Overview

Dataset statistics

Number of variables16
Number of observations1776
Missing cells8329
Missing cells (%)29.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory229.1 KiB
Average record size in memory132.1 B

Variable types

Text11
Numeric1
DateTime1
Categorical3

Dataset

Description산림과학기술의 지식재산권 실적관련 논문명(국문,영문), 논문발표일, 역할, 발생처, 학술지명 등 관련 정보 제공
Author산림청
URLhttps://www.data.go.kr/data/15072378/fileData.do

Alerts

학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물) is highly overall correlated with SCI여부(1:SCI, 2:비 SCI)High correlation
SCI여부(1:SCI, 2:비 SCI) is highly overall correlated with 학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)High correlation
논문제목영문 has 371 (20.9%) missing valuesMissing
논문발표일 has 619 (34.9%) missing valuesMissing
발행처명 has 885 (49.8%) missing valuesMissing
ISSN has 1233 (69.4%) missing valuesMissing
게재권 has 908 (51.1%) missing valuesMissing
게재호 has 1157 (65.1%) missing valuesMissing
시작페이지 has 949 (53.4%) missing valuesMissing
종료페이지 has 1033 (58.2%) missing valuesMissing
공동저자명 has 1174 (66.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 23:44:07.159737
Analysis finished2023-12-12 23:44:08.896033
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인력관리번호
Text

Distinct138
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
2023-12-13T08:44:09.076941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters17760
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

Unique18 ?
Unique (%)1.0%

Sample

1st rowUR00000572
2nd rowUR00000572
3rd rowUR00000572
4th rowUR00000675
5th rowUR00000675
ValueCountFrequency (%)
ur00003956 130
 
7.3%
ur00004261 116
 
6.5%
ur00005617 74
 
4.2%
ur00002056 58
 
3.3%
ur00003127 58
 
3.3%
ur00005583 53
 
3.0%
ur00004374 49
 
2.8%
ur00004152 42
 
2.4%
ur00000071 40
 
2.3%
ur00003824 38
 
2.1%
Other values (128) 1118
63.0%
2023-12-13T08:44:09.407907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7720
43.5%
U 1776
 
10.0%
R 1776
 
10.0%
1 1009
 
5.7%
2 865
 
4.9%
3 861
 
4.8%
4 791
 
4.5%
5 783
 
4.4%
6 782
 
4.4%
7 516
 
2.9%
Other values (2) 881
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14208
80.0%
Uppercase Letter 3552
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7720
54.3%
1 1009
 
7.1%
2 865
 
6.1%
3 861
 
6.1%
4 791
 
5.6%
5 783
 
5.5%
6 782
 
5.5%
7 516
 
3.6%
9 478
 
3.4%
8 403
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
U 1776
50.0%
R 1776
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14208
80.0%
Latin 3552
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7720
54.3%
1 1009
 
7.1%
2 865
 
6.1%
3 861
 
6.1%
4 791
 
5.6%
5 783
 
5.5%
6 782
 
5.5%
7 516
 
3.6%
9 478
 
3.4%
8 403
 
2.8%
Latin
ValueCountFrequency (%)
U 1776
50.0%
R 1776
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7720
43.5%
U 1776
 
10.0%
R 1776
 
10.0%
1 1009
 
5.7%
2 865
 
4.9%
3 861
 
4.8%
4 791
 
4.5%
5 783
 
4.4%
6 782
 
4.4%
7 516
 
2.9%
Other values (2) 881
 
5.0%

순번
Real number (ℝ)

Distinct130
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.295608
Minimum1
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.7 KiB
2023-12-13T08:44:09.528937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median11
Q325
95-th percentile79
Maximum130
Range129
Interquartile range (IQR)21

Descriptive statistics

Standard deviation24.891764
Coefficient of variation (CV)1.2264606
Kurtosis4.508881
Mean20.295608
Median Absolute Deviation (MAD)8
Skewness2.134844
Sum36045
Variance619.59989
MonotonicityNot monotonic
2023-12-13T08:44:09.640914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 138
 
7.8%
2 120
 
6.8%
3 110
 
6.2%
4 101
 
5.7%
5 86
 
4.8%
6 76
 
4.3%
7 65
 
3.7%
8 60
 
3.4%
9 58
 
3.3%
10 55
 
3.1%
Other values (120) 907
51.1%
ValueCountFrequency (%)
1 138
7.8%
2 120
6.8%
3 110
6.2%
4 101
5.7%
5 86
4.8%
6 76
4.3%
7 65
3.7%
8 60
3.4%
9 58
3.3%
10 55
 
3.1%
ValueCountFrequency (%)
130 1
0.1%
129 1
0.1%
128 1
0.1%
127 1
0.1%
126 1
0.1%
125 1
0.1%
124 1
0.1%
123 1
0.1%
122 1
0.1%
121 1
0.1%

논문제목국문
Text

Distinct1736
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
2023-12-13T08:44:09.888441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length247
Median length162
Mean length85.837275
Min length4

Characters and Unicode

Total characters152447
Distinct characters745
Distinct categories17 ?
Distinct scripts7 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1704 ?
Unique (%)95.9%

Sample

1st rowThe anti-tubercular activity of Melia azedarach L. and Lobelia chinensis Lour. and their potential as effective anti-Mycobacterium tuberculosis candidate agents
2nd row산수유 물추출물이 B16/F10 melanoma세포주의 멜라닌 생성에 미치는 영향
3rd row산수유 헥산 추출물의 항균효과 및 세포독성
4th row반하사심탕에서 9가지 마커 성분의 동시정량을 위한 HPLC-PDA 분석
5th rowHaCaT cell과 RAW 264.7 cell에서 조각자의 항염증 효과 및 동시 분석
ValueCountFrequency (%)
of 1158
 
5.3%
and 698
 
3.2%
in 598
 
2.8%
the 361
 
1.7%
a 261
 
1.2%
for 206
 
1.0%
on 190
 
0.9%
by 166
 
0.8%
with 161
 
0.7%
및 149
 
0.7%
Other values (7258) 17733
81.8%
2023-12-13T08:44:10.270185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20074
 
13.2%
e 11058
 
7.3%
i 10294
 
6.8%
a 9308
 
6.1%
o 9145
 
6.0%
n 8700
 
5.7%
t 8297
 
5.4%
r 6887
 
4.5%
s 6593
 
4.3%
l 5356
 
3.5%
Other values (735) 56735
37.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 107301
70.4%
Space Separator 20074
 
13.2%
Other Letter 14125
 
9.3%
Uppercase Letter 7790
 
5.1%
Dash Punctuation 1036
 
0.7%
Decimal Number 880
 
0.6%
Other Punctuation 763
 
0.5%
Open Punctuation 151
 
0.1%
Close Punctuation 151
 
0.1%
Control 139
 
0.1%
Other values (7) 37
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 637
 
4.5%
한 365
 
2.6%
에 331
 
2.3%
성 269
 
1.9%
이 239
 
1.7%
용 191
 
1.4%
지 173
 
1.2%
분 165
 
1.2%
과 165
 
1.2%
화 162
 
1.1%
Other values (638) 11428
80.9%
Lowercase Letter
ValueCountFrequency (%)
e 11058
10.3%
i 10294
 
9.6%
a 9308
 
8.7%
o 9145
 
8.5%
n 8700
 
8.1%
t 8297
 
7.7%
r 6887
 
6.4%
s 6593
 
6.1%
l 5356
 
5.0%
c 4966
 
4.6%
Other values (22) 26697
24.9%
Uppercase Letter
ValueCountFrequency (%)
A 888
 
11.4%
P 708
 
9.1%
C 689
 
8.8%
S 625
 
8.0%
E 464
 
6.0%
T 421
 
5.4%
M 420
 
5.4%
R 412
 
5.3%
I 380
 
4.9%
D 366
 
4.7%
Other values (16) 2417
31.0%
Other Punctuation
ValueCountFrequency (%)
, 272
35.6%
. 202
26.5%
: 160
21.0%
/ 94
 
12.3%
; 13
 
1.7%
& 9
 
1.2%
· 5
 
0.7%
# 3
 
0.4%
' 2
 
0.3%
% 1
 
0.1%
Other values (2) 2
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 214
24.3%
2 196
22.3%
3 104
11.8%
4 74
 
