D 15
 
2.4%
M 15
 
2.4%
S 13
 
2.1%
Other values (31) 111
17.6%
Common
ValueCountFrequency (%)
51353
39.8%
1 15660
 
12.2%
- 9709
 
7.5%
2 6873
 
5.3%
0 6303
 
4.9%
7 5449
 
4.2%
3 4854
 
3.8%
6 4712
 
3.7%
5 4176
 
3.2%
4 4133
 
3.2%
Other values (13) 15648
 
12.1%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159641
55.2%
ASCII 129409
44.8%
Number Forms 92
 
< 0.1%
Compat Jamo 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51353
39.7%
1 15660
 
12.1%
- 9709
 
7.5%
2 6873
 
5.3%
0 6303
 
4.9%
7 5449
 
4.2%
3 4854
 
3.8%
6 4712
 
3.6%
5 4176
 
3.2%
4 4133
 
3.2%
Other values (51) 16187
 
12.5%
Hangul
ValueCountFrequency (%)
20201
12.7%
11140
 
7.0%
10684
 
6.7%
10189
 
6.4%
10186
 
6.4%
10060
 
6.3%
10009
 
6.3%
10002
 
6.3%
10000
 
6.3%
6877
 
4.3%
Other values (376) 50293
31.5%
Number Forms
ValueCountFrequency (%)
61
66.3%
29
31.5%
2
 
2.2%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명주소
Text

MISSING 

Distinct5058
Distinct (%)90.6%
Missing4417
Missing (%)44.2%
Memory size156.2 KiB
2024-05-11T14:35:57.621406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length61
Mean length37.237328
Min length22

Characters and Unicode

Total characters207896
Distinct characters442
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4636 ?
Unique (%)83.0%

Sample

1st row서울특별시 강서구 등촌로51나길 5-17, 1층 (등촌동, 2동)
2nd row서울특별시 강서구 양천로 424, 가양역 데시앙플렉스 지식산업센터 1층 102~110호 (등촌동)
3rd row서울특별시 강서구 송정로 45-1 (공항동)
4th row서울특별시 강서구 방화대로47가길 7, 2층 205호 (방화동, 3동 샤르망)
5th row서울특별시 강서구 하늘길 38, 지하 1~2층 (방화동, 2동 김포공항스카이파크롯데몰)
ValueCountFrequency (%)
서울특별시 5583
 
13.6%
강서구 5583
 
13.6%
1층 3777
 
9.2%
화곡동 1918
 
4.7%
마곡동 1160
 
2.8%
1동 818
 
2.0%
2층 676
 
1.6%
등촌동 614
 
1.5%
방화동 567
 
1.4%
공항대로 398
 
1.0%
Other values (2848) 19882
48.5%
2024-05-11T14:35:58.378936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35405
 
17.0%
1 12553
 
6.0%
12424
 
6.0%
8391
 
4.0%
, 8073
 
3.9%
6749
 
3.2%
( 5979
 
2.9%
) 5978
 
2.9%
5743
 
2.8%
5647
 
2.7%
Other values (432) 100954
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115066
55.3%
Decimal Number 35497
 
17.1%
Space Separator 35405
 
17.0%
Other Punctuation 8079
 
3.9%
Open Punctuation 5979
 
2.9%
Close Punctuation 5978
 
2.9%
Dash Punctuation 979
 
0.5%
Uppercase Letter 517
 
0.2%
Math Symbol 294
 
0.1%
Letter Number 90
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12424
 
10.8%
8391
 
7.3%
6749
 
5.9%
5743
 
5.0%
5647
 
4.9%
5642
 
4.9%
5585
 
4.9%
5585
 
4.9%
5583
 
4.9%
5299
 
4.6%
Other values (374) 48418
42.1%
Uppercase Letter
ValueCountFrequency (%)
B 163
31.5%
A 138
26.7%
C 44
 
8.5%
N 34
 
6.6%
M 16
 
3.1%
S 13
 
2.5%
D 13
 
2.5%
H 12
 
2.3%
W 11
 
2.1%
I 11
 
2.1%
Other values (17) 62
 
12.0%
Decimal Number
ValueCountFrequency (%)
1 12553
35.4%
2 4711
 
13.3%
0 3113
 
8.8%
3 3065
 
8.6%
6 2666
 
7.5%
4 2589
 
7.3%
5 2455
 
6.9%
7 1589
 
4.5%
8 1421
 
4.0%
9 1335
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
a 2
16.7%
p 1
 
8.3%
c 1
 
8.3%
y 1
 
8.3%
t 1
 
8.3%
k 1
 
8.3%
s 1
 
8.3%
b 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 8073
99.9%
. 4
 
< 0.1%
? 1
 
< 0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
60
66.7%
28
31.1%
2
 
2.2%
Space Separator
ValueCountFrequency (%)
35405
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5979
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5978
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 979
100.0%
Math Symbol
ValueCountFrequency (%)
~ 294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115066
55.3%
Common 92211
44.4%
Latin 618
 
