Overview

Dataset statistics

Number of variables44
Number of observations383
Missing cells4666
Missing cells (%)27.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.8 KiB
Average record size in memory376.3 B

Variable types

Categorical18
Text9
DateTime4
Unsupported8
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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-17995/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
등급구분명 has constant value ""Constant
여성종사자수 is highly imbalanced (58.6%)Imbalance
급수시설구분명 is highly imbalanced (65.2%)Imbalance
다중이용업소여부 is highly imbalanced (96.7%)Imbalance
인허가취소일자 has 383 (100.0%) missing valuesMissing
폐업일자 has 107 (27.9%) missing valuesMissing
휴업시작일자 has 383 (100.0%) missing valuesMissing
휴업종료일자 has 383 (100.0%) missing valuesMissing
재개업일자 has 383 (100.0%) missing valuesMissing
전화번호 has 203 (53.0%) missing valuesMissing
소재지면적 has 122 (31.9%) missing valuesMissing
도로명주소 has 96 (25.1%) missing valuesMissing
도로명우편번호 has 105 (27.4%) missing valuesMissing
좌표정보(X) has 12 (3.1%) missing valuesMissing
좌표정보(Y) has 12 (3.1%) missing valuesMissing
영업장주변구분명 has 381 (99.5%) missing valuesMissing
등급구분명 has 382 (99.7%) missing valuesMissing
건물소유구분명 has 383 (100.0%) missing valuesMissing
다중이용업소여부 has 88 (23.0%) missing valuesMissing
시설총규모 has 88 (23.0%) missing valuesMissing
전통업소지정번호 has 383 (100.0%) missing valuesMissing
전통업소주된음식 has 383 (100.0%) missing valuesMissing
홈페이지 has 383 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 125 (32.6%) zerosZeros

Reproduction

Analysis started2024-04-06 09:57:49.649645
Analysis finished2024-04-06 09:57:50.903422
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3180000
383 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 383
100.0%

Length

2024-04-06T18:57:51.045434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:57:51.212118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 383
100.0%

관리번호
Text

UNIQUE 

Distinct383
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-06T18:57:51.498850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8426
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

Unique383 ?
Unique (%)100.0%

Sample

1st row3180000-120-2003-00001
2nd row3180000-120-2003-00002
3rd row3180000-120-2003-00003
4th row3180000-120-2003-00004
5th row3180000-120-2003-00005
ValueCountFrequency (%)
3180000-120-2003-00001 1
 
0.3%
3180000-120-2017-00006 1
 
0.3%
3180000-120-2017-00003 1
 
0.3%
3180000-120-2017-00002 1
 
0.3%
3180000-120-2017-00001 1
 
0.3%
3180000-120-2016-00014 1
 
0.3%
3180000-120-2016-00013 1
 
0.3%
3180000-120-2016-00012 1
 
0.3%
3180000-120-2016-00011 1
 
0.3%
3180000-120-2016-00010 1
 
0.3%
Other values (373) 373
97.4%
2024-04-06T18:57:52.003080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3859
45.8%
- 1149
 
13.6%
1 1123
 
13.3%
2 920
 
10.9%
3 548
 
6.5%
8 450
 
5.3%
4 87
 
1.0%
7 82
 
1.0%
6 79
 
0.9%
5 72
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7277
86.4%
Dash Punctuation 1149
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3859
53.0%
1 1123
 
15.4%
2 920
 
12.6%
3 548
 
7.5%
8 450
 
6.2%
4 87
 
1.2%
7 82
 
1.1%
6 79
 
1.1%
5 72
 
1.0%
9 57
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8426
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3859
45.8%
- 1149
 
13.6%
1 1123
 
13.3%
2 920
 
10.9%
3 548
 
6.5%
8 450
 
5.3%
4 87
 
1.0%
7 82
 
1.0%
6 79
 
0.9%
5 72
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8426
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3859
45.8%
- 1149
 
13.6%
1 1123
 
13.3%
2 920
 
10.9%
3 548
 
6.5%
8 450
 
5.3%
4 87
 
1.0%
7 82
 
1.0%
6 79
 
0.9%
5 72
 
0.9%
Distinct292
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2003-09-02 00:00:00
Maximum2024-03-27 00:00:00
2024-04-06T18:57:52.225816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:57:52.450533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
3
276 
1
107 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 276
72.1%
1 107
 
27.9%

Length

2024-04-06T18:57:52.702823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:57:52.910559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 276
72.1%
1 107
 
27.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
276 
영업/정상
107 

Length

Max length5
Median length2
Mean length2.8381201
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 276
72.1%
영업/정상 107
 
27.9%

Length

2024-04-06T18:57:53.178170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:57:53.376817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 276
72.1%
영업/정상 107
 
27.9%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2
276 
1
107 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 276
72.1%
1 107
 
27.9%

Length

2024-04-06T18:57:53.538142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:57:53.689521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 276
72.1%
1 107
 
27.9%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
폐업
276 
영업
107 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 276
72.1%
영업 107
 
27.9%

Length

2024-04-06T18:57:53.859644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:57:54.051619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 276
72.1%
영업 107
 
