Overview

Dataset statistics

Number of variables5
Number of observations44
Missing cells5
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory43.0 B

Variable types

Unsupported2
Text3

Dataset

Description전라북도요양보호사교육기관현황20174월현재
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202850

Alerts

요양보호사 교육원 현황 has 1 (2.3%) missing valuesMissing
Unnamed: 1 has 1 (2.3%) missing valuesMissing
Unnamed: 2 has 1 (2.3%) missing valuesMissing
Unnamed: 3 has 1 (2.3%) missing valuesMissing
Unnamed: 4 has 1 (2.3%) missing valuesMissing
요양보호사 교육원 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:54:48.929208
Analysis finished2024-03-14 02:54:49.367864
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요양보호사 교육원 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.3%
Memory size484.0 B

Unnamed: 1
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing1
Missing (%)2.3%
Memory size484.0 B
2024-03-14T11:54:49.508850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length14
Min length10

Characters and Unicode

Total characters602
Distinct characters83
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row명 칭
2nd row전주성모간호요양보호사교육원
3rd row전주성신간호학원 부설 요양보호사교육원
4th row온누리요양보호사교육원
5th row전주요양보호사교육원
ValueCountFrequency (%)
요양보호사교육원 9
 
15.0%
부설 5
 
8.3%
평화요양보호사교육원 2
 
3.3%
명 1
 
1.7%
제이성모요양보호사교육원 1
 
1.7%
익산 1
 
1.7%
중앙간호학원요양보호사교육원 1
 
1.7%
군산여성인력개발센터 1
 
1.7%
익산간호요양보호사교육원 1
 
1.7%
이리간호교육원 1
 
1.7%
Other values (37) 37
61.7%
2024-03-14T11:54:49.822060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 60
 
10.0%
호 60
 
10.0%
교 45
 
7.5%
육 44
 
7.3%
보 43
 
7.1%
사 43
 
7.1%
요 42
 
7.0%
양 42
 
7.0%
26
 
4.3%
간 17
 
2.8%
Other values (73) 180
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 574
95.3%
Space Separator 26
 
4.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 60
 
10.5%
호 60
 
10.5%
교 45
 
7.8%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (70) 164
28.6%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 574
95.3%
Common 26
 
4.3%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 60
 
10.5%
호 60
 
10.5%
교 45
 
7.8%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (70) 164
28.6%
Latin
ValueCountFrequency (%)
J 1
50.0%
K 1
50.0%
Common
ValueCountFrequency (%)
26
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 574
95.3%
ASCII 28
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 60
 
10.5%
호 60
 
10.5%
교 45
 
7.8%
육 44
 
7.7%
보 43
 
7.5%
사 43
 
7.5%
요 42
 
7.3%
양 42
 
7.3%
간 17
 
3.0%
학 14
 
2.4%
Other values (70) 164
28.6%
ASCII
ValueCountFrequency (%)
26
92.9%
J 1
 
3.6%
K 1
 
3.6%

Unnamed: 2
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing1
Missing (%)2.3%
Memory size484.0 B
2024-03-14T11:54:50.054641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length23
Mean length20.55814
Min length9

Characters and Unicode

Total characters884
Distinct characters127
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row소 재 지
2nd row전주시 완산구 팔달로 229 (고사동)
3rd row전주시 완산구 팔달로 250 (서노송동)
4th row전주시 완산구 팔달로 202-16 (3층)
5th row전주시 덕진구 떡전 4길 8 (금암동)
ValueCountFrequency (%)
전주시 19
 
9.5%
완산구 10
 
5.0%
덕진구 9
 
4.5%
3층 8
 
4.0%
익산시 8
 
4.0%
2층 5
 
2.5%
군산시 5
 
2.5%
무왕로 4
 
2.0%
4층 4
 
2.0%
익산대로 4
 
2.0%
Other values (109) 125
62.2%
2024-03-14T11:54:50.409607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
18.3%
로 42
 
