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 2 other fieldsHigh correlation
강우량(mm) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
유입량(ms) 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
일자/시간(t) has unique valuesUnique
방류량(ms) has 28 (28.0%) zerosZeros

Reproduction

Analysis started2023-12-10 11:52:47.513793
Analysis finished2023-12-10 11:52:53.289000
Duration5.78 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
낙동강하굿둑
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
낙동강하굿둑 100
100.0%

Length

2023-12-10T20:52:53.391790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:52:53.545066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낙동강하굿둑 100
100.0%

일자/시간(t)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0190605 × 109
Minimum2.0190603 × 109
Maximum2.0190607 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:52:53.709526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190603 × 109
5-th percentile2.0190603 × 109
Q12.0190604 × 109
median2.0190605 × 109
Q32.0190606 × 109
95-th percentile2.0190607 × 109
Maximum2.0190607 × 109
Range403
Interquartile range (IQR)201.5

Descriptive statistics

Standard deviation125.02027
Coefficient of variation (CV)6.1920024 × 10-8
Kurtosis-1.0966527
Mean2.0190605 × 109
Median Absolute Deviation (MAD)101
Skewness0.01200353
Sum2.0190605 × 1011
Variance15630.069
MonotonicityNot monotonic
2023-12-10T20:52:53.941242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019060712 1
 
1.0%
2019060420 1
 
1.0%
2019060410 1
 
1.0%
2019060411 1
 
1.0%
2019060412 1
 
1.0%
2019060413 1
 
1.0%
2019060414 1
 
1.0%
2019060415 1
 
1.0%
2019060416 1
 
1.0%
2019060417 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2019060310 1
1.0%
2019060311 1
1.0%
2019060312 1
1.0%
2019060313 1
1.0%
2019060314 1
1.0%
2019060315 1
1.0%
2019060316 1
1.0%
2019060317 1
1.0%
2019060318 1
1.0%
2019060319 1
1.0%
ValueCountFrequency (%)
2019060713 1
1.0%
2019060712 1
1.0%
2019060711 1
1.0%
2019060710 1
1.0%
2019060709 1
1.0%
2019060708 1
1.0%
2019060707 1
1.0%
2019060706 1
1.0%
2019060705 1
1.0%
2019060704 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

2023-12-10T20:52:54.148478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:52:54.268601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

강우량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.50888
Minimum296.836
Maximum307.025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:52:54.409688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum296.836
5-th percentile298.192
Q1300.059
median301.445
Q3302.835
95-th percentile304.694
Maximum307.025
Range10.189
Interquartile range (IQR)2.776

Descriptive statistics

Standard deviation2.0061244
Coefficient of variation (CV)0.0066536161
Kurtosis0.079914655
Mean301.50888
Median Absolute Deviation (MAD)1.386
Skewness0.11779466
Sum30150.888
Variance4.0245349
MonotonicityNot monotonic
2023-12-10T20:52:54.600649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
302.372 11
11.0%
300.983 9
9.0%
302.835 9
9.0%
300.059 9
9.0%
300.52 9
9.0%
301.445 8
 
8.0%
299.597 7
 
7.0%
303.764 7
 
7.0%
301.908 6
 
6.0%
303.299 4
 
4.0%
Other values (12) 21
21.0%
ValueCountFrequency (%)
296.836 1
 
1.0%
297.295 2
 
2.0%
297.755 2
 
2.0%
298.215 2
 
2.0%
298.675 1
 
1.0%
299.136 4
4.0%
299.597 7
7.0%
300.059 9
9.0%
300.52 9
9.0%
300.983 9
9.0%
ValueCountFrequency (%)
307.025 1
 
1.0%
306.558 1
 
1.0%
305.625 1
 
1.0%
305.159 1
 
1.0%
304.694 3
 
3.0%
304.229 2
 
2.0%
303.764 7
7.0%
303.299 4
 
4.0%
302.835 9
9.0%
302.372 11
11.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.146
Minimum96.6
Maximum99.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:52:54.796384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum96.6
5-th percentile97.09
Q197.7
median98.1
Q398.6
95-th percentile99.2
Maximum99.9
Range3.3
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.65217894
Coefficient of variation (CV)0.0066449875
Kurtosis0.060538155
Mean98.146
Median Absolute Deviation (MAD)0.4
Skewness0.11516037
Sum9814.6
Variance0.42533737
MonotonicityNot monotonic
2023-12-10T20:52:54.979951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
98.4 11
11.0%
98.0 9
9.0%
98.6 9
9.0%
97.7 9
9.0%
97.8 9
9.0%
98.1 8
 
