Overview

Dataset statistics

Number of variables44
Number of observations2605
Missing cells26214
Missing cells (%)22.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory956.7 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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18241/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (65.6%)Imbalance
영업상태명 is highly imbalanced (65.6%)Imbalance
상세영업상태코드 is highly imbalanced (65.6%)Imbalance
상세영업상태명 is highly imbalanced (65.6%)Imbalance
데이터갱신구분 is highly imbalanced (59.3%)Imbalance
위생업태명 is highly imbalanced (68.2%)Imbalance
등급구분명 is highly imbalanced (51.2%)Imbalance
급수시설구분명 is highly imbalanced (83.4%)Imbalance
총인원 is highly imbalanced (94.0%)Imbalance
건물소유구분명 is highly imbalanced (56.5%)Imbalance
인허가취소일자 has 2605 (100.0%) missing valuesMissing
폐업일자 has 167 (6.4%) missing valuesMissing
휴업시작일자 has 2605 (100.0%) missing valuesMissing
휴업종료일자 has 2605 (100.0%) missing valuesMissing
재개업일자 has 2605 (100.0%) missing valuesMissing
전화번호 has 450 (17.3%) missing valuesMissing
소재지면적 has 2407 (92.4%) missing valuesMissing
도로명주소 has 2137 (82.0%) missing valuesMissing
도로명우편번호 has 2144 (82.3%) missing valuesMissing
좌표정보(X) has 187 (7.2%) missing valuesMissing
좌표정보(Y) has 187 (7.2%) missing valuesMissing
다중이용업소여부 has 150 (5.8%) missing valuesMissing
시설총규모 has 150 (5.8%) missing valuesMissing
전통업소지정번호 has 2605 (100.0%) missing valuesMissing
전통업소주된음식 has 2605 (100.0%) missing valuesMissing
홈페이지 has 2605 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 20.58929293)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 112 (4.3%) zerosZeros
시설총규모 has 2441 (93.7%) zerosZeros

Reproduction

Analysis started2024-05-11 06:34:44.867137
Analysis finished2024-05-11 06:34:47.615002
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
3140000
2605 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 2605
100.0%

Length

2024-05-11T15:34:47.736770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:47.962863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 2605
100.0%

관리번호
Text

UNIQUE 

Distinct2605
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2024-05-11T15:34:48.310029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters57310
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

Unique2605 ?
Unique (%)100.0%

Sample

1st row3140000-112-1983-00003
2nd row3140000-112-1983-00008
3rd row3140000-112-1983-00011
4th row3140000-112-1983-00979
5th row3140000-112-1983-00980
ValueCountFrequency (%)
3140000-112-1983-00003 1
 
< 0.1%
3140000-112-2001-01750 1
 
< 0.1%
3140000-112-2001-01732 1
 
< 0.1%
3140000-112-2001-01740 1
 
< 0.1%
3140000-112-2001-01733 1
 
< 0.1%
3140000-112-2001-01734 1
 
< 0.1%
3140000-112-2001-01735 1
 
< 0.1%
3140000-112-2001-01736 1
 
< 0.1%
3140000-112-2001-01737 1
 
< 0.1%
3140000-112-2001-01738 1
 
< 0.1%
Other values (2595) 2595
99.6%
2024-05-11T15:34:49.003718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18498
32.3%
1 11849
20.7%
- 7815
13.6%
2 5007
 
8.7%
9 3855
 
6.7%
3 3603
 
6.3%
4 3428
 
6.0%
7 1019
 
1.8%
5 781
 
1.4%
8 732
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49495
86.4%
Dash Punctuation 7815
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18498
37.4%
1 11849
23.9%
2 5007
 
10.1%
9 3855
 
7.8%
3 3603
 
7.3%
4 3428
 
6.9%
7 1019
 
2.1%
5 781
 
1.6%
8 732
 
1.5%
6 723
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 7815
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18498
32.3%
1 11849
20.7%
- 7815
13.6%
2 5007
 
8.7%
9 3855
 
6.7%
3 3603
 
6.3%
4 3428
 
6.0%
7 1019
 
1.8%
5 781
 
1.4%
8 732
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18498
32.3%
1 11849
20.7%
- 7815
13.6%
2 5007
 
8.7%
9 3855
 
6.7%
3 3603
 
6.3%
4 3428
 
6.0%
7 1019
 
1.8%
5 781
 
1.4%
8 732
 
1.3%

인허가일자
Date

Distinct1283
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
Minimum1983-03-18 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T15:34:49.397510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:34:49.734553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
3
2438 
1
 
167

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 2438
93.6%
1 167
 
6.4%

Length

2024-05-11T15:34:49.981621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:50.187177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2438
93.6%
1 167
 
6.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
폐업
2438 
영업/정상
 
167

Length

Max length5
Median length2
Mean length2.1923225
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2438
93.6%
영업/정상 167
 
6.4%

Length

2024-05-11T15:34:50.437282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:50.643752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2438
93.6%
영업/정상 167
 
6.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2
2438 
1
 
167

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 2438
93.6%
1 167
 
6.4%

Length

2024-05-11T15:34:50.851227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:51.050797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2438
93.6%
1 167
 
6.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
폐업
2438 
영업
 
167

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 2438
93.6%
영업 167
 
6.4%

Length

2024-05-11T15:34:51.281942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:34:51.512622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2438
93.6%
영업 167
 
6.4%

폐업일자
Date

MISSING 

Distinct1597
Distinct (%)65.5%
Missing167
Missing (%)6.4%
Memory size20.5 KiB
Minimum1986-10-06 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T15:34:51.844197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:34:52.164342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

