Overview

Dataset statistics

Number of variables44
Number of observations3442
Missing cells36863
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory377.0 B

Variable types

Categorical19
Text6
DateTime4
Unsupported8
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-18680/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (61.0%)Imbalance
등급구분명 is highly imbalanced (54.8%)Imbalance
급수시설구분명 is highly imbalanced (55.7%)Imbalance
총인원 is highly imbalanced (75.7%)Imbalance
본사종업원수 is highly imbalanced (75.3%)Imbalance
공장사무직종업원수 is highly imbalanced (75.3%)Imbalance
공장판매직종업원수 is highly imbalanced (75.3%)Imbalance
공장생산직종업원수 is highly imbalanced (75.3%)Imbalance
보증액 is highly imbalanced (75.3%)Imbalance
월세액 is highly imbalanced (75.3%)Imbalance
다중이용업소여부 is highly imbalanced (92.7%)Imbalance
인허가취소일자 has 3442 (100.0%) missing valuesMissing
폐업일자 has 1068 (31.0%) missing valuesMissing
휴업시작일자 has 3442 (100.0%) missing valuesMissing
휴업종료일자 has 3442 (100.0%) missing valuesMissing
재개업일자 has 3442 (100.0%) missing valuesMissing
전화번호 has 1662 (48.3%) missing valuesMissing
소재지면적 has 57 (1.7%) missing valuesMissing
도로명주소 has 1091 (31.7%) missing valuesMissing
도로명우편번호 has 1152 (33.5%) missing valuesMissing
좌표정보(X) has 129 (3.7%) missing valuesMissing
좌표정보(Y) has 129 (3.7%) missing valuesMissing
남성종사자수 has 2361 (68.6%) missing valuesMissing
건물소유구분명 has 3442 (100.0%) missing valuesMissing
다중이용업소여부 has 838 (24.3%) missing valuesMissing
시설총규모 has 838 (24.3%) missing valuesMissing
전통업소지정번호 has 3442 (100.0%) missing valuesMissing
전통업소주된음식 has 3442 (100.0%) missing valuesMissing
홈페이지 has 3442 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 985 (28.6%) zerosZeros
시설총규모 has 56 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:05:36.921221
Analysis finished2024-05-11 06:05:38.618180
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
3030000
3442 

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 3442
100.0%

Length

2024-05-11T15:05:38.691076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:38.808493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 3442
100.0%

관리번호
Text

UNIQUE 

Distinct3442
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2024-05-11T15:05:39.021973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters75724
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

Unique3442 ?
Unique (%)100.0%

Sample

1st row3030000-104-1974-00318
2nd row3030000-104-1974-00379
3rd row3030000-104-1974-00549
4th row3030000-104-1974-00572
5th row3030000-104-1974-00575
ValueCountFrequency (%)
3030000-104-1974-00318 1
 
< 0.1%
3030000-104-2017-00173 1
 
< 0.1%
3030000-104-2018-00017 1
 
< 0.1%
3030000-104-2017-00176 1
 
< 0.1%
3030000-104-2017-00177 1
 
< 0.1%
3030000-104-2017-00178 1
 
< 0.1%
3030000-104-2017-00179 1
 
< 0.1%
3030000-104-2017-00180 1
 
< 0.1%
3030000-104-2017-00181 1
 
< 0.1%
3030000-104-2017-00182 1
 
< 0.1%
Other values (3432) 3432
99.7%
2024-05-11T15:05:39.469321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33666
44.5%
- 10326
 
13.6%
3 8147
 
10.8%
1 7549
 
10.0%
2 4659
 
6.2%
4 4634
 
6.1%
9 1983
 
2.6%
8 1366
 
1.8%
6 1222
 
1.6%
7 1120
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65398
86.4%
Dash Punctuation 10326
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33666
51.5%
3 8147
 
12.5%
1 7549
 
11.5%
2 4659
 
7.1%
4 4634
 
7.1%
9 1983
 
3.0%
8 1366
 
2.1%
6 1222
 
1.9%
7 1120
 
1.7%
5 1052
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 10326
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 75724
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33666
44.5%
- 10326
 
13.6%
3 8147
 
10.8%
1 7549
 
10.0%
2 4659
 
6.2%
4 4634
 
6.1%
9 1983
 
2.6%
8 1366
 
1.8%
6 1222
 
1.6%
7 1120
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75724
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33666
44.5%
- 10326
 
13.6%
3 8147
 
10.8%
1 7549
 
10.0%
2 4659
 
6.2%
4 4634
 
6.1%
9 1983
 
2.6%
8 1366
 
1.8%
6 1222
 
1.6%
7 1120
 
1.5%

인허가일자
Date

Distinct2625
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
Minimum1974-03-01 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:05:39.644452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:39.831842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
3
2374 
1
1068 

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 2374
69.0%
1 1068
31.0%

Length

2024-05-11T15:05:40.057417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:40.206663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2374
69.0%
1 1068
31.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
폐업
2374 
영업/정상
1068 

Length

Max length5
Median length2
Mean length2.9308542
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2374
69.0%
영업/정상 1068
31.0%

Length

2024-05-11T15:05:40.327543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:40.432160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2374
69.0%
영업/정상 1068
31.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2
2374 
1
1068 

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 2374
69.0%
1 1068
31.0%

Length

2024-05-11T15:05:40.550539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:40.664418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2374
69.0%
1 1068
31.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
폐업
2374 
영업
1068 

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 2374
69.0%
영업 1068
31.0%

Length

2024-05-11T15:05:40.811534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:40.915697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2374
69.0%
영업 1068
31.0%

폐업일자
Date

MISSING 

Distinct1803
Distinct (%)75.9%
Missing1068
Missing (%)31.0%
Memory size27.0 KiB
Minimum1987-12-11 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:05:41.043137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:41.243271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

전화번호
Text

MISSING 

Distinct1548
Distinct (%)87.0%
Missing1662
Missing (%)48.3%
Memory size27.0 KiB
2024-05-11T15:05:41.519799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.087079
Min length2

Characters and Unicode

Total characters17955
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1484 ?
Unique (%)83.4%

