Overview

Dataset statistics

Number of variables7
Number of observations120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory62.1 B

Variable types

Numeric5
Text2

Dataset

Description대구광역시 북구 보행자 전용도로 현황에 대한 데이터로 시설명, 폭원, 연장, 지번주소, 경도, 위도 등의 항목을 제공합니다
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15096537/fileData.do

Alerts

순번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:52:37.083204
Analysis finished2023-12-12 08:52:40.302883
Duration3.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.5
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:40.425222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q130.75
median60.5
Q390.25
95-th percentile114.05
Maximum120
Range119
Interquartile range (IQR)59.5

Descriptive statistics

Standard deviation34.785054
Coefficient of variation (CV)0.57495957
Kurtosis-1.2
Mean60.5
Median Absolute Deviation (MAD)30
Skewness0
Sum7260
Variance1210
MonotonicityStrictly increasing
2023-12-12T17:52:40.647642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
62 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (110) 110
91.7%
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 (%)
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%
112 1
0.8%
111 1
0.8%

시설명
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:52:41.012955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.2833333
Min length6

Characters and Unicode

Total characters994
Distinct characters27
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

Unique120 ?
Unique (%)100.0%

Sample

1st row소로1-금호12
2nd row소로1-금호5
3rd row소로1-금호7
4th row소로1-금호9
5th row소로1-북41
ValueCountFrequency (%)
소로1-금호12 1
 
0.8%
소로1-금호5 1
 
0.8%
소로3-칠(3)22 1
 
0.8%
소로3-칠(3)21 1
 
0.8%
소로3-칠(3)20 1
 
0.8%
소로3-칠(3)2 1
 
0.8%
소로3-칠(3)19 1
 
0.8%
소로3-칠(3)18 1
 
0.8%
소로3-칠(3)17 1
 
0.8%
소로3-칠(3)16 1
 
0.8%
Other values (110) 110
91.7%
2023-12-12T17:52:41.497652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 153
15.4%
- 120
12.1%
로 120
12.1%
소 117
11.8%
2 75
7.5%
1 64
6.4%
칠 62
 
6.2%
) 53
 
5.3%
( 53
 
5.3%
7 18
 
1.8%
Other values (17) 159
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 391
39.3%
Other Letter 376
37.8%
Dash Punctuation 120
 
12.1%
Close Punctuation 53
 
5.3%
Open Punctuation 53
 
5.3%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 120
31.9%
소 117
31.1%
칠 62
16.5%
남 18
 
4.8%
도 18
 
4.8%
매 13
 
3.5%
택 6
 
1.6%
학 6
 
1.6%
북 4
 
1.1%
금 4
 
1.1%
Other values (3) 8
 
2.1%
Decimal Number
ValueCountFrequency (%)
3 153
39.1%
2 75
19.2%
1 64
16.4%
7 18
 
4.6%
4 17
 
4.3%
0 14
 
3.6%
8 14
 
3.6%
5 14
 
3.6%
6 13
 
3.3%
9 9
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 618
62.2%
Hangul 376
37.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3 153
24.8%
- 120
19.4%
2 75
12.1%
1 64
10.4%
) 53
 
8.6%
( 53
 
8.6%
7 18
 
2.9%
4 17
 
2.8%
0 14
 
2.3%
8 14
 
2.3%
Other values (4) 37
 
6.0%
Hangul
ValueCountFrequency (%)
로 120
31.9%
소 117
31.1%
칠 62
16.5%
남 18
 
4.8%
도 18
 
4.8%
매 13
 
3.5%
택 6
 
1.6%
학 6
 
1.6%
북 4
 
1.1%
금 4
 
1.1%
Other values (3) 8
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 618
62.2%
Hangul 376
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 153
24.8%
- 120
19.4%
2 75
12.1%
1 64
10.4%
) 53
 
8.6%
( 53
 
8.6%
7 18
 
2.9%
4 17
 
2.8%
0 14
 
2.3%
8 14
 
2.3%
Other values (4) 37
 
6.0%
Hangul
ValueCountFrequency (%)
로 120
31.9%
소 117
31.1%
칠 62
16.5%
남 18
 
4.8%
도 18
 
4.8%
매 13
 
3.5%
택 6
 
1.6%
학 6
 
1.6%
북 4
 
1.1%
금 4
 
1.1%
Other values (3) 8
 
2.1%

폭원
Real number (ℝ)

