Overview

Dataset statistics

Number of variables44
Number of observations6485
Missing cells60309
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 MiB
Average record size in memory376.0 B

Variable types

Categorical22
Text6
DateTime4
Unsupported7
Numeric4
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18437/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (51.7%)Imbalance
영업상태명 is highly imbalanced (51.7%)Imbalance
상세영업상태코드 is highly imbalanced (51.7%)Imbalance
상세영업상태명 is highly imbalanced (51.7%)Imbalance
남성종사자수 is highly imbalanced (84.6%)Imbalance
여성종사자수 is highly imbalanced (82.9%)Imbalance
영업장주변구분명 is highly imbalanced (90.8%)Imbalance
등급구분명 is highly imbalanced (91.3%)Imbalance
급수시설구분명 is highly imbalanced (75.9%)Imbalance
총인원 is highly imbalanced (74.2%)Imbalance
공장판매직종업원수 is highly imbalanced (64.2%)Imbalance
공장생산직종업원수 is highly imbalanced (55.5%)Imbalance
시설총규모 is highly imbalanced (76.9%)Imbalance
인허가취소일자 has 6485 (100.0%) missing valuesMissing
폐업일자 has 677 (10.4%) missing valuesMissing
휴업시작일자 has 6485 (100.0%) missing valuesMissing
휴업종료일자 has 6485 (100.0%) missing valuesMissing
재개업일자 has 6485 (100.0%) missing valuesMissing
전화번호 has 4062 (62.6%) missing valuesMissing
소재지면적 has 4438 (68.4%) missing valuesMissing
소재지우편번호 has 165 (2.5%) missing valuesMissing
지번주소 has 165 (2.5%) missing valuesMissing
도로명주소 has 2138 (33.0%) missing valuesMissing
도로명우편번호 has 2175 (33.5%) missing valuesMissing
좌표정보(X) has 88 (1.4%) missing valuesMissing
좌표정보(Y) has 88 (1.4%) missing valuesMissing
다중이용업소여부 has 918 (14.2%) missing valuesMissing
전통업소지정번호 has 6485 (100.0%) missing valuesMissing
전통업소주된음식 has 6485 (100.0%) missing valuesMissing
홈페이지 has 6485 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 46.18642152)Skewed
좌표정보(X) is highly skewed (γ1 = 58.40745854)Skewed
좌표정보(Y) is highly skewed (γ1 = -47.67480984)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 198 (3.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:36:26.060750
Analysis finished2024-05-11 06:36:28.394563
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
3100000
6485 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 6485
100.0%

Length

2024-05-11T15:36:28.498437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:28.649441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 6485
100.0%

관리번호
Text

UNIQUE 

Distinct6485
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
2024-05-11T15:36:29.188727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters142670
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

Unique6485 ?
Unique (%)100.0%

Sample

1st row3100000-107-1972-00001
2nd row3100000-107-1972-00002
3rd row3100000-107-1972-00003
4th row3100000-107-1973-00001
5th row3100000-107-1975-00001
ValueCountFrequency (%)
3100000-107-1972-00001 1
 
< 0.1%
3100000-107-2018-00581 1
 
< 0.1%
3100000-107-2018-00603 1
 
< 0.1%
3100000-107-2018-00602 1
 
< 0.1%
3100000-107-2018-00601 1
 
< 0.1%
3100000-107-2018-00600 1
 
< 0.1%
3100000-107-2018-00599 1
 
< 0.1%
3100000-107-2018-00598 1
 
< 0.1%
3100000-107-2018-00597 1
 
< 0.1%
3100000-107-2018-00596 1
 
< 0.1%
Other values (6475) 6475
99.8%
2024-05-11T15:36:29.728691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64607
45.3%
1 19909
 
14.0%
- 19455
 
13.6%
2 10624
 
7.4%
3 9001
 
6.3%
7 8565
 
6.0%
9 2720
 
1.9%
8 2247
 
1.6%
4 1977
 
1.4%
5 1803
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123215
86.4%
Dash Punctuation 19455
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64607
52.4%
1 19909
 
16.2%
2 10624
 
8.6%
3 9001
 
7.3%
7 8565
 
7.0%
9 2720
 
2.2%
8 2247
 
1.8%
4 1977
 
1.6%
5 1803
 
1.5%
6 1762
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 19455
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 142670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64607
45.3%
1 19909
 
14.0%
- 19455
 
13.6%
2 10624
 
7.4%
3 9001
 
6.3%
7 8565
 
6.0%
9 2720
 
1.9%
8 2247
 
1.6%
4 1977
 
1.4%
5 1803
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64607
45.3%
1 19909
 
14.0%
- 19455
 
13.6%
2 10624
 
7.4%
3 9001
 
6.3%
7 8565
 
6.0%
9 2720
 
1.9%
8 2247
 
1.6%
4 1977
 
1.4%
5 1803
 
1.3%
Distinct3656
Distinct (%)56.4%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
Minimum1972-04-12 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:36:30.059093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:30.371853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
3
5808 
1
677 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 5808
89.6%
1 677
 
10.4%

Length

2024-05-11T15:36:30.647550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:30.806244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5808
89.6%
1 677
 
10.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
폐업
5808 
영업/정상
677 

Length

Max length5
Median length2
Mean length2.3131843
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 5808
89.6%
영업/정상 677
 
10.4%

Length

2024-05-11T15:36:30.976424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:31.159067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5808
89.6%
영업/정상 677
 
10.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
2
5808 
1
677 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 5808
89.6%
1 677
 
10.4%

Length

2024-05-11T15:36:31.326303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:31.513943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5808
89.6%
1 677
 
