Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory72.3 B

Variable types

Categorical3
Numeric5

Alerts

댐이름 has constant value ""Constant
강우량(mm) is highly overall correlated with 저수율 and 1 other fieldsHigh correlation
저수율 is highly overall correlated with 강우량(mm) and 1 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 강우량(mm) and 1 other fieldsHigh correlation
저수위(m) is highly imbalanced (91.9%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:30:45.555059
Analysis finished2023-12-10 10:30:50.952930
Duration5.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

댐이름
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
군남
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군남 100
100.0%

Length

2023-12-10T19:30:51.051097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:51.225214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군남 100
100.0%

일자/시간(t)
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190223 × 109
Minimum2.0190218 × 109
Maximum2.0190227 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:51.419252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190218 × 109
5-th percentile2.0190218 × 109
Q12.019022 × 109
median2.0190222 × 109
Q32.0190225 × 109
95-th percentile2.0190227 × 109
Maximum2.0190227 × 109
Range912
Interquartile range (IQR)509

Descriptive statistics

Standard deviation298.09096
Coefficient of variation (CV)1.4764125 × 10-7
Kurtosis-1.4199519
Mean2.0190223 × 109
Median Absolute Deviation (MAD)293
Skewness0.056272259
Sum2.0190223 × 1011
Variance88858.222
MonotonicityNot monotonic
2023-12-10T19:30:51.697799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019022110 1
 
1.0%
2019022714 1
 
1.0%
2019022524 1
 
1.0%
2019022606 1
 
1.0%
2019022608 1
 
1.0%
2019022612 1
 
1.0%
2019022614 1
 
1.0%
2019022622 1
 
1.0%
2019022624 1
 
1.0%
2019022704 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019021808 1
1.0%
2019021810 1
1.0%
2019021812 1
1.0%
2019021814 1
1.0%
2019021816 1
1.0%
2019021818 1
1.0%
2019021820 1
1.0%
2019021822 1
1.0%
2019021824 1
1.0%
2019021902 1
1.0%
ValueCountFrequency (%)
2019022720 1
1.0%
2019022718 1
1.0%
2019022716 1
1.0%
2019022714 1
1.0%
2019022712 1
1.0%
2019022710 1
1.0%
2019022708 1
1.0%
2019022706 1
1.0%
2019022704 1
1.0%
2019022702 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 99
99.0%
3 1
 
1.0%

Length

2023-12-10T19:30:51.919975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:52.099133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
3 1
 
1.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.62697
Minimum3.505
Maximum3.792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:52.266162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.505
5-th percentile3.55635
Q13.595
median3.621
Q33.66
95-th percentile3.726
Maximum3.792
Range0.287
Interquartile range (IQR)0.065

Descriptive statistics

Standard deviation0.054159595
Coefficient of variation (CV)0.014932463
Kurtosis0.26897123
Mean3.62697
Median Absolute Deviation (MAD)0.039
Skewness0.46766192
Sum362.697
Variance0.0029332617
MonotonicityNot monotonic
2023-12-10T19:30:52.480205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3.608 13
13.0%
3.595 12
12.0%
3.582 10
10.0%
3.647 8
8.0%
3.66 8
8.0%
3.673 8
8.0%
3.621 6
 
6.0%
3.634 6
 
6.0%
3.686 5
 
5.0%
3.57 5
 
5.0%
Other values (11) 19
19.0%
ValueCountFrequency (%)
3.505 1
 
1.0%
3.518 1
 
1.0%
3.531 2
 
2.0%
3.544 1
 
1.0%
3.557 4
 
4.0%
3.57 5
 
5.0%
3.582 10
10.0%
3.595 12
12.0%
3.608 13
13.0%
3.621 6
6.0%
ValueCountFrequency (%)
3.792 1
 
1.0%
3.765 1
 
1.0%
3.739 2
 
2.0%
3.726 2
 
2.0%
3.713 3
 
3.0%
3.7 1
 
1.0%
3.686 5
5.0%
3.673 8
8.0%
3.66 8
8.0%
3.647 8
8.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5.0
45 
5.1
36 
5.2
13 
4.9
 
