Overview

Dataset statistics

Number of variables44
Number of observations387
Missing cells3674
Missing cells (%)21.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.9 KiB
Average record size in memory375.3 B

Variable types

Categorical20
Text7
DateTime4
Unsupported7
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18201/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업태명 is highly imbalanced (53.7%)Imbalance
남성종사자수 is highly imbalanced (56.8%)Imbalance
영업장주변구분명 is highly imbalanced (59.3%)Imbalance
등급구분명 is highly imbalanced (62.0%)Imbalance
총인원 is highly imbalanced (70.7%)Imbalance
인허가취소일자 has 387 (100.0%) missing valuesMissing
폐업일자 has 62 (16.0%) missing valuesMissing
휴업시작일자 has 387 (100.0%) missing valuesMissing
휴업종료일자 has 387 (100.0%) missing valuesMissing
재개업일자 has 387 (100.0%) missing valuesMissing
전화번호 has 149 (38.5%) missing valuesMissing
소재지면적 has 24 (6.2%) missing valuesMissing
도로명주소 has 165 (42.6%) missing valuesMissing
도로명우편번호 has 166 (42.9%) missing valuesMissing
좌표정보(X) has 9 (2.3%) missing valuesMissing
좌표정보(Y) has 9 (2.3%) missing valuesMissing
여성종사자수 has 305 (78.8%) missing valuesMissing
다중이용업소여부 has 38 (9.8%) missing valuesMissing
시설총규모 has 38 (9.8%) missing valuesMissing
전통업소지정번호 has 387 (100.0%) missing valuesMissing
전통업소주된음식 has 387 (100.0%) missing valuesMissing
홈페이지 has 387 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 has 61 (15.8%) zerosZeros
시설총규모 has 316 (81.7%) zerosZeros

Reproduction

Analysis started2024-05-11 05:51:10.422442
Analysis finished2024-05-11 05:51:11.270587
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3240000
387 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 387
100.0%

Length

2024-05-11T14:51:11.356822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:11.541417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 387
100.0%

관리번호
Text

UNIQUE 

Distinct387
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:51:11.764189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8514
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

Unique387 ?
Unique (%)100.0%

Sample

1st row3240000-109-1993-00423
2nd row3240000-109-1995-00424
3rd row3240000-109-1995-00436
4th row3240000-109-1995-00446
5th row3240000-109-1995-00447
ValueCountFrequency (%)
3240000-109-1993-00423 1
 
0.3%
3240000-109-2010-00010 1
 
0.3%
3240000-109-2014-00010 1
 
0.3%
3240000-109-2014-00009 1
 
0.3%
3240000-109-2014-00008 1
 
0.3%
3240000-109-2014-00007 1
 
0.3%
3240000-109-2014-00006 1
 
0.3%
3240000-109-2014-00005 1
 
0.3%
3240000-109-2014-00004 1
 
0.3%
3240000-109-2014-00003 1
 
0.3%
Other values (377) 377
97.4%
2024-05-11T14:51:12.139022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3728
43.8%
- 1161
 
13.6%
2 893
 
10.5%
1 836
 
9.8%
9 578
 
6.8%
4 506
 
5.9%
3 491
 
5.8%
5 88
 
1.0%
7 83
 
1.0%
6 82
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7353
86.4%
Dash Punctuation 1161
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3728
50.7%
2 893
 
12.1%
1 836
 
11.4%
9 578
 
7.9%
4 506
 
6.9%
3 491
 
6.7%
5 88
 
1.2%
7 83
 
1.1%
6 82
 
1.1%
8 68
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8514
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3728
43.8%
- 1161
 
13.6%
2 893
 
10.5%
1 836
 
9.8%
9 578
 
6.8%
4 506
 
5.9%
3 491
 
5.8%
5 88
 
1.0%
7 83
 
1.0%
6 82
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8514
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3728
43.8%
- 1161
 
13.6%
2 893
 
10.5%
1 836
 
9.8%
9 578
 
6.8%
4 506
 
5.9%
3 491
 
5.8%
5 88
 
1.0%
7 83
 
1.0%
6 82
 
1.0%
Distinct370
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1993-11-25 00:00:00
Maximum2024-04-18 00:00:00
2024-05-11T14:51:12.331031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:51:12.520297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
3
325 
1
62 

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 (%)
3 325
84.0%
1 62
 
16.0%

Length

2024-05-11T14:51:12.688519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:12.846680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 325
84.0%
1 62
 
16.0%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
325 
영업/정상
62 

Length

Max length5
Median length2
Mean length2.4806202
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 325
84.0%
영업/정상 62
 
16.0%

Length

2024-05-11T14:51:12.992732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:13.108170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 325
84.0%
영업/정상 62
 
16.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2
325 
1
62 

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 (%)
2 325
84.0%
1 62
 
16.0%

Length

2024-05-11T14:51:13.222444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:13.339079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 325
84.0%
1 62
 
16.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
폐업
325 
영업
62 

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 325
84.0%
영업 62
 
16.0%

Length

2024-05-11T14:51:13.461847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:13.573086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 325
84.0%
영업 62
 
