Overview

Dataset statistics

Number of variables24
Number of observations3818
Missing cells0
Missing cells (%)0.0%
Duplicate rows15
Duplicate rows (%)0.4%
Total size in memory779.4 KiB
Average record size in memory209.0 B

Variable types

Numeric13
Text4
Categorical6
DateTime1

Dataset

Description농업용수로 사용되고 있는 농어촌공사가 보유한 저수지의 주소, 담당관리기관, 조사일자, 수질정보(총유기탄소,총질소,총인,부유물질) 등에 대한 데이터
URLhttps://www.data.go.kr/data/15037764/fileData.do

Alerts

시안 has constant value ""Constant
카드뮴 has constant value ""Constant
수은 has constant value ""Constant
6가크롬 has constant value ""Constant
Dataset has 15 (0.4%) duplicate rowsDuplicates
시설구분 is highly imbalanced (90.3%)Imbalance
관리구분 is highly imbalanced (50.1%)Imbalance
염소이온농도 is highly skewed (γ1 = 23.14924981)Skewed
납 is highly skewed (γ1 = 23.28035451)Skewed
구리 has 3441 (90.1%) zerosZeros
납 has 3781 (99.0%) zerosZeros
비소 has 3788 (99.2%) zerosZeros

Reproduction

Analysis started2023-12-12 20:22:17.357441
Analysis finished2023-12-12 20:22:18.022766
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설코드
Real number (ℝ)

Distinct950
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5149295 × 109
Minimum2.6710101 × 109
Maximum4.8890106 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:18.103016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6710101 × 109
5-th percentile4.15101 × 109
Q14.4130101 × 109
median4.6710102 × 109
Q34.7150101 × 109
95-th percentile4.88201 × 109
Maximum4.8890106 × 109
Range2.2180005 × 109
Interquartile range (IQR)3.0199998 × 108

Descriptive statistics

Standard deviation3.870968 × 108
Coefficient of variation (CV)0.085737064
Kurtosis9.6754923
Mean4.5149295 × 109
Median Absolute Deviation (MAD)1.5000016 × 108
Skewness-2.8929094
Sum1.7238001 × 1013
Variance1.4984393 × 1017
MonotonicityNot monotonic
2023-12-13T05:22:18.245376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4784010100 8
 
0.2%
4375010009 8
 
0.2%
4418010052 8
 
0.2%
4728010036 8
 
0.2%
4885010137 8
 
0.2%
4688010115 4
 
0.1%
4688010122 4
 
0.1%
4689090003 4
 
0.1%
4689010018 4
 
0.1%
4690010025 4
 
0.1%
Other values (940) 3758
98.4%
ValueCountFrequency (%)
2671010056 4
0.1%
2671010067 4
0.1%
2671010097 4
0.1%
2714010005 4
0.1%
2723010024 4
0.1%
2771010011 4
0.1%
2771010062 4
0.1%
2771010077 4
0.1%
2771010098 4
0.1%
2871010001 4
0.1%
ValueCountFrequency (%)
4889010599 4
0.1%
4889010336 4
0.1%
4889010332 4
0.1%
4889010331 4
0.1%
4889010285 4
0.1%
4889010185 4
0.1%
4889010149 4
0.1%
4889010129 4
0.1%
4889010056 4
0.1%
4888010326 4
0.1%

시설명
Text

Distinct953
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-13T05:22:18.545597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.9601886
Min length1

Characters and Unicode

Total characters11302
Distinct characters268
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row국화
2nd row길상2
3rd row김촌
4th row인산
5th row길정
ValueCountFrequency (%)
성주 8
 
0.2%
경천[문경 8
 
0.2%
하동 8
 
0.2%
청천 8
 
0.2%
백곡 6
 
0.2%
고금호 4
 
0.1%
월성[장성 4
 
0.1%
완도호 4
 
0.1%
군내호 4
 
0.1%
백운[완도 4
 
0.1%
Other values (943) 3760
98.5%
2023-12-13T05:22:19.013392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
[ 816
 
7.2%
] 816
 
7.2%
산 400
 
3.5%
천 288
 
2.5%
성 256
 
2.3%
곡 226
 
2.0%
동 220
 
1.9%
대 180
 
1.6%
정 172
 
1.5%
고 160
 
1.4%
Other values (258) 7768
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9488
83.9%
Open Punctuation 874
 
7.7%
Close Punctuation 874
 
7.7%
Decimal Number 66
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 400
 
4.2%
천 288
 
3.0%
성 256
 
2.7%
곡 226
 
2.4%
동 220
 
2.3%
대 180
 
1.9%
정 172
 
1.8%
고 160
 
1.7%
주 148
 
1.6%
용 140
 
1.5%
Other values (252) 7298
76.9%
Open Punctuation
ValueCountFrequency (%)
[ 816
93.4%
( 58
 
6.6%
Close Punctuation
ValueCountFrequency (%)
] 816
93.4%
) 58
 
6.6%
Decimal Number
ValueCountFrequency (%)
2 41
62.1%
1 25
37.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9488
83.9%
Common 1814
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 400
 
