Overview

Dataset statistics

Number of variables4
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory35.0 B

Variable types

Text2
DateTime1
Categorical1

Dataset

Description방위산업 관련 해외 전시회(일정, 이름, 개최도시 등) 정보입니다.코로나-19로 인해 20년 7월 이후 해외 전시회 정보는 없습니다.
Author방위사업청
URLhttps://www.data.go.kr/data/3084450/fileData.do

Alerts

전시회명 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:39:42.966868
Analysis finished2024-03-23 05:39:43.566415
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전시회명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-03-23T14:39:43.876701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length25.5
Mean length11.954545
Min length3

Characters and Unicode

Total characters526
Distinct characters54
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st rowFarnborough Airshow
2nd rowDefenpol China
3rd rowCYDES
4th rowEurosatory
5th rowKADEX
ValueCountFrequency (%)
airshow 4
 
5.1%
international 3
 
3.8%
defence 3
 
3.8%
exhibition 2
 
2.6%
forces 2
 
2.6%
security 2
 
2.6%
ausa 1
 
1.3%
and 1
 
1.3%
arms 1
 
1.3%
euronaval 1
 
1.3%
Other values (58) 58
74.4%
2024-03-23T14:39:44.655051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 37
 
7.0%
34
 
6.5%
r 29
 
5.5%
i 27
 
5.1%
n 27
 
5.1%
o 27
 
5.1%
a 27
 
5.1%
e 26
 
4.9%
E 21
 
4.0%
I 20
 
3.8%
Other values (44) 251
47.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 277
52.7%
Uppercase Letter 205
39.0%
Space Separator 34
 
6.5%
Other Punctuation 5
 
1.0%
Decimal Number 4
 
0.8%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 37
18.0%
E 21
10.2%
I 20
 
9.8%
S 19
 
9.3%
D 16
 
7.8%
C 10
 
4.9%
L 9
 
4.4%
X 8
 
3.9%
O 7
 
3.4%
N 7
 
3.4%
Other values (14) 51
24.9%
Lowercase Letter
ValueCountFrequency (%)
r 29
10.5%
i 27
9.7%
n 27
9.7%
o 27
9.7%
a 27
9.7%
e 26
9.4%
t 17
 
6.1%
s 14
 
5.1%
c 11
 
4.0%
l 10
 
3.6%
Other values (13) 62
22.4%
Other Punctuation
ValueCountFrequency (%)
; 2
40.0%
& 2
40.0%
/ 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
0 2
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 482
91.6%
Common 44
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 37
 
7.7%
r 29
 
6.0%
i 27
 
5.6%
n 27
 
5.6%
o 27
 
5.6%
a 27
 
5.6%
e 26
 
5.4%
E 21
 
4.4%
I 20
 
4.1%
S 19
 
3.9%
Other values (37) 222
46.1%
Common
ValueCountFrequency (%)
34
77.3%
2 2
 
4.5%
; 2
 
4.5%
& 2
 
4.5%
0 2
 
4.5%
/ 1
 
2.3%
- 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 526
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 37
 
7.0%
34
 
6.5%
r 29
 
5.5%
i 27
 
5.1%
n 27
 
5.1%
o 27
 
5.1%
a 27
 
5.1%
e 26
 
4.9%
E 21
 
4.0%
I 20
 
3.8%
Other values (44) 251
47.7%

개최국
Text

Distinct33
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2024-03-23T14:39:45.108181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.4318182
Min length2

Characters and Unicode

Total characters151
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)59.1%

Sample

1st row영국
2nd row중국
3rd row말레이시아
4th row프랑스
5th row카자흐스탄
ValueCountFrequency (%)
미국 6
 
13.6%
프랑스 2
 
4.5%
오스트레일리아 2
 
4.5%
중국 2
 
4.5%
칠레 2
 
4.5%
영국 2
 
4.5%
말레이시아 2
 
4.5%
남아프리카공화국 1
 
2.3%
노르웨이 1
 
2.3%
아제르바이잔 1
 
2.3%
Other values (23) 23
52.3%
2024-03-23T14:39:45.752706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 12
 
