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

Categorical5
Numeric3

Alerts

댐이름 has constant value ""Constant
저수위(m) has constant value ""Constant
강우량(mm) 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
저수율 is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
일자/시간(t) is highly overall correlated with 방류량(ms) and 4 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 일자/시간(t) and 1 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique
방류량(ms) has 6 (6.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:28:56.823437
Analysis finished2023-12-10 13:28:59.105645
Duration2.28 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

2023-12-10T22:28:59.234011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:28:59.443748image/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%
Mean2.0190109 × 1011
Minimum2.0190109 × 1011
Maximum2.0190109 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:28:59.673041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190109 × 1011
5-th percentile2.0190109 × 1011
Q12.0190109 × 1011
median2.0190109 × 1011
Q32.0190109 × 1011
95-th percentile2.0190109 × 1011
Maximum2.0190109 × 1011
Range1670
Interquartile range (IQR)825

Descriptive statistics

Standard deviation483.80099
Coefficient of variation (CV)2.3962277 × 10-9
Kurtosis-1.1968508
Mean2.0190109 × 1011
Median Absolute Deviation (MAD)410
Skewness-0.0015635452
Sum2.0190109 × 1013
Variance234063.39
MonotonicityNot monotonic
2023-12-10T22:28:59.929222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201901091340 1
 
1.0%
201901092330 1
 
1.0%
201901092020 1
 
1.0%
201901092050 1
 
1.0%
201901092100 1
 
1.0%
201901092120 1
 
1.0%
201901092130 1
 
1.0%
201901092210 1
 
1.0%
201901092220 1
 
1.0%
201901092240 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201901090730 1
1.0%
201901090740 1
1.0%
201901090750 1
1.0%
201901090800 1
1.0%
201901090810 1
1.0%
201901090820 1
1.0%
201901090830 1
1.0%
201901090840 1
1.0%
201901090850 1
1.0%
201901090900 1
1.0%
ValueCountFrequency (%)
201901092400 1
1.0%
201901092350 1
1.0%
201901092340 1
1.0%
201901092330 1
1.0%
201901092320 1
1.0%
201901092310 1
1.0%
201901092300 1
1.0%
201901092250 1
1.0%
201901092240 1
1.0%
201901092230 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

2023-12-10T22:29:00.240437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:29:00.428859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
27.585
51 
27.605
36 
27.565
13 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27.585
2nd row27.605
3rd row27.585
4th row27.585
5th row27.605

Common Values

ValueCountFrequency (%)
27.585 51
51.0%
27.605 36
36.0%
27.565 13
 
13.0%

Length

2023-12-10T22:29:00.665774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:29:00.862785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
27.585 51
51.0%
27.605 36
36.0%
27.565 13
 
13.0%

유입량(ms)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
56.6
64 
56.7
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row56.6
2nd row56.7
3rd row56.6
4th row56.6
5th row56.7

Common Values

ValueCountFrequency (%)
56.6 64
64.0%
56.7 36
36.0%

Length

2023-12-10T22:29:01.058559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:29:01.660859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
56.6 64
64.0%
56.7 36
36.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8459
Minimum0
Maximum0.911
Zeros6
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:29:01.910000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.894
median0.898
Q30.905
95-th percentile0.90905
Maximum0.911
Range0.911
Interquartile range (IQR)0.011

Descriptive statistics

Standard deviation0.21486484
Coefficient of variation (CV)0.25400738
Kurtosis12.37993
Mean0.8459
Median Absolute Deviation (MAD)0.005
Skewness-3.7576387
Sum84.59
Variance0.046166899
MonotonicityNot monotonic
2023-12-10T22:29:02.180697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.893 12
 
12.0%
0.894 9
 
9.0%
0.899 8
 
8.0%
0.905 8
 
8.0%
0.0 6
 
6.0%
0.895 6
 
6.0%
0.898 6
 
6.0%
0.904 5
 
5.0%
0.908 5
 
5.0%
0.907 5
 
5.0%
Other values (11) 30
30.0%
ValueCountFrequency (%)
0.0 6
6.0%
0.891 1
 
1.0%
0.892 3
 
3.0%
0.893 12
12.0%
0.894 9
9.0%
0.895 6
6.0%
0.896 4
 
4.0%
0.897 4
 
4.0%
0.898 6
6.0%
0.899 8
8.0%
ValueCountFrequency (%)
0.911 1
 
1.0%
0.91 4
4.0%
0.909 3
 
3.0%
0.908 5
5.0%
0.907 5
5.0%
0.906 3
 
3.0%
0.905 8
8.0%
0.904 5
5.0%
0.903 2
 
2.0%
0.901 2
 
2.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.89974
Minimum0.888
Maximum0.912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:29:02.423814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.888
5-th percentile0.891
Q10.89475
median0.899
Q30.905
95-th percentile0.91
Maximum0.912
Range0.024
Interquartile range (IQR)0.01025