4.2%
천 288
 
3.0%
성 256
 
2.7%
곡 226
 
2.4%
동 220
 
2.3%
대 180
 
1.9%
정 172
 
1.8%
고 160
 
1.7%
주 148
 
1.6%
용 140
 
1.5%
Other values (252) 7298
76.9%
Common
ValueCountFrequency (%)
[ 816
45.0%
] 816
45.0%
( 58
 
3.2%
) 58
 
3.2%
2 41
 
2.3%
1 25
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9488
83.9%
ASCII 1814
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
[ 816
45.0%
] 816
45.0%
( 58
 
3.2%
) 58
 
3.2%
2 41
 
2.3%
1 25
 
1.4%
Hangul
ValueCountFrequency (%)
산 400
 
4.2%
천 288
 
3.0%
성 256
 
2.7%
곡 226
 
2.4%
동 220
 
2.3%
대 180
 
1.9%
정 172
 
1.8%
고 160
 
1.7%
주 148
 
1.6%
용 140
 
1.5%
Other values (252) 7298
76.9%

주소
Text

Distinct926
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-13T05:22:19.343131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length15.883709
Min length11

Characters and Unicode

Total characters60644
Distinct characters292
Distinct categories3 ?
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 row인천광역시 강화군 강화읍 국화리
2nd row인천광역시 강화군 길상면 장흥리
3rd row인천광역시 강화군 화도면 장화리
4th row인천광역시 강화군 양도면 인산리
5th row인천광역시 강화군 양도면 길정리
ValueCountFrequency (%)
전라남도 884
 
5.8%
경상북도 652
 
4.3%
경상남도 459
 
3.0%
충청남도 451
 
3.0%
전라북도 448
 
2.9%
충청북도 312
 
2.0%
강원도 240
 
1.6%
경기도 208
 
1.4%
고흥군 108
 
0.7%
강진군 96
 
0.6%
Other values (1546) 11410
74.7%
2023-12-13T05:22:19.804170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11450
18.9%
도 3966
 
6.5%
리 3674
 
6.1%
면 3162
 
5.2%
군 2438
 
4.0%
남 2245
 
3.7%
북 1628
 
2.7%
시 1624
 
2.7%
경 1475
 
2.4%
전 1466
 
2.4%
Other values (282) 27516
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49186
81.1%
Space Separator 11450
 
18.9%
Decimal Number 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3966
 
8.1%
리 3674
 
7.5%
면 3162
 
6.4%
군 2438
 
5.0%
남 2245
 
4.6%
북 1628
 
3.3%
시 1624
 
3.3%
경 1475
 
3.0%
전 1466
 
3.0%
라 1356
 
2.8%
Other values (280) 26152
53.2%
Space Separator
ValueCountFrequency (%)
11450
100.0%
Decimal Number
ValueCountFrequency (%)
1 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49186
81.1%
Common 11458
 
18.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3966
 
8.1%
리 3674
 
7.5%
면 3162
 
6.4%
군 2438
 
5.0%
남 2245
 
4.6%
북 1628
 
3.3%
시 1624
 
3.3%
경 1475
 
3.0%
전 1466
 
3.0%
라 1356
 
2.8%
Other values (280) 26152
53.2%
Common
ValueCountFrequency (%)
11450
99.9%
1 8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49186
81.1%
ASCII 11458
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11450
99.9%
1 8
 
0.1%
Hangul
ValueCountFrequency (%)
도 3966
 
8.1%
리 3674
 
7.5%
면 3162
 
6.4%
군 2438
 
5.0%
남 2245
 
4.6%
북 1628
 
3.3%
시 1624
 
3.3%
경 1475
 
3.0%
전 1466
 
3.0%
라 1356
 
2.8%
Other values (280) 26152
53.2%

시설구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
저수지
3770 
담수호
 
48

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
저수지 3770
98.7%
담수호 48
 
1.3%

Length

2023-12-13T05:22:19.942487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:20.024901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저수지 3770
98.7%
담수호 48
 
1.3%

관리구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
공사
3399 
시군
419 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공사
2nd row공사
3rd row시군
4th row공사
5th row공사

Common Values

ValueCountFrequency (%)
공사 3399
89.0%
시군 419
 
11.0%

Length

2023-12-13T05:22:20.111306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:20.194764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공사 3399
89.0%
시군 419
 
11.0%

관리기관
Text

Distinct142
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-13T05:22:20.382531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.8072289
Min length4

Characters and Unicode

Total characters18354
Distinct characters102
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row강화옹진지사
2nd row강화옹진지사
3rd row강화군청
4th row강화옹진지사
5th row강화옹진지사
ValueCountFrequency (%)
해남완도지사 92
 
