Overview

Dataset statistics

Number of variables27
Number of observations2224
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory514.9 KiB
Average record size in memory237.1 B

Variable types

Numeric6
Categorical19
Text2

Dataset

Description수도법에 따라 반기마다 광역 또는 지방상수도에서 지하수를 원수로 사용하는 원수 수질 검사 결과 데이터로, 수질검사결과, 수질검사기관 등을 포함 * 상세자료조회는 아래 URL을 참고 해주시기 바랍니다. https://www.waternow.go.kr/web/lawData2/?pMENUID=96&ATTR_1=3105
URLhttps://www.data.go.kr/data/15093989/fileData.do

Alerts

카드뮴 has constant value ""Constant
시안 has constant value ""Constant
수은 has constant value ""Constant
납 has constant value ""Constant
크롬 has constant value ""Constant
다이아지논 has constant value ""Constant
파라티온 has constant value ""Constant
페니트로티온 has constant value ""Constant
셀레늄 has constant value ""Constant
페놀 has constant value ""Constant
지역 is highly imbalanced (56.7%)Imbalance
채수위치 is highly imbalanced (87.0%)Imbalance
수원 is highly imbalanced (51.7%)Imbalance
음이온 계면활성제 is highly imbalanced (99.0%)Imbalance
카바릴 is highly imbalanced (99.4%)Imbalance
1_1_1-트리클로로에탄 is highly imbalanced (99.4%)Imbalance
테트라클로로에틸렌 is highly imbalanced (99.4%)Imbalance
트리클로로에틸렌 is highly imbalanced (99.0%)Imbalance
암모니아성질소 is highly skewed (γ1 = 25.99981385)Skewed
연번 has unique valuesUnique
비소 has 2206 (99.2%) zerosZeros
불소 has 2011 (90.4%) zerosZeros
암모니아성질소 has 2202 (99.0%) zerosZeros

Reproduction

Analysis started2023-12-12 08:17:33.242240
Analysis finished2023-12-12 08:17:33.812007
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct2224
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1112.5
Minimum1
Maximum2224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:33.922674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile112.15
Q1556.75
median1112.5
Q31668.25
95-th percentile2112.85
Maximum2224
Range2223
Interquartile range (IQR)1111.5

Descriptive statistics

Standard deviation642.15782
Coefficient of variation (CV)0.57722051
Kurtosis-1.2
Mean1112.5
Median Absolute Deviation (MAD)556
Skewness0
Sum2474200
Variance412366.67
MonotonicityStrictly increasing
2023-12-12T17:17:34.095917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1487 1
 
< 0.1%
1481 1
 
< 0.1%
1482 1
 
< 0.1%
1483 1
 
< 0.1%
1484 1
 
< 0.1%
1485 1
 
< 0.1%
1486 1
 
< 0.1%
1488 1
 
< 0.1%
1496 1
 
< 0.1%
Other values (2214) 2214
99.6%
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 (%)
2224 1
< 0.1%
2223 1
< 0.1%
2222 1
< 0.1%
2221 1
< 0.1%
2220 1
< 0.1%
2219 1
< 0.1%
2218 1
< 0.1%
2217 1
< 0.1%
2216 1
< 0.1%
2215 1
< 0.1%

검사년도
Real number (ℝ)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5701
Minimum2015
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:34.223945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2018
Q32021
95-th percentile2022
Maximum2022
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3412299
Coefficient of variation (CV)0.0011598457
Kurtosis-1.3332767
Mean2018.5701
Median Absolute Deviation (MAD)2
Skewness0.0094767791
Sum4489300
Variance5.4813574
MonotonicityIncreasing
2023-12-12T17:17:34.364093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2017 325
14.6%
2022 316
14.2%
2020 305
13.7%
2021 303
13.6%
2016 289
13.0%
2018 286
12.9%
2015 253
11.4%
2019 147
6.6%
ValueCountFrequency (%)
2015 253
11.4%
2016 289
13.0%
2017 325
14.6%
2018 286
12.9%
2019 147
6.6%
2020 305
13.7%
2021 303
13.6%
2022 316
14.2%
ValueCountFrequency (%)
2022 316
14.2%
2021 303
13.6%
2020 305
13.7%
2019 147
6.6%
2018 286
12.9%
2017 325
14.6%
2016 289
13.0%
2015 253
11.4%