Sample

1st row02 2928705
2nd row02 2925494
3rd row02
4th row02 2936713
5th row02 4653797
ValueCountFrequency (%)
02 824
31.2%
070 28
 
1.1%
00000 22
 
0.8%
000222001210 13
 
0.5%
0234081234 11
 
0.4%
0 10
 
0.4%
8
 
0.3%
467 8
 
0.3%
0269161500 6
 
0.2%
462 6
 
0.2%
Other values (1582) 1706
64.6%
2024-05-11T15:05:41.940213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4199
23.4%
0 3690
20.6%
4 1346
 
7.5%
9 1288
 
7.2%
1194
 
6.6%
6 1180
 
6.6%
1 1123
 
6.3%
3 1036
 
5.8%
8 1031
 
5.7%
7 944
 
5.3%
Other values (2) 924
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16753
93.3%
Space Separator 1194
 
6.6%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4199
25.1%
0 3690
22.0%
4 1346
 
8.0%
9 1288
 
7.7%
6 1180
 
7.0%
1 1123
 
6.7%
3 1036
 
6.2%
8 1031
 
6.2%
7 944
 
5.6%
5 916
 
5.5%
Space Separator
ValueCountFrequency (%)
1194
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17955
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4199
23.4%
0 3690
20.6%
4 1346
 
7.5%
9 1288
 
7.2%
1194
 
6.6%
6 1180
 
6.6%
1 1123
 
6.3%
3 1036
 
5.8%
8 1031
 
5.7%
7 944
 
5.3%
Other values (2) 924
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4199
23.4%
0 3690
20.6%
4 1346
 
7.5%
9 1288
 
7.2%
1194
 
6.6%
6 1180
 
6.6%
1 1123
 
6.3%
3 1036
 
5.8%
8 1031
 
5.7%
7 944
 
5.3%
Other values (2) 924
 
5.1%

소재지면적
Real number (ℝ)

MISSING 

Distinct1840
Distinct (%)54.4%
Missing57
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean46.461099
Minimum0
Maximum538.62
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:42.107053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q115
median30
Q361.62
95-th percentile133.244
Maximum538.62
Range538.62
Interquartile range (IQR)46.62

Descriptive statistics

Standard deviation50.821836
Coefficient of variation (CV)1.0938578
Kurtosis15.129861
Mean46.461099
Median Absolute Deviation (MAD)20
Skewness3.0804944
Sum157270.82
Variance2582.859
MonotonicityNot monotonic
2024-05-11T15:05:42.332283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 162
 
4.7%
6.6 79
 
2.3%
33.0 62
 
1.8%
10.0 52
 
1.5%
20.0 29
 
0.8%
9.9 29
 
0.8%
15.0 23
 
0.7%
5.0 23
 
0.7%
6.0 23
 
0.7%
16.5 23
 
0.7%
Other values (1830) 2880
83.7%
(Missing) 57
 
1.7%
ValueCountFrequency (%)
0.0 3
 
0.1%
0.49 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 11
0.3%
1.2 1
 
< 0.1%
1.4 2
 
0.1%
1.5 11
0.3%
1.8 1
 
< 0.1%
1.83 1
 
< 0.1%
ValueCountFrequency (%)
538.62 1
< 0.1%
527.78 1
< 0.1%
454.3 1
< 0.1%
409.87 1
< 0.1%
391.77 1
< 0.1%
382.94 1
< 0.1%
380.83 1
< 0.1%
380.2 1
< 0.1%
367.53 1
< 0.1%
362.77 1
< 0.1%

소재지우편번호
Text

Distinct178
Distinct (%)5.2%
Missing1
Missing (%)< 0.1%
Memory size27.0 KiB
2024-05-11T15:05:42.817368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1554781
Min length6

Characters and Unicode

Total characters21181
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

Unique25 ?
Unique (%)0.7%

Sample

1st row133852
2nd row133854
3rd row133803
4th row133010
5th row133836
ValueCountFrequency (%)
133866 186
 
5.4%
133871 136
 
4.0%
133832 111
 
3.2%
133827 110
 
3.2%
133822 100
 
2.9%
133834 85
 
2.5%
133828 84
 
2.4%
133835 78
 
2.3%
133070 74
 
2.2%
133882 68
 
2.0%
Other values (168) 2409
70.0%
2024-05-11T15:05:43.517812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 7710
36.4%
1 4124
19.5%
8 3534
16.7%
2 1245
 
5.9%
0 1024
 
4.8%
6 817
 
3.9%
7 761
 
3.6%
5 606
 
2.9%
- 535
 
2.5%
4 507
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20646
97.5%
Dash Punctuation 535
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 7710
37.3%
1 4124
20.0%
8 3534
17.1%
2 1245
 
6.0%
0 1024
 
5.0%
6 817
 
4.0%
7 761
 
3.7%
5 606
 
2.9%
4 507
 
2.5%
9 318
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21181
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 7710
36.4%
1 4124
19.5%
8 3534
16.7%
2 1245
 
5.9%
0 1024
 
4.8%
6 817
 
3.9%
7 761
 
3.6%
5 606
 
2.9%
- 535
 
2.5%
4 507
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 7710
36.4%
1 4124
19.5%
8 3534
16.7%
2 1245
 
5.9%
0 1024
 
4.8%
6 817
 
3.9%
7 761
 
3.6%
5 606
 
2.9%
- 535
 
2.5%
4 507
 
2.4%

지번주소
Text

Distinct2745
Distinct (%)79.8%
Missing1
Missing (%)< 0.1%
Memory size27.0 KiB
2024-05-11T15:05:43.970027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length47
Mean length26.211566
Min length16

Characters and Unicode

Total characters90194
Distinct characters395
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2362 ?
Unique (%)68.6%

Sample

1st row서울특별시 성동구 응봉동 200-1번지
2nd row서울특별시 성동구 하왕십리동 395-0번지
3rd row서울특별시 성동구 금호동2가 325번지
4th row서울특별시 성동구 상왕십리동 773-5번지
5th row서울특별시 성동구 송정동 66-262번지
ValueCountFrequency (%)
서울특별시 3441
21.4%
성동구 3441
21.4%
성수동2가 766
 
