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 4 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 강우량(mm) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique
저수량(백만m3) has unique valuesUnique
방류량(ms) has 21 (21.0%) zerosZeros

Reproduction

Analysis started2023-12-10 11:53:32.123043
Analysis finished2023-12-10 11:53:38.035809
Duration5.91 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

2023-12-10T20:53:38.148075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:53:38.295192image/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%
Mean2.0190217 × 109
Minimum2.0190214 × 109
Maximum2.0190219 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:38.475085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190214 × 109
5-th percentile2.0190215 × 109
Q12.0190215 × 109
median2.0190217 × 109
Q32.0190218 × 109
95-th percentile2.0190218 × 109
Maximum2.0190219 × 109
Range479
Interquartile range (IQR)277.5

Descriptive statistics

Standard deviation120.31461
Coefficient of variation (CV)5.9590551 × 10-8
Kurtosis-1.1470049
Mean2.0190217 × 109
Median Absolute Deviation (MAD)139
Skewness0
Sum2.0190217 × 1011
Variance14475.606
MonotonicityNot monotonic
2023-12-10T20:53:38.706250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019021901 1
 
1.0%
2019021609 1
 
1.0%
2019021523 1
 
1.0%
2019021524 1
 
1.0%
2019021601 1
 
1.0%
2019021602 1
 
1.0%
2019021603 1
 
1.0%
2019021604 1
 
1.0%
2019021605 1
 
1.0%
2019021606 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019021423 1
1.0%
2019021424 1
1.0%
2019021501 1
1.0%
2019021502 1
1.0%
2019021503 1
1.0%
2019021504 1
1.0%
2019021505 1
1.0%
2019021506 1
1.0%
2019021507 1
1.0%
2019021508 1
1.0%
ValueCountFrequency (%)
2019021902 1
1.0%
2019021901 1
1.0%
2019021824 1
1.0%
2019021823 1
1.0%
2019021822 1
1.0%
2019021821 1
1.0%
2019021820 1
1.0%
2019021819 1
1.0%
2019021818 1
1.0%
2019021817 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

2023-12-10T20:53:38.939153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:53:39.092697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean304.83026
Minimum301.908
Maximum307.025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:39.230806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum301.908
5-th percentile302.372
Q1304.11275
median305.159
Q3306.092
95-th percentile306.558
Maximum307.025
Range5.117
Interquartile range (IQR)1.97925

Descriptive statistics

Standard deviation1.3178536
Coefficient of variation (CV)0.0043232374
Kurtosis-0.53271354
Mean304.83026
Median Absolute Deviation (MAD)0.933
Skewness-0.57227116
Sum30483.026
Variance1.7367381
MonotonicityNot monotonic
2023-12-10T20:53:39.424003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
306.092 16
16.0%
305.159 15
15.0%
304.229 13
13.0%
305.625 13
13.0%
306.558 10
10.0%
303.764 8
8.0%
304.694 7
7.0%
302.372 5
 
5.0%
303.299 5
 
5.0%
301.908 4
 
4.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
301.908 4
 
4.0%
302.372 5
 
5.0%
302.835 3
 
3.0%
303.299 5
 
5.0%
303.764 8
8.0%
304.229 13
13.0%
304.694 7
7.0%
305.159 15
15.0%
305.625 13
13.0%
306.092 16
16.0%
ValueCountFrequency (%)
307.025 1
 
1.0%
306.558 10
10.0%
306.092 16
16.0%
305.625 13
13.0%
305.159 15
15.0%
304.694 7
7.0%
304.229 13
13.0%
303.764 8
8.0%
303.299 5
 
5.0%
302.835 3
 
3.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.216
Minimum98.3
Maximum99.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:39.592402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum98.3
5-th percentile98.4
Q198.975
median99.3
Q399.6
95-th percentile99.8
Maximum99.9
Range1.6
Interquartile range (IQR)0.625

Descriptive statistics

Standard deviation0.42586098
Coefficient of variation (CV)0.0042922611
Kurtosis-0.56666924
Mean99.216
Median Absolute Deviation (MAD)0.3
Skewness-0.53892116
Sum9921.6
Variance0.18135758
MonotonicityNot monotonic
2023-12-10T20:53:39.768436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
99.6 16
16.0%
99.3 15
15.0%
99.0 13
13.0%
99.5 13
13.0%
99.8 10
10.0%
98.9 8
8.0%
99.2 7
7.0%
98.4 5
 