27.9%

폐업일자
Date

MISSING 

Distinct229
Distinct (%)83.0%
Missing107
Missing (%)27.9%
Memory size3.1 KiB
Minimum2003-12-31 00:00:00
Maximum2024-02-29 00:00:00
2024-04-06T18:57:54.272772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:57:54.522474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

전화번호
Text

MISSING 

Distinct151
Distinct (%)83.9%
Missing203
Missing (%)53.0%
Memory size3.1 KiB
2024-04-06T18:57:55.330764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.538889
Min length7

Characters and Unicode

Total characters1897
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

Unique133 ?
Unique (%)73.9%

Sample

1st row029722 089
2nd row024081 130
3rd row02 21746116
4th row0226326410
5th row0226368384
ValueCountFrequency (%)
02 79
25.7%
0233920455 8
 
2.6%
070 6
 
2.0%
0221754114 5
 
1.6%
031 5
 
1.6%
33976100 4
 
1.3%
0269669274 3
 
1.0%
20276080 3
 
1.0%
753 3
 
1.0%
9181 2
 
0.7%
Other values (168) 189
61.6%
2024-04-06T18:57:56.048565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 347
18.3%
2 299
15.8%
176
9.3%
3 162
8.5%
7 151
8.0%
6 150
7.9%
5 141
7.4%
1 135
 
7.1%
8 127
 
6.7%
9 107
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1721
90.7%
Space Separator 176
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 347
20.2%
2 299
17.4%
3 162
9.4%
7 151
8.8%
6 150
8.7%
5 141
8.2%
1 135
 
7.8%
8 127
 
7.4%
9 107
 
6.2%
4 102
 
5.9%
Space Separator
ValueCountFrequency (%)
176
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1897
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 347
18.3%
2 299
15.8%
176
9.3%
3 162
8.5%
7 151
8.0%
6 150
7.9%
5 141
7.4%
1 135
 
7.1%
8 127
 
6.7%
9 107
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1897
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 347
18.3%
2 299
15.8%
176
9.3%
3 162
8.5%
7 151
8.0%
6 150
7.9%
5 141
7.4%
1 135
 
7.1%
8 127
 
6.7%
9 107
 
5.6%

소재지면적
Text

MISSING 

Distinct203
Distinct (%)77.8%
Missing122
Missing (%)31.9%
Memory size3.1 KiB
2024-04-06T18:57:56.592210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9348659
Min length3

Characters and Unicode

Total characters1549
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

Unique162 ?
Unique (%)62.1%

Sample

1st row428.00
2nd row960.07
3rd row513.08
4th row653.00
5th row623.00
ValueCountFrequency (%)
00 10
 
3.8%
753.00 4
 
1.5%
693.69 4
 
1.5%
180.00 3
 
1.1%
676.00 3
 
1.1%
961.60 3
 
1.1%
88.00 3
 
1.1%
757.50 3
 
1.1%
233.00 2
 
0.8%
9.90 2
 
0.8%
Other values (193) 224
85.8%
2024-04-06T18:57:57.347054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 387
25.0%
. 261
16.8%
1 122
 
7.9%
2 116
 
7.5%
3 112
 
7.2%
5 112
 
7.2%
8 95
 
6.1%
9 85
 
5.5%
6 83
 
5.4%
4 81
 
5.2%
Other values (2) 95
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1273
82.2%
Other Punctuation 276
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 387
30.4%
1 122
 
9.6%
2 116
 
9.1%
3 112
 
8.8%
5 112
 
8.8%
8 95
 
7.5%
9 85
 
6.7%
6 83
 
6.5%
4 81
 
6.4%
7 80
 
6.3%
Other Punctuation
ValueCountFrequency (%)
. 261
94.6%
, 15
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1549
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 387
25.0%
. 261
16.8%
1 122
 
7.9%
2 116
 
7.5%
3 112
 
7.2%
5 112
 
7.2%
8 95
 
6.1%
9 85
 
5.5%
6 83
 
5.4%
4 81
 
5.2%
Other values (2) 95
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 387
25.0%
. 261
16.8%
1 122
 
7.9%
2 116
 
7.5%
3 112
 
7.2%
5 112
 
7.2%
8 95
 
6.1%
9 85
 
5.5%
6 83
 
5.4%
4 81
 
5.2%
Other values (2) 95
 
6.1%
Distinct123
Distinct (%)32.4%
Missing3
Missing (%)0.8%
Memory size3.1 KiB
2024-04-06T18:57:57.878014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1657895
Min length6

Characters and Unicode

Total characters2343
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

Unique45 ?
Unique (%)11.8%

Sample

1st row150834
2nd row150874
3rd row150869
4th row150037
5th row150815
ValueCountFrequency (%)
150876 16
 
4.2%
150860 12
 
3.2%
150841 12
 
3.2%
150038 10
 
2.6%
150874 9
 
2.4%
150010 9
 
2.4%
150102 9
 
2.4%
150882 9
 
2.4%
150866 9
 
2.4%
150891 9
 
2.4%
Other values (113) 276
72.6%
2024-04-06T18:57:58.674352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 533
22.7%
1 472
20.1%
5 425
18.1%
8 343
14.6%
6 113
 
