Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.3 B

Variable types

Text3
Categorical1
Boolean1

Dataset

Description학점은행제정보시스템 평가인정항목의 지표 메뉴 정보에 대한 데이터로 메뉴, 지표번호, 메뉴명, 메뉴단계 등의 항목을 제공합니다.
Author국가평생교육진흥원
URLhttps://www.data.go.kr/data/15089815/fileData.do

Alerts

메뉴단계 is highly overall correlated with 첨부파일유무High correlation
첨부파일유무 is highly overall correlated with 메뉴단계High correlation
메뉴 has unique valuesUnique
지표번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:34:31.515144
Analysis finished2023-12-12 13:34:31.928585
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

메뉴
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T22:34:32.133993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length20.25
Min length13

Characters and Unicode

Total characters810
Distinct characters95
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row1.1.1. 인적자원 확보의 적정성
2nd row1.1.1.1. 평생교육사 배치 여부
3rd row1.1.1.2. 운영조직 확보 여부
4th row1.2.1. 학습 지원시설 확보의 적정성
5th row1.2.1.1. 행정실 확보 여부
ValueCountFrequency (%)
적절성 14
 
8.5%
여부 9
 
5.5%
확보의 5
 
3.0%
확보 4
 
2.4%
적정성 4
 
2.4%
적합성 4
 
2.4%
교·강사 4
 
2.4%
수업계획의 4
 
2.4%
운영 3
 
1.8%
평가의 3
 
1.8%
Other values (95) 110
67.1%
2023-12-12T22:34:32.565799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 146
18.0%
124
15.3%
1 67
 
8.3%
2 40
 
4.9%
성 34
 
4.2%
의 33
 
4.1%
3 30
 
3.7%
적 28
 
3.5%
절 14
 
1.7%
정 12
 
1.5%
Other values (85) 282
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
47.9%
Other Punctuation 152
 
18.8%
Decimal Number 146
 
18.0%
Space Separator 124
 
15.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
확 9
 
2.3%
교 9
 
2.3%
영 9
 
2.3%
Other values (76) 218
56.2%
Decimal Number
ValueCountFrequency (%)
1 67
45.9%
2 40
27.4%
3 30
20.5%
4 7
 
4.8%
5 1
 
0.7%
6 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 146
96.1%
· 6
 
3.9%
Space Separator
ValueCountFrequency (%)
124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 422
52.1%
Hangul 388
47.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
확 9
 
2.3%
교 9
 
2.3%
영 9
 
2.3%
Other values (76) 218
56.2%
Common
ValueCountFrequency (%)
. 146
34.6%
124
29.4%
1 67
15.9%
2 40
 
9.5%
3 30
 
7.1%
4 7
 
1.7%
· 6
 
1.4%
5 1
 
0.2%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 416
51.4%
Hangul 388
47.9%
None 6
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 146
35.1%
124
29.8%
1 67
16.1%
2 40
 
9.6%
3 30
 
7.2%
4 7
 
1.7%
5 1
 
0.2%
6 1
 
0.2%
Hangul
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
확 9
 
2.3%
교 9
 
2.3%
영 9
 
2.3%
Other values (76) 218
56.2%
None
ValueCountFrequency (%)
· 6
100.0%

지표번호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T22:34:32.786361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.3
Min length5

Characters and Unicode

Total characters252
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row1.1.1
2nd row1.1.1.1
3rd row1.1.1.2
4th row1.2.1
5th row1.2.1.1
ValueCountFrequency (%)
1.1.1 1
 
2.5%
1.1.1.1 1
 
2.5%
3.1.2.6 1
 
2.5%
3.1.1.1 1
 
2.5%
3.1.2 1
 
2.5%
3.1.2.1 1
 
2.5%
3.1.2.2 1
 
2.5%
3.1.2.3 1
 
2.5%
3.1.2.4 1
 
2.5%
3.1.2.5 1
 
2.5%
Other values (30) 30
75.0%
2023-12-12T22:34:33.176051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 106
42.1%
1 67
26.6%
2 40
 
15.9%
3 30
 
11.9%
4 7
 
2.8%
6 1
 
0.4%
5 1
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 146
57.9%
Other Punctuation 106
42.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 67
45.9%
2 40
27.4%
3 30
20.5%
4 7
 
4.8%
6 1
 
0.7%
5 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 106
42.1%
1 67
26.6%
2 40
 
15.9%
3 30
 
11.9%
4 7
 
2.8%
6 1
 
0.4%
5 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 106
42.1%
1 67
26.6%
2 40
 
15.9%
3 30
 
11.9%
4 7
 
2.8%
6 1
 
0.4%
5 1
 
0.4%

메뉴명
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T22:34:33.410185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length11.95
Min length6

Characters and Unicode

Total characters478
Distinct characters88
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row인적자원 확보의 적정성
2nd row평생교육사 배치 여부
3rd row운영조직 확보 여부
4th row학습 지원시설 확보의 적정성
5th row행정실 확보 여부
ValueCountFrequency (%)
적절성 14
 
