Overview

Dataset statistics

Number of variables44
Number of observations68
Missing cells719
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.2 KiB
Average record size in memory379.9 B

Variable types

Categorical20
Text6
DateTime3
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18032/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (88.9%)Imbalance
여성종사자수 is highly imbalanced (88.9%)Imbalance
총인원 is highly imbalanced (88.9%)Imbalance
보증액 is highly imbalanced (88.9%)Imbalance
월세액 is highly imbalanced (88.9%)Imbalance
인허가취소일자 has 68 (100.0%) missing valuesMissing
폐업일자 has 20 (29.4%) missing valuesMissing
휴업시작일자 has 68 (100.0%) missing valuesMissing
휴업종료일자 has 68 (100.0%) missing valuesMissing
재개업일자 has 68 (100.0%) missing valuesMissing
전화번호 has 27 (39.7%) missing valuesMissing
소재지면적 has 1 (1.5%) missing valuesMissing
도로명주소 has 18 (26.5%) missing valuesMissing
도로명우편번호 has 19 (27.9%) missing valuesMissing
영업장주변구분명 has 68 (100.0%) missing valuesMissing
등급구분명 has 68 (100.0%) missing valuesMissing
다중이용업소여부 has 11 (16.2%) missing valuesMissing
시설총규모 has 11 (16.2%) missing valuesMissing
전통업소지정번호 has 68 (100.0%) missing valuesMissing
전통업소주된음식 has 68 (100.0%) missing valuesMissing
홈페이지 has 68 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 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
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 32 (47.1%) zerosZeros

Reproduction

Analysis started2024-05-11 06:29:05.619655
Analysis finished2024-05-11 06:29:06.510416
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
3050000
68 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 68
100.0%

Length

2024-05-11T15:29:06.646154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:06.811945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 68
100.0%

관리번호
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T15:29:07.074754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1496
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

Unique68 ?
Unique (%)100.0%

Sample

1st row3050000-122-2008-00001
2nd row3050000-122-2008-00002
3rd row3050000-122-2008-00003
4th row3050000-122-2008-00004
5th row3050000-122-2008-00005
ValueCountFrequency (%)
3050000-122-2008-00001 1
 
1.5%
3050000-122-2013-00004 1
 
1.5%
3050000-122-2012-00005 1
 
1.5%
3050000-122-2012-00006 1
 
1.5%
3050000-122-2013-00001 1
 
1.5%
3050000-122-2013-00002 1
 
1.5%
3050000-122-2013-00003 1
 
1.5%
3050000-122-2008-00002 1
 
1.5%
3050000-122-2014-00002 1
 
1.5%
3050000-122-2008-00009 1
 
1.5%
Other values (58) 58
85.3%
2024-05-11T15:29:07.573921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 699
46.7%
2 231
 
15.4%
- 204
 
13.6%
1 139
 
9.3%
3 88
 
5.9%
5 78
 
5.2%
8 21
 
1.4%
4 14
 
0.9%
9 9
 
0.6%
7 8
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1292
86.4%
Dash Punctuation 204
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 699
54.1%
2 231
 
17.9%
1 139
 
10.8%
3 88
 
6.8%
5 78
 
6.0%
8 21
 
1.6%
4 14
 
1.1%
9 9
 
0.7%
7 8
 
0.6%
6 5
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1496
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 699
46.7%
2 231
 
15.4%
- 204
 
13.6%
1 139
 
9.3%
3 88
 
5.9%
5 78
 
5.2%
8 21
 
1.4%
4 14
 
0.9%
9 9
 
0.6%
7 8
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 699
46.7%
2 231
 
15.4%
- 204
 
13.6%
1 139
 
9.3%
3 88
 
5.9%
5 78
 
5.2%
8 21
 
1.4%
4 14
 
0.9%
9 9
 
0.6%
7 8
 
0.5%

인허가일자
Date

Distinct65
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2008-03-19 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T15:29:07.827039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:08.034828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
3
48 
1
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 48
70.6%
1 20
29.4%

Length

2024-05-11T15:29:08.226479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:08.377352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 48
70.6%
1 20
29.4%

영업상태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
폐업
48 
영업/정상
20 

Length

Max length5
Median length2
Mean length2.8823529
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 48
70.6%
영업/정상 20
29.4%

Length

2024-05-11T15:29:08.554190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:08.736431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 48
70.6%
영업/정상 20
29.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
2
48 
1
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 48
70.6%
1 20
29.4%

Length

2024-05-11T15:29:08.945289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:09.144737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 48
70.6%
1 20
29.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
폐업
48 
영업
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 48
70.6%
영업 20
29.4%

Length

2024-05-11T15:29:09.311208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:09.467421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 48
70.6%
영업 20
29.4%

폐업일자
Date

MISSING 

Distinct45
Distinct (%)93.8%
Missing20
Missing (%)29.4%
Memory size676.0 B
Minimum2008-08-08 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T15:29:09.983473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:10.208362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

