Overview

Dataset statistics

Number of variables44
Number of observations93
Missing cells805
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.2 KiB
Average record size in memory376.4 B

Variable types

Categorical22
Text7
DateTime3
Unsupported7
Numeric4
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18326/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업장주변구분명 is highly imbalanced (72.9%)Imbalance
등급구분명 is highly imbalanced (70.5%)Imbalance
총인원 is highly imbalanced (85.0%)Imbalance
인허가취소일자 has 93 (100.0%) missing valuesMissing
폐업일자 has 31 (33.3%) missing valuesMissing
휴업시작일자 has 93 (100.0%) missing valuesMissing
휴업종료일자 has 93 (100.0%) missing valuesMissing
재개업일자 has 93 (100.0%) missing valuesMissing
전화번호 has 14 (15.1%) missing valuesMissing
소재지면적 has 4 (4.3%) missing valuesMissing
도로명주소 has 26 (28.0%) missing valuesMissing
도로명우편번호 has 27 (29.0%) missing valuesMissing
좌표정보(X) has 1 (1.1%) missing valuesMissing
좌표정보(Y) has 1 (1.1%) missing valuesMissing
다중이용업소여부 has 25 (26.9%) missing valuesMissing
시설총규모 has 25 (26.9%) missing valuesMissing
전통업소지정번호 has 93 (100.0%) missing valuesMissing
전통업소주된음식 has 93 (100.0%) missing valuesMissing
홈페이지 has 93 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 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
시설총규모 has 62 (66.7%) zerosZeros

Reproduction

Analysis started2024-05-11 00:22:39.208532
Analysis finished2024-05-11 00:22:40.449022
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
3240000
93 

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 93
100.0%

Length

2024-05-11T00:22:40.662465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:22:41.252010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 93
100.0%

관리번호
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-05-11T00:22:41.642573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2046
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

Unique93 ?
Unique (%)100.0%

Sample

1st row3240000-114-1990-00462
2nd row3240000-114-1996-00470
3rd row3240000-114-1996-00471
4th row3240000-114-1996-00472
5th row3240000-114-1996-00473
ValueCountFrequency (%)
3240000-114-1990-00462 1
 
1.1%
3240000-114-2009-00007 1
 
1.1%
3240000-114-2014-00004 1
 
1.1%
3240000-114-2014-00003 1
 
1.1%
3240000-114-2014-00002 1
 
1.1%
3240000-114-2014-00001 1
 
1.1%
3240000-114-2013-00003 1
 
1.1%
3240000-114-2013-00002 1
 
1.1%
3240000-114-2013-00001 1
 
1.1%
3240000-114-2012-00005 1
 
1.1%
Other values (83) 83
89.2%
2024-05-11T00:22:42.613559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 839
41.0%
- 279
 
13.6%
1 266
 
13.0%
2 216
 
10.6%
4 214
 
10.5%
3 121
 
5.9%
9 48
 
2.3%
6 17
 
0.8%
5 17
 
0.8%
7 15
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1767
86.4%
Dash Punctuation 279
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 839
47.5%
1 266
 
15.1%
2 216
 
12.2%
4 214
 
12.1%
3 121
 
6.8%
9 48
 
2.7%
6 17
 
1.0%
5 17
 
1.0%
7 15
 
0.8%
8 14
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2046
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 839
41.0%
- 279
 
13.6%
1 266
 
13.0%
2 216
 
10.6%
4 214
 
10.5%
3 121
 
5.9%
9 48
 
2.3%
6 17
 
0.8%
5 17
 
0.8%
7 15
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2046
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 839
41.0%
- 279
 
13.6%
1 266
 
13.0%
2 216
 
10.6%
4 214
 
10.5%
3 121
 
5.9%
9 48
 
2.3%
6 17
 
0.8%
5 17
 
0.8%
7 15
 
0.7%

인허가일자
Date

Distinct92
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum1990-12-14 00:00:00
Maximum2022-11-08 00:00:00
2024-05-11T00:22:42.935834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:22:43.382342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
3
62 
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 62
66.7%
1 31
33.3%

Length

2024-05-11T00:22:43.762489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:22:44.079220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 62
66.7%
1 31
33.3%

영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
폐업
62 
영업/정상
31 

Length

Max length5
Median length2
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 62
66.7%
영업/정상 31
33.3%

Length

2024-05-11T00:22:44.567521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:22:44.870279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 62
66.7%
영업/정상 31
33.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
2
62 
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 62
66.7%
1 31
33.3%

Length

2024-05-11T00:22:45.166824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:22:45.541234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 62
66.7%
1 31
33.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
폐업
62 
영업
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 62
66.7%
영업 31
33.3%

Length

2024-05-11T00:22:45.832481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:22:46.170914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 62
66.7%
영업 31
33.3%

폐업일자
Date

MISSING 

Distinct58
Distinct (%)93.5%
Missing31
Missing (%)33.3%
Memory size876.0 B
Minimum1999-05-29 00:00:00
Maximum2024-02-21 00:00:00
2024-05-11T00:22:46.580749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:22:47.060606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

전화번호
Text

MISSING 

Distinct74
Distinct (%)93.7%
Missing14
Missing (%)15.1%
Memory size876.0 B
2024-05-11T00:22:47.710827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.822785
Min length2

