Overview

Dataset statistics

Number of variables44
Number of observations150
Missing cells1526
Missing cells (%)23.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory55.2 KiB
Average record size in memory376.9 B

Variable types

Categorical21
Text6
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18001/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
소재지우편번호 has a high cardinality: 51 distinct valuesHigh cardinality
여성종사자수 is highly imbalanced (67.2%)Imbalance
영업장주변구분명 is highly imbalanced (83.7%)Imbalance
등급구분명 is highly imbalanced (72.8%)Imbalance
총인원 is highly imbalanced (94.2%)Imbalance
본사종업원수 is highly imbalanced (94.2%)Imbalance
공장사무직종업원수 is highly imbalanced (94.2%)Imbalance
공장판매직종업원수 is highly imbalanced (94.2%)Imbalance
공장생산직종업원수 is highly imbalanced (94.2%)Imbalance
보증액 is highly imbalanced (94.2%)Imbalance
월세액 is highly imbalanced (94.2%)Imbalance
인허가취소일자 has 150 (100.0%) missing valuesMissing
폐업일자 has 38 (25.3%) missing valuesMissing
휴업시작일자 has 150 (100.0%) missing valuesMissing
휴업종료일자 has 150 (100.0%) missing valuesMissing
재개업일자 has 150 (100.0%) missing valuesMissing
전화번호 has 59 (39.3%) missing valuesMissing
소재지면적 has 37 (24.7%) missing valuesMissing
지번주소 has 2 (1.3%) missing valuesMissing
도로명주소 has 52 (34.7%) missing valuesMissing
도로명우편번호 has 54 (36.0%) missing valuesMissing
좌표정보(X) has 2 (1.3%) missing valuesMissing
좌표정보(Y) has 2 (1.3%) missing valuesMissing
건물소유구분명 has 150 (100.0%) missing valuesMissing
다중이용업소여부 has 40 (26.7%) missing valuesMissing
시설총규모 has 40 (26.7%) missing valuesMissing
전통업소지정번호 has 150 (100.0%) missing valuesMissing
전통업소주된음식 has 150 (100.0%) missing valuesMissing
홈페이지 has 150 (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 37 (24.7%) zerosZeros

Reproduction

Analysis started2024-05-11 00:59:23.424106
Analysis finished2024-05-11 00:59:25.534613
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3240000
150 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3240000 150
100.0%

Length

2024-05-11T00:59:25.924798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:26.240615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 150
100.0%

관리번호
Text

UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:59:26.774062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3300
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

Unique150 ?
Unique (%)100.0%

Sample

1st row3240000-120-2003-00001
2nd row3240000-120-2003-00002
3rd row3240000-120-2003-00003
4th row3240000-120-2003-00004
5th row3240000-120-2003-00005
ValueCountFrequency (%)
3240000-120-2003-00001 1
 
0.7%
3240000-120-2017-00002 1
 
0.7%
3240000-120-2017-00004 1
 
0.7%
3240000-120-2017-00005 1
 
0.7%
3240000-120-2018-00001 1
 
0.7%
3240000-120-2018-00002 1
 
0.7%
3240000-120-2018-00003 1
 
0.7%
3240000-120-2018-00004 1
 
0.7%
3240000-120-2018-00005 1
 
0.7%
3240000-120-2018-00006 1
 
0.7%
Other values (140) 140
93.3%
2024-05-11T00:59:28.098095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1557
47.2%
2 529
 
16.0%
- 450
 
13.6%
1 257
 
7.8%
3 211
 
6.4%
4 188
 
5.7%
5 26
 
0.8%
9 21
 
0.6%
7 21
 
0.6%
6 20
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2850
86.4%
Dash Punctuation 450
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1557
54.6%
2 529
 
18.6%
1 257
 
9.0%
3 211
 
7.4%
4 188
 
6.6%
5 26
 
0.9%
9 21
 
0.7%
7 21
 
0.7%
6 20
 
0.7%
8 20
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3300
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1557
47.2%
2 529
 
16.0%
- 450
 
13.6%
1 257
 
7.8%
3 211
 
6.4%
4 188
 
5.7%
5 26
 
0.8%
9 21
 
0.6%
7 21
 
0.6%
6 20
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1557
47.2%
2 529
 
16.0%
- 450
 
13.6%
1 257
 
7.8%
3 211
 
6.4%
4 188
 
5.7%
5 26
 
0.8%
9 21
 
0.6%
7 21
 
0.6%
6 20
 
0.6%

인허가일자
Date

Distinct128
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2003-06-02 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T00:59:28.752899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:59:29.226444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
112 
1
38 

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 (%)
3 112
74.7%
1 38
 
25.3%

Length

2024-05-11T00:59:29.754386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:30.138545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 112
74.7%
1 38
 
25.3%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
112 
영업/정상
38 

Length

Max length5
Median length2
Mean length2.76
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 112
74.7%
영업/정상 38
 
25.3%

Length

2024-05-11T00:59:30.775510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:31.155411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 112
74.7%
영업/정상 38
 
