Overview

Dataset statistics

Number of variables44
Number of observations2362
Missing cells26861
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory872.0 KiB
Average record size in memory378.1 B

Variable types

Categorical19
Text7
DateTime4
Unsupported9
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
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18086/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (68.4%)Imbalance
여성종사자수 is highly imbalanced (68.4%)Imbalance
급수시설구분명 is highly imbalanced (80.7%)Imbalance
총인원 is highly imbalanced (68.9%)Imbalance
본사종업원수 is highly imbalanced (50.3%)Imbalance
공장사무직종업원수 is highly imbalanced (50.2%)Imbalance
공장판매직종업원수 is highly imbalanced (59.7%)Imbalance
보증액 is highly imbalanced (72.8%)Imbalance
월세액 is highly imbalanced (72.8%)Imbalance
홈페이지 is highly imbalanced (99.5%)Imbalance
인허가취소일자 has 2362 (100.0%) missing valuesMissing
폐업일자 has 565 (23.9%) missing valuesMissing
휴업시작일자 has 2362 (100.0%) missing valuesMissing
휴업종료일자 has 2362 (100.0%) missing valuesMissing
재개업일자 has 2362 (100.0%) missing valuesMissing
전화번호 has 1520 (64.4%) missing valuesMissing
소재지면적 has 1307 (55.3%) missing valuesMissing
도로명주소 has 460 (19.5%) missing valuesMissing
도로명우편번호 has 467 (19.8%) missing valuesMissing
업태구분명 has 2362 (100.0%) missing valuesMissing
영업장주변구분명 has 2362 (100.0%) missing valuesMissing
등급구분명 has 2362 (100.0%) missing valuesMissing
다중이용업소여부 has 624 (26.4%) missing valuesMissing
시설총규모 has 624 (26.4%) missing valuesMissing
전통업소지정번호 has 2362 (100.0%) missing valuesMissing
전통업소주된음식 has 2362 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 42.84008779)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 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
시설총규모 has 1572 (66.6%) zerosZeros

Reproduction

Analysis started2024-05-11 05:05:43.056930
Analysis finished2024-05-11 05:05:45.803071
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
3090000
2362 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 2362
100.0%

Length

2024-05-11T05:05:45.996197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:05:46.316695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 2362
100.0%

관리번호
Text

UNIQUE 

Distinct2362
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-05-11T05:05:46.713665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters51964
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

Unique2362 ?
Unique (%)100.0%

Sample

1st row3090000-134-2003-00001
2nd row3090000-134-2004-00001
3rd row3090000-134-2004-00002
4th row3090000-134-2004-00003
5th row3090000-134-2004-00004
ValueCountFrequency (%)
3090000-134-2003-00001 1
 
< 0.1%
3090000-134-2019-00048 1
 
< 0.1%
3090000-134-2019-00033 1
 
< 0.1%
3090000-134-2019-00034 1
 
< 0.1%
3090000-134-2019-00041 1
 
< 0.1%
3090000-134-2019-00035 1
 
< 0.1%
3090000-134-2019-00036 1
 
< 0.1%
3090000-134-2019-00037 1
 
< 0.1%
3090000-134-2019-00038 1
 
< 0.1%
3090000-134-2019-00039 1
 
< 0.1%
Other values (2352) 2352
99.6%
2024-05-11T05:05:47.620988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22162
42.6%
- 7086
 
13.6%
3 5510
 
10.6%
1 4697
 
9.0%
2 4012
 
7.7%
4 3245
 
6.2%
9 2963
 
5.7%
5 657
 
1.3%
6 550
 
1.1%
7 545
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44878
86.4%
Dash Punctuation 7086
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22162
49.4%
3 5510
 
12.3%
1 4697
 
10.5%
2 4012
 
8.9%
4 3245
 
7.2%
9 2963
 
6.6%
5 657
 
1.5%
6 550
 
1.2%
7 545
 
1.2%
8 537
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 7086
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51964
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22162
42.6%
- 7086
 
13.6%
3 5510
 
10.6%
1 4697
 
9.0%
2 4012
 
7.7%
4 3245
 
6.2%
9 2963
 
5.7%
5 657
 
1.3%
6 550
 
1.1%
7 545
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51964
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22162
42.6%
- 7086
 
13.6%
3 5510
 
10.6%
1 4697
 
9.0%
2 4012
 
7.7%
4 3245
 
6.2%
9 2963
 
5.7%
5 657
 
1.3%
6 550
 
1.1%
7 545
 
1.0%
Distinct1652
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum2004-03-19 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T05:05:48.076931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:05:48.505864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
3
1797 
1
565 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1797
76.1%
1 565
 
23.9%

Length

2024-05-11T05:05:48.926324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:05:49.264020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1797
76.1%
1 565
 
23.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
폐업
1797 
영업/정상
565 

Length

Max length5
Median length2
Mean length2.7176122
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1797
76.1%
영업/정상 565
 
23.9%

Length

2024-05-11T05:05:49.627786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:05:49.946076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1797
76.1%
영업/정상 565
 
23.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2
1797 
1
565 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1797
76.1%
1 565
 
23.9%

Length

2024-05-11T05:05:50.244330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:05:50.525732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1797
76.1%
1 565
 
23.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
폐업
1797 
영업
565 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1797
76.1%
영업 565
 
23.9%

Length

2024-05-11T05:05:50.951414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:05:51.217305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1797
76.1%
영업 565
 
23.9%

폐업일자
Date

MISSING 

Distinct1176
Distinct (%)65.4%
Missing565
Missing (%)23.9%
Memory size18.6 KiB
Minimum2004-06-25 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T05:05:51.637805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:05:52.234342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

전화번호
Text

MISSING 

Distinct799
Distinct (%)94.9%
Missing1520
Missing (%)64.4%
Memory size18.6 KiB
2024-05-11T05:05:53.294205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.307601
Min length2

