Overview

Dataset statistics

Number of variables7
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory63.3 B

Variable types

Categorical2
Text2
DateTime2
Numeric1

Dataset

Description창업자 및 창업기업의 해외진출을 지원하기 위한 2019, 2020년 해외 전시회 개최국가, 전시분야, 전시회명, 전시일정, 참가기업수
Author창업진흥원
URLhttps://www.data.go.kr/data/15037557/fileData.do

Alerts

지원년도 is highly overall correlated with 전시분야High correlation
전시분야 is highly overall correlated with 지원년도High correlation
전시회명 has unique valuesUnique
전시종료 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:22:47.380497
Analysis finished2023-12-12 05:22:48.034904
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지원년도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2019년
11 
2020년
10 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019년
2nd row2019년
3rd row2019년
4th row2019년
5th row2019년

Common Values

ValueCountFrequency (%)
2019년 11
52.4%
2020년 10
47.6%

Length

2023-12-12T14:22:48.098018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:22:48.212952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019년 11
52.4%
2020년 10
47.6%

개최국가
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T14:22:48.383748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4285714
Min length2

Characters and Unicode

Total characters51
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st row중국
2nd row베트남
3rd row일본
4th row인도
5th row홍콩
ValueCountFrequency (%)
중국 3
14.3%
미국 3
14.3%
독일 3
14.3%
베트남 2
9.5%
홍콩 2
9.5%
일본 1
 
4.8%
인도 1
 
4.8%
두바이 1
 
4.8%
인니 1
 
4.8%
프랑스 1
 
4.8%
Other values (3) 3
14.3%
2023-12-12T14:22:48.752155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 6
 
11.8%
일 4
 
7.8%
인 4
 
7.8%
중 3
 
5.9%
미 3
 
5.9%
독 3
 
5.9%
스 2
 
3.9%
도 2
 
3.9%
콩 2
 
3.9%
홍 2
 
3.9%
Other values (17) 20
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48
94.1%
Uppercase Letter 3
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 6
 
12.5%
일 4
 
8.3%
인 4
 
8.3%
중 3
 
6.2%
미 3
 
6.2%
독 3
 
6.2%
스 2
 
4.2%
도 2
 
4.2%
콩 2
 
4.2%
홍 2
 
4.2%
Other values (14) 17
35.4%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48
94.1%
Latin 3
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 6
 
12.5%
일 4
 
8.3%
인 4
 
8.3%
중 3
 
6.2%
미 3
 
6.2%
독 3
 
6.2%
스 2
 
4.2%
도 2
 
4.2%
콩 2
 
4.2%
홍 2
 
4.2%
Other values (14) 17
35.4%
Latin
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48
94.1%
ASCII 3
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 6
 
12.5%
일 4
 
8.3%
인 4
 
8.3%
중 3
 
6.2%
미 3
 
6.2%
독 3
 
6.2%
스 2
 
4.2%
도 2
 
4.2%
콩 2
 
4.2%
홍 2
 
4.2%
Other values (14) 17
35.4%
ASCII
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%

전시분야
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size300.0 B
종합
6 
소비재
6 
스타트업
5 
전기전자
2 
기계
1 

Length

Max length4
Median length3
Mean length3.047619
Min length2

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row종합
2nd row소비재
3rd row소비재
4th row기계
5th row전기전자

Common Values

ValueCountFrequency (%)
종합 6
28.6%
소비재 6
28.6%
스타트업 5
23.8%
전기전자 2
 
9.5%
기계 1
 
4.8%
정보통신 1
 
4.8%

Length

2023-12-12T14:22:48.905507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:22:49.032200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합 6
28.6%
소비재 6
28.6%
스타트업 5
23.8%
전기전자 2
 
9.5%
기계 1
 
4.8%
정보통신 1
 
4.8%

전시회명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T14:22:49.235977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length22.666667
Min length11

Characters and Unicode

Total characters476
Distinct characters113
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row2019 중국 광저우 수출입상품 교역회(캔톤페어)
2nd row2019 베트남 국제 프리미엄 소비재전
3rd row2019 동경 국제 선물용품 전시회
4th row2019 인도 전자부품박람회
5th row2019 홍콩 스타트업 런치패드
ValueCountFrequency (%)
2019 9
 
