Overview

Dataset statistics

Number of variables44
Number of observations441
Missing cells4374
Missing cells (%)22.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory162.5 KiB
Average record size in memory377.3 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강북구
URLhttps://data.seoul.go.kr/dataList/OA-18535/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
등급구분명 is highly imbalanced (50.1%)Imbalance
총인원 is highly imbalanced (56.1%)Imbalance
본사종업원수 is highly imbalanced (56.1%)Imbalance
공장사무직종업원수 is highly imbalanced (56.1%)Imbalance
공장판매직종업원수 is highly imbalanced (56.1%)Imbalance
공장생산직종업원수 is highly imbalanced (56.1%)Imbalance
보증액 is highly imbalanced (56.1%)Imbalance
월세액 is highly imbalanced (56.1%)Imbalance
다중이용업소여부 is highly imbalanced (93.4%)Imbalance
인허가취소일자 has 441 (100.0%) missing valuesMissing
폐업일자 has 88 (20.0%) missing valuesMissing
휴업시작일자 has 441 (100.0%) missing valuesMissing
휴업종료일자 has 441 (100.0%) missing valuesMissing
재개업일자 has 441 (100.0%) missing valuesMissing
전화번호 has 32 (7.3%) missing valuesMissing
소재지면적 has 8 (1.8%) missing valuesMissing
도로명주소 has 286 (64.9%) missing valuesMissing
도로명우편번호 has 292 (66.2%) missing valuesMissing
좌표정보(X) has 12 (2.7%) missing valuesMissing
좌표정보(Y) has 12 (2.7%) missing valuesMissing
건물소유구분명 has 441 (100.0%) missing valuesMissing
다중이용업소여부 has 58 (13.2%) missing valuesMissing
시설총규모 has 58 (13.2%) missing valuesMissing
전통업소지정번호 has 441 (100.0%) missing valuesMissing
전통업소주된음식 has 441 (100.0%) missing valuesMissing
홈페이지 has 441 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 9 (2.0%) zerosZeros

Reproduction

Analysis started2024-04-06 11:03:14.957691
Analysis finished2024-04-06 11:03:16.080040
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3080000
441 

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 441
100.0%

Length

2024-04-06T20:03:16.203119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:16.397152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3080000 441
100.0%

관리번호
Text

UNIQUE 

Distinct441
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-06T20:03:16.696470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters9702
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

Unique441 ?
Unique (%)100.0%

Sample

1st row3080000-103-1966-02101
2nd row3080000-103-1990-01226
3rd row3080000-103-1991-02135
4th row3080000-103-1993-00059
5th row3080000-103-1993-02096
ValueCountFrequency (%)
3080000-103-1966-02101 1
 
0.2%
3080000-103-1997-02019 1
 
0.2%
3080000-103-1997-02031 1
 
0.2%
3080000-103-1997-02030 1
 
0.2%
3080000-103-1997-02029 1
 
0.2%
3080000-103-1997-02028 1
 
0.2%
3080000-103-1997-02027 1
 
0.2%
3080000-103-1997-02026 1
 
0.2%
3080000-103-1997-02025 1
 
0.2%
3080000-103-1997-02024 1
 
0.2%
Other values (431) 431
97.7%
2024-04-06T20:03:17.219496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3593
37.0%
- 1323
 
13.6%
3 1097
 
11.3%
1 1045
 
10.8%
9 859
 
8.9%
2 601
 
6.2%
8 565
 
5.8%
4 167
 
1.7%
6 155
 
1.6%
5 151
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8379
86.4%
Dash Punctuation 1323
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3593
42.9%
3 1097
 
13.1%
1 1045
 
12.5%
9 859
 
10.3%
2 601
 
7.2%
8 565
 
6.7%
4 167
 
2.0%
6 155
 
1.8%
5 151
 
1.8%
7 146
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 1323
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9702
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3593
37.0%
- 1323
 
13.6%
3 1097
 
11.3%
1 1045
 
10.8%
9 859
 
8.9%
2 601
 
6.2%
8 565
 
5.8%
4 167
 
1.7%
6 155
 
1.6%
5 151
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9702
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3593
37.0%
- 1323
 
13.6%
3 1097
 
11.3%
1 1045
 
10.8%
9 859
 
8.9%
2 601
 
6.2%
8 565
 
5.8%
4 167
 
1.7%
6 155
 
1.6%
5 151
 
1.6%

인허가일자
Date

Distinct369
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1966-11-09 00:00:00
Maximum2024-01-10 00:00:00
2024-04-06T20:03:17.470357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:03:17.716104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
3
353 
1
88 

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 (%)
3 353
80.0%
1 88
 
20.0%

Length

2024-04-06T20:03:17.974085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:18.146528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 353
80.0%
1 88
 
20.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
353 
영업/정상
88 

Length

Max length5
Median length2
Mean length2.5986395
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 353
80.0%
영업/정상 88
 
20.0%

Length

2024-04-06T20:03:18.342539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:18.599849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 353
80.0%
영업/정상 88
 
20.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2
353 
1
88 

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 (%)
2 353
80.0%
1 88
 
20.0%

Length

2024-04-06T20:03:18.821162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:19.064601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 353
80.0%
1 88
 
