Overview

Dataset statistics

Number of variables8
Number of observations328
Missing cells623
Missing cells (%)23.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.6 KiB
Average record size in memory64.4 B

Variable types

Categorical1
Text7

Dataset

Description영도구 관내 사회복지관 프로그램 현황(복지관명, 사업명, 사업내용 등)에 대한 목록으로 영도구 관내 복지관명, 사업명, 사업 내용 등의 항목을 제공하고 있습니다.
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/15054239/fileData.do

Alerts

인원(명) has 5 (1.5%) missing valuesMissing
이용료(원) has 292 (89.0%) missing valuesMissing
비고 has 325 (99.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:28:27.566733
Analysis finished2023-12-12 05:28:28.509443
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사회복지관명
Categorical

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
영도구종합사회복지관
76 
동삼종합사회복지관
69 
상리종합사회복지관
65 
와치종합사회복지관
65 
절영종합사회복지관
53 

Length

Max length10
Median length9
Mean length9.2317073
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영도구종합사회복지관
2nd row영도구종합사회복지관
3rd row영도구종합사회복지관
4th row영도구종합사회복지관
5th row영도구종합사회복지관

Common Values

ValueCountFrequency (%)
영도구종합사회복지관 76
23.2%
동삼종합사회복지관 69
21.0%
상리종합사회복지관 65
19.8%
와치종합사회복지관 65
19.8%
절영종합사회복지관 53
16.2%

Length

2023-12-12T14:28:28.590203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:28:28.723804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영도구종합사회복지관 76
23.2%
동삼종합사회복지관 69
21.0%
상리종합사회복지관 65
19.8%
와치종합사회복지관 65
19.8%
절영종합사회복지관 53
16.2%

사업명
Text

Distinct303
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T14:28:28.991542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length9.7835366
Min length2

Characters and Unicode

Total characters3209
Distinct characters340
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)86.6%

Sample

1st row사례개발홍보
2nd row사례접수
3rd row상담(전화,방문,서신)
4th row스크리닝 회의
5th row타기관 의뢰
ValueCountFrequency (%)
및 15
 
2.5%
사업 12
 
2.0%
지원 7
 
1.2%
관리 7
 
1.2%
경로식당 6
 
1.0%
지역주민 6
 
1.0%
프로그램 6
 
1.0%
사례관리 6
 
1.0%
네트워크 5
 
0.8%
청소년 5
 
0.8%
Other values (446) 520
87.4%
2023-12-12T14:28:29.784978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
268
 
8.4%
사 168
 
5.2%
지 108
 
3.4%
원 77
 
2.4%
업 70
 
2.2%
' 54
 
1.7%
리 52
 
1.6%
스 44
 
1.4%
비 42
 
1.3%
자 41
 
1.3%
Other values (330) 2285
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2766
86.2%
Space Separator 268
 
8.4%
Other Punctuation 65
 
2.0%
Uppercase Letter 40
 
1.2%
Lowercase Letter 17
 
0.5%
Open Punctuation 16
 
0.5%
Close Punctuation 16
 
0.5%
Final Punctuation 8
 
0.2%
Initial Punctuation 8
 
0.2%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 168
 
6.1%
지 108
 
3.9%
원 77
 
2.8%
업 70
 
2.5%
리 52
 
1.9%
스 44
 
1.6%
비 42
 
1.5%
자 41
 
1.5%
서 41
 
1.5%
인 38
 
1.4%
Other values (298) 2085
75.4%
Uppercase Letter
ValueCountFrequency (%)
C 10
25.0%
B 10
25.0%
M 9
22.5%
P 3
 
7.5%
G 2
 
5.0%
J 2
 
5.0%
R 2
 
5.0%
Y 1
 
2.5%
U 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
e 4
23.5%
o 3
17.6%
f 2
11.8%
b 2
11.8%
r 2
11.8%
u 1
 
5.9%
n 1
 
5.9%
i 1
 
5.9%
t 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
' 54
83.1%
, 4
 
6.2%
" 4
 
6.2%
. 2
 
3.1%
· 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 8
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2765
86.2%
Common 386
 
12.0%
Latin 57
 
1.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 168
 
6.1%
지 108
 
3.9%
원 77
 
2.8%
업 70
 
2.5%
리 52
 
1.9%
스 44
 
1.6%
비 42
 
1.5%
자 41
 
1.5%
서 41
 
1.5%
인 38
 
1.4%
Other values (297) 2084
75.4%
Latin
ValueCountFrequency (%)
C 10
17.5%
B 10
17.5%
M 9
15.8%
e 4
 