16.0%

폐업일자
Date

MISSING 

Distinct287
Distinct (%)88.3%
Missing62
Missing (%)16.0%
Memory size3.2 KiB
Minimum1998-09-30 00:00:00
Maximum2024-03-27 00:00:00
2024-05-11T14:51:13.740111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:51:13.983389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

전화번호
Text

MISSING 

Distinct209
Distinct (%)87.8%
Missing149
Missing (%)38.5%
Memory size3.2 KiB
2024-05-11T14:51:14.481781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.268908
Min length2

Characters and Unicode

Total characters2444
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

Unique199 ?
Unique (%)83.6%

Sample

1st row02 4813697
2nd row0234266293
3rd row02 4261614
4th row02 5858114
5th row02 4262016
ValueCountFrequency (%)
02 202
38.8%
070 7
 
1.3%
428 7
 
1.3%
473 7
 
1.3%
441 6
 
1.2%
477 6
 
1.2%
488 5
 
1.0%
471 4
 
0.8%
429 4
 
0.8%
486 4
 
0.8%
Other values (238) 269
51.6%
2024-05-11T14:51:15.146341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 429
17.6%
394
16.1%
0 385
15.8%
4 298
12.2%
7 177
7.2%
8 173
7.1%
1 133
 
5.4%
3 123
 
5.0%
6 120
 
4.9%
5 114
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2050
83.9%
Space Separator 394
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 429
20.9%
0 385
18.8%
4 298
14.5%
7 177
8.6%
8 173
8.4%
1 133
 
6.5%
3 123
 
6.0%
6 120
 
5.9%
5 114
 
5.6%
9 98
 
4.8%
Space Separator
ValueCountFrequency (%)
394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 429
17.6%
394
16.1%
0 385
15.8%
4 298
12.2%
7 177
7.2%
8 173
7.1%
1 133
 
5.4%
3 123
 
5.0%
6 120
 
4.9%
5 114
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 429
17.6%
394
16.1%
0 385
15.8%
4 298
12.2%
7 177
7.2%
8 173
7.1%
1 133
 
5.4%
3 123
 
5.0%
6 120
 
4.9%
5 114
 
4.7%

소재지면적
Text

MISSING 

Distinct204
Distinct (%)56.2%
Missing24
Missing (%)6.2%
Memory size3.2 KiB
2024-05-11T14:51:15.641204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8539945
Min length3

Characters and Unicode

Total characters1762
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

Unique159 ?
Unique (%)43.8%

Sample

1st row80.00
2nd row78.28
3rd row45.59
4th row36.01
5th row27.50
ValueCountFrequency (%)
6.60 21
 
5.8%
33.00 16
 
4.4%
3.30 15
 
4.1%
10.00 12
 
3.3%
66.00 10
 
2.8%
30.00 9
 
2.5%
9.90 8
 
2.2%
25.00 7
 
1.9%
26.40 7
 
1.9%
20.00 6
 
1.7%
Other values (194) 252
69.4%
2024-05-11T14:51:16.360291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 503
28.5%
. 363
20.6%
3 144
 
8.2%
1 131
 
7.4%
6 130
 
7.4%
2 117
 
6.6%
5 97
 
5.5%
4 83
 
4.7%
9 79
 
4.5%
8 65
 
3.7%
Other values (2) 50
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1398
79.3%
Other Punctuation 364
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 503
36.0%
3 144
 
10.3%
1 131
 
9.4%
6 130
 
9.3%
2 117
 
8.4%
5 97
 
6.9%
4 83
 
5.9%
9 79
 
5.7%
8 65
 
4.6%
7 49
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 363
99.7%
, 1
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 503
28.5%
. 363
20.6%
3 144
 
8.2%
1 131
 
7.4%
6 130
 
7.4%
2 117
 
6.6%
5 97
 
5.5%
4 83
 
4.7%
9 79
 
4.5%
8 65
 
3.7%
Other values (2) 50
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 503
28.5%
. 363
20.6%
3 144
 
8.2%
1 131
 
7.4%
6 130
 
7.4%
2 117
 
6.6%
5 97
 
5.5%
4 83
 
4.7%
9 79
 
4.5%
8 65
 
3.7%
Other values (2) 50
 
2.8%
Distinct89
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:51:16.731976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0490956
Min length6

Characters and Unicode

Total characters2341
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

Unique30 ?
Unique (%)7.8%

Sample

1st row134855
2nd row134830
3rd row134803
4th row134880
5th row134838
ValueCountFrequency (%)
134830 26
 
6.7%
134874 23
 
5.9%
134890 16
 
4.1%
134822 13
 
3.4%
134837 12
 
3.1%
134843 10
 
2.6%
134825 9
 
2.3%
134867 9
 
2.3%
134841 9
 
2.3%
134864 8
 
2.1%
Other values (79) 252
65.1%
2024-05-11T14:51:17.259474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 489
20.9%
1 470
20.1%
3 467
19.9%
8 411
17.6%
0 117
 
5.0%
7 112
 
4.8%
5 73
 
3.1%
2 70
 
3.0%
6 63
 
2.7%
9 50
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2322
99.2%
Dash Punctuation 19
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 489
21.1%
1 470
20.2%
3 467
20.1%
8 411
17.7%
0 117
 
