Overview

Dataset statistics

Number of variables13
Number of observations85
Missing cells85
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory109.6 B

Variable types

Numeric2
Categorical5
DateTime3
Text2
Unsupported1

Dataset

Description해당 데이터는 인천광역시 남동구의 배출 부과금 징수현황에 관련된 자료로서, 인천광역시 남동구 배출 부과금 징수현황의 년도, 분야, 구분, 부과일자, 업체명, 대표자, 소재지, 납부기한, 오염 물질명, 부과금액(원) , 가산금액 , 미수부과금액, 납부일의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15104540/fileData.do

Alerts

구분 is highly overall correlated with 부과금액(원) and 3 other fieldsHigh correlation
가산금액 is highly overall correlated with 년도 and 5 other fieldsHigh correlation
오염 물질명 is highly overall correlated with 부과금액(원) and 4 other fieldsHigh correlation
분야 is highly overall correlated with 구분 and 3 other fieldsHigh correlation
년도 is highly overall correlated with 가산금액 High correlation
부과금액(원) is highly overall correlated with 구분 and 2 other fieldsHigh correlation
대표자 is highly overall correlated with 분야 and 2 other fieldsHigh correlation
가산금액 is highly imbalanced (82.8%)Imbalance
미수부과금액 has 85 (100.0%) missing valuesMissing
미수부과금액 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-23 05:38:17.627180
Analysis finished2024-03-23 05:38:25.166947
Duration7.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.6706
Minimum2006
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-03-23T05:38:25.351820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2007
Q12010
median2017
Q32022
95-th percentile2023
Maximum2023
Range17
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.2685691
Coefficient of variation (CV)0.0031099174
Kurtosis-1.6404051
Mean2015.6706
Median Absolute Deviation (MAD)6
Skewness-0.15754165
Sum171332
Variance39.294958
MonotonicityIncreasing
2024-03-23T05:38:25.925347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2023 14
16.5%
2022 13
15.3%
2021 9
10.6%
2007 9
10.6%
2012 7
8.2%
2008 5
 
5.9%
2010 5
 
5.9%
2011 4
 
4.7%
2017 4
 
4.7%
2006 3
 
3.5%
Other values (7) 12
14.1%
ValueCountFrequency (%)
2006 3
 
3.5%
2007 9
10.6%
2008 5
5.9%
2009 3
 
3.5%
2010 5
5.9%
2011 4
4.7%
2012 7
8.2%
2013 1
 
1.2%
2014 3
 
3.5%
2015 1
 
1.2%
ValueCountFrequency (%)
2023 14
16.5%
2022 13
15.3%
2021 9
10.6%
2019 1
 
1.2%
2018 2
 
2.4%
2017 4
 
4.7%
2016 1
 
1.2%
2015 1
 
1.2%
2014 3
 
3.5%
2013 1
 
1.2%

분야
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size812.0 B
수질
49 
대기
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수질
2nd row대기
3rd row수질
4th row대기
5th row대기

Common Values

ValueCountFrequency (%)
수질 49
57.6%
대기 36
42.4%

Length

2024-03-23T05:38:26.417154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:38:26.743938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수질 49
57.6%
대기 36
42.4%

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
초과
43 
기본
41 
과징금
 
1

Length

Max length3
Median length2
Mean length2.0117647
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row초과
2nd row기본
3rd row기본
4th row초과
5th row기본

Common Values

ValueCountFrequency (%)
초과 43
50.6%
기본 41
48.2%
과징금 1
 
1.2%

Length

2024-03-23T05:38:27.190383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:38:27.561947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초과 43
50.6%
기본 41
48.2%
과징금 1
 
1.2%

부과일자
Date

Distinct56
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2006-04-04 00:00:00
Maximum2023-10-19 00:00:00
2024-03-23T05:38:27.966872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:28.596124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업체명
Text

Distinct49
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Memory size812.0 B
2024-03-23T05:38:29.270859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.3058824
Min length2

Characters and Unicode

Total characters621
Distinct characters143
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)41.2%