4.8%
행당동 749
 
4.7%
성수동1가 512
 
3.2%
지상1층 399
 
2.5%
용답동 211
 
1.3%
하왕십리동 189
 
1.2%
옥수동 151
 
0.9%
마장동 129
 
0.8%
Other values (2891) 6119
38.0%
2024-05-11T15:05:44.696109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15236
16.9%
동 7052
 
7.8%
성 4838
 
5.4%
1 4403
 
4.9%
서 3532
 
3.9%
울 3525
 
3.9%
시 3455
 
3.8%
구 3453
 
3.8%
별 3444
 
3.8%
특 3441
 
3.8%
Other values (385) 37815
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52834
58.6%
Decimal Number 18233
 
20.2%
Space Separator 15236
 
16.9%
Dash Punctuation 2767
 
3.1%
Open Punctuation 336
 
0.4%
Close Punctuation 336
 
0.4%
Uppercase Letter 273
 
0.3%
Other Punctuation 96
 
0.1%
Lowercase Letter 73
 
0.1%
Letter Number 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7052
13.3%
성 4838
 
9.2%
서 3532
 
6.7%
울 3525
 
6.7%
시 3455
 
6.5%
구 3453
 
6.5%
별 3444
 
6.5%
특 3441
 
6.5%
지 2964
 
5.6%
번 2171
 
4.1%
Other values (327) 14959
28.3%
Uppercase Letter
ValueCountFrequency (%)
B 40
14.7%
T 31
11.4%
A 29
10.6%
E 22
 
8.1%
C 18
 
6.6%
K 15
 
5.5%
I 13
 
4.8%
S 13
 
4.8%
O 12
 
4.4%
L 11
 
4.0%
Other values (14) 69
25.3%
Lowercase Letter
ValueCountFrequency (%)
e 21
28.8%
r 13
17.8%
o 8
 
11.0%
n 7
 
9.6%
t 7
 
9.6%
w 6
 
8.2%
b 3
 
4.1%
c 2
 
2.7%
h 2
 
2.7%
m 1
 
1.4%
Other values (3) 3
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 4403
24.1%
2 2976
16.3%
3 2017
11.1%
6 1677
 
9.2%
0 1365
 
7.5%
5 1358
 
7.4%
4 1189
 
6.5%
8 1174
 
6.4%
7 1110
 
6.1%
9 964
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 87
90.6%
@ 5
 
5.2%
. 2
 
2.1%
/ 2
 
2.1%
Letter Number
ValueCountFrequency (%)
Ⅲ 6
75.0%
Ⅱ 2
 
25.0%
Space Separator
ValueCountFrequency (%)
15236
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2767
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52834
58.6%
Common 37006
41.0%
Latin 354
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7052
13.3%
성 4838
 
9.2%
서 3532
 
6.7%
울 3525
 
6.7%
시 3455
 
6.5%
구 3453
 
6.5%
별 3444
 
6.5%
특 3441
 
6.5%
지 2964
 
5.6%
번 2171
 
4.1%
Other values (327) 14959
28.3%
Latin
ValueCountFrequency (%)
B 40
 
11.3%
T 31
 
8.8%
A 29
 
8.2%
E 22
 
6.2%
e 21
 
5.9%
C 18
 
5.1%
K 15
 
4.2%
r 13
 
3.7%
I 13
 
3.7%
S 13
 
3.7%
Other values (29) 139
39.3%
Common
ValueCountFrequency (%)
15236
41.2%
1 4403
 
11.9%
2 2976
 
8.0%
- 2767
 
7.5%
3 2017
 
5.5%
6 1677
 
4.5%
0 1365
 
3.7%
5 1358
 
3.7%
4 1189
 
3.2%
8 1174
 
3.2%
Other values (9) 2844
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52833
58.6%
ASCII 37352
41.4%
Number Forms 8
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15236
40.8%
1 4403
 
11.8%
2 2976
 
8.0%
- 2767
 
7.4%
3 2017
 
5.4%
6 1677
 
4.5%
0 1365
 
3.7%
5 1358
 
3.6%
4 1189
 
3.2%
8 1174
 
3.1%
Other values (46) 3190
 
8.5%
Hangul
ValueCountFrequency (%)
동 7052
13.3%
성 4838
 
9.2%
서 3532
 
6.7%
울 3525
 
6.7%
시 3455
 
6.5%
구 3453
 
6.5%
별 3444
 
6.5%
특 3441
 
6.5%
지 2964
 
5.6%
번 2171
 
4.1%
Other values (326) 14958
28.3%
Number Forms
ValueCountFrequency (%)
Ⅲ 6
75.0%
Ⅱ 2
 
25.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

도로명주소
Text

MISSING 

Distinct2086
Distinct (%)88.7%
Missing1091
Missing (%)31.7%
Memory size27.0 KiB
2024-05-11T15:05:45.490258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length58
Mean length36.061251
Min length22

Characters and Unicode

Total characters84780
Distinct characters382
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

Unique1914 ?
Unique (%)81.4%

Sample

1st row서울특별시 성동구 광나루로9길 2 (송정동)
2nd row서울특별시 성동구 광나루로 296 (성수동2가)
3rd row서울특별시 성동구 왕십리로 362 (도선동)
4th row서울특별시 성동구 독서당로 295-1 (금호동3가)
5th row서울특별시 성동구 왕십리로 296-1 (행당동,,197-1)
ValueCountFrequency (%)
서울특별시 2351
 
14.5%
성동구 2351
 
14.5%
1층 1210
 
7.4%
성수동2가 517
 
3.2%
행당동 444
 
2.7%
성수동1가 390
 
2.4%
왕십리로 279
 
1.7%
지상1층 169
 
1.0%
17 164
 
1.0%
2층 160
 
1.0%
Other values (1858) 8220
50.6%
2024-05-11T15:05:46.100843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13912
 
16.4%
1 5225
 
6.2%
동 5171
 
6.1%
성 3736
 
4.4%
, 2991
 
3.5%
서 2646
 
3.1%
울 2534
 
3.0%
2 2495
 
2.9%
) 2475
 
2.9%
( 2475
 
2.9%
Other values (372) 41120
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48177
56.8%
Space Separator 13912
 
