Overview

Dataset statistics

Number of variables18
Number of observations363
Missing cells20
Missing cells (%)0.3%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory52.2 KiB
Average record size in memory147.4 B

Variable types

Text7
Categorical8
Numeric3

Dataset

Description광주광역시 동구 관내 사업장에서 배출한 폐기물 업체 현황으로 폐기물구분, 상호명, 폐기물종류, 전화번호, 처리방법, 사업장도로명주소, 신고기준년도 제공합니다. ○ 제공기간: (최초) 2016~ 2021. 5. 6., (추후) 연간 내역 제공
URLhttps://www.data.go.kr/data/15081087/fileData.do

Alerts

업무구분 has constant value ""Constant
데이터 기준 일자 has constant value ""Constant
Dataset has 1 (0.3%) duplicate rowsDuplicates
폐기물자가처리방법 is highly overall correlated with 생활계구분 and 3 other fieldsHigh correlation
처리방법 is highly overall correlated with 생활계구분 and 3 other fieldsHigh correlation
배출량(톤) is highly overall correlated with 운반량(톤) and 1 other fieldsHigh correlation
운반량(톤) is highly overall correlated with 배출량(톤) and 1 other fieldsHigh correlation
처리량(톤_연) is highly overall correlated with 배출량(톤) and 1 other fieldsHigh correlation
생활계구분 is highly overall correlated with 폐기물 종류 and 2 other fieldsHigh correlation
폐기물 종류 is highly overall correlated with 생활계구분 and 3 other fieldsHigh correlation
처리구분 is highly overall correlated with 폐기물 종류 and 2 other fieldsHigh correlation
처리구분 is highly imbalanced (85.4%)Imbalance
전화번호 has 20 (5.5%) missing valuesMissing
배출량(톤) has 8 (2.2%) zerosZeros
운반량(톤) has 10 (2.8%) zerosZeros
처리량(톤_연) has 10 (2.8%) zerosZeros

Reproduction

Analysis started2023-12-12 00:18:59.393109
Analysis finished2023-12-12 00:19:03.433559
Duration4.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct95
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:03.598147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length8.5922865
Min length1

Characters and Unicode

Total characters3119
Distinct characters190
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

Unique33 ?
Unique (%)9.1%

Sample

1st row동명병원
2nd row동명병원
3rd row동명병원
4th row동명병원
5th row동명병원
ValueCountFrequency (%)
조선대학교 19
 
4.8%
광주도로관리(주 17
 
4.3%
전남대학교병원 16
 
4.0%
의료법인 14
 
3.5%
홈플러스(주)계림점 11
 
2.8%
국립아시아문화전당 8
 
2.0%
광주소망병원 8
 
2.0%
강남요양병원 8
 
2.0%
광주고려요양병원 8
 
2.0%
삼성테스코(주)홈플러스(계림점 8
 
2.0%
Other values (91) 279
70.5%
2023-12-12T09:19:03.936616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 195
 
6.3%
) 142
 
4.6%
( 142
 
4.6%
원 115
 
3.7%
병 108
 
3.5%
학 100
 
3.2%
광 97
 
3.1%
대 90
 
2.9%
교 86
 
2.8%
조 62
 
2.0%
Other values (180) 1982
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2791
89.5%
Close Punctuation 142
 
4.6%
Open Punctuation 142
 
4.6%
Space Separator 35
 
1.1%
Uppercase Letter 8
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 195
 
7.0%
원 115
 
4.1%
병 108
 
3.9%
학 100
 
3.6%
광 97
 
3.5%
대 90
 
3.2%
교 86
 
3.1%
조 62
 
2.2%
선 56
 
2.0%
점 53
 
1.9%
Other values (172) 1829
65.5%
Uppercase Letter
ValueCountFrequency (%)
C 3
37.5%
N 3
37.5%
D 1
 
12.5%
F 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2791
89.5%
Common 320
 
10.3%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 195
 
7.0%
원 115
 
4.1%
병 108
 
3.9%
학 100
 
3.6%
광 97
 
3.5%
대 90
 
3.2%
교 86
 
3.1%
조 62
 
2.2%
선 56
 
2.0%
점 53
 
1.9%
Other values (172) 1829
65.5%
Common
ValueCountFrequency (%)
) 142
44.4%
( 142
44.4%
35
 
10.9%
& 1
 
0.3%
Latin
ValueCountFrequency (%)
C 3
37.5%
N 3
37.5%
D 1
 
12.5%
F 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2791
89.5%
ASCII 328
 
10.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 195
 
7.0%
원 115
 
4.1%
병 108
 
3.9%
학 100
 
3.6%
광 97
 
3.5%
대 90
 
3.2%
교 86
 
3.1%
조 62
 
2.2%
선 56
 
2.0%
점 53
 
1.9%
Other values (172) 1829
65.5%
ASCII
ValueCountFrequency (%)
) 142
43.3%
( 142
43.3%
35
 
10.7%
C 3
 
0.9%
N 3
 
0.9%
D 1
 
0.3%
F 1
 
0.3%
& 1
 
0.3%

전화번호
Text

MISSING 

Distinct86
Distinct (%)25.1%
Missing20
Missing (%)5.5%
Memory size3.0 KiB
2023-12-12T09:19:04.153608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.61516
Min length1

Characters and Unicode

Total characters3984
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)8.5%

Sample

1st row062-670-3333
2nd row062-670-3333
3rd row062-670-3333
4th row062-670-3333
5th row062-670-3333
ValueCountFrequency (%)
062-220-8863 17
 
5.2%
062-220-5128 15
 
4.5%
062-530-8124 11
 
3.3%
062-230-7581 10
 
3.0%
062-230-6216 9
 
2.7%
062-230-9000 8
 
2.4%
062-601-9000 8
 
2.4%
062-227-7775 8
 
2.4%
062-601-4362 8
 
2.4%
062-716-8021 8
 
2.4%
Other values (73) 228
69.1%
2023-12-12T09:19:04.517091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 817
20.5%
0 779
19.6%
- 660
16.6%
6 519
13.0%
3 264
 