2.4%
장흥지사 76
 
2.0%
경주지사 76
 
2.0%
진주산청지사 76
 
2.0%
고흥지사 72
 
1.9%
무진장지사 68
 
1.8%
경산청도지사 64
 
1.7%
홍천춘천지사 64
 
1.7%
괴산증평지사 64
 
1.7%
서산태안지사 64
 
1.7%
Other values (132) 3102
81.2%
2023-12-13T05:22:20.735817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 3441
18.7%
지 3401
18.5%
주 676
 
3.7%
천 652
 
3.6%
청 649
 
3.5%
산 512
 
2.8%
성 451
 
2.5%
진 436
 
2.4%
군 361
 
2.0%
안 340
 
1.9%
Other values (92) 7435
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18354
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 3441
18.7%
지 3401
18.5%
주 676
 
3.7%
천 652
 
3.6%
청 649
 
3.5%
산 512
 
2.8%
성 451
 
2.5%
진 436
 
2.4%
군 361
 
2.0%
안 340
 
1.9%
Other values (92) 7435
40.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18354
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 3441
18.7%
지 3401
18.5%
주 676
 
3.7%
천 652
 
3.6%
청 649
 
3.5%
산 512
 
2.8%
성 451
 
2.5%
진 436
 
2.4%
군 361
 
2.0%
안 340
 
1.9%
Other values (92) 7435
40.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18354
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 3441
18.7%
지 3401
18.5%
주 676
 
3.7%
천 652
 
3.6%
청 649
 
3.5%
산 512
 
2.8%
성 451
 
2.5%
진 436
 
2.4%
군 361
 
2.0%
안 340
 
1.9%
Other values (92) 7435
40.5%

조사일자
Date

Distinct205
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
Minimum2022-02-08 00:00:00
Maximum2022-12-05 00:00:00
2023-12-13T05:22:20.872105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:22:21.021219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수소이온농도
Real number (ℝ)

Distinct235
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6501598
Minimum5.4
Maximum10.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:21.166613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.4
5-th percentile6.5
Q17.1
median7.6
Q38.1
95-th percentile9.1
Maximum10.8
Range5.4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.75351358
Coefficient of variation (CV)0.09849645
Kurtosis0.4333168
Mean7.6501598
Median Absolute Deviation (MAD)0.5
Skewness0.56109747
Sum29208.31
Variance0.56778271
MonotonicityNot monotonic
2023-12-13T05:22:21.303902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.3 214
 
5.6%
7.5 213
 
5.6%
7.4 199
 
5.2%
7.2 197
 
5.2%
7.1 193
 
5.1%
7.8 192
 
5.0%
7.7 188
 
4.9%
7.6 174
 
4.6%
7.9 150
 
3.9%
7.0 141
 
3.7%
Other values (225) 1957
51.3%
ValueCountFrequency (%)
5.4 1
 
< 0.1%
5.59 1
 
< 0.1%
5.6 1
 
< 0.1%
5.7 4
 
0.1%
5.8 4
 
0.1%
5.83 1
 
< 0.1%
5.9 5
 
0.1%
5.94 1
 
< 0.1%
6.0 3
 
0.1%
6.1 13
0.3%
ValueCountFrequency (%)
10.8 1
 
< 0.1%
10.67 1
 
< 0.1%
10.5 1
 
< 0.1%
10.4 3
 
0.1%
10.3 4
 
0.1%
10.1 1
 
< 0.1%
10.0 2
 
0.1%
9.9 5
 
0.1%
9.8 8
0.2%
9.7 13
0.3%

전기전도도
Real number (ℝ)

Distinct542
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202.1231
Minimum6
Maximum8208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:21.452922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile43
Q173.25
median118
Q3190
95-th percentile416.45
Maximum8208
Range8202
Interquartile range (IQR)116.75

Descriptive statistics

Standard deviation430.77685
Coefficient of variation (CV)2.1312599
Kurtosis88.029848
Mean202.1231
Median Absolute Deviation (MAD)53
Skewness8.3531105
Sum771706
Variance185568.7
MonotonicityNot monotonic
2023-12-13T05:22:21.576417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 33
 
0.9%
52 32
 
0.8%
62 31
 
0.8%
50 30
 
0.8%
64 30
 
0.8%
88 29
 
0.8%
83 28
 
0.7%
55 28
 
0.7%
65 28
 
0.7%
117 27
 
0.7%
Other values (532) 3522
92.2%
ValueCountFrequency (%)
6 1
< 0.1%
9 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
19 1
< 0.1%
21 2
0.1%
23 1
< 0.1%
24 2
0.1%
25 1
< 0.1%
27 2
0.1%
ValueCountFrequency (%)
8208 1
< 0.1%
5546 1
< 0.1%
5094 1
< 0.1%
5052 1
< 0.1%
4940 1
< 0.1%
4906 1
< 0.1%
4793 1
< 0.1%
4753 1
< 0.1%
4584 1
< 0.1%
4242 1
< 0.1%

용존산소량
Text

Distinct513
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
2023-12-13T05:22:21.905793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.3205867
Min length1

Characters and Unicode

Total characters12678
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

Unique269 ?
Unique (%)7.0%

Sample

1st row11.9
2nd row10
3rd row13.5
4th row14.9
5th row12.9
ValueCountFrequency (%)
8.7 78
 
