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
일자/시간(t) has unique valuesUnique
방류량(ms) has 12 (12.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:28:49.635176
Analysis finished2023-12-10 13:28:51.987794
Duration2.35 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
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

2023-12-10T22:28:52.089312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:52.501193image/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%
Mean2.0190209 × 1011
Minimum2.0190209 × 1011
Maximum2.0190209 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:52.668449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190209 × 1011
5-th percentile2.0190209 × 1011
Q12.0190209 × 1011
median2.0190209 × 1011
Q32.0190209 × 1011
95-th percentile2.0190209 × 1011
Maximum2.0190209 × 1011
Range1670
Interquartile range (IQR)825

Descriptive statistics

Standard deviation483.80099
Coefficient of variation (CV)2.3962158 × 10-9
Kurtosis-1.1968508
Mean2.0190209 × 1011
Median Absolute Deviation (MAD)410
Skewness-0.0015635452
Sum2.0190209 × 1013
Variance234063.39
MonotonicityNot monotonic
2023-12-10T22:28:52.939391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201902091340 1
 
1.0%
201902092330 1
 
1.0%
201902092020 1
 
1.0%
201902092050 1
 
1.0%
201902092100 1
 
1.0%
201902092120 1
 
1.0%
201902092130 1
 
1.0%
201902092210 1
 
1.0%
201902092220 1
 
1.0%
201902092240 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201902090730 1
1.0%
201902090740 1
1.0%
201902090750 1
1.0%
201902090800 1
1.0%
201902090810 1
1.0%
201902090820 1
1.0%
201902090830 1
1.0%
201902090840 1
1.0%
201902090850 1
1.0%
201902090900 1
1.0%
ValueCountFrequency (%)
201902092400 1
1.0%
201902092350 1
1.0%
201902092340 1
1.0%
201902092330 1
1.0%
201902092320 1
1.0%
201902092310 1
1.0%
201902092300 1
1.0%
201902092250 1
1.0%
201902092240 1
1.0%
201902092230 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

2023-12-10T22:28:53.162575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:53.307214image/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
25.391
71 
25.372
15 
25.41
13 
25.429
 
1

Length

Max length6
Median length6
Mean length5.87
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row25.391
2nd row25.41
3rd row25.391
4th row25.391
5th row25.391

Common Values

ValueCountFrequency (%)
25.391 71
71.0%
25.372 15
 
15.0%
25.41 13
 
13.0%
25.429 1
 
1.0%

Length

2023-12-10T22:28:53.468973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:53.678440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
25.391 71
71.0%
25.372 15
 
15.0%
25.41 13
 
13.0%
25.429 1
 
1.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
52.1
86 
52.2
14 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row52.1
2nd row52.2
3rd row52.1
4th row52.1
5th row52.1

Common Values

ValueCountFrequency (%)
52.1 86
86.0%
52.2 14
 
14.0%

Length

2023-12-10T22:28:53.940720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:54.112224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52.1 86
86.0%
52.2 14
 
14.0%

방류량(ms)
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.12016
Minimum0
Maximum11.469
Zeros12
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:54.279440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.91175
median0.913
Q30.914
95-th percentile0.915
Maximum11.469
Range11.469
Interquartile range (IQR)0.00225

Descriptive statistics

Standard deviation1.8531376
Coefficient of variation (CV)1.6543508
Kurtosis28.234717
Mean1.12016
Median Absolute Deviation (MAD)0.001
Skewness5.3562658
Sum112.016
Variance3.4341188
MonotonicityNot monotonic
2023-12-10T22:28:54.478918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.914 25
25.0%
0.913 23
23.0%
0.912 13
13.0%
0.0 12
12.0%
0.915 10
 
