Overview

Dataset statistics

Number of variables44
Number of observations4074
Missing cells40802
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory376.0 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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18245/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (69.0%)Imbalance
영업상태명 is highly imbalanced (69.0%)Imbalance
상세영업상태코드 is highly imbalanced (69.0%)Imbalance
상세영업상태명 is highly imbalanced (69.0%)Imbalance
데이터갱신구분 is highly imbalanced (60.9%)Imbalance
위생업태명 is highly imbalanced (72.0%)Imbalance
여성종사자수 is highly imbalanced (57.6%)Imbalance
영업장주변구분명 is highly imbalanced (52.4%)Imbalance
급수시설구분명 is highly imbalanced (98.0%)Imbalance
총인원 is highly imbalanced (72.0%)Imbalance
본사종업원수 is highly imbalanced (82.1%)Imbalance
공장사무직종업원수 is highly imbalanced (72.0%)Imbalance
공장판매직종업원수 is highly imbalanced (72.0%)Imbalance
공장생산직종업원수 is highly imbalanced (72.0%)Imbalance
건물소유구분명 is highly imbalanced (54.2%)Imbalance
보증액 is highly imbalanced (72.0%)Imbalance
월세액 is highly imbalanced (72.0%)Imbalance
인허가취소일자 has 4074 (100.0%) missing valuesMissing
폐업일자 has 227 (5.6%) missing valuesMissing
휴업시작일자 has 4074 (100.0%) missing valuesMissing
휴업종료일자 has 4074 (100.0%) missing valuesMissing
재개업일자 has 4074 (100.0%) missing valuesMissing
전화번호 has 752 (18.5%) missing valuesMissing
소재지면적 has 3505 (86.0%) missing valuesMissing
도로명주소 has 3335 (81.9%) missing valuesMissing
도로명우편번호 has 3355 (82.4%) missing valuesMissing
좌표정보(X) has 353 (8.7%) missing valuesMissing
좌표정보(Y) has 353 (8.7%) missing valuesMissing
다중이용업소여부 has 198 (4.9%) missing valuesMissing
시설총규모 has 198 (4.9%) missing valuesMissing
전통업소지정번호 has 4074 (100.0%) missing valuesMissing
전통업소주된음식 has 4074 (100.0%) missing valuesMissing
홈페이지 has 4074 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 194 (4.8%) zerosZeros
시설총규모 has 3784 (92.9%) zerosZeros

Reproduction

Analysis started2024-05-11 05:54:39.031774
Analysis finished2024-05-11 05:54:41.451326
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
3180000
4074 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 4074
100.0%

Length

2024-05-11T14:54:41.579294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:41.783249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 4074
100.0%

관리번호
Text

UNIQUE 

Distinct4074
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
2024-05-11T14:54:42.123524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters89628
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

Unique4074 ?
Unique (%)100.0%

Sample

1st row3180000-112-0998-02063
2nd row3180000-112-0999-02138
3rd row3180000-112-0999-02221
4th row3180000-112-1981-00001
5th row3180000-112-1981-00002
ValueCountFrequency (%)
3180000-112-0998-02063 1
 
< 0.1%
3180000-112-2001-02763 1
 
< 0.1%
3180000-112-2001-02750 1
 
< 0.1%
3180000-112-2001-02813 1
 
< 0.1%
3180000-112-2001-02767 1
 
< 0.1%
3180000-112-2001-02753 1
 
< 0.1%
3180000-112-2001-02754 1
 
< 0.1%
3180000-112-2001-02755 1
 
< 0.1%
3180000-112-2001-02756 1
 
< 0.1%
3180000-112-2001-02757 1
 
< 0.1%
Other values (4064) 4064
99.8%
2024-05-11T14:54:42.716820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28027
31.3%
1 17906
20.0%
- 12222
13.6%
2 8807
 
9.8%
9 6099
 
6.8%
8 5735
 
6.4%
3 5725
 
6.4%
4 1356
 
1.5%
7 1329
 
1.5%
5 1218
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77406
86.4%
Dash Punctuation 12222
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28027
36.2%
1 17906
23.1%
2 8807
 
11.4%
9 6099
 
7.9%
8 5735
 
7.4%
3 5725
 
7.4%
4 1356
 
1.8%
7 1329
 
1.7%
5 1218
 
1.6%
6 1204
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 12222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 89628
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28027
31.3%
1 17906
20.0%
- 12222
13.6%
2 8807
 
9.8%
9 6099
 
6.8%
8 5735
 
6.4%
3 5725
 
6.4%
4 1356
 
1.5%
7 1329
 
1.5%
5 1218
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89628
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28027
31.3%
1 17906
20.0%
- 12222
13.6%
2 8807
 
9.8%
9 6099
 
6.8%
8 5735
 
6.4%
3 5725
 
6.4%
4 1356
 
1.5%
7 1329
 
1.5%
5 1218
 
1.4%
Distinct1746
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
Minimum1981-09-10 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:54:42.984613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:43.276023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
3
3847 
1
 
227

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 3847
94.4%
1 227
 
5.6%

Length

2024-05-11T14:54:43.518233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:43.713090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3847
94.4%
1 227
 
5.6%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
폐업
3847 
영업/정상
 
227

Length

Max length5
Median length2
Mean length2.1671576
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3847
94.4%
영업/정상 227
 
5.6%

Length

2024-05-11T14:54:43.971180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:44.148053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3847
94.4%
영업/정상 227
 
5.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
2
3847 
1
 
227

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 3847
94.4%
1 227
 
5.6%

Length

2024-05-11T14:54:44.314712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:44.484757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3847
94.4%
1 227
 