2.0%
8.8 76
 
2.0%
9.2 67
 
1.8%
8.1 66
 
1.7%
9 65
 
1.7%
8.5 62
 
1.6%
9.8 62
 
1.6%
8.2 62
 
1.6%
8.6 61
 
1.6%
9.5 55
 
1.4%
Other values (503) 3164
82.9%
2023-12-13T05:22:22.395843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3512
27.7%
1 2299
18.1%
8 1109
 
8.7%
9 978
 
7.7%
7 911
 
7.2%
2 806
 
6.4%
6 660
 
5.2%
3 649
 
5.1%
5 620
 
4.9%
0 571
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9166
72.3%
Other Punctuation 3512
 
27.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2299
25.1%
8 1109
12.1%
9 978
10.7%
7 911
 
9.9%
2 806
 
8.8%
6 660
 
7.2%
3 649
 
7.1%
5 620
 
6.8%
0 571
 
6.2%
4 563
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 3512
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12678
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 3512
27.7%
1 2299
18.1%
8 1109
 
8.7%
9 978
 
7.7%
7 911
 
7.2%
2 806
 
6.4%
6 660
 
5.2%
3 649
 
5.1%
5 620
 
4.9%
0 571
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12678
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3512
27.7%
1 2299
18.1%
8 1109
 
8.7%
9 978
 
7.7%
7 911
 
7.2%
2 806
 
6.4%
6 660
 
5.2%
3 649
 
5.1%
5 620
 
4.9%
0 571
 
4.5%

화학적산소요구량
Real number (ℝ)

Distinct124
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6512409
Minimum0.8
Maximum35.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:22.553278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile3
Q14.2
median5.6
Q38
95-th percentile14.8
Maximum35.3
Range34.5
Interquartile range (IQR)3.8

Descriptive statistics

Standard deviation3.8437465
Coefficient of variation (CV)0.57789915
Kurtosis8.6974275
Mean6.6512409
Median Absolute Deviation (MAD)1.6
Skewness2.394524
Sum25394.438
Variance14.774387
MonotonicityNot monotonic
2023-12-13T05:22:22.713828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.6 157
 
4.1%
5.0 145
 
3.8%
4.8 143
 
3.7%
3.8 139
 
3.6%
4.2 138
 
3.6%
4.0 137
 
3.6%
3.6 136
 
3.6%
3.4 135
 
3.5%
4.4 131
 
3.4%
5.4 119
 
3.1%
Other values (114) 2438
63.9%
ValueCountFrequency (%)
0.8 1
 
< 0.1%
1.2 1
 
< 0.1%
1.4 2
 
0.1%
1.6 5
 
0.1%
1.8 2
 
0.1%
2.0 8
 
0.2%
2.2 16
 
0.4%
2.4 22
 
0.6%
2.6 41
1.1%
2.8 74
1.9%
ValueCountFrequency (%)
35.3 1
 
< 0.1%
34.5 1
 
< 0.1%
33.6 1
 
< 0.1%
32.9 2
0.1%
30.4 3
0.1%
29.6 2
0.1%
28.9 3
0.1%
28.8 1
 
< 0.1%
28.0 2
0.1%
27.2 1
 
< 0.1%

총유기탄소량
Real number (ℝ)

Distinct131
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7438973
Minimum0.4
Maximum19.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:22.877575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile1.6
Q12.4
median3.2
Q34.6
95-th percentile7.7
Maximum19.2
Range18.8
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation2.0434591
Coefficient of variation (CV)0.54581067
Kurtosis5.6486124
Mean3.7438973
Median Absolute Deviation (MAD)1
Skewness1.8559572
Sum14294.2
Variance4.1757251
MonotonicityNot monotonic
2023-12-13T05:22:23.062050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.4 147
 
3.9%
3.2 116
 
3.0%
2.7 115
 
3.0%
2.0 113
 
3.0%
2.8 113
 
3.0%
3.3 113
 
3.0%
2.1 112
 
2.9%
2.5 108
 
2.8%
2.6 108
 
2.8%
2.9 107
 
2.8%
Other values (121) 2666
69.8%
ValueCountFrequency (%)
0.4 1
 
< 0.1%
0.7 5
 
0.1%
0.9 2
 
0.1%
1.0 4
 
0.1%
1.1 12
 
0.3%
1.2 25
 
0.7%
1.3 28
0.7%
1.4 49
1.3%
1.5 57
1.5%
1.6 68
1.8%
ValueCountFrequency (%)
19.2 1
< 0.1%
18.2 1
< 0.1%
17.2 1
< 0.1%
16.5 1
< 0.1%
16.0 1
< 0.1%
15.7 1
< 0.1%
15.2 1
< 0.1%
14.9 1
< 0.1%
14.1 1
< 0.1%
13.9 2
0.1%

총질소
Real number (ℝ)

