Overview

Dataset statistics

Number of variables44
Number of observations3152
Missing cells35577
Missing cells (%)25.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory377.0 B

Variable types

Categorical18
Text6
DateTime4
Unsupported8
Numeric7
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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18683/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (57.0%)Imbalance
등급구분명 is highly imbalanced (53.0%)Imbalance
총인원 is highly imbalanced (71.4%)Imbalance
본사종업원수 is highly imbalanced (71.2%)Imbalance
공장사무직종업원수 is highly imbalanced (71.2%)Imbalance
공장판매직종업원수 is highly imbalanced (71.2%)Imbalance
공장생산직종업원수 is highly imbalanced (71.2%)Imbalance
보증액 is highly imbalanced (71.2%)Imbalance
월세액 is highly imbalanced (71.2%)Imbalance
다중이용업소여부 is highly imbalanced (95.2%)Imbalance
인허가취소일자 has 3152 (100.0%) missing valuesMissing
폐업일자 has 1005 (31.9%) missing valuesMissing
휴업시작일자 has 3152 (100.0%) missing valuesMissing
휴업종료일자 has 3152 (100.0%) missing valuesMissing
재개업일자 has 3152 (100.0%) missing valuesMissing
전화번호 has 1604 (50.9%) missing valuesMissing
도로명주소 has 1092 (34.6%) missing valuesMissing
도로명우편번호 has 1102 (35.0%) missing valuesMissing
좌표정보(X) has 96 (3.0%) missing valuesMissing
좌표정보(Y) has 96 (3.0%) missing valuesMissing
남성종사자수 has 1981 (62.8%) missing valuesMissing
여성종사자수 has 1965 (62.3%) missing valuesMissing
건물소유구분명 has 3152 (100.0%) missing valuesMissing
다중이용업소여부 has 706 (22.4%) missing valuesMissing
시설총규모 has 706 (22.4%) missing valuesMissing
전통업소지정번호 has 3152 (100.0%) missing valuesMissing
전통업소주된음식 has 3152 (100.0%) missing valuesMissing
홈페이지 has 3152 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 20.10424238)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
건물소유구분명 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
남성종사자수 has 904 (28.7%) zerosZeros
여성종사자수 has 553 (17.5%) zerosZeros

Reproduction

Analysis started2024-05-11 05:38:38.703269
Analysis finished2024-05-11 05:38:41.312168
Duration2.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
3060000
3152 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 3152
100.0%

Length

2024-05-11T14:38:41.417923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:41.909631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 3152
100.0%

관리번호
Text

UNIQUE 

Distinct3152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
2024-05-11T14:38:42.181638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters69344
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

Unique3152 ?
Unique (%)100.0%

Sample

1st row3060000-104-1968-07265
2nd row3060000-104-1968-07587
3rd row3060000-104-1969-07262
4th row3060000-104-1969-07266
5th row3060000-104-1969-07276
ValueCountFrequency (%)
3060000-104-1968-07265 1
 
< 0.1%
3060000-104-2017-00111 1
 
< 0.1%
3060000-104-2017-00123 1
 
< 0.1%
3060000-104-2017-00114 1
 
< 0.1%
3060000-104-2017-00115 1
 
< 0.1%
3060000-104-2017-00116 1
 
< 0.1%
3060000-104-2017-00117 1
 
< 0.1%
3060000-104-2017-00118 1
 
< 0.1%
3060000-104-2017-00119 1
 
< 0.1%
3060000-104-2017-00120 1
 
< 0.1%
Other values (3142) 3142
99.7%
2024-05-11T14:38:42.737496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29837
43.0%
- 9456
 
13.6%
1 7015
 
10.1%
3 4278
 
6.2%
4 4207
 
6.1%
6 4203
 
6.1%
2 4111
 
5.9%
9 2340
 
3.4%
7 1758
 
2.5%
8 1240
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59888
86.4%
Dash Punctuation 9456
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29837
49.8%
1 7015
 
11.7%
3 4278
 
7.1%
4 4207
 
7.0%
6 4203
 
7.0%
2 4111
 
6.9%
9 2340
 
3.9%
7 1758
 
2.9%
8 1240
 
2.1%
5 899
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9456
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69344
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29837
43.0%
- 9456
 
13.6%
1 7015
 
10.1%
3 4278
 
6.2%
4 4207
 
6.1%
6 4203
 
6.1%
2 4111
 
5.9%
9 2340
 
3.4%
7 1758
 
2.5%
8 1240
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29837
43.0%
- 9456
 
13.6%
1 7015
 
10.1%
3 4278
 
6.2%
4 4207
 
6.1%
6 4203
 
6.1%
2 4111
 
5.9%
9 2340
 
3.4%
7 1758
 
2.5%
8 1240
 
1.8%

인허가일자
Date

Distinct2500
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
Minimum1968-05-04 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:38:42.924829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:43.147893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
3
2147 
1
1005 

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 2147
68.1%
1 1005
31.9%

Length

2024-05-11T14:38:43.344240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:43.476047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2147
68.1%
1 1005
31.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
폐업
2147 
영업/정상
1005 

Length

Max length5
Median length2
Mean length2.9565355
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2147
68.1%
영업/정상 1005
31.9%

Length

2024-05-11T14:38:43.623505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:43.780463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2147
68.1%
영업/정상 1005
31.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
2
2147 
1
1005 

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 2147
68.1%
1 1005
31.9%

Length

2024-05-11T14:38:43.995956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:44.205218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2147
68.1%
1 1005
31.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
폐업
2147 
영업
1005 

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 2147
68.1%
영업 1005
31.9%

Length

2024-05-11T14:38:44.422440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:44.632594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2147
68.1%
영업 1005
31.9%

폐업일자
Date

MISSING 

Distinct1784
Distinct (%)83.1%
Missing1005
Missing (%)31.9%
Memory size24.8 KiB
Minimum1988-09-30 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:38:44.932918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:45.192198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