6.6%
1 240
 
6.0%
8 169
 
4.2%
7 168
 
4.2%
5 152
 
3.8%
4 104
 
2.6%
Other values (2) 112
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3307
83.0%
Dash Punctuation 660
 
16.6%
Space Separator 17
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 817
24.7%
0 779
23.6%
6 519
15.7%
3 264
 
8.0%
1 240
 
7.3%
8 169
 
5.1%
7 168
 
5.1%
5 152
 
4.6%
4 104
 
3.1%
9 95
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 660
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3984
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 817
20.5%
0 779
19.6%
- 660
16.6%
6 519
13.0%
3 264
 
6.6%
1 240
 
6.0%
8 169
 
4.2%
7 168
 
4.2%
5 152
 
3.8%
4 104
 
2.6%
Other values (2) 112
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 817
20.5%
0 779
19.6%
- 660
16.6%
6 519
13.0%
3 264
 
6.6%
1 240
 
6.0%
8 169
 
4.2%
7 168
 
4.2%
5 152
 
3.8%
4 104
 
2.6%
Other values (2) 112
 
2.8%

신고일
Text

Distinct95
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:04.693801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters5082
Distinct characters14
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

Unique34 ?
Unique (%)9.4%

Sample

1st row2022 년11 월14 일
2nd row2022 년11 월14 일
3rd row2022 년11 월14 일
4th row2022 년11 월14 일
5th row2022 년11 월14 일
ValueCountFrequency (%)
일 363
25.0%
2011 65
 
4.5%
년07 61
 
4.2%
년04 58
 
4.0%
2014 53
 
3.7%
년12 40
 
2.8%
1996 38
 
2.6%
월22 35
 
2.4%
월27 33
 
2.3%
년06 33
 
2.3%
Other values (56) 673
46.3%
2023-12-12T09:19:04.988836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1089
21.4%
0 837
16.5%
2 638
12.6%
1 595
11.7%
년 363
 
7.1%
월 363
 
7.1%
일 363
 
7.1%
4 174
 
3.4%
9 154
 
3.0%
7 147
 
2.9%
Other values (4) 359
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2904
57.1%
Space Separator 1089
 
21.4%
Other Letter 1089
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 837
28.8%
2 638
22.0%
1 595
20.5%
4 174
 
6.0%
9 154
 
5.3%
7 147
 
5.1%
6 118
 
4.1%
3 103
 
3.5%
8 87
 
3.0%
5 51
 
1.8%
Other Letter
ValueCountFrequency (%)
년 363
33.3%
월 363
33.3%
일 363
33.3%
Space Separator
ValueCountFrequency (%)
1089
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3993
78.6%
Hangul 1089
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1089
27.3%
0 837
21.0%
2 638
16.0%
1 595
14.9%
4 174
 
4.4%
9 154
 
3.9%
7 147
 
3.7%
6 118
 
3.0%
3 103
 
2.6%
8 87
 
2.2%
Hangul
ValueCountFrequency (%)
년 363
33.3%
월 363
33.3%
일 363
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3993
78.6%
Hangul 1089
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1089
27.3%
0 837
21.0%
2 638
16.0%
1 595
14.9%
4 174
 
4.4%
9 154
 
3.9%
7 147
 
3.7%
6 118
 
3.0%
3 103
 
2.6%
8 87
 
2.2%
Hangul
ValueCountFrequency (%)
년 363
33.3%
월 363
33.3%
일 363
33.3%

생활계구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
비배출시설계
294 
50 
배출시설계
 
19

Length

Max length6
Median length6
Mean length5.2589532
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
비배출시설계 294
81.0%
50
 
13.8%
배출시설계 19
 
5.2%

Length

2023-12-12T09:19:05.108841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:05.213933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비배출시설계 294
93.9%
배출시설계 19
 
6.1%

폐기물 종류
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
그 밖의 폐기물
135 
폐합성수지류(폐염화비닐수지류는 제외한다)
58 
폐합성수지류
24 
음식물류폐기물
21 
사업장폐기물
20 
Other values (41)
105 

Length

Max length84
Median length49
Mean length10.110193
Min length1

Unique

Unique21 ?
Unique (%)5.8%

Sample

1st row그 밖의 폐섬유
2nd row음식물류폐기물
3rd row그 밖의 폐기물
4th row폐합성수지류(폐염화비닐수지류는 제외한다)
5th row그 밖의 폐섬유

Common Values

ValueCountFrequency (%)
그 밖의 폐기물 135
37.2%
폐합성수지류(폐염화비닐수지류는 제외한다) 58
16.0%
폐합성수지류 24
 
6.6%
음식물류폐기물 21
 
5.8%
사업장폐기물 20
 
5.5%
그 밖의 폐섬유 15
 
4.1%
기타 9
 
2.5%
7
 
1.9%
폐수처리오니 7
 
1.9%
폐목재류 1등급 7
 
1.9%
Other values (36) 60
16.5%

Length

2023-12-12T09:19:05.335719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
그 158
19.8%
밖의 158
19.8%
폐기물 140
17.5%
제외한다 61
 
7.6%
폐합성수지류(폐염화비닐수지류는 58
 
7.2%
폐합성수지류 24
 
3.0%
음식물류폐기물 21
 
2.6%
사업장폐기물 20
 
2.5%
폐섬유 15
 
1.9%
폐목재류 10
 
1.2%
Other values (71) 135
16.9%

배출량(톤)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.29574
Minimum0
Maximum3233
Zeros8
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T09:19:05.453228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.8
Q120
median50.4
Q3108
95-th percentile360
Maximum3233
Range3233
Interquartile range (IQR)88

