Overview

Dataset statistics

Number of variables8
Number of observations193
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.9 KiB
Average record size in memory68.7 B

Variable types

Numeric3
Text2
Categorical3

Dataset

Description폐형광등건전기 수거함 설치 현황(수거함 장소, 주소, 종류, 위경도)
Author서울특별시 도봉구
URLhttps://www.data.go.kr/data/15038207/fileData.do

Alerts

종류 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
설치수량 is highly overall correlated with 종류High correlation
연번 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
설치수량 is highly imbalanced (58.2%)Imbalance
종류 is highly imbalanced (59.4%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:58:20.305622
Analysis finished2023-12-12 06:58:21.949281
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97
Minimum1
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T15:58:22.013209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.6
Q149
median97
Q3145
95-th percentile183.4
Maximum193
Range192
Interquartile range (IQR)96

Descriptive statistics

Standard deviation55.858452
Coefficient of variation (CV)0.57586033
Kurtosis-1.2
Mean97
Median Absolute Deviation (MAD)48
Skewness0
Sum18721
Variance3120.1667
MonotonicityStrictly increasing
2023-12-12T15:58:22.143553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
146 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
Other values (183) 183
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%

장소
Text

Distinct174
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T15:58:22.358690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4248705
Min length3

Characters and Unicode

Total characters1240
Distinct characters196
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

Unique168 ?
Unique (%)87.0%

Sample

1st row동사무소
2nd row염광아파트
3rd row도봉도서관
4th row동익파크아파트
5th row쌍문1동 경로당
ValueCountFrequency (%)
동사무소 13
 
6.5%
한신아파트 3
 
1.5%
극동아파트 3
 
1.5%
청구아파트 2
 
1.0%
경로당 2
 
1.0%
아파트 2
 
1.0%
금용아파트 2
 
1.0%
삼익쎄라믹아파트 2
 
1.0%
북한산아이파크아파트 1
 
0.5%
동아그린아파트 1
 
0.5%
Other values (170) 170
84.6%
2023-12-12T15:58:22.704131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 129
 
10.4%
파 103
 
8.3%
트 103
 
8.3%
동 47
 
3.8%
차 30
 
2.4%
신 23
 
1.9%
학 23
 
1.9%
대 20
 
1.6%
도 19
 
1.5%
교 19
 
1.5%
Other values (186) 724
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1118
90.2%
Decimal Number 57
 
4.6%
Open Punctuation 18
 
1.5%
Close Punctuation 18
 
1.5%
Uppercase Letter 17
 
1.4%
Space Separator 8
 
0.6%
Other Punctuation 2
 
0.2%
Other Symbol 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 129
 
11.5%
파 103
 
9.2%
트 103
 
9.2%
동 47
 
4.2%
차 30
 
2.7%
신 23
 
2.1%
학 23
 
2.1%
대 20
 
1.8%
도 19
 
1.7%
교 19
 
1.7%
Other values (165) 602
53.8%
Decimal Number
ValueCountFrequency (%)
2 18
31.6%
1 17
29.8%
3 7
 
12.3%
4 6
 
10.5%
5 3
 
5.3%
7 2
 
3.5%
9 2
 
3.5%
8 1
 
1.8%
6 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
29.4%
A 4
23.5%
E 4
23.5%
K 2
 
11.8%
T 1
 
5.9%
D 1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1119
90.2%
Common 103
 
8.3%
Latin 18
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 129
 
11.5%
파 103
 
9.2%
트 103
 
9.2%
동 47
 
4.2%
차 30
 
2.7%
신 23
 
2.1%
학 23
 
2.1%
대 20
 
1.8%
도 19
 
1.7%
교 19
 
1.7%
Other values (166) 603
53.9%
Common
ValueCountFrequency (%)
( 18
17.5%
2 18
17.5%
) 18
17.5%
1 17
16.5%
8
7.8%
3 7
 
6.8%
4 6
 
5.8%
5 3
 
2.9%
, 2
 
1.9%
7 2
 
1.9%
Other values (3) 4
 
3.9%
Latin
ValueCountFrequency (%)
S 5
27.8%
A 4
22.2%
E 4
22.2%
K 2
 
11.1%
T 1
 
5.6%
D 1
 
5.6%
e 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1118
90.2%
ASCII 121
 
9.8%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 129
 
11.5%
파 103
 
9.2%
트 103
 
9.2%
동 47
 
4.2%
차 30
 
2.7%
신 23
 
2.1%
학 23
 
2.1%
대 20
 
1.8%
도 19
 
1.7%
교 19
 
1.7%
Other values (165) 602
53.8%
ASCII
ValueCountFrequency (%)
( 18
14.9%
2 18
14.9%
) 18
14.9%
1 17
14.0%
8
6.6%
3 7
 
