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
저수위(m) has constant value ""Constant
일자/시간(t) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수량(백만m3) and 1 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique
방류량(ms) has 18 (18.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:28:25.996706
Analysis finished2023-12-10 13:28:31.112685
Duration5.12 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
군위
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군위 100
100.0%

Length

2023-12-10T22:28:31.236109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:31.401846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군위 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190509 × 1011
Minimum2.0190509 × 1011
Maximum2.0190509 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:31.570246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190509 × 1011
5-th percentile2.0190509 × 1011
Q12.0190509 × 1011
median2.0190509 × 1011
Q32.0190509 × 1011
95-th percentile2.0190509 × 1011
Maximum2.0190509 × 1011
Range1670
Interquartile range (IQR)825

Descriptive statistics

Standard deviation483.80099
Coefficient of variation (CV)2.3961802 × 10-9
Kurtosis-1.1968508
Mean2.0190509 × 1011
Median Absolute Deviation (MAD)410
Skewness-0.0015635452
Sum2.0190509 × 1013
Variance234063.39
MonotonicityNot monotonic
2023-12-10T22:28:31.803386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201905091340 1
 
1.0%
201905092330 1
 
1.0%
201905092020 1
 
1.0%
201905092050 1
 
1.0%
201905092100 1
 
1.0%
201905092120 1
 
1.0%
201905092130 1
 
1.0%
201905092210 1
 
1.0%
201905092220 1
 
1.0%
201905092240 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201905090730 1
1.0%
201905090740 1
1.0%
201905090750 1
1.0%
201905090800 1
1.0%
201905090810 1
1.0%
201905090820 1
1.0%
201905090830 1
1.0%
201905090840 1
1.0%
201905090850 1
1.0%
201905090900 1
1.0%
ValueCountFrequency (%)
201905092400 1
1.0%
201905092350 1
1.0%
201905092340 1
1.0%
201905092330 1
1.0%
201905092320 1
1.0%
201905092310 1
1.0%
201905092300 1
1.0%
201905092250 1
1.0%
201905092240 1
1.0%
201905092230 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

2023-12-10T22:28:32.017010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:32.165930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.95639
Minimum21.908
Maximum22.014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:32.308463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.908
5-th percentile21.926
Q121.944
median21.944
Q321.979
95-th percentile22.014
Maximum22.014
Range0.106
Interquartile range (IQR)0.035

Descriptive statistics

Standard deviation0.028773548
Coefficient of variation (CV)0.0013104863
Kurtosis-0.33340441
Mean21.95639
Median Absolute Deviation (MAD)0.017
Skewness0.65340669
Sum2195.639
Variance0.00082791707
MonotonicityNot monotonic
2023-12-10T22:28:32.513483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
21.944 31
31.0%
21.961 20
20.0%
21.926 19
19.0%
22.014 11
 
11.0%
21.979 10
 
10.0%
21.997 5
 
5.0%
21.908 4
 
4.0%
ValueCountFrequency (%)
21.908 4
 
4.0%
21.926 19
19.0%
21.944 31
31.0%
21.961 20
20.0%
21.979 10
 
10.0%
21.997 5
 
5.0%
22.014 11
 
11.0%
ValueCountFrequency (%)
22.014 11
 
11.0%
21.997 5
 
5.0%
21.979 10
 
10.0%
21.961 20
20.0%
21.944 31
31.0%
21.926 19
19.0%
21.908 4
 
4.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
45.1
61 
45.0
23 
45.2
16 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row45.1
2nd row45.2
3rd row45.1
4th row45.1
5th row45.1

Common Values

ValueCountFrequency (%)
45.1 61
61.0%
45.0 23
 
23.0%
45.2 16
 
16.0%

Length

2023-12-10T22:28:32.709412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:32.870780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45.1 61
61.0%
45.0 23
 
23.0%
45.2 16
 
16.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.44275
Minimum0
Maximum1.956
Zeros18
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:33.025762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.725
median1.728
Q31.732
95-th percentile1.955
Maximum1.956
Range1.956
Interquartile range (IQR)0.007

Descriptive statistics

Standard deviation0.68296816
Coefficient of variation (CV)0.47337942
Kurtosis0.8148316
Mean1.44275
Median Absolute Deviation (MAD)0.004
Skewness-1.6471649
Sum144.275
Variance0.4664455
MonotonicityNot monotonic
2023-12-10T22:28:33.226825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 18
18.0%
1.732 13
13.0%
1.726 9
9.0%
1.731 8
8.0%
1.727 8
8.0%
1.728 7
 
7.0%
1.955 6
 
6.0%
1.725 5
 
5.0%
1.73 5
 
5.0%
1.729 4
 
4.0%
Other values (7) 17
17.0%
ValueCountFrequency (%)
0.0 18
18.0%
1.724 4
 
4.0%
1.725 5
 
5.0%
1.726 9
9.0%
1.727 8
8.0%
1.728 7
 
7.0%
1.729 4
 
4.0%
1.73 5
 
5.0%
1.731 8
8.0%
1.732 13
13.0%
ValueCountFrequency (%)
1.956 2
 
2.0%
1.955 6
6.0%
1.954 3
 
3.0%
1.736 1
 
1.0%
1.735 3
 
3.0%
1.734 1
 
1.0%
1.733 3
 
3.0%
1.732 13
13.0%
1.731 8
8.0%
1.73 5
 
5.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.72968
Minimum1.718
Maximum1.737
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:33.398640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.718
5-th percentile1.724
Q11.727
median1.73
Q31.73225
95-th percentile1.735
Maximum1.737
Range0.019
Interquartile range (IQR)0.00525

