Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells90282
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Categorical20
Text7
DateTime4
Unsupported6
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-18655/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
총인원 is highly imbalanced (76.9%)Imbalance
본사종업원수 is highly imbalanced (76.8%)Imbalance
공장사무직종업원수 is highly imbalanced (76.8%)Imbalance
공장판매직종업원수 is highly imbalanced (76.8%)Imbalance
공장생산직종업원수 is highly imbalanced (76.8%)Imbalance
보증액 is highly imbalanced (76.8%)Imbalance
월세액 is highly imbalanced (76.8%)Imbalance
다중이용업소여부 is highly imbalanced (84.5%)Imbalance
전통업소지정번호 is highly imbalanced (99.8%)Imbalance
전통업소주된음식 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2914 (29.1%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 3430 (34.3%) missing valuesMissing
소재지면적 has 107 (1.1%) missing valuesMissing
도로명주소 has 4428 (44.3%) missing valuesMissing
도로명우편번호 has 4522 (45.2%) missing valuesMissing
좌표정보(X) has 536 (5.4%) missing valuesMissing
좌표정보(Y) has 536 (5.4%) missing valuesMissing
남성종사자수 has 4820 (48.2%) missing valuesMissing
여성종사자수 has 4821 (48.2%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 2079 (20.8%) missing valuesMissing
시설총규모 has 2079 (20.8%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 44.62666429)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
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 4354 (43.5%) zerosZeros
여성종사자수 has 3986 (39.9%) zerosZeros
시설총규모 has 119 (1.2%) zerosZeros

Reproduction

Analysis started2024-05-11 01:09:32.246860
Analysis finished2024-05-11 01:09:37.955391
Duration5.71 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
3030000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 10000
100.0%

Length

2024-05-11T01:09:38.272067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:38.737524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T01:09:39.239099image/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 row3030000-101-2014-00105
2nd row3030000-101-1997-04491
3rd row3030000-101-2004-00234
4th row3030000-101-1998-01548
5th row3030000-101-1999-06137
ValueCountFrequency (%)
3030000-101-2014-00105 1
 
< 0.1%
3030000-101-1990-04988 1
 
< 0.1%
3030000-101-2017-00302 1
 
< 0.1%
3030000-101-1992-05141 1
 
< 0.1%
3030000-101-1993-05571 1
 
< 0.1%
3030000-101-2006-00229 1
 
< 0.1%
3030000-101-1997-04712 1
 
< 0.1%
3030000-101-1978-04379 1
 
< 0.1%
3030000-101-2004-00177 1
 
< 0.1%
3030000-101-1996-04765 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T01:09:40.588171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 89879
40.9%
1 31894
 
14.5%
- 30000
 
13.6%
3 25158
 
11.4%
2 13589
 
6.2%
9 9541
 
4.3%
4 4556
 
2.1%
5 4065
 
1.8%
8 3965
 
1.8%
6 3920
 
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 89879
47.3%
1 31894
 
16.8%
3 25158
 
13.2%
2 13589
 
7.2%
9 9541
 
5.0%
4 4556
 
2.4%
5 4065
 
2.1%
8 3965
 
2.1%
6 3920
 
2.1%
7 3433
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 89879
40.9%
1 31894
 
14.5%
- 30000
 
13.6%
3 25158
 
11.4%
2 13589
 
6.2%
9 9541
 
4.3%
4 4556
 
2.1%
5 4065
 
1.8%
8 3965
 
1.8%
6 3920
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 89879
40.9%
1 31894
 
14.5%
- 30000
 
13.6%
3 25158
 
11.4%
2 13589
 
6.2%
9 9541
 
4.3%
4 4556
 
2.1%
5 4065
 
1.8%
8 3965
 
1.8%
6 3920
 
1.8%
Distinct6126
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1970-07-11 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T01:09:41.308522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:09:41.966273image/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
7086 
1
2914 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7086
70.9%
1 2914
29.1%

Length

2024-05-11T01:09:42.458489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:42.766541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7086
70.9%
1 2914
29.1%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7086 
영업/정상
2914 

Length

Max length5
Median length2
Mean length2.8742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7086
70.9%
영업/정상 2914
29.1%

Length

2024-05-11T01:09:43.310848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:43.643121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7086
70.9%
영업/정상 2914
29.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7086 
1
2914 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7086
70.9%
1 2914
29.1%

Length

2024-05-11T01:09:43.975927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:44.306173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7086
70.9%
1 2914
29.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7086 
영업
2914 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7086
70.9%
영업 2914
29.1%

Length

2024-05-11T01:09:44.640395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:44.939507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7086
70.9%
영업 2914
29.1%

폐업일자
Date

MISSING 

Distinct3953
Distinct (%)55.8%
Missing2914
Missing (%)29.1%
Memory size156.2 KiB
Minimum1988-07-20 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T01:09:45.314132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:09:45.755855image/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 

Distinct5744
Distinct (%)87.4%
Missing3430
Missing (%)34.3%
Memory size156.2 KiB
2024-05-11T01:09:46.454233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6563166
Min length2

Characters and Unicode

Total characters63442
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5582 ?
Unique (%)85.0%

Sample

1st row0222977792
2nd row02 2120360
3rd row22990044
4th row02
5th row02 4692791
ValueCountFrequency (%)
02 3050
32.4%
0 83
 
0.9%
00000 55
 
0.6%
0200000000 27
 
0.3%
4469906 26
 
0.3%
070 24
 
0.3%
21
 
0.2%
499 18
 
0.2%
461 17
 
0.2%
462 15
 
0.2%
Other values (5804) 6092
64.6%
2024-05-11T01:09:47.445086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16102
25.4%
0 11660
18.4%
9 5839
 
9.2%
4 5066
 
8.0%
6 4324
 
6.8%
3693
 
5.8%
8 3497
 
5.5%
3 3467
 
5.5%
1 3377
 
5.3%
5 3278
 
5.2%
Other values (3) 3139
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59722
94.1%
Space Separator 3693
 
5.8%
Other Punctuation 27
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16102
27.0%
0 11660
19.5%
9 5839
 
