Overview

Dataset statistics

Number of variables9
Number of observations389
Missing cells16
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.9 KiB
Average record size in memory73.3 B

Variable types

Numeric1
Categorical4
Text4

Dataset

Description청주시_공원현황에 대한 데이터로 공원구분, 구분, 공원명, 읍면동, 주소, 관리면적 등에 대한 항목을 제공합니다.
Author충청북도 청주시
URLhttps://www.data.go.kr/data/15098751/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
구분 is highly overall correlated with 공원구분High correlation
공원구분 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
번호 is highly overall correlated with 구 명High correlation
구 명 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
공원구분 is highly imbalanced (59.5%)Imbalance
관리면적(제곱미터) has 16 (4.1%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:19:31.952093
Analysis finished2023-12-12 07:19:32.852336
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct389
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195
Minimum1
Maximum389
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T16:19:32.932545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.4
Q198
median195
Q3292
95-th percentile369.6
Maximum389
Range388
Interquartile range (IQR)194

Descriptive statistics

Standard deviation112.43887
Coefficient of variation (CV)0.5766096
Kurtosis-1.2
Mean195
Median Absolute Deviation (MAD)97
Skewness0
Sum75855
Variance12642.5
MonotonicityStrictly increasing
2023-12-12T16:19:33.108835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
245 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
Other values (379) 379
97.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
389 1
0.3%
388 1
0.3%
387 1
0.3%
386 1
0.3%
385 1
0.3%
384 1
0.3%
383 1
0.3%
382 1
0.3%
381 1
0.3%
380 1
0.3%

공원구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
생활권공원
343 
비공원
 
25
주제공원
 
21

Length

Max length5
Median length5
Mean length4.8174807
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활권공원 343
88.2%
비공원 25
 
6.4%
주제공원 21
 
5.4%

Length

2023-12-12T16:19:33.289773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:19:33.415515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활권공원 343
88.2%
비공원 25
 
6.4%
주제공원 21
 
5.4%

구분
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
어린이공원
187 
근린공원
82 
소공원
74 
광장
24 
수변공원
 
12
Other values (6)
 
10

Length

Max length5
Median length4
Mean length4.1619537
Min length2

Unique

Unique4 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이공원 187
48.1%
근린공원 82
21.1%
소공원 74
 
19.0%
광장 24
 
6.2%
수변공원 12
 
3.1%
생태공원 4
 
1.0%
가로공원 2
 
0.5%
체육공원 1
 
0.3%
역사공원 1
 
0.3%
문화공원 1
 
0.3%

Length

2023-12-12T16:19:33.535856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이공원 187
48.1%
근린공원 82
21.1%
소공원 74
 
19.0%
광장 24
 
6.2%
수변공원 12
 
3.1%
생태공원 4
 
1.0%
가로공원 2
 
0.5%
체육공원 1
 
0.3%
역사공원 1
 
0.3%
문화공원 1
 
0.3%

공 원 명
Text

Distinct364
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:19:33.860204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.3727506
Min length1

Characters and Unicode

Total characters1312
Distinct characters251
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

Unique343 ?
Unique (%)88.2%

Sample

1st row금천배수지
2nd row사랑
3rd row늘푸름
4th row으뜸
5th row금남
ValueCountFrequency (%)
샛별 4
 
1.0%
푸른 3
 
0.8%
쌈지 3
 
0.8%
명암 2
 
0.5%
영우리 2
 
0.5%
율량2 2
 
0.5%
새동네 2
 
0.5%
희망 2
 
0.5%
청남 2
 
0.5%
무궁화 2
 
0.5%
Other values (356) 368
93.9%
2023-12-12T16:19:34.369700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 108
 
8.2%
공 103
 
7.9%
호 61
 
4.6%
1 36
 
2.7%
수 31
 
2.4%
골 26
 
2.0%
장 23
 
1.8%
2 20
 
1.5%
산 20
 
1.5%
오 18
 
1.4%
Other values (241) 866
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1184
90.2%
Decimal Number 114
 
8.7%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%
Space Separator 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 108
 
9.1%
공 103
 
8.7%
호 61
 
5.2%
수 31
 
2.6%
골 26
 
2.2%
장 23
 
1.9%
산 20
 
1.7%
오 18
 
1.5%
창 18
 
1.5%
광 17
 
1.4%
Other values (227) 759
64.1%
Decimal Number
ValueCountFrequency (%)
1 36
31.6%
2 20
17.5%
3 11
 
