Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells106861
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 B

Variable types

Numeric7
Text6
DateTime4
Unsupported7
Categorical19
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
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16085/S/1/datasetView.do

Alerts

업태구분명 is highly imbalanced (96.5%)Imbalance
남성종사자수 is highly imbalanced (87.9%)Imbalance
여성종사자수 is highly imbalanced (86.4%)Imbalance
영업장주변구분명 is highly imbalanced (91.7%)Imbalance
등급구분명 is highly imbalanced (92.2%)Imbalance
급수시설구분명 is highly imbalanced (86.8%)Imbalance
총인원 is highly imbalanced (81.6%)Imbalance
본사종업원수 is highly imbalanced (76.4%)Imbalance
공장사무직종업원수 is highly imbalanced (80.0%)Imbalance
공장생산직종업원수 is highly imbalanced (81.6%)Imbalance
보증액 is highly imbalanced (86.7%)Imbalance
월세액 is highly imbalanced (86.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 2296 (23.0%) 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 6992 (69.9%) missing valuesMissing
소재지면적 has 3763 (37.6%) missing valuesMissing
도로명주소 has 943 (9.4%) missing valuesMissing
도로명우편번호 has 966 (9.7%) missing valuesMissing
좌표정보(X) has 212 (2.1%) missing valuesMissing
좌표정보(Y) has 212 (2.1%) missing valuesMissing
공장판매직종업원수 has 8897 (89.0%) missing valuesMissing
다중이용업소여부 has 6281 (62.8%) missing valuesMissing
시설총규모 has 6281 (62.8%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 55.72326253)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
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
소재지면적 has 1750 (17.5%) zerosZeros
공장판매직종업원수 has 959 (9.6%) zerosZeros
시설총규모 has 3310 (33.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:31:21.332797
Analysis finished2024-05-10 23:31:27.080373
Duration5.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3092872
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:31:27.432883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3000000
Q13010000
median3070000
Q33170000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)160000

Descriptive statistics

Standard deviation84161.63
Coefficient of variation (CV)0.027211482
Kurtosis-1.3962139
Mean3092872
Median Absolute Deviation (MAD)60000
Skewness0.42414868
Sum3.092872 × 1010
Variance7.0831799 × 109
MonotonicityNot monotonic
2024-05-10T23:31:27.858361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3010000 2308
23.1%
3020000 968
 
9.7%
3000000 635
 
6.3%
3220000 594
 
5.9%
3030000 478
 
4.8%
3210000 466
 
4.7%
3230000 383
 
3.8%
3180000 369
 
3.7%
3140000 360
 
3.6%
3130000 356
 
3.6%
Other values (15) 3083
30.8%
ValueCountFrequency (%)
3000000 635
 
6.3%
3010000 2308
23.1%
3020000 968
9.7%
3030000 478
 
4.8%
3040000 185
 
1.8%
3050000 179
 
1.8%
3060000 201
 
2.0%
3070000 248
 
2.5%
3080000 153
 
1.5%
3090000 190
 
1.9%
ValueCountFrequency (%)
3240000 342
3.4%
3230000 383
3.8%
3220000 594
5.9%
3210000 466
4.7%
3200000 176
 
1.8%
3190000 127
 
1.3%
3180000 369
3.7%
3170000 152
 
1.5%
3160000 316
3.2%
3150000 250
2.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:31:28.440868image/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 row3060000-107-2023-00276
2nd row3010000-107-2017-00424
3rd row3030000-107-2016-00086
4th row3180000-107-2024-00033
5th row3000000-107-2019-00166
ValueCountFrequency (%)
3060000-107-2023-00276 1
 
< 0.1%
3060000-107-2023-00099 1
 
< 0.1%
3160000-107-2023-00354 1
 
< 0.1%
3140000-107-2023-00217 1
 
< 0.1%
3020000-107-2021-00206 1
 
< 0.1%
3080000-107-2024-00012 1
 
< 0.1%
3010000-107-2016-00167 1
 
< 0.1%
3010000-107-2023-00257 1
 
< 0.1%
3010000-107-2023-00178 1
 
< 0.1%
3000000-107-2020-00059 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-10T23:31:29.605406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 94081
42.8%
- 30000
 
13.6%
2 24083
 
10.9%
1 23219
 
10.6%
3 18096
 
8.2%
7 12982
 
5.9%
4 5100
 
2.3%
9 3363
 
1.5%
6 3039
 
1.4%
5 3021
 
1.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94081
49.5%
2 24083
 
12.7%
1 23219
 
12.2%
3 18096
 
9.5%
7 12982
 
6.8%
4 5100
 
2.7%
9 3363
 
1.8%
6 3039
 
1.6%
5 3021
 
1.6%
8 3016
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 94081
42.8%
- 30000
 
13.6%
2 24083
 
10.9%
1 23219
 
10.6%
3 18096
 
8.2%
7 12982
 
5.9%
4 5100
 
2.3%
9 3363
 
1.5%
6 3039
 
1.4%
5 3021
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 94081
42.8%
- 30000
 
13.6%
2 24083
 
10.9%
1 23219
 
10.6%
3 18096
 
8.2%
7 12982
 
5.9%
4 5100
 
2.3%
9 3363
 
1.5%
6 3039
 
1.4%
5 3021
 
1.4%
Distinct3069
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1972-10-31 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:31:30.209769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:31:30.874894image/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
7704 
1
2296 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 7704
77.0%
1 2296
 
23.0%

Length

2024-05-10T23:31:31.478357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:31.891972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 7704
77.0%
1 2296
 
23.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7704 
영업/정상
2296 

Length

Max length5
Median length2
Mean length2.6888
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7704
77.0%
영업/정상 2296
 
23.0%

Length

2024-05-10T23:31:33.372081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:33.809267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7704
77.0%
영업/정상 2296
 
23.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
7704 
1
2296 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 7704
77.0%
1 2296
 
23.0%

Length

2024-05-10T23:31:34.167289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:34.468639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 7704
77.0%
1 2296
 
23.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
7704 
영업
2296 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 7704
77.0%
영업 2296
 
23.0%

Length

2024-05-10T23:31:34.795249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:35.122116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 7704
77.0%
영업 2296
 