Descriptive statistics

Standard deviation236.0615
Coefficient of variation (CV)2.2001014
Kurtosis90.31149
Mean107.29574
Median Absolute Deviation (MAD)38.4
Skewness8.063784
Sum38948.352
Variance55725.032
MonotonicityNot monotonic
2023-12-12T09:19:05.837962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108.0 45
 
12.4%
20.0 31
 
8.5%
60.0 23
 
6.3%
24.0 23
 
6.3%
96.0 18
 
5.0%
12.0 18
 
5.0%
36.0 17
 
4.7%
120.0 13
 
3.6%
18.0 12
 
3.3%
54.0 9
 
2.5%
Other values (63) 154
42.4%
ValueCountFrequency (%)
0.0 8
2.2%
0.36 1
 
0.3%
1.2 4
1.1%
2.4 1
 
0.3%
3.0 1
 
0.3%
3.6 2
 
0.6%
4.8 4
1.1%
4.992 1
 
0.3%
5.0 3
 
0.8%
5.6 1
 
0.3%
ValueCountFrequency (%)
3233.0 1
 
0.3%
1200.0 5
1.4%
730.0 1
 
0.3%
702.0 2
 
0.6%
571.2 1
 
0.3%
504.0 1
 
0.3%
480.0 4
1.1%
420.0 1
 
0.3%
408.0 1
 
0.3%
384.0 1
 
0.3%

운반자
Text

Distinct68
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:06.066582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length6.677686
Min length1

Characters and Unicode

Total characters2424
Distinct characters123
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)8.5%

Sample

1st row더바른환경
2nd row유성농장
3rd row(주)유현환경
4th row(주)유현환경
5th row더바른환경
ValueCountFrequency (%)
자)광주미화 79
22.3%
주)태양환경 62
17.5%
주)만복환경 24
 
6.8%
주)세진산업 19
 
5.4%
광주미화 16
 
4.5%
신흥자원(주 13
 
3.7%
합)광주미화 10
 
2.8%
주)자연환경산업 10
 
2.8%
자연환경(유 9
 
2.5%
주)녹색환경 7
 
2.0%
Other values (59) 105
29.7%
2023-12-12T09:19:06.409807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 309
12.7%
) 298
12.3%
( 296
12.2%
경 162
 
6.7%
환 158
 
6.5%
광 122
 
5.0%
자 120
 
5.0%
미 110
 
4.5%
화 110
 
4.5%
양 64
 
2.6%
Other values (113) 675
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1815
74.9%
Close Punctuation 298
 
12.3%
Open Punctuation 296
 
12.2%
Space Separator 13
 
0.5%
Other Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 309
17.0%
경 162
 
8.9%
환 158
 
8.7%
광 122
 
6.7%
자 120
 
6.6%
미 110
 
6.1%
화 110
 
6.1%
양 64
 
3.5%
태 62
 
3.4%
산 45
 
2.5%
Other values (108) 553
30.5%
Close Punctuation
ValueCountFrequency (%)
) 298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 296
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1815
74.9%
Common 609
 
25.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 309
17.0%
경 162
 
8.9%
환 158
 
8.7%
광 122
 
6.7%
자 120
 
6.6%
미 110
 
6.1%
화 110
 
6.1%
양 64
 
3.5%
태 62
 
3.4%
산 45
 
2.5%
Other values (108) 553
30.5%
Common
ValueCountFrequency (%)
) 298
48.9%
( 296
48.6%
13
 
2.1%
& 1
 
0.2%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1815
74.9%
ASCII 609
 
25.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 309
17.0%
경 162
 
8.9%
환 158
 
8.7%
광 122
 
6.7%
자 120
 
6.6%
미 110
 
6.1%
화 110
 
6.1%
양 64
 
3.5%
태 62
 
3.4%
산 45
 
2.5%
Other values (108) 553
30.5%
ASCII
ValueCountFrequency (%)
) 298
48.9%
( 296
48.6%
13
 
2.1%
& 1
 
0.2%
- 1
 
0.2%

운반량(톤)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.70565
Minimum0
Maximum3233
Zeros10
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T09:19:06.533933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.06
Q120
median50
Q3108
95-th percentile360
Maximum3233
Range3233
Interquartile range (IQR)88

Descriptive statistics

Standard deviation236.24537
Coefficient of variation (CV)2.2139911
Kurtosis90.102925
Mean106.70565
Median Absolute Deviation (MAD)38
Skewness8.0517219
Sum38734.152
Variance55811.875
MonotonicityNot monotonic
2023-12-12T09:19:06.641176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108.0 45
 
12.4%
20.0 31
 
8.5%
24.0 23
 
6.3%
60.0 22
 
6.1%
96.0 18
 
5.0%
12.0 17
 
4.7%
36.0 17
 
4.7%
120.0 13
 
3.6%
18.0 13
 
3.6%
0.0 10
 
2.8%
Other values (66) 154
42.4%
ValueCountFrequency (%)
0.0 10
2.8%
0.36 1
 
0.3%
0.5 1
 
0.3%
1.0 1
 
0.3%
1.2 3
 
0.8%
2.0 1
 
0.3%
2.4 1
 
0.3%
3.0 1
 
0.3%
3.6 2
 
0.6%
4.8 4
 
1.1%
ValueCountFrequency (%)
3233.0 1
 
0.3%
1200.0 5
1.4%
730.0 1
 
0.3%
702.0 2
 
0.6%
571.2 1
 
0.3%
504.0 1
 
0.3%
480.0 4
1.1%
420.0 1
 
0.3%
408.0 1
 
0.3%
384.0 1
 
0.3%

처리구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
위탁
351 
 
10
자가
 
2

Length

Max length2
Median length2
Mean length1.9724518
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁 351
96.7%
10
 