전화번호
Text

MISSING 

Distinct40
Distinct (%)97.6%
Missing27
Missing (%)39.7%
Memory size676.0 B
2024-05-11T15:29:10.514751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.536585
Min length7

Characters and Unicode

Total characters432
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

Unique39 ?
Unique (%)95.1%

Sample

1st row02 22943623
2nd row02 969 1301
3rd row02924 7945
4th row0222474040
5th row029675098
ValueCountFrequency (%)
02 21
27.3%
070 2
 
2.6%
949 2
 
2.6%
7715 2
 
2.6%
732 1
 
1.3%
0484 1
 
1.3%
024386100 1
 
1.3%
22943623 1
 
1.3%
0222530504 1
 
1.3%
07082727118 1
 
1.3%
Other values (44) 44
57.1%
2024-05-11T15:29:11.049517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 79
18.3%
2 76
17.6%
48
11.1%
4 40
9.3%
9 36
8.3%
6 30
 
6.9%
1 28
 
6.5%
7 27
 
6.2%
5 24
 
5.6%
3 24
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384
88.9%
Space Separator 48
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
20.6%
2 76
19.8%
4 40
10.4%
9 36
9.4%
6 30
 
7.8%
1 28
 
7.3%
7 27
 
7.0%
5 24
 
6.2%
3 24
 
6.2%
8 20
 
5.2%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 79
18.3%
2 76
17.6%
48
11.1%
4 40
9.3%
9 36
8.3%
6 30
 
6.9%
1 28
 
6.5%
7 27
 
6.2%
5 24
 
5.6%
3 24
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 79
18.3%
2 76
17.6%
48
11.1%
4 40
9.3%
9 36
8.3%
6 30
 
6.9%
1 28
 
6.5%
7 27
 
6.2%
5 24
 
5.6%
3 24
 
5.6%

소재지면적
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)71.6%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean58.333881
Minimum3.75
Maximum902.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T15:29:11.351599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.75
5-th percentile9.9
Q118.69
median33
Q361.975
95-th percentile125.46
Maximum902.85
Range899.1
Interquartile range (IQR)43.285

Descriptive statistics

Standard deviation110.11579
Coefficient of variation (CV)1.8876815
Kurtosis54.297858
Mean58.333881
Median Absolute Deviation (MAD)18
Skewness7.0467953
Sum3908.37
Variance12125.487
MonotonicityNot monotonic
2024-05-11T15:29:11.610639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
33.0 10
 
14.7%
49.5 3
 
4.4%
9.9 3
 
4.4%
32.5 2
 
2.9%
82.5 2
 
2.9%
66.0 2
 
2.9%
16.52 2
 
2.9%
82.0 2
 
2.9%
23.0 2
 
2.9%
120.0 1
 
1.5%
Other values (38) 38
55.9%
ValueCountFrequency (%)
3.75 1
 
1.5%
9.82 1
 
1.5%
9.9 3
4.4%
9.93 1
 
1.5%
10.2 1
 
1.5%
12.0 1
 
1.5%
13.0 1
 
1.5%
13.2 1
 
1.5%
14.0 1
 
1.5%
15.0 1
 
1.5%
ValueCountFrequency (%)
902.85 1
1.5%
150.0 1
1.5%
144.69 1
1.5%
127.8 1
1.5%
120.0 1
1.5%
100.0 1
1.5%
99.9 1
1.5%
98.18 1
1.5%
92.93 1
1.5%
82.5 2
2.9%

소재지우편번호
Text

Distinct36
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T15:29:11.945120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1029412
Min length6

Characters and Unicode

Total characters415
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

Unique26 ?
Unique (%)38.2%

Sample

1st row130827
2nd row130869
3rd row130823
4th row130878
5th row130817
ValueCountFrequency (%)
130863 8
 
11.8%
130864 7
 
10.3%
130862 7
 
10.3%
130878 4
 
5.9%
130817 4
 
5.9%
130827 3
 
4.4%
130030 3
 
4.4%
130823 2
 
2.9%
130846 2
 
2.9%
130805 2
 
2.9%
Other values (26) 26
38.2%
2024-05-11T15:29:12.579345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 85
20.5%
0 82
19.8%
1 76
18.3%
8 70
16.9%
6 32
 
7.7%
7 20
 
4.8%
4 19
 
4.6%
2 17
 
4.1%
- 7
 
1.7%
5 6
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
98.3%
Dash Punctuation 7
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 85
20.8%
0 82
20.1%
1 76
18.6%
8 70
17.2%
6 32
 
7.8%
7 20
 
4.9%
4 19
 
4.7%
2 17
 
4.2%
5 6
 
1.5%
9 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 85
20.5%
0 82
19.8%
1 76
18.3%
8 70
16.9%
6 32
 
7.7%
7 20
 
4.8%
4 19
 
4.6%
2 17
 
4.1%
- 7
 
1.7%
5 6
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 85
20.5%
0 82
19.8%
1 76
18.3%
8 70
16.9%
6 32
 
7.7%
7 20
 
4.8%
4 19
 
4.6%
2 17
 
4.1%
- 7
 
1.7%
5 6
 
1.4%

지번주소
Text

Distinct65
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T15:29:13.040422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length26.338235
Min length19

