Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells2899
Missing cells (%)3.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory800.8 KiB
Average record size in memory82.0 B

Variable types

Categorical3
Text4
Numeric2

Dataset

Description종목별 등록된 경기결과(종목명,종별명,세부종목명,대회명,대회시작일,대회종료일,대회장소,대회구분,성별 등)
Author대한체육회
URLhttps://www.data.go.kr/data/15052687/fileData.do

Alerts

대회시작일 is highly overall correlated with 대회종료일High correlation
대회종료일 is highly overall correlated with 대회시작일High correlation
종목명 is highly overall correlated with 성별High correlation
성별 is highly overall correlated with 종목명High correlation
대회구분 is highly imbalanced (77.7%)Imbalance
대회시작일 has 954 (9.5%) missing valuesMissing
대회종료일 has 965 (9.7%) missing valuesMissing
대회장소 has 978 (9.8%) missing valuesMissing
대회시작일 is highly skewed (γ1 = -30.72320195)Skewed
대회종료일 is highly skewed (γ1 = -28.16015609)Skewed

Reproduction

Analysis started2023-12-12 08:49:25.869824
Analysis finished2023-12-12 08:49:28.437876
Duration2.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종목명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
레슬링
5413 
배드민턴
888 
롤러
735 
배구
 
481
농구
 
468
Other values (20)
2015 

Length

Max length9
Median length3
Mean length2.872
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row레슬링
2nd row레슬링
3rd row롤러
4th row레슬링
5th row레슬링

Common Values

ValueCountFrequency (%)
레슬링 5413
54.1%
배드민턴 888
 
8.9%
롤러 735
 
7.3%
배구 481
 
4.8%
농구 468
 
4.7%
검도 363
 
3.6%
공수도 318
 
3.2%
골프 252
 
2.5%
당구 203
 
2.0%
근대5종 180
 
1.8%
Other values (15) 699
 
7.0%

Length

2023-12-12T17:49:28.554803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
레슬링 5413
54.1%
배드민턴 888
 
8.9%
롤러 735
 
7.3%
배구 481
 
4.8%
농구 468
 
4.7%
검도 363
 
3.6%
공수도 318
 
3.2%
골프 252
 
2.5%
당구 203
 
2.0%
근대5종 180
 
1.8%
Other values (15) 699
 
7.0%

종별명
Text

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:49:28.897399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length2
Mean length3.3768
Min length2

Characters and Unicode

Total characters33768
Distinct characters113
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)0.3%

Sample

1st row일반
2nd row남자고등부
3rd row여자초등부(5,6학년)
4th row일반
5th row여고
ValueCountFrequency (%)
남고 1225
 
11.8%
남일 1029
 
9.9%
고등 762
 
7.3%
남대 685
 
6.6%
일반 595
 
5.7%
여일 470
 
4.5%
일반부 438
 
4.2%
대학 436
 
4.2%
고등부 418
 
4.0%
남자고등부 412
 
4.0%
Other values (138) 3945
37.9%
2023-12-12T17:49:29.413472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
남 4893
14.5%
고 3457
10.2%
부 3435
10.2%
일 3055
 
9.0%
자 2574
 
7.6%
등 2439
 
7.2%
여 1824
 
5.4%
대 1570
 
4.6%
반 1552
 
4.6%
학 1273
 
3.8%
Other values (103) 7696
22.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29358
86.9%
Uppercase Letter 1874
 
5.5%
Decimal Number 608
 
1.8%
Open Punctuation 533
 
1.6%
Close Punctuation 533
 
1.6%
Space Separator 415
 
1.2%
Other Punctuation 296
 
0.9%
Lowercase Letter 136
 
0.4%
Connector Punctuation 11
 
< 0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 4893
16.7%
고 3457
11.8%
부 3435
11.7%
일 3055
10.4%
자 2574
8.8%
등 2439
8.3%
여 1824
 