16.4%
Decimal Number 13781
 
16.3%
Other Punctuation 2998
 
3.5%
Close Punctuation 2475
 
2.9%
Open Punctuation 2475
 
2.9%
Dash Punctuation 565
 
0.7%
Uppercase Letter 321
 
0.4%
Lowercase Letter 58
 
0.1%
Math Symbol 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5171
 
10.7%
성 3736
 
7.8%
서 2646
 
5.5%
울 2534
 
5.3%
시 2389
 
5.0%
구 2383
 
4.9%
별 2353
 
4.9%
특 2351
 
4.9%
층 2188
 
4.5%
로 1720
 
3.6%
Other values (314) 20706
43.0%
Uppercase Letter
ValueCountFrequency (%)
B 62
19.3%
A 33
10.3%
C 24
 
7.5%
L 23
 
7.2%
S 20
 
6.2%
T 20
 
6.2%
R 19
 
5.9%
I 18
 
5.6%
E 14
 
4.4%
J 12
 
3.7%
Other values (13) 76
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 15
25.9%
r 10
17.2%
o 8
13.8%
w 6
 
10.3%
t 4
 
6.9%
n 4
 
6.9%
h 2
 
3.4%
c 2
 
3.4%
b 2
 
3.4%
m 2
 
3.4%
Other values (3) 3
 
5.2%
Decimal Number
ValueCountFrequency (%)
1 5225
37.9%
2 2495
18.1%
3 1181
 
8.6%
0 1135
 
8.2%
4 928
 
6.7%
7 724
 
5.3%
5 604
 
4.4%
6 526
 
3.8%
9 492
 
3.6%
8 471
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 2991
99.8%
. 3
 
0.1%
? 2
 
0.1%
@ 1
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅲ 6
85.7%
Ⅱ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
13912
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2475
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2475
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 565
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48177
56.8%
Common 36217
42.7%
Latin 386
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5171
 
10.7%
성 3736
 
7.8%
서 2646
 
5.5%
울 2534
 
5.3%
시 2389
 
5.0%
구 2383
 
4.9%
별 2353
 
4.9%
특 2351
 
4.9%
층 2188
 
4.5%
로 1720
 
3.6%
Other values (314) 20706
43.0%
Latin
ValueCountFrequency (%)
B 62
16.1%
A 33
 
8.5%
C 24
 
6.2%
L 23
 
6.0%
S 20
 
5.2%
T 20
 
5.2%
R 19
 
4.9%
I 18
 
4.7%
e 15
 
3.9%
E 14
 
3.6%
Other values (28) 138
35.8%
Common
ValueCountFrequency (%)
13912
38.4%
1 5225
 
14.4%
, 2991
 
8.3%
2 2495
 
6.9%
) 2475
 
6.8%
( 2475
 
6.8%
3 1181
 
3.3%
0 1135
 
3.1%
4 928
 
2.6%
7 724
 
2.0%
Other values (10) 2676
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48177
56.8%
ASCII 36596
43.2%
Number Forms 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13912
38.0%
1 5225
 
14.3%
, 2991
 
8.2%
2 2495
 
6.8%
) 2475
 
6.8%
( 2475
 
6.8%
3 1181
 
3.2%
0 1135
 
3.1%
4 928
 
2.5%
7 724
 
2.0%
Other values (46) 3055
 
8.3%
Hangul
ValueCountFrequency (%)
동 5171
 
10.7%
성 3736
 
7.8%
서 2646
 
5.5%
울 2534
 
5.3%
시 2389
 
5.0%
구 2383
 
4.9%
별 2353
 
4.9%
특 2351
 
4.9%
층 2188
 
4.5%
로 1720
 
3.6%
Other values (314) 20706
43.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 6
85.7%
Ⅱ 1
 
14.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct103
Distinct (%)4.5%
Missing1152
Missing (%)33.5%
Infinite0
Infinite (%)0.0%
Mean4758.1323
Minimum4700
Maximum4808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:46.338702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4700
5-th percentile4704
Q14730
median4764
Q34782
95-th percentile4801
Maximum4808
Range108
Interquartile range (IQR)52

Descriptive statistics

Standard deviation31.531596
Coefficient of variation (CV)0.0066268851
Kurtosis-1.1307409
Mean4758.1323
Median Absolute Deviation (MAD)24.5
Skewness-0.35247015
Sum10896123
Variance994.24155
MonotonicityNot monotonic
2024-05-11T15:05:46.593684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4750 134
 
3.9%
4781 114
 
3.3%
4778 82
 
2.4%
4768 78
 
2.3%
4782 73
 
2.1%
4760 61
 
1.8%
4701 61
 
1.8%
4763 56
 
1.6%
4799 53
 
1.5%
4790 51
 
1.5%
Other values (93) 1527
44.4%
(Missing) 1152
33.5%
ValueCountFrequency (%)
4700 34
1.0%
4701 61
1.8%
4702 13
 
0.4%
4703 2
 
0.1%
4704 8
 
0.2%
4705 9
 
0.3%
4706 4
 
0.1%
4707 32
0.9%
4708 19
 
0.6%
4709 35
1.0%
ValueCountFrequency (%)
4808 32
0.9%
4807 2
 
0.1%
4806 5
 
0.1%
4805 27
0.8%
4804 30
0.9%
4803 3
 
0.1%
4802 2
 
0.1%
4801 27
0.8%
4800 13
 
0.4%
4799 53
1.5%

사업장명
Text

Distinct3177
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2024-05-11T15:05:47.213865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length7.6734457
Min length1

Characters and Unicode

Total characters26412
Distinct characters850
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2990 ?
Unique (%)86.9%

Sample

1st row대성
2nd row성미
3rd row리베로
4th row나드리커피숍
5th row학다방
ValueCountFrequency (%)
씨유 66
 
1.3%
gs25 56
 
1.1%
세븐일레븐 54
 
1.1%
성수점 45
 
0.9%
왕십리점 45
 
0.9%
카페 43
 
0.9%
이마트24 32
 
0.7%
한양대점 31
 
0.6%
coffee 30
 
0.6%
cafe 27
 
0.5%
Other values (3556) 4483
91.3%
2024-05-11T15:05:47.943968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1481
 