검사반기
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
상반기
1199 
하반기
1025 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상반기 1199
53.9%
하반기 1025
46.1%

Length

2023-12-12T17:17:34.512109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:34.633053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상반기 1199
53.9%
하반기 1025
46.1%

지역
Categorical

IMBALANCE 

Distinct27
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
제주특별자치도
1596 
충청북도 괴산군
 
86
충청북도 청주시
 
81
전라남도 화순군
 
60
강원도 영월군
 
41
Other values (22)
360 

Length

Max length8
Median length7
Mean length7.1510791
Min length5

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row강원도 삼척시
2nd row강원도 영월군
3rd row강원도 영월군
4th row강원도 원주시
5th row강원도 원주시

Common Values

ValueCountFrequency (%)
제주특별자치도 1596
71.8%
충청북도 괴산군 86
 
3.9%
충청북도 청주시 81
 
3.6%
전라남도 화순군 60
 
2.7%
강원도 영월군 41
 
1.8%
경기도 가평군 35
 
1.6%
인천광역시 32
 
1.4%
강원도 원주시 30
 
1.3%
경기도 포천시 28
 
1.3%
경상북도 성주군 24
 
1.1%
Other values (17) 211
 
9.5%

Length

2023-12-12T17:17:34.780093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제주특별자치도 1596
56.6%
충청북도 220
 
7.8%
강원도 118
 
4.2%
괴산군 86
 
3.0%
청주시 81
 
2.9%
경기도 78
 
2.8%
경상북도 72
 
2.6%
전라남도 67
 
2.4%
화순군 60
 
2.1%
영월군 41
 
1.5%
Other values (24) 401
 
14.2%

소규모수도시설명
Text

Distinct150
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
2023-12-12T17:17:35.104851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.6919964
Min length2

Characters and Unicode

Total characters12659
Distinct characters144
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)1.2%

Sample

1st row임원
2nd row주천
3rd row하동
4th row귀래
5th row신림
ValueCountFrequency (%)
신흥2광역수원 90
 
3.7%
행원1광역수원 75
 
3.1%
외도수원 75
 
3.1%
신흥1광역수원 75
 
3.1%
함덕광역수원 65
 
2.7%
행원2광역수원 61
 
2.5%
상귀광역수원 60
 
2.5%
저지광역수원 60
 
2.5%
어음광역수원 60
 
2.5%
서광광역수원 60
 
2.5%
Other values (149) 1732
71.8%
2023-12-12T17:17:35.582826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 1459
 
11.5%
수 1389
 
11.0%
광 1108
 
8.8%
역 1019
 
8.0%
1 407
 
3.2%
2 347
 
2.7%
호 318
 
2.5%
지 305
 
2.4%
정 233
 
1.8%
도 223
 
1.8%
Other values (134) 5851
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10927
86.3%
Decimal Number 1101
 
8.7%
Space Separator 189
 
1.5%
Dash Punctuation 135
 
1.1%
Other Punctuation 96
 
0.8%
Close Punctuation 68
 
0.5%
Open Punctuation 68
 
0.5%
Uppercase Letter 49
 
0.4%
Lowercase Letter 26
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 1459
 
13.4%
수 1389
 
12.7%
광 1108
 
10.1%
역 1019
 
9.3%
호 318
 
2.9%
지 305
 
2.8%
정 233
 
2.1%
도 223
 
2.0%
신 180
 
1.6%
흥 165
 
1.5%
Other values (112) 4528
41.4%
Decimal Number
ValueCountFrequency (%)
1 407
37.0%
2 347
31.5%
3 136
 