8.0%
97.5 7
 
7.0%
98.9 7
 
7.0%
98.3 6
 
6.0%
98.7 4
 
4.0%
Other values (12) 21
21.0%
ValueCountFrequency (%)
96.6 1
 
1.0%
96.8 2
 
2.0%
96.9 2
 
2.0%
97.1 2
 
2.0%
97.2 1
 
1.0%
97.4 4
4.0%
97.5 7
7.0%
97.7 9
9.0%
97.8 9
9.0%
98.0 9
9.0%
ValueCountFrequency (%)
99.9 1
 
1.0%
99.8 1
 
1.0%
99.5 1
 
1.0%
99.3 1
 
1.0%
99.2 3
 
3.0%
99.0 2
 
2.0%
98.9 7
7.0%
98.7 4
 
4.0%
98.6 9
9.0%
98.4 11
11.0%

방류량(ms)
Real number (ℝ)

ZEROS 

Distinct73
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.42077
Minimum0
Maximum1253.359
Zeros28
Zeros (%)28.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:52:55.189804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median143.4955
Q3273.99425
95-th percentile483.94795
Maximum1253.359
Range1253.359
Interquartile range (IQR)273.99425

Descriptive statistics

Standard deviation197.95502
Coefficient of variation (CV)1.1414724
Kurtosis7.7013618
Mean173.42077
Median Absolute Deviation (MAD)143.4955
Skewness2.0117526
Sum17342.077
Variance39186.192
MonotonicityNot monotonic
2023-12-10T20:52:55.410887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 28
28.0%
266.779 1
 
1.0%
147.161 1
 
1.0%
336.992 1
 
1.0%
191.777 1
 
1.0%
154.853 1
 
1.0%
1.227 1
 
1.0%
258.181 1
 
1.0%
258.571 1
 
1.0%
130.157 1
 
1.0%
Other values (63) 63
63.0%
ValueCountFrequency (%)
0.0 28
28.0%
1.0 1
 
1.0%
1.058 1
 
1.0%
1.118 1
 
1.0%
1.227 1
 
1.0%
6.243 1
 
1.0%
6.388 1
 
1.0%
7.133 1
 
1.0%
26.821 1
 
1.0%
34.334 1
 
1.0%
ValueCountFrequency (%)
1253.359 1
1.0%
659.626 1
1.0%
513.167 1
1.0%
498.102 1
1.0%
494.15 1
1.0%
483.411 1
1.0%
478.933 1
1.0%
469.191 1
1.0%
465.029 1
1.0%
463.253 1
1.0%

저수량(백만m3)
Real number (ℝ)

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.00887
Minimum-113.766
Maximum482.053
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)2.0%
Memory size1.0 KiB
2023-12-10T20:52:55.636352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-113.766
5-th percentile1.0038
Q143.44925
median111.396
Q3165.76825
95-th percentile328.8618
Maximum482.053
Range595.819
Interquartile range (IQR)122.319

Descriptive statistics

Standard deviation105.605
Coefficient of variation (CV)0.85159233
Kurtosis1.4612838
Mean124.00887
Median Absolute Deviation (MAD)64.428
Skewness0.91752005
Sum12400.887
Variance11152.417
MonotonicityNot monotonic
2023-12-10T20:52:55.868271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 3
 
3.0%
1.107 1
 
1.0%
26.436 1
 
1.0%
57.9 1
 
1.0%
138.279 1
 
1.0%
133.351 1
 
1.0%
118.753 1
 
1.0%
88.35 1
 
1.0%
154.296 1
 
1.0%
147.161 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
-113.766 1
 
1.0%
-65.518 1
 
1.0%
1.0 3
3.0%
1.004 1
 
1.0%
1.015 1
 
1.0%
1.043 1
 
1.0%
1.058 1
 
1.0%
1.098 1
 
1.0%
1.107 1
 
1.0%
1.118 1
 
1.0%
ValueCountFrequency (%)
482.053 1
1.0%
469.191 1
1.0%
354.237 1
1.0%
347.632 1
1.0%
345.179 1
1.0%
328.003 1
1.0%
313.083 1
1.0%
303.124 1
1.0%
297.546 1
1.0%
242.658 1
1.0%