23.0%

폐업일자
Date

MISSING 

Distinct2546
Distinct (%)33.0%
Missing2296
Missing (%)23.0%
Memory size156.2 KiB
Minimum1996-07-05 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:31:35.466278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:31:35.856933image/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 

Distinct1989
Distinct (%)66.1%
Missing6992
Missing (%)69.9%
Memory size156.2 KiB
2024-05-10T23:31:36.520630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.886303
Min length2

Characters and Unicode

Total characters32746
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

Unique1722 ?
Unique (%)57.2%

Sample

1st row02 4737910
2nd row0226335201
3rd row02 7649990
4th row02 3121929
5th row031 952 1448
ValueCountFrequency (%)
02 1262
 
20.9%
031 420
 
7.0%
070 165
 
2.7%
032 82
 
1.4%
055 66
 
1.1%
062 64
 
1.1%
07043009589 39
 
0.6%
4992 30
 
0.5%
311 28
 
0.5%
381 26
 
0.4%
Other values (2247) 3852
63.8%
2024-05-10T23:31:37.731701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5621
17.2%
2 4848
14.8%
3702
11.3%
3 3024
9.2%
1 2629
8.0%
7 2591
7.9%
5 2259
6.9%
9 2090
 
6.4%
8 2067
 
6.3%
4 2023
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29044
88.7%
Space Separator 3702
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5621
19.4%
2 4848
16.7%
3 3024
10.4%
1 2629
9.1%
7 2591
8.9%
5 2259
7.8%
9 2090
 
7.2%
8 2067
 
7.1%
4 2023
 
7.0%
6 1892
 
6.5%
Space Separator
ValueCountFrequency (%)
3702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5621
17.2%
2 4848
14.8%
3702
11.3%
3 3024
9.2%
1 2629
8.0%
7 2591
7.9%
5 2259
6.9%
9 2090
 
6.4%
8 2067
 
6.3%
4 2023
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5621
17.2%
2 4848
14.8%
3702
11.3%
3 3024
9.2%
1 2629
8.0%
7 2591
7.9%
5 2259
6.9%
9 2090
 
6.4%
8 2067
 
6.3%
4 2023
 
6.2%

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1256
Distinct (%)20.1%
Missing3763
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean58.277524
Minimum0
Maximum112658
Zeros1750
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:31:38.282878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.6
Q320.24
95-th percentile74.034
Maximum112658
Range112658
Interquartile range (IQR)20.24

Descriptive statistics

Standard deviation2018.1219
Coefficient of variation (CV)34.629506
Kurtosis3108.0093
Mean58.277524
Median Absolute Deviation (MAD)6.6
Skewness55.723263
Sum363476.92
Variance4072815.9
MonotonicityNot monotonic
2024-05-10T23:31:38.820301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1750
17.5%
3.3 584
 
5.8%
6.6 203
 
2.0%
10.0 198
 
2.0%
6.0 113
 
1.1%
3.0 108
 
1.1%
15.0 97
 
1.0%
9.9 97
 
1.0%
20.0 92
 
0.9%
232.58 77
 
0.8%
Other values (1246) 2918
29.2%
(Missing) 3763
37.6%
ValueCountFrequency (%)
0.0 1750
17.5%
0.1 1
 
< 0.1%
0.5 1
 
< 0.1%
0.7 1
 
< 0.1%
0.96 1
 
< 0.1%
1.0 9
 
0.1%
1.05 1
 
< 0.1%
1.1 5
 
0.1%
1.14 1
 
< 0.1%
1.25 1
 
< 0.1%
ValueCountFrequency (%)
112658.0 2
 
< 0.1%
1126.58 9
0.1%
1070.0 12
0.1%
608.0 1
 
< 0.1%
373.0 1
 
< 0.1%
315.0 1
 
< 0.1%
277.0 1
 
< 0.1%
272.73 1
 
< 0.1%
267.3 1
 
< 0.1%
266.28 1
 
< 0.1%
Distinct1878
Distinct (%)18.8%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-10T23:31:39.762212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.6151536
Min length6

Characters and Unicode

Total characters66092
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

Unique914 ?
Unique (%)9.1%

Sample

1st row131-809
2nd row100162
3rd row133070
4th row150-835
5th row110054
ValueCountFrequency (%)
100011 492
 
4.9%
100070 438
 
4.4%
140780 290
 
2.9%
100440 207
 
2.1%
100747 198
 
2.0%
100850 176
 
1.8%
100162 139
 
1.4%
158-050 125
 
1.3%
137-960 119
 
1.2%
152-706 106
 
1.1%
Other values (1868) 7701
77.1%
2024-05-10T23:31:41.351722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14494
21.9%
0 12959
19.6%
8 6721
10.2%
- 6146
9.3%
3 5594
 
8.5%
7 4107
 
6.2%
4 4030
 
6.1%
5 3996
 
6.0%
2 3629
 
5.5%
9 2252
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59946
90.7%
Dash Punctuation 6146
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14494
24.2%
0 12959
21.6%
8 6721
11.2%
3 5594
 
9.3%
7 4107
 
6.9%
4 4030
 
6.7%
5 3996
 
6.7%
2 3629
 
6.1%
9 2252
 
3.8%
6 2164
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 6146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66092
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14494
21.9%
0 12959
19.6%
8 6721
10.2%
- 6146
9.3%
3 5594
 
8.5%
7 4107
 
6.2%
4 4030
 
6.1%
5 3996
 
6.0%
2 3629
 
5.5%
9 2252
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66092
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14494
21.9%
0 12959
19.6%
8 6721
10.2%
- 6146
9.3%
3 5594
 
8.5%
7 4107
 
6.2%
4 4030
 
6.1%
5 3996
 
6.0%
2 3629
 
5.5%
9 2252
 
3.4%
Distinct4546
Distinct (%)45.5%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-10T23:31:42.226025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length47
Mean length25.729957
Min length14

Characters and Unicode

Total characters257068
Distinct characters562
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3929 ?
Unique (%)39.3%

Sample

1st row서울특별시 중랑구 망우동 506-1 E-마트 상봉점
2nd row서울특별시 중구 봉래동2가 122 롯데마트서울역점 2층
3rd row서울특별시 성동구 행당동 346
4th row서울특별시 영등포구 문래동3가 55-5 로데오 ? 쇼핑몰
5th row서울특별시 종로구 사직동 1-41
ValueCountFrequency (%)
서울특별시 9989
 
