Overview

Dataset statistics

Number of variables32
Number of observations10000
Missing cells387
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory291.0 B

Variable types

Numeric14
Categorical16
Text2

Dataset

Description수도법에 따라 분기마다 광역 또는 지방상수도에서 하천복류수를 원수로 사용하는 원수 수질 검사 결과 입니다. 제공항목 : 검사년도,검사분기,지역,취수장명,채수지점,수원,카드뮴,비소,시안,수은,납,크롬,유기인,폴리클로리네이티드비페닐,음이온 계면활성제,불소,셀레늄,암모니아성질소,질산성질소,카바릴,1-1-1_트리클로로에탄,테트라클로로에틸렌,트리클로로에틸렌,페놀,사염화탄소,1-2_디클로로에탄,디클로로메탄,벤젠,클로로포름,디에틸헥실프탈레이트,안티몬 * 상세자료조회는 아래 URL을 참고 해주시기 바랍니다. https://www.waternow.go.kr/web/lawData2/?pMENUID=96&ATTR_1=3102
URLhttps://www.data.go.kr/data/15093990/fileData.do

Alerts

수원 is highly imbalanced (60.5%)Imbalance
카드뮴 is highly imbalanced (98.1%)Imbalance
시안 is highly imbalanced (96.4%)Imbalance
수은 is highly imbalanced (96.4%)Imbalance
크롬 is highly imbalanced (96.8%)Imbalance
유기인 is highly imbalanced (96.4%)Imbalance
폴리클로리네이티드비페닐 is highly imbalanced (96.4%)Imbalance
카바릴 is highly imbalanced (98.3%)Imbalance
1-1-1_트리클로로에탄 is highly imbalanced (97.6%)Imbalance
테트라클로로에틸렌 is highly imbalanced (98.3%)Imbalance
트리클로로에틸렌 is highly imbalanced (97.9%)Imbalance
페놀 is highly imbalanced (98.1%)Imbalance
사염화탄소 is highly imbalanced (97.9%)Imbalance
벤젠 is highly imbalanced (97.5%)Imbalance
납 is highly skewed (γ1 = 28.23738289)Skewed
음이온 계면활성제 is highly skewed (γ1 = 41.109854)Skewed
불소 is highly skewed (γ1 = 42.51562682)Skewed
셀레늄 is highly skewed (γ1 = 80.74514216)Skewed
1-2_디클로로에탄 is highly skewed (γ1 = 25.9627794)Skewed
안티몬 is highly skewed (γ1 = 33.51024733)Skewed
연번 has unique valuesUnique
비소 has 9864 (98.6%) zerosZeros
납 has 9936 (99.4%) zerosZeros
음이온 계면활성제 has 9946 (99.5%) zerosZeros
불소 has 7738 (77.4%) zerosZeros
셀레늄 has 9939 (99.4%) zerosZeros
암모니아성질소 has 8317 (83.2%) zerosZeros
질산성질소 has 151 (1.5%) zerosZeros
1-2_디클로로에탄 has 9931 (99.3%) zerosZeros
디클로로메탄 has 9811 (98.1%) zerosZeros
클로로포름 has 8753 (87.5%) zerosZeros
디에틸헥실프탈레이트 has 9868 (98.7%) zerosZeros
안티몬 has 8792 (87.9%) zerosZeros

Reproduction

Analysis started2023-12-12 20:44:37.438670
Analysis finished2023-12-12 20:44:38.576731
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5049.1311
Minimum1
Maximum10096
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:38.687531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile506.95
Q12531.75
median5046.5
Q37571.25
95-th percentile9588.05
Maximum10096
Range10095
Interquartile range (IQR)5039.5

Descriptive statistics

Standard deviation2912.6585
Coefficient of variation (CV)0.57686332
Kurtosis-1.1991298
Mean5049.1311
Median Absolute Deviation (MAD)2520
Skewness-0.00025392535
Sum50491311
Variance8483579.7
MonotonicityNot monotonic
2023-12-13T05:44:38.864220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4378 1
 
< 0.1%
426 1
 
< 0.1%
9145 1
 
< 0.1%
7366 1
 
< 0.1%
1191 1
 
< 0.1%
3171 1
 
< 0.1%
38 1
 
< 0.1%
4116 1
 
< 0.1%
1264 1
 
< 0.1%
8287 1
 
< 0.1%
Other values (9990) 9990
99.9%
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 (%)
10096 1
< 0.1%
10095 1
< 0.1%
10094 1
< 0.1%
10093 1
< 0.1%
10092 1
< 0.1%
10091 1
< 0.1%
10090 1
< 0.1%
10089 1
< 0.1%
10088 1
< 0.1%
10087 1
< 0.1%