Distinct10
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4983333
Minimum3
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:41.654361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q16
median6
Q38
95-th percentile10
Maximum15
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1802006
Coefficient of variation (CV)0.3355015
Kurtosis2.6446965
Mean6.4983333
Median Absolute Deviation (MAD)0
Skewness1.3542936
Sum779.8
Variance4.7532745
MonotonicityNot monotonic
2023-12-12T17:52:41.777259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6.0 61
50.8%
4.0 23
 
19.2%
8.0 13
 
10.8%
10.0 12
 
10.0%
9.5 4
 
3.3%
5.0 2
 
1.7%
15.0 2
 
1.7%
3.0 1
 
0.8%
4.8 1
 
0.8%
12.0 1
 
0.8%
ValueCountFrequency (%)
3.0 1
 
0.8%
4.0 23
 
19.2%
4.8 1
 
0.8%
5.0 2
 
1.7%
6.0 61
50.8%
8.0 13
 
10.8%
9.5 4
 
3.3%
10.0 12
 
10.0%
12.0 1
 
0.8%
15.0 2
 
1.7%
ValueCountFrequency (%)
15.0 2
 
1.7%
12.0 1
 
0.8%
10.0 12
 
10.0%
9.5 4
 
3.3%
8.0 13
 
10.8%
6.0 61
50.8%
5.0 2
 
1.7%
4.8 1
 
0.8%
4.0 23
 
19.2%
3.0 1
 
0.8%

연장
Real number (ℝ)

Distinct54
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.1
Minimum10
Maximum680
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:41.924266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile13
Q121.75
median30
Q341.25
95-th percentile215.45
Maximum680
Range670
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation97.909614
Coefficient of variation (CV)1.7147043
Kurtosis19.86258
Mean57.1
Median Absolute Deviation (MAD)9
Skewness4.2773881
Sum6852
Variance9586.2924
MonotonicityNot monotonic
2023-12-12T17:52:42.066803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 18
 
15.0%
21 6
 
5.0%
26 6
 
5.0%
28 5
 
4.2%
33 5
 
4.2%
13 4
 
3.3%
31 4
 
3.3%
23 4
 
3.3%
16 3
 
2.5%
14 3
 
2.5%
Other values (44) 62
51.7%
ValueCountFrequency (%)
10 3
2.5%
12 1
 
0.8%
13 4
3.3%
14 3
2.5%
15 2
 
1.7%
16 3
2.5%
17 3
2.5%
18 3
2.5%
20 2
 
1.7%
21 6
5.0%
ValueCountFrequency (%)
680 1
0.8%
507 1
0.8%
432 1
0.8%
397 1
0.8%
386 1
0.8%
243 1
0.8%
214 1
0.8%
181 1
0.8%
130 1
0.8%
109 1
0.8%

지번주소
Text

Distinct116
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:52:42.422296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.608333
Min length16

Characters and Unicode

Total characters2113
Distinct characters47
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

Unique112 ?
Unique (%)93.3%

Sample

1st row대구광역시 북구 검단동 287-5
2nd row대구광역시 북구 검단동 464-4
3rd row대구광역시 북구 검단동 445-4
4th row대구광역시 북구 검단동 437-8
5th row대구광역시 북구 칠성동2가 32-23
ValueCountFrequency (%)
대구광역시 120
25.0%
북구 119
24.8%
구암동 28
 
5.8%
국우동 23
 
4.8%
동천동 22
 
4.6%
태전동 12
 
2.5%
매천동 9
 
1.9%
학정동 5
 
1.0%
도남동 4
 
0.8%
검단동 4
 
0.8%
Other values (126) 134
27.9%
2023-12-12T17:52:42.936613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
360
17.0%
구 268
12.7%
동 143
 
6.8%
대 120
 
5.7%
광 120
 
5.7%
역 120
 
5.7%
시 120
 
5.7%
북 119
 
5.6%
1 100
 
4.7%
- 78
 
3.7%
Other values (37) 565
26.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1202
56.9%
Decimal Number 473
 
