Overview

Dataset statistics

Number of variables8
Number of observations1320
Missing cells1320
Missing cells (%)12.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory85.2 KiB
Average record size in memory66.1 B

Variable types

Categorical2
Text3
Numeric2
DateTime1

Dataset

Description충청남도 아산시 대기배출시설, 폐수배출시설 현황 데이터로 사업장명, 소재지주소, 업종, 종별, 대기오염물질 발생량(톤), 폐수배출량(톤) 등의 정보 확인이 가능합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=373&beforeMenuCd=DOM_000000201001001000&publicdatapk=15076029

Alerts

대기오염물질 발생량(톤/년) is highly overall correlated with 시설구분High correlation
폐수배출량(㎥/일) is highly overall correlated with 시설구분 and 1 other fieldsHigh correlation
시설구분 is highly overall correlated with 대기오염물질 발생량(톤/년) and 1 other fieldsHigh correlation
종별 is highly overall correlated with 폐수배출량(㎥/일)High correlation
대기오염물질 발생량(톤/년) has 653 (49.5%) missing valuesMissing
폐수배출량(㎥/일) has 667 (50.5%) missing valuesMissing
대기오염물질 발생량(톤/년) is highly skewed (γ1 = 25.43681356)Skewed
대기오염물질 발생량(톤/년) has 78 (5.9%) zerosZeros
폐수배출량(㎥/일) has 32 (2.4%) zerosZeros

Reproduction

Analysis started2024-01-09 20:51:24.652444
Analysis finished2024-01-09 20:51:25.997514
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
대기배출시설
667 
폐수배출시설
653 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출시설 667
50.5%
폐수배출시설 653
49.5%

Length

2024-01-10T05:51:26.055435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:51:26.138987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출시설 667
50.5%
폐수배출시설 653
49.5%

사업장명
Text

Distinct1005
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2024-01-10T05:51:26.352573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.9166667
Min length2

Characters and Unicode

Total characters10450
Distinct characters457
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

Unique712 ?
Unique (%)53.9%

Sample

1st row(주)광일
2nd row현대병원
3rd row효성오앤비(주)
4th row(주)신도리코
5th row아일수지공업(주)
ValueCountFrequency (%)
아산공장 34
 
2.3%
주식회사 27
 
1.8%
아산지점 13
 
0.9%
제2공장 7
 
0.5%
주)세명테크 6
 
0.4%
농업회사법인 5
 
0.3%
2공장 5
 
0.3%
주)재이솔루션테크놀러지 4
 
0.3%
주)아산 4
 
0.3%
주)한미에프쓰리 4
 
0.3%
Other values (1051) 1381
92.7%
2024-01-10T05:51:26.728721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 970
 
9.3%
( 882
 
8.4%
) 882
 
8.4%
이 302
 
2.9%
산 296
 
2.8%
아 267
 
2.6%
스 205
 
2.0%
170
 
1.6%
업 169
 
1.6%
에 161
 
1.5%
Other values (447) 6146
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8350
79.9%
Open Punctuation 882
 
8.4%
Close Punctuation 882
 
8.4%
Space Separator 170
 
1.6%
Uppercase Letter 80
 
0.8%
Decimal Number 55
 
0.5%
Other Symbol 21
 
0.2%
Other Punctuation 6
 
0.1%
Lowercase Letter 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 970
 
11.6%
이 302
 
3.6%
산 296
 
3.5%
아 267
 
3.2%
스 205
 
2.5%
업 169
 
2.0%
에 161
 
1.9%
장 159
 
1.9%
공 147
 
1.8%
리 124
 
1.5%
Other values (409) 5550
66.5%
Uppercase Letter
ValueCountFrequency (%)
G 13
16.2%
K 7
8.8%
E 7
8.8%
L 7
8.8%
P 6
 
7.5%
C 6
 
7.5%
B 5
 
6.2%
N 4
 
5.0%
S 4
 
5.0%
O 4
 
5.0%
Other values (10) 17
21.2%
Decimal Number
ValueCountFrequency (%)
2 22
40.0%
1 21
38.2%
9 5
 
9.1%
4 2
 
3.6%
7 2
 
3.6%
3 2
 
3.6%
6 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 3
50.0%
/ 2
33.3%
& 1
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
u 1
33.3%
b 1
33.3%
l 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 882
100.0%
Close Punctuation
ValueCountFrequency (%)
) 882
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8371
80.1%
Common 1996
 
