Overview

Dataset statistics

Number of variables44
Number of observations3054
Missing cells31130
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 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-18237/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
데이터갱신구분 is highly imbalanced (56.7%)Imbalance
업태구분명 is highly imbalanced (99.6%)Imbalance
위생업태명 is highly imbalanced (71.7%)Imbalance
영업장주변구분명 is highly imbalanced (51.5%)Imbalance
등급구분명 is highly imbalanced (53.7%)Imbalance
급수시설구분명 is highly imbalanced (97.7%)Imbalance
총인원 is highly imbalanced (92.0%)Imbalance
건물소유구분명 is highly imbalanced (51.0%)Imbalance
보증액 is highly imbalanced (72.7%)Imbalance
월세액 is highly imbalanced (78.2%)Imbalance
시설총규모 is highly imbalanced (85.2%)Imbalance
인허가취소일자 has 3054 (100.0%) missing valuesMissing
폐업일자 has 342 (11.2%) missing valuesMissing
휴업시작일자 has 3054 (100.0%) missing valuesMissing
휴업종료일자 has 3054 (100.0%) missing valuesMissing
재개업일자 has 3054 (100.0%) missing valuesMissing
전화번호 has 620 (20.3%) missing valuesMissing
소재지면적 has 2873 (94.1%) missing valuesMissing
도로명주소 has 2416 (79.1%) missing valuesMissing
도로명우편번호 has 2426 (79.4%) missing valuesMissing
좌표정보(X) has 453 (14.8%) missing valuesMissing
좌표정보(Y) has 453 (14.8%) missing valuesMissing
다중이용업소여부 has 149 (4.9%) missing valuesMissing
전통업소지정번호 has 3054 (100.0%) missing valuesMissing
전통업소주된음식 has 3054 (100.0%) missing valuesMissing
홈페이지 has 3054 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 101 (3.3%) zerosZeros

Reproduction

Analysis started2024-05-11 07:01:52.070471
Analysis finished2024-05-11 07:01:54.326844
Duration2.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
3100000
3054 

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 3054
100.0%

Length

2024-05-11T16:01:54.448109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:54.625335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 3054
100.0%

관리번호
Text

UNIQUE 

Distinct3054
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2024-05-11T16:01:54.943341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters67188
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

Unique3054 ?
Unique (%)100.0%

Sample

1st row3100000-112-1983-00184
2nd row3100000-112-1985-00177
3rd row3100000-112-1985-00178
4th row3100000-112-1985-00179
5th row3100000-112-1985-00180
ValueCountFrequency (%)
3100000-112-1983-00184 1
 
< 0.1%
3100000-112-2003-00046 1
 
< 0.1%
3100000-112-2003-00083 1
 
< 0.1%
3100000-112-2003-00049 1
 
< 0.1%
3100000-112-2003-00039 1
 
< 0.1%
3100000-112-2003-00040 1
 
< 0.1%
3100000-112-2003-00041 1
 
< 0.1%
3100000-112-2003-00042 1
 
< 0.1%
3100000-112-2003-00043 1
 
< 0.1%
3100000-112-2003-00044 1
 
< 0.1%
Other values (3044) 3044
99.7%
2024-05-11T16:01:55.595560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24568
36.6%
1 13551
20.2%
- 9162
 
13.6%
2 5880
 
8.8%
9 5066
 
7.5%
3 4312
 
6.4%
4 1025
 
1.5%
5 1000
 
1.5%
8 901
 
1.3%
6 870
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58026
86.4%
Dash Punctuation 9162
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 24568
42.3%
1 13551
23.4%
2 5880
 
10.1%
9 5066
 
8.7%
3 4312
 
7.4%
4 1025
 
1.8%
5 1000
 
1.7%
8 901
 
1.6%
6 870
 
1.5%
7 853
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67188
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 24568
36.6%
1 13551
20.2%
- 9162
 
13.6%
2 5880
 
8.8%
9 5066
 
7.5%
3 4312
 
6.4%
4 1025
 
1.5%
5 1000
 
1.5%
8 901
 
1.3%
6 870
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 24568
36.6%
1 13551
20.2%
- 9162
 
13.6%
2 5880
 
8.8%
9 5066
 
7.5%
3 4312
 
6.4%
4 1025
 
1.5%
5 1000
 
1.5%
8 901
 
1.3%
6 870
 
1.3%

인허가일자
Date

Distinct1379
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
Minimum1983-12-14 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T16:01:55.897844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:56.182398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
3
2712 
1
342 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2712
88.8%
1 342
 
11.2%

Length

2024-05-11T16:01:56.443011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:56.611746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2712
88.8%
1 342
 
11.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
폐업
2712 
영업/정상
342 

Length

Max length5
Median length2
Mean length2.3359528
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2712
88.8%
영업/정상 342
 
11.2%

Length

2024-05-11T16:01:56.788249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:56.953758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2712
88.8%
영업/정상 342
 
11.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2
2712 
1
342 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 2712
88.8%
1 342
 
11.2%

Length

2024-05-11T16:01:57.133470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:57.334658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2712
88.8%
1 342
 
11.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
폐업
2712 
영업
342 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2712
88.8%
영업 342
 
11.2%

Length

2024-05-11T16:01:57.523483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:01:57.710257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2712
88.8%
영업 342
 
11.2%

폐업일자
Date

MISSING 

Distinct1655
Distinct (%)61.0%
Missing342
Missing (%)11.2%
Memory size24.0 KiB
Minimum1991-08-24 00:00:00
Maximum2024-02-26 00:00:00
2024-05-11T16:01:57.926382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:01:58.214678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

