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
저수위(m) has constant value ""Constant
강우량(mm) is highly overall correlated with 유입량(ms) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
저수율 is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:26:15.177061
Analysis finished2023-12-10 10:26:23.379519
Duration8.2 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

2023-12-10T19:26:23.485358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:26:23.634558image/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%
Mean2.0201224 × 109
Minimum2.0201216 × 109
Maximum2.0201231 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:23.794088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0201216 × 109
5-th percentile2.0201217 × 109
Q12.0201218 × 109
median2.0201225 × 109
Q32.020123 × 109
95-th percentile2.0201231 × 109
Maximum2.0201231 × 109
Range1502
Interquartile range (IQR)1191.75

Descriptive statistics

Standard deviation529.1074
Coefficient of variation (CV)2.6191848 × 10-7
Kurtosis-1.4497997
Mean2.0201224 × 109
Median Absolute Deviation (MAD)516
Skewness-0.15261182
Sum2.0201224 × 1011
Variance279954.64
MonotonicityNot monotonic
2023-12-10T19:26:24.045748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2020121804 1
 
1.0%
2020122604 1
 
1.0%
2020122419 1
 
1.0%
2020122501 1
 
1.0%
2020122502 1
 
1.0%
2020122506 1
 
1.0%
2020122508 1
 
1.0%
2020122515 1
 
1.0%
2020122517 1
 
1.0%
2020122520 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2020121622 1
1.0%
2020121623 1
1.0%
2020121701 1
1.0%
2020121703 1
1.0%
2020121704 1
1.0%
2020121706 1
1.0%
2020121707 1
1.0%
2020121709 1
1.0%
2020121711 1
1.0%
2020121713 1
1.0%
ValueCountFrequency (%)
2020123124 1
1.0%
2020123123 1
1.0%
2020123121 1
1.0%
2020123120 1
1.0%
2020123118 1
1.0%
2020123116 1
1.0%
2020123115 1
1.0%
2020123113 1
1.0%
2020123112 1
1.0%
2020123110 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

2023-12-10T19:26:24.291225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:26:24.443607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.92841
Minimum3.726
Maximum4.105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:24.585948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.726
5-th percentile3.8037
Q13.845
median3.886
Q34.03925
95-th percentile4.105
Maximum4.105
Range0.379
Interquartile range (IQR)0.19425

Descriptive statistics

Standard deviation0.10878671
Coefficient of variation (CV)0.027692299
Kurtosis-1.2485643
Mean3.92841
Median Absolute Deviation (MAD)0.054
Skewness0.35289418
Sum392.841
Variance0.011834547
MonotonicityNot monotonic
2023-12-10T19:26:24.815738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3.872 13
13.0%
3.832 12
12.0%
3.845 9
 
9.0%
4.105 8
 
8.0%
4.022 7
 
7.0%
4.063 6
 
6.0%
3.926 5
 
5.0%
3.805 5
 
5.0%
4.091 5
 
5.0%
3.899 4
 
4.0%
Other values (14) 26
26.0%
ValueCountFrequency (%)
3.726 1
 
1.0%
3.739 1
 
1.0%
3.765 2
 
2.0%
3.779 1
 
1.0%
3.805 5
 
5.0%
3.819 2
 
2.0%
3.832 12
12.0%
3.845 9
9.0%
3.859 3
 
3.0%
3.872 13
13.0%
ValueCountFrequency (%)
4.105 8
8.0%
4.091 5
5.0%
4.077 3
 
3.0%
4.063 6
6.0%
4.049 3
 
3.0%
4.036 1
 
1.0%
4.022 7
7.0%
4.008 1
 
1.0%
3.954 3
 
3.0%
3.94 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.494
Minimum5.2
Maximum5.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:25.018250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.2
5-th percentile5.3
Q15.4
median5.4
Q35.625
95-th percentile5.7
Maximum5.7
Range0.5
Interquartile range (IQR)0.225