12.4%
6 67
 
6.1%
4 49
 
4.5%
9 44
 
4.0%
5 28
 
2.5%
0 17
 
1.5%
8 4
 
0.4%
7 2
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
D 46
93.9%
F 1
 
2.0%
A 1
 
2.0%
S 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
# 81
84.4%
, 15
 
15.6%
Lowercase Letter
ValueCountFrequency (%)
e 13
50.0%
w 13
50.0%
Space Separator
ValueCountFrequency (%)
189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10927
86.3%
Common 1657
 
13.1%
Latin 75
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 1459
 
13.4%
수 1389
 
12.7%
광 1108
 
10.1%
역 1019
 
9.3%
호 318
 
2.9%
지 305
 
2.8%
정 233
 
2.1%
도 223
 
2.0%
신 180
 
1.6%
흥 165
 
1.5%
Other values (112) 4528
41.4%
Common
ValueCountFrequency (%)
1 407
24.6%
2 347
20.9%
189
11.4%
3 136
 
8.2%
- 135
 
8.1%
# 81
 
4.9%
) 68
 
4.1%
( 68
 
4.1%
6 67
 
4.0%
4 49
 
3.0%
Other values (6) 110
 
6.6%
Latin
ValueCountFrequency (%)
D 46
61.3%
e 13
 
17.3%
w 13
 
17.3%
F 1
 
1.3%
A 1
 
1.3%
S 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10927
86.3%
ASCII 1732
 
13.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 1459
 
13.4%
수 1389
 
12.7%
광 1108
 
10.1%
역 1019
 
9.3%
호 318
 
2.9%
지 305
 
2.8%
정 233
 
2.1%
도 223
 
2.0%
신 180
 
1.6%
흥 165
 
1.5%
Other values (112) 4528
41.4%
ASCII
ValueCountFrequency (%)
1 407
23.5%
2 347
20.0%
189
10.9%
3 136
 
7.9%
- 135
 
7.8%
# 81
 
4.7%
) 68
 
3.9%
( 68
 
3.9%
6 67
 
3.9%
4 49
 
2.8%
Other values (12) 185
10.7%

측정지점주소
Text

Distinct133
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
2023-12-12T17:17:36.026616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length21.822842
Min length3

Characters and Unicode

Total characters48534
Distinct characters180
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.8%

Sample

1st row강원도 삼척시 원덕읍 임원리 915
2nd row강원도 영월군 주천면 도천길 673
3rd row강원도 영월군 김삿갓면 강변로 1462-23
4th row강원도 원주시 귀래면 한치길 1141
5th row강원도 원주시 신림면 둔창예찬길 5147
ValueCountFrequency (%)
제주특별자치도 1478
 
14.3%
제주시 932
 
9.0%
서귀포시 607
 
5.9%
남원읍 320
 
3.1%
신흥리 245
 
2.4%
충청북도 220
 
2.1%
애월읍 205
 
2.0%
1567 151
 
1.5%
강원도 118
 
1.1%
구좌읍 98
 
0.9%
Other values (300) 5982
57.8%
2023-12-12T17:17:36.617555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8179
 
16.9%
주 2627
 
5.4%
제 2452
 
5.1%
도 2288
 
4.7%
1 1839
 
3.8%
시 1816
 
3.7%
치 1525
 
3.1%
자 1510
 
3.1%
별 1510
 
3.1%
특 1510
 
3.1%
Other values (170) 23278
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31840
65.6%
Decimal Number 8182
 
16.9%
Space Separator 8179
 
16.9%
Dash Punctuation 161
 
0.3%
Open Punctuation 65
 
0.1%
Close Punctuation 65
 
0.1%
Lowercase Letter 30
 
0.1%
Other Punctuation 10
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2627
 
