Overview

Dataset statistics

Number of variables12
Number of observations100
Missing cells45
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory99.3 B

Variable types

Text3
Categorical6
Numeric2
Boolean1

Alerts

partcpt_scale_value is highly overall correlated with game_begin_de and 6 other fieldsHigh correlation
game_flag_nm is highly overall correlated with game_begin_de and 6 other fieldsHigh correlation
asoc_nm is highly overall correlated with game_begin_de and 7 other fieldsHigh correlation
subitem_nm is highly overall correlated with game_begin_de and 7 other fieldsHigh correlation
intrl_game_at is highly overall correlated with game_begin_de and 7 other fieldsHigh correlation
game_aprvl_nm is highly overall correlated with asoc_nm and 5 other fieldsHigh correlation
item_nm is highly overall correlated with game_begin_de and 7 other fieldsHigh correlation
game_begin_de is highly overall correlated with game_end_de and 6 other fieldsHigh correlation
game_end_de is highly overall correlated with game_begin_de and 6 other fieldsHigh correlation
game_end_de has 2 (2.0%) missing valuesMissing
opar_nm has 41 (41.0%) missing valuesMissing
hmpg_url has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:53:18.984195
Analysis finished2023-12-10 09:53:22.672422
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

game_nm
Text

Distinct84
Distinct (%)84.8%
Missing1
Missing (%)1.0%
Memory size932.0 B
2023-12-10T18:53:23.046326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length27
Mean length17.575758
Min length3

Characters and Unicode

Total characters1740
Distinct characters229
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)72.7%

Sample

1st rowWKBL 총재배 춘계 전국여자중고농구 경산대회
2nd row한.일 국가대항 학생사이클경기대회
3rd row해외 경기 실적 연계
4th row구미 새마을 전국 산악 챌린저대회
5th row여자 기계체조 주니어 평가전
ValueCountFrequency (%)
주말리그 40
 
12.9%
고교야구 20
 
6.5%
고교 14
 
4.5%
전국고교야구대회 10
 
3.2%
전반기 10
 
3.2%
후반기 10
 
3.2%
겸 7
 
2.3%
왕중왕전 5
 
1.6%
국가대표 5
 
1.6%
선발전 5
 
1.6%
Other values (149) 184
59.4%
2023-12-10T18:53:24.240684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
 
12.2%
대 92
 
5.3%
전 69
 
4.0%
기 65
 
3.7%
회 63
 
3.6%
주 48
 
2.8%
리 48
 
2.8%
고 47
 
2.7%
교 47
 
2.7%
그 42
 
2.4%
Other values (219) 1007
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1394
80.1%
Space Separator 212
 
12.2%
Open Punctuation 39
 
2.2%
Close Punctuation 39
 
2.2%
Other Punctuation 26
 
1.5%
Decimal Number 16
 
0.9%
Uppercase Letter 13
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 92
 
6.6%
전 69
 
4.9%
기 65
 
4.7%
회 63
 
4.5%
주 48
 
3.4%
리 48
 
3.4%
고 47
 
3.4%
교 47
 
3.4%
그 42
 
3.0%
구 42
 
3.0%
Other values (196) 831
59.6%
Uppercase Letter
ValueCountFrequency (%)
K 3
23.1%
A 2
15.4%
W 2
15.4%
B 1
 
7.7%
L 1
 
7.7%
E 1
 
7.7%
T 1
 
7.7%
R 1
 
7.7%
F 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
· 13
50.0%
, 5
 
19.2%
& 4
 
15.4%
. 3
 
11.5%
! 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
0 6
37.5%
2 4
25.0%
1 3
18.8%
8 2
 
12.5%
4 1
 
6.2%
Space Separator
ValueCountFrequency (%)
212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1393
80.1%
Common 333
 
19.1%
Latin 13
 
0.7%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 92
 
6.6%
전 69
 
5.0%
기 65
 
4.7%
회 63
 
4.5%
주 48
 
3.4%
리 48
 
3.4%
고 47
 
3.4%
교 47
 
3.4%
그 42
 
3.0%
구 42
 
3.0%
Other values (195) 830
59.6%
Common
ValueCountFrequency (%)
212
63.7%
( 39
 
11.7%
) 39
 
11.7%
· 13
 
3.9%
0 6
 
1.8%
, 5
 
1.5%
& 4
 
1.2%
2 4
 
1.2%
. 3
 
0.9%
1 3
 
0.9%
Other values (4) 5
 
1.5%
Latin
ValueCountFrequency (%)
K 3
23.1%
A 2
15.4%
W 2
15.4%
B 1
 
7.7%
L 1
 
7.7%
E 1
 
7.7%
T 1
 
7.7%
R 1
 
7.7%
F 1
 
7.7%
Han
ValueCountFrequency (%)
故 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1390
79.9%
ASCII 333
 
