Overview

Dataset statistics

Number of variables44
Number of observations2859
Missing cells29134
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18232/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (65.7%)Imbalance
영업상태명 is highly imbalanced (65.7%)Imbalance
상세영업상태코드 is highly imbalanced (65.7%)Imbalance
상세영업상태명 is highly imbalanced (65.7%)Imbalance
데이터갱신구분 is highly imbalanced (60.5%)Imbalance
위생업태명 is highly imbalanced (76.3%)Imbalance
영업장주변구분명 is highly imbalanced (63.1%)Imbalance
급수시설구분명 is highly imbalanced (98.8%)Imbalance
총인원 is highly imbalanced (93.5%)Imbalance
건물소유구분명 is highly imbalanced (57.9%)Imbalance
보증액 is highly imbalanced (50.6%)Imbalance
월세액 is highly imbalanced (50.6%)Imbalance
인허가취소일자 has 2859 (100.0%) missing valuesMissing
폐업일자 has 183 (6.4%) missing valuesMissing
휴업시작일자 has 2859 (100.0%) missing valuesMissing
휴업종료일자 has 2859 (100.0%) missing valuesMissing
재개업일자 has 2859 (100.0%) missing valuesMissing
전화번호 has 517 (18.1%) missing valuesMissing
소재지면적 has 2436 (85.2%) missing valuesMissing
도로명주소 has 2375 (83.1%) missing valuesMissing
도로명우편번호 has 2388 (83.5%) missing valuesMissing
좌표정보(X) has 499 (17.5%) missing valuesMissing
좌표정보(Y) has 499 (17.5%) missing valuesMissing
다중이용업소여부 has 111 (3.9%) missing valuesMissing
시설총규모 has 111 (3.9%) missing valuesMissing
전통업소지정번호 has 2859 (100.0%) missing valuesMissing
전통업소주된음식 has 2859 (100.0%) missing valuesMissing
홈페이지 has 2859 (100.0%) missing valuesMissing
시설총규모 is highly skewed (γ1 = 27.3119713)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 220 (7.7%) zerosZeros
시설총규모 has 2633 (92.1%) zerosZeros

Reproduction

Analysis started2024-05-11 01:49:51.211547
Analysis finished2024-05-11 01:49:55.171752
Duration3.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
3050000
2859 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 2859
100.0%

Length

2024-05-11T01:49:55.471070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:49:55.925220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 2859
100.0%

관리번호
Text

UNIQUE 

Distinct2859
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
2024-05-11T01:49:56.522409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters62898
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

Unique2859 ?
Unique (%)100.0%

Sample

1st row3050000-112-1901-01025
2nd row3050000-112-1981-00410
3rd row3050000-112-1982-00230
4th row3050000-112-1982-00231
5th row3050000-112-1982-00232
ValueCountFrequency (%)
3050000-112-1901-01025 1
 
< 0.1%
3050000-112-2001-01916 1
 
< 0.1%
3050000-112-2001-01897 1
 
< 0.1%
3050000-112-2001-01898 1
 
< 0.1%
3050000-112-2001-01907 1
 
< 0.1%
3050000-112-2001-01899 1
 
< 0.1%
3050000-112-2001-01900 1
 
< 0.1%
3050000-112-2001-01901 1
 
< 0.1%
3050000-112-2001-01902 1
 
< 0.1%
3050000-112-2001-01903 1
 
< 0.1%
Other values (2849) 2849
99.7%
2024-05-11T01:49:57.844145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22987
36.5%
1 10140
16.1%
- 8577
 
13.6%
2 5376
 
8.5%
9 4488
 
7.1%
3 3925
 
6.2%
5 3784
 
6.0%
8 1121
 
1.8%
4 886
 
1.4%
6 812
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54321
86.4%
Dash Punctuation 8577
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22987
42.3%
1 10140
18.7%
2 5376
 
9.9%
9 4488
 
8.3%
3 3925
 
7.2%
5 3784
 
7.0%
8 1121
 
2.1%
4 886
 
1.6%
6 812
 
1.5%
7 802
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 8577
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62898
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22987
36.5%
1 10140
16.1%
- 8577
 
13.6%
2 5376
 
8.5%
9 4488
 
7.1%
3 3925
 
6.2%
5 3784
 
6.0%
8 1121
 
1.8%
4 886
 
1.4%
6 812
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62898
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22987
36.5%
1 10140
16.1%
- 8577
 
13.6%
2 5376
 
8.5%
9 4488
 
7.1%
3 3925
 
6.2%
5 3784
 
6.0%
8 1121
 
1.8%
4 886
 
1.4%
6 812
 
1.3%

인허가일자
Date

Distinct1335
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
Minimum1901-09-28 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T01:49:58.778620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:49:59.446000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
3
2676 
1
 
183

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 2676
93.6%
1 183
 
6.4%

Length

2024-05-11T01:50:00.154893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:00.615228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2676
93.6%
1 183
 
6.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
폐업
2676 
영업/정상
 
183

Length

Max length5
Median length2
Mean length2.1920252
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2676
93.6%
영업/정상 183
 
6.4%

Length

2024-05-11T01:50:01.168353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:01.510110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2676
93.6%
영업/정상 183
 
6.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
2
2676 
1
 
183

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 2676
93.6%
1 183
 
6.4%

Length

2024-05-11T01:50:01.833488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:02.264724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2676
93.6%
1 183
 