Characters and Unicode

Total characters1791
Distinct characters93
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)91.2%

Sample

1st row서울특별시 동대문구 이문동 63-9
2nd row서울특별시 동대문구 청량리동 348 1층(마파람길11)
3rd row서울특별시 동대문구 용두동 237-60
4th row서울특별시 동대문구 휘경동 286-4
5th row서울특별시 동대문구 용두동 39-1
ValueCountFrequency (%)
서울특별시 68
20.4%
동대문구 68
20.4%
제기동 25
 
7.5%
용두동 10
 
3.0%
1층 10
 
3.0%
장안동 9
 
2.7%
답십리동 8
 
2.4%
휘경동 8
 
2.4%
청량리동 3
 
0.9%
이문동 3
 
0.9%
Other values (110) 121
36.3%
2024-05-11T15:29:13.772384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
17.9%
동 144
 
8.0%
시 76
 
4.2%
1 76
 
4.2%
문 71
 
4.0%
서 70
 
3.9%
대 70
 
3.9%
특 68
 
3.8%
별 68
 
3.8%
구 68
 
3.8%
Other values (83) 760
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1006
56.2%
Decimal Number 366
 
20.4%
Space Separator 320
 
17.9%
Dash Punctuation 57
 
3.2%
Close Punctuation 20
 
1.1%
Open Punctuation 20
 
1.1%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 144
14.3%
시 76
 
7.6%
문 71
 
7.1%
서 70
 
7.0%
대 70
 
7.0%
특 68
 
6.8%
별 68
 
6.8%
구 68
 
6.8%
울 68
 
6.8%
기 26
 
2.6%
Other values (65) 277
27.5%
Decimal Number
ValueCountFrequency (%)
1 76
20.8%
2 52
14.2%
3 42
11.5%
5 38
10.4%
8 34
9.3%
9 31
8.5%
4 29
 
7.9%
7 24
 
6.6%
0 21
 
5.7%
6 19
 
5.2%
Close Punctuation
ValueCountFrequency (%)
) 16
80.0%
] 4
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 16
80.0%
[ 4
 
20.0%
Space Separator
ValueCountFrequency (%)
320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1006
56.2%
Common 785
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 144
14.3%
시 76
 
7.6%
문 71
 
7.1%
서 70
 
7.0%
대 70
 
7.0%
특 68
 
6.8%
별 68
 
6.8%
구 68
 
6.8%
울 68
 
6.8%
기 26
 
2.6%
Other values (65) 277
27.5%
Common
ValueCountFrequency (%)
320
40.8%
1 76
 
9.7%
- 57
 
7.3%
2 52
 
6.6%
3 42
 
5.4%
5 38
 
4.8%
8 34
 
4.3%
9 31
 
3.9%
4 29
 
3.7%
7 24
 
3.1%
Other values (8) 82
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1006
56.2%
ASCII 785
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
40.8%
1 76
 
9.7%
- 57
 
7.3%
2 52
 
6.6%
3 42
 
5.4%
5 38
 
4.8%
8 34
 
4.3%
9 31
 
3.9%
4 29
 
3.7%
7 24
 
3.1%
Other values (8) 82
 
10.4%
Hangul
ValueCountFrequency (%)
동 144
14.3%
시 76
 
7.6%
문 71
 
7.1%
서 70
 
7.0%
대 70
 
7.0%
특 68
 
6.8%
별 68
 
6.8%
구 68
 
6.8%
울 68
 
6.8%
기 26
 
2.6%
Other values (65) 277
27.5%

도로명주소
Text

MISSING 

Distinct50
Distinct (%)100.0%
Missing18
Missing (%)26.5%
Memory size676.0 B
2024-05-11T15:29:14.175290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length41
Mean length33.32
Min length23

Characters and Unicode

Total characters1666
Distinct characters92
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

Unique50 ?
Unique (%)100.0%

Sample

1st row서울특별시 동대문구 한천로58길 75-7 (이문동)
2nd row서울특별시 동대문구 약령시로14길 29 (제기동,[경동시장로9길18-3])
3rd row서울특별시 동대문구 정릉천동로 154 (제기동)
4th row서울특별시 동대문구 천호대로23길 19-1 (용두동,2층 1호)
5th row서울특별시 동대문구 망우로 80 (휘경동)
ValueCountFrequency (%)
서울특별시 50
 
16.1%
동대문구 50
 
16.1%
1층 25
 
8.0%
제기동 18
 
5.8%
장안동 7
 
2.3%
답십리동 7
 
2.3%
천호대로 4
 
1.3%
휘경동 4
 
1.3%
2층 3
 
1.0%
장한로 3
 
1.0%
Other values (115) 140
45.0%
2024-05-11T15:29:14.920685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
261
 
15.7%
동 111
 
6.7%
1 85
 
5.1%
대 62
 
3.7%
시 61
 
3.7%
) 53
 
3.2%
( 53
 
3.2%
로 52
 
3.1%
문 52
 
3.1%
서 51
 
3.1%
Other values (82) 825
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 976
58.6%
Space Separator 261
 
