Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory72.5 B

Variable types

Numeric3
Text3
Categorical1
DateTime1

Dataset

Description대구광역시 북구의 혈압측정기 설치 현황 데이터로 설치기관명, 도로명주소(위치), 설치상세위치, 전화번호, 위도, 경도 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15113965/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:46:09.465762
Analysis finished2023-12-12 23:46:10.677465
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:46:10.734719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-13T08:46:10.843028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

설치기관명
Text

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T08:46:11.001986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length9.5833333
Min length5

Characters and Unicode

Total characters230
Distinct characters48
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

Unique21 ?
Unique (%)87.5%

Sample

1st row북구보건소
2nd row강북보건지소
3rd row관문동행정복지센터
4th row동천동 행정복지센터
5th row구암건강생활지원센터
ValueCountFrequency (%)
행정복지센터 9
26.5%
대구보건대학교 3
 
8.8%
무태조야동행정복지센터 2
 
5.9%
태전2동 1
 
2.9%
강북보건지소 1
 
2.9%
침산1동행정복지센터 1
 
2.9%
노원동 1
 
2.9%
검단동행정복지센터 1
 
2.9%
칠성동 1
 
2.9%
국우동행정복지센터 1
 
2.9%
Other values (13) 13
38.2%
2023-12-13T08:46:11.324667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 20
 
8.7%
터 19
 
8.3%
센 19
 
8.3%
복 19
 
8.3%
동 19
 
8.3%
행 18
 
7.8%
정 18
 
7.8%
10
 
4.3%
대 6
 
2.6%
건 6
 
2.6%
Other values (38) 76
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
92.2%
Space Separator 10
 
4.3%
Decimal Number 8
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 20
 
9.4%
터 19
 
9.0%
센 19
 
9.0%
복 19
 
9.0%
동 19
 
9.0%
행 18
 
8.5%
정 18
 
8.5%
대 6
 
2.8%
건 6
 
2.8%
구 5
 
2.4%
Other values (33) 63
29.7%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 2
25.0%
4 1
 
12.5%
3 1
 
12.5%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
92.2%
Common 18
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 20
 
9.4%
터 19
 
9.0%
센 19
 
9.0%
복 19
 
9.0%
동 19
 
9.0%
행 18
 
8.5%
정 18
 
8.5%
대 6
 
2.8%
건 6
 
2.8%
구 5
 
2.4%
Other values (33) 63
29.7%
Common
ValueCountFrequency (%)
10
55.6%
1 4
 
22.2%
2 2
 
11.1%
4 1
 
5.6%
3 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
92.2%
ASCII 18
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 20
 
9.4%
터 19
 
9.0%
센 19
 
9.0%
복 19
 
9.0%
동 19
 
9.0%
행 18
 
8.5%
정 18
 
8.5%
대 6
 
2.8%
건 6
 
2.8%
구 5
 
2.4%
Other values (33) 63
29.7%
ASCII
ValueCountFrequency (%)
10
55.6%
1 4
 
22.2%
2 2
 
11.1%
4 1
 
5.6%
3 1
 
5.6%

도로명주소
Text

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T08:46:11.531865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length22.291667
Min length20

Characters and Unicode

Total characters535
Distinct characters62
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

Unique19 ?
Unique (%)79.2%

Sample

1st row대구광역시 북구 성북로 49(침산동)
2nd row대구광역시 북구 대천로 81(동천동)
3rd row대구광역시 북구 매천로18길 34(매천동)
4th row대구광역시 북구 대천로 81(동천동)
5th row대구광역시 북구 구암서로 30(구암동)
ValueCountFrequency (%)
대구광역시 24
25.0%
북구 24
25.0%
영송로 3
 
3.1%
15(태전동 3
 
3.1%
대천로 2
 
2.1%
81(동천동 2
 
2.1%
노원로10길 1
 
1.0%
561(읍내동 1
 
1.0%
구리로 1
 
1.0%
188(국우동 1
 
1.0%
Other values (34) 34
35.4%
2023-12-13T08:46:12.156659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
13.5%
구 52
 
9.7%
대 30
 
5.6%
동 28
 
5.2%
북 27
 
5.0%
광 24
 
4.5%
역 24
 
4.5%
시 24
 
4.5%
로 24
 
4.5%
) 24
 
4.5%
Other values (52) 206
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 338
63.2%
Decimal Number 76
 
14.2%
Space Separator 72
 
13.5%
Close Punctuation 24
 
4.5%
Open Punctuation 24
 
4.5%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 52
15.4%
대 30
 
8.9%
동 28
 
8.3%
북 27
 
8.0%
광 24
 
7.1%
역 24
 
7.1%
시 24
 
7.1%
로 24
 
7.1%
길 12
 
3.6%
산 7
 
2.1%
Other values (38) 86
25.4%
Decimal Number
ValueCountFrequency (%)
1 19
25.0%
3 11
14.5%
2 9
11.8%
5 7
 
9.2%
4 7
 
9.2%
6 6
 
7.9%
8 6
 
7.9%
0 5
 
6.6%
7 3
 
3.9%
9 3
 
3.9%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 338
63.2%
Common 197
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 52
15.4%
대 30
 