19.4%
중구 2301
 
4.5%
용산구 968
 
1.9%
지하1층 849
 
1.6%
충무로1가 824
 
1.6%
52-5 725
 
1.4%
종로구 636
 
1.2%
강남구 594
 
1.2%
1층 510
 
1.0%
성동구 478
 
0.9%
Other values (5547) 33727
65.4%
2024-05-10T23:31:43.831708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45285
 
17.6%
11357
 
4.4%
10651
 
4.1%
10626
 
4.1%
10264
 
4.0%
10090
 
3.9%
9995
 
3.9%
9993
 
3.9%
1 9717
 
3.8%
- 6669
 
2.6%
Other values (552) 122421
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161309
62.7%
Space Separator 45285
 
17.6%
Decimal Number 42193
 
16.4%
Dash Punctuation 6669
 
2.6%
Uppercase Letter 832
 
0.3%
Close Punctuation 266
 
0.1%
Open Punctuation 265
 
0.1%
Other Punctuation 150
 
0.1%
Lowercase Letter 51
 
< 0.1%
Other Symbol 29
 
< 0.1%
Other values (2) 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11357
 
7.0%
10651
 
6.6%
10626
 
6.6%
10264
 
6.4%
10090
 
6.3%
9995
 
6.2%
9993
 
6.2%
3268
 
2.0%
3031
 
1.9%
2869
 
1.8%
Other values (485) 79165
49.1%
Uppercase Letter
ValueCountFrequency (%)
S 107
12.9%
C 94
11.3%
E 76
9.1%
N 75
9.0%
G 74
8.9%
T 66
 
7.9%
A 61
 
7.3%
B 54
 
6.5%
I 31
 
3.7%
M 26
 
3.1%
Other values (14) 168
20.2%
Lowercase Letter
ValueCountFrequency (%)
e 9
17.6%
s 7
13.7%
o 7
13.7%
r 5
9.8%
g 4
7.8%
c 3
 
5.9%
n 2
 
3.9%
w 2
 
3.9%
t 2
 
3.9%
u 2
 
3.9%
Other values (6) 8
15.7%
Decimal Number
ValueCountFrequency (%)
1 9717
23.0%
2 6397
15.2%
5 4667
11.1%
3 4096
9.7%
9 3711
 
8.8%
4 3538
 
8.4%
6 2985
 
7.1%
0 2684
 
6.4%
7 2558
 
6.1%
8 1840
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 138
92.0%
? 5
 
3.3%
@ 2
 
1.3%
. 2
 
1.3%
& 1
 
0.7%
/ 1
 
0.7%
* 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 255
95.9%
] 11
 
4.1%
Open Punctuation
ValueCountFrequency (%)
( 254
95.8%
[ 11
 
4.2%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
45285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6669
100.0%
Other Symbol
ValueCountFrequency (%)
29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161335
62.8%
Common 94844
36.9%
Latin 886
 
0.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11357
 
7.0%
10651
 
6.6%
10626
 
6.6%
10264
 
6.4%
10090
 
6.3%
9995
 
6.2%
9993
 
6.2%
3268
 
2.0%
3031
 
1.9%
2869
 
1.8%
Other values (483) 79191
49.1%
Latin
ValueCountFrequency (%)
S 107
12.1%
C 94
10.6%
E 76
 
8.6%
N 75
 
8.5%
G 74
 
8.4%
T 66
 
7.4%
A 61
 
6.9%
B 54
 
6.1%
I 31
 
3.5%
M 26
 
2.9%
Other values (32) 222
25.1%
Common
ValueCountFrequency (%)
45285
47.7%
1 9717
 
10.2%
- 6669
 
7.0%
2 6397
 
6.7%
5 4667
 
4.9%
3 4096
 
4.3%
9 3711
 
3.9%
4 3538
 
3.7%
6 2985
 
3.1%
0 2684
 
2.8%
Other values (14) 5095
 
5.4%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161306
62.7%
ASCII 95727
37.2%
None 29
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45285
47.3%
1 9717
 
10.2%
- 6669
 
7.0%
2 6397
 
6.7%
5 4667
 
4.9%
3 4096
 
4.3%
9 3711
 
3.9%
4 3538
 
3.7%
6 2985
 
3.1%
0 2684
 
2.8%
Other values (54) 5978
 
6.2%
Hangul
ValueCountFrequency (%)
11357
 
7.0%
10651
 
6.6%
10626
 
6.6%
10264
 
6.4%
10090
 
6.3%
9995
 
6.2%
9993
 
6.2%
3268
 
2.0%
3031
 
1.9%
2869
 
1.8%
Other values (482) 79162
49.1%
None
ValueCountFrequency (%)
29
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct4968
Distinct (%)54.9%
Missing943
Missing (%)9.4%
Memory size156.2 KiB
2024-05-10T23:31:44.930198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length62
Mean length36.4666
Min length20

Characters and Unicode

Total characters330278
Distinct characters592
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4300 ?
Unique (%)47.5%

Sample

1st row서울특별시 중랑구 상봉로 118, E-마트 상봉점 (망우동)
2nd row서울특별시 중구 청파로 426 (봉래동2가, 롯데마트서울역점 2층)
3rd row서울특별시 성동구 행당로 82, 지하3층 (행당동, 롯데마트행당역점내)
4th row서울특별시 영등포구 당산로 34, 로데오 ? 쇼핑몰 118호 (문래동3가)
5th row서울특별시 종로구 인왕산로 5, 지상1층 (사직동)
ValueCountFrequency (%)
서울특별시 9055
 
14.1%
지하1층 2566
 
4.0%
1층 2290
 
3.6%
중구 1837
 
2.9%
지하2층 907
 
1.4%
용산구 802
 
1.2%
충무로1가 711
 
1.1%
63 676
 
1.1%
소공로 658
 
1.0%
강남구 592
 
0.9%
Other values (5628) 44246
68.8%
2024-05-10T23:31:46.724283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55307
 
16.7%
1 13182
 
4.0%
11553
 
3.5%
10711
 
3.2%
10415
 
3.2%
, 10284
 
3.1%
9857
 
3.0%
9815
 
3.0%
9368
 
2.8%
) 9243
 
2.8%
Other values (582) 180543
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202651
61.4%
Space Separator 55307
 
