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
저수위(m) has constant value ""Constant
일자/시간(t) is highly overall correlated with 강우량(mm) 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 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 유입량(ms)High correlation
저수율 is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique
방류량(ms) has 24 (24.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:15:40.083268
Analysis finished2023-12-10 13:15:46.911062
Duration6.83 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

2023-12-10T22:15:47.055044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:47.314927image/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%
Mean2.0190509 × 1011
Minimum2.0190508 × 1011
Maximum2.0190509 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:47.504915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190508 × 1011
5-th percentile2.0190508 × 1011
Q12.0190509 × 1011
median2.0190509 × 1011
Q32.0190509 × 1011
95-th percentile2.0190509 × 1011
Maximum2.0190509 × 1011
Range11180
Interquartile range (IQR)1745

Descriptive statistics

Standard deviation3678.2892
Coefficient of variation (CV)1.8217912 × 10-8
Kurtosis1.6250341
Mean2.0190509 × 1011
Median Absolute Deviation (MAD)760
Skewness-1.8188879
Sum2.0190509 × 1013
Variance13529811
MonotonicityNot monotonic
2023-12-10T22:15:47.785124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201905091830 1
 
1.0%
201905090450 1
 
1.0%
201905090140 1
 
1.0%
201905090210 1
 
1.0%
201905090220 1
 
1.0%
201905090240 1
 
1.0%
201905090250 1
 
1.0%
201905090330 1
 
1.0%
201905090340 1
 
1.0%
201905090400 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201905081220 1
1.0%
201905081230 1
1.0%
201905081240 1
1.0%
201905081250 1
1.0%
201905081300 1
1.0%
201905081310 1
1.0%
201905081320 1
1.0%
201905081330 1
1.0%
201905081340 1
1.0%
201905081350 1
1.0%
ValueCountFrequency (%)
201905092400 1
1.0%
201905092350 1
1.0%
201905092340 1
1.0%
201905092330 1
1.0%
201905092320 1
1.0%
201905092310 1
1.0%
201905092300 1
1.0%
201905092250 1
1.0%
201905092240 1
1.0%
201905092230 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

2023-12-10T22:15:48.133094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:48.345919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.39567
Minimum3.954
Maximum4.786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:48.673004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.954
5-th percentile3.994
Q14.203
median4.366
Q34.607
95-th percentile4.771
Maximum4.786
Range0.832
Interquartile range (IQR)0.404

Descriptive statistics

Standard deviation0.25913473
Coefficient of variation (CV)0.058952272
Kurtosis-1.3412091
Mean4.39567
Median Absolute Deviation (MAD)0.226
Skewness-0.059732953
Sum439.567
Variance0.067150809
MonotonicityNot monotonic
2023-12-10T22:15:49.063039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4.592 14
 
14.0%
4.607 12
 
12.0%
4.756 8
 
8.0%
4.203 6
 
6.0%
4.147 6
 
6.0%
4.771 4
 
4.0%
4.091 4
 
4.0%
4.786 3
 
3.0%
4.049 3
 
3.0%
4.621 3
 
3.0%
Other values (20) 37
37.0%
ValueCountFrequency (%)
3.954 2
 
2.0%
3.981 1
 
1.0%
3.994 3
3.0%
4.008 2
 
2.0%
4.022 2
 
2.0%
4.036 1
 
1.0%
4.049 3
3.0%
4.091 4
4.0%
4.147 6
6.0%
4.203 6
6.0%
ValueCountFrequency (%)
4.786 3
 
3.0%
4.771 4
 
4.0%
4.756 8
8.0%
4.621 3
 
3.0%
4.607 12
12.0%
4.592 14
14.0%
4.402 2
 
2.0%
4.388 1
 
1.0%
4.373 3
 
3.0%
4.359 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.139
Minimum5.5
Maximum6.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:49.330974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile5.6
Q15.9
median6.1
Q36.4
95-th percentile6.7
Maximum6.7
Range1.2
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.35388037
Coefficient of variation (CV)0.057644627
Kurtosis-1.2448975
Mean6.139
Median Absolute Deviation (MAD)0.3
Skewness-0.074305581
Sum613.9
Variance0.12523131
MonotonicityNot monotonic
2023-12-10T22:15:49.519125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
6.4 26
26.0%
5.9 12
12.0%
6.1 10
 