22.4%
Space Separator 360
 
17.0%
Dash Punctuation 78
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 268
22.3%
동 143
11.9%
대 120
10.0%
광 120
10.0%
역 120
10.0%
시 120
10.0%
북 119
9.9%
천 31
 
2.6%
암 29
 
2.4%
국 23
 
1.9%
Other values (25) 109
9.1%
Decimal Number
ValueCountFrequency (%)
1 100
21.1%
9 53
11.2%
8 46
9.7%
7 46
9.7%
2 44
9.3%
6 43
9.1%
0 38
 
8.0%
4 37
 
7.8%
3 35
 
7.4%
5 31
 
6.6%
Space Separator
ValueCountFrequency (%)
360
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1202
56.9%
Common 911
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 268
22.3%
동 143
11.9%
대 120
10.0%
광 120
10.0%
역 120
10.0%
시 120
10.0%
북 119
9.9%
천 31
 
2.6%
암 29
 
2.4%
국 23
 
1.9%
Other values (25) 109
9.1%
Common
ValueCountFrequency (%)
360
39.5%
1 100
 
11.0%
- 78
 
8.6%
9 53
 
5.8%
8 46
 
5.0%
7 46
 
5.0%
2 44
 
4.8%
6 43
 
4.7%
0 38
 
4.2%
4 37
 
4.1%
Other values (2) 66
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1202
56.9%
ASCII 911
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
360
39.5%
1 100
 
11.0%
- 78
 
8.6%
9 53
 
5.8%
8 46
 
5.0%
7 46
 
5.0%
2 44
 
4.8%
6 43
 
4.7%
0 38
 
4.2%
4 37
 
4.1%
Other values (2) 66
 
7.2%
Hangul
ValueCountFrequency (%)
구 268
22.3%
동 143
11.9%
대 120
10.0%
광 120
10.0%
역 120
10.0%
시 120
10.0%
북 119
9.9%
천 31
 
2.6%
암 29
 
2.4%
국 23
 
1.9%
Other values (25) 109
9.1%

경도
Real number (ℝ)

Distinct116
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.932813
Minimum35.877254
Maximum35.960188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:43.440788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.877254
5-th percentile35.90001
Q135.924721
median35.936344
Q335.944848
95-th percentile35.955661
Maximum35.960188
Range0.0829334
Interquartile range (IQR)0.02012675

Descriptive statistics

Standard deviation0.017785989
Coefficient of variation (CV)0.00049497904
Kurtosis0.28356771
Mean35.932813
Median Absolute Deviation (MAD)0.0110189
Skewness-0.78743678
Sum4311.9375
Variance0.00031634141
MonotonicityNot monotonic
2023-12-12T17:52:43.609918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.9415633 2
 
1.7%
35.950181 2
 
1.7%
35.9515413 2
 
1.7%
35.9524964 2
 
1.7%
35.9394993 1
 
0.8%
35.9352964 1
 
0.8%
35.9359276 1
 
0.8%
35.9467902 1
 
0.8%
35.936107 1
 
0.8%
35.9363589 1
 
0.8%
Other values (106) 106
88.3%
ValueCountFrequency (%)
35.8772541 1
0.8%
35.8841666 1
0.8%
35.8861751 1
0.8%
35.8952676 1
0.8%
35.895305 1
0.8%
35.8976339 1
0.8%
35.9001346 1
0.8%
35.9039352 1
0.8%
35.9048532 1
0.8%
35.9069771 1
0.8%
ValueCountFrequency (%)
35.9601875 1
0.8%
35.9601617 1
0.8%
35.9599756 1
0.8%
35.9598189 1
0.8%
35.9572942 1
0.8%
35.9558116 1
0.8%
35.9556535 1
0.8%
35.9554331 1
0.8%
35.9547004 1
0.8%
35.9540594 1
0.8%

위도
Real number (ℝ)

Distinct116
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.56564
Minimum128.5418
Maximum128.61965
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:52:43.752414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5418
5-th percentile128.54377
Q1128.55375
median128.56105
Q3128.57431
95-th percentile128.5955
Maximum128.61965
Range0.0778514
Interquartile range (IQR)0.02056165