Sample

1st row해안세차장
2nd row㈜경남산업
3rd row㈜하얀나라
4th row신태영자동차공업사
5th row㈜경남산업
ValueCountFrequency (%)
㈜경남산업 12
 
12.9%
의료)길의료재단 7
 
7.5%
소래포구전통어시장 5
 
5.4%
주)경남산업 4
 
4.3%
㈜하얀나라 3
 
3.2%
길의료재단중앙길병원 3
 
3.2%
㈜예림임업 3
 
3.2%
㈜장원(인천공장지점 3
 
3.2%
암센터 3
 
3.2%
좋은주유소 3
 
3.2%
Other values (42) 47
50.5%
2024-03-23T05:38:30.550394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 32
 
5.2%
업 27
 
4.3%
남 20
 
3.2%
산 19
 
3.1%
장 18
 
2.9%
) 17
 
2.7%
료 17
 
2.7%
의 17
 
2.7%
( 17
 
2.7%
경 16
 
2.6%
Other values (133) 421
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
86.5%
Other Symbol 32
 
5.2%
Close Punctuation 20
 
3.2%
Open Punctuation 20
 
3.2%
Space Separator 8
 
1.3%
Uppercase Letter 3
 
0.5%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 27
 
5.0%
남 20
 
3.7%
산 19
 
3.5%
장 18
 
3.4%
료 17
 
3.2%
의 17
 
3.2%
경 16
 
3.0%
주 15
 
2.8%
소 14
 
2.6%
길 13
 
2.4%
Other values (123) 361
67.2%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
S 1
33.3%
T 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 17
85.0%
] 3
 
15.0%
Open Punctuation
ValueCountFrequency (%)
( 17
85.0%
[ 3
 
15.0%
Other Symbol
ValueCountFrequency (%)
㈜ 32
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 569
91.6%
Common 49
 
7.9%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 32
 
5.6%
업 27
 
4.7%
남 20
 
3.5%
산 19
 
3.3%
장 18
 
3.2%
료 17
 
3.0%
의 17
 
3.0%
경 16
 
2.8%
주 15
 
2.6%
소 14
 
2.5%
Other values (124) 374
65.7%
Common
ValueCountFrequency (%)
) 17
34.7%
( 17
34.7%
8
16.3%
[ 3
 
6.1%
] 3
 
6.1%
1 1
 
2.0%
Latin
ValueCountFrequency (%)
M 1
33.3%
S 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
86.5%
ASCII 52
 
8.4%
None 32
 
5.2%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 32
100.0%
Hangul
ValueCountFrequency (%)
업 27
 
5.0%
남 20
 
3.7%
산 19
 
3.5%
장 18
 
3.4%
료 17
 
3.2%
의 17
 
3.2%
경 16
 
3.0%
주 15
 
2.8%
소 14
 
2.6%
길 13
 
2.4%
Other values (123) 361
67.2%
ASCII
ValueCountFrequency (%)
) 17
32.7%
( 17
32.7%
8
15.4%
[ 3
 
5.8%
] 3
 
5.8%
1 1
 
1.9%
M 1
 
1.9%
S 1
 
1.9%
T 1
 
1.9%

대표자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size812.0 B
개인정보
47 
대표이사
33 
남동구청장
5 

Length

Max length5
Median length4
Mean length4.0588235
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인정보 47
55.3%
대표이사 33
38.8%
남동구청장 5
 
5.9%

Length

2024-03-23T05:38:31.109992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:38:31.554548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인정보 47
55.3%
대표이사 33
38.8%
남동구청장 5
 
5.9%

소재지
Text

Distinct49
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Memory size812.0 B
2024-03-23T05:38:32.085052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length12.129412
Min length7

Characters and Unicode

Total characters1031
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)45.9%

Sample

1st row고잔동 523
2nd row고잔동 120-3
3rd row고잔동 86-8
4th row간석동 616-61
5th row고잔동 120-3
ValueCountFrequency (%)
고잔동 25
 
