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
강우량(mm) 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 4 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
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:24:36.068004
Analysis finished2023-12-10 10:24:43.228490
Duration7.16 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

2023-12-10T19:24:43.326546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:24:43.476899image/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%
Mean2.0211024 × 109
Minimum2.0211013 × 109
Maximum2.0211031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:43.653095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0211013 × 109
5-th percentile2.0211013 × 109
Q12.021102 × 109
median2.0211027 × 109
Q32.0211029 × 109
95-th percentile2.0211031 × 109
Maximum2.0211031 × 109
Range1821
Interquartile range (IQR)909

Descriptive statistics

Standard deviation651.19325
Coefficient of variation (CV)3.2219706 × 10-7
Kurtosis-1.196487
Mean2.0211024 × 109
Median Absolute Deviation (MAD)390
Skewness-0.58692738
Sum2.0211024 × 1011
Variance424052.65
MonotonicityNot monotonic
2023-12-10T19:24:44.001535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021102816 1
 
1.0%
2021102118 1
 
1.0%
2021103124 1
 
1.0%
2021102010 1
 
1.0%
2021102012 1
 
1.0%
2021102016 1
 
1.0%
2021102018 1
 
1.0%
2021102102 1
 
1.0%
2021102104 1
 
1.0%
2021102108 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2021101303 1
1.0%
2021101305 1
1.0%
2021101307 1
1.0%
2021101309 1
1.0%
2021101311 1
1.0%
2021101313 1
1.0%
2021101315 1
1.0%
2021101317 1
1.0%
2021101319 1
1.0%
2021101321 1
1.0%
ValueCountFrequency (%)
2021103124 1
1.0%
2021103122 1
1.0%
2021103120 1
1.0%
2021103118 1
1.0%
2021103116 1
1.0%
2021103114 1
1.0%
2021103112 1
1.0%
2021103110 1
1.0%
2021103108 1
1.0%
2021103106 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.74806
Minimum23.39
Maximum26.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:44.232883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.39
5-th percentile23.39
Q123.4
median23.42
Q323.76
95-th percentile25.79105
Maximum26.38
Range2.99
Interquartile range (IQR)0.36

Descriptive statistics

Standard deviation0.69641986
Coefficient of variation (CV)0.029325337
Kurtosis7.2832148
Mean23.74806
Median Absolute Deviation (MAD)0.03
Skewness2.816829
Sum2374.806
Variance0.48500062
MonotonicityNot monotonic
2023-12-10T19:24:44.438552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
23.39 24
24.0%
23.41 14
14.0%
23.4 10
 
10.0%
23.7 6
 
6.0%
23.42 6
 
6.0%
23.43 3
 
3.0%
23.84 2
 
2.0%
23.76 2
 
2.0%
23.68 2
 
2.0%
23.82 2
 
2.0%
Other values (28) 29
29.0%
ValueCountFrequency (%)
23.39 24
24.0%
23.4 10
10.0%
23.41 14
14.0%
23.42 6
 
6.0%
23.43 3
 
3.0%
23.66 1
 
1.0%
23.67 1
 
1.0%
23.68 2
 
2.0%
23.69 1
 
1.0%
23.7 6
 
6.0%
ValueCountFrequency (%)
26.38 1
1.0%
26.32 1
1.0%
26.296 1
1.0%
26.2 1
1.0%
26.058 1
1.0%
25.777 1
1.0%
25.475 1
1.0%
24.86 1
1.0%
24.624 1
1.0%
24.326 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

2023-12-10T19:24:44.696545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:24:44.872308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.08816
Minimum21.622
Maximum658.959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:45.074959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.622
5-th percentile27.3
Q127.639
median30.8
Q385.1965
95-th percentile540.90545
Maximum658.959
Range637.337
Interquartile range (IQR)57.5575

Descriptive statistics

Standard deviation141.78864
Coefficient of variation (CV)1.5231651
Kurtosis8.1828395
Mean93.08816
Median Absolute Deviation (MAD)3.5
Skewness3.0053662
Sum9308.816
Variance20104.018
MonotonicityNot monotonic
2023-12-10T19:24:45.322017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
27.3 24
24.0%
29.4 13
 
