Overview

Dataset statistics

Number of variables4
Number of observations55
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory34.4 B

Variable types

Categorical3
Text1

Dataset

Description공사 보인기술의 대국민 홍보 및 중소기업 상생협력 네트워크 강화를 위한 보안기술 설명회 개최현황 관련 데이터(개최횟수, 기술소개 등)
Author한국조폐공사
URLhttps://www.data.go.kr/data/15090707/fileData.do

Alerts

장소 has constant value ""Constant
개최 is highly overall correlated with 개최일자High correlation
개최일자 is highly overall correlated with 개최High correlation
기술소개 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:05:00.116056
Analysis finished2023-12-12 00:05:00.410848
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개최
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
6회
9 
5회
8 
1회
7 
2회
7 
3회
7 
Other values (3)
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1회
2nd row1회
3rd row1회
4th row1회
5th row1회

Common Values

ValueCountFrequency (%)
6회 9
16.4%
5회 8
14.5%
1회 7
12.7%
2회 7
12.7%
3회 7
12.7%
4회 6
10.9%
7회 6
10.9%
8회 5
9.1%

Length

2023-12-12T09:05:00.464510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:05:00.567185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6회 9
16.4%
5회 8
14.5%
1회 7
12.7%
2회 7
12.7%
3회 7
12.7%
4회 6
10.9%
7회 6
10.9%
8회 5
9.1%

개최일자
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
2019-11-28
9 
2018-10-25-
8 
2014-09-25
7 
2015-09-22
7 
2016-09-26
7 
Other values (3)
17 

Length

Max length11
Median length10
Mean length10.145455
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014-09-25
2nd row2014-09-25
3rd row2014-09-25
4th row2014-09-25
5th row2014-09-25

Common Values

ValueCountFrequency (%)
2019-11-28 9
16.4%
2018-10-25- 8
14.5%
2014-09-25 7
12.7%
2015-09-22 7
12.7%
2016-09-26 7
12.7%
2017-09-20 6
10.9%
2020-10-14 6
10.9%
2021-11-03 5
9.1%

Length

2023-12-12T09:05:00.717307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:05:00.829716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-11-28 9
16.4%
2018-10-25 8
14.5%
2014-09-25 7
12.7%
2015-09-22 7
12.7%
2016-09-26 7
12.7%
2017-09-20 6
10.9%
2020-10-14 6
10.9%
2021-11-03 5
9.1%

장소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
대한상공회의소
55 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대한상공회의소 55
100.0%

Length

2023-12-12T09:05:00.971873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:05:01.077471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대한상공회의소 55
100.0%

기술소개
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T09:05:01.297442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length28
Mean length13.363636
Min length4

Characters and Unicode

Total characters735
Distinct characters205
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row복사방해패턴
2nd row스마트씨
3rd row히든 QR
4th row엠보싱 잠상
5th row브랜드보호 라벨
ValueCountFrequency (%)
히든 3
 
2.2%
보안라벨 3
 
2.2%
브랜드보호 3
 
2.2%
솔루션 2
 
1.4%
기술 2
 
1.4%
친환경 2
 
1.4%
모바일상품권(chak 2
 
1.4%
모바일 2
 
1.4%
스마트씨 2
 
1.4%
보안모듈 2
 
1.4%
Other values (111) 115
83.3%
2023-12-12T09:05:01.735253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
 
11.3%
보 30
 
4.1%
안 24
 
3.3%
, 22
 
3.0%
( 19
 
2.6%
) 19
 
2.6%
모 12
 
1.6%
상 10
 
1.4%
스 10
 
1.4%
용 9
 
1.2%
Other values (195) 497
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 533
72.5%
Space Separator 83
 
11.3%
Uppercase Letter 42
 
5.7%
Other Punctuation 23
 
3.1%
Open Punctuation 19
 
2.6%
Close Punctuation 19
 
2.6%
Decimal Number 9
 
1.2%
Lowercase Letter 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 30
 
5.6%
안 24
 
4.5%
모 12
 
2.3%
상 10
 
1.9%
스 10
 
1.9%
용 9
 
1.7%
라 9
 
1.7%
일 9
 
1.7%
기 9
 
1.7%
형 9
 
1.7%
Other values (163) 402
75.4%
Uppercase Letter
ValueCountFrequency (%)
Q 6
14.3%
R 6
14.3%
C 5
11.9%
A 3
7.1%
S 3
7.1%
K 3
7.1%
D 3
7.1%
H 2
 
