Overview

Dataset statistics

Number of variables44
Number of observations116
Missing cells992
Missing cells (%)19.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.6 KiB
Average record size in memory376.1 B

Variable types

Categorical22
Text7
DateTime4
Unsupported7
Numeric3
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
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-18312/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (63.6%)Imbalance
영업장주변구분명 is highly imbalanced (76.7%)Imbalance
등급구분명 is highly imbalanced (77.1%)Imbalance
총인원 is highly imbalanced (63.8%)Imbalance
보증액 is highly imbalanced (63.8%)Imbalance
월세액 is highly imbalanced (63.8%)Imbalance
시설총규모 is highly imbalanced (58.7%)Imbalance
인허가취소일자 has 116 (100.0%) missing valuesMissing
폐업일자 has 51 (44.0%) missing valuesMissing
휴업시작일자 has 116 (100.0%) missing valuesMissing
휴업종료일자 has 116 (100.0%) missing valuesMissing
재개업일자 has 116 (100.0%) missing valuesMissing
전화번호 has 15 (12.9%) missing valuesMissing
소재지면적 has 2 (1.7%) missing valuesMissing
도로명주소 has 41 (35.3%) missing valuesMissing
도로명우편번호 has 41 (35.3%) missing valuesMissing
다중이용업소여부 has 28 (24.1%) missing valuesMissing
전통업소지정번호 has 116 (100.0%) missing valuesMissing
전통업소주된음식 has 116 (100.0%) missing valuesMissing
홈페이지 has 116 (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

Reproduction

Analysis started2024-04-06 09:58:06.705603
Analysis finished2024-04-06 09:58:08.024459
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
3100000
116 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 116
100.0%

Length

2024-04-06T18:58:08.153970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:08.299593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 116
100.0%

관리번호
Text

UNIQUE 

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T18:58:08.560405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2552
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

Unique116 ?
Unique (%)100.0%

Sample

1st row3100000-114-1990-00001
2nd row3100000-114-1991-00275
3rd row3100000-114-1992-00001
4th row3100000-114-1996-00184
5th row3100000-114-1996-00185
ValueCountFrequency (%)
3100000-114-1990-00001 1
 
0.9%
3100000-114-2008-00007 1
 
0.9%
3100000-114-2010-00004 1
 
0.9%
3100000-114-2010-00003 1
 
0.9%
3100000-114-2010-00002 1
 
0.9%
3100000-114-2010-00001 1
 
0.9%
3100000-114-2009-00008 1
 
0.9%
3100000-114-2009-00007 1
 
0.9%
3100000-114-2009-00006 1
 
0.9%
3100000-114-2009-00005 1
 
0.9%
Other values (106) 106
91.4%
2024-04-06T18:58:09.115906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1135
44.5%
1 442
 
17.3%
- 348
 
13.6%
2 163
 
6.4%
3 149
 
5.8%
4 140
 
5.5%
9 82
 
3.2%
6 32
 
1.3%
5 23
 
0.9%
8 22
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2204
86.4%
Dash Punctuation 348
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1135
51.5%
1 442
 
20.1%
2 163
 
7.4%
3 149
 
6.8%
4 140
 
6.4%
9 82
 
3.7%
6 32
 
1.5%
5 23
 
1.0%
8 22
 
1.0%
7 16
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 348
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1135
44.5%
1 442
 
17.3%
- 348
 
13.6%
2 163
 
6.4%
3 149
 
5.8%
4 140
 
5.5%
9 82
 
3.2%
6 32
 
1.3%
5 23
 
0.9%
8 22
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1135
44.5%
1 442
 
17.3%
- 348
 
13.6%
2 163
 
6.4%
3 149
 
5.8%
4 140
 
5.5%
9 82
 
3.2%
6 32
 
1.3%
5 23
 
0.9%
8 22
 
0.9%
Distinct109
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum1990-06-30 00:00:00
Maximum2023-04-21 00:00:00
2024-04-06T18:58:09.380678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:09.649073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
3
65 
1
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 65
56.0%
1 51
44.0%

Length

2024-04-06T18:58:09.894685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:10.068014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 65
56.0%
1 51
44.0%

영업상태명
Categorical

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
폐업
65 
영업/정상
51 

Length

Max length5
Median length2
Mean length3.3189655
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 65
56.0%
영업/정상 51
44.0%

