Overview

Dataset statistics

Number of variables44
Number of observations2295
Missing cells28810
Missing cells (%)28.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory845.1 KiB
Average record size in memory377.1 B

Variable types

Categorical18
Text8
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
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18085/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
남성종사자수 is highly imbalanced (67.7%)Imbalance
여성종사자수 is highly imbalanced (67.7%)Imbalance
급수시설구분명 is highly imbalanced (95.0%)Imbalance
총인원 is highly imbalanced (67.9%)Imbalance
공장사무직종업원수 is highly imbalanced (63.1%)Imbalance
공장판매직종업원수 is highly imbalanced (74.5%)Imbalance
보증액 is highly imbalanced (78.0%)Imbalance
월세액 is highly imbalanced (82.5%)Imbalance
인허가취소일자 has 2295 (100.0%) missing valuesMissing
폐업일자 has 659 (28.7%) missing valuesMissing
휴업시작일자 has 2295 (100.0%) missing valuesMissing
휴업종료일자 has 2295 (100.0%) missing valuesMissing
재개업일자 has 2295 (100.0%) missing valuesMissing
전화번호 has 1400 (61.0%) missing valuesMissing
소재지면적 has 1489 (64.9%) missing valuesMissing
도로명주소 has 413 (18.0%) missing valuesMissing
도로명우편번호 has 448 (19.5%) missing valuesMissing
업태구분명 has 2295 (100.0%) missing valuesMissing
좌표정보(X) has 35 (1.5%) missing valuesMissing
좌표정보(Y) has 35 (1.5%) missing valuesMissing
영업장주변구분명 has 2295 (100.0%) missing valuesMissing
등급구분명 has 2295 (100.0%) missing valuesMissing
다중이용업소여부 has 691 (30.1%) missing valuesMissing
시설총규모 has 691 (30.1%) missing valuesMissing
전통업소지정번호 has 2295 (100.0%) missing valuesMissing
전통업소주된음식 has 2295 (100.0%) missing valuesMissing
홈페이지 has 2294 (> 99.9%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 42.60140947)Skewed
좌표정보(X) is highly skewed (γ1 = 44.2027545)Skewed
좌표정보(Y) is highly skewed (γ1 = -41.98222061)Skewed
시설총규모 is highly skewed (γ1 = 27.37156695)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 1530 (66.7%) zerosZeros

Reproduction

Analysis started2024-05-18 00:52:56.123688
Analysis finished2024-05-18 00:52:59.022077
Duration2.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
3080000
2295 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3080000
2nd row3080000
3rd row3080000
4th row3080000
5th row3080000

Common Values

ValueCountFrequency (%)
3080000 2295
100.0%

Length

2024-05-18T09:52:59.204515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:52:59.480632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 2295
100.0%

관리번호
Text

UNIQUE 

Distinct2295
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2024-05-18T09:52:59.884922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters50490
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

Unique2295 ?
Unique (%)100.0%

Sample

1st row3080000-134-2004-00001
2nd row3080000-134-2004-00002
3rd row3080000-134-2004-00003
4th row3080000-134-2004-00004
5th row3080000-134-2004-00005
ValueCountFrequency (%)
3080000-134-2004-00001 1
 
< 0.1%
3080000-134-2019-00071 1
 
< 0.1%
3080000-134-2019-00073 1
 
< 0.1%
3080000-134-2019-00074 1
 
< 0.1%
3080000-134-2019-00075 1
 
< 0.1%
3080000-134-2019-00076 1
 
< 0.1%
3080000-134-2019-00077 1
 
< 0.1%
3080000-134-2019-00078 1
 
< 0.1%
3080000-134-2019-00072 1
 
< 0.1%
3080000-134-2019-00089 1
 
< 0.1%
Other values (2285) 2285
99.6%
2024-05-18T09:53:00.884746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21557
42.7%
- 6885
 
13.6%
3 5351
 
10.6%
1 4562
 
9.0%
2 3936
 
7.8%
4 3160
 
6.3%
8 2808
 
5.6%
5 595
 
1.2%
9 572
 
1.1%
6 552
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43605
86.4%
Dash Punctuation 6885
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21557
49.4%
3 5351
 
12.3%
1 4562
 
10.5%
2 3936
 
9.0%
4 3160
 
7.2%
8 2808
 
6.4%
5 595
 
1.4%
9 572
 
1.3%
6 552
 
1.3%
7 512
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 6885
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21557
42.7%
- 6885
 
13.6%
3 5351
 
10.6%
1 4562
 
9.0%
2 3936
 
7.8%
4 3160
 
6.3%
8 2808
 
5.6%
5 595
 
1.2%
9 572
 
1.1%
6 552
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21557
42.7%
- 6885
 
13.6%
3 5351
 
10.6%
1 4562
 
9.0%
2 3936
 
7.8%
4 3160
 
6.3%
8 2808
 
5.6%
5 595
 
1.2%
9 572
 
1.1%
6 552
 
1.1%
Distinct1629
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
Minimum2004-02-14 00:00:00
Maximum2024-05-14 00:00:00
2024-05-18T09:53:01.281889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:53:01.700301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
3
1636 
1
659 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1636
71.3%
1 659
28.7%

Length

2024-05-18T09:53:02.098877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:02.382557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1636
71.3%
1 659
28.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
폐업
1636 
영업/정상
659 

Length

Max length5
Median length2
Mean length2.8614379
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1636
71.3%
영업/정상 659
28.7%

Length

2024-05-18T09:53:02.720825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:03.033633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1636
71.3%
영업/정상 659
28.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2
1636 
1
659 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 1636
71.3%
1 659
28.7%

Length

2024-05-18T09:53:03.342183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:03.624954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1636
71.3%
1 659
28.7%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
폐업
1636 
영업
659 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1636
71.3%
영업 659
28.7%

Length

2024-05-18T09:53:03.937632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:04.227252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1636
71.3%
영업 659
28.7%

