Overview

Dataset statistics

Number of variables9
Number of observations50
Missing cells24
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory74.6 B

Variable types

Text8
Categorical1

Dataset

Description요양보호사교육원지정제현황20156
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202381

Alerts

요양보호사 교육원 has 3 (6.0%) missing valuesMissing
Unnamed: 1 has 1 (2.0%) missing valuesMissing
Unnamed: 2 has 1 (2.0%) missing valuesMissing
Unnamed: 3 has 3 (6.0%) missing valuesMissing
Unnamed: 4 has 3 (6.0%) missing valuesMissing
Unnamed: 6 has 4 (8.0%) missing valuesMissing
Unnamed: 7 has 6 (12.0%) missing valuesMissing
Unnamed: 8 has 3 (6.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 00:23:18.698294
Analysis finished2024-03-14 00:23:19.496604
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요양보호사 교육원
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing3
Missing (%)6.0%
Memory size532.0 B
2024-03-14T09:23:19.647762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8085106
Min length1

Characters and Unicode

Total characters85
Distinct characters12
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

Unique47 ?
Unique (%)100.0%

Sample

1st row번호
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
번호 1
 
2.1%
35 1
 
2.1%
25 1
 
2.1%
26 1
 
2.1%
27 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
Other values (37) 37
78.7%
2024-03-14T09:23:19.997273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.6%
2 15
17.6%
3 15
17.6%
4 12
14.1%
5 5
 
5.9%
6 5
 
5.9%
0 4
 
4.7%
7 4
 
4.7%
8 4
 
4.7%
9 4
 
4.7%
Other values (2) 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
97.6%
Other Letter 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
18.1%
2 15
18.1%
3 15
18.1%
4 12
14.5%
5 5
 
6.0%
6 5
 
6.0%
0 4
 
4.8%
7 4
 
4.8%
8 4
 
4.8%
9 4
 
4.8%
Other Letter
ValueCountFrequency (%)
번 1
50.0%
호 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
97.6%
Hangul 2
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.1%
2 15
18.1%
3 15
18.1%
4 12
14.5%
5 5
 
6.0%
6 5
 
6.0%
0 4
 
4.8%
7 4
 
4.8%
8 4
 
4.8%
9 4
 
4.8%
Hangul
ValueCountFrequency (%)
번 1
50.0%
호 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
97.6%
Hangul 2
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
18.1%
2 15
18.1%
3 15
18.1%
4 12
14.5%
5 5
 
6.0%
6 5
 
6.0%
0 4
 
4.8%
7 4
 
4.8%
8 4
 
4.8%
9 4
 
4.8%
Hangul
ValueCountFrequency (%)
번 1
50.0%
호 1
50.0%

Unnamed: 1
Text

MISSING 

Distinct49
Distinct (%)100.0%
Missing1
Missing (%)2.0%
Memory size532.0 B
2024-03-14T09:23:20.241350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length14.755102
Min length4

Characters and Unicode

Total characters723
Distinct characters102
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row명 칭
2nd row적정 요양보호사교육원 개소수
3rd row현재 운영 중인 교육원 개소수
4th row군산성모간호전문학원 부설 성모요양보호사교육원
5th row전주성모간호교육원 부설 전주성모요양보호사교육원
ValueCountFrequency (%)
요양보호사교육원 13
 
15.3%
부설 10
 
11.8%
개소수 2
 
2.4%
평생교육원 2
 
2.4%
탑클래스 1
 
1.2%
송천 1
 
1.2%
봉동간호학원 1
 
1.2%
현대요양보호사교육원 1
 
1.2%
jk요양보호사교육원 1
 
1.2%
미래간호학원 1
 
1.2%
Other values (52) 52
61.2%
2024-03-14T09:23:20.570479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 69
 
9.5%
호 65
 
9.0%
교 53
 
7.3%
육 51
 
7.1%
47
 
6.5%
보 47
 
6.5%
양 47
 
6.5%
사 46
 
6.4%
요 46
 
6.4%
부 19
 
2.6%
Other values (92) 233
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 672
92.9%
Space Separator 47
 
6.5%
Uppercase Letter 1
 
0.1%
Lowercase Letter 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 69
 
10.3%
호 65
 
9.7%
교 53
 
7.9%
육 51
 
7.6%
보 47
 
7.0%
양 47
 
7.0%
사 46
 
6.8%
요 46
 
6.8%
부 19
 
2.8%
설 18
 
2.7%
Other values (87) 211
31.4%
Space Separator
ValueCountFrequency (%)
47
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 672
92.9%
Common 49
 
