Overview

Dataset statistics

Number of variables44
Number of observations46
Missing cells486
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.1 KiB
Average record size in memory380.9 B

Variable types

Categorical19
Text6
DateTime4
Unsupported9
Numeric5
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-18036/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (84.9%)Imbalance
여성종사자수 is highly imbalanced (84.9%)Imbalance
총인원 is highly imbalanced (84.9%)Imbalance
보증액 is highly imbalanced (77.4%)Imbalance
월세액 is highly imbalanced (74.2%)Imbalance
인허가취소일자 has 46 (100.0%) missing valuesMissing
폐업일자 has 15 (32.6%) missing valuesMissing
휴업시작일자 has 46 (100.0%) missing valuesMissing
휴업종료일자 has 46 (100.0%) missing valuesMissing
재개업일자 has 46 (100.0%) missing valuesMissing
전화번호 has 20 (43.5%) missing valuesMissing
소재지면적 has 1 (2.2%) missing valuesMissing
도로명주소 has 5 (10.9%) missing valuesMissing
도로명우편번호 has 5 (10.9%) missing valuesMissing
영업장주변구분명 has 46 (100.0%) missing valuesMissing
등급구분명 has 46 (100.0%) missing valuesMissing
다중이용업소여부 has 13 (28.3%) missing valuesMissing
시설총규모 has 13 (28.3%) missing valuesMissing
전통업소지정번호 has 46 (100.0%) missing valuesMissing
전통업소주된음식 has 46 (100.0%) missing valuesMissing
홈페이지 has 46 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가일자 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 25 (54.3%) zerosZeros

Reproduction

Analysis started2024-05-11 04:04:03.750988
Analysis finished2024-05-11 04:04:05.120409
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
3090000
46 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3090000
2nd row3090000
3rd row3090000
4th row3090000
5th row3090000

Common Values

ValueCountFrequency (%)
3090000 46
100.0%

Length

2024-05-11T04:04:05.395481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:05.877855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3090000 46
100.0%

관리번호
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T04:04:06.288632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1012
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

Unique46 ?
Unique (%)100.0%

Sample

1st row3090000-122-2008-00001
2nd row3090000-122-2008-00002
3rd row3090000-122-2008-00003
4th row3090000-122-2008-00004
5th row3090000-122-2009-00001
ValueCountFrequency (%)
3090000-122-2008-00001 1
 
2.2%
3090000-122-2016-00002 1
 
2.2%
3090000-122-2023-00002 1
 
2.2%
3090000-122-2015-00001 1
 
2.2%
3090000-122-2015-00002 1
 
2.2%
3090000-122-2015-00003 1
 
2.2%
3090000-122-2015-00004 1
 
2.2%
3090000-122-2015-00005 1
 
2.2%
3090000-122-2015-00006 1
 
2.2%
3090000-122-2015-00007 1
 
2.2%
Other values (36) 36
78.3%
2024-05-11T04:04:07.365521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 473
46.7%
2 157
 
15.5%
- 138
 
13.6%
1 98
 
9.7%
3 62
 
6.1%
9 53
 
5.2%
5 10
 
1.0%
4 8
 
0.8%
7 5
 
0.5%
8 4
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 874
86.4%
Dash Punctuation 138
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 473
54.1%
2 157
 
18.0%
1 98
 
11.2%
3 62
 
7.1%
9 53
 
6.1%
5 10
 
1.1%
4 8
 
0.9%
7 5
 
0.6%
8 4
 
0.5%
6 4
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 473
46.7%
2 157
 
15.5%
- 138
 
13.6%
1 98
 
9.7%
3 62
 
6.1%
9 53
 
5.2%
5 10
 
1.0%
4 8
 
0.8%
7 5
 
0.5%
8 4
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 473
46.7%
2 157
 
15.5%
- 138
 
13.6%
1 98
 
9.7%
3 62
 
6.1%
9 53
 
5.2%
5 10
 
1.0%
4 8
 
0.8%
7 5
 
0.5%
8 4
 
0.4%

인허가일자
Date

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2008-03-17 00:00:00
Maximum2024-01-03 00:00:00
2024-05-11T04:04:07.847550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:04:08.289211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
3
31 
1
15 

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 31
67.4%
1 15
32.6%

Length

2024-05-11T04:04:08.864226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:09.329982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 31
67.4%
1 15
32.6%

영업상태명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
폐업
31 
영업/정상
15 

Length

Max length5
Median length2
Mean length2.9782609
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 31
67.4%
영업/정상 15
32.6%

Length

2024-05-11T04:04:09.850330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:10.272256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 31
67.4%
영업/정상 15
32.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
2
31 
1
15 

