Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory53.3 B

Variable types

Text3
Categorical3

Dataset

Description한국공예디자인문화진흥원이 추진한 공예현황 연구자료 결과물 (개관, 제도 및 정책, 산업, 전시와 행사, 연구, 교육)
Author한국공예디자인문화진흥원
URLhttps://www.data.go.kr/data/15052700/fileData.do

Alerts

발행처 has constant value ""Constant
판매가 is highly overall correlated with 작성일High correlation
작성일 is highly overall correlated with 판매가High correlation
판매가 is highly imbalanced (52.4%)Imbalance
도서명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:46:24.802966
Analysis finished2023-12-12 07:46:25.260350
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도서명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T16:46:25.404531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length9
Mean length9.56
Min length6

Characters and Unicode

Total characters239
Distinct characters72
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row핸드메이드 마켓플레이스
2nd row공예로 생각하기
3rd row온라인에서 공예품을 파는 모든 방법
4th row공예의 발명
5th row한눈에 보는 나전칠기
ValueCountFrequency (%)
보는 21
28.4%
한눈에 21
28.4%
핸드메이드 1
 
1.4%
백자 1
 
1.4%
옹기 1
 
1.4%
침선 1
 
1.4%
매듭 1
 
1.4%
입사 1
 
1.4%
청자 1
 
1.4%
옻칠 1
 
1.4%
Other values (24) 24
32.4%
2023-12-12T16:46:25.726308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
20.5%
보 22
 
9.2%
는 22
 
9.2%
에 22
 
9.2%
한 22
 
9.2%
눈 21
 
8.8%
칠 3
 
1.3%
기 3
 
1.3%
공 3
 
1.3%
예 3
 
1.3%
Other values (62) 69
28.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 190
79.5%
Space Separator 49
 
20.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 22
 
11.6%
는 22
 
11.6%
에 22
 
11.6%
한 22
 
11.6%
눈 21
 
11.1%
칠 3
 
1.6%
기 3
 
1.6%
공 3
 
1.6%
예 3
 
1.6%
자 2
 
1.1%
Other values (61) 67
35.3%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 190
79.5%
Common 49
 
20.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 22
 
11.6%
는 22
 
11.6%
에 22
 
11.6%
한 22
 
11.6%
눈 21
 
11.1%
칠 3
 
1.6%
기 3
 
1.6%
공 3
 
1.6%
예 3
 
1.6%
자 2
 
1.1%
Other values (61) 67
35.3%
Common
ValueCountFrequency (%)
49
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 190
79.5%
ASCII 49
 
20.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49
100.0%
Hangul
ValueCountFrequency (%)
보 22
 
11.6%
는 22
 
11.6%
에 22
 
11.6%
한 22
 
11.6%
눈 21
 
11.1%
칠 3
 
1.6%
기 3
 
1.6%
공 3
 
1.6%
예 3
 
1.6%
자 2
 
1.1%
Other values (61) 67
35.3%

저자
Text

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T16:46:25.917300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length9.28
Min length3

Characters and Unicode

Total characters232
Distinct characters84
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row카리 샤핀 
2nd row글렌 아담슨
3rd row킴 솔가
4th row글렌 아담슨
5th row김윤경
ValueCountFrequency (%)
및 19
28.4%
김미라 3
 
4.5%
글렌 2
 
3.0%
아담슨 2
 
3.0%
김윤경 2
 
3.0%
심연옥 1
 
1.5%
서정걸 1
 
1.5%
권소현 1
 
1.5%
조훈상 1
 
1.5%
김정은 1
 
1.5%
Other values (34) 34
50.7%
2023-12-12T16:46:26.220184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62
26.7%
및 19
 
8.2%
김 10
 
4.3%
이 7
 
3.0%
최 6
 
2.6%
  5
 
2.2%
경 5
 
2.2%
성 5
 
2.2%
박 4
 
1.7%
정 4
 
1.7%
Other values (74) 105
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
71.1%
Space Separator 67
28.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
및 19
 
