Overview

Dataset statistics

Number of variables5
Number of observations92
Missing cells18
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory41.4 B

Variable types

Text5

Dataset

Description평생교육법 등 관계 법령에 의거하여 평생교육바우처 지원 대상자가 바우처 카드를 사용하여 학습에 참여할 수 있도록 국가평생교육진흥원에 등록된 평생교육기관의 상세정보 안내
Author국가평생교육진흥원
URLhttps://www.data.go.kr/data/15104458/fileData.do

Alerts

DETAIL_ADDR has 5 (5.4%) missing valuesMissing
HOMEPAGE has 13 (14.1%) missing valuesMissing
ORGAN_NM has unique valuesUnique
ADDR has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:55:40.464372
Analysis finished2023-12-12 13:55:41.472335
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

ORGAN_NM
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T22:55:41.654567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length11.282609
Min length4

Characters and Unicode

Total characters1038
Distinct characters238
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

Unique92 ?
Unique (%)100.0%

Sample

1st row남서울대학교부설원격평생교육원
2nd row패스원평생교육원
3rd row(주)와이비엠넷
4th row휴넷평생교육원
5th row광주보건대학교부설평생교육원
ValueCountFrequency (%)
남서울대학교부설원격평생교육원 1
 
1.1%
신경남고시학원(신규 1
 
1.1%
비트컴퓨터학원 1
 
1.1%
건강한미래교육(주 1
 
1.1%
주)코리아아이티아카데미대구 1
 
1.1%
조선대학교시민르네상스평생교육원 1
 
1.1%
청어람컴퓨터학원 1
 
1.1%
한국리더십센터원격평생교육원 1
 
1.1%
학장자동차운전전문학원 1
 
1.1%
거성컴퓨터학원 1
 
1.1%
Other values (82) 82
89.1%
2023-12-12T22:55:42.048529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 76
 
7.3%
교 53
 
5.1%
학 52
 
5.0%
육 37
 
3.6%
평 32
 
3.1%
생 31
 
3.0%
터 23
 
2.2%
대 22
 
2.1%
인 16
 
1.5%
전 16
 
1.5%
Other values (228) 680
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 991
95.5%
Close Punctuation 15
 
1.4%
Open Punctuation 14
 
1.3%
Uppercase Letter 10
 
1.0%
Decimal Number 4
 
0.4%
Connector Punctuation 2
 
0.2%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 76
 
7.7%
교 53
 
5.3%
학 52
 
5.2%
육 37
 
3.7%
평 32
 
3.2%
생 31
 
3.1%
터 23
 
2.3%
대 22
 
2.2%
인 16
 
1.6%
전 16
 
1.6%
Other values (211) 633
63.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
20.0%
D 2
20.0%
M 1
10.0%
B 1
10.0%
Y 1
10.0%
P 1
10.0%
U 1
10.0%
N 1
10.0%
Decimal Number
ValueCountFrequency (%)
4 1
25.0%
0 1
25.0%
5 1
25.0%
3 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
u 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 991
95.5%
Common 35
 
3.4%
Latin 12
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 76
 
7.7%
교 53
 
5.3%
학 52
 
5.2%
육 37
 
3.7%
평 32
 
3.2%
생 31
 
3.1%
터 23
 
2.3%
대 22
 
2.2%
인 16
 
1.6%
전 16
 
1.6%
Other values (211) 633
63.9%
Latin
ValueCountFrequency (%)
C 2
16.7%
D 2
16.7%
M 1
8.3%
B 1
8.3%
e 1
8.3%
u 1
8.3%
Y 1
8.3%
P 1
8.3%
U 1
8.3%
N 1
8.3%
Common
ValueCountFrequency (%)
) 15
42.9%
( 14
40.0%
_ 2
 
5.7%
4 1
 
2.9%
0 1
 
2.9%
5 1
 
2.9%
3 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 991
95.5%
ASCII 47
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 76
 
7.7%
교 53
 
5.3%
학 52
 
5.2%
육 37
 
3.7%
평 32
 
3.2%
생 31
 
3.1%
터 23
 
2.3%
대 22
 
2.2%
인 16
 
1.6%
전 16
 
1.6%
Other values (211) 633
63.9%
ASCII
ValueCountFrequency (%)
) 15
31.9%
( 14
29.8%
C 2
 
