Overview

Dataset statistics

Number of variables7
Number of observations904
Missing cells0
Missing cells (%)0.0%
Duplicate rows17
Duplicate rows (%)1.9%
Total size in memory51.3 KiB
Average record size in memory58.1 B

Variable types

Text3
Numeric2
Categorical2

Dataset

Description서울특별시 서대문구 관내에 위치한 공원들의 야외운동기구 현황(시설명, 주소, 좌표 등)에 대한 정보를 제공합니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15085619/fileData.do

Alerts

관리부서 has constant value ""Constant
Dataset has 17 (1.9%) duplicate rowsDuplicates
경도 is highly overall correlated with 조사일자High correlation
조사일자 is highly overall correlated with 경도High correlation

Reproduction

Analysis started2023-12-12 00:56:50.214048
Analysis finished2023-12-12 00:56:51.332067
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공원명
Text

Distinct76
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T09:56:51.528438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.6548673
Min length4

Characters and Unicode

Total characters5112
Distinct characters127
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

Unique2 ?
Unique (%)0.2%

Sample

1st row연희지하차도위휴식공간
2nd row연희지하차도위휴식공간
3rd row연희지하차도위휴식공간
4th row연희지하차도위휴식공간
5th row연희지하차도위휴식공간
ValueCountFrequency (%)
안산공원 245
27.1%
궁동근린공원 90
 
10.0%
북한산공원 84
 
9.3%
백련산근린공원 68
 
7.5%
인왕산공원 45
 
5.0%
서대문독립공원 21
 
2.3%
실락어린이공원 13
 
1.4%
홍제근린공원 13
 
1.4%
창천근린공원 12
 
1.3%
창천동골목공원 11
 
1.2%
Other values (65) 302
33.4%
2023-12-12T09:56:51.958704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 874
17.1%
공 871
17.0%
산 448
 
8.8%
린 329
 
6.4%
안 245
 
4.8%
근 199
 
3.9%
이 138
 
2.7%
동 131
 
2.6%
어 130
 
2.5%
소 125
 
2.4%
Other values (117) 1622
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5099
99.7%
Decimal Number 12
 
0.2%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 874
17.1%
공 871
17.1%
산 448
 
8.8%
린 329
 
6.5%
안 245
 
4.8%
근 199
 
3.9%
이 138
 
2.7%
동 131
 
2.6%
어 130
 
2.5%
소 125
 
2.5%
Other values (114) 1609
31.6%
Decimal Number
ValueCountFrequency (%)
3 8
66.7%
2 4
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5099
99.7%
Common 13
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 874
17.1%
공 871
17.1%
산 448
 
8.8%
린 329
 
6.5%
안 245
 
4.8%
근 199
 
3.9%
이 138
 
2.7%
동 131
 
2.6%
어 130
 
2.5%
소 125
 
2.5%
Other values (114) 1609
31.6%
Common
ValueCountFrequency (%)
3 8
61.5%
2 4
30.8%
1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5099
99.7%
ASCII 13
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 874
17.1%
공 871
17.1%
산 448
 
8.8%
린 329
 
6.5%
안 245
 
4.8%
근 199
 
3.9%
이 138
 
2.7%
동 131
 
2.6%
어 130
 
2.5%
소 125
 
2.5%
Other values (114) 1609
31.6%
ASCII
ValueCountFrequency (%)
3 8
61.5%
2 4
30.8%
1
 
7.7%

소재지지번주소
Text

Distinct75
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T09:56:52.248177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length20.387168
Min length18

Characters and Unicode

Total characters18430
Distinct characters42
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

Unique1 ?
Unique (%)0.1%

Sample

1st row서울특별시 서대문구 연희동 151-32
2nd row서울특별시 서대문구 연희동 151-32
3rd row서울특별시 서대문구 연희동 151-32
4th row서울특별시 서대문구 연희동 151-32
5th row서울특별시 서대문구 연희동 151-32
ValueCountFrequency (%)
서울특별시 904
25.0%
서대문구 904
25.0%
연희동 385
10.6%
산2-75 245
 