9.8%
2020 9
 
9.8%
국제 6
 
6.5%
프리미엄 4
 
4.3%
소비재전(취소 3
 
3.3%
소비재전 3
 
3.3%
독일 3
 
3.3%
2021 3
 
3.3%
두바이 2
 
2.2%
미국 2
 
2.2%
Other values (38) 48
52.2%
2023-12-12T14:22:49.582950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
15.1%
2 33
 
6.9%
0 30
 
6.3%
전 14
 
2.9%
소 14
 
2.9%
( 13
 
2.7%
) 13
 
2.7%
국 13
 
2.7%
1 12
 
2.5%
제 10
 
2.1%
Other values (103) 252
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 254
53.4%
Decimal Number 85
 
17.9%
Space Separator 72
 
15.1%
Uppercase Letter 22
 
4.6%
Lowercase Letter 17
 
3.6%
Open Punctuation 13
 
2.7%
Close Punctuation 13
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 14
 
5.5%
소 14
 
5.5%
국 13
 
5.1%
제 10
 
3.9%
회 10
 
3.9%
스 7
 
2.8%
비 7
 
2.8%
취 7
 
2.8%
프 7
 
2.8%
시 6
 
2.4%
Other values (70) 159
62.6%
Uppercase Letter
ValueCountFrequency (%)
A 3
13.6%
F 3
13.6%
S 2
9.1%
V 2
9.1%
I 2
9.1%
C 2
9.1%
E 2
9.1%
Y 1
 
4.5%
M 1
 
4.5%
W 1
 
4.5%
Other values (3) 3
13.6%
Lowercase Letter
ValueCountFrequency (%)
r 2
11.8%
e 2
11.8%
u 2
11.8%
t 2
11.8%
o 2
11.8%
a 1
5.9%
y 1
5.9%
g 1
5.9%
l 1
5.9%
n 1
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
2 33
38.8%
0 30
35.3%
1 12
 
14.1%
9 9
 
10.6%
4 1
 
1.2%
Space Separator
ValueCountFrequency (%)
72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 254
53.4%
Common 183
38.4%
Latin 39
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 14
 
5.5%
소 14
 
5.5%
국 13
 
5.1%
제 10
 
3.9%
회 10
 
3.9%
스 7
 
2.8%
비 7
 
2.8%
취 7
 
2.8%
프 7
 
2.8%
시 6
 
2.4%
Other values (70) 159
62.6%
Latin
ValueCountFrequency (%)
A 3
 
7.7%
F 3
 
7.7%
r 2
 
5.1%
S 2
 
5.1%
V 2
 
5.1%
I 2
 
5.1%
e 2
 
5.1%
u 2
 
5.1%
t 2
 
5.1%
C 2
 
5.1%
Other values (15) 17
43.6%
Common
ValueCountFrequency (%)
72
39.3%
2 33
18.0%
0 30
16.4%
( 13
 
7.1%
) 13
 
7.1%
1 12
 
6.6%
9 9
 
4.9%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 254
53.4%
ASCII 222
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
32.4%
2 33
14.9%
0 30
13.5%
( 13
 
5.9%
) 13
 
5.9%
1 12
 
5.4%
9 9
 
4.1%
A 3
 
1.4%
F 3
 
1.4%
r 2
 
0.9%
Other values (23) 32
14.4%
Hangul
ValueCountFrequency (%)
전 14
 
5.5%
소 14
 
5.5%
국 13
 
5.1%
제 10
 
3.9%
회 10
 
3.9%
스 7
 
2.8%
비 7
 
2.8%
취 7
 
2.8%
프 7
 
2.8%
시 6
 
2.4%
Other values (70) 159
62.6%

전시시작
Date

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2018-05-01 00:00:00
Maximum2021-03-01 00:00:00
2023-12-12T14:22:49.755603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:22:49.902351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

전시종료
Date

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2019-05-05 00:00:00
Maximum2021-03-04 00:00:00
2023-12-12T14:22:50.002848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:22:50.100623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

참가기업(개사)
Real number (ℝ)

Distinct6
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.142857
Minimum10
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T14:22:50.205311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile20
Q120
median30
Q330
95-th percentile35
Maximum50
Range40
Interquartile range (IQR)10

