Overview

Dataset statistics

Number of variables44
Number of observations235
Missing cells2678
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.6 KiB
Average record size in memory377.6 B

Variable types

Categorical18
Text7
DateTime4
Unsupported9
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-17987/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (50.6%)Imbalance
영업장주변구분명 is highly imbalanced (78.6%)Imbalance
총인원 is highly imbalanced (72.7%)Imbalance
본사종업원수 is highly imbalanced (72.7%)Imbalance
공장사무직종업원수 is highly imbalanced (72.7%)Imbalance
공장판매직종업원수 is highly imbalanced (72.7%)Imbalance
공장생산직종업원수 is highly imbalanced (72.7%)Imbalance
보증액 is highly imbalanced (72.7%)Imbalance
월세액 is highly imbalanced (72.7%)Imbalance
인허가취소일자 has 235 (100.0%) missing valuesMissing
폐업일자 has 51 (21.7%) missing valuesMissing
휴업시작일자 has 235 (100.0%) missing valuesMissing
휴업종료일자 has 235 (100.0%) missing valuesMissing
재개업일자 has 235 (100.0%) missing valuesMissing
전화번호 has 62 (26.4%) missing valuesMissing
도로명주소 has 97 (41.3%) missing valuesMissing
도로명우편번호 has 99 (42.1%) missing valuesMissing
좌표정보(X) has 19 (8.1%) missing valuesMissing
좌표정보(Y) has 19 (8.1%) missing valuesMissing
여성종사자수 has 150 (63.8%) missing valuesMissing
등급구분명 has 235 (100.0%) missing valuesMissing
건물소유구분명 has 235 (100.0%) missing valuesMissing
다중이용업소여부 has 30 (12.8%) missing valuesMissing
시설총규모 has 30 (12.8%) missing valuesMissing
전통업소지정번호 has 235 (100.0%) missing valuesMissing
전통업소주된음식 has 235 (100.0%) missing valuesMissing
홈페이지 has 235 (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
등급구분명 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
여성종사자수 has 75 (31.9%) zerosZeros

Reproduction

Analysis started2024-04-29 19:32:13.261297
Analysis finished2024-04-29 19:32:14.111416
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3100000
235 

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 235
100.0%

Length

2024-04-30T04:32:14.167395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:14.244997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 235
100.0%

관리번호
Text

UNIQUE 

Distinct235
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:32:14.385549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5170
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

Unique235 ?
Unique (%)100.0%

Sample

1st row3100000-120-2003-00001
2nd row3100000-120-2003-00002
3rd row3100000-120-2003-00003
4th row3100000-120-2003-00004
5th row3100000-120-2003-00005
ValueCountFrequency (%)
3100000-120-2003-00001 1
 
0.4%
3100000-120-2015-00005 1
 
0.4%
3100000-120-2017-00007 1
 
0.4%
3100000-120-2014-00005 1
 
0.4%
3100000-120-2014-00006 1
 
0.4%
3100000-120-2014-00007 1
 
0.4%
3100000-120-2014-00008 1
 
0.4%
3100000-120-2014-00009 1
 
0.4%
3100000-120-2014-00010 1
 
0.4%
3100000-120-2014-00011 1
 
0.4%
Other values (225) 225
95.7%
2024-04-30T04:32:14.665455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2655
51.4%
- 705
 
13.6%
1 626
 
12.1%
2 565
 
10.9%
3 355
 
6.9%
4 60
 
1.2%
5 52
 
1.0%
6 43
 
0.8%
7 39
 
0.8%
9 36
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4465
86.4%
Dash Punctuation 705
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2655
59.5%
1 626
 
14.0%
2 565
 
12.7%
3 355
 
8.0%
4 60
 
1.3%
5 52
 
1.2%
6 43
 
1.0%
7 39
 
0.9%
9 36
 
0.8%
8 34
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 705
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2655
51.4%
- 705
 
13.6%
1 626
 
12.1%
2 565
 
10.9%
3 355
 
6.9%
4 60
 
1.2%
5 52
 
1.0%
6 43
 
0.8%
7 39
 
0.8%
9 36
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2655
51.4%
- 705
 
13.6%
1 626
 
12.1%
2 565
 
10.9%
3 355
 
6.9%
4 60
 
1.2%
5 52
 
1.0%
6 43
 
0.8%
7 39
 
0.8%
9 36
 
0.7%

인허가일자
Date

Distinct181
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2003-05-23 00:00:00
Maximum2024-03-18 00:00:00
2024-04-30T04:32:14.808738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:14.925285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
3
184 
1
51 

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 (%)
3 184
78.3%
1 51
 
21.7%

Length

2024-04-30T04:32:15.028696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:15.097588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 184
78.3%
1 51
 
21.7%

영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
184 
영업/정상
51 

Length

Max length5
Median length2
Mean length2.6510638
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 184
78.3%
영업/정상 51
 
21.7%

Length

2024-04-30T04:32:15.189875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:15.270414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 184
78.3%
영업/정상 51
 
21.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2
184 
1
51 

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 (%)
2 184
78.3%
1 51
 
21.7%

Length

2024-04-30T04:32:15.344903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:15.416199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 184
78.3%
1 51
 
