Overview

Dataset statistics

Number of variables3
Number of observations107
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory26.2 B

Variable types

Text2
Numeric1

Dataset

Description경상남도_남해군 자원봉사단체에 대한 데이터로 단체명, 단체원수, 대표자 이름 등 항목에 대한 정보를 제공합니다.
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3063222

Alerts

단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:16:24.652387
Analysis finished2023-12-10 23:16:24.981809
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단체명
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T08:16:25.149008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length9.1682243
Min length2

Characters and Unicode

Total characters981
Distinct characters194
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

Unique107 ?
Unique (%)100.0%

Sample

1st row남해기독신우회
2nd row남해청실회
3rd row새남해로타리클럽
4th row천도교봉사회
5th row한국자유총연맹 남해군지회
ValueCountFrequency (%)
새마을지회 20
 
12.0%
부녀회 10
 
6.0%
협의회 10
 
6.0%
봉사단 4
 
2.4%
보물섬 3
 
1.8%
고현면 2
 
1.2%
미조면 2
 
1.2%
남해읍 2
 
1.2%
삼동면 2
 
1.2%
상주면 2
 
1.2%
Other values (104) 110
65.9%
2023-12-11T08:16:25.514598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 74
 
7.5%
61
 
6.2%
남 36
 
3.7%
면 36
 
3.7%
사 35
 
3.6%
해 34
 
3.5%
봉 27
 
2.8%
지 27
 
2.8%
자 25
 
2.5%
새 23
 
2.3%
Other values (184) 603
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 901
91.8%
Space Separator 61
 
6.2%
Uppercase Letter 8
 
0.8%
Lowercase Letter 5
 
0.5%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 74
 
8.2%
남 36
 
4.0%
면 36
 
4.0%
사 35
 
3.9%
해 34
 
3.8%
봉 27
 
3.0%
지 27
 
3.0%
자 25
 
2.8%
새 23
 
2.6%
마 22
 
2.4%
Other values (172) 562
62.4%
Uppercase Letter
ValueCountFrequency (%)
M 2
25.0%
S 2
25.0%
G 2
25.0%
C 1
12.5%
I 1
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
n 1
20.0%
r 1
20.0%
g 1
20.0%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 901
91.8%
Common 67
 
6.8%
Latin 13
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 74
 
8.2%
남 36
 
4.0%
면 36
 
4.0%
사 35
 
3.9%
해 34
 
3.8%
봉 27
 
3.0%
지 27
 
3.0%
자 25
 
2.8%
새 23
 
2.6%
마 22
 
2.4%
Other values (172) 562
62.4%
Latin
ValueCountFrequency (%)
e 2
15.4%
M 2
15.4%
S 2
15.4%
G 2
15.4%
C 1
7.7%
I 1
7.7%
n 1
7.7%
r 1
7.7%
g 1
7.7%
Common
ValueCountFrequency (%)
61
91.0%
) 3
 
4.5%
( 3
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 901
91.8%
ASCII 80
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 74
 
8.2%
남 36
 
4.0%
면 36
 
4.0%
사 35
 
3.9%
해 34
 
3.8%
봉 27
 
3.0%
지 27
 
3.0%
자 25
 
2.8%
새 23
 
2.6%
마 22
 
2.4%
Other values (172) 562
62.4%
ASCII
ValueCountFrequency (%)
61
76.2%
) 3
 
3.8%
( 3
 
3.8%
e 2
 
2.5%
M 2
 
2.5%
S 2
 
2.5%
G 2
 
2.5%
C 1
 
1.2%
I 1
 
1.2%
n 1
 
1.2%
Other values (2) 2
 
2.5%

인원
Real number (ℝ)

Distinct43
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.757009
Minimum5
Maximum485
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T08:16:25.863196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.3
Q114
median20
Q330.5
95-th percentile139.2
Maximum485
Range480
Interquartile range (IQR)16.5