검사년도
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.0052
Minimum2015
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:39.008692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12016
median2018
Q32020
95-th percentile2021
Maximum2021
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0161794
Coefficient of variation (CV)0.00099909526
Kurtosis-1.2685866
Mean2018.0052
Median Absolute Deviation (MAD)2
Skewness0.01596341
Sum20180052
Variance4.0649795
MonotonicityNot monotonic
2023-12-13T05:44:39.135306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2018 1523
15.2%
2020 1513
15.1%
2021 1488
14.9%
2017 1456
14.6%
2015 1431
14.3%
2016 1426
14.3%
2019 1163
11.6%
ValueCountFrequency (%)
2015 1431
14.3%
2016 1426
14.3%
2017 1456
14.6%
2018 1523
15.2%
2019 1163
11.6%
2020 1513
15.1%
2021 1488
14.9%
ValueCountFrequency (%)
2021 1488
14.9%
2020 1513
15.1%
2019 1163
11.6%
2018 1523
15.2%
2017 1456
14.6%
2016 1426
14.3%
2015 1431
14.3%

검사분기
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1분기
2609 
2분기
2600 
4분기
2577 
3분기
2214 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1분기
2nd row3분기
3rd row1분기
4th row2분기
5th row4분기

Common Values

ValueCountFrequency (%)
1분기 2609
26.1%
2분기 2600
26.0%
4분기 2577
25.8%
3분기 2214
22.1%

Length

2023-12-13T05:44:39.295480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:39.422225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1분기 2609
26.1%
2분기 2600
26.0%
4분기 2577
25.8%
3분기 2214
22.1%

지역
Text

Distinct92
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:44:39.709572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.5129
Min length5

Characters and Unicode

Total characters75129
Distinct characters97
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 양평군
2nd row경상북도 의성군
3rd row충청남도 공주시
4th row강원도 동해시
5th row강원도 철원군
ValueCountFrequency (%)
경상북도 3271
 
16.8%
강원도 2802
 
14.4%
경상남도 1132
 
5.8%
전라북도 554
 
2.8%
충청북도 505
 
2.6%
정선군 496
 
2.5%
경기도 494
 
2.5%
전라남도 427
 
2.2%
홍천군 373
 
1.9%
봉화군 322
 
1.7%
Other values (90) 9075
46.7%
2023-12-13T05:44:40.201089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 9451
 
12.6%
9451
 
12.6%
군 6511
 
8.7%
경 5295
 
7.0%
상 4601
 
6.1%
북 4330
 
5.8%
원 3406
 
4.5%
시 3363
 
4.5%
강 2939
 
3.9%
남 2001
 
2.7%
Other values (87) 23781
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65678
87.4%
Space Separator 9451
 
12.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9451
14.4%
군 6511
 
9.9%
경 5295
 
8.1%
상 4601
 
7.0%
북 4330
 
6.6%
원 3406
 
5.2%
시 3363
 
5.1%
강 2939
 
4.5%
남 2001
 
3.0%
천 1649
 
2.5%
Other values (86) 22132
33.7%
Space Separator
ValueCountFrequency (%)
9451
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65678
87.4%
Common 9451
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9451
14.4%
군 6511
 
9.9%
경 5295
 
8.1%
상 4601
 
7.0%
북 4330
 
6.6%
원 3406
 
5.2%
시 3363
 
5.1%
강 2939
 
4.5%
남 2001
 
3.0%
천 1649
 
2.5%
Other values (86) 22132
33.7%
Common
ValueCountFrequency (%)
9451
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65678
87.4%
ASCII 9451
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 9451
14.4%
군 6511
 
9.9%
경 5295
 
8.1%
상 4601
 
7.0%
북 4330
 
6.6%
원 3406
 
5.2%
시 3363
 
5.1%
강 2939
 
4.5%
남 2001
 
3.0%
천 1649
 
2.5%
Other values (86) 22132
33.7%
ASCII
ValueCountFrequency (%)
9451
100.0%

취수장명
Text

Distinct234
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T05:44:40.624137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.3284
Min length2

Characters and Unicode

Total characters23284
Distinct characters172
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row양동
2nd row금성
3rd row유구
4th row쇄운
5th row통합
ValueCountFrequency (%)
강진 105
 
1.1%
영해 83
 
0.8%
창암 83
 
0.8%
안덕 81
 
0.8%
이사천 78
 
0.8%
고령 78
 
0.8%
서화 77
 
0.8%
고사 77
 
0.8%
덕천 76
 
0.8%
성리 62
 
0.6%
Other values (224) 9200
92.0%
2023-12-13T05:44:41.169749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 929
 
4.0%
천 791
 
3.4%
산 731
 
3.1%
동 720
 
3.1%
사 527
 
2.3%
성 512
 
2.2%
평 505
 
2.2%
남 413
 
1.8%
암 350
 
1.5%
창 349
 
1.5%
Other values (162) 17457
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22081
94.8%
Decimal Number 597
 
2.6%
Open Punctuation 277
 
1.2%
Close Punctuation 277
 
1.2%
Other Punctuation 52
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 929
 
4.2%
천 791
 
3.6%
산 731
 
3.3%
동 720
 
3.3%
사 527
 
2.4%
성 512
 
2.3%
평 505
 
2.3%
남 413
 
1.9%
암 350
 
1.6%
창 349
 
1.6%
Other values (156) 16254
73.6%
Decimal Number
ValueCountFrequency (%)
1 265
44.4%
2 243
40.7%
6 89
 
14.9%
Open Punctuation
ValueCountFrequency (%)
( 277
100.0%
Close Punctuation
ValueCountFrequency (%)
) 277
100.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22081
94.8%
Common 1203
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 929
 