20.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
폐업
353 
영업
88 

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 353
80.0%
영업 88
 
20.0%

Length

2024-04-06T20:03:19.318983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:19.478052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 353
80.0%
영업 88
 
20.0%

폐업일자
Date

MISSING 

Distinct298
Distinct (%)84.4%
Missing88
Missing (%)20.0%
Memory size3.6 KiB
Minimum1994-03-16 00:00:00
Maximum2023-06-02 00:00:00
2024-04-06T20:03:19.705813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:03:20.309302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

전화번호
Text

MISSING 

Distinct344
Distinct (%)84.1%
Missing32
Missing (%)7.3%
Memory size3.6 KiB
2024-04-06T20:03:20.889858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.6601467
Min length2

Characters and Unicode

Total characters3951
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

Unique326 ?
Unique (%)79.7%

Sample

1st row0209008181
2nd row02 9963858
3rd row02 9862000
4th row02 00000
5th row02 9550568
ValueCountFrequency (%)
02 335
45.0%
0200000000 23
 
3.1%
00000 6
 
0.8%
9995152 3
 
0.4%
9964462 3
 
0.4%
900 3
 
0.4%
9039331 2
 
0.3%
906 2
 
0.3%
908 2
 
0.3%
9001751 2
 
0.3%
Other values (352) 364
48.9%
2024-04-06T20:03:21.625369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 981
24.8%
9 595
15.1%
2 586
14.8%
373
 
9.4%
8 291
 
7.4%
5 215
 
5.4%
6 196
 
5.0%
3 185
 
4.7%
7 185
 
4.7%
1 176
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3578
90.6%
Space Separator 373
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 981
27.4%
9 595
16.6%
2 586
16.4%
8 291
 
8.1%
5 215
 
6.0%
6 196
 
5.5%
3 185
 
5.2%
7 185
 
5.2%
1 176
 
4.9%
4 168
 
4.7%
Space Separator
ValueCountFrequency (%)
373
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3951
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 981
24.8%
9 595
15.1%
2 586
14.8%
373
 
9.4%
8 291
 
7.4%
5 215
 
5.4%
6 196
 
5.0%
3 185
 
4.7%
7 185
 
4.7%
1 176
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 981
24.8%
9 595
15.1%
2 586
14.8%
373
 
9.4%
8 291
 
7.4%
5 215
 
5.4%
6 196
 
5.0%
3 185
 
4.7%
7 185
 
4.7%
1 176
 
4.5%

소재지면적
Real number (ℝ)

MISSING 

Distinct407
Distinct (%)94.0%
Missing8
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean106.15547
Minimum0
Maximum898.96
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-06T20:03:21.948479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile55.668
Q175.45
median98.77
Q3125.92
95-th percentile148.128
Maximum898.96
Range898.96
Interquartile range (IQR)50.47

Descriptive statistics

Standard deviation65.466919
Coefficient of variation (CV)0.6167079
Kurtosis71.911718
Mean106.15547
Median Absolute Deviation (MAD)25.69
Skewness7.2183203
Sum45965.32
Variance4285.9175
MonotonicityNot monotonic
2024-04-06T20:03:22.217335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
102.72 3
 
0.7%
108.75 3
 
0.7%
70.0 3
 
0.7%
132.95 3
 
0.7%
61.2 2
 
0.5%
86.07 2
 
0.5%
110.09 2
 
0.5%
198.64 2
 
0.5%
99.42 2
 
0.5%
62.19 2
 
0.5%
Other values (397) 409
92.7%
(Missing) 8
 
1.8%
ValueCountFrequency (%)
0.0 1
0.2%
15.63 1
0.2%
36.92 1
0.2%
37.52 1
0.2%
42.28 1
0.2%
44.32 1
0.2%
45.71 1
0.2%
46.0 1
0.2%
49.51 1
0.2%
51.09 1
0.2%
ValueCountFrequency (%)
898.96 1
0.2%
672.79 1
0.2%
587.8 1
0.2%
528.3 1
0.2%
287.38 1
0.2%
255.0 1
0.2%
198.64 2
0.5%
190.5 1
0.2%
190.05 1
0.2%
173.09 1
0.2%

소재지우편번호
Text

Distinct54
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-06T20:03:22.534162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0770975
Min length6

Characters and Unicode

Total characters2680
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

Unique17 ?
Unique (%)3.9%

Sample

1st row142881
2nd row142867
3rd row142804
4th row142878
5th row142876
ValueCountFrequency (%)
142878 83
18.8%
142804 53
 
12.0%
142876 45
 
10.2%
142867 33
 
7.5%
142070 17
 
3.9%
142803 14
 
3.2%
142891 14
 
3.2%
142874 13
 
2.9%
142872 12
 
2.7%
142873 12
 
2.7%
Other values (44) 145
32.9%
2024-04-06T20:03:23.091170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 527
19.7%
8 527
19.7%
1 492
18.4%
2 479
17.9%
7 278
10.4%
0 136
 
5.1%
6 126
 
4.7%
3 40
 
1.5%
- 34
 
1.3%
9 29
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2646
98.7%
Dash Punctuation 34
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 527
19.9%
8 527
19.9%
1 492
18.6%
2 479
18.1%
7 278
10.5%
0 136
 
