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
강우량(mm) is highly overall correlated with 유입량(ms) and 2 other fieldsHigh correlation
유입량(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 2 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:25:51.915702
Analysis finished2023-12-10 10:25:58.382442
Duration6.47 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

2023-12-10T19:25:58.484960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:58.640724image/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%
Mean2.0210223 × 109
Minimum2.0210219 × 109
Maximum2.0210228 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:58.815697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210219 × 109
5-th percentile2.0210219 × 109
Q12.021022 × 109
median2.0210221 × 109
Q32.0210227 × 109
95-th percentile2.0210228 × 109
Maximum2.0210228 × 109
Range923
Interquartile range (IQR)721.5

Descriptive statistics

Standard deviation393.82089
Coefficient of variation (CV)1.9486222 × 10-7
Kurtosis-1.8536686
Mean2.0210223 × 109
Median Absolute Deviation (MAD)194
Skewness0.29166219
Sum2.0210223 × 1011
Variance155094.89
MonotonicityNot monotonic
2023-12-10T19:25:59.063820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021022820 1
 
1.0%
2021022107 1
 
1.0%
2021022012 1
 
1.0%
2021022015 1
 
1.0%
2021022016 1
 
1.0%
2021022018 1
 
1.0%
2021022019 1
 
1.0%
2021022023 1
 
1.0%
2021022024 1
 
1.0%
2021022102 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2021021901 1
1.0%
2021021902 1
1.0%
2021021903 1
1.0%
2021021904 1
1.0%
2021021905 1
1.0%
2021021906 1
1.0%
2021021907 1
1.0%
2021021908 1
1.0%
2021021909 1
1.0%
2021021910 1
1.0%
ValueCountFrequency (%)
2021022824 1
1.0%
2021022823 1
1.0%
2021022822 1
1.0%
2021022821 1
1.0%
2021022820 1
1.0%
2021022819 1
1.0%
2021022818 1
1.0%
2021022817 1
1.0%
2021022816 1
1.0%
2021022815 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

2023-12-10T19:25:59.261395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:59.442169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.94062
Minimum3.739
Maximum4.105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:59.610000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.739
5-th percentile3.81765
Q13.872
median3.899
Q34.049
95-th percentile4.105
Maximum4.105
Range0.366
Interquartile range (IQR)0.177

Descriptive statistics

Standard deviation0.10229752
Coefficient of variation (CV)0.025959754
Kurtosis-1.0213397
Mean3.94062
Median Absolute Deviation (MAD)0.0475
Skewness0.38169974
Sum394.062
Variance0.010464783
MonotonicityNot monotonic
2023-12-10T19:25:59.840689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3.886 18
18.0%
3.899 12
12.0%
4.105 12
12.0%
4.077 7
 
7.0%
3.926 6
 
6.0%
3.845 6
 
6.0%
3.872 5
 
5.0%
3.859 5
 
5.0%
4.036 5
 
5.0%
3.832 4
 
4.0%
Other values (13) 20
20.0%
ValueCountFrequency (%)
3.739 2
 
2.0%
3.752 1
 
1.0%
3.779 1
 
1.0%
3.792 1
 
1.0%
3.819 1
 
1.0%
3.832 4
 
4.0%
3.845 6
 
6.0%
3.859 5
 
5.0%
3.872 5
 
5.0%
3.886 18
18.0%
ValueCountFrequency (%)
4.105 12
12.0%
4.091 2
 
2.0%
4.077 7
7.0%
4.063 3
 
3.0%
4.049 2
 
2.0%
4.036 5
5.0%
4.008 1
 
1.0%
3.981 1
 
1.0%
3.954 1
 
1.0%
3.94 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.506
Minimum5.2
Maximum5.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:00.070379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.2
5-th percentile5.3
Q15.4
median5.5
Q35.7
95-th percentile5.7
Maximum5.7
Range0.5
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.13767184
Coefficient of variation (CV)0.025003966
Kurtosis-0.88600309
Mean5.506
Median Absolute Deviation (MAD)0.1
Skewness0.15090483
Sum550.6
Variance0.018953535
MonotonicityNot monotonic
2023-12-10T19:26:00.264652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5.4 38
38.0%
5.7 26
26.0%
5.5 23
23.0%
5.6 7
 