10.0%
5.6 9
 
9.0%
6.6 8
 
8.0%
6.0 8
 
8.0%
6.7 7
 
7.0%
5.7 7
 
7.0%
5.8 6
 
6.0%
6.5 3
 
3.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
5.5 2
 
2.0%
5.6 9
 
9.0%
5.7 7
 
7.0%
5.8 6
 
6.0%
5.9 12
12.0%
6.0 8
 
8.0%
6.1 10
 
10.0%
6.2 2
 
2.0%
6.4 26
26.0%
6.5 3
 
3.0%
ValueCountFrequency (%)
6.7 7
 
7.0%
6.6 8
 
8.0%
6.5 3
 
3.0%
6.4 26
26.0%
6.2 2
 
2.0%
6.1 10
 
10.0%
6.0 8
 
8.0%
5.9 12
12.0%
5.8 6
 
6.0%
5.7 7
 
7.0%

방류량(ms)
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.33272
Minimum0
Maximum17.3
Zeros24
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:49.762645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.6435
median5.689
Q39.28375
95-th percentile17.2
Maximum17.3
Range17.3
Interquartile range (IQR)7.64025

Descriptive statistics

Standard deviation4.8162938
Coefficient of variation (CV)0.90315895
Kurtosis0.27752496
Mean5.33272
Median Absolute Deviation (MAD)3.973
Skewness0.81109248
Sum533.272
Variance23.196686
MonotonicityNot monotonic
2023-12-10T22:15:50.001950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 24
24.0%
5.689 11
 
11.0%
5.778 9
 
9.0%
7.333 5
 
5.0%
17.2 3
 
3.0%
9.567 3
 
3.0%
6.422 3
 
3.0%
17.3 3
 
3.0%
7.644 3
 
3.0%
9.289 3
 
3.0%
Other values (27) 33
33.0%
ValueCountFrequency (%)
0.0 24
24.0%
1.627 1
 
1.0%
1.649 1
 
1.0%
1.66 1
 
1.0%
1.663 1
 
1.0%
1.667 2
 
2.0%
1.678 2
 
2.0%
1.698 1
 
1.0%
1.7 2
 
2.0%
1.701 1
 
1.0%
ValueCountFrequency (%)
17.3 3
3.0%
17.2 3
3.0%
17.1 1
 
1.0%
9.756 2
2.0%
9.7 2
2.0%
9.664 1
 
1.0%
9.656 2
2.0%
9.64 1
 
1.0%
9.611 1
 
1.0%
9.567 3
3.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.54654
Minimum5.8
Maximum17.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:50.236301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.8
5-th percentile5.8
Q16.08325
median16.9
Q317.4
95-th percentile17.7
Maximum17.72
Range11.92
Interquartile range (IQR)11.31675

Descriptive statistics

Standard deviation5.4228627
Coefficient of variation (CV)0.43221977
Kurtosis-1.9255187
Mean12.54654
Median Absolute Deviation (MAD)0.8
Skewness-0.26872274
Sum1254.654
Variance29.40744
MonotonicityNot monotonic
2023-12-10T22:15:50.487733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
5.8 13
 
13.0%
6.0 10
 
10.0%
7.5 7
 
7.0%
17.7 7
 
7.0%
17.4 6
 
6.0%
16.9 6
 
6.0%
17.3 5
 
5.0%
17.5 5
 
5.0%
17.6 4
 
4.0%
17.2 4
 
4.0%
Other values (24) 33
33.0%
ValueCountFrequency (%)
5.8 13
13.0%
5.88 1
 
1.0%
6.0 10
10.0%
6.033 1
 
1.0%
6.1 1
 
1.0%
6.2 3
 
3.0%
7.5 7
7.0%
7.597 1
 
1.0%
7.6 3
 
3.0%
7.67 1
 
1.0%
ValueCountFrequency (%)
17.72 1
 
1.0%
17.7 7
7.0%
17.62 1
 
1.0%
17.607 1
 
1.0%
17.6 4
4.0%
17.5 5
5.0%
17.42 1
 
1.0%
17.4 6
6.0%
17.32 1
 
1.0%
17.3 5
5.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.2926
Minimum25.98
Maximum26.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:50.721517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.98
5-th percentile26.01
Q126.16
median26.275
Q326.44
95-th percentile26.55
Maximum26.56
Range0.58
Interquartile range (IQR)0.28

