Overview

Dataset statistics

Number of variables13
Number of observations269
Missing cells48
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.2 KiB
Average record size in memory107.5 B

Variable types

Numeric3
Categorical6
Text4

Dataset

Description한국폴리텍대학에서 시행하는 소규모사업장훈련 순번, 대학, 캠퍼스, 실사업명, 과정명/차수, 대표업체명, 훈련직종명, 직종대분류, 직종중분류, 훈련시간, 훈련기간, 주야구분, 수료인원
Author학교법인한국폴리텍
URLhttps://www.data.go.kr/data/15032095/fileData.do

Alerts

대학 is highly overall correlated with 캠퍼스High correlation
직종대분류 is highly overall correlated with 직종중분류High correlation
캠퍼스 is highly overall correlated with 대학 and 1 other fieldsHigh correlation
직종중분류 is highly overall correlated with 직종대분류High correlation
훈련시간 is highly overall correlated with 주야구분High correlation
실사업명 is highly overall correlated with 주야구분High correlation
주야구분 is highly overall correlated with 훈련시간 and 2 other fieldsHigh correlation
훈련직종명 has 48 (17.8%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:06:30.828697
Analysis finished2023-12-12 15:06:32.902632
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct269
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135
Minimum1
Maximum269
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-13T00:06:32.972609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.4
Q168
median135
Q3202
95-th percentile255.6
Maximum269
Range268
Interquartile range (IQR)134

Descriptive statistics

Standard deviation77.797815
Coefficient of variation (CV)0.57628011
Kurtosis-1.2
Mean135
Median Absolute Deviation (MAD)67
Skewness0
Sum36315
Variance6052.5
MonotonicityStrictly increasing
2023-12-13T00:06:33.091067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
186 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
178 1
 
0.4%
179 1
 
0.4%
Other values (259) 259
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%

대학
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
한국폴리텍Ⅰ대학
44 
한국폴리텍Ⅶ대학
40 
한국폴리텍Ⅱ대학
37 
한국폴리텍Ⅲ대학
34 
한국폴리텍Ⅵ대학
31 
Other values (3)
83 

Length

Max length11
Median length8
Mean length8.3011152
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한국폴리텍Ⅰ대학
2nd row한국폴리텍Ⅴ대학
3rd row한국폴리텍Ⅱ대학
4th row한국폴리텍Ⅴ대학
5th row한국폴리텍Ⅰ대학

Common Values

ValueCountFrequency (%)
한국폴리텍Ⅰ대학 44
16.4%
한국폴리텍Ⅶ대학 40
14.9%
한국폴리텍Ⅱ대학 37
13.8%
한국폴리텍Ⅲ대학 34
12.6%
한국폴리텍Ⅵ대학 31
11.5%
한국폴리텍Ⅳ대학 30
11.2%
한국폴리텍 특성화대학 27
10.0%
한국폴리텍Ⅴ대학 26
9.7%

Length

2023-12-13T00:06:33.194553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:33.287765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국폴리텍ⅰ대학 44
14.9%
한국폴리텍ⅶ대학 40
13.5%
한국폴리텍ⅱ대학 37
12.5%
한국폴리텍ⅲ대학 34
11.5%
한국폴리텍ⅵ대학 31
10.5%
한국폴리텍ⅳ대학 30
10.1%
한국폴리텍 27
9.1%
특성화대학 27
9.1%
한국폴리텍ⅴ대학 26
8.8%

캠퍼스
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
춘천캠퍼스
22 
서울정수캠퍼스
 
19
성남캠퍼스
 
13
부산캠퍼스
 
12
아산캠퍼스
 
12
Other values (29)
191 

Length

Max length7
Median length5
Mean length5.3605948
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울강서캠퍼스
2nd row광주캠퍼스
3rd row인천캠퍼스
4th row익산캠퍼스
5th row서울정수캠퍼스

Common Values

ValueCountFrequency (%)
춘천캠퍼스 22
 
8.2%
서울정수캠퍼스 19
 
7.1%
성남캠퍼스 13
 
4.8%
부산캠퍼스 12
 
4.5%
아산캠퍼스 12
 
4.5%
화성캠퍼스 12
 
4.5%
창원캠퍼스 11
 
4.1%
바이오캠퍼스 10
 
3.7%
안성캠퍼스 10
 
3.7%
대구캠퍼스 10
 
3.7%
Other values (24) 138
51.3%

Length

2023-12-13T00:06:33.402625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
춘천캠퍼스 22
 
