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 2 other fieldsHigh correlation
저수위(m) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 방류량(ms) and 1 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 유입량(ms) and 1 other fieldsHigh correlation
저수량(백만m3) 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
강우량(mm) is highly overall correlated with 유입량(ms) and 1 other fieldsHigh correlation
강우량(mm) is highly imbalanced (82.2%)Imbalance
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:25:28.019611
Analysis finished2023-12-10 10:25:34.820796
Duration6.8 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

2023-12-10T19:25:34.930188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:35.092933image/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%
Mean2.0210423 × 109
Minimum2.0210416 × 109
Maximum2.021043 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:35.275075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210416 × 109
5-th percentile2.0210416 × 109
Q12.0210418 × 109
median2.0210423 × 109
Q32.0210425 × 109
95-th percentile2.021043 × 109
Maximum2.021043 × 109
Range1422
Interquartile range (IQR)711

Descriptive statistics

Standard deviation468.73047
Coefficient of variation (CV)2.3192512 × 10-7
Kurtosis-1.1423503
Mean2.0210423 × 109
Median Absolute Deviation (MAD)496
Skewness0.14305633
Sum2.0210423 × 1011
Variance219708.25
MonotonicityNot monotonic
2023-12-10T19:25:35.546942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2021042916 1
 
1.0%
2021042522 1
 
1.0%
2021042408 1
 
1.0%
2021042414 1
 
1.0%
2021042416 1
 
1.0%
2021042420 1
 
1.0%
2021042422 1
 
1.0%
2021042506 1
 
1.0%
2021042508 1
 
1.0%
2021042512 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2021041602 1
1.0%
2021041604 1
1.0%
2021041606 1
1.0%
2021041608 1
1.0%
2021041610 1
1.0%
2021041612 1
1.0%
2021041614 1
1.0%
2021041616 1
1.0%
2021041618 1
1.0%
2021041620 1
1.0%
ValueCountFrequency (%)
2021043024 1
1.0%
2021043022 1
1.0%
2021043020 1
1.0%
2021043018 1
1.0%
2021043016 1
1.0%
2021043014 1
1.0%
2021043012 1
1.0%
2021043010 1
1.0%
2021043008 1
1.0%
2021043006 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.3337
Minimum26.7
Maximum27.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:35.797343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26.7
5-th percentile26.769
Q127.35
median27.46
Q327.49
95-th percentile27.5205
Maximum27.54
Range0.84
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.26910497
Coefficient of variation (CV)0.0098451717
Kurtosis0.6894281
Mean27.3337
Median Absolute Deviation (MAD)0.05
Skewness-1.5632738
Sum2733.37
Variance0.072417485
MonotonicityNot monotonic
2023-12-10T19:25:36.006154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
27.48 12
 
12.0%
27.45 7
 
7.0%
27.51 7
 
7.0%
27.47 6
 
6.0%
27.49 6
 
6.0%
27.5 6
 
6.0%
27.52 5
 
5.0%
26.78 5
 
5.0%
27.53 4
 
4.0%
27.46 4
 
4.0%
Other values (24) 38
38.0%
ValueCountFrequency (%)
26.7 1
 
1.0%
26.71 1
 
1.0%
26.73 1
 
1.0%
26.74 1
 
1.0%
26.75 1
 
1.0%
26.77 1
 
1.0%
26.78 5
5.0%
26.79 3
3.0%
26.8 1
 
1.0%
26.81 1
 
1.0%
ValueCountFrequency (%)
27.54 1
 
1.0%
27.53 4
 
4.0%
27.52 5
5.0%
27.51 7
7.0%
27.5 6
6.0%
27.49 6
6.0%
27.48 12
12.0%
27.47 6
6.0%
27.46 4
 
4.0%
27.45 7
7.0%

강우량(mm)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
96 
1
 
2
4
 
2

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 96
96.0%
1 2
 
2.0%
4 2
 
2.0%

Length

2023-12-10T19:25:36.201154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:25:36.364426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
96.0%
1 2
 
2.0%
4 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct85
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.56905
Minimum17.322
Maximum55.913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:36.572752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.322
5-th percentile17.494
Q122.89075
median26.226
Q329.139
95-th percentile51.29615
Maximum55.913
Range38.591
Interquartile range (IQR)6.24825

