Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows34
Duplicate rows (%)34.0%
Total size in memory7.1 KiB
Average record size in memory72.3 B

Variable types

Categorical3
Numeric5

Alerts

저수위(m) has constant value ""Constant
Dataset has 34 (34.0%) duplicate rowsDuplicates
강우량(mm) is highly overall correlated with 유입량(ms) and 3 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 강우량(mm) and 1 other fieldsHigh correlation
방류량(ms) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 강우량(mm) and 3 other fieldsHigh correlation
저수율 is highly overall correlated with 방류량(ms) and 2 other fieldsHigh correlation
댐이름 is highly overall correlated with 강우량(mm) and 4 other fieldsHigh correlation
강우량(mm) has 21 (21.0%) zerosZeros
유입량(ms) has 25 (25.0%) zerosZeros
방류량(ms) has 21 (21.0%) zerosZeros
저수량(백만m3) has 21 (21.0%) zerosZeros

Reproduction

Analysis started2023-12-10 12:52:05.294018
Analysis finished2023-12-10 12:52:08.492031
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자/시간(t)
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020030102
36 
2020030101
34 
2020030103
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020030101
2nd row2020030101
3rd row2020030101
4th row2020030101
5th row2020030101

Common Values

ValueCountFrequency (%)
2020030102 36
36.0%
2020030101 34
34.0%
2020030103 30
30.0%

Length

2023-12-10T21:52:08.552885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:52:08.645635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020030102 36
36.0%
2020030101 34
34.0%
2020030103 30
30.0%

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

2023-12-10T21:52:08.757073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:52:08.856383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.37589
Minimum0
Maximum100.932
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:52:08.966147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.98225
median14.967
Q353.384
95-th percentile86.611
Maximum100.932
Range100.932
Interquartile range (IQR)52.40175

Descriptive statistics

Standard deviation30.372484
Coefficient of variation (CV)1.1094611
Kurtosis-0.20664714
Mean27.37589
Median Absolute Deviation (MAD)14.967
Skewness0.98102771
Sum2737.589
Variance922.48779
MonotonicityNot monotonic
2023-12-10T21:52:09.115505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 21
21.0%
12.003 6
 
6.0%
53.384 5
 
5.0%
2.572 5
 
5.0%
9.769 5
 
5.0%
86.611 5
 
5.0%
27.823 4
 
4.0%
1.034 4
 
4.0%
76.545 4
 
4.0%
54.43 4
 
4.0%
Other values (22) 37
37.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.814 1
 
1.0%
0.818 1
 
1.0%
0.827 2
 
2.0%
1.034 4
 
4.0%
2.572 5
 
5.0%
6.872 1
 
1.0%
6.887 2
 
2.0%
6.902 1
 
1.0%
9.769 5
 
5.0%
ValueCountFrequency (%)
100.932 1
 
1.0%
100.728 3
3.0%
86.611 5
5.0%
76.545 4
4.0%
55.845 2
 
2.0%
55.758 1
 
1.0%
55.671 2
 
2.0%
54.43 4
4.0%
53.384 5
5.0%
48.861 3
3.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.208
Minimum0
Maximum135.6
Zeros25
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:52:09.276187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112.45
median92.9
Q3101.5
95-th percentile111.9
Maximum135.6
Range135.6
Interquartile range (IQR)89.05

Descriptive statistics

Standard deviation46.444051
Coefficient of variation (CV)0.70148699
Kurtosis-1.4557774
Mean66.208
Median Absolute Deviation (MAD)16.05
Skewness-0.48170645
Sum6620.8
Variance2157.0498
MonotonicityNot monotonic
2023-12-10T21:52:09.398088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 25
25.0%
106.5 6
 
6.0%
111.9 5
 
5.0%
16.6 5
 
5.0%
93.8 5
 
5.0%
101.2 5
 
5.0%
104.4 4
 
4.0%
101.6 4
 
4.0%
101.5 4
 
4.0%
18.3 4
 
4.0%
Other values (18) 33
33.0%
ValueCountFrequency (%)
0.0 25
25.0%
16.6 5
 
5.0%
18.3 4
 
4.0%
62.8 2
 
2.0%
63.0 1
 
1.0%
63.2 1
 
1.0%
76.6 1
 
1.0%
76.8 2
 
2.0%
76.9 1
 
1.0%
79.6 2
 
2.0%
ValueCountFrequency (%)
135.6 3
3.0%
135.5 1
 
1.0%
111.9 5
5.0%
106.5 6
6.0%
104.4 4
4.0%
101.6 4
4.0%
101.5 4
4.0%
101.2 5
5.0%
100.4 3
3.0%
100.0 2
 