5.6%
점 1002
 
3.8%
스 750
 
2.8%
이 653
 
2.5%
리 618
 
2.3%
( 512
 
1.9%
) 511
 
1.9%
피 496
 
1.9%
커 441
 
1.7%
수 389
 
1.5%
Other values (840) 19559
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20065
76.0%
Uppercase Letter 1723
 
6.5%
Space Separator 1481
 
5.6%
Lowercase Letter 1422
 
5.4%
Decimal Number 563
 
2.1%
Open Punctuation 512
 
1.9%
Close Punctuation 511
 
1.9%
Other Punctuation 87
 
0.3%
Dash Punctuation 45
 
0.2%
Modifier Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1002
 
5.0%
스 750
 
3.7%
이 653
 
3.3%
리 618
 
3.1%
피 496
 
2.5%
커 441
 
2.2%
수 389
 
1.9%
성 384
 
1.9%
트 290
 
1.4%
페 271
 
1.4%
Other values (762) 14771
73.6%
Uppercase Letter
ValueCountFrequency (%)
S 193
 
11.2%
C 157
 
9.1%
E 149
 
8.6%
G 142
 
8.2%
A 130
 
7.5%
O 123
 
7.1%
F 81
 
4.7%
P 73
 
4.2%
U 69
 
4.0%
R 67
 
3.9%
Other values (16) 539
31.3%
Lowercase Letter
ValueCountFrequency (%)
e 233
16.4%
o 159
11.2%
a 139
 
9.8%
f 96
 
6.8%
c 84
 
5.9%
i 77
 
5.4%
s 73
 
5.1%
n 70
 
4.9%
r 67
 
4.7%
t 64
 
4.5%
Other values (15) 360
25.3%
Decimal Number
ValueCountFrequency (%)
2 223
39.6%
5 142
25.2%
4 58
 
10.3%
1 49
 
8.7%
3 32
 
5.7%
0 20
 
3.6%
9 12
 
2.1%
7 11
 
2.0%
8 10
 
1.8%
6 6
 
1.1%
Other Punctuation
ValueCountFrequency (%)
& 21
24.1%
. 20
23.0%
' 18
20.7%
, 11
12.6%
? 9
10.3%
＆ 3
 
3.4%
/ 2
 
2.3%
! 1
 
1.1%
: 1
 
1.1%
？ 1
 
1.1%
Modifier Symbol
ValueCountFrequency (%)
˚ 1
50.0%
` 1
50.0%
Space Separator
ValueCountFrequency (%)
1481
100.0%
Open Punctuation
ValueCountFrequency (%)
( 512
100.0%
Close Punctuation
ValueCountFrequency (%)
) 511
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20054
75.9%
Common 3202
 
12.1%
Latin 3145
 
11.9%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1002
 
5.0%
스 750
 
3.7%
이 653
 
3.3%
리 618
 
3.1%
피 496
 
2.5%
커 441
 
2.2%
수 389
 
1.9%
성 384
 
1.9%
트 290
 
1.4%
페 271
 
1.4%
Other values (753) 14760
73.6%
Latin
ValueCountFrequency (%)
e 233
 
7.4%
S 193
 
6.1%
o 159
 
5.1%
C 157
 
5.0%
E 149
 
4.7%
G 142
 
4.5%
a 139
 
4.4%
A 130
 
4.1%
O 123
 
3.9%
f 96
 
3.1%
Other values (41) 1624
51.6%
Common
ValueCountFrequency (%)
1481
46.3%
( 512
 
16.0%
) 511
 
16.0%
2 223
 
7.0%
5 142
 
4.4%
4 58
 
1.8%
1 49
 
1.5%
- 45
 
1.4%
3 32
 
1.0%
& 21
 
0.7%
Other values (17) 128
 
4.0%
Han
ValueCountFrequency (%)
堂 2
18.2%
好 2
18.2%
火 1
9.1%
米 1
9.1%
朱 1
9.1%
辛 1
9.1%
兩 1
9.1%
面 1
9.1%
性 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20052
75.9%
ASCII 6341
 
24.0%
CJK 10
 
< 0.1%
None 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Modifier Letters 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1481
23.4%
( 512
 
8.1%
) 511
 
8.1%
e 233
 
3.7%
2 223
 
3.5%
S 193
 
3.0%
o 159
 
2.5%
C 157
 
2.5%
E 149
 
2.3%
5 142
 
2.2%
Other values (64) 2581
40.7%
Hangul
ValueCountFrequency (%)
점 1002
 
5.0%
스 750
 
3.7%
이 653
 
3.3%
리 618
 
3.1%
피 496
 
2.5%
커 441
 
2.2%
수 389
 
1.9%
성 384
 
1.9%
트 290
 
1.4%
페 271
 
1.4%
Other values (752) 14758
73.6%
None
ValueCountFrequency (%)
＆ 3
75.0%
？ 1
 
25.0%
CJK
ValueCountFrequency (%)
堂 2
20.0%
好 2
20.0%
火 1
10.0%
米 1
10.0%
朱 1
10.0%
辛 1
10.0%
面 1
10.0%
性 1
10.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 2
100.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
兩 1
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

최종수정일자
Date

Distinct2787
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
Minimum1999-05-28 00:00:00
Maximum2024-05-09 16:12:13
2024-05-11T15:05:48.150114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:48.372551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
I
2269 
U
1173 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2269
65.9%
U 1173
34.1%

Length

2024-05-11T15:05:48.639448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:48.828711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2269
65.9%
u 1173
34.1%

데이터갱신일자
Date

Distinct971
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:05:49.014614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:05:49.261914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
커피숍
1038 
일반조리판매
640 
다방
500 
기타 휴게음식점
495 
편의점
316 
Other values (11)
453 

Length

Max length8
Median length6
Mean length4.2495642
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1038
30.2%
일반조리판매 640
18.6%
다방 500
14.5%
기타 휴게음식점 495
14.4%
편의점 316
 