전화번호
Text

MISSING 

Distinct1376
Distinct (%)88.9%
Missing1604
Missing (%)50.9%
Memory size24.8 KiB
2024-05-11T14:38:45.646831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8869509
Min length2

Characters and Unicode

Total characters15305
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

Unique1327 ?
Unique (%)85.7%

Sample

1st row0209736643
2nd row02 4331093
3rd row0204356461
4th row0204330339
5th row0204344977
ValueCountFrequency (%)
02 1162
40.2%
433 30
 
1.0%
434 21
 
0.7%
493 15
 
0.5%
00000 15
 
0.5%
070 15
 
0.5%
437 12
 
0.4%
432 12
 
0.4%
491 11
 
0.4%
435 11
 
0.4%
Other values (1425) 1583
54.8%
2024-05-11T14:38:46.427436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2764
18.1%
2 2546
16.6%
4 1851
12.1%
1642
10.7%
3 1523
10.0%
9 1138
7.4%
7 834
 
5.4%
5 780
 
5.1%
1 778
 
5.1%
8 742
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13663
89.3%
Space Separator 1642
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2764
20.2%
2 2546
18.6%
4 1851
13.5%
3 1523
11.1%
9 1138
8.3%
7 834
 
6.1%
5 780
 
5.7%
1 778
 
5.7%
8 742
 
5.4%
6 707
 
5.2%
Space Separator
ValueCountFrequency (%)
1642
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2764
18.1%
2 2546
16.6%
4 1851
12.1%
1642
10.7%
3 1523
10.0%
9 1138
7.4%
7 834
 
5.4%
5 780
 
5.1%
1 778
 
5.1%
8 742
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2764
18.1%
2 2546
16.6%
4 1851
12.1%
1642
10.7%
3 1523
10.0%
9 1138
7.4%
7 834
 
5.4%
5 780
 
5.1%
1 778
 
5.1%
8 742
 
4.8%

소재지면적
Real number (ℝ)

Distinct1754
Distinct (%)55.8%
Missing6
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean44.967994
Minimum0
Maximum520.47
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:46.683917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q117
median30
Q360.185
95-th percentile125.3
Maximum520.47
Range520.47
Interquartile range (IQR)43.185

Descriptive statistics

Standard deviation45.051508
Coefficient of variation (CV)1.0018572
Kurtosis14.33024
Mean44.967994
Median Absolute Deviation (MAD)18.6
Skewness2.8550548
Sum141469.31
Variance2029.6384
MonotonicityNot monotonic
2024-05-11T14:38:47.024693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 203
 
6.4%
6.6 82
 
2.6%
33.0 56
 
1.8%
30.0 50
 
1.6%
10.0 41
 
1.3%
26.4 33
 
1.0%
9.9 30
 
1.0%
16.5 23
 
0.7%
13.2 20
 
0.6%
20.0 19
 
0.6%
Other values (1744) 2589
82.1%
ValueCountFrequency (%)
0.0 3
0.1%
0.13 1
 
< 0.1%
1.0 2
 
0.1%
1.44 1
 
< 0.1%
1.47 1
 
< 0.1%
1.65 5
0.2%
1.71 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 4
0.1%
2.12 1
 
< 0.1%
ValueCountFrequency (%)
520.47 1
< 0.1%
437.1 1
< 0.1%
396.0 1
< 0.1%
383.44 1
< 0.1%
381.71 1
< 0.1%
359.7 1
< 0.1%
358.87 1
< 0.1%
333.12 1
< 0.1%
321.86 1
< 0.1%
297.52 1
< 0.1%

소재지우편번호
Text

Distinct175
Distinct (%)5.6%
Missing1
Missing (%)< 0.1%
Memory size24.8 KiB
2024-05-11T14:38:47.631106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1459854
Min length6

Characters and Unicode

Total characters19366
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

Unique20 ?
Unique (%)0.6%

Sample

1st row131851
2nd row131861
3rd row131860
4th row131861
5th row131803
ValueCountFrequency (%)
131848 115
 
3.6%
131859 92
 
2.9%
131802 90
 
2.9%
131861 89
 
2.8%
131809 81
 
2.6%
131813 80
 
2.5%
131816 76
 
2.4%
131823 74
 
2.3%
131831 73
 
2.3%
131810 71
 
2.3%
Other values (165) 2310
73.3%
2024-05-11T14:38:48.421733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7274
37.6%
3 3657
18.9%
8 3521
18.2%
2 1006
 
5.2%
0 902
 
4.7%
6 703
 
3.6%
7 636
 
3.3%
5 595
 
3.1%
- 460
 
2.4%
4 321
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18906
97.6%
Dash Punctuation 460
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7274
38.5%
3 3657
19.3%
8 3521
18.6%
2 1006
 
5.3%
0 902
 
4.8%
6 703
 
3.7%
7 636
 
3.4%
5 595
 
3.1%
4 321
 
1.7%
9 291
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19366
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7274
37.6%
3 3657
18.9%
8 3521
18.2%
2 1006
 
5.2%
0 902
 
4.7%
6 703
 
3.6%
7 636
 
3.3%
5 595
 
3.1%
- 460
 
2.4%
4 321
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19366
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7274
37.6%
3 3657
18.9%
8 3521
18.2%
2 1006
 
5.2%
0 902
 
4.7%
6 703
 
3.6%
7 636
 
3.3%
5 595
 
3.1%
- 460
 
2.4%
4 321
 
1.7%

지번주소
Text

Distinct2554
Distinct (%)81.1%
Missing1
Missing (%)< 0.1%
Memory size24.8 KiB
2024-05-11T14:38:48.918115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length23.583307
Min length13

Characters and Unicode

Total characters74311
Distinct characters375
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2167 ?
Unique (%)68.8%

Sample

1st row서울특별시 중랑구 묵동 238-8번지
2nd row서울특별시 중랑구 상봉동 136-6번지
3rd row서울특별시 중랑구 상봉동 108-2번지
4th row서울특별시 중랑구 상봉동 130-130번지
5th row서울특별시 중랑구 망우동 340-22번지
ValueCountFrequency (%)
서울특별시 3150
22.4%
중랑구 3149
22.4%
면목동 1132
 