21.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
폐업
184 
영업
51 

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 184
78.3%
영업 51
 
21.7%

Length

2024-04-30T04:32:15.493341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:15.564857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 184
78.3%
영업 51
 
21.7%

폐업일자
Date

MISSING 

Distinct145
Distinct (%)78.8%
Missing51
Missing (%)21.7%
Memory size2.0 KiB
Minimum2004-06-24 00:00:00
Maximum2024-02-26 00:00:00
2024-04-30T04:32:15.673847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:15.796124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

전화번호
Text

MISSING 

Distinct142
Distinct (%)82.1%
Missing62
Missing (%)26.4%
Memory size2.0 KiB
2024-04-30T04:32:16.029876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.086705
Min length7

Characters and Unicode

Total characters1745
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

Unique130 ?
Unique (%)75.1%

Sample

1st row0220371578
2nd row02 9726717
3rd row02 9973126
4th row02 9501430
5th row9754327
ValueCountFrequency (%)
02 96
30.0%
0233920455 10
 
3.1%
33920455 8
 
2.5%
070 5
 
1.6%
20276080 4
 
1.2%
996 4
 
1.2%
7691 4
 
1.2%
5738215 4
 
1.2%
930 4
 
1.2%
950 4
 
1.2%
Other values (161) 177
55.3%
2024-04-30T04:32:16.376079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 288
16.5%
2 245
14.0%
9 216
12.4%
202
11.6%
3 155
8.9%
5 143
8.2%
7 135
7.7%
4 97
 
5.6%
1 94
 
5.4%
6 89
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1543
88.4%
Space Separator 202
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 288
18.7%
2 245
15.9%
9 216
14.0%
3 155
10.0%
5 143
9.3%
7 135
8.7%
4 97
 
6.3%
1 94
 
6.1%
6 89
 
5.8%
8 81
 
5.2%
Space Separator
ValueCountFrequency (%)
202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1745
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 288
16.5%
2 245
14.0%
9 216
12.4%
202
11.6%
3 155
8.9%
5 143
8.2%
7 135
7.7%
4 97
 
5.6%
1 94
 
5.4%
6 89
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1745
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 288
16.5%
2 245
14.0%
9 216
12.4%
202
11.6%
3 155
8.9%
5 143
8.2%
7 135
7.7%
4 97
 
5.6%
1 94
 
5.4%
6 89
 
5.1%

소재지면적
Text

Distinct198
Distinct (%)85.0%
Missing2
Missing (%)0.9%
Memory size2.0 KiB
2024-04-30T04:32:16.672959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.1502146
Min length4

Characters and Unicode

Total characters1433
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

Unique169 ?
Unique (%)72.5%

Sample

1st row254.67
2nd row189.00
3rd row764.28
4th row822.00
5th row523.24
ValueCountFrequency (%)
622.00 4
 
1.7%
203.10 3
 
1.3%
263.00 3
 
1.3%
178.70 3
 
1.3%
210.00 3
 
1.3%
1,005.00 2
 
0.9%
1,413.00 2
 
0.9%
220.18 2
 
0.9%
1,210.30 2
 
0.9%
452.59 2
 
0.9%
Other values (188) 207
88.8%
2024-04-30T04:32:17.122425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 286
20.0%
. 233
16.3%
2 157
11.0%
1 156
10.9%
4 95
 
6.6%
6 93
 
6.5%
7 91
 
6.4%
5 88
 
6.1%
3 82
 
5.7%
8 74
 
5.2%
Other values (2) 78
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1174
81.9%
Other Punctuation 259
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 286
24.4%
2 157
13.4%
1 156
13.3%
4 95
 
8.1%
6 93
 
7.9%
7 91
 
7.8%
5 88
 
7.5%
3 82
 
7.0%
8 74
 
6.3%
9 52
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 233
90.0%
, 26
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1433
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 286
20.0%
. 233
16.3%
2 157
11.0%
1 156
10.9%
4 95
 
6.6%
6 93
 
6.5%
7 91
 
6.4%
5 88
 
6.1%
3 82
 
5.7%
8 74
 
5.2%
Other values (2) 78
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 286
20.0%
. 233
16.3%
2 157
11.0%
1 156
10.9%
4 95
 
6.6%
6 93
 
6.5%
7 91
 
6.4%
5 88
 
6.1%
3 82
 
5.7%
8 74
 
5.2%
Other values (2) 78
 
5.4%

소재지우편번호
Text

Distinct61
Distinct (%)26.2%
Missing2
Missing (%)0.9%
Memory size2.0 KiB
2024-04-30T04:32:17.317071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0987124
Min length6

Characters and Unicode

Total characters1421
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

Unique23 ?
Unique (%)9.9%

Sample

1st row139200
2nd row139865
3rd row139865
4th row139200
5th row139863
ValueCountFrequency (%)
139869 19
 
8.2%
139200 15
 
6.4%
139800 12
 
5.2%
139865 11
 
4.7%
139838 10
 
4.3%
139831 9
 
3.9%
139050 9
 
3.9%
139230 9
 
3.9%
139804 8
 
3.4%
139240 8
 
3.4%
Other values (51) 123
52.8%
2024-04-30T04:32:17.598104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 277
19.5%
9 272
19.1%
1 255
17.9%
8 183
12.9%
0 127
8.9%
2 87
 