5.1%
6 126
 
4.8%
3 40
 
1.5%
9 29
 
1.1%
5 12
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2680
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 527
19.7%
8 527
19.7%
1 492
18.4%
2 479
17.9%
7 278
10.4%
0 136
 
5.1%
6 126
 
4.7%
3 40
 
1.5%
- 34
 
1.3%
9 29
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 527
19.7%
8 527
19.7%
1 492
18.4%
2 479
17.9%
7 278
10.4%
0 136
 
5.1%
6 126
 
4.7%
3 40
 
1.5%
- 34
 
1.3%
9 29
 
1.1%

지번주소
Text

Distinct375
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-06T20:03:23.674980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length23.294785
Min length18

Characters and Unicode

Total characters10273
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique321 ?
Unique (%)72.8%

Sample

1st row서울특별시 강북구 우이동 산 14-0번지
2nd row서울특별시 강북구 번동 443-94번지
3rd row서울특별시 강북구 미아동 42-8번지
4th row서울특별시 강북구 수유동 189-35번지
5th row서울특별시 강북구 수유동 176-56번지
ValueCountFrequency (%)
서울특별시 441
23.3%
강북구 441
23.3%
수유동 244
12.9%
미아동 124
 
6.6%
번동 63
 
3.3%
지하1층 15
 
0.8%
도봉로 11
 
0.6%
우이동 10
 
0.5%
48-8번지 5
 
0.3%
190-1번지 5
 
0.3%
Other values (423) 530
28.1%
2024-04-06T20:03:24.603603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1830
17.8%
- 450
 
4.4%
동 448
 
4.4%
구 444
 
4.3%
강 443
 
4.3%
북 443
 
4.3%
시 442
 
4.3%
1 442
 
4.3%
서 441
 
4.3%
특 441
 
4.3%
Other values (58) 4449
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5731
55.8%
Decimal Number 2144
 
20.9%
Space Separator 1830
 
17.8%
Dash Punctuation 450
 
4.4%
Open Punctuation 56
 
0.5%
Close Punctuation 56
 
0.5%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 448
 
7.8%
구 444
 
7.7%
강 443
 
7.7%
북 443
 
7.7%
시 442
 
7.7%
서 441
 
7.7%
특 441
 
7.7%
별 441
 
7.7%
울 441
 
7.7%
번 402
 
7.0%
Other values (42) 1345
23.5%
Decimal Number
ValueCountFrequency (%)
1 442
20.6%
4 273
12.7%
2 268
12.5%
3 205
9.6%
9 192
9.0%
7 191
8.9%
0 170
 
7.9%
6 152
 
7.1%
8 146
 
6.8%
5 105
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
, 2
33.3%
Space Separator
ValueCountFrequency (%)
1830
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5731
55.8%
Common 4542
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 448
 
7.8%
구 444
 
7.7%
강 443
 
7.7%
북 443
 
7.7%
시 442
 
7.7%
서 441
 
7.7%
특 441
 
7.7%
별 441
 
7.7%
울 441
 
7.7%
번 402
 
7.0%
Other values (42) 1345
23.5%
Common
ValueCountFrequency (%)
1830
40.3%
- 450
 
9.9%
1 442
 
9.7%
4 273
 
6.0%
2 268
 
5.9%
3 205
 
4.5%
9 192
 
4.2%
7 191
 
4.2%
0 170
 
3.7%
6 152
 
3.3%
Other values (6) 369
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5731
55.8%
ASCII 4542
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1830
40.3%
- 450
 
9.9%
1 442
 
9.7%
4 273
 
6.0%
2 268
 
5.9%
3 205
 
4.5%
9 192
 
4.2%
7 191
 
4.2%
0 170
 
3.7%
6 152
 
3.3%
Other values (6) 369
 
8.1%
Hangul
ValueCountFrequency (%)
동 448
 
7.8%
구 444
 
7.7%
강 443
 
7.7%
북 443
 
7.7%
시 442
 
7.7%
서 441
 
7.7%
특 441
 
7.7%
별 441
 
7.7%
울 441
 
7.7%
번 402
 
7.0%
Other values (42) 1345
23.5%

도로명주소
Text

MISSING 

Distinct155
Distinct (%)100.0%
Missing286
Missing (%)64.9%
Memory size3.6 KiB
2024-04-06T20:03:25.203246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length27.225806
Min length21

Characters and Unicode

Total characters4220
Distinct characters76
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)100.0%

Sample

1st row서울특별시 강북구 솔샘로 235 (미아동)
2nd row서울특별시 강북구 도봉로82길 26 (번동,(번문길 14 -1))
3rd row서울특별시 강북구 한천로 944 (번동)
4th row서울특별시 강북구 한천로 1023 (번동)
5th row서울특별시 강북구 노해로 88 (수유동,(쌍문동길 90))
ValueCountFrequency (%)
서울특별시 155
18.4%
강북구 155
18.4%
수유동 67
 
8.0%
미아동 34
 
4.0%
한천로 25
 
3.0%
도봉로 22
 
2.6%
번동 16
 
1.9%
지하1층 15
 
1.8%
도봉로87길 12
 
1.4%
노해로 11
 
1.3%
Other values (194) 329
39.1%
2024-04-06T20:03:26.036783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
686
 
