Overview

Dataset statistics

Number of variables7
Number of observations609
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.0 KiB
Average record size in memory57.2 B

Variable types

Categorical3
Text3
Numeric1

Dataset

Description대전광역시 공원현황에 대한 데이터로 내용으로는 관리청, 공원종류, 공원명, 위치, 면적 등이 안내되어 있습니다. * 기준일자 2022. 12. 31. 기준
URLhttps://www.data.go.kr/data/15073859/fileData.do

Alerts

위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:31:05.984213
Analysis finished2023-12-12 23:31:06.577918
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리청
Categorical

Distinct8
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
유성구청
198 
서구청
136 
동구청
91 
중구청
87 
대덕구청
83 
Other values (3)
 
14

Length

Max length6
Median length3
Mean length3.5090312
Min length3

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
유성구청 198
32.5%
서구청 136
22.3%
동구청 91
14.9%
중구청 87
14.3%
대덕구청 83
13.6%
대전광역시 12
 
2.0%
대전광역시 1
 
0.2%
대전현충원 1
 
0.2%

Length

2023-12-13T08:31:06.635383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:06.740240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유성구청 198
32.5%
서구청 136
22.3%
동구청 91
14.9%
중구청 87
14.3%
대덕구청 83
13.6%
대전광역시 13
 
2.1%
대전현충원 1
 
0.2%

공원종류
Categorical

Distinct9
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
어린이공원
316 
소공원
107 
근린공원
105 
문화공원
 
25
기타공원
 
18
Other values (4)
38 

Length

Max length5
Median length5
Mean length4.3431856
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
어린이공원 316
51.9%
소공원 107
 
17.6%
근린공원 105
 
17.2%
문화공원 25
 
4.1%
기타공원 18
 
3.0%
수변공원 17
 
2.8%
체육공원 12
 
2.0%
역사공원 8
 
1.3%
묘지공원 1
 
0.2%

Length

2023-12-13T08:31:06.862664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:06.958759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이공원 316
51.9%
소공원 107
 
17.6%
근린공원 105
 
17.2%
문화공원 25
 
4.1%
기타공원 18
 
3.0%
수변공원 17
 
2.8%
체육공원 12
 
2.0%
역사공원 8
 
1.3%
묘지공원 1
 
0.2%

공원명
Text

Distinct573
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-13T08:31:07.176681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length3.9819376
Min length2

Characters and Unicode

Total characters2425
Distinct characters307
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique539 ?
Unique (%)88.5%

Sample

1st row둔산대
2nd row사정
3rd row대사
4th row호동
5th row행평
ValueCountFrequency (%)
도마,변동 15
 
2.2%
1 15
 
2.2%
2 11
 
1.6%
3 6
 
0.9%
문화 6
 
0.9%
사정 5
 
0.7%
부사 4
 
0.6%
복용 4
 
0.6%
대흥 3
 
0.4%
안영 3
 
0.4%
Other values (555) 602
89.3%
2023-12-13T08:31:07.540511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 116
 
4.8%
) 116
 
4.8%
구 92
 
3.8%
1 92
 
3.8%
68
 
2.8%
역 68
 
2.8%
동 68
 
2.8%
2 64
 
2.6%
대 47
 
1.9%
도 46
 
1.9%
Other values (297) 1648
68.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1775
73.2%
Decimal Number 295
 
12.2%
Open Punctuation 116
 
4.8%
Close Punctuation 116
 
4.8%
Space Separator 68
 
2.8%
Other Punctuation 22
 
0.9%
Uppercase Letter 14
 
0.6%
Dash Punctuation 10
 
0.4%
Other Number 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 92
 
5.2%
역 68
 
3.8%
동 68
 
3.8%
대 47
 
2.6%
도 46
 
2.6%
골 39
 
2.2%
산 39
 
2.2%
마 32
 
1.8%
지 28
 
1.6%
화 28
 
1.6%
Other values (275) 1288
72.6%
Decimal Number
ValueCountFrequency (%)
1 92
31.2%
2 64
21.7%
3 34
 
11.5%
4 32
 
10.8%
8 25
 
8.5%
5 14
 
4.7%
6 12
 
4.1%
7 8
 
2.7%
9 7
 
2.4%
0 7
 
2.4%
Other Number
ValueCountFrequency (%)
① 6
66.7%
② 2
 
22.2%
③ 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 5
35.7%
H 5
35.7%
B 4
28.6%
Other Punctuation
ValueCountFrequency (%)
, 20
90.9%
. 2
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1775
73.2%
Common 636
 
26.2%
Latin 14
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 92
 
5.2%
역 68
 
3.8%
동 68
 
3.8%
대 47
 
2.6%
도 46
 
2.6%
골 39
 
2.2%
산 39
 
2.2%
마 32
 
1.8%
지 28
 
1.6%
화 28
 
1.6%
Other values (275) 1288
72.6%
Common
ValueCountFrequency (%)
( 116
18.2%
) 116
18.2%
1 92
14.5%
68
10.7%
2 64
10.1%
3 34
 
