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 강우량(mm) and 2 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수량 is highly overall correlated with 방류량(ms)High correlation
저수율(ms) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(백만m3) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 저수량High correlation
저수위(m) is highly imbalanced (91.9%)Imbalance
일자/시간(t) has unique valuesUnique
저수량 has 3 (3.0%) zerosZeros
방류량(ms) has 4 (4.0%) zerosZeros

Reproduction

Analysis started2024-04-17 06:02:51.111603
Analysis finished2024-04-17 06:02:54.384157
Duration3.27 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
감포
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감포 100
100.0%

Length

2024-04-17T15:02:54.437000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T15:02:54.511596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감포 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190307 × 109
Minimum2.0190301 × 109
Maximum2.0190323 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:54.602315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190301 × 109
5-th percentile2.0190301 × 109
Q12.0190303 × 109
median2.0190305 × 109
Q32.0190307 × 109
95-th percentile2.0190322 × 109
Maximum2.0190323 × 109
Range2208
Interquartile range (IQR)403

Descriptive statistics

Standard deviation714.97019
Coefficient of variation (CV)3.5411556 × 10-7
Kurtosis0.76904813
Mean2.0190307 × 109
Median Absolute Deviation (MAD)202
Skewness1.5306392
Sum2.0190307 × 1011
Variance511182.37
MonotonicityNot monotonic
2024-04-17T15:02:54.721052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019030218 1
 
1.0%
2019030716 1
 
1.0%
2019030602 1
 
1.0%
2019030608 1
 
1.0%
2019030610 1
 
1.0%
2019030614 1
 
1.0%
2019030616 1
 
1.0%
2019030624 1
 
1.0%
2019030702 1
 
1.0%
2019030706 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019030102 1
1.0%
2019030104 1
1.0%
2019030106 1
1.0%
2019030108 1
1.0%
2019030110 1
1.0%
2019030112 1
1.0%
2019030114 1
1.0%
2019030116 1
1.0%
2019030118 1
1.0%
2019030120 1
1.0%
ValueCountFrequency (%)
2019032310 1
1.0%
2019032308 1
1.0%
2019032306 1
1.0%
2019032304 1
1.0%
2019032302 1
1.0%
2019032224 1
1.0%
2019032222 1
1.0%
2019032220 1
1.0%
2019032218 1
1.0%
2019032216 1
1.0%

저수위(m)
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
99 
0.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 99
99.0%
0.5 1
 
1.0%

Length

2024-04-17T15:02:54.833582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T15:02:54.914615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 99
99.0%
0.5 1
 
1.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0916
Minimum2.062
Maximum2.107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:54.991053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.062
5-th percentile2.06295
Q12.091
median2.096
Q32.102
95-th percentile2.105
Maximum2.107
Range0.045
Interquartile range (IQR)0.011

Descriptive statistics

Standard deviation0.013981228
Coefficient of variation (CV)0.0066844657
Kurtosis0.43617407
Mean2.0916
Median Absolute Deviation (MAD)0.005
Skewness-1.329514
Sum209.16
Variance0.00019547475
MonotonicityNot monotonic
2024-04-17T15:02:55.088622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2.063 12
12.0%
2.093 12
12.0%
2.104 12
12.0%
2.096 10
10.0%
2.1 9
9.0%
2.102 7
7.0%
2.094 7
7.0%
2.091 7
7.0%
2.098 6
6.0%
2.089 6
6.0%
Other values (3) 12
12.0%
ValueCountFrequency (%)
2.062 5
5.0%
2.063 12
12.0%
2.089 6
6.0%
2.091 7
7.0%
2.093 12
12.0%
2.094 7
7.0%
2.096 10
10.0%
2.098 6
6.0%
2.1 9
9.0%
2.102 7
7.0%
ValueCountFrequency (%)
2.107 2
 
2.0%
2.105 5
5.0%
2.104 12
12.0%
2.102 7
7.0%
2.1 9
9.0%
2.098 6
6.0%
2.096 10
10.0%
2.094 7
7.0%
2.093 12
12.0%
2.091 7
7.0%