9.8%
4 5066
 
8.5%
6 4324
 
7.2%
8 3497
 
5.9%
3 3467
 
5.8%
1 3377
 
5.7%
5 3278
 
5.5%
7 3112
 
5.2%
Other Punctuation
ValueCountFrequency (%)
. 26
96.3%
* 1
 
3.7%
Space Separator
ValueCountFrequency (%)
3693
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16102
25.4%
0 11660
18.4%
9 5839
 
9.2%
4 5066
 
8.0%
6 4324
 
6.8%
3693
 
5.8%
8 3497
 
5.5%
3 3467
 
5.5%
1 3377
 
5.3%
5 3278
 
5.2%
Other values (3) 3139
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16102
25.4%
0 11660
18.4%
9 5839
 
9.2%
4 5066
 
8.0%
6 4324
 
6.8%
3693
 
5.8%
8 3497
 
5.5%
3 3467
 
5.5%
1 3377
 
5.3%
5 3278
 
5.2%
Other values (3) 3139
 
4.9%

소재지면적
Text

MISSING 

Distinct4829
Distinct (%)48.8%
Missing107
Missing (%)1.1%
Memory size156.2 KiB
2024-05-11T01:09:48.228101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1113919
Min length3

Characters and Unicode

Total characters50567
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

Unique3062 ?
Unique (%)31.0%

Sample

1st row102.00
2nd row55.87
3rd row64.50
4th row91.37
5th row33.00
ValueCountFrequency (%)
33.00 112
 
1.1%
30.00 67
 
0.7%
15.00 56
 
0.6%
20.00 56
 
0.6%
24.00 52
 
0.5%
27.00 42
 
0.4%
26.00 42
 
0.4%
66.00 41
 
0.4%
40.00 41
 
0.4%
26.40 40
 
0.4%
Other values (4819) 9344
94.5%
2024-05-11T01:09:49.580149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9893
19.6%
0 7623
15.1%
2 5103
10.1%
1 4519
8.9%
3 3858
 
7.6%
4 3811
 
7.5%
5 3545
 
7.0%
6 3491
 
6.9%
8 3117
 
6.2%
7 2813
 
5.6%
Other values (2) 2794
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40666
80.4%
Other Punctuation 9901
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7623
18.7%
2 5103
12.5%
1 4519
11.1%
3 3858
9.5%
4 3811
9.4%
5 3545
8.7%
6 3491
8.6%
8 3117
7.7%
7 2813
 
6.9%
9 2786
 
6.9%
Other Punctuation
ValueCountFrequency (%)
. 9893
99.9%
, 8
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50567
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9893
19.6%
0 7623
15.1%
2 5103
10.1%
1 4519
8.9%
3 3858
 
7.6%
4 3811
 
7.5%
5 3545
 
7.0%
6 3491
 
6.9%
8 3117
 
6.2%
7 2813
 
5.6%
Other values (2) 2794
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50567
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9893
19.6%
0 7623
15.1%
2 5103
10.1%
1 4519
8.9%
3 3858
 
7.6%
4 3811
 
7.5%
5 3545
 
7.0%
6 3491
 
6.9%
8 3117
 
6.2%
7 2813
 
5.6%
Other values (2) 2794
 
5.5%
Distinct185
Distinct (%)1.9%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T01:09:50.386522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1214607
Min length6

Characters and Unicode

Total characters61184
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

Unique21 ?
Unique (%)0.2%

Sample

1st row133-868
2nd row133847
3rd row133844
4th row133815
5th row133820
ValueCountFrequency (%)
133871 403
 
4.0%
133822 307
 
3.1%
133882 281
 
2.8%
133834 262
 
2.6%
133832 259
 
2.6%
133010 247
 
2.5%
133835 247
 
2.5%
133828 235
 
2.4%
133827 233
 
2.3%
133803 210
 
2.1%
Other values (175) 7311
73.1%
2024-05-11T01:09:51.511715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 22461
36.7%
1 12108
19.8%
8 10656
17.4%
2 3604
 
5.9%
0 3201
 
5.2%
4 1820
 
3.0%
5 1781
 
2.9%
7 1755
 
2.9%
6 1487
 
2.4%
- 1214
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59970
98.0%
Dash Punctuation 1214
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 22461
37.5%
1 12108
20.2%
8 10656
17.8%
2 3604
 
6.0%
0 3201
 
5.3%
4 1820
 
3.0%
5 1781
 
3.0%
7 1755
 
2.9%
6 1487
 
2.5%
9 1097
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 1214
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 22461
36.7%
1 12108
19.8%
8 10656
17.4%
2 3604
 
5.9%
0 3201
 
5.2%
4 1820
 
3.0%
5 1781
 
2.9%
7 1755
 
2.9%
6 1487
 
2.4%
- 1214
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 22461
36.7%
1 12108
19.8%
8 10656
17.4%
2 3604
 
5.9%
0 3201
 
5.2%
4 1820
 
3.0%
5 1781
 
2.9%
7 1755
 
2.9%
6 1487
 
2.4%
- 1214
 
2.0%
Distinct7188
Distinct (%)71.9%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T01:09:52.215286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length51
Mean length25.431216
Min length16

Characters and Unicode

Total characters254185
Distinct characters419
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

Unique5653 ?
Unique (%)56.6%

Sample

1st row서울특별시 성동구 행당동 317-85
2nd row서울특별시 성동구 용답동 4-13번지
3rd row서울특별시 성동구 옥수동 475번지 성원상떼뷰 비101호
4th row서울특별시 성동구 마장동 772-4번지
5th row서울특별시 성동구 성수동1가 563번지
ValueCountFrequency (%)
서울특별시 9995
22.3%
성동구 9995
22.3%
성수동2가 2181
 
4.9%
성수동1가 1501
 
3.3%
행당동 1464
 
3.3%
지상1층 1237
 
2.8%
용답동 740
 
1.6%
하왕십리동 587
 
1.3%
마장동 473
 
1.1%
도선동 410
 
0.9%
Other values (6292) 16336
36.4%
2024-05-11T01:09:53.375556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42764
16.8%
20374
 
8.0%
13928
 
5.5%
1 12089
 
4.8%
10129
 
4.0%
10114
 
4.0%
10063
 
4.0%
10009
 
3.9%
10002
 
3.9%
9995
 
3.9%
Other values (409) 104718
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146019
57.4%
Decimal Number 53062
 