5.3%
4 32
 
5.0%
8 25
 
3.9%
, 20
 
3.1%
5 14
 
2.2%
Other values (9) 55
8.6%
Latin
ValueCountFrequency (%)
A 5
35.7%
H 5
35.7%
B 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1775
73.2%
ASCII 641
 
26.4%
Enclosed Alphanum 9
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 116
18.1%
) 116
18.1%
1 92
14.4%
68
10.6%
2 64
10.0%
3 34
 
5.3%
4 32
 
5.0%
8 25
 
3.9%
, 20
 
3.1%
5 14
 
2.2%
Other values (9) 60
9.4%
Hangul
ValueCountFrequency (%)
구 92
 
5.2%
역 68
 
3.8%
동 68
 
3.8%
대 47
 
2.6%
도 46
 
2.6%
골 39
 
2.2%
산 39
 
2.2%
마 32
 
1.8%
지 28
 
1.6%
화 28
 
1.6%
Other values (275) 1288
72.6%
Enclosed Alphanum
ValueCountFrequency (%)
① 6
66.7%
② 2
 
22.2%
③ 1
 
11.1%

최초결정일(고시번호)
Text

Distinct273
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-13T08:31:07.718389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length16.356322
Min length8

Characters and Unicode

Total characters9961
Distinct characters31
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

Unique159 ?
Unique (%)26.1%

Sample

1st row1988-04-23(건고137)
2nd row1965-10-14(건고1903)
3rd row1965-10-14(건고1903)
4th row1965-10-14(건고1903)
5th row1965-10-14(건고1903)
ValueCountFrequency (%)
1998-01-08(대고3 13
 
2.1%
1996-06-25(대고76 11
 
1.8%
1998-06-13(대고88 11
 
1.8%
1984-08-20(건고315 10
 
1.6%
2008-08-26(대고130 10
 
1.6%
1978-03-30(건고68 10
 
1.6%
1998-11-06(대고166 9
 
1.5%
2000-07-31(대고83 9
 
1.5%
2013-07-12(대고127 9
 
1.5%
1965-10-14(건고1903 8
 
1.3%
Other values (269) 517
83.8%
2023-12-13T08:31:08.045132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1407
14.1%
0 1400
14.1%
- 1096
11.0%
2 948
9.5%
9 668
 
6.7%
( 597
 
6.0%
) 596
 
6.0%
고 569
 
5.7%
8 451
 
4.5%
3 436
 
4.4%
Other values (21) 1793
18.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6449
64.7%
Other Letter 1212
 
12.2%
Dash Punctuation 1096
 
11.0%
Open Punctuation 597
 
6.0%
Close Punctuation 596
 
6.0%
Space Separator 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 569
46.9%
대 371
30.6%
건 186
 
15.3%
구 17
 
1.4%
국 16
 
1.3%
충 10
 
0.8%
남 10
 
0.8%
동 9
 
0.7%
유 6
 
0.5%
덕 6
 
0.5%
Other values (7) 12
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 1407
21.8%
0 1400
21.7%
2 948
14.7%
9 668
10.4%
8 451
 
7.0%
3 436
 
6.8%
6 351
 
5.4%
7 298
 
4.6%
5 252
 
3.9%
4 238
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 1096
100.0%
Open Punctuation
ValueCountFrequency (%)
( 597
100.0%
Close Punctuation
ValueCountFrequency (%)
) 596
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8749
87.8%
Hangul 1212
 
12.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 569
46.9%
대 371
30.6%
건 186
 
15.3%
구 17
 
1.4%
국 16
 
1.3%
충 10
 
0.8%
남 10
 
0.8%
동 9
 
0.7%
유 6
 
0.5%
덕 6
 
0.5%
Other values (7) 12
 
1.0%
Common
ValueCountFrequency (%)
1 1407
16.1%
0 1400
16.0%
- 1096
12.5%
2 948
10.8%
9 668
7.6%
( 597
6.8%
) 596
6.8%
8 451
 
5.2%
3 436
 
5.0%
6 351
 
4.0%
Other values (4) 799
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8749
87.8%
Hangul 1212
 
12.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1407
16.1%
0 1400
16.0%
- 1096
12.5%
2 948
10.8%
9 668
7.6%
( 597
6.8%
) 596
6.8%
8 451
 
5.2%
3 436
 
5.0%
6 351
 
4.0%
Other values (4) 799
9.1%
Hangul
ValueCountFrequency (%)
고 569
46.9%
대 371
30.6%
건 186
 
