Overview

Dataset statistics

Number of variables9
Number of observations393
Missing cells180
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.9 KiB
Average record size in memory75.3 B

Variable types

Numeric1
Categorical5
Text3

Dataset

Description2020년 이후 우리구에 신고된 사업장일반폐기물, 지정폐기물의 배출자 신고현황 중 상호명, 폐기물종류, 처리방법, 사업장도로명주소, 신고기준년도, 데이터기준일자
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15081023/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
폐기물구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
폐기물 종류 is highly overall correlated with 폐기물구분 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 폐기물구분 and 1 other fieldsHigh correlation
처리방법 is highly overall correlated with 폐기물구분 and 1 other fieldsHigh correlation
신고기준년도 is highly overall correlated with 연번High correlation
폐기물구분 is highly imbalanced (69.0%)Imbalance
전화번호 has 177 (45.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 09:24:37.776019
Analysis finished2023-12-12 09:24:38.931208
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct392
Distinct (%)100.0%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean196.5
Minimum1
Maximum392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-12T18:24:39.012546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.55
Q198.75
median196.5
Q3294.25
95-th percentile372.45
Maximum392
Range391
Interquartile range (IQR)195.5

Descriptive statistics

Standard deviation113.3049
Coefficient of variation (CV)0.57661526
Kurtosis-1.2
Mean196.5
Median Absolute Deviation (MAD)98
Skewness0
Sum77028
Variance12838
MonotonicityStrictly increasing
2023-12-12T18:24:39.168614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
271 1
 
0.3%
269 1
 
0.3%
268 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
Other values (382) 382
97.2%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
392 1
0.3%
391 1
0.3%
390 1
0.3%
389 1
0.3%
388 1
0.3%
387 1
0.3%
386 1
0.3%
385 1
0.3%
384 1
0.3%
383 1
0.3%

폐기물구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
지정폐기물
353 
사업장폐기물
39 
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0966921
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
지정폐기물 353
89.8%
사업장폐기물 39
 
9.9%
<NA> 1
 
0.3%

Length

2023-12-12T18:24:39.344890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:39.531240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정폐기물 353
89.8%
사업장폐기물 39
 
9.9%
na 1
 
0.3%

상호
Text

Distinct115
Distinct (%)29.3%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2023-12-12T18:24:39.792042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length7.5586735
Min length2

Characters and Unicode

Total characters2963
Distinct characters209
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

Unique50 ?
Unique (%)12.8%

Sample

1st row개인
2nd row개인
3rd row서울특별시 동부병원
4th row(주)보명토건
5th row(주)보명토건
ValueCountFrequency (%)
개인 110
25.4%
주식회사 27
 
6.2%
동대문구청 22
 
5.1%
이문1재정비촉진구역주택재개발정비사업조합 21
 
4.8%
경희대학교 17
 
3.9%
한국고분자시험연구소(주 10
 
2.3%
서울시립대학교 8
 
1.8%
주)동서개발 8
 
1.8%
더랜드영 6
 
1.4%
경희의료원 5
 
1.2%
Other values (110) 199
46.0%
2023-12-12T18:24:40.619186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
개 154
 
5.2%
주 144
 
4.9%
인 114
 
3.8%
사 82
 
2.8%
( 82
 
2.8%
) 82
 
2.8%
교 75
 
2.5%
대 71
 
2.4%
구 69
 
2.3%
재 61
 
2.1%
Other values (199) 2029
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2724
91.9%
Open Punctuation 82
 
2.8%
Close Punctuation 82
 
2.8%
Space Separator 41
 
1.4%
Decimal Number 33
 
1.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 154
 
5.7%
주 144
 
5.3%
인 114
 
4.2%
사 82
 
3.0%
교 75
 
2.8%
대 71
 
2.6%
구 69
 
2.5%
재 61
 
2.2%
정 61
 
2.2%
비 60
 
2.2%
Other values (191) 1833
67.3%
Decimal Number
ValueCountFrequency (%)
1 25
75.8%
3 3
 
