Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells8
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

Text1
DateTime1
Numeric2

Dataset

Description기상청에서 관측하는 표류부이의 이동경로로서 지점,관측시간,위도,경도 등을 제공합니다.
Author기상청
URLhttps://www.data.go.kr/data/15043554/fileData.do

Reproduction

Analysis started2023-12-12 20:38:57.919722
Analysis finished2023-12-12 20:38:59.064242
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지점
Text

Distinct72
Distinct (%)0.7%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2023-12-13T05:38:59.267934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.3899119
Min length2

Characters and Unicode

Total characters63848
Distinct characters17
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row표류14005
2nd rowe4
3rd rowj5
4th row표류14005
5th row표류14009
ValueCountFrequency (%)
표류14009 852
 
8.5%
표류15001 706
 
7.1%
표류13006 612
 
6.1%
표류13005 542
 
5.4%
표류14003 438
 
4.4%
표류16007 434
 
4.3%
표류13001 421
 
4.2%
표류15004 411
 
4.1%
표류14005 403
 
4.0%
표류16004 400
 
4.0%
Other values (62) 4773
47.8%
2023-12-13T05:38:59.748921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17406
27.3%
1 10381
16.3%
표 8669
13.6%
류 8669
13.6%
4 3834
 
6.0%
3 3468
 
5.4%
6 3463
 
5.4%
5 2988
 
4.7%
9 1008
 
1.6%
7 892
 
1.4%
Other values (7) 3070
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 44736
70.1%
Other Letter 17338
 
27.2%
Lowercase Letter 1774
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17406
38.9%
1 10381
23.2%
4 3834
 
8.6%
3 3468
 
7.8%
6 3463
 
7.7%
5 2988
 
6.7%
9 1008
 
2.3%
7 892
 
2.0%
2 881
 
2.0%
8 415
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
s 759
42.8%
y 451
25.4%
m 237
 
13.4%
j 188
 
10.6%
e 139
 
7.8%
Other Letter
ValueCountFrequency (%)
표 8669
50.0%
류 8669
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44736
70.1%
Hangul 17338
 
27.2%
Latin 1774
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17406
38.9%
1 10381
23.2%
4 3834
 
8.6%
3 3468
 
7.8%
6 3463
 
7.7%
5 2988
 
6.7%
9 1008
 
2.3%
7 892
 
2.0%
2 881
 
2.0%
8 415
 
0.9%
Latin
ValueCountFrequency (%)
s 759
42.8%
y 451
25.4%
m 237
 
13.4%
j 188
 
10.6%
e 139
 
7.8%
Hangul
ValueCountFrequency (%)
표 8669
50.0%
류 8669
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46510
72.8%
Hangul 17338
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17406
37.4%
1 10381
22.3%
4 3834
 
8.2%
3 3468
 
7.5%
6 3463
 
7.4%
5 2988
 
6.4%
9 1008
 
2.2%
7 892
 
1.9%
2 881
 
1.9%
s 759
 
1.6%
Other values (5) 1430
 
3.1%
Hangul
ValueCountFrequency (%)
표 8669
50.0%
류 8669
50.0%

관측시간
Date

Distinct8044
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-08-28 21:00:00
Maximum2016-11-30 22:00:00
2023-12-13T05:38:59.941740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:39:00.129021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct9906
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.515463
Minimum23.55598
Maximum41.17414
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:39:00.290202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.55598
5-th percentile27.268956
Q131.44495
median33.673115
Q336.179215
95-th percentile38.477538
Maximum41.17414
Range17.61816
Interquartile range (IQR)4.734265

Descriptive statistics

Standard deviation3.3238079
Coefficient of variation (CV)0.099172372
Kurtosis-0.30107021
Mean33.515463
Median Absolute Deviation (MAD)2.39226
Skewness-0.36068028
Sum335154.63
Variance11.047699
MonotonicityNot monotonic
2023-12-13T05:39:00.478496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.30659 13
 