15.7%
Decimal Number 259
 
15.5%
Close Punctuation 54
 
3.2%
Open Punctuation 54
 
3.2%
Other Punctuation 49
 
2.9%
Dash Punctuation 13
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 111
 
11.4%
대 62
 
6.4%
시 61
 
6.2%
로 52
 
5.3%
문 52
 
5.3%
서 51
 
5.2%
울 51
 
5.2%
구 50
 
5.1%
별 50
 
5.1%
특 50
 
5.1%
Other values (65) 386
39.5%
Decimal Number
ValueCountFrequency (%)
1 85
32.8%
2 33
 
12.7%
5 23
 
8.9%
3 23
 
8.9%
8 20
 
7.7%
0 19
 
7.3%
4 16
 
6.2%
9 16
 
6.2%
7 14
 
5.4%
6 10
 
3.9%
Close Punctuation
ValueCountFrequency (%)
) 53
98.1%
] 1
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 53
98.1%
[ 1
 
1.9%
Space Separator
ValueCountFrequency (%)
261
100.0%
Other Punctuation
ValueCountFrequency (%)
, 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 976
58.6%
Common 690
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 111
 
11.4%
대 62
 
6.4%
시 61
 
6.2%
로 52
 
5.3%
문 52
 
5.3%
서 51
 
5.2%
울 51
 
5.2%
구 50
 
5.1%
별 50
 
5.1%
특 50
 
5.1%
Other values (65) 386
39.5%
Common
ValueCountFrequency (%)
261
37.8%
1 85
 
12.3%
) 53
 
7.7%
( 53
 
7.7%
, 49
 
7.1%
2 33
 
4.8%
5 23
 
3.3%
3 23
 
3.3%
8 20
 
2.9%
0 19
 
2.8%
Other values (7) 71
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 976
58.6%
ASCII 690
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
261
37.8%
1 85
 
12.3%
) 53
 
7.7%
( 53
 
7.7%
, 49
 
7.1%
2 33
 
4.8%
5 23
 
3.3%
3 23
 
3.3%
8 20
 
2.9%
0 19
 
2.8%
Other values (7) 71
 
10.3%
Hangul
ValueCountFrequency (%)
동 111
 
11.4%
대 62
 
6.4%
시 61
 
6.2%
로 52
 
5.3%
문 52
 
5.3%
서 51
 
5.2%
울 51
 
5.2%
구 50
 
5.1%
별 50
 
5.1%
특 50
 
5.1%
Other values (65) 386
39.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)65.3%
Missing19
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean2540.2449
Minimum2423
Maximum2646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T15:29:15.140147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2423
5-th percentile2438.4
Q12480
median2561
Q32590
95-th percentile2641.2
Maximum2646
Range223
Interquartile range (IQR)110

Descriptive statistics

Standard deviation65.299161
Coefficient of variation (CV)0.025705853
Kurtosis-1.2123248
Mean2540.2449
Median Absolute Deviation (MAD)64
Skewness-0.023509727
Sum124472
Variance4263.9804
MonotonicityNot monotonic
2024-05-11T15:29:15.350916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
2478 6
 
8.8%
2571 5
 
7.4%
2480 4
 
5.9%
2535 2
 
2.9%
2646 2
 
2.9%
2570 2
 
2.9%
2423 2
 
2.9%
2499 2
 
2.9%
2626 1
 
1.5%
2488 1
 
1.5%
Other values (22) 22
32.4%
(Missing) 19
27.9%
ValueCountFrequency (%)
2423 2
 
2.9%
2428 1
 
1.5%
2454 1
 
1.5%
2471 1
 
1.5%
2478 6
8.8%
2479 1
 
1.5%
2480 4
5.9%
2488 1
 
1.5%
2493 1
 
1.5%
2499 2
 
2.9%
ValueCountFrequency (%)
2646 2
2.9%
2644 1
1.5%
2637 1
1.5%
2629 1
1.5%
2626 1
1.5%
2625 1
1.5%
2615 1
1.5%
2609 1
1.5%
2604 1
1.5%
2603 1
1.5%

사업장명
Text

Distinct64
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-05-11T15:29:15.740359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length5.1911765
Min length2

Characters and Unicode

Total characters353
Distinct characters149
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)89.7%

Sample

1st row신광유통
2nd row시온유통
3rd row맥고야
4th row현미상회
5th row삼호물산
ValueCountFrequency (%)
자연드림 3
 
4.0%
훈자건강마을 2
 
2.7%
아산푸드 2
 
2.7%
주)영찬 1
 
1.3%
한신유통 1
 
1.3%
직영본점 1
 
1.3%
올프렌즈 1
 
1.3%
신광유통 1
 
1.3%
도드람양돈협동조합 1
 
1.3%
서울지점 1
 
1.3%
Other values (61) 61
81.3%
2024-05-11T15:29:16.448617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
드 16
 
