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
강우량(mm) has constant value ""Constant
유입량(ms) is highly overall correlated with 방류량(ms)High correlation
방류량(ms) is highly overall correlated with 유입량(ms)High correlation
저수위(m) is highly imbalanced (91.9%)Imbalance
저수량(백만m3) is highly imbalanced (91.9%)Imbalance
저수율 is highly imbalanced (91.9%)Imbalance

Reproduction

Analysis started2023-12-10 13:17:33.673800
Analysis finished2023-12-10 13:17:36.738261
Duration3.06 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
강천보
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강천보 100
100.0%

Length

2023-12-10T22:17:37.251472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:37.452387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강천보 100
100.0%

일자/시간(t)
Real number (ℝ)

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0200202 × 1011
Minimum2.0200201 × 1011
Maximum2.0200215 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:37.751605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0200201 × 1011
5-th percentile2.0200201 × 1011
Q12.0200202 × 1011
median2.0200202 × 1011
Q32.0200202 × 1011
95-th percentile2.0200202 × 1011
Maximum2.0200215 × 1011
Range138230
Interquartile range (IQR)1295

Descriptive statistics

Standard deviation13227.318
Coefficient of variation (CV)6.5481119 × 10-8
Kurtosis94.183138
Mean2.0200202 × 1011
Median Absolute Deviation (MAD)385
Skewness9.5492573
Sum2.0200202 × 1013
Variance1.7496195 × 108
MonotonicityNot monotonic
2023-12-10T22:17:38.071033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202002020630 2
 
2.0%
202002021700 2
 
2.0%
202002020530 2
 
2.0%
202002020100 2
 
2.0%
202002012330 2
 
2.0%
202002020330 2
 
2.0%
202002020400 2
 
2.0%
202002020500 2
 
2.0%
202002020700 2
 
2.0%
202002020730 2
 
2.0%
Other values (66) 80
80.0%
ValueCountFrequency (%)
202002012320 1
1.0%
202002012330 2
2.0%
202002012340 1
1.0%
202002012350 1
1.0%
202002012400 2
2.0%
202002020010 1
1.0%
202002020020 1
1.0%
202002020030 2
2.0%
202002020040 1
1.0%
202002020050 1
1.0%
ValueCountFrequency (%)
202002150550 1
1.0%
202002021820 1
1.0%
202002021810 1
1.0%
202002021800 2
2.0%
202002021750 1
1.0%
202002021740 1
1.0%
202002021730 2
2.0%
202002021720 1
1.0%
202002021710 1
1.0%
202002021700 2
2.0%

저수위(m)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
38.1
99 
38.02
 
1

Length

Max length5
Median length4
Mean length4.01
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row38.1
2nd row38.1
3rd row38.1
4th row38.1
5th row38.1

Common Values

ValueCountFrequency (%)
38.1 99
99.0%
38.02 1
 
1.0%

Length

2023-12-10T22:17:38.433296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:38.652691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.1 99
99.0%
38.02 1
 
1.0%

강우량(mm)
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

2023-12-10T22:17:38.823821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:39.004484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.60551
Minimum94.43
Maximum101.127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:39.211147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum94.43
5-th percentile94.463
Q194.5115
median94.545
Q394.57175
95-th percentile94.6032
Maximum101.127
Range6.697
Interquartile range (IQR)0.06025

Descriptive statistics

Standard deviation0.66012369
Coefficient of variation (CV)0.0069776452
Kurtosis99.136449
Mean94.60551
Median Absolute Deviation (MAD)0.032
Skewness9.9356795
Sum9460.551
Variance0.43576328
MonotonicityNot monotonic
2023-12-10T22:17:39.468607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
94.577 9
 
9.0%
94.533 6
 
6.0%
94.54 6
 
6.0%
94.583 4
 
4.0%
94.557 4
 
4.0%
94.463 4
 
4.0%
94.49 4
 
4.0%
94.567 4
 
4.0%
94.563 4
 
4.0%
94.53 4
 
4.0%
Other values (27) 51
51.0%
ValueCountFrequency (%)
94.43 2
2.0%
94.447 1
 
1.0%
94.463 4
4.0%
94.467 1
 
1.0%
94.477 1
 
1.0%
94.48 2
2.0%
94.487 3
3.0%
94.49 4
4.0%
94.497 2
2.0%
94.5 2
2.0%
ValueCountFrequency (%)
101.127 1
 
