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

Categorical3
Numeric5

Alerts

댐이름 has constant value ""Constant
일자/시간(t) is highly overall correlated with 저수위(m) and 2 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 저수위(m) and 4 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수위(m) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 유입량(ms)High correlation
저수율 is highly overall correlated with 일자/시간(t) and 4 other fieldsHigh correlation
강우량(mm) is highly imbalanced (87.9%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:23:42.343079
Analysis finished2023-12-10 10:23:46.925492
Duration4.58 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

2023-12-10T19:23:47.037493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:47.193008image/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%
Mean2.0220607 × 109
Minimum2.0220601 × 109
Maximum2.0220612 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:47.708793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0220601 × 109
5-th percentile2.0220601 × 109
Q12.0220606 × 109
median2.0220607 × 109
Q32.0220609 × 109
95-th percentile2.0220612 × 109
Maximum2.0220612 × 109
Range1108
Interquartile range (IQR)333.75

Descriptive statistics

Standard deviation341.5066
Coefficient of variation (CV)1.6889038 × 10-7
Kurtosis-0.82018845
Mean2.0220607 × 109
Median Absolute Deviation (MAD)190.5
Skewness-0.41883794
Sum2.0220607 × 1011
Variance116626.76
MonotonicityNot monotonic
2023-12-10T19:23:47.957199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022060814 1
 
1.0%
2022060316 1
 
1.0%
2022060103 1
 
1.0%
2022060107 1
 
1.0%
2022060108 1
 
1.0%
2022060111 1
 
1.0%
2022060114 1
 
1.0%
2022060121 1
 
1.0%
2022060123 1
 
1.0%
2022060204 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2022060102 1
1.0%
2022060103 1
1.0%
2022060104 1
1.0%
2022060105 1
1.0%
2022060107 1
1.0%
2022060108 1
1.0%
2022060109 1
1.0%
2022060111 1
1.0%
2022060114 1
1.0%
2022060115 1
1.0%
ValueCountFrequency (%)
2022061210 1
1.0%
2022061209 1
1.0%
2022061208 1
1.0%
2022061207 1
1.0%
2022061205 1
1.0%
2022061202 1
1.0%
2022061124 1
1.0%
2022061123 1
1.0%
2022061120 1
1.0%
2022061119 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.25147
Minimum23.15
Maximum23.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:48.147860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.15
5-th percentile23.16
Q123.24
median23.26
Q323.2825
95-th percentile23.31
Maximum23.33
Range0.18
Interquartile range (IQR)0.0425

Descriptive statistics

Standard deviation0.046622155
Coefficient of variation (CV)0.0020051272
Kurtosis0.11882704
Mean23.25147
Median Absolute Deviation (MAD)0.02
Skewness-0.85282064
Sum2325.147
Variance0.0021736254
MonotonicityNot monotonic
2023-12-10T19:23:48.333072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
23.25 16
16.0%
23.16 15
15.0%
23.26 13
13.0%
23.29 12
12.0%
23.24 11
11.0%
23.28 7
7.0%
23.3 5
 
5.0%
23.27 5
 
5.0%
23.33 4
 
4.0%
23.31 3
 
3.0%
Other values (6) 9
9.0%
ValueCountFrequency (%)
23.15 1
 
1.0%
23.16 15
15.0%
23.23 3
 
3.0%
23.24 11
11.0%
23.25 16
16.0%
23.252 1
 
1.0%
23.255 1
 
1.0%
23.26 13
13.0%
23.266 2
 
2.0%
23.27 5
 
5.0%
ValueCountFrequency (%)
23.33 4
 
4.0%
23.31 3
 
3.0%
23.308 1
 
1.0%
23.3 5
 
5.0%
23.29 12
12.0%
23.28 7
7.0%
23.27 5
 
5.0%
23.266 2
 
2.0%
23.26 13
13.0%
23.255 1
 
1.0%

강우량(mm)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
97 
2
 
1
3
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row0
2nd row2
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 97
97.0%
2 1
 