5.8%
4 6
 
5.0%
S 5
 
4.1%
A 4
 
3.3%
E 4
 
3.3%
Other values (10) 16
13.2%
None
ValueCountFrequency (%)
㈜ 1
100.0%

설치수량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
158 
<NA>
28 
2
 
6
4
 
1

Length

Max length4
Median length1
Mean length1.4352332
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 158
81.9%
<NA> 28
 
14.5%
2 6
 
3.1%
4 1
 
0.5%

Length

2023-12-12T15:58:23.211849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:58:23.349573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 158
81.9%
na 28
 
14.5%
2 6
 
3.1%
4 1
 
0.5%

행정동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
방학3동
23 
방학1동
18 
창4동
18 
창5동
18 
도봉2동
18 
Other values (9)
98 

Length

Max length4
Median length4
Mean length3.6528497
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row쌍문1동
2nd row쌍문1동
3rd row쌍문1동
4th row쌍문1동
5th row쌍문1동

Common Values

ValueCountFrequency (%)
방학3동 23
11.9%
방학1동 18
9.3%
창4동 18
9.3%
창5동 18
9.3%
도봉2동 18
9.3%
쌍문1동 17
8.8%
쌍문2동 16
8.3%
쌍문4동 14
7.3%
창1동 12
6.2%
창2동 11
 
5.7%
Other values (4) 28
14.5%

Length

2023-12-12T15:58:23.504721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방학3동 23
11.9%
방학1동 18
9.3%
창4동 18
9.3%
창5동 18
9.3%
도봉2동 18
9.3%
쌍문1동 17
8.8%
쌍문2동 16
8.3%
쌍문4동 14
7.3%
창1동 12
6.2%
창2동 11
 
5.7%
Other values (4) 28
14.5%

종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
수거함
164 
운반함박스
28 
<NA>
 
1

Length

Max length5
Median length3
Mean length3.2953368
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
수거함 164
85.0%
운반함박스 28
 
14.5%
<NA> 1
 
0.5%

Length

2023-12-12T15:58:23.686967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:58:23.799556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수거함 164
85.0%
운반함박스 28
 
14.5%
na 1
 
0.5%

주소
Text

Distinct188
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T15:58:24.074069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.880829
Min length15

Characters and Unicode

Total characters3644
Distinct characters46
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

Unique183 ?
Unique (%)94.8%

Sample

1st row서울특별시 도봉구 노해로 147
2nd row서울특별시 도봉구 우이천로30길 28
3rd row서울특별시 도봉구 삼양로 556
4th row서울특별시 도봉구 우이천로32길 67
5th row서울특별시 도봉구 우이천로34길 9-14
ValueCountFrequency (%)
서울특별시 193
25.2%
도봉구 193
25.2%
해등로 17
 
2.2%
마들로 16
 
2.1%
시루봉로 11
 
1.4%
도봉로 7
 
0.9%
방학로 7
 
0.9%
노해로 6
 
0.8%
도당로 6
 
0.8%
도봉로180길 5
 
0.7%
Other values (229) 305
39.8%
2023-12-12T15:58:24.504989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
576
15.8%
봉 258
 
7.1%
도 251
 
6.9%
시 209
 
5.7%
서 193
 
5.3%
구 193
 
5.3%
울 193
 
5.3%
별 193
 
5.3%
특 193
 
5.3%
로 191
 
5.2%
Other values (36) 1194
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2285
62.7%
Decimal Number 751
 
20.6%
Space Separator 576
 
15.8%
Dash Punctuation 32
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 258
11.3%
도 251
11.0%
시 209
9.1%
서 193
8.4%
구 193
8.4%
울 193
8.4%
별 193
8.4%
특 193
8.4%
로 191
8.4%
길 110
 
4.8%
Other values (24) 301
13.2%
Decimal Number
ValueCountFrequency (%)
1 156
20.8%
6 91
12.1%
2 91
12.1%
3 85
11.3%
5 75
10.0%
0 64
8.5%
4 63
8.4%
7 50
 