19.1%
Latin 83
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 970
 
11.6%
이 302
 
3.6%
산 296
 
3.5%
아 267
 
3.2%
스 205
 
2.4%
업 169
 
2.0%
에 161
 
1.9%
장 159
 
1.9%
공 147
 
1.8%
리 124
 
1.5%
Other values (410) 5571
66.6%
Latin
ValueCountFrequency (%)
G 13
15.7%
K 7
 
8.4%
E 7
 
8.4%
L 7
 
8.4%
P 6
 
7.2%
C 6
 
7.2%
B 5
 
6.0%
N 4
 
4.8%
S 4
 
4.8%
O 4
 
4.8%
Other values (13) 20
24.1%
Common
ValueCountFrequency (%)
( 882
44.2%
) 882
44.2%
170
 
8.5%
2 22
 
1.1%
1 21
 
1.1%
9 5
 
0.3%
. 3
 
0.2%
4 2
 
0.1%
7 2
 
0.1%
3 2
 
0.1%
Other values (4) 5
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8350
79.9%
ASCII 2079
 
19.9%
None 21
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 970
 
11.6%
이 302
 
3.6%
산 296
 
3.5%
아 267
 
3.2%
스 205
 
2.5%
업 169
 
2.0%
에 161
 
1.9%
장 159
 
1.9%
공 147
 
1.8%
리 124
 
1.5%
Other values (409) 5550
66.5%
ASCII
ValueCountFrequency (%)
( 882
42.4%
) 882
42.4%
170
 
8.2%
2 22
 
1.1%
1 21
 
1.0%
G 13
 
0.6%
K 7
 
0.3%
E 7
 
0.3%
L 7
 
0.3%
P 6
 
0.3%
Other values (27) 62
 
3.0%
None
ValueCountFrequency (%)
㈜ 21
100.0%

소재지주소
Text

Distinct997
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2024-01-10T05:51:27.037832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length22.586364
Min length15

Characters and Unicode

Total characters29814
Distinct characters207
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

Unique705 ?
Unique (%)53.4%

Sample

1st row충청남도 아산시 풍기동 226
2nd row충청남도 아산시 온천동 220-16
3rd row충청남도 아산시 신동 279-10
4th row충청남도 아산시 배방읍 공수리 883
5th row충청남도 아산시 실옥동 242
ValueCountFrequency (%)
충청남도 1320
19.9%
아산시 1320
19.9%
둔포면 335
 
5.0%
음봉면 234
 
3.5%
영인면 146
 
2.2%
신창면 96
 
1.4%
석곡리 82
 
1.2%
산동리 78
 
1.2%
인주면 77
 
1.2%
배방읍 68
 
1.0%
Other values (1120) 2879
43.4%
2024-01-10T05:51:27.504371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6638
22.3%
산 1517
 
5.1%
남 1407
 
4.7%
도 1361
 
4.6%
아 1327
 
4.5%
시 1326
 
4.4%
청 1326
 
4.4%
충 1321
 
4.4%
1 1219
 
4.1%
리 1161
 
3.9%
Other values (197) 11211
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17116
57.4%
Space Separator 6638
 
22.3%
Decimal Number 5094
 
17.1%
Dash Punctuation 927
 
3.1%
Open Punctuation 18
 
0.1%
Close Punctuation 18
 
0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 1517
 
8.9%
남 1407
 
8.2%
도 1361
 
8.0%
아 1327
 
7.8%
시 1326
 
7.7%
청 1326
 
7.7%
충 1321
 
7.7%
리 1161
 
6.8%
면 1031
 
6.0%
신 375
 
2.2%
Other values (180) 4964
29.0%
Decimal Number
ValueCountFrequency (%)
1 1219
23.9%
2 703
13.8%
3 615
12.1%
5 422
 
8.3%
4 416
 
8.2%
6 408
 
8.0%
0 344
 
6.8%
8 335
 
6.6%
9 333
 
6.5%
7 299
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%
Space Separator
ValueCountFrequency (%)
6638
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 927
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17116
57.4%
Common 12695
42.6%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 1517
 
