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

강우량(mm) has constant value ""Constant
저수위(m) is highly overall correlated with 방류량(ms) and 1 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 방류량(ms) and 2 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수위(m) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 유입량(ms) and 3 other fieldsHigh correlation
저수율 is highly overall correlated with 저수량(백만m3) and 1 other fieldsHigh correlation
댐이름 is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
유입량(ms) has 19 (19.0%) zerosZeros
방류량(ms) has 17 (17.0%) zerosZeros
저수량(백만m3) has 17 (17.0%) zerosZeros
저수율 has 21 (21.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:49:58.594256
Analysis finished2023-12-10 12:50:01.490473
Duration2.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자/시간(t)
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2022120101
23 
2022120102
23 
2022120103
23 
2022120104
23 
2022120105
8 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022120101
2nd row2022120101
3rd row2022120101
4th row2022120101
5th row2022120101

Common Values

ValueCountFrequency (%)
2022120101 23
23.0%
2022120102 23
23.0%
2022120103 23
23.0%
2022120104 23
23.0%
2022120105 8
 
8.0%

Length

2023-12-10T21:50:01.556597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:50:01.675066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022120101 23
23.0%
2022120102 23
23.0%
2022120103 23
23.0%
2022120104 23
23.0%
2022120105 8
 
8.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.312051
Minimum1.57
Maximum156.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:50:01.826820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.57
5-th percentile2.84165
Q16.98975
median28.04
Q347.53025
95-th percentile135.7903
Maximum156.75
Range155.18
Interquartile range (IQR)40.5405

Descriptive statistics

Standard deviation40.84194
Coefficient of variation (CV)1.0660338
Kurtosis1.9638015
Mean38.312051
Median Absolute Deviation (MAD)19.492
Skewness1.5957589
Sum3831.2051
Variance1668.064
MonotonicityNot monotonic
2023-12-10T21:50:02.061291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.4 5
 
5.0%
47.07 5
 
5.0%
33.12 4
 
4.0%
1.57 4
 
4.0%
77.57 4
 
4.0%
156.75 3
 
3.0%
18.5 3
 
3.0%
30.64 2
 
2.0%
8.57 2
 
2.0%
38.09 2
 
2.0%
Other values (60) 66
66.0%
ValueCountFrequency (%)
1.57 4
4.0%
2.835 1
 
1.0%
2.842 1
 
1.0%
2.844 1
 
1.0%
2.848 1
 
1.0%
2.854 1
 
1.0%
3.55 1
 
1.0%
3.58 2
2.0%
3.59 1
 
1.0%
3.735 1
 
1.0%
ValueCountFrequency (%)
156.75 3
3.0%
156.74 1
 
1.0%
135.796 1
 
1.0%
135.79 1
 
1.0%
135.786 1
 
1.0%
135.78 1
 
1.0%
135.771 1
 
1.0%
83.3058 1
 
1.0%
83.3054 1
 
1.0%
83.3052 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

2023-12-10T21:50:02.219261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:50:02.318819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.580268
Minimum0
Maximum246.792
Zeros19
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:50:02.430702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.807
median56.2895
Q393.09075
95-th percentile134.98255
Maximum246.792
Range246.792
Interquartile range (IQR)83.28375

Descriptive statistics

Standard deviation52.792581
Coefficient of variation (CV)0.90120074
Kurtosis2.171838
Mean58.580268
Median Absolute Deviation (MAD)42.163
Skewness1.1932633
Sum5858.0268
Variance2787.0566
MonotonicityNot monotonic
2023-12-10T21:50:02.573504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 19
 
19.0%
60.423 4
 
4.0%
3.755 3
 
3.0%
104.315 1
 
1.0%
233.268 1
 
1.0%
87.488 1
 
1.0%
80.879 1
 
1.0%
19.663 1
 
1.0%
106.005 1
 
1.0%
51.994 1
 
1.0%
Other values (67) 67
67.0%
ValueCountFrequency (%)
0.0 19
19.0%
0.123 1
 
1.0%
3.755 3
 
3.0%
5.768 1
 
1.0%
8.199 1
 
1.0%
10.343 1
 
1.0%
11.913 1
 
1.0%
13.085 1
 
1.0%
19.663 1
 
1.0%
19.667 1
 
1.0%
ValueCountFrequency (%)
246.792 1
1.0%
234.619 1
1.0%
233.268 1
1.0%
167.915 1
1.0%
141.225 1
1.0%
134.654 1
1.0%
123.951 1
1.0%
121.422 1
1.0%
120.504 1
1.0%
119.439 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.939643
Minimum0
Maximum224.153
Zeros17
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:50:02.724351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.755
median60.423
Q399.688
95-th percentile159.1984
Maximum224.153
Range224.153
Interquartile range (IQR)95.933