4.8%
7 108
 
4.6%
9 80
 
3.4%
3 78
 
3.3%
4 67
 
2.9%
- 63
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2280
97.3%
Dash Punctuation 63
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 533
23.4%
1 472
20.7%
5 425
18.6%
8 343
15.0%
6 113
 
5.0%
7 108
 
4.7%
9 80
 
3.5%
3 78
 
3.4%
4 67
 
2.9%
2 61
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2343
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 533
22.7%
1 472
20.1%
5 425
18.1%
8 343
14.6%
6 113
 
4.8%
7 108
 
4.6%
9 80
 
3.4%
3 78
 
3.3%
4 67
 
2.9%
- 63
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 533
22.7%
1 472
20.1%
5 425
18.1%
8 343
14.6%
6 113
 
4.8%
7 108
 
4.6%
9 80
 
3.4%
3 78
 
3.3%
4 67
 
2.9%
- 63
 
2.7%
Distinct323
Distinct (%)85.0%
Missing3
Missing (%)0.8%
Memory size3.1 KiB
2024-04-06T18:57:59.168554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length27.557895
Min length18

Characters and Unicode

Total characters10472
Distinct characters213
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

Unique274 ?
Unique (%)72.1%

Sample

1st row서울특별시 영등포구 문래동3가 48번지
2nd row서울특별시 영등포구 여의도동 17-13번지 (동국무역)
3rd row서울특별시 영등포구 여의도동 12-3번지 (주)신한
4th row서울특별시 영등포구 영등포동7가 94-46번지 (제일물산(주))
5th row서울특별시 영등포구 대림동 735번지 (영남중학교)
ValueCountFrequency (%)
서울특별시 380
20.3%
영등포구 380
20.3%
여의도동 169
 
9.0%
신길동 49
 
2.6%
지하1층 39
 
2.1%
대림동 22
 
1.2%
양평동4가 21
 
1.1%
문래동3가 13
 
0.7%
지하2층 12
 
0.6%
영등포동8가 12
 
0.6%
Other values (415) 776
41.4%
2024-04-06T18:57:59.927006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1786
 
17.1%
475
 
4.5%
451
 
4.3%
437
 
4.2%
399
 
3.8%
394
 
3.8%
389
 
3.7%
385
 
3.7%
383
 
3.7%
381
 
3.6%
Other values (203) 4992
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6882
65.7%
Space Separator 1786
 
17.1%
Decimal Number 1471
 
14.0%
Dash Punctuation 249
 
2.4%
Uppercase Letter 41
 
0.4%
Open Punctuation 16
 
0.2%
Close Punctuation 16
 
0.2%
Other Punctuation 9
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
475
 
6.9%
451
 
6.6%
437
 
6.3%
399
 
5.8%
394
 
5.7%
389
 
5.7%
385
 
5.6%
383
 
5.6%
381
 
5.5%
380
 
5.5%
Other values (176) 2808
40.8%
Decimal Number
ValueCountFrequency (%)
1 302
20.5%
2 243
16.5%
3 220
15.0%
4 179
12.2%
6 134
9.1%
5 118
 
8.0%
8 81
 
5.5%
7 78
 
5.3%
0 60
 
4.1%
9 56
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
K 13
31.7%
B 10
24.4%
S 5
 
12.2%
C 3
 
7.3%
T 3
 
7.3%
M 2
 
4.9%
N 2
 
4.9%
Y 1
 
2.4%
D 1
 
2.4%
G 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
. 3
33.3%
Space Separator
ValueCountFrequency (%)
1786
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 249
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6882
65.7%
Common 3549
33.9%
Latin 41
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
475
 
6.9%
451
 
6.6%
437
 
6.3%
399
 
5.8%
394
 
5.7%
389
 
5.7%
385
 
5.6%
383
 
5.6%
381
 
5.5%
380
 
5.5%
Other values (176) 2808
40.8%
Common
ValueCountFrequency (%)
1786
50.3%
1 302
 
8.5%
- 249
 
7.0%
2 243
 
6.8%
3 220
 
6.2%
4 179
 
5.0%
6 134
 
3.8%
5 118
 
3.3%
8 81
 
2.3%
7 78
 
2.2%
Other values (7) 159
 
4.5%
Latin
ValueCountFrequency (%)
K 13
31.7%
B 10
24.4%
S 5
 
12.2%
C 3
 
7.3%
T 3
 
7.3%
M 2
 
4.9%
N 2
 
4.9%
Y 1
 
2.4%
D 1
 
2.4%
G 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6882
65.7%
ASCII 3590
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1786
49.7%
1 302
 
8.4%
- 249
 
6.9%
2 243
 
6.8%
3 220
 
6.1%
4 179
 
5.0%
6 134
 
3.7%
5 118
 
3.3%
8 81
 
2.3%
7 78
 
2.2%
Other values (17) 200
 
5.6%
Hangul
ValueCountFrequency (%)
475
 
6.9%
451
 
6.6%
437
 
6.3%
399
 
5.8%
394
 
5.7%
389
 
5.7%
385
 
5.6%
383
 
5.6%
381
 
5.5%
380
 
5.5%
Other values (176) 2808
40.8%

도로명주소
Text

MISSING 

Distinct265
Distinct (%)92.3%
Missing96
Missing (%)25.1%
Memory size3.1 KiB
2024-04-06T18:58:00.458420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length35.728223
Min length23