4.8%
시 38
 
4.3%
1 33
 
3.7%
동 33
 
3.7%
) 32
 
3.6%
( 32
 
3.6%
2 32
 
3.6%
산 30
 
3.4%
주 21
 
2.4%
Other values (117) 429
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 469
53.1%
Space Separator 162
 
18.3%
Decimal Number 154
 
17.4%
Close Punctuation 32
 
3.6%
Open Punctuation 32
 
3.6%
Other Punctuation 15
 
1.7%
Lowercase Letter 10
 
1.1%
Dash Punctuation 6
 
0.7%
Uppercase Letter 3
 
0.3%
Control 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 42
 
9.0%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
주 21
 
4.5%
층 21
 
4.5%
전 20
 
4.3%
구 19
 
4.1%
익 12
 
2.6%
덕 11
 
2.3%
Other values (90) 222
47.3%
Decimal Number
ValueCountFrequency (%)
1 33
21.4%
2 32
20.8%
4 19
12.3%
3 19
12.3%
5 12
 
7.8%
6 9
 
5.8%
7 9
 
5.8%
0 7
 
4.5%
8 7
 
4.5%
9 7
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
u 3
30.0%
k 3
30.0%
r 1
 
10.0%
c 1
 
10.0%
a 1
 
10.0%
w 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 12
80.0%
. 2
 
13.3%
@ 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
Y 1
33.3%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 469
53.1%
Common 402
45.5%
Latin 13
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 42
 
9.0%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
주 21
 
4.5%
층 21
 
4.5%
전 20
 
4.3%
구 19
 
4.1%
익 12
 
2.6%
덕 11
 
2.3%
Other values (90) 222
47.3%
Common
ValueCountFrequency (%)
162
40.3%
1 33
 
8.2%
) 32
 
8.0%
( 32
 
8.0%
2 32
 
8.0%
4 19
 
4.7%
3 19
 
4.7%
5 12
 
3.0%
, 12
 
3.0%
6 9
 
2.2%
Other values (8) 40
 
10.0%
Latin
ValueCountFrequency (%)
u 3
23.1%
k 3
23.1%
r 1
 
7.7%
c 1
 
7.7%
a 1
 
7.7%
w 1
 
7.7%
C 1
 
7.7%
Y 1
 
7.7%
B 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 469
53.1%
ASCII 415
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
39.0%
1 33
 
8.0%
) 32
 
7.7%
( 32
 
7.7%
2 32
 
7.7%
4 19
 
4.6%
3 19
 
4.6%
5 12
 
2.9%
, 12
 
2.9%
6 9
 
2.2%
Other values (17) 53
 
12.8%
Hangul
ValueCountFrequency (%)
로 42
 
9.0%
시 38
 
8.1%
동 33
 
7.0%
산 30
 
6.4%
주 21
 
4.5%
층 21
 
4.5%
전 20
 
4.3%
구 19
 
4.1%
익 12
 
2.6%
덕 11
 
2.3%
Other values (90) 222
47.3%

Unnamed: 3
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing1
Missing (%)2.3%
Memory size484.0 B
2024-03-14T11:54:50.621194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length8.2790698
Min length4

Characters and Unicode

Total characters356
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

Unique43 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row283-6662~5
3rd row285-1999 285-1990
4th row231-4554
5th row284-1199
ValueCountFrequency (%)
전화번호 1
 
2.3%
272-4747 1
 
2.3%
833-4477 1
 
2.3%
471-2970 1
 
2.3%
468-0055 1
 
2.3%
858-9840 1
 
2.3%
851-2411 1
 
2.3%
840-1492 1
 
2.3%
853-8331 1
 
2.3%
852-0129 1
 
2.3%
Other values (34) 34
77.3%
2024-03-14T11:54:50.902210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 56
15.7%
- 44
12.4%
3 35
9.8%
4 32
9.0%
8 30
8.4%
1 30
8.4%
5 30
8.4%
6 25
7.0%
0 23
6.5%
7 23
6.5%
Other values (7) 28
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 306
86.0%
Dash Punctuation 44
 