Characters and Unicode

Total characters855
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

Unique70 ?
Unique (%)88.6%

Sample

1st row02
2nd row0234266155
3rd row02 4400783
4th row02 4772001
5th row02 473 5501
ValueCountFrequency (%)
02 71
39.9%
428 5
 
2.8%
481 4
 
2.2%
426 4
 
2.2%
442 3
 
1.7%
472 3
 
1.7%
473 2
 
1.1%
488 2
 
1.1%
5651 2
 
1.1%
487 2
 
1.1%
Other values (76) 80
44.9%
2024-05-11T00:22:48.881780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 155
18.1%
146
17.1%
0 129
15.1%
4 102
11.9%
5 60
 
7.0%
3 54
 
6.3%
7 51
 
6.0%
8 51
 
6.0%
1 49
 
5.7%
6 43
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 709
82.9%
Space Separator 146
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 155
21.9%
0 129
18.2%
4 102
14.4%
5 60
 
8.5%
3 54
 
7.6%
7 51
 
7.2%
8 51
 
7.2%
1 49
 
6.9%
6 43
 
6.1%
9 15
 
2.1%
Space Separator
ValueCountFrequency (%)
146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 855
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 155
18.1%
146
17.1%
0 129
15.1%
4 102
11.9%
5 60
 
7.0%
3 54
 
6.3%
7 51
 
6.0%
8 51
 
6.0%
1 49
 
5.7%
6 43
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 155
18.1%
146
17.1%
0 129
15.1%
4 102
11.9%
5 60
 
7.0%
3 54
 
6.3%
7 51
 
6.0%
8 51
 
6.0%
1 49
 
5.7%
6 43
 
5.0%

소재지면적
Text

MISSING 

Distinct81
Distinct (%)91.0%
Missing4
Missing (%)4.3%
Memory size876.0 B
2024-05-11T00:22:49.742237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2696629
Min length3

Characters and Unicode

Total characters558
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

Unique75 ?
Unique (%)84.3%

Sample

1st row1,292.05
2nd row984.50
3rd row588.40
4th row561.00
5th row1,089.00
ValueCountFrequency (%)
495.00 3
 
3.4%
1,476.00 3
 
3.4%
561.00 2
 
2.2%
00 2
 
2.2%
541.20 2
 
2.2%
360.00 2
 
2.2%
516.55 1
 
1.1%
484.23 1
 
1.1%
678.01 1
 
1.1%
384.71 1
 
1.1%
Other values (71) 71
79.8%
2024-05-11T00:22:51.077954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 144
25.8%
. 89
15.9%
5 44
 
7.9%
3 43
 
7.7%
4 40
 
7.2%
6 39
 
7.0%
1 38
 
6.8%
8 31
 
5.6%
7 27
 
4.8%
9 26
 
4.7%
Other values (2) 37
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 457
81.9%
Other Punctuation 101
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144
31.5%
5 44
 
9.6%
3 43
 
9.4%
4 40
 
8.8%
6 39
 
8.5%
1 38
 
8.3%
8 31
 
6.8%
7 27
 
5.9%
9 26
 
5.7%
2 25
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 89
88.1%
, 12
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Common 558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144
25.8%
. 89
15.9%
5 44
 
7.9%
3 43
 
7.7%
4 40
 
7.2%
6 39
 
7.0%
1 38
 
6.8%
8 31
 
5.6%
7 27
 
4.8%
9 26
 
4.7%
Other values (2) 37
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144
25.8%
. 89
15.9%
5 44
 
7.9%
3 43
 
7.7%
4 40
 
7.2%
6 39
 
7.0%
1 38
 
6.8%
8 31
 
5.6%
7 27
 
4.8%
9 26
 
4.7%
Other values (2) 37
 
6.6%

소재지우편번호
Text

Distinct52
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-05-11T00:22:51.797594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1505376
Min length6

Characters and Unicode

Total characters572
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

Unique33 ?
Unique (%)35.5%

Sample

1st row134825
2nd row134-824
3rd row134830
4th row134873
5th row134819
ValueCountFrequency (%)
134830 8
 
8.6%
134890 7
 
7.5%
134873 5
 
5.4%
134819 4
 
4.3%
134871 4
 
4.3%
134856 3
 
3.2%
134859 3
 
3.2%
134807 3
 
3.2%
134805 3
 
3.2%
134886 2
 
2.2%
Other values (42) 51
54.8%
2024-05-11T00:22:53.054420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 115
20.1%
3 115
20.1%
4 104
18.2%
8 98
17.1%
0 40
 
7.0%
7 23
 
4.0%
5 21
 
3.7%
9 17
 
3.0%
6 14
 
2.4%
- 14
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
97.6%
Dash Punctuation 14
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 115
20.6%
3 115
20.6%
4 104
18.6%
8 98
17.6%
0 40
 
7.2%
7 23
 
4.1%
5 21
 
3.8%
9 17
 
3.0%
6 14
 
2.5%
2 11
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 115
20.1%
3 115
20.1%
4 104
18.2%
8 98
17.1%
0 40
 
7.0%
7 23
 
4.0%
5 21
 
3.7%
9 17
 
3.0%
6 14
 
2.4%
- 14
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 115
20.1%
3 115
20.1%
4 104
18.2%
8 98
17.1%
0 40
 