6.8%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 69
 
10.3%
호 65
 
9.7%
교 53
 
7.9%
육 51
 
7.6%
보 47
 
7.0%
양 47
 
7.0%
사 46
 
6.8%
요 46
 
6.8%
부 19
 
2.8%
설 18
 
2.7%
Other values (87) 211
31.4%
Common
ValueCountFrequency (%)
47
95.9%
( 1
 
2.0%
) 1
 
2.0%
Latin
ValueCountFrequency (%)
J 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 672
92.9%
ASCII 51
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 69
 
10.3%
호 65
 
9.7%
교 53
 
7.9%
육 51
 
7.6%
보 47
 
7.0%
양 47
 
7.0%
사 46
 
6.8%
요 46
 
6.8%
부 19
 
2.8%
설 18
 
2.7%
Other values (87) 211
31.4%
ASCII
ValueCountFrequency (%)
47
92.2%
J 1
 
2.0%
k 1
 
2.0%
( 1
 
2.0%
) 1
 
2.0%

Unnamed: 2
Text

MISSING 

Distinct49
Distinct (%)100.0%
Missing1
Missing (%)2.0%
Memory size532.0 B
2024-03-14T09:23:20.856423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length26
Mean length23.387755
Min length9

Characters and Unicode

Total characters1146
Distinct characters130
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

Unique49 ?
Unique (%)100.0%

Sample

1st row소 재 지
2nd row65개소(전주21, 군산9, 익산10, 정읍3, 남원2, 김제3, 완주3, 진안2, 무주2, 장수2, 임실2, 순창2, 고창2, 부안2)
3rd row46개소(전주21, 군산5, 익산8, 정읍3, 남원2, 김제2, 완주1, 진안0, 무주0, 장수1, 임실0, 순창1, 고창1, 부안1) ▶ 73개소 중 28개소 폐지
4th row군산시 대학로 321 (나운동)
5th row전주시 완산구 어진길 114 (경원동 1가)
ValueCountFrequency (%)
전주시 21
 
8.2%
완산구 13
 
5.1%
3층 9
 
3.5%
익산시 8
 
3.1%
덕진구 8
 
3.1%
군산시 5
 
2.0%
2층 5
 
2.0%
익산대로 4
 
1.6%
2가 4
 
1.6%
4층 4
 
1.6%
Other values (153) 174
68.2%
2024-03-14T09:23:21.226257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
18.5%
2 49
 
4.3%
1 48
 
4.2%
로 44
 
3.8%
시 41
 
3.6%
( 38
 
3.3%
산 38
 
3.3%
) 38
 
3.3%
, 37
 
3.2%
동 33
 
2.9%
Other values (120) 568
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 593
51.7%
Decimal Number 214
 
18.7%
Space Separator 212
 
18.5%
Open Punctuation 38
 
3.3%
Close Punctuation 38
 
3.3%
Other Punctuation 38
 
3.3%
Dash Punctuation 8
 
0.7%
Uppercase Letter 3
 
0.3%
Other Symbol 1
 
0.1%
Control 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 44
 
7.4%
시 41
 
6.9%
산 38
 
6.4%
동 33
 
5.6%
주 30
 
5.1%
전 25
 
4.2%
층 23
 
3.9%
구 21
 
3.5%
완 17
 
2.9%
익 14
 
2.4%
Other values (99) 307
51.8%
Decimal Number
ValueCountFrequency (%)
2 49
22.9%
1 48
22.4%
3 29
13.6%
4 19
 
8.9%
0 16
 
7.5%
5 13
 
6.1%
6 12
 
5.6%
7 12
 
5.6%
8 10
 
4.7%
9 6
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
Y 1
33.3%
C 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 37
97.4%
. 1
 
2.6%
Space Separator
ValueCountFrequency (%)
212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Symbol
ValueCountFrequency (%)
▶ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 593
51.7%
Common 550
48.0%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 44
 
7.4%
시 41
 
6.9%
산 38
 
6.4%
동 33
 
5.6%
주 30
 
5.1%
전 25
 
4.2%
층 23
 
3.9%
구 21
 
3.5%
완 17
 
2.9%
익 14
 
2.4%
Other values (99) 307
51.8%
Common
ValueCountFrequency (%)
212
38.5%
2 49
 
8.9%
1 48
 
8.7%
( 38
 
6.9%
) 38
 
6.9%
, 37
 
6.7%
3 29
 
5.3%
4 19
 
3.5%
0 16
 
2.9%
5 13
 
2.4%
Other values (8) 51
 
9.3%
Latin
ValueCountFrequency (%)
B 1
33.3%
Y 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 593
51.7%
ASCII 552
48.2%
Geometric Shapes 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
38.4%
2 49
 