7.0%
5.3 3
 
3.0%
5.2 3
 
3.0%
ValueCountFrequency (%)
5.2 3
 
3.0%
5.3 3
 
3.0%
5.4 38
38.0%
5.5 23
23.0%
5.6 7
 
7.0%
5.7 26
26.0%
ValueCountFrequency (%)
5.7 26
26.0%
5.6 7
 
7.0%
5.5 23
23.0%
5.4 38
38.0%
5.3 3
 
3.0%
5.2 3
 
3.0%

방류량(ms)
Real number (ℝ)

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.91359
Minimum6.978
Maximum15.867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:00.488066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.978
5-th percentile7.06995
Q110.025
median10.9
Q311.69
95-th percentile15.32895
Maximum15.867
Range8.889
Interquartile range (IQR)1.665

Descriptive statistics

Standard deviation2.4545664
Coefficient of variation (CV)0.22490916
Kurtosis-0.47783263
Mean10.91359
Median Absolute Deviation (MAD)0.81
Skewness0.12803577
Sum1091.359
Variance6.0248961
MonotonicityNot monotonic
2023-12-10T19:26:00.713465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
10.9 23
23.0%
11.1 15
15.0%
8.0 9
 
9.0%
13.3 4
 
4.0%
7.267 4
 
4.0%
11.778 3
 
3.0%
10.7 3
 
3.0%
6.978 2
 
2.0%
11.622 2
 
2.0%
14.933 2
 
2.0%
Other values (30) 33
33.0%
ValueCountFrequency (%)
6.978 2
2.0%
7.035 1
 
1.0%
7.05 2
2.0%
7.071 1
 
1.0%
7.15 1
 
1.0%
7.151 1
 
1.0%
7.163 1
 
1.0%
7.239 1
 
1.0%
7.267 4
4.0%
7.8 1
 
1.0%
ValueCountFrequency (%)
15.867 1
1.0%
15.84 1
1.0%
15.692 1
1.0%
15.611 1
1.0%
15.556 1
1.0%
15.317 1
1.0%
15.161 1
1.0%
14.958 1
1.0%
14.933 2
2.0%
14.65 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.12385
Minimum7.8
Maximum13.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:00.921549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.8
5-th percentile7.9
Q18
median10.9
Q311.1
95-th percentile11.10125
Maximum13.3
Range5.5
Interquartile range (IQR)3.1

Descriptive statistics

Standard deviation1.5072633
Coefficient of variation (CV)0.14888242
Kurtosis-0.81697363
Mean10.12385
Median Absolute Deviation (MAD)0.2
Skewness-0.4109848
Sum1012.385
Variance2.2718425
MonotonicityNot monotonic
2023-12-10T19:26:01.115722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
10.9 25
25.0%
11.1 22
22.0%
8.0 16
16.0%
10.7 6
 
