Overview

Dataset statistics

Number of variables6
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory50.5 B

Variable types

Categorical2
Text4

Dataset

Description제주국제자유도시개발센터에서 운영하는 제주특별자치도 제주시에 위치한 첨단과학기술단지 내 제주혁신성장센터의 2020년 9월 기준 입주기업 정보입니다.
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15066202/fileData.do

Alerts

구분(분류) is highly overall correlated with 구분(기수)High correlation
구분(기수) is highly overall correlated with 구분(분류)High correlation
기업명 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:26:16.159158
Analysis finished2023-12-13 00:26:16.798743
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분(분류)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
ICT융합창업허브
31 
친환경스마트자동차연구센터
15 
낭그늘
6 

Length

Max length13
Median length10
Mean length10.057692
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ICT융합창업허브 31
59.6%
친환경스마트자동차연구센터 15
28.8%
낭그늘 6
 
11.5%

Length

2023-12-13T09:26:16.846220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:26:16.926767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ict융합창업허브 31
59.6%
친환경스마트자동차연구센터 15
28.8%
낭그늘 6
 
11.5%

구분(기수)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
2기
24 
1기
22 
해당없음
6 

Length

Max length4
Median length2
Mean length2.2307692
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1기
2nd row1기
3rd row1기
4th row1기
5th row1기

Common Values

ValueCountFrequency (%)
2기 24
46.2%
1기 22
42.3%
해당없음 6
 
11.5%

Length

2023-12-13T09:26:17.015737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:26:17.094286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2기 24
46.2%
1기 22
42.3%
해당없음 6
 
11.5%

기업명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T09:26:17.249472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length7.2307692
Min length3

Characters and Unicode

Total characters376
Distinct characters131
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row(주)블로코
2nd row농업회사법인 주식회사 프롬제주
3rd row인피니티 플래닛
4th row㈜다이브비앤비
5th row㈜디스커버제주
ValueCountFrequency (%)
주식회사 10
 
15.2%
주)블로코 1
 
1.5%
㈜지오라인 1
 
1.5%
㈜잇더컴퍼니 1
 
1.5%
㈜타디스 1
 
1.5%
테크놀로지 1
 
1.5%
㈜제이디테크 1
 
1.5%
㈜하이퍼리얼익스피리언스 1
 
1.5%
㈜해녀의부엌 1
 
1.5%
㈜구보엔지니어링 1
 
1.5%
Other values (47) 47
71.2%
2023-12-13T09:26:17.532038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 37
 
9.8%
이 19
 
5.1%
주 15
 
4.0%
스 14
 
3.7%
14
 
3.7%
사 13
 
3.5%
회 12
 
3.2%
식 10
 
2.7%
리 8
 
2.1%
오 7
 
1.9%
Other values (121) 227
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
83.8%
Other Symbol 37
 
9.8%
Space Separator 14
 
3.7%
Uppercase Letter 4
 
1.1%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 19
 
6.0%
주 15
 
4.8%
스 14
 
4.4%
사 13
 
4.1%
회 12
 
3.8%
식 10
 
3.2%
리 8
 
2.5%
오 7
 
2.2%
인 7
 
2.2%
지 7
 
2.2%
Other values (113) 203
64.4%
Uppercase Letter
ValueCountFrequency (%)
R 1
25.0%
A 1
25.0%
E 1
25.0%
V 1
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 37
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
93.6%
Common 20
 
5.3%
Latin 4
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 37
 
10.5%
이 19
 
5.4%
주 15
 
4.3%
스 14
 
4.0%
사 13
 
3.7%
회 12
 
3.4%
식 10
 
2.8%
리 8
 
2.3%
오 7
 
2.0%
인 7
 
2.0%
Other values (114) 210
59.7%
Latin
ValueCountFrequency (%)
R 1
25.0%
A 1
25.0%
E 1
25.0%
V 1
25.0%
Common
ValueCountFrequency (%)
14
70.0%
( 3
 