5.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
폐업
3847 
영업
 
227

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 3847
94.4%
영업 227
 
5.6%

Length

2024-05-11T14:54:44.698300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:44.883460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3847
94.4%
영업 227
 
5.6%

폐업일자
Date

MISSING 

Distinct1687
Distinct (%)43.9%
Missing227
Missing (%)5.6%
Memory size32.0 KiB
Minimum1984-02-12 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:54:45.083799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:45.326573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

전화번호
Text

MISSING 

Distinct1747
Distinct (%)52.6%
Missing752
Missing (%)18.5%
Memory size32.0 KiB
2024-05-11T14:54:45.724873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.7447321
Min length2

Characters and Unicode

Total characters25728
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

Unique1567 ?
Unique (%)47.2%

Sample

1st row02 6770966
2nd row02 6752663
3rd row02 8334377
4th row02
5th row02 6769123
ValueCountFrequency (%)
02 2350
47.4%
7812622 77
 
1.6%
0237731288 56
 
1.1%
028015 55
 
1.1%
357 33
 
0.7%
502 22
 
0.4%
7894754 19
 
0.4%
0260065500 17
 
0.3%
0234720333 17
 
0.3%
0226363290 16
 
0.3%
Other values (1792) 2291
46.3%
2024-05-11T14:54:46.299454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5363
20.8%
0 4528
17.6%
8 2354
9.1%
6 2129
 
8.3%
3 2119
 
8.2%
7 1974
 
7.7%
1755
 
6.8%
4 1634
 
6.4%
1 1598
 
6.2%
5 1249
 
4.9%
Other values (2) 1025
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23964
93.1%
Space Separator 1755
 
6.8%
Dash Punctuation 9
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5363
22.4%
0 4528
18.9%
8 2354
9.8%
6 2129
 
8.9%
3 2119
 
8.8%
7 1974
 
8.2%
4 1634
 
6.8%
1 1598
 
6.7%
5 1249
 
5.2%
9 1016
 
4.2%
Space Separator
ValueCountFrequency (%)
1755
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25728
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5363
20.8%
0 4528
17.6%
8 2354
9.1%
6 2129
 
8.3%
3 2119
 
8.2%
7 1974
 
7.7%
1755
 
6.8%
4 1634
 
6.4%
1 1598
 
6.2%
5 1249
 
4.9%
Other values (2) 1025
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5363
20.8%
0 4528
17.6%
8 2354
9.1%
6 2129
 
8.3%
3 2119
 
8.2%
7 1974
 
7.7%
1755
 
6.8%
4 1634
 
6.4%
1 1598
 
6.2%
5 1249
 
4.9%
Other values (2) 1025
 
4.0%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)5.8%
Missing3505
Missing (%)86.0%
Infinite0
Infinite (%)0.0%
Mean2.425413
Minimum0
Maximum60
Zeros194
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-05-11T14:54:46.527778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33.3
95-th percentile5.68
Maximum60
Range60
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation4.6981972
Coefficient of variation (CV)1.937071
Kurtosis65.275574
Mean2.425413
Median Absolute Deviation (MAD)1.3
Skewness7.1961784
Sum1380.06
Variance22.073057
MonotonicityNot monotonic
2024-05-11T14:54:46.748478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0.0 194
 
4.8%
3.3 139
 
3.4%
2.0 132
 
3.2%
3.0 27
 
0.7%
1.0 17
 
0.4%
6.6 10
 
0.2%
5.0 9
 
0.2%
1.5 5
 
0.1%
4.0 5
 
0.1%
6.0 4
 
0.1%
Other values (23) 27
 
0.7%
(Missing) 3505
86.0%
ValueCountFrequency (%)
0.0 194
4.8%
0.3 1
 
< 0.1%
0.45 1
 
< 0.1%
0.5 3
 
0.1%
0.9 1
 
< 0.1%
1.0 17
 
0.4%
1.32 1
 
< 0.1%
1.5 5
 
0.1%
1.65 1
 
< 0.1%
2.0 132
3.2%
ValueCountFrequency (%)
60.0 1
< 0.1%
42.9 1
< 0.1%
38.0 1
< 0.1%
33.0 2
< 0.1%
32.88 1
< 0.1%
30.0 1
< 0.1%
19.8 1
< 0.1%
18.0 1
< 0.1%
16.5 1
< 0.1%
15.67 1
< 0.1%
Distinct235
Distinct (%)5.8%
Missing4
Missing (%)0.1%
Memory size32.0 KiB
2024-05-11T14:54:47.318575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0329238
Min length6

Characters and Unicode

Total characters24554
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

Unique67 ?
Unique (%)1.6%

Sample

1st row150802
2nd row150105
3rd row150851
4th row150045
5th row150810
ValueCountFrequency (%)
150875 127
 
3.1%
150841 120
 
2.9%
150876 118
 
2.9%
150899 116
 
2.9%
150034 110
 
2.7%
150033 101
 
2.5%
150896 85
 
2.1%
150914 69
 
1.7%
150803 67
 
1.6%
150070 67
 
1.6%
Other values (225) 3090
75.9%
2024-05-11T14:54:48.177619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6047
24.6%
1 5074
20.7%
5 4807
19.6%
8 3290
13.4%
3 1122
 
4.6%
9 1017
 
4.1%
4 866
 
3.5%
7 822
 
3.3%
6 777
 
3.2%
2 598
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24420
99.5%
Dash Punctuation 134
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6047
24.8%
1 5074
20.8%
5 4807
19.7%
8 3290
13.5%
3 1122
 