10.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
폐업
5808 
영업
677 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5808
89.6%
영업 677
 
10.4%

Length

2024-05-11T15:36:31.690078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:31.837828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5808
89.6%
영업 677
 
10.4%

폐업일자
Date

MISSING 

Distinct3312
Distinct (%)57.0%
Missing677
Missing (%)10.4%
Memory size50.8 KiB
Minimum1997-01-24 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:36:31.996999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:32.221056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

전화번호
Text

MISSING 

Distinct1486
Distinct (%)61.3%
Missing4062
Missing (%)62.6%
Memory size50.8 KiB
2024-05-11T15:36:32.678997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.836566
Min length2

Characters and Unicode

Total characters26257
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

Unique1234 ?
Unique (%)50.9%

Sample

1st row02 9388038
2nd row02 9361174
3rd row02 9363019
4th row02 9367040
5th row02 9366041
ValueCountFrequency (%)
02 1267
24.9%
031 418
 
8.2%
070 59
 
1.2%
032 57
 
1.1%
07043009589 45
 
0.9%
055 42
 
0.8%
042 33
 
0.6%
062 33
 
0.6%
936 29
 
0.6%
4358 26
 
0.5%
Other values (1634) 3084
60.6%
2024-05-11T15:36:33.378227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4533
17.3%
2 3621
13.8%
3196
12.2%
9 2623
10.0%
3 2598
9.9%
1 2116
8.1%
5 1751
 
6.7%
7 1615
 
6.2%
8 1560
 
5.9%
4 1468
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23061
87.8%
Space Separator 3196
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4533
19.7%
2 3621
15.7%
9 2623
11.4%
3 2598
11.3%
1 2116
9.2%
5 1751
 
7.6%
7 1615
 
7.0%
8 1560
 
6.8%
4 1468
 
6.4%
6 1176
 
5.1%
Space Separator
ValueCountFrequency (%)
3196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 26257
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4533
17.3%
2 3621
13.8%
3196
12.2%
9 2623
10.0%
3 2598
9.9%
1 2116
8.1%
5 1751
 
6.7%
7 1615
 
6.2%
8 1560
 
5.9%
4 1468
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4533
17.3%
2 3621
13.8%
3196
12.2%
9 2623
10.0%
3 2598
9.9%
1 2116
8.1%
5 1751
 
6.7%
7 1615
 
6.2%
8 1560
 
5.9%
4 1468
 
5.6%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct596
Distinct (%)29.1%
Missing4438
Missing (%)68.4%
Infinite0
Infinite (%)0.0%
Mean16.241705
Minimum0
Maximum312
Zeros198
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2024-05-11T15:36:33.712180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.6
median9.77
Q323
95-th percentile47.191
Maximum312
Range312
Interquartile range (IQR)19.4

Descriptive statistics

Standard deviation22.325848
Coefficient of variation (CV)1.3746
Kurtosis42.148681
Mean16.241705
Median Absolute Deviation (MAD)6.77
Skewness4.9948297
Sum33246.77
Variance498.44351
MonotonicityNot monotonic
2024-05-11T15:36:34.006657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 198
 
3.1%
3.3 146
 
2.3%
6.0 104
 
1.6%
6.6 97
 
1.5%
10.0 85
 
1.3%
5.0 75
 
1.2%
3.0 62
 
1.0%
4.0 43
 
0.7%
9.9 41
 
0.6%
33.0 32
 
0.5%
Other values (586) 1164
 
17.9%
(Missing) 4438
68.4%
ValueCountFrequency (%)
0.0 198
3.1%
0.3 1
 
< 0.1%
0.61 1
 
< 0.1%
0.85 1
 
< 0.1%
0.9 1
 
< 0.1%
0.96 1
 
< 0.1%
1.0 19
 
0.3%
1.05 1
 
< 0.1%
1.09 1
 
< 0.1%
1.14 1
 
< 0.1%
ValueCountFrequency (%)
312.0 1
< 0.1%
295.85 1
< 0.1%
223.1 1
< 0.1%
199.32 1
< 0.1%
192.0 1
< 0.1%
173.66 1
< 0.1%
169.71 1
< 0.1%
168.75 1
< 0.1%
155.82 1
< 0.1%
143.41 1
< 0.1%

소재지우편번호
Text

MISSING 

Distinct159
Distinct (%)2.5%
Missing165
Missing (%)2.5%
Memory size50.8 KiB
2024-05-11T15:36:34.543523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.089557
Min length6

Characters and Unicode

Total characters38486
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

Unique29 ?
Unique (%)0.5%

Sample

1st row139810
2nd row139810
3rd row139810
4th row139818
5th row139810
ValueCountFrequency (%)
139708 608
 
9.6%
139200 408
 
6.5%
139842 383
 
6.1%
139865 379
 
6.0%
139050 344
 
5.4%
139220 265
 
4.2%
139826 251
 
4.0%
139926 236
 
3.7%
139822 233
 
3.7%
139712 199
 
3.1%
Other values (149) 3014
47.7%
2024-05-11T15:36:35.329541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7158
18.6%
9 7051
18.3%
3 7017
18.2%
8 4036
10.5%
0 3969
10.3%
2 3628
9.4%
6 1504
 
3.9%
7 1489
 
3.9%
5 1056
 
2.7%
4 1012
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37920
98.5%
Dash Punctuation 566
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7158
18.9%
9 7051
18.6%
3 7017
18.5%
8 4036
10.6%
0 3969
10.5%
2 3628
9.6%
6 1504
 