전화번호
Text

MISSING 

Distinct1122
Distinct (%)52.1%
Missing450
Missing (%)17.3%
Memory size20.5 KiB
2024-05-11T15:34:52.697031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.5800464
Min length2

Characters and Unicode

Total characters16335
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

Unique1066 ?
Unique (%)49.5%

Sample

1st row02
2nd row02
3rd row0226000662
4th row02
5th row02
ValueCountFrequency (%)
02 1110
42.0%
0200000000 223
 
8.4%
0 54
 
2.0%
00000 48
 
1.8%
0226505691 9
 
0.3%
0226203803 7
 
0.3%
0206171155 6
 
0.2%
0222528907 5
 
0.2%
0226450164 4
 
0.2%
07044937699 4
 
0.2%
Other values (1116) 1175
44.4%
2024-05-11T15:34:53.583591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5173
31.7%
2 3538
21.7%
6 1692
 
10.4%
4 957
 
5.9%
5 858
 
5.3%
9 836
 
5.1%
710
 
4.3%
3 660
 
4.0%
1 647
 
4.0%
8 632
 
3.9%
Other values (2) 632
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15624
95.6%
Space Separator 710
 
4.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5173
33.1%
2 3538
22.6%
6 1692
 
10.8%
4 957
 
6.1%
5 858
 
5.5%
9 836
 
5.4%
3 660
 
4.2%
1 647
 
4.1%
8 632
 
4.0%
7 631
 
4.0%
Space Separator
ValueCountFrequency (%)
710
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16335
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5173
31.7%
2 3538
21.7%
6 1692
 
10.4%
4 957
 
5.9%
5 858
 
5.3%
9 836
 
5.1%
710
 
4.3%
3 660
 
4.0%
1 647
 
4.0%
8 632
 
3.9%
Other values (2) 632
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16335
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5173
31.7%
2 3538
21.7%
6 1692
 
10.4%
4 957
 
5.9%
5 858
 
5.3%
9 836
 
5.1%
710
 
4.3%
3 660
 
4.0%
1 647
 
4.0%
8 632
 
3.9%
Other values (2) 632
 
3.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct44
Distinct (%)22.2%
Missing2407
Missing (%)92.4%
Infinite0
Infinite (%)0.0%
Mean5.7913131
Minimum0
Maximum53.31
Zeros112
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-05-11T15:34:53.909166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.3
95-th percentile30
Maximum53.31
Range53.31
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation10.704265
Coefficient of variation (CV)1.8483312
Kurtosis3.3162957
Mean5.7913131
Median Absolute Deviation (MAD)0
Skewness2.0412063
Sum1146.68
Variance114.58129
MonotonicityNot monotonic
2024-05-11T15:34:54.208986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 112
 
4.3%
3.3 39
 
1.5%
13.95 2
 
0.1%
6.6 2
 
0.1%
26.4 2
 
0.1%
28.8 2
 
0.1%
30.0 2
 
0.1%
3.6 1
 
< 0.1%
25.0 1
 
< 0.1%
30.25 1
 
< 0.1%
Other values (34) 34
 
1.3%
(Missing) 2407
92.4%
ValueCountFrequency (%)
0.0 112
4.3%
0.6 1
 
< 0.1%
1.0 1
 
< 0.1%
1.48 1
 
< 0.1%
2.0 1
 
< 0.1%
3.3 39
 
1.5%
3.6 1
 
< 0.1%
6.3 1
 
< 0.1%
6.5 1
 
< 0.1%
6.6 2
 
0.1%
ValueCountFrequency (%)
53.31 1
< 0.1%
41.0 1
< 0.1%
40.0 1
< 0.1%
39.4 1
< 0.1%
35.13 1
< 0.1%
33.6 1
< 0.1%
33.0 1
< 0.1%
30.94 1
< 0.1%
30.25 1
< 0.1%
30.0 2
0.1%

소재지우편번호
Text

Distinct148
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2024-05-11T15:34:54.707396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0287908
Min length6

Characters and Unicode

Total characters15705
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

Unique34 ?
Unique (%)1.3%

Sample

1st row158811
2nd row158841
3rd row158-738
4th row158806
5th row158070
ValueCountFrequency (%)
158806 146
 
5.6%
158050 137
 
5.3%
158860 122
 
4.7%
158861 114
 
4.4%
158070 105
 
4.0%
158811 75
 
2.9%
158864 69
 
2.6%
158849 64
 
2.5%
158857 64
 
2.5%
158824 63
 
2.4%
Other values (138) 1646
63.2%
2024-05-11T15:34:55.564627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 5153
32.8%
5 3259
20.8%
1 3217
20.5%
0 1073
 
6.8%
6 696
 
4.4%
2 543
 
3.5%
7 525
 
3.3%
4 500
 
3.2%
3 338
 
2.2%
9 326
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15630
99.5%
Dash Punctuation 75
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 5153
33.0%
5 3259
20.9%
1 3217
20.6%
0 1073
 
6.9%
6 696
 
4.5%
2 543
 
3.5%
7 525
 
3.4%
4 500
 
3.2%
3 338
 
2.2%
9 326
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 5153
32.8%
5 3259
20.8%
1 3217
20.5%
0 1073
 
6.8%
6 696
 
4.4%
2 543
 
3.5%
7 525
 
3.3%
4 500
 
3.2%
3 338
 
2.2%
9 326
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 5153
32.8%
5 3259
20.8%
1 3217
20.5%
0 1073
 