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 31
67.4%
1 15
32.6%

Length

2024-05-11T04:04:10.662812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:11.100804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 31
67.4%
1 15
32.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
폐업
31 
영업
15 

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 31
67.4%
영업 15
32.6%

Length

2024-05-11T04:04:11.479330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:11.833469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 31
67.4%
영업 15
32.6%

폐업일자
Date

MISSING 

Distinct25
Distinct (%)80.6%
Missing15
Missing (%)32.6%
Memory size500.0 B
Minimum2010-11-11 00:00:00
Maximum2024-04-26 00:00:00
2024-05-11T04:04:12.301609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:04:12.826651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

전화번호
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing20
Missing (%)43.5%
Memory size500.0 B
2024-05-11T04:04:13.358875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.846154
Min length8

Characters and Unicode

Total characters282
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 (%)100.0%

Sample

1st row02 34923682
2nd row907 8240
3rd row977 0811
4th row029737972
5th row02 954 0126
ValueCountFrequency (%)
02 14
26.4%
907 2
 
3.8%
8240 2
 
3.8%
031 2
 
3.8%
0260539330 1
 
1.9%
070 1
 
1.9%
82815541 1
 
1.9%
16886438 1
 
1.9%
955 1
 
1.9%
4297 1
 
1.9%
Other values (27) 27
50.9%
2024-05-11T04:04:14.458176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 46
16.3%
37
13.1%
2 36
12.8%
9 28
9.9%
7 22
7.8%
5 21
7.4%
6 20
7.1%
1 19
6.7%
8 18
 
6.4%
3 18
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 245
86.9%
Space Separator 37
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 46
18.8%
2 36
14.7%
9 28
11.4%
7 22
9.0%
5 21
8.6%
6 20
8.2%
1 19
7.8%
8 18
 
7.3%
3 18
 
7.3%
4 17
 
6.9%
Space Separator
ValueCountFrequency (%)
37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 46
16.3%
37
13.1%
2 36
12.8%
9 28
9.9%
7 22
7.8%
5 21
7.4%
6 20
7.1%
1 19
6.7%
8 18
 
6.4%
3 18
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 46
16.3%
37
13.1%
2 36
12.8%
9 28
9.9%
7 22
7.8%
5 21
7.4%
6 20
7.1%
1 19
6.7%
8 18
 
6.4%
3 18
 
6.4%

소재지면적
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)73.3%
Missing1
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean52.927778
Minimum3.3
Maximum495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T04:04:14.930396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile6.74
Q122
median30
Q356
95-th percentile128.12
Maximum495
Range491.7
Interquartile range (IQR)34

Descriptive statistics

Standard deviation84.207081
Coefficient of variation (CV)1.5909808
Kurtosis19.671825
Mean52.927778
Median Absolute Deviation (MAD)12
Skewness4.2727258
Sum2381.75
Variance7090.8324
MonotonicityNot monotonic
2024-05-11T04:04:15.386829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
25.0 4
 
8.7%
22.0 3
 
6.5%
24.94 3
 
6.5%
33.0 3
 
6.5%
30.0 2
 
4.3%
3.3 2
 
4.3%
56.0 2
 
4.3%
20.0 1
 
2.2%
9.3 1
 
2.2%
54.0 1
 
2.2%
Other values (23) 23
50.0%
ValueCountFrequency (%)
3.3 2
4.3%
6.1 1
 
2.2%
9.3 1
 
2.2%
10.0 1
 
2.2%
16.5 1
 
2.2%
17.0 1
 
2.2%
17.04 1
 
2.2%
17.83 1
 
2.2%
20.0 1
 
2.2%
22.0 3
6.5%
ValueCountFrequency (%)
495.0 1
2.2%
330.0 1
2.2%
135.0 1
2.2%
100.6 1
2.2%
68.87 1
2.2%
66.0 1
2.2%
63.42 1
2.2%
63.0 1
2.2%
62.62 1
2.2%
60.0 1
2.2%

소재지우편번호
Text

Distinct29
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T04:04:15.979014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1304348
Min length6

Characters and Unicode

Total characters282
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

Unique21 ?
Unique (%)45.7%

Sample

1st row132819
2nd row132918
3rd row132898
4th row132906
5th row132959
ValueCountFrequency (%)
132839 6
 
13.0%
132918 4
 
8.7%
132842 3
 
6.5%
132-898 3
 
6.5%
132820 3
 
6.5%
132819 2
 
4.3%
132821 2
 
4.3%
132845 2
 
4.3%
132898 1
 
2.2%
132809 1
 
2.2%
Other values (19) 19
41.3%
2024-05-11T04:04:17.033467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
21.6%
2 57
20.2%
3 55
19.5%
8 42
14.9%
9 29
10.3%
0 15
 