6.7%
8 44
 
5.9%
9 32
 
4.3%
Space Separator
ValueCountFrequency (%)
576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2285
62.7%
Common 1359
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 258
11.3%
도 251
11.0%
시 209
9.1%
서 193
8.4%
구 193
8.4%
울 193
8.4%
별 193
8.4%
특 193
8.4%
로 191
8.4%
길 110
 
4.8%
Other values (24) 301
13.2%
Common
ValueCountFrequency (%)
576
42.4%
1 156
 
11.5%
6 91
 
6.7%
2 91
 
6.7%
3 85
 
6.3%
5 75
 
5.5%
0 64
 
4.7%
4 63
 
4.6%
7 50
 
3.7%
8 44
 
3.2%
Other values (2) 64
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2285
62.7%
ASCII 1359
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
576
42.4%
1 156
 
11.5%
6 91
 
6.7%
2 91
 
6.7%
3 85
 
6.3%
5 75
 
5.5%
0 64
 
4.7%
4 63
 
4.6%
7 50
 
3.7%
8 44
 
3.2%
Other values (2) 64
 
4.7%
Hangul
ValueCountFrequency (%)
봉 258
11.3%
도 251
11.0%
시 209
9.1%
서 193
8.4%
구 193
8.4%
울 193
8.4%
별 193
8.4%
특 193
8.4%
로 191
8.4%
길 110
 
4.8%
Other values (24) 301
13.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct188
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.657906
Minimum37.63267
Maximum37.68693
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T15:58:24.635245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.63267
5-th percentile37.64068
Q137.650504
median37.656837
Q337.663477
95-th percentile37.682204
Maximum37.68693
Range0.0542606
Interquartile range (IQR)0.012972861

Descriptive statistics

Standard deviation0.011510254
Coefficient of variation (CV)0.00030565305
Kurtosis0.36607346
Mean37.657906
Median Absolute Deviation (MAD)0.0065048569
Skewness0.54944044
Sum7267.9759
Variance0.00013248595
MonotonicityNot monotonic
2023-12-12T15:58:24.795530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6554883 2
 
1.0%
37.6841853 2
 
1.0%
37.6594614287 2
 
1.0%
37.6616424655 2
 
1.0%
37.6609311047 2
 
1.0%
37.6558439 1
 
0.5%
37.6537018 1
 
0.5%
37.6607446 1
 
0.5%
37.6529104577 1
 
0.5%
37.6577850907 1
 
0.5%
Other values (178) 178
92.2%
ValueCountFrequency (%)
37.6326698 1
0.5%
37.6330531 1
0.5%
37.6334361401 1
0.5%
37.6361731 1
0.5%
37.6372226 1
0.5%
37.6375646376 1
0.5%
37.6381103 1
0.5%
37.6389973416 1
0.5%
37.6402476 1
0.5%
37.640415912 1
0.5%
ValueCountFrequency (%)
37.6869304 1
0.5%
37.6867707 1
0.5%
37.6864633 1
0.5%
37.6862598 1
0.5%
37.6853815 1
0.5%
37.6848884 1
0.5%
37.6841853 2
1.0%
37.6829494 1
0.5%
37.6826232928 1
0.5%
37.6819250727 1
0.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct188
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03773
Minimum127.0129
Maximum127.05356
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T15:58:24.951725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0129
5-th percentile127.0232
Q1127.02988
median127.03944
Q3127.04548
95-th percentile127.05064
Maximum127.05356
Range0.040662
Interquartile range (IQR)0.0156087

Descriptive statistics

Standard deviation0.00928051
Coefficient of variation (CV)7.3053179 × 10-5
Kurtosis-0.49045896
Mean127.03773
Median Absolute Deviation (MAD)0.0068589
Skewness-0.45361311
Sum24518.282
Variance8.6127865 × 10-5
MonotonicityNot monotonic
2023-12-12T15:58:25.140955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0427387 2
 
