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) 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 10:24:24.809843
Analysis finished2023-12-10 10:24:30.708688
Duration5.9 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

2023-12-10T19:24:30.811495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:24:30.964688image/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%
Mean2.0211026 × 109
Minimum2.021102 × 109
Maximum2.0211031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:31.147773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.021102 × 109
5-th percentile2.021102 × 109
Q12.0211021 × 109
median2.0211029 × 109
Q32.021103 × 109
95-th percentile2.0211031 × 109
Maximum2.0211031 × 109
Range1118
Interquartile range (IQR)916.5

Descriptive statistics

Standard deviation486.87732
Coefficient of variation (CV)2.4089688 × 10-7
Kurtosis-1.9035481
Mean2.0211026 × 109
Median Absolute Deviation (MAD)195
Skewness-0.26519541
Sum2.0211026 × 1011
Variance237049.52
MonotonicityNot monotonic
2023-12-10T19:24:31.472059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021103105 1
 
1.0%
2021102121 1
 
1.0%
2021102102 1
 
1.0%
2021102105 1
 
1.0%
2021102106 1
 
1.0%
2021102108 1
 
1.0%
2021102109 1
 
1.0%
2021102113 1
 
1.0%
2021102114 1
 
1.0%
2021102116 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2021102006 1
1.0%
2021102007 1
1.0%
2021102008 1
1.0%
2021102009 1
1.0%
2021102010 1
1.0%
2021102011 1
1.0%
2021102012 1
1.0%
2021102013 1
1.0%
2021102014 1
1.0%
2021102015 1
1.0%
ValueCountFrequency (%)
2021103124 1
1.0%
2021103123 1
1.0%
2021103122 1
1.0%
2021103121 1
1.0%
2021103120 1
1.0%
2021103119 1
1.0%
2021103118 1
1.0%
2021103117 1
1.0%
2021103116 1
1.0%
2021103115 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5324
Minimum23.39
Maximum23.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:31.739503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.39
5-th percentile23.39
Q123.39
median23.4
Q323.7
95-th percentile23.77
Maximum23.79
Range0.4
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.16464151
Coefficient of variation (CV)0.0069963758
Kurtosis-1.8273718
Mean23.5324
Median Absolute Deviation (MAD)0.01
Skewness0.34912871
Sum2353.24
Variance0.027106828
MonotonicityNot monotonic
2023-12-10T19:24:31.949863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
23.39 48
48.0%
23.7 11
 
11.0%
23.4 9
 
9.0%
23.76 4
 
4.0%
23.77 3
 
3.0%
23.69 3
 
3.0%
23.71 3
 
3.0%
23.68 3
 
3.0%
23.67 2
 
2.0%
23.72 2
 
2.0%
Other values (8) 12
 
12.0%
ValueCountFrequency (%)
23.39 48
48.0%
23.4 9
 
9.0%
23.66 2
 
2.0%
23.67 2
 
2.0%
23.68 3
 
3.0%
23.69 3
 
3.0%
23.7 11
 
11.0%
23.71 3
 
3.0%
23.72 2
 
2.0%
23.73 2
 
2.0%
ValueCountFrequency (%)
23.79 1
 
1.0%
23.786 1
 
1.0%
23.78 1
 
1.0%
23.77 3
3.0%
23.76 4
4.0%
23.75 2
2.0%
23.74 2
2.0%
23.734 1
 
1.0%
23.73 2
2.0%
23.72 2
2.0%

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

2023-12-10T19:24:32.209709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:24:32.372663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.75142
Minimum21.622
Maximum91.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:32.560351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.622
5-th percentile27.3
Q127.3
median28
Q377
95-th percentile87.3344
Maximum91.46
Range69.838
Interquartile range (IQR)49.7

Descriptive statistics

Standard deviation26.335755
Coefficient of variation (CV)0.5293468
Kurtosis-1.8084478
Mean49.75142
Median Absolute Deviation (MAD)0.7
Skewness0.35796024
Sum4975.142
Variance693.57199
MonotonicityNot monotonic
2023-12-10T19:24:32.816719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
27.3 47
47.0%
77.0 10
 
10.0%
28.0 8
 
8.0%
86.8 3
 
3.0%
78.4 2
 
2.0%
88.9 2
 
2.0%
72.8 2
 
2.0%
74.9 2
 
2.0%
82.982 1
 
1.0%
68.6 1
 
1.0%
Other values (22) 22
22.0%
ValueCountFrequency (%)
21.622 1
 
1.0%
25.641 1
 
1.0%
27.3 47
47.0%
28.0 8
 
8.0%
67.731 1
 
1.0%
68.6 1
 
1.0%
69.68 1
 
1.0%
70.7 1
 
1.0%
71.71 1
 
1.0%
72.8 2
 
2.0%
ValueCountFrequency (%)
91.46 1
 
1.0%
90.911 1
 
1.0%
88.934 1
 
1.0%
88.9 2
2.0%
87.252 1
 
1.0%
86.8 3
3.0%
85.4 1
 
1.0%
84.662 1
 
1.0%
84.0 1
 
1.0%
83.495 1
 
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.08866
Minimum21.622
Maximum93.217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:33.055982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.622
5-th percentile27.3
Q127.3
median28
Q377
95-th percentile88.9
Maximum93.217
Range71.595
Interquartile range (IQR)49.7

Descriptive statistics

Standard deviation26.691712
Coefficient of variation (CV)0.53288932
Kurtosis-1.8040873
Mean50.08866
Median Absolute Deviation (MAD)0.7
Skewness0.35957436
Sum5008.866
Variance712.4475
MonotonicityNot monotonic
2023-12-10T19:24:33.319399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
27.3 47
47.0%
77.0 10
 