6.1%
6 59
 
4.2%
4 54
 
3.8%
5 47
 
3.3%
7 37
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1398
98.4%
Dash Punctuation 23
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 277
19.8%
9 272
19.5%
1 255
18.2%
8 183
13.1%
0 127
9.1%
2 87
 
6.2%
6 59
 
4.2%
4 54
 
3.9%
5 47
 
3.4%
7 37
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1421
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 277
19.5%
9 272
19.1%
1 255
17.9%
8 183
12.9%
0 127
8.9%
2 87
 
6.1%
6 59
 
4.2%
4 54
 
3.8%
5 47
 
3.3%
7 37
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 277
19.5%
9 272
19.1%
1 255
17.9%
8 183
12.9%
0 127
8.9%
2 87
 
6.1%
6 59
 
4.2%
4 54
 
3.8%
5 47
 
3.3%
7 37
 
2.6%

지번주소
Text

Distinct167
Distinct (%)71.7%
Missing2
Missing (%)0.9%
Memory size2.0 KiB
2024-04-30T04:32:17.821700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length24.416309
Min length17

Characters and Unicode

Total characters5689
Distinct characters162
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127 ?
Unique (%)54.5%

Sample

1st row서울특별시 노원구 상계동 738번지
2nd row서울특별시 노원구 중계동 511-3번지 중원중학교내
3rd row서울특별시 노원구 중계동 514-2번지
4th row서울특별시 노원구 상계동 761-1번지
5th row서울특별시 노원구 중계동 506-1번지
ValueCountFrequency (%)
서울특별시 233
21.6%
노원구 233
21.6%
상계동 72
 
6.7%
중계동 44
 
4.1%
공릉동 43
 
4.0%
월계동 40
 
3.7%
하계동 34
 
3.2%
산 11
 
1.0%
648번지 8
 
0.7%
738번지 8
 
0.7%
Other values (198) 351
32.6%
2024-04-30T04:32:18.162605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1046
18.4%
서 250
 
4.4%
원 249
 
4.4%
울 246
 
4.3%
동 240
 
4.2%
노 239
 
4.2%
시 238
 
4.2%
구 236
 
4.1%
별 235
 
4.1%
특 235
 
4.1%
Other values (152) 2475
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3727
65.5%
Space Separator 1046
 
18.4%
Decimal Number 817
 
14.4%
Dash Punctuation 94
 
1.7%
Other Punctuation 3
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 250
 
6.7%
원 249
 
6.7%
울 246
 
6.6%
동 240
 
6.4%
노 239
 
6.4%
시 238
 
6.4%
구 236
 
6.3%
별 235
 
6.3%
특 235
 
6.3%
계 211
 
5.7%
Other values (137) 1348
36.2%
Decimal Number
ValueCountFrequency (%)
1 157
19.2%
2 109
13.3%
3 91
11.1%
6 87
10.6%
7 83
10.2%
4 73
8.9%
8 73
8.9%
5 65
8.0%
0 46
 
5.6%
9 33
 
4.0%
Space Separator
ValueCountFrequency (%)
1046
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3727
65.5%
Common 1962
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 250
 
6.7%
원 249
 
6.7%
울 246
 
6.6%
동 240
 
6.4%
노 239
 
6.4%
시 238
 
6.4%
구 236
 
6.3%
별 235
 
6.3%
특 235
 
6.3%
계 211
 
5.7%
Other values (137) 1348
36.2%
Common
ValueCountFrequency (%)
1046
53.3%
1 157
 
8.0%
2 109
 
5.6%
- 94
 
4.8%
3 91
 
4.6%
6 87
 
4.4%
7 83
 
4.2%
4 73
 
3.7%
8 73
 
3.7%
5 65
 
3.3%
Other values (5) 84
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3727
65.5%
ASCII 1962
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1046
53.3%
1 157
 
8.0%
2 109
 
5.6%
- 94
 
4.8%
3 91
 
4.6%
6 87
 
4.4%
7 83
 
4.2%
4 73
 
3.7%
8 73
 
3.7%
5 65
 
3.3%
Other values (5) 84
 
4.3%
Hangul
ValueCountFrequency (%)
서 250
 
6.7%
원 249
 
6.7%
울 246
 
6.6%
동 240
 
6.4%
노 239
 
6.4%
시 238
 
6.4%
구 236
 
6.3%
별 235
 
6.3%
특 235
 
6.3%
계 211
 
5.7%
Other values (137) 1348
36.2%

도로명주소
Text

MISSING 

Distinct114
Distinct (%)82.6%
Missing97
Missing (%)41.3%
Memory size2.0 KiB
2024-04-30T04:32:18.363437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length32.507246
Min length23

Characters and Unicode

Total characters4486
Distinct characters166
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)70.3%

Sample

1st row서울특별시 노원구 동일로204가길 34 (중계동)
2nd row서울특별시 노원구 노원로 330 (중계동)
3rd row서울특별시 노원구 공릉로 257 (공릉동)
4th row서울특별시 노원구 동일로 1414 (상계동,롯데백화점)
5th row서울특별시 노원구 덕릉로82길 64 (중계동,재현고등학교)
ValueCountFrequency (%)
서울특별시 138
 
