Overview

Dataset statistics

Number of variables6
Number of observations229
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory50.6 B

Variable types

Numeric1
Categorical2
Text1
DateTime2

Dataset

Description한국기술교육대학교 온라인평생교육원 스마트 직업훈련 플랫폼 (STEP)에 대한 라이브세미나 개설 이력에 관련한 내용을 제공합니다.
Author한국기술교육대학교
URLhttps://www.data.go.kr/data/15090836/fileData.do

Alerts

타입 코드 is highly imbalanced (92.9%)Imbalance
등록 국가 is highly imbalanced (50.3%)Imbalance
아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:46:19.936433
Analysis finished2023-12-12 07:46:20.446261
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

UNIQUE 

Distinct229
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean532.84716
Minimum1
Maximum1046
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T16:46:20.521411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile96.4
Q1241
median418
Q3886
95-th percentile1025.4
Maximum1046
Range1045
Interquartile range (IQR)645

Descriptive statistics

Standard deviation335.36743
Coefficient of variation (CV)0.62938767
Kurtosis-1.5621687
Mean532.84716
Median Absolute Deviation (MAD)291
Skewness0.21311186
Sum122022
Variance112471.31
MonotonicityStrictly increasing
2023-12-12T16:46:20.653659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
797 1
 
0.4%
802 1
 
0.4%
805 1
 
0.4%
807 1
 
0.4%
809 1
 
0.4%
811 1
 
0.4%
812 1
 
0.4%
814 1
 
0.4%
815 1
 
0.4%
Other values (219) 219
95.6%
ValueCountFrequency (%)
1 1
0.4%
4 1
0.4%
34 1
0.4%
55 1
0.4%
61 1
0.4%
64 1
0.4%
73 1
0.4%
79 1
0.4%
85 1
0.4%
88 1
0.4%
ValueCountFrequency (%)
1046 1
0.4%
1045 1
0.4%
1041 1
0.4%
1039 1
0.4%
1038 1
0.4%
1036 1
0.4%
1034 1
0.4%
1032 1
0.4%
1031 1
0.4%
1029 1
0.4%

타입 코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3
226 
2
 
2
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
3 226
98.7%
2 2
 
0.9%
1 1
 
0.4%

Length

2023-12-12T16:46:20.765947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:20.850261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 226
98.7%
2 2
 
0.9%
1 1
 
0.4%

제목
Text

Distinct190
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T16:46:21.129110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length27
Mean length19.436681
Min length3

Characters and Unicode

Total characters4451
Distinct characters293
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)73.8%

Sample

1st row라이브세미나 입니다.
2nd row라이브세미나 시연
3rd row과정복사 테스트를 위한 개설
4th row전기전자공학 라이브세미나
5th row기계제도와 도면해독 기본 라이브세미나
ValueCountFrequency (%)
라이브세미나 74
 
9.2%
라이브세미나(녹화 32
 
4.0%
테스트 24
 
3.0%
plc 19
 
2.4%
test 15
 
1.9%
웰컴 13
 
1.6%
세미나 12
 
1.5%
활용한 11
 
1.4%
배우는 10
 
1.2%
강사님의 10
 
1.2%
Other values (317) 587
72.7%
2023-12-12T16:46:21.602857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
586
 
13.2%
이 162
 
3.6%
세 144
 
3.2%
미 140
 
3.1%
라 139
 
3.1%
나 138
 
3.1%
브 134
 
3.0%
0 111
 
2.5%
) 106
 
2.4%
( 106
 
2.4%
Other values (283) 2685
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2476
55.6%
Space Separator 586
 
13.2%
Decimal Number 395
 
8.9%
Lowercase Letter 296
 
6.7%
Uppercase Letter 287
 
6.4%
Close Punctuation 127
 
2.9%
Open Punctuation 127
 
2.9%
Other Punctuation 103
 
2.3%
Math Symbol 40
 
0.9%
Connector Punctuation 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 162
 
6.5%
세 144
 
5.8%
미 140
 
5.7%
라 139
 
5.6%
나 138
 
5.6%
브 134
 
5.4%
기 74
 
3.0%
스 54
 
2.2%
트 49
 
2.0%
화 46
 
1.9%
Other values (219) 1396
56.4%
Lowercase Letter
ValueCountFrequency (%)
t 69
23.3%
e 40
13.5%
s 37
12.5%
o 25
 
8.4%
u 18
 
6.1%
l 18
 
6.1%
r 17
 
5.7%
c 15
 
5.1%
a 13
 
4.4%
d 9
 
3.0%
Other values (10) 35
11.8%
Uppercase Letter
ValueCountFrequency (%)
C 55
19.2%
A 40
13.9%
L 30
10.5%
D 28
9.8%
S 21
 
7.3%
E 20
 
7.0%
R 19
 
6.6%
P 19
 
6.6%
M 18
 
6.3%
I 8
 
2.8%
Other values (8) 29
10.1%
Decimal Number
ValueCountFrequency (%)
0 111
28.1%
1 90
22.8%
2 60
15.2%
7 29
 
7.3%
9 28
 
7.1%
3 26
 
6.6%
4 14
 
3.5%
8 13
 
3.3%
6 13
 
3.3%
5 11
 
2.8%
Other Punctuation
ValueCountFrequency (%)
: 36
35.0%
. 35
34.0%
! 13
 
12.6%
, 7
 
6.8%
" 6
 
5.8%
/ 4
 
3.9%
# 2
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 106
83.5%
] 21
 
16.5%
Open Punctuation
ValueCountFrequency (%)
( 106
83.5%
[ 21
 
16.5%
Math Symbol
ValueCountFrequency (%)
~ 36
90.0%
+ 4
 
10.0%
Space Separator
ValueCountFrequency (%)
586
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2476
55.6%
Common 1392
31.3%
Latin 583
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 162
 
