Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells38
Missing cells (%)28.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory44.9 B

Variable types

Text3
Categorical1
DateTime1

Dataset

Description중소벤처기업부 및 창업진흥원이 운영하는 메이크올 사이트에서 확인할 수 있는 메이크올 추천 우수 메이커 정보. 제목, 주요활동분야, 홈페이지url, 관련동영상url, 등록일
Author창업진흥원
URLhttps://www.data.go.kr/data/15088126/fileData.do

Alerts

홈페이지URL has 15 (55.6%) missing valuesMissing
관련동영상URL has 23 (85.2%) missing valuesMissing
등록일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:05:14.665851
Analysis finished2023-12-12 04:05:15.878419
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제목
Text

Distinct24
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T13:05:16.189629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length24.962963
Min length11

Characters and Unicode

Total characters674
Distinct characters200
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

Unique21 ?
Unique (%)77.8%

Sample

1st row추워지고 있는 날씨에 유용하게 활용가능한 워셔블 매트 메이커를 추천합니다.
2nd row생활속 작은 혁신, 택배용 커터기를 개발한 이영희 메이커를 추천합니다.
3rd row우수메이커 추천 이벤트 당첨자 발표
4th rowEVENT 우수메이커 추천하고 경품 받으세요
5th row코딩을 재밌게 배우는 페이퍼 블록 코딩키트, '스마트시티'
ValueCountFrequency (%)
메이커를 8
 
5.3%
추천합니다 8
 
5.3%
우수메이커 6
 
4.0%
메이커 6
 
4.0%
event 4
 
2.6%
추천하고 4
 
2.6%
경품 4
 
2.6%
받으세요 4
 
2.6%
추천 2
 
1.3%
및 2
 
1.3%
Other values (99) 103
68.2%
2023-12-12T13:05:16.807700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
18.7%
이 28
 
4.2%
커 23
 
3.4%
메 21
 
3.1%
추 16
 
2.4%
천 15
 
2.2%
를 13
 
1.9%
다 12
 
1.8%
하 11
 
1.6%
니 10
 
1.5%
Other values (190) 399
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494
73.3%
Space Separator 126
 
18.7%
Uppercase Letter 24
 
3.6%
Other Punctuation 19
 
2.8%
Math Symbol 3
 
0.4%
Lowercase Letter 3
 
0.4%
Decimal Number 2
 
0.3%
Final Punctuation 1
 
0.1%
Initial Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 28
 
5.7%
커 23
 
4.7%
메 21
 
4.3%
추 16
 
3.2%
천 15
 
3.0%
를 13
 
2.6%
다 12
 
2.4%
하 11
 
2.2%
니 10
 
2.0%
수 9
 
1.8%
Other values (170) 336
68.0%
Uppercase Letter
ValueCountFrequency (%)
E 8
33.3%
V 4
16.7%
N 4
16.7%
T 4
16.7%
D 2
 
8.3%
M 1
 
4.2%
I 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
' 8
42.1%
. 7
36.8%
, 3
 
15.8%
! 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
o 1
33.3%
r 1
33.3%
p 1
33.3%
Space Separator
ValueCountFrequency (%)
126
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 494
73.3%
Common 153
 
22.7%
Latin 27
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 28
 
5.7%
커 23
 
4.7%
메 21
 
4.3%
추 16
 
3.2%
천 15
 
3.0%
를 13
 
2.6%
다 12
 
2.4%
하 11
 
2.2%
니 10
 
2.0%
수 9
 
1.8%
Other values (170) 336
68.0%
Common
ValueCountFrequency (%)
126
82.4%
' 8
 
5.2%
. 7
 
4.6%
, 3
 
2.0%
~ 3
 
2.0%
3 2
 
1.3%
’ 1
 
0.7%
‘ 1
 
0.7%
! 1
 
0.7%
- 1
 
0.7%
Latin
ValueCountFrequency (%)
E 8
29.6%
V 4
14.8%
N 4
14.8%
T 4
14.8%
D 2
 
7.4%
M 1
 
3.7%
I 1
 
3.7%
o 1
 
3.7%
r 1
 
3.7%
p 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 494
73.3%
ASCII 178
 
26.4%
Punctuation 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
70.8%
E 8
 
4.5%
' 8
 
4.5%
. 7
 
3.9%
V 4
 
2.2%
N 4
 
2.2%
T 4
 
2.2%
, 3
 
1.7%
~ 3
 
1.7%
D 2
 
1.1%
Other values (8) 9
 
5.1%
Hangul
ValueCountFrequency (%)
이 28
 
5.7%
커 23
 
4.7%
메 21
 
4.3%
추 16
 
3.2%
천 15
 
3.0%
를 13
 
2.6%
다 12
 
2.4%
하 11
 
2.2%
니 10
 
2.0%
수 9
 
1.8%
Other values (170) 336
68.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

주요활동분야
Categorical

Distinct8
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size348.0 B
<NA>
9 
테크놀로지
6 
생활/홈데코
5 
크래프트/예술
3 
대중적인 참신한 메이커
1 
Other values (3)
3 