전화번호
Text

MISSING 

Distinct1456
Distinct (%)59.8%
Missing620
Missing (%)20.3%
Memory size24.0 KiB
2024-05-11T16:01:58.881240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.8118324
Min length2

Characters and Unicode

Total characters19014
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1386 ?
Unique (%)56.9%

Sample

1st row02
2nd row02
3rd row02
4th row02
5th row02
ValueCountFrequency (%)
02 1662
45.0%
0200000000 247
 
6.7%
0 58
 
1.6%
00000 35
 
0.9%
978 26
 
0.7%
4166416 22
 
0.6%
949 14
 
0.4%
9071378 9
 
0.2%
829 8
 
0.2%
0222128399 8
 
0.2%
Other values (1437) 1607
43.5%
2024-05-11T16:01:59.837583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5149
27.1%
2 2881
15.2%
9 2297
12.1%
3 1541
 
8.1%
1532
 
8.1%
7 1133
 
6.0%
1 1108
 
5.8%
5 874
 
4.6%
6 845
 
4.4%
4 837
 
4.4%
Other values (2) 817
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17480
91.9%
Space Separator 1532
 
8.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5149
29.5%
2 2881
16.5%
9 2297
13.1%
3 1541
 
8.8%
7 1133
 
6.5%
1 1108
 
6.3%
5 874
 
5.0%
6 845
 
4.8%
4 837
 
4.8%
8 815
 
4.7%
Space Separator
ValueCountFrequency (%)
1532
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19014
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5149
27.1%
2 2881
15.2%
9 2297
12.1%
3 1541
 
8.1%
1532
 
8.1%
7 1133
 
6.0%
1 1108
 
5.8%
5 874
 
4.6%
6 845
 
4.4%
4 837
 
4.4%
Other values (2) 817
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19014
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5149
27.1%
2 2881
15.2%
9 2297
12.1%
3 1541
 
8.1%
1532
 
8.1%
7 1133
 
6.0%
1 1108
 
5.8%
5 874
 
4.6%
6 845
 
4.4%
4 837
 
4.4%
Other values (2) 817
 
4.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct47
Distinct (%)26.0%
Missing2873
Missing (%)94.1%
Infinite0
Infinite (%)0.0%
Mean7.3201657
Minimum0
Maximum120.07
Zeros101
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size27.0 KiB
2024-05-11T16:02:00.164896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.3
95-th percentile37.21
Maximum120.07
Range120.07
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation15.749081
Coefficient of variation (CV)2.1514651
Kurtosis16.71911
Mean7.3201657
Median Absolute Deviation (MAD)0
Skewness3.476565
Sum1324.95
Variance248.03355
MonotonicityNot monotonic
2024-05-11T16:02:00.439240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 101
 
3.3%
3.3 17
 
0.6%
3.0 10
 
0.3%
1.0 6
 
0.2%
5.0 2
 
0.1%
2.0 2
 
0.1%
6.6 2
 
0.1%
30.0 2
 
0.1%
77.84 1
 
< 0.1%
30.24 1
 
< 0.1%
Other values (37) 37
 
1.2%
(Missing) 2873
94.1%
ValueCountFrequency (%)
0.0 101
3.3%
0.5 1
 
< 0.1%
1.0 6
 
0.2%
1.8 1
 
< 0.1%
2.0 2
 
0.1%
2.53 1
 
< 0.1%
3.0 10
 
0.3%
3.3 17
 
0.6%
3.6 1
 
< 0.1%
5.0 2
 
0.1%
ValueCountFrequency (%)
120.07 1
< 0.1%
77.84 1
< 0.1%
59.5 1
< 0.1%
53.9 1
< 0.1%
46.0 1
< 0.1%
44.45 1
< 0.1%
44.0 1
< 0.1%
40.0 1
< 0.1%
39.0 1
< 0.1%
37.21 1
< 0.1%

소재지우편번호
Text

Distinct155
Distinct (%)5.1%
Missing10
Missing (%)0.3%
Memory size24.0 KiB
2024-05-11T16:02:00.920609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0289093
Min length6

Characters and Unicode

Total characters18352
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

Unique50 ?
Unique (%)1.6%

Sample

1st row139240
2nd row139200
3rd row139200
4th row139200
5th row139200
ValueCountFrequency (%)
139240 258
 
8.5%
139200 177
 
5.8%
139800 156
 
5.1%
139816 137
 
4.5%
139837 117
 
3.8%
139808 88
 
2.9%
139846 86
 
2.8%
139810 85
 
2.8%
139942 73
 
2.4%
139230 72
 
2.4%
Other values (145) 1795
59.0%
2024-05-11T16:02:01.617815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3860
21.0%
3 3627
19.8%
9 3255
17.7%
8 2537
13.8%
0 1659
9.0%
2 1172
 
6.4%
4 818
 
4.5%
6 570
 
3.1%
5 384
 
2.1%
7 382
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18264
99.5%
Dash Punctuation 88
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3860
21.1%
3 3627
19.9%
9 3255
17.8%
8 2537
13.9%
0 1659
9.1%
2 1172
 
6.4%
4 818
 
4.5%
6 570
 
3.1%
5 384
 
2.1%
7 382
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3860
21.0%
3 3627
19.8%
9 3255
17.7%
8 2537
13.8%
0 1659
9.0%
2 1172
 