2.8%
자가 2
 
0.6%

Length

2023-12-12T09:19:06.748199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:06.829045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁 351
99.4%
자가 2
 
0.6%

처리업소명
Text

Distinct95
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:06.984877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length6.8016529
Min length1

Characters and Unicode

Total characters2469
Distinct characters130
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)15.2%

Sample

1st row주식회사 이엠케이승경
2nd row유성농장
3rd row초당환경(유)
4th row남도에너지(주)
5th row(주)에코비트에너지명성
ValueCountFrequency (%)
초당환경(유 38
 
10.5%
위생매립장 32
 
8.8%
남도에너지(주 32
 
8.8%
청정빛고을(주 27
 
7.5%
주)전주에너지 22
 
6.1%
유)초당환경 14
 
3.9%
광역위생매립장 13
 
3.6%
풍산자원 12
 
3.3%
주)성주환경 12
 
3.3%
주)명성환경 9
 
2.5%
Other values (85) 151
41.7%
2023-12-12T09:19:07.281686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 234
 
9.5%
주 233
 
9.4%
( 228
 
9.2%
경 98
 
4.0%
환 96
 
3.9%
장 71
 
2.9%
에 70
 
2.8%
지 68
 
2.8%
너 63
 
2.6%
립 62
 
2.5%
Other values (120) 1246
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1984
80.4%
Close Punctuation 234
 
9.5%
Open Punctuation 228
 
9.2%
Space Separator 21
 
0.9%
Decimal Number 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 233
 
11.7%
경 98
 
4.9%
환 96
 
4.8%
장 71
 
3.6%
에 70
 
3.5%
지 68
 
3.4%
너 63
 
3.2%
립 62
 
3.1%
매 62
 
3.1%
유 60
 
3.0%
Other values (115) 1101
55.5%
Close Punctuation
ValueCountFrequency (%)
) 234
100.0%
Open Punctuation
ValueCountFrequency (%)
( 228
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1984
80.4%
Common 485
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 233
 
11.7%
경 98
 
4.9%
환 96
 
4.8%
장 71
 
3.6%
에 70
 
3.5%
지 68
 
3.4%
너 63
 
3.2%
립 62
 
3.1%
매 62
 
3.1%
유 60
 
3.0%
Other values (115) 1101
55.5%
Common
ValueCountFrequency (%)
) 234
48.2%
( 228
47.0%
21
 
4.3%
2 1
 
0.2%
- 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1984
80.4%
ASCII 485
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 234
48.2%
( 228
47.0%
21
 
4.3%
2 1
 
0.2%
- 1
 
0.2%
Hangul
ValueCountFrequency (%)
주 233
 
11.7%
경 98
 
4.9%
환 96
 
4.8%
장 71
 
3.6%
에 70
 
3.5%
지 68
 
3.4%
너 63
 
3.2%
립 62
 
3.1%
매 62
 
3.1%
유 60
 
3.0%
Other values (115) 1101
55.5%

처리방법
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
재활용(연료·고형연료제품 제조)
85 
중간처분(일반소각)
78 
매립(지방자치단체매립시설)
69 
재활용(기타)
35 
재활용(농업생산활동에 사용)
17 
Other values (18)
79 

Length

Max length19
Median length15
Mean length12.322314
Min length1

Unique

Unique4 ?
Unique (%)1.1%

Sample

1st row중간처분(일반소각)
2nd row재활용(직접 제품제조)
3rd row중간처분(일반소각)
4th row재활용(연료·고형연료제품 제조)
5th row중간처분(일반소각)

Common Values

ValueCountFrequency (%)
재활용(연료·고형연료제품 제조) 85
23.4%
중간처분(일반소각) 78
21.5%
매립(지방자치단체매립시설) 69
19.0%
재활용(기타) 35
9.6%
재활용(농업생산활동에 사용) 17
 
4.7%
재활용(중간가공폐기물 제조) 10
 
2.8%
10
 
2.8%
매립(민간관리형매립시설) 8
 
2.2%
재활용(파쇄.분쇄) 7
 
1.9%
재활용(원료가공) 6
 
1.7%
Other values (13) 38
10.5%

Length

2023-12-12T09:19:07.394657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조 100
20.7%
재활용(연료·고형연료제품 85
17.6%
중간처분(일반소각 78
16.1%
매립(지방자치단체매립시설 69
14.3%
재활용(기타 35
 
7.2%
사용 19
 
3.9%
재활용(농업생산활동에 17
 
3.5%
재활용(중간가공폐기물 10
 
2.1%
매립(민간관리형매립시설 8
 
1.7%
재활용(파쇄.분쇄 7
 
1.4%
Other values (17) 55
11.4%

처리량(톤_연)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.40813
Minimum0
Maximum3233
Zeros10
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-12T09:19:07.495395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.8
Q120
median50.4
Q3108
95-th percentile360
Maximum3233
Range3233
Interquartile range (IQR)88

Descriptive statistics

Standard deviation236.06395
Coefficient of variation (CV)2.1978219
Kurtosis90.292118
Mean107.40813
Median Absolute Deviation (MAD)38.4
Skewness8.0620564
Sum38989.152
Variance55726.188
MonotonicityNot monotonic
2023-12-12T09:19:07.604323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108.0 45
 