14.1%
120-3 16
 
9.0%
간석동 9
 
5.1%
남동대로774번길 9
 
5.1%
장도로 5
 
2.8%
86-14 5
 
2.8%
21 4
 
2.3%
남동대로262번길 4
 
2.3%
21(구월동 4
 
2.3%
616-61 4
 
2.3%
Other values (75) 92
52.0%
2024-03-23T05:38:33.638813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
8.9%
동 85
 
8.2%
1 77
 
7.5%
- 54
 
5.2%
3 54
 
5.2%
2 50
 
4.8%
고 47
 
4.6%
6 47
 
4.6%
로 46
 
4.5%
4 42
 
4.1%
Other values (51) 437
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 441
42.8%
Decimal Number 379
36.8%
Space Separator 92
 
8.9%
Dash Punctuation 54
 
5.2%
Close Punctuation 32
 
3.1%
Open Punctuation 32
 
3.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 85
19.3%
고 47
10.7%
로 46
10.4%
잔 42
9.5%
번 28
 
6.3%
길 28
 
6.3%
대 24
 
5.4%
남 16
 
3.6%
석 14
 
3.2%
간 13
 
2.9%
Other values (36) 98
22.2%
Decimal Number
ValueCountFrequency (%)
1 77
20.3%
3 54
14.2%
2 50
13.2%
6 47
12.4%
4 42
11.1%
7 34
9.0%
0 26
 
6.9%
8 24
 
6.3%
5 13
 
3.4%
9 12
 
3.2%
Space Separator
ValueCountFrequency (%)
92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 590
57.2%
Hangul 441
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 85
19.3%
고 47
10.7%
로 46
10.4%
잔 42
9.5%
번 28
 
6.3%
길 28
 
6.3%
대 24
 
5.4%
남 16
 
3.6%
석 14
 
3.2%
간 13
 
2.9%
Other values (36) 98
22.2%
Common
ValueCountFrequency (%)
92
15.6%
1 77
13.1%
- 54
9.2%
3 54
9.2%
2 50
8.5%
6 47
8.0%
4 42
7.1%
7 34
 
5.8%
) 32
 
5.4%
( 32
 
5.4%
Other values (5) 76
12.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 590
57.2%
Hangul 441
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
15.6%
1 77
13.1%
- 54
9.2%
3 54
9.2%
2 50
8.5%
6 47
8.0%
4 42
7.1%
7 34
 
5.8%
) 32
 
5.4%
( 32
 
5.4%
Other values (5) 76
12.9%
Hangul
ValueCountFrequency (%)
동 85
19.3%
고 47
10.7%
로 46
10.4%
잔 42
9.5%
번 28
 
6.3%
길 28
 
6.3%
대 24
 
5.4%
남 16
 
3.6%
석 14
 
3.2%
간 13
 
2.9%
Other values (36) 98
22.2%

납부기한
Date

Distinct61
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2006-05-08 00:00:00
Maximum2023-11-20 00:00:00
2024-03-23T05:38:34.202846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:34.789474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

오염 물질명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
먼지
23 
COD
14 
TOC
10 
질소산화물
9 
BOD+SS
5 
Other values (13)
24 

Length

Max length16
Median length10
Mean length4.1411765
Min length2

Unique

Unique7 ?
Unique (%)8.2%

Sample

1st rowCOD
2nd row먼지
3rd rowCOD
4th row먼지
5th row먼지

Common Values

ValueCountFrequency (%)
먼지 23
27.1%
COD 14
16.5%
TOC 10
11.8%
질소산화물 9
 
10.6%
BOD+SS 5
 
5.9%
유기물질(COD) 4
 
4.7%
부유물질(SS) 3
 
3.5%
질소산화물+먼지 3
 
3.5%
총인 3
 
3.5%
COD+SS 2
 
2.4%
Other values (8) 9
 
10.6%

Length

2024-03-23T05:38:35.239653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
먼지 23
27.1%
cod 14
16.5%
toc 10
11.8%
질소산화물 9
 
