Overview

Dataset statistics

Number of variables7
Number of observations291
Missing cells49
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory58.5 B

Variable types

Numeric2
Categorical2
Text3

Dataset

Description보령시의 각 읍면동에 설치된 야외운동시설(철봉, 허리돌리기, 달리기운동, 파도타기, 등지압기, 벤치, 어깨근육풀기 등) 설치 현황 데이터로 행정동, 설치장소, 주소, 운동기구현황, 설치연도, 데이터기준일로 구성되어 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=307&beforeMenuCd=DOM_000000201001001000&publicdatapk=15094100

Alerts

데이터기준일 has constant value ""Constant
번호 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 번호High correlation
설치장소 has 12 (4.1%) missing valuesMissing
설치장소 주소 has 6 (2.1%) missing valuesMissing
설치연도 has 31 (10.7%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:26:45.072013
Analysis finished2024-01-09 21:26:45.949185
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct291
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean146
Minimum1
Maximum291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-01-10T06:26:46.004255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.5
Q173.5
median146
Q3218.5
95-th percentile276.5
Maximum291
Range290
Interquartile range (IQR)145

Descriptive statistics

Standard deviation84.148678
Coefficient of variation (CV)0.57636081
Kurtosis-1.2
Mean146
Median Absolute Deviation (MAD)73
Skewness0
Sum42486
Variance7081
MonotonicityStrictly increasing
2024-01-10T06:26:46.108465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
184 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
194 1
 
0.3%
193 1
 
0.3%
Other values (281) 281
96.6%
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 (%)
291 1
0.3%
290 1
0.3%
289 1
0.3%
288 1
0.3%
287 1
0.3%
286 1
0.3%
285 1
0.3%
284 1
0.3%
283 1
0.3%
282 1
0.3%

행정동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
웅천읍
39 
남포면
26 
청라면
24 
대천5동
22 
천북면
20 
Other values (11)
160 

Length

Max length4
Median length3
Mean length3.2611684
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
웅천읍 39
13.4%
남포면 26
 
8.9%
청라면 24
 
8.2%
대천5동 22
 
7.6%
천북면 20
 
6.9%
청소면 19
 
6.5%
주산면 18
 
6.2%
오천면 17
 
5.8%
미산면 17
 
5.8%
대천4동 16
 
5.5%
Other values (6) 73
25.1%

Length

2024-01-10T06:26:46.443758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
웅천읍 39
13.4%
남포면 26
 
8.9%
청라면 24
 
8.2%
대천5동 22
 
7.6%
천북면 20
 
6.9%
청소면 19
 
6.5%
주산면 18
 
6.2%
오천면 17
 
5.8%
미산면 17
 
5.8%
대천4동 16
 
5.5%
Other values (6) 73
25.1%

설치장소
Text

MISSING 

Distinct274
Distinct (%)98.2%
Missing12
Missing (%)4.1%
Memory size2.4 KiB
2024-01-10T06:26:46.584656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.8100358
Min length3

Characters and Unicode

Total characters2179
Distinct characters222
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique269 ?
Unique (%)96.4%

Sample

1st row평1리경로당
2nd row평2리마을공용주차장
3rd row수부1리마을회관
4th row수부2리마을회관
5th row수부3리마을회관
ValueCountFrequency (%)
등산로 4
 
1.4%
신흑3통마을회관옆 2
 
0.7%
대천여중운동장 2
 
0.7%
청천저수지등산로 2
 
0.7%
두룡2리마을회관 2
 
0.7%
옥마산 2
 
0.7%
창암3리마을회관 1
 
0.3%
다목적체육공원 1
 
0.3%
산암사등산로입구 1
 
0.3%
삼곡2리마을회관옆 1
 
0.3%
Other values (272) 272
93.8%
2024-01-10T06:26:46.853202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 174
 
8.0%
관 155
 
7.1%
회 150
 
6.9%
마 138
 
6.3%
을 134
 
6.1%
1 72
 
3.3%
2 65
 
3.0%
산 38
 
1.7%
대 38
 
1.7%
천 37
 
1.7%
Other values (212) 1178
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1959
89.9%
Decimal Number 204
 
9.4%
Space Separator 11
 
0.5%
Dash Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 174
 
8.9%
관 155
 
7.9%
회 150
 
7.7%
마 138
 
7.0%
을 134
 
6.8%
산 38
 
1.9%
대 38
 
1.9%
천 37
 
1.9%
로 35
 
1.8%
공 35
 
1.8%
Other values (197) 1025
52.3%
Decimal Number
ValueCountFrequency (%)
1 72
35.3%
2 65
31.9%
3 31
15.2%
4 10
 
4.9%
8 8
 
3.9%
5 5
 
2.5%
0 4
 
2.0%
7 4
 
2.0%
6 3
 
1.5%
9 2
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1959
89.9%
Common 218
 
