Overview

Dataset statistics

Number of variables6
Number of observations880
Missing cells62
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.2 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description인천광역시 부평구 사업장 폐기물 배출자 신고현황입니다.(일련번호,상호,연락처,주소,폐기물종류,처리방법)ex) 1,(주)심팩,032-510-0033,인천광역시 부평구 부평북로 141(청천동),폐합성수지류,폐흡착제류 중간처분(고온소각) 등
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15060445&srcSe=7661IVAWM27C61E190

Alerts

처리방법 is highly imbalanced (78.0%)Imbalance
연락처 has 62 (7.0%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:29:00.568135
Analysis finished2024-03-18 04:29:01.576148
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct880
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440.5
Minimum1
Maximum880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-18T13:29:01.634569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44.95
Q1220.75
median440.5
Q3660.25
95-th percentile836.05
Maximum880
Range879
Interquartile range (IQR)439.5

Descriptive statistics

Standard deviation254.17842
Coefficient of variation (CV)0.57702251
Kurtosis-1.2
Mean440.5
Median Absolute Deviation (MAD)220
Skewness0
Sum387640
Variance64606.667
MonotonicityStrictly increasing
2024-03-18T13:29:01.741606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
593 1
 
0.1%
582 1
 
0.1%
583 1
 
0.1%
584 1
 
0.1%
585 1
 
0.1%
586 1
 
0.1%
587 1
 
0.1%
588 1
 
0.1%
589 1
 
0.1%
Other values (870) 870
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
880 1
0.1%
879 1
0.1%
878 1
0.1%
877 1
0.1%
876 1
0.1%
875 1
0.1%
874 1
0.1%
873 1
0.1%
872 1
0.1%
871 1
0.1%

상 호
Text

Distinct872
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-18T13:29:01.943015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.6806818
Min length3

Characters and Unicode

Total characters6759
Distinct characters443
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique864 ?
Unique (%)98.2%

Sample

1st row ㈜심팩
2nd row㈜삼송캐스터
3rd row 한국요꼬가와일렉트로닉스매뉴팩처링㈜
4th row 린나이코리아㈜ 제2공장
5th row인그리디언코리아(유) 부평공장
ValueCountFrequency (%)
주식회사 11
 
1.2%
근로복지공단 4
 
0.4%
부평지점 3
 
0.3%
부평점 3
 
0.3%
글로리병원 2
 
0.2%
부평 2
 
0.2%
부평세림병원 2
 
0.2%
한국전력공사 2
 
0.2%
롯데쇼핑㈜ 2
 
0.2%
부평구보건소 2
 
0.2%
Other values (901) 912
96.5%
2024-03-18T13:29:02.262010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 731
 
10.8%
의 653
 
9.7%
과 420
 
6.2%
치 191
 
2.8%
한 165
 
2.4%
부 153
 
2.3%
평 113
 
1.7%
인 112
 
1.7%
이 112
 
1.7%
78
 
1.2%
Other values (433) 4031
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6488
96.0%
Space Separator 78
 
1.2%
Close Punctuation 47
 
0.7%
Open Punctuation 46
 
0.7%
Decimal Number 36
 
0.5%
Other Symbol 35
 
0.5%
Uppercase Letter 23
 
0.3%
Dash Punctuation 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 731
 
11.3%
의 653
 
10.1%
과 420
 
6.5%
치 191
 
2.9%
한 165
 
2.5%
부 153
 
2.4%
평 113
 
1.7%
인 112
 
1.7%
이 112
 
1.7%
성 73
 
1.1%
Other values (406) 3765
58.0%
Uppercase Letter
ValueCountFrequency (%)
K 6
26.1%
S 4
17.4%
J 2
 
8.7%
B 2
 
8.7%
T 2
 
8.7%
O 2
 
8.7%
G 1
 
4.3%
Y 1
 
4.3%
R 1
 
4.3%
M 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 8
22.2%
1 6
16.7%
0 5
13.9%
3 5
13.9%
8 3
 
8.3%
5 3
 
8.3%
6 3
 
8.3%
4 3
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
e 1
50.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6523
96.5%
Common 211
 
3.1%
Latin 25
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 731
 
11.2%
의 653
 
10.0%
과 420
 
6.4%
치 191
 
2.9%
한 165
 
2.5%
부 153
 
2.3%
평 113
 
1.7%
인 112
 
1.7%
이 112
 
1.7%
성 73
 
1.1%
Other values (407) 3800
58.3%
Common
ValueCountFrequency (%)
78
37.0%
) 47
22.3%
( 46
21.8%
2 8
 