9.6%
8 9
 
7.9%
9 9
 
7.9%
4 7
 
6.1%
5 7
 
6.1%
7 6
 
5.3%
6 6
 
5.3%
0 3
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1184
90.2%
Common 128
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 108
 
9.1%
공 103
 
8.7%
호 61
 
5.2%
수 31
 
2.6%
골 26
 
2.2%
장 23
 
1.9%
산 20
 
1.7%
오 18
 
1.5%
창 18
 
1.5%
광 17
 
1.4%
Other values (227) 759
64.1%
Common
ValueCountFrequency (%)
1 36
28.1%
2 20
15.6%
3 11
 
8.6%
8 9
 
7.0%
9 9
 
7.0%
4 7
 
5.5%
5 7
 
5.5%
7 6
 
4.7%
6 6
 
4.7%
) 5
 
3.9%
Other values (4) 12
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1184
90.2%
ASCII 128
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 108
 
9.1%
공 103
 
8.7%
호 61
 
5.2%
수 31
 
2.6%
골 26
 
2.2%
장 23
 
1.9%
산 20
 
1.7%
오 18
 
1.5%
창 18
 
1.5%
광 17
 
1.4%
Other values (227) 759
64.1%
ASCII
ValueCountFrequency (%)
1 36
28.1%
2 20
15.6%
3 11
 
8.6%
8 9
 
7.0%
9 9
 
7.0%
4 7
 
5.5%
5 7
 
5.5%
7 6
 
4.7%
6 6
 
4.7%
) 5
 
3.9%
Other values (4) 12
 
9.4%

구 명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
흥덕구
123 
청원구
83 
상당구
79 
서원구
76 
상당구
14 
Other values (3)
14 

Length

Max length4
Median length3
Mean length3.0719794
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
흥덕구 123
31.6%
청원구 83
21.3%
상당구 79
20.3%
서원구 76
19.5%
상당구 14
 
3.6%
청원구 11
 
2.8%
흥덕구 2
 
0.5%
서원구 1
 
0.3%

Length

2023-12-12T16:19:34.540571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:19:34.700636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
흥덕구 125
32.1%
청원구 94
24.2%
상당구 93
23.9%
서원구 77
19.8%

읍면동
Text

Distinct59
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:19:34.926312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.4087404
Min length2

Characters and Unicode

Total characters1326
Distinct characters64
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

Unique11 ?
Unique (%)2.8%

Sample

1st row금천동
2nd row금천동
3rd row금천동
4th row금천동
5th row금천동
ValueCountFrequency (%)
오창읍 43
 
11.1%
가경동 28
 
7.2%
율량동 20
 
5.1%
오송읍 19
 
4.9%
용암동 16
 
4.1%
분평동 14
 
3.6%
내덕동 13
 
3.3%
개신동 13
 
3.3%
방서지구 12
 
3.1%
복대1동 10
 
2.6%
Other values (47) 201
51.7%
2023-12-12T16:19:35.293836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 300
22.6%
100
 
7.5%
읍 64
 
4.8%
오 64
 
4.8%
창 47
 
3.5%
용 38
 
2.9%
암 35
 
2.6%
대 30
 
2.3%
가 29
 
2.2%
경 29
 
2.2%
Other values (54) 590
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1170
88.2%
Space Separator 100
 
7.5%
Decimal Number 56
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 300
25.6%
읍 64
 
5.5%
오 64
 
5.5%
창 47
 
4.0%
용 38
 
3.2%
암 35
 
3.0%
대 30
 
2.6%
가 29
 
2.5%
경 29
 
2.5%
복 26
 
2.2%
Other values (49) 508
43.4%
Decimal Number
ValueCountFrequency (%)
2 27
48.2%
1 27
48.2%
5 1
 
1.8%
4 1
 
1.8%
Space Separator
ValueCountFrequency (%)
100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1170
88.2%
Common 156
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 300
25.6%
읍 64
 
5.5%
오 64
 
5.5%
창 47
 
4.0%
용 38
 
3.2%
암 35
 
3.0%
대 30
 
2.6%
가 29
 
2.5%
경 29
 
2.5%
복 26
 
2.2%
Other values (49) 508
43.4%
Common
ValueCountFrequency (%)
100
64.1%
2 27
 
17.3%
1 27
 
17.3%
5 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1170
88.2%
ASCII 156
 