7.0%
7 23
 
4.0%
5 21
 
3.7%
9 17
 
3.0%
6 14
 
2.4%
- 14
 
2.4%

지번주소
Text

Distinct89
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-05-11T00:22:53.700660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length38
Mean length26.053763
Min length17

Characters and Unicode

Total characters2423
Distinct characters114
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

Unique85 ?
Unique (%)91.4%

Sample

1st row서울특별시 강동구 명일동 46-4
2nd row서울특별시 강동구 명일동 15 삼익상가 지하 22호
3rd row서울특별시 강동구 명일동 309-1 삼익그린상가지하1층
4th row서울특별시 강동구 천호동 421-4
5th row서울특별시 강동구 둔촌동 172-1
ValueCountFrequency (%)
서울특별시 93
19.5%
강동구 93
19.5%
암사동 16
 
3.4%
천호동 15
 
3.1%
명일동 15
 
3.1%
성내동 15
 
3.1%
고덕동 10
 
2.1%
둔촌동 9
 
1.9%
1층 9
 
1.9%
길동 8
 
1.7%
Other values (139) 194
40.7%
2024-05-11T00:22:54.932008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
447
18.4%
동 195
 
8.0%
1 125
 
5.2%
강 96
 
4.0%
시 95
 
3.9%
서 94
 
3.9%
울 94
 
3.9%
구 93
 
3.8%
별 93
 
3.8%
특 93
 
3.8%
Other values (104) 998
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1383
57.1%
Decimal Number 474
 
19.6%
Space Separator 447
 
18.4%
Dash Punctuation 70
 
2.9%
Other Punctuation 26
 
1.1%
Open Punctuation 9
 
0.4%
Close Punctuation 9
 
0.4%
Uppercase Letter 4
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 195
14.1%
강 96
 
6.9%
시 95
 
6.9%
서 94
 
6.8%
울 94
 
6.8%
구 93
 
6.7%
별 93
 
6.7%
특 93
 
6.7%
층 38
 
2.7%
지 31
 
2.2%
Other values (85) 461
33.3%
Decimal Number
ValueCountFrequency (%)
1 125
26.4%
4 71
15.0%
2 63
13.3%
0 45
 
9.5%
3 33
 
7.0%
5 32
 
6.8%
6 30
 
6.3%
8 29
 
6.1%
9 27
 
5.7%
7 19
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 25
96.2%
. 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%
Space Separator
ValueCountFrequency (%)
447
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1383
57.1%
Common 1036
42.8%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 195
14.1%
강 96
 
6.9%
시 95
 
6.9%
서 94
 
6.8%
울 94
 
6.8%
구 93
 
6.7%
별 93
 
6.7%
특 93
 
6.7%
층 38
 
2.7%
지 31
 
2.2%
Other values (85) 461
33.3%
Common
ValueCountFrequency (%)
447
43.1%
1 125
 
12.1%
4 71
 
6.9%
- 70
 
6.8%
2 63
 
6.1%
0 45
 
4.3%
3 33
 
3.2%
5 32
 
3.1%
6 30
 
2.9%
8 29
 
2.8%
Other values (7) 91
 
8.8%
Latin
ValueCountFrequency (%)
B 3
75.0%
A 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1383
57.1%
ASCII 1040
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
447
43.0%
1 125
 
12.0%
4 71
 
6.8%
- 70
 
6.7%
2 63
 
6.1%
0 45
 
4.3%
3 33
 
3.2%
5 32
 
3.1%
6 30
 
2.9%
8 29
 
2.8%
Other values (9) 95
 
9.1%
Hangul
ValueCountFrequency (%)
동 195
14.1%
강 96
 
6.9%
시 95
 
6.9%
서 94
 
6.8%
울 94
 
6.8%
구 93
 
6.7%
별 93
 
6.7%
특 93
 
6.7%
층 38
 
2.7%
지 31
 
2.2%
Other values (85) 461
33.3%

도로명주소
Text

MISSING 

Distinct66
Distinct (%)98.5%
Missing26
Missing (%)28.0%
Memory size876.0 B
2024-05-11T00:22:55.733124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length44
Mean length33.716418
Min length22

Characters and Unicode

Total characters2259
Distinct characters122
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

Unique65 ?
Unique (%)97.0%

Sample

1st row서울특별시 강동구 명일로 375 (명일동, 삼익상가 지하22호)
2nd row서울특별시 강동구 명일로 74 (둔촌동)
3rd row서울특별시 강동구 천호대로 1005 (천호동)
4th row서울특별시 강동구 진황도로31길 26 (천호동)
5th row서울특별시 강동구 양재대로 1355 (성내동)
ValueCountFrequency (%)
서울특별시 67
 
15.8%
강동구 67
 
15.8%
1층 10
 
2.4%
지하1층 10
 
2.4%
명일동 10
 
2.4%
양재대로 9
 
2.1%
성내동 9
 
2.1%
암사동 9
 
2.1%
천호동 8
 
1.9%
고덕로 8
 
1.9%
Other values (150) 216
51.1%
2024-05-11T00:22:57.255908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
356
 