Descriptive statistics

Standard deviation8.7085696
Coefficient of variation (CV)0.31588211
Kurtosis2.9843174
Mean27.56905
Median Absolute Deviation (MAD)3.326
Skewness1.7761752
Sum2756.905
Variance75.839185
MonotonicityNot monotonic
2023-12-10T19:25:36.824911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.4 5
 
5.0%
26.4 5
 
5.0%
22.911 2
 
2.0%
26.122 2
 
2.0%
17.711 2
 
2.0%
17.567 2
 
2.0%
17.494 2
 
2.0%
22.9 2
 
2.0%
20.889 2
 
2.0%
30.9 1
 
1.0%
Other values (75) 75
75.0%
ValueCountFrequency (%)
17.322 1
1.0%
17.35 1
1.0%
17.455 1
1.0%
17.467 1
1.0%
17.494 2
2.0%
17.522 1
1.0%
17.567 2
2.0%
17.711 2
2.0%
20.731 1
1.0%
20.889 2
2.0%
ValueCountFrequency (%)
55.913 1
1.0%
54.187 1
1.0%
53.563 1
1.0%
51.942 1
1.0%
51.717 1
1.0%
51.274 1
1.0%
48.596 1
1.0%
47.246 1
1.0%
44.546 1
1.0%
43.274 1
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.394873
Minimum15.87
Maximum58.493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:37.065280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.87
5-th percentile22.07
Q122.575
median25.7585
Q330.1205
95-th percentile55.6278
Maximum58.493
Range42.623
Interquartile range (IQR)7.5455

Descriptive statistics

Standard deviation9.278379
Coefficient of variation (CV)0.32676247
Kurtosis3.7375778
Mean28.394873
Median Absolute Deviation (MAD)3.3585
Skewness1.9893947
Sum2839.4873
Variance86.088316
MonotonicityNot monotonic
2023-12-10T19:25:37.644585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.3 6
 
6.0%
24.4 6
 
6.0%
26.4 5
 
5.0%
22.1 5
 
5.0%
22.9 4
 
4.0%
22.4 4
 
4.0%
27.8 3
 
3.0%
22.6 3
 
3.0%
24.9 3
 
3.0%
30.9 3
 
3.0%
Other values (53) 58
58.0%
ValueCountFrequency (%)
15.87 1
 
1.0%
16.0 2
 
2.0%
16.1 1
 
1.0%
21.5 1
 
1.0%
22.1 5
5.0%
22.15333333333333 1
 
1.0%
22.233 1
 
1.0%
22.3 6
6.0%
22.363 1
 
1.0%
22.4 4
4.0%
ValueCountFrequency (%)
58.493 1
1.0%
57.841 1
1.0%
57.318 1
1.0%
56.275 1
1.0%
56.023 1
1.0%
55.607 1
1.0%
51.552 1
1.0%
48.907 1
1.0%
43.274 1
1.0%
42.885 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.042336
Minimum5
Maximum6.392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:37.854808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.10745
Q16.061
median6.251
Q36.304
95-th percentile6.3579
Maximum6.392
Range1.392
Interquartile range (IQR)0.243

Descriptive statistics

Standard deviation0.44661914
Coefficient of variation (CV)0.07391498
Kurtosis0.65773555
Mean6.042336
Median Absolute Deviation (MAD)0.088
Skewness-1.5483865
Sum604.2336
Variance0.19946866
MonotonicityNot monotonic
2023-12-10T19:25:38.076519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
6.286 12
 
12.0%
6.234 7
 
7.0%
6.339 7
 
7.0%
6.269 6
 
6.0%
6.304 6
 
6.0%
6.322 6
 
6.0%
5.124 5
 
5.0%
6.357 5
 
5.0%
6.251 4
 
4.0%
6.375 4
 
4.0%
Other values (25) 38
38.0%
ValueCountFrequency (%)
5.0 1
 
1.0%
5.015 1
 
1.0%
5.046 1
 
1.0%
5.062 1
 
1.0%
5.078 1
 
1.0%
5.109 1
 
1.0%
5.124 5
5.0%
5.14 3
3.0%
5.156 1
 
1.0%
5.172 1
 
1.0%
ValueCountFrequency (%)
6.392 1
 
1.0%
6.375 4
 
4.0%
6.357 5
5.0%
6.339 7
7.0%
6.322 6
6.0%
6.304 6
6.0%
6.286 12
12.0%
6.269 6
6.0%
6.251 4
 