폐업일자
Date

MISSING 

Distinct1125
Distinct (%)68.8%
Missing659
Missing (%)28.7%
Memory size18.1 KiB
Minimum2004-05-11 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T09:53:04.527112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:53:04.779346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

전화번호
Text

MISSING 

Distinct850
Distinct (%)95.0%
Missing1400
Missing (%)61.0%
Memory size18.1 KiB
2024-05-18T09:53:05.376048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.12067
Min length2

Characters and Unicode

Total characters9953
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

Unique813 ?
Unique (%)90.8%

Sample

1st row02 9039476
2nd row02 9457955
3rd row02 9995522
4th row02 9978323
5th row02 9947488
ValueCountFrequency (%)
02 758
35.5%
070 57
 
2.7%
988 24
 
1.1%
945 23
 
1.1%
900 21
 
1.0%
989 19
 
0.9%
980 19
 
0.9%
987 17
 
0.8%
985 16
 
0.7%
983 16
 
0.7%
Other values (903) 1164
54.5%
2024-05-18T09:53:06.222685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1753
17.6%
0 1662
16.7%
2 1308
13.1%
9 1250
12.6%
8 797
8.0%
5 612
 
6.1%
7 603
 
6.1%
4 519
 
5.2%
1 506
 
5.1%
3 491
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8200
82.4%
Space Separator 1753
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1662
20.3%
2 1308
16.0%
9 1250
15.2%
8 797
9.7%
5 612
 
7.5%
7 603
 
7.4%
4 519
 
6.3%
1 506
 
6.2%
3 491
 
6.0%
6 452
 
5.5%
Space Separator
ValueCountFrequency (%)
1753
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9953
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1753
17.6%
0 1662
16.7%
2 1308
13.1%
9 1250
12.6%
8 797
8.0%
5 612
 
6.1%
7 603
 
6.1%
4 519
 
5.2%
1 506
 
5.1%
3 491
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9953
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1753
17.6%
0 1662
16.7%
2 1308
13.1%
9 1250
12.6%
8 797
8.0%
5 612
 
6.1%
7 603
 
6.1%
4 519
 
5.2%
1 506
 
5.1%
3 491
 
4.9%

소재지면적
Text

MISSING 

Distinct341
Distinct (%)42.3%
Missing1489
Missing (%)64.9%
Memory size18.1 KiB
2024-05-18T09:53:06.900965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.7320099
Min length3

Characters and Unicode

Total characters3814
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

Unique270 ?
Unique (%)33.5%

Sample

1st row82.65
2nd row33.00
3rd row100.00
4th row170.90
5th row27.00
ValueCountFrequency (%)
3.30 94
 
11.7%
00 64
 
7.9%
3.00 50
 
6.2%
33.00 20
 
2.5%
6.60 18
 
2.2%
0.00 13
 
1.6%
24.00 12
 
1.5%
6.00 11
 
1.4%
10.00 11
 
1.4%
26.40 11
 
1.4%
Other values (331) 502
62.3%
2024-05-18T09:53:07.903289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1099
28.8%
. 806
21.1%
3 420
 
11.0%
1 293
 
7.7%
2 266
 
7.0%
6 214
 
5.6%
5 176
 
4.6%
4 166
 
4.4%
9 139
 
3.6%
8 123
 
3.2%
Other values (2) 112
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3006
78.8%
Other Punctuation 808
 
21.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1099
36.6%
3 420
 
14.0%
1 293
 
9.7%
2 266
 
8.8%
6 214
 
7.1%
5 176
 
5.9%
4 166
 
5.5%
9 139
 
4.6%
8 123
 
4.1%
7 110
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 806
99.8%
, 2
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 3814
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1099
28.8%
. 806
21.1%
3 420
 
11.0%
1 293
 
7.7%
2 266
 
7.0%
6 214
 
5.6%
5 176
 
4.6%
4 166
 
4.4%
9 139
 
3.6%
8 123
 
3.2%
Other values (2) 112
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1099
28.8%
. 806
21.1%
3 420
 
11.0%
1 293
 
7.7%
2 266
 
7.0%
6 214
 
5.6%
5 176
 
4.6%
4 166
 
4.4%
9 139
 
3.6%
8 123
 
3.2%
Other values (2) 112
 
2.9%
Distinct150
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2024-05-18T09:53:08.498910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1982571
Min length6

Characters and Unicode

Total characters14225
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

Unique25 ?
Unique (%)1.1%

Sample

1st row142100
2nd row142801
3rd row142805
4th row142865
5th row142865
ValueCountFrequency (%)
142100 144
 
6.3%
142867 83
 
3.6%
142804 77
 
3.4%
142070 77
 
3.4%
142878 77
 
3.4%
142876 70
 
3.1%
142809 61
 
2.7%
142874 57
 
2.5%
142810 52
 
2.3%
142877 51
 
2.2%
Other values (140) 1546
67.4%
2024-05-18T09:53:09.371748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2918
20.5%
2 2638
18.5%
4 2610
18.3%
8 2289
16.1%
0 1222
8.6%
7 921
 
6.5%
6 599
 
4.2%
- 455
 
3.2%
9 222
 
1.6%
5 194
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13770
96.8%
Dash Punctuation 455
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2918
21.2%
2 2638
19.2%
4 2610
19.0%
8 2289
16.6%
0 1222
8.9%
7 921
 
6.7%
6 599
 
4.4%
9 222
 
1.6%
5 194
 
1.4%
3 157
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 455
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14225
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2918
20.5%
2 2638
18.5%
4 2610
18.3%
8 2289
16.1%
0 1222
8.6%
7 921
 
6.5%
6 599
 
4.2%
- 455
 
3.2%
9 222
 
1.6%
5 194
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2918
20.5%
2 2638
18.5%
4 2610
18.3%
8 2289
16.1%
0 1222
8.6%
7 921
 