4.0%
7 1489
 
3.9%
5 1056
 
2.8%
4 1012
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 566
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38486
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7158
18.6%
9 7051
18.3%
3 7017
18.2%
8 4036
10.5%
0 3969
10.3%
2 3628
9.4%
6 1504
 
3.9%
7 1489
 
3.9%
5 1056
 
2.7%
4 1012
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7158
18.6%
9 7051
18.3%
3 7017
18.2%
8 4036
10.5%
0 3969
10.3%
2 3628
9.4%
6 1504
 
3.9%
7 1489
 
3.9%
5 1056
 
2.7%
4 1012
 
2.6%

지번주소
Text

MISSING 

Distinct2098
Distinct (%)33.2%
Missing165
Missing (%)2.5%
Memory size50.8 KiB
2024-05-11T15:36:35.982860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length24.721994
Min length17

Characters and Unicode

Total characters156243
Distinct characters317
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

Unique1742 ?
Unique (%)27.6%

Sample

1st row서울특별시 노원구 상계동 95-3
2nd row서울특별시 노원구 상계동 95-3
3rd row서울특별시 노원구 상계동 95-3
4th row서울특별시 노원구 상계동 389-234
5th row서울특별시 노원구 상계동 101-37
ValueCountFrequency (%)
서울특별시 6318
19.9%
노원구 6317
19.9%
상계동 2518
 
7.9%
중계동 1811
 
5.7%
월계동 1021
 
3.2%
713 1011
 
3.2%
333-1 746
 
2.4%
롯데백화점 692
 
2.2%
하계동 500
 
1.6%
지하1층 496
 
1.6%
Other values (1974) 10308
32.5%
2024-05-11T15:36:36.918243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30664
19.6%
6780
 
4.3%
6549
 
4.2%
6463
 
4.1%
6398
 
4.1%
6397
 
4.1%
6378
 
4.1%
6339
 
4.1%
6326
 
4.0%
6318
 
4.0%
Other values (307) 67631
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94672
60.6%
Space Separator 30664
 
19.6%
Decimal Number 26746
 
17.1%
Dash Punctuation 3148
 
2.0%
Uppercase Letter 272
 
0.2%
Open Punctuation 261
 
0.2%
Close Punctuation 261
 
0.2%
Other Punctuation 204
 
0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6780
 
7.2%
6549
 
6.9%
6463
 
6.8%
6398
 
6.8%
6397
 
6.8%
6378
 
6.7%
6339
 
6.7%
6326
 
6.7%
6318
 
6.7%
6318
 
6.7%
Other values (279) 30406
32.1%
Decimal Number
ValueCountFrequency (%)
1 6287
23.5%
3 4824
18.0%
2 2394
 
9.0%
5 2217
 
8.3%
7 2069
 
7.7%
0 2063
 
7.7%
4 1847
 
6.9%
6 1817
 
6.8%
9 1699
 
6.4%
8 1529
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
G 99
36.4%
S 94
34.6%
B 57
21.0%
A 11
 
4.0%
L 6
 
2.2%
N 2
 
0.7%
D 2
 
0.7%
K 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 125
61.3%
@ 76
37.3%
. 2
 
1.0%
/ 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
s 8
53.3%
g 7
46.7%
Space Separator
ValueCountFrequency (%)
30664
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3148
100.0%
Open Punctuation
ValueCountFrequency (%)
( 261
100.0%
Close Punctuation
ValueCountFrequency (%)
) 261
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94672
60.6%
Common 61284
39.2%
Latin 287
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6780
 
7.2%
6549
 
6.9%
6463
 
6.8%
6398
 
6.8%
6397
 
6.8%
6378
 
6.7%
6339
 
6.7%
6326
 
6.7%
6318
 
6.7%
6318
 
6.7%
Other values (279) 30406
32.1%
Common
ValueCountFrequency (%)
30664
50.0%
1 6287
 
10.3%
3 4824
 
7.9%
- 3148
 
5.1%
2 2394
 
3.9%
5 2217
 
3.6%
7 2069
 
3.4%
0 2063
 
3.4%
4 1847
 
3.0%
6 1817
 
3.0%
Other values (8) 3954
 
6.5%
Latin
ValueCountFrequency (%)
G 99
34.5%
S 94
32.8%
B 57
19.9%
A 11
 
3.8%
s 8
 
2.8%
g 7
 
2.4%
L 6
 
2.1%
N 2
 
0.7%
D 2
 
0.7%
K 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94672
60.6%
ASCII 61571
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30664
49.8%
1 6287
 
10.2%
3 4824
 
7.8%
- 3148
 
5.1%
2 2394
 
3.9%
5 2217
 
3.6%
7 2069
 
3.4%
0 2063
 
3.4%
4 1847
 
3.0%
6 1817
 
3.0%
Other values (18) 4241
 
6.9%
Hangul
ValueCountFrequency (%)
6780
 
7.2%
6549
 
6.9%
6463
 
6.8%
6398
 
6.8%
6397
 
6.8%
6378
 
6.7%
6339
 
6.7%
6326
 
6.7%
6318
 
6.7%
6318
 
6.7%
Other values (279) 30406
32.1%

도로명주소
Text

MISSING 

Distinct1995
Distinct (%)45.9%
Missing2138
Missing (%)33.0%
Memory size50.8 KiB
2024-05-11T15:36:37.285654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length62
Mean length36.00253
Min length21

Characters and Unicode

Total characters156503
Distinct characters326
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