6.2%
대 1570
 
5.3%
반 1552
 
5.3%
학 1273
 
4.3%
Other values (64) 3286
11.2%
Uppercase Letter
ValueCountFrequency (%)
M 373
19.9%
E 373
19.9%
N 373
19.9%
W 246
13.1%
O 217
11.6%
B 123
 
6.6%
S 53
 
2.8%
D 30
 
1.6%
F 29
 
1.5%
I 25
 
1.3%
Other values (5) 32
 
1.7%
Lowercase Letter
ValueCountFrequency (%)
o 30
22.1%
i 20
14.7%
r 20
14.7%
e 16
11.8%
n 16
11.8%
u 13
9.6%
t 9
 
6.6%
h 6
 
4.4%
d 3
 
2.2%
l 3
 
2.2%
Decimal Number
ValueCountFrequency (%)
6 135
22.2%
5 120
19.7%
1 101
16.6%
2 91
15.0%
4 68
11.2%
3 68
11.2%
7 25
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 245
82.8%
/ 51
 
17.2%
Open Punctuation
ValueCountFrequency (%)
( 533
100.0%
Close Punctuation
ValueCountFrequency (%)
) 533
100.0%
Space Separator
ValueCountFrequency (%)
415
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29358
86.9%
Common 2400
 
7.1%
Latin 2010
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 4893
16.7%
고 3457
11.8%
부 3435
11.7%
일 3055
10.4%
자 2574
8.8%
등 2439
8.3%
여 1824
 
6.2%
대 1570
 
5.3%
반 1552
 
5.3%
학 1273
 
4.3%
Other values (64) 3286
11.2%
Latin
ValueCountFrequency (%)
M 373
18.6%
E 373
18.6%
N 373
18.6%
W 246
12.2%
O 217
10.8%
B 123
 
6.1%
S 53
 
2.6%
D 30
 
1.5%
o 30
 
1.5%
F 29
 
1.4%
Other values (15) 163
8.1%
Common
ValueCountFrequency (%)
( 533
22.2%
) 533
22.2%
415
17.3%
, 245
10.2%
6 135
 
5.6%
5 120
 
5.0%
1 101
 
4.2%
2 91
 
3.8%
4 68
 
2.8%
3 68
 
2.8%
Other values (4) 91
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29358
86.9%
ASCII 4410
 
13.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
남 4893
16.7%
고 3457
11.8%
부 3435
11.7%
일 3055
10.4%
자 2574
8.8%
등 2439
8.3%
여 1824
 
6.2%
대 1570
 
5.3%
반 1552
 
5.3%
학 1273
 
4.3%
Other values (64) 3286
11.2%
ASCII
ValueCountFrequency (%)
( 533
12.1%
) 533
12.1%
415
9.4%
M 373
 
8.5%
E 373
 
8.5%
N 373
 
8.5%
W 246
 
5.6%
, 245
 
5.6%
O 217
 
4.9%
6 135
 
3.1%
Other values (29) 967
21.9%

세부종목명
Text

Distinct3127
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T17:49:29.795340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length11.2496
Min length2

Characters and Unicode

Total characters112496
Distinct characters242
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1474 ?
Unique (%)14.7%

Sample

1st row그레꼬로만형　１３０ＫＧ급-준준결승경기２
2nd rowF76kg
3rd rowE3,000m
4th row그레꼬로만형　６８ＫＧ급-예선경기４
5th row자유형67kg급-준준결승경기４
ValueCountFrequency (%)
그레꼬로만형 417
 
3.5%
자유형 415
 
3.5%
단체전 242
 
2.0%
개인복식 230
 
1.9%
women 217
 
1.8%
단체전-결승 194
 
1.6%
개인단식 171
 
1.4%
개인전 167
 
1.4%
men 156
 
1.3%
개인대련 130
 
1.1%
Other values (2543) 9513
80.3%
2023-12-12T17:49:30.342961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7288
 