8.9%
1 48
 
8.7%
( 38
 
6.9%
) 38
 
6.9%
, 37
 
6.7%
3 29
 
5.3%
4 19
 
3.4%
0 16
 
2.9%
5 13
 
2.4%
Other values (10) 53
 
9.6%
Hangul
ValueCountFrequency (%)
로 44
 
7.4%
시 41
 
6.9%
산 38
 
6.4%
동 33
 
5.6%
주 30
 
5.1%
전 25
 
4.2%
층 23
 
3.9%
구 21
 
3.5%
완 17
 
2.9%
익 14
 
2.4%
Other values (99) 307
51.8%
Geometric Shapes
ValueCountFrequency (%)
▶ 1
100.0%

Unnamed: 3
Text

MISSING 

Distinct46
Distinct (%)97.9%
Missing3
Missing (%)6.0%
Memory size532.0 B
2024-03-14T09:23:21.408164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.6170213
Min length3

Characters and Unicode

Total characters170
Distinct characters71
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st row대표자
2nd row정봉성
3rd row윤석길
4th row기성옥
5th row박성희
ValueCountFrequency (%)
배순주 2
 
4.0%
박진표 1
 
2.0%
신동아학원(홍정길 1
 
2.0%
오규만 1
 
2.0%
최문성 1
 
2.0%
이서현 1
 
2.0%
조희경 1
 
2.0%
학교법인 1
 
2.0%
전주기독학원(윤정길 1
 
2.0%
최정옥 1
 
2.0%
Other values (39) 39
78.0%
2024-03-14T09:23:21.705855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 12
 
7.1%
성 9
 
5.3%
박 8
 
4.7%
김 7
 
4.1%
이 6
 
3.5%
숙 5
 
2.9%
순 5
 
2.9%
기 5
 
2.9%
신 4
 
2.4%
주 4
 
2.4%
Other values (61) 105
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
95.9%
Space Separator 2
 
1.2%
Open Punctuation 2
 
1.2%
Close Punctuation 2
 
1.2%
Control 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 12
 
7.4%
성 9
 
5.5%
박 8
 
4.9%
김 7
 
4.3%
이 6
 
3.7%
숙 5
 
3.1%
순 5
 
3.1%
기 5
 
3.1%
신 4
 
2.5%
주 4
 
2.5%
Other values (57) 98
60.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
95.9%
Common 7
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 12
 
7.4%
성 9
 
5.5%
박 8
 
4.9%
김 7
 
4.3%
이 6
 
3.7%
숙 5
 
3.1%
순 5
 
3.1%
기 5
 
3.1%
신 4
 
2.5%
주 4
 
2.5%
Other values (57) 98
60.1%
Common
ValueCountFrequency (%)
2
28.6%
( 2
28.6%
) 2
28.6%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
95.9%
ASCII 7
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 12
 
7.4%
성 9
 
5.5%
박 8
 
4.9%
김 7
 
4.3%
이 6
 
3.7%
숙 5
 
3.1%
순 5
 
3.1%
기 5
 
3.1%
신 4
 
2.5%
주 4
 
2.5%
Other values (57) 98
60.1%
ASCII
ValueCountFrequency (%)
2
28.6%
( 2
28.6%
) 2
28.6%
1
14.3%

Unnamed: 4
Text

MISSING 

Distinct37
Distinct (%)78.7%
Missing3
Missing (%)6.0%
Memory size532.0 B
2024-03-14T09:23:21.872181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6382979
Min length3

Characters and Unicode

Total characters453
Distinct characters14
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

Unique34 ?
Unique (%)72.3%

Sample

1st row지정일
2nd row2008.02.19
3rd row2008.02.28
4th row2008.02.28
5th row2008.10.01
ValueCountFrequency (%)
2010.10.28 7
 
14.9%
2010.10.20 4
 
8.5%
2008.02.28 2
 
4.3%
2014.10.22 1
 
2.1%
2014.11.07 1
 
2.1%
2014.12.02 1
 
2.1%
2014.07.23 1
 
2.1%
2014.07.24 1
 
2.1%
2014.10.06 1
 
2.1%
2014.10.15 1
 
2.1%
Other values (27) 27
57.4%
2024-03-14T09:23:22.191215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 116
25.6%
. 92
20.3%
1 89
19.6%
2 80
17.7%
8 20
 