6.5%
6 599
 
4.2%
- 455
 
3.2%
9 222
 
1.6%
5 194
 
1.4%
Distinct1162
Distinct (%)50.6%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2024-05-18T09:53:09.977941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length26.709368
Min length17

Characters and Unicode

Total characters61298
Distinct characters387
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique960 ?
Unique (%)41.8%

Sample

1st row서울특별시 강북구 미아동 ****번지 SK주상가 ***호
2nd row서울특별시 강북구 미아동 *-***번지 상원빌딩 *층
3rd row서울특별시 강북구 미아동 ***-**번지 송원빌딩 *층
4th row서울특별시 강북구 번동 ***-**번지
5th row서울특별시 강북구 번동 ***-**번지
ValueCountFrequency (%)
서울특별시 2294
19.8%
강북구 2291
19.7%
번지 1256
10.8%
1239
10.7%
미아동 998
8.6%
수유동 840
 
7.2%
번동 399
 
3.4%
300
 
2.6%
290
 
2.5%
83
 
0.7%
Other values (773) 1614
13.9%
2024-05-18T09:53:10.749949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 12826
20.9%
10774
17.6%
2490
 
4.1%
2370
 
3.9%
2363
 
3.9%
2307
 
3.8%
2304
 
3.8%
2300
 
3.8%
2300
 
3.8%
2297
 
3.7%
Other values (377) 18967
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34665
56.6%
Other Punctuation 12899
 
21.0%
Space Separator 10774
 
17.6%
Dash Punctuation 2063
 
3.4%
Open Punctuation 249
 
0.4%
Close Punctuation 249
 
0.4%
Uppercase Letter 199
 
0.3%
Decimal Number 171
 
0.3%
Lowercase Letter 28
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2490
 
7.2%
2370
 
6.8%
2363
 
6.8%
2307
 
6.7%
2304
 
6.6%
2300
 
6.6%
2300
 
6.6%
2297
 
6.6%
2294
 
6.6%
1677
 
4.8%
Other values (325) 11963
34.5%
Uppercase Letter
ValueCountFrequency (%)
S 56
28.1%
K 55
27.6%
B 30
15.1%
A 23
11.6%
F 7
 
3.5%
J 4
 
2.0%
G 3
 
1.5%
C 3
 
1.5%
D 3
 
1.5%
O 3
 
1.5%
Other values (7) 12
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
s 6
21.4%
k 5
17.9%
e 3
10.7%
c 2
 
7.1%
o 2
 
7.1%
m 2
 
7.1%
a 1
 
3.6%
h 1
 
3.6%
f 1
 
3.6%
n 1
 
3.6%
Other values (4) 4
14.3%
Decimal Number
ValueCountFrequency (%)
1 39
22.8%
3 25
14.6%
2 23
13.5%
0 19
11.1%
7 18
10.5%
4 16
9.4%
6 14
 
8.2%
8 8
 
4.7%
9 5
 
2.9%
5 4
 
2.3%
Other Punctuation
ValueCountFrequency (%)
* 12826
99.4%
, 36
 
0.3%
. 24
 
0.2%
@ 10
 
0.1%
/ 2
 
< 0.1%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
10774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2063
100.0%
Open Punctuation
ValueCountFrequency (%)
( 249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34663
56.5%
Common 26406
43.1%
Latin 227
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2490
 
7.2%
2370
 
6.8%
2363
 
6.8%
2307
 
6.7%
2304
 
6.6%
2300
 
6.6%
2300
 
6.6%
2297
 
6.6%
2294
 
6.6%
1677
 
4.8%
Other values (323) 11961
34.5%
Latin
ValueCountFrequency (%)
S 56
24.7%
K 55
24.2%
B 30
13.2%
A 23
10.1%
F 7
 
3.1%
s 6
 
2.6%
k 5
 
2.2%
J 4
 
1.8%
G 3
 
1.3%
e 3
 
1.3%
Other values (21) 35
15.4%
Common
ValueCountFrequency (%)
* 12826
48.6%
10774
40.8%
- 2063
 
7.8%
( 249
 
0.9%
) 249
 
0.9%
1 39
 
0.1%
, 36
 
0.1%
3 25
 
0.1%
. 24
 
0.1%
2 23
 
0.1%
Other values (11) 98
 
0.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34663
56.5%
ASCII 26633
43.4%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 12826
48.2%
10774
40.5%
- 2063
 
7.7%
( 249
 
0.9%
) 249
 
0.9%
S 56
 
0.2%
K 55
 
0.2%
1 39
 
0.1%
, 36
 
0.1%
B 30
 
0.1%
Other values (42) 256
 
1.0%
Hangul
ValueCountFrequency (%)
2490
 
7.2%
2370
 
6.8%
2363
 
6.8%
2307
 
6.7%
2304
 
6.6%
2300
 
6.6%
2300
 
6.6%
2297
 
6.6%
2294
 
6.6%
1677
 
4.8%
Other values (323) 11961
34.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct1245
Distinct (%)66.2%
Missing413
Missing (%)18.0%
Memory size18.1 KiB
2024-05-18T09:53:11.180924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length46
Mean length33.722635
Min length21

Characters and Unicode

Total characters63466
Distinct characters371
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1014 ?
Unique (%)53.9%

Sample

1st row서울특별시 강북구 숭인로 ** (미아동,송원빌딩 *층)
2nd row서울특별시 강북구 한천로 **** (번동)
3rd row서울특별시 강북구 오패산로**길 * (번동)
4th row서울특별시 강북구 도봉로 ***, 청암빌딩 *층 ***호 (미아동)
5th row서울특별시 강북구 솔샘로**길 **, *층 (미아동)
ValueCountFrequency (%)
1965
16.1%
서울특별시 1881
15.4%
강북구 1880
15.4%
미아동 712
 