6.8%
6 696
 
4.4%
2 543
 
3.5%
7 525
 
3.3%
4 500
 
3.2%
3 338
 
2.2%
9 326
 
2.1%

지번주소
Text

Distinct2288
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2024-05-11T15:34:56.361621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length45
Mean length24.309405
Min length16

Characters and Unicode

Total characters63326
Distinct characters463
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2072 ?
Unique (%)79.5%

Sample

1st row서울특별시 양천구 목동 613-6 제일등촌점
2nd row서울특별시 양천구 신월동 550-5
3rd row서울특별시 양천구 신정동 899-1 홍익병원 본관1층
4th row서울특별시 양천구 목동 406-28 한전강서지점
5th row서울특별시 양천구 신정동 606-1 서서울병원
ValueCountFrequency (%)
서울특별시 2605
21.2%
양천구 2605
21.2%
신정동 1006
 
8.2%
신월동 803
 
6.5%
목동 797
 
6.5%
실외 156
 
1.3%
실내 79
 
0.6%
산 46
 
0.4%
지상1층 41
 
0.3%
1층 40
 
0.3%
Other values (2805) 4109
33.4%
2024-05-11T15:34:57.465997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12102
19.1%
1 2931
 
4.6%
동 2837
 
4.5%
서 2694
 
4.3%
양 2674
 
4.2%
천 2658
 
4.2%
시 2641
 
4.2%
구 2641
 
4.2%
울 2620
 
4.1%
별 2612
 
4.1%
Other values (453) 26916
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35053
55.4%
Decimal Number 12549
 
19.8%
Space Separator 12102
 
19.1%
Dash Punctuation 2466
 
3.9%
Open Punctuation 469
 
0.7%
Close Punctuation 468
 
0.7%
Uppercase Letter 117
 
0.2%
Other Punctuation 93
 
0.1%
Lowercase Letter 6
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2837
 
8.1%
서 2694
 
7.7%
양 2674
 
7.6%
천 2658
 
7.6%
시 2641
 
7.5%
구 2641
 
7.5%
울 2620
 
7.5%
별 2612
 
7.5%
특 2605
 
7.4%
신 1936
 
5.5%
Other values (414) 9135
26.1%
Uppercase Letter
ValueCountFrequency (%)
B 37
31.6%
A 18
15.4%
C 16
13.7%
S 13
 
11.1%
D 8
 
6.8%
G 6
 
5.1%
T 3
 
2.6%
P 3
 
2.6%
L 3
 
2.6%
I 3
 
2.6%
Other values (6) 7
 
6.0%
Decimal Number
ValueCountFrequency (%)
1 2931
23.4%
2 1555
12.4%
0 1321
10.5%
9 1271
10.1%
3 1036
 
8.3%
5 1031
 
8.2%
4 1030
 
8.2%
7 824
 
6.6%
6 810
 
6.5%
8 740
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 81
87.1%
/ 7
 
7.5%
. 2
 
2.2%
@ 2
 
2.2%
? 1
 
1.1%
Lowercase Letter
ValueCountFrequency (%)
c 3
50.0%
a 2
33.3%
b 1
 
16.7%
Space Separator
ValueCountFrequency (%)
12102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 469
100.0%
Close Punctuation
ValueCountFrequency (%)
) 468
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35053
55.4%
Common 28150
44.5%
Latin 123
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2837
 
8.1%
서 2694
 
7.7%
양 2674
 
7.6%
천 2658
 
7.6%
시 2641
 
7.5%
구 2641
 
7.5%
울 2620
 
7.5%
별 2612
 
7.5%
특 2605
 
7.4%
신 1936
 
5.5%
Other values (414) 9135
26.1%
Common
ValueCountFrequency (%)
12102
43.0%
1 2931
 
10.4%
- 2466
 
8.8%
2 1555
 
5.5%
0 1321
 
4.7%
9 1271
 
4.5%
3 1036
 
3.7%
5 1031
 
3.7%
4 1030
 
3.7%
7 824
 
2.9%
Other values (10) 2583
 
9.2%
Latin
ValueCountFrequency (%)
B 37
30.1%
A 18
14.6%
C 16
13.0%
S 13
 
10.6%
D 8
 
6.5%
G 6
 
4.9%
T 3
 
2.4%
c 3
 
2.4%
P 3
 
2.4%
L 3
 
2.4%
Other values (9) 13
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35053
55.4%
ASCII 28273
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12102
42.8%
1 2931
 
10.4%
- 2466
 
8.7%
2 1555
 
5.5%
0 1321
 
4.7%
9 1271
 
4.5%
3 1036
 
3.7%
5 1031
 
3.6%
4 1030
 
3.6%
7 824
 
2.9%
Other values (29) 2706
 
9.6%
Hangul
ValueCountFrequency (%)
동 2837
 
8.1%
서 2694
 
7.7%
양 2674
 
7.6%
천 2658
 
7.6%
시 2641
 
7.5%
구 2641
 
7.5%
울 2620
 
7.5%
별 2612
 
7.5%
특 2605
 
7.4%
신 1936
 
5.5%
Other values (414) 9135
26.1%

도로명주소
Text

MISSING 

Distinct453
Distinct (%)96.8%
Missing2137
Missing (%)82.0%
Memory size20.5 KiB
2024-05-11T15:34:58.029939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length34.852564
Min length22

Characters and Unicode

Total characters16311
Distinct characters273
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique438 ?
Unique (%)93.6%