8.3%
제 2452
 
7.7%
도 2288
 
7.2%
시 1816
 
5.7%
치 1525
 
4.8%
자 1510
 
4.7%
별 1510
 
4.7%
특 1510
 
4.7%
리 1359
 
4.3%
읍 825
 
2.6%
Other values (147) 14418
45.3%
Decimal Number
ValueCountFrequency (%)
1 1839
22.5%
2 931
11.4%
6 833
10.2%
3 800
9.8%
0 790
9.7%
7 710
 
8.7%
4 655
 
8.0%
8 625
 
7.6%
5 615
 
7.5%
9 384
 
4.7%
Lowercase Letter
ValueCountFrequency (%)
w 13
43.3%
e 13
43.3%
n 1
 
3.3%
u 1
 
3.3%
r 1
 
3.3%
a 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
8179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31840
65.6%
Common 16662
34.3%
Latin 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2627
 
8.3%
제 2452
 
7.7%
도 2288
 
7.2%
시 1816
 
5.7%
치 1525
 
4.8%
자 1510
 
4.7%
별 1510
 
4.7%
특 1510
 
4.7%
리 1359
 
4.3%
읍 825
 
2.6%
Other values (147) 14418
45.3%
Common
ValueCountFrequency (%)
8179
49.1%
1 1839
 
11.0%
2 931
 
5.6%
6 833
 
5.0%
3 800
 
4.8%
0 790
 
4.7%
7 710
 
4.3%
4 655
 
3.9%
8 625
 
3.8%
5 615
 
3.7%
Other values (5) 685
 
4.1%
Latin
ValueCountFrequency (%)
w 13
40.6%
e 13
40.6%
M 1
 
3.1%
n 1
 
3.1%
u 1
 
3.1%
J 1
 
3.1%
r 1
 
3.1%
a 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31840
65.6%
ASCII 16694
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8179
49.0%
1 1839
 
11.0%
2 931
 
5.6%
6 833
 
5.0%
3 800
 
4.8%
0 790
 
4.7%
7 710
 
4.3%
4 655
 
3.9%
8 625
 
3.7%
5 615
 
3.7%
Other values (13) 717
 
4.3%
Hangul
ValueCountFrequency (%)
주 2627
 
8.3%
제 2452
 
7.7%
도 2288
 
7.2%
시 1816
 
5.7%
치 1525
 
4.8%
자 1510
 
4.7%
별 1510
 
4.7%
특 1510
 
4.7%
리 1359
 
4.3%
읍 825
 
2.6%
Other values (147) 14418
45.3%

채수위치
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
취수구
2184 
착수정
 
40

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
취수구 2184
98.2%
착수정 40
 
1.8%

Length

2023-12-12T17:17:36.786268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:36.895839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
취수구 2184
98.2%
착수정 40
 
1.8%

수원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
지하수
1992 
용천수
232 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하수 1992
89.6%
용천수 232
 
10.4%

Length

2023-12-12T17:17:37.001490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:37.122515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하수 1992
89.6%
용천수 232
 
10.4%

카드뮴
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:37.284843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:37.410536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

비소
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.6546763 × 10-5
Minimum0
Maximum0.013
Zeros2206
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:37.504841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0.013
Range0.013
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0007735364
Coefficient of variation (CV)11.623952
Kurtosis168.70983
Mean6.6546763 × 10-5
Median Absolute Deviation (MAD)0
Skewness12.602973
Sum0.148
Variance5.9835856 × 10-7
MonotonicityNot monotonic
2023-12-12T17:17:37.621361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 2206
99.2%
0.006 5
 
