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

Categorical2
Numeric6

Alerts

댐이름 has constant value ""Constant
일자/시간(t) is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
저수위(m) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 5 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 유입량(ms)High correlation
강우량(mm) is highly imbalanced (91.9%)Imbalance
일자/시간(t) has unique valuesUnique
유입량(ms) has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:22:27.952301
Analysis finished2023-12-10 10:22:33.529852
Duration5.58 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
군남
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군남 100
100.0%

Length

2023-12-10T19:22:33.634516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:33.754285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군남 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0230106 × 109
Minimum2.0230101 × 109
Maximum2.0230113 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:34.233788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0230101 × 109
5-th percentile2.0230101 × 109
Q12.0230103 × 109
median2.0230106 × 109
Q32.0230111 × 109
95-th percentile2.0230112 × 109
Maximum2.0230113 × 109
Range1202
Interquartile range (IQR)799

Descriptive statistics

Standard deviation391.69679
Coefficient of variation (CV)1.9362072 × 10-7
Kurtosis-1.3587131
Mean2.0230106 × 109
Median Absolute Deviation (MAD)400
Skewness0.1523856
Sum2.0230106 × 1011
Variance153426.37
MonotonicityNot monotonic
2023-12-10T19:22:34.479073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2023011204 1
 
1.0%
2023010610 1
 
1.0%
2023010210 1
 
1.0%
2023010216 1
 
1.0%
2023010218 1
 
1.0%
2023010222 1
 
1.0%
2023010224 1
 
1.0%
2023010518 1
 
1.0%
2023010520 1
 
1.0%
2023010524 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2023010102 1
1.0%
2023010104 1
1.0%
2023010106 1
1.0%
2023010108 1
1.0%
2023010110 1
1.0%
2023010112 1
1.0%
2023010114 1
1.0%
2023010116 1
1.0%
2023010118 1
1.0%
2023010120 1
1.0%
ValueCountFrequency (%)
2023011304 1
1.0%
2023011302 1
1.0%
2023011224 1
1.0%
2023011222 1
1.0%
2023011220 1
1.0%
2023011218 1
1.0%
2023011216 1
1.0%
2023011214 1
1.0%
2023011212 1
1.0%
2023011210 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.8843
Minimum23.3
Maximum24.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:34.728426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.3
5-th percentile23.31
Q123.3775
median23.78
Q324.40775
95-th percentile24.55
Maximum24.59
Range1.29
Interquartile range (IQR)1.03025

Descriptive statistics

Standard deviation0.49245047
Coefficient of variation (CV)0.020618166
Kurtosis-1.7498585
Mean23.8843
Median Absolute Deviation (MAD)0.431
Skewness0.081463784
Sum2388.43
Variance0.24250746
MonotonicityNot monotonic
2023-12-10T19:22:34.950683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.38 11
 
11.0%
23.37 6
 
6.0%
23.36 4
 
4.0%
23.3 4
 
4.0%
24.47 4
 
4.0%
23.32 3
 
3.0%
23.39 3
 
3.0%
24.59 3
 
3.0%
23.31 3
 
3.0%
23.35 3
 
3.0%
Other values (46) 56
56.0%
ValueCountFrequency (%)
23.3 4
 
4.0%
23.31 3
 
3.0%
23.32 3
 
3.0%
23.33 1
 
1.0%
23.334 1
 
1.0%
23.35 3
 
3.0%
23.36 4
 
4.0%
23.37 6
6.0%
23.38 11
11.0%
23.39 3
 
3.0%
ValueCountFrequency (%)
24.59 3
3.0%
24.56 1
 
1.0%
24.55 2
2.0%
24.54 3
3.0%
24.52 1
 
1.0%
24.516 1
 
1.0%
24.48 2
2.0%
24.47 4
4.0%
24.45 1
 
1.0%
24.43 3
3.0%

강우량(mm)
Categorical

HIGH CORRELATION  IMBALANCE 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
1 1
 
1.0%

Length

2023-12-10T19:22:35.159050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:35.306015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
1 1
 
1.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.60261
Minimum0
Maximum27.3
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:35.462165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.98
Q18.94225
median15.43
Q323.23625
95-th percentile25.9
Maximum27.3
Range27.3
Interquartile range (IQR)14.294

