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
일자/시간(t) is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
저수위(m) 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 일자/시간(t) and 4 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
강우량(mm) is highly imbalanced (67.7%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:23:16.424512
Analysis finished2023-12-10 10:23:22.440168
Duration6.02 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

2023-12-10T19:23:22.524080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:22.644168image/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%
Mean2.0220826 × 109
Minimum2.0220819 × 109
Maximum2.0220831 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:22.826466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0220819 × 109
5-th percentile2.0220819 × 109
Q12.022082 × 109
median2.0220829 × 109
Q32.022083 × 109
95-th percentile2.0220831 × 109
Maximum2.0220831 × 109
Range1205
Interquartile range (IQR)1003.5

Descriptive statistics

Standard deviation498.57584
Coefficient of variation (CV)2.4656551 × 10-7
Kurtosis-1.7319384
Mean2.0220826 × 109
Median Absolute Deviation (MAD)190
Skewness-0.47307181
Sum2.0220826 × 1011
Variance248577.87
MonotonicityNot monotonic
2023-12-10T19:23:23.060167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022083024 1
 
1.0%
2022082105 1
 
1.0%
2022082010 1
 
1.0%
2022082013 1
 
1.0%
2022082014 1
 
1.0%
2022082016 1
 
1.0%
2022082017 1
 
1.0%
2022082021 1
 
1.0%
2022082022 1
 
1.0%
2022082024 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2022081919 1
1.0%
2022081920 1
1.0%
2022081921 1
1.0%
2022081922 1
1.0%
2022081923 1
1.0%
2022081924 1
1.0%
2022082001 1
1.0%
2022082002 1
1.0%
2022082003 1
1.0%
2022082004 1
1.0%
ValueCountFrequency (%)
2022083124 1
1.0%
2022083123 1
1.0%
2022083122 1
1.0%
2022083121 1
1.0%
2022083120 1
1.0%
2022083119 1
1.0%
2022083118 1
1.0%
2022083117 1
1.0%
2022083116 1
1.0%
2022083115 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.8802
Minimum23.57
Maximum25.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:23.302690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.57
5-th percentile23.57
Q123.58
median23.615
Q324.1685
95-th percentile24.75225
Maximum25.15
Range1.58
Interquartile range (IQR)0.5885

Descriptive statistics

Standard deviation0.42051431
Coefficient of variation (CV)0.017609329
Kurtosis1.1849166
Mean23.8802
Median Absolute Deviation (MAD)0.045
Skewness1.3797585
Sum2388.02
Variance0.17683228
MonotonicityNot monotonic
2023-12-10T19:23:23.554255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
23.61 16
16.0%
23.57 14
14.0%
23.62 12
 
12.0%
23.58 12
 
12.0%
23.6 4
 
4.0%
23.59 3
 
3.0%
24.31 2
 
2.0%
24.3 2
 
2.0%
23.99 2
 
2.0%
23.98 2
 
2.0%
Other values (30) 31
31.0%
ValueCountFrequency (%)
23.57 14
14.0%
23.58 12
12.0%
23.59 3
 
3.0%
23.6 4
 
4.0%
23.608 1
 
1.0%
23.61 16
16.0%
23.62 12
12.0%
23.98 2
 
2.0%
23.99 2
 
2.0%
24.0 1
 
1.0%
ValueCountFrequency (%)
25.15 1
1.0%
25.136 1
1.0%
25.129 1
1.0%
25.034 1
1.0%
24.89 1
1.0%
24.745 1
1.0%
24.607 1
1.0%
24.52 1
1.0%
24.464 1
1.0%
24.41 1
1.0%

강우량(mm)
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
87 
1
 
8
2
 
3
5
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 87
87.0%
1 8
 
8.0%
2 3
 
3.0%
5 1
 
1.0%
3 1
 
1.0%

Length

2023-12-10T19:23:23.781212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:23.950280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 87
87.0%
1 8
 
8.0%
2 3
 
3.0%
5 1
 
1.0%
3 1
 
1.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)55.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.25313
Minimum51.397
Maximum378.969
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:24.132597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.397
5-th percentile51.8
Q154.158
median59.915
Q3168.46825
95-th percentile289.18395
Maximum378.969
Range327.572
Interquartile range (IQR)114.31025