4.3%
D 2
 
4.3%
_ 2
 
4.3%
M 1
 
2.1%
B 1
 
2.1%
4 1
 
2.1%
e 1
 
2.1%
0 1
 
2.1%
Other values (7) 7
14.9%

ADDR
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T22:55:42.329043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length18.771739
Min length15

Characters and Unicode

Total characters1727
Distinct characters167
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)100.0%

Sample

1st row충청남도 천안시 서북구 성환읍 대학로 91
2nd row서울특별시 동작구 장승배기로 171
3rd row서울특별시 종로구 종로 98
4th row서울특별시 구로구 디지털로26길 5
5th row광주광역시 광산구 북문대로419번길 73
ValueCountFrequency (%)
서울특별시 26
 
6.6%
전라북도 12
 
3.0%
경기도 12
 
3.0%
부산광역시 8
 
2.0%
전주시 6
 
1.5%
경상남도 6
 
1.5%
광주광역시 5
 
1.3%
동대문구 5
 
1.3%
완산구 4
 
1.0%
충청북도 4
 
1.0%
Other values (248) 306
77.7%
2023-12-12T22:55:42.756705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
302
 
17.5%
시 90
 
5.2%
로 87
 
5.0%
구 68
 
3.9%
1 56
 
3.2%
도 48
 
2.8%
2 43
 
2.5%
대 35
 
2.0%
산 34
 
2.0%
서 34
 
2.0%
Other values (157) 930
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1128
65.3%
Space Separator 302
 
17.5%
Decimal Number 285
 
16.5%
Dash Punctuation 11
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 90
 
8.0%
로 87
 
7.7%
구 68
 
6.0%
도 48
 
4.3%
대 35
 
3.1%
산 34
 
3.0%
서 34
 
3.0%
광 29
 
2.6%
길 29
 
2.6%
별 28
 
2.5%
Other values (144) 646
57.3%
Decimal Number
ValueCountFrequency (%)
1 56
19.6%
2 43
15.1%
4 31
10.9%
3 30
10.5%
6 28
9.8%
7 26
9.1%
8 22
 
7.7%
9 18
 
6.3%
5 17
 
6.0%
0 14
 
4.9%
Space Separator
ValueCountFrequency (%)
302
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1128
65.3%
Common 599
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 90
 
8.0%
로 87
 
7.7%
구 68
 
6.0%
도 48
 
4.3%
대 35
 
3.1%
산 34
 
3.0%
서 34
 
3.0%
광 29
 
2.6%
길 29
 
2.6%
별 28
 
2.5%
Other values (144) 646
57.3%
Common
ValueCountFrequency (%)
302
50.4%
1 56
 
9.3%
2 43
 
7.2%
4 31
 
5.2%
3 30
 
5.0%
6 28
 
4.7%
7 26
 
4.3%
8 22
 
3.7%
9 18
 
3.0%
5 17
 
2.8%
Other values (3) 26
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1128
65.3%
ASCII 598
34.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302
50.5%
1 56
 
9.4%
2 43
 
7.2%
4 31
 
5.2%
3 30
 
5.0%
6 28
 
4.7%
7 26
 
4.3%
8 22
 
3.7%
9 18
 
3.0%
5 17
 
2.8%
Other values (2) 25
 
4.2%
Hangul
ValueCountFrequency (%)
시 90
 
8.0%
로 87
 
7.7%
구 68
 
6.0%
도 48
 
4.3%
대 35
 
3.1%
산 34
 
3.0%
서 34
 
3.0%
광 29
 
2.6%
길 29
 
2.6%
별 28
 
2.5%
Other values (144) 646
57.3%
None
ValueCountFrequency (%)
· 1
100.0%

DETAIL_ADDR
Text

MISSING 

Distinct77
Distinct (%)88.5%
Missing5
Missing (%)5.4%
Memory size868.0 B
2023-12-12T22:55:42.969048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length16
Mean length8.8275862
Min length2

Characters and Unicode

Total characters768
Distinct characters195
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)83.9%

Sample

1st row21세기개발관 209호
2nd row2층 일부, 11층 일부
3rd rowYBM별관 4, 5층
4th row에이스하이엔드타워1차 8층
5th row솔로몬관1층
ValueCountFrequency (%)
3층 12
 
