Overview

Dataset statistics

Number of variables13
Number of observations78
Missing cells18
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory105.7 B

Variable types

Text7
Categorical6

Dataset

Description장애인복지시설거주시설_안내20151
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202346

Alerts

전라북도 장애인복지시설(거주시설)현황 is highly overall correlated with Unnamed: 7 and 4 other fieldsHigh correlation
Unnamed: 7 is highly overall correlated with 전라북도 장애인복지시설(거주시설)현황 and 2 other fieldsHigh correlation
Unnamed: 8 is highly overall correlated with 전라북도 장애인복지시설(거주시설)현황 and 2 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with 전라북도 장애인복지시설(거주시설)현황 and 2 other fieldsHigh correlation
Unnamed: 11 is highly overall correlated with 전라북도 장애인복지시설(거주시설)현황High correlation
Unnamed: 12 is highly overall correlated with 전라북도 장애인복지시설(거주시설)현황High correlation
Unnamed: 0 has 2 (2.6%) missing valuesMissing
Unnamed: 2 has 2 (2.6%) missing valuesMissing
Unnamed: 3 has 3 (3.8%) missing valuesMissing
Unnamed: 4 has 3 (3.8%) missing valuesMissing
Unnamed: 5 has 3 (3.8%) missing valuesMissing
Unnamed: 6 has 3 (3.8%) missing valuesMissing
Unnamed: 10 has 2 (2.6%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:53:43.673643
Analysis finished2024-03-14 02:53:45.536082
Duration1.86 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Text

MISSING 

Distinct76
Distinct (%)100.0%
Missing2
Missing (%)2.6%
Memory size756.0 B
2024-03-14T11:53:45.697396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8815789
Min length1

Characters and Unicode

Total characters143
Distinct characters14
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

Unique76 ?
Unique (%)100.0%

Sample

1st row연번
2nd row총계
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
35 1
 
1.3%
38 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
50 1
 
1.3%
49 1
 
1.3%
48 1
 
1.3%
46 1
 
1.3%
Other values (66) 66
86.8%
2024-03-14T11:53:46.056338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 18
12.6%
1 18
12.6%
2 18
12.6%
4 18
12.6%
5 17
11.9%
6 17
11.9%
7 12
8.4%
9 7
 
4.9%
0 7
 
4.9%
8 7
 
4.9%
Other values (4) 4
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 139
97.2%
Other Letter 4
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 18
12.9%
1 18
12.9%
2 18
12.9%
4 18
12.9%
5 17
12.2%
6 17
12.2%
7 12
8.6%
9 7
 
5.0%
0 7
 
5.0%
8 7
 
5.0%
Other Letter
ValueCountFrequency (%)
총 1
25.0%
계 1
25.0%
연 1
25.0%
번 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 139
97.2%
Hangul 4
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3 18
12.9%
1 18
12.9%
2 18
12.9%
4 18
12.9%
5 17
12.2%
6 17
12.2%
7 12
8.6%
9 7
 
5.0%
0 7
 
5.0%
8 7
 
5.0%
Hangul
ValueCountFrequency (%)
총 1
25.0%
계 1
25.0%
연 1
25.0%
번 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139
97.2%
Hangul 4
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 18
12.9%
1 18
12.9%
2 18
12.9%
4 18
12.9%
5 17
12.2%
6 17
12.2%
7 12
8.6%
9 7
 
5.0%
0 7
 
5.0%
8 7
 
5.0%
Hangul
ValueCountFrequency (%)
총 1
25.0%
계 1
25.0%
연 1
25.0%
번 1
25.0%

전라북도 장애인복지시설(거주시설)현황
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
장애인거주시설
51 
장애인 공동생활가정
17 
장애인공동생활가정
 
4
<NA>
 
2
장애인 단기거주시설
 
2
Other values (2)
 
2

Length

Max length10
Median length7
Mean length7.6794872
Min length4

Unique

Unique2 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
장애인거주시설 51
65.4%
장애인 공동생활가정 17
 
21.8%
장애인공동생활가정 4
 
5.1%
<NA> 2
 
2.6%
장애인 단기거주시설 2
 
2.6%
시설구분 1
 
1.3%
전라북도 1
 
1.3%

Length

2024-03-14T11:53:46.202323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:53:46.361409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장애인거주시설 51
52.6%
장애인 19
 
