Overview

Dataset statistics

Number of variables5
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory42.6 B

Variable types

Categorical3
Text2

Dataset

Description년도별 내일채움공제 가입 우수기업 선정 현황 공공데이터는 년도, 지역, 기업, 업종, 주생산품 정보를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15086518/fileData.do

Reproduction

Analysis started2023-12-12 18:34:30.929665
Analysis finished2023-12-12 18:34:32.537837
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct5
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023
26 
2018
15 
2020
15 
2021
15 
2019
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2023 26
31.0%
2018 15
17.9%
2020 15
17.9%
2021 15
17.9%
2019 13
15.5%

Length

2023-12-13T03:34:32.687714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:34:32.909194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 26
31.0%
2018 15
17.9%
2020 15
17.9%
2021 15
17.9%
2019 13
15.5%

지역
Categorical

Distinct16
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
서울
12 
경기
11 
경남
7 
전북
6 
전남
6 
Other values (11)
42 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st row서울
2nd row서울
3rd row경기
4th row경기
5th row경기

Common Values

ValueCountFrequency (%)
서울 12
14.3%
경기 11
13.1%
경남 7
8.3%
전북 6
 
7.1%
전남 6
 
7.1%
경북 6
 
7.1%
강원 5
 
6.0%
부산 5
 
6.0%
인천 5
 
6.0%
충남 5
 
6.0%
Other values (6) 16
19.0%

Length

2023-12-13T03:34:33.148092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 12
14.3%
경기 11
13.1%
경남 7
8.3%
전북 6
 
7.1%
전남 6
 
7.1%
경북 6
 
7.1%
강원 5
 
6.0%
부산 5
 
6.0%
인천 5
 
6.0%
충남 5
 
6.0%
Other values (6) 16
19.0%

기업명
Text

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T03:34:33.427159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length6.0833333
Min length3

Characters and Unicode

Total characters511
Distinct characters170
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)95.2%

Sample

1st row㈜하몬소프트
2nd row㈜비원씨앤알
3rd row㈜우성플라테크
4th row㈜뷰웍스
5th row㈜동방파스텍
ValueCountFrequency (%)
아이엔테코㈜ 2
 
2.3%
주식회사 2
 
2.3%
버드나무양조장㈜ 2
 
2.3%
㈜성호전자 1
 
1.2%
㈜우리식품 1
 
1.2%
㈜에이치엘아이 1
 
1.2%
케이에스콤프레샤㈜ 1
 
1.2%
㈜데이타뱅크 1
 
1.2%
온오프시스템 1
 
1.2%
㈜포스타입 1
 
1.2%
Other values (73) 73
84.9%
2023-12-13T03:34:33.959700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 72
 
14.1%
스 24
 
4.7%
이 17
 
3.3%
에 11
 
2.2%
인 9
 
1.8%
산 8
 
1.6%
아 8
 
1.6%
프 7
 
1.4%
주 7
 
1.4%
씨 7
 
1.4%
Other values (160) 341
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 429
84.0%
Other Symbol 72
 
14.1%
Close Punctuation 4
 
0.8%
Open Punctuation 4
 
0.8%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 24
 
5.6%
이 17
 
4.0%
에 11
 
2.6%
인 9
 
2.1%
산 8
 
1.9%
아 8
 
1.9%
프 7
 
1.6%
주 7
 
1.6%
씨 7
 
1.6%
지 7
 
1.6%
Other values (156) 324
75.5%
Other Symbol
ValueCountFrequency (%)
㈜ 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 501
98.0%
Common 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 72
 
14.4%
스 24
 
4.8%
이 17
 
3.4%
에 11
 
2.2%
인 9
 
1.8%
산 8
 
1.6%
아 8
 
1.6%
프 7
 
1.4%
주 7
 
1.4%
씨 7
 
1.4%
Other values (157) 331
66.1%
Common
ValueCountFrequency (%)
) 4
40.0%
( 4
40.0%
2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 429
84.0%
None 72
 
14.1%
ASCII 10
 
2.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 72
100.0%
Hangul
ValueCountFrequency (%)
스 24
 
5.6%
이 17
 
4.0%
에 11
 
2.6%
인 9
 
2.1%
산 8
 
1.9%
아 8
 
1.9%
프 7
 
1.6%
주 7
 
1.6%
씨 7
 
1.6%
지 7
 
1.6%
Other values (156) 324
75.5%
ASCII
ValueCountFrequency (%)
) 4
40.0%
( 4
40.0%
2
20.0%

업종
Categorical

Distinct14
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size804.0 B
기계
21 
기타
12 
식료
9 
정보
8 
화공
8 
Other values (9)
26 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row정보
2nd row잡화
3rd row화공
4th row기계
5th row금속

Common Values

ValueCountFrequency (%)
기계 21
25.0%
기타 12
14.3%
식료 9
10.7%
정보 8
 
9.5%
화공 8
 
9.5%
전기 7
 
8.3%
유통 5
 
6.0%
잡화 4
 
4.8%
금속 4
 
4.8%
전자 2
 
2.4%
Other values (4) 4
 
4.8%

Length

2023-12-13T03:34:34.164651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계 21
25.0%
기타 12
14.3%
식료 9
10.7%
정보 8
 
9.5%
화공 8
 
9.5%
전기 7
 
8.3%
유통 5
 
6.0%
잡화 4
 
4.8%
금속 4
 
4.8%
전자 2
 
2.4%
Other values (4) 4
 
4.8%

주생산품
Text

Distinct82
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T03:34:34.438913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19.5
Mean length9.9285714
Min length2