3.8%
1 6
 
2.8%
0 5
 
2.4%
3 5
 
2.4%
- 3
 
1.4%
8 3
 
1.4%
5 3
 
1.4%
Other values (3) 7
 
3.3%
Latin
ValueCountFrequency (%)
K 6
24.0%
S 4
16.0%
J 2
 
8.0%
B 2
 
8.0%
T 2
 
8.0%
O 2
 
8.0%
n 1
 
4.0%
e 1
 
4.0%
G 1
 
4.0%
Y 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6488
96.0%
ASCII 236
 
3.5%
None 35
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 731
 
11.3%
의 653
 
10.1%
과 420
 
6.5%
치 191
 
2.9%
한 165
 
2.5%
부 153
 
2.4%
평 113
 
1.7%
인 112
 
1.7%
이 112
 
1.7%
성 73
 
1.1%
Other values (406) 3765
58.0%
ASCII
ValueCountFrequency (%)
78
33.1%
) 47
19.9%
( 46
19.5%
2 8
 
3.4%
1 6
 
2.5%
K 6
 
2.5%
0 5
 
2.1%
3 5
 
2.1%
S 4
 
1.7%
- 3
 
1.3%
Other values (16) 28
 
11.9%
None
ValueCountFrequency (%)
㈜ 35
100.0%

연락처
Text

MISSING 

Distinct806
Distinct (%)98.5%
Missing62
Missing (%)7.0%
Memory size7.0 KiB
2024-03-18T13:29:02.466457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.976773
Min length9

Characters and Unicode

Total characters9797
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

Unique794 ?
Unique (%)97.1%

Sample

1st row032-510-0033
2nd row032-527-2151
3rd row032-510-3261
4th row032-570-8323
5th row032-577-7183
ValueCountFrequency (%)
032-509-8200 2
 
0.2%
032-529-2875 2
 
0.2%
032-525-1800 2
 
0.2%
032-724-7352 2
 
0.2%
032-280-6406 2
 
0.2%
032-298-1004 2
 
0.2%
032-582-6741 2
 
0.2%
032-507-3355 2
 
0.2%
032-520-4715 2
 
0.2%
032-521-5555 2
 
0.2%
Other values (796) 798
97.6%
2024-03-18T13:29:02.821906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1632
16.7%
- 1629
16.6%
0 1495
15.3%
3 1295
13.2%
5 1154
11.8%
1 637
 
6.5%
7 607
 
6.2%
8 467
 
4.8%
6 317
 
3.2%
4 303
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8168
83.4%
Dash Punctuation 1629
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1632
20.0%
0 1495
18.3%
3 1295
15.9%
5 1154
14.1%
1 637
 
7.8%
7 607
 
7.4%
8 467
 
5.7%
6 317
 
3.9%
4 303
 
3.7%
9 261
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 1629
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9797
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1632
16.7%
- 1629
16.6%
0 1495
15.3%
3 1295
13.2%
5 1154
11.8%
1 637
 
6.5%
7 607
 
6.2%
8 467
 
4.8%
6 317
 
3.2%
4 303
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9797
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1632
16.7%
- 1629
16.6%
0 1495
15.3%
3 1295
13.2%
5 1154
11.8%
1 637
 
6.5%
7 607
 
6.2%
8 467
 
4.8%
6 317
 
3.2%
4 303
 
3.1%

주소
Text

Distinct810
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-18T13:29:03.087209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length51
Mean length29.142045
Min length16

Characters and Unicode

Total characters25645
Distinct characters285
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique761 ?
Unique (%)86.5%

Sample

1st row인천광역시 부평구 부평북로 141(청천동)
2nd row인천광역시 부평구 안남로418번길 74(청천동)
3rd row인천광역시 부평구 부평대로297번길 82(청천동)
4th row인천광역시 부평구 백범로577번길 48(십정동)
5th row인천광역시 부평구 백범로 584(십정동)
ValueCountFrequency (%)
부평구 880
 
17.4%
인천광역시 878
 
17.3%
부평동 313
 
6.2%
산곡동 105
 
2.1%
부평대로 100
 
2.0%
삼산동 99
 
2.0%
청천동 76
 
1.5%
경원대로 75
 
1.5%
2층 65
 
1.3%
십정동 62
 
1.2%
Other values (957) 2419
47.7%
2024-03-18T13:29:03.495689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4243
 
