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

Categorical3
Numeric5

Alerts

댐이름 has constant value ""Constant
강우량(mm) is highly overall correlated with 방류량(ms) and 3 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 강우량(mm) and 1 other fieldsHigh correlation
저수위(m) is highly imbalanced (85.9%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:16:03.453860
Analysis finished2023-12-10 13:16:08.947327
Duration5.49 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

2023-12-10T22:16:09.071129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:09.292742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군남 100
100.0%

일자/시간(t)
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190204 × 1011
Minimum2.0190203 × 1011
Maximum2.0190204 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:09.481598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190203 × 1011
5-th percentile2.0190203 × 1011
Q12.0190203 × 1011
median2.0190203 × 1011
Q32.0190204 × 1011
95-th percentile2.0190204 × 1011
Maximum2.0190204 × 1011
Range9390
Interquartile range (IQR)8415

Descriptive statistics

Standard deviation4153.3318
Coefficient of variation (CV)2.0571025 × 10-8
Kurtosis-1.815224
Mean2.0190204 × 1011
Median Absolute Deviation (MAD)710
Skewness0.44978684
Sum2.0190204 × 1013
Variance17250165
MonotonicityNot monotonic
2023-12-10T22:16:09.742909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201902031930 1
 
1.0%
201902040520 1
 
1.0%
201902040210 1
 
1.0%
201902040240 1
 
1.0%
201902040250 1
 
1.0%
201902040310 1
 
1.0%
201902040320 1
 
1.0%
201902040400 1
 
1.0%
201902040410 1
 
1.0%
201902040430 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201902031320 1
1.0%
201902031330 1
1.0%
201902031340 1
1.0%
201902031350 1
1.0%
201902031400 1
1.0%
201902031410 1
1.0%
201902031420 1
1.0%
201902031430 1
1.0%
201902031440 1
1.0%
201902031450 1
1.0%
ValueCountFrequency (%)
201902040710 1
1.0%
201902040700 1
1.0%
201902040650 1
1.0%
201902040640 1
1.0%
201902040550 1
1.0%
201902040540 1
1.0%
201902040530 1
1.0%
201902040520 1
1.0%
201902040510 1
1.0%
201902040500 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
98 
1
 
2

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 98
98.0%
1 2
 
2.0%

Length

2023-12-10T22:16:09.955980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:10.185933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 98
98.0%
1 2
 
2.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.63127
Minimum3.595
Maximum3.673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:10.329007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.595
5-th percentile3.595
Q13.621
median3.634
Q33.647
95-th percentile3.673
Maximum3.673
Range0.078
Interquartile range (IQR)0.026

Descriptive statistics

Standard deviation0.024323931
Coefficient of variation (CV)0.006698464
Kurtosis-0.7640561
Mean3.63127
Median Absolute Deviation (MAD)0.013
Skewness0.11372931
Sum363.127
Variance0.00059165364
MonotonicityNot monotonic
2023-12-10T22:16:10.711565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3.634 34
34.0%
3.595 18
18.0%
3.621 15
15.0%
3.673 12
 
12.0%
3.66 9
 
9.0%
3.647 6
 
6.0%
3.608 6
 
6.0%
ValueCountFrequency (%)
3.595 18
18.0%
3.608 6
 
6.0%
3.621 15
15.0%
3.634 34
34.0%
3.647 6
 
6.0%
3.66 9
 
9.0%
3.673 12
 
12.0%
ValueCountFrequency (%)
3.673 12
 
12.0%
3.66 9
 
9.0%
3.647 6
 
6.0%
3.634 34
34.0%
3.621 15
15.0%
3.608 6
 
6.0%
3.595 18
18.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
5.1
76 
5.0
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.1
2nd row5.1
3rd row5.0
4th row5.1
5th row5.1

Common Values

ValueCountFrequency (%)
5.1 76
76.0%
5.0 24
 
24.0%

Length

2023-12-10T22:16:10.973671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:16:11.139028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.1 76
76.0%
5.0 24
 
24.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.44019
Minimum2.447
Maximum25.278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:11.325258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.447
5-th percentile2.578
Q19.8
median9.8
Q318
95-th percentile25.07235
Maximum25.278
Range22.831
Interquartile range (IQR)8.2

Descriptive statistics

Standard deviation6.1699969
Coefficient of variation (CV)0.49597288
Kurtosis-0.15263055
Mean12.44019
Median Absolute Deviation (MAD)0.2
Skewness0.73441652
Sum1244.019
Variance38.068862
MonotonicityNot monotonic
2023-12-10T22:16:11.684766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
9.8 45
45.0%
9.6 15
 
15.0%
18.0 14
 
14.0%
2.578 6
 
6.0%
25.278 3
 
3.0%
17.022 2
 
2.0%
24.056 1
 
1.0%
2.447 1
 
1.0%
24.719 1
 
1.0%
25.202 1
 
1.0%
Other values (11) 11
 
11.0%
ValueCountFrequency (%)
2.447 1
 
1.0%
2.513 1
 
1.0%
2.578 6
 
6.0%
2.58 1
 
1.0%
9.6 15
 
15.0%
9.8 45
45.0%
10.88 1
 
1.0%
17.022 2
 
2.0%
18.0 14
 
14.0%
19.386 1
 
1.0%
ValueCountFrequency (%)
25.278 3
3.0%
25.202 1
 
1.0%
25.136 1
 
1.0%
25.069 1
 
1.0%
25.022 1
 
1.0%
24.719 1
 
1.0%
24.3 1
 
1.0%
24.189 1
 
1.0%
24.122 1
 
1.0%
24.056 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.7147
Minimum9.6
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:11.906861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.6
5-th percentile9.6
Q19.8
median9.8
Q39.8
95-th percentile18
Maximum18
Range8.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.5107133
Coefficient of variation (CV)0.29968444
Kurtosis-0.47036249
Mean11.7147
Median Absolute Deviation (MAD)0
Skewness1.2379072
Sum1171.47
Variance12.325108
MonotonicityNot monotonic
2023-12-10T22:16:12.061130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
9.8 58
58.0%
18.0 19
 
