Overview

Dataset statistics

Number of variables17
Number of observations2757
Missing cells3589
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory390.5 KiB
Average record size in memory145.0 B

Variable types

Text6
Categorical2
Numeric9

Dataset

Description한국연구재단의 한국학술지인용색인(KCI) 시스템정보입니다. 컬럼명은 ISSN , 학술지명, 발행기관 , 논문수, 피인용횟수 등 여러 자료를 나타내고 있습니다
URLhttps://www.data.go.kr/data/3049380/fileData.do

Alerts

한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년) is highly overall correlated with 한국학술지인용색인 영향력지수 (2년) and 1 other fieldsHigh correlation
한국학술지인용색인 영향력지수 (2년) is highly overall correlated with 한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년) and 4 other fieldsHigh correlation
자기인용제외 IF (2년) is highly overall correlated with 한국학술지인용색인 영향력지수 (2년) and 4 other fieldsHigh correlation
중심성 지수(3년) is highly overall correlated with 한국학술지인용색인 영향력지수 (2년) and 3 other fieldsHigh correlation
즉시성지수 is highly overall correlated with 한국학술지인용색인 영향력지수 (2년) and 3 other fieldsHigh correlation
자기인용 비율(2년) is highly overall correlated with 자기인용제외 IF (2년) and 1 other fieldsHigh correlation
논문수(2년) is highly overall correlated with 피인용횟수(2년)High correlation
피인용횟수(2년) is highly overall correlated with 한국학술지인용색인 영향력지수 (2년) and 3 other fieldsHigh correlation
웹오브사이언스 피인용횟수(2년) is highly overall correlated with 한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)High correlation
등재정보 is highly imbalanced (76.4%)Imbalance
국제표준연속 간행물 번호 has 73 (2.6%) missing valuesMissing
학술지명 외국어 has 278 (10.1%) missing valuesMissing
발행기관 영문 has 268 (9.7%) missing valuesMissing
한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년) has 2621 (95.1%) missing valuesMissing
한국학술지인용색인 영향력지수 (2년) has 95 (3.4%) missing valuesMissing
자기인용제외 IF (2년) has 95 (3.4%) missing valuesMissing
중심성 지수(3년) has 58 (2.1%) missing valuesMissing
자기인용 비율(2년) has 95 (3.4%) missing valuesMissing
피인용횟수(2년) is highly skewed (γ1 = 20.91635017)Skewed
자기인용제외 IF (2년) has 48 (1.7%) zerosZeros
즉시성지수 has 366 (13.3%) zerosZeros
자기인용 비율(2년) has 235 (8.5%) zerosZeros
논문수(2년) has 93 (3.4%) zerosZeros
피인용횟수(2년) has 158 (5.7%) zerosZeros
웹오브사이언스 피인용횟수(2년) has 2621 (95.1%) zerosZeros

Reproduction

Analysis started2023-12-11 23:35:10.124695
Analysis finished2023-12-11 23:35:21.340642
Duration11.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct2682
Distinct (%)99.9%
Missing73
Missing (%)2.6%
Memory size21.7 KiB
2023-12-12T08:35:21.573432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9873323
Min length6

Characters and Unicode

Total characters21438
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2680 ?
Unique (%)99.9%

Sample

1st row12297569
2nd row26358875
3rd row20051298
4th row22348646
5th row25088262
ValueCountFrequency (%)
12259489 2
 
0.1%
12299154 2
 
0.1%
12293288 1
 
< 0.1%
22884467 1
 
< 0.1%
12266655 1
 
< 0.1%
23838892 1
 
< 0.1%
1226363x 1
 
< 0.1%
15982351 1
 
< 0.1%
17386098 1
 
< 0.1%
22875778 1
 
< 0.1%
Other values (2672) 2672
99.6%
2023-12-12T08:35:22.014160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4174
19.5%
1 2897
13.5%
9 2155
10.1%
8 2052
9.6%
5 2008
9.4%
3 1729
8.1%
7 1724
8.0%
6 1719
8.0%
0 1533
 
7.2%
4 1200
 
5.6%
Other values (2) 247
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21191
98.8%
Uppercase Letter 232
 
1.1%
Lowercase Letter 15
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4174
19.7%
1 2897
13.7%
9 2155
10.2%
8 2052
9.7%
5 2008
9.5%
3 1729
8.2%
7 1724
8.1%
6 1719
8.1%
0 1533
 
7.2%
4 1200
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
X 232
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21191
98.8%
Latin 247
 
1.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4174
19.7%
1 2897
13.7%
9 2155
10.2%
8 2052
9.7%
5 2008
9.5%
3 1729
8.2%
7 1724
8.1%
6 1719
8.1%
0 1533
 
7.2%
4 1200
 
5.7%
Latin
ValueCountFrequency (%)
X 232
93.9%
x 15
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4174
19.5%
1 2897
13.5%
9 2155
10.1%
8 2052
9.6%
5 2008
9.4%
3 1729
8.1%
7 1724
8.0%
6 1719
8.0%
0 1533
 
7.2%
4 1200
 
5.6%
Other values (2) 247
 
1.2%
Distinct2715
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2023-12-12T08:35:22.413719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length68
Mean length11.351106
Min length2

Characters and Unicode

Total characters31295
Distinct characters584
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2693 ?
Unique (%)97.7%

Sample

1st row제주도연구
2nd row산업융합연구
3rd row기독교철학
4th rowPediatric Gastroenterology, Hepatology & Nutrition
5th row정형스포츠물리치료학회지
ValueCountFrequency (%)
of 237
 
5.1%
journal 227
 
4.8%
and 137
 
2.9%
research 49
 
1.0%
korean 47
 
1.0%
the 39
 
0.8%
international 39
 
0.8%
36
 
0.8%
science 34
 
0.7%
연구 34
 
0.7%
Other values (2992) 3803
81.2%
2023-12-12T08:35:23.403492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1975
 
6.3%
n 1260
 
4.0%
1220
 
3.9%
o 1190
 
3.8%
a 1179
 
3.8%
e 1104
 
3.5%
i 961
 
3.1%
944
 
3.0%
920
 
2.9%
r 840
 
2.7%
Other values (574) 19702
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15866
50.7%
Lowercase Letter 11242
35.9%
Space Separator 1976
 
