Overview

Dataset statistics

Number of variables14
Number of observations2001
Missing cells7411
Missing cells (%)26.5%
Duplicate rows20
Duplicate rows (%)1.0%
Total size in memory220.9 KiB
Average record size in memory113.1 B

Variable types

Categorical1
Text12
Numeric1

Dataset

Description본 데이터는 환경보건종합정보시스템에서 제공하는 국내외환경보건연구논문에 대해 정리한 데이터로, 관련 제목, 키워드, 발행처 등을 확인할 수 있습니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15089780/fileData.do

Alerts

Dataset has 20 (1.0%) duplicate rowsDuplicates
핵심키워드2 has 52 (2.6%) missing valuesMissing
핵심키워드3 has 325 (16.2%) missing valuesMissing
핵심키워드4 has 1033 (51.6%) missing valuesMissing
핵심키워드5 has 1613 (80.6%) missing valuesMissing
연관키워드2 has 214 (10.7%) missing valuesMissing
연관키워드3 has 803 (40.1%) missing valuesMissing
연관키워드4 has 1398 (69.9%) missing valuesMissing
연관키워드5 has 1787 (89.3%) missing valuesMissing
발행처 has 92 (4.6%) missing valuesMissing
발행년도 has 92 (4.6%) missing valuesMissing

Reproduction

Analysis started2024-04-21 09:49:35.164772
Analysis finished2024-04-21 09:49:39.967554
Duration4.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
국외연구논문
1740 
국내연구논문
261 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국외연구논문 1740
87.0%
국내연구논문 261
 
13.0%

Length

2024-04-21T18:49:40.070733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:49:40.242436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국외연구논문 1740
87.0%
국내연구논문 261
 
13.0%

제목
Text

Distinct1956
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
2024-04-21T18:49:41.153873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length200
Median length145
Mean length105.54823
Min length14

Characters and Unicode

Total characters211202
Distinct characters499
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1911 ?
Unique (%)95.5%

Sample

1st row시흥 · 안산 산단 및 영향지역의 휘발성유기화합물질(VOCs) 분포 특성
2nd row우리나라 성인 중 비흡연자에 대한 코티닌 노출수준 및 영향요인 분석 - 국민환경보건 기초조사(2009-2017) 결과 -
3rd row다중 영향 및 환경정의를 고려한 지역 환경보건수준 평가 사례연구
4th row국내 주요 환경보건 재난의 전개 과정과 그 교훈, 그리고 환경보건 전문가의 역할
5th row화학물질 배출·이동량 자료를 이용한 유해기반 지수의 시공간 특성 연구
ValueCountFrequency (%)
and 1561
 
5.2%
in 1444
 
4.8%
of 1423
 
4.7%
the 770
 
2.6%
a 643
 
2.1%
to 494
 
1.6%
exposure 480
 
1.6%
study 362
 
1.2%
on 291
 
1.0%
air 261
 
0.9%
Other values (5856) 22290
74.3%
2024-04-21T18:49:42.412103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
28140
13.3%
e 16812
 
8.0%
i 14434
 
6.8%
n 14121
 
6.7%
a 13929
 
6.6%
o 13601
 
6.4%
t 13111
 
6.2%
r 10156
 
4.8%
s 10021
 
4.7%
l 7398
 
3.5%
Other values (489) 69479
32.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 155330
73.5%
Space Separator 28140
 
13.3%
Uppercase Letter 16204
 
7.7%
Other Letter 7051
 
3.3%
Other Punctuation 1587
 
0.8%
Decimal Number 1453
 
0.7%
Dash Punctuation 1014
 
0.5%
Close Punctuation 175
 
0.1%
Open Punctuation 175
 
0.1%
Final Punctuation 58
 
< 0.1%
Other values (3) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
253
 
3.6%
144
 
2.0%
144
 
2.0%
135
 
1.9%
113
 
1.6%
109
 
1.5%
105
 
1.5%
104
 
1.5%
103
 
1.5%
97
 
1.4%
Other values (394) 5744
81.5%
Lowercase Letter
ValueCountFrequency (%)
e 16812
10.8%
i 14434
9.3%
n 14121
 
9.1%
a 13929
 
9.0%
o 13601
 
8.8%
t 13111
 
8.4%
r 10156
 
6.5%
s 10021
 
6.5%
l 7398
 
4.8%
d 5796
 
3.7%
Other values (21) 35951
23.1%
Uppercase Letter
ValueCountFrequency (%)
A 1888
11.7%
C 1707
 
10.5%
P 1418
 
8.8%
S 1400
 
8.6%
E 1219
 
7.5%
M 1030
 
6.4%
R 860
 
5.3%
D 765
 
4.7%
I 715
 
4.4%
H 698
 
4.3%
Other values (16) 4504
27.8%
Other Punctuation
ValueCountFrequency (%)
, 712
44.9%
: 617
38.9%
. 199
 
12.5%
/ 35
 
2.2%
· 9
 
0.6%
' 7
 
0.4%
; 5
 
0.3%
% 1
 
0.1%
1
 
0.1%
& 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 398
27.4%
0 301
20.7%
1 276
19.0%
5 169
11.6%
3 77
 
5.3%
9 69
 
4.7%
4 55
 
3.8%
7 44
 
3.0%
6 34
 
2.3%
8 30
 
2.1%
Math Symbol
ValueCountFrequency (%)
+ 3
37.5%
~ 2
25.0%
< 1
 
12.5%
1
 
12.5%
1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1012
99.8%
2
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 169
96.6%
] 6
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 169
96.6%
[ 6
 
3.4%
Final Punctuation
ValueCountFrequency (%)
56
96.6%
2
 
3.4%
Initial Punctuation
ValueCountFrequency (%)
2
50.0%
2
50.0%
Other Symbol
ValueCountFrequency (%)
° 2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
28140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 171517
81.2%
Common 32617
 
15.4%
Hangul 7049
 
3.3%
Greek 17
 
< 0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
253
 
3.6%
144
 
2.0%
144
 
2.0%
135
 
1.9%
113
 
1.6%
109
 
1.5%
105
 
1.5%
104
 
1.5%
103
 
1.5%
97
 
1.4%
Other values (392) 5742
81.5%
Latin
ValueCountFrequency (%)
e 16812
 
9.8%
i 14434
 
8.4%
n 14121
 
8.2%
a 13929
 
8.1%
o 13601
 
7.9%
t 13111
 
7.6%
r 10156
 
5.9%
s 10021
 
5.8%
l 7398
 
4.3%
d 5796
 
3.4%
Other values (42) 52138
30.4%
Common
ValueCountFrequency (%)
28140
86.3%
- 1012
 
3.1%
, 712
 
2.2%
: 617
 
1.9%
2 398
 
1.2%
0 301
 
0.9%
1 276
 
0.8%
. 199
 
0.6%
) 169
 
0.5%
( 169
 
0.5%
Other values (28) 624
 
1.9%
Greek
ValueCountFrequency (%)
β 8
47.1%
γ 4
23.5%
ε 2
 
11.8%
α 2
 
11.8%
μ 1
 
5.9%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204055
96.6%
Hangul 7048
 
3.3%
Punctuation 65
 
< 0.1%
None 28
 
< 0.1%
CJK 2
 
< 0.1%
Arrows 1
 
< 0.1%
Math Operators 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
28140
13.8%
e 16812
 
8.2%
i 14434
 
7.1%
n 14121
 
6.9%
a 13929
 
6.8%
o 13601
 
6.7%
t 13111
 
6.4%
r 10156
 
5.0%
s 10021
 
4.9%
l 7398
 
3.6%
Other values (69) 62332
30.5%
Hangul
ValueCountFrequency (%)
253
 
3.6%
144
 
2.0%
144
 
2.0%
135
 
1.9%
113
 
1.6%
109
 
1.5%
105
 
1.5%
104
 
1.5%
103
 
1.5%
97
 
1.4%
Other values (391) 5741
81.5%
Punctuation
ValueCountFrequency (%)
56
86.2%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
1
 
