Overview

Dataset statistics

Number of variables10
Number of observations158
Missing cells417
Missing cells (%)26.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory80.8 B

Variable types

Categorical4
Text6

Dataset

Description부산광역시사상구_사업장폐기물배출자현황_20230721
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15060273

Alerts

구분 has constant value ""Constant
폐기물종류1 is highly overall correlated with 폐기물종류2High correlation
폐기물종류2 is highly overall correlated with 폐기물종류1High correlation
전화번호(051) has 3 (1.9%) missing valuesMissing
폐기물종류3 has 127 (80.4%) missing valuesMissing
폐기물종류4 has 140 (88.6%) missing valuesMissing
폐기물종류5 has 147 (93.0%) missing valuesMissing

Reproduction

Analysis started2023-12-10 17:24:44.738344
Analysis finished2023-12-10 17:24:46.555696
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
사업장 폐기물
158 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장 폐기물
2nd row사업장 폐기물
3rd row사업장 폐기물
4th row사업장 폐기물
5th row사업장 폐기물

Common Values

ValueCountFrequency (%)
사업장 폐기물 158
100.0%

Length

2023-12-11T02:24:46.747066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:24:47.004183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장 158
50.0%
폐기물 158
50.0%

업소명
Text

Distinct157
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T02:24:47.565107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.9050633
Min length3

Characters and Unicode

Total characters1249
Distinct characters226
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

Unique156 ?
Unique (%)98.7%

Sample

1st row(의)은성의료재단좋은삼선병원
2nd row동일철강(주)
3rd row케이티아이상사
4th row동아금속
5th row천지유리
ValueCountFrequency (%)
삼화스틸(주 3
 
1.7%
주)보생 2
 
1.1%
주)희원금속 2
 
1.1%
농협경제지주 2
 
1.1%
사상공장 2
 
1.1%
학장지점 1
 
0.6%
한일시멘트(주)부산공장 1
 
0.6%
조광페인트(주 1
 
0.6%
주)파티트리 1
 
0.6%
부산새벽시장상인회 1
 
0.6%
Other values (165) 165
91.2%
2023-12-11T02:24:48.491234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 94
 
7.5%
) 94
 
7.5%
주 92
 
7.4%
산 41
 
3.3%
금 32
 
2.6%
속 31
 
2.5%
부 28
 
2.2%
공 26
 
2.1%
24
 
1.9%
업 24
 
1.9%
Other values (216) 763
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1027
82.2%
Open Punctuation 94
 
7.5%
Close Punctuation 94
 
7.5%
Space Separator 24
 
1.9%
Decimal Number 3
 
0.2%
Uppercase Letter 3
 
0.2%
Lowercase Letter 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 92
 
9.0%
산 41
 
4.0%
금 32
 
3.1%
속 31
 
3.0%
부 28
 
2.7%
공 26
 
2.5%
업 24
 
2.3%
동 21
 
2.0%
장 20
 
1.9%
원 19
 
1.9%
Other values (204) 693
67.5%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
C 1
33.3%
J 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
y 1
33.3%
i 1
33.3%
t 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1027
82.2%
Common 216
 
17.3%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 92
 
9.0%
산 41
 
4.0%
금 32
 
3.1%
속 31
 
3.0%
부 28
 
2.7%
공 26
 
2.5%
업 24
 
2.3%
동 21
 
2.0%
장 20
 
1.9%
원 19
 
1.9%
Other values (204) 693
67.5%
Common
ValueCountFrequency (%)
( 94
43.5%
) 94
43.5%
24
 
11.1%
1 2
 
0.9%
- 1
 
0.5%
2 1
 
0.5%
Latin
ValueCountFrequency (%)
M 1
16.7%
C 1
16.7%
y 1
16.7%
i 1
16.7%
t 1
16.7%
J 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1027
82.2%
ASCII 222
 
17.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 94
42.3%
) 94
42.3%
24
 
10.8%
1 2
 
0.9%
- 1
 
0.5%
M 1
 
0.5%
C 1
 
0.5%
y 1
 
0.5%
i 1
 
0.5%
t 1
 
0.5%
Other values (2) 2
 
0.9%
Hangul
ValueCountFrequency (%)
주 92
 
9.0%
산 41
 
4.0%
금 32
 
3.1%
속 31
 
3.0%
부 28
 
2.7%
공 26
 
2.5%
업 24
 
2.3%
동 21
 
2.0%
장 20
 
1.9%
원 19
 
1.9%
Other values (204) 693
67.5%

소재지(배출지)
Text

Distinct156
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T02:24:49.172048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length24.658228
Min length11