5.0%
98.7 5
 
5.0%
98.3 4
 
4.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
98.3 4
 
4.0%
98.4 5
 
5.0%
98.6 3
 
3.0%
98.7 5
 
5.0%
98.9 8
8.0%
99.0 13
13.0%
99.2 7
7.0%
99.3 15
15.0%
99.5 13
13.0%
99.6 16
16.0%
ValueCountFrequency (%)
99.9 1
 
1.0%
99.8 10
10.0%
99.6 16
16.0%
99.5 13
13.0%
99.3 15
15.0%
99.2 7
7.0%
99.0 13
13.0%
98.9 8
8.0%
98.7 5
 
5.0%
98.6 3
 
3.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct80
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.687
Minimum0
Maximum409.552
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:40.005867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.8
median142.325
Q3183.29825
95-th percentile343.9303
Maximum409.552
Range409.552
Interquartile range (IQR)176.49825

Descriptive statistics

Standard deviation117.68329
Coefficient of variation (CV)0.87375385
Kurtosis-0.78130182
Mean134.687
Median Absolute Deviation (MAD)122.6115
Skewness0.41880154
Sum13468.7
Variance13849.356
MonotonicityNot monotonic
2023-12-10T20:53:40.210314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
21.0%
178.721 1
 
1.0%
402.844 1
 
1.0%
278.389 1
 
1.0%
178.015 1
 
1.0%
177.8 1
 
1.0%
308.218 1
 
1.0%
312.42 1
 
1.0%
184.235 1
 
1.0%
51.852 1
 
1.0%
Other values (70) 70
70.0%
ValueCountFrequency (%)
0.0 21
21.0%
1.423 1
 
1.0%
6.14 1
 
1.0%
6.362 1
 
1.0%
6.665 1
 
1.0%
6.845 1
 
1.0%
7.307 1
 
1.0%
7.556 1
 
1.0%
12.463 1
 
1.0%
16.429 1
 
1.0%
ValueCountFrequency (%)
409.552 1
1.0%
402.844 1
1.0%
392.976 1
1.0%
386.983 1
1.0%
344.962 1
1.0%
343.876 1
1.0%
312.42 1
1.0%
311.126 1
1.0%
308.218 1
1.0%
306.893 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.99539
Minimum5.539
Maximum217.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:40.413340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.539
5-th percentile6.3566
Q114.41425
median137.195
Q3175.7115
95-th percentile182.62045
Maximum217.66
Range212.121
Interquartile range (IQR)161.29725

Descriptive statistics

Standard deviation72.231587
Coefficient of variation (CV)0.69456528
Kurtosis-1.6186783
Mean103.99539
Median Absolute Deviation (MAD)45.3875
Skewness-0.28278787
Sum10399.539
Variance5217.4022
MonotonicityNot monotonic
2023-12-10T20:53:40.934880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.183 1
 
1.0%
182.986 1
 
1.0%
148.639 1
 
1.0%
180.272 1
 
1.0%
178.015 1
 
1.0%
177.8 1
 
1.0%
178.69 1
 
1.0%
182.781 1
 
1.0%
184.235 1
 
1.0%
181.491 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
5.539 1
1.0%
6.001 1
1.0%
6.14 1
1.0%
6.236 1
1.0%
6.254 1
1.0%
6.362 1
1.0%
6.468 1
1.0%
6.59 1
1.0%
6.665 1
1.0%
6.706 1
1.0%
ValueCountFrequency (%)
217.66 1
1.0%
184.676 1
1.0%
184.235 1
1.0%
182.986 1
1.0%
182.781 1
1.0%
182.612 1
1.0%
182.553 1
1.0%
181.982 1
1.0%
181.491 1
1.0%
181.487 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9229
Minimum0.86
Maximum0.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:53:41.144016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.86
5-th percentile0.87
Q10.9075
median0.93
Q30.95
95-th percentile0.96
Maximum0.97
Range0.11
Interquartile range (IQR)0.0425