Characters and Unicode

Total characters8679
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

Unique769 ?
Unique (%)91.3%

Sample

1st row02 990 3128
2nd row02 9947785
3rd row02 9011234
4th row02 9920360
5th row0233920271
ValueCountFrequency (%)
02 506
31.0%
070 43
 
2.6%
954 21
 
1.3%
900 18
 
1.1%
905 14
 
0.9%
903 14
 
0.9%
902 11
 
0.7%
955 11
 
0.7%
906 10
 
0.6%
992 8
 
0.5%
Other values (844) 977
59.8%
2024-05-11T05:05:54.801307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1505
17.3%
9 1162
13.4%
2 1151
13.3%
1057
12.2%
5 643
7.4%
3 626
7.2%
4 601
 
6.9%
7 558
 
6.4%
8 471
 
5.4%
1 461
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7622
87.8%
Space Separator 1057
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1505
19.7%
9 1162
15.2%
2 1151
15.1%
5 643
8.4%
3 626
8.2%
4 601
 
7.9%
7 558
 
7.3%
8 471
 
6.2%
1 461
 
6.0%
6 444
 
5.8%
Space Separator
ValueCountFrequency (%)
1057
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8679
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1505
17.3%
9 1162
13.4%
2 1151
13.3%
1057
12.2%
5 643
7.4%
3 626
7.2%
4 601
 
6.9%
7 558
 
6.4%
8 471
 
5.4%
1 461
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8679
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1505
17.3%
9 1162
13.4%
2 1151
13.3%
1057
12.2%
5 643
7.4%
3 626
7.2%
4 601
 
6.9%
7 558
 
6.4%
8 471
 
5.4%
1 461
 
5.3%

소재지면적
Text

MISSING 

Distinct348
Distinct (%)33.0%
Missing1307
Missing (%)55.3%
Memory size18.6 KiB
2024-05-11T05:05:55.772351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.6047393
Min length3

Characters and Unicode

Total characters4858
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

Unique243 ?
Unique (%)23.0%

Sample

1st row.00
2nd row233.00
3rd row24.00
4th row33.00
5th row197.42
ValueCountFrequency (%)
00 166
 
15.7%
3.30 62
 
5.9%
3.00 47
 
4.5%
33.00 40
 
3.8%
16.50 21
 
2.0%
6.60 20
 
1.9%
30.00 18
 
1.7%
6.00 13
 
1.2%
26.40 13
 
1.2%
10.00 12
 
1.1%
Other values (338) 643
60.9%
2024-05-11T05:05:57.463352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1709
35.2%
. 1055
21.7%
3 449
 
9.2%
1 346
 
7.1%
2 270
 
5.6%
6 265
 
5.5%
5 200
 
4.1%
9 166
 
3.4%
4 161
 
3.3%
8 136
 
2.8%
Other values (2) 101
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3801
78.2%
Other Punctuation 1057
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1709
45.0%
3 449
 
11.8%
1 346
 
9.1%
2 270
 
7.1%
6 265
 
7.0%
5 200
 
5.3%
9 166
 
4.4%
4 161
 
4.2%
8 136
 
3.6%
7 99
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 1055
99.8%
, 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1709
35.2%
. 1055
21.7%
3 449
 
9.2%
1 346
 
7.1%
2 270
 
5.6%
6 265
 
5.5%
5 200
 
4.1%
9 166
 
3.4%
4 161
 
3.3%
8 136
 
2.8%
Other values (2) 101
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1709
35.2%
. 1055
21.7%
3 449
 
9.2%
1 346
 
7.1%
2 270
 
5.6%
6 265
 
5.5%
5 200
 
4.1%
9 166
 
3.4%
4 161
 
3.3%
8 136
 
2.8%
Other values (2) 101
 
2.1%
Distinct290
Distinct (%)12.3%
Missing3
Missing (%)0.1%
Memory size18.6 KiB
2024-05-11T05:05:58.625766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1818567
Min length6

Characters and Unicode

Total characters14583
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

Unique66 ?
Unique (%)2.8%

Sample

1st row132918
2nd row132904
3rd row132821
4th row132-904
5th row132893
ValueCountFrequency (%)
132854 95
 
4.0%
132898 75
 
3.2%
132924 61
 
2.6%
132040 59
 
2.5%
132821 57
 
2.4%
132893 49
 
2.1%
132864 41
 
1.7%
132863 40
 
1.7%
132904 35
 
1.5%
132926 32
 
1.4%
Other values (280) 1815
76.9%
2024-05-11T05:06:00.179748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2973
20.4%
1 2945
20.2%
3 2729
18.7%
8 1803
12.4%
9 1082
 
7.4%
0 742
 
5.1%
4 597
 
4.1%
6 439
 
3.0%
- 429
 
2.9%
5 426
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14154
97.1%
Dash Punctuation 429
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2973
21.0%
1 2945
20.8%
3 2729
19.3%
8 1803
12.7%
9 1082
 
7.6%
0 742
 
5.2%
4 597
 
4.2%
6 439
 
3.1%
5 426
 
3.0%
7 418
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 429
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14583
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2973
20.4%
1 2945
20.2%
3 2729
18.7%
8 1803
12.4%
9 1082
 
7.4%
0 742
 
5.1%
4 597
 
4.1%
6 439
 
3.0%
- 429
 
2.9%
5 426
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14583
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2973
20.4%
1 2945
20.2%
3 2729
18.7%
8 1803
12.4%
9 1082
 
7.4%
0 742
 
5.1%
4 597
 
4.1%
6 439
 
3.0%
- 429
 
2.9%
5 426
 
2.9%
Distinct1359
Distinct (%)57.6%
Missing3
Missing (%)0.1%
Memory size18.6 KiB
2024-05-11T05:06:01.183821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length28.980076
Min length16

