Overview

Dataset statistics

Number of variables5
Number of observations63
Missing cells10
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory43.1 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description한국공예디자인문화진흥원 아카이브센터의 공공디자인 도서 목록 데이터로 도서구분, 제목, 저자, 발행처, 발행연도 항목을 제공합니다.
Author한국공예디자인문화진흥원
URLhttps://www.data.go.kr/data/15072434/fileData.do

Alerts

도서구분 has constant value ""Constant
발행연도 has 10 (15.9%) missing valuesMissing
제목 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:51:33.753558
Analysis finished2023-12-12 14:51:34.618603
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도서구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
공공디자인
63 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공디자인 63
100.0%

Length

2023-12-12T23:51:34.710502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:51:34.830314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공디자인 63
100.0%

제목
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T23:51:35.153459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length48
Mean length37.428571
Min length8

Characters and Unicode

Total characters2358
Distinct characters293
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row도시환경과 벽화디자인
2nd row멋진 신세계, 꽃이 피다:"도시가 작품이다" 서울시 도시갤러리 프로젝트
3rd row메트로폴리스 : 아방가르드 예술과 건축에 관한 13가지 주제 /
4th row한국 도시디자인 탐사: 광역시의 정체성을 찾아서
5th row서울을 디자인한다 = Designing seoul :디자인 서울의 22원칙
ValueCountFrequency (%)
58
 
12.1%
디자인 24
 
5.0%
design 21
 
4.4%
the 17
 
3.5%
도시 14
 
2.9%
시티 9
 
1.9%
앤 9
 
1.9%
더 9
 
1.9%
city[비디오녹화자료 8
 
1.7%
public 7
 
1.5%
Other values (244) 303
63.3%
2023-12-12T23:51:35.753483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
531
22.5%
e 77
 
3.3%
i 70
 
3.0%
n 67
 
2.8%
자 58
 
2.5%
디 57
 
2.4%
인 55
 
2.3%
시 55
 
2.3%
t 46
 
2.0%
: 41
 
1.7%
Other values (283) 1301
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 987
41.9%
Lowercase Letter 599
25.4%
Space Separator 531
22.5%
Other Punctuation 93
 
3.9%
Uppercase Letter 52
 
2.2%
Math Symbol 23
 
1.0%
Decimal Number 23
 
1.0%
Close Punctuation 22
 
0.9%
Open Punctuation 22
 
0.9%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 58
 
5.9%
디 57
 
5.8%
인 55
 
5.6%
시 55
 
5.6%
도 40
 
4.1%
공 33
 
3.3%
이 24
 
2.4%
의 19
 
1.9%
서 16
 
1.6%
기 15
 
1.5%
Other values (219) 615
62.3%
Lowercase Letter
ValueCountFrequency (%)
e 77
12.9%
i 70
11.7%
n 67
11.2%
t 46
 
7.7%
a 38
 
6.3%
s 33
 
5.5%
r 32
 
5.3%
g 32
 
5.3%
o 28
 
4.7%
c 26
 
4.3%
Other values (13) 150
25.0%
Uppercase Letter
ValueCountFrequency (%)
D 15
28.8%
R 5
 
9.6%
U 5
 
9.6%
S 4
 
7.7%
T 4
 
7.7%
P 4
 
7.7%
A 3
 
5.8%
L 2
 
3.8%
C 2
 
3.8%
N 1
 
1.9%
Other values (7) 7
13.5%
Decimal Number
ValueCountFrequency (%)
1 6
26.1%
2 5
21.7%
0 4
17.4%
3 2
 
8.7%
7 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
4 1
 
4.3%
6 1
 
4.3%
5 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
: 41
44.1%
/ 14
 
15.1%
, 12
 
12.9%
. 11
 
11.8%
& 10
 
10.8%
' 3
 
3.2%
" 2
 
2.2%
Close Punctuation
ValueCountFrequency (%)
] 11
50.0%
) 11
50.0%
Open Punctuation
ValueCountFrequency (%)
[ 11
50.0%
( 11
50.0%
Space Separator
ValueCountFrequency (%)
531
100.0%
Math Symbol
ValueCountFrequency (%)
= 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 984
41.7%
Common 720
30.5%
Latin 651
27.6%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 58
 