7.0%
P 3
 
5.3%
o 3
 
5.3%
G 2
 
3.5%
f 2
 
3.5%
J 2
 
3.5%
b 2
 
3.5%
Other values (8) 10
17.5%
Common
ValueCountFrequency (%)
268
69.4%
' 54
 
14.0%
( 16
 
4.1%
) 16
 
4.1%
’ 8
 
2.1%
‘ 8
 
2.1%
, 4
 
1.0%
" 4
 
1.0%
1 2
 
0.5%
. 2
 
0.5%
Other values (4) 4
 
1.0%
Han
ValueCountFrequency (%)
溫 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2765
86.2%
ASCII 426
 
13.3%
Punctuation 16
 
0.5%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
268
62.9%
' 54
 
12.7%
( 16
 
3.8%
) 16
 
3.8%
C 10
 
2.3%
B 10
 
2.3%
M 9
 
2.1%
e 4
 
0.9%
, 4
 
0.9%
" 4
 
0.9%
Other values (19) 31
 
7.3%
Hangul
ValueCountFrequency (%)
사 168
 
6.1%
지 108
 
3.9%
원 77
 
2.8%
업 70
 
2.5%
리 52
 
1.9%
스 44
 
1.6%
비 42
 
1.5%
자 41
 
1.5%
서 41
 
1.5%
인 38
 
1.4%
Other values (297) 2084
75.4%
Punctuation
ValueCountFrequency (%)
’ 8
50.0%
‘ 8
50.0%
CJK
ValueCountFrequency (%)
溫 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

사업내용
Text

Distinct325
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T14:28:30.165868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length89
Median length61
Mean length35.972561
Min length9

Characters and Unicode

Total characters11799
Distinct characters440
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

Unique322 ?
Unique (%)98.2%

Sample

1st row요보호대상자를 수시로 발굴하기 위한 공문 등 홍보활동
2nd row지역사회의 개인, 단체, 기관에서 요보호대상자의 발견시 접수를 통한 지원체계마련
3rd row사례발굴에 따른 요보호대상자의 욕구가 무엇인지에 대한 파악을 위한 초기상담
4th row사례접수된 요보호대상자가 일반 프로그램이나 단순 재가대상자인지에 대해 심의
5th row복지관 대상자로 부적합할 경우 적합한 타기관으로 의뢰
ValueCountFrequency (%)
및 131
 
4.7%
지원 52
 
1.9%
등 50
 
1.8%
내 45
 
1.6%
지역 39
 
1.4%
제공 36
 
1.3%
위한 36
 
1.3%
통한 29
 
1.0%
대상으로 29
 
1.0%
저소득 25
 
0.9%
Other values (1376) 2325
83.1%
2023-12-12T14:28:30.783497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2509
 
21.3%
지 313
 
2.7%
, 209
 
1.8%
한 189
 
1.6%
사 188
 
1.6%
을 185
 
1.6%
대 165
 
1.4%
원 164
 
1.4%
상 145
 
1.2%
의 145
 
1.2%
Other values (430) 7587
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8788
74.5%
Space Separator 2509
 
21.3%
Other Punctuation 295
 
2.5%
Decimal Number 90
 
0.8%
Uppercase Letter 33
 
0.3%
Open Punctuation 29
 
0.2%
Close Punctuation 29
 
0.2%
Lowercase Letter 20
 
0.2%
Math Symbol 5
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 313
 
3.6%
한 189
 
2.2%
사 188
 
2.1%
을 185
 
2.1%
대 165
 
1.9%
원 164
 
1.9%
상 145
 
1.6%
의 145
 
1.6%
및 131
 
1.5%
자 130
 
1.5%
Other values (388) 7033
80.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
25.0%
r 2
 
10.0%
t 2
 
10.0%
n 2
 
10.0%
f 2
 
10.0%
g 1
 
5.0%
p 1
 
5.0%
i 1
 
5.0%
u 1
 
5.0%
o 1
 
5.0%
Other values (2) 2
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 26
28.9%
5 17
18.9%
6 14
15.6%
2 14
15.6%
3 6
 
6.7%
0 5
 
5.6%
8 3
 
3.3%
7 2
 
2.2%
9 2
 
2.2%
4 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
C 9
27.3%
M 9
27.3%
B 8
24.2%
T 2
 