19.1%
None 13
 
0.7%
Compat Jamo 3
 
0.2%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
63.7%
( 39
 
11.7%
) 39
 
11.7%
0 6
 
1.8%
, 5
 
1.5%
& 4
 
1.2%
2 4
 
1.2%
. 3
 
0.9%
K 3
 
0.9%
1 3
 
0.9%
Other values (12) 15
 
4.5%
Hangul
ValueCountFrequency (%)
대 92
 
6.6%
전 69
 
5.0%
기 65
 
4.7%
회 63
 
4.5%
주 48
 
3.5%
리 48
 
3.5%
고 47
 
3.4%
교 47
 
3.4%
그 42
 
3.0%
구 42
 
3.0%
Other values (194) 827
59.5%
None
ValueCountFrequency (%)
· 13
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 3
100.0%
CJK
ValueCountFrequency (%)
故 1
100.0%

asoc_nm
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
대한야구소프트볼협회
52 
대한육상경기연맹
12 
대한스키협회(사)
 
5
대한자전거연맹
 
4
대한체조협회(사)
 
4
Other values (16)
23 

Length

Max length16
Median length10
Mean length9.31
Min length6

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row대한민국배구협회
2nd row대한농구협회
3rd row대한자전거연맹
4th row대한펜싱협회(사)
5th row대한자전거연맹

Common Values

ValueCountFrequency (%)
대한야구소프트볼협회 52
52.0%
대한육상경기연맹 12
 
12.0%
대한스키협회(사) 5
 
5.0%
대한자전거연맹 4
 
4.0%
대한체조협회(사) 4
 
4.0%
대한펜싱협회(사) 3
 
3.0%
대한복싱협회 3
 
3.0%
대한테니스협회(사) 2
 
2.0%
대한농구협회 2
 
2.0%
대한유도회(사) 2
 
2.0%
Other values (11) 11
 
11.0%

Length

2023-12-10T18:53:24.574060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대한야구소프트볼협회 52
52.0%
대한육상경기연맹 12
 
12.0%
대한스키협회(사 5
 
5.0%
대한자전거연맹 4
 
4.0%
대한체조협회(사 4
 
4.0%
대한펜싱협회(사 3
 
3.0%
대한복싱협회 3
 
3.0%
대한테니스협회(사 2
 
2.0%
대한농구협회 2
 
2.0%
대한유도회(사 2
 
2.0%
Other values (11) 11
 
11.0%

item_nm
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
야구
52 
육상
12 
스키(알파인)
 
5
사이클
 
4
체조
 
4
Other values (16)
23 

Length

Max length7
Median length2
Mean length2.51
Min length2

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row배구
2nd row농구
3rd row사이클
4th row펜싱
5th row사이클

Common Values

ValueCountFrequency (%)
야구 52
52.0%
육상 12
 
12.0%
스키(알파인) 5
 
5.0%
사이클 4
 
4.0%
체조 4
 
4.0%
펜싱 3
 
3.0%
복싱 3
 
3.0%
테니스 2
 
2.0%
농구 2
 
2.0%
유도 2
 
2.0%
Other values (11) 11
 
11.0%

Length

2023-12-10T18:53:24.835985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
야구 52
52.0%
육상 12
 
12.0%
스키(알파인 5
 
5.0%
사이클 4
 
4.0%
체조 4
 
4.0%
펜싱 3
 
3.0%
복싱 3
 
3.0%
테니스 2
 
2.0%
농구 2
 
2.0%
유도 2
 
2.0%
Other values (11) 11
 
11.0%

subitem_nm
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
야구
52 
육상
12 
사이클
 
