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 4 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수위(m) is highly imbalanced (67.2%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:25:40.058741
Analysis finished2023-12-10 10:25:46.413061
Duration6.35 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

2023-12-10T19:25:46.517174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:46.693783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군남 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0210326 × 109
Minimum2.0210319 × 109
Maximum2.0210331 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:47.203368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210319 × 109
5-th percentile2.021032 × 109
Q12.0210321 × 109
median2.0210328 × 109
Q32.0210329 × 109
95-th percentile2.0210331 × 109
Maximum2.0210331 × 109
Range1202
Interquartile range (IQR)799

Descriptive statistics

Standard deviation406.81875
Coefficient of variation (CV)2.0129252 × 10-7
Kurtosis-1.3588191
Mean2.0210326 × 109
Median Absolute Deviation (MAD)205.5
Skewness-0.54333026
Sum2.0210326 × 1011
Variance165501.5
MonotonicityNot monotonic
2023-12-10T19:25:47.429849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021033001 1
 
1.0%
2021032707 1
 
1.0%
2021032105 1
 
1.0%
2021032111 1
 
1.0%
2021032113 1
 
1.0%
2021032117 1
 
1.0%
2021032119 1
 
1.0%
2021032203 1
 
1.0%
2021032205 1
 
1.0%
2021032209 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2021031921 1
1.0%
2021031923 1
1.0%
2021032001 1
1.0%
2021032003 1
1.0%
2021032005 1
1.0%
2021032007 1
1.0%
2021032009 1
1.0%
2021032011 1
1.0%
2021032013 1
1.0%
2021032015 1
1.0%
ValueCountFrequency (%)
2021033123 1
1.0%
2021033121 1
1.0%
2021033119 1
1.0%
2021033117 1
1.0%
2021033115 1
1.0%
2021033113 1
1.0%
2021033111 1
1.0%
2021033109 1
1.0%
2021033107 1
1.0%
2021033105 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
87 
1
 
7
3
 
4
5
 
1
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 87
87.0%
1 7
 
7.0%
3 4
 
4.0%
5 1
 
1.0%
2 1
 
1.0%

Length

2023-12-10T19:25:47.689601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:47.864309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 87
87.0%
1 7
 
7.0%
3 4
 
4.0%
5 1
 
1.0%
2 1
 
1.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.78425
Minimum4.287
Maximum7.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:48.064133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.287
5-th percentile4.38585
Q14.681
median6.2255
Q36.4855
95-th percentile6.991
Maximum7.01
Range2.723
Interquartile range (IQR)1.8045

Descriptive statistics

Standard deviation0.9229665
Coefficient of variation (CV)0.15956546
Kurtosis-1.3993965
Mean5.78425
Median Absolute Deviation (MAD)0.5115
Skewness-0.44996994
Sum578.425
Variance0.85186716
MonotonicityNot monotonic
2023-12-10T19:25:48.319821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.517 6
 
6.0%
6.234 5
 
5.0%
4.431 4
 
4.0%
4.666 4
 
4.0%
6.991 4
 
4.0%
4.681 4
 
4.0%
4.287 4
 
4.0%
6.217 3
 
3.0%
6.322 2
 
2.0%
6.463 2
 
2.0%
Other values (53) 62
62.0%
ValueCountFrequency (%)
4.287 4
4.0%
4.345 1
 
1.0%
4.388 1
 
1.0%
4.402 1
 
1.0%
4.417 1
 
1.0%
4.431 4
4.0%
4.445 1
 
1.0%
4.475 1
 
1.0%
4.504 1
 
1.0%
4.562 1
 
1.0%
ValueCountFrequency (%)
7.01 2
2.0%
6.991 4
4.0%
6.954 2
2.0%
6.935 1
 
1.0%
6.898 1
 
1.0%
6.843 1
 
1.0%
6.806 1
 
1.0%
6.752 1
 
1.0%
6.697 1
 
1.0%
6.661 1
 
1.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.085
Minimum6
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:48.550756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6.1
Q16.5
median8.7
Q39.1
95-th percentile9.8
Maximum9.8
Range3.8
Interquartile range (IQR)2.6

Descriptive statistics

Standard deviation1.2919623
Coefficient of variation (CV)0.15979744
Kurtosis-1.4052636
Mean8.085
Median Absolute Deviation (MAD)0.7
Skewness-0.44573601
Sum808.5
Variance1.6691667
MonotonicityNot monotonic
2023-12-10T19:25:48.759232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8.7 11
 
