Overview

Dataset statistics

Number of variables44
Number of observations2057
Missing cells20556
Missing cells (%)22.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory755.4 KiB
Average record size in memory376.1 B

Variable types

Categorical21
Text6
DateTime4
Unsupported7
Numeric5
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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-18243/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (60.9%)Imbalance
위생업태명 is highly imbalanced (67.3%)Imbalance
영업장주변구분명 is highly imbalanced (50.5%)Imbalance
급수시설구분명 is highly imbalanced (73.9%)Imbalance
총인원 is highly imbalanced (87.9%)Imbalance
보증액 is highly imbalanced (50.9%)Imbalance
월세액 is highly imbalanced (50.9%)Imbalance
인허가취소일자 has 2057 (100.0%) missing valuesMissing
폐업일자 has 233 (11.3%) missing valuesMissing
휴업시작일자 has 2057 (100.0%) missing valuesMissing
휴업종료일자 has 2057 (100.0%) missing valuesMissing
재개업일자 has 2057 (100.0%) missing valuesMissing
전화번호 has 453 (22.0%) missing valuesMissing
소재지면적 has 1773 (86.2%) missing valuesMissing
도로명주소 has 1528 (74.3%) missing valuesMissing
도로명우편번호 has 1540 (74.9%) missing valuesMissing
좌표정보(X) has 189 (9.2%) missing valuesMissing
좌표정보(Y) has 189 (9.2%) missing valuesMissing
다중이용업소여부 has 123 (6.0%) missing valuesMissing
시설총규모 has 123 (6.0%) missing valuesMissing
전통업소지정번호 has 2057 (100.0%) missing valuesMissing
전통업소주된음식 has 2057 (100.0%) missing valuesMissing
홈페이지 has 2057 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 21.47516024)Skewed
시설총규모 is highly skewed (γ1 = 42.1344521)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 101 (4.9%) zerosZeros
시설총규모 has 1882 (91.5%) zerosZeros

Reproduction

Analysis started2024-04-29 19:40:15.917700
Analysis finished2024-04-29 19:40:17.197773
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
3160000
2057 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 2057
100.0%

Length

2024-04-30T04:40:17.257412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:17.340330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 2057
100.0%

관리번호
Text

UNIQUE 

Distinct2057
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2024-04-30T04:40:17.488590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters45254
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

Unique2057 ?
Unique (%)100.0%

Sample

1st row3160000-112-1983-00002
2nd row3160000-112-1983-00004
3rd row3160000-112-1983-00005
4th row3160000-112-1983-00006
5th row3160000-112-1983-00007
ValueCountFrequency (%)
3160000-112-1983-00002 1
 
< 0.1%
3160000-112-2003-00213 1
 
< 0.1%
3160000-112-2003-00178 1
 
< 0.1%
3160000-112-2003-00177 1
 
< 0.1%
3160000-112-2003-00176 1
 
< 0.1%
3160000-112-2003-00175 1
 
< 0.1%
3160000-112-2003-00174 1
 
< 0.1%
3160000-112-2003-00173 1
 
< 0.1%
3160000-112-2003-00172 1
 
< 0.1%
3160000-112-2003-00171 1
 
< 0.1%
Other values (2047) 2047
99.5%
2024-04-30T04:40:17.768280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15335
33.9%
1 8528
18.8%
- 6171
13.6%
2 4158
 
9.2%
3 3060
 
6.8%
9 3049
 
6.7%
6 2591
 
5.7%
4 650
 
1.4%
8 639
 
1.4%
5 554
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39083
86.4%
Dash Punctuation 6171
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15335
39.2%
1 8528
21.8%
2 4158
 
10.6%
3 3060
 
7.8%
9 3049
 
7.8%
6 2591
 
6.6%
4 650
 
1.7%
8 639
 
1.6%
5 554
 
1.4%
7 519
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 6171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45254
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15335
33.9%
1 8528
18.8%
- 6171
13.6%
2 4158
 
9.2%
3 3060
 
6.8%
9 3049
 
6.7%
6 2591
 
5.7%
4 650
 
1.4%
8 639
 
1.4%
5 554
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45254
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15335
33.9%
1 8528
18.8%
- 6171
13.6%
2 4158
 
9.2%
3 3060
 
6.8%
9 3049
 
6.7%
6 2591
 
5.7%
4 650
 
1.4%
8 639
 
1.4%
5 554
 
1.2%

인허가일자
Date

Distinct1044
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1983-02-22 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:40:17.886687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:18.024194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
3
1824 
1
233 

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 1824
88.7%
1 233
 
11.3%

Length

2024-04-30T04:40:18.132250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:18.215971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1824
88.7%
1 233
 
11.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
폐업
1824 
영업/정상
233 

Length

Max length5
Median length2
Mean length2.3398153
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1824
88.7%
영업/정상 233
 
11.3%

Length

2024-04-30T04:40:18.339669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:18.434408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1824
88.7%
영업/정상 233
 
11.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2
1824 
1
233 

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 1824
88.7%
1 233
 
11.3%

Length

2024-04-30T04:40:18.537517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:18.617038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1824
88.7%
1 233
 
11.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
폐업
1824 
영업
233 

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 1824
88.7%
영업 233
 
11.3%

Length

2024-04-30T04:40:18.709805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:18.790606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1824
88.7%
영업 233
 
11.3%

폐업일자
Date

MISSING 

Distinct1230
Distinct (%)67.4%
Missing233
Missing (%)11.3%
Memory size16.2 KiB
Minimum1994-06-22 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:40:18.892225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:19.007321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