Sample

1st row서울특별시 양천구 목동로 225 (신정동, 홍익병원 본관1층)
2nd row서울특별시 양천구 남부순환로 353 (신월동,가로공원(실외))
3rd row서울특별시 양천구 남부순환로 353 (신월동,국민신월점(실내))
4th row서울특별시 양천구 중앙로32길 1 (신정동)
5th row서울특별시 양천구 화곡로 50 (신월동,신월5동사(실외))
ValueCountFrequency (%)
서울특별시 468
 
15.7%
양천구 468
 
15.7%
신정동 117
 
3.9%
목동 111
 
3.7%
1층 105
 
3.5%
신월동 73
 
2.5%
지상1층 51
 
1.7%
실내 50
 
1.7%
목동동로 44
 
1.5%
목동서로 39
 
1.3%
Other values (692) 1450
48.7%
2024-05-11T15:34:58.897120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2508
 
15.4%
동 793
 
4.9%
1 668
 
4.1%
) 662
 
4.1%
( 662
 
4.1%
, 617
 
3.8%
양 537
 
3.3%
서 530
 
3.2%
천 514
 
3.2%
시 487
 
3.0%
Other values (263) 8333
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9615
58.9%
Space Separator 2508
 
15.4%
Decimal Number 2175
 
13.3%
Close Punctuation 662
 
4.1%
Open Punctuation 662
 
4.1%
Other Punctuation 619
 
3.8%
Uppercase Letter 36
 
0.2%
Dash Punctuation 32
 
0.2%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 793
 
8.2%
양 537
 
5.6%
서 530
 
5.5%
천 514
 
5.3%
시 487
 
5.1%
로 484
 
5.0%
구 483
 
5.0%
울 472
 
4.9%
별 471
 
4.9%
특 468
 
4.9%
Other values (232) 4376
45.5%
Uppercase Letter
ValueCountFrequency (%)
B 9
25.0%
A 6
16.7%
S 4
11.1%
C 4
11.1%
G 3
 
8.3%
R 2
 
5.6%
I 2
 
5.6%
P 1
 
2.8%
E 1
 
2.8%
U 1
 
2.8%
Other values (3) 3
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 668
30.7%
2 274
12.6%
0 253
 
11.6%
3 241
 
11.1%
5 147
 
6.8%
4 142
 
6.5%
7 132
 
6.1%
6 129
 
5.9%
9 101
 
4.6%
8 88
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 617
99.7%
. 2
 
0.3%
Space Separator
ValueCountFrequency (%)
2508
100.0%
Close Punctuation
ValueCountFrequency (%)
) 662
100.0%
Open Punctuation
ValueCountFrequency (%)
( 662
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9615
58.9%
Common 6659
40.8%
Latin 37
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 793
 
8.2%
양 537
 
5.6%
서 530
 
5.5%
천 514
 
5.3%
시 487
 
5.1%
로 484
 
5.0%
구 483
 
5.0%
울 472
 
4.9%
별 471
 
4.9%
특 468
 
4.9%
Other values (232) 4376
45.5%
Common
ValueCountFrequency (%)
2508
37.7%
1 668
 
10.0%
) 662
 
9.9%
( 662
 
9.9%
, 617
 
9.3%
2 274
 
4.1%
0 253
 
3.8%
3 241
 
3.6%
5 147
 
2.2%
4 142
 
2.1%
Other values (7) 485
 
7.3%
Latin
ValueCountFrequency (%)
B 9
24.3%
A 6
16.2%
S 4
10.8%
C 4
10.8%
G 3
 
8.1%
R 2
 
5.4%
I 2
 
5.4%
P 1
 
2.7%
m 1
 
2.7%
E 1
 
2.7%
Other values (4) 4
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9615
58.9%
ASCII 6696
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2508
37.5%
1 668
 
10.0%
) 662
 
9.9%
( 662
 
9.9%
, 617
 
9.2%
2 274
 
4.1%
0 253
 
3.8%
3 241
 
3.6%
5 147
 
2.2%
4 142
 
2.1%
Other values (21) 522
 
7.8%
Hangul
ValueCountFrequency (%)
동 793
 
8.2%
양 537
 
5.6%
서 530
 
5.5%
천 514
 
5.3%
시 487
 
5.1%
로 484
 
5.0%
구 483
 
5.0%
울 472
 
4.9%
별 471
 
4.9%
특 468
 
4.9%
Other values (232) 4376
45.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct153
Distinct (%)33.2%
Missing2144
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean8000.3991
Minimum7900
Maximum8110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-05-11T15:34:59.177603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7905
Q17950
median7999
Q38041
95-th percentile8095
Maximum8110
Range210
Interquartile range (IQR)91

Descriptive statistics

Standard deviation59.060922
Coefficient of variation (CV)0.007382247
Kurtosis-0.98158104
Mean8000.3991
Median Absolute Deviation (MAD)45
Skewness0.069716032
Sum3688184
Variance3488.1925
MonotonicityNot monotonic
2024-05-11T15:34:59.422684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7985 16
 
0.6%
8095 15
 
0.6%
8006 11
 
0.4%
8023 7
 
0.3%
7902 7
 
0.3%
8073 7
 
0.3%
7988 7
 
0.3%
7950 6
 
0.2%
7912 6
 
0.2%
7915 6
 
0.2%
Other values (143) 373
 
14.3%
(Missing) 2144
82.3%
ValueCountFrequency (%)
7900 3
0.1%
7901 1
 
< 0.1%
7902 7
0.3%
7903 5
0.2%
7904 5
0.2%
7905 3
0.1%
7907 1
 
< 0.1%
7909 5
0.2%
7910 4
0.2%
7912 6
0.2%
ValueCountFrequency (%)
8110 2
 
0.1%
8107 1
 
< 0.1%
8106 3
 
0.1%
8104 5
 
0.2%
8103 1
 
< 0.1%
8100 3
 
0.1%
8098 3
 
0.1%
8097 2
 
0.1%
8096 1
 
< 0.1%
8095 15
0.6%

사업장명
Text

Distinct2209
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
2024-05-11T15:34:59.904628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length5.1873321
Min length1