9.1%
4 3
 
9.1%
7 2
 
6.1%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2724
91.9%
Common 238
 
8.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 154
 
5.7%
주 144
 
5.3%
인 114
 
4.2%
사 82
 
3.0%
교 75
 
2.8%
대 71
 
2.6%
구 69
 
2.5%
재 61
 
2.2%
정 61
 
2.2%
비 60
 
2.2%
Other values (191) 1833
67.3%
Common
ValueCountFrequency (%)
( 82
34.5%
) 82
34.5%
41
17.2%
1 25
 
10.5%
3 3
 
1.3%
4 3
 
1.3%
7 2
 
0.8%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2724
91.9%
ASCII 239
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
개 154
 
5.7%
주 144
 
5.3%
인 114
 
4.2%
사 82
 
3.0%
교 75
 
2.8%
대 71
 
2.6%
구 69
 
2.5%
재 61
 
2.2%
정 61
 
2.2%
비 60
 
2.2%
Other values (191) 1833
67.3%
ASCII
ValueCountFrequency (%)
( 82
34.3%
) 82
34.3%
41
17.2%
1 25
 
10.5%
3 3
 
1.3%
4 3
 
1.3%
7 2
 
0.8%
B 1
 
0.4%

전화번호
Text

MISSING 

Distinct87
Distinct (%)40.3%
Missing177
Missing (%)45.0%
Memory size3.2 KiB
2023-12-12T18:24:40.926148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.467593
Min length1

Characters and Unicode

Total characters2261
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

Unique38 ?
Unique (%)17.6%

Sample

1st row02-920-9113
2nd row02-961-2726
3rd row02-961-2726
4th row02-2245-7223
5th row02-2245-7223
ValueCountFrequency (%)
02-960-2788 24
 
12.4%
02-961-0040 10
 
5.2%
02-963-2586 10
 
5.2%
02-958-3232 5
 
2.6%
02-2127-5000 4
 
2.1%
02-6110-5379 4
 
2.1%
031-944-0105 4
 
2.1%
02-2250-8888 3
 
1.5%
02-2127-4717 3
 
1.5%
02-700-2441 3
 
1.5%
Other values (76) 124
63.9%
2023-12-12T18:24:41.399817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 393
17.4%
- 388
17.2%
0 357
15.8%
4 160
7.1%
1 159
7.0%
8 149
 
6.6%
7 145
 
6.4%
9 141
 
6.2%
6 141
 
6.2%
3 109
 
4.8%
Other values (2) 119
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1851
81.9%
Dash Punctuation 388
 
17.2%
Space Separator 22
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 393
21.2%
0 357
19.3%
4 160
8.6%
1 159
8.6%
8 149
 
8.0%
7 145
 
7.8%
9 141
 
7.6%
6 141
 
7.6%
3 109
 
5.9%
5 97
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 388
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2261
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 393
17.4%
- 388
17.2%
0 357
15.8%
4 160
7.1%
1 159
7.0%
8 149
 
6.6%
7 145
 
6.4%
9 141
 
6.2%
6 141
 
6.2%
3 109
 
4.8%
Other values (2) 119
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 393
17.4%
- 388
17.2%
0 357
15.8%
4 160
7.1%
1 159
7.0%
8 149
 
6.6%
7 145
 
6.4%
9 141
 
6.2%
6 141
 
6.2%
3 109
 
4.8%
Other values (2) 119
 
5.3%

폐기물 종류
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등
140 
흩날릴 우려가 없는 폐석면
140 
흩날릴 우려가 있는 폐석면
29 
폐절연유(폴리클로리네이티드비페닐 함유 폐기물을 제외한다)
27 
임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)
25 
Other values (14)
32 

Length

Max length66
Median length49
Mean length25.966921
Min length3

Unique

Unique7 ?
Unique (%)1.8%

Sample

1st row석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등
2nd row흩날릴 우려가 없는 폐석면
3rd row폐황산이 포함된 2차폐축전지
4th row석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등
5th row흩날릴 우려가 없는 폐석면