5.0%
7 112
 
4.8%
5 73
 
3.1%
2 70
 
3.0%
6 63
 
2.7%
9 50
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2341
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 489
20.9%
1 470
20.1%
3 467
19.9%
8 411
17.6%
0 117
 
5.0%
7 112
 
4.8%
5 73
 
3.1%
2 70
 
3.0%
6 63
 
2.7%
9 50
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2341
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 489
20.9%
1 470
20.1%
3 467
19.9%
8 411
17.6%
0 117
 
5.0%
7 112
 
4.8%
5 73
 
3.1%
2 70
 
3.0%
6 63
 
2.7%
9 50
 
2.1%
Distinct355
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:51:17.611706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length24.242894
Min length17

Characters and Unicode

Total characters9382
Distinct characters168
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

Unique334 ?
Unique (%)86.3%

Sample

1st row서울특별시 강동구 암사동 441-11
2nd row서울특별시 강동구 명일동 350-4
3rd row서울특별시 강동구 고덕동 255-3
4th row서울특별시 강동구 길동 406-10
5th row서울특별시 강동구 상일동 301-1
ValueCountFrequency (%)
서울특별시 387
20.5%
강동구 387
20.5%
성내동 92
 
4.9%
천호동 85
 
4.5%
1층 48
 
2.5%
명일동 45
 
2.4%
길동 43
 
2.3%
암사동 40
 
2.1%
둔촌동 34
 
1.8%
고덕동 25
 
1.3%
Other values (478) 703
37.2%
2024-05-11T14:51:18.110306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1808
19.3%
799
 
8.5%
1 413
 
4.4%
396
 
4.2%
390
 
4.2%
388
 
4.1%
387
 
4.1%
387
 
4.1%
387
 
4.1%
387
 
4.1%
Other values (158) 3640
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5191
55.3%
Decimal Number 1983
 
21.1%
Space Separator 1808
 
19.3%
Dash Punctuation 346
 
3.7%
Uppercase Letter 19
 
0.2%
Open Punctuation 14
 
0.1%
Close Punctuation 14
 
0.1%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
799
15.4%
396
 
7.6%
390
 
7.5%
388
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
173
 
3.3%
130
 
2.5%
Other values (138) 1367
26.3%
Decimal Number
ValueCountFrequency (%)
1 413
20.8%
2 275
13.9%
4 272
13.7%
3 222
11.2%
5 198
10.0%
0 172
8.7%
6 118
 
6.0%
8 114
 
5.7%
9 107
 
5.4%
7 92
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
G 5
26.3%
A 4
21.1%
L 4
21.1%
S 3
15.8%
B 3
15.8%
Space Separator
ValueCountFrequency (%)
1808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5191
55.3%
Common 4172
44.5%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
799
15.4%
396
 
7.6%
390
 
7.5%
388
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
173
 
3.3%
130
 
2.5%
Other values (138) 1367
26.3%
Common
ValueCountFrequency (%)
1808
43.3%
1 413
 
9.9%
- 346
 
8.3%
2 275
 
6.6%
4 272
 
6.5%
3 222
 
5.3%
5 198
 
4.7%
0 172
 
4.1%
6 118
 
2.8%
8 114
 
2.7%
Other values (5) 234
 
5.6%
Latin
ValueCountFrequency (%)
G 5
26.3%
A 4
21.1%
L 4
21.1%
S 3
15.8%
B 3
15.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5191
55.3%
ASCII 4191
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1808
43.1%
1 413
 
9.9%
- 346
 
8.3%
2 275
 
6.6%
4 272
 
6.5%
3 222
 
5.3%
5 198
 
4.7%
0 172
 
4.1%
6 118
 
2.8%
8 114
 
2.7%
Other values (10) 253
 
6.0%
Hangul
ValueCountFrequency (%)
799
15.4%
396
 
7.6%
390
 
7.5%
388
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
387
 
7.5%
173
 
3.3%
130
 
2.5%
Other values (138) 1367
26.3%

도로명주소
Text

MISSING 

Distinct218
Distinct (%)98.2%
Missing165
Missing (%)42.6%
Memory size3.2 KiB
2024-05-11T14:51:18.493607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length45
Mean length32.779279
Min length22

Characters and Unicode

Total characters7277
Distinct characters158
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)96.4%

Sample

1st row서울특별시 강동구 양재대로99길 6 (성내동)
2nd row서울특별시 강동구 올림픽로 820 (암사동)
3rd row서울특별시 강동구 천호대로 1005 (천호동)
4th row서울특별시 강동구 성안로31길 43 (천호동)
5th row서울특별시 강동구 진황도로31길 26 (천호동)
ValueCountFrequency (%)
서울특별시 222
 
15.7%
강동구 222
 
15.7%
성내동 66
 
4.7%
1층 61
 
4.3%
천호동 35
 
2.5%
길동 24
 
1.7%
양재대로 24
 
1.7%
암사동 23
 
1.6%
명일동 19
 
1.3%
2층 18
 
1.3%
Other values (387) 703
49.6%
2024-05-11T14:51:19.138576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1195
 