8.2%
2층 9
 
6.2%
4층 6
 
4.1%
5층 4
 
2.7%
평생교육원 4
 
2.7%
1층 3
 
2.1%
11층 3
 
2.1%
6층 3
 
2.1%
8층 2
 
1.4%
일부 2
 
1.4%
Other values (97) 98
67.1%
2023-12-12T22:55:43.292616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
7.7%
층 54
 
7.0%
1 30
 
3.9%
2 24
 
3.1%
원 23
 
3.0%
3 22
 
2.9%
학 21
 
2.7%
호 19
 
2.5%
4 16
 
2.1%
0 16
 
2.1%
Other values (185) 484
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 535
69.7%
Decimal Number 134
 
17.4%
Space Separator 59
 
7.7%
Uppercase Letter 11
 
1.4%
Other Punctuation 8
 
1.0%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%
Lowercase Letter 6
 
0.8%
Dash Punctuation 2
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 54
 
10.1%
원 23
 
4.3%
학 21
 
3.9%
호 19
 
3.6%
교 16
 
3.0%
빌 14
 
2.6%
딩 14
 
2.6%
관 12
 
2.2%
동 11
 
2.1%
육 10
 
1.9%
Other values (157) 341
63.7%
Decimal Number
ValueCountFrequency (%)
1 30
22.4%
2 24
17.9%
3 22
16.4%
4 16
11.9%
0 16
11.9%
5 9
 
6.7%
6 6
 
4.5%
7 5
 
3.7%
9 3
 
2.2%
8 3
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
M 2
18.2%
B 2
18.2%
Y 2
18.2%
W 1
9.1%
C 1
9.1%
N 1
9.1%
L 1
9.1%
H 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
t 2
33.3%
e 2
33.3%
u 1
16.7%
s 1
16.7%
Space Separator
ValueCountFrequency (%)
59
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 535
69.7%
Common 216
28.1%
Latin 17
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 54
 
10.1%
원 23
 
4.3%
학 21
 
3.9%
호 19
 
3.6%
교 16
 
3.0%
빌 14
 
2.6%
딩 14
 
2.6%
관 12
 
2.2%
동 11
 
2.1%
육 10
 
1.9%
Other values (157) 341
63.7%
Common
ValueCountFrequency (%)
59
27.3%
1 30
13.9%
2 24
11.1%
3 22
 
10.2%
4 16
 
7.4%
0 16
 
7.4%
5 9
 
4.2%
, 8
 
3.7%
6 6
 
2.8%
( 6
 
2.8%
Other values (6) 20
 
9.3%
Latin
ValueCountFrequency (%)
t 2
11.8%
M 2
11.8%
e 2
11.8%
B 2
11.8%
Y 2
11.8%
W 1
5.9%
u 1
5.9%
C 1
5.9%
N 1
5.9%
s 1
5.9%
Other values (2) 2
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 535
69.7%
ASCII 233
30.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
25.3%
1 30
12.9%
2 24
10.3%
3 22
 
9.4%
4 16
 
6.9%
0 16
 
6.9%
5 9
 
3.9%
, 8
 
3.4%
6 6
 
2.6%
( 6
 
2.6%
Other values (18) 37
15.9%
Hangul
ValueCountFrequency (%)
층 54
 
10.1%
원 23
 
4.3%
학 21
 
3.9%
호 19
 
3.6%
교 16
 
3.0%
빌 14
 
2.6%
딩 14
 
2.6%
관 12
 
2.2%
동 11
 
2.1%
육 10
 
1.9%
Other values (157) 341
63.7%

HOMEPAGE
Text

MISSING 

Distinct79
Distinct (%)100.0%
Missing13
Missing (%)14.1%
Memory size868.0 B
2023-12-12T22:55:43.481028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length32
Mean length23.64557
Min length10

Characters and Unicode

Total characters1868
Distinct characters51
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)100.0%

Sample

1st rowhttp://nsucyber.nsu.ac.kr/
2nd rowhttp://welfare.passone.net/
3rd rowwww.ybmhakjum.com
4th rowhttps://www.hunet.co.kr/lllcard
5th rowhttp://lifelong.ghu.ac.kr
ValueCountFrequency (%)
http://nsucyber.nsu.ac.kr 1
 
