Overview

Dataset statistics

Number of variables7
Number of observations78
Missing cells2
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory58.7 B

Variable types

Numeric1
Text3
DateTime1
Categorical2

Dataset

Description관내 사업장폐기물 배출자 신고 현황에 대한 데이터로 상호명, 주소, 연락처, 신고일자, 폐기물구분, 폐기물종류 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15060308/fileData.do

Alerts

폐기물구분 is highly overall correlated with 폐기물종류High correlation
폐기물종류 is highly overall correlated with 폐기물구분High correlation
폐기물종류 is highly imbalanced (63.6%)Imbalance
연락처 has 2 (2.6%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:02:53.041044
Analysis finished2023-12-12 01:02:56.672666
Duration3.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.5
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T10:02:56.745811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q120.25
median39.5
Q358.75
95-th percentile74.15
Maximum78
Range77
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation22.660538
Coefficient of variation (CV)0.57368452
Kurtosis-1.2
Mean39.5
Median Absolute Deviation (MAD)19.5
Skewness0
Sum3081
Variance513.5
MonotonicityStrictly increasing
2023-12-12T10:02:56.894113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
51 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
50 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%

상호명
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T10:02:57.209841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.5128205
Min length4

Characters and Unicode

Total characters664
Distinct characters188
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row대연중학교
2nd row동국씨엠(주)부산공장
3rd row(유)피피지코리아
4th row(주)농협사료 부산바이오
5th row부산환경공단남부사업소
ValueCountFrequency (%)
관리사무소 2
 
2.1%
주식회사 2
 
2.1%
대연중학교 1
 
1.0%
예문여자고등학교 1
 
1.0%
동국씨엠(주)부산공장 1
 
1.0%
중앙스톤 1
 
1.0%
그랜드자연요양병원 1
 
1.0%
용당초등학교 1
 
1.0%
새라새요양병원 1
 
1.0%
인창대연요양병원 1
 
1.0%
Other values (84) 84
87.5%
2023-12-12T10:02:58.396203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 30
 
4.5%
교 29
 
4.4%
( 25
 
3.8%
) 25
 
3.8%
부 22
 
3.3%
주 21
 
3.2%
18
 
2.7%
등 16
 
2.4%
산 16
 
2.4%
원 16
 
2.4%
Other values (178) 446
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 576
86.7%
Open Punctuation 25
 
3.8%
Close Punctuation 25
 
3.8%
Space Separator 18
 
2.7%
Decimal Number 12
 
1.8%
Uppercase Letter 8
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 30
 
5.2%
교 29
 
5.0%
부 22
 
3.8%
주 21
 
3.6%
등 16
 
2.8%
산 16
 
2.8%
원 16
 
2.8%
대 14
 
2.4%
스 13
 
2.3%
고 13
 
2.3%
Other values (163) 386
67.0%
Decimal Number
ValueCountFrequency (%)
3 3
25.0%
7 2
16.7%
2 2
16.7%
1 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
5 1
 
8.3%
6 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
G 3
37.5%
K 1
 
12.5%
L 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 576
86.7%
Common 80
 
12.0%
Latin 8
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 30
 
5.2%
교 29
 
5.0%
부 22
 
3.8%
주 21
 
3.6%
등 16
 
2.8%
산 16
 
2.8%
원 16
 
2.8%
대 14
 
2.4%
스 13
 
2.3%
고 13
 
2.3%
Other values (163) 386
67.0%
Common
ValueCountFrequency (%)
( 25
31.2%
) 25
31.2%
18
22.5%
3 3
 
3.8%
7 2
 
2.5%
2 2
 
2.5%
1 1
 
1.2%
0 1
 
1.2%
8 1
 
1.2%
5 1
 
1.2%
Latin
ValueCountFrequency (%)
S 3
37.5%
G 3
37.5%
K 1
 
12.5%
L 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 576
86.7%
ASCII 88
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 30
 
5.2%
교 29
 
5.0%
부 22
 
3.8%
주 21
 
3.6%
등 16
 
2.8%
산 16
 
2.8%
원 16
 
2.8%
대 14
 
2.4%
스 13
 
2.3%
고 13
 
2.3%
Other values (163) 386
67.0%
ASCII
ValueCountFrequency (%)
( 25
28.4%
) 25
28.4%
18
20.5%
S 3
 
