Overview

Dataset statistics

Number of variables5
Number of observations249
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory40.5 B

Variable types

Text4
Categorical1

Dataset

Description한국연구재단이 보유하고있는 온라인논문투고심사시스템에 있는학술대회운영조직 데이터 입니다. 대표 데이터는 기관명, 기관ID 명 등이 있습니다.
Author한국연구재단
URLhttps://www.data.go.kr/data/15092912/fileData.do

Alerts

운영조직(ID) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:45:58.890625
Analysis finished2023-12-12 15:45:59.565657
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관명
Text

Distinct71
Distinct (%)28.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T00:45:59.834203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length17
Mean length9.9959839
Min length5

Characters and Unicode

Total characters2489
Distinct characters146
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

Unique33 ?
Unique (%)13.3%

Sample

1st row강릉원주대학교 한국일본문화학회
2nd row강릉원주대학교 한국일본문화학회
3rd row한국감성과학회
4th row한국인지및생물심리학회
5th row사단법인 한국교육심리학회
ValueCountFrequency (%)
사)한국스마트미디어학회 25
 
8.5%
사단법인 21
 
7.2%
대한수학교육학회 14
 
4.8%
대한통합의학회 13
 
4.4%
한국비블리아학회 13
 
4.4%
한국산업정보학회 13
 
4.4%
유공압건설기계학회 11
 
3.8%
한국정보관리학회 10
 
3.4%
한국유통과학회 8
 
2.7%
사)한국동물생명공학회 8
 
2.7%
Other values (70) 157
53.6%
2023-12-13T00:46:00.418008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 285
 
11.5%
회 249
 
10.0%
한 235
 
9.4%
국 196
 
7.9%
사 81
 
3.3%
교 60
 
2.4%
대 57
 
2.3%
44
 
1.8%
보 43
 
1.7%
육 43
 
1.7%
Other values (136) 1196
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2337
93.9%
Space Separator 44
 
1.8%
Open Punctuation 42
 
1.7%
Close Punctuation 42
 
1.7%
Uppercase Letter 19
 
0.8%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 285
 
12.2%
회 249
 
10.7%
한 235
 
10.1%
국 196
 
8.4%
사 81
 
3.5%
교 60
 
2.6%
대 57
 
2.4%
보 43
 
1.8%
육 43
 
1.8%
리 41
 
1.8%
Other values (126) 1047
44.8%
Uppercase Letter
ValueCountFrequency (%)
T 5
26.3%
P 3
15.8%
A 3
15.8%
E 3
15.8%
K 3
15.8%
I 2
 
10.5%
Space Separator
ValueCountFrequency (%)
44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Other Punctuation
ValueCountFrequency (%)
？ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2337
93.9%
Common 133
 
5.3%
Latin 19
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 285
 
12.2%
회 249
 
10.7%
한 235
 
10.1%
국 196
 
8.4%
사 81
 
3.5%
교 60
 
2.6%
대 57
 
2.4%
보 43
 
1.8%
육 43
 
1.8%
리 41
 
1.8%
Other values (126) 1047
44.8%
Latin
ValueCountFrequency (%)
T 5
26.3%
P 3
15.8%
A 3
15.8%
E 3
15.8%
K 3
15.8%
I 2
 
10.5%
Common
ValueCountFrequency (%)
44
33.1%
( 42
31.6%
) 42
31.6%
？ 5
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2337
93.9%
ASCII 147
 
5.9%
None 5
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 285
 
12.2%
회 249
 
10.7%
한 235
 
10.1%
국 196
 
8.4%
사 81
 
3.5%
교 60
 
2.6%
대 57
 
2.4%
보 43
 
1.8%
육 43
 
1.8%
리 41
 
1.8%
Other values (126) 1047
44.8%
ASCII
ValueCountFrequency (%)
44
29.9%
( 42
28.6%
) 42
28.6%
T 5
 
3.4%
P 3
 
2.0%
A 3
 
2.0%
E 3
 
2.0%
K 3
 
2.0%
I 2
 
1.4%
None
ValueCountFrequency (%)
？ 5
100.0%

기관(ID)
Text

Distinct71
Distinct (%)28.5%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T00:46:00.779908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2988
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)13.3%

