Overview

Dataset statistics

Number of variables7
Number of observations185
Missing cells100
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory56.7 B

Variable types

Categorical2
Text5

Dataset

Description울산광역시 공공체육시설의 명칭, 면적, 수용인원, 규모, 소유기관, 관리주체, 연면적, 트랙, 필드바닥 등에 관한 정보를 제공하고 있습니다.
Author울산광역시
URLhttps://www.data.go.kr/data/15055530/fileData.do

Alerts

부지면적 has 2 (1.1%) missing valuesMissing
연면적 has 98 (53.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 08:56:19.215093
Analysis finished2024-03-14 08:56:20.716677
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설유형
Categorical

Distinct14
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
기타시설
60 
축구장
28 
게이트볼장
26 
테니스장
19 
수영장
15 
Other values (9)
37 

Length

Max length7
Median length5
Mean length4
Min length3

Unique

Unique3 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
기타시설 60
32.4%
축구장 28
15.1%
게이트볼장 26
14.1%
테니스장 19
 
10.3%
수영장 15
 
8.1%
생활체육관 11
 
5.9%
육상경기장 6
 
3.2%
구기체육관 6
 
3.2%
야구장 5
 
2.7%
국궁장 4
 
2.2%
Other values (4) 5
 
2.7%

Length

2024-03-14T17:56:20.960977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타시설 60
32.4%
축구장 28
15.1%
게이트볼장 26
14.1%
테니스장 19
 
10.3%
수영장 15
 
8.1%
생활체육관 11
 
5.9%
육상경기장 6
 
3.2%
구기체육관 6
 
3.2%
야구장 5
 
2.7%
국궁장 4
 
2.2%
Other values (4) 5
 
2.7%

시설명
Text

Distinct180
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T17:56:21.850650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.4918919
Min length3

Characters and Unicode

Total characters1571
Distinct characters197
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

Unique176 ?
Unique (%)95.1%

Sample

1st row울산종합운동장
2nd row울산종합운동장 보조경기장
3rd row농소운동장
4th row달천운동장
5th row간절곶스포츠파크운동장
ValueCountFrequency (%)
게이트볼장 16
 
6.4%
수영장 9
 
3.6%
풋살장 5
 
2.0%
파크골프장 4
 
1.6%
미포구장 4
 
1.6%
족구장 4
 
1.6%
테니스장 3
 
1.2%
청량 3
 
1.2%
보조경기장 3
 
1.2%
울주종합체육공원 3
 
1.2%
Other values (174) 195
78.3%
2024-03-14T17:56:23.218824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 166
 
10.6%
64
 
4.1%
구 64
 
4.1%
체 40
 
2.5%
육 40
 
2.5%
수 36
 
2.3%
동 36
 
2.3%
이 26
 
1.7%
공 26
 
1.7%
스 25
 
1.6%
Other values (187) 1048
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1483
94.4%
Space Separator 64
 
4.1%
Close Punctuation 9
 
0.6%
Open Punctuation 9
 
0.6%
Uppercase Letter 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 166
 
11.2%
구 64
 
4.3%
체 40
 
2.7%
육 40
 
2.7%
수 36
 
2.4%
동 36
 
2.4%
이 26
 
1.8%
공 26
 
1.8%
스 25
 
1.7%
트 25
 
1.7%
Other values (181) 999
67.4%
Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
T 2
33.3%
X 2
33.3%
Space Separator
ValueCountFrequency (%)
64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1483
94.4%
Common 82
 
5.2%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 166
 
11.2%
구 64
 
4.3%
체 40
 
2.7%
육 40
 
2.7%
수 36
 
2.4%
동 36
 
2.4%
이 26
 
1.8%
공 26
 
1.8%
스 25
 
1.7%
트 25
 
1.7%
Other values (181) 999
67.4%
Common
ValueCountFrequency (%)
64
78.0%
) 9
 
11.0%
( 9
 
11.0%
Latin
ValueCountFrequency (%)
K 2
33.3%
T 2
33.3%
X 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1483
94.4%
ASCII 88
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 166
 
