Overview

Dataset statistics

Number of variables5
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.8%
Total size in memory5.0 KiB
Average record size in memory42.1 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description2023년도 생활체육 종목별 대회현황 및 지원현황으로 대회 구분별로 종목, 대회기간, 장소, 보조금액(자부담 제외)을 제공합니다.(2023. 2. 15. 기준)
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15103967&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 1 (0.8%) duplicate rowsDuplicates
보조금(천원) is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 보조금(천원) High correlation

Reproduction

Analysis started2024-01-28 17:13:30.324608
Analysis finished2024-01-28 17:13:30.972127
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
전국규모 생활체육대회 참가
51 
종목회장기(배) 대회 개최
39 
시장기(배) 대회 개최
19 
전국규모 생활체육대회 개최
 
3
클럽대항 청소년 생활체육대회 개최
 
1
Other values (8)
8 

Length

Max length18
Median length14
Mean length13.735537
Min length12

Unique

Unique9 ?
Unique (%)7.4%

Sample

1st row시장기(배) 대회 개최
2nd row시장기(배) 대회 개최
3rd row시장기(배) 대회 개최
4th row시장기(배) 대회 개최
5th row시장기(배) 대회 개최

Common Values

ValueCountFrequency (%)
전국규모 생활체육대회 참가 51
42.1%
종목회장기(배) 대회 개최 39
32.2%
시장기(배) 대회 개최 19
 
15.7%
전국규모 생활체육대회 개최 3
 
2.5%
클럽대항 청소년 생활체육대회 개최 1
 
0.8%
어르신생활체육대회 개최 1
 
0.8%
종목별 생활체육 리그전 개최 1
 
0.8%
전국생활체육대축전 참가 1
 
0.8%
아시아태평양 마스터스 대회 참가 1
 
0.8%
교육감배 장애학생체육대회 개최 1
 
0.8%
Other values (3) 3
 
2.5%

Length

2024-01-29T02:13:31.027677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개최 66
18.3%
대회 59
16.4%
생활체육대회 55
15.3%
전국규모 54
15.0%
참가 54
15.0%
종목회장기(배 39
10.8%
시장기(배 19
 
5.3%
아시아태평양 1
 
0.3%
서울국제휠체어마라톤대회 1
 
0.3%
장애인종합생활체육대회 1
 
0.3%
Other values (11) 11
 
3.1%

종목
Text

Distinct53
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T02:13:31.245525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length3.3719008
Min length2

Characters and Unicode

Total characters408
Distinct characters108
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)19.0%

Sample

1st row검도
2nd row탁구
3rd row등산
4th row피구
5th row줄넘기
ValueCountFrequency (%)
게이트볼 5
 
3.8%
축구 5
 
3.8%
그라운드골프 5
 
3.8%
농구 5
 
3.8%
배드민턴 5
 
3.8%
검도 4
 
3.0%
종목 4
 
3.0%
탁구 4
 
3.0%
테니스 4
 
3.0%
체조 4
 
3.0%
Other values (48) 88
66.2%
2024-01-29T02:13:31.591637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 29
 
7.1%
프 15
 
3.7%
볼 13
 
3.2%
드 13
 
3.2%
도 12
 
2.9%
12
 
2.9%
기 12
 
2.9%
골 11
 
2.7%
스 9
 
2.2%
트 9
 
2.2%
Other values (98) 273
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 380
93.1%
Space Separator 12
 
2.9%
Decimal Number 9
 
2.2%
Close Punctuation 3
 
0.7%
Open Punctuation 3
 
0.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 29
 
7.6%
프 15
 
3.9%
볼 13
 
3.4%
드 13
 
3.4%
도 12
 
3.2%
기 12
 
3.2%
골 11
 
2.9%
스 9
 
2.4%
트 9
 
2.4%
배 9
 
2.4%
Other values (88) 248
65.3%
Decimal Number
ValueCountFrequency (%)
1 2
22.2%
3 2
22.2%
0 2
22.2%
7 1
11.1%
5 1
11.1%
9 1
11.1%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 380
93.1%
Common 28
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 29
 
7.6%
프 15
 
3.9%
볼 13
 
3.4%
드 13
 
3.4%
도 12
 
3.2%
기 12
 
3.2%
골 11
 
2.9%
스 9
 
2.4%
트 9
 
2.4%
배 9
 
2.4%
Other values (88) 248
65.3%
Common
ValueCountFrequency (%)
12
42.9%
) 3
 
10.7%
( 3
 
10.7%
1 2
 
7.1%
3 2
 
7.1%
0 2
 
7.1%
7 1
 
3.6%
, 1
 
3.6%
5 1
 
3.6%
9 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 380
93.1%
ASCII 28
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 29
 