4.5%
유 12
 
3.4%
통 12
 
3.4%
푸 11
 
3.1%
주 11
 
3.1%
( 10
 
2.8%
산 10
 
2.8%
) 10
 
2.8%
7
 
2.0%
품 7
 
2.0%
Other values (139) 247
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
90.9%
Open Punctuation 10
 
2.8%
Close Punctuation 10
 
2.8%
Space Separator 7
 
2.0%
Uppercase Letter 5
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 16
 
5.0%
유 12
 
3.7%
통 12
 
3.7%
푸 11
 
3.4%
주 11
 
3.4%
산 10
 
3.1%
품 7
 
2.2%
식 6
 
1.9%
회 6
 
1.9%
상 6
 
1.9%
Other values (132) 224
69.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
F 1
20.0%
K 1
20.0%
I 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 321
90.9%
Common 27
 
7.6%
Latin 5
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 16
 
5.0%
유 12
 
3.7%
통 12
 
3.7%
푸 11
 
3.4%
주 11
 
3.4%
산 10
 
3.1%
품 7
 
2.2%
식 6
 
1.9%
회 6
 
1.9%
상 6
 
1.9%
Other values (132) 224
69.8%
Latin
ValueCountFrequency (%)
S 2
40.0%
F 1
20.0%
K 1
20.0%
I 1
20.0%
Common
ValueCountFrequency (%)
( 10
37.0%
) 10
37.0%
7
25.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 321
90.9%
ASCII 32
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
드 16
 
5.0%
유 12
 
3.7%
통 12
 
3.7%
푸 11
 
3.4%
주 11
 
3.4%
산 10
 
3.1%
품 7
 
2.2%
식 6
 
1.9%
회 6
 
1.9%
상 6
 
1.9%
Other values (132) 224
69.8%
ASCII
ValueCountFrequency (%)
( 10
31.2%
) 10
31.2%
7
21.9%
S 2
 
6.2%
F 1
 
3.1%
K 1
 
3.1%
I 1
 
3.1%

최종수정일자
Date

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum2008-06-09 10:35:30
Maximum2024-05-02 14:35:27
2024-05-11T15:29:16.713550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:29:17.347282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
I
53 
U
15 

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 53
77.9%
U 15
 
22.1%

Length

2024-05-11T15:29:17.670180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:17.802432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 53
77.9%
u 15
 
22.1%

데이터갱신일자
Categorical

Distinct24
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size676.0 B
2018-08-31 23:59:59.0
45 
2019-02-21 02:40:00.0
 
1
2021-11-01 23:05:00.0
 
1
2020-05-27 02:40:00.0
 
1
2021-02-27 02:40:00.0
 
1
Other values (19)
19 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique23 ?
Unique (%)33.8%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 45
66.2%
2019-02-21 02:40:00.0 1
 
1.5%
2021-11-01 23:05:00.0 1
 
1.5%
2020-05-27 02:40:00.0 1
 
1.5%
2021-02-27 02:40:00.0 1
 
1.5%
2020-04-23 02:40:00.0 1
 
1.5%
2021-10-31 23:06:00.0 1
 
1.5%
2020-05-06 02:40:00.0 1
 
1.5%
2021-05-01 00:23:12.0 1
 
1.5%
2020-11-27 02:40:00.0 1
 
1.5%
Other values (14) 14
 
20.6%

Length

2024-05-11T15:29:17.939271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 45
33.1%
23:59:59.0 45
33.1%
02:40:00.0 8
 
5.9%
2022-12-07 2
 
1.5%
2021-11-01 2
 
1.5%
22:09:00.0 2
 
1.5%
2022-12-02 1
 
0.7%
00:23:15.0 1
 
0.7%
22:03:00.0 1
 
0.7%
2022-02-05 1
 
0.7%
Other values (28) 28
20.6%

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
집단급식소 식품판매업
68 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 68
100.0%

Length

2024-05-11T15:29:18.264128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:18.454339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 68
50.0%
식품판매업 68
50.0%

좌표정보(X)
Real number (ℝ)

Distinct62
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204269.92
Minimum202185.94
Maximum206573.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T15:29:18.680815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202185.94
5-th percentile202894.68
Q1203357.36
median203704.51
Q3205441.02
95-th percentile206141.78
Maximum206573.59
Range4387.6554
Interquartile range (IQR)2083.6595

Descriptive statistics

Standard deviation1203.4735
Coefficient of variation (CV)0.0058915842
Kurtosis-1.1733883
Mean204269.92
Median Absolute Deviation (MAD)563.68701
Skewness0.43098993
Sum13890355
Variance1448348.4
MonotonicityNot monotonic
2024-05-11T15:29:18.923195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
205762.994263246 2
 