15.0%
) 3
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
83.8%
None 37
 
9.8%
ASCII 24
 
6.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 37
100.0%
Hangul
ValueCountFrequency (%)
이 19
 
6.0%
주 15
 
4.8%
스 14
 
4.4%
사 13
 
4.1%
회 12
 
3.8%
식 10
 
3.2%
리 8
 
2.5%
오 7
 
2.2%
인 7
 
2.2%
지 7
 
2.2%
Other values (113) 203
64.4%
ASCII
ValueCountFrequency (%)
14
58.3%
( 3
 
12.5%
) 3
 
12.5%
R 1
 
4.2%
A 1
 
4.2%
E 1
 
4.2%
V 1
 
4.2%

업종
Text

Distinct45
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T09:26:17.730374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17.5
Mean length9.2307692
Min length2

Characters and Unicode

Total characters480
Distinct characters128
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

Unique40 ?
Unique (%)76.9%

Sample

1st row블록체인
2nd row제주원물 6차산업
3rd row관광IT
4th row관광IT
5th row관광IT
ValueCountFrequency (%)
연구개발업 6
 
5.9%
ict 5
 
5.0%
개발 4
 
4.0%
및 4
 
4.0%
관광it 3
 
3.0%
서비스업 3
 
3.0%
공학기술연구개발 2
 
2.0%
도소매 2
 
2.0%
소프트웨어 2
 
2.0%
제조 2
 
2.0%
Other values (61) 68
67.3%
2023-12-13T09:26:18.025003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
 
10.2%
업 17
 
3.5%
개 17
 
3.5%
발 16
 
3.3%
, 15
 
3.1%
스 14
 
2.9%
구 13
 
2.7%
연 12
 
2.5%
제 10
 
2.1%
비 10
 
2.1%
Other values (118) 307
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
77.3%
Space Separator 49
 
10.2%
Uppercase Letter 35
 
7.3%
Other Punctuation 17
 
3.5%
Decimal Number 2
 
0.4%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 17
 
4.6%
개 17
 
4.6%
발 16
 
4.3%
스 14
 
3.8%
구 13
 
3.5%
연 12
 
3.2%
제 10
 
2.7%
비 10
 
2.7%
서 10
 
2.7%
전 9
 
2.4%
Other values (102) 243
65.5%
Uppercase Letter
ValueCountFrequency (%)
I 10
28.6%
T 10
28.6%
C 7
20.0%
W 3
 
8.6%
S 2
 
5.7%
H 1
 
2.9%
R 1
 
2.9%
V 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 15
88.2%
/ 1
 
5.9%
& 1
 
5.9%
Space Separator
ValueCountFrequency (%)
49
100.0%
Decimal Number
ValueCountFrequency (%)
6 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
77.3%
Common 74
 
15.4%
Latin 35
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 17
 
4.6%
개 17
 
4.6%
발 16
 
4.3%
스 14
 
3.8%
구 13
 
3.5%
연 12
 
3.2%
제 10
 
2.7%
비 10
 
2.7%
서 10
 
2.7%
전 9
 
2.4%
Other values (102) 243
65.5%
Common
ValueCountFrequency (%)
49
66.2%
, 15
 
20.3%
6 2
 
2.7%
( 2
 
2.7%
) 2
 
2.7%
- 2
 
2.7%
/ 1
 
1.4%
& 1
 
1.4%
Latin
ValueCountFrequency (%)
I 10
28.6%
T 10
28.6%
C 7
20.0%
W 3
 
8.6%
S 2
 
5.7%
H 1
 
2.9%
R 1
 
2.9%
V 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
77.3%
ASCII 109
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
45.0%
, 15
 
13.8%
I 10
 
9.2%
T 10
 
9.2%
C 7
 
6.4%
W 3
 
2.8%
6 2
 
1.8%
( 2
 
1.8%
) 2
 
1.8%
- 2
 
1.8%
Other values (6) 7
 
6.4%
Hangul
ValueCountFrequency (%)
업 17
 
4.6%
개 17
 
4.6%
발 16
 
4.3%
스 14
 
3.8%
구 13
 
3.5%
연 12
 
3.2%
제 10
 
2.7%
비 10
 
2.7%
서 10
 
2.7%
전 9
 
2.4%
Other values (102) 243
65.5%

사업내용
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T09:26:18.258315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length35.5
Mean length27.346154
Min length7