4.4%
4 15
 
3.3%
5 12
 
2.6%
9 8
 
1.8%
3 7
 
1.5%
6 6
 
1.3%
Other values (4) 8
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 358
79.0%
Other Punctuation 92
 
20.3%
Other Letter 3
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 116
32.4%
1 89
24.9%
2 80
22.3%
8 20
 
5.6%
4 15
 
4.2%
5 12
 
3.4%
9 8
 
2.2%
3 7
 
2.0%
6 6
 
1.7%
7 5
 
1.4%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
정 1
33.3%
일 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 450
99.3%
Hangul 3
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 116
25.8%
. 92
20.4%
1 89
19.8%
2 80
17.8%
8 20
 
4.4%
4 15
 
3.3%
5 12
 
2.7%
9 8
 
1.8%
3 7
 
1.6%
6 6
 
1.3%
Hangul
ValueCountFrequency (%)
지 1
33.3%
정 1
33.3%
일 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 450
99.3%
Hangul 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 116
25.8%
. 92
20.4%
1 89
19.8%
2 80
17.8%
8 20
 
4.4%
4 15
 
3.3%
5 12
 
2.7%
9 8
 
1.8%
3 7
 
1.6%
6 6
 
1.3%
Hangul
ValueCountFrequency (%)
지 1
33.3%
정 1
33.3%
일 1
33.3%

Unnamed: 5
Categorical

Distinct12
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
30명
20 
40명
14 
<NA>
3 
35명
 
2
20명
 
2
Other values (7)
9 

Length

Max length4
Median length3
Mean length3.04
Min length2

Unique

Unique5 ?
Unique (%)10.0%

Sample

1st row<NA>
2nd row정원
3rd row<NA>
4th row<NA>
5th row40명

Common Values

ValueCountFrequency (%)
30명 20
40.0%
40명 14
28.0%
<NA> 3
 
6.0%
35명 2
 
4.0%
20명 2
 
4.0%
15명 2
 
4.0%
25명 2
 
4.0%
정원 1
 
2.0%
36명 1
 
2.0%
34명 1
 
2.0%
Other values (2) 2
 
4.0%

Length

2024-03-14T09:23:22.334575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30명 20
40.0%
40명 14
28.0%
na 3
 
6.0%
35명 2
 
4.0%
20명 2
 
4.0%
15명 2
 
4.0%
25명 2
 
4.0%
정원 1
 
2.0%
36명 1
 
2.0%
34명 1
 
2.0%
Other values (2) 2
 
4.0%

Unnamed: 6
Text

MISSING 

Distinct46
Distinct (%)100.0%
Missing4
Missing (%)8.0%
Memory size532.0 B
2024-03-14T09:23:22.547481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length8.3478261
Min length4

Characters and Unicode

Total characters384
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row471-8420
3rd row283-6662~5
4th row858-9840
5th row632-2993
ValueCountFrequency (%)
231-4554 1
 
2.1%
471-8420 1
 
2.1%
833-3370 1
 
2.1%
626-2233 1
 
2.1%
277-7701 1
 
2.1%
272-4747 1
 
2.1%
280-5271 1
 
2.1%
232-0230 1
 
2.1%
261-1125 1
 
2.1%
274-9858 1
 
2.1%
Other values (38) 38
79.2%
2024-03-14T09:23:23.041024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 62
16.1%
- 47
12.2%
8 37
9.6%
5 36
9.4%
3 35
9.1%
1 31
8.1%
4 29
7.6%
6 25
6.5%
9 25
6.5%
0 25
6.5%
Other values (7) 32
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
85.9%
Dash Punctuation 47
 
12.2%
Other Letter 4
 
1.0%
Control 2
 
0.5%
Math Symbol 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 62
18.8%
8 37
11.2%
5 36
10.9%
3 35
10.6%
1 31
9.4%
4 29
8.8%
6 25
7.6%
9 25
7.6%
0 25
7.6%
7 25
7.6%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 380
99.0%
Hangul 4
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 62
16.3%
- 47
12.4%
8 37
9.7%
5 36
9.5%
3 35
9.2%
1 31
8.2%
4 29
7.6%
6 25
6.6%
9 25
6.6%
0 25
6.6%
Other values (3) 28
7.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 380
99.0%
Hangul 4
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 62
16.3%
- 47
12.4%
8 37
9.7%
5 36
9.5%
3 35
9.2%
1 31
8.2%
4 29
7.6%
6 25
6.6%
9 25
6.6%
0 25
6.6%
Other values (3) 28
7.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 7
Text

