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

Categorical5
Numeric3

Alerts

댐이름 has constant value ""Constant
저수위(m) has constant value ""Constant
강우량(mm) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
일자/시간(t) is highly overall correlated with 방류량(ms) and 4 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 일자/시간(t) and 1 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
유입량(ms) is highly imbalanced (65.9%)Imbalance
일자/시간(t) has unique valuesUnique
방류량(ms) has 12 (12.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:28:19.419906
Analysis finished2023-12-10 13:28:21.657618
Duration2.24 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
군위
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군위 100
100.0%

Length

2023-12-10T22:28:21.830120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:22.007916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군위 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190609 × 1011
Minimum2.0190609 × 1011
Maximum2.0190609 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:22.188667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190609 × 1011
5-th percentile2.0190609 × 1011
Q12.0190609 × 1011
median2.0190609 × 1011
Q32.0190609 × 1011
95-th percentile2.0190609 × 1011
Maximum2.0190609 × 1011
Range1670
Interquartile range (IQR)825

Descriptive statistics

Standard deviation483.80099
Coefficient of variation (CV)2.3961683 × 10-9
Kurtosis-1.1968508
Mean2.0190609 × 1011
Median Absolute Deviation (MAD)410
Skewness-0.0015635452
Sum2.0190609 × 1013
Variance234063.39
MonotonicityNot monotonic
2023-12-10T22:28:22.436565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201906091340 1
 
1.0%
201906092330 1
 
1.0%
201906092020 1
 
1.0%
201906092050 1
 
1.0%
201906092100 1
 
1.0%
201906092120 1
 
1.0%
201906092130 1
 
1.0%
201906092210 1
 
1.0%
201906092220 1
 
1.0%
201906092240 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201906090730 1
1.0%
201906090740 1
1.0%
201906090750 1
1.0%
201906090800 1
1.0%
201906090810 1
1.0%
201906090820 1
1.0%
201906090830 1
1.0%
201906090840 1
1.0%
201906090850 1
1.0%
201906090900 1
1.0%
ValueCountFrequency (%)
201906092400 1
1.0%
201906092350 1
1.0%
201906092340 1
1.0%
201906092330 1
1.0%
201906092320 1
1.0%
201906092310 1
1.0%
201906092300 1
1.0%
201906092250 1
1.0%
201906092240 1
1.0%
201906092230 1
1.0%

저수위(m)
Categorical

CONSTANT 

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

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 (%)
0 100
100.0%

Length

2023-12-10T22:28:22.644709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:22.795174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
19.067
38 
19.1
30 
19.083
22 
19.05
8 
19.116
 
2

Length

Max length6
Median length6
Mean length5.32
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19.083
2nd row19.1
3rd row19.067
4th row19.083
5th row19.1

Common Values

ValueCountFrequency (%)
19.067 38
38.0%
19.1 30
30.0%
19.083 22
22.0%
19.05 8
 
8.0%
19.116 2
 
2.0%

Length

2023-12-10T22:28:23.008244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:23.203458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19.067 38
38.0%
19.1 30
30.0%
19.083 22
22.0%
19.05 8
 
8.0%
19.116 2
 
2.0%

유입량(ms)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
39.2
90 
39.1
 
8
39.3
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row39.2
2nd row39.2
3rd row39.2
4th row39.2
5th row39.2

Common Values

ValueCountFrequency (%)
39.2 90
90.0%
39.1 8
 
8.0%
39.3 2
 
2.0%

Length

2023-12-10T22:28:23.391467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:23.578172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
39.2 90
90.0%
39.1 8
 
8.0%
39.3 2
 
2.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93027
Minimum0
Maximum1.066
Zeros12
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:23.829289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.051
median1.057
Q31.06
95-th percentile1.06405
Maximum1.066
Range1.066
Interquartile range (IQR)0.009

Descriptive statistics

Standard deviation0.34528117
Coefficient of variation (CV)0.37116232
Kurtosis3.7102393
Mean0.93027
Median Absolute Deviation (MAD)0.004
Skewness-2.3738107
Sum93.027
Variance0.11921909
MonotonicityNot monotonic
2023-12-10T22:28:24.029561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 12
12.0%
1.057 10
 
10.0%
1.061 8
 
8.0%
1.05 8
 
8.0%
1.059 7
 
7.0%
1.062 7
 
7.0%
1.051 6
 
6.0%
1.055 6
 
6.0%
1.056 5
 
5.0%
1.06 5
 
5.0%
Other values (8) 26
26.0%
ValueCountFrequency (%)
0.0 12
12.0%
1.05 8
8.0%
1.051 6
6.0%
1.052 5
5.0%
1.053 3
 
3.0%
1.054 4
 
4.0%
1.055 6
6.0%
1.056 5
5.0%
1.057 10
10.0%
1.058 5
5.0%
ValueCountFrequency (%)
1.066 2
 