16.7%
Decimal Number 41400
 
12.5%
Other Punctuation 10294
 
3.1%
Close Punctuation 9253
 
2.8%
Open Punctuation 9253
 
2.8%
Uppercase Letter 1266
 
0.4%
Dash Punctuation 702
 
0.2%
Lowercase Letter 80
 
< 0.1%
Math Symbol 41
 
< 0.1%
Other values (2) 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11553
 
5.7%
10711
 
5.3%
10415
 
5.1%
9857
 
4.9%
9815
 
4.8%
9368
 
4.6%
9060
 
4.5%
9059
 
4.5%
7558
 
3.7%
4963
 
2.4%
Other values (514) 110292
54.4%
Uppercase Letter
ValueCountFrequency (%)
B 232
18.3%
S 189
14.9%
G 127
10.0%
C 107
8.5%
A 96
7.6%
E 85
 
6.7%
N 76
 
6.0%
T 70
 
5.5%
D 44
 
3.5%
I 33
 
2.6%
Other values (14) 207
16.4%
Lowercase Letter
ValueCountFrequency (%)
s 16
20.0%
e 12
15.0%
g 11
13.8%
o 7
8.8%
b 6
 
7.5%
r 5
 
6.2%
w 4
 
5.0%
t 4
 
5.0%
c 3
 
3.8%
n 2
 
2.5%
Other values (7) 10
12.5%
Decimal Number
ValueCountFrequency (%)
1 13182
31.8%
2 6271
15.1%
3 4785
 
11.6%
0 3438
 
8.3%
5 3034
 
7.3%
6 2837
 
6.9%
4 2828
 
6.8%
7 2036
 
4.9%
8 1674
 
4.0%
9 1315
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 10284
99.9%
? 3
 
< 0.1%
. 2
 
< 0.1%
@ 2
 
< 0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
* 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 9243
99.9%
] 10
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 9243
99.9%
[ 10
 
0.1%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
55307
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 702
100.0%
Math Symbol
ValueCountFrequency (%)
~ 41
100.0%
Other Symbol
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202676
61.4%
Common 126250
38.2%
Latin 1349
 
0.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11553
 
5.7%
10711
 
5.3%
10415
 
5.1%
9857
 
4.9%
9815
 
4.8%
9368
 
4.6%
9060
 
4.5%
9059
 
4.5%
7558
 
3.7%
4963
 
2.4%
Other values (512) 110317
54.4%
Latin
ValueCountFrequency (%)
B 232
17.2%
S 189
14.0%
G 127
9.4%
C 107
 
7.9%
A 96
 
7.1%
E 85
 
6.3%
N 76
 
5.6%
T 70
 
5.2%
D 44
 
3.3%
I 33
 
2.4%
Other values (33) 290
21.5%
Common
ValueCountFrequency (%)
55307
43.8%
1 13182
 
10.4%
, 10284
 
8.1%
) 9243
 
7.3%
( 9243
 
7.3%
2 6271
 
5.0%
3 4785
 
3.8%
0 3438
 
2.7%
5 3034
 
2.4%
6 2837
 
2.2%
Other values (14) 8626
 
6.8%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202648
61.4%
ASCII 127596
38.6%
None 28
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55307
43.3%
1 13182
 
10.3%
, 10284
 
8.1%
) 9243
 
7.2%
( 9243
 
7.2%
2 6271
 
4.9%
3 4785
 
3.8%
0 3438
 
2.7%
5 3034
 
2.4%
6 2837
 
2.2%
Other values (55) 9972
 
7.8%
Hangul
ValueCountFrequency (%)
11553
 
5.7%
10711
 
5.3%
10415
 
5.1%
9857
 
4.9%
9815
 
4.8%
9368
 
4.6%
9060
 
4.5%
9059
 
4.5%
7558
 
3.7%
4963
 
2.4%
Other values (511) 110289
54.4%
None
ValueCountFrequency (%)
28
100.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1875
Distinct (%)20.8%
Missing966
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean5031.8896
Minimum1002
Maximum47292
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:31:47.293808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1002
5-th percentile1751
Q14147
median4563
Q36326
95-th percentile8288
Maximum47292
Range46290
Interquartile range (IQR)2179

Descriptive statistics

Standard deviation1921.3609
Coefficient of variation (CV)0.38183684
Kurtosis25.202587
Mean5031.8896
Median Absolute Deviation (MAD)1257
Skewness1.3191226
Sum45458091
Variance3691627.5
MonotonicityNot monotonic
2024-05-10T23:31:47.845350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4530 715
 
7.1%
4377 327
 
3.3%
4533 315
 
3.1%
4572 209
 
2.1%
4563 175
 
1.8%
6164 129
 
1.3%
6546 128
 
1.3%
7998 126
 
1.3%
8209 106
 
1.1%
4509 103
 
1.0%
Other values (1865) 6701
67.0%
(Missing) 966
 
9.7%
ValueCountFrequency (%)
1002 1
 
< 0.1%
1010 1
 
< 0.1%
1011 1
 
< 0.1%
1012 1
 
< 0.1%
1015 1
 
< 0.1%
1030 1
 
< 0.1%
1036 1
 
< 0.1%
1041 2
< 0.1%
1047 3
< 0.1%
1053 1
 
< 0.1%
ValueCountFrequency (%)
47292 1
 
< 0.1%
14347 1
 
< 0.1%
8863 1
 
< 0.1%
8862 1
 
< 0.1%
8859 1
 
< 0.1%
8852 1
 
< 0.1%
8849 8
0.1%
8846 1
 
< 0.1%
8838 1
 
< 0.1%
8835 1
 
< 0.1%
Distinct5471
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T23:31:48.447028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length7.1554
Min length1

Characters and Unicode

Total characters71554
Distinct characters1015
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4574 ?
Unique (%)45.7%

Sample

1st row(주)신세계푸드
2nd row(주)신풍특산
3rd row(주)해심
4th row곱 문래점
5th row투단미
ValueCountFrequency (%)
주식회사 890
 
6.9%
한시적영업 244
 
1.9%
농업회사법인 100
 
0.8%
월드푸드 97
 
0.8%
주)케이프라이드 91
 
0.7%
주)마켓인 84
 
0.7%
수라원 77
 
0.6%
주)푸드뱅크코리아 74
 
0.6%
주)신세계푸드 64
 
0.5%
아띠몽 64
 
0.5%
Other values (6052) 11037
86.1%
2024-05-10T23:31:49.840865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3213
 