19.6%
공동생활가정 17
 
17.5%
장애인공동생활가정 4
 
4.1%
na 2
 
2.1%
단기거주시설 2
 
2.1%
시설구분 1
 
1.0%
전라북도 1
 
1.0%

Unnamed: 2
Text

MISSING 

Distinct76
Distinct (%)100.0%
Missing2
Missing (%)2.6%
Memory size756.0 B
2024-03-14T11:53:46.585600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length5.6052632
Min length2

Characters and Unicode

Total characters426
Distinct characters141
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)100.0%

Sample

1st row시 설 일 반 현 황
2nd row시설명
3rd row전주자림원
4th row자림인애원
5th row동암재활원
ValueCountFrequency (%)
집 4
 
4.4%
자림공동생활가정 2
 
2.2%
새소망단기보호센터 1
 
1.1%
화평의 1
 
1.1%
지구촌마을 1
 
1.1%
둥지지공동생활가정 1
 
1.1%
부설공동생활가정 1
 
1.1%
남원장애인복지관 1
 
1.1%
편한세상 1
 
1.1%
평화의집 1
 
1.1%
Other values (76) 76
84.4%
2024-03-14T11:53:46.943846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
집 28
 
6.6%
의 24
 
5.6%
원 16
 
3.8%
동 15
 
3.5%
14
 
3.3%
활 10
 
2.3%
공 10
 
2.3%
자 10
 
2.3%
은 9
 
2.1%
가 9
 
2.1%
Other values (131) 281
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 406
95.3%
Space Separator 14
 
3.3%
Decimal Number 5
 
1.2%
Control 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
3.9%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
자 10
 
2.5%
은 9
 
2.2%
가 9
 
2.2%
나 8
 
2.0%
Other values (126) 267
65.8%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 2
40.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 406
95.3%
Common 20
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
3.9%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
자 10
 
2.5%
은 9
 
2.2%
가 9
 
2.2%
나 8
 
2.0%
Other values (126) 267
65.8%
Common
ValueCountFrequency (%)
14
70.0%
2 2
 
10.0%
1 2
 
10.0%
1
 
5.0%
3 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 406
95.3%
ASCII 20
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
집 28
 
6.9%
의 24
 
5.9%
원 16
 
3.9%
동 15
 
3.7%
활 10
 
2.5%
공 10
 
2.5%
자 10
 
2.5%
은 9
 
2.2%
가 9
 
2.2%
나 8
 
2.0%
Other values (126) 267
65.8%
ASCII
ValueCountFrequency (%)
14
70.0%
2 2
 
10.0%
1 2
 
10.0%
1
 
5.0%
3 1
 
5.0%

Unnamed: 3
Text

MISSING 

Distinct69
Distinct (%)92.0%
Missing3
Missing (%)3.8%
Memory size756.0 B
2024-03-14T11:53:47.204994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0266667
Min length5

Characters and Unicode

Total characters602
Distinct characters17
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

Unique65 ?
Unique (%)86.7%

Sample

1st row설치신고일
2nd row80.12.20
3rd row87.07.01
4th row90.09.03
5th row06.04.28
ValueCountFrequency (%)
02.03.27 3
 
4.0%
07.03.09 3
 
4.0%
08.07.31 2
 
2.7%
06.12.26 2
 
2.7%
14.12.24 1
 
1.3%
01.09.28 1
 
1.3%
03.10.14 1
 
1.3%
06,04,12 1
 
1.3%
08.07.30 1
 
1.3%
90.10.05 1
 
1.3%
Other values (59) 59
78.7%
2024-03-14T11:53:47.525073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 159
26.4%
. 147
24.4%
1 81
13.5%
2 55
 
9.1%
7 32
 
5.3%
3 26
 
4.3%
6 25
 
4.2%
9 19
 
3.2%
4 19
 
3.2%
8 17
 
2.8%
Other values (7) 22
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 448
74.4%
Other Punctuation 149
 
24.8%
Other Letter 5
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 159
35.5%
1 81
18.1%
2 55
 
12.3%
7 32
 
7.1%
3 26
 
5.8%
6 25
 
5.6%
9 19
 
4.2%
4 19
 
4.2%
8 17
 
3.8%
5 15
 
3.3%
Other Letter
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 147
98.7%
, 2
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 597
99.2%
Hangul 5
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 159
26.6%
. 147
24.6%
1 81
13.6%
2 55
 
