Overview

Dataset statistics

Number of variables8
Number of observations75
Missing cells96
Missing cells (%)16.0%
Duplicate rows2
Duplicate rows (%)2.7%
Total size in memory4.8 KiB
Average record size in memory65.8 B

Variable types

Text4
Categorical4

Dataset

Description경력단절여성국도비직업교육훈련과정
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201665

Alerts

Dataset has 2 (2.7%) duplicate rowsDuplicates
센터명 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
유형 is highly overall correlated with 센터명 and 2 other fieldsHigh correlation
훈 련 과 정 명 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
교육기간 is highly overall correlated with 센터명 and 2 other fieldsHigh correlation
연번 has 18 (24.0%) missing valuesMissing
교육인원 has 17 (22.7%) missing valuesMissing
교육시간 has 25 (33.3%) missing valuesMissing
Unnamed: 7 has 36 (48.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 00:50:42.856580
Analysis finished2024-03-14 00:50:43.546917
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Text

MISSING 

Distinct47
Distinct (%)82.5%
Missing18
Missing (%)24.0%
Memory size732.0 B
2024-03-14T09:50:43.676065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length2
Mean length2.6666667
Min length1

Characters and Unicode

Total characters152
Distinct characters42
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)64.9%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
2 3
 
4.5%
6 3
 
4.5%
3 3
 
4.5%
9 2
 
3.0%
10 2
 
3.0%
15 2
 
3.0%
1 2
 
3.0%
11 2
 
3.0%
8 2
 
3.0%
4 2
 
3.0%
Other values (42) 44
65.7%
2024-03-14T09:50:44.021448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
 
12.5%
2 16
 
10.5%
3 15
 
9.9%
일 10
 
6.6%
10
 
6.6%
새 9
 
5.9%
5 6
 
3.9%
7 6
 
3.9%
6 6
 
3.9%
4 5
 
3.3%
Other values (32) 50
32.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85
55.9%
Other Letter 57
37.5%
Space Separator 10
 
6.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 10
17.5%
새 9
15.8%
정 4
 
7.0%
전 3
 
5.3%
과 3
 
5.3%
산 2
 
3.5%
주 2
 
3.5%
김 1
 
1.8%
원 1
 
1.8%
남 1
 
1.8%
Other values (21) 21
36.8%
Decimal Number
ValueCountFrequency (%)
1 19
22.4%
2 16
18.8%
3 15
17.6%
5 6
 
7.1%
7 6
 
7.1%
6 6
 
7.1%
4 5
 
5.9%
9 4
 
4.7%
8 4
 
4.7%
0 4
 
4.7%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95
62.5%
Hangul 57
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 10
17.5%
새 9
15.8%
정 4
 
7.0%
전 3
 
5.3%
과 3
 
5.3%
산 2
 
3.5%
주 2
 
3.5%
김 1
 
1.8%
원 1
 
1.8%
남 1
 
1.8%
Other values (21) 21
36.8%
Common
ValueCountFrequency (%)
1 19
20.0%
2 16
16.8%
3 15
15.8%
10
10.5%
5 6
 
6.3%
7 6
 
6.3%
6 6
 
6.3%
4 5
 
5.3%
9 4
 
4.2%
8 4
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95
62.5%
Hangul 57
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
20.0%
2 16
16.8%
3 15
15.8%
10
10.5%
5 6
 
6.3%
7 6
 
6.3%
6 6
 
6.3%
4 5
 
5.3%
9 4
 
4.2%
8 4
 
4.2%
Hangul
ValueCountFrequency (%)
일 10
17.5%
새 9
15.8%
정 4
 
7.0%
전 3
 
5.3%
과 3
 
5.3%
산 2
 
3.5%
주 2
 
3.5%
김 1
 
1.8%
원 1
 
1.8%
남 1
 
1.8%
Other values (21) 21
36.8%

센터명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
17 
전북새일
11 
전주새일
6 
익산새일
5 
(산단형)
5 
Other values (13)
31 