전화번호
Text

MISSING 

Distinct1019
Distinct (%)63.5%
Missing453
Missing (%)22.0%
Memory size16.2 KiB
2024-04-30T04:40:19.231580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.3204489
Min length2

Characters and Unicode

Total characters13346
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

Unique979 ?
Unique (%)61.0%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 1142
45.9%
0 102
 
4.1%
0200000000 41
 
1.6%
00000 30
 
1.2%
0226361723 23
 
0.9%
9298400 14
 
0.6%
6828322 9
 
0.4%
0226363290 7
 
0.3%
0232728988 7
 
0.3%
0222128398 7
 
0.3%
Other values (1043) 1108
44.5%
2024-04-30T04:40:19.599565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2767
20.7%
2 2699
20.2%
6 1326
9.9%
1265
9.5%
8 1265
9.5%
1 809
 
6.1%
5 749
 
5.6%
3 743
 
5.6%
7 601
 
4.5%
9 561
 
4.2%
Other values (2) 561
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12080
90.5%
Space Separator 1265
 
9.5%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2767
22.9%
2 2699
22.3%
6 1326
11.0%
8 1265
10.5%
1 809
 
6.7%
5 749
 
6.2%
3 743
 
6.2%
7 601
 
5.0%
9 561
 
4.6%
4 560
 
4.6%
Space Separator
ValueCountFrequency (%)
1265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13346
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2767
20.7%
2 2699
20.2%
6 1326
9.9%
1265
9.5%
8 1265
9.5%
1 809
 
6.1%
5 749
 
5.6%
3 743
 
5.6%
7 601
 
4.5%
9 561
 
4.2%
Other values (2) 561
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2767
20.7%
2 2699
20.2%
6 1326
9.9%
1265
9.5%
8 1265
9.5%
1 809
 
6.1%
5 749
 
5.6%
3 743
 
5.6%
7 601
 
4.5%
9 561
 
4.2%
Other values (2) 561
 
4.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct66
Distinct (%)23.2%
Missing1773
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean7.2501761
Minimum0
Maximum303
Zeros101
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-04-30T04:40:19.727100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.105
Q33.3
95-th percentile32.6985
Maximum303
Range303
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation21.366086
Coefficient of variation (CV)2.9469747
Kurtosis130.6297
Mean7.2501761
Median Absolute Deviation (MAD)2.105
Skewness9.9143471
Sum2059.05
Variance456.50962
MonotonicityNot monotonic
2024-04-30T04:40:19.844381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 101
 
4.9%
3.3 69
 
3.4%
1.0 28
 
1.4%
3.0 14
 
0.7%
3.6 4
 
0.2%
16.5 2
 
0.1%
24.14 2
 
0.1%
2.0 2
 
0.1%
1.1 2
 
0.1%
24.9 2
 
0.1%
Other values (56) 58
 
2.8%
(Missing) 1773
86.2%
ValueCountFrequency (%)
0.0 101
4.9%
0.3 1
 
< 0.1%
0.5 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 28
 
1.4%
1.1 2
 
0.1%
1.33 1
 
< 0.1%
1.5 2
 
0.1%
1.6 1
 
< 0.1%
1.65 1
 
< 0.1%
ValueCountFrequency (%)
303.0 1
< 0.1%
80.0 1
< 0.1%
62.77 1
< 0.1%
56.0 1
< 0.1%
51.88 1
< 0.1%
50.82 1
< 0.1%
50.67 1
< 0.1%
47.25 1
< 0.1%
46.2 1
< 0.1%
39.23 1
< 0.1%

소재지우편번호
Text

Distinct174
Distinct (%)8.5%
Missing4
Missing (%)0.2%
Memory size16.2 KiB
2024-04-30T04:40:20.093274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0394545
Min length6

Characters and Unicode

Total characters12399
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

Unique50 ?
Unique (%)2.4%

Sample

1st row152806
2nd row152883
3rd row152887
4th row152805
5th row152815
ValueCountFrequency (%)
152848 67
 
3.3%
152862 65
 
3.2%
152894 63
 
3.1%
152888 53
 
2.6%
152845 53
 
2.6%
152880 52
 
2.5%
152842 48
 
2.3%
152800 46
 
2.2%
152826 46
 
2.2%
152840 44
 
2.1%
Other values (164) 1516
73.8%
2024-04-30T04:40:20.464556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2502
20.2%
2 2419
19.5%
1 2374
19.1%
8 2359
19.0%
0 683
 
5.5%
4 563
 
4.5%
6 440
 
3.5%
9 346
 
2.8%
7 338
 
2.7%
3 294
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12318
99.3%
Dash Punctuation 81
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2502
20.3%
2 2419
19.6%
1 2374
19.3%
8 2359
19.2%
0 683
 
5.5%
4 563
 
4.6%
6 440
 
3.6%
9 346
 
2.8%
7 338
 
2.7%
3 294
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12399
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2502
20.2%
2 2419
19.5%
1 2374
19.1%
8 2359
19.0%
0 683
 
5.5%
4 563
 
4.5%
6 440
 
3.5%
9 346
 
2.8%
7 338
 
2.7%
3 294
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2502
20.2%
2 2419
19.5%
1 2374
19.1%
8 2359
19.0%
0 683
 
5.5%
4 563
 
4.5%
6 440
 
3.5%
9 346
 
2.8%
7 338
 
2.7%
3 294
 
2.4%

지번주소
Text

Distinct1707
Distinct (%)83.1%
Missing2
Missing (%)0.1%
Memory size16.2 KiB
2024-04-30T04:40:20.775719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length22.522628
Min length15