0.3%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12424
 
10.8%
8391
 
7.3%
6749
 
5.9%
5743
 
5.0%
5647
 
4.9%
5642
 
4.9%
5585
 
4.9%
5585
 
4.9%
5583
 
4.9%
5299
 
4.6%
Other values (374) 48418
42.1%
Latin
ValueCountFrequency (%)
B 163
26.4%
A 138
22.3%
60
 
9.7%
C 44
 
7.1%
N 34
 
5.5%
28
 
4.5%
M 16
 
2.6%
S 13
 
2.1%
D 13
 
2.1%
H 12
 
1.9%
Other values (28) 97
15.7%
Common
ValueCountFrequency (%)
35405
38.4%
1 12553
 
13.6%
, 8073
 
8.8%
( 5979
 
6.5%
) 5978
 
6.5%
2 4711
 
5.1%
0 3113
 
3.4%
3 3065
 
3.3%
6 2666
 
2.9%
4 2589
 
2.8%
Other values (9) 8079
 
8.8%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115066
55.3%
ASCII 92739
44.6%
Number Forms 90
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35405
38.2%
1 12553
 
13.5%
, 8073
 
8.7%
( 5979
 
6.4%
) 5978
 
6.4%
2 4711
 
5.1%
0 3113
 
3.4%
3 3065
 
3.3%
6 2666
 
2.9%
4 2589
 
2.8%
Other values (44) 8607
 
9.3%
Hangul
ValueCountFrequency (%)
12424
 
10.8%
8391
 
7.3%
6749
 
5.9%
5743
 
5.0%
5647
 
4.9%
5642
 
4.9%
5585
 
4.9%
5585
 
4.9%
5583
 
4.9%
5299
 
4.6%
Other values (374) 48418
42.1%
Number Forms
ValueCountFrequency (%)
60
66.7%
28
31.1%
2
 
2.2%
None
ValueCountFrequency (%)
Ι 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct265
Distinct (%)4.8%
Missing4491
Missing (%)44.9%
Infinite0
Infinite (%)0.0%
Mean7678.1837
Minimum7503
Maximum7811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:35:58.634404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7503
5-th percentile7524
Q17604
median7673
Q37773
95-th percentile7803
Maximum7811
Range308
Interquartile range (IQR)169

Descriptive statistics

Standard deviation92.51233
Coefficient of variation (CV)0.012048726
Kurtosis-1.2482415
Mean7678.1837
Median Absolute Deviation (MAD)83
Skewness-0.15239426
Sum42299114
Variance8558.5312
MonotonicityNot monotonic
2024-05-11T14:35:58.931690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7803 274
 
2.7%
7788 261
 
2.6%
7802 124
 
1.2%
7801 91
 
0.9%
7663 91
 
0.9%
7505 85
 
0.9%
7631 83
 
0.8%
7654 81
 
0.8%
7604 81
 
0.8%
7657 78
 
0.8%
Other values (255) 4260
42.6%
(Missing) 4491
44.9%
ValueCountFrequency (%)
7503 2
 
< 0.1%
7505 85
0.9%
7506 11
 
0.1%
7508 1
 
< 0.1%
7509 6
 
0.1%
7510 35
0.4%
7511 30
 
0.3%
7512 7
 
0.1%
7513 2
 
< 0.1%
7516 33
 
0.3%
ValueCountFrequency (%)
7811 1
 
< 0.1%
7809 2
 
< 0.1%
7808 13
 
0.1%
7807 38
 
0.4%
7806 56
 
0.6%
7805 9
 
0.1%
7804 3
 
< 0.1%
7803 274
2.7%
7802 124
1.2%
7801 91
 
0.9%
Distinct8724
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:35:59.467205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length5.7093
Min length1

Characters and Unicode

Total characters57093
Distinct characters1112
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7949 ?
Unique (%)79.5%

Sample

1st row등촌도토리마을
2nd row배달의 명가 등촌점
3rd row모스베이커리카페
4th row전주식당
5th row조코제주똥돼지
ValueCountFrequency (%)
마곡점 134
 