Descriptive statistics

Standard deviation63.614381
Coefficient of variation (CV)1.6848363
Kurtosis26.356546
Mean37.757009
Median Absolute Deviation (MAD)7
Skewness4.7400397
Sum4040
Variance4046.7895
MonotonicityNot monotonic
2023-12-11T08:16:25.980735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
20 16
 
15.0%
10 6
 
5.6%
25 6
 
5.6%
13 5
 
4.7%
22 5
 
4.7%
23 5
 
4.7%
17 4
 
3.7%
12 3
 
2.8%
8 3
 
2.8%
50 3
 
2.8%
Other values (33) 51
47.7%
ValueCountFrequency (%)
5 2
 
1.9%
6 2
 
1.9%
7 2
 
1.9%
8 3
2.8%
9 2
 
1.9%
10 6
5.6%
11 2
 
1.9%
12 3
2.8%
13 5
4.7%
15 2
 
1.9%
ValueCountFrequency (%)
485 1
0.9%
290 1
0.9%
260 1
0.9%
222 1
0.9%
181 1
0.9%
150 1
0.9%
114 1
0.9%
89 1
0.9%
81 1
0.9%
66 1
0.9%

대표자
Text

Distinct101
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T08:16:26.309119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9906542
Min length2

Characters and Unicode

Total characters320
Distinct characters104
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

Unique95 ?
Unique (%)88.8%

Sample

1st row김점중
2nd row이창섭
3rd row한영관
4th row이영미
5th row양태종
ValueCountFrequency (%)
김민정 2
 
1.9%
배경순 2
 
1.9%
최현숙 2
 
1.9%
정용수 2
 
1.9%
이영미 2
 
1.9%
김미경 2
 
1.9%
강문호 1
 
0.9%
이선화 1
 
0.9%
조민지 1
 
0.9%
김영희 1
 
0.9%
Other values (91) 91
85.0%
2023-12-11T08:16:26.852733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 22
 
6.9%
이 15
 
4.7%
정 14
 
4.4%
영 12
 
3.8%
경 10
 
3.1%
박 10
 
3.1%
숙 10
 
3.1%
미 8
 
2.5%
순 8
 
2.5%
최 7
 
2.2%
Other values (94) 204
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 22
 
6.9%
이 15
 
4.7%
정 14
 
4.4%
영 12
 
3.8%
경 10
 
3.1%
박 10
 
3.1%
숙 10
 
3.1%
미 8
 
2.5%
순 8
 
2.5%
최 7
 
2.2%
Other values (94) 204
63.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 22
 
6.9%
이 15
 
4.7%
정 14
 
4.4%
영 12
 
3.8%
경 10
 
3.1%
박 10
 
3.1%
숙 10
 
3.1%
미 8
 
2.5%
순 8
 
2.5%
최 7
 
2.2%
Other values (94) 204
63.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 22
 
6.9%
이 15
 
4.7%
정 14
 
4.4%
영 12
 
3.8%
경 10
 
3.1%
박 10
 
3.1%
숙 10
 
3.1%
미 8
 
2.5%
순 8
 
2.5%
최 7
 
2.2%
Other values (94) 204
63.7%

Interactions

2023-12-11T08:16:24.798851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-11T08:16:24.892314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:16:24.956856image/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

단체명인원대표자
0남해기독신우회30김점중
1남해청실회43이창섭
2새남해로타리클럽81한영관
3천도교봉사회17이영미
4한국자유총연맹 남해군지회290양태종
5손사랑서금요법 봉사단20김두엽
6남해로타리클럽89백서훈
7재향군인여성회260이양옥
8바르게살기운동남해군협의회485하의현
9아이코리아25서영숙
단체명인원대표자
97보물섬 스킨스쿠버동아리5홍성훈
98내고향남해사랑 재경향우회 봉사단12구덕순
99내고향남해사랑 재김해향우회 봉사단20김미경
100쉼과 여백8이재범
101청춘어람봉사단114정세준
102웰니스봉사단20권오천
103행복더하기19정현진
104남해장애인복지관17이경은
105남해군여성예비군소대9백승동
106온나누리7고영우