Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory71.3 B

Variable types

Numeric5
Categorical3

Dataset

Description샘플 데이터
Author세종대학교 산학협력단
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=b9546230-31dd-11ea-b948-6903051715f4

Alerts

위도(°) has constant value ""Constant
그리드 번호 is highly overall correlated with 경도(°) and 1 other fieldsHigh correlation
경도(°) is highly overall correlated with 그리드 번호 and 1 other fieldsHigh correlation
효율 량 is highly overall correlated with 잠재 발전 량(KW/㎢/m) and 1 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 13:17:34.229435
Analysis finished2023-12-10 13:17:39.388532
Duration5.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

그리드 번호
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.54
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:39.562409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median14
Q318.25
95-th percentile23
Maximum25
Range24
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation6.5372592
Coefficient of variation (CV)0.48281087
Kurtosis-0.87958779
Mean13.54
Median Absolute Deviation (MAD)5
Skewness-0.1795137
Sum1354
Variance42.735758
MonotonicityIncreasing
2023-12-10T22:17:39.806769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
14 6
 
6.0%
15 6
 
6.0%
23 6
 
6.0%
22 6
 
6.0%
17 6
 
6.0%
11 6
 
6.0%
12 6
 
6.0%
13 6
 
6.0%
16 6
 
6.0%
24 3
 
3.0%
Other values (15) 43
43.0%
ValueCountFrequency (%)
1 3
3.0%
2 3
3.0%
3 3
3.0%
4 3
3.0%
5 3
3.0%
6 3
3.0%
7 3
3.0%
8 3
3.0%
9 3
3.0%
10 3
3.0%
ValueCountFrequency (%)
25 1
 
1.0%
24 3
3.0%
23 6
6.0%
22 6
6.0%
21 3
3.0%
20 3
3.0%
19 3
3.0%
18 3
3.0%
17 6
6.0%
16 6
6.0%

전망 코드
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
s1
34 
s2
33 
s3
33 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rows1
2nd rows2
3rd rows3
4th rows1
5th rows2

Common Values

ValueCountFrequency (%)
s1 34
34.0%
s2 33
33.0%
s3 33
33.0%

Length

2023-12-10T22:17:40.002804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:40.204375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s1 34
34.0%
s2 33
33.0%
s3 33
33.0%

국가 코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
RS
61 
KZ
39 

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 61
61.0%
KZ 39
39.0%

Length

2023-12-10T22:17:40.374321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:40.641936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rs 61
61.0%
kz 39
39.0%

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

2023-12-10T22:17:40.838696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:17:40.993310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
54.75 100
100.0%

경도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.52
Minimum60.25
Maximum72.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:41.260032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60.25
5-th percentile60.75
Q164.25
median66.75
Q368.875
95-th percentile71.25
Maximum72.25
Range12
Interquartile range (IQR)4.625

Descriptive statistics

Standard deviation3.2686296
Coefficient of variation (CV)0.049137546
Kurtosis-0.87958779
Mean66.52
Median Absolute Deviation (MAD)2.5
Skewness-0.1795137
Sum6652
Variance10.683939
MonotonicityIncreasing
2023-12-10T22:17:41.471700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
66.75 6
 
6.0%
67.25 6
 
6.0%
71.25 6
 
6.0%
70.75 6
 
6.0%
68.25 6
 
6.0%
65.25 6
 
6.0%
65.75 6
 
6.0%
66.25 6
 
6.0%
67.75 6
 
6.0%
71.75 3
 
3.0%
Other values (15) 43
43.0%
ValueCountFrequency (%)
60.25 3
3.0%
60.75 3
3.0%
61.25 3
3.0%
61.75 3
3.0%
62.25 3
3.0%
62.75 3
3.0%
63.25 3
3.0%
63.75 3
3.0%
64.25 3
3.0%
64.75 3
3.0%
ValueCountFrequency (%)
72.25 1
 
1.0%
71.75 3
3.0%
71.25 6
6.0%
70.75 6
6.0%
70.25 3
3.0%
69.75 3
3.0%
69.25 3
3.0%
68.75 3
3.0%
68.25 6
6.0%
67.75 6
6.0%