5.3%
4 8
 
2.8%
- 6
 
2.1%
5 5
 
1.8%
7 3
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 276
97.9%
Dash Punctuation 6
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 61
22.1%
2 57
20.7%
3 55
19.9%
8 42
15.2%
9 29
10.5%
0 15
 
5.4%
4 8
 
2.9%
5 5
 
1.8%
7 3
 
1.1%
6 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 61
21.6%
2 57
20.2%
3 55
19.5%
8 42
14.9%
9 29
10.3%
0 15
 
5.3%
4 8
 
2.8%
- 6
 
2.1%
5 5
 
1.8%
7 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
21.6%
2 57
20.2%
3 55
19.5%
8 42
14.9%
9 29
10.3%
0 15
 
5.3%
4 8
 
2.8%
- 6
 
2.1%
5 5
 
1.8%
7 3
 
1.1%

지번주소
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T04:04:17.709065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length22.804348
Min length14

Characters and Unicode

Total characters1049
Distinct characters63
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)91.3%

Sample

1st row서울특별시 도봉구 도봉동 603-1
2nd row서울특별시 도봉구 창동 585-23
3rd row서울특별시 도봉구 창동 1-10
4th row서울특별시 도봉구 창동 263-8
5th row서울특별시 도봉구 창동 578-17 1층
ValueCountFrequency (%)
서울특별시 46
20.5%
도봉구 46
20.5%
창동 18
 
8.0%
방학동 16
 
7.1%
1층 16
 
7.1%
도봉동 11
 
4.9%
617-5 3
 
1.3%
101호 3
 
1.3%
9 2
 
0.9%
611-4 2
 
0.9%
Other values (57) 61
27.2%
2024-05-11T04:04:19.016415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
209
19.9%
봉 58
 
5.5%
도 58
 
5.5%
1 55
 
5.2%
서 46
 
4.4%
울 46
 
4.4%
구 46
 
4.4%
동 46
 
4.4%
시 46
 
4.4%
별 46
 
4.4%
Other values (53) 393
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 562
53.6%
Decimal Number 234
22.3%
Space Separator 209
 
19.9%
Dash Punctuation 38
 
3.6%
Lowercase Letter 3
 
0.3%
Uppercase Letter 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 58
10.3%
도 58
10.3%
서 46
8.2%
울 46
8.2%
구 46
8.2%
동 46
8.2%
시 46
8.2%
별 46
8.2%
특 46
8.2%
층 21
 
3.7%
Other values (35) 103
18.3%
Decimal Number
ValueCountFrequency (%)
1 55
23.5%
2 31
13.2%
6 28
12.0%
5 22
 
9.4%
3 21
 
9.0%
8 20
 
8.5%
0 15
 
6.4%
9 14
 
6.0%
4 14
 
6.0%
7 14
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
d 1
33.3%
c 1
33.3%
m 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 562
53.6%
Common 482
45.9%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 58
10.3%
도 58
10.3%
서 46
8.2%
울 46
8.2%
구 46
8.2%
동 46
8.2%
시 46
8.2%
별 46
8.2%
특 46
8.2%
층 21
 
3.7%
Other values (35) 103
18.3%
Common
ValueCountFrequency (%)
209
43.4%
1 55
 
11.4%
- 38
 
7.9%
2 31
 
6.4%
6 28
 
5.8%
5 22
 
4.6%
3 21
 
4.4%
8 20
 
4.1%
0 15
 
3.1%
9 14
 
2.9%
Other values (3) 29
 
6.0%
Latin
ValueCountFrequency (%)
d 1
20.0%
c 1
20.0%
B 1
20.0%
A 1
20.0%
m 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 562
53.6%
ASCII 487
46.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
209
42.9%
1 55
 
11.3%
- 38
 
7.8%
2 31
 
6.4%
6 28
 
5.7%
5 22
 
4.5%
3 21
 
4.3%
8 20
 
4.1%
0 15
 
3.1%
9 14
 
2.9%
Other values (8) 34
 
7.0%
Hangul
ValueCountFrequency (%)
봉 58
10.3%
도 58
10.3%
서 46
8.2%
울 46
8.2%
구 46
8.2%
동 46
8.2%
시 46
8.2%
별 46
8.2%
특 46
8.2%
층 21
 
3.7%
Other values (35) 103
18.3%

도로명주소
Text

MISSING 

Distinct39
Distinct (%)95.1%
Missing5
Missing (%)10.9%
Memory size500.0 B
2024-05-11T04:04:19.670509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length31.780488
Min length25