9.2%
7 32
 
5.4%
3 26
 
4.4%
6 25
 
4.2%
9 19
 
3.2%
4 19
 
3.2%
8 17
 
2.8%
Other values (2) 17
 
2.8%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 597
99.2%
Hangul 5
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 159
26.6%
. 147
24.6%
1 81
13.6%
2 55
 
9.2%
7 32
 
5.4%
3 26
 
4.4%
6 25
 
4.2%
9 19
 
3.2%
4 19
 
3.2%
8 17
 
2.8%
Other values (2) 17
 
2.8%
Hangul
ValueCountFrequency (%)
설 1
20.0%
치 1
20.0%
신 1
20.0%
고 1
20.0%
일 1
20.0%

Unnamed: 4
Text

MISSING 

Distinct64
Distinct (%)85.3%
Missing3
Missing (%)3.8%
Memory size756.0 B
2024-03-14T11:53:47.739730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.12
Min length3

Characters and Unicode

Total characters234
Distinct characters83
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

Unique57 ?
Unique (%)76.0%

Sample

1st row시설장
2nd row박미숙
3rd row홍규식
4th row진용철
5th row박청자
ValueCountFrequency (%)
박미숙 4
 
5.1%
진숙선 3
 
3.8%
김혜자 3
 
3.8%
권영조 2
 
2.5%
원종훈 2
 
2.5%
손정녀 2
 
2.5%
이순자 2
 
2.5%
김성필 1
 
1.3%
최준식 1
 
1.3%
이용문 1
 
1.3%
Other values (58) 58
73.4%
2024-03-14T11:53:48.066517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
6.0%
박 12
 
5.1%
숙 12
 
5.1%
12
 
5.1%
정 8
 
3.4%
자 8
 
3.4%
순 7
 
3.0%
종 7
 
3.0%
이 6
 
2.6%
미 5
 
2.1%
Other values (73) 143
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
94.9%
Space Separator 12
 
5.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
6.3%
박 12
 
5.4%
숙 12
 
5.4%
정 8
 
3.6%
자 8
 
3.6%
순 7
 
3.2%
종 7
 
3.2%
이 6
 
2.7%
미 5
 
2.3%
진 5
 
2.3%
Other values (72) 138
62.2%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
94.9%
Common 12
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
6.3%
박 12
 
5.4%
숙 12
 
5.4%
정 8
 
3.6%
자 8
 
3.6%
순 7
 
3.2%
종 7
 
3.2%
이 6
 
2.7%
미 5
 
2.3%
진 5
 
2.3%
Other values (72) 138
62.2%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
94.9%
ASCII 12
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
6.3%
박 12
 
5.4%
숙 12
 
5.4%
정 8
 
3.6%
자 8
 
3.6%
순 7
 
3.2%
종 7
 
3.2%
이 6
 
2.7%
미 5
 
2.3%
진 5
 
2.3%
Other values (72) 138
62.2%
ASCII
ValueCountFrequency (%)
12
100.0%

Unnamed: 5
Text

MISSING 

Distinct72
Distinct (%)96.0%
Missing3
Missing (%)3.8%
Memory size756.0 B
2024-03-14T11:53:48.342953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length18.333333
Min length3

Characters and Unicode

Total characters1375
Distinct characters157
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)92.0%

Sample

1st row주 소
2nd row전주시 덕진구 번영로230-14(성덕동)
3rd row전주시 덕진구 번영로230-14(성덕동)
4th row전주시 완산구 천잠로275(효자동3가)
5th row전주시 완산구 우림로595-32(용복동)
ValueCountFrequency (%)
익산시 15
 
5.2%
전주시 14
 
4.8%
정읍시 9
 
3.1%
완주군 9
 
3.1%
전북 9
 
3.1%
군산시 8
 
2.8%
덕진구 7
 
2.4%
완산구 7
 
2.4%
김제시 4
 
1.4%
남원시 4
 
1.4%
Other values (177) 204
70.3%
2024-03-14T11:53:48.835816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
218
 