10.0%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 174
 
8.9%
관 155
 
7.9%
회 150
 
7.7%
마 138
 
7.0%
을 134
 
6.8%
산 38
 
1.9%
대 38
 
1.9%
천 37
 
1.9%
로 35
 
1.8%
공 35
 
1.8%
Other values (197) 1025
52.3%
Common
ValueCountFrequency (%)
1 72
33.0%
2 65
29.8%
3 31
14.2%
11
 
5.0%
4 10
 
4.6%
8 8
 
3.7%
5 5
 
2.3%
0 4
 
1.8%
7 4
 
1.8%
6 3
 
1.4%
Other values (3) 5
 
2.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1959
89.9%
ASCII 220
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 174
 
8.9%
관 155
 
7.9%
회 150
 
7.7%
마 138
 
7.0%
을 134
 
6.8%
산 38
 
1.9%
대 38
 
1.9%
천 37
 
1.9%
로 35
 
1.8%
공 35
 
1.8%
Other values (197) 1025
52.3%
ASCII
ValueCountFrequency (%)
1 72
32.7%
2 65
29.5%
3 31
14.1%
11
 
5.0%
4 10
 
4.5%
8 8
 
3.6%
5 5
 
2.3%
0 4
 
1.8%
7 4
 
1.8%
6 3
 
1.4%
Other values (5) 7
 
3.2%

설치장소 주소
Text

MISSING 

Distinct281
Distinct (%)98.6%
Missing6
Missing (%)2.1%
Memory size2.4 KiB
2024-01-10T06:26:47.119872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length20.575439
Min length14

Characters and Unicode

Total characters5864
Distinct characters172
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

Unique277 ?
Unique (%)97.2%

Sample

1st row충청남도 보령시 웅천읍 평1리 23
2nd row충청남도 보령시 웅천읍 평2리 397
3rd row충청남도 보령시 웅천읍 수부1리 297-3
4th row충청남도 보령시 웅천읍 수부2리 808
5th row충청남도 보령시 웅천읍 수부3리 586
ValueCountFrequency (%)
충청남도 285
21.3%
보령시 285
21.3%
웅천읍 39
 
2.9%
남포면 26
 
1.9%
청라면 22
 
1.6%
천북면 20
 
1.5%
오천면 19
 
1.4%
주산면 18
 
1.3%
청소면 18
 
1.3%
미산면 17
 
1.3%
Other values (450) 591
44.1%
2024-01-10T06:26:47.491849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1055
18.0%
청 332
 
5.7%
남 320
 
5.5%
도 292
 
5.0%
보 292
 
5.0%
령 288
 
4.9%
충 286
 
4.9%
시 285
 
4.9%
1 210
 
3.6%
면 179
 
3.1%
Other values (162) 2325
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3615
61.6%
Space Separator 1055
 
18.0%
Decimal Number 1035
 
17.7%
Dash Punctuation 159
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 332
 
9.2%
남 320
 
8.9%
도 292
 
8.1%
보 292
 
8.1%
령 288
 
8.0%
충 286
 
7.9%
시 285
 
7.9%
면 179
 
5.0%
리 130
 
3.6%
천 110
 
3.0%
Other values (150) 1101
30.5%
Decimal Number
ValueCountFrequency (%)
1 210
20.3%
2 137
13.2%
3 118
11.4%
5 101
9.8%
4 100
9.7%
8 88
8.5%
7 73
 
7.1%
9 71
 
6.9%
6 70
 
6.8%
0 67
 
6.5%
Space Separator
ValueCountFrequency (%)
1055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3615
61.6%
Common 2249
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 332
 
9.2%
남 320
 
8.9%
도 292
 
8.1%
보 292
 
8.1%
령 288
 
8.0%
충 286
 
7.9%
시 285
 
7.9%
면 179
 
5.0%
리 130
 
3.6%
천 110
 
3.0%
Other values (150) 1101
30.5%
Common
ValueCountFrequency (%)
1055
46.9%
1 210
 
9.3%
- 159
 
7.1%
2 137
 
6.1%
3 118
 
5.2%
5 101
 
4.5%
4 100
 
4.4%
8 88
 
3.9%
7 73
 
3.2%
9 71
 
3.2%
Other values (2) 137
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3615
61.6%
ASCII 2249
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1055
46.9%
1 210
 
9.3%
- 159
 
7.1%
2 137
 
6.1%
3 118
 
5.2%
5 101
 
4.5%
4 100
 
4.4%
8 88
 
3.9%
7 73
 
3.2%
9 71
 
3.2%
Other values (2) 137
 
6.1%
Hangul
ValueCountFrequency (%)
청 332
 
9.2%
남 320
 
8.9%
도 292
 
8.1%
보 292
 
8.1%
령 288
 
8.0%
충 286
 
7.9%
시 285
 
7.9%
면 179
 
5.0%
리 130
 
3.6%
천 110
 
3.0%
Other values (150) 1101
30.5%

운동기구현황
Text

Distinct272
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-01-10T06:26:47.681173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length112
Median length46
Mean length23.931271
Min length3