Common Values

ValueCountFrequency (%)
석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등 140
35.6%
흩날릴 우려가 없는 폐석면 140
35.6%
흩날릴 우려가 있는 폐석면 29
 
7.4%
폐절연유(폴리클로리네이티드비페닐 함유 폐기물을 제외한다) 27
 
6.9%
임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다) 25
 
6.4%
폐합성수지류(폐염화비닐수지류는 제외한다) 6
 
1.5%
하수준설토 4
 
1.0%
그 밖의 폐유기용제 4
 
1.0%
폐황산이 포함된 2차폐축전지 4
 
1.0%
연구ㆍ검사용 폐시약 3
 
0.8%
Other values (9) 11
 
2.8%

Length

2023-12-12T18:24:41.609757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
흩날릴 169
 
8.7%
우려가 169
 
8.7%
폐석면 169
 
8.7%
석면의 140
 
7.2%
사용된 140
 
7.2%
모든 140
 
7.2%
비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 140
 
7.2%
등 140
 
7.2%
없는 140
 
7.2%
제거작업에 140
 
7.2%
Other values (42) 463
23.7%

처리방법
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
매립(민간관리형매립시설)
232 
중간처분(고형화)
77 
재활용(중간가공폐기물 제조)
39 
재활용(직접 제품제조)
 
18
재활용(원료 제조)
 
8
Other values (7)
 
19

Length

Max length19
Median length13
Mean length12.236641
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row매립(민간관리형매립시설)
2nd row매립(민간관리형매립시설)
3rd row재활용(중간가공폐기물 제조)
4th row매립(민간관리형매립시설)
5th row매립(민간관리형매립시설)

Common Values

ValueCountFrequency (%)
매립(민간관리형매립시설) 232
59.0%
중간처분(고형화) 77
 
19.6%
재활용(중간가공폐기물 제조) 39
 
9.9%
재활용(직접 제품제조) 18
 
4.6%
재활용(원료 제조) 8
 
2.0%
중간처분(고온소각) 5
 
1.3%
중간처분(일반소각) 4
 
1.0%
재활용(연료·고형연료제품 제조) 4
 
1.0%
중간처분(중화) 2
 
0.5%
중간처분(파쇄.분쇄) 2
 
0.5%
Other values (2) 2
 
0.5%

Length

2023-12-12T18:24:41.758523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
매립(민간관리형매립시설 232
50.0%
중간처분(고형화 77
 
16.6%
제조 51
 
11.0%
재활용(중간가공폐기물 39
 
8.4%
재활용(직접 18
 
3.9%
제품제조 18
 
3.9%
재활용(원료 8
 
1.7%
중간처분(고온소각 5
 
1.1%
중간처분(일반소각 4
 
0.9%
재활용(연료·고형연료제품 4
 
0.9%
Other values (6) 8
 
1.7%

사업장도로명주소
Text

Distinct182
Distinct (%)46.4%
Missing1
Missing (%)0.3%
Memory size3.2 KiB
2023-12-12T18:24:42.018421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length29.994898
Min length1

Characters and Unicode

Total characters11758
Distinct characters196
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

Unique51 ?
Unique (%)13.0%

Sample

1st row서울특별시 동대문구 무학로49길 18 (용두동)
2nd row서울특별시 동대문구 무학로49길 18 (용두동)
3rd row서울특별시 동대문구 무학로 124 (용두동)
4th row
5th row
ValueCountFrequency (%)
서울특별시 383
 
17.2%
동대문구 377
 
16.9%
장안동 79
 
3.5%
전농동 51
 
2.3%
외 49
 
2.2%
제기동 41
 
1.8%
이문동 39
 
1.8%
휘경동 34
 
1.5%
회기동 33
 
1.5%
답십리동 33
 
1.5%
Other values (359) 1109
49.8%
2023-12-12T18:24:42.458491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1846
 
15.7%
동 808
 
6.9%
대 500
 
4.3%
문 466
 
4.0%
서 427
 
3.6%
시 426
 
3.6%
울 421
 
3.6%
구 396
 
3.4%
로 392
 
3.3%
( 391
 
3.3%
Other values (186) 5685
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7374
62.7%
Space Separator 1846
 