Characters and Unicode

Total characters46284
Distinct characters337
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1501 ?
Unique (%)73.0%

Sample

1st row서울특별시 구로구 개봉동 170-33
2nd row서울특별시 구로구 궁동 198-0
3rd row서울특별시 구로구 신도림동 410-0
4th row서울특별시 구로구 개봉동 157-0
5th row서울특별시 구로구 개봉동 353-2
ValueCountFrequency (%)
서울특별시 2053
22.7%
구로구 2052
22.7%
구로동 992
 
11.0%
개봉동 296
 
3.3%
고척동 226
 
2.5%
오류동 211
 
2.3%
신도림동 129
 
1.4%
가리봉동 88
 
1.0%
온수동 44
 
0.5%
궁동 40
 
0.4%
Other values (1919) 2908
32.2%
2024-04-30T04:40:21.214528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8882
19.2%
구 5163
 
11.2%
로 3091
 
6.7%
동 2128
 
4.6%
서 2064
 
4.5%
시 2063
 
4.5%
울 2057
 
4.4%
특 2053
 
4.4%
별 2053
 
4.4%
1 2045
 
4.4%
Other values (327) 14685
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25833
55.8%
Decimal Number 9474
 
20.5%
Space Separator 8882
 
19.2%
Dash Punctuation 1928
 
4.2%
Uppercase Letter 43
 
0.1%
Close Punctuation 41
 
0.1%
Open Punctuation 40
 
0.1%
Other Punctuation 32
 
0.1%
Lowercase Letter 9
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 5163
20.0%
로 3091
12.0%
동 2128
8.2%
서 2064
 
8.0%
시 2063
 
8.0%
울 2057
 
8.0%
특 2053
 
7.9%
별 2053
 
7.9%
봉 399
 
1.5%
개 311
 
1.2%
Other values (286) 4451
17.2%
Uppercase Letter
ValueCountFrequency (%)
B 12
27.9%
D 6
14.0%
A 4
 
9.3%
K 4
 
9.3%
G 3
 
7.0%
S 3
 
7.0%
L 3
 
7.0%
C 2
 
4.7%
Z 1
 
2.3%
F 1
 
2.3%
Other values (4) 4
 
9.3%
Decimal Number
ValueCountFrequency (%)
1 2045
21.6%
2 1140
12.0%
3 1056
11.1%
0 966
10.2%
4 921
9.7%
5 805
 
8.5%
7 755
 
8.0%
6 747
 
7.9%
8 554
 
5.8%
9 485
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
w 2
22.2%
t 1
11.1%
s 1
11.1%
x 1
11.1%
a 1
11.1%
e 1
11.1%
i 1
11.1%
v 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 23
71.9%
. 7
 
21.9%
@ 2
 
6.2%
Space Separator
ValueCountFrequency (%)
8882
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1928
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25832
55.8%
Common 20398
44.1%
Latin 53
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 5163
20.0%
로 3091
12.0%
동 2128
8.2%
서 2064
 
8.0%
시 2063
 
8.0%
울 2057
 
8.0%
특 2053
 
7.9%
별 2053
 
7.9%
봉 399
 
1.5%
개 311
 
1.2%
Other values (285) 4450
17.2%
Latin
ValueCountFrequency (%)
B 12
22.6%
D 6
11.3%
A 4
 
7.5%
K 4
 
7.5%
G 3
 
5.7%
S 3
 
5.7%
L 3
 
5.7%
w 2
 
3.8%
C 2
 
3.8%
Z 1
 
1.9%
Other values (13) 13
24.5%
Common
ValueCountFrequency (%)
8882
43.5%
1 2045
 
10.0%
- 1928
 
9.5%
2 1140
 
5.6%
3 1056
 
5.2%
0 966
 
4.7%
4 921
 
4.5%
5 805
 
3.9%
7 755
 
3.7%
6 747
 
3.7%
Other values (8) 1153
 
5.7%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25832
55.8%
ASCII 20450
44.2%
CJK 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8882
43.4%
1 2045
 
10.0%
- 1928
 
9.4%
2 1140
 
5.6%
3 1056
 
5.2%
0 966
 
4.7%
4 921
 
4.5%
5 805
 
3.9%
7 755
 
3.7%
6 747
 
3.7%
Other values (30) 1205
 
5.9%
Hangul
ValueCountFrequency (%)
구 5163
20.0%
로 3091
12.0%
동 2128
8.2%
서 2064
 
8.0%
시 2063
 
8.0%
울 2057
 
8.0%
특 2053
 
7.9%
별 2053
 
7.9%
봉 399
 
1.5%
개 311
 
1.2%
Other values (285) 4450
17.2%
CJK
ValueCountFrequency (%)
內 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct504
Distinct (%)95.3%
Missing1528
Missing (%)74.3%
Memory size16.2 KiB
2024-04-30T04:40:21.495722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length30.922495
Min length21

Characters and Unicode

Total characters16358
Distinct characters279
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

Unique486 ?
Unique (%)91.9%

Sample

1st row서울특별시 구로구 시흥대로 573 (구로동)
2nd row서울특별시 구로구 디지털로 288 (구로동)
3rd row서울특별시 구로구 디지털로26길 72 (구로동)
4th row서울특별시 구로구 경인로40길 47 (개봉동, 개봉역상행홈)
5th row서울특별시 구로구 디지털로31길 38-9 (구로동)
ValueCountFrequency (%)
서울특별시 528
 
16.8%
구로구 527
 
16.8%
구로동 213
 
6.8%
1층 101
 
3.2%
개봉동 84
 
2.7%
고척동 52
 
1.7%
경인로 49
 
1.6%
오류동 47
 
1.5%
신도림동 29
 
0.9%
가리봉동 25
 
0.8%
Other values (703) 1490
47.4%
2024-04-30T04:40:21.912319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2617
 