4.2%
천 791
 
3.6%
산 731
 
3.3%
동 720
 
3.3%
사 527
 
2.4%
성 512
 
2.3%
평 505
 
2.3%
남 413
 
1.9%
암 350
 
1.6%
창 349
 
1.6%
Other values (156) 16254
73.6%
Common
ValueCountFrequency (%)
( 277
23.0%
) 277
23.0%
1 265
22.0%
2 243
20.2%
6 89
 
7.4%
, 52
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22081
94.8%
ASCII 1203
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 929
 
4.2%
천 791
 
3.6%
산 731
 
3.3%
동 720
 
3.3%
사 527
 
2.4%
성 512
 
2.3%
평 505
 
2.3%
남 413
 
1.9%
암 350
 
1.6%
창 349
 
1.6%
Other values (156) 16254
73.6%
ASCII
ValueCountFrequency (%)
( 277
23.0%
) 277
23.0%
1 265
22.0%
2 243
20.2%
6 89
 
7.4%
, 52
 
4.3%

채수지점
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
취수구
5540 
착수정
4460 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취수구
2nd row착수정
3rd row착수정
4th row착수정
5th row착수정

Common Values

ValueCountFrequency (%)
취수구 5540
55.4%
착수정 4460
44.6%

Length

2023-12-13T05:44:41.314253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:41.445547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취수구 5540
55.4%
착수정 4460
44.6%

수원
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
복류수
8038 
하천수
1504 
강변여과수
 
303
계곡수
 
141
지표수
 
14

Length

Max length5
Median length3
Mean length3.0606
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
복류수 8038
80.4%
하천수 1504
 
15.0%
강변여과수 303
 
3.0%
계곡수 141
 
1.4%
지표수 14
 
0.1%

Length

2023-12-13T05:44:41.609773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:41.731271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
복류수 8038
80.4%
하천수 1504
 
15.0%
강변여과수 303
 
3.0%
계곡수 141
 
1.4%
지표수 14
 
0.1%

카드뮴
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9952 
<NA>
 
37
0.004
 
5
0.002
 
4
0.005
 
1

Length

Max length5
Median length3
Mean length3.0059
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9952
99.5%
<NA> 37
 
0.4%
0.004 5
 
0.1%
0.002 4
 
< 0.1%
0.005 1
 
< 0.1%
0.003 1
 
< 0.1%

Length

2023-12-13T05:44:41.886354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:42.007763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9952
99.5%
na 37
 
0.4%
0.004 5
 
< 0.1%
0.002 4
 
< 0.1%
0.005 1
 
< 0.1%
0.003 1
 
< 0.1%

비소
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean7.4924714 × 10-5
Minimum0
Maximum0.019
Zeros9864
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:42.128030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.019
Range0.019
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00081158266
Coefficient of variation (CV)10.831975
Kurtosis173.64197
Mean7.4924714 × 10-5
Median Absolute Deviation (MAD)0
Skewness12.424542
Sum0.7464
Variance6.5866642 × 10-7
MonotonicityNot monotonic
2023-12-13T05:44:42.265378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 9864
98.6%
0.006 24
 
0.2%
0.005 23
 
0.2%
0.007 13
 
0.1%
0.008 10
 
0.1%
0.012 7
 
0.1%
0.01 6
 
0.1%
0.011 5
 
0.1%
0.013 4
 
< 0.1%
0.014 2
 
< 0.1%
Other values (4) 4
 
< 0.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9864
98.6%
0.0011 1
 
< 0.1%
0.0013 1
 
< 0.1%
0.005 23
 
0.2%
0.006 24
 
0.2%
0.007 13
 
0.1%
0.008 10
 
0.1%
0.01 6
 
0.1%
0.011 5
 
0.1%
0.012 7
 
0.1%
ValueCountFrequency (%)
0.019 1
 
< 0.1%
0.016 1
 
< 0.1%
0.014 2
 
< 0.1%
0.013 4
 
< 0.1%
0.012 7
 
0.1%
0.011 5
 
0.1%
0.01 6
 
0.1%
0.008 10
0.1%
0.007 13
0.1%
0.006 24
0.2%

시안
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9962 
<NA>
 
38

Length

Max length4
Median length1
Mean length1.0114
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9962
99.6%
<NA> 38
 
0.4%

Length

2023-12-13T05:44:42.421517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:42.526122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9962
99.6%
na 38
 
0.4%

수은
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9962 
<NA>
 
38

Length

Max length4
Median length1
Mean length1.0114
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9962
99.6%
<NA> 38
 
0.4%

Length

2023-12-13T05:44:42.633631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:42.732722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9962
99.6%
na 38
 
0.4%

납
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.5559125 × 10-5
Minimum0
Maximum0.017
Zeros9936
Zeros (%)99.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:42.804859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.017
Range0.017
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00034630413
Coefficient of variation (CV)22.257301
Kurtosis975.84903
Mean1.5559125 × 10-5
Median Absolute Deviation (MAD)0
Skewness28.237383
Sum0.155
Variance1.1992655 × 10-7
MonotonicityNot monotonic
2023-12-13T05:44:42.925699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 9936
99.4%
0.005 8
 
