Overview

Dataset statistics

Number of variables12
Number of observations168
Missing cells197
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory96.8 B

Variable types

Text12

Dataset

Description병역의무부과대상인 사회복무요원의 복무기간중 원격교육을 위한 온라인 e-러닝 참여 대학교 명단 군인공제회 제공 자료
Author병무청
URLhttps://www.data.go.kr/data/15062418/fileData.do

Alerts

2018년 1학기 has 32 (19.0%) missing valuesMissing
2018년 2학기 has 35 (20.8%) missing valuesMissing
2019년 1학기 has 28 (16.7%) missing valuesMissing
2019년 2학기 has 22 (13.1%) missing valuesMissing
2020년 1학기 has 17 (10.1%) missing valuesMissing
2020년 2학기 has 16 (9.5%) missing valuesMissing
2021년 1학기 has 15 (8.9%) missing valuesMissing
2021년 2학기 has 13 (7.7%) missing valuesMissing
2022년 1학기 has 9 (5.4%) missing valuesMissing
2022년 2학기 has 6 (3.6%) missing valuesMissing
2023년 1학기 has 4 (2.4%) missing valuesMissing
2023년 2학기 has unique valuesUnique

Reproduction

Analysis started2024-03-15 02:23:49.353019
Analysis finished2024-03-15 02:23:52.110678
Duration2.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2018년 1학기
Text

MISSING 

Distinct136
Distinct (%)100.0%
Missing32
Missing (%)19.0%
Memory size1.4 KiB
2024-03-15T11:23:53.177748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.9779412
Min length3

Characters and Unicode

Total characters541
Distinct characters120
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row카톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
경기대 1
 
0.7%
서울과학기술대 1
 
0.7%
전주비전대 1
 
0.7%
전주대 1
 
0.7%
전북대 1
 
0.7%
전남대 1
 
0.7%
인하대 1
 
0.7%
인천대 1
 
0.7%
인천가톨릭대 1
 
0.7%
경북대 1
 
0.7%
Other values (126) 126
92.6%
2024-03-15T11:23:54.787635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
26.6%
18
 
3.3%
17
 
3.1%
16
 
3.0%
13
 
2.4%
12
 
2.2%
11
 
2.0%
11
 
2.0%
11
 
2.0%
11
 
2.0%
Other values (110) 277
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 526
97.2%
Close Punctuation 6
 
1.1%
Open Punctuation 6
 
1.1%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
144
27.4%
18
 
3.4%
17
 
3.2%
16
 
3.0%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (107) 262
49.8%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 526
97.2%
Common 15
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
144
27.4%
18
 
3.4%
17
 
3.2%
16
 
3.0%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (107) 262
49.8%
Common
ValueCountFrequency (%)
) 6
40.0%
( 6
40.0%
, 3
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 526
97.2%
ASCII 15
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
144
27.4%
18
 
3.4%
17
 
3.2%
16
 
3.0%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (107) 262
49.8%
ASCII
ValueCountFrequency (%)
) 6
40.0%
( 6
40.0%
, 3
20.0%

2018년 2학기
Text

MISSING 

Distinct133
Distinct (%)100.0%
Missing35
Missing (%)20.8%
Memory size1.4 KiB
2024-03-15T11:23:56.013511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.9849624
Min length3

Characters and Unicode

Total characters530
Distinct characters115
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)100.0%

Sample

1st row가톨릭관동대
2nd row강남대
3rd row강동대
4th row강릉원주대
5th row강원대
ValueCountFrequency (%)
경상대 1
 
0.8%
중앙대 1
 
0.8%
전주비전대 1
 
0.8%
전주대 1
 
0.8%
전북대 1
 
0.8%
전남대 1
 
0.8%
인하대 1
 
0.8%
인천대 1
 
0.8%
인천가톨릭대 1
 
0.8%
인제대 1
 
0.8%
Other values (123) 123
92.5%
2024-03-15T11:23:57.486085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
26.2%
18
 
3.4%
17
 
3.2%
16
 
3.0%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (105) 271
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 517
97.5%
Close Punctuation 5
 