Length

Max length5
Median length4
Mean length3.6666667
Min length2

Unique

Unique5 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
22.7%
전북새일 11
14.7%
전주새일 6
 
8.0%
익산새일 5
 
6.7%
(산단형) 5
 
6.7%
새일 4
 
5.3%
센터 4
 
5.3%
남원새일 3
 
4.0%
완주새일 3
 
4.0%
김제새일 3
 
4.0%
Other values (8) 14
18.7%

Length

2024-03-14T09:50:44.136162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 17
22.7%
전북새일 11
14.7%
전주새일 6
 
8.0%
익산새일 5
 
6.7%
산단형 5
 
6.7%
새일 4
 
5.3%
센터 4
 
5.3%
정읍새일 3
 
4.0%
3 3
 
4.0%
군산새일 3
 
4.0%
Other values (8) 14
18.7%

유형
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
일반
18 
<NA>
15 
전문
11 
일반과정
8 
계
8 
Other values (9)
15 

Length

Max length4
Median length3
Mean length2.72
Min length1

Unique

Unique6 ?
Unique (%)8.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 18
24.0%
<NA> 15
20.0%
전문 11
14.7%
일반과정 8
10.7%
계 8
10.7%
취약계층 5
 
6.7%
소 계 2
 
2.7%
창업 2
 
2.7%
소계 1
 
1.3%
기업맞춤 1
 
1.3%
Other values (4) 4
 
5.3%

Length

2024-03-14T09:50:44.249582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반 18
23.4%
na 15
19.5%
전문 11
14.3%
계 10
13.0%
일반과정 8
10.4%
취약계층 5
 
6.5%
소 2
 
2.6%
창업 2
 
2.6%
소계 1
 
1.3%
기업맞춤 1
 
1.3%
Other values (4) 4
 
5.2%

훈 련 과 정 명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
22 
일반
15 
기업
9 
이민
4 
결혼
4 
Other values (17)
21 

Length

Max length12
Median length2
Mean length3.6533333
Min length2

Unique

Unique14 ?
Unique (%)18.7%

Sample

1st row<NA>
2nd row10개 과정
3rd row직업교육훈련 취업담당자
4th row직무연수
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 22
29.3%
일반 15
20.0%
기업 9
12.0%
이민 4
 
5.3%
결혼 4
 
5.3%
역량 3
 
4.0%
창업 2
 
2.7%
기술 2
 
2.7%
호텔객실관리사 1
 
1.3%
직업교육훈련 취업담당자 1
 
1.3%
Other values (12) 12
16.0%

Length

2024-03-14T09:50:44.345492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 22
28.6%
일반 15
19.5%
기업 9
11.7%
이민 4
 
5.2%
결혼 4
 
5.2%
역량 3
 
3.9%
창업 2
 
2.6%
기술 2
 
2.6%
떡공방창업과정 1
 
1.3%
과정 1
 
1.3%
Other values (14) 14
18.2%

교육인원
Text

MISSING 

Distinct48
Distinct (%)82.8%
Missing17
Missing (%)22.7%
Memory size732.0 B
2024-03-14T09:50:44.535987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14.5
Mean length8.2758621
Min length2

Characters and Unicode

Total characters480
Distinct characters137
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)79.3%

Sample

1st row(명)
2nd row212
3rd row30
4th row20
5th row20
ValueCountFrequency (%)
20 8
 
9.0%
과정 8
 
9.0%
양성교육 5
 
5.6%
3개 5
 
5.6%
제조인력 3
 
3.4%
양성과정 3
 
3.4%
새일역량교육 3
 
3.4%
품질검사원 2
 
2.2%
단체급식조리사 2
 
2.2%
양성 2
 
2.2%
Other values (48) 48
53.9%
2024-03-14T09:50:44.855223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
7.7%
과 24
 
5.0%
정 20
 
4.2%
성 17
 
3.5%
사 15
 
3.1%
양 15
 
3.1%
2 13
 
2.7%
리 12
 
2.5%
육 10
 
2.1%
교 10
 
2.1%
Other values (127) 307
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 395
82.3%
Space Separator 37
 