6.4%
4 818
 
4.5%
6 570
 
3.1%
5 384
 
2.1%
7 382
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3860
21.0%
3 3627
19.8%
9 3255
17.7%
8 2537
13.8%
0 1659
9.0%
2 1172
 
6.4%
4 818
 
4.5%
6 570
 
3.1%
5 384
 
2.1%
7 382
 
2.1%

지번주소
Text

Distinct2367
Distinct (%)77.8%
Missing10
Missing (%)0.3%
Memory size24.0 KiB
2024-05-11T16:02:02.369614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length40
Mean length23.112681
Min length14

Characters and Unicode

Total characters70355
Distinct characters367
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

Unique2010 ?
Unique (%)66.0%

Sample

1st row서울특별시 노원구 공릉동 366-15
2nd row서울특별시 노원구 상계동 611-1
3rd row서울특별시 노원구 상계동 611-1
4th row서울특별시 노원구 상계동 611-1
5th row서울특별시 노원구 상계동 611-1
ValueCountFrequency (%)
서울특별시 3044
21.9%
노원구 3044
21.9%
상계동 1352
 
9.7%
공릉동 634
 
4.6%
중계동 474
 
3.4%
월계동 425
 
3.1%
하계동 160
 
1.2%
산 87
 
0.6%
1층 53
 
0.4%
1동 43
 
0.3%
Other values (2658) 4590
33.0%
2024-05-11T16:02:03.272483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13666
19.4%
동 3254
 
4.6%
원 3163
 
4.5%
노 3105
 
4.4%
서 3082
 
4.4%
구 3077
 
4.4%
시 3074
 
4.4%
울 3065
 
4.4%
별 3045
 
4.3%
특 3044
 
4.3%
Other values (357) 28780
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39860
56.7%
Decimal Number 14019
 
19.9%
Space Separator 13666
 
19.4%
Dash Punctuation 2654
 
3.8%
Open Punctuation 45
 
0.1%
Close Punctuation 45
 
0.1%
Uppercase Letter 34
 
< 0.1%
Other Punctuation 31
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3254
 
8.2%
원 3163
 
7.9%
노 3105
 
7.8%
서 3082
 
7.7%
구 3077
 
7.7%
시 3074
 
7.7%
울 3065
 
7.7%
별 3045
 
7.6%
특 3044
 
7.6%
계 2498
 
6.3%
Other values (328) 9453
23.7%
Decimal Number
ValueCountFrequency (%)
1 2979
21.2%
0 1692
12.1%
3 1556
11.1%
2 1478
10.5%
6 1233
8.8%
7 1205
8.6%
4 1204
8.6%
5 1185
 
8.5%
9 755
 
5.4%
8 732
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 11
32.4%
A 7
20.6%
D 3
 
8.8%
P 2
 
5.9%
T 2
 
5.9%
L 2
 
5.9%
G 2
 
5.9%
C 2
 
5.9%
U 2
 
5.9%
E 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 22
71.0%
@ 4
 
12.9%
. 3
 
9.7%
/ 2
 
6.5%
Space Separator
ValueCountFrequency (%)
13666
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2654
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39860
56.7%
Common 30461
43.3%
Latin 34
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3254
 
8.2%
원 3163
 
7.9%
노 3105
 
7.8%
서 3082
 
7.7%
구 3077
 
7.7%
시 3074
 
7.7%
울 3065
 
7.7%
별 3045
 
7.6%
특 3044
 
7.6%
계 2498
 
6.3%
Other values (328) 9453
23.7%
Common
ValueCountFrequency (%)
13666
44.9%
1 2979
 
9.8%
- 2654
 
8.7%
0 1692
 
5.6%
3 1556
 
5.1%
2 1478
 
4.9%
6 1233
 
4.0%
7 1205
 
4.0%
4 1204
 
4.0%
5 1185
 
3.9%
Other values (9) 1609
 
5.3%
Latin
ValueCountFrequency (%)
B 11
32.4%
A 7
20.6%
D 3
 
8.8%
P 2
 
5.9%
T 2
 
5.9%
L 2
 
5.9%
G 2
 
5.9%
C 2
 
5.9%
U 2
 
5.9%
E 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39860
56.7%
ASCII 30495
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13666
44.8%
1 2979
 
9.8%
- 2654
 
8.7%
0 1692
 
5.5%
3 1556
 
5.1%
2 1478
 
4.8%
6 1233
 
4.0%
7 1205
 
4.0%
4 1204
 
3.9%
5 1185
 
3.9%
Other values (19) 1643
 
5.4%
Hangul
ValueCountFrequency (%)
동 3254
 
8.2%
원 3163
 
7.9%
노 3105
 
7.8%
서 3082
 
7.7%
구 3077
 
7.7%
시 3074
 
7.7%
울 3065
 
7.7%
별 3045
 
7.6%
특 3044
 
7.6%
계 2498
 
6.3%
Other values (328) 9453
23.7%

도로명주소
Text

MISSING 

Distinct598
Distinct (%)93.7%
Missing2416
Missing (%)79.1%
Memory size24.0 KiB
2024-05-11T16:02:03.823029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length47
Mean length31.915361
Min length22

Characters and Unicode

Total characters20362
Distinct characters281
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)89.2%

