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

Categorical2
Numeric6

Alerts

댐이름 has constant value ""Constant
저수위(m) has constant value ""Constant
일자/시간(t) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique
저수량(백만m3) has unique valuesUnique
방류량(ms) has 26 (26.0%) zerosZeros

Reproduction

Analysis started2023-12-10 11:53:20.133016
Analysis finished2023-12-10 11:53:26.798456
Duration6.67 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
낙동강하굿둑
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
낙동강하굿둑 100
100.0%

Length

2023-12-10T20:53:26.920897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:53:27.078458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낙동강하굿둑 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190303 × 109
Minimum2.0190301 × 109
Maximum2.0190305 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:27.280598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190301 × 109
5-th percentile2.0190301 × 109
Q12.0190302 × 109
median2.0190303 × 109
Q32.0190304 × 109
95-th percentile2.0190305 × 109
Maximum2.0190305 × 109
Range403
Interquartile range (IQR)201.5

Descriptive statistics

Standard deviation124.87134
Coefficient of variation (CV)6.1847185 × 10-8
Kurtosis-1.0979699
Mean2.0190303 × 109
Median Absolute Deviation (MAD)101
Skewness-0.023816882
Sum2.0190303 × 1011
Variance15592.852
MonotonicityNot monotonic
2023-12-10T20:53:27.580585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019030515 1
 
1.0%
2019030223 1
 
1.0%
2019030213 1
 
1.0%
2019030214 1
 
1.0%
2019030215 1
 
1.0%
2019030216 1
 
1.0%
2019030217 1
 
1.0%
2019030218 1
 
1.0%
2019030219 1
 
1.0%
2019030220 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019030113 1
1.0%
2019030114 1
1.0%
2019030115 1
1.0%
2019030116 1
1.0%
2019030117 1
1.0%
2019030118 1
1.0%
2019030119 1
1.0%
2019030120 1
1.0%
2019030121 1
1.0%
2019030122 1
1.0%
ValueCountFrequency (%)
2019030516 1
1.0%
2019030515 1
1.0%
2019030514 1
1.0%
2019030513 1
1.0%
2019030512 1
1.0%
2019030511 1
1.0%
2019030510 1
1.0%
2019030509 1
1.0%
2019030508 1
1.0%
2019030507 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

2023-12-10T20:53:27.817100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:53:27.969606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.32586
Minimum298.215
Maximum302.372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:28.109569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum298.215
5-th percentile299.136
Q1300.86725
median301.908
Q3301.908
95-th percentile302.372
Maximum302.372
Range4.157
Interquartile range (IQR)1.04075

Descriptive statistics

Standard deviation1.0686528
Coefficient of variation (CV)0.0035465022
Kurtosis0.3215648
Mean301.32586
Median Absolute Deviation (MAD)0.463
Skewness-1.2042533
Sum30132.586
Variance1.1420189
MonotonicityNot monotonic
2023-12-10T20:53:28.322819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
301.908 37
37.0%
301.445 18
18.0%
302.372 17
17.0%
299.597 8
 
8.0%
300.52 6
 
6.0%
299.136 5
 
5.0%
300.059 3
 
3.0%
298.675 2
 
2.0%
300.983 2
 
2.0%
302.3716 1
 
1.0%
ValueCountFrequency (%)
298.215 1
 
1.0%
298.675 2
 
2.0%
299.136 5
 
5.0%
299.597 8
 
8.0%
300.059 3
 
3.0%
300.52 6
 
6.0%
300.983 2
 
2.0%
301.445 18
18.0%
301.908 37
37.0%
302.3716 1
 
1.0%
ValueCountFrequency (%)
302.372 17
17.0%
302.3716 1
 
1.0%
301.908 37
37.0%
301.445 18
18.0%
300.983 2
 
2.0%
300.52 6
 
6.0%
300.059 3
 
3.0%
299.597 8
 
8.0%
299.136 5
 
5.0%
298.675 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.085
Minimum97.1
Maximum98.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:28.520549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum97.1
5-th percentile97.4
Q197.95
median98.3
Q398.3
95-th percentile98.4
Maximum98.4
Range1.3
Interquartile range (IQR)0.35

