Overview

Dataset statistics

Number of variables6
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory53.3 B

Variable types

Numeric1
Categorical2
Text2
DateTime1

Dataset

Description한국기술교육대학교 온라인평생교육원 스마트 직업훈련 플랫폼 (STEP)에 대한 LMS 테스트 과정 관련 내용을 제공합니다.
Author한국기술교육대학교
URLhttps://www.data.go.kr/data/15090998/fileData.do

Alerts

기관 아이디 has constant value ""Constant
아이디 is highly overall correlated with 등록 국가High correlation
등록 국가 is highly overall correlated with 아이디High correlation
아이디 has unique valuesUnique
코드 has unique valuesUnique
등록 일시 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:47:07.581653
Analysis finished2023-12-11 23:47:08.002915
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.025
Minimum1
Maximum172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T08:47:08.052688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q124.75
median83.5
Q3139.75
95-th percentile166.15
Maximum172
Range171
Interquartile range (IQR)115

Descriptive statistics

Standard deviation60.496445
Coefficient of variation (CV)0.71998149
Kurtosis-1.6638139
Mean84.025
Median Absolute Deviation (MAD)58.5
Skewness0.00391828
Sum3361
Variance3659.8199
MonotonicityStrictly increasing
2023-12-12T08:47:08.155199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
88 1
 
2.5%
121 1
 
2.5%
124 1
 
2.5%
127 1
 
2.5%
130 1
 
2.5%
133 1
 
2.5%
136 1
 
2.5%
139 1
 
2.5%
142 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
5 1
2.5%
8 1
2.5%
9 1
2.5%
12 1
2.5%
13 1
2.5%
16 1
2.5%
21 1
2.5%
24 1
2.5%
ValueCountFrequency (%)
172 1
2.5%
169 1
2.5%
166 1
2.5%
163 1
2.5%
160 1
2.5%
157 1
2.5%
154 1
2.5%
148 1
2.5%
145 1
2.5%
142 1
2.5%

기관 아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 40
100.0%

Length

2023-12-12T08:47:08.251996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:47:08.321318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
100.0%

코드
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T08:47:08.472825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length11.75
Min length10

Characters and Unicode

Total characters470
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
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 rowFORMAL2017CU001
2nd rowFORMAL2017CU002
3rd rowFORMAL2017CU003
4th rowFORMAL2018CU001
5th rowFORMAL2018CU002
ValueCountFrequency (%)
formal2017cu001 1
 
2.5%
formal2017cu002 1
 
2.5%
12023cu011 1
 
2.5%
12023cu004 1
 
2.5%
12023cu005 1
 
2.5%
12023cu006 1
 
2.5%
12023cu007 1
 
2.5%
12023cu008 1
 
2.5%
12023cu009 1
 
2.5%
12023cu010 1
 
2.5%
Other values (30) 30
75.0%
2023-12-12T08:47:08.808259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 108
23.0%
2 74
15.7%
1 62
13.2%
C 40
 
8.5%
U 40
 
8.5%
3 23
 
4.9%
F 14
 
3.0%
R 14
 
3.0%
M 14
 
3.0%
A 14
 
3.0%
Other values (8) 67
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
65.1%
Uppercase Letter 164
34.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 108
35.3%
2 74
24.2%
1 62
20.3%
3 23
 
7.5%
8 14
 
4.6%
9 6
 
2.0%
7 6
 
2.0%
5 5
 
1.6%
4 5
 
1.6%
6 3
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
C 40
24.4%
U 40
24.4%
F 14
 
8.5%
R 14
 
8.5%
M 14
 
8.5%
A 14
 
8.5%
L 14
 
8.5%
O 14
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Common 306
65.1%
Latin 164
34.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 108
35.3%
2 74
24.2%
1 62
20.3%
3 23
 
7.5%
8 14
 
4.6%
9 6
 
2.0%
7 6
 
2.0%
5 5
 
1.6%
4 5
 
1.6%
6 3
 
1.0%
Latin
ValueCountFrequency (%)
C 40
24.4%
U 40
24.4%
F 14
 
8.5%
R 14
 
8.5%
M 14
 
8.5%
A 14
 
8.5%
L 14
 
8.5%
O 14
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 108
23.0%
2 74
15.7%
1 62
13.2%
C 40
 