Unique1673 ?
Unique (%)38.5%

Sample

1st row서울특별시 노원구 덕릉로115길 3, 1층 (상계동)
2nd row서울특별시 노원구 석계로11길 14 (월계동, 지상1층)
3rd row서울특별시 노원구 공릉로34길 14 (공릉동)
4th row서울특별시 노원구 석계로7길 7 (월계동)
5th row서울특별시 노원구 동일로180길 40, 1층 (공릉동)
ValueCountFrequency (%)
서울특별시 4345
 
14.3%
노원구 4344
 
14.3%
상계동 1756
 
5.8%
동일로 1277
 
4.2%
중계동 1065
 
3.5%
1층 965
 
3.2%
월계동 826
 
2.7%
지하1층 800
 
2.6%
1414 777
 
2.6%
롯데백화점 727
 
2.4%
Other values (1720) 13436
44.3%
2024-05-11T15:36:38.064671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25989
 
16.6%
1 7472
 
4.8%
6676
 
4.3%
5729
 
3.7%
4909
 
3.1%
4900
 
3.1%
, 4791
 
3.1%
4494
 
2.9%
4477
 
2.9%
) 4471
 
2.9%
Other values (316) 82595
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94484
60.4%
Space Separator 25989
 
16.6%
Decimal Number 21643
 
13.8%
Other Punctuation 4800
 
3.1%
Close Punctuation 4471
 
2.9%
Open Punctuation 4471
 
2.9%
Uppercase Letter 320
 
0.2%
Dash Punctuation 279
 
0.2%
Lowercase Letter 39
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6676
 
7.1%
5729
 
6.1%
4909
 
5.2%
4900
 
5.2%
4494
 
4.8%
4477
 
4.7%
4392
 
4.6%
4374
 
4.6%
4353
 
4.6%
4345
 
4.6%
Other values (286) 45835
48.5%
Decimal Number
ValueCountFrequency (%)
1 7472
34.5%
4 2970
 
13.7%
3 2481
 
11.5%
2 2325
 
10.7%
0 1774
 
8.2%
5 1567
 
7.2%
7 1054
 
4.9%
8 733
 
3.4%
6 731
 
3.4%
9 536
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
S 108
33.8%
G 107
33.4%
B 84
26.2%
A 15
 
4.7%
D 2
 
0.6%
I 1
 
0.3%
K 1
 
0.3%
C 1
 
0.3%
L 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 4791
99.8%
@ 7
 
0.1%
. 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
g 19
48.7%
s 19
48.7%
b 1
 
2.6%
Space Separator
ValueCountFrequency (%)
25989
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4471
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94484
60.4%
Common 61660
39.4%
Latin 359
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6676
 
7.1%
5729
 
6.1%
4909
 
5.2%
4900
 
5.2%
4494
 
4.8%
4477
 
4.7%
4392
 
4.6%
4374
 
4.6%
4353
 
4.6%
4345
 
4.6%
Other values (286) 45835
48.5%
Common
ValueCountFrequency (%)
25989
42.1%
1 7472
 
12.1%
, 4791
 
7.8%
) 4471
 
7.3%
( 4471
 
7.3%
4 2970
 
4.8%
3 2481
 
4.0%
2 2325
 
3.8%
0 1774
 
2.9%
5 1567
 
2.5%
Other values (8) 3349
 
5.4%
Latin
ValueCountFrequency (%)
S 108
30.1%
G 107
29.8%
B 84
23.4%
g 19
 
5.3%
s 19
 
5.3%
A 15
 
4.2%
D 2
 
0.6%
I 1
 
0.3%
b 1
 
0.3%
K 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94484
60.4%
ASCII 62019
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25989
41.9%
1 7472
 
12.0%
, 4791
 
7.7%
) 4471
 
7.2%
( 4471
 
7.2%
4 2970
 
4.8%
3 2481
 
4.0%
2 2325
 
3.7%
0 1774
 
2.9%
5 1567
 
2.5%
Other values (20) 3708
 
6.0%
Hangul
ValueCountFrequency (%)
6676
 
7.1%
5729
 
6.1%
4909
 
5.2%
4900
 
5.2%
4494
 
4.8%
4477
 
4.7%
4392
 
4.6%
4374
 
4.6%
4353
 
4.6%
4345
 
4.6%
Other values (286) 45835
48.5%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct221
Distinct (%)5.1%
Missing2175
Missing (%)33.5%
Infinite0
Infinite (%)0.0%
Mean1784.0842
Minimum1600
Maximum52683
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2024-05-11T15:36:38.458349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1600
5-th percentile1634.45
Q11695
median1746
Q31827
95-th percentile1906
Maximum52683
Range51083
Interquartile range (IQR)132

Descriptive statistics

Standard deviation1036.3054
Coefficient of variation (CV)0.58086127
Kurtosis2156.3987
Mean1784.0842
Median Absolute Deviation (MAD)51
Skewness46.186422
Sum7689403
Variance1073928.9
MonotonicityNot monotonic
2024-05-11T15:36:38.723031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1695 779
 
12.0%
1906 635
 
9.8%
1783 418
 
6.4%
1784 263
 
4.1%
1746 244
 
3.8%
1674 191
 
2.9%
1678 156
 
2.4%
1760 82
 
1.3%
1827 80
 
1.2%
1726 75
 
1.2%
Other values (211) 1387
21.4%
(Missing) 2175
33.5%
ValueCountFrequency (%)
1600 2
 