16.5%
부 1597
 
6.2%
평 1451
 
5.7%
천 1034
 
4.0%
동 949
 
3.7%
인 923
 
3.6%
광 909
 
3.5%
시 900
 
3.5%
구 893
 
3.5%
역 883
 
3.4%
Other values (275) 11863
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14984
58.4%
Space Separator 4243
 
16.5%
Decimal Number 3982
 
15.5%
Close Punctuation 799
 
3.1%
Open Punctuation 799
 
3.1%
Connector Punctuation 600
 
2.3%
Dash Punctuation 119
 
0.5%
Uppercase Letter 48
 
0.2%
Other Punctuation 39
 
0.2%
Math Symbol 26
 
0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1597
 
10.7%
평 1451
 
9.7%
천 1034
 
6.9%
동 949
 
6.3%
인 923
 
6.2%
광 909
 
6.1%
시 900
 
6.0%
구 893
 
6.0%
역 883
 
5.9%
로 817
 
5.5%
Other values (231) 4628
30.9%
Uppercase Letter
ValueCountFrequency (%)
A 5
10.4%
B 5
10.4%
K 4
 
8.3%
D 4
 
8.3%
P 4
 
8.3%
I 4
 
8.3%
C 3
 
6.2%
R 3
 
6.2%
S 3
 
6.2%
F 2
 
4.2%
Other values (9) 11
22.9%
Decimal Number
ValueCountFrequency (%)
1 717
18.0%
2 610
15.3%
3 527
13.2%
4 516
13.0%
0 429
10.8%
6 311
7.8%
5 296
7.4%
7 205
 
5.1%
8 187
 
4.7%
9 184
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
e 1
20.0%
y 1
20.0%
t 1
20.0%
i 1
20.0%
c 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 21
53.8%
, 17
43.6%
· 1
 
2.6%
Space Separator
ValueCountFrequency (%)
4243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 799
100.0%
Open Punctuation
ValueCountFrequency (%)
( 799
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 600
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Math Symbol
ValueCountFrequency (%)
~ 26
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14984
58.4%
Common 10607
41.4%
Latin 54
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1597
 
10.7%
평 1451
 
9.7%
천 1034
 
6.9%
동 949
 
6.3%
인 923
 
6.2%
광 909
 
6.1%
시 900
 
6.0%
구 893
 
6.0%
역 883
 
5.9%
로 817
 
5.5%
Other values (231) 4628
30.9%
Latin
ValueCountFrequency (%)
A 5
 
9.3%
B 5
 
9.3%
K 4
 
7.4%
D 4
 
7.4%
P 4
 
7.4%
I 4
 
7.4%
C 3
 
5.6%
R 3
 
5.6%
S 3
 
5.6%
F 2
 
3.7%
Other values (15) 17
31.5%
Common
ValueCountFrequency (%)
4243
40.0%
) 799
 
7.5%
( 799
 
7.5%
1 717
 
6.8%
2 610
 
5.8%
_ 600
 
5.7%
3 527
 
5.0%
4 516
 
4.9%
0 429
 
4.0%
6 311
 
2.9%
Other values (9) 1056
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14984
58.4%
ASCII 10659
41.6%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4243
39.8%
) 799
 
7.5%
( 799
 
7.5%
1 717
 
6.7%
2 610
 
5.7%
_ 600
 
5.6%
3 527
 
4.9%
4 516
 
4.8%
0 429
 
4.0%
6 311
 
2.9%
Other values (32) 1108
 
10.4%
Hangul
ValueCountFrequency (%)
부 1597
 
10.7%
평 1451
 
9.7%
천 1034
 
6.9%
동 949
 
6.3%
인 923
 
6.2%
광 909
 
6.1%
시 900
 
6.0%
구 893
 
6.0%
역 883
 
5.9%
로 817
 
5.5%
Other values (231) 4628
30.9%
None
ValueCountFrequency (%)
· 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

폐기물종류
Text

Distinct54
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-18T13:29:03.717861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length9
Mean length9.8261364
Min length5

Characters and Unicode

Total characters8647
Distinct characters116
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

Unique40 ?
Unique (%)4.5%

Sample

1st row폐합성수지류, 폐활성탄
2nd row폐합성수지류, 폐사
3rd row폐합성수지, 폐활성탄
4th row폐합성수지류, 폐폴리염화비닐수지류, 폐발포합성수지, 그밖의분진, 폐활성탄, 폐받침목, 그밖의폐유리, 음식물류폐기물, 폐수처리오니
5th row그밖의폐수처리오니, 폐합성수지류, 그밖의분진, 폐흡착제, 그 밖의 식물성잔재물, 음식물쓰레기, 그 밖의 폐목재
ValueCountFrequency (%)
등 775
41.0%
일반의료폐기물 767
40.6%
그 48
 