Descriptive statistics

Standard deviation0.14412396
Coefficient of variation (CV)0.026232975
Kurtosis-1.1452609
Mean5.494
Median Absolute Deviation (MAD)0.1
Skewness0.25146171
Sum549.4
Variance0.020771717
MonotonicityNot monotonic
2023-12-10T19:26:25.207763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5.4 39
39.0%
5.7 25
25.0%
5.5 15
 
15.0%
5.3 10
 
10.0%
5.6 9
 
9.0%
5.2 2
 
2.0%
ValueCountFrequency (%)
5.2 2
 
2.0%
5.3 10
 
10.0%
5.4 39
39.0%
5.5 15
 
15.0%
5.6 9
 
9.0%
5.7 25
25.0%
ValueCountFrequency (%)
5.7 25
25.0%
5.6 9
 
9.0%
5.5 15
 
15.0%
5.4 39
39.0%
5.3 10
 
10.0%
5.2 2
 
2.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.34162
Minimum5.578
Maximum18.633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:25.404107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.578
5-th percentile8.42975
Q19.3
median10.9
Q314.8
95-th percentile17.65165
Maximum18.633
Range13.055
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.2262085
Coefficient of variation (CV)0.26140883
Kurtosis-0.81919438
Mean12.34162
Median Absolute Deviation (MAD)2.094
Skewness0.38996838
Sum1234.162
Variance10.408421
MonotonicityNot monotonic
2023-12-10T19:26:25.660592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
9.3 20
20.0%
10.8 17
17.0%
14.8 15
15.0%
17.6 8
 
8.0%
10.9 5
 
5.0%
18.633 5
 
5.0%
10.967 4
 
4.0%
12.994 3
 
3.0%
8.406 2
 
2.0%
14.55 1
 
1.0%
Other values (20) 20
20.0%
ValueCountFrequency (%)
5.578 1
 
1.0%
5.606 1
 
1.0%
8.127 1
 
1.0%
8.406 2
 
2.0%
8.431 1
 
1.0%
8.433 1
 
1.0%
8.717 1
 
1.0%
9.3 20
20.0%
10.678 1
 
1.0%
10.762 1
 
1.0%
ValueCountFrequency (%)
18.633 5
 
5.0%
17.6 8
8.0%
16.63 1
 
1.0%
16.433 1
 
1.0%
16.206 1
 
1.0%
14.8 15
15.0%
14.678 1
 
1.0%
14.65 1
 
1.0%
14.635 1
 
1.0%
14.6 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.15246
Minimum8.127
Maximum17.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:25.891082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.127
5-th percentile9.3
Q19.3
median10.9
Q314.8
95-th percentile17.6
Maximum17.6
Range9.473
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation2.7125029
Coefficient of variation (CV)0.22320607
Kurtosis-0.98409321
Mean12.15246
Median Absolute Deviation (MAD)1.6
Skewness0.51888923
Sum1215.246
Variance7.3576718
MonotonicityNot monotonic
2023-12-10T19:26:26.079923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9.3 26
26.0%
14.8 24
24.0%
10.8 19
19.0%
17.6 8
 
8.0%
10.9 7
 
7.0%
12.1 3
 
3.0%
14.6 2
 
2.0%
13.675 1
 
1.0%
12.153 1
 
1.0%
10.857 1
 
1.0%
Other values (8) 8
 
8.0%
ValueCountFrequency (%)
8.127 1
 
1.0%
8.717 1
 
1.0%
9.297 1
 
1.0%
9.3 26
26.0%
10.8 19
19.0%
10.857 1
 
1.0%
10.9 7
 
7.0%
12.1 3
 
3.0%
12.153 1
 
1.0%
12.4 1
 
1.0%
ValueCountFrequency (%)
17.6 8
 
8.0%
14.8 24
24.0%
14.6 2
 
2.0%
14.54 1
 
1.0%
14.4 1
 
1.0%
13.68 1
 
1.0%
13.675 1
 
1.0%
12.6 1
 
1.0%
12.4 1
 
1.0%
12.153 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.961
Minimum25.81
Maximum26.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:26.263717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.81
5-th percentile25.869
Q125.9
median25.93
Q326.0425
95-th percentile26.09
Maximum26.09
Range0.28
Interquartile range (IQR)0.1425

