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 2 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 2 other fieldsHigh correlation
일자/시간(t) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수량(백만m3)High correlation
저수량(백만m3) is highly overall correlated with 방류량(ms)High correlation
일자/시간(t) has unique valuesUnique
방류량(ms) has 9 (9.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:28:41.897768
Analysis finished2023-12-10 13:28:44.813942
Duration2.92 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

2023-12-10T22:28:44.944105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:45.125661image/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%
Mean2.0190309 × 1011
Minimum2.0190309 × 1011
Maximum2.0190309 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:45.312798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190309 × 1011
5-th percentile2.0190309 × 1011
Q12.0190309 × 1011
median2.0190309 × 1011
Q32.0190309 × 1011
95-th percentile2.0190309 × 1011
Maximum2.0190309 × 1011
Range1670
Interquartile range (IQR)825

Descriptive statistics

Standard deviation483.80099
Coefficient of variation (CV)2.396204 × 10-9
Kurtosis-1.1968508
Mean2.0190309 × 1011
Median Absolute Deviation (MAD)410
Skewness-0.0015635452
Sum2.0190309 × 1013
Variance234063.39
MonotonicityNot monotonic
2023-12-10T22:28:45.573192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201903091340 1
 
1.0%
201903092330 1
 
1.0%
201903092020 1
 
1.0%
201903092050 1
 
1.0%
201903092100 1
 
1.0%
201903092120 1
 
1.0%
201903092130 1
 
1.0%
201903092210 1
 
1.0%
201903092220 1
 
1.0%
201903092240 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201903090730 1
1.0%
201903090740 1
1.0%
201903090750 1
1.0%
201903090800 1
1.0%
201903090810 1
1.0%
201903090820 1
1.0%
201903090830 1
1.0%
201903090840 1
1.0%
201903090850 1
1.0%
201903090900 1
1.0%
ValueCountFrequency (%)
201903092400 1
1.0%
201903092350 1
1.0%
201903092340 1
1.0%
201903092330 1
1.0%
201903092320 1
1.0%
201903092310 1
1.0%
201903092300 1
1.0%
201903092250 1
1.0%
201903092240 1
1.0%
201903092230 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

2023-12-10T22:28:45.840031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:46.018276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
24.6
35 
24.619
31 
24.638
19 
24.581
15 

Length

Max length6
Median length6
Mean length5.3
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row24.619
2nd row24.638
3rd row24.6
4th row24.619
5th row24.638

Common Values

ValueCountFrequency (%)
24.6 35
35.0%
24.619 31
31.0%
24.638 19
19.0%
24.581 15
15.0%

Length

2023-12-10T22:28:46.236239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:46.471169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
24.6 35
35.0%
24.619 31
31.0%
24.638 19
19.0%
24.581 15
15.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
50.6
50 
50.5
50 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50.6
2nd row50.6
3rd row50.5
4th row50.6
5th row50.6

Common Values

ValueCountFrequency (%)
50.6 50
50.0%
50.5 50
50.0%

Length

2023-12-10T22:28:46.672915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:46.911341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50.6 50
50.0%
50.5 50
50.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.02846
Minimum0
Maximum1.136
Zeros9
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:47.103835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.128
median1.13
Q31.132
95-th percentile1.133
Maximum1.136
Range1.136
Interquartile range (IQR)0.004

Descriptive statistics

Standard deviation0.32507088
Coefficient of variation (CV)0.31607538
Kurtosis6.5938973
Mean1.02846
Median Absolute Deviation (MAD)0.002
Skewness-2.9089431
Sum102.846
Variance0.10567108
MonotonicityNot monotonic
2023-12-10T22:28:47.348199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1.132 18
18.0%
1.131 17
17.0%
1.13 15
15.0%
1.128 12
12.0%
1.129 11
11.0%
0.0 9
9.0%
1.127 8
8.0%
1.133 5
 
5.0%
1.126 2
 
2.0%
1.136 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
0.0 9
9.0%
1.126 2
 
2.0%
1.127 8
8.0%
1.128 12
12.0%
1.129 11
11.0%
1.13 15
15.0%
1.131 17
17.0%
1.132 18
18.0%
1.133 5
 