Descriptive statistics

Standard deviation0.0037735925
Coefficient of variation (CV)0.0021816709
Kurtosis-0.34527746
Mean1.72968
Median Absolute Deviation (MAD)0.003
Skewness-0.24194163
Sum172.968
Variance1.424 × 10-5
MonotonicityNot monotonic
2023-12-10T22:28:33.583168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.732 10
10.0%
1.728 10
10.0%
1.729 9
9.0%
1.731 9
9.0%
1.725 9
9.0%
1.726 8
8.0%
1.73 8
8.0%
1.735 8
8.0%
1.734 7
7.0%
1.733 6
 
6.0%
Other values (7) 16
16.0%
ValueCountFrequency (%)
1.718 1
 
1.0%
1.722 1
 
1.0%
1.723 1
 
1.0%
1.724 4
 
4.0%
1.725 9
9.0%
1.726 8
8.0%
1.727 5
5.0%
1.728 10
10.0%
1.729 9
9.0%
1.73 8
8.0%
ValueCountFrequency (%)
1.737 1
 
1.0%
1.736 3
 
3.0%
1.735 8
8.0%
1.734 7
7.0%
1.733 6
6.0%
1.732 10
10.0%
1.731 9
9.0%
1.73 8
8.0%
1.729 9
9.0%
1.728 10
10.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.1472
Minimum192.12
Maximum192.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:33.798021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192.12
5-th percentile192.13
Q1192.14
median192.14
Q3192.16
95-th percentile192.18
Maximum192.18
Range0.06
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.016334879
Coefficient of variation (CV)8.501232 × 10-5
Kurtosis-0.33635307
Mean192.1472
Median Absolute Deviation (MAD)0.01
Skewness0.66235058
Sum19214.72
Variance0.00026682828
MonotonicityNot monotonic
2023-12-10T22:28:33.957732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
192.14 31
31.0%
192.15 20
20.0%
192.13 19
19.0%
192.18 11
 
11.0%
192.16 10
 
10.0%
192.17 5
 
5.0%
192.12 4
 
4.0%
ValueCountFrequency (%)
192.12 4
 
4.0%
192.13 19
19.0%
192.14 31
31.0%
192.15 20
20.0%
192.16 10
 
10.0%
192.17 5
 
5.0%
192.18 11
 
11.0%
ValueCountFrequency (%)
192.18 11
 
11.0%
192.17 5
 
5.0%
192.16 10
 
10.0%
192.15 20
20.0%
192.14 31
31.0%
192.13 19
19.0%
192.12 4
 
4.0%

Interactions

2023-12-10T22:28:29.907634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:26.278441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:27.094301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.280495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:29.123268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:30.082314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:26.435468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:27.236696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.448747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:29.280254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:30.237718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:26.587490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:27.364415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.600271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:29.416487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:30.443675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:26.755995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:27.518262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.777924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:29.573155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:30.605841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:26.935469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.127769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:28.957319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:29.743351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:28:34.090931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8900.9170.7950.4130.903
강우량(mm)0.8901.0001.0000.7980.3301.000
유입량(ms)0.9171.0001.0000.8760.6511.000
방류량(ms)0.7950.7980.8761.0000.4970.949
저수량(백만m3)0.4130.3300.6510.4971.0000.419
저수율0.9031.0001.0000.9490.4191.000
2023-12-10T22:28:34.237718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)방류량(ms)저수량(백만m3)저수율유입량(ms)
일자/시간(t)1.000-0.976-0.406-0.550-0.9760.854
강우량(mm)-0.9761.0000.4620.5361.0000.979
방류량(ms)-0.4060.4621.0000.5390.4620.573
저수량(백만m3)-0.5500.5360.5391.0000.5360.353
저수율-0.9761.0000.4620.5361.0000.979
유입량(ms)0.8540.9790.5730.3530.9791.000

Missing values

2023-12-10T22:28:30.806876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:28:31.034587image/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
0군위201905091340021.96145.11.7311.729192.15
1군위201905090750022.01445.21.9541.732192.18
2군위201905091900021.94445.11.7271.727192.14
3군위201905091350021.96145.11.7311.729192.15
4군위201905091030021.97945.10.01.733192.16
5군위201905090800022.01445.21.9541.734192.18
6군위201905092140021.92645.01.7271.727192.13
7군위201905091910021.94445.11.7261.728192.14
8군위201905091630021.94445.11.7321.729192.14
9군위201905091400021.96145.11.7271.725192.15
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위201905091510021.94445.10.01.733192.14
91군위201905091500021.96145.11.7271.726192.15
92군위201905091440021.96145.11.7291.731192.15
93군위201905091430021.96145.11.7271.728192.15
94군위201905091330021.96145.11.7311.731192.15
95군위201905091320021.96145.11.7311.728192.15
96군위201905091300021.96145.11.7351.735192.15
97군위201905091250021.96145.11.7351.731192.15
98군위201905090730022.01445.21.9551.735192.18
99군위201905090740022.01445.21.9541.729192.18