Overview

Dataset statistics

Number of variables27
Number of observations31
Missing cells62
Missing cells (%)7.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory231.3 B

Variable types

Numeric8
Categorical8
Text11

Dataset

Description경남도내 경기장 현황 데이터입니다. 시군구별 시설명, 소유기관명, 주소, 홈페이지 주소, 관리주체, 관리인원등의 데이터를 포함하고 있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3080549

Alerts

시도 has constant value ""Constant
경기장 트랙 주로연장 is highly imbalanced (74.2%)Imbalance
경기장 트랙 주로면적 is highly imbalanced (54.5%)Imbalance
운영조직(연락처) has 7 (22.6%) missing valuesMissing
주소 has 8 (25.8%) missing valuesMissing
홈페이지주소 has 16 (51.6%) missing valuesMissing
관리인원(명) has 9 (29.0%) missing valuesMissing
이용단체명 has 14 (45.2%) missing valuesMissing
경기장 트랙 주로폭(m) has 8 (25.8%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique
부지면적 has unique valuesUnique
건축면적 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:27:07.781500
Analysis finished2023-12-11 00:27:08.359245
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:08.425002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-11T09:27:08.566933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
경상남도
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도
2nd row경상남도
3rd row경상남도
4th row경상남도
5th row경상남도

Common Values

ValueCountFrequency (%)
경상남도 31
100.0%

Length

2023-12-11T09:27:08.706235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:08.795241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 31
100.0%

시군구
Text

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:08.948006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters29
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

Unique9 ?
Unique (%)29.0%

Sample

1st row창원시
2nd row창원시
3rd row창원시
4th row진주시
5th row진주시
ValueCountFrequency (%)
거제시 5
16.1%
창원시 3
 
9.7%
사천시 2
 
6.5%
김해시 2
 
6.5%
밀양시 2
 
6.5%
함양군 2
 
6.5%
의령군 2
 
6.5%
진주시 2
 
6.5%
고성군 2
 
6.5%
하동군 1
 
3.2%
Other values (8) 8
25.8%
2023-12-11T09:27:09.270275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

시설명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:09.508090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.6774194
Min length5

Characters and Unicode

Total characters238
Distinct characters58
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row창원종합운동장
2nd row마산종합운동장 주경기장
3rd row진해공설운동장
4th row진주종합경기장 주경기장
5th row진주공설운동장
ValueCountFrequency (%)
주경기장 3
 
8.3%
창원종합운동장 1
 
2.8%
거류체육공원 1
 
2.8%
의령공설운동장 1
 
2.8%
부림공설운동장 1
 
2.8%
함안공설운동장 1
 
2.8%
창녕공설운동장 1
 
2.8%
고성군 1
 
2.8%
종합운동장 1
 
2.8%
남해군공설운동장 1
 
2.8%
Other values (24) 24
66.7%
2023-12-11T09:27:09.931968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 32
 
13.4%
동 28
 
11.8%
운 27
 
11.3%
공 17
 
7.1%
설 15
 
6.3%
합 11
 
4.6%
종 10
 
4.2%
주 6
 
2.5%
5
 
2.1%
기 5
 
2.1%
Other values (48) 82
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
97.9%
Space Separator 5
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 32
13.7%
동 28
 
12.0%
운 27
 
11.6%
공 17
 
7.3%
설 15
 
6.4%
합 11
 
4.7%
종 10
 
4.3%
주 6
 
2.6%
기 5
 
2.1%
경 5
 
2.1%
Other values (47) 77
33.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
97.9%
Common 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 32
13.7%
동 28
 
12.0%
운 27
 
11.6%
공 17
 
7.3%
설 15
 
6.4%
합 11
 
4.7%
종 10
 
4.3%
주 6
 
2.6%
기 5
 
2.1%
경 5
 
2.1%
Other values (47) 77
33.0%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
97.9%
ASCII 5
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 32
13.7%
동 28
 
12.0%
운 27
 
11.6%
공 17
 
7.3%
설 15
 
6.4%
합 11
 
4.7%
종 10
 
4.3%
주 6
 
2.6%
기 5
 
2.1%
경 5
 
2.1%
Other values (47) 77
33.0%
ASCII
ValueCountFrequency (%)
5
100.0%

소유기관
Text

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:10.096915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters29
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

Unique9 ?
Unique (%)29.0%

Sample

1st row창원시
2nd row창원시
3rd row창원시
4th row진주시
5th row진주시
ValueCountFrequency (%)
거제시 5
16.1%
창원시 3
 
9.7%
사천시 2
 
6.5%
김해시 2
 
6.5%
밀양시 2
 
6.5%
함양군 2
 
6.5%
의령군 2
 
6.5%
진주시 2
 
6.5%
고성군 2
 
6.5%
하동군 1
 
3.2%
Other values (8) 8
25.8%
2023-12-11T09:27:10.419248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 18
19.4%
군 13
14.0%
거 6
 
6.5%
창 5
 
5.4%
양 5
 
5.4%
제 5
 
5.4%
원 3
 
3.2%
천 3
 
3.2%
해 3
 
3.2%
함 3
 
3.2%
Other values (19) 29
31.2%

운영조직(연락처)
Text

MISSING 

Distinct20
Distinct (%)83.3%
Missing7
Missing (%)22.6%
Memory size380.0 B
2023-12-11T09:27:10.622707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length13.208333
Min length5

Characters and Unicode

Total characters317
Distinct characters56
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

