Overview

Dataset statistics

Number of variables8
Number of observations135
Missing cells35
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory65.0 B

Variable types

Text7
Categorical1

Dataset

Description전국전문대학교 현황(대학명,지역,전화,팩스,대표 이메일 등)
Author한국전문대학교육협의회
URLhttps://www.data.go.kr/data/15068978/fileData.do

Alerts

대표메일 has 34 (25.2%) missing valuesMissing
대학명 has unique valuesUnique
영문명 has unique valuesUnique
주소 has unique valuesUnique
홈페이지 has unique valuesUnique
전화 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:28:55.290524
Analysis finished2023-12-12 01:28:56.141655
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대학명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:28:56.407467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.3777778
Min length4

Characters and Unicode

Total characters861
Distinct characters121
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st row가톨릭상지대학교
2nd row강동대학교
3rd row강릉영동대학교
4th row강원관광대학교
5th row강원도립대학교
ValueCountFrequency (%)
가톨릭상지대학교 1
 
0.7%
인덕대학교 1
 
0.7%
웅지세무대학교 1
 
0.7%
울산과학대학교 1
 
0.7%
우송정보대학 1
 
0.7%
용인송담대학교 1
 
0.7%
오산대학교 1
 
0.7%
영진전문대학교 1
 
0.7%
영남이공대학교 1
 
0.7%
영남외국어대학 1
 
0.7%
Other values (125) 125
92.6%
2023-12-12T10:28:56.956470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 149
17.3%
대 145
16.8%
교 124
 
14.4%
과 16
 
1.9%
동 16
 
1.9%
경 15
 
1.7%
전 14
 
1.6%
보 14
 
1.6%
산 13
 
1.5%
건 12
 
1.4%
Other values (111) 343
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 861
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 149
17.3%
대 145
16.8%
교 124
 
14.4%
과 16
 
1.9%
동 16
 
1.9%
경 15
 
1.7%
전 14
 
1.6%
보 14
 
1.6%
산 13
 
1.5%
건 12
 
1.4%
Other values (111) 343
39.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 861
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 149
17.3%
대 145
16.8%
교 124
 
14.4%
과 16
 
1.9%
동 16
 
1.9%
경 15
 
1.7%
전 14
 
1.6%
보 14
 
1.6%
산 13
 
1.5%
건 12
 
1.4%
Other values (111) 343
39.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 861
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 149
17.3%
대 145
16.8%
교 124
 
14.4%
과 16
 
1.9%
동 16
 
1.9%
경 15
 
1.7%
전 14
 
1.6%
보 14
 
1.6%
산 13
 
1.5%
건 12
 
1.4%
Other values (111) 343
39.8%

영문명
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:28:57.389055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length34
Mean length23.659259
Min length12

Characters and Unicode

Total characters3194
Distinct characters50
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st rowCATHOLIC SANGJI COLLEGE
2nd rowGANGDONG UNIVERSITY
3rd rowGANGNEUNG YEONGDONG UNIVERSITY
4th rowKANGWON TOURISM COLLEGE
5th rowGANGWON STATE UNIVERSITY
ValueCountFrequency (%)
university 71
 
17.6%
college 58
 
14.4%
of 24
 
5.9%
science 12
 
3.0%
health 11
 
2.7%
institute 9
 
2.2%
technology 8
 
2.0%
arts 5
 
1.2%
and 5
 
1.2%
korea 5
 
1.2%
Other values (164) 196
48.5%
2023-12-12T10:28:57.994272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 339
 
10.6%
N 286
 
9.0%
271
 
8.5%
I 235
 
7.4%
O 228
 
7.1%
G 174
 
5.4%
U 172
 
5.4%
S 169
 
5.3%
L 168
 
5.3%
T 153
 
4.8%
Other values (40) 999
31.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2782
87.1%
Space Separator 271
 
8.5%
Lowercase Letter 124
 
3.9%
Final Punctuation 6
 
0.2%
Other Punctuation 5
 
0.2%
Dash Punctuation 4
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 339
12.2%
N 286
 
