Overview

Dataset statistics

Number of variables5
Number of observations51
Missing cells8
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory42.6 B

Variable types

Text3
Categorical2

Dataset

Description한국가스공사 기술이전현황 데이터로 한국가스공사의 이전기술 명칭, 기술이전 업체, 등록번호 등에 대한 정보를 제공합니다.
Author한국가스공사
URLhttps://www.data.go.kr/data/15042126/fileData.do

Alerts

기타 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 기타High correlation
등록번호 has 8 (15.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 02:12:43.376839
Analysis finished2023-12-12 02:12:43.911885
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기술이전업체
Text

Distinct41
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T11:12:44.126942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length9
Mean length6.4117647
Min length3

Characters and Unicode

Total characters327
Distinct characters120
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)70.6%

Sample

1st row㈜한유 SK ETS (구.㈜지코스)
2nd row㈜동성화인텍
3rd row㈜한울인텍스
4th row코렐 테크놀로지㈜
5th row강림인슈㈜
ValueCountFrequency (%)
성화산업㈜ 4
 
7.0%
태산enc 4
 
7.0%
㈜한국에너지기술단 3
 
5.3%
강림인슈㈜ 2
 
3.5%
㈜코씰 2
 
3.5%
㈜아이지아이에스 1
 
1.8%
sk 1
 
1.8%
ets 1
 
1.8%
구.㈜지코스 1
 
1.8%
㈜크린테크 1
 
1.8%
Other values (37) 37
64.9%
2023-12-12T11:12:44.573230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 33
 
10.1%
이 15
 
4.6%
11
 
3.4%
산 11
 
3.4%
스 8
 
2.4%
성 7
 
2.1%
( 7
 
2.1%
) 7
 
2.1%
한 7
 
2.1%
지 7
 
2.1%
Other values (110) 214
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 239
73.1%
Other Symbol 33
 
10.1%
Uppercase Letter 28
 
8.6%
Space Separator 11
 
3.4%
Open Punctuation 7
 
2.1%
Close Punctuation 7
 
2.1%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 15
 
6.3%
산 11
 
4.6%
스 8
 
3.3%
성 7
 
2.9%
한 7
 
2.9%
지 7
 
2.9%
업 7
 
2.9%
에 6
 
2.5%
주 6
 
2.5%
화 6
 
2.5%
Other values (96) 159
66.5%
Uppercase Letter
ValueCountFrequency (%)
C 7
25.0%
N 5
17.9%
E 5
17.9%
T 4
14.3%
S 3
10.7%
K 2
 
7.1%
R 1
 
3.6%
D 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
. 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 33
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
83.2%
Latin 28
 
8.6%
Common 27
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 33
 
12.1%
이 15
 
5.5%
산 11
 
4.0%
스 8
 
2.9%
성 7
 
2.6%
한 7
 
2.6%
지 7
 
2.6%
업 7
 
2.6%
에 6
 
2.2%
주 6
 
2.2%
Other values (97) 165
60.7%
Latin
ValueCountFrequency (%)
C 7
25.0%
N 5
17.9%
E 5
17.9%
T 4
14.3%
S 3
10.7%
K 2
 
7.1%
R 1
 
3.6%
D 1
 
3.6%
Common
ValueCountFrequency (%)
11
40.7%
( 7
25.9%
) 7
25.9%
& 1
 
3.7%
. 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 239
73.1%
ASCII 55
 
16.8%
None 33
 
10.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 33
100.0%
Hangul
ValueCountFrequency (%)
이 15
 
6.3%
산 11
 
4.6%
스 8
 
3.3%
성 7
 
2.9%
한 7
 
2.9%
지 7
 
2.9%
업 7
 
2.9%
에 6
 
2.5%
주 6
 
2.5%
화 6
 
2.5%
Other values (96) 159
66.5%
ASCII
ValueCountFrequency (%)
11
20.0%
( 7
12.7%
) 7
12.7%
C 7
12.7%
N 5
9.1%
E 5
9.1%
T 4
 
7.3%
S 3
 
5.5%
K 2
 
3.6%
R 1
 
1.8%
Other values (3) 3
 
5.5%

이전 기술명
Text

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T11:12:44.919473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length28
Mean length17.882353
Min length4

Characters and Unicode

Total characters912
Distinct characters201
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)60.8%

Sample

1st row가스히터용 부식억제제 GH-110 제조기술
2nd row멤브레인형 저장탱크 단열재 제조방법
3rd row천연가스누설 경보기제조기술
4th row벤처 포괄기술이전 (무선송출 기능을 갖는 데이터 로거 장치 등 3건)
5th row초저온 보냉용 폴리우레탄폼 및 제조기술
ValueCountFrequency (%)
기술 13
 