16.3%
노원구 138
 
16.3%
상계동 45
 
5.3%
공릉로 24
 
2.8%
중계동 24
 
2.8%
공릉동 23
 
2.7%
월계동 21
 
2.5%
하계동 19
 
2.2%
1층 17
 
2.0%
동일로 17
 
2.0%
Other values (154) 383
45.1%
2024-04-30T04:32:18.663047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
711
 
15.8%
동 182
 
4.1%
노 160
 
3.6%
원 156
 
3.5%
서 153
 
3.4%
울 150
 
3.3%
계 145
 
3.2%
시 143
 
3.2%
특 140
 
3.1%
별 140
 
3.1%
Other values (156) 2406
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2841
63.3%
Space Separator 711
 
15.8%
Decimal Number 543
 
12.1%
Open Punctuation 139
 
3.1%
Close Punctuation 139
 
3.1%
Other Punctuation 111
 
2.5%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 182
 
6.4%
노 160
 
5.6%
원 156
 
5.5%
서 153
 
5.4%
울 150
 
5.3%
계 145
 
5.1%
시 143
 
5.0%
특 140
 
4.9%
별 140
 
4.9%
구 140
 
4.9%
Other values (141) 1332
46.9%
Decimal Number
ValueCountFrequency (%)
1 125
23.0%
2 115
21.2%
4 86
15.8%
3 57
10.5%
6 41
 
7.6%
5 40
 
7.4%
7 30
 
5.5%
8 21
 
3.9%
0 18
 
3.3%
9 10
 
1.8%
Space Separator
ValueCountFrequency (%)
711
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Close Punctuation
ValueCountFrequency (%)
) 139
100.0%
Other Punctuation
ValueCountFrequency (%)
, 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2841
63.3%
Common 1645
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 182
 
6.4%
노 160
 
5.6%
원 156
 
5.5%
서 153
 
5.4%
울 150
 
5.3%
계 145
 
5.1%
시 143
 
5.0%
특 140
 
4.9%
별 140
 
4.9%
구 140
 
4.9%
Other values (141) 1332
46.9%
Common
ValueCountFrequency (%)
711
43.2%
( 139
 
8.4%
) 139
 
8.4%
1 125
 
7.6%
2 115
 
7.0%
, 111
 
6.7%
4 86
 
5.2%
3 57
 
3.5%
6 41
 
2.5%
5 40
 
2.4%
Other values (5) 81
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2841
63.3%
ASCII 1645
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
711
43.2%
( 139
 
8.4%
) 139
 
8.4%
1 125
 
7.6%
2 115
 
7.0%
, 111
 
6.7%
4 86
 
5.2%
3 57
 
3.5%
6 41
 
2.5%
5 40
 
2.4%
Other values (5) 81
 
4.9%
Hangul
ValueCountFrequency (%)
동 182
 
6.4%
노 160
 
5.6%
원 156
 
5.5%
서 153
 
5.4%
울 150
 
5.3%
계 145
 
5.1%
시 143
 
5.0%
특 140
 
4.9%
별 140
 
4.9%
구 140
 
4.9%
Other values (141) 1332
46.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)30.1%
Missing99
Missing (%)42.1%
Infinite0
Infinite (%)0.0%
Mean1772.3235
Minimum1602
Maximum1906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:32:18.792725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1602
5-th percentile1605.75
Q11721
median1783
Q31811
95-th percentile1879
Maximum1906
Range304
Interquartile range (IQR)90

Descriptive statistics

Standard deviation77.118944
Coefficient of variation (CV)0.043512904
Kurtosis-0.16374249
Mean1772.3235
Median Absolute Deviation (MAD)43
Skewness-0.41955055
Sum241036
Variance5947.3316
MonotonicityNot monotonic
2024-04-30T04:32:18.903409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1878 11
 
4.7%
1797 8
 
3.4%
1761 8
 
3.4%
1832 7
 
3.0%
1602 7
 
3.0%
1810 7
 
3.0%
1687 7
 
3.0%
1783 6
 
2.6%
1785 5
 
2.1%
1906 5
 
2.1%
Other values (31) 65
27.7%
(Missing) 99
42.1%
ValueCountFrequency (%)
1602 7
3.0%
1607 1
 
0.4%
1613 2
 
0.9%
1627 1
 
0.4%
1679 1
 
0.4%
1682 1
 
0.4%
1687 7
3.0%
1688 1
 
0.4%
1689 3
1.3%
1695 3
1.3%
ValueCountFrequency (%)
1906 5
2.1%
1890 1
 
0.4%
1882 1
 
0.4%
1878 11
4.7%
1874 4
 
1.7%
1862 1
 
0.4%
1858 1
 
0.4%
1832 7
3.0%
1830 1
 
0.4%
1811 4
 
1.7%

사업장명
Text

Distinct231
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T04:32:19.089597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length19
Mean length14.089362
Min length3

Characters and Unicode

Total characters3311
Distinct characters254
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)96.6%