2.0%
1.065 3
 
3.0%
1.064 2
 
2.0%
1.063 2
 
2.0%
1.062 7
7.0%
1.061 8
8.0%
1.06 5
5.0%
1.059 7
7.0%
1.058 5
5.0%
1.057 10
10.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.05703
Minimum1.048
Maximum1.066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:24.215353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.048
5-th percentile1.049
Q11.053
median1.057
Q31.061
95-th percentile1.06505
Maximum1.066
Range0.018
Interquartile range (IQR)0.008

Descriptive statistics

Standard deviation0.004951186
Coefficient of variation (CV)0.0046840543
Kurtosis-0.98742384
Mean1.05703
Median Absolute Deviation (MAD)0.004
Skewness0.013296414
Sum105.703
Variance2.4514242 × 10-5
MonotonicityNot monotonic
2023-12-10T22:28:24.403484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1.056 10
 
10.0%
1.057 9
 
9.0%
1.063 6
 
6.0%
1.062 6
 
6.0%
1.059 6
 
6.0%
1.051 6
 
6.0%
1.049 6
 
6.0%
1.06 6
 
6.0%
1.052 6
 
6.0%
1.061 6
 
6.0%
Other values (9) 33
33.0%
ValueCountFrequency (%)
1.048 1
 
1.0%
1.049 6
6.0%
1.05 5
5.0%
1.051 6
6.0%
1.052 6
6.0%
1.053 4
 
4.0%
1.054 4
 
4.0%
1.055 4
 
4.0%
1.056 10
10.0%
1.057 9
9.0%
ValueCountFrequency (%)
1.066 5
5.0%
1.065 2
 
2.0%
1.064 3
 
3.0%
1.063 6
6.0%
1.062 6
6.0%
1.061 6
6.0%
1.06 6
6.0%
1.059 6
6.0%
1.058 5
5.0%
1.057 9
9.0%

저수율
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
190.46
38 
190.48
30 
190.47
22 
190.45
8 
190.49
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row190.47
2nd row190.48
3rd row190.46
4th row190.47
5th row190.48

Common Values

ValueCountFrequency (%)
190.46 38
38.0%
190.48 30
30.0%
190.47 22
22.0%
190.45 8
 
8.0%
190.49 2
 
2.0%

Length

2023-12-10T22:28:24.596730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:24.757120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
190.46 38
38.0%
190.48 30
30.0%
190.47 22
22.0%
190.45 8
 
8.0%
190.49 2
 
2.0%

Interactions

2023-12-10T22:28:20.768811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:19.853339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.311375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.922881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.018837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.481457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:21.070430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.161447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:20.618357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:28:24.881580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9820.7840.5520.8350.982
강우량(mm)0.9821.0001.0000.1170.8551.000
유입량(ms)0.7841.0001.0000.1150.6631.000
방류량(ms)0.5520.1170.1151.0000.1460.117
저수량(백만m3)0.8350.8550.6630.1461.0000.855
저수율0.9821.0001.0000.1170.8551.000
2023-12-10T22:28:25.041024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량(mm)유입량(ms)저수율
강우량(mm)1.0000.9901.000
유입량(ms)0.9901.0000.990
저수율1.0000.9901.000
2023-12-10T22:28:25.190973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.686-0.8720.7990.6790.799
방류량(ms)-0.6861.0000.6850.1400.1890.140
저수량(백만m3)-0.8720.6851.0000.5210.4940.521
강우량(mm)0.7990.1400.5211.0000.9901.000
유입량(ms)0.6790.1890.4940.9901.0000.990
저수율0.7990.1400.5211.0000.9901.000

Missing values

2023-12-10T22:28:21.304005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:28:21.563454image/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
0군위201906091340019.08339.21.0611.063190.47
1군위201906090750019.139.20.01.066190.48
2군위201906091900019.06739.21.0581.056190.46
3군위201906091350019.08339.21.0591.056190.47
4군위201906091030019.139.21.0611.061190.48
5군위201906090800019.139.20.01.066190.48
6군위201906092140019.06739.21.0521.052190.46
7군위201906091910019.06739.21.0551.052190.46
8군위201906091630019.06739.20.01.053190.46
9군위201906091400019.08339.21.0591.06190.47
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위201906091510019.08339.21.0571.057190.47
91군위201906091500019.08339.21.0571.057190.47
92군위201906091440019.08339.21.0561.056190.47
93군위201906091430019.08339.21.0571.057190.47
94군위201906091330019.08339.21.061.06190.47
95군위201906091320019.08339.21.0611.06190.47
96군위201906091300019.08339.20.01.061190.47
97군위201906091250019.08339.20.01.059190.47
98군위201906090730019.11639.31.0661.066190.49
99군위201906090740019.11639.31.0661.066190.49