Overview

Dataset statistics

Number of variables44
Number of observations524
Missing cells4717
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory192.0 KiB
Average record size in memory375.3 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18012/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (60.9%)Imbalance
영업장주변구분명 is highly imbalanced (55.6%)Imbalance
등급구분명 is highly imbalanced (52.5%)Imbalance
총인원 is highly imbalanced (81.3%)Imbalance
본사종업원수 is highly imbalanced (51.3%)Imbalance
공장사무직종업원수 is highly imbalanced (81.3%)Imbalance
공장판매직종업원수 is highly imbalanced (81.3%)Imbalance
공장생산직종업원수 is highly imbalanced (81.3%)Imbalance
건물소유구분명 is highly imbalanced (71.5%)Imbalance
인허가취소일자 has 524 (100.0%) missing valuesMissing
폐업일자 has 287 (54.8%) missing valuesMissing
휴업시작일자 has 524 (100.0%) missing valuesMissing
휴업종료일자 has 524 (100.0%) missing valuesMissing
재개업일자 has 524 (100.0%) missing valuesMissing
전화번호 has 57 (10.9%) missing valuesMissing
소재지면적 has 19 (3.6%) missing valuesMissing
도로명주소 has 70 (13.4%) missing valuesMissing
도로명우편번호 has 71 (13.5%) missing valuesMissing
좌표정보(X) has 7 (1.3%) missing valuesMissing
좌표정보(Y) has 7 (1.3%) missing valuesMissing
여성종사자수 has 401 (76.5%) missing valuesMissing
다중이용업소여부 has 63 (12.0%) missing valuesMissing
시설총규모 has 63 (12.0%) missing valuesMissing
전통업소지정번호 has 524 (100.0%) missing valuesMissing
전통업소주된음식 has 524 (100.0%) missing valuesMissing
홈페이지 has 524 (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
여성종사자수 has 90 (17.2%) zerosZeros
시설총규모 has 88 (16.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:27:51.875784
Analysis finished2024-05-11 05:27:53.348260
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
3100000
524 

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 524
100.0%

Length

2024-05-11T14:27:53.455265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:27:53.939978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 524
100.0%

관리번호
Text

UNIQUE 

Distinct524
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:27:54.191178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters11528
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

Unique524 ?
Unique (%)100.0%

Sample

1st row3100000-105-1972-00001
2nd row3100000-105-1973-00002
3rd row3100000-105-1976-00005
4th row3100000-105-1980-00012
5th row3100000-105-1984-00006
ValueCountFrequency (%)
3100000-105-1972-00001 1
 
0.2%
3100000-105-2013-00028 1
 
0.2%
3100000-105-2013-00026 1
 
0.2%
3100000-105-2013-00025 1
 
0.2%
3100000-105-2013-00024 1
 
0.2%
3100000-105-2013-00023 1
 
0.2%
3100000-105-2013-00022 1
 
0.2%
3100000-105-2013-00021 1
 
0.2%
3100000-105-2013-00020 1
 
0.2%
3100000-105-2013-00019 1
 
0.2%
Other values (514) 514
98.1%
2024-05-11T14:27:54.812806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5596
48.5%
1 1600
 
13.9%
- 1572
 
13.6%
5 699
 
6.1%
3 665
 
5.8%
2 602
 
5.2%
9 333
 
2.9%
8 135
 
1.2%
6 118
 
1.0%
7 106
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9956
86.4%
Dash Punctuation 1572
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5596
56.2%
1 1600
 
16.1%
5 699
 
7.0%
3 665
 
6.7%
2 602
 
6.0%
9 333
 
3.3%
8 135
 
1.4%
6 118
 
1.2%
7 106
 
1.1%
4 102
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11528
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5596
48.5%
1 1600
 
13.9%
- 1572
 
13.6%
5 699
 
6.1%
3 665
 
5.8%
2 602
 
5.2%
9 333
 
2.9%
8 135
 
1.2%
6 118
 
1.0%
7 106
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5596
48.5%
1 1600
 
13.9%
- 1572
 
13.6%
5 699
 
6.1%
3 665
 
5.8%
2 602
 
5.2%
9 333
 
2.9%
8 135
 
1.2%
6 118
 
1.0%
7 106
 
0.9%
Distinct441
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1972-12-13 00:00:00
Maximum2023-06-23 00:00:00
2024-05-11T14:27:55.045372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:27:55.262552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
1
287 
3
237 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 287
54.8%
3 237
45.2%

Length

2024-05-11T14:27:55.502970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:27:55.677439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 287
54.8%
3 237
45.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
영업/정상
287 
폐업
237 

Length

Max length5
Median length5
Mean length3.6431298
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 287
54.8%
폐업 237
45.2%

Length

2024-05-11T14:27:55.851254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:27:56.023839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 287
54.8%
폐업 237
45.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
1
287 
2
237 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 287
54.8%
2 237
45.2%

Length

2024-05-11T14:27:56.217191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:27:56.398352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 287
54.8%
2 237
45.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
영업
287 
폐업
237 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 287
54.8%
폐업 237
45.2%

Length

2024-05-11T14:27:56.576384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:27:56.754101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 287
54.8%
폐업 237
45.2%

폐업일자
Date

MISSING 

Distinct218
Distinct (%)92.0%
Missing287
Missing (%)54.8%
Memory size4.2 KiB
Minimum1997-05-06 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T14:27:56.980757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:27:57.227512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

전화번호
Text

MISSING 

Distinct444
Distinct (%)95.1%
Missing57
Missing (%)10.9%
Memory size4.2 KiB
2024-05-11T14:27:57.677600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.122056
Min length7

