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 4 other fieldsHigh correlation
강우량(mm) 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
일자/시간(t) has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:26:50.287083
Analysis finished2023-12-10 10:26:57.068258
Duration6.78 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

2023-12-10T19:26:57.177970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:26:57.315169image/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%
Mean2.0200926 × 109
Minimum2.020091 × 109
Maximum2.020093 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:57.488377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.020091 × 109
5-th percentile2.0200923 × 109
Q12.0200924 × 109
median2.0200926 × 109
Q32.0200928 × 109
95-th percentile2.020093 × 109
Maximum2.020093 × 109
Range2012
Interquartile range (IQR)403

Descriptive statistics

Standard deviation381.94155
Coefficient of variation (CV)1.8907131 × 10-7
Kurtosis7.3418647
Mean2.0200926 × 109
Median Absolute Deviation (MAD)202
Skewness-2.2687558
Sum2.0200926 × 1011
Variance145879.35
MonotonicityNot monotonic
2023-12-10T19:26:57.735741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2020092524 1
 
1.0%
2020093022 1
 
1.0%
2020092908 1
 
1.0%
2020092914 1
 
1.0%
2020092916 1
 
1.0%
2020092920 1
 
1.0%
2020092922 1
 
1.0%
2020093006 1
 
1.0%
2020093008 1
 
1.0%
2020093012 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2020091012 1
1.0%
2020091014 1
1.0%
2020091016 1
1.0%
2020091716 1
1.0%
2020091718 1
1.0%
2020092304 1
1.0%
2020092306 1
1.0%
2020092308 1
1.0%
2020092310 1
1.0%
2020092312 1
1.0%
ValueCountFrequency (%)
2020093024 1
1.0%
2020093022 1
1.0%
2020093020 1
1.0%
2020093018 1
1.0%
2020093016 1
1.0%
2020093014 1
1.0%
2020093012 1
1.0%
2020093010 1
1.0%
2020093008 1
1.0%
2020093006 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

2023-12-10T19:26:57.936282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:26:58.083119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4335
Minimum1.312
Maximum2.124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:58.225911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.312
5-th percentile1.319
Q11.333
median1.3845
Q31.52
95-th percentile1.56035
Maximum2.124
Range0.812
Interquartile range (IQR)0.187

Descriptive statistics

Standard deviation0.14937381
Coefficient of variation (CV)0.10420217
Kurtosis9.8648148
Mean1.4335
Median Absolute Deviation (MAD)0.0575
Skewness2.7415342
Sum143.35
Variance0.022312535
MonotonicityNot monotonic
2023-12-10T19:26:58.440654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1.557 14
14.0%
1.319 13
13.0%
1.327 10
 
10.0%
1.342 9
 
9.0%
1.396 6
 
6.0%
1.365 5
 
5.0%
1.428 5
 
5.0%
1.549 4
 
4.0%
1.35 3
 
3.0%
1.491 2
 
2.0%
Other values (22) 29
29.0%
ValueCountFrequency (%)
1.312 2
 
2.0%
1.319 13
13.0%
1.327 10
10.0%
1.335 2
 
2.0%
1.342 9
9.0%
1.35 3
 
3.0%
1.358 2
 
2.0%
1.365 5
 
5.0%
1.373 2
 
2.0%
1.381 2
 
2.0%
ValueCountFrequency (%)
2.124 1
 
1.0%
2.095 1
 
1.0%
2.075 1
 
1.0%
1.649 1
 
1.0%
1.624 1
 
1.0%
1.557 14
14.0%
1.549 4
 
4.0%
1.54 1
 
1.0%
1.532 1
 
1.0%
1.516 2
 
2.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.012
Minimum1.8
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:58.666766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.8
5-th percentile1.8
Q11.9
median1.9
Q32.1
95-th percentile2.205
Maximum3
Range1.2
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.21474909
Coefficient of variation (CV)0.10673414
Kurtosis8.3631448
Mean2.012
Median Absolute Deviation (MAD)0.1
Skewness2.4451968
Sum201.2
Variance0.046117172
MonotonicityNot monotonic
2023-12-10T19:26:58.864685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1.9 36
36.0%
2.2 19
19.0%
2.0 19
19.0%
1.8 15
15.0%
2.1 6
 