16.0%
구 1418
 
8.7%
로 1405
 
8.6%
1 667
 
4.1%
동 629
 
3.8%
서 548
 
3.4%
( 542
 
3.3%
) 542
 
3.3%
시 540
 
3.3%
특 528
 
3.2%
Other values (269) 6922
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9749
59.6%
Space Separator 2617
 
16.0%
Decimal Number 2421
 
14.8%
Open Punctuation 542
 
3.3%
Close Punctuation 542
 
3.3%
Other Punctuation 368
 
2.2%
Dash Punctuation 88
 
0.5%
Uppercase Letter 25
 
0.2%
Lowercase Letter 4
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1418
14.5%
로 1405
14.4%
동 629
 
6.5%
서 548
 
5.6%
시 540
 
5.5%
특 528
 
5.4%
별 528
 
5.4%
울 528
 
5.4%
길 303
 
3.1%
봉 165
 
1.7%
Other values (234) 3157
32.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
20.0%
C 3
12.0%
K 3
12.0%
A 3
12.0%
U 2
 
8.0%
S 2
 
8.0%
F 1
 
4.0%
Z 1
 
4.0%
M 1
 
4.0%
D 1
 
4.0%
Other values (3) 3
12.0%
Decimal Number
ValueCountFrequency (%)
1 667
27.6%
2 357
14.7%
3 270
11.2%
0 244
 
10.1%
5 176
 
7.3%
7 172
 
7.1%
4 165
 
6.8%
6 158
 
6.5%
8 122
 
5.0%
9 90
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
w 1
25.0%
x 1
25.0%
t 1
25.0%
s 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 367
99.7%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2617
100.0%
Open Punctuation
ValueCountFrequency (%)
( 542
100.0%
Close Punctuation
ValueCountFrequency (%)
) 542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9749
59.6%
Common 6579
40.2%
Latin 30
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1418
14.5%
로 1405
14.4%
동 629
 
6.5%
서 548
 
5.6%
시 540
 
5.5%
특 528
 
5.4%
별 528
 
5.4%
울 528
 
5.4%
길 303
 
3.1%
봉 165
 
1.7%
Other values (234) 3157
32.4%
Latin
ValueCountFrequency (%)
B 5
16.7%
C 3
 
10.0%
K 3
 
10.0%
A 3
 
10.0%
U 2
 
6.7%
S 2
 
6.7%
Ⅰ 1
 
3.3%
F 1
 
3.3%
Z 1
 
3.3%
M 1
 
3.3%
Other values (8) 8
26.7%
Common
ValueCountFrequency (%)
2617
39.8%
1 667
 
10.1%
( 542
 
8.2%
) 542
 
8.2%
, 367
 
5.6%
2 357
 
5.4%
3 270
 
4.1%
0 244
 
3.7%
5 176
 
2.7%
7 172
 
2.6%
Other values (7) 625
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9749
59.6%
ASCII 6608
40.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2617
39.6%
1 667
 
10.1%
( 542
 
8.2%
) 542
 
8.2%
, 367
 
5.6%
2 357
 
5.4%
3 270
 
4.1%
0 244
 
3.7%
5 176
 
2.7%
7 172
 
2.6%
Other values (24) 654
 
9.9%
Hangul
ValueCountFrequency (%)
구 1418
14.5%
로 1405
14.4%
동 629
 
6.5%
서 548
 
5.6%
시 540
 
5.5%
특 528
 
5.4%
별 528
 
5.4%
울 528
 
5.4%
길 303
 
3.1%
봉 165
 
1.7%
Other values (234) 3157
32.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct168
Distinct (%)32.5%
Missing1540
Missing (%)74.9%
Infinite0
Infinite (%)0.0%
Mean8313.5048
Minimum8090
Maximum14786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-04-30T04:40:22.040453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8090
5-th percentile8212.8
Q18259
median8300
Q38351
95-th percentile8390.2
Maximum14786
Range6696
Interquartile range (IQR)92

Descriptive statistics

Standard deviation290.66947
Coefficient of variation (CV)0.03496353
Kurtosis479.03327
Mean8313.5048
Median Absolute Deviation (MAD)45
Skewness21.47516
Sum4298082
Variance84488.743
MonotonicityNot monotonic
2024-04-30T04:40:22.156812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8271 12
 
0.6%
8298 11
 
0.5%
8391 11
 
0.5%
8376 10
 
0.5%
8304 10
 
0.5%
8312 9
 
0.4%
8223 9
 
0.4%
8353 7
 
0.3%
8284 7
 
0.3%
8320 7
 
0.3%
Other values (158) 424
 
20.6%
(Missing) 1540
74.9%
ValueCountFrequency (%)
8090 1
 
< 0.1%
8200 1
 
< 0.1%
8201 1
 
< 0.1%
8202 2
 
0.1%
8203 1
 
< 0.1%
8204 1
 
< 0.1%
8206 2
 
0.1%
8207 2
 
0.1%
8208 2
 
0.1%
8209 6
0.3%
ValueCountFrequency (%)
14786 1
 
< 0.1%
8395 4
 
0.2%
8394 1
 
< 0.1%
8393 5
0.2%
8392 4
 
0.2%
8391 11
0.5%
8390 3
 
0.1%
8389 2
 
0.1%
8388 2
 
0.1%
8387 2
 
0.1%

사업장명
Text

Distinct1827
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
2024-04-30T04:40:22.402210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length9.0841031
Min length1