3.4%
3 3
 
3.4%
G 3
 
3.4%
7 2
 
2.3%
2 2
 
2.3%
K 1
 
1.1%
L 1
 
1.1%
Other values (5) 5
 
5.7%

주 소
Text

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T10:02:59.003316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length35
Mean length28.653846
Min length1

Characters and Unicode

Total characters2235
Distinct characters167
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

Unique76 ?
Unique (%)97.4%

Sample

1st row부산광역시 남구 천제등로16번길 81_ 대연중학교 (대연동)
2nd row부산광역시 남구 신선로 102 (감만동)
3rd row부산광역시 남구 신선로356번길 21 (용당동)
4th row부산광역시 남구 우암로 337_ 부산특수사료공장 (문현동)
5th row부산광역시 남구 이기대공원로 11 (용호동)
ValueCountFrequency (%)
부산광역시 77
17.2%
남구 77
17.2%
대연동 28
 
6.3%
용호동 16
 
3.6%
신선로 14
 
3.1%
감만동 12
 
2.7%
용당동 11
 
2.5%
수영로 11
 
2.5%
문현동 8
 
1.8%
분포로 6
 
1.3%
Other values (170) 187
41.8%
2023-12-12T10:02:59.427900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
371
 
16.6%
부 87
 
3.9%
동 87
 
3.9%
산 85
 
3.8%
남 83
 
3.7%
( 79
 
3.5%
시 79
 
3.5%
로 79
 
3.5%
) 79
 
3.5%
구 78
 
3.5%
Other values (157) 1128
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1349
60.4%
Space Separator 371
 
16.6%
Decimal Number 281
 
12.6%
Open Punctuation 79
 
3.5%
Close Punctuation 79
 
3.5%
Connector Punctuation 46
 
2.1%
Dash Punctuation 15
 
0.7%
Uppercase Letter 11
 
0.5%
Lowercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 87
 
6.4%
동 87
 
6.4%
산 85
 
6.3%
남 83
 
6.2%
시 79
 
5.9%
로 79
 
5.9%
구 78
 
5.8%
광 77
 
5.7%
역 77
 
5.7%
대 48
 
3.6%
Other values (131) 569
42.2%
Decimal Number
ValueCountFrequency (%)
1 70
24.9%
2 37
13.2%
5 29
10.3%
3 29
10.3%
4 28
 
10.0%
9 22
 
7.8%
0 21
 
7.5%
6 20
 
7.1%
8 13
 
4.6%
7 12
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
G 2
18.2%
K 1
 
9.1%
V 1
 
9.1%
I 1
 
9.1%
E 1
 
9.1%
W 1
 
9.1%
H 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
50.0%
s 1
25.0%
i 1
25.0%
Space Separator
ValueCountFrequency (%)
371
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1349
60.4%
Common 871
39.0%
Latin 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 87
 
6.4%
동 87
 
6.4%
산 85
 
6.3%
남 83
 
6.2%
시 79
 
5.9%
로 79
 
5.9%
구 78
 
5.8%
광 77
 
5.7%
역 77
 
5.7%
대 48
 
3.6%
Other values (131) 569
42.2%
Common
ValueCountFrequency (%)
371
42.6%
( 79
 
9.1%
) 79
 
9.1%
1 70
 
8.0%
_ 46
 
5.3%
2 37
 
4.2%
5 29
 
3.3%
3 29
 
3.3%
4 28
 
3.2%
9 22
 
2.5%
Other values (5) 81
 
9.3%
Latin
ValueCountFrequency (%)
S 3
20.0%
l 2
13.3%
G 2
13.3%
s 1
 
6.7%
K 1
 
6.7%
V 1
 
6.7%
I 1
 
6.7%
E 1
 
6.7%
W 1
 
6.7%
H 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1349
60.4%
ASCII 886
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
371
41.9%
( 79
 
8.9%
) 79
 
8.9%
1 70
 
7.9%
_ 46
 
5.2%
2 37
 
4.2%
5 29
 
3.3%
3 29
 
3.3%
4 28
 
3.2%
9 22
 
2.5%
Other values (16) 96
 
10.8%
Hangul
ValueCountFrequency (%)
부 87
 
6.4%
동 87
 
6.4%
산 85
 
6.3%
남 83
 
6.2%
시 79
 
5.9%
로 79
 
5.9%
구 78
 
5.8%
광 77
 
5.7%
역 77
 
5.7%
대 48
 
3.6%
Other values (131) 569
42.2%

연락처
Text

MISSING 

Distinct74
Distinct (%)97.4%
Missing2
Missing (%)2.6%
Memory size756.0 B
2023-12-12T10:02:59.658832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.013158
Min length12