Descriptive statistics

Standard deviation0.18004837
Coefficient of variation (CV)0.0068478723
Kurtosis-1.3304125
Mean26.2926
Median Absolute Deviation (MAD)0.155
Skewness-0.09213953
Sum2629.26
Variance0.032417414
MonotonicityNot monotonic
2023-12-10T22:15:50.924223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
26.43 14
 
14.0%
26.44 12
 
12.0%
26.54 8
 
8.0%
26.16 6
 
6.0%
26.12 6
 
6.0%
26.55 4
 
4.0%
26.08 4
 
4.0%
26.56 3
 
3.0%
26.05 3
 
3.0%
26.45 3
 
3.0%
Other values (20) 37
37.0%
ValueCountFrequency (%)
25.98 2
 
2.0%
26.0 1
 
1.0%
26.01 3
3.0%
26.02 2
 
2.0%
26.03 2
 
2.0%
26.04 1
 
1.0%
26.05 3
3.0%
26.08 4
4.0%
26.12 6
6.0%
26.16 6
6.0%
ValueCountFrequency (%)
26.56 3
 
3.0%
26.55 4
 
4.0%
26.54 8
8.0%
26.45 3
 
3.0%
26.44 12
12.0%
26.43 14
14.0%
26.3 2
 
2.0%
26.29 1
 
1.0%
26.28 3
 
3.0%
26.27 2
 
2.0%

Interactions

2023-12-10T22:15:45.547057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:40.382065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.309503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.269901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:43.225772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.608244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.688513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:40.569078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.447920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.421603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:43.399812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.801570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.815100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:40.713556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.579646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.544447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:43.558505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.945773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.998337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:40.860334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.745059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.677946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.142726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.097953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:46.173589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.009331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.984550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.900391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.311434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.251533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:46.343753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:41.166495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:42.128773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:43.054818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.471266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.408180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:15:51.090139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9220.9220.7961.0000.922
강우량(mm)0.9221.0000.9950.8081.0000.997
유입량(ms)0.9220.9951.0000.8201.0000.998
방류량(ms)0.7960.8080.8201.0000.9750.787
저수량(백만m3)1.0001.0001.0000.9751.0001.000
저수율0.9220.9970.9980.7871.0001.000
2023-12-10T22:15:51.343497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.997-0.9880.0410.485-0.997
강우량(mm)-0.9971.0000.991-0.008-0.4881.000
유입량(ms)-0.9880.9911.000-0.011-0.5090.991
방류량(ms)0.041-0.008-0.0111.0000.225-0.008
저수량(백만m3)0.485-0.488-0.5090.2251.000-0.488
저수율-0.9971.0000.991-0.008-0.4881.000

Missing values

2023-12-10T22:15:46.593086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:15:46.826736image/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
0군남20190509183004.2315.91.67817.426.18
1군남20190508124004.7866.77.6447.726.56
2군남20190509235003.9545.50.016.825.98
3군남20190509184004.2315.99.56717.426.18
4군남20190509152004.3736.11.717.726.28
5군남20190508125004.7716.70.07.6726.55
6군남20190509030004.6076.45.7786.026.44
7군남20190509240003.9545.50.016.82725.98
8군남20190509212004.0915.70.017.126.08
9군남20190509185004.2175.99.56717.426.17
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남20190509200004.2035.917.317.326.16
91군남20190509195004.2035.917.317.326.16
92군남20190509193004.2035.99.47317.326.16
93군남20190509192004.2035.99.50717.326.16
94군남20190509182004.2315.90.017.426.18
95군남20190509181004.2455.91.71817.426.19
96군남20190509175004.2736.09.61117.526.21
97군남20190509174004.2736.01.66717.526.21
98군남20190508122004.7866.77.6447.726.56
99군남20190508123004.7866.77.6447.726.56