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 3 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
저수율 is highly overall correlated with 일자/시간(t) and 3 other fieldsHigh correlation
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:30:32.213190
Analysis finished2023-12-10 10:30:40.136183
Duration7.92 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

2023-12-10T19:30:40.263281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:40.427263image/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%
Mean2.0190326 × 109
Minimum2.0190312 × 109
Maximum2.0190331 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:40.619266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190312 × 109
5-th percentile2.0190312 × 109
Q12.019032 × 109
median2.0190327 × 109
Q32.0190329 × 109
95-th percentile2.0190331 × 109
Maximum2.0190331 × 109
Range1912
Interquartile range (IQR)917

Descriptive statistics

Standard deviation533.94542
Coefficient of variation (CV)2.6445607 × 10-7
Kurtosis0.29366835
Mean2.0190326 × 109
Median Absolute Deviation (MAD)242
Skewness-1.1429143
Sum2.0190326 × 1011
Variance285097.71
MonotonicityNot monotonic
2023-12-10T19:30:40.932350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019032901 1
 
1.0%
2019032603 1
 
1.0%
2019031823 1
 
1.0%
2019031905 1
 
1.0%
2019031907 1
 
1.0%
2019031911 1
 
1.0%
2019031913 1
 
1.0%
2019031921 1
 
1.0%
2019031923 1
 
1.0%
2019032003 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019031211 1
1.0%
2019031213 1
1.0%
2019031215 1
1.0%
2019031217 1
1.0%
2019031219 1
1.0%
2019031221 1
1.0%
2019031815 1
1.0%
2019031817 1
1.0%
2019031819 1
1.0%
2019031821 1
1.0%
ValueCountFrequency (%)
2019033123 1
1.0%
2019033121 1
1.0%
2019033119 1
1.0%
2019033117 1
1.0%
2019033115 1
1.0%
2019033113 1
1.0%
2019033111 1
1.0%
2019033109 1
1.0%
2019033107 1
1.0%
2019033105 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

2023-12-10T19:30:41.185091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:30:41.382719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4676
Minimum3.57
Maximum7.836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:41.663805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.57
5-th percentile3.63335
Q14.73725
median6.935
Q37.464
95-th percentile7.816
Maximum7.836
Range4.266
Interquartile range (IQR)2.72675

Descriptive statistics

Standard deviation1.3449097
Coefficient of variation (CV)0.20794572
Kurtosis-0.63565598
Mean6.4676
Median Absolute Deviation (MAD)0.629
Skewness-0.93173577
Sum646.76
Variance1.8087821
MonotonicityNot monotonic
2023-12-10T19:30:41.913450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.625 6
 
6.0%
7.658 5
 
5.0%
7.836 4
 
4.0%
7.464 4
 
4.0%
6.935 4
 
4.0%
4.607 4
 
4.0%
7.254 3
 
3.0%
7.796 3
 
3.0%
6.917 3
 
3.0%
7.273 3
 
3.0%
Other values (46) 61
61.0%
ValueCountFrequency (%)
3.57 1
1.0%
3.582 2
2.0%
3.608 1
1.0%
3.621 1
1.0%
3.634 1
1.0%
4.402 2
2.0%
4.431 2
2.0%
4.445 1
1.0%
4.46 1
1.0%
4.475 1
1.0%
ValueCountFrequency (%)
7.836 4
4.0%
7.816 2
 
2.0%
7.796 3
3.0%
7.776 1
 
1.0%
7.717 1
 
1.0%
7.658 5
5.0%
7.639 1
 
1.0%
7.619 3
3.0%
7.6 1
 
1.0%
7.58 1
 
1.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.037
Minimum5
Maximum10.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:42.118088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.1
Q16.575
median9.7
Q310.4
95-th percentile10.9
Maximum10.9
Range5.9
Interquartile range (IQR)3.825

Descriptive statistics

Standard deviation1.8765784
Coefficient of variation (CV)0.20765502
Kurtosis-0.63161716
Mean9.037
Median Absolute Deviation (MAD)0.9
Skewness-0.93969258
Sum903.7
Variance3.5215465
MonotonicityNot monotonic
2023-12-10T19:30:42.364342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
10.9 10
 