15.7%
Decimal Number 1445
 
12.3%
Open Punctuation 391
 
3.3%
Close Punctuation 391
 
3.3%
Connector Punctuation 225
 
1.9%
Dash Punctuation 81
 
0.7%
Other Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 808
 
11.0%
대 500
 
6.8%
문 466
 
6.3%
서 427
 
5.8%
시 426
 
5.8%
울 421
 
5.7%
구 396
 
5.4%
로 392
 
5.3%
별 385
 
5.2%
특 383
 
5.2%
Other values (168) 2770
37.6%
Decimal Number
ValueCountFrequency (%)
1 312
21.6%
2 209
14.5%
3 193
13.4%
6 137
9.5%
4 116
 
8.0%
5 113
 
7.8%
9 106
 
7.3%
8 92
 
6.4%
7 88
 
6.1%
0 79
 
5.5%
Space Separator
ValueCountFrequency (%)
1846
100.0%
Open Punctuation
ValueCountFrequency (%)
( 391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 391
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7374
62.7%
Common 4383
37.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 808
 
11.0%
대 500
 
6.8%
문 466
 
6.3%
서 427
 
5.8%
시 426
 
5.8%
울 421
 
5.7%
구 396
 
5.4%
로 392
 
5.3%
별 385
 
5.2%
특 383
 
5.2%
Other values (168) 2770
37.6%
Common
ValueCountFrequency (%)
1846
42.1%
( 391
 
8.9%
) 391
 
8.9%
1 312
 
7.1%
_ 225
 
5.1%
2 209
 
4.8%
3 193
 
4.4%
6 137
 
3.1%
4 116
 
2.6%
5 113
 
2.6%
Other values (7) 450
 
10.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7374
62.7%
ASCII 4384
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1846
42.1%
( 391
 
8.9%
) 391
 
8.9%
1 312
 
7.1%
_ 225
 
5.1%
2 209
 
4.8%
3 193
 
4.4%
6 137
 
3.1%
4 116
 
2.6%
5 113
 
2.6%
Other values (8) 451
 
10.3%
Hangul
ValueCountFrequency (%)
동 808
 
11.0%
대 500
 
6.8%
문 466
 
6.3%
서 427
 
5.8%
시 426
 
5.8%
울 421
 
5.7%
구 396
 
5.4%
로 392
 
5.3%
별 385
 
5.2%
특 383
 
5.2%
Other values (168) 2770
37.6%

신고기준년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2020
305 
2021
88 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2020 305
77.6%
2021 88
 
22.4%

Length

2023-12-12T18:24:42.644867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:42.772541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 305
77.6%
2021 88
 
22.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
20210501
393 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210501
2nd row20210501
3rd row20210501
4th row20210501
5th row20210501

Common Values

ValueCountFrequency (%)
20210501 393
100.0%

Length

2023-12-12T18:24:42.893960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:24:43.017083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210501 393
100.0%

Interactions

2023-12-12T18:24:38.336151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:24:43.094276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번폐기물구분전화번호폐기물 종류처리방법신고기준년도
연번1.0001.0000.9620.6620.5850.996
폐기물구분1.0001.0000.9451.0000.8220.000
전화번호0.9620.9451.0000.9190.9560.959
폐기물 종류0.6621.0000.9191.0000.9520.312
처리방법0.5850.8220.9560.9521.0000.314
신고기준년도0.9960.0000.9590.3120.3141.000
2023-12-12T18:24:43.203263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물구분신고기준년도처리방법폐기물 종류
폐기물구분1.0000.0000.8090.979
신고기준년도0.0001.0000.2970.241
처리방법0.8090.2971.0000.766
폐기물 종류0.9790.2410.7661.000
2023-12-12T18:24:43.305529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번폐기물구분폐기물 종류처리방법신고기준년도
연번1.0000.9760.3210.2950.931
폐기물구분0.9761.0000.9790.8090.000
폐기물 종류0.3210.9791.0000.7660.241
처리방법0.2950.8090.7661.0000.297
신고기준년도0.9310.0000.2410.2971.000