6.1%
R 2
 
6.1%
V 1
 
3.0%
E 1
 
3.0%
I 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 209
70.8%
. 67
 
22.7%
/ 6
 
2.0%
· 5
 
1.7%
? 5
 
1.7%
' 2
 
0.7%
: 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2509
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8788
74.5%
Common 2958
 
25.1%
Latin 53
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 313
 
3.6%
한 189
 
2.2%
사 188
 
2.1%
을 185
 
2.1%
대 165
 
1.9%
원 164
 
1.9%
상 145
 
1.6%
의 145
 
1.6%
및 131
 
1.5%
자 130
 
1.5%
Other values (388) 7033
80.0%
Common
ValueCountFrequency (%)
2509
84.8%
, 209
 
7.1%
. 67
 
2.3%
( 29
 
1.0%
) 29
 
1.0%
1 26
 
0.9%
5 17
 
0.6%
6 14
 
0.5%
2 14
 
0.5%
3 6
 
0.2%
Other values (12) 38
 
1.3%
Latin
ValueCountFrequency (%)
C 9
17.0%
M 9
17.0%
B 8
15.1%
e 5
9.4%
r 2
 
3.8%
T 2
 
3.8%
t 2
 
3.8%
n 2
 
3.8%
f 2
 
3.8%
R 2
 
3.8%
Other values (10) 10
18.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8788
74.5%
ASCII 3006
 
25.5%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2509
83.5%
, 209
 
7.0%
. 67
 
2.2%
( 29
 
1.0%
) 29
 
1.0%
1 26
 
0.9%
5 17
 
0.6%
6 14
 
0.5%
2 14
 
0.5%
C 9
 
0.3%
Other values (31) 83
 
2.8%
Hangul
ValueCountFrequency (%)
지 313
 
3.6%
한 189
 
2.2%
사 188
 
2.1%
을 185
 
2.1%
대 165
 
1.9%
원 164
 
1.9%
상 145
 
1.6%
의 145
 
1.6%
및 131
 
1.5%
자 130
 
1.5%
Other values (388) 7033
80.0%
None
ValueCountFrequency (%)
· 5
100.0%

대상/명
Text

Distinct221
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T14:28:31.098876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length44
Mean length10.25
Min length2

Characters and Unicode

Total characters3362
Distinct characters226
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

Unique185 ?
Unique (%)56.4%

Sample

1st row지역주민
2nd row지역주민
3rd row지역주민
4th row지역주민
5th row지역주민
ValueCountFrequency (%)
지역주민 62
 
7.8%
내 31
 
3.9%
지역 29
 
3.7%
이상 27
 
3.4%
65세 24
 
3.0%
만 19
 
2.4%
어르신 16
 
2.0%
저소득 15
 
1.9%
및 15
 
1.9%
노인 13
 
1.6%
Other values (312) 543
68.4%
2023-12-12T14:28:31.572071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
499
 
14.8%
지 185
 
5.5%
역 142
 
4.2%
주 131
 
3.9%
민 118
 
3.5%
상 72
 
2.1%
/ 69
 
2.1%
0 62
 
1.8%
자 61
 
1.8%
이 57
 
1.7%
Other values (216) 1966
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2440
72.6%
Space Separator 499
 
14.8%
Decimal Number 271
 
8.1%
Other Punctuation 90
 
2.7%
Uppercase Letter 39
 
1.2%
Math Symbol 9
 
0.3%
Close Punctuation 7
 
0.2%
Open Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 185
 
7.6%
역 142
 
5.8%
주 131
 
5.4%
민 118
 
4.8%
상 72
 
3.0%
자 61
 
2.5%
이 57
 
2.3%
인 57
 
2.3%
소 56
 
2.3%
세 52
 
2.1%
Other values (194) 1509
61.8%
Decimal Number
ValueCountFrequency (%)
0 62
22.9%
5 54
19.9%
6 44
16.2%
2 38
14.0%
1 28
10.3%
3 16
 
5.9%
4 14
 
5.2%
8 7
 
2.6%
7 7
 
2.6%
9 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
/ 69
76.7%
, 15
 
16.7%
· 3
 
3.3%
. 2
 
2.2%
% 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B 13
33.3%
M 13
33.3%
C 13
33.3%
Space Separator
ValueCountFrequency (%)
499
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2440
72.6%
Common 883
 