20.9%
Space Separator 42764
 
16.8%
Dash Punctuation 8333
 
3.3%
Close Punctuation 1407
 
0.6%
Open Punctuation 1398
 
0.5%
Uppercase Letter 633
 
0.2%
Other Punctuation 428
 
0.2%
Lowercase Letter 120
 
< 0.1%
Math Symbol 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20374
14.0%
13928
 
9.5%
10129
 
6.9%
10114
 
6.9%
10063
 
6.9%
10009
 
6.9%
10002
 
6.8%
9995
 
6.8%
8951
 
6.1%
6828
 
4.7%
Other values (345) 35626
24.4%
Uppercase Letter
ValueCountFrequency (%)
A 103
16.3%
B 101
16.0%
T 58
9.2%
E 52
8.2%
K 40
 
6.3%
S 38
 
6.0%
I 35
 
5.5%
C 32
 
5.1%
V 31
 
4.9%
R 31
 
4.9%
Other values (14) 112
17.7%
Lowercase Letter
ValueCountFrequency (%)
o 24
20.0%
e 24
20.0%
r 20
16.7%
w 14
11.7%
t 6
 
5.0%
l 5
 
4.2%
a 4
 
3.3%
m 4
 
3.3%
i 3
 
2.5%
h 3
 
2.5%
Other values (7) 13
10.8%
Decimal Number
ValueCountFrequency (%)
1 12089
22.8%
2 8957
16.9%
3 5669
10.7%
6 4691
 
8.8%
5 4133
 
7.8%
4 3744
 
7.1%
0 3738
 
7.0%
9 3438
 
6.5%
8 3318
 
6.3%
7 3285
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 388
90.7%
. 22
 
5.1%
@ 15
 
3.5%
/ 1
 
0.2%
& 1
 
0.2%
: 1
 
0.2%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
42764
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8333
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1407
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1398
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146019
57.4%
Common 107410
42.3%
Latin 756
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20374
14.0%
13928
 
9.5%
10129
 
6.9%
10114
 
6.9%
10063
 
6.9%
10009
 
6.9%
10002
 
6.8%
9995
 
6.8%
8951
 
6.1%
6828
 
4.7%
Other values (345) 35626
24.4%
Latin
ValueCountFrequency (%)
A 103
13.6%
B 101
13.4%
T 58
 
7.7%
E 52
 
6.9%
K 40
 
5.3%
S 38
 
5.0%
I 35
 
4.6%
C 32
 
4.2%
V 31
 
4.1%
R 31
 
4.1%
Other values (33) 235
31.1%
Common
ValueCountFrequency (%)
42764
39.8%
1 12089
 
11.3%
2 8957
 
8.3%
- 8333
 
7.8%
3 5669
 
5.3%
6 4691
 
4.4%
5 4133
 
3.8%
4 3744
 
3.5%
0 3738
 
3.5%
9 3438
 
3.2%
Other values (11) 9854
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146019
57.4%
ASCII 108163
42.6%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42764
39.5%
1 12089
 
11.2%
2 8957
 
8.3%
- 8333
 
7.7%
3 5669
 
5.2%
6 4691
 
4.3%
5 4133
 
3.8%
4 3744
 
3.5%
0 3738
 
3.5%
9 3438
 
3.2%
Other values (52) 10607
 
9.8%
Hangul
ValueCountFrequency (%)
20374
14.0%
13928
 
9.5%
10129
 
6.9%
10114
 
6.9%
10063
 
6.9%
10009
 
6.9%
10002
 
6.8%
9995
 
6.8%
8951
 
6.1%
6828
 
4.7%
Other values (345) 35626
24.4%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%

도로명주소
Text

MISSING 

Distinct4923
Distinct (%)88.4%
Missing4428
Missing (%)44.3%
Memory size156.2 KiB
2024-05-11T01:09:54.039070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length65
Mean length34.18916
Min length22

Characters and Unicode

Total characters190502
Distinct characters406
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

Unique4435 ?
Unique (%)79.6%

Sample

1st row서울특별시 성동구 행당로11길 4, 1층 (행당동)
2nd row서울특별시 성동구 독서당로 166 (옥수동,성원상떼뷰 비101호)
3rd row서울특별시 성동구 무학로14길 6-11, 1층 (홍익동)
4th row서울특별시 성동구 무학로8길 29, 1층 (홍익동)
5th row서울특별시 성동구 아차산로7길 36, 1층 1-5호 (성수동2가)
ValueCountFrequency (%)
서울특별시 5572
 
15.5%
성동구 5572
 
15.5%
1층 2376
 
6.6%
성수동2가 1242
 
3.5%
성수동1가 936
 
2.6%
행당동 686
 
1.9%
2층 435
 
1.2%
지상1층 377
 
1.0%
왕십리로 353
 
1.0%
하왕십리동 274
 
0.8%
Other values (2898) 18147
50.5%
2024-05-11T01:09:55.190246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30413
 
16.0%
12103
 
6.4%
1 12012
 
6.3%
8978
 
4.7%
, 6269
 
3.3%
6210
 
3.3%
( 6110
 
3.2%
) 6109
 
3.2%
2 5980
 
3.1%
5955
 
3.1%
Other values (396) 90363
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106637
56.0%
Decimal Number 32554
 
17.1%
Space Separator 30413
 
16.0%
Other Punctuation 6285
 
3.3%
Open Punctuation 6110
 
3.2%
Close Punctuation 6109
 
3.2%
Dash Punctuation 1685
 
0.9%
Uppercase Letter 577
 
0.3%
Lowercase Letter 90
 
< 0.1%
Math Symbol 39
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12103
 
11.3%
8978
 
8.4%
6210
 
5.8%
5955
 
5.6%
5669
 
5.3%
5617
 
5.3%
5580
 
5.2%
5572
 
5.2%
4770
 
4.5%
3740
 
3.5%
Other values (335) 42443
39.8%
Uppercase Letter
ValueCountFrequency (%)
B 169
29.3%
A 65
 
11.3%
I 44
 
7.6%
R 39
 
6.8%
T 36
 
6.2%
C 26
 
4.5%
S 25
 
4.3%
K 25
 
4.3%
J 22
 
3.8%
E 22
 
3.8%
Other values (13) 104
18.0%
Lowercase Letter
ValueCountFrequency (%)
e 19
21.1%
o 17
18.9%
r 15
16.7%
w 11
12.2%
t 5
 