6.5%
기 4879
 
4.3%
경 4875
 
4.3%
준 4812
 
4.3%
형 4300
 
3.8%
급 4264
 
3.8%
결 3877
 
3.4%
승 3838
 
3.4%
선 2627
 
2.3%
예 2590
 
2.3%
Other values (232) 69146
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67316
59.8%
Decimal Number 19629
 
17.4%
Uppercase Letter 9641
 
8.6%
Dash Punctuation 7316
 
6.5%
Lowercase Letter 5680
 
5.0%
Space Separator 1853
 
1.6%
Other Punctuation 407
 
0.4%
Close Punctuation 280
 
0.2%
Open Punctuation 280
 
0.2%
Math Symbol 89
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 4879
 
7.2%
경 4875
 
7.2%
준 4812
 
7.1%
형 4300
 
6.4%
급 4264
 
6.3%
결 3877
 
5.8%
승 3838
 
5.7%
선 2627
 
3.9%
예 2590
 
3.8%
자 2446
 
3.6%
Other values (152) 28808
42.8%
Uppercase Letter
ValueCountFrequency (%)
Ｋ 1719
17.8%
Ｇ 1664
17.3%
G 1347
14.0%
K 972
10.1%
F 748
7.8%
E 463
 
4.8%
N 460
 
4.8%
W 460
 
4.8%
M 403
 
4.2%
O 344
 
3.6%
Other values (22) 1061
11.0%
Decimal Number
ValueCountFrequency (%)
0 2539
12.9%
5 1644
 
8.4%
１ 1604
 
8.2%
２ 1464
 
7.5%
6 1337
 
6.8%
４ 1198
 
6.1%
３ 1095
 
5.6%
1 942
 
4.8%
５ 858
 
4.4%
６ 835
 
4.3%
Other values (10) 6113
31.1%
Lowercase Letter
ValueCountFrequency (%)
g 2442
43.0%
k 2442
43.0%
m 702
 
12.4%
i 18
 
0.3%
a 14
 
0.2%
l 10
 
0.2%
d 10
 
0.2%
n 10
 
0.2%
u 9
 
0.2%
s 9
 
0.2%
Other values (2) 14
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 71
79.8%
~ 16
 
18.0%
< 1
 
1.1%
> 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 231
56.8%
. 101
24.8%
． 75
 
18.4%
Dash Punctuation
ValueCountFrequency (%)
- 7288
99.6%
－ 28
 
0.4%
Space Separator
ValueCountFrequency (%)
　 939
50.7%
914
49.3%
Close Punctuation
ValueCountFrequency (%)
) 227
81.1%
） 53
 
18.9%
Open Punctuation
ValueCountFrequency (%)
( 227
81.1%
（ 53
 
18.9%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67316
59.8%
Common 29859
26.5%
Latin 15321
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 4879
 
7.2%
경 4875
 
7.2%
준 4812
 
7.1%
형 4300
 
6.4%
급 4264
 
6.3%
결 3877
 
5.8%
승 3838
 
5.7%
선 2627
 
3.9%
예 2590
 
3.8%
자 2446
 
3.6%
Other values (152) 28808
42.8%
Latin
ValueCountFrequency (%)
g 2442
15.9%
k 2442
15.9%
Ｋ 1719
11.2%
Ｇ 1664
10.9%
G 1347
8.8%
K 972
 
6.3%
F 748
 
4.9%
m 702
 
4.6%
E 463
 
3.0%
N 460
 
3.0%
Other values (34) 2362
15.4%
Common
ValueCountFrequency (%)
- 7288
24.4%
0 2539
 
8.5%
5 1644
 
5.5%
１ 1604
 
5.4%
２ 1464
 
4.9%
6 1337
 
4.5%
４ 1198
 
4.0%
３ 1095
 
3.7%
1 942
 
3.2%
　 939
 
3.1%
Other values (26) 9809
32.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67316
59.8%
ASCII 31238
27.8%
None 13942
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7288
23.3%
0 2539
 