11.2%
구 64
 
4.3%
체 40
 
2.7%
육 40
 
2.7%
수 36
 
2.4%
동 36
 
2.4%
이 26
 
1.8%
공 26
 
1.8%
스 25
 
1.7%
트 25
 
1.7%
Other values (181) 999
67.4%
ASCII
ValueCountFrequency (%)
64
72.7%
) 9
 
10.2%
( 9
 
10.2%
K 2
 
2.3%
T 2
 
2.3%
X 2
 
2.3%

소재지
Text

Distinct141
Distinct (%)76.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T17:56:24.795687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length18.151351
Min length8

Characters and Unicode

Total characters3358
Distinct characters148
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

Unique112 ?
Unique (%)60.5%

Sample

1st row울산광역시 북구 염포로 55
2nd row울산광역시 북구 염포로 55
3rd row울산광역시 북구 호수중앙로 14
4th row울산광역시 북구 농서로 301
5th row울산광역시 울주군 서생면 서생리 21
ValueCountFrequency (%)
울산광역시 183
24.0%
울주군 71
 
9.3%
북구 38
 
5.0%
남구 32
 
4.2%
중구 24
 
3.1%
동구 18
 
2.4%
범서읍 10
 
1.3%
상북면 7
 
0.9%
서생면 7
 
0.9%
청량읍 6
 
0.8%
Other values (244) 366
48.0%
2024-03-14T17:56:26.715822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
579
17.2%
울 257
 
7.7%
산 221
 
6.6%
역 184
 
5.5%
광 183
 
5.4%
시 183
 
5.4%
1 148
 
4.4%
구 118
 
3.5%
- 73
 
2.2%
군 71
 
2.1%
Other values (138) 1341
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2123
63.2%
Decimal Number 583
 
17.4%
Space Separator 579
 
17.2%
Dash Punctuation 73
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
울 257
 
12.1%
산 221
 
10.4%
역 184
 
8.7%
광 183
 
8.6%
시 183
 
8.6%
구 118
 
5.6%
군 71
 
3.3%
주 71
 
3.3%
동 70
 
3.3%
로 64
 
3.0%
Other values (126) 701
33.0%
Decimal Number
ValueCountFrequency (%)
1 148
25.4%
5 65
11.1%
2 62
10.6%
4 55
 
9.4%
3 52
 
8.9%
6 48
 
8.2%
0 44
 
7.5%
8 42
 
7.2%
7 40
 
6.9%
9 27
 
4.6%
Space Separator
ValueCountFrequency (%)
579
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2123
63.2%
Common 1235
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
울 257
 
12.1%
산 221
 
10.4%
역 184
 
8.7%
광 183
 
8.6%
시 183
 
8.6%
구 118
 
5.6%
군 71
 
3.3%
주 71
 
3.3%
동 70
 
3.3%
로 64
 
3.0%
Other values (126) 701
33.0%
Common
ValueCountFrequency (%)
579
46.9%
1 148
 
12.0%
- 73
 
5.9%
5 65
 
5.3%
2 62
 
5.0%
4 55
 
4.5%
3 52
 
4.2%
6 48
 
3.9%
0 44
 
3.6%
8 42
 
3.4%
Other values (2) 67
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2123
63.2%
ASCII 1235
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
579
46.9%
1 148
 
12.0%
- 73
 
5.9%
5 65
 
5.3%
2 62
 
5.0%
4 55
 
4.5%
3 52
 
4.2%
6 48
 
3.9%
0 44
 
3.6%
8 42
 
3.4%
Other values (2) 67
 
5.4%
Hangul
ValueCountFrequency (%)
울 257
 
12.1%
산 221
 
10.4%
역 184
 
8.7%
광 183
 
8.6%
시 183
 
8.6%
구 118
 
5.6%
군 71
 
3.3%
주 71
 
3.3%
동 70
 
3.3%
로 64
 
3.0%
Other values (126) 701
33.0%

시설내역
Text

Distinct130
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T17:56:27.666661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length33
Mean length16.686486
Min length3

Characters and Unicode

Total characters3087
Distinct characters137
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)58.9%

