Overview

Dataset statistics

Number of variables6
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory52.2 B

Variable types

Numeric1
Text3
Categorical2

Dataset

Description경남도내 등록체육시설(골프장, 스키장) 현황을 제공합니다. 연번, 사업장명, 홀/슬로프의 수 위치, 연락처 ,비고등의 데이터를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3082694

Alerts

홀 또는 슬로프 수 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 홀 또는 슬로프 수High correlation
비고 is highly imbalanced (83.5%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:38:23.281763
Analysis finished2023-12-11 00:38:23.934504
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21
Minimum1
Maximum41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T09:38:24.003677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q331
95-th percentile39
Maximum41
Range40
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.979149
Coefficient of variation (CV)0.57043565
Kurtosis-1.2
Mean21
Median Absolute Deviation (MAD)10
Skewness0
Sum861
Variance143.5
MonotonicityStrictly increasing
2023-12-11T09:38:24.163149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
1 1
 
2.4%
32 1
 
2.4%
24 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%

사업장명
Text

Distinct38
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:38:24.436884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.2682927
Min length4

Characters and Unicode

Total characters298
Distinct characters99
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)85.4%

Sample

1st row창원CC
2nd row용원CC
3rd row아라미르골프앤리조트
4th row진주CC
5th row통영동원로얄 컨트리클럽
ValueCountFrequency (%)
컨트리클럽 3
 
5.4%
서경타니cc 2
 
3.6%
힐마루cc 2
 
3.6%
창녕 2
 
3.6%
가야cc 2
 
3.6%
고성cc 1
 
1.8%
창원cc 1
 
1.8%
아닌티남해cc 1
 
1.8%
의령친환경 1
 
1.8%
대중골프장 1
 
1.8%
Other values (40) 40
71.4%
2023-12-11T09:38:24.823701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 58
 
19.5%
15
 
5.0%
스 9
 
3.0%
리 9
 
3.0%
트 8
 
2.7%
이 7
 
2.3%
클 6
 
2.0%
럽 6
 
2.0%
경 6
 
2.0%
아 5
 
1.7%
Other values (89) 169
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 218
73.2%
Uppercase Letter 61
 
20.5%
Space Separator 15
 
5.0%
Lowercase Letter 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 9
 
4.1%
리 9
 
4.1%
트 8
 
3.7%
이 7
 
3.2%
클 6
 
2.8%
럽 6
 
2.8%
경 6
 
2.8%
아 5
 
2.3%
원 5
 
2.3%
컨 5
 
2.3%
Other values (81) 152
69.7%
Lowercase Letter
ValueCountFrequency (%)
i 1
25.0%
e 1
25.0%
o 1
25.0%
n 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
C 58
95.1%
G 2
 
3.3%
R 1
 
1.6%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 218
73.2%
Latin 65
 
21.8%
Common 15
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 9
 
4.1%
리 9
 
4.1%
트 8
 
3.7%
이 7
 
3.2%
클 6
 
2.8%
럽 6
 
2.8%
경 6
 
2.8%
아 5
 
2.3%
원 5
 
2.3%
컨 5
 
2.3%
Other values (81) 152
69.7%
Latin
ValueCountFrequency (%)
C 58
89.2%
G 2
 
3.1%
R 1
 
1.5%
i 1
 
1.5%
e 1
 
1.5%
o 1
 
1.5%
n 1
 
1.5%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 218
73.2%
ASCII 80
 
26.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 58
72.5%
15
 
18.8%
G 2
 
2.5%
R 1
 
1.2%
i 1
 
1.2%
e 1
 
1.2%
o 1
 
1.2%
n 1
 
1.2%
Hangul
ValueCountFrequency (%)
스 9
 
4.1%
리 9
 
4.1%
트 8
 
3.7%
이 7
 
3.2%
클 6
 
2.8%
럽 6
 
2.8%
경 6
 
2.8%
아 5
 
2.3%
원 5
 
2.3%
컨 5
 
2.3%
Other values (81) 152
69.7%

홀 또는 슬로프 수
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
대중18
10 
대중9
9 
회원18
7 
대중27
6 
회원27
5 
Other values (4)
4 

Length

Max length5
Median length4
Mean length3.8292683
Min length3

Unique

Unique4 ?
Unique (%)9.8%

Sample

1st row회원18
2nd row회원27
3rd row재중 36
4th row대중18
5th row대중18

Common Values

ValueCountFrequency (%)
대중18 10
24.4%
대중9 9
22.0%
회원18 7
17.1%
대중27 6
14.6%
회원27 5
12.2%
재중 36 1
 
