Overview

Dataset statistics

Number of variables5
Number of observations51
Missing cells9
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory43.6 B

Variable types

Text3
Numeric1
Categorical1

Dataset

Description그랜드코리아레저 휠체어펜싱팀의 22년까지의 경기 참가 현황에 대한 데이터로 대회일자, 참가대회명, 성적 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15048179/fileData.do

Alerts

종목 has constant value ""Constant
성적 has 9 (17.6%) missing valuesMissing
대회일자 has unique valuesUnique
참가대회 has unique valuesUnique
순서 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:58:05.659258
Analysis finished2023-12-12 12:58:06.170191
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대회일자
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T21:58:06.372629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters1071
Distinct characters12
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

Unique51 ?
Unique (%)100.0%

Sample

1st row2022-11-25~2022-11-27
2nd row2022-10-19~2022-10-24
3rd row2022-07-29~2022-07-31
4th row2022-07-17~2022-06-19
5th row2022-04-01~2022-04-03
ValueCountFrequency (%)
2022-11-25~2022-11-27 1
 
2.0%
2018-09-14~2018-09-16 1
 
2.0%
2018-08-03~2018-08-05 1
 
2.0%
2018-07-03~2018-07-10 1
 
2.0%
2018-06-01~2018-06-03 1
 
2.0%
2018-04-24~2018-05-01 1
 
2.0%
2018-04-06~2018-04-08 1
 
2.0%
2018-03-07~2018-03-13 1
 
2.0%
2018-02-14~2018-02-20 1
 
2.0%
2017-11-06~2017-11-14 1
 
2.0%
Other values (41) 41
80.4%
2023-12-12T21:58:06.783552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
20.2%
1 205
19.1%
- 204
19.0%
2 170
15.9%
~ 51
 
4.8%
9 49
 
4.6%
8 46
 
4.3%
6 37
 
3.5%
7 34
 
3.2%
3 24
 
2.2%
Other values (2) 35
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 816
76.2%
Dash Punctuation 204
 
19.0%
Math Symbol 51
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
26.5%
1 205
25.1%
2 170
20.8%
9 49
 
6.0%
8 46
 
5.6%
6 37
 
4.5%
7 34
 
4.2%
3 24
 
2.9%
5 18
 
2.2%
4 17
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Math Symbol
ValueCountFrequency (%)
~ 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1071
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
20.2%
1 205
19.1%
- 204
19.0%
2 170
15.9%
~ 51
 
4.8%
9 49
 
4.6%
8 46
 
4.3%
6 37
 
3.5%
7 34
 
3.2%
3 24
 
2.2%
Other values (2) 35
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1071
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
20.2%
1 205
19.1%
- 204
19.0%
2 170
15.9%
~ 51
 
4.8%
9 49
 
4.6%
8 46
 
4.3%
6 37
 
3.5%
7 34
 
3.2%
3 24
 
2.2%
Other values (2) 35
 
3.3%

참가대회
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-12T21:58:07.123219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length27
Mean length19.411765
Min length11

Characters and Unicode

Total characters990
Distinct characters104
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

Unique51 ?
Unique (%)100.0%

Sample

1st row제11회 추계 전국휠체어펜싱 선수권대회
2nd row제42회 전국 장애인 체육대회
3rd row제7회 세종특별시장배 전국휠체어펜싱 선수권대회
4th row제5회 오픈배 전국휠체어펜싱 선수권대회
5th row제18회 춘계 전국휠체어펜싱 선수권대회
ValueCountFrequency (%)
선수권대회 20
 
9.6%
전국휠체어펜싱 13
 
6.2%
월드컵 12
 
5.8%
대회 11
 
5.3%
8
 
3.8%
2018 8
 
3.8%
2019 6
 
2.9%
제5회 4
 
1.9%
은1 4
 
1.9%
춘계전국휠체어펜싱 3
 
1.4%
Other values (82) 119
57.2%
2023-12-12T21:58:07.597620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
 