Sample

1st row(주)세호푸드(상계고등학교)
2nd row(주)한스케더링(중원중학교)
3rd row대진식품사업부(대진여고)
4th row서울캐터링서비스(주)(상계백병원)
5th row(주)선진케이터링(건영백화점)
ValueCountFrequency (%)
주)엘에스씨푸드 15
 
4.9%
주)정오아카데미 7
 
2.3%
주)아워홈 4
 
1.3%
가람푸드써비스(주 4
 
1.3%
주)웰스팜 3
 
1.0%
주식회사 3
 
1.0%
서울여대점 3
 
1.0%
가람푸드써비스 3
 
1.0%
참푸드시스템 3
 
1.0%
대진고등학교점 2
 
0.7%
Other values (245) 260
84.7%
2024-04-30T04:32:19.401771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 205
 
6.2%
) 205
 
6.2%
주 173
 
5.2%
스 111
 
3.4%
점 102
 
3.1%
드 100
 
3.0%
고 98
 
3.0%
푸 94
 
2.8%
학 89
 
2.7%
에 80
 
2.4%
Other values (244) 2054
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2776
83.8%
Open Punctuation 205
 
6.2%
Close Punctuation 205
 
6.2%
Space Separator 72
 
2.2%
Dash Punctuation 21
 
0.6%
Uppercase Letter 20
 
0.6%
Decimal Number 7
 
0.2%
Other Punctuation 4
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 173
 
6.2%
스 111
 
4.0%
점 102
 
3.7%
드 100
 
3.6%
고 98
 
3.5%
푸 94
 
3.4%
학 89
 
3.2%
에 80
 
2.9%
교 78
 
2.8%
대 54
 
1.9%
Other values (224) 1797
64.7%
Uppercase Letter
ValueCountFrequency (%)
J 5
25.0%
C 5
25.0%
S 3
15.0%
P 2
 
10.0%
I 1
 
5.0%
A 1
 
5.0%
L 1
 
5.0%
F 1
 
5.0%
D 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
8 2
28.6%
1 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 1
25.0%
? 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 205
100.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2777
83.9%
Common 514
 
15.5%
Latin 20
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 173
 
6.2%
스 111
 
4.0%
점 102
 
3.7%
드 100
 
3.6%
고 98
 
3.5%
푸 94
 
3.4%
학 89
 
3.2%
에 80
 
2.9%
교 78
 
2.8%
대 54
 
1.9%
Other values (225) 1798
64.7%
Common
ValueCountFrequency (%)
( 205
39.9%
) 205
39.9%
72
 
14.0%
- 21
 
4.1%
2 4
 
0.8%
8 2
 
0.4%
. 2
 
0.4%
1 1
 
0.2%
, 1
 
0.2%
? 1
 
0.2%
Latin
ValueCountFrequency (%)
J 5
25.0%
C 5
25.0%
S 3
15.0%
P 2
 
10.0%
I 1
 
5.0%
A 1
 
5.0%
L 1
 
5.0%
F 1
 
5.0%
D 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2776
83.8%
ASCII 534
 
16.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 205
38.4%
) 205
38.4%
72
 
13.5%
- 21
 
3.9%
J 5
 
0.9%
C 5
 
0.9%
2 4
 
0.7%
S 3
 
0.6%
P 2
 
0.4%
8 2
 
0.4%
Other values (9) 10
 
1.9%
Hangul
ValueCountFrequency (%)
주 173
 
6.2%
스 111
 
4.0%
점 102
 
3.7%
드 100
 
3.6%
고 98
 
3.5%
푸 94
 
3.4%
학 89
 
3.2%
에 80
 
2.9%
교 78
 
2.8%
대 54
 
1.9%
Other values (224) 1797
64.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

Distinct197
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2004-04-20 00:00:00
Maximum2024-04-23 15:01:12
2024-04-30T04:32:19.508266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:19.619031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
I
172 
U
63 

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 172
73.2%
U 63
 
26.8%

Length

2024-04-30T04:32:19.726051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:19.796685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 172
73.2%
u 63
 
26.8%

데이터갱신일자
Date

Distinct68
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:09:00
2024-04-30T04:32:20.060460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:32:20.164521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
위탁급식영업
235 

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 235
100.0%

Length

2024-04-30T04:32:20.271719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:20.355509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 235
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)39.8%
Missing19
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean205931.85
Minimum204160.91
Maximum209368.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:32:20.466636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204160.91
5-th percentile204607.27
Q1205057.66
median205869.85
Q3206600.02
95-th percentile207918.32
Maximum209368.94
Range5208.0212
Interquartile range (IQR)1542.3533

Descriptive statistics

Standard deviation1087.5626
Coefficient of variation (CV)0.0052811771
Kurtosis0.4437125
Mean205931.85
Median Absolute Deviation (MAD)785.78493
Skewness0.73315004
Sum44481280
Variance1182792.4
MonotonicityNot monotonic
2024-04-30T04:32:20.587343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206503.621729317 11
 
