Overview

Dataset statistics

Number of variables6
Number of observations133
Missing cells51
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory50.0 B

Variable types

Numeric1
Text3
Categorical2

Dataset

Description광주광역시 동구 환경보호와 지역주민의 건강을 증진시키기 위해 관내 음식물쓰레기다량배출업소에 대한 상호명과 주소, 연락처 등을 공개함.
Author광주광역시 동구
URLhttps://www.data.go.kr/data/15018338/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 연번High correlation
연락처 has 51 (38.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:23:00.803318
Analysis finished2023-12-12 15:23:01.369101
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67
Minimum1
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T00:23:01.465256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.6
Q134
median67
Q3100
95-th percentile126.4
Maximum133
Range132
Interquartile range (IQR)66

Descriptive statistics

Standard deviation38.53786
Coefficient of variation (CV)0.57519194
Kurtosis-1.2
Mean67
Median Absolute Deviation (MAD)33
Skewness0
Sum8911
Variance1485.1667
MonotonicityStrictly increasing
2023-12-13T00:23:01.621206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
85 1
 
0.8%
99 1
 
0.8%
98 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
Other values (123) 123
92.5%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
133 1
0.8%
132 1
0.8%
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%

상호
Text

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:23:01.868337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length7.1203008
Min length2

Characters and Unicode

Total characters947
Distinct characters250
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

Unique130 ?
Unique (%)97.7%

Sample

1st row청하
2nd row영안반점
3rd row삼희
4th row쌍학
5th row수정
ValueCountFrequency (%)
신락원 3
 
1.9%
전남대학교병원 3
 
1.9%
조선대학교 2
 
1.2%
충장로점 2
 
1.2%
구내식당 2
 
1.2%
학동점 1
 
0.6%
바른초밥 1
 
0.6%
용우동 1
 
0.6%
광주중앙초등학교 1
 
0.6%
광주서석초등학교 1
 
0.6%
Other values (143) 143
89.4%
2023-12-13T00:23:02.477387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 38
 
4.0%
주 34
 
3.6%
점 29
 
3.1%
교 29
 
3.1%
27
 
2.9%
광 23
 
2.4%
등 21
 
2.2%
) 20
 
2.1%
( 20
 
2.1%
대 18
 
1.9%
Other values (240) 688
72.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 829
87.5%
Uppercase Letter 46
 
4.9%
Space Separator 27
 
2.9%
Close Punctuation 20
 
2.1%
Open Punctuation 20
 
2.1%
Other Punctuation 3
 
0.3%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 38
 
4.6%
주 34
 
4.1%
점 29
 
3.5%
교 29
 
3.5%
광 23
 
2.8%
등 21
 
2.5%
대 18
 
2.2%
장 18
 
2.2%
스 17
 
2.1%
원 17
 
2.1%
Other values (215) 585
70.6%
Uppercase Letter
ValueCountFrequency (%)
C 10
21.7%
A 8
17.4%
N 5
10.9%
G 4
 
8.7%
R 3
 
6.5%
Y 2
 
4.3%
W 2
 
4.3%
E 2
 
4.3%
P 1
 
2.2%
Z 1
 
2.2%
Other values (8) 8
17.4%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
' 1
33.3%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 829
87.5%
Common 72
 
7.6%
Latin 46
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 38
 
4.6%
주 34
 
4.1%
점 29
 
3.5%
교 29
 
3.5%
광 23
 
2.8%
등 21
 
2.5%
대 18
 
2.2%
장 18
 
2.2%
스 17
 
2.1%
원 17
 
2.1%
Other values (215) 585
70.6%
Latin
ValueCountFrequency (%)
C 10
21.7%
A 8
17.4%
N 5
10.9%
G 4
 
8.7%
R 3
 
6.5%
Y 2
 
4.3%
W 2
 
4.3%
E 2
 
4.3%
P 1
 
2.2%
Z 1
 
2.2%
Other values (8) 8
17.4%
Common
ValueCountFrequency (%)
27
37.5%
) 20
27.8%
( 20
27.8%
. 2
 
2.8%
' 1
 
1.4%
3 1
 
1.4%
1 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 829
87.5%
ASCII 118
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 38
 
4.6%
주 34
 
4.1%
점 29
 
3.5%
교 29
 
3.5%
광 23
 
2.8%
등 21
 
2.5%
대 18
 
2.2%
장 18
 
2.2%
스 17
 
2.1%
원 17
 
2.1%
Other values (215) 585
70.6%
ASCII
ValueCountFrequency (%)
27
22.9%
) 20
16.9%
( 20
16.9%
C 10
 