Sample

1st rowINS000001630
2nd rowINS000001630
3rd rowINS000001565
4th rowINS000000947
5th rowINS000000754
ValueCountFrequency (%)
ins000010113 25
 
10.0%
ins000000952 14
 
5.6%
ins000001286 13
 
5.2%
ins000011210 13
 
5.2%
ins000000021 13
 
5.2%
ins000000238 11
 
4.4%
ins000001217 10
 
4.0%
ins000000509 8
 
3.2%
ins000001161 8
 
3.2%
ins000006678 7
 
2.8%
Other values (61) 127
51.0%
2023-12-13T00:46:01.280644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1390
46.5%
1 287
 
9.6%
I 249
 
8.3%
N 249
 
8.3%
S 249
 
8.3%
2 121
 
4.0%
3 81
 
2.7%
5 76
 
2.5%
8 72
 
2.4%
6 68
 
2.3%
Other values (3) 146
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2241
75.0%
Uppercase Letter 747
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1390
62.0%
1 287
 
12.8%
2 121
 
5.4%
3 81
 
3.6%
5 76
 
3.4%
8 72
 
3.2%
6 68
 
3.0%
9 53
 
2.4%
7 49
 
2.2%
4 44
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
I 249
33.3%
N 249
33.3%
S 249
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2241
75.0%
Latin 747
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1390
62.0%
1 287
 
12.8%
2 121
 
5.4%
3 81
 
3.6%
5 76
 
3.4%
8 72
 
3.2%
6 68
 
3.0%
9 53
 
2.4%
7 49
 
2.2%
4 44
 
2.0%
Latin
ValueCountFrequency (%)
I 249
33.3%
N 249
33.3%
S 249
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2988
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1390
46.5%
1 287
 
9.6%
I 249
 
8.3%
N 249
 
8.3%
S 249
 
8.3%
2 121
 
4.0%
3 81
 
2.7%
5 76
 
2.5%
8 72
 
2.4%
6 68
 
2.3%
Other values (3) 146
 
4.9%

학술대회(ID)
Categorical

Distinct22
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
AC0000000001
72 
AC0000000004
32 
AC0000000002
23 
AC0000000003
23 
AC0000000006
21 
Other values (17)
78 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique6 ?
Unique (%)2.4%

Sample

1st rowAC0000000002
2nd rowAC0000000003
3rd rowAC0000000002
4th rowAC0000000001
5th rowAC0000000001

Common Values

ValueCountFrequency (%)
AC0000000001 72
28.9%
AC0000000004 32
12.9%
AC0000000002 23
 
9.2%
AC0000000003 23
 
9.2%
AC0000000006 21
 
8.4%
AC0000000005 14
 
5.6%
AC0000000007 14
 
5.6%
AC0000000011 11
 
4.4%
AC0000000015 11
 
4.4%
AC0000000008 6
 
2.4%
Other values (12) 22
 
8.8%

Length

2023-12-13T00:46:01.484758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ac0000000001 72
28.9%
ac0000000004 32
12.9%
ac0000000002 23
 
9.2%
ac0000000003 23
 
9.2%
ac0000000006 21
 
8.4%
ac0000000005 14
 
5.6%
ac0000000007 14
 
5.6%
ac0000000011 11
 
4.4%
ac0000000015 11
 
4.4%
ac0000000008 6
 
2.4%
Other values (12) 22
 
8.8%

운영조직(ID)
Text

UNIQUE 

Distinct249
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T00:46:01.764325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2988
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)100.0%

Sample

1st rowOOR000000007
2nd rowOOR000000008
3rd rowOOR000000009
4th rowOOR000000013
5th rowOOR000000018
ValueCountFrequency (%)
oor000000007 1
 
0.4%
oor000000294 1
 
0.4%
oor000000318 1
 
0.4%
oor000000269 1
 
0.4%
oor000000270 1
 
0.4%
oor000000271 1
 
0.4%
oor000000272 1
 
0.4%
oor000000274 1
 
0.4%
oor000000275 1
 
0.4%
oor000000277 1
 
0.4%
Other values (239) 239
96.0%
2023-12-13T00:46:02.195432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1593
53.3%
O 498
 