4.6%
9 1017
 
4.2%
4 866
 
3.5%
7 822
 
3.4%
6 777
 
3.2%
2 598
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24554
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6047
24.6%
1 5074
20.7%
5 4807
19.6%
8 3290
13.4%
3 1122
 
4.6%
9 1017
 
4.1%
4 866
 
3.5%
7 822
 
3.3%
6 777
 
3.2%
2 598
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6047
24.6%
1 5074
20.7%
5 4807
19.6%
8 3290
13.4%
3 1122
 
4.6%
9 1017
 
4.1%
4 866
 
3.5%
7 822
 
3.3%
6 777
 
3.2%
2 598
 
2.4%
Distinct2806
Distinct (%)68.9%
Missing4
Missing (%)0.1%
Memory size32.0 KiB
2024-05-11T14:54:48.745523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length48
Mean length24.086732
Min length17

Characters and Unicode

Total characters98033
Distinct characters385
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2386 ?
Unique (%)58.6%

Sample

1st row서울특별시 영등포구 당산동3가 1-6
2nd row서울특별시 영등포구 양평동5가 2-2
3rd row서울특별시 영등포구 신길동 436-26
4th row서울특별시 영등포구 당산동5가 11-1
5th row서울특별시 영등포구 당산동6가 338-1
ValueCountFrequency (%)
서울특별시 4070
22.4%
영등포구 4070
22.4%
여의도동 1100
 
6.1%
신길동 591
 
3.3%
대림동 572
 
3.2%
1층 185
 
1.0%
당산동3가 165
 
0.9%
영등포동 144
 
0.8%
도림동 138
 
0.8%
20-0 123
 
0.7%
Other values (2816) 6975
38.5%
2024-05-11T14:54:49.541888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17768
18.1%
4776
 
4.9%
4752
 
4.8%
4748
 
4.8%
4402
 
4.5%
4123
 
4.2%
4114
 
4.2%
4108
 
4.2%
4082
 
4.2%
4076
 
4.2%
Other values (375) 41084
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58150
59.3%
Decimal Number 18051
 
18.4%
Space Separator 17768
 
18.1%
Dash Punctuation 3711
 
3.8%
Uppercase Letter 172
 
0.2%
Close Punctuation 64
 
0.1%
Open Punctuation 63
 
0.1%
Other Punctuation 38
 
< 0.1%
Lowercase Letter 13
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4776
 
8.2%
4752
 
8.2%
4748
 
8.2%
4402
 
7.6%
4123
 
7.1%
4114
 
7.1%
4108
 
7.1%
4082
 
7.0%
4076
 
7.0%
4071
 
7.0%
Other values (327) 14898
25.6%
Uppercase Letter
ValueCountFrequency (%)
S 43
25.0%
G 29
16.9%
B 24
14.0%
K 17
 
9.9%
C 11
 
6.4%
L 8
 
4.7%
A 6
 
3.5%
N 5
 
2.9%
T 5
 
2.9%
U 4
 
2.3%
Other values (8) 20
11.6%
Decimal Number
ValueCountFrequency (%)
1 3524
19.5%
3 2429
13.5%
2 2291
12.7%
0 2104
11.7%
4 1845
10.2%
5 1454
8.1%
6 1432
7.9%
8 1050
 
5.8%
7 1038
 
5.8%
9 884
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
30.8%
r 2
15.4%
n 2
15.4%
t 1
 
7.7%
c 1
 
7.7%
w 1
 
7.7%
o 1
 
7.7%
i 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 19
50.0%
. 7
 
18.4%
? 5
 
13.2%
/ 4
 
10.5%
@ 2
 
5.3%
& 1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 63
98.4%
] 1
 
1.6%
Space Separator
ValueCountFrequency (%)
17768
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3711
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58147
59.3%
Common 39698
40.5%
Latin 185
 
0.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4776
 
8.2%
4752
 
8.2%
4748
 
8.2%
4402
 
7.6%
4123
 
7.1%
4114
 
7.1%
4108
 
7.1%
4082
 
7.0%
4076
 
7.0%
4071
 
7.0%
Other values (325) 14895
25.6%
Latin
ValueCountFrequency (%)
S 43
23.2%
G 29
15.7%
B 24
13.0%
K 17
 
9.2%
C 11
 
5.9%
L 8
 
4.3%
A 6
 
3.2%
N 5
 
2.7%
T 5
 
2.7%
U 4
 
2.2%
Other values (16) 33
17.8%
Common
ValueCountFrequency (%)
17768
44.8%
- 3711
 
9.3%
1 3524
 
8.9%
3 2429
 
6.1%
2 2291
 
5.8%
0 2104
 
5.3%
4 1845
 
4.6%
5 1454
 
3.7%
6 1432
 
3.6%
8 1050
 
2.6%
Other values (12) 2090
 
5.3%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58147
59.3%
ASCII 39883
40.7%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17768
44.6%
- 3711
 
9.3%
1 3524
 
8.8%
3 2429
 
6.1%
2 2291
 
5.7%
0 2104
 
5.3%
4 1845
 
4.6%
5 1454
 
3.6%
6 1432
 
3.6%
8 1050
 
2.6%
Other values (38) 2275
 
5.7%
Hangul
ValueCountFrequency (%)
4776
 
8.2%
4752
 
8.2%
4748
 
8.2%
4402
 
7.6%
4123
 
7.1%
4114
 
7.1%
4108
 
7.1%
4082
 
7.0%
4076
 
7.0%
4071
 
7.0%
Other values (325) 14895
25.6%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%

