Overview

Dataset statistics

Number of variables16
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory141.5 B

Variable types

Numeric2
Categorical14

Dataset

Description수도법에 따라 2년마다 소규모수도시설에서 호소수를 원수로 사용하는 원수 수질 검사 결과 데이터로, 수질검사결과, 수질검사기관 등을 포함 * 상세자료조회는 아래 URL을 참고 해주시기 바랍니다. https://www.waternow.go.kr/web/lawData7/?pMENUID=150&ATTR_1=3203
URLhttps://www.data.go.kr/data/15094000/fileData.do

Alerts

수원 has constant value ""Constant
카드뮴 has constant value ""Constant
비소 has constant value ""Constant
시안 has constant value ""Constant
수은 has constant value ""Constant
납 has constant value ""Constant
크롬 has constant value ""Constant
유기인 has constant value ""Constant
폴리크로리네이티드페닐 has constant value ""Constant
음이온 계면활성제 has constant value ""Constant
측정지점주소 is highly overall correlated with 지역 and 2 other fieldsHigh correlation
소규모수도시설명 is highly overall correlated with 지역 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 검사년도High correlation
검사년도 is highly overall correlated with 연번High correlation
지역 is highly overall correlated with 소규모수도시설명 and 2 other fieldsHigh correlation
수도규모 is highly overall correlated with 지역 and 2 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:09:18.066280
Analysis finished2023-12-12 06:09:19.541619
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T15:09:19.610622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-12-12T15:09:19.766004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

검사년도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5769
Minimum2015
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-12T15:09:19.937032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2019
Q32021
95-th percentile2021
Maximum2022
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.0802164
Coefficient of variation (CV)0.0010305361
Kurtosis-1.0505245
Mean2018.5769
Median Absolute Deviation (MAD)2
Skewness-0.18112173
Sum104966
Variance4.3273002
MonotonicityIncreasing
2023-12-12T15:09:20.077462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2017 13
25.0%
2021 12
23.1%
2019 11
21.2%
2015 6
11.5%
2020 4
 
7.7%
2018 3
 
5.8%
2022 2
 
3.8%
2016 1
 
1.9%
ValueCountFrequency (%)
2015 6
11.5%
2016 1
 
1.9%
2017 13
25.0%
2018 3
 
5.8%
2019 11
21.2%
2020 4
 
7.7%
2021 12
23.1%
2022 2
 
3.8%
ValueCountFrequency (%)
2022 2
 
3.8%
2021 12
23.1%
2020 4
 
7.7%
2019 11
21.2%
2018 3
 
5.8%
2017 13
25.0%
2016 1
 
1.9%
2015 6
11.5%

지역
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
전라남도 신안군
22 
전라북도 군산시
9 
전라남도 영광군
5 
경상북도 울진군
4 
대구광역시
4 
Other values (5)
8 

Length

Max length8
Median length8
Mean length7.7692308
Min length5

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row전라남도 광양시
2nd row전라남도 영광군
3rd row전라북도 군산시
4th row전라북도 군산시
5th row전라북도 군산시

Common Values

ValueCountFrequency (%)
전라남도 신안군 22
42.3%
전라북도 군산시 9
17.3%
전라남도 영광군 5
 
9.6%
경상북도 울진군 4
 
7.7%
대구광역시 4
 
7.7%
전라남도 광양시 2
 
3.8%
경상남도 의령군 2
 
3.8%
경상북도 경주시 2
 
3.8%
전라남도 여수시 1
 
1.9%
전라북도 무주군 1
 
1.9%

Length

2023-12-12T15:09:20.248734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:20.395014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 30
30.0%
신안군 22
22.0%
전라북도 10
 
10.0%
군산시 9
 
9.0%
경상북도 6
 
6.0%
영광군 5
 
5.0%
울진군 4
 
4.0%
대구광역시 4
 
4.0%
광양시 2
 
2.0%
경상남도 2
 
2.0%
Other values (4) 6
 
6.0%

소규모수도시설명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size548.0 B
송이
5 
대둔도
4 
돈목
 