Sample

1st row서울특별시 노원구 동일로 1449 (상계동)
2nd row서울특별시 노원구 동일로 1449 (상계동)
3rd row서울특별시 노원구 동일로 1449 (상계동)
4th row서울특별시 노원구 동일로 1449 (상계동)
5th row서울특별시 노원구 동일로 1449 (상계동)
ValueCountFrequency (%)
서울특별시 638
 
16.3%
노원구 638
 
16.3%
상계동 241
 
6.2%
1층 126
 
3.2%
공릉동 111
 
2.8%
중계동 98
 
2.5%
동일로 90
 
2.3%
월계동 76
 
1.9%
한글비석로 45
 
1.2%
하계동 33
 
0.8%
Other values (886) 1814
46.4%
2024-05-11T16:02:04.762913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3273
 
16.1%
동 899
 
4.4%
1 862
 
4.2%
원 743
 
3.6%
노 733
 
3.6%
계 690
 
3.4%
서 652
 
3.2%
) 651
 
3.2%
( 651
 
3.2%
울 649
 
3.2%
Other values (271) 10559
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12002
58.9%
Space Separator 3273
 
16.1%
Decimal Number 3177
 
15.6%
Close Punctuation 651
 
3.2%
Open Punctuation 651
 
3.2%
Other Punctuation 521
 
2.6%
Dash Punctuation 57
 
0.3%
Uppercase Letter 30
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 899
 
7.5%
원 743
 
6.2%
노 733
 
6.1%
계 690
 
5.7%
서 652
 
5.4%
울 649
 
5.4%
구 645
 
5.4%
로 641
 
5.3%
시 641
 
5.3%
별 639
 
5.3%
Other values (245) 5070
42.2%
Decimal Number
ValueCountFrequency (%)
1 862
27.1%
2 466
14.7%
3 321
 
10.1%
4 307
 
9.7%
0 299
 
9.4%
5 215
 
6.8%
6 209
 
6.6%
7 192
 
6.0%
8 156
 
4.9%
9 150
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 7
23.3%
B 7
23.3%
U 3
10.0%
C 3
10.0%
S 3
10.0%
G 3
10.0%
E 1
 
3.3%
T 1
 
3.3%
P 1
 
3.3%
D 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 520
99.8%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3273
100.0%
Close Punctuation
ValueCountFrequency (%)
) 651
100.0%
Open Punctuation
ValueCountFrequency (%)
( 651
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12002
58.9%
Common 8330
40.9%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 899
 
7.5%
원 743
 
6.2%
노 733
 
6.1%
계 690
 
5.7%
서 652
 
5.4%
울 649
 
5.4%
구 645
 
5.4%
로 641
 
5.3%
시 641
 
5.3%
별 639
 
5.3%
Other values (245) 5070
42.2%
Common
ValueCountFrequency (%)
3273
39.3%
1 862
 
10.3%
) 651
 
7.8%
( 651
 
7.8%
, 520
 
6.2%
2 466
 
5.6%
3 321
 
3.9%
4 307
 
3.7%
0 299
 
3.6%
5 215
 
2.6%
Other values (6) 765
 
9.2%
Latin
ValueCountFrequency (%)
A 7
23.3%
B 7
23.3%
U 3
10.0%
C 3
10.0%
S 3
10.0%
G 3
10.0%
E 1
 
3.3%
T 1
 
3.3%
P 1
 
3.3%
D 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12002
58.9%
ASCII 8360
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3273
39.2%
1 862
 
10.3%
) 651
 
7.8%
( 651
 
7.8%
, 520
 
6.2%
2 466
 
5.6%
3 321
 
3.8%
4 307
 
3.7%
0 299
 
3.6%
5 215
 
2.6%
Other values (16) 795
 
9.5%
Hangul
ValueCountFrequency (%)
동 899
 
7.5%
원 743
 
6.2%
노 733
 
6.1%
계 690
 
5.7%
서 652
 
5.4%
울 649
 
5.4%
구 645
 
5.4%
로 641
 
5.3%
시 641
 
5.3%
별 639
 
5.3%
Other values (245) 5070
42.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct222
Distinct (%)35.4%
Missing2426
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean1752.7818
Minimum1600
Maximum1914
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.0 KiB
2024-05-11T16:02:04.992575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1600
5-th percentile1619
Q11684
median1745
Q31835
95-th percentile1898
Maximum1914
Range314
Interquartile range (IQR)151

Descriptive statistics

Standard deviation87.79806
Coefficient of variation (CV)0.050090695
Kurtosis-1.1442245
Mean1752.7818
Median Absolute Deviation (MAD)70.5
Skewness0.14441787
Sum1100747
Variance7708.4994
MonotonicityNot monotonic
2024-05-11T16:02:05.244562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1693 19
 
0.6%
1695 13
 
0.4%
1689 11
 
0.4%
1783 11
 
0.4%
1663 9
 
0.3%
1684 8
 
0.3%
1852 8
 
0.3%
1762 7
 
0.2%
1767 7
 
0.2%
1849 7
 
0.2%
Other values (212) 528
 
17.3%
(Missing) 2426
79.4%
ValueCountFrequency (%)
1600 1
 
< 0.1%
1601 2
 
0.1%
1602 1
 
< 0.1%
1604 2
 
0.1%
1605 1
 
< 0.1%
1606 7
0.2%
1607 1
 
< 0.1%
1608 3
0.1%
1610 1
 
< 0.1%
1611 1
 
< 0.1%
ValueCountFrequency (%)
1914 4
0.1%
1913 3
0.1%
1910 2
 
0.1%
1909 2
 
0.1%
1906 6
0.2%
1905 3
0.1%
1904 2
 
0.1%
1903 1
 
< 0.1%
1902 1
 
< 0.1%
1901 2
 
0.1%

사업장명
Text

Distinct2525
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
2024-05-11T16:02:05.742551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length5.4328749
Min length1