6.3%
Uppercase Letter 1945
 
6.2%
Other Punctuation 135
 
0.4%
Close Punctuation 49
 
0.2%
Open Punctuation 49
 
0.2%
Dash Punctuation 22
 
0.1%
Decimal Number 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1220
 
7.7%
944
 
5.9%
920
 
5.8%
701
 
4.4%
697
 
4.4%
673
 
4.2%
618
 
3.9%
415
 
2.6%
328
 
2.1%
296
 
1.9%
Other values (504) 9054
57.1%
Lowercase Letter
ValueCountFrequency (%)
n 1260
11.2%
o 1190
10.6%
a 1179
10.5%
e 1104
9.8%
i 961
8.5%
r 840
 
7.5%
l 731
 
6.5%
t 637
 
5.7%
c 587
 
5.2%
s 487
 
4.3%
Other values (16) 2266
20.2%
Uppercase Letter
ValueCountFrequency (%)
J 241
12.4%
S 171
 
8.8%
A 169
 
8.7%
E 140
 
7.2%
C 137
 
7.0%
I 136
 
7.0%
P 112
 
5.8%
R 112
 
5.8%
T 104
 
5.3%
M 101
 
5.2%
Other values (15) 522
26.8%
Other Punctuation
ValueCountFrequency (%)
& 35
25.9%
: 29
21.5%
· 27
20.0%
. 21
15.6%
, 16
11.9%
5
 
3.7%
' 2
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 5
45.5%
2 3
27.3%
8 1
 
9.1%
9 1
 
9.1%
0 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1975
99.9%
  1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 47
95.9%
2
 
4.1%
Open Punctuation
ValueCountFrequency (%)
( 47
95.9%
2
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15655
50.0%
Latin 13187
42.1%
Common 2242
 
7.2%
Han 211
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1220
 
7.8%
944
 
6.0%
920
 
5.9%
701
 
4.5%
697
 
4.5%
673
 
4.3%
618
 
3.9%
415
 
2.7%
328
 
2.1%
296
 
1.9%
Other values (428) 8843
56.5%
Han
ValueCountFrequency (%)
23
 
10.9%
21
 
10.0%
21
 
10.0%
16
 
7.6%
7
 
3.3%
6
 
2.8%
6
 
2.8%
6
 
2.8%
6
 
2.8%
5
 
2.4%
Other values (66) 94
44.5%
Latin
ValueCountFrequency (%)
n 1260
 
9.6%
o 1190
 
9.0%
a 1179
 
8.9%
e 1104
 
8.4%
i 961
 
7.3%
r 840
 
6.4%
l 731
 
5.5%
t 637
 
4.8%
c 587
 
4.5%
s 487
 
3.7%
Other values (41) 4211
31.9%
Common
ValueCountFrequency (%)
1975
88.1%
) 47
 
2.1%
( 47
 
2.1%
& 35
 
1.6%
: 29
 
1.3%
· 27
 
1.2%
- 22
 
1.0%
. 21
 
0.9%
, 16
 
0.7%
5
 
0.2%
Other values (9) 18
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15653
50.0%
ASCII 15392
49.2%
CJK 206
 
0.7%
None 37
 
0.1%
CJK Compat Ideographs 5
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1975
12.8%
n 1260
 
8.2%
o 1190
 
7.7%
a 1179
 
7.7%
e 1104
 
7.2%
i 961
 
6.2%
r 840
 
5.5%
l 731
 
4.7%
t 637
 
4.1%
c 587
 
3.8%
Other values (55) 4928
32.0%
Hangul
ValueCountFrequency (%)
1220
 
7.8%
944
 
6.0%
920
 
5.9%
701
 
4.5%
697
 
4.5%
673
 
4.3%
618
 
3.9%
415
 
2.7%
328
 
2.1%
296
 
1.9%
Other values (427) 8841
56.5%
None
ValueCountFrequency (%)
· 27
73.0%
5
 
13.5%
2
 
5.4%
2
 
5.4%
  1
 
2.7%
CJK
ValueCountFrequency (%)
23
 
11.2%
21
 
10.2%
21
 
10.2%
16
 
7.8%
7
 
3.4%
6
 
2.9%
6
 
2.9%
6
 
2.9%
6
 
2.9%
5
 
2.4%
Other values (63) 89
43.2%
CJK Compat Ideographs
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Distinct2472
Distinct (%)99.7%
Missing278
Missing (%)10.1%
Memory size21.7 KiB
2023-12-12T08:35:23.736692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length70
Mean length36.015329
Min length1

Characters and Unicode

Total characters89282
Distinct characters126
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2465 ?
Unique (%)99.4%

Sample

1st rowJournal of Jeju Studies
2nd rowJournal of Industrial Convergence
3rd rowJournal of Christian Philosophy
4th rowPediatric Gastroenterology, Hepatology & Nutrition
5th rowArchives of Orthopedic and Sports Physical Therapy
ValueCountFrequency (%)
of 1845
 
14.5%
journal 1547
 
12.1%
korean 772
 
6.1%
the 695
 
5.4%
and 574
 
4.5%
studies 314
 
2.5%
society 236
 
1.9%
education 186
 
1.5%
research 183
 
1.4%
172
 
1.3%
Other values (1779) 6229
48.8%
2023-12-12T08:35:24.247250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10401
 
11.6%
o 7591
 
8.5%
e 6689
 
7.5%
a 6654
 
7.5%
n 6587
 
7.4%
r 5063
 
5.7%
i 4949
 
5.5%
t 3877
 
4.3%
l 3590
 
4.0%
u 3349
 
3.8%
Other values (116) 30532
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64177
71.9%
Uppercase Letter 14162
 
15.9%
Space Separator 10402
 
11.7%
Other Punctuation 302
 
0.3%
Dash Punctuation 115
 
0.1%
Other Letter 62
 
0.1%
Open Punctuation 21
 
< 0.1%
Close Punctuation 21
 
< 0.1%
Decimal Number 12
 
< 0.1%
Currency Symbol 3
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3
 
4.8%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
2
 
3.2%
Other values (41) 41
66.1%
Lowercase Letter
ValueCountFrequency (%)
o 7591
11.8%
e 6689
10.4%
a 6654
10.4%
n 6587
10.3%
r 5063
 
7.9%
i 4949
 
7.7%
t 3877
 
6.0%
l 3590
 
5.6%
u 3349
 
5.2%
c 2706
 
4.2%
Other values (16) 13122
20.4%
Uppercase Letter
ValueCountFrequency (%)
J 1611
 
11.4%
S 1256
 
8.9%
E 1103
 
7.8%
K 1055
 
7.4%
T 1021
 
7.2%
A 1020
 
7.2%
R 816
 
5.8%
C 811
 
5.7%
I 667
 
4.7%
O 651
 
4.6%
Other values (16) 4151
29.3%
Other Punctuation
ValueCountFrequency (%)
& 170
56.3%
, 61
 