25.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
112 
1
38 

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 (%)
2 112
74.7%
1 38
 
25.3%

Length

2024-05-11T00:59:31.612755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:31.941642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 112
74.7%
1 38
 
25.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
112 
영업
38 

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 112
74.7%
영업 38
 
25.3%

Length

2024-05-11T00:59:32.325451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:32.692719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 112
74.7%
영업 38
 
25.3%

폐업일자
Date

MISSING 

Distinct95
Distinct (%)84.8%
Missing38
Missing (%)25.3%
Memory size1.3 KiB
Minimum2004-02-26 00:00:00
Maximum2024-03-11 00:00:00
2024-05-11T00:59:33.379992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:59:33.924841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

전화번호
Text

MISSING 

Distinct80
Distinct (%)87.9%
Missing59
Missing (%)39.3%
Memory size1.3 KiB
2024-05-11T00:59:34.706791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.054945
Min length10

Characters and Unicode

Total characters1006
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

Unique72 ?
Unique (%)79.1%

Sample

1st row02 4424201
2nd row0222255728
3rd row0222258731
4th row02 7294047
5th row0234531100
ValueCountFrequency (%)
02 73
38.0%
8215 4
 
2.1%
4565700 4
 
2.1%
573 4
 
2.1%
485 3
 
1.6%
33920455 2
 
1.0%
0002 2
 
1.0%
6100 2
 
1.0%
578 2
 
1.0%
426 2
 
1.0%
Other values (89) 94
49.0%
2024-05-11T00:59:35.947529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 183
18.2%
2 167
16.6%
149
14.8%
4 101
10.0%
5 78
7.8%
1 69
 
6.9%
7 63
 
6.3%
6 59
 
5.9%
8 55
 
5.5%
3 53
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 857
85.2%
Space Separator 149
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 183
21.4%
2 167
19.5%
4 101
11.8%
5 78
9.1%
1 69
 
8.1%
7 63
 
7.4%
6 59
 
6.9%
8 55
 
6.4%
3 53
 
6.2%
9 29
 
3.4%
Space Separator
ValueCountFrequency (%)
149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1006
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 183
18.2%
2 167
16.6%
149
14.8%
4 101
10.0%
5 78
7.8%
1 69
 
6.9%
7 63
 
6.3%
6 59
 
5.9%
8 55
 
5.5%
3 53
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 183
18.2%
2 167
16.6%
149
14.8%
4 101
10.0%
5 78
7.8%
1 69
 
6.9%
7 63
 
6.3%
6 59
 
5.9%
8 55
 
5.5%
3 53
 
5.3%

소재지면적
Text

MISSING 

Distinct81
Distinct (%)71.7%
Missing37
Missing (%)24.7%
Memory size1.3 KiB
2024-05-11T00:59:36.705395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.8938053
Min length3

Characters and Unicode

Total characters666
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

Unique54 ?
Unique (%)47.8%

Sample

1st row789.00
2nd row99.00
3rd row679.80
4th row983.00
5th row873.75
ValueCountFrequency (%)
360.00 4
 
3.5%
444.46 3
 
2.7%
233.00 3
 
2.7%
285.54 3
 
2.7%
155.00 2
 
1.8%
367.50 2
 
1.8%
144.00 2
 
1.8%
347.46 2
 
1.8%
789.00 2
 
1.8%
410.00 2
 
1.8%
Other values (71) 88
77.9%
2024-05-11T00:59:37.875893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 146
21.9%
. 113
17.0%
4 55
 
8.3%
1 52
 
7.8%
5 49
 
7.4%
3 48
 
7.2%
2 47
 
7.1%
7 43
 
6.5%
8 38
 
5.7%
6 36
 
5.4%
Other values (2) 39
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 548
82.3%
Other Punctuation 118
 
17.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 146
26.6%
4 55
 
10.0%
1 52
 
9.5%
5 49
 
8.9%
3 48
 
8.8%
2 47
 
8.6%
7 43
 
7.8%
8 38
 
6.9%
6 36
 
6.6%
9 34
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 113
95.8%
, 5
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
Common 666
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 146
21.9%
. 113
17.0%
4 55
 
8.3%
1 52
 
7.8%
5 49
 
7.4%
3 48
 
7.2%
2 47
 
7.1%
7 43
 
6.5%
8 38
 
5.7%
6 36
 
5.4%
Other values (2) 39
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 146
21.9%
. 113
17.0%
4 55
 
8.3%
1 52
 
7.8%
5 49
 
7.4%
3 48
 
7.2%
2 47
 
7.1%
7 43
 
6.5%
8 38
 
5.7%
6 36
 
5.4%
Other values (2) 39
 
5.9%

소재지우편번호
Categorical

HIGH CARDINALITY 

Distinct51
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
134837
15 
134825
14 
134817
13 
134850
 