7.7%
Decimal Number 36
 
7.5%
Uppercase Letter 9
 
1.9%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 24
 
6.1%
정 20
 
5.1%
성 17
 
4.3%
사 15
 
3.8%
양 15
 
3.8%
리 12
 
3.0%
육 10
 
2.5%
교 10
 
2.5%
개 9
 
2.3%
무 8
 
2.0%
Other values (111) 255
64.6%
Decimal Number
ValueCountFrequency (%)
2 13
36.1%
0 9
25.0%
3 8
22.2%
1 4
 
11.1%
6 1
 
2.8%
5 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
D 3
33.3%
I 2
22.2%
Y 1
 
11.1%
T 1
 
11.1%
L 1
 
11.1%
E 1
 
11.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 395
82.3%
Common 76
 
15.8%
Latin 9
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 24
 
6.1%
정 20
 
5.1%
성 17
 
4.3%
사 15
 
3.8%
양 15
 
3.8%
리 12
 
3.0%
육 10
 
2.5%
교 10
 
2.5%
개 9
 
2.3%
무 8
 
2.0%
Other values (111) 255
64.6%
Common
ValueCountFrequency (%)
37
48.7%
2 13
 
17.1%
0 9
 
11.8%
3 8
 
10.5%
1 4
 
5.3%
6 1
 
1.3%
( 1
 
1.3%
) 1
 
1.3%
& 1
 
1.3%
5 1
 
1.3%
Latin
ValueCountFrequency (%)
D 3
33.3%
I 2
22.2%
Y 1
 
11.1%
T 1
 
11.1%
L 1
 
11.1%
E 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 395
82.3%
ASCII 85
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
43.5%
2 13
 
15.3%
0 9
 
10.6%
3 8
 
9.4%
1 4
 
4.7%
D 3
 
3.5%
I 2
 
2.4%
Y 1
 
1.2%
T 1
 
1.2%
L 1
 
1.2%
Other values (6) 6
 
7.1%
Hangul
ValueCountFrequency (%)
과 24
 
6.1%
정 20
 
5.1%
성 17
 
4.3%
사 15
 
3.8%
양 15
 
3.8%
리 12
 
3.0%
육 10
 
2.5%
교 10
 
2.5%
개 9
 
2.3%
무 8
 
2.0%
Other values (111) 255
64.6%

교육기간
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
27 
20
25 
22
5 
15
4 
24
3 
Other values (11)
11 

Length

Max length15
Median length2
Mean length4.4533333
Min length2

Unique

Unique11 ?
Unique (%)14.7%

Sample

1st row<NA>
2nd row<NA>
3rd row04. 21 ~ 04. 25
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 27
36.0%
20 25
33.3%
22 5
 
6.7%
15 4
 
5.3%
24 3
 
4.0%
04. 21 ~ 04. 25 1
 
1.3%
04. 04 ~ 07. 11 1
 
1.3%
04. 11 ~ 07. 29 1
 
1.3%
04. 18 ~ 05. 27 1
 
1.3%
06. 20 ~ 07. 19 1
 
1.3%
Other values (6) 6
 
8.0%

Length

2024-03-14T09:50:44.965569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 27
23.5%
20 27
23.5%
04 12
10.4%
10
 
8.7%
22 5
 
4.3%
15 5
 
4.3%
07 5
 
4.3%
24 3
 
2.6%
06 3
 
2.6%
05 3
 
2.6%
Other values (11) 15
13.0%

교육시간
Text

MISSING 

Distinct48
Distinct (%)96.0%
Missing25
Missing (%)33.3%
Memory size732.0 B
2024-03-14T09:50:45.116457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length10.42
Min length2

Characters and Unicode

Total characters521
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)94.0%

Sample

1st row(시간)
2nd row4박5일
3rd row160
4th row184
5th row128
ValueCountFrequency (%)
24
20.7%
04 10
 
