Overview

Dataset statistics

Number of variables9
Number of observations311
Missing cells270
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory72.4 B

Variable types

Categorical1
Text7
DateTime1

Dataset

Description부산광역시사하구_사업장폐기물배출자신고현황_20221021
Author부산광역시 사하구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15081086

Alerts

사업장등록번호 has 269 (86.5%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:14:01.565279
Analysis finished2023-12-10 16:14:03.213078
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
사업장일반폐기물
275 
지정폐기물
36 

Length

Max length8
Median length8
Mean length7.6527331
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사업장일반폐기물 275
88.4%
지정폐기물 36
 
11.6%

Length

2023-12-11T01:14:03.703178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:03.869156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장일반폐기물 275
88.4%
지정폐기물 36
 
11.6%

상호명
Text

Distinct303
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:04.243144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length6.8681672
Min length3

Characters and Unicode

Total characters2136
Distinct characters289
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique295 ?
Unique (%)94.9%

Sample

1st row해양경찰정비창장
2nd row동아대학교 승학캠퍼스
3rd row동주대학교
4th row㈜서원유통탑마트신평점
5th row롯데쇼핑㈜롯데마트사하점
ValueCountFrequency (%)
주식회사 13
 
3.8%
부산운수환경조합 2
 
0.6%
동아대학교 2
 
0.6%
㈜동성화학 2
 
0.6%
장림공장 2
 
0.6%
㈜창신inc 2
 
0.6%
㈜대경오앤티 2
 
0.6%
신평공장 2
 
0.6%
㈜삼호그린종합폐차장 2
 
0.6%
부산패션칼라산업협동조합 2
 
0.6%
Other values (309) 313
91.0%
2023-12-11T01:14:05.056064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 197
 
9.2%
산 79
 
3.7%
공 41
 
1.9%
업 41
 
1.9%
부 40
 
1.9%
이 39
 
1.8%
39
 
1.8%
사 39
 
1.8%
장 37
 
1.7%
동 33
 
1.5%
Other values (279) 1551
72.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1838
86.0%
Other Symbol 197
 
9.2%
Space Separator 39
 
1.8%
Uppercase Letter 24
 
1.1%
Close Punctuation 13
 
0.6%
Open Punctuation 13
 
0.6%
Decimal Number 10
 
0.5%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 79
 
4.3%
공 41
 
2.2%
업 41
 
2.2%
부 40
 
2.2%
이 39
 
2.1%
사 39
 
2.1%
장 37
 
2.0%
동 33
 
1.8%
식 33
 
1.8%
수 32
 
1.7%
Other values (256) 1424
77.5%
Uppercase Letter
ValueCountFrequency (%)
S 4
16.7%
C 4
16.7%
N 3
12.5%
I 2
8.3%
M 2
8.3%
Y 1
 
4.2%
D 1
 
4.2%
E 1
 
4.2%
T 1
 
4.2%
O 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
2 5
50.0%
1 3
30.0%
3 2
 
20.0%
Other Symbol
ValueCountFrequency (%)
㈜ 197
100.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2035
95.3%
Common 77
 
3.6%
Latin 24
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 197
 
9.7%
산 79
 
3.9%
공 41
 
2.0%
업 41
 
2.0%
부 40
 
2.0%
이 39
 
1.9%
사 39
 
1.9%
장 37
 
1.8%
동 33
 
1.6%
식 33
 
1.6%
Other values (257) 1456
71.5%
Latin
ValueCountFrequency (%)
S 4
16.7%
C 4
16.7%
N 3
12.5%
I 2
8.3%
M 2
8.3%
Y 1
 
4.2%
D 1
 
4.2%
E 1
 
4.2%
T 1
 
4.2%
O 1
 
4.2%
Other values (4) 4
16.7%
Common
ValueCountFrequency (%)
39
50.6%
) 13
 
16.9%
( 13
 
16.9%
2 5
 
6.5%
1 3
 
3.9%
3 2
 
2.6%
& 1
 
1.3%
- 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1838
86.0%
None 197
 
9.2%
ASCII 101
 
4.7%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 197
100.0%
Hangul
ValueCountFrequency (%)
산 79
 