Characters and Unicode

Total characters18686
Distinct characters620
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1721 ?
Unique (%)83.7%

Sample

1st row금석빌딩
2nd row원호병원(자판기)
3rd row종근당마을금고
4th row조흥은행개봉동지점
5th row도영병원(자판기)
ValueCountFrequency (%)
자판기 34
 
1.5%
코레일유통주식회사 33
 
1.4%
씨유 25
 
1.1%
gs25 24
 
1.0%
애경백화점 15
 
0.6%
애경백화점(자판기 14
 
0.6%
애경새마을금고 12
 
0.5%
2호선 12
 
0.5%
금성벤딩(주 11
 
0.5%
지에스25 9
 
0.4%
Other values (1918) 2142
91.9%
2024-04-30T04:40:22.781872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1322
 
7.1%
자 1314
 
7.0%
( 1298
 
6.9%
) 1295
 
6.9%
판 1273
 
6.8%
구 306
 
1.6%
점 293
 
1.6%
275
 
1.5%
로 220
 
1.2%
동 207
 
1.1%
Other values (610) 10883
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15143
81.0%
Open Punctuation 1298
 
6.9%
Close Punctuation 1295
 
6.9%
Decimal Number 370
 
2.0%
Space Separator 275
 
1.5%
Uppercase Letter 248
 
1.3%
Lowercase Letter 25
 
0.1%
Other Punctuation 18
 
0.1%
Dash Punctuation 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1322
 
8.7%
자 1314
 
8.7%
판 1273
 
8.4%
구 306
 
2.0%
점 293
 
1.9%
로 220
 
1.5%
동 207
 
1.4%
퍼 203
 
1.3%
주 196
 
1.3%
슈 185
 
1.2%
Other values (557) 9624
63.6%
Uppercase Letter
ValueCountFrequency (%)
S 57
23.0%
G 54
21.8%
C 33
13.3%
U 23
9.3%
P 10
 
4.0%
M 8
 
3.2%
K 7
 
2.8%
L 7
 
2.8%
O 6
 
2.4%
E 6
 
2.4%
Other values (13) 37
14.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
24.0%
g 3
12.0%
f 3
12.0%
o 2
 
8.0%
c 2
 
8.0%
a 2
 
8.0%
s 2
 
8.0%
t 1
 
4.0%
r 1
 
4.0%
m 1
 
4.0%
Other values (2) 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
2 142
38.4%
5 74
20.0%
4 38
 
10.3%
1 38
 
10.3%
0 29
 
7.8%
3 24
 
6.5%
7 16
 
4.3%
6 6
 
1.6%
8 3
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 10
55.6%
? 4
 
22.2%
/ 2
 
11.1%
@ 1
 
5.6%
, 1
 
5.6%
Open Punctuation
ValueCountFrequency (%)
( 1298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1295
100.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15143
81.0%
Common 3270
 
17.5%
Latin 273
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1322
 
8.7%
자 1314
 
8.7%
판 1273
 
8.4%
구 306
 
2.0%
점 293
 
1.9%
로 220
 
1.5%
동 207
 
1.4%
퍼 203
 
1.3%
주 196
 
1.3%
슈 185
 
1.2%
Other values (557) 9624
63.6%
Latin
ValueCountFrequency (%)
S 57
20.9%
G 54
19.8%
C 33
12.1%
U 23
 
8.4%
P 10
 
3.7%
M 8
 
2.9%
K 7
 
2.6%
L 7
 
2.6%
O 6
 
2.2%
E 6
 
2.2%
Other values (25) 62
22.7%
Common
ValueCountFrequency (%)
( 1298
39.7%
) 1295
39.6%
275
 
8.4%
2 142
 
4.3%
5 74
 
2.3%
4 38
 
1.2%
1 38
 
1.2%
0 29
 
0.9%
3 24
 
0.7%
7 16
 
0.5%
Other values (8) 41
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15143
81.0%
ASCII 3543
 
19.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1322
 
8.7%
자 1314
 
8.7%
판 1273
 
8.4%
구 306
 
2.0%
점 293
 
1.9%
로 220
 
1.5%
동 207
 
1.4%
퍼 203
 
1.3%
주 196
 
1.3%
슈 185
 
1.2%
Other values (557) 9624
63.6%
ASCII
ValueCountFrequency (%)
( 1298
36.6%
) 1295
36.6%
275
 
7.8%
2 142
 
4.0%
5 74
 
2.1%
S 57
 
1.6%
G 54
 
1.5%
4 38
 
1.1%
1 38
 
1.1%
C 33
 
0.9%
Other values (43) 239
 
6.7%

최종수정일자
Date

Distinct1079
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum1999-01-19 00:00:00
Maximum2024-04-24 15:58:41
2024-04-30T04:40:22.907090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:23.195064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
I
1899 
U
 
158

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 1899
92.3%
U 158
 
7.7%

Length

2024-04-30T04:40:23.300637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:23.383266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1899
92.3%
u 158
 
7.7%

데이터갱신일자
Date

Distinct223
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:01:00
2024-04-30T04:40:23.538016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:40:23.731688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
식품자동판매기영업
2057 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 2057
100.0%

Length

2024-04-30T04:40:23.834778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:23.918658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2057
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1267
Distinct (%)67.8%
Missing189
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean188576.15
Minimum183685.66
Maximum191280.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-04-30T04:40:24.028259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183685.66
5-th percentile185201.23
Q1187057.95
median189465.45
Q3190141.03
95-th percentile190669.02
Maximum191280.66
Range7594.9949
Interquartile range (IQR)3083.0726