Descriptive statistics

Standard deviation54.514966
Coefficient of variation (CV)0.86614672
Kurtosis1.0563858
Mean62.939643
Median Absolute Deviation (MAD)42.374
Skewness0.92701924
Sum6293.9643
Variance2971.8815
MonotonicityNot monotonic
2023-12-10T21:50:02.858825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
17.0%
0.33 5
 
5.0%
60.423 4
 
4.0%
3.755 3
 
3.0%
222.955 1
 
1.0%
33.1 1
 
1.0%
216.296 1
 
1.0%
87.488 1
 
1.0%
99.685 1
 
1.0%
52.949 1
 
1.0%
Other values (65) 65
65.0%
ValueCountFrequency (%)
0.0 17
17.0%
0.33 5
 
5.0%
3.401 1
 
1.0%
3.755 3
 
3.0%
12.99 1
 
1.0%
13.085 1
 
1.0%
13.121 1
 
1.0%
13.199 1
 
1.0%
33.1 1
 
1.0%
35.973 1
 
1.0%
ValueCountFrequency (%)
224.153 1
1.0%
223.313 1
1.0%
222.955 1
1.0%
216.296 1
1.0%
179.308 1
1.0%
158.14 1
1.0%
153.857 1
1.0%
129.832 1
1.0%
126.838 1
1.0%
125.918 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.690227
Minimum0
Maximum98.4074
Zeros17
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:50:03.281626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.817125
median14.5875
Q351.2735
95-th percentile76.5864
Maximum98.4074
Range98.4074
Interquartile range (IQR)49.456375

Descriptive statistics

Standard deviation27.765018
Coefficient of variation (CV)1.0807619
Kurtosis-0.0075992559
Mean25.690227
Median Absolute Deviation (MAD)14.5875
Skewness1.003625
Sum2569.0227
Variance770.89624
MonotonicityNot monotonic
2023-12-10T21:50:03.410461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 17
 
17.0%
27.6961 5
 
5.0%
11.7869 4
 
4.0%
16.505 4
 
4.0%
3.8517 3
 
3.0%
76.5864 3
 
3.0%
53.6874 2
 
2.0%
0.916 2
 
2.0%
39.2301 2
 
2.0%
0.9759 2
 
2.0%
Other values (51) 56
56.0%
ValueCountFrequency (%)
0.0 17
17.0%
0.903 1
 
1.0%
0.916 2
 
2.0%
0.921 1
 
1.0%
0.9757 1
 
1.0%
0.9759 2
 
2.0%
0.976 1
 
1.0%
2.0975 1
 
1.0%
2.0999 1
 
1.0%
2.1014 1
 
1.0%
ValueCountFrequency (%)
98.4074 1
 
1.0%
98.3259 1
 
1.0%
98.0002 1
 
1.0%
97.9391 1
 
1.0%
76.5864 3
3.0%
76.4399 1
 
1.0%
63.4342 1
 
1.0%
63.3171 2
2.0%
63.2 2
2.0%
57.5319 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.257
Minimum0
Maximum159.7
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:50:03.551257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.725
median83.4
Q3100.95
95-th percentile107.805
Maximum159.7
Range159.7
Interquartile range (IQR)90.225

Descriptive statistics

Standard deviation46.968576
Coefficient of variation (CV)0.7197477
Kurtosis-1.0115691
Mean65.257
Median Absolute Deviation (MAD)20.55
Skewness-0.19995308
Sum6525.7
Variance2206.0471
MonotonicityNot monotonic
2023-12-10T21:50:03.708683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
21.0%
101.1 5
 