MISSING 

Distinct43
Distinct (%)97.7%
Missing6
Missing (%)12.0%
Memory size532.0 B
2024-03-14T09:23:23.213548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8863636
Min length3

Characters and Unicode

Total characters347
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st rowFAX
2nd row471-8425
3rd row286-6661
4th row858-9841
5th row631-2993
ValueCountFrequency (%)
853-8334 2
 
4.5%
243-1165 1
 
2.3%
227-1010 1
 
2.3%
445-5056 1
 
2.3%
626-2283 1
 
2.3%
277-7702 1
 
2.3%
255-4748 1
 
2.3%
285-0230 1
 
2.3%
261-1165 1
 
2.3%
353-6699 1
 
2.3%
Other values (33) 33
75.0%
2024-03-14T09:23:23.477464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 52
15.0%
- 43
12.4%
8 34
9.8%
3 34
9.8%
5 33
9.5%
1 33
9.5%
4 27
7.8%
6 25
7.2%
0 22
6.3%
9 21
6.1%
Other values (4) 23
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 301
86.7%
Dash Punctuation 43
 
12.4%
Uppercase Letter 3
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 52
17.3%
8 34
11.3%
3 34
11.3%
5 33
11.0%
1 33
11.0%
4 27
9.0%
6 25
8.3%
0 22
7.3%
9 21
7.0%
7 20
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
F 1
33.3%
A 1
33.3%
X 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 344
99.1%
Latin 3
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 52
15.1%
- 43
12.5%
8 34
9.9%
3 34
9.9%
5 33
9.6%
1 33
9.6%
4 27
7.8%
6 25
7.3%
0 22
6.4%
9 21
6.1%
Latin
ValueCountFrequency (%)
F 1
33.3%
A 1
33.3%
X 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 52
15.0%
- 43
12.4%
8 34
9.8%
3 34
9.8%
5 33
9.5%
1 33
9.5%
4 27
7.8%
6 25
7.2%
0 22
6.3%
9 21
6.1%
Other values (4) 23
6.6%

Unnamed: 8
Text

MISSING 

Distinct37
Distinct (%)78.7%
Missing3
Missing (%)6.0%
Memory size532.0 B
2024-03-14T09:23:23.646421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length7.0212766
Min length4

Characters and Unicode

Total characters330
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)63.8%

Sample

1st row2015. 5월 현재
2nd row우편번호
3rd row573-870
4th row560-020
5th row570-993
ValueCountFrequency (%)
561-810 4
 
8.2%
560-023 3
 
6.1%
570-982 2
 
4.1%
561-820 2
 
4.1%
561-870 2
 
4.1%
560-760 2
 
4.1%
570-993 2
 
4.1%
573-863 1
 
2.0%
5월 1
 
2.0%
현재 1
 
2.0%
Other values (29) 29
59.2%
2024-03-14T09:23:23.962944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59
17.9%
5 58
17.6%
- 45
13.6%
6 30
9.1%
7 28
8.5%
8 26
7.9%
1 25
7.6%
2 15
 
4.5%
3 14
 
4.2%
9 14
 
4.2%
Other values (10) 16
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
83.3%
Dash Punctuation 45
 
13.6%
Other Letter 7
 
2.1%
Space Separator 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
21.5%
5 58
21.1%
6 30
10.9%
7 28
10.2%
8 26
9.5%
1 25
9.1%
2 15
 
5.5%
3 14
 
5.1%
9 14
 
5.1%
4 6
 
2.2%
Other Letter
ValueCountFrequency (%)
현 1
14.3%
월 1
14.3%
우 1
14.3%
호 1
14.3%
번 1
14.3%
편 1
14.3%
재 1
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 323
97.9%
Hangul 7
 
2.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59
18.3%
5 58
18.0%
- 45
13.9%
6 30
9.3%
7 28
8.7%
8 26
8.0%
1 25
7.7%
2 15
 
4.6%
3 14
 
4.3%
9 14
 
4.3%
Other values (3) 9
 
2.8%
Hangul
ValueCountFrequency (%)
현 1
14.3%
월 1
14.3%
우 1
14.3%
호 1
14.3%
번 1
14.3%
편 1
14.3%
재 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
97.9%
Hangul 7
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59
18.3%
5 58
18.0%
- 45
13.9%
6 30
9.3%
7 28
8.7%
8 26
8.0%
1 25
7.7%
2 15
 