11.5%
김 10
 
6.1%
이 7
 
4.2%
최 6
 
3.6%
경 5
 
3.0%
성 5
 
3.0%
박 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
영 4
 
2.4%
Other values (72) 97
58.8%
Space Separator
ValueCountFrequency (%)
62
92.5%
  5
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
71.1%
Common 67
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
및 19
 
11.5%
김 10
 
6.1%
이 7
 
4.2%
최 6
 
3.6%
경 5
 
3.0%
성 5
 
3.0%
박 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
영 4
 
2.4%
Other values (72) 97
58.8%
Common
ValueCountFrequency (%)
62
92.5%
  5
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
71.1%
ASCII 62
 
26.7%
None 5
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62
100.0%
Hangul
ValueCountFrequency (%)
및 19
 
11.5%
김 10
 
6.1%
이 7
 
4.2%
최 6
 
3.6%
경 5
 
3.0%
성 5
 
3.0%
박 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
영 4
 
2.4%
Other values (72) 97
58.8%
None
ValueCountFrequency (%)
  5
100.0%

발행처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
한국공예디자인문화진흥원
25 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한국공예디자인문화진흥원 25
100.0%

Length

2023-12-12T16:46:26.373021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:26.475827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국공예디자인문화진흥원 25
100.0%

발행일
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T16:46:26.607404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.2
Min length5

Characters and Unicode

Total characters230
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)32.0%

Sample

1st row2015-12-15
2nd row2016-02-25
3rd row2016-12-20
4th row2017-08-18
5th row2011-07-01
ValueCountFrequency (%)
2013-12-20 3
12.0%
2014-11-20 2
 
8.0%
2015-12-24 2
 
8.0%
2016-12-23 2
 
8.0%
2017-12-29 2
 
8.0%
2018-12-07 2
 
8.0%
2019-12-11 2
 
8.0%
2020년 2
 
8.0%
2015-12-15 1
 
4.0%
2016-02-25 1
 
4.0%
Other values (6) 6
24.0%
2023-12-12T16:46:26.916400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 62
27.0%
1 50
21.7%
- 42
18.3%
0 39
17.0%
7 6
 
2.6%
3 5
 
2.2%
4 5
 
2.2%
5 5
 
2.2%
6 4
 
1.7%
9 4
 
1.7%
Other values (2) 8
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 184
80.0%
Dash Punctuation 42
 
18.3%
Other Letter 4
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 62
33.7%
1 50
27.2%
0 39
21.2%
7 6
 
3.3%
3 5
 
2.7%
4 5
 
2.7%
5 5
 
2.7%
6 4
 
2.2%
9 4
 
2.2%
8 4
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Other Letter
ValueCountFrequency (%)
년 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 226
98.3%
Hangul 4
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 62
27.4%
1 50
22.1%
- 42
18.6%
0 39
17.3%
7 6
 
2.7%
3 5
 
2.2%
4 5
 
2.2%
5 5
 
2.2%
6 4
 
1.8%
9 4
 
1.8%
Hangul
ValueCountFrequency (%)
년 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 226
98.3%
Hangul 4
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 62
27.4%
1 50
22.1%
- 42
18.6%
0 39
17.3%
7 6
 
2.7%
3 5
 
2.2%
4 5
 
2.2%
5 5
 
2.2%
6 4
 
1.8%
9 4
 
1.8%
Hangul
ValueCountFrequency (%)
년 4
100.0%

판매가
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
16000원
20 
<NA>
 
2
20000원
 
1
18000원
 
1
22000원
 
1

Length

Max length6
Median length6
Mean length5.84
Min length4

Unique

Unique3 ?
Unique (%)12.0%

Sample

1st row16000원
2nd row20000원
3rd row18000원
4th row22000원
5th row<NA>

Common Values

ValueCountFrequency (%)
16000원 20
80.0%
<NA> 2
 
8.0%
20000원 1
 
4.0%
18000원 1
 
4.0%
22000원 1
 
4.0%

Length

2023-12-12T16:46:27.046272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:27.152004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
16000원 20
80.0%
na 2
 
8.0%
20000원 1
 
4.0%
18000원 1
 
4.0%
22000원 1
 
4.0%

작성일
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2019-02-14
15 
2022-07-06
3 
2016-10-04
2 
2020-01-23
2 
2017-01-24
 