26.3%
Latin 39
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 185
 
7.6%
역 142
 
5.8%
주 131
 
5.4%
민 118
 
4.8%
상 72
 
3.0%
자 61
 
2.5%
이 57
 
2.3%
인 57
 
2.3%
소 56
 
2.3%
세 52
 
2.1%
Other values (194) 1509
61.8%
Common
ValueCountFrequency (%)
499
56.5%
/ 69
 
7.8%
0 62
 
7.0%
5 54
 
6.1%
6 44
 
5.0%
2 38
 
4.3%
1 28
 
3.2%
3 16
 
1.8%
, 15
 
1.7%
4 14
 
1.6%
Other values (9) 44
 
5.0%
Latin
ValueCountFrequency (%)
B 13
33.3%
M 13
33.3%
C 13
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2440
72.6%
ASCII 919
 
27.3%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
499
54.3%
/ 69
 
7.5%
0 62
 
6.7%
5 54
 
5.9%
6 44
 
4.8%
2 38
 
4.1%
1 28
 
3.0%
3 16
 
1.7%
, 15
 
1.6%
4 14
 
1.5%
Other values (11) 80
 
8.7%
Hangul
ValueCountFrequency (%)
지 185
 
7.6%
역 142
 
5.8%
주 131
 
5.4%
민 118
 
4.8%
상 72
 
3.0%
자 61
 
2.5%
이 57
 
2.3%
인 57
 
2.3%
소 56
 
2.3%
세 52
 
2.1%
Other values (194) 1509
61.8%
None
ValueCountFrequency (%)
· 3
100.0%

인원(명)
Text

MISSING 

Distinct147
Distinct (%)45.5%
Missing5
Missing (%)1.5%
Memory size2.7 KiB
2023-12-12T14:28:31.917649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length2.7987616
Min length1

Characters and Unicode

Total characters904
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)34.1%

Sample

1st row120
2nd row30
3rd row50
4th row30
5th row10
ValueCountFrequency (%)
200 22
 
6.8%
10 21
 
6.5%
50 15
 
4.6%
20 11
 
3.4%
100 11
 
3.4%
40 10
 
3.1%
30 10
 
3.1%
8 9
 
2.8%
15 7
 
2.2%
300 7
 
2.2%
Other values (137) 200
61.9%
2023-12-12T14:28:32.451835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 294
32.5%
1 124
13.7%
2 109
 
12.1%
5 76
 
8.4%
4 65
 
7.2%
3 56
 
6.2%
, 53
 
5.9%
8 44
 
4.9%
6 32
 
3.5%
7 26
 
2.9%
Other values (2) 25
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 850
94.0%
Other Punctuation 53
 
5.9%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 294
34.6%
1 124
14.6%
2 109
 
12.8%
5 76
 
8.9%
4 65
 
7.6%
3 56
 
6.6%
8 44
 
5.2%
6 32
 
3.8%
7 26
 
3.1%
9 24
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 904
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 294
32.5%
1 124
13.7%
2 109
 
12.1%
5 76
 
8.4%
4 65
 
7.2%
3 56
 
6.2%
, 53
 
5.9%
8 44
 
4.9%
6 32
 
3.5%
7 26
 
2.9%
Other values (2) 25
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 294
32.5%
1 124
13.7%
2 109
 
12.1%
5 76
 
8.4%
4 65
 
7.2%
3 56
 
6.2%
, 53
 
5.9%
8 44
 
4.9%
6 32
 
3.5%
7 26
 
2.9%
Other values (2) 25
 
2.8%

이용료(원)
Text

MISSING 

Distinct25
Distinct (%)69.4%
Missing292
Missing (%)89.0%
Memory size2.7 KiB
2023-12-12T14:28:32.692788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.9722222
Min length1

Characters and Unicode

Total characters287
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)66.7%

Sample

1st row장난감별 상이
2nd row70,000~150,000
3rd row50,000~130000
4th row12,000
5th row실비 25,000 바우처 소득별 상이
ValueCountFrequency (%)
무료 13
22.4%
상이 4
 
6.9%
월 3
 
5.2%
소득별 3
 
5.2%
20,000 2
 
3.4%
9 1
 
1.7%
100000 1
 
1.7%
상이(무료~80,000 1
 
1.7%
수급자 1
 
1.7%
차상위 1
 
1.7%
Other values (28) 28
48.3%
2023-12-12T14:28:33.038923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 93
32.4%
22
 