Distinct1847
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2086752
Minimum0.072
Maximum11.546
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:23.256449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.072
5-th percentile0.359
Q10.67125
median1.024
Q31.515
95-th percentile2.6686
Maximum11.546
Range11.474
Interquartile range (IQR)0.84375

Descriptive statistics

Standard deviation0.83806162
Coefficient of variation (CV)0.69337205
Kurtosis25.594937
Mean1.2086752
Median Absolute Deviation (MAD)0.4005
Skewness3.4046799
Sum4614.722
Variance0.70234728
MonotonicityNot monotonic
2023-12-13T05:22:23.473246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.583 9
 
0.2%
0.581 9
 
0.2%
0.619 8
 
0.2%
0.778 8
 
0.2%
0.468 7
 
0.2%
1.349 7
 
0.2%
0.644 7
 
0.2%
0.743 7
 
0.2%
0.688 7
 
0.2%
1.396 7
 
0.2%
Other values (1837) 3742
98.0%
ValueCountFrequency (%)
0.072 1
< 0.1%
0.095 1
< 0.1%
0.1 1
< 0.1%
0.105 1
< 0.1%
0.133 1
< 0.1%
0.144 2
0.1%
0.146 1
< 0.1%
0.161 1
< 0.1%
0.171 1
< 0.1%
0.188 1
< 0.1%
ValueCountFrequency (%)
11.546 1
< 0.1%
11.479 1
< 0.1%
11.026 1
< 0.1%
9.671 1
< 0.1%
7.676 1
< 0.1%
7.618 1
< 0.1%
7.0 1
< 0.1%
6.794 1
< 0.1%
6.644 1
< 0.1%
6.636 1
< 0.1%

총인
Real number (ℝ)

Distinct218
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.035104243
Minimum0.001
Maximum1.896
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:23.648501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.006
Q10.011
median0.019
Q30.036
95-th percentile0.10515
Maximum1.896
Range1.895
Interquartile range (IQR)0.025

Descriptive statistics

Standard deviation0.068483985
Coefficient of variation (CV)1.9508749
Kurtosis220.07445
Mean0.035104243
Median Absolute Deviation (MAD)0.009
Skewness11.736
Sum134.028
Variance0.0046900562
MonotonicityNot monotonic
2023-12-13T05:22:23.809794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 164
 
4.3%
0.011 160
 
4.2%
0.012 154
 
4.0%
0.014 153
 
4.0%
0.015 152
 
4.0%
0.009 145
 
3.8%
0.013 140
 
3.7%
0.008 131
 
3.4%
0.016 124
 
3.2%
0.007 119
 
3.1%
Other values (208) 2376
62.2%
ValueCountFrequency (%)
0.001 5
 
0.1%
0.002 15
 
0.4%
0.003 34
 
0.9%
0.004 40
 
1.0%
0.005 63
 
1.7%
0.006 90
2.4%
0.007 119
3.1%
0.008 131
3.4%
0.009 145
3.8%
0.01 164
4.3%
ValueCountFrequency (%)
1.896 1
< 0.1%
1.311 1
< 0.1%
0.985 1
< 0.1%
0.969 1
< 0.1%
0.94 1
< 0.1%
0.794 1
< 0.1%
0.772 1
< 0.1%
0.687 1
< 0.1%
0.638 1
< 0.1%
0.619 1
< 0.1%

부유물질량
Real number (ℝ)

Distinct285
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3873573
Minimum0.2
Maximum386.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:24.447698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.1
Q12.4
median4.3
Q38
95-th percentile22.83
Maximum386.7
Range386.5
Interquartile range (IQR)5.6

Descriptive statistics

Standard deviation11.683972
Coefficient of variation (CV)1.5816173
Kurtosis324.52731
Mean7.3873573
Median Absolute Deviation (MAD)2.3
Skewness12.576516
Sum28204.93
Variance136.51521
MonotonicityNot monotonic
2023-12-13T05:22:24.647445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.3 97
 
2.5%
2.0 87
 
2.3%
4.0 84
 
2.2%
2.7 77
 
2.0%
2.8 74
 
1.9%
3.3 73
 
1.9%
1.7 71
 
1.9%
3.0 69
 
1.8%
3.2 69
 
1.8%
6.0 64
 
1.7%
Other values (275) 3053
80.0%
ValueCountFrequency (%)
0.2 3
 
0.1%
0.3 4
 
0.1%
0.4 3
 
0.1%
0.5 7
 
0.2%
0.6 14
 
0.4%
0.7 32
0.8%
0.8 26
0.7%
0.9 35
0.9%
1.0 35
0.9%
1.1 48
1.3%
ValueCountFrequency (%)
386.7 1
< 0.1%
193.0 1
< 0.1%
172.0 1
< 0.1%
102.0 1
< 0.1%
95.0 1
< 0.1%
92.0 1
< 0.1%
87.0 1
< 0.1%
76.0 1
< 0.1%
74.0 2
0.1%
73.0 1
< 0.1%

염소이온농도
Real number (ℝ)