4
체조
 
4
펜싱
 
3
Other values (19)
25 

Length

Max length10
Median length2
Mean length2.64
Min length2

Unique

Unique14 ?
Unique (%)14.0%

Sample

1st row배구
2nd row농구
3rd row사이클
4th row펜싱
5th row사이클

Common Values

ValueCountFrequency (%)
야구 52
52.0%
육상 12
 
12.0%
사이클 4
 
4.0%
체조 4
 
4.0%
펜싱 3
 
3.0%
복싱 3
 
3.0%
테니스 2
 
2.0%
농구 2
 
2.0%
유도 2
 
2.0%
스키(알파인) 2
 
2.0%
Other values (14) 14
 
14.0%

Length

2023-12-10T18:53:25.135437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
야구 52
52.0%
육상 12
 
12.0%
사이클 4
 
4.0%
체조 4
 
4.0%
펜싱 3
 
3.0%
복싱 3
 
3.0%
테니스 2
 
2.0%
농구 2
 
2.0%
유도 2
 
2.0%
스키(알파인 2
 
2.0%
Other values (14) 14
 
14.0%

game_begin_de
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)68.7%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean20144110
Minimum19880723
Maximum20210819
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:25.391761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880723
5-th percentile19998314
Q120110366
median20151103
Q320200620
95-th percentile20210536
Maximum20210819
Range330096
Interquartile range (IQR)90254

Descriptive statistics

Standard deviation68000.184
Coefficient of variation (CV)0.0033756857
Kurtosis1.6981575
Mean20144110
Median Absolute Deviation (MAD)49517
Skewness-1.3005499
Sum1.9942669 × 109
Variance4.6240251 × 109
MonotonicityNot monotonic
2023-12-10T18:53:25.703608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140531 7
 
7.0%
20140322 7
 
7.0%
20210417 5
 
5.0%
20200620 5
 
5.0%
20210529 5
 
5.0%
20200801 5
 
5.0%
19980228 2
 
2.0%
20191226 2
 
2.0%
20100225 2
 
2.0%
20100408 1
 
1.0%
Other values (58) 58
58.0%
ValueCountFrequency (%)
19880723 1
1.0%
19980222 1
1.0%
19980225 1
1.0%
19980228 2
2.0%
20000324 1
1.0%
20031026 1
1.0%
20031129 1
1.0%
20051008 1
1.0%
20051023 1
1.0%
20051204 1
1.0%
ValueCountFrequency (%)
20210819 1
 
1.0%
20210818 1
 
1.0%
20210813 1
 
1.0%
20210706 1
 
1.0%
20210601 1
 
1.0%
20210529 5
5.0%
20210417 5
5.0%
20201121 1
 
1.0%
20201026 1
 
1.0%
20201016 1
 
1.0%

game_end_de
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct68
Distinct (%)69.4%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean20143886
Minimum19880723
Maximum20210829
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:53:26.012681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880723
5-th percentile19997310
Q120110405
median20150611
Q320200726
95-th percentile20210704
Maximum20210829
Range330106
Interquartile range (IQR)90321.25

Descriptive statistics

Standard deviation68318.319
Coefficient of variation (CV)0.0033915164
Kurtosis1.6433257
Mean20143886
Median Absolute Deviation (MAD)50115
Skewness-1.2855284
Sum1.9741008 × 109
Variance4.6673928 × 109
MonotonicityNot monotonic
2023-12-10T18:53:26.358619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20140504 7
 
7.0%
20140629 7
 
7.0%
20210523 5
 
5.0%
20200726 5
 
5.0%
20210704 3
 
3.0%
20200906 3
 
3.0%
20191010 2
 
2.0%
20210627 2
 
2.0%
20200913 2
 
2.0%
19980228 2
 
2.0%
Other values (58) 60
60.0%
ValueCountFrequency (%)
19880723 1
1.0%
19980222 1
1.0%
19980225 1
1.0%
19980228 2
2.0%
20000325 1
1.0%
20031026 1
1.0%
20031130 1
1.0%
20051008 1
1.0%
20051023 1
1.0%
20051204 1
1.0%
ValueCountFrequency (%)
20210829 1
 
1.0%
20210822 1
 
1.0%
20210820 1
 
1.0%
20210719 1
 
1.0%
20210704 3
3.0%
20210627 2
 
2.0%
20210614 1
 
1.0%
20210523 5
5.0%
20201124 1
 
1.0%
20201102 2
 
2.0%

opar_nm
Text

MISSING 

Distinct52
Distinct (%)88.1%
Missing41
Missing (%)41.0%
Memory size932.0 B
2023-12-10T18:53:26.917420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.8474576
Min length2

