Overview

Dataset statistics

Number of variables10
Number of observations103
Missing cells101
Missing cells (%)9.8%
Duplicate rows3
Duplicate rows (%)2.9%
Total size in memory8.7 KiB
Average record size in memory86.3 B

Variable types

Categorical8
Text2

Dataset

Description학점은행제 정보공시 자료의 검증결과 정보이며 공시년도, 공시시기, 공시항목명, 검증결과구분명, 검증지표값1, 검증지표값2, 검증지표값3, 검증지표값4, 생성일시, 수정일시 항목의 정보를 제공합니다.
Author국가평생교육진흥원
URLhttps://www.data.go.kr/data/15088892/fileData.do

Alerts

공시년도 has constant value ""Constant
Dataset has 3 (2.9%) duplicate rowsDuplicates
생성일시 is highly overall correlated with 공시시기 and 2 other fieldsHigh correlation
공시항목명 is highly overall correlated with 공시시기 and 2 other fieldsHigh correlation
수정일시 is highly overall correlated with 공시시기 and 2 other fieldsHigh correlation
공시시기 is highly overall correlated with 공시항목명 and 2 other fieldsHigh correlation
공시시기 is highly imbalanced (92.1%)Imbalance
공시항목명 is highly imbalanced (90.1%)Imbalance
검증지표값2 is highly imbalanced (92.1%)Imbalance
검증지표값3 is highly imbalanced (92.1%)Imbalance
검증지표값4 is highly imbalanced (92.1%)Imbalance
생성일시 is highly imbalanced (90.1%)Imbalance
수정일시 is highly imbalanced (90.1%)Imbalance
검증결과구분명 has 101 (98.1%) missing valuesMissing

Reproduction

Analysis started2024-04-17 17:30:59.484412
Analysis finished2024-04-17 17:30:59.979349
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공시년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2018
103 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 103
100.0%

Length

2024-04-18T02:31:00.026124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:00.095856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 103
100.0%

공시시기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
3
102 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row3
2nd row2
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 102
99.0%
2 1
 
1.0%

Length

2024-04-18T02:31:00.168336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:00.235782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 102
99.0%
2 1
 
1.0%

공시항목명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
교수 또는 강사의 강의 담당 현황
101 
교수 또는 강사의 수
 
1
교사(校舍) 등 시설 현황
 
1

Length

Max length18
Median length18
Mean length17.893204
Min length11

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row교수 또는 강사의 수
2nd row교사(校舍) 등 시설 현황
3rd row교수 또는 강사의 강의 담당 현황
4th row교수 또는 강사의 강의 담당 현황
5th row교수 또는 강사의 강의 담당 현황

Common Values

ValueCountFrequency (%)
교수 또는 강사의 강의 담당 현황 101
98.1%
교수 또는 강사의 수 1
 
1.0%
교사(校舍) 등 시설 현황 1
 
1.0%

Length

2024-04-18T02:31:00.335584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:00.414967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교수 102
16.6%
또는 102
16.6%
강사의 102
16.6%
현황 102
16.6%
강의 101
16.4%
담당 101
16.4%
수 1
 
0.2%
교사(校舍 1
 
0.2%
등 1
 
0.2%
시설 1
 
0.2%

검증결과구분명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing101
Missing (%)98.1%
Memory size956.0 B
2024-04-18T02:31:00.515661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length9
Min length4

Characters and Unicode

Total characters18
Distinct characters14
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

Unique2 ?
Unique (%)100.0%

Sample

1st row아동미술
2nd row도서실(지도교수실)(2층)
ValueCountFrequency (%)
아동미술 1
50.0%
도서실(지도교수실)(2층 1
50.0%
2024-04-18T02:31:00.722308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 2
11.1%
실 2
11.1%
( 2
11.1%
) 2
11.1%
아 1
 
5.6%
동 1
 
5.6%
미 1
 
5.6%
술 1
 
5.6%
서 1
 
5.6%
지 1
 
5.6%
Other values (4) 4
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
72.2%
Open Punctuation 2
 
11.1%
Close Punctuation 2
 
11.1%
Decimal Number 1
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 2
15.4%
실 2
15.4%
아 1
7.7%
동 1
7.7%
미 1
7.7%
술 1
7.7%
서 1
7.7%
지 1
7.7%
교 1
7.7%
수 1
7.7%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
72.2%
Common 5
 
27.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 2
15.4%
실 2
15.4%
아 1
7.7%
동 1
7.7%
미 1
7.7%
술 1
7.7%
서 1
7.7%
지 1
7.7%
교 1
7.7%
수 1
7.7%
Common
ValueCountFrequency (%)
( 2
40.0%
) 2
40.0%
2 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
72.2%
ASCII 5
 