15.9%
1 79
 
5.7%
시 55
 
4.0%
길 43
 
3.1%
산 42
 
3.1%
- 41
 
3.0%
5 38
 
2.8%
2 37
 
2.7%
0 36
 
2.6%
면 34
 
2.5%
Other values (147) 752
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 738
53.7%
Decimal Number 330
24.0%
Space Separator 218
 
15.9%
Dash Punctuation 41
 
3.0%
Close Punctuation 16
 
1.2%
Open Punctuation 16
 
1.2%
Other Punctuation 11
 
0.8%
Lowercase Letter 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.8%
산 42
 
5.7%
면 34
 
4.6%
주 29
 
3.9%
로 29
 
3.9%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
완 16
 
2.2%
Other values (129) 415
56.2%
Decimal Number
ValueCountFrequency (%)
1 79
23.9%
5 38
11.5%
2 37
11.2%
0 36
10.9%
4 28
 
8.5%
3 27
 
8.2%
6 27
 
8.2%
7 23
 
7.0%
8 19
 
5.8%
9 16
 
4.8%
Other Punctuation
ValueCountFrequency (%)
@ 6
54.5%
, 3
27.3%
/ 2
 
18.2%
Space Separator
ValueCountFrequency (%)
218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 738
53.7%
Common 632
46.0%
Latin 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.8%
산 42
 
5.7%
면 34
 
4.6%
주 29
 
3.9%
로 29
 
3.9%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
완 16
 
2.2%
Other values (129) 415
56.2%
Common
ValueCountFrequency (%)
218
34.5%
1 79
 
12.5%
- 41
 
6.5%
5 38
 
6.0%
2 37
 
5.9%
0 36
 
5.7%
4 28
 
4.4%
3 27
 
4.3%
6 27
 
4.3%
7 23
 
3.6%
Other values (7) 78
 
12.3%
Latin
ValueCountFrequency (%)
a 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 738
53.7%
ASCII 637
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
218
34.2%
1 79
 
12.4%
- 41
 
6.4%
5 38
 
6.0%
2 37
 
5.8%
0 36
 
5.7%
4 28
 
4.4%
3 27
 
4.2%
6 27
 
4.2%
7 23
 
3.6%
Other values (8) 83
 
13.0%
Hangul
ValueCountFrequency (%)
시 55
 
7.5%
길 43
 
5.8%
산 42
 
5.7%
면 34
 
4.6%
주 29
 
3.9%
로 29
 
3.9%
군 28
 
3.8%
전 24
 
3.3%
동 23
 
3.1%
완 16
 
2.2%
Other values (129) 415
56.2%

Unnamed: 6
Text

MISSING 

Distinct73
Distinct (%)97.3%
Missing3
Missing (%)3.8%
Memory size756.0 B
2024-03-14T11:53:49.056786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.1333333
Min length4

Characters and Unicode

Total characters610
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)94.7%

Sample

1st row전화번호
2nd row223-1568
3rd row276-1568
4th row222-4444
5th row222-2786
ValueCountFrequency (%)
536-1451 2
 
2.7%
452-0911 2
 
2.7%
263-4352 1
 
1.3%
535-0737 1
 
1.3%
547-9464 1
 
1.3%
542-9466 1
 
1.3%
542-5844 1
 
1.3%
636-6204 1
 
1.3%
536-1453 1
 
1.3%
635-1546 1
 
1.3%
Other values (63) 63
84.0%
2024-03-14T11:53:49.405874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 76
12.5%
- 76
12.5%
3 74
12.1%
4 66
10.8%
2 61
10.0%
1 54
8.9%
6 51
8.4%
8 47
7.7%
0 34
5.6%
9 34
5.6%
Other values (6) 37
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 528
86.6%
Dash Punctuation 76
 
12.5%
Other Letter 4
 
0.7%
Math Symbol 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 76
14.4%
3 74
14.0%
4 66
12.5%
2 61
11.6%
1 54
10.2%
6 51
9.7%
8 47
8.9%
0 34
6.4%
9 34
6.4%
7 31
5.9%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 606
99.3%
Hangul 4
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
5 76
12.5%
- 76
12.5%
3 74
12.2%
4 66
10.9%
2 61
10.1%
1 54
8.9%
6 51
8.4%
8 47
7.8%
0 34
5.6%
9 34
5.6%
Other values (2) 33
5.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 606
99.3%
Hangul 4
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 76
12.5%
- 76
12.5%
3 74
12.2%
4 66
10.9%
2 61
10.1%
1 54
8.9%
6 51
8.4%
8 47
7.8%
0 34
5.6%
9 34
5.6%
Other values (2) 33
5.4%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 7
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size756.0 B
1
20 
26
5 
22
 