Descriptive statistics

Standard deviation7.3799001
Coefficient of variation (CV)0.47299139
Kurtosis-1.2746694
Mean15.60261
Median Absolute Deviation (MAD)6.7175
Skewness0.078423545
Sum1560.261
Variance54.462926
MonotonicityNot monotonic
2023-12-10T19:22:35.682412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.9 10
 
10.0%
25.2 5
 
5.0%
18.2 4
 
4.0%
27.3 3
 
3.0%
7.3 3
 
3.0%
23.8 2
 
2.0%
7.1 2
 
2.0%
7.4 2
 
2.0%
0.0 2
 
2.0%
7.0 2
 
2.0%
Other values (65) 65
65.0%
ValueCountFrequency (%)
0.0 2
2.0%
4.523 1
 
1.0%
6.55 1
 
1.0%
6.6 1
 
1.0%
7.0 2
2.0%
7.1 2
2.0%
7.237 1
 
1.0%
7.3 3
3.0%
7.4 2
2.0%
7.878 1
 
1.0%
ValueCountFrequency (%)
27.3 3
 
3.0%
25.9 10
10.0%
25.616 1
 
1.0%
25.2 5
5.0%
24.556 1
 
1.0%
24.076 1
 
1.0%
24.003 1
 
1.0%
23.8 2
 
2.0%
23.516 1
 
1.0%
23.143 1
 
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.92237
Minimum6.3
Maximum27.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:35.914215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.3
5-th percentile6.695
Q17.3
median12.71
Q322.46725
95-th percentile25.9
Maximum27.3
Range21
Interquartile range (IQR)15.16725

Descriptive statistics

Standard deviation7.433209
Coefficient of variation (CV)0.49812523
Kurtosis-1.421357
Mean14.92237
Median Absolute Deviation (MAD)5.616
Skewness0.39297352
Sum1492.237
Variance55.252596
MonotonicityNot monotonic
2023-12-10T19:22:36.152854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.9 10
 
10.0%
25.2 5
 
5.0%
7.3 5
 
5.0%
7.0 4
 
4.0%
18.2 4
 
4.0%
27.3 3
 
3.0%
7.4 3
 
3.0%
7.1 3
 
3.0%
23.8 2
 
2.0%
13.8 2
 
2.0%
Other values (57) 59
59.0%
ValueCountFrequency (%)
6.3 1
 
1.0%
6.435 1
 
1.0%
6.597 1
 
1.0%
6.6 2
2.0%
6.7 1
 
1.0%
6.733 1
 
1.0%
6.888 1
 
1.0%
6.918 1
 
1.0%
7.0 4
4.0%
7.08 1
 
1.0%
ValueCountFrequency (%)
27.3 3
 
3.0%
26.588 1
 
1.0%
25.9 10
10.0%
25.223 1
 
1.0%
25.2 5
5.0%
24.488 1
 
1.0%
24.115 1
 
1.0%
23.8 2
 
2.0%
22.528 1
 
1.0%
22.447 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.802695
Minimum0.5696
Maximum1.1055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:36.396064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5696
5-th percentile0.5731
Q10.596625
median0.7473
Q31.01845
95-th percentile1.0861
Maximum1.1055
Range0.5359
Interquartile range (IQR)0.421825

Descriptive statistics

Standard deviation0.20237521
Coefficient of variation (CV)0.25211968
Kurtosis-1.7184828
Mean0.802695
Median Absolute Deviation (MAD)0.16905
Skewness0.13743598
Sum80.2695
Variance0.040955726
MonotonicityNot monotonic
2023-12-10T19:22:36.645545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5975 11
 