27.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 2
15.4%
실 2
15.4%
아 1
7.7%
동 1
7.7%
미 1
7.7%
술 1
7.7%
서 1
7.7%
지 1
7.7%
교 1
7.7%
수 1
7.7%
ASCII
ValueCountFrequency (%)
( 2
40.0%
) 2
40.0%
2 1
20.0%

검증지표값1
Text

Distinct100
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-04-18T02:31:00.917961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.0582524
Min length1

Characters and Unicode

Total characters933
Distinct characters15
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)94.2%

Sample

1st row2 < 3
2nd row0
3rd row423 != 414
4th row492 != 798
5th row573 != 438
ValueCountFrequency (%)
102
33.2%
21 7
 
2.3%
81 6
 
2.0%
18 5
 
1.6%
9 5
 
1.6%
33 4
 
1.3%
15 4
 
1.3%
60 4
 
1.3%
42 4
 
1.3%
51 4
 
1.3%
Other values (115) 162
52.8%
2024-04-18T02:31:01.218780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
21.9%
! 101
10.8%
= 101
10.8%
1 100
10.7%
2 64
 
6.9%
3 57
 
6.1%
8 52
 
5.6%
5 48
 
5.1%
6 44
 
4.7%
4 43
 
4.6%
Other values (5) 119
12.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 513
55.0%
Space Separator 204
 
21.9%
Other Punctuation 114
 
12.2%
Math Symbol 102
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 100
19.5%
2 64
12.5%
3 57
11.1%
8 52
10.1%
5 48
9.4%
6 44
8.6%
4 43
8.4%
9 39
 
7.6%
0 36
 
7.0%
7 30
 
5.8%
Other Punctuation
ValueCountFrequency (%)
! 101
88.6%
, 13
 
11.4%
Math Symbol
ValueCountFrequency (%)
= 101
99.0%
< 1
 
1.0%
Space Separator
ValueCountFrequency (%)
204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 933
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
204
21.9%
! 101
10.8%
= 101
10.8%
1 100
10.7%
2 64
 
6.9%
3 57
 
6.1%
8 52
 
5.6%
5 48
 
5.1%
6 44
 
4.7%
4 43
 
4.6%
Other values (5) 119
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 933
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
21.9%
! 101
10.8%
= 101
10.8%
1 100
10.7%
2 64
 
6.9%
3 57
 
6.1%
8 52
 
5.6%
5 48
 
5.1%
6 44
 
4.7%
4 43
 
4.6%
Other values (5) 119
12.8%

검증지표값2
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
<NA>
102 
0
 
1

Length

Max length4
Median length4
Mean length3.9708738
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 102
99.0%
0 1
 
1.0%

Length

2024-04-18T02:31:01.329008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:01.666432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
99.0%
0 1
 
1.0%

검증지표값3
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
<NA>
102 
1
 
1

Length

Max length4
Median length4
Mean length3.9708738
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 102
99.0%
1 1
 
1.0%

Length

2024-04-18T02:31:01.753782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:01.828299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
99.0%
1 1
 
1.0%

검증지표값4
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
<NA>
102 
21
 
1

Length

Max length4
Median length4
Mean length3.9805825
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row21
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 102
99.0%
21 1
 
1.0%

Length

2024-04-18T02:31:01.907632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:01.984937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
99.0%
21 1
 
1.0%

생성일시
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
2018-03-15 14:40:34.0
101 
2018-03-13 19:04:23.0
 
1
2018-02-21 13:53:12.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row2018-03-13 19:04:23.0
2nd row2018-02-21 13:53:12.0
3rd row2018-03-15 14:40:34.0
4th row2018-03-15 14:40:34.0
5th row2018-03-15 14:40:34.0

Common Values

ValueCountFrequency (%)
2018-03-15 14:40:34.0 101
98.1%
2018-03-13 19:04:23.0 1
 
1.0%
2018-02-21 13:53:12.0 1
 
1.0%

Length

2024-04-18T02:31:02.056062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:02.128723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-03-15 101
49.0%
14:40:34.0 101
49.0%
2018-03-13 1
 
0.5%
19:04:23.0 1
 
0.5%
2018-02-21 1
 
0.5%
13:53:12.0 1
 
0.5%

수정일시
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size956.0 B
2018-03-15 14:40:34.0
101 
2018-03-13 19:04:23.0
 
1
2018-02-21 13:53:12.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row2018-03-13 19:04:23.0
2nd row2018-02-21 13:53:12.0
3rd row2018-03-15 14:40:34.0
4th row2018-03-15 14:40:34.0
5th row2018-03-15 14:40:34.0