4.3%
공 41
 
2.2%
업 41
 
2.2%
부 40
 
2.2%
이 39
 
2.1%
사 39
 
2.1%
장 37
 
2.0%
동 33
 
1.8%
식 33
 
1.8%
수 32
 
1.7%
Other values (256) 1424
77.5%
ASCII
ValueCountFrequency (%)
39
38.6%
) 13
 
12.9%
( 13
 
12.9%
2 5
 
5.0%
S 4
 
4.0%
C 4
 
4.0%
N 3
 
3.0%
1 3
 
3.0%
I 2
 
2.0%
3 2
 
2.0%
Other values (12) 13
 
12.9%

폐기물종류
Text

Distinct164
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:05.753341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length57
Mean length13.003215
Min length2

Characters and Unicode

Total characters4044
Distinct characters164
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)44.1%

Sample

1st row폐합성수지폐목재생활폐기물음식물류폐기물
2nd row생활폐기물폐목재폐합성수지
3rd row생활폐기물음식물류폐기물
4th row생활폐기물음식물류폐기물
5th row생활폐기물음식물류폐기물폐합성수지폐발포합성수지폐식용유축산물가공잔재물
ValueCountFrequency (%)
수산물가공잔재물 63
 
17.6%
폐합성수지 28
 
7.8%
그밖의폐기물 10
 
2.8%
폐합성섬유 8
 
2.2%
수산잔재물 6
 
1.7%
폐콘크리트 5
 
1.4%
그밖의폐유 4
 
1.1%
화학점결폐주물사 4
 
1.1%
동물성잔재물 4
 
1.1%
그밖의 4
 
1.1%
Other values (190) 222
62.0%
2023-12-11T01:14:06.556132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 429
 
10.6%
물 364
 
9.0%
수 228
 
5.6%
성 173
 
4.3%
재 169
 
4.2%
그 141
 
3.5%
밖 137
 
3.4%
의 134
 
3.3%
합 130
 
3.2%
기 127
 
3.1%
Other values (154) 2012
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3722
92.0%
Decimal Number 104
 
2.6%
Open Punctuation 59
 
1.5%
Close Punctuation 58
 
1.4%
Space Separator 48
 
1.2%
Dash Punctuation 34
 
0.8%
Other Punctuation 11
 
0.3%
Other Symbol 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 429
 
11.5%
물 364
 
9.8%
수 228
 
6.1%
성 173
 
4.6%
재 169
 
4.5%
그 141
 
3.8%
밖 137
 
3.7%
의 134
 
3.6%
합 130
 
3.5%
기 127
 
3.4%
Other values (138) 1690
45.4%
Decimal Number
ValueCountFrequency (%)
0 56
53.8%
6 13
 
12.5%
3 12
 
11.5%
1 11
 
10.6%
9 6
 
5.8%
2 4
 
3.8%
5 2
 
1.9%
Other Punctuation
ValueCountFrequency (%)
/ 6
54.5%
. 2
 
18.2%
· 2
 
18.2%
, 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Other Symbol
ValueCountFrequency (%)
□ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3722
92.0%
Common 322
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 429
 
11.5%
물 364
 
9.8%
수 228
 
6.1%
성 173
 
4.6%
재 169
 
4.5%
그 141
 
3.8%
밖 137
 
3.7%
의 134
 
3.6%
합 130
 
3.5%
기 127
 
3.4%
Other values (138) 1690
45.4%
Common
ValueCountFrequency (%)
( 59
18.3%
) 58
18.0%
0 56
17.4%
48
14.9%
- 34
10.6%
6 13
 
4.0%
3 12
 
3.7%
1 11
 
3.4%
□ 8
 
2.5%
/ 6
 
1.9%
Other values (6) 17
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3722
92.0%
ASCII 312
 
7.7%
Geometric Shapes 8
 
0.2%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 429
 
11.5%
물 364
 
9.8%
수 228
 
6.1%
성 173
 
4.6%
재 169
 
4.5%
그 141
 
3.8%
밖 137
 
3.7%
의 134
 
3.6%
합 130
 
3.5%
기 127
 
3.4%
Other values (138) 1690
45.4%
ASCII
ValueCountFrequency (%)
( 59
18.9%
) 58
18.6%
0 56
17.9%
48
15.4%
- 34
10.9%
6 13
 
4.2%
3 12
 
3.8%
1 11
 
3.5%
/ 6
 
1.9%
9 6
 
1.9%
Other values (4) 9
 
2.9%
Geometric Shapes
ValueCountFrequency (%)
□ 8
100.0%
None
ValueCountFrequency (%)
· 2
100.0%