Characters and Unicode

Total characters834
Distinct characters238
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

Unique80 ?
Unique (%)95.2%

Sample

1st row통합관제시스템 등 시스템 구축 및 유지보수
2nd row종이상자
3rd row화장품 용기
4th row줌카메라 모듈
5th row방화문 프레임 부품제조
ValueCountFrequency (%)
등 12
 
6.2%
및 7
 
3.6%
제조 5
 
2.6%
소프트웨어 4
 
2.1%
케이블 4
 
2.1%
반도체 3
 
1.6%
제조업 2
 
1.0%
광고대행 2
 
1.0%
디스플레이 2
 
1.0%
수제맥주 2
 
1.0%
Other values (145) 150
77.7%
2023-12-13T03:34:34.880332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
 
13.2%
제 23
 
2.8%
이 17
 
2.0%
스 16
 
1.9%
리 13
 
1.6%
등 12
 
1.4%
조 11
 
1.3%
기 11
 
1.3%
용 11
 
1.3%
비 11
 
1.3%
Other values (228) 599
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 693
83.1%
Space Separator 110
 
13.2%
Uppercase Letter 17
 
2.0%
Open Punctuation 5
 
0.6%
Close Punctuation 5
 
0.6%
Other Punctuation 3
 
0.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 23
 
3.3%
이 17
 
2.5%
스 16
 
2.3%
리 13
 
1.9%
등 12
 
1.7%
조 11
 
1.6%
기 11
 
1.6%
용 11
 
1.6%
비 11
 
1.6%
지 11
 
1.6%
Other values (210) 557
80.4%
Uppercase Letter
ValueCountFrequency (%)
T 4
23.5%
A 2
11.8%
I 2
11.8%
C 1
 
5.9%
N 1
 
5.9%
B 1
 
5.9%
R 1
 
5.9%
E 1
 
5.9%
Y 1
 
5.9%
W 1
 
5.9%
Other values (2) 2
11.8%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 693
83.1%
Common 124
 
14.9%
Latin 17
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 23
 
3.3%
이 17
 
2.5%
스 16
 
2.3%
리 13
 
1.9%
등 12
 
1.7%
조 11
 
1.6%
기 11
 
1.6%
용 11
 
1.6%
비 11
 
1.6%
지 11
 
1.6%
Other values (210) 557
80.4%
Latin
ValueCountFrequency (%)
T 4
23.5%
A 2
11.8%
I 2
11.8%
C 1
 
5.9%
N 1
 
5.9%
B 1
 
5.9%
R 1
 
5.9%
E 1
 
5.9%
Y 1
 
5.9%
W 1
 
5.9%
Other values (2) 2
11.8%
Common
ValueCountFrequency (%)
110
88.7%
( 5
 
4.0%
) 5
 
4.0%
/ 2
 
1.6%
3 1
 
0.8%
. 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 693
83.1%
ASCII 141
 
16.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
78.0%
( 5
 
3.5%
) 5
 
3.5%
T 4
 
2.8%
A 2
 
1.4%
I 2
 
1.4%
/ 2
 
1.4%
C 1
 
0.7%
N 1
 
0.7%
3 1
 
0.7%
Other values (8) 8
 
5.7%
Hangul
ValueCountFrequency (%)
제 23
 
3.3%
이 17
 
2.5%
스 16
 
2.3%
리 13
 
1.9%
등 12
 
1.7%
조 11
 
1.6%
기 11
 
1.6%
용 11
 
1.6%
비 11
 
1.6%
지 11
 
1.6%
Other values (210) 557
80.4%

Correlations

2023-12-13T03:34:35.009429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도지역기업명업종주생산품
년도1.0000.0000.7750.0000.775
지역0.0001.0001.0000.5371.000
기업명0.7751.0001.0001.0001.000
업종0.0000.5371.0001.0001.000
주생산품0.7751.0001.0001.0001.000
2023-12-13T03:34:35.116559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종년도
지역1.0000.2070.000
업종0.2071.0000.000
년도0.0000.0001.000
2023-12-13T03:34:35.233594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도지역업종
년도1.0000.0000.000
지역0.0001.0000.207
업종0.0000.2071.000

Missing values

2023-12-13T03:34:32.167962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:34:32.438133image/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

년도지역기업명업종주생산품
02018서울㈜하몬소프트정보통합관제시스템 등 시스템 구축 및 유지보수
12018서울㈜비원씨앤알잡화종이상자
22018경기㈜우성플라테크화공화장품 용기
32018경기㈜뷰웍스기계줌카메라 모듈
42018경기㈜동방파스텍금속방화문 프레임 부품제조
52018강원지오멕스소프트정보지리정보 소프트웨어
62018대전㈜알테오젠기타바이오시밀러
72018충북(주)유니언스화공합성수지 및 기타 플라스틱물질 제조업
82018전북㈜새롬식품식료식빵 두부
92018전북정우화인㈜화공우레탄폴리올 판넬접착제
년도지역기업명업종주생산품
742023제주㈜대한에프앤비축산축산업 등
752023경북㈜엠소닉전자스피커 오디오
762023경북㈜승헌기타금속류 원료 재생
772023경북㈜모빌퍼스잡화사무용가구(파티션 의자)
782023부산㈜청우기술단기타전기안전서비스대행
792023부산에스제이이㈜기계스팀세척기
802023울산㈜높임기계선박부품 제조 등
812023경남㈜성호전자전기방산용 케이블 및 하네스
822023경남아이엔테코㈜기계절삭가공칩 처리설비
832023경남㈜금산산기기계엘리베이터부품