도로명주소
Text

MISSING 

Distinct689
Distinct (%)93.2%
Missing3335
Missing (%)81.9%
Memory size32.0 KiB
2024-05-11T14:54:50.031288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length33.725304
Min length22

Characters and Unicode

Total characters24923
Distinct characters340
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique659 ?
Unique (%)89.2%

Sample

1st row서울특별시 영등포구 도림로 220 (신길동)
2nd row서울특별시 영등포구 영등포로64길 19-6 (신길동,지상)
3rd row서울특별시 영등포구 당산로31길 10 (당산동3가)
4th row서울특별시 영등포구 의사당대로 13 (여의도동)
5th row서울특별시 영등포구 여의대방로53길 22 (신길동)
ValueCountFrequency (%)
서울특별시 739
 
16.0%
영등포구 739
 
16.0%
1층 253
 
5.5%
여의도동 107
 
2.3%
신길동 101
 
2.2%
대림동 100
 
2.2%
당산동3가 34
 
0.7%
도림로 33
 
0.7%
지하1층 30
 
0.6%
지하 30
 
0.6%
Other values (969) 2459
53.2%
2024-05-11T14:54:51.256637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3886
 
15.6%
1 1092
 
4.4%
1008
 
4.0%
936
 
3.8%
932
 
3.7%
826
 
3.3%
760
 
3.0%
760
 
3.0%
757
 
3.0%
( 752
 
3.0%
Other values (330) 13214
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15166
60.9%
Space Separator 3886
 
15.6%
Decimal Number 3589
 
14.4%
Close Punctuation 753
 
3.0%
Open Punctuation 752
 
3.0%
Other Punctuation 578
 
2.3%
Uppercase Letter 112
 
0.4%
Dash Punctuation 71
 
0.3%
Lowercase Letter 12
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1008
 
6.6%
936
 
6.2%
932
 
6.1%
826
 
5.4%
760
 
5.0%
760
 
5.0%
757
 
5.0%
750
 
4.9%
745
 
4.9%
742
 
4.9%
Other values (287) 6950
45.8%
Uppercase Letter
ValueCountFrequency (%)
S 28
25.0%
G 25
22.3%
B 13
11.6%
K 10
 
8.9%
A 7
 
6.2%
C 5
 
4.5%
T 5
 
4.5%
U 4
 
3.6%
N 3
 
2.7%
L 3
 
2.7%
Other values (6) 9
 
8.0%
Decimal Number
ValueCountFrequency (%)
1 1092
30.4%
2 465
13.0%
3 422
 
11.8%
4 320
 
8.9%
0 282
 
7.9%
5 267
 
7.4%
6 221
 
6.2%
7 199
 
5.5%
8 178
 
5.0%
9 143
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
n 2
16.7%
r 2
16.7%
c 1
 
8.3%
t 1
 
8.3%
w 1
 
8.3%
o 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 574
99.3%
. 2
 
0.3%
& 1
 
0.2%
? 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 752
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3886
100.0%
Open Punctuation
ValueCountFrequency (%)
( 752
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15165
60.8%
Common 9633
38.7%
Latin 124
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1008
 
6.6%
936
 
6.2%
932
 
6.1%
826
 
5.4%
760
 
5.0%
760
 
5.0%
757
 
5.0%
750
 
4.9%
745
 
4.9%
742
 
4.9%
Other values (286) 6949
45.8%
Latin
ValueCountFrequency (%)
S 28
22.6%
G 25
20.2%
B 13
10.5%
K 10
 
8.1%
A 7
 
5.6%
C 5
 
4.0%
T 5
 
4.0%
e 4
 
3.2%
U 4
 
3.2%
N 3
 
2.4%
Other values (13) 20
16.1%
Common
ValueCountFrequency (%)
3886
40.3%
1 1092
 
11.3%
( 752
 
7.8%
) 752
 
7.8%
, 574
 
6.0%
2 465
 
4.8%
3 422
 
4.4%
4 320
 
3.3%
0 282
 
2.9%
5 267
 
2.8%
Other values (10) 821
 
8.5%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15165
60.8%
ASCII 9757
39.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3886
39.8%
1 1092
 
11.2%
( 752
 
7.7%
) 752
 
7.7%
, 574
 
5.9%
2 465
 
4.8%
3 422
 
4.3%
4 320
 
3.3%
0 282
 
2.9%
5 267
 
2.7%
Other values (33) 945
 
9.7%
Hangul
ValueCountFrequency (%)
1008
 
6.6%
936
 
6.2%
932
 
6.1%
826
 
5.4%
760
 
5.0%
760
 
5.0%
757
 
5.0%
750
 
4.9%
745
 
4.9%
742
 
4.9%
Other values (286) 6949
45.8%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)28.5%
Missing3355
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean7314.6537
Minimum7201
Maximum7448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-05-11T14:54:51.512026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7201
5-th percentile7212
Q17255.5
median7306
Q37374
95-th percentile7433
Maximum7448
Range247
Interquartile range (IQR)118.5

Descriptive statistics

Standard deviation70.296653
Coefficient of variation (CV)0.0096103871
Kurtosis-1.1209758
Mean7314.6537
Median Absolute Deviation (MAD)56
Skewness0.2012646
Sum5259236
Variance4941.6195
MonotonicityNot monotonic
2024-05-11T14:54:51.762893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7260 16
 