2.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.75517
Minimum0
Maximum307.621
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:52:09.527668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.538
median128.6905
Q3163.116
95-th percentile235.371
Maximum307.621
Range307.621
Interquartile range (IQR)148.578

Descriptive statistics

Standard deviation78.979911
Coefficient of variation (CV)0.78387949
Kurtosis-1.005209
Mean100.75517
Median Absolute Deviation (MAD)40.594
Skewness0.036218495
Sum10075.517
Variance6237.8263
MonotonicityNot monotonic
2023-12-10T21:52:09.643729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
21.0%
16.247 3
 
3.0%
88.061 2
 
2.0%
18.917 2
 
2.0%
163.915 2
 
2.0%
17.339 2
 
2.0%
125.062 2
 
2.0%
112.183 2
 
2.0%
144.475 2
 
2.0%
166.443 2
 
2.0%
Other values (44) 60
60.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.33 1
 
1.0%
6.724 1
 
1.0%
9.411 2
 
2.0%
16.247 3
 
3.0%
17.311 1
 
1.0%
17.339 2
 
2.0%
18.917 2
 
2.0%
19.312 1
 
1.0%
21.422 1
 
1.0%
ValueCountFrequency (%)
307.621 1
1.0%
250.662 1
1.0%
249.91 2
2.0%
235.371 2
2.0%
184.78 1
1.0%
184.768 2
2.0%
184.738 1
1.0%
168.527 2
2.0%
168.525 1
1.0%
168.513 2
2.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.69267
Minimum0
Maximum251.065
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:52:09.764983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.733
median128.489
Q3163.083
95-th percentile187.2924
Maximum251.065
Range251.065
Interquartile range (IQR)154.35

Descriptive statistics

Standard deviation77.669301
Coefficient of variation (CV)0.78698145
Kurtosis-1.3316477
Mean98.69267
Median Absolute Deviation (MAD)48.348
Skewness-0.10784278
Sum9869.267
Variance6032.5203
MonotonicityNot monotonic
2023-12-10T21:52:09.898704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 21
 
21.0%
20.8 4
 
4.0%
0.33 4
 
4.0%
13.2 4
 
4.0%
166.443 2
 
2.0%
139.359 2
 
2.0%
125.062 2
 
2.0%
128.489 2
 
2.0%
144.475 2
 
2.0%
88.061 2
 
2.0%
Other values (39) 55
55.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.33 4
 
4.0%
11.534 1
 
1.0%
11.695 2
 
2.0%
11.724 1
 
1.0%
13.2 4
 
4.0%
20.8 4
 
4.0%
88.042 1
 
1.0%
88.061 2
 
2.0%
88.132 1
 
1.0%
ValueCountFrequency (%)
251.065 1
1.0%
250.662 1
1.0%
249.91 2
2.0%
188.535 1
1.0%
187.227 2
2.0%
187.177 2
2.0%
184.78 1
1.0%
184.768 2
2.0%
184.738 1
1.0%
168.527 2
2.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.0228
Minimum1.48
Maximum134.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:52:10.072416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.48
5-th percentile3.3595
Q18.28
median28.14
Q344.43
95-th percentile86
Maximum134.4
Range132.92
Interquartile range (IQR)36.15

Descriptive statistics

Standard deviation32.022374
Coefficient of variation (CV)0.94120338
Kurtosis1.9542667
Mean34.0228
Median Absolute Deviation (MAD)18.96
Skewness1.4204941
Sum3402.28
Variance1025.4325
MonotonicityNot monotonic
2023-12-10T21:52:10.251144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
44.43 6
 
6.0%
33.17 6
 
6.0%
19.16 5
 
5.0%
4.51 5
 
5.0%
38.23 5
 
5.0%
80.76 5
 
5.0%
86.0 5
 
5.0%
32.6 5
 
5.0%
25.62 4
 
4.0%
9.03 4
 
4.0%
Other values (26) 50
50.0%
ValueCountFrequency (%)
1.48 2
 
2.0%
1.49 1
 
1.0%
1.5 1
 
1.0%
3.35 1
 
1.0%
3.36 1
 
1.0%
3.38 2
 
2.0%
4.2 1
 
1.0%
4.21 3
3.0%
4.51 5
5.0%
4.99 3
3.0%
ValueCountFrequency (%)
134.4 3
3.0%
134.39 1
 
