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

Categorical2
Numeric6

Alerts

댐이름 has constant value ""Constant
일자/시간(t) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수량 is highly overall correlated with 방류량(ms)High correlation
저수율(ms) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(백만m3) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수량High correlation
저수위(m) is highly imbalanced (85.9%)Imbalance
일자/시간(t) has unique valuesUnique
방류량(ms) has 5 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-17 06:02:56.772129
Analysis finished2024-04-17 06:03:00.279964
Duration3.51 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
감포
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감포 100
100.0%

Length

2024-04-17T15:03:00.337141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T15:03:00.415045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감포 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190208 × 109
Minimum2.0190201 × 109
Maximum2.0190223 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:00.520421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190201 × 109
5-th percentile2.0190201 × 109
Q12.0190203 × 109
median2.0190205 × 109
Q32.0190207 × 109
95-th percentile2.0190222 × 109
Maximum2.0190223 × 109
Range2200
Interquartile range (IQR)403

Descriptive statistics

Standard deviation751.47716
Coefficient of variation (CV)3.7219883 × 10-7
Kurtosis-0.1217706
Mean2.0190208 × 109
Median Absolute Deviation (MAD)202
Skewness1.2623467
Sum2.0190208 × 1011
Variance564717.92
MonotonicityNot monotonic
2024-04-17T15:03:00.653487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019020209 1
 
1.0%
2019020707 1
 
1.0%
2019020517 1
 
1.0%
2019020523 1
 
1.0%
2019020601 1
 
1.0%
2019020605 1
 
1.0%
2019020607 1
 
1.0%
2019020615 1
 
1.0%
2019020617 1
 
1.0%
2019020621 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019020101 1
1.0%
2019020103 1
1.0%
2019020105 1
1.0%
2019020107 1
1.0%
2019020109 1
1.0%
2019020111 1
1.0%
2019020113 1
1.0%
2019020115 1
1.0%
2019020117 1
1.0%
2019020119 1
1.0%
ValueCountFrequency (%)
2019022301 1
1.0%
2019022223 1
1.0%
2019022221 1
1.0%
2019022219 1
1.0%
2019022217 1
1.0%
2019022215 1
1.0%
2019022213 1
1.0%
2019022211 1
1.0%
2019022209 1
1.0%
2019022207 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
98 
0.5
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 98
98.0%
0.5 2
 
2.0%

Length

2024-04-17T15:03:00.767277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T15:03:00.844858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 98
98.0%
0.5 2
 
2.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.15716
Minimum2.12
Maximum2.176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:00.930572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.12
5-th percentile2.12
Q12.1585
median2.165
Q32.171
95-th percentile2.174
Maximum2.176
Range0.056
Interquartile range (IQR)0.0125

Descriptive statistics

Standard deviation0.019068574
Coefficient of variation (CV)0.0088396659
Kurtosis-0.17615567
Mean2.15716
Median Absolute Deviation (MAD)0.006
Skewness-1.2290496
Sum215.716
Variance0.00036361051
MonotonicityNot monotonic
2024-04-17T15:03:01.023122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2.171 14
14.0%
2.122 12
12.0%
2.172 11
11.0%
2.165 9
9.0%
2.161 8
8.0%
2.163 8
8.0%
2.12 7
7.0%
2.159 7
7.0%
2.167 7
7.0%
2.169 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
2.12 7
7.0%
2.122 12
12.0%
2.124 2
 
2.0%
2.156 2
 
2.0%
2.157 2
 
2.0%
2.159 7
7.0%
2.161 8
8.0%
2.163 8
8.0%
2.165 9
9.0%
2.167 7
7.0%
ValueCountFrequency (%)
2.176 2
 
2.0%
2.174 4
 
4.0%
2.172 11
11.0%
2.171 14
14.0%
2.169 5
 
5.0%
2.167 7
7.0%
2.165 9
9.0%
2.163 8
8.0%
2.161 8
8.0%
2.159 7
7.0%

저수량
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03989
Minimum0
Maximum0.081
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:01.135771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02765
Q10.04
median0.04
Q30.04
95-th percentile0.05005
Maximum0.081
Range0.081
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0093861008
Coefficient of variation (CV)0.23529959
Kurtosis11.419571
Mean0.03989
Median Absolute Deviation (MAD)0
Skewness0.030654822
Sum3.989
Variance8.8098889 × 10-5
MonotonicityNot monotonic
2024-04-17T15:03:01.238369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.04 79
79.0%
0.043 3
 