11.3%
여부 9
 
7.3%
확보의 5
 
4.0%
수업계획의 4
 
3.2%
교·강사 4
 
3.2%
적합성 4
 
3.2%
적정성 4
 
3.2%
확보 4
 
3.2%
운영 3
 
2.4%
지원시설 3
 
2.4%
Other values (55) 70
56.5%
2023-12-12T22:34:33.847767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
17.6%
성 34
 
7.1%
의 33
 
6.9%
적 28
 
5.9%
절 14
 
2.9%
정 12
 
2.5%
학 11
 
2.3%
수 11
 
2.3%
영 9
 
1.9%
확 9
 
1.9%
Other values (78) 233
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
81.2%
Space Separator 84
 
17.6%
Other Punctuation 6
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
영 9
 
2.3%
확 9
 
2.3%
부 9
 
2.3%
Other values (76) 218
56.2%
Space Separator
ValueCountFrequency (%)
84
100.0%
Other Punctuation
ValueCountFrequency (%)
· 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
81.2%
Common 90
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
영 9
 
2.3%
확 9
 
2.3%
부 9
 
2.3%
Other values (76) 218
56.2%
Common
ValueCountFrequency (%)
84
93.3%
· 6
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
81.2%
ASCII 84
 
17.6%
None 6
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
100.0%
Hangul
ValueCountFrequency (%)
성 34
 
8.8%
의 33
 
8.5%
적 28
 
7.2%
절 14
 
3.6%
정 12
 
3.1%
학 11
 
2.8%
수 11
 
2.8%
영 9
 
2.3%
확 9
 
2.3%
부 9
 
2.3%
Other values (76) 218
56.2%
None
ValueCountFrequency (%)
· 6
100.0%

메뉴단계
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2
26 
1
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 26
65.0%
1 14
35.0%

Length

2023-12-12T22:34:34.011002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:34:34.122803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 26
65.0%
1 14
35.0%

첨부파일유무
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size172.0 B
False
23 
True
17 
ValueCountFrequency (%)
False 23
57.5%
True 17
42.5%
2023-12-12T22:34:34.218817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:34:34.300810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴지표번호메뉴명메뉴단계첨부파일유무
메뉴1.0001.0001.0001.0001.000
지표번호1.0001.0001.0001.0001.000
메뉴명1.0001.0001.0000.0001.000
메뉴단계1.0001.0000.0001.0000.773
첨부파일유무1.0001.0001.0000.7731.000
2023-12-12T22:34:34.398850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴단계첨부파일유무
메뉴단계1.0000.562
첨부파일유무0.5621.000
2023-12-12T22:34:34.481553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
메뉴단계첨부파일유무
메뉴단계1.0000.562
첨부파일유무0.5621.000

Missing values

2023-12-12T22:34:31.784984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:34:31.893425image/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

메뉴지표번호메뉴명메뉴단계첨부파일유무
01.1.1. 인적자원 확보의 적정성1.1.1인적자원 확보의 적정성1N
11.1.1.1. 평생교육사 배치 여부1.1.1.1평생교육사 배치 여부2Y
21.1.1.2. 운영조직 확보 여부1.1.1.2운영조직 확보 여부2Y
31.2.1. 학습 지원시설 확보의 적정성1.2.1학습 지원시설 확보의 적정성1N
41.2.1.1. 행정실 확보 여부1.2.1.1행정실 확보 여부2Y
51.2.1.2. 교·강사 지원시설 확보 여부1.2.1.2교·강사 지원시설 확보 여부2Y
61.2.1.3. 학습자 지원시설 확보 여부1.2.1.3학습자 지원시설 확보 여부2Y
71.3.1. 기관운영의 체계성1.3.1기관운영의 체계성1N
81.3.1.1. 학점은행제 운영 관련 규정 수립 여부1.3.1.1학점은행제 운영 관련 규정 수립 여부2Y
91.3.1.2. 상담창구 운영 여부1.3.1.2상담창구 운영 여부2Y
메뉴지표번호메뉴명메뉴단계첨부파일유무
303.2.1. 학업 성취도 평가의 적절성3.2.1학업 성취도 평가의 적절성1N
313.2.1.1. 평가요소의 적절성3.2.1.1평가요소의 적절성2N
323.2.2. 학업 성취도 평가의 엄정성3.2.2학업 성취도 평가의 엄정성1N
333.2.2.1. 평가문항 관리의 적절성3.2.2.1평가문항 관리의 적절성2N
343.3.1. 수업 만족도 평가의 적절성3.3.1수업 만족도 평가의 적절성1N
353.3.1.1. 강의평가의 적절성3.3.1.1강의평가의 적절성2Y
363.4.1. 기관 운영의 특성화3.4.1기관 운영의 특성화1N
373.4.1.1. 기관 운영의 특성화 및 질 관리의 적절성3.4.1.1기관 운영의 특성화 및 질 관리의 적절성2Y
383.4.2. 재정 건전성3.4.2재정 건전성1N
393.4.2.1. 세금 체납 여부3.4.2.1세금 체납 여부2Y