8.0%
상봉동 515
 
3.7%
망우동 509
 
3.6%
중화동 357
 
2.5%
묵동 351
 
2.5%
신내동 289
 
2.1%
1층 133
 
0.9%
지상1층 105
 
0.7%
Other values (2731) 4386
31.2%
2024-05-11T14:38:49.718184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13289
17.9%
중 3533
 
4.8%
동 3316
 
4.5%
1 3289
 
4.4%
시 3180
 
4.3%
서 3179
 
4.3%
울 3169
 
4.3%
랑 3160
 
4.3%
구 3160
 
4.3%
특 3151
 
4.2%
Other values (365) 31885
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43172
58.1%
Decimal Number 14751
 
19.9%
Space Separator 13289
 
17.9%
Dash Punctuation 2853
 
3.8%
Uppercase Letter 135
 
0.2%
Other Punctuation 56
 
0.1%
Lowercase Letter 32
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Open Punctuation 10
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 3533
 
8.2%
동 3316
 
7.7%
시 3180
 
7.4%
서 3179
 
7.4%
울 3169
 
7.3%
랑 3160
 
7.3%
구 3160
 
7.3%
특 3151
 
7.3%
별 3151
 
7.3%
지 2270
 
5.3%
Other values (313) 11903
27.6%
Uppercase Letter
ValueCountFrequency (%)
B 35
25.9%
A 16
11.9%
S 13
 
9.6%
E 12
 
8.9%
M 8
 
5.9%
Y 7
 
5.2%
T 6
 
4.4%
R 5
 
3.7%
C 5
 
3.7%
H 5
 
3.7%
Other values (11) 23
17.0%
Lowercase Letter
ValueCountFrequency (%)
e 7
21.9%
n 4
12.5%
r 3
9.4%
s 3
9.4%
t 3
9.4%
c 3
9.4%
g 2
 
6.2%
a 2
 
6.2%
k 2
 
6.2%
i 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 3289
22.3%
2 1817
12.3%
3 1568
10.6%
4 1494
10.1%
0 1362
9.2%
5 1292
 
8.8%
6 1251
 
8.5%
7 948
 
6.4%
8 944
 
6.4%
9 786
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 46
82.1%
& 5
 
8.9%
? 4
 
7.1%
@ 1
 
1.8%
Space Separator
ValueCountFrequency (%)
13289
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2853
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43171
58.1%
Common 30972
41.7%
Latin 167
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 3533
 
8.2%
동 3316
 
7.7%
시 3180
 
7.4%
서 3179
 
7.4%
울 3169
 
7.3%
랑 3160
 
7.3%
구 3160
 
7.3%
특 3151
 
7.3%
별 3151
 
7.3%
지 2270
 
5.3%
Other values (312) 11902
27.6%
Latin
ValueCountFrequency (%)
B 35
21.0%
A 16
 
9.6%
S 13
 
7.8%
E 12
 
7.2%
M 8
 
4.8%
e 7
 
4.2%
Y 7
 
4.2%
T 6
 
3.6%
R 5
 
3.0%
C 5
 
3.0%
Other values (23) 53
31.7%
Common
ValueCountFrequency (%)
13289
42.9%
1 3289
 
10.6%
- 2853
 
9.2%
2 1817
 
5.9%
3 1568
 
5.1%
4 1494
 
4.8%
0 1362
 
4.4%
5 1292
 
4.2%
6 1251
 
4.0%
7 948
 
3.1%
Other values (9) 1809
 
5.8%
Han
ValueCountFrequency (%)
休 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43171
58.1%
ASCII 31139
41.9%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13289
42.7%
1 3289
 
10.6%
- 2853
 
9.2%
2 1817
 
5.8%
3 1568
 
5.0%
4 1494
 
4.8%
0 1362
 
4.4%
5 1292
 
4.1%
6 1251
 
4.0%
7 948
 
3.0%
Other values (42) 1976
 
6.3%
Hangul
ValueCountFrequency (%)
중 3533
 
8.2%
동 3316
 
7.7%
시 3180
 
7.4%
서 3179
 
7.4%
울 3169
 
7.3%
랑 3160
 
7.3%
구 3160
 
7.3%
특 3151
 
7.3%
별 3151
 
7.3%
지 2270
 
5.3%
Other values (312) 11902
27.6%
CJK
ValueCountFrequency (%)
休 1
100.0%

도로명주소
Text

MISSING 

Distinct1837
Distinct (%)89.2%
Missing1092
Missing (%)34.6%
Memory size24.8 KiB
2024-05-11T14:38:50.142584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length56
Mean length31.590777
Min length21

Characters and Unicode

Total characters65077
Distinct characters378
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1672 ?
Unique (%)81.2%

Sample

1st row서울특별시 중랑구 동일로163길 7 (묵동)
2nd row서울특별시 중랑구 겸재로18길 3 (면목동)
3rd row서울특별시 중랑구 공릉로 51 (묵동)
4th row서울특별시 중랑구 면목로 262 (면목동)
5th row서울특별시 중랑구 용마공원로 7 (망우동)
ValueCountFrequency (%)
서울특별시 2060
 
15.7%
중랑구 2059
 
15.7%
1층 1129
 
8.6%
면목동 664
 
5.1%
상봉동 331
 
2.5%
망우동 317
 
2.4%
묵동 218
 
1.7%
중화동 215
 
1.6%
망우로 206
 
1.6%
신내동 195
 
1.5%
Other values (1496) 5726
43.6%
2024-05-11T14:38:50.986364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11066
 
17.0%
1 3404
 
5.2%
동 2600
 
4.0%
중 2453
 
3.8%
랑 2172
 
3.3%
, 2145
 
3.3%
시 2094
 
3.2%
서 2086
 
3.2%
울 2076
 
3.2%
구 2069
 
3.2%
Other values (368) 32912
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36858
56.6%
Space Separator 11066
 
