Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory63.3 B

Variable types

Numeric5
Categorical2

Dataset

Description샘플 데이터
Author세종대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=a3b1bf90-31dd-11ea-b948-6903051715f4

Alerts

위도(°) has constant value ""Constant
그리드 번호 is highly overall correlated with 경도(°) and 2 other fieldsHigh correlation
경도(°) is highly overall correlated with 그리드 번호 and 2 other fieldsHigh correlation
효율 량 is highly overall correlated with 그리드 번호 and 3 other fieldsHigh correlation
잠재 발전 량(KW/㎢/m) is highly overall correlated with 효율 량 and 1 other fieldsHigh correlation
발전 가능 량(KW/㎢/m) is highly overall correlated with 효율 량 and 1 other fieldsHigh correlation
국가 코드 is highly overall correlated with 그리드 번호 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 12:17:39.725092
Analysis finished2023-12-10 12:17:43.277711
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

그리드 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.29
Minimum1
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:17:43.346575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q118.75
median41.5
Q366.25
95-th percentile86.05
Maximum91
Range90
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation26.658444
Coefficient of variation (CV)0.61581067
Kurtosis-1.2568088
Mean43.29
Median Absolute Deviation (MAD)24
Skewness0.1718823
Sum4329
Variance710.67263
MonotonicityIncreasing
2023-12-10T21:17:43.464287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15 2
 
2.0%
23 2
 
2.0%
16 2
 
2.0%
14 2
 
2.0%
13 2
 
2.0%
12 2
 
2.0%
11 2
 
2.0%
22 2
 
2.0%
17 2
 
2.0%
63 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%
87 1
1.0%
86 1
1.0%
85 1
1.0%
84 1
1.0%
83 1
1.0%
82 1
1.0%

국가 코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
RS
87 
KZ
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
RS 87
87.0%
KZ 13
 
13.0%

Length

2023-12-10T21:17:43.579371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:17:43.691875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rs 87
87.0%
kz 13
 
13.0%

위도(°)
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
54.75
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row54.75
2nd row54.75
3rd row54.75
4th row54.75
5th row54.75

Common Values

ValueCountFrequency (%)
54.75 100
100.0%

Length

2023-12-10T21:17:43.838385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:17:43.916744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
54.75 100
100.0%

경도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.395
Minimum60.25
Maximum105.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:17:44.023048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60.25
5-th percentile62.725
Q169.125
median80.5
Q392.875
95-th percentile102.775
Maximum105.25
Range45
Interquartile range (IQR)23.75

Descriptive statistics

Standard deviation13.329222
Coefficient of variation (CV)0.16375971
Kurtosis-1.2568088
Mean81.395
Median Absolute Deviation (MAD)12
Skewness0.1718823
Sum8139.5
Variance177.66816
MonotonicityIncreasing
2023-12-10T21:17:44.144480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67.25 2
 
2.0%
71.25 2
 
2.0%
67.75 2
 
2.0%
66.75 2
 
2.0%
66.25 2
 
2.0%
65.75 2
 
2.0%
65.25 2
 
2.0%
70.75 2
 
2.0%
68.25 2
 
2.0%
91.25 1
 
1.0%
Other values (81) 81
81.0%
ValueCountFrequency (%)
60.25 1
1.0%
60.75 1
1.0%
61.25 1
1.0%
61.75 1
1.0%
62.25 1
1.0%
62.75 1
1.0%
63.25 1
1.0%
63.75 1
1.0%
64.25 1
1.0%
64.75 1
1.0%
ValueCountFrequency (%)
105.25 1
1.0%
104.75 1
1.0%
104.25 1
1.0%
103.75 1
1.0%
103.25 1
1.0%
102.75 1
1.0%
102.25 1
1.0%
101.75 1
1.0%
101.25 1
1.0%
100.75 1
1.0%

효율 량
Real number (ℝ)

HIGH CORRELATION 

Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.651062
Minimum0.2933
Maximum0.7422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:17:44.264267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2933
5-th percentile0.4706
Q10.6199
median0.67275
Q30.716875
95-th percentile0.732245
Maximum0.7422
Range0.4489
Interquartile range (IQR)0.096975

Descriptive statistics

Standard deviation0.08877735
Coefficient of variation (CV)0.13635775
Kurtosis5.1078964
Mean0.651062
Median Absolute Deviation (MAD)0.0468
Skewness-2.0602972
Sum65.1062
Variance0.0078814179
MonotonicityNot monotonic
2023-12-10T21:17:44.585754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7198 3
 
3.0%
0.6914 2
 
2.0%
0.6199 2
 
2.0%
0.7214 2
 
2.0%
0.7183 2
 
2.0%
0.7234 2
 
2.0%
0.7289 2
 
2.0%
0.6904 2
 
2.0%
0.7244 2
 
2.0%
0.6729 2
 
2.0%
Other values (77) 79
79.0%
ValueCountFrequency (%)
0.2933 1
1.0%
0.2982 1
1.0%
0.3461 1
1.0%
0.4553 1
1.0%
0.4573 1
1.0%
0.4713 1
1.0%
0.4742 1
1.0%
0.5017 1
1.0%
0.5371 1
1.0%
0.5462 1
1.0%
ValueCountFrequency (%)
0.7422 1
1.0%
0.7373 1
1.0%
0.7348 1
1.0%
0.7345 1
1.0%
0.7331 1
1.0%
0.7322 1
1.0%
0.7295 1
1.0%
0.7289 2
2.0%
0.7247 1
1.0%
0.7244 2
2.0%