사업장등록번호
Text

MISSING 

Distinct36
Distinct (%)85.7%
Missing269
Missing (%)86.5%
Memory size2.6 KiB
2023-12-11T01:14:06.952683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters504
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

Unique31 ?
Unique (%)73.8%

Sample

1st row603-99-45983
2nd row103-86-01995
3rd row603-81-46430
4th row602-81-19624
5th row603-81-74445
ValueCountFrequency (%)
602-81-19624 3
 
7.1%
603-81-33935 2
 
4.8%
603-81-68093 2
 
4.8%
106-81-59002 2
 
4.8%
621-81-18169 2
 
4.8%
850-87-00634 1
 
2.4%
490-87-00922 1
 
2.4%
808-86-00844 1
 
2.4%
537-81-01005 1
 
2.4%
603-81-72582 1
 
2.4%
Other values (26) 26
61.9%
2023-12-11T01:14:07.547683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 84
16.7%
0 79
15.7%
1 67
13.3%
8 53
10.5%
6 50
9.9%
3 50
9.9%
2 34
6.7%
9 28
 
5.6%
5 24
 
4.8%
4 21
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
83.3%
Dash Punctuation 84
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
18.8%
1 67
16.0%
8 53
12.6%
6 50
11.9%
3 50
11.9%
2 34
8.1%
9 28
 
6.7%
5 24
 
5.7%
4 21
 
5.0%
7 14
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 504
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 84
16.7%
0 79
15.7%
1 67
13.3%
8 53
10.5%
6 50
9.9%
3 50
9.9%
2 34
6.7%
9 28
 
5.6%
5 24
 
4.8%
4 21
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 84
16.7%
0 79
15.7%
1 67
13.3%
8 53
10.5%
6 50
9.9%
3 50
9.9%
2 34
6.7%
9 28
 
5.6%
5 24
 
4.8%
4 21
 
4.2%

운반자명
Text

Distinct202
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:07.889919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length242
Median length89
Mean length13.675241
Min length3

Characters and Unicode

Total characters4253
Distinct characters222
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)53.4%

Sample

1st row미래환경미래환경세화산업㈜대한리싸이클
2nd row세화산업태산자원㈜(주)청도산업
3rd row세화산업㈜지원환경
4th row미진산업아이맥스환경
5th row㈜여민환경㈜여민환경㈜여민환경대신산업,성창리사이클링미래&동명물류센터지현유지
ValueCountFrequency (%)
현대수산사료㈜ 19
 
5.9%
영남상회 13
 
4.0%
원우수산 12
 
3.7%
㈜에너지네트웍 11
 
3.4%
㈜미진산업 9
 
2.8%
㈜동아유화 7
 
2.2%
부국물산 7
 
2.2%
㈜에이치에스아쿠아피드 4
 
1.2%
한성종합상사 3
 
0.9%
득원산업 3
 
0.9%
Other values (201) 235
72.8%
2023-12-11T01:14:08.531448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 493
 
11.6%
207
 
4.9%
경 196
 
4.6%
산 194
 
4.6%
환 183
 
4.3%
업 155
 
3.6%
대 111
 
2.6%
지 98
 
2.3%
에 97
 
2.3%
이 87
 
2.0%
Other values (212) 2432
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3455
81.2%
Other Symbol 493
 
11.6%
Space Separator 207
 
4.9%
Open Punctuation 33
 
0.8%
Close Punctuation 33
 
0.8%
Uppercase Letter 16
 
0.4%
Other Punctuation 12
 
0.3%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 196
 
5.7%
산 194
 
5.6%
환 183
 
5.3%
업 155
 
4.5%
대 111
 
3.2%
지 98
 
2.8%
에 97
 
2.8%
이 87
 
2.5%
원 81
 
2.3%
수 65
 
1.9%
Other values (197) 2188
63.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
31.2%
H 4
25.0%
N 3
18.8%
E 2
 
12.5%
O 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 9
75.0%
" 1
 
8.3%
& 1
 
8.3%
＆ 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 2
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 493
100.0%
Space Separator
ValueCountFrequency (%)
207
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3948
92.8%
Common 289
 