8
134803
 
7
Other values (46)
93 

Length

Max length7
Median length6
Mean length6.1866667
Min length4

Unique

Unique23 ?
Unique (%)15.3%

Sample

1st row134837
2nd row134847
3rd row134874
4th row134878
5th row134861

Common Values

ValueCountFrequency (%)
134837 15
 
10.0%
134825 14
 
9.3%
134817 13
 
8.7%
134850 8
 
5.3%
134803 7
 
4.7%
134878 6
 
4.0%
134861 6
 
4.0%
134-837 6
 
4.0%
134814 5
 
3.3%
134-800 4
 
2.7%
Other values (41) 66
44.0%

Length

2024-05-11T00:59:38.459026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
134837 15
 
10.0%
134825 14
 
9.3%
134817 13
 
8.7%
134850 8
 
5.3%
134803 7
 
4.7%
134878 6
 
4.0%
134861 6
 
4.0%
134-837 6
 
4.0%
134814 5
 
3.3%
134873 4
 
2.7%
Other values (41) 66
44.0%

지번주소
Text

MISSING 

Distinct110
Distinct (%)74.3%
Missing2
Missing (%)1.3%
Memory size1.3 KiB
2024-05-11T00:59:39.175086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length23.364865
Min length15

Characters and Unicode

Total characters3458
Distinct characters133
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

Unique89 ?
Unique (%)60.1%

Sample

1st row서울특별시 강동구 상일동 166번지
2nd row서울특별시 강동구 성내동 448-10번지
3rd row서울특별시 강동구 천호동 455-8번지
4th row서울특별시 강동구 고덕동 313번지
5th row서울특별시 강동구 천호동 23-3번지 성덕여상
ValueCountFrequency (%)
서울특별시 148
22.1%
강동구 148
22.1%
상일동 25
 
3.7%
성내동 25
 
3.7%
둔촌동 23
 
3.4%
고덕동 20
 
3.0%
천호동 20
 
3.0%
명일동 14
 
2.1%
길동 12
 
1.8%
40번지 11
 
1.6%
Other values (135) 225
33.5%
2024-05-11T00:59:40.614697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
631
18.2%
동 308
 
8.9%
강 158
 
4.6%
서 151
 
4.4%
울 151
 
4.4%
시 150
 
4.3%
특 148
 
4.3%
별 148
 
4.3%
구 148
 
4.3%
지 106
 
3.1%
Other values (123) 1359
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2218
64.1%
Space Separator 631
 
18.2%
Decimal Number 497
 
14.4%
Dash Punctuation 84
 
2.4%
Open Punctuation 8
 
0.2%
Close Punctuation 8
 
0.2%
Other Punctuation 8
 
0.2%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 308
13.9%
강 158
 
7.1%
서 151
 
6.8%
울 151
 
6.8%
시 150
 
6.8%
특 148
 
6.7%
별 148
 
6.7%
구 148
 
6.7%
지 106
 
4.8%
번 96
 
4.3%
Other values (105) 654
29.5%
Decimal Number
ValueCountFrequency (%)
4 88
17.7%
1 83
16.7%
3 58
11.7%
5 51
10.3%
2 50
10.1%
6 47
9.5%
9 42
8.5%
0 34
 
6.8%
7 26
 
5.2%
8 18
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
, 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
X 2
50.0%
K 2
50.0%
Space Separator
ValueCountFrequency (%)
631
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2218
64.1%
Common 1236
35.7%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 308
13.9%
강 158
 
7.1%
서 151
 
6.8%
울 151
 
6.8%
시 150
 
6.8%
특 148
 
6.7%
별 148
 
6.7%
구 148
 
6.7%
지 106
 
4.8%
번 96
 
4.3%
Other values (105) 654
29.5%
Common
ValueCountFrequency (%)
631
51.1%
4 88
 
7.1%
- 84
 
6.8%
1 83
 
6.7%
3 58
 
4.7%
5 51
 
4.1%
2 50
 
4.0%
6 47
 
3.8%
9 42
 
3.4%
0 34
 
2.8%
Other values (6) 68
 
5.5%
Latin
ValueCountFrequency (%)
X 2
50.0%
K 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2218
64.1%
ASCII 1240
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
631
50.9%
4 88
 
7.1%
- 84
 
6.8%
1 83
 
6.7%
3 58
 
4.7%
5 51
 
4.1%
2 50
 
4.0%
6 47
 
3.8%
9 42
 
3.4%
0 34
 
2.7%
Other values (8) 72
 
5.8%
Hangul
ValueCountFrequency (%)
동 308
13.9%
강 158
 
7.1%
서 151
 
6.8%
울 151
 
6.8%
시 150
 
6.8%
특 148
 
6.7%
별 148
 
6.7%
구 148
 
6.7%
지 106
 
4.8%
번 96
 
4.3%
Other values (105) 654
29.5%

도로명주소
Text

MISSING 

Distinct77
Distinct (%)78.6%
Missing52
Missing (%)34.7%
Memory size1.3 KiB
2024-05-11T00:59:41.700823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length31.346939
Min length22

Characters and Unicode

Total characters3072
Distinct characters140
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

Unique64 ?
Unique (%)65.3%

Sample

1st row서울특별시 강동구 동남로 832 (상일동)
2nd row서울특별시 강동구 구천면로 202 (천호동)
3rd row서울특별시 강동구 고덕로 276 (명일동)
4th row서울특별시 강동구 천호대로 1017 (천호동)
5th row서울특별시 강동구 고덕로 183 (고덕동)
ValueCountFrequency (%)
서울특별시 98
 