Characters and Unicode

Total characters3896
Distinct characters73
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

Unique154 ?
Unique (%)97.5%

Sample

1st row부산광역시 사상구 가야대로 326(주례동)
2nd row부산광역시 사상구 가야대로 46(학장동)
3rd row부산광역시 사상구 가야대로 91(감전동)
4th row부산광역시 사상구 가야대로103번길 16(감전동)
5th row부산광역시 사상구 가야대로11번길 43(감전동)
ValueCountFrequency (%)
부산광역시 151
24.0%
사상구 151
24.0%
낙동대로 13
 
2.1%
감전천로 8
 
1.3%
광장로 6
 
1.0%
대동로 6
 
1.0%
학장로 6
 
1.0%
농산물시장로 4
 
0.6%
82(학장동 4
 
0.6%
사상로 3
 
0.5%
Other values (233) 276
43.9%
2023-12-11T02:24:50.104453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
470
 
12.1%
동 209
 
5.4%
사 163
 
4.2%
상 163
 
4.2%
시 159
 
4.1%
산 159
 
4.1%
( 158
 
4.1%
) 158
 
4.1%
로 158
 
4.1%
광 157
 
4.0%
Other values (63) 1942
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2448
62.8%
Decimal Number 641
 
16.5%
Space Separator 470
 
12.1%
Open Punctuation 158
 
4.1%
Close Punctuation 158
 
4.1%
Dash Punctuation 13
 
0.3%
Other Punctuation 4
 
0.1%
Uppercase Letter 3
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 209
 
8.5%
사 163
 
6.7%
상 163
 
6.7%
시 159
 
6.5%
산 159
 
6.5%
로 158
 
6.5%
광 157
 
6.4%
부 151
 
6.2%
역 151
 
6.2%
구 151
 
6.2%
Other values (44) 827
33.8%
Decimal Number
ValueCountFrequency (%)
1 105
16.4%
2 80
12.5%
3 69
10.8%
6 69
10.8%
7 61
9.5%
4 60
9.4%
9 52
8.1%
8 50
7.8%
5 50
7.8%
0 45
7.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
T 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
470
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2448
62.8%
Common 1445
37.1%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 209
 
8.5%
사 163
 
6.7%
상 163
 
6.7%
시 159
 
6.5%
산 159
 
6.5%
로 158
 
6.5%
광 157
 
6.4%
부 151
 
6.2%
역 151
 
6.2%
구 151
 
6.2%
Other values (44) 827
33.8%
Common
ValueCountFrequency (%)
470
32.5%
( 158
 
10.9%
) 158
 
10.9%
1 105
 
7.3%
2 80
 
5.5%
3 69
 
4.8%
6 69
 
4.8%
7 61
 
4.2%
4 60
 
4.2%
9 52
 
3.6%
Other values (6) 163
 
11.3%
Latin
ValueCountFrequency (%)
A 1
33.3%
T 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2448
62.8%
ASCII 1448
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
470
32.5%
( 158
 
10.9%
) 158
 
10.9%
1 105
 
7.3%
2 80
 
5.5%
3 69
 
4.8%
6 69
 
4.8%
7 61
 
4.2%
4 60
 
4.1%
9 52
 
3.6%
Other values (9) 166
 
11.5%
Hangul
ValueCountFrequency (%)
동 209
 
8.5%
사 163
 
6.7%
상 163
 
6.7%
시 159
 
6.5%
산 159
 
6.5%
로 158
 
6.5%
광 157
 
6.4%
부 151
 
6.2%
역 151
 
6.2%
구 151
 
6.2%
Other values (44) 827
33.8%

전화번호(051)
Text

MISSING 

Distinct152
Distinct (%)98.1%
Missing3
Missing (%)1.9%
Memory size1.4 KiB
2023-12-11T02:24:50.853826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.1225806
Min length8

Characters and Unicode

Total characters1259
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

Unique149 ?
Unique (%)96.1%

Sample

1st row322-0900
2nd row322-1177
3rd row312-1495
4th row322-8898
5th row313-7000
ValueCountFrequency (%)
315-5567 2
 