Descriptive statistics

Standard deviation0.028330481
Coefficient of variation (CV)0.030697238
Kurtosis-0.52757474
Mean0.9229
Median Absolute Deviation (MAD)0.02
Skewness-0.57601118
Sum92.29
Variance0.00080261616
MonotonicityNot monotonic
2023-12-10T20:53:41.327608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.95 16
16.0%
0.93 15
15.0%
0.91 13
13.0%
0.94 13
13.0%
0.96 10
10.0%
0.9 8
8.0%
0.92 7
7.0%
0.87 5
 
5.0%
0.89 5
 
5.0%
0.86 4
 
4.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
0.86 4
 
4.0%
0.87 5
 
5.0%
0.88 3
 
3.0%
0.89 5
 
5.0%
0.9 8
8.0%
0.91 13
13.0%
0.92 7
7.0%
0.93 15
15.0%
0.94 13
13.0%
0.95 16
16.0%
ValueCountFrequency (%)
0.97 1
 
1.0%
0.96 10
10.0%
0.95 16
16.0%
0.94 13
13.0%
0.93 15
15.0%
0.92 7
7.0%
0.91 13
13.0%
0.9 8
8.0%
0.89 5
 
5.0%
0.88 3
 
3.0%

Interactions

2023-12-10T20:53:36.836575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:32.428437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.392093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.215343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.170145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.977804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.976483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:32.749866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.523402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.414179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.321584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.154405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:37.117845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:32.875366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.645258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.565911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.466644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.317266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:37.261121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.006532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.796554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.731914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.615429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.468517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:37.382957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.126602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.912258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.883751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.736830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.586859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:37.505959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:33.262516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:34.052712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.024980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:35.854162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:53:36.700678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:53:41.446316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.7670.7850.5400.8740.785
강우량(mm)0.7671.0001.0000.3720.7221.000
유입량(ms)0.7851.0001.0000.3980.7221.000
방류량(ms)0.5400.3720.3981.0000.7060.398
저수량(백만m3)0.8740.7220.7220.7061.0000.722
저수율0.7851.0001.0000.3980.7221.000
2023-12-10T20:53:41.620497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.639-0.639-0.224-0.448-0.639
강우량(mm)-0.6391.0001.0000.5450.6811.000
유입량(ms)-0.6391.0001.0000.5450.6811.000
방류량(ms)-0.2240.5450.5451.0000.4080.545
저수량(백만m3)-0.4480.6810.6810.4081.0000.681
저수율-0.6391.0001.0000.5450.6811.000

Missing values

2023-12-10T20:53:37.687963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:53:37.935281image/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
0낙동강하굿둑20190219010303.76498.90.07.1830.9
1낙동강하굿둑20190218240305.15999.3136.0876.7540.93
2낙동강하굿둑20190218230304.69499.27.5567.5560.92
3낙동강하굿둑20190218220304.69499.2136.3377.1150.92
4낙동강하굿둑20190218210304.22999.0134.655.5390.91
5낙동강하굿둑20190218200303.76498.9392.9766.2540.9
6낙동강하굿둑20190218190302.37298.40.07.1370.87
7낙동강하굿둑20190218180302.83598.66.3626.3620.88
8낙동강하굿둑20190218170302.83598.6264.4616.9330.88
9낙동강하굿둑20190218160301.90898.30.043.4020.86
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90낙동강하굿둑20190215070306.09299.6217.66217.660.95
91낙동강하굿둑20190215060306.09299.618.35147.9890.95
92낙동강하굿둑20190215050306.55899.8157.526157.5260.96
93낙동강하굿둑20190215040306.55899.8275.717146.0780.96
94낙동강하굿둑20190215030306.09299.6273.065143.5370.95
95낙동강하굿둑20190215020305.62599.512.463141.9910.94
96낙동강하굿둑20190215010306.09299.6142.872142.8720.95
97낙동강하굿둑20190214240306.09299.6143.382143.3820.95
98낙동강하굿둑20190214230306.09299.6271.63142.1020.95
99낙동강하굿둑20190219020304.22999.0135.8856.7740.91