0.1%
34.30658 8
 
0.1%
34.3066 7
 
0.1%
34.30656 3
 
< 0.1%
35.31557 2
 
< 0.1%
34.043 2
 
< 0.1%
32.78064 2
 
< 0.1%
31.0334 2
 
< 0.1%
30.13948 2
 
< 0.1%
31.83336 2
 
< 0.1%
Other values (9896) 9957
99.6%
ValueCountFrequency (%)
23.55598 1
< 0.1%
23.67375 1
< 0.1%
23.71639 1
< 0.1%
23.73377 1
< 0.1%
23.74786 1
< 0.1%
23.76915 1
< 0.1%
23.90631 1
< 0.1%
23.92376 1
< 0.1%
23.95522 1
< 0.1%
24.03222 1
< 0.1%
ValueCountFrequency (%)
41.17414 1
< 0.1%
41.14171 1
< 0.1%
41.13957 1
< 0.1%
41.12583 1
< 0.1%
41.10873 1
< 0.1%
41.07647 1
< 0.1%
41.07083 1
< 0.1%
41.0049 1
< 0.1%
40.99002 1
< 0.1%
40.96441 1
< 0.1%

경도
Real number (ℝ)

Distinct9899
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.81342
Minimum120.18247
Maximum140.64957
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T05:39:00.636816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120.18247
5-th percentile123.16682
Q1125.20146
median127.45927
Q3131.33604
95-th percentile137.95669
Maximum140.64957
Range20.4671
Interquartile range (IQR)6.13458

Descriptive statistics

Standard deviation4.5480604
Coefficient of variation (CV)0.035307351
Kurtosis-0.35576808
Mean128.81342
Median Absolute Deviation (MAD)2.697645
Skewness0.75657904
Sum1288134.2
Variance20.684854
MonotonicityNot monotonic
2023-12-13T05:39:00.788429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.3036 18
 
0.2%
129.30359 8
 
0.1%
129.30357 4
 
< 0.1%
129.30362 3
 
< 0.1%
126.01767 3
 
< 0.1%
126.04621 2
 
< 0.1%
128.65877 2
 
< 0.1%
125.00916 2
 
< 0.1%
131.03621 2
 
< 0.1%
129.19374 2
 
< 0.1%
Other values (9889) 9954
99.5%
ValueCountFrequency (%)
120.18247 1
< 0.1%
120.19499 1
< 0.1%
120.24677 1
< 0.1%
120.25764 1
< 0.1%
120.26447 1
< 0.1%
120.26773 1
< 0.1%
120.26899 1
< 0.1%
120.27081 1
< 0.1%
120.27938 1
< 0.1%
120.27993 1
< 0.1%
ValueCountFrequency (%)
140.64957 1
< 0.1%
140.64407 1
< 0.1%
140.63634 1
< 0.1%
140.62476 1
< 0.1%
140.61618 1
< 0.1%
140.60344 1
< 0.1%
140.59976 1
< 0.1%
140.56917 1
< 0.1%
140.55971 1
< 0.1%
140.5551 1
< 0.1%

Interactions

2023-12-13T05:38:58.637523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:58.322352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:58.771967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:38:58.506338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:39:00.912731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점위도경도
지점1.0000.8840.904
위도0.8841.0000.795
경도0.9040.7951.000
2023-12-13T05:39:01.012670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.114
경도0.1141.000

Missing values

2023-12-13T05:38:58.915801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:38:59.015234image/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

지점관측시간위도경도
17928표류140052014-08-14 02:0031.71299126.31123
392e42016-08-07 07:0036.44336129.59395
933j52016-04-19 00:0032.99987126.16554
18908표류140052014-10-07 04:0038.5364130.24709
23545표류140092015-02-27 05:0028.56356140.3392
26063표류150012015-07-21 10:0032.80428125.40578
29254표류150022015-08-05 23:0035.97844126.42963
7281표류130022013-10-12 00:0032.88611123.41876
17286표류140042014-08-15 16:0032.6901126.86604
20206표류140062014-12-25 09:0036.91626135.76266
지점관측시간위도경도
36e12016-08-07 03:0037.04031129.62413
5329ys72016-06-09 08:0034.5324124.52505
25907표류150012015-07-14 20:0032.56183126.26705
20407표류140072014-11-20 08:0034.83556130.72832
35705표류160042016-03-05 17:0036.91675135.86595
13131표류130062014-02-09 19:0027.18626137.61559
9788표류130052013-12-30 10:0032.44418135.85916
33296표류160032016-01-31 04:0036.96302129.96365
34488표류160032016-03-20 23:0036.88886130.82239
15454표류140032014-08-13 11:0032.36423125.65514