Sample

1st row트랙(우레탄 400×8), 필드(천연잔디 105m×75m)
2nd row트랙(우레탄 400×4), 필드(인조잔디 115m×68m)
3rd row트랙(우레탄 400×8), 필드(인조잔디 105m×68m)
4th row트랙(우레탄 ×3), 필드(인조잔디 105m×64m)
5th row트랙(우레탄 400×8), 필드(인조잔디 104m×68m)
ValueCountFrequency (%)
1면 38
 
7.4%
풋살장 17
 
3.3%
테니스장 17
 
3.3%
2면 17
 
3.3%
족구장 14
 
2.7%
수영조 11
 
2.1%
면적 11
 
2.1%
300 8
 
1.6%
게이트볼장(17×22 8
 
1.6%
헬스장 7
 
1.4%
Other values (234) 364
71.1%
2024-03-14T17:56:29.157325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
328
 
10.6%
1 200
 
6.5%
장 195
 
6.3%
( 144
 
4.7%
) 143
 
4.6%
2 140
 
4.5%
면 134
 
4.3%
m 130
 
4.2%
× 103
 
3.3%
, 99
 
3.2%
Other values (127) 1471
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1380
44.7%
Decimal Number 751
24.3%
Space Separator 328
 
10.6%
Open Punctuation 144
 
4.7%
Close Punctuation 143
 
4.6%
Lowercase Letter 132
 
4.3%
Math Symbol 103
 
3.3%
Other Punctuation 103
 
3.3%
Other Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 195
 
14.1%
면 134
 
9.7%
구 71
 
5.1%
인 53
 
3.8%
조 44
 
3.2%
레 39
 
2.8%
스 38
 
2.8%
영 35
 
2.5%
이 34
 
2.5%
트 34
 
2.5%
Other values (106) 703
50.9%
Decimal Number
ValueCountFrequency (%)
1 200
26.6%
2 140
18.6%
0 90
12.0%
5 66
 
8.8%
4 60
 
8.0%
6 58
 
7.7%
3 45
 
6.0%
8 37
 
4.9%
7 34
 
4.5%
9 21
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
m 130
98.5%
ø 1
 
0.8%
x 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 99
96.1%
. 2
 
1.9%
/ 2
 
1.9%
Space Separator
ValueCountFrequency (%)
328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 144
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Math Symbol
ValueCountFrequency (%)
× 103
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1575
51.0%
Hangul 1380
44.7%
Latin 132
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 195
 
14.1%
면 134
 
9.7%
구 71
 
5.1%
인 53
 
3.8%
조 44
 
3.2%
레 39
 
2.8%
스 38
 
2.8%
영 35
 
2.5%
이 34
 
2.5%
트 34
 
2.5%
Other values (106) 703
50.9%
Common
ValueCountFrequency (%)
328
20.8%
1 200
12.7%
( 144
9.1%
) 143
9.1%
2 140
8.9%
× 103
 
6.5%
, 99
 
6.3%
0 90
 
5.7%
5 66
 
4.2%
4 60
 
3.8%
Other values (8) 202
12.8%
Latin
ValueCountFrequency (%)
m 130
98.5%
ø 1
 
0.8%
x 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
51.8%
Hangul 1380
44.7%
None 104
 
3.4%
CJK Compat 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
328
20.5%
1 200
12.5%
( 144
9.0%
) 143
8.9%
2 140
8.8%
m 130
 
8.1%
, 99
 
6.2%
0 90
 
5.6%
5 66
 
4.1%
4 60
 
3.8%
Other values (8) 200
12.5%
Hangul
ValueCountFrequency (%)
장 195
 
14.1%
면 134
 
9.7%
구 71
 
5.1%
인 53
 
3.8%
조 44
 
3.2%
레 39
 
2.8%
스 38
 
2.8%
영 35
 
2.5%
이 34
 
2.5%
트 34
 
2.5%
Other values (106) 703
50.9%
None
ValueCountFrequency (%)
× 103
99.0%
ø 1
 
1.0%
CJK Compat
ValueCountFrequency (%)
㎡ 3
100.0%

소유기관
Categorical

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
울주군
67 
북구
37 
시
29 
중구
20 
남구
18 