< 0.1%
1601 1
 
< 0.1%
1603 1
 
< 0.1%
1604 5
0.1%
1606 11
0.2%
1607 2
 
< 0.1%
1608 9
0.1%
1609 4
 
0.1%
1610 3
 
< 0.1%
1611 5
0.1%
ValueCountFrequency (%)
52683 1
 
< 0.1%
46519 1
 
< 0.1%
2555 1
 
< 0.1%
1914 5
 
0.1%
1913 43
 
0.7%
1911 3
 
< 0.1%
1910 1
 
< 0.1%
1909 37
 
0.6%
1906 635
9.8%
1905 2
 
< 0.1%
Distinct3385
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
2024-05-11T15:36:39.156918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length6.8232845
Min length1

Characters and Unicode

Total characters44249
Distinct characters751
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2599 ?
Unique (%)40.1%

Sample

1st row서울기름집
2nd row충남기름집
3rd row상주기름집
4th row중앙기름집
5th row한일기름집
ValueCountFrequency (%)
주식회사 376
 
4.8%
마켓인 69
 
0.9%
주)인네이처 67
 
0.9%
주)행복생활건강 46
 
0.6%
주)명류당티에프 41
 
0.5%
농업회사법인 41
 
0.5%
월드푸드 40
 
0.5%
다우 40
 
0.5%
신한성식품 38
 
0.5%
남도장터(주 32
 
0.4%
Other values (3578) 7020
89.9%
2024-05-11T15:36:39.748028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2356
 
5.3%
) 2015
 
4.6%
( 1998
 
4.5%
1327
 
3.0%
1021
 
2.3%
961
 
2.2%
854
 
1.9%
828
 
1.9%
791
 
1.8%
759
 
1.7%
Other values (741) 31339
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37584
84.9%
Close Punctuation 2015
 
4.6%
Open Punctuation 1998
 
4.5%
Space Separator 1327
 
3.0%
Dash Punctuation 542
 
1.2%
Lowercase Letter 294
 
0.7%
Uppercase Letter 276
 
0.6%
Other Punctuation 115
 
0.3%
Decimal Number 95
 
0.2%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2356
 
6.3%
1021
 
2.7%
961
 
2.6%
854
 
2.3%
828
 
2.2%
791
 
2.1%
759
 
2.0%
705
 
1.9%
699
 
1.9%
622
 
1.7%
Other values (673) 27988
74.5%
Lowercase Letter
ValueCountFrequency (%)
e 42
14.3%
o 23
 
7.8%
a 23
 
7.8%
t 20
 
6.8%
n 20
 
6.8%
h 20
 
6.8%
m 20
 
6.8%
r 15
 
5.1%
l 14
 
4.8%
s 13
 
4.4%
Other values (14) 84
28.6%
Uppercase Letter
ValueCountFrequency (%)
H 45
16.3%
D 32
11.6%
S 28
 
10.1%
M 27
 
9.8%
L 12
 
4.3%
O 12
 
4.3%
G 12
 
4.3%
K 12
 
4.3%
N 11
 
4.0%
F 10
 
3.6%
Other values (12) 75
27.2%
Decimal Number
ValueCountFrequency (%)
1 28
29.5%
2 22
23.2%
5 7
 
7.4%
3 7
 
7.4%
7 6
 
6.3%
8 6
 
6.3%
4 5
 
5.3%
0 5
 
5.3%
9 5
 
5.3%
6 4
 
4.2%
Other Punctuation
ValueCountFrequency (%)
& 74
64.3%
. 22
 
19.1%
, 9
 
7.8%
? 7
 
6.1%
' 3
 
2.6%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 2015
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1998
100.0%
Space Separator
ValueCountFrequency (%)
1327
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 542
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37581
84.9%
Common 6095
 
13.8%
Latin 570
 
1.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2356
 
6.3%
1021
 
2.7%
961
 
2.6%
854
 
2.3%
828
 
2.2%
791
 
2.1%
759
 
2.0%
705
 
1.9%
699
 
1.9%
622
 
1.7%
Other values (671) 27985
74.5%
Latin
ValueCountFrequency (%)
H 45
 
7.9%
e 42
 
7.4%
D 32
 
5.6%
S 28
 
4.9%
M 27
 
4.7%
o 23
 
4.0%
a 23
 
4.0%
t 20
 
3.5%
n 20
 
3.5%
h 20
 
3.5%
Other values (36) 290
50.9%
Common
ValueCountFrequency (%)
) 2015
33.1%
( 1998
32.8%
1327
21.8%
- 542
 
8.9%
& 74
 
1.2%
1 28
 
0.5%
2 22
 
0.4%
. 22
 
0.4%
, 9
 
0.1%
5 7
 
0.1%
Other values (12) 51
 
0.8%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37581
84.9%
ASCII 6665
 
15.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2356
 
6.3%
1021
 
2.7%
961
 
2.6%
854
 
2.3%
828
 
2.2%
791
 
2.1%
759
 
2.0%
705
 
1.9%
699
 
1.9%
622
 
1.7%
Other values (671) 27985
74.5%
ASCII
ValueCountFrequency (%)
) 2015
30.2%
( 1998
30.0%
1327
19.9%
- 542
 
8.1%
& 74
 
1.1%
H 45
 
0.7%
e 42
 
0.6%
D 32
 
0.5%
1 28
 
0.4%
S 28
 
0.4%
Other values (58) 534
 
8.0%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%
Distinct4424
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
Minimum1999-06-12 00:00:00
Maximum2024-05-09 04:15:09
2024-05-11T15:36:39.981112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:40.215334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
I
4035 
U
2450 

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 4035
62.2%
U 2450
37.8%

Length

2024-05-11T15:36:40.483871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:40.669163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4035
62.2%
u 2450
37.8%
Distinct1316
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:36:40.838104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:36:41.085288image/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 size50.8 KiB
즉석판매제조가공업
6485 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 6485
100.0%