Length

Max length14
Median length10
Mean length5.6666667
Min length4

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row생활/홈데코
2nd row생활/홈데코
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9
33.3%
테크놀로지 6
22.2%
생활/홈데코 5
18.5%
크래프트/예술 3
 
11.1%
대중적인 참신한 메이커 1
 
3.7%
디지털 패브리케이션 1
 
3.7%
단체 운영 1
 
3.7%
행사기획/교육 1
 
3.7%

Length

2023-12-12T13:05:16.983170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:05:17.123278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9
29.0%
테크놀로지 6
19.4%
생활/홈데코 5
16.1%
크래프트/예술 3
 
9.7%
대중적인 1
 
3.2%
참신한 1
 
3.2%
메이커 1
 
3.2%
디지털 1
 
3.2%
패브리케이션 1
 
3.2%
단체 1
 
3.2%
Other values (2) 2
 
6.5%

홈페이지URL
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing15
Missing (%)55.6%
Memory size348.0 B
2023-12-12T13:05:17.407351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length33.5
Mean length38.583333
Min length15

Characters and Unicode

Total characters463
Distinct characters41
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st rowhttps://www.makeall.com/shop/shopview.php?tsort=2&msort=&s_key=&s_type=&no=151&page=1
2nd rowhttps://tumblbug.com/jring
3rd rowhttps://blog.naver.com/ahdoc/221334301132
4th rowwww.kocoafab.cc
5th rowhttp://anatz.com/
ValueCountFrequency (%)
https://www.makeall.com/shop/shopview.php?tsort=2&msort=&s_key=&s_type=&no=151&page=1 1
8.3%
https://tumblbug.com/jring 1
8.3%
https://blog.naver.com/ahdoc/221334301132 1
8.3%
www.kocoafab.cc 1
8.3%
http://anatz.com 1
8.3%
https://www.facebook.com/withcampkr 1
8.3%
https://www.instagram.com/zigi_fun 1
8.3%
https://cafe.naver.com/toymakers 1
8.3%
https://www.makeall.com/network/storyview.php?tsort=3&msort=10&s_key=&s_type=&no=165&page=1 1
8.3%
https://blog.naver.com/thecube57 1
8.3%
Other values (2) 2
16.7%
2023-12-12T13:05:17.859511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 38
 
8.2%
/ 37
 
8.0%
o 32
 
6.9%
. 24
 
5.2%
s 23
 
5.0%
p 22
 
4.8%
w 22
 
4.8%
a 22
 
4.8%
e 21
 
4.5%
m 20
 
4.3%
Other values (31) 202
43.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 333
71.9%
Other Punctuation 84
 
18.1%
Decimal Number 27
 
5.8%
Math Symbol 12
 
2.6%
Connector Punctuation 5
 
1.1%
Uppercase Letter 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 38
 
11.4%
o 32
 
9.6%
s 23
 
6.9%
p 22
 
6.6%
w 22
 
6.6%
a 22
 
6.6%
e 21
 
6.3%
m 20
 
6.0%
c 19
 
5.7%
h 18
 
5.4%
Other values (14) 96
28.8%
Decimal Number
ValueCountFrequency (%)
1 9
33.3%
3 6
22.2%
2 4
14.8%
5 3
 
11.1%
0 2
 
7.4%
4 1
 
3.7%
6 1
 
3.7%
7 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/ 37
44.0%
. 24
28.6%
: 11
 
13.1%
& 10
 
11.9%
? 2
 
2.4%
Math Symbol
ValueCountFrequency (%)
= 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 334
72.1%
Common 129
 
27.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 38
 
11.4%
o 32
 
9.6%
s 23
 
6.9%
p 22
 
6.6%
w 22
 
6.6%
a 22
 
6.6%
e 21
 
6.3%
m 20
 
6.0%
c 19
 
5.7%
h 18
 
5.4%
Other values (15) 97
29.0%
Common
ValueCountFrequency (%)
/ 37
28.7%
. 24
18.6%
= 12
 
9.3%
: 11
 
8.5%
& 10
 
7.8%
1 9
 
7.0%
3 6
 
4.7%
_ 5
 
3.9%
2 4
 
3.1%
5 3
 
2.3%
Other values (6) 8
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 463
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 38
 
8.2%
/ 37
 
8.0%
o 32
 
6.9%
. 24
 
5.2%
s 23
 
5.0%
p 22
 
4.8%
w 22
 
4.8%
a 22
 
4.8%
e 21
 
4.5%
m 20
 
4.3%
Other values (31) 202
43.6%

관련동영상URL
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing23
Missing (%)85.2%
Memory size348.0 B
2023-12-12T13:05:18.116489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length46.5
Mean length46
Min length28

