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 12 (12.0%) zerosZeros
저수량(백만m3) has 11 (11.0%) zerosZeros

Reproduction

Analysis started2024-04-16 18:11:18.327273
Analysis finished2024-04-16 18:11:19.381918
Duration1.05 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

2024-04-17T03:11:19.432932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:19.506218image/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%
Mean2.0190309 × 1011
Minimum2.0190308 × 1011
Maximum2.0190309 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:19.615514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190308 × 1011
5-th percentile2.0190308 × 1011
Q12.0190308 × 1011
median2.0190309 × 1011
Q32.0190309 × 1011
95-th percentile2.0190309 × 1011
Maximum2.0190309 × 1011
Range10900
Interquartile range (IQR)9240

Descriptive statistics

Standard deviation4225.8083
Coefficient of variation (CV)2.0929884 × 10-8
Kurtosis-1.0493003
Mean2.0190309 × 1011
Median Absolute Deviation (MAD)920
Skewness-0.93309791
Sum2.0190309 × 1013
Variance17857456
MonotonicityNot monotonic
2024-04-17T03:11:19.736235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201903090310 1
 
1.0%
201903092250 1
 
1.0%
201903091630 1
 
1.0%
201903091730 1
 
1.0%
201903091750 1
 
1.0%
201903091830 1
 
1.0%
201903091850 1
 
1.0%
201903092010 1
 
1.0%
201903092030 1
 
1.0%
201903092110 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201903081450 1
1.0%
201903081510 1
1.0%
201903081530 1
1.0%
201903081550 1
1.0%
201903081610 1
1.0%
201903081630 1
1.0%
201903081650 1
1.0%
201903081710 1
1.0%
201903081730 1
1.0%
201903081750 1
1.0%
ValueCountFrequency (%)
201903092350 1
1.0%
201903092330 1
1.0%
201903092310 1
1.0%
201903092250 1
1.0%
201903092230 1
1.0%
201903092210 1
1.0%
201903092150 1
1.0%
201903092130 1
1.0%
201903092110 1
1.0%
201903092050 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

2024-04-17T03:11:19.838717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:19.916008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2.087
59 
2.085
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.087
2nd row2.087
3rd row2.085
4th row2.087
5th row2.087

Common Values

ValueCountFrequency (%)
2.087 59
59.0%
2.085 41
41.0%

Length

2024-04-17T03:11:19.992022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:20.068672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2.087 59
59.0%
2.085 41
41.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
79.2
59 
79.1
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row79.2
2nd row79.2
3rd row79.1
4th row79.2
5th row79.2

Common Values

ValueCountFrequency (%)
79.2 59
59.0%
79.1 41
41.0%

Length

2024-04-17T03:11:20.152007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:20.226471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
79.2 59
59.0%
79.1 41
41.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03665
Minimum0
Maximum0.1
Zeros12
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:20.304477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median0.04
Q30.04
95-th percentile0.0481
Maximum0.1
Range0.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.018073573
Coefficient of variation (CV)0.49313978
Kurtosis3.7617089
Mean0.03665
Median Absolute Deviation (MAD)0
Skewness0.24164117
Sum3.665
Variance0.00032665404
MonotonicityNot monotonic
2024-04-17T03:11:20.398991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.04 75
75.0%
0.0 12
 
12.0%
0.042 2
 
2.0%
0.088 1
 
1.0%
0.023 1
 
1.0%
0.015 1
 
1.0%
0.004 1
 
1.0%
0.1 1
 
1.0%
0.05 1
 
1.0%
0.03 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
0.0 12
 
12.0%
0.004 1
 
1.0%
0.015 1
 
1.0%
0.023 1
 
1.0%
0.03 1
 
1.0%
0.035 1
 
1.0%
0.04 75
75.0%
0.042 2
 
2.0%
0.048 1
 
1.0%
0.05 1
 
1.0%
ValueCountFrequency (%)
0.1 1
 
1.0%
0.097 1
 
1.0%
0.091 1
 
1.0%
0.088 1
 
1.0%
0.05 1
 
1.0%
0.048 1
 
1.0%
0.042 2
 
2.0%
0.04 75
75.0%
0.035 1
 
1.0%
0.03 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03734
Minimum0
Maximum0.1
Zeros11
Zeros (%)11.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:20.487907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.04
median0.04
Q30.04
95-th percentile0.0507
Maximum0.1
Range0.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.018096944
Coefficient of variation (CV)0.48465303
Kurtosis3.9650269
Mean0.03734
Median Absolute Deviation (MAD)0
Skewness0.3601301
Sum3.734
Variance0.00032749939
MonotonicityNot monotonic
2024-04-17T03:11:20.583392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.04 78
78.0%
0.0 11
 