8.2%
서울정수캠퍼스 19
 
7.1%
성남캠퍼스 13
 
4.8%
부산캠퍼스 12
 
4.5%
아산캠퍼스 12
 
4.5%
화성캠퍼스 12
 
4.5%
창원캠퍼스 11
 
4.1%
서울강서캠퍼스 10
 
3.7%
대구캠퍼스 10
 
3.7%
안성캠퍼스 10
 
3.7%
Other values (24) 138
51.3%

실사업명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
소규모사업장(현장맞춤)훈련
126 
소규모사업장(현장애로)훈련
94 
소규모사업장(대학집체)훈련
49 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소규모사업장(현장애로)훈련
2nd row소규모사업장(현장애로)훈련
3rd row소규모사업장(현장맞춤)훈련
4th row소규모사업장(현장맞춤)훈련
5th row소규모사업장(현장애로)훈련

Common Values

ValueCountFrequency (%)
소규모사업장(현장맞춤)훈련 126
46.8%
소규모사업장(현장애로)훈련 94
34.9%
소규모사업장(대학집체)훈련 49
 
18.2%

Length

2023-12-13T00:06:33.498133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:33.573860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소규모사업장(현장맞춤)훈련 126
46.8%
소규모사업장(현장애로)훈련 94
34.9%
소규모사업장(대학집체)훈련 49
 
18.2%

과정명_차수
Text

Distinct267
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:06:33.797041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length30
Mean length16.349442
Min length6

Characters and Unicode

Total characters4398
Distinct characters355
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)98.5%

Sample

1st row2D이미지 채색/1
2nd row3D 모델링 기술지도/1
3rd row3D CAD (SolidWorks)/1
4th row3D모델링/1
5th row3D프린터 활용법/1
ValueCountFrequency (%)
및 48
 
5.6%
실무/1 11
 
1.3%
위한 10
 
1.2%
활용한 9
 
1.0%
고급과정/1 8
 
0.9%
초급과정/1 7
 
0.8%
이용한 7
 
0.8%
과정/1 7
 
0.8%
설계 7
 
0.8%
중급과정/1 7
 
0.8%
Other values (545) 739
85.9%
2023-12-13T00:06:34.149867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
 
13.4%
/ 271
 
6.2%
1 259
 
5.9%
기 105
 
2.4%
정 79
 
1.8%
제 78
 
1.8%
용 71
 
1.6%
무 68
 
1.5%
설 67
 
1.5%
전 67
 
1.5%
Other values (345) 2742
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2922
66.4%
Space Separator 591
 
13.4%
Decimal Number 290
 
6.6%
Other Punctuation 278
 
6.3%
Uppercase Letter 194
 
4.4%
Lowercase Letter 95
 
2.2%
Close Punctuation 14
 
0.3%
Open Punctuation 13
 
0.3%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 105
 
3.6%
정 79
 
2.7%
제 78
 
2.7%
용 71
 
2.4%
무 68
 
2.3%
설 67
 
2.3%
전 67
 
2.3%
실 64
 
2.2%
비 56
 
1.9%
자 56
 
1.9%
Other values (288) 2211
75.7%
Uppercase Letter
ValueCountFrequency (%)
C 33
17.0%
P 21
10.8%
D 18
9.3%
L 17
8.8%
A 16
8.2%
S 14
 
7.2%
N 12
 
6.2%
M 9
 
4.6%
I 9
 
4.6%
W 8
 
4.1%
Other values (12) 37
19.1%
Lowercase Letter
ValueCountFrequency (%)
o 15
15.8%
a 11
11.6%
t 9
9.5%
r 8
 
8.4%
i 7
 
7.4%
n 6
 
6.3%
e 6
 
6.3%
s 5
 
5.3%
m 4
 
4.2%
y 4
 
4.2%
Other values (10) 20
21.1%
Decimal Number
ValueCountFrequency (%)
1 259
89.3%
2 17
 
5.9%
3 8
 
2.8%
4 3
 
1.0%
6 2
 
0.7%
5 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
/ 271
97.5%
, 3
 
1.1%
. 2
 
0.7%
· 1
 
0.4%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
591
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2922
66.4%
Common 1187
27.0%
Latin 289
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 105
 