Length

2024-04-06T18:58:10.278581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:10.433993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 65
56.0%
영업/정상 51
44.0%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2
65 
1
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 65
56.0%
1 51
44.0%

Length

2024-04-06T18:58:10.586677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:10.742986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 65
56.0%
1 51
44.0%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
폐업
65 
영업
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 65
56.0%
영업 51
44.0%

Length

2024-04-06T18:58:10.896550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:11.055798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 65
56.0%
영업 51
44.0%

폐업일자
Date

MISSING 

Distinct63
Distinct (%)96.9%
Missing51
Missing (%)44.0%
Memory size1.0 KiB
Minimum1998-07-15 00:00:00
Maximum2023-12-18 00:00:00
2024-04-06T18:58:11.237965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:11.478898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

전화번호
Text

MISSING 

Distinct95
Distinct (%)94.1%
Missing15
Missing (%)12.9%
Memory size1.0 KiB
2024-04-06T18:58:11.912482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.50495
Min length7

Characters and Unicode

Total characters1061
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

Unique89 ?
Unique (%)88.1%

Sample

1st row02 9859000
2nd row02 9734764
3rd row02 950 2405
4th row02 9512032
5th row02 9393114
ValueCountFrequency (%)
02 88
40.6%
930 4
 
1.8%
931 3
 
1.4%
950 2
 
0.9%
938 2
 
0.9%
976 2
 
0.9%
974 2
 
0.9%
9373333 2
 
0.9%
933 2
 
0.9%
9518600 2
 
0.9%
Other values (104) 108
49.8%
2024-04-06T18:58:12.603956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 177
16.7%
2 160
15.1%
144
13.6%
9 133
12.5%
3 117
11.0%
1 71
6.7%
7 63
 
5.9%
4 59
 
5.6%
5 54
 
5.1%
8 51
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 917
86.4%
Space Separator 144
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 177
19.3%
2 160
17.4%
9 133
14.5%
3 117
12.8%
1 71
7.7%
7 63
 
6.9%
4 59
 
6.4%
5 54
 
5.9%
8 51
 
5.6%
6 32
 
3.5%
Space Separator
ValueCountFrequency (%)
144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1061
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 177
16.7%
2 160
15.1%
144
13.6%
9 133
12.5%
3 117
11.0%
1 71
6.7%
7 63
 
5.9%
4 59
 
5.6%
5 54
 
5.1%
8 51
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1061
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 177
16.7%
2 160
15.1%
144
13.6%
9 133
12.5%
3 117
11.0%
1 71
6.7%
7 63
 
5.9%
4 59
 
5.6%
5 54
 
5.1%
8 51
 
4.8%

소재지면적
Text

MISSING 

Distinct106
Distinct (%)93.0%
Missing2
Missing (%)1.7%
Memory size1.0 KiB
2024-04-06T18:58:13.119883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1842105
Min length3

Characters and Unicode

Total characters705
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

Unique100 ?
Unique (%)87.7%

Sample

1st row2336.27
2nd row1,280.56
3rd row5,786.25
4th row.00
5th row.00
ValueCountFrequency (%)
00 3
 
2.6%
460.00 3
 
2.6%
425.02 2
 
1.8%
430.00 2
 
1.8%
300.00 2
 
1.8%
726.96 2
 
1.8%
315.00 1
 
0.9%
2336.27 1
 
0.9%
786.46 1
 
0.9%
739.83 1
 
0.9%
Other values (96) 96
84.2%
2024-04-06T18:58:13.840416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 125
17.7%
. 114
16.2%
3 62
8.8%
4 61
8.7%
6 56
7.9%
5 53
7.5%
2 50
 
7.1%
8 50
 
7.1%
7 42
 
6.0%
9 41
 
5.8%
Other values (2) 51
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 578
82.0%
Other Punctuation 127
 
18.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 125
21.6%
3 62
10.7%
4 61
10.6%
6 56
9.7%
5 53
9.2%
2 50
 
8.7%
8 50
 
8.7%
7 42
 
7.3%
9 41
 
7.1%
1 38
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 114
89.8%
, 13
 
10.2%

Most occurring scripts

ValueCountFrequency (%)
Common 705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 125
17.7%
. 114
16.2%
3 62
8.8%
4 61
8.7%
6 56
7.9%
5 53
7.5%
2 50
 
7.1%
8 50
 
7.1%
7 42
 
6.0%
9 41
 
5.8%
Other values (2) 51
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 125
17.7%
. 114
16.2%
3 62
8.8%
4 61
8.7%
6 56
7.9%
5 53
7.5%
2 50
 
