Overview

Dataset statistics

Number of variables7
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory61.3 B

Variable types

Numeric2
Categorical2
Text2
DateTime1

Dataset

Description인천광역시 남동구 구청장배 제육대회 일정에 관한 데이터로 월별, 종목, 대회명, 개회일시, 장소, 참여인원 등을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15113330/fileData.do

Alerts

연번 is highly overall correlated with 월별High correlation
참여인원 is highly overall correlated with 장소High correlation
월별 is highly overall correlated with 연번High correlation
장소 is highly overall correlated with 참여인원High correlation
연번 has unique valuesUnique
대회명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:33:44.363001
Analysis finished2023-12-12 00:33:45.536288
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T09:33:45.604301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T09:33:45.742831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

월별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
09월
10 
10월
05월
06월
04월
Other values (4)

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row03월
2nd row04월
3rd row04월
4th row04월
5th row04월

Common Values

ValueCountFrequency (%)
09월 10
25.0%
10월 9
22.5%
05월 6
15.0%
06월 5
12.5%
04월 4
 
10.0%
07월 2
 
5.0%
11월 2
 
5.0%
03월 1
 
2.5%
08월 1
 
2.5%

Length

2023-12-12T09:33:45.860162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:45.999137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09월 10
25.0%
10월 9
22.5%
05월 6
15.0%
06월 5
12.5%
04월 4
 
10.0%
07월 2
 
5.0%
11월 2
 
5.0%
03월 1
 
2.5%
08월 1
 
2.5%

종목
Text

Distinct25
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T09:33:46.180593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.025
Min length2

Characters and Unicode

Total characters121
Distinct characters56
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

Unique10 ?
Unique (%)25.0%

Sample

1st row농구
2nd row축구
3rd row테니스
4th row보디빌딩
5th row배드민턴
ValueCountFrequency (%)
농구 2
 
5.0%
그라운드골프 2
 
5.0%
합기도 2
 
5.0%
줄넘기 2
 
5.0%
파크골프 2
 
5.0%
검도 2
 
5.0%
족구 2
 
5.0%
축구 2
 
5.0%
무에타이 2
 
5.0%
태권도 2
 
5.0%
Other values (15) 20
50.0%
2023-12-12T09:33:46.480407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
8.3%
7
 
5.8%
5
 
4.1%
4
 
3.3%
4
 
3.3%
4
 
3.3%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
Other values (46) 74
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
 
8.3%
7
 
5.8%
5
 
4.1%
4
 
3.3%
4
 
3.3%
4
 
3.3%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
Other values (46) 74
61.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10
 
8.3%
7
 
5.8%
5
 
4.1%
4
 
3.3%
4
 
3.3%
4
 
3.3%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
Other values (46) 74
61.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10
 
8.3%
7
 
5.8%
5
 
4.1%
4
 
3.3%
4
 
3.3%
4
 
3.3%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
Other values (46) 74
61.2%

대회명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T09:33:46.679745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17
Min length15

Characters and Unicode

Total characters680
Distinct characters75
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

Unique40 ?
Unique (%)100.0%

Sample

1st row제10회 남동구협협회장배 농구대회
2nd row제33회 남동구청장기 축구대회
3rd row제28회 남동구협회장기 테니스대회
4th row제3회 남동구청장배 보디빌딩대회
5th row제5회 남동구협회장배 배드민턴대회
ValueCountFrequency (%)
남동구협회장기 13
 
10.8%
남동구청장기 13
 
10.8%
남동구청장배 9
 
7.5%
제13회 4
 
3.3%
제4회 4
 
3.3%
남동구협회장배 4
 
3.3%
제23회 3
 
2.5%
제6회 3
 
2.5%
제5회 3
 
2.5%
제10회 3
 
2.5%
Other values (39) 61
50.8%
2023-12-12T09:33:47.030133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
14.4%
80
11.8%
50
 
7.4%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
40
 
5.9%
31
 
4.6%
22
 
3.2%
Other values (65) 199
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 540
79.4%
Space Separator 80
 
11.8%
Decimal Number 60
 
8.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
98
18.1%
50
9.3%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
31
 
5.7%
22
 
4.1%
19
 
3.5%
Other values (54) 120
22.2%
Decimal Number
ValueCountFrequency (%)
2 13
21.7%
1 12
20.0%
3 11
18.3%
8 5
 
8.3%
5 5
 
8.3%
4 5
 
8.3%
0 3
 
5.0%
6 3
 
5.0%
9 2
 
3.3%
7 1
 
1.7%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 540
79.4%
Common 140
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
98
18.1%
50
9.3%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
31
 
5.7%
22
 
4.1%
19
 
3.5%
Other values (54) 120
22.2%
Common
ValueCountFrequency (%)
80
57.1%
2 13
 
9.3%
1 12
 
8.6%
3 11
 
7.9%
8 5
 
3.6%
5 5
 
3.6%
4 5
 
3.6%
0 3
 
2.1%
6 3
 
2.1%
9 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 540
79.4%
ASCII 140
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
98
18.1%
50
9.3%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
40
 
7.4%
31
 
5.7%
22
 
4.1%
19
 
3.5%
Other values (54) 120
22.2%
ASCII
ValueCountFrequency (%)
80
57.1%
2 13
 
9.3%
1 12
 
8.6%
3 11
 
7.9%
8 5
 
3.6%
5 5
 
3.6%
4 5
 
3.6%
0 3
 
2.1%
6 3
 
2.1%
9 2
 
1.4%
Distinct33
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2023-03-18 00:00:00
Maximum2023-11-17 00:00:00
2023-12-12T09:33:47.142855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:47.245242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)