3.6%
정 79
 
2.7%
제 78
 
2.7%
용 71
 
2.4%
무 68
 
2.3%
설 67
 
2.3%
전 67
 
2.3%
실 64
 
2.2%
비 56
 
1.9%
자 56
 
1.9%
Other values (288) 2211
75.7%
Latin
ValueCountFrequency (%)
C 33
 
11.4%
P 21
 
7.3%
D 18
 
6.2%
L 17
 
5.9%
A 16
 
5.5%
o 15
 
5.2%
S 14
 
4.8%
N 12
 
4.2%
a 11
 
3.8%
t 9
 
3.1%
Other values (32) 123
42.6%
Common
ValueCountFrequency (%)
591
49.8%
/ 271
22.8%
1 259
21.8%
2 17
 
1.4%
) 14
 
1.2%
( 13
 
1.1%
3 8
 
0.7%
4 3
 
0.3%
, 3
 
0.3%
. 2
 
0.2%
Other values (5) 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2922
66.4%
ASCII 1475
33.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
591
40.1%
/ 271
18.4%
1 259
17.6%
C 33
 
2.2%
P 21
 
1.4%
D 18
 
1.2%
2 17
 
1.2%
L 17
 
1.2%
A 16
 
1.1%
o 15
 
1.0%
Other values (46) 217
 
14.7%
Hangul
ValueCountFrequency (%)
기 105
 
3.6%
정 79
 
2.7%
제 78
 
2.7%
용 71
 
2.4%
무 68
 
2.3%
설 67
 
2.3%
전 67
 
2.3%
실 64
 
2.2%
비 56
 
1.9%
자 56
 
1.9%
Other values (288) 2211
75.7%
None
ValueCountFrequency (%)
· 1
100.0%

대표업체명
Text

Distinct222
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:06:34.365447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length7.8141264
Min length2

Characters and Unicode

Total characters2102
Distinct characters301
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)68.0%

Sample

1st row㈜새롬애니메이션
2nd row주식회사 디앤에스몰드에칭
3rd row(주)유니온공조이엔지
4th row(유)정연엔지니어링
5th row동원펌프(주)
ValueCountFrequency (%)
주)동우유니온 5
 
1.8%
주)선경이엔아이 5
 
1.8%
주)두성텍스타일 4
 
1.4%
주식회사 4
 
1.4%
주)퀴즈톡 2
 
0.7%
㈜와우텍 2
 
0.7%
주)비비드펄 2
 
0.7%
주)미래티엔씨 2
 
0.7%
주)디웍스 2
 
0.7%
하이버스(주 2
 
0.7%
Other values (221) 253
89.4%
2023-12-13T00:06:34.696328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 186
 
8.8%
주 186
 
8.8%
( 185
 
8.8%
이 70
 
3.3%
스 52
 
2.5%
아 37
 
1.8%
엔 32
 
1.5%
지 27
 
1.3%
에 27
 
1.3%
사 23
 
1.1%
Other values (291) 1277
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1619
77.0%
Close Punctuation 186
 
8.8%
Open Punctuation 185
 
8.8%
Uppercase Letter 42
 
2.0%
Other Symbol 22
 
1.0%
Lowercase Letter 21
 
1.0%
Space Separator 15
 
0.7%
Decimal Number 6
 
0.3%
Dash Punctuation 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 186
 
11.5%
이 70
 
4.3%
스 52
 
3.2%
아 37
 
2.3%
엔 32
 
2.0%
지 27
 
1.7%
에 27
 
1.7%
사 23
 
1.4%
업 23
 
1.4%
비 22
 
1.4%
Other values (255) 1120
69.2%
Uppercase Letter
ValueCountFrequency (%)
E 5
11.9%
D 4
 
9.5%
J 4
 
9.5%
S 3
 
7.1%
T 3
 
7.1%
K 3
 
7.1%
B 3
 
7.1%
C 3
 
7.1%
L 2
 
4.8%
N 2
 
4.8%
Other values (6) 10
23.8%
Lowercase Letter
ValueCountFrequency (%)
e 5
23.8%
t 4
19.0%
x 2
 
9.5%
s 2
 
9.5%
i 2
 
9.5%
n 1
 
4.8%
o 1
 
4.8%
a 1
 
4.8%
h 1
 
4.8%
c 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
1 4
66.7%
3 2
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 185
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 22
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1641
78.1%
Common 398
 