Characters and Unicode

Total characters345
Distinct characters134
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)78.0%

Sample

1st row미정
2nd row전라남도 나주시
3rd row서울
4th row경상북도 구미
5th row태릉선수촌
ValueCountFrequency (%)
서울 3
 
3.8%
태릉선수촌 3
 
3.8%
호주 3
 
3.8%
탄천야구장 2
 
2.5%
알펜시아 2
 
2.5%
체육관 2
 
2.5%
경북 2
 
2.5%
필승 2
 
2.5%
주 2
 
2.5%
광주야구장 2
 
2.5%
Other values (55) 57
71.2%
2023-12-10T18:53:27.715807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
6.1%
구 18
 
5.2%
장 16
 
4.6%
야 15
 
4.3%
주 12
 
3.5%
육 9
 
2.6%
체 9
 
2.6%
시 9
 
2.6%
관 7
 
2.0%
트 6
 
1.7%
Other values (124) 223
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
88.7%
Space Separator 21
 
6.1%
Uppercase Letter 14
 
4.1%
Lowercase Letter 2
 
0.6%
Other Punctuation 1
 
0.3%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 18
 
5.9%
장 16
 
5.2%
야 15
 
4.9%
주 12
 
3.9%
육 9
 
2.9%
체 9
 
2.9%
시 9
 
2.9%
관 7
 
2.3%
트 6
 
2.0%
동 6
 
2.0%
Other values (111) 199
65.0%
Uppercase Letter
ValueCountFrequency (%)
L 3
21.4%
E 2
14.3%
I 2
14.3%
G 2
14.3%
N 2
14.3%
V 1
 
7.1%
S 1
 
7.1%
A 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
f 1
50.0%
d 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
88.7%
Common 23
 
6.7%
Latin 16
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 18
 
5.9%
장 16
 
5.2%
야 15
 
4.9%
주 12
 
3.9%
육 9
 
2.9%
체 9
 
2.9%
시 9
 
2.9%
관 7
 
2.3%
트 6
 
2.0%
동 6
 
2.0%
Other values (111) 199
65.0%
Latin
ValueCountFrequency (%)
L 3
18.8%
E 2
12.5%
I 2
12.5%
G 2
12.5%
N 2
12.5%
V 1
 
6.2%
S 1
 
6.2%
A 1
 
6.2%
f 1
 
6.2%
d 1
 
6.2%
Common
ValueCountFrequency (%)
21
91.3%
/ 1
 
4.3%
3 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
87.8%
ASCII 39
 
11.3%
Compat Jamo 3
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
53.8%
L 3
 
7.7%
E 2
 
5.1%
I 2
 
5.1%
G 2
 
5.1%
N 2
 
5.1%
/ 1
 
2.6%
3 1
 
2.6%
V 1
 
2.6%
S 1
 
2.6%
Other values (3) 3
 
7.7%
Hangul
ValueCountFrequency (%)
구 18
 
5.9%
장 16
 
5.3%
야 15
 
5.0%
주 12
 
4.0%
육 9
 
3.0%
체 9
 
3.0%
시 9
 
3.0%
관 7
 
2.3%
트 6
 
2.0%
동 6
 
2.0%
Other values (110) 196
64.7%
Compat Jamo
ValueCountFrequency (%)
ㅇ 3
100.0%

hmpg_url
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:53:28.282568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length71
Mean length67
Min length64

Characters and Unicode

Total characters6700
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowhttps://result.sports.or.kr/vb/E02.jsp?classCd=08&toCd=MH1401&page=1
2nd rowhttps://result.sports.or.kr/bb/E02.jsp?classCd=07&toCd=201301&page=1
3rd rowhttps://result.sports.or.kr/cy/E02.jsp?classCd=12&toCd=CY10815&page=1
4th rowhttps://result.sports.or.kr/fe/E02.jsp?classCd=25&toCd=COMPM00225&page=1
5th rowhttps://result.sports.or.kr/cy/E02.jsp?classCd=12&toCd=CY10896&page=1
ValueCountFrequency (%)
https://result.sports.or.kr/vb/e02.jsp?classcd=08&tocd=mh1401&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=902&page=1 1
 
1.0%
https://result.sports.or.kr/ju/e02.jsp?classcd=17&tocd=11&page=1 1
 
1.0%
https://result.sports.or.kr/bm/e02.jsp?classcd=26&tocd=3000313&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=766&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=749&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=849&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=906&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=747&page=1 1
 