0.9%
Open Punctuation 5
 
0.9%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
139
26.9%
18
 
3.5%
17
 
3.3%
16
 
3.1%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (102) 258
49.9%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 517
97.5%
Common 13
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
139
26.9%
18
 
3.5%
17
 
3.3%
16
 
3.1%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (102) 258
49.9%
Common
ValueCountFrequency (%)
) 5
38.5%
( 5
38.5%
, 3
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 517
97.5%
ASCII 13
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
139
26.9%
18
 
3.5%
17
 
3.3%
16
 
3.1%
13
 
2.5%
12
 
2.3%
11
 
2.1%
11
 
2.1%
11
 
2.1%
11
 
2.1%
Other values (102) 258
49.9%
ASCII
ValueCountFrequency (%)
) 5
38.5%
( 5
38.5%
, 3
23.1%

2019년 1학기
Text

MISSING 

Distinct140
Distinct (%)100.0%
Missing28
Missing (%)16.7%
Memory size1.4 KiB
2024-03-15T11:23:58.665518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length4.0642857
Min length3

Characters and Unicode

Total characters569
Distinct characters124
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique140 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row가톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
경기대 1
 
0.7%
원광대 1
 
0.7%
인제대 1
 
0.7%
인천가톨릭대 1
 
0.7%
인천대 1
 
0.7%
인하대 1
 
0.7%
인하공업전문대 1
 
0.7%
전남대 1
 
0.7%
원광디지털대 1
 
0.7%
선문대 1
 
0.7%
Other values (130) 130
92.9%
2024-03-15T11:24:00.152946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
25.5%
20
 
3.5%
18
 
3.2%
16
 
2.8%
14
 
2.5%
13
 
2.3%
12
 
2.1%
12
 
2.1%
11
 
1.9%
11
 
1.9%
Other values (114) 297
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
97.2%
Open Punctuation 6
 
1.1%
Close Punctuation 6
 
1.1%
Other Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
145
26.2%
20
 
3.6%
18
 
3.3%
16
 
2.9%
14
 
2.5%
13
 
2.4%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
Other values (111) 281
50.8%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 553
97.2%
Common 16
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
145
26.2%
20
 
3.6%
18
 
3.3%
16
 
2.9%
14
 
2.5%
13
 
2.4%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
Other values (111) 281
50.8%
Common
ValueCountFrequency (%)
( 6
37.5%
) 6
37.5%
, 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
97.2%
ASCII 16
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
145
26.2%
20
 
3.6%
18
 
3.3%
16
 
2.9%
14
 
2.5%
13
 
2.4%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
Other values (111) 281
50.8%
ASCII
ValueCountFrequency (%)
( 6
37.5%
) 6
37.5%
, 4
25.0%

2019년 2학기
Text

MISSING 

Distinct146
Distinct (%)100.0%
Missing22
Missing (%)13.1%
Memory size1.4 KiB
2024-03-15T11:24:01.378337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length4.0068493
Min length3

Characters and Unicode

Total characters585
Distinct characters119
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

Unique146 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row가톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
남서울대 1
 
0.7%
서울대 1
 
0.7%
유원대 1
 
0.7%
영남이공대 1
 
0.7%
용인대 1
 
0.7%
우석대 1
 
0.7%
웅지세무대 1
 
0.7%
원광대 1
 
0.7%
원광디지털대 1
 
0.7%
인제대 1
 
0.7%
Other values (136) 136
93.2%
2024-03-15T11:24:02.962524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
25.6%
20
 
3.4%
19
 
3.2%
15
 
2.6%
15
 
2.6%
14
 
2.4%
12
 
2.1%
12
 
2.1%
11
 
1.9%
10
 
1.7%
Other values (109) 307
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 569
97.3%
Close Punctuation 8
 
1.4%
Open Punctuation 8
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
150
26.4%
20
 
3.5%
19
 
3.3%
15
 
2.6%
15
 
2.6%
14
 
2.5%
12
 
2.1%
12
 
2.1%
11
 
1.9%
10
 
1.8%
Other values (107) 291
51.1%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 569
97.3%
Common 16
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
150
26.4%
20
 
