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=af7ab750-31dd-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 13:10:27.047636
Analysis finished2023-12-10 13:10:32.064109
Duration5.02 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
2023-12-10T22:10:32.158749image/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
2023-12-10T22:10:32.362415image/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

2023-12-10T22:10:32.539179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:10:32.671371image/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

2023-12-10T22:10:32.862040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:10:32.997636image/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

2023-12-10T22:10:33.140893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:10:33.273323image/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
2023-12-10T22:10:33.400040image/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
2023-12-10T22:10:33.563681image/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 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.664163
Minimum0.5741
Maximum0.7168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:10:33.750027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5741
5-th percentile0.5813
Q10.6342
median0.6803
Q30.69485
95-th percentile0.706695
Maximum0.7168
Range0.1427
Interquartile range (IQR)0.06065

Descriptive statistics

Standard deviation0.042355791
Coefficient of variation (CV)0.063773187
Kurtosis-0.58663075
Mean0.664163
Median Absolute Deviation (MAD)0.0178
Skewness-0.93990107
Sum66.4163
Variance0.0017940131
MonotonicityNot monotonic
2023-12-10T22:10:33.908552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6941 4
 
4.0%
0.6721 4
 
4.0%
0.6996 3
 
3.0%
0.6767 3
 
3.0%
0.6975 2
 
2.0%
0.6594 2
 
2.0%
0.6903 2
 
2.0%
0.6922 2
 
2.0%
0.679 2
 
2.0%
0.6768 2
 
2.0%
Other values (57) 74
74.0%
ValueCountFrequency (%)
0.5741 2
2.0%
0.5759 2
2.0%
0.5813 2
2.0%
0.5831 2
2.0%
0.5898 1
1.0%
0.5899 1
1.0%
0.5946 2
2.0%
0.5972 1
1.0%
0.6 1
1.0%
0.6029 1
1.0%
ValueCountFrequency (%)
0.7168 1
1.0%
0.7134 1
1.0%
0.7127 1
1.0%
0.709 1
1.0%
0.7085 1
1.0%
0.7066 1
1.0%
0.7049 2
2.0%
0.7037 1
1.0%
0.7035 1
1.0%
0.7014 2
2.0%

잠재 발전 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.050134
Minimum0.0298
Maximum0.0761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:10:34.125831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0298
5-th percentile0.032865
Q10.042975
median0.0523
Q30.057
95-th percentile0.06428
Maximum0.0761
Range0.0463
Interquartile range (IQR)0.014025

Descriptive statistics

Standard deviation0.010451613
Coefficient of variation (CV)0.20847354
Kurtosis-0.42160849
Mean0.050134
Median Absolute Deviation (MAD)0.00555
Skewness-0.28569315
Sum5.0134
Variance0.00010923621
MonotonicityNot monotonic
2023-12-10T22:10:34.464642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0579 4
 
4.0%
0.0523 4
 
4.0%
0.0564 4
 
4.0%
0.0525 3
 
3.0%
0.0515 2
 
2.0%
0.0512 2
 
2.0%
0.047 2
 
2.0%
0.0511 2
 
2.0%
0.0557 2
 
2.0%
0.0608 2
 
2.0%
Other values (55) 73
73.0%
ValueCountFrequency (%)
0.0298 2
2.0%
0.0308 2
2.0%
0.0322 1
1.0%
0.0329 1
1.0%
0.0331 1
1.0%
0.0332 2
2.0%
0.0339 2
2.0%
0.0347 2
2.0%
0.0348 2
2.0%
0.0351 1
1.0%
ValueCountFrequency (%)
0.0761 1
1.0%
0.0743 1
1.0%
0.0681 2
2.0%
0.0658 1
1.0%
0.0642 1
1.0%
0.0628 1
1.0%
0.062 2
2.0%
0.0608 2
2.0%
0.0605 1
1.0%
0.0602 1
1.0%

발전 가능 량(KW/㎢/m)
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.033702
Minimum0.0174
Maximum0.0545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:10:34.683130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0174
5-th percentile0.019
Q10.02755
median0.0358
Q30.0394
95-th percentile0.045825
Maximum0.0545
Range0.0371
Interquartile range (IQR)0.01185