5.9%
디 57
 
5.8%
인 55
 
5.6%
시 55
 
5.6%
도 40
 
4.1%
공 33
 
3.4%
이 24
 
2.4%
의 19
 
1.9%
서 16
 
1.6%
기 15
 
1.5%
Other values (216) 612
62.2%
Latin
ValueCountFrequency (%)
e 77
 
11.8%
i 70
 
10.8%
n 67
 
10.3%
t 46
 
7.1%
a 38
 
5.8%
s 33
 
5.1%
r 32
 
4.9%
g 32
 
4.9%
o 28
 
4.3%
c 26
 
4.0%
Other values (30) 202
31.0%
Common
ValueCountFrequency (%)
531
73.8%
: 41
 
5.7%
= 23
 
3.2%
/ 14
 
1.9%
, 12
 
1.7%
. 11
 
1.5%
] 11
 
1.5%
[ 11
 
1.5%
( 11
 
1.5%
) 11
 
1.5%
Other values (14) 44
 
6.1%
Han
ValueCountFrequency (%)
公 1
33.3%
共 1
33.3%
新 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1371
58.1%
Hangul 984
41.7%
CJK 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
531
38.7%
e 77
 
5.6%
i 70
 
5.1%
n 67
 
4.9%
t 46
 
3.4%
: 41
 
3.0%
a 38
 
2.8%
s 33
 
2.4%
r 32
 
2.3%
g 32
 
2.3%
Other values (54) 404
29.5%
Hangul
ValueCountFrequency (%)
자 58
 
5.9%
디 57
 
5.8%
인 55
 
5.6%
시 55
 
5.6%
도 40
 
4.1%
공 33
 
3.4%
이 24
 
2.4%
의 19
 
1.9%
서 16
 
1.6%
기 15
 
1.5%
Other values (216) 612
62.2%
CJK
ValueCountFrequency (%)
公 1
33.3%
共 1
33.3%
新 1
33.3%

저자
Text

Distinct52
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T23:51:36.122104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length23
Mean length9.7301587
Min length3

Characters and Unicode

Total characters613
Distinct characters188
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

Unique48 ?
Unique (%)76.2%

Sample

1st row고성종;고필종 [공]지음
2nd row디자인로커스
3rd row김원갑
4th row김민수
5th row권영걸
ValueCountFrequency (%)
지음 14
 
10.3%
skyhd 8
 
5.9%
지은이 4
 
2.9%
권영걸 3
 
2.2%
손정목 3
 
2.2%
외 3
 
2.2%
저 3
 
2.2%
료 2
 
1.5%
최인규 2
 
1.5%
공]지음 2
 
1.5%
Other values (90) 92
67.6%
2023-12-12T23:51:36.663144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
11.9%
지 23
 
3.8%
음 18
 
2.9%
김 15
 
2.4%
i 13
 
2.1%
이 12
 
2.0%
k 12
 
2.0%
y 11
 
1.8%
e 11
 
1.8%
; 11
 
1.8%
Other values (178) 414
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 346
56.4%
Lowercase Letter 109
 
17.8%
Space Separator 73
 
11.9%
Uppercase Letter 39
 
6.4%
Other Punctuation 34
 
5.5%
Close Punctuation 6
 
1.0%
Open Punctuation 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 23
 
6.6%
음 18
 
5.2%
김 15
 
4.3%
이 12
 
3.5%
영 9
 
2.6%
은 7
 
2.0%
자 6
 
1.7%
정 6
 
1.7%
저 6
 
1.7%
인 6
 
1.7%
Other values (137) 238
68.8%
Lowercase Letter
ValueCountFrequency (%)
i 13
11.9%
k 12
11.0%
y 11
10.1%
e 11
10.1%
t 8
 
7.3%
u 8
 
7.3%
n 7
 
6.4%
r 6
 
5.5%
a 5
 
4.6%
h 4
 
3.7%
Other values (12) 24
22.0%
Uppercase Letter
ValueCountFrequency (%)
S 9
23.1%
D 8
20.5%
H 8
20.5%
R 2
 
5.1%
K 2
 
5.1%
L 2
 
5.1%
C 2
 
5.1%
M 2
 
5.1%
Y 1
 
2.6%
P 1
 
2.6%
Other values (2) 2
 
5.1%
Other Punctuation
ValueCountFrequency (%)
; 11
32.4%
: 9
26.5%
, 8
23.5%
. 6
17.6%
Space Separator
ValueCountFrequency (%)
73
100.0%
Close Punctuation
ValueCountFrequency (%)
] 6
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
56.4%
Latin 148
24.1%
Common 119
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 23
 
6.6%
음 18
 
5.2%
김 15
 
4.3%
이 12
 
3.5%
영 9
 
2.6%
은 7
 
2.0%
자 6
 
1.7%
정 6
 
1.7%
저 6
 
1.7%
인 6
 
1.7%
Other values (137) 238
68.8%
Latin
ValueCountFrequency (%)
i 13
 
8.8%
k 12
 
8.1%
y 11
 
7.4%
e 11
 
7.4%
S 9
 
6.1%
t 8
 
5.4%
D 8
 
5.4%
H 8
 
5.4%
u 8
 
5.4%
n 7
 
4.7%
Other values (24) 53
35.8%
Common
ValueCountFrequency (%)
73
61.3%
; 11
 
9.2%
: 9
 
7.6%
, 8
 
6.7%
] 6
 
5.0%
. 6
 
5.0%
[ 6
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 346
56.4%
ASCII 267
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
27.3%
i 13
 