Unique16 ?
Unique (%)66.7%

Sample

1st row창원시시설관리공단
2nd row체육시설관리소(240-2430)
3rd row문화공보실
4th row진주시기획예산담당관실
5th row통영시공공시설관리사업소
ValueCountFrequency (%)
밀양시공공시설관리사업소 2
 
8.0%
의령군시설관리사업소(055-570-2463 2
 
8.0%
사천시체육시설관리사업소(830-4462 2
 
8.0%
거제시시설관리공단 2
 
8.0%
고성군공공시설관리사업소 1
 
4.0%
창원시시설관리공단 1
 
4.0%
문화공보과 1
 
4.0%
창녕군 1
 
4.0%
거창군문화관광과 1
 
4.0%
함양군청(960-5552 1
 
4.0%
Other values (11) 11
44.0%
2023-12-11T09:27:10.996904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 26
 
8.2%
공 19
 
6.0%
관 17
 
5.4%
설 16
 
5.0%
5 16
 
5.0%
리 15
 
4.7%
사 15
 
4.7%
소 14
 
4.4%
업 13
 
4.1%
- 13
 
4.1%
Other values (46) 153
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
66.9%
Decimal Number 75
 
23.7%
Dash Punctuation 13
 
4.1%
Open Punctuation 8
 
2.5%
Close Punctuation 8
 
2.5%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 26
 
12.3%
공 19
 
9.0%
관 17
 
8.0%
설 16
 
7.5%
리 15
 
7.1%
사 15
 
7.1%
소 14
 
6.6%
업 13
 
6.1%
군 7
 
3.3%
체 5
 
2.4%
Other values (32) 65
30.7%
Decimal Number
ValueCountFrequency (%)
5 16
21.3%
0 13
17.3%
3 12
16.0%
4 9
12.0%
2 8
10.7%
6 6
 
8.0%
7 4
 
5.3%
9 3
 
4.0%
1 2
 
2.7%
8 2
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
66.9%
Common 105
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 26
 
12.3%
공 19
 
9.0%
관 17
 
8.0%
설 16
 
7.5%
리 15
 
7.1%
사 15
 
7.1%
소 14
 
6.6%
업 13
 
6.1%
군 7
 
3.3%
체 5
 
2.4%
Other values (32) 65
30.7%
Common
ValueCountFrequency (%)
5 16
15.2%
- 13
12.4%
0 13
12.4%
3 12
11.4%
4 9
8.6%
( 8
7.6%
) 8
7.6%
2 8
7.6%
6 6
 
5.7%
7 4
 
3.8%
Other values (4) 8
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
66.9%
ASCII 105
33.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 26
 
12.3%
공 19
 
9.0%
관 17
 
8.0%
설 16
 
7.5%
리 15
 
7.1%
사 15
 
7.1%
소 14
 
6.6%
업 13
 
6.1%
군 7
 
3.3%
체 5
 
2.4%
Other values (32) 65
30.7%
ASCII
ValueCountFrequency (%)
5 16
15.2%
- 13
12.4%
0 13
12.4%
3 12
11.4%
4 9
8.6%
( 8
7.6%
) 8
7.6%
2 8
7.6%
6 6
 
5.7%
7 4
 
3.8%
Other values (4) 8
7.6%

주소
Text

MISSING 

Distinct22
Distinct (%)95.7%
Missing8
Missing (%)25.8%
Memory size380.0 B
2023-12-11T09:27:11.266003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length19.782609
Min length16

Characters and Unicode

Total characters455
Distinct characters79
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)91.3%

Sample

1st row경상남도 창원시 의창구 두대동 145
2nd row경상남도 창원시 마산회원구 양덕동 477
3rd row경상남도 창원시 진해구 도만동 1번지
4th row경상남도 진주시 신안동 1-1
5th row경상남도 통영시 북신동 77-2
ValueCountFrequency (%)
경상남도 23
 
21.3%
창원시 3
 
2.8%
의령읍 2
 
1.9%
동동리 2
 
1.9%
821 2
 
1.9%
거제시 2
 
1.9%
의령군 2
 
1.9%
밀양시 2
 
1.9%
남해군 1
 
0.9%
적량면 1
 
0.9%
Other values (68) 68
63.0%
2023-12-11T09:27:11.740207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
18.7%
남 25
 
5.5%
도 25
 
5.5%
경 23
 
5.1%
상 23
 
5.1%
1 22
 
4.8%
동 15
 
3.3%
리 14
 
3.1%
시 13
 
2.9%
읍 12
 
2.6%
Other values (69) 198
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 288
63.3%
Space Separator 85
 
18.7%
Decimal Number 73
 
16.0%
Dash Punctuation 9
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 25
 
8.7%
도 25
 
8.7%
경 23
 
8.0%
상 23
 
8.0%
동 15
 
5.2%
리 14
 
4.9%
시 13
 
4.5%
읍 12
 
4.2%
군 11
 
3.8%
창 8
 
2.8%
Other values (57) 119
41.3%
Decimal Number
ValueCountFrequency (%)
1 22
30.1%
7 9
12.3%
2 9
12.3%
5 6
 
8.2%
4 6
 
8.2%
9 6
 
8.2%
3 5
 
6.8%
6 4
 
5.5%
0 3
 
4.1%
8 3
 
4.1%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
63.3%
Common 167
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 25
 