Descriptive statistics

Standard deviation0.0086694981
Coefficient of variation (CV)0.25723987
Kurtosis-0.54727643
Mean0.033702
Median Absolute Deviation (MAD)0.0043
Skewness-0.35379452
Sum3.3702
Variance7.5160198 × 10-5
MonotonicityNot monotonic
2023-12-10T22:10:34.968084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0401 4
 
4.0%
0.0383 3
 
3.0%
0.0358 3
 
3.0%
0.0375 3
 
3.0%
0.0351 3
 
3.0%
0.0386 3
 
3.0%
0.0402 3
 
3.0%
0.0337 2
 
2.0%
0.0314 2
 
2.0%
0.0354 2
 
2.0%
Other values (54) 72
72.0%
ValueCountFrequency (%)
0.0174 2
2.0%
0.0179 2
2.0%
0.019 2
2.0%
0.0192 1
1.0%
0.0194 1
1.0%
0.0195 1
1.0%
0.02 2
2.0%
0.0201 2
2.0%
0.021 2
2.0%
0.0214 1
1.0%
ValueCountFrequency (%)
0.0545 1
1.0%
0.0523 1
1.0%
0.0485 1
1.0%
0.048 1
1.0%
0.0463 1
1.0%
0.0458 1
1.0%
0.0443 1
1.0%
0.0432 2
2.0%
0.0429 1
1.0%
0.0426 2
2.0%

Interactions

2023-12-10T22:10:30.998836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:27.482327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:28.537002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:29.252230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.291862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:31.149000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:27.664822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:28.665178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:29.443824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.416432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:31.299057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:27.825458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:28.796465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:29.628588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.545367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:31.445965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:27.959128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:28.950222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:29.870935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.721903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:31.575891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:28.397232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:29.091086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.101784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:10:30.850029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:10:35.178796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그리드 번호전망 코드국가 코드경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
그리드 번호1.0000.0000.7281.0000.8900.8530.873
전망 코드0.0001.0000.0000.0000.3480.3310.114
국가 코드0.7280.0001.0000.7280.4070.2180.341
경도(°)1.0000.0000.7281.0000.8700.8350.855
효율 량0.8900.3480.4070.8701.0000.9050.915
잠재 발전 량(KW/㎢/m)0.8530.3310.2180.8350.9051.0000.996
발전 가능 량(KW/㎢/m)0.8730.1140.3410.8550.9150.9961.000
2023-12-10T22:10:35.389626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전망 코드국가 코드
전망 코드1.0000.000
국가 코드0.0001.000
2023-12-10T22:10:35.524485image/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 번호1.0001.000-0.435-0.351-0.3670.0000.546
경도(°)1.0001.000-0.435-0.351-0.3670.0000.546
효율 량-0.435-0.4351.0000.8600.9050.2130.298
잠재 발전 량(KW/㎢/m)-0.351-0.3510.8601.0000.9920.2010.157
발전 가능 량(KW/㎢/m)-0.367-0.3670.9050.9921.0000.0580.249
전망 코드0.0000.0000.2130.2010.0581.0000.000
국가 코드0.5460.5460.2980.1570.2490.0001.000

Missing values

2023-12-10T22:10:31.774273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:10:31.987574image/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)
01s1RS54.7560.250.70850.05790.041
11s2RS54.7560.250.70490.06280.0443
21s3RS54.7560.250.71340.06420.0458
32s1RS54.7560.750.70660.05310.0375
42s2RS54.7560.750.69960.05740.0401
52s3RS54.7560.750.70140.05940.0417
63s1RS54.7561.250.70490.06810.048
73s2RS54.7561.250.70370.07430.0523
83s3RS54.7561.250.71680.07610.0545
94s1RS54.7561.750.7090.06050.0429
그리드 번호전망 코드국가 코드위도(°)경도(°)효율 량잠재 발전 량(KW/㎢/m)발전 가능 량(KW/㎢/m)
9023s1KZ54.7571.250.58130.03080.0179
9123s1RS54.7571.250.58130.03080.0179
9223s2KZ54.7571.250.6030.03480.021
9323s2RS54.7571.250.6030.03480.021
9423s3KZ54.7571.250.57590.03470.02
9523s3RS54.7571.250.57590.03470.02
9624s1RS54.7571.750.65220.04370.0285
9724s2RS54.7571.750.66150.04790.0317
9824s3RS54.7571.750.64130.04750.0305
9925s1RS54.7572.250.58990.03310.0195