Characters and Unicode

Total characters6964
Distinct characters192
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)89.0%

Sample

1st row허리돌리기+좌우파도타기+큰활차머신+달리기운동
2nd row다리뻗치기+옆파도타기+허리돌리기및온몸돌리기+온몸역기올리기및근육풀기+온몸노젓기
3rd row윗몸일으키기+다리뻗치기+허리돌리기+역기내리기+좌우파도타기
4th row온몸근육풀기+등지압기+공중걷기
5th row옆파도타기+허리돌리기+어깨근육풀기+윗몸일으키기
ValueCountFrequency (%)
공중걷기+허리돌리기 5
 
1.7%
온몸근육풀기+하체흔들기+달리기+공중걷기 3
 
1.0%
허리돌리기+공중걷기 3
 
1.0%
노젓기+허리돌리기+파도타기+등근육풀기+상체근육풀기 3
 
1.0%
운동 3
 
1.0%
온몸근육풀기+어깨근육풀기+허리돌리기+공중걷기 2
 
0.7%
마라톤운동+어깨근육풀기 2
 
0.7%
마라톤운동+공중걷기운동+허리지압기+등지압기+허리돌리기 2
 
0.7%
달리기 2
 
0.7%
어깨근육풀기+등허리지압기+온몸허리돌리기 2
 
0.7%
Other values (268) 276
91.1%
2024-01-10T06:26:47.984074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1072
 
15.4%
+ 895
 
12.9%
리 608
 
8.7%
허 217
 
3.1%
돌 206
 
3.0%
몸 184
 
2.6%
근 158
 
2.3%
걷 154
 
2.2%
풀 154
 
2.2%
육 152
 
2.2%
Other values (182) 3164
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6051
86.9%
Math Symbol 897
 
12.9%
Space Separator 8
 
0.1%
Control 7
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1072
 
17.7%
리 608
 
10.0%
허 217
 
3.6%
돌 206
 
3.4%
몸 184
 
3.0%
근 158
 
2.6%
걷 154
 
2.5%
풀 154
 
2.5%
육 152
 
2.5%
온 140
 
2.3%
Other values (177) 3006
49.7%
Math Symbol
ValueCountFrequency (%)
+ 895
99.8%
＋ 2
 
0.2%
Space Separator
ValueCountFrequency (%)
8
100.0%
Control
ValueCountFrequency (%)
7
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6051
86.9%
Common 913
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1072
 
17.7%
리 608
 
10.0%
허 217
 
3.6%
돌 206
 
3.4%
몸 184
 
3.0%
근 158
 
2.6%
걷 154
 
2.5%
풀 154
 
2.5%
육 152
 
2.5%
온 140
 
2.3%
Other values (177) 3006
49.7%
Common
ValueCountFrequency (%)
+ 895
98.0%
8
 
0.9%
7
 
0.8%
＋ 2
 
0.2%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6051
86.9%
ASCII 911
 
13.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1072
 
17.7%
리 608
 
10.0%
허 217
 
3.6%
돌 206
 
3.4%
몸 184
 
3.0%
근 158
 
2.6%
걷 154
 
2.5%
풀 154
 
2.5%
육 152
 
2.5%
온 140
 
2.3%
Other values (177) 3006
49.7%
ASCII
ValueCountFrequency (%)
+ 895
98.2%
8
 
0.9%
7
 
0.8%
3 1
 
0.1%
None
ValueCountFrequency (%)
＋ 2
100.0%

설치연도
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)6.2%
Missing31
Missing (%)10.7%
Infinite0
Infinite (%)0.0%
Mean2015.0423
Minimum2005
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-01-10T06:26:48.082006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2009
Q12013
median2016
Q32017
95-th percentile2019
Maximum2020
Range15
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.2278557
Coefficient of variation (CV)0.0016018799
Kurtosis0.56882909
Mean2015.0423
Median Absolute Deviation (MAD)2
Skewness-0.90328536
Sum523911
Variance10.419053
MonotonicityNot monotonic
2024-01-10T06:26:48.168319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2017 40
13.7%
2016 35
12.0%
2018 33
11.3%
2015 31
10.7%
2014 23
7.9%
2013 19
6.5%
2019 19
6.5%
2012 14
 
