Overview

Dataset statistics

Number of variables8
Number of observations330
Missing cells7
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.1 KiB
Average record size in memory65.4 B

Variable types

Numeric1
Categorical4
Text3

Dataset

Description도봉구 관내 소규모 체육시설 야외운동기구 현황 데이터로 설치장소,기구명,설치년도, 관리번호, 행정동 정보를 제공합니다
Author서울특별시 도봉구
URLhttps://www.data.go.kr/data/15037803/fileData.do

Alerts

상세위치 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
행정동 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 위치 and 3 other fieldsHigh correlation
위치 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
설치년도 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
설치년월 has 7 (2.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:48:08.447400
Analysis finished2023-12-12 21:48:09.369220
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct330
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean165.5
Minimum1
Maximum330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T06:48:09.487403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.45
Q183.25
median165.5
Q3247.75
95-th percentile313.55
Maximum330
Range329
Interquartile range (IQR)164.5

Descriptive statistics

Standard deviation95.407023
Coefficient of variation (CV)0.57647748
Kurtosis-1.2
Mean165.5
Median Absolute Deviation (MAD)82.5
Skewness0
Sum54615
Variance9102.5
MonotonicityStrictly increasing
2023-12-13T06:48:09.652352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
228 1
 
0.3%
226 1
 
0.3%
225 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
Other values (320) 320
97.0%
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 (%)
330 1
0.3%
329 1
0.3%
328 1
0.3%
327 1
0.3%
326 1
0.3%
325 1
0.3%
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%

위치
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
우이천
68 
중랑천
68 
마을마당
45 
중랑천제방
40 
배드민턴장
34 
Other values (16)
75 

Length

Max length8
Median length7
Mean length4.2181818
Min length3

Unique

Unique9 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
우이천 68
20.6%
중랑천 68
20.6%
마을마당 45
13.6%
중랑천제방 40
12.1%
배드민턴장 34
10.3%
도봉천변 20
 
6.1%
우이천제방 12
 
3.6%
다락원 체육공원 9
 
2.7%
요셉의집 부근 8
 
2.4%
바가지 약수터 7
 
2.1%
Other values (11) 19
 
5.8%

Length

2023-12-13T06:48:09.818851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
우이천 68
18.7%
중랑천 68
18.7%
마을마당 45
12.4%
중랑천제방 40
11.0%
배드민턴장 34
9.4%
도봉천변 20
 
5.5%
우이천제방 12
 
3.3%
다락원 9
 
2.5%
체육공원 9
 
2.5%
소공원 9
 
2.5%
Other values (15) 49
13.5%

상세위치
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
서원아파트 116동 앞 (정자 주변)
 
15
노원교 아래(서광101동)
 
15
도봉1동 마을마당 203-5
 
14
녹천교 아래
 
14
서원아파트 105동 아래
 
11
Other values (39)
261 

Length

Max length24
Median length18
Mean length13.357576
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수유교 아래(한일병원)
2nd row수유교 아래(한일병원)
3rd row수유교 아래(한일병원)
4th row수유교 아래(한일병원)
5th row수유교 아래(한일병원)

Common Values

ValueCountFrequency (%)
서원아파트 116동 앞 (정자 주변) 15
 
4.5%
노원교 아래(서광101동) 15
 
4.5%
도봉1동 마을마당 203-5 14
 
4.2%
녹천교 아래 14
 
4.2%
서원아파트 105동 아래 11
 
3.3%
수유교 아래(분수대 주변) 11
 
3.3%
누원고등학교 아래 11
 
3.3%
도봉1동 산96 (노불배드민턴장) 10
 
3.0%
우이2교~우이3교(금용@ 부근) 10
 
3.0%
방학2동 산 55-1 (청송배드민턴장) 9
 
2.7%
Other values (34) 210
63.6%

Length

2023-12-13T06:48:10.291009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아래 90
 
10.0%
도봉1동 36
 
4.0%
앞 35
 
3.9%
마을마당 35
 
3.9%
방학2동 32
 
3.6%
서원아파트 31
 
3.4%
주변 26
 
2.9%
데크 20
 
2.2%
수유교 20
 
2.2%
쌍문1동 17
 
1.9%
Other values (71) 557
62.0%

기구명
Text

Distinct115
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T06:48:10.525250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length6.3575758
Min length2

Characters and Unicode

Total characters2098
Distinct characters136
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)21.8%

Sample

1st row거꾸로매달리기
2nd row공중걷기
3rd row좌우파도타기
4th row2인 윗몸일으키기
5th row3단철봉
ValueCountFrequency (%)
2인 28
 