Characters and Unicode

Total characters4727
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

Unique423 ?
Unique (%)90.6%

Sample

1st row02 9396176
2nd row02 9392298
3rd row02 9700081
4th row02 9356000
5th row02 9742501
ValueCountFrequency (%)
02 336
37.2%
070 9
 
1.0%
970 7
 
0.8%
948 7
 
0.8%
932 5
 
0.6%
952 5
 
0.6%
9600 4
 
0.4%
930 4
 
0.4%
950 4
 
0.4%
937 4
 
0.4%
Other values (463) 518
57.4%
2024-05-11T14:27:58.396077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 817
17.3%
9 661
14.0%
2 643
13.6%
562
11.9%
3 453
9.6%
7 361
7.6%
1 284
 
6.0%
5 280
 
5.9%
8 229
 
4.8%
6 219
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4165
88.1%
Space Separator 562
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 817
19.6%
9 661
15.9%
2 643
15.4%
3 453
10.9%
7 361
8.7%
1 284
 
6.8%
5 280
 
6.7%
8 229
 
5.5%
6 219
 
5.3%
4 218
 
5.2%
Space Separator
ValueCountFrequency (%)
562
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4727
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 817
17.3%
9 661
14.0%
2 643
13.6%
562
11.9%
3 453
9.6%
7 361
7.6%
1 284
 
6.0%
5 280
 
5.9%
8 229
 
4.8%
6 219
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4727
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 817
17.3%
9 661
14.0%
2 643
13.6%
562
11.9%
3 453
9.6%
7 361
7.6%
1 284
 
6.0%
5 280
 
5.9%
8 229
 
4.8%
6 219
 
4.6%

소재지면적
Text

MISSING 

Distinct349
Distinct (%)69.1%
Missing19
Missing (%)3.6%
Memory size4.2 KiB
2024-05-11T14:27:59.015455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.980198
Min length3

Characters and Unicode

Total characters2515
Distinct characters12
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

Unique291 ?
Unique (%)57.6%

Sample

1st row56.40
2nd row12.90
3rd row191.70
4th row18.10
5th row336.16
ValueCountFrequency (%)
00 71
 
14.1%
0.00 11
 
2.2%
18.00 5
 
1.0%
19.80 4
 
0.8%
10.00 4
 
0.8%
16.50 4
 
0.8%
24.75 4
 
0.8%
9.11 3
 
0.6%
135.00 3
 
0.6%
33.00 3
 
0.6%
Other values (339) 393
77.8%
2024-05-11T14:27:59.913402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 601
23.9%
. 505
20.1%
1 285
11.3%
2 181
 
7.2%
5 158
 
6.3%
6 145
 
5.8%
4 141
 
5.6%
9 128
 
5.1%
8 123
 
4.9%
3 123
 
4.9%
Other values (2) 125
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2002
79.6%
Other Punctuation 513
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 601
30.0%
1 285
14.2%
2 181
 
9.0%
5 158
 
7.9%
6 145
 
7.2%
4 141
 
7.0%
9 128
 
6.4%
8 123
 
6.1%
3 123
 
6.1%
7 117
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 505
98.4%
, 8
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Common 2515
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 601
23.9%
. 505
20.1%
1 285
11.3%
2 181
 
7.2%
5 158
 
6.3%
6 145
 
5.8%
4 141
 
5.6%
9 128
 
5.1%
8 123
 
4.9%
3 123
 
4.9%
Other values (2) 125
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2515
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 601
23.9%
. 505
20.1%
1 285
11.3%
2 181
 
7.2%
5 158
 
6.3%
6 145
 
5.8%
4 141
 
5.6%
9 128
 
5.1%
8 123
 
4.9%
3 123
 
4.9%
Other values (2) 125
 
5.0%
Distinct99
Distinct (%)19.0%
Missing2
Missing (%)0.4%
Memory size4.2 KiB
2024-05-11T14:28:00.345345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0823755
Min length6

Characters and Unicode

Total characters3175
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

Unique27 ?
Unique (%)5.2%

Sample

1st row139836
2nd row139838
3rd row139800
4th row139812
5th row139-706
ValueCountFrequency (%)
139200 32
 
6.1%
139800 31
 
5.9%
139831 30
 
5.7%
139240 29
 
5.6%
139230 24
 
4.6%
139816 21
 
4.0%
139838 17
 
3.3%
139865 14
 
2.7%
139837 14
 
2.7%
139810 12
 
2.3%
Other values (89) 298
57.1%
2024-05-11T14:28:01.105476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 661
20.8%
1 635
20.0%
9 568
17.9%
8 423
13.3%
0 293
9.2%
2 177
 
5.6%
4 116
 
3.7%
6 96
 
3.0%
7 82
 
2.6%
5 81
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3132
98.6%
Dash Punctuation 43
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 661
21.1%
1 635
20.3%
9 568
18.1%
8 423
13.5%
0 293
9.4%
2 177
 
5.7%
4 116
 
3.7%
6 96
 
3.1%
7 82
 
2.6%
5 81
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 661
20.8%
1 635
20.0%
9 568
17.9%
8 423
13.3%
0 293
9.2%
2 177
 
5.6%
4 116
 
3.7%
6 96
 
3.0%
7 82
 
2.6%
5 81
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 661
20.8%
1 635
20.0%
9 568
17.9%
8 423
13.3%
0 293
9.2%
2 177
 
5.6%
4 116
 
3.7%
6 96
 
3.0%
7 82
 
2.6%
5 81
 
2.6%
Distinct444
Distinct (%)85.1%
Missing2
Missing (%)0.4%
Memory size4.2 KiB
2024-05-11T14:28:01.621751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length24.408046
Min length17