6.0%
2.9 2
 
2.0%
2.3 2
 
2.0%
3.0 1
 
1.0%
ValueCountFrequency (%)
1.8 15
15.0%
1.9 36
36.0%
2.0 19
19.0%
2.1 6
 
6.0%
2.2 19
19.0%
2.3 2
 
2.0%
2.9 2
 
2.0%
3.0 1
 
1.0%
ValueCountFrequency (%)
3.0 1
 
1.0%
2.9 2
 
2.0%
2.3 2
 
2.0%
2.2 19
19.0%
2.1 6
 
6.0%
2.0 19
19.0%
1.9 36
36.0%
1.8 15
15.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.3322
Minimum42.689
Maximum226.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:59.081041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.689
5-th percentile44.1
Q146.55
median56.468
Q387.23025
95-th percentile93.0522
Maximum226.8
Range184.111
Interquartile range (IQR)40.68025

Descriptive statistics

Standard deviation32.780851
Coefficient of variation (CV)0.48685251
Kurtosis12.067246
Mean67.3322
Median Absolute Deviation (MAD)10.968
Skewness3.085856
Sum6733.22
Variance1074.5842
MonotonicityNot monotonic
2023-12-10T19:26:59.346931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
92.4 14
 
14.0%
44.1 12
 
12.0%
45.5 9
 
9.0%
48.3 8
 
8.0%
53.2 5
 
5.0%
58.8 4
 
4.0%
49.7 3
 
3.0%
65.1 3
 
3.0%
51.1 2
 
2.0%
42.7 2
 
2.0%
Other values (35) 38
38.0%
ValueCountFrequency (%)
42.689 1
 
1.0%
42.7 2
 
2.0%
43.412 1
 
1.0%
44.1 12
12.0%
45.5 9
9.0%
46.9 2
 
2.0%
47.188 1
 
1.0%
48.3 8
8.0%
49.7 3
 
3.0%
51.1 2
 
2.0%
ValueCountFrequency (%)
226.8 1
 
1.0%
218.039 1
 
1.0%
212.723 1
 
1.0%
109.257 1
 
1.0%
105.444 1
 
1.0%
92.4 14
14.0%
91.318 1
 
1.0%
90.3 2
 
2.0%
88.9 1
 
1.0%
88.792 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.54136
Minimum42.7
Maximum226.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:26:59.609463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.7
5-th percentile44.1
Q146.55575
median57.0265
Q385.16675
95-th percentile93.16885
Maximum226.8
Range184.1
Interquartile range (IQR)38.611

Descriptive statistics

Standard deviation33.026915
Coefficient of variation (CV)0.48898801
Kurtosis12.199954
Mean67.54136
Median Absolute Deviation (MAD)11.5265
Skewness3.1136639
Sum6754.136
Variance1090.7771
MonotonicityNot monotonic
2023-12-10T19:26:59.830019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
92.4 14
 
14.0%
44.1 12
 
12.0%
45.5 9
 
9.0%
48.3 8
 
8.0%
53.2 5
 
5.0%
58.8 4
 
4.0%
49.7 3
 
3.0%
65.1 3
 
3.0%
51.1 2
 
2.0%
42.7 2
 
2.0%
Other values (35) 38
38.0%
ValueCountFrequency (%)
42.7 2
 
2.0%
44.1 12
12.0%
44.8 1
 
1.0%
45.5 9
9.0%
45.523 1
 
1.0%
46.9 2
 
2.0%
48.3 8
8.0%
49.327 1
 
1.0%
49.7 3
 
3.0%
51.1 2
 
2.0%
ValueCountFrequency (%)
226.8 1
 
1.0%
220.733 1
 
1.0%
215.39 1
 
1.0%
114.007 1
 
1.0%
107.777 1
 
1.0%
92.4 14
14.0%
91.07 1
 
1.0%
90.3 2
 
2.0%
89.04 1
 
1.0%
88.9 1
 
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.6229
Minimum23.47
Maximum24.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:27:00.084806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.47
5-th percentile23.48
Q123.4975
median23.565
Q323.735
95-th percentile23.784
Maximum24.41
Range0.94
Interquartile range (IQR)0.2375