2.5%
밖의 48
 
2.5%
폐합성수지류 24
 
1.3%
폐합성수지 23
 
1.2%
폐산 16
 
0.8%
폐황산이 16
 
0.8%
포함된 16
 
0.8%
2차폐축전지 16
 
0.8%
Other values (61) 140
 
7.4%
2024-03-18T13:29:04.036477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1009
11.7%
폐 973
11.3%
의 832
9.6%
물 825
9.5%
기 796
9.2%
등 775
9.0%
일 767
8.9%
료 767
8.9%
반 767
8.9%
, 100
 
1.2%
Other values (106) 1036
12.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7520
87.0%
Space Separator 1009
 
11.7%
Other Punctuation 100
 
1.2%
Decimal Number 16
 
0.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 973
12.9%
의 832
11.1%
물 825
11.0%
기 796
10.6%
등 775
10.3%
일 767
10.2%
료 767
10.2%
반 767
10.2%
지 67
 
0.9%
수 67
 
0.9%
Other values (101) 884
11.8%
Space Separator
ValueCountFrequency (%)
1009
100.0%
Other Punctuation
ValueCountFrequency (%)
, 100
100.0%
Decimal Number
ValueCountFrequency (%)
2 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7520
87.0%
Common 1127
 
13.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 973
12.9%
의 832
11.1%
물 825
11.0%
기 796
10.6%
등 775
10.3%
일 767
10.2%
료 767
10.2%
반 767
10.2%
지 67
 
0.9%
수 67
 
0.9%
Other values (101) 884
11.8%
Common
ValueCountFrequency (%)
1009
89.5%
, 100
 
8.9%
2 16
 
1.4%
) 1
 
0.1%
( 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7520
87.0%
ASCII 1127
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1009
89.5%
, 100
 
8.9%
2 16
 
1.4%
) 1
 
0.1%
( 1
 
0.1%
Hangul
ValueCountFrequency (%)
폐 973
12.9%
의 832
11.1%
물 825
11.0%
기 796
10.6%
등 775
10.3%
일 767
10.2%
료 767
10.2%
반 767
10.2%
지 67
 
0.9%
수 67
 
0.9%
Other values (101) 884
11.8%

처리방법
Categorical

IMBALANCE 

Distinct29
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
중간처분(일반소각)
769 
재활용(원료 제조)
 
20
중간처분(일반소각) 등
 
13
재활용(중간가공폐기물제조) 등
 
12
재활용(중간가공폐기물 제조) 등
 
9
Other values (24)
 
57

Length

Max length47
Median length10
Mean length10.4375
Min length9

Unique

Unique11 ?
Unique (%)1.2%

Sample

1st row중간처분(고온소각) 등 등
2nd row재활용(중간가공폐기물 제조) 등
3rd row재활용(중간가공폐기물 제조) 등
4th row중간처분(파쇄,분쇄) 등
5th row매립(민간관리형매립시설) 등

Common Values

ValueCountFrequency (%)
중간처분(일반소각) 769
87.4%
재활용(원료 제조) 20
 
2.3%
중간처분(일반소각) 등 13
 
1.5%
재활용(중간가공폐기물제조) 등 12
 
1.4%
재활용(중간가공폐기물 제조) 등 9
 
1.0%
재활용(원료 제조) 등 8
 
0.9%
재활용(연료,고형연료제품제조) 4
 
0.5%
재활용(직접제품제조) 4
 
0.5%
중간처분(고온소각) 4
 
0.5%
중간처분(파쇄분쇄) 등 4
 
0.5%
Other values (19) 33
 
3.8%

Length

2024-03-18T13:29:04.145303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중간처분(일반소각 782
78.0%
등 73
 
7.3%
제조 42
 
4.2%
재활용(원료 28
 
2.8%
재활용(중간가공폐기물제조 14
 
1.4%
재활용(중간가공폐기물 12
 
1.2%
재활용(연료,고형연료제품제조 6
 
0.6%
중간처분(고온소각 5
 
0.5%
재활용(원료제조 5
 
0.5%
재활용(직접제품제조 4
 
0.4%
Other values (19) 32
 
3.2%

Interactions

2024-03-18T13:29:01.320637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T13:29:04.216851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호폐기물종류처리방법
일련번호1.0000.6550.668
폐기물종류0.6551.0000.994
처리방법0.6680.9941.000
2024-03-18T13:29:04.305447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호처리방법
일련번호1.0000.303
처리방법0.3031.000