8.7%
도 25
 
8.7%
경 23
 
8.0%
상 23
 
8.0%
동 15
 
5.2%
리 14
 
4.9%
시 13
 
4.5%
읍 12
 
4.2%
군 11
 
3.8%
창 8
 
2.8%
Other values (57) 119
41.3%
Common
ValueCountFrequency (%)
85
50.9%
1 22
 
13.2%
7 9
 
5.4%
2 9
 
5.4%
- 9
 
5.4%
5 6
 
3.6%
4 6
 
3.6%
9 6
 
3.6%
3 5
 
3.0%
6 4
 
2.4%
Other values (2) 6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 288
63.3%
ASCII 167
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
50.9%
1 22
 
13.2%
7 9
 
5.4%
2 9
 
5.4%
- 9
 
5.4%
5 6
 
3.6%
4 6
 
3.6%
9 6
 
3.6%
3 5
 
3.0%
6 4
 
2.4%
Other values (2) 6
 
3.6%
Hangul
ValueCountFrequency (%)
남 25
 
8.7%
도 25
 
8.7%
경 23
 
8.0%
상 23
 
8.0%
동 15
 
5.2%
리 14
 
4.9%
시 13
 
4.5%
읍 12
 
4.2%
군 11
 
3.8%
창 8
 
2.8%
Other values (57) 119
41.3%

홈페이지주소
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing16
Missing (%)51.6%
Memory size380.0 B
2023-12-11T09:27:11.953636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length16.2
Min length11

Characters and Unicode

Total characters243
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)73.3%

Sample

1st rowcwsisul.or.kr
2nd rowhttp://masan.go.kr
3rd rowjinju.go.kr
4th rowhttp://www.gnty.net/
5th rowhttp://gsiseol.or.kr
ValueCountFrequency (%)
http://uiryeong.go.kr 2
13.3%
www.hygn.go.kr 2
13.3%
cwsisul.or.kr 1
 
6.7%
http://masan.go.kr 1
 
6.7%
jinju.go.kr 1
 
6.7%
http://www.gnty.net 1
 
6.7%
http://gsiseol.or.kr 1
 
6.7%
www.yscity.or.kr 1
 
6.7%
haman.go.kr 1
 
6.7%
http://cng.go.kr 1
 
6.7%
Other values (3) 3
20.0%
2023-12-11T09:27:12.310022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 33
13.6%
g 20
 
8.2%
o 19
 
7.8%
r 18
 
7.4%
t 18
 
7.4%
w 16
 
6.6%
/ 15
 
6.2%
n 14
 
5.8%
k 14
 
5.8%
h 12
 
4.9%
Other values (12) 64
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 188
77.4%
Other Punctuation 55
 
22.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 20
10.6%
o 19
10.1%
r 18
9.6%
t 18
9.6%
w 16
 
8.5%
n 14
 
7.4%
k 14
 
7.4%
h 12
 
6.4%
e 8
 
4.3%
y 7
 
3.7%
Other values (9) 42
22.3%
Other Punctuation
ValueCountFrequency (%)
. 33
60.0%
/ 15
27.3%
: 7
 
12.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 188
77.4%
Common 55
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 20
10.6%
o 19
10.1%
r 18
9.6%
t 18
9.6%
w 16
 
8.5%
n 14
 
7.4%
k 14
 
7.4%
h 12
 
6.4%
e 8
 
4.3%
y 7
 
3.7%
Other values (9) 42
22.3%
Common
ValueCountFrequency (%)
. 33
60.0%
/ 15
27.3%
: 7
 
12.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 243
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 33
13.6%
g 20
 
8.2%
o 19
 
7.8%
r 18
 
7.4%
t 18
 
7.4%
w 16
 
6.6%
/ 15
 
6.2%
n 14
 
5.8%
k 14
 
5.8%
h 12
 
4.9%
Other values (12) 64
26.3%

관리주체
Text

Distinct16
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:12.507040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7
Min length3

Characters and Unicode

Total characters217
Distinct characters41
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

Unique7 ?
Unique (%)22.6%

Sample

1st row시설관리공단
2nd row시설관리공단
3rd row시설관리공단
4th row진주시
5th row진주시
ValueCountFrequency (%)
위탁(거제해양관광개발공사 5
16.1%
시설관리공단 4
12.9%
체육시설사업소 3
9.7%
진주시 2
 
6.5%
사천시 2
 
6.5%
김해시도시개발공사 2
 
6.5%
시설관리사업소 2
 
6.5%
고성군 2
 
6.5%
함양군 2
 
6.5%
통영시 1
 
3.2%
Other values (6) 6
19.4%
2023-12-11T09:27:12.834184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 21
 
9.7%
사 18
 
8.3%
공 14
 
6.5%
설 12
 
5.5%
관 12
 
5.5%
업 8
 
3.7%
소 8
 
3.7%
발 8
 
3.7%
개 8
 
3.7%
군 8
 
3.7%
Other values (31) 100
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 205
94.5%
Close Punctuation 6
 
2.8%
Open Punctuation 6
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 21
 
10.2%
사 18
 
8.8%
공 14
 
6.8%
설 12
 
5.9%
관 12
 
5.9%
업 8
 
3.9%
소 8
 
3.9%
발 8
 
3.9%
개 8
 
3.9%
군 8
 
3.9%
Other values (29) 88
42.9%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 205
94.5%
Common 12
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 21
 
10.2%
사 18
 
8.8%
공 14
 
6.8%
설 12
 
5.9%
관 12
 
5.9%
업 8
 
3.9%
소 8
 
3.9%
발 8
 
3.9%
개 8
 
3.9%
군 8
 
3.9%
Other values (29) 88
42.9%
Common
ValueCountFrequency (%)
) 6
50.0%
( 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 205
94.5%
ASCII 12
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 21
 
