Overview

Dataset statistics

Number of variables11
Number of observations212
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 KiB
Average record size in memory88.6 B

Variable types

Text7
Categorical4

Alerts

현원(종사자) is highly overall correlated with 정원(종사자)High correlation
정원(종사자) is highly overall correlated with 현원(종사자)High correlation
비고 is highly imbalanced (94.5%)Imbalance

Reproduction

Analysis started2024-03-14 03:18:09.845533
Analysis finished2024-03-14 03:18:10.946158
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

언번
Text

Distinct52
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:11.063457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.4622642
Min length1

Characters and Unicode

Total characters310
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

Unique26 ?
Unique (%)12.3%

Sample

1st row총계
2nd row소계
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
1 14
 
6.6%
2 14
 
6.6%
3 14
 
6.6%
4 14
 
6.6%
소계 14
 
6.6%
5 13
 
6.1%
6 13
 
6.1%
7 12
 
5.7%
8 11
 
5.2%
9 9
 
4.2%
Other values (42) 84
39.6%
2024-03-14T12:18:11.312918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 66
21.3%
2 45
14.5%
3 33
10.6%
4 33
10.6%
5 21
 
6.8%
6 19
 
6.1%
7 18
 
5.8%
8 17
 
5.5%
계 15
 
4.8%
9 15
 
4.8%
Other values (3) 28
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
90.3%
Other Letter 30
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 66
23.6%
2 45
16.1%
3 33
11.8%
4 33
11.8%
5 21
 
7.5%
6 19
 
6.8%
7 18
 
6.4%
8 17
 
6.1%
9 15
 
5.4%
0 13
 
4.6%
Other Letter
ValueCountFrequency (%)
계 15
50.0%
소 14
46.7%
총 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 280
90.3%
Hangul 30
 
9.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 66
23.6%
2 45
16.1%
3 33
11.8%
4 33
11.8%
5 21
 
7.5%
6 19
 
6.8%
7 18
 
6.4%
8 17
 
6.1%
9 15
 
5.4%
0 13
 
4.6%
Hangul
ValueCountFrequency (%)
계 15
50.0%
소 14
46.7%
총 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 280
90.3%
Hangul 30
 
9.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 66
23.6%
2 45
16.1%
3 33
11.8%
4 33
11.8%
5 21
 
7.5%
6 19
 
6.8%
7 18
 
6.4%
8 17
 
6.1%
9 15
 
5.4%
0 13
 
4.6%
Hangul
ValueCountFrequency (%)
계 15
50.0%
소 14
46.7%
총 1
 
3.3%

시설구분
Categorical

Distinct41
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
장애인주간보호시설
26 
여성폭력피해보호시설
23 
지역자활센터
18 
장애인보호작업장
17 
장애인수화통역센터
15 
Other values (36)
113 

Length

Max length16
Median length12
Mean length7.5377358
Min length3

Unique

Unique21 ?
Unique (%)9.9%

Sample

1st row전라북도
2nd row전주시
3rd row사회복지관
4th row사회복지관
5th row사회복지관

Common Values

ValueCountFrequency (%)
장애인주간보호시설 26
12.3%
여성폭력피해보호시설 23
10.8%
지역자활센터 18
 
8.5%
장애인보호작업장 17
 
8.0%
장애인수화통역센터 15
 
7.1%
장애인심부름센터 15
 
7.1%
사회복지관 14
 
6.6%
다문화가족지원센터 14
 
6.6%
노인복지관 13
 
6.1%
장애인복지관 12
 
5.7%
Other values (31) 45
21.2%

Length

2024-03-14T12:18:11.420085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장애인주간보호시설 26
12.0%
여성폭력피해보호시설 23
10.6%
지역자활센터 18
 
8.3%
장애인보호작업장 17
 
7.9%
장애인수화통역센터 15
 
6.9%
장애인심부름센터 15
 
6.9%
노인복지관 15
 
6.9%
사회복지관 14
 
6.5%
다문화가족지원센터 14
 
6.5%
장애인복지관 12
 
5.6%
Other values (30) 47
21.8%

시설명
Text

Distinct209
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:11.577318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length9.2311321
Min length1

Characters and Unicode

Total characters1957
Distinct characters195
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

Unique206 ?
Unique (%)97.2%

Sample

1st row197
2nd row50
3rd row전북종합사회복지관
4th row전주종합사회복지관
5th row학산종합사회복지관
ValueCountFrequency (%)
장애인복지관 11
 