16.3%
) 191
 
4.5%
( 191
 
4.5%
로 165
 
3.9%
1 162
 
3.8%
동 159
 
3.8%
강 157
 
3.7%
북 157
 
3.7%
구 157
 
3.7%
시 156
 
3.7%
Other values (66) 2039
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2409
57.1%
Space Separator 686
 
16.3%
Decimal Number 652
 
15.5%
Close Punctuation 191
 
4.5%
Open Punctuation 191
 
4.5%
Other Punctuation 71
 
1.7%
Dash Punctuation 19
 
0.5%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 165
 
6.8%
동 159
 
6.6%
강 157
 
6.5%
북 157
 
6.5%
구 157
 
6.5%
시 156
 
6.5%
특 155
 
6.4%
별 155
 
6.4%
울 155
 
6.4%
서 155
 
6.4%
Other values (49) 838
34.8%
Decimal Number
ValueCountFrequency (%)
1 162
24.8%
2 75
11.5%
3 68
10.4%
8 66
10.1%
0 58
 
8.9%
7 54
 
8.3%
9 54
 
8.3%
4 46
 
7.1%
6 35
 
5.4%
5 34
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 64
90.1%
. 7
 
9.9%
Space Separator
ValueCountFrequency (%)
686
100.0%
Close Punctuation
ValueCountFrequency (%)
) 191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2409
57.1%
Common 1810
42.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 165
 
6.8%
동 159
 
6.6%
강 157
 
6.5%
북 157
 
6.5%
구 157
 
6.5%
시 156
 
6.5%
특 155
 
6.4%
별 155
 
6.4%
울 155
 
6.4%
서 155
 
6.4%
Other values (49) 838
34.8%
Common
ValueCountFrequency (%)
686
37.9%
) 191
 
10.6%
( 191
 
10.6%
1 162
 
9.0%
2 75
 
4.1%
3 68
 
3.8%
8 66
 
3.6%
, 64
 
3.5%
0 58
 
3.2%
7 54
 
3.0%
Other values (6) 195
 
10.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2409
57.1%
ASCII 1811
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
686
37.9%
) 191
 
10.5%
( 191
 
10.5%
1 162
 
8.9%
2 75
 
4.1%
3 68
 
3.8%
8 66
 
3.6%
, 64
 
3.5%
0 58
 
3.2%
7 54
 
3.0%
Other values (7) 196
 
10.8%
Hangul
ValueCountFrequency (%)
로 165
 
6.8%
동 159
 
6.6%
강 157
 
6.5%
북 157
 
6.5%
구 157
 
6.5%
시 156
 
6.5%
특 155
 
6.4%
별 155
 
6.4%
울 155
 
6.4%
서 155
 
6.4%
Other values (49) 838
34.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)36.2%
Missing292
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean1096.9664
Minimum1001
Maximum1237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-06T20:03:26.302954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1001
5-th percentile1037
Q11062
median1073
Q31127
95-th percentile1220.6
Maximum1237
Range236
Interquartile range (IQR)65

Descriptive statistics

Standard deviation57.332649
Coefficient of variation (CV)0.052264725
Kurtosis0.052327344
Mean1096.9664
Median Absolute Deviation (MAD)19
Skewness1.0289954
Sum163448
Variance3287.0327
MonotonicityNot monotonic
2024-04-06T20:03:26.569789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1074 12
 
2.7%
1073 12
 
2.7%
1053 10
 
2.3%
1221 7
 
1.6%
1069 7
 
1.6%
1220 6
 
1.4%
1080 6
 
1.4%
1071 6
 
1.4%
1054 5
 
1.1%
1128 5
 
1.1%
Other values (44) 73
 
16.6%
(Missing) 292
66.2%
ValueCountFrequency (%)
1001 1
0.2%
1002 1
0.2%
1006 1
0.2%
1011 2
0.5%
1026 2
0.5%
1037 2
0.5%
1043 1
0.2%
1044 1
0.2%
1046 1
0.2%
1048 1
0.2%
ValueCountFrequency (%)
1237 1
 
0.2%
1221 7
1.6%
1220 6
1.4%
1202 1
 
0.2%
1201 1
 
0.2%
1194 1
 
0.2%
1189 3
0.7%
1178 1
 
0.2%
1176 2
 
0.5%
1174 1
 
0.2%

사업장명
Text

Distinct395
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2024-04-06T20:03:27.092063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length4.1020408
Min length1

Characters and Unicode

Total characters1809
Distinct characters369
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)81.4%

Sample

1st row(주)호텔 그린파크 단란주점
2nd row태마단란주점
3rd row호텔빅토리아유니온
4th row탑슬
5th row이화
ValueCountFrequency (%)
단란주점 11
 
2.3%
멤피스 4
 
0.8%
이장댁 4
 
0.8%
7080 4
 
0.8%
엠파이어 3
 
0.6%
라이브 3
 
0.6%
일번지 3
 
0.6%
차차차 3
 
0.6%
프린스 3
 
0.6%
은하수 3
 
0.6%
Other values (395) 432
91.3%
2024-04-06T20:03:27.828534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 116
 