Characters and Unicode

Total characters10254
Distinct characters233
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

Unique246 ?
Unique (%)85.7%

Sample

1st row서울특별시 영등포구 여의나루로4길 21 (여의도동)
2nd row서울특별시 영등포구 여의대로 38 (여의도동)
3rd row서울특별시 영등포구 의사당대로 3 (여의도동)
4th row서울특별시 영등포구 버드나루로7길 12, 지하1층 (영등포동7가, 한강성심병원 )
5th row서울특별시 영등포구 신길로 1 (대림동, 강남성심병원 지하1층)
ValueCountFrequency (%)
서울특별시 287
 
15.7%
영등포구 287
 
15.7%
여의도동 106
 
5.8%
지하1층 61
 
3.3%
신길동 35
 
1.9%
의사당대로 29
 
1.6%
영중로 20
 
1.1%
13 18
 
1.0%
선유로 18
 
1.0%
1층 16
 
0.9%
Other values (376) 951
52.0%
2024-04-06T18:58:01.496892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1541
 
15.0%
390
 
3.8%
389
 
3.8%
351
 
3.4%
312
 
3.0%
306
 
3.0%
302
 
2.9%
295
 
2.9%
( 295
 
2.9%
) 295
 
2.9%
Other values (223) 5778
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6651
64.9%
Space Separator 1541
 
15.0%
Decimal Number 1138
 
11.1%
Open Punctuation 295
 
2.9%
Close Punctuation 295
 
2.9%
Other Punctuation 285
 
2.8%
Uppercase Letter 43
 
0.4%
Dash Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
390
 
5.9%
389
 
5.8%
351
 
5.3%
312
 
4.7%
306
 
4.6%
302
 
4.5%
295
 
4.4%
294
 
4.4%
290
 
4.4%
290
 
4.4%
Other values (195) 3432
51.6%
Uppercase Letter
ValueCountFrequency (%)
K 13
30.2%
B 10
23.3%
S 5
 
11.6%
T 3
 
7.0%
C 3
 
7.0%
M 2
 
4.7%
N 2
 
4.7%
G 2
 
4.7%
Y 1
 
2.3%
D 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 286
25.1%
2 186
16.3%
3 130
11.4%
6 120
10.5%
4 109
 
9.6%
5 89
 
7.8%
8 74
 
6.5%
7 72
 
6.3%
0 42
 
3.7%
9 30
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 282
98.9%
. 3
 
1.1%
Space Separator
ValueCountFrequency (%)
1541
100.0%
Open Punctuation
ValueCountFrequency (%)
( 295
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6651
64.9%
Common 3560
34.7%
Latin 43
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
390
 
5.9%
389
 
5.8%
351
 
5.3%
312
 
4.7%
306
 
4.6%
302
 
4.5%
295
 
4.4%
294
 
4.4%
290
 
4.4%
290
 
4.4%
Other values (195) 3432
51.6%
Common
ValueCountFrequency (%)
1541
43.3%
( 295
 
8.3%
) 295
 
8.3%
1 286
 
8.0%
, 282
 
7.9%
2 186
 
5.2%
3 130
 
3.7%
6 120
 
3.4%
4 109
 
3.1%
5 89
 
2.5%
Other values (7) 227
 
6.4%
Latin
ValueCountFrequency (%)
K 13
30.2%
B 10
23.3%
S 5
 
11.6%
T 3
 
7.0%
C 3
 
7.0%
M 2
 
4.7%
N 2
 
4.7%
G 2
 
4.7%
Y 1
 
2.3%
D 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6651
64.9%
ASCII 3603
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1541
42.8%
( 295
 
8.2%
) 295
 
8.2%
1 286
 
7.9%
, 282
 
7.8%
2 186
 
5.2%
3 130
 
3.6%
6 120
 
3.3%
4 109
 
3.0%
5 89
 
2.5%
Other values (18) 270
 
7.5%
Hangul
ValueCountFrequency (%)
390
 
5.9%
389
 
5.8%
351
 
5.3%
312
 
4.7%
306
 
4.6%
302
 
4.5%
295
 
4.4%
294
 
4.4%
290
 
4.4%
290
 
4.4%
Other values (195) 3432
51.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct81
Distinct (%)29.1%
Missing105
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean7303.6978
Minimum7202
Maximum7448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-06T18:58:01.953643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7202
5-th percentile7209
Q17242
median7311
Q37336
95-th percentile7436.15
Maximum7448
Range246
Interquartile range (IQR)94

Descriptive statistics

Standard deviation65.04929
Coefficient of variation (CV)0.0089063501
Kurtosis-0.44435616
Mean7303.6978
Median Absolute Deviation (MAD)50
Skewness0.48979582
Sum2030428
Variance4231.4102
MonotonicityNot monotonic
2024-04-06T18:58:02.279855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7330 12
 
3.1%
7233 11
 
2.9%
7278 10
 
2.6%
7436 9
 
2.3%
7242 9
 
2.3%
7305 8
 
2.1%
7237 7
 
1.8%
7209 7
 
1.8%
7397 7
 
1.8%
7336 7
 
1.8%
Other values (71) 191
49.9%
(Missing) 105
27.4%
ValueCountFrequency (%)
7202 1
 
