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

강우량(mm) has constant value ""Constant
저수위(m) is highly overall correlated with 저수량(백만m3) and 1 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 방류량(ms) and 3 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 유입량(ms) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
저수율 is highly overall correlated with 유입량(ms) and 3 other fieldsHigh correlation
댐이름 is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
유입량(ms) has 7 (7.0%) zerosZeros
방류량(ms) has 7 (7.0%) zerosZeros
저수율 has 7 (7.0%) zerosZeros

Reproduction

Analysis started2024-04-19 05:58:23.902230
Analysis finished2024-04-19 05:58:27.889749
Duration3.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

댐이름
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
군남
31 
한탄강
31 
평화의댐
31 
여주저류지
7 

Length

Max length5
Median length4
Mean length3.14
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군남 31
31.0%
한탄강 31
31.0%
평화의댐 31
31.0%
여주저류지 7
 
7.0%

Length

2024-04-19T14:58:27.956429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:58:28.062061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군남 31
31.0%
한탄강 31
31.0%
평화의댐 31
31.0%
여주저류지 7
 
7.0%

일자/시간(t)
Real number (ℝ)

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190116
Minimum20190101
Maximum20190131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:28.163688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190101
5-th percentile20190102
Q120190108
median20190116
Q320190124
95-th percentile20190130
Maximum20190131
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.9555355
Coefficient of variation (CV)4.4356038 × 10-7
Kurtosis-1.2055892
Mean20190116
Median Absolute Deviation (MAD)8
Skewness-0.024533469
Sum2.0190116 × 109
Variance80.201616
MonotonicityNot monotonic
2024-04-19T14:58:28.280248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20190117 4
 
4.0%
20190113 4
 
4.0%
20190123 4
 
4.0%
20190106 4
 
4.0%
20190125 4
 
4.0%
20190124 4
 
4.0%
20190102 4
 
4.0%
20190111 3
 
3.0%
20190131 3
 
3.0%
20190129 3
 
3.0%
Other values (21) 63
63.0%
ValueCountFrequency (%)
20190101 3
3.0%
20190102 4
4.0%
20190103 3
3.0%
20190104 3
3.0%
20190105 3
3.0%
20190106 4
4.0%
20190107 3
3.0%
20190108 3
3.0%
20190109 3
3.0%
20190110 3
3.0%
ValueCountFrequency (%)
20190131 3
3.0%
20190130 3
3.0%
20190129 3
3.0%
20190128 3
3.0%
20190127 3
3.0%
20190126 3
3.0%
20190125 4
4.0%
20190124 4
4.0%
20190123 4
4.0%
20190122 3
3.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.0652
Minimum25.54
Maximum174.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:28.419564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.54
5-th percentile25.629
Q125.7175
median47.215
Q3171.255
95-th percentile173.9305
Maximum174.27
Range148.73
Interquartile range (IQR)145.5375

Descriptive statistics

Standard deviation64.246537
Coefficient of variation (CV)0.82298562
Kurtosis-1.3444107
Mean78.0652
Median Absolute Deviation (MAD)21.515
Skewness0.77423479
Sum7806.52
Variance4127.6175
MonotonicityNot monotonic
2024-04-19T14:58:28.567207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.64 5
 
5.0%
25.74 4
 
4.0%
25.7 4
 
4.0%
25.6 3
 
3.0%
47.21 3
 
3.0%
47.36 3
 
3.0%
25.71 3
 
3.0%
28.34 3
 
3.0%
28.33 2
 
2.0%
25.67 2
 
2.0%
Other values (60) 68
68.0%
ValueCountFrequency (%)
25.54 1
 
1.0%
25.6 3
3.0%
25.61 1
 
1.0%
25.63 2
 
2.0%
25.64 5
5.0%
25.66 2
 
2.0%
25.67 2
 
2.0%
25.69 2
 
2.0%
25.7 4
4.0%
25.71 3
3.0%
ValueCountFrequency (%)
174.27 1
1.0%
174.17 1
1.0%
174.05 1
1.0%
173.95 1
1.0%
173.94 1
1.0%
173.93 1
1.0%
173.77 1
1.0%
173.6 1
1.0%
173.43 1
1.0%
173.25 1
1.0%

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

2024-04-19T14:58:28.695900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:58:28.778680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.31842
Minimum0
Maximum46.398
Zeros7
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:28.880273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.659
median11.6745
Q318.47125
95-th percentile34.76755
Maximum46.398
Range46.398
Interquartile range (IQR)12.81225

