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
저수율 is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
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
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 5 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-16 18:11:03.859980
Analysis finished2024-04-16 18:11:04.946199
Duration1.09 second
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
감포
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감포 100
100.0%

Length

2024-04-17T03:11:04.997111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:05.073966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감포 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190602 × 1011
Minimum2.0190601 × 1011
Maximum2.0190602 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:05.160677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190601 × 1011
5-th percentile2.0190601 × 1011
Q12.0190601 × 1011
median2.0190602 × 1011
Q32.0190602 × 1011
95-th percentile2.0190602 × 1011
Maximum2.0190602 × 1011
Range11900
Interquartile range (IQR)10270

Descriptive statistics

Standard deviation5069.1979
Coefficient of variation (CV)2.5106721 × 10-8
Kurtosis-1.8766
Mean2.0190602 × 1011
Median Absolute Deviation (MAD)1400
Skewness-0.32725639
Sum2.0190602 × 1013
Variance25696768
MonotonicityNot monotonic
2024-04-17T03:11:05.284333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201906021100 1
 
1.0%
201906011120 1
 
1.0%
201906010500 1
 
1.0%
201906010600 1
 
1.0%
201906010620 1
 
1.0%
201906010700 1
 
1.0%
201906010720 1
 
1.0%
201906010840 1
 
1.0%
201906010900 1
 
1.0%
201906010940 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201906010020 1
1.0%
201906010040 1
1.0%
201906010100 1
1.0%
201906010120 1
1.0%
201906010140 1
1.0%
201906010200 1
1.0%
201906010220 1
1.0%
201906010240 1
1.0%
201906010300 1
1.0%
201906010320 1
1.0%
ValueCountFrequency (%)
201906021920 1
1.0%
201906021900 1
1.0%
201906021840 1
1.0%
201906021820 1
1.0%
201906021800 1
1.0%
201906021740 1
1.0%
201906021720 1
1.0%
201906021700 1
1.0%
201906021640 1
1.0%
201906021620 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

2024-04-17T03:11:05.401162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:05.473084image/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
1.979
45 
1.983
27 
1.977
18 
1.981
10 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.979
2nd row1.979
3rd row1.983
4th row1.979
5th row1.979

Common Values

ValueCountFrequency (%)
1.979 45
45.0%
1.983 27
27.0%
1.977 18
 
18.0%
1.981 10
 
10.0%

Length

2024-04-17T03:11:05.547011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:05.628150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.979 45
45.0%
1.983 27
27.0%
1.977 18
 
18.0%
1.981 10
 
10.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
75.1
45 
75.2
37 
75.0
18 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row75.1
2nd row75.1
3rd row75.2
4th row75.1
5th row75.1

Common Values

ValueCountFrequency (%)
75.1 45
45.0%
75.2 37
37.0%
75.0 18
 
18.0%

Length

2024-04-17T03:11:05.714901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:05.796314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
75.1 45
45.0%
75.2 37
37.0%
75.0 18
 
18.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03337
Minimum0
Maximum0.07
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:05.877405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0285
Q10.03
median0.03
Q30.03
95-th percentile0.07
Maximum0.07
Range0.07
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.014562062
Coefficient of variation (CV)0.43638183
Kurtosis2.6391803
Mean0.03337
Median Absolute Deviation (MAD)0
Skewness1.0517825
Sum3.337
Variance0.00021205364
MonotonicityNot monotonic
2024-04-17T03:11:05.964213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.03 79
79.0%
0.07 9
 