Descriptive statistics

Standard deviation85.383037
Coefficient of variation (CV)0.75391326
Kurtosis1.4864365
Mean113.25313
Median Absolute Deviation (MAD)8.115
Skewness1.4590384
Sum11325.313
Variance7290.263
MonotonicityNot monotonic
2023-12-10T19:23:24.357319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58.8 14
 
14.0%
51.8 13
 
13.0%
60.9 11
 
11.0%
53.9 10
 
10.0%
56.7 2
 
2.0%
203.0 1
 
1.0%
129.161 1
 
1.0%
131.036 1
 
1.0%
139.114 1
 
1.0%
142.768 1
 
1.0%
Other values (45) 45
45.0%
ValueCountFrequency (%)
51.397 1
 
1.0%
51.8 13
13.0%
53.404 1
 
1.0%
53.9 10
10.0%
54.244 1
 
1.0%
55.014 1
 
1.0%
55.3 1
 
1.0%
55.931 1
 
1.0%
56.006 1
 
1.0%
56.7 2
 
2.0%
ValueCountFrequency (%)
378.969 1
1.0%
374.636 1
1.0%
374.447 1
1.0%
349.366 1
1.0%
317.322 1
1.0%
287.703 1
1.0%
259.211 1
1.0%
242.661 1
1.0%
233.78 1
1.0%
221.319 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.71649
Minimum51.8
Maximum376.775
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:24.607045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum51.8
5-th percentile51.8
Q153.9
median59.4475
Q3172.7045
95-th percentile309.93375
Maximum376.775
Range324.975
Interquartile range (IQR)118.8045

Descriptive statistics

Standard deviation87.691154
Coefficient of variation (CV)0.76441629
Kurtosis1.3446082
Mean114.71649
Median Absolute Deviation (MAD)7.6475
Skewness1.4437025
Sum11471.649
Variance7689.7385
MonotonicityNot monotonic
2023-12-10T19:23:24.806628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58.8 15
 
15.0%
51.8 13
 
13.0%
60.9 11
 
11.0%
53.9 10
 
10.0%
56.7 2
 
2.0%
203.0 1
 
1.0%
132.23 1
 
1.0%
141.225 1
 
1.0%
145.157 1
 
1.0%
156.345 1
 
1.0%
Other values (44) 44
44.0%
ValueCountFrequency (%)
51.8 13
13.0%
52.348 1
 
1.0%
52.453 1
 
1.0%
53.188 1
 
1.0%
53.9 10
10.0%
54.903 1
 
1.0%
55.3 1
 
1.0%
55.93 1
 
1.0%
56.07 1
 
1.0%
56.7 2
 
2.0%
ValueCountFrequency (%)
376.775 1
1.0%
375.747 1
1.0%
368.197 1
1.0%
364.838 1
1.0%
338.6 1
1.0%
308.425 1
1.0%
278.322 1
1.0%
254.383 1
1.0%
241.197 1
1.0%
228.375 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.79745
Minimum0.6664
Maximum1.3972
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:25.024614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6664
5-th percentile0.6664
Q10.6702
median0.68335
Q30.90985
95-th percentile1.18633
Maximum1.3972
Range0.7308
Interquartile range (IQR)0.23965

Descriptive statistics

Standard deviation0.18543134
Coefficient of variation (CV)0.23253036
Kurtosis2.0929149
Mean0.79745
Median Absolute Deviation (MAD)0.01695
Skewness1.5907266
Sum79.745
Variance0.03438478
MonotonicityNot monotonic
2023-12-10T19:23:25.302036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0.6815 16
16.0%
0.6664 14
14.0%
0.6852 12
 
12.0%
0.6702 12
 
12.0%
0.6777 4
 
4.0%
0.6739 3
 
3.0%
0.9733 2
 
2.0%
0.9687 2
 
2.0%
0.833 2
 
2.0%
0.8288 2
 
2.0%
Other values (30) 31
31.0%
ValueCountFrequency (%)
0.6664 14
14.0%
0.6702 12
12.0%
0.6739 3
 
