Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory54.3 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description대전광역시 중구체육회에서 운영하는 생활체육교실 운영현황에 대한 정보제공 (생활체육교실 종목, 장소, 요일, 시간, 강사명)
URLhttps://www.data.go.kr/data/15119765/fileData.do

Alerts

연번 is highly overall correlated with 종목High correlation
종목 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
강사명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:44:40.915754
Analysis finished2023-12-12 09:44:41.862678
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-12T18:44:41.932456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-12T18:44:42.151360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

종목
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
생활체조
7 
댄스스포츠
5 
파크골프
3 
국학기공
2 
축구
2 
Other values (5)
6 

Length

Max length5
Median length4
Mean length3.68
Min length2

Unique

Unique4 ?
Unique (%)16.0%

Sample

1st row게이트볼
2nd row국학기공
3rd row국학기공
4th row댄스스포츠
5th row댄스스포츠

Common Values

ValueCountFrequency (%)
생활체조 7
28.0%
댄스스포츠 5
20.0%
파크골프 3
12.0%
국학기공 2
 
8.0%
축구 2
 
8.0%
탁구 2
 
8.0%
게이트볼 1
 
4.0%
배구 1
 
4.0%
우드볼 1
 
4.0%
족구 1
 
4.0%

Length

2023-12-12T18:44:42.305887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:44:42.453159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활체조 7
28.0%
댄스스포츠 5
20.0%
파크골프 3
12.0%
국학기공 2
 
8.0%
축구 2
 
8.0%
탁구 2
 
8.0%
게이트볼 1
 
4.0%
배구 1
 
4.0%
우드볼 1
 
4.0%
족구 1
 
4.0%

장소
Text

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:44:42.671085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.92
Min length5

Characters and Unicode

Total characters198
Distinct characters79
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)72.0%

Sample

1st row버드내게이트볼장
2nd row충무체육관
3rd row서대전시민공원
4th row유천2동행정복지센터
5th row목동행정복지센터
ValueCountFrequency (%)
중구파크골프장 3
 
12.0%
대전기독교종합사회복지관 2
 
8.0%
오류초등학교 2
 
8.0%
버드내게이트볼장 1
 
4.0%
중촌동행정복지센터 1
 
4.0%
대전광역시노인복지관 1
 
4.0%
중구체육복지센터2 1
 
4.0%
중구체육복지센터1 1
 
4.0%
보훈족구장 1
 
4.0%
중구우드볼장 1
 
4.0%
Other values (11) 11
44.0%
2023-12-12T18:44:43.098131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 11
 
5.6%
복 11
 
5.6%
센 8
 
4.0%
터 8
 
4.0%
행 7
 
3.5%
구 7
 
3.5%
중 7
 
3.5%
동 6
 
3.0%
장 6
 
3.0%
정 6
 
3.0%
Other values (69) 121
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
98.0%
Decimal Number 4
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 11
 
5.7%
복 11
 
5.7%
센 8
 
4.1%
터 8
 
4.1%
행 7
 
3.6%
구 7
 
3.6%
중 7
 
3.6%
동 6
 
3.1%
장 6
 
3.1%
정 6
 
3.1%
Other values (67) 117
60.3%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
98.0%
Common 4
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 11
 
5.7%
복 11
 
5.7%
센 8
 
4.1%
터 8
 
4.1%
행 7
 
3.6%
구 7
 
3.6%
중 7
 
3.6%
동 6
 
3.1%
장 6
 
3.1%
정 6
 
3.1%
Other values (67) 117
60.3%
Common
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
98.0%
ASCII 4
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 11
 
5.7%
복 11
 
5.7%
센 8
 
4.1%
터 8
 
4.1%
행 7
 
3.6%
구 7
 
3.6%
중 7
 
3.6%
동 6
 
3.1%
장 6
 
3.1%
정 6
 
3.1%
Other values (67) 117
60.3%
ASCII
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%

요일
Text

Distinct14
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:44:43.270429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length5.28
Min length1

Characters and Unicode

Total characters132
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)40.0%

Sample

1st row화, 목
2nd row월, 수, 금
3rd row월, 수, 금
4th row수, 금
5th row화, 목
ValueCountFrequency (%)
화 17
28.3%
목 13
21.7%
수 11
18.3%
금 11
18.3%
월 7
11.7%
월,목 1
 
1.7%
2023-12-12T18:44:43.568795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 36
27.3%
35
26.5%
화 17
12.9%
목 14
 
10.6%
수 11
 
8.3%
금 11
 
8.3%
월 8
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
46.2%
Other Punctuation 36
27.3%
Space Separator 35
26.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 17
27.9%
목 14
23.0%
수 11
18.0%
금 11
18.0%
월 8
13.1%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
53.8%
Hangul 61
46.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 17
27.9%
목 14
23.0%
수 11
18.0%
금 11
18.0%
월 8
13.1%
Common
ValueCountFrequency (%)
, 36
50.7%
35
49.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
53.8%
Hangul 61
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 36
50.7%
35
49.3%
Hangul
ValueCountFrequency (%)
화 17
27.9%
목 14
23.0%
수 11
18.0%
금 11
18.0%
월 8
13.1%

시간
Text

Distinct15
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:44:43.813401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters275
Distinct characters11
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