6.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
폐업
2676 
영업
 
183

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 2676
93.6%
영업 183
 
6.4%

Length

2024-05-11T01:50:02.616468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:02.911454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2676
93.6%
영업 183
 
6.4%

폐업일자
Date

MISSING 

Distinct1569
Distinct (%)58.6%
Missing183
Missing (%)6.4%
Memory size22.5 KiB
Minimum1990-11-24 00:00:00
Maximum2024-05-03 00:00:00
2024-05-11T01:50:03.330561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:50:03.884502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

전화번호
Text

MISSING 

Distinct1186
Distinct (%)50.6%
Missing517
Missing (%)18.1%
Memory size22.5 KiB
2024-05-11T01:50:04.884758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.7433817
Min length2

Characters and Unicode

Total characters15793
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

Unique1128 ?
Unique (%)48.2%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 1603
52.9%
0200000000 82
 
2.7%
9607472 23
 
0.8%
4166416 12
 
0.4%
9225578 7
 
0.2%
9669856 6
 
0.2%
9204310 6
 
0.2%
0222102724 5
 
0.2%
0226308800 4
 
0.1%
6115245 4
 
0.1%
Other values (1208) 1278
42.2%
2024-05-11T01:50:06.450010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4326
27.4%
0 3697
23.4%
9 1187
 
7.5%
6 1094
 
6.9%
4 1066
 
6.7%
1 894
 
5.7%
5 796
 
5.0%
737
 
4.7%
7 718
 
4.5%
3 671
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15056
95.3%
Space Separator 737
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4326
28.7%
0 3697
24.6%
9 1187
 
7.9%
6 1094
 
7.3%
4 1066
 
7.1%
1 894
 
5.9%
5 796
 
5.3%
7 718
 
4.8%
3 671
 
4.5%
8 607
 
4.0%
Space Separator
ValueCountFrequency (%)
737
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4326
27.4%
0 3697
23.4%
9 1187
 
7.5%
6 1094
 
6.9%
4 1066
 
6.7%
1 894
 
5.7%
5 796
 
5.0%
737
 
4.7%
7 718
 
4.5%
3 671
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4326
27.4%
0 3697
23.4%
9 1187
 
7.5%
6 1094
 
6.9%
4 1066
 
6.7%
1 894
 
5.7%
5 796
 
5.0%
737
 
4.7%
7 718
 
4.5%
3 671
 
4.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct47
Distinct (%)11.1%
Missing2436
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean3.5227187
Minimum0
Maximum85
Zeros220
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size25.3 KiB
2024-05-11T01:50:07.048283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.3
95-th percentile22.135
Maximum85
Range85
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation9.045155
Coefficient of variation (CV)2.5676632
Kurtosis24.535924
Mean3.5227187
Median Absolute Deviation (MAD)0
Skewness4.4269656
Sum1490.11
Variance81.814829
MonotonicityNot monotonic
2024-05-11T01:50:07.676868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 220
 
7.7%
3.3 59
 
2.1%
1.0 52
 
1.8%
2.0 14
 
0.5%
1.5 13
 
0.5%
6.6 10
 
0.3%
3.6 6
 
0.2%
3.0 3
 
0.1%
33.0 3
 
0.1%
23.0 3
 
0.1%
Other values (37) 40
 
1.4%
(Missing) 2436
85.2%
ValueCountFrequency (%)
0.0 220
7.7%
1.0 52
 
1.8%
1.5 13
 
0.5%
2.0 14
 
0.5%
2.4 2
 
0.1%
3.0 3
 
0.1%
3.11 1
 
< 0.1%
3.3 59
 
2.1%
3.5 1
 
< 0.1%
3.6 6
 
0.2%
ValueCountFrequency (%)
85.0 1
< 0.1%
56.38 1
< 0.1%
52.98 1
< 0.1%
46.48 1
< 0.1%
45.0 1
< 0.1%
41.31 1
< 0.1%
40.0 1
< 0.1%
39.6 1
< 0.1%
34.0 1
< 0.1%
33.41 1
< 0.1%

소재지우편번호
Text

Distinct142
Distinct (%)5.0%
Missing1
Missing (%)< 0.1%
Memory size22.5 KiB
2024-05-11T01:50:08.410243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0290413
Min length6

Characters and Unicode

Total characters17231
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 (%)1.2%

Sample

1st row130876
2nd row130874
3rd row130872
4th row130872
5th row130872
ValueCountFrequency (%)
130872 137
 
4.8%
130851 127
 
4.4%
130805 98
 
3.4%
130867 93
 
3.3%
130810 81
 
2.8%
130811 80
 
2.8%
130080 76
 
2.7%
130876 74
 
2.6%
130837 71
 
2.5%
130840 69
 
2.4%
Other values (132) 1952
68.3%
2024-05-11T01:50:10.204445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3861
22.4%
1 3576
20.8%
3 3348
19.4%
8 2989
17.3%
7 719
 
4.2%
4 669
 
3.9%
2 616
 
3.6%
6 606
 
3.5%
5 571
 
3.3%
9 193
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17148
99.5%
Dash Punctuation 83
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3861
22.5%
1 3576
20.9%
3 3348
19.5%
8 2989
17.4%
7 719
 