5.6%
l 4
 
4.4%
i 3
 
3.3%
n 2
 
2.2%
s 2
 
2.2%
z 2
 
2.2%
Other values (6) 10
11.1%
Decimal Number
ValueCountFrequency (%)
1 12012
36.9%
2 5980
18.4%
3 2884
 
8.9%
0 2329
 
7.2%
4 2260
 
6.9%
7 1650
 
5.1%
5 1636
 
5.0%
6 1442
 
4.4%
8 1202
 
3.7%
9 1159
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 6269
99.7%
@ 6
 
0.1%
. 6
 
0.1%
? 3
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
30413
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1685
100.0%
Math Symbol
ValueCountFrequency (%)
~ 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106637
56.0%
Common 83195
43.7%
Latin 670
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12103
 
11.3%
8978
 
8.4%
6210
 
5.8%
5955
 
5.6%
5669
 
5.3%
5617
 
5.3%
5580
 
5.2%
5572
 
5.2%
4770
 
4.5%
3740
 
3.5%
Other values (335) 42443
39.8%
Latin
ValueCountFrequency (%)
B 169
25.2%
A 65
 
9.7%
I 44
 
6.6%
R 39
 
5.8%
T 36
 
5.4%
C 26
 
3.9%
S 25
 
3.7%
K 25
 
3.7%
J 22
 
3.3%
E 22
 
3.3%
Other values (31) 197
29.4%
Common
ValueCountFrequency (%)
30413
36.6%
1 12012
 
14.4%
, 6269
 
7.5%
( 6110
 
7.3%
) 6109
 
7.3%
2 5980
 
7.2%
3 2884
 
3.5%
0 2329
 
2.8%
4 2260
 
2.7%
- 1685
 
2.0%
Other values (10) 7144
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106637
56.0%
ASCII 83862
44.0%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30413
36.3%
1 12012
 
14.3%
, 6269
 
7.5%
( 6110
 
7.3%
) 6109
 
7.3%
2 5980
 
7.1%
3 2884
 
3.4%
0 2329
 
2.8%
4 2260
 
2.7%
- 1685
 
2.0%
Other values (49) 7811
 
9.3%
Hangul
ValueCountFrequency (%)
12103
 
11.3%
8978
 
8.4%
6210
 
5.8%
5955
 
5.6%
5669
 
5.3%
5617
 
5.3%
5580
 
5.2%
5572
 
5.2%
4770
 
4.5%
3740
 
3.5%
Other values (335) 42443
39.8%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)1.9%
Missing4522
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean4758.4693
Minimum4700
Maximum4808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:09:55.687570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4704
Q14726
median4768
Q34783
95-th percentile4804
Maximum4808
Range108
Interquartile range (IQR)57

Descriptive statistics

Standard deviation32.85029
Coefficient of variation (CV)0.0069035414
Kurtosis-1.2293917
Mean4758.4693
Median Absolute Deviation (MAD)24
Skewness-0.37088666
Sum26066895
Variance1079.1416
MonotonicityNot monotonic
2024-05-11T01:09:56.172944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4760 269
 
2.7%
4778 234
 
2.3%
4782 230
 
2.3%
4768 221
 
2.2%
4775 154
 
1.5%
4709 148
 
1.5%
4781 148
 
1.5%
4714 135
 
1.4%
4804 133
 
1.3%
4700 115
 
1.1%
Other values (95) 3691
36.9%
(Missing) 4522
45.2%
ValueCountFrequency (%)
4700 115
1.1%
4701 93
0.9%
4702 31
 
0.3%
4703 7
 
0.1%
4704 36
 
0.4%
4705 31
 
0.3%
4706 21
 
0.2%
4707 78
0.8%
4708 93
0.9%
4709 148
1.5%
ValueCountFrequency (%)
4808 53
 
0.5%
4807 1
 
< 0.1%
4806 2
 
< 0.1%
4805 105
1.1%
4804 133
1.3%
4803 20
 
0.2%
4802 14
 
0.1%
4801 99
1.0%
4800 20
 
0.2%
4799 115
1.1%
Distinct8701
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T01:09:56.855184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length36
Mean length5.7616
Min length1

Characters and Unicode

Total characters57616
Distinct characters1117
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7978 ?
Unique (%)79.8%

Sample

1st row깐부치킨 행당역점
2nd row한우촌막창
3rd row파필라팝
4th row5호선소주그리고호프
5th row돌가마식당
ValueCountFrequency (%)
성수점 125
 
1.0%
왕십리점 98
 
0.8%
한양대점 63
 
0.5%
성수 62
 
0.5%
전주식당 33
 
0.3%
금호점 30
 
0.2%
서울숲점 30
 
0.2%
행당점 28
 
0.2%
카페 27
 
0.2%
주식회사 27
 
0.2%
Other values (9485) 11719
95.7%
2024-05-11T01:09:58.285065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2249
 
3.9%
1535
 
2.7%
1227
 
2.1%
1132
 
2.0%
1087
 
1.9%
1038
 
1.8%
888
 
1.5%
853
 
1.5%
690
 
1.2%
) 683
 
1.2%
Other values (1107) 46234
80.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49360
85.7%
Space Separator 2249
 
3.9%
Uppercase Letter 2019
 
3.5%
Lowercase Letter 1819
 
3.2%
Close Punctuation 683
 
1.2%
Open Punctuation 681
 
1.2%
Decimal Number 598
 
1.0%
Other Punctuation 180
 
0.3%
Dash Punctuation 14
 
< 0.1%
Modifier Symbol 6
 
< 0.1%
Other values (5) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1535
 
3.1%
1227
 
2.5%
1132
 
2.3%
1087
 
2.2%
1038
 
2.1%
888
 
1.8%
853
 
1.7%
690
 
1.4%
620
 
1.3%
583
 
1.2%
Other values (1024) 39707
80.4%
Lowercase Letter
ValueCountFrequency (%)
e 271
14.9%
o 190
 
10.4%
a 155
 
8.5%
r 133
 
7.3%
i 118
 
6.5%
n 112
 
6.2%
t 110
 
6.0%
s 102
 
5.6%
l 85
 
4.7%
h 59
 
3.2%
Other values (16) 484
26.6%
Uppercase Letter
ValueCountFrequency (%)
E 175
 
8.7%
A 175
 
8.7%
O 159
 
7.9%
T 117
 
5.8%
N 115
 
5.7%
S 115
 
5.7%
L 111
 
5.5%
B 106
 
5.3%
C 101
 
5.0%
R 91
 
4.5%
Other values (16) 754
37.3%
Other Punctuation
ValueCountFrequency (%)
& 58
32.2%
. 48
26.7%
, 26
14.4%
' 19
 