Characters and Unicode

Total characters13513
Distinct characters639
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

Unique2000 ?
Unique (%)76.8%

Sample

1st row제일은행등천동지점
2nd row유양열
3rd row홍익병원
4th row김윤화
5th row김명훈
ValueCountFrequency (%)
무 45
 
1.6%
이대목동병원 16
 
0.6%
이마트24 13
 
0.5%
gs25 13
 
0.5%
씨유 12
 
0.4%
김도생 12
 
0.4%
구내매점(코너스톤 11
 
0.4%
장범식 8
 
0.3%
정기현 7
 
0.3%
정점조 7
 
0.3%
Other values (2248) 2598
94.7%
2024-05-11T15:35:00.615444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 332
 
2.5%
이 293
 
2.2%
점 265
 
2.0%
신 218
 
1.6%
목 214
 
1.6%
정 196
 
1.5%
스 185
 
1.4%
퍼 184
 
1.4%
김 179
 
1.3%
지 163
 
1.2%
Other values (629) 11284
83.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12499
92.5%
Decimal Number 335
 
2.5%
Uppercase Letter 202
 
1.5%
Space Separator 141
 
1.0%
Open Punctuation 129
 
1.0%
Close Punctuation 129
 
1.0%
Lowercase Letter 50
 
0.4%
Other Punctuation 21
 
0.2%
Dash Punctuation 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 332
 
2.7%
이 293
 
2.3%
점 265
 
2.1%
신 218
 
1.7%
목 214
 
1.7%
정 196
 
1.6%
스 185
 
1.5%
퍼 184
 
1.5%
김 179
 
1.4%
지 163
 
1.3%
Other values (572) 10270
82.2%
Uppercase Letter
ValueCountFrequency (%)
S 44
21.8%
G 38
18.8%
C 28
13.9%
P 12
 
5.9%
L 10
 
5.0%
K 10
 
5.0%
A 8
 
4.0%
U 7
 
3.5%
T 7
 
3.5%
B 6
 
3.0%
Other values (12) 32
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 11
22.0%
o 9
18.0%
a 6
12.0%
f 5
10.0%
l 4
 
8.0%
c 4
 
8.0%
p 2
 
4.0%
r 2
 
4.0%
d 2
 
4.0%
s 2
 
4.0%
Other values (3) 3
 
6.0%
Decimal Number
ValueCountFrequency (%)
2 109
32.5%
5 78
23.3%
4 50
14.9%
1 45
13.4%
3 18
 
5.4%
9 9
 
2.7%
7 7
 
2.1%
6 7
 
2.1%
8 6
 
1.8%
0 6
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 15
71.4%
, 2
 
9.5%
? 2
 
9.5%
@ 1
 
4.8%
& 1
 
4.8%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12499
92.5%
Common 762
 
5.6%
Latin 252
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 332
 
2.7%
이 293
 
2.3%
점 265
 
2.1%
신 218
 
1.7%
목 214
 
1.7%
정 196
 
1.6%
스 185
 
1.5%
퍼 184
 
1.5%
김 179
 
1.4%
지 163
 
1.3%
Other values (572) 10270
82.2%
Latin
ValueCountFrequency (%)
S 44
17.5%
G 38
15.1%
C 28
 
11.1%
P 12
 
4.8%
e 11
 
4.4%
L 10
 
4.0%
K 10
 
4.0%
o 9
 
3.6%
A 8
 
3.2%
U 7
 
2.8%
Other values (25) 75
29.8%
Common
ValueCountFrequency (%)
141
18.5%
( 129
16.9%
) 129
16.9%
2 109
14.3%
5 78
10.2%
4 50
 
6.6%
1 45
 
5.9%
3 18
 
2.4%
. 15
 
2.0%
9 9
 
1.2%
Other values (12) 39
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12498
92.5%
ASCII 1014
 
7.5%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 332
 
2.7%
이 293
 
2.3%
점 265
 
2.1%
신 218
 
1.7%
목 214
 
1.7%
정 196
 
1.6%
스 185
 
1.5%
퍼 184
 
1.5%
김 179
 
1.4%
지 163
 
1.3%
Other values (571) 10269
82.2%
ASCII
ValueCountFrequency (%)
141
13.9%
( 129
12.7%
) 129
12.7%
2 109
10.7%
5 78
 
7.7%
4 50
 
4.9%
1 45
 
4.4%
S 44
 
4.3%
G 38
 
3.7%
C 28
 
2.8%
Other values (47) 223
22.0%
Compat Jamo
ValueCountFrequency (%)
ㅌ 1
100.0%

최종수정일자
Date

Distinct1410
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
Minimum1999-01-15 00:00:00
Maximum2024-05-08 15:18:27
2024-05-11T15:35:00.890104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:01.199405image/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 size20.5 KiB
I
2393 
U
 
212

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 2393
91.9%
U 212
 
8.1%

Length

2024-05-11T15:35:01.499426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:01.671644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2393
91.9%
u 212
 
8.1%

데이터갱신일자
Date

Distinct219
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:35:01.896696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:35:02.162113image/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 size20.5 KiB
식품자동판매기영업
2605 