Characters and Unicode

Total characters68364
Distinct characters365
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1092 ?
Unique (%)46.3%

Sample

1st row서울특별시 도봉구 창동 ***-**번지
2nd row서울특별시 도봉구 창동 ***-**번지 *층
3rd row서울특별시 도봉구 도봉동 ***-**번지
4th row서울특별시 도봉구 창동 ***-**
5th row서울특별시 도봉구 쌍문동 ***번지 삼환웨딩프라자 빌딩 ***호
ValueCountFrequency (%)
서울특별시 2359
17.7%
도봉구 2357
17.7%
번지 1438
10.8%
1006
7.6%
942
 
7.1%
창동 901
 
6.8%
587
 
4.4%
방학동 552
 
4.1%
쌍문동 534
 
4.0%
464
 
3.5%
Other values (844) 2163
16.3%
2024-05-11T05:06:02.604692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 15415
22.5%
12230
17.9%
3150
 
4.6%
2828
 
4.1%
2818
 
4.1%
2392
 
3.5%
2379
 
3.5%
2378
 
3.5%
2365
 
3.5%
2360
 
3.5%
Other values (355) 20049
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37789
55.3%
Other Punctuation 15640
22.9%
Space Separator 12230
 
17.9%
Dash Punctuation 1733
 
2.5%
Decimal Number 327
 
0.5%
Lowercase Letter 310
 
0.5%
Uppercase Letter 200
 
0.3%
Open Punctuation 62
 
0.1%
Close Punctuation 62
 
0.1%
Other Symbol 8
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3150
 
8.3%
2828
 
7.5%
2818
 
7.5%
2392
 
6.3%
2379
 
6.3%
2378
 
6.3%
2365
 
6.3%
2360
 
6.2%
2359
 
6.2%
1704
 
4.5%
Other values (288) 13056
34.5%
Lowercase Letter
ValueCountFrequency (%)
w 63
20.3%
o 38
12.3%
c 26
8.4%
k 23
 
7.4%
r 20
 
6.5%
a 19
 
6.1%
e 19
 
6.1%
m 15
 
4.8%
t 12
 
3.9%
n 11
 
3.5%
Other values (12) 64
20.6%
Uppercase Letter
ValueCountFrequency (%)
B 59
29.5%
A 33
16.5%
S 27
13.5%
E 14
 
7.0%
Y 10
 
5.0%
O 8
 
4.0%
W 7
 
3.5%
D 7
 
3.5%
C 5
 
2.5%
T 5
 
2.5%
Other values (10) 25
12.5%
Decimal Number
ValueCountFrequency (%)
1 60
18.3%
0 49
15.0%
3 45
13.8%
2 34
10.4%
5 33
10.1%
6 31
9.5%
4 27
8.3%
8 21
 
6.4%
7 15
 
4.6%
9 12
 
3.7%
Other Punctuation
ValueCountFrequency (%)
* 15415
98.6%
@ 99
 
0.6%
, 59
 
0.4%
. 58
 
0.4%
/ 7
 
< 0.1%
& 1
 
< 0.1%
: 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
12230
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1733
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Other Symbol
ValueCountFrequency (%)
8
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37797
55.3%
Common 30056
44.0%
Latin 511
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3150
 
8.3%
2828
 
7.5%
2818
 
7.5%
2392
 
6.3%
2379
 
6.3%
2378
 
6.3%
2365
 
6.3%
2360
 
6.2%
2359
 
6.2%
1704
 
4.5%
Other values (289) 13064
34.6%
Latin
ValueCountFrequency (%)
w 63
 
12.3%
B 59
 
11.5%
o 38
 
7.4%
A 33
 
6.5%
S 27
 
5.3%
c 26
 
5.1%
k 23
 
4.5%
r 20
 
3.9%
a 19
 
3.7%
e 19
 
3.7%
Other values (33) 184
36.0%
Common
ValueCountFrequency (%)
* 15415
51.3%
12230
40.7%
- 1733
 
5.8%
@ 99
 
0.3%
( 62
 
0.2%
) 62
 
0.2%
1 60
 
0.2%
, 59
 
0.2%
. 58
 
0.2%
0 49
 
0.2%
Other values (13) 229
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37789
55.3%
ASCII 30566
44.7%
None 8
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 15415
50.4%
12230
40.0%
- 1733
 
5.7%
@ 99
 
0.3%
w 63
 
0.2%
( 62
 
0.2%
) 62
 
0.2%
1 60
 
0.2%
, 59
 
0.2%
B 59
 
0.2%
Other values (55) 724
 
2.4%
Hangul
ValueCountFrequency (%)
3150
 
8.3%
2828
 
7.5%
2818
 
7.5%
2392
 
6.3%
2379
 
6.3%
2378
 
6.3%
2365
 
6.3%
2360
 
6.2%
2359
 
6.2%
1704
 
4.5%
Other values (288) 13056
34.5%
None
ValueCountFrequency (%)
8
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct1354
Distinct (%)71.2%
Missing460
Missing (%)19.5%
Memory size18.6 KiB
2024-05-11T05:06:03.554823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length35.727129
Min length21

Characters and Unicode

Total characters67953
Distinct characters359
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1100 ?
Unique (%)57.8%

Sample

1st row서울특별시 도봉구 덕릉로**길 ** (창동)
2nd row서울특별시 도봉구 도봉로***길 ** (도봉동)
3rd row서울특별시 도봉구 노해로**길 * (창동)
4th row서울특별시 도봉구 도봉로 *** (쌍문동,삼환웨딩프라자 빌딩 ***호)
5th row서울특별시 도봉구 방학로 ***, 신우빌딩 *층 (방학동)
ValueCountFrequency (%)
서울특별시 1901
14.7%
도봉구 1900
14.7%
1891
14.7%
957
 