10.6%
! 9
 
5.0%
? 9
 
5.0%
4
 
2.2%
/ 3
 
1.7%
: 2
 
1.1%
; 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 122
20.4%
1 110
18.4%
0 82
13.7%
9 57
9.5%
7 51
8.5%
3 50
8.4%
5 46
 
7.7%
8 34
 
5.7%
4 25
 
4.2%
6 21
 
3.5%
Space Separator
ValueCountFrequency (%)
2249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 683
100.0%
Open Punctuation
ValueCountFrequency (%)
( 681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49323
85.6%
Common 4417
 
7.7%
Latin 3839
 
6.7%
Han 35
 
0.1%
Katakana 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1535
 
3.1%
1227
 
2.5%
1132
 
2.3%
1087
 
2.2%
1038
 
2.1%
888
 
1.8%
853
 
1.7%
690
 
1.4%
620
 
1.3%
583
 
1.2%
Other values (992) 39670
80.4%
Latin
ValueCountFrequency (%)
e 271
 
7.1%
o 190
 
4.9%
E 175
 
4.6%
A 175
 
4.6%
O 159
 
4.1%
a 155
 
4.0%
r 133
 
3.5%
i 118
 
3.1%
T 117
 
3.0%
N 115
 
3.0%
Other values (43) 2231
58.1%
Common
ValueCountFrequency (%)
2249
50.9%
) 683
 
15.5%
( 681
 
15.4%
2 122
 
2.8%
1 110
 
2.5%
0 82
 
1.9%
& 58
 
1.3%
9 57
 
1.3%
7 51
 
1.2%
3 50
 
1.1%
Other values (20) 274
 
6.2%
Han
ValueCountFrequency (%)
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (20) 20
57.1%
Katakana
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49319
85.6%
ASCII 8249
 
14.3%
CJK 35
 
0.1%
None 5
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Katakana 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2249
27.3%
) 683
 
8.3%
( 681
 
8.3%
e 271
 
3.3%
o 190
 
2.3%
E 175
 
2.1%
A 175
 
2.1%
O 159
 
1.9%
a 155
 
1.9%
r 133
 
1.6%
Other values (69) 3378
41.0%
Hangul
ValueCountFrequency (%)
1535
 
3.1%
1227
 
2.5%
1132
 
2.3%
1087
 
2.2%
1038
 
2.1%
888
 
1.8%
853
 
1.7%
690
 
1.4%
620
 
1.3%
583
 
1.2%
Other values (989) 39666
80.4%
None
ValueCountFrequency (%)
4
80.0%
° 1
 
20.0%
CJK
ValueCountFrequency (%)
3
 
8.6%
2
 
5.7%
2
 
5.7%
2
 
5.7%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (20) 20
57.1%
Compat Jamo
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6864
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-03-10 00:00:00
Maximum2024-05-09 16:43:42
2024-05-11T01:09:58.794082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:09:59.425867image/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
6973 
U
3027 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 6973
69.7%
U 3027
30.3%

Length

2024-05-11T01:09:59.980880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:00.498110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 6973
69.7%
u 3027
30.3%
Distinct1414
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T01:10:01.489551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:10:02.055896image/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
4499 
기타
1338 
호프/통닭
876 
뷔페식
736 
경양식
671 
Other values (21)
1880 

Length

Max length15
Median length2
Mean length2.7795
Min length2

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row통닭(치킨)
2nd row한식
3rd row분식
4th row뷔페식
5th row한식

Common Values

ValueCountFrequency (%)
한식 4499
45.0%
기타 1338
 
13.4%
호프/통닭 876
 
8.8%
뷔페식 736
 
7.4%
경양식 671
 
6.7%
분식 470
 
4.7%
일식 327
 
3.3%
중국식 319
 
3.2%
통닭(치킨) 205
 
2.1%
까페 134
 
1.3%
Other values (16) 425
 
4.2%

Length

2024-05-11T01:10:02.555370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4499
45.0%
기타 1338
 
13.4%
호프/통닭 876
 
8.8%
뷔페식 736
 
7.4%
경양식 671
 
6.7%
분식 470
 
4.7%
일식 327
 
3.3%
중국식 319
 
3.2%
통닭(치킨 205
 
2.1%
까페 134
 
1.3%
Other values (16) 425
 
4.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3673
Distinct (%)38.8%
Missing536
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean203625.87
Minimum200812.99
Maximum206382.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:10:03.000154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200812.99
5-th percentile201622.88
Q1202702.37
median203674.93
Q3204679.81
95-th percentile205579.59
Maximum206382.16
Range5569.1651
Interquartile range (IQR)1977.4378

Descriptive statistics

Standard deviation1236.193
Coefficient of variation (CV)0.0060709035
Kurtosis-0.89325587
Mean203625.87
Median Absolute Deviation (MAD)995.14997
Skewness-0.15796221
Sum1.9271152 × 109
Variance1528173.1
MonotonicityNot monotonic
2024-05-11T01:10:03.612988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205784.868811814 105
 
1.1%
202113.869605464 101
 
1.0%
202372.912023599 72
 
0.7%
203512.949927348 56
 
0.6%
203292.151898869 51
 
0.5%
203017.021457357 43
 
0.4%
202511.142930696 42
 
0.4%
203321.562330114 39
 
0.4%
204848.299601913 25
 
0.2%
205167.535545926 24
 
0.2%
Other values (3663) 8906
89.1%
(Missing) 536
 
5.4%
ValueCountFrequency (%)
200812.992681398 3
< 0.1%
200851.500793699 2
 
< 0.1%
200881.613384356 1
 
< 0.1%
200886.870660767 1
 
< 0.1%
200896.532906303 6
0.1%
200901.882621053 2
 
< 0.1%
200906.190812824 2
 
< 0.1%
200913.361072125 4
< 0.1%
200935.024540138 2
 
< 0.1%
200936.792076121 1
 
< 0.1%
ValueCountFrequency (%)
206382.157826605 1
 
< 0.1%
206314.71632058 1
 
< 0.1%
206311.197916136 3
< 0.1%
206281.078197048 2
< 0.1%
206267.144320265 4
< 0.1%
206244.726769207 2
< 0.1%
206243.875021499 1
 