10.3%
I 235
 
8.4%
O 228
 
8.2%
G 174
 
6.3%
U 172
 
6.2%
S 169
 
6.1%
L 168
 
6.0%
T 153
 
5.5%
C 132
 
4.7%
Other values (14) 726
26.1%
Lowercase Letter
ValueCountFrequency (%)
n 17
13.7%
e 16
12.9%
o 11
8.9%
a 11
8.9%
t 10
 
8.1%
i 10
 
8.1%
y 7
 
5.6%
g 6
 
4.8%
s 5
 
4.0%
h 5
 
4.0%
Other values (9) 26
21.0%
Other Punctuation
ValueCountFrequency (%)
& 4
80.0%
' 1
 
20.0%
Space Separator
ValueCountFrequency (%)
271
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2906
91.0%
Common 288
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 339
 
11.7%
N 286
 
9.8%
I 235
 
8.1%
O 228
 
7.8%
G 174
 
6.0%
U 172
 
5.9%
S 169
 
5.8%
L 168
 
5.8%
T 153
 
5.3%
C 132
 
4.5%
Other values (33) 850
29.2%
Common
ValueCountFrequency (%)
271
94.1%
’ 6
 
2.1%
& 4
 
1.4%
- 4
 
1.4%
( 1
 
0.3%
) 1
 
0.3%
' 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3188
99.8%
Punctuation 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 339
 
10.6%
N 286
 
9.0%
271
 
8.5%
I 235
 
7.4%
O 228
 
7.2%
G 174
 
5.5%
U 172
 
5.4%
S 169
 
5.3%
L 168
 
5.3%
T 153
 
4.8%
Other values (39) 993
31.1%
Punctuation
ValueCountFrequency (%)
’ 6
100.0%

지역
Categorical

Distinct17
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
경기
31 
경북
15 
경남
10 
부산
9 
서울
9 
Other values (12)
61 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row경북
2nd row충북
3rd row강원
4th row강원
5th row강원

Common Values

ValueCountFrequency (%)
경기 31
23.0%
경북 15
11.1%
경남 10
 
7.4%
부산 9
 
6.7%
서울 9
 
6.7%
전남 9
 
6.7%
전북 8
 
5.9%
강원 8
 
5.9%
대구 7
 
5.2%
광주 6
 
4.4%
Other values (7) 23
17.0%

Length

2023-12-12T10:28:58.188054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 31
23.0%
경북 15
11.1%
경남 10
 
7.4%
부산 9
 
6.7%
서울 9
 
6.7%
전남 9
 
6.7%
전북 8
 
5.9%
강원 8
 
5.9%
대구 7
 
5.2%
광주 6
 
4.4%
Other values (7) 23
17.0%

주소
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:28:58.468244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length36
Mean length24.296296
Min length13

Characters and Unicode

Total characters3280
Distinct characters222
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st row경북 안동시 상지길 45
2nd row충북 음성군 감곡면 대학길 278
3rd row강원도 강릉시 공제로 357
4th row강원도 태백시 대학길 97(황지동 산 439번지) 강원관광대학교
5th row강원 강릉시 주문진읍 연주로 270 (우 210-804)
ValueCountFrequency (%)
경기도 30
 
4.2%
경북 14
 
1.9%
경남 9
 
1.3%
전남 9
 
1.3%
북구 8
 
1.1%
대학길 8
 
1.1%
부산광역시 8
 
1.1%
대구광역시 7
 
1.0%
강원도 7
 
1.0%
충남 6
 
0.8%
Other values (517) 613
85.3%
2023-12-12T10:28:58.926776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
597
 
18.2%
시 127
 
3.9%
1 115
 
3.5%
로 105
 
3.2%
대 88
 
2.7%
구 76
 
2.3%
경 75
 
2.3%
5 66
 
2.0%
학 61
 
1.9%
7 60
 
1.8%
Other values (212) 1910
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1953
59.5%
Space Separator 597
 
18.2%
Decimal Number 588
 
17.9%
Close Punctuation 56
 
1.7%
Open Punctuation 54
 
1.6%
Dash Punctuation 27
 
0.8%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 127
 
6.5%
로 105
 
5.4%
대 88
 
4.5%
구 76
 
3.9%
경 75
 
3.8%
학 61
 
3.1%
동 59
 
3.0%
길 53
 
2.7%
산 53
 
2.7%
도 51
 
2.6%
Other values (193) 1205
61.7%
Decimal Number
ValueCountFrequency (%)
1 115
19.6%
5 66
11.2%
7 60
10.2%
3 60
10.2%
2 56
9.5%
0 55
9.4%
4 53
9.0%
6 46
 