0.1%
0.006 6
 
0.1%
0.002 5
 
0.1%
0.007 3
 
< 0.1%
0.01 1
 
< 0.1%
0.009 1
 
< 0.1%
0.017 1
 
< 0.1%
0.012 1
 
< 0.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9936
99.4%
0.002 5
 
0.1%
0.005 8
 
0.1%
0.006 6
 
0.1%
0.007 3
 
< 0.1%
0.009 1
 
< 0.1%
0.01 1
 
< 0.1%
0.012 1
 
< 0.1%
0.017 1
 
< 0.1%
ValueCountFrequency (%)
0.017 1
 
< 0.1%
0.012 1
 
< 0.1%
0.01 1
 
< 0.1%
0.009 1
 
< 0.1%
0.007 3
 
< 0.1%
0.006 6
 
0.1%
0.005 8
 
0.1%
0.002 5
 
0.1%
0.0 9936
99.4%

크롬
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9924 
<NA>
 
39
0.01
 
34
0.02
 
2
0.0005
 
1

Length

Max length6
Median length3
Mean length3.0078
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9924
99.2%
<NA> 39
 
0.4%
0.01 34
 
0.3%
0.02 2
 
< 0.1%
0.0005 1
 
< 0.1%

Length

2023-12-13T05:44:43.055535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:43.155227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9924
99.2%
na 39
 
0.4%
0.01 34
 
0.3%
0.02 2
 
< 0.1%
0.0005 1
 
< 0.1%

유기인
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9962 
<NA>
 
38

Length

Max length4
Median length1
Mean length1.0114
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9962
99.6%
<NA> 38
 
0.4%

Length

2023-12-13T05:44:43.265558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:43.364287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9962
99.6%
na 38
 
0.4%

폴리클로리네이티드비페닐
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9962 
<NA>
 
38

Length

Max length4
Median length1
Mean length1.0114
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9962
99.6%
<NA> 38
 
0.4%

Length

2023-12-13T05:44:43.460412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:43.559941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9962
99.6%
na 38
 
0.4%

음이온 계면활성제
Real number (ℝ)

SKEWED  ZEROS 

Distinct7
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.00010339289
Minimum0
Maximum0.2
Zeros9946
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:43.650694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.2
Range0.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0032061566
Coefficient of variation (CV)31.009449
Kurtosis2010.4553
Mean0.00010339289
Median Absolute Deviation (MAD)0
Skewness41.109854
Sum1.03
Variance1.027944 × 10-5
MonotonicityNot monotonic
2023-12-13T05:44:43.791359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 9946
99.5%
0.1 5
 
0.1%
0.02 4
 
< 0.1%
0.05 3
 
< 0.1%
0.03 2
 
< 0.1%
0.2 1
 
< 0.1%
0.04 1
 
< 0.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9946
99.5%
0.02 4
 
< 0.1%
0.03 2
 
< 0.1%
0.04 1
 
< 0.1%
0.05 3
 
< 0.1%
0.1 5
 
0.1%
0.2 1
 
< 0.1%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.1 5
 
0.1%
0.05 3
 
< 0.1%
0.04 1
 
< 0.1%
0.03 2
 
< 0.1%
0.02 4
 
< 0.1%
0.0 9946
99.5%

불소
Real number (ℝ)

SKEWED  ZEROS 

Distinct97
Distinct (%)1.0%
Missing25
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.05872381
Minimum0
Maximum17.5
Zeros7738
Zeros (%)77.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:43.968334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.27
Maximum17.5
Range17.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.30415617
Coefficient of variation (CV)5.1794352
Kurtosis2263.186
Mean0.05872381
Median Absolute Deviation (MAD)0
Skewness42.515627
Sum585.77
Variance0.092510974
MonotonicityNot monotonic
2023-12-13T05:44:44.115510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7738
77.4%
0.2 237
 
2.4%
0.17 187
 
1.9%
0.16 180
 
1.8%
0.18 167
 
1.7%
0.15 136
 
1.4%
0.19 109
 
1.1%
0.22 109
 
1.1%
0.21 107
 
1.1%
0.24 96
 
1.0%
Other values (87) 909
 
9.1%
ValueCountFrequency (%)
0.0 7738
77.4%
0.01 1
 
< 0.1%
0.02 1
 
< 0.1%
0.05 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 2
 
< 0.1%
0.08 9
 
0.1%
0.09 8
 
0.1%
0.1 38
 
0.4%
0.11 31
 
0.3%
ValueCountFrequency (%)
17.5 1
< 0.1%
17.4 1
< 0.1%
8.2 1
< 0.1%
7.6 1
< 0.1%
7.22 1
< 0.1%
2.8 1
< 0.1%
1.5 1
< 0.1%
1.44 1
< 0.1%
1.42 1
< 0.1%
1.4 1
< 0.1%

셀레늄
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean2.4994981 × 10-5
Minimum0
Maximum0.09
Zeros9939
Zeros (%)99.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:44.251102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.09
Range0.09
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00097384613
Coefficient of variation (CV)38.961667
Kurtosis7337.8084
Mean2.4994981 × 10-5
Median Absolute Deviation (MAD)0
Skewness80.745142
Sum0.249
Variance9.4837629 × 10-7
MonotonicityNot monotonic
2023-12-13T05:44:44.364515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 9939
99.4%
0.006 10
 
