Overview

Dataset statistics

Number of variables5
Number of observations139
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory43.9 B

Variable types

Numeric3
Categorical2

Dataset

Description경상북도 구미시가 운영 관리하는 취수장의 취수량 데이터로 년도별, 월별, 취수장명, 취수량 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15086169/fileData.do

Alerts

취수장 has constant value ""Constant
용수종류 has constant value ""Constant
연도 is highly overall correlated with 취수량(m3)High correlation
취수량(m3) is highly overall correlated with 연도High correlation
취수량(m3) has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:48:48.368103
Analysis finished2023-12-12 13:48:49.594999
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.4388
Minimum2011
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:48:49.662692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2011
Q12013
median2016
Q32019
95-th percentile2022.1
Maximum2023
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5795618
Coefficient of variation (CV)0.0017751898
Kurtosis-1.0250077
Mean2016.4388
Median Absolute Deviation (MAD)3
Skewness0.1848697
Sum280285
Variance12.813262
MonotonicityIncreasing
2023-12-12T22:48:49.831382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2011 12
8.6%
2012 12
8.6%
2013 12
8.6%
2014 12
8.6%
2015 12
8.6%
2016 12
8.6%
2017 12
8.6%
2018 12
8.6%
2019 12
8.6%
2020 12
8.6%
Other values (2) 19
13.7%
ValueCountFrequency (%)
2011 12
8.6%
2012 12
8.6%
2013 12
8.6%
2014 12
8.6%
2015 12
8.6%
2016 12
8.6%
2017 12
8.6%
2018 12
8.6%
2019 12
8.6%
2020 12
8.6%
ValueCountFrequency (%)
2023 7
5.0%
2022 12
8.6%
2020 12
8.6%
2019 12
8.6%
2018 12
8.6%
2017 12
8.6%
2016 12
8.6%
2015 12
8.6%
2014 12
8.6%
2013 12
8.6%

월
Real number (ℝ)

Distinct12
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.3741007
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:48:49.993844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4500019
Coefficient of variation (CV)0.54125311
Kurtosis-1.1996811
Mean6.3741007
Median Absolute Deviation (MAD)3
Skewness0.053943619
Sum886
Variance11.902513
MonotonicityNot monotonic
2023-12-12T22:48:50.455055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 12
8.6%
2 12
8.6%
3 12
8.6%
4 12
8.6%
5 12
8.6%
6 12
8.6%
7 12
8.6%
8 11
7.9%
9 11
7.9%
10 11
7.9%
Other values (2) 22
15.8%
ValueCountFrequency (%)
1 12
8.6%
2 12
8.6%
3 12
8.6%
4 12
8.6%
5 12
8.6%
6 12
8.6%
7 12
8.6%
8 11
7.9%
9 11
7.9%
10 11
7.9%
ValueCountFrequency (%)
12 11
7.9%
11 11
7.9%
10 11
7.9%
9 11
7.9%
8 11
7.9%
7 12
8.6%
6 12
8.6%
5 12
8.6%
4 12
8.6%
3 12
8.6%

취수장
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
구미취수장
139 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구미취수장 139
100.0%

Length

2023-12-12T22:48:50.598987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:48:50.696569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구미취수장 139
100.0%

용수종류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
공업용수
139 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공업용수 139
100.0%

Length

2023-12-12T22:48:50.839668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:48:50.950289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공업용수 139
100.0%

취수량(m3)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3129784.3
Minimum51820
Maximum4465510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T22:48:51.094791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51820
5-th percentile1301936
Q12388925
median3504550
Q33921865
95-th percentile4188104
Maximum4465510
Range4413690
Interquartile range (IQR)1532940

Descriptive statistics

Standard deviation970779.73
Coefficient of variation (CV)0.31017465
Kurtosis0.44205684
Mean3129784.3
Median Absolute Deviation (MAD)586800
Skewness-0.95225727
Sum4.3504001 × 108
Variance9.4241328 × 1011
MonotonicityNot monotonic
2023-12-12T22:48:51.257619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3504550 1
 
0.7%
3118850 1
 
0.7%
3584530 1
 
0.7%
3887850 1
 
0.7%
3366430 1
 
0.7%
3096130 1
 
0.7%
2977260 1
 
0.7%
1291640 1
 
0.7%
2830150 1
 
0.7%
3941510 1
 
0.7%
Other values (129) 129
92.8%
ValueCountFrequency (%)
51820 1
0.7%
74150 1
0.7%
403880 1
0.7%
598390 1
0.7%
1020930 1
0.7%
1288900 1
0.7%
1291640 1
0.7%
1303080 1
0.7%
1360940 1
0.7%
1475540 1
0.7%
ValueCountFrequency (%)
4465510 1
0.7%
4253840 1
0.7%
4249430 1
0.7%
4246660 1
0.7%
4242990 1
0.7%
4237450 1
0.7%
4189130 1
0.7%
4187990 1
0.7%
4146370 1
0.7%
4135490 1
0.7%

Interactions

2023-12-12T22:48:49.097693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.484924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.812653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:49.205452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.593812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.907074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:49.299427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.721421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:48:48.996905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:48:51.380719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월취수량(m3)
연도1.0000.0000.725
월0.0001.0000.059
취수량(m3)0.7250.0591.000
2023-12-12T22:48:51.490859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도월취수량(m3)
연도1.000-0.060-0.555
월-0.0601.000-0.101
취수량(m3)-0.555-0.1011.000

Missing values

2023-12-12T22:48:49.412187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:48:49.542818image/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

연도월취수장용수종류취수량(m3)
020111구미취수장공업용수3504550
120112구미취수장공업용수3544820
220113구미취수장공업용수3920160
320114구미취수장공업용수2246970
420115구미취수장공업용수4101190
520116구미취수장공업용수3942080
620117구미취수장공업용수4107100
720118구미취수장공업용수4189130
820119구미취수장공업용수3986330
9201110구미취수장공업용수4023010
연도월취수장용수종류취수량(m3)
129202210구미취수장공업용수2120280
130202211구미취수장공업용수2033820
131202212구미취수장공업용수2275100
13220231구미취수장공업용수2262360
13320232구미취수장공업용수2024290
13420233구미취수장공업용수2229540
13520234구미취수장공업용수2155030
13620235구미취수장공업용수2228130
13720236구미취수장공업용수2209910
13820237구미취수장공업용수2307170