1.3%
315-4404 2
 
1.3%
323-9992 2
 
1.3%
301-3110 1
 
0.6%
304-2522 1
 
0.6%
323-1512 1
 
0.6%
327-7991 1
 
0.6%
322-0900 1
 
0.6%
314-2563 1
 
0.6%
366-5383 1
 
0.6%
Other values (142) 142
91.6%
2023-12-11T02:24:52.125945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 230
18.3%
1 159
12.6%
- 159
12.6%
0 153
12.2%
2 147
11.7%
5 83
 
6.6%
6 69
 
5.5%
9 68
 
5.4%
7 67
 
5.3%
4 67
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1100
87.4%
Dash Punctuation 159
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 230
20.9%
1 159
14.5%
0 153
13.9%
2 147
13.4%
5 83
 
7.5%
6 69
 
6.3%
9 68
 
6.2%
7 67
 
6.1%
4 67
 
6.1%
8 57
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1259
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 230
18.3%
1 159
12.6%
- 159
12.6%
0 153
12.2%
2 147
11.7%
5 83
 
6.6%
6 69
 
5.5%
9 68
 
5.4%
7 67
 
5.3%
4 67
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 230
18.3%
1 159
12.6%
- 159
12.6%
0 153
12.2%
2 147
11.7%
5 83
 
6.6%
6 69
 
5.5%
9 68
 
5.4%
7 67
 
5.3%
4 67
 
5.3%

비고
Categorical

Distinct17
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
제조업
97 
대형상가
12 
사무실 등
11 
폐기물처리업
10 
병원
 
8
Other values (12)
20 

Length

Max length21
Median length3
Mean length3.7531646
Min length2

Unique

Unique7 ?
Unique (%)4.4%

Sample

1st row병원
2nd row제조업
3rd row제조업
4th row제조업
5th row제조업

Common Values

ValueCountFrequency (%)
제조업 97
61.4%
대형상가 12
 
7.6%
사무실 등 11
 
7.0%
폐기물처리업 10
 
6.3%
병원 8
 
5.1%
대학교 3
 
1.9%
서비스업 3
 
1.9%
음식점 3
 
1.9%
공공시설 2
 
1.3%
자동차폐차 2
 
1.3%
Other values (7) 7
 
4.4%

Length

2023-12-11T02:24:52.566087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조업 101
56.1%
대형상가 12
 
6.7%
사무실 11
 
6.1%
등 11
 
6.1%
폐기물처리업 10
 
5.6%
병원 8
 
4.4%
서비스업 3
 
1.7%
음식점 3
 
1.7%
대학교 3
 
1.7%
공공시설 2
 
1.1%
Other values (14) 16
 
8.9%

폐기물종류1
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
그 밖의 폐기물
40 
화학점결폐주물사
37 
폐합성수지류
28 
폐수처리오니
6 
그 밖의 분진
 
4
Other values (25)
43 

Length

Max length14
Median length8
Mean length7.1202532
Min length2

Unique

Unique16 ?
Unique (%)10.1%

Sample

1st row그 밖의 폐기물
2nd row그 밖의 공정오니
3rd row폐합성수지류
4th row화학점결폐주물사
5th row폐유리

Common Values

ValueCountFrequency (%)
그 밖의 폐기물 40
25.3%
화학점결폐주물사 37
23.4%
폐합성수지류 28
17.7%
폐수처리오니 6
 
3.8%
그 밖의 분진 4
 
2.5%
점토점결폐주물사 4
 
2.5%
공정오니 4
 
2.5%
폐합성고무류 3
 
1.9%
그 밖의 폐섬유 3
 
1.9%
폐콘크리트 3
 
1.9%
Other values (20) 26
16.5%

Length

2023-12-11T02:24:53.015482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
그 52
19.8%
밖의 52
19.8%
폐기물 40
15.2%
화학점결폐주물사 37
14.1%
폐합성수지류 28
10.6%
분진 7
 
2.7%
공정오니 6
 
2.3%
폐수처리오니 6
 
2.3%
폐섬유 4
 
1.5%
점토점결폐주물사 4
 
1.5%
Other values (19) 27
10.3%

폐기물종류2
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
82 
음식물류폐기물
30 
폐합성수지류
 