20.2%
: 23
 
7.6%
. 14
 
4.6%
13
 
4.3%
' 9
 
3.0%
¡ 3
 
1.0%
3
 
1.0%
/ 3
 
1.0%
2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
2 4
33.3%
0 2
 
16.7%
Space Separator
ValueCountFrequency (%)
10401
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 78339
87.7%
Common 10881
 
12.2%
Hangul 33
 
< 0.1%
Han 29
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 7591
 
9.7%
e 6689
 
8.5%
a 6654
 
8.5%
n 6587
 
8.4%
r 5063
 
6.5%
i 4949
 
6.3%
t 3877
 
4.9%
l 3590
 
4.6%
u 3349
 
4.3%
c 2706
 
3.5%
Other values (42) 27284
34.8%
Hangul
ValueCountFrequency (%)
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (20) 20
60.6%
Common
ValueCountFrequency (%)
10401
95.6%
& 170
 
1.6%
- 115
 
1.1%
, 61
 
0.6%
: 23
 
0.2%
( 21
 
0.2%
) 21
 
0.2%
. 14
 
0.1%
13
 
0.1%
' 9
 
0.1%
Other values (13) 33
 
0.3%
Han
ValueCountFrequency (%)
3
 
10.3%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (11) 11
37.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89193
99.9%
Hangul 33
 
< 0.1%
CJK 28
 
< 0.1%
None 25
 
< 0.1%
Punctuation 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10401
 
11.7%
o 7591
 
8.5%
e 6689
 
7.5%
a 6654
 
7.5%
n 6587
 
7.4%
r 5063
 
5.7%
i 4949
 
5.5%
t 3877
 
4.3%
l 3590
 
4.0%
u 3349
 
3.8%
Other values (58) 30443
34.1%
None
ValueCountFrequency (%)
13
52.0%
¤ 3
 
12.0%
¡ 3
 
12.0%
3
 
12.0%
2
 
8.0%
  1
 
4.0%
CJK
ValueCountFrequency (%)
3
 
10.7%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
1
 
3.6%
Other values (10) 10
35.7%
Hangul
ValueCountFrequency (%)
2
 
6.1%
2
 
6.1%
2
 
6.1%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
1
 
3.0%
Other values (20) 20
60.6%
Punctuation
ValueCountFrequency (%)
2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct2459
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2023-12-12T08:35:24.586507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length8.0754443
Min length3

Characters and Unicode

Total characters22264
Distinct characters501
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2272 ?
Unique (%)82.4%

Sample

1st row제주학회
2nd row대한산업경영학회
3rd row한국기독교철학회
4th row대한소아소화기영양학회
5th row대한스포츠물리치료학회
ValueCountFrequency (%)
사단법인 34
 
1.2%
법학연구소 31
 
1.1%
인문과학연구소 12
 
0.4%
인문학연구원 8
 
0.3%
사회과학연구원 7
 
0.2%
인문학연구소 7
 
0.2%
법학연구원 7
 
0.2%
사회과학연구소 6
 
0.2%
교육연구소 6
 
0.2%
한국 6
 
0.2%
Other values (2525) 2784
95.7%
2023-12-12T08:35:25.128120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2380
 
10.7%
2219
 
10.0%
1924
 
8.6%
1697
 
7.6%
681
 
3.1%
669
 
3.0%
438
 
2.0%
423
 
1.9%
393
 
1.8%
382
 
1.7%
Other values (491) 11058
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21765
97.8%
Space Separator 162
 
0.7%
Uppercase Letter 87
 
0.4%
Other Punctuation 60
 
0.3%
Close Punctuation 54
 
0.2%
Open Punctuation 52
 
0.2%
Lowercase Letter 50
 
0.2%
Decimal Number 30
 
0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2380
 
10.9%
2219
 
10.2%
1924
 
8.8%
1697
 
7.8%
681
 
3.1%
669
 
3.1%
438
 
2.0%
423
 
1.9%
393
 
1.8%
382
 
1.8%
Other values (438) 10559
48.5%
Uppercase Letter
ValueCountFrequency (%)
I 11
12.6%
A 9
10.3%
E 8
 
9.2%
T 7
 
8.0%
P 6
 
6.9%
S 6
 
6.9%
H 5
 
5.7%
K 5
 
5.7%
C 5
 
5.7%
R 4
 
4.6%
Other values (8) 21
24.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
16.0%
n 7
14.0%
s 7
14.0%
i 4
8.0%
t 4
8.0%
a 4
8.0%
u 4
8.0%
m 3
 
6.0%
c 2
 
4.0%
g 2
 
4.0%
Other values (5) 5
10.0%
Other Punctuation
ValueCountFrequency (%)
· 30
50.0%
. 12
 
20.0%
8
 
13.3%
, 3
 
5.0%
& 3
 
5.0%
/ 2
 
3.3%
; 1
 
1.7%
# 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 9
30.0%
2 5
16.7%
8 4
13.3%
9 4
13.3%
3 3
 
10.0%
6 2
 
6.7%
5 2
 
6.7%
0 1
 
3.3%
Space Separator
ValueCountFrequency (%)
162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21765
97.8%
Common 362
 
1.6%
Latin 137
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2380
 
10.9%
2219
 
10.2%
1924
 
8.8%
1697
 
7.8%
681
 
3.1%
669
 
3.1%
438
 
2.0%
423
 
1.9%
393
 
1.8%
382
 
1.8%
Other values (438) 10559
48.5%
Latin
ValueCountFrequency (%)
I 11
 
8.0%
A 9
 
6.6%
e 8
 
5.8%
E 8
 
5.8%
n 7
 
5.1%
s 7
 
5.1%
T 7
 
5.1%
P 6
 
4.4%
S 6
 
4.4%
H 5
 
3.6%
Other values (23) 63
46.0%
Common
ValueCountFrequency (%)
162
44.8%
) 54
 
14.9%
( 52
 
14.4%
· 30
 
8.3%
. 12
 
3.3%
1 9
 
2.5%
8
 
2.2%
2 5
 
1.4%
8 4
 
1.1%
- 4
 
1.1%
Other values (10) 22
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21761
97.7%
ASCII 461
 