11.0%
9.1 10
 
10.0%
6.5 10
 
10.0%
6.2 7
 
7.0%
8.8 6
 
6.0%
9.0 6
 
6.0%
9.8 6
 
6.0%
6.0 4
 
4.0%
8.0 4
 
4.0%
8.9 4
 
4.0%
Other values (18) 32
32.0%
ValueCountFrequency (%)
6.0 4
 
4.0%
6.1 2
 
2.0%
6.2 7
7.0%
6.3 2
 
2.0%
6.4 2
 
2.0%
6.5 10
10.0%
6.6 3
 
3.0%
6.7 3
 
3.0%
7.9 2
 
2.0%
8.0 4
 
4.0%
ValueCountFrequency (%)
9.8 6
6.0%
9.7 3
 
3.0%
9.6 2
 
2.0%
9.5 1
 
1.0%
9.4 2
 
2.0%
9.3 1
 
1.0%
9.2 2
 
2.0%
9.1 10
10.0%
9.0 6
6.0%
8.9 4
 
4.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.93338
Minimum4.461
Maximum27.447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:49.046956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.461
5-th percentile8.4
Q112.69725
median16.5
Q319.489
95-th percentile23.9402
Maximum27.447
Range22.986
Interquartile range (IQR)6.79175

Descriptive statistics

Standard deviation5.2606223
Coefficient of variation (CV)0.33016361
Kurtosis-0.82343992
Mean15.93338
Median Absolute Deviation (MAD)3.7165
Skewness-0.016856993
Sum1593.338
Variance27.674147
MonotonicityNot monotonic
2023-12-10T19:25:49.395626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.4 10
 
10.0%
14.4 9
 
9.0%
16.5 8
 
8.0%
8.6 7
 
7.0%
16.6 4
 
4.0%
14.6 3
 
3.0%
19.233 3
 
3.0%
19.489 2
 
2.0%
18.989 2
 
2.0%
8.8 2
 
2.0%
Other values (45) 50
50.0%
ValueCountFrequency (%)
4.461 1
 
1.0%
8.4 10
10.0%
8.6 7
7.0%
8.8 2
 
2.0%
9.4 2
 
2.0%
12.4 1
 
1.0%
12.428 1
 
1.0%
12.656 1
 
1.0%
12.711 1
 
1.0%
12.739 1
 
1.0%
ValueCountFrequency (%)
27.447 1
1.0%
27.122 1
1.0%
25.367 1
1.0%
24.4 2
2.0%
23.916 1
1.0%
23.794 1
1.0%
23.195 1
1.0%
23.0 1
1.0%
22.837 1
1.0%
22.089 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.05061
Minimum8.4
Maximum24.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:49.652517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.4
5-th percentile8.4
Q18.6
median14.4
Q316.5
95-th percentile20.33185
Maximum24.4
Range16
Interquartile range (IQR)7.9

Descriptive statistics

Standard deviation4.3493562
Coefficient of variation (CV)0.33326842
Kurtosis-0.38122925
Mean13.05061
Median Absolute Deviation (MAD)4.795
Skewness0.56848654
Sum1305.061
Variance18.916899
MonotonicityNot monotonic
2023-12-10T19:25:49.885476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
8.4 14
14.0%
14.4 14
14.0%
8.6 14
14.0%
16.5 9
9.0%
9.4 6
 
6.0%
14.6 6
 
6.0%
8.8 5
 
5.0%
16.6 5
 
5.0%
9.6 4
 
4.0%
16.7 3
 
3.0%
Other values (16) 20
20.0%
ValueCountFrequency (%)
8.4 14
14.0%
8.6 14
14.0%
8.8 5
 
5.0%
9.4 6
6.0%
9.6 4
 
4.0%
9.61 1
 
1.0%
9.8 1
 
1.0%
13.058 1
 
1.0%
14.4 14
14.0%
14.507 1
 
1.0%
ValueCountFrequency (%)
24.4 2
2.0%
23.665 1
 
1.0%
23.0 1
 
1.0%
22.837 1
 
1.0%
20.2 2
2.0%
18.028 1
 
1.0%
16.95 1
 
1.0%
16.9 3
3.0%
16.845 1
 
1.0%
16.7 3
3.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.1619
Minimum26.22
Maximum27.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:50.143527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.22
5-th percentile26.2885
Q126.49
median27.445
Q327.5925
95-th percentile27.87
Maximum27.88
Range1.66
Interquartile range (IQR)1.1025