4.3%
부설 7
 
2.8%
주간보호센터 6
 
2.4%
주간보호시설 3
 
1.2%
익산 3
 
1.2%
장수군다문화가족지원센터 2
 
0.8%
가정폭력상담소 2
 
0.8%
장수군 2
 
0.8%
9 2
 
0.8%
8 2
 
0.8%
Other values (213) 213
84.2%
2024-03-14T12:18:11.844043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 98
 
5.0%
터 87
 
4.4%
센 86
 
4.4%
복 61
 
3.1%
관 60
 
3.1%
인 58
 
3.0%
장 56
 
2.9%
주 51
 
2.6%
부 45
 
2.3%
군 43
 
2.2%
Other values (185) 1312
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1879
96.0%
Space Separator 42
 
2.1%
Decimal Number 26
 
1.3%
Uppercase Letter 8
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 98
 
5.2%
터 87
 
4.6%
센 86
 
4.6%
복 61
 
3.2%
관 60
 
3.2%
인 58
 
3.1%
장 56
 
3.0%
주 51
 
2.7%
부 45
 
2.4%
군 43
 
2.3%
Other values (169) 1234
65.7%
Decimal Number
ValueCountFrequency (%)
1 7
26.9%
2 4
15.4%
9 3
11.5%
4 3
11.5%
7 2
 
7.7%
5 2
 
7.7%
0 2
 
7.7%
8 2
 
7.7%
6 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1879
96.0%
Common 70
 
3.6%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 98
 
5.2%
터 87
 
4.6%
센 86
 
4.6%
복 61
 
3.2%
관 60
 
3.2%
인 58
 
3.1%
장 56
 
3.0%
주 51
 
2.7%
부 45
 
2.4%
군 43
 
2.3%
Other values (169) 1234
65.7%
Common
ValueCountFrequency (%)
42
60.0%
1 7
 
10.0%
2 4
 
5.7%
9 3
 
4.3%
4 3
 
4.3%
7 2
 
2.9%
5 2
 
2.9%
0 2
 
2.9%
8 2
 
2.9%
6 1
 
1.4%
Other values (2) 2
 
2.9%
Latin
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1879
96.0%
ASCII 78
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 98
 
5.2%
터 87
 
4.6%
센 86
 
4.6%
복 61
 
3.2%
관 60
 
3.2%
인 58
 
3.1%
장 56
 
3.0%
주 51
 
2.7%
부 45
 
2.4%
군 43
 
2.3%
Other values (169) 1234
65.7%
ASCII
ValueCountFrequency (%)
42
53.8%
1 7
 
9.0%
2 4
 
5.1%
9 3
 
3.8%
4 3
 
3.8%
7 2
 
2.6%
A 2
 
2.6%
5 2
 
2.6%
C 2
 
2.6%
W 2
 
2.6%
Other values (6) 9
 
11.5%

설치신고일
Text

Distinct182
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:12.084705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.2358491
Min length1

Characters and Unicode

Total characters1746
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)79.7%

Sample

1st row-
2nd row-
3rd row88.12.27
4th row92.12.28
5th row95.12.29
ValueCountFrequency (%)
16
 
6.7%
2001.07.01 5
 
2.1%
1 4
 
1.7%
09 4
 
1.7%
06 3
 
1.2%
2000.03.29 2
 
0.8%
05 2
 
0.8%
07 2
 
0.8%
6 2
 
0.8%
2011.11.01 2
 
0.8%
Other values (187) 198
82.5%
2024-03-14T12:18:12.424924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 394
22.6%
0 380
21.8%
1 272
15.6%
2 227
13.0%
9 110
 
6.3%
3 79
 
4.5%
7 55
 
3.2%
8 51
 
2.9%
5 48
 
2.7%
4 43
 
2.5%
Other values (5) 87
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1300
74.5%
Other Punctuation 394
 
22.6%
Space Separator 34
 
1.9%
Dash Punctuation 16
 
0.9%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 380
29.2%
1 272
20.9%
2 227
17.5%
9 110
 
8.5%
3 79
 
6.1%
7 55
 
4.2%
8 51
 
3.9%
5 48
 
3.7%
4 43
 
3.3%
6 35
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 394
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 394
22.6%
0 380
21.8%
1 272
15.6%
2 227
13.0%
9 110
 
6.3%
3 79
 
4.5%
7 55
 
3.2%
8 51
 
2.9%
5 48
 
2.7%
4 43
 
2.5%
Other values (5) 87
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 394
22.6%
0 380
21.8%
1 272
15.6%
2 227
13.0%
9 110
 