10.0%
0.911 10
 
10.0%
11.469 2
 
2.0%
0.91 2
 
2.0%
0.909 1
 
1.0%
0.916 1
 
1.0%
ValueCountFrequency (%)
0.0 12
12.0%
0.909 1
 
1.0%
0.91 2
 
2.0%
0.911 10
 
10.0%
0.912 13
13.0%
0.913 23
23.0%
0.914 25
25.0%
0.915 10
 
10.0%
0.916 1
 
1.0%
11.468 1
 
1.0%
ValueCountFrequency (%)
11.469 2
 
2.0%
11.468 1
 
1.0%
0.916 1
 
1.0%
0.915 10
 
10.0%
0.914 25
25.0%
0.913 23
23.0%
0.912 13
13.0%
0.911 10
 
10.0%
0.91 2
 
2.0%
0.909 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91318
Minimum0.908
Maximum0.917
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:54.708345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.908
5-th percentile0.91
Q10.912
median0.913
Q30.914
95-th percentile0.916
Maximum0.917
Range0.009
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.0019299867
Coefficient of variation (CV)0.0021134789
Kurtosis0.058405565
Mean0.91318
Median Absolute Deviation (MAD)0.001
Skewness-0.34655877
Sum91.318
Variance3.7248485 × 10-6
MonotonicityNot monotonic
2023-12-10T22:28:54.909149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.914 23
23.0%
0.913 21
21.0%
0.912 14
14.0%
0.915 11
11.0%
0.911 11
11.0%
0.916 9
 
9.0%
0.91 4
 
4.0%
0.917 3
 
3.0%
0.909 2
 
2.0%
0.908 2
 
2.0%
ValueCountFrequency (%)
0.908 2
 
2.0%
0.909 2
 
2.0%
0.91 4
 
4.0%
0.911 11
11.0%
0.912 14
14.0%
0.913 21
21.0%
0.914 23
23.0%
0.915 11
11.0%
0.916 9
 
9.0%
0.917 3
 
3.0%
ValueCountFrequency (%)
0.917 3
 
3.0%
0.916 9
 
9.0%
0.915 11
11.0%
0.914 23
23.0%
0.913 21
21.0%
0.912 14
14.0%
0.911 11
11.0%
0.91 4
 
4.0%
0.909 2
 
2.0%
0.908 2
 
2.0%

저수율
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
194.02
71 
194.01
15 
194.03
13 
194.04
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row194.02
2nd row194.03
3rd row194.02
4th row194.02
5th row194.02

Common Values

ValueCountFrequency (%)
194.02 71
71.0%
194.01 15
 
15.0%
194.03 13
 
13.0%
194.04 1
 
1.0%

Length

2023-12-10T22:28:55.105205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:55.359473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
194.02 71
71.0%
194.01 15
 
15.0%
194.03 13
 
13.0%
194.04 1
 
1.0%

Interactions

2023-12-10T22:28:51.258343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:50.405233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:50.823234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:51.397932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:50.540062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:50.982874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:51.546353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:50.691198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:51.123835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:28:55.489564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8770.9680.2240.4780.877
강우량(mm)0.8771.0001.0000.0000.1231.000
유입량(ms)0.9681.0001.0000.0000.2301.000
방류량(ms)0.2240.0000.0001.0000.2220.000
저수량(백만m3)0.4780.1230.2300.2221.0000.123
저수율0.8771.0001.0000.0000.1231.000
2023-12-10T22:28:55.681661image/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
2023-12-10T22:28:55.847827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.133-0.1550.6300.8210.630
방류량(ms)-0.1331.0000.4270.0000.0000.000
저수량(백만m3)-0.1550.4271.0000.0650.1670.065
강우량(mm)0.6300.0000.0651.0000.9901.000
유입량(ms)0.8210.0000.1670.9901.0000.990
저수율0.6300.0000.0651.0000.9901.000

Missing values

2023-12-10T22:28:51.721499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:28:51.912913image/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
0군위201902091340025.39152.10.9130.914194.02
1군위201902090750025.4152.20.00.909194.03
2군위201902091900025.39152.10.9130.916194.02
3군위201902091350025.39152.10.9130.913194.02
4군위201902091030025.39152.10.9150.917194.02
5군위201902090800025.4152.20.00.916194.03
6군위201902092140025.39152.10.9090.912194.02
7군위201902091910025.39152.10.9140.914194.02
8군위201902091630025.39152.10.9130.912194.02
9군위201902091400025.39152.10.9140.915194.02
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위201902091510025.37252.10.00.912194.01
91군위201902091500025.39152.10.9140.914194.02
92군위201902091440025.39152.10.9120.913194.02
93군위201902091430025.39152.10.9110.911194.02
94군위201902091330025.39152.10.9120.911194.02
95군위201902091320025.39152.10.9110.912194.02
96군위201902091300025.39152.10.9110.911194.02
97군위201902091250025.39152.10.9130.913194.02
98군위201902090730025.42952.20.9120.913194.04
99군위201902090740025.4152.20.00.912194.03