1.1%
화곡점 93
 
0.8%
강서점 46
 
0.4%
마곡나루점 38
 
0.3%
발산점 31
 
0.3%
전주식당 26
 
0.2%
등촌점 25
 
0.2%
마곡나루역점 23
 
0.2%
방화점 22
 
0.2%
가양점 20
 
0.2%
Other values (9304) 11715
96.2%
2024-05-11T14:36:00.373055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2175
 
3.8%
1269
 
2.2%
1173
 
2.1%
1145
 
2.0%
948
 
1.7%
899
 
1.6%
894
 
1.6%
813
 
1.4%
756
 
1.3%
631
 
1.1%
Other values (1102) 46390
81.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51121
89.5%
Space Separator 2175
 
3.8%
Uppercase Letter 1033
 
1.8%
Lowercase Letter 967
 
1.7%
Decimal Number 526
 
0.9%
Close Punctuation 506
 
0.9%
Open Punctuation 500
 
0.9%
Other Punctuation 251
 
0.4%
Dash Punctuation 9
 
< 0.1%
Math Symbol 2
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1269
 
2.5%
1173
 
2.3%
1145
 
2.2%
948
 
1.9%
899
 
1.8%
894
 
1.7%
813
 
1.6%
756
 
1.5%
631
 
1.2%
572
 
1.1%
Other values (1023) 42021
82.2%
Lowercase Letter
ValueCountFrequency (%)
e 146
15.1%
o 92
 
9.5%
a 84
 
8.7%
i 70
 
7.2%
n 68
 
7.0%
r 62
 
6.4%
t 61
 
6.3%
s 54
 
5.6%
l 38
 
3.9%
c 38
 
3.9%
Other values (16) 254
26.3%
Uppercase Letter
ValueCountFrequency (%)
B 106
 
10.3%
A 77
 
7.5%
O 74
 
7.2%
C 65
 
6.3%
E 62
 
6.0%
N 58
 
5.6%
L 57
 
5.5%
M 48
 
4.6%
I 43
 
4.2%
T 43
 
4.2%
Other values (16) 400
38.7%
Other Punctuation
ValueCountFrequency (%)
& 98
39.0%
. 65
25.9%
, 33
 
13.1%
? 20
 
8.0%
! 16
 
6.4%
' 11
 
4.4%
# 4
 
1.6%
; 2
 
0.8%
: 1
 
0.4%
/ 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 84
16.0%
0 82
15.6%
2 77
14.6%
5 53
10.1%
8 51
9.7%
9 44
8.4%
3 40
7.6%
4 39
7.4%
6 32
 
6.1%
7 24
 
4.6%
Space Separator
ValueCountFrequency (%)
2175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 506
100.0%
Open Punctuation
ValueCountFrequency (%)
( 500
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51070
89.5%
Common 3972
 
7.0%
Latin 2000
 
3.5%
Han 47
 
0.1%
Hiragana 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1269
 
2.5%
1173
 
2.3%
1145
 
2.2%
948
 
1.9%
899
 
1.8%
894
 
1.8%
813
 
1.6%
756
 
1.5%
631
 
1.2%
572
 
1.1%
Other values (986) 41970
82.2%
Latin
ValueCountFrequency (%)
e 146
 
7.3%
B 106
 
5.3%
o 92
 
4.6%
a 84
 
4.2%
A 77
 
3.9%
O 74
 
3.7%
i 70
 
3.5%
n 68
 
3.4%
C 65
 
3.2%
r 62
 
3.1%
Other values (42) 1156
57.8%
Han
ValueCountFrequency (%)
6
 
12.8%
3
 
6.4%
3
 
6.4%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
2
 
4.3%
1
 
2.1%
1
 
2.1%
Other values (23) 23
48.9%
Common
ValueCountFrequency (%)
2175
54.8%
) 506
 
12.7%
( 500
 
12.6%
& 98
 
2.5%
1 84
 
2.1%
0 82
 
2.1%
2 77
 
1.9%
. 65
 
1.6%
5 53
 
1.3%
8 51
 
1.3%
Other values (17) 281
 
7.1%
Hiragana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51070
89.5%
ASCII 5972
 
10.5%
CJK 43
 
0.1%
CJK Compat Ideographs 4
 
< 0.1%
Hiragana 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2175
36.4%
) 506
 