Descriptive statistics

Standard deviation1868.264
Coefficient of variation (CV)0.0099072122
Kurtosis-0.88301432
Mean188576.15
Median Absolute Deviation (MAD)1030.6508
Skewness-0.60282673
Sum3.5226025 × 108
Variance3490410.2
MonotonicityNot monotonic
2024-04-30T04:40:24.156435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189570.360930049 34
 
1.7%
190302.580042588 29
 
1.4%
189995.453991496 20
 
1.0%
189737.563067918 17
 
0.8%
190561.787378446 17
 
0.8%
188840.515865617 15
 
0.7%
187525.339802832 13
 
0.6%
190163.724552507 9
 
0.4%
190364.350034207 8
 
0.4%
187798.86926511 7
 
0.3%
Other values (1257) 1699
82.6%
(Missing) 189
 
9.2%
ValueCountFrequency (%)
183685.662788976 1
 
< 0.1%
183726.703010057 1
 
< 0.1%
183753.970850626 1
 
< 0.1%
183798.274607731 1
 
< 0.1%
183807.118188697 1
 
< 0.1%
183856.646621367 1
 
< 0.1%
183954.271761364 1
 
< 0.1%
183992.189194863 1
 
< 0.1%
184019.610971952 1
 
< 0.1%
184055.794590129 4
0.2%
ValueCountFrequency (%)
191280.657696914 2
 
0.1%
191268.482434255 1
 
< 0.1%
191250.050385034 1
 
< 0.1%
191239.693382941 1
 
< 0.1%
191225.591920564 1
 
< 0.1%
191209.106092001 2
 
0.1%
191205.791543965 1
 
< 0.1%
191200.722936426 2
 
0.1%
191191.131566069 6
0.3%
191187.50683561 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1265
Distinct (%)67.7%
Missing189
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean443665.95
Minimum440029.18
Maximum446140.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-04-30T04:40:24.299695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440029.18
5-th percentile442286.63
Q1443086.7
median443682.33
Q3444330.12
95-th percentile444998.88
Maximum446140.07
Range6110.8879
Interquartile range (IQR)1243.4184

Descriptive statistics

Standard deviation838.78316
Coefficient of variation (CV)0.0018905737
Kurtosis-0.57407571
Mean443665.95
Median Absolute Deviation (MAD)632.47247
Skewness-0.10362341
Sum8.28768 × 108
Variance703557.19
MonotonicityNot monotonic
2024-04-30T04:40:24.437276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444336.051330144 34
 
1.7%
445174.416440663 29
 
1.4%
443578.513105216 20
 
1.0%
443461.858357272 17
 
0.8%
443329.459368413 17
 
0.8%
444306.771104527 15
 
0.7%
443643.833213749 13
 
0.6%
443865.923656986 9
 
0.4%
445207.323738651 8
 
0.4%
444038.299358594 7
 
0.3%
Other values (1255) 1699
82.6%
(Missing) 189
 
9.2%
ValueCountFrequency (%)
440029.180821002 1
< 0.1%
441599.355055656 1
< 0.1%
441686.663572767 1
< 0.1%
441811.482181569 1
< 0.1%
441862.85496884 1
< 0.1%
441868.707510887 1
< 0.1%
441871.776245407 1
< 0.1%
441919.511061468 1
< 0.1%
441937.41788015 1
< 0.1%
441941.589844702 1
< 0.1%
ValueCountFrequency (%)
446140.068718483 1
< 0.1%
445736.112975672 1
< 0.1%
445679.829839399 1
< 0.1%
445651.639934138 1
< 0.1%
445556.641493041 1
< 0.1%
445532.056886722 1
< 0.1%
445473.428068255 1
< 0.1%
445458.335742134 1
< 0.1%
445454.453705465 1
< 0.1%
445436.246414949 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
식품자동판매기영업
1934 
<NA>
 
123

Length

Max length9
Median length9
Mean length8.7010209
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 1934
94.0%
<NA> 123
 
6.0%

Length

2024-04-30T04:40:24.546215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:24.643620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 1934
94.0%
na 123
 
6.0%

남성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1016 
0
809 
1
232 

Length

Max length4
Median length1
Mean length2.4817696
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1016
49.4%
0 809
39.3%
1 232
 
11.3%

Length

2024-04-30T04:40:24.745617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:24.835047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1016
49.4%
0 809
39.3%
1 232
 
11.3%

여성종사자수
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1019 
0
918 
1
119 
2
 
1

Length

Max length4
Median length1
Mean length2.4861449
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1019
49.5%
0 918
44.6%
1 119
 
5.8%
2 1
 
< 0.1%

Length

2024-04-30T04:40:24.926719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:25.013964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1019
49.5%
0 918
44.6%
1 119
 
5.8%
2 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
967 
기타
929 
주택가주변
131 
아파트지역
 
18
유흥업소밀집지역
 
10
Other values (2)
 
2

Length

Max length8
Median length7
Mean length3.1920272
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 967
47.0%
기타 929
45.2%
주택가주변 131
 
6.4%
아파트지역 18
 
0.9%
유흥업소밀집지역 10
 
0.5%
학교정화(절대) 1
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

Length

2024-04-30T04:40:25.126281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:25.253084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 967
47.0%
기타 929
45.2%
주택가주변 131
 
6.4%
아파트지역 18
 
0.9%
유흥업소밀집지역 10
 
0.5%
학교정화(절대 1
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
967 
기타
555 
자율
466 
지도
 
65
을
 
2
Other values (2)
 
2

Length

Max length4
Median length2
Mean length2.9392319
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row지도
2nd row지도
3rd row자율
4th row지도
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 967
47.0%
기타 555
27.0%
자율 466
22.7%
지도 65
 
