Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows476
Duplicate rows (%)4.8%
Total size in memory634.8 KiB
Average record size in memory65.0 B

Variable types

DateTime1
Categorical6

Dataset

Description항공기상청에서 설치한 인천 공항기상레이더(TDWR)에서 생산되는 윈드시어 경고 자료로 관측시간(TM), 공항코드(STN_ID, 인천공항 113), 활주로(RWY_DIR), 이착륙구분(RWY_AD), 경보발생영역(LOC), 경보종류(ALERT), 경보풍속(LG)으로 구성되어있다.
Author기상청 항공기상청
URLhttps://www.data.go.kr/data/15091980/fileData.do

Alerts

공항코드 has constant value ""Constant
Dataset has 476 (4.8%) duplicate rowsDuplicates
경보종류 is highly overall correlated with 경보풍속High correlation
경보풍속 is highly overall correlated with 경보종류High correlation
이착륙구분 is highly overall correlated with 경보발생구역High correlation
경보발생구역 is highly overall correlated with 이착륙구분High correlation
경보풍속 is highly imbalanced (53.0%)Imbalance

Reproduction

Analysis started2023-12-12 22:12:16.010754
Analysis finished2023-12-12 22:12:16.822002
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시간
Date

Distinct5414
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2013-11-25 22:18:00
Maximum2020-11-19 05:25:00
2023-12-13T07:12:16.903744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:12:17.076438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

공항코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
113
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row113
2nd row113
3rd row113
4th row113
5th row113

Common Values

ValueCountFrequency (%)
113 10000
100.0%

Length

2023-12-13T07:12:17.228838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:12:17.336978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
113 10000
100.0%

활주로
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
34-
2192 
17-
1773 
33L
1617 
33R
1561 
16-
1251 
Other values (2)
1606 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row17-
2nd row16-
3rd row34-
4th row17-
5th row17-

Common Values

ValueCountFrequency (%)
34- 2192
21.9%
17- 1773
17.7%
33L 1617
16.2%
33R 1561
15.6%
16- 1251
12.5%
15L 827
 
8.3%
15R 779
 
7.8%

Length

2023-12-13T07:12:17.470029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:12:17.583961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
34 2192
21.9%
17 1773
17.7%
33l 1617
16.2%
33r 1561
15.6%
16 1251
12.5%
15l 827
 
8.3%
15r 779
 
7.8%

이착륙구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
D
5012 
A
4988 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowD
2nd rowA
3rd rowD
4th rowA
5th rowD

Common Values

ValueCountFrequency (%)
D 5012
50.1%
A 4988
49.9%

Length

2023-12-13T07:12:17.735033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:12:17.850752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
d 5012
50.1%
a 4988
49.9%

경보발생구역
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5715 
RWY
3285 
2MF
 
394
1MF
 
391
3MF
 
139
Other values (3)
 
76

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1MF
3rd rowRWY
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5715
57.1%
RWY 3285
32.9%
2MF 394
 
3.9%
1MF 391
 
3.9%
3MF 139
 
1.4%
3MD 47
 
0.5%
1MD 15
 
0.1%
2MD 14
 
0.1%

Length

2023-12-13T07:12:17.954944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:12:18.090282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5715
57.1%
rwy 3285
32.9%
2mf 394
 
3.9%
1mf 391
 
3.9%
3mf 139
 
1.4%
3md 47
 
0.5%
1md 15
 
0.1%
2md 14
 
0.1%

경보종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5715 
WSA
3599 
MBA
686 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd rowWSA
3rd rowWSA
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5715
57.1%
WSA 3599
36.0%
MBA 686
 
6.9%

Length

2023-12-13T07:12:18.220187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:12:18.317566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5715
57.1%
wsa 3599
36.0%
mba 686
 
6.9%

경보풍속
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5715 
15K+
1225 
25K+
991 
30K-
 
524
25K-
 
384
Other values (22)
1161 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row30K-
3rd row30K-
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 5715
57.1%
15K+ 1225
 
