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

Categorical3
Numeric5

Alerts

댐이름 has constant value ""Constant
강우량(mm) has constant value ""Constant
일자/시간(t) is highly overall correlated with 저수위(m) and 4 other fieldsHigh correlation
저수위(m) 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 10:22:56.417295
Analysis finished2023-12-10 10:23:00.845142
Duration4.43 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

2023-12-10T19:23:00.942279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:01.082227image/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%
Mean2.0221028 × 109
Minimum2.0221023 × 109
Maximum2.0221031 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:01.243413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0221023 × 109
5-th percentile2.0221023 × 109
Q12.0221024 × 109
median2.0221029 × 109
Q32.022103 × 109
95-th percentile2.0221031 × 109
Maximum2.0221031 × 109
Range805
Interquartile range (IQR)603.5

Descriptive statistics

Standard deviation301.2727
Coefficient of variation (CV)1.489898 × 10-7
Kurtosis-1.4763436
Mean2.0221028 × 109
Median Absolute Deviation (MAD)186
Skewness-0.57428362
Sum2.0221028 × 1011
Variance90765.24
MonotonicityNot monotonic
2023-12-10T19:23:01.763516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2022103020 1
 
1.0%
2022102501 1
 
1.0%
2022102406 1
 
1.0%
2022102409 1
 
1.0%
2022102410 1
 
1.0%
2022102412 1
 
1.0%
2022102413 1
 
1.0%
2022102417 1
 
1.0%
2022102418 1
 
1.0%
2022102420 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2022102319 1
1.0%
2022102320 1
1.0%
2022102321 1
1.0%
2022102322 1
1.0%
2022102323 1
1.0%
2022102324 1
1.0%
2022102401 1
1.0%
2022102402 1
1.0%
2022102403 1
1.0%
2022102404 1
1.0%
ValueCountFrequency (%)
2022103124 1
1.0%
2022103123 1
1.0%
2022103122 1
1.0%
2022103121 1
1.0%
2022103120 1
1.0%
2022103119 1
1.0%
2022103118 1
1.0%
2022103117 1
1.0%
2022103116 1
1.0%
2022103115 1
1.0%

저수위(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.61176
Minimum23.48
Maximum23.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:01.965143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.48
5-th percentile23.4995
Q123.6
median23.6
Q323.67
95-th percentile23.7
Maximum23.7
Range0.22
Interquartile range (IQR)0.07

Descriptive statistics

Standard deviation0.059278851
Coefficient of variation (CV)0.0025105647
Kurtosis-0.36868667
Mean23.61176
Median Absolute Deviation (MAD)0.0365
Skewness-0.42803026
Sum2361.176
Variance0.0035139822
MonotonicityNot monotonic
2023-12-10T19:23:02.107910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
23.6 48
48.0%
23.67 21
21.0%
23.7 7
 
7.0%
23.5 5
 
5.0%
23.49 4
 
4.0%
23.69 3
 
3.0%
23.54 2
 
2.0%
23.52 2
 
2.0%
23.48 1
 
1.0%
23.57 1
 
1.0%
Other values (6) 6
 
6.0%
ValueCountFrequency (%)
23.48 1
 
1.0%
23.49 4
 
4.0%
23.5 5
 
5.0%
23.51 1
 
1.0%
23.52 2
 
2.0%
23.54 2
 
2.0%
23.557 1
 
1.0%
23.57 1
 
1.0%
23.59 1
 
1.0%
23.6 48
48.0%
ValueCountFrequency (%)
23.7 7
 
7.0%
23.691 1
 
1.0%
23.69 3
 
3.0%
23.68 1
 
1.0%
23.678 1
 
1.0%
23.67 21
21.0%
23.6 48
48.0%
23.59 1
 
1.0%
23.57 1
 
1.0%
23.557 1
 
1.0%

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

2023-12-10T19:23:02.270374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:02.406058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

유입량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.54745
Minimum15.705
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:02.534740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.705
5-th percentile17.5294
Q124.3
median24.3
Q330.3
95-th percentile33
Maximum33
Range17.295
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.6208368
Coefficient of variation (CV)0.18087272
Kurtosis-0.6794614
Mean25.54745
Median Absolute Deviation (MAD)3.0385
Skewness-0.12891118
Sum2554.745
Variance21.352133
MonotonicityNot monotonic
2023-12-10T19:23:02.738371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
24.3 47
47.0%
30.3 20
20.0%
33.0 7
 
7.0%
17.7 3
 
3.0%
32.1 2
 
2.0%
17.1 2
 
2.0%
21.586 1
 
1.0%
24.059 1
 
1.0%
20.937 1
 
1.0%
20.547 1
 
1.0%
Other values (15) 15
 
15.0%
ValueCountFrequency (%)
15.705 1
 
1.0%
16.397 1
 
1.0%
16.8 1
 
1.0%
17.1 2
2.0%
17.552 1
 
1.0%
17.7 3
3.0%
17.744 1
 
1.0%
17.785 1
 
1.0%
18.353 1
 
1.0%
19.02 1
 
1.0%
ValueCountFrequency (%)
33.0 7
 
7.0%
32.1 2
 
2.0%
31.989 1
 
1.0%
31.963 1
 
1.0%
30.978 1
 
1.0%
30.3 20
20.0%
30.279 1
 
1.0%
29.489 1
 
1.0%
24.3 47
47.0%
24.059 1
 
1.0%

방류량(ms)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.65245
Minimum16.705
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:02.930007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.705
5-th percentile17.42
Q124.3
median24.3
Q330.3
95-th percentile33
Maximum33
Range16.295
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.581328
Coefficient of variation (CV)0.17859222
Kurtosis-0.71056642
Mean25.65245
Median Absolute Deviation (MAD)1.85
Skewness-0.092572421
Sum2565.245
Variance20.988566
MonotonicityNot monotonic
2023-12-10T19:23:03.123757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
24.3 47
47.0%
30.3 20
20.0%
33.0 7
 
