Overview

Dataset statistics

Number of variables4
Number of observations132
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory34.0 B

Variable types

Numeric1
Categorical2
Text1

Dataset

Description한국폴리텍대학에서 제공하고 있는 이러닝 콘텐츠의 목록입니다. 제공하는 데이터 항목은 분야와 콘텐츠명 정보를 제공합니다.
Author학교법인한국폴리텍
URLhttps://www.data.go.kr/data/15053544/fileData.do

Alerts

번호 is highly overall correlated with 분야 and 1 other fieldsHigh correlation
분야 is highly overall correlated with 번호High correlation
비고 is highly overall correlated with 번호High correlation
비고 is highly imbalanced (60.8%)Imbalance
번호 has unique valuesUnique
콘텐츠명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:16:13.505571
Analysis finished2023-12-11 23:16:13.892708
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.5
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T08:16:14.175691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.55
Q133.75
median66.5
Q399.25
95-th percentile125.45
Maximum132
Range131
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation38.249183
Coefficient of variation (CV)0.57517568
Kurtosis-1.2
Mean66.5
Median Absolute Deviation (MAD)33
Skewness0
Sum8778
Variance1463
MonotonicityStrictly increasing
2023-12-12T08:16:14.287429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
85 1
 
0.8%
99 1
 
0.8%
98 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
Other values (122) 122
92.4%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
132 1
0.8%
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%

분야
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
교양
27 
전기전자
19 
영어
16 
기계
12 
정보통신
12 
Other values (14)
46 

Length

Max length6
Median length2
Mean length2.9621212
Min length2

Unique

Unique4 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
교양 27
20.5%
전기전자 19
14.4%
영어 16
12.1%
기계 12
9.1%
정보통신 12
9.1%
OA 8
 
6.1%
미디어디자인 8
 
6.1%
자동화 6
 
4.5%
자동차 5
 
3.8%
바이오 4
 
3.0%
Other values (9) 15
11.4%

Length

2023-12-12T08:16:14.406640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교양 27
20.5%
전기전자 19
14.4%
영어 16
12.1%
기계 12
9.1%
정보통신 12
9.1%
oa 8
 
6.1%
미디어디자인 8
 
6.1%
자동화 6
 
4.5%
자동차 5
 
3.8%
바이오 4
 
3.0%
Other values (9) 15
11.4%

콘텐츠명
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T08:16:14.629904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length24
Mean length14.295455
Min length2

Characters and Unicode

Total characters1887
Distinct characters322
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)100.0%

Sample

1st row[Must Know]PC Basic
2nd row[Must Know]PC Intermedia
3rd row[Must Know]PC Advanced
4th row성공 프레젠테이션 나도 할 수 있다.
5th row업무의 달인을 인정받는 Excel 2007
ValueCountFrequency (%)
이용한 6
 
1.5%
기초 6
 
1.5%
to 6
 
1.5%
how 6
 
1.5%
basic 5
 
1.3%
및 5
 
1.3%
1 4
 
1.0%
2 4
 
1.0%
설계 4
 
1.0%
toeic 4
 
1.0%
Other values (283) 339
87.1%
2023-12-12T08:16:14.935706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
 
13.8%
기 66
 
3.5%
C 35
 
1.9%
이 27
 
1.4%
전 26
 
1.4%
) 25
 
1.3%
( 25
 
1.3%
I 20
 
1.1%
t 20
 
1.1%
자 20
 
1.1%
Other values (312) 1363
72.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1126
59.7%
Space Separator 260
 
13.8%
Uppercase Letter 224
 
11.9%
Lowercase Letter 149
 
7.9%
Decimal Number 32
 
1.7%
Close Punctuation 31
 
1.6%
Open Punctuation 31
 
1.6%
Other Punctuation 25
 
1.3%
Dash Punctuation 5
 
0.3%
Math Symbol 2
 
0.1%
Other values (2) 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 66
 
5.9%
이 27
 
2.4%
전 26
 
2.3%
자 20
 
1.8%
제 18
 
1.6%
영 16
 
1.4%
로 16
 
1.4%
모 16
 
1.4%
어 16
 
1.4%
계 16
 
1.4%
Other values (249) 889
79.0%
Uppercase Letter
ValueCountFrequency (%)
C 35
15.6%
I 20
 
8.9%
A 19
 
8.5%
P 18
 
8.0%
O 15
 
6.7%
S 14
 
6.2%
E 14
 
6.2%
T 12
 
5.4%
D 12
 
5.4%
M 10
 
4.5%
Other values (12) 55
24.6%
Lowercase Letter
ValueCountFrequency (%)
t 20
13.4%
o 17
11.4%
e 13
8.7%
n 12
 