효율 량
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6629
Minimum0.5738
Maximum0.7261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:41.652989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5738
5-th percentile0.5857
Q10.63345
median0.6786
Q30.6925
95-th percentile0.709855
Maximum0.7261
Range0.1523
Interquartile range (IQR)0.05905

Descriptive statistics

Standard deviation0.04099201
Coefficient of variation (CV)0.061837396
Kurtosis-0.64650623
Mean0.6629
Median Absolute Deviation (MAD)0.0197
Skewness-0.79102109
Sum66.29
Variance0.0016803448
MonotonicityNot monotonic
2023-12-10T22:17:41.840580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6958 3
 
3.0%
0.6918 3
 
3.0%
0.6737 2
 
2.0%
0.6854 2
 
2.0%
0.6783 2
 
2.0%
0.6861 2
 
2.0%
0.6832 2
 
2.0%
0.6712 2
 
2.0%
0.6698 2
 
2.0%
0.6802 2
 
2.0%
Other values (61) 78
78.0%
ValueCountFrequency (%)
0.5738 2
2.0%
0.5774 2
2.0%
0.5857 2
2.0%
0.586 1
1.0%
0.5877 2
2.0%
0.5942 1
1.0%
0.5965 1
1.0%
0.6015 1
1.0%
0.6033 1
1.0%
0.6078 1
1.0%
ValueCountFrequency (%)
0.7261 1
1.0%
0.7191 1
1.0%
0.7113 1
1.0%
0.7109 2
2.0%
0.7098 1
1.0%
0.7074 1
1.0%
0.707 1
1.0%
0.7068 1
1.0%
0.7051 1
1.0%
0.7047 1
1.0%

잠재 발전 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.048123
Minimum0.0288
Maximum0.0724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:42.100825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0288
5-th percentile0.0309
Q10.041575
median0.0496
Q30.055225
95-th percentile0.061515
Maximum0.0724
Range0.0436
Interquartile range (IQR)0.01365

Descriptive statistics

Standard deviation0.0099340131
Coefficient of variation (CV)0.20642963
Kurtosis-0.54900886
Mean0.048123
Median Absolute Deviation (MAD)0.00645
Skewness-0.29465135
Sum4.8123
Variance9.8684617 × 10-5
MonotonicityNot monotonic
2023-12-10T22:17:42.384932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0486 4
 
4.0%
0.0567 3
 
3.0%
0.0309 3
 
3.0%
0.0562 3
 
3.0%
0.0577 2
 
2.0%
0.0583 2
 
2.0%
0.0537 2
 
2.0%
0.0487 2
 
2.0%
0.0437 2
 
2.0%
0.0435 2
 
2.0%
Other values (56) 75
75.0%
ValueCountFrequency (%)
0.0288 2
2.0%
0.0305 2
2.0%
0.0309 3
3.0%
0.0313 1
 
1.0%
0.0324 2
2.0%
0.0329 1
 
1.0%
0.0335 1
 
1.0%
0.0342 2
2.0%
0.0343 2
2.0%
0.0347 1
 
1.0%
ValueCountFrequency (%)
0.0724 1
1.0%
0.069 1
1.0%
0.0671 1
1.0%
0.0639 1
1.0%
0.0618 1
1.0%
0.0615 1
1.0%
0.059 1
1.0%
0.0588 1
1.0%
0.0587 2
2.0%
0.0583 2
2.0%

발전 가능 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.032265
Minimum0.0169
Maximum0.0502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:17:42.628062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0169
5-th percentile0.0179
Q10.0263
median0.0341
Q30.03815
95-th percentile0.04332
Maximum0.0502
Range0.0333
Interquartile range (IQR)0.01185

Descriptive statistics

Standard deviation0.0081979349
Coefficient of variation (CV)0.25408135
Kurtosis-0.7091859
Mean0.032265
Median Absolute Deviation (MAD)0.0048
Skewness-0.33679502
Sum3.2265
Variance6.7206136 × 10-5
MonotonicityNot monotonic
2023-12-10T22:17:43.382981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0312 3
 
