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

Categorical5
Numeric3

Alerts

댐이름 has constant value ""Constant
강우량(mm) has constant value ""Constant
저수위(m) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
저수율 is highly overall correlated with 저수위(m) and 1 other fieldsHigh correlation
저수량(백만m3) is highly overall correlated with 일자/시간(t) and 2 other fieldsHigh correlation
일자/시간(t) is highly overall correlated with 저수위(m) and 1 other fieldsHigh correlation
유입량(ms) is highly overall correlated with 방류량(ms)High correlation
방류량(ms) is highly overall correlated with 유입량(ms)High correlation
저수율 is highly imbalanced (80.6%)Imbalance
일자/시간(t) has unique valuesUnique
유입량(ms) has 5 (5.0%) zerosZeros
방류량(ms) has 3 (3.0%) zerosZeros

Reproduction

Analysis started2024-04-16 18:11:27.842370
Analysis finished2024-04-16 18:11:28.813643
Duration0.97 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

2024-04-17T03:11:28.879514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:28.964947image/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%
Mean2.0190109 × 1011
Minimum2.0190108 × 1011
Maximum2.0190109 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:29.055511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0190108 × 1011
5-th percentile2.0190108 × 1011
Q12.0190108 × 1011
median2.0190109 × 1011
Q32.0190109 × 1011
95-th percentile2.0190109 × 1011
Maximum2.0190109 × 1011
Range10900
Interquartile range (IQR)9240

Descriptive statistics

Standard deviation4225.8083
Coefficient of variation (CV)2.0930092 × 10-8
Kurtosis-1.0493003
Mean2.0190109 × 1011
Median Absolute Deviation (MAD)920
Skewness-0.93309791
Sum2.0190109 × 1013
Variance17857456
MonotonicityNot monotonic
2024-04-17T03:11:29.170862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201901090310 1
 
1.0%
201901092250 1
 
1.0%
201901091630 1
 
1.0%
201901091730 1
 
1.0%
201901091750 1
 
1.0%
201901091830 1
 
1.0%
201901091850 1
 
1.0%
201901092010 1
 
1.0%
201901092030 1
 
1.0%
201901092110 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
201901081450 1
1.0%
201901081510 1
1.0%
201901081530 1
1.0%
201901081550 1
1.0%
201901081610 1
1.0%
201901081630 1
1.0%
201901081650 1
1.0%
201901081710 1
1.0%
201901081730 1
1.0%
201901081750 1
1.0%
ValueCountFrequency (%)
201901092350 1
1.0%
201901092330 1
1.0%
201901092310 1
1.0%
201901092250 1
1.0%
201901092230 1
1.0%
201901092210 1
1.0%
201901092150 1
1.0%
201901092130 1
1.0%
201901092110 1
1.0%
201901092050 1
1.0%

저수위(m)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
39.23
72 
39.24
25 
39.22
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row39.23
2nd row39.24
3rd row39.23
4th row39.23
5th row39.24

Common Values

ValueCountFrequency (%)
39.23 72
72.0%
39.24 25
 
25.0%
39.22 3
 
3.0%

Length

2024-04-17T03:11:29.271841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:29.357967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
39.23 72
72.0%
39.24 25
 
25.0%
39.22 3
 
3.0%

강우량(mm)
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

2024-04-17T03:11:29.451702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:29.525101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03644
Minimum0
Maximum0.09
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:29.595757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.00095
Q10.03
median0.0335
Q30.04
95-th percentile0.0824
Maximum0.09
Range0.09
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.016777402
Coefficient of variation (CV)0.46041169
Kurtosis4.548415
Mean0.03644
Median Absolute Deviation (MAD)0.0065
Skewness1.2709165
Sum3.644
Variance0.00028148121
MonotonicityNot monotonic
2024-04-17T03:11:29.686455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.03 42
42.0%
0.04 38
38.0%
0.09 5
 
5.0%
0.0 5
 
5.0%
0.05 1
 
1.0%
0.061 1
 
1.0%
0.049 1
 
1.0%
0.082 1
 
1.0%
0.037 1
 
1.0%
0.001 1
 
1.0%
Other values (4) 4
 
4.0%
ValueCountFrequency (%)
0.0 5
 
5.0%
0.001 1
 
1.0%
0.021 1
 
1.0%
0.028 1
 
1.0%
0.03 42
42.0%
0.037 1
 
1.0%
0.04 38
38.0%
0.042 1
 
1.0%
0.043 1
 
1.0%
0.049 1
 
1.0%
ValueCountFrequency (%)
0.09 5
 
5.0%
0.082 1
 
1.0%
0.061 1
 
1.0%
0.05 1
 
1.0%
0.049 1
 
1.0%
0.043 1
 
1.0%
0.042 1
 
1.0%
0.04 38
38.0%
0.037 1
 
1.0%
0.03 42
42.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03729
Minimum0
Maximum0.09
Zeros3
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T03:11:29.775419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02955
Q10.03
median0.04
Q30.04
95-th percentile0.0805
Maximum0.09
Range0.09
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.016106524
Coefficient of variation (CV)0.43192608
Kurtosis4.9949948
Mean0.03729
Median Absolute Deviation (MAD)0.01
Skewness1.6029309
Sum3.729
Variance0.0002594201
MonotonicityNot monotonic
2024-04-17T03:11:30.126354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.03 44
44.0%
0.04 43
43.0%
0.09 5
 