10.2%
사 18
 
8.8%
공 14
 
6.8%
설 12
 
5.9%
관 12
 
5.9%
업 8
 
3.9%
소 8
 
3.9%
발 8
 
3.9%
개 8
 
3.9%
군 8
 
3.9%
Other values (29) 88
42.9%
ASCII
ValueCountFrequency (%)
) 6
50.0%
( 6
50.0%

관리인원(명)
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)36.4%
Missing9
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean4
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:12.984394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile9.9
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9439203
Coefficient of variation (CV)0.73598007
Kurtosis0.46081772
Mean4
Median Absolute Deviation (MAD)2
Skewness1.0839997
Sum88
Variance8.6666667
MonotonicityNot monotonic
2023-12-11T09:27:13.115527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 5
16.1%
5 4
12.9%
3 4
12.9%
2 3
 
9.7%
8 2
 
6.5%
4 2
 
6.5%
11 1
 
3.2%
10 1
 
3.2%
(Missing) 9
29.0%
ValueCountFrequency (%)
1 5
16.1%
2 3
9.7%
3 4
12.9%
4 2
 
6.5%
5 4
12.9%
8 2
 
6.5%
10 1
 
3.2%
11 1
 
3.2%
ValueCountFrequency (%)
11 1
 
3.2%
10 1
 
3.2%
8 2
 
6.5%
5 4
12.9%
4 2
 
6.5%
3 4
12.9%
2 3
9.7%
1 5
16.1%

이용단체명
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing14
Missing (%)45.2%
Memory size380.0 B
2023-12-11T09:27:13.273503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.3529412
Min length2

Characters and Unicode

Total characters108
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)70.6%

Sample

1st row시민
2nd row일반시민
3rd row통영시민,체육단체
4th row시민
5th row시민
ValueCountFrequency (%)
시민 5
23.8%
관내동호회 2
 
9.5%
및 2
 
9.5%
일반시민 1
 
4.8%
통영시민,체육단체 1
 
4.8%
밀양육상경기연맹 1
 
4.8%
축구조기회 1
 
4.8%
함안군청육상선수단 1
 
4.8%
창녕군육상연맹,축구협회 1
 
4.8%
동계합숙훈련팀 1
 
4.8%
Other values (5) 5
23.8%
2023-12-11T09:27:13.575202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
민 8
 
7.4%
시 7
 
6.5%
회 6
 
5.6%
군 5
 
4.6%
육 5
 
4.6%
동 4
 
3.7%
4
 
3.7%
, 3
 
2.8%
구 3
 
2.8%
축 3
 
2.8%
Other values (43) 60
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
88.9%
Decimal Number 5
 
4.6%
Space Separator 4
 
3.7%
Other Punctuation 3
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
민 8
 
8.3%
시 7
 
7.3%
회 6
 
6.2%
군 5
 
5.2%
육 5
 
5.2%
동 4
 
4.2%
구 3
 
3.1%
축 3
 
3.1%
체 3
 
3.1%
상 3
 
3.1%
Other values (37) 49
51.0%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
0 1
20.0%
4 1
20.0%
8 1
20.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
88.9%
Common 12
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
민 8
 
8.3%
시 7
 
7.3%
회 6
 
6.2%
군 5
 
5.2%
육 5
 
5.2%
동 4
 
4.2%
구 3
 
3.1%
축 3
 
3.1%
체 3
 
3.1%
상 3
 
3.1%
Other values (37) 49
51.0%
Common
ValueCountFrequency (%)
4
33.3%
, 3
25.0%
1 2
16.7%
0 1
 
8.3%
4 1
 
8.3%
8 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
88.9%
ASCII 12
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
민 8
 
8.3%
시 7
 
7.3%
회 6
 
6.2%
군 5
 
5.2%
육 5
 
5.2%
동 4
 
4.2%
구 3
 
3.1%
축 3
 
3.1%
체 3
 
3.1%
상 3
 
3.1%
Other values (37) 49
51.0%
ASCII
ValueCountFrequency (%)
4
33.3%
, 3
25.0%
1 2
16.7%
0 1
 
8.3%
4 1
 
8.3%
8 1
 
8.3%

부지면적
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74669.932
Minimum15000
Maximum369924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:13.691508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15000
5-th percentile20055
Q133012
median55704
Q374984
95-th percentile206131.95
Maximum369924
Range354924
Interquartile range (IQR)41972

Descriptive statistics

Standard deviation73279.601
Coefficient of variation (CV)0.9813803
Kurtosis8.4521554
Mean74669.932
Median Absolute Deviation (MAD)22166
Skewness2.7002688
Sum2314767.9
Variance5.3698999 × 109
MonotonicityNot monotonic
2023-12-11T09:27:13.825591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
369924.0 1
 
3.2%
37501.0 1
 
3.2%
52751.0 1
 
3.2%
206049.0 1
 
3.2%
15000.0 1
 
3.2%
31795.0 1
 
3.2%
72775.0 1
 
3.2%
96288.0 1
 
3.2%
28106.0 1
 
3.2%
18410.0 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
15000.0 1
3.2%
18410.0 1
3.2%
21700.0 1
3.2%
22509.0 1
3.2%
26197.0 1
3.2%
28106.0 1
3.2%
31795.0 1
3.2%
32486.0 1
3.2%
33538.0 1
3.2%
37501.0 1
3.2%
ValueCountFrequency (%)
369924.0 1
3.2%
206214.9 1
3.2%
206049.0 1
3.2%
168704.0 1
3.2%
98505.0 1
3.2%
96288.0 1
3.2%
92560.0 1
3.2%
76468.0 1
3.2%
73500.0 1
3.2%
72775.0 1
3.2%