0.2%
0.013 2
 
0.1%
0.01 2
 
0.1%
0.008 2
 
0.1%
0.007 2
 
0.1%
0.005 2
 
0.1%
0.011 1
 
< 0.1%
0.009 1
 
< 0.1%
0.012 1
 
< 0.1%
ValueCountFrequency (%)
0.0 2206
99.2%
0.005 2
 
0.1%
0.006 5
 
0.2%
0.007 2
 
0.1%
0.008 2
 
0.1%
0.009 1
 
< 0.1%
0.01 2
 
0.1%
0.011 1
 
< 0.1%
0.012 1
 
< 0.1%
0.013 2
 
0.1%
ValueCountFrequency (%)
0.013 2
 
0.1%
0.012 1
 
< 0.1%
0.011 1
 
< 0.1%
0.01 2
 
0.1%
0.009 1
 
< 0.1%
0.008 2
 
0.1%
0.007 2
 
0.1%
0.006 5
 
0.2%
0.005 2
 
0.1%
0.0 2206
99.2%

시안
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:37.739538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:37.830014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

수은
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:37.920895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.009640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

납
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:38.100564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.184418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

크롬
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:38.269176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.356203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

다이아지논
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:38.453680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.565449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

파라티온
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:38.676904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.769127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

페니트로티온
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:38.870983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:38.994293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

음이온 계면활성제
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0.0
2221 
0.21
 
2
0.36
 
1

Length

Max length4
Median length3
Mean length3.0013489
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 2221
99.9%
0.21 2
 
0.1%
0.36 1
 
< 0.1%

Length

2023-12-12T17:17:39.101518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:39.234994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2221
99.9%
0.21 2
 
0.1%
0.36 1
 
< 0.1%

불소
Real number (ℝ)

ZEROS 

Distinct57
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.028767986
Minimum0
Maximum1.41
Zeros2011
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:39.655588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.25
Maximum1.41
Range1.41
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.10344151
Coefficient of variation (CV)3.5957161
Kurtosis31.404074
Mean0.028767986
Median Absolute Deviation (MAD)0
Skewness4.8231475
Sum63.98
Variance0.010700146
MonotonicityNot monotonic
2023-12-12T17:17:39.837805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2011
90.4%
0.16 14
 
0.6%
0.29 13
 
0.6%
0.27 11
 
0.5%
0.25 11
 
0.5%
0.26 10
 
0.4%
0.19 9
 
0.4%
0.15 9
 
0.4%
0.18 9
 
0.4%
0.28 8
 
0.4%
Other values (47) 119
 
5.4%
ValueCountFrequency (%)
0.0 2011
90.4%
0.05 2
 
0.1%
0.07 1
 
< 0.1%
0.08 3
 
0.1%
0.11 3
 
0.1%
0.12 1
 
< 0.1%
0.14 2
 
0.1%
0.15 9
 
0.4%
0.16 14
 
0.6%
0.17 8
 
0.4%
ValueCountFrequency (%)
1.41 1
 
< 0.1%
0.97 1
 
< 0.1%
0.85 1
 
< 0.1%
0.72 2
0.1%
0.7 1
 
< 0.1%
0.66 1
 
< 0.1%
0.65 1
 
< 0.1%
0.62 1
 
< 0.1%
0.61 2
0.1%
0.6 4
0.2%

셀레늄
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:39.987399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:40.086285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

암모니아성질소
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00034802158
Minimum0
Maximum0.2
Zeros2202
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:40.196683image/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 deviation0.0056085626
Coefficient of variation (CV)16.11556
Kurtosis810.91789
Mean0.00034802158
Median Absolute Deviation (MAD)0
Skewness25.999814
Sum0.774
Variance3.1455974 × 10-5
MonotonicityNot monotonic
2023-12-12T17:17:40.343569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 2202
99.0%
0.01 11
 