12.2%
25K+ 991
 
9.9%
30K- 524
 
5.2%
25K- 384
 
3.8%
35K- 357
 
3.6%
30K+ 353
 
3.5%
45K- 228
 
2.3%
40K- 50
 
0.5%
50K- 32
 
0.3%
Other values (17) 141
 
1.4%

Length

2023-12-13T07:12:18.412454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 5715
57.1%
25k 1375
 
13.8%
15k 1225
 
12.2%
30k 877
 
8.8%
35k 383
 
3.8%
45k 236
 
2.4%
40k 54
 
0.5%
20k 46
 
0.5%
50k 32
 
0.3%
10k 14
 
0.1%
Other values (9) 43
 
0.4%

Correlations

2023-12-13T07:12:18.487134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활주로이착륙구분경보발생구역경보종류경보풍속
활주로1.0000.0410.3500.5130.514
이착륙구분0.0411.0000.5020.0550.159
경보발생구역0.3500.5021.0000.2800.646
경보종류0.5130.0550.2801.0001.000
경보풍속0.5140.1590.6461.0001.000
2023-12-13T07:12:18.617262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경보발생구역이착륙구분경보종류경보풍속활주로
경보발생구역1.0000.5380.3000.3390.217
이착륙구분0.5381.0000.0350.1260.044
경보종류0.3000.0351.0000.9970.371
경보풍속0.3390.1260.9971.0000.259
활주로0.2170.0440.3710.2591.000
2023-12-13T07:12:18.739688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
활주로이착륙구분경보발생구역경보종류경보풍속
활주로1.0000.0440.2170.3710.259
이착륙구분0.0441.0000.5380.0350.126
경보발생구역0.2170.5381.0000.3000.339
경보종류0.3710.0350.3001.0000.997
경보풍속0.2590.1260.3390.9971.000

Missing values

2023-12-13T07:12:16.625591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:12:16.765486image/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

시간공항코드활주로이착륙구분경보발생구역경보종류경보풍속
211782014-11-02 13:5411317-D<NA><NA><NA>
813942018-04-10 16:5511316-A1MFWSA30K-
882342019-08-29 9:4111334-DRWYWSA30K-
49872014-01-18 13:4611317-A<NA><NA><NA>
663202015-09-16 23:3411317-D<NA><NA><NA>
720962016-05-03 22:4811334-DRWYWSA25K+
25122013-12-09 18:1711333LD<NA><NA><NA>
69602014-01-26 4:4611333LDRWYWSA15K+
782322017-08-11 17:4411333RARWYWSA25K+
746532016-09-11 4:2811333RDRWYMBA45K-
시간공항코드활주로이착륙구분경보발생구역경보종류경보풍속
856322018-10-23 10:2411333RA2MFWSA30K+
424612014-12-16 8:2011317-A<NA><NA><NA>
855802018-08-28 19:0711315RARWYWSA25K+
41472013-12-11 15:5811333LD<NA><NA><NA>
418022014-12-01 18:0011334-D<NA><NA><NA>
492482015-03-03 23:4511317-D<NA><NA><NA>
878692019-05-01 20:0011334-ARWYWSA30K+
146702014-07-26 0:3711317-D<NA><NA><NA>
219442014-11-02 13:5411333RD<NA><NA><NA>
152292014-07-26 0:3811316-DRWYMBA45K-

Duplicate rows

Most frequently occurring

시간공항코드활주로이착륙구분경보발생구역경보종류경보풍속# duplicates
102013-12-11 5:3211317-A<NA><NA><NA>3
232014-03-17 20:1611315RD<NA><NA><NA>3
322014-04-05 18:5411317-A<NA><NA><NA>3
642014-07-26 1:0611315LA<NA><NA><NA>3
712014-07-26 2:1811315RD<NA><NA><NA>3
922014-10-16 3:2311315LD<NA><NA><NA>3
1072014-11-02 16:5411333LD<NA><NA><NA>3
1392014-12-01 11:3211333RD<NA><NA><NA>3
1492014-12-01 12:2311317-A<NA><NA><NA>3
1512014-12-01 12:4011333LA<NA><NA><NA>3