5.8%
675
 
5.5%
613
 
5.0%
수유동 595
 
4.9%
도봉로 301
 
2.5%
번동 273
 
2.2%
도봉로**길 204
 
1.7%
Other values (887) 3123
25.6%
2024-05-18T09:53:11.894419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 11198
17.6%
10346
 
16.3%
2213
 
3.5%
, 2050
 
3.2%
) 2018
 
3.2%
( 2018
 
3.2%
1946
 
3.1%
1946
 
3.1%
1929
 
3.0%
1892
 
3.0%
Other values (361) 25910
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34932
55.0%
Other Punctuation 13291
 
20.9%
Space Separator 10346
 
16.3%
Close Punctuation 2018
 
3.2%
Open Punctuation 2018
 
3.2%
Dash Punctuation 383
 
0.6%
Uppercase Letter 234
 
0.4%
Decimal Number 227
 
0.4%
Lowercase Letter 14
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2213
 
6.3%
1946
 
5.6%
1946
 
5.6%
1929
 
5.5%
1892
 
5.4%
1891
 
5.4%
1887
 
5.4%
1884
 
5.4%
1884
 
5.4%
1881
 
5.4%
Other values (312) 15579
44.6%
Uppercase Letter
ValueCountFrequency (%)
B 63
26.9%
S 47
20.1%
K 47
20.1%
A 30
12.8%
J 7
 
3.0%
R 6
 
2.6%
F 6
 
2.6%
D 5
 
2.1%
C 5
 
2.1%
H 3
 
1.3%
Other values (7) 15
 
6.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
14.3%
s 2
14.3%
k 2
14.3%
u 1
7.1%
n 1
7.1%
b 1
7.1%
c 1
7.1%
m 1
7.1%
o 1
7.1%
a 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 51
22.5%
2 41
18.1%
0 29
12.8%
4 25
11.0%
6 17
 
7.5%
3 17
 
7.5%
7 15
 
6.6%
5 12
 
5.3%
9 11
 
4.8%
8 9
 
4.0%
Other Punctuation
ValueCountFrequency (%)
* 11198
84.3%
, 2050
 
15.4%
. 29
 
0.2%
@ 9
 
0.1%
/ 3
 
< 0.1%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
10346
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2018
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2018
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 383
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34930
55.0%
Common 28286
44.6%
Latin 248
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2213
 
6.3%
1946
 
5.6%
1946
 
5.6%
1929
 
5.5%
1892
 
5.4%
1891
 
5.4%
1887
 
5.4%
1884
 
5.4%
1884
 
5.4%
1881
 
5.4%
Other values (310) 15577
44.6%
Latin
ValueCountFrequency (%)
B 63
25.4%
S 47
19.0%
K 47
19.0%
A 30
12.1%
J 7
 
2.8%
R 6
 
2.4%
F 6
 
2.4%
D 5
 
2.0%
C 5
 
2.0%
H 3
 
1.2%
Other values (18) 29
11.7%
Common
ValueCountFrequency (%)
* 11198
39.6%
10346
36.6%
, 2050
 
7.2%
) 2018
 
7.1%
( 2018
 
7.1%
- 383
 
1.4%
1 51
 
0.2%
2 41
 
0.1%
0 29
 
0.1%
. 29
 
0.1%
Other values (11) 123
 
0.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34930
55.0%
ASCII 28534
45.0%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 11198
39.2%
10346
36.3%
, 2050
 
7.2%
) 2018
 
7.1%
( 2018
 
7.1%
- 383
 
1.3%
B 63
 
0.2%
1 51
 
0.2%
S 47
 
0.2%
K 47
 
0.2%
Other values (39) 313
 
1.1%
Hangul
ValueCountFrequency (%)
2213
 
6.3%
1946
 
5.6%
1946
 
5.6%
1929
 
5.5%
1892
 
5.4%
1891
 
5.4%
1887
 
5.4%
1884
 
5.4%
1884
 
5.4%
1881
 
5.4%
Other values (310) 15577
44.6%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct222
Distinct (%)12.0%
Missing448
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean1139.7807
Minimum1001
Maximum38628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.3 KiB
2024-05-18T09:53:12.196483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1024
Q11062
median1117
Q31179
95-th percentile1223
Maximum38628
Range37627
Interquartile range (IQR)117

Descriptive statistics

Standard deviation875.3168
Coefficient of variation (CV)0.76796947
Kurtosis1825.5083
Mean1139.7807
Median Absolute Deviation (MAD)60
Skewness42.601409
Sum2105175
Variance766179.49
MonotonicityNot monotonic
2024-05-18T09:53:12.475523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1062 60
 
2.6%
1192 52
 
2.3%
1215 42
 
1.8%
1073 33
 
1.4%
1054 31
 
1.4%
1161 30
 
1.3%
1170 27
 
1.2%
1114 24
 
1.0%
1118 23
 
1.0%
1041 23
 
1.0%
Other values (212) 1502
65.4%
(Missing) 448
 
19.5%
ValueCountFrequency (%)
1001 4
 
0.2%
1002 8
0.3%
1003 4
 
0.2%
1004 5
0.2%
1005 6
0.3%
1006 12
0.5%
1009 1
 
< 0.1%
1010 3
 
0.1%
1011 1
 
< 0.1%
1012 2
 
0.1%
ValueCountFrequency (%)
38628 1
 
< 0.1%
1464 1
 
< 0.1%
1237 7
0.3%
1236 8
0.3%
1234 8
0.3%
1233 8
0.3%
1232 3
 
0.1%
1231 4
 
0.2%
1230 15
0.7%
1229 2
 
0.1%
Distinct2101
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
2024-05-18T09:53:13.155592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length25
Mean length6.4936819
Min length2

Characters and Unicode

Total characters14903
Distinct characters711
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1988 ?
Unique (%)86.6%

Sample

1st row유기농미생채
2nd row케어베스트
3rd row로즈마리의원
4th row예일소아과의원
5th row예스숍
ValueCountFrequency (%)
주식회사 29
 