8.4%
0 71
 
8.1%
5 67
 
7.6%
6 50
 
5.7%
7 41
 
4.7%
8 33
 
3.8%
9 30
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 148
98.0%
[ 3
 
2.0%
Close Punctuation
ValueCountFrequency (%)
) 148
98.0%
] 3
 
2.0%
Control
ValueCountFrequency (%)
138
99.3%
1
 
0.7%
Final Punctuation
ValueCountFrequency (%)
’ 11
91.7%
” 1
 
8.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 7
87.5%
“ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
20074
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1036
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 115051
75.5%
Common 23229
 
15.2%
Hangul 14042
 
9.2%
Greek 42
 
< 0.1%
Han 37
 
< 0.1%
Katakana 29
 
< 0.1%
Hiragana 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 637
 
4.5%
한 365
 
2.6%
에 331
 
2.4%
성 269
 
1.9%
이 239
 
1.7%
용 191
 
1.4%
지 173
 
1.2%
분 165
 
1.2%
과 165
 
1.2%
화 162
 
1.2%
Other values (579) 11345
80.8%
Latin
ValueCountFrequency (%)
e 11058
 
9.6%
i 10294
 
8.9%
a 9308
 
8.1%
o 9145
 
7.9%
n 8700
 
7.6%
t 8297
 
7.2%
r 6887
 
6.0%
s 6593
 
5.7%
l 5356
 
4.7%
c 4966
 
4.3%
Other values (44) 34447
29.9%
Common
ValueCountFrequency (%)
20074
86.4%
- 1036
 
4.5%
, 272
 
1.2%
1 214
 
0.9%
. 202
 
0.9%
2 196
 
0.8%
: 160
 
0.7%
( 148
 
0.6%
) 148
 
0.6%
138
 
0.6%
Other values (28) 641
 
2.8%
Han
ValueCountFrequency (%)
換 2
 
5.4%
伐 2
 
5.4%
流 2
 
5.4%
吸 2
 
5.4%
部 2
 
5.4%
口 2
 
5.4%
開 2
 
5.4%
置 2
 
5.4%
空 2
 
5.4%
及 1
 
2.7%
Other values (18) 18
48.6%
Katakana
ValueCountFrequency (%)
リ 6
20.7%
ム 2
 
6.9%
ア 2
 
6.9%
ル 2
 
6.9%
グ 2
 
6.9%
ヘ 2
 
6.9%
ウ 1
 
3.4%
ド 1
 
3.4%
ミ 1
 
3.4%
ク 1
 
3.4%
Other values (9) 9
31.0%
Hiragana
ValueCountFrequency (%)
の 3
17.6%
る 3
17.6%
お 2
11.8%
び 1
 
5.9%
を 1
 
5.9%
と 1
 
5.9%
あ 1
 
5.9%
に 1
 
5.9%
け 1
 
5.9%
う 1
 
5.9%
Other values (2) 2
11.8%
Greek
ValueCountFrequency (%)
β 15
35.7%
α 14
33.3%
κ 9
21.4%
γ 3
 
7.1%
δ 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138249
90.7%
Hangul 14040
 
9.2%
None 51
 
< 0.1%
CJK 37
 
< 0.1%
Katakana 29
 
< 0.1%
Punctuation 20
 
< 0.1%
Hiragana 17
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20074
14.5%
e 11058
 
8.0%
i 10294
 
7.4%
a 9308
 
6.7%
o 9145
 
6.6%
n 8700
 
6.3%
t 8297
 
6.0%
r 6887
 
5.0%
s 6593
 
4.8%
l 5356
 
3.9%
Other values (72) 42537
30.8%
Hangul
ValueCountFrequency (%)
의 637
 
4.5%
한 365
 
2.6%
에 331
 
2.4%
성 269
 
1.9%
이 239
 
1.7%
용 191
 
1.4%
지 173
 
1.2%
분 165
 
1.2%
과 165
 
1.2%
화 162
 
1.2%
Other values (578) 11343
80.8%
None
ValueCountFrequency (%)
β 15
29.4%
α 14
27.5%
κ 9
17.6%
· 5
 
9.8%
γ 3
 
5.9%
． 1
 
2.0%
ß 1
 
2.0%
­ 1
 
2.0%
® 1
 
2.0%
δ 1
 
2.0%
Punctuation
ValueCountFrequency (%)
’ 11
55.0%
‘ 7
35.0%
“ 1
 
5.0%
” 1
 
5.0%
Katakana
ValueCountFrequency (%)
リ 6
20.7%
ム 2
 
6.9%
ア 2
 
6.9%
ル 2
 
6.9%
グ 2
 
6.9%
ヘ 2
 
6.9%
ウ 1
 
3.4%
ド 1
 
3.4%
ミ 1
 
3.4%
ク 1
 
3.4%
Other values (9) 9
31.0%
Hiragana
ValueCountFrequency (%)
の 3
17.6%
る 3
17.6%
お 2
11.8%
び 1
 
5.9%
を 1
 
5.9%
と 1
 
5.9%
あ 1
 
5.9%
に 1
 
5.9%
け 1
 
5.9%
う 1
 
5.9%
Other values (2) 2
11.8%
CJK
ValueCountFrequency (%)
換 2
 
5.4%
伐 2
 
5.4%
流 2
 
5.4%
吸 2
 
5.4%
部 2
 
5.4%
口 2
 
5.4%
開 2
 
5.4%
置 2
 
5.4%
空 2
 
5.4%
及 1
 
2.7%
Other values (18) 18
48.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

논문제목영문
Text

MISSING 

Distinct1383
Distinct (%)98.4%
Missing371
Missing (%)20.9%
Memory size14.0 KiB
2023-12-13T08:44:10.510846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length247
Median length171
Mean length109.52384
Min length4

Characters and Unicode

Total characters153881
Distinct characters240
Distinct categories17 ?
Distinct scripts7 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1365 ?
Unique (%)97.2%

Sample

1st rowThe anti-tubercular activity of Melia azedarach L. and Lobelia chinensis Lour. and their potential as effective anti-Mycobacterium tuberculosis candidate agents
2nd rowWater Extract from Cornis Fructus Regulates Melanogenesis in B16/F10 Melanoma
3rd rowScreening of Cytotoxicity and Antimicrobial Effects of Hexane Extracts from Cornis fructus
4th rowHPLC-PDA Method for Simultaneous Determination of Nine Marker Components in Banhasasim-Tang
5th rowQuantitative analysis and anti-inflammatory effects of Gleditsia sinensis thorns in RAW 264.7 macrophages and HaCaT keratinocytes
ValueCountFrequency (%)
of 1479
 
7.3%
and 804
 
4.0%
in 649
 
3.2%
the 527
 
2.6%
a 296
 
1.5%
on 295
 
1.5%
for 271
 
1.3%
with 197
 
1.0%
by 186
 
0.9%
from 136
 
0.7%
Other values (5286) 15332
76.0%
2023-12-13T08:44:10.878808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18918
 
12.3%
e 12826
 
8.3%
i 11619
 
7.6%
o 10634
 
6.9%
a 10508
 
6.8%
n 9907
 
6.4%
t 9611
 
6.2%
r 7935
 
5.2%
s 7562
 
4.9%
l 5924
 
3.8%
Other values (230) 48437
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 122707
79.7%
Space Separator 18918
 
12.3%
Uppercase Letter 8947
 
5.8%
Dash Punctuation 1077
 
0.7%
Decimal Number 775
 
0.5%
Other Punctuation 743
 
0.5%
Other Letter 277
 
0.2%
Close Punctuation 140
 
0.1%
Open Punctuation 140
 
0.1%
Control 120
 
0.1%
Other values (7) 37
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 9
 
3.2%
에 8
 
2.9%
기 7
 
2.5%
부 5
 
1.8%
유 5
 
1.8%
및 5
 
1.8%
치 5
 
1.8%
구 4
 
1.4%
과 4
 
1.4%
개 4
 
1.4%
Other values (134) 221
79.8%
Lowercase Letter
ValueCountFrequency (%)
e 12826
10.5%
i 11619
 
9.5%
o 10634
 
8.7%
a 10508
 
8.6%
n 9907
 
8.1%
t 9611
 
7.8%
r 7935
 
6.5%
s 7562
 
6.2%
l 5924
 
4.8%
c 5574
 
4.5%
Other values (22) 30607
24.9%
Uppercase Letter
ValueCountFrequency (%)
A 1013
 