16.4%
476
 
6.5%
1 380
 
5.2%
243
 
3.3%
230
 
3.2%
, 227
 
3.1%
( 227
 
3.1%
) 227
 
3.1%
224
 
3.1%
222
 
3.1%
Other values (148) 3626
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4107
56.4%
Decimal Number 1266
 
17.4%
Space Separator 1195
 
16.4%
Other Punctuation 227
 
3.1%
Open Punctuation 227
 
3.1%
Close Punctuation 227
 
3.1%
Dash Punctuation 22
 
0.3%
Uppercase Letter 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
476
 
11.6%
243
 
5.9%
230
 
5.6%
224
 
5.5%
222
 
5.4%
222
 
5.4%
222
 
5.4%
222
 
5.4%
218
 
5.3%
175
 
4.3%
Other values (129) 1653
40.2%
Decimal Number
ValueCountFrequency (%)
1 380
30.0%
2 155
12.2%
3 134
 
10.6%
0 130
 
10.3%
5 92
 
7.3%
4 90
 
7.1%
6 88
 
7.0%
9 75
 
5.9%
7 63
 
5.0%
8 59
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
S 1
 
20.0%
L 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1195
100.0%
Other Punctuation
ValueCountFrequency (%)
, 227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4107
56.4%
Common 3165
43.5%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
476
 
11.6%
243
 
5.9%
230
 
5.6%
224
 
5.5%
222
 
5.4%
222
 
5.4%
222
 
5.4%
222
 
5.4%
218
 
5.3%
175
 
4.3%
Other values (129) 1653
40.2%
Common
ValueCountFrequency (%)
1195
37.8%
1 380
 
12.0%
, 227
 
7.2%
( 227
 
7.2%
) 227
 
7.2%
2 155
 
4.9%
3 134
 
4.2%
0 130
 
4.1%
5 92
 
2.9%
4 90
 
2.8%
Other values (6) 308
 
9.7%
Latin
ValueCountFrequency (%)
A 3
60.0%
S 1
 
20.0%
L 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4107
56.4%
ASCII 3170
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1195
37.7%
1 380
 
12.0%
, 227
 
7.2%
( 227
 
7.2%
) 227
 
7.2%
2 155
 
4.9%
3 134
 
4.2%
0 130
 
4.1%
5 92
 
2.9%
4 90
 
2.8%
Other values (9) 313
 
9.9%
Hangul
ValueCountFrequency (%)
476
 
11.6%
243
 
5.9%
230
 
5.6%
224
 
5.5%
222
 
5.4%
222
 
5.4%
222
 
5.4%
222
 
5.4%
218
 
5.3%
175
 
4.3%
Other values (129) 1653
40.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)45.7%
Missing166
Missing (%)42.9%
Infinite0
Infinite (%)0.0%
Mean5327.1131
Minimum5211
Maximum5411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T14:51:19.315332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5211
5-th percentile5226
Q15272
median5334
Q35381
95-th percentile5404
Maximum5411
Range200
Interquartile range (IQR)109

Descriptive statistics

Standard deviation58.788456
Coefficient of variation (CV)0.011035706
Kurtosis-1.1740383
Mean5327.1131
Median Absolute Deviation (MAD)51
Skewness-0.30476806
Sum1177292
Variance3456.0826
MonotonicityNot monotonic
2024-05-11T14:51:19.770448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5404 14
 
3.6%
5328 9
 
2.3%
5251 6
 
1.6%
5295 6
 
1.6%
5343 6
 
1.6%
5350 6
 
1.6%
5376 6
 
1.6%
5383 5
 
1.3%
5282 4
 
1.0%
5378 4
 
1.0%
Other values (91) 155
40.1%
(Missing) 166
42.9%
ValueCountFrequency (%)
5211 1
 
0.3%
5213 1
 
0.3%
5219 1
 
0.3%
5220 2
0.5%
5221 2
0.5%
5222 3
0.8%
5226 2
0.5%
5227 2
0.5%
5232 1
 
0.3%
5236 3
0.8%
ValueCountFrequency (%)
5411 4
 
1.0%
5409 1
 
0.3%
5408 1
 
0.3%
5407 1
 
0.3%
5406 1
 
0.3%
5405 3
 
0.8%
5404 14
3.6%
5403 2
 
0.5%
5398 2
 
0.5%
5395 1
 
0.3%
Distinct367
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-11T14:51:20.119802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length6.2764858
Min length1

Characters and Unicode

Total characters2429
Distinct characters381
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique350 ?
Unique (%)90.4%

Sample

1st row한국양봉진흥주식회사
2nd row방주물산
3rd row천호상회
4th row파랑월드
5th row대동유통
ValueCountFrequency (%)
주식회사 11
 
2.5%
강경젓갈 3
 
0.7%
황토특산 3
 
0.7%
주)예주병과 3
 
0.7%
엘라인유통(주 2
 
0.5%
2
 
0.5%
뻥소리 2
 
0.5%
대호식품 2
 
0.5%
효성어묵 2
 
0.5%
영우유통 2
 
0.5%
Other values (391) 401
92.6%
2024-05-11T14:51:20.647971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130
 