0.5%
0.02 2
 
0.1%
0.05 2
 
0.1%
0.014 1
 
< 0.1%
0.04 1
 
< 0.1%
0.2 1
 
< 0.1%
0.03 1
 
< 0.1%
0.11 1
 
< 0.1%
0.07 1
 
< 0.1%
ValueCountFrequency (%)
0.0 2202
99.0%
0.01 11
 
0.5%
0.014 1
 
< 0.1%
0.02 2
 
0.1%
0.03 1
 
< 0.1%
0.04 1
 
< 0.1%
0.05 2
 
0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.11 1
 
< 0.1%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.11 1
 
< 0.1%
0.07 1
 
< 0.1%
0.06 1
 
< 0.1%
0.05 2
 
0.1%
0.04 1
 
< 0.1%
0.03 1
 
< 0.1%
0.02 2
 
0.1%
0.014 1
 
< 0.1%
0.01 11
0.5%

질산성질소
Real number (ℝ)

Distinct98
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3025301
Minimum0
Maximum11.6
Zeros20
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size19.7 KiB
2023-12-12T17:17:40.517815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q11.4
median2.2
Q32.9
95-th percentile4.8
Maximum11.6
Range11.6
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.4581645
Coefficient of variation (CV)0.63328792
Kurtosis4.6734644
Mean2.3025301
Median Absolute Deviation (MAD)0.8
Skewness1.5070925
Sum5120.827
Variance2.1262437
MonotonicityNot monotonic
2023-12-12T17:17:40.696026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.4 109
 
4.9%
2.2 91
 
4.1%
1.8 86
 
3.9%
1.7 80
 
3.6%
2.5 78
 
3.5%
2.1 74
 
3.3%
2.3 73
 
3.3%
1.9 72
 
3.2%
2.0 72
 
3.2%
1.6 64
 
2.9%
Other values (88) 1425
64.1%
ValueCountFrequency (%)
0.0 20
 
0.9%
0.1 27
1.2%
0.2 59
2.7%
0.3 34
1.5%
0.4 27
1.2%
0.5 32
1.4%
0.6 41
1.8%
0.7 44
2.0%
0.8 33
1.5%
0.9 37
1.7%
ValueCountFrequency (%)
11.6 1
< 0.1%
10.9 1
< 0.1%
9.8 1
< 0.1%
9.7 1
< 0.1%
9.5 1
< 0.1%
9.4 1
< 0.1%
9.3 2
0.1%
9.2 2
0.1%
9.1 1
< 0.1%
8.8 1
< 0.1%

카바릴
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0.0
2223 
0.005
 
1

Length

Max length5
Median length3
Mean length3.0008993
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 2223
> 99.9%
0.005 1
 
< 0.1%

Length

2023-12-12T17:17:40.853540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:40.997956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2223
> 99.9%
0.005 1
 
< 0.1%

1_1_1-트리클로로에탄
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0.0
2223 
0.001
 
1

Length

Max length5
Median length3
Mean length3.0008993
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 2223
> 99.9%
0.001 1
 
< 0.1%

Length

2023-12-12T17:17:41.143236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:41.287369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2223
> 99.9%
0.001 1
 
< 0.1%

테트라클로로에틸렌
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0.0
2223 
0.001
 
1

Length

Max length5
Median length3
Mean length3.0008993
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 2223
> 99.9%
0.001 1
 
< 0.1%

Length

2023-12-12T17:17:41.424820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:41.552618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2223
> 99.9%
0.001 1
 
< 0.1%

트리클로로에틸렌
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0.0
2221 
0.003
 
2
0.001
 
1

Length

Max length5
Median length3
Mean length3.0026978
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 2221
99.9%
0.003 2
 
0.1%
0.001 1
 
< 0.1%

Length

2023-12-12T17:17:41.668729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:41.809156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 2221
99.9%
0.003 2
 
0.1%
0.001 1
 
< 0.1%

페놀
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.5 KiB
0
2224 

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 2224
100.0%

Length

2023-12-12T17:17:41.922977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:17:42.028333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2224
100.0%