1.0%
94.623 1
 
1.0%
94.613 2
 
2.0%
94.607 1
 
1.0%
94.603 3
 
3.0%
94.6 3
 
3.0%
94.59 1
 
1.0%
94.583 4
4.0%
94.577 9
9.0%
94.57 2
 
2.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.60477
Minimum94.36
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:39.731027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum94.36
5-th percentile94.43
Q194.5
median94.55
Q394.58
95-th percentile94.64
Maximum101
Range6.64
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.64884994
Coefficient of variation (CV)0.006858533
Kurtosis98.190807
Mean94.60477
Median Absolute Deviation (MAD)0.04
Skewness9.8649821
Sum9460.477
Variance0.42100624
MonotonicityNot monotonic
2023-12-10T22:17:40.057326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
94.55 7
 
7.0%
94.54 7
 
7.0%
94.5 6
 
6.0%
94.56 6
 
6.0%
94.58 5
 
5.0%
94.46 4
 
4.0%
94.61 4
 
4.0%
94.62 4
 
4.0%
94.53 4
 
4.0%
94.48 3
 
3.0%
Other values (32) 50
50.0%
ValueCountFrequency (%)
94.36 1
 
1.0%
94.4 1
 
1.0%
94.42 1
 
1.0%
94.43 3
3.0%
94.44 2
2.0%
94.45 2
2.0%
94.46 4
4.0%
94.463 1
 
1.0%
94.47 1
 
1.0%
94.48 3
3.0%
ValueCountFrequency (%)
101.0 1
 
1.0%
94.66 1
 
1.0%
94.65 1
 
1.0%
94.64 3
3.0%
94.63 2
2.0%
94.62 4
4.0%
94.613 1
 
1.0%
94.61 4
4.0%
94.603 1
 
1.0%
94.6 1
 
1.0%

저수량(백만m3)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
9.181
99 
8.819
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row9.181
2nd row9.181
3rd row9.181
4th row9.181
5th row9.181

Common Values

ValueCountFrequency (%)
9.181 99
99.0%
8.819 1
 
1.0%

Length

2023-12-10T22:17:40.453052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:40.648405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9.181 99
99.0%
8.819 1
 
1.0%

저수율
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
105.2
99 
101.0
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row105.2
2nd row105.2
3rd row105.2
4th row105.2
5th row105.2

Common Values

ValueCountFrequency (%)
105.2 99
99.0%
101.0 1
 
1.0%

Length

2023-12-10T22:17:40.797649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:40.957194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
105.2 99
99.0%
101.0 1
 
1.0%

Interactions

2023-12-10T22:17:35.509073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.239206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.913014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.742531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.397172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.170335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.914979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.673645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.351725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:17:41.085916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.6930.6930.6930.6930.693
저수위(m)0.6931.0000.6930.6930.6930.693
유입량(ms)0.6930.6931.0000.6930.6930.693
방류량(ms)0.6930.6930.6931.0000.6930.693
저수량(백만m3)0.6930.6930.6930.6931.0000.693
저수율0.6930.6930.6930.6930.6931.000
2023-12-10T22:17:41.303641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수위(m)저수량(백만m3)저수율
저수위(m)1.0000.4870.487
저수량(백만m3)0.4871.0000.487
저수율0.4870.4871.000
2023-12-10T22:17:41.451581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)유입량(ms)방류량(ms)저수위(m)저수량(백만m3)저수율
일자/시간(t)1.0000.1040.1050.4870.4870.487
유입량(ms)0.1041.0000.6260.4870.4870.487
방류량(ms)0.1050.6261.0000.4870.4870.487
저수위(m)0.4870.4870.4871.0000.4870.487
저수량(백만m3)0.4870.4870.4870.4871.0000.487
저수율0.4870.4870.4870.4870.4871.000

Missing values

2023-12-10T22:17:36.203674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:17:36.583681image/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
0강천보20200201234038.1094.58394.59.181105.2
1강천보20200201233038.1094.61394.629.181105.2
2강천보20200202002038.1094.50794.549.181105.2
3강천보20200201235038.1094.53394.489.181105.2
4강천보20200201240038.1094.4894.489.181105.2
5강천보20200201240038.1094.4894.469.181105.2
6강천보20200202003038.1094.5594.559.181105.2
7강천보20200202150038.1094.55394.5539.181105.2
8강천보20200202004038.1094.5694.559.181105.2
9강천보20200202001038.1094.48794.529.181105.2
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90강천보20200202054038.1094.57794.469.181105.2
91강천보20200202053038.1094.57794.5779.181105.2
92강천보20200202052038.1094.55794.659.181105.2
93강천보20200202051038.1094.50794.469.181105.2
94강천보20200215055038.020101.127101.08.819101.0
95강천보20200202043038.1094.57794.5779.181105.2
96강천보20200202041038.1094.47794.59.181105.2
97강천보20200202040038.1094.4994.499.181105.2
98강천보20200201232038.1094.56394.639.181105.2
99강천보20200201233038.1094.61394.6139.181105.2