17.0%
Decimal Number 10447
 
16.1%
Other Punctuation 2151
 
3.3%
Open Punctuation 2064
 
3.2%
Close Punctuation 2064
 
3.2%
Uppercase Letter 193
 
0.3%
Dash Punctuation 188
 
0.3%
Lowercase Letter 34
 
0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2600
 
7.1%
중 2453
 
6.7%
랑 2172
 
5.9%
시 2094
 
5.7%
서 2086
 
5.7%
울 2076
 
5.6%
구 2069
 
5.6%
로 2065
 
5.6%
별 2060
 
5.6%
특 2060
 
5.6%
Other values (316) 15123
41.0%
Uppercase Letter
ValueCountFrequency (%)
B 62
32.1%
C 23
 
11.9%
A 22
 
11.4%
S 18
 
9.3%
E 14
 
7.3%
Y 8
 
4.1%
M 7
 
3.6%
R 6
 
3.1%
H 5
 
2.6%
T 4
 
2.1%
Other values (11) 24
 
12.4%
Lowercase Letter
ValueCountFrequency (%)
e 7
20.6%
n 4
11.8%
r 4
11.8%
s 3
8.8%
c 3
8.8%
t 3
8.8%
k 2
 
5.9%
a 2
 
5.9%
g 2
 
5.9%
l 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
1 3404
32.6%
2 1319
 
12.6%
3 1100
 
10.5%
0 915
 
8.8%
4 841
 
8.1%
5 723
 
6.9%
6 584
 
5.6%
9 565
 
5.4%
7 536
 
5.1%
8 460
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 2145
99.7%
& 5
 
0.2%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
11066
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2064
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36857
56.6%
Common 27992
43.0%
Latin 227
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2600
 
7.1%
중 2453
 
6.7%
랑 2172
 
5.9%
시 2094
 
5.7%
서 2086
 
5.7%
울 2076
 
5.6%
구 2069
 
5.6%
로 2065
 
5.6%
별 2060
 
5.6%
특 2060
 
5.6%
Other values (315) 15122
41.0%
Latin
ValueCountFrequency (%)
B 62
27.3%
C 23
 
10.1%
A 22
 
9.7%
S 18
 
7.9%
E 14
 
6.2%
Y 8
 
3.5%
M 7
 
3.1%
e 7
 
3.1%
R 6
 
2.6%
H 5
 
2.2%
Other values (24) 55
24.2%
Common
ValueCountFrequency (%)
11066
39.5%
1 3404
 
12.2%
, 2145
 
7.7%
( 2064
 
7.4%
) 2064
 
7.4%
2 1319
 
4.7%
3 1100
 
3.9%
0 915
 
3.3%
4 841
 
3.0%
5 723
 
2.6%
Other values (8) 2351
 
8.4%
Han
ValueCountFrequency (%)
休 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36857
56.6%
ASCII 28219
43.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11066
39.2%
1 3404
 
12.1%
, 2145
 
7.6%
( 2064
 
7.3%
) 2064
 
7.3%
2 1319
 
4.7%
3 1100
 
3.9%
0 915
 
3.2%
4 841
 
3.0%
5 723
 
2.6%
Other values (42) 2578
 
9.1%
Hangul
ValueCountFrequency (%)
동 2600
 
7.1%
중 2453
 
6.7%
랑 2172
 
5.9%
시 2094
 
5.7%
서 2086
 
5.7%
울 2076
 
5.6%
구 2069
 
5.6%
로 2065
 
5.6%
별 2060
 
5.6%
특 2060
 
5.6%
Other values (315) 15122
41.0%
CJK
ValueCountFrequency (%)
休 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct246
Distinct (%)12.0%
Missing1102
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean2127.699
Minimum2001
Maximum6057
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:51.246223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2015
Q12061
median2127
Q32188
95-th percentile2244
Maximum6057
Range4056
Interquartile range (IQR)127

Descriptive statistics

Standard deviation113.81318
Coefficient of variation (CV)0.053491204
Kurtosis692.69214
Mean2127.699
Median Absolute Deviation (MAD)63
Skewness20.104242
Sum4361783
Variance12953.44
MonotonicityNot monotonic
2024-05-11T14:38:51.497607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2033 53
 
1.7%
2087 52
 
1.6%
2169 37
 
1.2%
2024 31
 
1.0%
2228 31
 
1.0%
2086 30
 
1.0%
2017 30
 
1.0%
2163 28
 
0.9%
2057 26
 
0.8%
2244 25
 
0.8%
Other values (236) 1707
54.2%
(Missing) 1102
35.0%
ValueCountFrequency (%)
2001 1
 
< 0.1%
2002 6
0.2%
2003 9
0.3%
2004 3
 
0.1%
2005 4
 
0.1%
2006 13
0.4%
2007 10
0.3%
2008 5
 
0.2%
2009 5
 
0.2%
2010 6
0.2%
ValueCountFrequency (%)
6057 1
 
< 0.1%
2263 1
 
< 0.1%
2262 7
0.2%
2261 4
0.1%
2260 1
 
< 0.1%
2259 3
0.1%
2258 1
 
< 0.1%
2257 7
0.2%
2256 3
0.1%
2255 4
0.1%

사업장명
Text

Distinct2875
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
2024-05-11T14:38:51.983437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length7.0824873
Min length1

Characters and Unicode

Total characters22324
Distinct characters802
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2685 ?
Unique (%)85.2%

Sample

1st row등대
2nd row청학커피숍
3rd row은하
4th row중앙
5th row영
ValueCountFrequency (%)
씨유 57
 
1.4%
세븐일레븐 55
 
1.4%
gs25 33
 
0.8%
카페 32
 
0.8%
cafe 21
 
0.5%
상봉역점 20
 
0.5%
상봉점 20
 
0.5%
메가엠지씨커피 19
 
0.5%
이마트24 18
 
0.4%
이디야 18
 
0.4%
Other values (3029) 3771
92.8%
2024-05-11T14:38:52.704566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 1001
 