4.2%
4 669
 
3.9%
2 616
 
3.6%
6 606
 
3.5%
5 571
 
3.3%
9 193
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17231
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3861
22.4%
1 3576
20.8%
3 3348
19.4%
8 2989
17.3%
7 719
 
4.2%
4 669
 
3.9%
2 616
 
3.6%
6 606
 
3.5%
5 571
 
3.3%
9 193
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3861
22.4%
1 3576
20.8%
3 3348
19.4%
8 2989
17.3%
7 719
 
4.2%
4 669
 
3.9%
2 616
 
3.6%
6 606
 
3.5%
5 571
 
3.3%
9 193
 
1.1%

지번주소
Text

Distinct2316
Distinct (%)81.0%
Missing1
Missing (%)< 0.1%
Memory size22.5 KiB
2024-05-11T01:50:11.333067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length23.927222
Min length17

Characters and Unicode

Total characters68384
Distinct characters319
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

Unique2034 ?
Unique (%)71.2%

Sample

1st row서울특별시 동대문구 휘경동 191-5
2nd row서울특별시 동대문구 휘경동 29-1 (망우로194)
3rd row서울특별시 동대문구 회기동 1-0
4th row서울특별시 동대문구 회기동 1-0
5th row서울특별시 동대문구 회기동 1-0
ValueCountFrequency (%)
서울특별시 2858
23.0%
동대문구 2858
23.0%
장안동 563
 
4.5%
전농동 361
 
2.9%
답십리동 359
 
2.9%
이문동 282
 
2.3%
휘경동 247
 
2.0%
신설동 246
 
2.0%
용두동 225
 
1.8%
제기동 215
 
1.7%
Other values (2616) 4212
33.9%
2024-05-11T01:50:13.057019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12318
18.0%
동 5806
 
8.5%
문 3167
 
4.6%
대 2946
 
4.3%
시 2886
 
4.2%
서 2879
 
4.2%
구 2869
 
4.2%
울 2867
 
4.2%
별 2859
 
4.2%
특 2858
 
4.2%
Other values (309) 26929
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38508
56.3%
Decimal Number 13566
 
19.8%
Space Separator 12318
 
18.0%
Dash Punctuation 2741
 
4.0%
Open Punctuation 600
 
0.9%
Close Punctuation 600
 
0.9%
Uppercase Letter 25
 
< 0.1%
Other Punctuation 22
 
< 0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5806
15.1%
문 3167
 
8.2%
대 2946
 
7.7%
시 2886
 
7.5%
서 2879
 
7.5%
구 2869
 
7.5%
울 2867
 
7.4%
별 2859
 
7.4%
특 2858
 
7.4%
장 660
 
1.7%
Other values (283) 8711
22.6%
Decimal Number
ValueCountFrequency (%)
1 2615
19.3%
2 1814
13.4%
3 1585
11.7%
4 1310
9.7%
0 1244
9.2%
5 1118
8.2%
6 1094
8.1%
9 954
 
7.0%
7 940
 
6.9%
8 892
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
S 7
28.0%
K 7
28.0%
A 5
20.0%
B 3
12.0%
C 1
 
4.0%
T 1
 
4.0%
P 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 20
90.9%
@ 1
 
4.5%
. 1
 
4.5%
Space Separator
ValueCountFrequency (%)
12318
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2741
100.0%
Open Punctuation
ValueCountFrequency (%)
( 600
100.0%
Close Punctuation
ValueCountFrequency (%)
) 600
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38508
56.3%
Common 29849
43.6%
Latin 27
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5806
15.1%
문 3167
 
8.2%
대 2946
 
7.7%
시 2886
 
7.5%
서 2879
 
7.5%
구 2869
 
7.5%
울 2867
 
7.4%
별 2859
 
7.4%
특 2858
 
7.4%
장 660
 
1.7%
Other values (283) 8711
22.6%
Common
ValueCountFrequency (%)
12318
41.3%
- 2741
 
9.2%
1 2615
 
8.8%
2 1814
 
6.1%
3 1585
 
5.3%
4 1310
 
4.4%
0 1244
 
4.2%
5 1118
 
3.7%
6 1094
 
3.7%
9 954
 
3.2%
Other values (8) 3056
 
10.2%
Latin
ValueCountFrequency (%)
S 7
25.9%
K 7
25.9%
A 5
18.5%
B 3
11.1%
e 2
 
7.4%
C 1
 
3.7%
T 1
 
3.7%
P 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38508
56.3%
ASCII 29876
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12318
41.2%
- 2741
 
9.2%
1 2615
 
8.8%
2 1814
 
6.1%
3 1585
 
5.3%
4 1310
 
4.4%
0 1244
 
4.2%
5 1118
 
3.7%
6 1094
 
3.7%
9 954
 
3.2%
Other values (16) 3083
 
10.3%
Hangul
ValueCountFrequency (%)
동 5806
15.1%
문 3167
 
8.2%
대 2946
 
7.7%
시 2886
 
7.5%
서 2879
 
7.5%
구 2869
 
7.5%
울 2867
 
7.4%
별 2859
 
7.4%
특 2858
 
7.4%
장 660
 
1.7%
Other values (283) 8711
22.6%

도로명주소
Text

MISSING 

Distinct473
Distinct (%)97.7%
Missing2375
Missing (%)83.1%
Memory size22.5 KiB
2024-05-11T01:50:13.995992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length33.497934
Min length23