8.9%
남 1407
 
8.2%
도 1361
 
8.0%
아 1327
 
7.8%
시 1326
 
7.7%
청 1326
 
7.7%
충 1321
 
7.7%
리 1161
 
6.8%
면 1031
 
6.0%
신 375
 
2.2%
Other values (180) 4964
29.0%
Common
ValueCountFrequency (%)
6638
52.3%
1 1219
 
9.6%
- 927
 
7.3%
2 703
 
5.5%
3 615
 
4.8%
5 422
 
3.3%
4 416
 
3.3%
6 408
 
3.2%
0 344
 
2.7%
8 335
 
2.6%
Other values (4) 668
 
5.3%
Latin
ValueCountFrequency (%)
S 1
33.3%
G 1
33.3%
I 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17116
57.4%
ASCII 12698
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6638
52.3%
1 1219
 
9.6%
- 927
 
7.3%
2 703
 
5.5%
3 615
 
4.8%
5 422
 
3.3%
4 416
 
3.3%
6 408
 
3.2%
0 344
 
2.7%
8 335
 
2.6%
Other values (7) 671
 
5.3%
Hangul
ValueCountFrequency (%)
산 1517
 
8.9%
남 1407
 
8.2%
도 1361
 
8.0%
아 1327
 
7.8%
시 1326
 
7.7%
청 1326
 
7.7%
충 1321
 
7.7%
리 1161
 
6.8%
면 1031
 
6.0%
신 375
 
2.2%
Other values (180) 4964
29.0%

업종
Text

Distinct275
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
2024-01-10T05:51:27.759153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length12.144697
Min length1

Characters and Unicode

Total characters16031
Distinct characters269
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)7.1%

Sample

1st row식품 첨가물 제조업
2nd row병원
3rd row기타 비료 및 질소화합물 제조업
4th row조립금속제품 제조업 기계 및 가구 제외
5th row플라스틱제품 제조업
ValueCountFrequency (%)
제조업 733
 
16.9%
및 392
 
9.0%
기타 344
 
7.9%
자동차 210
 
4.8%
그외 130
 
3.0%
부품 93
 
2.1%
세차업 76
 
1.7%
운영업 63
 
1.4%
주유소 61
 
1.4%
생산업 56
 
1.3%
Other values (405) 2190
50.4%
2024-01-10T05:51:28.138302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3317
20.7%
업 1252
 
7.8%
제 1009
 
6.3%
조 873
 
5.4%
기 627
 
3.9%
품 448
 
2.8%
및 413
 
2.6%
차 379
 
2.4%
타 368
 
2.3%
자 305
 
1.9%
Other values (259) 7040
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12703
79.2%
Space Separator 3317
 
20.7%
Other Punctuation 9
 
0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1252
 
9.9%
제 1009
 
7.9%
조 873
 
6.9%
기 627
 
4.9%
품 448
 
3.5%
및 413
 
3.3%
차 379
 
3.0%
타 368
 
2.9%
자 305
 
2.4%
동 298
 
2.3%
Other values (256) 6731
53.0%
Space Separator
ValueCountFrequency (%)
3317
100.0%
Other Punctuation
ValueCountFrequency (%)
· 9
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12703
79.2%
Common 3328
 
20.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1252
 
9.9%
제 1009
 
7.9%
조 873
 
6.9%
기 627
 
4.9%
품 448
 
3.5%
및 413
 
3.3%
차 379
 
3.0%
타 368
 
2.9%
자 305
 
2.4%
동 298
 
2.3%
Other values (256) 6731
53.0%
Common
ValueCountFrequency (%)
3317
99.7%
· 9
 
0.3%
1 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12703
79.2%
ASCII 3319
 
20.7%
None 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3317
99.9%
1 2
 
0.1%
Hangul
ValueCountFrequency (%)
업 1252
 
9.9%
제 1009
 
7.9%
조 873
 
6.9%
기 627
 
4.9%
품 448
 
3.5%
및 413
 
3.3%
차 379
 
3.0%
타 368
 
2.9%
자 305
 
2.4%
동 298
 
2.3%
Other values (256) 6731
53.0%
None
ValueCountFrequency (%)
· 9
100.0%

종별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
5종
1033 
4종
259 
3종
 
28

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5종
2nd row5종
3rd row4종
4th row3종
5th row4종

