Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory419.9 KiB
Average record size in memory43.0 B

Variable types

DateTime1
Numeric3

Dataset

Description한국전력공사가 보유한 낙뢰감시기를 통해 관측된 낙뢰 발생 지점의 경도, 위도별 정보(시간 위도 경도 크기 컬럼 보유), 시스템 폐기로 과거데이터 참고용으로 활용해주기 바랍니다.
URLhttps://www.data.go.kr/data/15083360/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
크기 has 3130 (31.3%) zerosZeros

Reproduction

Analysis started2023-12-12 21:40:57.884786
Analysis finished2023-12-12 21:40:59.472475
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시간
Date

Distinct8530
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-10-01 00:00:19
Maximum2018-10-26 01:10:25
2023-12-13T06:40:59.540099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:59.672790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct9945
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.851114
Minimum27.8508
Maximum43.030552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:40:59.781432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.8508
5-th percentile33.979051
Q135.971402
median36.720335
Q337.678166
95-th percentile40.036563
Maximum43.030552
Range15.179752
Interquartile range (IQR)1.7067642

Descriptive statistics

Standard deviation1.8569372
Coefficient of variation (CV)0.05039026
Kurtosis1.9907266
Mean36.851114
Median Absolute Deviation (MAD)0.825802
Skewness-0.4037997
Sum368511.14
Variance3.4482158
MonotonicityNot monotonic
2023-12-13T06:40:59.905065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.467739 3
 
< 0.1%
36.05114 2
 
< 0.1%
36.918167 2
 
< 0.1%
35.665031 2
 
< 0.1%
36.333813 2
 
< 0.1%
36.561714 2
 
< 0.1%
37.419659 2
 
< 0.1%
36.691536 2
 
< 0.1%
36.252907 2
 
< 0.1%
37.385048 2
 
< 0.1%
Other values (9935) 9979
99.8%
ValueCountFrequency (%)
27.8508 1
< 0.1%
27.853481 1
< 0.1%
28.108387 1
< 0.1%
28.253757 1
< 0.1%
28.28911 1
< 0.1%
28.487068 1
< 0.1%
28.652411 1
< 0.1%
28.943457 1
< 0.1%
29.166817 1
< 0.1%
29.185436 1
< 0.1%
ValueCountFrequency (%)
43.030552 1
< 0.1%
42.95837 1
< 0.1%
42.915981 1
< 0.1%
42.788391 1
< 0.1%
42.636875 1
< 0.1%
42.534706 1
< 0.1%
42.328571 1
< 0.1%
42.287403 1
< 0.1%
42.283321 1
< 0.1%
42.274593 1
< 0.1%

경도
Real number (ℝ)

Distinct9945
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.24867
Minimum114.43707
Maximum139.36757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T06:41:00.309971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum114.43707
5-th percentile118.99005
Q1123.71833
median126.93783
Q3131.00133
95-th percentile134.34425
Maximum139.36757
Range24.930504
Interquartile range (IQR)7.2829988

Descriptive statistics

Standard deviation4.7568799
Coefficient of variation (CV)0.037382551
Kurtosis-0.6679325
Mean127.24867
Median Absolute Deviation (MAD)3.7489315
Skewness-0.20740403
Sum1272486.7
Variance22.627906
MonotonicityNot monotonic
2023-12-13T06:41:00.431532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121.888336 2
 
< 0.1%
129.778793 2
 
< 0.1%
125.870872 2
 
< 0.1%
131.274002 2
 
< 0.1%
132.513351 2
 
< 0.1%
125.544846 2
 
< 0.1%
122.018127 2
 
< 0.1%
124.593956 2
 
< 0.1%
125.832138 2
 
< 0.1%
126.323242 2
 
< 0.1%
Other values (9935) 9980
99.8%
ValueCountFrequency (%)
114.437065 1
< 0.1%
114.467827 1
< 0.1%
114.512741 1
< 0.1%
114.521126 1
< 0.1%
114.538864 1
< 0.1%
114.573837 1
< 0.1%
114.582695 1
< 0.1%
114.605949 1
< 0.1%
114.73967 1
< 0.1%
114.795326 1
< 0.1%
ValueCountFrequency (%)
139.367569 1
< 0.1%
139.243332 1
< 0.1%
139.190491 1
< 0.1%
139.161285 1
< 0.1%
138.933868 1
< 0.1%
138.820358 1
< 0.1%
138.811508 1
< 0.1%
138.767792 1
< 0.1%
138.732544 1
< 0.1%
138.729218 1
< 0.1%