3.0%
0.6777 4
 
4.0%
0.6807 1
 
1.0%
0.6815 16
16.0%
0.6852 12
12.0%
0.8288 2
 
2.0%
0.833 2
 
2.0%
0.8372 1
 
1.0%
ValueCountFrequency (%)
1.3972 1
1.0%
1.3895 1
1.0%
1.3856 1
1.0%
1.3338 1
1.0%
1.2572 1
1.0%
1.1826 1
1.0%
1.1138 1
1.0%
1.0716 1
1.0%
1.0449 1
1.0%
1.0195 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.127
Minimum0.9
Maximum2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:25.558877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile0.9
Q10.9
median1
Q31.3
95-th percentile1.705
Maximum2
Range1.1
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.26585293
Coefficient of variation (CV)0.23589434
Kurtosis1.6583941
Mean1.127
Median Absolute Deviation (MAD)0.1
Skewness1.4406325
Sum112.7
Variance0.070677778
MonotonicityNot monotonic
2023-12-10T19:23:25.739136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1.0 33
33.0%
0.9 29
29.0%
1.4 12
 
12.0%
1.2 11
 
11.0%
1.3 6
 
6.0%
1.9 3
 
3.0%
1.5 2
 
2.0%
1.8 1
 
1.0%
2.0 1
 
1.0%
1.6 1
 
1.0%
ValueCountFrequency (%)
0.9 29
29.0%
1.0 33
33.0%
1.2 11
 
11.0%
1.3 6
 
6.0%
1.4 12
 
12.0%
1.5 2
 
2.0%
1.6 1
 
1.0%
1.7 1
 
1.0%
1.8 1
 
1.0%
1.9 3
 
3.0%
ValueCountFrequency (%)
2.0 1
 
1.0%
1.9 3
 
3.0%
1.8 1
 
1.0%
1.7 1
 
1.0%
1.6 1
 
1.0%
1.5 2
 
2.0%
1.4 12
 
12.0%
1.3 6
 
6.0%
1.2 11
 
11.0%
1.0 33
33.0%

Interactions

2023-12-10T19:23:21.244944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:16.681056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.560973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.396589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.227797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.365184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.377037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:16.799235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.727154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.521930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.360826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.527709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.518273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:16.936148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.879806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.683864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.516576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.681606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.659210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.048682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.019448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.819290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.661664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.824751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.800273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.180655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.149769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.962445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.797036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.967157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.954826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:17.335290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:18.285419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:19.103541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:20.233267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:21.104586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:23:25.892961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.8860.0280.8510.8670.8360.836
저수위(m)0.8861.0000.0000.9961.0000.9920.992
강우량(mm)0.0280.0001.0000.0000.0000.0000.000
유입량(ms)0.8510.9960.0001.0000.9960.9990.998
방류량(ms)0.8671.0000.0000.9961.0000.9930.993
저수량(백만m3)0.8360.9920.0000.9990.9931.0001.000
저수율0.8360.9920.0000.9980.9931.0001.000
2023-12-10T19:23:26.110315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율강우량(mm)
일자/시간(t)1.000-0.615-0.617-0.613-0.615-0.6250.000
저수위(m)-0.6151.0000.9980.9981.0000.9730.000
유입량(ms)-0.6170.9981.0000.9960.9980.9710.000
방류량(ms)-0.6130.9980.9961.0000.9980.9710.000
저수량(백만m3)-0.6151.0000.9980.9981.0000.9730.000
저수율-0.6250.9730.9710.9710.9731.0000.000
강우량(mm)0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-10T19:23:22.167031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:23:22.357630image/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
0군남202208302423.62060.960.90.68521.0
1군남202208291323.58053.953.90.67020.9
2군남202208200224.520242.661254.3831.07161.5
3군남202208310123.62060.960.90.68521.0
4군남202208300523.57051.851.80.66640.9
5군남202208291423.58053.953.90.67020.9
6군남202208201824.230182.007185.7570.93711.3
7군남202208200324.4640233.78241.1971.04491.5
8군남202208311723.61058.858.80.68151.0
9군남202208310223.62060.960.90.68521.0
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202208310923.61058.858.80.68151.0
91군남202208310823.61058.858.80.68151.0
92군남202208310623.61058.08759.1150.68151.0
93군남202208310523.62060.960.90.68521.0
94군남202208302323.62060.960.90.68521.0
95군남202208302223.62060.960.90.68521.0
96군남202208302023.62060.960.90.68521.0
97군남202208301923.62060.960.90.68521.0
98군남202208291123.57051.851.80.66640.9
99군남202208291223.58054.24453.1880.67020.9