7.6%
프 15
 
3.9%
볼 13
 
3.4%
드 13
 
3.4%
도 12
 
3.2%
기 12
 
3.2%
골 11
 
2.9%
스 9
 
2.4%
트 9
 
2.4%
배 9
 
2.4%
Other values (88) 248
65.3%
ASCII
ValueCountFrequency (%)
12
42.9%
) 3
 
10.7%
( 3
 
10.7%
1 2
 
7.1%
3 2
 
7.1%
0 2
 
7.1%
7 1
 
3.6%
, 1
 
3.6%
5 1
 
3.6%
9 1
 
3.6%

대회기간
Text

Distinct78
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T02:13:31.761035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length23
Mean length13.429752
Min length2

Characters and Unicode

Total characters1625
Distinct characters22
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)51.2%

Sample

1st row2023-03-11~2023-03-12
2nd row2023-03-18~2023-03-19
3rd row2023-04-02
4th row2023-04-29
5th row2023-05-21
ValueCountFrequency (%)
미정 14
 
11.0%
2023.9월중 10
 
7.9%
2023.10월중 3
 
2.4%
2023-08-19~2023-08-20 3
 
2.4%
2023-06-17 3
 
2.4%
2023.11월중 3
 
2.4%
2023-09-23 3
 
2.4%
2023.9~10월중 3
 
2.4%
2023-06-10~2023-06-11 3
 
2.4%
2023-06-24 2
 
1.6%
Other values (72) 80
63.0%
2024-01-29T02:13:32.051127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 372
22.9%
0 323
19.9%
- 262
16.1%
3 183
11.3%
1 116
 
7.1%
9 51
 
3.1%
~ 50
 
3.1%
6 36
 
2.2%
7 33
 
2.0%
. 31
 
1.9%
Other values (12) 168
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1193
73.4%
Dash Punctuation 262
 
16.1%
Other Letter 76
 
4.7%
Math Symbol 50
 
3.1%
Other Punctuation 36
 
2.2%
Space Separator 6
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 372
31.2%
0 323
27.1%
3 183
15.3%
1 116
 
9.7%
9 51
 
4.3%
6 36
 
3.0%
7 33
 
2.8%
5 28
 
2.3%
4 27
 
2.3%
8 24
 
2.0%
Other Letter
ValueCountFrequency (%)
월 23
30.3%
중 23
30.3%
정 15
19.7%
미 14
18.4%
예 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 31
86.1%
, 5
 
13.9%
Dash Punctuation
ValueCountFrequency (%)
- 262
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1549
95.3%
Hangul 76
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 372
24.0%
0 323
20.9%
- 262
16.9%
3 183
11.8%
1 116
 
7.5%
9 51
 
3.3%
~ 50
 
3.2%
6 36
 
2.3%
7 33
 
2.1%
. 31
 
2.0%
Other values (7) 92
 
5.9%
Hangul
ValueCountFrequency (%)
월 23
30.3%
중 23
30.3%
정 15
19.7%
미 14
18.4%
예 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1549
95.3%
Hangul 76
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 372
24.0%
0 323
20.9%
- 262
16.9%
3 183
11.8%
1 116
 
7.5%
9 51
 
3.3%
~ 50
 
3.2%
6 36
 
2.3%
7 33
 
2.1%
. 31
 
2.0%
Other values (7) 92
 
5.9%
Hangul
ValueCountFrequency (%)
월 23
30.3%
중 23
30.3%
정 15
19.7%
미 14
18.4%
예 1
 
1.3%

장소
Text

Distinct83
Distinct (%)68.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-29T02:13:32.252216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length6.3140496
Min length2

Characters and Unicode

Total characters764
Distinct characters153
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)59.5%

Sample

1st row선학체육관
2nd row선학체육관
3rd row소래산
4th row인천해양과학고체육관
5th row계양체육관
ValueCountFrequency (%)
미정 22
 
12.7%
선학체육관 7
 
4.0%
강원 6
 
3.5%
경북 6
 
3.5%
일원 4
 
2.3%
인천시 3
 
1.7%
남동다목적체육관 3
 
1.7%
외 3
 
1.7%
충남 3
 
1.7%
경기 2
 
1.2%
Other values (100) 114
65.9%
2024-01-29T02:13:32.558740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
6.8%
장 33
 
4.3%
체 31
 
4.1%
육 31
 
4.1%
관 28
 
3.7%
정 25
 
3.3%
미 22
 
2.9%
구 21
 
2.7%
경 20
 
2.6%
원 19
 
2.5%
Other values (143) 482
63.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 695
91.0%
Space Separator 52
 
6.8%
Uppercase Letter 9
 
1.2%
Other Punctuation 5
 
0.7%
Decimal Number 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 33
 
4.7%
체 31
 
4.5%
육 31
 
4.5%
관 28
 
4.0%
정 25
 
3.6%
미 22
 
3.2%
구 21
 
3.0%
경 20
 
2.9%
원 19
 
2.7%
천 18
 
2.6%
Other values (134) 447
64.3%
Uppercase Letter
ValueCountFrequency (%)
G 3
33.3%
N 3
33.3%
L 3
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
4 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 3
60.0%
, 2
40.0%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 695
91.0%
Common 60
 