11.3%
P 789
 
8.8%
S 777
 
8.7%
C 771
 
8.6%
E 584
 
6.5%
T 485
 
5.4%
R 482
 
5.4%
M 479
 
5.4%
D 433
 
4.8%
I 409
 
4.6%
Other values (16) 2725
30.5%
Other Punctuation
ValueCountFrequency (%)
, 239
32.2%
. 230
31.0%
: 159
21.4%
/ 89
 
12.0%
; 9
 
1.2%
' 7
 
0.9%
& 5
 
0.7%
# 3
 
0.4%
· 1
 
0.1%
@ 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 187
24.1%
2 177
22.8%
3 93
12.0%
4 74
 
9.5%
5 57
 
7.4%
0 56
 
7.2%
6 44
 
5.7%
7 36
 
4.6%
8 29
 
3.7%
9 22
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 137
97.9%
] 3
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 137
97.9%
[ 3
 
2.1%
Control
ValueCountFrequency (%)
119
99.2%
1
 
0.8%
Final Punctuation
ValueCountFrequency (%)
’ 11
91.7%
” 1
 
8.3%
Initial Punctuation
ValueCountFrequency (%)
‘ 6
85.7%
“ 1
 
14.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
18918
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1077
100.0%
Math Symbol
ValueCountFrequency (%)
+ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Other Symbol
ValueCountFrequency (%)
® 2
100.0%
Format
ValueCountFrequency (%)
­ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 131613
85.5%
Common 21948
 
14.3%
Hangul 236
 
0.2%
Greek 43
 
< 0.1%
Han 19
 
< 0.1%
Hiragana 14
 
< 0.1%
Katakana 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 9
 
3.8%
에 8
 
3.4%
기 7
 
3.0%
부 5
 
2.1%
유 5
 
2.1%
및 5
 
2.1%
치 5
 
2.1%
구 4
 
1.7%
과 4
 
1.7%
개 4
 
1.7%
Other values (108) 180
76.3%
Latin
ValueCountFrequency (%)
e 12826
 
9.7%
i 11619
 
8.8%
o 10634
 
8.1%
a 10508
 
8.0%
n 9907
 
7.5%
t 9611
 
7.3%
r 7935
 
6.0%
s 7562
 
5.7%
l 5924
 
4.5%
c 5574
 
4.2%
Other values (45) 39513
30.0%
Common
ValueCountFrequency (%)
18918
86.2%
- 1077
 
4.9%
, 239
 
1.1%
. 230
 
1.0%
1 187
 
0.9%
2 177
 
0.8%
: 159
 
0.7%
) 137
 
0.6%
( 137
 
0.6%
119
 
0.5%
Other values (26) 568
 
2.6%
Han
ValueCountFrequency (%)
流 2
10.5%
置 2
10.5%
換 2
10.5%
部 2
10.5%
空 2
10.5%
開 2
10.5%
口 2
10.5%
切 1
5.3%
化 1
5.3%
及 1
5.3%
Other values (2) 2
10.5%
Hiragana
ValueCountFrequency (%)
る 3
21.4%
の 2
14.3%
お 2
14.3%
に 1
 
7.1%
あ 1
 
7.1%
け 1
 
7.1%
う 1
 
7.1%
び 1
 
7.1%
と 1
 
7.1%
を 1
 
7.1%
Greek
ValueCountFrequency (%)
β 17
39.5%
α 14
32.6%
κ 8
18.6%
γ 3
 
7.0%
δ 1
 
2.3%
Katakana
ValueCountFrequency (%)
リ 3
37.5%
ム 2
25.0%
ヘ 2
25.0%
ウ 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153535
99.8%
Hangul 236
 
0.2%
None 48
 
< 0.1%
Punctuation 19
 
< 0.1%
CJK 19
 
< 0.1%
Hiragana 14
 
< 0.1%
Katakana 8
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18918
 
12.3%
e 12826
 
8.4%
i 11619
 
7.6%
o 10634
 
6.9%
a 10508
 
6.8%
n 9907
 
6.5%
t 9611
 
6.3%
r 7935
 
5.2%
s 7562
 
4.9%
l 5924
 
3.9%
Other values (71) 48091
31.3%
None
ValueCountFrequency (%)
β 17
35.4%
α 14
29.2%
κ 8
16.7%
γ 3
 
6.2%
® 2
 
4.2%
· 1
 
2.1%
δ 1
 
2.1%
ß 1
 
2.1%
­ 1
 
2.1%
Punctuation
ValueCountFrequency (%)
’ 11
57.9%
‘ 6
31.6%
“ 1
 
5.3%
” 1
 
5.3%
Hangul
ValueCountFrequency (%)
의 9
 
3.8%
에 8
 
3.4%
기 7
 
3.0%
부 5
 
2.1%
유 5
 
2.1%
및 5
 
2.1%
치 5
 
2.1%
구 4
 
1.7%
과 4
 
1.7%
개 4
 
1.7%
Other values (108) 180
76.3%
Katakana
ValueCountFrequency (%)
リ 3
37.5%
ム 2
25.0%
ヘ 2
25.0%
ウ 1
 
12.5%
Hiragana
ValueCountFrequency (%)
る 3
21.4%
の 2
14.3%
お 2
14.3%
に 1
 
7.1%
あ 1
 
7.1%
け 1
 
7.1%
う 1
 
7.1%
び 1
 
7.1%
と 1
 
7.1%
を 1
 
7.1%
CJK
ValueCountFrequency (%)
流 2
10.5%
置 2
10.5%
換 2
10.5%
部 2
10.5%
空 2
10.5%
開 2
10.5%
口 2
10.5%
切 1
5.3%
化 1
5.3%
及 1
5.3%
Other values (2) 2
10.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

논문발표일
Date

MISSING 

Distinct720
Distinct (%)62.2%
Missing619
Missing (%)34.9%
Memory size14.0 KiB
Minimum1987-10-20 00:00:00
Maximum2020-11-01 00:00:00
2023-12-13T08:44:11.001976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:44:11.123853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

역할구분(3:주저자, 4:교신저자)
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
3
936 
4
840 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row3
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 936
52.7%
4 840
47.3%

Length

2023-12-13T08:44:11.232949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:11.315421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 936
52.7%
4 840
47.3%

발행처명
Text

MISSING 

Distinct449
Distinct (%)50.4%
Missing885
Missing (%)49.8%
Memory size14.0 KiB
2023-12-13T08:44:11.538279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length94
Median length58
Mean length16.414141
Min length3

Characters and Unicode

Total characters14625
Distinct characters279
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

Unique332 ?
Unique (%)37.3%

Sample

1st rowHainan Medical University, Elsevier
2nd row동의생리병리학회
3rd row동의생리병리학회
4th rowAthens, Greece : D. A. Spandidos
5th rowMumbai : Medknow Publications and Media
ValueCountFrequency (%)
of 89
 
4.5%
elsevier 69
 
3.5%
한국목재공학회 66
 
3.3%
and 56
 
2.8%
journal 54
 
2.7%
springer 51
 
2.6%
mdpi 49
 
2.5%
society 49
 
2.5%
science 45
 
2.3%
44
 
2.2%
Other values (561) 1417
71.2%
2023-12-13T08:44:11.934970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1185
 
8.1%
e 736
 
5.0%
o 678
 
4.6%
i 667
 
4.6%
r 569
 
3.9%
n 562
 
3.8%
a 513
 
3.5%
E 419
 
2.9%
I 400
 
2.7%
l 387
 
2.6%
Other values (269) 8509
58.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6592
45.1%
Uppercase Letter 3873
26.5%
Other Letter 2710
18.5%
Space Separator 1185
 
8.1%
Other Punctuation 138
 
0.9%
Decimal Number 77
 
0.5%
Dash Punctuation 22
 
0.2%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Math Symbol 4
 
< 0.1%
Other values (3) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 354
 
13.1%
회 309
 
11.4%
한 281
 
10.4%
국 265
 
9.8%
공 117
 
4.3%
재 85
 
3.1%
목 74
 
2.7%
경 49
 
1.8%
대 48
 
1.8%
기 42
 
1.5%
Other values (191) 1086
40.1%
Lowercase Letter
ValueCountFrequency (%)
e 736
11.2%
o 678
10.3%
i 667
10.1%
r 569
8.6%
n 562
 
