Overview

Dataset statistics

Number of variables8
Number of observations122
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory69.1 B

Variable types

Categorical3
Numeric3
Text2

Dataset

Description대구광역시 북구 관내 그늘막설치현황 데이터는 행정동, 관리번호, 소재지주소, 위도, 경도 등의 정보를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15060756/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
관리번호(지도번호) is highly overall correlated with 그늘막지름(m)High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 경도High correlation
그늘막지름(m) is highly overall correlated with 관리번호(지도번호)High correlation
그늘막지름(m) is highly imbalanced (57.0%)Imbalance
관리번호(지도번호) has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:31:19.258187
Analysis finished2024-04-06 08:31:22.754157
Duration3.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
국우동
11 
무태조야동
10 
침산2동
8 
관문동
8 
칠성동
 
7
Other values (18)
78 

Length

Max length5
Median length4
Mean length3.5983607
Min length3

Unique

Unique2 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
국우동 11
 
9.0%
무태조야동 10
 
8.2%
침산2동 8
 
6.6%
관문동 8
 
6.6%
칠성동 7
 
5.7%
동천동 7
 
5.7%
복현2동 7
 
5.7%
침산3동 6
 
4.9%
태전1동 6
 
4.9%
태전2동 6
 
4.9%
Other values (13) 46
37.7%

Length

2024-04-06T17:31:23.038119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국우동 11
 
9.0%
무태조야동 10
 
8.2%
침산2동 8
 
6.6%
관문동 8
 
6.6%
칠성동 7
 
5.7%
동천동 7
 
5.7%
복현2동 7
 
5.7%
침산3동 6
 
4.9%
태전1동 6
 
4.9%
태전2동 6
 
4.9%
Other values (13) 46
37.7%

관리번호(지도번호)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct122
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.5
Minimum1
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:31:23.389669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.05
Q131.25
median61.5
Q391.75
95-th percentile115.95
Maximum122
Range121
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation35.362409
Coefficient of variation (CV)0.57499853
Kurtosis-1.2
Mean61.5
Median Absolute Deviation (MAD)30.5
Skewness0
Sum7503
Variance1250.5
MonotonicityNot monotonic
2024-04-06T17:31:23.752900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
0.8%
71 1
 
0.8%
59 1
 
0.8%
49 1
 
0.8%
119 1
 
0.8%
93 1
 
0.8%
66 1
 
0.8%
61 1
 
0.8%
47 1
 
0.8%
20 1
 
0.8%
Other values (112) 112
91.8%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
122 1
0.8%
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%

소재지주소
Text

Distinct118
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:31:24.404064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.811475
Min length16

Characters and Unicode

Total characters2295
Distinct characters53
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

Unique115 ?
Unique (%)94.3%

Sample

1st row대구광역시 북구 고성동3가 38-3
2nd row대구광역시 북구 노원동1가 366-1
3rd row대구광역시 북구 고성동3가 1-1
4th row대구광역시 북구 고성동3가 114
5th row대구광역시 북구 고성동1가 50-217
ValueCountFrequency (%)
대구광역시 122
24.9%
북구 122
24.9%
산격동 16
 
3.3%
침산동 15
 
3.1%
태전동 12
 
2.5%
복현동 10
 
2.0%
국우동 8
 
1.6%
동천동 7
 
1.4%
구암동 5
 
1.0%
사수동 5
 
1.0%
Other values (134) 167
34.2%
2024-04-06T17:31:25.305501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
21.3%
구 249
 
10.8%
동 129
 
5.6%
대 127
 
5.5%
광 122
 
5.3%
역 122
 
5.3%
시 122
 
5.3%
북 122
 
5.3%
1 101
 
4.4%
- 77
 
3.4%
Other values (43) 635
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1237
53.9%
Decimal Number 492
 
21.4%
Space Separator 489
 
21.3%
Dash Punctuation 77
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 249
20.1%
동 129
10.4%
대 127
10.3%
광 122
9.9%
역 122
9.9%
시 122
9.9%
북 122
9.9%
산 32
 
2.6%
격 16
 
1.3%
가 16
 
1.3%
Other values (31) 180
14.6%
Decimal Number
ValueCountFrequency (%)
1 101
20.5%
3 69
14.0%
2 56
11.4%
9 46
9.3%
7 45
9.1%
8 39
 
7.9%
6 36
 
7.3%
5 34
 
6.9%
0 33
 
6.7%
4 33
 
6.7%
Space Separator
ValueCountFrequency (%)
489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1237
53.9%
Common 1058
46.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 249
20.1%
동 129
10.4%
대 127
10.3%
광 122
9.9%
역 122
9.9%
시 122
9.9%
북 122
9.9%
산 32
 