Common Values

ValueCountFrequency (%)
5종 1033
78.3%
4종 259
 
19.6%
3종 28
 
2.1%

Length

2024-01-10T05:51:28.261530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:51:28.400136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 1033
78.3%
4종 259
 
19.6%
3종 28
 
2.1%

대기오염물질 발생량(톤/년)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct396
Distinct (%)59.4%
Missing653
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean9.6879715
Minimum0
Maximum3900
Zeros78
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size11.7 KiB
2024-01-10T05:51:28.592003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1795
median1.179
Q34.308
95-th percentile9.544
Maximum3900
Range3900
Interquartile range (IQR)4.1285

Descriptive statistics

Standard deviation151.65883
Coefficient of variation (CV)15.654343
Kurtosis653.0217
Mean9.6879715
Median Absolute Deviation (MAD)1.169
Skewness25.436814
Sum6461.877
Variance23000.4
MonotonicityNot monotonic
2024-01-10T05:51:28.849366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 78
 
5.9%
0.07 7
 
0.5%
0.02 7
 
0.5%
0.28 7
 
0.5%
0.01 7
 
0.5%
0.06 6
 
0.5%
0.03 6
 
0.5%
0.04 6
 
0.5%
0.63 5
 
0.4%
0.34 5
 
0.4%
Other values (386) 533
40.4%
(Missing) 653
49.5%
ValueCountFrequency (%)
0.0 78
5.9%
0.002 1
 
0.1%
0.004 4
 
0.3%
0.005 2
 
0.2%
0.006 1
 
0.1%
0.01 7
 
0.5%
0.018 1
 
0.1%
0.02 7
 
0.5%
0.025 1
 
0.1%
0.03 6
 
0.5%
ValueCountFrequency (%)
3900.0 1
0.1%
331.73 1
0.1%
171.7 1
0.1%
103.2 1
0.1%
62.6 1
0.1%
37.54 1
0.1%
30.06 1
0.1%
29.04 1
0.1%
19.79 1
0.1%
19.7 1
0.1%

폐수배출량(㎥/일)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct353
Distinct (%)54.1%
Missing667
Missing (%)50.5%
Infinite0
Infinite (%)0.0%
Mean21.21013
Minimum0
Maximum621
Zeros32
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size11.7 KiB
2024-01-10T05:51:29.019001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.046
Q11.42
median6
Q321
95-th percentile49.3338
Maximum621
Range621
Interquartile range (IQR)19.58

Descriptive statistics

Standard deviation57.989923
Coefficient of variation (CV)2.7340673
Kurtosis54.83615
Mean21.21013
Median Absolute Deviation (MAD)5.57
Skewness6.8237128
Sum13850.215
Variance3362.8312
MonotonicityNot monotonic
2024-01-10T05:51:29.159694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 32
 
2.4%
3.0 28
 
2.1%
2.0 15
 
1.1%
9.0 13
 
1.0%
24.0 12
 
0.9%
6.0 10
 
0.8%
12.0 10
 
0.8%
10.0 9
 
0.7%
0.3 9
 
0.7%
8.0 9
 
0.7%
Other values (343) 506
38.3%
(Missing) 667
50.5%
ValueCountFrequency (%)
0.0 32
2.4%
0.04 1
 
0.1%
0.05 1
 
0.1%
0.07 1
 
0.1%
0.08 2
 
0.2%
0.1 4
 
0.3%
0.1032 1
 
0.1%
0.12 1
 
0.1%
0.13 3
 
0.2%
0.14 2
 
0.2%
ValueCountFrequency (%)
621.0 1
0.1%
597.01 1
0.1%
525.16 1
0.1%
500.0 1
0.1%
390.3 1
0.1%
372.49 1
0.1%
360.7 1
0.1%
288.16 1
0.1%
277.0 1
0.1%
260.0 1
0.1%