1.5%
None
ValueCountFrequency (%)
· 9
32.1%
β 8
28.6%
γ 4
14.3%
ε 2
 
7.1%
α 2
 
7.1%
° 2
 
7.1%
μ 1
 
3.6%
Arrows
ValueCountFrequency (%)
1
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Distinct469
Distinct (%)23.4%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2024-04-21T18:49:43.349607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length5.9895
Min length1

Characters and Unicode

Total characters11979
Distinct characters312
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)16.2%

Sample

1st rowVOCs
2nd rowCotinine
3rd rowcumulative impact
4th rowHumidifier disinfect
5th rowPRTR(화학물질 배출 및 이동량)
ValueCountFrequency (%)
대기오염 293
 
12.8%
유해화학물질 208
 
9.1%
기후변화 122
 
5.3%
미세먼지 66
 
2.9%
화학물질 63
 
2.8%
실내공기오염물질 56
 
2.4%
물환경 54
 
2.4%
대기오염물질 52
 
2.3%
환경보건 48
 
2.1%
air 40
 
1.7%
Other values (521) 1285
56.2%
2024-04-21T18:49:44.585370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
606
 
5.1%
511
 
4.3%
505
 
4.2%
493
 
4.1%
481
 
4.0%
i 459
 
3.8%
444
 
3.7%
e 389
 
3.2%
358
 
3.0%
t 345
 
2.9%
Other values (302) 7388
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7246
60.5%
Lowercase Letter 3817
31.9%
Uppercase Letter 535
 
4.5%
Space Separator 287
 
2.4%
Decimal Number 25
 
0.2%
Open Punctuation 20
 
0.2%
Close Punctuation 20
 
0.2%
Dash Punctuation 14
 
0.1%
Other Punctuation 14
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
606
 
8.4%
511
 
7.1%
505
 
7.0%
493
 
6.8%
481
 
6.6%
444
 
6.1%
358
 
4.9%
304
 
4.2%
245
 
3.4%
236
 
3.3%
Other values (239) 3063
42.3%
Lowercase Letter
ValueCountFrequency (%)
i 459
12.0%
e 389
10.2%
t 345
9.0%
a 299
 
7.8%
o 299
 
7.8%
r 280
 
7.3%
l 251
 
6.6%
n 241
 
6.3%
s 239
 
6.3%
c 153
 
4.0%
Other values (16) 862
22.6%
Uppercase Letter
ValueCountFrequency (%)
A 147
27.5%
D 69
12.9%
P 54
 
10.1%
C 47
 
8.8%
M 32
 
6.0%
H 25
 
4.7%
B 24
 
4.5%
I 21
 
3.9%
E 19
 
3.6%
O 16
 
3.0%
Other values (13) 81
15.1%
Decimal Number
ValueCountFrequency (%)
5 9
36.0%
2 9
36.0%
1 3
 
12.0%
9 3
 
12.0%
3 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 19
95.0%
[ 1
 
5.0%
Close Punctuation
ValueCountFrequency (%)
) 19
95.0%
] 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 11
78.6%
/ 3
 
21.4%
Space Separator
ValueCountFrequency (%)
287
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7246
60.5%
Latin 4352
36.3%
Common 381
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
606
 
8.4%
511
 
7.1%
505
 
7.0%
493
 
6.8%
481
 
6.6%
444
 
6.1%
358
 
4.9%
304
 
4.2%
245
 
3.4%
236
 
3.3%
Other values (239) 3063
42.3%
Latin
ValueCountFrequency (%)
i 459
 
10.5%
e 389
 
8.9%
t 345
 
7.9%
a 299
 
6.9%
o 299
 
6.9%
r 280
 
6.4%
l 251
 
5.8%
n 241
 
5.5%
s 239
 
5.5%
c 153
 
3.5%
Other values (39) 1397
32.1%
Common
ValueCountFrequency (%)
287
75.3%
( 19
 
5.0%
) 19
 
5.0%
- 14
 
3.7%
. 11
 
2.9%
5 9
 
2.4%
2 9
 
2.4%
/ 3
 
0.8%
1 3
 
0.8%
9 3
 
0.8%
Other values (4) 4
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7246
60.5%
ASCII 4732
39.5%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
606
 
8.4%
511
 
7.1%
505
 
7.0%
493
 
6.8%
481
 
6.6%
444
 
6.1%
358
 
4.9%
304
 
4.2%
245
 
3.4%
236
 
3.3%
Other values (239) 3063
42.3%
ASCII
ValueCountFrequency (%)
i 459
 
9.7%
e 389
 
8.2%
t 345
 
7.3%
a 299
 
6.3%
o 299
 
6.3%
287
 
6.1%
r 280
 
5.9%
l 251
 
5.3%
n 241
 
5.1%
s 239
 
5.1%
Other values (52) 1643
34.7%
Punctuation
ValueCountFrequency (%)
1
100.0%

핵심키워드2
Text

MISSING 

Distinct652
Distinct (%)33.5%
Missing52
Missing (%)2.6%
Memory size15.8 KiB
2024-04-21T18:49:45.684909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length6.1021036
Min length1

Characters and Unicode

Total characters11893
Distinct characters347
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique448 ?
Unique (%)23.0%

Sample

1st rowaffected area
2nd rowsecondhand smoke
3rd rowEnvironmental health
4th rowphenol contamination
5th rowRSEI
ValueCountFrequency (%)
대기오염물질 261
 
11.6%
화학물질 196
 
8.7%
실내공기질 55
 
2.4%
대기오염 41
 
1.8%
유해화학물질 35
 
1.6%
수질오염물질 34
 
1.5%
미세먼지 32
 
1.4%
실내공기오염물질 29
 
1.3%
토양오염물질 23
 
1.0%
수질오염 23
 
1.0%
Other values (713) 1520
67.6%
2024-04-21T18:49:46.941078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
786
 
6.6%
648
 
5.4%
500
 
4.2%
472
 
4.0%
440
 
3.7%
i 388
 
3.3%
e 387
 
3.3%
t 328
 
2.8%
313
 
2.6%
a 312
 
2.6%
Other values (337) 7319
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7170
60.3%
Lowercase Letter 3868
32.5%
Uppercase Letter 477
 
4.0%
Space Separator 300
 
2.5%
Decimal Number 34
 
0.3%
Dash Punctuation 16
 
0.1%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Other Punctuation 9
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
786
 
11.0%
648
 
9.0%
500
 
7.0%
472
 
6.6%
440
 
6.1%
313
 
4.4%
309
 
4.3%
248
 
3.5%
124
 
1.7%
119
 
1.7%
Other values (277) 3211
44.8%
Lowercase Letter
ValueCountFrequency (%)
i 388
10.0%
e 387
10.0%
t 328
 
8.5%
a 312
 
8.1%
o 309
 
8.0%
r 295
 
7.6%
n 253
 
6.5%
l 246
 
6.4%
s 234
 
6.0%
c 166
 
4.3%
Other values (16) 950
24.6%
Uppercase Letter
ValueCountFrequency (%)
A 81
17.0%
P 53
11.1%
C 52
10.9%
D 47
9.9%
M 30
 
6.3%
S 25
 
5.2%
B 25
 
5.2%
H 23
 
4.8%
E 22
 
4.6%
I 18
 
3.8%
Other values (11) 101
21.2%
Decimal Number
ValueCountFrequency (%)
5 10
29.4%
2 9
26.5%
1 7
20.6%
0 3
 
8.8%
3 2
 
5.9%
9 2
 
5.9%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7170
60.3%
Latin 4345
36.5%
Common 378
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
786
 