4.5%
913
 
4.1%
스 588
 
2.6%
이 538
 
2.4%
피 495
 
2.2%
커 463
 
2.1%
) 392
 
1.8%
( 390
 
1.7%
리 356
 
1.6%
중 279
 
1.2%
Other values (792) 16909
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18038
80.8%
Uppercase Letter 991
 
4.4%
Lowercase Letter 946
 
4.2%
Space Separator 913
 
4.1%
Decimal Number 550
 
2.5%
Close Punctuation 392
 
1.8%
Open Punctuation 390
 
1.7%
Other Punctuation 96
 
0.4%
Dash Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1001
 
5.5%
스 588
 
3.3%
이 538
 
3.0%
피 495
 
2.7%
커 463
 
2.6%
리 356
 
2.0%
중 279
 
1.5%
카 248
 
1.4%
페 245
 
1.4%
방 241
 
1.3%
Other values (716) 13584
75.3%
Lowercase Letter
ValueCountFrequency (%)
e 157
16.6%
a 101
10.7%
c 78
 
8.2%
o 76
 
8.0%
f 75
 
7.9%
n 53
 
5.6%
r 47
 
5.0%
i 45
 
4.8%
s 45
 
4.8%
t 44
 
4.7%
Other values (15) 225
23.8%
Uppercase Letter
ValueCountFrequency (%)
S 145
14.6%
C 123
12.4%
G 121
12.2%
E 82
 
8.3%
A 56
 
5.7%
O 52
 
5.2%
P 48
 
4.8%
F 43
 
4.3%
U 39
 
3.9%
B 36
 
3.6%
Other values (15) 246
24.8%
Decimal Number
ValueCountFrequency (%)
2 206
37.5%
5 175
31.8%
1 47
 
8.5%
4 34
 
6.2%
3 29
 
5.3%
9 23
 
4.2%
0 14
 
2.5%
7 10
 
1.8%
6 9
 
1.6%
8 3
 
0.5%
Other Punctuation
ValueCountFrequency (%)
& 25
26.0%
. 19
19.8%
/ 15
15.6%
, 13
13.5%
? 9
 
9.4%
' 8
 
8.3%
: 3
 
3.1%
! 2
 
2.1%
# 2
 
2.1%
Space Separator
ValueCountFrequency (%)
913
100.0%
Close Punctuation
ValueCountFrequency (%)
) 392
100.0%
Open Punctuation
ValueCountFrequency (%)
( 390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18034
80.8%
Common 2349
 
10.5%
Latin 1937
 
8.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1001
 
5.6%
스 588
 
3.3%
이 538
 
3.0%
피 495
 
2.7%
커 463
 
2.6%
리 356
 
2.0%
중 279
 
1.5%
카 248
 
1.4%
페 245
 
1.4%
방 241
 
1.3%
Other values (712) 13580
75.3%
Latin
ValueCountFrequency (%)
e 157
 
8.1%
S 145
 
7.5%
C 123
 
6.4%
G 121
 
6.2%
a 101
 
5.2%
E 82
 
4.2%
c 78
 
4.0%
o 76
 
3.9%
f 75
 
3.9%
A 56
 
2.9%
Other values (40) 923
47.7%
Common
ValueCountFrequency (%)
913
38.9%
) 392
16.7%
( 390
16.6%
2 206
 
8.8%
5 175
 
7.4%
1 47
 
2.0%
4 34
 
1.4%
3 29
 
1.2%
& 25
 
1.1%
9 23
 
1.0%
Other values (16) 115
 
4.9%
Han
ValueCountFrequency (%)
明 1
25.0%
果 1
25.0%
愛 1
25.0%
情 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18034
80.8%
ASCII 4285
 
19.2%
CJK 4
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 1001
 
5.6%
스 588
 
3.3%
이 538
 
3.0%
피 495
 
2.7%
커 463
 
2.6%
리 356
 
2.0%
중 279
 
1.5%
카 248
 
1.4%
페 245
 
1.4%
방 241
 
1.3%
Other values (712) 13580
75.3%
ASCII
ValueCountFrequency (%)
913
21.3%
) 392
 
9.1%
( 390
 
9.1%
2 206
 
4.8%
5 175
 
4.1%
e 157
 
3.7%
S 145
 
3.4%
C 123
 
2.9%
G 121
 
2.8%
a 101
 
2.4%
Other values (65) 1562
36.5%
CJK
ValueCountFrequency (%)
明 1
25.0%
果 1
25.0%
愛 1
25.0%
情 1
25.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

최종수정일자
Date

Distinct2494
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
Minimum1999-02-18 00:00:00
Maximum2024-05-09 17:38:06
2024-05-11T14:38:52.969366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:53.304070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
I
2155 
U
997 

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 2155
68.4%
U 997
31.6%

Length

2024-05-11T14:38:53.655991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:53.824380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2155
68.4%
u 997
31.6%

데이터갱신일자
Date

Distinct903
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:38:54.025257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:38:54.589542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
커피숍
817 
다방
535 
기타 휴게음식점
476 
일반조리판매
385 
편의점
385 
Other values (11)
554 

Length

Max length8
Median length6
Mean length4.106599
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 817
25.9%
다방 535
17.0%
기타 휴게음식점 476
15.1%
일반조리판매 385
12.2%
편의점 385
12.2%
과자점 284
 
9.0%
패스트푸드 205
 
6.5%
아이스크림 16
 
0.5%
철도역구내 13
 
0.4%
푸드트럭 10
 
0.3%
Other values (6) 26
 
0.8%

Length

2024-05-11T14:38:54.837162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 817
22.5%
다방 535
14.7%
기타 476
13.1%
휴게음식점 476
13.1%
일반조리판매 385
10.6%
편의점 385
10.6%
과자점 284
 
7.8%
패스트푸드 205
 
5.7%
아이스크림 16
 
0.4%
철도역구내 13
 
0.4%
Other values (7) 36
 
1.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1779
Distinct (%)58.2%
Missing96
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean207665.37
Minimum203121.2
Maximum210062.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:55.100463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203121.2
5-th percentile206600.68
Q1206953.3
median207645.85
Q3208263.09
95-th percentile209046.99
Maximum210062.77
Range6941.5661
Interquartile range (IQR)1309.7871