12.4%
20.0 31
 
8.5%
24.0 23
 
6.3%
60.0 23
 
6.3%
96.0 18
 
5.0%
12.0 18
 
5.0%
36.0 17
 
4.7%
120.0 14
 
3.9%
18.0 12
 
3.3%
0.0 10
 
2.8%
Other values (63) 152
41.9%
ValueCountFrequency (%)
0.0 10
2.8%
0.36 1
 
0.3%
1.2 3
 
0.8%
2.4 1
 
0.3%
3.0 1
 
0.3%
3.6 2
 
0.6%
4.8 4
 
1.1%
4.992 1
 
0.3%
5.0 3
 
0.8%
5.6 1
 
0.3%
ValueCountFrequency (%)
3233.0 1
 
0.3%
1200.0 5
1.4%
730.0 1
 
0.3%
702.0 2
 
0.6%
571.2 1
 
0.3%
504.0 1
 
0.3%
480.0 4
1.1%
420.0 1
 
0.3%
408.0 1
 
0.3%
384.0 1
 
0.3%

사업장도로명주소
Text

Distinct80
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:07.825636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length41
Mean length21.300275
Min length1

Characters and Unicode

Total characters7732
Distinct characters134
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)6.6%

Sample

1st row광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)
2nd row광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)
3rd row광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)
4th row광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)
5th row광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)
ValueCountFrequency (%)
광주광역시 303
18.7%
동구 301
18.6%
계림동 64
 
3.9%
서석동 50
 
3.1%
학동 47
 
2.9%
필문대로 45
 
2.8%
남문로 31
 
1.9%
중앙로 30
 
1.9%
제봉로 28
 
1.7%
무등로 26
 
1.6%
Other values (146) 696
42.9%
2023-12-12T09:19:08.152286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1430
18.5%
광 623
 
8.1%
동 596
 
7.7%
로 336
 
4.3%
구 325
 
4.2%
( 309
 
4.0%
) 309
 
4.0%
주 309
 
4.0%
시 305
 
3.9%
역 303
 
3.9%
Other values (124) 2887
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4533
58.6%
Space Separator 1430
 
18.5%
Decimal Number 1032
 
13.3%
Open Punctuation 309
 
4.0%
Close Punctuation 309
 
4.0%
Connector Punctuation 67
 
0.9%
Dash Punctuation 43
 
0.6%
Math Symbol 5
 
0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 623
13.7%
동 596
13.1%
로 336
 
7.4%
구 325
 
7.2%
주 309
 
6.8%
시 305
 
6.7%
역 303
 
6.7%
문 93
 
2.1%
대 90
 
2.0%
계 76
 
1.7%
Other values (104) 1477
32.6%
Decimal Number
ValueCountFrequency (%)
3 184
17.8%
2 173
16.8%
1 142
13.8%
0 97
9.4%
6 85
8.2%
8 80
7.8%
4 75
7.3%
9 69
 
6.7%
7 68
 
6.6%
5 59
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
1430
100.0%
Open Punctuation
ValueCountFrequency (%)
( 309
100.0%
Close Punctuation
ValueCountFrequency (%)
) 309
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4533
58.6%
Common 3195
41.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 623
13.7%
동 596
13.1%
로 336
 
7.4%
구 325
 
7.2%
주 309
 
6.8%
시 305
 
6.7%
역 303
 
6.7%
문 93
 
2.1%
대 90
 
2.0%
계 76
 
1.7%
Other values (104) 1477
32.6%
Common
ValueCountFrequency (%)
1430
44.8%
( 309
 
9.7%
) 309
 
9.7%
3 184
 
5.8%
2 173
 
5.4%
1 142
 
4.4%
0 97
 
3.0%
6 85
 
2.7%
8 80
 
2.5%
4 75
 
2.3%
Other values (6) 311
 
9.7%
Latin
ValueCountFrequency (%)
s 1
25.0%
C 1
25.0%
N 1
25.0%
k 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4533
58.6%
ASCII 3199
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1430
44.7%
( 309
 
9.7%
) 309
 
9.7%
3 184
 
5.8%
2 173
 
5.4%
1 142
 
4.4%
0 97
 
3.0%
6 85
 
2.7%
8 80
 
2.5%
4 75
 
2.3%
Other values (10) 315
 
9.8%
Hangul
ValueCountFrequency (%)
광 623
13.7%
동 596
13.1%
로 336
 
7.4%
구 325
 
7.2%
주 309
 
6.8%
시 305
 
6.7%
역 303
 
6.7%
문 93
 
2.1%
대 90
 
2.0%
계 76
 
1.7%
Other values (104) 1477
32.6%

사업장지번주소
Text

Distinct82
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T09:19:08.340458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length31
Mean length18.608815
Min length1

Characters and Unicode

Total characters6755
Distinct characters114
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

Unique24 ?
Unique (%)6.6%

Sample

1st row광주광역시 동구 동명동 20-4
2nd row광주광역시 동구 동명동 20-4
3rd row광주광역시 동구 동명동 20-4
4th row광주광역시 동구 동명동 20-4
5th row광주광역시 동구 동명동 20-4
ValueCountFrequency (%)
광주광역시 341
23.1%
동구 339
23.0%
계림동 64
 
4.3%
학동 58
 
3.9%
서석동 54
 
3.7%
산 30
 
2.0%
소태동 27
 
1.8%
505-900 25
 
1.7%
대인동 23
 
1.6%
광산동 20
 
1.4%
Other values (123) 495
33.5%
2023-12-12T09:19:08.650844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1494
22.1%
광 708
 
10.5%
동 658
 
9.7%
시 350
 
5.2%
주 347
 
5.1%
구 346
 
5.1%
역 341
 
5.0%
- 222
 
3.3%
1 194
 
2.9%
0 194
 
2.9%
Other values (104) 1901
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3835
56.8%
Space Separator 1494
 
22.1%
Decimal Number 1198
 
17.7%
Dash Punctuation 222
 
3.3%
Connector Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 708
18.5%
동 658
17.2%
시 350
9.1%
주 347
9.0%
구 346
9.0%
역 341
8.9%
산 80
 
2.1%
학 79
 
2.1%
림 71
 
1.9%
계 70
 
1.8%
Other values (87) 785
20.5%
Decimal Number
ValueCountFrequency (%)
1 194
16.2%
0 194
16.2%
2 165
13.8%
8 140
11.7%
5 120
10.0%
3 117
9.8%
4 81
6.8%
7 65
 