Characters and Unicode

Total characters1422
Distinct characters269
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)96.2%

Sample

1st row블록체인 플랫폼
2nd row청정제주 식용곤충을 활용한 글로벌 바이오 기업(숙취해소제 벵주야)
3rd row디지털트랜스포메이션 기반 미래관광 플랫폼
4th row전 세계 스쿠버다이빙 리조트 및 리브어보드 관리 및 예약 플랫폼
5th row지역 연계 액티비티 여행 플랫폼
ValueCountFrequency (%)
및 15
 
4.4%
플랫폼 13
 
3.8%
서비스 10
 
2.9%
개발 9
 
2.6%
활용한 7
 
2.0%
전기차 7
 
2.0%
충전 6
 
1.7%
솔루션 5
 
1.5%
공유 4
 
1.2%
시스템 4
 
1.2%
Other values (214) 263
76.7%
2023-12-13T09:26:18.619071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
298
 
21.0%
기 41
 
2.9%
전 34
 
2.4%
스 29
 
2.0%
, 21
 
1.5%
비 17
 
1.2%
한 17
 
1.2%
공 17
 
1.2%
개 17
 
1.2%
제 17
 
1.2%
Other values (259) 914
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1026
72.2%
Space Separator 298
 
21.0%
Uppercase Letter 31
 
2.2%
Lowercase Letter 26
 
1.8%
Other Punctuation 22
 
1.5%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%
Final Punctuation 3
 
0.2%
Initial Punctuation 3
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 41
 
4.0%
전 34
 
3.3%
스 29
 
2.8%
비 17
 
1.7%
한 17
 
1.7%
공 17
 
1.7%
개 17
 
1.7%
제 17
 
1.7%
플 16
 
1.6%
및 15
 
1.5%
Other values (224) 806
78.6%
Uppercase Letter
ValueCountFrequency (%)
T 5
16.1%
C 4
12.9%
S 3
9.7%
M 3
9.7%
I 3
9.7%
E 2
 
6.5%
V 2
 
6.5%
R 2
 
6.5%
A 2
 
6.5%
D 2
 
6.5%
Other values (3) 3
9.7%
Lowercase Letter
ValueCountFrequency (%)
g 3
11.5%
a 3
11.5%
t 3
11.5%
i 3
11.5%
n 2
7.7%
r 2
7.7%
o 2
7.7%
p 2
7.7%
h 2
7.7%
u 1
 
3.8%
Other values (3) 3
11.5%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
& 1
 
4.5%
Space Separator
ValueCountFrequency (%)
298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Final Punctuation
ValueCountFrequency (%)
” 3
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1026
72.2%
Common 339
 
23.8%
Latin 57
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 41
 
4.0%
전 34
 
3.3%
스 29
 
2.8%
비 17
 
1.7%
한 17
 
1.7%
공 17
 
1.7%
개 17
 
1.7%
제 17
 
1.7%
플 16
 
1.6%
및 15
 
1.5%
Other values (224) 806
78.6%
Latin
ValueCountFrequency (%)
T 5
 
8.8%
C 4
 
7.0%
g 3
 
5.3%
S 3
 
5.3%
M 3
 
5.3%
I 3
 
5.3%
a 3
 
5.3%
t 3
 
5.3%
i 3
 
5.3%
n 2
 
3.5%
Other values (16) 25
43.9%
Common
ValueCountFrequency (%)
298
87.9%
, 21
 
6.2%
( 5
 
1.5%
) 5
 
1.5%
” 3
 
0.9%
“ 3
 
0.9%
- 2
 
0.6%
3 1
 
0.3%
& 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1026
72.2%
ASCII 390
 
27.4%
Punctuation 6
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
298
76.4%
, 21
 