2.6%
격 16
 
1.3%
가 16
 
1.3%
Other values (31) 180
14.6%
Common
ValueCountFrequency (%)
489
46.2%
1 101
 
9.5%
- 77
 
7.3%
3 69
 
6.5%
2 56
 
5.3%
9 46
 
4.3%
7 45
 
4.3%
8 39
 
3.7%
6 36
 
3.4%
5 34
 
3.2%
Other values (2) 66
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1237
53.9%
ASCII 1058
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
46.2%
1 101
 
9.5%
- 77
 
7.3%
3 69
 
6.5%
2 56
 
5.3%
9 46
 
4.3%
7 45
 
4.3%
8 39
 
3.7%
6 36
 
3.4%
5 34
 
3.2%
Other values (2) 66
 
6.2%
Hangul
ValueCountFrequency (%)
구 249
20.1%
동 129
10.4%
대 127
10.3%
광 122
9.9%
역 122
9.9%
시 122
9.9%
북 122
9.9%
산 32
 
2.6%
격 16
 
1.3%
가 16
 
1.3%
Other values (31) 180
14.6%

설치장소
Text

Distinct117
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:31:25.731852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length11.819672
Min length5

Characters and Unicode

Total characters1442
Distinct characters246
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)92.6%

Sample

1st row북부도서관 남편
2nd row북구청네거리 교회 앞
3rd row도시공사 앞 교통섬
4th row북구청 네거리
5th row고성지구대 맞은편
ValueCountFrequency (%)
앞 64
 
18.7%
교통섬 19
 
5.5%
횡단보도 9
 
2.6%
맞은편 6
 
1.7%
코너 5
 
1.5%
아파트 4
 
1.2%
인근 3
 
0.9%
건너편 3
 
0.9%
사거리 3
 
0.9%
주요소 3
 
0.9%
Other values (191) 224
65.3%
2024-04-06T17:31:26.454905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
 
15.6%
앞 67
 
4.6%
교 44
 
3.1%
리 30
 
2.1%
거 28
 
1.9%
대 24
 
1.7%
동 23
 
1.6%
트 23
 
1.6%
스 21
 
1.5%
단 20
 
1.4%
Other values (236) 937
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1124
77.9%
Space Separator 225
 
15.6%
Decimal Number 51
 
3.5%
Uppercase Letter 31
 
2.1%
Dash Punctuation 4
 
0.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Lowercase Letter 2
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 67
 
6.0%
교 44
 
3.9%
리 30
 
2.7%
거 28
 
2.5%
대 24
 
2.1%
동 23
 
2.0%
트 23
 
2.0%
스 21
 
1.9%
단 20
 
1.8%
섬 19
 
1.7%
Other values (208) 825
73.4%
Uppercase Letter
ValueCountFrequency (%)
S 6
19.4%
K 6
19.4%
L 3
9.7%
O 3
9.7%
T 3
9.7%
D 2
 
6.5%
R 2
 
6.5%
W 2
 
6.5%
C 1
 
3.2%
P 1
 
3.2%
Other values (2) 2
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 17
33.3%
0 8
15.7%
3 6
 
11.8%
2 5
 
9.8%
5 4
 
7.8%
9 4
 
7.8%
8 3
 
5.9%
6 2
 
3.9%
4 2
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
d 1
50.0%
m 1
50.0%
Space Separator
ValueCountFrequency (%)
225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1124
77.9%
Common 285
 
19.8%
Latin 33
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 67
 
6.0%
교 44
 
3.9%
리 30
 
2.7%
거 28
 
2.5%
대 24
 
2.1%
동 23
 
2.0%
트 23
 
2.0%
스 21
 
1.9%
단 20
 
1.8%
섬 19
 
1.7%
Other values (208) 825
73.4%
Common
ValueCountFrequency (%)
225
78.9%
1 17
 
6.0%
0 8
 
2.8%
3 6
 
2.1%
2 5
 
1.8%
- 4
 
1.4%
5 4
 
1.4%
9 4
 
1.4%
8 3
 
1.1%
6 2
 
0.7%
Other values (4) 7
 
2.5%
Latin
ValueCountFrequency (%)
S 6
18.2%
K 6
18.2%
L 3
9.1%
O 3
9.1%
T 3
9.1%
D 2
 
6.1%
R 2
 
6.1%
W 2
 
6.1%
d 1
 
3.0%
m 1
 
3.0%
Other values (4) 4
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1124
77.9%
ASCII 318
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
225
70.8%
1 17
 