16.6%
강동구 98
 
16.6%
상일동 19
 
3.2%
명일로 16
 
2.7%
성내동 16
 
2.7%
지1층 15
 
2.5%
둔촌동 15
 
2.5%
동남로 13
 
2.2%
명일동 11
 
1.9%
구천면로 9
 
1.5%
Other values (128) 282
47.6%
2024-05-11T00:59:43.709697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
494
 
16.1%
동 228
 
7.4%
강 114
 
3.7%
구 107
 
3.5%
) 105
 
3.4%
( 105
 
3.4%
서 101
 
3.3%
울 101
 
3.3%
시 100
 
3.3%
로 100
 
3.3%
Other values (130) 1517
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1890
61.5%
Space Separator 494
 
16.1%
Decimal Number 393
 
12.8%
Close Punctuation 105
 
3.4%
Open Punctuation 105
 
3.4%
Other Punctuation 76
 
2.5%
Dash Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 228
 
12.1%
강 114
 
6.0%
구 107
 
5.7%
서 101
 
5.3%
울 101
 
5.3%
시 100
 
5.3%
로 100
 
5.3%
별 98
 
5.2%
특 98
 
5.2%
일 57
 
3.0%
Other values (111) 786
41.6%
Decimal Number
ValueCountFrequency (%)
1 99
25.2%
5 50
12.7%
3 50
12.7%
2 41
10.4%
6 29
 
7.4%
8 29
 
7.4%
0 28
 
7.1%
4 26
 
6.6%
7 23
 
5.9%
9 18
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 69
90.8%
. 7
 
9.2%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
X 2
50.0%
Space Separator
ValueCountFrequency (%)
494
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1890
61.5%
Common 1178
38.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 228
 
12.1%
강 114
 
6.0%
구 107
 
5.7%
서 101
 
5.3%
울 101
 
5.3%
시 100
 
5.3%
로 100
 
5.3%
별 98
 
5.2%
특 98
 
5.2%
일 57
 
3.0%
Other values (111) 786
41.6%
Common
ValueCountFrequency (%)
494
41.9%
) 105
 
8.9%
( 105
 
8.9%
1 99
 
8.4%
, 69
 
5.9%
5 50
 
4.2%
3 50
 
4.2%
2 41
 
3.5%
6 29
 
2.5%
8 29
 
2.5%
Other values (7) 107
 
9.1%
Latin
ValueCountFrequency (%)
K 2
50.0%
X 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1890
61.5%
ASCII 1182
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
494
41.8%
) 105
 
8.9%
( 105
 
8.9%
1 99
 
8.4%
, 69
 
5.8%
5 50
 
4.2%
3 50
 
4.2%
2 41
 
3.5%
6 29
 
2.5%
8 29
 
2.5%
Other values (9) 111
 
9.4%
Hangul
ValueCountFrequency (%)
동 228
 
12.1%
강 114
 
6.0%
구 107
 
5.7%
서 101
 
5.3%
울 101
 
5.3%
시 100
 
5.3%
로 100
 
5.3%
별 98
 
5.2%
특 98
 
5.2%
일 57
 
3.0%
Other values (111) 786
41.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)36.5%
Missing54
Missing (%)36.0%
Infinite0
Infinite (%)0.0%
Mean5315.6458
Minimum5203
Maximum5412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:59:44.248703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5203
5-th percentile5212.75
Q15269
median5314
Q35367.25
95-th percentile5403.25
Maximum5412
Range209
Interquartile range (IQR)98.25

Descriptive statistics

Standard deviation61.442139
Coefficient of variation (CV)0.011558734
Kurtosis-1.1601711
Mean5315.6458
Median Absolute Deviation (MAD)46
Skewness-0.065271881
Sum510302
Variance3775.1364
MonotonicityNot monotonic
2024-05-11T00:59:44.981750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5279 14
 
9.3%
5367 8
 
5.3%
5268 8
 
5.3%
5368 5
 
3.3%
5203 5
 
3.3%
5398 5
 
3.3%
5314 4
 
2.7%
5328 3
 
2.0%
5397 3
 
2.0%
5327 3
 
2.0%
Other values (25) 38
25.3%
(Missing) 54
36.0%
ValueCountFrequency (%)
5203 5
3.3%
5216 1
 
0.7%
5225 2
 
1.3%
5234 1
 
0.7%
5235 1
 
0.7%
5238 3
 
2.0%
5239 1
 
0.7%
5242 1
 
0.7%
5268 8
5.3%
5269 2
 
1.3%
ValueCountFrequency (%)
5412 1
 
0.7%
5411 2
 
1.3%
5407 2
 
1.3%
5402 2
 
1.3%
5398 5
3.3%
5397 3
2.0%
5394 1
 
0.7%
5391 1
 
0.7%
5387 1
 
0.7%
5379 1
 
0.7%

사업장명
Text

Distinct147
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:59:45.497545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length22
Mean length14.166667
Min length3