Characters and Unicode

Total characters16592
Distinct characters647
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2294 ?
Unique (%)75.1%

Sample

1st row최용운
2nd row경찰국장
3rd row경찰국장
4th row경찰국장
5th row경찰국장
ValueCountFrequency (%)
변동복 29
 
0.9%
오광열 29
 
0.9%
코카콜라 24
 
0.7%
정인재 22
 
0.7%
미도파백화점 18
 
0.5%
gs25 16
 
0.5%
정송밴딩 14
 
0.4%
카페 13
 
0.4%
씨유 13
 
0.4%
상계역 12
 
0.4%
Other values (2619) 3167
94.3%
2024-05-11T16:02:06.473681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 343
 
2.1%
점 335
 
2.0%
324
 
2.0%
계 307
 
1.9%
이 266
 
1.6%
상 259
 
1.6%
동 227
 
1.4%
퍼 193
 
1.2%
마 193
 
1.2%
지 186
 
1.1%
Other values (637) 13959
84.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15068
90.8%
Decimal Number 472
 
2.8%
Space Separator 324
 
2.0%
Uppercase Letter 323
 
1.9%
Close Punctuation 174
 
1.0%
Open Punctuation 173
 
1.0%
Lowercase Letter 34
 
0.2%
Other Punctuation 17
 
0.1%
Dash Punctuation 4
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 343
 
2.3%
점 335
 
2.2%
계 307
 
2.0%
이 266
 
1.8%
상 259
 
1.7%
동 227
 
1.5%
퍼 193
 
1.3%
마 193
 
1.3%
지 186
 
1.2%
김 180
 
1.2%
Other values (577) 12579
83.5%
Uppercase Letter
ValueCountFrequency (%)
S 76
23.5%
C 60
18.6%
G 57
17.6%
U 33
10.2%
P 26
 
8.0%
T 10
 
3.1%
K 8
 
2.5%
A 8
 
2.5%
M 8
 
2.5%
I 6
 
1.9%
Other values (13) 31
9.6%
Lowercase Letter
ValueCountFrequency (%)
e 5
14.7%
a 4
11.8%
f 4
11.8%
c 3
8.8%
n 3
8.8%
i 3
8.8%
s 3
8.8%
m 2
 
5.9%
k 2
 
5.9%
u 1
 
2.9%
Other values (4) 4
11.8%
Decimal Number
ValueCountFrequency (%)
2 142
30.1%
4 74
15.7%
5 72
15.3%
1 54
 
11.4%
7 47
 
10.0%
0 32
 
6.8%
3 21
 
4.4%
6 21
 
4.4%
9 5
 
1.1%
8 4
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 8
47.1%
, 5
29.4%
& 2
 
11.8%
# 1
 
5.9%
? 1
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 172
98.9%
] 2
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 171
98.8%
[ 2
 
1.2%
Space Separator
ValueCountFrequency (%)
324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15068
90.8%
Common 1167
 
7.0%
Latin 357
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 343
 
2.3%
점 335
 
2.2%
계 307
 
2.0%
이 266
 
1.8%
상 259
 
1.7%
동 227
 
1.5%
퍼 193
 
1.3%
마 193
 
1.3%
지 186
 
1.2%
김 180
 
1.2%
Other values (577) 12579
83.5%
Latin
ValueCountFrequency (%)
S 76
21.3%
C 60
16.8%
G 57
16.0%
U 33
9.2%
P 26
 
7.3%
T 10
 
2.8%
K 8
 
2.2%
A 8
 
2.2%
M 8
 
2.2%
I 6
 
1.7%
Other values (27) 65
18.2%
Common
ValueCountFrequency (%)
324
27.8%
) 172
14.7%
( 171
14.7%
2 142
12.2%
4 74
 
6.3%
5 72
 
6.2%
1 54
 
4.6%
7 47
 
4.0%
0 32
 
2.7%
3 21
 
1.8%
Other values (13) 58
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15067
90.8%
ASCII 1524
 
9.2%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 343
 
2.3%
점 335
 
2.2%
계 307
 
2.0%
이 266
 
1.8%
상 259
 
1.7%
동 227
 
1.5%
퍼 193
 
1.3%
마 193
 
1.3%
지 186
 
1.2%
김 180
 
1.2%
Other values (576) 12578
83.5%
ASCII
ValueCountFrequency (%)
324
21.3%
) 172
11.3%
( 171
11.2%
2 142
9.3%
S 76
 
5.0%
4 74
 
4.9%
5 72
 
4.7%
C 60
 
3.9%
G 57
 
3.7%
1 54
 
3.5%
Other values (50) 322
21.1%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
100.0%

최종수정일자
Date

Distinct1370
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
Minimum1999-01-04 00:00:00
Maximum2024-05-08 17:54:48
2024-05-11T16:02:06.741210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:02:07.004244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
I
2782 
U
 
272

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 2782
91.1%
U 272
 
8.9%

Length

2024-05-11T16:02:07.241342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:07.411086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2782
91.1%
u 272
 
8.9%

데이터갱신일자
Date

Distinct275
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:01:00
2024-05-11T16:02:07.597252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:02:07.814270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
식품자동판매기영업
3053 
<NA>
 