크기
Real number (ℝ)

ZEROS 

Distinct65
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.7854
Minimum-32
Maximum32
Zeros3130
Zeros (%)31.3%
Negative4059
Negative (%)40.6%
Memory size166.0 KiB
2023-12-13T06:41:00.556098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-32
5-th percentile-26
Q1-10
median0
Q37
95-th percentile27
Maximum32
Range64
Interquartile range (IQR)17

Descriptive statistics

Standard deviation14.971719
Coefficient of variation (CV)-19.06254
Kurtosis-0.37666914
Mean-0.7854
Median Absolute Deviation (MAD)10
Skewness0.17085801
Sum-7854
Variance224.15236
MonotonicityNot monotonic
2023-12-13T06:41:00.671065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3130
31.3%
-9 208
 
2.1%
-7 202
 
2.0%
-6 193
 
1.9%
-10 193
 
1.9%
-12 183
 
1.8%
-4 182
 
1.8%
-11 180
 
1.8%
-5 178
 
1.8%
-3 172
 
1.7%
Other values (55) 5179
51.8%
ValueCountFrequency (%)
-32 64
0.6%
-31 76
0.8%
-30 94
0.9%
-29 57
0.6%
-28 91
0.9%
-27 100
1.0%
-26 99
1.0%
-25 80
0.8%
-24 99
1.0%
-23 107
1.1%
ValueCountFrequency (%)
32 86
0.9%
31 82
0.8%
30 81
0.8%
29 70
0.7%
28 84
0.8%
27 102
1.0%
26 103
1.0%
25 101
1.0%
24 106
1.1%
23 93
0.9%

Interactions

2023-12-13T06:40:58.978379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.255985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.611674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:59.111959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.382065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.740092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:59.217757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.498447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:40:58.862709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:41:00.748043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도크기
위도1.0000.6310.419
경도0.6311.0000.556
크기0.4190.5561.000
2023-12-13T06:41:00.817180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도크기
위도1.000-0.227-0.011
경도-0.2271.000-0.110
크기-0.011-0.1101.000

Missing values

2023-12-13T06:40:59.342248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:40:59.431842image/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

시간위도경도크기
76602018-10-18 22:44:4336.087517134.783508-22
76282018-10-18 22:54:5636.540775131.230484-24
154702018-10-10 01:01:0937.333126.5033190
145032018-10-16 02:54:2537.438766114.79532625
123212018-10-17 01:45:2936.390392132.24485814
166762018-10-09 08:53:1435.674469120.5306425
153472018-10-10 03:40:5034.359276128.264359-4
5552018-10-23 18:32:3139.332558134.92561328
161872018-10-09 14:41:4034.557091121.3808360
144722018-10-16 04:45:0937.857819123.559372-9
시간위도경도크기
106002018-10-18 02:20:3736.434013131.613983-12
149962018-10-10 23:34:4034.498623138.52255222
149312018-10-12 00:11:5630.36174133.46084615
163242018-10-09 12:02:2835.53492122.19731110
73372018-10-19 00:10:0636.614849131.7348180
124992018-10-17 00:24:4934.908516121.02117222
182412018-10-09 00:08:2136.663471118.705162-25
142582018-10-16 11:45:4535.420433123.125130
67342018-10-19 02:52:0536.730297132.468140
65332018-10-19 03:44:1236.891373132.88443-14

Duplicate rows

Most frequently occurring

시간위도경도크기# duplicates
02018-10-09 11:20:0636.057549122.20099602