11.0%
648
 
9.0%
500
 
7.0%
472
 
6.6%
440
 
6.1%
313
 
4.4%
309
 
4.3%
248
 
3.5%
124
 
1.7%
119
 
1.7%
Other values (277) 3211
44.8%
Latin
ValueCountFrequency (%)
i 388
 
8.9%
e 387
 
8.9%
t 328
 
7.5%
a 312
 
7.2%
o 309
 
7.1%
r 295
 
6.8%
n 253
 
5.8%
l 246
 
5.7%
s 234
 
5.4%
c 166
 
3.8%
Other values (37) 1427
32.8%
Common
ValueCountFrequency (%)
300
79.4%
- 16
 
4.2%
5 10
 
2.6%
) 9
 
2.4%
2 9
 
2.4%
( 9
 
2.4%
. 9
 
2.4%
1 7
 
1.9%
0 3
 
0.8%
3 2
 
0.5%
Other values (3) 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7170
60.3%
ASCII 4722
39.7%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
786
 
11.0%
648
 
9.0%
500
 
7.0%
472
 
6.6%
440
 
6.1%
313
 
4.4%
309
 
4.3%
248
 
3.5%
124
 
1.7%
119
 
1.7%
Other values (277) 3211
44.8%
ASCII
ValueCountFrequency (%)
i 388
 
8.2%
e 387
 
8.2%
t 328
 
6.9%
a 312
 
6.6%
o 309
 
6.5%
300
 
6.4%
r 295
 
6.2%
n 253
 
5.4%
l 246
 
5.2%
s 234
 
5.0%
Other values (49) 1670
35.4%
Punctuation
ValueCountFrequency (%)
1
100.0%

핵심키워드3
Text

MISSING 

Distinct691
Distinct (%)41.2%
Missing325
Missing (%)16.2%
Memory size15.8 KiB
2024-04-21T18:49:47.809292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.1056086
Min length1

Characters and Unicode

Total characters10233
Distinct characters365
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)28.5%

Sample

1st rownon-smoker
2nd rowoil spill
3rd rowhazardous score
4th rowchronic exposure
5th rowPM2.5
ValueCountFrequency (%)
미세먼지 134
 
6.6%
노출 36
 
1.8%
교란물질 30
 
1.5%
대기오염물질 30
 
1.5%
내분비계 30
 
1.5%
살충제 29
 
1.4%
어린이 27
 
1.3%
환경보건 24
 
1.2%
수질오염물질 23
 
1.1%
프탈레이트 20
 
1.0%
Other values (756) 1645
81.1%
2024-04-21T18:49:48.926384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 442
 
4.3%
352
 
3.4%
i 348
 
3.4%
a 317
 
3.1%
t 310
 
3.0%
302
 
3.0%
o 297
 
2.9%
s 273
 
2.7%
n 270
 
2.6%
r 258
 
2.5%
Other values (355) 7064
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5537
54.1%
Lowercase Letter 3773
36.9%
Uppercase Letter 489
 
4.8%
Space Separator 352
 
3.4%
Decimal Number 37
 
0.4%
Dash Punctuation 27
 
0.3%
Other Punctuation 8
 
0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Final Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
302
 
5.5%
211
 
3.8%
176
 
3.2%
174
 
3.1%
156
 
2.8%
148
 
2.7%
145
 
2.6%
144
 
2.6%
141
 
2.5%
128
 
2.3%
Other values (293) 3812
68.8%
Lowercase Letter
ValueCountFrequency (%)
e 442
11.7%
i 348
 
9.2%
a 317
 
8.4%
t 310
 
8.2%
o 297
 
7.9%
s 273
 
7.2%
n 270
 
7.2%
r 258
 
6.8%
l 216
 
5.7%
c 150
 
4.0%
Other values (16) 892
23.6%
Uppercase Letter
ValueCountFrequency (%)
A 74
15.1%
P 67
13.7%
C 50
10.2%
S 36
 
7.4%
M 30
 
6.1%
D 27
 
5.5%
F 27
 
5.5%
E 26
 
5.3%
H 25
 
5.1%
I 20
 
4.1%
Other values (13) 107
21.9%
Decimal Number
ValueCountFrequency (%)
1 11
29.7%
5 8
21.6%
2 8
21.6%
0 5
13.5%
7 2
 
5.4%
9 2
 
5.4%
3 1
 
2.7%
Space Separator
ValueCountFrequency (%)
352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5537
54.1%
Latin 4260
41.6%
Common 434
 
4.2%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
302
 
5.5%
211
 
3.8%
176
 
3.2%
174
 
3.1%
156
 
2.8%
148
 
2.7%
145
 
2.6%
144
 
2.6%
141
 
2.5%
128
 
2.3%
Other values (293) 3812
68.8%
Latin
ValueCountFrequency (%)
e 442
 
10.4%
i 348
 
8.2%
a 317
 
7.4%
t 310
 
7.3%
o 297
 
7.0%
s 273
 
6.4%
n 270
 
6.3%
r 258
 
6.1%
l 216
 
5.1%
c 150
 
3.5%
Other values (38) 1379
32.4%
Common
ValueCountFrequency (%)
352
81.1%
- 27
 
6.2%
1 11
 
2.5%
5 8
 
1.8%
. 8
 
1.8%
2 8
 
1.8%
0 5
 
1.2%
) 4
 
0.9%
( 4
 
0.9%
2
 
0.5%
Other values (3) 5
 
1.2%
Greek
ValueCountFrequency (%)
β 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5537
54.1%
ASCII 4692
45.9%
Punctuation 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 442
 
9.4%
352
 
7.5%
i 348
 
7.4%
a 317
 
6.8%
t 310
 
6.6%
o 297
 
6.3%
s 273
 
5.8%
n 270
 
5.8%
r 258
 
5.5%
l 216
 
4.6%
Other values (50) 1609
34.3%
Hangul
ValueCountFrequency (%)
302
 
5.5%
211
 
3.8%
176
 
3.2%
174
 
3.1%
156
 
2.8%
148
 
2.7%
145
 
2.6%
144
 
2.6%
141
 
2.5%
128
 
2.3%
Other values (293) 3812
68.8%
Punctuation
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
β 2
100.0%

핵심키워드4
Text

MISSING 

Distinct520
Distinct (%)53.7%
Missing1033
Missing (%)51.6%
Memory size15.8 KiB
2024-04-21T18:49:49.887004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length6.6663223
Min length1

Characters and Unicode

Total characters6453
Distinct characters329
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique380 ?
Unique (%)39.3%

Sample

1st rowKoNEHS
2nd rowpollution disease
3rd rowregression analysis
4th rowuncertainty
5th rowtank-lorry
ValueCountFrequency (%)
어린이 34
 
2.8%
환경보건 29
 
2.4%
미세먼지 23
 
1.9%
이산화질소 18
 
1.5%
비소 16
 
1.3%
노출 16
 
1.3%
심혈관질환 15
 
1.3%
수질오염물질 13
 
1.1%
중금속 12
 
1.0%
호흡기질환 12
 
1.0%
Other values (585) 1011
84.3%
2024-04-21T18:49:51.117523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 334
 
5.2%
i 298
 
4.6%
t 240
 
3.7%
a 237
 
3.7%
231
 
3.6%
r 222
 
3.4%
o 216
 
3.3%
n 215
 
3.3%
s 177
 
2.7%
163
 
2.5%
Other values (319) 4120
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2884
44.7%
Lowercase Letter 2857
44.3%
Uppercase Letter 401
 
6.2%
Space Separator 231
 
3.6%
Decimal Number 44
 
0.7%
Dash Punctuation 19
 
0.3%
Other Punctuation 10
 
0.2%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
 
5.7%
102
 
3.5%
91
 
3.2%
84
 
2.9%
79
 
2.7%
76
 
2.6%
74
 
2.6%
71
 
2.5%
67
 
2.3%
52
 
1.8%
Other values (257) 2025
70.2%
Lowercase Letter
ValueCountFrequency (%)
e 334
11.7%
i 298
10.4%
t 240
 
8.4%
a 237
 
8.3%
r 222
 
7.8%
o 216
 
7.6%
n 215
 
7.5%
s 177
 
6.2%
l 145
 
5.1%
c 106
 
3.7%
Other values (16) 667
23.3%
Uppercase Letter
ValueCountFrequency (%)
P 61
15.2%
A 47
11.7%
C 40
10.0%
D 33
 