6.8%
홍은동 227
 
6.3%
홍제동 95
 
2.6%
188-22 90
 
2.5%
산1-279 84
 
2.3%
산11-279 68
 
1.9%
산1-1 45
 
1.2%
Other values (79) 569
15.7%
2023-12-12T09:56:52.627428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2712
14.7%
서 1808
 
9.8%
울 904
 
4.9%
문 904
 
4.9%
대 904
 
4.9%
구 904
 
4.9%
시 904
 
4.9%
별 904
 
4.9%
특 904
 
4.9%
동 899
 
4.9%
Other values (32) 6683
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11415
61.9%
Decimal Number 3463
 
18.8%
Space Separator 2712
 
14.7%
Dash Punctuation 840
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1808
15.8%
울 904
7.9%
문 904
7.9%
대 904
7.9%
구 904
7.9%
시 904
7.9%
별 904
7.9%
특 904
7.9%
동 899
7.9%
산 442
 
3.9%
Other values (20) 1938
17.0%
Decimal Number
ValueCountFrequency (%)
2 759
21.9%
1 673
19.4%
7 522
15.1%
5 394
11.4%
8 283
 
8.2%
3 246
 
7.1%
9 228
 
6.6%
4 156
 
4.5%
0 106
 
3.1%
6 96
 
2.8%
Space Separator
ValueCountFrequency (%)
2712
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11415
61.9%
Common 7015
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1808
15.8%
울 904
7.9%
문 904
7.9%
대 904
7.9%
구 904
7.9%
시 904
7.9%
별 904
7.9%
특 904
7.9%
동 899
7.9%
산 442
 
3.9%
Other values (20) 1938
17.0%
Common
ValueCountFrequency (%)
2712
38.7%
- 840
 
12.0%
2 759
 
10.8%
1 673
 
9.6%
7 522
 
7.4%
5 394
 
5.6%
8 283
 
4.0%
3 246
 
3.5%
9 228
 
3.3%
4 156
 
2.2%
Other values (2) 202
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11415
61.9%
ASCII 7015
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2712
38.7%
- 840
 
12.0%
2 759
 
10.8%
1 673
 
9.6%
7 522
 
7.4%
5 394
 
5.6%
8 283
 
4.0%
3 246
 
3.5%
9 228
 
3.3%
4 156
 
2.2%
Other values (2) 202
 
2.9%
Hangul
ValueCountFrequency (%)
서 1808
15.8%
울 904
7.9%
문 904
7.9%
대 904
7.9%
구 904
7.9%
시 904
7.9%
별 904
7.9%
특 904
7.9%
동 899
7.9%
산 442
 
3.9%
Other values (20) 1938
17.0%

시설명
Text

Distinct127
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T09:56:52.830574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length5.2356195
Min length2

Characters and Unicode

Total characters4733
Distinct characters128
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

Unique67 ?
Unique (%)7.4%

Sample

1st row기타(체어풀)
2nd row공중걷기
3rd row상체근육풀기
4th row허리돌리기
5th row기타(스텝사이클)
ValueCountFrequency (%)
허리돌리기 119
 
12.3%
공중걷기 87
 
9.0%
기타 82
 
8.4%
파도타기 79
 
8.1%
상체근육풀기 68
 
7.0%
윗몸일으키기 62
 
6.4%
허리돌리기(롤링 30
 
3.1%
평행봉 30
 
3.1%
턱걸이 29
 
3.0%
거꾸로매달리기 25
 
2.6%
Other values (104) 360
37.1%
2023-12-12T09:56:53.180750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 851
 
18.0%
리 465
 
9.8%
타 243
 
5.1%
허 193
 
4.1%
돌 160
 
3.4%
126
 
2.7%
풀 106
 
2.2%
) 99
 
2.1%
( 99
 
2.1%
공 91
 
1.9%
Other values (118) 2300
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4339
91.7%
Space Separator 126
 
