Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows49
Duplicate rows (%)49.0%
Total size in memory7.1 KiB
Average record size in memory72.3 B

Variable types

Categorical3
Numeric5

Alerts

댐이름 has constant value ""Constant
강우량(mm) has constant value ""Constant
Dataset has 49 (49.0%) duplicate rowsDuplicates
일자/시간(t) is highly overall correlated with 저수위(m) and 2 other fieldsHigh correlation
저수위(m) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 저수율High correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
유입량(ms) has 13 (13.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:00:13.273350
Analysis finished2023-12-10 12:00:17.850739
Duration4.58 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

2023-12-10T21:00:17.968564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:18.118608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군위 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190205 × 109
Minimum2.0190204 × 109
Maximum2.0190206 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:00:18.280819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190204 × 109
5-th percentile2.0190204 × 109
Q12.0190205 × 109
median2.0190205 × 109
Q32.0190206 × 109
95-th percentile2.0190206 × 109
Maximum2.0190206 × 109
Range202
Interquartile range (IQR)100.5

Descriptive statistics

Standard deviation64.792773
Coefficient of variation (CV)3.2091191 × 10-8
Kurtosis-0.91676343
Mean2.0190205 × 109
Median Absolute Deviation (MAD)82.5
Skewness-0.28998385
Sum2.0190205 × 1011
Variance4198.1034
MonotonicityNot monotonic
2023-12-10T21:00:18.508742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019020513 2
 
2.0%
2019020505 2
 
2.0%
2019020610 2
 
2.0%
2019020608 2
 
2.0%
2019020603 2
 
2.0%
2019020602 2
 
2.0%
2019020524 2
 
2.0%
2019020520 2
 
2.0%
2019020516 2
 
2.0%
2019020515 2
 
2.0%
Other values (41) 80
80.0%
ValueCountFrequency (%)
2019020418 1
1.0%
2019020419 2
2.0%
2019020420 2
2.0%
2019020421 2
2.0%
2019020422 2
2.0%
2019020423 2
2.0%
2019020424 2
2.0%
2019020501 2
2.0%
2019020502 2
2.0%
2019020503 2
2.0%
ValueCountFrequency (%)
2019020620 1
1.0%
2019020619 2
2.0%
2019020618 2
2.0%
2019020617 2
2.0%
2019020616 2
2.0%
2019020615 2
2.0%
2019020614 2
2.0%
2019020613 2
2.0%
2019020612 2
2.0%
2019020611 2
2.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194.1697
Minimum194.13
Maximum194.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:00:18.703467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum194.13
5-th percentile194.14
Q1194.15
median194.17
Q3194.19
95-th percentile194.2
Maximum194.2
Range0.07
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.020765891
Coefficient of variation (CV)0.00010694712
Kurtosis-1.2958269
Mean194.1697
Median Absolute Deviation (MAD)0.02
Skewness0.013150069
Sum19416.97
Variance0.00043122222
MonotonicityNot monotonic
2023-12-10T21:00:18.889556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
194.16 18
18.0%
194.19 16
16.0%
194.2 15
15.0%
194.14 14
14.0%
194.15 14
14.0%
194.18 12
12.0%
194.17 10
10.0%
194.13 1
 
1.0%
ValueCountFrequency (%)
194.13 1
 
1.0%
194.14 14
14.0%
194.15 14
14.0%
194.16 18
18.0%
194.17 10
10.0%
194.18 12
12.0%
194.19 16
16.0%
194.2 15
15.0%
ValueCountFrequency (%)
194.2 15
15.0%
194.19 16
16.0%
194.18 12
12.0%
194.17 10
10.0%
194.16 18
18.0%
194.15 14
14.0%
194.14 14
14.0%
194.13 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

2023-12-10T21:00:19.043283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:19.184436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.80146
Minimum0
Maximum1.029
Zeros13
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:00:19.321867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.80675
median0.917
Q30.999
95-th percentile1.028
Maximum1.029
Range1.029
Interquartile range (IQR)0.19225

Descriptive statistics

Standard deviation0.32297917
Coefficient of variation (CV)0.40298851
Kurtosis2.2770341
Mean0.80146
Median Absolute Deviation (MAD)0.084
Skewness-1.9268677
Sum80.146
Variance0.10431554
MonotonicityNot monotonic
2023-12-10T21:00:19.477372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 13
13.0%
0.999 12
 
12.0%
0.834 8
 
8.0%
0.918 7
 
7.0%
1.028 6
 
6.0%
0.778 6
 
6.0%
1.0 4
 
4.0%
1.027 4
 
4.0%
0.806 4
 
4.0%
0.835 4
 
4.0%
Other values (14) 32
32.0%
ValueCountFrequency (%)
0.0 13
13.0%
0.775 2
 
2.0%
0.778 6
6.0%
0.806 4
 
4.0%
0.807 2
 
2.0%
0.808 2
 
2.0%
0.809 2
 
2.0%
0.833 2
 
2.0%
0.834 8
8.0%
0.835 4
 
4.0%
ValueCountFrequency (%)
1.029 2
 
2.0%
1.028 6
6.0%
1.027 4
 
4.0%
1.026 4
 
4.0%
1.002 2
 
2.0%
1.001 2
 
2.0%
1.0 4
 
4.0%
0.999 12
12.0%
0.998 2
 
2.0%
0.997 2
 
2.0%

방류량(ms)
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91676
Minimum0.914
Maximum0.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:00:19.636158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.914
5-th percentile0.91495
Q10.916
median0.917
Q30.918
95-th percentile0.919
Maximum0.92
Range0.006
Interquartile range (IQR)0.002

