Overview

Dataset statistics

Number of variables3
Number of observations119
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory26.1 B

Variable types

Text2
Numeric1

Dataset

Description경상남도 함안군 자원봉사단체 현황에 대한 데이터로 자원봉사 단체명, 자원봉사 단체 대표 및 회원수의 항목에 대한 데이터를 제공합니다.
Author경상남도 함안군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3066735

Alerts

단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:58:40.405721
Analysis finished2023-12-10 22:58:40.738319
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단체명
Text

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T07:58:40.853743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.5714286
Min length2

Characters and Unicode

Total characters1020
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

Unique119 ?
Unique (%)100.0%

Sample

1st row(사)소비자교육함안군지회
2nd row(사)친환경실천국민운동본부
3rd rowSS프렌드청소년자원봉사팀
4th row가야국악예술단
5th row가야둥이들
ValueCountFrequency (%)
새마을협의회 10
 
6.6%
적십자봉사회 10
 
6.6%
자원봉사대 6
 
4.0%
칠원읍 3
 
2.0%
군북면 3
 
2.0%
법수면 3
 
2.0%
가야읍 3
 
2.0%
산인면 3
 
2.0%
대산면 3
 
2.0%
칠서면 2
 
1.3%
Other values (101) 105
69.5%
2023-12-11T07:58:41.155975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 59
 
5.8%
봉 43
 
4.2%
회 41
 
4.0%
32
 
3.1%
함 30
 
2.9%
면 30
 
2.9%
안 29
 
2.8%
단 28
 
2.7%
대 27
 
2.6%
자 26
 
2.5%
Other values (185) 675
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 976
95.7%
Space Separator 32
 
3.1%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%
Uppercase Letter 2
 
0.2%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 59
 
6.0%
봉 43
 
4.4%
회 41
 
4.2%
함 30
 
3.1%
면 30
 
3.1%
안 29
 
3.0%
단 28
 
2.9%
대 27
 
2.8%
자 26
 
2.7%
원 24
 
2.5%
Other values (180) 639
65.5%
Space Separator
ValueCountFrequency (%)
32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 976
95.7%
Common 42
 
4.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 59
 
6.0%
봉 43
 
4.4%
회 41
 
4.2%
함 30
 
3.1%
면 30
 
3.1%
안 29
 
3.0%
단 28
 
2.9%
대 27
 
2.8%
자 26
 
2.7%
원 24
 
2.5%
Other values (180) 639
65.5%
Common
ValueCountFrequency (%)
32
76.2%
( 4
 
9.5%
) 4
 
9.5%
. 2
 
4.8%
Latin
ValueCountFrequency (%)
S 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 976
95.7%
ASCII 44
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 59
 
6.0%
봉 43
 
4.4%
회 41
 
4.2%
함 30
 
3.1%
면 30
 
3.1%
안 29
 
3.0%
단 28
 
2.9%
대 27
 
2.8%
자 26
 
2.7%
원 24
 
2.5%
Other values (180) 639
65.5%
ASCII
ValueCountFrequency (%)
32
72.7%
( 4
 
9.1%
) 4
 
9.1%
S 2
 
4.5%
. 2
 
4.5%

단체대표
Text

Distinct114
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T07:58:41.442475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters357
Distinct characters106
Distinct categories1 ?
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 (%)91.6%

Sample

1st row정재숙
2nd row노영주
3rd row이유림
4th row김혜숙
5th row안수경
ValueCountFrequency (%)
안인순 2
 
1.7%
이정숙 2
 
1.7%
권영희 2
 
1.7%
윤정필 2
 
1.7%
이미영 2
 
1.7%
권미련 1
 
0.8%
윤정희 1
 
0.8%
신순옥 1
 
0.8%
이말순 1
 
0.8%
황윤정 1
 
0.8%
Other values (104) 104
87.4%
2023-12-11T07:58:41.878985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 22
 
6.2%
정 19
 
5.3%
영 16
 
4.5%
순 13
 
3.6%
숙 12
 
3.4%
희 12
 
3.4%
윤 11
 
3.1%
김 11
 
3.1%
박 10
 
2.8%
미 9
 
2.5%
Other values (96) 222
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 357
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 22
 
6.2%
정 19
 
5.3%
영 16
 
4.5%
순 13
 
3.6%
숙 12
 
3.4%
희 12
 
3.4%
윤 11
 
3.1%
김 11
 
3.1%
박 10
 
2.8%
미 9
 
2.5%
Other values (96) 222
62.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 357
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 22
 
6.2%
정 19
 
5.3%
영 16
 
4.5%
순 13
 
3.6%
숙 12
 
3.4%
희 12
 
3.4%
윤 11
 
3.1%
김 11
 
3.1%
박 10
 
2.8%
미 9
 
2.5%
Other values (96) 222
62.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 357
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 22
 
6.2%
정 19
 
5.3%
영 16
 
4.5%
순 13
 
3.6%
숙 12
 
3.4%
희 12
 
3.4%
윤 11
 
3.1%
김 11
 
3.1%
박 10
 
2.8%
미 9
 
2.5%
Other values (96) 222
62.2%

회원수
Real number (ℝ)

Distinct63
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.411765
Minimum2
Maximum625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T07:58:42.279732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile9
Q117
median30
Q347.5
95-th percentile109.3
Maximum625
Range623
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation61.119557
Coefficient of variation (CV)1.4410991
Kurtosis70.754693
Mean42.411765
Median Absolute Deviation (MAD)15
Skewness7.5735124
Sum5047
Variance3735.6002
MonotonicityNot monotonic
2023-12-11T07:58:42.397643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 6
 
5.0%
41 6
 
5.0%
20 5
 
4.2%
22 5
 
4.2%
9 5
 
4.2%
31 4
 
3.4%
18 4
 
3.4%
19 4
 
3.4%
17 3
 
2.5%
13 3
 
2.5%
Other values (53) 74
62.2%
ValueCountFrequency (%)
2 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
9 5
4.2%
10 2
 
1.7%
11 3
2.5%
12 6
5.0%
13 3
2.5%
14 2
 
1.7%
15 3
2.5%
ValueCountFrequency (%)
625 1
0.8%
141 1
0.8%
133 1
0.8%
126 1
0.8%
115 1
0.8%
112 1
0.8%
109 1
0.8%
103 1
0.8%
88 1
0.8%
86 1
0.8%

Interactions

2023-12-11T07:58:40.547086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-11T07:58:40.651877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:58:40.714058image/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

단체명단체대표회원수
0(사)소비자교육함안군지회정재숙84
1(사)친환경실천국민운동본부노영주48
2SS프렌드청소년자원봉사팀이유림22
3가야국악예술단김혜숙47
4가야둥이들안수경12
5가야읍 새마을협의회안상목88
6가야읍 자원봉사대이미영115
7가야읍 적십자봉사회이정숙45
8가야읍의용소방대윤진희133
9고.주.모 사물놀이반김양순27
단체명단체대표회원수
109함안면의용소방대안인준43
110함안문화원어르신문화나눔봉사단홍선자11
111함안박물관자원봉사단이정숙9
112함안아동요리지도사고영미9
113함안아라라이온스클럽주귀옥42
114함안아시랑로타리클럽양연숙56
115함안외국인센터윤혁권36
116함안청소년오케스트라정진향41
117함중사모회권영희12
118희망나눔봉사단정영림9