장소
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
남동다목적실내체육관
17 
남동구청 대강당
남동공단근린공원
남동공단근린공원 테니스장
제3호 남동체육광장
Other values (9)
13 

Length

Max length22
Median length13
Mean length9.6
Min length5

Unique

Unique5 ?
Unique (%)12.5%

Sample

1st row남동 어울림체육관
2nd row남동공단근린공원
3rd row남동공단근린공원 테니스장
4th row남동구청 대강당
5th row남동다목적실내체육관

Common Values

ValueCountFrequency (%)
남동다목적실내체육관 17
42.5%
남동구청 대강당 4
 
10.0%
남동공단근린공원 2
 
5.0%
남동공단근린공원 테니스장 2
 
5.0%
제3호 남동체육광장 2
 
5.0%
남동공단 축구장 2
 
5.0%
장수파크골프장 2
 
5.0%
남동다목적운동장 2
 
5.0%
구월체육공원게이트볼장 2
 
5.0%
남동 어울림체육관 1
 
2.5%
Other values (4) 4
 
10.0%

Length

2023-12-12T09:33:47.361845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남동다목적실내체육관 18
32.7%
남동구청 4
 
7.3%
대강당 4
 
7.3%
남동공단근린공원 4
 
7.3%
어울림체육관 2
 
3.6%
남동 2
 
3.6%
구월체육공원게이트볼장 2
 
3.6%
남동다목적운동장 2
 
3.6%
장수파크골프장 2
 
3.6%
축구장 2
 
3.6%
Other values (9) 13
23.6%

참여인원
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean516.6
Minimum50
Maximum1800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T09:33:47.464286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile145
Q1291
median300
Q3625
95-th percentile1515
Maximum1800
Range1750
Interquartile range (IQR)334

Descriptive statistics

Standard deviation443.43859
Coefficient of variation (CV)0.858379
Kurtosis2.2642198
Mean516.6
Median Absolute Deviation (MAD)100
Skewness1.6989431
Sum20664
Variance196637.78
MonotonicityNot monotonic
2023-12-12T09:33:47.567388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
300 11
27.5%
400 6
15.0%
150 2
 
5.0%
1000 2
 
5.0%
1200 2
 
5.0%
700 2
 
5.0%
50 2
 
5.0%
1800 2
 
5.0%
220 2
 
5.0%
600 1
 
2.5%
Other values (8) 8
20.0%
ValueCountFrequency (%)
50 2
 
5.0%
150 2
 
5.0%
180 1
 
2.5%
200 1
 
2.5%
210 1
 
2.5%
220 2
 
5.0%
264 1
 
2.5%
300 11
27.5%
400 6
15.0%
470 1
 
2.5%
ValueCountFrequency (%)
1800 2
 
5.0%
1500 1
 
2.5%
1200 2
 
5.0%
1000 2
 
5.0%
800 1
 
2.5%
700 2
 
5.0%
600 1
 
2.5%
500 1
 
2.5%
470 1
 
2.5%
400 6
15.0%

Interactions

2023-12-12T09:33:45.168636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:44.666509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:45.266956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:44.773919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:33:47.653551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번월별종목대회명개회일시장소참여인원
연번1.0000.8730.0001.0000.9900.0000.000
월별0.8731.0000.0001.0001.0000.0000.492
종목0.0000.0001.0001.0000.3920.9790.906
대회명1.0001.0001.0001.0001.0001.0001.000
개회일시0.9901.0000.3921.0001.0000.0000.000
장소0.0000.0000.9791.0000.0001.0000.868
참여인원0.0000.4920.9061.0000.0000.8681.000
2023-12-12T09:33:47.750086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월별장소
월별1.0000.000
장소0.0001.000
2023-12-12T09:33:47.835203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번참여인원월별장소
연번1.000-0.2970.6310.000
참여인원-0.2971.0000.1580.553
월별0.6310.1581.0000.000
장소0.0000.5530.0001.000

Missing values

2023-12-12T09:33:45.394108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:33:45.496208image/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

연번월별종목대회명개회일시장소참여인원
0103월농구제10회 남동구협협회장배 농구대회2023-03-18남동 어울림체육관470
1204월축구제33회 남동구청장기 축구대회2023-04-09남동공단근린공원1800
2304월테니스제28회 남동구협회장기 테니스대회2023-04-15남동공단근린공원 테니스장1000
3404월보디빌딩제3회 남동구청장배 보디빌딩대회2023-04-15남동구청 대강당400
4504월배드민턴제5회 남동구협회장배 배드민턴대회2023-04-23남동다목적실내체육관1200
5605월그라운드골프제8회 남동구협회장기 그라운드골프대회2023-05-11제3호 남동체육광장210
6705월탁구제13회 남동구청장기 탁구대회2023-05-13남동다목적실내체육관700
7805월풋살제6회 남동구청장기 풋살대회2023-05-14남동공단 축구장300
8905월태권도제10회 남동구협회장기 태권도대회2023-05-20남동다목적실내체육관800
91005월파크골프제2회 남동구청장배 파크골프대회2023-05-20장수파크골프장150
연번월별종목대회명개회일시장소참여인원
303110월줄넘기제1회 남동구협회장배 줄넘기대회2023-10-14남동다목적실내체육관300
313210월풋살제10회 남동구협회장기 풋살대회2023-10-15남동공단 축구장300
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