저수량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03787
Minimum0
Maximum0.09
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:55.186368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01785
Q10.04
median0.04
Q30.04
95-th percentile0.04
Maximum0.09
Range0.09
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.010837323
Coefficient of variation (CV)0.28617173
Kurtosis10.646425
Mean0.03787
Median Absolute Deviation (MAD)0
Skewness0.11221971
Sum3.787
Variance0.00011744758
MonotonicityNot monotonic
2024-04-17T15:02:55.284474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.04 76
76.0%
0.03 10
 
10.0%
0.0 3
 
3.0%
0.051 1
 
1.0%
0.039 1
 
1.0%
0.018 1
 
1.0%
0.036 1
 
1.0%
0.042 1
 
1.0%
0.015 1
 
1.0%
0.035 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
0.0 3
 
3.0%
0.012 1
 
1.0%
0.015 1
 
1.0%
0.018 1
 
1.0%
0.029 1
 
1.0%
0.03 10
 
10.0%
0.035 1
 
1.0%
0.036 1
 
1.0%
0.039 1
 
1.0%
0.04 76
76.0%
ValueCountFrequency (%)
0.09 1
 
1.0%
0.08 1
 
1.0%
0.051 1
 
1.0%
0.042 1
 
1.0%
0.04 76
76.0%
0.039 1
 
1.0%
0.036 1
 
1.0%
0.035 1
 
1.0%
0.03 10
 
10.0%
0.029 1
 
1.0%

저수율(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.4543
Minimum38.29
Maximum38.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:55.390454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.29
5-th percentile38.2995
Q138.45
median38.48
Q338.51
95-th percentile38.53
Maximum38.54
Range0.25
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.076147849
Coefficient of variation (CV)0.0019802168
Kurtosis0.43808537
Mean38.4543
Median Absolute Deviation (MAD)0.03
Skewness-1.3283896
Sum3845.43
Variance0.0057984949
MonotonicityNot monotonic
2024-04-17T15:02:55.494295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
38.3 12
12.0%
38.46 12
12.0%
38.52 12
12.0%
38.48 10
10.0%
38.5 9
9.0%
38.51 7
7.0%
38.47 7
7.0%
38.45 7
7.0%
38.49 6
6.0%
38.44 6
6.0%
Other values (3) 12
12.0%
ValueCountFrequency (%)
38.29 5
5.0%
38.3 12
12.0%
38.44 6
6.0%
38.45 7
7.0%
38.46 12
12.0%
38.47 7
7.0%
38.48 10
10.0%
38.49 6
6.0%
38.5 9
9.0%
38.51 7
7.0%
ValueCountFrequency (%)
38.54 2
 
2.0%
38.53 5
5.0%
38.52 12
12.0%
38.51 7
7.0%
38.5 9
9.0%
38.49 6
6.0%
38.48 10
10.0%
38.47 7
7.0%
38.46 12
12.0%
38.45 7
7.0%

유입량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.349
Minimum78.2
Maximum79.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:55.582833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum78.2
5-th percentile78.295
Q179.3
median79.5
Q379.7
95-th percentile79.9
Maximum79.9
Range1.7
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.5250291
Coefficient of variation (CV)0.0066167072
Kurtosis0.39063444
Mean79.349
Median Absolute Deviation (MAD)0.2
Skewness-1.3060192
Sum7934.9
Variance0.27565556
MonotonicityNot monotonic
2024-04-17T15:02:55.670408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
79.5 17
17.0%
79.7 16
16.0%
78.3 12
12.0%
79.4 12
12.0%
79.8 12
12.0%
79.9 7
7.0%
79.3 7
7.0%
79.6 6
 
6.0%
79.2 6
 
6.0%
78.2 5
 
5.0%
ValueCountFrequency (%)
78.2 5
 
5.0%
78.3 12
12.0%
79.2 6
 
6.0%
79.3 7
7.0%
79.4 12
12.0%
79.5 17
17.0%
79.6 6
 
6.0%
79.7 16
16.0%
79.8 12
12.0%
79.9 7
7.0%
ValueCountFrequency (%)
79.9 7
7.0%
79.8 12
12.0%
79.7 16
16.0%
79.6 6
 