3
매화
 
3
어청도
 
3
Other values (17)
34 

Length

Max length6
Median length5
Mean length2.9807692
Min length2

Unique

Unique4 ?
Unique (%)7.7%

Sample

1st row광양제철
2nd row송이
3rd row무녀도
4th row비안도
5th row선유도

Common Values

ValueCountFrequency (%)
송이 5
 
9.6%
대둔도 4
 
7.7%
돈목 3
 
5.8%
매화 3
 
5.8%
어청도 3
 
5.8%
진리 3
 
5.8%
수치 3
 
5.8%
병풍도 3
 
5.8%
고사 3
 
5.8%
대의정수장 2
 
3.8%
Other values (12) 20
38.5%

Length

2023-12-12T15:09:20.551726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송이 5
 
9.6%
대둔도 4
 
7.7%
돈목 3
 
5.8%
매화 3
 
5.8%
어청도 3
 
5.8%
진리 3
 
5.8%
수치 3
 
5.8%
병풍도 3
 
5.8%
고사 3
 
5.8%
위덕대학교 2
 
3.8%
Other values (12) 20
38.5%

측정지점주소
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size548.0 B
전라남도 영광군 낙월면 송이 소촌
5 
전라남도 신안군 흑산면 대둔도 수리
4 
전라남도 신안군 도초면 우이도 돈목
 
3
전라남도 신안군 압해읍 매화도
 
3
전라북도 군산시 옥도면 어청도리 68
 
3
Other values (17)
34 

Length

Max length21
Median length19
Mean length17.096154
Min length5

Unique

Unique4 ?
Unique (%)7.7%

Sample

1st row전라남도 광양시 금호동
2nd row전라남도 영광군 낙월면 송이 소촌
3rd row전라북도 군산시 옥도면 무녀도리
4th row전라북도 군산시 옥도면 비안도리
5th row전라북도 군산시 옥도면 선유도리

Common Values

ValueCountFrequency (%)
전라남도 영광군 낙월면 송이 소촌 5
 
9.6%
전라남도 신안군 흑산면 대둔도 수리 4
 
7.7%
전라남도 신안군 도초면 우이도 돈목 3
 
5.8%
전라남도 신안군 압해읍 매화도 3
 
5.8%
전라북도 군산시 옥도면 어청도리 68 3
 
5.8%
전라남도 신안군 도초면 우이도 지리 3
 
5.8%
전라남도 신안군 비금면 수치리 3
 
5.8%
전라남도 신안군 증도면 병풍도리 3
 
5.8%
전라남도 신안군 신의면 고평사리 고사 3
 
5.8%
662-6 2
 
3.8%
Other values (12) 20
38.5%

Length

2023-12-12T15:09:20.687884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라남도 30
 
13.4%
신안군 22
 
9.8%
전라북도 10
 
4.5%
옥도면 9
 
4.0%
군산시 9
 
4.0%
경상북도 6
 
2.7%
도초면 6
 
2.7%
우이도 6
 
2.7%
낙월면 5
 
2.2%
송이 5
 
2.2%
Other values (46) 116
51.8%

수도규모
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
마을상수도
42 
전용상수도시설
7 
소규모급수시설
 
3

Length

Max length7
Median length5
Mean length5.3846154
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전용상수도시설
2nd row마을상수도
3rd row마을상수도
4th row마을상수도
5th row마을상수도

Common Values

ValueCountFrequency (%)
마을상수도 42
80.8%
전용상수도시설 7
 
13.5%
소규모급수시설 3
 
5.8%

Length

2023-12-12T15:09:20.893757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:21.122033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을상수도 42
80.8%
전용상수도시설 7
 
13.5%
소규모급수시설 3
 
5.8%

수원
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
호소수
52 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
호소수 52
100.0%

Length

2023-12-12T15:09:21.260009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:21.344135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호소수 52
100.0%

카드뮴
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:21.450089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:21.563797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

비소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:21.658683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:21.767205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

시안
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:21.857912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:21.946619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

수은
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:22.035744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:22.153152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

납
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:22.289773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:22.392031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

크롬
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:22.487107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:22.577948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

유기인
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:22.682425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:22.816757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