7.4%
창동 651
 
5.0%
560
 
4.3%
448
 
3.5%
방학동 392
 
3.0%
쌍문동 382
 
3.0%
도봉로***길 323
 
2.5%
Other values (862) 3495
27.1%
2024-05-11T05:06:05.016178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 13121
19.3%
11002
16.2%
3023
 
4.4%
2994
 
4.4%
2646
 
3.9%
, 2416
 
3.6%
2030
 
3.0%
) 1925
 
2.8%
( 1924
 
2.8%
1920
 
2.8%
Other values (349) 24952
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36483
53.7%
Other Punctuation 15610
23.0%
Space Separator 11002
 
16.2%
Close Punctuation 1925
 
2.8%
Open Punctuation 1924
 
2.8%
Dash Punctuation 392
 
0.6%
Decimal Number 343
 
0.5%
Uppercase Letter 171
 
0.3%
Lowercase Letter 92
 
0.1%
Other Symbol 8
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3023
 
8.3%
2994
 
8.2%
2646
 
7.3%
2030
 
5.6%
1920
 
5.3%
1920
 
5.3%
1907
 
5.2%
1901
 
5.2%
1901
 
5.2%
1891
 
5.2%
Other values (285) 14350
39.3%
Lowercase Letter
ValueCountFrequency (%)
w 12
13.0%
o 10
10.9%
r 8
8.7%
e 8
8.7%
k 8
8.7%
a 7
 
7.6%
c 6
 
6.5%
h 6
 
6.5%
p 5
 
5.4%
t 4
 
4.3%
Other values (10) 18
19.6%
Uppercase Letter
ValueCountFrequency (%)
B 55
32.2%
A 30
17.5%
S 25
14.6%
E 12
 
7.0%
Y 10
 
5.8%
O 7
 
4.1%
C 5
 
2.9%
D 4
 
2.3%
R 4
 
2.3%
Q 3
 
1.8%
Other values (9) 16
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 73
21.3%
0 52
15.2%
2 45
13.1%
4 39
11.4%
3 35
10.2%
6 26
 
7.6%
5 24
 
7.0%
8 20
 
5.8%
9 19
 
5.5%
7 10
 
2.9%
Other Punctuation
ValueCountFrequency (%)
* 13121
84.1%
, 2416
 
15.5%
@ 52
 
0.3%
. 15
 
0.1%
/ 4
 
< 0.1%
& 1
 
< 0.1%
: 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
11002
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1925
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1924
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 392
100.0%
Other Symbol
ValueCountFrequency (%)
8
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 36491
53.7%
Common 31198
45.9%
Latin 264
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3023
 
8.3%
2994
 
8.2%
2646
 
7.3%
2030
 
5.6%
1920
 
5.3%
1920
 
5.3%
1907
 
5.2%
1901
 
5.2%
1901
 
5.2%
1891
 
5.2%
Other values (286) 14358
39.3%
Latin
ValueCountFrequency (%)
B 55
20.8%
A 30
 
11.4%
S 25
 
9.5%
w 12
 
4.5%
E 12
 
4.5%
o 10
 
3.8%
Y 10
 
3.8%
r 8
 
3.0%
e 8
 
3.0%
k 8
 
3.0%
Other values (30) 86
32.6%
Common
ValueCountFrequency (%)
* 13121
42.1%
11002
35.3%
, 2416
 
7.7%
) 1925
 
6.2%
( 1924
 
6.2%
- 392
 
1.3%
1 73
 
0.2%
@ 52
 
0.2%
0 52
 
0.2%
2 45
 
0.1%
Other values (13) 196
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 36483
53.7%
ASCII 31461
46.3%
None 8
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 13121
41.7%
11002
35.0%
, 2416
 
7.7%
) 1925
 
6.1%
( 1924
 
6.1%
- 392
 
1.2%
1 73
 
0.2%
B 55
 
0.2%
@ 52
 
0.2%
0 52
 
0.2%
Other values (52) 449
 
1.4%
Hangul
ValueCountFrequency (%)
3023
 
8.3%
2994
 
8.2%
2646
 
7.3%
2030
 
5.6%
1920
 
5.3%
1920
 
5.3%
1907
 
5.2%
1901
 
5.2%
1901
 
5.2%
1891
 
5.2%
Other values (285) 14350
39.3%
None
ValueCountFrequency (%)
8
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct185
Distinct (%)9.8%
Missing467
Missing (%)19.8%
Infinite0
Infinite (%)0.0%
Mean1402.4781
Minimum1073
Maximum24059
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-05-11T05:06:05.551938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1073
5-th percentile1307
Q11342
median1395
Q31433.5
95-th percentile1473
Maximum24059
Range22986
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation523.51981
Coefficient of variation (CV)0.37328198
Kurtosis1854.9554
Mean1402.4781
Median Absolute Deviation (MAD)46
Skewness42.840088
Sum2657696
Variance274072.99
MonotonicityNot monotonic
2024-05-11T05:06:06.077506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1414 52
 
2.2%
1318 44
 
1.9%
1454 35
 
1.5%
1332 35
 
1.5%
1405 32
 
1.4%
1413 30
 
1.3%
1421 27
 
1.1%
1402 26
 
1.1%
1303 26
 
1.1%
1399 24
 
1.0%
Other values (175) 1564
66.2%
(Missing) 467
 
19.8%
ValueCountFrequency (%)
1073 1
 
< 0.1%
1300 3
 
0.1%
1301 7
 
0.3%
1302 10
 
0.4%
1303 26
1.1%
1304 10
 
0.4%
1305 12
0.5%
1306 19
0.8%
1307 12
0.5%
1308 10
 
0.4%
ValueCountFrequency (%)
24059 1
 
< 0.1%
1489 15
0.6%
1488 4
 
0.2%
1487 12
0.5%
1486 2
 
0.1%
1484 8
0.3%
1483 1
 
< 0.1%
1482 2
 
0.1%
1481 6
 
0.3%
1480 5
 
0.2%
Distinct2094
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
2024-05-11T05:06:06.933100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length6.5393734
Min length1