6.4%
점 109
 
6.0%
단 82
 
4.5%
란 80
 
4.4%
이 58
 
3.2%
스 38
 
2.1%
32
 
1.8%
리 26
 
1.4%
래 26
 
1.4%
노 24
 
1.3%
Other values (359) 1218
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1685
93.1%
Decimal Number 46
 
2.5%
Space Separator 32
 
1.8%
Uppercase Letter 17
 
0.9%
Lowercase Letter 9
 
0.5%
Close Punctuation 7
 
0.4%
Open Punctuation 7
 
0.4%
Other Punctuation 5
 
0.3%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 116
 
6.9%
점 109
 
6.5%
단 82
 
4.9%
란 80
 
4.7%
이 58
 
3.4%
스 38
 
2.3%
리 26
 
1.5%
래 26
 
1.5%
노 24
 
1.4%
마 20
 
1.2%
Other values (325) 1106
65.6%
Uppercase Letter
ValueCountFrequency (%)
B 3
17.6%
A 3
17.6%
U 2
11.8%
R 2
11.8%
G 1
 
5.9%
N 1
 
5.9%
L 1
 
5.9%
X 1
 
5.9%
W 1
 
5.9%
S 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
n 1
11.1%
e 1
11.1%
w 1
11.1%
o 1
11.1%
p 1
11.1%
r 1
11.1%
s 1
11.1%
h 1
11.1%
a 1
11.1%
Decimal Number
ValueCountFrequency (%)
0 17
37.0%
8 9
19.6%
7 8
17.4%
2 6
 
13.0%
5 4
 
8.7%
1 1
 
2.2%
3 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
, 2
40.0%
? 1
20.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1684
93.1%
Common 97
 
5.4%
Latin 27
 
1.5%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 116
 
6.9%
점 109
 
6.5%
단 82
 
4.9%
란 80
 
4.8%
이 58
 
3.4%
스 38
 
2.3%
리 26
 
1.5%
래 26
 
1.5%
노 24
 
1.4%
마 20
 
1.2%
Other values (324) 1105
65.6%
Latin
ValueCountFrequency (%)
B 3
 
11.1%
A 3
 
11.1%
U 2
 
7.4%
R 2
 
7.4%
G 1
 
3.7%
n 1
 
3.7%
Ⅱ 1
 
3.7%
N 1
 
3.7%
e 1
 
3.7%
w 1
 
3.7%
Other values (11) 11
40.7%
Common
ValueCountFrequency (%)
32
33.0%
0 17
17.5%
8 9
 
9.3%
7 8
 
8.2%
) 7
 
7.2%
( 7
 
7.2%
2 6
 
6.2%
5 4
 
4.1%
. 2
 
2.1%
, 2
 
2.1%
Other values (3) 3
 
3.1%
Han
ValueCountFrequency (%)
水 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1684
93.1%
ASCII 123
 
6.8%
Number Forms 1
 
0.1%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 116
 
6.9%
점 109
 
6.5%
단 82
 
4.9%
란 80
 
4.8%
이 58
 
3.4%
스 38
 
2.3%
리 26
 
1.5%
래 26
 
1.5%
노 24
 
1.4%
마 20
 
1.2%
Other values (324) 1105
65.6%
ASCII
ValueCountFrequency (%)
32
26.0%
0 17
13.8%
8 9
 
7.3%
7 8
 
6.5%
) 7
 
5.7%
( 7
 
5.7%
2 6
 
4.9%
5 4
 
3.3%
B 3
 
2.4%
A 3
 
2.4%
Other values (23) 27
22.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
CJK
ValueCountFrequency (%)
水 1
100.0%

최종수정일자
Date

Distinct272
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum1999-04-09 00:00:00
Maximum2024-03-25 11:55:51
2024-04-06T20:03:28.085601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:03:28.422451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
I
324 
U
117 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 324
73.5%
U 117
 
26.5%

Length

2024-04-06T20:03:28.657994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:28.869631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 324
73.5%
u 117
 
26.5%

데이터갱신일자
Date

Distinct85
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T20:03:29.060538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:03:29.331911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
단란주점
441 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 441
100.0%

Length

2024-04-06T20:03:29.538541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:29.688910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 441
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct321
Distinct (%)74.8%
Missing12
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean202096.66
Minimum200888.56
Maximum203093.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-06T20:03:29.863555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200888.56
5-th percentile201195.71
Q1201909.94
median202107.82
Q3202368.34
95-th percentile202792.8
Maximum203093.49
Range2204.9282
Interquartile range (IQR)458.39543

Descriptive statistics

Standard deviation421.10937
Coefficient of variation (CV)0.0020837027
Kurtosis0.50391343
Mean202096.66
Median Absolute Deviation (MAD)209.56493
Skewness-0.39279614
Sum86699468
Variance177333.1
MonotonicityNot monotonic
2024-04-06T20:03:30.128073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202063.769977656 5
 