7.9%
Latin 9
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 33
 
4.7%
체 31
 
4.5%
육 31
 
4.5%
관 28
 
4.0%
정 25
 
3.6%
미 22
 
3.2%
구 21
 
3.0%
경 20
 
2.9%
원 19
 
2.7%
천 18
 
2.6%
Other values (134) 447
64.3%
Common
ValueCountFrequency (%)
52
86.7%
/ 3
 
5.0%
, 2
 
3.3%
2 1
 
1.7%
1 1
 
1.7%
4 1
 
1.7%
Latin
ValueCountFrequency (%)
G 3
33.3%
N 3
33.3%
L 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 695
91.0%
ASCII 69
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
75.4%
G 3
 
4.3%
N 3
 
4.3%
L 3
 
4.3%
/ 3
 
4.3%
, 2
 
2.9%
2 1
 
1.4%
1 1
 
1.4%
4 1
 
1.4%
Hangul
ValueCountFrequency (%)
장 33
 
4.7%
체 31
 
4.5%
육 31
 
4.5%
관 28
 
4.0%
정 25
 
3.6%
미 22
 
3.2%
구 21
 
3.0%
경 20
 
2.9%
원 19
 
2.7%
천 18
 
2.6%
Other values (134) 447
64.3%

보조금(천원)
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10904.579
Minimum1500
Maximum397514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-29T02:13:32.663384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1500
5-th percentile1500
Q13500
median7000
Q38500
95-th percentile20000
Maximum397514
Range396014
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation37042.869
Coefficient of variation (CV)3.3970014
Kurtosis101.17621
Mean10904.579
Median Absolute Deviation (MAD)3000
Skewness9.7610718
Sum1319454
Variance1.3721741 × 109
MonotonicityNot monotonic
2024-01-29T02:13:32.757737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2500 15
12.4%
3500 15
12.4%
7000 13
10.7%
7500 10
8.3%
1500 10
8.3%
4000 9
7.4%
8500 9
7.4%
9000 8
 
6.6%
9500 6
 
5.0%
6500 5
 
4.1%
Other values (16) 21
17.4%
ValueCountFrequency (%)
1500 10
8.3%
2000 2
 
1.7%
2500 15
12.4%
3000 1
 
0.8%
3500 15
12.4%
4000 9
7.4%
5000 1
 
0.8%
5500 2
 
1.7%
6500 5
 
4.1%
7000 13
10.7%
ValueCountFrequency (%)
397514 1
0.8%
100000 1
0.8%
44940 1
0.8%
40000 1
0.8%
38000 1
0.8%
30000 1
0.8%
20000 1
0.8%
15000 1
0.8%
13000 1
0.8%
11000 1
0.8%

Interactions

2024-01-29T02:13:30.769248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:13:32.835460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종목대회기간장소보조금(천원)
구분1.0000.9760.0000.0001.000
종목0.9761.0000.0000.9231.000
대회기간0.0000.0001.0000.9880.000
장소0.0000.9230.9881.0000.000
보조금(천원)1.0001.0000.0000.0001.000
2024-01-29T02:13:32.921627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보조금(천원)구분
보조금(천원)1.0000.961
구분0.9611.000

Missing values

2024-01-29T02:13:30.865580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:13:30.940967image/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

구분종목대회기간장소보조금(천원)
0시장기(배) 대회 개최검도2023-03-11~2023-03-12선학체육관9500
1시장기(배) 대회 개최탁구2023-03-18~2023-03-19선학체육관9500
2시장기(배) 대회 개최등산2023-04-02소래산8500
3시장기(배) 대회 개최피구2023-04-29인천해양과학고체육관8500
4시장기(배) 대회 개최줄넘기2023-05-21계양체육관8500
5시장기(배) 대회 개최족구2023-05-28남동근린공원운동장9000
6시장기(배) 대회 개최육상(건강달리기)2023-06-25인천대공원7500
7시장기(배) 대회 개최국학기공2032-07-29남동구청 대강당7500
8시장기(배) 대회 개최태권도2023-08-19~2023-08-20선학체육관9500
9시장기(배) 대회 개최골프2023.9월중미정9000
구분종목대회기간장소보조금(천원)
111전국규모 생활체육대회 참가농구미정충남 청양3500
112전국규모 생활체육대회 참가배구미정미정1500
113전국규모 생활체육대회 참가배구미정미정1500
114전국규모 생활체육대회 참가산악미정미정2500
115전국규모 생활체육대회 참가골프미정미정1500
116전국규모 생활체육대회 참가하키미정충북 제천2500
117교육감배 장애학생체육대회 개최역도 등 7개 종목2023-10-20인천시 일원10000
118장애인종합생활체육대회 개최수영 등 19개 종목2023-09-15 ~ 2023-09-16인천시 일원38000
119서울국제휠체어마라톤대회 참가휠체어 마라톤미정서울시 일원3500
120미추홀배전국장애인바둑대회바둑미정인천시 일원7000

Duplicate rows

Most frequently occurring

구분종목대회기간장소보조금(천원)# duplicates
0전국규모 생활체육대회 참가배구미정미정15002