1
Other values (2)
2 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique3 ?
Unique (%)12.0%

Sample

1st row2016-10-04
2nd row2016-10-04
3rd row2017-01-24
4th row2017-08-23
5th row2019-02-14

Common Values

ValueCountFrequency (%)
2019-02-14 15
60.0%
2022-07-06 3
 
12.0%
2016-10-04 2
 
8.0%
2020-01-23 2
 
8.0%
2017-01-24 1
 
4.0%
2017-08-23 1
 
4.0%
2023-06-21 1
 
4.0%

Length

2023-12-12T16:46:27.265111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:27.385928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-02-14 15
60.0%
2022-07-06 3
 
12.0%
2016-10-04 2
 
8.0%
2020-01-23 2
 
8.0%
2017-01-24 1
 
4.0%
2017-08-23 1
 
4.0%
2023-06-21 1
 
4.0%

Correlations

2023-12-12T16:46:27.463980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도서명저자발행일판매가작성일
도서명1.0001.0001.0001.0001.000
저자1.0001.0000.8380.0000.000
발행일1.0000.8381.0001.0001.000
판매가1.0000.0001.0001.0000.909
작성일1.0000.0001.0000.9091.000
2023-12-12T16:46:27.553844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매가작성일
판매가1.0000.800
작성일0.8001.000
2023-12-12T16:46:27.627123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매가작성일
판매가1.0000.800
작성일0.8001.000

Missing values

2023-12-12T16:46:25.117573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:46:25.224979image/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

도서명저자발행처발행일판매가작성일
0핸드메이드 마켓플레이스카리 샤핀한국공예디자인문화진흥원2015-12-1516000원2016-10-04
1공예로 생각하기글렌 아담슨한국공예디자인문화진흥원2016-02-2520000원2016-10-04
2온라인에서 공예품을 파는 모든 방법킴 솔가한국공예디자인문화진흥원2016-12-2018000원2017-01-24
3공예의 발명글렌 아담슨한국공예디자인문화진흥원2017-08-1822000원2017-08-23
4한눈에 보는 나전칠기김윤경한국공예디자인문화진흥원2011-07-01<NA>2019-02-14
5한눈에 보는 전통천연염색한국공예디자인문화진흥원 및 김윤경한국공예디자인문화진흥원2012-12-24<NA>2019-02-14
6한눈에 보는 소목김삼대자한국공예디자인문화진흥원2013-12-2016000원2019-02-14
7한눈에 보는 정석김미라 및 최혜성한국공예디자인문화진흥원2013-12-2016000원2019-02-14
8한눈에 보는 한지최영숙 및 이주은한국공예디자인문화진흥원2013-12-2016000원2019-02-14
9한눈에 보는 백자최건 및 장기훈 및 이정용한국공예디자인문화진흥원2014-11-2016000원2019-02-14
도서명저자발행처발행일판매가작성일
15한눈에 보는 청자강경인 및 서정걸 및 권소현한국공예디자인문화진흥원2017-12-2916000원2019-02-14
16한눈에 보는 옻칠조훈상 및 김미라 및 김정은 및 이희승한국공예디자인문화진흥원2017-12-2916000원2019-02-14
17한눈에 보는 소반최공호 및 김미라한국공예디자인문화진흥원2018-12-0716000원2019-02-14
18한눈에 보는 제와김성구한국공예디자인문화진흥원2018-12-0716000원2019-02-14
19한눈에 보는 금박심연옥 및 이선용한국공예디자인문화진흥원2019-12-1116000원2020-01-23
20한눈에 보는 화혜장경희한국공예디자인문화진흥원2019-12-1116000원2020-01-23
21한눈에 보는 칠보노용숙 및 성다솜한국공예디자인문화진흥원2020년16000원2022-07-06
22한눈에 보는 단청곽동해 및 임영주한국공예디자인문화진흥원2020년16000원2022-07-06
23한눈에 보는 채화정병모 및 최성우한국공예디자인문화진흥원2021년16000원2022-07-06
24한눈에 보는 갓이주영 및 박형박한국공예디자인문화진흥원2022년16000원2023-06-21