Overview

Dataset statistics

Number of variables6
Number of observations2261
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory110.5 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical5

Dataset

Description사회리더 대학생 멘토링은 기업 및 학계 등 사회 각 분야에서 다양한 성공경험과 전문지식을 겸비한 사회지도층 멘토의 멘토링을 통해 참여 대학(원)생 멘티들을 미래 대한민국을 이끄는 배움과 나눔의 인재로 양성하고자 하며, 사회리더 대학생 멘토링의 멘티 현황(성별, 분과별 등)에 대한 정보를 제공하고 있습니다. ※ 상세 정보는 한국장학재단 홈페이지 참고(메뉴: 인재육성>사회리더 대학생 멘토링)
URLhttps://www.data.go.kr/data/15084723/fileData.do

Alerts

연도 has constant value ""Constant
참여자 구분 has constant value ""Constant
활동지역 is highly imbalanced (52.9%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:07:55.897255
Analysis finished2023-12-12 13:07:56.329821
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct2261
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1131
Minimum1
Maximum2261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.0 KiB
2023-12-12T22:07:56.395861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile114
Q1566
median1131
Q31696
95-th percentile2148
Maximum2261
Range2260
Interquartile range (IQR)1130

Descriptive statistics

Standard deviation652.8388
Coefficient of variation (CV)0.57722264
Kurtosis-1.2
Mean1131
Median Absolute Deviation (MAD)565
Skewness0
Sum2557191
Variance426198.5
MonotonicityStrictly increasing
2023-12-12T22:07:56.528664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1512 1
 
< 0.1%
1506 1
 
< 0.1%
1507 1
 
< 0.1%
1508 1
 
< 0.1%
1509 1
 
< 0.1%
1510 1
 
< 0.1%
1511 1
 
< 0.1%
1513 1
 
< 0.1%
1504 1
 
< 0.1%
Other values (2251) 2251
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2261 1
< 0.1%
2260 1
< 0.1%
2259 1
< 0.1%
2258 1
< 0.1%
2257 1
< 0.1%
2256 1
< 0.1%
2255 1
< 0.1%
2254 1
< 0.1%
2253 1
< 0.1%
2252 1
< 0.1%

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
2022
2261 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 2261
100.0%

Length

2023-12-12T22:07:56.664542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:56.748684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 2261
100.0%

성별
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
여
1439 
남
822 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row남
4th row남
5th row여

Common Values

ValueCountFrequency (%)
여 1439
63.6%
남 822
36.4%

Length

2023-12-12T22:07:56.847773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:56.950716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 1439
63.6%
남 822
36.4%

전문분과
Categorical

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
과학기술/IT/연구
515 
경영관리
388 
문화예술콘텐츠
255 
영업/마케팅
246 
사회행정서비스
219 
Other values (4)
638 

Length

Max length10
Median length7
Mean length6.1716055
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row과학기술/IT/연구
2nd row경영관리
3rd row창업/사회혁신
4th row문화예술콘텐츠
5th row과학기술/IT/연구

Common Values

ValueCountFrequency (%)
과학기술/IT/연구 515
22.8%
경영관리 388
17.2%
문화예술콘텐츠 255
11.3%
영업/마케팅 246
10.9%
사회행정서비스 219
9.7%
창업/사회혁신 218
9.6%
금융 196
 
8.7%
교육 178
 
7.9%
보건의료 46
 
2.0%

Length

2023-12-12T22:07:57.375080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:57.498352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
과학기술/it/연구 515
22.8%
경영관리 388
17.2%
문화예술콘텐츠 255
11.3%
영업/마케팅 246
10.9%
사회행정서비스 219
9.7%
창업/사회혁신 218
9.6%
금융 196
 
8.7%
교육 178
 
7.9%
보건의료 46
 
2.0%

참여자 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
멘티
2261 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
멘티 2261
100.0%

Length

2023-12-12T22:07:57.631877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:07:57.746003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
멘티 2261
100.0%

활동지역
Categorical

IMBALANCE 

Distinct13
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.8 KiB
서울특별시
1582 
부산광역시
190 
대구광역시
 
139
경기도
 
121
대전광역시
 
83
Other values (8)
 
146

Length

Max length7
Median length5
Mean length4.8522778
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row경기도
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 1582
70.0%
부산광역시 190
 
8.4%
대구광역시 139
 
6.1%
경기도 121
 
5.4%
대전광역시 83
 
3.7%
전라북도 41
 
1.8%
광주광역시 26
 
1.1%
경상남도 22
 
1.0%
경상북도 15
 
0.7%
충청남도 14
 
0.6%
Other values (3) 28
 
1.2%

Length

2023-12-12T22:07:57.864983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 1582
70.0%
부산광역시 190
 
8.4%
대구광역시 139
 
6.1%
경기도 121
 
5.4%
대전광역시 83
 
3.7%
전라북도 41
 
1.8%
광주광역시 26
 
1.1%
경상남도 22
 
1.0%
경상북도 15
 
0.7%
충청남도 14
 
0.6%
Other values (3) 28
 
1.2%

Interactions

2023-12-12T22:07:56.093534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:07:57.962197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번성별전문분과활동지역
순번1.0000.0920.0000.045
성별0.0921.0000.1900.119
전문분과0.0000.1901.0000.397
활동지역0.0450.1190.3971.000
2023-12-12T22:07:58.085795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별전문분과활동지역
성별1.0000.1900.110
전문분과0.1901.0000.182
활동지역0.1100.1821.000
2023-12-12T22:07:58.182512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번성별전문분과활동지역
순번1.0000.0710.0000.019
성별0.0711.0000.1900.110
전문분과0.0000.1901.0000.182
활동지역0.0190.1100.1821.000

Missing values

2023-12-12T22:07:56.196470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:07:56.290209image/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

순번연도성별전문분과참여자 구분활동지역
012022남과학기술/IT/연구멘티서울특별시
122022여경영관리멘티서울특별시
232022남창업/사회혁신멘티서울특별시
342022남문화예술콘텐츠멘티경기도
452022여과학기술/IT/연구멘티서울특별시
562022여문화예술콘텐츠멘티경기도
672022남영업/마케팅멘티경기도
782022여문화예술콘텐츠멘티서울특별시
892022여사회행정서비스멘티서울특별시
9102022여보건의료멘티부산광역시
순번연도성별전문분과참여자 구분활동지역
225122522022남과학기술/IT/연구멘티대구광역시
225222532022여과학기술/IT/연구멘티서울특별시
225322542022여영업/마케팅멘티서울특별시
225422552022남영업/마케팅멘티서울특별시
225522562022남문화예술콘텐츠멘티서울특별시
225622572022남과학기술/IT/연구멘티서울특별시
225722582022여창업/사회혁신멘티경상북도
225822592022남사회행정서비스멘티서울특별시
225922602022여문화예술콘텐츠멘티서울특별시
226022612022여사회행정서비스멘티서울특별시