4.5%
) 3030
 
4.2%
( 2952
 
4.1%
2844
 
4.0%
1709
 
2.4%
1680
 
2.3%
1450
 
2.0%
1449
 
2.0%
1283
 
1.8%
1210
 
1.7%
Other values (1005) 50734
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59457
83.1%
Close Punctuation 3030
 
4.2%
Open Punctuation 2952
 
4.1%
Space Separator 2844
 
4.0%
Lowercase Letter 1589
 
2.2%
Uppercase Letter 1295
 
1.8%
Decimal Number 215
 
0.3%
Other Punctuation 147
 
0.2%
Dash Punctuation 19
 
< 0.1%
Connector Punctuation 4
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3213
 
5.4%
1709
 
2.9%
1680
 
2.8%
1450
 
2.4%
1449
 
2.4%
1283
 
2.2%
1210
 
2.0%
1154
 
1.9%
1128
 
1.9%
1074
 
1.8%
Other values (928) 44107
74.2%
Uppercase Letter
ValueCountFrequency (%)
E 118
 
9.1%
O 95
 
7.3%
A 93
 
7.2%
S 88
 
6.8%
F 76
 
5.9%
B 71
 
5.5%
L 71
 
5.5%
R 69
 
5.3%
D 64
 
4.9%
I 64
 
4.9%
Other values (16) 486
37.5%
Lowercase Letter
ValueCountFrequency (%)
e 247
15.5%
o 157
 
9.9%
a 146
 
9.2%
t 98
 
6.2%
r 94
 
5.9%
n 90
 
5.7%
l 83
 
5.2%
i 83
 
5.2%
s 78
 
4.9%
c 69
 
4.3%
Other values (15) 444
27.9%
Decimal Number
ValueCountFrequency (%)
2 49
22.8%
0 34
15.8%
1 25
11.6%
3 22
10.2%
5 19
 
8.8%
7 17
 
7.9%
8 16
 
7.4%
9 15
 
7.0%
4 12
 
5.6%
6 6
 
2.8%
Other Punctuation
ValueCountFrequency (%)
& 71
48.3%
. 20
 
13.6%
, 19
 
12.9%
? 16
 
10.9%
' 9
 
6.1%
! 6
 
4.1%
* 4
 
2.7%
1
 
0.7%
: 1
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 3030
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2952
100.0%
Space Separator
ValueCountFrequency (%)
2844
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59433
83.1%
Common 9212
 
12.9%
Latin 2884
 
4.0%
Han 25
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3213
 
5.4%
1709
 
2.9%
1680
 
2.8%
1450
 
2.4%
1449
 
2.4%
1283
 
2.2%
1210
 
2.0%
1154
 
1.9%
1128
 
1.9%
1074
 
1.8%
Other values (906) 44083
74.2%
Latin
ValueCountFrequency (%)
e 247
 
8.6%
o 157
 
5.4%
a 146
 
5.1%
E 118
 
4.1%
t 98
 
3.4%
O 95
 
3.3%
r 94
 
3.3%
A 93
 
3.2%
n 90
 
3.1%
S 88
 
3.1%
Other values (41) 1658
57.5%
Common
ValueCountFrequency (%)
) 3030
32.9%
( 2952
32.0%
2844
30.9%
& 71
 
0.8%
2 49
 
0.5%
0 34
 
0.4%
1 25
 
0.3%
3 22
 
0.2%
. 20
 
0.2%
, 19
 
0.2%
Other values (15) 146
 
1.6%
Han
ValueCountFrequency (%)
2
 
8.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (13) 13
52.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59426
83.1%
ASCII 12095
 
16.9%
CJK 22
 
< 0.1%
Compat Jamo 6
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3213
 
5.4%
1709
 
2.9%
1680
 
2.8%
1450
 
2.4%
1449
 
2.4%
1283
 
2.2%
1210
 
2.0%
1154
 
1.9%
1128
 
1.9%
1074
 
1.8%
Other values (900) 44076
74.2%
ASCII
ValueCountFrequency (%)
) 3030
25.1%
( 2952
24.4%
2844
23.5%
e 247
 
2.0%
o 157
 
1.3%
a 146
 
1.2%
E 118
 
1.0%
t 98
 
0.8%
O 95
 
0.8%
r 94
 
0.8%
Other values (65) 2314
19.1%
Compat Jamo
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
CJK
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (10) 10
45.5%
CJK Compat Ideographs
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct6734
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1999-03-12 00:00:00
Maximum2024-05-09 17:51:08
2024-05-10T23:31:50.482123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:31:51.113228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
U
6310 
I
3688 
D
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 6310
63.1%
I 3688
36.9%
D 2
 
< 0.1%

Length

2024-05-10T23:31:51.761493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:52.215571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 6310
63.1%
i 3688
36.9%
d 2
 
< 0.1%
Distinct1375
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-10T23:31:52.659806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:31:53.364478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
9938 
<NA>
 
59
기타
 
3

Length

Max length9
Median length9
Mean length8.9684
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9938
99.4%
<NA> 59
 
0.6%
기타 3
 
< 0.1%

Length

2024-05-10T23:31:53.811284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:54.131934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9938
99.4%
na 59
 
0.6%
기타 3
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct3386
Distinct (%)34.6%
Missing212
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean199254.74
Minimum182524.82
Maximum387688.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:31:54.505951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182524.82
5-th percentile188729.19
Q1196594.06
median198263.91
Q3203401.31
95-th percentile209913.83
Maximum387688.44
Range205163.62
Interquartile range (IQR)6807.2524

Descriptive statistics

Standard deviation6463.1702
Coefficient of variation (CV)0.03243672
Kurtosis73.279816
Mean199254.74
Median Absolute Deviation (MAD)4202.8927
Skewness2.4452921
Sum1.9503054 × 109
Variance41772570
MonotonicityNot monotonic
2024-05-10T23:31:54.947871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198263.90839194 713
 