5.4%
9 64
 
5.3%
6 58
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
N 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
1494
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3835
56.8%
Common 2916
43.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 708
18.5%
동 658
17.2%
시 350
9.1%
주 347
9.0%
구 346
9.0%
역 341
8.9%
산 80
 
2.1%
학 79
 
2.1%
림 71
 
1.9%
계 70
 
1.8%
Other values (87) 785
20.5%
Common
ValueCountFrequency (%)
1494
51.2%
- 222
 
7.6%
1 194
 
6.7%
0 194
 
6.7%
2 165
 
5.7%
8 140
 
4.8%
5 120
 
4.1%
3 117
 
4.0%
4 81
 
2.8%
7 65
 
2.2%
Other values (3) 124
 
4.3%
Latin
ValueCountFrequency (%)
C 1
25.0%
k 1
25.0%
s 1
25.0%
N 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3835
56.8%
ASCII 2920
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1494
51.2%
- 222
 
7.6%
1 194
 
6.6%
0 194
 
6.6%
2 165
 
5.7%
8 140
 
4.8%
5 120
 
4.1%
3 117
 
4.0%
4 81
 
2.8%
7 65
 
2.2%
Other values (7) 128
 
4.4%
Hangul
ValueCountFrequency (%)
광 708
18.5%
동 658
17.2%
시 350
9.1%
주 347
9.0%
구 346
9.0%
역 341
8.9%
산 80
 
2.1%
학 79
 
2.1%
림 71
 
1.9%
계 70
 
1.8%
Other values (87) 785
20.5%

업무구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
사업장폐기물배출자(2호)
363 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장폐기물배출자(2호)
2nd row사업장폐기물배출자(2호)
3rd row사업장폐기물배출자(2호)
4th row사업장폐기물배출자(2호)
5th row사업장폐기물배출자(2호)

Common Values

ValueCountFrequency (%)
사업장폐기물배출자(2호) 363
100.0%

Length

2023-12-12T09:19:08.754099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:08.850734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장폐기물배출자(2호 363
100.0%

폐기물자가처리방법
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
재활용(연료·고형연료제품 제조)
85 
중간처분(일반소각)
78 
매립(지방자치단체매립시설)
69 
재활용(기타)
35 
재활용(농업생산활동에 사용)
17 
Other values (18)
79 

Length

Max length19
Median length15
Mean length12.322314
Min length1

Unique

Unique4 ?
Unique (%)1.1%

Sample

1st row중간처분(일반소각)
2nd row재활용(직접 제품제조)
3rd row중간처분(일반소각)
4th row재활용(연료·고형연료제품 제조)
5th row중간처분(일반소각)

Common Values

ValueCountFrequency (%)
재활용(연료·고형연료제품 제조) 85
23.4%
중간처분(일반소각) 78
21.5%
매립(지방자치단체매립시설) 69
19.0%
재활용(기타) 35
9.6%
재활용(농업생산활동에 사용) 17
 
4.7%
재활용(중간가공폐기물 제조) 10
 
2.8%
10
 
2.8%
매립(민간관리형매립시설) 8
 
2.2%
재활용(파쇄.분쇄) 7
 
1.9%
재활용(원료가공) 6
 
1.7%
Other values (13) 38
10.5%

Length

2023-12-12T09:19:08.964592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조 100
20.7%
재활용(연료·고형연료제품 85
17.6%
중간처분(일반소각 78
16.1%
매립(지방자치단체매립시설 69
14.3%
재활용(기타 35
 
7.2%
사용 19
 
3.9%
재활용(농업생산활동에 17
 
3.5%
재활용(중간가공폐기물 10
 
2.1%
매립(민간관리형매립시설 8
 
1.7%
재활용(파쇄.분쇄 7
 
1.4%
Other values (17) 55
11.4%

비고
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
248 
<NA>
82 
전화번호 존재하지않음
33 

Length

Max length12
Median length1
Mean length2.677686
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 (%)
248
68.3%
<NA> 82
 
22.6%
전화번호 존재하지않음 33
 
9.1%

Length

2023-12-12T09:19:09.075918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:09.163250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 82
55.4%
전화번호 33
22.3%
존재하지않음 33
22.3%

데이터 기준 일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-08-23
363 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-23
2nd row2023-08-23
3rd row2023-08-23
4th row2023-08-23
5th row2023-08-23

Common Values

ValueCountFrequency (%)
2023-08-23 363
100.0%

Length

2023-12-12T09:19:09.260613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:19:09.352467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-23 363
100.0%