1.1%
202146.24309535 5
 
1.1%
202108.293118768 4
 
0.9%
201972.074242101 4
 
0.9%
201886.415245076 4
 
0.9%
202032.757631932 3
 
0.7%
202145.315820342 3
 
0.7%
202170.935280241 3
 
0.7%
202369.787497499 3
 
0.7%
202437.450759529 3
 
0.7%
Other values (311) 392
88.9%
(Missing) 12
 
2.7%
ValueCountFrequency (%)
200888.560414673 2
0.5%
200989.060545805 1
0.2%
201032.570986839 1
0.2%
201039.8009288 1
0.2%
201042.545720065 1
0.2%
201056.297923916 1
0.2%
201065.826734805 1
0.2%
201079.998722105 1
0.2%
201084.302500989 1
0.2%
201098.210685821 2
0.5%
ValueCountFrequency (%)
203093.488566 2
0.5%
203073.286856866 1
0.2%
203047.423719877 1
0.2%
203031.068146331 2
0.5%
202882.532584046 1
0.2%
202874.88760196 1
0.2%
202862.370494903 1
0.2%
202856.985508346 1
0.2%
202846.299297438 1
0.2%
202842.518400095 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct321
Distinct (%)74.8%
Missing12
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean459043.71
Minimum456377.65
Maximum462339.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-06T20:03:30.361720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456377.65
5-th percentile456547.93
Q1458861.12
median459387.46
Q3459814.67
95-th percentile460581.47
Maximum462339.15
Range5961.4984
Interquartile range (IQR)953.55139

Descriptive statistics

Standard deviation1208.7383
Coefficient of variation (CV)0.002633166
Kurtosis0.26394037
Mean459043.71
Median Absolute Deviation (MAD)432.75808
Skewness-0.73412988
Sum1.9692975 × 108
Variance1461048.2
MonotonicityNot monotonic
2024-04-06T20:03:30.601705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
459216.615761343 5
 
1.1%
459844.600778291 5
 
1.1%
459565.148082111 4
 
0.9%
458995.166703288 4
 
0.9%
459109.869798884 4
 
0.9%
459259.443978524 3
 
0.7%
459566.178827233 3
 
0.7%
459208.382958216 3
 
0.7%
459861.409375247 3
 
0.7%
457238.204413734 3
 
0.7%
Other values (311) 392
88.9%
(Missing) 12
 
2.7%
ValueCountFrequency (%)
456377.651999255 1
 
0.2%
456419.111212319 1
 
0.2%
456422.95319709 1
 
0.2%
456434.500687631 1
 
0.2%
456449.379330053 1
 
0.2%
456473.886142136 3
0.7%
456502.936579267 1
 
0.2%
456514.983925518 3
0.7%
456516.997283985 2
0.5%
456517.74915445 1
 
0.2%
ValueCountFrequency (%)
462339.150431724 1
0.2%
462268.254665642 1
0.2%
462243.633653421 1
0.2%
462134.918206526 1
0.2%
462121.472783112 1
0.2%
461927.581171231 1
0.2%
461436.631100173 1
0.2%
461383.338586109 1
0.2%
460764.752692299 1
0.2%
460695.334652569 1
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
단란주점
383 
<NA>
58 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단란주점 383
86.8%
<NA> 58
 
13.2%

Length

2024-04-06T20:03:30.823315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:30.971328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단란주점 383
86.8%
na 58
 
13.2%

남성종사자수
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
225 
<NA>
103 
1
91 
2
 
20
3
 
2

Length

Max length4
Median length1
Mean length1.7006803
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 225
51.0%
<NA> 103
23.4%
1 91
20.6%
2 20
 
4.5%
3 2
 
0.5%

Length

2024-04-06T20:03:31.172204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:31.361089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 225
51.0%
na 103
23.4%
1 91
20.6%
2 20
 
4.5%
3 2
 
0.5%

여성종사자수
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
0
179 
1
112 
<NA>
102 
2
42 
3
 
6

Length

Max length4
Median length1
Mean length1.6938776
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 179
40.6%
1 112
25.4%
<NA> 102
23.1%
2 42
 
9.5%
3 6
 
1.4%

Length

2024-04-06T20:03:31.585436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:31.789863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 179
40.6%
1 112
25.4%
na 102
23.1%
2 42
 
9.5%
3 6
 
1.4%

영업장주변구분명
Categorical

Distinct7
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
주택가주변
175 
<NA>
94 
유흥업소밀집지역
84 
기타
83 
결혼예식장주변
 
3
Other values (2)
 
2

Length

Max length8
Median length7
Mean length4.814059
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
주택가주변 175
39.7%
<NA> 94
21.3%
유흥업소밀집지역 84
19.0%
기타 83
18.8%
결혼예식장주변 3
 
0.7%
아파트지역 1
 
0.2%
학교정화(상대) 1
 
0.2%

Length

2024-04-06T20:03:32.003636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:32.213183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택가주변 175
39.7%
na 94
21.3%
유흥업소밀집지역 84
19.0%
기타 83
18.8%
결혼예식장주변 3
 
0.7%
아파트지역 1
 
0.2%
학교정화(상대 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
기타
296 
<NA>
103 
자율
34 
관리
 
5
우수
 
2

Length

Max length4
Median length2
Mean length2.4648526
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
기타 296
67.1%
<NA> 103
 