7.1%
198259.65357739 469
 
4.7%
196762.077394917 355
 
3.5%
201823.908977364 222
 
2.2%
200613.510297669 176
 
1.8%
200250.447804795 128
 
1.3%
188884.075622342 126
 
1.3%
190107.045415333 106
 
1.1%
205210.358779172 95
 
0.9%
196813.258497258 92
 
0.9%
Other values (3376) 7306
73.1%
(Missing) 212
 
2.1%
ValueCountFrequency (%)
182524.823835629 27
0.3%
182876.367858149 1
 
< 0.1%
182944.731406147 1
 
< 0.1%
183007.220061564 1
 
< 0.1%
183057.177845017 1
 
< 0.1%
183225.928107356 1
 
< 0.1%
183307.197874057 5
 
0.1%
183310.626609467 1
 
< 0.1%
183317.969623951 2
 
< 0.1%
183343.938672429 1
 
< 0.1%
ValueCountFrequency (%)
387688.441613365 1
 
< 0.1%
215303.913311463 5
 
0.1%
215279.715657108 1
 
< 0.1%
215181.448713688 1
 
< 0.1%
215179.900827427 1
 
< 0.1%
215060.679642858 1
 
< 0.1%
215033.44426991 1
 
< 0.1%
215010.763627235 14
0.1%
214847.417797592 1
 
< 0.1%
214761.228719522 3
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct3384
Distinct (%)34.6%
Missing212
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean449563.81
Minimum185991.5
Maximum465066.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:31:55.346862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185991.5
5-th percentile441993.85
Q1446857.79
median450278.1
Q3451817.52
95-th percentile458028.98
Maximum465066.42
Range279074.92
Interquartile range (IQR)4959.7235

Descriptive statistics

Standard deviation5318.4598
Coefficient of variation (CV)0.011830267
Kurtosis615.68208
Mean449563.81
Median Absolute Deviation (MAD)2623.6744
Skewness-12.219428
Sum4.4003305 × 109
Variance28286015
MonotonicityNot monotonic
2024-05-10T23:31:55.857905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450960.762964932 713
 
7.1%
451392.198218657 469
 
4.7%
447480.039577359 355
 
3.5%
452076.818664092 222
 
2.2%
451817.515366883 176
 
1.8%
444683.220506107 128
 
1.3%
447186.888604306 126
 
1.3%
445157.626366229 106
 
1.1%
445154.42225208 95
 
0.9%
447881.970772064 92
 
0.9%
Other values (3374) 7306
73.1%
(Missing) 212
 
2.1%
ValueCountFrequency (%)
185991.498403346 1
< 0.1%
435405.631407888 1
< 0.1%
437860.476197184 1
< 0.1%
437887.474322994 1
< 0.1%
437898.766330059 2
< 0.1%
438311.916078002 1
< 0.1%
438400.973299439 2
< 0.1%
438410.522111193 1
< 0.1%
438622.881788184 1
< 0.1%
438657.135608207 1
< 0.1%
ValueCountFrequency (%)
465066.422725731 1
 
< 0.1%
464840.183818755 1
 
< 0.1%
464814.717432497 1
 
< 0.1%
464552.486156478 1
 
< 0.1%
464474.910004698 1
 
< 0.1%
464463.403607965 9
0.1%
464199.048415229 1
 
< 0.1%
463898.587913996 1
 
< 0.1%
463898.535477145 1
 
< 0.1%
463887.942604325 1
 
< 0.1%

위생업태명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6339 
즉석판매제조가공업
3658 
기타
 
3

Length

Max length9
Median length4
Mean length5.8284
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6339
63.4%
즉석판매제조가공업 3658
36.6%
기타 3
 
< 0.1%

Length

2024-05-10T23:31:56.838542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:57.179311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6339
63.4%
즉석판매제조가공업 3658
36.6%
기타 3
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9564 
0
 
398
1
 
29
2
 
8
3
 
1

Length

Max length4
Median length4
Mean length3.8692
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> 9564
95.6%
0 398
 
4.0%
1 29
 
0.3%
2 8
 
0.1%
3 1
 
< 0.1%

Length

2024-05-10T23:31:57.540404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:57.863065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9564
95.6%
0 398
 
4.0%
1 29
 
0.3%
2 8
 
0.1%
3 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9569 
0
 
403
1
 
27
2
 
1

Length

Max length4
Median length4
Mean length3.8707
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> 9569
95.7%
0 403
 
4.0%
1 27
 
0.3%
2 1
 
< 0.1%

Length

2024-05-10T23:31:58.285843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:58.759299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9569
95.7%
0 403
 
4.0%
1 27
 
0.3%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9746 
기타
 
206
주택가주변
 
40
아파트지역
 
6
유흥업소밀집지역
 
2

Length

Max length8
Median length4
Mean length3.9642
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9746
97.5%
기타 206
 
2.1%
주택가주변 40
 
0.4%
아파트지역 6
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

Length

2024-05-10T23:31:59.252705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:31:59.772116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9746
97.5%
기타 206
 
2.1%
주택가주변 40
 
0.4%
아파트지역 6
 
0.1%
유흥업소밀집지역 2
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9746 
기타
 
235
자율
 
16
 
2
 
1

Length

Max length4
Median length4
Mean length3.9489
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> 9746
97.5%
기타 235
 
2.4%
자율 16
 
0.2%
2
 
< 0.1%
1
 
< 0.1%

Length

2024-05-10T23:32:00.173097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:00.871418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9746
97.5%
기타 235
 
2.4%
자율 16
 
0.2%
2
 
< 0.1%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9557 
상수도전용
 
440
지하수전용
 
2
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.0455
Min length4

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> 9557
95.6%
상수도전용 440
 
4.4%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-05-10T23:32:01.415493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:01.896322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9557
95.6%
상수도전용 440
 
4.4%
지하수전용 2
 
< 0.1%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9721 
0
 
279

Length

Max length4
Median length4
Mean length3.9163
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> 9721
97.2%
0 279
 
2.8%

Length

2024-05-10T23:32:02.355551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:02.674241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9721
97.2%
0 279
 
2.8%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9021 
0
969 
2
 
6
1
 
4

Length

Max length4
Median length4
Mean length3.7063
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 9021
90.2%
0 969
 
9.7%
2 6
 
0.1%
1 4
 
< 0.1%

Length

2024-05-10T23:32:03.014169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:03.460626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9021
90.2%
0 969
 
9.7%
2 6
 
0.1%
1 4
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9026 
0
971 
1
 
1
6
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.7078
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 9026
90.3%
0 971
 