8.5%
A 8
 
6.8%
N 5
 
4.2%
G 4
 
3.4%
R 3
 
2.5%
Y 2
 
1.7%
W 2
 
1.7%
Other values (15) 17
14.4%

주소
Text

Distinct132
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T00:23:02.960619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length20.518797
Min length11

Characters and Unicode

Total characters2729
Distinct characters118
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

Unique131 ?
Unique (%)98.5%

Sample

1st row충장로 45-12 (충장로4가,외3필지(1층))
2nd row충장로 45-13, 1~3층 (금남로5가)
3rd row구성로 164 (충장로5가,(1층))
4th row구성로152번길 13 (수기동,(1,2층))
5th row천변우로 393-18, 1,2층 (불로동)
ValueCountFrequency (%)
1층 15
 
3.3%
2층 13
 
2.8%
충장로 10
 
2.2%
필문대로 9
 
2.0%
중앙로160번길 9
 
2.0%
문화전당로35번길 7
 
1.5%
무등로 7
 
1.5%
학동 7
 
1.5%
중앙로 7
 
1.5%
지산동 7
 
1.5%
Other values (251) 369
80.2%
2023-12-13T00:23:03.570849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
372
 
13.6%
( 186
 
6.8%
) 186
 
6.8%
1 173
 
6.3%
로 148
 
5.4%
동 118
 
4.3%
, 118
 
4.3%
2 116
 
4.3%
층 92
 
3.4%
3 90
 
3.3%
Other values (108) 1130
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1155
42.3%
Decimal Number 652
23.9%
Space Separator 372
 
13.6%
Open Punctuation 186
 
6.8%
Close Punctuation 186
 
6.8%
Other Punctuation 124
 
4.5%
Dash Punctuation 44
 
1.6%
Uppercase Letter 6
 
0.2%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 148
 
12.8%
동 118
 
10.2%
층 92
 
8.0%
길 69
 
6.0%
번 56
 
4.8%
지 46
 
4.0%
산 39
 
3.4%
장 33
 
2.9%
충 32
 
2.8%
문 24
 
2.1%
Other values (88) 498
43.1%
Decimal Number
ValueCountFrequency (%)
1 173
26.5%
2 116
17.8%
3 90
13.8%
5 52
 
8.0%
0 50
 
7.7%
4 48
 
7.4%
6 41
 
6.3%
9 28
 
4.3%
8 27
 
4.1%
7 27
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
C 3
50.0%
N 2
33.3%
I 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 118
95.2%
. 6
 
4.8%
Space Separator
ValueCountFrequency (%)
372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1568
57.5%
Hangul 1155
42.3%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 148
 
12.8%
동 118
 
10.2%
층 92
 
8.0%
길 69
 
6.0%
번 56
 
4.8%
지 46
 
4.0%
산 39
 
3.4%
장 33
 
2.9%
충 32
 
2.8%
문 24
 
2.1%
Other values (88) 498
43.1%
Common
ValueCountFrequency (%)
372
23.7%
( 186
11.9%
) 186
11.9%
1 173
11.0%
, 118
 
7.5%
2 116
 
7.4%
3 90
 
5.7%
5 52
 
3.3%
0 50
 
3.2%
4 48
 
3.1%
Other values (7) 177
11.3%
Latin
ValueCountFrequency (%)
C 3
50.0%
N 2
33.3%
I 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1574
57.7%
Hangul 1155
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
372
23.6%
( 186
11.8%
) 186
11.8%
1 173
11.0%
, 118
 
7.5%
2 116
 
7.4%
3 90
 
5.7%
5 52
 
3.3%
0 50
 
3.2%
4 48
 
3.0%
Other values (10) 183
11.6%
Hangul
ValueCountFrequency (%)
로 148
 
12.8%
동 118
 
10.2%
층 92
 
8.0%
길 69
 
6.0%
번 56
 
4.8%
지 46
 
4.0%
산 39
 
3.4%
장 33
 
2.9%
충 32
 
2.8%
문 24
 
2.1%
Other values (88) 498
43.1%

연락처
Text

MISSING 

Distinct78
Distinct (%)95.1%
Missing51
Missing (%)38.3%
Memory size1.2 KiB
2023-12-13T00:23:03.921335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters984
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

Unique74 ?
Unique (%)90.2%

Sample

1st row062-223-7037
2nd row062-225-3233
3rd row062-226-0011
4th row062-234-8006
5th row062-227-6849
ValueCountFrequency (%)
062-226-0011 2
 
2.4%
062-571-6000 2
 
2.4%
062-236-2023 2
 
2.4%
062-220-1492 2
 
2.4%
062-232-9897 1
 
1.2%
062-230-7661 1
 
1.2%
062-225-5436 1
 
1.2%
062-220-3933 1
 
1.2%
062-230-8073 1
 
1.2%
062-605-8023 1
 
1.2%
Other values (68) 68
82.9%
2023-12-13T00:23:04.427379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 233
23.7%
0 174
17.7%
- 164
16.7%
6 114
11.6%
3 70
 