1.3%
http://cyber.gch.ac.kr 1
 
1.3%
https://www.aatesol.com 1
 
1.3%
http://daegu.koreaisacademy.com 1
 
1.3%
https://lifelong.chosun.ac.kr/lifelong/index.do 1
 
1.3%
https://blog.naver.com/gkdus3493 1
 
1.3%
https://kjlc.co.kr 1
 
1.3%
hjcar.foredu.kr 1
 
1.3%
http://www.geosung1.co.kr 1
 
1.3%
hd21.or.kr 1
 
1.3%
Other values (69) 69
87.3%
2023-12-12T22:55:43.786889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 191
 
10.2%
/ 142
 
7.6%
t 129
 
6.9%
w 122
 
6.5%
o 115
 
6.2%
r 100
 
5.4%
c 93
 
5.0%
a 86
 
4.6%
e 86
 
4.6%
h 85
 
4.6%
Other values (41) 719
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1432
76.7%
Other Punctuation 386
 
20.7%
Decimal Number 29
 
1.6%
Other Letter 14
 
0.7%
Dash Punctuation 5
 
0.3%
Connector Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 129
 
9.0%
w 122
 
8.5%
o 115
 
8.0%
r 100
 
7.0%
c 93
 
6.5%
a 86
 
6.0%
e 86
 
6.0%
h 85
 
5.9%
p 74
 
5.2%
k 69
 
4.8%
Other values (14) 473
33.0%
Other Letter
ValueCountFrequency (%)
웅 2
14.3%
원 1
 
7.1%
드 1
 
7.1%
예 1
 
7.1%
학 1
 
7.1%
공 1
 
7.1%
터 1
 
7.1%
센 1
 
7.1%
화 1
 
7.1%
문 1
 
7.1%
Other values (3) 3
21.4%
Decimal Number
ValueCountFrequency (%)
2 6
20.7%
0 5
17.2%
3 4
13.8%
5 3
10.3%
1 3
10.3%
9 3
10.3%
4 2
 
6.9%
6 2
 
6.9%
8 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 191
49.5%
/ 142
36.8%
: 53
 
13.7%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1432
76.7%
Common 422
 
22.6%
Hangul 14
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 129
 
9.0%
w 122
 
8.5%
o 115
 
8.0%
r 100
 
7.0%
c 93
 
6.5%
a 86
 
6.0%
e 86
 
6.0%
h 85
 
5.9%
p 74
 
5.2%
k 69
 
4.8%
Other values (14) 473
33.0%
Common
ValueCountFrequency (%)
. 191
45.3%
/ 142
33.6%
: 53
 
12.6%
2 6
 
1.4%
0 5
 
1.2%
- 5
 
1.2%
3 4
 
0.9%
5 3
 
0.7%
1 3
 
0.7%
9 3
 
0.7%
Other values (4) 7
 
1.7%
Hangul
ValueCountFrequency (%)
웅 2
14.3%
원 1
 
7.1%
드 1
 
7.1%
예 1
 
7.1%
학 1
 
7.1%
공 1
 
7.1%
터 1
 
7.1%
센 1
 
7.1%
화 1
 
7.1%
문 1
 
7.1%
Other values (3) 3
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1854
99.3%
Hangul 14
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 191
 
10.3%
/ 142
 
7.7%
t 129
 
7.0%
w 122
 
6.6%
o 115
 
6.2%
r 100
 
5.4%
c 93
 
5.0%
a 86
 
4.6%
e 86
 
4.6%
h 85
 
4.6%
Other values (28) 705
38.0%
Hangul
ValueCountFrequency (%)
웅 2
14.3%
원 1
 
7.1%
드 1
 
7.1%
예 1
 
7.1%
학 1
 
7.1%
공 1
 
7.1%
터 1
 
7.1%
센 1
 
7.1%
화 1
 
7.1%
문 1
 
7.1%
Other values (3) 3
21.4%

MAJOR_EDU_NM_1
Text

Distinct86
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size868.0 B
2023-12-12T22:55:43.984776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length21
Mean length10.73913
Min length2

Characters and Unicode

Total characters988
Distinct characters256
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