23.4%
자율 34
 
7.7%
관리 5
 
1.1%
우수 2
 
0.5%
갑 1
 
0.2%

Length

2024-04-06T20:03:32.468311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:32.681823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 296
67.1%
na 103
 
23.4%
자율 34
 
7.7%
관리 5
 
1.1%
우수 2
 
0.5%
갑 1
 
0.2%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
상수도전용
344 
<NA>
97 

Length

Max length5
Median length5
Mean length4.7800454
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 344
78.0%
<NA> 97
 
22.0%

Length

2024-04-06T20:03:32.902076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:33.100530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 344
78.0%
na 97
 
22.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:33.326591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:33.543456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:33.730301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:33.904814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:34.106437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:34.618362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:34.808442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:34.968216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:35.146297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:35.309275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:35.483595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:35.752471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
<NA>
401 
0
 
40

Length

Max length4
Median length4
Mean length3.7278912
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> 401
90.9%
0 40
 
9.1%

Length

2024-04-06T20:03:35.970914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:03:36.148288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 401
90.9%
0 40
 
9.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing58
Missing (%)13.2%
Memory size1014.0 B
False
380 
True
 
3
(Missing)
58 
ValueCountFrequency (%)
False 380
86.2%
True 3
 
0.7%
(Missing) 58
 
13.2%
2024-04-06T20:03:36.307197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct358
Distinct (%)93.5%
Missing58
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean105.49423
Minimum0
Maximum898.96
Zeros9
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-04-06T20:03:36.561749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51.254
Q173.615
median98.1
Q3127.81
95-th percentile148.72
Maximum898.96
Range898.96
Interquartile range (IQR)54.195

Descriptive statistics

Standard deviation70.494175
Coefficient of variation (CV)0.66822778
Kurtosis60.471963
Mean105.49423
Median Absolute Deviation (MAD)26.7
Skewness6.5069638
Sum40404.29
Variance4969.4287
MonotonicityNot monotonic
2024-04-06T20:03:36.802028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9
 