3.2%
을 2
 
0.1%
관리 1
 
< 0.1%
우수 1
 
< 0.1%

Length

2024-04-30T04:40:25.370239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:25.468493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 967
47.0%
기타 555
27.0%
자율 466
22.7%
지도 65
 
3.2%
을 2
 
0.1%
관리 1
 
< 0.1%
우수 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1966 
상수도전용
 
91

Length

Max length5
Median length4
Mean length4.0442392
Min length4

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> 1966
95.6%
상수도전용 91
 
4.4%

Length

2024-04-30T04:40:25.566122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:25.648586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1966
95.6%
상수도전용 91
 
4.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
2023 
0
 
34

Length

Max length4
Median length4
Mean length3.9504132
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> 2023
98.3%
0 34
 
1.7%

Length

2024-04-30T04:40:25.744943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:25.839327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2023
98.3%
0 34
 
1.7%

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1502 
0
555 

Length

Max length4
Median length4
Mean length3.1905688
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> 1502
73.0%
0 555
 
27.0%

Length

2024-04-30T04:40:25.946308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:26.039096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1502
73.0%
0 555
 
27.0%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1502 
0
555 

Length

Max length4
Median length4
Mean length3.1905688
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> 1502
73.0%
0 555
 
27.0%

Length

2024-04-30T04:40:26.131362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:26.227137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1502
73.0%
0 555
 
27.0%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1502 
0
555 

Length

Max length4
Median length4
Mean length3.1905688
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> 1502
73.0%
0 555
 
27.0%

Length

2024-04-30T04:40:26.321200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:26.406579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1502
73.0%
0 555
 
27.0%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1502 
0
555 

Length

Max length4
Median length4
Mean length3.1905688
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> 1502
73.0%
0 555
 
27.0%

Length

2024-04-30T04:40:26.510827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:26.610535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1502
73.0%
0 555
 
27.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1442 
자가
525 
임대
 
90

Length

Max length4
Median length4
Mean length3.4020418
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> 1442
70.1%
자가 525
 
25.5%
임대 90
 
4.4%

Length

2024-04-30T04:40:26.719423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:26.894380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1442
70.1%
자가 525
 
25.5%
임대 90
 
4.4%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1589 
0
467 
7000000
 
1

Length

Max length7
Median length4
Mean length3.3203695
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> 1589
77.2%
0 467
 
22.7%
7000000 1
 
< 0.1%

Length

2024-04-30T04:40:27.002465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:27.089051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1589
77.2%
0 467
 
22.7%
7000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.2 KiB
<NA>
1589 
0
467 
200000
 
1

Length

Max length6
Median length4
Mean length3.3198833
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> 1589
77.2%
0 467
 
22.7%
200000 1
 
< 0.1%

Length

2024-04-30T04:40:27.178329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:40:27.274787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1589
77.2%
0 467
 
22.7%
200000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing123
Missing (%)6.0%
Memory size4.1 KiB
False
1934 
(Missing)
 
123
ValueCountFrequency (%)
False 1934
94.0%
(Missing) 123
 
6.0%
2024-04-30T04:40:27.345345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct14
Distinct (%)0.7%
Missing123
Missing (%)6.0%
Infinite0
Infinite (%)0.0%
Mean0.25628232
Minimum0
Maximum303
Zeros1882
Zeros (%)91.5%
Negative0
Negative (%)0.0%
Memory size18.2 KiB
2024-04-30T04:40:27.411398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum303
Range303
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.9958008
Coefficient of variation (CV)27.297244
Kurtosis1818.0497
Mean0.25628232
Median Absolute Deviation (MAD)0
Skewness42.134452
Sum495.65
Variance48.941229
MonotonicityNot monotonic
2024-04-30T04:40:27.495657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 1882
91.5%
3.3 23
 