Descriptive statistics

Standard deviation781.73858
Coefficient of variation (CV)0.0037644148
Kurtosis-0.44324078
Mean207665.37
Median Absolute Deviation (MAD)648.68151
Skewness0.26459015
Sum6.3462536 × 108
Variance611115.2
MonotonicityNot monotonic
2024-05-11T14:38:55.372570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207923.745922676 48
 
1.5%
208183.558935157 31
 
1.0%
206777.731391054 28
 
0.9%
207089.21659098 26
 
0.8%
208208.786684767 26
 
0.8%
208295.099818379 15
 
0.5%
206808.914669794 14
 
0.4%
206556.148986381 14
 
0.4%
207163.791145804 13
 
0.4%
208112.860200669 11
 
0.3%
Other values (1769) 2830
89.8%
(Missing) 96
 
3.0%
ValueCountFrequency (%)
203121.203642767 1
 
< 0.1%
206260.394582177 2
0.1%
206280.483272835 4
0.1%
206296.725620359 1
 
< 0.1%
206297.016274369 1
 
< 0.1%
206303.031613921 1
 
< 0.1%
206321.919332707 2
0.1%
206328.785504793 3
0.1%
206329.891285253 1
 
< 0.1%
206363.827759373 3
0.1%
ValueCountFrequency (%)
210062.769774313 1
 
< 0.1%
209931.172836 1
 
< 0.1%
209856.1161416 1
 
< 0.1%
209797.760188391 4
0.1%
209681.607188118 1
 
< 0.1%
209667.606965418 1
 
< 0.1%
209644.308531451 1
 
< 0.1%
209521.669970747 2
0.1%
209521.169706304 1
 
< 0.1%
209505.319471833 2
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1779
Distinct (%)58.2%
Missing96
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean454828.46
Minimum446464.38
Maximum457702.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:55.627680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446464.38
5-th percentile452925.14
Q1453975.7
median454823.56
Q3455579.05
95-th percentile457028.91
Maximum457702.63
Range11238.251
Interquartile range (IQR)1603.3509

Descriptive statistics

Standard deviation1218.4453
Coefficient of variation (CV)0.0026789117
Kurtosis0.10354702
Mean454828.46
Median Absolute Deviation (MAD)802.61106
Skewness0.0027522707
Sum1.3899558 × 109
Variance1484608.9
MonotonicityNot monotonic
2024-05-11T14:38:55.881153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
455090.718335439 48
 
1.5%
454911.24852306 31
 
1.0%
456837.219624564 28
 
0.9%
453074.476763597 26
 
0.8%
457054.793655589 26
 
0.8%
456014.999180519 15
 
0.5%
456949.35802282 14
 
0.4%
454633.631796621 14
 
0.4%
454984.412728653 13
 
0.4%
457113.638411288 11
 
0.3%
Other values (1769) 2830
89.8%
(Missing) 96
 
3.0%
ValueCountFrequency (%)
446464.379990564 1
< 0.1%
452077.782812274 2
0.1%
452098.766989799 1
< 0.1%
452131.289461027 1
< 0.1%
452146.66493964 1
< 0.1%
452156.632616372 1
< 0.1%
452156.798939417 1
< 0.1%
452163.883585036 1
< 0.1%
452171.83048285 2
0.1%
452180.759882096 1
< 0.1%
ValueCountFrequency (%)
457702.631123 4
0.1%
457697.301013 1
 
< 0.1%
457511.137973201 1
 
< 0.1%
457508.017117704 1
 
< 0.1%
457507.041329636 2
0.1%
457471.0 1
 
< 0.1%
457462.766652935 3
0.1%
457449.962679084 1
 
< 0.1%
457446.479605 1
 
< 0.1%
457438.909754748 3
0.1%

위생업태명
Categorical

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
706 
다방
534 
커피숍
519 
일반조리판매
340 
기타 휴게음식점
287 
Other values (11)
766 

Length

Max length8
Median length6
Mean length3.9622462
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 706
22.4%
다방 534
16.9%
커피숍 519
16.5%
일반조리판매 340
10.8%
기타 휴게음식점 287
9.1%
과자점 283
9.0%
편의점 263
 
8.3%
패스트푸드 180
 
5.7%
철도역구내 12
 
0.4%
떡카페 8
 
0.3%
Other values (6) 20
 
0.6%

Length

2024-05-11T14:38:56.112756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 706
20.5%
다방 534
15.5%
커피숍 519
15.1%
일반조리판매 340
9.9%
기타 287
8.3%
휴게음식점 287
8.3%
과자점 283
8.2%
편의점 263
 
7.6%
패스트푸드 180
 
5.2%
철도역구내 12
 
0.3%
Other values (7) 28
 
0.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing1981
Missing (%)62.8%
Infinite0
Infinite (%)0.0%
Mean0.29888984
Minimum0
Maximum6
Zeros904
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:56.357257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.64143839
Coefficient of variation (CV)2.1460696
Kurtosis12.593079
Mean0.29888984
Median Absolute Deviation (MAD)0
Skewness2.9426612
Sum350
Variance0.41144321
MonotonicityNot monotonic
2024-05-11T14:38:56.526882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 904
28.7%
1 207
 
6.6%
2 45
 
1.4%
3 10
 
0.3%
4 3
 
0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1981
62.8%
ValueCountFrequency (%)
0 904
28.7%
1 207
 
6.6%
2 45
 
1.4%
3 10
 
0.3%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 10
 
0.3%
2 45
 
1.4%
1 207
 
6.6%
0 904
28.7%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.6%
Missing1965
Missing (%)62.3%
Infinite0
Infinite (%)0.0%
Mean0.957877
Minimum0
Maximum7
Zeros553
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:38:56.712410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1102367
Coefficient of variation (CV)1.1590598
Kurtosis0.80084122
Mean0.957877
Median Absolute Deviation (MAD)1
Skewness1.0682049
Sum1137
Variance1.2326255
MonotonicityNot monotonic
2024-05-11T14:38:56.938036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 553
 