0.3%
7203 1
 
0.3%
7206 5
1.3%
7207 1
 
0.3%
7209 7
1.8%
7212 1
 
0.3%
7219 4
1.0%
7222 1
 
0.3%
7226 5
1.3%
7228 4
1.0%
ValueCountFrequency (%)
7448 3
 
0.8%
7445 3
 
0.8%
7442 4
1.0%
7441 2
 
0.5%
7437 2
 
0.5%
7436 9
2.3%
7432 2
 
0.5%
7397 7
1.8%
7392 1
 
0.3%
7387 1
 
0.3%
Distinct377
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2024-04-06T18:58:02.638588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length13.804178
Min length2

Characters and Unicode

Total characters5287
Distinct characters324
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

Unique371 ?
Unique (%)96.9%

Sample

1st row(주)세호푸드
2nd row신세계푸드 동국무역
3rd row신세계푸드 신한건설
4th row신세계푸드제일물산
5th row(주)이바돔
ValueCountFrequency (%)
주)아워홈 14
 
2.7%
주)엘에스씨푸드 11
 
2.1%
주)현대그린푸드 9
 
1.7%
영등포점 6
 
1.2%
신세계푸드 6
 
1.2%
참푸드시스템 6
 
1.2%
주)신세계푸드 5
 
1.0%
본우리집밥 4
 
0.8%
관악고점 3
 
0.6%
대영고등학교 3
 
0.6%
Other values (421) 448
87.0%
2024-04-06T18:58:03.210926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 295
 
5.6%
( 293
 
5.5%
288
 
5.4%
198
 
3.7%
174
 
3.3%
162
 
3.1%
153
 
2.9%
132
 
2.5%
82
 
1.6%
79
 
1.5%
Other values (314) 3431
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4461
84.4%
Close Punctuation 295
 
5.6%
Open Punctuation 293
 
5.5%
Space Separator 132
 
2.5%
Uppercase Letter 88
 
1.7%
Dash Punctuation 12
 
0.2%
Decimal Number 5
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
288
 
6.5%
198
 
4.4%
174
 
3.9%
162
 
3.6%
153
 
3.4%
82
 
1.8%
79
 
1.8%
74
 
1.7%
69
 
1.5%
64
 
1.4%
Other values (289) 3118
69.9%
Uppercase Letter
ValueCountFrequency (%)
K 18
20.5%
B 16
18.2%
S 12
13.6%
C 11
12.5%
D 5
 
5.7%
F 5
 
5.7%
I 4
 
4.5%
M 3
 
3.4%
L 3
 
3.4%
J 2
 
2.3%
Other values (7) 9
10.2%
Decimal Number
ValueCountFrequency (%)
2 3
60.0%
3 1
 
20.0%
1 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 293
100.0%
Space Separator
ValueCountFrequency (%)
132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4461
84.4%
Common 738
 
14.0%
Latin 88
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
288
 
6.5%
198
 
4.4%
174
 
3.9%
162
 
3.6%
153
 
3.4%
82
 
1.8%
79
 
1.8%
74
 
1.7%
69
 
1.5%
64
 
1.4%
Other values (289) 3118
69.9%
Latin
ValueCountFrequency (%)
K 18
20.5%
B 16
18.2%
S 12
13.6%
C 11
12.5%
D 5
 
5.7%
F 5
 
5.7%
I 4
 
4.5%
M 3
 
3.4%
L 3
 
3.4%
J 2
 
2.3%
Other values (7) 9
10.2%
Common
ValueCountFrequency (%)
) 295
40.0%
( 293
39.7%
132
17.9%
- 12
 
1.6%
2 3
 
0.4%
3 1
 
0.1%
1 1
 
0.1%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4461
84.4%
ASCII 826
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 295
35.7%
( 293
35.5%
132
16.0%
K 18
 
2.2%
B 16
 
1.9%
S 12
 
1.5%
- 12
 
1.5%
C 11
 
1.3%
D 5
 
0.6%
F 5
 
0.6%
Other values (15) 27
 
3.3%
Hangul
ValueCountFrequency (%)
288
 
6.5%
198
 
4.4%
174
 
3.9%
162
 
3.6%
153
 
3.4%
82
 
1.8%
79
 
1.8%
74
 
1.7%
69
 
1.5%
64
 
1.4%
Other values (289) 3118
69.9%
Distinct350
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2003-09-03 00:00:00
Maximum2024-03-29 15:31:55
2024-04-06T18:58:03.452921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:03.691519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
I
245 
U
138 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 245
64.0%
U 138
36.0%

Length

2024-04-06T18:58:03.929902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:04.074156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 245
64.0%
u 138
36.0%
Distinct136
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T18:58:04.242184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:58:04.451995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
위탁급식영업
383 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 383
100.0%

Length

2024-04-06T18:58:04.681401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:04.820035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 383
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct170
Distinct (%)45.8%
Missing12
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean192150.34
Minimum189586.24
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-06T18:58:04.990147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189586.24
5-th percentile189967.27
Q1190965.8
median192450.94
Q3193258.91
95-th percentile194019.91
Maximum194632.53
Range5046.2896
Interquartile range (IQR)2293.1056