15.8%
동 145
 
6.4%
1 119
 
5.3%
구 75
 
3.3%
) 74
 
3.3%
( 74
 
3.3%
강 70
 
3.1%
, 70
 
3.1%
로 68
 
3.0%
시 68
 
3.0%
Other values (112) 1140
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1309
57.9%
Decimal Number 358
 
15.8%
Space Separator 356
 
15.8%
Close Punctuation 74
 
3.3%
Open Punctuation 74
 
3.3%
Other Punctuation 71
 
3.1%
Uppercase Letter 7
 
0.3%
Dash Punctuation 6
 
0.3%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 145
 
11.1%
구 75
 
5.7%
강 70
 
5.3%
로 68
 
5.2%
시 68
 
5.2%
울 67
 
5.1%
서 67
 
5.1%
특 67
 
5.1%
별 67
 
5.1%
층 40
 
3.1%
Other values (93) 575
43.9%
Decimal Number
ValueCountFrequency (%)
1 119
33.2%
2 41
 
11.5%
0 35
 
9.8%
6 31
 
8.7%
5 27
 
7.5%
3 27
 
7.5%
9 23
 
6.4%
7 23
 
6.4%
8 18
 
5.0%
4 14
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 70
98.6%
. 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
B 6
85.7%
A 1
 
14.3%
Space Separator
ValueCountFrequency (%)
356
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1309
57.9%
Common 943
41.7%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 145
 
11.1%
구 75
 
5.7%
강 70
 
5.3%
로 68
 
5.2%
시 68
 
5.2%
울 67
 
5.1%
서 67
 
5.1%
특 67
 
5.1%
별 67
 
5.1%
층 40
 
3.1%
Other values (93) 575
43.9%
Common
ValueCountFrequency (%)
356
37.8%
1 119
 
12.6%
) 74
 
7.8%
( 74
 
7.8%
, 70
 
7.4%
2 41
 
4.3%
0 35
 
3.7%
6 31
 
3.3%
5 27
 
2.9%
3 27
 
2.9%
Other values (7) 89
 
9.4%
Latin
ValueCountFrequency (%)
B 6
85.7%
A 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1309
57.9%
ASCII 950
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
356
37.5%
1 119
 
12.5%
) 74
 
7.8%
( 74
 
7.8%
, 70
 
7.4%
2 41
 
4.3%
0 35
 
3.7%
6 31
 
3.3%
5 27
 
2.8%
3 27
 
2.8%
Other values (9) 96
 
10.1%
Hangul
ValueCountFrequency (%)
동 145
 
11.1%
구 75
 
5.7%
강 70
 
5.3%
로 68
 
5.2%
시 68
 
5.2%
울 67
 
5.1%
서 67
 
5.1%
특 67
 
5.1%
별 67
 
5.1%
층 40
 
3.1%
Other values (93) 575
43.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)71.2%
Missing27
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean5310.7879
Minimum5211
Maximum5415
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T00:22:57.726763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5211
5-th percentile5225.25
Q15261
median5298
Q35363
95-th percentile5410.5
Maximum5415
Range204
Interquartile range (IQR)102

Descriptive statistics

Standard deviation64.568751
Coefficient of variation (CV)0.012158036
Kurtosis-1.3145409
Mean5310.7879
Median Absolute Deviation (MAD)52.5
Skewness0.24336451
Sum350512
Variance4169.1235
MonotonicityNot monotonic
2024-05-11T00:22:58.196768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
5404 6
 
6.5%
5266 4
 
4.3%
5328 3
 
3.2%
5265 2
 
2.2%
5391 2
 
2.2%
5211 2
 
2.2%
5412 2
 
2.2%
5232 2
 
2.2%
5251 2
 
2.2%
5296 2
 
2.2%
Other values (37) 39
41.9%
(Missing) 27
29.0%
ValueCountFrequency (%)
5211 2
2.2%
5222 1
1.1%
5224 1
1.1%
5229 1
1.1%
5232 2
2.2%
5233 1
1.1%
5236 1
1.1%
5237 1
1.1%
5239 1
1.1%
5240 1
1.1%
ValueCountFrequency (%)
5415 1
 
1.1%
5412 2
 
2.2%
5411 1
 
1.1%
5409 1
 
1.1%
5404 6
6.5%
5398 1
 
1.1%
5391 2
 
2.2%
5390 1
 
1.1%
5370 1
 
1.1%
5364 1
 
1.1%

사업장명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-05-11T00:22:59.084270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length8.3548387
Min length3

Characters and Unicode

Total characters777
Distinct characters140
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st row주)해태유통해태마트
2nd row(주)이마트에브리데이 명일동점
3rd row아트유통
4th row(주)이천일아울렛천호점
5th row(주)농협유통 둔촌점
ValueCountFrequency (%)
주)이마트에브리데이 4
 
3.3%
둔촌점 2
 
1.7%
프레시 2
 
1.7%
명일점 2
 
1.7%
지에스 2
 
1.7%
주식회사 2
 
1.7%
더 2
 
1.7%
고덕점 2
 
1.7%
주)지에스리테일 2
 
1.7%
주)대농할인마트 1
 
0.8%
Other values (100) 100
82.6%
2024-05-11T00:23:00.307064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 68
 