8.5%
( 500
 
8.4%
e 146
 
2.4%
B 106
 
1.8%
& 98
 
1.6%
o 92
 
1.5%
1 84
 
1.4%
a 84
 
1.4%
0 82
 
1.4%
Other values (69) 2099
35.1%
Hangul
ValueCountFrequency (%)
1269
 
2.5%
1173
 
2.3%
1145
 
2.2%
948
 
1.9%
899
 
1.8%
894
 
1.8%
813
 
1.6%
756
 
1.5%
631
 
1.2%
572
 
1.1%
Other values (986) 41970
82.2%
CJK
ValueCountFrequency (%)
6
 
14.0%
3
 
7.0%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
2
 
4.7%
1
 
2.3%
1
 
2.3%
1
 
2.3%
Other values (21) 21
48.8%
CJK Compat Ideographs
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Hiragana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Distinct7741
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-05-17 00:00:00
Maximum2024-05-09 17:40:43
2024-05-11T14:36:00.629544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:00.863976image/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
6736 
U
3264 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6736
67.4%
U 3264
32.6%

Length

2024-05-11T14:36:01.108707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:01.279891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6736
67.4%
u 3264
32.6%
Distinct1323
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:36:01.487099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:36:01.766735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4930 
분식
1097 
정종/대포집/소주방
970 
경양식
732 
호프/통닭
520 
Other values (21)
1751 

Length

Max length15
Median length2
Mean length3.2936
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row호프/통닭
3rd row기타
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 4930
49.3%
분식 1097
 
11.0%
정종/대포집/소주방 970
 
9.7%
경양식 732
 
7.3%
호프/통닭 520
 
5.2%
일식 470
 
4.7%
기타 322
 
3.2%
중국식 296
 
3.0%
통닭(치킨) 289
 
2.9%
패스트푸드 110
 
1.1%
Other values (16) 264
 
2.6%

Length

2024-05-11T14:36:02.032990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4930
49.3%
분식 1097
 
11.0%
정종/대포집/소주방 970
 
9.7%
경양식 732
 
7.3%
호프/통닭 520
 
5.2%
일식 470
 
4.7%
기타 322
 
3.2%
중국식 296
 
3.0%
통닭(치킨 289
 
2.9%
패스트푸드 110
 
1.1%
Other values (16) 264
 
2.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3742
Distinct (%)39.8%
Missing602
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean185769.77
Minimum180450.88
Maximum189200.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:36:02.301203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180450.88
5-th percentile183137.92
Q1184959.61
median185894.28
Q3186787.64
95-th percentile187872.94
Maximum189200.15
Range8749.2714
Interquartile range (IQR)1828.0342

Descriptive statistics

Standard deviation1519.6381
Coefficient of variation (CV)0.0081802229
Kurtosis-0.57327378
Mean185769.77
Median Absolute Deviation (MAD)904.14585
Skewness-0.33567743
Sum1.7458643 × 109
Variance2309300
MonotonicityNot monotonic
2024-05-11T14:36:02.532176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182524.823835629 57
 
0.6%
186594.265612983 36
 
0.4%
185824.428508883 28
 
0.3%
187952.560027898 27
 
0.3%
185550.853784183 27
 
0.3%
186501.233192961 27
 
0.3%
183366.101249557 26
 
0.3%
182735.786874703 24
 
0.2%
184650.0 24
 
0.2%
186414.512866944 24
 
0.2%
Other values (3732) 9098
91.0%
(Missing) 602
 
6.0%
ValueCountFrequency (%)
180450.876349055 1
 
< 0.1%
180943.793439985 1
 
< 0.1%
181159.607146035 1
 
< 0.1%
181587.305368529 1
 
< 0.1%
181682.433518522 1
 
< 0.1%
181817.623739958 1
 
< 0.1%
181843.707389758 2
< 0.1%
182086.388313239 1
 
< 0.1%
182141.205465089 4
< 0.1%
182154.410343287 1
 
< 0.1%
ValueCountFrequency (%)
189200.147733153 2
 
< 0.1%
189198.425397063 1
 
< 0.1%
189172.250232972 3
 
< 0.1%
189152.269637156 2
 
< 0.1%
189124.441211963 3
 
< 0.1%
189105.201587182 5
0.1%
189102.277524848 4
 
< 0.1%
189098.806779959 12
0.1%
189083.879252663 1
 
< 0.1%
189066.642961645 5
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3737
Distinct (%)39.8%
Missing602
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean449921.19
Minimum447209.71
Maximum453484.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:36:02.743126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447209.71
5-th percentile447570.24
Q1448612.98
median450085.29
Q3450997.02
95-th percentile452244.26
Maximum453484.1
Range6274.3895
Interquartile range (IQR)2384.0417

Descriptive statistics

Standard deviation1504.4155
Coefficient of variation (CV)0.0033437312
Kurtosis-1.0731632
Mean449921.19
Median Absolute Deviation (MAD)1177.3668
Skewness-0.13231052
Sum4.2283593 × 109
Variance2263266.1
MonotonicityNot monotonic
2024-05-11T14:36:03.329529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451438.25089679 57
 
