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
저수율 has constant value ""Constant
저수위(m) is highly overall correlated with 유입량(ms) and 2 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 저수위(m) and 2 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수위(m) and 2 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 저수위(m) and 2 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:22:47.750387
Analysis finished2023-12-10 10:22:51.752613
Duration4 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

2023-12-10T19:22:52.192760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:52.332856image/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%
Mean2.0221107 × 109
Minimum2.0221101 × 109
Maximum2.0221111 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:52.491736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0221101 × 109
5-th percentile2.0221101 × 109
Q12.0221102 × 109
median2.0221107 × 109
Q32.022111 × 109
95-th percentile2.0221111 × 109
Maximum2.0221111 × 109
Range1010
Interquartile range (IQR)808.5

Descriptive statistics

Standard deviation369.19708
Coefficient of variation (CV)1.8258006 × 10-7
Kurtosis-1.2189646
Mean2.0221107 × 109
Median Absolute Deviation (MAD)305
Skewness-0.52894737
Sum2.0221107 × 1011
Variance136306.49
MonotonicityNot monotonic
2023-12-10T19:22:52.725689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022110609 1
 
1.0%
2022110124 1
 
1.0%
2022110107 1
 
1.0%
2022110110 1
 
1.0%
2022110111 1
 
1.0%
2022110113 1
 
1.0%
2022110114 1
 
1.0%
2022110118 1
 
1.0%
2022110119 1
 
1.0%
2022110121 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2022110101 1
1.0%
2022110102 1
1.0%
2022110103 1
1.0%
2022110104 1
1.0%
2022110105 1
1.0%
2022110106 1
1.0%
2022110107 1
1.0%
2022110108 1
1.0%
2022110109 1
1.0%
2022110110 1
1.0%
ValueCountFrequency (%)
2022111111 1
1.0%
2022111110 1
1.0%
2022111109 1
1.0%
2022111108 1
1.0%
2022111107 1
1.0%
2022111106 1
1.0%
2022111105 1
1.0%
2022111104 1
1.0%
2022111103 1
1.0%
2022111102 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.53544
Minimum23.47
Maximum23.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:52.928242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.47
5-th percentile23.4895
Q123.52
median23.54
Q323.55
95-th percentile23.5805
Maximum23.59
Range0.12
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.027987486
Coefficient of variation (CV)0.0011891635
Kurtosis-0.18061664
Mean23.53544
Median Absolute Deviation (MAD)0.011
Skewness-0.18855454
Sum2353.544
Variance0.00078329939
MonotonicityNot monotonic
2023-12-10T19:22:53.135895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
23.54 17
17.0%
23.53 16
16.0%
23.55 12
12.0%
23.56 8
8.0%
23.49 6
 
6.0%
23.51 5
 
5.0%
23.59 5
 
5.0%
23.58 5
 
5.0%
23.52 5
 
5.0%
23.5 4
 
4.0%
Other values (12) 17
17.0%
ValueCountFrequency (%)
23.47 1
 
1.0%
23.477 1
 
1.0%
23.48 3
3.0%
23.49 6
6.0%
23.495 1
 
1.0%
23.5 4
4.0%
23.51 5
5.0%
23.511 1
 
1.0%
23.52 5
5.0%
23.525 1
 
1.0%
ValueCountFrequency (%)
23.59 5
 
5.0%
23.58 5
 
5.0%
23.57 2
 
2.0%
23.561 1
 
1.0%
23.56 8
8.0%
23.552 1
 
1.0%
23.55 12
12.0%
23.542 2
 
2.0%
23.541 1
 
1.0%
23.54 17
17.0%

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

2023-12-10T19:22:53.330774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:53.461392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.05638
Minimum15.005
Maximum24.258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:53.626503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.005
5-th percentile16.32725
Q118.972
median20.361
Q321.34625
95-th percentile23.7
Maximum24.258
Range9.253
Interquartile range (IQR)2.37425

Descriptive statistics

Standard deviation2.0849849
Coefficient of variation (CV)0.10395619
Kurtosis-0.18529797
Mean20.05638
Median Absolute Deviation (MAD)1.239
Skewness-0.29006649
Sum2005.638
Variance4.3471621
MonotonicityNot monotonic
2023-12-10T19:22:53.893227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.4 10
 
10.0%
19.8 6
 
6.0%
21.6 5
 
5.0%
21.0 4
 
4.0%
23.7 4
 
4.0%
18.3 2
 
2.0%
17.1 2
 
2.0%
23.1 2
 
2.0%
21.877 1
 
1.0%
22.558 1
 
1.0%
Other values (63) 63
63.0%
ValueCountFrequency (%)
15.005 1
1.0%
15.575 1
1.0%
15.585 1
1.0%
16.212 1
1.0%
16.237 1
1.0%
16.332 1
1.0%
16.377 1
1.0%
16.427 1
1.0%
16.5 1
1.0%
16.629 1
1.0%
ValueCountFrequency (%)
24.258 1
 
1.0%
23.888 1
 
1.0%
23.7 4
4.0%
23.696 1
 
1.0%
23.506 1
 
1.0%
23.1 2
2.0%
22.558 1
 
1.0%
22.476 1
 
1.0%
22.262 1
 
1.0%
22.228 1
 
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.08748
Minimum15.935
Maximum23.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:54.122560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.935
5-th percentile16.6895
Q119.15
median20.4
Q321.1325
95-th percentile23.233
Maximum23.7
Range7.765
Interquartile range (IQR)1.9825