2.7%
Close Punctuation 99
 
2.1%
Open Punctuation 99
 
2.1%
Decimal Number 63
 
1.3%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 851
19.6%
리 465
 
10.7%
타 243
 
5.6%
허 193
 
4.4%
돌 160
 
3.7%
풀 106
 
2.4%
공 91
 
2.1%
걷 91
 
2.1%
중 90
 
2.1%
체 88
 
2.0%
Other values (107) 1961
45.2%
Decimal Number
ValueCountFrequency (%)
2 42
66.7%
3 10
 
15.9%
4 5
 
7.9%
5 3
 
4.8%
6 1
 
1.6%
7 1
 
1.6%
1 1
 
1.6%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4339
91.7%
Common 394
 
8.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 851
19.6%
리 465
 
10.7%
타 243
 
5.6%
허 193
 
4.4%
돌 160
 
3.7%
풀 106
 
2.4%
공 91
 
2.1%
걷 91
 
2.1%
중 90
 
2.1%
체 88
 
2.0%
Other values (107) 1961
45.2%
Common
ValueCountFrequency (%)
126
32.0%
) 99
25.1%
( 99
25.1%
2 42
 
10.7%
3 10
 
2.5%
/ 7
 
1.8%
4 5
 
1.3%
5 3
 
0.8%
6 1
 
0.3%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4339
91.7%
ASCII 394
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 851
19.6%
리 465
 
10.7%
타 243
 
5.6%
허 193
 
4.4%
돌 160
 
3.7%
풀 106
 
2.4%
공 91
 
2.1%
걷 91
 
2.1%
중 90
 
2.1%
체 88
 
2.0%
Other values (107) 1961
45.2%
ASCII
ValueCountFrequency (%)
126
32.0%
) 99
25.1%
( 99
25.1%
2 42
 
10.7%
3 10
 
2.5%
/ 7
 
1.8%
4 5
 
1.3%
5 3
 
0.8%
6 1
 
0.3%
7 1
 
0.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct557
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94051
Minimum126.90701
Maximum126.96237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2023-12-12T09:56:53.326269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90701
5-th percentile126.91698
Q1126.9301
median126.94324
Q3126.95101
95-th percentile126.95885
Maximum126.96237
Range0.055357
Interquartile range (IQR)0.0209114

Descriptive statistics

Standard deviation0.012999679
Coefficient of variation (CV)0.00010240765
Kurtosis-0.66614348
Mean126.94051
Median Absolute Deviation (MAD)0.01047995
Skewness-0.45196215
Sum114754.22
Variance0.00016899166
MonotonicityNot monotonic
2023-12-12T09:56:53.544863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9228491 14
 
1.5%
126.9432716 13
 
1.4%
126.9516261 13
 
1.4%
126.9248091 9
 
1.0%
126.9576168 9
 
1.0%
126.940595 8
 
0.9%
126.9430363 8
 
0.9%
126.9292457 8
 
0.9%
126.930451 8
 
0.9%
126.9465 7
 
0.8%
Other values (547) 807
89.3%
ValueCountFrequency (%)
126.907011 1
0.1%
126.907017 1
0.1%
126.908279 1
0.1%
126.908284 1
0.1%
126.908288 1
0.1%
126.908302 1
0.1%
126.908311 1
0.1%
126.908332 1
0.1%
126.90834 1
0.1%
126.909731 1
0.1%
ValueCountFrequency (%)
126.962368 1
 
0.1%
126.962334 1
 
0.1%
126.9623 1
 
0.1%
126.962269 1
 
0.1%
126.962239 1
 
0.1%
126.961806 2
 
0.2%
126.96093 5
0.6%
126.960918 1
 
0.1%
126.9609 1
 
0.1%
126.960878 1
 
0.1%

위도
Real number (ℝ)

Distinct552
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.579239
Minimum37.557657
Maximum37.603869
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2023-12-12T09:56:53.725538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.557657
5-th percentile37.560564
Q137.570668
median37.575128
Q337.588386
95-th percentile37.601551
Maximum37.603869
Range0.046212
Interquartile range (IQR)0.01771737

Descriptive statistics

Standard deviation0.012048349
Coefficient of variation (CV)0.00032061185
Kurtosis-0.7540197
Mean37.579239
Median Absolute Deviation (MAD)0.0065741
Skewness0.40586046
Sum33971.632
Variance0.00014516271
MonotonicityNot monotonic
2023-12-12T09:56:53.933170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5697866 14
 