7.1%
8 50
 
7.1%
7 42
 
6.0%
9 41
 
5.8%
Other values (2) 51
7.2%
Distinct57
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T18:58:14.211642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1293103
Min length6

Characters and Unicode

Total characters711
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

Unique35 ?
Unique (%)30.2%

Sample

1st row139-230
2nd row139863
3rd row139708
4th row139859
5th row139861
ValueCountFrequency (%)
139816 10
 
8.6%
139837 8
 
6.9%
139865 5
 
4.3%
139800 5
 
4.3%
139860 5
 
4.3%
139810 4
 
3.4%
139859 4
 
3.4%
139861 4
 
3.4%
139812 3
 
2.6%
139863 3
 
2.6%
Other values (47) 65
56.0%
2024-04-06T18:58:14.790371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 149
21.0%
3 140
19.7%
9 128
18.0%
8 101
14.2%
0 53
 
7.5%
6 37
 
5.2%
2 35
 
4.9%
7 21
 
3.0%
5 18
 
2.5%
- 15
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 696
97.9%
Dash Punctuation 15
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 149
21.4%
3 140
20.1%
9 128
18.4%
8 101
14.5%
0 53
 
7.6%
6 37
 
5.3%
2 35
 
5.0%
7 21
 
3.0%
5 18
 
2.6%
4 14
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 711
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 149
21.0%
3 140
19.7%
9 128
18.0%
8 101
14.2%
0 53
 
7.5%
6 37
 
5.2%
2 35
 
4.9%
7 21
 
3.0%
5 18
 
2.5%
- 15
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 711
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 149
21.0%
3 140
19.7%
9 128
18.0%
8 101
14.2%
0 53
 
7.5%
6 37
 
5.2%
2 35
 
4.9%
7 21
 
3.0%
5 18
 
2.5%
- 15
 
2.1%
Distinct107
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T18:58:15.199123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length33.5
Mean length25.913793
Min length17

Characters and Unicode

Total characters3006
Distinct characters132
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

Unique100 ?
Unique (%)86.2%

Sample

1st row서울특별시 노원구 하계동 284
2nd row서울특별시 노원구 중계동 506-1
3rd row서울특별시 노원구 상계동 713 롯데백화점
4th row서울특별시 노원구 중계동 434-1 지하동
5th row서울특별시 노원구 중계동 364-17 지하동
ValueCountFrequency (%)
서울특별시 116
20.2%
노원구 116
20.2%
상계동 52
 
9.1%
중계동 37
 
6.4%
공릉동 16
 
2.8%
지하1층 8
 
1.4%
월계동 7
 
1.2%
1층 6
 
1.0%
하계동 4
 
0.7%
대덕프라자 3
 
0.5%
Other values (171) 209
36.4%
2024-04-06T18:58:15.915547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
543
 
18.1%
1 160
 
5.3%
124
 
4.1%
120
 
4.0%
118
 
3.9%
117
 
3.9%
117
 
3.9%
117
 
3.9%
116
 
3.9%
116
 
3.9%
Other values (122) 1358
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1765
58.7%
Decimal Number 574
 
19.1%
Space Separator 543
 
18.1%
Dash Punctuation 95
 
3.2%
Other Punctuation 14
 
0.5%
Uppercase Letter 9
 
0.3%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
124
 
7.0%
120
 
6.8%
118
 
6.7%
117
 
6.6%
117
 
6.6%
117
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
Other values (100) 588
33.3%
Decimal Number
ValueCountFrequency (%)
1 160
27.9%
3 73
12.7%
0 59
 
10.3%
2 56
 
9.8%
5 54
 
9.4%
6 46
 
8.0%
4 36
 
6.3%
9 33
 
5.7%
8 32
 
5.6%
7 25
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 4
44.4%
P 1
 
11.1%
V 1
 
11.1%
I 1
 
11.1%
K 1
 
11.1%
S 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 13
92.9%
@ 1
 
7.1%
Space Separator
ValueCountFrequency (%)
543
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1765
58.7%
Common 1232
41.0%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
124
 
7.0%
120
 
6.8%
118
 
6.7%
117
 
6.6%
117
 
6.6%
117
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
Other values (100) 588
33.3%
Common
ValueCountFrequency (%)
543
44.1%
1 160
 