1.1%
하이리빙 16
 
0.6%
허브다이어트 16
 
0.6%
다이어트 13
 
0.5%
미아점 12
 
0.5%
세븐일레븐 11
 
0.4%
한국암웨이 10
 
0.4%
수유점 9
 
0.3%
허브 8
 
0.3%
gs25 8
 
0.3%
Other values (2221) 2488
95.0%
2024-05-18T09:53:14.111782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
637
 
4.3%
417
 
2.8%
325
 
2.2%
302
 
2.0%
293
 
2.0%
290
 
1.9%
) 272
 
1.8%
( 271
 
1.8%
247
 
1.7%
230
 
1.5%
Other values (701) 11619
78.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12969
87.0%
Uppercase Letter 417
 
2.8%
Lowercase Letter 408
 
2.7%
Space Separator 325
 
2.2%
Close Punctuation 272
 
1.8%
Open Punctuation 271
 
1.8%
Decimal Number 194
 
1.3%
Other Punctuation 27
 
0.2%
Dash Punctuation 19
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
637
 
4.9%
417
 
3.2%
302
 
2.3%
293
 
2.3%
290
 
2.2%
247
 
1.9%
230
 
1.8%
212
 
1.6%
204
 
1.6%
200
 
1.5%
Other values (631) 9937
76.6%
Uppercase Letter
ValueCountFrequency (%)
S 68
16.3%
G 51
 
12.2%
N 30
 
7.2%
A 22
 
5.3%
H 22
 
5.3%
I 21
 
5.0%
O 20
 
4.8%
J 17
 
4.1%
B 17
 
4.1%
L 16
 
3.8%
Other values (15) 133
31.9%
Lowercase Letter
ValueCountFrequency (%)
e 53
13.0%
o 50
12.3%
a 33
 
8.1%
n 31
 
7.6%
r 28
 
6.9%
i 27
 
6.6%
t 22
 
5.4%
s 20
 
4.9%
l 20
 
4.9%
d 17
 
4.2%
Other values (13) 107
26.2%
Decimal Number
ValueCountFrequency (%)
2 66
34.0%
5 59
30.4%
6 16
 
8.2%
4 13
 
6.7%
1 11
 
5.7%
3 11
 
5.7%
0 10
 
5.2%
9 4
 
2.1%
8 3
 
1.5%
7 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 9
33.3%
& 6
22.2%
? 6
22.2%
, 3
 
11.1%
' 1
 
3.7%
! 1
 
3.7%
# 1
 
3.7%
Space Separator
ValueCountFrequency (%)
325
100.0%
Close Punctuation
ValueCountFrequency (%)
) 272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 271
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12967
87.0%
Common 1109
 
7.4%
Latin 825
 
5.5%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
637
 
4.9%
417
 
3.2%
302
 
2.3%
293
 
2.3%
290
 
2.2%
247
 
1.9%
230
 
1.8%
212
 
1.6%
204
 
1.6%
200
 
1.5%
Other values (629) 9935
76.6%
Latin
ValueCountFrequency (%)
S 68
 
8.2%
e 53
 
6.4%
G 51
 
6.2%
o 50
 
6.1%
a 33
 
4.0%
n 31
 
3.8%
N 30
 
3.6%
r 28
 
3.4%
i 27
 
3.3%
A 22
 
2.7%
Other values (38) 432
52.4%
Common
ValueCountFrequency (%)
325
29.3%
) 272
24.5%
( 271
24.4%
2 66
 
6.0%
5 59
 
5.3%
- 19
 
1.7%
6 16
 
1.4%
4 13
 
1.2%
1 11
 
1.0%
3 11
 
1.0%
Other values (12) 46
 
4.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12967
87.0%
ASCII 1934
 
13.0%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
637
 
4.9%
417
 
3.2%
302
 
2.3%
293
 
2.3%
290
 
2.2%
247
 
1.9%
230
 
1.8%
212
 
1.6%
204
 
1.6%
200
 
1.5%
Other values (629) 9935
76.6%
ASCII
ValueCountFrequency (%)
325
16.8%
) 272
 
14.1%
( 271
 
14.0%
S 68
 
3.5%
2 66
 
3.4%
5 59
 
3.1%
e 53
 
2.7%
G 51
 
2.6%
o 50
 
2.6%
a 33
 
1.7%
Other values (60) 686
35.5%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct2212
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
Minimum2004-03-31 00:00:00
Maximum2024-05-16 18:33:47
2024-05-18T09:53:14.519687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:53:14.954472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
I
1394 
U
901 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1394
60.7%
U 901
39.3%

Length

2024-05-18T09:53:15.374108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:15.668573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1394
60.7%
u 901
39.3%
Distinct693
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-18T09:53:16.002854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:53:16.427145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING  SKEWED 

Distinct1395
Distinct (%)61.7%
Missing35
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean202073.27
Minimum200265.86
Maximum356617.17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.3 KiB
2024-05-18T09:53:17.030086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200265.86
5-th percentile200928.94
Q1201495.9
median202014.64
Q3202461.94
95-th percentile203213.01
Maximum356617.17
Range156351.31
Interquartile range (IQR)966.03291

Descriptive statistics

Standard deviation3332.5424
Coefficient of variation (CV)0.016491753
Kurtosis2049.8297
Mean202073.27
Median Absolute Deviation (MAD)476.80002
Skewness44.202755
Sum4.5668559 × 108
Variance11105839
MonotonicityNot monotonic
2024-05-18T09:53:17.497664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201045.611312321 57
 