18.9%
Latin 63
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 186
 
11.3%
이 70
 
4.3%
스 52
 
3.2%
아 37
 
2.3%
엔 32
 
2.0%
지 27
 
1.6%
에 27
 
1.6%
사 23
 
1.4%
업 23
 
1.4%
비 22
 
1.3%
Other values (256) 1142
69.6%
Latin
ValueCountFrequency (%)
e 5
 
7.9%
E 5
 
7.9%
D 4
 
6.3%
t 4
 
6.3%
J 4
 
6.3%
S 3
 
4.8%
T 3
 
4.8%
K 3
 
4.8%
B 3
 
4.8%
C 3
 
4.8%
Other values (17) 26
41.3%
Common
ValueCountFrequency (%)
) 186
46.7%
( 185
46.5%
15
 
3.8%
1 4
 
1.0%
- 4
 
1.0%
3 2
 
0.5%
, 1
 
0.3%
. 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1619
77.0%
ASCII 461
 
21.9%
None 22
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 186
40.3%
( 185
40.1%
15
 
3.3%
e 5
 
1.1%
E 5
 
1.1%
1 4
 
0.9%
- 4
 
0.9%
D 4
 
0.9%
t 4
 
0.9%
J 4
 
0.9%
Other values (25) 45
 
9.8%
Hangul
ValueCountFrequency (%)
주 186
 
11.5%
이 70
 
4.3%
스 52
 
3.2%
아 37
 
2.3%
엔 32
 
2.0%
지 27
 
1.7%
에 27
 
1.7%
사 23
 
1.4%
업 23
 
1.4%
비 22
 
1.4%
Other values (255) 1120
69.2%
None
ValueCountFrequency (%)
㈜ 22
100.0%

훈련직종명
Text

MISSING 

Distinct92
Distinct (%)41.6%
Missing48
Missing (%)17.8%
Memory size2.2 KiB
2023-12-13T00:06:34.883005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.3348416
Min length2

Characters and Unicode

Total characters1400
Distinct characters166
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)21.7%

Sample

1st row애니메이션
2nd row컴퓨터모델링기술
3rd row컴퓨터설계(CAD)
4th row3D
5th row전자기기
ValueCountFrequency (%)
및 18
 
7.0%
전기설비 13
 
5.1%
자동제어 13
 
5.1%
자동차정비(기관·새시·전기 12
 
4.7%
에너지설비 12
 
4.7%
정보통신 11
 
4.3%
plc 9
 
3.5%
공유압(유압기초 6
 
2.3%
자동차검사 5
 
1.9%
전기시스템제어 5
 
1.9%
Other values (86) 153
59.5%
2023-12-13T00:06:35.178498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 105
 
7.5%
자 68
 
4.9%
전 65
 
4.6%
비 47
 
3.4%
설 46
 
3.3%
동 46
 
3.3%
계 38
 
2.7%
36
 
2.6%
제 34
 
2.4%
정 31
 
2.2%
Other values (156) 884
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1209
86.4%
Uppercase Letter 66
 
4.7%
Space Separator 36
 
2.6%
Open Punctuation 28
 
2.0%
Close Punctuation 28
 
2.0%
Other Punctuation 27
 
1.9%
Lowercase Letter 5
 
0.4%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 105
 
8.7%
자 68
 
5.6%
전 65
 
5.4%
비 47
 
3.9%
설 46
 
3.8%
동 46
 
3.8%
계 38
 
3.1%
제 34
 
2.8%
정 31
 
2.6%
시 30
 
2.5%
Other values (136) 699
57.8%
Uppercase Letter
ValueCountFrequency (%)
C 23
34.8%
P 10
15.2%
L 9
 
13.6%
A 9
 
13.6%
D 7
 
10.6%
N 3
 
4.5%
M 2
 
3.0%
O 2
 
3.0%
W 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
f 2
40.0%
e 1
20.0%
c 1
20.0%
i 1
20.0%
Other Punctuation
ValueCountFrequency (%)
· 24
88.9%
& 2
 