6.3%
3 79
 
4.5%
7 55
 
3.2%
8 51
 
2.9%
5 48
 
2.7%
4 43
 
2.5%
Other values (5) 87
 
5.0%

시설장
Text

Distinct179
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:12.731707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.8867925
Min length1

Characters and Unicode

Total characters612
Distinct characters134
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

Unique162 ?
Unique (%)76.4%

Sample

1st row-
2nd row-
3rd row문정훈
4th row강기오
5th row노영웅
ValueCountFrequency (%)
15
 
6.9%
진 3
 
1.4%
이춘섭 3
 
1.4%
이영재 3
 
1.4%
김 3
 
1.4%
전윤주 2
 
0.9%
이희수 2
 
0.9%
배인재 2
 
0.9%
박승택 2
 
0.9%
조영호 2
 
0.9%
Other values (171) 179
82.9%
2024-03-14T12:18:13.136878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 39
 
6.4%
이 27
 
4.4%
영 22
 
3.6%
정 19
 
3.1%
박 18
 
2.9%
진 16
 
2.6%
- 15
 
2.5%
희 14
 
2.3%
수 14
 
2.3%
성 13
 
2.1%
Other values (124) 415
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 585
95.6%
Dash Punctuation 15
 
2.5%
Space Separator 10
 
1.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 39
 
6.7%
이 27
 
4.6%
영 22
 
3.8%
정 19
 
3.2%
박 18
 
3.1%
진 16
 
2.7%
희 14
 
2.4%
수 14
 
2.4%
성 13
 
2.2%
기 11
 
1.9%
Other values (120) 392
67.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 585
95.6%
Common 27
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 39
 
6.7%
이 27
 
4.6%
영 22
 
3.8%
정 19
 
3.2%
박 18
 
3.1%
진 16
 
2.7%
희 14
 
2.4%
수 14
 
2.4%
성 13
 
2.2%
기 11
 
1.9%
Other values (120) 392
67.0%
Common
ValueCountFrequency (%)
- 15
55.6%
10
37.0%
( 1
 
3.7%
) 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 585
95.6%
ASCII 27
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 39
 
6.7%
이 27
 
4.6%
영 22
 
3.8%
정 19
 
3.2%
박 18
 
3.1%
진 16
 
2.7%
희 14
 
2.4%
수 14
 
2.4%
성 13
 
2.2%
기 11
 
1.9%
Other values (120) 392
67.0%
ASCII
ValueCountFrequency (%)
- 15
55.6%
10
37.0%
( 1
 
3.7%
) 1
 
3.7%

주 소
Text

Distinct176
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:13.387896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length14.589623
Min length1

Characters and Unicode

Total characters3093
Distinct characters201
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

Unique157 ?
Unique (%)74.1%

Sample

1st row-
2nd row-
3rd row전주시 완산구 흑석로 70
4th row전주시 완산구 덕적골2길 10
5th row전주시 완산구 모악로 4726-1
ValueCountFrequency (%)
전주시 50
 
6.8%
완산구 36
 
4.9%
익산시 24
 
3.3%
군산시 20
 
2.7%
15
 
2.1%
정읍시 14
 
1.9%
덕진구 12
 
1.6%
김제시 12
 
1.6%
임실읍 11
 
1.5%
남원시 11
 
1.5%
Other values (352) 526
72.0%
2024-03-14T12:18:13.747648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
522
 
16.9%
1 149
 
4.8%
시 138
 
4.5%
로 116
 
3.8%
2 103
 
3.3%
산 102
 
3.3%
- 89
 
2.9%
읍 79
 
2.6%
군 78
 
2.5%
길 76
 
2.5%
Other values (191) 1641
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1763
57.0%
Decimal Number 665
 
21.5%
Space Separator 522
 
16.9%
Dash Punctuation 89
 
2.9%
Open Punctuation 23
 
0.7%
Close Punctuation 23
 
0.7%
Other Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 138
 
7.8%
로 116
 
6.6%
산 102
 
5.8%
읍 79
 
4.5%
군 78
 
4.4%
길 76
 
4.3%
주 75
 
4.3%
전 58
 
3.3%
동 54
 
3.1%
구 51
 
2.9%
Other values (171) 936
53.1%
Decimal Number
ValueCountFrequency (%)
1 149
22.4%
2 103
15.5%
5 68
10.2%
4 66
9.9%
3 65
9.8%
7 57
 