17.5%
1 285
 
9.0%
2 237
 
7.5%
3 75
 
2.4%
4 34
 
1.1%
5 2
 
0.1%
7 1
 
< 0.1%
(Missing) 1965
62.3%
ValueCountFrequency (%)
0 553
17.5%
1 285
9.0%
2 237
7.5%
3 75
 
2.4%
4 34
 
1.1%
5 2
 
0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
5 2
 
0.1%
4 34
 
1.1%
3 75
 
2.4%
2 237
7.5%
1 285
9.0%
0 553
17.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2212 
주택가주변
607 
기타
243 
아파트지역
 
49
유흥업소밀집지역
 
31
Other values (3)
 
10

Length

Max length8
Median length4
Mean length4.1050127
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2212
70.2%
주택가주변 607
 
19.3%
기타 243
 
7.7%
아파트지역 49
 
1.6%
유흥업소밀집지역 31
 
1.0%
학교정화(상대) 5
 
0.2%
결혼예식장주변 3
 
0.1%
학교정화(절대) 2
 
0.1%

Length

2024-05-11T14:38:57.163762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:57.342399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2212
70.2%
주택가주변 607
 
19.3%
기타 243
 
7.7%
아파트지역 49
 
1.6%
유흥업소밀집지역 31
 
1.0%
학교정화(상대 5
 
0.2%
결혼예식장주변 3
 
0.1%
학교정화(절대 2
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2260 
기타
471 
지도
 
169
갑
 
139
자율
 
50
Other values (3)
 
63

Length

Max length4
Median length4
Mean length3.3784898
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2260
71.7%
기타 471
 
14.9%
지도 169
 
5.4%
갑 139
 
4.4%
자율 50
 
1.6%
을 36
 
1.1%
관리 25
 
0.8%
우수 2
 
0.1%

Length

2024-05-11T14:38:57.577913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:57.771447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2260
71.7%
기타 471
 
14.9%
지도 169
 
5.4%
갑 139
 
4.4%
자율 50
 
1.6%
을 36
 
1.1%
관리 25
 
0.8%
우수 2
 
0.1%

급수시설구분명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
1584 
상수도전용
1566 
상수도(음용)지하수(주방용)겸용
 
1
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.501269
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1584
50.3%
상수도전용 1566
49.7%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T14:38:58.002065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.178123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1584
50.3%
상수도전용 1566
49.7%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2995 
0
 
157

Length

Max length4
Median length4
Mean length3.8505711
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> 2995
95.0%
0 157
 
5.0%

Length

2024-05-11T14:38:58.388652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.569865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2995
95.0%
0 157
 
5.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:38:58.775887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:58.953883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:38:59.151828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:59.342953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:38:59.532061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:38:59.730016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:39:00.010225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:00.205695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:39:00.411582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:00.597514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.8 KiB
<NA>
2993 
0
 
159

Length

Max length4
Median length4
Mean length3.8486675
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> 2993
95.0%
0 159
 
5.0%

Length

2024-05-11T14:39:00.880896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:39:01.135984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2993
95.0%
0 159
 
5.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing706
Missing (%)22.4%
Memory size6.3 KiB
False
2433 
True
 
13
(Missing)
706 
ValueCountFrequency (%)
False 2433
77.2%
True 13
 
0.4%
(Missing) 706
 
22.4%
2024-05-11T14:39:01.280292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct1509
Distinct (%)61.7%
Missing706
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean45.614853
Minimum0
Maximum520.47
Zeros5
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size27.8 KiB
2024-05-11T14:39:01.473088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q118.165
median31.225
Q363.84
95-th percentile123.9425
Maximum520.47
Range520.47
Interquartile range (IQR)45.675

Descriptive statistics

Standard deviation42.883536
Coefficient of variation (CV)0.9401222
Kurtosis14.643128
Mean45.614853
Median Absolute Deviation (MAD)18.775
Skewness2.6538324
Sum111573.93
Variance1838.9976
MonotonicityNot monotonic
2024-05-11T14:39:01.721944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 128
 
4.1%
6.6 58
 
1.8%
33.0 42
 
1.3%
30.0 34
 
1.1%
10.0 30
 
1.0%
26.4 26
 
0.8%
9.9 24
 
0.8%
16.5 18
 
0.6%
13.2 17
 
0.5%
21.0 14
 
0.4%
Other values (1499) 2055
65.2%
(Missing) 706
 
22.4%
ValueCountFrequency (%)
0.0 5
0.2%
0.13 1
 
< 0.1%
1.0 1
 
< 0.1%
1.44 1
 
< 0.1%
1.47 1
 
< 0.1%
1.65 3
0.1%
1.71 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 4
0.1%
2.12 1
 