12.4%
Other Letter 4
 
1.1%
Math Symbol 1
 
0.3%
Control 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 56
18.3%
3 35
11.4%
4 32
10.5%
8 30
9.8%
1 30
9.8%
5 30
9.8%
6 25
8.2%
0 23
7.5%
7 23
7.5%
9 22
 
7.2%
Other Letter
ValueCountFrequency (%)
화 1
25.0%
호 1
25.0%
번 1
25.0%
전 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 352
98.9%
Hangul 4
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 56
15.9%
- 44
12.5%
3 35
9.9%
4 32
9.1%
8 30
8.5%
1 30
8.5%
5 30
8.5%
6 25
7.1%
0 23
6.5%
7 23
6.5%
Other values (3) 24
6.8%
Hangul
ValueCountFrequency (%)
화 1
25.0%
호 1
25.0%
번 1
25.0%
전 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 352
98.9%
Hangul 4
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 56
15.9%
- 44
12.5%
3 35
9.9%
4 32
9.1%
8 30
8.5%
1 30
8.5%
5 30
8.5%
6 25
7.1%
0 23
6.5%
7 23
6.5%
Other values (3) 24
6.8%
Hangul
ValueCountFrequency (%)
화 1
25.0%
호 1
25.0%
번 1
25.0%
전 1
25.0%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.3%
Memory size484.0 B

Correlations

2024-03-14T11:54:51.022065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3
Unnamed: 11.0001.0001.000
Unnamed: 21.0001.0001.000
Unnamed: 31.0001.0001.000

Missing values

2024-03-14T11:54:49.148082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:54:49.235598image/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.
2024-03-14T11:54:49.315058image/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 교육원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
0NaN<NA><NA><NA>NaN
1번호명 칭소 재 지전화번호우편번호
21전주성모간호요양보호사교육원전주시 완산구 팔달로 229 (고사동)283-6662~555039
32전주성신간호학원 부설 요양보호사교육원전주시 완산구 팔달로 250 (서노송동)285-1999 285-199054995
43온누리요양보호사교육원전주시 완산구 팔달로 202-16 (3층)231-455455000
54전주요양보호사교육원전주시 덕진구 떡전 4길 8 (금암동)284-119954932
65전주여성인력개발센터 요양보호사교육원전주시 완산구 장승배기로 213 BYC빌딩 2층232-234655106
76전주메디칼요양보호사교육원전주시 완산구 용머리로 57 3층 (효자동1가)225-391055056
87평화요양보호사교육원전주시 완산구 장승배기로 210 (평화동 1가)225-144155122
98송천 탑클래스간호학원 요양보호사교육원전주시 덕진구 천마산로 19(송천동2가)277-770154829
요양보호사 교육원 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
341종로요양보호사교육원정읍시 관통로 14-4 (장명동)538-366356165
352정읍간호학원부설요양보호사교육원정읍시 충정로 324 (연지동)535-029756181
363성모간호학원부설요양보호사교육원정읍시 충정로 175-1 (연지동)534-111956165
371남원간호요양보호사교육원남원시 의총로 77. 3층 (왕정동)632-299355764
382남원한국요양보호사교육원남원시 광한북로 43-2 (하정동)626-223355763
391김제성모 요양보호사교육원김제시 동서로 222 (요촌동)545-988854392
401봉동간호학원 부설 요양보호사교육원완주군 봉동읍 봉동로 139261-112555326
411순창요양보호사교육원순창군 순창읍 순화로 25 (2층)652-800156038
421고창성모요양보호사교육원고창군 고창읍 중앙로 180, 3층563-003856436
431부안요양보호사교육원부안군 부안읍 석정로 241 (2층)582-622256315