Length

2024-05-11T15:36:41.293770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:41.855502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 6485
100.0%

좌표정보(X)
Real number (ℝ)

MISSING  SKEWED 

Distinct872
Distinct (%)13.6%
Missing88
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean205842.88
Minimum203721.87
Maximum382983.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2024-05-11T15:36:42.073228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203721.87
5-th percentile204985.15
Q1205320.28
median205715.54
Q3206132.43
95-th percentile207062.47
Maximum382983.92
Range179262.05
Interquartile range (IQR)812.14773

Descriptive statistics

Standard deviation2572.0538
Coefficient of variation (CV)0.012495228
Kurtosis3781.4493
Mean205842.88
Median Absolute Deviation (MAD)395.25417
Skewness58.407459
Sum1.3167769 × 109
Variance6615460.6
MonotonicityNot monotonic
2024-05-11T15:36:42.491678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205320.28476675 1021
15.7%
205391.070378059 780
 
12.0%
205985.953324881 435
 
6.7%
205994.811815848 389
 
6.0%
205715.538939251 345
 
5.3%
206132.432496938 262
 
4.0%
206204.445134058 259
 
4.0%
205931.05327036 248
 
3.8%
205039.222100248 228
 
3.5%
207311.175792021 88
 
1.4%
Other values (862) 2342
36.1%
(Missing) 88
 
1.4%
ValueCountFrequency (%)
203721.865206618 1
 
< 0.1%
203809.293429767 1
 
< 0.1%
203839.989956111 2
 
< 0.1%
203904.660962669 1
 
< 0.1%
203920.396022963 1
 
< 0.1%
203920.549325193 1
 
< 0.1%
204081.282117393 1
 
< 0.1%
204325.989587591 6
0.1%
204360.413814457 4
0.1%
204415.700533907 1
 
< 0.1%
ValueCountFrequency (%)
382983.91775577 1
 
< 0.1%
298496.244248698 1
 
< 0.1%
209221.923150049 1
 
< 0.1%
208582.845949263 1
 
< 0.1%
208223.756335908 1
 
< 0.1%
208149.544920696 1
 
< 0.1%
207892.695157902 1
 
< 0.1%
207831.44934045 1
 
< 0.1%
207827.752843377 1
 
< 0.1%
207577.515810212 18
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING  SKEWED 

Distinct872
Distinct (%)13.6%
Missing88
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean460321.36
Minimum189144.04
Maximum465253.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.1 KiB
2024-05-11T15:36:42.733692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189144.04
5-th percentile457784.82
Q1459266.57
median460516.39
Q3461419.88
95-th percentile462654.89
Maximum465253.15
Range276109.11
Interquartile range (IQR)2153.3113

Descriptive statistics

Standard deviation5009.7934
Coefficient of variation (CV)0.010883252
Kurtosis2546.3202
Mean460321.36
Median Absolute Deviation (MAD)1013.7465
Skewness-47.67481
Sum2.9446758 × 109
Variance25098029
MonotonicityNot monotonic
2024-05-11T15:36:42.978784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461419.881795004 1021
15.7%
458333.989216339 780
 
12.0%
459730.43776924 435
 
6.7%
459502.645279682 389
 
6.0%
462416.211580109 345
 
5.3%
460549.311157153 262
 
4.0%
460466.440748874 259
 
4.0%
459884.197207567 248
 
3.8%
462624.307076651 228
 
3.5%
457610.711998051 88
 
1.4%
Other values (862) 2342
36.1%
(Missing) 88
 
1.4%
ValueCountFrequency (%)
189144.044742335 1
< 0.1%
196375.470354374 1
< 0.1%
453187.395154017 1
< 0.1%
456990.07335337 1
< 0.1%
457003.886641127 2
< 0.1%
457032.61474419 1
< 0.1%
457052.24147811 1
< 0.1%
457062.152187862 1
< 0.1%
457074.394607107 1
< 0.1%
457091.210036301 1
< 0.1%
ValueCountFrequency (%)
465253.152004 1
 
< 0.1%
465103.755134816 2
 
< 0.1%
464995.722147154 1
 
< 0.1%
464356.527197506 1
 
< 0.1%
464346.663669239 2
 
< 0.1%
464208.305428933 1
 
< 0.1%
464199.048415229 3
< 0.1%
464080.593904719 5
0.1%
464047.73248518 1
 
< 0.1%
464044.481993 1
 
< 0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
즉석판매제조가공업
5567 
<NA>
918 

Length

Max length9
Median length9
Mean length8.2922128
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 5567
85.8%
<NA> 918
 
14.2%

Length

2024-05-11T15:36:43.228967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:43.423823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 5567
85.8%
na 918
 
14.2%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6101 
0
 
344
1
 
33
2
 
6
3
 
1

Length

Max length4
Median length4
Mean length3.8223593
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6101
94.1%
0 344
 
5.3%
1 33
 
0.5%
2 6
 
0.1%
3 1
 
< 0.1%

Length

2024-05-11T15:36:43.623020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:43.819866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6101
94.1%
0 344
 
5.3%
1 33
 
0.5%
2 6
 
0.1%
3 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6114 
0
 
341
1
 
28
2
 
2

Length

Max length4
Median length4
Mean length3.8283732
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> 6114
94.3%
0 341
 
5.3%
1 28
 
0.4%
2 2
 
< 0.1%

Length

2024-05-11T15:36:44.072462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:44.284727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6114
94.3%
0 341
 