9.2%
과자점 215
 
6.2%
패스트푸드 163
 
4.7%
백화점 23
 
0.7%
아이스크림 19
 
0.6%
철도역구내 16
 
0.5%
Other values (6) 17
 
0.5%

Length

2024-05-11T15:05:49.611795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1038
26.4%
일반조리판매 640
16.3%
다방 500
12.7%
기타 495
12.6%
휴게음식점 495
12.6%
편의점 316
 
8.0%
과자점 215
 
5.5%
패스트푸드 163
 
4.1%
백화점 23
 
0.6%
아이스크림 19
 
0.5%
Other values (7) 33
 
0.8%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1673
Distinct (%)50.5%
Missing129
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean203629.99
Minimum200812.99
Maximum206382.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:49.820212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200812.99
5-th percentile201538.06
Q1202767.06
median203655.74
Q3204614.27
95-th percentile205583.57
Maximum206382.16
Range5569.1651
Interquartile range (IQR)1847.2146

Descriptive statistics

Standard deviation1214.0298
Coefficient of variation (CV)0.0059619399
Kurtosis-0.75227453
Mean203629.99
Median Absolute Deviation (MAD)958.52976
Skewness-0.16630651
Sum6.7462616 × 108
Variance1473868.2
MonotonicityNot monotonic
2024-05-11T15:05:50.043582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203292.151898869 102
 
3.0%
203321.562330114 75
 
2.2%
204614.272744322 60
 
1.7%
203684.127182478 39
 
1.1%
202372.912023599 35
 
1.0%
205784.868811814 34
 
1.0%
202511.142930696 34
 
1.0%
202113.869605464 33
 
1.0%
204108.263654233 27
 
0.8%
202326.503044305 25
 
0.7%
Other values (1663) 2849
82.8%
(Missing) 129
 
3.7%
ValueCountFrequency (%)
200812.992681398 3
0.1%
200813.000885632 1
 
< 0.1%
200886.870660767 1
 
< 0.1%
200896.532906303 3
0.1%
200906.190812824 1
 
< 0.1%
200913.361072125 1
 
< 0.1%
200935.024540138 1
 
< 0.1%
200951.206580662 6
0.2%
200967.537033206 4
0.1%
200975.906541768 1
 
< 0.1%
ValueCountFrequency (%)
206382.157826605 1
< 0.1%
206299.734441078 1
< 0.1%
206267.144320265 2
0.1%
206243.875021499 1
< 0.1%
206209.280864162 1
< 0.1%
206203.256423765 1
< 0.1%
206188.003773446 1
< 0.1%
206185.104313258 1
< 0.1%
206112.681512323 1
< 0.1%
206068.841405164 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1673
Distinct (%)50.5%
Missing129
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean450072.04
Minimum448074.6
Maximum452148.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:50.302696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448074.6
5-th percentile448492.77
Q1449237.45
median449891.97
Q3451001.87
95-th percentile451594.71
Maximum452148.34
Range4073.7402
Interquartile range (IQR)1764.4233

Descriptive statistics

Standard deviation1031.0194
Coefficient of variation (CV)0.0022907876
Kurtosis-1.2837112
Mean450072.04
Median Absolute Deviation (MAD)942.34196
Skewness0.029932595
Sum1.4910887 × 109
Variance1063001.1
MonotonicityNot monotonic
2024-05-11T15:05:50.561069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451267.730901002 102
 
3.0%
451001.868687869 75
 
2.2%
448607.441251647 60
 
1.7%
450698.570810848 39
 
1.1%
451536.680876573 35
 
1.0%
450883.524006222 34
 
1.0%
450401.303715561 34
 
1.0%
451897.581865192 33
 
1.0%
450598.470063263 27
 
0.8%
450625.58422744 25
 
0.7%
Other values (1663) 2849
82.8%
(Missing) 129
 
3.7%
ValueCountFrequency (%)
448074.599156032 1
< 0.1%
448169.308636228 1
< 0.1%
448175.694252303 2
0.1%
448179.869576203 2
0.1%
448190.579149916 1
< 0.1%
448202.293163154 1
< 0.1%
448229.126737125 2
0.1%
448231.135811849 1
< 0.1%
448231.838190374 1
< 0.1%
448236.227470207 1
< 0.1%
ValueCountFrequency (%)
452148.339373773 1
< 0.1%
452127.749317533 1
< 0.1%
452108.522149464 1
< 0.1%
452063.440192474 1
< 0.1%
452060.343042602 1
< 0.1%
452032.253768878 1
< 0.1%
452031.523389946 1
< 0.1%
452019.558572479 2
0.1%
452019.132498433 2
0.1%
452010.908223981 1
< 0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
838 
커피숍
658 
일반조리판매
550 
다방
498 
기타 휴게음식점
270 
Other values (12)
628 

Length

Max length8
Median length6
Mean length4.0674027
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 838
24.3%
커피숍 658
19.1%
일반조리판매 550
16.0%
다방 498
14.5%
기타 휴게음식점 270
 
7.8%
편의점 216
 
6.3%
과자점 215
 
6.2%
패스트푸드 138
 
4.0%
백화점 20
 
0.6%
철도역구내 14
 
0.4%
Other values (7) 25
 
0.7%

Length

2024-05-11T15:05:50.835163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 838
22.6%
커피숍 658
17.7%
일반조리판매 550
14.8%
다방 498
13.4%
기타 270
 
7.3%
휴게음식점 270
 
7.3%
편의점 216
 
5.8%
과자점 215
 
5.8%
패스트푸드 138
 
3.7%
백화점 20
 
0.5%
Other values (8) 39
 
1.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.6%
Missing2361
Missing (%)68.6%
Infinite0
Infinite (%)0.0%
Mean0.12025902
Minimum0
Maximum8
Zeros985
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:51.008617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.46782231
Coefficient of variation (CV)3.8901224
Kurtosis85.568806
Mean0.12025902
Median Absolute Deviation (MAD)0
Skewness7.1289662
Sum130
Variance0.21885771
MonotonicityNot monotonic
2024-05-11T15:05:51.198506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 985
28.6%
1 73
 