4
8
 
4
10
 
3
Other values (24)
42 

Length

Max length7
Median length5.5
Mean length3.5128205
Min length2

Unique

Unique11 ?
Unique (%)14.1%

Sample

1st row<NA>
2nd row종사자
3rd row정원
4th row 1,001
5th row 40

Common Values

ValueCountFrequency (%)
1 20
25.6%
26 5
 
6.4%
22 4
 
5.1%
8 4
 
5.1%
10 3
 
3.8%
9 3
 
3.8%
6 3
 
3.8%
21 3
 
3.8%
18 3
 
3.8%
7 3
 
3.8%
Other values (19) 27
34.6%

Length

2024-03-14T11:53:49.519190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 20
25.6%
26 5
 
6.4%
22 4
 
5.1%
8 4
 
5.1%
10 3
 
3.8%
9 3
 
3.8%
6 3
 
3.8%
21 3
 
3.8%
18 3
 
3.8%
7 3
 
3.8%
Other values (19) 27
34.6%

Unnamed: 8
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size756.0 B
1
19 
25
6 
22
 
4
10
 
4
18
 
3
Other values (25)
42 

Length

Max length5
Median length4
Mean length3.5
Min length2

Unique

Unique11 ?
Unique (%)14.1%

Sample

1st row<NA>
2nd row<NA>
3rd row현원
4th row 946
5th row 29

Common Values

ValueCountFrequency (%)
1 19
24.4%
25 6
 
7.7%
22 4
 
5.1%
10 4
 
5.1%
18 3
 
3.8%
8 3
 
3.8%
4 3
 
3.8%
6 3
 
3.8%
16 2
 
2.6%
- 2
 
2.6%
Other values (20) 29
37.2%

Length

2024-03-14T11:53:49.622253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 19
24.4%
25 6
 
7.7%
22 4
 
5.1%
10 4
 
5.1%
18 3
 
3.8%
8 3
 
3.8%
4 3
 
3.8%
6 3
 
3.8%
24 2
 
2.6%
32 2
 
2.6%
Other values (20) 29
37.2%

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
4
16 
40
7 
50
6 
30
5 
20
 
4
Other values (27)
40 

Length

Max length7
Median length4
Mean length3.7435897
Min length2

Unique

Unique17 ?
Unique (%)21.8%

Sample

1st row<NA>
2nd row생활인
3rd row정원
4th row 2,239
5th row 100

Common Values

ValueCountFrequency (%)
4 16
20.5%
40 7
 
9.0%
50 6
 
7.7%
30 5
 
6.4%
20 4
 
5.1%
15 3
 
3.8%
29 3
 
3.8%
10 3
 
3.8%
60 2
 
2.6%
9 2
 
2.6%
Other values (22) 27
34.6%

Length

2024-03-14T11:53:49.731397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 16
20.5%
40 7
 
9.0%
50 6
 
7.7%
30 5
 
6.4%
20 4
 
5.1%
15 3
 
3.8%
29 3
 
3.8%
10 3
 
3.8%
25 2
 
2.6%
2
 
2.6%
Other values (22) 27
34.6%

Unnamed: 10
Text

MISSING 

Distinct43
Distinct (%)56.6%
Missing2
Missing (%)2.6%
Memory size756.0 B
2024-03-14T11:53:49.855066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.6052632
Min length1

Characters and Unicode

Total characters274
Distinct characters15
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

Unique22 ?
Unique (%)28.9%

Sample

1st row현원
2nd row 1,950
3rd row 72
4th row 67
5th row 51
ValueCountFrequency (%)
4 11
 
14.5%
30 3
 
3.9%
3 3
 
3.9%
2 3
 
3.9%
28 3
 
3.9%
34 3
 
3.9%
10 2
 
2.6%
50 2
 
2.6%
48 2
 
2.6%
29 2
 
2.6%
Other values (32) 42
55.3%
2024-03-14T11:53:50.108743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
52.6%
4 25
 