8.8%
트 67
 
8.6%
주 35
 
4.5%
점 35
 
4.5%
) 34
 
4.4%
( 33
 
4.2%
28
 
3.6%
스 20
 
2.6%
이 17
 
2.2%
에 16
 
2.1%
Other values (130) 424
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 678
87.3%
Close Punctuation 34
 
4.4%
Open Punctuation 33
 
4.2%
Space Separator 28
 
3.6%
Uppercase Letter 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 68
 
10.0%
트 67
 
9.9%
주 35
 
5.2%
점 35
 
5.2%
스 20
 
2.9%
이 17
 
2.5%
에 16
 
2.4%
동 15
 
2.2%
일 13
 
1.9%
데 13
 
1.9%
Other values (124) 379
55.9%
Uppercase Letter
ValueCountFrequency (%)
G 2
66.7%
S 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 678
87.3%
Common 96
 
12.4%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 68
 
10.0%
트 67
 
9.9%
주 35
 
5.2%
점 35
 
5.2%
스 20
 
2.9%
이 17
 
2.5%
에 16
 
2.4%
동 15
 
2.2%
일 13
 
1.9%
데 13
 
1.9%
Other values (124) 379
55.9%
Common
ValueCountFrequency (%)
) 34
35.4%
( 33
34.4%
28
29.2%
- 1
 
1.0%
Latin
ValueCountFrequency (%)
G 2
66.7%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 678
87.3%
ASCII 99
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 68
 
10.0%
트 67
 
9.9%
주 35
 
5.2%
점 35
 
5.2%
스 20
 
2.9%
이 17
 
2.5%
에 16
 
2.4%
동 15
 
2.2%
일 13
 
1.9%
데 13
 
1.9%
Other values (124) 379
55.9%
ASCII
ValueCountFrequency (%)
) 34
34.3%
( 33
33.3%
28
28.3%
G 2
 
2.0%
S 1
 
1.0%
- 1
 
1.0%

최종수정일자
Date

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum1999-05-29 00:00:00
Maximum2024-05-03 17:45:00
2024-05-11T00:23:00.801846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:23:01.629306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
I
57 
U
36 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 57
61.3%
U 36
38.7%

Length

2024-05-11T00:23:02.184156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:02.489429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 57
61.3%
u 36
38.7%

데이터갱신일자
Categorical

Distinct36
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Memory size876.0 B
2018-08-31 23:59:59.0
51 
2021-12-09 00:03:00.0
 
3
2021-10-30 23:05:00.0
 
2
2023-12-05 00:05:00.0
 
2
2023-12-03 23:04:00.0
 
2
Other values (31)
33 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique29 ?
Unique (%)31.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2023-12-05 00:05:00.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 51
54.8%
2021-12-09 00:03:00.0 3
 
3.2%
2021-10-30 23:05:00.0 2
 
2.2%
2023-12-05 00:05:00.0 2
 
2.2%
2023-12-03 23:04:00.0 2
 
2.2%
2022-12-03 22:00:00.0 2
 
2.2%
2021-10-30 22:02:00.0 2
 
2.2%
2021-03-18 02:40:00.0 1
 
1.1%
2022-12-05 22:05:00.0 1
 
1.1%
2023-12-01 22:03:00.0 1
 
1.1%
Other values (26) 26
28.0%

Length

2024-05-11T00:23:03.067127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 51
27.4%
23:59:59.0 51
27.4%
02:40:00.0 13
 
7.0%
00:03:00.0 5
 
2.7%
2021-10-30 4
 
2.2%
2021-12-09 3
 
1.6%
23:05:00.0 3
 
1.6%
2023-12-03 3
 
1.6%
2023-12-01 3
 
1.6%
2021-09-29 2
 
1.1%
Other values (41) 48
25.8%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
기타식품판매업
93 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 93
100.0%

Length

2024-05-11T00:23:03.541166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:04.074448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 93
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)67.4%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean212374.56
Minimum210566.88
Maximum215426.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T00:23:04.464403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile211016.88
Q1211679.89
median211979.52
Q3212886.35
95-th percentile214862.49
Maximum215426.03
Range4859.1525
Interquartile range (IQR)1206.4569

Descriptive statistics

Standard deviation1162.5012
Coefficient of variation (CV)0.0054738251
Kurtosis0.25853104
Mean212374.56
Median Absolute Deviation (MAD)743.4335
Skewness0.88496198
Sum19538460
Variance1351409.1
MonotonicityNot monotonic
2024-05-11T00:23:05.269761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211838.35431041 6
 
6.5%
211979.520569314 4
 
4.3%
214293.085340515 3
 
3.2%
211820.878022259 3
 
3.2%
213700.877714971 2
 
2.2%
210694.989265395 2
 
2.2%
212334.69890736 2
 
2.2%
211047.878697259 2
 
2.2%
211066.384353658 2
 
2.2%
211055.486155787 2
 
2.2%
Other values (52) 64
68.8%
ValueCountFrequency (%)
210566.875626134 1
1.1%
210694.989265395 2
2.2%
210929.919693661 1
1.1%
211005.821291238 1
1.1%
211025.924972294 2
2.2%
211047.878697259 2
2.2%
211055.486155787 2
2.2%
211066.384353658 2
2.2%
211173.675641926 1
1.1%
211174.771171465 2
2.2%
ValueCountFrequency (%)
215426.028109 1
 