1.5%
37.5746111 13
 
1.4%
37.6038249 13
 
1.4%
37.5673875 9
 
1.0%
37.5685536 9
 
1.0%
37.583373 8
 
0.9%
37.580702 8
 
0.9%
37.5982676 8
 
0.9%
37.5952947 8
 
0.9%
37.579353 7
 
0.8%
Other values (542) 807
89.3%
ValueCountFrequency (%)
37.5576572 2
0.2%
37.5576609 1
0.1%
37.5576634 1
0.1%
37.5576745 1
0.1%
37.5576968 1
0.1%
37.5577297 1
0.1%
37.5577427 1
0.1%
37.5577439 1
0.1%
37.5578636 2
0.2%
37.557871 1
0.1%
ValueCountFrequency (%)
37.6038692 1
 
0.1%
37.6038679 1
 
0.1%
37.6038249 13
1.4%
37.6037255 2
 
0.2%
37.6034537 2
 
0.2%
37.603083 3
 
0.3%
37.6028764 2
 
0.2%
37.6026688 5
 
0.6%
37.6018979 3
 
0.3%
37.601725 1
 
0.1%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
서대문구청 푸른도시과
904 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서대문구청 푸른도시과
2nd row서대문구청 푸른도시과
3rd row서대문구청 푸른도시과
4th row서대문구청 푸른도시과
5th row서대문구청 푸른도시과

Common Values

ValueCountFrequency (%)
서대문구청 푸른도시과 904
100.0%

Length

2023-12-12T09:56:54.137748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:56:54.587934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구청 904
50.0%
푸른도시과 904
50.0%

조사일자
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2021-07-26
282 
2021-07-27
70 
2021-07-07
69 
2021-07-13
51 
2021-07-21
50 
Other values (12)
382 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-05
2nd row2021-07-05
3rd row2021-07-05
4th row2021-07-05
5th row2021-07-05

Common Values

ValueCountFrequency (%)
2021-07-26 282
31.2%
2021-07-27 70
 
7.7%
2021-07-07 69
 
7.6%
2021-07-13 51
 
5.6%
2021-07-21 50
 
5.5%
2021-07-09 45
 
5.0%
2021-07-14 44
 
4.9%
2021-07-08 41
 
4.5%
2021-07-22 40
 
4.4%
2021-07-06 40
 
4.4%
Other values (7) 172
19.0%

Length

2023-12-12T09:56:54.680163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-07-26 282
31.2%
2021-07-27 70
 
7.7%
2021-07-07 69
 
7.6%
2021-07-13 51
 
5.6%
2021-07-21 50
 
5.5%
2021-07-09 45
 
5.0%
2021-07-14 44
 
4.9%
2021-07-08 41
 
4.5%
2021-07-06 40
 
4.4%
2021-07-22 40
 
4.4%
Other values (7) 172
19.0%

Interactions

2023-12-12T09:56:50.882568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:56:50.627267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:56:50.997128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:56:50.740008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:56:54.781307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공원명소재지지번주소경도위도조사일자
공원명1.0001.0000.9700.9690.995
소재지지번주소1.0001.0000.9720.9710.994
경도0.9700.9721.0000.6310.826
위도0.9690.9710.6311.0000.815
조사일자0.9950.9940.8260.8151.000
2023-12-12T09:56:54.910310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도조사일자
경도1.0000.0210.506
위도0.0211.0000.490
조사일자0.5060.4901.000

Missing values

2023-12-12T09:56:51.141985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:56:51.284141image/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