0.6%
449819.1839312 36
 
0.4%
450866.252126246 28
 
0.3%
450482.868069557 27
 
0.3%
450562.020225978 27
 
0.3%
451485.251875922 27
 
0.3%
450938.0 26
 
0.3%
452817.469477897 26
 
0.3%
450851.460122005 24
 
0.2%
451667.0 24
 
0.2%
Other values (3727) 9096
91.0%
(Missing) 602
 
6.0%
ValueCountFrequency (%)
447209.706639763 1
 
< 0.1%
447215.959475895 1
 
< 0.1%
447239.554007375 1
 
< 0.1%
447266.978172789 1
 
< 0.1%
447297.791614934 2
 
< 0.1%
447306.502430305 1
 
< 0.1%
447316.214981355 9
0.1%
447322.448363152 4
 
< 0.1%
447323.008024977 3
 
< 0.1%
447326.548615694 14
0.1%
ValueCountFrequency (%)
453484.09618897 1
 
< 0.1%
453468.096258454 1
 
< 0.1%
453178.305694113 3
< 0.1%
453142.430233817 2
 
< 0.1%
453050.733807442 7
0.1%
453018.037256925 1
 
< 0.1%
453018.018573883 1
 
< 0.1%
453015.644256685 1
 
< 0.1%
452954.122241351 2
 
< 0.1%
452947.739057258 1
 
< 0.1%

위생업태명
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3869 
<NA>
1991 
분식
1004 
정종/대포집/소주방
902 
경양식
548 
Other values (19)
1686 

Length

Max length15
Median length2
Mean length3.522
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row호프/통닭
3rd row<NA>
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 3869
38.7%
<NA> 1991
19.9%
분식 1004
 
10.0%
정종/대포집/소주방 902
 
9.0%
경양식 548
 
5.5%
호프/통닭 398
 
4.0%
일식 318
 
3.2%
통닭(치킨) 265
 
2.6%
중국식 227
 
2.3%
기타 178
 
1.8%
Other values (14) 300
 
3.0%

Length

2024-05-11T14:36:03.552767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3869
38.7%
na 1991
19.9%
분식 1004
 
10.0%
정종/대포집/소주방 902
 
9.0%
경양식 548
 
5.5%
호프/통닭 398
 
4.0%
일식 318
 
3.2%
통닭(치킨 265
 
2.6%
중국식 227
 
2.3%
기타 178
 
1.8%
Other values (14) 300
 
3.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.3%
Missing5272
Missing (%)52.7%
Infinite0
Infinite (%)0.0%
Mean0.51015228
Minimum0
Maximum20
Zeros2987
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:36:03.745701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0298602
Coefficient of variation (CV)2.0187309
Kurtosis107.88647
Mean0.51015228
Median Absolute Deviation (MAD)0
Skewness7.5933055
Sum2412
Variance1.060612
MonotonicityNot monotonic
2024-05-11T14:36:03.978476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 2987
29.9%
1 1384
 
13.8%
2 244
 
2.4%
3 60
 
0.6%
5 18
 
0.2%
4 16
 
0.2%
7 5
 
0.1%
10 3
 
< 0.1%
9 2
 
< 0.1%
20 2
 
< 0.1%
Other values (6) 7
 
0.1%
(Missing) 5272
52.7%
ValueCountFrequency (%)
0 2987
29.9%
1 1384
13.8%
2 244
 
2.4%
3 60
 
0.6%
4 16
 
0.2%
5 18
 
0.2%
6 1
 
< 0.1%
7 5
 
0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
20 2
 
< 0.1%
19 1
 
< 0.1%
17 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 3
< 0.1%
9 2
 
< 0.1%
8 2
 
< 0.1%
7 5
0.1%
6 1
 
< 0.1%

여성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.4%
Missing5058
Missing (%)50.6%
Infinite0
Infinite (%)0.0%
Mean1.0623229
Minimum0
Maximum93
Zeros1861
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:36:04.190344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum93
Range93
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9796989
Coefficient of variation (CV)1.8635565
Kurtosis995.19489
Mean1.0623229
Median Absolute Deviation (MAD)1
Skewness24.034889
Sum5250
Variance3.9192076
MonotonicityNot monotonic
2024-05-11T14:36:04.374295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 1861
 
18.6%
1 1830
 
18.3%
2 892
 
8.9%
3 215
 
2.1%
4 59
 
0.6%
5 39
 
0.4%
6 12
 
0.1%
8 7
 
0.1%
7 7
 
0.1%
10 4
 
< 0.1%
Other values (9) 16
 
0.2%
(Missing) 5058
50.6%
ValueCountFrequency (%)
0 1861
18.6%
1 1830
18.3%
2 892
8.9%
3 215
 