1

Length

Max length9
Median length9
Mean length8.9983628
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 3053
> 99.9%
<NA> 1
 
< 0.1%

Length

2024-05-11T16:02:08.366307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:08.537324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 3053
> 99.9%
na 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1397
Distinct (%)53.7%
Missing453
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean205988.11
Minimum203737.41
Maximum209288.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.0 KiB
2024-05-11T16:02:08.717195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203737.41
5-th percentile204718.53
Q1205307.79
median205994.81
Q3206658.44
95-th percentile207249.56
Maximum209288.47
Range5551.0632
Interquartile range (IQR)1350.6424

Descriptive statistics

Standard deviation854.89159
Coefficient of variation (CV)0.0041501988
Kurtosis-0.22898131
Mean205988.11
Median Absolute Deviation (MAD)674.52705
Skewness0.20599889
Sum5.3577507 × 108
Variance730839.63
MonotonicityNot monotonic
2024-05-11T16:02:08.939535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206981.454072644 48
 
1.6%
205320.28476675 34
 
1.1%
205198.498721037 33
 
1.1%
207192.873108421 26
 
0.9%
207033.517055516 25
 
0.8%
206280.789903642 22
 
0.7%
207918.320414714 21
 
0.7%
205645.891969072 14
 
0.5%
206960.872286183 14
 
0.5%
205984.15211292 13
 
0.4%
Other values (1387) 2351
77.0%
(Missing) 453
 
14.8%
ValueCountFrequency (%)
203737.409404091 1
< 0.1%
203786.584663472 1
< 0.1%
203798.287690402 2
0.1%
203802.357238897 1
< 0.1%
203809.293429767 2
0.1%
203839.989956111 2
0.1%
203857.946409231 1
< 0.1%
203904.660962669 1
< 0.1%
203920.396022963 1
< 0.1%
203920.549325193 2
0.1%
ValueCountFrequency (%)
209288.472624641 1
 
< 0.1%
209137.785636441 8
 
0.3%
208532.777004106 1
 
< 0.1%
208347.884966182 8
 
0.3%
208311.476758 1
 
< 0.1%
208258.296165225 1
 
< 0.1%
208236.117919423 1
 
< 0.1%
208039.14 1
 
< 0.1%
208032.453023926 1
 
< 0.1%
207918.320414714 21
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1397
Distinct (%)53.7%
Missing453
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean460412.27
Minimum456912.19
Maximum465103.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.0 KiB
2024-05-11T16:02:09.139426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456912.19
5-th percentile457361.43
Q1458452.73
median460895.26
Q3461986.01
95-th percentile463532.93
Maximum465103.76
Range8191.5659
Interquartile range (IQR)3533.2766

Descriptive statistics

Standard deviation2020.9771
Coefficient of variation (CV)0.0043894945
Kurtosis-1.2075499
Mean460412.27
Median Absolute Deviation (MAD)1719.0182
Skewness-0.064054622
Sum1.1975323 × 109
Variance4084348.5
MonotonicityNot monotonic
2024-05-11T16:02:09.337366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
458960.471391303 48
 
1.6%
461419.881795004 34
 
1.1%
457486.206509046 33
 
1.1%
458452.733971782 26
 
0.9%
458126.482303883 25
 
0.8%
462002.498987713 22
 
0.7%
458383.983421656 21
 
0.7%
459609.012509743 14
 
0.5%
458615.554432061 14
 
0.5%
457275.799282625 13
 
0.4%
Other values (1387) 2351
77.0%
(Missing) 453
 
14.8%
ValueCountFrequency (%)
456912.189269131 1
 
< 0.1%
456930.30571679 1
 
< 0.1%
456932.955961768 1
 
< 0.1%
456950.152059544 4
0.1%
456952.991044244 1
 
< 0.1%
456954.147370611 3
0.1%
456975.436848678 1
 
< 0.1%
456977.250021038 3
0.1%
456990.07335337 2
0.1%
456994.517426262 1
 
< 0.1%
ValueCountFrequency (%)
465103.755134816 1
 
< 0.1%
464995.722147154 2
 
0.1%
464984.088648704 1
 
< 0.1%
464959.058464501 1
 
< 0.1%
464917.553024908 1
 
< 0.1%
464819.128577763 1
 
< 0.1%
464650.949131666 1
 
< 0.1%
464589.376201942 1
 
< 0.1%
464508.952781941 5
0.2%
464502.030304529 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
식품자동판매기영업
2904 
<NA>
 
150

Length

Max length9
Median length9
Mean length8.7544204
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품자동판매기영업 2904
95.1%
<NA> 150
 
4.9%

Length

2024-05-11T16:02:09.512211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:09.630445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품자동판매기영업 2904
95.1%
na 150
 
4.9%

남성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
0
1822 
<NA>
1199 
1
 
33

Length

Max length4
Median length1
Mean length2.1777996
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1822
59.7%
<NA> 1199
39.3%
1 33
 
1.1%

Length

2024-05-11T16:02:09.770192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:09.922185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1822
59.7%
na 1199
39.3%
1 33
 
1.1%

여성종사자수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
0
1822 
<NA>
1199 
1
 
33

Length

Max length4
Median length1
Mean length2.1777996
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 1822
59.7%
<NA> 1199
39.3%
1 33
 
1.1%

Length

2024-05-11T16:02:10.077026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:10.243298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1822
59.7%
na 1199
39.3%
1 33
 