8.2%
M 31
 
7.7%
S 27
 
6.7%
E 24
 
6.0%
T 22
 
5.5%
F 16
 
4.0%
H 16
 
4.0%
Other values (13) 84
20.9%
Decimal Number
ValueCountFrequency (%)
2 14
31.8%
5 10
22.7%
1 8
18.2%
0 5
 
11.4%
3 5
 
11.4%
9 1
 
2.3%
7 1
 
2.3%
Space Separator
ValueCountFrequency (%)
231
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3257
50.5%
Hangul 2884
44.7%
Common 311
 
4.8%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
 
5.7%
102
 
3.5%
91
 
3.2%
84
 
2.9%
79
 
2.7%
76
 
2.6%
74
 
2.6%
71
 
2.5%
67
 
2.3%
52
 
1.8%
Other values (257) 2025
70.2%
Latin
ValueCountFrequency (%)
e 334
 
10.3%
i 298
 
9.1%
t 240
 
7.4%
a 237
 
7.3%
r 222
 
6.8%
o 216
 
6.6%
n 215
 
6.6%
s 177
 
5.4%
l 145
 
4.5%
c 106
 
3.3%
Other values (38) 1067
32.8%
Common
ValueCountFrequency (%)
231
74.3%
- 19
 
6.1%
2 14
 
4.5%
5 10
 
3.2%
. 10
 
3.2%
1 8
 
2.6%
0 5
 
1.6%
3 5
 
1.6%
) 3
 
1.0%
( 3
 
1.0%
Other values (3) 3
 
1.0%
Greek
ValueCountFrequency (%)
β 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3567
55.3%
Hangul 2884
44.7%
Punctuation 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 334
 
9.4%
i 298
 
8.4%
t 240
 
6.7%
a 237
 
6.6%
231
 
6.5%
r 222
 
6.2%
o 216
 
6.1%
n 215
 
6.0%
s 177
 
5.0%
l 145
 
4.1%
Other values (50) 1252
35.1%
Hangul
ValueCountFrequency (%)
163
 
5.7%
102
 
3.5%
91
 
3.2%
84
 
2.9%
79
 
2.7%
76
 
2.6%
74
 
2.6%
71
 
2.5%
67
 
2.3%
52
 
1.8%
Other values (257) 2025
70.2%
Punctuation
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
β 1
100.0%

핵심키워드5
Text

MISSING 

Distinct260
Distinct (%)67.0%
Missing1613
Missing (%)80.6%
Memory size15.8 KiB
2024-04-21T18:49:51.976777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.6546392
Min length1

Characters and Unicode

Total characters2970
Distinct characters251
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique206 ?
Unique (%)53.1%

Sample

1st rowcourt judgment
2nd rowfood group
3rd rowbuilding material
4th rowplants
5th rowsocioeconomic cost
ValueCountFrequency (%)
어린이 20
 
3.9%
환경보건 20
 
3.9%
risk 10
 
1.9%
미세먼지 8
 
1.6%
이산화질소 7
 
1.4%
식수 6
 
1.2%
6
 
1.2%
health 6
 
1.2%
pollution 6
 
1.2%
factors 5
 
1.0%
Other values (307) 420
81.7%
2024-04-21T18:49:53.097370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 170
 
5.7%
i 167
 
5.6%
t 136
 
4.6%
o 129
 
4.3%
126
 
4.2%
r 113
 
3.8%
s 110
 
3.7%
a 107
 
3.6%
n 105
 
3.5%
l 97
 
3.3%
Other values (241) 1710
57.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1596
53.7%
Other Letter 1045
35.2%
Uppercase Letter 185
 
6.2%
Space Separator 126
 
4.2%
Decimal Number 10
 
0.3%
Dash Punctuation 4
 
0.1%
Other Punctuation 3
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
57
 
5.5%
41
 
3.9%
36
 
3.4%
33
 
3.2%
31
 
3.0%
31
 
3.0%
28
 
2.7%
28
 
2.7%
28
 
2.7%
25
 
2.4%
Other values (185) 707
67.7%
Lowercase Letter
ValueCountFrequency (%)
e 170
10.7%
i 167
10.5%
t 136
 
8.5%
o 129
 
8.1%
r 113
 
7.1%
s 110
 
6.9%
a 107
 
6.7%
n 105
 
6.6%
l 97
 
6.1%
c 64
 
4.0%
Other values (16) 398
24.9%
Uppercase Letter
ValueCountFrequency (%)
C 25
13.5%
P 24
13.0%
A 19
10.3%
S 17
9.2%
R 12
 
6.5%
D 11
 
5.9%
F 10
 
5.4%
M 10
 
5.4%
B 10
 
5.4%
E 8
 
4.3%
Other values (12) 39
21.1%
Decimal Number
ValueCountFrequency (%)
2 5
50.0%
5 3
30.0%
3 1
 
10.0%
4 1
 
10.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1781
60.0%
Hangul 1045
35.2%
Common 144
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
57
 
5.5%
41
 
3.9%
36
 
3.4%
33
 
3.2%
31
 
3.0%
31
 
3.0%
28
 
2.7%
28
 
2.7%
28
 
2.7%
25
 
2.4%
Other values (185) 707
67.7%
Latin
ValueCountFrequency (%)
e 170
 
9.5%
i 167
 
9.4%
t 136
 
7.6%
o 129
 
7.2%
r 113
 
6.3%
s 110
 
6.2%
a 107
 
6.0%
n 105
 
5.9%
l 97
 
5.4%
c 64
 
3.6%
Other values (38) 583
32.7%
Common
ValueCountFrequency (%)
126
87.5%
2 5
 
3.5%
- 4
 
2.8%
. 3
 
2.1%
5 3
 
2.1%
3 1
 
0.7%
4 1
 
0.7%
1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1924
64.8%
Hangul 1045
35.2%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 170
 
8.8%
i 167
 
8.7%
t 136
 
7.1%
o 129
 
6.7%
126
 
6.5%
r 113
 
5.9%
s 110
 
5.7%
a 107
 
5.6%
n 105
 
5.5%
l 97
 
5.0%
Other values (45) 664
34.5%
Hangul
ValueCountFrequency (%)
57
 
5.5%
41
 
3.9%
36
 
3.4%
33
 
3.2%
31
 
3.0%
31
 
3.0%
28
 
2.7%
28
 
2.7%
28
 
2.7%
25
 
2.4%
Other values (185) 707
67.7%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct631
Distinct (%)31.6%
Missing1
Missing (%)< 0.1%
Memory size15.8 KiB
2024-04-21T18:49:53.913675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length4
Mean length4.509
Min length1

Characters and Unicode

Total characters9018
Distinct characters398
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)18.0%

Sample

1st row휘발성유기화합물
2nd row코티닌
3rd row환경보건지표
4th row가습기살균제
5th row화학물질 이동량 및 배출량
ValueCountFrequency (%)
건강영향 492
 
21.5%
어린이 41
 
1.8%
산모영향 37
 
1.6%
대기오염 34
 
1.5%
아토피피부염 31
 
1.4%
건강보호 31
 
1.4%
노출평가 26
 
1.1%
미세먼지 26
 
1.1%
천식 20
 
0.9%
노출영향 19
 
0.8%
Other values (675) 1530
66.9%
2024-04-21T18:49:54.967450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
 
6.6%
590
 
6.5%
565
 
6.3%
549
 
6.1%
287
 
3.2%
223
 
2.5%
175
 
1.9%
150
 
1.7%
142
 
1.6%
119
 
1.3%
Other values (388) 5627
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8504
94.3%
Space Separator 287
 
3.2%
Uppercase Letter 130
 
1.4%
Decimal Number 59
 
0.7%
Other Punctuation 19
 
0.2%
Lowercase Letter 12
 
0.1%
Dash Punctuation 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
591
 
6.9%
590
 
6.9%
565
 
6.6%
549
 
6.5%
223
 
2.6%
175
 
2.1%
150
 
1.8%
142
 
1.7%
119
 
1.4%
118
 
1.4%
Other values (352) 5282
62.1%
Uppercase Letter
ValueCountFrequency (%)
P 31
23.8%
M 26
20.0%
A 20
15.4%
D 15
11.5%
N 9
 