4.9%
k 12
 
4.5%
y 11
 
4.1%
e 11
 
4.1%
; 11
 
4.1%
: 9
 
3.4%
S 9
 
3.4%
t 8
 
3.0%
D 8
 
3.0%
Other values (31) 102
38.2%
Hangul
ValueCountFrequency (%)
지 23
 
6.6%
음 18
 
5.2%
김 15
 
4.3%
이 12
 
3.5%
영 9
 
2.6%
은 7
 
2.0%
자 6
 
1.7%
정 6
 
1.7%
저 6
 
1.7%
인 6
 
1.7%
Other values (137) 238
68.8%

발행처
Text

Distinct44
Distinct (%)69.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T23:51:36.936470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length6.5079365
Min length2

Characters and Unicode

Total characters410
Distinct characters132
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

Unique33 ?
Unique (%)52.4%

Sample

1st row미진사
2nd row디자인로커스
3rd row열린책들,
4th row도서출판 그린비
5th row디자인하우스
ValueCountFrequency (%)
미디어우토 9
 
10.7%
공급 9
 
10.7%
한울 4
 
4.8%
안그라픽스 2
 
2.4%
press 2
 
2.4%
그린비 2
 
2.4%
디자인하우스 2
 
2.4%
디자인로커스 2
 
2.4%
2
 
2.4%
시공문화사 2
 
2.4%
Other values (43) 48
57.1%
2023-12-12T23:51:37.416574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
5.1%
미 16
 
3.9%
우 15
 
3.7%
디 14
 
3.4%
e 12
 
2.9%
스 12
 
2.9%
공 11
 
2.7%
어 10
 
2.4%
[ 9
 
2.2%
급 9
 
2.2%
Other values (122) 281
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 273
66.6%
Lowercase Letter 70
 
17.1%
Uppercase Letter 22
 
5.4%
Space Separator 21
 
5.1%
Open Punctuation 9
 
2.2%
Close Punctuation 9
 
2.2%
Other Punctuation 6
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 16
 
5.9%
우 15
 
5.5%
디 14
 
5.1%
스 12
 
4.4%
공 11
 
4.0%
어 10
 
3.7%
급 9
 
3.3%
토 9
 
3.3%
시 7
 
2.6%
한 6
 
2.2%
Other values (86) 164
60.1%
Lowercase Letter
ValueCountFrequency (%)
e 12
17.1%
s 9
12.9%
a 6
8.6%
h 5
 
7.1%
r 5
 
7.1%
i 5
 
7.1%
c 4
 
5.7%
t 4
 
5.7%
m 3
 
4.3%
u 3
 
4.3%
Other values (8) 14
20.0%
Uppercase Letter
ValueCountFrequency (%)
T 3
13.6%
C 3
13.6%
P 3
13.6%
I 2
9.1%
A 2
9.1%
S 2
9.1%
H 1
 
4.5%
K 1
 
4.5%
B 1
 
4.5%
M 1
 
4.5%
Other values (3) 3
13.6%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
& 2
33.3%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
] 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 273
66.6%
Latin 92
 
22.4%
Common 45
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 16
 
5.9%
우 15
 
5.5%
디 14
 
5.1%
스 12
 
4.4%
공 11
 
4.0%
어 10
 
3.7%
급 9
 
3.3%
토 9
 
3.3%
시 7
 
2.6%
한 6
 
2.2%
Other values (86) 164
60.1%
Latin
ValueCountFrequency (%)
e 12
 
13.0%
s 9
 
9.8%
a 6
 
6.5%
h 5
 
5.4%
r 5
 
5.4%
i 5
 
5.4%
c 4
 
4.3%
t 4
 
4.3%
T 3
 
3.3%
C 3
 
3.3%
Other values (21) 36
39.1%
Common
ValueCountFrequency (%)
21
46.7%
[ 9
20.0%
] 9
20.0%
, 4
 
8.9%
& 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 273
66.6%
ASCII 137
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
15.3%
e 12
 