Characters and Unicode

Total characters12741
Distinct characters248
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

Unique393 ?
Unique (%)75.3%

Sample

1st row서울특별시 노원구 상계동 산 51번지
2nd row서울특별시 노원구 상계동 1266번지
3rd row서울특별시 노원구 공릉동 223-19번지
4th row서울특별시 노원구 상계동 110-8번지
5th row서울특별시 노원구 공릉동 215-4 한국원자력의학원
ValueCountFrequency (%)
서울특별시 522
22.0%
노원구 522
22.0%
상계동 210
 
8.8%
공릉동 110
 
4.6%
중계동 84
 
3.5%
월계동 71
 
3.0%
하계동 48
 
2.0%
2층 14
 
0.6%
126번지 12
 
0.5%
8
 
0.3%
Other values (578) 773
32.6%
2024-05-11T14:28:02.415565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2305
18.1%
576
 
4.5%
541
 
4.2%
540
 
4.2%
539
 
4.2%
539
 
4.2%
538
 
4.2%
527
 
4.1%
523
 
4.1%
523
 
4.1%
Other values (238) 5590
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7998
62.8%
Space Separator 2305
 
18.1%
Decimal Number 2105
 
16.5%
Dash Punctuation 308
 
2.4%
Other Punctuation 9
 
0.1%
Math Symbol 5
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
576
 
7.2%
541
 
6.8%
540
 
6.8%
539
 
6.7%
539
 
6.7%
538
 
6.7%
527
 
6.6%
523
 
6.5%
523
 
6.5%
464
 
5.8%
Other values (217) 2688
33.6%
Decimal Number
ValueCountFrequency (%)
1 424
20.1%
2 295
14.0%
3 212
10.1%
6 210
10.0%
7 195
9.3%
5 190
9.0%
0 185
8.8%
4 168
 
8.0%
8 128
 
6.1%
9 98
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
@ 2
 
22.2%
. 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
H 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
2305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 308
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7998
62.8%
Common 4740
37.2%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
576
 
7.2%
541
 
6.8%
540
 
6.8%
539
 
6.7%
539
 
6.7%
538
 
6.7%
527
 
6.6%
523
 
6.5%
523
 
6.5%
464
 
5.8%
Other values (217) 2688
33.6%
Common
ValueCountFrequency (%)
2305
48.6%
1 424
 
8.9%
- 308
 
6.5%
2 295
 
6.2%
3 212
 
4.5%
6 210
 
4.4%
7 195
 
4.1%
5 190
 
4.0%
0 185
 
3.9%
4 168
 
3.5%
Other values (8) 248
 
5.2%
Latin
ValueCountFrequency (%)
B 1
33.3%
H 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7998
62.8%
ASCII 4743
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2305
48.6%
1 424
 
8.9%
- 308
 
6.5%
2 295
 
6.2%
3 212
 
4.5%
6 210
 
4.4%
7 195
 
4.1%
5 190
 
4.0%
0 185
 
3.9%
4 168
 
3.5%
Other values (11) 251
 
5.3%
Hangul
ValueCountFrequency (%)
576
 
7.2%
541
 
6.8%
540
 
6.8%
539
 
6.7%
539
 
6.7%
538
 
6.7%
527
 
6.6%
523
 
6.5%
523
 
6.5%
464
 
5.8%
Other values (217) 2688
33.6%

도로명주소
Text

MISSING 

Distinct386
Distinct (%)85.0%
Missing70
Missing (%)13.4%
Memory size4.2 KiB
2024-05-11T14:28:02.854618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length29.348018
Min length22

Characters and Unicode

Total characters13324
Distinct characters247
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique342 ?
Unique (%)75.3%

Sample

1st row서울특별시 노원구 동일로250길 44-142 (상계동)
2nd row서울특별시 노원구 동일로248길 30 (상계동)
3rd row서울특별시 노원구 덕릉로 811 (상계동)
4th row서울특별시 노원구 노원로 75, 한국원자력의학원 지하1층 (공릉동)
5th row서울특별시 노원구 월계로 280 (월계동)
ValueCountFrequency (%)
서울특별시 454
17.7%
노원구 454
17.7%
상계동 175
 
6.8%
공릉동 85
 
3.3%
중계동 73
 
2.9%
월계동 57
 
2.2%
하계동 44
 
1.7%
동일로 35
 
1.4%
노원로 30
 
1.2%
화랑로 29
 
1.1%
Other values (545) 1122
43.9%
2024-05-11T14:28:03.570786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2104
 
15.8%
582
 
4.4%
570
 
4.3%
541
 
4.1%
473
 
3.5%
472
 
3.5%
468
 
3.5%
460
 
3.5%
456
 
3.4%
( 456
 
3.4%
Other values (237) 6742
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8173
61.3%
Space Separator 2104
 
15.8%
Decimal Number 1858
 
13.9%
Open Punctuation 456
 
3.4%
Close Punctuation 456
 
3.4%
Other Punctuation 241
 
1.8%
Dash Punctuation 30
 
0.2%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
582
 
7.1%
570
 
7.0%
541
 
6.6%
473
 
5.8%
472
 
5.8%
468
 
5.7%
460
 
5.6%
456
 
5.6%
455
 
5.6%
455
 
5.6%
Other values (219) 3241
39.7%
Decimal Number
ValueCountFrequency (%)
1 372
20.0%
2 324
17.4%
4 232
12.5%
3 199
10.7%
5 159
8.6%
6 132
 