6.9%
B 5
 
3.8%
C 5
 
3.8%
O 5
 
3.8%
E 3
 
2.3%
F 3
 
2.3%
Other values (6) 8
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
25.0%
n 2
16.7%
a 1
 
8.3%
x 1
 
8.3%
z 1
 
8.3%
l 1
 
8.3%
y 1
 
8.3%
h 1
 
8.3%
t 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 21
35.6%
5 19
32.2%
1 9
15.3%
0 6
 
10.2%
9 3
 
5.1%
3 1
 
1.7%
Space Separator
ValueCountFrequency (%)
287
100.0%
Other Punctuation
ValueCountFrequency (%)
. 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8504
94.3%
Common 372
 
4.1%
Latin 142
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
591
 
6.9%
590
 
6.9%
565
 
6.6%
549
 
6.5%
223
 
2.6%
175
 
2.1%
150
 
1.8%
142
 
1.7%
119
 
1.4%
118
 
1.4%
Other values (352) 5282
62.1%
Latin
ValueCountFrequency (%)
P 31
21.8%
M 26
18.3%
A 20
14.1%
D 15
10.6%
N 9
 
6.3%
B 5
 
3.5%
C 5
 
3.5%
O 5
 
3.5%
E 3
 
2.1%
F 3
 
2.1%
Other values (15) 20
14.1%
Common
ValueCountFrequency (%)
287
77.2%
2 21
 
5.6%
5 19
 
5.1%
. 19
 
5.1%
1 9
 
2.4%
0 6
 
1.6%
- 3
 
0.8%
9 3
 
0.8%
( 2
 
0.5%
) 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8504
94.3%
ASCII 514
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
591
 
6.9%
590
 
6.9%
565
 
6.6%
549
 
6.5%
223
 
2.6%
175
 
2.1%
150
 
1.8%
142
 
1.7%
119
 
1.4%
118
 
1.4%
Other values (352) 5282
62.1%
ASCII
ValueCountFrequency (%)
287
55.8%
P 31
 
6.0%
M 26
 
5.1%
2 21
 
4.1%
A 20
 
3.9%
5 19
 
3.7%
. 19
 
3.7%
D 15
 
2.9%
1 9
 
1.8%
N 9
 
1.8%
Other values (26) 58
 
11.3%

연관키워드2
Text

MISSING 

Distinct639
Distinct (%)35.8%
Missing214
Missing (%)10.7%
Memory size15.8 KiB
2024-04-21T18:49:55.936314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length4.5366536
Min length1

Characters and Unicode

Total characters8107
Distinct characters398
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

Unique385 ?
Unique (%)21.5%

Sample

1st row시화반월단지
2nd row간접흡연
3rd row환경정의
4th row폐놀오염
5th row위험점수
ValueCountFrequency (%)
건강영향 196
 
9.5%
산모영향 76
 
3.7%
어린이 61
 
3.0%
건강보호 47
 
2.3%
노출영향 45
 
2.2%
태아피해 39
 
1.9%
호흡기질환 29
 
1.4%
사망률 25
 
1.2%
농도조사 24
 
1.2%
미세먼지 23
 
1.1%
Other values (677) 1500
72.6%
2024-04-21T18:49:57.127744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
375
 
4.6%
372
 
4.6%
281
 
3.5%
278
 
3.4%
271
 
3.3%
219
 
2.7%
189
 
2.3%
164
 
2.0%
163
 
2.0%
159
 
2.0%
Other values (388) 5636
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7647
94.3%
Space Separator 278
 
3.4%
Uppercase Letter 91
 
1.1%
Lowercase Letter 51
 
0.6%
Decimal Number 26
 
0.3%
Other Punctuation 10
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
375
 
4.9%
372
 
4.9%
281
 
3.7%
271
 
3.5%
219
 
2.9%
189
 
2.5%
164
 
2.1%
163
 
2.1%
159
 
2.1%
135
 
1.8%
Other values (345) 5319
69.6%
Uppercase Letter
ValueCountFrequency (%)
D 18
19.8%
P 15
16.5%
A 15
16.5%
M 12
13.2%
N 7
 
7.7%
H 4
 
4.4%
O 3
 
3.3%
C 3
 
3.3%
T 3
 
3.3%
B 3
 
3.3%
Other values (8) 8
8.8%
Lowercase Letter
ValueCountFrequency (%)
e 10
19.6%
l 8
15.7%
o 4
 
7.8%
h 3
 
5.9%
p 3
 
5.9%
r 3
 
5.9%
n 3
 
5.9%
i 3
 
5.9%
s 2
 
3.9%
a 2
 
3.9%
Other values (7) 10
19.6%
Decimal Number
ValueCountFrequency (%)
5 11
42.3%
2 10
38.5%
1 3
 
11.5%
0 2
 
7.7%
Space Separator
ValueCountFrequency (%)
278
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7647
94.3%
Common 318
 
3.9%
Latin 142
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
375
 
4.9%
372
 
4.9%
281
 
3.7%
271
 
3.5%
219
 
2.9%
189
 
2.5%
164
 
2.1%
163
 
2.1%
159
 
2.1%
135
 
1.8%
Other values (345) 5319
69.6%
Latin
ValueCountFrequency (%)
D 18
 
12.7%
P 15
 
10.6%
A 15
 
10.6%
M 12
 
8.5%
e 10
 
7.0%
l 8
 
5.6%
N 7
 
4.9%
o 4
 
2.8%
H 4
 
2.8%
O 3
 
2.1%
Other values (25) 46
32.4%
Common
ValueCountFrequency (%)
278
87.4%
5 11
 
3.5%
. 10
 
3.1%
2 10
 
3.1%
1 3
 
0.9%
( 2
 
0.6%
) 2
 
0.6%
0 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7647
94.3%
ASCII 460
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
375
 
4.9%
372
 
4.9%
281
 
3.7%
271
 
3.5%
219
 
2.9%
189
 
2.5%
164
 
2.1%
163
 
2.1%
159
 
2.1%
135
 
1.8%
Other values (345) 5319
69.6%
ASCII
ValueCountFrequency (%)
278
60.4%
D 18
 
3.9%
P 15
 
3.3%
A 15
 
3.3%
M 12
 
2.6%
5 11
 
2.4%
e 10
 
2.2%
. 10
 
2.2%
2 10
 
2.2%
l 8
 
1.7%
Other values (33) 73
 
15.9%

연관키워드3
Text

MISSING 

Distinct491
Distinct (%)41.0%
Missing803
Missing (%)40.1%
Memory size15.8 KiB
2024-04-21T18:49:58.086499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length4.4624374
Min length1

Characters and Unicode

Total characters5346
Distinct characters362
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique321 ?
Unique (%)26.8%

Sample

1st row비흡연자
2nd row누적영향
3rd row기름유출
4th row포름알데히드
5th row초미세먼지
ValueCountFrequency (%)
건강영향 80
 
5.8%
태아피해 79
 
5.8%
어린이 43
 
3.1%
건강보호 32
 
2.3%
산모영향 31
 
2.3%
농도조사 24
 
1.8%
노출 18
 
1.3%
노출평가 17
 
1.2%
호흡기질환 16
 
1.2%
천식 14
 
1.0%
Other values (529) 1014
74.1%
2024-04-21T18:49:59.287556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
 
3.2%
159
 
3.0%
157
 
2.9%
146
 
2.7%
137
 
2.6%
133
 
2.5%
130
 
2.4%
113
 
2.1%
108
 
2.0%
101
 
1.9%
Other values (352) 3992
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5052
94.5%
Space Separator 170
 
3.2%
Uppercase Letter 67
 
1.3%
Lowercase Letter 33
 
0.6%
Decimal Number 14
 
0.3%
Other Punctuation 5
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
159
 