7.7%
, 21
 
7.3%
료 16
 
5.6%
무 15
 
5.2%
5 13
 
4.5%
1 9
 
3.1%
~ 7
 
2.4%
상 7
 
2.4%
이 6
 
2.1%
Other values (45) 78
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134
46.7%
Other Letter 92
32.1%
Other Punctuation 24
 
8.4%
Space Separator 22
 
7.7%
Math Symbol 7
 
2.4%
Open Punctuation 4
 
1.4%
Close Punctuation 4
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 16
17.4%
무 15
16.3%
상 7
 
7.6%
이 6
 
6.5%
별 5
 
5.4%
소 4
 
4.3%
득 4
 
4.3%
월 3
 
3.3%
위 2
 
2.2%
또 1
 
1.1%
Other values (29) 29
31.5%
Decimal Number
ValueCountFrequency (%)
0 93
69.4%
5 13
 
9.7%
1 9
 
6.7%
2 6
 
4.5%
8 3
 
2.2%
7 3
 
2.2%
6 2
 
1.5%
4 2
 
1.5%
3 2
 
1.5%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 21
87.5%
% 3
 
12.5%
Space Separator
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 195
67.9%
Hangul 92
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 16
17.4%
무 15
16.3%
상 7
 
7.6%
이 6
 
6.5%
별 5
 
5.4%
소 4
 
4.3%
득 4
 
4.3%
월 3
 
3.3%
위 2
 
2.2%
또 1
 
1.1%
Other values (29) 29
31.5%
Common
ValueCountFrequency (%)
0 93
47.7%
22
 
11.3%
, 21
 
10.8%
5 13
 
6.7%
1 9
 
4.6%
~ 7
 
3.6%
2 6
 
3.1%
( 4
 
2.1%
) 4
 
2.1%
% 3
 
1.5%
Other values (6) 13
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 195
67.9%
Hangul 92
32.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 93
47.7%
22
 
11.3%
, 21
 
10.8%
5 13
 
6.7%
1 9
 
4.6%
~ 7
 
3.6%
2 6
 
3.1%
( 4
 
2.1%
) 4
 
2.1%
% 3
 
1.5%
Other values (6) 13
 
6.7%
Hangul
ValueCountFrequency (%)
료 16
17.4%
무 15
16.3%
상 7
 
7.6%
이 6
 
6.5%
별 5
 
5.4%
소 4
 
4.3%
득 4
 
4.3%
월 3
 
3.3%
위 2
 
2.2%
또 1
 
1.1%
Other values (29) 29
31.5%

기간
Text

Distinct85
Distinct (%)26.0%
Missing1
Missing (%)0.3%
Memory size2.7 KiB
2023-12-12T14:28:33.371081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length5.3272171
Min length2

Characters and Unicode

Total characters1742
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)16.2%

Sample

1st row1월~12월
2nd row1월~12월
3rd row1월~12월
4th row1월~12월
5th row1월~12월
ValueCountFrequency (%)
1월~12월 100
24.4%
연중 42
 
10.3%
1회 32
 
7.8%
수시 18
 
4.4%
년 14
 
3.4%
3월~12월 13
 
3.2%
월 13
 
3.2%
주 11
 
2.7%
연 8
 
2.0%
주5회 6
 
1.5%
Other values (96) 152
37.2%
2023-12-12T14:28:33.944113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 355
20.4%
월 349
20.0%
2 167
9.6%
~ 162
9.3%
회 89
 
5.1%
82
 
4.7%
연 56
 
3.2%
중 52
 
3.0%
주 39
 
2.2%
) 32
 
1.8%
Other values (61) 359
20.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 768
44.1%
Decimal Number 634
36.4%
Math Symbol 162
 
9.3%
Space Separator 82
 
4.7%
Close Punctuation 32
 
1.8%
Open Punctuation 32
 
1.8%
Other Punctuation 27
 
1.5%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 349
45.4%
회 89
 
11.6%
연 56
 
7.3%
중 52
 
6.8%
주 39
 
5.1%
시 26
 
3.4%
년 26
 
3.4%
수 22
 
2.9%
일 9
 
1.2%
학 8
 
1.0%
Other values (42) 92
 
12.0%
Decimal Number
ValueCountFrequency (%)
1 355
56.0%
2 167
26.3%
0 25
 
3.9%
5 24
 
3.8%
3 23
 
3.6%
4 15
 
2.4%
6 14
 
2.2%
8 4
 
0.6%
7 4
 
0.6%
9 3
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 12
44.4%
, 10
37.0%
/ 4
 