7.9%
아 11
 
7.3%
스 8
 
5.3%
미 7
 
4.6%
레 7
 
4.6%
이 6
 
4.0%
리 6
 
4.0%
트 5
 
3.3%
르 4
 
2.6%
일 4
 
2.6%
Other values (57) 81
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 12
 
7.9%
아 11
 
7.3%
스 8
 
5.3%
미 7
 
4.6%
레 7
 
4.6%
이 6
 
4.0%
리 6
 
4.0%
트 5
 
3.3%
르 4
 
2.6%
일 4
 
2.6%
Other values (57) 81
53.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 12
 
7.9%
아 11
 
7.3%
스 8
 
5.3%
미 7
 
4.6%
레 7
 
4.6%
이 6
 
4.0%
리 6
 
4.0%
트 5
 
3.3%
르 4
 
2.6%
일 4
 
2.6%
Other values (57) 81
53.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 12
 
7.9%
아 11
 
7.3%
스 8
 
5.3%
미 7
 
4.6%
레 7
 
4.6%
이 6
 
4.0%
리 6
 
4.0%
트 5
 
3.3%
르 4
 
2.6%
일 4
 
2.6%
Other values (57) 81
53.6%

기간
Date

Distinct40
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2020-02-28 00:00:00
Maximum2020-12-08 00:00:00
2024-03-23T14:39:46.036706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T14:39:46.304605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

전시품목
Categorical

Distinct18
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
육/해/공
8 
방산
6 
항공
6 
보안
4 
방산/보안
4 
Other values (13)
16 

Length

Max length11
Median length6
Mean length3.6363636
Min length2

Unique

Unique10 ?
Unique (%)22.7%

Sample

1st row항공
2nd row보안
3rd row사이버
4th row방산
5th row육/해/공

Common Values

ValueCountFrequency (%)
육/해/공 8
18.2%
방산 6
13.6%
항공 6
13.6%
보안 4
9.1%
방산/보안 4
9.1%
특수전장비 2
 
4.5%
해상 2
 
4.5%
지상 2
 
4.5%
통신/정보 1
 
2.3%
방산품목 1
 
2.3%
Other values (8) 8
18.2%

Length

2024-03-23T14:39:46.547709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
육/해/공 9
20.0%
항공 6
13.3%
방산 6
13.3%
보안 4
8.9%
방산/보안 4
8.9%
특수전장비 2
 
4.4%
해상 2
 
4.4%
지상 2
 
4.4%
해병 1
 
2.2%
보안/대테러 1
 
2.2%
Other values (8) 8
17.8%

Correlations

2024-03-23T14:39:46.693425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전시회명개최국기간전시품목
전시회명1.0001.0001.0001.000
개최국1.0001.0000.8530.000
기간1.0000.8531.0000.914
전시품목1.0000.0000.9141.000

Missing values

2024-03-23T14:39:43.347070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T14:39:43.507517image/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

전시회명개최국기간전시품목
0Farnborough Airshow영국2020-07-20항공
1Defenpol China중국2020-07-17보안
2CYDES말레이시아2020-06-23사이버
3Eurosatory프랑스2020-06-08방산
4KADEX카자흐스탄2020-05-28육/해/공
5LANPAC미국2020-05-19육/해/공
6International Police EXPO인도2020-05-14보안/대테러
7ILA Berlin Airshow독일2020-05-13항공
8AUVSI미국2020-05-04무인차량
9ITEC영국2020-04-28육/해/공 시뮬레이션
전시회명개최국기간전시품목
34ADAS필리핀2020-09-23방산
35Africa Aerospace & Defence남아프리카공화국2020-09-16특수전장비
36DX-Korea대한민국2020-09-16지상
37VIDSE베트남2020-09-14방산
38ADEX아제르바이잔2020-09-08육/해/공
39MSPO폴란드2020-09-08육/해/공
40LAND FORCES AUSTRAILIA오스트레일리아2020-09-01지상
41FSI Exhibition노르웨이2020-08-26방산/보안
42DSA말레이시아2020-08-24방산/보안
43army 2020러시아2020-08-23육/해/공