공원명소재지지번주소시설명경도위도관리부서조사일자
0연희지하차도위휴식공간서울특별시 서대문구 연희동 151-32기타(체어풀)126.93415837.576803서대문구청 푸른도시과2021-07-05
1연희지하차도위휴식공간서울특별시 서대문구 연희동 151-32공중걷기126.93412737.576792서대문구청 푸른도시과2021-07-05
2연희지하차도위휴식공간서울특별시 서대문구 연희동 151-32상체근육풀기126.93416437.576783서대문구청 푸른도시과2021-07-05
3연희지하차도위휴식공간서울특별시 서대문구 연희동 151-32허리돌리기126.93413537.576773서대문구청 푸른도시과2021-07-05
4연희지하차도위휴식공간서울특별시 서대문구 연희동 151-32기타(스텝사이클)126.93415137.576791서대문구청 푸른도시과2021-07-05
5다람쥐어린이공원서울특별시 서대문구 연희동 151-49윗몸일으키기126.93447337.575994서대문구청 푸른도시과2021-07-05
6다람쥐어린이공원서울특별시 서대문구 연희동 151-49상체근육풀기126.93445437.576045서대문구청 푸른도시과2021-07-05
7다람쥐어린이공원서울특별시 서대문구 연희동 151-49공중걷기126.93445637.576071서대문구청 푸른도시과2021-07-05
8홍연소공원서울특별시 서대문구 연희동 723-15등허리지압기126.9324637.576124서대문구청 푸른도시과2021-07-05
9홍연소공원서울특별시 서대문구 연희동 723-15공중걷기126.93245237.57616서대문구청 푸른도시과2021-07-05
공원명소재지지번주소시설명경도위도관리부서조사일자
894창천근린공원서울특별시 서대문구 창천동 4-55거꾸로매달리기126.94023937.557744서대문구청 푸른도시과2021-07-28
895창천근린공원서울특별시 서대문구 창천동 4-55파도타기126.94027337.557697서대문구청 푸른도시과2021-07-28
896창천근린공원서울특별시 서대문구 창천동 4-55파도타기2126.94027337.557674서대문구청 푸른도시과2021-07-28
897창천근린공원서울특별시 서대문구 창천동 4-55등허리지압기126.94026137.557663서대문구청 푸른도시과2021-07-28
898창천근린공원서울특별시 서대문구 창천동 4-55풀웨이트126.94030437.557661서대문구청 푸른도시과2021-07-28
899창천근린공원서울특별시 서대문구 창천동 4-55기타126.94027937.557657서대문구청 푸른도시과2021-07-28
900창천근린공원서울특별시 서대문구 창천동 4-55기타2126.94027937.557657서대문구청 푸른도시과2021-07-28
901창천근린공원서울특별시 서대문구 창천동 4-55평행봉126.94083837.557864서대문구청 푸른도시과2021-07-28
902창천근린공원서울특별시 서대문구 창천동 4-55윗몸일으키기126.94082537.557901서대문구청 푸른도시과2021-07-28
903창천근린공원서울특별시 서대문구 창천동 4-55기타126.94084437.557864서대문구청 푸른도시과2021-07-28

Duplicate rows

Most frequently occurring

공원명소재지지번주소시설명경도위도관리부서조사일자# duplicates
7안산공원서울특별시 서대문구 연희동 산2-75기타126.95098837.570946서대문구청 푸른도시과2021-07-265
1안산공원서울특별시 서대문구 연희동 산2-75기타126.94311637.575369서대문구청 푸른도시과2021-07-264
2안산공원서울특별시 서대문구 연희동 산2-75기타126.94327237.574611서대문구청 푸른도시과2021-07-264
8안산공원서울특별시 서대문구 연희동 산2-75기타126.9570537.570154서대문구청 푸른도시과2021-07-264
4안산공원서울특별시 서대문구 연희동 산2-75기타126.946537.579353서대문구청 푸른도시과2021-07-263
11안산공원서울특별시 서대문구 연희동 산2-75허리돌리기126.94059537.580702서대문구청 푸른도시과2021-07-263
15안산공원서울특별시 서대문구 연희동 산2-75허리돌리기126.95172937.570362서대문구청 푸른도시과2021-07-263
0안산공원서울특별시 서대문구 연희동 산2-75공중걷기126.94327237.574611서대문구청 푸른도시과2021-07-262
3안산공원서울특별시 서대문구 연희동 산2-75기타126.94429537.573855서대문구청 푸른도시과2021-07-262
5안산공원서울특별시 서대문구 연희동 산2-75기타126.94663137.574517서대문구청 푸른도시과2021-07-262