Characters and Unicode

Total characters15446
Distinct characters706
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1980 ?
Unique (%)83.8%

Sample

1st row명자다이어트
2nd row미건의료기(창동점)
3rd row광동메디칼도봉지점
4th row(주)이마트
5th row아모레도봉특약점
ValueCountFrequency (%)
아모레카운셀러 54
 
1.9%
하이리빙 35
 
1.3%
주식회사 33
 
1.2%
gs25 21
 
0.8%
창동점 18
 
0.6%
방학점 13
 
0.5%
다이어트 13
 
0.5%
암웨이 12
 
0.4%
애터미 12
 
0.4%
허브스토리 11
 
0.4%
Other values (2256) 2559
92.0%
2024-05-11T05:06:08.315006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
679
 
4.4%
443
 
2.9%
419
 
2.7%
329
 
2.1%
) 289
 
1.9%
( 281
 
1.8%
278
 
1.8%
252
 
1.6%
242
 
1.6%
236
 
1.5%
Other values (696) 11998
77.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13271
85.9%
Uppercase Letter 443
 
2.9%
Lowercase Letter 434
 
2.8%
Space Separator 419
 
2.7%
Close Punctuation 289
 
1.9%
Open Punctuation 281
 
1.8%
Decimal Number 249
 
1.6%
Other Punctuation 46
 
0.3%
Dash Punctuation 14
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
679
 
5.1%
443
 
3.3%
329
 
2.5%
278
 
2.1%
252
 
1.9%
242
 
1.8%
236
 
1.8%
188
 
1.4%
169
 
1.3%
165
 
1.2%
Other values (626) 10290
77.5%
Lowercase Letter
ValueCountFrequency (%)
e 50
11.5%
a 44
 
10.1%
o 38
 
8.8%
n 33
 
7.6%
t 33
 
7.6%
r 27
 
6.2%
i 25
 
5.8%
s 24
 
5.5%
w 19
 
4.4%
m 17
 
3.9%
Other values (15) 124
28.6%
Uppercase Letter
ValueCountFrequency (%)
S 81
18.3%
G 48
 
10.8%
A 32
 
7.2%
H 24
 
5.4%
N 24
 
5.4%
B 21
 
4.7%
I 20
 
4.5%
C 19
 
4.3%
D 19
 
4.3%
O 17
 
3.8%
Other values (14) 138
31.2%
Decimal Number
ValueCountFrequency (%)
2 72
28.9%
5 68
27.3%
0 20
 
8.0%
1 20
 
8.0%
4 19
 
7.6%
9 16
 
6.4%
3 15
 
6.0%
6 13
 
5.2%
8 3
 
1.2%
7 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 20
43.5%
& 11
23.9%
, 7
 
15.2%
? 4
 
8.7%
' 2
 
4.3%
; 1
 
2.2%
! 1
 
2.2%
Space Separator
ValueCountFrequency (%)
419
100.0%
Close Punctuation
ValueCountFrequency (%)
) 289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13270
85.9%
Common 1298
 
8.4%
Latin 877
 
5.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
679
 
5.1%
443
 
3.3%
329
 
2.5%
278
 
2.1%
252
 
1.9%
242
 
1.8%
236
 
1.8%
188
 
1.4%
169
 
1.3%
165
 
1.2%
Other values (625) 10289
77.5%
Latin
ValueCountFrequency (%)
S 81
 
9.2%
e 50
 
5.7%
G 48
 
5.5%
a 44
 
5.0%
o 38
 
4.3%
n 33
 
3.8%
t 33
 
3.8%
A 32
 
3.6%
r 27
 
3.1%
i 25
 
2.9%
Other values (39) 466
53.1%
Common
ValueCountFrequency (%)
419
32.3%
) 289
22.3%
( 281
21.6%
2 72
 
5.5%
5 68
 
5.2%
0 20
 
1.5%
1 20
 
1.5%
. 20
 
1.5%
4 19
 
1.5%
9 16
 
1.2%
Other values (11) 74
 
5.7%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13270
85.9%
ASCII 2175
 
14.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
679
 
5.1%
443
 
3.3%
329
 
2.5%
278
 
2.1%
252
 
1.9%
242
 
1.8%
236
 
1.8%
188
 
1.4%
169
 
1.3%
165
 
1.2%
Other values (625) 10289
77.5%
ASCII
ValueCountFrequency (%)
419
19.3%
) 289
 
13.3%
( 281
 
12.9%
S 81
 
3.7%
2 72
 
3.3%
5 68
 
3.1%
e 50
 
2.3%
G 48
 
2.2%
a 44
 
2.0%
o 38
 
1.7%
Other values (60) 785
36.1%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct2265
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum2004-03-20 00:00:00
Maximum2024-05-09 14:26:42
2024-05-11T05:06:08.760062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:06:09.611223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
I
1456 
U
906 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1456
61.6%
U 906
38.4%

Length

2024-05-11T05:06:10.121308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:10.553031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1456
61.6%
u 906
38.4%
Distinct685
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T05:06:11.179584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:06:11.779987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

좌표정보(X)
Real number (ℝ)

Distinct1196
Distinct (%)51.0%
Missing15
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean203407.31
Minimum201076.85
Maximum238219.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-05-11T05:06:12.375775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201076.85
5-th percentile202160.39
Q1202976.96
median203439.45
Q3203941.61
95-th percentile204383.78
Maximum238219.41
Range37142.553
Interquartile range (IQR)964.64807