7.1%
7 125
 
6.7%
8 122
 
6.6%
9 101
 
5.4%
0 92
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 238
98.8%
@ 2
 
0.8%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
2104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 456
100.0%
Close Punctuation
ValueCountFrequency (%)
) 456
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8173
61.3%
Common 5151
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
582
 
7.1%
570
 
7.0%
541
 
6.6%
473
 
5.8%
472
 
5.8%
468
 
5.7%
460
 
5.6%
456
 
5.6%
455
 
5.6%
455
 
5.6%
Other values (219) 3241
39.7%
Common
ValueCountFrequency (%)
2104
40.8%
( 456
 
8.9%
) 456
 
8.9%
1 372
 
7.2%
2 324
 
6.3%
, 238
 
4.6%
4 232
 
4.5%
3 199
 
3.9%
5 159
 
3.1%
6 132
 
2.6%
Other values (8) 479
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8173
61.3%
ASCII 5151
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2104
40.8%
( 456
 
8.9%
) 456
 
8.9%
1 372
 
7.2%
2 324
 
6.3%
, 238
 
4.6%
4 232
 
4.5%
3 199
 
3.9%
5 159
 
3.1%
6 132
 
2.6%
Other values (8) 479
 
9.3%
Hangul
ValueCountFrequency (%)
582
 
7.1%
570
 
7.0%
541
 
6.6%
473
 
5.8%
472
 
5.8%
468
 
5.7%
460
 
5.6%
456
 
5.6%
455
 
5.6%
455
 
5.6%
Other values (219) 3241
39.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct191
Distinct (%)42.2%
Missing71
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean1757.0662
Minimum1601
Maximum1913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-05-11T14:28:03.823637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1601
5-th percentile1619
Q11689
median1764
Q31823
95-th percentile1896
Maximum1913
Range312
Interquartile range (IQR)134

Descriptive statistics

Standard deviation86.814496
Coefficient of variation (CV)0.049408778
Kurtosis-1.0466853
Mean1757.0662
Median Absolute Deviation (MAD)73
Skewness-0.03434288
Sum795951
Variance7536.7567
MonotonicityNot monotonic
2024-05-11T14:28:04.048893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1772 16
 
3.1%
1797 10
 
1.9%
1795 9
 
1.7%
1811 8
 
1.5%
1623 7
 
1.3%
1747 7
 
1.3%
1689 7
 
1.3%
1862 7
 
1.3%
1691 7
 
1.3%
1861 6
 
1.1%
Other values (181) 369
70.4%
(Missing) 71
 
13.5%
ValueCountFrequency (%)
1601 1
 
0.2%
1602 3
0.6%
1603 2
0.4%
1604 3
0.6%
1605 1
 
0.2%
1606 1
 
0.2%
1607 1
 
0.2%
1610 1
 
0.2%
1613 4
0.8%
1616 1
 
0.2%
ValueCountFrequency (%)
1913 2
0.4%
1911 1
 
0.2%
1909 1
 
0.2%
1907 3
0.6%
1906 4
0.8%
1905 4
0.8%
1904 3
0.6%
1901 2
0.4%
1899 2
0.4%
1896 2
0.4%
Distinct437
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
2024-05-11T14:28:04.413824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length8.1125954
Min length2

Characters and Unicode

Total characters4251
Distinct characters318
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

Unique362 ?
Unique (%)69.1%

Sample

1st row시립수락양로원
2nd row대린원
3rd row대한체육회선수촌
4th row흥안운수
5th row한국원자력의학원
ValueCountFrequency (%)
어린이집 12
 
2.1%
시립중계노인전문요양원 5
 
0.9%
쉼터요양원 4
 
0.7%
학생식당 4
 
0.7%
구립하계실버센터 4
 
0.7%
노원구청직장어린이집 3
 
0.5%
서울여자대학교부속유치원 3
 
0.5%
서울특별시 3
 
0.5%
북부기술교육원 3
 
0.5%
의료법인 3
 
0.5%
Other values (456) 540
92.5%
2024-05-11T14:28:05.081123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
 
5.6%
175
 
4.1%
156
 
3.7%
154
 
3.6%
135
 
3.2%
128
 
3.0%
124
 
2.9%
96
 
2.3%
90
 
2.1%
83
 
2.0%
Other values (308) 2872
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4101
96.5%
Space Separator 60
 
1.4%
Close Punctuation 25
 
0.6%
Open Punctuation 25
 
0.6%
Decimal Number 19
 
0.4%
Other Punctuation 11
 
0.3%
Uppercase Letter 9
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
238
 
5.8%
175
 
4.3%
156
 
3.8%
154
 
3.8%
135
 
3.3%
128
 
3.1%
124
 
3.0%
96
 
2.3%
90
 
2.2%
83
 
2.0%
Other values (291) 2722
66.4%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 4
21.1%
8 3
15.8%
4 2
 
10.5%
3 2
 
10.5%
5 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
K 3
33.3%
I 2
22.2%
A 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 6
54.5%
. 3
27.3%
! 2
 
18.2%
Space Separator
ValueCountFrequency (%)
60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4101
96.5%
Common 141
 
3.3%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
238
 
5.8%
175
 
4.3%
156
 
3.8%
154
 
3.8%
135
 
3.3%
128
 
3.1%
124
 
3.0%
96
 
2.3%
90
 
2.2%
83
 
2.0%
Other values (291) 2722
66.4%
Common
ValueCountFrequency (%)
60
42.6%
) 25
17.7%
( 25
17.7%
2 7
 