건축면적
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:14.026653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.8709677
Min length1

Characters and Unicode

Total characters120
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row19370
2nd row12738
3rd row6758
4th row33496
5th row13090
ValueCountFrequency (%)
19370 1
 
3.2%
125.44 1
 
3.2%
7317 1
 
3.2%
1
 
3.2%
5468 1
 
3.2%
367 1
 
3.2%
343 1
 
3.2%
1329 1
 
3.2%
140 1
 
3.2%
10520 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T09:27:14.378480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
15.8%
3 16
13.3%
9 13
10.8%
2 11
9.2%
6 11
9.2%
4 11
9.2%
7 10
8.3%
0 9
7.5%
5 9
7.5%
8 8
6.7%
Other values (2) 3
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 117
97.5%
Other Punctuation 2
 
1.7%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
16.2%
3 16
13.7%
9 13
11.1%
2 11
9.4%
6 11
9.4%
4 11
9.4%
7 10
8.5%
0 9
7.7%
5 9
7.7%
8 8
6.8%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
15.8%
3 16
13.3%
9 13
10.8%
2 11
9.2%
6 11
9.2%
4 11
9.2%
7 10
8.3%
0 9
7.5%
5 9
7.5%
8 8
6.7%
Other values (2) 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
15.8%
3 16
13.3%
9 13
10.8%
2 11
9.2%
6 11
9.2%
4 11
9.2%
7 10
8.3%
0 9
7.5%
5 9
7.5%
8 8
6.7%
Other values (2) 3
 
2.5%

연면적
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:14.569789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.8064516
Min length1

Characters and Unicode

Total characters118
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row30820
2nd row21915
3rd row6758
4th row41160
5th row13330
ValueCountFrequency (%)
763 2
 
6.5%
30820 1
 
3.2%
21915 1
 
3.2%
9708 1
 
3.2%
1
 
3.2%
6318 1
 
3.2%
1329 1
 
3.2%
140 1
 
3.2%
18545 1
 
3.2%
2304 1
 
3.2%
Other values (20) 20
64.5%
2023-12-11T09:27:14.926654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
16.9%
5 14
11.9%
0 13
11.0%
3 12
10.2%
2 12
10.2%
4 10
8.5%
7 9
7.6%
6 9
7.6%
8 9
7.6%
9 8
 
6.8%
Other values (2) 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 116
98.3%
Other Punctuation 1
 
0.8%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
17.2%
5 14
12.1%
0 13
11.2%
3 12
10.3%
2 12
10.3%
4 10
8.6%
7 9
7.8%
6 9
7.8%
8 9
7.8%
9 8
 
6.9%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
16.9%
5 14
11.9%
0 13
11.0%
3 12
10.2%
2 12
10.2%
4 10
8.5%
7 9
7.6%
6 9
7.6%
8 9
7.6%
9 8
 
6.8%
Other values (2) 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
16.9%
5 14
11.9%
0 13
11.0%
3 12
10.2%
2 12
10.2%
4 10
8.5%
7 9
7.6%
6 9
7.6%
8 9
7.6%
9 8
 
6.8%
Other values (2) 2
 
1.7%

경기장 트랙 바닥재료
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
우레탄
21 
몬도
5 
합성탄성고무
 
2
몬도(우레탄)
 
2
토사
 
1

Length

Max length7
Median length3
Mean length3.2580645
Min length2

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row우레탄
2nd row우레탄
3rd row몬도
4th row몬도
5th row우레탄

Common Values

ValueCountFrequency (%)
우레탄 21
67.7%
몬도 5
 
16.1%
합성탄성고무 2
 
6.5%
몬도(우레탄) 2
 
6.5%
토사 1
 
3.2%

Length

2023-12-11T09:27:15.062179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:15.158869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우레탄 21
67.7%
몬도 5
 
16.1%
합성탄성고무 2
 
6.5%
몬도(우레탄 2
 
6.5%
토사 1
 
3.2%

경기장 트랙 주로연장
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
400
29 
360
 
1
100
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row400
2nd row400
3rd row400
4th row400
5th row400

Common Values

ValueCountFrequency (%)
400 29
93.5%
360 1
 
3.2%
100 1
 
3.2%

Length

2023-12-11T09:27:15.261783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:15.357242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
400 29
93.5%
360 1
 
3.2%
100 1
 
3.2%

경기장 트랙 주로폭(m)
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)26.1%
Missing8
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean318.81087
Minimum1
Maximum6500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:15.451240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.2
Q11.2
median1.2
Q31.2
95-th percentile400
Maximum6500
Range6499
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1352.3111
Coefficient of variation (CV)4.2417347
Kurtosis22.622942
Mean318.81087
Median Absolute Deviation (MAD)0
Skewness4.7413147
Sum7332.65
Variance1828745.4
MonotonicityNot monotonic
2023-12-11T09:27:15.572248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1.2 17
54.8%
400.0 2
 