등록일
Date

Distinct1010
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size10.4 KiB
Minimum1972-08-01 00:00:00
Maximum2021-01-13 00:00:00
2024-01-10T05:51:29.300961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:51:29.448246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-01-10T05:51:25.595250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:51:25.436981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:51:25.656304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:51:25.531928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:51:29.548138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분종별대기오염물질 발생량(톤/년)폐수배출량(㎥/일)
시설구분1.0000.259NaNNaN
종별0.2591.0000.0000.991
대기오염물질 발생량(톤/년)NaN0.0001.000NaN
폐수배출량(㎥/일)NaN0.991NaN1.000
2024-01-10T05:51:29.654130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분종별
시설구분1.0000.421
종별0.4211.000
2024-01-10T05:51:29.747003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대기오염물질 발생량(톤/년)폐수배출량(㎥/일)시설구분종별
대기오염물질 발생량(톤/년)1.000NaN1.0000.000
폐수배출량(㎥/일)NaN1.0001.0000.879
시설구분1.0001.0001.0000.421
종별0.0000.8790.4211.000

Missing values

2024-01-10T05:51:25.763455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:51:25.869069image/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.
2024-01-10T05:51:25.953968image/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

시설구분사업장명소재지주소업종종별대기오염물질 발생량(톤/년)폐수배출량(㎥/일)등록일
0대기배출시설(주)광일충청남도 아산시 풍기동 226식품 첨가물 제조업5종0.21<NA>1972-08-01
1대기배출시설현대병원충청남도 아산시 온천동 220-16병원5종1.203<NA>1973-09-07
2대기배출시설효성오앤비(주)충청남도 아산시 신동 279-10기타 비료 및 질소화합물 제조업4종3.82<NA>1982-09-16
3대기배출시설(주)신도리코충청남도 아산시 배방읍 공수리 883조립금속제품 제조업 기계 및 가구 제외3종19.79<NA>1984-12-08
4대기배출시설아일수지공업(주)충청남도 아산시 실옥동 242플라스틱제품 제조업4종3.56<NA>1986-06-19
5대기배출시설한라엔컴(주)충청남도 아산시 배방읍 갈매리 111-1비금속광물제품 제조업4종4.87<NA>1986-05-22
6대기배출시설우진특수도장충청남도 아산시 염치읍 석정리 31-11기타 조립금속제품 제조업4종3.22<NA>1986-08-02
7대기배출시설한일산업(주)아산공장충청남도 아산시 염치읍 염성리 155콘크리트 시멘트 및 플라스터 제품 제조업4종7.74<NA>1987-07-07
8대기배출시설(주)대승충청남도 아산시 도고면 기곡리 174-13숙박업4종9.2<NA>1987-09-04
9대기배출시설삼성레미콘(주)충청남도 아산시 배방읍 공수리 519콘크리트 시멘트 및 플라스터 제품 제조업4종6.09<NA>1991-08-19
시설구분사업장명소재지주소업종종별대기오염물질 발생량(톤/년)폐수배출량(㎥/일)등록일
1310폐수배출시설(주)지아이텍충청남도 아산시 둔포면 석곡리 2045주형 및 금형 제조업5종<NA>22.592020-11-23
1311폐수배출시설에이시스(주)충청남도 아산시 둔포면 석곡리 1488주형 및 금형 제조업5종<NA>2.862020-11-25
1312폐수배출시설(주)블루파인충청남도 아산시 선장면 선창리 264-12얼음 제조업5종<NA>19.62020-12-02
1313폐수배출시설장인열처리(주)2공장충청남도 아산시 둔포면 석곡리 1327금속 절삭기계 제조업5종<NA>3.052020-12-03
1314폐수배출시설(주)에이치엔에프충청남도 아산시 음봉면 쌍암리 26-2기체 펌프 및 압축기 제조업5종<NA>4.02020-12-11
1315폐수배출시설풍기동세차장충청남도 아산시 풍기동 3-1 외 7필지자동차 세차업5종<NA>20.02020-12-21
1316폐수배출시설삼미환경충청남도 아산시 음봉면 산동리 445-33비금속원료 재생업5종<NA>0.02020-12-21
1317폐수배출시설(주)유엠하이텍 아산공장충청남도 아산시 음봉면 신휴리 785그외 기타 자동차 부품 제조업5종<NA>11.32020-12-24
1318폐수배출시설미그린탕정주유소충청남도 아산시 탕정면 매곡리 607-75 외 6필지주유소 운영업5종<NA>35.02020-12-27
1319폐수배출시설동보테크(주)충청남도 아산시 음봉면 신휴리 421산업용 냉장 및 냉동 장비 제조업5종<NA>0.02021-01-13