3.5%
19
 
3.3%
15
 
2.6%
15
 
2.6%
14
 
2.5%
12
 
2.1%
12
 
2.1%
11
 
1.9%
10
 
1.8%
Other values (107) 291
51.1%
Common
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 569
97.3%
ASCII 16
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
150
26.4%
20
 
3.5%
19
 
3.3%
15
 
2.6%
15
 
2.6%
14
 
2.5%
12
 
2.1%
12
 
2.1%
11
 
1.9%
10
 
1.8%
Other values (107) 291
51.1%
ASCII
ValueCountFrequency (%)
) 8
50.0%
( 8
50.0%

2020년 1학기
Text

MISSING 

Distinct151
Distinct (%)100.0%
Missing17
Missing (%)10.1%
Memory size1.4 KiB
2024-03-15T11:24:04.074671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length4.2781457
Min length3

Characters and Unicode

Total characters646
Distinct characters131
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row가톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
건국대 1
 
0.7%
전주비전대 1
 
0.7%
연세대(서울 1
 
0.7%
영남대 1
 
0.7%
영남이공대 1
 
0.7%
용인대 1
 
0.7%
우석대 1
 
0.7%
원광대 1
 
0.7%
원광디지털대 1
 
0.7%
인제대 1
 
0.7%
Other values (141) 141
93.4%
2024-03-15T11:24:05.959876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
24.5%
22
 
3.4%
22
 
3.4%
19
 
2.9%
17
 
2.6%
15
 
2.3%
( 14
 
2.2%
) 14
 
2.2%
13
 
2.0%
13
 
2.0%
Other values (121) 339
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 616
95.4%
Open Punctuation 14
 
2.2%
Close Punctuation 14
 
2.2%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
158
25.6%
22
 
3.6%
22
 
3.6%
19
 
3.1%
17
 
2.8%
15
 
2.4%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 312
50.6%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 616
95.4%
Common 30
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
158
25.6%
22
 
3.6%
22
 
3.6%
19
 
3.1%
17
 
2.8%
15
 
2.4%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 312
50.6%
Common
ValueCountFrequency (%)
( 14
46.7%
) 14
46.7%
, 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 616
95.4%
ASCII 30
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
158
25.6%
22
 
3.6%
22
 
3.6%
19
 
3.1%
17
 
2.8%
15
 
2.4%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 312
50.6%
ASCII
ValueCountFrequency (%)
( 14
46.7%
) 14
46.7%
, 2
 
6.7%

2020년 2학기
Text

MISSING 

Distinct152
Distinct (%)100.0%
Missing16
Missing (%)9.5%
Memory size1.4 KiB
2024-03-15T11:24:07.296750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length4.1907895
Min length3

Characters and Unicode

Total characters637
Distinct characters129
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

Unique152 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row가톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
건국대 1
 
0.7%
유원대 1
 
0.7%
전주비전대 1
 
0.7%
영남대 1
 
0.7%
영남이공대 1
 
0.7%
용인대 1
 
0.7%
우석대 1
 
0.7%
원광대 1
 
0.7%
원광디지털대 1
 
0.7%
인천가톨릭대 1
 
0.7%
Other values (142) 142
93.4%
2024-03-15T11:24:09.058534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
24.6%
21
 
3.3%
21
 
3.3%
18
 
2.8%
17
 
2.7%
14
 
2.2%
13
 
2.0%
13
 
2.0%
) 13
 
2.0%
13
 
2.0%
Other values (119) 337
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
96.1%
Close Punctuation 13
 
2.0%
Open Punctuation 12
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
157
25.7%
21
 
3.4%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 313
51.1%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
96.1%
Common 25
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
157
25.7%
21
 
3.4%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 313
51.1%
Common
ValueCountFrequency (%)
) 13
52.0%
( 12
48.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
96.1%
ASCII 25
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
157
25.7%
21
 
3.4%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 313
51.1%
ASCII
ValueCountFrequency (%)
) 13
52.0%
( 12
48.0%

2021년 1학기
Text

MISSING 

Distinct153
Distinct (%)100.0%
Missing15
Missing (%)8.9%
Memory size1.4 KiB
2024-03-15T11:24:10.289153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length4.1764706
Min length3