6.0%
79.5 17
17.0%
79.4 12
12.0%
79.3 7
7.0%
79.2 6
 
6.0%
78.3 12
12.0%
78.2 5
 
5.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03747
Minimum0
Maximum0.09
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T15:02:55.771240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01485
Q10.04
median0.04
Q30.04
95-th percentile0.04
Maximum0.09
Range0.09
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.011477211
Coefficient of variation (CV)0.30630399
Kurtosis9.0690098
Mean0.03747
Median Absolute Deviation (MAD)0
Skewness-0.16912393
Sum3.747
Variance0.00013172636
MonotonicityNot monotonic
2024-04-17T15:02:55.869393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.04 75
75.0%
0.03 10
 
10.0%
0.0 4
 
4.0%
0.051 1
 
1.0%
0.039 1
 
1.0%
0.018 1
 
1.0%
0.036 1
 
1.0%
0.042 1
 
1.0%
0.015 1
 
1.0%
0.035 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
0.0 4
 
4.0%
0.012 1
 
1.0%
0.015 1
 
1.0%
0.018 1
 
1.0%
0.029 1
 
1.0%
0.03 10
 
10.0%
0.035 1
 
1.0%
0.036 1
 
1.0%
0.039 1
 
1.0%
0.04 75
75.0%
ValueCountFrequency (%)
0.09 1
 
1.0%
0.08 1
 
1.0%
0.051 1
 
1.0%
0.042 1
 
1.0%
0.04 75
75.0%
0.039 1
 
1.0%
0.036 1
 
1.0%
0.035 1
 
1.0%
0.03 10
 
10.0%
0.029 1
 
1.0%

Interactions

2024-04-17T15:02:53.785090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.304811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.718647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.149229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.578984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.045774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.853251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.370249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.795671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.228356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.646307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.131453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.926604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.439026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.860003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.308270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.717913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.224346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.995651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.506247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.929478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.374905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.791301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.305196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:54.066675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.574656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.005693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.444679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.865314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.378602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:54.140086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:51.648788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.077494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.516027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:52.958297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T15:02:53.719878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T15:02:55.958124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)
일자/시간(t)1.0000.0900.9100.6420.9840.9400.647
저수위(m)0.0901.0000.0000.0000.0000.0000.000
강우량(mm)0.9100.0001.0000.4431.0000.9340.456
저수량0.6420.0000.4431.0000.4100.4151.000
저수율(ms)0.9840.0001.0000.4101.0000.9970.432
유입량(백만m3)0.9400.0000.9340.4150.9971.0000.412
방류량(ms)0.6470.0000.4561.0000.4320.4121.000
2024-04-17T15:02:56.072446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)저수위(m)
일자/시간(t)1.000-0.996-0.348-0.996-0.992-0.3480.060
강우량(mm)-0.9961.0000.3601.0000.9970.3640.000
저수량-0.3480.3601.0000.3600.3570.9670.000
저수율(ms)-0.9961.0000.3601.0000.9970.3640.000
유입량(백만m3)-0.9920.9970.3570.9971.0000.3620.000
방류량(ms)-0.3480.3640.9670.3640.3621.0000.000
저수위(m)0.0600.0000.0000.0000.0000.0001.000

Missing values

2024-04-17T15:02:54.232790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T15:02:54.341249image/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)저수량저수율(ms)유입량(백만m3)방류량(ms)
0감포20190302180.02.1020.05138.5179.70.051
1감포20190322060.02.0630.0338.378.30.03
2감포20190305100.02.0940.0438.4779.50.04
3감포20190302200.02.1020.0438.5179.70.04
4감포20190301040.02.1070.0438.5479.90.04
5감포20190322080.02.0630.0338.378.30.03
6감포20190306180.02.0930.0438.4679.40.04
7감포20190305120.02.0940.0438.4779.50.04
8감포20190304040.02.0980.0438.4979.60.04
9감포20190302220.02.1020.03938.5179.70.039
댐이름일자/시간(t)저수위(m)강우량(mm)저수량저수율(ms)유입량(백만m3)방류량(ms)
90감포20190303120.02.10.0438.579.70.04
91감포20190303100.02.10.0338.579.70.03
92감포20190303060.02.10.0438.579.70.04
93감포20190303040.02.1020.0438.5179.70.04
94감포20190302160.02.1020.0938.5179.70.09
95감포20190302140.02.1040.0438.5279.80.04
96감포20190302100.02.1040.0438.5279.80.04
97감포20190302080.02.1040.0438.5279.80.04
98감포20190322020.02.0630.0338.378.30.03
99감포20190322040.02.0630.0338.378.30.03