2.9%
203433.80458423 2
 
2.9%
203728.132135578 2
 
2.9%
205435.088371881 2
 
2.9%
203140.82770834 2
 
2.9%
206082.433793407 2
 
2.9%
203705.160747829 1
 
1.5%
204274.832114038 1
 
1.5%
203257.607703086 1
 
1.5%
203564.00286956 1
 
1.5%
Other values (52) 52
76.5%
ValueCountFrequency (%)
202185.938538774 1
1.5%
202196.042575334 1
1.5%
202538.011840845 1
1.5%
202875.632667655 1
1.5%
202930.067173465 1
1.5%
202943.797952618 1
1.5%
203140.82770834 2
2.9%
203188.427527295 1
1.5%
203190.301135395 1
1.5%
203247.35191919 1
1.5%
ValueCountFrequency (%)
206573.59398246 1
1.5%
206386.640489187 1
1.5%
206282.745291263 1
1.5%
206173.74256303 1
1.5%
206082.433793407 2
2.9%
206070.29392676 1
1.5%
206059.225281459 1
1.5%
205952.506670626 1
1.5%
205916.327051894 1
1.5%
205912.152705259 1
1.5%

좌표정보(Y)
Real number (ℝ)

Distinct62
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean453119.41
Minimum451170.63
Maximum455354.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T15:29:19.149966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451170.63
5-th percentile451523.85
Q1452583.28
median453247.09
Q3453676.49
95-th percentile454569.19
Maximum455354.99
Range4184.3616
Interquartile range (IQR)1093.2122

Descriptive statistics

Standard deviation932.75103
Coefficient of variation (CV)0.0020585104
Kurtosis0.23080196
Mean453119.41
Median Absolute Deviation (MAD)533.86963
Skewness0.057272309
Sum30812120
Variance870024.49
MonotonicityNot monotonic
2024-05-11T15:29:19.397451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452510.004742539 2
 
2.9%
453342.445696552 2
 
2.9%
452778.89330743 2
 
2.9%
454165.72746027 2
 
2.9%
453480.967221394 2
 
2.9%
451216.206095278 2
 
2.9%
453200.139013199 1
 
1.5%
453672.880516146 1
 
1.5%
452402.42855781 1
 
1.5%
453883.297637547 1
 
1.5%
Other values (52) 52
76.5%
ValueCountFrequency (%)
451170.628868201 1
1.5%
451216.206095278 2
2.9%
451494.590428778 1
1.5%
451578.200073082 1
1.5%
451803.558407339 1
1.5%
451814.915620366 1
1.5%
451870.778303081 1
1.5%
451880.41402323 1
1.5%
452059.747091201 1
1.5%
452075.510388308 1
1.5%
ValueCountFrequency (%)
455354.99049628 1
1.5%
455335.922919766 1
1.5%
455324.155870975 1
1.5%
454640.971129672 1
1.5%
454435.879584332 1
1.5%
454165.72746027 2
2.9%
454103.425915978 1
1.5%
454100.932592147 1
1.5%
453883.297637547 1
1.5%
453873.164675531 1
1.5%

위생업태명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
집단급식소 식품판매업
57 
<NA>
11 

Length

Max length11
Median length11
Mean length9.8676471
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row집단급식소 식품판매업
2nd row집단급식소 식품판매업
3rd row집단급식소 식품판매업
4th row집단급식소 식품판매업
5th row집단급식소 식품판매업

Common Values

ValueCountFrequency (%)
집단급식소 식품판매업 57
83.8%
<NA> 11
 
16.2%

Length

2024-05-11T15:29:19.651879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:19.814571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 57
45.6%
식품판매업 57
45.6%
na 11
 
8.8%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
0
 
1

Length

Max length4
Median length4
Mean length3.9558824
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
0 1
 
1.5%

Length

2024-05-11T15:29:20.002892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:20.193208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
0 1
 
1.5%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
0
 
1

Length

Max length4
Median length4
Mean length3.9558824
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
0 1
 
1.5%

Length

2024-05-11T15:29:20.406340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:20.636074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
0 1
 
1.5%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

급수시설구분명
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
45 
상수도전용
23 

Length

Max length5
Median length4
Mean length4.3382353
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
66.2%
상수도전용 23
33.8%

Length

2024-05-11T15:29:20.817708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:20.970134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
66.2%
상수도전용 23
33.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
0
 
1

Length

Max length4
Median length4
Mean length3.9558824
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
0 1
 
1.5%

Length

2024-05-11T15:29:21.120035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:21.291617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
0 1
 
1.5%

본사종업원수
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
24 
1
 
1

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 24
35.3%
1 1
 
1.5%

Length

2024-05-11T15:29:21.456977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:21.605725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 24
35.3%
1 1
 
1.5%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
25 

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 25
36.8%

Length

2024-05-11T15:29:21.774746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:21.941887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 25
36.8%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
25 

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 25
36.8%

Length

2024-05-11T15:29:22.122977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:22.272332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 25
36.8%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
43 
0
25 

Length

Max length4
Median length4
Mean length2.8970588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
63.2%
0 25
36.8%

Length

2024-05-11T15:29:22.427135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:22.601841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
63.2%
0 25
36.8%

건물소유구분명
Categorical

Distinct3
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
36 
임대
24 
자가
8 

Length

Max length4
Median length4
Mean length3.0588235
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
52.9%
임대 24
35.3%
자가 8
 