11.0%
0.594 6
 
6.0%
0.5905 4
 
4.0%
0.5696 4
 
4.0%
1.0477 4
 
4.0%
0.5765 3
 
3.0%
0.601 3
 
3.0%
1.1055 3
 
3.0%
0.5731 3
 
3.0%
0.587 3
 
3.0%
Other values (46) 56
56.0%
ValueCountFrequency (%)
0.5696 4
 
4.0%
0.5731 3
 
3.0%
0.5765 3
 
3.0%
0.58 1
 
1.0%
0.5814 1
 
1.0%
0.587 3
 
3.0%
0.5905 4
 
4.0%
0.594 6
6.0%
0.5975 11
11.0%
0.601 3
 
3.0%
ValueCountFrequency (%)
1.1055 3
3.0%
1.0909 1
 
1.0%
1.0861 2
2.0%
1.0812 3
3.0%
1.0716 1
 
1.0%
1.0697 1
 
1.0%
1.0525 2
2.0%
1.0477 4
4.0%
1.0383 1
 
1.0%
1.0288 3
3.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.113
Minimum0.8
Maximum1.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:36.830282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile0.8
Q10.8
median1.05
Q31.4
95-th percentile1.5
Maximum1.5
Range0.7
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.29116797
Coefficient of variation (CV)0.26160644
Kurtosis-1.7440006
Mean1.113
Median Absolute Deviation (MAD)0.25
Skewness0.10666276
Sum111.3
Variance0.084778788
MonotonicityNot monotonic
2023-12-10T19:22:37.016938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.8 39
39.0%
1.5 18
18.0%
1.4 16
16.0%
1.3 9
 
9.0%
1.0 9
 
9.0%
1.2 5
 
5.0%
1.1 2
 
2.0%
0.9 2
 
2.0%
ValueCountFrequency (%)
0.8 39
39.0%
0.9 2
 
2.0%
1.0 9
 
9.0%
1.1 2
 
2.0%
1.2 5
 
5.0%
1.3 9
 
9.0%
1.4 16
16.0%
1.5 18
18.0%
ValueCountFrequency (%)
1.5 18
18.0%
1.4 16
16.0%
1.3 9
 
9.0%
1.2 5
 
5.0%
1.1 2
 
2.0%
1.0 9
 
9.0%
0.9 2
 
2.0%
0.8 39
39.0%

Interactions

2023-12-10T19:22:32.405643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:28.291897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.152894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.002983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.797114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.601181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.555240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:28.448047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.300623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.132009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.917638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.753620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.684300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:28.586924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.451020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.270072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.053437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.890046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.808971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:28.742867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.592655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.414201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.210166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.016866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.932941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:28.861405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.712232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.537688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.324810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.131289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:33.063948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.002172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:29.853197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:30.660539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:31.440499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:32.274078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:22:37.181861image/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)1.0000.8450.0000.6350.9140.8540.843
저수위(m)0.8451.0000.0000.7400.7770.9900.941
강우량(mm)0.0000.0001.0000.8340.0000.0000.000
유입량(ms)0.6350.7400.8341.0000.7490.7630.641
방류량(ms)0.9140.7770.0000.7491.0000.7800.786
저수량(백만m3)0.8540.9900.0000.7630.7801.0000.953
저수율0.8430.9410.0000.6410.7860.9531.000
2023-12-10T19:22:37.369459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율강우량(mm)
일자/시간(t)1.0000.878-0.904-0.9010.8780.9470.000
저수위(m)0.8781.000-0.769-0.7591.0000.9650.000
유입량(ms)-0.904-0.7691.0000.914-0.769-0.8620.639
방류량(ms)-0.901-0.7590.9141.000-0.759-0.8530.000
저수량(백만m3)0.8781.000-0.769-0.7591.0000.9650.000
저수율0.9470.965-0.862-0.8530.9651.0000.000
강우량(mm)0.0000.0000.6390.0000.0000.0001.000

Missing values

2023-12-10T19:22:33.277992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:22:33.452366image/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
0군남202301120424.55012.3557.2721.08611.5
1군남202301062023.896016.78610.480.7941.1
2군남202301011823.39027.327.30.6010.8
3군남202301120624.5909.0117.41.10551.5
4군남202301080424.21016.85912.5530.92821.3
5군남202301062224.022018.56211.340.84651.2
6군남202301051223.3018.218.20.56960.8
7군남202301012023.38025.61626.5880.59750.8
8군남202301031023.31018.87819.8220.57310.8
9군남202301120824.5907.47.41.10551.5
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202301122224.5407.37.31.08121.5
91군남202301122024.5408.6337.31.08121.5
92군남202301121624.4808.4337.11.05251.5
93군남202301121424.4804.5237.1621.05251.5
94군남202301120224.4508.3337.01.03831.5
95군남202301112424.4307.07.01.02881.4
96군남202301112024.4308.3067.01.02881.4
97군남202301111824.407010.3886.8881.01811.4
98군남202301082424.12012.212.20.88861.2
99군남202301061823.79014.4499.7270.75131.1