5.4%
T 5
 
1.3%
( 5
 
1.3%
) 5
 
1.3%
C 4
 
1.0%
g 3
 
0.8%
S 3
 
0.8%
M 3
 
0.8%
I 3
 
0.8%
Other values (23) 40
 
10.3%
Hangul
ValueCountFrequency (%)
기 41
 
4.0%
전 34
 
3.3%
스 29
 
2.8%
비 17
 
1.7%
한 17
 
1.7%
공 17
 
1.7%
개 17
 
1.7%
제 17
 
1.7%
플 16
 
1.6%
및 15
 
1.5%
Other values (224) 806
78.6%
Punctuation
ValueCountFrequency (%)
” 3
50.0%
“ 3
50.0%

대표자명
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T09:26:18.812030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length3.5769231
Min length2

Characters and Unicode

Total characters186
Distinct characters87
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)96.2%

Sample

1st row김원범, 박병옥 지사장
2nd row김병주
3rd row해당정보 없음
4th row이순진
5th row김형우, HER JONAH JIN
ValueCountFrequency (%)
신재희 2
 
3.4%
김애옥 1
 
1.7%
박병옥 1
 
1.7%
지사장 1
 
1.7%
이용권 1
 
1.7%
이상천 1
 
1.7%
최영훈 1
 
1.7%
김하원 1
 
1.7%
강규남 1
 
1.7%
박용희 1
 
1.7%
Other values (48) 48
81.4%
2023-12-13T09:26:19.103266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 15
 
8.1%
이 12
 
6.5%
용 8
 
4.3%
박 7
 
3.8%
7
 
3.8%
정 6
 
3.2%
성 5
 
2.7%
신 5
 
2.7%
희 5
 
2.7%
형 4
 
2.2%
Other values (77) 112
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
88.7%
Uppercase Letter 11
 
5.9%
Space Separator 7
 
3.8%
Other Punctuation 3
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 15
 
9.1%
이 12
 
7.3%
용 8
 
4.8%
박 7
 
4.2%
정 6
 
3.6%
성 5
 
3.0%
신 5
 
3.0%
희 5
 
3.0%
형 4
 
2.4%
옥 4
 
2.4%
Other values (67) 94
57.0%
Uppercase Letter
ValueCountFrequency (%)
N 2
18.2%
J 2
18.2%
H 2
18.2%
E 1
9.1%
R 1
9.1%
O 1
9.1%
A 1
9.1%
I 1
9.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
88.7%
Latin 11
 
5.9%
Common 10
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 15
 
9.1%
이 12
 
7.3%
용 8
 
4.8%
박 7
 
4.2%
정 6
 
3.6%
성 5
 
3.0%
신 5
 
3.0%
희 5
 
3.0%
형 4
 
2.4%
옥 4
 
2.4%
Other values (67) 94
57.0%
Latin
ValueCountFrequency (%)
N 2
18.2%
J 2
18.2%
H 2
18.2%
E 1
9.1%
R 1
9.1%
O 1
9.1%
A 1
9.1%
I 1
9.1%
Common
ValueCountFrequency (%)
7
70.0%
, 3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
88.7%
ASCII 21
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 15
 
9.1%
이 12
 
7.3%
용 8
 
4.8%
박 7
 
4.2%
정 6
 
3.6%
성 5
 
3.0%
신 5
 
3.0%
희 5
 
3.0%
형 4
 
2.4%
옥 4
 
2.4%
Other values (67) 94
57.0%
ASCII
ValueCountFrequency (%)
7
33.3%
, 3
14.3%
N 2
 
9.5%
J 2
 
9.5%
H 2
 
9.5%
E 1
 
4.8%
R 1
 
4.8%
O 1
 
4.8%
A 1
 
4.8%
I 1
 
4.8%

Correlations

2023-12-13T09:26:19.180719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(분류)구분(기수)기업명업종사업내용대표자명
구분(분류)1.0000.9471.0001.0001.0001.000
구분(기수)0.9471.0001.0000.9951.0000.882
기업명1.0001.0001.0001.0001.0001.000
업종1.0000.9951.0001.0000.9851.000
사업내용1.0001.0001.0000.9851.0000.997
대표자명1.0000.8821.0001.0000.9971.000
2023-12-13T09:26:19.254771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(기수)구분(분류)
구분(기수)1.0000.718
구분(분류)0.7181.000
2023-12-13T09:26:19.312468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분(분류)구분(기수)
구분(분류)1.0000.718
구분(기수)0.7181.000