13.0%
- 95
 
7.7%
3 73
 
5.9%
0 59
 
4.8%
2 56
 
4.5%
5 54
 
4.4%
6 46
 
3.7%
4 36
 
2.9%
9 33
 
2.7%
Other values (6) 77
 
6.2%
Latin
ValueCountFrequency (%)
B 4
44.4%
P 1
 
11.1%
V 1
 
11.1%
I 1
 
11.1%
K 1
 
11.1%
S 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1765
58.7%
ASCII 1241
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
543
43.8%
1 160
 
12.9%
- 95
 
7.7%
3 73
 
5.9%
0 59
 
4.8%
2 56
 
4.5%
5 54
 
4.4%
6 46
 
3.7%
4 36
 
2.9%
9 33
 
2.7%
Other values (12) 86
 
6.9%
Hangul
ValueCountFrequency (%)
124
 
7.0%
120
 
6.8%
118
 
6.7%
117
 
6.6%
117
 
6.6%
117
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
116
 
6.6%
Other values (100) 588
33.3%

도로명주소
Text

MISSING 

Distinct75
Distinct (%)100.0%
Missing41
Missing (%)35.3%
Memory size1.0 KiB
2024-04-06T18:58:16.386994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length39
Mean length35.533333
Min length21

Characters and Unicode

Total characters2665
Distinct characters131
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

Unique75 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 한글비석로 57 (하계동)
2nd row서울특별시 노원구 동일로 1414, 롯데백화점 (상계동)
3rd row서울특별시 노원구 동일로 1541, 11단지종합상가 지층 (상계동)
4th row서울특별시 노원구 섬밭로 229, 지층 (하계동, 극동,건영,벽산아파트)
5th row서울특별시 노원구 동일로227길 26, 지층 (상계동, 상계주공15단지아파트)
ValueCountFrequency (%)
서울특별시 75
 
14.8%
노원구 75
 
14.8%
상계동 36
 
7.1%
지층 26
 
5.1%
중계동 22
 
4.3%
1층 16
 
3.2%
동일로 11
 
2.2%
한글비석로 10
 
2.0%
공릉동 8
 
1.6%
월계동 7
 
1.4%
Other values (177) 220
43.5%
2024-04-06T18:58:17.050244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
431
 
16.2%
1 132
 
5.0%
104
 
3.9%
95
 
3.6%
, 94
 
3.5%
87
 
3.3%
87
 
3.3%
( 80
 
3.0%
) 80
 
3.0%
77
 
2.9%
Other values (121) 1398
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1544
57.9%
Space Separator 431
 
16.2%
Decimal Number 422
 
15.8%
Other Punctuation 94
 
3.5%
Open Punctuation 80
 
3.0%
Close Punctuation 80
 
3.0%
Dash Punctuation 10
 
0.4%
Uppercase Letter 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
104
 
6.7%
95
 
6.2%
87
 
5.6%
87
 
5.6%
77
 
5.0%
76
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
Other values (103) 718
46.5%
Decimal Number
ValueCountFrequency (%)
1 132
31.3%
2 64
15.2%
3 43
 
10.2%
0 40
 
9.5%
5 32
 
7.6%
4 31
 
7.3%
7 24
 
5.7%
8 20
 
4.7%
9 19
 
4.5%
6 17
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
431
100.0%
Other Punctuation
ValueCountFrequency (%)
, 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1544
57.9%
Common 1118
42.0%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
104
 
6.7%
95
 
6.2%
87
 
5.6%
87
 
5.6%
77
 
5.0%
76
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
Other values (103) 718
46.5%
Common
ValueCountFrequency (%)
431
38.6%
1 132
 
11.8%
, 94
 
8.4%
( 80
 
7.2%
) 80
 
7.2%
2 64
 
5.7%
3 43
 
3.8%
0 40
 
3.6%
5 32
 
2.9%
4 31
 
2.8%
Other values (6) 91
 
8.1%
Latin
ValueCountFrequency (%)
B 2
66.7%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1544
57.9%
ASCII 1121
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
431
38.4%
1 132
 