5.0%
1.134 1
 
1.0%
ValueCountFrequency (%)
1.136 1
 
1.0%
1.135 1
 
1.0%
1.134 1
 
1.0%
1.133 5
 
5.0%
1.132 18
18.0%
1.131 17
17.0%
1.13 15
15.0%
1.129 11
11.0%
1.128 12
12.0%
1.127 8
8.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.13034
Minimum1.123
Maximum1.139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:47.589518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.123
5-th percentile1.125
Q11.129
median1.131
Q31.132
95-th percentile1.136
Maximum1.139
Range0.016
Interquartile range (IQR)0.003

Descriptive statistics

Standard deviation0.0030425269
Coefficient of variation (CV)0.0026916918
Kurtosis0.37462342
Mean1.13034
Median Absolute Deviation (MAD)0.002
Skewness-0.039047805
Sum113.034
Variance9.2569697 × 10-6
MonotonicityNot monotonic
2023-12-10T22:28:47.816304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1.131 18
18.0%
1.132 18
18.0%
1.129 13
13.0%
1.128 9
9.0%
1.133 9
9.0%
1.13 9
9.0%
1.126 5
 
5.0%
1.125 4
 
4.0%
1.124 3
 
3.0%
1.136 3
 
3.0%
Other values (6) 9
9.0%
ValueCountFrequency (%)
1.123 1
 
1.0%
1.124 3
 
3.0%
1.125 4
 
4.0%
1.126 5
 
5.0%
1.127 2
 
2.0%
1.128 9
9.0%
1.129 13
13.0%
1.13 9
9.0%
1.131 18
18.0%
1.132 18
18.0%
ValueCountFrequency (%)
1.139 1
 
1.0%
1.137 2
 
2.0%
1.136 3
 
3.0%
1.135 2
 
2.0%
1.134 1
 
1.0%
1.133 9
9.0%
1.132 18
18.0%
1.131 18
18.0%
1.13 9
9.0%
1.129 13
13.0%

저수율
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
193.6
35 
193.61
31 
193.62
19 
193.59
15 

Length

Max length6
Median length6
Mean length5.65
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row193.61
2nd row193.62
3rd row193.6
4th row193.61
5th row193.62

Common Values

ValueCountFrequency (%)
193.6 35
35.0%
193.61 31
31.0%
193.62 19
19.0%
193.59 15
15.0%

Length

2023-12-10T22:28:48.039955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:48.233196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
193.6 35
35.0%
193.61 31
31.0%
193.62 19
19.0%
193.59 15
15.0%

Interactions

2023-12-10T22:28:43.837453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:42.518777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:43.195145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:44.031750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:42.707970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:43.435945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:44.269735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:42.959419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:43.629580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:28:48.385516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9730.9990.2410.4170.973
강우량(mm)0.9731.0001.0000.1620.3081.000
유입량(ms)0.9991.0001.0000.0000.2201.000
방류량(ms)0.2410.1620.0001.0000.0000.162
저수량(백만m3)0.4170.3080.2200.0001.0000.308
저수율0.9731.0001.0000.1620.3081.000
2023-12-10T22:28:48.581971image/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
2023-12-10T22:28:48.744136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.0030.0760.8890.9390.889
방류량(ms)-0.0031.0000.5060.1050.0000.105
저수량(백만m3)0.0760.5061.0000.1620.1530.162
강우량(mm)0.8890.1050.1621.0000.9901.000
유입량(ms)0.9390.0000.1530.9901.0000.990
저수율0.8890.1050.1621.0000.9901.000

Missing values

2023-12-10T22:28:44.499115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:28:44.718045image/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
0군위201903091340024.61950.61.1291.127193.61
1군위201903090750024.63850.61.1321.136193.62
2군위201903091900024.650.51.1311.133193.6
3군위201903091350024.61950.61.1291.13193.61
4군위201903091030024.63850.61.1311.131193.62
5군위201903090800024.63850.61.1321.132193.62
6군위201903092140024.58150.50.01.133193.59
7군위201903091910024.650.51.1291.125193.6
8군위201903091630024.650.51.1271.126193.6
9군위201903091400024.61950.61.1281.128193.61
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위201903091510024.61950.61.1311.129193.61
91군위201903091500024.61950.61.1311.131193.61
92군위201903091440024.61950.61.1281.129193.61
93군위201903091430024.61950.61.1281.129193.61
94군위201903091330024.61950.61.1281.13193.61
95군위201903091320024.61950.61.1281.131193.61
96군위201903091300024.61950.61.131.129193.61
97군위201903091250024.61950.61.1311.132193.61
98군위201903090730024.63850.61.1321.132193.62
99군위201903090740024.63850.61.131.128193.62