1.0%
3 1
 
1.0%
5 1
 
1.0%

Length

2023-12-10T19:23:48.527653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:48.755514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 97
97.0%
2 1
 
1.0%
3 1
 
1.0%
5 1
 
1.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.38748
Minimum5.861
Maximum21.577
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:49.055952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.861
5-th percentile7
Q111.942
median14
Q315.04775
95-th percentile18.2197
Maximum21.577
Range15.716
Interquartile range (IQR)3.10575

Descriptive statistics

Standard deviation3.5542459
Coefficient of variation (CV)0.26549029
Kurtosis-0.24815236
Mean13.38748
Median Absolute Deviation (MAD)1.5995
Skewness-0.48066142
Sum1338.748
Variance12.632664
MonotonicityNot monotonic
2023-12-10T19:23:49.311013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
7.0 15
 
15.0%
14.0 13
 
13.0%
14.7 8
 
8.0%
17.5 7
 
7.0%
13.3 6
 
6.0%
15.0 3
 
3.0%
18.2 3
 
3.0%
13.5 2
 
2.0%
13.611 2
 
2.0%
12.6 2
 
2.0%
Other values (38) 39
39.0%
ValueCountFrequency (%)
5.861 1
 
1.0%
7.0 15
15.0%
8.911 1
 
1.0%
10.15 1
 
1.0%
10.5 1
 
1.0%
10.952 1
 
1.0%
11.0 1
 
1.0%
11.251 1
 
1.0%
11.566 1
 
1.0%
11.741 1
 
1.0%
ValueCountFrequency (%)
21.577 1
 
1.0%
19.402 1
 
1.0%
19.15 1
 
1.0%
19.103 1
 
1.0%
18.594 1
 
1.0%
18.2 3
3.0%
17.547 1
 
1.0%
17.5 7
7.0%
17.283 1
 
1.0%
16.825 1
 
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.37219
Minimum7
Maximum18.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:49.585131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7
Q112.80025
median14
Q314.9325
95-th percentile17.5
Maximum18.2
Range11.2
Interquartile range (IQR)2.13225

Descriptive statistics

Standard deviation3.2363127
Coefficient of variation (CV)0.24201815
Kurtosis0.026482994
Mean13.37219
Median Absolute Deviation (MAD)1.0615
Skewness-0.87271008
Sum1337.219
Variance10.47372
MonotonicityNot monotonic
2023-12-10T19:23:49.817175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
7.0 16
16.0%
14.0 15
15.0%
14.7 9
 
9.0%
17.5 7
 
7.0%
13.3 6
 
6.0%
18.2 3
 
3.0%
15.0 3
 
3.0%
12.0 2
 
2.0%
15.4 2
 
2.0%
13.5 2
 
2.0%
Other values (34) 35
35.0%
ValueCountFrequency (%)
7.0 16
16.0%
10.5 1
 
1.0%
10.883 1
 
1.0%
11.0 1
 
1.0%
12.0 2
 
2.0%
12.15 1
 
1.0%
12.5 1
 
1.0%
12.6 2
 
2.0%
12.867 1
 
1.0%
12.924 1
 
1.0%
ValueCountFrequency (%)
18.2 3
3.0%
17.605 1
 
1.0%
17.5 7
7.0%
17.283 1
 
1.0%
17.15 1
 
1.0%
17.103 1
 
1.0%
17.092 1
 
1.0%
17.033 1
 
1.0%
16.8 1
 
1.0%
16.345 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.152576
Minimum1.082
Maximum1.2084
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:50.016747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.082
5-th percentile1.0888
Q11.1443
median1.1583
Q31.1743
95-th percentile1.194
Maximum1.2084
Range0.1264
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.032659254
Coefficient of variation (CV)0.028335879
Kurtosis0.09559544
Mean1.152576
Median Absolute Deviation (MAD)0.0142
Skewness-0.82152118
Sum115.2576
Variance0.0010666269
MonotonicityNot monotonic
2023-12-10T19:23:50.253942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1.1513 16
16.0%
1.0888 15
15.0%
1.1583 13
13.0%
1.1797 12
12.0%
1.1443 11
11.0%
1.1725 7
7.0%
1.1868 5
 