2.5%
202625.646264572 40
 
1.7%
202155.401317068 33
 
1.4%
201606.445832012 24
 
1.0%
200886.333781015 20
 
0.9%
201731.684416461 19
 
0.8%
202032.757631932 15
 
0.7%
202465.042504763 15
 
0.7%
202228.431717714 15
 
0.7%
201530.926516903 14
 
0.6%
Other values (1385) 2008
87.5%
(Missing) 35
 
1.5%
ValueCountFrequency (%)
200265.862283018 1
< 0.1%
200279.459422208 1
< 0.1%
200379.899453178 1
< 0.1%
200414.365717827 1
< 0.1%
200458.131223977 1
< 0.1%
200507.690201067 1
< 0.1%
200508.093539335 1
< 0.1%
200529.76116563 1
< 0.1%
200536.752063254 1
< 0.1%
200556.255190334 1
< 0.1%
ValueCountFrequency (%)
356617.172394402 1
 
< 0.1%
212921.096131717 1
 
< 0.1%
204089.673173372 13
0.6%
204083.177112537 1
 
< 0.1%
203981.35 3
 
0.1%
203975.790220599 1
 
< 0.1%
203938.252559434 1
 
< 0.1%
203932.991517795 3
 
0.1%
203874.192185321 2
 
0.1%
203833.459463804 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING  SKEWED 

Distinct1395
Distinct (%)61.7%
Missing35
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean458644.08
Minimum259390.17
Maximum462238.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.3 KiB
2024-05-18T09:53:17.931911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum259390.17
5-th percentile456875.97
Q1457645.18
median458756.89
Q3459729.78
95-th percentile460517.35
Maximum462238.8
Range202848.62
Interquartile range (IQR)2084.5943

Descriptive statistics

Standard deviation4370.5219
Coefficient of variation (CV)0.0095292234
Kurtosis1914.5048
Mean458644.08
Median Absolute Deviation (MAD)1035.3451
Skewness-41.982221
Sum1.0365356 × 109
Variance19101462
MonotonicityNot monotonic
2024-05-18T09:53:18.468249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
457292.961457264 57
 
2.5%
456875.973976242 40
 
1.7%
459411.940883021 33
 
1.4%
460001.632075829 24
 
1.0%
457645.184347648 20
 
0.9%
457219.335594234 19
 
0.8%
459259.443978524 15
 
0.7%
457640.23984676 15
 
0.7%
458158.105668456 15
 
0.7%
456987.839409342 14
 
0.6%
Other values (1385) 2008
87.5%
(Missing) 35
 
1.5%
ValueCountFrequency (%)
259390.173506214 1
< 0.1%
448633.774021252 1
< 0.1%
456219.797491714 1
< 0.1%
456360.433254943 1
< 0.1%
456377.651999255 1
< 0.1%
456442.951197483 2
0.1%
456473.886142136 1
< 0.1%
456495.652435006 1
< 0.1%
456528.977767312 1
< 0.1%
456565.910124276 1
< 0.1%
ValueCountFrequency (%)
462238.797763435 1
 
< 0.1%
462226.287725886 1
 
< 0.1%
462190.323651894 1
 
< 0.1%
462160.312358665 3
0.1%
462155.182142037 1
 
< 0.1%
462125.747036509 1
 
< 0.1%
462096.302470558 1
 
< 0.1%
462094.995937209 1
 
< 0.1%
462091.982159615 1
 
< 0.1%
462086.429119874 1
 
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
영업장판매
860 
<NA>
691 
전자상거래(통신판매업)
383 
방문판매
158 
다단계판매
124 
Other values (6)
 
79

Length

Max length14
Median length12
Mean length5.779085
Min length4

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row영업장판매
2nd row통신판매
3rd row영업장판매
4th row영업장판매
5th row영업장판매

Common Values

ValueCountFrequency (%)
영업장판매 860
37.5%
<NA> 691
30.1%
전자상거래(통신판매업) 383
16.7%
방문판매 158
 
6.9%
다단계판매 124
 
5.4%
통신판매 69
 
3.0%
도매업(유통) 4
 
0.2%
전화권유판매 3
 
0.1%
기타(복합 등) 1
 
< 0.1%
자동판매기판매 1
 
< 0.1%

Length

2024-05-18T09:53:18.921488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 860
37.4%
na 691
30.1%
전자상거래(통신판매업 383
16.7%
방문판매 158
 
6.9%
다단계판매 124
 
5.4%
통신판매 69
 
3.0%
도매업(유통 4
 
0.2%
전화권유판매 3
 
0.1%
기타(복합 1
 
< 0.1%
1
 
< 0.1%
Other values (3) 3
 
0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2160 
0
 
135

Length

Max length4
Median length4
Mean length3.8235294
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> 2160
94.1%
0 135
 
5.9%

Length

2024-05-18T09:53:19.316051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:19.638022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2160
94.1%
0 135
 
5.9%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2160 
0
 
135

Length

Max length4
Median length4
Mean length3.8235294
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> 2160
94.1%
0 135
 
5.9%

Length

2024-05-18T09:53:20.032349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:20.314049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2160
94.1%
0 135
 
5.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2282 
상수도전용
 
13

Length

Max length5
Median length4
Mean length4.0056645
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> 2282
99.4%
상수도전용 13
 
0.6%

Length

2024-05-18T09:53:20.602922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:20.878377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2282
99.4%
상수도전용 13
 
0.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2161 
0
 
134

Length

Max length4
Median length4
Mean length3.8248366
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> 2161
94.2%
0 134
 
5.8%

Length

2024-05-18T09:53:21.443177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:21.717626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2161
94.2%
0 134
 
5.8%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
1977 
0
318 

Length

Max length4
Median length4
Mean length3.5843137
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> 1977
86.1%
0 318
 
13.9%

Length

2024-05-18T09:53:22.027394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:22.282585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1977
86.1%
0 318
 
13.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
1977 
0
317 
3
 
1

Length

Max length4
Median length4
Mean length3.5843137
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1977
86.1%
0 317
 
13.8%
3 1
 
< 0.1%

Length

2024-05-18T09:53:22.604987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:22.922229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1977
86.1%
0 317
 
13.8%
3 1
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
1977 
0
315 
5
 
1
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.5843137
Min length1

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1977
86.1%
0 315
 
13.7%
5 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-05-18T09:53:23.331365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:23.667385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1977
86.1%
0 315
 
