Overview

Dataset statistics

Number of variables3
Number of observations32
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory900.0 B
Average record size in memory28.1 B

Variable types

Text2
Categorical1

Dataset

Description경기도여성가족재단 연속간행물 구독 목록
Author경기도여성가족재단
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=LN2OHEQYBNYS095RROTO31545649&infSeq=1

Alerts

연속간행물명 has unique valuesUnique

Reproduction

Analysis started2024-04-29 13:25:09.414367
Analysis finished2024-04-29 13:25:11.087182
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연속간행물명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-29T22:25:11.231208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23
Mean length9.96875
Min length4

Characters and Unicode

Total characters319
Distinct characters105
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

Unique32 ?
Unique (%)100.0%

Sample

1st row여성신문
2nd row농촌여성신문
3rd row인천여성가족재단 정책브리프 (IFWF Brief)
4th row부산여성가족 BRIEF
5th row대구여성가족 브리핑
ValueCountFrequency (%)
brief 7
 
11.3%
울산여성가족 2
 
3.2%
issue 2
 
3.2%
브리핑 2
 
3.2%
브리프 2
 
3.2%
여성신문 1
 
1.6%
경기저널 1
 
1.6%
프론티어 1
 
1.6%
경기여성 1
 
1.6%
젠더리뷰 1
 
1.6%
Other values (42) 42
67.7%
2024-04-29T22:25:11.622701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
9.4%
성 17
 
5.3%
여 16
 
5.0%
가 10
 
3.1%
정 9
 
2.8%
족 9
 
2.8%
e 8
 
2.5%
책 8
 
2.5%
B 8
 
2.5%
리 7
 
2.2%
Other values (95) 197
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 215
67.4%
Uppercase Letter 38
 
11.9%
Space Separator 30
 
9.4%
Lowercase Letter 29
 
9.1%
Open Punctuation 3
 
0.9%
Close Punctuation 3
 
0.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 17
 
7.9%
여 16
 
7.4%
가 10
 
4.7%
정 9
 
4.2%
족 9
 
4.2%
책 8
 
3.7%
리 7
 
3.3%
경 6
 
2.8%
육 6
 
2.8%
구 5
 
2.3%
Other values (72) 122
56.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
21.1%
I 7
18.4%
F 7
18.4%
E 4
10.5%
R 3
 
7.9%
S 2
 
5.3%
W 2
 
5.3%
G 2
 
5.3%
U 1
 
2.6%
J 1
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
e 8
27.6%
r 6
20.7%
f 5
17.2%
i 5
17.2%
s 2
 
6.9%
d 1
 
3.4%
n 1
 
3.4%
u 1
 
3.4%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 215
67.4%
Latin 67
 
21.0%
Common 37
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 17
 
7.9%
여 16
 
7.4%
가 10
 
4.7%
정 9
 
4.2%
족 9
 
4.2%
책 8
 
3.7%
리 7
 
3.3%
경 6
 
2.8%
육 6
 
2.8%
구 5
 
2.3%
Other values (72) 122
56.7%
Latin
ValueCountFrequency (%)
e 8
11.9%
B 8
11.9%
I 7
10.4%
F 7
10.4%
r 6
9.0%
f 5
7.5%
i 5
7.5%
E 4
 
6.0%
R 3
 
4.5%
S 2
 
3.0%
Other values (9) 12
17.9%
Common
ValueCountFrequency (%)
30
81.1%
( 3
 
8.1%
) 3
 
8.1%
& 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 215
67.4%
ASCII 104
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
28.8%
e 8
 
7.7%
B 8
 
7.7%
I 7
 
6.7%
F 7
 
6.7%
r 6
 
5.8%
f 5
 
4.8%
i 5
 
4.8%
E 4
 
3.8%
( 3
 
2.9%
Other values (13) 21
20.2%
Hangul
ValueCountFrequency (%)
성 17
 
7.9%
여 16
 
7.4%
가 10
 
4.7%
정 9
 
4.2%
족 9
 
4.2%
책 8
 
3.7%
리 7
 
3.3%
경 6
 
2.8%
육 6
 
2.8%
구 5
 
2.3%
Other values (72) 122
56.7%

발간기관
Text

Distinct26
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-04-29T22:25:11.846632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.59375
Min length4

Characters and Unicode

Total characters275
Distinct characters69
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)65.6%

Sample

1st row여성신문사
2nd row농촌여성신문사
3rd row인천여성가족재단
4th row부산여성가족개발원
5th row대구여성가족재단
ValueCountFrequency (%)
육아정책연구소 3
 