8.1%
g 2442
 
7.8%
k 2442
 
7.8%
5 1644
 
5.3%
G 1347
 
4.3%
6 1337
 
4.3%
K 972
 
3.1%
1 942
 
3.0%
914
 
2.9%
Other values (45) 9371
30.0%
Hangul
ValueCountFrequency (%)
기 4879
 
7.2%
경 4875
 
7.2%
준 4812
 
7.1%
형 4300
 
6.4%
급 4264
 
6.3%
결 3877
 
5.8%
승 3838
 
5.7%
선 2627
 
3.9%
예 2590
 
3.8%
자 2446
 
3.6%
Other values (152) 28808
42.8%
None
ValueCountFrequency (%)
Ｋ 1719
12.3%
Ｇ 1664
11.9%
１ 1604
11.5%
２ 1464
10.5%
４ 1198
8.6%
３ 1095
7.9%
　 939
6.7%
５ 858
6.2%
６ 835
6.0%
０ 664
 
4.8%
Other values (15) 1902
13.6%

대회명
Text

Distinct1029
Distinct (%)10.3%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T17:49:30.738689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length11
Mean length15.239748
Min length4

Characters and Unicode

Total characters152367
Distinct characters374
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique535 ?
Unique (%)5.4%

Sample

1st row제70회 전국체육대회
2nd row양정모올림픽제패기념 제38회 KBS배 전국레슬링대회
3rd row제36회 전국남녀종별롤러경기대회
4th row제76회 전국체육대회
5th row제96회 전국체육대회
ValueCountFrequency (%)
전국체육대회 6859
27.6%
전국 522
 
2.1%
및 333
 
1.3%
롤러경기대회 306
 
1.2%
국가대표 258
 
1.0%
제98회 250
 
1.0%
제93회 246
 
1.0%
제97회 243
 
1.0%
제96회 242
 
1.0%
제95회 239
 
1.0%
Other values (915) 15372
61.8%
2023-12-12T17:49:31.291246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 19923
 
13.1%
14940
 
9.8%
대 11511
 
7.6%
국 9707
 
6.4%
제 9664
 
6.3%
전 9511
 
6.2%
체 7315
 
4.8%
육 7307
 
4.8%
9 3457
 
2.3%
8 2691
 
1.8%
Other values (364) 56341
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111506
73.2%
Decimal Number 23037
 
15.1%
Space Separator 14940
 
9.8%
Uppercase Letter 1648
 
1.1%
Lowercase Letter 422
 
0.3%
Open Punctuation 247
 
0.2%
Close Punctuation 247
 
0.2%
Other Punctuation 226
 
0.1%
Final Punctuation 76
 
< 0.1%
Dash Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 19923
17.9%
대 11511
 
10.3%
국 9707
 
8.7%
제 9664
 
8.7%
전 9511
 
8.5%
체 7315
 
6.6%
육 7307
 
6.6%
선 1807
 
1.6%
기 1590
 
1.4%
수 1512
 
1.4%
Other values (304) 31659
28.4%
Uppercase Letter
ValueCountFrequency (%)
S 281
17.1%
K 248
15.0%
B 232
14.1%
O 104
 
6.3%
A 102
 
6.2%
E 78
 
4.7%
N 73
 
4.4%
I 71
 
4.3%
T 69
 
4.2%
C 63
 
3.8%
Other values (12) 327
19.8%
Lowercase Letter
ValueCountFrequency (%)
t 54
12.8%
a 54
12.8%
h 54
12.8%
e 47
11.1%
n 45
10.7%
o 36
8.5%
r 29
6.9%
p 29
6.9%
i 27
6.4%
s 18
 
4.3%
Other values (4) 29
6.9%
Decimal Number
ValueCountFrequency (%)
9 3457
15.0%
8 2691
11.7%
7 2660
11.5%
2 2603
11.3%
0 2515
10.9%
1 2496
10.8%
3 2172
9.4%
4 1674
7.3%
5 1555
6.8%
6 1214
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 158
69.9%
, 21
 