2.1%
4 59
 
0.6%
5 39
 
0.4%
6 12
 
0.1%
7 7
 
0.1%
8 7
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
40 1
 
< 0.1%
34 1
 
< 0.1%
25 1
 
< 0.1%
20 1
 
< 0.1%
16 2
< 0.1%
15 1
 
< 0.1%
12 4
< 0.1%
10 4
< 0.1%
9 4
< 0.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6030 
주택가주변
1984 
기타
1470 
아파트지역
 
254
유흥업소밀집지역
 
222
Other values (3)
 
40

Length

Max length8
Median length4
Mean length4.0336
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6030
60.3%
주택가주변 1984
 
19.8%
기타 1470
 
14.7%
아파트지역 254
 
2.5%
유흥업소밀집지역 222
 
2.2%
학교정화(상대) 21
 
0.2%
결혼예식장주변 10
 
0.1%
학교정화(절대) 9
 
0.1%

Length

2024-05-11T14:36:04.620589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:04.826839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6030
60.3%
주택가주변 1984
 
19.8%
기타 1470
 
14.7%
아파트지역 254
 
2.5%
유흥업소밀집지역 222
 
2.2%
학교정화(상대 21
 
0.2%
결혼예식장주변 10
 
0.1%
학교정화(절대 9
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6128 
기타
1937 
자율
952 
 
353
지도
 
326
Other values (3)
 
304

Length

Max length4
Median length4
Mean length3.1831
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6128
61.3%
기타 1937
 
19.4%
자율 952
 
9.5%
353
 
3.5%
지도 326
 
3.3%
우수 215
 
2.1%
72
 
0.7%
관리 17
 
0.2%

Length

2024-05-11T14:36:05.081052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:05.298484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6128
61.3%
기타 1937
 
19.4%
자율 952
 
9.5%
353
 
3.5%
지도 326
 
3.3%
우수 215
 
2.1%
72
 
0.7%
관리 17
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
6386 
<NA>
3532 
지하수전용
 
58
상수도(음용)지하수(주방용)겸용
 
15
간이상수도
 
8

Length

Max length19
Median length5
Mean length4.6662
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 6386
63.9%
<NA> 3532
35.3%
지하수전용 58
 
0.6%
상수도(음용)지하수(주방용)겸용 15
 
0.1%
간이상수도 8
 
0.1%
전용상수도(특정시설의 자가용 수도) 1
 
< 0.1%

Length

2024-05-11T14:36:05.555218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:05.772444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 6386
63.8%
na 3532
35.3%
지하수전용 58
 
0.6%
상수도(음용)지하수(주방용)겸용 15
 
0.1%
간이상수도 8
 
0.1%
전용상수도(특정시설의 1
 
< 0.1%
자가용 1
 
< 0.1%
수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9554 
0
 
446

Length

Max length4
Median length4
Mean length3.8662
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> 9554
95.5%
0 446
 
4.5%

Length

2024-05-11T14:36:06.104691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:06.291463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9554
95.5%
0 446
 
4.5%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:06.457390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:06.629019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:06.846955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:07.027695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:07.207577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:07.401380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:07.595106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:07.782099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

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>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:07.957614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:08.124069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9553 
0
 
447

Length

Max length4
Median length4
Mean length3.8659
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> 9553
95.5%
0 447
 
4.5%

Length

2024-05-11T14:36:08.285565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:08.454959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9553
95.5%
0 447
 
4.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1990
Missing (%)19.9%
Memory size97.7 KiB
False
7835 
True
 
175
(Missing)
1990 
ValueCountFrequency (%)
False 7835
78.3%
True 175
 
1.8%
(Missing) 1990
 
19.9%
2024-05-11T14:36:08.604515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct4313
Distinct (%)53.8%
Missing1990
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean74.7638
Minimum0
Maximum80038.06
Zeros270
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T14:36:08.787071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.929
Q125.7625
median39.15
Q373.53
95-th percentile180.1595
Maximum80038.06
Range80038.06
Interquartile range (IQR)47.7675

Descriptive statistics

Standard deviation898.33857
Coefficient of variation (CV)12.015689
Kurtosis7841.2277
Mean74.7638
Median Absolute Deviation (MAD)17.11
Skewness88.088999
Sum598858.04
Variance807012.19
MonotonicityNot monotonic
2024-05-11T14:36:09.078599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 270
 