5.0%
, 6
 
4.3%
1 4
 
2.8%
8 3
 
2.1%
. 3
 
2.1%
4 2
 
1.4%
! 2
 
1.4%
Other values (3) 4
 
2.8%
Latin
ValueCountFrequency (%)
B 3
33.3%
K 3
33.3%
I 2
22.2%
A 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4101
96.5%
ASCII 150
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
238
 
5.8%
175
 
4.3%
156
 
3.8%
154
 
3.8%
135
 
3.3%
128
 
3.1%
124
 
3.0%
96
 
2.3%
90
 
2.2%
83
 
2.0%
Other values (291) 2722
66.4%
ASCII
ValueCountFrequency (%)
60
40.0%
) 25
16.7%
( 25
16.7%
2 7
 
4.7%
, 6
 
4.0%
1 4
 
2.7%
8 3
 
2.0%
. 3
 
2.0%
B 3
 
2.0%
K 3
 
2.0%
Other values (7) 11
 
7.3%
Distinct519
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum1999-04-26 00:00:00
Maximum2024-05-01 09:37:04
2024-05-11T14:28:05.336524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:28:05.606702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
U
276 
I
248 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 276
52.7%
I 248
47.3%

Length

2024-05-11T14:28:05.882384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:06.027302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 276
52.7%
i 248
47.3%
Distinct166
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T14:28:06.234964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:28:06.483848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct10
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
어린이집
156 
집단급식소
128 
학교
94 
사회복지시설
54 
병원
32 
Other values (5)
60 

Length

Max length8
Median length6
Mean length4.0171756
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row사회복지시설
2nd row사회복지시설
3rd row집단급식소
4th row집단급식소
5th row병원

Common Values

ValueCountFrequency (%)
어린이집 156
29.8%
집단급식소 128
24.4%
학교 94
17.9%
사회복지시설 54
 
10.3%
병원 32
 
6.1%
산업체 28
 
5.3%
기타 집단급식소 15
 
2.9%
공공기관 10
 
1.9%
기숙사 6
 
1.1%
수련원 1
 
0.2%

Length

2024-05-11T14:28:06.783436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:07.022688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 156
28.9%
집단급식소 143
26.5%
학교 94
17.4%
사회복지시설 54
 
10.0%
병원 32
 
5.9%
산업체 28
 
5.2%
기타 15
 
2.8%
공공기관 10
 
1.9%
기숙사 6
 
1.1%
수련원 1
 
0.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct314
Distinct (%)60.7%
Missing7
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean206004.71
Minimum203719.16
Maximum209696.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-05-11T14:28:07.255892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum203719.16
5-th percentile204618.53
Q1205153.55
median205920.87
Q3206621.81
95-th percentile207918.32
Maximum209696.96
Range5977.7984
Interquartile range (IQR)1468.2613

Descriptive statistics

Standard deviation1055.3775
Coefficient of variation (CV)0.0051230748
Kurtosis0.79870392
Mean206004.71
Median Absolute Deviation (MAD)730.82864
Skewness0.79550491
Sum1.0650444 × 108
Variance1113821.7
MonotonicityNot monotonic
2024-05-11T14:28:07.440202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207918.320414714 13
 
2.5%
204940.089436072 10
 
1.9%
206981.454072644 9
 
1.7%
209288.472624641 8
 
1.5%
204946.18863562 7
 
1.3%
205136.500230395 6
 
1.1%
206402.099724168 6
 
1.1%
205428.666292679 6
 
1.1%
205596.695083587 6
 
1.1%
206551.60704052 6
 
1.1%
Other values (304) 440
84.0%
(Missing) 7
 
1.3%
ValueCountFrequency (%)
203719.161728968 1
 
0.2%
204160.914455692 1
 
0.2%
204235.465605799 1
 
0.2%
204325.989587591 3
0.6%
204332.196679491 1
 
0.2%
204387.387609735 3
0.6%
204412.836637873 1
 
0.2%
204415.700533907 1
 
0.2%
204443.183439987 1
 
0.2%
204454.974085477 1
 
0.2%
ValueCountFrequency (%)
209696.960166997 1
 
0.2%
209482.460550931 1
 
0.2%
209481.274650006 2
 
0.4%
209288.472624641 8
1.5%
208532.777004106 2
 
0.4%
208014.393680914 3
 
0.6%
208011.354088636 1
 
0.2%
207937.525903167 2
 
0.4%
207918.320414714 13
2.5%
207642.144523897 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct314
Distinct (%)60.7%
Missing7
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean460374.46
Minimum456950.15
Maximum464922.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-05-11T14:28:07.640779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456950.15
5-th percentile457484.4
Q1458679.83
median460122.92
Q3461775.65
95-th percentile463727.47
Maximum464922.21
Range7972.061
Interquartile range (IQR)3095.8209

Descriptive statistics

Standard deviation1939.563
Coefficient of variation (CV)0.0042130118
Kurtosis-0.87962624
Mean460374.46
Median Absolute Deviation (MAD)1556.9055
Skewness0.26042969
Sum2.3801359 × 108
Variance3761904.6
MonotonicityNot monotonic
2024-05-11T14:28:08.287041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
458383.983421656 13
 
2.5%
459998.314879897 10
 
1.9%
458960.471391303 9
 
1.7%
460064.53972057 8
 
1.5%
464241.922622024 7
 
1.3%
459748.436215367 6
 
1.1%
460228.467088494 6
 
1.1%
462625.053235914 6
 
1.1%
458975.496774634 6
 
1.1%
457326.722941972 6
 
1.1%
Other values (304) 440
84.0%
(Missing) 7
 
1.3%
ValueCountFrequency (%)
456950.152059544 3
0.6%
457275.799282625 3
0.6%
457326.722941972 6
1.1%
457344.246400901 1
 