5.9%
타공사 11
 
5.0%
감시시스템 11
 
5.0%
상시 11
 
5.0%
제조기술 8
 
3.6%
및 8
 
3.6%
장치 6
 
2.7%
폼 3
 
1.4%
이용한 3
 
1.4%
이를 3
 
1.4%
Other values (111) 145
65.3%
2023-12-12T11:12:45.699468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
 
19.0%
시 43
 
4.7%
기 32
 
3.5%
용 29
 
3.2%
술 25
 
2.7%
스 23
 
2.5%
제 19
 
2.1%
조 16
 
1.8%
사 14
 
1.5%
장 14
 
1.5%
Other values (191) 524
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 656
71.9%
Space Separator 173
 
19.0%
Lowercase Letter 37
 
4.1%
Uppercase Letter 33
 
3.6%
Decimal Number 8
 
0.9%
Dash Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 43
 
6.6%
기 32
 
4.9%
용 29
 
4.4%
술 25
 
3.8%
스 23
 
3.5%
제 19
 
2.9%
조 16
 
2.4%
사 14
 
2.1%
장 14
 
2.1%
템 13
 
2.0%
Other values (158) 428
65.2%
Uppercase Letter
ValueCountFrequency (%)
G 8
24.2%
N 5
15.2%
L 5
15.2%
C 2
 
6.1%
T 2
 
6.1%
E 2
 
6.1%
M 2
 
6.1%
D 2
 
6.1%
H 2
 
6.1%
B 1
 
3.0%
Other values (2) 2
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
e 7
18.9%
n 6
16.2%
i 6
16.2%
t 4
10.8%
r 4
10.8%
a 3
8.1%
l 2
 
5.4%
o 2
 
5.4%
k 1
 
2.7%
s 1
 
2.7%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
0 1
 
12.5%
9 1
 
12.5%
4 1
 
12.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
% 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 656
71.9%
Common 186
 
20.4%
Latin 70
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 43
 
6.6%
기 32
 
4.9%
용 29
 
4.4%
술 25
 
3.8%
스 23
 
3.5%
제 19
 
2.9%
조 16
 
2.4%
사 14
 
2.1%
장 14
 
2.1%
템 13
 
2.0%
Other values (158) 428
65.2%
Latin
ValueCountFrequency (%)
G 8
 
11.4%
e 7
 
10.0%
n 6
 
8.6%
i 6
 
8.6%
N 5
 
7.1%
L 5
 
7.1%
t 4
 
5.7%
r 4
 
5.7%
a 3
 
4.3%
l 2
 
2.9%
Other values (13) 20
28.6%
Common
ValueCountFrequency (%)
173
93.0%
1 4
 
2.2%
- 2
 
1.1%
0 1
 
0.5%
% 1
 
0.5%
9 1
 
0.5%
4 1
 
0.5%
) 1
 
0.5%
3 1
 
0.5%
( 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 656
71.9%
ASCII 256
 
28.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
67.6%
G 8
 
3.1%
e 7
 
2.7%
n 6
 
2.3%
i 6
 
2.3%
N 5
 
2.0%
L 5
 
2.0%
t 4
 
1.6%
1 4
 
1.6%
r 4
 
1.6%
Other values (23) 34
 
13.3%
Hangul
ValueCountFrequency (%)
시 43
 
6.6%
기 32
 
4.9%
용 29
 
4.4%
술 25
 
3.8%
스 23
 
3.5%
제 19
 
2.9%
조 16
 
2.4%
사 14
 
2.1%
장 14
 
2.1%
템 13
 
2.0%
Other values (158) 428
65.2%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size540.0 B
특허
39 
노하우
7 
노하우 및 특허
 
2
노아우 및 특허
 
2
프로그램
 
1

Length

Max length8
Median length2
Mean length2.6470588
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row노하우
2nd row노하우 및 특허
3rd row노하우 및 특허
4th row노아우 및 특허
5th row노하우

Common Values

ValueCountFrequency (%)
특허 39
76.5%
노하우 7
 
13.7%
노하우 및 특허 2
 
3.9%
노아우 및 특허 2
 
3.9%
프로그램 1
 
2.0%

Length

2023-12-12T11:12:45.840737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:12:45.972373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특허 43
72.9%
노하우 9
 
15.3%
및 4
 
6.8%
노아우 2
 
3.4%
프로그램 1
 
1.7%

등록번호
Text

MISSING 

Distinct26
Distinct (%)60.5%
Missing8
Missing (%)15.7%
Memory size540.0 B
2023-12-12T11:12:46.152393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length10
Mean length10.44186
Min length10