Descriptive statistics

Standard deviation0.006034614
Coefficient of variation (CV)0.0067070642
Kurtosis-1.0605976
Mean0.89974
Median Absolute Deviation (MAD)0.005
Skewness0.20532915
Sum89.974
Variance3.6416566 × 10-5
MonotonicityNot monotonic
2023-12-10T22:29:02.663696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.893 11
 
11.0%
0.9 8
 
8.0%
0.904 6
 
6.0%
0.908 6
 
6.0%
0.894 6
 
6.0%
0.899 6
 
6.0%
0.896 6
 
6.0%
0.895 6
 
6.0%
0.906 6
 
6.0%
0.897 5
 
5.0%
Other values (14) 34
34.0%
ValueCountFrequency (%)
0.888 1
 
1.0%
0.889 1
 
1.0%
0.891 5
5.0%
0.892 1
 
1.0%
0.893 11
11.0%
0.894 6
6.0%
0.895 6
6.0%
0.896 6
6.0%
0.897 5
5.0%
0.898 3
 
3.0%
ValueCountFrequency (%)
0.912 1
 
1.0%
0.911 1
 
1.0%
0.91 4
4.0%
0.909 3
3.0%
0.908 6
6.0%
0.907 2
 
2.0%
0.906 6
6.0%
0.905 3
3.0%
0.904 6
6.0%
0.903 2
 
2.0%

저수율
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
195.15
51 
195.16
36 
195.14
13 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row195.15
2nd row195.16
3rd row195.15
4th row195.15
5th row195.16

Common Values

ValueCountFrequency (%)
195.15 51
51.0%
195.16 36
36.0%
195.14 13
 
13.0%

Length

2023-12-10T22:29:02.902971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:29:03.137804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
195.15 51
51.0%
195.16 36
36.0%
195.14 13
 
13.0%

Interactions

2023-12-10T22:28:58.289065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:57.300005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:57.789585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:58.440733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:57.504640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:58.007326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:58.575696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:57.653061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:28:58.150503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:29:03.285365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9310.9970.6120.8640.931
강우량(mm)0.9311.0001.0000.1620.8021.000
유입량(ms)0.9971.0001.0000.1660.9841.000
방류량(ms)0.6120.1620.1661.0000.2790.162
저수량(백만m3)0.8640.8020.9840.2791.0000.802
저수율0.9311.0001.0000.1620.8021.000
2023-12-10T22:29:03.483687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량(mm)유입량(ms)저수율
강우량(mm)1.0000.9951.000
유입량(ms)0.9951.0000.995
저수율1.0000.9951.000
2023-12-10T22:29:03.698448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)방류량(ms)저수량(백만m3)강우량(mm)유입량(ms)저수율
일자/시간(t)1.000-0.889-0.9180.8740.9140.874
방류량(ms)-0.8891.0000.8930.2660.1060.266
저수량(백만m3)-0.9180.8931.0000.6730.8580.673
강우량(mm)0.8740.2660.6731.0000.9951.000
유입량(ms)0.9140.1060.8580.9951.0000.995
저수율0.8740.2660.6731.0000.9951.000

Missing values

2023-12-10T22:28:58.769624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:28:59.019431image/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
0군위201901091340027.58556.60.00.9195.15
1군위201901090750027.60556.70.9070.906195.16
2군위201901091900027.58556.60.8970.897195.15
3군위201901091350027.58556.60.00.9195.15
4군위201901091030027.60556.70.9060.902195.16
5군위201901090800027.60556.70.9080.908195.16
6군위201901092140027.58556.60.8940.894195.15
7군위201901091910027.58556.60.8970.897195.15
8군위201901091630027.58556.60.8990.9195.15
9군위201901091400027.58556.60.8990.899195.15
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군위201901091510027.58556.60.9010.899195.15
91군위201901091500027.58556.60.9010.901195.15
92군위201901091440027.58556.60.8980.898195.15
93군위201901091430027.58556.60.8990.899195.15
94군위201901091330027.58556.60.00.904195.15
95군위201901091320027.60556.70.9030.904195.16
96군위201901091300027.60556.70.9050.902195.16
97군위201901091250027.60556.70.9050.906195.16
98군위201901090730027.60556.70.9070.904195.16
99군위201901090740027.60556.70.9070.909195.16