Descriptive statistics

Standard deviation0.34913313
Coefficient of variation (CV)0.0035594956
Kurtosis0.20634923
Mean98.085
Median Absolute Deviation (MAD)0.1
Skewness-1.194416
Sum9808.5
Variance0.12189394
MonotonicityNot monotonic
2023-12-10T20:53:28.809635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
98.3 37
37.0%
98.1 18
18.0%
98.4 18
18.0%
97.5 8
 
8.0%
97.8 6
 
6.0%
97.4 5
 
5.0%
97.7 3
 
3.0%
97.2 2
 
2.0%
98.0 2
 
2.0%
97.1 1
 
1.0%
ValueCountFrequency (%)
97.1 1
 
1.0%
97.2 2
 
2.0%
97.4 5
 
5.0%
97.5 8
 
8.0%
97.7 3
 
3.0%
97.8 6
 
6.0%
98.0 2
 
2.0%
98.1 18
18.0%
98.3 37
37.0%
98.4 18
18.0%
ValueCountFrequency (%)
98.4 18
18.0%
98.3 37
37.0%
98.1 18
18.0%
98.0 2
 
2.0%
97.8 6
 
6.0%
97.7 3
 
3.0%
97.5 8
 
8.0%
97.4 5
 
5.0%
97.2 2
 
2.0%
97.1 1
 
1.0%

방류량(ms)
Real number (ℝ)

ZEROS 

Distinct75
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.58513
Minimum0
Maximum390.538
Zeros26
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:29.052210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.5035
Q32.7525
95-th percentile201.2095
Maximum390.538
Range390.538
Interquartile range (IQR)2.7525

Descriptive statistics

Standard deviation83.948865
Coefficient of variation (CV)2.1756792
Kurtosis6.5937424
Mean38.58513
Median Absolute Deviation (MAD)1.5035
Skewness2.5544206
Sum3858.513
Variance7047.4119
MonotonicityNot monotonic
2023-12-10T20:53:29.336425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 26
 
26.0%
1.157 1
 
1.0%
1.215 1
 
1.0%
1.46 1
 
1.0%
1.167 1
 
1.0%
1.264 1
 
1.0%
1.246 1
 
1.0%
129.707 1
 
1.0%
1.398 1
 
1.0%
1.661 1
 
1.0%
Other values (65) 65
65.0%
ValueCountFrequency (%)
0.0 26
26.0%
1.073 1
 
1.0%
1.131 1
 
1.0%
1.155 1
 
1.0%
1.157 1
 
1.0%
1.167 1
 
1.0%
1.191 1
 
1.0%
1.208 1
 
1.0%
1.215 1
 
1.0%
1.227 1
 
1.0%
ValueCountFrequency (%)
390.538 1
1.0%
389.574 1
1.0%
330.191 1
1.0%
262.135 1
1.0%
261.981 1
1.0%
198.011 1
1.0%
174.224 1
1.0%
136.586 1
1.0%
133.981 1
1.0%
130.811 1
1.0%

저수량(백만m3)
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.13418
Minimum1.008
Maximum92.775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:29.603603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.008
5-th percentile1.12875
Q11.326
median1.6605
Q33.335
95-th percentile66.3116
Maximum92.775
Range91.767
Interquartile range (IQR)2.009

Descriptive statistics

Standard deviation18.9108
Coefficient of variation (CV)2.3248563
Kurtosis8.3940359
Mean8.13418
Median Absolute Deviation (MAD)0.426
Skewness3.0945322
Sum813.418
Variance357.61834
MonotonicityNot monotonic
2023-12-10T20:53:29.833802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
92.775 1
 
1.0%
1.629 1
 
1.0%
1.167 1
 
1.0%
1.129 1
 
1.0%
1.264 1
 
1.0%
1.246 1
 
1.0%
1.124 1
 
1.0%
1.377 1
 
1.0%
1.398 1
 
1.0%
1.269 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1.008 1
1.0%
1.023 1
1.0%
1.06 1
1.0%
1.073 1
1.0%
1.124 1
1.0%
1.129 1
1.0%
1.131 1
1.0%
1.152 1
1.0%
1.155 1
1.0%
1.167 1
1.0%
ValueCountFrequency (%)
92.775 1
1.0%
73.58 1
1.0%
72.036 1
1.0%
69.928 1
1.0%
68.128 1
1.0%
66.216 1
1.0%
56.135 1
1.0%
53.107 1
1.0%
46.141 1
1.0%
8.086 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8474
Minimum0.78
Maximum0.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:30.064117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.78
5-th percentile0.8
Q10.8375
median0.86
Q30.86
95-th percentile0.87
Maximum0.87
Range0.09
Interquartile range (IQR)0.0225