Characters and Unicode

Total characters16213
Distinct characters253
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

Unique463 ?
Unique (%)95.7%

Sample

1st row서울특별시 동대문구 왕산로 205 (청량리동,(망우로1))
2nd row서울특별시 동대문구 회기로 44 (청량리동,(회기로46))
3rd row서울특별시 동대문구 왕산로 180 (전농동,(왕산로318))
4th row서울특별시 동대문구 전농로15길 42 (전농동,(부군당4길12))
5th row서울특별시 동대문구 한천로14길 87 (장안동,(장한로57))
ValueCountFrequency (%)
서울특별시 484
 
16.9%
동대문구 484
 
16.9%
1층 164
 
5.7%
장안동 54
 
1.9%
전농동 48
 
1.7%
왕산로 37
 
1.3%
용두동 34
 
1.2%
답십리동 33
 
1.2%
이문동 33
 
1.2%
제기동 26
 
0.9%
Other values (745) 1463
51.2%
2024-05-11T01:50:15.691275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2376
 
14.7%
동 1034
 
6.4%
1 705
 
4.3%
) 647
 
4.0%
( 647
 
4.0%
대 596
 
3.7%
문 574
 
3.5%
로 540
 
3.3%
시 530
 
3.3%
서 514
 
3.2%
Other values (243) 8050
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9589
59.1%
Decimal Number 2386
 
14.7%
Space Separator 2376
 
14.7%
Close Punctuation 647
 
4.0%
Open Punctuation 647
 
4.0%
Other Punctuation 472
 
2.9%
Dash Punctuation 71
 
0.4%
Uppercase Letter 22
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1034
 
10.8%
대 596
 
6.2%
문 574
 
6.0%
로 540
 
5.6%
시 530
 
5.5%
서 514
 
5.4%
울 508
 
5.3%
구 490
 
5.1%
별 484
 
5.0%
특 484
 
5.0%
Other values (218) 3835
40.0%
Decimal Number
ValueCountFrequency (%)
1 705
29.5%
2 315
13.2%
3 253
 
10.6%
4 190
 
8.0%
5 174
 
7.3%
0 162
 
6.8%
6 162
 
6.8%
7 153
 
6.4%
8 150
 
6.3%
9 122
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S 7
31.8%
K 6
27.3%
B 2
 
9.1%
C 2
 
9.1%
U 2
 
9.1%
G 1
 
4.5%
W 1
 
4.5%
D 1
 
4.5%
Space Separator
ValueCountFrequency (%)
2376
100.0%
Close Punctuation
ValueCountFrequency (%)
) 647
100.0%
Open Punctuation
ValueCountFrequency (%)
( 647
100.0%
Other Punctuation
ValueCountFrequency (%)
, 472
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9589
59.1%
Common 6600
40.7%
Latin 24
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1034
 
10.8%
대 596
 
6.2%
문 574
 
6.0%
로 540
 
5.6%
시 530
 
5.5%
서 514
 
5.4%
울 508
 
5.3%
구 490
 
5.1%
별 484
 
5.0%
특 484
 
5.0%
Other values (218) 3835
40.0%
Common
ValueCountFrequency (%)
2376
36.0%
1 705
 
10.7%
) 647
 
9.8%
( 647
 
9.8%
, 472
 
7.2%
2 315
 
4.8%
3 253
 
3.8%
4 190
 
2.9%
5 174
 
2.6%
0 162
 
2.5%
Other values (6) 659
 
10.0%
Latin
ValueCountFrequency (%)
S 7
29.2%
K 6
25.0%
B 2
 
8.3%
C 2
 
8.3%
U 2
 
8.3%
e 2
 
8.3%
G 1
 
4.2%
W 1
 
4.2%
D 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9589
59.1%
ASCII 6624
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2376
35.9%
1 705
 
10.6%
) 647
 
9.8%
( 647
 
9.8%
, 472
 
7.1%
2 315
 
4.8%
3 253
 
3.8%
4 190
 
2.9%
5 174
 
2.6%
0 162
 
2.4%
Other values (15) 683
 
10.3%
Hangul
ValueCountFrequency (%)
동 1034
 
10.8%
대 596
 
6.2%
문 574
 
6.0%
로 540
 
5.6%
시 530
 
5.5%
서 514
 
5.4%
울 508
 
5.3%
구 490
 
5.1%
별 484
 
5.0%
특 484
 
5.0%
Other values (218) 3835
40.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct180
Distinct (%)38.2%
Missing2388
Missing (%)83.5%
Infinite0
Infinite (%)0.0%
Mean2537.155
Minimum2400
Maximum2646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.3 KiB
2024-05-11T01:50:16.355834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2422
Q12475
median2551
Q32587.5
95-th percentile2637
Maximum2646
Range246
Interquartile range (IQR)112.5

Descriptive statistics

Standard deviation68.733802
Coefficient of variation (CV)0.027090896
Kurtosis-1.1054285
Mean2537.155
Median Absolute Deviation (MAD)54
Skewness-0.23461373
Sum1195000
Variance4724.3355
MonotonicityNot monotonic
2024-05-11T01:50:16.892977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2582 10
 