Missing values

2024-03-18T13:29:01.428886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:29:01.543128image/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

일련번호상 호연락처주소폐기물종류처리방법
01㈜심팩032-510-0033인천광역시 부평구 부평북로 141(청천동)폐합성수지류, 폐활성탄중간처분(고온소각) 등 등
12㈜삼송캐스터032-527-2151인천광역시 부평구 안남로418번길 74(청천동)폐합성수지류, 폐사재활용(중간가공폐기물 제조) 등
23한국요꼬가와일렉트로닉스매뉴팩처링㈜032-510-3261인천광역시 부평구 부평대로297번길 82(청천동)폐합성수지, 폐활성탄재활용(중간가공폐기물 제조) 등
34린나이코리아㈜ 제2공장032-570-8323인천광역시 부평구 백범로577번길 48(십정동)폐합성수지류, 폐폴리염화비닐수지류, 폐발포합성수지, 그밖의분진, 폐활성탄, 폐받침목, 그밖의폐유리, 음식물류폐기물, 폐수처리오니중간처분(파쇄,분쇄) 등
45인그리디언코리아(유) 부평공장032-577-7183인천광역시 부평구 백범로 584(십정동)그밖의폐수처리오니, 폐합성수지류, 그밖의분진, 폐흡착제, 그 밖의 식물성잔재물, 음식물쓰레기, 그 밖의 폐목재매립(민간관리형매립시설) 등
56동서식품㈜032-500-3279인천광역시 부평구 새벌로 55(청천동)그 밖의 폐수처리오니, 폐합성수지류, 금속성폐촉매, 그 밖의 연소잔재물, 그 밖의 식물성잔재물, 그밖의폐기물중간처분(일반소각) 등
67㈜와이지-원 인천공장032-500-5359인천광역시 부평구 세월천로 211 외 2필지(청천동)그밖의공정오니, 폐가구류,폐도장목,폐목재포장재, 폐전선드럼(원목상태의 깨끗한 목재를 말한다), 폐활성탄중간처분(일반소각) 등
78㈜삼성금속032-529-2662인천광역시 부평구 부평북로 149(청천동)폐수처리오니, 그밖의공정오니, 폐합성수지류, 그밖의분진재활용(직접 제품제조) 등
89㈜서울피막032-522-8532인천광역시 부평구 장제로 421(갈산동)폐수처리오니, 그 밖의 공정오니, 폐합성수지류재활용(원료 제조) 등
910대원인물㈜032-582-6741인천광역시 부평구 가좌로96번길 57(십정동)그밖의공정오니매립(관리형매립시설) 등
일련번호상 호연락처주소폐기물종류처리방법
870871(주)이건이엔씨02-6013-5976인천광역시 부평구 청천동 36-3 e편한세상 부평그랑힐스 현장폐유성페인트중간처분(고온소각)
871872(주)부광정공032-527-5464인천광역시 항동로143번길 10-27그 밖의 폐광물유재활용(직접제품제조)
872873현대건설(주)02-746-3644인천광역시 부평구 부흥로144번길 15(산곡동)그 밖의 폐광물유재활용(연료?고형연료제품제조)
873874풍윤정밀<NA>인천광역시 부평구 청천동 70-95그 밖의 폐광물유재활용(중간가공폐기물 제조) 등
874875인천교통공사032-451-7215경기도 부천시 길주로 486, 2층 7호선운영부문폐황산이 포함된 2차폐축전지재활용(중간가공폐기물 제조)
875876밧데리1번지출장전문자동차배터리할인매장<NA>인천광역시 부평구 부흥로 370폐황산이 포함된 2차폐축전지재활용(원료 제조)
876877유영상사<NA>인천광역시 부평구 부평대로 337, 제이타워3차 107호폐황산이 포함된 2차폐축전지재활용(중간가공폐기물 제조)
877878주식회사 티이피032-218-9907인천광역시 부평구 주부토로 236, 비동 비120호그 밖의 폐광물유재활용(중간가공폐기물 제조)
878879주식회사 아리수엔지니어링02-525-6505인천광역시 부평구 부평동 657-30그 밖의 폐광물유재활용(연료?고형연료제품제조)
879880주식회사 개미자동차<NA>인천광역시 부평구 산곡동 371-41폐황산이 포함된 2차폐축전지재활용(원료 제조)