4.7%
207918.320414714 10
 
4.3%
204790.424786507 10
 
4.3%
204868.290334022 10
 
4.3%
205084.063363624 9
 
3.8%
204637.502775824 8
 
3.4%
206981.454072644 7
 
3.0%
206506.856524902 7
 
3.0%
205869.848293189 6
 
2.6%
204387.387609735 6
 
2.6%
Other values (76) 132
56.2%
(Missing) 19
 
8.1%
ValueCountFrequency (%)
204160.914455692 1
 
0.4%
204235.465605799 1
 
0.4%
204387.387609735 6
2.6%
204454.974085477 2
 
0.9%
204521.596923347 1
 
0.4%
204635.833855802 2
 
0.9%
204637.502775824 8
3.4%
204655.450296645 2
 
0.9%
204683.105183962 3
 
1.3%
204745.470516867 1
 
0.4%
ValueCountFrequency (%)
209368.935678 1
 
0.4%
209288.472624641 3
 
1.3%
209221.923150049 1
 
0.4%
208011.354088636 1
 
0.4%
207918.320414714 10
4.3%
207337.782859518 1
 
0.4%
207255.005556152 5
2.1%
207141.325803475 1
 
0.4%
207118.871795138 2
 
0.9%
207070.814921171 2
 
0.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)39.8%
Missing19
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean460153.39
Minimum456950.15
Maximum464506.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:32:20.696150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456950.15
5-th percentile457555.44
Q1458749.28
median459996.38
Q3461103.15
95-th percentile463435.31
Maximum464506.65
Range7556.4938
Interquartile range (IQR)2353.8737

Descriptive statistics

Standard deviation1711.8046
Coefficient of variation (CV)0.0037200738
Kurtosis0.041029028
Mean460153.39
Median Absolute Deviation (MAD)1243.4824
Skewness0.66989441
Sum99393133
Variance2930275
MonotonicityNot monotonic
2024-04-30T04:32:20.837312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
458967.060918506 11
 
4.7%
458383.983421656 10
 
4.3%
458749.280581727 10
 
4.3%
461103.154307129 10
 
4.3%
461823.993026614 9
 
3.8%
464502.030304529 8
 
3.4%
458960.471391303 7
 
3.0%
458654.259607784 7
 
3.0%
460413.071542001 6
 
2.6%
458716.592442905 6
 
2.6%
Other values (76) 132
56.2%
(Missing) 19
 
8.1%
ValueCountFrequency (%)
456950.152059544 1
 
0.4%
457477.154924921 4
1.7%
457486.206509046 5
2.1%
457512.040697156 1
 
0.4%
457569.903285767 1
 
0.4%
457740.184614927 1
 
0.4%
458050.925453764 1
 
0.4%
458271.863468723 1
 
0.4%
458289.069882291 2
 
0.9%
458333.989216339 4
1.7%
ValueCountFrequency (%)
464506.645890474 1
 
0.4%
464502.030304529 8
3.4%
463943.786866443 1
 
0.4%
463544.675453894 1
 
0.4%
463398.855128598 3
 
1.3%
463241.435236829 1
 
0.4%
462696.752241068 2
 
0.9%
462625.053235914 3
 
1.3%
462218.367284872 2
 
0.9%
462165.884423249 1
 
0.4%

위생업태명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
위탁급식영업
205 
<NA>
30 

Length

Max length6
Median length6
Mean length5.7446809
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 205
87.2%
<NA> 30
 
12.8%

Length

2024-04-30T04:32:20.972489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:21.067929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 205
87.2%
na 30
 
12.8%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
151 
0
76 
1
 
5
2
 
2
10
 
1

Length

Max length4
Median length4
Mean length2.9319149
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 151
64.3%
0 76
32.3%
1 5
 
2.1%
2 2
 
0.9%
10 1
 
0.4%

Length

2024-04-30T04:32:21.154920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:21.251667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
64.3%
0 76
32.3%
1 5
 
2.1%
2 2
 
0.9%
10 1
 
0.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)8.2%
Missing150
Missing (%)63.8%
Infinite0
Infinite (%)0.0%
Mean0.65882353
Minimum0
Maximum14
Zeros75
Zeros (%)31.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:32:21.339096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5192258
Coefficient of variation (CV)3.8238249
Kurtosis17.912238
Mean0.65882353
Median Absolute Deviation (MAD)0
Skewness4.2671698
Sum56
Variance6.3464986
MonotonicityNot monotonic
2024-04-30T04:32:21.432133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 75
31.9%
1 5
 
2.1%
10 1
 
0.4%
14 1
 
0.4%
6 1
 
0.4%
13 1
 
0.4%
8 1
 
0.4%
(Missing) 150
63.8%
ValueCountFrequency (%)
0 75
31.9%
1 5
 
2.1%
6 1
 
0.4%
8 1
 
0.4%
10 1
 
0.4%
13 1
 
0.4%
14 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
13 1
 
0.4%
10 1
 
0.4%
8 1
 
0.4%
6 1
 
0.4%
1 5
 
2.1%
0 75
31.9%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
219 
아파트지역
 
12
기타
 
3
주택가주변
 
1

Length

Max length5
Median length4
Mean length4.0297872
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 219
93.2%
아파트지역 12
 