Characters and Unicode

Total characters1303
Distinct characters87
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

Unique37 ?
Unique (%)90.2%

Sample

1st row서울특별시 도봉구 시루봉로27길 62 (도봉동)
2nd row서울특별시 도봉구 해등로16길 94, 5층 (창동)
3rd row서울특별시 도봉구 덕릉로59가길 51 (창동,1층)
4th row서울특별시 도봉구 도봉로136다길 26-1, 2층 (창동)
5th row서울특별시 도봉구 도봉로170길 8, 2층 224호 (도봉동)
ValueCountFrequency (%)
서울특별시 41
 
16.2%
도봉구 41
 
16.2%
1층 17
 
6.7%
방학동 14
 
5.5%
창동 11
 
4.3%
도봉동 10
 
4.0%
시루봉로 6
 
2.4%
191-1 3
 
1.2%
2층 3
 
1.2%
2 2
 
0.8%
Other values (92) 105
41.5%
2024-05-11T04:04:21.395735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
16.3%
1 85
 
6.5%
봉 73
 
5.6%
도 70
 
5.4%
시 51
 
3.9%
동 43
 
3.3%
울 41
 
3.1%
( 41
 
3.1%
로 41
 
3.1%
서 41
 
3.1%
Other values (77) 605
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 711
54.6%
Decimal Number 241
 
18.5%
Space Separator 212
 
16.3%
Open Punctuation 41
 
3.1%
Close Punctuation 41
 
3.1%
Other Punctuation 37
 
2.8%
Dash Punctuation 13
 
1.0%
Uppercase Letter 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 73
 
10.3%
도 70
 
9.8%
시 51
 
7.2%
동 43
 
6.0%
울 41
 
5.8%
로 41
 
5.8%
서 41
 
5.8%
구 41
 
5.8%
별 41
 
5.8%
특 41
 
5.8%
Other values (56) 228
32.1%
Decimal Number
ValueCountFrequency (%)
1 85
35.3%
2 35
14.5%
6 21
 
8.7%
5 20
 
8.3%
9 18
 
7.5%
0 16
 
6.6%
4 15
 
6.2%
3 12
 
5.0%
8 10
 
4.1%
7 9
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
E 1
14.3%
P 1
14.3%
T 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 36
97.3%
. 1
 
2.7%
Space Separator
ValueCountFrequency (%)
212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 711
54.6%
Common 585
44.9%
Latin 7
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 73
 
10.3%
도 70
 
9.8%
시 51
 
7.2%
동 43
 
6.0%
울 41
 
5.8%
로 41
 
5.8%
서 41
 
5.8%
구 41
 
5.8%
별 41
 
5.8%
특 41
 
5.8%
Other values (56) 228
32.1%
Common
ValueCountFrequency (%)
212
36.2%
1 85
14.5%
( 41
 
7.0%
) 41
 
7.0%
, 36
 
6.2%
2 35
 
6.0%
6 21
 
3.6%
5 20
 
3.4%
9 18
 
3.1%
0 16
 
2.7%
Other values (6) 60
 
10.3%
Latin
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
E 1
14.3%
P 1
14.3%
T 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 711
54.6%
ASCII 592
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
35.8%
1 85
14.4%
( 41
 
6.9%
) 41
 
6.9%
, 36
 
6.1%
2 35
 
5.9%
6 21
 
3.5%
5 20
 
3.4%
9 18
 
3.0%
0 16
 
2.7%
Other values (11) 67
 
11.3%
Hangul
ValueCountFrequency (%)
봉 73
 
10.3%
도 70
 
9.8%
시 51
 
7.2%
동 43
 
6.0%
울 41
 
5.8%
로 41
 
5.8%
서 41
 
5.8%
구 41
 
5.8%
별 41
 
5.8%
특 41
 
5.8%
Other values (56) 228
32.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)75.6%
Missing5
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean1369.4146
Minimum1308
Maximum1476
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T04:04:21.799471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1308
5-th percentile1310
Q11318
median1352
Q31410
95-th percentile1472
Maximum1476
Range168
Interquartile range (IQR)92

Descriptive statistics

Standard deviation55.19238
Coefficient of variation (CV)0.040303629
Kurtosis-0.76298775
Mean1369.4146
Median Absolute Deviation (MAD)37
Skewness0.70750678
Sum56146
Variance3046.1988
MonotonicityNot monotonic
2024-05-11T04:04:22.254957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1315 5
 