13.0%
28.0 9
 
9.0%
30.8 5
 
5.0%
77.0 5
 
5.0%
32.2 2
 
2.0%
99.4 2
 
2.0%
70.7 1
 
1.0%
98.642 1
 
1.0%
110.181 1
 
1.0%
Other values (37) 37
37.0%
ValueCountFrequency (%)
21.622 1
 
1.0%
27.3 24
24.0%
27.752 1
 
1.0%
28.0 9
 
9.0%
29.4 13
13.0%
29.545 1
 
1.0%
30.8 5
 
5.0%
32.2 2
 
2.0%
33.968 1
 
1.0%
68.6 1
 
1.0%
ValueCountFrequency (%)
658.959 1
1.0%
623.331 1
1.0%
615.253 1
1.0%
589.68 1
1.0%
566.431 1
1.0%
539.562 1
1.0%
424.951 1
1.0%
353.916 1
1.0%
201.054 1
1.0%
183.76 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.99791
Minimum21.622
Maximum611.197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:45.555094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.622
5-th percentile27.3
Q127.825
median30.8
Q386.835
95-th percentile491.60695
Maximum611.197
Range589.575
Interquartile range (IQR)59.01

Descriptive statistics

Standard deviation137.60994
Coefficient of variation (CV)1.47971
Kurtosis7.6982264
Mean92.99791
Median Absolute Deviation (MAD)3.5
Skewness2.9159907
Sum9299.791
Variance18936.495
MonotonicityNot monotonic
2023-12-10T19:24:45.796768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
27.3 24
24.0%
29.4 13
 
13.0%
28.0 9
 
9.0%
30.8 5
 
5.0%
77.0 5
 
5.0%
32.2 2
 
2.0%
99.4 2
 
2.0%
70.7 1
 
1.0%
100.975 1
 
1.0%
120.237 1
 
1.0%
Other values (37) 37
37.0%
ValueCountFrequency (%)
21.622 1
 
1.0%
27.3 24
24.0%
28.0 9
 
9.0%
29.4 13
13.0%
29.808 1
 
1.0%
30.8 5
 
5.0%
31.628 1
 
1.0%
31.885 1
 
1.0%
32.2 2
 
2.0%
68.6 1
 
1.0%
ValueCountFrequency (%)
611.197 1
1.0%
605.847 1
1.0%
590.153 1
1.0%
588.792 1
1.0%
572.812 1
1.0%
487.333 1
1.0%
453.442 1
1.0%
298.998 1
1.0%
251.368 1
1.0%
217.677 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.58765
Minimum1.252
Maximum4.518
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:46.035107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.252
5-th percentile1.252
Q11.26
median1.274
Q31.54
95-th percentile3.7009
Maximum4.518
Range3.266
Interquartile range (IQR)0.28

Descriptive statistics

Standard deviation0.73340609
Coefficient of variation (CV)0.46194444
Kurtosis8.7547983
Mean1.58765
Median Absolute Deviation (MAD)0.022
Skewness3.0882044
Sum158.765
Variance0.53788449
MonotonicityNot monotonic
2023-12-10T19:24:46.242469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1.252 24
24.0%
1.267 14
14.0%
1.26 10
 
10.0%
1.491 6
 
6.0%
1.274 6
 
6.0%
1.282 3
 
3.0%
1.607 2
 
2.0%
1.54 2
 
2.0%
1.475 2
 
2.0%
1.59 2
 
2.0%
Other values (28) 29
29.0%
ValueCountFrequency (%)
1.252 24
24.0%
1.26 10
10.0%
1.267 14
14.0%
1.274 6
 