16.1%
회 72
 
7.3%
대 44
 
4.4%
1 35
 
3.5%
전 32
 
3.2%
국 32
 
3.2%
제 30
 
3.0%
선 28
 
2.8%
권 28
 
2.8%
수 28
 
2.8%
Other values (94) 502
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 687
69.4%
Space Separator 159
 
16.1%
Decimal Number 126
 
12.7%
Dash Punctuation 8
 
0.8%
Other Punctuation 7
 
0.7%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 72
 
10.5%
대 44
 
6.4%
전 32
 
4.7%
국 32
 
4.7%
제 30
 
4.4%
선 28
 
4.1%
권 28
 
4.1%
수 28
 
4.1%
체 26
 
3.8%
펜 20
 
2.9%
Other values (78) 347
50.5%
Decimal Number
ValueCountFrequency (%)
1 35
27.8%
2 24
19.0%
0 19
15.1%
8 12
 
9.5%
3 9
 
7.1%
9 7
 
5.6%
4 6
 
4.8%
7 6
 
4.8%
5 5
 
4.0%
6 3
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
U 1
33.3%
A 1
33.3%
E 1
33.3%
Space Separator
ValueCountFrequency (%)
159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 687
69.4%
Common 300
30.3%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 72
 
10.5%
대 44
 
6.4%
전 32
 
4.7%
국 32
 
4.7%
제 30
 
4.4%
선 28
 
4.1%
권 28
 
4.1%
수 28
 
4.1%
체 26
 
3.8%
펜 20
 
2.9%
Other values (78) 347
50.5%
Common
ValueCountFrequency (%)
159
53.0%
1 35
 
11.7%
2 24
 
8.0%
0 19
 
6.3%
8 12
 
4.0%
3 9
 
3.0%
- 8
 
2.7%
, 7
 
2.3%
9 7
 
2.3%
4 6
 
2.0%
Other values (3) 14
 
4.7%
Latin
ValueCountFrequency (%)
U 1
33.3%
A 1
33.3%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 687
69.4%
ASCII 303
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
52.5%
1 35
 
11.6%
2 24
 
7.9%
0 19
 
6.3%
8 12
 
4.0%
3 9
 
3.0%
- 8
 
2.6%
, 7
 
2.3%
9 7
 
2.3%
4 6
 
2.0%
Other values (6) 17
 
5.6%
Hangul
ValueCountFrequency (%)
회 72
 
10.5%
대 44
 
6.4%
전 32
 
4.7%
국 32
 
4.7%
제 30
 
4.4%
선 28
 
4.1%
권 28
 
4.1%
수 28
 
4.1%
체 26
 
3.8%
펜 20
 
2.9%
Other values (78) 347
50.5%

순서
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-12T21:58:07.775897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly decreasing
2023-12-12T21:58:07.935765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 1
 
2.0%
50 1
 
2.0%
23 1
 
2.0%
22 1
 
2.0%
21 1
 
2.0%
20 1
 
2.0%
19 1
 
2.0%
18 1
 
2.0%
17 1
 
2.0%
16 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

종목
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
펜싱
51 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
펜싱 51
100.0%

Length

2023-12-12T21:58:08.092106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:58:08.185349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
펜싱 51
100.0%

성적
Text

MISSING 

Distinct41
Distinct (%)97.6%
Missing9
Missing (%)17.6%
Memory size540.0 B
2023-12-12T21:58:08.394951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length225
Median length106.5
Mean length95.309524
Min length28

Characters and Unicode

Total characters4003
Distinct characters60
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)95.2%

Sample

1st row박천희 [에뻬] 8강, [플러레] 1위, [사브르] 8강/심재훈 [에뻬] 1위, [플러레] 2위, [사브르] 1위
2nd row박천희 [플러레B] 2위, [사브르B] 2위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위/단체전(박천희, 심재훈, 엄성수_세종시체육회) [에뻬] 2위, [플러레] 2위, [사브르] 1위
3rd row박천희 [플러레B] 1위, [사브르B] 1위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위
4th row박천희 [플러레B] 1위, [사브르B] 3위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위
5th row박천희 [에뻬B] 1위, [플러레B] 2위, [사브르B] 2위/심재훈 [에뻬A] 1위, [사브르A] 1위
ValueCountFrequency (%)
에 51
 