7.5%
허리돌리기 26
 
7.0%
오금펴기 21
 
5.6%
윗몸일으키기 21
 
5.6%
달리기 16
 
4.3%
공중걷기 16
 
4.3%
역기올리기+역기내리기 16
 
4.3%
파도타기 15
 
4.0%
거꾸로매달리기 11
 
2.9%
역기 8
 
2.1%
Other values (107) 195
52.3%
2023-12-13T06:48:10.916356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 372
 
17.7%
리 176
 
8.4%
허 55
 
2.6%
역 49
 
2.3%
+ 47
 
2.2%
45
 
2.1%
달 38
 
1.8%
펴 37
 
1.8%
인 37
 
1.8%
돌 34
 
1.6%
Other values (126) 1208
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1925
91.8%
Math Symbol 47
 
2.2%
Space Separator 45
 
2.1%
Decimal Number 42
 
2.0%
Close Punctuation 19
 
0.9%
Open Punctuation 19
 
0.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 372
 
19.3%
리 176
 
9.1%
허 55
 
2.9%
역 49
 
2.5%
달 38
 
2.0%
펴 37
 
1.9%
인 37
 
1.9%
돌 34
 
1.8%
타 33
 
1.7%
트 32
 
1.7%
Other values (119) 1062
55.2%
Decimal Number
ValueCountFrequency (%)
2 32
76.2%
3 10
 
23.8%
Math Symbol
ValueCountFrequency (%)
+ 47
100.0%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1925
91.8%
Common 173
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 372
 
19.3%
리 176
 
9.1%
허 55
 
2.9%
역 49
 
2.5%
달 38
 
2.0%
펴 37
 
1.9%
인 37
 
1.9%
돌 34
 
1.8%
타 33
 
1.7%
트 32
 
1.7%
Other values (119) 1062
55.2%
Common
ValueCountFrequency (%)
+ 47
27.2%
45
26.0%
2 32
18.5%
) 19
11.0%
( 19
11.0%
3 10
 
5.8%
· 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1925
91.8%
ASCII 172
 
8.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 372
 
19.3%
리 176
 
9.1%
허 55
 
2.9%
역 49
 
2.5%
달 38
 
2.0%
펴 37
 
1.9%
인 37
 
1.9%
돌 34
 
1.8%
타 33
 
1.7%
트 32
 
1.7%
Other values (119) 1062
55.2%
ASCII
ValueCountFrequency (%)
+ 47
27.3%
45
26.2%
2 32
18.6%
) 19
11.0%
( 19
11.0%
3 10
 
5.8%
None
ValueCountFrequency (%)
· 1
100.0%

설치년월
Text

MISSING 

Distinct59
Distinct (%)18.3%
Missing7
Missing (%)2.1%
Memory size2.7 KiB
2023-12-13T06:48:11.151492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.8266254
Min length4

Characters and Unicode

Total characters2205
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)7.1%

Sample

1st row2011.5
2nd row2019.10.
3rd row2019.10.
4th row2007
5th row2007
ValueCountFrequency (%)
2018.11 38
 
11.5%
2021.2 30
 
9.1%
2018.12 25
 
7.6%
2020.2 17
 
5.1%
2020.4 15
 
4.5%
2019.4 15
 
4.5%
2019.3 13
 
3.9%
2018.3 12
 
3.6%
2016.9 12
 
3.6%
2020.3 11
 
3.3%
Other values (47) 143
43.2%
2023-12-13T06:48:11.565016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 536
24.3%
. 512
23.2%
0 416
18.9%
1 404
18.3%
8 95
 
4.3%
9 62
 
2.8%
3 45
 
2.0%
4 41
 
1.9%
6 37
 
1.7%
7 32
 
1.5%
Other values (2) 25
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1685
76.4%
Other Punctuation 512
 
23.2%
Space Separator 8
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 536
31.8%
0 416
24.7%
1 404
24.0%
8 95
 
5.6%
9 62
 
3.7%
3 45
 
2.7%
4 41
 
2.4%
6 37
 
2.2%
7 32
 
1.9%
5 17
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 512
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2205
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 536
24.3%
. 512
23.2%
0 416
18.9%
1 404
18.3%
8 95
 
4.3%
9 62
 
2.8%
3 45
 
2.0%
4 41
 
1.9%
6 37
 
1.7%
7 32
 
1.5%
Other values (2) 25
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 536
24.3%
. 512
23.2%
0 416
18.9%
1 404
18.3%
8 95
 
4.3%
9 62
 
2.8%
3 45
 
2.0%
4 41
 
1.9%
6 37
 
1.7%
7 32
 
1.5%
Other values (2) 25
 
1.1%

설치년도
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2021.2.
30 
2018.11.
29 
2016
24 
2018.12.
23 
2017
22 
Other values (36)
202 