11.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 300
25.6%
읍 64
 
5.5%
오 64
 
5.5%
창 47
 
4.0%
용 38
 
3.2%
암 35
 
3.0%
대 30
 
2.6%
가 29
 
2.5%
경 29
 
2.5%
복 26
 
2.2%
Other values (49) 508
43.4%
ASCII
ValueCountFrequency (%)
100
64.1%
2 27
 
17.3%
1 27
 
17.3%
5 1
 
0.6%
4 1
 
0.6%

주 소
Text

Distinct378
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-12T16:19:35.749949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length9.9254499
Min length4

Characters and Unicode

Total characters3861
Distinct characters97
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique377 ?
Unique (%)96.9%

Sample

1st row금천동 330
2nd row금천동 314
3rd row금천동 331
4th row금천동 449
5th row금천동 122-6
ValueCountFrequency (%)
오창읍 43
 
4.6%
일원 34
 
3.7%
가경동 28
 
3.0%
율량동 20
 
2.2%
오송읍 19
 
2.0%
용암동 16
 
1.7%
분평동 14
 
1.5%
등 14
 
1.5%
내덕동 13
 
1.4%
개신동 13
 
1.4%
Other values (459) 716
77.0%
2023-12-12T16:19:36.348197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
643
16.7%
동 300
 
7.8%
1 288
 
7.5%
2 213
 
5.5%
3 180
 
4.7%
6 154
 
4.0%
5 138
 
3.6%
4 133
 
3.4%
- 130
 
3.4%
0 119
 
3.1%
Other values (87) 1563
40.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1534
39.7%
Other Letter 1532
39.7%
Space Separator 643
16.7%
Dash Punctuation 130
 
3.4%
Other Punctuation 22
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 300
 
19.6%
리 77
 
5.0%
오 66
 
4.3%
읍 64
 
4.2%
창 48
 
3.1%
용 39
 
2.5%
산 37
 
2.4%
원 36
 
2.3%
일 36
 
2.3%
암 35
 
2.3%
Other values (74) 794
51.8%
Decimal Number
ValueCountFrequency (%)
1 288
18.8%
2 213
13.9%
3 180
11.7%
6 154
10.0%
5 138
9.0%
4 133
8.7%
0 119
7.8%
7 111
 
7.2%
9 108
 
7.0%
8 90
 
5.9%
Space Separator
ValueCountFrequency (%)
643
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2329
60.3%
Hangul 1532
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 300
 
19.6%
리 77
 
5.0%
오 66
 
4.3%
읍 64
 
4.2%
창 48
 
3.1%
용 39
 
2.5%
산 37
 
2.4%
원 36
 
2.3%
일 36
 
2.3%
암 35
 
2.3%
Other values (74) 794
51.8%
Common
ValueCountFrequency (%)
643
27.6%
1 288
12.4%
2 213
 
9.1%
3 180
 
7.7%
6 154
 
6.6%
5 138
 
5.9%
4 133
 
5.7%
- 130
 
5.6%
0 119
 
5.1%
7 111
 
4.8%
Other values (3) 220
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2329
60.3%
Hangul 1532
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
643
27.6%
1 288
12.4%
2 213
 
9.1%
3 180
 
7.7%
6 154
 
6.6%
5 138
 
5.9%
4 133
 
5.7%
- 130
 
5.6%
0 119
 
5.1%
7 111
 
4.8%
Other values (3) 220
 
9.4%
Hangul
ValueCountFrequency (%)
동 300
 
19.6%
리 77
 
5.0%
오 66
 
4.3%
읍 64
 
4.2%
창 48
 
3.1%
용 39
 
2.5%
산 37
 
2.4%
원 36
 
2.3%
일 36
 
2.3%
암 35
 
2.3%
Other values (74) 794
51.8%

관리면적(제곱미터)
Text

MISSING 

Distinct334
Distinct (%)89.5%
Missing16
Missing (%)4.1%
Memory size3.2 KiB
2023-12-12T16:19:36.760386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.8900804
Min length2

Characters and Unicode

Total characters1824
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

Unique316 ?
Unique (%)84.7%

Sample

1st row17,500
2nd row1,501
3rd row1,840
4th row2,318
5th row398
ValueCountFrequency (%)
1,500 20
 