9.7%
1 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-05-10T23:32:03.901661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:04.257979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9026
90.3%
0 971
 
9.7%
1 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)1.3%
Missing8897
Missing (%)89.0%
Infinite0
Infinite (%)0.0%
Mean0.356301
Minimum0
Maximum15
Zeros959
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:32:04.606120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2232524
Coefficient of variation (CV)3.4331994
Kurtosis48.318135
Mean0.356301
Median Absolute Deviation (MAD)0
Skewness5.8985795
Sum393
Variance1.4963464
MonotonicityNot monotonic
2024-05-10T23:32:04.990064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 959
 
9.6%
2 68
 
0.7%
1 29
 
0.3%
3 22
 
0.2%
4 9
 
0.1%
5 5
 
0.1%
8 2
 
< 0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
11 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 8897
89.0%
ValueCountFrequency (%)
0 959
9.6%
1 29
 
0.3%
2 68
 
0.7%
3 22
 
0.2%
4 9
 
0.1%
5 5
 
0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 2
 
< 0.1%
5 5
0.1%
4 9
0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9018 
0
969 
1
 
10
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.7054
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 9018
90.2%
0 969
 
9.7%
1 10
 
0.1%
2 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-05-10T23:32:05.411083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:05.753412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9018
90.2%
0 969
 
9.7%
1 10
 
0.1%
2 1
 
< 0.1%
4 1
 
< 0.1%
3 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8144 
자가
1010 
임대
846 

Length

Max length4
Median length4
Mean length3.6288
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8144
81.4%
자가 1010
 
10.1%
임대 846
 
8.5%

Length

2024-05-10T23:32:06.102728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:06.449771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8144
81.4%
자가 1010
 
10.1%
임대 846
 
8.5%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9454 
0
 
543
40000000
 
1
8000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.8382
Min length1

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> 9454
94.5%
0 543
 
5.4%
40000000 1
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%

Length

2024-05-10T23:32:06.832888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:07.183815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9454
94.5%
0 543
 
5.4%
40000000 1
 
< 0.1%
8000000 1
 
< 0.1%
10000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9454 
0
 
543
300000
 
1
500000
 
1
450000
 
1

Length

Max length6
Median length4
Mean length3.8377
Min length1

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> 9454
94.5%
0 543
 
5.4%
300000 1
 
< 0.1%
500000 1
 
< 0.1%
450000 1
 
< 0.1%

Length

2024-05-10T23:32:07.476350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:32:07.667975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9454
94.5%
0 543
 
5.4%
300000 1
 
< 0.1%
500000 1
 
< 0.1%
450000 1
 
< 0.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing6281
Missing (%)62.8%
Memory size97.7 KiB
False
3718 
True
 
1
(Missing)
6281 
ValueCountFrequency (%)
False 3718
37.2%
True 1
 
< 0.1%
(Missing) 6281
62.8%
2024-05-10T23:32:07.900202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct124
Distinct (%)3.3%
Missing6281
Missing (%)62.8%
Infinite0
Infinite (%)0.0%
Mean1.4361119
Minimum0
Maximum140.7
Zeros3310
Zeros (%)33.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T23:32:08.221140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6.03
Maximum140.7
Range140.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.29614
Coefficient of variation (CV)5.0804817
Kurtosis109.40924
Mean1.4361119
Median Absolute Deviation (MAD)0
Skewness9.0983633
Sum5340.9
Variance53.233659
MonotonicityNot monotonic
2024-05-10T23:32:08.645224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3310
33.1%
3.3 191
 