1.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
기타
1612 
<NA>
1144 
주택가주변
189 
아파트지역
 
102
유흥업소밀집지역
 
3
Other values (3)
 
4

Length

Max length8
Median length2
Mean length3.048461
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1612
52.8%
<NA> 1144
37.5%
주택가주변 189
 
6.2%
아파트지역 102
 
3.3%
유흥업소밀집지역 3
 
0.1%
학교정화(절대) 2
 
0.1%
학교정화(상대) 1
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

Length

2024-05-11T16:02:10.407639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:10.565123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1612
52.8%
na 1144
37.5%
주택가주변 189
 
6.2%
아파트지역 102
 
3.3%
유흥업소밀집지역 3
 
0.1%
학교정화(절대 2
 
0.1%
학교정화(상대 1
 
< 0.1%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
기타
1733 
<NA>
1144 
자율
 
133
지도
 
27
우수
 
9
Other values (2)
 
8

Length

Max length4
Median length2
Mean length2.7468893
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1733
56.7%
<NA> 1144
37.5%
자율 133
 
4.4%
지도 27
 
0.9%
우수 9
 
0.3%
갑 7
 
0.2%
관리 1
 
< 0.1%

Length

2024-05-11T16:02:10.719628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:10.911626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 1733
56.7%
na 1144
37.5%
자율 133
 
4.4%
지도 27
 
0.9%
우수 9
 
0.3%
갑 7
 
0.2%
관리 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
3047 
상수도전용
 
7

Length

Max length5
Median length4
Mean length4.0022921
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> 3047
99.8%
상수도전용 7
 
0.2%

Length

2024-05-11T16:02:11.146347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:11.309686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3047
99.8%
상수도전용 7
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
3024 
0
 
30

Length

Max length4
Median length4
Mean length3.9705305
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> 3024
99.0%
0 30
 
1.0%

Length

2024-05-11T16:02:11.481499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:11.650431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3024
99.0%
0 30
 
1.0%

본사종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2269 
0
785 

Length

Max length4
Median length4
Mean length3.2288802
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> 2269
74.3%
0 785
 
25.7%

Length

2024-05-11T16:02:11.809893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:11.954568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2269
74.3%
0 785
 
25.7%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2269 
0
785 

Length

Max length4
Median length4
Mean length3.2288802
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> 2269
74.3%
0 785
 
25.7%

Length

2024-05-11T16:02:12.095510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:12.245696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2269
74.3%
0 785
 
25.7%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2269 
0
784 
1
 
1

Length

Max length4
Median length4
Mean length3.2288802
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> 2269
74.3%
0 784
 
25.7%
1 1
 
< 0.1%

Length

2024-05-11T16:02:12.409263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:12.555063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2269
74.3%
0 784
 
25.7%
1 1
 
< 0.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2269 
0
785 

Length

Max length4
Median length4
Mean length3.2288802
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> 2269
74.3%
0 785
 
25.7%

Length

2024-05-11T16:02:12.684114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:12.825636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2269
74.3%
0 785
 
25.7%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2411 
자가
628 
임대
 
15

Length

Max length4
Median length4
Mean length3.5789129
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> 2411
78.9%
자가 628
 
20.6%
임대 15
 
0.5%

Length

2024-05-11T16:02:13.014021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:13.278664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2411
78.9%
자가 628
 
20.6%
임대 15
 
0.5%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2786 
0
 
267
10
 
1

Length

Max length4
Median length4
Mean length3.7370661
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> 2786
91.2%
0 267
 
8.7%
10 1
 
< 0.1%

Length

2024-05-11T16:02:13.596879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:13.839549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2786
91.2%
0 267
 
8.7%
10 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
<NA>
2785 
0
 
267
10
 
1
600000
 
1

Length

Max length6
Median length4
Mean length3.737721
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2785
91.2%
0 267
 
8.7%
10 1
 
< 0.1%
600000 1
 
< 0.1%

Length

2024-05-11T16:02:14.012512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:14.191913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2785
91.2%
0 267
 
8.7%
10 1
 
< 0.1%
600000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing149
Missing (%)4.9%
Memory size6.1 KiB
False
2905 
(Missing)
 
149
ValueCountFrequency (%)
False 2905
95.1%
(Missing) 149
 
4.9%
2024-05-11T16:02:14.340334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.0 KiB
0.0
2901 
<NA>
 
149
3.3
 
3
20.0
 
1

Length

Max length4
Median length3
Mean length3.0491159
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 2901
95.0%
<NA> 149
 
4.9%
3.3 3
 
0.1%
20.0 1
 
< 0.1%

Length

2024-05-11T16:02:14.486313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:02:14.642345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2901
95.0%
na 149
 