2.1%
None 38
 
0.2%
Compat Jamo 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2380
 
10.9%
2219
 
10.2%
1924
 
8.8%
1697
 
7.8%
681
 
3.1%
669
 
3.1%
438
 
2.0%
423
 
1.9%
393
 
1.8%
382
 
1.8%
Other values (437) 10555
48.5%
ASCII
ValueCountFrequency (%)
162
35.1%
) 54
 
11.7%
( 52
 
11.3%
. 12
 
2.6%
I 11
 
2.4%
A 9
 
2.0%
1 9
 
2.0%
e 8
 
1.7%
E 8
 
1.7%
n 7
 
1.5%
Other values (41) 129
28.0%
None
ValueCountFrequency (%)
· 30
78.9%
8
 
21.1%
Compat Jamo
ValueCountFrequency (%)
4
100.0%

발행기관 영문
Text

MISSING 

Distinct2312
Distinct (%)92.9%
Missing268
Missing (%)9.7%
Memory size21.7 KiB
2023-12-12T08:35:25.488276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length72
Mean length41.347529
Min length2

Characters and Unicode

Total characters102914
Distinct characters76
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2160 ?
Unique (%)86.8%

Sample

1st rowSociety for Jeju Studies
2nd rowDae Han Society of Industrial Management
3rd rowThe society of christian philosophers in Korea
4th rowThe Korean Society of Pediatric Gastroenterology, Hepatology and Nutrition
5th rowKorean Society Of Sports Physical Therapy (Ksspt)
ValueCountFrequency (%)
of 1294
 
9.2%
korean 1281
 
9.1%
the 1077
 
7.7%
society 985
 
7.0%
association 616
 
4.4%
for 577
 
4.1%
institute 541
 
3.8%
korea 453
 
3.2%
and 389
 
2.8%
studies 287
 
2.0%
Other values (1747) 6561
46.7%
2023-12-12T08:35:26.013262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11753
 
11.4%
e 9498
 
9.2%
o 8525
 
8.3%
i 7475
 
7.3%
n 6803
 
6.6%
a 6751
 
6.6%
t 6735
 
6.5%
r 5234
 
5.1%
s 4417
 
4.3%
c 4258
 
4.1%
Other values (66) 31465
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76287
74.1%
Uppercase Letter 14298
 
13.9%
Space Separator 11753
 
11.4%
Other Punctuation 309
 
0.3%
Dash Punctuation 105
 
0.1%
Close Punctuation 69
 
0.1%
Open Punctuation 69
 
0.1%
Decimal Number 11
 
< 0.1%
Other Letter 6
 
< 0.1%
Currency Symbol 4
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 9498
12.5%
o 8525
11.2%
i 7475
9.8%
n 6803
8.9%
a 6751
8.8%
t 6735
8.8%
r 5234
 
6.9%
s 4417
 
5.8%
c 4258
 
5.6%
u 2483
 
3.3%
Other values (16) 14108
18.5%
Uppercase Letter
ValueCountFrequency (%)
S 2008
14.0%
K 1870
13.1%
T 1469
10.3%
A 1458
10.2%
I 1007
 
7.0%
E 865
 
6.0%
C 790
 
5.5%
O 756
 
5.3%
R 509
 
3.6%
L 461
 
3.2%
Other values (16) 3105
21.7%
Other Punctuation
ValueCountFrequency (%)
& 141
45.6%
, 103
33.3%
. 19
 
6.1%
' 19
 
6.1%
: 12
 
3.9%
/ 8
 
2.6%
¡ 4
 
1.3%
2
 
0.6%
; 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 5
45.5%
2 4
36.4%
0 1
 
9.1%
8 1
 
9.1%
Other Letter
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
1
16.7%
Space Separator
ValueCountFrequency (%)
11753
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 69
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 4
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 90585
88.0%
Common 12323
 
12.0%
Hangul 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 9498
 
10.5%
o 8525
 
9.4%
i 7475
 
8.3%
n 6803
 
7.5%
a 6751
 
7.5%
t 6735
 
7.4%
r 5234
 
5.8%
s 4417
 
4.9%
c 4258
 
4.7%
u 2483
 
2.7%
Other values (42) 28406
31.4%
Common
ValueCountFrequency (%)
11753
95.4%
& 141
 
1.1%
- 105
 
0.9%
, 103
 
0.8%
) 69
 
0.6%
( 69
 
0.6%
. 19
 
0.2%
' 19
 
0.2%
: 12
 
0.1%
/ 8
 
0.1%
Other values (10) 25
 
0.2%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102896
> 99.9%
None 10
 
< 0.1%
Hangul 6
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11753
 
11.4%
e 9498
 
9.2%
o 8525
 
8.3%
i 7475
 
7.3%
n 6803
 
6.6%
a 6751
 
6.6%
t 6735
 
6.5%
r 5234
 
5.1%
s 4417
 
4.3%
c 4258
 
4.1%
Other values (58) 31447
30.6%
None
ValueCountFrequency (%)
¤ 4
40.0%
¡ 4
40.0%
2
20.0%
Hangul
ValueCountFrequency (%)
2
33.3%
2
33.3%
1
16.7%
1
16.7%
Punctuation
ValueCountFrequency (%)
2
100.0%

대분류
Categorical

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
사회과학
998 
인문학
632 
의약학
347 
공학
261 
예술체육학
164 
Other values (3)
355 

Length

Max length5
Median length4
Mean length3.4943779
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사회과학
2nd row복합학
3rd row인문학
4th row의약학
5th row의약학

Common Values

ValueCountFrequency (%)
사회과학 998
36.2%
인문학 632
22.9%
의약학 347
 
12.6%
공학 261
 
9.5%
예술체육학 164
 
5.9%
복합학 142
 
5.2%
자연과학 128
 
4.6%
농수해양학 85
 
3.1%

Length

2023-12-12T08:35:26.156755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:26.293729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사회과학 998
36.2%
인문학 632
22.9%
의약학 347
 
12.6%
공학 261
 
9.5%
예술체육학 164
 
5.9%
복합학 142
 
5.2%
자연과학 128
 
4.6%
농수해양학 85
 
3.1%
Distinct150
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2023-12-12T08:35:26.612768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.8879217
Min length2

Characters and Unicode

Total characters10719
Distinct characters151
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.4%

Sample

1st row지역학
2nd row학제간연구
3rd row철학
4th row소아과학
5th row물리치료학
ValueCountFrequency (%)
교육학 193
 