0.4%
7301 12
 
0.3%
7305 12
 
0.3%
7222 11
 
0.3%
7236 11
 
0.3%
7306 10
 
0.2%
7441 9
 
0.2%
7250 9
 
0.2%
7333 9
 
0.2%
7258 9
 
0.2%
Other values (195) 611
 
15.0%
(Missing) 3355
82.4%
ValueCountFrequency (%)
7201 4
0.1%
7202 1
 
< 0.1%
7203 4
0.1%
7204 3
0.1%
7205 5
0.1%
7206 5
0.1%
7207 3
0.1%
7208 2
 
< 0.1%
7209 3
0.1%
7210 3
0.1%
ValueCountFrequency (%)
7448 4
0.1%
7447 1
 
< 0.1%
7445 4
0.1%
7443 2
 
< 0.1%
7442 4
0.1%
7441 9
0.2%
7439 1
 
< 0.1%
7438 2
 
< 0.1%
7436 4
0.1%
7435 2
 
< 0.1%
Distinct2839
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
2024-05-11T14:54:52.248942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length6.3605793
Min length1

Characters and Unicode

Total characters25913
Distinct characters660
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2445 ?
Unique (%)60.0%

Sample

1st row한식촌
2nd row경은식품
3rd row유진식품
4th row롯데산업(주)
5th row주유소판매기
ValueCountFrequency (%)
사)한국방송공사공제회 84
 
1.9%
55
 
1.2%
보광 52
 
1.2%
캐리어엘지 46
 
1.0%
금성산전 43
 
1.0%
주식회사 38
 
0.9%
두산음료 30
 
0.7%
코레일유통(주 29
 
0.7%
한국마사회 17
 
0.4%
한국아이비엠구내식당 16
 
0.4%
Other values (2951) 4027
90.8%
2024-05-11T14:54:53.014558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 520
 
2.0%
( 517
 
2.0%
493
 
1.9%
466
 
1.8%
419
 
1.6%
416
 
1.6%
390
 
1.5%
370
 
1.4%
369
 
1.4%
350
 
1.4%
Other values (650) 21603
83.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23286
89.9%
Decimal Number 627
 
2.4%
Close Punctuation 520
 
2.0%
Open Punctuation 517
 
2.0%
Uppercase Letter 465
 
1.8%
Space Separator 369
 
1.4%
Lowercase Letter 78
 
0.3%
Other Punctuation 35
 
0.1%
Dash Punctuation 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
493
 
2.1%
466
 
2.0%
419
 
1.8%
416
 
1.8%
390
 
1.7%
370
 
1.6%
350
 
1.5%
349
 
1.5%
342
 
1.5%
340
 
1.5%
Other values (587) 19351
83.1%
Uppercase Letter
ValueCountFrequency (%)
S 123
26.5%
G 112
24.1%
C 51
11.0%
U 24
 
5.2%
K 23
 
4.9%
L 18
 
3.9%
B 17
 
3.7%
E 14
 
3.0%
O 12
 
2.6%
P 11
 
2.4%
Other values (13) 60
12.9%
Lowercase Letter
ValueCountFrequency (%)
e 13
16.7%
c 10
12.8%
a 9
11.5%
s 7
9.0%
g 5
 
6.4%
f 5
 
6.4%
r 4
 
5.1%
p 4
 
5.1%
k 3
 
3.8%
m 3
 
3.8%
Other values (10) 15
19.2%
Decimal Number
ValueCountFrequency (%)
2 221
35.2%
5 165
26.3%
1 68
 
10.8%
4 53
 
8.5%
3 33
 
5.3%
0 27
 
4.3%
7 19
 
3.0%
8 14
 
2.2%
6 14
 
2.2%
9 13
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 19
54.3%
/ 5
 
14.3%
, 5
 
14.3%
& 3
 
8.6%
? 2
 
5.7%
; 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 520
100.0%
Open Punctuation
ValueCountFrequency (%)
( 517
100.0%
Space Separator
ValueCountFrequency (%)
369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23286
89.9%
Common 2084
 
8.0%
Latin 543
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
493
 
2.1%
466
 
2.0%
419
 
1.8%
416
 
1.8%
390
 
1.7%
370
 
1.6%
350
 
1.5%
349
 
1.5%
342
 
1.5%
340
 
1.5%
Other values (587) 19351
83.1%
Latin
ValueCountFrequency (%)
S 123
22.7%
G 112
20.6%
C 51
 
9.4%
U 24
 
4.4%
K 23
 
4.2%
L 18
 
3.3%
B 17
 
3.1%
E 14
 
2.6%
e 13
 
2.4%
O 12
 
2.2%
Other values (33) 136
25.0%
Common
ValueCountFrequency (%)
) 520
25.0%
( 517
24.8%
369
17.7%
2 221
10.6%
5 165
 
7.9%
1 68
 
3.3%
4 53
 
2.5%
3 33
 
1.6%
0 27
 
1.3%
7 19
 
0.9%
Other values (10) 92
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23283
89.9%
ASCII 2627
 
10.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 520
19.8%
( 517
19.7%
369
14.0%
2 221
8.4%
5 165
 
6.3%
S 123
 
4.7%
G 112
 
4.3%
1 68
 
2.6%
4 53
 
2.0%
C 51
 
1.9%
Other values (53) 428
16.3%
Hangul
ValueCountFrequency (%)
493
 
2.1%
466
 
2.0%
419
 
1.8%
416
 
1.8%
390
 
1.7%
370
 
1.6%
350
 
1.5%
349
 
1.5%
342
 
1.5%
340
 
1.5%
Other values (585) 19348
83.1%
Compat Jamo
ValueCountFrequency (%)
2
66.7%
1
33.3%
Distinct1617
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
Minimum1999-04-26 00:00:00
Maximum2024-05-09 16:48:35
2024-05-11T14:54:53.250356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:53.550015image/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 size32.0 KiB
I
3761 
U
 