7.4%
/ 1
 
3.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1209
86.4%
Common 120
 
8.6%
Latin 71
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 105
 
8.7%
자 68
 
5.6%
전 65
 
5.4%
비 47
 
3.9%
설 46
 
3.8%
동 46
 
3.8%
계 38
 
3.1%
제 34
 
2.8%
정 31
 
2.6%
시 30
 
2.5%
Other values (136) 699
57.8%
Latin
ValueCountFrequency (%)
C 23
32.4%
P 10
14.1%
L 9
 
12.7%
A 9
 
12.7%
D 7
 
9.9%
N 3
 
4.2%
M 2
 
2.8%
O 2
 
2.8%
f 2
 
2.8%
e 1
 
1.4%
Other values (3) 3
 
4.2%
Common
ValueCountFrequency (%)
36
30.0%
( 28
23.3%
) 28
23.3%
· 24
20.0%
& 2
 
1.7%
3 1
 
0.8%
/ 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1209
86.4%
ASCII 167
 
11.9%
None 24
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 105
 
8.7%
자 68
 
5.6%
전 65
 
5.4%
비 47
 
3.9%
설 46
 
3.8%
동 46
 
3.8%
계 38
 
3.1%
제 34
 
2.8%
정 31
 
2.6%
시 30
 
2.5%
Other values (136) 699
57.8%
ASCII
ValueCountFrequency (%)
36
21.6%
( 28
16.8%
) 28
16.8%
C 23
13.8%
P 10
 
6.0%
L 9
 
5.4%
A 9
 
5.4%
D 7
 
4.2%
N 3
 
1.8%
M 2
 
1.2%
Other values (9) 12
 
7.2%
None
ValueCountFrequency (%)
· 24
100.0%

직종대분류
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
기계·장비분야
92 
<NA>
46 
정보·통신분야
29 
전기분야
28 
전자분야
27 
Other values (7)
47 

Length

Max length7
Median length6
Mean length5.5464684
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row정보·통신분야
2nd row산업응용분야
3rd row정보·통신분야
4th row산업응용분야
5th row<NA>

Common Values

ValueCountFrequency (%)
기계·장비분야 92
34.2%
<NA> 46
17.1%
정보·통신분야 29
 
10.8%
전기분야 28
 
10.4%
전자분야 27
 
10.0%
산업응용분야 15
 
5.6%
사무관리분야 10
 
3.7%
금속분야 8
 
3.0%
섬유분야 8
 
3.0%
건설분야 4
 
1.5%
Other values (2) 2
 
0.7%

Length

2023-12-13T00:06:35.299042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계·장비분야 92
34.2%
na 46
17.1%
정보·통신분야 29
 
10.8%
전기분야 28
 
10.4%
전자분야 27
 
10.0%
산업응용분야 15
 
5.6%
사무관리분야 10
 
3.7%
금속분야 8
 
3.0%
섬유분야 8
 
3.0%
건설분야 4
 
1.5%
Other values (2) 2
 
0.7%

직종중분류
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
46 
기계가공·조립
37 
용접·판금·배관
27 
기계·설비·제어
23 
정비·설비
23 
Other values (23)
113 

Length

Max length8
Median length7
Mean length6.0111524
Min length2

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row정보·통신응용
2nd row디자인개발
3rd row정보·통신응용
4th row디자인개발
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 46
17.1%
기계가공·조립 37
13.8%
용접·판금·배관 27
10.0%
기계·설비·제어 23
8.6%
정비·설비 23
8.6%
기기·설비·제어 19
 
7.1%
통신설비·운용 14
 
5.2%
디자인개발 14
 
5.2%
금속가공 8
 
3.0%
가공·조립·수리 8
 
3.0%
Other values (18) 50
18.6%

Length

2023-12-13T00:06:35.423837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 46
17.0%
기계가공·조립 37
13.7%
용접·판금·배관 27
10.0%
기계·설비·제어 23
8.5%
정비·설비 23
8.5%
기기·설비·제어 19
 
7.0%
통신설비·운용 14
 
5.2%
디자인개발 14
 
5.2%
금속가공 8
 
3.0%
가공·조립·수리 8
 
3.0%
Other values (19) 52
19.2%

훈련시간
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.594796
Minimum8
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-13T00:06:35.525890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile12
Q116
median24
Q340
95-th percentile60
Maximum60
Range52
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.124293
Coefficient of variation (CV)0.49394627
Kurtosis-0.20388658
Mean28.594796
Median Absolute Deviation (MAD)8
Skewness0.82180905
Sum7692
Variance199.49564
MonotonicityNot monotonic
2023-12-13T00:06:35.634266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
16 49
18.2%
40 45
16.7%
20 42
15.6%
24 33
12.3%
60 23
8.6%
32 17
 