5.4%
) 109
 
4.5%
( 106
 
4.4%
64
 
2.6%
59
 
2.4%
48
 
2.0%
46
 
1.9%
44
 
1.8%
42
 
1.7%
42
 
1.7%
Other values (371) 1739
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2128
87.6%
Close Punctuation 109
 
4.5%
Open Punctuation 106
 
4.4%
Space Separator 46
 
1.9%
Uppercase Letter 29
 
1.2%
Other Punctuation 7
 
0.3%
Lowercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
130
 
6.1%
64
 
3.0%
59
 
2.8%
48
 
2.3%
44
 
2.1%
42
 
2.0%
42
 
2.0%
42
 
2.0%
41
 
1.9%
41
 
1.9%
Other values (349) 1575
74.0%
Uppercase Letter
ValueCountFrequency (%)
F 4
13.8%
A 4
13.8%
G 4
13.8%
B 3
10.3%
L 3
10.3%
E 2
6.9%
C 2
6.9%
K 2
6.9%
M 1
 
3.4%
T 1
 
3.4%
Other values (3) 3
10.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
25.0%
r 1
25.0%
o 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
. 3
42.9%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2128
87.6%
Common 268
 
11.0%
Latin 33
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
130
 
6.1%
64
 
3.0%
59
 
2.8%
48
 
2.3%
44
 
2.1%
42
 
2.0%
42
 
2.0%
42
 
2.0%
41
 
1.9%
41
 
1.9%
Other values (349) 1575
74.0%
Latin
ValueCountFrequency (%)
F 4
12.1%
A 4
12.1%
G 4
12.1%
B 3
9.1%
L 3
9.1%
E 2
 
6.1%
C 2
 
6.1%
K 2
 
6.1%
a 1
 
3.0%
r 1
 
3.0%
Other values (7) 7
21.2%
Common
ValueCountFrequency (%)
) 109
40.7%
( 106
39.6%
46
17.2%
& 4
 
1.5%
. 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2128
87.6%
ASCII 301
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
130
 
6.1%
64
 
3.0%
59
 
2.8%
48
 
2.3%
44
 
2.1%
42
 
2.0%
42
 
2.0%
42
 
2.0%
41
 
1.9%
41
 
1.9%
Other values (349) 1575
74.0%
ASCII
ValueCountFrequency (%)
) 109
36.2%
( 106
35.2%
46
15.3%
& 4
 
1.3%
F 4
 
1.3%
A 4
 
1.3%
G 4
 
1.3%
B 3
 
1.0%
L 3
 
1.0%
. 3
 
1.0%
Other values (12) 15
 
5.0%
Distinct360
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum1999-01-14 00:00:00
Maximum2024-04-18 15:23:09
2024-05-11T14:51:20.843533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:51:21.109954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
I
312 
U
75 

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 312
80.6%
U 75
 
19.4%

Length

2024-05-11T14:51:21.361415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:21.537508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 312
80.6%
u 75
 
19.4%
Distinct100
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:00:00
2024-05-11T14:51:21.706787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:51:21.936548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
식품소분업
387 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 387
100.0%

Length

2024-05-11T14:51:22.141802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:22.305228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 387
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct292
Distinct (%)77.2%
Missing9
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean212236.05
Minimum210528.38
Maximum215984.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T14:51:22.463633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210528.38
5-th percentile210842.4
Q1211388.16
median211979.52
Q3212726.51
95-th percentile215029.57
Maximum215984.38
Range5455.9928
Interquartile range (IQR)1338.3571

Descriptive statistics

Standard deviation1171.8285
Coefficient of variation (CV)0.005521345
Kurtosis0.68125422
Mean212236.05
Median Absolute Deviation (MAD)685.46651
Skewness1.0648372
Sum80225228
Variance1373182
MonotonicityNot monotonic
2024-05-11T14:51:22.662630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210931.643485 19
 
4.9%
211838.35431041 9
 
2.3%
211979.520569314 6
 
1.6%
212676.162193508 5
 
1.3%
213700.877714971 5
 
1.3%
212334.69890736 4
 
1.0%
211025.924972294 4
 
1.0%
212334.9584644 3
 
0.8%
212771.950892437 3
 
0.8%
212016.915921852 3
 
0.8%
Other values (282) 317
81.9%
(Missing) 9
 
2.3%
ValueCountFrequency (%)
210528.382324953 1
0.3%
210566.875626134 2
0.5%
210607.856193423 2
0.5%
210621.633987432 2
0.5%
210649.789630326 1
0.3%
210661.929283313 1
0.3%
210677.600797353 1
0.3%
210702.347047613 1
0.3%
210704.774772111 1
0.3%
210757.026210431 1
0.3%
ValueCountFrequency (%)
215984.375136997 1
 
0.3%
215661.222623 1
 
0.3%
215254.0 1
 
0.3%
215206.101435737 1
 
0.3%
215203.799066155 1
 
0.3%
215195.884311721 2
0.5%
215178.170771585 1
 
0.3%
215177.804033096 3
0.8%
215172.159803867 1
 
0.3%
215167.502111577 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct292
Distinct (%)77.2%
Missing9
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean448821.52
Minimum446598.59
Maximum451725.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T14:51:22.905910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446598.59
5-th percentile447195.68
Q1447918.68
median448661.84
Q3449693.71
95-th percentile450907.68
Maximum451725.94
Range5127.3498
Interquartile range (IQR)1775.0319