8.1%
a 11
 
7.4%
u 11
 
7.4%
i 10
 
6.7%
c 10
 
6.7%
r 8
 
5.4%
w 7
 
4.7%
Other values (9) 30
20.1%
Decimal Number
ValueCountFrequency (%)
1 9
28.1%
2 9
28.1%
0 6
18.8%
3 4
12.5%
7 2
 
6.2%
5 1
 
3.1%
6 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 16
64.0%
/ 3
 
12.0%
. 2
 
8.0%
: 2
 
8.0%
· 1
 
4.0%
% 1
 
4.0%
Close Punctuation
ValueCountFrequency (%)
) 25
80.6%
] 6
 
19.4%
Open Punctuation
ValueCountFrequency (%)
( 25
80.6%
[ 6
 
19.4%
Space Separator
ValueCountFrequency (%)
260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1126
59.7%
Common 388
 
20.6%
Latin 373
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 66
 
5.9%
이 27
 
2.4%
전 26
 
2.3%
자 20
 
1.8%
제 18
 
1.6%
영 16
 
1.4%
로 16
 
1.4%
모 16
 
1.4%
어 16
 
1.4%
계 16
 
1.4%
Other values (249) 889
79.0%
Latin
ValueCountFrequency (%)
C 35
 
9.4%
I 20
 
5.4%
t 20
 
5.4%
A 19
 
5.1%
P 18
 
4.8%
o 17
 
4.6%
O 15
 
4.0%
S 14
 
3.8%
E 14
 
3.8%
e 13
 
3.5%
Other values (31) 188
50.4%
Common
ValueCountFrequency (%)
260
67.0%
) 25
 
6.4%
( 25
 
6.4%
, 16
 
4.1%
1 9
 
2.3%
2 9
 
2.3%
] 6
 
1.5%
[ 6
 
1.5%
0 6
 
1.5%
- 5
 
1.3%
Other values (12) 21
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1126
59.7%
ASCII 758
40.2%
Punctuation 2
 
0.1%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260
34.3%
C 35
 
4.6%
) 25
 
3.3%
( 25
 
3.3%
I 20
 
2.6%
t 20
 
2.6%
A 19
 
2.5%
P 18
 
2.4%
o 17
 
2.2%
, 16
 
2.1%
Other values (50) 303
40.0%
Hangul
ValueCountFrequency (%)
기 66
 
5.9%
이 27
 
2.4%
전 26
 
2.3%
자 20
 
1.8%
제 18
 
1.6%
영 16
 
1.4%
로 16
 
1.4%
모 16
 
1.4%
어 16
 
1.4%
계 16
 
1.4%
Other values (249) 889
79.0%
Punctuation
ValueCountFrequency (%)
” 1
50.0%
“ 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
113 
12년도 구매
12 
13년도 구매
 
4
14년도 구매
 
3

Length

Max length7
Median length4
Mean length4.4318182
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 113
85.6%
12년도 구매 12
 
9.1%
13년도 구매 4
 
3.0%
14년도 구매 3
 
2.3%

Length

2023-12-12T08:16:15.047913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:16:15.130294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
74.8%
구매 19
 
12.6%
12년도 12
 
7.9%
13년도 4
 
2.6%
14년도 3
 
2.0%

Interactions

2023-12-12T08:16:13.711486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:16:15.185587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분야비고
번호1.0000.9390.534
분야0.9391.0000.319
비고0.5340.3191.000
2023-12-12T08:16:15.260479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고분야
비고1.0000.493
분야0.4931.000
2023-12-12T08:16:15.333348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분야비고
번호1.0000.7000.513
분야0.7001.0000.493
비고0.5130.4931.000

Missing values

2023-12-12T08:16:13.801139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:16:13.866777image/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

번호분야콘텐츠명비고
01OA[Must Know]PC Basic<NA>
12OA[Must Know]PC Intermedia<NA>
23OA[Must Know]PC Advanced<NA>
34OA성공 프레젠테이션 나도 할 수 있다.<NA>
45OA업무의 달인을 인정받는 Excel 2007<NA>
56OA업무의 달인을 인정받는 Powerpoint 2007<NA>
67OA사무자동화산업기사<NA>
78OA컴퓨터그래픽스운용기능사<NA>
89교양메모의 기술<NA>
910교양기술 교과 개요<NA>
번호분야콘텐츠명비고
122123정보통신정보처리산업기사<NA>
123124정보통신사례로 들어보는 홈네트워크 시공<NA>
124125정보통신홈네트워크망설계 및 유지관리방법<NA>
125126정보통신홈네트워크건축도면의 이해및 설계<NA>
126127정보통신무선랜 기술과 스마트폰 활용<NA>
127128패션모듈형(디자인도식화, 패션코디네이션, 패션VMD)<NA>
128129패션패션 디자인의 요소 및 원리<NA>
129130표면처리전기도금<NA>
130131환경화학위험물 산업기사<NA>
131132환경화학신재생 에너지<NA>