2.1%
2 18
 
0.5%
3 3
 
0.1%
8 1
 
< 0.1%
4 1
 
< 0.1%
(Missing) 2361
68.6%
ValueCountFrequency (%)
0 985
28.6%
1 73
 
2.1%
2 18
 
0.5%
3 3
 
0.1%
4 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
4 1
 
< 0.1%
3 3
 
0.1%
2 18
 
0.5%
1 73
 
2.1%
0 985
28.6%

여성종사자수
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
2361 
0
710 
2
 
140
3
 
136
1
 
85

Length

Max length4
Median length4
Mean length3.0578152
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row0
4th row0
5th row3

Common Values

ValueCountFrequency (%)
<NA> 2361
68.6%
0 710
 
20.6%
2 140
 
4.1%
3 136
 
4.0%
1 85
 
2.5%
4 10
 
0.3%

Length

2024-05-11T15:05:51.433567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:51.770011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2361
68.6%
0 710
 
20.6%
2 140
 
4.1%
3 136
 
4.0%
1 85
 
2.5%
4 10
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
2599 
주택가주변
400 
기타
367 
아파트지역
 
48
학교정화(상대)
 
11
Other values (3)
 
17

Length

Max length8
Median length4
Mean length3.9482859
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2599
75.5%
주택가주변 400
 
11.6%
기타 367
 
10.7%
아파트지역 48
 
1.4%
학교정화(상대) 11
 
0.3%
학교정화(절대) 8
 
0.2%
유흥업소밀집지역 5
 
0.1%
결혼예식장주변 4
 
0.1%

Length

2024-05-11T15:05:52.052385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:52.267935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2599
75.5%
주택가주변 400
 
11.6%
기타 367
 
10.7%
아파트지역 48
 
1.4%
학교정화(상대 11
 
0.3%
학교정화(절대 8
 
0.2%
유흥업소밀집지역 5
 
0.1%
결혼예식장주변 4
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
2663 
기타
380 
지도
 
203
을
 
155
자율
 
24

Length

Max length4
Median length4
Mean length3.4973852
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지도
2nd row지도
3rd row을
4th row기타
5th row을

Common Values

ValueCountFrequency (%)
<NA> 2663
77.4%
기타 380
 
11.0%
지도 203
 
5.9%
을 155
 
4.5%
자율 24
 
0.7%
갑 17
 
0.5%

Length

2024-05-11T15:05:52.500904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:52.698587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2663
77.4%
기타 380
 
11.0%
지도 203
 
5.9%
을 155
 
4.5%
자율 24
 
0.7%
갑 17
 
0.5%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
2435 
상수도전용
1002 
상수도(음용)지하수(주방용)겸용
 
4
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.3065078
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2435
70.7%
상수도전용 1002
29.1%
상수도(음용)지하수(주방용)겸용 4
 
0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T15:05:52.898195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:53.076661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2435
70.7%
상수도전용 1002
29.1%
상수도(음용)지하수(주방용)겸용 4
 
0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3304 
0
 
138

Length

Max length4
Median length4
Mean length3.8797211
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> 3304
96.0%
0 138
 
4.0%

Length

2024-05-11T15:05:53.259309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:53.401825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3304
96.0%
0 138
 
4.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:53.581170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:53.739938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:53.910770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:54.093986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:54.256192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:54.437782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:54.599752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:54.752441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:54.903921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:55.017338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
<NA>
3301 
0
 
141

Length

Max length4
Median length4
Mean length3.8771063
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> 3301
95.9%
0 141
 
4.1%

Length

2024-05-11T15:05:55.494113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:05:55.654351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3301
95.9%
0 141
 
4.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing838
Missing (%)24.3%
Memory size6.9 KiB
False
2581 
True
 
23
(Missing)
838 
ValueCountFrequency (%)
False 2581
75.0%
True 23
 
0.7%
(Missing) 838
 
24.3%
2024-05-11T15:05:55.760384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct1529
Distinct (%)58.7%
Missing838
Missing (%)24.3%
Infinite0
Infinite (%)0.0%
Mean44.959171
Minimum0
Maximum538.62
Zeros56
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size30.4 KiB
2024-05-11T15:05:55.907954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114.63
median29.7
Q363.0825
95-th percentile130.0675
Maximum538.62
Range538.62
Interquartile range (IQR)48.4525

Descriptive statistics

Standard deviation45.816162
Coefficient of variation (CV)1.0190616
Kurtosis11.479204
Mean44.959171
Median Absolute Deviation (MAD)19.8
Skewness2.5046213
Sum117073.68
Variance2099.1207
MonotonicityNot monotonic
2024-05-11T15:05:56.115314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 92
 
2.7%
6.6 59
 
1.7%
0.0 56
 
1.6%
33.0 43
 
1.2%
10.0 34
 
1.0%
9.9 26
 
0.8%
20.0 25
 
0.7%
5.0 21
 
0.6%
6.0 20
 
0.6%
16.5 19
 
0.6%
Other values (1519) 2209
64.2%
(Missing) 838
 
24.3%
ValueCountFrequency (%)
0.0 56
1.6%
0.49 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 7
 