Descriptive statistics

Standard deviation1266.5329
Coefficient of variation (CV)0.006591364
Kurtosis-0.99454727
Mean192150.34
Median Absolute Deviation (MAD)944.78666
Skewness-0.29559554
Sum71287777
Variance1604105.5
MonotonicityNot monotonic
2024-04-06T18:58:05.239521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192450.93552236 12
 
3.1%
194076.262887209 9
 
2.3%
189619.432198508 9
 
2.3%
190872.704815767 7
 
1.8%
194182.153879146 7
 
1.8%
191943.27624427 7
 
1.8%
191385.057392247 6
 
1.6%
190408.509134733 6
 
1.6%
191623.000857941 5
 
1.3%
193622.797801127 5
 
1.3%
Other values (160) 298
77.8%
(Missing) 12
 
3.1%
ValueCountFrequency (%)
189586.236800721 4
1.0%
189619.432198508 9
2.3%
189621.592266026 2
 
0.5%
189698.002361566 1
 
0.3%
189804.380187717 1
 
0.3%
189814.860666388 1
 
0.3%
189859.071768836 1
 
0.3%
190075.470408684 2
 
0.5%
190119.734954633 1
 
0.3%
190170.669260909 1
 
0.3%
ValueCountFrequency (%)
194632.526367463 1
 
0.3%
194324.398950764 1
 
0.3%
194222.797405532 1
 
0.3%
194182.153879146 7
1.8%
194076.262887209 9
2.3%
193963.563089797 2
 
0.5%
193767.829589155 5
1.3%
193751.84893094 1
 
0.3%
193718.613176315 1
 
0.3%
193711.992981014 3
 
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct171
Distinct (%)46.1%
Missing12
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean446516.62
Minimum442697.97
Maximum448948.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-06T18:58:05.483350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442697.97
5-th percentile443929.04
Q1446227.08
median446707.53
Q3447258.37
95-th percentile448018.63
Maximum448948.72
Range6250.7528
Interquartile range (IQR)1031.2957

Descriptive statistics

Standard deviation1206.0607
Coefficient of variation (CV)0.0027010432
Kurtosis1.4469509
Mean446516.62
Median Absolute Deviation (MAD)540.61135
Skewness-1.2128971
Sum1.6565767 × 108
Variance1454582.4
MonotonicityNot monotonic
2024-04-06T18:58:05.698705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447649.476828035 12
 
3.1%
446974.968037797 9
 
2.3%
446609.119564116 8
 
2.1%
448534.504128423 7
 
1.8%
446722.718400043 7
 
1.8%
443930.05209812 7
 
1.8%
446098.555926507 6
 
1.6%
447298.022173646 6
 
1.6%
444590.223861317 5
 
1.3%
446584.917721507 5
 
1.3%
Other values (161) 299
78.1%
(Missing) 12
 
3.1%
ValueCountFrequency (%)
442697.970107753 1
 
0.3%
442777.411153359 2
 
0.5%
442812.211045947 3
0.8%
443157.388663332 2
 
0.5%
443231.351977519 2
 
0.5%
443331.347120697 2
 
0.5%
443459.357676774 2
 
0.5%
443679.272217418 3
0.8%
443928.02168029 2
 
0.5%
443930.05209812 7
1.8%
ValueCountFrequency (%)
448948.722953309 1
 
0.3%
448827.040748715 1
 
0.3%
448775.455324573 1
 
0.3%
448739.129269078 1
 
0.3%
448534.504128423 7
1.8%
448352.840608043 1
 
0.3%
448196.897432361 1
 
0.3%
448191.644571742 1
 
0.3%
448165.910755347 1
 
0.3%
448061.33130312 4
1.0%

위생업태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
위탁급식영업
295 
<NA>
88 

Length

Max length6
Median length6
Mean length5.54047
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:05.990436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:06.186592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 295
77.0%
na 88
 
23.0%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
294 
<NA>
88 
1
 
1

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 294
76.8%
<NA> 88
 
23.0%
1 1
 
0.3%

Length

2024-04-06T18:58:06.450119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:06.640103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 294
76.8%
na 88
 
23.0%
1 1
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
293 
<NA>
88 
5
 
1
1
 
1

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
0 293
76.5%
<NA> 88
 
23.0%
5 1
 
0.3%
1 1
 
0.3%

Length

2024-04-06T18:58:06.850425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:07.030613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 293
76.5%
na 88
 
23.0%
5 1
 
0.3%
1 1
 
0.3%
Distinct2
Distinct (%)100.0%
Missing381
Missing (%)99.5%
Memory size3.1 KiB
2024-04-06T18:58:07.232410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row기타
2nd row주택가주변
ValueCountFrequency (%)
기타 1
50.0%
주택가주변 1
50.0%
2024-04-06T18:58:07.704591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

등급구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing382
Missing (%)99.7%
Memory size3.1 KiB
2024-04-06T18:58:07.851555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row자율
ValueCountFrequency (%)
자율 1
100.0%
2024-04-06T18:58:08.419623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
<NA>
358 
상수도전용
 
25

Length

Max length5
Median length4
Mean length4.0652742
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> 358
93.5%
상수도전용 25
 