9.1%
3 21
 
7.7%
2 18
 
6.6%
0 13
 
4.7%
8 11
 
4.0%
1 11
 
4.0%
5 10
 
3.6%
7 7
 
2.6%
9 5
 
1.8%
Other values (5) 9
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 144
52.6%
Decimal Number 125
45.6%
Dash Punctuation 2
 
0.7%
Other Letter 2
 
0.7%
Other Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 25
20.0%
3 21
16.8%
2 18
14.4%
0 13
10.4%
8 11
8.8%
1 11
8.8%
5 10
 
8.0%
7 7
 
5.6%
9 5
 
4.0%
6 4
 
3.2%
Other Letter
ValueCountFrequency (%)
현 1
50.0%
원 1
50.0%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 272
99.3%
Hangul 2
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
144
52.9%
4 25
 
9.2%
3 21
 
7.7%
2 18
 
6.6%
0 13
 
4.8%
8 11
 
4.0%
1 11
 
4.0%
5 10
 
3.7%
7 7
 
2.6%
9 5
 
1.8%
Other values (3) 7
 
2.6%
Hangul
ValueCountFrequency (%)
현 1
50.0%
원 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 272
99.3%
Hangul 2
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
52.9%
4 25
 
9.2%
3 21
 
7.7%
2 18
 
6.6%
0 13
 
4.8%
8 11
 
4.0%
1 11
 
4.0%
5 10
 
3.7%
7 7
 
2.6%
9 5
 
1.8%
Other values (3) 7
 
2.6%
Hangul
ValueCountFrequency (%)
현 1
50.0%
원 1
50.0%

Unnamed: 11
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
개인
22 
사복)중도원
6 
사복)자림복지재단
5 
사복)자애복지재단
 
3
사복)창혜복지재단
 
3
Other values (29)
39 

Length

Max length17
Median length15
Mean length7.1794872
Min length2

Unique

Unique21 ?
Unique (%)26.9%

Sample

1st row2015. 1월말 현재
2nd row운영주체(법인명)
3rd row<NA>
4th row<NA>
5th row사복)자림복지재단

Common Values

ValueCountFrequency (%)
개인 22
28.2%
사복)중도원 6
 
7.7%
사복)자림복지재단 5
 
6.4%
사복)자애복지재단 3
 
3.8%
사복)창혜복지재단 3
 
3.8%
사복)해오름복지재단 3
 
3.8%
사복)전주가톨릭사회복지회 3
 
3.8%
사복)국제원 2
 
2.6%
<NA> 2
 
2.6%
사복)어깨동무복지재단 2
 
2.6%
Other values (24) 27
34.6%

Length

2024-03-14T11:53:50.223813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개인 22
26.5%
사복)중도원 6
 
7.2%
사복)자림복지재단 5
 
6.0%
사복)자애복지재단 3
 
3.6%
사복)창혜복지재단 3
 
3.6%
사복)해오름복지재단 3
 
3.6%
사복)전주가톨릭사회복지회 3
 
3.6%
사복)전주카톨릭사회복지회 2
 
2.4%
사복)한기장복지재단 2
 
2.4%
사복)전북보성원 2
 
2.4%
Other values (29) 32
38.6%

Unnamed: 12
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size756.0 B
지적
27 
<NA>
24 
중증
9 
지적
5 
지체
5 
Other values (7)
8 

Length

Max length20
Median length2
Mean length3.2179487
Min length2

Unique

Unique6 ?
Unique (%)7.7%

Sample

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

Common Values

ValueCountFrequency (%)
지적 27
34.6%
<NA> 24
30.8%
중증 9
 
11.5%
지적 5
 
6.4%
지체 5
 
6.4%
중증실비 2
 
2.6%
비고 1
 
1.3%
지적(여) 1
 
1.3%
휴지 중 14.6.18~15.5.31 1
 
1.3%
시각 1
 
1.3%
Other values (2) 2
 
2.6%

Length

2024-03-14T11:53:50.332257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지적 32
39.0%
na 24
29.3%
중증 9
 