Missing values

2023-12-12T18:24:38.493027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:24:38.655981image/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.
2023-12-12T18:24:38.822949image/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

연번폐기물구분상호전화번호폐기물 종류처리방법사업장도로명주소신고기준년도데이터기준일자
01지정폐기물개인<NA>석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등매립(민간관리형매립시설)서울특별시 동대문구 무학로49길 18 (용두동)202120210501
12지정폐기물개인<NA>흩날릴 우려가 없는 폐석면매립(민간관리형매립시설)서울특별시 동대문구 무학로49길 18 (용두동)202120210501
23지정폐기물서울특별시 동부병원02-920-9113폐황산이 포함된 2차폐축전지재활용(중간가공폐기물 제조)서울특별시 동대문구 무학로 124 (용두동)202120210501
34지정폐기물(주)보명토건<NA>석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등매립(민간관리형매립시설)202120210501
45지정폐기물(주)보명토건<NA>흩날릴 우려가 없는 폐석면매립(민간관리형매립시설)202120210501
56지정폐기물개인<NA>흩날릴 우려가 없는 폐석면매립(민간관리형매립시설)서울특별시 동대문구 장한로 119_ 3007호 (장안동_ 장안삼성쉐르빌)202120210501
67지정폐기물개인<NA>석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등매립(민간관리형매립시설)서울특별시 동대문구 장한로 119_ 3007호 (장안동_ 장안삼성쉐르빌)202120210501
78지정폐기물국립산림과학원02-961-2726흩날릴 우려가 없는 폐석면중간처분(고형화)서울특별시 동대문구 회기로 57_ 국립산림과학원 (청량리동)202120210501
89지정폐기물국립산림과학원02-961-2726석면의 제거작업에 사용된 모든 비닐시트ㆍ방진마스크ㆍ작업복ㆍ집진필터 등중간처분(고형화)서울특별시 동대문구 회기로 57_ 국립산림과학원 (청량리동)202120210501
910지정폐기물개인<NA>흩날릴 우려가 없는 폐석면매립(민간관리형매립시설)202120210501
연번폐기물구분상호전화번호폐기물 종류처리방법사업장도로명주소신고기준년도데이터기준일자
383384사업장폐기물보광종합건설(주)02-514-1982임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(연료·고형연료제품 제조)서울특별시 동대문구 장안벚꽃로 77 (장평근린공원) 외 장안근린공원 (장안동)202020210501
384385사업장폐기물(주)자연에임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(직접 제품제조)서울특별시 동대문구 이문로 190_ 외 (이문동)202020210501
385386사업장폐기물(주)에코랜드031-451-3511임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(중간가공폐기물 제조)경기도 안양시 동안구 엘에스로91번길 16-39 (호계동)202020210501
386387사업장폐기물서울시립대학교02-6490-6470임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(중간가공폐기물 제조)서울특별시 동대문구 서울시립대로 163_ 서울시립대학교 (전농동)202020210501
387388사업장폐기물서울특별시 동대문구청02-2127-4856하수준설토재활용(직접 제품제조)서울특별시 동대문구 천호대로 145_ 동대문구청 (용두동)202020210501
388389사업장폐기물동대문구청02-2127-4815임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(직접 제품제조)서울특별시 동대문구 천호대로 145 (용두동)202020210501
389390사업장폐기물우나조경건설 주식회사02-488-8697임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(직접 제품제조)서울특별시 동대문구 장안벚꽃로 205_ 외 (장안동)202020210501
390391사업장폐기물주식회사 단풍나무02-471-9721임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)재활용(중간가공폐기물 제조)서울특별시 동대문구 제기로 129 (청량리동_ 한신아파트)202020210501
391392사업장폐기물서울특별시동부교육청<NA>폐합성수지류(폐염화비닐수지류는 제외한다)재활용(연료·고형연료제품 제조)서울특별시 동대문구 전농동 188-7 서울동부교육지원청202020210501
392<NA><NA><NA><NA><NA><NA><NA>202020210501