10.6%
bod+ss 5
 
5.9%
유기물질(cod 4
 
4.7%
부유물질(ss 3
 
3.5%
질소산화물+먼지 3
 
3.5%
총인 3
 
3.5%
ss 2
 
2.4%
Other values (8) 9
 
10.6%

부과금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1347773.1
Minimum14170
Maximum45000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-03-23T05:38:35.774240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14170
5-th percentile35650
Q1215210
median500000
Q3577500
95-th percentile1985582
Maximum45000000
Range44985830
Interquartile range (IQR)362290

Descriptive statistics

Standard deviation5185465.7
Coefficient of variation (CV)3.8474324
Kurtosis62.108013
Mean1347773.1
Median Absolute Deviation (MAD)214200
Skewness7.6032323
Sum1.1456071 × 108
Variance2.6889055 × 1013
MonotonicityNot monotonic
2024-03-23T05:38:36.324289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500000 19
 
22.4%
770940 1
 
1.2%
16709670 1
 
1.2%
164940 1
 
1.2%
1073450 1
 
1.2%
714200 1
 
1.2%
154880 1
 
1.2%
6504610 1
 
1.2%
500830 1
 
1.2%
1197240 1
 
1.2%
Other values (57) 57
67.1%
ValueCountFrequency (%)
14170 1
1.2%
19410 1
1.2%
21470 1
1.2%
29460 1
1.2%
34380 1
1.2%
40730 1
1.2%
48500 1
1.2%
59890 1
1.2%
82330 1
1.2%
84870 1
1.2%
ValueCountFrequency (%)
45000000 1
1.2%
16709670 1
1.2%
6504610 1
1.2%
5767940 1
1.2%
1992270 1
1.2%
1958830 1
1.2%
1894130 1
1.2%
1469160 1
1.2%
1197240 1
1.2%
1073450 1
1.2%

가산금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size812.0 B
<NA>
81 
15000
 
2
50560
 
1
501290
 
1

Length

Max length6
Median length4
Mean length4.0588235
Min length4

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 81
95.3%
15000 2
 
2.4%
50560 1
 
1.2%
501290 1
 
1.2%

Length

2024-03-23T05:38:36.932667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:38:37.445500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 81
95.3%
15000 2
 
2.4%
50560 1
 
1.2%
501290 1
 
1.2%

미수부과금액
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing85
Missing (%)100.0%
Memory size897.0 B

납부일
Date

Distinct75
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size812.0 B
Minimum2006-04-14 00:00:00
Maximum2023-11-20 00:00:00
2024-03-23T05:38:37.965205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:38.384126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-23T05:38:22.764679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:22.116459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:23.377297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:38:22.487456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:38:38.704372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도분야구분부과일자업체명대표자소재지납부기한오염 물질명부과금액(원)가산금액납부일
년도1.0000.3310.5361.0000.9570.4380.9231.0000.7600.2611.0001.000
분야0.3311.0000.4290.0000.9880.3660.9820.2851.0000.126NaN0.791
구분0.5360.4291.0000.9670.9760.6710.9750.9950.9960.677NaN0.996
부과일자1.0000.0000.9671.0000.9870.0000.9871.0000.8870.8631.0000.998
업체명0.9570.9880.9760.9871.0000.9721.0000.9900.9950.9151.0000.992
대표자0.4380.3660.6710.0000.9721.0000.9610.0000.9810.4331.0000.790
소재지0.9230.9820.9750.9871.0000.9611.0000.9910.9980.9151.0000.996
납부기한1.0000.2850.9951.0000.9900.0000.9911.0000.9210.7451.0000.997
오염 물질명0.7601.0000.9960.8870.9950.9810.9980.9211.0000.9551.0000.984
부과금액(원)0.2610.1260.6770.8630.9150.4330.9150.7450.9551.0001.0000.000
가산금액1.000NaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.000
납부일1.0000.7910.9960.9980.9920.7900.9960.9970.9840.0001.0001.000
2024-03-23T05:38:39.197351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대표자가산금액오염 물질명분야
구분1.0000.3301.0000.8330.665
대표자0.3301.0000.7070.7630.579
가산금액1.0000.7071.0001.0001.000
오염 물질명0.8330.7631.0001.0000.898
분야0.6650.5791.0000.8981.000
2024-03-23T05:38:39.615029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도부과금액(원)분야구분대표자오염 물질명가산금액
년도1.0000.0570.2340.3670.3030.3811.000
부과금액(원)0.0571.0000.0810.7030.4240.7840.707
분야0.2340.0811.0000.6650.5790.8981.000
구분0.3670.7030.6651.0000.3300.8331.000
대표자0.3030.4240.5790.3301.0000.7630.707
오염 물질명0.3810.7840.8980.8330.7631.0001.000
가산금액1.0000.7071.0001.0000.7071.0001.000