6.3%
8 11
 
4.1%
48 9
 
3.3%
30 6
 
2.2%
12 5
 
1.9%
Other values (16) 29
10.8%
ValueCountFrequency (%)
8 11
 
4.1%
10 1
 
0.4%
12 5
 
1.9%
14 2
 
0.7%
15 2
 
0.7%
16 49
18.2%
17 1
 
0.4%
18 2
 
0.7%
20 42
15.6%
21 2
 
0.7%
ValueCountFrequency (%)
60 23
8.6%
56 1
 
0.4%
51 1
 
0.4%
48 9
 
3.3%
45 1
 
0.4%
42 1
 
0.4%
40 45
16.7%
36 4
 
1.5%
34 1
 
0.4%
32 17
 
6.3%

훈련기간
Text

Distinct234
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:06:35.878132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters5649
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)75.1%

Sample

1st row2019-11-07~2019-11-15
2nd row2019-06-11~2019-07-09
3rd row2019-05-11~2019-06-08
4th row2019-05-27~2019-05-31
5th row2019-06-12~2019-06-19
ValueCountFrequency (%)
2019-07-22~2019-07-26 4
 
1.5%
2019-01-14~2019-01-18 3
 
1.1%
2019-03-04~2019-03-22 2
 
0.7%
2019-06-10~2019-06-28 2
 
0.7%
2019-03-25~2019-04-05 2
 
0.7%
2019-05-20~2019-06-07 2
 
0.7%
2019-08-12~2019-08-30 2
 
0.7%
2019-07-01~2019-07-19 2
 
0.7%
2019-11-12~2019-11-13 2
 
0.7%
2019-06-13~2019-06-14 2
 
0.7%
Other values (224) 246
91.4%
2023-12-13T00:06:36.241720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1189
21.0%
- 1076
19.0%
1 1021
18.1%
2 826
14.6%
9 618
10.9%
~ 269
 
4.8%
7 134
 
2.4%
5 127
 
2.2%
6 114
 
2.0%
3 100
 
1.8%
Other values (2) 175
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4304
76.2%
Dash Punctuation 1076
 
19.0%
Math Symbol 269
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1189
27.6%
1 1021
23.7%
2 826
19.2%
9 618
14.4%
7 134
 
3.1%
5 127
 
3.0%
6 114
 
2.6%
3 100
 
2.3%
8 95
 
2.2%
4 80
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1076
100.0%
Math Symbol
ValueCountFrequency (%)
~ 269
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5649
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1189
21.0%
- 1076
19.0%
1 1021
18.1%
2 826
14.6%
9 618
10.9%
~ 269
 
4.8%
7 134
 
2.4%
5 127
 
2.2%
6 114
 
2.0%
3 100
 
1.8%
Other values (2) 175
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5649
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1189
21.0%
- 1076
19.0%
1 1021
18.1%
2 826
14.6%
9 618
10.9%
~ 269
 
4.8%
7 134
 
2.4%
5 127
 
2.2%
6 114
 
2.0%
3 100
 
1.8%
Other values (2) 175
 
3.1%

주야구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
주간
156 
야간
72 
<NA>
41 

Length

Max length4
Median length2
Mean length2.3048327
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주간 156
58.0%
야간 72
26.8%
<NA> 41
 
15.2%

Length

2023-12-13T00:06:36.384145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:36.498937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주간 156
58.0%
야간 72
26.8%
na 41
 
15.2%

수료인원
Real number (ℝ)

Distinct29
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.855019
Minimum4
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-13T00:06:36.606143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q17
median10
Q314
95-th percentile24.6
Maximum37
Range33
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.127789
Coefficient of variation (CV)0.51689408
Kurtosis2.1154555
Mean11.855019
Median Absolute Deviation (MAD)3
Skewness1.3907235
Sum3189
Variance37.549797
MonotonicityNot monotonic
2023-12-13T00:06:36.753458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
10 35
13.0%
5 28
10.4%
6 22
 
