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
일자/시간(t) is highly overall correlated with 저수위(m) and 3 other fieldsHigh correlation
저수위(m) 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
방류량(ms) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:22:38.447908
Analysis finished2023-12-10 10:22:43.128341
Duration4.68 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

2023-12-10T19:22:43.255196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:43.489307image/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%
Mean2.0221205 × 109
Minimum2.0221201 × 109
Maximum2.0221209 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:43.660206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0221201 × 109
5-th percentile2.0221201 × 109
Q12.0221203 × 109
median2.0221205 × 109
Q32.0221206 × 109
95-th percentile2.0221209 × 109
Maximum2.0221209 × 109
Range818
Interquartile range (IQR)301.5

Descriptive statistics

Standard deviation271.46927
Coefficient of variation (CV)1.342498 × 10-7
Kurtosis-1.0434861
Mean2.0221205 × 109
Median Absolute Deviation (MAD)200
Skewness-0.046461353
Sum2.0221205 × 1011
Variance73695.566
MonotonicityNot monotonic
2023-12-10T19:22:43.958168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022120320 1
 
1.0%
2022120116 1
 
1.0%
2022120916 1
 
1.0%
2022120919 1
 
1.0%
2022120101 1
 
1.0%
2022120103 1
 
1.0%
2022120104 1
 
1.0%
2022120108 1
 
1.0%
2022120109 1
 
1.0%
2022120111 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2022120101 1
1.0%
2022120102 1
1.0%
2022120103 1
1.0%
2022120104 1
1.0%
2022120105 1
1.0%
2022120106 1
1.0%
2022120107 1
1.0%
2022120108 1
1.0%
2022120109 1
1.0%
2022120110 1
1.0%
ValueCountFrequency (%)
2022120919 1
1.0%
2022120918 1
1.0%
2022120917 1
1.0%
2022120916 1
1.0%
2022120915 1
1.0%
2022120914 1
1.0%
2022120913 1
1.0%
2022120912 1
1.0%
2022120911 1
1.0%
2022120910 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.47733
Minimum23.44
Maximum23.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:44.164107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.44
5-th percentile23.44
Q123.46
median23.47
Q323.49
95-th percentile23.5305
Maximum23.55
Range0.11
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.029803415
Coefficient of variation (CV)0.001269455
Kurtosis-0.30079529
Mean23.47733
Median Absolute Deviation (MAD)0.02
Skewness0.68756506
Sum2347.733
Variance0.00088824354
MonotonicityNot monotonic
2023-12-10T19:22:44.371155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
23.49 19
19.0%
23.46 19
19.0%
23.44 16
16.0%
23.52 11
11.0%
23.48 9
9.0%
23.47 9
9.0%
23.45 8
8.0%
23.55 3
 
3.0%
23.54 2
 
2.0%
23.53 2
 
2.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
23.44 16
16.0%
23.45 8
8.0%
23.46 19
19.0%
23.47 9
9.0%
23.473 1
 
1.0%
23.48 9
9.0%
23.49 19
19.0%
23.51 1
 
1.0%
23.52 11
11.0%
23.53 2
 
2.0%
ValueCountFrequency (%)
23.55 3
 
3.0%
23.54 2
 
2.0%
23.53 2
 
2.0%
23.52 11
11.0%
23.51 1
 
1.0%
23.49 19
19.0%
23.48 9
9.0%
23.473 1
 
1.0%
23.47 9
9.0%
23.46 19
19.0%

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

2023-12-10T19:22:44.584155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:44.721694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.34384
Minimum33.6
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:44.857387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.6
5-th percentile33.6
Q135.66125
median37.1
Q339.9
95-th percentile46.2466
Maximum49
Range15.4
Interquartile range (IQR)4.23875

Descriptive statistics

Standard deviation4.0792009
Coefficient of variation (CV)0.10638478
Kurtosis0.060384234
Mean38.34384
Median Absolute Deviation (MAD)2.8
Skewness0.89730097
Sum3834.384
Variance16.63988
MonotonicityNot monotonic
2023-12-10T19:22:45.061360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35.7 18
18.0%
39.9 18
18.0%
33.6 14
14.0%
44.1 10
10.0%
38.5 9
9.0%
37.1 8
8.0%
35.0 6
 
6.0%
49.0 3
 
3.0%
34.845 1
 
1.0%
33.755 1
 
1.0%
Other values (12) 12
12.0%
ValueCountFrequency (%)
33.6 14
14.0%
33.685 1
 
1.0%
33.755 1
 
1.0%
34.845 1
 
1.0%
35.0 6
 
6.0%
35.524 1
 
1.0%
35.545 1
 
1.0%
35.7 18
18.0%
36.834 1
 
1.0%
37.1 8
8.0%
ValueCountFrequency (%)
49.0 3
 
3.0%
47.6 1
 
1.0%
47.132 1
 
1.0%
46.2 1
 
1.0%
45.569 1
 
1.0%
44.46 1
 
1.0%
44.1 10
10.0%
42.839 1
 
1.0%
40.165 1
 
1.0%
39.9 18
18.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.39524
Minimum33.6
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:45.251186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.6
5-th percentile33.6
Q135.7
median37.1
Q339.9
95-th percentile46.64715
Maximum49
Range15.4
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation4.1385626
Coefficient of variation (CV)0.10778843
Kurtosis0.080905467
Mean38.39524
Median Absolute Deviation (MAD)2.8
Skewness0.9230085
Sum3839.524
Variance17.127701
MonotonicityNot monotonic
2023-12-10T19:22:45.495980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35.7 18
18.0%
39.9 18
18.0%
33.6 14
14.0%
44.1 10
10.0%
38.5 9
9.0%
37.1 8
8.0%
35.0 6
 