15.3%
구 17
 
1.4%
국 16
 
1.3%
충 10
 
0.8%
남 10
 
0.8%
동 9
 
0.7%
유 6
 
0.5%
덕 6
 
0.5%
Other values (7) 12
 
1.0%

위치
Text

UNIQUE 

Distinct609
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2023-12-13T08:31:08.286624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length14.679803
Min length7

Characters and Unicode

Total characters8940
Distinct characters161
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique609 ?
Unique (%)100.0%

Sample

1st row서구 둔산대로169(만년동396)
2nd row중구 사정동산2 일원
3rd row중구 대사동190-1 일원
4th row중구 호동 산10-1 일원
5th row중구 사정동100 일원
ValueCountFrequency (%)
유성구 198
 
11.3%
일원 140
 
8.0%
서구 136
 
7.7%
중구 92
 
5.2%
동구 91
 
5.2%
대덕구 83
 
4.7%
지족동 11
 
0.6%
선화동 10
 
0.6%
신성동 6
 
0.3%
용산동 6
 
0.3%
Other values (833) 984
56.0%
2023-12-13T08:31:08.634703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1213
 
13.6%
동 718
 
8.0%
구 622
 
7.0%
1 555
 
6.2%
- 375
 
4.2%
2 363
 
4.1%
3 293
 
3.3%
4 281
 
3.1%
6 262
 
2.9%
5 259
 
2.9%
Other values (151) 3999
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4336
48.5%
Decimal Number 2770
31.0%
Space Separator 1213
 
13.6%
Dash Punctuation 375
 
4.2%
Close Punctuation 122
 
1.4%
Open Punctuation 122
 
1.4%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 718
16.6%
구 622
 
14.3%
성 235
 
5.4%
유 207
 
4.8%
원 202
 
4.7%
일 200
 
4.6%
대 171
 
3.9%
서 144
 
3.3%
중 117
 
2.7%
로 117
 
2.7%
Other values (136) 1603
37.0%
Decimal Number
ValueCountFrequency (%)
1 555
20.0%
2 363
13.1%
3 293
10.6%
4 281
10.1%
6 262
9.5%
5 259
9.4%
8 229
8.3%
7 197
 
7.1%
9 166
 
6.0%
0 165
 
6.0%
Space Separator
ValueCountFrequency (%)
1213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 375
100.0%
Close Punctuation
ValueCountFrequency (%)
) 122
100.0%
Open Punctuation
ValueCountFrequency (%)
( 122
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4604
51.5%
Hangul 4336
48.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 718
16.6%
구 622
 
14.3%
성 235
 
5.4%
유 207
 
4.8%
원 202
 
4.7%
일 200
 
4.6%
대 171
 
3.9%
서 144
 
3.3%
중 117
 
2.7%
로 117
 
2.7%
Other values (136) 1603
37.0%
Common
ValueCountFrequency (%)
1213
26.3%
1 555
12.1%
- 375
 
8.1%
2 363
 
7.9%
3 293
 
6.4%
4 281
 
6.1%
6 262
 
5.7%
5 259
 
5.6%
8 229
 
5.0%
7 197
 
4.3%
Other values (5) 577
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4604
51.5%
Hangul 4336
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1213
26.3%
1 555
12.1%
- 375
 
8.1%
2 363
 
7.9%
3 293
 
6.4%
4 281
 
6.1%
6 262
 
5.7%
5 259
 
5.6%
8 229
 
5.0%
7 197
 
4.3%
Other values (5) 577
12.5%
Hangul
ValueCountFrequency (%)
동 718
16.6%
구 622
 
14.3%
성 235
 
5.4%
유 207
 
4.8%
원 202
 
4.7%
일 200
 
4.6%
대 171
 
3.9%
서 144
 
3.3%
중 117
 
2.7%
로 117
 
2.7%
Other values (136) 1603
37.0%

면적(제곱미터)
Real number (ℝ)

Distinct544
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33895.148
Minimum48
Maximum3235379
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2023-12-13T08:31:08.747032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48
5-th percentile674.8
Q11591
median2479
Q38100
95-th percentile105086.6
Maximum3235379
Range3235331
Interquartile range (IQR)6509

Descriptive statistics

Standard deviation201377.43
Coefficient of variation (CV)5.9411875
Kurtosis169.08599
Mean33895.148
Median Absolute Deviation (MAD)1143
Skewness12.162137
Sum20642145
Variance4.055287 × 1010
MonotonicityNot monotonic
2023-12-13T08:31:08.879394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1600.0 11
 