Length

Max length3
Median length2
Mean length2.2054054
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시
2nd row시
3rd row북구
4th row북구
5th row울주군

Common Values

ValueCountFrequency (%)
울주군 67
36.2%
북구 37
20.0%
시 29
15.7%
중구 20
 
10.8%
남구 18
 
9.7%
동구 14
 
7.6%

Length

2024-03-14T17:56:29.397865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:56:29.610194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울주군 67
36.2%
북구 37
20.0%
시 29
15.7%
중구 20
 
10.8%
남구 18
 
9.7%
동구 14
 
7.6%

부지면적
Text

MISSING 

Distinct157
Distinct (%)85.8%
Missing2
Missing (%)1.1%
Memory size1.6 KiB
2024-03-14T17:56:31.092098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1256831
Min length3

Characters and Unicode

Total characters755
Distinct characters12
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

Unique136 ?
Unique (%)74.3%

Sample

1st row113602
2nd row44131
3rd row21126
4th row83544
5th row57081
ValueCountFrequency (%)
800 4
 
2.2%
1000 4
 
2.2%
8000 3
 
1.6%
83544 2
 
1.1%
374 2
 
1.1%
1400 2
 
1.1%
18323 2
 
1.1%
15332 2
 
1.1%
9280 2
 
1.1%
4958 2
 
1.1%
Other values (147) 158
86.3%
2024-03-14T17:56:32.715257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 172
22.8%
1 110
14.6%
2 74
9.8%
8 68
 
9.0%
5 65
 
8.6%
4 64
 
8.5%
3 55
 
7.3%
7 50
 
6.6%
9 48
 
6.4%
6 46
 
6.1%
Other values (2) 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 752
99.6%
Other Punctuation 3
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 172
22.9%
1 110
14.6%
2 74
9.8%
8 68
 
9.0%
5 65
 
8.6%
4 64
 
8.5%
3 55
 
7.3%
7 50
 
6.6%
9 48
 
6.4%
6 46
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 755
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 172
22.8%
1 110
14.6%
2 74
9.8%
8 68
 
9.0%
5 65
 
8.6%
4 64
 
8.5%
3 55
 
7.3%
7 50
 
6.6%
9 48
 
6.4%
6 46
 
6.1%
Other values (2) 3
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 172
22.8%
1 110
14.6%
2 74
9.8%
8 68
 
9.0%
5 65
 
8.6%
4 64
 
8.5%
3 55
 
7.3%
7 50
 
6.6%
9 48
 
6.4%
6 46
 
6.1%
Other values (2) 3
 
0.4%

연면적
Text

MISSING 

Distinct74
Distinct (%)85.1%
Missing98
Missing (%)53.0%
Memory size1.6 KiB
2024-03-14T17:56:33.543305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5862069
Min length2

Characters and Unicode

Total characters312
Distinct characters12
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

Unique64 ?
Unique (%)73.6%

Sample

1st row37120
2nd row690
3rd row198
4th row89
5th row668
ValueCountFrequency (%)
374 5
 
5.7%
414 2
 
2.3%
6523 2
 
2.3%
2860 2
 
2.3%
668 2
 
2.3%
4128 2
 
2.3%
4050 2
 
2.3%
3879 2
 
2.3%
396 2
 
2.3%
378 2
 
2.3%
Other values (64) 64
73.6%
2024-03-14T17:56:34.597148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
14.1%
1 42
13.5%
3 36
11.5%
5 33
10.6%
2 31
9.9%
4 29
9.3%
7 27
8.7%
8 27
8.7%
6 25
8.0%
9 16
 
5.1%
Other values (2) 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
99.4%
Other Punctuation 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
14.2%
1 42
13.5%
3 36
11.6%
5 33
10.6%
2 31
10.0%
4 29
9.4%
7 27
8.7%
8 27
8.7%
6 25
8.1%
9 16
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44
14.1%
1 42
13.5%
3 36
11.5%
5 33
10.6%
2 31
9.9%
4 29
9.3%
7 27
8.7%
8 27
8.7%
6 25
8.0%
9 16
 
