Overview

Dataset statistics

Number of variables6
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory56.1 B

Variable types

DateTime1
Categorical1
Numeric4

Dataset

Description한국동서발전의 풍력출자회사 풍속데이터 정보입니다. 풍력출자회사 풍속데이터는 연월, 단위, 경주1단계, 경주2단계, 호남풍력발전, 백수풍력발전의 항목으로 구성됩니다.
Author한국동서발전(주)
URLhttps://www.data.go.kr/data/15065378/fileData.do

Alerts

단위 has constant value ""Constant
경주1단계 is highly overall correlated with 경주2단계 and 2 other fieldsHigh correlation
경주2단계 is highly overall correlated with 경주1단계 and 2 other fieldsHigh correlation
호남풍력발전 is highly overall correlated with 경주1단계 and 2 other fieldsHigh correlation
백수풍력발전 is highly overall correlated with 경주1단계 and 2 other fieldsHigh correlation
연월 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:57:55.114170
Analysis finished2023-12-12 17:57:57.380983
Duration2.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Date

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2019-01-01 00:00:00
Maximum2021-08-01 00:00:00
2023-12-13T02:57:57.464358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:57.650853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
m/s
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowm/s
2nd rowm/s
3rd rowm/s
4th rowm/s
5th rowm/s

Common Values

ValueCountFrequency (%)
m/s 32
100.0%

Length

2023-12-13T02:57:57.825449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:57:57.929304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m/s 32
100.0%

경주1단계
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.61875
Minimum4.9
Maximum8.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T02:57:58.049910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.9
5-th percentile5.165
Q16.075
median6.7
Q37.125
95-th percentile8.025
Maximum8.8
Range3.9
Interquartile range (IQR)1.05

Descriptive statistics

Standard deviation0.92123252
Coefficient of variation (CV)0.13918527
Kurtosis0.006161325
Mean6.61875
Median Absolute Deviation (MAD)0.55
Skewness0.064516392
Sum211.8
Variance0.84866935
MonotonicityNot monotonic
2023-12-13T02:57:58.197924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
7.0 3
 
9.4%
5.5 2
 
6.2%
6.8 2
 
6.2%
5.3 2
 
6.2%
6.4 2
 
6.2%
6.6 2
 
6.2%
6.7 2
 
6.2%
7.3 2
 
6.2%
8.3 1
 
3.1%
5.0 1
 
3.1%
Other values (13) 13
40.6%
ValueCountFrequency (%)
4.9 1
3.1%
5.0 1
3.1%
5.3 2
6.2%
5.5 2
6.2%
5.6 1
3.1%
6.0 1
3.1%
6.1 1
3.1%
6.3 1
3.1%
6.4 2
6.2%
6.5 1
3.1%
ValueCountFrequency (%)
8.8 1
 
3.1%
8.3 1
 
3.1%
7.8 1
 
3.1%
7.7 1
 
3.1%
7.4 1
 
3.1%
7.3 2
6.2%
7.2 1
 
3.1%
7.1 1
 
3.1%
7.0 3
9.4%
6.9 1
 
3.1%

경주2단계
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.1590625
Minimum5.12
Maximum10.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T02:57:58.365101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.12
5-th percentile5.23
Q16.09
median7.045
Q37.77
95-th percentile9.7165
Maximum10.43
Range5.31
Interquartile range (IQR)1.68

Descriptive statistics

Standard deviation1.3762885
Coefficient of variation (CV)0.19224424
Kurtosis-0.062887703
Mean7.1590625
Median Absolute Deviation (MAD)0.815
Skewness0.57508427
Sum229.09
Variance1.8941701
MonotonicityNot monotonic
2023-12-13T02:57:58.514545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5.23 2
 
6.2%
7.77 2
 
6.2%
9.81 1
 
3.1%
7.03 1
 
3.1%
5.8 1
 
3.1%
5.33 1
 
3.1%
5.12 1
 
3.1%
6.86 1
 
3.1%
7.31 1
 
3.1%
6.89 1
 
3.1%
Other values (20) 20
62.5%
ValueCountFrequency (%)
5.12 1
3.1%
5.23 2
6.2%
5.33 1
3.1%
5.71 1
3.1%
5.79 1
3.1%
5.8 1
3.1%
5.94 1
3.1%
6.14 1
3.1%
6.38 1
3.1%
6.52 1
3.1%
ValueCountFrequency (%)
10.43 1
3.1%
9.81 1
3.1%
9.64 1
3.1%
9.01 1
3.1%
8.84 1
3.1%
8.53 1
3.1%
8.21 1
3.1%
7.77 2
6.2%
7.64 1
3.1%
7.33 1
3.1%

호남풍력발전
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.86875
Minimum3.8
Maximum5.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T02:57:58.655143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.8
5-th percentile3.924
Q14.2975
median4.845
Q35.35
95-th percentile5.765
Maximum5.98
Range2.18
Interquartile range (IQR)1.0525