2.7%
33.0 120
 
1.2%
30.0 47
 
0.5%
26.4 45
 
0.4%
26.0 38
 
0.4%
40.0 34
 
0.3%
23.1 32
 
0.3%
25.0 31
 
0.3%
66.0 30
 
0.3%
20.0 28
 
0.3%
Other values (4303) 7335
73.4%
(Missing) 1990
 
19.9%
ValueCountFrequency (%)
0.0 270
2.7%
3.3 3
 
< 0.1%
4.48 1
 
< 0.1%
4.5 2
 
< 0.1%
5.0 1
 
< 0.1%
6.0 1
 
< 0.1%
6.4 1
 
< 0.1%
6.5 1
 
< 0.1%
6.82 1
 
< 0.1%
7.0 1
 
< 0.1%
ValueCountFrequency (%)
80038.06 1
< 0.1%
2078.35 1
< 0.1%
1917.81 1
< 0.1%
1879.05 1
< 0.1%
1386.6 1
< 0.1%
1379.04 1
< 0.1%
1298.52 1
< 0.1%
1146.19 1
< 0.1%
990.71 1
< 0.1%
964.75 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
한식
 
3

Length

Max length4
Median length4
Mean length3.9994
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
한식 3
 
< 0.1%

Length

2024-05-11T14:36:09.335361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:36:09.504670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
한식 3
 