0.1%
0.005 4
 
< 0.1%
0.007 3
 
< 0.1%
0.01 2
 
< 0.1%
0.008 1
 
< 0.1%
0.09 1
 
< 0.1%
0.011 1
 
< 0.1%
0.019 1
 
< 0.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9939
99.4%
0.005 4
 
< 0.1%
0.006 10
 
0.1%
0.007 3
 
< 0.1%
0.008 1
 
< 0.1%
0.01 2
 
< 0.1%
0.011 1
 
< 0.1%
0.019 1
 
< 0.1%
0.09 1
 
< 0.1%
ValueCountFrequency (%)
0.09 1
 
< 0.1%
0.019 1
 
< 0.1%
0.011 1
 
< 0.1%
0.01 2
 
< 0.1%
0.008 1
 
< 0.1%
0.007 3
 
< 0.1%
0.006 10
 
0.1%
0.005 4
 
< 0.1%
0.0 9939
99.4%

암모니아성질소
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)1.3%
Missing37
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.021006725
Minimum0
Maximum4.5
Zeros8317
Zeros (%)83.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:44.483955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.08
Maximum4.5
Range4.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1417462
Coefficient of variation (CV)6.7476581
Kurtosis328.35065
Mean0.021006725
Median Absolute Deviation (MAD)0
Skewness15.992415
Sum209.29
Variance0.020091985
MonotonicityNot monotonic
2023-12-13T05:44:44.615694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8317
83.2%
0.01 295
 
2.9%
0.02 260
 
2.6%
0.03 175
 
1.8%
0.04 116
 
1.2%
0.06 90
 
0.9%
0.05 74
 
0.7%
0.08 66
 
0.7%
0.07 61
 
0.6%
0.09 48
 
0.5%
Other values (118) 461
 
4.6%
ValueCountFrequency (%)
0.0 8317
83.2%
0.01 295
 
2.9%
0.011 3
 
< 0.1%
0.012 5
 
0.1%
0.013 1
 
< 0.1%
0.014 2
 
< 0.1%
0.015 3
 
< 0.1%
0.016 3
 
< 0.1%
0.017 3
 
< 0.1%
0.018 3
 
< 0.1%
ValueCountFrequency (%)
4.5 1
< 0.1%
3.45 2
< 0.1%
3.3 1
< 0.1%
2.99 1
< 0.1%
2.75 2
< 0.1%
2.59 1
< 0.1%
2.5 1
< 0.1%
2.4 2
< 0.1%
2.36 1
< 0.1%
2.35 1
< 0.1%

질산성질소
Real number (ℝ)

ZEROS 

Distinct169
Distinct (%)1.7%
Missing4
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.847766
Minimum0
Maximum20.8
Zeros151
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:44.753447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q11
median1.6
Q32.4
95-th percentile4.2
Maximum20.8
Range20.8
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.3827056
Coefficient of variation (CV)0.74831206
Kurtosis21.524707
Mean1.847766
Median Absolute Deviation (MAD)0.7
Skewness2.9916186
Sum18470.269
Variance1.9118747
MonotonicityNot monotonic
2023-12-13T05:44:45.159272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2 421
 
4.2%
1.4 417
 
4.2%
0.9 414
 
4.1%
1.6 407
 
4.1%
1.3 397
 
4.0%
1.0 394
 
3.9%
1.1 388
 
3.9%
1.5 383
 
3.8%
2.0 380
 
3.8%
0.8 375
 
3.8%
Other values (159) 6020
60.2%
ValueCountFrequency (%)
0.0 151
1.5%
0.09 1
 
< 0.1%
0.1 53
 
0.5%
0.13 1
 
< 0.1%
0.14 1
 
< 0.1%
0.19 1
 
< 0.1%
0.2 160
1.6%
0.3 169
1.7%
0.4 231
2.3%
0.5 216
2.2%
ValueCountFrequency (%)
20.8 1
< 0.1%
20.7 1
< 0.1%
18.0 1
< 0.1%
17.9 1
< 0.1%
17.2 2
< 0.1%
15.3 2
< 0.1%
15.0 1
< 0.1%
14.5 1
< 0.1%
14.0 1
< 0.1%
11.6 2
< 0.1%

카바릴
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9957 
<NA>
 
39
0.5
 
1
9.0
 
1
0.007
 
1

Length

Max length5
Median length3
Mean length3.0043
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9957
99.6%
<NA> 39
 
0.4%
0.5 1
 
< 0.1%
9.0 1
 
< 0.1%
0.007 1
 
< 0.1%
0.014 1
 
< 0.1%

Length

2023-12-13T05:44:45.283871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:45.382491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9957
99.6%
na 39
 
0.4%
0.5 1
 
< 0.1%
9.0 1
 
< 0.1%
0.007 1
 
< 0.1%
0.014 1
 
< 0.1%

1-1-1_트리클로로에탄
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9946 
<NA>
 
39
0.001
 
10
0.002
 
4
0.013
 
1

Length

Max length5
Median length3
Mean length3.0069
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9946
99.5%
<NA> 39
 
0.4%
0.001 10
 
0.1%
0.002 4
 
< 0.1%
0.013 1
 
< 0.1%

Length

2023-12-13T05:44:45.492806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:45.607705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9946
99.5%
na 39
 