7.1%
8 47
 
4.8%
1 43
 
4.4%
5 39
 
4.0%
9 36
 
3.7%
4 32
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 820
83.3%
Dash Punctuation 164
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 233
28.4%
0 174
21.2%
6 114
13.9%
3 70
 
8.5%
8 47
 
5.7%
1 43
 
5.2%
5 39
 
4.8%
9 36
 
4.4%
4 32
 
3.9%
7 32
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 984
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 233
23.7%
0 174
17.7%
- 164
16.7%
6 114
11.6%
3 70
 
7.1%
8 47
 
4.8%
1 43
 
4.4%
5 39
 
4.0%
9 36
 
3.7%
4 32
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 233
23.7%
0 174
17.7%
- 164
16.7%
6 114
11.6%
3 70
 
7.1%
8 47
 
4.8%
1 43
 
4.4%
5 39
 
4.0%
9 36
 
3.7%
4 32
 
3.3%

종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일반음식점
87 
집단급식소
38 
관광숙박업
 
4
대규모점포
 
3
휴게음식점
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 87
65.4%
집단급식소 38
28.6%
관광숙박업 4
 
3.0%
대규모점포 3
 
2.3%
휴게음식점 1
 
0.8%

Length

2023-12-13T00:23:04.625370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:23:04.779858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 87
65.4%
집단급식소 38
28.6%
관광숙박업 4
 
3.0%
대규모점포 3
 
2.3%
휴게음식점 1
 
0.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-10-11
133 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-11
2nd row2023-10-11
3rd row2023-10-11
4th row2023-10-11
5th row2023-10-11

Common Values

ValueCountFrequency (%)
2023-10-11 133
100.0%

Length

2023-12-13T00:23:05.295876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:23:05.415310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-11 133
100.0%

Interactions

2023-12-13T00:23:01.101135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:23:05.483616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연락처종류
연번1.0000.8810.870
연락처0.8811.0000.804
종류0.8700.8041.000
2023-12-13T00:23:05.593387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류
연번1.0000.531
종류0.5311.000

Missing values

2023-12-13T00:23:01.213634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:23:01.322329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번상호주소연락처종류데이터기준일자
01청하충장로 45-12 (충장로4가,외3필지(1층))062-223-7037일반음식점2023-10-11
12영안반점충장로 45-13, 1~3층 (금남로5가)<NA>일반음식점2023-10-11
23삼희구성로 164 (충장로5가,(1층))062-225-3233일반음식점2023-10-11
34쌍학구성로152번길 13 (수기동,(1,2층))<NA>일반음식점2023-10-11
45수정천변우로 393-18, 1,2층 (불로동)<NA>일반음식점2023-10-11
56아리랑 하우스무등로321번길 2 (계림동,(1,2층))<NA>일반음식점2023-10-11
67스푼더마켓(광주충장로점)중앙로160번길 13 (황금동,파레스(7층))<NA>일반음식점2023-10-11
78호텔무등파크지호로164번길 14-10 (지산동,, 68-17 (10층))062-226-0011일반음식점2023-10-11
89관가의재로96번길 18 (소태동)<NA>일반음식점2023-10-11
910고려조삼계탕금남로 231 (금남로2가,(점포21개))<NA>일반음식점2023-10-11
연번상호주소연락처종류데이터기준일자
123124지한초등학교남계길 37, 1층 (내남동)<NA>집단급식소2023-10-11
124125광주전남지방병무청복지위원회양림로119번길 8, 병무청 지하1층 (학동)062-230-4214집단급식소2023-10-11
125126전남대학교병원 환자식당제봉로 42, 전남대학교병원 지하층 (학동)062-220-5030집단급식소2023-10-11
126127금호계림주상복합상가중앙로 358(계림동)062-522-5522대규모점포2023-10-11
127128Y'Z PARK 충장로점충장로 72(충장로3가)062-236-5989대규모점포2023-10-11
128129NCWAVE충장점중앙로 163(충장로4가)062-718-9355대규모점포2023-10-11
129130무등파크호텔지호로164번길 14-10 (지산동)062-226-0011관광숙박업2023-10-11
130131오아시타동명로20번길 20 (동명동)<NA>관광숙박업2023-10-11
131132ACC DESIGN호텔금남로 226-11 (충장로2가)062-234-8000관광숙박업2023-10-11
132133벤틀리호텔서석로10번길 5 (불로동)062-236-5881관광숙박업2023-10-11