8.5%
U 40
 
8.5%
3 23
 
4.9%
F 14
 
3.0%
R 14
 
3.0%
M 14
 
3.0%
A 14
 
3.0%
Other values (8) 67
14.3%

제목
Text

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T08:47:09.027088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27.5
Mean length19.075
Min length1

Characters and Unicode

Total characters763
Distinct characters127
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)90.0%

Sample

1st row빅데이터 과정
2nd row빅데이터 분석 실무 활용 중급 과정
3rd row빅데이터 분석 실무 활용 중급 온라인 기초
4th row(test)HTML5 기반 스마트 앱 개발하기
5th rowHTML5 기반 스마트 웹 페이지 제작하기_1
ValueCountFrequency (%)
패키지 23
 
11.7%
및 12
 
6.1%
2차 10
 
5.1%
빅데이터 8
 
4.1%
설계 6
 
3.0%
과정 5
 
2.5%
웹 5
 
2.5%
기반 5
 
2.5%
반도체 5
 
2.5%
분석 4
 
2.0%
Other values (55) 114
57.9%
2023-12-12T08:47:09.331382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
20.6%
지 30
 
3.9%
이 24
 
3.1%
( 23
 
3.0%
) 23
 
3.0%
키 23
 
3.0%
패 23
 
3.0%
기 15
 
2.0%
스 13
 
1.7%
차 13
 
1.7%
Other values (117) 419
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 490
64.2%
Space Separator 157
 
20.6%
Uppercase Letter 32
 
4.2%
Open Punctuation 27
 
3.5%
Close Punctuation 27
 
3.5%
Decimal Number 15
 
2.0%
Lowercase Letter 14
 
1.8%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 30
 
6.1%
이 24
 
4.9%
키 23
 
4.7%
패 23
 
4.7%
기 15
 
3.1%
스 13
 
2.7%
차 13
 
2.7%
트 12
 
2.4%
및 12
 
2.4%
데 11
 
2.2%
Other values (88) 314
64.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
15.6%
M 5
15.6%
S 4
12.5%
H 4
12.5%
L 4
12.5%
W 3
9.4%
V 2
 
6.2%
R 2
 
6.2%
D 1
 
3.1%
I 1
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
t 4
28.6%
s 2
14.3%
e 2
14.3%
g 1
 
7.1%
j 1
 
7.1%
a 1
 
7.1%
n 1
 
7.1%
o 1
 
7.1%
d 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 10
66.7%
5 4
 
26.7%
1 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 23
85.2%
[ 4
 
14.8%
Close Punctuation
ValueCountFrequency (%)
) 23
85.2%
] 4
 
14.8%
Space Separator
ValueCountFrequency (%)
157
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 490
64.2%
Common 227
29.8%
Latin 46
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 30
 
6.1%
이 24
 
4.9%
키 23
 
4.7%
패 23
 
4.7%
기 15
 
3.1%
스 13
 
2.7%
차 13
 
2.7%
트 12
 
2.4%
및 12
 
2.4%
데 11
 
2.2%
Other values (88) 314
64.1%
Latin
ValueCountFrequency (%)
T 5
10.9%
M 5
10.9%
t 4
 
8.7%
S 4
 
8.7%
H 4
 
8.7%
L 4
 
8.7%
W 3
 
6.5%
V 2
 
4.3%
R 2
 
4.3%
s 2
 
4.3%
Other values (10) 11
23.9%
Common
ValueCountFrequency (%)
157
69.2%
( 23
 
10.1%
) 23
 
10.1%
2 10
 
4.4%
[ 4
 
1.8%
] 4
 
1.8%
5 4
 
1.8%
_ 1
 
0.4%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 490
64.2%
ASCII 273
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
57.5%
( 23
 