10.9%
1357 3
 
6.5%
1414 2
 
4.3%
1349 2
 
4.3%
1405 2
 
4.3%
1347 2
 
4.3%
1468 1
 
2.2%
1313 1
 
2.2%
1476 1
 
2.2%
1318 1
 
2.2%
Other values (21) 21
45.7%
(Missing) 5
 
10.9%
ValueCountFrequency (%)
1308 1
 
2.2%
1309 1
 
2.2%
1310 1
 
2.2%
1313 1
 
2.2%
1314 1
 
2.2%
1315 5
10.9%
1318 1
 
2.2%
1321 1
 
2.2%
1325 1
 
2.2%
1327 1
 
2.2%
ValueCountFrequency (%)
1476 1
2.2%
1474 1
2.2%
1472 1
2.2%
1471 1
2.2%
1468 1
2.2%
1463 1
2.2%
1422 1
2.2%
1414 2
4.3%
1413 1
2.2%
1410 1
2.2%

사업장명
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T04:04:22.945623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length6.2608696
Min length3

Characters and Unicode

Total characters288
Distinct characters108
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)91.3%

Sample

1st row동원그린유통
2nd row동서유통
3rd row창동하나로곡류특판
4th row대농바이오영농조합농수산
5th row대갑유통
ValueCountFrequency (%)
민속김치 2
 
3.9%
세빈푸드 2
 
3.9%
미소식품 1
 
2.0%
주)위프 1
 
2.0%
서울지점 1
 
2.0%
동원그린유통 1
 
2.0%
동서유통 1
 
2.0%
한진식품 1
 
2.0%
주)대한한울 1
 
2.0%
채소나라 1
 
2.0%
Other values (39) 39
76.5%
2024-05-11T04:04:23.851375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 14
 
4.9%
주 14
 
4.9%
) 14
 
4.9%
푸 11
 
3.8%
드 10
 
3.5%
농 10
 
3.5%
통 8
 
2.8%
유 8
 
2.8%
산 7
 
2.4%
식 6
 
2.1%
Other values (98) 186
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
88.5%
Open Punctuation 14
 
4.9%
Close Punctuation 14
 
4.9%
Space Separator 5
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 14
 
5.5%
푸 11
 
4.3%
드 10
 
3.9%
농 10
 
3.9%
통 8
 
3.1%
유 8
 
3.1%
산 7
 
2.7%
식 6
 
2.4%
품 6
 
2.4%
한 6
 
2.4%
Other values (95) 169
66.3%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
88.5%
Common 33
 
11.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 14
 
5.5%
푸 11
 
4.3%
드 10
 
3.9%
농 10
 
3.9%
통 8
 
3.1%
유 8
 
3.1%
산 7
 
2.7%
식 6
 
2.4%
품 6
 
2.4%
한 6
 
2.4%
Other values (95) 169
66.3%
Common
ValueCountFrequency (%)
( 14
42.4%
) 14
42.4%
5
 
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
88.5%
ASCII 33
 
11.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 14
42.4%
) 14
42.4%
5
 
15.2%
Hangul
ValueCountFrequency (%)
주 14
 
5.5%
푸 11
 
4.3%
드 10
 
3.9%
농 10
 
3.9%
통 8
 
3.1%
유 8
 
3.1%
산 7
 
2.7%
식 6
 
2.4%
품 6
 
2.4%
한 6
 
2.4%
Other values (95) 169
66.3%

최종수정일자
Date

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2008-03-21 16:48:43
Maximum2024-04-26 14:05:48
2024-05-11T04:04:24.219022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:04:24.644051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
I
24 
U
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 24
52.2%
U 22
47.8%

Length

2024-05-11T04:04:24.994001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:25.288348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 24
52.2%
u 22
47.8%

데이터갱신일자
Date

Distinct23
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:08:00
2024-05-11T04:04:25.561253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:04:25.976269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
집단급식소 식품판매업
46 

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 46
100.0%

Length

2024-05-11T04:04:26.354292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:26.652844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 46
50.0%
식품판매업 46
50.0%

좌표정보(X)
Real number (ℝ)

Distinct38
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203407.41
Minimum201295.45
Maximum204413.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T04:04:27.177023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201295.45
5-th percentile202653.07
Q1202981.88
median203469.91
Q3203894.92
95-th percentile204345.83
Maximum204413.62
Range3118.1668
Interquartile range (IQR)913.03041

Descriptive statistics

Standard deviation644.70158
Coefficient of variation (CV)0.0031695089
Kurtosis1.1745139
Mean203407.41
Median Absolute Deviation (MAD)460.69574
Skewness-0.70269687
Sum9356740.8
Variance415640.13
MonotonicityNot monotonic
2024-05-11T04:04:27.582407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
202751.355 3
 