< 0.1%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1136531500003150000-101-2005-0042620051101<NA>3폐업2폐업20110411<NA><NA><NA>2642599088.88157836서울특별시 강서구 등촌동 510-14번지<NA><NA>등촌도토리마을2007-03-12 00:00:00I2018-08-31 23:59:59.0분식187805.593084449601.316483분식12주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N88.88<NA><NA><NA>
1245131500003150000-101-2008-0010220080416<NA>1영업/정상1영업<NA><NA><NA><NA>022651998239.64157836서울특별시 강서구 등촌동 366-99 (지상 1층)서울특별시 강서구 등촌로51나길 5-17, 1층 (등촌동, 2동)7667배달의 명가 등촌점2021-07-08 17:23:27U2021-07-10 02:40:00.0호프/통닭187703.641465449634.383997호프/통닭<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N39.64<NA><NA><NA>
2146831500003150000-101-2023-004512023-07-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>401.70157-030서울특별시 강서구 등촌동 14-7 가양역 데시앙플렉스 지식산업센터 102~110호서울특별시 강서구 양천로 424, 가양역 데시앙플렉스 지식산업센터 1층 102~110호 (등촌동)7573모스베이커리카페2024-01-25 11:06:37U2023-11-30 22:07:00.0기타186501.110937451334.591084<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1014331500003150000-101-2003-0069420031119<NA>3폐업2폐업20150224<NA><NA><NA>0226651723<NA>157812서울특별시 강서구 공항동 60-25번지서울특별시 강서구 송정로 45-1 (공항동)7627전주식당2003-11-19 00:00:00I2018-08-31 23:59:59.0한식183177.28985450759.490724한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
975431500003150000-101-2003-0028720030514<NA>1영업/정상1영업<NA><NA><NA><NA>022666166295.37157857서울특별시 강서구 방화동 830-3번지 샤르망 (지상 2층) 205호서울특별시 강서구 방화대로47가길 7, 2층 205호 (방화동, 3동 샤르망)7511조코제주똥돼지2012-11-13 10:52:48I2018-08-31 23:59:59.0한식183414.494799452706.10492한식13기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.37<NA><NA><NA>
233731500003150000-101-1992-0551819921222<NA>3폐업2폐업19970305<NA><NA><NA>02 0000050.36157280서울특별시 강서구 내발산동 663-6번지<NA><NA>우장족발2001-09-28 00:00:00I2018-08-31 23:59:59.0한식185806.754805450274.115197한식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.36<NA><NA><NA>
1647131500003150000-101-2017-0016620170419<NA>1영업/정상1영업<NA><NA><NA><NA>0261165763236.77157220서울특별시 강서구 방화동 886-0 김포공항스카이파크롯데몰 (지하 1~2층)서울특별시 강서구 하늘길 38, 지하 1~2층 (방화동, 2동 김포공항스카이파크롯데몰)7505헤븐온탑 김포공항점2022-11-24 15:54:09U2021-10-31 22:06:00.0경양식182524.823836451438.250897<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1234631500003150000-101-2007-0040120070814<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.04157851서울특별시 강서구 방화동 599-1번지 (지상 1층)서울특별시 강서구 초원로 53, 1층 (방화동, 2동)7608윤영이네 마차2019-06-03 11:25:27U2019-06-05 02:40:00.0한식183257.363825451756.674811한식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.04<NA><NA><NA>
981431500003150000-101-2003-0034920030605<NA>3폐업2폐업20120725<NA><NA><NA>0226447019<NA>157897서울특별시 강서구 화곡동 782-1번지<NA><NA>춘천닭갈비2012-07-25 14:24:11I2018-08-31 23:59:59.0경양식187868.19216447679.060114경양식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1405731500003150000-101-2011-0038320111125<NA>3폐업2폐업20130614<NA><NA><NA><NA>90.88157873서울특별시 강서구 화곡동 1063-0번지 (지상 1층)서울특별시 강서구 화곡로27가길 2, 2층 (화곡동, 우장산동)7702레스트바2011-11-25 14:57:46I2018-08-31 23:59:59.0호프/통닭185862.269709448900.253656호프/통닭<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N90.88<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
683531500003150000-101-1999-0744819990809<NA>3폐업2폐업19991213<NA><NA><NA>02 662363113.73157847서울특별시 강서구 방화동 285-16번지<NA><NA>미락칼국수1999-12-16 00:00:00I2018-08-31 23:59:59.0한식183543.660224452316.316554한식11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N13.73<NA><NA><NA>
722631500003150000-101-1999-0912219990303<NA>3폐업2폐업20040920<NA><NA><NA>023665459225.08157280서울특별시 강서구 내발산동 703-29번지<NA><NA>굿모닝살로만치킨2003-10-07 00:00:00I2018-08-31 23:59:59.0일식185683.587868450020.692692일식11주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.08<NA><NA><NA>
2121731500003150000-101-2023-001992023-03-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>14.78157-930서울특별시 강서구 등촌동 700 플러스존 220-B호서울특별시 강서구 공항대로41길 34, 플러스존 2층 220-B호 (등촌동)7587스테이크 앤 파스타2023-03-30 11:28:44I2022-12-04 00:01:00.0경양식186299.742677450792.016506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
333431500003150000-101-1994-0254519940625<NA>3폐업2폐업19960816<NA><NA><NA>02 605662123.25157280서울특별시 강서구 내발산동 산 720-20번지<NA><NA>예송분식2001-09-28 00:00:00I2018-08-31 23:59:59.0분식<NA><NA>분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.25<NA><NA><NA>
1490831500003150000-101-2013-0037520131210<NA>1영업/정상1영업<NA><NA><NA><NA>023663272434.00157863서울특별시 강서구 염창동 272-5번지 (지상 1층)서울특별시 강서구 공항대로63길 8, 1층 (염창동)7561봉구비어 등촌역1호점2014-06-10 14:30:22I2018-08-31 23:59:59.0호프/통닭188175.987473449817.658834호프/통닭<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.0<NA><NA><NA>
441631500003150000-101-1995-0818919951007<NA>3폐업2폐업19960716<NA><NA><NA>02 668768526.39157800서울특별시 강서구 가양동 1-4번지 빌딩 1층동<NA><NA>강마을2001-09-28 00:00:00I2018-08-31 23:59:59.0정종/대포집/소주방<NA><NA>정종/대포집/소주방00아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.39<NA><NA><NA>
309931500003150000-101-1994-0084819941026<NA>3폐업2폐업19950816<NA><NA><NA>020694356527.00157928서울특별시 강서구 화곡동 1130-7번지<NA><NA>바이타임2001-09-28 00:00:00I2018-08-31 23:59:59.0패스트푸드187210.989837449892.034221패스트푸드00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.0<NA><NA><NA>
18531500003150000-101-1981-0600319811209<NA>3폐업2폐업20021107<NA><NA><NA>02 696201023.10157840서울특별시 강서구 등촌동 646-14번지<NA><NA>모아분식2001-11-26 00:00:00I2018-08-31 23:59:59.0한식187861.377394450149.799907한식11주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N23.1<NA><NA><NA>
1914431500003150000-101-2020-0065520201014<NA>3폐업2폐업20221227<NA><NA><NA>023663011743.92157210서울특별시 강서구 마곡동 794-1 우성에스비타워 1층 121호서울특별시 강서구 강서로 385, 우성에스비타워 1층 121호 (마곡동)7803상아김밥2022-12-27 16:57:06U2021-11-01 22:09:00.0분식185642.667278450883.006755<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1920431500003150000-101-2020-0071520201030<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.00157842서울특별시 강서구 등촌동 655-37 신성빌딩서울특별시 강서구 공항대로 423, 신성빌딩 1층 (등촌동)7571무제2020-10-30 17:44:22I2020-11-01 00:23:09.0일식187062.179875450374.104548일식<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N32.0<NA><NA><NA>