Characters and Unicode

Total characters449
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)48.8%

Sample

1st row10-0284981
2nd row30-0244885
3rd row10-0284981
4th row10-1147545
5th row10-0812100
ValueCountFrequency (%)
10-1388498 11
25.0%
10-1691722 4
 
9.1%
10-0284981 3
 
6.8%
10-1274883 2
 
4.5%
10-1994098 2
 
4.5%
10-0964826 1
 
2.3%
2009-01-121-004618 1
 
2.3%
10-0967183 1
 
2.3%
10-1620262 1
 
2.3%
10-0869896 1
 
2.3%
Other values (17) 17
38.6%
2023-12-12T11:12:46.458938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 91
20.3%
0 72
16.0%
8 67
14.9%
- 46
10.2%
9 34
 
7.6%
4 33
 
7.3%
2 27
 
6.0%
3 21
 
4.7%
7 21
 
4.7%
6 19
 
4.2%
Other values (2) 18
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 402
89.5%
Dash Punctuation 46
 
10.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91
22.6%
0 72
17.9%
8 67
16.7%
9 34
 
8.5%
4 33
 
8.2%
2 27
 
6.7%
3 21
 
5.2%
7 21
 
5.2%
6 19
 
4.7%
5 17
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 449
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 91
20.3%
0 72
16.0%
8 67
14.9%
- 46
10.2%
9 34
 
7.6%
4 33
 
7.3%
2 27
 
6.0%
3 21
 
4.7%
7 21
 
4.7%
6 19
 
4.2%
Other values (2) 18
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 91
20.3%
0 72
16.0%
8 67
14.9%
- 46
10.2%
9 34
 
7.6%
4 33
 
7.3%
2 27
 
6.0%
3 21
 
4.7%
7 21
 
4.7%
6 19
 
4.2%
Other values (2) 18
 
4.0%

기타
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size540.0 B
<NA>
31 
무상 기술나눔
20 

Length

Max length7
Median length4
Mean length5.1764706
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 31
60.8%
무상 기술나눔 20
39.2%

Length

2023-12-12T11:12:46.643785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:12:46.793314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
43.7%
무상 20
28.2%
기술나눔 20
28.2%

Correlations

2023-12-12T11:12:46.866963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기술이전업체이전 기술명구분등록번호
기술이전업체1.0000.0000.9820.000
이전 기술명0.0001.0001.0000.997
구분0.9821.0001.0000.688
등록번호0.0000.9970.6881.000
2023-12-12T11:12:46.986512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기타구분
기타1.0001.000
구분1.0001.000
2023-12-12T11:12:47.083438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기타
구분1.0001.000
기타1.0001.000

Missing values

2023-12-12T11:12:43.747329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:12:43.868532image/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

기술이전업체이전 기술명구분등록번호기타
0㈜한유 SK ETS (구.㈜지코스)가스히터용 부식억제제 GH-110 제조기술노하우<NA><NA>
1㈜동성화인텍멤브레인형 저장탱크 단열재 제조방법노하우 및 특허10-0284981<NA>
2㈜한울인텍스천연가스누설 경보기제조기술노하우 및 특허30-0244885<NA>
3코렐 테크놀로지㈜벤처 포괄기술이전 (무선송출 기능을 갖는 데이터 로거 장치 등 3건)노아우 및 특허<NA><NA>
4강림인슈㈜초저온 보냉용 폴리우레탄폼 및 제조기술노하우10-0284981<NA>
5㈜하이트롤LNG연료용기용 레벨게이지 제작기술노아우 및 특허<NA><NA>
6현대종합금속㈜9%니켈강 용접봉 제조기술노하우<NA><NA>
7㈜코씰연료전지용 황흡착제 제조기술노하우<NA><NA>
8㈜코씰연료전지용 황화합물 검지용지시제 제조기술특허10-1147545<NA>
9㈜희성촉매DME 합성촉매 제조기술특허10-0812100<NA>
기술이전업체이전 기술명구분등록번호기타
41성화산업㈜액화가스 저장탱크의 액화가스 공급용 배관특허10-0964826무상 기술나눔
42성화산업㈜경질 폴리우레탄 폼 조성물 및 이를 이용한 보냉재특허10-0507847무상 기술나눔
43성화산업㈜경질 폴리우레탄 폼 조성물 및 이를 이용한 보냉재특허10-0585531무상 기술나눔
44성화산업㈜용량 가변형 가스용 정압기특허10-1721778무상 기술나눔
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