5.3%
0 8
 
2.5%
S 6
 
1.9%
3 6
 
1.9%
K 6
 
1.9%
2 5
 
1.6%
- 4
 
1.3%
5 4
 
1.3%
9 4
 
1.3%
Other values (18) 33
 
10.4%
Hangul
ValueCountFrequency (%)
앞 67
 
6.0%
교 44
 
3.9%
리 30
 
2.7%
거 28
 
2.5%
대 24
 
2.1%
동 23
 
2.0%
트 23
 
2.0%
스 21
 
1.9%
단 20
 
1.8%
섬 19
 
1.7%
Other values (208) 825
73.4%

그늘막지름(m)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
5.0
101 
5.4
15 
4.0
 
3
3.0
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.0
2nd row5.0
3rd row5.0
4th row5.0
5th row5.0

Common Values

ValueCountFrequency (%)
5.0 101
82.8%
5.4 15
 
12.3%
4.0 3
 
2.5%
3.0 3
 
2.5%

Length

2024-04-06T17:31:26.740454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:31:26.975682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.0 101
82.8%
5.4 15
 
12.3%
4.0 3
 
2.5%
3.0 3
 
2.5%

위도
Real number (ℝ)

Distinct107
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.907047
Minimum35.876522
Maximum35.955215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:31:27.261417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.876522
5-th percentile35.876522
Q135.886812
median35.899063
Q335.932295
95-th percentile35.946217
Maximum35.955215
Range0.0786931
Interquartile range (IQR)0.0454832

Descriptive statistics

Standard deviation0.02421047
Coefficient of variation (CV)0.00067425399
Kurtosis-1.1847618
Mean35.907047
Median Absolute Deviation (MAD)0.01591665
Skewness0.49609838
Sum4380.6598
Variance0.00058614685
MonotonicityNot monotonic
2024-04-06T17:31:28.118846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8765217 10
 
8.2%
35.8831045 3
 
2.5%
35.9275 2
 
1.6%
35.9416583 2
 
1.6%
35.8899 2
 
1.6%
35.8883 2
 
1.6%
35.9136707 1
 
0.8%
35.9317271 1
 
0.8%
35.9416629 1
 
0.8%
35.925727 1
 
0.8%
Other values (97) 97
79.5%
ValueCountFrequency (%)
35.8765217 10
8.2%
35.8784 1
 
0.8%
35.8788685 1
 
0.8%
35.8798 1
 
0.8%
35.8801908 1
 
0.8%
35.8821 1
 
0.8%
35.8822998 1
 
0.8%
35.8831045 3
 
2.5%
35.883189 1
 
0.8%
35.8842394 1
 
0.8%
ValueCountFrequency (%)
35.9552148 1
0.8%
35.9537502 1
0.8%
35.9535722 1
0.8%
35.9512 1
0.8%
35.9502263 1
0.8%
35.9502 1
0.8%
35.9463 1
0.8%
35.9446347 1
0.8%
35.944496 1
0.8%
35.9442878 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58379
Minimum128.5094
Maximum128.6229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:31:28.622144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5094
5-th percentile128.54226
Q1128.56158
median128.5931
Q3128.60429
95-th percentile128.61867
Maximum128.6229
Range0.1135023
Interquartile range (IQR)0.042710275

Descriptive statistics

Standard deviation0.028238872
Coefficient of variation (CV)0.00021961456
Kurtosis-0.35410092
Mean128.58379
Median Absolute Deviation (MAD)0.01724485
Skewness-0.71642459
Sum15687.222
Variance0.00079743388
MonotonicityNot monotonic
2024-04-06T17:31:28.935086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6042914 10
 
8.2%
128.6081752 3
 
2.5%
128.599 2
 
1.6%
128.6154735 2
 
1.6%
128.5837 2
 
1.6%
128.5845173 1
 
0.8%
128.5487254 1
 
0.8%
128.547615 1
 
0.8%
128.5655055 1
 
0.8%
128.5474962 1
 
0.8%
Other values (98) 98
80.3%
ValueCountFrequency (%)
128.5094009 1
0.8%
128.511331 1
0.8%
128.513594 1
0.8%
128.5154 1
0.8%
128.5155 1
0.8%
128.5412662 1
0.8%
128.5422372 1
0.8%
128.5427525 1
0.8%
128.5427981 1
0.8%
128.54451 1
0.8%
ValueCountFrequency (%)
128.6229032 1
0.8%
128.6222219 1
0.8%
128.6219269 1
0.8%
128.6217929 1
0.8%
128.620154 1
0.8%
128.6193539 1
0.8%
128.6186951 1
0.8%
128.6181568 1
0.8%
128.6154735 2
1.6%
128.6152667 1
0.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-27
122 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-27
2nd row2024-03-27
3rd row2024-03-27
4th row2024-03-27
5th row2024-03-27