9.3%
/ 20
 
8.8%
· 19
 
8.4%
& 4
 
1.8%
' 4
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 241
97.6%
[ 6
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 241
97.6%
] 6
 
2.4%
Space Separator
ValueCountFrequency (%)
14940
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111506
73.2%
Common 38791
 
25.5%
Latin 2070
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 19923
17.9%
대 11511
 
10.3%
국 9707
 
8.7%
제 9664
 
8.7%
전 9511
 
8.5%
체 7315
 
6.6%
육 7307
 
6.6%
선 1807
 
1.6%
기 1590
 
1.4%
수 1512
 
1.4%
Other values (304) 31659
28.4%
Latin
ValueCountFrequency (%)
S 281
 
13.6%
K 248
 
12.0%
B 232
 
11.2%
O 104
 
5.0%
A 102
 
4.9%
E 78
 
3.8%
N 73
 
3.5%
I 71
 
3.4%
T 69
 
3.3%
C 63
 
3.0%
Other values (26) 749
36.2%
Common
ValueCountFrequency (%)
14940
38.5%
9 3457
 
8.9%
8 2691
 
6.9%
7 2660
 
6.9%
2 2603
 
6.7%
0 2515
 
6.5%
1 2496
 
6.4%
3 2172
 
5.6%
4 1674
 
4.3%
5 1555
 
4.0%
Other values (14) 2028
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111503
73.2%
ASCII 40766
 
26.8%
Punctuation 76
 
< 0.1%
None 19
 
< 0.1%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 19923
17.9%
대 11511
 
10.3%
국 9707
 
8.7%
제 9664
 
8.7%
전 9511
 
8.5%
체 7315
 
6.6%
육 7307
 
6.6%
선 1807
 
1.6%
기 1590
 
1.4%
수 1512
 
1.4%
Other values (303) 31656
28.4%
ASCII
ValueCountFrequency (%)
14940
36.6%
9 3457
 
8.5%
8 2691
 
6.6%
7 2660
 
6.5%
2 2603
 
6.4%
0 2515
 
6.2%
1 2496
 
6.1%
3 2172
 
5.3%
4 1674
 
4.1%
5 1555
 
3.8%
Other values (48) 4003
 
9.8%
Punctuation
ValueCountFrequency (%)
’ 76
100.0%
None
ValueCountFrequency (%)
· 19
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%

대회시작일
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct1064
Distinct (%)11.8%
Missing954
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean20060550
Minimum0
Maximum20191130
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:49:31.484330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19911009
Q120011013
median20111007
Q320151019
95-th percentile20190620
Maximum20191130
Range20191130
Interquartile range (IQR)140006

Descriptive statistics

Standard deviation639486.12
Coefficient of variation (CV)0.031877796
Kurtosis961.20369
Mean20060550
Median Absolute Deviation (MAD)59715.5
Skewness-30.723202
Sum1.8146774 × 1011
Variance4.089425 × 1011
MonotonicityNot monotonic
2023-12-12T17:49:31.680593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161008 65
 
0.7%
20171021 63
 
0.6%
19980928 61
 
0.6%
20091021 60
 
0.6%
20190622 57
 
0.6%
19921011 57
 
0.6%
20121012 55
 
0.5%
20151017 55
 
0.5%
20161009 55
 
0.5%
19980926 54
 
0.5%
Other values (1054) 8464
84.6%
(Missing) 954
 
9.5%
ValueCountFrequency (%)
0 9
0.1%
19740514 2
 
< 0.1%
19770329 1
 
< 0.1%
19770914 1
 
< 0.1%
19771011 1
 
< 0.1%
19790515 2
 
< 0.1%
19791012 1
 
< 0.1%
19791210 1
 
< 0.1%
19800428 2
 
< 0.1%
19800911 1
 
< 0.1%
ValueCountFrequency (%)
20191130 1
 
< 0.1%
20191126 1
 
< 0.1%
20191118 30
0.3%
20191116 16
0.2%
20191027 1
 
< 0.1%
20191023 1
 
< 0.1%
20191022 1
 
< 0.1%
20191013 1
 
< 0.1%
20191010 23
0.2%
20191009 23
0.2%

대회종료일
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct1034
Distinct (%)11.4%
Missing965
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean20062396
Minimum0
Maximum29171112
Zeros9
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T17:49:31.859185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19911009
Q120011013
median20111007
Q320151019
95-th percentile20190623
Maximum29171112
Range29171112
Interquartile range (IQR)140006