Descriptive statistics

Standard deviation0.17761208
Coefficient of variation (CV)0.0075186399
Kurtosis8.1180751
Mean23.6229
Median Absolute Deviation (MAD)0.075
Skewness2.4555667
Sum2362.29
Variance0.031546051
MonotonicityNot monotonic
2023-12-10T19:27:00.314489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
23.78 14
14.0%
23.48 13
13.0%
23.49 10
 
10.0%
23.51 9
 
9.0%
23.58 6
 
6.0%
23.54 5
 
5.0%
23.62 5
 
5.0%
23.77 4
 
4.0%
23.52 3
 
3.0%
23.7 2
 
2.0%
Other values (22) 29
29.0%
ValueCountFrequency (%)
23.47 2
 
2.0%
23.48 13
13.0%
23.49 10
10.0%
23.5 2
 
2.0%
23.51 9
9.0%
23.52 3
 
3.0%
23.53 2
 
2.0%
23.54 5
 
5.0%
23.55 2
 
2.0%
23.56 2
 
2.0%
ValueCountFrequency (%)
24.41 1
 
1.0%
24.38 1
 
1.0%
24.36 1
 
1.0%
23.89 1
 
1.0%
23.86 1
 
1.0%
23.78 14
14.0%
23.77 4
 
4.0%
23.76 1
 
1.0%
23.75 1
 
1.0%
23.73 2
 
2.0%

Interactions

2023-12-10T19:26:55.527655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:50.584427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.592685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.550676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:53.555882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.600987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.692911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:50.755150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.759782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.745479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:53.859985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.759990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.838247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:50.954214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.921905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.888157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.032757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.909767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.967620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.119781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.084289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:53.030026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.176465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.072721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:56.459242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.296650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.237288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:53.222185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.315971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.229621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:56.601428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:51.455473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:52.412245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:53.399279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:54.470073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:26:55.400648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:27:00.449769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.9630.9780.8850.8880.979
강우량(mm)0.9631.0000.9930.8970.8970.990
유입량(ms)0.9780.9931.0000.9410.9411.000
방류량(ms)0.8850.8970.9411.0000.9990.937
저수량(백만m3)0.8880.8970.9410.9991.0000.937
저수율0.9790.9901.0000.9370.9371.000
2023-12-10T19:27:00.646650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.890-0.870-0.890-0.887-0.890
강우량(mm)-0.8901.0000.9710.9970.9991.000
유입량(ms)-0.8700.9711.0000.9660.9700.971
방류량(ms)-0.8900.9970.9661.0000.9940.997
저수량(백만m3)-0.8870.9990.9700.9941.0000.999
저수율-0.8901.0000.9710.9970.9991.000

Missing values

2023-12-10T19:26:56.773372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:26:56.981165image/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
0군남202009252401.542.288.988.923.76
1군남202009230801.4282.065.165.123.62
2군남202009281601.3421.948.348.323.51
3군남202009260201.5162.182.56284.8423.73
4군남202009241601.5492.290.390.323.77
5군남202009231001.4282.065.165.123.62
6군남202009292401.3191.844.144.123.48
7군남202009281801.3421.948.348.323.51
8군남202009271001.3651.953.253.223.54
9군남202009260401.4912.175.7980.2923.7
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202009261801.3962.056.93659.10323.58
91군남202009261601.4042.058.560.66723.59
92군남202009261201.4282.063.65365.84723.62
93군남202009261001.4432.066.70968.90323.64
94군남202009252201.5492.288.79291.0723.77
95군남202009252001.5572.292.492.423.78
96군남202009251601.5572.292.492.423.78
97군남202009251401.5572.292.492.423.78
98군남202009230401.4352.066.566.523.63
99군남202009230601.4282.065.165.123.62