Overview

Dataset statistics

Number of variables3
Number of observations2256
Missing cells0
Missing cells (%)0.0%
Duplicate rows26
Duplicate rows (%)1.2%
Total size in memory57.4 KiB
Average record size in memory26.1 B

Variable types

DateTime1
Numeric2

Dataset

Description주파수 및 송전단 수요실적(16.7.4~16.8.8, 일별, 2초단위, 주파수, 전력수요량)
Author한국전력거래소
URLhttps://www.data.go.kr/data/15051433/fileData.do

Alerts

Dataset has 26 (1.2%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-13 01:00:17.325134
Analysis finished2023-12-13 01:00:17.850597
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대상일시
Date

Distinct81
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
Minimum2016-07-04 16:40:00
Maximum2016-08-08 13:30:00
2023-12-13T10:00:17.900423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:18.001734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주파수
Real number (ℝ)

Distinct120
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.999115
Minimum59.896
Maximum60.046001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.0 KiB
2023-12-13T10:00:18.105743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59.896
5-th percentile59.963001
Q159.986
median60.000999
Q360.014999
95-th percentile60.028999
Maximum60.046001
Range0.150001
Interquartile range (IQR)0.028999

Descriptive statistics

Standard deviation0.021539049
Coefficient of variation (CV)0.00035898945
Kurtosis1.6733518
Mean59.999115
Median Absolute Deviation (MAD)0.014
Skewness-0.88318896
Sum135358
Variance0.00046393064
MonotonicityNot monotonic
2023-12-13T10:00:18.211094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.007999 54
 
2.4%
60.014 54
 
2.4%
60.013 54
 
2.4%
60.015999 53
 
2.3%
60.014999 51
 
2.3%
59.998001 49
 
2.2%
59.999001 47
 
2.1%
60.011002 47
 
2.1%
59.994999 47
 
2.1%
59.995998 46
 
2.0%
Other values (110) 1754
77.7%
ValueCountFrequency (%)
59.896 2
0.1%
59.898998 1
 
< 0.1%
59.904999 1
 
< 0.1%
59.912998 2
0.1%
59.914001 2
0.1%
59.917 1
 
< 0.1%
59.917999 2
0.1%
59.919998 3
0.1%
59.921001 2
0.1%
59.922001 3
0.1%
ValueCountFrequency (%)
60.046001 2
 
0.1%
60.043999 2
 
0.1%
60.042 6
0.3%
60.041 2
 
0.1%
60.040001 5
0.2%
60.039001 6
0.3%
60.037998 1
 
< 0.1%
60.036999 6
0.3%
60.035999 4
0.2%
60.035 8
0.4%

수요
Real number (ℝ)

Distinct2203
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68468.635
Minimum53965.383
Maximum78295.602
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.0 KiB
2023-12-13T10:00:18.316695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53965.383
5-th percentile54657.612
Q165963.707
median69994.465
Q372245.74
95-th percentile78028.93
Maximum78295.602
Range24330.219
Interquartile range (IQR)6282.0332

Descriptive statistics

Standard deviation6569.7831
Coefficient of variation (CV)0.095953178
Kurtosis0.25040461
Mean68468.635
Median Absolute Deviation (MAD)3708.5352
Skewness-0.81490239
Sum1.5446524 × 108
Variance43162050
MonotonicityNot monotonic
2023-12-13T10:00:18.635151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70034.91406 4
 
0.2%
70019.75 4
 
0.2%
54518.45313 3
 
0.1%
65407.73047 3
 
0.1%
72129.45313 3
 
0.1%
70576.76563 3
 
0.1%
66150.26563 3
 
0.1%
66208.32031 3
 
0.1%
72244.57813 3
 
0.1%
65684.13281 3
 
0.1%
Other values (2193) 2224
98.6%
ValueCountFrequency (%)
53965.38281 1
< 0.1%
54000.3125 1
< 0.1%
54035.14453 1
< 0.1%
54042.85156 1
< 0.1%
54043.84766 1
< 0.1%
54053.52734 1
< 0.1%
54063.37891 1
< 0.1%
54064.87891 1
< 0.1%
54070.13281 1
< 0.1%
54085.875 1
< 0.1%
ValueCountFrequency (%)
78295.60156 1
< 0.1%
78279.5 1
< 0.1%
78260.51563 1
< 0.1%
78257.08594 1
< 0.1%
78240.42188 1
< 0.1%
78240.11719 1
< 0.1%
78237.73438 1
< 0.1%
78229.32031 1
< 0.1%
78222.25781 1
< 0.1%
78221.28906 1
< 0.1%

Interactions

2023-12-13T10:00:17.619999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:17.435553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:17.698441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T10:00:17.531240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T10:00:18.701510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대상일시주파수수요
대상일시1.0000.8330.999
주파수0.8331.0000.305
수요0.9990.3051.000
2023-12-13T10:00:18.780541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주파수수요
주파수1.000-0.047
수요-0.0471.000

Missing values

2023-12-13T10:00:17.775666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T10:00:17.828579image/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

대상일시주파수수요
02016-07-04 16:4059.99900166150.21875
12016-07-04 16:4059.99900166153.42188
22016-07-04 16:4059.99900166165.66406
32016-07-04 16:4060.00099966153.95313
42016-07-04 16:4059.99800166182.58594
52016-07-04 16:4060.066173.125
62016-07-04 16:4059.99900166162.74219
72016-07-04 16:4059.99900166170.61719
82016-07-04 16:4059.99700266186.26563
92016-07-04 16:4059.99900166157.86719
대상일시주파수수요
22462016-08-08 13:2959.99399978176.14063
22472016-08-08 13:2959.99399978169.96875
22482016-08-08 13:2959.99800178164.8125
22492016-08-08 13:2960.00600178147.08594
22502016-08-08 13:2960.00778183.21875
22512016-08-08 13:2960.00400278182.05469
22522016-08-08 13:2959.99700278217.05469
22532016-08-08 13:2959.99499978229.32031
22542016-08-08 13:2959.99399978213.10156
22552016-08-08 13:3059.99200178240.11719

Duplicate rows

Most frequently occurring

대상일시주파수수요# duplicates
192016-07-29 12:0160.02870034.914064
202016-07-29 12:0559.99800170019.754
12016-07-04 16:4459.97399966150.265633
32016-07-04 16:4960.02399866208.320313
72016-07-04 16:5860.0265407.730473
82016-07-08 7:0259.96799954518.453133
142016-07-22 11:2859.97499870909.53
162016-07-25 19:0260.01599972244.578133
182016-07-25 19:0760.01372129.453133
02016-07-04 16:4160.00099966048.789062