Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory45.3 B

Variable types

Categorical2
Numeric3

Dataset

Description샘플 데이터
Author세종대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=96965730-31dd-11ea-b948-6903051715f4

Alerts

소유역 명 has constant value ""Constant
전망 일 is highly overall correlated with 증발 량(mm)High correlation
강수 량(mm) is highly overall correlated with 증발 량(mm)High correlation
증발 량(mm) is highly overall correlated with 전망 일 and 2 other fieldsHigh correlation
유량 계(mm) is highly overall correlated with 증발 량(mm)High correlation
유량 계(mm) is highly imbalanced (85.9%)Imbalance
전망 일 has unique valuesUnique
강수 량(mm) has 17 (17.0%) zerosZeros

Reproduction

Analysis started2023-12-10 13:09:54.414691
Analysis finished2023-12-10 13:09:56.429950
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소유역 명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
AM_01_01_01
100 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAM_01_01_01
2nd rowAM_01_01_01
3rd rowAM_01_01_01
4th rowAM_01_01_01
5th rowAM_01_01_01

Common Values

ValueCountFrequency (%)
AM_01_01_01 100
100.0%

Length

2023-12-10T22:09:56.569225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:09:56.722321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
am_01_01_01 100
100.0%

전망 일
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20070235
Minimum20070101
Maximum20070410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:09:56.953116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070101
5-th percentile20070106
Q120070126
median20070220
Q320070316
95-th percentile20070405
Maximum20070410
Range309
Interquartile range (IQR)190.5

Descriptive statistics

Standard deviation98.046521
Coefficient of variation (CV)4.8851707 × 10-6
Kurtosis-1.1930186
Mean20070235
Median Absolute Deviation (MAD)95.5
Skewness0.15908349
Sum2.0070235 × 109
Variance9613.1203
MonotonicityStrictly increasing
2023-12-10T22:09:57.248021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070101 1
 
1.0%
20070306 1
 
1.0%
20070316 1
 
1.0%
20070315 1
 
1.0%
20070314 1
 
1.0%
20070313 1
 
1.0%
20070312 1
 
1.0%
20070311 1
 
1.0%
20070310 1
 
1.0%
20070309 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
20070101 1
1.0%
20070102 1
1.0%
20070103 1
1.0%
20070104 1
1.0%
20070105 1
1.0%
20070106 1
1.0%
20070107 1
1.0%
20070108 1
1.0%
20070109 1
1.0%
20070110 1
1.0%
ValueCountFrequency (%)
20070410 1
1.0%
20070409 1
1.0%
20070408 1
1.0%
20070407 1
1.0%
20070406 1
1.0%
20070405 1
1.0%
20070404 1
1.0%
20070403 1
1.0%
20070402 1
1.0%
20070401 1
1.0%

강수 량(mm)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0714
Minimum0
Maximum0.33
Zeros17
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:09:57.473850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.04
Q30.1225
95-th percentile0.2005
Maximum0.33
Range0.33
Interquartile range (IQR)0.1125

Descriptive statistics

Standard deviation0.075958787
Coefficient of variation (CV)1.0638486
Kurtosis1.1053573
Mean0.0714
Median Absolute Deviation (MAD)0.04
Skewness1.1982226
Sum7.14
Variance0.0057697374
MonotonicityNot monotonic
2023-12-10T22:09:57.862958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 17
17.0%
0.01 15
15.0%
0.02 10
10.0%
0.08 6
 
6.0%
0.03 6
 
6.0%
0.07 5
 
5.0%
0.13 5
 
5.0%
0.18 4
 
4.0%
0.05 4
 
4.0%
0.12 4
 
4.0%
Other values (13) 24
24.0%
ValueCountFrequency (%)
0.0 17
17.0%
0.01 15
15.0%
0.02 10
10.0%
0.03 6
 