Common Values

ValueCountFrequency (%)
2024-03-27 122
100.0%

Length

2024-04-06T17:31:29.378398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:31:29.637006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-27 122
100.0%

Interactions

2024-04-06T17:31:21.274438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:19.942117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:20.586746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:21.466937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:20.141693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:20.796076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:21.694315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:20.382897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:31:21.057180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:31:29.790452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동관리번호(지도번호)그늘막지름(m)위도경도
행정동1.0000.6490.4280.8320.898
관리번호(지도번호)0.6491.0000.7210.7030.561
그늘막지름(m)0.4280.7211.0000.0000.223
위도0.8320.7030.0001.0000.790
경도0.8980.5610.2230.7901.000
2024-04-06T17:31:30.002808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동그늘막지름(m)
행정동1.0000.218
그늘막지름(m)0.2181.000
2024-04-06T17:31:30.176099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호(지도번호)위도경도행정동그늘막지름(m)
관리번호(지도번호)1.000-0.0660.2720.2830.511
위도-0.0661.000-0.4000.4640.000
경도0.272-0.4001.0000.5930.138
행정동0.2830.4640.5931.0000.218
그늘막지름(m)0.5110.0000.1380.2181.000

Missing values

2024-04-06T17:31:21.994630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:31:22.580741image/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

행정동관리번호(지도번호)소재지주소설치장소그늘막지름(m)위도경도데이터기준일자
0고성동2대구광역시 북구 고성동3가 38-3북부도서관 남편5.035.88435128.5845172024-03-27
1고성동3대구광역시 북구 노원동1가 366-1북구청네거리 교회 앞5.035.885059128.581522024-03-27
2고성동4대구광역시 북구 고성동3가 1-1도시공사 앞 교통섬5.035.883189128.5896342024-03-27
3고성동5대구광역시 북구 고성동3가 114북구청 네거리5.035.884827128.5820852024-03-27
4고성동53대구광역시 북구 고성동1가 50-217고성지구대 맞은편5.035.878869128.5885332024-03-27
5칠성동1대구광역시 북구 칠성동2가 89-1북부도서관 동편 교통섬5.035.884778128.5851742024-03-27
6칠성동57대구광역시 북구 칠성동2가 733오페라삼정그린더베스트 사거리5.035.885381128.5910182024-03-27
7칠성동82대구광역시 북구 칠성동2가 350-9정태훈 내과 앞5.435.8798128.5962024-03-27
8칠성동102대구광역시 북구 칠성동2가 1-2대구일중학교 신협 앞5.035.885939128.5859672024-03-27
9칠성동104대구광역시 북구 칠성동1가 164-4SK해바라기 주요소 앞5.035.883105128.6081752024-03-27
행정동관리번호(지도번호)소재지주소설치장소그늘막지름(m)위도경도데이터기준일자
112국우동50대구광역시 북구 국우동 1123-2부영1단지 인근 횡단보도5.035.944263128.564072024-03-27
113국우동68대구광역시 북구 학정동 304학정청아람 아파트 맞은편5.035.913349128.5467342024-03-27
114국우동78대구광역시 북구 국우동 1076부영1단지 101동 코너 횡단보도5.435.9463128.56442024-03-27
115국우동85대구광역시 북구 국우동 236-2도남 힐스테이트 4단지 앞5.035.9512128.58372024-03-27
116국우동86대구광역시 북구 국우동 592-1그린빌 1단지 도남 힐스테이트 2단지 사이5.035.9502128.57842024-03-27
117국우동92대구광역시 북구 학정동 533근로복지공단 대구병원 앞5.035.950226128.5645842024-03-27
118국우동97대구광역시 북구 국우동 132-3국우초등학교 옆 어린이안전 입간판 앞5.035.955215128.5845732024-03-27
119국우동111대구광역시 북구 국우동 118-4도남중앙로 9길 이디야 커피 앞5.035.876522128.6042912024-03-27
120국우동112대구광역시 북구 국우동 52-2국우초등학교 앞5.035.876522128.6042912024-03-27
121국우동120대구광역시 북구 학정동 377-350사단 정문 앞5.035.876522128.6042912024-03-27