1.0%
127.0506781 2
 
1.0%
127.0480342372 2
 
1.0%
127.0463809607 2
 
1.0%
127.0278935913 2
 
1.0%
127.0406987 1
 
0.5%
127.0528025 1
 
0.5%
127.0496053 1
 
0.5%
127.0455868143 1
 
0.5%
127.0492752377 1
 
0.5%
Other values (178) 178
92.2%
ValueCountFrequency (%)
127.012899 1
0.5%
127.0136444 1
0.5%
127.0138531 1
0.5%
127.0139875 1
0.5%
127.0149044 1
0.5%
127.0173606 1
0.5%
127.0186501 1
0.5%
127.0216044 1
0.5%
127.0226882102 1
0.5%
127.0227487 1
0.5%
ValueCountFrequency (%)
127.053561 1
0.5%
127.0533207 1
0.5%
127.0528242654 1
0.5%
127.0528025 1
0.5%
127.0523186642 1
0.5%
127.051537973 1
0.5%
127.0513911 1
0.5%
127.0507188 1
0.5%
127.0506781 2
1.0%
127.0506149 1
0.5%

Interactions

2023-12-12T15:58:21.442437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:20.747452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:21.129767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:21.536078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:20.872940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:21.247874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:21.633603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:20.990301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:58:21.337017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:58:25.276268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치수량행정동종류위도경도
연번1.0000.4130.9140.9850.7930.761
설치수량0.4131.0000.307NaN0.1610.000
행정동0.9140.3071.0000.1020.8710.822
종류0.985NaN0.1021.0000.0000.000
위도0.7930.1610.8710.0001.0000.486
경도0.7610.0000.8220.0000.4861.000
2023-12-12T15:58:25.387813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류행정동설치수량
종류1.0000.0751.000
행정동0.0751.0000.172
설치수량1.0000.1721.000
2023-12-12T15:58:25.477403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도설치수량행정동종류
연번1.0000.1710.5640.1960.6890.874
위도0.1711.0000.2530.0930.5910.000
경도0.5640.2531.0000.0000.5090.000
설치수량0.1960.0930.0001.0000.1721.000
행정동0.6890.5910.5090.1721.0000.075
종류0.8740.0000.0001.0000.0751.000

Missing values

2023-12-12T15:58:21.792974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:58:21.909251image/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

연번장소설치수량행정동종류주소위도경도
01동사무소1쌍문1동수거함서울특별시 도봉구 노해로 14737.647999127.026036
12염광아파트1쌍문1동수거함서울특별시 도봉구 우이천로30길 2837.64842127.026311
23도봉도서관1쌍문1동수거함서울특별시 도봉구 삼양로 55637.652566127.012899
34동익파크아파트1쌍문1동수거함서울특별시 도봉구 우이천로32길 6737.650797127.025134
45쌍문1동 경로당1쌍문1동수거함서울특별시 도봉구 우이천로34길 9-1437.649925127.022749
56현대3차 아파트1쌍문1동수거함서울특별시 도봉구 우이천로38가길 3237.651806127.021604
67극동아파트1쌍문1동수거함서울특별시 도봉구 노해로45길 2637.651299127.02728
78쌍우경로당1쌍문1동수거함서울특별시 도봉구 우이천로45길 22-437.654483127.014904
89e편한세상아파트1쌍문1동수거함서울특별시 도봉구 노해로41가길 1637.649695127.027271
910월드메르디앙아파트1쌍문1동수거함서울특별시 도봉구 삼양로 56637.653782127.013644
연번장소설치수량행정동종류주소위도경도
183184자운초등학교<NA>창4동운반함박스서울특별시 도봉구 마들로13길 16637.657717127.046395
184185노곡중학교<NA>창4동운반함박스서울특별시 도봉구 노해로70길 9537.648591127.053561
185186창동초등학교<NA>창5동운반함박스서울특별시 도봉구 해등로16길 8137.655192127.044686
186187구민회관<NA>창5동운반함박스서울특별시 도봉구 도봉로 55237.654001127.038604
187188북부교욱청<NA>창5동운반함박스서울특별시 도봉구 노해로 31337.651686127.04339
188189이마트할인점<NA>창5동운반함박스서울특별시 도봉구 노해로65길 437.651682127.046933
189190㈜금호조명손치용<NA>도봉1동운반함박스서울특별시 도봉구 도봉로 90537.685381127.04572
190191누원초등학교<NA>도봉2동운반함박스서울특별시 도봉구 마들로 859-4437.68693127.049069
191192도봉중학교<NA>도봉2동운반함박스서울특별시 도봉구 마들로 67137.670728127.045974
192193북부지청<NA>도봉2동운반함박스서울특별시 도봉구 마들로 74737.676344127.045879