7.8%
8 40
 
6.8%
9 37
 
6.3%
Other Punctuation
ValueCountFrequency (%)
/ 3
60.0%
: 1
 
20.0%
. 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 54
96.4%
] 2
 
3.6%
Open Punctuation
ValueCountFrequency (%)
( 52
96.3%
[ 2
 
3.7%
Space Separator
ValueCountFrequency (%)
597
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1953
59.5%
Common 1327
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 127
 
6.5%
로 105
 
5.4%
대 88
 
4.5%
구 76
 
3.9%
경 75
 
3.8%
학 61
 
3.1%
동 59
 
3.0%
길 53
 
2.7%
산 53
 
2.7%
도 51
 
2.6%
Other values (193) 1205
61.7%
Common
ValueCountFrequency (%)
597
45.0%
1 115
 
8.7%
5 66
 
5.0%
7 60
 
4.5%
3 60
 
4.5%
2 56
 
4.2%
0 55
 
4.1%
) 54
 
4.1%
4 53
 
4.0%
( 52
 
3.9%
Other values (9) 159
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1953
59.5%
ASCII 1327
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
597
45.0%
1 115
 
8.7%
5 66
 
5.0%
7 60
 
4.5%
3 60
 
4.5%
2 56
 
4.2%
0 55
 
4.1%
) 54
 
4.1%
4 53
 
4.0%
( 52
 
3.9%
Other values (9) 159
 
12.0%
Hangul
ValueCountFrequency (%)
시 127
 
6.5%
로 105
 
5.4%
대 88
 
4.5%
구 76
 
3.9%
경 75
 
3.8%
학 61
 
3.1%
동 59
 
3.0%
길 53
 
2.7%
산 53
 
2.7%
도 51
 
2.6%
Other values (193) 1205
61.7%

홈페이지
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:28:59.186521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length21.437037
Min length15

Characters and Unicode

Total characters2894
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st rowhttp://www.csj.ac.kr
2nd rowhttp://www.gangdong.ac.kr
3rd rowhttp://www.gyc.ac.kr
4th rowhttp://www.kt.ac.kr
5th rowhttp://www.gw.ac.kr
ValueCountFrequency (%)
http://www.csj.ac.kr 1
 
0.7%
http://www.induk.ac.kr 1
 
0.7%
http://www.wat.ac.kr 1
 
0.7%
http://www.uc.ac.kr 1
 
0.7%
http://www.wsi.ac.kr 1
 
0.7%
http://www.ysc.ac.kr 1
 
0.7%
http://www.osan.ac.kr 1
 
0.7%
http://www.yju.ac.kr 1
 
0.7%
http://www.ync.ac.kr 1
 
0.7%
http://www.yflc.ac.kr 1
 
0.7%
Other values (125) 125
92.6%
2023-12-12T10:28:59.569155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 411
14.2%
. 401
13.9%
t 293
10.1%
/ 282
9.7%
c 190
 
6.6%
a 177
 
6.1%
k 168
 
5.8%
h 162
 
5.6%
p 145
 
5.0%
r 142
 
4.9%
Other values (17) 523
18.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2075
71.7%
Other Punctuation 818
 
28.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 411
19.8%
t 293
14.1%
c 190
9.2%
a 177
8.5%
k 168
8.1%
h 162
 
7.8%
p 145
 
7.0%
r 142
 
6.8%
n 61
 
2.9%
s 56
 
2.7%
Other values (13) 270
13.0%
Other Punctuation
ValueCountFrequency (%)
. 401
49.0%
/ 282
34.5%
: 135
 
16.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2075
71.7%
Common 819
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 411
19.8%
t 293
14.1%
c 190
9.2%
a 177
8.5%
k 168
8.1%
h 162
 
7.8%
p 145
 
7.0%
r 142
 
6.8%
n 61
 
2.9%
s 56
 
2.7%
Other values (13) 270
13.0%
Common
ValueCountFrequency (%)
. 401
49.0%
/ 282
34.4%
: 135
 
