Overview

Dataset statistics

Number of variables5
Number of observations120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory45.1 B

Variable types

Numeric4
Categorical1

Dataset

Description양산시 2011년부터 2020년까지 월별 취수량을 원동취수장, 물금취수장, 신도시취수장 등 지역별 취수량을 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15085964

Alerts

기준일 has constant value ""Constant
연도 is highly overall correlated with 온양가압장(원동취수장) 월 취수량 and 2 other fieldsHigh correlation
온양가압장(원동취수장) 월 취수량 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
물금취수장 월 취수량 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
신도시취수장 월 취수량 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
온양가압장(원동취수장) 월 취수량 has unique valuesUnique
신도시취수장 월 취수량 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:04:45.967160
Analysis finished2023-12-11 00:04:48.086390
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.5
Minimum2011
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T09:04:48.156826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013
median2015.5
Q32018
95-th percentile2020
Maximum2020
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8843245
Coefficient of variation (CV)0.0014310714
Kurtosis-1.2251099
Mean2015.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum241860
Variance8.3193277
MonotonicityIncreasing
2023-12-11T09:04:48.295668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2011 12
10.0%
2012 12
10.0%
2013 12
10.0%
2014 12
10.0%
2015 12
10.0%
2016 12
10.0%
2017 12
10.0%
2018 12
10.0%
2019 12
10.0%
2020 12
10.0%
ValueCountFrequency (%)
2011 12
10.0%
2012 12
10.0%
2013 12
10.0%
2014 12
10.0%
2015 12
10.0%
2016 12
10.0%
2017 12
10.0%
2018 12
10.0%
2019 12
10.0%
2020 12
10.0%
ValueCountFrequency (%)
2020 12
10.0%
2019 12
10.0%
2018 12
10.0%
2017 12
10.0%
2016 12
10.0%
2015 12
10.0%
2014 12
10.0%
2013 12
10.0%
2012 12
10.0%
2011 12
10.0%

온양가압장(원동취수장) 월 취수량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean836826.43
Minimum630870
Maximum998859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T09:04:48.463094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum630870
5-th percentile676562
Q1780427.5
median849300
Q3907515
95-th percentile964677
Maximum998859
Range367989
Interquartile range (IQR)127087.5

Descriptive statistics

Standard deviation91401.748
Coefficient of variation (CV)0.10922426
Kurtosis-0.73082249
Mean836826.43
Median Absolute Deviation (MAD)64600
Skewness-0.43797834
Sum1.0041917 × 108
Variance8.3542795 × 109
MonotonicityNot monotonic
2023-12-11T09:04:48.614487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
752710 1
 
0.8%
782320 1
 
0.8%
847820 1
 
0.8%
901630 1
 
0.8%
863500 1
 
0.8%
893820 1
 
0.8%
843830 1
 
0.8%
913310 1
 
0.8%
947690 1
 
0.8%
913080 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
630870 1
0.8%
636440 1
0.8%
638350 1
0.8%
670160 1
0.8%
671250 1
0.8%
674890 1
0.8%
676650 1
0.8%
678800 1
0.8%
680570 1
0.8%
682600 1
0.8%
ValueCountFrequency (%)
998859 1
0.8%
990420 1
0.8%
974910 1
0.8%
973289 1
0.8%
972510 1
0.8%
972030 1
0.8%
964290 1
0.8%
955800 1
0.8%
947690 1
0.8%
947170 1
0.8%

물금취수장 월 취수량
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean425299.03
Minimum79400
Maximum1052620
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T09:04:48.780015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum79400
5-th percentile149427
Q1244558
median338490
Q3629630
95-th percentile887337
Maximum1052620
Range973220
Interquartile range (IQR)385072

Descriptive statistics

Standard deviation240180.63
Coefficient of variation (CV)0.56473355
Kurtosis-0.37740954
Mean425299.03
Median Absolute Deviation (MAD)134610
Skewness0.77726677
Sum51035884
Variance5.7686737 × 1010
MonotonicityNot monotonic
2023-12-11T09:04:48.960635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
244360 2
 