4
5.3
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.2
2nd row5.0
3rd row5.2
4th row5.2
5th row5.0

Common Values

ValueCountFrequency (%)
5.0 45
45.0%
5.1 36
36.0%
5.2 13
 
13.0%
4.9 4
 
4.0%
5.3 2
 
2.0%

Length

2023-12-10T19:30:52.709432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:52.909079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.0 45
45.0%
5.1 36
36.0%
5.2 13
 
13.0%
4.9 4
 
4.0%
5.3 2
 
2.0%

방류량(ms)
Real number (ℝ)

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.20364
Minimum2.461
Maximum31.843
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:53.106506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.461
5-th percentile3.978
Q18.3575
median11.2
Q314.818
95-th percentile23.54175
Maximum31.843
Range29.382
Interquartile range (IQR)6.4605

Descriptive statistics

Standard deviation5.899258
Coefficient of variation (CV)0.48340151
Kurtosis1.1751766
Mean12.20364
Median Absolute Deviation (MAD)3
Skewness1.0647849
Sum1220.364
Variance34.801245
MonotonicityNot monotonic
2023-12-10T19:30:53.345130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.2 10
 
10.0%
9.6 6
 
6.0%
8.4 6
 
6.0%
14.0 4
 
4.0%
11.0 4
 
4.0%
7.561 3
 
3.0%
3.978 3
 
3.0%
7.589 2
 
2.0%
12.039 2
 
2.0%
19.0 2
 
2.0%
Other values (53) 58
58.0%
ValueCountFrequency (%)
2.461 1
 
1.0%
3.833 1
 
1.0%
3.922 1
 
1.0%
3.95 1
 
1.0%
3.978 3
3.0%
4.226 1
 
1.0%
4.596 1
 
1.0%
6.072 1
 
1.0%
6.266 1
 
1.0%
6.626 1
 
1.0%
ValueCountFrequency (%)
31.843 1
1.0%
29.565 1
1.0%
27.883 1
1.0%
25.861 1
1.0%
23.594 1
1.0%
23.539 1
1.0%
22.299 1
1.0%
22.033 1
1.0%
21.909 1
1.0%
21.704 1
1.0%

저수량(백만m3)
Real number (ℝ)

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.20809
Minimum8.2
Maximum24.607
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:53.579500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile8.38085
Q19.6
median11.2
Q313.83575
95-th percentile19.35715
Maximum24.607
Range16.407
Interquartile range (IQR)4.23575

Descriptive statistics

Standard deviation3.8515347
Coefficient of variation (CV)0.31549036
Kurtosis2.714028
Mean12.20809
Median Absolute Deviation (MAD)1.6
Skewness1.6557373
Sum1220.809
Variance14.83432
MonotonicityNot monotonic
2023-12-10T19:30:53.916582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
11.2 25
25.0%
9.6 10
 
10.0%
8.4 10
 
10.0%
11.0 8
 
8.0%
14.0 5
 
5.0%
8.2 4
 
4.0%
9.8 3
 
3.0%
16.4 3
 
3.0%
13.8 2
 
2.0%
19.0 2
 
2.0%
Other values (27) 28
28.0%
ValueCountFrequency (%)
8.2 4
 
4.0%
8.207 1
 
1.0%
8.39 1
 
1.0%
8.397 1
 
1.0%
8.4 10
10.0%
8.662 1
 
1.0%
9.6 10
10.0%
9.8 3
 
3.0%
11.0 8
8.0%
11.103 1
 
1.0%
ValueCountFrequency (%)
24.607 1
1.0%
24.6 1
1.0%
24.593 1
1.0%
24.407 1
1.0%
22.343 1
1.0%
19.2 1
1.0%
19.0 2
2.0%
18.66 1
1.0%
16.807 1
1.0%
16.6 2
2.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.7344
Minimum25.64
Maximum25.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:54.164191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.64
5-th percentile25.6795
Q125.71
median25.73
Q325.76
95-th percentile25.81
Maximum25.86
Range0.22
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.041641083
Coefficient of variation (CV)0.0016181097
Kurtosis0.23126243
Mean25.7344
Median Absolute Deviation (MAD)0.03
Skewness0.43702806
Sum2573.44
Variance0.0017339798
MonotonicityNot monotonic
2023-12-10T19:30:54.358552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
25.72 13
13.0%
25.71 12
12.0%
25.7 10
10.0%
25.75 8
8.0%
25.76 8
8.0%
25.77 8
8.0%
25.73 6
 