6.5%
1.25 1
 
3.2%
10.0 1
 
3.2%
1.0 1
 
3.2%
6500.0 1
 
3.2%
(Missing) 8
25.8%
ValueCountFrequency (%)
1.0 1
 
3.2%
1.2 17
54.8%
1.25 1
 
3.2%
10.0 1
 
3.2%
400.0 2
 
6.5%
6500.0 1
 
3.2%
ValueCountFrequency (%)
6500.0 1
 
3.2%
400.0 2
 
6.5%
10.0 1
 
3.2%
1.25 1
 
3.2%
1.2 17
54.8%
1.0 1
 
3.2%

경기장 트랙 주로수
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
8
23 
4
5 
6
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 23
74.2%
4 5
 
16.1%
6 2
 
6.5%
2 1
 
3.2%

Length

2023-12-11T09:27:15.721294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:15.823210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 23
74.2%
4 5
 
16.1%
6 2
 
6.5%
2 1
 
3.2%

경기장 트랙 주로면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
25 
3200
3 
5000
 
1
3840
 
1
22492
 
1

Length

Max length5
Median length4
Mean length4.0322581
Min length4

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row<NA>
2nd row<NA>
3rd row5000
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
80.6%
3200 3
 
9.7%
5000 1
 
3.2%
3840 1
 
3.2%
22492 1
 
3.2%

Length

2023-12-11T09:27:15.941494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:16.068192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
80.6%
3200 3
 
9.7%
5000 1
 
3.2%
3840 1
 
3.2%
22492 1
 
3.2%

경기장 필드 바닥재료
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
천연잔디
17 
인조잔디
12 
토사
 
1
우레탄
 
1

Length

Max length4
Median length4
Mean length3.9032258
Min length2

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row천연잔디
2nd row천연잔디
3rd row인조잔디
4th row천연잔디
5th row인조잔디

Common Values

ValueCountFrequency (%)
천연잔디 17
54.8%
인조잔디 12
38.7%
토사 1
 
3.2%
우레탄 1
 
3.2%

Length

2023-12-11T09:27:16.215465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:16.345002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천연잔디 17
54.8%
인조잔디 12
38.7%
토사 1
 
3.2%
우레탄 1
 
3.2%

경기장 필드 폭(m)
Real number (ℝ)

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.483871
Minimum65
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:16.457987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile67
Q168
median70
Q372
95-th percentile75
Maximum80
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0427068
Coefficient of variation (CV)0.043168838
Kurtosis1.9817651
Mean70.483871
Median Absolute Deviation (MAD)2
Skewness1.0452192
Sum2185
Variance9.2580645
MonotonicityNot monotonic
2023-12-11T09:27:16.565100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
70 10
32.3%
68 7
22.6%
75 3
 
9.7%
72 3
 
9.7%
73 3
 
9.7%
69 2
 
6.5%
66 1
 
3.2%
80 1
 
3.2%
65 1
 
3.2%
ValueCountFrequency (%)
65 1
 
3.2%
66 1
 
3.2%
68 7
22.6%
69 2
 
6.5%
70 10
32.3%
72 3
 
9.7%
73 3
 
9.7%
75 3
 
9.7%
80 1
 
3.2%
ValueCountFrequency (%)
80 1
 
3.2%
75 3
 
9.7%
73 3
 
9.7%
72 3
 
9.7%
70 10
32.3%
69 2
 
6.5%
68 7
22.6%
66 1
 
3.2%
65 1
 
3.2%

경기장 필드 길이(m)
Real number (ℝ)

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.64516
Minimum100
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:16.661711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile102.5
Q1105
median105
Q3109
95-th percentile110
Maximum157
Range57
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.485246
Coefficient of variation (CV)0.088115861
Kurtosis26.555429
Mean107.64516
Median Absolute Deviation (MAD)0
Skewness4.9787144
Sum3337
Variance89.969892
MonotonicityNot monotonic
2023-12-11T09:27:16.753619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
105 17
54.8%
110 4
 
12.9%
109 4
 
12.9%
106 1
 
3.2%
100 1
 
3.2%
108 1
 
3.2%
157 1
 
3.2%
102 1
 
3.2%
103 1
 
3.2%
ValueCountFrequency (%)
100 1
 
3.2%
102 1
 
3.2%
103 1
 
3.2%
105 17
54.8%
106 1
 
3.2%
108 1
 
3.2%
109 4
 
12.9%
110 4
 
12.9%
157 1
 
3.2%
ValueCountFrequency (%)
157 1
 
3.2%
110 4
 
12.9%
109 4
 
12.9%
108 1
 
3.2%
106 1
 
3.2%
105 17
54.8%
103 1
 
3.2%
102 1
 
3.2%
100 1
 
3.2%

관람석 좌석수
Text

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:27:16.901566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.0967742
Min length1

Characters and Unicode

Total characters127
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)77.4%

Sample

1st row27085
2nd row21034
3rd row5707
4th row20116
5th row20000
ValueCountFrequency (%)
10000 4
 
12.9%
3000 3
 
9.7%
27085 1
 
3.2%
112 1
 
3.2%
11000 1
 
3.2%
1
 
3.2%
15000 1
 
3.2%
560 1
 
3.2%
6465 1
 
3.2%
5302 1
 
3.2%
Other values (16) 16
51.6%
2023-12-11T09:27:17.226207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 56
44.1%
1 16
 
12.6%
2 12
 
9.4%
5 11
 
8.7%
6 11
 
8.7%
3 5
 
3.9%
7 5
 
3.9%
8 5
 
3.9%
4 5
 
3.9%
- 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126
99.2%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 56
44.4%
1 16
 