Descriptive statistics

Standard deviation1004.689
Coefficient of variation (CV)0.0049392967
Kurtosis613.83584
Mean203407.31
Median Absolute Deviation (MAD)481.56387
Skewness17.493162
Sum4.7739695 × 108
Variance1009400.1
MonotonicityNot monotonic
2024-05-11T05:06:13.029695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204169.847670316 40
 
1.7%
203348.210556651 32
 
1.4%
204413.616574592 32
 
1.4%
203831.240616823 27
 
1.1%
204192.915094501 22
 
0.9%
203780.770313219 18
 
0.8%
202999.2675169 18
 
0.8%
203790.013568785 18
 
0.8%
203242.968498731 17
 
0.7%
202625.589439164 17
 
0.7%
Other values (1186) 2106
89.2%
ValueCountFrequency (%)
201076.85313831 2
0.1%
201080.934192453 1
 
< 0.1%
201098.761383515 1
 
< 0.1%
201103.54012205 4
0.2%
201104.585304581 1
 
< 0.1%
201112.008025201 2
0.1%
201122.155870704 2
0.1%
201128.59404573 1
 
< 0.1%
201130.167615522 1
 
< 0.1%
201141.657871469 1
 
< 0.1%
ValueCountFrequency (%)
238219.406104324 1
 
< 0.1%
205295.96383496 1
 
< 0.1%
204682.545958314 1
 
< 0.1%
204674.438928377 6
0.3%
204641.872260793 14
0.6%
204623.018873403 2
 
0.1%
204571.128614151 7
0.3%
204569.769384803 2
 
0.1%
204510.908809878 2
 
0.1%
204506.921108086 4
 
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct1196
Distinct (%)51.0%
Missing15
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean461827.06
Minimum458966.84
Maximum526275.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-05-11T05:06:13.713712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum458966.84
5-th percentile459817.77
Q1460855.12
median461632.33
Q3462628.03
95-th percentile464514.89
Maximum526275.34
Range67308.508
Interquartile range (IQR)1772.9086

Descriptive statistics

Standard deviation1890.0646
Coefficient of variation (CV)0.004092581
Kurtosis575.41316
Mean461827.06
Median Absolute Deviation (MAD)887.53242
Skewness17.06104
Sum1.0839081 × 109
Variance3572344.4
MonotonicityNot monotonic
2024-05-11T05:06:14.267068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464814.717432497 40
 
1.7%
461557.310544671 32
 
1.4%
461378.588676784 32
 
1.4%
460855.122289493 27
 
1.1%
461653.03000502 22
 
0.9%
461726.003547675 18
 
0.8%
460616.701327584 18
 
0.8%
462495.417040876 18
 
0.8%
460001.081136921 17
 
0.7%
460395.256601978 17
 
0.7%
Other values (1186) 2106
89.2%
ValueCountFrequency (%)
458966.835132155 1
< 0.1%
459009.265716602 2
0.1%
459019.059992346 1
< 0.1%
459045.100013686 2
0.1%
459052.547149504 2
0.1%
459052.90411219 1
< 0.1%
459054.652119336 1
< 0.1%
459076.349555381 1
< 0.1%
459117.006622619 1
< 0.1%
459124.768666401 2
0.1%
ValueCountFrequency (%)
526275.343392409 1
< 0.1%
465405.33344411 1
< 0.1%
465134.101701726 1
< 0.1%
465123.841705959 1
< 0.1%
465122.344733894 1
< 0.1%
465115.162846828 1
< 0.1%
465106.406054016 2
0.1%
465076.350406458 1
< 0.1%
465042.493324016 1
< 0.1%
465034.646663463 1
< 0.1%

위생업태명
Categorical

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
영업장판매
789 
<NA>
625 
전자상거래(통신판매업)
357 
방문판매
266 
통신판매
193 
Other values (3)
132 

Length

Max length12
Median length7
Mean length5.6071126
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업장판매 789
33.4%
<NA> 625
26.5%
전자상거래(통신판매업) 357
15.1%
방문판매 266
 
11.3%
통신판매 193
 
8.2%
다단계판매 121
 
5.1%
도매업(유통) 8
 
0.3%
전화권유판매 3
 
0.1%

Length

2024-05-11T05:06:14.847270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:15.276370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업장판매 789
33.4%
na 625
26.5%
전자상거래(통신판매업 357
15.1%
방문판매 266
 
11.3%
통신판매 193
 
8.2%
다단계판매 121
 
5.1%
도매업(유통 8
 
0.3%
전화권유판매 3
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2227 
0
 
135

Length

Max length4
Median length4
Mean length3.8285351
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> 2227
94.3%
0 135
 
5.7%

Length

2024-05-11T05:06:15.817953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:16.249419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2227
94.3%
0 135
 
5.7%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2227 
0
 
135

Length

Max length4
Median length4
Mean length3.8285351
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> 2227
94.3%
0 135
 
5.7%

Length

2024-05-11T05:06:16.697543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:17.090088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2227
94.3%
0 135
 
5.7%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2292 
상수도전용
 
70

Length

Max length5
Median length4
Mean length4.0296359
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> 2292
97.0%
상수도전용 70
 
3.0%

Length

2024-05-11T05:06:17.516033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:17.844514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2292
97.0%
상수도전용 70
 
3.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2230 
0
 
132

Length

Max length4
Median length4
Mean length3.8323455
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> 2230
94.4%
0 132
 
5.6%

Length

2024-05-11T05:06:18.307083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:18.733162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2230
94.4%
0 132
 
5.6%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1811 
0
550 
1
 
1

Length

Max length4
Median length4
Mean length3.3001693
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1811
76.7%
0 550
 