8
그 밖의 폐기물
 
6
폐합성고무류
 
5
Other values (15)
27 

Length

Max length12
Median length4
Mean length5.1329114
Min length2

Unique

Unique11 ?
Unique (%)7.0%

Sample

1st row음식물류폐기물
2nd row그 밖의 분진
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 82
51.9%
음식물류폐기물 30
 
19.0%
폐합성수지류 8
 
5.1%
그 밖의 폐기물 6
 
3.8%
폐합성고무류 5
 
3.2%
폐목재류 5
 
3.2%
분진 4
 
2.5%
그 밖의 분진 4
 
2.5%
그 밖의 식물성잔재물 3
 
1.9%
그 밖의 동식물성잔재물 1
 
0.6%
Other values (10) 10
 
6.3%

Length

2023-12-11T02:24:54.145678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 82
43.9%
음식물류폐기물 30
 
16.0%
그 14
 
7.5%
밖의 14
 
7.5%
폐합성수지류 8
 
4.3%
분진 8
 
4.3%
폐기물 6
 
3.2%
폐합성고무류 5
 
2.7%
폐목재류 5
 
2.7%
식물성잔재물 3
 
1.6%
Other values (12) 12
 
6.4%

폐기물종류3
Text

MISSING 

Distinct17
Distinct (%)54.8%
Missing127
Missing (%)80.4%
Memory size1.4 KiB
2023-12-11T02:24:54.665156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.1290323
Min length2

Characters and Unicode

Total characters190
Distinct characters39
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)35.5%

Sample

1st row폐합성수지류
2nd row폐촉매
3rd row식물성잔재물
4th row폐합성수지류
5th row그 밖의 폐목재류
ValueCountFrequency (%)
폐합성수지류 8
17.0%
밖의 8
17.0%
그 8
17.0%
폐목재류 5
10.6%
폐기물 3
 
6.4%
폐합성섬유 2
 
4.3%
음식물류폐기물 2
 
4.3%
폐섬유 2
 
4.3%
폐촉매 1
 
2.1%
동식물성잔재물 1
 
2.1%
Other values (7) 7
14.9%
2023-12-11T02:24:55.577070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 25
13.2%
류 16
 
8.4%
16
 
8.4%
성 13
 
6.8%
물 11
 
5.8%
합 11
 
5.8%
수 10
 
5.3%
지 9
 
4.7%
재 9
 
4.7%
그 8
 
4.2%
Other values (29) 62
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
91.6%
Space Separator 16
 
8.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 25
14.4%
류 16
 
9.2%
성 13
 
7.5%
물 11
 
6.3%
합 11
 
6.3%
수 10
 
5.7%
지 9
 
5.2%
재 9
 
5.2%
그 8
 
4.6%
밖 8
 
4.6%
Other values (28) 54
31.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
91.6%
Common 16
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 25
14.4%
류 16
 
9.2%
성 13
 
7.5%
물 11
 
6.3%
합 11
 
6.3%
수 10
 
5.7%
지 9
 
5.2%
재 9
 
5.2%
그 8
 
4.6%
밖 8
 
4.6%
Other values (28) 54
31.0%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
91.6%
ASCII 16
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 25
14.4%
류 16
 
9.2%
성 13
 
7.5%
물 11
 
6.3%
합 11
 
6.3%
수 10
 
5.7%
지 9
 
5.2%
재 9
 
5.2%
그 8
 
4.6%
밖 8
 
4.6%
Other values (28) 54
31.0%
ASCII
ValueCountFrequency (%)
16
100.0%

폐기물종류4
Text

MISSING 

Distinct14
Distinct (%)77.8%
Missing140
Missing (%)88.6%
Memory size1.4 KiB
2023-12-11T02:24:56.025700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length6.0555556
Min length3

Characters and Unicode

Total characters109
Distinct characters41
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)61.1%

Sample

1st row폐냉매
2nd row폐발포성합성수지
3rd row폐합성수지류
4th row폐식용유
5th row음식물류폐기물
ValueCountFrequency (%)
폐합성수지류 3
 
11.5%
그 3
 
11.5%
밖의 3
 
11.5%
폐기물 2
 
7.7%
폐목재류 2
 
7.7%
기타 1
 
3.8%
폐흡착제 1
 
3.8%
도로스 1
 
3.8%
폐촉매 1
 
3.8%
폐합성고무류 1
 
3.8%
Other values (8) 8
30.8%
2023-12-11T02:24:56.769560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 17
15.6%
성 8
 