11.8%

Length

2024-05-11T15:29:22.803883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:22.981306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
52.9%
임대 24
35.3%
자가 8
 
11.8%

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
0
 
1

Length

Max length4
Median length4
Mean length3.9558824
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
0 1
 
1.5%

Length

2024-05-11T15:29:23.536626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:23.759889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
0 1
 
1.5%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size676.0 B
<NA>
67 
0
 
1

Length

Max length4
Median length4
Mean length3.9558824
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 67
98.5%
0 1
 
1.5%

Length

2024-05-11T15:29:23.954320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:29:24.163959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 67
98.5%
0 1
 
1.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.8%
Missing11
Missing (%)16.2%
Memory size268.0 B
False
57 
(Missing)
11 
ValueCountFrequency (%)
False 57
83.8%
(Missing) 11
 
16.2%
2024-05-11T15:29:24.346667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)42.1%
Missing11
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean19.774035
Minimum0
Maximum150
Zeros32
Zeros (%)47.1%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-05-11T15:29:24.496029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q327.95
95-th percentile85.6
Maximum150
Range150
Interquartile range (IQR)27.95

Descriptive statistics

Standard deviation33.468857
Coefficient of variation (CV)1.6925659
Kurtosis4.3377086
Mean19.774035
Median Absolute Deviation (MAD)0
Skewness2.0861457
Sum1127.12
Variance1120.1644
MonotonicityNot monotonic
2024-05-11T15:29:24.681781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 32
47.1%
9.9 2
 