4.9%
3.3 3
 
0.1%
20.0 1
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3054
Missing (%)100.0%
Memory size27.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-112-1983-0018419831214<NA>3폐업2폐업20031110<NA><NA><NA>02<NA>139240서울특별시 노원구 공릉동 366-15<NA><NA>최용운2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206495.832721458493.11889식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131000003100000-112-1985-0017719850108<NA>1영업/정상1영업<NA><NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 611-1서울특별시 노원구 동일로 1449 (상계동)1688경찰국장2013-12-23 14:23:20I2018-08-31 23:59:59.0식품자동판매기영업205120.16182461503.265441식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231000003100000-112-1985-0017819850108<NA>1영업/정상1영업<NA><NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 611-1서울특별시 노원구 동일로 1449 (상계동)1688경찰국장2013-12-23 14:26:10I2018-08-31 23:59:59.0식품자동판매기영업205120.16182461503.265441식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331000003100000-112-1985-0017919850108<NA>1영업/정상1영업<NA><NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 611-1서울특별시 노원구 동일로 1449 (상계동)1688경찰국장2013-12-23 14:28:16I2018-08-31 23:59:59.0식품자동판매기영업205120.16182461503.265441식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431000003100000-112-1985-0018019850108<NA>1영업/정상1영업<NA><NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 611-1서울특별시 노원구 동일로 1449 (상계동)1688경찰국장2013-12-23 14:29:34I2018-08-31 23:59:59.0식품자동판매기영업205120.16182461503.265441식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531000003100000-112-1985-0018119850108<NA>1영업/정상1영업<NA><NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 611-1서울특별시 노원구 동일로 1449 (상계동)1688경찰국장2013-12-23 14:30:21I2018-08-31 23:59:59.0식품자동판매기영업205120.16182461503.265441식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631000003100000-112-1985-0018719850628<NA>3폐업2폐업20000125<NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 173-0<NA><NA>상계역지하철역2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206280.789904462002.498988식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731000003100000-112-1985-0018919850628<NA>3폐업2폐업19920610<NA><NA><NA>02<NA>139200서울특별시 노원구 상계동 173-0<NA><NA>심완조2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206280.789904462002.498988식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831000003100000-112-1985-0019019850628<NA>3폐업2폐업19931118<NA><NA><NA>02<NA>139816서울특별시 노원구 상계동 355-0<NA><NA>심완조2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업<NA><NA>식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931000003100000-112-1986-0018319860924<NA>3폐업2폐업19970829<NA><NA><NA>02 0<NA>139810서울특별시 노원구 상계동 95-3<NA><NA>박양숙2001-09-29 00:00:00I2018-08-31 23:59:59.0식품자동판매기영업206799.020098462509.638446식품자동판매기영업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
304431000003100000-112-2024-000072024-03-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0139-815서울특별시 노원구 상계동 169-489 대동속셈학원서울특별시 노원구 한글비석로 405, 대동속셈학원 1층 (상계동)1682메일빈 (mail bean)2024-03-12 15:16:04I2023-12-02 23:04:00.0식품자동판매기영업206202.140564462061.564496<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
304531000003100000-112-2024-000082024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.0139-816서울특별시 노원구 상계동 197-26 1층 우측호서울특별시 노원구 상계로12길 87, 1층 우측호 (상계동)1702커피 어때요2024-04-08 16:55:14I2023-12-03 23:00:00.0식품자동판매기영업206238.656561461401.080028<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
304631000003100000-112-2024-000092024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.0139-831서울특별시 노원구 상계동 764-1 하라프라자센타 1층 109호서울특별시 노원구 동일로 1323, 하라프라자센타 1층 109호 (상계동)1767위아원카페_메고지고 중계위너2024-04-23 16:40:12I2023-12-03 22:05:00.0식품자동판매기영업205457.289886460487.443376<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
304731000003100000-112-2024-000112024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0139-836서울특별시 노원구 상계동 994 명한빌딩서울특별시 노원구 동일로230길 31, 명한빌딩 102호 (상계동)1629데이롱 카페 상계중앙점2024-04-24 10:54:17I2023-12-03 22:06:00.0식품자동판매기영업205050.277653463253.973796<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
304831000003100000-112-2024-000122024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.06139-823서울특별시 노원구 상계동 652-1 평강교회서울특별시 노원구 동일로227길 43, 평강교회 104호 (상계동)1619카페일분 상계점2024-04-24 14:48:54I2023-12-03 22:06:00.0식품자동판매기영업204741.063719462734.253629<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
304931000003100000-112-2024-000132024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>139-838서울특별시 노원구 상계동 1253 수락고등학교서울특별시 노원구 동일로245길 143, 수락고등학교 1층 수라운지호 (상계동)1602정직한유통2024-04-29 11:43:51I2023-12-05 00:01:00.0식품자동판매기영업204637.502776464502.030305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
305031000003100000-112-2024-000142024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3139-865서울특별시 노원구 중계동 508 노원평생학습관서울특별시 노원구 동일로204길 13, 노원평생학습관 1층 (중계동)1783노원평생학습관 자판기2024-05-08 09:30:28I2023-12-04 23:00:00.0식품자동판매기영업205853.862931459752.225293<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
305131000003100000-112-2024-000152024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>120.07139-867서울특별시 노원구 중계동 599 극동의푸른별 2차아파트서울특별시 노원구 한글비석로14길 36, 상가동 1층 101호 (중계동, 극동의푸른별 2차아파트)1717티타임2024-05-08 11:02:12I2023-12-04 23:00:00.0식품자동판매기영업206755.874503461832.798437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
305231000003100000-112-2024-000162024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.88139-816서울특별시 노원구 상계동 177-86서울특별시 노원구 상계로12길 22, 1층 우측호 (상계동)1696밀라커피 상계점2024-05-08 16:25:50I2023-12-04 23:00:00.0식품자동판매기영업205995.482266461616.850137<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
305331000003100000-112-2024-000172024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.3139-848서울특별시 노원구 월계동 749-7서울특별시 노원구 마들로5길 89-27, 1층 (월계동)1866초안산캠핑장 매점카페2024-05-08 17:54:48I2023-12-04 23:00:00.0식품자동판매기영업204346.745711460050.142848<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>