Descriptive statistics

Standard deviation0.62005593
Coefficient of variation (CV)0.12735423
Kurtosis-1.0521722
Mean4.86875
Median Absolute Deviation (MAD)0.535
Skewness-0.093975298
Sum155.8
Variance0.38446935
MonotonicityNot monotonic
2023-12-13T02:57:58.817958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4.73 2
 
6.2%
4.16 2
 
6.2%
5.12 2
 
6.2%
4.84 2
 
6.2%
5.24 1
 
3.1%
4.26 1
 
3.1%
4.04 1
 
3.1%
3.88 1
 
3.1%
4.85 1
 
3.1%
4.75 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
3.8 1
3.1%
3.88 1
3.1%
3.96 1
3.1%
4.04 1
3.1%
4.06 1
3.1%
4.16 2
6.2%
4.26 1
3.1%
4.31 1
3.1%
4.57 1
3.1%
4.61 1
3.1%
ValueCountFrequency (%)
5.98 1
3.1%
5.82 1
3.1%
5.72 1
3.1%
5.64 1
3.1%
5.61 1
3.1%
5.45 1
3.1%
5.44 1
3.1%
5.38 1
3.1%
5.34 1
3.1%
5.32 1
3.1%

백수풍력발전
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.865625
Minimum3.65
Maximum6.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-13T02:57:58.964618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.65
5-th percentile3.73
Q14.25
median4.91
Q35.4525
95-th percentile5.9525
Maximum6.24
Range2.59
Interquartile range (IQR)1.2025

Descriptive statistics

Standard deviation0.75069833
Coefficient of variation (CV)0.15428611
Kurtosis-1.0929798
Mean4.865625
Median Absolute Deviation (MAD)0.655
Skewness-0.02004191
Sum155.7
Variance0.56354798
MonotonicityNot monotonic
2023-12-13T02:57:59.117285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
4.87 2
 
6.2%
3.73 2
 
6.2%
4.93 2
 
6.2%
3.95 2
 
6.2%
5.24 1
 
3.1%
3.84 1
 
3.1%
4.06 1
 
3.1%
5.98 1
 
3.1%
5.2 1
 
3.1%
5.02 1
 
3.1%
Other values (18) 18
56.2%
ValueCountFrequency (%)
3.65 1
3.1%
3.73 2
6.2%
3.84 1
3.1%
3.95 2
6.2%
4.06 1
3.1%
4.19 1
3.1%
4.27 1
3.1%
4.28 1
3.1%
4.46 1
3.1%
4.5 1
3.1%
ValueCountFrequency (%)
6.24 1
3.1%
5.98 1
3.1%
5.93 1
3.1%
5.87 1
3.1%
5.73 1
3.1%
5.64 1
3.1%
5.62 1
3.1%
5.58 1
3.1%
5.41 1
3.1%
5.27 1
3.1%

Interactions

2023-12-13T02:57:56.736058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.298031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.714391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.229897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.858927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.403500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.834803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.382301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.967254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.502460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.949628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.497838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:57.060673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:55.602457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.093841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:57:56.624568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:57:59.220460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연월경주1단계경주2단계호남풍력발전백수풍력발전
연월1.0001.0001.0001.0001.000
경주1단계1.0001.0000.9470.4570.497
경주2단계1.0000.9471.0000.6040.495
호남풍력발전1.0000.4570.6041.0000.910
백수풍력발전1.0000.4970.4950.9101.000
2023-12-13T02:57:59.368329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경주1단계경주2단계호남풍력발전백수풍력발전
경주1단계1.0000.9570.7090.722
경주2단계0.9571.0000.7240.741
호남풍력발전0.7090.7241.0000.993
백수풍력발전0.7220.7410.9931.000

Missing values

2023-12-13T02:57:57.202460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:57:57.324124image/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

연월단위경주1단계경주2단계호남풍력발전백수풍력발전
02019-01-01m/s8.39.815.245.24
12019-02-01m/s6.77.645.615.73
22019-03-01m/s7.07.025.345.27
32019-04-01m/s6.36.383.963.73
42019-05-01m/s6.87.274.314.28
52019-06-01m/s5.35.233.83.65
62019-07-01m/s6.46.524.734.5
72019-08-01m/s5.65.714.163.95
82019-09-01m/s6.05.944.614.46
92019-10-01m/s6.97.34.734.68
연월단위경주1단계경주2단계호남풍력발전백수풍력발전
222020-11-01m/s7.48.535.645.87
232020-12-01m/s8.810.435.125.02
242021-01-01m/s7.09.645.25.2
252021-02-01m/s7.79.015.825.98
262021-03-01m/s6.66.894.874.87
272021-04-01m/s7.07.314.754.93
282021-05-01m/s6.66.864.854.93
292021-06-01m/s4.95.123.883.73
302021-07-01m/s5.05.334.164.06
312021-08-01m/s5.55.84.043.84