Characters and Unicode

Total characters913
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)94.7%

Sample

1st row051-606-7705
2nd row051-640-5246
3rd row051-620-8212
4th row051-606-1900
5th row051-713-0135
ValueCountFrequency (%)
051-629-5103 2
 
2.6%
051-636-3082 2
 
2.6%
051-634-6699 1
 
1.3%
051-660-1506 1
 
1.3%
051-606-7705 1
 
1.3%
051-624-4350 1
 
1.3%
051-628-6005 1
 
1.3%
051-774-1004 1
 
1.3%
051-610-3303 1
 
1.3%
051-622-9435 1
 
1.3%
Other values (64) 64
84.2%
2023-12-12T10:03:00.063332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 161
17.6%
- 152
16.6%
1 124
13.6%
5 114
12.5%
6 105
11.5%
2 70
7.7%
3 54
 
5.9%
4 40
 
4.4%
7 35
 
3.8%
8 30
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 761
83.4%
Dash Punctuation 152
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 161
21.2%
1 124
16.3%
5 114
15.0%
6 105
13.8%
2 70
9.2%
3 54
 
7.1%
4 40
 
5.3%
7 35
 
4.6%
8 30
 
3.9%
9 28
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 161
17.6%
- 152
16.6%
1 124
13.6%
5 114
12.5%
6 105
11.5%
2 70
7.7%
3 54
 
5.9%
4 40
 
4.4%
7 35
 
3.8%
8 30
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 161
17.6%
- 152
16.6%
1 124
13.6%
5 114
12.5%
6 105
11.5%
2 70
7.7%
3 54
 
5.9%
4 40
 
4.4%
7 35
 
3.8%
8 30
 
3.3%

신고일자
Date

Distinct56
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum1999-02-19 00:00:00
Maximum2023-06-21 00:00:00
2023-12-12T10:03:00.193295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:03:00.320587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐기물구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
사업장일반
68 
사업장배출시설
10 

Length

Max length7
Median length5
Mean length5.2564103
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장일반
2nd row사업장배출시설
3rd row사업장배출시설
4th row사업장배출시설
5th row사업장배출시설

Common Values

ValueCountFrequency (%)
사업장일반 68
87.2%
사업장배출시설 10
 
12.8%

Length

2023-12-12T10:03:00.502690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:03:00.654560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장일반 68
87.2%
사업장배출시설 10
 
12.8%

폐기물종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
생활폐기물
64 
폐합성수지
 
4
폐콘크리트
 
2
수산물가공잔재물
 
2
폐수처리오니, 공정오니
 
1
Other values (5)
 
5

Length

Max length12
Median length5
Mean length5.2051282
Min length3

Unique

Unique6 ?
Unique (%)7.7%

Sample

1st row생활폐기물
2nd row폐수처리오니, 공정오니
3rd row폐활성탄
4th row폐합성수지
5th row하수처리오니

Common Values

ValueCountFrequency (%)
생활폐기물 64
82.1%
폐합성수지 4
 
5.1%
폐콘크리트 2
 
2.6%
수산물가공잔재물 2
 
2.6%
폐수처리오니, 공정오니 1
 
1.3%
폐활성탄 1
 
1.3%
하수처리오니 1
 
1.3%
폐합성수지, 분진 1
 
1.3%
폐석재 1
 
1.3%
폐합성수지류 1
 
1.3%

Length

2023-12-12T10:03:00.763355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:03:00.902173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활폐기물 64
80.0%
폐합성수지 5
 