Descriptive statistics

Standard deviation0.023121113
Coefficient of variation (CV)0.027284769
Kurtosis0.32863086
Mean0.8474
Median Absolute Deviation (MAD)0.01
Skewness-1.2070122
Sum84.74
Variance0.00053458586
MonotonicityNot monotonic
2023-12-10T20:53:30.258334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.86 37
37.0%
0.85 18
18.0%
0.87 18
18.0%
0.81 8
 
8.0%
0.83 6
 
6.0%
0.8 5
 
5.0%
0.82 3
 
3.0%
0.79 2
 
2.0%
0.84 2
 
2.0%
0.78 1
 
1.0%
ValueCountFrequency (%)
0.78 1
 
1.0%
0.79 2
 
2.0%
0.8 5
 
5.0%
0.81 8
 
8.0%
0.82 3
 
3.0%
0.83 6
 
6.0%
0.84 2
 
2.0%
0.85 18
18.0%
0.86 37
37.0%
0.87 18
18.0%
ValueCountFrequency (%)
0.87 18
18.0%
0.86 37
37.0%
0.85 18
18.0%
0.84 2
 
2.0%
0.83 6
 
6.0%
0.82 3
 
3.0%
0.81 8
 
8.0%
0.8 5
 
5.0%
0.79 2
 
2.0%
0.78 1
 
1.0%

Interactions

2023-12-10T20:53:25.596242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:20.430367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:21.821427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.714715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.728509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.704763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.765069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:20.609100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:21.984793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.898057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.919152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.883326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.891754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:20.764127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.126923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.097556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.071602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.006314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:26.041455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:20.935358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.295276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.277772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.224586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.158874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:26.197350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:21.473670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.442386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.439068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.389174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.326505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:26.314183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:21.671355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:22.579403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:23.585313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:24.546397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:25.462115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:53:30.404557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.6580.6140.0000.2790.627
강우량(mm)0.6581.0001.0000.6400.6531.000
유입량(ms)0.6141.0001.0000.7990.5691.000
방류량(ms)0.0000.6400.7991.0000.8360.637
저수량(백만m3)0.2790.6530.5690.8361.0000.657
저수율0.6271.0001.0000.6370.6571.000
2023-12-10T20:53:30.566522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.773-0.774-0.0650.441-0.774
강우량(mm)-0.7731.0001.0000.236-0.4301.000
유입량(ms)-0.7741.0001.0000.233-0.4341.000
방류량(ms)-0.0650.2360.2331.0000.2180.233
저수량(백만m3)0.441-0.430-0.4340.2181.000-0.434
저수율-0.7741.0001.0000.233-0.4341.000

Missing values

2023-12-10T20:53:26.508087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:53:26.715896image/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
0낙동강하굿둑20190305150298.67597.20.092.7750.79
1낙동강하굿둑20190305140299.59797.5174.22446.1410.81
2낙동강하굿둑20190305130299.13697.41.0731.0730.8
3낙동강하굿둑20190305120299.13697.40.01.060.8
4낙동강하굿둑20190305110299.59797.50.01.0080.81
5낙동강하굿둑20190305100300.5297.81.5541.5540.83
6낙동강하굿둑20190305090300.5297.8129.5491.2710.83
7낙동강하굿둑20190305080300.05997.7389.5745.2960.82
8낙동강하굿둑20190305070298.67597.20.05.7880.79
9낙동강하굿둑20190305060299.13697.40.06.1510.8
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90낙동강하굿둑20190301210301.90898.31.5131.5130.86
91낙동강하굿둑20190301200301.90898.33.6463.590.86
92낙동강하굿둑20190301190301.90898.31.2081.1520.86
93낙동강하굿둑20190301180301.90898.31.9131.8570.86
94낙동강하굿둑20190301170301.90898.31.1311.1310.86
95낙동강하굿둑20190301160301.90898.32.2882.2880.86
96낙동강하굿둑20190301150301.90898.31.2471.2470.86
97낙동강하굿둑20190301140301.90898.30.01.0230.86
98낙동강하굿둑20190301130302.37298.4129.9141.1920.87
99낙동강하굿둑20190305160298.21597.10.066.2160.78