5.0%
104.6 4
 
4.0%
17.3 4
 
4.0%
101.6 4
 
4.0%
13.5 4
 
4.0%
2.4 4
 
4.0%
82.9 3
 
3.0%
104.7 2
 
2.0%
74.5 2
 
2.0%
Other values (41) 47
47.0%
ValueCountFrequency (%)
0.0 21
21.0%
2.4 4
 
4.0%
13.5 4
 
4.0%
17.3 4
 
4.0%
62.6 1
 
1.0%
62.7 1
 
1.0%
62.8 1
 
1.0%
62.9 1
 
1.0%
63.0 1
 
1.0%
72.7 1
 
1.0%
ValueCountFrequency (%)
159.7 1
 
1.0%
159.6 1
 
1.0%
159.5 1
 
1.0%
159.4 1
 
1.0%
159.2 1
 
1.0%
105.1 1
 
1.0%
104.7 2
2.0%
104.6 4
4.0%
104.5 1
 
1.0%
104.2 1
 
1.0%

댐이름
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
구담보
 
5
단양수중보
 
5
상주보
 
5
승촌보
 
5
달성보
 
5
Other values (18)
75 

Length

Max length7
Median length3
Mean length3.5
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여주보
2nd row강천보
3rd row백제보
4th row단양수중보
5th row귤현보

Common Values

ValueCountFrequency (%)
구담보 5
 
5.0%
단양수중보 5
 
5.0%
상주보 5
 
5.0%
승촌보 5
 
5.0%
달성보 5
 
5.0%
강천보 5
 
5.0%
칠곡보 5
 
5.0%
백제보 5
 
5.0%
수하보 4
 
4.0%
귤현보 4
 
4.0%
Other values (13) 52
52.0%

Length

2023-12-10T21:50:03.882096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구담보 5
 
5.0%
상주보 5
 
5.0%
승촌보 5
 
5.0%
달성보 5
 
5.0%
강천보 5
 
5.0%
칠곡보 5
 
5.0%
백제보 5
 
5.0%
단양수중보 5
 
5.0%
죽산보 4
 
4.0%
세종보 4
 
4.0%
Other values (13) 52
52.0%

Interactions

2023-12-10T21:50:00.725273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:58.862575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.354957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.838814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.286252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.887396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:58.976580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.472613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.924043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.378010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.985507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.084088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.564744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.014097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.470279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:01.069942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.172719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.640966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.105365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.541739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:01.163192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.258136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:49:59.739573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.198310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:50:00.618803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:50:03.976661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
일자/시간(t)1.0000.0000.0000.0000.0000.0000.000
저수위(m)0.0001.0000.6560.5920.7980.7611.000
유입량(ms)0.0000.6561.0000.8240.8440.5660.914
방류량(ms)0.0000.5920.8241.0000.8120.7490.961
저수량(백만m3)0.0000.7980.8440.8121.0000.7271.000
저수율0.0000.7610.5660.7490.7271.0001.000
댐이름0.0001.0000.9140.9611.0001.0001.000
2023-12-10T21:50:04.082415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
댐이름일자/시간(t)
댐이름1.0000.000
일자/시간(t)0.0001.000
2023-12-10T21:50:04.174512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율일자/시간(t)댐이름
저수위(m)1.000-0.469-0.516-0.2290.2210.0000.915
유입량(ms)-0.4691.0000.8960.6190.4400.0000.620
방류량(ms)-0.5160.8961.0000.5910.4640.0000.746
저수량(백만m3)-0.2290.6190.5911.0000.5490.0000.915
저수율0.2210.4400.4640.5491.0000.0000.910
일자/시간(t)0.0000.0000.0000.0000.0001.0000.000
댐이름0.9150.6200.7460.9150.9100.0001.000

Missing values

2023-12-10T21:50:01.300208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:50:01.427101image/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

일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
0202212010133.120104.315104.31511.7869104.6여주보
1202212010138.098093.747103.1919.1715105.1강천보
220221201012.854047.63171.18715.226363.0백제보
32022120101135.78011.9130.3357.4206159.4단양수중보
420221201013.5908.19913.1990.9210.0귤현보
52022120101156.7503.7553.7553.8517101.6영주유사조절지
620221201017.012041.652373.5698.327692.8승촌보
7202212010128.020105.692116.9714.4313100.6이포보
8202212010118.5028.02768.74976.586482.9강정고령보
9202212010139.77025.79442.133.327696.1낙단보
일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
90202212010418.50108.7468.04676.586482.9강정고령보
9120221201043.5505.76812.990.9030.0귤현보
9220221201056.656035.568770.4027.821687.2승촌보
932022120105135.7900.00.3357.4902159.6단양수중보
94202212010538.08091.16299.9689.0901104.2강천보
95202212010547.07054.25954.25927.6961101.1상주보
96202212010560.400.00.00.00.0구담보
97202212010513.540103.255126.83853.687491.7달성보
9820221201052.835059.69770.00315.125662.6백제보
99202212010524.620120.50487.97663.434284.2칠곡보