8.2%
9 22
 
8.2%
7 21
 
7.8%
11 20
 
7.4%
12 16
 
5.9%
15 15
 
5.6%
14 13
 
4.8%
13 12
 
4.5%
Other values (19) 65
24.2%
ValueCountFrequency (%)
4 1
 
0.4%
5 28
10.4%
6 22
8.2%
7 21
7.8%
8 12
 
4.5%
9 22
8.2%
10 35
13.0%
11 20
7.4%
12 16
5.9%
13 12
 
4.5%
ValueCountFrequency (%)
37 1
 
0.4%
36 1
 
0.4%
33 1
 
0.4%
30 1
 
0.4%
29 1
 
0.4%
28 3
1.1%
27 3
1.1%
25 3
1.1%
24 2
0.7%
23 2
0.7%

Interactions

2023-12-13T00:06:32.360435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:31.812534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.085408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.439789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:31.902910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.168737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.523867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.002524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:32.259897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:06:36.859755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대학캠퍼스실사업명훈련직종명직종대분류직종중분류훈련시간주야구분수료인원
순번1.0000.3160.6010.0900.8620.4690.6750.3620.3550.183
대학0.3161.0001.0000.3100.9070.5090.7320.5240.5890.299
캠퍼스0.6011.0001.0000.6630.9690.8000.8400.8160.8120.559
실사업명0.0900.3100.6631.0000.7630.3850.6350.3710.3120.242
훈련직종명0.8620.9070.9690.7631.0001.0001.0000.8050.7280.807
직종대분류0.4690.5090.8000.3851.0001.0001.0000.4550.2720.110
직종중분류0.6750.7320.8400.6351.0001.0001.0000.6790.4750.731
훈련시간0.3620.5240.8160.3710.8050.4550.6791.0000.7400.447
주야구분0.3550.5890.8120.3120.7280.2720.4750.7401.0000.296
수료인원0.1830.2990.5590.2420.8070.1100.7310.4470.2961.000
2023-12-13T00:06:37.318203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실사업명대학주야구분직종대분류캠퍼스직종중분류
실사업명1.0000.2050.5020.2400.4070.354
대학0.2051.0000.4390.2670.9490.381
주야구분0.5020.4391.0000.2540.6270.382
직종대분류0.2400.2670.2541.0000.4010.962
캠퍼스0.4070.9490.6270.4011.0000.343
직종중분류0.3540.3810.3820.9620.3431.000
2023-12-13T00:06:37.435901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번훈련시간수료인원대학캠퍼스실사업명직종대분류직종중분류주야구분
순번1.000-0.012-0.0360.1560.2450.0510.2200.3040.267
훈련시간-0.0121.000-0.0170.2810.4310.2360.2110.3070.570
수료인원-0.036-0.0171.0000.1460.2200.1460.0450.3510.223
대학0.1560.2810.1461.0000.9490.2050.2670.3810.439
캠퍼스0.2450.4310.2200.9491.0000.4070.4010.3430.627
실사업명0.0510.2360.1460.2050.4071.0000.2400.3540.502
직종대분류0.2200.2110.0450.2670.4010.2401.0000.9620.254
직종중분류0.3040.3070.3510.3810.3430.3540.9621.0000.382
주야구분0.2670.5700.2230.4390.6270.5020.2540.3821.000

Missing values

2023-12-13T00:06:32.665576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:06:32.847551image/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