Descriptive statistics

Standard deviation654057.88
Coefficient of variation (CV)0.032601185
Kurtosis887.83803
Mean20062396
Median Absolute Deviation (MAD)59723
Skewness-28.160156
Sum1.8126375 × 1011
Variance4.2779171 × 1011
MonotonicityNot monotonic
2023-12-12T17:49:32.017814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20171021 63
 
0.6%
19980928 61
 
0.6%
20161008 60
 
0.6%
20151018 59
 
0.6%
19921011 57
 
0.6%
20161009 57
 
0.6%
19980926 54
 
0.5%
20021111 54
 
0.5%
19971009 52
 
0.5%
20181013 52
 
0.5%
Other values (1024) 8466
84.7%
(Missing) 965
 
9.7%
ValueCountFrequency (%)
0 9
0.1%
19740519 2
 
< 0.1%
19770403 1
 
< 0.1%
19770917 1
 
< 0.1%
19771015 1
 
< 0.1%
19790519 2
 
< 0.1%
19791017 1
 
< 0.1%
19791214 1
 
< 0.1%
19800503 2
 
< 0.1%
19800914 1
 
< 0.1%
ValueCountFrequency (%)
29171112 2
 
< 0.1%
20191201 2
 
< 0.1%
20191122 30
0.3%
20191118 4
 
< 0.1%
20191117 12
 
0.1%
20191103 1
 
< 0.1%
20191030 1
 
< 0.1%
20191027 1
 
< 0.1%
20191013 1
 
< 0.1%
20191010 30
0.3%

대회장소
Text

MISSING 

Distinct976
Distinct (%)10.8%
Missing978
Missing (%)9.8%
Memory size156.2 KiB
2023-12-12T17:49:32.317866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length32
Mean length8.9961206
Min length1

Characters and Unicode

Total characters81163
Distinct characters431
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

Unique325 ?
Unique (%)3.6%

Sample

1st row성남실내체육관
2nd row전남 해남군 우슬체육관
3rd row경상북도, 김천시
4th row동국대체육관
5th row강릉실내종합체육관
ValueCountFrequency (%)
체육관 390
 
3.0%
제주관광대체육관 378
 
2.9%
강원도 324
 
2.5%
전라남도 290
 
2.2%
경상북도 263
 
2.0%
실내체육관 222
 
1.7%
우슬체육관 198
 
1.5%
해남군 197
 
1.5%
전라북도 166
 
1.3%
전남 161
 
1.2%
Other values (1053) 10583
80.3%
2023-12-12T17:49:32.789245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
육 6902
 
8.5%
체 6861
 
8.5%
관 6742
 
8.3%
4240
 
5.2%
대 2352
 
2.9%
전 1532
 
1.9%
시 1515
 
1.9%
경 1507
 
1.9%
남 1497
 
1.8%
도 1454
 
1.8%
Other values (421) 46561
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73670
90.8%
Space Separator 4267
 
5.3%
Other Punctuation 959
 
1.2%
Uppercase Letter 613
 
0.8%
Decimal Number 469
 
0.6%
Open Punctuation 392
 
0.5%
Close Punctuation 392
 
0.5%
Lowercase Letter 269
 
0.3%
Dash Punctuation 132
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
육 6902
 