0.4%
0.001 10
 
0.1%
0.002 4
 
< 0.1%
0.013 1
 
< 0.1%

테트라클로로에틸렌
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9959 
<NA>
 
38
0.001
 
1
0.002
 
1
0.003
 
1

Length

Max length5
Median length3
Mean length3.0044
Min length3

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9959
99.6%
<NA> 38
 
0.4%
0.001 1
 
< 0.1%
0.002 1
 
< 0.1%
0.003 1
 
< 0.1%

Length

2023-12-13T05:44:45.723687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:45.820798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9959
99.6%
na 38
 
0.4%
0.001 1
 
< 0.1%
0.002 1
 
< 0.1%
0.003 1
 
< 0.1%

트리클로로에틸렌
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9946 
<NA>
 
38
0.002
 
11
0.003
 
2
0.001
 
2

Length

Max length5
Median length3
Mean length3.007
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9946
99.5%
<NA> 38
 
0.4%
0.002 11
 
0.1%
0.003 2
 
< 0.1%
0.001 2
 
< 0.1%
0.005 1
 
< 0.1%

Length

2023-12-13T05:44:45.932377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:46.026714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9946
99.5%
na 38
 
0.4%
0.002 11
 
0.1%
0.003 2
 
< 0.1%
0.001 2
 
< 0.1%
0.005 1
 
< 0.1%

페놀
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9957 
<NA>
 
38
0.005
 
2
0.007
 
2
0.001
 
1

Length

Max length5
Median length3
Mean length3.0048
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9957
99.6%
<NA> 38
 
0.4%
0.005 2
 
< 0.1%
0.007 2
 
< 0.1%
0.001 1
 
< 0.1%

Length

2023-12-13T05:44:46.145552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:46.245746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9957
99.6%
na 38
 
0.4%
0.005 2
 
< 0.1%
0.007 2
 
< 0.1%
0.001 1
 
< 0.1%

사염화탄소
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9957 
<NA>
 
38
0.001
 
4
0.002
 
1

Length

Max length5
Median length3
Mean length3.0048
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9957
99.6%
<NA> 38
 
0.4%
0.001 4
 
< 0.1%
0.002 1
 
< 0.1%

Length

2023-12-13T05:44:46.349463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:46.444690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9957
99.6%
na 38
 
0.4%
0.001 4
 
< 0.1%
0.002 1
 
< 0.1%

1-2_디클로로에탄
Real number (ℝ)

SKEWED  ZEROS 

Distinct8
Distinct (%)0.1%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean5.9927725 × 10-6
Minimum0
Maximum0.005
Zeros9931
Zeros (%)99.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:46.525900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.005
Range0.005
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00012273538
Coefficient of variation (CV)20.480567
Kurtosis801.88539
Mean5.9927725 × 10-6
Median Absolute Deviation (MAD)0
Skewness25.962779
Sum0.0597
Variance1.5063973 × 10-8
MonotonicityNot monotonic
2023-12-13T05:44:46.619069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 9931
99.3%
0.001 12
 
0.1%
0.002 9
 
0.1%
0.003 5
 
0.1%
0.005 2
 
< 0.1%
0.0017 1
 
< 0.1%
0.0016 1
 
< 0.1%
0.0014 1
 
< 0.1%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9931
99.3%
0.001 12
 
0.1%
0.0014 1
 
< 0.1%
0.0016 1
 
< 0.1%
0.0017 1
 
< 0.1%
0.002 9
 
0.1%
0.003 5
 
0.1%
0.005 2
 
< 0.1%
ValueCountFrequency (%)
0.005 2
 
< 0.1%
0.003 5
 
0.1%
0.002 9
 
0.1%
0.0017 1
 
< 0.1%
0.0016 1
 
< 0.1%
0.0014 1
 
< 0.1%
0.001 12
 
0.1%
0.0 9931
99.3%

디클로로메탄
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)0.2%
Missing36
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean6.7041349 × 10-5
Minimum0
Maximum0.019
Zeros9811
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:46.713781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.019
Range0.019
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00069289105
Coefficient of variation (CV)10.335279
Kurtosis311.4835
Mean6.7041349 × 10-5
Median Absolute Deviation (MAD)0
Skewness15.714405
Sum0.668
Variance4.80098 × 10-7
MonotonicityNot monotonic
2023-12-13T05:44:46.809462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 9811
98.1%
0.003 47
 
0.5%
0.002 34
 
0.3%
0.004 17
 
0.2%
0.005 13
 
0.1%
0.001 10
 
0.1%
0.006 9
 
0.1%
0.007 4
 
< 0.1%
0.013 4
 
< 0.1%
0.008 4
 
< 0.1%
Other values (5) 11
 
0.1%
(Missing) 36
 
0.4%
ValueCountFrequency (%)
0.0 9811
98.1%
0.001 10
 
0.1%
0.002 34
 
0.3%
0.003 47
 
0.5%
0.004 17
 
0.2%
0.005 13
 
0.1%
0.006 9
 
0.1%
0.007 4
 
< 0.1%
0.008 4
 
< 0.1%
0.009 3
 
< 0.1%
ValueCountFrequency (%)
0.019 2
 
< 0.1%
0.016 4
 
< 0.1%
0.013 4
 
< 0.1%
0.011 1
 
< 0.1%
0.01 1
 
< 0.1%
0.009 3
 
< 0.1%
0.008 4
 
< 0.1%
0.007 4
 
< 0.1%
0.006 9
0.1%
0.005 13
0.1%

벤젠
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0.0
9951 
<NA>
 
37
0.001
 
6
0.002
 
6

Length

Max length5
Median length3
Mean length3.0061
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 9951
99.5%
<NA> 37
 