0.3%
2586 10
 
0.3%
2559 8
 
0.3%
2580 7
 
0.2%
2532 7
 
0.2%
2584 7
 
0.2%
2558 7
 
0.2%
2637 7
 
0.2%
2488 6
 
0.2%
2555 6
 
0.2%
Other values (170) 396
 
13.9%
(Missing) 2388
83.5%
ValueCountFrequency (%)
2400 1
 
< 0.1%
2401 1
 
< 0.1%
2402 1
 
< 0.1%
2404 1
 
< 0.1%
2405 1
 
< 0.1%
2406 2
0.1%
2407 2
0.1%
2408 2
0.1%
2409 3
0.1%
2410 2
0.1%
ValueCountFrequency (%)
2646 3
0.1%
2645 5
0.2%
2644 5
0.2%
2643 2
 
0.1%
2641 2
 
0.1%
2640 1
 
< 0.1%
2639 3
0.1%
2637 7
0.2%
2636 5
0.2%
2635 1
 
< 0.1%

사업장명
Text

Distinct2393
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
2024-05-11T01:50:17.938296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length4.9590766
Min length1

Characters and Unicode

Total characters14178
Distinct characters636
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2188 ?
Unique (%)76.5%

Sample

1st row채원볼링장
2nd row김경자
3rd row박순영
4th row박순영
5th row박순영
ValueCountFrequency (%)
박순영 34
 
1.1%
신강벤딩 24
 
0.8%
허석 24
 
0.8%
박창용 22
 
0.7%
정한주 20
 
0.7%
심완조 17
 
0.6%
씨유(cu 15
 
0.5%
재)홍익회 13
 
0.4%
김영관 11
 
0.4%
씨유 10
 
0.3%
Other values (2437) 2811
93.7%
2024-05-11T01:50:19.378046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 268
 
1.9%
이 251
 
1.8%
동 247
 
1.7%
식 221
 
1.6%
퍼 220
 
1.6%
슈 208
 
1.5%
대 203
 
1.4%
장 191
 
1.3%
리 190
 
1.3%
영 171
 
1.2%
Other values (626) 12008
84.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13187
93.0%
Decimal Number 271
 
1.9%
Uppercase Letter 251
 
1.8%
Space Separator 142
 
1.0%
Close Punctuation 135
 
1.0%
Open Punctuation 135
 
1.0%
Lowercase Letter 42
 
0.3%
Other Punctuation 8
 
0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 268
 
2.0%
이 251
 
1.9%
동 247
 
1.9%
식 221
 
1.7%
퍼 220
 
1.7%
슈 208
 
1.6%
대 203
 
1.5%
장 191
 
1.4%
리 190
 
1.4%
영 171
 
1.3%
Other values (575) 11017
83.5%
Uppercase Letter
ValueCountFrequency (%)
C 59
23.5%
S 43
17.1%
U 40
15.9%
G 35
13.9%
P 16
 
6.4%
K 8
 
3.2%
A 7
 
2.8%
F 6
 
2.4%
N 6
 
2.4%
T 4
 
1.6%
Other values (12) 27
10.8%
Lowercase Letter
ValueCountFrequency (%)
e 7
16.7%
c 6
14.3%
o 6
14.3%
f 6
14.3%
p 3
7.1%
s 3
7.1%
a 2
 
4.8%
r 2
 
4.8%
u 2
 
4.8%
h 2
 
4.8%
Other values (3) 3
7.1%
Decimal Number
ValueCountFrequency (%)
2 102
37.6%
5 63
23.2%
1 40
 
14.8%
4 30
 
11.1%
0 14
 
5.2%
3 9
 
3.3%
9 5
 
1.8%
6 4
 
1.5%
8 4
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 5
62.5%
, 2
 
25.0%
? 1
 
12.5%
Space Separator
ValueCountFrequency (%)
142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13187
93.0%
Common 698
 
4.9%
Latin 293
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 268
 
2.0%
이 251
 
1.9%
동 247
 
1.9%
식 221
 
1.7%
퍼 220
 
1.7%
슈 208
 
1.6%
대 203
 
1.5%
장 191
 
1.4%
리 190
 
1.4%
영 171
 
1.3%
Other values (575) 11017
83.5%
Latin
ValueCountFrequency (%)
C 59
20.1%
S 43
14.7%
U 40
13.7%
G 35
11.9%
P 16
 
5.5%
K 8
 
2.7%
A 7
 
2.4%
e 7
 
2.4%
c 6
 
2.0%
o 6
 
2.0%
Other values (25) 66
22.5%
Common
ValueCountFrequency (%)
142
20.3%
) 135
19.3%
( 135
19.3%
2 102
14.6%
5 63
9.0%
1 40
 
5.7%
4 30
 
4.3%
0 14
 
2.0%
3 9
 
1.3%
- 7
 
1.0%
Other values (6) 21
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13187
93.0%
ASCII 991
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 268
 
2.0%
이 251
 
1.9%
동 247
 
1.9%
식 221
 
1.7%
퍼 220
 
1.7%
슈 208
 
1.6%
대 203
 
1.5%
장 191
 
1.4%
리 190
 
1.4%
영 171
 
1.3%
Other values (575) 11017
83.5%
ASCII
ValueCountFrequency (%)
142
14.3%
) 135
13.6%
( 135
13.6%
2 102
10.3%
5 63
 