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 2605
100.0%

Length

2024-05-11T15:35:02.429133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:02.633638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2605
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1520
Distinct (%)62.9%
Missing187
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean187210.42
Minimum184320.2
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-05-11T15:35:02.835013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184320.2
5-th percentile184747.1
Q1185962.81
median187536.9
Q3188354.12
95-th percentile189023.3
Maximum189878.41
Range5558.211
Interquartile range (IQR)2391.315

Descriptive statistics

Standard deviation1417.2961
Coefficient of variation (CV)0.0075706048
Kurtosis-1.0392056
Mean187210.42
Median Absolute Deviation (MAD)1055.0685
Skewness-0.35027772
Sum4.526748 × 108
Variance2008728.3
MonotonicityNot monotonic
2024-05-11T15:35:03.103009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188904.571764159 21
 
0.8%
189878.40729119 19
 
0.7%
189469.901305589 17
 
0.7%
188871.512837973 15
 
0.6%
188248.45432693 15
 
0.6%
187995.261631804 12
 
0.5%
188467.215363052 11
 
0.4%
186990.442889775 10
 
0.4%
188344.714956921 10
 
0.4%
188977.171050288 10
 
0.4%
Other values (1510) 2278
87.4%
(Missing) 187
 
7.2%
ValueCountFrequency (%)
184320.196338406 1
 
< 0.1%
184325.616204517 1
 
< 0.1%
184330.402293717 1
 
< 0.1%
184373.07604881 4
0.2%
184383.822944091 1
 
< 0.1%
184400.769531722 1
 
< 0.1%
184411.044783706 2
0.1%
184443.469766368 2
0.1%
184448.497335143 1
 
< 0.1%
184457.852171363 2
0.1%
ValueCountFrequency (%)
189878.40729119 19
0.7%
189755.541308355 7
 
0.3%
189749.776358917 2
 
0.1%
189735.691305213 1
 
< 0.1%
189709.803505321 1
 
< 0.1%
189659.125277836 2
 
0.1%
189576.475334065 3
 
0.1%
189512.045139098 1
 
< 0.1%
189508.199599752 7
 
0.3%
189471.306217651 2
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1520
Distinct (%)62.9%
Missing187
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean447245.06
Minimum444888.21
Maximum449789.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-05-11T15:35:03.777076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444888.21
5-th percentile445905.19
Q1446514.13
median446989.32
Q3448022.98
95-th percentile449325.92
Maximum449789.73
Range4901.5206
Interquartile range (IQR)1508.854

Descriptive statistics

Standard deviation1031.0596
Coefficient of variation (CV)0.0023053571
Kurtosis-0.42108805
Mean447245.06
Median Absolute Deviation (MAD)662.77353
Skewness0.49084107
Sum1.0814386 × 109
Variance1063083.8
MonotonicityNot monotonic
2024-05-11T15:35:04.074667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446861.525362878 21
 
0.8%
448255.199632516 19
 
0.7%
447591.034147017 17
 
0.7%
447348.13213342 15
 
0.6%
447406.301288366 15
 
0.6%
445782.650926649 12
 
0.5%
446003.941216623 11
 
0.4%
446243.520221567 10
 
0.4%
446998.822550306 10
 
0.4%
447466.355031447 10
 
0.4%
Other values (1510) 2278
87.4%
(Missing) 187
 
7.2%
ValueCountFrequency (%)
444888.208549896 1
< 0.1%
444932.284596469 1
< 0.1%
444959.165614069 1
< 0.1%
444975.320976036 1
< 0.1%
444980.576843755 1
< 0.1%
445006.611450798 2
0.1%
445039.928375227 1
< 0.1%
445064.011138948 2
0.1%
445081.396522145 1
< 0.1%
445085.413102479 2
0.1%
ValueCountFrequency (%)
449789.729178343 2
0.1%
449763.347390512 1
 
< 0.1%
449753.158413664 3
0.1%
449727.47955699 1
 
< 0.1%
449722.378668012 1
 
< 0.1%
449714.789164209 2
0.1%
449706.807437882 1
 
< 0.1%
449701.802558519 1
 
< 0.1%
449698.560303556 2
0.1%
449683.219205227 2
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
식품자동판매기영업
2455 
<NA>
 
150

Length

Max length9
Median length9
Mean length8.7120921
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 2455
94.2%
<NA> 150
 
5.8%

Length

2024-05-11T15:35:04.324184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:04.504585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2455
94.2%
na 150
 
5.8%

남성종사자수
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
0
1357 
<NA>
1047 
1
198 
2
 
3

Length

Max length4
Median length1
Mean length2.2057582
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1357
52.1%
<NA> 1047
40.2%
1 198
 
7.6%
2 3
 
0.1%

Length

2024-05-11T15:35:04.716700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:04.906402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1357
52.1%
na 1047
40.2%
1 198
 
7.6%
2 3
 
0.1%

여성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
0
1371 
<NA>
1047 
1
187 

Length

Max length4
Median length1
Mean length2.2057582
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1371
52.6%
<NA> 1047
40.2%
1 187
 
7.2%

Length

2024-05-11T15:35:05.101925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:05.277925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1371
52.6%
na 1047
40.2%
1 187
 
7.2%

영업장주변구분명
Categorical

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
기타
1281 
<NA>
904 
주택가주변
405 
아파트지역
 
12
학교정화(절대)
 
2

Length

Max length8
Median length5
Mean length3.18119
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1281
49.2%
<NA> 904
34.7%
주택가주변 405
 