11.0%
지체 5
 
6.1%
중증실비 2
 
2.4%
휴지 2
 
2.4%
중 2
 
2.4%
비고 1
 
1.2%
지적(여 1
 
1.2%
14.6.18~15.5.31 1
 
1.2%
Other values (3) 3
 
3.7%

Correlations

2024-03-14T11:53:50.411443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 0전라북도 장애인복지시설(거주시설)현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
Unnamed: 01.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전라북도 장애인복지시설(거주시설)현황1.0001.0001.0000.0000.9461.0000.9720.9640.8850.9640.9240.9160.913
Unnamed: 21.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 31.0000.0001.0001.0000.9750.9940.9820.9450.9670.9790.9690.9850.000
Unnamed: 41.0000.9461.0000.9751.0000.9901.0000.9550.9730.9700.9631.0000.000
Unnamed: 51.0001.0001.0000.9940.9901.0000.9920.9770.0000.0000.4811.0000.884
Unnamed: 61.0000.9721.0000.9821.0000.9921.0000.9810.9950.9870.9961.0001.000
Unnamed: 71.0000.9641.0000.9450.9550.9770.9811.0000.9740.9720.9760.7410.804
Unnamed: 81.0000.8851.0000.9670.9730.0000.9950.9741.0000.9710.9770.0000.692
Unnamed: 91.0000.9641.0000.9790.9700.0000.9870.9720.9711.0000.9820.6520.000
Unnamed: 101.0000.9241.0000.9690.9630.4810.9960.9760.9770.9821.0000.0000.753
Unnamed: 111.0000.9161.0000.9851.0001.0001.0000.7410.0000.6520.0001.0000.715
Unnamed: 121.0000.9131.0000.0000.0000.8841.0000.8040.6920.0000.7530.7151.000
2024-03-14T11:53:50.534497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 7Unnamed: 8Unnamed: 12Unnamed: 9전라북도 장애인복지시설(거주시설)현황Unnamed: 11
Unnamed: 71.0000.6800.3480.6470.6930.225
Unnamed: 80.6801.0000.2370.6510.5490.000
Unnamed: 120.3480.2371.0000.0000.7920.265
Unnamed: 90.6470.6510.0001.0000.6170.165
전라북도 장애인복지시설(거주시설)현황0.6930.5490.7920.6171.0000.568
Unnamed: 110.2250.0000.2650.1650.5681.000
2024-03-14T11:53:50.679994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전라북도 장애인복지시설(거주시설)현황Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 11Unnamed: 12
전라북도 장애인복지시설(거주시설)현황1.0000.6930.5490.6170.5680.792
Unnamed: 70.6931.0000.6800.6470.2250.348
Unnamed: 80.5490.6801.0000.6510.0000.237
Unnamed: 90.6170.6470.6511.0000.1650.000
Unnamed: 110.5680.2250.0000.1651.0000.265
Unnamed: 120.7920.3480.2370.0000.2651.000

Missing values

2024-03-14T11:53:45.147316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:53:45.281894image/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.
2024-03-14T11:53:45.413999image/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

Unnamed: 0전라북도 장애인복지시설(거주시설)현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2015. 1월말 현재<NA>
1연번시설구분시 설 일 반 현 황<NA><NA><NA><NA>종사자<NA>생활인<NA>운영주체(법인명)비고
2<NA><NA>시설명설치신고일시설장주 소전화번호정원현원정원현원<NA><NA>
3총계전라북도<NA><NA><NA><NA><NA>1,0019462,2391,950<NA><NA>
41장애인거주시설전주자림원80.12.20박미숙전주시 덕진구 번영로230-14(성덕동)223-1568402910072사복)자림복지재단지적
52장애인거주시설자림인애원87.07.01홍규식전주시 덕진구 번영로230-14(성덕동)276-156840407267사복)자림복지재단중증
63장애인거주시설동암재활원90.09.03진용철전주시 완산구 천잠로275(효자동3가)222-444420177051사복)동암지체
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96장애인 단기거주시설한마음단기보호센터02.03.27김학권전주시 완산구 계룡산길 44-8223-4935441010사)전북장애인부모회<NA>
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6865장애인거주시설흰마실08.04.22박주종진안군 백운면 윤기길 4-35433-220021213030사복)낮은자리지적
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7168장애인거주시설만나의집06.05.08김태곤장수군 번암면 성암길 458-16352-3688----개인휴지 중 10.6.~16.1.16
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7673장애인거주시설로뎀나무10.03.15전정섭순창군 금과면 방계로 33-2652-2393862925개인지적
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