11.8%
, 94
 
8.4%
( 80
 
7.1%
) 80
 
7.1%
2 64
 
5.7%
3 43
 
3.8%
0 40
 
3.6%
5 32
 
2.9%
4 31
 
2.8%
Other values (8) 94
 
8.4%
Hangul
ValueCountFrequency (%)
104
 
6.7%
95
 
6.2%
87
 
5.6%
87
 
5.6%
77
 
5.0%
76
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
75
 
4.9%
Other values (103) 718
46.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct60
Distinct (%)80.0%
Missing41
Missing (%)35.3%
Infinite0
Infinite (%)0.0%
Mean1730.7067
Minimum1607
Maximum1913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T18:58:17.322710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1607
5-th percentile1616
Q11670
median1715
Q31782.5
95-th percentile1906
Maximum1913
Range306
Interquartile range (IQR)112.5

Descriptive statistics

Standard deviation84.709324
Coefficient of variation (CV)0.048944934
Kurtosis-0.55556763
Mean1730.7067
Median Absolute Deviation (MAD)64
Skewness0.53739366
Sum129803
Variance7175.6695
MonotonicityNot monotonic
2024-04-06T18:58:17.583691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1616 3
 
2.6%
1702 2
 
1.7%
1637 2
 
1.7%
1718 2
 
1.7%
1782 2
 
1.7%
1695 2
 
1.7%
1631 2
 
1.7%
1906 2
 
1.7%
1827 2
 
1.7%
1699 2
 
1.7%
Other values (50) 54
46.6%
(Missing) 41
35.3%
ValueCountFrequency (%)
1607 1
 
0.9%
1612 1
 
0.9%
1616 3
2.6%
1617 1
 
0.9%
1620 1
 
0.9%
1625 1
 
0.9%
1630 1
 
0.9%
1631 2
1.7%
1637 2
1.7%
1644 1
 
0.9%
ValueCountFrequency (%)
1913 1
0.9%
1909 2
1.7%
1906 2
1.7%
1880 1
0.9%
1864 1
0.9%
1851 1
0.9%
1848 1
0.9%
1840 1
0.9%
1835 1
0.9%
1834 1
0.9%
Distinct114
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T18:58:18.127823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.3189655
Min length3

Characters and Unicode

Total characters965
Distinct characters177
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

Unique112 ?
Unique (%)96.6%

Sample

1st row(주)세이브존아이앤씨
2nd row(주)씨마마트중계점
3rd row롯데쇼핑(주)
4th row(주)엘지유통(중계점)
5th row그린벤츄어스
ValueCountFrequency (%)
상계점 5
 
3.4%
주)이마트에브리데이 5
 
3.4%
마트 4
 
2.7%
중계점 3
 
2.0%
진로마트 2
 
1.4%
롯데쇼핑(주)롯데슈퍼 2
 
1.4%
상계할인마트 2
 
1.4%
주식회사 2
 
1.4%
주)gs리테일 2
 
1.4%
멜론플러스 1
 
0.7%
Other values (120) 120
81.1%
2024-04-06T18:58:18.812466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
7.9%
76
 
7.9%
( 45
 
4.7%
) 45
 
4.7%
42
 
4.4%
34
 
3.5%
33
 
3.4%
32
 
3.3%
23
 
2.4%
21
 
2.2%
Other values (167) 538
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 802
83.1%
Open Punctuation 45
 
4.7%
Close Punctuation 45
 
4.7%
Space Separator 32
 
3.3%
Uppercase Letter 16
 
1.7%
Lowercase Letter 11
 
1.1%
Decimal Number 9
 
0.9%
Dash Punctuation 4
 
0.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
76
 
9.5%
76
 
9.5%
42
 
5.2%
34
 
4.2%
33
 
4.1%
23
 
2.9%
21
 
2.6%
20
 
2.5%
17
 
2.1%
15
 
1.9%
Other values (144) 445
55.5%
Uppercase Letter
ValueCountFrequency (%)
G 3
18.8%
S 3
18.8%
M 3
18.8%
K 2
12.5%
D 1
 
6.2%
L 1
 
6.2%
C 1
 
6.2%
N 1
 
6.2%
O 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 2
22.2%
3 2
22.2%
6 2
22.2%
5 2
22.2%
2 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
r 3
27.3%
a 3
27.3%
t 3
27.3%
m 2
18.2%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 802
83.1%
Common 136
 
14.1%
Latin 27
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
76
 
9.5%
76
 
9.5%
42
 
5.2%
34
 
4.2%
33
 
4.1%
23
 
2.9%
21
 
2.6%
20
 
2.5%
17
 
2.1%
15
 
1.9%
Other values (144) 445
55.5%
Latin
ValueCountFrequency (%)
G 3
11.1%
S 3
11.1%
r 3
11.1%
M 3
11.1%
a 3
11.1%
t 3
11.1%
K 2
7.4%
m 2
7.4%
D 1
 