6.5%
203062.318246725 2
 
4.3%
204413.616574592 2
 
4.3%
203032.117712116 2
 
4.3%
202653.072678853 2
 
4.3%
204345.826664906 2
 
4.3%
203472.993066508 2
 
4.3%
203518.403974345 1
 
2.2%
203413.480080383 1
 
2.2%
202804.611963049 1
 
2.2%
Other values (28) 28
60.9%
ValueCountFrequency (%)
201295.449760602 1
 
2.2%
202086.881864109 1
 
2.2%
202653.072678853 2
4.3%
202751.355 3
6.5%
202804.611963049 1
 
2.2%
202849.341485463 1
 
2.2%
202942.061116816 1
 
2.2%
202951.176727644 1
 
2.2%
202965.140259028 1
 
2.2%
203032.117712116 2
4.3%
ValueCountFrequency (%)
204413.616574592 2
4.3%
204345.826664906 2
4.3%
204214.210632572 1
2.2%
204169.847670316 1
2.2%
204136.58447783 1
2.2%
203985.566277234 1
2.2%
203984.137173444 1
2.2%
203974.826951671 1
2.2%
203953.509197376 1
2.2%
203901.637804203 1
2.2%

좌표정보(Y)
Real number (ℝ)

Distinct38
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean462081.57
Minimum459467.61
Maximum464814.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T04:04:27.930086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum459467.61
5-th percentile459607.94
Q1461119.96
median462591.32
Q3462999.12
95-th percentile463926.6
Maximum464814.72
Range5347.1036
Interquartile range (IQR)1879.1656

Descriptive statistics

Standard deviation1409.9242
Coefficient of variation (CV)0.0030512454
Kurtosis-0.71037202
Mean462081.57
Median Absolute Deviation (MAD)863.3525
Skewness-0.45237958
Sum21255752
Variance1987886.4
MonotonicityNot monotonic
2024-05-11T04:04:28.455990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
462687.56 3
 
6.5%
459687.916963478 2
 
4.3%
461378.588676784 2
 
4.3%
462810.857864872 2
 
4.3%
462907.777925026 2
 
4.3%
461119.957690091 2
 
4.3%
463167.997413815 2
 
4.3%
459821.84648093 1
 
2.2%
462906.521140092 1
 
2.2%
462690.957655527 1
 
2.2%
Other values (28) 28
60.9%
ValueCountFrequency (%)
459467.613847618 1
2.2%
459499.0514426 1
2.2%
459581.284179201 1
2.2%
459687.916963478 2
4.3%
459821.84648093 1
2.2%
459861.837337547 1
2.2%
460135.037622894 1
2.2%
460746.553675666 1
2.2%
461008.914009807 1
2.2%
461040.287040565 1
2.2%
ValueCountFrequency (%)
464814.717432497 1
2.2%
464212.297931928 1
2.2%
463990.79883758 1
2.2%
463733.991468683 1
2.2%
463573.102150294 1
2.2%
463523.566914004 1
2.2%
463385.78557338 1
2.2%
463382.646082016 1
2.2%
463167.997413815 2
4.3%
463117.539126587 1
2.2%

위생업태명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
집단급식소 식품판매업
33 
<NA>
13 

Length

Max length11
Median length11
Mean length9.0217391
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 33
71.7%
<NA> 13
 
28.3%

Length

2024-05-11T04:04:29.167696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:29.647039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 33
41.8%
식품판매업 33
41.8%
na 13
 
16.5%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
45 
0
 
1

Length

Max length4
Median length4
Mean length3.9347826
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
97.8%
0 1
 
2.2%

Length

2024-05-11T04:04:30.010509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:30.420661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
97.8%
0 1
 
2.2%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
45 
0
 
1

Length

Max length4
Median length4
Mean length3.9347826
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
97.8%
0 1
 
2.2%

Length

2024-05-11T04:04:30.934024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:31.323897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
97.8%
0 1
 
2.2%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

급수시설구분명
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
40 
상수도전용
6 

Length

Max length5
Median length4
Mean length4.1304348
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 40
87.0%
상수도전용 6
 
13.0%

Length

2024-05-11T04:04:31.813723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:32.107763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
87.0%
상수도전용 6
 
13.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
45 
0
 
1

Length

Max length4
Median length4
Mean length3.9347826
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
97.8%
0 1
 
2.2%

Length

2024-05-11T04:04:32.440235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:32.709377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
97.8%
0 1
 
2.2%

본사종업원수
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
36 
0
10 

Length

Max length4
Median length4
Mean length3.3478261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
78.3%
0 10
 