6.8%
Latin 16
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 493
 
12.5%
경 196
 
5.0%
산 194
 
4.9%
환 183
 
4.6%
업 155
 
3.9%
대 111
 
2.8%
지 98
 
2.5%
에 97
 
2.5%
이 87
 
2.2%
원 81
 
2.1%
Other values (198) 2253
57.1%
Common
ValueCountFrequency (%)
207
71.6%
( 33
 
11.4%
) 33
 
11.4%
, 9
 
3.1%
2 2
 
0.7%
3 2
 
0.7%
" 1
 
0.3%
& 1
 
0.3%
＆ 1
 
0.3%
Latin
ValueCountFrequency (%)
C 5
31.2%
H 4
25.0%
N 3
18.8%
E 2
 
12.5%
O 2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3455
81.2%
None 494
 
11.6%
ASCII 304
 
7.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 493
99.8%
＆ 1
 
0.2%
ASCII
ValueCountFrequency (%)
207
68.1%
( 33
 
10.9%
) 33
 
10.9%
, 9
 
3.0%
C 5
 
1.6%
H 4
 
1.3%
N 3
 
1.0%
2 2
 
0.7%
3 2
 
0.7%
E 2
 
0.7%
Other values (3) 4
 
1.3%
Hangul
ValueCountFrequency (%)
경 196
 
5.7%
산 194
 
5.6%
환 183
 
5.3%
업 155
 
4.5%
대 111
 
3.2%
지 98
 
2.8%
에 97
 
2.8%
이 87
 
2.5%
원 81
 
2.3%
수 65
 
1.9%
Other values (197) 2188
63.3%

처리업소명
Text

Distinct203
Distinct (%)65.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:08.868665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length215
Median length75
Mean length17.614148
Min length3

Characters and Unicode

Total characters5478
Distinct characters242
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique171 ?
Unique (%)55.0%

Sample

1st rowKC한미산업㈜㈜태원산업부산광역처리시설(명지자원에너지센터등)㈜대한리싸이클
2nd row부산이앤이부산환경공단 명지사업소태산자원㈜㈜청도산업
3rd row㈜부산이앤이부산환경공단명지사업소부산환경공단생곡사업소㈜지원지피더블유
4th row㈜부산이앤이부산환경공단명지사업소부산환경공단생곡사업소㈜피마
5th row부산환경공단생곡사업소부산환경공단명지사업소부산이앤이㈜태양비료㈜MOA고속화학,성창리사이클링대신산업,성창리사이클링미래유지태인산업㈜
ValueCountFrequency (%)
㈜에너지네트웍 24
 
7.0%
현대수산사료㈜ 20
 
5.8%
원우수산 17
 
5.0%
우진에스에프㈜ 8
 
2.3%
㈜부산이앤이명지자원에너지센터부산환경공단생곡사업소 6
 
1.7%
대일알앤에프 5
 
1.5%
㈜하나산업 5
 
1.5%
㈜부영개발 4
 
1.2%
하나산업㈜ 4
 
1.2%
㈜와이에스텍 3
 
0.9%
Other values (222) 247
72.0%
2023-12-11T01:14:09.478348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 566
 
10.3%
산 287
 
5.2%
지 257
 
4.7%
에 245
 
4.5%
이 158
 
2.9%
너 154
 
2.8%
업 146
 
2.7%
부 139
 
2.5%
경 128
 
2.3%
트 119
 
2.2%
Other values (232) 3279
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4673
85.3%
Other Symbol 566
 
10.3%
Uppercase Letter 90
 
1.6%
Close Punctuation 45
 
0.8%
Open Punctuation 45
 
0.8%
Space Separator 33
 
0.6%
Other Punctuation 20
 
0.4%
Decimal Number 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 287
 
6.1%
지 257
 
5.5%
에 245
 
5.2%
이 158
 
3.4%
너 154
 
3.3%
업 146
 
3.1%
부 139
 
3.0%
경 128
 
2.7%
트 119
 
2.5%
사 115
 
2.5%
Other values (211) 2925
62.6%
Uppercase Letter
ValueCountFrequency (%)
C 28
31.1%
N 21
23.3%
A 8
 
8.9%
M 8
 
8.9%
O 8
 
8.9%
K 7
 
7.8%
S 4
 
4.4%
P 3
 
3.3%
B 1
 
1.1%
J 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 18
90.0%
/ 1
 
5.0%
. 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
3 3
50.0%
2 2
33.3%
1 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 566
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5239
95.6%
Common 149
 