6.5%

Length

2024-04-06T18:58:08.793028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:08.984949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 358
93.5%
상수도전용 25
 
6.5%

총인원
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:09.190641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:09.444205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:09.641172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:09.859700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:10.044831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:10.273259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:10.820306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:11.049991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%
Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:11.323956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:11.506680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

보증액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:11.670408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:11.833376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%

월세액
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
0
295 
<NA>
88 

Length

Max length4
Median length1
Mean length1.689295
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 295
77.0%
<NA> 88
 
23.0%

Length

2024-04-06T18:58:12.051533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:58:12.235634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 295
77.0%
na 88
 
23.0%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.7%
Missing88
Missing (%)23.0%
Memory size898.0 B
False
294 
True
 
1
(Missing)
88 
ValueCountFrequency (%)
False 294
76.8%
True 1
 
0.3%
(Missing) 88
 
23.0%
2024-04-06T18:58:12.373649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct140
Distinct (%)47.5%
Missing88
Missing (%)23.0%
Infinite0
Infinite (%)0.0%
Mean288.12132
Minimum0
Maximum2031.82
Zeros125
Zeros (%)32.6%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2024-04-06T18:58:12.544968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median142
Q3479.12
95-th percentile963.52
Maximum2031.82
Range2031.82
Interquartile range (IQR)479.12

Descriptive statistics

Standard deviation376.30423
Coefficient of variation (CV)1.3060617
Kurtosis1.9743174
Mean288.12132
Median Absolute Deviation (MAD)142
Skewness1.4736311
Sum84995.79
Variance141604.87
MonotonicityNot monotonic
2024-04-06T18:58:12.784253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 125
32.6%
961.6 3
 
0.8%
813.0 2
 
0.5%
1326.29 2
 
0.5%
330.0 2
 
0.5%
97.35 2
 
0.5%
1123.13 2
 
0.5%
154.3 2
 
0.5%
693.69 2
 
0.5%
233.0 2
 
0.5%
Other values (130) 151
39.4%
(Missing) 88
23.0%
ValueCountFrequency (%)
0.0 125
32.6%
24.7 1
 