23.3%
1 1
 
< 0.1%

Length

2024-05-11T05:06:19.137931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:19.520666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1811
76.7%
0 550
 
23.3%
1 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1810 
0
551 
1
 
1

Length

Max length4
Median length4
Mean length3.2988992
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1810
76.6%
0 551
 
23.3%
1 1
 
< 0.1%

Length

2024-05-11T05:06:19.918452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:20.272360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1810
76.6%
0 551
 
23.3%
1 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1810 
0
546 
1
 
5
2
 
1

Length

Max length4
Median length4
Mean length3.2988992
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1810
76.6%
0 546
 
23.1%
1 5
 
0.2%
2 1
 
< 0.1%

Length

2024-05-11T05:06:20.629395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:20.968811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1810
76.6%
0 546
 
23.1%
1 5
 
0.2%
2 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1811 
0
551 

Length

Max length4
Median length4
Mean length3.3001693
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1811
76.7%
0 551
 
23.3%

Length

2024-05-11T05:06:21.481726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:21.898900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1811
76.7%
0 551
 
23.3%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
1508 
자가
431 
임대
423 

Length

Max length4
Median length4
Mean length3.276884
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1508
63.8%
자가 431
 
18.2%
임대 423
 
17.9%

Length

2024-05-11T05:06:22.498082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:22.986264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1508
63.8%
자가 431
 
18.2%
임대 423
 
17.9%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2074 
0
286 
25000000
 
1
10000000
 
1

Length

Max length8
Median length4
Mean length3.6401355
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2074
87.8%
0 286
 
12.1%
25000000 1
 
< 0.1%
10000000 1
 
< 0.1%

Length

2024-05-11T05:06:23.585598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:23.970942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2074
87.8%
0 286
 
12.1%
25000000 1
 
< 0.1%
10000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2074 
0
286 
1000000
 
1
1100000
 
1

Length

Max length7
Median length4
Mean length3.6392887
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2074
87.8%
0 286
 
12.1%
1000000 1
 
< 0.1%
1100000 1
 
< 0.1%

Length

2024-05-11T05:06:24.411123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:24.755619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2074
87.8%
0 286
 
12.1%
1000000 1
 
< 0.1%
1100000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing624
Missing (%)26.4%
Memory size4.7 KiB
False
1738 
(Missing)
624 
ValueCountFrequency (%)
False 1738
73.6%
(Missing) 624
 
26.4%
2024-05-11T05:06:25.033841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct89
Distinct (%)5.1%
Missing624
Missing (%)26.4%
Infinite0
Infinite (%)0.0%
Mean4.6163751
Minimum0
Maximum739
Zeros1572
Zeros (%)66.6%
Negative0
Negative (%)0.0%
Memory size20.9 KiB
2024-05-11T05:06:25.512835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile26.06
Maximum739
Range739
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.406333
Coefficient of variation (CV)6.370005
Kurtosis373.74032
Mean4.6163751
Median Absolute Deviation (MAD)0
Skewness16.912455
Sum8023.26
Variance864.73241
MonotonicityNot monotonic
2024-05-11T05:06:26.104270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1572
66.6%
33.0 17
 
0.7%
3.3 11
 
0.5%
24.0 6
 
0.3%
30.0 5
 
0.2%
15.0 5
 
0.2%
26.4 5
 
0.2%
49.5 4
 
0.2%
9.9 4
 
0.2%
26.0 4
 
0.2%
Other values (79) 105
 
4.4%
(Missing) 624
 
26.4%
ValueCountFrequency (%)
0.0 1572
66.6%
1.0 1
 
< 0.1%
2.4 1
 
< 0.1%
3.3 11
 
0.5%
4.0 1
 
< 0.1%
4.95 1
 
< 0.1%
5.0 1
 
< 0.1%
6.0 2
 
0.1%
6.27 1
 
< 0.1%
6.6 2
 
0.1%
ValueCountFrequency (%)
739.0 1
< 0.1%
660.0 1
< 0.1%
275.52 1
< 0.1%
198.0 2
0.1%
176.0 1
< 0.1%
168.0 1
< 0.1%
156.0 1
< 0.1%
136.65 1
< 0.1%
132.0 1
< 0.1%
128.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2362
Missing (%)100.0%
Memory size20.9 KiB

홈페이지
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
<NA>
2361 
9045003
 
1

Length

Max length7
Median length4
Mean length4.0012701
Min length4

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> 2361
> 99.9%
9045003 1
 
< 0.1%

Length

2024-05-11T05:06:26.796496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:06:27.212196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2361
> 99.9%
9045003 1
 