13.7%
5 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
1977 
0
318 

Length

Max length4
Median length4
Mean length3.5843137
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> 1977
86.1%
0 318
 
13.9%

Length

2024-05-18T09:53:24.032297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:24.337108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1977
86.1%
0 318
 
13.9%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
1745 
임대
323 
자가
227 

Length

Max length4
Median length4
Mean length3.5206972
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> 1745
76.0%
임대 323
 
14.1%
자가 227
 
9.9%

Length

2024-05-18T09:53:24.701705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:25.046724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1745
76.0%
임대 323
 
14.1%
자가 227
 
9.9%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2149 
0
 
144
1000000
 
2

Length

Max length7
Median length4
Mean length3.8143791
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> 2149
93.6%
0 144
 
6.3%
1000000 2
 
0.1%

Length

2024-05-18T09:53:25.395558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:25.641851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2149
93.6%
0 144
 
6.3%
1000000 2
 
0.1%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.1 KiB
<NA>
2149 
0
 
144
200000
 
1
2000000
 
1

Length

Max length7
Median length4
Mean length3.8139434
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2149
93.6%
0 144
 
6.3%
200000 1
 
< 0.1%
2000000 1
 
< 0.1%

Length

2024-05-18T09:53:25.834935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:53:26.065491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2149
93.6%
0 144
 
6.3%
200000 1
 
< 0.1%
2000000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing691
Missing (%)30.1%
Memory size4.6 KiB
False
1604 
(Missing)
691 
ValueCountFrequency (%)
False 1604
69.9%
(Missing) 691
30.1%
2024-05-18T09:53:26.344342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct53
Distinct (%)3.3%
Missing691
Missing (%)30.1%
Infinite0
Infinite (%)0.0%
Mean3.5832606
Minimum0
Maximum1323
Zeros1530
Zeros (%)66.7%
Negative0
Negative (%)0.0%
Memory size20.3 KiB
2024-05-18T09:53:26.686971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1323
Range1323
Interquartile range (IQR)0

Descriptive statistics

Standard deviation38.083027
Coefficient of variation (CV)10.628037
Kurtosis909.79778
Mean3.5832606
Median Absolute Deviation (MAD)0
Skewness27.371567
Sum5747.55
Variance1450.3169
MonotonicityNot monotonic
2024-05-18T09:53:27.213552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1530
66.7%
33.0 8
 
0.3%
3.3 4
 
0.2%
24.0 3
 
0.1%
120.0 2
 
0.1%
19.8 2
 
0.1%
45.0 2
 
0.1%
21.0 2
 
0.1%
9.9 2
 
0.1%
99.0 2
 
0.1%
Other values (43) 47
 
2.0%
(Missing) 691
30.1%
ValueCountFrequency (%)
0.0 1530
66.7%
3.3 4
 
0.2%
6.0 1
 
< 0.1%
6.6 1
 
< 0.1%
9.9 2
 
0.1%
13.2 1
 
< 0.1%
15.0 1
 
< 0.1%
17.7 1
 
< 0.1%
18.0 2
 
0.1%
18.86 1
 
< 0.1%
ValueCountFrequency (%)
1323.0 1
< 0.1%
404.58 1
< 0.1%
221.85 1
< 0.1%
200.0 1
< 0.1%
194.0 1
< 0.1%
173.55 1
< 0.1%
169.86 1
< 0.1%
164.0 1
< 0.1%
160.0 1
< 0.1%
154.48 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2295
Missing (%)100.0%
Memory size20.3 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing2294
Missing (%)> 99.9%
Memory size18.1 KiB
2024-05-18T09:53:27.644847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowwww.roadwalk.co.kr
ValueCountFrequency (%)
www.roadwalk.co.kr 1
100.0%
2024-05-18T09:53:28.343020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 4
22.2%
. 3
16.7%
r 2
11.1%
o 2
11.1%
a 2
11.1%
k 2
11.1%
d 1
 
5.6%
l 1
 
5.6%
c 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15
83.3%
Other Punctuation 3
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 4
26.7%
r 2
13.3%
o 2
13.3%
a 2
13.3%
k 2
13.3%
d 1
 
6.7%
l 1
 
6.7%
c 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15
83.3%
Common 3
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 4
26.7%
r 2
13.3%
o 2
13.3%
a 2
13.3%
k 2
13.3%
d 1
 
6.7%
l 1
 
6.7%
c 1
 
6.7%
Common
ValueCountFrequency (%)
. 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 4
22.2%
. 3
16.7%
r 2
11.1%
o 2
11.1%
a 2
11.1%
k 2
11.1%
d 1
 