Characters and Unicode

Total characters2125
Distinct characters245
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

Unique144 ?
Unique (%)96.0%

Sample

1st row(주)정캐터링
2nd row아라코(주)현대영어사지점
3rd row(주)현대그린푸드 현대백화점천호점
4th row한화국토개발(주)배재고점
5th row서울캐터링서비스(주)성덕
ValueCountFrequency (%)
주)엘에스씨푸드 6
 
2.7%
주)현대그린푸드 5
 
2.2%
티엔티푸드(주 4
 
1.8%
강동점 4
 
1.8%
천호점 4
 
1.8%
주)세우미 3
 
1.3%
주)동원홈푸드 3
 
1.3%
주)아워홈 3
 
1.3%
강동고등학교 3
 
1.3%
주식회사 2
 
0.9%
Other values (176) 187
83.5%
2024-05-11T00:59:46.557288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 126
 
5.9%
( 126
 
5.9%
주 124
 
5.8%
74
 
3.5%
드 69
 
3.2%
푸 67
 
3.2%
스 65
 
3.1%
점 64
 
3.0%
고 52
 
2.4%
동 48
 
2.3%
Other values (235) 1310
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1764
83.0%
Close Punctuation 127
 
6.0%
Open Punctuation 127
 
6.0%
Space Separator 74
 
3.5%
Decimal Number 12
 
0.6%
Uppercase Letter 10
 
0.5%
Dash Punctuation 7
 
0.3%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 124
 
7.0%
드 69
 
3.9%
푸 67
 
3.8%
스 65
 
3.7%
점 64
 
3.6%
고 52
 
2.9%
동 48
 
2.7%
강 39
 
2.2%
이 37
 
2.1%
원 36
 
2.0%
Other values (214) 1163
65.9%
Uppercase Letter
ValueCountFrequency (%)
K 2
20.0%
B 2
20.0%
S 1
10.0%
F 1
10.0%
D 1
10.0%
C 1
10.0%
E 1
10.0%
G 1
10.0%
Decimal Number
ValueCountFrequency (%)
0 4
33.3%
1 3
25.0%
2 2
16.7%
5 1
 
8.3%
9 1
 
8.3%
4 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 126
99.2%
] 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 126
99.2%
[ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1764
83.0%
Common 351
 
16.5%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 124
 
7.0%
드 69
 
3.9%
푸 67
 
3.8%
스 65
 
3.7%
점 64
 
3.6%
고 52
 
2.9%
동 48
 
2.7%
강 39
 
2.2%
이 37
 
2.1%
원 36
 
2.0%
Other values (214) 1163
65.9%
Common
ValueCountFrequency (%)
) 126
35.9%
( 126
35.9%
74
21.1%
- 7
 
2.0%
. 4
 
1.1%
0 4
 
1.1%
1 3
 
0.9%
2 2
 
0.6%
5 1
 
0.3%
] 1
 
0.3%
Other values (3) 3
 
0.9%
Latin
ValueCountFrequency (%)
K 2
20.0%
B 2
20.0%
S 1
10.0%
F 1
10.0%
D 1
10.0%
C 1
10.0%
E 1
10.0%
G 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1764
83.0%
ASCII 361
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 126
34.9%
( 126
34.9%
74
20.5%
- 7
 
1.9%
. 4
 
1.1%
0 4
 
1.1%
1 3
 
0.8%
K 2
 
0.6%
B 2
 
0.6%
2 2
 
0.6%
Other values (11) 11
 
3.0%
Hangul
ValueCountFrequency (%)
주 124
 
7.0%
드 69
 
3.9%
푸 67
 
3.8%
스 65
 
3.7%
점 64
 
3.6%
고 52
 
2.9%
동 48
 
2.7%
강 39
 
2.2%
이 37
 
2.1%
원 36
 
2.0%
Other values (214) 1163
65.9%

최종수정일자
Date

Distinct145
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2003-07-18 00:00:00
Maximum2024-04-30 14:07:56
2024-05-11T00:59:46.980477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:59:47.418765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
92 
U
58 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 92
61.3%
U 58
38.7%

Length

2024-05-11T00:59:47.840074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:48.264512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 92
61.3%
u 58
38.7%

데이터갱신일자
Date

Distinct62
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T00:59:49.039264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:59:49.538064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
위탁급식영업
150 

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 150
100.0%

Length

2024-05-11T00:59:50.097438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:50.409992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 150
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)46.6%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean212636.19
Minimum210566.88
Maximum215589.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:59:50.958530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile210922.86
Q1211377.04
median212675.21
Q3213735.5
95-th percentile214690.67
Maximum215589.51
Range5022.6384
Interquartile range (IQR)2358.4578

Descriptive statistics

Standard deviation1244.4349
Coefficient of variation (CV)0.0058524138
Kurtosis-0.82797332
Mean212636.19
Median Absolute Deviation (MAD)1170.1158
Skewness0.12989066
Sum31470156
Variance1548618.3
MonotonicityNot monotonic
2024-05-11T00:59:51.427881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213214.567809826 11
 