5.1%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
14.1%
1 42
13.5%
3 36
11.5%
5 33
10.6%
2 31
9.9%
4 29
9.3%
7 27
8.7%
8 27
8.7%
6 25
8.0%
9 16
 
5.1%
Other values (2) 2
 
0.6%

Correlations

2024-03-14T17:56:34.751105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형소유기관연면적
시설유형1.0000.3780.990
소유기관0.3781.0001.000
연면적0.9901.0001.000
2024-03-14T17:56:35.103577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유기관시설유형
소유기관1.0000.191
시설유형0.1911.000
2024-03-14T17:56:35.301051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형소유기관
시설유형1.0000.191
소유기관0.1911.000

Missing values

2024-03-14T17:56:19.912168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:56:20.293806image/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.
2024-03-14T17:56:20.583106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시설유형시설명소재지시설내역소유기관부지면적연면적
0육상경기장울산종합운동장울산광역시 북구 염포로 55트랙(우레탄 400×8), 필드(천연잔디 105m×75m)시11360237120
1육상경기장울산종합운동장 보조경기장울산광역시 북구 염포로 55트랙(우레탄 400×4), 필드(인조잔디 115m×68m)시<NA>690
2육상경기장농소운동장울산광역시 북구 호수중앙로 14트랙(우레탄 400×8), 필드(인조잔디 105m×68m)북구44131198
3육상경기장달천운동장울산광역시 북구 농서로 301트랙(우레탄 ×3), 필드(인조잔디 105m×64m)북구2112689
4육상경기장간절곶스포츠파크운동장울산광역시 울주군 서생면 서생리 21트랙(우레탄 400×8), 필드(인조잔디 104m×68m)울주군83544668
5육상경기장온양체육공원운동장울산광역시 울주군 온양읍 외고산옹기길 154트랙(우레탄, 400m×4레인)울주군57081135
6축구장태화십리대밭축구장울산광역시 중구 내오산로 121축구장 2면(68m× 106m) 1면(105m×64), 1면(80m×54m)중구14300<NA>
7축구장문수축구경기장울산광역시 남구 문수로 44주경기장(115m× 78m), 보조경기장1(109× 74m)시91231082781
8축구장문수축구 보조경기장울산광역시 남구 문수로 44주경기장(115m× 78m), 보조경기장1(109× 74m)시<NA>1074
9축구장미포구장 축구기장울산광역시 동구 화정동 55-1주경기장(100m×70m), 보조경기장1(105×74m)시50,6767000
시설유형시설명소재지시설내역소유기관부지면적연면적
175기타시설상북향산(청구골든)풋살장울산광역시 울주군 상북면 산전리 1084-51풋살장1면, 족구장1면울주군640<NA>
176기타시설삼남마산마을풋살장울산광역시 울주군풋살장1면, 족구장1면울주군940<NA>
177기타시설삼남방기풋살장울산광역시 울주군 삼남읍 방기리 590-3풋살장1면울주군1150<NA>
178기타시설상북행정마을족구장울산광역시 울주군 상북면 덕현리 912-2족구장1면울주군1000<NA>
179기타시설언양실버배드민턴장울산광역시 울주군 언양읍 구수리 산169-2번지배드민턴장 4면울주군200<NA>
180기타시설청량 파크골프장울산광역시 울주군 청량읍 덕하리 979-6318홀 (2013년 9홀 조성, 2015년9홀추가)울주군6296<NA>
181기타시설범서 파크골프장울산광역시 울주군 범서읍 천상리 1041-7718홀울주군6552<NA>
182기타시설상북 알프스파크골프장울산광역시 울주군 상북면 등억알프스리701-36파크골프장 9홀울주군8850<NA>
183기타시설범서굴화체육시설울산광역시 울주군풋살장 2면, 족구장2면울주군6055<NA>
184기타시설울주종합체육공원울산광역시 울주군 삼남늡 교동리 산86-17풋살장1면, 족구장4면울주군17600<NA>