< 0.1%
206231.067970479 2
< 0.1%
206209.280864162 1
 
< 0.1%
206194.671177891 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3673
Distinct (%)38.8%
Missing536
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean450081.29
Minimum448074.6
Maximum452138.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:10:04.121648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448074.6
5-th percentile448426.66
Q1449265.12
median449783.46
Q3451042.22
95-th percentile451670.71
Maximum452138.17
Range4063.5722
Interquartile range (IQR)1777.1004

Descriptive statistics

Standard deviation1070.4244
Coefficient of variation (CV)0.0023782913
Kurtosis-1.2783908
Mean450081.29
Median Absolute Deviation (MAD)953.68909
Skewness0.080544636
Sum4.2595693 × 109
Variance1145808.5
MonotonicityNot monotonic
2024-05-11T01:10:04.643620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450883.524006222 105
 
1.1%
451897.581865192 101
 
1.0%
451536.680876573 72
 
0.7%
450799.537553394 56
 
0.6%
451267.730901002 51
 
0.5%
451346.281102634 43
 
0.4%
450401.303715561 42
 
0.4%
451001.868687869 39
 
0.4%
449551.236385759 25
 
0.2%
448920.682564138 24
 
0.2%
Other values (3663) 8906
89.1%
(Missing) 536
 
5.4%
ValueCountFrequency (%)
448074.599156032 1
 
< 0.1%
448087.759178142 2
 
< 0.1%
448099.758846759 1
 
< 0.1%
448126.232831252 1
 
< 0.1%
448169.308636228 7
0.1%
448175.694252303 1
 
< 0.1%
448181.187548779 2
 
< 0.1%
448196.044738964 3
< 0.1%
448202.293163154 1
 
< 0.1%
448207.483556232 1
 
< 0.1%
ValueCountFrequency (%)
452138.17136839 2
 
< 0.1%
452135.290338411 13
0.1%
452132.575043363 1
 
< 0.1%
452130.256229522 1
 
< 0.1%
452127.749317533 2
 
< 0.1%
452126.951366987 3
 
< 0.1%
452121.007853106 2
 
< 0.1%
452116.187204484 1
 
< 0.1%
452113.850073968 2
 
< 0.1%
452108.522149464 1
 
< 0.1%

위생업태명
Categorical

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
3779 
<NA>
2079 
호프/통닭
774 
뷔페식
733 
기타
602 
Other values (20)
2033 

Length

Max length15
Median length2
Mean length3.0522
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 3779
37.8%
<NA> 2079
20.8%
호프/통닭 774
 
7.7%
뷔페식 733
 
7.3%
기타 602
 
6.0%
경양식 496
 
5.0%
분식 388
 
3.9%
중국식 275
 
2.8%
일식 256
 
2.6%
통닭(치킨) 182
 
1.8%
Other values (15) 436
 
4.4%

Length

2024-05-11T01:10:05.217367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 3779
37.8%
na 2079
20.8%
호프/통닭 774
 
7.7%
뷔페식 733
 
7.3%
기타 602
 
6.0%
경양식 496
 
5.0%
분식 388
 
3.9%
중국식 275
 
2.8%
일식 256
 
2.6%
통닭(치킨 182
 
1.8%
Other values (15) 436
 
4.4%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.2%
Missing4820
Missing (%)48.2%
Infinite0
Infinite (%)0.0%
Mean0.246139
Minimum0
Maximum93
Zeros4354
Zeros (%)43.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:10:05.581432image/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 deviation1.9058336
Coefficient of variation (CV)7.7429161
Kurtosis2166.3031
Mean0.246139
Median Absolute Deviation (MAD)0
Skewness44.626664
Sum1275
Variance3.6322017
MonotonicityNot monotonic
2024-05-11T01:10:06.017013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 4354
43.5%
1 620
 
6.2%
2 161
 
1.6%
3 35
 
0.4%
5 4
 
< 0.1%
4 3
 
< 0.1%
93 2
 
< 0.1%
10 1
 
< 0.1%
(Missing) 4820
48.2%
ValueCountFrequency (%)
0 4354
43.5%
1 620
 
6.2%
2 161
 
1.6%
3 35
 
0.4%
4 3
 
< 0.1%
5 4
 
< 0.1%
10 1
 
< 0.1%
93 2
 
< 0.1%
ValueCountFrequency (%)
93 2
 
< 0.1%
10 1
 
< 0.1%
5 4
 
< 0.1%
4 3
 
< 0.1%
3 35
 
0.4%
2 161
 
1.6%
1 620
 
6.2%
0 4354
43.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.2%
Missing4821
Missing (%)48.2%
Infinite0
Infinite (%)0.0%
Mean0.32960031
Minimum0
Maximum20
Zeros3986
Zeros (%)39.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:10:06.380513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.73566804
Coefficient of variation (CV)2.2320005
Kurtosis106.0095
Mean0.32960031
Median Absolute Deviation (MAD)0
Skewness5.8134975
Sum1707
Variance0.54120747
MonotonicityNot monotonic
2024-05-11T01:10:06.849595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 3986
39.9%
1 789
 
7.9%
2 339
 
3.4%
3 49
 
0.5%
4 9
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
8 1
 
< 0.1%
20 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 4821
48.2%
ValueCountFrequency (%)
0 3986
39.9%
1 789
 
7.9%
2 339
 
3.4%
3 49
 
0.5%
4 9
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
4 9
 
0.1%
3 49
 
0.5%
2 339
 
3.4%
1 789
 
7.9%
0 3986
39.9%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5545 
주택가주변
2272 
기타
1887 
아파트지역
 
112
학교정화(상대)
 
78
Other values (3)
 
106

Length

Max length8
Median length4
Mean length3.9324
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5545
55.5%
주택가주변 2272
22.7%
기타 1887
 
18.9%
아파트지역 112
 
1.1%
학교정화(상대) 78
 
0.8%
유흥업소밀집지역 67
 
0.7%
결혼예식장주변 22
 
0.2%
학교정화(절대) 17
 
0.2%

Length

2024-05-11T01:10:07.324254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:07.732918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5545
55.5%
주택가주변 2272
22.7%
기타 1887
 