Characters and Unicode

Total characters639
Distinct characters129
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

Unique153 ?
Unique (%)100.0%

Sample

1st row가천대
2nd row가톨릭관동대
3rd row강남대
4th row강동대
5th row강릉원주대
ValueCountFrequency (%)
거제대 1
 
0.7%
원광디지털대 1
 
0.7%
전주대 1
 
0.7%
연세대(미래 1
 
0.7%
영남대 1
 
0.7%
영남이공대 1
 
0.7%
용인대 1
 
0.7%
우석대 1
 
0.7%
원광대 1
 
0.7%
인제대 1
 
0.7%
Other values (143) 143
93.5%
2024-03-15T11:24:11.998879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
24.7%
22
 
3.4%
21
 
3.3%
18
 
2.8%
17
 
2.7%
14
 
2.2%
13
 
2.0%
13
 
2.0%
) 13
 
2.0%
( 13
 
2.0%
Other values (119) 337
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 613
95.9%
Close Punctuation 13
 
2.0%
Open Punctuation 13
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
158
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 312
50.9%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 613
95.9%
Common 26
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
158
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 312
50.9%
Common
ValueCountFrequency (%)
) 13
50.0%
( 13
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 613
95.9%
ASCII 26
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
158
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
17
 
2.8%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
2.0%
Other values (117) 312
50.9%
ASCII
ValueCountFrequency (%)
) 13
50.0%
( 13
50.0%

2021년 2학기
Text

MISSING 

Distinct155
Distinct (%)100.0%
Missing13
Missing (%)7.7%
Memory size1.4 KiB
2024-03-15T11:24:13.142254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.1419355
Min length3

Characters and Unicode

Total characters797
Distinct characters131
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)100.0%

Sample

1st row가야대
2nd row 가천대
3rd row 가톨릭관동대
4th row 강남대
5th row 강동대
ValueCountFrequency (%)
거제대 1
 
0.6%
원광디지털대 1
 
0.6%
전주대 1
 
0.6%
연세대(미래 1
 
0.6%
영남대 1
 
0.6%
영남이공대 1
 
0.6%
용인대 1
 
0.6%
우석대 1
 
0.6%
원광대 1
 
0.6%
인제대 1
 
0.6%
Other values (145) 145
93.5%
2024-03-15T11:24:14.764011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
20.1%
152
19.1%
22
 
2.8%
21
 
2.6%
18
 
2.3%
18
 
2.3%
14
 
1.8%
( 13
 
1.6%
13
 
1.6%
) 13
 
1.6%
Other values (121) 353
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 619
77.7%
Space Separator 152
 
19.1%
Open Punctuation 13
 
1.6%
Close Punctuation 13
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
160
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
18
 
2.9%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 315
50.9%
Space Separator
ValueCountFrequency (%)
152
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 619
77.7%
Common 178
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
160
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
18
 
2.9%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 315
50.9%
Common
ValueCountFrequency (%)
152
85.4%
( 13
 
7.3%
) 13
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 619
77.7%
ASCII 178
 
22.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
160
25.8%
22
 
3.6%
21
 
3.4%
18
 
2.9%
18
 
2.9%
14
 
2.3%
13
 
2.1%
13
 
2.1%
13
 
2.1%
12
 
1.9%
Other values (118) 315
50.9%
ASCII
ValueCountFrequency (%)
152
85.4%
( 13
 
7.3%
) 13
 
7.3%

2022년 1학기
Text

MISSING 

Distinct159
Distinct (%)100.0%
Missing9
Missing (%)5.4%
Memory size1.4 KiB
2024-03-15T11:24:15.814200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.2138365
Min length3

Characters and Unicode

Total characters829
Distinct characters135
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)100.0%

Sample

1st row가야대
2nd row 가천대
3rd row 가톨릭대
4th row 가톨릭관동대
5th row 강남대
ValueCountFrequency (%)
가천대 1
 
0.6%
인천가톨릭대 1
 
0.6%
영남대 1
 
0.6%
영남이공대 1
 
0.6%
용인대 1
 
0.6%
우석대 1
 
0.6%
원광대 1
 
0.6%
원광디지털대 1
 
0.6%
유원대 1
 
0.6%
정화예술대 1
 
0.6%
Other values (149) 149
93.7%
2024-03-15T11:24:17.352515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
19.7%
156
18.8%
24
 