Sample

연번검사년도검사반기지역소규모수도시설명측정지점주소채수위치수원카드뮴비소시안수은납크롬다이아지논파라티온페니트로티온음이온 계면활성제불소셀레늄암모니아성질소질산성질소카바릴1_1_1-트리클로로에탄테트라클로로에틸렌트리클로로에틸렌페놀
012015상반기강원도 삼척시임원강원도 삼척시 원덕읍 임원리 915착수정지하수00.000000000.00.000.00.90.00.00.00.00
122015상반기강원도 영월군주천강원도 영월군 주천면 도천길 673취수구지하수00.000000000.00.000.01.80.00.00.00.00
232015상반기강원도 영월군하동강원도 영월군 김삿갓면 강변로 1462-23취수구지하수00.000000000.00.000.01.30.00.00.00.00
342015상반기강원도 원주시귀래강원도 원주시 귀래면 한치길 1141취수구지하수00.000000000.00.000.01.40.00.00.00.00
452015상반기강원도 원주시신림강원도 원주시 신림면 둔창예찬길 5147취수구지하수00.000000000.00.000.03.60.00.00.00.00
562015상반기강원도 인제군상남취수장강원도 인제군 상남면 상남리 천1759 (상남리 722 인근)취수구지하수00.000000000.00.200.02.40.00.00.00.00
672015상반기강원도 인제군상남취수장강원도 인제군 상남면 상남리 천1759 (상남리 722 인근)취수구지하수00.000000000.00.1900.02.40.00.00.00.00
782015상반기강원도 태백시혈리강원도 태백시 태백산로 4499 (혈동)취수구용천수00.000000000.00.000.01.80.00.00.00.00
892015상반기경기도 안성시죽산경기도 안성시 죽산면 죽양대로 8취수구지하수00.000000000.00.1900.01.10.00.00.00.00
9102015상반기경기도 포천시관인경기도 포천시 관인면 냉정리 산1414취수구지하수00.000000000.00.000.03.50.00.00.00.00
연번검사년도검사반기지역소규모수도시설명측정지점주소채수위치수원카드뮴비소시안수은납크롬다이아지논파라티온페니트로티온음이온 계면활성제불소셀레늄암모니아성질소질산성질소카바릴1_1_1-트리클로로에탄테트라클로로에틸렌트리클로로에틸렌페놀
221422152022하반기충청북도 괴산군청천-5호정충청북도 괴산군 청천면 선평리 175취수구지하수00.000000000.00.000.04.20.00.00.00.00
221522162022하반기충청북도 단양군영춘충청북도 단양군 영춘면 하리 167취수구지하수00.000000000.00.000.03.50.00.00.00.00
221622172022하반기충청북도 보은군내북충청북도 보은군 내북면 도원리 2306외 5개소취수구지하수00.000000000.00.000.03.40.00.00.00.00
221722182022하반기충청북도 진천군백곡충청북도 진천군 백곡면 석현리 12816취수구지하수00.000000000.00.000.07.50.00.00.00.00
221822192022하반기충청북도 청주시낭성 #1관정충청북도 청주시 상당구 낭성면 이목리 96-4취수구지하수00.000000000.00.000.02.60.00.00.00.00
221922202022하반기충청북도 청주시낭성 #2관정충청북도 청주시 상당구 낭성면 이목리 865취수구지하수00.000000000.00.000.02.30.00.00.00.00
222022212022하반기충청북도 청주시미원 #1관정충청북도 청주시 상당구 미원면 쌍이리 393취수구지하수00.000000000.00.000.01.70.00.00.00.00
222122222022하반기충청북도 청주시미원 #2관정충청북도 청주시 상당구 미원면 내산리 962취수구지하수00.000000000.00.000.02.20.00.00.00.00
222222232022하반기충청북도 청주시미원 #3관정충청북도 청주시 상당구 미원면 내산리 519취수구지하수00.000000000.00.000.03.30.00.00.00.00
222322242022하반기충청북도 청주시미원 #4관정충청북도 청주시 상당구 미원면 미원리 568취수구지하수00.000000000.00.000.04.10.00.00.00.00