8.6%
6 44
 
6.6%
8 43
 
6.5%
9 36
 
5.4%
0 34
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
A 1
25.0%
Y 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
＠ 2
50.0%
Space Separator
ValueCountFrequency (%)
522
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1763
57.0%
Common 1326
42.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 138
 
7.8%
로 116
 
6.6%
산 102
 
5.8%
읍 79
 
4.5%
군 78
 
4.4%
길 76
 
4.3%
주 75
 
4.3%
전 58
 
3.3%
동 54
 
3.1%
구 51
 
2.9%
Other values (171) 936
53.1%
Common
ValueCountFrequency (%)
522
39.4%
1 149
 
11.2%
2 103
 
7.8%
- 89
 
6.7%
5 68
 
5.1%
4 66
 
5.0%
3 65
 
4.9%
7 57
 
4.3%
6 44
 
3.3%
8 43
 
3.2%
Other values (6) 120
 
9.0%
Latin
ValueCountFrequency (%)
M 1
25.0%
A 1
25.0%
Y 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1763
57.0%
ASCII 1328
42.9%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
522
39.3%
1 149
 
11.2%
2 103
 
7.8%
- 89
 
6.7%
5 68
 
5.1%
4 66
 
5.0%
3 65
 
4.9%
7 57
 
4.3%
6 44
 
3.3%
8 43
 
3.2%
Other values (9) 122
 
9.2%
Hangul
ValueCountFrequency (%)
시 138
 
7.8%
로 116
 
6.6%
산 102
 
5.8%
읍 79
 
4.5%
군 78
 
4.4%
길 76
 
4.3%
주 75
 
4.3%
전 58
 
3.3%
동 54
 
3.1%
구 51
 
2.9%
Other values (171) 936
53.1%
None
ValueCountFrequency (%)
＠ 2
100.0%

정원(종사자)
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
65 
6
18 
4
16 
5
13 
-
13 
Other values (40)
87 

Length

Max length7
Median length3
Mean length3.0424528
Min length1

Unique

Unique20 ?
Unique (%)9.4%

Sample

1st row 1,511
2nd row-
3rd row 11
4th row 10
5th row 12

Common Values

ValueCountFrequency (%)
3 65
30.7%
6 18
 
8.5%
4 16
 
7.5%
5 13
 
6.1%
- 13
 
6.1%
7 10
 
4.7%
10 6
 
2.8%
2 5
 
2.4%
17 4
 
1.9%
11 4
 
1.9%
Other values (35) 58
27.4%

Length

2024-03-14T12:18:13.856997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 66
31.1%
6 18
 
8.5%
4 16
 
7.5%
15
 
7.1%
5 14
 
6.6%
7 13
 
6.1%
2 8
 
3.8%
11 7
 
3.3%
10 6
 
2.8%
17 5
 
2.4%
Other values (23) 44
20.8%

현원(종사자)
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
3
37 
4
27 
6
20 
5
20 
-
13 
Other values (41)
95 

Length

Max length7
Median length3
Mean length3.0283019
Min length1

Unique

Unique18 ?
Unique (%)8.5%

Sample

1st row 1,504
2nd row-
3rd row 11
4th row 10
5th row 12

Common Values

ValueCountFrequency (%)
3 37
17.5%
4 27
12.7%
6 20
 
9.4%
5 20
 
9.4%
- 13
 
6.1%
7 11
 
5.2%
1 7
 
3.3%
2 7
 
3.3%
10 5
 
2.4%
12 4
 
1.9%
Other values (36) 61
28.8%

Length

2024-03-14T12:18:13.956596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 38
17.9%
4 27
12.7%
5 23
10.8%
6 20
9.4%
15
 
7.1%
7 12
 
5.7%
1 10
 
4.7%
2 10
 
4.7%
9 5
 
2.4%
11 5
 
2.4%
Other values (23) 47
22.2%

월평균이용인원
Text

Distinct134
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:14.187038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.4858491
Min length1

Characters and Unicode

Total characters951
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)51.4%

Sample

1st row-
2nd row-
3rd row 7,220
4th row 11,000
5th row 9,160
ValueCountFrequency (%)
31
 
14.6%
20 8
 
3.8%
30 8
 
3.8%
100 6
 
2.8%
21 4
 
1.9%
14 4
 
1.9%
150 4
 
1.9%
80 3
 
1.4%
22 3
 
1.4%
42 3
 
1.4%
Other values (118) 138
65.1%
2024-03-14T12:18:14.554184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
39.9%
0 127
 