Descriptive statistics

Standard deviation1.8445341
Coefficient of variation (CV)0.091825062
Kurtosis-0.22340607
Mean20.08748
Median Absolute Deviation (MAD)1.0025
Skewness-0.21358103
Sum2008.748
Variance3.4023061
MonotonicityNot monotonic
2023-12-10T19:22:54.368217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.4 11
 
11.0%
19.8 8
 
8.0%
21.6 5
 
5.0%
21.0 4
 
4.0%
23.7 4
 
4.0%
20.96 2
 
2.0%
18.3 2
 
2.0%
17.1 2
 
2.0%
23.1 2
 
2.0%
20.7 2
 
2.0%
Other values (57) 58
58.0%
ValueCountFrequency (%)
15.935 1
1.0%
16.005 1
1.0%
16.5 1
1.0%
16.575 1
1.0%
16.585 1
1.0%
16.695 1
1.0%
16.93 1
1.0%
17.1 2
2.0%
17.265 1
1.0%
17.335 1
1.0%
ValueCountFrequency (%)
23.7 4
4.0%
23.29 1
 
1.0%
23.23 1
 
1.0%
23.1 2
2.0%
23.055 1
 
1.0%
22.615 1
 
1.0%
22.45 1
 
1.0%
22.375 1
 
1.0%
21.96 1
 
1.0%
21.64 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.653645
Minimum0.6297
Maximum0.6739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:54.586505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6297
5-th percentile0.63672
Q10.6479
median0.6553
Q30.659
95-th percentile0.670385
Maximum0.6739
Range0.0442
Interquartile range (IQR)0.0111

Descriptive statistics

Standard deviation0.01033364
Coefficient of variation (CV)0.015809254
Kurtosis-0.18729387
Mean0.653645
Median Absolute Deviation (MAD)0.00405
Skewness-0.16805402
Sum65.3645
Variance0.00010678412
MonotonicityNot monotonic
2023-12-10T19:22:54.779279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.6553 17
17.0%
0.6516 16
16.0%
0.659 12
12.0%
0.6627 8
8.0%
0.6369 6
 
6.0%
0.6442 5
 
5.0%
0.6739 5
 
5.0%
0.6702 5
 
5.0%
0.6479 5
 
5.0%
0.6406 4
 
4.0%
Other values (12) 17
17.0%
ValueCountFrequency (%)
0.6297 1
 
1.0%
0.6322 1
 
1.0%
0.6333 3
3.0%
0.6369 6
6.0%
0.6387 1
 
1.0%
0.6406 4
4.0%
0.6442 5
5.0%
0.6446 1
 
1.0%
0.6479 5
5.0%
0.6498 1
 
1.0%
ValueCountFrequency (%)
0.6739 5
 
5.0%
0.6702 5
 
5.0%
0.6664 2
 
2.0%
0.6631 1
 
1.0%
0.6627 8
8.0%
0.6597 1
 
1.0%
0.659 12
12.0%
0.656 2
 
2.0%
0.6557 1
 
1.0%
0.6553 17
17.0%

저수율
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.9
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.9
2nd row0.9
3rd row0.9
4th row0.9
5th row0.9

Common Values

ValueCountFrequency (%)
0.9 100
100.0%

Length

2023-12-10T19:22:54.981383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:55.118383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.9 100
100.0%

Interactions

2023-12-10T19:22:50.704135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.005444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.674313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.331932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.020131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.849708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.129540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.794637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.464116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.138968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:51.015594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.273198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.939847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.639832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.270085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:51.140210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.397725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.063462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.754422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.410728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:51.299487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:48.548730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.213775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:49.895125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:50.563593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:22:55.219737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)
일자/시간(t)1.0000.5900.5410.7290.565
저수위(m)0.5901.0000.9110.9670.999
유입량(ms)0.5410.9111.0000.8620.903
방류량(ms)0.7290.9670.8621.0000.971
저수량(백만m3)0.5650.9990.9030.9711.000
2023-12-10T19:22:55.379305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)
일자/시간(t)1.000-0.363-0.280-0.371-0.363
저수위(m)-0.3631.0000.9140.9731.000
유입량(ms)-0.2800.9141.0000.8500.914
방류량(ms)-0.3710.9730.8501.0000.973
저수량(백만m3)-0.3631.0000.9140.9731.000

Missing values

2023-12-10T19:22:51.473483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:22:51.675171image/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
0군남202211060923.58023.123.10.67020.9
1군남202211061223.55020.32221.350.6590.9
2군남202211061023.57021.55922.6150.66640.9
3군남202211100323.495018.4316.930.63870.9
4군남202211070423.52020.18818.160.64790.9
5군남202211061323.54019.67220.70.65530.9
6군남202211061123.56020.93221.960.66270.9
7군남202211111123.54019.47220.50.65530.9
8군남202211101923.54020.420.40.65530.9
9군남202211100423.51019.44817.920.64420.9
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202211101123.55020.08221.110.6590.9
91군남202211101023.56021.621.60.66270.9
92군남202211100823.56022.55821.530.66270.9
93군남202211100723.55021.87720.960.6590.9
94군남202211100123.48015.58516.5850.63330.9
95군남202211092423.49016.23717.2650.63690.9
96군남202211092223.511017.17619.120.64460.9
97군남202211092123.53019.05220.080.65160.9
98군남202211060723.58023.88823.0550.67020.9
99군남202211060823.58023.123.10.67020.9