21.7%

Length

2024-05-11T04:04:33.060822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:33.375739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
78.3%
0 10
 
21.7%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
36 
0
10 

Length

Max length4
Median length4
Mean length3.3478261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
78.3%
0 10
 
21.7%

Length

2024-05-11T04:04:33.814093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:34.204658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
78.3%
0 10
 
21.7%

공장판매직종업원수
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
36 
0
10 

Length

Max length4
Median length4
Mean length3.3478261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
78.3%
0 10
 
21.7%

Length

2024-05-11T04:04:34.669269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:35.095011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
78.3%
0 10
 
21.7%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
36 
0
10 

Length

Max length4
Median length4
Mean length3.3478261
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 36
78.3%
0 10
 
21.7%

Length

2024-05-11T04:04:35.544540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:35.979142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
78.3%
0 10
 
21.7%

건물소유구분명
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
28 
임대
16 
자가
 
2

Length

Max length4
Median length4
Mean length3.2173913
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
60.9%
임대 16
34.8%
자가 2
 
4.3%

Length

2024-05-11T04:04:36.511935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:36.952343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
60.9%
임대 16
34.8%
자가 2
 
4.3%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
43 
10000000
 
1
2000000
 
1
0
 
1

Length

Max length8
Median length4
Mean length4.0869565
Min length1

Unique

Unique3 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
93.5%
10000000 1
 
2.2%
2000000 1
 
2.2%
0 1
 
2.2%

Length

2024-05-11T04:04:37.433402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:37.815226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
93.5%
10000000 1
 
2.2%
2000000 1
 
2.2%
0 1
 
2.2%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
42 
450000
 
1
2000000
 
1
0
 
1
800000
 
1

Length

Max length7
Median length4
Mean length4.0869565
Min length1

Unique

Unique4 ?
Unique (%)8.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
91.3%
450000 1
 
2.2%
2000000 1
 
2.2%
0 1
 
2.2%
800000 1
 
2.2%

Length

2024-05-11T04:04:38.235423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:04:38.687659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
91.3%
450000 1
 
2.2%
2000000 1
 
2.2%
0 1
 
2.2%
800000 1
 
2.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.0%
Missing13
Missing (%)28.3%
Memory size224.0 B
False
33 
(Missing)
13 
ValueCountFrequency (%)
False 33
71.7%
(Missing) 13
 
28.3%
2024-05-11T04:04:39.050273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)24.2%
Missing13
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean13.518788
Minimum0
Maximum135
Zeros25
Zeros (%)54.3%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T04:04:39.443085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile65.6
Maximum135
Range135
Interquartile range (IQR)0

Descriptive statistics

Standard deviation29.639543
Coefficient of variation (CV)2.1924705
Kurtosis8.3320391
Mean13.518788
Median Absolute Deviation (MAD)0
Skewness2.7249913
Sum446.12
Variance878.50252
MonotonicityNot monotonic
2024-05-11T04:04:39.984324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 25
54.3%
33.0 2
 