0.2%
457344.469525861 1
 
0.2%
457353.229350385 2
 
0.4%
457358.731978332 2
 
0.4%
457404.729056799 2
 
0.4%
457419.522429279 1
 
0.2%
457419.544028716 1
 
0.2%
ValueCountFrequency (%)
464922.213107238 1
 
0.2%
464623.095556742 1
 
0.2%
464522.768676269 2
 
0.4%
464508.952781941 2
 
0.4%
464506.645890474 1
 
0.2%
464502.030304529 1
 
0.2%
464346.663669239 2
 
0.4%
464241.922622024 7
1.3%
464174.158420444 1
 
0.2%
464133.975605555 2
 
0.4%

위생업태명
Categorical

Distinct11
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
어린이집
129 
집단급식소
128 
학교
92 
<NA>
63 
사회복지시설
40 
Other values (6)
72 

Length

Max length8
Median length6
Mean length3.9923664
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 129
24.6%
집단급식소 128
24.4%
학교 92
17.6%
<NA> 63
12.0%
사회복지시설 40
 
7.6%
병원 25
 
4.8%
산업체 19
 
3.6%
기타 집단급식소 12
 
2.3%
공공기관 9
 
1.7%
기숙사 6
 
1.1%

Length

2024-05-11T14:28:08.587867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
집단급식소 140
26.1%
어린이집 129
24.1%
학교 92
17.2%
na 63
11.8%
사회복지시설 40
 
7.5%
병원 25
 
4.7%
산업체 19
 
3.5%
기타 12
 
2.2%
공공기관 9
 
1.7%
기숙사 6
 
1.1%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
404 
0
107 
1
 
11
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.3129771
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 404
77.1%
0 107
 
20.4%
1 11
 
2.1%
5 1
 
0.2%
2 1
 
0.2%

Length

2024-05-11T14:28:08.793340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:08.992315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 404
77.1%
0 107
 
20.4%
1 11
 
2.1%
5 1
 
0.2%
2 1
 
0.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)7.3%
Missing401
Missing (%)76.5%
Infinite0
Infinite (%)0.0%
Mean1.3902439
Minimum0
Maximum11
Zeros90
Zeros (%)17.2%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-05-11T14:28:09.188953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6.9
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5012592
Coefficient of variation (CV)1.7991513
Kurtosis1.5307275
Mean1.3902439
Median Absolute Deviation (MAD)0
Skewness1.600088
Sum171
Variance6.2562975
MonotonicityNot monotonic
2024-05-11T14:28:09.336872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 90
 
17.2%
4 8
 
1.5%
5 7
 
1.3%
6 6
 
1.1%
3 4
 
0.8%
7 4
 
0.8%
8 2
 
0.4%
1 1
 
0.2%
11 1
 
0.2%
(Missing) 401
76.5%
ValueCountFrequency (%)
0 90
17.2%
1 1
 
0.2%
3 4
 
0.8%
4 8
 
1.5%
5 7
 
1.3%
6 6
 
1.1%
7 4
 
0.8%
8 2
 
0.4%
11 1
 
0.2%
ValueCountFrequency (%)
11 1
 
0.2%
8 2
 
0.4%
7 4
 
0.8%
6 6
 
1.1%
5 7
 
1.3%
4 8
 
1.5%
3 4
 
0.8%
1 1
 
0.2%
0 90
17.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
411 
기타
57 
주택가주변
 
19
아파트지역
 
18
학교정화(절대)
 
18

Length

Max length8
Median length4
Mean length3.9980916
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 411
78.4%
기타 57
 
10.9%
주택가주변 19
 
3.6%
아파트지역 18
 
3.4%
학교정화(절대) 18
 
3.4%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-11T14:28:09.520430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:09.701890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
78.4%
기타 57
 
10.9%
주택가주변 19
 
3.6%
아파트지역 18
 
3.4%
학교정화(절대 18
 
3.4%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
411 
기타
56 
우수
 
30
자율
 
24
 
3

Length

Max length4
Median length4
Mean length3.5629771
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 411
78.4%
기타 56
 
10.7%
우수 30
 
5.7%
자율 24
 
4.6%
3
 
0.6%

Length

2024-05-11T14:28:09.891792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.080841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
78.4%
기타 56
 
10.7%
우수 30
 
5.7%
자율 24
 
4.6%
3
 
0.6%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
351 
상수도전용
173 

Length

Max length5
Median length4
Mean length4.3301527
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
67.0%
상수도전용 173
33.0%

Length

2024-05-11T14:28:10.300453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.494772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
67.0%
상수도전용 173
33.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
509 
0
 
15

Length

Max length4
Median length4
Mean length3.9141221
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> 509
97.1%
0 15
 
2.9%

Length

2024-05-11T14:28:10.730016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:10.973659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
97.1%
0 15
 
2.9%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
0
413 
<NA>
109 
2
 
2

Length

Max length4
Median length1
Mean length1.6240458
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 413
78.8%
<NA> 109
 
20.8%
2 2
 
0.4%

Length

2024-05-11T14:28:11.195852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:11.440400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 413
78.8%
na 109
 
20.8%
2 2
 
0.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
509 
0
 
15

Length

Max length4
Median length4
Mean length3.9141221
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> 509
97.1%
0 15
 
2.9%

Length

2024-05-11T14:28:11.650856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:11.843307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
97.1%
0 15
 
2.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
509 
0
 
15

Length

Max length4
Median length4
Mean length3.9141221
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> 509
97.1%
0 15
 