15.5%
아파트지역 12
 
0.5%
학교정화(절대) 2
 
0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-05-11T15:35:05.463939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:05.638659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1281
49.2%
na 904
34.7%
주택가주변 405
 
15.5%
아파트지역 12
 
0.5%
학교정화(절대 2
 
0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
기타
1611 
<NA>
904 
지도
 
88
갑
 
1
자율
 
1

Length

Max length4
Median length2
Mean length2.693666
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1611
61.8%
<NA> 904
34.7%
지도 88
 
3.4%
갑 1
 
< 0.1%
자율 1
 
< 0.1%

Length

2024-05-11T15:35:05.890312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:06.119678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1611
61.8%
na 904
34.7%
지도 88
 
3.4%
갑 1
 
< 0.1%
자율 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
2541 
상수도전용
 
64

Length

Max length5
Median length4
Mean length4.0245681
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> 2541
97.5%
상수도전용 64
 
2.5%

Length

2024-05-11T15:35:06.330781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:06.501626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2541
97.5%
상수도전용 64
 
2.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
2587 
0
 
18

Length

Max length4
Median length4
Mean length3.9792706
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> 2587
99.3%
0 18
 
0.7%

Length

2024-05-11T15:35:06.686826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:06.834882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2587
99.3%
0 18
 
0.7%

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
1783 
0
822 

Length

Max length4
Median length4
Mean length3.0533589
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> 1783
68.4%
0 822
31.6%

Length

2024-05-11T15:35:07.005952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:07.162344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1783
68.4%
0 822
31.6%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
1783 
0
822 

Length

Max length4
Median length4
Mean length3.0533589
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> 1783
68.4%
0 822
31.6%

Length

2024-05-11T15:35:07.348064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:07.517159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1783
68.4%
0 822
31.6%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
1783 
0
822 

Length

Max length4
Median length4
Mean length3.0533589
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> 1783
68.4%
0 822
31.6%

Length

2024-05-11T15:35:07.686781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:07.853677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1783
68.4%
0 822
31.6%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
1783 
0
822 

Length

Max length4
Median length4
Mean length3.0533589
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> 1783
68.4%
0 822
31.6%

Length

2024-05-11T15:35:08.102855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:08.322481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1783
68.4%
0 822
31.6%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
2195 
자가
379 
임대
 
31

Length

Max length4
Median length4
Mean length3.6852207
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> 2195
84.3%
자가 379
 
14.5%
임대 31
 
1.2%

Length

2024-05-11T15:35:08.510446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:08.702906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2195
84.3%
자가 379
 
14.5%
임대 31
 
1.2%

보증액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
2271 
0
334 

Length

Max length4
Median length4
Mean length3.6153551
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> 2271
87.2%
0 334
 
12.8%

Length

2024-05-11T15:35:08.904878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:09.074367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
87.2%
0 334
 
12.8%

월세액
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size20.5 KiB
<NA>
2271 
0
334 

Length

Max length4
Median length4
Mean length3.6153551
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> 2271
87.2%
0 334
 
12.8%

Length

2024-05-11T15:35:09.253320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:35:09.401222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2271
87.2%
0 334
 
12.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing150
Missing (%)5.8%
Memory size5.2 KiB
False
2455 
(Missing)
 
150
ValueCountFrequency (%)
False 2455
94.2%
(Missing) 150
 
5.8%
2024-05-11T15:35:09.526169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.3%
Missing150
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean0.078680244
Minimum0
Maximum35.13
Zeros2441
Zeros (%)93.7%
Negative0
Negative (%)0.0%
Memory size23.0 KiB
2024-05-11T15:35:09.669321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum35.13
Range35.13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4060957
Coefficient of variation (CV)17.871013
Kurtosis440.88106
Mean0.078680244
Median Absolute Deviation (MAD)0
Skewness20.589293
Sum193.16
Variance1.9771051
MonotonicityNot monotonic
2024-05-11T15:35:09.856160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 2441
93.7%
3.3 8
 