SKEWED 

Distinct621
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.756391
Minimum0
Maximum7290
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:24.798752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.1
Q16.325
median9.5
Q315.7
95-th percentile72.03
Maximum7290
Range7290
Interquartile range (IQR)9.375

Descriptive statistics

Standard deviation171.71372
Coefficient of variation (CV)5.0868507
Kurtosis859.32583
Mean33.756391
Median Absolute Deviation (MAD)3.8
Skewness23.14925
Sum128881.9
Variance29485.602
MonotonicityNot monotonic
2023-12-13T05:22:24.988100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.7 46
 
1.2%
6.1 45
 
1.2%
5.2 44
 
1.2%
7.6 40
 
1.0%
7.5 39
 
1.0%
5.1 39
 
1.0%
5.3 38
 
1.0%
7.4 37
 
1.0%
6.5 37
 
1.0%
9.5 36
 
0.9%
Other values (611) 3417
89.5%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
1.2 1
 
< 0.1%
1.9 1
 
< 0.1%
2.1 2
 
0.1%
2.2 1
 
< 0.1%
2.3 4
0.1%
2.4 4
0.1%
2.5 5
0.1%
2.6 3
0.1%
2.7 4
0.1%
ValueCountFrequency (%)
7290.0 1
< 0.1%
1987.4 1
< 0.1%
1798.8 1
< 0.1%
1585.2 1
< 0.1%
1578.2 1
< 0.1%
1485.2 1
< 0.1%
1483.8 1
< 0.1%
1455.6 1
< 0.1%
1357.2 1
< 0.1%
1351.4 1
< 0.1%

클로로필에이
Real number (ℝ)

Distinct701
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.803719
Minimum0
Maximum399.9
Zeros4
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:25.188859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.1
Q16.4
median10.9
Q321.775
95-th percentile67.73
Maximum399.9
Range399.9
Interquartile range (IQR)15.375

Descriptive statistics

Standard deviation26.862037
Coefficient of variation (CV)1.3564138
Kurtosis32.943603
Mean19.803719
Median Absolute Deviation (MAD)5.8
Skewness4.5536512
Sum75610.6
Variance721.56905
MonotonicityNot monotonic
2023-12-13T05:22:25.376618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.6 38
 
1.0%
6.9 37
 
1.0%
9.2 33
 
0.9%
4.7 32
 
0.8%
5.7 31
 
0.8%
6.8 31
 
0.8%
5.0 30
 
0.8%
6.7 30
 
0.8%
5.2 28
 
0.7%
7.0 27
 
0.7%
Other values (691) 3501
91.7%
ValueCountFrequency (%)
0.0 4
0.1%
0.1 1
 
< 0.1%
0.2 1
 
< 0.1%
0.7 1
 
< 0.1%
1.1 1
 
< 0.1%
1.2 2
 
0.1%
1.3 2
 
0.1%
1.4 1
 
< 0.1%
1.5 7
0.2%
1.6 8
0.2%
ValueCountFrequency (%)
399.9 1
< 0.1%
304.1 1
< 0.1%
303.8 1
< 0.1%
275.9 1
< 0.1%
258.8 1
< 0.1%
258.7 1
< 0.1%
241.5 1
< 0.1%
239.5 1
< 0.1%
221.7 1
< 0.1%
217.9 1
< 0.1%

시안
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
0
3818 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3818
100.0%

Length

2023-12-13T05:22:25.537392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:25.660348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3818
100.0%

구리
Real number (ℝ)

ZEROS 

Distinct344
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00042331587
Minimum0
Maximum0.081279
Zeros3441
Zeros (%)90.1%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:25.790913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0028083
Maximum0.081279
Range0.081279
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0021041628
Coefficient of variation (CV)4.9706682
Kurtosis607.47446
Mean0.00042331587
Median Absolute Deviation (MAD)0
Skewness18.743034
Sum1.61622
Variance4.4275009 × 10-6
MonotonicityNot monotonic
2023-12-13T05:22:25.970127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3441
90.1%
0.00243 3
 
0.1%
0.0025 3
 
0.1%
0.00272 3
 
0.1%
0.002066 2
 
0.1%
0.00211 2
 
0.1%
0.00269 2
 
0.1%
0.00266 2
 
0.1%
0.00278 2
 
0.1%
0.00222 2
 
0.1%
Other values (334) 356
 
9.3%
ValueCountFrequency (%)
0.0 3441
90.1%
0.001995 1
 
< 0.1%
0.002 1
 
< 0.1%
0.002003 1
 
< 0.1%
0.002004 1
 
< 0.1%
0.002007 1
 
< 0.1%
0.002012 1
 
< 0.1%
0.002016 2
 
0.1%
0.002018 1
 
< 0.1%
0.00202 1
 
< 0.1%
ValueCountFrequency (%)
0.081279 1
< 0.1%
0.03222 1
< 0.1%
0.027125 1
< 0.1%
0.026644 1
< 0.1%
0.019893 1
< 0.1%
0.01688 1
< 0.1%
0.016764 1
< 0.1%
0.01676 1
< 0.1%
0.016197 1
< 0.1%
0.0156 1
< 0.1%