10.0%
28.0 8
 
8.0%
86.8 3
 
3.0%
78.4 2
 
2.0%
88.9 2
 
2.0%
72.8 2
 
2.0%
74.9 2
 
2.0%
85.26 1
 
1.0%
68.6 1
 
1.0%
Other values (22) 22
22.0%
ValueCountFrequency (%)
21.622 1
 
1.0%
27.3 47
47.0%
27.697 1
 
1.0%
28.0 8
 
8.0%
68.6 1
 
1.0%
69.953 1
 
1.0%
70.7 1
 
1.0%
71.902 1
 
1.0%
72.8 2
 
2.0%
73.932 1
 
1.0%
ValueCountFrequency (%)
93.217 1
 
1.0%
92.377 1
 
1.0%
90.323 1
 
1.0%
89.53 1
 
1.0%
88.9 2
2.0%
86.94 1
 
1.0%
86.8 3
3.0%
85.773 1
 
1.0%
85.4 1
 
1.0%
85.26 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.36233
Minimum1.252
Maximum1.565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:24:33.618246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.252
5-th percentile1.252
Q11.252
median1.26
Q31.491
95-th percentile1.549
Maximum1.565
Range0.313
Interquartile range (IQR)0.239

Descriptive statistics

Standard deviation0.12766687
Coefficient of variation (CV)0.093712147
Kurtosis-1.8120473
Mean1.36233
Median Absolute Deviation (MAD)0.008
Skewness0.35629918
Sum136.233
Variance0.016298829
MonotonicityNot monotonic
2023-12-10T19:24:33.899700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1.252 48
48.0%
1.491 11
 
11.0%
1.26 9
 
9.0%
1.54 4
 
4.0%
1.549 3
 
3.0%
1.483 3
 
3.0%
1.5 3
 
3.0%
1.475 3
 
3.0%
1.467 2
 
2.0%
1.508 2
 
2.0%
Other values (8) 12
 
12.0%
ValueCountFrequency (%)
1.252 48
48.0%
1.26 9
 
9.0%
1.459 2
 
2.0%
1.467 2
 
2.0%
1.475 3
 
3.0%
1.483 3
 
3.0%
1.491 11
 
11.0%
1.5 3
 
3.0%
1.508 2
 
2.0%
1.516 2
 
2.0%
ValueCountFrequency (%)
1.565 1
 
1.0%
1.562 1
 
1.0%
1.557 1
 
1.0%
1.549 3
3.0%
1.54 4
4.0%
1.532 2
2.0%
1.524 2
2.0%
1.519 1
 
1.0%
1.516 2
2.0%
1.508 2
2.0%

저수율
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1.8
57 
2.1
31 
2.2
10 
2.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.8
2nd row1.8
3rd row2.1
4th row1.8
5th row1.8

Common Values

ValueCountFrequency (%)
1.8 57
57.0%
2.1 31
31.0%
2.2 10
 
10.0%
2.0 2
 
2.0%

Length

2023-12-10T19:24:34.147437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:24:34.315706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.8 57
57.0%
2.1 31
31.0%
2.2 10
 
10.0%
2.0 2
 
2.0%

Interactions

2023-12-10T19:24:29.488811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:25.352063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:26.496123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:27.450142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:28.700341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.632998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:25.591622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:26.660668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:27.658706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:28.856625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.818645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:25.871486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:26.900239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:28.214898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.033147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.987306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:26.063514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:27.117265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:28.375227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.179780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:30.161472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:26.286688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:27.284816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:28.552236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:24:29.337969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:24:34.445386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.7190.7400.7370.7600.926
저수위(m)0.7191.0000.9980.9970.9931.000
유입량(ms)0.7400.9981.0000.9900.9940.908
방류량(ms)0.7370.9970.9901.0000.9980.923
저수량(백만m3)0.7600.9930.9940.9981.0000.900
저수율0.9261.0000.9080.9230.9001.000
2023-12-10T19:24:34.639108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.942-0.912-0.927-0.9420.641
저수위(m)-0.9421.0000.9770.9771.0000.995
유입량(ms)-0.9120.9771.0000.9840.9770.909
방류량(ms)-0.9270.9770.9841.0000.9770.931
저수량(백만m3)-0.9421.0000.9770.9771.0000.898
저수율0.6410.9950.9090.9310.8981.000

Missing values

2023-12-10T19:24:30.385439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:24:30.614298image/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
0군남202110310523.39027.327.31.2521.8
1군남202110291823.4021.62221.6221.261.8
2군남202110201823.74082.98285.261.5242.1
3군남202110310623.39027.327.31.2521.8
4군남202110301023.39027.327.31.2521.8
5군남202110291923.4028.028.01.261.8
6군남202110211023.7077.077.01.4912.1
7군남202110201923.74084.084.01.5242.1
8군남202110312223.39027.327.31.2521.8
9군남202110310723.39027.327.31.2521.8
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202110311423.39027.327.31.2521.8
91군남202110311323.39027.327.31.2521.8
92군남202110311123.39027.327.31.2521.8
93군남202110311023.39027.327.31.2521.8
94군남202110310423.39027.327.31.2521.8
95군남202110310323.39027.327.31.2521.8
96군남202110310123.39027.327.31.2521.8
97군남202110302423.39027.327.31.2521.8
98군남202110291623.4028.028.01.261.8
99군남202110291723.4028.028.01.261.8