2.0%
132.95 3
 
0.7%
102.72 3
 
0.7%
62.19 2
 
0.5%
86.07 2
 
0.5%
110.09 2
 
0.5%
198.64 2
 
0.5%
70.0 2
 
0.5%
125.92 2
 
0.5%
72.54 2
 
0.5%
Other values (348) 354
80.3%
(Missing) 58
 
13.2%
ValueCountFrequency (%)
0.0 9
2.0%
15.63 1
 
0.2%
36.92 1
 
0.2%
37.52 1
 
0.2%
42.28 1
 
0.2%
44.32 1
 
0.2%
45.71 1
 
0.2%
46.0 1
 
0.2%
49.51 1
 
0.2%
51.09 1
 
0.2%
ValueCountFrequency (%)
898.96 1
0.2%
672.79 1
0.2%
587.8 1
0.2%
528.3 1
0.2%
287.38 1
0.2%
255.0 1
0.2%
198.64 2
0.5%
190.5 1
0.2%
190.05 1
0.2%
173.09 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing441
Missing (%)100.0%
Memory size4.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030800003080000-103-1966-0210119661109<NA>3폐업2폐업20070628<NA><NA><NA>0209008181133.37142881서울특별시 강북구 우이동 산 14-0번지<NA><NA>(주)호텔 그린파크 단란주점2004-01-30 00:00:00I2018-08-31 23:59:59.0단란주점<NA><NA>단란주점02기타갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N133.37<NA><NA><NA>
130800003080000-103-1990-0122619900625<NA>3폐업2폐업20090728<NA><NA><NA>02 9963858122.4142867서울특별시 강북구 번동 443-94번지<NA><NA>태마단란주점2007-04-19 00:00:00I2018-08-31 23:59:59.0단란주점202205.542183459191.453552단란주점00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N122.4<NA><NA><NA>
230800003080000-103-1991-0213519910420<NA>3폐업2폐업19950325<NA><NA><NA>02 986200062.05142804서울특별시 강북구 미아동 42-8번지<NA><NA>호텔빅토리아유니온2001-09-26 00:00:00I2018-08-31 23:59:59.0단란주점202651.538047456473.886142단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N62.05<NA><NA><NA>
330800003080000-103-1993-0005919931211<NA>3폐업2폐업19950110<NA><NA><NA>02 00000<NA>142878서울특별시 강북구 수유동 189-35번지<NA><NA>탑슬2001-10-19 00:00:00I2018-08-31 23:59:59.0단란주점202129.983395459857.729451단란주점00주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430800003080000-103-1993-0209619931204<NA>3폐업2폐업20010601<NA><NA><NA>02 955056871.79142876서울특별시 강북구 수유동 176-56번지<NA><NA>이화2001-09-26 00:00:00I2018-08-31 23:59:59.0단란주점202355.585797459847.797181단란주점00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N71.79<NA><NA><NA>
530800003080000-103-1993-0210319930922<NA>3폐업2폐업20000223<NA><NA><NA>02 9842323145.02142873서울특별시 강북구 수유동 48-7번지<NA><NA>멤피스2004-11-09 00:00:00I2018-08-31 23:59:59.0단란주점201909.943575459112.873835단란주점00유흥업소밀집지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N145.02<NA><NA><NA>
630800003080000-103-1993-0210519931209<NA>1영업/정상1영업<NA><NA><NA><NA>020988798855.29142821서울특별시 강북구 미아동 701-8번지서울특별시 강북구 솔샘로 235 (미아동)1189아리랑2020-03-13 17:44:29U2020-03-15 02:40:00.0단란주점201598.416993457523.13295단란주점11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N55.29<NA><NA><NA>
730800003080000-103-1993-0210719931113<NA>3폐업2폐업20000624<NA><NA><NA>020988480591.21142100서울특별시 강북구 미아동 산 701-19번지<NA><NA>목화2001-11-08 00:00:00I2018-08-31 23:59:59.0단란주점<NA><NA>단란주점01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N91.21<NA><NA><NA>
830800003080000-103-1993-0211419931211<NA>1영업/정상1영업<NA><NA><NA><NA>02 993061589.33142867서울특별시 강북구 번동 448-9 (번문길 14 -1)서울특별시 강북구 도봉로82길 26 (번동,(번문길 14 -1))1069오케이 단란주점2021-11-24 15:23:53U2021-11-26 02:40:00.0단란주점202117.779121459205.104521단란주점00주택가주변기타상수도전용00000<NA>00N89.33<NA><NA><NA>
930800003080000-103-1993-0211619931126<NA>1영업/정상1영업<NA><NA><NA><NA>02 906816163.69142865서울특별시 강북구 번동 430-59번지서울특별시 강북구 한천로 944 (번동)1136역마차2005-09-13 00:00:00I2018-08-31 23:59:59.0단란주점203047.42372459184.151684단란주점01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.69<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
43130800003080000-103-2019-0000120190315<NA>3폐업2폐업20200903<NA><NA><NA><NA>82.7142878서울특별시 강북구 수유동 191-16 지하1층서울특별시 강북구 도봉로 341, 지하1층 (수유동)1074럭스 바(LUXE BAR)2020-09-03 13:38:32U2020-09-05 02:40:00.0단란주점202189.124742459553.649543단란주점<NA><NA>유흥업소밀집지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y82.7<NA><NA><NA>
43230800003080000-103-2020-000012020-08-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>123.93142-878서울특별시 강북구 수유동 191-78서울특별시 강북구 한천로139길 39 (수유동)1074발렌타인2024-01-26 14:59:41U2023-11-30 22:08:00.0단란주점202157.645758459585.806247<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43330800003080000-103-2020-0000220201104<NA>1영업/정상1영업<NA><NA><NA><NA><NA>51.15142878서울특별시 강북구 수유동 229-2 덕인빌딩 202호서울특별시 강북구 도봉로87길 3, 덕인빌딩 2층 202호 (수유동)1073팔로우2022-10-20 19:18:28U2021-10-30 22:02:00.0단란주점202151.414278459525.916131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43430800003080000-103-2022-000012022-01-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>81.98142-878서울특별시 강북구 수유동 191-57서울특별시 강북구 한천로139길 11, 3층 (수유동)1074명월이2023-12-27 16:22:06U2022-11-01 22:09:00.0단란주점202247.09326459688.514696<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43530800003080000-103-2022-0000220220728<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.08142891서울특별시 강북구 수유동 45-1 평익타워서울특별시 강북구 노해로 3, 평익타워 지하1층 B02호 (수유동)1081그린2022-07-28 12:18:31I2021-12-06 21:00:00.0단란주점201933.21092459282.7969<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43630800003080000-103-2022-000032022-09-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>68.94142-878서울특별시 강북구 수유동 229-2 덕인빌딩 3층 301호서울특별시 강북구 도봉로87길 3, 덕인빌딩 3층 301호 (수유동)1073와우노래타운2024-02-23 15:46:58U2023-12-01 22:05:00.0단란주점202151.414278459525.916131<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43730800003080000-103-2022-0000420221202<NA>1영업/정상1영업<NA><NA><NA><NA>02992 969793.46142878서울특별시 강북구 수유동 229-53 지하1층서울특별시 강북구 도봉로83길 10, 지하1층 (수유동)1073오렌지노래주점2022-12-02 09:44:34I2021-11-02 00:04:00.0단란주점202059.626241459458.740806<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43830800003080000-103-2022-0000520221212<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.0142878서울특별시 강북구 수유동 229-1서울특별시 강북구 도봉로87길 15, 2층 (수유동)1073이장댁2022-12-12 15:53:30I2021-11-01 23:04:00.0단란주점202108.293119459565.148082<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43930800003080000-103-2022-0000620221212<NA>1영업/정상1영업<NA><NA><NA><NA><NA>78.0142878서울특별시 강북구 수유동 229-1서울특별시 강북구 도봉로87길 15, 3층 (수유동)1073이장댁2022-12-12 16:00:30I2021-11-01 23:04:00.0단란주점202108.293119459565.148082<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44030800003080000-103-2024-000012024-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>112.1142-804서울특별시 강북구 미아동 35-23 지상2층서울특별시 강북구 도봉로6길 12, 2층 (미아동)1220골목길7080라이브 단란주점2024-01-10 20:27:01I2023-11-30 23:02:00.0단란주점202646.435083456678.791358<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>