4.3%
63.42 1
 
2.2%
17.83 1
 
2.2%
56.0 1
 
2.2%
39.0 1
 
2.2%
135.0 1
 
2.2%
68.87 1
 
2.2%
(Missing) 13
28.3%
ValueCountFrequency (%)
0.0 25
54.3%
17.83 1
 
2.2%
33.0 2
 
4.3%
39.0 1
 
2.2%
56.0 1
 
2.2%
63.42 1
 
2.2%
68.87 1
 
2.2%
135.0 1
 
2.2%
ValueCountFrequency (%)
135.0 1
 
2.2%
68.87 1
 
2.2%
63.42 1
 
2.2%
56.0 1
 
2.2%
39.0 1
 
2.2%
33.0 2
 
4.3%
17.83 1
 
2.2%
0.0 25
54.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030900003090000-122-2008-0000120080317<NA>3폐업2폐업20131007<NA><NA><NA>02 3492368263.42132819서울특별시 도봉구 도봉동 603-1서울특별시 도봉구 시루봉로27길 62 (도봉동)1309동원그린유통2011-10-30 15:11:46I2018-08-31 23:59:59.0집단급식소 식품판매업203727.184462463523.566914집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N63.42<NA><NA><NA>
130900003090000-122-2008-0000220080321<NA>3폐업2폐업20120608<NA><NA><NA>907 824060.0132918서울특별시 도봉구 창동 585-23<NA><NA>동서유통2008-03-21 16:48:43I2018-08-31 23:59:59.0집단급식소 식품판매업203062.318247459687.916963집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
230900003090000-122-2008-0000320080328<NA>3폐업2폐업20101111<NA><NA><NA>977 0811330.0132898서울특별시 도봉구 창동 1-10<NA><NA>창동하나로곡류특판2008-03-28 10:05:40I2018-08-31 23:59:59.0집단급식소 식품판매업204413.616575461378.588677집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
330900003090000-122-2008-0000420080521<NA>3폐업2폐업20190809<NA><NA><NA>02973797217.04132906서울특별시 도봉구 창동 263-8서울특별시 도봉구 해등로16길 94, 5층 (창동)1403대농바이오영농조합농수산2019-08-09 15:20:11U2019-08-11 02:40:00.0집단급식소 식품판매업203901.637804461355.060995집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430900003090000-122-2009-0000120090518<NA>3폐업2폐업20140107<NA><NA><NA><NA><NA>132959서울특별시 도봉구 창동 578-17 1층서울특별시 도봉구 덕릉로59가길 51 (창동,1층)1471대갑유통2009-05-18 15:40:56I2018-08-31 23:59:59.0집단급식소 식품판매업203204.538361459581.284179집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530900003090000-122-2009-0000220090603<NA>3폐업2폐업20110601<NA><NA><NA>02 954 012635.0132850서울특별시 도봉구 방학동 681-25 1층<NA><NA>다림푸드2009-06-03 10:13:46I2018-08-31 23:59:59.0집단급식소 식품판매업203609.610888462408.092911집단급식소 식품판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630900003090000-122-2009-0000320090813<NA>3폐업2폐업20210121<NA><NA><NA><NA>22.0132928서울특별시 도봉구 창동 748-2서울특별시 도봉구 도봉로136다길 26-1, 2층 (창동)1397신우푸디스(주)2021-01-21 16:17:37U2021-01-23 02:40:00.0집단급식소 식품판매업203707.967232462011.007306집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730900003090000-122-2009-0000420090227<NA>1영업/정상1영업<NA><NA><NA><NA>031 843 771110.0132801서울특별시 도봉구 도봉동 89-148 224호서울특별시 도봉구 도봉로170길 8, 2층 224호 (도봉동)1321남도식품유통2019-03-08 11:24:20U2019-03-10 02:40:00.0집단급식소 식품판매업203985.566277464212.297932집단급식소 식품판매업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830900003090000-122-2010-0000120100226<NA>3폐업2폐업20120608<NA><NA><NA>02 907 824030.0132918서울특별시 도봉구 창동 585-23 지상 1층<NA><NA>한아름농산2010-02-26 14:00:49I2018-08-31 23:59:59.0집단급식소 식품판매업203062.318247459687.916963집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
930900003090000-122-2010-0000220100610<NA>3폐업2폐업20190823<NA><NA><NA><NA>41.75132905서울특별시 도봉구 창동 181-46 플러스오피스텔 212호서울특별시 도봉구 도봉로136길 80, 212호 (창동,플러스오피스텔)1410보령유통2019-08-23 15:59:40U2019-08-25 02:40:00.0집단급식소 식품판매업203953.509197461885.226146집단급식소 식품판매업<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
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3730900003090000-122-2017-000032017-05-12<NA>1영업/정상1영업<NA><NA><NA><NA>0234996000495.0132-898서울특별시 도봉구 창동 1-10서울특별시 도봉구 마들로11길 20, 1층 (창동)1413(주)농협유통 창동 농산물 종합유통센터2024-03-14 10:11:46U2023-12-02 23:06:00.0집단급식소 식품판매업204413.616575461378.588677<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3830900003090000-122-2017-0000420171017<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.0132833서울특별시 도봉구 방학동 397-15 1층서울특별시 도봉구 시루봉로15라길 33 (방학동)1314오향푸드2017-10-17 15:25:46I2018-08-31 23:59:59.0집단급식소 식품판매업202849.341485463001.574574집단급식소 식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
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4230900003090000-122-2022-0000120220719<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.0132820서울특별시 도봉구 도봉동 609-27 1층 우측서울특별시 도봉구 시루봉로 280, 1층 우측호 (도봉동)1349세빈푸드2022-07-19 09:23:27I2021-12-06 22:01:00.0집단급식소 식품판매업203472.993067463167.997414<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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4430900003090000-122-2023-000022023-11-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.3132-800서울특별시 도봉구 도봉동 30-1 도봉한신아파트서울특별시 도봉구 도봉로180나길 41, 도봉한신아파트 상가1동 222호 (도봉동)1318(주)진성푸드2023-11-13 10:05:12U2022-10-31 23:05:00.0집단급식소 식품판매업204169.84767464814.717432<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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