8.5%
a 513
 
7.8%
l 387
 
5.9%
c 373
 
5.7%
t 363
 
5.5%
s 339
 
5.1%
Other values (16) 1405
21.3%
Uppercase Letter
ValueCountFrequency (%)
E 419
 
10.8%
I 400
 
10.3%
S 370
 
9.6%
C 271
 
7.0%
A 229
 
5.9%
N 215
 
5.6%
P 207
 
5.3%
R 202
 
5.2%
L 201
 
5.2%
M 196
 
5.1%
Other values (16) 1163
30.0%
Decimal Number
ValueCountFrequency (%)
1 22
28.6%
0 20
26.0%
2 9
11.7%
3 9
11.7%
9 4
 
5.2%
4 4
 
5.2%
8 3
 
3.9%
5 3
 
3.9%
6 2
 
2.6%
7 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
& 40
29.0%
. 38
27.5%
, 27
19.6%
· 20
14.5%
: 8
 
5.8%
/ 3
 
2.2%
@ 2
 
1.4%
Math Symbol
ValueCountFrequency (%)
= 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Other Symbol
ValueCountFrequency (%)
™ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10465
71.6%
Hangul 2693
 
18.4%
Common 1450
 
9.9%
Han 17
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 354
 
13.1%
회 309
 
11.5%
한 281
 
10.4%
국 265
 
9.8%
공 117
 
4.3%
재 85
 
3.2%
목 74
 
2.7%
경 49
 
1.8%
대 48
 
1.8%
기 42
 
1.6%
Other values (176) 1069
39.7%
Latin
ValueCountFrequency (%)
e 736
 
7.0%
o 678
 
6.5%
i 667
 
6.4%
r 569
 
5.4%
n 562
 
5.4%
a 513
 
4.9%
E 419
 
4.0%
I 400
 
3.8%
l 387
 
3.7%
c 373
 
3.6%
Other values (42) 5161
49.3%
Common
ValueCountFrequency (%)
1185
81.7%
& 40
 
2.8%
. 38
 
2.6%
, 27
 
1.9%
1 22
 
1.5%
- 22
 
1.5%
· 20
 
1.4%
0 20
 
1.4%
( 9
 
0.6%
) 9
 
0.6%
Other values (16) 58
 
4.0%
Han
ValueCountFrequency (%)
學 2
 
11.8%
會 2
 
11.8%
山 1
 
5.9%
究 1
 
5.9%
硏 1
 
5.9%
濟 1
 
5.9%
經 1
 
5.9%
林 1
 
5.9%
誌 1
 
5.9%
劑 1
 
5.9%
Other values (5) 5
29.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11892
81.3%
Hangul 2693
 
18.4%
None 20
 
0.1%
CJK 17
 
0.1%
Punctuation 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1185
 
10.0%
e 736
 
6.2%
o 678
 
5.7%
i 667
 
5.6%
r 569
 
4.8%
n 562
 
4.7%
a 513
 
4.3%
E 419
 
3.5%
I 400
 
3.4%
l 387
 
3.3%
Other values (65) 5776
48.6%
Hangul
ValueCountFrequency (%)
학 354
 
13.1%
회 309
 
11.5%
한 281
 
10.4%
국 265
 
9.8%
공 117
 
4.3%
재 85
 
3.2%
목 74
 
2.7%
경 49
 
1.8%
대 48
 
1.8%
기 42
 
1.6%
Other values (176) 1069
39.7%
None
ValueCountFrequency (%)
· 20
100.0%
CJK
ValueCountFrequency (%)
學 2
 
11.8%
會 2
 
11.8%
山 1
 
5.9%
究 1
 
5.9%
硏 1
 
5.9%
濟 1
 
5.9%
經 1
 
5.9%
林 1
 
5.9%
誌 1
 
5.9%
劑 1
 
5.9%
Other values (5) 5
29.4%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
™ 1
100.0%

학술지명
Text

Distinct1003
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
2023-12-13T08:44:12.213495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length110
Median length63.5
Mean length22.726351
Min length3

Characters and Unicode

Total characters40362
Distinct characters292
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique687 ?
Unique (%)38.7%

Sample

1st rowAsian Pacific Journal of Tropical Biomedicine
2nd row동의생리병리학회지
3rd row동의생리병리학회지
4th rowJournal of Chromatographic Science
5th rowMolecular Medicine Reports
ValueCountFrequency (%)
of 476
 
8.8%
journal 438
 
8.1%
and 255
 
4.7%
research 116
 
2.2%
science 110
 
2.0%
international 76
 
1.4%
j 71
 
1.3%
medicine 69
 
1.3%
67
 
1.2%
korean 63
 
1.2%
Other values (960) 3650
67.7%
2023-12-13T08:44:12.882800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3752
 
9.3%
o 2870
 
7.1%
e 2317
 
5.7%
n 2265
 
5.6%
a 2102
 
5.2%
i 1862
 
4.6%
l 1819
 
4.5%
r 1769
 
4.4%
c 1315
 
3.3%
t 1252
 
3.1%
Other values (282) 19039
47.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23510
58.2%
Uppercase Letter 8402
 
20.8%
Other Letter 4010
 
9.9%
Space Separator 3752
 
9.3%
Decimal Number 285
 
0.7%
Other Punctuation 255
 
0.6%
Control 84
 
0.2%
Dash Punctuation 39
 
0.1%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 479
 
11.9%
회 345
 
8.6%
한 303
 
7.6%
지 279
 
7.0%
국 270
 
6.7%
공 121
 
3.0%
재 88
 
2.2%
술 87
 
2.2%
목 76
 
1.9%
경 74
 
1.8%
Other values (205) 1888
47.1%
Lowercase Letter
ValueCountFrequency (%)
o 2870
12.2%
e 2317
9.9%
n 2265
9.6%
a 2102
8.9%
i 1862
 
7.9%
l 1819
 
7.7%
r 1769
 
7.5%
c 1315
 
5.6%
t 1252
 
5.3%
u 912
 
3.9%
Other values (16) 5027
21.4%
Uppercase Letter
ValueCountFrequency (%)
E 723
 
8.6%
C 677
 
8.1%
A 667
 
7.9%
R 588
 
7.0%
I 568
 
6.8%
O 542
 
6.5%
S 524
 
6.2%
N 522
 
6.2%
J 510
 
6.1%
P 442
 
5.3%
Other values (16) 2639
31.4%
Decimal Number
ValueCountFrequency (%)
0 83
29.1%
2 71
24.9%
1 56
19.6%
3 19
 
6.7%
6 17
 
6.0%
5 13
 
4.6%
4 10
 
3.5%
8 8
 
2.8%
7 7
 
2.5%
9 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 132
51.8%
& 63
24.7%
, 31
 
12.2%
· 13
 
5.1%
: 13
 
5.1%
/ 3
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 9
90.0%
「 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 9
90.0%
」 1
 
10.0%
Space Separator
ValueCountFrequency (%)
3752
100.0%
Control
ValueCountFrequency (%)
84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
= 3
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31912
79.1%
Common 4440
 
11.0%
Hangul 3992
 
9.9%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 479
 
12.0%
회 345
 
8.6%
한 303
 
7.6%
지 279
 
7.0%
국 270
 
6.8%
공 121
 
3.0%
재 88
 
2.2%
술 87
 
2.2%
목 76
 
1.9%
경 74
 
1.9%
Other values (192) 1870
46.8%
Latin
ValueCountFrequency (%)
o 2870
 
9.0%
e 2317
 
7.3%
n 2265
 
7.1%
a 2102
 
6.6%
i 1862
 
5.8%
l 1819
 
5.7%
r 1769
 
5.5%
c 1315
 
4.1%
t 1252
 
3.9%
u 912
 
2.9%
Other values (42) 13429
42.1%
Common
ValueCountFrequency (%)
3752
84.5%
. 132
 
3.0%
84
 
1.9%
0 83
 
1.9%
2 71
 
1.6%
& 63
 
1.4%
1 56
 
1.3%
- 39
 
0.9%
, 31
 
0.7%
3 19
 
0.4%
Other values (15) 110
 
2.5%
Han
ValueCountFrequency (%)
會 3
16.7%
學 3
16.7%
誌 2
11.1%
木 1
 
5.6%
韓 1
 
5.6%
材 1
 
5.6%
國 1
 
5.6%
山 1
 
5.6%
林 1
 
5.6%
經 1
 
5.6%
Other values (3) 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36335
90.0%
Hangul 3992
 