6.0%
0.04 3
 
3.0%
0.05 4
 
4.0%
0.06 2
 
2.0%
0.07 5
 
5.0%
0.08 6
 
6.0%
0.1 2
 
2.0%
ValueCountFrequency (%)
0.33 2
2.0%
0.23 1
 
1.0%
0.21 2
2.0%
0.2 2
2.0%
0.19 2
2.0%
0.18 4
4.0%
0.17 1
 
1.0%
0.16 3
3.0%
0.15 2
2.0%
0.14 1
 
1.0%

증발 량(mm)
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.078
Minimum0.02
Maximum0.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:09:58.263838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.02
Q10.05
median0.07
Q30.1
95-th percentile0.16
Maximum0.23
Range0.21
Interquartile range (IQR)0.05

Descriptive statistics

Standard deviation0.043785519
Coefficient of variation (CV)0.56135281
Kurtosis0.69512986
Mean0.078
Median Absolute Deviation (MAD)0.025
Skewness0.94490837
Sum7.8
Variance0.0019171717
MonotonicityNot monotonic
2023-12-10T22:09:58.421049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.05 13
13.0%
0.06 12
12.0%
0.09 11
11.0%
0.03 9
9.0%
0.07 8
8.0%
0.02 7
7.0%
0.04 7
7.0%
0.13 6
 
6.0%
0.08 6
 
6.0%
0.12 5
 
5.0%
Other values (8) 16
16.0%
ValueCountFrequency (%)
0.02 7
7.0%
0.03 9
9.0%
0.04 7
7.0%
0.05 13
13.0%
0.06 12
12.0%
0.07 8
8.0%
0.08 6
6.0%
0.09 11
11.0%
0.1 4
 
4.0%
0.11 1
 
1.0%
ValueCountFrequency (%)
0.23 1
 
1.0%
0.2 1
 
1.0%
0.17 1
 
1.0%
0.16 3
3.0%
0.15 4
4.0%
0.14 1
 
1.0%
0.13 6
6.0%
0.12 5
5.0%
0.11 1
 
1.0%
0.1 4
4.0%

유량 계(mm)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.02
98 
0.03
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.02
2nd row0.02
3rd row0.02
4th row0.02
5th row0.02

Common Values

ValueCountFrequency (%)
0.02 98
98.0%
0.03 2
 
2.0%

Length

2023-12-10T22:09:58.594459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:09:58.736525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.02 98
98.0%
0.03 2
 
2.0%

Interactions

2023-12-10T22:09:55.552178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:54.671705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:55.123581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:55.732595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:54.841232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:55.266936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:55.867326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:54.995301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:09:55.408412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:09:58.840479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전망 일강수 량(mm)증발 량(mm)유량 계(mm)
전망 일1.0000.0870.5680.182
강수 량(mm)0.0871.0000.6980.665
증발 량(mm)0.5680.6981.0000.886
유량 계(mm)0.1820.6650.8861.000
2023-12-10T22:09:59.046364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전망 일강수 량(mm)증발 량(mm)유량 계(mm)
전망 일1.0000.3630.6690.129
강수 량(mm)0.3631.0000.6250.489
증발 량(mm)0.6690.6251.0000.690
유량 계(mm)0.1290.4890.6901.000

Missing values

2023-12-10T22:09:56.088591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:09:56.296371image/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

소유역 명전망 일강수 량(mm)증발 량(mm)유량 계(mm)
0AM_01_01_01200701010.010.070.02
1AM_01_01_01200701020.010.040.02
2AM_01_01_01200701030.010.030.02
3AM_01_01_01200701040.00.030.02
4AM_01_01_01200701050.00.020.02
5AM_01_01_01200701060.00.030.02
6AM_01_01_01200701070.00.030.02
7AM_01_01_01200701080.00.020.02
8AM_01_01_01200701090.010.030.02
9AM_01_01_01200701100.00.020.02
소유역 명전망 일강수 량(mm)증발 량(mm)유량 계(mm)
90AM_01_01_01200704010.180.230.03
91AM_01_01_01200704020.080.150.02
92AM_01_01_01200704030.00.090.02
93AM_01_01_01200704040.050.10.02
94AM_01_01_01200704050.120.130.02
95AM_01_01_01200704060.160.140.02
96AM_01_01_01200704070.00.090.02
97AM_01_01_01200704080.010.090.02
98AM_01_01_01200704090.010.090.02
99AM_01_01_01200704100.030.090.02