19.0%
9.6 17
 
17.0%
17.8 3
 
3.0%
17.94 1
 
1.0%
16.89 1
 
1.0%
9.64 1
 
1.0%
ValueCountFrequency (%)
9.6 17
 
17.0%
9.64 1
 
1.0%
9.8 58
58.0%
16.89 1
 
1.0%
17.8 3
 
3.0%
17.94 1
 
1.0%
18.0 19
 
19.0%
ValueCountFrequency (%)
18.0 19
 
19.0%
17.94 1
 
1.0%
17.8 3
 
3.0%
16.89 1
 
1.0%
9.8 58
58.0%
9.64 1
 
1.0%
9.6 17
 
17.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.7379
Minimum25.71
Maximum25.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:16:12.207263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.71
5-th percentile25.71
Q125.73
median25.74
Q325.75
95-th percentile25.77
Maximum25.77
Range0.06
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.018710716
Coefficient of variation (CV)0.00072697137
Kurtosis-0.7640561
Mean25.7379
Median Absolute Deviation (MAD)0.01
Skewness0.11372931
Sum2573.79
Variance0.00035009091
MonotonicityNot monotonic
2023-12-10T22:16:12.383586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
25.74 34
34.0%
25.71 18
18.0%
25.73 15
15.0%
25.77 12
 
12.0%
25.76 9
 
9.0%
25.75 6
 
6.0%
25.72 6
 
6.0%
ValueCountFrequency (%)
25.71 18
18.0%
25.72 6
 
6.0%
25.73 15
15.0%
25.74 34
34.0%
25.75 6
 
6.0%
25.76 9
 
9.0%
25.77 12
 
12.0%
ValueCountFrequency (%)
25.77 12
 
12.0%
25.76 9
 
9.0%
25.75 6
 
6.0%
25.74 34
34.0%
25.73 15
15.0%
25.72 6
 
6.0%
25.71 18
18.0%

Interactions

2023-12-10T22:16:07.596916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.000192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.891794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.695469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:06.928555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.727870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.187978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.041300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.902969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.053097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.900253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.365456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.201578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:06.051169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.201744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:08.039088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.558308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.333067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:06.188260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.319112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:08.285741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:04.748902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:05.525558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:06.792525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:16:07.435264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:16:12.607220image/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)1.0000.0000.7490.2940.8620.8120.749
저수위(m)0.0001.0000.0000.0000.0000.0000.000
강우량(mm)0.7490.0001.0001.0000.6230.7161.000
유입량(ms)0.2940.0001.0001.0000.5390.1731.000
방류량(ms)0.8620.0000.6230.5391.0000.9970.623
저수량(백만m3)0.8120.0000.7160.1730.9971.0000.716
저수율0.7490.0001.0001.0000.6230.7161.000
2023-12-10T22:16:12.903484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수위(m)유입량(ms)
저수위(m)1.0000.000
유입량(ms)0.0001.000
2023-12-10T22:16:13.080544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)방류량(ms)저수량(백만m3)저수율저수위(m)유입량(ms)
일자/시간(t)1.0000.3350.4590.3840.3350.0000.473
강우량(mm)0.3351.0000.8250.8931.0000.0000.974
방류량(ms)0.4590.8251.0000.8340.8250.0000.382
저수량(백만m3)0.3840.8930.8341.0000.8930.0000.283
저수율0.3351.0000.8250.8931.0000.0000.974
저수위(m)0.0000.0000.0000.0000.0001.0000.000
유입량(ms)0.4730.9740.3820.2830.9740.0001.000

Missing values

2023-12-10T22:16:08.480438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:16:08.781089image/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
0군남20190203193003.6215.12.5789.825.73
1군남20190203134003.6345.19.89.825.74
2군남20190204005003.5955.09.69.625.71
3군남20190203194003.6215.19.89.825.73
4군남20190203162003.6345.19.89.825.74
5군남20190203135003.6345.19.89.825.74
6군남20190204033003.665.118.018.025.76
7군남20190204010003.5955.09.69.625.71
8군남20190203222003.5955.02.5139.625.71
9군남20190203195003.6215.19.89.825.73
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남20190203210003.6215.19.89.825.73
91군남20190203205003.6215.19.89.825.73
92군남20190203203003.6215.19.89.825.73
93군남20190203202003.6215.19.89.825.73
94군남20190203192003.6215.12.5789.825.73
95군남20190203191003.6215.12.5789.825.73
96군남20190203185003.6345.19.89.825.74
97군남20190203184003.6345.19.89.825.74
98군남20190203132003.6345.19.89.825.74
99군남20190203133003.6345.19.89.825.74