5.1%
기타 3
 
1.3%
주택가주변 1
 
0.4%

Length

2024-04-30T04:32:21.531212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:21.623307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 219
93.2%
아파트지역 12
 
5.1%
기타 3
 
1.3%
주택가주변 1
 
0.4%

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

급수시설구분명
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
163 
상수도전용
72 

Length

Max length5
Median length4
Mean length4.306383
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 163
69.4%
상수도전용 72
30.6%

Length

2024-04-30T04:32:21.716174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:21.797042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 163
69.4%
상수도전용 72
30.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:21.876260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:21.953838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.032247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.103829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.187759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.261799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.338172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.411850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.508761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.588257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.665785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.748832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
224 
0
 
11

Length

Max length4
Median length4
Mean length3.8595745
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> 224
95.3%
0 11
 
4.7%

Length

2024-04-30T04:32:22.849029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:32:22.943259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 224
95.3%
0 11
 
4.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing30
Missing (%)12.8%
Memory size602.0 B
False
205 
(Missing)
30 
ValueCountFrequency (%)
False 205
87.2%
(Missing) 30
 
12.8%
2024-04-30T04:32:23.011627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)88.3%
Missing30
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean464.38263
Minimum0
Maximum2077
Zeros2
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-04-30T04:32:23.103599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile64.776
Q1198.43
median288
Q3635.7
95-th percentile1210.3
Maximum2077
Range2077
Interquartile range (IQR)437.27

Descriptive statistics

Standard deviation393.109
Coefficient of variation (CV)0.84651961
Kurtosis2.2683379
Mean464.38263
Median Absolute Deviation (MAD)156.96
Skewness1.5015469
Sum95198.44
Variance154534.69
MonotonicityNot monotonic
2024-04-30T04:32:23.234032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263.0 3
 