7.0%
법학 162
 
5.9%
역사학 122
 
4.4%
기타인문학 113
 
4.1%
경영학 97
 
3.5%
한국어와문학 97
 
3.5%
학제간연구 83
 
3.0%
사회과학일반 73
 
2.6%
경제학 66
 
2.4%
지역학 56
 
2.0%
Other values (140) 1695
61.5%
2023-12-12T08:35:27.027755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2631
24.5%
392
 
3.7%
361
 
3.4%
320
 
3.0%
296
 
2.8%
290
 
2.7%
244
 
2.3%
240
 
2.2%
239
 
2.2%
228
 
2.1%
Other values (141) 5478
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10656
99.4%
Other Punctuation 63
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2631
24.7%
392
 
3.7%
361
 
3.4%
320
 
3.0%
296
 
2.8%
290
 
2.7%
244
 
2.3%
240
 
2.3%
239
 
2.2%
228
 
2.1%
Other values (140) 5415
50.8%
Other Punctuation
ValueCountFrequency (%)
/ 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10656
99.4%
Common 63
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2631
24.7%
392
 
3.7%
361
 
3.4%
320
 
3.0%
296
 
2.8%
290
 
2.7%
244
 
2.3%
240
 
2.3%
239
 
2.2%
228
 
2.1%
Other values (140) 5415
50.8%
Common
ValueCountFrequency (%)
/ 63
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10656
99.4%
ASCII 63
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2631
24.7%
392
 
3.7%
361
 
3.4%
320
 
3.0%
296
 
2.8%
290
 
2.7%
244
 
2.3%
240
 
2.3%
239
 
2.2%
228
 
2.1%
Other values (140) 5415
50.8%
ASCII
ValueCountFrequency (%)
/ 63
100.0%

등재정보
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
등재
2454 
등재후보
 
225
우수등재
 
68
미등재
 
5
탈락
 
4

Length

Max length11
Median length2
Mean length2.2176279
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row등재
2nd row등재
3rd row등재후보
4th row등재
5th row등재

Common Values

ValueCountFrequency (%)
등재 2454
89.0%
등재후보 225
 
8.2%
우수등재 68
 
2.5%
미등재 5
 
0.2%
탈락 4
 
0.1%
구)KCI등재(통합) 1
 
< 0.1%

Length

2023-12-12T08:35:27.194570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:35:27.338251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등재 2454
89.0%
등재후보 225
 
8.2%
우수등재 68
 
2.5%
미등재 5
 
0.2%
탈락 4
 
0.1%
구)kci등재(통합 1
 
< 0.1%
Distinct112
Distinct (%)82.4%
Missing2621
Missing (%)95.1%
Infinite0
Infinite (%)0.0%
Mean2.5750735
Minimum0.24
Maximum10.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:27.544668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.24
5-th percentile0.495
Q11.4775
median2.385
Q33.1375
95-th percentile5.7225
Maximum10.72
Range10.48
Interquartile range (IQR)1.66

Descriptive statistics

Standard deviation1.6323171
Coefficient of variation (CV)0.63389147
Kurtosis5.2537698
Mean2.5750735
Median Absolute Deviation (MAD)0.865
Skewness1.7093487
Sum350.21
Variance2.6644593
MonotonicityNot monotonic
2023-12-12T08:35:27.725543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.01 4
 
0.1%
2.69 3
 
0.1%
2.76 2
 
0.1%
2.38 2
 
0.1%
2.03 2
 
0.1%
1.55 2
 
0.1%
1.49 2
 
0.1%
4.0 2
 
0.1%
2.31 2
 
0.1%
2.53 2
 
0.1%
Other values (102) 113
 
4.1%
(Missing) 2621
95.1%
ValueCountFrequency (%)
0.24 1
< 0.1%
0.28 1
< 0.1%
0.42 1
< 0.1%
0.46 1
< 0.1%
0.47 2
0.1%
0.48 1
< 0.1%
0.5 1
< 0.1%
0.55 1
< 0.1%
0.56 1
< 0.1%
0.59 1
< 0.1%
ValueCountFrequency (%)
10.72 1
< 0.1%
8.99 1
< 0.1%
6.57 1
< 0.1%
6.15 1
< 0.1%
6.11 1
< 0.1%
6.01 1
< 0.1%
5.76 1
< 0.1%
5.71 1
< 0.1%
5.34 1
< 0.1%
5.23 1
< 0.1%

한국학술지인용색인 영향력지수 (2년)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct307
Distinct (%)11.5%
Missing95
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean0.84429752
Minimum0
Maximum7.73
Zeros19
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:27.921075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.35
median0.68
Q31.1375
95-th percentile2.17
Maximum7.73
Range7.73
Interquartile range (IQR)0.7875

Descriptive statistics

Standard deviation0.69686425
Coefficient of variation (CV)0.82537758
Kurtosis7.2485789
Mean0.84429752
Median Absolute Deviation (MAD)0.38
Skewness1.9293943
Sum2247.52
Variance0.48561978
MonotonicityNot monotonic
2023-12-12T08:35:28.128843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.25 36
 
1.3%
0.13 33
 
1.2%
0.42 32
 
1.2%
0.53 31
 
1.1%
0.5 29
 
1.1%
0.22 27
 
1.0%
0.56 27
 
1.0%
0.29 26
 
0.9%
0.88 25
 
0.9%
0.31 25
 
0.9%
Other values (297) 2371
86.0%
(Missing) 95
 
3.4%
ValueCountFrequency (%)
0.0 19
0.7%
0.01 1
 
< 0.1%
0.02 8
0.3%
0.03 9
0.3%
0.04 12
0.4%
0.05 18
0.7%
0.06 18
0.7%
0.07 12
0.4%
0.08 14
0.5%
0.09 13
0.5%
ValueCountFrequency (%)
7.73 1
< 0.1%
5.34 1
< 0.1%
5.09 1
< 0.1%
5.05 1
< 0.1%
4.65 1
< 0.1%
4.34 1
< 0.1%
4.17 1
< 0.1%
4.11 1
< 0.1%
3.94 1
< 0.1%
3.92 2
0.1%

자기인용제외 IF (2년)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1712
Distinct (%)64.3%
Missing95
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean0.69652769
Minimum0
Maximum7.169
Zeros48
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:28.321423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.039115
Q10.2162
median0.5313
Q30.97805
95-th percentile1.945325
Maximum7.169
Range7.169
Interquartile range (IQR)0.76185

Descriptive statistics

Standard deviation0.65488634
Coefficient of variation (CV)0.9402158
Kurtosis7.7506178
Mean0.69652769
Median Absolute Deviation (MAD)0.3548
Skewness2.0303827
Sum1854.1567
Variance0.42887612
MonotonicityNot monotonic
2023-12-12T08:35:28.503140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 48
 