1.7%
167130 1
 
0.8%
464230 1
 
0.8%
865780 1
 
0.8%
871340 1
 
0.8%
1001000 1
 
0.8%
1052620 1
 
0.8%
946940 1
 
0.8%
1004840 1
 
0.8%
959480 1
 
0.8%
Other values (109) 109
90.8%
ValueCountFrequency (%)
79400 1
0.8%
79750 1
0.8%
102350 1
0.8%
114640 1
0.8%
125410 1
0.8%
126380 1
0.8%
150640 1
0.8%
157300 1
0.8%
160910 1
0.8%
166180 1
0.8%
ValueCountFrequency (%)
1052620 1
0.8%
1004840 1
0.8%
1001000 1
0.8%
959480 1
0.8%
950030 1
0.8%
946940 1
0.8%
884200 1
0.8%
871340 1
0.8%
865780 1
0.8%
811970 1
0.8%

신도시취수장 월 취수량
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365715.38
Minimum830
Maximum1009090
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T09:04:49.115641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum830
5-th percentile167671
Q1263275
median347030
Q3403407.5
95-th percentile805180
Maximum1009090
Range1008260
Interquartile range (IQR)140132.5

Descriptive statistics

Standard deviation172069.53
Coefficient of variation (CV)0.4705012
Kurtosis4.3457919
Mean365715.38
Median Absolute Deviation (MAD)69365
Skewness1.8131661
Sum43885846
Variance2.9607922 × 1010
MonotonicityNot monotonic
2023-12-11T09:04:49.297291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
238700 1
 
0.8%
304400 1
 
0.8%
690080 1
 
0.8%
750120 1
 
0.8%
831840 1
 
0.8%
828360 1
 
0.8%
803960 1
 
0.8%
931500 1
 
0.8%
957640 1
 
0.8%
966190 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
830 1
0.8%
106060 1
0.8%
141110 1
0.8%
145730 1
0.8%
158980 1
0.8%
166360 1
0.8%
167740 1
0.8%
168190 1
0.8%
181010 1
0.8%
195240 1
0.8%
ValueCountFrequency (%)
1009090 1
0.8%
966190 1
0.8%
957640 1
0.8%
931500 1
0.8%
831840 1
0.8%
828360 1
0.8%
803960 1
0.8%
750120 1
0.8%
690080 1
0.8%
555010 1
0.8%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2021-08-12
120 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-12
2nd row2021-08-12
3rd row2021-08-12
4th row2021-08-12
5th row2021-08-12

Common Values

ValueCountFrequency (%)
2021-08-12 120
100.0%

Length

2023-12-11T09:04:49.445448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:04:49.551854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-12 120
100.0%

Interactions

2023-12-11T09:04:47.451171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.114676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.574704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.056412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.569226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.224056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.690623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.151794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.687673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.335504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.806744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.278174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.793157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.462334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:46.940000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:04:47.357610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:04:49.626836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도온양가압장(원동취수장) 월 취수량물금취수장 월 취수량신도시취수장 월 취수량
연도1.0000.7180.7120.740
온양가압장(원동취수장) 월 취수량0.7181.0000.5220.305
물금취수장 월 취수량0.7120.5221.0000.745
신도시취수장 월 취수량0.7400.3050.7451.000
2023-12-11T09:04:49.742157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도온양가압장(원동취수장) 월 취수량물금취수장 월 취수량신도시취수장 월 취수량
연도1.0000.8130.7350.602
온양가압장(원동취수장) 월 취수량0.8131.0000.6420.619
물금취수장 월 취수량0.7350.6421.0000.403
신도시취수장 월 취수량0.6020.6190.4031.000

Missing values

2023-12-11T09:04:47.913663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:04:48.029808image/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

연도온양가압장(원동취수장) 월 취수량물금취수장 월 취수량신도시취수장 월 취수량기준일
020117527101671302387002021-08-12
120116957801573001589802021-08-12
220116364402586302195302021-08-12
320116383501661802823602021-08-12
420116701601762902379102021-08-12
520116712502195902437702021-08-12
620117298402687602970102021-08-12
720117235802296803391202021-08-12
820116918102443602988902021-08-12
920116975101254104045402021-08-12
연도온양가압장(원동취수장) 월 취수량물금취수장 월 취수량신도시취수장 월 취수량기준일
11020209166807156503788802021-08-12
11120208892976850003528502021-08-12
11220209332006994503426802021-08-12
11320209057007097203942002021-08-12
11420209348168842002585302021-08-12
11520209725109500302208402021-08-12
11620209073107010004014002021-08-12
11720209300907082703914702021-08-12
11820208984906853403910202021-08-12
11920209443706947104030302021-08-12