Overview

Dataset statistics

Number of variables5
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory43.4 B

Variable types

Categorical2
Text1
Numeric1
DateTime1

Dataset

Description부산광역시 영도구에서 추진하는 영도구 노인일자리 정보를 제공합니다.(수행기관, 사업명, 유형, 참여인원 등)
Author부산광역시 영도구
URLhttps://www.data.go.kr/data/3070054/fileData.do

Alerts

데이터기준일자 has constant value ""Constant

Reproduction

Analysis started2024-03-14 11:35:37.988037
Analysis finished2024-03-14 11:35:39.067955
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수행기관
Categorical

Distinct10
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size560.0 B
부산영도시니어클럽
27 
영도구노인복지관
6 
동삼종합사회복지관
5 
영도구노인복지관 분관
3 
영도구종합사회복지관
3 
Other values (5)
10 

Length

Max length11
Median length9
Mean length8.962963
Min length3

Unique

Unique2 ?
Unique (%)3.7%

Sample

1st row영도구
2nd row대한노인회영도구지회
3rd row영도구노인복지관
4th row영도구노인복지관
5th row영도구노인복지관

Common Values

ValueCountFrequency (%)
부산영도시니어클럽 27
50.0%
영도구노인복지관 6
 
11.1%
동삼종합사회복지관 5
 
9.3%
영도구노인복지관 분관 3
 
5.6%
영도구종합사회복지관 3
 
5.6%
절영종합사회복지관 3
 
5.6%
상리종합사회복지관 3
 
5.6%
와치종합사회복지관 2
 
3.7%
영도구 1
 
1.9%
대한노인회영도구지회 1
 
1.9%

Length

2024-03-14T20:35:39.312163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:35:39.687756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산영도시니어클럽 27
47.4%
영도구노인복지관 9
 
15.8%
동삼종합사회복지관 5
 
8.8%
분관 3
 
5.3%
영도구종합사회복지관 3
 
5.3%
절영종합사회복지관 3
 
5.3%
상리종합사회복지관 3
 
5.3%
와치종합사회복지관 2
 
3.5%
영도구 1
 
1.8%
대한노인회영도구지회 1
 
1.8%

유형
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size560.0 B
공익활동
26 
사회서비스형
11 
공익활동형
9 
시장형
8 

Length

Max length6
Median length5
Mean length4.4259259
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공익활동 26
48.1%
사회서비스형 11
20.4%
공익활동형 9
 
16.7%
시장형 8
 
14.8%

Length

2024-03-14T20:35:40.132601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:35:40.468872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공익활동 26
48.1%
사회서비스형 11
20.4%
공익활동형 9
 
16.7%
시장형 8
 
14.8%

사업명
Text

Distinct53
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size560.0 B
2024-03-14T20:35:41.342713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.2592593
Min length5

Characters and Unicode

Total characters446
Distinct characters135
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)96.3%

Sample

1st row우리동네환경지킴이
2nd row경로당활성화지원사업
3rd row지역사회환경개선봉사
4th row행복도시락배달부
5th row태종대문화재시설봉사
ValueCountFrequency (%)
스쿨존교통안전캠페인 2
 
3.7%
우리동네환경지킴이 1
 
1.9%
공익증진서비스사업단 1
 
1.9%
횡단보도관리사업단 1
 
1.9%
학교교통지킴이사업단 1
 
1.9%
맑은누리사업단 1
 
1.9%
푸른바다사업단 1
 
1.9%
교통안전활동사업단 1
 
1.9%
공공시설봉사사업단 1
 
1.9%
소방안전사업단 1
 
1.9%
Other values (43) 43
79.6%
2024-03-14T20:35:42.677570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 44
 
9.9%
단 41
 
9.2%
업 30
 
6.7%
시 12
 
2.7%
지 11
 
2.5%
리 11
 
2.5%
봉 10
 
2.2%
교 9
 
2.0%
설 9
 
2.0%
도 8
 
1.8%
Other values (125) 261
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
99.3%
Other Symbol 1
 
0.2%
Decimal Number 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 44
 
9.9%
단 41
 
9.3%
업 30
 
6.8%
시 12
 
2.7%
지 11
 
2.5%
리 11
 
2.5%
봉 10
 
2.3%
교 9
 
2.0%
설 9
 
2.0%
도 8
 
1.8%
Other values (122) 258
58.2%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 443
99.3%
Common 3
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 44
 