9.9%
CJK 18
 
< 0.1%
None 15
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3752
 
10.3%
o 2870
 
7.9%
e 2317
 
6.4%
n 2265
 
6.2%
a 2102
 
5.8%
i 1862
 
5.1%
l 1819
 
5.0%
r 1769
 
4.9%
c 1315
 
3.6%
t 1252
 
3.4%
Other values (63) 15012
41.3%
Hangul
ValueCountFrequency (%)
학 479
 
12.0%
회 345
 
8.6%
한 303
 
7.6%
지 279
 
7.0%
국 270
 
6.8%
공 121
 
3.0%
재 88
 
2.2%
술 87
 
2.2%
목 76
 
1.9%
경 74
 
1.9%
Other values (192) 1870
46.8%
None
ValueCountFrequency (%)
· 13
86.7%
」 1
 
6.7%
「 1
 
6.7%
CJK
ValueCountFrequency (%)
會 3
16.7%
學 3
16.7%
誌 2
11.1%
木 1
 
5.6%
韓 1
 
5.6%
材 1
 
5.6%
國 1
 
5.6%
山 1
 
5.6%
林 1
 
5.6%
經 1
 
5.6%
Other values (3) 3
16.7%
Punctuation
ValueCountFrequency (%)
’ 2
100.0%

학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
1
1148 
3
512 
4
 
69
6
 
24
2
 
23

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1148
64.6%
3 512
28.8%
4 69
 
3.9%
6 24
 
1.4%
2 23
 
1.3%

Length

2023-12-13T08:44:13.012022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:13.103249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1148
64.6%
3 512
28.8%
4 69
 
3.9%
6 24
 
1.4%
2 23
 
1.3%

SCI여부(1:SCI, 2:비 SCI)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size14.0 KiB
1
1195 
2
581 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 1195
67.3%
2 581
32.7%

Length

2023-12-13T08:44:13.215257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:44:13.306997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1195
67.3%
2 581
32.7%

ISSN
Text

MISSING 

Distinct315
Distinct (%)58.0%
Missing1233
Missing (%)69.4%
Memory size14.0 KiB
2023-12-13T08:44:13.548216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length9
Mean length9.0055249
Min length2

Characters and Unicode

Total characters4890
Distinct characters30
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique228 ?
Unique (%)42.0%

Sample

1st row0096-2686
2nd row1791-2997
3rd row0973-1296
4th row0973-1296
5th row1472-6882
ValueCountFrequency (%)
1660-4601 22
 
4.0%
1225-1755 16
 
2.9%
2077-0383 9
 
1.6%
0445-4650 9
 
1.6%
2093-3150 8
 
1.5%
0025-7974 8
 
1.5%
1229-8085 7
 
1.3%
2071-1050 7
 
1.3%
1229-3032 7
 
1.3%
1017-0715 7
 
1.3%
Other values (296) 446
81.7%
2023-12-13T08:44:13.969811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 629
12.9%
1 619
12.7%
0 610
12.5%
- 525
10.7%
5 403
8.2%
6 391
8.0%
3 367
7.5%
7 346
7.1%
9 316
6.5%
4 296
6.1%
Other values (20) 388
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4259
87.1%
Dash Punctuation 525
 
10.7%
Uppercase Letter 48
 
1.0%
Space Separator 47
 
1.0%
Other Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%
Other Letter 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 629
14.8%
1 619
14.5%
0 610
14.3%
5 403
9.5%
6 391
9.2%
3 367
8.6%
7 346
8.1%
9 316
7.4%
4 296
6.9%
8 282
6.6%
Uppercase Letter
ValueCountFrequency (%)
X 25
52.1%
S 7
 
14.6%
A 3
 
6.2%
E 3
 
6.2%
P 3
 
6.2%
K 3
 
6.2%
N 2
 
4.2%
I 2
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
v 1
33.3%
o 1
33.3%
l 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Other Letter
ValueCountFrequency (%)
일 1
50.0%
월 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 525
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4837
98.9%
Latin 51
 
1.0%
Hangul 2
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 629
13.0%
1 619
12.8%
0 610
12.6%
- 525
10.9%
5 403
8.3%
6 391
8.1%
3 367
7.6%
7 346
7.2%
9 316
6.5%
4 296
6.1%
Other values (7) 335
6.9%
Latin
ValueCountFrequency (%)
X 25
49.0%
S 7
 
13.7%
A 3
 
5.9%
E 3
 
5.9%
P 3
 
5.9%
K 3
 
5.9%
N 2
 
3.9%
I 2
 
3.9%
v 1
 
2.0%
o 1
 
2.0%
Hangul
ValueCountFrequency (%)
일 1
50.0%
월 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4888
> 99.9%
Hangul 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 629
12.9%
1 619
12.7%
0 610
12.5%
- 525
10.7%
5 403
8.2%
6 391
8.0%
3 367
7.5%
7 346
7.1%
9 316
6.5%
4 296
6.1%
Other values (18) 386
7.9%
Hangul
ValueCountFrequency (%)
일 1
50.0%
월 1
50.0%

게재권
Text

MISSING 

Distinct284
Distinct (%)32.7%
Missing908
Missing (%)51.1%
Memory size14.0 KiB
2023-12-13T08:44:14.319740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length2
Mean length2.593318
Min length1

Characters and Unicode

Total characters2251
Distinct characters60
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique163 ?
Unique (%)18.8%

Sample

1st row6
2nd row16
3rd row17
4th row54
5th row12
ValueCountFrequency (%)
9 26
 
2.9%
12 18
 
2.0%
7 15
 
1.7%
11 15
 
1.7%
8 15
 
1.7%
27 15
 
1.7%
17 15
 
1.7%
46 14
 
1.6%
43 14
 
1.6%
32 14
 
1.6%
Other values (267) 723
81.8%
2023-12-13T08:44:14.772575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 339
15.1%
2 325
14.4%
3 250
11.1%
4 204
9.1%
5 157
7.0%
0 152
6.8%
9 138
6.1%
6 133
 
5.9%
7 126
 
5.6%
8 126
 
5.6%
Other values (50) 301
13.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1950
86.6%
Other Letter 80
 
3.6%
Lowercase Letter 67
 
3.0%
Open Punctuation 33
 
1.5%
Close Punctuation 33
 
1.5%
Uppercase Letter 32
 
1.4%
Other Punctuation 21
 
0.9%
Space Separator 20
 
0.9%
Dash Punctuation 15
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
권 20
25.0%
계 8
 
10.0%
제 6
 
7.5%
추 5
 
6.2%
재 5
 
6.2%
학 5
 
6.2%
공 4
 
5.0%
목 4
 
5.0%
춘 4
 
5.0%
술 2
 
2.5%
Other values (16) 17
21.2%
Decimal Number
ValueCountFrequency (%)
1 339
17.4%
2 325
16.7%
3 250
12.8%
4 204
10.5%
5 157
8.1%
0 152
7.8%
9 138
7.1%
6 133
 
6.8%
7 126
 
6.5%
8 126
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
o 24
35.8%
l 23
34.3%
e 5
 
7.5%
m 4
 
6.0%
u 4
 
6.0%
v 3
 
4.5%
s 2
 
3.0%
r 1
 
1.5%
n 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
V 21
65.6%
P 4
 
12.5%
N 2
 
6.2%
I 1
 
3.1%
W 1
 
3.1%
L 1
 
3.1%
M 1
 
3.1%
E 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 18
85.7%
/ 2
 
9.5%
, 1
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2072
92.0%
Latin 99
 
4.4%
Hangul 74
 
3.3%
Han 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
권 20
27.0%
계 8
 
10.8%
제 6
 
8.1%
추 5
 
6.8%
재 5
 
6.8%
학 5
 
6.8%
공 4
 
5.4%
목 4
 
5.4%
춘 4
 
5.4%
술 2
 
2.7%
Other values (10) 11
14.9%
Common
ValueCountFrequency (%)
1 339
16.4%
2 325
15.7%
3 250
12.1%
4 204
9.8%
5 157
7.6%
0 152
7.3%
9 138
6.7%
6 133
 
6.4%
7 126
 
6.1%
8 126
 
6.1%
Other values (7) 122
 
5.9%
Latin
ValueCountFrequency (%)
o 24
24.2%
l 23
23.2%
V 21
21.2%
e 5
 
5.1%
m 4
 
4.0%
P 4
 
4.0%
u 4
 
4.0%
v 3
 
3.0%
N 2
 
2.0%
s 2
 
2.0%
Other values (7) 7
 
7.1%
Han
ValueCountFrequency (%)
硏 1
16.7%
究 1
16.7%
濟 1
16.7%
經 1
16.7%
林 1
16.7%
山 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2171
96.4%
Hangul 74
 