3.7%
L 1
 
3.7%
Other values (3) 3
11.1%
Common
ValueCountFrequency (%)
( 45
33.1%
) 45
33.1%
32
23.5%
- 4
 
2.9%
1 2
 
1.5%
3 2
 
1.5%
6 2
 
1.5%
5 2
 
1.5%
2 1
 
0.7%
. 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 802
83.1%
ASCII 163
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
76
 
9.5%
76
 
9.5%
42
 
5.2%
34
 
4.2%
33
 
4.1%
23
 
2.9%
21
 
2.6%
20
 
2.5%
17
 
2.1%
15
 
1.9%
Other values (144) 445
55.5%
ASCII
ValueCountFrequency (%)
( 45
27.6%
) 45
27.6%
32
19.6%
- 4
 
2.5%
G 3
 
1.8%
S 3
 
1.8%
r 3
 
1.8%
M 3
 
1.8%
a 3
 
1.8%
t 3
 
1.8%
Other values (13) 19
11.7%
Distinct106
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2001-01-29 00:00:00
Maximum2024-03-18 11:34:43
2024-04-06T18:58:19.077323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:19.370194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
U
58 
I
58 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 58
50.0%
I 58
50.0%

Length

2024-04-06T18:58:19.603168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:19.785850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 58
50.0%
i 58
50.0%
Distinct62
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-02 22:00:00
2024-04-06T18:58:20.002503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:20.234004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
기타식품판매업
116 

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 116
100.0%

Length

2024-04-06T18:58:20.479065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:20.648075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 116
100.0%

좌표정보(X)
Real number (ℝ)

Distinct82
Distinct (%)71.3%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean206035.92
Minimum204670.57
Maximum207577.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T18:58:20.821607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204670.57
5-th percentile204759.38
Q1205462.44
median205994.81
Q3206652.91
95-th percentile207155.19
Maximum207577.52
Range2906.9421
Interquartile range (IQR)1190.4699

Descriptive statistics

Standard deviation739.70803
Coefficient of variation (CV)0.0035901896
Kurtosis-0.91397759
Mean206035.92
Median Absolute Deviation (MAD)584.16422
Skewness-0.088459938
Sum23694131
Variance547167.97
MonotonicityNot monotonic
2024-04-06T18:58:21.024574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206799.020098051 3
 
2.6%
204738.040906241 3
 
2.6%
207311.175792021 3
 
2.6%
205645.891969072 3
 
2.6%
206342.011931277 3
 
2.6%
206490.247358174 3
 
2.6%
205805.621561106 3
 
2.6%
206719.586259379 3
 
2.6%
206964.311274368 2
 
1.7%
205341.384982763 2
 
1.7%
Other values (72) 87
75.0%
ValueCountFrequency (%)
204670.573678123 1
 
0.9%
204716.08725542 1
 
0.9%
204729.107669379 1
 
0.9%
204738.040906241 3
2.6%
204768.524212264 1
 
0.9%
204780.483091647 1
 
0.9%
204867.242318939 1
 
0.9%
204872.498745804 1
 
0.9%
204894.014602534 1
 
0.9%
204911.578026602 1
 
0.9%
ValueCountFrequency (%)
207577.515810212 1
 
0.9%
207311.175792021 3
2.6%
207274.300313358 1
 
0.9%
207224.076240442 1
 
0.9%
207125.667279979 2
1.7%
207111.945468592 1
 
0.9%
206989.985490379 1
 
0.9%
206964.311274368 2
1.7%
206952.444113646 1
 
0.9%
206943.526138135 1
 
0.9%

좌표정보(Y)
Real number (ℝ)

Distinct82
Distinct (%)71.3%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean460842.36
Minimum457275.8
Maximum463966.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T18:58:21.230129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457275.8
5-th percentile457792.61
Q1459669.73
median461164.12
Q3462031.23
95-th percentile463290.41
Maximum463966.29
Range6690.4936
Interquartile range (IQR)2361.5068

Descriptive statistics

Standard deviation1756.2403
Coefficient of variation (CV)0.003810935
Kurtosis-0.83075551
Mean460842.36
Median Absolute Deviation (MAD)1202.886
Skewness-0.39817285
Sum52996871
Variance3084379.9
MonotonicityNot monotonic
2024-04-06T18:58:21.792997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462509.638445514 3
 