9.9%
단 41
 
9.3%
업 30
 
6.8%
시 12
 
2.7%
지 11
 
2.5%
리 11
 
2.5%
봉 10
 
2.3%
교 9
 
2.0%
설 9
 
2.0%
도 8
 
1.8%
Other values (122) 258
58.2%
Common
ValueCountFrequency (%)
℃ 1
33.3%
0 1
33.3%
· 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 443
99.3%
Letterlike Symbols 1
 
0.2%
ASCII 1
 
0.2%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 44
 
9.9%
단 41
 
9.3%
업 30
 
6.8%
시 12
 
2.7%
지 11
 
2.5%
리 11
 
2.5%
봉 10
 
2.3%
교 9
 
2.0%
설 9
 
2.0%
도 8
 
1.8%
Other values (122) 258
58.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
ASCII
ValueCountFrequency (%)
0 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

일자리수(명)
Real number (ℝ)

Distinct32
Distinct (%)59.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.148148
Minimum4
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size614.0 B
2024-03-14T20:35:43.074843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile9.3
Q116
median35
Q393.5
95-th percentile181.55
Maximum200
Range196
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation58.705985
Coefficient of variation (CV)0.97602316
Kurtosis0.045125517
Mean60.148148
Median Absolute Deviation (MAD)25
Skewness1.1658134
Sum3248
Variance3446.3927
MonotonicityNot monotonic
2024-03-14T20:35:43.496590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
10 7
 
13.0%
30 3
 
5.6%
40 3
 
5.6%
20 3
 
5.6%
25 3
 
5.6%
160 2
 
3.7%
55 2
 
3.7%
50 2
 
3.7%
190 2
 
3.7%
35 2
 
3.7%
Other values (22) 25
46.3%
ValueCountFrequency (%)
4 1
 
1.9%
6 1
 
1.9%
8 1
 
1.9%
10 7
13.0%
14 2
 
3.7%
15 1
 
1.9%
16 2
 
3.7%
20 3
5.6%
22 1
 
1.9%
24 1
 
1.9%
ValueCountFrequency (%)
200 1
1.9%
190 2
3.7%
177 1
1.9%
174 1
1.9%
163 1
1.9%
160 2
3.7%
150 1
1.9%
110 1
1.9%
105 1
1.9%
104 1
1.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size560.0 B
Minimum2024-01-22 00:00:00
Maximum2024-01-22 00:00:00
2024-03-14T20:35:43.862844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:35:44.157848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T20:35:38.272331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:35:44.366712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수행기관유형사업명일자리수(명)
수행기관1.0000.6250.8570.403
유형0.6251.0001.0000.686
사업명0.8571.0001.0000.986
일자리수(명)0.4030.6860.9861.000
2024-03-14T20:35:44.616083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수행기관유형
수행기관1.0000.397
유형0.3971.000
2024-03-14T20:35:44.852012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자리수(명)수행기관유형
일자리수(명)1.0000.1840.490
수행기관0.1841.0000.397
유형0.4900.3971.000

Missing values

2024-03-14T20:35:38.623623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:35:38.944347image/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

수행기관유형사업명일자리수(명)데이터기준일자
0영도구공익활동우리동네환경지킴이1102024-01-22
1대한노인회영도구지회공익활동경로당활성화지원사업1502024-01-22
2영도구노인복지관공익활동지역사회환경개선봉사1602024-01-22
3영도구노인복지관공익활동행복도시락배달부402024-01-22
4영도구노인복지관공익활동태종대문화재시설봉사402024-01-22
5영도구노인복지관공익활동스쿨존교통안전캠페인402024-01-22
6영도구노인복지관공익활동남항대교공공시설봉사202024-01-22
7영도구노인복지관시장형카페희망역사업단62024-01-22
8영도구노인복지관 분관공익활동스쿨존교통안전캠페인222024-01-22
9영도구노인복지관 분관공익활동시니어교통안전활동1042024-01-22
수행기관유형사업명일자리수(명)데이터기준일자
44부산영도시니어클럽사회서비스형마을탐방사업단452024-01-22
45부산영도시니어클럽사회서비스형서포터즈사업단502024-01-22
46부산영도시니어클럽사회서비스형치안지킴이사업단302024-01-22
47부산영도시니어클럽시장형요리조리사업단942024-01-22
48부산영도시니어클럽시장형방아깨비사업단102024-01-22
49부산영도시니어클럽시장형풀잎0℃카페사업단202024-01-22
50부산영도시니어클럽시장형금비사업단352024-01-22
51부산영도시니어클럽시장형주차장관리사업단252024-01-22
52부산영도시니어클럽시장형싱싱가게사업단152024-01-22
53부산영도시니어클럽시장형어울림사업단1052024-01-22