1.1%
215303.913311463 1
 
1.1%
215254.0 1
 
1.1%
215008.531272849 1
 
1.1%
214864.638202048 1
 
1.1%
214860.734709632 1
 
1.1%
214761.228719522 1
 
1.1%
214293.085340515 3
3.2%
213700.877714971 2
2.2%
213646.900696177 2
2.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)67.4%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean449087.38
Minimum446862.23
Maximum452189.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T00:23:05.858024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446862.23
5-th percentile447077.32
Q1447983.54
median449259.36
Q3450115.94
95-th percentile450750.55
Maximum452189.76
Range5327.5209
Interquartile range (IQR)2132.3966

Descriptive statistics

Standard deviation1278.121
Coefficient of variation (CV)0.0028460407
Kurtosis-0.87138038
Mean449087.38
Median Absolute Deviation (MAD)985.84311
Skewness-0.052772899
Sum41316039
Variance1633593.2
MonotonicityNot monotonic
2024-05-11T00:23:06.382098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447195.676766748 6
 
6.5%
446932.653730601 4
 
4.3%
450636.626425939 3
 
3.2%
449831.785568227 3
 
3.2%
450278.100930843 2
 
2.2%
447815.986328694 2
 
2.2%
447728.865137096 2
 
2.2%
450021.504957301 2
 
2.2%
447620.18848462 2
 
2.2%
448786.697371515 2
 
2.2%
Other values (52) 64
68.8%
ValueCountFrequency (%)
446862.234226426 1
 
1.1%
446932.653730601 4
4.3%
447195.676766748 6
6.5%
447248.126116539 1
 
1.1%
447402.629676369 1
 
1.1%
447453.686764129 1
 
1.1%
447620.18848462 2
 
2.2%
447690.40418764 2
 
2.2%
447728.865137096 2
 
2.2%
447815.986328694 2
 
2.2%
ValueCountFrequency (%)
452189.755118282 1
 
1.1%
451728.460795 1
 
1.1%
451457.0 1
 
1.1%
450751.524331915 1
 
1.1%
450750.547533484 2
2.2%
450684.210584771 1
 
1.1%
450636.626425939 3
3.2%
450566.106650078 1
 
1.1%
450493.347291827 1
 
1.1%
450346.790651613 1
 
1.1%

위생업태명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
기타식품판매업
68 
<NA>
25 

Length

Max length7
Median length7
Mean length6.1935484
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 68
73.1%
<NA> 25
 
26.9%

Length

2024-05-11T00:23:06.924969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:07.260732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 68
73.1%
na 25
 
26.9%

남성종사자수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
82 
0
11 

Length

Max length4
Median length4
Mean length3.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 82
88.2%
0 11
 
11.8%

Length

2024-05-11T00:23:07.685577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:08.018852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
88.2%
0 11
 
11.8%

여성종사자수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
82 
0
11 

Length

Max length4
Median length4
Mean length3.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 82
88.2%
0 11
 
11.8%

Length

2024-05-11T00:23:08.419945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:08.818674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
88.2%
0 11
 
11.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
84 
아파트지역
 
4
기타
 
3
유흥업소밀집지역
 
1
주택가주변
 
1

Length

Max length8
Median length4
Mean length4.0322581
Min length2

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
90.3%
아파트지역 4
 
4.3%
기타 3
 
3.2%
유흥업소밀집지역 1
 
1.1%
주택가주변 1
 
1.1%

Length

2024-05-11T00:23:09.176079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:09.508792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
90.3%
아파트지역 4
 
4.3%
기타 3
 
3.2%
유흥업소밀집지역 1
 
1.1%
주택가주변 1
 
1.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
84 
자율
 
5
기타
 
3
을
 
1

Length

Max length4
Median length4
Mean length3.7956989
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 84
90.3%
자율 5
 
5.4%
기타 3
 
3.2%
을 1
 
1.1%

Length

2024-05-11T00:23:10.054415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:10.475366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 84
90.3%
자율 5
 
5.4%
기타 3
 
3.2%
을 1
 
1.1%

급수시설구분명
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
69 
상수도전용
24 

Length

Max length5
Median length4
Mean length4.2580645
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 69
74.2%
상수도전용 24
 
25.8%

Length

2024-05-11T00:23:11.271970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:11.756615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 69
74.2%
상수도전용 24
 
25.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
91 
0
 
2

Length

Max length4
Median length4
Mean length3.9354839
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> 91
97.8%
0 2
 
2.2%

Length

2024-05-11T00:23:12.108615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:12.413342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 91
97.8%
0 2
 
2.2%

본사종업원수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
51 
0
42 

Length

Max length4
Median length4
Mean length2.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
54.8%
0 42
45.2%

Length

2024-05-11T00:23:12.748611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:13.114031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
54.8%
0 42
45.2%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
51 
0
42 

Length

Max length4
Median length4
Mean length2.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
54.8%
0 42
45.2%

Length

2024-05-11T00:23:13.520088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:13.840016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
54.8%
0 42
45.2%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
51 
0
42 

Length

Max length4
Median length4
Mean length2.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
54.8%
0 42
45.2%