2.6%
463290.410210672 3
 
2.6%
457610.711998051 3
 
2.6%
459609.012509743 3
 
2.6%
461845.269709197 3
 
2.6%
460830.615360327 3
 
2.6%
460041.339536101 3
 
2.6%
460669.836412326 3
 
2.6%
462947.66303412 2
 
1.7%
460838.369137318 2
 
1.7%
Other values (72) 87
75.0%
ValueCountFrequency (%)
457275.799282625 1
 
0.9%
457610.711998051 3
2.6%
457736.364674901 1
 
0.9%
457741.465197875 1
 
0.9%
457814.529614419 1
 
0.9%
457867.662188322 2
1.7%
457893.814951571 1
 
0.9%
457909.125969428 1
 
0.9%
458028.977530331 2
1.7%
458051.469220935 1
 
0.9%
ValueCountFrequency (%)
463966.29285643 1
 
0.9%
463745.952218533 1
 
0.9%
463532.934877533 1
 
0.9%
463432.221471752 1
 
0.9%
463290.410210672 3
2.6%
463288.357039657 1
 
0.9%
463199.356724032 1
 
0.9%
463190.151176403 1
 
0.9%
463180.195049662 1
 
0.9%
463089.784688928 1
 
0.9%

위생업태명
Categorical

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
기타식품판매업
88 
<NA>
28 

Length

Max length7
Median length7
Mean length6.2758621
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 88
75.9%
<NA> 28
 
24.1%

Length

2024-04-06T18:58:22.020231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:22.201123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 88
75.9%
na 28
 
24.1%

남성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
102 
0
13 
1
 
1

Length

Max length4
Median length4
Mean length3.637931
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 102
87.9%
0 13
 
11.2%
1 1
 
0.9%

Length

2024-04-06T18:58:22.380024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:22.684035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
87.9%
0 13
 
11.2%
1 1
 
0.9%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
103 
0
13 

Length

Max length4
Median length4
Mean length3.6637931
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 103
88.8%
0 13
 
11.2%

Length

2024-04-06T18:58:23.145509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:23.517298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 103
88.8%
0 13
 
11.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
108 
아파트지역
 
4
주택가주변
 
2
기타
 
2

Length

Max length5
Median length4
Mean length4.0172414
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 108
93.1%
아파트지역 4
 
3.4%
주택가주변 2
 
1.7%
기타 2
 
1.7%

Length

2024-04-06T18:58:23.729274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:23.908226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
93.1%
아파트지역 4
 
3.4%
주택가주변 2
 
1.7%
기타 2
 
1.7%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
108 
 
4
기타
 
3
자율
 
1

Length

Max length4
Median length4
Mean length3.8275862
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 108
93.1%
4
 
3.4%
기타 3
 
2.6%
자율 1
 
0.9%

Length

2024-04-06T18:58:24.102679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:24.330536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
93.1%
4
 
3.4%
기타 3
 
2.6%
자율 1
 
0.9%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
99 
상수도전용
17 

Length

Max length5
Median length4
Mean length4.1465517
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
85.3%
상수도전용 17
 
14.7%

Length

2024-04-06T18:58:24.552573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:24.753137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
85.3%
상수도전용 17
 
14.7%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
108 
0
 
8

Length

Max length4
Median length4
Mean length3.7931034
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> 108
93.1%
0 8
 
6.9%

Length

2024-04-06T18:58:24.937635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:25.100626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
93.1%
0 8
 
6.9%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
59 
0
57 

Length

Max length4
Median length4
Mean length2.5258621
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> 59
50.9%
0 57
49.1%

Length

2024-04-06T18:58:25.283220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:25.480996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
50.9%
0 57
49.1%
Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
58 
0
57 
1
 
1

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
50.0%
0 57
49.1%
1 1
 
0.9%

Length

2024-04-06T18:58:25.725903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:26.018833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
50.0%
0 57
49.1%
1 1
 
0.9%
Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
58 
0
57 
9
 
1

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
50.0%
0 57
49.1%
9 1
 
0.9%

Length

2024-04-06T18:58:26.262085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:26.462953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
50.0%
0 57
49.1%
9 1
 
0.9%
Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
59 
0
57 

Length

Max length4
Median length4
Mean length2.5258621
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> 59
50.9%
0 57
49.1%

Length

2024-04-06T18:58:26.710733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:26.932427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
50.9%
0 57
49.1%
Distinct3
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
87 
자가
18 
임대
11 