9.4%
체 6861
 
9.3%
관 6742
 
9.2%
대 2352
 
3.2%
전 1532
 
2.1%
시 1515
 
2.1%
경 1507
 
2.0%
남 1497
 
2.0%
도 1454
 
2.0%
원 1405
 
1.9%
Other values (362) 41903
56.9%
Uppercase Letter
ValueCountFrequency (%)
B 155
25.3%
C 112
18.3%
S 61
 
10.0%
Ａ 56
 
9.1%
Ｃ 40
 
6.5%
I 32
 
5.2%
Ｂ 31
 
5.1%
D 29
 
4.7%
K 29
 
4.7%
O 11
 
1.8%
Other values (11) 57
 
9.3%
Lowercase Letter
ValueCountFrequency (%)
m 62
23.0%
a 27
10.0%
r 26
9.7%
o 20
 
7.4%
n 19
 
7.1%
i 16
 
5.9%
u 15
 
5.6%
t 14
 
5.2%
p 12
 
4.5%
c 12
 
4.5%
Other values (11) 46
17.1%
Decimal Number
ValueCountFrequency (%)
2 350
74.6%
0 98
 
20.9%
1 15
 
3.2%
3 4
 
0.9%
4 1
 
0.2%
6 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 735
76.6%
. 164
 
17.1%
/ 54
 
5.6%
& 3
 
0.3%
· 3
 
0.3%
Space Separator
ValueCountFrequency (%)
4240
99.4%
　 27
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
－ 126
95.5%
- 6
 
4.5%
Open Punctuation
ValueCountFrequency (%)
( 392
100.0%
Close Punctuation
ValueCountFrequency (%)
) 392
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73670
90.8%
Common 6611
 
8.1%
Latin 882
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
육 6902
 
9.4%
체 6861
 
9.3%
관 6742
 
9.2%
대 2352
 
3.2%
전 1532
 
2.1%
시 1515
 
2.1%
경 1507
 
2.0%
남 1497
 
2.0%
도 1454
 
2.0%
원 1405
 
1.9%
Other values (362) 41903
56.9%
Latin
ValueCountFrequency (%)
B 155
17.6%
C 112
12.7%
m 62
 
7.0%
S 61
 
6.9%
Ａ 56
 
6.3%
Ｃ 40
 
4.5%
I 32
 
3.6%
Ｂ 31
 
3.5%
D 29
 
3.3%
K 29
 
3.3%
Other values (32) 275
31.2%
Common
ValueCountFrequency (%)
4240
64.1%
, 735
 
11.1%
( 392
 
5.9%
) 392
 
5.9%
2 350
 
5.3%
. 164
 
2.5%
－ 126
 
1.9%
0 98
 
1.5%
/ 54
 
0.8%
　 27
 
0.4%
Other values (7) 33
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73670
90.8%
ASCII 7210
 
8.9%
None 283
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
육 6902
 
9.4%
체 6861
 
9.3%
관 6742
 
9.2%
대 2352
 
3.2%
전 1532
 
2.1%
시 1515
 
2.1%
경 1507
 
2.0%
남 1497
 
2.0%
도 1454
 
2.0%
원 1405
 
1.9%
Other values (362) 41903
56.9%
ASCII
ValueCountFrequency (%)
4240
58.8%
, 735
 
10.2%
( 392
 
5.4%
) 392
 
5.4%
2 350
 
4.9%
. 164
 
2.3%
B 155
 
2.1%
C 112
 
1.6%
0 98
 
1.4%
m 62
 
0.9%
Other values (43) 510
 
7.1%
None
ValueCountFrequency (%)
－ 126
44.5%
Ａ 56
19.8%
Ｃ 40
 
14.1%
Ｂ 31
 
11.0%
　 27
 
9.5%
· 3
 
1.1%

대회구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
국내 대회
9198 
국제 대회
 
507
국내 체전대회
 
161
대회
 
108
체전대회
 
26

Length

Max length7
Median length5
Mean length5.0106
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국내 대회
2nd row국내 대회
3rd row국내 대회
4th row국내 대회
5th row국내 대회