13.4%
1 93
 
9.8%
2 75
 
7.9%
3 45
 
4.7%
4 42
 
4.4%
5 36
 
3.8%
, 32
 
3.4%
- 31
 
3.3%
6 27
 
2.8%
Other values (3) 64
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 509
53.5%
Space Separator 379
39.9%
Other Punctuation 32
 
3.4%
Dash Punctuation 31
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 127
25.0%
1 93
18.3%
2 75
14.7%
3 45
 
8.8%
4 42
 
8.3%
5 36
 
7.1%
6 27
 
5.3%
9 25
 
4.9%
7 22
 
4.3%
8 17
 
3.3%
Space Separator
ValueCountFrequency (%)
379
100.0%
Other Punctuation
ValueCountFrequency (%)
, 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 951
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
379
39.9%
0 127
 
13.4%
1 93
 
9.8%
2 75
 
7.9%
3 45
 
4.7%
4 42
 
4.4%
5 36
 
3.8%
, 32
 
3.4%
- 31
 
3.3%
6 27
 
2.8%
Other values (3) 64
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
39.9%
0 127
 
13.4%
1 93
 
9.8%
2 75
 
7.9%
3 45
 
4.7%
4 42
 
4.4%
5 36
 
3.8%
, 32
 
3.4%
- 31
 
3.3%
6 27
 
2.8%
Other values (3) 64
 
6.7%

운영주체(법인명)
Text

Distinct158
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T12:18:14.778560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length14.5
Mean length9.3632075
Min length1

Characters and Unicode

Total characters1985
Distinct characters185
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique133 ?
Unique (%)62.7%

Sample

1st row-
2nd row-
3rd row 어린이재단
4th row 삼동회
5th row한기장복지재단
ValueCountFrequency (%)
15
 
5.5%
사 12
 
4.4%
삼동회 10
 
3.7%
개인 8
 
3.0%
사복 8
 
3.0%
사회복지법인 7
 
2.6%
한기장복지재단 7
 
2.6%
사단법인 5
 
1.8%
한국장애인부모회 4
 
1.5%
대한성공회유지재단 4
 
1.5%
Other values (159) 191
70.5%
2024-03-14T12:18:15.073399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 156
 
7.9%
사 113
 
5.7%
지 107
 
5.4%
인 85
 
4.3%
복 76
 
3.8%
69
 
3.5%
. 68
 
3.4%
전 58
 
2.9%
단 55
 
2.8%
장 54
 
2.7%
Other values (175) 1144
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1796
90.5%
Space Separator 69
 
3.5%
Other Punctuation 68
 
3.4%
Dash Punctuation 15
 
0.8%
Close Punctuation 13
 
0.7%
Uppercase Letter 12
 
0.6%
Open Punctuation 10
 
0.5%
Control 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 156
 
8.7%
사 113
 
6.3%
지 107
 
6.0%
인 85
 
4.7%
복 76
 
4.2%
전 58
 
3.2%
단 55
 
3.1%
장 54
 
3.0%
한 49
 
2.7%
재 46
 
2.6%
Other values (163) 997
55.5%
Uppercase Letter
ValueCountFrequency (%)
Y 3
25.0%
A 3
25.0%
C 3
25.0%
W 2
16.7%
M 1
 
8.3%
Space Separator
ValueCountFrequency (%)
69
100.0%
Other Punctuation
ValueCountFrequency (%)
. 68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1796
90.5%
Common 177
 
8.9%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 156
 
8.7%
사 113
 
6.3%
지 107
 
6.0%
인 85
 
4.7%
복 76
 
4.2%
전 58
 
3.2%
단 55
 
3.1%
장 54
 
3.0%
한 49
 
2.7%
재 46
 
2.6%
Other values (163) 997
55.5%
Common
ValueCountFrequency (%)
69
39.0%
. 68
38.4%
- 15
 
8.5%
) 13
 
7.3%
( 10
 
5.6%
1
 
0.6%
0 1
 
0.6%
Latin
ValueCountFrequency (%)
Y 3
25.0%
A 3
25.0%
C 3
25.0%
W 2
16.7%
M 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1796
90.5%
ASCII 189
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 156
 
8.7%
사 113
 
6.3%
지 107
 
6.0%
인 85
 
4.7%
복 76
 
4.2%
전 58
 
3.2%
단 55
 
3.1%
장 54
 
3.0%
한 49
 
2.7%
재 46
 
2.6%
Other values (163) 997
55.5%
ASCII
ValueCountFrequency (%)
69
36.5%
. 68
36.0%
- 15
 