313

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3761
92.3%
U 313
 
7.7%

Length

2024-05-11T14:54:53.833105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:54.041953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3761
92.3%
u 313
 
7.7%
Distinct290
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:54:54.323429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:54:54.627771image/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 size32.0 KiB
식품자동판매기영업
4074 

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 4074
100.0%

Length

2024-05-11T14:54:54.885163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:55.090373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 4074
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1888
Distinct (%)50.7%
Missing353
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean191967.19
Minimum189469.39
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-05-11T14:54:55.330574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189469.39
5-th percentile190238.18
Q1190997.35
median191741.35
Q3193073.03
95-th percentile193818.18
Maximum194632.53
Range5163.1401
Interquartile range (IQR)2075.6874

Descriptive statistics

Standard deviation1195.6592
Coefficient of variation (CV)0.0062284559
Kurtosis-0.90251208
Mean191967.19
Median Absolute Deviation (MAD)911.50202
Skewness0.29534096
Sum7.1430992 × 108
Variance1429600.9
MonotonicityNot monotonic
2024-05-11T14:54:55.556810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193674.743726431 117
 
2.9%
192538.786642476 70
 
1.7%
194632.526367463 59
 
1.4%
191741.345847708 33
 
0.8%
193338.741394754 31
 
0.8%
191937.502334563 28
 
0.7%
193567.523026773 25
 
0.6%
191719.558993387 25
 
0.6%
191581.500265536 25
 
0.6%
193469.554731741 24
 
0.6%
Other values (1878) 3284
80.6%
(Missing) 353
 
8.7%
ValueCountFrequency (%)
189469.386236853 1
 
< 0.1%
189532.438871214 1
 
< 0.1%
189549.847307536 3
0.1%
189554.182520551 1
 
< 0.1%
189570.401236233 2
< 0.1%
189574.962072527 1
 
< 0.1%
189583.108318652 1
 
< 0.1%
189586.236800721 2
< 0.1%
189602.767582543 1
 
< 0.1%
189607.598899153 1
 
< 0.1%
ValueCountFrequency (%)
194632.526367463 59
1.4%
194599.854707059 1
 
< 0.1%
194592.276750438 1
 
< 0.1%
194561.746032498 2
 
< 0.1%
194530.535390096 4
 
0.1%
194504.656267957 1
 
< 0.1%
194422.414881513 1
 
< 0.1%
194370.32715363 12
 
0.3%
194324.398950764 23
 
0.6%
194294.277022719 9
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1888
Distinct (%)50.7%
Missing353
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean446045.72
Minimum442621.79
Maximum449759.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-05-11T14:54:55.775932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442621.79
5-th percentile443410.45
Q1445138.81
median446401.93
Q3446966.89
95-th percentile448034.65
Maximum449759.5
Range7137.716
Interquartile range (IQR)1828.0746

Descriptive statistics

Standard deviation1384.0771
Coefficient of variation (CV)0.0031029938
Kurtosis-0.41203148
Mean446045.72
Median Absolute Deviation (MAD)727.16006
Skewness-0.59040499
Sum1.6597361 × 109
Variance1915669.4
MonotonicityNot monotonic
2024-05-11T14:54:56.000899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447296.226305826 117
 
2.9%
447017.15917925 70
 
1.7%
446401.926526228 59
 
1.4%
445970.307641467 33
 
0.8%
446812.951473248 31
 
0.8%
446027.480859705 28
 
0.7%
446758.859822407 25
 
0.6%
446221.08893117 25
 
0.6%
446108.807192753 25
 
0.6%
446508.068667777 24
 
0.6%
Other values (1878) 3284
80.6%
(Missing) 353
 
8.7%
ValueCountFrequency (%)
442621.787911877 3
0.1%
442653.958507 2
 
< 0.1%
442700.796497298 3
0.1%
442710.662421803 1
 
< 0.1%
442715.143228546 1
 
< 0.1%
442715.677609564 1
 
< 0.1%
442744.165176674 1
 
< 0.1%
442751.471769958 2
 
< 0.1%
442756.531513655 1
 
< 0.1%
442777.411153359 6
0.1%
ValueCountFrequency (%)
449759.503932538 1
< 0.1%
449133.635570461 1
< 0.1%
449133.481757616 1
< 0.1%
449085.444429773 1
< 0.1%
449058.532372675 1
< 0.1%
449033.097215692 1
< 0.1%
449021.440559054 1
< 0.1%
449011.743315832 1
< 0.1%
449011.654080903 1
< 0.1%
448990.816559516 1
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
식품자동판매기영업
3876 
<NA>
 
198

Length

Max length9
Median length9
Mean length8.7569956
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:54:56.226587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.399817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 3876
95.1%
na 198
 
4.9%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
2483 
1
1390 
<NA>
 
198
2
 
3

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 2483
60.9%
1 1390
34.1%
<NA> 198
 
4.9%
2 3
 
0.1%

Length

2024-05-11T14:54:56.608781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:56.831897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2483
60.9%
1 1390
34.1%
na 198
 
4.9%
2 3
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3351 
1
511 
<NA>
 
198
2
 
14

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 3351
82.3%
1 511
 
12.5%
<NA> 198
 
4.9%
2 14
 
0.3%

Length

2024-05-11T14:54:57.145241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.332920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3351
82.3%
1 511
 