잠재 발전 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.039873
Minimum0.0039
Maximum0.1647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:17:44.701025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0039
5-th percentile0.008405
Q10.026475
median0.04095
Q30.048
95-th percentile0.066325
Maximum0.1647
Range0.1608
Interquartile range (IQR)0.021525

Descriptive statistics

Standard deviation0.024279283
Coefficient of variation (CV)0.60891539
Kurtosis7.8025103
Mean0.039873
Median Absolute Deviation (MAD)0.01265
Skewness1.8572445
Sum3.9873
Variance0.00058948361
MonotonicityNot monotonic
2023-12-10T21:17:44.856743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0443 3
 
3.0%
0.0396 3
 
3.0%
0.0454 3
 
3.0%
0.0403 3
 
3.0%
0.044 2
 
2.0%
0.0273 2
 
2.0%
0.0246 2
 
2.0%
0.0238 2
 
2.0%
0.0419 2
 
2.0%
0.045 2
 
2.0%
Other values (73) 76
76.0%
ValueCountFrequency (%)
0.0039 1
1.0%
0.004 1
1.0%
0.0044 1
1.0%
0.0062 1
1.0%
0.0066 1
1.0%
0.0085 1
1.0%
0.0086 1
1.0%
0.0087 1
1.0%
0.0091 1
1.0%
0.0093 1
1.0%
ValueCountFrequency (%)
0.1647 1
1.0%
0.1328 1
1.0%
0.092 1
1.0%
0.0898 1
1.0%
0.0687 1
1.0%
0.0662 1
1.0%
0.0657 1
1.0%
0.0648 1
1.0%
0.0642 1
1.0%
0.0631 1
1.0%

발전 가능 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.026821
Minimum0.0012
Maximum0.0949
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:17:44.999578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0012
5-th percentile0.00452
Q10.016675
median0.0277
Q30.03455
95-th percentile0.04752
Maximum0.0949
Range0.0937
Interquartile range (IQR)0.017875

Descriptive statistics

Standard deviation0.015879307
Coefficient of variation (CV)0.59204753
Kurtosis3.0138475
Mean0.026821
Median Absolute Deviation (MAD)0.0094
Skewness0.96361977
Sum2.6821
Variance0.00025215238
MonotonicityNot monotonic
2023-12-10T21:17:45.118415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0273 3
 
3.0%
0.0371 2
 
2.0%
0.0312 2
 
2.0%
0.0046 2
 
2.0%
0.0184 2
 
2.0%
0.0153 2
 
2.0%
0.0147 2
 
2.0%
0.0328 2
 
2.0%
0.0301 2
 
2.0%
0.0325 2
 
2.0%
Other values (73) 79
79.0%
ValueCountFrequency (%)
0.0012 2
2.0%
0.0015 1
1.0%
0.0028 1
1.0%
0.003 1
1.0%
0.0046 2
2.0%
0.0047 1
1.0%
0.005 1
1.0%
0.0052 1
1.0%
0.0054 1
1.0%
0.0057 1
1.0%
ValueCountFrequency (%)
0.0949 1
1.0%
0.0785 1
1.0%
0.0574 1
1.0%
0.0568 1
1.0%
0.0479 1
1.0%
0.0475 1
1.0%
0.0468 1
1.0%
0.0464 1
1.0%
0.045 1
1.0%
0.0439 1
1.0%

Interactions

2023-12-10T21:17:42.670733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:40.938989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.563342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.937926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.305273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.769700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.078033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.640610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.002470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.373650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.869905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.147336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.710695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.065287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.444302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.936157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.412691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.778528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.131908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.513714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:43.014935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.492970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:41.858214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.228153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:17:42.594281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:17:45.199064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그리드 번호국가 코드경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
그리드 번호1.0000.7491.0000.6370.7400.740
국가 코드0.7491.0000.7720.0000.3410.296
경도(°)1.0000.7721.0000.6360.7360.740
효율 량0.6370.0000.6361.0000.6490.713
잠재 발전 량(KW/㎢/m)0.7400.3410.7360.6491.0000.994
발전 가능 량(KW/㎢/m)0.7400.2960.7400.7130.9941.000
2023-12-10T21:17:45.308125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그리드 번호경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)국가 코드
그리드 번호1.0001.000-0.522-0.398-0.4240.583
경도(°)1.0001.000-0.522-0.398-0.4240.583
효율 량-0.522-0.5221.0000.6590.7120.000
잠재 발전 량(KW/㎢/m)-0.398-0.3980.6591.0000.9900.247
발전 가능 량(KW/㎢/m)-0.424-0.4240.7120.9901.0000.214
국가 코드0.5830.5830.0000.2470.2141.000

Missing values

2023-12-10T21:17:43.113183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:17:43.232013image/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

그리드 번호국가 코드위도(°)경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
01RS54.7560.250.70820.05240.0371
12RS54.7560.750.71280.04820.0344
23RS54.7561.250.70850.05990.0424
34RS54.7561.750.71050.05280.0375
45RS54.7562.250.61930.02750.017
56RS54.7562.750.62680.03030.019
67RS54.7563.250.62420.02740.0171
78RS54.7563.750.63690.02960.0188
89RS54.7564.250.72470.04470.0324
910RS54.7564.750.72440.04590.0332
그리드 번호국가 코드위도(°)경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
9082RS54.75100.750.66720.01390.0093
9183RS54.75101.250.53710.00860.0046
9284RS54.75101.750.55480.00850.0047
9385RS54.75102.250.59810.00950.0057
9486RS54.75102.750.34610.00440.0015
9587RS54.75103.250.60150.00870.0052
9688RS54.75103.750.29820.00390.0012
9789RS54.75104.250.29330.0040.0012
9890RS54.75104.750.45730.00620.0028
9991RS54.75105.250.45530.00660.003