0.3%
33.0 2
 
0.5%
40.49 1
 
0.3%
45.25 1
 
0.3%
61.35 2
 
0.5%
76.4 1
 
0.3%
91.83 1
 
0.3%
92.71 2
 
0.5%
93.0 1
 
0.3%
ValueCountFrequency (%)
2031.82 1
0.3%
1687.0 1
0.3%
1482.56 1
0.3%
1425.6 1
0.3%
1326.29 2
0.5%
1309.8 1
0.3%
1247.54 1
0.3%
1232.29 1
0.3%
1144.0 1
0.3%
1123.13 2
0.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing383
Missing (%)100.0%
Memory size3.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-120-2003-0000120030902<NA>3폐업2폐업20061031<NA><NA><NA>029722 089<NA>150834서울특별시 영등포구 문래동3가 48번지<NA><NA>(주)세호푸드2006-03-07 00:00:00I2018-08-31 23:59:59.0위탁급식영업190749.883436446369.766232위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
131800003180000-120-2003-0000220030903<NA>3폐업2폐업20050401<NA><NA><NA><NA><NA>150874서울특별시 영등포구 여의도동 17-13번지 (동국무역)<NA><NA>신세계푸드 동국무역2004-02-12 00:00:00I2018-08-31 23:59:59.0위탁급식영업192671.748496447184.898324위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
231800003180000-120-2003-0000320030903<NA>3폐업2폐업20060331<NA><NA><NA><NA><NA>150869서울특별시 영등포구 여의도동 12-3번지 (주)신한<NA><NA>신세계푸드 신한건설2005-03-21 00:00:00I2018-08-31 23:59:59.0위탁급식영업193259.164012447503.839458위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
331800003180000-120-2003-0000420030903<NA>3폐업2폐업20040816<NA><NA><NA><NA><NA>150037서울특별시 영등포구 영등포동7가 94-46번지 (제일물산(주))<NA><NA>신세계푸드제일물산2003-09-03 00:00:00I2018-08-31 23:59:59.0위탁급식영업191921.794068447058.097595위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
431800003180000-120-2003-0000520030904<NA>3폐업2폐업20050310<NA><NA><NA>024081 130<NA>150815서울특별시 영등포구 대림동 735번지 (영남중학교)<NA><NA>(주)이바돔2004-02-12 00:00:00I2018-08-31 23:59:59.0위탁급식영업190732.438064443928.02168위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
531800003180000-120-2003-0000720031007<NA>3폐업2폐업20180809<NA><NA><NA><NA>428.00150884서울특별시 영등포구 여의도동 34-4번지서울특별시 영등포구 여의나루로4길 21 (여의도동)7330(주)현대그린푸드 KB증권점2018-08-09 16:47:30I2018-08-31 23:59:59.0위탁급식영업193605.388456446606.665034위탁급식영업00<NA><NA><NA>00000<NA>00N428.0<NA><NA><NA>
631800003180000-120-2003-000082003-10-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-880서울특별시 영등포구 여의도동 27서울특별시 영등포구 여의대로 38 (여의도동)7321(주)풀무원푸드앤컬처금융감독원2023-07-21 15:44:56U2022-12-06 22:03:00.0위탁급식영업192976.019743446761.108856<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731800003180000-120-2003-0000920031008<NA>3폐업2폐업20111108<NA><NA><NA><NA><NA>150874서울특별시 영등포구 여의도동 17-5번지 대림산업10층<NA><NA>(주)아워홈대림산업여의도점2010-12-14 15:48:15I2018-08-31 23:59:59.0위탁급식영업192622.209447248.142201위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
831800003180000-120-2003-0001020031008<NA>3폐업2폐업20050104<NA><NA><NA><NA><NA>150869서울특별시 영등포구 여의도동 12번지<NA><NA>(주)현대지네트국민일보점2004-01-26 00:00:00I2018-08-31 23:59:59.0위탁급식영업193293.251953447448.342915위탁급식영업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
931800003180000-120-2003-0001120031008<NA>3폐업2폐업20170601<NA><NA><NA><NA>960.07150872서울특별시 영등포구 여의도동 15-21번지서울특별시 영등포구 의사당대로 3 (여의도동)7237(주)현대그린푸드현대캐피탈점2017-06-01 12:51:50I2018-08-31 23:59:59.0위탁급식영업192689.645966447427.72321위탁급식영업00<NA><NA><NA>00000<NA>00N960.07<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
37331800003180000-120-2023-000182023-12-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>104.79150-893서울특별시 영등포구 여의도동 47 여의도자이서울특별시 영등포구 여의동로3길 10, 지하1층 (여의도동, 여의도자이)7324(주)한울에프앤에스 이마트여의도점2024-02-22 09:49:06U2023-12-01 22:04:00.0위탁급식영업193393.096554446218.443828<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37431800003180000-120-2023-000192023-12-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>70.00150-798서울특별시 영등포구 영등포동4가 442 타임스퀘어서울특별시 영등포구 영중로 15, 타임스퀘어 코트야드메리어트서울 타임스퀘어 지하2층 (영등포동4가)7305코트야드메리어트서울 타임스퀘어 직원식당2023-12-27 15:08:48I2022-11-01 22:09:00.0위탁급식영업191385.057392446098.555927<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37531800003180000-120-2023-000202023-12-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2005.55150-873서울특별시 영등포구 여의도동 16-3 한국산업은행서울특별시 영등포구 은행로 14, 한국산업은행 지하1층 (여의도동)7242(주)엘에스씨푸드 한국산업은행2023-12-29 17:57:29I2022-11-01 21:01:00.0위탁급식영업192939.417125447205.313717<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37631800003180000-120-2024-000012024-01-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>616.39150-010서울특별시 영등포구 여의도동 525 브라이튼 여의도서울특별시 영등포구 국제금융로 39, 101동 3층 (여의도동, 브라이튼 여의도)7339브라이튼 여의도2024-01-24 10:23:19I2023-11-30 22:06:00.0위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37731800003180000-120-2024-000022024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA>0237796889716.10150-996서울특별시 영등포구 여의도동 16-1 한국수출입은행빌딩서울특별시 영등포구 은행로 38, 한국수출입은행빌딩 직원식당 8층 (여의도동)7242(주)후니드 한국수출입은행 직원식당 여의도점2024-02-01 17:07:03I2023-12-02 00:03:00.0위탁급식영업193159.124448447376.605815<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37831800003180000-120-2024-000032024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA>02217426331064.00150-872서울특별시 영등포구 여의도동 15-21 현대카드빌딩 1관서울특별시 영등포구 의사당대로 3, 현대카드빌딩 1관 지하1층 (여의도동)7237푸디스트 주식회사 현대카드 본사점2024-02-29 14:37:55I2023-12-03 00:02:00.0위탁급식영업192689.645966447427.72321<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
37931800003180000-120-2024-000042024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>610.24150-827서울특별시 영등포구 대림동 1100-1서울특별시 영등포구 도림천로19길 12-2, 현대건설 기술교육원 구내식당 지하1층 (대림동)7448현대건설 기술교육원 지점2024-03-04 15:57:01I2023-12-03 00:06:00.0위탁급식영업191179.991348442777.411153<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38031800003180000-120-2024-000052024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>0233920455753.00150-102서울특별시 영등포구 양평동2가 23-2 관악고등학교서울특별시 영등포구 영등포로6길 26, 관악고등학교 1층 (양평동2가)7278(주)엘에스씨푸드 관악고등학교2024-03-04 16:06:27I2023-12-03 00:06:00.0위탁급식영업189619.432199446609.119564<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38131800003180000-120-2024-000062024-03-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>693.69150-840서울특별시 영등포구 신길동 176 장훈고등학교서울특별시 영등포구 영등포로64길 26, 장훈고등학교 1,2,3층 (신길동)7316주식회사 이유에프에스 장훈고점2024-03-08 10:02:42I2023-12-02 23:00:00.0위탁급식영업192451.279455445734.869714<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
38231800003180000-120-2024-000072024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>2422.00150-875서울특별시 영등포구 여의도동 20서울특별시 영등포구 여의대로 128, 동관 지하1층 (여의도동)7336(주)디앤오2024-03-27 17:08:14I2023-12-02 22:09:00.0위탁급식영업193674.743726447296.226306<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>