7.3%
213845.322882473 10
 
6.7%
212675.207080135 10
 
6.7%
212987.26073707 6
 
4.0%
213267.941832187 6
 
4.0%
214165.815676657 5
 
3.3%
214953.780958725 4
 
2.7%
212598.951968838 4
 
2.7%
212501.369116329 4
 
2.7%
210587.488645319 4
 
2.7%
Other values (59) 84
56.0%
ValueCountFrequency (%)
210566.875626134 1
 
0.7%
210587.488645319 4
2.7%
210657.904424574 1
 
0.7%
210808.253116091 1
 
0.7%
210921.837350385 1
 
0.7%
210924.756895635 1
 
0.7%
210931.643485 1
 
0.7%
210972.121940888 1
 
0.7%
211025.924972294 2
1.3%
211027.8338921 1
 
0.7%
ValueCountFrequency (%)
215589.514019218 1
 
0.7%
215423.76462869 1
 
0.7%
215339.644961398 1
 
0.7%
215327.573332527 1
 
0.7%
214953.780958725 4
2.7%
214202.035389784 2
 
1.3%
214178.370124575 1
 
0.7%
214165.815676657 5
3.3%
214103.557154115 1
 
0.7%
214087.23222755 1
 
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)46.6%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean448946.29
Minimum446408.47
Maximum451723.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T00:59:51.828787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446408.47
5-th percentile447018.08
Q1447642.87
median449277.09
Q3449789.14
95-th percentile450845.05
Maximum451723.48
Range5315.0062
Interquartile range (IQR)2146.2622

Descriptive statistics

Standard deviation1272.8034
Coefficient of variation (CV)0.0028350907
Kurtosis-1.0618539
Mean448946.29
Median Absolute Deviation (MAD)1042.4216
Skewness0.01669108
Sum66444051
Variance1620028.6
MonotonicityNot monotonic
2024-05-11T00:59:52.390813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449737.631252831 11
 
7.3%
449620.769443842 10
 
6.7%
447642.874428318 10
 
6.7%
447505.011652735 6
 
4.0%
450380.968512845 6
 
4.0%
449789.1366027 5
 
3.3%
449635.686071108 4
 
2.7%
448244.501622609 4
 
2.7%
449282.31038379 4
 
2.7%
447299.229870215 4
 
2.7%
Other values (59) 84
56.0%
ValueCountFrequency (%)
446408.470922092 1
 
0.7%
446851.325224794 2
1.3%
446899.094121557 3
2.0%
446921.590368548 2
1.3%
447197.273286818 2
1.3%
447249.901828336 1
 
0.7%
447299.229870215 4
2.7%
447354.170679245 1
 
0.7%
447398.854888409 1
 
0.7%
447402.629676369 1
 
0.7%
ValueCountFrequency (%)
451723.477156569 1
 
0.7%
451625.467060082 2
1.3%
451614.026873853 1
 
0.7%
450873.810386368 1
 
0.7%
450872.909067608 3
2.0%
450793.315222513 3
2.0%
450658.429979105 1
 
0.7%
450530.743141958 1
 
0.7%
450443.942304284 1
 
0.7%
450391.570479617 3
2.0%

위생업태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
위탁급식영업
110 
<NA>
40 

Length

Max length6
Median length6
Mean length5.4666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁급식영업 110
73.3%
<NA> 40
 
26.7%

Length

2024-05-11T00:59:52.851430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:53.197693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁급식영업 110
73.3%
na 40
 
26.7%

남성종사자수
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
128 
0
22 

Length

Max length4
Median length4
Mean length3.56
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
85.3%
0 22
 
14.7%

Length

2024-05-11T00:59:53.416600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:53.779895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
85.3%
0 22
 
14.7%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
128 
0
17 
3
 
3
4
 
1
5
 
1

Length

Max length4
Median length4
Mean length3.56
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 128
85.3%
0 17
 
11.3%
3 3
 
2.0%
4 1
 
0.7%
5 1
 
0.7%

Length

2024-05-11T00:59:54.143115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:54.534832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
85.3%
0 17
 
11.3%
3 3
 
2.0%
4 1
 
0.7%
5 1
 
0.7%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
143 
주택가주변
 
5
유흥업소밀집지역
 
1
아파트지역
 
1

Length

Max length8
Median length4
Mean length4.0666667
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 143
95.3%
주택가주변 5
 
3.3%
유흥업소밀집지역 1
 
0.7%
아파트지역 1
 
0.7%

Length

2024-05-11T00:59:54.943974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:55.329032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 143
95.3%
주택가주변 5
 
3.3%
유흥업소밀집지역 1
 
0.7%
아파트지역 1
 
0.7%

등급구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
143 
우수
 
7

Length

Max length4
Median length4
Mean length3.9066667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 143
95.3%
우수 7
 
4.7%

Length

2024-05-11T00:59:55.813781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:56.196366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 143
95.3%
우수 7
 
4.7%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
120 
상수도전용
30 

Length

Max length5
Median length4
Mean length4.2
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 120
80.0%
상수도전용 30
 
20.0%

Length

2024-05-11T00:59:56.612207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:56.983013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 120
80.0%
상수도전용 30
 