2.4%
회원45 1
 
2.4%
회원36 1
 
2.4%
슬로프 7 1
 
2.4%

Length

2023-12-11T09:38:25.004827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:38:25.150375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대중18 10
23.3%
대중9 9
20.9%
회원18 7
16.3%
대중27 6
14.0%
회원27 5
11.6%
재중 1
 
2.3%
36 1
 
2.3%
회원45 1
 
2.3%
회원36 1
 
2.3%
슬로프 1
 
2.3%

위치
Text

Distinct37
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:38:25.440820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.95122
Min length16

Characters and Unicode

Total characters900
Distinct characters105
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

Unique33 ?
Unique (%)80.5%

Sample

1st row경상남도 창원시 의창구 대봉로 137
2nd row경상남도 창원시 진해구 가주로 133
3rd row경상남도 창원시 진해구 수제로 36
4th row경상남도 진주시 진성면 진성로 464번길 82
5th row경상남도 통영시 산양읍 영운리 산184-5
ValueCountFrequency (%)
경상남도 41
 
20.0%
양산시 8
 
3.9%
김해시 5
 
2.4%
사천시 4
 
2.0%
밀양시 3
 
1.5%
남해군 3
 
1.5%
창원시 3
 
1.5%
창녕군 3
 
1.5%
469-195 2
 
1.0%
원동면 2
 
1.0%
Other values (114) 131
63.9%
2023-12-11T09:38:25.883233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
164
 
18.2%
남 50
 
5.6%
상 44
 
4.9%
경 41
 
4.6%
도 41
 
4.6%
1 33
 
3.7%
로 32
 
3.6%
면 29
 
3.2%
시 27
 
3.0%
4 26
 
2.9%
Other values (95) 413
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 549
61.0%
Decimal Number 173
 
19.2%
Space Separator 164
 
18.2%
Dash Punctuation 14
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 50
 
9.1%
상 44
 
8.0%
경 41
 
7.5%
도 41
 
7.5%
로 32
 
5.8%
면 29
 
5.3%
시 27
 
4.9%
산 19
 
3.5%
양 15
 
2.7%
군 14
 
2.6%
Other values (83) 237
43.2%
Decimal Number
ValueCountFrequency (%)
1 33
19.1%
4 26
15.0%
9 24
13.9%
5 18
10.4%
0 16
9.2%
2 15
8.7%
3 13
 
7.5%
8 10
 
5.8%
7 10
 
5.8%
6 8
 
4.6%
Space Separator
ValueCountFrequency (%)
164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 549
61.0%
Common 351
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 50
 
9.1%
상 44
 
8.0%
경 41
 
7.5%
도 41
 
7.5%
로 32
 
5.8%
면 29
 
5.3%
시 27
 
4.9%
산 19
 
3.5%
양 15
 
2.7%
군 14
 
2.6%
Other values (83) 237
43.2%
Common
ValueCountFrequency (%)
164
46.7%
1 33
 
9.4%
4 26
 
7.4%
9 24
 
6.8%
5 18
 
5.1%
0 16
 
4.6%
2 15
 
4.3%
- 14
 
4.0%
3 13
 
3.7%
8 10
 
2.8%
Other values (2) 18
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 549
61.0%
ASCII 351
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
164
46.7%
1 33
 
9.4%
4 26
 
7.4%
9 24
 
6.8%
5 18
 
5.1%
0 16
 
4.6%
2 15
 
4.3%
- 14
 
4.0%
3 13
 
3.7%
8 10
 
2.8%
Other values (2) 18
 
5.1%
Hangul
ValueCountFrequency (%)
남 50
 
9.1%
상 44
 
8.0%
경 41
 
7.5%
도 41
 
7.5%
로 32
 
5.8%
면 29
 
5.3%
시 27
 
4.9%
산 19
 
3.5%
양 15
 
2.7%
군 14
 
2.6%
Other values (83) 237
43.2%

연락처
Text

Distinct37
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T09:38:26.107007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.926829
Min length9

Characters and Unicode

Total characters489
Distinct characters11
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

Unique33 ?
Unique (%)80.5%

Sample

1st row055-288-4112
2nd row055-540-0715
3rd row055-548-9908
4th row055-758-0400
5th row055-640-5000
ValueCountFrequency (%)
055-831-7000 2
 
4.9%
055-860-0321 2
 
4.9%
055-520-8000 2
 
4.9%
055-330-0730 2
 
4.9%
1644-0280 1
 
2.4%
055-359-8500 1
 
2.4%
055-389-7000 1
 
2.4%
055-880-7979 1
 
2.4%
055-930-7777 1
 
2.4%
055-960-7000 1
 
2.4%
Other values (27) 27
65.9%
2023-12-11T09:38:26.482082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
27.0%
5 101
20.7%
- 81
16.6%
3 41
 