Descriptive statistics

Standard deviation0.0013113337
Coefficient of variation (CV)0.0014304002
Kurtosis-0.16754292
Mean0.91676
Median Absolute Deviation (MAD)0.001
Skewness-0.14647269
Sum91.676
Variance1.719596 × 10-6
MonotonicityNot monotonic
2023-12-10T21:00:19.796438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.917 34
34.0%
0.918 23
23.0%
0.916 18
18.0%
0.915 14
14.0%
0.914 5
 
5.0%
0.919 4
 
4.0%
0.92 2
 
2.0%
ValueCountFrequency (%)
0.914 5
 
5.0%
0.915 14
14.0%
0.916 18
18.0%
0.917 34
34.0%
0.918 23
23.0%
0.919 4
 
4.0%
0.92 2
 
2.0%
ValueCountFrequency (%)
0.92 2
 
2.0%
0.919 4
 
4.0%
0.918 23
23.0%
0.917 34
34.0%
0.916 18
18.0%
0.915 14
14.0%
0.914 5
 
5.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.67596
Minimum25.6
Maximum25.734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:00:19.966777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.6
5-th percentile25.619
Q125.638
median25.677
Q325.715
95-th percentile25.734
Maximum25.734
Range0.134
Interquartile range (IQR)0.077

Descriptive statistics

Standard deviation0.039896563
Coefficient of variation (CV)0.0015538489
Kurtosis-1.308191
Mean25.67596
Median Absolute Deviation (MAD)0.038
Skewness0.010932197
Sum2567.596
Variance0.0015917358
MonotonicityNot monotonic
2023-12-10T21:00:20.127041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
25.657 18
18.0%
25.715 16
16.0%
25.734 15
15.0%
25.619 14
14.0%
25.638 14
14.0%
25.696 12
12.0%
25.677 10
10.0%
25.6 1
 
1.0%
ValueCountFrequency (%)
25.6 1
 
1.0%
25.619 14
14.0%
25.638 14
14.0%
25.657 18
18.0%
25.677 10
10.0%
25.696 12
12.0%
25.715 16
16.0%
25.734 15
15.0%
ValueCountFrequency (%)
25.734 15
15.0%
25.715 16
16.0%
25.696 12
12.0%
25.677 10
10.0%
25.657 18
18.0%
25.638 14
14.0%
25.619 14
14.0%
25.6 1
 
1.0%

저수율
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
52.8
43 
52.7
42 
52.6
15 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row52.8
2nd row52.8
3rd row52.7
4th row52.8
5th row52.8

Common Values

ValueCountFrequency (%)
52.8 43
43.0%
52.7 42
42.0%
52.6 15
 
15.0%

Length

2023-12-10T21:00:20.295599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:20.457602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
52.8 43
43.0%
52.7 42
42.0%
52.6 15
 
15.0%

Interactions

2023-12-10T21:00:16.832670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:13.561184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:14.618695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.414283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.158543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.969878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:13.716561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:14.785383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.579946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.310438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:17.124702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:13.870638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:14.938789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.730090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.460274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:17.253858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:14.331236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.090194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.865977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.570474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:17.378726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:14.468887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:15.245574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.014672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:00:16.692742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:00:20.571268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8740.8930.3930.9810.624
저수위(m)0.8741.0000.8360.7361.0001.000
유입량(ms)0.8930.8361.0000.5650.9690.579
방류량(ms)0.3930.7360.5651.0000.5900.467
저수량(백만m3)0.9811.0000.9690.5901.0001.000
저수율0.6241.0000.5790.4671.0001.000
2023-12-10T21:00:20.721727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.9890.373-0.438-0.9890.642
저수위(m)-0.9891.000-0.3320.4291.0000.974
유입량(ms)0.373-0.3321.000-0.142-0.3320.587
방류량(ms)-0.4380.429-0.1421.0000.4290.347
저수량(백만m3)-0.9891.000-0.3320.4291.0000.974
저수율0.6420.9740.5870.3470.9741.000

Missing values

2023-12-10T21:00:17.576062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:00:17.772624image/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
0군위2019020513194.1800.8070.91925.69652.8
1군위2019020419194.200.9170.91725.73452.8
2군위2019020605194.1601.0270.91625.65752.7
3군위2019020513194.1800.8070.91925.69652.8
4군위2019020503194.1900.8340.91825.71552.8
5군위2019020420194.200.9170.91725.73452.8
6군위2019020613194.1400.00.91625.61952.6
7군위2019020605194.1601.0270.91625.65752.7
8군위2019020521194.1600.00.91725.65752.7
9군위2019020514194.1800.8060.91725.69652.8
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위2019020517194.1700.7780.91725.67752.7
91군위2019020517194.1700.7780.91725.67752.7
92군위2019020516194.1700.00.91825.67752.7
93군위2019020515194.1800.8060.91725.69652.8
94군위2019020512194.1800.8080.91925.69652.8
95군위2019020512194.1800.8080.91925.69652.8
96군위2019020511194.1800.8090.9225.69652.8
97군위2019020510194.1800.00.91725.69652.8
98군위2019020418194.200.9180.91825.73452.8
99군위2019020419194.200.9170.91725.73452.8

Duplicate rows

Most frequently occurring

댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율# duplicates
0군위2019020419194.200.9170.91725.73452.82
1군위2019020420194.200.9170.91725.73452.82
2군위2019020421194.200.9180.91825.73452.82
3군위2019020422194.200.9180.91825.73452.82
4군위2019020423194.200.9160.91625.73452.82
5군위2019020424194.200.9180.91825.73452.82
6군위2019020501194.200.9150.91525.73452.82
7군위2019020502194.1900.00.91625.71552.82
8군위2019020503194.1900.8340.91825.71552.82
9군위2019020504194.1900.8340.91725.71552.82