6.5%
세 144
 
5.8%
미 140
 
5.7%
라 139
 
5.6%
나 138
 
5.6%
브 134
 
5.4%
기 74
 
3.0%
스 54
 
2.2%
트 49
 
2.0%
화 46
 
1.9%
Other values (219) 1396
56.4%
Latin
ValueCountFrequency (%)
t 69
 
11.8%
C 55
 
9.4%
e 40
 
6.9%
A 40
 
6.9%
s 37
 
6.3%
L 30
 
5.1%
D 28
 
4.8%
o 25
 
4.3%
S 21
 
3.6%
E 20
 
3.4%
Other values (28) 218
37.4%
Common
ValueCountFrequency (%)
586
42.1%
0 111
 
8.0%
) 106
 
7.6%
( 106
 
7.6%
1 90
 
6.5%
2 60
 
4.3%
: 36
 
2.6%
~ 36
 
2.6%
. 35
 
2.5%
7 29
 
2.1%
Other values (16) 197
 
14.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2475
55.6%
ASCII 1975
44.4%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
586
29.7%
0 111
 
5.6%
) 106
 
5.4%
( 106
 
5.4%
1 90
 
4.6%
t 69
 
3.5%
2 60
 
3.0%
C 55
 
2.8%
e 40
 
2.0%
A 40
 
2.0%
Other values (54) 712
36.1%
Hangul
ValueCountFrequency (%)
이 162
 
6.5%
세 144
 
5.8%
미 140
 
5.7%
라 139
 
5.6%
나 138
 
5.6%
브 134
 
5.4%
기 74
 
3.0%
스 54
 
2.2%
트 49
 
2.0%
화 46
 
1.9%
Other values (218) 1395
56.4%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

시작 일자
Date

Distinct195
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2015-02-05 06:00:00
Maximum2019-07-01 00:00:00
2023-12-12T16:46:21.782489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:21.912754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종료 일자
Date

Distinct190
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2015-02-05 17:30:00
Maximum2019-07-01 23:59:59
2023-12-12T16:46:22.035225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:46:22.176056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록 국가
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
KR
204 
UNKNOWN
25 

Length

Max length7
Median length2
Mean length2.5458515
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
KR 204
89.1%
UNKNOWN 25
 
10.9%

Length

2023-12-12T16:46:22.319462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:46:22.437211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kr 204
89.1%
unknown 25
 
10.9%

Interactions

2023-12-12T16:46:20.173249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:46:22.494647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디타입 코드등록 국가
아이디1.0000.0000.632
타입 코드0.0001.0000.000
등록 국가0.6320.0001.000
2023-12-12T16:46:22.584551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
타입 코드등록 국가
타입 코드1.0000.000
등록 국가0.0001.000
2023-12-12T16:46:22.670253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디타입 코드등록 국가
아이디1.0000.0000.473
타입 코드0.0001.0000.000
등록 국가0.4730.0001.000

Missing values

2023-12-12T16:46:20.281935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:46:20.398312image/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

아이디타입 코드제목시작 일자종료 일자등록 국가
013라이브세미나 입니다.2015-02-05 06:00:002015-02-05 17:30:00KR
143라이브세미나 시연2015-03-03 06:00:002015-03-03 23:59:00KR
2343과정복사 테스트를 위한 개설2015-04-17 00:00:002015-04-30 23:59:00KR
3553전기전자공학 라이브세미나2015-07-14 20:00:002015-07-14 21:00:00KR
4613기계제도와 도면해독 기본 라이브세미나2015-07-22 20:00:002015-07-22 21:10:00KR
5643AutoCAD 마스터하기 라이브세미나2015-07-22 18:00:002015-07-22 20:00:00KR
6733test2015-08-07 00:00:002015-08-07 23:59:00KR
77937월 24일 라이브세미나 시연2015-07-23 00:00:002015-07-24 23:59:00KR
8853전자회로 CAD(OrCAD) 라이브세미나 (첫 번재 파일)2015-07-30 10:00:002015-07-30 11:00:00KR
9883LED 구동회로 라이브세미나2015-07-30 11:00:002015-07-30 12:00:00KR
아이디타입 코드제목시작 일자종료 일자등록 국가
219102933차 라이브세미나2018-12-05 20:00:002018-12-05 22:59:59KR
220103131차 라이브세미나2018-10-18 15:00:002018-10-18 22:59:59KR
22110323라이브세니마 테스트2018-10-15 00:00:002018-10-15 23:59:59KR
222103432차 라이브세미나2018-10-30 20:00:002018-10-30 22:59:59UNKNOWN
22310363메이머스트 라이브세미나 테스트2018-10-25 10:00:002018-10-26 12:59:59KR
224103833차 라이브세미나(인터뷰 관련)2018-11-09 00:00:002018-11-12 23:59:59KR
22510393메이머스트 담당자와 함께하는 채용 관련 Live 소통시간!2018-11-27 20:00:002018-11-27 21:15:00KR
22610413메이머스트 담당자와 함께하는 채용 관련 Live 소통시간!2018-11-15 00:00:002018-11-30 23:59:59KR
22710453test2018-12-06 11:30:002018-12-06 12:59:59KR
22810463라이브세미나 테스트 07012019-07-01 00:00:002019-07-01 23:59:59KR