14.8%
· 1
 
3.7%
Math Symbol
ValueCountFrequency (%)
~ 162
100.0%
Space Separator
ValueCountFrequency (%)
82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 974
55.9%
Hangul 768
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 349
45.4%
회 89
 
11.6%
연 56
 
7.3%
중 52
 
6.8%
주 39
 
5.1%
시 26
 
3.4%
년 26
 
3.4%
수 22
 
2.9%
일 9
 
1.2%
학 8
 
1.0%
Other values (42) 92
 
12.0%
Common
ValueCountFrequency (%)
1 355
36.4%
2 167
17.1%
~ 162
16.6%
82
 
8.4%
) 32
 
3.3%
( 32
 
3.3%
0 25
 
2.6%
5 24
 
2.5%
3 23
 
2.4%
4 15
 
1.5%
Other values (9) 57
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 973
55.9%
Hangul 768
44.1%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 355
36.5%
2 167
17.2%
~ 162
16.6%
82
 
8.4%
) 32
 
3.3%
( 32
 
3.3%
0 25
 
2.6%
5 24
 
2.5%
3 23
 
2.4%
4 15
 
1.5%
Other values (8) 56
 
5.8%
Hangul
ValueCountFrequency (%)
월 349
45.4%
회 89
 
11.6%
연 56
 
7.3%
중 52
 
6.8%
주 39
 
5.1%
시 26
 
3.4%
년 26
 
3.4%
수 22
 
2.9%
일 9
 
1.2%
학 8
 
1.0%
Other values (42) 92
 
12.0%
None
ValueCountFrequency (%)
· 1
100.0%

비고
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing325
Missing (%)99.1%
Memory size2.7 KiB
2023-12-12T14:28:34.164216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length7
Mean length10.333333
Min length6

Characters and Unicode

Total characters31
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row토공휴일 제외
2nd row일요일 제외
3rd row(여름방학 7명, 겨울방학 7명)
ValueCountFrequency (%)
제외 2
25.0%
7명 2
25.0%
토공휴일 1
12.5%
일요일 1
12.5%
여름방학 1
12.5%
겨울방학 1
12.5%
2023-12-12T14:28:34.448000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
16.1%
일 3
 
9.7%
학 2
 
6.5%
제 2
 
6.5%
외 2
 
6.5%
명 2
 
6.5%
7 2
 
6.5%
방 2
 
6.5%
토 1
 
3.2%
울 1
 
3.2%
Other values (9) 9
29.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21
67.7%
Space Separator 5
 
16.1%
Decimal Number 2
 
6.5%
Other Punctuation 1
 
3.2%
Open Punctuation 1
 
3.2%
Close Punctuation 1
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 3
14.3%
학 2
9.5%
제 2
9.5%
외 2
9.5%
명 2
9.5%
방 2
9.5%
토 1
 
4.8%
울 1
 
4.8%
겨 1
 
4.8%
여 1
 
4.8%
Other values (4) 4
19.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
7 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21
67.7%
Common 10
32.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 3
14.3%
학 2
9.5%
제 2
9.5%
외 2
9.5%
명 2
9.5%
방 2
9.5%
토 1
 
4.8%
울 1
 
4.8%
겨 1
 
4.8%
여 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
5
50.0%
7 2
 
20.0%
, 1
 
10.0%
( 1
 
10.0%
) 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21
67.7%
ASCII 10
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
50.0%
7 2
 
20.0%
, 1
 
10.0%
( 1
 
10.0%
) 1
 
10.0%
Hangul
ValueCountFrequency (%)
일 3
14.3%
학 2
9.5%
제 2
9.5%
외 2
9.5%
명 2
9.5%
방 2
9.5%
토 1
 
4.8%
울 1
 
4.8%
겨 1
 
4.8%
여 1
 
4.8%
Other values (4) 4
19.0%

Correlations

2023-12-12T14:28:34.534534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사회복지관명이용료(원)기간비고
사회복지관명1.0001.0000.8801.000
이용료(원)1.0001.0000.000NaN
기간0.8800.0001.0001.000
비고1.000NaN1.0001.000