8.4%
7 32
 
6.5%
8 29
 
5.9%
1 18
 
3.7%
9 18
 
3.7%
2 15
 
3.1%
6 11
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 408
83.4%
Dash Punctuation 81
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 132
32.4%
5 101
24.8%
3 41
 
10.0%
7 32
 
7.8%
8 29
 
7.1%
1 18
 
4.4%
9 18
 
4.4%
2 15
 
3.7%
6 11
 
2.7%
4 11
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 132
27.0%
5 101
20.7%
- 81
16.6%
3 41
 
8.4%
7 32
 
6.5%
8 29
 
5.9%
1 18
 
3.7%
9 18
 
3.7%
2 15
 
3.1%
6 11
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
27.0%
5 101
20.7%
- 81
16.6%
3 41
 
8.4%
7 32
 
6.5%
8 29
 
5.9%
1 18
 
3.7%
9 18
 
3.7%
2 15
 
3.1%
6 11
 
2.2%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
골프장
40 
스키장
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
골프장 40
97.6%
스키장 1
 
2.4%

Length

2023-12-11T09:38:26.605563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:38:26.710971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골프장 40
97.6%
스키장 1
 
2.4%

Interactions

2023-12-11T09:38:23.555611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:38:26.794327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장명홀 또는 슬로프 수위치연락처비고
연번1.0001.0000.0000.9860.9860.160
사업장명1.0001.0000.0001.0001.0001.000
홀 또는 슬로프 수0.0000.0001.0000.7680.7681.000
위치0.9861.0000.7681.0001.0001.000
연락처0.9861.0000.7681.0001.0001.000
비고0.1601.0001.0001.0001.0001.000
2023-12-11T09:38:26.913307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
홀 또는 슬로프 수비고
홀 또는 슬로프 수1.0000.906
비고0.9061.000
2023-12-11T09:38:27.000961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번홀 또는 슬로프 수비고
연번1.0000.0580.080
홀 또는 슬로프 수0.0581.0000.906
비고0.0800.9061.000

Missing values

2023-12-11T09:38:23.761529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:38:23.895950image/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

연번사업장명홀 또는 슬로프 수위치연락처비고
01창원CC회원18경상남도 창원시 의창구 대봉로 137055-288-4112골프장
12용원CC회원27경상남도 창원시 진해구 가주로 133055-540-0715골프장
23아라미르골프앤리조트재중 36경상남도 창원시 진해구 수제로 36055-548-9908골프장
34진주CC대중18경상남도 진주시 진성면 진성로 464번길 82055-758-0400골프장
45통영동원로얄 컨트리클럽대중18경상남도 통영시 산양읍 영운리 산184-5055-640-5000골프장
56서경타니CC대중27경상남도 사천시 곤양면 흥신로 210055-831-7000골프장
67서경타니CC대중9경상남도 사천시 곤양면 흥신로 210055-831-7000골프장
78삼삼CC대중9경상남도 사천시 축동면 화당산로 224055-958-3300골프장
89골프존카운티사천대중27경상남도 사천시 서포면 구송로 151055-833-3010골프장
910가야CC회원45경상남도 김해시 인제로 495055-330-0730골프장
연번사업장명홀 또는 슬로프 수위치연락처비고
3132고성CC대중9경상남도 고성군 고성읍 월평리 산48055-672-0070골프장
3233아닌티남해CC대중9경상남도 남해군 남면 남서대로 1179번길 40-109055-860-0321골프장
3334아닌티남해GC대중9경상남도 남해군 남면 남서대로 1179번길 40-109055-860-0321골프장
3435사우스케이프 오너스클럽대중18경상남도 남해군 창선면 흥선로 1505번길 951644-0280골프장
3536경남스카이 뷰CC대중18경상남도 함양군 서상면 소로길 207055-960-7000골프장
3637아델 스코트CC대중27경상남도 합천군 가야면 가조가야로 1916-35055-930-7777골프장
3738거창친환경대중골프장대중9경상남도 거창군 가조면 우륵길 410-284055-880-7979골프장
3839양산동원로얄CC대중18경상남도 양산시 어실로 380-45055-389-7000골프장
3940밀양노벨컨트리클럽대중18경상남도 밀양시 단장면 단장로 946055-359-8500골프장
4041에덴밸리스키장슬로프 7경상남도 양산시 원동면 대리 1040-1번지055-379-8000스키장