1.0%
https://result.sports.or.kr/ba/e02.jsp?classcd=04&tocd=816&page=1 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T18:53:29.372051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 710
 
10.6%
t 517
 
7.7%
r 404
 
6.0%
. 400
 
6.0%
p 400
 
6.0%
/ 400
 
6.0%
o 303
 
4.5%
= 300
 
4.5%
0 276
 
4.1%
a 265
 
4.0%
Other values (39) 2725
40.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3906
58.3%
Other Punctuation 1200
 
17.9%
Decimal Number 938
 
14.0%
Uppercase Letter 356
 
5.3%
Math Symbol 300
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 710
18.2%
t 517
13.2%
r 404
10.3%
p 400
10.2%
o 303
7.8%
a 265
 
6.8%
e 206
 
5.3%
l 201
 
5.1%
d 200
 
5.1%
g 104
 
2.7%
Other values (13) 596
15.3%
Decimal Number
ValueCountFrequency (%)
0 276
29.4%
1 207
22.1%
2 158
16.8%
4 89
 
9.5%
8 49
 
5.2%
9 42
 
4.5%
3 33
 
3.5%
5 30
 
3.2%
7 29
 
3.1%
6 25
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
C 205
57.6%
E 102
28.7%
H 15
 
4.2%
T 12
 
3.4%
A 12
 
3.4%
Y 4
 
1.1%
M 3
 
0.8%
P 1
 
0.3%
O 1
 
0.3%
B 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 400
33.3%
/ 400
33.3%
& 200
16.7%
? 100
 
8.3%
: 100
 
8.3%
Math Symbol
ValueCountFrequency (%)
= 300
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4262
63.6%
Common 2438
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 710
16.7%
t 517
12.1%
r 404
9.5%
p 400
9.4%
o 303
 
7.1%
a 265
 
6.2%
e 206
 
4.8%
C 205
 
4.8%
l 201
 
4.7%
d 200
 
4.7%
Other values (23) 851
20.0%
Common
ValueCountFrequency (%)
. 400
16.4%
/ 400
16.4%
= 300
12.3%
0 276
11.3%
1 207
8.5%
& 200
8.2%
2 158
 
6.5%
? 100
 
4.1%
: 100
 
4.1%
4 89
 
3.7%
Other values (6) 208
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 710
 
10.6%
t 517
 
7.7%
r 404
 
6.0%
. 400
 
6.0%
p 400
 
6.0%
/ 400
 
6.0%
o 303
 
4.5%
= 300
 
4.5%
0 276
 
4.1%
a 265
 
4.0%
Other values (39) 2725
40.7%

intrl_game_at
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size232.0 B
False
85 
True
15 
ValueCountFrequency (%)
False 85
85.0%
True 15
 
15.0%
2023-12-10T18:53:29.603139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

partcpt_scale_value
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
60 
50개팀 이하
35 
300명 이하
 
2
50-100개팀
 
2
1000명 이상
 
1

Length

Max length8
Median length4
Mean length5.23
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1000명 이상
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 60
60.0%
50개팀 이하 35
35.0%
300명 이하 2
 
2.0%
50-100개팀 2
 
2.0%
1000명 이상 1
 
1.0%

Length

2023-12-10T18:53:29.929694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:30.272157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
43.5%
이하 37
26.8%
50개팀 35
25.4%
300명 2
 
1.4%
50-100개팀 2
 
1.4%
1000명 1
 
0.7%
이상 1
 
0.7%

game_aprvl_nm
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
60 
기타승인
31 
정부명칭대회
8 
기타
 
1

Length

Max length6
Median length4
Mean length4.14
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 60
60.0%
기타승인 31
31.0%
정부명칭대회 8
 
8.0%
기타 1
 
1.0%

Length

2023-12-10T18:53:30.573074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:30.943325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
60.0%
기타승인 31
31.0%
정부명칭대회 8
 
8.0%
기타 1
 
1.0%

game_flag_nm
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
61 
기타
31 
대통령배
7 
대한체육회장배
 
1

Length

Max length7
Median length4
Mean length3.41
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 61
61.0%
기타 31
31.0%
대통령배 7
 
7.0%
대한체육회장배 1
 
1.0%

Length

2023-12-10T18:53:31.289840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:53:31.560934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 61
61.0%
기타 31
31.0%
대통령배 7
 