8.6%
재)경기도교육연구원 2
 
5.7%
울산여성가족개발원 2
 
5.7%
한국여성정책연구원 2
 
5.7%
전북연구원 2
 
5.7%
부산여성가족개발원 2
 
5.7%
사)경기언론인클럽 1
 
2.9%
이화여자대학교 1
 
2.9%
여성신문사 1
 
2.9%
경기도청 1
 
2.9%
Other values (18) 18
51.4%
2024-04-29T22:25:12.175968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
여 19
 
6.9%
성 18
 
6.5%
구 14
 
5.1%
원 14
 
5.1%
연 13
 
4.7%
가 11
 
4.0%
족 10
 
3.6%
경 9
 
3.3%
정 8
 
2.9%
기 7
 
2.5%
Other values (59) 152
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 264
96.0%
Close Punctuation 4
 
1.5%
Open Punctuation 4
 
1.5%
Space Separator 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 19
 
7.2%
성 18
 
6.8%
구 14
 
5.3%
원 14
 
5.3%
연 13
 
4.9%
가 11
 
4.2%
족 10
 
3.8%
경 9
 
3.4%
정 8
 
3.0%
기 7
 
2.7%
Other values (56) 141
53.4%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 264
96.0%
Common 11
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 19
 
7.2%
성 18
 
6.8%
구 14
 
5.3%
원 14
 
5.3%
연 13
 
4.9%
가 11
 
4.2%
족 10
 
3.8%
경 9
 
3.4%
정 8
 
3.0%
기 7
 
2.7%
Other values (56) 141
53.4%
Common
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 264
96.0%
ASCII 11
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
여 19
 
7.2%
성 18
 
6.8%
구 14
 
5.3%
원 14
 
5.3%
연 13
 
4.9%
가 11
 
4.2%
족 10
 
3.8%
경 9
 
3.4%
정 8
 
3.0%
기 7
 
2.7%
Other values (56) 141
53.4%
ASCII
ValueCountFrequency (%)
) 4
36.4%
( 4
36.4%
3
27.3%

발행주기
Categorical

Distinct7
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
계간
11 
격월간
8 
월간
5 
반년간
3 
주간
2 
Other values (2)
3 

Length

Max length3
Median length2
Mean length2.4375
Min length2

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st row주간
2nd row주간
3rd row월간
4th row계간
5th row계간

Common Values

ValueCountFrequency (%)
계간 11
34.4%
격월간 8
25.0%
월간 5
15.6%
반년간 3
 
9.4%
주간 2
 
6.2%
격주간 2
 
6.2%
연3회 1
 
3.1%

Length

2024-04-29T22:25:12.312525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T22:25:12.445924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계간 11
34.4%
격월간 8
25.0%
월간 5
15.6%
반년간 3
 
9.4%
주간 2
 
6.2%
격주간 2
 
6.2%
연3회 1
 
3.1%

Correlations

2024-04-29T22:25:12.534436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연속간행물명발간기관발행주기
연속간행물명1.0001.0001.000
발간기관1.0001.0000.760
발행주기1.0000.7601.000

Missing values

2024-04-29T22:25:10.946023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-29T22:25:11.052074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연속간행물명발간기관발행주기
0여성신문여성신문사주간
1농촌여성신문농촌여성신문사주간
2인천여성가족재단 정책브리프 (IFWF Brief)인천여성가족재단월간
3부산여성가족 BRIEF부산여성가족개발원계간
4대구여성가족 브리핑대구여성가족재단계간
5Gender Brief (광주여성가족재단 성평등 정책 이슈)광주여성가족재단격월간
6여성우리부산여성가족개발원반년간
7울산여성가족 BRIEF울산여성가족개발원격월간
8경상남도 여성가족정책 브리프경상남도여성가족재단격월간
9경북여성가족정책 브리핑경북여성정책개발원격월간
연속간행물명발간기관발행주기
22공동육아공동육아와공동체교육계간
23울산여성가족 젠더이슈톡톡울산여성가족개발원격월간
24경기도의회경기도의회격월간
25나의 경기도경기도청월간
26교육시선 오늘(재)경기도교육연구원격월간
27통계로 보는 오늘의 교육(재)경기도교육연구원계간
28육아정책포럼육아정책연구소계간
29육아정책연구육아정책연구소연3회
30육아정책 Brief육아정책연구소계간
31이화젠더법학이화여자대학교 젠더법학연구소계간