Missing values

2023-12-12T14:28:28.228265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:28:28.343655image/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.
2023-12-12T14:28:28.447038image/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

사회복지관명사업명사업내용대상/명인원(명)이용료(원)기간비고
0영도구종합사회복지관사례개발홍보요보호대상자를 수시로 발굴하기 위한 공문 등 홍보활동지역주민120<NA>1월~12월<NA>
1영도구종합사회복지관사례접수지역사회의 개인, 단체, 기관에서 요보호대상자의 발견시 접수를 통한 지원체계마련지역주민30<NA>1월~12월<NA>
2영도구종합사회복지관상담(전화,방문,서신)사례발굴에 따른 요보호대상자의 욕구가 무엇인지에 대한 파악을 위한 초기상담지역주민50<NA>1월~12월<NA>
3영도구종합사회복지관스크리닝 회의사례접수된 요보호대상자가 일반 프로그램이나 단순 재가대상자인지에 대해 심의지역주민30<NA>1월~12월<NA>
4영도구종합사회복지관타기관 의뢰복지관 대상자로 부적합할 경우 적합한 타기관으로 의뢰지역주민10<NA>1월~12월<NA>
5영도구종합사회복지관생활현황조사사례관리 대상자로 심의된 요보호대상자에 대해 심화생활현황 조사 실시지역주민20<NA>1월~12월<NA>
6영도구종합사회복지관사례판정 사례회의사례관리대상자인지, 단순 재가대상자인지 판정하는 회의지역주민20<NA>1월~12월<NA>
7영도구종합사회복지관상황욕구강점사정개인의 생태체계에 따른 강점을 발견하는 상담실시지역주민14<NA>1월~12월<NA>
8영도구종합사회복지관개입목표설정 사례회의대상자의 복합문제에 대한 사회복지사의 사례회의 실시지역주민14<NA>1월~12월<NA>
9영도구종합사회복지관사례관리 계약대상자와 개입목요에 대해 조정, 일정기간의 동의, 계약 실시지역주민14<NA>1월~12월<NA>
사회복지관명사업명사업내용대상/명인원(명)이용료(원)기간비고
318와치종합사회복지관한진중공업 지정기탁 문화복지사업지역 내 소외계층 대상 문화공연 지원지역주민250<NA>수시<NA>
319와치종합사회복지관소상공인 후원자와 함께 하는 지역주민 나눔 활동소상공인 연계 지역주민 물품 지원BMC 2지구 지역 주민100<NA>5월<NA>
320와치종합사회복지관지역주민 한마음 놀이마당BMC 2지구 지역주민 대표(동대표 및 통장)와 연계하여 주민 놀이마당 실시BMC 2지구 지역 주민350<NA>10월<NA>
321와치종합사회복지관청소년유해환경감시단지역 내 성인으로 구성된 활동단원을 구성하여 청소년 유해환경에 대한 지속적인 감시활동을 진행함.지역주민23<NA>2월~12월<NA>
322와치종합사회복지관사회복지관 지역(주민)조직화 지원사업BMC2지구 지역주민이 사업 주체로 참여하여 마을 만들기 사업 구상 및 실시, 평가지역주민12<NA>2월~12월<NA>
323와치종합사회복지관BMC동삼2지구 공유세탁방 '사랑채'BMC동삼2지구 지역주민에게 세탁서비스 및 공동체 형성 프로그램 제공지역주민100<NA>1월~12월<NA>
324와치종합사회복지관지역주민 교육사업 명사초청 특강 '생생정보교실'지역주민 욕구조사 후 교육 주제를 선정하여 전문 강사를 초빙, 교육을 제공지역 주민30<NA>4월, 8월, 10월<NA>
325와치종합사회복지관텃밭 가꾸기 '힐링텃밭'계절별 작물 수확, 자조모임 등 마을 텃밭 가꾸기 활동 진행지역주민8<NA>2월~12월<NA>
326와치종합사회복지관자원봉사자 개발 및 관리자원봉사활동을 하고자 하는 의지를 가진 지역주민을 대상으로 자원봉사활동 연계, 간담회, 송년행사 등의 사업을 진행자원봉사자20<NA>1월~12월<NA>
327와치종합사회복지관후원자 개발 및 관리지역 내 소외계층의 경제적 지원을 위한 후원자를 개발하여 후원금품 연계, 후원감사 편지 전달, 송년행사 등 사업진행후원자100<NA>1월~12월<NA>