< 0.1%
ValueCountFrequency (%)
520.47 1
< 0.1%
437.1 1
< 0.1%
383.44 1
< 0.1%
381.71 1
< 0.1%
321.86 1
< 0.1%
280.5 1
< 0.1%
270.06 1
< 0.1%
263.18 1
< 0.1%
252.61 1
< 0.1%
246.57 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3152
Missing (%)100.0%
Memory size27.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-104-1968-0726519680504<NA>3폐업2폐업19921027<NA><NA><NA>0209736643110.19131851서울특별시 중랑구 묵동 238-8번지<NA><NA>등대2001-09-28 00:00:00I2018-08-31 23:59:59.0다방206712.645739456738.441211다방01기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N110.19<NA><NA><NA>
130600003060000-104-1968-0758719681002<NA>3폐업2폐업20070530<NA><NA><NA>02 433109387.95131861서울특별시 중랑구 상봉동 136-6번지<NA><NA>청학커피숍2003-03-18 00:00:00I2018-08-31 23:59:59.0다방206437.69135454516.250155다방02주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N87.95<NA><NA><NA>
230600003060000-104-1969-0726219690813<NA>3폐업2폐업19930918<NA><NA><NA>020435646199.15131860서울특별시 중랑구 상봉동 108-2번지<NA><NA>은하2001-09-28 00:00:00I2018-08-31 23:59:59.0다방207506.24855454647.912047다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.15<NA><NA><NA>
330600003060000-104-1969-0726619691218<NA>3폐업2폐업19890905<NA><NA><NA>020433033988.5131861서울특별시 중랑구 상봉동 130-130번지<NA><NA>중앙2001-09-28 00:00:00I2018-08-31 23:59:59.0다방206679.749624454550.037054다방02기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N88.5<NA><NA><NA>
430600003060000-104-1969-0727619690811<NA>3폐업2폐업19940414<NA><NA><NA>020434497797.35131803서울특별시 중랑구 망우동 340-22번지<NA><NA>영2001-09-28 00:00:00I2018-08-31 23:59:59.0다방209056.320461455369.284965다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.35<NA><NA><NA>
530600003060000-104-1969-0728619691202<NA>3폐업2폐업20110117<NA><NA><NA>02 435133393.94131831서울특별시 중랑구 면목동 496-6번지<NA><NA>샘2002-07-09 00:00:00I2018-08-31 23:59:59.0다방207739.445608453239.400387다방03주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N93.94<NA><NA><NA>
630600003060000-104-1969-0752819690911<NA>3폐업2폐업20041201<NA><NA><NA>020973450083.32131848서울특별시 중랑구 묵동 162-1번지<NA><NA>길다방2003-03-18 00:00:00I2018-08-31 23:59:59.0다방206934.010159457125.95332다방02주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N83.32<NA><NA><NA>
730600003060000-104-1970-0729519701222<NA>3폐업2폐업19940310<NA><NA><NA>020435870689.25131120서울특별시 중랑구 중화동 산 314-1번지<NA><NA>코스모스2001-09-28 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N89.25<NA><NA><NA>
830600003060000-104-1970-0735319701019<NA>3폐업2폐업20020118<NA><NA><NA>02 4347595159.62131860서울특별시 중랑구 상봉동 118-5번지<NA><NA>칠성다방2001-06-22 00:00:00I2018-08-31 23:59:59.0다방207208.057491454772.376318다방02기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N159.62<NA><NA><NA>
930600003060000-104-1970-0742319701205<NA>3폐업2폐업19950825<NA><NA><NA>02 4351423104.52131820서울특별시 중랑구 면목동 147-7번지<NA><NA>남경2001-09-28 00:00:00I2018-08-31 23:59:59.0다방207029.006118453850.192959다방04기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N104.52<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
314230600003060000-104-2024-000412024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.58131-852서울특별시 중랑구 묵동 240-175 1층서울특별시 중랑구 동일로163길 35, 1층 (묵동)2007카페클래스 1호점2024-04-19 11:14:21I2023-12-03 22:01:00.0커피숍206576.724441456601.514818<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314330600003060000-104-2024-000422024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.02131-857서울특별시 중랑구 상봉동 116-17 로젠하임 제1동 제101호서울특별시 중랑구 망우로 275, 제1층 제101호 (상봉동, 로젠하임)2098메가엠지씨커피 서울중랑우체국점2024-04-22 10:31:27I2023-12-03 22:04:00.0커피숍207271.995497454865.791491<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314430600003060000-104-2024-000432024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3131-770서울특별시 중랑구 신내동 795 새한아파트서울특별시 중랑구 용마산로 616, 상가동 1층 111호 (신내동, 새한아파트)2058GS25신내새한점2024-04-22 13:33:40I2023-12-03 22:04:00.0편의점208889.864991455878.542779<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314530600003060000-104-2024-000442024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0131-827서울특별시 중랑구 면목동 665-45서울특별시 중랑구 사가정로50길 70, 27호점 1층 (면목동)2240오뎅순대(떡뽁군,김밥양)2024-04-29 11:01:49I2023-12-05 00:01:00.0기타 휴게음식점207425.309548452855.609343<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314630600003060000-104-2024-000452024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>264.44131-861서울특별시 중랑구 상봉동 475-11 우리빌딩서울특별시 중랑구 망우로 166-17, 우리빌딩 2~3층 (상봉동)2118카페하인나2024-04-29 16:19:12I2023-12-05 00:01:00.0기타 휴게음식점206260.394582454407.566322<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314730600003060000-104-2024-000462024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3131-802서울특별시 중랑구 망우동 207-20서울특별시 중랑구 용마산로116길 81, 1층 (망우동)2177지에스(GS)25 망우청광점2024-04-30 16:03:25I2023-12-05 00:02:00.0편의점209205.517993455297.298258<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314830600003060000-104-2024-000472024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0131-820서울특별시 중랑구 면목동 177-146 청라음악학원서울특별시 중랑구 겸재로3길 22, 청라음악학원 1층 우측5호 (면목동)2134디저트파파2024-05-09 11:20:00U2023-12-04 23:01:00.0기타 휴게음식점206703.270519453845.04202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
314930600003060000-104-2024-000482024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>67.0131-857서울특별시 중랑구 상봉동 99-9 대동빌딩 1층 101-1호서울특별시 중랑구 망우로 319, 대동빌딩 1층 101-1호 (상봉동)2098153구포국수 상봉역점2024-05-03 16:00:23I2023-12-05 00:05:00.0일반조리판매207677.729376454995.182491<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
315030600003060000-104-2024-000492024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.6131-811서울특별시 중랑구 면목동 15-1 1층서울특별시 중랑구 용마산로96길 16, 1층 (면목동)2189씨유 면목하모니점(CU)2024-05-09 17:38:06I2023-12-04 23:01:00.0편의점208608.730097454213.122853<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
315130600003060000-104-2201-0978720010403<NA>1영업/정상1영업<NA><NA><NA><NA>02 4391144437.1131858서울특별시 중랑구 상봉동 81-0번지서울특별시 중랑구 망우로 336 (상봉동)2150(주)코스트코코리아푸드코트2015-12-01 12:51:00I2018-08-31 23:59:59.0패스트푸드207897.260402454953.363448패스트푸드00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N437.1<NA><NA><NA>