납
Real number (ℝ)

SKEWED  ZEROS 

Distinct37
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2619172 × 10-5
Minimum0
Maximum0.022521
Zeros3781
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:26.138804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.022521
Range0.022521
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.00056296865
Coefficient of variation (CV)13.209282
Kurtosis753.7025
Mean4.2619172 × 10-5
Median Absolute Deviation (MAD)0
Skewness23.280355
Sum0.16272
Variance3.169337 × 10-7
MonotonicityNot monotonic
2023-12-13T05:22:26.321764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 3781
99.0%
0.002463 2
 
0.1%
0.003438 1
 
< 0.1%
0.002451 1
 
< 0.1%
0.002023 1
 
< 0.1%
0.002751 1
 
< 0.1%
0.002472 1
 
< 0.1%
0.004886 1
 
< 0.1%
0.0023 1
 
< 0.1%
0.002619 1
 
< 0.1%
Other values (27) 27
 
0.7%
ValueCountFrequency (%)
0.0 3781
99.0%
0.002023 1
 
< 0.1%
0.00211 1
 
< 0.1%
0.002169 1
 
< 0.1%
0.002258 1
 
< 0.1%
0.00228 1
 
< 0.1%
0.0023 1
 
< 0.1%
0.002445 1
 
< 0.1%
0.002451 1
 
< 0.1%
0.002463 2
 
0.1%
ValueCountFrequency (%)
0.022521 1
< 0.1%
0.010853 1
< 0.1%
0.008803 1
< 0.1%
0.00771 1
< 0.1%
0.007646 1
< 0.1%
0.00648 1
< 0.1%
0.006389 1
< 0.1%
0.005653 1
< 0.1%
0.004886 1
< 0.1%
0.00485 1
< 0.1%

카드뮴
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
0
3818 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3818
100.0%

Length

2023-12-13T05:22:26.456598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:26.570081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3818
100.0%

비소
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00011618727
Minimum0
Maximum0.05201
Zeros3788
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size33.7 KiB
2023-12-13T05:22:26.682099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.05201
Range0.05201
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0015587809
Coefficient of variation (CV)13.416108
Kurtosis461.0323
Mean0.00011618727
Median Absolute Deviation (MAD)0
Skewness18.926784
Sum0.443603
Variance2.429798 × 10-6
MonotonicityNot monotonic
2023-12-13T05:22:26.841661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 3788
99.2%
0.00871 1
 
< 0.1%
0.01761 1
 
< 0.1%
0.01457 1
 
< 0.1%
0.02105 1
 
< 0.1%
0.00778 1
 
< 0.1%
0.01603 1
 
< 0.1%
0.0348 1
 
< 0.1%
0.024323 1
 
< 0.1%
0.00998 1
 
< 0.1%
Other values (21) 21
 
0.6%
ValueCountFrequency (%)
0.0 3788
99.2%
0.006208 1
 
< 0.1%
0.0067 1
 
< 0.1%
0.00674 1
 
< 0.1%
0.00733 1
 
< 0.1%
0.007533 1
 
< 0.1%
0.00774 1
 
< 0.1%
0.00778 1
 
< 0.1%
0.008002 1
 
< 0.1%
0.008006 1
 
< 0.1%
ValueCountFrequency (%)
0.05201 1
< 0.1%
0.0348 1
< 0.1%
0.024323 1
< 0.1%
0.023773 1
< 0.1%
0.02116 1
< 0.1%
0.02105 1
< 0.1%
0.019198 1
< 0.1%
0.01761 1
< 0.1%
0.01741 1
< 0.1%
0.017149 1
< 0.1%

수은
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
0
3818 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3818
100.0%

Length

2023-12-13T05:22:26.992381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:27.102735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3818
100.0%

6가크롬
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.0 KiB
0
3818 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 3818
100.0%

Length

2023-12-13T05:22:27.215075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:22:27.356217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3818
100.0%