Unique9 ?
Unique (%)36.0%

Sample

1st row09:00~11:00
2nd row06:00~07:00
3rd row05:20~06:20
4th row13:00~15:00
5th row13:00~15:00
ValueCountFrequency (%)
06:00~07:00 3
12.0%
13:00~15:00 3
12.0%
05:30~06:30 3
12.0%
20:00~22:00 3
12.0%
10:00~12:00 2
 
8.0%
10:00~11:00 2
 
8.0%
09:00~11:00 1
 
4.0%
05:20~06:20 1
 
4.0%
16:00~18:00 1
 
4.0%
11:00~13:00 1
 
4.0%
Other values (5) 5
20.0%
2023-12-12T18:44:44.188134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 110
40.0%
: 50
18.2%
1 34
 
12.4%
~ 25
 
9.1%
3 16
 
5.8%
2 14
 
5.1%
5 9
 
3.3%
6 8
 
2.9%
7 5
 
1.8%
9 3
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
72.7%
Other Punctuation 50
 
18.2%
Math Symbol 25
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 110
55.0%
1 34
 
17.0%
3 16
 
8.0%
2 14
 
7.0%
5 9
 
4.5%
6 8
 
4.0%
7 5
 
2.5%
9 3
 
1.5%
8 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 50
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 275
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 110
40.0%
: 50
18.2%
1 34
 
12.4%
~ 25
 
9.1%
3 16
 
5.8%
2 14
 
5.1%
5 9
 
3.3%
6 8
 
2.9%
7 5
 
1.8%
9 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 110
40.0%
: 50
18.2%
1 34
 
12.4%
~ 25
 
9.1%
3 16
 
5.8%
2 14
 
5.1%
5 9
 
3.3%
6 8
 
2.9%
7 5
 
1.8%
9 3
 
1.1%

강사명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-12T18:44:44.472577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.96
Min length2

Characters and Unicode

Total characters74
Distinct characters48
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

Unique25 ?
Unique (%)100.0%

Sample

1st row임기수
2nd row이규혜
3rd row채남준
4th row김옥화
5th row장미
ValueCountFrequency (%)
임기수 1
 
4.0%
최옥희 1
 
4.0%
신영식 1
 
4.0%
신동갑 1
 
4.0%
지수란 1
 
4.0%
지수민 1
 
4.0%
이유임 1
 
4.0%
홍민지 1
 
4.0%
박제광 1
 
4.0%
이종순 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T18:44:44.857773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 4
 
5.4%
임 3
 
4.1%
혜 3
 
4.1%
진 3
 
4.1%
지 3
 
4.1%
민 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
채 2
 
2.7%
경 2
 
2.7%
Other values (38) 45
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 4
 
5.4%
임 3
 
4.1%
혜 3
 
4.1%
진 3
 
4.1%
지 3
 
4.1%
민 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
채 2
 
2.7%
경 2
 
2.7%
Other values (38) 45
60.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 4
 
5.4%
임 3
 
4.1%
혜 3
 
4.1%
진 3
 
4.1%
지 3
 
4.1%
민 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
채 2
 
2.7%
경 2
 
2.7%
Other values (38) 45
60.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 4
 
5.4%
임 3
 
4.1%
혜 3
 
4.1%
진 3
 
4.1%
지 3
 
4.1%
민 3
 
4.1%
이 3
 
4.1%
수 3
 
4.1%
채 2
 
2.7%
경 2
 
2.7%
Other values (38) 45
60.8%

Interactions

2023-12-12T18:44:41.222871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:44:44.992548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종목장소요일시간강사명
연번1.0000.9640.9430.6260.8691.000
종목0.9641.0000.9320.0000.9121.000
장소0.9430.9321.0000.4600.5761.000
요일0.6260.0000.4601.0000.7911.000
시간0.8690.9120.5760.7911.0001.000
강사명1.0001.0001.0001.0001.0001.000
2023-12-12T18:44:45.140880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종목
연번1.0000.664
종목0.6641.000

Missing values

2023-12-12T18:44:41.681348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:44:41.811429image/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

연번종목장소요일시간강사명
01게이트볼버드내게이트볼장화, 목09:00~11:00임기수
12국학기공충무체육관월, 수, 금06:00~07:00이규혜
23국학기공서대전시민공원월, 수, 금05:20~06:20채남준
34댄스스포츠유천2동행정복지센터수, 금13:00~15:00김옥화
45댄스스포츠목동행정복지센터화, 목13:00~15:00장미
56댄스스포츠은행선화동행정복지센터화, 목16:00~18:00조빛나
67댄스스포츠산성동행정복지센터월,목11:00~13:00전순균
78댄스스포츠대전기독교종합사회복지관화, 금13:00~15:00최진성
89배구오류초등학교화, 목19:00~21:00박형용
910생활체조보문산야외음악당화, 수, 목, 금05:30~06:30김다경
연번종목장소요일시간강사명
1516생활체조한밭가든천변화, 수, 목, 금05:30~06:30황혜경
1617우드볼중구우드볼장월, 화, 목, 금10:00~11:00이종순
1718족구보훈족구장수, 금20:00~22:00박제광
1819축구중구체육복지센터1화, 목20:00~22:00홍민지
1920축구중구체육복지센터2화, 목20:00~22:00이유임
2021탁구대전기독교종합사회복지관수15:30~17:30지수민
2122탁구대전광역시노인복지관목09:30~11:30지수란
2223파크골프중구파크골프장월, 화15:00~17:00신동갑
2324파크골프중구파크골프장화, 목10:00~12:00신영식
2425파크골프중구파크골프장월, 수, 금10:00~11:00김민자