4.8%
I 2
 
4.8%
O 2
 
4.8%
Other values (5) 7
16.7%
Decimal Number
ValueCountFrequency (%)
0 2
22.2%
7 2
22.2%
4 2
22.2%
2 1
11.1%
1 1
11.1%
3 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
28.6%
y 1
14.3%
a 1
14.3%
e 1
14.3%
h 1
14.3%
o 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 22
95.7%
& 1
 
4.3%
Space Separator
ValueCountFrequency (%)
83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 533
72.5%
Common 153
 
20.8%
Latin 49
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 30
 
5.6%
안 24
 
4.5%
모 12
 
2.3%
상 10
 
1.9%
스 10
 
1.9%
용 9
 
1.7%
라 9
 
1.7%
일 9
 
1.7%
기 9
 
1.7%
형 9
 
1.7%
Other values (163) 402
75.4%
Latin
ValueCountFrequency (%)
Q 6
12.2%
R 6
12.2%
C 5
 
10.2%
A 3
 
6.1%
S 3
 
6.1%
K 3
 
6.1%
D 3
 
6.1%
l 2
 
4.1%
H 2
 
4.1%
I 2
 
4.1%
Other values (11) 14
28.6%
Common
ValueCountFrequency (%)
83
54.2%
, 22
 
14.4%
( 19
 
12.4%
) 19
 
12.4%
0 2
 
1.3%
7 2
 
1.3%
4 2
 
1.3%
2 1
 
0.7%
1 1
 
0.7%
3 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 533
72.5%
ASCII 202
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
41.1%
, 22
 
10.9%
( 19
 
9.4%
) 19
 
9.4%
Q 6
 
3.0%
R 6
 
3.0%
C 5
 
2.5%
A 3
 
1.5%
S 3
 
1.5%
K 3
 
1.5%
Other values (22) 33
 
16.3%
Hangul
ValueCountFrequency (%)
보 30
 
5.6%
안 24
 
4.5%
모 12
 
2.3%
상 10
 
1.9%
스 10
 
1.9%
용 9
 
1.7%
라 9
 
1.7%
일 9
 
1.7%
기 9
 
1.7%
형 9
 
1.7%
Other values (163) 402
75.4%

Correlations

2023-12-12T09:05:01.846419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개최개최일자기술소개
개최1.0001.0001.000
개최일자1.0001.0001.000
기술소개1.0001.0001.000
2023-12-12T09:05:01.946407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개최개최일자
개최1.0001.000
개최일자1.0001.000
2023-12-12T09:05:02.024397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개최개최일자
개최1.0001.000
개최일자1.0001.000

Missing values

2023-12-12T09:05:00.307245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:05:00.380051image/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

개최개최일자장소기술소개
01회2014-09-25대한상공회의소복사방해패턴
11회2014-09-25대한상공회의소스마트씨
21회2014-09-25대한상공회의소히든 QR
31회2014-09-25대한상공회의소엠보싱 잠상
41회2014-09-25대한상공회의소브랜드보호 라벨
51회2014-09-25대한상공회의소입체형 보안필름
61회2014-09-25대한상공회의소카드 위변조방지 기술
72회2015-09-22대한상공회의소히든 CODE
82회2015-09-22대한상공회의소스마트입체필름
92회2015-09-22대한상공회의소형광 보안패턴
개최개최일자장소기술소개
457회2020-10-14대한상공회의소(인증) 모바일 ID, 모바일 투표, 전기차
467회2020-10-14대한상공회의소(브랜드보호) 보안라벨,의류, 형광다중화
477회2020-10-14대한상공회의소(보안솔루션) 보안잉크, 용지, COS솔루션, 보안모듈패턴
487회2020-10-14대한상공회의소(금융) 홍보은행권, 모바일상품권
497회2020-10-14대한상공회의소(친환경) 일회용 보증컵
508회2021-11-03대한상공회의소(모바일페이) 모바일상품권(CHAK), 가맹점QR결제, 통합관리시스템
518회2021-11-03대한상공회의소(모바일신분증) 모바일공무원증, QR로그인, 증명서관리, 청사출입시스템
528회2021-11-03대한상공회의소(브랜드보호) 오키브랜드, 브랜드보호사업
538회2021-11-03대한상공회의소(연구성과) 1회용컵 보안라벨, 시차변색형 잉크적용 메달, 스마튠, 보안메달
548회2021-11-03대한상공회의소(70년사) 70년 변천사, 특수압인제품