Descriptive statistics

Standard deviation0.079943162
Coefficient of variation (CV)0.003079356
Kurtosis-1.2458515
Mean25.961
Median Absolute Deviation (MAD)0.04
Skewness0.33738808
Sum2596.1
Variance0.0063909091
MonotonicityNot monotonic
2023-12-10T19:26:26.457483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
25.92 13
13.0%
25.89 12
12.0%
25.9 9
 
9.0%
26.09 8
 
8.0%
26.03 7
 
7.0%
26.06 6
 
6.0%
25.96 5
 
5.0%
25.87 5
 
5.0%
26.08 5
 
5.0%
25.94 4
 
4.0%
Other values (14) 26
26.0%
ValueCountFrequency (%)
25.81 1
 
1.0%
25.82 1
 
1.0%
25.84 2
 
2.0%
25.85 1
 
1.0%
25.87 5
 
5.0%
25.88 2
 
2.0%
25.89 12
12.0%
25.9 9
9.0%
25.91 3
 
3.0%
25.92 13
13.0%
ValueCountFrequency (%)
26.09 8
8.0%
26.08 5
5.0%
26.07 3
 
3.0%
26.06 6
6.0%
26.05 3
 
3.0%
26.04 1
 
1.0%
26.03 7
7.0%
26.02 1
 
1.0%
25.98 3
 
3.0%
25.97 2
 
2.0%

Interactions

2023-12-10T19:26:21.618181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:15.652521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.675648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:18.607017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.731169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.707630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:21.858850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:15.831504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.850800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:18.841994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.888981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.865995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:22.060838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.023946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:17.032744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.067709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.054737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:21.019629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:22.302198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.210078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:17.189159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.289322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.227555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:21.177908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:22.570502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.369295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:17.424096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.438139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.389179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:21.313429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:22.810793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:16.516361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:18.370697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:19.585777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:20.530550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:21.469279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:26:26.616955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8370.7860.8240.9040.841
강우량(mm)0.8371.0000.9650.8360.8101.000
유입량(ms)0.7860.9651.0000.7250.7720.965
방류량(ms)0.8240.8360.7251.0000.8790.835
저수량(백만m3)0.9040.8100.7720.8791.0000.810
저수율0.8411.0000.9650.8350.8101.000
2023-12-10T19:26:26.775990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.383-0.241-0.308-0.334-0.383
강우량(mm)-0.3831.0000.9620.8500.8851.000
유입량(ms)-0.2410.9621.0000.8340.8410.962
방류량(ms)-0.3080.8500.8341.0000.7720.850
저수량(백만m3)-0.3340.8850.8410.7721.0000.885
저수율-0.3831.0000.9620.8500.8851.000

Missing values

2023-12-10T19:26:23.078031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:26:23.283370image/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
0군남202012180403.9265.514.6510.925.96
1군남202012292103.7655.38.40612.125.84
2군남202012240504.0635.714.814.826.06
3군남202012180503.9265.510.910.925.96
4군남202012310203.8055.39.39.325.87
5군남202012292303.7395.28.43312.125.82
6군남202012251004.0225.614.814.826.03
7군남202012240704.0635.714.814.826.06
8군남202012310703.8325.49.39.325.89
9군남202012180703.9265.510.910.925.96
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202012182003.9265.510.82214.625.96
91군남202012181803.9545.514.614.625.98
92군남202012181503.9545.510.910.925.98
93군남202012181303.945.510.910.925.97
94군남202012180203.9135.514.63510.85725.95
95군남202012180103.8995.510.810.825.94
96군남202012172103.8995.514.5510.825.94
97군남202012172003.8865.410.810.825.93
98군남202012291803.8055.38.43112.15325.87
99군남202012292003.7795.38.40612.125.85