Descriptive statistics

Standard deviation8.3023233
Coefficient of variation (CV)0.30587507
Kurtosis1.9915052
Mean27.142857
Median Absolute Deviation (MAD)5
Skewness0.6089746
Sum570
Variance68.928571
MonotonicityNot monotonic
2023-12-12T14:22:50.327056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 7
33.3%
20 6
28.6%
25 3
14.3%
35 3
14.3%
50 1
 
4.8%
10 1
 
4.8%
ValueCountFrequency (%)
10 1
 
4.8%
20 6
28.6%
25 3
14.3%
30 7
33.3%
35 3
14.3%
50 1
 
4.8%
ValueCountFrequency (%)
50 1
 
4.8%
35 3
14.3%
30 7
33.3%
25 3
14.3%
20 6
28.6%
10 1
 
4.8%

Interactions

2023-12-12T14:22:47.678934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:22:50.479446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원년도개최국가전시분야전시회명전시시작전시종료참가기업(개사)
지원년도1.0000.0000.9851.0001.0001.0000.366
개최국가0.0001.0000.7341.0000.9241.0000.809
전시분야0.9850.7341.0001.0001.0001.0000.725
전시회명1.0001.0001.0001.0001.0001.0001.000
전시시작1.0000.9241.0001.0001.0001.0001.000
전시종료1.0001.0001.0001.0001.0001.0001.000
참가기업(개사)0.3660.8090.7251.0001.0001.0001.000
2023-12-12T14:22:50.577424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원년도전시분야
지원년도1.0000.789
전시분야0.7891.000
2023-12-12T14:22:50.659746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
참가기업(개사)지원년도전시분야
참가기업(개사)1.0000.2080.317
지원년도0.2081.0000.789
전시분야0.3170.7891.000

Missing values

2023-12-12T14:22:47.833634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:22:47.978458image/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

지원년도개최국가전시분야전시회명전시시작전시종료참가기업(개사)
02019년중국종합2019 중국 광저우 수출입상품 교역회(캔톤페어)2018-05-012019-05-0520
12019년베트남소비재2019 베트남 국제 프리미엄 소비재전2019-05-302019-06-0230
22019년일본소비재2019 동경 국제 선물용품 전시회2019-09-032019-09-0630
32019년인도기계2019 인도 전자부품박람회2019-09-252019-09-2720
42019년홍콩전기전자2019 홍콩 스타트업 런치패드2019-10-182019-10-2125
52019년두바이정보통신2019 두바이 정보통신 전시회2019-10-062019-10-1020
62019년홍콩소비재2019 홍콩 메가쇼2019-10-202019-10-2320
72019년중국소비재2019 상해 국제수입박람회2019-11-052019-11-1030
82019년인니소비재2019 인도네시아 자카르타 국제 프리미엄 소비재전2019-11-072019-11-0950
92019년미국전기전자2020 국제전자제품박람회2020-01-072020-01-1025
지원년도개최국가전시분야전시회명전시시작전시종료참가기업(개사)
112020년베트남종합2020 베트남 국제 프리미엄 소비재전2020-05-292020-06-0135
122020년프랑스스타트업2020 프랑스 파리 VIVA Technology(취소)2020-06-112020-06-1310
132020년미국종합2020 미국 라스베가스 소비재전(취소)2020-08-022020-08-0530
142020년독일스타트업2020 독일 베를린 국제 가전 박람회(IFA)(취소)2020-09-042020-09-0920
152020년UAE스타트업2020 UAE 두바이 정보통신 전시회(Future Star)(취소)2020-09-272020-09-3025
162020년중국종합2020 중국 상해 국제수입박람회(취소)2020-11-052020-11-1035
172020년인도네시아종합2020 인도네시아 자카르타 국제 프리미엄 소비재전(취소)2020-11-052020-11-0735
182020년미국스타트업2021 미국 라스베가스 소비전자 전시회(CES)(온라인변경)2021-01-062021-01-0930
192020년독일종합2021 독일 프랑크푸르트 소비재전(취소)2021-02-192021-02-2330
202020년스페인스타트업2021 스페인 바르셀로나 MWC(4YFN)2021-03-012021-03-0420