5.3%
1 28
 
0.4%
2 2
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6317 
아파트지역
 
83
주택가주변
 
49
기타
 
33
유흥업소밀집지역
 
3

Length

Max length8
Median length4
Mean length4.0120278
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> 6317
97.4%
아파트지역 83
 
1.3%
주택가주변 49
 
0.8%
기타 33
 
0.5%
유흥업소밀집지역 3
 
< 0.1%

Length

2024-05-11T15:36:44.761211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:45.057213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6317
97.4%
아파트지역 83
 
1.3%
주택가주변 49
 
0.8%
기타 33
 
0.5%
유흥업소밀집지역 3
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6317 
기타
 
124
 
27
자율
 
16
우수
 
1

Length

Max length4
Median length4
Mean length3.9440247
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6317
97.4%
기타 124
 
1.9%
27
 
0.4%
자율 16
 
0.2%
우수 1
 
< 0.1%

Length

2024-05-11T15:36:45.350886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:45.582163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6317
97.4%
기타 124
 
1.9%
27
 
0.4%
자율 16
 
0.2%
우수 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6228 
상수도전용
 
257

Length

Max length5
Median length4
Mean length4.0396299
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> 6228
96.0%
상수도전용 257
 
4.0%

Length

2024-05-11T15:36:45.855224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:46.097878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6228
96.0%
상수도전용 257
 
4.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
6203 
0
 
282

Length

Max length4
Median length4
Mean length3.8695451
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> 6203
95.7%
0 282
 
4.3%

Length

2024-05-11T15:36:46.335805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:46.605121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6203
95.7%
0 282
 
4.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
4817 
0
1668 

Length

Max length4
Median length4
Mean length3.2283732
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4817
74.3%
0 1668
 
25.7%

Length

2024-05-11T15:36:46.900851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:47.188174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4817
74.3%
0 1668
 
25.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
4817 
0
1668 

Length

Max length4
Median length4
Mean length3.2283732
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4817
74.3%
0 1668
 
25.7%

Length

2024-05-11T15:36:47.547627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:47.804535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4817
74.3%
0 1668
 
25.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
4746 
0
1658 
1
 
50
2
 
29
4
 
1

Length

Max length4
Median length4
Mean length3.1955281
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4746
73.2%
0 1658
 
25.6%
1 50
 
0.8%
2 29
 
0.4%
4 1
 
< 0.1%
3 1
 
< 0.1%

Length

2024-05-11T15:36:48.072109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:48.303485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4746
73.2%
0 1658
 
25.6%
1 50
 
0.8%
2 29
 
0.4%
4 1
 
< 0.1%
3 1
 
< 0.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
4772 
0
1660 
1
 
46
2
 
7

Length

Max length4
Median length4
Mean length3.2075559
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4772
73.6%
0 1660
 
25.6%
1 46
 
0.7%
2 7
 
0.1%

Length

2024-05-11T15:36:48.558390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:48.793504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4772
73.6%
0 1660
 
25.6%
1 46
 
0.7%
2 7
 
0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
4284 
자가
1757 
임대
444 

Length

Max length4
Median length4
Mean length3.3212028
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> 4284
66.1%
자가 1757
27.1%
임대 444
 
6.8%

Length

2024-05-11T15:36:49.042035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:49.293444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4284
66.1%
자가 1757
27.1%
임대 444
 
6.8%

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
5246 
0
1239 

Length

Max length4
Median length4
Mean length3.4268311
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> 5246
80.9%
0 1239
 
19.1%

Length

2024-05-11T15:36:49.538446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:49.768803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5246
80.9%
0 1239
 
19.1%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
<NA>
5246 
0
1239 

Length

Max length4
Median length4
Mean length3.4268311
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> 5246
80.9%
0 1239
 
19.1%

Length

2024-05-11T15:36:50.009850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:50.231817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5246
80.9%
0 1239
 
19.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing918
Missing (%)14.2%
Memory size12.8 KiB
False
5567 
(Missing)
918 
ValueCountFrequency (%)
False 5567
85.8%
(Missing) 918
 
14.2%
2024-05-11T15:36:50.395781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size50.8 KiB
0.0
5563 
<NA>
918 
11.0
 
1
6.0
 
1
3.3
 
1

Length

Max length4
Median length3
Mean length3.1418658
Min length3

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 5563
85.8%
<NA> 918
 
14.2%
11.0 1
 
< 0.1%
6.0 1
 
< 0.1%
3.3 1
 
< 0.1%
22.0 1
 
< 0.1%

Length

2024-05-11T15:36:50.570310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:36:50.772238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 5563
85.8%
na 918
 