3.3%
CJK 6
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 339
15.6%
2 325
15.0%
3 250
11.5%
4 204
9.4%
5 157
7.2%
0 152
7.0%
9 138
6.4%
6 133
 
6.1%
7 126
 
5.8%
8 126
 
5.8%
Other values (24) 221
10.2%
Hangul
ValueCountFrequency (%)
권 20
27.0%
계 8
 
10.8%
제 6
 
8.1%
추 5
 
6.8%
재 5
 
6.8%
학 5
 
6.8%
공 4
 
5.4%
목 4
 
5.4%
춘 4
 
5.4%
술 2
 
2.7%
Other values (10) 11
14.9%
CJK
ValueCountFrequency (%)
硏 1
16.7%
究 1
16.7%
濟 1
16.7%
經 1
16.7%
林 1
16.7%
山 1
16.7%

게재호
Text

MISSING 

Distinct91
Distinct (%)14.7%
Missing1157
Missing (%)65.1%
Memory size14.0 KiB
2023-12-13T08:44:14.995066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length1
Mean length1.6235864
Min length1

Characters and Unicode

Total characters1005
Distinct characters43
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

Unique58 ?
Unique (%)9.4%

Sample

1st row10
2nd row4
3rd row2
4th row3
5th row3
ValueCountFrequency (%)
1 102
15.8%
3 98
15.1%
4 74
11.4%
2 71
11.0%
5 47
 
7.3%
6 44
 
6.8%
11 22
 
3.4%
9 15
 
2.3%
12 14
 
2.2%
7 12
 
1.9%
Other values (83) 148
22.9%
2023-12-13T08:44:15.338358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 209
20.8%
2 133
13.2%
3 115
11.4%
4 99
9.9%
6 67
 
6.7%
5 64
 
6.4%
0 52
 
5.2%
31
 
3.1%
. 25
 
2.5%
호 24
 
2.4%
Other values (33) 186
18.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 802
79.8%
Lowercase Letter 58
 
5.8%
Other Letter 41
 
4.1%
Uppercase Letter 37
 
3.7%
Other Punctuation 34
 
3.4%
Space Separator 31
 
3.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 20
34.5%
s 8
 
13.8%
t 8
 
13.8%
r 5
 
8.6%
e 5
 
8.6%
a 4
 
6.9%
u 3
 
5.2%
n 2
 
3.4%
p 1
 
1.7%
i 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 209
26.1%
2 133
16.6%
3 115
14.3%
4 99
12.3%
6 67
 
8.4%
5 64
 
8.0%
0 52
 
6.5%
8 22
 
2.7%
9 21
 
2.6%
7 20
 
2.5%
Other Letter
ValueCountFrequency (%)
호 24
58.5%
제 5
 
12.2%
월 2
 
4.9%
일 2
 
4.9%
계 2
 
4.9%
춘 2
 
4.9%
권 1
 
2.4%
봄 1
 
2.4%
가 1
 
2.4%
을 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 19
51.4%
P 8
21.6%
B 4
 
10.8%
I 3
 
8.1%
A 2
 
5.4%
S 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 25
73.5%
, 8
 
23.5%
/ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 869
86.5%
Latin 95
 
9.5%
Hangul 41
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 20
21.1%
N 19
20.0%
s 8
 
8.4%
P 8
 
8.4%
t 8
 
8.4%
r 5
 
5.3%
e 5
 
5.3%
B 4
 
4.2%
a 4
 
4.2%
u 3
 
3.2%
Other values (7) 11
11.6%
Common
ValueCountFrequency (%)
1 209
24.1%
2 133
15.3%
3 115
13.2%
4 99
11.4%
6 67
 
7.7%
5 64
 
7.4%
0 52
 
6.0%
31
 
3.6%
. 25
 
2.9%
8 22
 
2.5%
Other values (6) 52
 
6.0%
Hangul
ValueCountFrequency (%)
호 24
58.5%
제 5
 
12.2%
월 2
 
4.9%
일 2
 
4.9%
계 2
 
4.9%
춘 2
 
4.9%
권 1
 
2.4%
봄 1
 
2.4%
가 1
 
2.4%
을 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 964
95.9%
Hangul 41
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 209
21.7%
2 133
13.8%
3 115
11.9%
4 99
10.3%
6 67
 
7.0%
5 64
 
6.6%
0 52
 
5.4%
31
 
3.2%
. 25
 
2.6%
8 22
 
2.3%
Other values (23) 147
15.2%
Hangul
ValueCountFrequency (%)
호 24
58.5%
제 5
 
12.2%
월 2
 
4.9%
일 2
 
4.9%
계 2
 
4.9%
춘 2
 
4.9%
권 1
 
2.4%
봄 1
 
2.4%
가 1
 
2.4%
을 1
 
2.4%

시작페이지
Text

MISSING 

Distinct561
Distinct (%)67.8%
Missing949
Missing (%)53.4%
Memory size14.0 KiB
2023-12-13T08:44:15.675284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length2.9891173
Min length1

Characters and Unicode

Total characters2472
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique422 ?
Unique (%)51.0%

Sample

1st row830
2nd row818
3rd row476
4th row299
5th row4773
ValueCountFrequency (%)
1 37
 
4.5%
51 6
 
0.7%
65 6
 
0.7%
43 5
 
0.6%
110 5
 
0.6%
31 5
 
0.6%
10 5
 
0.6%
91 5
 
0.6%
35 5
 
0.6%
28 4
 
0.5%
Other values (550) 744
90.0%
2023-12-13T08:44:16.167597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 452
18.3%
3 303
12.3%
5 290
11.7%
2 276
11.2%
4 220
8.9%
7 199
8.1%
0 181
7.3%
9 178
 
7.2%
8 176
 
7.1%
6 171
 
6.9%
Other values (8) 26
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2446
98.9%
Lowercase Letter 13
 
0.5%
Other Punctuation 8
 
0.3%
Uppercase Letter 3
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 452
18.5%
3 303
12.4%
5 290
11.9%
2 276
11.3%
4 220
9.0%
7 199
8.1%
0 181
7.4%
9 178
 
7.3%
8 176
 
7.2%
6 171
 
7.0%
Lowercase Letter
ValueCountFrequency (%)
e 10
76.9%
i 2
 
15.4%
p 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
. 7
87.5%
: 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
E 2
66.7%
R 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2456
99.4%
Latin 16
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 452
18.4%
3 303
12.3%
5 290
11.8%
2 276
11.2%
4 220
9.0%
7 199
8.1%
0 181
7.4%
9 178
 
7.2%
8 176
 
7.2%
6 171
 
7.0%
Other values (3) 10
 
0.4%
Latin
ValueCountFrequency (%)
e 10
62.5%
i 2
 
12.5%
E 2
 
12.5%
p 1
 
6.2%
R 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 452
18.3%
3 303
12.3%
5 290
11.7%
2 276
11.2%
4 220
8.9%
7 199
8.1%
0 181
7.3%
9 178
 
7.2%
8 176
 
7.1%
6 171
 
6.9%
Other values (8) 26
 
1.1%

종료페이지
Text

MISSING 

Distinct520
Distinct (%)70.0%
Missing1033
Missing (%)58.2%
Memory size14.0 KiB
2023-12-13T08:44:16.562672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length2.9690444
Min length1

Characters and Unicode

Total characters2206
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique380 ?
Unique (%)51.1%

Sample

1st row835
2nd row822
3rd row480
4th row304
5th row4781
ValueCountFrequency (%)
10 6
 
0.8%
160 6
 
0.8%
8 6
 
0.8%
57 5
 
0.7%
55 5
 
0.7%
48 5
 
0.7%
30 5
 
0.7%
77 4
 
0.5%
101 4
 
0.5%
20 4
 
0.5%
Other values (510) 693
93.3%
2023-12-13T08:44:17.093365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 366
16.6%
2 263
11.9%
5 244
11.1%
3 244
11.1%
4 209
9.5%
8 202
9.2%
6 178
8.1%
0 169
7.7%
9 161
7.3%
7 158
7.2%
Other values (3) 12
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2194
99.5%
Other Punctuation 8
 