순번대학캠퍼스실사업명과정명_차수대표업체명훈련직종명직종대분류직종중분류훈련시간훈련기간주야구분수료인원
01한국폴리텍Ⅰ대학서울강서캠퍼스소규모사업장(현장애로)훈련2D이미지 채색/1㈜새롬애니메이션애니메이션정보·통신분야정보·통신응용122019-11-07~2019-11-15주간14
12한국폴리텍Ⅴ대학광주캠퍼스소규모사업장(현장애로)훈련3D 모델링 기술지도/1주식회사 디앤에스몰드에칭컴퓨터모델링기술산업응용분야디자인개발402019-06-11~2019-07-09<NA>6
23한국폴리텍Ⅱ대학인천캠퍼스소규모사업장(현장맞춤)훈련3D CAD (SolidWorks)/1(주)유니온공조이엔지컴퓨터설계(CAD)정보·통신분야정보·통신응용402019-05-11~2019-06-08<NA>8
34한국폴리텍Ⅴ대학익산캠퍼스소규모사업장(현장맞춤)훈련3D모델링/1(유)정연엔지니어링3D산업응용분야디자인개발152019-05-27~2019-05-31<NA>9
45한국폴리텍Ⅰ대학서울정수캠퍼스소규모사업장(현장애로)훈련3D프린터 활용법/1동원펌프(주)<NA><NA><NA>182019-06-12~2019-06-19주간5
56한국폴리텍Ⅶ대학창원캠퍼스소규모사업장(현장맞춤)훈련4축 로봇 운용 프로그램 개발/1㈜신스윈전자기기전자분야기기·설비·제어182019-07-17~2019-07-24야간8
67한국폴리텍Ⅱ대학남인천캠퍼스소규모사업장(대학집체)훈련가솔린전자제어장치정비/1그린에너지자동차정비(기관·새시·전기)기계·장비분야정비·설비302019-04-30~2019-05-30야간13
78한국폴리텍Ⅲ대학춘천캠퍼스소규모사업장(현장맞춤)훈련가스설비제작 고급과정/1(주)델리캡에너지설비기계·장비분야용접·판금·배관602019-10-28~2019-11-15야간10
89한국폴리텍Ⅲ대학춘천캠퍼스소규모사업장(현장맞춤)훈련가스설비제작 초급과정/1(주)델리캡에너지설비기계·장비분야용접·판금·배관602019-10-07~2019-10-25야간12
910한국폴리텍Ⅳ대학아산캠퍼스소규모사업장(현장맞춤)훈련가스용접및 특수(브레이징)용접/1(주)대흥금속특수용접기계·장비분야용접·판금·배관322019-10-07~2019-10-18주간10
순번대학캠퍼스실사업명과정명_차수대표업체명훈련직종명직종대분류직종중분류훈련시간훈련기간주야구분수료인원
259260한국폴리텍Ⅵ대학포항캠퍼스소규모사업장(현장맞춤)훈련PLC제어 기본모듈 프로그램 개발 및 CAD/1(주)국제전기안전관리공사<NA><NA><NA>402019-10-14~2019-10-25야간15
260261한국폴리텍Ⅳ대학대전캠퍼스소규모사업장(현장맞춤)훈련PLC제어 실무/1Nextech(넥스텍)PLC전기분야기계·설비·제어242019-01-29~2019-01-31주간7
261262한국폴리텍Ⅴ대학목포캠퍼스소규모사업장(현장맞춤)훈련PLC제어 프로그램 개발 /1(유)주영엔지니어링PLC전기분야기계·설비·제어562019-06-03~2019-06-27야간5
262263한국폴리텍Ⅶ대학진주캠퍼스소규모사업장(대학집체)훈련PLC제어/1(주)한빛전기안전관리PLC전기분야기계·설비·제어152019-05-13~2019-05-17야간12
263264한국폴리텍Ⅰ대학성남캠퍼스소규모사업장(대학집체)훈련Smart Factory 멜섹Q PLC의 서보제어/1(주)시스템코리아자동화제어기술전기분야기계·설비·제어242019-11-09~2019-11-23<NA>7
264265한국폴리텍Ⅶ대학부산캠퍼스소규모사업장(현장맞춤)훈련SMPS 및 회로설계/1(주)유진에프에이기계전자(메카트로닉스)기계·장비분야기계가공·조립162019-07-22~2019-07-25주간12
265266한국폴리텍Ⅵ대학구미캠퍼스소규모사업장(현장맞춤)훈련SMT품질관리/1코아엠에스(주)품질관리종합사무관리분야생산사무분야202019-02-20~2019-02-25주간11
266267한국폴리텍Ⅵ대학영주캠퍼스소규모사업장(현장애로)훈련TIG용접장비 진단 및 용접공정 검토/1소백산업<NA><NA><NA>162019-10-04~2019-10-10주간10
267268한국폴리텍Ⅳ대학아산캠퍼스소규모사업장(현장맞춤)훈련UN NX를 활용한3D 프레스 금형설계/1㈜부광정기프레스금형설계기계·장비분야설계·제도482019-01-21~2019-01-26주간5
268269한국폴리텍Ⅴ대학목포캠퍼스소규모사업장(현장맞춤)훈련WPS에 따른 용접실무/1(유)나연산업용접기계·장비분야용접·판금·배관162019-11-15~2019-11-16주간9