3.0%
0.0342 3
 
3.0%
0.0365 3
 
3.0%
0.0317 2
 
2.0%
0.0364 2
 
2.0%
0.0386 2
 
2.0%
0.0337 2
 
2.0%
0.0389 2
 
2.0%
0.0326 2
 
2.0%
0.0297 2
 
2.0%
Other values (57) 77
77.0%
ValueCountFrequency (%)
0.0169 2
2.0%
0.0177 2
2.0%
0.0179 2
2.0%
0.0187 2
2.0%
0.0189 1
1.0%
0.019 1
1.0%
0.0201 1
1.0%
0.0203 1
1.0%
0.0205 1
1.0%
0.0208 2
2.0%
ValueCountFrequency (%)
0.0502 1
1.0%
0.0488 1
1.0%
0.0482 1
1.0%
0.0449 1
1.0%
0.0437 1
1.0%
0.0433 1
1.0%
0.0424 1
1.0%
0.0416 1
1.0%
0.0414 1
1.0%
0.0413 2
2.0%

Interactions

2023-12-10T22:17:37.867903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.839876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.535522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.351074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:37.145623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:38.024290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:34.972497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.705643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.498463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:37.287220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:38.243480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.117363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.884355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.649858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:37.425133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:38.544518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.266369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.044436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.822027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:37.577231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:38.727619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:35.392545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.191433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:36.975390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:17:37.697005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:17:43.539144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그리드 번호전망 코드국가 코드경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
그리드 번호1.0000.0000.7281.0000.8560.8030.884
전망 코드0.0001.0000.0000.0000.5300.5030.442
국가 코드0.7280.0001.0000.7280.2480.1580.204
경도(°)1.0000.0000.7281.0000.8410.7740.871
효율 량0.8560.5300.2480.8411.0000.8960.955
잠재 발전 량(KW/㎢/m)0.8030.5030.1580.7740.8961.0000.972
발전 가능 량(KW/㎢/m)0.8840.4420.2040.8710.9550.9721.000
2023-12-10T22:17:43.719311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국가 코드전망 코드
국가 코드1.0000.000
전망 코드0.0001.000
2023-12-10T22:17:43.852152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그리드 번호경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)전망 코드국가 코드
그리드 번호1.0001.000-0.396-0.318-0.3540.0000.546
경도(°)1.0001.000-0.396-0.318-0.3540.0000.546
효율 량-0.396-0.3961.0000.8750.9180.3600.180
잠재 발전 량(KW/㎢/m)-0.318-0.3180.8751.0000.9920.3360.112
발전 가능 량(KW/㎢/m)-0.354-0.3540.9180.9921.0000.2850.147
전망 코드0.0000.0000.3600.3360.2851.0000.000
국가 코드0.5460.5460.1800.1120.1470.0001.000

Missing values

2023-12-10T22:17:38.998916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:17:39.301199image/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 번호전망 코드국가 코드위도(°)경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
01s1RS54.7560.250.70140.06180.0433
11s2RS54.7560.250.71130.05830.0414
21s3RS54.7560.250.70510.0590.0416
32s1RS54.7560.750.70040.05670.0397
42s2RS54.7560.750.70680.05260.0371
52s3RS54.7560.750.68840.05460.0376
63s1RS54.7561.250.69360.07240.0502
73s2RS54.7561.250.71910.06710.0482
83s3RS54.7561.250.7070.0690.0488
94s1RS54.7561.750.70260.06390.0449
그리드 번호전망 코드국가 코드위도(°)경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
9023s1KZ54.7571.250.57740.03240.0187
9123s1RS54.7571.250.57740.03240.0187
9223s2KZ54.7571.250.58570.03050.0179
9323s2RS54.7571.250.58570.03050.0179
9423s3KZ54.7571.250.61160.03570.0218
9523s3RS54.7571.250.61160.03570.0218
9624s1RS54.7571.750.63970.04480.0286
9724s2RS54.7571.750.64070.04240.0271
9824s3RS54.7571.750.65580.04750.0312
9925s1RS54.7572.250.5860.03430.0201