6.0%
49.0 3
 
3.0%
33.845 1
 
1.0%
34.755 1
 
1.0%
Other values (12) 12
12.0%
ValueCountFrequency (%)
33.6 14
14.0%
33.845 1
 
1.0%
34.545 1
 
1.0%
34.685 1
 
1.0%
34.755 1
 
1.0%
35.0 6
 
6.0%
35.7 18
18.0%
36.552 1
 
1.0%
37.1 8
8.0%
37.112 1
 
1.0%
ValueCountFrequency (%)
49.0 3
 
3.0%
48.16 1
 
1.0%
47.6 1
 
1.0%
46.597 1
 
1.0%
46.2 1
 
1.0%
45.488 1
 
1.0%
44.1 10
10.0%
43.867 1
 
1.0%
39.9 18
18.0%
39.165 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.632347
Minimum0.6188
Maximum0.659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:22:45.738554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6188
5-th percentile0.6188
Q10.626
median0.6297
Q30.6369
95-th percentile0.651785
Maximum0.659
Range0.0402
Interquartile range (IQR)0.0109

Descriptive statistics

Standard deviation0.010865862
Coefficient of variation (CV)0.017183385
Kurtosis-0.27228309
Mean0.632347
Median Absolute Deviation (MAD)0.0072
Skewness0.70242816
Sum63.2347
Variance0.00011806696
MonotonicityNot monotonic
2023-12-10T19:22:45.967879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.6369 19
19.0%
0.626 19
19.0%
0.6188 16
16.0%
0.6479 11
11.0%
0.6333 9
9.0%
0.6297 9
9.0%
0.6224 8
8.0%
0.659 3
 
3.0%
0.6553 2
 
2.0%
0.6516 2
 
2.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
0.6188 16
16.0%
0.6224 8
8.0%
0.626 19
19.0%
0.6297 9
9.0%
0.6307 1
 
1.0%
0.6333 9
9.0%
0.6369 19
19.0%
0.6442 1
 
1.0%
0.6479 11
11.0%
0.6516 2
 
2.0%
ValueCountFrequency (%)
0.659 3
 
3.0%
0.6553 2
 
2.0%
0.6516 2
 
2.0%
0.6479 11
11.0%
0.6442 1
 
1.0%
0.6369 19
19.0%
0.6333 9
9.0%
0.6307 1
 
1.0%
0.6297 9
9.0%
0.626 19
19.0%

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

2023-12-10T19:22:46.221208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:22:46.393308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.9 100
100.0%

Interactions

2023-12-10T19:22:41.691237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:38.723225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.458849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.093307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.934938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:41.852691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:38.881259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.587719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.235612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:41.085789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:42.001945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.019040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.711787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.461577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:41.209170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:42.160646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.164425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.854400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.603228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:41.368234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:42.311214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.311099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:39.962134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:40.767080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:41.521045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:22:46.512825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)
일자/시간(t)1.0000.8880.8920.8920.889
저수위(m)0.8881.0000.9820.9981.000
유입량(ms)0.8920.9821.0000.9700.985
방류량(ms)0.8920.9980.9701.0000.997
저수량(백만m3)0.8891.0000.9850.9971.000
2023-12-10T19:22:46.714076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)
일자/시간(t)1.000-0.959-0.957-0.958-0.959
저수위(m)-0.9591.0000.9980.9971.000
유입량(ms)-0.9570.9981.0000.9950.998
방류량(ms)-0.9580.9970.9951.0000.997
저수량(백만m3)-0.9591.0000.9980.9971.000

Missing values

2023-12-10T19:22:42.853964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:22:43.051702image/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
0군남202212032023.48038.538.50.63330.9
1군남202212051823.48038.538.50.63330.9
2군남202212090823.44033.633.60.61880.9
3군남202212032123.49040.16539.1650.63690.9
4군남202212061023.46035.735.70.6260.9
5군남202212051923.48038.538.50.63330.9
6군남202212010523.54047.647.60.65530.9
7군남202212090923.44033.633.60.61880.9
8군남202212041323.49039.939.90.63690.9
9군남202212032223.49039.939.90.63690.9
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202212040523.49039.939.90.63690.9
91군남202212040423.49039.939.90.63690.9
92군남202212040223.49039.939.90.63690.9
93군남202212040123.49039.939.90.63690.9
94군남202212031923.48038.538.50.63330.9
95군남202212031823.48038.538.50.63330.9
96군남202212031623.48038.538.50.63330.9
97군남202212062423.46035.735.70.6260.9
98군남202212051623.48038.538.50.63330.9
99군남202212051723.48038.538.50.63330.9