14.2%
11.0 1
 
< 0.1%
6.0 1
 
< 0.1%
3.3 1
 
< 0.1%
22.0 1
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6485
Missing (%)100.0%
Memory size57.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-107-1972-0000119720412<NA>3폐업2폐업19990329<NA><NA><NA>02 9388038<NA>139810서울특별시 노원구 상계동 95-3<NA><NA>서울기름집2001-11-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업206799.020098462509.638446즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131000003100000-107-1972-0000219720412<NA>3폐업2폐업20061122<NA><NA><NA>02 9361174<NA>139810서울특별시 노원구 상계동 95-3<NA><NA>충남기름집2001-11-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업206799.020098462509.638446즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
231000003100000-107-1972-0000319720413<NA>3폐업2폐업20120322<NA><NA><NA>02 9363019<NA>139810서울특별시 노원구 상계동 95-3<NA><NA>상주기름집2001-11-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업206799.020098462509.638446즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331000003100000-107-1973-0000119731019<NA>3폐업2폐업20060418<NA><NA><NA>02 9367040<NA>139818서울특별시 노원구 상계동 389-234<NA><NA>중앙기름집2001-11-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431000003100000-107-1975-0000119750904<NA>1영업/정상1영업<NA><NA><NA><NA>02 936604140.0139810서울특별시 노원구 상계동 101-37서울특별시 노원구 덕릉로115길 3, 1층 (상계동)1640한일기름집2017-08-07 10:04:34I2018-08-31 23:59:59.0즉석판매제조가공업206794.713591462685.175055즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531000003100000-107-1977-0000119771102<NA>1영업/정상1영업<NA><NA><NA><NA>02 905388527.35139841서울특별시 노원구 월계동 74-8 지상1층서울특별시 노원구 석계로11길 14 (월계동, 지상1층)1901인덕기름집2016-05-13 11:12:10I2018-08-31 23:59:59.0즉석판매제조가공업205538.013584457266.392183즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631000003100000-107-1977-0000219771111<NA>3폐업2폐업20060206<NA><NA><NA><NA><NA>139838서울특별시 노원구 상계동 1205<NA><NA>노원2002-01-18 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업204849.169789464995.722147즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731000003100000-107-1978-0000119780407<NA>3폐업2폐업19970429<NA><NA><NA>02 9362486<NA>139809서울특별시 노원구 상계동 49-3<NA><NA>제일기름집2001-11-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업207297.771717463238.582456즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
831000003100000-107-1981-000011981-04-21<NA>3폐업2폐업2023-11-13<NA><NA><NA>02 9769480<NA>139-800서울특별시 노원구 공릉동 240-20서울특별시 노원구 공릉로34길 14 (공릉동)1824충남기름집2023-11-13 11:32:39U2022-10-31 23:05:00.0즉석판매제조가공업206992.993644457796.651105<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
931000003100000-107-1981-0000219810618<NA>1영업/정상1영업<NA><NA><NA><NA>02 9433393<NA>139841서울특별시 노원구 월계동 68-64서울특별시 노원구 석계로7길 7 (월계동)1902상신2004-08-12 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업205575.790053457134.729724즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
647531000003100000-107-2024-001082024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-926서울특별시 노원구 중계동 509-2 홈플러스서울특별시 노원구 동일로204가길 12, 홈플러스 (중계동)1783주식회사 씨엔 줄리앙와플2024-04-30 16:11:24I2023-12-05 00:02:00.0즉석판매제조가공업205985.953325459730.437769<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
647631000003100000-107-2024-001092024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-708서울특별시 노원구 상계동 713 롯데백화점서울특별시 노원구 동일로 1414, 롯데백화점 지하1층 식품관호 (상계동)1695우진유통2024-04-30 16:50:23I2023-12-05 00:02:00.0즉석판매제조가공업205320.284767461419.881795<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
647731000003100000-107-2024-001102024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-920서울특별시 노원구 중계동 361 롯데마트서울특별시 노원구 노원로 330, 롯데마트 (중계동)1746주식회사 현승에프앤디2024-04-30 17:00:07I2023-12-05 00:02:00.0즉석판매제조가공업206204.445134460466.440749<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
647831000003100000-107-2024-001112024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-050서울특별시 노원구 월계동 333-1서울특별시 노원구 마들로3길 17, 1층 (월계동)1906제우스에프앤비2024-05-01 17:38:26I2023-12-05 00:03:00.0즉석판매제조가공업205391.070378458333.989216<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
647931000003100000-107-2024-001122024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-800서울특별시 노원구 공릉동 89-1 대덕프라자서울특별시 노원구 노원로1길 67, 1층 이마트에브리데이 공릉동점호 (공릉동)1827티제이푸드2024-05-02 10:37:35I2023-12-05 00:04:00.0즉석판매제조가공업207311.175792457610.711998<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
648031000003100000-107-2024-001132024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA>02 339980923.3139-726서울특별시 노원구 중계동 509 2001아울렛 일부호서울특별시 노원구 동일로204가길 46, 2001아울렛 지하1층 일부호 (중계동)1783킴스클럽 중계점2024-05-03 13:27:01I2023-12-05 00:05:00.0즉석판매제조가공업205931.05327459884.197208<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
648131000003100000-107-2024-001142024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA>032 519 8264<NA>139-708서울특별시 노원구 상계동 713 롯데백화점서울특별시 노원구 동일로 1414, 롯데백화점 지하1층 식품행사장호 (상계동)1695농업회사법인 주식회사 두영에프앤디2024-05-07 10:39:04I2023-12-05 00:09:00.0즉석판매제조가공업205320.284767461419.881795<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
648231000003100000-107-2024-001152024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 화랑빌딩서울특별시 노원구 동일로192길 63, 인근 행사장호 (공릉동)1841트위그 페스츄리(twig pastry)2024-05-07 11:37:49I2023-12-05 00:09:00.0즉석판매제조가공업206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
648331000003100000-107-2024-001162024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-810서울특별시 노원구 상계동 76-22 성우빌딩서울특별시 노원구 덕릉로 822, 성우빌딩 5층 일부호 (상계동)1644백두산천지인2024-05-08 15:03:02I2023-12-04 23:00:00.0즉석판매제조가공업207084.290989463046.677775<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
648431000003100000-107-2024-001172024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-240서울특별시 노원구 공릉동 389-9 화랑빌딩서울특별시 노원구 동일로192길 63, 인근 축제장 (공릉동)1841하오청2024-05-08 17:27:31I2023-12-04 23:00:00.0즉석판매제조가공업206659.512758458320.51828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>