폴리크로리네이티드페닐
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:22.947261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:23.049986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

음이온 계면활성제
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
0
52 

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 52
100.0%

Length

2023-12-12T15:09:23.155794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:09:23.268039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 52
100.0%

Interactions

2023-12-12T15:09:18.723678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:09:18.514815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:09:18.834861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:09:18.609894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:09:23.329520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번검사년도지역소규모수도시설명측정지점주소수도규모
연번1.0000.7910.5290.0000.0000.000
검사년도0.7911.0000.4200.0000.0000.000
지역0.5290.4201.0001.0001.0000.721
소규모수도시설명0.0000.0001.0001.0001.0001.000
측정지점주소0.0000.0001.0001.0001.0001.000
수도규모0.0000.0000.7211.0001.0001.000
2023-12-12T15:09:23.439885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정지점주소수도규모지역소규모수도시설명
측정지점주소1.0000.7820.8451.000
수도규모0.7821.0000.5370.782
지역0.8450.5371.0000.845
소규모수도시설명1.0000.7820.8451.000
2023-12-12T15:09:23.524817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번검사년도지역소규모수도시설명측정지점주소수도규모
연번1.0000.9800.1760.0000.0000.000
검사년도0.9801.0000.2620.0000.0000.000
지역0.1760.2621.0000.8450.8450.537
소규모수도시설명0.0000.0000.8451.0001.0000.782
측정지점주소0.0000.0000.8451.0001.0000.782
수도규모0.0000.0000.5370.7820.7821.000

Missing values

2023-12-12T15:09:18.986884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:09:19.466251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번검사년도지역소규모수도시설명측정지점주소수도규모수원카드뮴비소시안수은납크롬유기인폴리크로리네이티드페닐음이온 계면활성제
012015전라남도 광양시광양제철전라남도 광양시 금호동전용상수도시설호소수000000000
122015전라남도 영광군송이전라남도 영광군 낙월면 송이 소촌마을상수도호소수000000000
232015전라북도 군산시무녀도전라북도 군산시 옥도면 무녀도리마을상수도호소수000000000
342015전라북도 군산시비안도전라북도 군산시 옥도면 비안도리마을상수도호소수000000000
452015전라북도 군산시선유도전라북도 군산시 옥도면 선유도리마을상수도호소수000000000
562015전라북도 군산시신시도전라북도 군산시 옥도면 신시도리마을상수도호소수000000000
672016경상북도 울진군흥부경상북도 울진군 북면 부구1마을상수도호소수000000000
782017경상남도 의령군대의정수장662-6마을상수도호소수000000000
892017경상북도 경주시위덕대학교경상북도 경주시 강동면 유금리 산50전용상수도시설호소수000000000
9102017전라남도 광양시광양제철전라남도 광양시 금호동전용상수도시설호소수000000000
연번검사년도지역소규모수도시설명측정지점주소수도규모수원카드뮴비소시안수은납크롬유기인폴리크로리네이티드페닐음이온 계면활성제
42432021전라남도 신안군고사전라남도 신안군 신의면 고평사리 고사소규모급수시설호소수000000000
43442021전라남도 신안군대둔도전라남도 신안군 흑산면 대둔도 수리마을상수도호소수000000000
44452021전라남도 신안군돈목전라남도 신안군 도초면 우이도 돈목마을상수도호소수000000000
45462021전라남도 신안군매화전라남도 신안군 압해읍 매화도마을상수도호소수000000000
46472021전라남도 신안군병풍도전라남도 신안군 증도면 병풍도리마을상수도호소수000000000
47482021전라남도 신안군수치전라남도 신안군 비금면 수치리마을상수도호소수000000000
48492021전라남도 신안군진리전라남도 신안군 도초면 우이도 지리마을상수도호소수000000000
49502021전라북도 무주군무주리조트전라북도 무주군 설천면 심곡리 1352전용상수도시설호소수000000000
50512022전라남도 영광군송이전라남도 영광군 낙월면 송이 소촌마을상수도호소수000000000
51522022전라북도 군산시어청도전라북도 군산시 옥도면 어청도리 68마을상수도호소수000000000