0.4%
0.001 6
 
0.1%
0.002 6
 
0.1%

Length

2023-12-13T05:44:46.926046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:44:47.031239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 9951
99.5%
na 37
 
0.4%
0.001 6
 
0.1%
0.002 6
 
0.1%

클로로포름
Real number (ℝ)

ZEROS 

Distinct56
Distinct (%)0.6%
Missing23
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.00095680064
Minimum0
Maximum0.138
Zeros8753
Zeros (%)87.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:47.131034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.005
Maximum0.138
Range0.138
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0044601099
Coefficient of variation (CV)4.661483
Kurtosis145.98154
Mean0.00095680064
Median Absolute Deviation (MAD)0
Skewness9.2500111
Sum9.546
Variance1.989258 × 10-5
MonotonicityNot monotonic
2023-12-13T05:44:47.268889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8753
87.5%
0.002 254
 
2.5%
0.001 225
 
2.2%
0.004 115
 
1.1%
0.003 111
 
1.1%
0.005 61
 
0.6%
0.006 40
 
0.4%
0.008 39
 
0.4%
0.007 38
 
0.4%
0.01 33
 
0.3%
Other values (46) 308
 
3.1%
ValueCountFrequency (%)
0.0 8753
87.5%
0.001 225
 
2.2%
0.002 254
 
2.5%
0.003 111
 
1.1%
0.004 115
 
1.1%
0.005 61
 
0.6%
0.006 40
 
0.4%
0.007 38
 
0.4%
0.008 39
 
0.4%
0.009 20
 
0.2%
ValueCountFrequency (%)
0.138 1
 
< 0.1%
0.072 1
 
< 0.1%
0.064 1
 
< 0.1%
0.063 1
 
< 0.1%
0.061 1
 
< 0.1%
0.059 1
 
< 0.1%
0.056 3
< 0.1%
0.052 2
< 0.1%
0.051 1
 
< 0.1%
0.05 1
 
< 0.1%

디에틸헥실프탈레이트
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)0.3%
Missing38
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean2.6758683 × 10-5
Minimum0
Maximum0.0074
Zeros9868
Zeros (%)98.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:47.387225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.0074
Range0.0074
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00031032292
Coefficient of variation (CV)11.597092
Kurtosis184.86035
Mean2.6758683 × 10-5
Median Absolute Deviation (MAD)0
Skewness12.985062
Sum0.26657
Variance9.6300315 × 10-8
MonotonicityNot monotonic
2023-12-13T05:44:47.512789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 9868
98.7%
0.004 15
 
0.1%
0.001 11
 
0.1%
0.003 9
 
0.1%
0.002 7
 
0.1%
0.0029 5
 
0.1%
0.0002 5
 
0.1%
0.005 4
 
< 0.1%
0.0026 4
 
< 0.1%
0.0027 3
 
< 0.1%
Other values (21) 31
 
0.3%
(Missing) 38
 
0.4%
ValueCountFrequency (%)
0.0 9868
98.7%
0.0001 2
 
< 0.1%
0.0002 5
 
0.1%
0.0003 2
 
< 0.1%
0.0004 1
 
< 0.1%
0.001 11
 
0.1%
0.002 7
 
0.1%
0.0025 1
 
< 0.1%
0.0026 4
 
< 0.1%
0.0027 3
 
< 0.1%
ValueCountFrequency (%)
0.0074 1
 
< 0.1%
0.0061 1
 
< 0.1%
0.0059 1
 
< 0.1%
0.0058 1
 
< 0.1%
0.005 4
 
< 0.1%
0.0043 1
 
< 0.1%
0.0042 1
 
< 0.1%
0.004 15
0.1%
0.0039 1
 
< 0.1%
0.0037 2
 
< 0.1%

안티몬
Real number (ℝ)

SKEWED  ZEROS 

Distinct119
Distinct (%)1.2%
Missing34
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean8.6388521 × 10-5
Minimum0
Maximum0.04
Zeros8792
Zeros (%)87.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:44:47.658690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0005
Maximum0.04
Range0.04
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00062607124
Coefficient of variation (CV)7.2471578
Kurtosis1811.6619
Mean8.6388521 × 10-5
Median Absolute Deviation (MAD)0
Skewness33.510247
Sum0.860948
Variance3.919652 × 10-7
MonotonicityNot monotonic
2023-12-13T05:44:47.808835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8792
87.9%
0.0001 110
 