3.0%
0.017 2
 
2.0%
0.05 2
 
2.0%
0.081 1
 
1.0%
0.004 1
 
1.0%
0.051 1
 
1.0%
0.055 1
 
1.0%
0.056 1
 
1.0%
0.041 1
 
1.0%
Other values (8) 8
 
8.0%
ValueCountFrequency (%)
0.0 1
 
1.0%
0.004 1
 
1.0%
0.017 2
 
2.0%
0.021 1
 
1.0%
0.028 1
 
1.0%
0.032 1
 
1.0%
0.033 1
 
1.0%
0.038 1
 
1.0%
0.04 79
79.0%
0.041 1
 
1.0%
ValueCountFrequency (%)
0.081 1
 
1.0%
0.08 1
 
1.0%
0.056 1
 
1.0%
0.055 1
 
1.0%
0.051 1
 
1.0%
0.05 2
 
2.0%
0.046 1
 
1.0%
0.043 3
 
3.0%
0.041 1
 
1.0%
0.04 79
79.0%

저수율(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.8084
Minimum38.61
Maximum38.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:01.347967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.61
5-th percentile38.61
Q138.8175
median38.85
Q338.88
95-th percentile38.9
Maximum38.91
Range0.3
Interquartile range (IQR)0.0625

Descriptive statistics

Standard deviation0.10201723
Coefficient of variation (CV)0.0026287409
Kurtosis-0.17029347
Mean38.8084
Median Absolute Deviation (MAD)0.03
Skewness-1.2315234
Sum3880.84
Variance0.010407515
MonotonicityNot monotonic
2024-04-17T15:03:01.447082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
38.88 14
14.0%
38.62 12
12.0%
38.89 11
11.0%
38.85 9
9.0%
38.83 8
8.0%
38.84 8
8.0%
38.61 7
7.0%
38.82 7
7.0%
38.86 7
7.0%
38.87 5
 
5.0%
Other values (5) 12
12.0%
ValueCountFrequency (%)
38.61 7
7.0%
38.62 12
12.0%
38.63 2
 
2.0%
38.8 2
 
2.0%
38.81 2
 
2.0%
38.82 7
7.0%
38.83 8
8.0%
38.84 8
8.0%
38.85 9
9.0%
38.86 7
7.0%
ValueCountFrequency (%)
38.91 2
 
2.0%
38.9 4
 
4.0%
38.89 11
11.0%
38.88 14
14.0%
38.87 5
 
5.0%
38.86 7
7.0%
38.85 9
9.0%
38.84 8
8.0%
38.83 8
8.0%
38.82 7
7.0%

유입량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.829
Minimum80.4
Maximum82.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:01.547620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80.4
5-th percentile80.4
Q181.875
median82.1
Q382.3
95-th percentile82.5
Maximum82.6
Range2.2
Interquartile range (IQR)0.425

Descriptive statistics

Standard deviation0.72324954
Coefficient of variation (CV)0.008838548
Kurtosis-0.14980166
Mean81.829
Median Absolute Deviation (MAD)0.2
Skewness-1.2371817
Sum8182.9
Variance0.5230899
MonotonicityNot monotonic
2024-04-17T15:03:01.644840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
82.3 19
19.0%
82.1 17
17.0%
80.5 12
12.0%
82.4 11
11.0%
82.0 8
8.0%
80.4 7
 
7.0%
81.9 7
 
7.0%
82.2 7
 
7.0%
82.5 4
 
4.0%
81.8 4
 
4.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
80.4 7
 
7.0%
80.5 12
12.0%
80.6 2
 
2.0%
81.8 4
 
4.0%
81.9 7
 
7.0%
82.0 8
8.0%
82.1 17
17.0%
82.2 7
 
7.0%
82.3 19
19.0%
82.4 11
11.0%
ValueCountFrequency (%)
82.6 2
 
2.0%
82.5 4
 
4.0%
82.4 11
11.0%
82.3 19
19.0%
82.2 7
 
7.0%
82.1 17
17.0%
82.0 8
8.0%
81.9 7
 
7.0%
81.8 4
 
4.0%
80.6 2
 
2.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03819
Minimum0
Maximum0.081
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:03:01.743316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0038
Q10.04
median0.04
Q30.04
95-th percentile0.05005
Maximum0.081
Range0.081
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.012183525
Coefficient of variation (CV)0.31902396
Kurtosis6.2360281
Mean0.03819
Median Absolute Deviation (MAD)0
Skewness-1.0089435
Sum3.819
Variance0.00014843828
MonotonicityNot monotonic
2024-04-17T15:03:01.847761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.04 76
76.0%
0.0 5
 