7.0%
대한체육회장배 1
 
1.0%

Interactions

2023-12-10T18:53:21.364532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:20.954683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:21.568894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T18:53:21.159321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:53:31.762871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
game_nmasoc_nmitem_nmsubitem_nmgame_begin_degame_end_deopar_nmhmpg_urlintrl_game_atpartcpt_scale_valuegame_aprvl_nmgame_flag_nm
game_nm1.0001.0001.0001.0001.0001.0000.9651.0001.0001.0001.0001.000
asoc_nm1.0001.0001.0001.0000.8920.8870.9731.0000.8690.9780.6860.936
item_nm1.0001.0001.0001.0000.8920.8870.9731.0000.8690.9780.6860.936
subitem_nm1.0001.0001.0001.0000.8990.8960.9811.0000.9720.9780.6860.936
game_begin_de1.0000.8920.8920.8991.0001.0000.9611.0000.6280.8660.1421.000
game_end_de1.0000.8870.8870.8961.0001.0000.9611.0000.6270.8660.1421.000
opar_nm0.9650.9730.9730.9810.9610.9611.0001.0000.8791.0001.0000.000
hmpg_url1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
intrl_game_at1.0000.8690.8690.9720.6280.6270.8791.0001.0001.0001.000NaN
partcpt_scale_value1.0000.9780.9780.9780.8660.8661.0001.0001.0001.0000.6660.796
game_aprvl_nm1.0000.6860.6860.6860.1420.1421.0001.0001.0000.6661.0001.000
game_flag_nm1.0000.9360.9360.9361.0001.0000.0001.000NaN0.7961.0001.000
2023-12-10T18:53:32.055747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
partcpt_scale_valuegame_flag_nmasoc_nmsubitem_nmintrl_game_atgame_aprvl_nmitem_nm
partcpt_scale_value1.0000.4580.7990.7990.9730.6840.799
game_flag_nm0.4581.0000.6900.6901.0000.9860.690
asoc_nm0.7990.6901.0000.9810.7250.7091.000
subitem_nm0.7990.6900.9811.0000.7690.7090.981
intrl_game_at0.9731.0000.7250.7691.0000.9870.725
game_aprvl_nm0.6840.9860.7090.7090.9871.0000.709
item_nm0.7990.6901.0000.9810.7250.7091.000
2023-12-10T18:53:32.269327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
game_begin_degame_end_deasoc_nmitem_nmsubitem_nmintrl_game_atpartcpt_scale_valuegame_aprvl_nmgame_flag_nm
game_begin_de1.0000.9990.5420.5420.5420.6520.6490.2290.986
game_end_de0.9991.0000.5330.5330.5340.6500.6490.2290.986
asoc_nm0.5420.5331.0001.0000.9810.7250.7990.7090.690
item_nm0.5420.5331.0001.0000.9810.7250.7990.7090.690
subitem_nm0.5420.5340.9810.9811.0000.7690.7990.7090.690
intrl_game_at0.6520.6500.7250.7250.7691.0000.9730.9871.000
partcpt_scale_value0.6490.6490.7990.7990.7990.9731.0000.6840.458
game_aprvl_nm0.2290.2290.7090.7090.7090.9870.6841.0000.986
game_flag_nm0.9860.9860.6900.6900.6901.0000.4580.9861.000

Missing values

2023-12-10T18:53:21.875036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:53:22.237156image/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.
2023-12-10T18:53:22.493480image/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

