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) 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
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
일자/시간(t) is highly overall correlated with 방류량(ms) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 방류량(ms) and 1 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 일자/시간(t) and 1 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 유입량(ms)High correlation
강우량(mm) is highly imbalanced (69.8%)Imbalance
일자/시간(t) has unique valuesUnique
유입량(ms) has 6 (6.0%) zerosZeros
방류량(ms) has 4 (4.0%) zerosZeros

Reproduction

Analysis started2024-04-16 18:11:14.761215
Analysis finished2024-04-16 18:11:16.081916
Duration1.32 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

2024-04-17T03:11:16.134022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:16.204731image/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%
Mean2.0190409 × 1011
Minimum2.0190408 × 1011
Maximum2.0190409 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:16.299207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190408 × 1011
5-th percentile2.0190408 × 1011
Q12.0190408 × 1011
median2.0190409 × 1011
Q32.0190409 × 1011
95-th percentile2.0190409 × 1011
Maximum2.0190409 × 1011
Range10900
Interquartile range (IQR)9240

Descriptive statistics

Standard deviation4225.4595
Coefficient of variation (CV)2.0928053 × 10-8
Kurtosis-1.049369
Mean2.0190409 × 1011
Median Absolute Deviation (MAD)940
Skewness-0.93296494
Sum2.0190409 × 1013
Variance17854508
MonotonicityNot monotonic
2024-04-17T03:11:16.422692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201904090320 1
 
1.0%
201904092300 1
 
1.0%
201904091640 1
 
1.0%
201904091740 1
 
1.0%
201904091800 1
 
1.0%
201904091840 1
 
1.0%
201904091900 1
 
1.0%
201904092020 1
 
1.0%
201904092040 1
 
1.0%
201904092120 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201904081500 1
1.0%
201904081520 1
1.0%
201904081540 1
1.0%
201904081600 1
1.0%
201904081620 1
1.0%
201904081640 1
1.0%
201904081700 1
1.0%
201904081720 1
1.0%
201904081740 1
1.0%
201904081800 1
1.0%
ValueCountFrequency (%)
201904092400 1
1.0%
201904092340 1
1.0%
201904092320 1
1.0%
201904092300 1
1.0%
201904092240 1
1.0%
201904092220 1
1.0%
201904092200 1
1.0%
201904092140 1
1.0%
201904092120 1
1.0%
201904092100 1
1.0%

저수위(m)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
38.05
47 
38.04
33 
38.03
20 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38.05
2nd row38.05
3rd row38.04
4th row38.05
5th row38.05

Common Values

ValueCountFrequency (%)
38.05 47
47.0%
38.04 33
33.0%
38.03 20
20.0%

Length

2024-04-17T03:11:16.527584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:16.607193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.05 47
47.0%
38.04 33
33.0%
38.03 20
20.0%

강우량(mm)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
92 
1.0
 
5
0.5
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 92
92.0%
1.0 5
 
5.0%
0.5 3
 
3.0%

Length

2024-04-17T03:11:16.698013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:16.786678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 92
92.0%
1.0 5
 
5.0%
0.5 3
 
3.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05769
Minimum0
Maximum1.04
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:16.890361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median0.04
Q30.04
95-th percentile0.05145
Maximum1.04
Range1.04
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.14151887
Coefficient of variation (CV)2.4530918
Kurtosis46.533038
Mean0.05769
Median Absolute Deviation (MAD)0
Skewness6.8658728
Sum5.769
Variance0.02002759
MonotonicityNot monotonic
2024-04-17T03:11:16.992067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.04 72
72.0%
0.0 6
 
6.0%
0.042 2
 
2.0%
0.03 2
 
2.0%
1.04 1
 
1.0%
0.048 1
 
1.0%
0.044 1
 
1.0%
0.084 1
 
1.0%
0.05 1
 
1.0%
0.041 1
 
1.0%
Other values (12) 12
 
12.0%
ValueCountFrequency (%)
0.0 6
 
6.0%
0.009 1
 
1.0%
0.011 1
 
1.0%
0.017 1
 
1.0%
0.019 1
 
1.0%
0.026 1
 
1.0%
0.03 2
 
2.0%
0.033 1
 
1.0%
0.037 1
 
1.0%
0.04 72
72.0%
ValueCountFrequency (%)
1.04 1
1.0%
1.038 1
1.0%
0.09 1
1.0%
0.084 1
1.0%
0.06 1
1.0%
0.051 1
1.0%
0.05 1
1.0%
0.048 1
1.0%
0.047 1
1.0%
0.044 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03882
Minimum0
Maximum0.1
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:17.086723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0157
Q10.04
median0.04
Q30.04
95-th percentile0.04815
Maximum0.1
Range0.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01172012
Coefficient of variation (CV)0.30190932
Kurtosis11.464995
Mean0.03882
Median Absolute Deviation (MAD)0
Skewness0.055239323
Sum3.882
Variance0.00013736121
MonotonicityNot monotonic
2024-04-17T03:11:17.184264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.04 80
80.0%
0.0 4
 