< 0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030900003090000-134-2003-0000120081106<NA>3폐업2폐업20180226<NA><NA><NA>02 990 3128.00132918서울특별시 도봉구 창동 ***-**번지서울특별시 도봉구 덕릉로**길 ** (창동)1470명자다이어트2018-02-26 13:19:37I2018-08-31 23:59:59.0<NA>203220.921406459746.924431방문판매<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
130900003090000-134-2004-0000120040319<NA>3폐업2폐업20070131<NA><NA><NA>02 9947785<NA>132904서울특별시 도봉구 창동 ***-**번지 *층<NA><NA>미건의료기(창동점)2004-03-20 00:00:00I2018-08-31 23:59:59.0<NA>203471.182492461627.080914영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230900003090000-134-2004-0000220040407<NA>3폐업2폐업20181127<NA><NA><NA><NA><NA>132821서울특별시 도봉구 도봉동 ***-**번지서울특별시 도봉구 도봉로***길 ** (도봉동)1327광동메디칼도봉지점2018-11-27 17:46:54U2018-11-29 02:40:00.0<NA>203946.932869463378.76703영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330900003090000-134-2004-000032004-04-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 9011234<NA>132-904서울특별시 도봉구 창동 ***-**서울특별시 도봉구 노해로**길 * (창동)1405(주)이마트2024-04-12 11:15:49U2023-12-03 23:04:00.0<NA>204107.090272461072.642449<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
430900003090000-134-2004-0000420040420<NA>3폐업2폐업20160617<NA><NA><NA>02 9920360233.00132893서울특별시 도봉구 쌍문동 ***번지 삼환웨딩프라자 빌딩 ***호서울특별시 도봉구 도봉로 *** (쌍문동,삼환웨딩프라자 빌딩 ***호)1432아모레도봉특약점2016-06-17 17:48:02I2018-08-31 23:59:59.0<NA>203348.210557461557.310545영업장판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
530900003090000-134-2004-0000520040426<NA>3폐업2폐업20080416<NA><NA><NA>023392027124.00132864서울특별시 도봉구 쌍문동 ***-**번지<NA><NA>(주)하이리빙 강북지점2007-05-09 00:00:00I2018-08-31 23:59:59.0<NA>202708.520221460186.02138영업장판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
630900003090000-134-2004-0000620040504<NA>3폐업2폐업20050822<NA><NA><NA>02 992200633.00132918서울특별시 도봉구 창동 ***-**번지<NA><NA>대상 웰라이프 도봉점2004-05-04 00:00:00I2018-08-31 23:59:59.0<NA>203137.482344459830.779556영업장판매<NA><NA><NA><NA><NA><NA>0000임대00N0.0<NA><NA><NA>
730900003090000-134-2004-000072004-05-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>197.42132-850서울특별시 도봉구 방학동 ***-**서울특별시 도봉구 방학로 ***, 신우빌딩 *층 (방학동)1345아모레도봉제일특약점2023-12-08 14:26:27U2022-11-01 23:00:00.0<NA>203502.673698462296.379602<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830900003090000-134-2004-0000820040518<NA>3폐업2폐업20060404<NA><NA><NA>02 9036268165.00132711서울특별시 도봉구 창동 **번지 제일빌딩 *층<NA><NA>남양알로에 창동영업국2004-05-18 00:00:00I2018-08-31 23:59:59.0<NA>204462.811446461156.296425방문판매<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
930900003090000-134-2004-0000920040518<NA>3폐업2폐업20060829<NA><NA><NA>02 996696359.40132919서울특별시 도봉구 창동 ***-**번지 *층<NA><NA>초이스정보2004-05-18 00:00:00I2018-08-31 23:59:59.0<NA>203406.89009460123.978283전자상거래(통신판매업)<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
235230900003090000-134-2024-000322024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-816서울특별시 도봉구 도봉동 *** 지층서울특별시 도봉구 도봉로***가길 **, 지층 (도봉동)1313스파클2024-04-09 14:23:22I2023-12-03 23:01:00.0<NA>203488.978821464143.085548<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235330900003090000-134-2024-000332024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-734서울특별시 도봉구 창동 ***-** 성원아파트 **층 ***동 *호서울특별시 도봉구 마들로**길 **, ***동 **층 *호 (창동, 성원아파트)1408제이제이 글로벌2024-04-15 09:36:12I2023-12-03 23:07:00.0<NA>204322.735946462047.520465<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235430900003090000-134-2024-000342024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-822서울특별시 도봉구 도봉동 *** *층서울특별시 도봉구 마들로 ***, *층 (도봉동)1330(주)스테오2024-04-22 14:25:10I2023-12-03 22:04:00.0<NA>204052.949128463179.786985<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235530900003090000-134-2024-000352024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-904서울특별시 도봉구 창동 ***-** M&W빌딩 *층서울특별시 도봉구 해등로 ***, M&W빌딩 *층 (창동)1401다비치안경 창동점2024-04-22 15:04:08I2023-12-03 22:04:00.0<NA>203456.527132461595.099133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235630900003090000-134-2024-000362024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 991 5583<NA>132-864서울특별시 도봉구 쌍문동 **-* 우림빌딩서울특별시 도봉구 도봉로 ***, 우림빌딩 *층 (쌍문동)1447서울이지아동발달클리닉2024-04-26 15:56:54I2023-12-03 22:08:00.0<NA>202871.080505460522.031749<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235730900003090000-134-2024-000372024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-917서울특별시 도봉구 창동 ***-**서울특별시 도봉구 덕릉로**길 *-*, 지층 (창동)1473우리건강 지킴2024-04-29 13:37:13I2023-12-05 00:01:00.0<NA>203433.904789459706.680749<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235830900003090000-134-2024-000382024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30132-863서울특별시 도봉구 쌍문동 **-*** *층서울특별시 도봉구 노해로 ***, *층 (쌍문동)1440혜당 생활과학 의료기2024-04-30 16:14:08I2023-12-05 00:02:00.0<NA>203086.031717461022.886643<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
235930900003090000-134-2024-000392024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-901서울특별시 도봉구 창동 ** 주공**단지아파트 ****동 ****호서울특별시 도봉구 덕릉로**길 **, ****동 ****호 (창동, 주공**단지아파트)1489별가온2024-05-02 14:01:51I2023-12-05 00:04:00.0<NA>204641.872261460205.497135<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236030900003090000-134-2024-000402024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>132-694서울특별시 도봉구 방학동 ***-* ESA 아파트 ***동 ***호서울특별시 도봉구 도봉로***길 **, ***동 ***호 (방학동, ESA 아파트)1332미뢰2024-05-08 09:35:06I2023-12-04 23:01:00.0<NA>203890.49271462686.077388<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
236130900003090000-134-2024-000412024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30132-925서울특별시 도봉구 창동 ***-** YS타워 지층서울특별시 도봉구 도봉로***길 **, YS타워 지층 (창동)1456창동 힐링 점핑2024-05-08 14:37:59I2023-12-04 23:01:00.0<NA>203243.218395460451.726155<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>