18.9%
아파트지역 112
 
1.1%
학교정화(상대 78
 
0.8%
유흥업소밀집지역 67
 
0.7%
결혼예식장주변 22
 
0.2%
학교정화(절대 17
 
0.2%

등급구분명
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6001 
기타
2754 
 
544
지도
 
480
자율
 
191
Other values (2)
 
30

Length

Max length4
Median length4
Mean length3.1431
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6001
60.0%
기타 2754
27.5%
544
 
5.4%
지도 480
 
4.8%
자율 191
 
1.9%
27
 
0.3%
우수 3
 
< 0.1%

Length

2024-05-11T01:10:08.238883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:08.630525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6001
60.0%
기타 2754
27.5%
544
 
5.4%
지도 480
 
4.8%
자율 191
 
1.9%
27
 
0.3%
우수 3
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5115 
상수도전용
4879 
상수도(음용)지하수(주방용)겸용
 
6

Length

Max length17
Median length4
Mean length4.4957
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5115
51.1%
상수도전용 4879
48.8%
상수도(음용)지하수(주방용)겸용 6
 
0.1%

Length

2024-05-11T01:10:09.100639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:09.513734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5115
51.1%
상수도전용 4879
48.8%
상수도(음용)지하수(주방용)겸용 6
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9624 
0
 
376

Length

Max length4
Median length4
Mean length3.8872
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> 9624
96.2%
0 376
 
3.8%

Length

2024-05-11T01:10:09.928066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:10.233069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9624
96.2%
0 376
 
3.8%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:10.831944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:11.215365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:11.603536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:11.980847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:12.468272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:12.813013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:13.172196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:13.555030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

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>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:13.999011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:14.308802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9623 
0
 
377

Length

Max length4
Median length4
Mean length3.8869
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> 9623
96.2%
0 377
 
3.8%

Length

2024-05-11T01:10:14.739896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:15.177883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9623
96.2%
0 377
 
3.8%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing2079
Missing (%)20.8%
Memory size97.7 KiB
False
7743 
True
 
178
(Missing)
2079 
ValueCountFrequency (%)
False 7743
77.4%
True 178
 
1.8%
(Missing) 2079
 
20.8%
2024-05-11T01:10:15.573600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct4149
Distinct (%)52.4%
Missing2079
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean56.664084
Minimum0
Maximum2874.37
Zeros119
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T01:10:16.141404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.05
Q123.61
median36.48
Q366
95-th percentile148.8
Maximum2874.37
Range2874.37
Interquartile range (IQR)42.39

Descriptive statistics

Standard deviation77.992443
Coefficient of variation (CV)1.3764
Kurtosis298.62975
Mean56.664084
Median Absolute Deviation (MAD)16.88
Skewness12.178837
Sum448836.21
Variance6082.8212
MonotonicityNot monotonic
2024-05-11T01:10:16.935744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 119
 
1.2%
33.0 83
 
0.8%
30.0 46
 
0.5%
26.4 39
 
0.4%
27.0 37
 
0.4%
15.0 35
 
0.4%
20.0 35
 
0.4%
24.0 35
 
0.4%
23.1 32
 
0.3%
25.0 29
 
0.3%
Other values (4139) 7431
74.3%
(Missing) 2079
 
20.8%
ValueCountFrequency (%)
0.0 119
1.2%
2.42 1
 
< 0.1%
3.0 1
 
< 0.1%
4.0 1
 
< 0.1%
4.2 1
 
< 0.1%
4.93 1
 
< 0.1%
4.95 1
 
< 0.1%
4.96 1
 
< 0.1%
5.0 1
 
< 0.1%
5.2 1
 
< 0.1%
ValueCountFrequency (%)
2874.37 1
< 0.1%
1744.39 1
< 0.1%
1553.77 1
< 0.1%
1336.06 1
< 0.1%
1242.0 1
< 0.1%
1071.33 1
< 0.1%
1063.55 1
< 0.1%
1004.19 1
< 0.1%
958.0 1
< 0.1%
922.51 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9997 
2400
 
1
2419
 
1
2396
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9997
> 99.9%
2400 1
 
< 0.1%
2419 1
 
< 0.1%
2396 1
 
< 0.1%

Length

2024-05-11T01:10:17.419918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:17.819189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9997
> 99.9%
2400 1
 
< 0.1%
2419 1
 
< 0.1%
2396 1
 
< 0.1%

전통업소주된음식
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
7
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9999
> 99.9%
7 1
 
< 0.1%

Length

2024-05-11T01:10:18.248548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:10:18.762576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
7 1
 