Descriptive statistics

Standard deviation10.038533
Coefficient of variation (CV)0.75373304
Kurtosis0.94838836
Mean13.31842
Median Absolute Deviation (MAD)6.099
Skewness1.1072221
Sum1331.842
Variance100.77215
MonotonicityNot monotonic
2024-04-19T14:58:29.014528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7
 
7.0%
12.242 1
 
1.0%
4.725 1
 
1.0%
18.348 1
 
1.0%
20.628 1
 
1.0%
38.156 1
 
1.0%
19.175 1
 
1.0%
23.897 1
 
1.0%
46.398 1
 
1.0%
18.461 1
 
1.0%
Other values (84) 84
84.0%
ValueCountFrequency (%)
0.0 7
7.0%
3.275 1
 
1.0%
3.498 1
 
1.0%
3.503 1
 
1.0%
3.516 1
 
1.0%
4.252 1
 
1.0%
4.529 1
 
1.0%
4.725 1
 
1.0%
4.767 1
 
1.0%
5.367 1
 
1.0%
ValueCountFrequency (%)
46.398 1
1.0%
40.199 1
1.0%
38.302 1
1.0%
38.156 1
1.0%
35.899 1
1.0%
34.708 1
1.0%
34.148 1
1.0%
29.035 1
1.0%
28.603 1
1.0%
27.967 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.62187
Minimum0
Maximum46.016
Zeros7
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:29.162179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.68125
median11.7925
Q323.48725
95-th percentile39.85085
Maximum46.016
Range46.016
Interquartile range (IQR)17.806

Descriptive statistics

Standard deviation11.616544
Coefficient of variation (CV)0.79446361
Kurtosis0.053630354
Mean14.62187
Median Absolute Deviation (MAD)6.135
Skewness0.97487838
Sum1462.187
Variance134.94409
MonotonicityNot monotonic
2024-04-19T14:58:29.315655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7
 
7.0%
5.697 2
 
2.0%
12.821 1
 
1.0%
3.653 1
 
1.0%
24.39 1
 
1.0%
26.913 1
 
1.0%
42.056 1
 
1.0%
25.332 1
 
1.0%
30.263 1
 
1.0%
46.016 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
0.0 7
7.0%
3.653 1
 
1.0%
3.655 1
 
1.0%
3.672 1
 
1.0%
3.715 1
 
1.0%
4.217 1
 
1.0%
4.274 1
 
1.0%
5.184 1
 
1.0%
5.211 1
 
1.0%
5.476 1
 
1.0%
ValueCountFrequency (%)
46.016 1
1.0%
42.955 1
1.0%
42.056 1
1.0%
41.537 1
1.0%
40.494 1
1.0%
39.817 1
1.0%
38.488 1
1.0%
35.389 1
1.0%
34.402 1
1.0%
32.031 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct69
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.86848
Minimum0.009
Maximum23.381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:29.452096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.009
5-th percentile0.009
Q10.50075
median3.5375
Q314.38475
95-th percentile22.24665
Maximum23.381
Range23.372
Interquartile range (IQR)13.884

Descriptive statistics

Standard deviation7.9042278
Coefficient of variation (CV)1.1507972
Kurtosis-0.81586722
Mean6.86848
Median Absolute Deviation (MAD)3.043
Skewness0.91856659
Sum686.848
Variance62.476817
MonotonicityNot monotonic
2024-04-19T14:58:29.608735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.009 7
 
7.0%
3.505 4
 
4.0%
3.634 4
 
4.0%
3.582 4
 
4.0%
0.5 4
 
4.0%
3.595 3
 
3.0%
3.6 2
 
2.0%
0.517 2
 
2.0%
3.544 2
 
2.0%
0.516 2
 
2.0%
Other values (59) 66
66.0%
ValueCountFrequency (%)
0.009 7
7.0%
0.425 1
 
1.0%
0.44 1
 
1.0%
0.453 1
 
1.0%
0.462 1
 
1.0%
0.465 1
 
1.0%
0.478 1
 
1.0%
0.481 1
 
1.0%
0.486 1
 
1.0%
0.491 1
 
1.0%
ValueCountFrequency (%)
23.381 1
1.0%
23.044 1
1.0%
22.642 1
1.0%
22.311 1
1.0%
22.278 1
1.0%
22.245 1
1.0%
22.1 1
1.0%
21.5 1
1.0%
20.631 1
1.0%
20.066 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.817
Minimum0
Maximum5.1
Zeros7
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-19T14:58:29.711593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median0.6
Q34.9
95-th percentile5
Maximum5.1
Range5.1
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation2.1303509
Coefficient of variation (CV)1.1724551
Kurtosis-1.3351877
Mean1.817
Median Absolute Deviation (MAD)0.4
Skewness0.7948292
Sum181.7
Variance4.5383949
MonotonicityNot monotonic
2024-04-19T14:58:29.820744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.2 31
31.0%
5.0 15
15.0%
0.6 9
 