5.0%
0.043 3
 
3.0%
0.017 2
 
2.0%
0.081 1
 
1.0%
0.004 1
 
1.0%
0.05 1
 
1.0%
0.051 1
 
1.0%
0.055 1
 
1.0%
0.056 1
 
1.0%
Other values (8) 8
 
8.0%
ValueCountFrequency (%)
0.0 5
 
5.0%
0.004 1
 
1.0%
0.017 2
 
2.0%
0.021 1
 
1.0%
0.028 1
 
1.0%
0.032 1
 
1.0%
0.033 1
 
1.0%
0.038 1
 
1.0%
0.04 76
76.0%
0.041 1
 
1.0%
ValueCountFrequency (%)
0.081 1
 
1.0%
0.08 1
 
1.0%
0.056 1
 
1.0%
0.055 1
 
1.0%
0.051 1
 
1.0%
0.05 1
 
1.0%
0.046 1
 
1.0%
0.043 3
 
3.0%
0.041 1
 
1.0%
0.04 76
76.0%

Interactions

2024-04-17T15:02:59.561079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:56.997422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.441850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.893656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.379472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.840202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.639308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.066427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.517396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.966687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.448988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.167161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.728427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.136996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.588799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.057631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.525144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.233943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.819947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.213513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.671155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.139476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.606191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.323591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.904506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.288390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.744252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.221538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.687387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.404453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.993114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.363531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:57.810580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.292911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:58.757949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:59.475887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T15:03:01.928001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)
일자/시간(t)1.0000.1460.8920.0000.8770.8520.000
저수위(m)0.1461.0000.0610.0000.0610.1120.000
강우량(mm)0.8920.0611.0000.0000.9950.9870.000
저수량0.0000.0000.0001.0000.0000.0000.998
저수율(ms)0.8770.0610.9950.0001.0000.9640.136
유입량(백만m3)0.8520.1120.9870.0000.9641.0000.123
방류량(ms)0.0000.0000.0000.9980.1360.1231.000
2024-04-17T15:03:02.028732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)저수위(m)
일자/시간(t)1.000-0.996-0.029-0.996-0.992-0.0670.088
강우량(mm)-0.9961.0000.0111.0000.9960.0580.071
저수량-0.0290.0111.0000.0110.0300.8290.000
저수율(ms)-0.9961.0000.0111.0000.9960.0580.071
유입량(백만m3)-0.9920.9960.0300.9961.0000.0660.134
방류량(ms)-0.0670.0580.8290.0580.0661.0000.000
저수위(m)0.0880.0710.0000.0710.1340.0001.000

Missing values

2024-04-17T15:03:00.128371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T15:03:00.239031image/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)저수량저수율(ms)유입량(백만m3)방류량(ms)
0감포20190202090.02.1720.03238.8982.40.032
1감포20190221130.02.1220.0438.6280.50.0
2감포20190205010.02.1650.0438.8582.10.04
3감포20190202110.02.1710.0438.8882.30.04
4감포20190222210.02.120.0438.6180.40.04
5감포20190221150.02.1220.0438.6280.50.04
6감포20190206090.02.1610.0438.8382.00.04
7감포20190205030.02.1650.0438.8582.10.04
8감포20190203190.02.1690.04338.8782.30.043
9감포20190202130.02.1710.0438.8882.30.04
댐이름일자/시간(t)저수위(m)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)
90감포20190203030.02.1710.0438.8882.30.04
91감포20190203010.02.1710.0438.8882.30.04
92감포20190202210.02.1710.04338.8882.30.043
93감포20190202190.02.1710.0438.8882.30.04
94감포20190202070.02.1720.00438.8982.40.004
95감포20190202050.02.1720.0438.8982.40.04
96감포20190202010.02.1720.0438.8982.40.04
97감포20190201230.02.1720.0438.8982.40.04
98감포20190221090.02.1240.0438.6380.60.04
99감포20190221110.02.1240.0438.6380.60.04