1.7%
1.0 20
 
0.7%
0.5 19
 
0.7%
0.75 19
 
0.7%
0.4 14
 
0.5%
0.3333 13
 
0.5%
0.125 11
 
0.4%
0.2857 11
 
0.4%
0.25 10
 
0.4%
0.1429 10
 
0.4%
Other values (1702) 2487
90.2%
(Missing) 95
 
3.4%
ValueCountFrequency (%)
0.0 48
1.7%
0.0082 1
 
< 0.1%
0.0086 1
 
< 0.1%
0.0093 1
 
< 0.1%
0.0104 1
 
< 0.1%
0.0112 1
 
< 0.1%
0.0118 1
 
< 0.1%
0.0123 2
 
0.1%
0.0127 1
 
< 0.1%
0.0133 1
 
< 0.1%
ValueCountFrequency (%)
7.169 1
< 0.1%
5.1379 1
< 0.1%
5.0 1
< 0.1%
4.4667 1
< 0.1%
4.2577 1
< 0.1%
4.0851 1
< 0.1%
3.9286 1
< 0.1%
3.8442 1
< 0.1%
3.8333 1
< 0.1%
3.7234 1
< 0.1%

중심성 지수(3년)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1446
Distinct (%)53.6%
Missing58
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean1.0045009
Minimum0
Maximum7.693
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:28.705446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.276
Q10.5015
median0.848
Q31.3115
95-th percentile2.2733
Maximum7.693
Range7.693
Interquartile range (IQR)0.81

Descriptive statistics

Standard deviation0.67912495
Coefficient of variation (CV)0.67608195
Kurtosis8.6298228
Mean1.0045009
Median Absolute Deviation (MAD)0.383
Skewness2.00474
Sum2711.148
Variance0.4612107
MonotonicityNot monotonic
2023-12-12T08:35:28.886286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.499 9
 
0.3%
0.536 8
 
0.3%
0.803 7
 
0.3%
0.456 7
 
0.3%
0.312 6
 
0.2%
0.491 6
 
0.2%
0.742 6
 
0.2%
0.973 6
 
0.2%
0.447 6
 
0.2%
0.396 6
 
0.2%
Other values (1436) 2632
95.5%
(Missing) 58
 
2.1%
ValueCountFrequency (%)
0.0 1
< 0.1%
0.165 1
< 0.1%
0.167 1
< 0.1%
0.168 1
< 0.1%
0.171 1
< 0.1%
0.174 1
< 0.1%
0.176 1
< 0.1%
0.178 1
< 0.1%
0.181 1
< 0.1%
0.184 2
0.1%
ValueCountFrequency (%)
7.693 1
< 0.1%
7.002 1
< 0.1%
5.202 1
< 0.1%
5.172 1
< 0.1%
4.649 1
< 0.1%
4.527 1
< 0.1%
4.248 1
< 0.1%
4.221 1
< 0.1%
4.172 1
< 0.1%
4.021 1
< 0.1%

즉시성지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct115
Distinct (%)4.2%
Missing6
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.23040712
Minimum0
Maximum3.6
Zeros366
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:29.083019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.07
median0.17
Q30.33
95-th percentile0.66
Maximum3.6
Range3.6
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.23093151
Coefficient of variation (CV)1.0022759
Kurtosis20.342131
Mean0.23040712
Median Absolute Deviation (MAD)0.12
Skewness2.6880849
Sum633.85
Variance0.053329361
MonotonicityNot monotonic
2023-12-12T08:35:29.302367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 366
 
13.3%
0.1 88
 
3.2%
0.06 82
 
3.0%
0.08 79
 
2.9%
0.07 72
 
2.6%
0.18 71
 
2.6%
0.17 70
 
2.5%
0.14 70
 
2.5%
0.09 69
 
2.5%
0.13 69
 
2.5%
Other values (105) 1715
62.2%
ValueCountFrequency (%)
0.0 366
13.3%
0.01 8
 
0.3%
0.02 33
 
1.2%
0.03 53
 
1.9%
0.04 52
 
1.9%
0.05 67
 
2.4%
0.06 82
 
3.0%
0.07 72
 
2.6%
0.08 79
 
2.9%
0.09 69
 
2.5%
ValueCountFrequency (%)
3.6 1
< 0.1%
1.91 1
< 0.1%
1.75 1
< 0.1%
1.69 1
< 0.1%
1.39 1
< 0.1%
1.37 1
< 0.1%
1.33 1
< 0.1%
1.32 1
< 0.1%
1.26 2
0.1%
1.21 1
< 0.1%

자기인용 비율(2년)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1028
Distinct (%)38.6%
Missing95
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean24.375571
Minimum0
Maximum100
Zeros235
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:29.472606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.5125
median16.345
Q336.36
95-th percentile73.0745
Maximum100
Range100
Interquartile range (IQR)29.8475

Descriptive statistics

Standard deviation23.713849
Coefficient of variation (CV)0.97285306
Kurtosis1.0771835
Mean24.375571
Median Absolute Deviation (MAD)12.035
Skewness1.2818658
Sum64887.77
Variance562.34663
MonotonicityNot monotonic
2023-12-12T08:35:29.614208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 235
 
8.5%
50.0 56
 
2.0%
33.33 49
 
1.8%
100.0 48
 
1.7%
25.0 39
 
1.4%
16.67 37
 
1.3%
66.67 32
 
1.2%
14.29 28
 
1.0%
11.11 27
 
1.0%
20.0 26
 
0.9%
Other values (1018) 2085
75.6%
(Missing) 95
 
3.4%
ValueCountFrequency (%)
0.0 235
8.5%
0.36 1
 
< 0.1%
0.9 1
 
< 0.1%
0.91 1
 
< 0.1%
1.0 1
 
< 0.1%
1.04 1
 
< 0.1%
1.06 1
 
< 0.1%
1.08 1
 
< 0.1%
1.18 2
 
0.1%
1.25 1
 
< 0.1%
ValueCountFrequency (%)
100.0 48
1.7%
98.96 1
 
< 0.1%
98.67 1
 
< 0.1%
96.0 2
 
0.1%
94.48 1
 
< 0.1%
94.12 1
 
< 0.1%
93.78 1
 
< 0.1%
93.6 1
 
< 0.1%
93.48 1
 
< 0.1%
92.86 1
 
< 0.1%

논문수(2년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct187
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.607907
Minimum0
Maximum1472
Zeros93
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:29.749083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q116
median27
Q344
95-th percentile99
Maximum1472
Range1472
Interquartile range (IQR)28