16.5%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 411
14.2%
. 401
13.9%
t 293
10.1%
/ 282
9.7%
c 190
 
6.6%
a 177
 
6.1%
k 168
 
5.8%
h 162
 
5.6%
p 145
 
5.0%
r 142
 
4.9%
Other values (17) 523
18.1%

전화
Text

UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:28:59.814172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length12
Mean length12.911111
Min length9

Characters and Unicode

Total characters1743
Distinct characters17
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)100.0%

Sample

1st row054-857-9101
2nd row043-879-3312~8
3rd row033-6100-127
4th row033-550-6114
5th row033-660-8000
ValueCountFrequency (%)
054-857-9101 1
 
0.7%
041-580-1114 1
 
0.7%
054-851-3500 1
 
0.7%
031-400-6900 1
 
0.7%
7000 1
 
0.7%
031-880-5555 1
 
0.7%
031-441-1100 1
 
0.7%
055-751-2000 1
 
0.7%
053-810-0122 1
 
0.7%
031-490-6511 1
 
0.7%
Other values (133) 133
93.0%
2023-12-12T10:29:00.189962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 413
23.7%
- 269
15.4%
1 188
10.8%
3 149
 
8.5%
5 143
 
8.2%
2 128
 
7.3%
4 120
 
6.9%
6 103
 
5.9%
7 69
 
4.0%
9 63
 
3.6%
Other values (7) 98
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1431
82.1%
Dash Punctuation 269
 
15.4%
Math Symbol 18
 
1.0%
Other Punctuation 9
 
0.5%
Space Separator 8
 
0.5%
Close Punctuation 6
 
0.3%
Open Punctuation 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 413
28.9%
1 188
13.1%
3 149
 
10.4%
5 143
 
10.0%
2 128
 
8.9%
4 120
 
8.4%
6 103
 
7.2%
7 69
 
4.8%
9 63
 
4.4%
8 55
 
3.8%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
/ 1
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 269
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1743
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 413
23.7%
- 269
15.4%
1 188
10.8%
3 149
 
8.5%
5 143
 
8.2%
2 128
 
7.3%
4 120
 
6.9%
6 103
 
5.9%
7 69
 
4.0%
9 63
 
3.6%
Other values (7) 98
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 413
23.7%
- 269
15.4%
1 188
10.8%
3 149
 
8.5%
5 143
 
8.2%
2 128
 
7.3%
4 120
 
6.9%
6 103
 
5.9%
7 69
 
4.0%
9 63
 
3.6%
Other values (7) 98
 
5.6%

팩스
Text

Distinct134
Distinct (%)100.0%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2023-12-12T10:29:00.430912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length12.410448
Min length9

Characters and Unicode

Total characters1663
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)100.0%

Sample

1st row054-857-9590
2nd row043-879-3310
3rd row033-6100-364
4th row033-550-6134
5th row033-660-8015
ValueCountFrequency (%)
054-857-9590 1
 
0.7%
053-627-0145 1
 
0.7%
031-400-7097 1
 
0.7%
031-883-5113 1
 
0.7%
031-442-4400 1
 
0.7%
055-751-2099 1
 
0.7%
041-580-1060 1
 
0.7%
053-810-0199 1
 
0.7%
053-625-1688 1
 
0.7%
02-950-7059 1
 
0.7%
Other values (131) 131
92.9%
2023-12-12T10:29:00.829300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 301
18.1%
- 265
15.9%
3 171
10.3%
1 156
9.4%
5 155
9.3%
2 127
7.6%
9 109
 
6.6%
4 107
 
6.4%
6 104
 
6.3%
7 80
 
4.8%
Other values (5) 88
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1377
82.8%
Dash Punctuation 265
 
15.9%
Close Punctuation 7
 
0.4%
Space Separator 7
 
0.4%
Other Punctuation 4
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 301
21.9%
3 171
12.4%
1 156
11.3%
5 155
11.3%
2 127
9.2%
9 109
 
7.9%
4 107
 
7.8%
6 104
 
7.6%
7 80
 
5.8%
8 67
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1663
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 301
18.1%
- 265
15.9%
3 171
10.3%
1 156
9.4%
5 155
9.3%
2 127
7.6%
9 109
 