9.1%
1위 44
 
7.9%
뻬a 34
 
6.1%
플러뢰a 29
 
5.2%
뻬b 24
 
4.3%
플러뢰b 24
 
4.3%
조영래 22
 
3.9%
박천희 18
 
3.2%
김기홍 16
 
2.9%
사브르b 15
 
2.7%
Other values (137) 282
50.4%
2023-12-12T21:58:08.778622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
757
18.9%
, 292
 
7.3%
위 290
 
7.2%
] 200
 
5.0%
[ 200
 
5.0%
1 159
 
4.0%
A 152
 
3.8%
플 117
 
2.9%
러 117
 
2.9%
뻬 105
 
2.6%
Other values (50) 1614
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1684
42.1%
Space Separator 757
18.9%
Decimal Number 419
 
10.5%
Other Punctuation 308
 
7.7%
Close Punctuation 284
 
7.1%
Open Punctuation 284
 
7.1%
Uppercase Letter 258
 
6.4%
Dash Punctuation 8
 
0.2%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 290
17.2%
플 117
 
6.9%
러 117
 
6.9%
뻬 105
 
6.2%
에 105
 
6.2%
르 76
 
4.5%
브 76
 
4.5%
뢰 71
 
4.2%
심 57
 
3.4%
재 57
 
3.4%
Other values (25) 613
36.4%
Decimal Number
ValueCountFrequency (%)
1 159
37.9%
2 82
19.6%
3 60
 
14.3%
4 28
 
6.7%
8 21
 
5.0%
6 21
 
5.0%
5 18
 
4.3%
7 15
 
3.6%
0 10
 
2.4%
9 5
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 292
94.8%
* 8
 
2.6%
/ 8
 
2.6%
Close Punctuation
ValueCountFrequency (%)
] 200
70.4%
］ 83
29.2%
) 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
[ 200
70.4%
［ 83
29.2%
( 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
A 152
58.9%
B 103
39.9%
C 3
 
1.2%
Space Separator
ValueCountFrequency (%)
757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2061
51.5%
Hangul 1684
42.1%
Latin 258
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 290
17.2%
플 117
 
6.9%
러 117
 
6.9%
뻬 105
 
6.2%
에 105
 
6.2%
르 76
 
4.5%
브 76
 
4.5%
뢰 71
 
4.2%
심 57
 
3.4%
재 57
 
3.4%
Other values (25) 613
36.4%
Common
ValueCountFrequency (%)
757
36.7%
, 292
 
14.2%
] 200
 
9.7%
[ 200
 
9.7%
1 159
 
7.7%
］ 83
 
4.0%
［ 83
 
4.0%
2 82
 
4.0%
3 60
 
2.9%
4 28
 
1.4%
Other values (12) 117
 
5.7%
Latin
ValueCountFrequency (%)
A 152
58.9%
B 103
39.9%
C 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2153
53.8%
Hangul 1684
42.1%
None 166
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
757
35.2%
, 292
 
13.6%
] 200
 
9.3%
[ 200
 
9.3%
1 159
 
7.4%
A 152
 
7.1%
B 103
 
4.8%
2 82
 
3.8%
3 60
 
2.8%
4 28
 
1.3%
Other values (13) 120
 
5.6%
Hangul
ValueCountFrequency (%)
위 290
17.2%
플 117
 
6.9%
러 117
 
6.9%
뻬 105
 
6.2%
에 105
 
6.2%
르 76
 
4.5%
브 76
 
4.5%
뢰 71
 
4.2%
심 57
 
3.4%
재 57
 
3.4%
Other values (25) 613
36.4%
None
ValueCountFrequency (%)
］ 83
50.0%
［ 83
50.0%

Interactions

2023-12-12T21:58:05.886074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:58:08.893346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대회일자참가대회순서성적
대회일자1.0001.0001.0001.000
참가대회1.0001.0001.0001.000
순서1.0001.0001.0001.000
성적1.0001.0001.0001.000