8.8%
[ 9
 
6.6%
] 9
 
6.6%
s 9
 
6.6%
a 6
 
4.4%
h 5
 
3.6%
r 5
 
3.6%
i 5
 
3.6%
c 4
 
2.9%
Other values (26) 52
38.0%
Hangul
ValueCountFrequency (%)
미 16
 
5.9%
우 15
 
5.5%
디 14
 
5.1%
스 12
 
4.4%
공 11
 
4.0%
어 10
 
3.7%
급 9
 
3.3%
토 9
 
3.3%
시 7
 
2.6%
한 6
 
2.2%
Other values (86) 164
60.1%

발행연도
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)26.4%
Missing10
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean2010.3208
Minimum2002
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T23:51:37.580543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2006
Q12009
median2010
Q32012
95-th percentile2015.8
Maximum2018
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.2330837
Coefficient of variation (CV)0.0016082427
Kurtosis0.59841616
Mean2010.3208
Median Absolute Deviation (MAD)1
Skewness0.1787177
Sum106547
Variance10.45283
MonotonicityNot monotonic
2023-12-12T23:51:37.713782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2009 15
23.8%
2010 7
11.1%
2011 7
11.1%
2015 4
 
6.3%
2008 3
 
4.8%
2006 3
 
4.8%
2014 3
 
4.8%
2012 2
 
3.2%
2013 2
 
3.2%
2007 2
 
3.2%
Other values (4) 5
 
7.9%
(Missing) 10
15.9%
ValueCountFrequency (%)
2002 1
 
1.6%
2003 1
 
1.6%
2006 3
 
4.8%
2007 2
 
3.2%
2008 3
 
4.8%
2009 15
23.8%
2010 7
11.1%
2011 7
11.1%
2012 2
 
3.2%
2013 2
 
3.2%
ValueCountFrequency (%)
2018 1
 
1.6%
2017 2
 
3.2%
2015 4
 
6.3%
2014 3
 
4.8%
2013 2
 
3.2%
2012 2
 
3.2%
2011 7
11.1%
2010 7
11.1%
2009 15
23.8%
2008 3
 
4.8%

Interactions

2023-12-12T23:51:34.279171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:51:37.844427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제목저자발행처발행연도
제목1.0001.0001.0001.000
저자1.0001.0000.9991.000
발행처1.0000.9991.0000.940
발행연도1.0001.0000.9401.000

Missing values

2023-12-12T23:51:34.436513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:51:34.557843image/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

도서구분제목저자발행처발행연도
0공공디자인도시환경과 벽화디자인고성종;고필종 [공]지음미진사2003
1공공디자인멋진 신세계, 꽃이 피다:"도시가 작품이다" 서울시 도시갤러리 프로젝트디자인로커스디자인로커스2008
2공공디자인메트로폴리스 : 아방가르드 예술과 건축에 관한 13가지 주제 /김원갑열린책들,2002
3공공디자인한국 도시디자인 탐사: 광역시의 정체성을 찾아서김민수도서출판 그린비<NA>
4공공디자인서울을 디자인한다 = Designing seoul :디자인 서울의 22원칙권영걸디자인하우스2010
5공공디자인공공디자인 행정론:2010년 최초 시행 디자인직류 공무원 임용 시험윤종영;안혜신 [공]지음삼성출판사2009
6공공디자인부엉배 화이트 :부엉배마을 이야기:공공미술에서 커뮤니티 비즈니스까지들로화구름서재2010
7공공디자인도시디자인 프로젝트 = (The) projects of urban design최인규 지음시공문화사2008
8공공디자인미술, 공간, 도시-공공미술과 도시의 미래맬컴 마일스학고재<NA>
9공공디자인新문화도시 전략과 시사점 /전영옥삼성경제연구소,2006
도서구분제목저자발행처발행연도
53공공디자인상상의 아테네, 베를린.도쿄.서울 : 전진성 지음전진성 지음천년의상상2015
54공공디자인안전디자인으로 대한민국 바꾸기 / 한국도시설계학회 홍보 안전디자인연구회 엮음한국도시설계학회 홍보 안전디자인연구회 엮음미세움2015
55공공디자인공공(公共)을 위한 디자인과 예술 = Design & art for public / 김문석 지음김문석 지음한국학술정보2011
56공공디자인거리의 디자인 : 지은이: 카를레스 브로토지은이: 카를레스 브로토;옮긴이: 이지민한스미디어2015
57공공디자인작은 마을 디자인하기 / 글쓴이: 이누이 구미코글쓴이: 이누이 구미코,야마자키 료디자인하우스2014
58공공디자인커뮤니티 디자인을 하다 :주민참여로 가꿔나가는 삶의 공간커뮤니티 디자인센터 지음나무도시2011
59공공디자인(뉴욕 런던 서울의)도시재생 이야기 = Urban regeneration in New York, London and Seoul도시재생네트워크 지음픽셀하우스2010
60공공디자인나의 국가디자인전략 : 지은이: 권영걸지은이: 권영걸김영사2013
61공공디자인커뮤니티 디자인 = Community design사토마사루 저;김명환 역디자인로커스2006
62공공디자인Public art :a world's eye view[art supervision, Yumiko Mochizuki ... et al.]ICO2007