5.0%
1.1654 5
 
5.0%
1.2084 4
 
4.0%
1.194 3
 
3.0%
Other values (6) 9
9.0%
ValueCountFrequency (%)
1.082 1
 
1.0%
1.0888 15
15.0%
1.1373 3
 
3.0%
1.1443 11
11.0%
1.1513 16
16.0%
1.1527 1
 
1.0%
1.1548 1
 
1.0%
1.1583 13
13.0%
1.1626 2
 
2.0%
1.1654 5
 
5.0%
ValueCountFrequency (%)
1.2084 4
 
4.0%
1.194 3
 
3.0%
1.1925 1
 
1.0%
1.1868 5
 
5.0%
1.1797 12
12.0%
1.1725 7
7.0%
1.1654 5
 
5.0%
1.1626 2
 
2.0%
1.1583 13
13.0%
1.1548 1
 
1.0%

저수율
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1.6
59 
1.7
25 
1.5
16 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.6
2nd row1.7
3rd row1.6
4th row1.6
5th row1.6

Common Values

ValueCountFrequency (%)
1.6 59
59.0%
1.7 25
25.0%
1.5 16
 
16.0%

Length

2023-12-10T19:23:50.475897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:50.627844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.6 59
59.0%
1.7 25
25.0%
1.5 16
 
16.0%

Interactions

2023-12-10T19:23:45.790101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:42.722934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.421423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.180337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.013745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.963689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:42.848418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.565843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.323035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.154758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:46.112268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:42.994305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.720290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.519522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.318187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:46.281436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.146791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.875513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.680423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.468333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:46.408844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:43.279166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.019149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:44.833713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:45.596205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:23:50.749458image/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)1.0000.7530.1590.6460.8450.7340.835
저수위(m)0.7531.0000.2210.7200.8120.9970.919
강우량(mm)0.1590.2211.0000.7570.0000.2210.068
유입량(ms)0.6460.7200.7571.0000.8270.7600.877
방류량(ms)0.8450.8120.0000.8271.0000.8480.886
저수량(백만m3)0.7340.9970.2210.7600.8481.0000.919
저수율0.8350.9190.0680.8770.8860.9191.000
2023-12-10T19:23:50.906096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량(mm)저수율
강우량(mm)1.0000.061
저수율0.0611.000
2023-12-10T19:23:51.065602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)강우량(mm)저수율
일자/시간(t)1.0000.5290.1910.1460.5290.0710.758
저수위(m)0.5291.0000.7480.6931.0000.1490.911
유입량(ms)0.1910.7481.0000.8640.7480.5490.783
방류량(ms)0.1460.6930.8641.0000.6930.0000.840
저수량(백만m3)0.5291.0000.7480.6931.0000.1490.911
강우량(mm)0.0710.1490.5490.0000.1491.0000.061
저수율0.7580.9110.7830.8400.9110.0611.000

Missing values

2023-12-10T19:23:46.595658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:23:46.835894image/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
0군남202206081423.252013.10914.6651.15271.6
1군남202206060623.3218.218.21.18681.7
2군남202206112423.2608.91110.8831.15831.6
3군남202206081523.25013.61114.01.15131.6
4군남202206071023.28015.03317.0331.17251.6
5군남202206060723.3018.218.21.18681.7
6군남202206011523.1607.07.01.08881.5
7군남202206120223.26010.510.51.15831.6
8군남202206102423.24013.313.31.14431.6
9군남202206081623.25014.014.01.15131.6
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202206090123.23012.612.61.13731.6
91군남202206082423.23011.25113.1951.13731.6
92군남202206082223.24011.74113.6851.14431.6
93군남202206082123.25014.014.01.15131.6
94군남202206081323.26012.84514.8171.15831.6
95군남202206081123.27014.37316.3451.16541.6
96군남202206080623.29017.517.51.17971.7
97군남202206080523.29019.1517.151.17971.7
98군남202206060323.266317.54714.4081.16261.6
99군남202206060523.3521.57717.6051.18681.7