저수율
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8513
Minimum0.75
Maximum0.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:52:56.084851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.75
5-th percentile0.7795
Q10.82
median0.85
Q30.88
95-th percentile0.92
Maximum0.97
Range0.22
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.043336946
Coefficient of variation (CV)0.050906785
Kurtosis0.074190471
Mean0.8513
Median Absolute Deviation (MAD)0.03
Skewness0.10734457
Sum85.13
Variance0.0018780909
MonotonicityNot monotonic
2023-12-10T20:52:56.264730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.87 11
11.0%
0.84 9
9.0%
0.88 9
9.0%
0.82 9
9.0%
0.83 9
9.0%
0.85 8
 
8.0%
0.81 7
 
7.0%
0.9 7
 
7.0%
0.86 6
 
6.0%
0.89 4
 
4.0%
Other values (12) 21
21.0%
ValueCountFrequency (%)
0.75 1
 
1.0%
0.76 2
 
2.0%
0.77 2
 
2.0%
0.78 2
 
2.0%
0.79 1
 
1.0%
0.8 4
4.0%
0.81 7
7.0%
0.82 9
9.0%
0.83 9
9.0%
0.84 9
9.0%
ValueCountFrequency (%)
0.97 1
 
1.0%
0.96 1
 
1.0%
0.94 1
 
1.0%
0.93 1
 
1.0%
0.92 3
 
3.0%
0.91 2
 
2.0%
0.9 7
7.0%
0.89 4
 
4.0%
0.88 9
9.0%
0.87 11
11.0%

Interactions

2023-12-10T20:52:51.720163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:47.785586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.664562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.418589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.249190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.966817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.997022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:47.941303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.802529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.559271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.401378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.107323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:52.108980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.075140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.908621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.669286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.504093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.226450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:52.229671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.221932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.040291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.805109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.637307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.344875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:52.353089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.390073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.186913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.970258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.767265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.456502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:52.460814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:48.537378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:49.308043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.118784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:50.866604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:52:51.582231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:52:56.399606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.6790.6940.0580.5150.694
강우량(mm)0.6791.0000.9990.0700.2031.000
유입량(ms)0.6940.9991.0000.0000.3231.000
방류량(ms)0.0580.0700.0001.0000.4400.051
저수량(백만m3)0.5150.2030.3230.4401.0000.261
저수율0.6941.0001.0000.0510.2611.000
2023-12-10T20:52:56.549588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.5280.5280.1940.2480.528
강우량(mm)0.5281.0001.0000.219-0.1451.000
유입량(ms)0.5281.0001.0000.219-0.1451.000
방류량(ms)0.1940.2190.2191.0000.1580.219
저수량(백만m3)0.248-0.145-0.1450.1581.000-0.145
저수율0.5281.0001.0000.219-0.1451.000

Missing values

2023-12-10T20:52:53.011808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:52:53.213513image/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
0낙동강하굿둑20190607120305.62599.50.01.1070.94
1낙동강하굿둑20190607110307.02599.9233.15103.40.97
2낙동강하굿둑20190607100306.55899.8494.15105.5670.96
3낙동강하굿둑20190607090305.15999.3191.70562.3720.93
4낙동강하굿둑20190607080304.69499.2659.626143.3760.92
5낙동강하굿둑20190607070302.83598.60.0215.8130.88
6낙동강하굿둑20190607060303.76498.9469.191469.1910.9
7낙동강하굿둑20190607050303.76498.9483.411225.4940.9
8낙동강하굿둑20190607040302.83598.61253.359482.0530.88
9낙동강하굿둑20190607030300.05997.70.0303.1240.82
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90낙동강하굿둑20190603180297.75596.9167.3239.6530.77
91낙동강하굿둑20190603170297.29596.8150.2122.6270.76
92낙동강하굿둑20190603160296.83696.60.083.5060.75
93낙동강하굿둑20190603150297.75596.90.0116.5840.77
94낙동강하굿둑20190603140299.13697.4124.155124.1550.8
95낙동강하굿둑20190603130299.13697.46.243134.3260.8
96낙동강하굿둑20190603120299.59797.5106.208106.2080.81
97낙동강하굿둑20190603110299.59797.50.068.1280.81
98낙동강하굿둑20190603100300.5297.80.050.3020.83
99낙동강하굿둑20190607130300.98398.00.0230.5760.84