Descriptive statistics

Standard deviation0.017811043
Coefficient of variation (CV)0.00013853657
Kurtosis1.065125
Mean128.56564
Median Absolute Deviation (MAD)0.009689
Skewness1.1010891
Sum15427.877
Variance0.00031723324
MonotonicityNot monotonic
2023-12-12T17:52:43.941625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5572024 2
 
1.7%
128.5649655 2
 
1.7%
128.5652499 2
 
1.7%
128.5832345 2
 
1.7%
128.558281 1
 
0.8%
128.5587459 1
 
0.8%
128.5572873 1
 
0.8%
128.5708046 1
 
0.8%
128.5593237 1
 
0.8%
128.5587 1
 
0.8%
Other values (106) 106
88.3%
ValueCountFrequency (%)
128.5418019 1
0.8%
128.5419048 1
0.8%
128.542106 1
0.8%
128.5423909 1
0.8%
128.542431 1
0.8%
128.542899 1
0.8%
128.5438113 1
0.8%
128.5440587 1
0.8%
128.5441737 1
0.8%
128.5445152 1
0.8%
ValueCountFrequency (%)
128.6196533 1
0.8%
128.6188793 1
0.8%
128.6169334 1
0.8%
128.6138412 1
0.8%
128.6127848 1
0.8%
128.6117924 1
0.8%
128.5946474 1
0.8%
128.5915591 1
0.8%
128.5886106 1
0.8%
128.5882791 1
0.8%

Interactions

2023-12-12T17:52:39.427176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.351332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.857865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.398626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.900853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.544557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.460316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.972390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.502260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.992472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.661385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.553833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.083663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.604133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.100819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.817043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.643580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.182999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.707659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.196665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.929750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:37.733286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.291115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:38.792033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:52:39.293947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:52:44.049306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폭원연장경도위도
순번1.0000.7740.2130.8030.649
폭원0.7741.0000.5650.4980.563
연장0.2130.5651.0000.5760.107
경도0.8030.4980.5761.0000.841
위도0.6490.5630.1070.8411.000
2023-12-12T17:52:44.175091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번폭원연장경도위도
순번1.000-0.381-0.3820.053-0.240
폭원-0.3811.0000.3200.1780.340
연장-0.3820.3201.000-0.0530.178
경도0.0530.178-0.0531.0000.426
위도-0.2400.3400.1780.4261.000

Missing values

2023-12-12T17:52:40.082718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:52:40.240938image/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

순번시설명폭원연장지번주소경도위도
01소로1-금호1210.073대구광역시 북구 검단동 287-535.922618128.618879
12소로1-금호510.033대구광역시 북구 검단동 464-435.918092128.611792
23소로1-금호710.034대구광역시 북구 검단동 445-435.918729128.612785
34소로1-금호910.035대구광역시 북구 검단동 437-835.91941128.613841
45소로1-북4110.059대구광역시 북구 칠성동2가 32-2335.884167128.591559
56소로1-칠(3)1310.0106대구광역시 북구 동천동 951-435.943591128.557866
67소로1-칠(3)1410.0386대구광역시 북구 동천동 896-635.942918128.563199
78소로1-칠(3)1510.067대구광역시 북구 동천동 894-235.94419128.559761
89소로1-칠(3)1610.067대구광역시 북구 동천동 897-435.943521128.56253
910소로1-칠(3)1710.057대구광역시 북구 구암동 767-335.942756128.56446
순번시설명폭원연장지번주소경도위도
110111소로3-칠택1344.018대구광역시 북구 태전동 1053-1035.926591128.548925
111112소로3-학16.030대구광역시 북구 학정동 373-135.955812128.565976
112113소로3-학26.020대구광역시 북구 학정동 286-235.951541128.56525
113114소로3-학36.020대구광역시 북구 학정동 286-235.951541128.56525
114115소로3-학46.030대구광역시 북구 학정동 27235.950181128.564965
115116소로3-학56.030대구광역시 북구 학정동 27235.950181128.564965
116117소로3-학66.021대구광역시 북구 구암동 694-135.928221128.557819
117118중로2-20015.0397대구광역시 북구 동천동 914-235.939461128.560716
118119중로2-20115.0432대구광역시 북구 구암동 785-435.938834128.566902
119120중로3-8512.010대구광역시 북구 읍내동 707-135.94699128.545629