7.0%
17.7 3
 
3.0%
32.1 3
 
3.0%
17.1 2
 
2.0%
19.53 1
 
1.0%
25.115 1
 
1.0%
23.02 1
 
1.0%
21.88 1
 
1.0%
Other values (14) 14
 
14.0%
ValueCountFrequency (%)
16.705 1
 
1.0%
16.785 1
 
1.0%
17.1 2
2.0%
17.325 1
 
1.0%
17.425 1
 
1.0%
17.7 3
3.0%
17.8 1
 
1.0%
18.23 1
 
1.0%
18.58 1
 
1.0%
19.53 1
 
1.0%
ValueCountFrequency (%)
33.0 7
 
7.0%
32.935 1
 
1.0%
32.1 3
 
3.0%
31.335 1
 
1.0%
31.2 1
 
1.0%
30.35 1
 
1.0%
30.3 20
20.0%
25.115 1
 
1.0%
24.3 47
47.0%
23.76 1
 
1.0%

저수량(백만m3)
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.682316
Minimum0.6333
Maximum0.7159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:23:03.294166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6333
5-th percentile0.640415
Q10.6777
median0.6777
Q30.7043
95-th percentile0.7159
Maximum0.7159
Range0.0826
Interquartile range (IQR)0.0266

Descriptive statistics

Standard deviation0.022316311
Coefficient of variation (CV)0.032706709
Kurtosis-0.41063354
Mean0.682316
Median Absolute Deviation (MAD)0.0137
Skewness-0.39223006
Sum68.2316
Variance0.00049801772
MonotonicityNot monotonic
2023-12-10T19:23:03.464651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.6777 48
48.0%
0.7043 21
21.0%
0.7159 7
 
7.0%
0.6406 5
 
5.0%
0.6369 4
 
4.0%
0.712 3
 
3.0%
0.6553 2
 
2.0%
0.6479 2
 
2.0%
0.6333 1
 
1.0%
0.6664 1
 
1.0%
Other values (6) 6
 
6.0%
ValueCountFrequency (%)
0.6333 1
 
1.0%
0.6369 4
 
4.0%
0.6406 5
 
5.0%
0.6442 1
 
1.0%
0.6479 2
 
2.0%
0.6553 2
 
2.0%
0.6616 1
 
1.0%
0.6664 1
 
1.0%
0.6739 1
 
1.0%
0.6777 48
48.0%
ValueCountFrequency (%)
0.7159 7
 
7.0%
0.7124 1
 
1.0%
0.712 3
 
3.0%
0.7082 1
 
1.0%
0.7074 1
 
1.0%
0.7043 21
21.0%
0.6777 48
48.0%
0.6739 1
 
1.0%
0.6664 1
 
1.0%
0.6616 1
 
1.0%

저수율
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1.0
82 
0.9
18 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 82
82.0%
0.9 18
 
18.0%

Length

2023-12-10T19:23:03.653859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:23:03.805234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0 82
82.0%
0.9 18
 
18.0%

Interactions

2023-12-10T19:22:59.749327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:56.745519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.533141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.300903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.037583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.897542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:56.919970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.705178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.461978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.153651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:00.005225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.069615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.837864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.610932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.272753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:00.156237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.222271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.010263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.758728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.440726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:23:00.324247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:57.385984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.171594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:58.918573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:22:59.607403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:23:03.910494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.0000.7840.7960.7990.7950.961
저수위(m)0.7841.0000.9780.9870.9990.998
유입량(ms)0.7960.9781.0000.9670.9750.998
방류량(ms)0.7990.9870.9671.0000.9850.998
저수량(백만m3)0.7950.9990.9750.9851.0001.000
저수율0.9610.9980.9980.9981.0001.000
2023-12-10T19:23:04.074481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자/시간(t)저수위(m)유입량(ms)방류량(ms)저수량(백만m3)저수율
일자/시간(t)1.000-0.935-0.917-0.940-0.9350.807
저수위(m)-0.9351.0000.9910.9951.0000.969
유입량(ms)-0.9170.9911.0000.9770.9910.934
방류량(ms)-0.9400.9950.9771.0000.9950.934
저수량(백만m3)-0.9351.0000.9910.9951.0000.969
저수율0.8070.9690.9340.9340.9691.000

Missing values

2023-12-10T19:23:00.508786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:23:00.761679image/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
0군남202210302023.6024.324.30.67771.0
1군남202210290923.6024.324.30.67771.0
2군남202210232223.7033.033.00.71591.0
3군남202210302123.6024.324.30.67771.0
4군남202210300123.6024.324.30.67771.0
5군남202210291023.6024.324.30.67771.0
6군남202210241423.67030.330.30.70431.0
7군남202210232323.7033.033.00.71591.0
8군남202210311323.5016.817.80.64060.9
9군남202210302223.6024.324.30.67771.0
댐이름일자/시간(t)저수위(m)강우량(mm)유입량(ms)방류량(ms)저수량(백만m3)저수율
90군남202210310523.6024.324.30.67771.0
91군남202210310423.6024.324.30.67771.0
92군남202210310223.6024.324.30.67771.0
93군남202210310123.6024.324.30.67771.0
94군남202210301923.6024.324.30.67771.0
95군남202210301823.6024.324.30.67771.0
96군남202210301623.6024.324.30.67771.0
97군남202210301523.6024.324.30.67771.0
98군남202210290723.6024.05925.1150.67771.0
99군남202210290823.6024.324.30.67771.0