Missing values

2023-12-13T09:26:16.693108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:26:16.769116image/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

구분(분류)구분(기수)기업명업종사업내용대표자명
0ICT융합창업허브1기(주)블로코블록체인블록체인 플랫폼김원범, 박병옥 지사장
1ICT융합창업허브1기농업회사법인 주식회사 프롬제주제주원물 6차산업청정제주 식용곤충을 활용한 글로벌 바이오 기업(숙취해소제 벵주야)김병주
2ICT융합창업허브1기인피니티 플래닛관광IT디지털트랜스포메이션 기반 미래관광 플랫폼해당정보 없음
3ICT융합창업허브1기㈜다이브비앤비관광IT전 세계 스쿠버다이빙 리조트 및 리브어보드 관리 및 예약 플랫폼이순진
4ICT융합창업허브1기㈜디스커버제주관광IT지역 연계 액티비티 여행 플랫폼김형우, HER JONAH JIN
5ICT융합창업허브1기㈜바딧ICT(앱&디바이스-체형교정)체형 교정을 위한 모니터링 서비스(앱 및 디바이스)신민용
6ICT융합창업허브1기㈜브이에스팜텍바이오방사선 조사 치료 시 항암효과를 증진시키고 부작용을 경감시키는 항암보조제 연구개발 기업박신영
7ICT융합창업허브1기㈜브이오엠랩멀티미디어 플렛폼글로벌 멀티미디어 플랫폼신재희
8ICT융합창업허브1기㈜아스타리아블록체인블록체인 디앱서비스 플랫폼조한열
9ICT융합창업허브1기㈜에이투젯VR 플랫폼VR기반 기술개발기업김성국
구분(분류)구분(기수)기업명업종사업내용대표자명
42친환경스마트자동차연구센터2기㈜지니연구개발업, 제조업, 도소매, 소프트웨어개발업, 서비스업충전인프라 구축 사업, 충전 플랫폼 및 솔루션 개발, 전기차 충전기 개발, 전기공사, 신재생에너지최선옥
43친환경스마트자동차연구센터2기㈜시그넷에너지연구개발업, 유지보수 서비스업에너지저장장치 활용 기반 EV Smart Charging Solution이해옥
44친환경스마트자동차연구센터2기㈜진우소프트이노베이션SW 및 HW 개발 공학기술연구개발비공용 충전기를 활용한 공유 개방형 충전 인프라 전환 솔루션이무용
45친환경스마트자동차연구센터2기메티스정보㈜공학기술연구개발비공용 충전기를 활용한 공유 개방형 충전 인프라 전환 솔루션김봉수
46낭그늘해당없음㈜남의집경제 및 경영학 연구개발업가정집 거실에서 낯선이들과 집주인의 취향을 나누는 거실 여행 서비스김성용
47낭그늘해당없음주식회사 어플라이드론활용서비스인공지능 경량드론을 활용한 시설물 모니터링이건우
48낭그늘해당없음㈜위대한상사공유점포컨설팅서비스공유주방,점포 창업 플랫폼 서비스김유구
49낭그늘해당없음주식회사 이빛컴퍼니자동차 소프트웨어, 스마트 전기차 개초 플랫폼내연기관 자동차를 전기차로 개조박정민
50낭그늘해당없음주신글로벌테크 주식회사전기,전자공학 연구개발업폐플라스틱을 재활용한 사출성형장치 기술 개발장길남
51낭그늘해당없음주식회사 카카오패밀리식품 생산공학 연구개발업로컬 식자재와 콜라보한 관광상품 3종 개발 및 소셜다이닝김정아