5.4%
1,501 5
 
1.3%
10,000 2
 
0.5%
1,571 2
 
0.5%
1,505 2
 
0.5%
300 2
 
0.5%
170 2
 
0.5%
297 2
 
0.5%
1,652 2
 
0.5%
1,702 2
 
0.5%
Other values (324) 332
89.0%
2023-12-12T16:19:37.271671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 319
17.5%
, 308
16.9%
0 197
10.8%
5 175
9.6%
2 164
9.0%
3 128
7.0%
7 121
 
6.6%
8 117
 
6.4%
6 105
 
5.8%
4 97
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1516
83.1%
Other Punctuation 308
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 319
21.0%
0 197
13.0%
5 175
11.5%
2 164
10.8%
3 128
8.4%
7 121
 
8.0%
8 117
 
7.7%
6 105
 
6.9%
4 97
 
6.4%
9 93
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 319
17.5%
, 308
16.9%
0 197
10.8%
5 175
9.6%
2 164
9.0%
3 128
7.0%
7 121
 
6.6%
8 117
 
6.4%
6 105
 
5.8%
4 97
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 319
17.5%
, 308
16.9%
0 197
10.8%
5 175
9.6%
2 164
9.0%
3 128
7.0%
7 121
 
6.6%
8 117
 
6.4%
6 105
 
5.8%
4 97
 
5.3%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2022-01-27
389 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-01-27
2nd row2022-01-27
3rd row2022-01-27
4th row2022-01-27
5th row2022-01-27

Common Values

ValueCountFrequency (%)
2022-01-27 389
100.0%

Length

2023-12-12T16:19:37.427527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:19:37.533444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-01-27 389
100.0%

Interactions

2023-12-12T16:19:32.484977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:19:37.603643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호공원구분구분구 명읍면동
번호1.0000.4340.4630.8320.995
공원구분0.4341.0001.0000.7620.846
구분0.4631.0001.0000.7160.849
구 명0.8320.7620.7161.0000.961
읍면동0.9950.8460.8490.9611.000
2023-12-12T16:19:37.721171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 명구분공원구분
구 명1.0000.4410.666
구분0.4411.0000.990
공원구분0.6660.9901.000
2023-12-12T16:19:38.134425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호공원구분구분구 명
번호1.0000.2870.2170.596
공원구분0.2871.0000.9900.666
구분0.2170.9901.0000.441
구 명0.5960.6660.4411.000

Missing values

2023-12-12T16:19:32.649875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:19:32.791890image/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

번호공원구분구분공 원 명구 명읍면동주 소관리면적(제곱미터)데이터 기준일
01생활권공원근린공원금천배수지상당구금천동금천동 33017,5002022-01-27
12생활권공원어린이공원사랑상당구금천동금천동 3141,5012022-01-27
23생활권공원어린이공원늘푸름상당구금천동금천동 3311,8402022-01-27
34생활권공원어린이공원으뜸상당구금천동금천동 4492,3182022-01-27
45생활권공원소공원금남상당구금천동금천동 122-63982022-01-27
56생활권공원소공원쇠내상당구금천동금천동 251-85, 175-82432022-01-27
67생활권공원소공원꽃산상당구금천동금천동 105-11752022-01-27
78생활권공원소공원쇠내울상당구금천동금천동 261-901,4082022-01-27
89생활권공원소공원쌈지상당구금천동금천동 62-1, 62-21302022-01-27
910주제공원체육공원호미골체육공원상당구금천동금천동 327-28,0002022-01-27
번호공원구분구분공 원 명구 명읍면동주 소관리면적(제곱미터)데이터 기준일
379380생활권공원소공원달맞이청원구율량동율량동 1193, 11941,9842022-01-27
380381생활권공원소공원율량청원구율량동율량동 13034612022-01-27
381382생활권공원어린이공원주성청원구주성동주성동 4351,8722022-01-27
382383비공원광장율량2 광장2청원구주성동주성동 3447222022-01-27
383384생활권공원근린공원주중공원청원구주중동주중동 10218,1132022-01-27
384385생활권공원근린공원마로니에시공원청원구주중동주중동 102430,9492022-01-27
385386생활권공원근린공원생명누리공원청원구주중동주중동 514-8114,4992022-01-27
386387생활권공원어린이공원주중청원구주중동주중동 10022,0312022-01-27
387388생활권공원어린이공원푸른청원구주중동주중동 8512,4752022-01-27
388389비공원광장율량2 광장1청원구주중동주중동 10617282022-01-27