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
일자/시간(t) is highly overall correlated with 유입량(ms)High correlation
강우량(mm) is highly overall correlated with 방류량(ms) 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
유입량(ms) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수위(m) is highly imbalanced (75.6%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:30:05.537986
Analysis finished2023-12-10 10:30:12.243270
Duration6.71 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

2023-12-10T19:30:12.450238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:12.743935image/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%
Mean2.0190525 × 109
Minimum2.0190518 × 109
Maximum2.0190531 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:12.981437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190518 × 109
5-th percentile2.0190518 × 109
Q12.019052 × 109
median2.0190526 × 109
Q32.0190529 × 109
95-th percentile2.0190531 × 109
Maximum2.0190531 × 109
Range1320
Interquartile range (IQR)917

Descriptive statistics

Standard deviation468.63921
Coefficient of variation (CV)2.3210848 × 10-7
Kurtosis-1.3606973
Mean2.0190525 × 109
Median Absolute Deviation (MAD)392
Skewness-0.4323798
Sum2.0190525 × 1011
Variance219622.71
MonotonicityNot monotonic
2023-12-10T19:30:13.281924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019053116 1
 
1.0%
2019052704 1
 
1.0%
2019052514 1
 
1.0%
2019052520 1
 
1.0%
2019052522 1
 
1.0%
2019052602 1
 
1.0%
2019052604 1
 
1.0%
2019052612 1
 
1.0%
2019052614 1
 
1.0%
2019052618 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019051804 1
1.0%
2019051806 1
1.0%
2019051808 1
1.0%
2019051810 1
1.0%
2019051812 1
1.0%
2019051814 1
1.0%
2019051816 1
1.0%
2019051818 1
1.0%
2019051820 1
1.0%
2019051822 1
1.0%
ValueCountFrequency (%)
2019053124 1
1.0%
2019053122 1
1.0%
2019053120 1
1.0%
2019053118 1
1.0%
2019053116 1
1.0%
2019053114 1
1.0%
2019053112 1
1.0%
2019053110 1
1.0%
2019053108 1
1.0%
2019053106 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
91 
2
 
6
4
 
1
6
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 91
91.0%
2 6
 
6.0%
4 1
 
1.0%
6 1
 
1.0%
1 1
 
1.0%

Length

2023-12-10T19:30:13.527415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:13.714895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 91
91.0%
2 6
 
6.0%
4 1
 
1.0%
6 1
 
1.0%
1 1
 
1.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.10533
Minimum1.082
Maximum1.137
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:14.279314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.082
5-th percentile1.089
Q11.096
median1.103
Q31.116
95-th percentile1.1237
Maximum1.137
Range0.055
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.013186353
Coefficient of variation (CV)0.011929788
Kurtosis-0.18994558
Mean1.10533
Median Absolute Deviation (MAD)0.007
Skewness0.51761142
Sum110.533
Variance0.0001738799
MonotonicityNot monotonic
2023-12-10T19:30:14.770326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1.103 23
23.0%
1.096 20
20.0%
1.116 18
18.0%
1.089 14
14.0%
1.123 9
 
9.0%
1.109 8
 
8.0%
1.137 5
 
5.0%
1.082 3
 
3.0%
ValueCountFrequency (%)
1.082 3
 
3.0%
1.089 14
14.0%
1.096 20
20.0%
1.103 23
23.0%
1.109 8
 
8.0%
1.116 18
18.0%
1.123 9
 
9.0%
1.137 5
 
5.0%
ValueCountFrequency (%)
1.137 5
 
5.0%
1.123 9
 
9.0%
1.116 18
18.0%
1.109 8
 
8.0%
1.103 23
23.0%
1.096 20
20.0%
1.089 14
14.0%
1.082 3
 
3.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1.5
60 
1.6
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.5
2nd row1.6
3rd row1.6
4th row1.5
5th row1.5

Common Values

ValueCountFrequency (%)
1.5 60
60.0%
1.6 40
40.0%

Length

2023-12-10T19:30:15.073849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:15.261797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.5 60
60.0%
1.6 40
40.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.42313
Minimum6.453
Maximum16.434
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:15.545260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.453
5-th percentile7.675
Q18.6685
median10.434
Q311.9
95-th percentile14.7
Maximum16.434
Range9.981
Interquartile range (IQR)3.2315

Descriptive statistics

Standard deviation2.0434224
Coefficient of variation (CV)0.19604691
Kurtosis0.0038098482
Mean10.42313
Median Absolute Deviation (MAD)1.466
Skewness0.52269543
Sum1042.313
Variance4.1755751
MonotonicityNot monotonic
2023-12-10T19:30:15.786807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
11.9 15
15.0%
8.4 15
15.0%
10.5 10
10.0%
9.8 10
10.0%
9.0 9
9.0%
12.6 7
 
7.0%
11.2 4
 
4.0%
14.7 4
 
4.0%
7.2 3
 
3.0%
7.7 2
 
2.0%
Other values (21) 21
21.0%
ValueCountFrequency (%)
6.453 1
 
1.0%
7.071 1
 
1.0%
7.2 3
 
3.0%
7.7 2
 
2.0%
7.946 1
 
1.0%
8.028 1
 
1.0%
8.284 1
 
1.0%
8.4 15
15.0%
8.758 1
 
1.0%
9.0 9
9.0%
ValueCountFrequency (%)
16.434 1
 
1.0%
15.691 1
 
1.0%
14.7 4
 
4.0%
13.517 1
 
1.0%
12.872 1
 
1.0%
12.825 1
 
1.0%
12.6 7
7.0%
12.331 1
 
1.0%
12.307 1
 
1.0%
11.9 15
15.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.44146
Minimum7.2
Maximum14.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:16.138651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile8.3099
Q19
median10.5
Q311.9
95-th percentile13.27115
Maximum14.7
Range7.5
Interquartile range (IQR)2.9