Descriptive statistics

Standard deviation54.163895
Coefficient of variation (CV)1.4029223
Kurtosis227.3337
Mean38.607907
Median Absolute Deviation (MAD)13
Skewness11.321289
Sum106442
Variance2933.7276
MonotonicityNot monotonic
2023-12-12T08:35:29.891726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 93
 
3.4%
20 78
 
2.8%
15 73
 
2.6%
18 70
 
2.5%
14 68
 
2.5%
19 68
 
2.5%
16 66
 
2.4%
12 65
 
2.4%
21 65
 
2.4%
25 63
 
2.3%
Other values (177) 2048
74.3%
ValueCountFrequency (%)
0 93
3.4%
3 1
 
< 0.1%
4 5
 
0.2%
5 11
 
0.4%
6 29
 
1.1%
7 26
 
0.9%
8 48
1.7%
9 47
1.7%
10 55
2.0%
11 59
2.1%
ValueCountFrequency (%)
1472 1
< 0.1%
952 1
< 0.1%
719 1
< 0.1%
577 1
< 0.1%
504 1
< 0.1%
466 1
< 0.1%
440 1
< 0.1%
403 1
< 0.1%
374 1
< 0.1%
349 1
< 0.1%

피인용횟수(2년)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct184
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.807037
Minimum0
Maximum2813
Zeros158
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:30.053807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median18
Q336
95-th percentile96
Maximum2813
Range2813
Interquartile range (IQR)29

Descriptive statistics

Standard deviation77.197815
Coefficient of variation (CV)2.4270672
Kurtosis660.3126
Mean31.807037
Median Absolute Deviation (MAD)13
Skewness20.91635
Sum87692
Variance5959.5027
MonotonicityNot monotonic
2023-12-12T08:35:30.198506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 158
 
5.7%
1 93
 
3.4%
8 88
 
3.2%
6 85
 
3.1%
9 83
 
3.0%
2 81
 
2.9%
3 80
 
2.9%
12 80
 
2.9%
7 77
 
2.8%
4 74
 
2.7%
Other values (174) 1858
67.4%
ValueCountFrequency (%)
0 158
5.7%
1 93
3.4%
2 81
2.9%
3 80
2.9%
4 74
2.7%
5 67
2.4%
6 85
3.1%
7 77
2.8%
8 88
3.2%
9 83
3.0%
ValueCountFrequency (%)
2813 1
< 0.1%
1356 1
< 0.1%
1086 1
< 0.1%
701 1
< 0.1%
583 1
< 0.1%
537 1
< 0.1%
489 1
< 0.1%
445 1
< 0.1%
427 1
< 0.1%
426 1
< 0.1%

웹오브사이언스 피인용횟수(2년)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct115
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.554226
Minimum0
Maximum2652
Zeros2621
Zeros (%)95.1%
Negative0
Negative (%)0.0%
Memory size24.4 KiB
2023-12-12T08:35:30.342072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2652
Range2652
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87.381637
Coefficient of variation (CV)6.9603367
Kurtosis352.29952
Mean12.554226
Median Absolute Deviation (MAD)0
Skewness15.068608
Sum34612
Variance7635.5505
MonotonicityNot monotonic
2023-12-12T08:35:30.470034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2621
95.1%
136 3
 
0.1%
228 3
 
0.1%
122 2
 
0.1%
130 2
 
0.1%
76 2
 
0.1%
165 2
 
0.1%
370 2
 
0.1%
97 2
 
0.1%
318 2
 
0.1%
Other values (105) 116
 
4.2%
ValueCountFrequency (%)
0 2621
95.1%
1 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
11 2
 
0.1%
13 1
 
< 0.1%
14 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
2652 1
< 0.1%
1467 1
< 0.1%
855 1
< 0.1%
831 1
< 0.1%
814 1
< 0.1%
804 1
< 0.1%
784 1
< 0.1%
737 1
< 0.1%
734 1
< 0.1%
639 1
< 0.1%

Interactions

2023-12-12T08:35:19.958393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:11.941702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.846268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.815030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.774644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.688701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.036425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.103846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.141236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.045617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.041483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.935952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.907847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.879835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.785972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.134829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.204682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.242556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.150483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.141691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.063118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.017233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.004312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.899389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.265151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.336742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.338414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.246179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.255682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.175120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.120917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.102699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.309798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.371193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.446417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.430656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.345251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.368767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.287376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.221544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.209875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.428047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.483801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.551815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.520965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.458528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.460495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.402495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.324088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.307943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.563578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.640204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.683956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.612102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.550038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.550300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.504958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.418566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.403074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.667824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.764382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.790096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.686466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.660646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.633295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.605983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.522278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.500430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.788942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.892613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:18.928801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.772658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:20.737365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:12.743980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:13.709626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:14.651565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:15.599922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:16.904465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:17.997676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.033862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:35:19.860454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:35:30.871650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류등재정보한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)한국학술지인용색인 영향력지수 (2년)자기인용제외 IF (2년)중심성 지수(3년)즉시성지수자기인용 비율(2년)논문수(2년)피인용횟수(2년)웹오브사이언스 피인용횟수(2년)
대분류1.0000.1240.3180.5000.3710.5360.2330.3970.1700.0800.170
등재정보0.1241.0000.0000.0890.0880.0910.0780.1060.0000.0000.000
한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)0.3180.0001.0000.3910.0000.5140.1190.1910.1580.0000.555
한국학술지인용색인 영향력지수 (2년)0.5000.0890.3911.0000.9550.9350.4230.2760.0000.2350.000
자기인용제외 IF (2년)0.3710.0880.0000.9551.0000.8570.4040.3590.0000.2800.000
중심성 지수(3년)0.5360.0910.5140.9350.8571.0000.5120.3950.0200.1890.064
즉시성지수0.2330.0780.1190.4230.4040.5121.0000.1350.0000.0920.000
자기인용 비율(2년)0.3970.1060.1910.2760.3590.3950.1351.0000.1770.0000.260
논문수(2년)0.1700.0000.1580.0000.0000.0200.0000.1771.0000.9090.596
피인용횟수(2년)0.0800.0000.0000.2350.2800.1890.0920.0000.9091.0000.081
웹오브사이언스 피인용횟수(2년)0.1700.0000.5550.0000.0000.0640.0000.2600.5960.0811.000
2023-12-12T08:35:31.007753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류등재정보
대분류1.0000.069
등재정보0.0691.000
2023-12-12T08:35:31.098249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)한국학술지인용색인 영향력지수 (2년)자기인용제외 IF (2년)중심성 지수(3년)즉시성지수자기인용 비율(2년)논문수(2년)피인용횟수(2년)웹오브사이언스 피인용횟수(2년)대분류등재정보
한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)1.0000.5290.2730.2350.4310.2470.1220.4160.6790.1710.000
한국학술지인용색인 영향력지수 (2년)0.5291.0000.9530.8930.669-0.366-0.0210.709-0.1940.1870.049
자기인용제외 IF (2년)0.2730.9531.0000.9290.625-0.570-0.0810.640-0.2570.1920.044
중심성 지수(3년)0.2350.8930.9291.0000.572-0.508-0.2150.488-0.2590.2040.050
즉시성지수0.4310.6690.6250.5721.000-0.2030.1410.548-0.1260.1240.045
자기인용 비율(2년)0.247-0.366-0.570-0.508-0.2031.0000.267-0.1090.2540.2010.059
논문수(2년)0.122-0.021-0.081-0.2150.1410.2671.0000.6410.2590.0910.000
피인용횟수(2년)0.4160.7090.6400.4880.548-0.1090.6411.0000.0710.0440.000
웹오브사이언스 피인용횟수(2년)0.679-0.194-0.257-0.259-0.1260.2540.2590.0711.0000.0950.000
대분류0.1710.1870.1920.2040.1240.2010.0910.0440.0951.0000.069
등재정보0.0000.0490.0440.0500.0450.0590.0000.0000.0000.0691.000