Descriptive statistics

Standard deviation1115.4628
Coefficient of variation (CV)0.0024853149
Kurtosis-0.78929901
Mean448821.52
Median Absolute Deviation (MAD)911.5619
Skewness0.23848713
Sum1.6965454 × 108
Variance1244257.3
MonotonicityNot monotonic
2024-05-11T14:51:23.122236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448522.079827 19
 
4.9%
447195.676766748 9
 
2.3%
446932.653730601 6
 
1.6%
449910.881572138 5
 
1.3%
450278.100930843 5
 
1.3%
447728.865137096 4
 
1.0%
448495.189151526 4
 
1.0%
450346.790651613 3
 
0.8%
450113.214810361 3
 
0.8%
447600.544562582 3
 
0.8%
Other values (282) 317
81.9%
(Missing) 9
 
2.3%
ValueCountFrequency (%)
446598.591776331 1
 
0.3%
446761.604007505 1
 
0.3%
446812.537064604 1
 
0.3%
446882.690089639 2
 
0.5%
446932.653730601 6
1.6%
446940.608800863 1
 
0.3%
447012.990706287 1
 
0.3%
447055.923693449 1
 
0.3%
447086.687082877 1
 
0.3%
447125.42728615 1
 
0.3%
ValueCountFrequency (%)
451725.941564 1
0.3%
451457.0 1
0.3%
451368.118053367 1
0.3%
451105.958039247 1
0.3%
451078.579292321 1
0.3%
451049.255756892 1
0.3%
451031.660707591 1
0.3%
451029.854926958 1
0.3%
451026.433073355 1
0.3%
451009.062585424 1
0.3%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
식품소분업
349 
<NA>
38 

Length

Max length5
Median length5
Mean length4.9018088
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품소분업 349
90.2%
<NA> 38
 
9.8%

Length

2024-05-11T14:51:23.385841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:23.547082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품소분업 349
90.2%
na 38
 
9.8%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
305 
0
56 
1
 
20
2
 
4
3
 
2

Length

Max length4
Median length4
Mean length3.3643411
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row<NA>
3rd row1
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 305
78.8%
0 56
 
14.5%
1 20
 
5.2%
2 4
 
1.0%
3 2
 
0.5%

Length

2024-05-11T14:51:23.734477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:23.921401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 305
78.8%
0 56
 
14.5%
1 20
 
5.2%
2 4
 
1.0%
3 2
 
0.5%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)7.3%
Missing305
Missing (%)78.8%
Infinite0
Infinite (%)0.0%
Mean0.48780488
Minimum0
Maximum5
Zeros61
Zeros (%)15.8%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T14:51:24.082852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.75
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation0.99683329
Coefficient of variation (CV)2.0435082
Kurtosis6.2067101
Mean0.48780488
Median Absolute Deviation (MAD)0
Skewness2.4106338
Sum40
Variance0.9936766
MonotonicityNot monotonic
2024-05-11T14:51:24.250214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 61
 
15.8%
1 9
 
2.3%
2 8
 
2.1%
3 2
 
0.5%
5 1
 
0.3%
4 1
 
0.3%
(Missing) 305
78.8%
ValueCountFrequency (%)
0 61
15.8%
1 9
 
2.3%
2 8
 
2.1%
3 2
 
0.5%
4 1
 
0.3%
5 1
 
0.3%
ValueCountFrequency (%)
5 1
 
0.3%
4 1
 
0.3%
3 2
 
0.5%
2 8
 
2.1%
1 9
 
2.3%
0 61
15.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
315 
주택가주변
40 
기타
 
26
아파트지역
 
5
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9922481
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 315
81.4%
주택가주변 40
 
10.3%
기타 26
 
6.7%
아파트지역 5
 
1.3%
유흥업소밀집지역 1
 
0.3%

Length

2024-05-11T14:51:24.457007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:24.628690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
81.4%
주택가주변 40
 
10.3%
기타 26
 
6.7%
아파트지역 5
 
1.3%
유흥업소밀집지역 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
315 
자율
68 
기타
 
3
 
1

Length

Max length4
Median length4
Mean length3.625323
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 315
81.4%
자율 68
 
17.6%
기타 3
 
0.8%
1
 
0.3%

Length

2024-05-11T14:51:24.827279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:24.992392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 315
81.4%
자율 68
 
17.6%
기타 3
 
0.8%
1
 
0.3%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
259 
상수도전용
128 

Length

Max length5
Median length4
Mean length4.3307494
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 259
66.9%
상수도전용 128
33.1%

Length

2024-05-11T14:51:25.197732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:25.404483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 259
66.9%
상수도전용 128
33.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
367 
0
 
20

Length

Max length4
Median length4
Mean length3.8449612
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> 367
94.8%
0 20
 
5.2%

Length

2024-05-11T14:51:25.673384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:25.954725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
94.8%
0 20
 