Unique81 ?
Unique (%)88.0%

Sample

1st row사회복지사2급 자격증
2nd row사회복지사 자격과정
3rd row사회복지사 2급 자격증과정
4th row사회복지사
5th row사회복지현장실습
ValueCountFrequency (%)
사회복지사 5
 
2.9%
자격과정 4
 
2.3%
컴퓨터활용능력 3
 
1.7%
취득과정 3
 
1.7%
사회복지사2급 3
 
1.7%
2급 3
 
1.7%
운전면허 3
 
1.7%
공인중개사 2
 
1.1%
자격증 2
 
1.1%
및 2
 
1.1%
Other values (136) 145
82.9%
2023-12-12T22:55:44.289734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
8.5%
사 44
 
4.5%
정 30
 
3.0%
과 26
 
2.6%
기 17
 
1.7%
지 17
 
1.7%
자 17
 
1.7%
회 16
 
1.6%
2 15
 
1.5%
복 14
 
1.4%
Other values (246) 708
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 773
78.2%
Space Separator 84
 
8.5%
Decimal Number 37
 
3.7%
Lowercase Letter 28
 
2.8%
Uppercase Letter 28
 
2.8%
Other Punctuation 15
 
1.5%
Open Punctuation 10
 
1.0%
Close Punctuation 10
 
1.0%
Math Symbol 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 44
 
5.7%
정 30
 
3.9%
과 26
 
3.4%
기 17
 
2.2%
지 17
 
2.2%
자 17
 
2.2%
회 16
 
2.1%
복 14
 
1.8%
인 14
 
1.8%
교 13
 
1.7%
Other values (200) 565
73.1%
Lowercase Letter
ValueCountFrequency (%)
t 6
21.4%
e 3
10.7%
o 3
10.7%
a 2
 
7.1%
r 2
 
7.1%
h 2
 
7.1%
d 1
 
3.6%
y 1
 
3.6%
p 1
 
3.6%
g 1
 
3.6%
Other values (6) 6
21.4%
Uppercase Letter
ValueCountFrequency (%)
A 6
21.4%
D 5
17.9%
C 4
14.3%
S 3
10.7%
I 3
10.7%
Y 1
 
3.6%
T 1
 
3.6%
Q 1
 
3.6%
O 1
 
3.6%
P 1
 
3.6%
Other values (2) 2
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 15
40.5%
1 12
32.4%
0 4
 
10.8%
3 3
 
8.1%
8 2
 
5.4%
6 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 8
53.3%
/ 3
 
20.0%
. 2
 
13.3%
: 1
 
6.7%
& 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 9
90.0%
[ 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 9
90.0%
] 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
~ 1
33.3%
Space Separator
ValueCountFrequency (%)
84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 773
78.2%
Common 159
 
16.1%
Latin 56
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 44
 
5.7%
정 30
 
3.9%
과 26
 
3.4%
기 17
 
2.2%
지 17
 
2.2%
자 17
 
2.2%
회 16
 
2.1%
복 14
 
1.8%
인 14
 
1.8%
교 13
 
1.7%
Other values (200) 565
73.1%
Latin
ValueCountFrequency (%)
t 6
 
10.7%
A 6
 
10.7%
D 5
 
8.9%
C 4
 
7.1%
S 3
 
5.4%
e 3
 
5.4%
I 3
 
5.4%
o 3
 
5.4%
a 2
 
3.6%
r 2
 
3.6%
Other values (18) 19
33.9%
Common
ValueCountFrequency (%)
84
52.8%
2 15
 
9.4%
1 12
 
7.5%
( 9
 
5.7%
) 9
 
5.7%
, 8
 
5.0%
0 4
 
2.5%
3 3
 
1.9%
/ 3
 
1.9%
+ 2
 
1.3%
Other values (8) 10
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 773
78.2%
ASCII 215
 