9.0%
4.9 8
 
8.0%
0.0 7
 
7.0%
0.7 6
 
6.0%
0.8 6
 
6.0%
0.9 6
 
6.0%
5.1 4
 
4.0%
0.5 4
 
4.0%
Other values (2) 4
 
4.0%
ValueCountFrequency (%)
0.0 7
 
7.0%
0.2 31
31.0%
0.5 4
 
4.0%
0.6 9
 
9.0%
0.7 6
 
6.0%
0.8 6
 
6.0%
0.9 6
 
6.0%
4.7 1
 
1.0%
4.8 3
 
3.0%
4.9 8
 
8.0%
ValueCountFrequency (%)
5.1 4
 
4.0%
5.0 15
15.0%
4.9 8
8.0%
4.8 3
 
3.0%
4.7 1
 
1.0%
0.9 6
 
6.0%
0.8 6
 
6.0%
0.7 6
 
6.0%
0.6 9
9.0%
0.5 4
 
4.0%

Interactions

2024-04-19T14:58:27.165382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.148228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.756673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.370394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.156464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.627894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.271146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.236032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.853115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.776852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.233674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.710229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.365936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.352552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.969618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.859706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.320999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.826284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.438943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.445701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.052598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.931813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.390145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.909236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.516676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.583543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.158772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.004128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.461318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.987731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.589287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:24.670813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:25.282864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.078930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:26.538778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:58:27.085680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:58:29.919569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
댐이름일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
댐이름1.0000.0001.0000.9270.9360.8680.871
일자/시간(t)0.0001.0000.0000.2420.4720.4910.000
저수위(m)1.0000.0001.0000.9110.9220.9030.986
유입량(ms)0.9270.2420.9111.0000.9750.8640.927
방류량(ms)0.9360.4720.9220.9751.0000.8860.930
저수량(백만m3)0.8680.4910.9030.8640.8861.0001.000
저수율0.8710.0000.9860.9270.9301.0001.000
2024-04-19T14:58:30.033049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
일자/시간(t)1.000-0.155-0.249-0.232-0.162-0.1140.000
저수위(m)-0.1551.0000.4470.4400.507-0.3270.995
유입량(ms)-0.2490.4471.0000.9740.9570.6200.806
방류량(ms)-0.2320.4400.9741.0000.9400.5930.821
저수량(백만m3)-0.1620.5070.9570.9401.0000.6180.791
저수율-0.114-0.3270.6200.5930.6181.0000.939
댐이름0.0000.9950.8060.8210.7910.9391.000

Missing values

2024-04-19T14:58:27.695128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:58:27.834214image/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
0군남2019010825.6012.24212.8213.65.0
1군남2019012625.67010.6269.5963.5445.0
2군남2019011325.64012.43511.8563.5054.9
3군남2019012025.63012.20913.393.4934.9
4군남2019010425.74013.79613.1943.6345.1
5군남2019010525.74014.13714.1373.6345.1
6군남2019012525.6010.12112.1933.4554.8
7군남2019011025.61013.57214.9033.4674.8
8군남2019010325.7013.09412.9553.5825.0
9군남2019011725.67012.17412.0243.5445.0
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90평화의댐20190112173.1028.60327.53819.6020.8
91평화의댐20190110173.25025.49232.03120.0660.8
92평화의댐20190111173.07027.96734.40219.510.7
93여주저류지2019011728.3300.00.00.0090.0
94여주저류지2019011328.3400.00.00.0090.0
95여주저류지2019010628.3400.00.00.0090.0
96여주저류지2019010228.3400.00.00.0090.0
97여주저류지2019012528.3200.00.00.0090.0
98여주저류지2019012428.3200.00.00.0090.0
99여주저류지2019012328.3300.00.00.0090.0