5.0%
0.0 3
 
3.0%
0.08 1
 
1.0%
0.066 1
 
1.0%
0.004 1
 
1.0%
0.068 1
 
1.0%
0.021 1
 
1.0%
ValueCountFrequency (%)
0.0 3
 
3.0%
0.004 1
 
1.0%
0.021 1
 
1.0%
0.03 44
44.0%
0.04 43
43.0%
0.066 1
 
1.0%
0.068 1
 
1.0%
0.08 1
 
1.0%
0.09 5
 
5.0%
ValueCountFrequency (%)
0.09 5
 
5.0%
0.08 1
 
1.0%
0.068 1
 
1.0%
0.066 1
 
1.0%
0.04 43
43.0%
0.03 44
44.0%
0.021 1
 
1.0%
0.004 1
 
1.0%
0.0 3
 
3.0%

저수량(백만m3)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2.237
72 
2.239
25 
2.235
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.237
2nd row2.239
3rd row2.237
4th row2.237
5th row2.239

Common Values

ValueCountFrequency (%)
2.237 72
72.0%
2.239 25
 
25.0%
2.235 3
 
3.0%

Length

2024-04-17T03:11:30.213589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:30.286426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2.237 72
72.0%
2.239 25
 
25.0%
2.235 3
 
3.0%

저수율
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
84.9
97 
84.8
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row84.9
2nd row84.9
3rd row84.9
4th row84.9
5th row84.9

Common Values

ValueCountFrequency (%)
84.9 97
97.0%
84.8 3
 
3.0%

Length

2024-04-17T03:11:30.371475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T03:11:30.446580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
84.9 97
97.0%
84.8 3
 
3.0%

Interactions

2024-04-17T03:11:28.445879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.055511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.254008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.515681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.122964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.321271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.576941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.189909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T03:11:28.384850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T03:11:30.501451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.6380.7330.8210.6380.274
저수위(m)0.6381.0000.5360.3841.0001.000
유입량(ms)0.7330.5361.0000.9780.5360.369
방류량(ms)0.8210.3840.9781.0000.3840.000
저수량(백만m3)0.6381.0000.5360.3841.0001.000
저수율0.2741.0000.3690.0001.0001.000
2024-04-17T03:11:30.593237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
저수위(m)저수율저수량(백만m3)
저수위(m)1.0000.9951.000
저수율0.9951.0000.995
저수량(백만m3)1.0000.9951.000
2024-04-17T03:11:30.667488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)유입량(ms)방류량(ms)저수위(m)저수량(백만m3)저수율
일자/시간(t)1.0000.1330.2600.6580.6580.181
유입량(ms)0.1331.0000.8380.4150.4150.384
방류량(ms)0.2600.8381.0000.2730.2730.000
저수위(m)0.6580.4150.2731.0001.0000.995
저수량(백만m3)0.6580.4150.2731.0001.0000.995
저수율0.1810.3840.0000.9950.9951.000

Missing values

2024-04-17T03:11:28.663740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T03:11:28.763003image/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
0감포20190109031039.2300.030.032.23784.9
1감포20190108153039.2400.090.092.23984.9
2감포20190109135039.2300.040.042.23784.9
3감포20190109033039.2300.030.032.23784.9
4감포20190108205039.2400.050.082.23984.9
5감포20190108155039.2400.090.092.23984.9
6감포20190109191039.2300.040.042.23784.9
7감포20190109141039.2300.040.042.23784.9
8감포20190109085039.2300.030.032.23784.9
9감포20190109035039.2300.030.032.23784.9
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90감포20190109061039.2300.030.032.23784.9
91감포20190109055039.2300.030.032.23784.9
92감포20190109051039.2300.030.032.23784.9
93감포20190109045039.2300.030.032.23784.9
94감포20190109025039.2300.030.032.23784.9
95감포20190109023039.2300.030.032.23784.9
96감포20190109015039.2300.030.032.23784.9
97감포20190109013039.2300.0210.0212.23784.9
98감포20190108145039.2400.090.092.23984.9
99감포20190108151039.2400.090.092.23984.9