8.6%
05 5
 
4.3%
04.04 5
 
4.3%
160 3
 
2.6%
07.26 2
 
1.7%
18 2
 
1.7%
02 2
 
1.7%
20 2
 
1.7%
06.01 2
 
1.7%
Other values (51) 59
50.9%
2024-03-14T09:50:45.427562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
23.0%
. 74
14.2%
66
12.7%
1 40
 
7.7%
4 39
 
7.5%
~ 38
 
7.3%
2 26
 
5.0%
7 20
 
3.8%
6 20
 
3.8%
5 19
 
3.6%
Other values (14) 59
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 324
62.2%
Other Punctuation 74
 
14.2%
Space Separator 69
 
13.2%
Math Symbol 38
 
7.3%
Other Letter 12
 
2.3%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
37.0%
1 40
 
12.3%
4 39
 
12.0%
2 26
 
8.0%
7 20
 
6.2%
6 20
 
6.2%
5 19
 
5.9%
8 19
 
5.9%
3 11
 
3.4%
9 10
 
3.1%
Other Letter
ValueCountFrequency (%)
일 3
25.0%
간 2
16.7%
월 2
16.7%
기 1
 
8.3%
육 1
 
8.3%
박 1
 
8.3%
교 1
 
8.3%
시 1
 
8.3%
Space Separator
ValueCountFrequency (%)
66
95.7%
　 3
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 74
100.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 509
97.7%
Hangul 12
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
23.6%
. 74
14.5%
66
13.0%
1 40
 
7.9%
4 39
 
7.7%
~ 38
 
7.5%
2 26
 
5.1%
7 20
 
3.9%
6 20
 
3.9%
5 19
 
3.7%
Other values (6) 47
 
9.2%
Hangul
ValueCountFrequency (%)
일 3
25.0%
간 2
16.7%
월 2
16.7%
기 1
 
8.3%
육 1
 
8.3%
박 1
 
8.3%
교 1
 
8.3%
시 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 506
97.1%
Hangul 12
 
2.3%
None 3
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
23.7%
. 74
14.6%
66
13.0%
1 40
 
7.9%
4 39
 
7.7%
~ 38
 
7.5%
2 26
 
5.1%
7 20
 
4.0%
6 20
 
4.0%
5 19
 
3.8%
Other values (5) 44
 
8.7%
Hangul
ValueCountFrequency (%)
일 3
25.0%
간 2
16.7%
월 2
16.7%
기 1
 
8.3%
육 1
 
8.3%
박 1
 
8.3%
교 1
 
8.3%
시 1
 
8.3%
None
ValueCountFrequency (%)
　 3
100.0%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)56.4%
Missing36
Missing (%)48.0%
Memory size732.0 B
2024-03-14T09:50:45.567216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8205128
Min length2

Characters and Unicode

Total characters110
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)43.6%

Sample

1st row교육
2nd row시간
3rd row120
4th row260
5th row120
ValueCountFrequency (%)
120 9
23.1%
200 4
 
10.3%
20 3
 
7.7%
184 3
 
7.7%
160 3
 
7.7%
205 1
 
2.6%
92 1
 
2.6%
180 1
 
2.6%
240 1
 
2.6%
219 1
 
2.6%
Other values (12) 12
30.8%
2024-03-14T09:50:45.811831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
28.2%
1 24
21.8%
2 24
21.8%
6 8
 
7.3%
8 7
 
6.4%
4 7
 
6.4%
7 2
 
1.8%
9 2
 
1.8%
시 1
 
0.9%
간 1
 
0.9%
Other values (3) 3
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106
96.4%
Other Letter 4
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
29.2%
1 24
22.6%
2 24
22.6%
6 8
 
7.5%
8 7
 
6.6%
4 7
 
6.6%
7 2
 
1.9%
9 2
 
1.9%
5 1
 
0.9%
Other Letter
ValueCountFrequency (%)
시 1
25.0%
간 1
25.0%
교 1
25.0%
육 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106
96.4%
Hangul 4
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
29.2%
1 24
22.6%
2 24
22.6%
6 8
 
