Overview

Dataset statistics

Number of variables6
Number of observations128
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory49.0 B

Variable types

Text1
Categorical1
DateTime4

Dataset

Description전남개발공사의 위탁운영 중인 국제자동차경주장 대회의 대회명, 장소, 대회시작일, 대회종료일, 대회시작시간, 대회종료시간에 대한 정보 입니다.
URLhttps://www.data.go.kr/data/15119768/fileData.do

Alerts

대회시작시간 has constant value ""Constant
대회종료시간 has constant value ""Constant

Reproduction

Analysis started2023-12-12 04:58:33.092770
Analysis finished2023-12-12 04:58:33.476503
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대회명
Text

Distinct77
Distinct (%)60.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T13:58:33.663211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length9.265625
Min length3

Characters and Unicode

Total characters1186
Distinct characters126
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)40.6%

Sample

1st row2017-2018 동계 시즌권 대회
2nd rowKSBK 1전
3rd rowKIC-CUP / KSF 공식연습
4th row슈퍼챌린지 1전
5th rowKIC-CUP 1전 / KSF 1전
ValueCountFrequency (%)
kic-cup 19
 
7.6%
ksbk 18
 
7.2%
2전 14
 
5.6%
krrc 13
 
5.2%
1전 12
 
4.8%
3전 9
 
3.6%
슈퍼레이스 7
 
2.8%
7
 
2.8%
5전 7
 
2.8%
knsc 6
 
2.4%
Other values (64) 138
55.2%
2023-12-12T13:58:34.203249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
 
10.3%
K 112
 
9.4%
C 71
 
6.0%
전 67
 
5.6%
S 49
 
4.1%
R 42
 
3.5%
I 27
 
2.3%
스 26
 
2.2%
e 22
 
1.9%
이 20
 
1.7%
Other values (116) 628
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
36.8%
Uppercase Letter 413
34.8%
Space Separator 122
 
10.3%
Lowercase Letter 94
 
7.9%
Decimal Number 68
 
5.7%
Dash Punctuation 20
 
1.7%
Close Punctuation 12
 
1.0%
Open Punctuation 12
 
1.0%
Other Punctuation 9
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 67
 
15.4%
스 26
 
6.0%
이 20
 
4.6%
대 16
 
3.7%
레 13
 
3.0%
슈 12
 
2.8%
페 12
 
2.8%
컵 12
 
2.8%
퍼 12
 
2.8%
회 11
 
2.5%
Other values (70) 235
53.9%
Uppercase Letter
ValueCountFrequency (%)
K 112
27.1%
C 71
17.2%
S 49
11.9%
R 42
 
10.2%
I 27
 
6.5%
P 19
 
4.6%
U 19
 
4.6%
B 18
 
4.4%
F 17
 
4.1%
N 15
 
3.6%
Other values (5) 24
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
e 22
23.4%
a 13
13.8%
r 8
 
8.5%
d 6
 
6.4%
i 6
 
6.4%
o 6
 
6.4%
p 6
 
6.4%
n 4
 
4.3%
s 4
 
4.3%
l 4
 
4.3%
Other values (5) 15
16.0%
Decimal Number
ValueCountFrequency (%)
2 16
23.5%
1 15
22.1%
3 11
16.2%
4 8
11.8%
5 7
10.3%
6 5
 
7.4%
0 2
 
2.9%
7 2
 
2.9%
8 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 7
77.8%
, 1
 
11.1%
& 1
 
11.1%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 507
42.7%
Hangul 436
36.8%
Common 243
20.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 67
 
15.4%
스 26
 
6.0%
이 20
 
4.6%
대 16
 
3.7%
레 13
 
3.0%
슈 12
 
2.8%
페 12
 
2.8%
컵 12
 
2.8%
퍼 12
 
2.8%
회 11
 
2.5%
Other values (70) 235
53.9%
Latin
ValueCountFrequency (%)
K 112
22.1%
C 71
14.0%
S 49
9.7%
R 42
 
8.3%
I 27
 
5.3%
e 22
 
4.3%
P 19
 
3.7%
U 19
 
3.7%
B 18
 
3.6%
F 17
 
3.4%
Other values (20) 111
21.9%
Common
ValueCountFrequency (%)
122
50.2%
- 20
 
8.2%
2 16
 
6.6%
1 15
 
6.2%
) 12
 
4.9%
( 12
 
4.9%
3 11
 
4.5%
4 8
 
3.3%
/ 7
 
2.9%
5 7
 
2.9%
Other values (6) 13
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 750
63.2%
Hangul 436
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
16.3%
K 112
14.9%
C 71
 