16.7%
R 249
 
8.3%
3 121
 
4.0%
1 106
 
3.5%
2 99
 
3.3%
7 60
 
2.0%
6 60
 
2.0%
8 55
 
1.8%
5 54
 
1.8%
Other values (2) 93
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2241
75.0%
Uppercase Letter 747
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1593
71.1%
3 121
 
5.4%
1 106
 
4.7%
2 99
 
4.4%
7 60
 
2.7%
6 60
 
2.7%
8 55
 
2.5%
5 54
 
2.4%
9 52
 
2.3%
4 41
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
O 498
66.7%
R 249
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2241
75.0%
Latin 747
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1593
71.1%
3 121
 
5.4%
1 106
 
4.7%
2 99
 
4.4%
7 60
 
2.7%
6 60
 
2.7%
8 55
 
2.5%
5 54
 
2.4%
9 52
 
2.3%
4 41
 
1.8%
Latin
ValueCountFrequency (%)
O 498
66.7%
R 249
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2988
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1593
53.3%
O 498
 
16.7%
R 249
 
8.3%
3 121
 
4.0%
1 106
 
3.5%
2 99
 
3.3%
7 60
 
2.0%
6 60
 
2.0%
8 55
 
1.8%
5 54
 
1.8%
Other values (2) 93
 
3.1%

한글운영조직명
Text

Distinct159
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T00:46:02.532766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length9.1726908
Min length2

Characters and Unicode

Total characters2284
Distinct characters202
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

Unique135 ?
Unique (%)54.2%

Sample

1st row한국일본문화학회 제35회 국제학술대회 조직위원회
2nd row한국일본문화학회 제35회 국제학술대회 조직위
3rd row2010 춘계학술대회 조직위원회
4th row테스트 학술대회 조직위
5th row학술위원회
ValueCountFrequency (%)
조직위원회 44
 
10.1%
학술위원회 28
 
6.5%
운영위원회 16
 
3.7%
학술대회 14
 
3.2%
춘계학술대회 10
 
2.3%
준비위원회 10
 
2.3%
수학교육학 9
 
2.1%
위원 8
 
1.8%
2015년 6
 
1.4%
2018 5
 
1.2%
Other values (193) 284
65.4%
2023-12-13T00:46:03.063813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 233
 
10.2%
185
 
8.1%
원 178
 
7.8%
위 173
 
7.6%
학 154
 
6.7%
술 98
 
4.3%
대 71
 
3.1%
조 64
 
2.8%
직 64
 
2.8%
0 47
 
2.1%
Other values (192) 1017
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1803
78.9%
Space Separator 185
 
8.1%
Decimal Number 182
 
8.0%
Lowercase Letter 75
 
3.3%
Uppercase Letter 27
 
1.2%
Other Punctuation 11
 
0.5%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 233
 
12.9%
원 178
 
9.9%
위 173
 
9.6%
학 154
 
8.5%
술 98
 
5.4%
대 71
 
3.9%
조 64
 
3.5%
직 64
 
3.5%
장 31
 
1.7%
영 27
 
1.5%
Other values (153) 710
39.4%
Lowercase Letter
ValueCountFrequency (%)
e 17
22.7%
i 9
12.0%
n 9
12.0%
t 7
9.3%
m 6
 
8.0%
o 6
 
8.0%
c 5
 
6.7%
r 5
 
6.7%
f 4
 
5.3%
h 2
 
2.7%
Other values (3) 5
 
6.7%
Decimal Number
ValueCountFrequency (%)
0 47
25.8%
2 47
25.8%
1 34
18.7%
5 12
 
6.6%
7 10
 
5.5%
6 9
 
4.9%
8 7
 
3.8%
9 6
 
3.3%
3 5
 
2.7%
4 5
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
C 8
29.6%
S 4
14.8%
K 3
 
11.1%
A 3
 
11.1%
E 2
 
7.4%
M 2
 
7.4%
T 2
 
7.4%
P 1
 
3.7%
R 1
 
3.7%
O 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
: 5
45.5%
, 4
36.4%
/ 1
 