12.7%
2 12
 
9.5%
5 11
 
8.7%
6 11
 
8.7%
3 5
 
4.0%
7 5
 
4.0%
8 5
 
4.0%
4 5
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 56
44.1%
1 16
 
12.6%
2 12
 
9.4%
5 11
 
8.7%
6 11
 
8.7%
3 5
 
3.9%
7 5
 
3.9%
8 5
 
3.9%
4 5
 
3.9%
- 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 56
44.1%
1 16
 
12.6%
2 12
 
9.4%
5 11
 
8.7%
6 11
 
8.7%
3 5
 
3.9%
7 5
 
3.9%
8 5
 
3.9%
4 5
 
3.9%
- 1
 
0.8%

관람석 수용인원
Real number (ℝ)

Distinct14
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13263.516
Minimum162
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:17.342818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162
5-th percentile2150
Q18500
median10000
Q317500
95-th percentile30000
Maximum35000
Range34838
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation9525.6486
Coefficient of variation (CV)0.71818427
Kurtosis-0.11376299
Mean13263.516
Median Absolute Deviation (MAD)4293
Skewness0.97168067
Sum411169
Variance90737981
MonotonicityNot monotonic
2023-12-11T09:27:17.458039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
10000 13
41.9%
30000 4
 
12.9%
5000 3
 
9.7%
5707 1
 
3.2%
22000 1
 
3.2%
25000 1
 
3.2%
20000 1
 
3.2%
35000 1
 
3.2%
4000 1
 
3.2%
162 1
 
3.2%
Other values (4) 4
 
12.9%
ValueCountFrequency (%)
162 1
 
3.2%
300 1
 
3.2%
4000 1
 
3.2%
5000 3
 
9.7%
5707 1
 
3.2%
7000 1
 
3.2%
10000 13
41.9%
12000 1
 
3.2%
15000 1
 
3.2%
20000 1
 
3.2%
ValueCountFrequency (%)
35000 1
 
3.2%
30000 4
 
12.9%
25000 1
 
3.2%
22000 1
 
3.2%
20000 1
 
3.2%
15000 1
 
3.2%
12000 1
 
3.2%
10000 13
41.9%
7000 1
 
3.2%
5707 1
 
3.2%

관람석 좌석형태
Categorical

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
계단식
14 
의자식
8 
<NA>
8 
10000
 
1

Length

Max length5
Median length3
Mean length3.3225806
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
계단식 14
45.2%
의자식 8
25.8%
<NA> 8
25.8%
10000 1
 
3.2%

Length

2023-12-11T09:27:17.852520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:17.976399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계단식 14
45.2%
의자식 8
25.8%
na 8
25.8%
10000 1
 
3.2%

관람석 건축구조
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
철근콘크리트
18 
<NA>
9 
철근콘크리이트
2 
콘크리트 구조
 
1
계단식
 
1

Length

Max length7
Median length6
Mean length5.4193548
Min length3

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트 18
58.1%
<NA> 9
29.0%
철근콘크리이트 2
 
6.5%
콘크리트 구조 1
 
3.2%
계단식 1
 
3.2%

Length

2023-12-11T09:27:18.120256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:27:18.227655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트 18
56.2%
na 9
28.1%
철근콘크리이트 2
 
6.2%
콘크리트 1
 
3.1%
구조 1
 
3.1%
계단식 1
 
3.1%

준공연도
Real number (ℝ)

Distinct23
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1995.4839
Minimum1963
Maximum2014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T09:27:18.341169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1963
5-th percentile1969.5
Q11990.5
median1998
Q32004.5
95-th percentile2011.5
Maximum2014
Range51
Interquartile range (IQR)14

Descriptive statistics

Standard deviation12.740672
Coefficient of variation (CV)0.0063847533
Kurtosis0.51466781
Mean1995.4839
Median Absolute Deviation (MAD)7
Skewness-0.87509736
Sum61860
Variance162.32473
MonotonicityNot monotonic
2023-12-11T09:27:18.468004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1993 3
 
9.7%
2004 2
 
6.5%
1992 2
 
6.5%
1982 2
 
6.5%
1998 2
 
6.5%
1999 2
 
6.5%
2006 2
 
6.5%
1986 1
 
3.2%
1963 1
 
3.2%
1990 1
 
3.2%
Other values (13) 13
41.9%
ValueCountFrequency (%)
1963 1
 
3.2%
1969 1
 
3.2%
1970 1
 
3.2%
1982 2
6.5%
1986 1
 
3.2%
1987 1
 
3.2%
1990 1
 
3.2%
1991 1
 
3.2%
1992 2
6.5%
1993 3
9.7%
ValueCountFrequency (%)
2014 1
3.2%
2012 1
3.2%
2011 1
3.2%
2010 1
3.2%
2009 1
3.2%
2006 2
6.5%
2005 1
3.2%
2004 2
6.5%
2003 1
3.2%
2002 1
3.2%