1.0%
86.0 5
5.0%
80.76 5
5.0%
62.52 3
3.0%
62.51 2
 
2.0%
47.1 4
4.0%
44.43 6
6.0%
39.85 1
 
1.0%
39.84 2
 
2.0%

댐이름
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
여주보
 
6
쾌쾌보
 
6
수하보
 
5
구담보
 
5
구미보
 
5
Other values (17)
73 

Length

Max length5
Median length3
Mean length3.36
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row죽산보
2nd row공주보
3rd row구담보
4th row구미보
5th row귤현보

Common Values

ValueCountFrequency (%)
여주보 6
 
6.0%
쾌쾌보 6
 
6.0%
수하보 5
 
5.0%
구담보 5
 
5.0%
구미보 5
 
5.0%
합천창녕보 5
 
5.0%
강정고령보 5
 
5.0%
안동보 5
 
5.0%
공주보 5
 
5.0%
강천보 5
 
5.0%
Other values (12) 48
48.0%

Length

2023-12-10T21:52:10.407434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여주보 6
 
6.0%
쾌쾌보 6
 
6.0%
수하보 5
 
5.0%
구담보 5
 
5.0%
구미보 5
 
5.0%
합천창녕보 5
 
5.0%
강정고령보 5
 
5.0%
안동보 5
 
5.0%
공주보 5
 
5.0%
강천보 5
 
5.0%
Other values (12) 48
48.0%

Interactions

2023-12-10T21:52:07.752853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:05.593645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.285425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.802010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.258548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.850418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:05.690489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.367687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.908219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.342426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.943273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:05.776127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.479714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.994632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.438019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:08.045369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.097982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.591223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.084765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.538694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:08.160247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.185802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:06.689657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.163579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:52:07.638497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:52:10.491225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
일자/시간(t)1.0000.0000.0000.0000.0000.0000.000
강우량(mm)0.0001.0000.8340.8590.8700.8141.000
유입량(ms)0.0000.8341.0000.7940.8330.9141.000
방류량(ms)0.0000.8590.7941.0000.9370.5960.959
저수량(백만m3)0.0000.8700.8330.9371.0000.6691.000
저수율0.0000.8140.9140.5960.6691.0001.000
댐이름0.0001.0001.0000.9591.0001.0001.000
2023-12-10T21:52:10.593306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
댐이름일자/시간(t)
댐이름1.0000.000
일자/시간(t)0.0001.000
2023-12-10T21:52:10.679636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율일자/시간(t)댐이름
강우량(mm)1.0000.6320.7350.734-0.3200.0000.926
유입량(ms)0.6321.0000.4970.4660.0350.0000.921
방류량(ms)0.7350.4971.0000.984-0.5390.0000.739
저수량(백만m3)0.7340.4660.9841.000-0.5500.0000.916
저수율-0.3200.035-0.539-0.5501.0000.0000.921
일자/시간(t)0.0000.0000.0000.0000.0001.0000.000
댐이름0.9260.9210.7390.9160.9210.0001.000

Missing values

2023-12-10T21:52:08.307931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:52:08.442513image/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

일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
02020030101016.17863.032.18920.81.49죽산보
1202003010102.57216.6144.475144.4754.51공주보
2202003010100.00.00.00.062.52구담보
32020030101053.384101.2137.786137.78632.6구미보
4202003010100.8140.019.31211.5343.35귤현보
52020030101048.804135.516.2470.33134.39단양수중보
6202003010101.03418.3139.266139.2669.03세종보
72020030101076.545101.6154.451125.97925.62칠곡보
82020030101054.4392.9184.768184.76813.61달성보
92020030101033.79797.5128.483128.48339.85낙단보
일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름
90202003010300.8180.06.72411.7243.36귤현보
91202003010300.00.00.00.086.0안동보
9220200301030100.932100.0307.621251.0655.0창녕함안보
932020030103027.823101.588.13288.13247.1상주보
942020030103055.75879.7164.452188.5359.31합천창녕보
95202003010302.57216.6142.557142.5574.51공주보
96202003010306.90276.917.31113.26.03승촌보
972020030103033.6897.1112.127128.43339.83낙단보
98202003010309.769111.9125.065125.06538.23강천보
99202003010300.00.00.00.062.51구담보

Duplicate rows

Most frequently occurring

일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율댐이름# duplicates
0202003010100.00.00.00.044.43쾌쾌보2
1202003010100.00.00.00.062.52구담보2
2202003010100.00.00.00.080.76수하보2
3202003010100.00.00.00.086.0안동보2
4202003010101.03418.3139.266139.2669.03세종보2
5202003010102.57216.6144.475144.4754.51공주보2
62020030101012.003106.5163.128163.12833.17여주보2
72020030101053.384101.2137.786137.78632.6구미보2
82020030101054.4392.9184.768184.76813.61달성보2
92020030101055.67179.6163.116187.2279.3합천창녕보2