12.5%
na 198
 
4.9%
2 14
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
기타
2353 
<NA>
1325 
주택가주변
298 
유흥업소밀집지역
 
47
아파트지역
 
38
Other values (3)
 
13

Length

Max length8
Median length2
Mean length2.9845361
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2353
57.8%
<NA> 1325
32.5%
주택가주변 298
 
7.3%
유흥업소밀집지역 47
 
1.2%
아파트지역 38
 
0.9%
결혼예식장주변 7
 
0.2%
학교정화(상대) 4
 
0.1%
학교정화(절대) 2
 
< 0.1%

Length

2024-05-11T14:54:57.536751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:57.794990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2353
57.8%
na 1325
32.5%
주택가주변 298
 
7.3%
유흥업소밀집지역 47
 
1.2%
아파트지역 38
 
0.9%
결혼예식장주변 7
 
0.2%
학교정화(상대 4
 
0.1%
학교정화(절대 2
 
< 0.1%

등급구분명
Categorical

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
기타
2141 
<NA>
1325 
자율
465 
우수
 
115
지도
 
17
Other values (2)
 
11

Length

Max length4
Median length2
Mean length2.6502209
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 2141
52.6%
<NA> 1325
32.5%
자율 465
 
11.4%
우수 115
 
2.8%
지도 17
 
0.4%
관리 10
 
0.2%
1
 
< 0.1%

Length

2024-05-11T14:54:58.033298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.226040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 2141
52.6%
na 1325
32.5%
자율 465
 
11.4%
우수 115
 
2.8%
지도 17
 
0.4%
관리 10
 
0.2%
1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
<NA>
4066 
상수도전용
 
8

Length

Max length5
Median length4
Mean length4.0019637
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> 4066
99.8%
상수도전용 8
 
0.2%

Length

2024-05-11T14:54:58.465941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:58.751531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4066
99.8%
상수도전용 8
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:54:58.977445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:59.228729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3875 
<NA>
 
198
11
 
1

Length

Max length4
Median length1
Mean length1.1460481
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 3875
95.1%
<NA> 198
 
4.9%
11 1
 
< 0.1%

Length

2024-05-11T14:54:59.425174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:59.610931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3875
95.1%
na 198
 
4.9%
11 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:54:59.783869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:54:59.997445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:55:00.184410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:00.358045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:55:00.529974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:00.704936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
<NA>
3322 
자가
729 
임대
 
23

Length

Max length4
Median length4
Mean length3.6308297
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> 3322
81.5%
자가 729
 
17.9%
임대 23
 
0.6%

Length

2024-05-11T14:55:00.922042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:01.135024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3322
81.5%
자가 729
 
17.9%
임대 23
 
0.6%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:55:01.339688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:01.539007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.0 KiB
0
3876 
<NA>
 
198

Length

Max length4
Median length1
Mean length1.1458027
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3876
95.1%
<NA> 198
 
4.9%

Length

2024-05-11T14:55:01.723152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:02.226041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3876
95.1%
na 198
 
4.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing198
Missing (%)4.9%
Memory size8.1 KiB
False
3876 
(Missing)
 
198
ValueCountFrequency (%)
False 3876
95.1%
(Missing) 198
 
4.9%
2024-05-11T14:55:02.364952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.2%
Missing198
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean0.055959752
Minimum0
Maximum8
Zeros3784
Zeros (%)92.9%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-05-11T14:55:02.498257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.39530546
Coefficient of variation (CV)7.0641031
Kurtosis109.34768
Mean0.055959752
Median Absolute Deviation (MAD)0
Skewness9.1640773
Sum216.9
Variance0.15626641
MonotonicityNot monotonic
2024-05-11T14:55:02.674885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 3784
92.9%
2.0 74
 
