Overview

Dataset statistics

Number of variables6
Number of observations526
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.3 KiB
Average record size in memory49.2 B

Variable types

Categorical4
DateTime1
Numeric1

Dataset

Description낙동강유역의 취수장 고도정수처리시설의 원수 분석 결과 입니다.검사주기 : 월 단위채수지점(정수장명)- 문산취수장(문산정수장)- 매곡취수장(매곡정수장)- 칠서취수장(칠서정수장)- 본포취수장(석동정수장)- 창암취수장(삼계정수장, 명동정수장)- 매리취수장(덕산정수장)- 원동취수장(천상정수장, 회야정수장, 웅상정수장)- 물금취수장(화명정수장, 명장정수장)- 신도시취수장(범어정수장)제공항목- BOD(1~4차) 및 평균 값- TOC(1~4차) 및 평균 값
Author한국수자원공사
URLhttps://www.data.go.kr/data/15119029/fileData.do

Alerts

채수지점 is highly overall correlated with 정수장명High correlation
정수장명 is highly overall correlated with 채수지점High correlation
분석값 is highly overall correlated with 분석유형High correlation
분석유형 is highly overall correlated with 분석값High correlation

Reproduction

Analysis started2024-03-14 10:35:12.469552
Analysis finished2024-03-14 10:35:13.692309
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채수지점
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
원동취수장
111 
창암취수장
78 
물금취수장
74 
신도시취수장
74 
칠서취수장
39 
Other values (4)
150 

Length

Max length6
Median length5
Mean length5.1406844
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원동취수장 111
21.1%
창암취수장 78
14.8%
물금취수장 74
14.1%
신도시취수장 74
14.1%
칠서취수장 39
 
7.4%
본포취수장 39
 
7.4%
문산취수장 37
 
7.0%
매곡취수장 37
 
7.0%
매리취수장 37
 
7.0%

Length

2024-03-14T19:35:13.910337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:35:14.257353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원동취수장 111
21.1%
창암취수장 78
14.8%
물금취수장 74
14.1%
신도시취수장 74
14.1%
칠서취수장 39
 
7.4%
본포취수장 39
 
7.4%
문산취수장 37
 
7.0%
매곡취수장 37
 
7.0%
매리취수장 37
 
7.0%

정수장명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
칠서
39 
석동
39 
삼계
39 
명동
39 
문산
37 
Other values (9)
333 

Length

Max length3
Median length2
Mean length2.0703422
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
칠서 39
 
7.4%
석동 39
 
7.4%
삼계 39
 
7.4%
명동 39
 
7.4%
문산 37
 
7.0%
매곡 37
 
7.0%
덕산 37
 
7.0%
천상 37
 
7.0%
회야 37
 
7.0%
웅상 37
 
7.0%
Other values (4) 148
28.1%

Length

2024-03-14T19:35:14.495334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
칠서 39
 
7.4%
석동 39
 
7.4%
삼계 39
 
7.4%
명동 39
 
7.4%
문산 37
 
7.0%
매곡 37
 
7.0%
덕산 37
 
7.0%
천상 37
 
7.0%
회야 37
 
7.0%
웅상 37
 
7.0%
Other values (4) 148
28.1%

주차
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
1주차
140 
3주차
140 
2주차
124 
4주차
122 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1주차
2nd row2주차
3rd row3주차
4th row1주차
5th row2주차

Common Values

ValueCountFrequency (%)
1주차 140
26.6%
3주차 140
26.6%
2주차 124
23.6%
4주차 122
23.2%

Length

2024-03-14T19:35:14.696704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:35:14.937209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1주차 140
26.6%
3주차 140
26.6%
2주차 124
23.6%
4주차 122
23.2%

분석일
Date

Distinct35
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
Minimum2023-08-01 00:00:00
Maximum2023-12-27 00:00:00
2024-03-14T19:35:15.272282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:35:15.688435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

분석유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.2 KiB
TOC
270 
BOD
256 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBOD
2nd rowBOD
3rd rowBOD
4th rowTOC
5th rowTOC