1.8%
1500.0 6
 
1.0%
1502.0 5
 
0.8%
1984.0 4
 
0.7%
1505.0 4
 
0.7%
2000.0 3
 
0.5%
1495.0 3
 
0.5%
1653.0 3
 
0.5%
2208.0 2
 
0.3%
1662.0 2
 
0.3%
Other values (534) 566
92.9%
ValueCountFrequency (%)
48.0 1
0.2%
59.0 1
0.2%
93.0 1
0.2%
118.0 1
0.2%
200.0 1
0.2%
207.0 1
0.2%
319.0 1
0.2%
344.0 1
0.2%
367.0 1
0.2%
368.0 1
0.2%
ValueCountFrequency (%)
3235379.0 1
0.2%
2784144.0 1
0.2%
1518461.0 1
0.2%
1285620.0 1
0.2%
739191.0 1
0.2%
721707.0 1
0.2%
683766.0 1
0.2%
567892.0 1
0.2%
430234.0 1
0.2%
407900.0 1
0.2%

비고
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<조 성>
403 
<미조성>
128 
<조성중>
59 
<조 성>
 
17
<조성중>
 
1

Length

Max length9
Median length7
Mean length6.3612479
Min length5

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row<조 성>
2nd row<조성중>
3rd row<조성중>
4th row<조성중>
5th row<조성중>

Common Values

ValueCountFrequency (%)
<조 성> 403
66.2%
<미조성> 128
 
21.0%
<조성중> 59
 
9.7%
<조 성> 17
 
2.8%
<조성중> 1
 
0.2%
<조 성> 1
 
0.2%

Length

2023-12-13T08:31:08.990635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:31:09.089011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조 421
40.9%
성 421
40.9%
미조성 128
 
12.4%
조성중 60
 
5.8%

Interactions

2023-12-13T08:31:06.350224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:31:09.154611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리청공원종류면적(제곱미터)비고
관리청1.0000.6910.7000.437
공원종류0.6911.0000.6440.559
면적(제곱미터)0.7000.6441.0000.094
비고0.4370.5590.0941.000
2023-12-13T08:31:09.231445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공원종류관리청비고
공원종류1.0000.4300.316
관리청0.4301.0000.260
비고0.3160.2601.000
2023-12-13T08:31:09.520801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)관리청공원종류비고
면적(제곱미터)1.0000.4710.4110.056
관리청0.4711.0000.4300.260
공원종류0.4110.4301.0000.316
비고0.0560.2600.3161.000

Missing values

2023-12-13T08:31:06.458056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:31:06.542902image/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

관리청공원종류공원명최초결정일(고시번호)위치면적(제곱미터)비고
0대전광역시근린공원둔산대1988-04-23(건고137)서구 둔산대로169(만년동396)567892.0<조 성>
1대전광역시근린공원사정1965-10-14(건고1903)중구 사정동산2 일원1285620.0<조성중>
2대전광역시근린공원대사1965-10-14(건고1903)중구 대사동190-1 일원739191.0<조성중>
3대전광역시근린공원호동1965-10-14(건고1903)중구 호동 산10-1 일원407900.0<조성중>
4대전광역시근린공원행평1965-10-14(건고1903)중구 사정동100 일원2784144.0<조성중>
5대전광역시근린공원세천1986-09-26(건고422)동구 세천동산76-3 일원315875.0<조성중>
6대전광역시근린공원용전1965-10-14(건고1903)동구, 대덕구192930.0<조성중>
7대전광역시근린공원갑천지구2014-01-23(국고37)서구 도안동398번지 일원430234.0<조성중>
8대전광역시근린공원명암2011-03-11(대고42)서구 정림동251-1 일원28970.0<조성중>
9동구청근린공원용운1982-04-09(건고123)동구 용운동389-212749.0<조 성>
관리청공원종류공원명최초결정일(고시번호)위치면적(제곱미터)비고
599중구청기타공원은행1구역(H-4)20070601(대고72)중구 은행동3-1번지 일원1886.0<미조성>
600중구청기타공원은행1구역(H-5)20070601(대고72)중구 은행동111-4번지 일원704.0<미조성>
601중구청기타공원은행1구역(H-6)20070601(대고72)중구 은행동114-44번지 일원2233.0<미조성>
602서구청기타공원진벌2016-12-16(대고191)서구 평촌동179-3일원9666.0<미조성>
603서구청기타공원우정1971-04-02(건고18)서구 괴정동 425-1(용문로 41-17)1742.0<조 성>
604유성구청기타공원엑스포과학2015-10-23(대고172)유성구 도룡동 3-1(대덕대로 480)106754.0<조성중>
605유성구청기타공원검제들2019-10-11(대고180)유성구 용산동 370-7일원13053.0<조성중>
606유성구청기타공원금생들2019-10-11(대고180)유성구 용산동 388일원9973.0<조성중>
607대덕구청기타공원대청2016-06-30(대덕구46)대덕구 신탄진동 7723235.0<미조성>
608대덕구청기타공원평촌12016-12-23(대고200)대덕구 평촌동산4-1 일원4173.0<미조성>