3.1%
157
 
3.1%
146
 
2.9%
137
 
2.7%
133
 
2.6%
130
 
2.6%
113
 
2.2%
108
 
2.1%
101
 
2.0%
101
 
2.0%
Other values (310) 3767
74.6%
Uppercase Letter
ValueCountFrequency (%)
P 13
19.4%
D 7
10.4%
A 6
9.0%
C 6
9.0%
M 6
9.0%
O 4
 
6.0%
E 4
 
6.0%
N 3
 
4.5%
V 3
 
4.5%
T 3
 
4.5%
Other values (7) 12
17.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
15.2%
s 4
12.1%
l 4
12.1%
o 3
9.1%
n 3
9.1%
a 2
 
6.1%
g 2
 
6.1%
t 2
 
6.1%
r 2
 
6.1%
u 2
 
6.1%
Other values (4) 4
12.1%
Decimal Number
ValueCountFrequency (%)
2 6
42.9%
5 4
28.6%
1 2
 
14.3%
0 1
 
7.1%
9 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 4
80.0%
/ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
170
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5052
94.5%
Common 194
 
3.6%
Latin 100
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
159
 
3.1%
157
 
3.1%
146
 
2.9%
137
 
2.7%
133
 
2.6%
130
 
2.6%
113
 
2.2%
108
 
2.1%
101
 
2.0%
101
 
2.0%
Other values (310) 3767
74.6%
Latin
ValueCountFrequency (%)
P 13
 
13.0%
D 7
 
7.0%
A 6
 
6.0%
C 6
 
6.0%
M 6
 
6.0%
e 5
 
5.0%
s 4
 
4.0%
O 4
 
4.0%
l 4
 
4.0%
E 4
 
4.0%
Other values (21) 41
41.0%
Common
ValueCountFrequency (%)
170
87.6%
2 6
 
3.1%
. 4
 
2.1%
5 4
 
2.1%
1 2
 
1.0%
( 2
 
1.0%
) 2
 
1.0%
0 1
 
0.5%
9 1
 
0.5%
/ 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5052
94.5%
ASCII 294
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
57.8%
P 13
 
4.4%
D 7
 
2.4%
A 6
 
2.0%
C 6
 
2.0%
M 6
 
2.0%
2 6
 
2.0%
e 5
 
1.7%
s 4
 
1.4%
O 4
 
1.4%
Other values (32) 67
 
22.8%
Hangul
ValueCountFrequency (%)
159
 
3.1%
157
 
3.1%
146
 
2.9%
137
 
2.7%
133
 
2.6%
130
 
2.6%
113
 
2.2%
108
 
2.1%
101
 
2.0%
101
 
2.0%
Other values (310) 3767
74.6%

연관키워드4
Text

MISSING 

Distinct325
Distinct (%)53.9%
Missing1398
Missing (%)69.9%
Memory size15.8 KiB
2024-04-21T18:50:00.272074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length4.4726368
Min length1

Characters and Unicode

Total characters2697
Distinct characters321
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)38.5%

Sample

1st row공해병
2nd row만성노출
3rd row의료용
4th row불확실성
5th row수질기준
ValueCountFrequency (%)
건강영향 29
 
4.2%
어린이 24
 
3.4%
태아피해 22
 
3.2%
산모영향 15
 
2.2%
건강보호 14
 
2.0%
호흡기질환 10
 
1.4%
성장발달 9
 
1.3%
방해 9
 
1.3%
노출평가 7
 
1.0%
조산 7
 
1.0%
Other values (349) 550
79.0%
2024-04-21T18:50:01.494402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
 
3.4%
77
 
2.9%
72
 
2.7%
63
 
2.3%
61
 
2.3%
61
 
2.3%
54
 
2.0%
54
 
2.0%
53
 
2.0%
52
 
1.9%
Other values (311) 2057
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2521
93.5%
Space Separator 93
 
3.4%
Uppercase Letter 45
 
1.7%
Lowercase Letter 27
 
1.0%
Decimal Number 7
 
0.3%
Dash Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
77
 
3.1%
72
 
2.9%
63
 
2.5%
61
 
2.4%
61
 
2.4%
54
 
2.1%
54
 
2.1%
53
 
2.1%
52
 
2.1%
43
 
1.7%
Other values (272) 1931
76.6%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
l 4
14.8%
n 3
11.1%
d 2
 
7.4%
s 2
 
7.4%
z 1
 
3.7%
x 1
 
3.7%
p 1
 
3.7%
m 1
 
3.7%
o 1
 
3.7%
Other values (7) 7
25.9%
Uppercase Letter
ValueCountFrequency (%)
D 8
17.8%
A 7
15.6%
P 6
13.3%
N 5
11.1%
C 4
8.9%
M 3
 
6.7%
T 2
 
4.4%
E 2
 
4.4%
B 2
 
4.4%
H 2
 
4.4%
Other values (3) 4
8.9%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
0 2
28.6%
5 1
 
14.3%
2 1
 
14.3%
Space Separator
ValueCountFrequency (%)
93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2521
93.5%
Common 104
 
3.9%
Latin 72
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
77
 
3.1%
72
 
2.9%
63
 
2.5%
61
 
2.4%
61
 
2.4%
54
 
2.1%
54
 
2.1%
53
 
2.1%
52
 
2.1%
43
 
1.7%
Other values (272) 1931
76.6%
Latin
ValueCountFrequency (%)
D 8
 
11.1%
A 7
 
9.7%
P 6
 
8.3%
N 5
 
6.9%
e 4
 
5.6%
l 4
 
5.6%
C 4
 
5.6%
n 3
 
4.2%
M 3
 
4.2%
d 2
 
2.8%
Other values (20) 26
36.1%
Common
ValueCountFrequency (%)
93
89.4%
1 3
 
2.9%
0 2
 
1.9%
- 1
 
1.0%
5 1
 
1.0%
. 1
 
1.0%
2 1
 
1.0%
) 1
 
1.0%
( 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2521
93.5%
ASCII 176
 
6.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
52.8%
D 8
 
4.5%
A 7
 
4.0%
P 6
 
3.4%
N 5
 
2.8%
e 4
 
2.3%
l 4
 
2.3%
C 4
 
2.3%
n 3
 
1.7%
1 3
 
1.7%
Other values (29) 39
22.2%
Hangul
ValueCountFrequency (%)
77
 
3.1%
72
 
2.9%
63
 
2.5%
61
 
2.4%
61
 
2.4%
54
 
2.1%
54
 
2.1%
53
 
2.1%
52
 
2.1%
43
 
1.7%
Other values (272) 1931
76.6%

연관키워드5
Text

MISSING 

Distinct151
Distinct (%)70.6%
Missing1787
Missing (%)89.3%
Memory size15.8 KiB
2024-04-21T18:50:02.554383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.4906542
Min length2

Characters and Unicode

Total characters961
Distinct characters245
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)56.5%

Sample

1st row회귀분석
2nd row법원판결
3rd row식품군
4th row테레프탈레이트
5th row건축자재
ValueCountFrequency (%)
태아피해 12
 
4.8%
미세먼지 8
 
3.2%
신경발달 6
 
2.4%
어린이 6
 
2.4%
성장발달 5
 
2.0%
방해 5
 
2.0%
건강보호 5
 
2.0%
모니터링 4
 
1.6%
호흡기질환 4
 
1.6%
위험평가 4
 
1.6%
Other values (158) 189
76.2%
2024-04-21T18:50:03.810699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
3.5%
27
 
2.8%
23
 
2.4%
22
 
2.3%
21
 
2.2%
21
 
2.2%
20
 
2.1%
19
 
2.0%
16
 
1.7%
15
 
1.6%
Other values (235) 743
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 903
94.0%
Space Separator 34
 