6.0%
10.8 5
 
5.0%
7.9 5
 
5.0%
13.3 4
 
4.0%
7.8 3
 
3.0%
10.757 1
 
1.0%
10.885 1
 
1.0%
Other values (12) 12
12.0%
ValueCountFrequency (%)
7.8 3
 
3.0%
7.857 1
 
1.0%
7.9 5
 
5.0%
7.934 1
 
1.0%
7.948 1
 
1.0%
8.0 16
16.0%
8.053 1
 
1.0%
8.173 1
 
1.0%
8.2 1
 
1.0%
9.215 1
 
1.0%
ValueCountFrequency (%)
13.3 4
 
4.0%
11.125 1
 
1.0%
11.1 22
22.0%
10.9 25
25.0%
10.885 1
 
1.0%
10.873 1
 
1.0%
10.812 1
 
1.0%
10.8 5
 
5.0%
10.793 1
 
1.0%
10.76 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.97
Minimum25.82
Maximum26.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:01.367987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.82
5-th percentile25.879
Q125.92
median25.94
Q326.05
95-th percentile26.09
Maximum26.09
Range0.27
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.075062264
Coefficient of variation (CV)0.0028903452
Kurtosis-1.0095363
Mean25.97
Median Absolute Deviation (MAD)0.035
Skewness0.36278705
Sum2597
Variance0.0056343434
MonotonicityNot monotonic
2023-12-10T19:26:01.581376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
25.93 18
18.0%
25.94 12
12.0%
26.09 12
12.0%
26.07 7
 
7.0%
25.96 6
 
6.0%
25.9 6
 
6.0%
25.92 5
 
5.0%
25.91 5
 
5.0%
26.04 5
 
5.0%
25.89 4
 
4.0%
Other values (13) 20
20.0%
ValueCountFrequency (%)
25.82 2
 
2.0%
25.83 1
 
1.0%
25.85 1
 
1.0%
25.86 1
 
1.0%
25.88 1
 
1.0%
25.89 4
 
4.0%
25.9 6
 
6.0%
25.91 5
 
5.0%
25.92 5
 
5.0%
25.93 18
18.0%
ValueCountFrequency (%)
26.09 12
12.0%
26.08 2
 
2.0%
26.07 7
7.0%
26.06 3
 
3.0%
26.05 2
 
2.0%
26.04 5
5.0%
26.02 1
 
1.0%
26.0 1
 
1.0%
25.98 1
 
1.0%
25.97 2
 
2.0%

Interactions

2023-12-10T19:25:56.971735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.294119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.106866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.028571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.859851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.718168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:57.128021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.423012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.273223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.177241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.984874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.866585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:57.300143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.572197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.436412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.331533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.128943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:56.011628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:57.447150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.709520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.579434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.477720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.269032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:56.176459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:57.586309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.836632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.723541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.614676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.403509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:56.303986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:57.728625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:52.966118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:53.879636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:54.749751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:55.541093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:56.824474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:26:01.725282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8860.7150.7270.9500.886
강우량(mm)0.8861.0000.9380.6100.8651.000
유입량(ms)0.7150.9381.0000.5410.6440.938
방류량(ms)0.7270.6100.5411.0000.9100.610
저수량(백만m3)0.9500.8650.6440.9101.0000.865
저수율0.8861.0000.9380.6100.8651.000
2023-12-10T19:26:01.947320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.242-0.224-0.3190.424-0.242
강우량(mm)-0.2421.0000.9620.2970.6171.000
유입량(ms)-0.2240.9621.0000.2910.6140.962
방류량(ms)-0.3190.2970.2911.0000.0150.297
저수량(백만m3)0.4240.6170.6140.0151.0000.617
저수율-0.2421.0000.9620.2970.6171.000

Missing values

2023-12-10T19:25:57.997850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:25:58.299674image/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
0군남202102282003.8725.410.810.825.92
1군남202102270903.8995.514.6510.925.94
2군남202102200404.0365.615.6928.05326.04
3군남202102282103.8595.47.0510.825.91
4군남202102280103.8455.410.710.725.9
5군남202102271003.8995.510.910.925.94
6군남202102202004.0775.77.26711.126.07
7군남202102200504.0635.715.848.17326.06
8군남202102191303.8995.511.758.025.94
9군남202102282203.8455.47.07110.79325.9
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202102190503.7925.311.5517.85725.86
91군남202102190403.7795.315.1617.825.85
92군남202102190203.7395.27.87.825.82
93군남202102190103.7395.27.9347.93425.82
94군남202102281903.8725.47.16310.88525.92
95군남202102281803.8865.410.910.925.93
96군남202102281603.8865.410.910.925.93
97군남202102281503.8865.410.910.925.93
98군남202102270703.8865.410.910.925.93
99군남202102270803.8865.410.910.925.93