Common Values

ValueCountFrequency (%)
2018-03-15 14:40:34.0 101
98.1%
2018-03-13 19:04:23.0 1
 
1.0%
2018-02-21 13:53:12.0 1
 
1.0%

Length

2024-04-18T02:31:02.218309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T02:31:02.295388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-03-15 101
49.0%
14:40:34.0 101
49.0%
2018-03-13 1
 
0.5%
19:04:23.0 1
 
0.5%
2018-02-21 1
 
0.5%
13:53:12.0 1
 
0.5%

Correlations

2024-04-18T02:31:02.346626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시시기공시항목명검증결과구분명검증지표값1생성일시수정일시
공시시기1.0001.0000.0001.0001.0001.000
공시항목명1.0001.0000.0001.0001.0001.000
검증결과구분명0.0000.0001.0000.0000.0000.000
검증지표값11.0001.0000.0001.0001.0001.000
생성일시1.0001.0000.0001.0001.0001.000
수정일시1.0001.0000.0001.0001.0001.000
2024-04-18T02:31:02.427879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생성일시공시항목명검증지표값4검증지표값2검증지표값3수정일시공시시기
생성일시1.0001.000NaNNaNNaN1.0000.995
공시항목명1.0001.000NaNNaNNaN1.0000.995
검증지표값4NaNNaN1.000NaNNaNNaNNaN
검증지표값2NaNNaNNaN1.000NaNNaNNaN
검증지표값3NaNNaNNaNNaN1.000NaNNaN
수정일시1.0001.000NaNNaNNaN1.0000.995
공시시기0.9950.995NaNNaNNaN0.9951.000
2024-04-18T02:31:02.515320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시시기공시항목명검증지표값2검증지표값3검증지표값4생성일시수정일시
공시시기1.0000.995NaNNaNNaN0.9950.995
공시항목명0.9951.000NaNNaNNaN1.0001.000
검증지표값2NaNNaN1.000NaNNaNNaNNaN
검증지표값3NaNNaNNaN1.000NaNNaNNaN
검증지표값4NaNNaNNaNNaN1.000NaNNaN
생성일시0.9951.000NaNNaNNaN1.0001.000
수정일시0.9951.000NaNNaNNaN1.0001.000

Missing values

2024-04-18T02:30:59.830347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T02:30:59.937210image/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

공시년도공시시기공시항목명검증결과구분명검증지표값1검증지표값2검증지표값3검증지표값4생성일시수정일시
020183교수 또는 강사의 수아동미술2 < 3<NA><NA><NA>2018-03-13 19:04:23.02018-03-13 19:04:23.0
120182교사(校舍) 등 시설 현황도서실(지도교수실)(2층)001212018-02-21 13:53:12.02018-02-21 13:53:12.0
220183교수 또는 강사의 강의 담당 현황<NA>423 != 414<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
320183교수 또는 강사의 강의 담당 현황<NA>492 != 798<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
420183교수 또는 강사의 강의 담당 현황<NA>573 != 438<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
520183교수 또는 강사의 강의 담당 현황<NA>412 != 144<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
620183교수 또는 강사의 강의 담당 현황<NA>213 != 231<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
720183교수 또는 강사의 강의 담당 현황<NA>108 != 99<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
820183교수 또는 강사의 강의 담당 현황<NA>81 != 51<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
920183교수 또는 강사의 강의 담당 현황<NA>363 != 312<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
공시년도공시시기공시항목명검증결과구분명검증지표값1검증지표값2검증지표값3검증지표값4생성일시수정일시
9320183교수 또는 강사의 강의 담당 현황<NA>102 != 153<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9420183교수 또는 강사의 강의 담당 현황<NA>867 != 834<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9520183교수 또는 강사의 강의 담당 현황<NA>33 != 39<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9620183교수 또는 강사의 강의 담당 현황<NA>294 != 693<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9720183교수 또는 강사의 강의 담당 현황<NA>18 != 15<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9820183교수 또는 강사의 강의 담당 현황<NA>66 != 75<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
9920183교수 또는 강사의 강의 담당 현황<NA>156 != 90<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
10020183교수 또는 강사의 강의 담당 현황<NA>708 != 1,032<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
10120183교수 또는 강사의 강의 담당 현황<NA>33 != 9<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0
10220183교수 또는 강사의 강의 담당 현황<NA>78 != 75<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.0

Duplicate rows

Most frequently occurring

공시년도공시시기공시항목명검증결과구분명검증지표값1검증지표값2검증지표값3검증지표값4생성일시수정일시# duplicates
020183교수 또는 강사의 강의 담당 현황<NA>21 != 9<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.02
120183교수 또는 강사의 강의 담당 현황<NA>33 != 39<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.02
220183교수 또는 강사의 강의 담당 현황<NA>45 != 48<NA><NA><NA>2018-03-15 14:40:34.02018-03-15 14:40:34.02