1.8%
4.0 3
 
0.1%
3.3 3
 
0.1%
1.0 3
 
0.1%
3.0 3
 
0.1%
5.0 3
 
0.1%
6.0 2
 
< 0.1%
8.0 1
 
< 0.1%
(Missing) 198
 
4.9%
ValueCountFrequency (%)
0.0 3784
92.9%
1.0 3
 
0.1%
2.0 74
 
1.8%
3.0 3
 
0.1%
3.3 3
 
0.1%
4.0 3
 
0.1%
5.0 3
 
0.1%
6.0 2
 
< 0.1%
8.0 1
 
< 0.1%
ValueCountFrequency (%)
8.0 1
 
< 0.1%
6.0 2
 
< 0.1%
5.0 3
 
0.1%
4.0 3
 
0.1%
3.3 3
 
0.1%
3.0 3
 
0.1%
2.0 74
 
1.8%
1.0 3
 
0.1%
0.0 3784
92.9%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4074
Missing (%)100.0%
Memory size35.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-112-0998-0206319990520<NA>3폐업2폐업20030802<NA><NA><NA>02 6770966<NA>150802서울특별시 영등포구 당산동3가 1-6<NA><NA>한식촌2003-08-07 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업191227.414087446808.109514식품자동판매기영업01기타자율<NA>00000<NA>00N0.0<NA><NA><NA>
131800003180000-112-0999-0213819990623<NA>3폐업2폐업20111206<NA><NA><NA>02 6752663<NA>150105서울특별시 영등포구 양평동5가 2-2<NA><NA>경은식품2002-11-11 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업190414.563955448225.321185식품자동판매기영업02기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
231800003180000-112-0999-0222119990918<NA>3폐업2폐업20221125<NA><NA><NA>02 8334377<NA>150851서울특별시 영등포구 신길동 436-26서울특별시 영등포구 도림로 220 (신길동)7424유진식품2022-11-25 10:38:01U2021-10-31 22:07:00.0식품자동판매기영업191486.891258443986.911026<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331800003180000-112-1981-0000119810910<NA>3폐업2폐업20001023<NA><NA><NA>02<NA>150045서울특별시 영등포구 당산동5가 11-1<NA><NA>롯데산업(주)2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
431800003180000-112-1981-0000219810922<NA>3폐업2폐업20000711<NA><NA><NA>02 6769123<NA>150810서울특별시 영등포구 당산동6가 338-1<NA><NA>주유소판매기2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업191096.383033448115.641405식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
531800003180000-112-1981-0042319810926<NA>3폐업2폐업19980831<NA><NA><NA>02<NA>150887서울특별시 영등포구 여의도동 37-0<NA><NA>라이프여의슈퍼2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업193209.283508446474.956573식품자동판매기영업10기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
631800003180000-112-1981-0110819811204<NA>3폐업2폐업19960229<NA><NA><NA>02 8432169<NA>150830서울특별시 영등포구 도림동 145-2<NA><NA>2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업191260.258237445172.510978식품자동판매기영업00기타관리<NA>00000<NA>00N0.0<NA><NA><NA>
731800003180000-112-1983-0000319830324<NA>3폐업2폐업20001023<NA><NA><NA>02<NA>150040서울특별시 영등포구 당산동 121-81<NA><NA>어머니회관2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업191807.897612447406.79965식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
831800003180000-112-1983-0000419830324<NA>3폐업2폐업19960116<NA><NA><NA>02<NA>150045서울특별시 영등포구 당산동5가 4-0<NA><NA>(주)효성중공업2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
931800003180000-112-1983-0000519830324<NA>3폐업2폐업19960116<NA><NA><NA>02<NA>150045서울특별시 영등포구 당산동5가 5-4<NA><NA>효성중공업구판장2001-08-02 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA>00000<NA>00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
406431800003180000-112-2024-000092024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-814서울특별시 영등포구 대림동 710서울특별시 영등포구 도림로41길 6, 1층 (대림동)7413GS25 대림으뜸점2024-02-21 15:21:01I2023-12-01 22:03:00.0식품자동판매기영업190938.080289443591.339482<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406531800003180000-112-2024-000102024-03-05<NA>1영업/정상1영업<NA><NA><NA><NA>02 84547576.6150-842서울특별시 영등포구 신길동 623서울특별시 영등포구 여의대방로 159, 1층 (신길동)7392아리다2024-04-30 11:10:17U2023-12-05 00:02:00.0식품자동판매기영업192904.214242444355.323896<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406631800003180000-112-2024-000112024-03-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6150-832서울특별시 영등포구 도림동 234-14서울특별시 영등포구 도림로113길 11, 101호 (도림동)7374커피봇&얼음꽃2024-03-08 16:19:20U2023-12-02 23:00:00.0식품자동판매기영업190953.474743445170.006908<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406731800003180000-112-2024-000122024-03-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-815서울특별시 영등포구 대림동 739-2 조양빌딩서울특별시 영등포구 대림로 187, 조양빌딩 1층 (대림동)7412수성카 종합상사2024-03-25 10:31:09I2023-12-02 22:07:00.0식품자동판매기영업190946.718498443932.700621<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406831800003180000-112-2024-000132024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-858서울특별시 영등포구 신길동 3599 신풍역서울특별시 영등포구 신풍로 지하 27, 신풍역 7호선 (신길동)7393GS25s신풍역점2024-04-02 13:15:29I2023-12-04 00:04:00.0식품자동판매기영업191918.986667444237.236667<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
406931800003180000-112-2024-000142024-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-096서울특별시 영등포구 문래동6가 35서울특별시 영등포구 문래로 31, 1층 (문래동6가)7280(주)문래자동차검사정비사업소2024-04-05 09:13:22I2023-12-04 00:07:00.0식품자동판매기영업189797.798364446514.802025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407031800003180000-112-2024-000152024-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-034서울특별시 영등포구 영등포동4가 149서울특별시 영등포구 영등포로34길 3, 1층 일부호 (영등포동4가)7301무인카페 선2024-04-05 15:46:33I2023-12-04 00:07:00.0식품자동판매기영업191307.599894446417.535106<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407131800003180000-112-2024-000162024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-836서울특별시 영등포구 문래동3가 82-20 문래비즈타워서울특별시 영등포구 문래로 89, 문래비즈타워 1층 107호 (문래동3가)7294씨유 문래아카데미점2024-04-22 11:48:06I2023-12-03 22:04:00.0식품자동판매기영업190378.925728446388.933977<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407231800003180000-112-2024-000172024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3150-040서울특별시 영등포구 당산동 121-41 강변 한솔 그라치아서울특별시 영등포구 버드나루로22길 5, 103호 (당산동, 강변 한솔 그라치아)7224지에스25 당산리버파크점2024-04-26 13:30:34I2023-12-03 22:08:00.0식품자동판매기영업191763.779422447633.778132<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
407331800003180000-112-2024-000182024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-835서울특별시 영등포구 문래동3가 68-1 문래역서울특별시 영등포구 당산로 지하 28, 문래역 지하2층 (문래동3가)72982호선 문래역 지하2층2024-05-08 15:13:52I2023-12-04 23:00:00.0식품자동판매기영업190610.706271446232.11126<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>