9.1%
· 1
 
9.1%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1803
78.9%
Common 379
 
16.6%
Latin 102
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 233
 
12.9%
원 178
 
9.9%
위 173
 
9.6%
학 154
 
8.5%
술 98
 
5.4%
대 71
 
3.9%
조 64
 
3.5%
직 64
 
3.5%
장 31
 
1.7%
영 27
 
1.5%
Other values (153) 710
39.4%
Latin
ValueCountFrequency (%)
e 17
16.7%
i 9
 
8.8%
n 9
 
8.8%
C 8
 
7.8%
t 7
 
6.9%
m 6
 
5.9%
o 6
 
5.9%
c 5
 
4.9%
r 5
 
4.9%
f 4
 
3.9%
Other values (13) 26
25.5%
Common
ValueCountFrequency (%)
185
48.8%
0 47
 
12.4%
2 47
 
12.4%
1 34
 
9.0%
5 12
 
3.2%
7 10
 
2.6%
6 9
 
2.4%
8 7
 
1.8%
9 6
 
1.6%
3 5
 
1.3%
Other values (6) 17
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1803
78.9%
ASCII 480
 
21.0%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 233
 
12.9%
원 178
 
9.9%
위 173
 
9.6%
학 154
 
8.5%
술 98
 
5.4%
대 71
 
3.9%
조 64
 
3.5%
직 64
 
3.5%
장 31
 
1.7%
영 27
 
1.5%
Other values (153) 710
39.4%
ASCII
ValueCountFrequency (%)
185
38.5%
0 47
 
9.8%
2 47
 
9.8%
1 34
 
7.1%
e 17
 
3.5%
5 12
 
2.5%
7 10
 
2.1%
i 9
 
1.9%
n 9
 
1.9%
6 9
 
1.9%
Other values (28) 101
21.0%
None
ValueCountFrequency (%)
· 1
100.0%

Correlations

2023-12-13T00:46:03.184139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명기관(ID)학술대회(ID)
기관명1.0001.0000.765
기관(ID)1.0001.0000.765
학술대회(ID)0.7650.7651.000

Missing values

2023-12-13T00:45:59.369833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:45:59.511911image/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

기관명기관(ID)학술대회(ID)운영조직(ID)한글운영조직명
0강릉원주대학교 한국일본문화학회INS000001630AC0000000002OOR000000007한국일본문화학회 제35회 국제학술대회 조직위원회
1강릉원주대학교 한국일본문화학회INS000001630AC0000000003OOR000000008한국일본문화학회 제35회 국제학술대회 조직위
2한국감성과학회INS000001565AC0000000002OOR0000000092010 춘계학술대회 조직위원회
3한국인지및생물심리학회INS000000947AC0000000001OOR000000013테스트 학술대회 조직위
4사단법인 한국교육심리학회INS000000754AC0000000001OOR000000018학술위원회
5한국IT서비스학회INS000000284AC0000000001OOR000000027조직위원회
6한국IT서비스학회INS000000284AC0000000001OOR000000028학술위원회
7한국유통과학회INS000000509AC0000000001OOR000000031학술위원회
8한국음성학회INS000006678AC0000000002OOR000000044학술대회장
9한국음성학회INS000006678AC0000000002OOR000000045조직위원회
기관명기관(ID)학술대회(ID)운영조직(ID)한글운영조직명
239사단법인 유공압건설기계학회INS000000238AC0000000015OOR000000390특별세션위원
240사단법인 유공압건설기계학회INS000000238AC0000000015OOR000000391대외홍보위원
241사단법인 유공압건설기계학회INS000000238AC0000000015OOR000000392후원재무위원
242사단법인 유공압건설기계학회INS000000238AC0000000015OOR000000393학회 사무국
243한국기술혁신학회INS000001743AC0000000007OOR000000394학술위원회
244한국기술혁신학회INS000001743AC0000000007OOR000000395운영위원회
245한국기술혁신학회INS000001743AC0000000008OOR000000396학술위원회
246한국기술혁신학회INS000001743AC0000000008OOR000000397운영위원회
247한국디지털포렌식학회INS000009412AC0000000006OOR000000398프로그램위원회
248대한통합의학회INS000011210AC0000000008OOR000000400운영위원회