6.4%
C 59
 
6.0%
S 43
 
4.3%
1 40
 
4.0%
U 40
 
4.0%
G 35
 
3.5%
Other values (41) 197
19.9%

최종수정일자
Date

Distinct1318
Distinct (%)46.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
Minimum1999-01-20 00:00:00
Maximum2024-05-03 13:31:35
2024-05-11T01:50:20.060640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:50:20.669396image/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 size22.5 KiB
I
2636 
U
 
223

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2636
92.2%
U 223
 
7.8%

Length

2024-05-11T01:50:21.298021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:21.611332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2636
92.2%
u 223
 
7.8%

데이터갱신일자
Date

Distinct209
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T01:50:21.991906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:50:22.503101image/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 size22.5 KiB
식품자동판매기영업
2859 

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 2859
100.0%

Length

2024-05-11T01:50:22.931280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:23.234565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2859
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1683
Distinct (%)71.3%
Missing499
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean204634.61
Minimum201991.59
Maximum206687.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.3 KiB
2024-05-11T01:50:23.571198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201991.59
5-th percentile202223.24
Q1203785.43
median204916.69
Q3205677.05
95-th percentile206300.23
Maximum206687.93
Range4696.3425
Interquartile range (IQR)1891.6135

Descriptive statistics

Standard deviation1242.8138
Coefficient of variation (CV)0.0060733313
Kurtosis-0.76633977
Mean204634.61
Median Absolute Deviation (MAD)899.11298
Skewness-0.50832687
Sum4.8293769 × 108
Variance1544586.2
MonotonicityNot monotonic
2024-05-11T01:50:24.022006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203996.013917877 28
 
1.0%
204190.10878253 18
 
0.6%
204161.668545626 17
 
0.6%
204089.817117361 14
 
0.5%
205622.517700168 13
 
0.5%
202132.961071614 13
 
0.5%
202319.532216101 9
 
0.3%
205872.880792458 9
 
0.3%
205271.704936121 9
 
0.3%
203075.098504907 8
 
0.3%
Other values (1673) 2222
77.7%
(Missing) 499
 
17.5%
ValueCountFrequency (%)
201991.588408047 1
 
< 0.1%
202010.550405076 1
 
< 0.1%
202015.405337661 1
 
< 0.1%
202022.650035503 2
0.1%
202023.921749857 1
 
< 0.1%
202024.479054844 3
0.1%
202026.286928788 2
0.1%
202028.666639027 1
 
< 0.1%
202033.22548938 2
0.1%
202034.733564967 2
0.1%
ValueCountFrequency (%)
206687.930864017 1
 
< 0.1%
206685.867361931 2
 
0.1%
206676.04734862 1
 
< 0.1%
206630.901669352 2
 
0.1%
206618.082278385 1
 
< 0.1%
206607.014952243 1
 
< 0.1%
206590.046202018 5
0.2%
206574.561496753 1
 
< 0.1%
206573.59398246 2
 
0.1%
206546.935298263 2
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1682
Distinct (%)71.3%
Missing499
Missing (%)17.5%
Infinite0
Infinite (%)0.0%
Mean452985.41
Minimum450987.05
Maximum455917.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.3 KiB
2024-05-11T01:50:24.593882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450987.05
5-th percentile451335.47
Q1452190.52
median452831.53
Q3453772.06
95-th percentile455013.82
Maximum455917.55
Range4930.5042
Interquartile range (IQR)1581.5367

Descriptive statistics

Standard deviation1108.3953
Coefficient of variation (CV)0.0024468676
Kurtosis-0.40772021
Mean452985.41
Median Absolute Deviation (MAD)746.42792
Skewness0.46159789
Sum1.0690456 × 109
Variance1228540.2
MonotonicityNot monotonic
2024-05-11T01:50:25.090420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453058.665828669 28
 
1.0%
453415.795068163 18
 
0.6%
453096.477725918 17
 
0.6%
453314.135663101 14
 
0.5%
454115.432829144 13
 
0.5%
452712.645095691 13
 
0.5%
452310.545623253 9
 
0.3%
455497.909359708 9
 
0.3%
452706.897879436 9
 
0.3%
452918.836458244 8
 
0.3%
Other values (1672) 2222
77.7%
(Missing) 499
 
17.5%
ValueCountFrequency (%)
450987.048392613 1
< 0.1%
450990.782258934 2
0.1%
450998.638678935 1
< 0.1%
451011.194201757 1
< 0.1%
451017.179310496 1
< 0.1%
451020.696425047 2
0.1%
451025.902075739 1
< 0.1%
451031.569748553 2
0.1%
451052.826209824 1
< 0.1%
451053.76563095 2
0.1%
ValueCountFrequency (%)
455917.552544887 2
0.1%
455899.982370316 2
0.1%
455896.598021847 4
0.1%
455876.231869346 1
 
< 0.1%
455846.122930171 1
 
< 0.1%
455813.713540339 1
 
< 0.1%
455758.767536948 2
0.1%
455757.377714057 1
 
< 0.1%
455750.85927464 1
 
< 0.1%
455746.103581101 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
식품자동판매기영업
2748 
<NA>
 
111

Length

Max length9
Median length9
Mean length8.8058762
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 2748
96.1%
<NA> 111
 
3.9%

Length

2024-05-11T01:50:25.688563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:26.234891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2748
96.1%
na 111
 