8.4%
) 23
 
8.4%
2 10
 
3.7%
T 5
 
1.8%
M 5
 
1.8%
t 4
 
1.5%
S 4
 
1.5%
H 4
 
1.5%
[ 4
 
1.5%
Other values (19) 34
 
12.5%
Hangul
ValueCountFrequency (%)
지 30
 
6.1%
이 24
 
4.9%
키 23
 
4.7%
패 23
 
4.7%
기 15
 
3.1%
스 13
 
2.7%
차 13
 
2.7%
트 12
 
2.4%
및 12
 
2.4%
데 11
 
2.2%
Other values (88) 314
64.1%

등록 국가
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
KR
22 
UNKNOWN
18 

Length

Max length7
Median length2
Mean length4.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KR 22
55.0%
UNKNOWN 18
45.0%

Length

2023-12-12T08:47:09.444065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:47:09.524312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kr 22
55.0%
unknown 18
45.0%

등록 일시
Date

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2017-07-21 13:10:05
Maximum2023-08-21 13:30:50
2023-12-12T08:47:09.606455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:47:09.712847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

Interactions

2023-12-12T08:47:07.798276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:47:09.809217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디코드제목등록 국가등록 일시
아이디1.0001.0001.0001.0001.000
코드1.0001.0001.0001.0001.000
제목1.0001.0001.0001.0001.000
등록 국가1.0001.0001.0001.0001.000
등록 일시1.0001.0001.0001.0001.000
2023-12-12T08:47:09.892145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디등록 국가
아이디1.0000.889
등록 국가0.8891.000

Missing values

2023-12-12T08:47:07.893646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:47:07.972362image/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

아이디기관 아이디코드제목등록 국가등록 일시
011FORMAL2017CU001빅데이터 과정KR2017-07-21 13:10:05
121FORMAL2017CU002빅데이터 분석 실무 활용 중급 과정KR2017-12-04 19:20:52
251FORMAL2017CU003빅데이터 분석 실무 활용 중급 온라인 기초KR2017-12-07 17:07:30
381FORMAL2018CU001(test)HTML5 기반 스마트 앱 개발하기KR2018-04-16 21:51:57
491FORMAL2018CU002HTML5 기반 스마트 웹 페이지 제작하기_1KR2018-05-04 18:41:13
5121FORMAL2018CU003Django 기반 웹 사이트 개발하기KR2018-05-04 18:42:24
6131FORMAL2018CU004HTML5 기반 스마트 웹 페이지 제작하기KR2018-05-24 16:37:15
7161FORMAL2018CU005HTML5 기반 스마트 웹 페이지 제작하기KR2018-05-24 16:55:20
8211FORMAL2018CU007[팀 프로젝트] IT기반 파이썬 메이커 과정KR2018-05-31 09:34:24
9241FORMAL2018CU008웹 사이트 제작하기KR2018-07-02 13:40:17
아이디기관 아이디코드제목등록 국가등록 일시
30142112023CU012(패키지) 반도체 공정 및 제조UNKNOWN2023-05-04 14:57:33
31145112023CU013(패키지 2차) 반도체 공정 및 제조UNKNOWN2023-08-21 11:00:52
32148112023CU014(패키지 2차) 시스템 반도체 회로 설계UNKNOWN2023-08-21 11:06:20
33154112023CU015(패키지 2차) 빅데이터 입문UNKNOWN2023-08-21 11:18:40
34157112023CU016(패키지 2차) 인공지능 모델러 설계UNKNOWN2023-08-21 11:22:24
35160112023CU017(패키지 2차) 수소 에너지UNKNOWN2023-08-21 13:10:56
36163112023CU018(패키지 2차) 가상현실(VR) 콘텐츠 제작자 고급UNKNOWN2023-08-21 13:13:26
37166112023CU019(패키지 2차) 자율주행차 SW 개발UNKNOWN2023-08-21 13:17:17
38169112023CU020(패키지 2차) 스마트공장 시스템 설계 및 개발자(FMS) 입문UNKNOWN2023-08-21 13:25:52
39172112023CU021(패키지 2차) 데이터 수집 및 분석을 통한 품질관리자 기초UNKNOWN2023-08-21 13:30:50