0.2%
1.2 1
 
< 0.1%
1.4 2
 
0.1%
1.5 8
 
0.2%
1.8 1
 
< 0.1%
2.0 4
 
0.1%
ValueCountFrequency (%)
538.62 1
< 0.1%
353.05 1
< 0.1%
348.56 1
< 0.1%
333.0 1
< 0.1%
321.32 1
< 0.1%
315.32 1
< 0.1%
308.13 1
< 0.1%
295.68 1
< 0.1%
294.77 1
< 0.1%
293.27 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3442
Missing (%)100.0%
Memory size30.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030300003030000-104-1974-0031819740301<NA>3폐업2폐업19951110<NA><NA><NA>02 292870578.8133852서울특별시 성동구 응봉동 200-1번지<NA><NA>대성2001-09-25 00:00:00I2018-08-31 23:59:59.0다방202679.134888449737.382798다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.8<NA><NA><NA>
130300003030000-104-1974-0037919740301<NA>3폐업2폐업19941227<NA><NA><NA>02 292549465.41133854서울특별시 성동구 하왕십리동 395-0번지<NA><NA>성미2001-09-25 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.41<NA><NA><NA>
230300003030000-104-1974-0054919740301<NA>3폐업2폐업20000927<NA><NA><NA>0273.49133803서울특별시 성동구 금호동2가 325번지<NA><NA>리베로2001-12-03 00:00:00I2018-08-31 23:59:59.0다방201662.343568450253.502014다방00주택가주변을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N73.49<NA><NA><NA>
330300003030000-104-1974-0057219740301<NA>3폐업2폐업19971120<NA><NA><NA>02 293671372.4133010서울특별시 성동구 상왕십리동 773-5번지<NA><NA>나드리커피숍2001-09-25 00:00:00I2018-08-31 23:59:59.0다방202103.932695451449.217629다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N72.4<NA><NA><NA>
430300003030000-104-1974-0057519740301<NA>3폐업2폐업20151228<NA><NA><NA><NA>95.45133836서울특별시 성동구 송정동 66-262번지서울특별시 성동구 광나루로9길 2 (송정동)4801학다방2015-12-29 13:01:01I2018-08-31 23:59:59.0다방205579.590818449581.301611다방03기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N95.45<NA><NA><NA>
530300003030000-104-1974-0058219740301<NA>3폐업2폐업20051201<NA><NA><NA>02 465379788.2133834서울특별시 성동구 성수동2가 289-4번지<NA><NA>성수커피숍2003-09-22 00:00:00I2018-08-31 23:59:59.0다방204830.977323449477.44846다방03기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N88.2<NA><NA><NA>
630300003030000-104-1974-0059919740301<NA>3폐업2폐업19991004<NA><NA><NA>0277.76133881서울특별시 성동구 홍익동 469-1번지<NA><NA>두꺼비2001-09-25 00:00:00I2018-08-31 23:59:59.0다방202567.184596451588.11553다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N77.76<NA><NA><NA>
730300003030000-104-1974-0060119740301<NA>3폐업2폐업20021126<NA><NA><NA>02 4667789111.17133836서울특별시 성동구 송정동 67-11번지<NA><NA>복2002-11-26 00:00:00I2018-08-31 23:59:59.0다방205521.823532449566.095817다방03기타을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N111.17<NA><NA><NA>
830300003030000-104-1974-0066219740301<NA>3폐업2폐업19940820<NA><NA><NA>02 2926724115.64133865서울특별시 성동구 행당동 133-5번지<NA><NA>월성2001-09-25 00:00:00I2018-08-31 23:59:59.0다방203197.939381450737.153597다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N115.64<NA><NA><NA>
930300003030000-104-1974-0074719740301<NA>3폐업2폐업19910912<NA><NA><NA>02 293620978.17133010서울특별시 성동구 상왕십리동 96-30번지<NA><NA>수2001-09-25 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.17<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
343230300003030000-104-2024-000482024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.59133-852서울특별시 성동구 응봉동 100 대림종합상가서울특별시 성동구 독서당로 434, 대림종합상가 지1층 지층2호 (응봉동)4741스탭52024-04-23 16:20:19I2023-12-03 22:05:00.0기타 휴게음식점202869.775809449963.043498<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343330300003030000-104-2024-000492024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>43.14133-835서울특별시 성동구 성수동2가 301-27서울특별시 성동구 연무장1길 7, 1층 (성수동2가)4782따우전드 성수점2024-04-25 16:28:07I2023-12-03 22:07:00.0커피숍204398.359449449143.242118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343430300003030000-104-2024-000502024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.0133-835서울특별시 성동구 성수동2가 315-15 (주)팔도수산서울특별시 성동구 연무장9길 10-1 (주)팔도수산 2층 202호 (성수동2가)4782케익다방 성수점2024-04-25 17:46:54I2023-12-03 22:07:00.0커피숍204893.981988448987.054907<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343530300003030000-104-2024-000512024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>84.32133-020서울특별시 성동구 하왕십리동 1070 센트라스서울특별시 성동구 왕십리로 410, J동 104호 (하왕십리동, 센트라스)4701읍천리382 왕십리신당점2024-04-26 13:21:47I2023-12-03 22:08:00.0커피숍202372.912024451536.680877<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343630300003030000-104-2024-000522024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA>070 4794230033.71133-823서울특별시 성동구 성수동1가 656-623서울특별시 성동구 왕십리로6길 14-1, 1층 (성수동1가)4778헤이 앨리스(Hey Alice)2024-04-26 13:42:32I2023-12-03 22:08:00.0커피숍204017.714635449283.147453<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343730300003030000-104-2024-000532024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 456 380664.0133-822서울특별시 성동구 성수동1가 13-320 빌라드 고릴라서울특별시 성동구 상원6길 8-14, 빌라드 고릴라 지1층 (성수동1가)4790고스티(Gosty)2024-04-30 09:52:36I2023-12-05 00:02:00.0커피숍204269.95957449561.544189<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343830300003030000-104-2024-000542024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.0133-825서울특별시 성동구 성수동1가 685-325서울특별시 성동구 서울숲2길 19-18, 지1층 (성수동1가)4768센트럴모굴2024-04-30 10:58:38I2023-12-05 00:02:00.0커피숍203572.583109449460.392236<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
343930300003030000-104-2024-000552024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>380.2133-882서울특별시 성동구 도선동 39-1 신방빌딩서울특별시 성동구 무학로2길 52, 신방빌딩 1층 (도선동)4709더 카페 신방(THE CAFE SHEENBANG)2024-04-30 15:25:17I2023-12-05 00:02:00.0커피숍203033.815492451096.333215<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
344030300003030000-104-2024-000562024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.0133-843서울특별시 성동구 성수동1가 656-745 뚝섬역서울특별시 성동구 아차산로 18, 뚝섬역 210-006호 (성수동1가)4778하나맛뜨레P&B2024-05-02 16:19:42I2023-12-05 00:04:00.0기타 휴게음식점<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
344130300003030000-104-2024-000572024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3133-866서울특별시 성동구 행당동 196-9서울특별시 성동구 왕십리광장로 10-1, 1층 (행당동)4751씨유 왕십리삼부점2024-05-08 10:12:10I2023-12-04 23:00:00.0편의점203156.572744450974.141664<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>