Sample

연번시도시군구시설명소유기관운영조직(연락처)주소홈페이지주소관리주체관리인원(명)이용단체명부지면적건축면적연면적경기장 트랙 바닥재료경기장 트랙 주로연장경기장 트랙 주로폭(m)경기장 트랙 주로수경기장 트랙 주로면적경기장 필드 바닥재료경기장 필드 폭(m)경기장 필드 길이(m)관람석 좌석수관람석 수용인원관람석 좌석형태관람석 건축구조준공연도
01경상남도창원시창원종합운동장창원시창원시시설관리공단경상남도 창원시 의창구 두대동 145cwsisul.or.kr시설관리공단<NA>시민369924.01937030820우레탄4001.28<NA>천연잔디751102708530000의자식철근콘크리트1993
12경상남도창원시마산종합운동장 주경기장창원시체육시설관리소(240-2430)경상남도 창원시 마산회원구 양덕동 477http://masan.go.kr시설관리공단5일반시민37501.01273821915우레탄4001.258<NA>천연잔디691062103430000의자식철근콘크리트1982
23경상남도창원시진해공설운동장창원시문화공보실경상남도 창원시 진해구 도만동 1번지<NA>시설관리공단3<NA>61833.067586758몬도40010.085000인조잔디6810557075707계단식철근콘크리트1963
34경상남도진주시진주종합경기장 주경기장진주시<NA><NA><NA>진주시<NA><NA>206214.93349641160몬도400<NA>8<NA>천연잔디681052011622000<NA><NA>2010
45경상남도진주시진주공설운동장진주시진주시기획예산담당관실경상남도 진주시 신안동 1-1jinju.go.kr진주시1<NA>57111.01309013330우레탄4001.28<NA>인조잔디721052000025000의자식철근콘크리트1969
56경상남도통영시통영공설운동장통영시통영시공공시설관리사업소경상남도 통영시 북신동 77-2http://www.gnty.net/통영시3통영시민,체육단체32486.0789.111045우레탄4001.28<NA>천연잔디75105560020000계단식철근콘크리트1970
67경상남도사천시삼천포종합운동장사천시사천시체육시설관리사업소(830-4462)경상남도 산천시 벌리동 274-3<NA>사천시5시민55704.052297981우레탄400400.083200천연잔디75110680610000계단식철근콘크리이트1986
78경상남도사천시사천종합운동장사천시사천시체육시설관리사업소(830-4462)경상남도 사천시 사천읍 정의리 7<NA>사천시5시민42307.01589576우레탄400400.083200천연잔디70105486810000계단식철근콘크리이트1982
89경상남도김해시김해운동장김해시<NA><NA><NA>김해시도시개발공사<NA><NA>61127.034963512우레탄400<NA>8<NA>천연잔디661001147635000<NA><NA>2004
910경상남도김해시진영공설운동장 육상경기장김해시055-323-7313경상남도 김해시 진영읍 진영리 1279http://gsiseol.or.kr김해시도시개발공사1<NA>73500.07421310몬도400<NA>8<NA>인조잔디80110400010000계단식콘크리트 구조1999
연번시도시군구시설명소유기관운영조직(연락처)주소홈페이지주소관리주체관리인원(명)이용단체명부지면적건축면적연면적경기장 트랙 바닥재료경기장 트랙 주로연장경기장 트랙 주로폭(m)경기장 트랙 주로수경기장 트랙 주로면적경기장 필드 바닥재료경기장 필드 폭(m)경기장 필드 길이(m)관람석 좌석수관람석 수용인원관람석 좌석형태관람석 건축구조준공연도
2122경상남도창녕군창녕공설운동장창녕군창녕군 문화공보과경상남도 창녕군군 창녕읍 퇴천리 62http://cng.go.kr창녕군개발공사2창녕군육상연맹,축구협회56952.091062304우레탄4001.28<NA>인조잔디70109530210000계단식철근콘크리트2005
2223경상남도고성군고성군 종합운동장고성군고성군공공시설관리사업소경상남도 고성군 고성읍 기월리83-10http://www.goseong.go.kr고성군1동계합숙훈련팀92560.01052018545우레탄4001.28<NA>천연잔디70105646510000의자식철근콘크리트1998
2324경상남도고성군거류체육공원고성군<NA><NA><NA>고성군<NA>18,41018410.0140140우레탄4006500.04<NA>인조잔디721095605000<NA><NA>2006
2425경상남도남해군남해군공설운동장남해군문화체육시설사업소경상남도 남해군 남해읍 서변리 산1번지namhae.go.kr체육시설사업소3<NA>28106.013291329우레탄4001.283840천연잔디701101000010000계단식철근콘크리트1987
2526경상남도하동군하동공설운동장하동군공공시설관리사업소경상남도 하동군 적량면 고절리 산 195<NA>하동군(체육시설사업소)10하동군축구협회96288.0343763우레탄4001.28<NA>천연잔디701051000010000계단식철근콘크리트1993
2627경상남도산청군산청공설운동장산청군<NA><NA><NA>산청군<NA><NA>72775.0367763우레탄400<NA>6<NA>인조잔디6810530005000<NA><NA>1992
2728경상남도함양군함양종합운동장함양군함양군청(960-5551)경상남도 함양군 함양읍 백연리 569-1www.hygn.go.kr함양군4함양군체육회31795.054686318몬도(우레탄)4001.28<NA>천연잔디701571500015000계단식철근콘크리트1991
2829경상남도함양군휴천공설운동장함양군함양군청(960-5552)<NA>www.hygn.go.kr함양군<NA><NA>15000.0--우레탄1001.22<NA>인조잔디65102-300<NA><NA>2011
2930경상남도거창군거창종합운동장거창군거창군문화관광과경상남도 거창군 거창읍 양평리 1160keochang.net거창군3군민206049.073179708몬도4001.28<NA>천연잔디73109110001200010000계단식2009
3031경상남도합천군합천군민공설운동장합천군공공시설관리사업소(055-930-3734)경상남도 합천군 합천읍 합천리 937번지<NA>공공시설관리사업소4합천마라톤클럽52751.07051025몬도(우레탄)4001.2822492천연잔디73103652510000의자식철근콘크리트1990