Interactions

2023-12-12T09:19:02.808018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.202759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.459992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.900710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.286478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.554220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.997346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.371409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:19:02.667444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:19:09.430738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호전화번호신고일생활계구분폐기물 종류배출량(톤)운반자운반량(톤)처리구분처리업소명처리방법처리량(톤_연)사업장도로명주소사업장지번주소폐기물자가처리방법비고
상호1.0001.0001.0000.9660.9610.8640.9830.8640.9420.9750.9580.8641.0001.0000.9581.000
전화번호1.0001.0000.9990.9630.9510.8650.9840.8650.8450.9550.9540.8650.9991.0000.9541.000
신고일1.0000.9991.0000.9820.9710.6760.9880.6760.9490.9840.9590.6760.9991.0000.9590.985
생활계구분0.9660.9630.9821.0000.9150.2010.8920.2010.6230.9110.8100.2010.8400.9410.8100.243
폐기물 종류0.9610.9510.9710.9151.0000.6600.9840.6600.9180.9850.9770.6600.8980.9620.9770.545
배출량(톤)0.8640.8650.6760.2010.6601.0000.5711.0000.0000.0000.7341.0000.8620.8830.7340.000
운반자0.9830.9840.9880.8920.9840.5711.0000.5710.9500.9960.9560.5710.9710.9810.9560.610
운반량(톤)0.8640.8650.6760.2010.6601.0000.5711.0000.0000.0000.7341.0000.8620.8830.7340.000
처리구분0.9420.8450.9490.6230.9180.0000.9500.0001.0000.9450.9490.0000.8410.8990.9490.243
처리업소명0.9750.9550.9840.9110.9850.0000.9960.0000.9451.0000.9820.0000.8820.9540.9820.656
처리방법0.9580.9540.9590.8100.9770.7340.9560.7340.9490.9821.0000.7340.8800.9341.0000.458
처리량(톤_연)0.8640.8650.6760.2010.6601.0000.5711.0000.0000.0000.7341.0000.8620.8830.7340.000
사업장도로명주소1.0000.9990.9990.8400.8980.8620.9710.8620.8410.8820.8800.8621.0000.9990.8800.884
사업장지번주소1.0001.0001.0000.9410.9620.8830.9810.8830.8990.9540.9340.8830.9991.0000.9340.993
폐기물자가처리방법0.9580.9540.9590.8100.9770.7340.9560.7340.9490.9821.0000.7340.8800.9341.0000.458
비고1.0001.0000.9850.2430.5450.0000.6100.0000.2430.6560.4580.0000.8840.9930.4581.000
2023-12-12T09:19:09.557684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물자가처리방법비고생활계구분처리구분폐기물 종류처리방법
폐기물자가처리방법1.0000.3890.6040.8410.6101.000
비고0.3891.0000.3950.3950.4320.389
생활계구분0.6040.3951.0000.2900.7070.604
처리구분0.8410.3950.2901.0000.7130.841
폐기물 종류0.6100.4320.7070.7131.0000.610
처리방법1.0000.3890.6040.8410.6101.000
2023-12-12T09:19:09.641261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출량(톤)운반량(톤)처리량(톤_연)생활계구분폐기물 종류처리구분처리방법폐기물자가처리방법비고
배출량(톤)1.0000.9750.9740.1540.3500.0000.4590.4590.000
운반량(톤)0.9751.0000.9880.1540.3500.0000.4590.4590.000
처리량(톤_연)0.9740.9881.0000.1540.3500.0000.4590.4590.000
생활계구분0.1540.1540.1541.0000.7070.2900.6040.6040.395
폐기물 종류0.3500.3500.3500.7071.0000.7130.6100.6100.432
처리구분0.0000.0000.0000.2900.7131.0000.8410.8410.395
처리방법0.4590.4590.4590.6040.6100.8411.0001.0000.389
폐기물자가처리방법0.4590.4590.4590.6040.6100.8411.0001.0000.389
비고0.0000.0000.0000.3950.4320.3950.3890.3891.000

Missing values

2023-12-12T09:19:03.144081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:19:03.357382image/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