< 0.1%

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
943530300003030000-101-2014-001052014-04-23<NA>3폐업2폐업2023-03-06<NA><NA><NA>0222977792102.00133-868서울특별시 성동구 행당동 317-85서울특별시 성동구 행당로11길 4, 1층 (행당동)4714깐부치킨 행당역점2023-03-06 09:11:21U2022-12-03 00:08:00.0통닭(치킨)202652.241386450659.356016<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406130300003030000-101-1997-0449119971001<NA>3폐업2폐업19981215<NA><NA><NA>02 212036055.87133847서울특별시 성동구 용답동 4-13번지<NA><NA>한우촌막창2001-09-25 00:00:00I2018-08-31 23:59:59.0한식204703.606389451370.151136한식<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.87<NA><NA><NA>
694730300003030000-101-2004-0023420040816<NA>3폐업2폐업20160824<NA><NA><NA>2299004464.50133844서울특별시 성동구 옥수동 475번지 성원상떼뷰 비101호서울특별시 성동구 독서당로 166 (옥수동,성원상떼뷰 비101호)4736파필라팝2016-08-24 17:16:40I2018-08-31 23:59:59.0분식200967.537033448709.190493분식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N64.5<NA><NA><NA>
431430300003030000-101-1998-0154819980603<NA>3폐업2폐업20001116<NA><NA><NA>0291.37133815서울특별시 성동구 마장동 772-4번지<NA><NA>5호선소주그리고호프2001-10-25 00:00:00I2018-08-31 23:59:59.0뷔페식203727.54121451575.016071뷔페식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.37<NA><NA><NA>
491730300003030000-101-1999-0613719990731<NA>3폐업2폐업20011009<NA><NA><NA>02 469279133.00133820서울특별시 성동구 성수동1가 563번지<NA><NA>돌가마식당2001-11-06 00:00:00I2018-08-31 23:59:59.0한식203926.374149448594.469961한식00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.0<NA><NA><NA>
1205130300003030000-101-2020-003402020-08-12<NA>1영업/정상1영업<NA><NA><NA><NA>022299133339.67133-881서울특별시 성동구 홍익동 429서울특별시 성동구 무학로14길 6-11, 1층 (홍익동)4706대도식당2023-09-13 11:38:25U2022-12-08 23:05:00.0한식202656.120169451690.619042<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
785530300003030000-101-2008-0000520080111<NA>3폐업2폐업20100611<NA><NA><NA><NA>30.44133858서울특별시 성동구 하왕십리동 979-10번지 지상1층<NA><NA>썬더치킨2008-04-03 14:14:01I2018-08-31 23:59:59.0통닭(치킨)202573.720836450934.133995통닭(치킨)<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N30.44<NA><NA><NA>
1410930300003030000-101-2024-001792024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>59.57133-880서울특별시 성동구 홍익동 246서울특별시 성동구 무학로8길 29, 1층 (홍익동)4708수스수2024-05-08 11:20:16I2023-12-04 23:00:00.0기타202949.094146451465.226522<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
861130300003030000-101-2011-000762011-04-22<NA>3폐업2폐업2023-03-31<NA><NA><NA>00020464004450.76133-834서울특별시 성동구 성수동2가 289-39서울특별시 성동구 아차산로7길 36, 1층 1-5호 (성수동2가)4795옛날순대국2023-03-31 10:44:21U2022-12-04 00:02:00.0한식204848.299602449551.236386<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
161930300003030000-101-1991-0321819910401<NA>3폐업2폐업20121025<NA><NA><NA>02 2295200093.10133858서울특별시 성동구 하왕십리동 966-26번지<NA><NA>만다생2007-07-16 20:38:17I2018-08-31 23:59:59.0일식202859.66366451069.554753일식22주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N93.1<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
862430300003030000-101-2011-0008920110517<NA>3폐업2폐업20150526<NA><NA><NA><NA>33.00133050서울특별시 성동구 마장동 439-1번지 청계참숯가마사우나내 지하1층서울특별시 성동구 마장로35길 68 (마장동,청계참숯가마사우나내 지하1층)4752청계식당2011-05-17 13:42:43I2018-08-31 23:59:59.0한식203576.594692452041.559037한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N33.0<NA><NA><NA>
669330300003030000-101-2003-0037220031211<NA>3폐업2폐업20081231<NA><NA><NA>22825985186.25133856서울특별시 성동구 하왕십리동 827-1번지 외 5필지<NA><NA>뒷골목아구통2003-12-11 00:00:00I2018-08-31 23:59:59.0한식202274.820885451492.169638한식00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N186.25<NA><NA><NA>
620130300003030000-101-2002-0035720020910<NA>3폐업2폐업20080304<NA><NA><NA><NA>20.98133809서울특별시 성동구 금호동4가 505-2번지<NA><NA>준호프2002-09-10 00:00:00I2018-08-31 23:59:59.0호프/통닭202032.077006449516.371117호프/통닭00주택가주변<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N20.98<NA><NA><NA>
53230300003030000-101-1984-0310319840425<NA>3폐업2폐업19891107<NA><NA><NA>02 0000029.24133924서울특별시 성동구 성수동1가 656-968번지<NA><NA>맛또와분식2001-09-25 00:00:00I2018-08-31 23:59:59.0뷔페식203895.448795449401.289889뷔페식11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N29.24<NA><NA><NA>
688330300003030000-101-2004-0017020040614<NA>3폐업2폐업20091221<NA><NA><NA>00022299197224.04133872서울특별시 성동구 행당동 297-6번지 (지상1층)<NA><NA>옹켈피자2008-03-25 11:00:28I2018-08-31 23:59:59.0패스트푸드202677.097144450835.144512패스트푸드00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N24.04<NA><NA><NA>
914430300003030000-101-2013-0010520130603<NA>1영업/정상1영업<NA><NA><NA><NA><NA>55.72133866서울특별시 성동구 행당동 168-200번지 왕십리민자역사(enter-6) 지상4층서울특별시 성동구 왕십리광장로 17, 지상4층 (행당동, 왕십리민자역사(enter-6))4750아폴로(보글보글밥상)2014-04-16 11:20:12I2018-08-31 23:59:59.0한식203292.151899451267.730901한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N55.72<NA><NA><NA>
1094830300003030000-101-2018-0013220180502<NA>3폐업2폐업20200605<NA><NA><NA><NA>158.05133834서울특별시 성동구 성수동2가 289-14번지서울특별시 성동구 성수일로8길 39, 국민프린텍 2층 201호 (성수동2가)4794샤브퐁2020-06-05 16:48:08U2020-06-07 02:40:00.0한식204772.717086449279.670825한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y158.05<NA><NA><NA>
131130300003030000-101-1990-0146219900725<NA>3폐업2폐업19931130<NA><NA><NA>02 292481778.96133862서울특별시 성동구 행당동 32-6번지<NA><NA>로저스코리아2001-09-25 00:00:00I2018-08-31 23:59:59.0뷔페식203680.207589450527.658541뷔페식16학교정화(절대)지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.96<NA><NA><NA>
1202430300003030000-101-2020-0031320200731<NA>1영업/정상1영업<NA><NA><NA><NA><NA>148.50133800서울특별시 성동구 금호동1가 172서울특별시 성동구 난계로 35, 2층 (금호동1가)4727신의주찹쌀순대(금호점)2020-08-28 10:41:27U2020-08-30 02:40:00.0한식202101.398694450358.716766한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N148.5<NA><NA><NA>
715930300003030000-101-2005-0008720050429<NA>1영업/정상1영업<NA><NA><NA><NA>022294247386.10133866서울특별시 성동구 행당동 168-9 (지상1층)서울특별시 성동구 고산자로14길 12-1 (행당동,(지상1층))4750거창식당2021-12-30 14:21:29U2022-01-01 02:40:00.0한식203226.620308451102.920448한식00<NA><NA><NA>00000<NA>00N86.1<NA><NA><NA>