2.7%
Latin 90
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 566
 
10.8%
산 287
 
5.5%
지 257
 
4.9%
에 245
 
4.7%
이 158
 
3.0%
너 154
 
2.9%
업 146
 
2.8%
부 139
 
2.7%
경 128
 
2.4%
트 119
 
2.3%
Other values (212) 3040
58.0%
Latin
ValueCountFrequency (%)
C 28
31.1%
N 21
23.3%
A 8
 
8.9%
M 8
 
8.9%
O 8
 
8.9%
K 7
 
7.8%
S 4
 
4.4%
P 3
 
3.3%
B 1
 
1.1%
J 1
 
1.1%
Common
ValueCountFrequency (%)
) 45
30.2%
( 45
30.2%
33
22.1%
, 18
 
12.1%
3 3
 
2.0%
2 2
 
1.3%
1 1
 
0.7%
/ 1
 
0.7%
. 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4673
85.3%
None 566
 
10.3%
ASCII 239
 
4.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 566
100.0%
Hangul
ValueCountFrequency (%)
산 287
 
6.1%
지 257
 
5.5%
에 245
 
5.2%
이 158
 
3.4%
너 154
 
3.3%
업 146
 
3.1%
부 139
 
3.0%
경 128
 
2.7%
트 119
 
2.5%
사 115
 
2.5%
Other values (211) 2925
62.6%
ASCII
ValueCountFrequency (%)
) 45
18.8%
( 45
18.8%
33
13.8%
C 28
11.7%
N 21
8.8%
, 18
 
7.5%
A 8
 
3.3%
M 8
 
3.3%
O 8
 
3.3%
K 7
 
2.9%
Other values (10) 18
 
7.5%

처리방법
Text

Distinct168
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:09.809036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length281
Median length80
Mean length20.254019
Min length2

Characters and Unicode

Total characters6299
Distinct characters75
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)46.3%

Sample

1st row일반소각재활용(2009)소각(2117)재활용(2005)
2nd row재활용(2009)소각(2117)재활용(2009)재활용(2010)
3rd row재활용(2005)지자체소각(2117)지자체매립(2205)재활용(2005)
4th row재활용(2009)소각(2117)매립(2205)재활용(2005)
5th row매립/지자체소각재활용(2009)재활용(2005)재활용(2010)재활용(2003)재활용(2003)재활용(2010)재활용(2003)
ValueCountFrequency (%)
재활용(2005 42
 
12.4%
재활용(2004 20
 
5.9%
재활용(2010 20
 
5.9%
재활용(2003 15
 
4.4%
소각 14
 
4.1%
소각(2101 9
 
2.7%
재활용(2009 8
 
2.4%
매립 8
 
2.4%
고형연료화(2009)지자체소각(2117)지자체매립(2205 6
 
1.8%
일반소각(2101 6
 
1.8%
Other values (162) 190
56.2%
2023-12-11T01:14:10.413880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1030
16.4%
2 658
10.4%
( 654
10.4%
) 652
10.4%
활 451
 
7.2%
재 450
 
7.1%
용 448
 
7.1%
1 357
 
5.7%
소 194
 
3.1%
각 194
 
3.1%
Other values (65) 1211
19.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2558
40.6%
Decimal Number 2392
38.0%
Open Punctuation 654
 
10.4%
Close Punctuation 652
 
10.4%
Space Separator 28
 
0.4%
Other Punctuation 15
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
활 451
17.6%
재 450
17.6%
용 448
17.5%
소 194
7.6%
각 194
7.6%
립 119
 
4.7%
매 119
 
4.7%
간 59
 
2.3%
중 54
 
2.1%
반 41
 
1.6%
Other values (49) 429
16.8%
Decimal Number
ValueCountFrequency (%)
0 1030
43.1%
2 658
27.5%
1 357
 
14.9%
5 99
 
4.1%
3 70
 
2.9%
9 64
 
2.7%
4 53
 
2.2%
7 44
 
1.8%
6 16
 
0.7%
8 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
· 1
 
6.7%
/ 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 654
100.0%
Close Punctuation
ValueCountFrequency (%)
) 652
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3741
59.4%
Hangul 2558
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
활 451
17.6%
재 450
17.6%
용 448
17.5%
소 194
7.6%
각 194
7.6%
립 119
 
4.7%
매 119
 
4.7%
간 59
 
2.3%
중 54
 
2.1%
반 41
 
1.6%
Other values (49) 429
16.8%
Common
ValueCountFrequency (%)
0 1030
27.5%
2 658
17.6%
( 654
17.5%
) 652
17.4%
1 357
 