7.9%
) 13
 
6.9%
( 10
 
5.3%
Y 3
 
1.6%
A 3
 
1.6%
C 3
 
1.6%
W 2
 
1.1%
M 1
 
0.5%
Other values (2) 2
 
1.1%

비고
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
-
210 
휴지중
 
1
재지정
 
1

Length

Max length3
Median length1
Mean length1.0188679
Min length1

Unique

Unique2 ?
Unique (%)0.9%

Sample

1st row-
2nd row-
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 210
99.1%
휴지중 1
 
0.5%
재지정 1
 
0.5%

Length

2024-03-14T12:18:15.187604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:18:15.272877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
210
99.1%
휴지중 1
 
0.5%
재지정 1
 
0.5%

Correlations

2024-03-14T12:18:15.328662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
언번시설구분정원(종사자)현원(종사자)비고
언번1.0000.5470.0000.0000.454
시설구분0.5471.0000.8940.8790.000
정원(종사자)0.0000.8941.0000.9980.000
현원(종사자)0.0000.8790.9981.0000.000
비고0.4540.0000.0000.0001.000
2024-03-14T12:18:15.406963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고시설구분현원(종사자)정원(종사자)
비고1.0000.0000.0000.000
시설구분0.0001.0000.3220.346
현원(종사자)0.0000.3221.0000.915
정원(종사자)0.0000.3460.9151.000
2024-03-14T12:18:15.488352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분정원(종사자)현원(종사자)비고
시설구분1.0000.3460.3220.000
정원(종사자)0.3461.0000.9150.000
현원(종사자)0.3220.9151.0000.000
비고0.0000.0000.0001.000

Missing values

2024-03-14T12:18:10.749795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:18:10.888223image/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

언번시설구분시설명설치신고일시설장주 소정원(종사자)현원(종사자)월평균이용인원운영주체(법인명)비고
0총계전라북도197---1,5111,504---
1소계전주시50--------
21사회복지관전북종합사회복지관88.12.27문정훈전주시 완산구 흑석로 7011117,220어린이재단-
32사회복지관전주종합사회복지관92.12.28강기오전주시 완산구 덕적골2길 10101011,000삼동회-
43사회복지관학산종합사회복지관95.12.29노영웅전주시 완산구 모악로 4726-112129,160한기장복지재단-
54사회복지관선너머종합사회복지관04.04.01정식수전주시 완산구 선너머로 5412129,000전주카톨릭사회복지회-
65사회복지관평화사회복지관92.01.13성동학전주시 완산구 덕적골2길 11778,400삼동회-
76노인복지관안골노인복지관1994.12.03이연숙전주시 덕진구 인후동1가764-5101020,000중부복지재단-
87노인복지관금암노인복지관2001.06.21서양열전주시 덕진구 금암동 1546-17714,000나누는사람들-
98노인복지관서원노인복지관2002.01.01조석주전주시 완산구 중화산동 555-1131324,000금산사복지원-
언번시설구분시설명설치신고일시설장주 소정원(종사자)현원(종사자)월평균이용인원운영주체(법인명)비고
202소계부안군9--------
2031장애인복지관부안군 장애인복지관06.5.25이춘섭부안군 부안읍 용암로 13415156,439사복.한기장복지재단-
2042장애인수화통역센터부안수화통역센터06.1.12문정복부안군 부안읍 소금샘길 2334193사.한국농아인협회전북협회부안군지회-
2053장애인심부름센터부안심부름센터05.7.6김명곤부안군 부안읍 남문안길1533207사.전북시각장애인연합회부안군지회-
2064장애인주간보호시설부안장애인복지관 부설 주간보호센터12.10.30이춘섭부안군 부안읍 용암로 134349사복. 한기장복지재단-
2075장애인근로사업장바다의향기2011.01.25조상완부안읍 봉두길 529938부신정회-
2086사회복지관부안종합사회복지관2006.02.23이춘섭부안군 부안읍 용암로134777,000한기장복지재단-
2097여성폭력피해보호시설부안성폭력상담소2006.5.12김정호부안읍 당산로 75-1335사)한국청소년치유협회-
2108지역자활센터부안지역자활센터2001.5.23장헌진부안군 행안면 월륜길555-부안제일교회-
2119다문화가족지원센터부안군다문화가족지원센터2009.02.25정흥귀부안군 부안읍 오리정로 892120100직영-