1.1%
0.0005 97
 
1.0%
0.0004 73
 
0.7%
0.0006 60
 
0.6%
0.001 55
 
0.5%
7e-05 46
 
0.5%
0.0007 44
 
0.4%
8e-05 40
 
0.4%
6e-05 39
 
0.4%
Other values (109) 610
 
6.1%
ValueCountFrequency (%)
0.0 8792
87.9%
9e-06 2
 
< 0.1%
2e-05 1
 
< 0.1%
3e-05 1
 
< 0.1%
5e-05 38
 
0.4%
6e-05 39
 
0.4%
7e-05 46
 
0.5%
8e-05 40
 
0.4%
9e-05 23
 
0.2%
0.0001 110
 
1.1%
ValueCountFrequency (%)
0.04 1
 
< 0.1%
0.02 1
 
< 0.1%
0.012 1
 
< 0.1%
0.011 1
 
< 0.1%
0.0097 1
 
< 0.1%
0.008 3
< 0.1%
0.0073 1
 
< 0.1%
0.007 4
< 0.1%
0.0065 2
< 0.1%
0.006 4
< 0.1%

Sample

연번검사년도검사분기지역취수장명채수지점수원카드뮴비소시안수은납크롬유기인폴리클로리네이티드비페닐음이온 계면활성제불소셀레늄암모니아성질소질산성질소카바릴1-1-1_트리클로로에탄테트라클로로에틸렌트리클로로에틸렌페놀사염화탄소1-2_디클로로에탄디클로로메탄벤젠클로로포름디에틸헥실프탈레이트안티몬
4377437820181분기경기도 양평군양동취수구복류수0.00.0000.00.0000.00.00.00.03.60.00.00.00.00.00.00.00.00.00.00.00.001
2407240820163분기경상북도 의성군금성착수정복류수0.00.0000.00.0000.00.00.00.01.60.00.00.00.00.00.00.00.00.00.00.00.0
3040304120171분기충청남도 공주시유구착수정복류수0.00.0000.00.0000.00.00.00.021.80.00.00.00.00.00.00.00.00.00.00.00.0
6310631120192분기강원도 동해시쇄운착수정복류수0.00.0000.00.0000.00.00.00.021.70.00.00.00.00.00.00.00.00.00.0020.00.00012
8314831520204분기강원도 철원군통합착수정복류수0.00.0000.00.0000.00.170.00.02.10.00.00.00.00.00.00.00.00.00.0040.00.0
1159116020154분기강원도 홍천군태학취수구복류수0.00.0000.00.0000.00.00.00.03.80.00.00.00.00.00.00.00.00.00.00.00.0
6526652720192분기경상북도 경산시경산취수구하천수0.00.0000.00.0000.00.210.00.00.80.00.00.00.00.00.00.00.00.00.00.00.0
100651006620214분기경상남도 산청군산청,생초취수구복류수0.00.0000.00.0000.00.00.00.01.70.00.00.00.00.00.00.00.00.00.00.00.0
8487848820204분기경상북도 영양군영양착수정복류수0.00.0000.00.0000.00.00.00.01.00.00.00.00.00.00.00.00.00.00.00.00.0
5380538120183분기경상북도 청송군부남취수구복류수0.00.0000.00.0000.00.00.00.01.90.00.00.00.00.00.00.00.00.00.00.00.0
연번검사년도검사분기지역취수장명채수지점수원카드뮴비소시안수은납크롬유기인폴리클로리네이티드비페닐음이온 계면활성제불소셀레늄암모니아성질소질산성질소카바릴1-1-1_트리클로로에탄테트라클로로에틸렌트리클로로에틸렌페놀사염화탄소1-2_디클로로에탄디클로로메탄벤젠클로로포름디에틸헥실프탈레이트안티몬
3644364520173분기강원도 춘천시소양취수구하천수0.00.0000.00.0000.00.00.00.01.60.00.00.00.00.00.00.00.00.00.00.00.00006
7437743820201분기수자원공사덕소취수구하천수0.00.0000.00.0000.00.00.00.02.20.00.00.00.00.00.00.00.00.00.00.00.0
9804980520214분기강원도 평창군평창취수구복류수0.00.0000.00.0000.00.00.00.04.20.00.00.00.00.00.00.00.00.00.00.00.0
3173317420171분기경상북도 예천군용궁취수구복류수0.00.0000.00.0000.00.140.00.021.40.00.00.00.00.00.00.00.00.00.00.00.0
2353235420163분기전라남도 보성군득량착수정복류수0.00.0000.00.0000.00.00.00.00.2<NA><NA>0.00.00.00.00.00.00.00.00.00.0
3719372020173분기강원도 양구군동면취수구복류수0.00.0000.00.0000.00.00.00.00.50.00.00.00.00.00.00.00.00.00.00.00.0
5913591420191분기경기도 연천군연천취수구하천수0.00.0000.00.0000.00.00.00.01.30.00.00.00.00.00.00.00.00.00.0020.0040.0
4348434920174분기수자원공사원동(구)(대암댐)취수구하천수0.00.0000.00.0000.00.140.00.01.40.00.00.00.00.00.00.00.00.00.00.00.0007
3207320820171분기경상남도 창원시대산6만(2단계)착수정강변여과수0.00.0000.00.0000.00.220.00.290.00.00.00.00.00.00.00.00.00.00.00.00.00052
7204720520201분기충청북도 충주시단월2취수구복류수0.00.0000.00.0000.00.00.00.02.90.00.00.00.00.00.00.00.00.00.00.00.0