3.5%
Uppercase Letter 13
 
1.4%
Lowercase Letter 5
 
0.5%
Decimal Number 4
 
0.4%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
27
 
3.0%
23
 
2.5%
22
 
2.4%
21
 
2.3%
21
 
2.3%
20
 
2.2%
19
 
2.1%
16
 
1.8%
15
 
1.7%
15
 
1.7%
Other values (214) 704
78.0%
Uppercase Letter
ValueCountFrequency (%)
P 3
23.1%
A 2
15.4%
V 1
 
7.7%
M 1
 
7.7%
C 1
 
7.7%
O 1
 
7.7%
B 1
 
7.7%
E 1
 
7.7%
N 1
 
7.7%
D 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
h 1
20.0%
g 1
20.0%
n 1
20.0%
o 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 903
94.0%
Common 40
 
4.2%
Latin 18
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
27
 
3.0%
23
 
2.5%
22
 
2.4%
21
 
2.3%
21
 
2.3%
20
 
2.2%
19
 
2.1%
16
 
1.8%
15
 
1.7%
15
 
1.7%
Other values (214) 704
78.0%
Latin
ValueCountFrequency (%)
P 3
16.7%
A 2
 
11.1%
V 1
 
5.6%
M 1
 
5.6%
C 1
 
5.6%
O 1
 
5.6%
a 1
 
5.6%
B 1
 
5.6%
h 1
 
5.6%
g 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
34
85.0%
2 2
 
5.0%
5 1
 
2.5%
. 1
 
2.5%
- 1
 
2.5%
1 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 903
94.0%
ASCII 58
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
58.6%
P 3
 
5.2%
A 2
 
3.4%
2 2
 
3.4%
V 1
 
1.7%
5 1
 
1.7%
. 1
 
1.7%
M 1
 
1.7%
C 1
 
1.7%
O 1
 
1.7%
Other values (11) 11
 
19.0%
Hangul
ValueCountFrequency (%)
27
 
3.0%
23
 
2.5%
22
 
2.4%
21
 
2.3%
21
 
2.3%
20
 
2.2%
19
 
2.1%
16
 
1.8%
15
 
1.7%
15
 
1.7%
Other values (214) 704
78.0%

발행처
Text

MISSING 

Distinct255
Distinct (%)13.4%
Missing92
Missing (%)4.6%
Memory size15.8 KiB
2024-04-21T18:50:04.558349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length9.151912
Min length1

Characters and Unicode

Total characters17471
Distinct characters182
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

Unique175 ?
Unique (%)9.2%

Sample

1st row한국환경보건학회
2nd row한국환경보건학회
3rd row한국환경보건학회
4th row한국환경보건학회
5th row한국환경보건학회
ValueCountFrequency (%)
ijerph 619
24.6%
environmental 417
16.6%
health 417
16.6%
ehp 317
12.6%
한국환경보건학회지 68
 
2.7%
한국환경보건학회 48
 
1.9%
jkms 14
 
0.6%
한국냄새환경학회 13
 
0.5%
aair 12
 
0.5%
12
 
0.5%
Other values (299) 576
22.9%
2024-04-21T18:50:05.575945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1339
 
7.7%
e 1273
 
7.3%
E 1166
 
6.7%
h 926
 
5.3%
a 919
 
5.3%
H 915
 
5.2%
t 913
 
5.2%
l 896
 
5.1%
I 695
 
4.0%
J 694
 
4.0%
Other values (172) 7735
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9264
53.0%
Uppercase Letter 5393
30.9%
Other Letter 2192
 
12.5%
Space Separator 606
 
3.5%
Other Punctuation 8
 
< 0.1%
Decimal Number 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
241
11.0%
240
10.9%
206
 
9.4%
183
 
8.3%
181
 
8.3%
178
 
8.1%
127
 
5.8%
127
 
5.8%
108
 
4.9%
49
 
2.2%
Other values (118) 552
25.2%
Lowercase Letter
ValueCountFrequency (%)
n 1339
14.5%
e 1273
13.7%
h 926
10.0%
a 919
9.9%
t 913
9.9%
l 896
9.7%
r 513
 
5.5%
o 511
 
5.5%
i 511
 
5.5%
m 446
 
4.8%
Other values (13) 1017
11.0%
Uppercase Letter
ValueCountFrequency (%)
E 1166
21.6%
H 915
17.0%
I 695
12.9%
J 694
12.9%
R 693
12.8%
P 693
12.8%
A 134
 
2.5%
S 81
 
1.5%
T 65
 
1.2%
M 63
 
1.2%
Other values (13) 194
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 3
37.5%
' 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 3
60.0%
1 2
40.0%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14657
83.9%
Hangul 2192
 
12.5%
Common 622
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
241
11.0%
240
10.9%
206
 
9.4%
183
 
8.3%
181
 
8.3%
178
 
8.1%
127
 
5.8%
127
 
5.8%
108
 
4.9%
49
 
2.2%
Other values (118) 552
25.2%
Latin
ValueCountFrequency (%)
n 1339
 
9.1%
e 1273
 
8.7%
E 1166
 
8.0%
h 926
 
6.3%
a 919
 
6.3%
H 915
 
6.2%
t 913
 
6.2%
l 896
 
6.1%
I 695
 
4.7%
J 694
 
4.7%
Other values (36) 4921
33.6%
Common
ValueCountFrequency (%)
606
97.4%
. 4
 
0.6%
, 3
 
0.5%
2 3
 
0.5%
- 2
 
0.3%
1 2
 
0.3%
' 1
 
0.2%
( 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15279
87.5%
Hangul 2192
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1339
 
8.8%
e 1273
 
8.3%
E 1166
 
7.6%
h 926
 
6.1%
a 919
 
6.0%
H 915
 
6.0%
t 913
 
6.0%
l 896
 
5.9%
I 695
 
4.5%
J 694
 
4.5%
Other values (44) 5543
36.3%
Hangul
ValueCountFrequency (%)
241
11.0%
240
10.9%
206
 
9.4%
183
 
8.3%
181
 
8.3%
178
 
8.1%
127
 
5.8%
127
 
5.8%
108
 
4.9%
49
 
2.2%
Other values (118) 552
25.2%

발행년도
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)0.9%
Missing92
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean2018.2991
Minimum2006
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-04-21T18:50:05.769859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2013
Q12018
median2018
Q32020
95-th percentile2021
Maximum2022
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.2573208
Coefficient of variation (CV)0.0011184273
Kurtosis4.7800755
Mean2018.2991
Median Absolute Deviation (MAD)1
Skewness-1.7891634
Sum3852933
Variance5.0954971
MonotonicityNot monotonic
2024-04-21T18:50:05.979417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2018 649
32.4%
2019 438
21.9%
2020 317
15.8%
2021 125
 
6.2%
2017 106
 
5.3%
2022 62
 
3.1%
2012 44
 
2.2%
2016 41
 
2.0%
2014 33
 
1.6%
2015 30
 
1.5%
Other values (7) 64
 
3.2%
(Missing) 92
 
4.6%
ValueCountFrequency (%)
2006 1
 
< 0.1%
2007 3
 
0.1%
2008 6
 
0.3%
2009 5
 
0.2%
2010 7
 
0.3%
2011 17
 
0.8%
2012 44
2.2%
2013 25
1.2%
2014 33
1.6%
2015 30
1.5%
ValueCountFrequency (%)
2022 62
 
3.1%
2021 125
 
6.2%
2020 317
15.8%
2019 438
21.9%
2018 649
32.4%
2017 106
 
5.3%
2016 41
 
2.0%
2015 30
 
1.5%
2014 33
 
1.6%
2013 25
 
1.2%

Interactions

2024-04-21T18:49:38.376342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T18:50:06.136765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분발행년도
구분1.0000.598
발행년도0.5981.000
2024-04-21T18:50:06.272651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발행년도구분
발행년도1.0000.464
구분0.4641.000

Missing values

2024-04-21T18:49:38.786346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T18:49:39.238420image/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.
2024-04-21T18:49:39.536247image/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