Length

Max length8
Median length7
Mean length6.1242424
Min length4

Unique

Unique9 ?
Unique (%)2.7%

Sample

1st row2011
2nd row2019.10.
3rd row2019.10.
4th row2007
5th row2007

Common Values

ValueCountFrequency (%)
2021.2. 30
 
9.1%
2018.11. 29
 
8.8%
2016 24
 
7.3%
2018.12. 23
 
7.0%
2017 22
 
6.7%
2020.2. 17
 
5.2%
2020.4. 15
 
4.5%
2018 14
 
4.2%
2012 13
 
3.9%
2019.3. 12
 
3.6%
Other values (31) 131
39.7%

Length

2023-12-13T06:48:11.729263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018.11 38
 
11.5%
2021.2 30
 
9.1%
2018.12 25
 
7.6%
2016 24
 
7.3%
2017 22
 
6.7%
2020.2 17
 
5.2%
2020.4 15
 
4.5%
2019.4 15
 
4.5%
2018 14
 
4.2%
2019.3 13
 
3.9%
Other values (26) 117
35.5%

관리번호
Text

Distinct328
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T06:48:12.009366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.5727273
Min length4

Characters and Unicode

Total characters2499
Distinct characters61
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

Unique326 ?
Unique (%)98.8%

Sample

1st row우이천 1-1
2nd row우이천 1-2
3rd row우이천 1-3
4th row우이천 1-4
5th row우이천 1-5
ValueCountFrequency (%)
우이천 62
 
12.7%
중랑천 54
 
11.0%
중랑천(제방 33
 
6.7%
도봉2동 10
 
2.0%
2-4 4
 
0.8%
3-4 4
 
0.8%
2-1 4
 
0.8%
2-3 4
 
0.8%
2-2 4
 
0.8%
1-1 3
 
0.6%
Other values (251) 307
62.8%
2023-12-13T06:48:12.498352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 330
 
13.2%
천 203
 
8.1%
159
 
6.4%
1 158
 
6.3%
2 119
 
4.8%
중 98
 
3.9%
랑 98
 
3.9%
이 80
 
3.2%
마 80
 
3.2%
우 80
 
3.2%
Other values (51) 1094
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1286
51.5%
Decimal Number 634
25.4%
Dash Punctuation 330
 
13.2%
Space Separator 159
 
6.4%
Open Punctuation 45
 
1.8%
Close Punctuation 45
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 203
15.8%
중 98
 
7.6%
랑 98
 
7.6%
이 80
 
6.2%
마 80
 
6.2%
우 80
 
6.2%
방 65
 
5.1%
동 64
 
5.0%
제 53
 
4.1%
당 46
 
3.6%
Other values (37) 419
32.6%
Decimal Number
ValueCountFrequency (%)
1 158
24.9%
2 119
18.8%
3 78
12.3%
4 70
11.0%
5 58
 
9.1%
6 42
 
6.6%
8 36
 
5.7%
7 35
 
5.5%
9 28
 
4.4%
0 10
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 330
100.0%
Space Separator
ValueCountFrequency (%)
159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1286
51.5%
Common 1213
48.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 203
15.8%
중 98
 
7.6%
랑 98
 
7.6%
이 80
 
6.2%
마 80
 
6.2%
우 80
 
6.2%
방 65
 
5.1%
동 64
 
5.0%
제 53
 
4.1%
당 46
 
3.6%
Other values (37) 419
32.6%
Common
ValueCountFrequency (%)
- 330
27.2%
159
13.1%
1 158
13.0%
2 119
 
9.8%
3 78
 
6.4%
4 70
 
5.8%
5 58
 
4.8%
( 45
 
3.7%
) 45
 
3.7%
6 42
 
3.5%
Other values (4) 109
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1286
51.5%
ASCII 1213
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 330
27.2%
159
13.1%
1 158
13.0%
2 119
 
9.8%
3 78
 
6.4%
4 70
 
5.8%
5 58
 
4.8%
( 45
 
3.7%
) 45
 
3.7%
6 42
 
3.5%
Other values (4) 109
 
9.0%
Hangul
ValueCountFrequency (%)
천 203
15.8%
중 98
 
7.6%
랑 98
 
7.6%
이 80
 
6.2%
마 80
 
6.2%
우 80
 
6.2%
방 65
 
5.1%
동 64
 
5.0%
제 53
 
4.1%
당 46
 
3.6%
Other values (37) 419
32.6%

행정동
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
도봉2동
79 
도봉1동
43 
창2동
32 
방학2동
32 
창4동
30 
Other values (7)
114 