3.9%

남성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
0
1863 
<NA>
994 
60
 
2

Length

Max length4
Median length1
Mean length2.0437216
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1863
65.2%
<NA> 994
34.8%
60 2
 
0.1%

Length

2024-05-11T01:50:27.026075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:27.407151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1863
65.2%
na 994
34.8%
60 2
 
0.1%

여성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
0
1863 
<NA>
994 
60
 
2

Length

Max length4
Median length1
Mean length2.0437216
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1863
65.2%
<NA> 994
34.8%
60 2
 
0.1%

Length

2024-05-11T01:50:27.915805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:28.313355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1863
65.2%
na 994
34.8%
60 2
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
기타
1916 
<NA>
931 
결혼예식장주변
 
5
학교정화(상대)
 
5
아파트지역
 
1

Length

Max length8
Median length2
Mean length2.6736621
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1916
67.0%
<NA> 931
32.6%
결혼예식장주변 5
 
0.2%
학교정화(상대) 5
 
0.2%
아파트지역 1
 
< 0.1%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-05-11T01:50:28.659735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:29.018094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1916
67.0%
na 931
32.6%
결혼예식장주변 5
 
0.2%
학교정화(상대 5
 
0.2%
아파트지역 1
 
< 0.1%
유흥업소밀집지역 1
 
< 0.1%

등급구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
기타
1749 
<NA>
931 
지도
 
156
갑
 
23

Length

Max length4
Median length2
Mean length2.6432319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1749
61.2%
<NA> 931
32.6%
지도 156
 
5.5%
갑 23
 
0.8%

Length

2024-05-11T01:50:29.428450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:29.855176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1749
61.2%
na 931
32.6%
지도 156
 
5.5%
갑 23
 
0.8%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2856 
상수도전용
 
3

Length

Max length5
Median length4
Mean length4.0010493
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> 2856
99.9%
상수도전용 3
 
0.1%

Length

2024-05-11T01:50:30.180919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:30.407347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2856
99.9%
상수도전용 3
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2837 
0
 
22

Length

Max length4
Median length4
Mean length3.976915
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> 2837
99.2%
0 22
 
0.8%

Length

2024-05-11T01:50:30.710750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:30.954150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2837
99.2%
0 22
 
0.8%

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2462 
0
397 

Length

Max length4
Median length4
Mean length3.5834208
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2462
86.1%
0 397
 
13.9%

Length

2024-05-11T01:50:31.230646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:31.512171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
86.1%
0 397
 
13.9%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2462 
0
397 

Length

Max length4
Median length4
Mean length3.5834208
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2462
86.1%
0 397
 
13.9%

Length

2024-05-11T01:50:31.784175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:32.114451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
86.1%
0 397
 
13.9%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2462 
0
397 

Length

Max length4
Median length4
Mean length3.5834208
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2462
86.1%
0 397
 
13.9%

Length

2024-05-11T01:50:32.403560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:32.774402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
86.1%
0 397
 
13.9%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2462 
0
397 

Length

Max length4
Median length4
Mean length3.5834208
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2462
86.1%
0 397
 
13.9%

Length

2024-05-11T01:50:33.135299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:33.459007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2462
86.1%
0 397
 
13.9%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2429 
자가
399 
임대
 
31

Length

Max length4
Median length4
Mean length3.6991955
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> 2429
85.0%
자가 399
 
14.0%
임대 31
 
1.1%

Length

2024-05-11T01:50:33.791768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:34.071636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2429
85.0%
자가 399
 
14.0%
임대 31
 
1.1%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2550 
0
309 

Length

Max length4
Median length4
Mean length3.6757608
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> 2550
89.2%
0 309
 
10.8%

Length

2024-05-11T01:50:34.274105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:34.492281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2550
89.2%
0 309
 
10.8%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size22.5 KiB
<NA>
2550 
0
309 

Length

Max length4
Median length4
Mean length3.6757608
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> 2550
89.2%
0 309
 
10.8%

Length

2024-05-11T01:50:34.849083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:50:35.180539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2550
89.2%
0 309
 
10.8%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing111
Missing (%)3.9%
Memory size5.7 KiB
False
2748 
(Missing)
 
111
ValueCountFrequency (%)
False 2748
96.1%
(Missing) 111
 
3.9%
2024-05-11T01:50:35.445645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct15
Distinct (%)0.5%
Missing111
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean0.12278748
Minimum0
Maximum46.48
Zeros2633
Zeros (%)92.1%
Negative0
Negative (%)0.0%
Memory size25.3 KiB
2024-05-11T01:50:35.663116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum46.48
Range46.48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1676003
Coefficient of variation (CV)9.5091153
Kurtosis972.74339
Mean0.12278748
Median Absolute Deviation (MAD)0
Skewness27.311971
Sum337.42
Variance1.3632905
MonotonicityNot monotonic
2024-05-11T01:50:36.030476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 2633
92.1%
1.0 42
 