7.5%
8 7
 
6.6%
4 7
 
6.6%
7 2
 
1.9%
9 2
 
1.9%
5 1
 
0.9%
Hangul
ValueCountFrequency (%)
시 1
25.0%
간 1
25.0%
교 1
25.0%
육 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
96.4%
Hangul 4
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
29.2%
1 24
22.6%
2 24
22.6%
6 8
 
7.5%
8 7
 
6.6%
4 7
 
6.6%
7 2
 
1.9%
9 2
 
1.9%
5 1
 
0.9%
Hangul
ValueCountFrequency (%)
시 1
25.0%
간 1
25.0%
교 1
25.0%
육 1
25.0%

Correlations

2024-03-14T09:50:45.922730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번센터명유형훈 련 과 정 명교육인원교육기간교육시간Unnamed: 7
연번1.0000.5660.0000.0000.9820.0000.9901.000
센터명0.5661.0000.8710.8670.7700.8990.7520.933
유형0.0000.8711.0000.9830.0000.8641.0000.957
훈 련 과 정 명0.0000.8670.9831.0000.0000.9770.0000.916
교육인원0.9820.7700.0000.0001.0000.0001.0001.000
교육기간0.0000.8990.8640.9770.0001.0000.0000.891
교육시간0.9900.7521.0000.0001.0000.0001.0001.000
Unnamed: 71.0000.9330.9570.9161.0000.8911.0001.000
2024-03-14T09:50:46.053601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형센터명훈 련 과 정 명교육기간
유형1.0000.5290.7800.534
센터명0.5291.0000.4570.591
훈 련 과 정 명0.7800.4571.0000.792
교육기간0.5340.5910.7921.000
2024-03-14T09:50:46.145444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명유형훈 련 과 정 명교육기간
센터명1.0000.5290.4570.591
유형0.5291.0000.7800.534
훈 련 과 정 명0.4570.7801.0000.792
교육기간0.5910.5340.7921.000

Missing values

2024-03-14T09:50:43.284276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:50:43.378866image/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.
2024-03-14T09:50:43.472744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번센터명유형훈 련 과 정 명교육인원교육기간교육시간Unnamed: 7
0<NA><NA><NA><NA>(명)<NA>(시간)<NA>
1<NA><NA><NA>10개 과정212<NA><NA><NA>
21광역일반과정직업교육훈련 취업담당자3004. 21 ~ 04. 254박5일<NA>
3<NA>새일<NA>직무연수<NA><NA><NA><NA>
4<NA>센터<NA><NA><NA><NA><NA><NA>
5<NA>전주소계<NA><NA><NA><NA><NA>
62새일일반과정방과후특기적성지도사2004. 04 ~ 07. 11160<NA>
73센터일반과정IT사무원2004. 11 ~ 07. 29184<NA>
84-3일반과정탄소소재제조생산인력양성2004. 18 ~ 05. 27128<NA>
9<NA>군산소 계<NA><NA><NA><NA><NA>
연번센터명유형훈 련 과 정 명교육인원교육기간교육시간Unnamed: 7
6530남원새일일반일반방과후아동지도사양성과정2004.04 ~ 09.05219
6631남원새일일반일반사무행정실무과정2004.04 ~ 07.26240
67김제새일<NA>계<NA>3개 과정<NA><NA><NA>
6832김제새일취약계층결혼이민네일아트국가자격증2203. 02 ~ 05. 24184
6933김제새일일반일반로봇과학방과후지도사2404. 18 ~ 06. 20180
7034김제새일일반일반커리어IT실무자2005. 09 ~ 07. 08184
71완주새일<NA>계<NA>3개 과정<NA><NA><NA>
7235완주새일일반일반생산제조품질관리원1505. 18 ~ 06. 16120
7336완주새일일반일반자동차부품제조양성과정1509. 21 ~ 10. 20120
7437완주새일창업창업폐백이야기1504. 21 ~ 05. 27100

Duplicate rows

Most frequently occurring

연번센터명유형훈 련 과 정 명교육인원교육기간교육시간Unnamed: 7# duplicates
0<NA>(산단형)<NA><NA><NA><NA><NA><NA>4
1<NA><NA><NA>이민<NA><NA><NA><NA>2