Length

Max length4
Median length4
Mean length3.7424242
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쌍문3동
2nd row쌍문3동
3rd row쌍문3동
4th row쌍문3동
5th row쌍문3동

Common Values

ValueCountFrequency (%)
도봉2동 79
23.9%
도봉1동 43
13.0%
창2동 32
9.7%
방학2동 32
9.7%
창4동 30
 
9.1%
쌍문3동 28
 
8.5%
방학1동 26
 
7.9%
창3동 23
 
7.0%
쌍문1동 17
 
5.2%
방학3동 10
 
3.0%
Other values (2) 10
 
3.0%

Length

2023-12-13T06:48:12.649880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도봉2동 79
23.9%
도봉1동 43
13.0%
창2동 32
9.7%
방학2동 32
9.7%
창4동 30
 
9.1%
쌍문3동 28
 
8.5%
방학1동 26
 
7.9%
창3동 23
 
7.0%
쌍문1동 17
 
5.2%
방학3동 10
 
3.0%
Other values (2) 10
 
3.0%

Interactions

2023-12-13T06:48:09.007966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:48:12.761255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위치상세위치설치년월설치년도행정동
연번1.0000.9390.9940.9290.9080.870
위치0.9391.0000.9780.8830.8320.917
상세위치0.9940.9781.0000.9780.9571.000
설치년월0.9290.8830.9781.0000.9990.946
설치년도0.9080.8320.9570.9991.0000.899
행정동0.8700.9171.0000.9460.8991.000
2023-12-13T06:48:12.890337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세위치설치년도행정동위치
상세위치1.0000.5000.9480.707
설치년도0.5001.0000.5270.343
행정동0.9480.5271.0000.623
위치0.7070.3430.6231.000
2023-12-13T06:48:13.016627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위치상세위치설치년도행정동
연번1.0000.7090.8890.5340.611
위치0.7091.0000.7070.3430.623
상세위치0.8890.7071.0000.5000.948
설치년도0.5340.3430.5001.0000.527
행정동0.6110.6230.9480.5271.000

Missing values

2023-12-13T06:48:09.144699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:48:09.301460image/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

연번위치상세위치기구명설치년월설치년도관리번호행정동
01우이천수유교 아래(한일병원)거꾸로매달리기2011.52011우이천 1-1쌍문3동
12우이천수유교 아래(한일병원)공중걷기2019.10.2019.10.우이천 1-2쌍문3동
23우이천수유교 아래(한일병원)좌우파도타기2019.10.2019.10.우이천 1-3쌍문3동
34우이천수유교 아래(한일병원)2인 윗몸일으키기20072007우이천 1-4쌍문3동
45우이천수유교 아래(한일병원)3단철봉20072007우이천 1-5쌍문3동
56우이천수유교 아래(한일병원)상체근육풀기2018.3.2018우이천 1-6쌍문3동
67우이천수유교 아래(한일병원)역기올리기+역기내리기2018.3.2018우이천 1-7쌍문3동
78우이천수유교 아래(한일병원)평형봉20052005우이천 1-8쌍문3동
89우이천수유교 아래(한일병원)역기20102010우이천 1-9쌍문3동
910우이천수유교 아래(분수대 주변)등허리지압기2018.11.2018.11우이천 2-1쌍문3동
연번위치상세위치기구명설치년월설치년도관리번호행정동
320321방학천변쌍문동 8-14양팔줄당기기2017. 7.2017방학천1-5쌍문2동
321322다락원 체육공원다락원체육공원 건너편 인도오금펴기+파도타기2020.2.2020.2.다락원1-1도봉2동
322323다락원 체육공원다락원체육공원 건너편 인도롤링웨이스트(파도타기)2019.3.2019.3.다락원1-2도봉2동
323324다락원 체육공원다락원체육공원 건너편 인도레그프레스(오금펴기)2019.3.2019.3.다락원1-3도봉2동
324325다락원 체육공원다락원체육공원 건너편 인도역기올리기+역기내리기2019.3.2019.3.다락원1-4도봉2동
325326다락원 체육공원다락원체육공원 건너편 인도양팔줄당기기2019.3.2019.3.다락원1-5도봉2동
326327다락원 체육공원다락원체육공원 건너편 인도달리기2021.2.2021.2.다락원1-6도봉2동
327328다락원 체육공원다락원체육공원 건너편 인도공중걷기2021.2.2021.2.다락원1-7도봉2동
328329다락원 체육공원다락원체육공원 건너편 인도어깨유연성운동2021.2.2021.2.다락원1-8도봉2동
329330다락원 체육공원다락원체육공원 건너편 인도로프당기기2021.2.2021.2.다락원1-9도봉2동