2.9%

Length

2024-05-11T14:28:12.026053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:12.185761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
97.1%
0 15
 
2.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
509 
0
 
15

Length

Max length4
Median length4
Mean length3.9141221
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> 509
97.1%
0 15
 
2.9%

Length

2024-05-11T14:28:12.360041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:12.528810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 509
97.1%
0 15
 
2.9%

건물소유구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
498 
자가
 
26

Length

Max length4
Median length4
Mean length3.9007634
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> 498
95.0%
자가 26
 
5.0%

Length

2024-05-11T14:28:12.713567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:12.906843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 498
95.0%
자가 26
 
5.0%

보증액
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
280 
0
244 

Length

Max length4
Median length4
Mean length2.6030534
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> 280
53.4%
0 244
46.6%

Length

2024-05-11T14:28:13.099283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:13.279618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 280
53.4%
0 244
46.6%

월세액
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
<NA>
280 
0
244 

Length

Max length4
Median length4
Mean length2.6030534
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> 280
53.4%
0 244
46.6%

Length

2024-05-11T14:28:13.477731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:28:13.666360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 280
53.4%
0 244
46.6%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing63
Missing (%)12.0%
Memory size1.2 KiB
False
461 
(Missing)
63 
ValueCountFrequency (%)
False 461
88.0%
(Missing) 63
 
12.0%
2024-05-11T14:28:13.786767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct312
Distinct (%)67.7%
Missing63
Missing (%)12.0%
Infinite0
Infinite (%)0.0%
Mean104.45868
Minimum0
Maximum1229.37
Zeros88
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-05-11T14:28:13.922031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median24.75
Q3135
95-th percentile500
Maximum1229.37
Range1229.37
Interquartile range (IQR)126

Descriptive statistics

Standard deviation184.55535
Coefficient of variation (CV)1.7667785
Kurtosis11.409115
Mean104.45868
Median Absolute Deviation (MAD)24.75
Skewness3.1079066
Sum48155.45
Variance34060.677
MonotonicityNot monotonic
2024-05-11T14:28:14.119193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 88
 