1.1%
1.0 11
 
0.5%
3.0 5
 
0.2%
3.6 4
 
0.2%
47.25 1
 
< 0.1%
16.5 1
 
< 0.1%
2.4 1
 
< 0.1%
7.0 1
 
< 0.1%
0.8 1
 
< 0.1%
Other values (4) 4
 
0.2%
(Missing) 123
 
6.0%
ValueCountFrequency (%)
0.0 1882
91.5%
0.3 1
 
< 0.1%
0.5 1
 
< 0.1%
0.8 1
 
< 0.1%
1.0 11
 
0.5%
1.6 1
 
< 0.1%
2.4 1
 
< 0.1%
3.0 5
 
0.2%
3.3 23
 
1.1%
3.6 4
 
0.2%
ValueCountFrequency (%)
303.0 1
 
< 0.1%
47.25 1
 
< 0.1%
16.5 1
 
< 0.1%
7.0 1
 
< 0.1%
3.6 4
 
0.2%
3.3 23
1.1%
3.0 5
 
0.2%
2.4 1
 
< 0.1%
1.6 1
 
< 0.1%
1.0 11
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2057
Missing (%)100.0%
Memory size18.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031600003160000-112-1983-0000219830321<NA>3폐업2폐업20080710<NA><NA><NA>02<NA>152806서울특별시 구로구 개봉동 170-33<NA><NA>금석빌딩2002-07-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업187471.842861443829.62611식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131600003160000-112-1983-0000419830321<NA>3폐업2폐업20151231<NA><NA><NA>02<NA>152883서울특별시 구로구 궁동 198-0<NA><NA>원호병원(자판기)2015-12-31 14:36:33I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231600003160000-112-1983-0000519830321<NA>3폐업2폐업19981230<NA><NA><NA>02<NA>152887서울특별시 구로구 신도림동 410-0<NA><NA>종근당마을금고2001-09-26 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업10주택가주변자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331600003160000-112-1983-0000619830321<NA>3폐업2폐업20001101<NA><NA><NA>02<NA>152805서울특별시 구로구 개봉동 157-0<NA><NA>조흥은행개봉동지점2000-11-01 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업187250.863801443969.170559식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431600003160000-112-1983-0000719830321<NA>3폐업2폐업20070914<NA><NA><NA>02<NA>152815서울특별시 구로구 개봉동 353-2<NA><NA>도영병원(자판기)2002-07-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업187263.423645443866.78976식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531600003160000-112-1983-0000819830321<NA>3폐업2폐업19990304<NA><NA><NA>02<NA>152858서울특별시 구로구 구로동 501-0<NA><NA>애경유지새마을금고2002-07-11 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업189682.799435444193.860003식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631600003160000-112-1983-0000919830322<NA>3폐업2폐업19981217<NA><NA><NA>02<NA>152858서울특별시 구로구 구로동 474-3<NA><NA>삼교상사(내)2001-09-26 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업10기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731600003160000-112-1983-0001519830322<NA>3폐업2폐업20050106<NA><NA><NA>02<NA>152872서울특별시 구로구 구로동 735-26<NA><NA>한빛은행구로지점(내)2001-09-26 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업189733.172124442988.783982식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831600003160000-112-1983-0001619830322<NA>3폐업2폐업19990310<NA><NA><NA>02<NA>152848서울특별시 구로구 구로동 224-14<NA><NA>성도섬유(내)2001-09-26 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업01유흥업소밀집지역자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931600003160000-112-1983-000171983-03-22<NA>3폐업2폐업2023-06-05<NA><NA><NA><NA><NA>152-880서울특별시 구로구 구로동 1123-2서울특별시 구로구 시흥대로 573 (구로동)8391동일석유남부충전소(내)2023-06-05 10:30:29U2022-12-06 00:08:00.0식품자동판매기영업191268.482434442460.543208<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
204731600003160000-112-2024-000012024-01-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3152-842서울특별시 구로구 구로동 106-1 시립구로도서관서울특별시 구로구 공원로 15, 시립구로도서관 4층 (구로동)8298서울특별시교육청구로도서관2024-01-02 11:10:37I2023-12-01 00:04:00.0식품자동판매기영업190354.758784444038.299359<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204831600003160000-112-2024-000022024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.47152-887서울특별시 구로구 신도림동 416-22서울특별시 구로구 신도림로9길 2, 1층 (신도림동)820624시무인카페 귀족2024-01-12 10:26:58I2023-11-30 23:04:00.0식품자동판매기영업189321.0445091.48<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204931600003160000-112-2024-000032024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.75152-862서울특별시 구로구 구로동 560 신도림현대아파트서울특별시 구로구 새말로9길 45, 상가동 106호 (구로동, 신도림현대아파트)829124시무인카페 귀족2024-01-12 10:33:29I2023-11-30 23:04:00.0식품자동판매기영업189836.89383444739.3026<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205031600003160000-112-2024-000042024-01-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.82152-811서울특별시 구로구 개봉동 270-44서울특별시 구로구 개봉로11가길 29-8, 지층 (개봉동)8349모그(MOG)2024-01-23 14:37:01I2023-11-30 22:05:00.0식품자동판매기영업186887.482997443048.496234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205131600003160000-112-2024-000052024-02-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3152-889서울특별시 구로구 오류동 9-231 오류동 삼전솔하임서울특별시 구로구 경인로 187, 오류동 삼전솔하임 102-1호 (오류동)8269흥양산업 스마트오류솔하임점2024-02-06 17:07:24I2023-12-02 00:08:00.0식품자동판매기영업185936.972363443719.520929<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205231600003160000-112-2024-000062024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3152-865서울특별시 구로구 구로동 615-3 에스티엑스 더블유 타워서울특별시 구로구 경인로53길 90, 에스티엑스 더블유 타워 103호 (구로동)8215GS25 구로W타워점2024-02-21 13:51:34I2023-12-01 22:03:00.0식품자동판매기영업188890.674097444722.181249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205331600003160000-112-2024-000072024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2.0152-846서울특별시 구로구 구로동 141-14 한진빌딩서울특별시 구로구 도림로 75, 한진빌딩 뒤측 주차장 펜스 (구로동)8312다니엘2024-03-05 11:41:42I2023-12-03 00:07:00.0식품자동판매기영업190356.378018443098.420833<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205431600003160000-112-2024-000082024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>28.0152-815서울특별시 구로구 개봉동 356-13서울특별시 구로구 개봉로3길 86, 1층 (개봉동)835124시 무인카페 만월경 구로개봉점2024-04-09 11:10:52I2023-12-03 23:01:00.0식품자동판매기영업186790.070818442678.736237<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205531600003160000-112-2024-000092024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3152-868서울특별시 구로구 구로동 685-215 종합상가서울특별시 구로구 구일로4길 33, 종합상가 103호 (구로동)8324주식회사 지에스25구로제일2024-04-23 09:51:51I2023-12-03 22:05:00.0식품자동판매기영업188946.885362443320.519553<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205631600003160000-112-2024-000102024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.0152-130서울특별시 구로구 천왕동 14-25 천왕역서울특별시 구로구 오리로 지하 1154, 천왕역 (천왕동)8342지에스25(GS25 S)천왕역점2024-04-24 15:58:41I2023-12-03 22:07:00.0식품자동판매기영업185638.815174442784.972769<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>