2.9%
23
 
2.8%
18
 
2.2%
18
 
2.2%
16
 
1.9%
14
 
1.7%
14
 
1.7%
( 14
 
1.7%
Other values (125) 369
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 644
77.7%
Space Separator 156
 
18.8%
Open Punctuation 14
 
1.7%
Close Punctuation 14
 
1.7%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
163
25.3%
24
 
3.7%
23
 
3.6%
18
 
2.8%
18
 
2.8%
16
 
2.5%
14
 
2.2%
14
 
2.2%
13
 
2.0%
12
 
1.9%
Other values (121) 329
51.1%
Space Separator
ValueCountFrequency (%)
156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 644
77.7%
Common 185
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
163
25.3%
24
 
3.7%
23
 
3.6%
18
 
2.8%
18
 
2.8%
16
 
2.5%
14
 
2.2%
14
 
2.2%
13
 
2.0%
12
 
1.9%
Other values (121) 329
51.1%
Common
ValueCountFrequency (%)
156
84.3%
( 14
 
7.6%
) 14
 
7.6%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 644
77.7%
ASCII 185
 
22.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
163
25.3%
24
 
3.7%
23
 
3.6%
18
 
2.8%
18
 
2.8%
16
 
2.5%
14
 
2.2%
14
 
2.2%
13
 
2.0%
12
 
1.9%
Other values (121) 329
51.1%
ASCII
ValueCountFrequency (%)
156
84.3%
( 14
 
7.6%
) 14
 
7.6%
8 1
 
0.5%

2022년 2학기
Text

MISSING 

Distinct162
Distinct (%)100.0%
Missing6
Missing (%)3.6%
Memory size1.4 KiB
2024-03-15T11:24:18.301708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.2654321
Min length3

Characters and Unicode

Total characters853
Distinct characters137
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

Unique162 ?
Unique (%)100.0%

Sample

1st row가야대
2nd row 가천대
3rd row 가톨릭관동대
4th row 가톨릭대
5th row 강남대
ValueCountFrequency (%)
대구가톨릭대 1
 
0.6%
서울한영대 1
 
0.6%
인하공업전문대학 1
 
0.6%
우석대 1
 
0.6%
원광대 1
 
0.6%
원광디지털대 1
 
0.6%
유원대 1
 
0.6%
인제대 1
 
0.6%
인천가톨릭대 1
 
0.6%
인천대 1
 
0.6%
Other values (152) 152
93.8%
2024-03-15T11:24:19.494876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
19.6%
158
18.5%
27
 
3.2%
24
 
2.8%
20
 
2.3%
18
 
2.1%
17
 
2.0%
15
 
1.8%
) 13
 
1.5%
13
 
1.5%
Other values (127) 381
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 660
77.4%
Space Separator 158
 
18.5%
Close Punctuation 13
 
1.5%
Open Punctuation 13
 
1.5%
Uppercase Letter 8
 
0.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
167
25.3%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (117) 334
50.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
25.0%
I 2
25.0%
T 1
12.5%
E 1
12.5%
R 1
12.5%
A 1
12.5%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 660
77.4%
Common 185
 
21.7%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
167
25.3%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (117) 334
50.6%
Latin
ValueCountFrequency (%)
C 2
25.0%
I 2
25.0%
T 1
12.5%
E 1
12.5%
R 1
12.5%
A 1
12.5%
Common
ValueCountFrequency (%)
158
85.4%
) 13
 
7.0%
( 13
 
7.0%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 660
77.4%
ASCII 193
 
22.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
167
25.3%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (117) 334
50.6%
ASCII
ValueCountFrequency (%)
158
81.9%
) 13
 
6.7%
( 13
 
6.7%
C 2
 
1.0%
I 2
 
1.0%
8 1
 
0.5%
T 1
 
0.5%
E 1
 
0.5%
R 1
 
0.5%
A 1
 
0.5%

2023년 1학기
Text

MISSING 

Distinct164
Distinct (%)100.0%
Missing4
Missing (%)2.4%
Memory size1.4 KiB
2024-03-15T11:24:20.679266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.2439024
Min length3