Sample

시설코드시설명주소시설구분관리구분관리기관조사일자수소이온농도전기전도도용존산소량화학적산소요구량총유기탄소량총질소총인부유물질량염소이온농도클로로필에이시안구리납카드뮴비소수은6가크롬
02871010001국화인천광역시 강화군 강화읍 국화리저수지공사강화옹진지사2022-04-057.616011.96.43.62.3540.0226.419.218.500.00.000.000
12871010007길상2인천광역시 강화군 길상면 장흥리저수지공사강화옹진지사2022-03-247.5397106.83.31.4910.06219.171.716.400.00.000.000
22871010040김촌인천광역시 강화군 화도면 장화리저수지시군강화군청2022-04-157.77713.54.83.02.6420.0122.311.72.700.00.000.000
32871010011인산인천광역시 강화군 양도면 인산리저수지공사강화옹진지사2022-04-058.326414.910.25.73.1530.0547.340.113.400.00.000.000
42871010012길정인천광역시 강화군 양도면 길정리저수지공사강화옹진지사2022-04-157.511212.95.83.82.5750.0092.327.12.200.00.000.000
52871010013고려인천광역시 강화군 내가면 고천리저수지공사강화옹진지사2022-04-058.025313.89.65.41.9250.05513.343.141.700.00.000.000
62871010024하점인천광역시 강화군 하점면 삼거리저수지공사강화옹진지사2022-04-158.51214.25.43.42.0480.011.121.24.300.00.000.000
72871010019대산[강화]인천광역시 강화군 송해면 숭뢰리저수지공사강화옹진지사2022-04-058.3367137.45.22.1170.03511.4179.74.700.00.000.000
82871010020하도[강화]인천광역시 강화군 송해면 하도리저수지공사강화옹진지사2022-04-077.7113127.64.32.2720.0155.311.09.900.00.000.000
92871010026양오인천광역시 강화군 송해면 양오리저수지공사강화옹진지사2022-04-057.745212.17.45.62.3540.0222.398.34.800.00.000.000
시설코드시설명주소시설구분관리구분관리기관조사일자수소이온농도전기전도도용존산소량화학적산소요구량총유기탄소량총질소총인부유물질량염소이온농도클로로필에이시안구리납카드뮴비소수은6가크롬
38084889010332장계[합천]경상남도 합천군 합천읍 장계리저수지공사합천지사2022-11-307.81588.74.22.71.1550.0112.48.86.800.00.000.000
38094889010599노곡경상남도 합천군 봉산면 노곡리저수지시군합천군청2022-10-247.411498.64.50.4180.03714.05.615.600.00.000.000
38104889010056죽전경상남도 합천군 가야면 죽전리저수지공사합천지사2022-11-307.76510.13.41.70.6990.0071.41.97.000.00.000.000
38114889010331율곡경상남도 합천군 율곡면 노양리저수지공사합천지사2022-10-246.9655.55.43.60.3250.0084.04.53.100.00.000.000
38124889010129상신경상남도 합천군 쌍책면 상신리저수지공사합천지사2022-10-207.2103611.68.60.430.0124.94.75.000.00.000.000
38134889010149율원경상남도 합천군 덕곡면 율원리저수지공사합천지사2022-10-207.31155.110.47.20.6920.0195.34.47.600.00.000.000
38144889010185명곡경상남도 합천군 적중면 누하리저수지공사합천지사2022-10-257.0687.24.22.51.330.0081.04.51.600.00.000.000
38154872010145오산[합천]경상남도 합천군 대양면 오산리저수지공사의령지사2022-10-257.2687.45.23.10.8880.013.23.27.100.00.000.000
38164889010336중촌경상남도 합천군 쌍백면 평지리저수지공사합천지사2022-10-257.3887.56.23.80.2580.0134.84.56.900.00.000.000
38174889010285가회경상남도 합천군 가회면 둔내리저수지공사합천지사2022-10-257.68994.02.00.60.0074.25.011.800.00.000.000

Duplicate rows

Most frequently occurring

시설코드시설명주소시설구분관리구분관리기관조사일자수소이온농도전기전도도용존산소량화학적산소요구량총유기탄소량총질소총인부유물질량염소이온농도클로로필에이시안구리납카드뮴비소수은6가크롬# duplicates
04375010009백곡충청북도 진천군 진천읍 건송리저수지공사진천지사2022-06-089.517012.110.85.30.9030.028.012.837.300.0022840.000.0002
14375010009백곡충청북도 진천군 진천읍 건송리저수지공사진천지사2022-09-077.11244.35.22.82.1460.0164.39.012.400.00.000.0002
24375010009백곡충청북도 진천군 진천읍 건송리저수지공사진천지사2022-11-187.41326.74.62.71.6210.0162.09.43.100.00.000.0002
34418010052청천충청남도 보령시 죽정동저수지공사보령지사2022-06-098.71859.45.23.10.7140.0171.915.99.800.00.000.0002
44418010052청천충청남도 보령시 죽정동저수지공사보령지사2022-09-227.31338..54.42.51.5160.0163.310.29.800.002690.000.0002
54418010052청천충청남도 보령시 죽정동저수지공사보령지사2022-11-096.81467.13.62.21.3890.0144.09.53.800.002580.000.0002
64728010036경천[문경]경상북도 문경시 동로면 마광리저수지공사문경지사2022-05-168.41019.84.22.31.830.0154.85.49.000.0045070.00246300.0002
74728010036경천[문경]경상북도 문경시 동로면 마광리저수지공사문경지사2022-07-217.11459.53.82.13.6710.0372.26.76.800.00.000.0002
84728010036경천[문경]경상북도 문경시 동로면 마광리저수지공사문경지사2022-10-317.4888.74.22.12.4730.0153.34.917.600.00.000.0002
94784010100성주경상북도 성주군 가천면 중산리저수지공사성주지사2022-06-096.4848.83.41.81.0630.0124.66.59.700.0022220.000.0002