21.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
39.1%
2 15
 
7.0%
1 12
 
5.6%
( 9
 
4.2%
) 9
 
4.2%
, 8
 
3.7%
t 6
 
2.8%
A 6
 
2.8%
D 5
 
2.3%
C 4
 
1.9%
Other values (36) 57
26.5%
Hangul
ValueCountFrequency (%)
사 44
 
5.7%
정 30
 
3.9%
과 26
 
3.4%
기 17
 
2.2%
지 17
 
2.2%
자 17
 
2.2%
회 16
 
2.1%
복 14
 
1.8%
인 14
 
1.8%
교 13
 
1.7%
Other values (200) 565
73.1%

Correlations

2023-12-12T22:55:44.371050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ORGAN_NMADDRDETAIL_ADDRHOMEPAGEMAJOR_EDU_NM_1
ORGAN_NM1.0001.0001.0001.0001.000
ADDR1.0001.0001.0001.0001.000
DETAIL_ADDR1.0001.0001.0001.0000.704
HOMEPAGE1.0001.0001.0001.0001.000
MAJOR_EDU_NM_11.0001.0000.7041.0001.000

Missing values

2023-12-12T22:55:41.227545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:55:41.336767image/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.
2023-12-12T22:55:41.421004image/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

ORGAN_NMADDRDETAIL_ADDRHOMEPAGEMAJOR_EDU_NM_1
0남서울대학교부설원격평생교육원충청남도 천안시 서북구 성환읍 대학로 9121세기개발관 209호http://nsucyber.nsu.ac.kr/사회복지사2급 자격증
1패스원평생교육원서울특별시 동작구 장승배기로 1712층 일부, 11층 일부http://welfare.passone.net/사회복지사 자격과정
2(주)와이비엠넷서울특별시 종로구 종로 98YBM별관 4, 5층www.ybmhakjum.com사회복지사 2급 자격증과정
3휴넷평생교육원서울특별시 구로구 디지털로26길 5에이스하이엔드타워1차 8층https://www.hunet.co.kr/lllcard사회복지사
4광주보건대학교부설평생교육원광주광역시 광산구 북문대로419번길 73솔로몬관1층http://lifelong.ghu.ac.kr사회복지현장실습
5잠실한국문화센터평생교육원서울특별시 송파구 백제고분로9길 373층 잠실한국문화센터평생교육원www.js-hanc.com카페디저트
6전주여성인력개발평생교육원전라북도 전주시 완산구 장승배기로 2134층www.jjwoman.or.kr산모신생아건강관리사
7인애복지재단경남종합사회복지관경상남도 창원시 마산회원구 팔용로 272<NA>www.knsw.or.kr어르신 컴퓨터 기초반
8군산여성인력개발센터전라북도 군산시 백토로 119대주빌딩 2층http://www.kswork.or.kr소도구필레테스
9경기대학교원격교육원경기도 수원시 영통구 광교산로 154-42미래관 510호 원격교육원http://www.ekgu.ac.kr/index관광경영학 전공과정
ORGAN_NMADDRDETAIL_ADDRHOMEPAGEMAJOR_EDU_NM_1
82양서면주민자치위원회경기도 양평군 양서면 북한강로 38에코힐링센타4층<NA>요가
83한국교통대학교부설평생교육원충청북도 충주시 대소원면 대학로 50강의동(W5) 107호https://edulife.ut.ac.kr대조 풍수지리, 한국전통서각(현대서각)
84구미대학교부설평생교육원경상북도 구미시 야은로 37(부곡동)365.gumi.ac.kr부동산경매
85주현컴퓨터평생교육원서울특별시 송파구 송파대로 284소석빌딩 4층http://www.jucomputer.comITQ(한글,엑셀,파워포인트)자격증취득및활용
86예랑도예학원(송파점)서울특별시 송파구 백제고분로 4143층https://blog.naver.com/yerangdoye도자기물레성형
87엘리트배관용접학원경기도 양주시 백석읍 연곡로124번길 111층elitewelding.eplus-m.kr피복아크용접입문
88YBM어학원종로e4u센터서울특별시 종로구 삼일대로20길 6YBM어학원 종로e4u센터http://e4u.ybmedu.com/hakwon/center/center_main.asp미친토익
89(주)웅웅드론평생교육원대구광역시 동구 아양로 39우진빌딩 6층https://웅웅드론.com/드론기초입문
90수완우리뷰티미용학원광주광역시 광산구 풍영로101번안길 19-14소층망빌딩 4층https://blog.naver.com/2brightlaw헤어미용사자격증반
91경희사이버대학교서울특별시 동대문구 경희대로 26경희사이버대학교 네오르네상스관www.khcu.ac.kr시간제등록생 모집 강좌