4.6%
3 14
 
4.3%
9 14
 
4.3%
Other values (3) 9
 
2.8%
Hangul
ValueCountFrequency (%)
현 1
14.3%
월 1
14.3%
우 1
14.3%
호 1
14.3%
번 1
14.3%
편 1
14.3%
재 1
14.3%

Correlations

2024-03-14T09:23:24.045031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요양보호사 교육원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
요양보호사 교육원1.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0000.9731.0001.0000.9950.987
Unnamed: 41.0001.0001.0000.9731.0000.9151.0000.9910.581
Unnamed: 51.0001.0001.0001.0000.9151.0001.0000.9930.840
Unnamed: 61.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0000.9950.9910.9931.0001.0000.994
Unnamed: 81.0001.0001.0000.9870.5810.8401.0000.9941.000

Missing values

2024-03-14T09:23:19.184515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:23:19.287489image/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.
2024-03-14T09:23:19.395362image/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

요양보호사 교육원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0<NA><NA><NA><NA><NA><NA><NA><NA>2015. 5월 현재
1번호명 칭소 재 지대표자지정일정원전화번호FAX우편번호
2<NA>적정 요양보호사교육원 개소수65개소(전주21, 군산9, 익산10, 정읍3, 남원2, 김제3, 완주3, 진안2, 무주2, 장수2, 임실2, 순창2, 고창2, 부안2)<NA><NA><NA><NA><NA><NA>
3<NA>현재 운영 중인 교육원 개소수46개소(전주21, 군산5, 익산8, 정읍3, 남원2, 김제2, 완주1, 진안0, 무주0, 장수1, 임실0, 순창1, 고창1, 부안1) ▶ 73개소 중 28개소 폐지<NA><NA><NA><NA><NA><NA>
41군산성모간호전문학원 부설 성모요양보호사교육원군산시 대학로 321 (나운동)정봉성2008.02.1940명471-8420471-8425573-870
52전주성모간호교육원 부설 전주성모요양보호사교육원전주시 완산구 어진길 114 (경원동 1가)윤석길2008.02.2835명283-6662~5286-6661560-020
63익산간호요양보호사교육원익산시 익산대로 133-2 (창인동 2가)기성옥2008.02.2840명858-9840858-9841570-993
74남원간호요양보호사교육원남원시 의총로 77. 3층 (왕정동)박성희2008.10.0136명632-2993631-2993590-120
85목민요양보호사교육원전주시 완산구 용머리로 203 (서완산동 2가)김옥숙2009.09.0630명229-3144229-3147560-152
96김제성모 요양보호사교육원김제시 동서로 222 (요촌동)박수임2010.01.34명545-9888545-9887576-805
요양보호사 교육원Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
4037고창요양보호사교육원고창군 고창읍 중앙로 180, 3층김재홍2014.11.0730명563-0038563-0018585-808
4138아중안골요양보호사교육원전주시 덕진구 견훤로 289, 3층김은희2014.12.0235명282-2323242-1441561-870
4239군산여성인력개발센터 요양보호사교육원군산시 백토로 119, 대주빌딩 (2층)백지연2014.12.1130명468-0055468-0058573-863
4340평화탑클래스요양보호사교육원전주시 완산구 소대배기로 5, 4층기정임2015.1.1515명229-6229229-6228560-865
4441덕진간호학원부설요양보호사교육원전주시 덕진구 기린대로 481 (동원타워 5층)김지은2015.2.1730명276-6767276-6768561-810
4542호남제일간호학원부설요양보호사교육원전주시 덕진구 편운로 6 (동산동 종로약국4층)이성민2015.4.2330명212-7571212-7572561-810
4643한양간호학원부설요양보호사교육원전주시 완산구 장승배기로 200 (세영빌딩6층)박영자2015.4.2720명236-8788223-5920561-810
4744부안요양보호사교육원부안군 부안읍 석정로 241 (2층)김인수2015.5.1230명582-6222<NA><NA>
4845전주비전대학교부설요양보호사교육원전주시 완산구 천잠로 235학교번입 신동아학원(홍정길)2015.6.1940명220-3982220-3989560-760
4946성모간호학원부설요양보호사교육원정읍시 충정로 175-1 (3층)박미숙6015.06.2925명534-1119<NA>560-760