2.9%
23.0 2
 
2.9%
50.0 1
 
1.5%
27.95 1
 
1.5%
54.0 1
 
1.5%
12.0 1
 
1.5%
33.0 1
 
1.5%
3.75 1
 
1.5%
82.0 1
 
1.5%
Other values (14) 14
20.6%
(Missing) 11
 
16.2%
ValueCountFrequency (%)
0.0 32
47.1%
3.75 1
 
1.5%
9.82 1
 
1.5%
9.9 2
 
2.9%
9.93 1
 
1.5%
10.2 1
 
1.5%
12.0 1
 
1.5%
17.55 1
 
1.5%
23.0 2
 
2.9%
27.95 1
 
1.5%
ValueCountFrequency (%)
150.0 1
1.5%
120.0 1
1.5%
100.0 1
1.5%
82.0 1
1.5%
80.0 1
1.5%
66.0 1
1.5%
55.8 1
1.5%
54.0 1
1.5%
51.8 1
1.5%
50.0 1
1.5%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing68
Missing (%)100.0%
Memory size744.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-122-2008-0000120080319<NA>1영업/정상1영업<NA><NA><NA><NA>02 2294362332.5130827서울특별시 동대문구 이문동 63-9서울특별시 동대문구 한천로58길 75-7 (이문동)2423신광유통2012-10-02 16:27:34I2018-08-31 23:59:59.0집단급식소 식품판매업206070.293927455324.155871집단급식소 식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
130500003050000-122-2008-0000220080407<NA>3폐업2폐업20120529<NA><NA><NA>02 969 130199.9130869서울특별시 동대문구 청량리동 348 1층(마파람길11)<NA><NA>시온유통2010-06-03 13:53:21I2018-08-31 23:59:59.0집단급식소 식품판매업203841.428655453546.030088집단급식소 식품판매업<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
230500003050000-122-2008-0000320080609<NA>3폐업2폐업20080808<NA><NA><NA>02924 794582.5130823서울특별시 동대문구 용두동 237-60<NA><NA>맥고야2008-06-09 10:35:30I2018-08-31 23:59:59.0집단급식소 식품판매업202930.067173452601.926803집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
330500003050000-122-2008-0000420080613<NA>3폐업2폐업20091204<NA><NA><NA>022247404017.4130878서울특별시 동대문구 휘경동 286-4<NA><NA>현미상회2008-06-16 08:55:48I2018-08-31 23:59:59.0집단급식소 식품판매업205411.097836454103.425916집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
430500003050000-122-2008-0000520080728<NA>3폐업2폐업20101229<NA><NA><NA>02967509849.5130817서울특별시 동대문구 용두동 39-1<NA><NA>삼호물산2011-01-07 09:18:56I2018-08-31 23:59:59.0집단급식소 식품판매업203728.132136452778.893307집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
530500003050000-122-2008-0000620080812<NA>1영업/정상1영업<NA><NA><NA><NA>026223010419.83130863서울특별시 동대문구 제기동 896 [경동시장로9길18-3]서울특별시 동대문구 약령시로14길 29 (제기동,[경동시장로9길18-3])2571후암유통2010-11-30 17:37:36I2018-08-31 23:59:59.0집단급식소 식품판매업203396.659013453249.868409집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000자가<NA><NA>N0.0<NA><NA><NA>
630500003050000-122-2008-0000720080825<NA>3폐업2폐업20190219<NA><NA><NA>02 967 697826.0130864서울특별시 동대문구 제기동 859-30서울특별시 동대문구 정릉천동로 154 (제기동)2478삼육식품2019-02-19 15:20:38U2019-02-21 02:40:00.0집단급식소 식품판매업203190.301135453716.425752집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730500003050000-122-2008-0000820080828<NA>3폐업2폐업20081031<NA><NA><NA>022215300433.0130878서울특별시 동대문구 휘경동 285-1<NA><NA>건강의 샘2008-08-28 13:49:03I2018-08-31 23:59:59.0집단급식소 식품판매업205432.512871454100.932592집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
830500003050000-122-2008-0000920080917<NA>3폐업2폐업20100119<NA><NA><NA>0221746210902.85130810서울특별시 동대문구 신설동 76-10 지상3, 7층<NA><NA>한화리조트(주)2009-01-14 16:04:31I2018-08-31 23:59:59.0집단급식소 식품판매업202185.938539452713.196952집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
930500003050000-122-2008-0001020080925<NA>1영업/정상1영업<NA><NA><NA><NA>02923 333749.5130820서울특별시 동대문구 용두동 102-35 2층 1호서울특별시 동대문구 천호대로23길 19-1 (용두동,2층 1호)2585경기식품2011-12-02 14:18:21I2018-08-31 23:59:59.0집단급식소 식품판매업202875.632668452527.328721집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
5830500003050000-122-2019-0000220191113<NA>1영업/정상1영업<NA><NA><NA><NA><NA>54.0130030서울특별시 동대문구 답십리동 989-1 우성그린아파트서울특별시 동대문구 답십리로59길 33, 1층 102호 (답십리동, 우성그린아파트)2535영일만축산2019-11-13 13:44:02I2019-11-15 00:23:15.0집단급식소 식품판매업205762.994263452510.004743집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N54.0<NA><NA><NA>
5930500003050000-122-2019-0000320191212<NA>3폐업2폐업20221221<NA><NA><NA><NA>33.0130865서울특별시 동대문구 제기동 1019 경동시장서울특별시 동대문구 고산자로36길 3, 경동시장 지하1층 40511호 (제기동)2571형제정육점2022-12-21 11:44:49U2021-11-01 22:03:00.0집단급식소 식품판매업203403.019535452985.72542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6030500003050000-122-2020-0000120200227<NA>1영업/정상1영업<NA><NA><NA><NA><NA>27.95130862서울특별시 동대문구 제기동 287-23서울특별시 동대문구 홍릉로15길 22, 1층 (제기동)2480해들식품2022-02-03 11:22:19I2022-02-05 00:22:38.0집단급식소 식품판매업203658.848247453675.702599집단급식소 식품판매업00<NA><NA><NA>01000<NA>00N27.95<NA><NA><NA>
6130500003050000-122-2021-0000120211111<NA>3폐업2폐업20221027<NA><NA><NA>02 6715711630.0130805서울특별시 동대문구 답십리동 497-67서울특별시 동대문구 천호대로 263, 3층 (답십리동)2603(주) 초록마을2022-10-27 10:44:23U2021-10-30 22:09:00.0집단급식소 식품판매업204447.698148451803.558407<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6230500003050000-122-2023-000012023-02-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0130-883서울특별시 동대문구 답십리동 29-60서울특별시 동대문구 답십리로48길 82, 1층 (답십리동)2615신선유통2023-02-07 14:46:29I2022-12-02 00:09:00.0집단급식소 식품판매업205011.345721451870.778303<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6330500003050000-122-2023-000022023-02-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.9130-847서울특별시 동대문구 장안동 555-1 한신아파트서울특별시 동대문구 사가정로 245-3, 106호 (장안동, 한신아파트)2515가나식품2023-08-16 15:19:20U2022-12-07 23:08:00.0집단급식소 식품판매업206282.745291453027.766626<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6430500003050000-122-2023-000032023-06-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 33958011127.8130-804서울특별시 동대문구 답십리동 465-72서울특별시 동대문구 천호대로 219, 1층 (답십리동)2597(주)영찬2023-06-27 10:18:41I2022-12-05 22:09:00.0집단급식소 식품판매업204097.201777452075.510388<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6530500003050000-122-2023-000042023-08-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>51.72130-864서울특별시 동대문구 제기동 730-3서울특별시 동대문구 약령중앙로 76, 지하층 (제기동)2478올프렌즈2023-08-14 11:26:43I2022-12-07 23:07:00.0집단급식소 식품판매업203254.983165453641.433838<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6630500003050000-122-2024-000012024-01-19<NA>3폐업2폐업2024-04-26<NA><NA><NA>033 732 862416.52130-872서울특별시 동대문구 회기동 16-71서울특별시 동대문구 경희대로 7, 1층 (회기동)2454끌레베르 경희대 직영본점2024-04-26 09:42:14U2023-12-03 22:08:00.0집단급식소 식품판매업204540.905552454435.879584<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6730500003050000-122-2024-000022024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.0130-875서울특별시 동대문구 휘경동 118-22서울특별시 동대문구 휘경로 71, 2층 (휘경동)2428애드플러스2024-05-02 14:35:27I2023-12-05 00:04:00.0집단급식소 식품판매업205912.152705454640.97113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>