9.5%
5 99
 
2.6%
3 70
 
1.9%
9 64
 
1.7%
4 53
 
1.4%
7 44
 
1.2%
Other values (6) 60
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3740
59.4%
Hangul 2558
40.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1030
27.5%
2 658
17.6%
( 654
17.5%
) 652
17.4%
1 357
 
9.5%
5 99
 
2.6%
3 70
 
1.9%
9 64
 
1.7%
4 53
 
1.4%
7 44
 
1.2%
Other values (5) 59
 
1.6%
Hangul
ValueCountFrequency (%)
활 451
17.6%
재 450
17.6%
용 448
17.5%
소 194
7.6%
각 194
7.6%
립 119
 
4.7%
매 119
 
4.7%
간 59
 
2.3%
중 54
 
2.1%
반 41
 
1.6%
Other values (49) 429
16.8%
None
ValueCountFrequency (%)
· 1
100.0%

사업장도로명주소
Text

Distinct298
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T01:14:10.858756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length25
Mean length15.048232
Min length6

Characters and Unicode

Total characters4680
Distinct characters100
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)92.3%

Sample

1st row다대로605번길 93(다대동) 정비관리과
2nd row낙동대로550번길37(하단동)
3rd row사리로55번길16(괴정동)
4th row하신중앙로210(신평동)
5th row을숙도대로 610(장림동)
ValueCountFrequency (%)
다산로 28
 
4.2%
감천항로 24
 
3.6%
을숙도대로 18
 
2.7%
다대로605번길 14
 
2.1%
다산로225번길 14
 
2.1%
다대로1066번길 13
 
2.0%
장평로 12
 
1.8%
감천항로405번길 9
 
1.4%
다대로 9
 
1.4%
신산로 8
 
1.2%
Other values (360) 517
77.6%
2023-12-11T01:14:11.443062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
 
7.7%
동 329
 
7.0%
) 306
 
6.5%
( 306
 
6.5%
로 305
 
6.5%
1 214
 
4.6%
번 175
 
3.7%
다 170
 
3.6%
2 167
 
3.6%
길 158
 
3.4%
Other values (90) 2190
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2452
52.4%
Decimal Number 1212
25.9%
Space Separator 360
 
7.7%
Close Punctuation 306
 
6.5%
Open Punctuation 306
 
6.5%
Other Punctuation 25
 
0.5%
Dash Punctuation 16
 
0.3%
Uppercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 329
13.4%
로 305
12.4%
번 175
 
7.1%
다 170
 
6.9%
길 158
 
6.4%
평 154
 
6.3%
대 146
 
6.0%
장 136
 
5.5%
신 123
 
5.0%
림 112
 
4.6%
Other values (70) 644
26.3%
Decimal Number
ValueCountFrequency (%)
1 214
17.7%
2 167
13.8%
5 153
12.6%
6 144
11.9%
0 119
9.8%
3 116
9.6%
7 96
7.9%
4 92
7.6%
9 65
 
5.4%
8 46
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 21
84.0%
: 2
 
8.0%
※ 2
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
360
100.0%
Close Punctuation
ValueCountFrequency (%)
) 306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2452
52.4%
Common 2226
47.6%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 329
13.4%
로 305
12.4%
번 175
 
7.1%
다 170
 
6.9%
길 158
 
6.4%
평 154
 
6.3%
대 146
 
6.0%
장 136
 
5.5%
신 123
 
5.0%
림 112
 
4.6%
Other values (70) 644
26.3%
Common
ValueCountFrequency (%)
360
16.2%
) 306
13.7%
( 306
13.7%
1 214
9.6%
2 167
7.5%
5 153
6.9%
6 144
 
6.5%
0 119
 
5.3%
3 116
 
5.2%
7 96
 
4.3%
Other values (8) 245
11.0%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2452
52.4%
ASCII 2226
47.6%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
16.2%
) 306
13.7%
( 306
13.7%
1 214
9.6%
2 167
7.5%
5 153
6.9%
6 144
 
6.5%
0 119
 
5.3%
3 116
 
5.2%
7 96
 
4.3%
Other values (9) 245
11.0%
Hangul
ValueCountFrequency (%)
동 329
13.4%
로 305
12.4%
번 175
 