20.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T00:59:57.365809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:57.723838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T00:59:58.131014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:58.760156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T00:59:59.093959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:59:59.421558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T00:59:59.838474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:00:00.323306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T01:00:00.667223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:00:01.142357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T01:00:01.525236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:00:01.895707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
149 
0
 
1

Length

Max length4
Median length4
Mean length3.98
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 149
99.3%
0 1
 
0.7%

Length

2024-05-11T01:00:02.284725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:00:02.669925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 149
99.3%
0 1
 
0.7%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing40
Missing (%)26.7%
Memory size432.0 B
False
110 
(Missing)
40 
ValueCountFrequency (%)
False 110
73.3%
(Missing) 40
 
26.7%
2024-05-11T01:00:02.943783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct56
Distinct (%)50.9%
Missing40
Missing (%)26.7%
Infinite0
Infinite (%)0.0%
Mean227.27936
Minimum0
Maximum1251.27
Zeros37
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-11T01:00:03.377602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median125.33
Q3340.2125
95-th percentile904.6875
Maximum1251.27
Range1251.27
Interquartile range (IQR)340.2125

Descriptive statistics

Standard deviation301.99013
Coefficient of variation (CV)1.3287178
Kurtosis2.8350565
Mean227.27936
Median Absolute Deviation (MAD)125.33
Skewness1.7866088
Sum25000.73
Variance91198.038
MonotonicityNot monotonic
2024-05-11T01:00:03.929787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 37
24.7%
360.0 4
 
2.7%
444.46 3
 
2.0%
233.0 3
 
2.0%
155.0 2
 
1.3%
410.0 2
 
1.3%
99.0 2
 
1.3%
347.46 2
 
1.3%
85.5 2
 
1.3%
120.66 2
 
1.3%
Other values (46) 51
34.0%
(Missing) 40
26.7%
ValueCountFrequency (%)
0.0 37
24.7%
12.51 1
 