Common Values

ValueCountFrequency (%)
TOC 270
51.3%
BOD 256
48.7%

Length

2024-03-14T19:35:16.095781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:35:16.597316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
toc 270
51.3%
bod 256
48.7%

분석값
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2022814
Minimum0.2
Maximum6.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.7 KiB
2024-03-14T19:35:16.927719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.4
Q11
median2
Q33.4
95-th percentile4.475
Maximum6.8
Range6.6
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation1.3794804
Coefficient of variation (CV)0.626387
Kurtosis-0.91230794
Mean2.2022814
Median Absolute Deviation (MAD)1.2
Skewness0.39628568
Sum1158.4
Variance1.9029662
MonotonicityNot monotonic
2024-03-14T19:35:17.378722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 25
 
4.8%
1.2 23
 
4.4%
0.9 20
 
3.8%
1.4 19
 
3.6%
1.3 19
 
3.6%
1.0 18
 
3.4%
0.7 17
 
3.2%
0.4 17
 
3.2%
0.5 17
 
3.2%
3.9 16
 
3.0%
Other values (43) 335
63.7%
ValueCountFrequency (%)
0.2 6
 
1.1%
0.3 13
2.5%
0.4 17
3.2%
0.5 17
3.2%
0.6 12
2.3%
0.7 17
3.2%
0.8 25
4.8%
0.9 20
3.8%
1.0 18
3.4%
1.1 15
2.9%
ValueCountFrequency (%)
6.8 1
 
0.2%
6.0 1
 
0.2%
5.8 2
 
0.4%
5.4 2
 
0.4%
5.0 1
 
0.2%
4.9 1
 
0.2%
4.8 3
0.6%
4.7 3
0.6%
4.6 6
1.1%
4.5 7
1.3%

Interactions

2024-03-14T19:35:12.841688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:35:17.656367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채수지점정수장명주차분석일분석유형분석값
채수지점1.0001.0000.0000.4960.0000.295
정수장명1.0001.0000.0000.0000.0000.211
주차0.0000.0001.0001.0000.0000.272
분석일0.4960.0001.0001.0000.0000.706
분석유형0.0000.0000.0000.0001.0000.992
분석값0.2950.2110.2720.7060.9921.000
2024-03-14T19:35:17.935367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석유형채수지점정수장명주차
분석유형1.0000.0000.0000.000
채수지점0.0001.0000.9950.000
정수장명0.0000.9951.0000.000
주차0.0000.0000.0001.000
2024-03-14T19:35:18.192905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분석값채수지점정수장명주차분석유형
분석값1.0000.1350.0800.1610.915
채수지점0.1351.0000.9950.0000.000
정수장명0.0800.9951.0000.0000.000
주차0.1610.0000.0001.0000.000
분석유형0.9150.0000.0000.0001.000

Missing values

2024-03-14T19:35:13.201238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:35:13.548893image/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

채수지점정수장명주차분석일분석유형분석값
0문산취수장문산1주차2023-08-01BOD1.4
1문산취수장문산2주차2023-08-08BOD2.3
2문산취수장문산3주차2023-08-22BOD0.9
3문산취수장문산1주차2023-08-01TOC4.3
4문산취수장문산2주차2023-08-08TOC4.5
5문산취수장문산3주차2023-08-22TOC6.0
6매곡취수장매곡1주차2023-08-01BOD1.3
7매곡취수장매곡2주차2023-08-08BOD1.3
8매곡취수장매곡3주차2023-08-22BOD0.6
9매곡취수장매곡1주차2023-08-01TOC4.3
채수지점정수장명주차분석일분석유형분석값
516신도시취수장범어3주차2023-12-20TOC2.3
517신도시취수장범어4주차2023-12-27TOC2.0
518신도시취수장신도시1주차2023-12-06BOD0.6
519신도시취수장신도시2주차2023-12-13BOD0.8
520신도시취수장신도시3주차2023-12-20BOD0.4
521신도시취수장신도시4주차2023-12-27BOD1.3
522신도시취수장신도시1주차2023-12-06TOC2.0
523신도시취수장신도시2주차2023-12-13TOC2.5
524신도시취수장신도시3주차2023-12-20TOC2.3
525신도시취수장신도시4주차2023-12-27TOC2.0