4.0%
0.03 3
 
3.0%
0.031 2
 
2.0%
0.039 2
 
2.0%
0.061 1
 
1.0%
0.016 1
 
1.0%
0.072 1
 
1.0%
0.051 1
 
1.0%
0.01 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
0.0 4
 
4.0%
0.01 1
 
1.0%
0.016 1
 
1.0%
0.03 3
 
3.0%
0.031 2
 
2.0%
0.039 2
 
2.0%
0.04 80
80.0%
0.042 1
 
1.0%
0.048 1
 
1.0%
0.051 1
 
1.0%
ValueCountFrequency (%)
0.1 1
 
1.0%
0.072 1
 
1.0%
0.061 1
 
1.0%
0.052 1
 
1.0%
0.051 1
 
1.0%
0.048 1
 
1.0%
0.042 1
 
1.0%
0.04 80
80.0%
0.039 2
 
2.0%
0.031 2
 
2.0%

저수량(백만m3)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2.018
47 
2.017
33 
2.015
20 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.018
2nd row2.018
3rd row2.017
4th row2.018
5th row2.018

Common Values

ValueCountFrequency (%)
2.018 47
47.0%
2.017 33
33.0%
2.015 20
20.0%

Length

2024-04-17T03:11:17.281984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:17.363491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2.018 47
47.0%
2.017 33
33.0%
2.015 20
20.0%

저수율
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
76.6
47 
76.5
33 
76.4
20 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row76.6
2nd row76.6
3rd row76.5
4th row76.6
5th row76.6

Common Values

ValueCountFrequency (%)
76.6 47
47.0%
76.5 33
33.0%
76.4 20
20.0%

Length

2024-04-17T03:11:17.463302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:17.543448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
76.6 47
47.0%
76.5 33
33.0%
76.4 20
20.0%

Interactions

2024-04-17T03:11:15.444789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.026224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.240602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.517477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.100706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.308001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.590614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.170476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:15.376800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T03:11:17.614446image/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)1.0000.6600.2550.1600.4990.6600.660
저수위(m)0.6601.0000.6160.0890.5521.0001.000
강우량(mm)0.2550.6161.0000.3870.5780.6160.616
유입량(ms)0.1600.0890.3871.0000.6140.0890.089
방류량(ms)0.4990.5520.5780.6141.0000.5520.552
저수량(백만m3)0.6601.0000.6160.0890.5521.0001.000
저수율0.6601.0000.6160.0890.5521.0001.000
2024-04-17T03:11:17.705181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수위(m)저수율강우량(mm)저수량(백만m3)
저수위(m)1.0001.0000.2841.000
저수율1.0001.0000.2841.000
강우량(mm)0.2840.2841.0000.284
저수량(백만m3)1.0001.0000.2841.000
2024-04-17T03:11:17.791690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)유입량(ms)방류량(ms)저수위(m)강우량(mm)저수량(백만m3)저수율
일자/시간(t)1.000-0.389-0.5630.6850.2430.6850.685
유입량(ms)-0.3891.0000.6790.1460.6090.1460.146
방류량(ms)-0.5630.6791.0000.3830.2500.3830.383
저수위(m)0.6850.1460.3831.0000.2841.0001.000
강우량(mm)0.2430.6090.2500.2841.0000.2840.284
저수량(백만m3)0.6850.1460.3831.0000.2841.0001.000
저수율0.6850.1460.3831.0000.2841.0001.000

Missing values

2024-04-17T03:11:15.943636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T03:11:16.041364image/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
0감포20190409032038.050.00.090.0612.01876.6
1감포20190408154038.050.00.040.042.01876.6
2감포20190409140038.040.00.040.042.01776.5
3감포20190409034038.050.00.0470.042.01876.6
4감포20190408210038.050.00.040.042.01876.6
5감포20190408160038.050.00.040.042.01876.6
6감포20190409192038.030.00.0190.0162.01576.4
7감포20190409142038.040.00.040.042.01776.5
8감포20190409090038.040.00.040.042.01776.5
9감포20190409040038.050.00.040.042.01876.6
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90감포20190409062038.050.00.040.042.01876.6
91감포20190409060038.050.00.040.042.01876.6
92감포20190409052038.050.00.040.042.01876.6
93감포20190409050038.050.00.040.042.01876.6
94감포20190409030038.050.00.0840.12.01876.6
95감포20190409024038.050.00.0440.0522.01876.6
96감포20190409020038.050.00.040.042.01876.6
97감포20190409014038.050.00.040.042.01876.6
98감포20190408150038.050.00.0480.0482.01876.6
99감포20190408152038.050.00.0420.042.01876.6