5.2%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
271 
0
116 

Length

Max length4
Median length4
Mean length3.1007752
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> 271
70.0%
0 116
30.0%

Length

2024-05-11T14:51:26.147228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:26.301598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 271
70.0%
0 116
30.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
271 
0
116 

Length

Max length4
Median length4
Mean length3.1007752
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> 271
70.0%
0 116
30.0%

Length

2024-05-11T14:51:26.463648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:26.614351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 271
70.0%
0 116
30.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
271 
0
116 

Length

Max length4
Median length4
Mean length3.1007752
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> 271
70.0%
0 116
30.0%

Length

2024-05-11T14:51:26.765638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:26.904811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 271
70.0%
0 116
30.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
271 
0
116 

Length

Max length4
Median length4
Mean length3.1007752
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> 271
70.0%
0 116
30.0%

Length

2024-05-11T14:51:27.041567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:27.191708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 271
70.0%
0 116
30.0%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
임대
188 
<NA>
137 
자가
62 

Length

Max length4
Median length2
Mean length2.7080103
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 (%)
임대 188
48.6%
<NA> 137
35.4%
자가 62
 
16.0%

Length

2024-05-11T14:51:27.385390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:27.571135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 188
48.6%
na 137
35.4%
자가 62
 
16.0%

보증액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
313 
0
74 

Length

Max length4
Median length4
Mean length3.4263566
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> 313
80.9%
0 74
 
19.1%

Length

2024-05-11T14:51:27.772340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:28.051835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 313
80.9%
0 74
 
19.1%

월세액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
313 
0
74 

Length

Max length4
Median length4
Mean length3.4263566
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> 313
80.9%
0 74
 
19.1%

Length

2024-05-11T14:51:28.205448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:51:28.359992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 313
80.9%
0 74
 
19.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing38
Missing (%)9.8%
Memory size906.0 B
False
349 
(Missing)
38 
ValueCountFrequency (%)
False 349
90.2%
(Missing) 38
 
9.8%
2024-05-11T14:51:28.474460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)8.6%
Missing38
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean3.9319771
Minimum0
Maximum149
Zeros316
Zeros (%)81.7%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-05-11T14:51:28.600285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile30
Maximum149
Range149
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.906459
Coefficient of variation (CV)4.0454099
Kurtosis34.246415
Mean3.9319771
Median Absolute Deviation (MAD)0
Skewness5.3929877
Sum1372.26
Variance253.01544
MonotonicityNot monotonic
2024-05-11T14:51:28.791741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 316
81.7%
3.3 2
 