6.2%
폐콘크리트 2
 
2.5%
수산물가공잔재물 2
 
2.5%
폐수처리오니 1
 
1.2%
공정오니 1
 
1.2%
폐활성탄 1
 
1.2%
하수처리오니 1
 
1.2%
분진 1
 
1.2%
폐석재 1
 
1.2%

Interactions

2023-12-12T10:02:56.302170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:03:01.007151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명주 소연락처신고일자폐기물구분폐기물종류
연번1.0001.0000.9410.8740.9660.3960.000
상호명1.0001.0001.0001.0001.0001.0001.000
주 소0.9411.0001.0000.9950.9821.0000.000
연락처0.8741.0000.9951.0000.8041.0001.000
신고일자0.9661.0000.9820.8041.0001.0001.000
폐기물구분0.3961.0001.0001.0001.0001.0000.981
폐기물종류0.0001.0000.0001.0001.0000.9811.000
2023-12-12T10:03:01.125273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물구분폐기물종류
폐기물구분1.0000.833
폐기물종류0.8331.000
2023-12-12T10:03:01.229059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번폐기물구분폐기물종류
연번1.0000.2850.000
폐기물구분0.2851.0000.833
폐기물종류0.0000.8331.000

Missing values

2023-12-12T10:02:56.495550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:02:56.618654image/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

연번상호명주 소연락처신고일자폐기물구분폐기물종류
01대연중학교부산광역시 남구 천제등로16번길 81_ 대연중학교 (대연동)051-606-77051999-02-19사업장일반생활폐기물
12동국씨엠(주)부산공장부산광역시 남구 신선로 102 (감만동)051-640-52461999-11-25사업장배출시설폐수처리오니, 공정오니
23(유)피피지코리아부산광역시 남구 신선로356번길 21 (용당동)051-620-82122000-04-08사업장배출시설폐활성탄
34(주)농협사료 부산바이오부산광역시 남구 우암로 337_ 부산특수사료공장 (문현동)051-606-19002000-05-10사업장배출시설폐합성수지
45부산환경공단남부사업소부산광역시 남구 이기대공원로 11 (용호동)051-713-01352001-03-29사업장배출시설하수처리오니
56동명대학교부산광역시 남구 신선로 428 (용당동)051-610-81952001-03-30사업장일반생활폐기물
67해군작전사령부부산광역시 남구 백운포로 95 (용호동)051-679-20262001-09-20사업장일반생활폐기물
78부경대학교(대연캠퍼스)부산광역시 남구 용소로 45 (대연동)051-629-51032002-12-11사업장일반생활폐기물
89(주)이마트문현점부산광역시 남구 전포대로91번길 47 (문현동)051-609-10522003-09-06사업장일반생활폐기물
910(주)홈플러스 부산감만점부산광역시 남구 우암로 124_ 홈플러스 부산감만점 (감만동)051-609-81242006-08-07사업장일반생활폐기물
연번상호명주 소연락처신고일자폐기물구분폐기물종류
6869연우자산관리(주)부산광역시 남구 수영로 295_ 세웅빌딩 외 1개소(수영로293번길 14) (대연동)051-626-00232021-12-03사업장일반생활폐기물
6970리마크빌 관리사무소부산광역시 남구 수영로 324 (대연동_ 리마크빌 대연)051-626-86042021-12-24사업장일반생활폐기물
7071지에스(GS)하이츠 상가 운영위원회부산광역시 남구 신선로 566 (용호동_ GS하이츠자이)051-626-36312022-01-05사업장일반생활폐기물
7172(주)진광에프엔지부산광역시 남구 분포로 66-30_ 1층 101호 (용호동)<NA>2022-01-06사업장일반수산물가공잔재물
7273스파크관리단부산광역시 남구 수영로 305_ 관리사무소 (대연동)051-620-70002022-06-08사업장일반생활폐기물
7374GS칼텍스(주)부산물류센터부산광역시 남구 신선로 180_ GS칼텍스 (감만동)051-640-84442022-08-25사업장배출시설생활폐기물
7475(주)학승부산광역시 남구 황령대로 401-9 (대연동)051-922-22002022-09-21사업장일반생활폐기물
7576동원부산컨테이너터미널(주)부산광역시 남구 북항로 191_ 동부부산컨테이너터미널 (감만동)051-630-33152023-02-03사업장일반폐합성수지류
7677의료법인 정화의료재단 봉생힐링병원부산광역시 남구 양지골로 241 (감만동)051-668-60412023-04-22사업장일반생활폐기물
7778더리본(주)삼성힐타워상가부산광역시 남구 전포대로 26 (문현동_ 문현삼성힐타워)051-636-30822023-06-21사업장일반생활폐기물