6.0%
25.74 6
 
6.0%
25.78 5
 
5.0%
25.69 5
 
5.0%
Other values (11) 19
19.0%
ValueCountFrequency (%)
25.64 1
 
1.0%
25.65 1
 
1.0%
25.66 2
 
2.0%
25.67 1
 
1.0%
25.68 4
 
4.0%
25.69 5
 
5.0%
25.7 10
10.0%
25.71 12
12.0%
25.72 13
13.0%
25.73 6
6.0%
ValueCountFrequency (%)
25.86 1
 
1.0%
25.84 1
 
1.0%
25.82 2
 
2.0%
25.81 2
 
2.0%
25.8 3
 
3.0%
25.79 1
 
1.0%
25.78 5
5.0%
25.77 8
8.0%
25.76 8
8.0%
25.75 8
8.0%

Interactions

2023-12-10T19:30:49.762913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:45.934598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:46.912085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.821069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.539251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:49.912538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:46.114110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.124070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.970106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.694964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:50.114052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:46.340432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.330046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.118997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.848250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:50.262123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:46.518726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.510028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.261638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:49.417445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:50.436446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:46.755334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:47.662914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:48.403002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:49.593079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:30:54.522398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.0000.5560.6130.2060.7210.564
저수위(m)0.0001.0000.0000.0000.0000.0430.000
강우량(mm)0.5560.0001.0001.0000.0000.2291.000
유입량(ms)0.6130.0001.0001.0000.0000.3201.000
방류량(ms)0.2060.0000.0000.0001.0000.6760.000
저수량(백만m3)0.7210.0430.2290.3200.6761.0000.000
저수율0.5640.0001.0001.0000.0000.0001.000
2023-12-10T19:30:54.722897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입량(ms)저수위(m)
유입량(ms)1.0000.000
저수위(m)0.0001.000
2023-12-10T19:30:54.877610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)방류량(ms)저수량(백만m3)저수율저수위(m)유입량(ms)
일자/시간(t)1.000-0.107-0.177-0.326-0.1070.0000.396
강우량(mm)-0.1071.0000.2730.4321.0000.0000.973
방류량(ms)-0.1770.2731.0000.3300.2730.0000.000
저수량(백만m3)-0.3260.4320.3301.0000.4320.0300.185
저수율-0.1071.0000.2730.4321.0000.0000.973
저수위(m)0.0000.0000.0000.0300.0001.0000.000
유입량(ms)0.3960.9730.0000.1850.9730.0001.000

Missing values

2023-12-10T19:30:50.634114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:30:50.860001image/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

댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
0군남201902211003.7265.27.5214.85325.81
1군남201902181203.6085.09.89.825.72
2군남201902250803.6865.214.014.025.78
3군남201902211203.7395.215.06411.39725.82
4군남201902192003.5575.015.3398.225.68
5군남201902181403.6475.121.70414.48225.75
6군남201902261603.6085.08.48.425.72
7군남201902251003.665.110.36114.025.76
8군남201902222003.5825.08.28.225.7
9군남201902211403.7265.211.211.225.81
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남201902220403.6085.019.019.025.72
91군남201902220203.575.018.13911.025.69
92군남201902212203.6085.03.97811.225.72
93군남201902212003.665.111.211.225.76
94군남201902210803.7655.39.41816.80725.84
95군남201902210603.7925.315.09411.425.86
96군남201902210203.6475.122.03311.225.75
97군남201902202403.6085.03.97811.225.72
98군남201902180803.6215.114.014.025.73
99군남201902181003.6085.09.89.825.72