0.5%
66.0 2
 
0.5%
33.0 2
 
0.5%
30.0 2
 
0.5%
18.5 1
 
0.3%
149.0 1
 
0.3%
81.38 1
 
0.3%
23.92 1
 
0.3%
75.46 1
 
0.3%
Other values (20) 20
 
5.2%
(Missing) 38
 
9.8%
ValueCountFrequency (%)
0.0 316
81.7%
2.0 1
 
0.3%
3.3 2
 
0.5%
6.6 1
 
0.3%
12.2 1
 
0.3%
14.0 1
 
0.3%
18.0 1
 
0.3%
18.5 1
 
0.3%
19.8 1
 
0.3%
20.7 1
 
0.3%
ValueCountFrequency (%)
149.0 1
0.3%
116.89 1
0.3%
96.66 1
0.3%
81.38 1
0.3%
75.46 1
0.3%
66.25 1
0.3%
66.0 2
0.5%
63.15 1
0.3%
49.5 1
0.3%
49.0 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing387
Missing (%)100.0%
Memory size3.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-109-1993-0042319931125<NA>3폐업2폐업20080213<NA><NA><NA>02 481369780.00134855서울특별시 강동구 암사동 441-11<NA><NA>한국양봉진흥주식회사2008-02-17 12:47:05I2018-08-31 23:59:59.0식품소분업211438.476784450316.299898식품소분업31주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132400003240000-109-1995-0042419950309<NA>3폐업2폐업20050421<NA><NA><NA>023426629378.28134830서울특별시 강동구 명일동 350-4<NA><NA>방주물산2002-07-15 00:00:00I2018-08-31 23:59:59.0식품소분업212785.236301449150.358975식품소분업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232400003240000-109-1995-0043619951128<NA>3폐업2폐업20051222<NA><NA><NA>02 426161445.59134803서울특별시 강동구 고덕동 255-3<NA><NA>천호상회2002-06-06 00:00:00I2018-08-31 23:59:59.0식품소분업214322.719075450939.870971식품소분업12주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332400003240000-109-1995-0044619950531<NA>3폐업2폐업20080213<NA><NA><NA>02 585811436.01134880서울특별시 강동구 길동 406-10<NA><NA>파랑월드2008-02-17 12:47:55I2018-08-31 23:59:59.0식품소분업212477.07187448107.433152식품소분업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432400003240000-109-1995-0044719950706<NA>3폐업2폐업20040709<NA><NA><NA>02 426201627.50134838서울특별시 강동구 상일동 301-1<NA><NA>대동유통2002-07-15 00:00:00I2018-08-31 23:59:59.0식품소분업215111.246226449501.11552식품소분업12주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532400003240000-109-1995-0044819951110<NA>3폐업2폐업20030519<NA><NA><NA>02 489426420.10134817서울특별시 강동구 둔촌동 65-3<NA><NA>산수식품2002-06-06 00:00:00I2018-08-31 23:59:59.0식품소분업212517.266139447921.013888식품소분업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632400003240000-109-1996-0044019961030<NA>1영업/정상1영업<NA><NA><NA><NA>02 487224925.00134843서울특별시 강동구 성내동 387-43서울특별시 강동구 양재대로99길 6 (성내동)5375한국델푸드산업사2013-12-19 19:39:04I2018-08-31 23:59:59.0식품소분업212054.166049447747.986862식품소분업22주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
732400003240000-109-1996-0044119961224<NA>3폐업2폐업19991123<NA><NA><NA>02 058.66134859서울특별시 강동구 암사동 491-6<NA><NA>해광물산2002-06-06 00:00:00I2018-08-31 23:59:59.0식품소분업211523.330598449679.025268식품소분업21주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832400003240000-109-1997-0042219970911<NA>3폐업2폐업20020228<NA><NA><NA>02110.34134825서울특별시 강동구 명일동 46-4<NA><NA>주)해태유통해태마트2002-02-28 00:00:00I2018-08-31 23:59:59.0식품소분업213700.877715450278.100931식품소분업35아파트지역<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-109-1997-0042519971213<NA>3폐업2폐업20010118<NA><NA><NA>02 483144224.75134822서울특별시 강동구 둔촌동 459-0<NA><NA>(주)동우농산2002-06-06 00:00:00I2018-08-31 23:59:59.0식품소분업212417.485133447742.943283식품소분업<NA>3주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
37732400003240000-109-2022-0000520220809<NA>1영업/정상1영업<NA><NA><NA><NA>02 441 996830.56134830서울특별시 강동구 명일동 333-1서울특별시 강동구 양재대로138길 14, A동 102호 (명일동)5295명일건어물2022-08-09 11:38:31I2021-12-07 23:01:00.0식품소분업212706.795162449694.9654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37832400003240000-109-2022-0000620220818<NA>1영업/정상1영업<NA><NA><NA><NA>02 482 030113.00134846서울특별시 강동구 성내동 437-8서울특별시 강동구 양재대로87길 51, 1층 102호 (성내동)5406토브2022-08-18 16:13:42I2021-12-07 22:00:00.0식품소분업211619.626234447086.687083<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37932400003240000-109-2022-0000720221028<NA>1영업/정상1영업<NA><NA><NA><NA>02 488 082230.00134815서울특별시 강동구 길동 252-1서울특별시 강동구 명일로 199-5, 2층 (길동)5350우성산업2022-10-28 15:45:38I2021-10-30 21:00:00.0식품소분업212779.984907448273.989571<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38032400003240000-109-2023-000012023-02-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.78134-811서울특별시 강동구 길동 347-12 동호빌딩서울특별시 강동구 양재대로 1522, 동호빌딩 2층 209호 (길동)5303아이엔조이2023-02-24 15:47:36I2022-12-01 22:06:00.0식품소분업212453.914837448811.888383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38132400003240000-109-2023-000022023-02-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.00134-856서울특별시 강동구 암사동 487-36서울특별시 강동구 구천면로 333, 1층 (암사동)5259농업법인(주)자연촌2023-02-28 16:08:48I2022-12-03 00:03:00.0식품소분업211974.529997449663.797812<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38232400003240000-109-2023-000032023-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.00134-870서울특별시 강동구 천호동 382-12서울특별시 강동구 구천면로33길 44, 1층 (천호동)5325샬롬2023-03-08 13:57:00I2022-12-02 23:00:00.0식품소분업211301.209267448933.687561<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38332400003240000-109-2023-000042023-09-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.97134-855서울특별시 강동구 암사동 446-16서울특별시 강동구 고덕로 77, 102호 (암사동)5237바다향기2023-09-12 15:50:30I2022-12-08 23:04:00.0식품소분업211762.01166450307.409849<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38432400003240000-109-2023-000052023-12-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.90134-827서울특별시 강동구 명일동 257 주공아파트9단지종합상가서울특별시 강동구 구천면로 476, 주공아파트9단지종합상가 121호 (명일동)5272수다스쿱마켓2023-12-29 14:40:15I2022-11-01 21:01:00.0식품소분업213262.059722449527.440852<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38532400003240000-109-2024-000012024-02-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.00134-867서울특별시 강동구 천호동 299-27 대성예가서울특별시 강동구 천중로18길 9, 1층 101호 (천호동, 대성예가)5325라온2024-02-14 14:59:16I2023-12-01 23:06:00.0식품소분업211436.615058449119.826384<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38632400003240000-109-2024-000022024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.00134-812서울특별시 강동구 길동 368-6 스타빌딩서울특별시 강동구 양재대로 1505, 스타빌딩 502호 (길동)5342정도담은2024-04-18 15:23:09I2023-12-03 22:00:00.0식품소분업212355.582269448676.991643<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>