7.3%
합 8
 
7.3%
8
 
7.3%
류 7
 
6.4%
물 5
 
4.6%
수 4
 
3.7%
지 4
 
3.7%
기 4
 
3.7%
그 3
 
2.8%
Other values (31) 41
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101
92.7%
Space Separator 8
 
7.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 17
16.8%
성 8
 
7.9%
합 8
 
7.9%
류 7
 
6.9%
물 5
 
5.0%
수 4
 
4.0%
지 4
 
4.0%
기 4
 
4.0%
그 3
 
3.0%
밖 3
 
3.0%
Other values (30) 38
37.6%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101
92.7%
Common 8
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 17
16.8%
성 8
 
7.9%
합 8
 
7.9%
류 7
 
6.9%
물 5
 
5.0%
수 4
 
4.0%
지 4
 
4.0%
기 4
 
4.0%
그 3
 
3.0%
밖 3
 
3.0%
Other values (30) 38
37.6%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101
92.7%
ASCII 8
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 17
16.8%
성 8
 
7.9%
합 8
 
7.9%
류 7
 
6.9%
물 5
 
5.0%
수 4
 
4.0%
지 4
 
4.0%
기 4
 
4.0%
그 3
 
3.0%
밖 3
 
3.0%
Other values (30) 38
37.6%
ASCII
ValueCountFrequency (%)
8
100.0%

폐기물종류5
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing147
Missing (%)93.0%
Memory size1.4 KiB
2023-12-11T02:24:57.117367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.5454545
Min length1

Characters and Unicode

Total characters61
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)63.6%

Sample

1st row폐식용유
2nd row동물성잔재물
3rd row폐식용유
4th row그 밖의 폐기물
5th row폐타이어
ValueCountFrequency (%)
그 3
16.7%
밖의 3
16.7%
폐식용유 2
11.1%
폐기물 2
11.1%
폐타이어 2
11.1%
동물성잔재물 1
 
5.6%
자동차 1
 
5.6%
0 1
 
5.6%
폐합성수지류 1
 
5.6%
폐목재류 1
 
5.6%
2023-12-11T02:24:57.723624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 9
 
14.8%
7
 
11.5%
물 4
 
6.6%
유 3
 
4.9%
그 3
 
4.9%
밖 3
 
4.9%
의 3
 
4.9%
식 2
 
3.3%
류 2
 
3.3%
어 2
 
3.3%
Other values (16) 23
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53
86.9%
Space Separator 7
 
11.5%
Decimal Number 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 9
17.0%
물 4
 
7.5%
유 3
 
5.7%
그 3
 
5.7%
밖 3
 
5.7%
의 3
 
5.7%
식 2
 
3.8%
류 2
 
3.8%
어 2
 
3.8%
이 2
 
3.8%
Other values (14) 20
37.7%
Space Separator
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53
86.9%
Common 8
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 9
17.0%
물 4
 
7.5%
유 3
 
5.7%
그 3
 
5.7%
밖 3
 
5.7%
의 3
 
5.7%
식 2
 
3.8%
류 2
 
3.8%
어 2
 
3.8%
이 2
 
3.8%
Other values (14) 20
37.7%
Common
ValueCountFrequency (%)
7
87.5%
0 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53
86.9%
ASCII 8
 
13.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 9
17.0%
물 4
 
7.5%
유 3
 
5.7%
그 3
 
5.7%
밖 3
 
5.7%
의 3
 
5.7%
식 2
 
3.8%
류 2
 
3.8%
어 2
 
3.8%
이 2
 
3.8%
Other values (14) 20
37.7%
ASCII
ValueCountFrequency (%)
7
87.5%
0 1
 
12.5%

Correlations

2023-12-11T02:24:57.905599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고폐기물종류1폐기물종류2폐기물종류3폐기물종류4폐기물종류5
비고1.0000.7570.7720.3860.9530.684
폐기물종류10.7571.0000.9270.9220.5370.923
폐기물종류20.7720.9271.0000.9580.0000.923
폐기물종류30.3860.9220.9581.0000.7480.883
폐기물종류40.9530.5370.0000.7481.0000.821
폐기물종류50.6840.9230.9230.8830.8211.000
2023-12-11T02:24:58.135010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물종류2폐기물종류1비고
폐기물종류21.0000.5770.367
폐기물종류10.5771.0000.300
비고0.3670.3001.000
2023-12-11T02:24:58.328003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고폐기물종류1폐기물종류2
비고1.0000.3000.367
폐기물종류10.3001.0000.577
폐기물종류20.3670.5771.000