0.3%
35.13 1
 
< 0.1%
24.0 1
 
< 0.1%
33.6 1
 
< 0.1%
26.4 1
 
< 0.1%
26.0 1
 
< 0.1%
21.63 1
 
< 0.1%
(Missing) 150
 
5.8%
ValueCountFrequency (%)
0.0 2441
93.7%
3.3 8
 
0.3%
21.63 1
 
< 0.1%
24.0 1
 
< 0.1%
26.0 1
 
< 0.1%
26.4 1
 
< 0.1%
33.6 1
 
< 0.1%
35.13 1
 
< 0.1%
ValueCountFrequency (%)
35.13 1
 
< 0.1%
33.6 1
 
< 0.1%
26.4 1
 
< 0.1%
26.0 1
 
< 0.1%
24.0 1
 
< 0.1%
21.63 1
 
< 0.1%
3.3 8
 
0.3%
0.0 2441
93.7%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2605
Missing (%)100.0%
Memory size23.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-112-1983-0000319830518<NA>3폐업2폐업20021216<NA><NA><NA>02<NA>158811서울특별시 양천구 목동 613-6 제일등촌점<NA><NA>제일은행등천동지점2009-03-16 17:06:56I2018-08-31 23:59:59.0식품자동판매기영업187896.039585449631.367669식품자동판매기영업10기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131400003140000-112-1983-0000819830325<NA>3폐업2폐업19931222<NA><NA><NA>02<NA>158841서울특별시 양천구 신월동 550-5<NA><NA>유양열2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업185983.85621446209.123108식품자동판매기영업20기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231400003140000-112-1983-000111983-03-18<NA>3폐업2폐업2023-05-10<NA><NA><NA>0226000662<NA>158-738서울특별시 양천구 신정동 899-1 홍익병원 본관1층서울특별시 양천구 목동로 225 (신정동, 홍익병원 본관1층)7937홍익병원2023-05-10 11:57:18U2022-12-04 23:02:00.0식품자동판매기영업187879.054915447370.031968<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331400003140000-112-1983-0097919830326<NA>3폐업2폐업19890327<NA><NA><NA>02<NA>158806서울특별시 양천구 목동 406-28 한전강서지점<NA><NA>김윤화2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업188951.756198446969.38865식품자동판매기영업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431400003140000-112-1983-0098019830325<NA>3폐업2폐업19890327<NA><NA><NA>02<NA>158070서울특별시 양천구 신정동 606-1 서서울병원<NA><NA>김명훈2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531400003140000-112-1984-0000219840210<NA>3폐업2폐업20070525<NA><NA><NA>02<NA>158808서울특별시 양천구 목동 514-5 대림슈퍼<NA><NA>김선옥2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업188841.553358449381.980698식품자동판매기영업01기타지도<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631400003140000-112-1984-0000519840807<NA>3폐업2폐업20070321<NA><NA><NA>02<NA>158824서울특별시 양천구 신월동 51-11 서안복음병<NA><NA>김길원2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업184705.403438448358.384142식품자동판매기영업01기타지도<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731400003140000-112-1984-0001019840507<NA>3폐업2폐업19911210<NA><NA><NA>02<NA>158855서울특별시 양천구 신정동 812-0<NA><NA>심완조2001-09-28 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831400003140000-112-1985-0000719850215<NA>3폐업2폐업20000203<NA><NA><NA>02<NA>158841서울특별시 양천구 신월동 550-1<NA><NA>희선상회2000-02-03 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업185927.65252446155.143264식품자동판매기영업10기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931400003140000-112-1986-0000919860411<NA>3폐업2폐업20001113<NA><NA><NA>02 7251408<NA>158861서울특별시 양천구 신정동 1029-14<NA><NA>산수갑산내2000-11-13 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업187147.122566446555.544194식품자동판매기영업01기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
259531400003140000-112-2024-000082024-02-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.1158-811서울특별시 양천구 목동 615-7서울특별시 양천구 목동중앙북로8나길 24, 1층 (목동)7950데이롱카페 목동깨비시장점2024-02-26 10:32:10I2023-12-01 22:08:00.0식품자동판매기영업187933.347617449502.116638<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
259631400003140000-112-2024-000092024-03-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3158-823서울특별시 양천구 신월동 45-7서울특별시 양천구 남부순환로 338, 1층 (신월동)7909지에스25 신월기쁨점2024-03-20 14:08:14I2023-12-02 22:02:00.0식품자동판매기영업184672.62285448273.098689<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
259731400003140000-112-2024-000102024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3158-865서울특별시 양천구 신정동 1282 푸른마을 1단지아파트서울특별시 양천구 신정로7길 70, 지하105호~지하107호 (신정동, 푸른마을 1단지아파트)8048지에스(GS)25 신정푸른마을점2024-03-21 17:50:12I2023-12-02 22:03:00.0식품자동판매기영업185451.540644445616.763199<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
259831400003140000-112-2024-000112024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3158-852서울특별시 양천구 신정동 295-4서울특별시 양천구 신목로 25, 1층 (신정동)8017지에스(GS)25 신정사랑점2024-03-22 15:18:38I2023-12-02 22:04:00.0식품자동판매기영업188827.890646446169.555331<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
259931400003140000-112-2024-000122024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.13158-857서울특별시 양천구 신정동 909-14서울특별시 양천구 은행정로 73, 1층 (신정동)7944871113 커피무카2024-03-29 13:54:32I2023-12-02 21:01:00.0식품자동판매기영업187449.841428447122.523897<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260031400003140000-112-2024-000132024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.4158-070서울특별시 양천구 신정동 1322-7서울특별시 양천구 신정이펜1로 90, 1층 102호 (신정동)8045위닝무인카페2024-04-02 17:54:34I2023-12-04 00:04:00.0식품자동판매기영업184817.116669445825.399064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260131400003140000-112-2024-000142024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.0158-815서울특별시 양천구 목동 736-18서울특별시 양천구 목동중앙남로 28, 1층 일부호 (목동)7960카인드카페(KIND CAFE)2024-04-09 17:05:39I2023-12-03 23:01:00.0식품자동판매기영업188209.772444448256.874746<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260231400003140000-112-2024-000152024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>39.4158-865서울특별시 양천구 신정동 1289 대림프라자 105호서울특별시 양천구 신정로13길 22, 대림프라자 105호 (신정동)8080데이롱카페 신정점2024-04-24 15:02:35I2023-12-03 22:07:00.0식품자동판매기영업186064.682339445479.209299<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260331400003140000-112-2024-000162024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3158-816서울특별시 양천구 목동 751-2 해피하우스서울특별시 양천구 목동중앙본로 26, 해피하우스 1층 (목동)7976지에스(GS)25 목동고목점2024-04-30 11:00:15I2023-12-05 00:02:00.0식품자동판매기영업188466.125047448535.743636<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
260431400003140000-112-2024-000172024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3158-724서울특별시 양천구 목동 961 현대하이페리온2 205동 122호서울특별시 양천구 오목로 300, 205동 122호 (목동, 현대하이페리온2)8004지에스(GS)25 목동현대2024-05-03 16:07:23I2023-12-05 00:05:00.0식품자동판매기영업188431.286329446909.365904<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>