16.8%
20.0 5
 
1.0%
24.75 5
 
1.0%
50.0 4
 
0.8%
19.8 4
 
0.8%
18.0 4
 
0.8%
15.0 4
 
0.8%
10.0 4
 
0.8%
33.0 4
 
0.8%
180.0 3
 
0.6%
Other values (302) 336
64.1%
(Missing) 63
 
12.0%
ValueCountFrequency (%)
0.0 88
16.8%
3.3 1
 
0.2%
3.78 1
 
0.2%
4.0 1
 
0.2%
4.37 1
 
0.2%
4.44 1
 
0.2%
4.6 1
 
0.2%
5.0 2
 
0.4%
5.58 1
 
0.2%
5.94 1
 
0.2%
ValueCountFrequency (%)
1229.37 1
0.2%
1179.35 1
0.2%
1133.2 1
0.2%
1033.5 1
0.2%
965.91 1
0.2%
876.68 1
0.2%
822.0 1
0.2%
765.45 1
0.2%
735.55 1
0.2%
728.84 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing524
Missing (%)100.0%
Memory size4.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-105-1972-0000119721213<NA>3폐업2폐업20190116<NA><NA><NA>02 939617656.40139836서울특별시 노원구 상계동 산 51번지서울특별시 노원구 동일로250길 44-142 (상계동)1622시립수락양로원2019-01-16 10:39:27U2019-01-18 02:40:00.0사회복지시설205911.424214464522.768676사회복지시설00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N159.45<NA><NA><NA>
131000003100000-105-1973-0000219730625<NA>1영업/정상1영업<NA><NA><NA><NA>02 939229812.90139838서울특별시 노원구 상계동 1266번지서울특별시 노원구 동일로248길 30 (상계동)1623대린원2018-07-17 17:01:34I2018-08-31 23:59:59.0사회복지시설204946.188636464241.922622사회복지시설00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N148.3<NA><NA><NA>
231000003100000-105-1976-0000519760101<NA>3폐업2폐업20130705<NA><NA><NA>02 9700081191.70139800서울특별시 노원구 공릉동 223-19번지<NA><NA>대한체육회선수촌2011-01-06 09:47:02I2018-08-31 23:59:59.0집단급식소207010.637188458128.770337집단급식소00기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N438.78<NA><NA><NA>
331000003100000-105-1980-0001219800401<NA>3폐업2폐업20160623<NA><NA><NA>02 935600018.10139812서울특별시 노원구 상계동 110-8번지서울특별시 노원구 덕릉로 811 (상계동)1637흥안운수2009-07-07 16:25:21I2018-08-31 23:59:59.0집단급식소206993.79127462994.974733집단급식소00기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N60.2<NA><NA><NA>
431000003100000-105-1984-000061984-12-01<NA>1영업/정상1영업<NA><NA><NA><NA>02 9742501336.16139-706서울특별시 노원구 공릉동 215-4 한국원자력의학원서울특별시 노원구 노원로 75, 한국원자력의학원 지하1층 (공릉동)1812한국원자력의학원2023-05-12 16:58:02U2022-12-04 23:04:00.0병원207192.873108458452.733972<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531000003100000-105-1986-0000419860801<NA>3폐업2폐업20130701<NA><NA><NA>02 9703226210.00139800서울특별시 노원구 공릉동 170-2번지<NA><NA>한전인재개발원2012-03-08 09:39:43I2018-08-31 23:59:59.0집단급식소207421.02967459008.686538집단급식소00기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N485.6<NA><NA><NA>
631000003100000-105-1987-0000319870628<NA>3폐업2폐업20130529<NA><NA><NA>02 937690024.00139831서울특별시 노원구 상계동 771-1번지<NA><NA>성모자애보육원2010-02-08 09:12:24I2018-08-31 23:59:59.0집단급식소205071.864337460063.379472집단급식소00기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N137.0<NA><NA><NA>
731000003100000-105-1988-0001119881101<NA>1영업/정상1영업<NA><NA><NA><NA>02 918603417.20139847서울특별시 노원구 월계동 541-1번지서울특별시 노원구 월계로 280 (월계동)1884삼화상운(주)2017-07-06 13:10:32I2018-08-31 23:59:59.0산업체204616.097465458162.081675산업체00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N68.7<NA><NA><NA>
831000003100000-105-1989-0000819890201<NA>3폐업2폐업20190408<NA><NA><NA>070 4651239766.00139230서울특별시 노원구 하계동 284번지서울특별시 노원구 한글비석로 57 (하계동)1784(주)세이브존아이앤씨2019-04-08 17:24:20U2019-04-10 02:40:00.0산업체205994.811816459502.64528산업체00기타기타상수도전용<NA>0<NA><NA><NA><NA><NA><NA>N201.1<NA><NA><NA>
931000003100000-105-1989-0000919890501<NA>3폐업2폐업20190416<NA><NA><NA>02 970538450.00139240서울특별시 노원구 공릉동 126번지서울특별시 노원구 화랑로 621 (공릉동)1797서울여자대학교 학생식당2019-04-16 10:38:43U2019-04-18 02:40:00.0기숙사207918.320415458383.983422기숙사00기타기타<NA><NA>0<NA><NA><NA><NA><NA><NA>N483.75<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
51431000003100000-105-2021-0001320210806<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.23139230서울특별시 노원구 하계동 288-1서울특별시 노원구 노원로18길 41, 1층 (하계동)1747동천일리하우스2021-08-06 15:04:11I2021-08-08 00:22:51.0사회복지시설206402.099724460228.467088사회복지시설00<NA><NA>상수도전용00000<NA>00N50.0<NA><NA><NA>
51531000003100000-105-2022-0000120220209<NA>1영업/정상1영업<NA><NA><NA><NA><NA>.00139847서울특별시 노원구 월계동 534-64서울특별시 노원구 월계로44나길 31-4 (월계동)1888월계숲속 어린이집2022-02-09 15:29:16I2022-02-11 00:22:38.0어린이집204718.492536457896.477856어린이집00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
51631000003100000-105-2022-0000220220330<NA>1영업/정상1영업<NA><NA><NA><NA><NA>79.31139808서울특별시 노원구 공릉동 680-9 태릉성심종합병원(치과,요양,정신건강)서울특별시 노원구 동일로 987, 태릉성심종합병원(치과,요양,정신건강) 8층 (공릉동)1861모아한방병원2022-03-30 16:37:08I2021-12-04 00:02:00.0병원206551.607041457326.722942<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51731000003100000-105-2022-0000320220531<NA>1영업/정상1영업<NA><NA><NA><NA><NA>24.51139818서울특별시 노원구 상계동 389-356 경인빌딩서울특별시 노원구 상계로27길 12, 경인빌딩 4,5층 (상계동)168288재활데이케어센터2022-05-31 15:59:37I2021-12-06 00:04:00.0사회복지시설206172.233158461867.226671<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51831000003100000-105-2022-0000420220607<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.50139800서울특별시 노원구 공릉동 230 태릉해링턴플레이스서울특별시 노원구 공릉로34길 86, 1층 (공릉동, 태릉해링턴플레이스)1817태릉해링턴 어린이집2022-06-07 17:15:01I2021-12-06 00:09:00.0어린이집207261.78171458228.274014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51931000003100000-105-2022-0000520220907<NA>1영업/정상1영업<NA><NA><NA><NA><NA>7.04139802서울특별시 노원구 공릉동 339-1 동산빌딩서울특별시 노원구 공릉로37길 6, 동산빌딩 1층 (공릉동)1836동산 어린이집2022-09-07 13:23:46I2021-12-09 00:09:00.0어린이집206914.521404457904.997882<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52031000003100000-105-2022-0000620221229<NA>1영업/정상1영업<NA><NA><NA><NA>029348380210.00139942서울특별시 노원구 상계동 709-2 메가빌딩서울특별시 노원구 노해로 459, 메가빌딩 지하1층 (상계동)1689강북메가스터디학원2022-12-29 13:55:07I2021-11-01 21:01:00.0산업체205137.089791461322.100331<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52131000003100000-105-2023-000012023-02-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.49139-816서울특별시 노원구 상계동 301-6 7층서울특별시 노원구 노원로 416, 새힘병원 7층 (상계동)1704새힘병원2023-02-23 10:10:04U2022-12-01 22:05:00.0병원205922.151234461261.657202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52231000003100000-105-2023-000022023-05-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00139-800서울특별시 노원구 공릉동 51-1 육사화랑어린이집서울특별시 노원구 화랑로 564 (공릉동, 육사아파트)1805육사화랑어린이집2023-05-30 16:13:26I2022-12-06 00:01:00.0어린이집208014.393681457647.818425<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52331000003100000-105-2023-000032023-06-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00139-836서울특별시 노원구 상계동 963-5 구립 수락노인종합복지관서울특별시 노원구 수락산로 214, 구립 수락노인종합복지관 (상계동)1616구립 수락노인종합복지관2023-06-23 16:12:05I2022-12-05 22:05:00.0사회복지시설204780.238753463188.718025<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>