6.6%
4 107
 
6.4%
6 104
 
6.3%
7 80
 
4.8%
Other values (5) 88
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 301
18.1%
- 265
15.9%
3 171
10.3%
1 156
9.4%
5 155
9.3%
2 127
7.6%
9 109
 
6.6%
4 107
 
6.4%
6 104
 
6.3%
7 80
 
4.8%
Other values (5) 88
 
5.3%

대표메일
Text

MISSING 

Distinct101
Distinct (%)100.0%
Missing34
Missing (%)25.2%
Memory size1.2 KiB
2023-12-12T10:29:01.082993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length17.19802
Min length9

Characters and Unicode

Total characters1737
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st rowtyyun@csj.ac.kr
2nd rowipsi19@gangdong.ac.kr
3rd rowjbj@gyc.ac.kr
4th rowktcqi@naver.com
5th rowwebmaster@gw.ac.kr
ValueCountFrequency (%)
engine@kbsc.ac.kr 1
 
1.0%
jhcho@yonam.ac.kr 1
 
1.0%
jy393@induk.ac.kr 1
 
1.0%
kyu@yuhan.ac.kr 1
 
1.0%
wat.ac.kr 1
 
1.0%
1
 
1.0%
pianse3 1
 
1.0%
chjung26@ysc.ac.kr 1
 
1.0%
sgyoon@osan.ac.kr 1
 
1.0%
sangyoul@yju.ac.kr 1
 
1.0%
Other values (93) 93
90.3%
2023-12-12T10:29:01.442767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 194
 
11.2%
a 162
 
9.3%
c 150
 
8.6%
k 147
 
8.5%
r 121
 
7.0%
@ 100
 
5.8%
n 77
 
4.4%
e 76
 
4.4%
s 75
 
4.3%
o 75
 
4.3%
Other values (28) 560
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1347
77.5%
Other Punctuation 294
 
16.9%
Decimal Number 93
 
5.4%
Space Separator 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 162
12.0%
c 150
11.1%
k 147
10.9%
r 121
 
9.0%
n 77
 
5.7%
e 76
 
5.6%
s 75
 
5.6%
o 75
 
5.6%
i 67
 
5.0%
h 57
 
4.2%
Other values (14) 340
25.2%
Decimal Number
ValueCountFrequency (%)
0 15
16.1%
3 13
14.0%
1 12
12.9%
8 10
10.8%
2 10
10.8%
9 8
8.6%
5 7
7.5%
4 7
7.5%
6 6
 
6.5%
7 5
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 194
66.0%
@ 100
34.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1347
77.5%
Common 390
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 162
12.0%
c 150
11.1%
k 147
10.9%
r 121
 
9.0%
n 77
 
5.7%
e 76
 
5.6%
s 75
 
5.6%
o 75
 
5.6%
i 67
 
5.0%
h 57
 
4.2%
Other values (14) 340
25.2%
Common
ValueCountFrequency (%)
. 194
49.7%
@ 100
25.6%
0 15
 
3.8%
3 13
 
3.3%
1 12
 
3.1%
8 10
 
2.6%
2 10
 
2.6%
9 8
 
2.1%
5 7
 
1.8%
4 7
 
1.8%
Other values (4) 14
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1737
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 194
 
11.2%
a 162
 
9.3%
c 150
 
8.6%
k 147
 
8.5%
r 121
 
7.0%
@ 100
 
5.8%
n 77
 
4.4%
e 76
 
4.4%
s 75
 
4.3%
o 75
 
4.3%
Other values (28) 560
32.2%

Missing values

2023-12-12T10:28:55.778126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:28:55.963170image/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.
2023-12-12T10:28:56.086527image/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