1.9%
10.0 15
 
0.1%
6.6 12
 
0.1%
13.2 10
 
0.1%
3.0 9
 
0.1%
9.0 7
 
0.1%
6.0 6
 
0.1%
16.5 6
 
0.1%
33.0 5
 
0.1%
Other values (114) 148
 
1.5%
(Missing) 6281
62.8%
ValueCountFrequency (%)
0.0 3310
33.1%
2.0 3
 
< 0.1%
3.0 9
 
0.1%
3.1 1
 
< 0.1%
3.24 1
 
< 0.1%
3.3 191
 
1.9%
3.5 1
 
< 0.1%
4.0 3
 
< 0.1%
4.4 1
 
< 0.1%
5.0 4
 
< 0.1%
ValueCountFrequency (%)
140.7 1
< 0.1%
126.13 1
< 0.1%
96.92 1
< 0.1%
92.34 1
< 0.1%
90.0 1
< 0.1%
85.5 1
< 0.1%
80.94 1
< 0.1%
74.74 1
< 0.1%
72.0 1
< 0.1%
68.1 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
750330600003060000-107-2023-002762023-12-26<NA>3폐업2폐업2024-01-11<NA><NA><NA><NA><NA>131-809서울특별시 중랑구 망우동 506-1 E-마트 상봉점서울특별시 중랑구 상봉로 118, E-마트 상봉점 (망우동)2169(주)신세계푸드2024-01-12 04:15:12U2023-11-30 23:04:00.0즉석판매제조가공업208183.558935454911.248523<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1931430100003010000-107-2017-0042420171024<NA>3폐업2폐업20171126<NA><NA><NA>02 4737910<NA>100162서울특별시 중구 봉래동2가 122 롯데마트서울역점 2층서울특별시 중구 청파로 426 (봉래동2가, 롯데마트서울역점 2층)4509(주)신풍특산2017-11-27 04:15:25I2018-08-31 23:59:59.0즉석판매제조가공업197243.215346450655.10424즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
2369530300003030000-107-2016-0008620161007<NA>3폐업2폐업20161105<NA><NA><NA><NA><NA>133070서울특별시 성동구 행당동 346서울특별시 성동구 행당로 82, 지하3층 (행당동, 롯데마트행당역점내)4717(주)해심2016-11-06 04:15:24I2018-08-31 23:59:59.0즉석판매제조가공업202511.142931450401.303716즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1165031800003180000-107-2024-000332024-01-26<NA>1영업/정상1영업<NA><NA><NA><NA>022633520182.5150-835서울특별시 영등포구 문래동3가 55-5 로데오 ? 쇼핑몰서울특별시 영등포구 당산로 34, 로데오 ? 쇼핑몰 118호 (문래동3가)7297곱 문래점2024-01-26 15:26:53I2023-11-30 22:08:00.0즉석판매제조가공업190777.430587446138.269919<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1602830000003000000-107-2019-0016620191220<NA>3폐업2폐업20201218<NA><NA><NA><NA>232.58110054서울특별시 종로구 사직동 1-41서울특별시 종로구 인왕산로 5, 지상1층 (사직동)3028투단미2020-12-18 10:41:50U2020-12-20 02:40:00.0즉석판매제조가공업197011.024973452511.723705즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
1557630000003000000-107-2003-0001720030514<NA>3폐업2폐업20121112<NA><NA><NA>02 7649990<NA>110807서울특별시 종로구 돈의동 17-1서울특별시 종로구 수표로28길 44 (돈의동)3133종로두부2012-03-19 13:01:49I2018-08-31 23:59:59.0즉석판매제조가공업199112.911401452327.07349즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1944930100003010000-107-2018-0029220180711<NA>3폐업2폐업20180718<NA><NA><NA><NA>3.3100011서울특별시 중구 충무로1가 52-5 신세계백화점 본점 지하1층서울특별시 중구 소공로 63, 신세계백화점 본점 지하1층 (충무로1가)4530설봄2018-07-19 04:15:08I2018-08-31 23:59:59.0즉석판매제조가공업198263.908392450960.762965즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N3.3<NA><NA><NA>
1816130100003010000-107-1996-0012219961129<NA>3폐업2폐업20000630<NA><NA><NA>02 312192927.6100372서울특별시 중구 만리동2가 12-42<NA><NA>한국방앗간2000-06-30 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업196876.247441450275.559172즉석판매제조가공업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1627730000003000000-107-2018-0005720180928<NA>3폐업2폐업20181030<NA><NA><NA>031 952 1448<NA>110054서울특별시 종로구 사직동 9 서서울농협하나마트 내서울특별시 종로구 사직로8길 4 (사직동, 광화문 풍림스페이스본)3168(주)세원2018-10-31 04:15:09U2018-11-02 02:36:53.0즉석판매제조가공업197181.393302452458.826652즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
1865530100003010000-107-2016-0006020160511<NA>3폐업2폐업20180620<NA><NA><NA>022253595913.2100823서울특별시 중구 신당동 241-6서울특별시 중구 다산로35길 19, 지하1층 (신당동)4611구수하니 현미누룽지2018-06-20 10:01:52I2018-08-31 23:59:59.0즉석판매제조가공업201216.130816451269.358649즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N13.2<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
605931400003140000-107-2023-003712023-09-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.0158-879서울특별시 양천구 목동 909-6 목동우방빌딩서울특별시 양천구 목동동로 431, 목동우방빌딩 101호 (목동)7984포르코피자2023-09-26 15:20:43I2022-12-08 22:08:00.0즉석판매제조가공업189709.803505448328.288936<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
498030300003030000-107-2023-001142023-06-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0133-871서울특별시 성동구 행당동 3-10서울특별시 성동구 마조로7길 9-1, 1층 (행당동)4760쭈식이 상회2023-10-25 12:35:39U2022-10-30 22:07:00.0즉석판매제조가공업203472.704074450936.938171<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2080330100003010000-107-2021-0033020210817<NA>3폐업2폐업20210902<NA><NA><NA><NA><NA>100070서울특별시 중구 소공동 1서울특별시 중구 남대문로 81, 지하1층 (소공동)4533(주)푸드트립2021-09-03 04:15:09U2021-09-05 02:40:00.0즉석판매제조가공업198259.653577451392.198219즉석판매제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
2158830200003020000-107-2020-0011320200529<NA>1영업/정상1영업<NA><NA><NA><NA><NA>48.0140886서울특별시 용산구 한남동 68-27서울특별시 용산구 한남대로20길 21-14, 3층 (한남동)4419산수화2020-05-29 11:43:48I2020-05-31 00:23:29.0즉석판매제조가공업200717.111496448118.294524즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
1199531400003140000-107-2024-001362024-04-08<NA>3폐업2폐업2024-04-11<NA><NA><NA><NA>0.0158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998이스터에그2024-04-12 04:15:08U2023-12-03 23:04:00.0즉석판매제조가공업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1051730400003040000-107-2024-000092024-01-09<NA>3폐업2폐업2024-01-31<NA><NA><NA><NA><NA>143-758서울특별시 광진구 자양동 227-342 롯데백화점 지하1층서울특별시 광진구 능동로 92, 롯데백화점 지하1층 (자양동)5065마더앤피쉬2024-02-01 04:15:08U2023-12-02 00:03:00.0즉석판매제조가공업206217.434726448506.218744<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
933032100003210000-107-2024-000032024-01-02<NA>3폐업2폐업2024-01-10<NA><NA><NA><NA>0.0137-140서울특별시 서초구 우면동 728 황금빌딩서울특별시 서초구 태봉로 60, 이마트에브리데이 우면점 1층 (우면동)6764(주)행복생활에프앤비2024-01-11 04:15:09U2023-11-30 23:03:00.0즉석판매제조가공업202151.207983440152.039103<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1284830700003070000-107-2024-000932024-04-23<NA>3폐업2폐업2024-05-02<NA><NA><NA><NA><NA>136-719서울특별시 성북구 길음동 20-1 현대백화점미아점서울특별시 성북구 동소문로 315, 현대백화점미아점 지하1층 (길음동)2730미식동원2024-05-03 04:15:09U2023-12-05 00:05:00.0즉석판매제조가공업202466.801085456227.571721<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1160031600003160000-107-2024-000302024-01-23<NA>3폐업2폐업2024-02-24<NA><NA><NA><NA>0.0152-848서울특별시 구로구 구로동 188-26 이마트구로점서울특별시 구로구 디지털로32길 43, 이마트구로점 1층 (구로동)8379(주)마켓인2024-02-25 04:15:09U2023-12-01 22:07:00.0즉석판매제조가공업190901.977947442466.813411<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1173431800003180000-107-2024-000322024-01-26<NA>1영업/정상1영업<NA><NA><NA><NA>02882120861.16150-092서울특별시 영등포구 문래동2가 42-10서울특별시 영등포구 경인로79길 17-1, 1층 (문래동2가)7290원조마늘곱창2024-01-26 15:16:56I2023-11-30 22:08:00.0즉석판매제조가공업190510.115973445677.198902<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>