Missing values

2023-12-11T02:24:45.733114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:24:46.079511image/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.
2023-12-11T02:24:46.365438image/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

구분업소명소재지(배출지)전화번호(051)비고폐기물종류1폐기물종류2폐기물종류3폐기물종류4폐기물종류5
0사업장 폐기물(의)은성의료재단좋은삼선병원부산광역시 사상구 가야대로 326(주례동)322-0900병원그 밖의 폐기물음식물류폐기물<NA><NA><NA>
1사업장 폐기물동일철강(주)부산광역시 사상구 가야대로 46(학장동)322-1177제조업그 밖의 공정오니그 밖의 분진<NA><NA><NA>
2사업장 폐기물케이티아이상사부산광역시 사상구 가야대로 91(감전동)312-1495제조업폐합성수지류<NA><NA><NA><NA>
3사업장 폐기물동아금속부산광역시 사상구 가야대로103번길 16(감전동)322-8898제조업화학점결폐주물사<NA><NA><NA><NA>
4사업장 폐기물천지유리부산광역시 사상구 가야대로11번길 43(감전동)313-7000제조업폐유리<NA><NA><NA><NA>
5사업장 폐기물제일하이텍(주)부산광역시 사상구 가야대로175번길 16(주례동)324-1513제조업폐합성수지류<NA><NA><NA><NA>
6사업장 폐기물한국전력공사 부산울산지역본부부산광역시 사상구 가야대로214번길 42(학장동)055-320-2668서비스업그 밖의 폐합성고분자화합물폐전주<NA><NA><NA>
7사업장 폐기물경남정보대학부산광역시 사상구 가야대로360번길 48(주례동)320-1589대학교그 밖의 폐기물음식물류폐기물폐합성수지류<NA><NA>
8사업장 폐기물주례여자고등학교부산광역시 사상구 가야대로366번길 146(주례동)310-3508학교그 밖의 폐기물음식물류폐기물<NA><NA><NA>
9사업장 폐기물고속화학부산광역시 사상구 가야대로48번길 34(학장동)324-1896폐기물처리업폐합성수지류<NA><NA><NA><NA>
구분업소명소재지(배출지)전화번호(051)비고폐기물종류1폐기물종류2폐기물종류3폐기물종류4폐기물종류5
148사업장 폐기물한양식품부산광역시 사상구 학장로83번길 34(학장동)316-1677제조업수산물가공잔재물폐합성수지류<NA><NA><NA>
149사업장 폐기물(주)경동특수주강부산광역시 사상구 학장로95번길 20(학장동)311-1670제조업화학점결폐주물사분진광재폐합성수지류폐섬유
150사업장 폐기물(주)동광주물부산광역시 사상구 학장로95번길 9(학장동)325-0598제조업화학점결폐주물사<NA><NA><NA><NA>
151사업장 폐기물(주)푸드엔 엄궁지점농산물시장로 42(엄궁동)<NA>대형상가그 밖의 폐기물음식물류폐기물<NA><NA><NA>
152사업장 폐기물(주)에이비씨사상로 559(모라동)<NA>제조업그 밖의 폐기물음식물류폐기물<NA><NA><NA>
153사업장 폐기물(주)에이스 유나이티드낙동대로 1420번길 17(삼락동)301-3110제조업폐합성수지<NA><NA><NA><NA>
154사업장 폐기물동훈산업사주례로 216(학장동)328-9807제조업화학점결폐주물사<NA><NA><NA><NA>
155사업장 폐기물금강화학낙동대로1472(삼락동)305-5353제조업폐합성수지<NA><NA><NA><NA>
156사업장 폐기물(주)영창에코낙동대로 901번길 40(감전동)301-7739제조업폐합성수지류<NA><NA><NA><NA>
157사업장 폐기물(주)예인엠텍학장로 55(학장동)322-3387제조업폐합성수지류<NA><NA><NA><NA>