0.4%
Dash Punctuation 3
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 366
16.7%
2 263
12.0%
5 244
11.1%
3 244
11.1%
4 209
9.5%
8 202
9.2%
6 178
8.1%
0 169
7.7%
9 161
7.3%
7 158
7.2%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2205
> 99.9%
Latin 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 366
16.6%
2 263
11.9%
5 244
11.1%
3 244
11.1%
4 209
9.5%
8 202
9.2%
6 178
8.1%
0 169
7.7%
9 161
7.3%
7 158
7.2%
Other values (2) 11
 
0.5%
Latin
ValueCountFrequency (%)
R 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 366
16.6%
2 263
11.9%
5 244
11.1%
3 244
11.1%
4 209
9.5%
8 202
9.2%
6 178
8.1%
0 169
7.7%
9 161
7.3%
7 158
7.2%
Other values (3) 12
 
0.5%

공동저자명
Text

MISSING 

Distinct569
Distinct (%)94.5%
Missing1174
Missing (%)66.1%
Memory size14.0 KiB
2023-12-13T08:44:17.423000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length346
Median length177
Mean length51.626246
Min length3

Characters and Unicode

Total characters31079
Distinct characters274
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique545 ?
Unique (%)90.5%

Sample

1st rowWon Hyung Choi; In Ah Lee
2nd row양현옥; 최원형; 전병훈; 백승화; 천현자
3rd row천현자; 최원형; 이정호; 양현옥; 백승화
4th row임혜선, 하혜경, 진성은, 신현규
5th row정수진, 유새롬, 이나리, 신현규
ValueCountFrequency (%)
lee 266
 
4.9%
kim 241
 
4.5%
choi 86
 
1.6%
양인 72
 
1.3%
park 72
 
1.3%
yang 69
 
1.3%
jun 66
 
1.2%
jae 65
 
1.2%
cho 60
 
1.1%
한규성 54
 
1.0%
Other values (1524) 4340
80.5%
2023-12-13T08:44:17.921942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4850
 
15.6%
n 1997
 
6.4%
o 1575
 
5.1%
; 1452
 
4.7%
, 1426
 
4.6%
e 1374
 
4.4%
a 1140
 
3.7%
g 1026
 
3.3%
i 927
 
3.0%
u 902
 
2.9%
Other values (264) 14410
46.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11825
38.0%
Uppercase Letter 5699
18.3%
Space Separator 4850
15.6%
Other Punctuation 3886
 
12.5%
Other Letter 3878
 
12.5%
Dash Punctuation 337
 
1.1%
Open Punctuation 268
 
0.9%
Close Punctuation 268
 
0.9%
Decimal Number 67
 
0.2%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 205
 
5.3%
이 177
 
4.6%
성 118
 
3.0%
인 117
 
3.0%
규 116
 
3.0%
정 102
 
2.6%
최 100
 
2.6%
한 95
 
2.4%
진 95
 
2.4%
영 93
 
2.4%
Other values (188) 2660
68.6%
Uppercase Letter
ValueCountFrequency (%)
S 761
13.4%
J 750
13.2%
H 665
11.7%
K 536
9.4%
Y 455
 
8.0%
L 399
 
7.0%
C 378
 
6.6%
M 249
 
4.4%
B 163
 
2.9%
W 145
 
2.5%
Other values (16) 1198
21.0%
Lowercase Letter
ValueCountFrequency (%)
n 1997
16.9%
o 1575
13.3%
e 1374
11.6%
a 1140
9.6%
g 1026
8.7%
i 927
7.8%
u 902
7.6%
h 640
 
5.4%
m 396
 
3.3%
y 312
 
2.6%
Other values (14) 1536
13.0%
Decimal Number
ValueCountFrequency (%)
1 22
32.8%
4 15
22.4%
2 9
13.4%
3 5
 
7.5%
0 5
 
7.5%
5 3
 
4.5%
6 2
 
3.0%
7 2
 
3.0%
8 2
 
3.0%
9 2
 
3.0%
Other Punctuation
ValueCountFrequency (%)
; 1452
37.4%
, 1426
36.7%
. 700
18.0%
/ 254
 
6.5%
# 25
 
0.6%
& 12
 
0.3%
* 11
 
0.3%
· 5
 
0.1%
† 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 259
96.6%
[ 9
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 259
96.6%
] 9
 
3.4%
Space Separator
ValueCountFrequency (%)
4850
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 337
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17524
56.4%
Common 9677
31.1%
Hangul 3868
 
12.4%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 205
 
5.3%
이 177
 
4.6%
성 118
 
3.1%
인 117
 
3.0%
규 116
 
3.0%
정 102
 
2.6%
최 100
 
2.6%
한 95
 
2.5%
진 95
 
2.5%
영 93
 
2.4%
Other values (179) 2650
68.5%
Latin
ValueCountFrequency (%)
n 1997
 
11.4%
o 1575
 
9.0%
e 1374
 
7.8%
a 1140
 
6.5%
g 1026
 
5.9%
i 927
 
5.3%
u 902
 
5.1%
S 761
 
4.3%
J 750
 
4.3%
H 665
 
3.8%
Other values (40) 6407
36.6%
Common
ValueCountFrequency (%)
4850
50.1%
; 1452
 
15.0%
, 1426
 
14.7%
. 700
 
7.2%
- 337
 
3.5%
( 259
 
2.7%
) 259
 
2.7%
/ 254
 
2.6%
# 25
 
0.3%
1 22
 
0.2%
Other values (16) 93
 
1.0%
Han
ValueCountFrequency (%)
田 2
20.0%
坂 1
10.0%
博 1
10.0%
朴 1
10.0%
光 1
10.0%
功 1
10.0%
森 1
10.0%
範 1
10.0%
相 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27195
87.5%
Hangul 3868
 
12.4%
CJK 10
 
< 0.1%
None 5
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4850
17.8%
n 1997
 
7.3%
o 1575
 
5.8%
; 1452
 
5.3%
, 1426
 
5.2%
e 1374
 
5.1%
a 1140
 
4.2%
g 1026
 
3.8%
i 927
 
3.4%
u 902
 
3.3%
Other values (64) 10526
38.7%
Hangul
ValueCountFrequency (%)
김 205
 
5.3%
이 177
 
4.6%
성 118
 
3.1%
인 117
 
3.0%
규 116
 
3.0%
정 102
 
2.6%
최 100
 
2.6%
한 95
 
2.5%
진 95
 
2.5%
영 93
 
2.4%
Other values (179) 2650
68.5%
None
ValueCountFrequency (%)
· 5
100.0%
CJK
ValueCountFrequency (%)
田 2
20.0%
坂 1
10.0%
博 1
10.0%
朴 1
10.0%
光 1
10.0%
功 1
10.0%
森 1
10.0%
範 1
10.0%
相 1
10.0%
Punctuation
ValueCountFrequency (%)
† 1
100.0%

Interactions

2023-12-13T08:44:08.315070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:44:18.020218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번역할구분(3:주저자, 4:교신저자)학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)SCI여부(1:SCI, 2:비 SCI)게재호
순번1.0000.2020.3220.1400.000
역할구분(3:주저자, 4:교신저자)0.2021.0000.0680.1290.233
학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)0.3220.0681.0000.6830.887
SCI여부(1:SCI, 2:비 SCI)0.1400.1290.6831.0000.356
게재호0.0000.2330.8870.3561.000
2023-12-13T08:44:18.125065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)역할구분(3:주저자, 4:교신저자)SCI여부(1:SCI, 2:비 SCI)
학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)1.0000.0830.815
역할구분(3:주저자, 4:교신저자)0.0831.0000.082
SCI여부(1:SCI, 2:비 SCI)0.8150.0821.000
2023-12-13T08:44:18.224871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번역할구분(3:주저자, 4:교신저자)학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)SCI여부(1:SCI, 2:비 SCI)
순번1.0000.1540.1390.107
역할구분(3:주저자, 4:교신저자)0.1541.0000.0830.082
학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)0.1390.0831.0000.815
SCI여부(1:SCI, 2:비 SCI)0.1070.0820.8151.000

Missing values

2023-12-13T08:44:08.436795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:44:08.643211image/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.
2023-12-13T08:44:08.802538image/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