대학명영문명지역주소홈페이지전화팩스대표메일
0가톨릭상지대학교CATHOLIC SANGJI COLLEGE경북경북 안동시 상지길 45http://www.csj.ac.kr054-857-9101054-857-9590tyyun@csj.ac.kr
1강동대학교GANGDONG UNIVERSITY충북충북 음성군 감곡면 대학길 278http://www.gangdong.ac.kr043-879-3312~8043-879-3310ipsi19@gangdong.ac.kr
2강릉영동대학교GANGNEUNG YEONGDONG UNIVERSITY강원강원도 강릉시 공제로 357http://www.gyc.ac.kr033-6100-127033-6100-364jbj@gyc.ac.kr
3강원관광대학교KANGWON TOURISM COLLEGE강원강원도 태백시 대학길 97(황지동 산 439번지) 강원관광대학교http://www.kt.ac.kr033-550-6114033-550-6134ktcqi@naver.com
4강원도립대학교GANGWON STATE UNIVERSITY강원강원 강릉시 주문진읍 연주로 270 (우 210-804)http://www.gw.ac.kr033-660-8000033-660-8015webmaster@gw.ac.kr
5거제대학교KOJE COLLEGE경남경남 거제시 마전1길 91(구.장승포동 654-1)http://www.koje.ac.kr055-680-1507055-680-1540tipark@koje.ac.kr
6경기과학기술대학교GYEONGGI UNIVERSITY OF SCIENCEANDTECHNOLOGY경기경기도 시흥시 경기과기대로 269(정왕동)http://www.gtec.ac.kr031-496-4791031-496-9165ebebe@gtec.ac.kr
7경남도립거창대학University of Gyeongnam Geochang(UGG)경남경남 거창군 거창읍 거창대학로 72(대평리 1396) 경남도립거창대학http://www.gc.ac.kr055-254-2762055-254-2718imantra@korea.kr
8경남도립남해대학UniversityofGyeongnamNamhae경남경남 남해군 남해읍 화전로78번길 30http://www.namhae.ac.kr055-254-2400055-254-2419sskang@namhae.ac.kr
9경남정보대학교KYUNGNAMCOLLEGE OF INFORMATION & TECHNOLOGY부산부산광역시 사상구 주례로 45http://web.kit.ac.kr/www051-324-5555051-312-1009dongil@eagle.kit.ac.kr
대학명영문명지역주소홈페이지전화팩스대표메일
125한국골프대학교KOREA GOLF UNIVERSITY강원강원도 횡성군 우천면 하대5길 101http://www.kg.ac.kr033-810-1000033-810-1001hkw@kg.ac.kr
126한국관광대학교KOREA TOURISM COLLEGE경기(467-745)경기도 이천시 이장로 311번길 197-73http://www.ktc.ac.kr031-644-1100031-644-1014yong@ktc.ac.kr
127한국복지대학교KOREA NATIONAL UNIVERSIRY OF WELFARE경기경기도 평택시 삼남로 283http://www.knuw.ac.kr031-610-4600031-610-4615s001030@knuw.ac.kr
128한국승강기대학교KOREA LIFT COLLEGE경남경상남도 거창군 거창읍 운정1길 120http://www.klc.ac.kr055-949-2220055-949-2222jhs@klc.ac.kr
129한국영상대학교KOREA UNIVERSITY OF MEDIA ARTS세종30056 세종특별자치시 장군면 대학길 300http://www.pro.ac.kr/044-850-9032044-850-9039mgg@pro.ac.kr
130한림성심대학교HALLYM POLYTECHNIC UNIVERSITY강원강원도 춘천시 동면 장학길 48 한림성심대학교http://www.hsc.ac.kr033-240-9006033-252-2992yesmoney@hsc.ac.kr
131한양여자대학교HANYANG WOMEN'S UNIVERSITY서울(04763) 서울시 성동구 살곶이길200(사근동)http://www.hywoman.ac.kr02-2290-211402-2290-2039<NA>
132한영대학HANYEONG COLLEGE전남전남 여수시 장군산길 18-43(여수시 여서동 61)http://www.hanyeong.ac.kr061-650-4000061-650-4020k8763012@hanyeong.ac.kr
133혜전대학교HYEJEON COLLEGE충남충남 홍성군 홍성읍 대학1길 19 혜전대학교http://hj.ac.kr041-630-5114041-630-5154<NA>
134호산대학교HOSAN UNIVERSITY경북경북 경산시 하양읍 대경로 105길 19http://www.hosan.ac.kr053-850-8000053-853-9754vision@hosan.ac.kr