Descriptive statistics

Standard deviation1.7950022
Coefficient of variation (CV)0.17191104
Kurtosis-0.33047014
Mean10.44146
Median Absolute Deviation (MAD)1.4
Skewness0.37565971
Sum1044.146
Variance3.222033
MonotonicityNot monotonic
2023-12-10T19:30:16.422163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11.9 15
15.0%
8.4 15
15.0%
10.5 10
10.0%
9.8 10
10.0%
9.0 9
9.0%
12.6 7
 
7.0%
11.2 4
 
4.0%
14.7 4
 
4.0%
7.2 3
 
3.0%
11.573 2
 
2.0%
Other values (20) 21
21.0%
ValueCountFrequency (%)
7.2 3
 
3.0%
7.7 2
 
2.0%
8.342 1
 
1.0%
8.4 15
15.0%
8.587 1
 
1.0%
8.96 1
 
1.0%
9.0 9
9.0%
9.403 1
 
1.0%
9.8 10
10.0%
9.835 1
 
1.0%
ValueCountFrequency (%)
14.7 4
 
4.0%
14.49 1
 
1.0%
13.207 1
 
1.0%
12.6 7
7.0%
12.285 1
 
1.0%
12.052 1
 
1.0%
11.9 15
15.0%
11.83 1
 
1.0%
11.573 2
 
2.0%
11.223 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.1839
Minimum23.15
Maximum23.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:17.003607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.15
5-th percentile23.16
Q123.17
median23.18
Q323.2
95-th percentile23.211
Maximum23.23
Range0.08
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.019431049
Coefficient of variation (CV)0.00083812684
Kurtosis-0.28790643
Mean23.1839
Median Absolute Deviation (MAD)0.01
Skewness0.51101502
Sum2318.39
Variance0.00037756566
MonotonicityNot monotonic
2023-12-10T19:30:17.237319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
23.18 23
23.0%
23.17 20
20.0%
23.2 18
18.0%
23.16 14
14.0%
23.21 9
 
9.0%
23.19 8
 
8.0%
23.23 5
 
5.0%
23.15 3
 
3.0%
ValueCountFrequency (%)
23.15 3
 
3.0%
23.16 14
14.0%
23.17 20
20.0%
23.18 23
23.0%
23.19 8
 
8.0%
23.2 18
18.0%
23.21 9
 
9.0%
23.23 5
 
5.0%
ValueCountFrequency (%)
23.23 5
 
5.0%
23.21 9
 
9.0%
23.2 18
18.0%
23.19 8
 
8.0%
23.18 23
23.0%
23.17 20
20.0%
23.16 14
14.0%
23.15 3
 
3.0%

Interactions

2023-12-10T19:30:10.134174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:06.088805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:07.102591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:08.131614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:09.100794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:10.390110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:06.366190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:07.340441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:08.311857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:09.302748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:10.691607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:06.581590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:07.567664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:08.477936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:09.469362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:10.978059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:06.763240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:07.744617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:08.629051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:09.651584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:11.264430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:06.934535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:07.923703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:08.815886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:09.887010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:30:17.461518image/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)1.0000.2670.5580.5580.6520.6440.558
저수위(m)0.2671.0000.0230.2060.0000.0000.023
강우량(mm)0.5580.0231.0001.0000.8690.9441.000
유입량(ms)0.5580.2061.0001.0000.9320.9991.000
방류량(ms)0.6520.0000.8690.9321.0000.9670.869
저수량(백만m3)0.6440.0000.9440.9990.9671.0000.944
저수율0.5580.0231.0001.0000.8690.9441.000
2023-12-10T19:30:17.680986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유입량(ms)저수위(m)
유입량(ms)1.0000.247
저수위(m)0.2471.000
2023-12-10T19:30:17.845422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)방류량(ms)저수량(백만m3)저수율저수위(m)유입량(ms)
일자/시간(t)1.000-0.158-0.299-0.318-0.1580.1630.584
강우량(mm)-0.1581.0000.8790.9481.0000.0000.969
방류량(ms)-0.2990.8791.0000.8760.8790.0000.747
저수량(백만m3)-0.3180.9480.8761.0000.9480.0000.938
저수율-0.1581.0000.8790.9481.0000.0000.969
저수위(m)0.1630.0000.0000.0000.0001.0000.247
유입량(ms)0.5840.9690.7470.9380.9690.2471.000

Missing values

2023-12-10T19:30:11.715928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:30:12.105486image/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
0군남201905311601.1031.59.09.023.18
1군남201905281801.1161.610.36812.28523.2
2군남201905201001.1231.612.612.623.21
3군남201905311801.1031.59.09.023.18
4군남201905300201.0891.58.48.423.16
5군남201905282001.1091.69.62911.57323.19
6군남201905260601.1231.615.69111.8323.21
7군남201905201201.1231.612.612.623.21
8군남201905190401.0891.58.48.423.16
9군남201905312001.1031.59.09.023.18
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남201905181201.0961.59.89.823.17
91군남201905181001.0961.511.329.40323.17
92군남201905180601.0821.57.77.723.15
93군남201905180401.0821.56.4538.34223.15
94군남201905311401.1031.59.09.023.18
95군남201905311201.1031.59.09.023.18
96군남201905310801.0891.57.27.223.16
97군남201905310601.0891.57.27.223.16
98군남201905281401.1231.612.612.623.21
99군남201905281601.1231.612.612.623.21