인력관리번호순번논문제목국문논문제목영문논문발표일역할구분(3:주저자, 4:교신저자)발행처명학술지명학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)SCI여부(1:SCI, 2:비 SCI)ISSN게재권게재호시작페이지종료페이지공동저자명
0UR0000057216The anti-tubercular activity of Melia azedarach L. and Lobelia chinensis Lour. and their potential as effective anti-Mycobacterium tuberculosis candidate agentsThe anti-tubercular activity of Melia azedarach L. and Lobelia chinensis Lour. and their potential as effective anti-Mycobacterium tuberculosis candidate agents2016-10-314Hainan Medical University, ElsevierAsian Pacific Journal of Tropical Biomedicine11<NA>610830835Won Hyung Choi; In Ah Lee
1UR0000057217산수유 물추출물이 B16/F10 melanoma세포주의 멜라닌 생성에 미치는 영향Water Extract from Cornis Fructus Regulates Melanogenesis in B16/F10 Melanoma2002-12-303동의생리병리학회동의생리병리학회지32<NA>164818822양현옥; 최원형; 전병훈; 백승화; 천현자
2UR0000057218산수유 헥산 추출물의 항균효과 및 세포독성Screening of Cytotoxicity and Antimicrobial Effects of Hexane Extracts from Cornis fructus2003-06-303동의생리병리학회동의생리병리학회지32<NA>172476480천현자; 최원형; 이정호; 양현옥; 백승화
3UR000006751반하사심탕에서 9가지 마커 성분의 동시정량을 위한 HPLC-PDA 분석HPLC-PDA Method for Simultaneous Determination of Nine Marker Components in Banhasasim-Tang<NA>4<NA>Journal of Chromatographic Science110096-2686543299304<NA>
4UR000006752HaCaT cell과 RAW 264.7 cell에서 조각자의 항염증 효과 및 동시 분석Quantitative analysis and anti-inflammatory effects of Gleditsia sinensis thorns in RAW 264.7 macrophages and HaCaT keratinocytes2015-09-304Athens, Greece : D. A. SpandidosMolecular Medicine Reports111791-299712347734781임혜선, 하혜경, 진성은, 신현규
5UR000006753지유의 성분인 gallic acid, ellagic acid, quercetin의 항염증 효과 및 정량 분석Quantitative Analysis and In vitro Anti-inflammatory Effects of Gallic Acid, Ellagic Acid, and Quercetin from Radix Sanguisorbae<NA>4Mumbai : Medknow Publications and MediaPharmacognosy Magazine110973-12961246104108정수진, 유새롬, 이나리, 신현규
6UR000006754HPLC에 의한 당귀수산에서 9개 마커 성분의 동시 정량Simultaneous determination of nine marker compounds in the traditional Korean medicine, Dangguisu-san by high-performance liquid chromatography<NA>4Mumbai : Medknow Publications and MediaPharmacognosy Magazine110973-12961143555561신현규
7UR000006755황련해독탕의 항동맥경화 효과 및 동시 정량Simultaneous quantification and antiatherosclerosis effect of the traditional Korean medicine, Hwangryunhaedok-tang<NA>4London : BioMed CentralBMC Complementary and Alternative Medicine111472-6882815108<NA>김온순; 김정훈; 신현규
8UR000006881활엽수재 횡단면의 관공 특징 연구를 위한 화상분석 프로그램의 개발과 응용Development and Application of Image Analysis Program for Investigation of Pore Characteristics in the Transverse Surface of Hardwoods<NA>4<NA>목재공학32<NA><NA><NA><NA><NA><NA>
9UR000006882레이저프로필로미터를 이용한 두께과 밀도 맵핑Application of Thickness and Apparent Density Mapping by Laser Profilometry<NA>3<NA>13th Fundamental Research Symposium, Cambridge22<NA><NA><NA><NA><NA><NA>
인력관리번호순번논문제목국문논문제목영문논문발표일역할구분(3:주저자, 4:교신저자)발행처명학술지명학술지구분(1:해외 학회지, 2:해외 학술대회, 3:국내 학회지, 4:국내 학술대회, 6:기타 간행물)SCI여부(1:SCI, 2:비 SCI)ISSN게재권게재호시작페이지종료페이지공동저자명
1766UR0000558350Efficacy of direct arthroscopy-guided suprascapular nerve block after arthroscopic rotator cuff repair: a prospective randomized studyEfficacy of direct arthroscopy-guided suprascapular nerve block after arthroscopic rotator cuff repair: a prospective randomized study2015-02-234SPRINGERKNEE SURGERY SPORTS TRAUMATOLOGY ARTHROSCOPY110942-2056232562566Jae Jun Lee, Yon-Sik Yoo, Jung-Taek Hwang, Do-Young Kim, Seong-Jae Jeon, Sung Mi Hwang, Ji Su Jang
1767UR000056171Genome-wide blood DNA methylation analysis in patients with delayed cerebral ischemia after subarachnoid hemorrhageGenome-wide blood DNA methylation analysis in patients with delayed cerebral ischemia after subarachnoid hemorrhage<NA>4<NA>Scientific Reports112045-2322<NA><NA><NA><NA><NA>
1768UR0000558351Predictors of survival following extracorporeal cardiopulmonary resuscitation in patients with acute myocardial infarction-complicated refractory cardiac arrest in the emergency department: a retrospective studyPredictors of survival following extracorporeal cardiopulmonary resuscitation in patients with acute myocardial infarction-complicated refractory cardiac arrest in the emergency department: a retrospective study2015-02-244BIOMED CENTRAL LTDJOURNAL OF CARDIOTHORACIC SURGERY111749-80901024<NA><NA>Sang Jin Han , Hyoung Soo Kim , Hyun Hee Choi, Gyung Soon Hong, Won Ki Lee, Sun Hee Lee, Dong Geun You, Jae Jun Lee
1769UR0000558352The effect of dexmedetomidine as an adjuvant to ropivacaine on the bispectral index for supraclavicular brachial plexus blockThe effect of dexmedetomidine as an adjuvant to ropivacaine on the bispectral index for supraclavicular brachial plexus block2015-02-013Korean Journal of AnesthesiologyKorean Journal of Anesthesiology112005-64196813236Youngsuk Kwon, Sung Mi Hwang, Jae Jun Lee, Jong Ho Kim
1770UR0000558353Efficacy of Veno-Venous Extracorporeal Membrane Oxygenation in Severe Acute Respiratory FailureEfficacy of Veno-Venous Extracorporeal Membrane Oxygenation in Severe Acute Respiratory Failure2015-01-314Yonsei Medical JournalYonsei Medical Journal110513-5796561212219Jae Jun Lee, Sung Mi Hwang, Jae Houn Ko, Hyoung Soo Kim, Kyung Soon Hong, Hyun Hee Choi, Myung Goo Lee, Chang Youl Lee, Won Ki Lee, Eun Jin Soun, Tae Hun Lee, Jeong Yeol Seo
1771UR000056172A Preliminary Study of the Association between SOX17 Gene Variants and Intracranial Aneurysms Using Exome SequencingA Preliminary Study of the Association between SOX17 Gene Variants and Intracranial Aneurysms Using Exome Sequencing<NA>4<NA>JOURNAL OF KOREAN NEUROSURGICAL SOCIETY112005-3711<NA><NA><NA><NA><NA>
1772UR000056173Characterization of the tcr β chain cdr3 repertoire in subarachnoid hemorrhage patients with delayed cerebral ischemiaCharacterization of the tcr β chain cdr3 repertoire in subarachnoid hemorrhage patients with delayed cerebral ischemia<NA>4<NA>INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES111661-6596<NA><NA><NA><NA><NA>
1773UR000056174Monitoring of Delayed Cerebral Ischemia in Patients with Subarachnoid Hemorrhage via Near-Infrared SpectroscopyMonitoring of Delayed Cerebral Ischemia in Patients with Subarachnoid Hemorrhage via Near-Infrared Spectroscopy<NA>4<NA>JOURNAL OF CLINICAL MEDICINE112077-0383<NA><NA><NA><NA><NA>
1774UR000056175Seizure incidence of angiogram-negative subarachnoid hemorrhage: An updated meta-analysisSeizure incidence of angiogram-negative subarachnoid hemorrhage: An updated meta-analysis<NA>4LIPPINCOTT WILLIAMS & WILKINS , TWO COMMERCE SQ, 2001 MARKET ST, PHILADELPHIA, USA, PA, 19103JOURNAL OF THE CHINESE MEDICAL ASSOCIATION111726-4901<NA><NA><NA><NA><NA>
1775UR000056176The Dynamics of Respiratory Microbiota during Mechanical Ventilation in Patients with PneumoniaThe Dynamics of Respiratory Microbiota during Mechanical Ventilation in Patients with Pneumonia<NA>3<NA>JOURNAL OF CLINICAL MEDICINE11<NA><NA><NA><NA><NA><NA>