9.0%
0.0 5
 
5.0%
0.058 2
 
2.0%
0.063 1
 
1.0%
0.037 1
 
1.0%
0.051 1
 
1.0%
0.031 1
 
1.0%
0.039 1
 
1.0%
ValueCountFrequency (%)
0.0 5
 
5.0%
0.03 79
79.0%
0.031 1
 
1.0%
0.037 1
 
1.0%
0.039 1
 
1.0%
0.051 1
 
1.0%
0.058 2
 
2.0%
0.063 1
 
1.0%
0.07 9
 
9.0%
ValueCountFrequency (%)
0.07 9
 
9.0%
0.063 1
 
1.0%
0.058 2
 
2.0%
0.051 1
 
1.0%
0.039 1
 
1.0%
0.037 1
 
1.0%
0.031 1
 
1.0%
0.03 79
79.0%
0.0 5
 
5.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0349
Minimum0.02
Maximum0.071
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:06.055410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.03
Q10.03
median0.03
Q30.03
95-th percentile0.07
Maximum0.071
Range0.051
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.012924411
Coefficient of variation (CV)0.37032697
Kurtosis3.5200421
Mean0.0349
Median Absolute Deviation (MAD)0
Skewness2.2836603
Sum3.49
Variance0.0001670404
MonotonicityNot monotonic
2024-04-17T03:11:06.144654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.03 84
84.0%
0.07 10
 
10.0%
0.052 1
 
1.0%
0.071 1
 
1.0%
0.054 1
 
1.0%
0.034 1
 
1.0%
0.02 1
 
1.0%
0.039 1
 
1.0%
ValueCountFrequency (%)
0.02 1
 
1.0%
0.03 84
84.0%
0.034 1
 
1.0%
0.039 1
 
1.0%
0.052 1
 
1.0%
0.054 1
 
1.0%
0.07 10
 
10.0%
0.071 1
 
1.0%
ValueCountFrequency (%)
0.071 1
 
1.0%
0.07 10
 
10.0%
0.054 1
 
1.0%
0.052 1
 
1.0%
0.039 1
 
1.0%
0.034 1
 
1.0%
0.03 84
84.0%
0.02 1
 
1.0%

저수율
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
37.83
45 
37.85
27 
37.82
18 
37.84
10 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37.83
2nd row37.83
3rd row37.85
4th row37.83
5th row37.83

Common Values

ValueCountFrequency (%)
37.83 45
45.0%
37.85 27
27.0%
37.82 18
 
18.0%
37.84 10
 
10.0%

Length

2024-04-17T03:11:06.235392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:06.318113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37.83 45
45.0%
37.85 27
27.0%
37.82 18
 
18.0%
37.84 10
 
10.0%

Interactions

2024-04-17T03:11:04.543145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.078534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.304616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.619456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.150212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.381685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.697085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.232284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:04.462613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T03:11:06.379928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9250.7390.5670.5890.925
강우량(mm)0.9251.0001.0000.3810.3531.000
유입량(ms)0.7391.0001.0000.5560.5801.000
방류량(ms)0.5670.3810.5561.0000.9050.381
저수량(백만m3)0.5890.3530.5800.9051.0000.353
저수율0.9251.0001.0000.3810.3531.000
2024-04-17T03:11:06.471266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수율강우량(mm)유입량(ms)
저수율1.0001.0000.995
강우량(mm)1.0001.0000.995
유입량(ms)0.9950.9951.000
2024-04-17T03:11:06.555237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.219-0.3220.6370.7820.637
방류량(ms)-0.2191.0000.7890.2560.2790.256
저수량(백만m3)-0.3220.7891.0000.2310.2850.231
강우량(mm)0.6370.2560.2311.0000.9951.000
유입량(ms)0.7820.2790.2850.9951.0000.995
저수율0.6370.2560.2311.0000.9951.000

Missing values

2024-04-17T03:11:04.799001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T03:11:04.903852image/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
0감포20190602110001.97975.10.030.0337.83
1감포20190601232001.97975.10.0630.05237.83
2감포20190601022001.98375.20.030.0337.85
3감포20190602112001.97975.10.030.0337.83
4감포20190602044001.97975.10.030.0337.83
5감포20190601234001.97975.10.0370.0337.83
6감포20190601074001.98375.20.070.0737.85
7감포20190601024001.98375.20.030.0337.85
8감포20190602164001.97775.00.030.0337.82
9감포20190602114001.97975.10.030.0337.83
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90감포20190602140001.97775.00.030.0337.82
91감포20190602134001.97775.00.00.0337.82
92감포20190602130001.97975.10.030.0337.83
93감포20190602124001.97975.10.030.0337.83
94감포20190602104001.97975.10.030.0337.83
95감포20190602102001.97975.10.030.0337.83
96감포20190602094001.97975.10.030.0337.83
97감포20190602092001.97975.10.030.0337.83
98감포20190601224001.97975.10.00.0237.83
99감포20190601230001.97975.10.0390.03937.83