9.5%
S 49
 
6.5%
R 42
 
5.6%
I 27
 
3.6%
e 22
 
2.9%
- 20
 
2.7%
P 19
 
2.5%
U 19
 
2.5%
Other values (36) 247
32.9%
Hangul
ValueCountFrequency (%)
전 67
 
15.4%
스 26
 
6.0%
이 20
 
4.6%
대 16
 
3.7%
레 13
 
3.0%
슈 12
 
2.8%
페 12
 
2.8%
컵 12
 
2.8%
퍼 12
 
2.8%
회 11
 
2.5%
Other values (70) 235
53.9%

장소
Categorical

Distinct8
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
상설트랙
45 
상설서킷
27 
상설 서킷
24 
F1트랙
17 
제2트랙
6 
Other values (3)
9 

Length

Max length5
Median length4
Mean length4.1796875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row상설 서킷
2nd row상설 서킷
3rd row상설 서킷
4th row상설트랙
5th row상설 서킷

Common Values

ValueCountFrequency (%)
상설트랙 45
35.2%
상설서킷 27
21.1%
상설 서킷 24
18.8%
F1트랙 17
 
13.3%
제2트랙 6
 
4.7%
카트장 4
 
3.1%
F1 트랙 3
 
2.3%
F1서킷 2
 
1.6%

Length

2023-12-12T13:58:34.390012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:58:34.521738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설트랙 45
29.0%
상설서킷 27
17.4%
상설 24
15.5%
서킷 24
15.5%
f1트랙 17
 
11.0%
제2트랙 6
 
3.9%
카트장 4
 
2.6%
f1 3
 
1.9%
트랙 3
 
1.9%
f1서킷 2
 
1.3%

대회시작일
Date

Distinct125
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-03-03 00:00:00
Maximum2023-06-11 00:00:00
2023-12-12T13:58:34.672139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:58:34.831524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대회종료일
Date

Distinct125
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2018-03-04 00:00:00
Maximum2023-06-11 00:00:00
2023-12-12T13:58:34.981288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:58:35.128184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대회시작시간
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-12-12 09:00:00
Maximum2023-12-12 09:00:00
2023-12-12T13:58:35.242426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:58:35.358510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

대회종료시간
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-12-12 18:00:00
Maximum2023-12-12 18:00:00
2023-12-12T13:58:35.463801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:58:35.580183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T13:58:35.655059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대회명장소
대회명1.0000.959
장소0.9591.000

Missing values

2023-12-12T13:58:33.317246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:58:33.430313image/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

대회명장소대회시작일대회종료일대회시작시간대회종료시간
02017-2018 동계 시즌권 대회상설 서킷2018-03-032018-03-0409:0018:00
1KSBK 1전상설 서킷2018-03-172018-03-1809:0018:00
2KIC-CUP / KSF 공식연습상설 서킷2018-03-242018-03-2509:0018:00
3슈퍼챌린지 1전상설트랙2018-03-312018-04-0109:0018:00
4KIC-CUP 1전 / KSF 1전상설 서킷2018-04-072018-04-0809:0018:00
5넥센타이어 스피드레이싱 엔페라컵 1전상설 서킷2018-04-142018-04-1509:0018:00
6KNSC 1전상설 서킷2018-04-212018-04-2209:0018:00
7슈퍼레이스 챔피언십 2전F1 트랙2018-05-042018-05-0609:0018:00
8넥센타이어 스피드레이싱 엔페라컵 2전상설 서킷2018-05-122018-05-1309:0018:00
9KIC-CUP 2전 / KSF 2전상설 서킷2018-05-192018-05-2009:0018:00
대회명장소대회시작일대회종료일대회시작시간대회종료시간
118KMRC(카트장)카트장2023-04-092023-04-0909:0018:00
119KMG상설서킷2023-04-152023-04-1609:0018:00
120KIC컵상설서킷2023-04-222023-04-2309:0018:00
121현대N상설서킷2023-04-292023-04-3009:0018:00
122이륜차보급협회상설서킷2023-05-062023-05-0709:0018:00
123KIC카트대회(카트장)카트장2023-05-142023-05-1409:0018:00
124이륜차보급협회상설서킷2023-05-202023-05-2109:0018:00
125KMG상설서킷2023-05-272023-05-2809:0018:00
126KMRC(카트장)카트장2023-06-042023-06-0409:0018:00
127KIC카트대회(카트장)카트장2023-06-112023-06-1109:0018:00