Missing values

2024-03-23T05:38:24.021291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:38:24.788638image/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

년도분야구분부과일자업체명대표자소재지납부기한오염 물질명부과금액(원)가산금액미수부과금액납부일
02006수질초과2006-04-04해안세차장개인정보고잔동 5232006-05-08COD500830<NA><NA>2006-04-14
12006대기기본2006-09-09㈜경남산업개인정보고잔동 120-32006-10-25먼지212120<NA><NA>2006-10-25
22006수질기본2006-09-09㈜하얀나라개인정보고잔동 86-82006-10-25COD48500<NA><NA>2006-10-12
32007대기초과2007-02-02신태영자동차공업사개인정보간석동 616-612007-03-05먼지19410<NA><NA>2007-03-05
42007대기기본2007-03-03㈜경남산업개인정보고잔동 120-32007-04-27먼지693960<NA><NA>2007-04-10
52007수질기본2007-03-03㈜하얀나라개인정보고잔동 86-82007-04-27COD84870<NA><NA>2007-04-03
62007수질기본2007-03-03길의료재단중앙길병원개인정보구월동 11982007-04-27BOD59890<NA><NA>2007-04-24
72007대기기본2007-09-09㈜경남산업개인정보고잔동 120-32007-10-28먼지229560<NA><NA>2007-10-09
82007대기기본2007-09-09신태영자동차공업사개인정보간석동 616-612007-10-28먼지14170<NA><NA>2007-10-22
92007수질기본2007-09-09세원산업개인정보고잔동 9712007-10-28SS1958830<NA><NA>2007-10-29
년도분야구분부과일자업체명대표자소재지납부기한오염 물질명부과금액(원)가산금액미수부과금액납부일
752023수질기본2023-03-31소래포구전통어시장남동구청장장도로 86-142023-05-01BOD+SS1894130<NA><NA>2023-04-05
762023수질초과2023-03-31㈜장원오일(남동지점 좋은주유소)대표이사앵고개로 676(고잔동)2023-05-01TOC500000<NA><NA>2023-05-01
772023수질초과2023-04-19㈜장원오일(남동지점 좋은주유소)대표이사앵고개로 676(고잔동)2023-05-22TOC500000<NA><NA>2023-05-22
782023수질초과2023-04-25삼미상사㈜남촌도림셀프주유소대표이사비류대로 811(도림동)2023-05-24TOC500000<NA><NA>2023-05-22
792023대기기본2023-09-27(의료)길의료재단대표이사남동대로774번길 21(구월동)2023-11-03질소산화물365820<NA><NA>2023-11-02
802023대기기본2023-09-27(의료)길의료재단 [암센터]대표이사남동대로774번길 21(구월동)2023-11-03질소산화물170110<NA><NA>2023-11-02
812023대기기본2023-09-27㈜예림임업대표이사고잔동 246-1(고잔동)2023-11-03먼지21470<NA><NA>2023-10-31
822023대기기본2023-09-27㈜장원(인천공장지점)대표이사남동대로262번길 30-37(논현동)2023-11-03질소산화물+먼지507980<NA><NA>2023-10-10
832023수질기본2023-09-27소래포구전통어시장남동구청장장도로 86-142023-11-03BOD+SS1992270<NA><NA>2023-10-17
842023수질초과2023-10-19주식회사 대성씨엠텍개인정보경원대로 9342023-11-20TOC500000<NA><NA>2023-11-20