5.6%
l 1
 
5.6%
c 1
 
5.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-134-2004-0000120040329<NA>3폐업2폐업20190530<NA><NA><NA>02 9039476<NA>142100서울특별시 강북구 미아동 ****번지 SK주상가 ***호<NA><NA>유기농미생채2019-05-30 13:38:39U2019-06-01 02:40:00.0<NA>201045.611312457292.961457영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130800003080000-134-2004-0000220040331<NA>3폐업2폐업20040623<NA><NA><NA><NA><NA>142801서울특별시 강북구 미아동 *-***번지 상원빌딩 *층<NA><NA>케어베스트2004-03-31 00:00:00I2018-08-31 23:59:59.0<NA>202949.35765457154.744565통신판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230800003080000-134-2004-0000320040408<NA>3폐업2폐업20170719<NA><NA><NA>02 9457955<NA>142805서울특별시 강북구 미아동 ***-**번지 송원빌딩 *층서울특별시 강북구 숭인로 ** (미아동,송원빌딩 *층)1211로즈마리의원2017-07-19 10:42:58I2018-08-31 23:59:59.0<NA>202461.533827456705.48988영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330800003080000-134-2004-0000420040420<NA>3폐업2폐업20040511<NA><NA><NA>02 9995522<NA>142865서울특별시 강북구 번동 ***-**번지<NA><NA>예일소아과의원2010-07-27 15:55:10I2018-08-31 23:59:59.0<NA>202607.278547459509.686719영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430800003080000-134-2004-0000520040503<NA>3폐업2폐업20170419<NA><NA><NA><NA><NA>142865서울특별시 강북구 번동 ***-**번지서울특별시 강북구 한천로 **** (번동)1059예스숍2017-04-19 16:34:03I2018-08-31 23:59:59.0<NA>202607.278547459509.686719영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530800003080000-134-2004-0000620040511<NA>1영업/정상1영업<NA><NA><NA><NA>02 9978323<NA>142864서울특별시 강북구 번동 ***-**번지서울특별시 강북구 오패산로**길 * (번동)1064선삼정미아판매점2004-05-12 00:00:00I2018-08-31 23:59:59.0<NA>202435.283624459353.048072영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630800003080000-134-2004-0000720040513<NA>3폐업2폐업20060908<NA><NA><NA>02 9947488<NA>142867서울특별시 강북구 번동 ***-**번지 가든타워 *동 ****호<NA><NA>클로렐라A+2004-05-13 00:00:00I2018-08-31 23:59:59.0<NA>202155.401317459411.940883영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730800003080000-134-2004-0000820040524<NA>1영업/정상1영업<NA><NA><NA><NA>02 989333082.65142803서울특별시 강북구 미아동 ***-** 청암빌딩서울특별시 강북구 도봉로 ***, 청암빌딩 *층 ***호 (미아동)1132유니베라강북대리점2022-11-04 15:40:33U2021-11-01 00:06:00.0<NA>202099.830367458756.889792<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830800003080000-134-2004-0000920040525<NA>1영업/정상1영업<NA><NA><NA><NA>02 9848880<NA>142815서울특별시 강북구 미아동 ***-**번지 *층서울특별시 강북구 솔샘로**길 **, *층 (미아동)1177마임2013-01-28 15:20:42I2018-08-31 23:59:59.0<NA>202399.141092457515.66769방문판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930800003080000-134-2004-0001020040525<NA>3폐업2폐업20071004<NA><NA><NA>02 9993112<NA>142876서울특별시 강북구 수유동 ***-*번지<NA><NA>생그린한방화장품2004-05-25 00:00:00I2018-08-31 23:59:59.0<NA>202426.032099459837.927511영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
228530800003080000-134-2024-000532024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>142-803서울특별시 강북구 미아동 ***-* 한국전력 강북성북지사서울특별시 강북구 도봉로 ***, 한국전력 강북성북지사 *층 *호 (미아동)1132다비치안경2024-04-23 16:19:46I2023-12-03 22:05:00.0<NA>202132.411671458690.802597<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
228630800003080000-134-2024-000542024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.76142-872서울특별시 강북구 수유동 **-**서울특별시 강북구 수유로**길 **, *층 (수유동)1078리얼클린족욕2024-04-30 13:33:47I2023-12-05 00:03:00.0<NA>201872.268568459614.552362<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
228730800003080000-134-2024-000552024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>118.35142-100서울특별시 강북구 미아동 ****-* 금강빌딩서울특별시 강북구 삼양로**길 ***, 금강빌딩 *층 *,*,*,*,*(일부)호 (미아동)1193세븐일레븐 삼각산SK점2024-04-30 16:16:17I2023-12-05 00:03:00.0<NA>201293.723872457479.348899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
228830800003080000-134-2024-000562024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>246.82142-804서울특별시 강북구 미아동 **-** 덕신빌딩서울특별시 강북구 월계로 *, 덕신빌딩 *층 ***호 (미아동)1220다비치안경 미아사거리점2024-04-30 17:00:10I2023-12-05 00:03:00.0<NA>202635.072291456360.433255<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
228930800003080000-134-2024-000572024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00142-803서울특별시 강북구 미아동 ***-**서울특별시 강북구 도봉로 ***-*, *층 J-*호 (미아동)1128문약사 건강이네2024-05-01 10:46:04I2023-12-05 00:03:00.0<NA>202030.253406458962.158613<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229030800003080000-134-2024-000582024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.13142-877서울특별시 강북구 수유동 ***-**서울특별시 강북구 삼양로***길 **, *층 (수유동)1038주식회사 에스제이엘이노베이션2024-05-02 16:37:17I2023-12-05 00:04:00.0<NA>201378.456209460317.260863<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229130800003080000-134-2024-000592024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00142-803서울특별시 강북구 미아동 ***-**서울특별시 강북구 도봉로 ***-*, *층 J-*호 (미아동)1128주식회사 파맥스코리아2024-05-02 14:31:46I2023-12-05 00:04:00.0<NA>202030.253406458962.158613<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229230800003080000-134-2024-000602024-05-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>142-803서울특별시 강북구 미아동 ***-* 대복빌딩서울특별시 강북구 덕릉로 ***-*, 대복빌딩 ***-에이호 (미아동)1129엔핏커넥트 주식회사2024-05-10 11:10:44I2023-12-04 23:02:00.0<NA>202265.854898459150.572305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229330800003080000-134-2024-000612024-05-09<NA>3폐업2폐업2024-05-16<NA><NA><NA><NA><NA>142-100서울특별시 강북구 미아동 ***-* 위브 테라스 파크서울특별시 강북구 삼양로**길 **, 위브 테라스 파크 *층 ***-A***호 (미아동)1197스페셜피스2024-05-16 14:09:45U2023-12-04 23:08:00.0<NA>201598.511377457357.306972<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229430800003080000-134-2024-000622024-05-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>142-070서울특별시 강북구 수유동 ***-*서울특별시 강북구 *.**로**길 **-*, *층 (수유동)1012빛,소금,물2024-05-16 18:33:47I2023-12-04 23:08:00.0<NA>200379.899453460449.41796<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>