Missing values

2023-12-12T08:35:20.864682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:35:21.060277image/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.
2023-12-12T08:35:21.235013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

국제표준연속 간행물 번호학술지명 국문학술지명 외국어발행기관발행기관 영문대분류중분류등재정보한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)한국학술지인용색인 영향력지수 (2년)자기인용제외 IF (2년)중심성 지수(3년)즉시성지수자기인용 비율(2년)논문수(2년)피인용횟수(2년)웹오브사이언스 피인용횟수(2년)
012297569제주도연구Journal of Jeju Studies제주학회Society for Jeju Studies사회과학지역학등재<NA>0.580.48840.7380.3316.01870
126358875산업융합연구Journal of Industrial Convergence대한산업경영학회Dae Han Society of Industrial Management복합학학제간연구등재<NA>1.080.9560.9510.2611.2284780
220051298기독교철학Journal of Christian Philosophy한국기독교철학회The society of christian philosophers in Korea인문학철학등재후보<NA>0.140.09090.5170.0833.33600
322348646Pediatric Gastroenterology, Hepatology & NutritionPediatric Gastroenterology, Hepatology & Nutrition대한소아소화기영양학회The Korean Society of Pediatric Gastroenterology, Hepatology and Nutrition의약학소아과학등재<NA>0.140.11110.4580.0418.7557100
425088262정형스포츠물리치료학회지Archives of Orthopedic and Sports Physical Therapy대한스포츠물리치료학회Korean Society Of Sports Physical Therapy (Ksspt)의약학물리치료학등재<NA>0.240.21050.4090.011.112170
515980960한국지방자치연구KOREAN LOCAL GOVERNMENT REVIEW대한지방자치학회National Association of Korean Local Government Studies사회과학행정학등재<NA>1.461.10711.2320.2124.3925340
617383188대중서사연구Journal of Popular Narrative대중서사학회The Association of Popular Narrative복합학학제간연구등재<NA>0.870.85451.5970.262.0832310
717387132규제연구Journal of Regulation Studies한국규제학회<NA>사회과학행정학등재<NA>2.092.04552.0290.092.1710350
812290939신라문화<NA>신라문화연구소The Research Institute for Silla Culture of Dongguk University인문학역사학등재<NA>1.321.23732.760.276.4127220
912251682대한골절학회지Journal of the Korean Fracture Society대한골절학회The Korean Fracture Society의약학정형외과학등재<NA>0.070.00.2440.0100.03530
국제표준연속 간행물 번호학술지명 국문학술지명 외국어발행기관발행기관 영문대분류중분류등재정보한국학술지인용색인의 웹오브사이언스 통합 영향력지수 (2년)한국학술지인용색인 영향력지수 (2년)자기인용제외 IF (2년)중심성 지수(3년)즉시성지수자기인용 비율(2년)논문수(2년)피인용횟수(2년)웹오브사이언스 피인용횟수(2년)
27472800020X융합영어영문학Convergence Studies in English Language & Literature융합영어영문학회Convergence English Language and Literature Association인문학영어와문학등재후보<NA><NA><NA>0.5030.06<NA>000
274823840803유통법연구Distribution Law Review한국유통법학회Korea Distribution Law Association사회과학법학등재<NA>2.862.66671.820.276.6711290
27492799970X중한연구학간Journal of Chinese and Korean Studies중한연구학회Chinese and Korean Studies Association인문학중국어와문학등재후보<NA><NA><NA><NA>0.0<NA>000
275012260959한국연소학회지Journal of The Korean Society of Combustion한국연소학회The Korean Society Of Combustion공학기계공학등재<NA>0.450.22450.6050.1850.024120
275120926553한국교수불자연합학회지Journal of Buddhist Professors in Korea사단법인한국교수불자연합회kbpa인문학불교학등재<NA>0.320.28570.5360.0511.1134100
275217384087한국환경보건학회지JOURNAL OF ENVIRONMENTAL HEALTH SCIENCES한국환경보건학회Korean Society of Environmental Health공학환경공학우수등재<NA>0.590.36590.7490.2237.572430
275326714744국방품질연구논집(JDQS)Journal of Defense Quality Society (J. Def. Qual. Soc.)국방기술품질원Defense Agency for Technology and Quality공학산업공학등재후보<NA>0.040.02080.2520.050.02500
275412290548슬라브학보<NA>한국슬라브?유라시아학회The Korean Association of Slavic-Eurasian Studies인문학러시아어와문학등재<NA>0.440.38750.8030.3911.4339190
275526359111한국청소년활동연구<NA>한국청소년활동학회Korea Youth Activity Research Association자연과학생활과학등재<NA>2.652.2752.7370.314.1521650
275629825164Parasites, Hosts and DiseasesParasites, Hosts and Diseases대한기생충학ㆍ열대의학회The Korean Society For Parasitology and Tropical Medicine의약학예방의학/직업환경의학등재1.360.130.06020.240.0252.38898122