Characters and Unicode

Total characters860
Distinct characters140
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

Unique164 ?
Unique (%)100.0%

Sample

1st rowICT폴리텍대학
2nd row 가야대
3rd row 가천대
4th row 가톨릭관동대
5th row 가톨릭대
ValueCountFrequency (%)
서울신학대 1
 
0.6%
서원대 1
 
0.6%
원광대 1
 
0.6%
원광디지털대 1
 
0.6%
유원대 1
 
0.6%
인제대 1
 
0.6%
인천가톨릭대 1
 
0.6%
인천대 1
 
0.6%
인하공업전문대학 1
 
0.6%
인하대 1
 
0.6%
Other values (154) 154
93.9%
2024-03-15T11:24:22.233238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
169
19.7%
159
18.5%
27
 
3.1%
24
 
2.8%
20
 
2.3%
18
 
2.1%
17
 
2.0%
15
 
1.7%
13
 
1.5%
( 13
 
1.5%
Other values (130) 385
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 666
77.4%
Space Separator 159
 
18.5%
Open Punctuation 13
 
1.5%
Close Punctuation 13
 
1.5%
Uppercase Letter 8
 
0.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
169
25.4%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (120) 338
50.8%
Uppercase Letter
ValueCountFrequency (%)
I 2
25.0%
C 2
25.0%
E 1
12.5%
A 1
12.5%
R 1
12.5%
T 1
12.5%
Space Separator
ValueCountFrequency (%)
159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 666
77.4%
Common 186
 
21.6%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
169
25.4%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (120) 338
50.8%
Latin
ValueCountFrequency (%)
I 2
25.0%
C 2
25.0%
E 1
12.5%
A 1
12.5%
R 1
12.5%
T 1
12.5%
Common
ValueCountFrequency (%)
159
85.5%
( 13
 
7.0%
) 13
 
7.0%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 666
77.4%
ASCII 194
 
22.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
169
25.4%
27
 
4.1%
24
 
3.6%
20
 
3.0%
18
 
2.7%
17
 
2.6%
15
 
2.3%
13
 
2.0%
13
 
2.0%
12
 
1.8%
Other values (120) 338
50.8%
ASCII
ValueCountFrequency (%)
159
82.0%
( 13
 
6.7%
) 13
 
6.7%
I 2
 
1.0%
C 2
 
1.0%
E 1
 
0.5%
A 1
 
0.5%
R 1
 
0.5%
8 1
 
0.5%
T 1
 
0.5%

2023년 2학기
Text

UNIQUE 

Distinct168
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T11:24:23.346881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length5.2380952
Min length3

Characters and Unicode

Total characters880
Distinct characters143
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

Unique168 ?
Unique (%)100.0%

Sample

1st rowICT폴리텍대학
2nd row 가야대
3rd row 가천대
4th row 가톨릭관동대
5th row 가톨릭대
ValueCountFrequency (%)
ict폴리텍대학 1
 
0.6%
전남대 1
 
0.6%
중원대 1
 
0.6%
원광디지털대 1
 
0.6%
유원대 1
 
0.6%
인제대 1
 
0.6%
인천가톨릭대 1
 
0.6%
인천대 1
 
0.6%
인하공업전문대학 1
 
0.6%
인하대 1
 
0.6%
Other values (158) 158
94.0%
2024-03-15T11:24:24.946215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
19.7%
163
18.5%
28
 
3.2%
24
 
2.7%
21
 
2.4%
18
 
2.0%
17
 
1.9%
15
 
1.7%
14
 
1.6%
14
 
1.6%
Other values (133) 393
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
77.5%
Space Separator 163
 
18.5%
Close Punctuation 13
 
1.5%
Open Punctuation 13
 
1.5%
Uppercase Letter 8
 
0.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
173
25.4%
28
 
4.1%
24
 
3.5%
21
 
3.1%
18
 
2.6%
17
 
2.5%
15
 
2.2%
14
 
2.1%
14
 
2.1%
12
 
1.8%
Other values (123) 346
50.7%
Uppercase Letter
ValueCountFrequency (%)
I 2
25.0%
C 2
25.0%
E 1
12.5%
R 1
12.5%
A 1
12.5%
T 1
12.5%
Space Separator
ValueCountFrequency (%)
163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 682
77.5%
Common 190
 