상호전화번호신고일생활계구분폐기물 종류배출량(톤)운반자운반량(톤)처리구분처리업소명처리방법처리량(톤_연)사업장도로명주소사업장지번주소업무구분폐기물자가처리방법비고데이터 기준 일자
0동명병원062-670-33332022 년11 월14 일비배출시설계그 밖의 폐섬유120.0더바른환경120.0위탁주식회사 이엠케이승경중간처분(일반소각)120.0광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)광주광역시 동구 동명동 20-4사업장폐기물배출자(2호)중간처분(일반소각)<NA>2023-08-23
1동명병원062-670-33332022 년11 월14 일비배출시설계음식물류폐기물60.0유성농장60.0위탁유성농장재활용(직접 제품제조)60.0광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)광주광역시 동구 동명동 20-4사업장폐기물배출자(2호)재활용(직접 제품제조)<NA>2023-08-23
2동명병원062-670-33332022 년11 월14 일비배출시설계그 밖의 폐기물12.0(주)유현환경12.0위탁초당환경(유)중간처분(일반소각)12.0광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)광주광역시 동구 동명동 20-4사업장폐기물배출자(2호)중간처분(일반소각)<NA>2023-08-23
3동명병원062-670-33332022 년11 월14 일비배출시설계폐합성수지류(폐염화비닐수지류는 제외한다)24.0(주)유현환경24.0위탁남도에너지(주)재활용(연료·고형연료제품 제조)24.0광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)광주광역시 동구 동명동 20-4사업장폐기물배출자(2호)재활용(연료·고형연료제품 제조)<NA>2023-08-23
4동명병원062-670-33332022 년11 월14 일비배출시설계그 밖의 폐섬유120.0더바른환경120.0위탁(주)에코비트에너지명성중간처분(일반소각)120.0광주광역시 동구 동명로70번길 5 (1층 일부제외_ 2층 제외) 지하2~지상10층 (동명동)광주광역시 동구 동명동 20-4사업장폐기물배출자(2호)중간처분(일반소각)<NA>2023-08-23
5광주광역시 동구청062-608-25122020 년09 월10 일그 밖의 폐타이어22.0광주타이어22.0위탁(주)고려시멘트재활용(직접 제품제조)22.0광주광역시 동구 서남로 1 (서석동)광주광역시 동구 서석동 31사업장폐기물배출자(2호)재활용(직접 제품제조)2023-08-23
6광주광역시 동구청062-608-25042020 년08 월10 일비배출시설계그 밖의 생활폐기물100.0(자)광주미화100.0위탁광주광역시 위생매립장매립(지방자치단체매립시설)100.0광주광역시 동구 서남로 1_ 동구청 (서석동)광주광역시 동구 서석동 31 동구청사업장폐기물배출자(2호)매립(지방자치단체매립시설)2023-08-23
7광주광역시 동구청062-608-25042020 년08 월10 일비배출시설계그 밖의 생활폐기물100.0무경지앤씨(주)100.0위탁광주광역시 위생매립장매립(지방자치단체매립시설)100.0광주광역시 동구 서남로 1_ 동구청 (서석동)광주광역시 동구 서석동 31 동구청사업장폐기물배출자(2호)매립(지방자치단체매립시설)2023-08-23
8광주광역시 동구청062-608-25042020 년08 월10 일비배출시설계종량제봉투 배출 폐기물(합성수지 종량제 봉투에 배출되는 폐기물을 말한다)100.0무경지앤씨(주)100.0위탁광주광역시 위생매립장매립(지방자치단체매립시설)100.0광주광역시 동구 서남로 1_ 동구청 (서석동)광주광역시 동구 서석동 31 동구청사업장폐기물배출자(2호)매립(지방자치단체매립시설)2023-08-23
9광주광역시 동구청062-608-25042020 년08 월10 일비배출시설계종량제봉투 배출 폐기물(합성수지 종량제 봉투에 배출되는 폐기물을 말한다)100.0(자)광주미화100.0위탁광주광역시 위생매립장매립(지방자치단체매립시설)100.0광주광역시 동구 서남로 1_ 동구청 (서석동)광주광역시 동구 서석동 31 동구청사업장폐기물배출자(2호)매립(지방자치단체매립시설)2023-08-23
상호전화번호신고일생활계구분폐기물 종류배출량(톤)운반자운반량(톤)처리구분처리업소명처리방법처리량(톤_연)사업장도로명주소사업장지번주소업무구분폐기물자가처리방법비고데이터 기준 일자
353조선대학교062-230-62161996 년04 월22 일비배출시설계폐지54.0(합)광주미화54.0위탁푸른자원재활용(기타)54.0광주광역시 동구 필문대로 309 (서석동)광주광역시 동구 서석동 375사업장폐기물배출자(2호)재활용(기타)<NA>2023-08-23
354조선대학교062-230-62161996 년04 월22 일비배출시설계기타1200.0(합)광주미화1200.0위탁동구위생매립장매립(지방자치단체매립시설)1200.0광주광역시 동구 필문대로 309 (서석동)광주광역시 동구 서석동 375사업장폐기물배출자(2호)매립(지방자치단체매립시설)<NA>2023-08-23
355조선대학교062-230-62161996 년04 월22 일비배출시설계기타60.0(합)광주미화60.0위탁명성환경중간처분(일반소각)60.0광주광역시 동구 필문대로 309 (서석동)광주광역시 동구 서석동 375사업장폐기물배출자(2호)중간처분(일반소각)<NA>2023-08-23
356조선대학교062-230-62161996 년04 월22 일비배출시설계기타18.0(합)광주미화18.0위탁푸른자원재활용(기타)18.0광주광역시 동구 필문대로 309 (서석동)광주광역시 동구 서석동 375사업장폐기물배출자(2호)재활용(기타)<NA>2023-08-23
357(주)농협파트너스02-560-91001996 년04 월22 일비배출시설계폐합성수지류(폐염화비닐수지류는 제외한다)108.0(자)광주미화108.0위탁남도에너지(주)재활용(연료·고형연료제품 제조)108.0광주광역시 동구 금남로 148 (금남로5가)광주광역시 동구 금남로5가 55-1사업장폐기물배출자(2호)재활용(연료·고형연료제품 제조)<NA>2023-08-23
358학문외과062-225-33221996 년04 월22 일비배출시설계그 밖의 폐기물108.0(자)광주미화108.0위탁위생매립장매립(지방자치단체매립시설)108.0광주광역시 동구 남문로 780 (학동)광주광역시 동구 학동 26-12사업장폐기물배출자(2호)매립(지방자치단체매립시설)<NA>2023-08-23
359학문외과062-225-33221996 년04 월22 일비배출시설계그 밖의 폐기물108.0(자)광주미화108.0위탁청정빛고을(주)재활용(연료·고형연료제품 제조)108.0광주광역시 동구 남문로 780 (학동)광주광역시 동구 학동 26-12사업장폐기물배출자(2호)재활용(연료·고형연료제품 제조)<NA>2023-08-23
360학문외과062-225-33221996 년04 월22 일비배출시설계그 밖의 폐기물108.0(자)광주미화108.0위탁초당환경(유)중간처분(일반소각)108.0광주광역시 동구 남문로 780 (학동)광주광역시 동구 학동 26-12사업장폐기물배출자(2호)중간처분(일반소각)<NA>2023-08-23
361학문외과062-225-33221996 년04 월22 일비배출시설계폐합성수지류(폐염화비닐수지류는 제외한다)108.0(자)광주미화108.0위탁남도에너지(주)재활용(연료·고형연료제품 제조)108.0광주광역시 동구 남문로 780 (학동)광주광역시 동구 학동 26-12사업장폐기물배출자(2호)재활용(연료·고형연료제품 제조)<NA>2023-08-23
362신용보증기금062-607-91002000 년11 월25 일0.00.00.0광주광역시 동구 제봉로 218 (대인동)광주광역시 동구 대인동 324-5사업장폐기물배출자(2호)<NA>2023-08-23

Duplicate rows

Most frequently occurring

상호전화번호신고일생활계구분폐기물 종류배출량(톤)운반자운반량(톤)처리구분처리업소명처리방법처리량(톤_연)사업장도로명주소사업장지번주소업무구분폐기물자가처리방법비고데이터 기준 일자# duplicates
0삼성테스코(주)홈플러스(계림점)062-511-02782007 년12 월27 일사업장폐기물60.0(주)세진산업60.0위탁거성피엔씨재활용(원료가공)60.0광주광역시 동구 무등로 314 (계림동)광주광역시 동구 계림동 505-900사업장폐기물배출자(2호)재활용(원료가공)2023-08-232