Length

Max length4
Median length4
Mean length3.5
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> 87
75.0%
자가 18
 
15.5%
임대 11
 
9.5%

Length

2024-04-06T18:58:27.263003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:27.490658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 87
75.0%
자가 18
 
15.5%
임대 11
 
9.5%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
108 
0
 
8

Length

Max length4
Median length4
Mean length3.7931034
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> 108
93.1%
0 8
 
6.9%

Length

2024-04-06T18:58:27.707677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:27.902997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
93.1%
0 8
 
6.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
<NA>
108 
0
 
8

Length

Max length4
Median length4
Mean length3.7931034
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> 108
93.1%
0 8
 
6.9%

Length

2024-04-06T18:58:28.071138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:28.270120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 108
93.1%
0 8
 
6.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.1%
Missing28
Missing (%)24.1%
Memory size364.0 B
False
88 
(Missing)
28 
ValueCountFrequency (%)
False 88
75.9%
(Missing) 28
 
24.1%
2024-04-06T18:58:28.509183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct6
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0.0
84 
<NA>
28 
315.0
 
1
499.8
 
1
583.4
 
1

Length

Max length5
Median length3
Mean length3.2931034
Min length3

Unique

Unique4 ?
Unique (%)3.4%

Sample

1st row<NA>
2nd row0.0
3rd row<NA>
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 84
72.4%
<NA> 28
 
24.1%
315.0 1
 
0.9%
499.8 1
 
0.9%
583.4 1
 
0.9%
6.6 1
 
0.9%

Length

2024-04-06T18:58:28.775645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:29.060571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 84
72.4%
na 28
 
24.1%
315.0 1
 
0.9%
499.8 1
 
0.9%
583.4 1
 
0.9%
6.6 1
 
0.9%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing116
Missing (%)100.0%
Memory size1.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-114-1990-000011990-06-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 98590002336.27139-230서울특별시 노원구 하계동 284서울특별시 노원구 한글비석로 57 (하계동)1784(주)세이브존아이앤씨2023-05-15 15:14:04U2022-12-04 23:07:00.0기타식품판매업205994.811816459502.64528<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131000003100000-114-1991-0027519910605<NA>3폐업2폐업20040320<NA><NA><NA>02 97347641,280.56139863서울특별시 노원구 중계동 506-1<NA><NA>(주)씨마마트중계점2003-01-10 00:00:00I2018-08-31 23:59:59.0기타식품판매업205645.891969459609.01251기타식품판매업00아파트지역<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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531000003100000-114-1996-0021519960703<NA>3폐업2폐업20110331<NA><NA><NA>02 9482077308.84139865서울특별시 노원구 중계동 512-0 시영2단지 상가 지하<NA><NA>가우리할인마트2009-03-06 10:59:36I2018-08-31 23:59:59.0기타식품판매업205805.621561460041.339536기타식품판매업00아파트지역<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
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931000003100000-114-1996-0023219960624<NA>3폐업2폐업20030624<NA><NA><NA>02 9360407441.98139832서울특별시 노원구 상계동 749-5 주공4단지상가<NA><NA>드림할인마트2003-06-24 00:00:00I2018-08-31 23:59:59.0기타식품판매업205421.148836460856.264208기타식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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11231000003100000-114-2022-0000320220831<NA>1영업/정상1영업<NA><NA><NA><NA><NA>370.25139240서울특별시 노원구 공릉동 375-16 공릉동VIPS서울특별시 노원구 동일로 1090, 1층 (공릉동)1840식자재유통센터2022-08-31 15:49:55I2021-12-09 00:03:00.0기타식품판매업206342.407296458322.83911<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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11431000003100000-114-2023-000012023-04-05<NA>3폐업2폐업2023-05-17<NA><NA><NA><NA>326.00139-200서울특별시 노원구 상계동 630 청수빌딩서울특별시 노원구 동일로228길 35, 청수빌딩 지하1층 101호 (상계동)1669세일마트2023-05-17 18:03:41U2022-12-04 23:09:00.0기타식품판매업205138.926439462840.104437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11531000003100000-114-2023-000022023-04-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>896.59139-837서울특별시 노원구 상계동 1023-11서울특별시 노원구 동일로234길 13 (상계동)1630(주)새로나마트2023-04-21 17:42:59I2022-12-03 22:03:00.0기타식품판매업204911.578027463432.221472<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>