1.5%
3.3 25
 
0.9%
2.0 14
 
0.5%
1.5 13
 
0.5%
3.6 6
 
0.2%
6.6 4
 
0.1%
3.0 3
 
0.1%
2.4 2
 
0.1%
46.48 1
 
< 0.1%
Other values (5) 5
 
0.2%
(Missing) 111
 
3.9%
ValueCountFrequency (%)
0.0 2633
92.1%
1.0 42
 
1.5%
1.5 13
 
0.5%
2.0 14
 
0.5%
2.4 2
 
0.1%
3.0 3
 
0.1%
3.3 25
 
0.9%
3.5 1
 
< 0.1%
3.6 6
 
0.2%
4.0 1
 
< 0.1%
ValueCountFrequency (%)
46.48 1
 
< 0.1%
21.0 1
 
< 0.1%
19.64 1
 
< 0.1%
9.0 1
 
< 0.1%
6.6 4
 
0.1%
4.0 1
 
< 0.1%
3.6 6
 
0.2%
3.5 1
 
< 0.1%
3.3 25
0.9%
3.0 3
 
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2859
Missing (%)100.0%
Memory size25.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-112-1901-0102519010928<NA>3폐업2폐업20060321<NA><NA><NA>02<NA>130876서울특별시 동대문구 휘경동 191-5<NA><NA>채원볼링장2006-02-06 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업204977.724964454216.971551식품자동판매기영업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130500003050000-112-1981-0041019811118<NA>3폐업2폐업20100127<NA><NA><NA>02<NA>130874서울특별시 동대문구 휘경동 29-1 (망우로194)<NA><NA>김경자2009-03-25 14:55:49I2018-08-31 23:59:59.0식품자동판매기영업205622.5177454115.432829식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230500003050000-112-1982-0023019821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330500003050000-112-1982-0023119821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430500003050000-112-1982-0023219821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530500003050000-112-1982-0023419821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630500003050000-112-1982-0023519821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730500003050000-112-1982-0023619821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830500003050000-112-1982-0023719821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930500003050000-112-1982-0023819821120<NA>3폐업2폐업19970811<NA><NA><NA>02<NA>130872서울특별시 동대문구 회기동 1-0<NA><NA>박순영2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타지도<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
284930500003050000-112-2024-000112024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-841서울특별시 동대문구 장안동 349-16 유림빌딩서울특별시 동대문구 답십리로72길 114, 유림빌딩 1층 (장안동)2640씨유(CU) 장안래미안 1차점2024-03-04 14:21:20I2023-12-03 00:06:00.0식품자동판매기영업206296.915448451669.713565<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285030500003050000-112-2024-000122024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-867서울특별시 동대문구 청량리동 235-6서울특별시 동대문구 왕산로 239, 1층 134호 (청량리동)2489카페빈2024-03-13 17:01:59I2023-12-02 23:06:00.0식품자동판매기영업204190.108783453415.795068<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285130500003050000-112-2024-000132024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.11130-827서울특별시 동대문구 이문동 189 이문체육센터서울특별시 동대문구 한천로58길 81-49, 이문체육센터 2층 (이문동)2421허잉2024-03-21 15:38:57I2023-12-02 22:03:00.0식품자동판매기영업206024.297322455556.182306<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285230500003050000-112-2024-000142024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA>02157780073.3130-817서울특별시 동대문구 용두동 40-28서울특별시 동대문구 고산자로 393, 1층 (용두동)2566씨유(CU) 뉴용두래미안점2024-03-22 17:16:20I2023-12-02 22:04:00.0식품자동판매기영업203271.183654452510.065863<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285330500003050000-112-2024-000152024-03-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-829서울특별시 동대문구 이문동 264-445서울특별시 동대문구 천장산로 47, 1층 나12, 13호 (이문동)2448씨유(CU) 이문삼성2024-03-26 16:58:54I2023-12-02 22:08:00.0식품자동판매기영업204991.594355455332.294542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285430500003050000-112-2024-000162024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA>02342470106.3130-812서울특별시 동대문구 신설동 102-30서울특별시 동대문구 천호대로 7-6, 1층 (신설동)2582더리터24 신설점2024-04-03 11:34:32I2023-12-04 00:05:00.0식품자동판매기영업202114.759844452554.624414<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285530500003050000-112-2024-000172024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA>070863310573.3130-817서울특별시 동대문구 용두동 39-1 청량리역한양수자인그라시엘서울특별시 동대문구 고산자로32길 78, 지하1층 B167호 (용두동, 청량리역한양수자인그라시엘)2561세라젬 웰파크 청량리점2024-04-04 13:42:08I2023-12-04 00:06:00.0식품자동판매기영업203728.022004452778.965235<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285630500003050000-112-2024-000182024-04-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-827서울특별시 동대문구 이문동 64 쌍용아파트서울특별시 동대문구 한천로58길 47, 상가동 1층 107호 (이문동, 쌍용아파트)2423카페가다2024-04-16 14:23:37I2023-12-03 23:08:00.0식품자동판매기영업205980.772169455275.83595<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285730500003050000-112-2024-000192024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0130-878서울특별시 동대문구 휘경동 268-3서울특별시 동대문구 망우로 62, 1층 (휘경동)2496티타임커피 회기역점2024-04-18 11:19:13I2023-12-03 22:01:00.0식품자동판매기영업205243.536682454114.757493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
285830500003050000-112-2024-000202024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3130-844서울특별시 동대문구 장안동 424-7서울특별시 동대문구 장한로5길 16, 1층 (장안동)2629씨유(CU) 장안지우점2024-04-22 15:46:57I2023-12-03 22:04:00.0식품자동판매기영업205722.737527451359.751072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>