구분제목핵심키워드1핵심키워드2핵심키워드3핵심키워드4핵심키워드5연관키워드1연관키워드2연관키워드3연관키워드4연관키워드5발행처발행년도
0국내연구논문시흥 · 안산 산단 및 영향지역의 휘발성유기화합물질(VOCs) 분포 특성VOCsaffected area<NA><NA><NA>휘발성유기화합물시화반월단지<NA><NA><NA>한국환경보건학회2020
1국내연구논문우리나라 성인 중 비흡연자에 대한 코티닌 노출수준 및 영향요인 분석 - 국민환경보건 기초조사(2009-2017) 결과 -Cotininesecondhand smokenon-smokerKoNEHS<NA>코티닌간접흡연비흡연자<NA><NA>한국환경보건학회2020
2국내연구논문다중 영향 및 환경정의를 고려한 지역 환경보건수준 평가 사례연구cumulative impactEnvironmental health<NA><NA><NA>환경보건지표환경정의누적영향<NA><NA>한국환경보건학회2020
3국내연구논문국내 주요 환경보건 재난의 전개 과정과 그 교훈, 그리고 환경보건 전문가의 역할Humidifier disinfectphenol contaminationoil spillpollution disease<NA>가습기살균제폐놀오염기름유출공해병<NA>한국환경보건학회2022
4국내연구논문화학물질 배출·이동량 자료를 이용한 유해기반 지수의 시공간 특성 연구PRTR(화학물질 배출 및 이동량)RSEIhazardous score<NA><NA>화학물질 이동량 및 배출량위험점수<NA><NA><NA>한국환경보건학회2021
5국내연구논문화학사고물질 노출에 따른 피해지역 주민 건강위해성평가: 폼알데하이드 사례를 중심으로Chemical accidentformaldehydechronic exposure<NA><NA>화학사고건강위험평가포름알데히드만성노출<NA>한국환경보건학회2021
6국내연구논문미세먼지 발생 레미콘시설에서의 대기확산모델 CALPUFF와 AERMOD 비교 분석AERMODPM10PM2.5<NA><NA>대기분산모델미세먼지초미세먼지<NA><NA>한국환경보건학회2021
7국내연구논문대기오염물질과 환경성 질환 관련 의료이용률과의 연관성 - 일반거주지역을 대상으로 -Air pollutantscorrelation analysismedical usageregression analysis<NA>대기오염물질상관분석환경성질환의료용회귀분석한국환경보건학회2021
8국내연구논문CMIT/MIT 함유 가습기 살균제 제품의 제조 및 판매기업 형사판결 1심 재판 판결문에 대한 과학적 고찰 (II) - 동물실험, 폐 손상 판정기준, 개인 인과CMIT/MIThumidifier disinfectcausalityuncertaintycourt judgment가습기살균제가습기살균제 관련 폐 손상인과관계불확실성법원판결한국환경보건학회2021
9국내연구논문석유화학단지 주변 주거지역 다환방향족탄화수소(PAHs)의 농도와 Monte-Carlo 모의실험을 통한 위해성평가Monte-carloPAHsrisk assessment<NA><NA>위험평가다환방향족탄화수소<NA><NA><NA>한국환경보건학회2021
구분제목핵심키워드1핵심키워드2핵심키워드3핵심키워드4핵심키워드5연관키워드1연관키워드2연관키워드3연관키워드4연관키워드5발행처발행년도
1991국외연구논문Submicron fungal fragments as another indoor biocontaminant in elementary schools실내공기학교곰팡이<NA><NA>초등학교<NA><NA><NA><NA><NA><NA>
1992국외연구논문Performance IQ in children is associated with blood cadmium concentration in early pregnancy어린이산모혈액카드뮴<NA>모자환경보건센터<NA><NA><NA><NA><NA><NA>
1993국외연구논문Long-range transport of air pollutants originating in China: A Possible major cause of multi-day high-PM10 episodes during cold season in Seoul, Korea중국장거리이동대기오염물질PM10<NA><NA>대기질 영향<NA><NA><NA><NA><NA><NA>
1994국외연구논문Predicting long-term change of groundwater level with regional climate model in South Korea기후변화지하수하천강수량<NA>기후모델<NA><NA><NA><NA><NA><NA>
1995국외연구논문Evaluation of toxicity to triclosan in rats following 28 days of exposure to aerosol inhalation에어로졸독성물질아만성 독성<NA><NA>트리클로산흡입<NA><NA><NA><NA><NA>
1996국외연구논문Temporal changes in urinary levels of cadmium, N-acetyl-β-d-glucosaminidase and β2-microglobulin in individuals in a cadmium-contaminated area카드뮴소변<NA><NA><NA>중금속독성<NA><NA><NA><NA><NA>
1997국외연구논문The association between ambient temperature and children’s lungfunction in Baotou, China중국어린이폐기능온도<NA>패널연구건강영향<NA><NA><NA><NA><NA>
1998국외연구논문Occurrence and removal of hazardous chemicals and toxic metals in 27 industrial wastewater treatment plants in Korea유해화학물질독성물질중금속산업폐수<NA>벤젠수은비소11-디클로로에틸렌<NA><NA>
1999국외연구논문Didecyldimethylammonium chloride induces oxidative stress and inhibits cell growth in lung epithelial cellsDDAC폐 상피세포폐섬유화폐독성<NA>유해화학물질화학물질<NA><NA><NA><NA><NA>
2000국외연구논문The Effects of Different Noise Types on Heart Rate Variability in Men소음심박수 영향자율신경계<NA><NA>건강영향<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분제목핵심키워드1핵심키워드2핵심키워드3핵심키워드4핵심키워드5연관키워드1연관키워드2연관키워드3연관키워드4연관키워드5발행처발행년도# duplicates
0국외연구논문Air pollution in the week prior to delivery and preterm birth in 24 Canadian cities: a time to event analysis대기오염대기오염물질<NA><NA><NA>건강영향조산산모영향태아피해<NA>Environmental health20192
1국외연구논문Arsenic Metabolism in Mice Carrying a BORCS7/AS3MT Locus Humanized by Syntenic Replacement물환경수질오염수질오염물질식수비소건강영향<NA><NA><NA><NA>ehp20202
2국외연구논문Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis대기오염물질대기오염알레르기 질환도로오염물질<NA>미세먼지이산화질소초미세먼지아토피피부염알레르기비염Environmental health20202
3국외연구논문Association of low-level blood lead with serum uric acid in U.S. adolescents: a cross-sectional study화학물질유해화학물질청소년<NA>건강영향<NA><NA><NA><NA>Environmental health20192
4국외연구논문Associations between High Temperature, Heavy Rainfall, and Diarrhea among Young Children in Rural Tamil Nadu, India: A Prospective Cohort Study기후변화이상고온폭우수질오염어린이 환경보건설사어린이 건강보호건강영향<NA><NA>ehp20192
5국외연구논문Cadmium, Smoking, and Human Blood DNA Methylation Profiles in Adults from the Strong Heart Study실내공기오염물질실내공기질담배담배연기카드뮴DNA후성유전체<NA><NA><NA>ehp20202
6국외연구논문Co-Benefits to Children’s Health of the U.S. Regional Greenhouse Gas Initiative기후변화대기오염물질대기오염어린이 환경보건<NA>기후변화 관리어린이 건강보호<NA><NA><NA>ehp20202
7국외연구논문Comparison of Toxic Metal Distribution Characteristics and Health Risk between Cultured and Wild Fish Captured from Honghu City, China물환경수질오염수질오염물질중금속어류독성건강영향발암위험성<NA><NA><NA>IJERPH20182
8국외연구논문Critical Windows for Associations between Manganese Exposure during Pregnancy and Size at Birth: A Longitudinal Cohort Study in Wuhan, China유해화학물질화학물질망간<NA><NA>태아피해산모영향성장발달 방해<NA><NA>ehp20202
9국외연구논문Determinants of arsenic methylation efficiency and urinary arsenic level in pregnant women in Bangladesh물환경먹는물식수비소<NA>건강영향산모영향태아피해<NA><NA>Environmental health20202