6.0%
1.282 3
 
3.0%
1.459 1
 
1.0%
1.467 1
 
1.0%
1.475 2
 
2.0%
1.483 1
 
1.0%
1.491 6
 
6.0%
ValueCountFrequency (%)
4.518 1
1.0%
4.431 1
1.0%
4.396 1
1.0%
4.259 1
1.0%
4.06 1
1.0%
3.682 1
1.0%
3.298 1
1.0%
2.586 1
1.0%
2.338 1
1.0%
2.043 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.242
Minimum1.8
Maximum6.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:46.454113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile1.8
Q11.8
median1.8
Q32.2
95-th percentile5.13
Maximum6.3
Range4.5
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation1.0148573
Coefficient of variation (CV)0.45265714
Kurtosis8.8984914
Mean2.242
Median Absolute Deviation (MAD)0
Skewness3.1179223
Sum224.2
Variance1.0299354
MonotonicityNot monotonic
2023-12-10T19:24:46.644887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.8 57
57.0%
2.1 16
 
16.0%
2.2 11
 
11.0%
2.3 3
 
3.0%
2.5 1
 
1.0%
2.0 1
 
1.0%
6.2 1
 
1.0%
6.0 1
 
1.0%
4.6 1
 
1.0%
3.3 1
 
1.0%
Other values (7) 7
 
7.0%
ValueCountFrequency (%)
1.8 57
57.0%
2.0 1
 
1.0%
2.1 16
 
16.0%
2.2 11
 
11.0%
2.3 3
 
3.0%
2.5 1
 
1.0%
2.6 1
 
1.0%
2.9 1
 
1.0%
3.3 1
 
1.0%
3.6 1
 
1.0%
ValueCountFrequency (%)
6.3 1
1.0%
6.2 1
1.0%
6.1 1
1.0%
6.0 1
1.0%
5.7 1
1.0%
5.1 1
1.0%
4.6 1
1.0%
3.6 1
1.0%
3.3 1
1.0%
2.9 1
1.0%

Interactions

2023-12-10T19:24:41.985201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:36.360451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.581794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:38.989360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.968769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.995567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:42.152452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:36.566380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.743548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.158818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.144888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:41.170622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:42.297081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:36.779917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.883816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.360607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.333270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:41.334293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:42.462625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.041142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:38.031333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.516114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.511443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:41.516274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:42.603260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.254577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:38.246302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.662761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.678170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:41.692518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:42.764072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:37.432896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:38.472250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:39.827774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:40.836422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:41.842427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:24:46.783098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.6840.7720.6300.5830.426
저수위(m)0.6841.0000.9080.9500.9950.996
유입량(ms)0.7720.9081.0000.9700.9430.926
방류량(ms)0.6300.9500.9701.0000.9380.935
저수량(백만m3)0.5830.9950.9430.9381.0000.999
저수율0.4260.9960.9260.9350.9991.000
2023-12-10T19:24:46.962699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.989-0.982-0.985-0.989-0.899
저수위(m)-0.9891.0000.9930.9941.0000.908
유입량(ms)-0.9820.9931.0000.9960.9930.907
방류량(ms)-0.9850.9940.9961.0000.9940.907
저수량(백만m3)-0.9891.0000.9930.9941.0000.908
저수율-0.8990.9080.9070.9070.9081.000

Missing values

2023-12-10T19:24:42.937627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:24:43.148780image/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
0군남202110281623.41029.429.41.2671.8
1군남202110130324.860424.951251.3682.5863.6
2군남202110310823.39027.327.31.2521.8
3군남202110281823.41029.429.41.2671.8
4군남202110141123.82097.397.31.592.2
5군남202110130525.7770623.331453.4423.6825.1
6군남202110202023.734082.59283.9531.5192.1
7군남202110311023.39027.327.31.2521.8
8군남202110300223.39027.327.31.2521.8
9군남202110282023.41029.429.41.2671.8
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202110291023.4028.028.01.261.8
91군남202110290823.4028.028.01.261.8
92군남202110290423.41029.429.41.2671.8
93군남202110290223.41029.429.41.2671.8
94군남202110281423.41029.429.41.2671.8
95군남202110281223.41029.429.41.2671.8
96군남202110280823.41029.429.41.2671.8
97군남202110280623.41029.429.41.2671.8
98군남202110270823.42030.830.81.2741.8
99군남202110271023.42030.830.81.2741.8