Missing values

2023-12-12T21:58:06.001987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:58:06.121704image/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

대회일자참가대회순서종목성적
02022-11-25~2022-11-27제11회 추계 전국휠체어펜싱 선수권대회51펜싱박천희 [에뻬] 8강, [플러레] 1위, [사브르] 8강/심재훈 [에뻬] 1위, [플러레] 2위, [사브르] 1위
12022-10-19~2022-10-24제42회 전국 장애인 체육대회50펜싱박천희 [플러레B] 2위, [사브르B] 2위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위/단체전(박천희, 심재훈, 엄성수_세종시체육회) [에뻬] 2위, [플러레] 2위, [사브르] 1위
22022-07-29~2022-07-31제7회 세종특별시장배 전국휠체어펜싱 선수권대회49펜싱박천희 [플러레B] 1위, [사브르B] 1위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위
32022-07-17~2022-06-19제5회 오픈배 전국휠체어펜싱 선수권대회48펜싱박천희 [플러레B] 1위, [사브르B] 3위/심재훈 [에뻬A] 1위, [플러레A] 1위, [사브르A] 1위
42022-04-01~2022-04-03제18회 춘계 전국휠체어펜싱 선수권대회47펜싱박천희 [에뻬B] 1위, [플러레B] 2위, [사브르B] 2위/심재훈 [에뻬A] 1위, [사브르A] 1위
52021-11-26~2021-11-28제10회 추계전국 휠체어펜싱 선수권대회46펜싱심재훈A 플러레 1위, 에뻬 1위, 샤브르 1위/박천희B 플러레 3위, 에뻬 3위, 샤브르 2위
62021-10-21~2021-10-24제41회전국장애인체육대회45펜싱박천희B 플러레 3위, 에뻬 3위, 샤브르 16강/심재훈A 플러레 1위, 에뻬 1위, 샤브르 1위
72021-03-05~2021-03-07제17회 춘계전국휠체어펜싱 선수권대회44펜싱박천희 플러레B 3위, 에뻬B 3위, 샤브르B 2위
82020-02-11~2020-02-182020 헝가리 에게르 월드컵43펜싱심재훈［플러레A］27위［에뻬A］11위［샤브르A］26위
92019-11-12~2019-11-192019 네덜란드 암스테르담 월드컵42펜싱조영래［플러레A］40위［에뻬A］37위［샤브르A］31위,,박천희［플러레B］15위［에뻬B］24위［샤브르B］15위,,심재훈［플러레A］7위［에뻬A］14위［샤브르A］17위
대회일자참가대회순서종목성적
412017-03-15~2017-03-212017 피사월드컵대회10펜싱김기홍 [에 뻬B] 8위,[플러뢰B] 10위,박천희 [플러뢰B] 13위, [에 뻬B] 20위,심재훈 [에 뻬A] 22위,[플러뢰A] 13위
422016-12-05~2016-12-16중국 상하이 전지훈련9펜싱<NA>
432016-11-18~2016-11-20제5회 추계전국휠체어펜싱 선수권대회 - 금2, 은18펜싱<NA>
442016-11-10~2016-11-15피사월드컵대회 - 8강 외7펜싱<NA>
452016-10-31~2016-11-09이탈리아 피사 전지훈련 - 이탈리아 국가대표 합동훈련6펜싱<NA>
462016-10-21~2016-10-25제36회 전국장애인체육대회 - 금4, 은1, 동15펜싱<NA>
472016-09-23~2016-09-25제1회 세종시장배 전국휠체어펜싱 선수권대회 - 금1, 은1, 동14펜싱<NA>
482016-08-26~2016-08-28제5회 직지배 전국휠체어펜싱 선수권대회 - 금2, 은13펜싱<NA>
492016-07-29~2016-07-31제2회 충청북도지사배 전국휠체어펜싱 선수권대회 - 금32펜싱<NA>
502016-06-03~2016-06-05제13회 춘계전국휠체어펜싱 선수권대회 - 금1, 은21펜싱<NA>