0.7%
15.0 1
 
0.7%
16.5 1
 
0.7%
19.0 1
 
0.7%
32.48 1
 
0.7%
45.75 1
 
0.7%
59.04 1
 
0.7%
59.4 1
 
0.7%
62.0 1
 
0.7%
ValueCountFrequency (%)
1251.27 2
1.3%
1251.2 1
0.7%
1028.0 1
0.7%
983.0 1
0.7%
930.0 1
0.7%
873.75 1
0.7%
846.0 1
0.7%
789.0 1
0.7%
785.11 1
0.7%
719.7 1
0.7%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-120-2003-0000120030602<NA>3폐업2폐업20190228<NA><NA><NA>02 4424201789.00134837서울특별시 강동구 상일동 166번지서울특별시 강동구 동남로 832 (상일동)5279(주)정캐터링2019-02-28 12:00:36U2019-03-02 02:40:00.0위탁급식영업213845.322882449620.769444위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N789.0<NA><NA><NA>
132400003240000-120-2003-0000220030605<NA>3폐업2폐업20120427<NA><NA><NA>022225572899.00134847서울특별시 강동구 성내동 448-10번지<NA><NA>아라코(주)현대영어사지점2010-06-11 15:48:39I2018-08-31 23:59:59.0위탁급식영업211377.039493446899.094122위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.0<NA><NA><NA>
232400003240000-120-2003-0000320030709<NA>3폐업2폐업20110208<NA><NA><NA>0222258731679.80134874서울특별시 강동구 천호동 455-8번지<NA><NA>(주)현대그린푸드 현대백화점천호점2010-07-16 10:02:41I2018-08-31 23:59:59.0위탁급식영업210931.643485448522.079827위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N679.8<NA><NA><NA>
332400003240000-120-2003-0000420030718<NA>3폐업2폐업20050302<NA><NA><NA>02 7294047983.00134878서울특별시 강동구 고덕동 313번지<NA><NA>한화국토개발(주)배재고점2003-07-18 00:00:00I2018-08-31 23:59:59.0위탁급식영업213267.941832450380.968513위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N983.0<NA><NA><NA>
432400003240000-120-2003-0000520030731<NA>3폐업2폐업20110225<NA><NA><NA>0234531100873.75134861서울특별시 강동구 천호동 23-3번지 성덕여상<NA><NA>서울캐터링서비스(주)성덕2003-07-31 00:00:00I2018-08-31 23:59:59.0위탁급식영업212495.038141449747.414848위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N873.75<NA><NA><NA>
532400003240000-120-2003-0000620030804<NA>3폐업2폐업20171109<NA><NA><NA>02 426 2001<NA>134873서울특별시 강동구 천호동 421-4번지서울특별시 강동구 구천면로 202 (천호동)53292001아울렛천호점2017-11-09 14:48:15I2018-08-31 23:59:59.0위탁급식영업211174.771171448678.909948위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632400003240000-120-2003-0000720030819<NA>3폐업2폐업20100615<NA><NA><NA>02 4275986846.00134710서울특별시 강동구 상일동 166번지 한영중학교<NA><NA>다솜푸드시스템2003-10-31 00:00:00I2018-08-31 23:59:59.0위탁급식영업213845.322882449620.769444위탁급식영업00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N846.0<NA><NA><NA>
732400003240000-120-2003-0000820030826<NA>3폐업2폐업20060309<NA><NA><NA>02 4726885176.00134867서울특별시 강동구 천호동 313-5번지<NA><NA>(주)이바돔(천일중학교)2003-08-26 00:00:00I2018-08-31 23:59:59.0위탁급식영업211227.346866449277.087059위탁급식영업00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N176.0<NA><NA><NA>
832400003240000-120-2003-0001020031010<NA>3폐업2폐업20080801<NA><NA><NA>02 4878757<NA>134850서울특별시 강동구 성내동 540-1번지<NA><NA>강동경찰서아라코(주)2008-07-02 17:18:52I2018-08-31 23:59:59.0위탁급식영업210924.756896447510.463345위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-120-2003-0001120031010<NA>3폐업2폐업20181031<NA><NA><NA>02 21451196318.47134825서울특별시 강동구 명일동 46-4번지서울특별시 강동구 고덕로 276 (명일동)5269(주)신세계푸드 이마트 명일점2018-10-31 15:39:04U2018-11-02 02:36:35.0위탁급식영업213700.877715450278.100931위탁급식영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N318.47<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
14032400003240000-120-2023-000072023-10-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>81.00134-800서울특별시 강동구 고덕동 38-12 KX서울특별시 강동구 고덕비즈밸리로6길 90, KX 3층 (고덕동)5203지엘유통개발 케이엑스그룹2023-10-27 11:42:12I2022-10-30 22:09:00.0위탁급식영업214202.03539451625.46706<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14132400003240000-120-2023-000082023-12-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA>107.21134-874서울특별시 강동구 천호동 454-1 이마트서울특별시 강동구 천호대로 1017, 이마트 6층 (천호동)5328(주)한울에프앤에스 이마트천호점2024-02-26 10:55:30U2023-12-01 22:09:00.0위탁급식영업211025.924972448495.189152<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14232400003240000-120-2024-000012024-01-02<NA>1영업/정상1영업<NA><NA><NA><NA>022135546539.50134-848서울특별시 강동구 성내동 452 포레스트서울특별시 강동구 강동대로 143-52, 포레스트 6층 (성내동)5398(주)현대그린푸드 KB골든라이프케어 강동케어센터2024-01-02 09:21:21I2023-12-01 00:04:00.0위탁급식영업210587.488645447299.22987<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14332400003240000-120-2024-000022024-01-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>284.00134-800서울특별시 강동구 고덕동 98-6 에이스메디칼타워서울특별시 강동구 고덕비즈밸리로4길 30, 에이스메디칼타워 지1층 (고덕동)5203대영푸드시스템 에이스메디칼점2024-01-22 15:56:00I2023-11-30 22:04:00.0위탁급식영업214103.557154451614.026874<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14432400003240000-120-2024-000032024-01-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>339.00134-080서울특별시 강동구 고덕동 0서울특별시 강동구 고덕비즈밸리로2가길 27, 3층 (고덕동)5203(주)에이치제이푸드일화구내식당점2024-01-30 13:37:08I2023-12-02 00:01:00.0위탁급식영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14532400003240000-120-2024-000042024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>789.59134-837서울특별시 강동구 상일동 166 한영중.고등학교서울특별시 강동구 동남로 832, 한영중.고등학교 (상일동)5279(주)엘에스씨푸드 한영외국어고등학교2024-02-27 10:38:57I2023-12-01 22:09:00.0위탁급식영업213845.322882449620.769444<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14632400003240000-120-2024-000052024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>1249.00134-837서울특별시 강동구 상일동 166 한영중.고등학교서울특별시 강동구 동남로 832, 한영중.고등학교 (상일동)5279(주)엘에스씨푸드 한영고등학교2024-02-27 10:52:59I2023-12-01 22:09:00.0위탁급식영업213845.322882449620.769444<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14732400003240000-120-2024-000062024-02-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>285.54134-817서울특별시 강동구 둔촌동 79-3 둔촌고등학교서울특별시 강동구 명일로 140, 둔촌고등학교 (둔촌동)5367(주)정오아카데미 둔촌고등학교점2024-02-29 16:03:38I2023-12-03 00:02:00.0위탁급식영업212675.20708447642.874428<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14832400003240000-120-2024-000072024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>82.50134-100서울특별시 강동구 강일동 699-5 벨포레스트서울특별시 강동구 고덕로 463, 벨포레스트 지1층 (강일동)5216벨프레시푸드(주)2024-04-29 17:29:06I2023-12-05 00:01:00.0위탁급식영업215589.514019450658.429979<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14932400003240000-120-2024-000082024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>259.70134-851서울특별시 강동구 성내동 322-9 스타빌딩서울특별시 강동구 올림픽로 564, 스타빌딩 2층 (성내동)5391(주)풀무원푸드앤컬처 스타비젼2024-04-30 14:07:56I2023-12-05 00:02:00.0위탁급식영업210657.904425447744.110717<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>