game_nmasoc_nmitem_nmsubitem_nmgame_begin_degame_end_deopar_nmhmpg_urlintrl_game_atpartcpt_scale_valuegame_aprvl_nmgame_flag_nm
0<NA>대한민국배구협회배구배구<NA><NA><NA>https://result.sports.or.kr/vb/E02.jsp?classCd=08&toCd=MH1401&page=1N<NA><NA><NA>
1WKBL 총재배 춘계 전국여자중고농구 경산대회대한농구협회농구농구2013012120130128미정https://result.sports.or.kr/bb/E02.jsp?classCd=07&toCd=201301&page=1N<NA><NA><NA>
2한.일 국가대항 학생사이클경기대회대한자전거연맹사이클사이클2015110320151104전라남도 나주시https://result.sports.or.kr/cy/E02.jsp?classCd=12&toCd=CY10815&page=1N<NA><NA><NA>
3해외 경기 실적 연계대한펜싱협회(사)펜싱펜싱2018121820181227서울https://result.sports.or.kr/fe/E02.jsp?classCd=25&toCd=COMPM00225&page=1Y1000명 이상기타<NA>
4구미 새마을 전국 산악 챌린저대회대한자전거연맹사이클사이클2017090320170903경상북도 구미https://result.sports.or.kr/cy/E02.jsp?classCd=12&toCd=CY10896&page=1N<NA><NA><NA>
5여자 기계체조 주니어 평가전대한체조협회(사)체조체조2010022520100225태릉선수촌https://result.sports.or.kr/gy/E02.jsp?classCd=23&toCd=200999&page=1N<NA><NA><NA>
6고교 주말리그 전반기(경기&인천권)대한야구소프트볼협회야구야구2014032220140504LNG야구장https://result.sports.or.kr/ba/E02.jsp?classCd=04&toCd=14H10&page=1N<NA><NA><NA>
7WKF KARATE1 월드컵 - 부산 2012대한카라테연맹<준>카라테카라테2012081820120819부산광역시 사직실내체육관https://result.sports.or.kr/kr/E02.jsp?classCd=52&toCd=201208&page=1Y<NA><NA><NA>
8고교 주말리그 후반기(경기&인천권)대한야구소프트볼협회야구야구2014053120140629탄천야구장https://result.sports.or.kr/ba/E02.jsp?classCd=04&toCd=14H19&page=1N<NA><NA><NA>
9고교 주말리그 후반기(남부&경상권)대한야구소프트볼협회야구야구2014053120140629삼원야구장https://result.sports.or.kr/ba/E02.jsp?classCd=04&toCd=14H15&page=1N<NA><NA><NA>
game_nmasoc_nmitem_nmsubitem_nmgame_begin_degame_end_deopar_nmhmpg_urlintrl_game_atpartcpt_scale_valuegame_aprvl_nmgame_flag_nm
90스포츠토토와 함께하는 국민체육진흥공단이사장배 전국초등학교핸드볼대회대한핸드볼협회(사)핸드볼핸드볼2009112020091124경북 안동https://result.sports.or.kr/hb/E02.jsp?classCd=10&toCd=200901&page=1N<NA><NA><NA>
91민족평화축전 하프마라톤대회대한육상경기연맹육상육상2003102620031026제주https://result.sports.or.kr/at/E02.jsp?classCd=AT&toCd=1283001&page=1N<NA><NA><NA>
92전국체육대회(고등부)대한야구소프트볼협회야구야구2019100420191010<NA>https://result.sports.or.kr/ba/E02.jsp?classCd=04&toCd=759&page=1N50개팀 이하기타승인기타
93전국체육대회(일반부)대한야구소프트볼협회야구야구2019100520191010<NA>https://result.sports.or.kr/ba/E02.jsp?classCd=04&toCd=760&page=1N50개팀 이하기타승인기타
94두딘스경보대회대한육상경기연맹육상육상2006032520060325두딘스카https://result.sports.or.kr/at/E02.jsp?classCd=AT&toCd=1354001&page=1Y<NA><NA><NA>
95시드니육상대회대한육상경기연맹육상육상1998022819980228호주 시드니https://result.sports.or.kr/at/E02.jsp?classCd=AT&toCd=1055098&page=1Y<NA><NA><NA>
96호버트육상대회대한육상경기연맹육상육상1998022219980222호주 호버트https://result.sports.or.kr/at/E02.jsp?classCd=AT&toCd=1054098&page=1Y<NA><NA><NA>
97한국항공총재배 전국실내모형항공기대회대한민국항공회<비>항공스포츠항공스포츠2013052620130526한국항공대학교 격납고https://result.sports.or.kr/as/E02.jsp?classCd=61&toCd=201301&page=1N300명 이하정부명칭대회대한체육회장배
98동계체전예행연습대한스키협회(사)스키(알파인)스키(스노보드)2009021220090213성우리조트https://result.sports.or.kr/si/E02.jsp?classCd=9&toCd=xxtest&page=1N<NA><NA><NA>
99함양물레방아축제 장거리 듀애슬론대회대한트라이애슬론연맹(사)트라이애슬론트라이애슬론2005100820051008함양https://result.sports.or.kr/tr/E02.jsp?classCd=40&toCd=88&page=1N<NA><NA><NA>