10.0%
10.4 9
 
9.0%
9.7 8
 
8.0%
9.3 8
 
8.0%
10.1 7
 
7.0%
10.7 6
 
6.0%
6.4 6
 
6.0%
6.2 6
 
6.0%
6.5 5
 
5.0%
10.6 5
 
5.0%
Other values (17) 30
30.0%
ValueCountFrequency (%)
5.0 4
4.0%
5.1 2
 
2.0%
6.2 6
6.0%
6.3 2
 
2.0%
6.4 6
6.0%
6.5 5
5.0%
6.6 1
 
1.0%
8.8 3
3.0%
9.0 1
 
1.0%
9.1 1
 
1.0%
ValueCountFrequency (%)
10.9 10
10.0%
10.8 1
 
1.0%
10.7 6
6.0%
10.6 5
5.0%
10.5 2
 
2.0%
10.4 9
9.0%
10.3 1
 
1.0%
10.2 4
 
4.0%
10.1 7
7.0%
10.0 1
 
1.0%

방류량(ms)
Real number (ℝ)

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.39366
Minimum0
Maximum30.056
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:42.627317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5486
Q15.6
median5.9
Q310.89175
95-th percentile20.69875
Maximum30.056
Range30.056
Interquartile range (IQR)5.29175

Descriptive statistics

Standard deviation5.8186815
Coefficient of variation (CV)0.69322339
Kurtosis1.9360202
Mean8.39366
Median Absolute Deviation (MAD)0.5
Skewness1.3221506
Sum839.366
Variance33.857054
MonotonicityNot monotonic
2023-12-10T19:30:42.907680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.9 14
 
14.0%
6.0 8
 
8.0%
5.5 8
 
8.0%
5.8 6
 
6.0%
5.7 6
 
6.0%
5.6 5
 
5.0%
5.4 4
 
4.0%
10.839 2
 
2.0%
0.483 2
 
2.0%
11.261 2
 
2.0%
Other values (43) 43
43.0%
ValueCountFrequency (%)
0.0 1
1.0%
0.483 2
2.0%
0.5 1
1.0%
0.522 1
1.0%
0.55 1
1.0%
0.561 1
1.0%
0.6 1
1.0%
1.344 1
1.0%
1.372 1
1.0%
1.389 1
1.0%
ValueCountFrequency (%)
30.056 1
1.0%
26.394 1
1.0%
22.15 1
1.0%
22.078 1
1.0%
21.511 1
1.0%
20.656 1
1.0%
17.778 1
1.0%
16.889 1
1.0%
16.761 1
1.0%
16.706 1
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.02851
Minimum5.4
Maximum14.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:43.120141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.4
5-th percentile5.4
Q15.6
median5.8
Q35.9
95-th percentile8.2
Maximum14.89
Range9.49
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation1.3369745
Coefficient of variation (CV)0.22177529
Kurtosis24.448606
Mean6.02851
Median Absolute Deviation (MAD)0.2
Skewness4.75109
Sum602.851
Variance1.7875009
MonotonicityNot monotonic
2023-12-10T19:30:43.306945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5.9 23
23.0%
5.5 16
16.0%
5.8 12
12.0%
5.7 12
12.0%
5.6 12
12.0%
6.0 11
11.0%
5.4 7
 
7.0%
11.2 2
 
2.0%
8.2 2
 
2.0%
10.883 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
5.4 7
 
7.0%
5.5 16
16.0%
5.578 1
 
1.0%
5.6 12
12.0%
5.7 12
12.0%
5.8 12
12.0%
5.9 23
23.0%
6.0 11
11.0%
8.2 2
 
2.0%
10.883 1
 
1.0%
ValueCountFrequency (%)
14.89 1
 
1.0%
11.2 2
 
2.0%
10.883 1
 
1.0%
8.2 2
 
2.0%
6.0 11
11.0%
5.9 23
23.0%
5.8 12
12.0%
5.7 12
12.0%
5.6 12
12.0%
5.578 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.5337
Minimum25.69
Maximum28.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:30:43.536931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25.69
5-th percentile25.7395
Q126.5275
median27.84
Q328.12
95-th percentile28.3
Maximum28.31
Range2.62
Interquartile range (IQR)1.5925