Length

2024-05-11T00:23:14.177644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:14.408703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
54.8%
0 42
45.2%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
51 
0
42 

Length

Max length4
Median length4
Mean length2.6451613
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
54.8%
0 42
45.2%

Length

2024-05-11T00:23:14.622304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:14.833622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
54.8%
0 42
45.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
42 
임대
31 
자가
20 

Length

Max length4
Median length2
Mean length2.9032258
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
45.2%
임대 31
33.3%
자가 20
21.5%

Length

2024-05-11T00:23:15.176062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:15.492203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
45.2%
임대 31
33.3%
자가 20
21.5%

보증액
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
76 
0
17 

Length

Max length4
Median length4
Mean length3.4516129
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> 76
81.7%
0 17
 
18.3%

Length

2024-05-11T00:23:15.780774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:16.043838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
81.7%
0 17
 
18.3%

월세액
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
76 
0
17 

Length

Max length4
Median length4
Mean length3.4516129
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> 76
81.7%
0 17
 
18.3%

Length

2024-05-11T00:23:16.406744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:23:16.730676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
81.7%
0 17
 
18.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.5%
Missing25
Missing (%)26.9%
Memory size318.0 B
False
68 
(Missing)
25 
ValueCountFrequency (%)
False 68
73.1%
(Missing) 25
 
26.9%
2024-05-11T00:23:16.978104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)10.3%
Missing25
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean56.827794
Minimum0
Maximum1476
Zeros62
Zeros (%)66.7%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-05-11T00:23:17.257024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile442.5
Maximum1476
Range1476
Interquartile range (IQR)0

Descriptive statistics

Standard deviation217.9643
Coefficient of variation (CV)3.8355227
Kurtosis27.993155
Mean56.827794
Median Absolute Deviation (MAD)0
Skewness4.9374481
Sum3864.29
Variance47508.434
MonotonicityNot monotonic
2024-05-11T00:23:17.622116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 62
66.7%
345.0 1
 