7.1%
다 170
 
6.9%
길 158
 
6.4%
평 154
 
6.3%
대 146
 
6.0%
장 136
 
5.5%
신 123
 
5.0%
림 112
 
4.6%
Other values (70) 644
26.3%
Punctuation
ValueCountFrequency (%)
※ 2
100.0%

신고기준연도
Date

Distinct271
Distinct (%)87.4%
Missing1
Missing (%)0.3%
Memory size2.6 KiB
Minimum1995-03-08 00:00:00
Maximum2021-05-04 00:00:00
2023-12-11T01:14:11.676812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:11.876633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-11T01:14:11.996817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분사업장등록번호
구분1.0000.691
사업장등록번호0.6911.000

Missing values

2023-12-11T01:14:02.688704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:14:02.927422image/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.
2023-12-11T01:14:03.127820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분상호명폐기물종류사업장등록번호운반자명처리업소명처리방법사업장도로명주소신고기준연도
0사업장일반폐기물해양경찰정비창장폐합성수지폐목재생활폐기물음식물류폐기물<NA>미래환경미래환경세화산업㈜대한리싸이클KC한미산업㈜㈜태원산업부산광역처리시설(명지자원에너지센터등)㈜대한리싸이클일반소각재활용(2009)소각(2117)재활용(2005)다대로605번길 93(다대동) 정비관리과1995-03-08
1사업장일반폐기물동아대학교 승학캠퍼스생활폐기물폐목재폐합성수지<NA>세화산업태산자원㈜(주)청도산업부산이앤이부산환경공단 명지사업소태산자원㈜㈜청도산업재활용(2009)소각(2117)재활용(2009)재활용(2010)낙동대로550번길37(하단동)1995-03-08
2사업장일반폐기물동주대학교생활폐기물음식물류폐기물<NA>세화산업㈜지원환경㈜부산이앤이부산환경공단명지사업소부산환경공단생곡사업소㈜지원지피더블유재활용(2005)지자체소각(2117)지자체매립(2205)재활용(2005)사리로55번길16(괴정동)1995-03-08
3사업장일반폐기물㈜서원유통탑마트신평점생활폐기물음식물류폐기물<NA>미진산업아이맥스환경㈜부산이앤이부산환경공단명지사업소부산환경공단생곡사업소㈜피마재활용(2009)소각(2117)매립(2205)재활용(2005)하신중앙로210(신평동)1998-12-19
4사업장일반폐기물롯데쇼핑㈜롯데마트사하점생활폐기물음식물류폐기물폐합성수지폐발포합성수지폐식용유축산물가공잔재물<NA>㈜여민환경㈜여민환경㈜여민환경대신산업,성창리사이클링미래&동명물류센터지현유지부산환경공단생곡사업소부산환경공단명지사업소부산이앤이㈜태양비료㈜MOA고속화학,성창리사이클링대신산업,성창리사이클링미래유지태인산업㈜매립/지자체소각재활용(2009)재활용(2005)재활용(2010)재활용(2003)재활용(2003)재활용(2010)재활용(2003)을숙도대로 610(장림동)2000-10-11
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6사업장일반폐기물㈜등푸른식품수산물가공잔재물<NA>영남상회원우수산재활용(2004)다산로 265(장림동)2004-10-11
7사업장일반폐기물뉴코아아울렛괴정점그밖의폐기물(생활폐기물)음식물류폐기물폐발포합성수지폐합성수지<NA>이레환경㈜여민환경대신산업,성창리사이클링㈜여민환경부산환경공단생곡매립장부산환경공단명지사업소부산이앤이㈜태양비료㈜MOA대신산업,성창리사이클링고속수지,성창리사이클링지자체매립지자체소각재활용(2009)재활용(2005)재활용(2010)재활용(2003)재활용(2003)사하로 190(괴정동)2006-04-28
8사업장일반폐기물㈜성원그린그밖의폐기물<NA>자가㈜에너지네트웍㈜대호환경현진환경개발㈜석지환경개발㈜에너지네트웍석지환경개발㈜중간(소각)중간(소각)중간(소각)재활용(2010)중간(소각)재활용(2010)구평로10(구평동)2007-05-15
9사업장일반폐기물㈜동원해사랑수산물가공잔재물<NA>현대수산사료㈜현대수산사료㈜재활용(2005)감천항로 24(감천동)2009-06-30
구분상호명폐기물종류사업장등록번호운반자명처리업소명처리방법사업장도로명주소신고기준연도
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