11.0%
0.1 2
 
2.0%
0.05 2
 
2.0%
0.015 1
 
1.0%
0.011 1
 
1.0%
0.03 1
 
1.0%
0.012 1
 
1.0%
0.09 1
 
1.0%
0.092 1
 
1.0%
ValueCountFrequency (%)
0.0 11
 
11.0%
0.011 1
 
1.0%
0.012 1
 
1.0%
0.015 1
 
1.0%
0.03 1
 
1.0%
0.04 78
78.0%
0.05 2
 
2.0%
0.064 1
 
1.0%
0.09 1
 
1.0%
0.092 1
 
1.0%
ValueCountFrequency (%)
0.1 2
 
2.0%
0.092 1
 
1.0%
0.09 1
 
1.0%
0.064 1
 
1.0%
0.05 2
 
2.0%
0.04 78
78.0%
0.03 1
 
1.0%
0.015 1
 
1.0%
0.012 1
 
1.0%
0.011 1
 
1.0%

저수율
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
38.43
59 
38.42
41 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38.43
2nd row38.43
3rd row38.42
4th row38.43
5th row38.43

Common Values

ValueCountFrequency (%)
38.43 59
59.0%
38.42 41
41.0%

Length

2024-04-17T03:11:20.681106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:20.766307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38.43 59
59.0%
38.42 41
41.0%

Interactions

2024-04-17T03:11:18.970690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.547369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.753767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:19.045295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.616264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.825766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:19.113958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.685913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:18.891003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T03:11:20.818851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9760.9760.3610.2800.976
강우량(mm)0.9761.0000.9990.5710.3830.999
유입량(ms)0.9760.9991.0000.5710.3830.999
방류량(ms)0.3610.5710.5711.0000.9030.571
저수량(백만m3)0.2800.3830.3830.9031.0000.383
저수율0.9760.9990.9990.5710.3831.000
2024-04-17T03:11:20.906225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수율강우량(mm)유입량(ms)
저수율1.0000.9790.979
강우량(mm)0.9791.0000.979
유입량(ms)0.9790.9791.000
2024-04-17T03:11:20.980133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.091-0.1240.8520.8520.852
방류량(ms)-0.0911.0000.7810.3820.3820.382
저수량(백만m3)-0.1240.7811.0000.3860.3860.386
강우량(mm)0.8520.3820.3861.0000.9790.979
유입량(ms)0.8520.3820.3860.9791.0000.979
저수율0.8520.3820.3860.9790.9791.000

Missing values

2024-04-17T03:11:19.213358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T03:11:19.331906image/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
0감포20190309031002.08779.20.040.0438.43
1감포20190308153002.08779.20.040.0438.43
2감포20190309135002.08579.10.00.038.42
3감포20190309033002.08779.20.040.0438.43
4감포20190308205002.08779.20.040.0438.43
5감포20190308155002.08779.20.040.0438.43
6감포20190309191002.08579.10.040.0438.42
7감포20190309141002.08579.10.00.038.42
8감포20190309085002.08779.20.040.0438.43
9감포20190309035002.08779.20.040.0438.43
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90감포20190309061002.08779.20.040.0438.43
91감포20190309055002.08779.20.040.0438.43
92감포20190309051002.08779.20.040.0438.43
93감포20190309045002.08779.20.040.0438.43
94감포20190309025002.08779.20.040.0438.43
95감포20190309023002.08779.20.040.0438.43
96감포20190309015002.08779.20.040.0438.43
97감포20190309013002.08779.20.040.0438.43
98감포20190308145002.08779.20.040.0438.43
99감포20190308151002.08779.20.040.0438.43