1.1%
319.7 1
 
1.1%
653.75 1
 
1.1%
574.84 1
 
1.1%
495.0 1
 
1.1%
1476.0 1
 
1.1%
(Missing) 25
26.9%
ValueCountFrequency (%)
0.0 62
66.7%
319.7 1
 
1.1%
345.0 1
 
1.1%
495.0 1
 
1.1%
574.84 1
 
1.1%
653.75 1
 
1.1%
1476.0 1
 
1.1%
ValueCountFrequency (%)
1476.0 1
 
1.1%
653.75 1
 
1.1%
574.84 1
 
1.1%
495.0 1
 
1.1%
345.0 1
 
1.1%
319.7 1
 
1.1%
0.0 62
66.7%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-114-1990-0046219901214<NA>3폐업2폐업20020228<NA><NA><NA>021,292.05134825서울특별시 강동구 명일동 46-4<NA><NA>주)해태유통해태마트2002-02-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업213700.877715450278.100931기타식품판매업00아파트지역을<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132400003240000-114-1996-004701996-06-17<NA>1영업/정상1영업<NA><NA><NA><NA>0234266155984.50134-824서울특별시 강동구 명일동 15 삼익상가 지하 22호서울특별시 강동구 명일로 375 (명일동, 삼익상가 지하22호)5267(주)이마트에브리데이 명일동점2024-05-03 17:33:35U2023-12-05 00:05:00.0기타식품판매업213048.69218450124.105735<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
232400003240000-114-1996-0047119960617<NA>3폐업2폐업20061023<NA><NA><NA>02 4400783588.40134830서울특별시 강동구 명일동 309-1 삼익그린상가지하1층<NA><NA>아트유통2005-11-09 00:00:00I2018-08-31 23:59:59.0기타식품판매업212771.950892450113.21481기타식품판매업00아파트지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332400003240000-114-1996-0047219960704<NA>3폐업2폐업20041129<NA><NA><NA>02 4772001561.00134873서울특별시 강동구 천호동 421-4<NA><NA>(주)이천일아울렛천호점2004-11-29 00:00:00I2018-08-31 23:59:59.0기타식품판매업211174.771171448678.909948기타식품판매업00유흥업소밀집지역기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
432400003240000-114-1996-0047319960923<NA>3폐업2폐업20171106<NA><NA><NA>02 473 55011,089.00134819서울특별시 강동구 둔촌동 172-1서울특별시 강동구 명일로 74 (둔촌동)5412(주)농협유통 둔촌점2017-11-06 17:34:26I2018-08-31 23:59:59.0기타식품판매업211979.520569446932.653731기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
532400003240000-114-1997-004651997-08-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2228.00134-874서울특별시 강동구 천호동 455-8서울특별시 강동구 천호대로 1005 (천호동)5328현대백화점천호점2024-02-29 15:12:14U2023-12-03 00:03:00.0기타식품판매업210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632400003240000-114-1998-0049519980803<NA>3폐업2폐업20010525<NA><NA><NA>02 4726353.00134849서울특별시 강동구 성내동 513-0<NA><NA>농심가슈퍼마트2002-01-15 00:00:00I2018-08-31 23:59:59.0기타식품판매업211454.628343447690.404188기타식품판매업00주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732400003240000-114-1998-0049619980501<NA>3폐업2폐업20050325<NA><NA><NA>02 4887244<NA>134871서울특별시 강동구 천호동 565<NA><NA>(주)이씀2002-11-27 00:00:00I2018-08-31 23:59:59.0기타식품판매업211750.896224448202.632547기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832400003240000-114-1999-0052019990331<NA>3폐업2폐업19990529<NA><NA><NA>02.00134871서울특별시 강동구 천호동 564-0<NA><NA>함지유통1999-05-29 00:00:00I2018-08-31 23:59:59.0기타식품판매업211791.891201448500.557185기타식품판매업00아파트지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-114-1999-0054219990513<NA>3폐업2폐업20000518<NA><NA><NA>02633.00134871서울특별시 강동구 천호동 410-100<NA><NA>천호마트2000-05-18 00:00:00I2018-08-31 23:59:59.0기타식품판매업211279.030242448548.819717기타식품판매업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
8332400003240000-114-2019-0000420191203<NA>1영업/정상1영업<NA><NA><NA><NA>02 20062353565.04134807서울특별시 강동구 고덕동 217 고덕그라시움아파트(상가1동)108~119,128호서울특별시 강동구 고덕로 353, 고덕그라시움아파트(상가1동)108~119,128호 (고덕동)5224지에스 더 프레시 고덕그라시움점2019-12-03 11:34:41I2019-12-05 00:23:26.0기타식품판매업214293.085341450636.626426기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
8432400003240000-114-2020-0000120200421<NA>3폐업2폐업20220901<NA><NA><NA><NA>446.65134801서울특별시 강동구 고덕동 191-5 백두쇼핑센타서울특별시 강동구 고덕로83길 28, 백두쇼핑센타 지하1층 (고덕동)5222(주)한강식자재마트2022-09-01 10:39:44U2021-12-09 00:03:00.0기타식품판매업214864.638202450684.210585<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8532400003240000-114-2020-0000220200603<NA>1영업/정상1영업<NA><NA><NA><NA>02 487 4080805.00134873서울특별시 강동구 천호동 421-4 행복타워빌딩서울특별시 강동구 구천면로 202, 행복타워빌딩 1층 (천호동)5329강동농협하나로마트 로데오점2020-06-03 16:11:58I2020-06-05 00:23:19.0기타식품판매업211174.771171448678.909948기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
8632400003240000-114-2020-0000320200617<NA>3폐업2폐업20220816<NA><NA><NA>02 481 5200800.00134830서울특별시 강동구 명일동 309-4 삼익상가서울특별시 강동구 양재대로 1666, 삼익상가 지하1층 (명일동)5266드림홈마트2022-08-16 10:51:25U2021-12-07 23:08:00.0기타식품판매업212727.784179450245.203248<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8732400003240000-114-2021-000012021-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>819.03134-100서울특별시 강동구 강일동 76-2 아이메디컬서울특별시 강동구 아리수로93나길 38, 아이메디컬 B101호 (강일동)5415(주)이마트에브리데이 고덕강일점2024-05-03 17:45:00U2023-12-05 00:05:00.0기타식품판매업215303.913311452189.755118<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
8832400003240000-114-2021-0000220210225<NA>1영업/정상1영업<NA><NA><NA><NA>02 34264561541.20134836서울특별시 강동구 상일동 124서울특별시 강동구 상일로 55, 고덕자이아파트상가 1동 B1층 119호 (상일동)5275지에스 더 프레시 강동고덕점2021-02-25 16:02:41I2021-02-27 00:23:00.0기타식품판매업215008.531273450016.148655기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
8932400003240000-114-2021-0000320210927<NA>1영업/정상1영업<NA><NA><NA><NA><NA>680.00134805서울특별시 강동구 고덕동 499 고덕아이파크서울특별시 강동구 동남로79길 26, 비1층 101~109호 (고덕동, 고덕아이파크)5232킹마트2021-09-27 15:42:50I2021-09-29 00:22:48.0기타식품판매업213646.900696450750.547533기타식품판매업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
9032400003240000-114-2021-000042021-12-06<NA>1영업/정상1영업<NA><NA><NA><NA>02 34275125695.00134-876서울특별시 강동구 암사동 599서울특별시 강동구 고덕로 19, 1층 (암사동)5239남한강 식자재마트2024-01-05 13:52:42U2023-12-01 00:07:00.0기타식품판매업211179.768625450318.036941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9132400003240000-114-2022-0000120221019<NA>1영업/정상1영업<NA><NA><NA><NA>02 481 5200760.33134830서울특별시 강동구 명일동 309-4 삼익상가서울특별시 강동구 양재대로 1666, 삼익상가 지하1층 (명일동)5266마켓프레고2022-10-19 11:34:17I2021-10-30 22:02:00.0기타식품판매업212727.784179450245.203248<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9232400003240000-114-2022-0000220221108<NA>1영업/정상1영업<NA><NA><NA><NA>02 21555168961.32134811서울특별시 강동구 길동 348-6서울특별시 강동구 양재대로 1504, B동 (길동)5343주식회사 오아시스 길동역점2022-11-08 15:55:08I2021-10-31 23:00:00.0기타식품판매업212402.422646448634.438798<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>