Descriptive statistics

Standard deviation0.80911681
Coefficient of variation (CV)0.029386418
Kurtosis-0.41329294
Mean27.5337
Median Absolute Deviation (MAD)0.34
Skewness-1.0311167
Sum2753.37
Variance0.65467001
MonotonicityNot monotonic
2023-12-10T19:30:43.805187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.67 6
 
6.0%
28.22 5
 
5.0%
28.31 4
 
4.0%
28.12 4
 
4.0%
27.84 4
 
4.0%
26.44 4
 
4.0%
28.01 3
 
3.0%
28.29 3
 
3.0%
27.83 3
 
3.0%
28.02 3
 
3.0%
Other values (46) 61
61.0%
ValueCountFrequency (%)
25.69 1
1.0%
25.7 2
2.0%
25.72 1
1.0%
25.73 1
1.0%
25.74 1
1.0%
26.3 2
2.0%
26.32 2
2.0%
26.33 1
1.0%
26.34 1
1.0%
26.35 1
1.0%
ValueCountFrequency (%)
28.31 4
4.0%
28.3 2
 
2.0%
28.29 3
3.0%
28.28 1
 
1.0%
28.25 1
 
1.0%
28.22 5
5.0%
28.21 1
 
1.0%
28.2 3
3.0%
28.19 1
 
1.0%
28.18 1
 
1.0%

Interactions

2023-12-10T19:30:38.238105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:32.601855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:33.788535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.997843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.258029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.285142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:38.372801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:32.785820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.059042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:35.177247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.450665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.465970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:38.872115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:32.946082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.306396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:35.379237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.620873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.624038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:39.020783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:33.150038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.475671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:35.638790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.803647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.796557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:39.192988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:33.331739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.653939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:35.829637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.977886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.955518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:39.359613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:33.517095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:34.810875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:36.007682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:37.132209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:30:38.097671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:30:43.975234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9780.9280.5490.6750.988
강우량(mm)0.9781.0000.9820.5110.6090.978
유입량(ms)0.9280.9821.0000.5710.5990.930
방류량(ms)0.5490.5110.5711.0000.7680.539
저수량(백만m3)0.6750.6090.5990.7681.0000.609
저수율0.9880.9780.9300.5390.6091.000
2023-12-10T19:30:44.198775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9930.9950.1070.6440.993
강우량(mm)0.9931.0000.9980.1280.6451.000
유입량(ms)0.9950.9981.0000.1180.6460.998
방류량(ms)0.1070.1280.1181.0000.2080.128
저수량(백만m3)0.6440.6450.6460.2081.0000.645
저수율0.9931.0000.9980.1280.6451.000

Missing values

2023-12-10T19:30:39.742994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:30:40.045394image/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
0군남201903290107.25410.111.055.828.01
1군남201903121503.6085.07.58911.225.72
2군남201903311707.83610.96.06.028.31
3군남201903290307.3310.211.1065.828.05
4군남201903271106.9179.75.75.727.83
5군남201903121703.5825.07.27210.88325.7
6군남201903191504.6366.55.55.526.46
7군남201903311907.81610.96.06.028.3
8군남201903301107.65810.75.95.928.22
9군남201903290507.38710.35.95.928.08
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남201903291907.46410.45.95.928.12
91군남201903291707.48410.55.95.928.13
92군남201903291307.46410.45.95.928.12
93군남201903291107.46410.45.95.928.12
94군남201903282307.21610.15.85.827.99
95군남201903282107.23510.10.555.828.0
96군남201903281707.27310.25.85.828.02
97군남201903281507.27310.25.85.828.02
98군남201903121103.6345.114.8914.8925.74
99군남201903121303.6215.111.211.225.73