4.0%
6.234 7
7.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.4473
Minimum7
Maximum8.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:25:38.274811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7.1
Q18.4975
median8.7
Q38.8
95-th percentile8.9
Maximum8.9
Range1.9
Interquartile range (IQR)0.3025

Descriptive statistics

Standard deviation0.62122371
Coefficient of variation (CV)0.073541097
Kurtosis0.62175306
Mean8.4473
Median Absolute Deviation (MAD)0.1
Skewness-1.5285286
Sum844.73
Variance0.3859189
MonotonicityNot monotonic
2023-12-10T19:25:38.459393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8.8 30
30.0%
8.9 17
17.0%
8.7 14
14.0%
7.2 11
 
11.0%
8.6 8
 
8.0%
8.5 6
 
6.0%
8.4 5
 
5.0%
7.1 4
 
4.0%
7.0 2
 
2.0%
8.49 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
7.0 2
 
2.0%
7.1 4
 
4.0%
7.2 11
11.0%
7.3 1
 
1.0%
8.4 5
 
5.0%
8.44 1
 
1.0%
8.49 1
 
1.0%
8.5 6
6.0%
8.6 8
8.0%
8.7 14
14.0%
ValueCountFrequency (%)
8.9 17
17.0%
8.8 30
30.0%
8.7 14
14.0%
8.6 8
 
8.0%
8.5 6
 
6.0%
8.49 1
 
1.0%
8.44 1
 
1.0%
8.4 5
 
5.0%
7.3 1
 
1.0%
7.2 11
 
11.0%

Interactions

2023-12-10T19:25:33.389856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:28.690224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.743563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.616307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.631268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.507482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:33.548540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:28.874772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.910769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.786049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.792491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.664931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:33.690550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.010209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.022088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.923251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.937037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.805679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:33.918069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.226483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.182275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.085755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.080408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.954722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:34.099128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.373754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.301383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.233953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.202095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:33.084467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:34.293244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:29.551508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:30.451740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:31.415900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:32.354911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:25:33.242009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:25:38.620479image/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)1.0000.7820.0600.6560.7520.7790.779
저수위(m)0.7821.0000.3430.8260.9090.9980.987
강우량(mm)0.0600.3431.0000.7920.7850.3440.297
유입량(ms)0.6560.8260.7921.0000.9750.8190.889
방류량(ms)0.7520.9090.7850.9751.0000.9060.940
저수량(백만m3)0.7790.9980.3440.8190.9061.0000.996
저수율0.7790.9870.2970.8890.9400.9961.000
2023-12-10T19:25:38.838381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율강우량(mm)
일자/시간(t)1.000-0.8110.2570.336-0.811-0.7880.036
저수위(m)-0.8111.000-0.245-0.3231.0000.9830.273
유입량(ms)0.257-0.2451.0000.631-0.246-0.2650.653
방류량(ms)0.336-0.3230.6311.000-0.323-0.3390.644
저수량(백만m3)-0.8111.000-0.246-0.3231.0000.9830.274
저수율-0.7880.983-0.265-0.3390.9831.0000.231
강우량(mm)0.0360.2730.6530.6440.2740.2311.000

Missing values

2023-12-10T19:25:34.522797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:25:34.735059image/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
0군남202104291626.82025.71130.15.1877.2
1군남202104160627.46029.73324.96.2518.7
2군남202104231627.48022.622.66.2868.8
3군남202104291826.81030.130.15.1727.2
4군남202104171427.47027.76122.96.2698.8
5군남202104160827.47024.924.96.2698.8
6군남202104242427.38027.07822.36.1128.5
7군남202104231827.47022.522.56.2698.8
8군남202104221027.48028.46123.66.2868.8
9군남202104292026.8030.030.05.1567.2
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202104301026.78043.27443.2745.1247.2
91군남202104300826.78044.54648.9075.1247.2
92군남202104300426.78438.0438.045.1247.2
93군남202104300226.78436.536.55.1247.2
94군남202104291426.83025.79330.1825.2037.3
95군남202104182427.53024.424.46.3758.9
96군남202104182027.52024.424.46.3578.9
97군남202104181827.51024.424.46.3398.9
98군남202104160227.46029.829.86.2518.7
99군남202104160427.45023.29228.1256.2348.7