1.3%
203.1 3
 
1.3%
178.7 3
 
1.3%
1413.0 2
 
0.9%
1127.0 2
 
0.9%
1128.75 2
 
0.9%
143.95 2
 
0.9%
1005.0 2
 
0.9%
0.0 2
 
0.9%
448.0 2
 
0.9%
Other values (171) 182
77.4%
(Missing) 30
 
12.8%
ValueCountFrequency (%)
0.0 2
0.9%
13.9 1
0.4%
15.0 1
0.4%
19.5 1
0.4%
26.4 1
0.4%
31.5 1
0.4%
32.0 1
0.4%
52.68 1
0.4%
56.0 1
0.4%
63.0 1
0.4%
ValueCountFrequency (%)
2077.0 1
0.4%
1978.0 1
0.4%
1836.74 1
0.4%
1433.0 2
0.9%
1413.0 2
0.9%
1404.63 2
0.9%
1234.9 1
0.4%
1210.3 2
0.9%
1161.87 1
0.4%
1149.1 1
0.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing235
Missing (%)100.0%
Memory size2.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031000003100000-120-2003-0000120030523<NA>3폐업2폐업20041118<NA><NA><NA>0220371578254.67139200서울특별시 노원구 상계동 738번지<NA><NA>(주)세호푸드(상계고등학교)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업204868.290334461103.154307위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N254.67<NA><NA><NA>
131000003100000-120-2003-0000220030529<NA>3폐업2폐업20100224<NA><NA><NA>02 9726717189.00139865서울특별시 노원구 중계동 511-3번지 중원중학교내<NA><NA>(주)한스케더링(중원중학교)2004-06-08 00:00:00I2018-08-31 23:59:59.0위탁급식영업205941.781523460182.206185위탁급식영업00아파트지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N189.0<NA><NA><NA>
231000003100000-120-2003-0000320030530<NA>3폐업2폐업20120113<NA><NA><NA>02 9973126764.28139865서울특별시 노원구 중계동 514-2번지<NA><NA>대진식품사업부(대진여고)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업205869.848293460413.071542위탁급식영업00아파트지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N764.28<NA><NA><NA>
331000003100000-120-2003-0000420030602<NA>3폐업2폐업20091007<NA><NA><NA>02 9501430822.00139200서울특별시 노원구 상계동 761-1번지<NA><NA>서울캐터링서비스(주)(상계백병원)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업205488.916466460701.027581위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N822.0<NA><NA><NA>
431000003100000-120-2003-0000520030604<NA>3폐업2폐업20100927<NA><NA><NA>9754327523.24139863서울특별시 노원구 중계동 506-1번지<NA><NA>(주)선진케이터링(건영백화점)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업205645.891969459609.01251위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N523.24<NA><NA><NA>
531000003100000-120-2003-0000620030612<NA>3폐업2폐업20091231<NA><NA><NA>02 9779324225.00139804서울특별시 노원구 공릉동 481번지<NA><NA>에렉스에프앤비(주)한천중학교2007-05-28 00:00:00I2018-08-31 23:59:59.0위탁급식영업206338.606054458756.513844위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N225.0<NA><NA><NA>
631000003100000-120-2003-0000720030619<NA>3폐업2폐업20060320<NA><NA><NA>9374740135.94139800서울특별시 노원구 공릉동 250번지<NA><NA>(주)이바돔(공릉중학교)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업207337.78286457740.184615위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N135.94<NA><NA><NA>
731000003100000-120-2003-0000920030623<NA>3폐업2폐업20100218<NA><NA><NA>9485380446.90139852서울특별시 노원구 월계동 805-5번지<NA><NA>(주)미래캐터링(신창중학교)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업204160.914456458440.047419위탁급식영업00아파트지역<NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N446.9<NA><NA><NA>
831000003100000-120-2003-0001020030623<NA>3폐업2폐업20040625<NA><NA><NA>33916771445.70139859서울특별시 노원구 중계동 369-3번지<NA><NA>(주)미래캐터링(미래산업과학고)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업206897.710524461851.659587위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N445.7<NA><NA><NA>
931000003100000-120-2003-0001120030623<NA>3폐업2폐업20100512<NA><NA><NA>9770798209.53139842서울특별시 노원구 월계동 321-7번지<NA><NA>(주)미래캐터링(녹천중학교)2004-06-04 00:00:00I2018-08-31 23:59:59.0위탁급식영업205431.888051458765.299892위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N209.53<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
22531000003100000-120-2023-000032023-02-28<NA>3폐업2폐업2024-02-23<NA><NA><NA><NA>622.00139-804서울특별시 노원구 공릉동 481-3 동산정보산업고등학교서울특별시 노원구 공릉로 257, 동산정보산업고등학교 (공릉동)1832세종에프앤에스(주)-서울동산고2024-02-23 13:14:19U2023-12-01 22:05:00.0위탁급식영업206506.856525458654.259608<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22631000003100000-120-2023-000042023-03-06<NA>3폐업2폐업2024-02-23<NA><NA><NA><NA>1210.30139-827서울특별시 노원구 상계동 696 용화여자고등학교서울특별시 노원구 동일로 1461, 용화여자고등학교 (상계동)1687세종에프앤에스(주)-용화여고2024-02-23 13:11:09U2023-12-01 22:05:00.0위탁급식영업205084.063364461823.993027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22731000003100000-120-2023-000052023-03-30<NA>1영업/정상1영업<NA><NA><NA><NA>02 975955589.26139-230서울특별시 노원구 하계동 357 구립하계실버센터서울특별시 노원구 한글비석로 4, 구립하계실버센터 지하1층 (하계동)1862구립하계실버센터2023-03-30 15:29:41I2022-12-04 00:01:00.0위탁급식영업205596.695084458975.496775<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22831000003100000-120-2023-000062023-04-14<NA>1영업/정상1영업<NA><NA><NA><NA>02 996 7691465.37139-774서울특별시 노원구 공릉동 126 서울여자대학교서울특별시 노원구 화랑로 621, 서울여자대학교 샬롬하우스 131호 (공릉동)1797(주)정오아카데미 서울여대점 기숙사식당2023-04-14 13:21:36I2022-12-03 23:06:00.0위탁급식영업207918.320415458383.983422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22931000003100000-120-2023-000072023-04-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>513.71139-774서울특별시 노원구 공릉동 126 서울여자대학교서울특별시 노원구 화랑로 621, 서울여자대학교 바롬인성교육관 205호 (공릉동)1797(주)정오아카데미 서울여대점 바롬인성교육관 식당2023-04-14 13:25:28I2022-12-03 23:06:00.0위탁급식영업207918.320415458383.983422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23031000003100000-120-2024-000012024-01-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>144.00139-229서울특별시 노원구 중계동 311-14 서울노원우체국서울특별시 노원구 중계로 123, 서울노원우체국 (중계동)1740(주)대흥푸드2024-01-16 13:13:03I2023-11-30 23:08:00.0위탁급식영업207070.814921460437.410422<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23131000003100000-120-2024-000022024-02-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 950 35000.00139-827서울특별시 노원구 상계동 696 용화여자고등학교서울특별시 노원구 동일로 1461, 용화여자고등학교 (상계동)1687용화여자고등학교 급식실2024-02-26 13:55:22I2023-12-01 22:08:00.0위탁급식영업205084.063364461823.993027<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23231000003100000-120-2024-000032024-02-26<NA>1영업/정상1영업<NA><NA><NA><NA>02 33920455622.00139-804서울특별시 노원구 공릉동 481-3 동산정보산업고등학교서울특별시 노원구 공릉로 257, 동산정보산업고등학교 (공릉동)1832서울동산고등학교2024-02-26 15:48:05I2023-12-01 22:08:00.0위탁급식영업206506.856525458654.259608<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23331000003100000-120-2024-000042024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA>02 996 76911071.00139-860서울특별시 노원구 중계동 313 서라벌고등학교서울특별시 노원구 한글비석로5길 18, 서라벌고등학교 (중계동)1745(주)정오아카데미 서라벌고등학교점2024-03-04 13:12:07I2023-12-03 00:06:00.0위탁급식영업206600.017945460307.853841<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23431000003100000-120-2024-000052024-03-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>585.23139-230서울특별시 노원구 하계동 산 16-38 혜성여자고등학교서울특별시 노원구 노원로16길 2, 혜성여자고등학교 1층 (하계동)1749세종에프앤에스(주)-혜성여고2024-03-18 17:52:32I2023-12-02 22:00:00.0위탁급식영업206405.396339459857.014883<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>