Characters and Unicode

Total characters184
Distinct characters51
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowhttps://www.youtube.com/watch?v=ZIh-yzYdn8M&feature=youtu.be
2nd rowhttps://www.youtube.com/channel/UCWiKHqQiwIa__vHi-BS3Lfg/videos
3rd rowhttps://kocoafab.cc/make/view/645
4th rowhttps://youtu.be/kijZZvz_alM
ValueCountFrequency (%)
https://www.youtube.com/watch?v=zih-yzydn8m&feature=youtu.be 1
25.0%
https://www.youtube.com/channel/ucwikhqqiwia__vhi-bs3lfg/videos 1
25.0%
https://kocoafab.cc/make/view/645 1
25.0%
https://youtu.be/kijzzvz_alm 1
25.0%
2023-12-12T13:05:18.603302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 16
 
8.7%
t 14
 
7.6%
e 10
 
5.4%
u 9
 
4.9%
o 9
 
4.9%
w 9
 
4.9%
a 8
 
4.3%
c 7
 
3.8%
h 7
 
3.8%
. 7
 
3.8%
Other values (41) 88
47.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 125
67.9%
Other Punctuation 29
 
15.8%
Uppercase Letter 18
 
9.8%
Decimal Number 5
 
2.7%
Connector Punctuation 3
 
1.6%
Math Symbol 2
 
1.1%
Dash Punctuation 2
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 14
 
11.2%
e 10
 
8.0%
u 9
 
7.2%
o 9
 
7.2%
w 9
 
7.2%
a 8
 
6.4%
c 7
 
5.6%
h 7
 
5.6%
i 6
 
4.8%
y 5
 
4.0%
Other values (15) 41
32.8%
Uppercase Letter
ValueCountFrequency (%)
Z 3
16.7%
H 2
11.1%
M 2
11.1%
I 2
11.1%
L 1
 
5.6%
S 1
 
5.6%
B 1
 
5.6%
K 1
 
5.6%
Q 1
 
5.6%
W 1
 
5.6%
Other values (3) 3
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 16
55.2%
. 7
24.1%
: 4
 
13.8%
? 1
 
3.4%
& 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
6 1
20.0%
4 1
20.0%
3 1
20.0%
5 1
20.0%
8 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 143
77.7%
Common 41
 
22.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 14
 
9.8%
e 10
 
7.0%
u 9
 
6.3%
o 9
 
6.3%
w 9
 
6.3%
a 8
 
5.6%
c 7
 
4.9%
h 7
 
4.9%
i 6
 
4.2%
y 5
 
3.5%
Other values (28) 59
41.3%
Common
ValueCountFrequency (%)
/ 16
39.0%
. 7
17.1%
: 4
 
9.8%
_ 3
 
7.3%
= 2
 
4.9%
- 2
 
4.9%
6 1
 
2.4%
? 1
 
2.4%
4 1
 
2.4%
3 1
 
2.4%
Other values (3) 3
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 16
 
8.7%
t 14
 
7.6%
e 10
 
5.4%
u 9
 
4.9%
o 9
 
4.9%
w 9
 
4.9%
a 8
 
4.3%
c 7
 
3.8%
h 7
 
3.8%
. 7
 
3.8%
Other values (41) 88
47.8%

등록일
Date

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2018-04-16 18:57:00
Maximum2020-01-16 11:19:00
2023-12-12T13:05:18.780895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:05:18.922276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

Correlations

2023-12-12T13:05:19.019255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제목주요활동분야홈페이지URL관련동영상URL등록일
제목1.0001.0001.0001.0001.000
주요활동분야1.0001.0001.0001.0001.000
홈페이지URL1.0001.0001.0001.0001.000
관련동영상URL1.0001.0001.0001.0001.000
등록일1.0001.0001.0001.0001.000

Missing values

2023-12-12T13:05:15.082960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:05:15.683475image/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.
2023-12-12T13:05:15.809246image/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

제목주요활동분야홈페이지URL관련동영상URL등록일
0추워지고 있는 날씨에 유용하게 활용가능한 워셔블 매트 메이커를 추천합니다.생활/홈데코https://www.makeall.com/shop/shopview.php?tsort=2&msort=&s_key=&s_type=&no=151&page=1<NA>2018-10-30 15:25
1생활속 작은 혁신, 택배용 커터기를 개발한 이영희 메이커를 추천합니다.생활/홈데코https://tumblbug.com/jringhttps://www.youtube.com/watch?v=ZIh-yzYdn8M&feature=youtu.be2018-10-31 00:31
2우수메이커 추천 이벤트 당첨자 발표<NA><NA><NA>2018-11-15 10:18
3EVENT 우수메이커 추천하고 경품 받으세요<NA><NA><NA>2018-11-15 10:19
4코딩을 재밌게 배우는 페이퍼 블록 코딩키트, '스마트시티'<NA><NA><NA>2018-11-18 01:22
5EVENT 우수메이커 추천하고 경품 받으세요<NA><NA><NA>2018-12-03 19:08
6EVENT 우수메이커 추천하고 경품 받으세요<NA><NA><NA>2018-12-17 17:54
7우수메이커 추천 이벤트 당첨자 발표<NA><NA><NA>2018-12-17 17:57
8적정기술 도입한 참신한 메이커대중적인 참신한 메이커<NA><NA>2018-12-30 05:38
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