Common Values

ValueCountFrequency (%)
국내 대회 9198
92.0%
국제 대회 507
 
5.1%
국내 체전대회 161
 
1.6%
대회 108
 
1.1%
체전대회 26
 
0.3%

Length

2023-12-12T17:49:32.938235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:49:33.041344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대회 9813
49.4%
국내 9359
47.1%
국제 507
 
2.6%
체전대회 187
 
0.9%

성별
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
3903 
-
2629 
<NA>
1842 
여
1503 
혼성
 
65

Length

Max length4
Median length1
Mean length1.5591
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row<NA>
3rd row여
4th row-
5th row여

Common Values

ValueCountFrequency (%)
남 3903
39.0%
- 2629
26.3%
<NA> 1842
18.4%
여 1503
 
15.0%
혼성 65
 
0.7%
3 58
 
0.6%

Length

2023-12-12T17:49:33.170635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:49:33.294254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 3903
39.0%
2629
26.3%
na 1842
18.4%
여 1503
 
15.0%
혼성 65
 
0.7%
3 58
 
0.6%

Interactions

2023-12-12T17:49:27.465603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:49:27.196377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:49:27.657783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:49:27.328358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:49:33.374079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종목명대회시작일대회종료일대회구분성별
종목명1.0000.0470.1610.7470.819
대회시작일0.0471.0001.0000.0000.000
대회종료일0.1611.0001.0000.0000.164
대회구분0.7470.0000.0001.0000.116
성별0.8190.0000.1640.1161.000
2023-12-12T17:49:33.488958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종목명성별대회구분
종목명1.0000.5080.426
성별0.5081.0000.095
대회구분0.4260.0951.000
2023-12-12T17:49:33.601956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대회시작일대회종료일종목명대회구분성별
대회시작일1.0001.0000.0370.0000.000
대회종료일1.0001.0000.0840.0000.124
종목명0.0370.0841.0000.4260.508
대회구분0.0000.0000.4261.0000.095
성별0.0000.1240.5080.0951.000

Missing values

2023-12-12T17:49:27.912681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:49:28.123009image/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.
2023-12-12T17:49:28.311403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

종목명종별명세부종목명대회명대회시작일대회종료일대회장소대회구분성별
42375레슬링일반그레꼬로만형　１３０ＫＧ급-준준결승경기２제70회 전국체육대회1989092719890927성남실내체육관국내 대회-
31664레슬링남자고등부F76kg양정모올림픽제패기념 제38회 KBS배 전국레슬링대회2013061820130622전남 해남군 우슬체육관국내 대회<NA>
51674롤러여자초등부(5,6학년)E3,000m제36회 전국남녀종별롤러경기대회2017033020170402경상북도, 김천시국내 대회여
42720레슬링일반그레꼬로만형　６８ＫＧ급-예선경기４제76회 전국체육대회1995100319951003동국대체육관국내 대회-
39560레슬링여고자유형67kg급-준준결승경기４제96회 전국체육대회2015101920151019강릉실내종합체육관국내 대회여
50926롤러여자일반부3000m계주제94회 전국체육대회2013101920131021인천 동춘롤러경기장국내 체전대회여
49703롤러남자초등부B(1,2학년)스피드200mO.R제23회 문화체육관광부장관배 전국시도대항 롤러경기대회2011072820110731김천롤러경기장국내 대회남
59818배드민턴남일개인복식-준결승경기１제90회 전국체육대회2009102220091022도솔체육관국내 대회남
22104레슬링남고그레꼬로만형５８ＫＧ급-예선경기４제84회 전국체육대회2003101120031011전주실내체육관국내 대회남
30962레슬링남일자유형97KG급-준준결승경기３제97회 전국체육대회2016100820161008이순신빙상장.체육관국내 대회남
종목명종별명세부종목명대회명대회시작일대회종료일대회장소대회구분성별
22303레슬링남고자유형120kg급-예선경기２제98회 전국체육대회2017102620171026호암 제2체육관국내 대회남
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