4.8%
2010 11
 
3.8%
2011 9
 
3.1%
Other values (6) 26
8.9%
(Missing) 31
10.7%
ValueCountFrequency (%)
2005 4
 
1.4%
2006 1
 
0.3%
2007 2
 
0.7%
2008 5
 
1.7%
2009 5
 
1.7%
2010 11
3.8%
2011 9
 
3.1%
2012 14
4.8%
2013 19
6.5%
2014 23
7.9%
ValueCountFrequency (%)
2020 9
 
3.1%
2019 19
6.5%
2018 33
11.3%
2017 40
13.7%
2016 35
12.0%
2015 31
10.7%
2014 23
7.9%
2013 19
6.5%
2012 14
 
4.8%
2011 9
 
3.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-04-07
291 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-07
2nd row2023-04-07
3rd row2023-04-07
4th row2023-04-07
5th row2023-04-07

Common Values

ValueCountFrequency (%)
2023-04-07 291
100.0%

Length

2024-01-10T06:26:48.260668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:26:48.332661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-07 291
100.0%

Interactions

2024-01-10T06:26:45.586773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:26:45.438338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:26:45.655708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:26:45.507753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:26:48.381999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호행정동설치연도
번호1.0000.9690.474
행정동0.9691.0000.385
설치연도0.4740.3851.000
2024-01-10T06:26:48.457164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치연도행정동
번호1.000-0.0100.859
설치연도-0.0101.0000.180
행정동0.8590.1801.000

Missing values

2024-01-10T06:26:45.748512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:26:45.834688image/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.
2024-01-10T06:26:45.908590image/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

번호행정동설치장소설치장소 주소운동기구현황설치연도데이터기준일
01웅천읍평1리경로당충청남도 보령시 웅천읍 평1리 23허리돌리기+좌우파도타기+큰활차머신+달리기운동20082023-04-07
12웅천읍평2리마을공용주차장충청남도 보령시 웅천읍 평2리 397다리뻗치기+옆파도타기+허리돌리기및온몸돌리기+온몸역기올리기및근육풀기+온몸노젓기20132023-04-07
23웅천읍수부1리마을회관충청남도 보령시 웅천읍 수부1리 297-3윗몸일으키기+다리뻗치기+허리돌리기+역기내리기+좌우파도타기20132023-04-07
34웅천읍수부2리마을회관충청남도 보령시 웅천읍 수부2리 808온몸근육풀기+등지압기+공중걷기20142023-04-07
45웅천읍수부3리마을회관충청남도 보령시 웅천읍 수부3리 586옆파도타기+허리돌리기+어깨근육풀기+윗몸일으키기20152023-04-07
56웅천읍성돌1리마을회관충청남도 보령시 웅천읍 성동1리 199-1허리돌리기+공중걷기20112023-04-07
67웅천읍성동2리윗뜸두레방충청남도 보령시 웅천읍 성동큰길 278윗몸일으키기+큰활차머신+역기내리기+좌우파도타기+허리돌리기20122023-04-07
78웅천읍성동3리고인돌공원충청남도 보령시 웅천읍 성동3리 779철봉+윗몸일으키기+허리돌리기+큰활차머신+파도타기+역기내리기20112023-04-07
89웅천읍웅천읍복지회관충청남도 보령시 웅천읍 대창1리 435-3크로스컨트리+트리플트위스트20132023-04-07
910웅천읍대창2리마을회관충청남도 보령시 웅천읍 대창2리 380롤링웨이스트+트원트위스트20132023-04-07
번호행정동설치장소설치장소 주소운동기구현황설치연도데이터기준일
281282대천5동대천항항만공원충청남도 보령시 신흑동2240-4앉아밀어주기+하늘걷기+앉아당기기+다리펴기+팔관절운동기20112023-04-07
282283대천5동신흑3통마을회관옆충청남도 보령시 신흑동 산2249온몸근육풀기+양팔줄당기기+어깨근육풀기20092023-04-07
283284대천5동남곡1통마을회충청남도 보령시 남곡동 252-1허리돌리기+달리기+하늘걷기20172023-04-07
284285대천5동<NA>충청남도 보령시 남곡동 417자전거타기+등허리지압기+큰활차머신+공중걷기+파도타기20182023-04-07
285286대천5동<NA>충청남도 보령시 남곡동 1212노젓기+공중걷기+싸이클20182023-04-07
286287대천5동<NA>충청남도 보령시 됫박산1길 33자전거타기+파도타기+역기내리기20182023-04-07
287288대천5동<NA>충청남도 보령시 육굴길 141걷기운동+공중걷기+옆파도타기+온몸노젓기+어깨근육풀기+온몸돌리기20182023-04-07
288289대천5동<NA>충청남도 보령시 신흑동 1634-6등허리지압+큰활차+공중걷기+파도타기20192023-04-07
289290대천5동신흑6통충청남도 보령시 신흑동 1635하늘걷기+어깨근육풀기+온몸근육풀기+양팔줄당기기20202023-04-07
290291대천5동<NA>충청남도 보령시 신흑동 800-13공중걷기+어깨근육풀기+양팔줄당기기+허리돌리기20202023-04-07