Descriptive statistics

Standard deviation0.56527761
Coefficient of variation (CV)0.020811416
Kurtosis-1.3853222
Mean27.1619
Median Absolute Deviation (MAD)0.295
Skewness-0.50376349
Sum2716.19
Variance0.31953878
MonotonicityNot monotonic
2023-12-10T19:25:50.374985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.61 6
 
6.0%
27.45 5
 
5.0%
26.32 4
 
4.0%
26.48 4
 
4.0%
27.87 4
 
4.0%
26.49 4
 
4.0%
26.22 4
 
4.0%
27.44 3
 
3.0%
27.5 2
 
2.0%
27.58 2
 
2.0%
Other values (53) 62
62.0%
ValueCountFrequency (%)
26.22 4
4.0%
26.26 1
 
1.0%
26.29 1
 
1.0%
26.3 1
 
1.0%
26.31 1
 
1.0%
26.32 4
4.0%
26.33 1
 
1.0%
26.35 1
 
1.0%
26.37 1
 
1.0%
26.41 1
 
1.0%
ValueCountFrequency (%)
27.88 2
2.0%
27.87 4
4.0%
27.85 2
2.0%
27.84 1
 
1.0%
27.82 1
 
1.0%
27.79 1
 
1.0%
27.77 1
 
1.0%
27.74 1
 
1.0%
27.71 1
 
1.0%
27.69 1
 
1.0%

Interactions

2023-12-10T19:25:45.057108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:40.438274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.289971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.196628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.172650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.079134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:45.203781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:40.568707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.437847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.375775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.312747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.219813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:45.385048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:40.707305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.567604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.543091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.467216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.375185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:45.551714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:40.863104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.723991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.680017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.618638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.527200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:45.692427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:40.996991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.860287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.803850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.759006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.678145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:45.860683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:41.151072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.043597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:42.979627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:43.929301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:44.856997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:25:50.533949image/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)1.0000.3240.8980.9760.7420.7290.916
저수위(m)0.3241.0000.5470.5280.0000.2280.485
강우량(mm)0.8980.5471.0000.9910.7640.9020.990
유입량(ms)0.9760.5280.9911.0000.7800.8000.960
방류량(ms)0.7420.0000.7640.7801.0000.7780.806
저수량(백만m3)0.7290.2280.9020.8000.7781.0000.915
저수율0.9160.4850.9900.9600.8060.9151.000
2023-12-10T19:25:50.743667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율저수위(m)
일자/시간(t)1.0000.9980.9970.7900.9940.9980.210
강우량(mm)0.9981.0000.9980.7960.9951.0000.368
유입량(ms)0.9970.9981.0000.7970.9950.9980.385
방류량(ms)0.7900.7960.7971.0000.8040.7960.000
저수량(백만m3)0.9940.9950.9950.8041.0000.9950.136
저수율0.9981.0000.9980.7960.9951.0000.317
저수위(m)0.2100.3680.3850.0000.1360.3171.000

Missing values

2023-12-10T19:25:46.105087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:25:46.321443image/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
0군남202103300106.5179.121.55516.58327.61
1군남202103272105.9248.318.9899.627.27
2군남202103201314.4316.28.48.426.32
3군남202103300306.5179.116.616.627.61
4군남202103282006.2698.814.414.427.47
5군남202103272215.9758.423.7949.627.3
6군남202103212104.6666.58.68.626.48
7군남202103201504.4316.28.48.426.32
8군남202103311106.9919.824.424.427.87
9군남202103300506.5179.116.616.627.61
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202103301906.6619.321.72816.727.69
91군남202103301706.6069.221.716.727.66
92군남202103301306.5179.121.51216.5427.61
93군남202103301106.4999.116.516.527.6
94군남202103292306.4999.116.516.527.6
95군남202103292106.4819.116.516.527.59
96군남202103291706.4639.016.516.527.58
97군남202103291506.4639.016.516.527.58
98군남202103271855.8238.118.9339.627.21
99군남202103272025.898.218.9899.627.25