21.6%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
173
25.4%
28
 
4.1%
24
 
3.5%
21
 
3.1%
18
 
2.6%
17
 
2.5%
15
 
2.2%
14
 
2.1%
14
 
2.1%
12
 
1.8%
Other values (123) 346
50.7%
Latin
ValueCountFrequency (%)
I 2
25.0%
C 2
25.0%
E 1
12.5%
R 1
12.5%
A 1
12.5%
T 1
12.5%
Common
ValueCountFrequency (%)
163
85.8%
) 13
 
6.8%
( 13
 
6.8%
8 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 682
77.5%
ASCII 198
 
22.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
173
25.4%
28
 
4.1%
24
 
3.5%
21
 
3.1%
18
 
2.6%
17
 
2.5%
15
 
2.2%
14
 
2.1%
14
 
2.1%
12
 
1.8%
Other values (123) 346
50.7%
ASCII
ValueCountFrequency (%)
163
82.3%
) 13
 
6.6%
( 13
 
6.6%
I 2
 
1.0%
C 2
 
1.0%
8 1
 
0.5%
E 1
 
0.5%
R 1
 
0.5%
A 1
 
0.5%
T 1
 
0.5%

Missing values

2024-03-15T11:23:50.833233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:23:51.359521image/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.
2024-03-15T11:23:51.802020image/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

2018년 1학기2018년 2학기2019년 1학기2019년 2학기2020년 1학기2020년 2학기2021년 1학기2021년 2학기2022년 1학기2022년 2학기2023년 1학기2023년 2학기
0가천대가톨릭관동대가천대가천대가천대가천대가천대가야대가야대가야대ICT폴리텍대학ICT폴리텍대학
1카톨릭관동대강남대가톨릭관동대가톨릭관동대가톨릭관동대가톨릭관동대가톨릭관동대가천대가천대가천대가야대가야대
2강남대강동대강남대강남대강남대강남대강남대가톨릭관동대가톨릭대가톨릭관동대가천대가천대
3강동대강릉원주대강동대강동대강동대강동대강동대강남대가톨릭관동대가톨릭대가톨릭관동대가톨릭관동대
4강릉원주대강원대강릉원주대강릉원주대강릉원주대강릉원주대강릉원주대강동대강남대강남대가톨릭대가톨릭대
5강원대거재대강원대강원대강원대(삼척)강원대(삼척)강원대(삼척)강릉원주대강동대강동대강남대강남대
6거제대건국대(서울,충주)거제대거제대강원대(춘천)강원대(춘천)강원대(춘천)강원대(삼척)강릉원주대강릉원주대강동대강동대
7건국대(서울,충주)건양대건국대(서울,충주)건국대(서울)거제대거제대거제대강원대(춘천)강원대(삼척)강원대강릉원주대강릉원주대
8건양대경기대건양대건국대(충주)건국대건국대건국대거제대강원대(춘천)거제대강원대강원대
9경기대경남과학기술대경기대건양대건국대(글로컬)건국대(글로컬)건국대(글로컬)건국대거제대건국대거제대거제대
2018년 1학기2018년 2학기2019년 1학기2019년 2학기2020년 1학기2020년 2학기2021년 1학기2021년 2학기2022년 1학기2022년 2학기2023년 1학기2023년 2학기
158<NA><NA><NA><NA><NA><NA><NA><NA>홍익대호서대호남대호남대
159<NA><NA><NA><NA><NA><NA><NA><NA><NA>호원대호서대호서대
160<NA><NA><NA><NA><NA><NA><NA><NA><NA>홍익대호원대호원대
161<NA><NA><NA><NA><NA><NA><NA><NA><NA>ICT폴리텍대학홍익대홍익대
162<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>숭실대숭실대
163<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>을지대서울기독대
164<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>한밭대
165<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>을지대
166<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>두원공과대
167<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>우송대