8.9%
동 28
 
8.3%
북 27
 
8.0%
광 24
 
7.1%
역 24
 
7.1%
시 24
 
7.1%
로 24
 
7.1%
길 12
 
3.6%
산 7
 
2.1%
Other values (38) 86
25.4%
Common
ValueCountFrequency (%)
72
36.5%
) 24
 
12.2%
( 24
 
12.2%
1 19
 
9.6%
3 11
 
5.6%
2 9
 
4.6%
5 7
 
3.6%
4 7
 
3.6%
6 6
 
3.0%
8 6
 
3.0%
Other values (4) 12
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 338
63.2%
ASCII 197
36.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
36.5%
) 24
 
12.2%
( 24
 
12.2%
1 19
 
9.6%
3 11
 
5.6%
2 9
 
4.6%
5 7
 
3.6%
4 7
 
3.6%
6 6
 
3.0%
8 6
 
3.0%
Other values (4) 12
 
6.1%
Hangul
ValueCountFrequency (%)
구 52
15.4%
대 30
 
8.9%
동 28
 
8.3%
북 27
 
8.0%
광 24
 
7.1%
역 24
 
7.1%
시 24
 
7.1%
로 24
 
7.1%
길 12
 
3.6%
산 7
 
2.1%
Other values (38) 86
25.4%

설치상세위치
Categorical

Distinct7
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
1층 민원실
18 
2층 민원실
 
1
1층 민원실
 
1
본관 1층 로비
 
1
연마관 1층 로비
 
1
Other values (2)
2 

Length

Max length9
Median length6
Mean length6.4583333
Min length6

Unique

Unique6 ?
Unique (%)25.0%

Sample

1st row1층 민원실
2nd row2층 민원실
3rd row1층 민원실
4th row1층 민원실
5th row1층 민원실

Common Values

ValueCountFrequency (%)
1층 민원실 18
75.0%
2층 민원실 1
 
4.2%
1층 민원실 1
 
4.2%
본관 1층 로비 1
 
4.2%
연마관 1층 로비 1
 
4.2%
인당관 1층 로비 1
 
4.2%
1층 민원실 1
 
4.2%

Length

2023-12-13T08:46:12.312499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:46:12.405506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1층 23
45.1%
민원실 21
41.2%
로비 3
 
5.9%
2층 1
 
2.0%
본관 1
 
2.0%
연마관 1
 
2.0%
인당관 1
 
2.0%

전화번호
Text

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T08:46:12.582927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)87.5%

Sample

1st row053-665-3211
2nd row053-665-4200
3rd row053-665-3756
4th row053-665-3324
5th row053-665-4281
ValueCountFrequency (%)
053-320-4580 3
 
12.5%
053-665-3211 1
 
4.2%
053-665-4200 1
 
4.2%
053-665-3303 1
 
4.2%
053-665-3505 1
 
4.2%
053-665-3710 1
 
4.2%
053-665-3428 1
 
4.2%
053-665-3882 1
 
4.2%
053-665-3845 1
 
4.2%
053-665-3157 1
 
4.2%
Other values (12) 12
50.0%
2023-12-13T08:46:12.880984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 58
20.1%
3 52
18.1%
- 48
16.7%
6 48
16.7%
0 38
13.2%
2 11
 
3.8%
8 11
 
3.8%
4 10
 
3.5%
1 6
 
2.1%
7 6
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 58
24.2%
3 52
21.7%
6 48
20.0%
0 38
15.8%
2 11
 
4.6%
8 11
 
4.6%
4 10
 
4.2%
1 6
 
2.5%
7 6
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 58
20.1%
3 52
18.1%
- 48
16.7%
6 48
16.7%
0 38
13.2%
2 11
 
3.8%
8 11
 
3.8%
4 10
 
3.5%
1 6
 
2.1%
7 6
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 58
20.1%
3 52
18.1%
- 48
16.7%
6 48
16.7%
0 38
13.2%
2 11
 
3.8%
8 11
 
3.8%
4 10
 
3.5%
1 6
 
2.1%
7 6
 
2.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.912284
Minimum35.879224
Maximum35.948025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:46:13.019251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.879224
5-th percentile35.883092
Q135.89331
median35.911989
Q335.926846
95-th percentile35.944832
Maximum35.948025
Range0.0688011
Interquartile range (IQR)0.033535995

Descriptive statistics

Standard deviation0.021046256
Coefficient of variation (CV)0.00058604614
Kurtosis-1.2774668
Mean35.912284
Median Absolute Deviation (MAD)0.0182768
Skewness0.13452467
Sum861.89483
Variance0.00044294487
MonotonicityNot monotonic
2023-12-13T08:46:13.124601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.92684647 3
 
12.5%
35.93732675 2
 
8.3%
35.89187948 1
 
4.2%
35.89376687 1
 
4.2%
35.89032098 1
 
4.2%
35.89014747 1
 
4.2%
35.91346979 1
 
4.2%
35.87922383 1
 
4.2%
35.94802493 1
 
4.2%
35.94592467 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
35.87922383 1
4.2%
35.88184711 1
4.2%
35.89014747 1
4.2%
35.89032098 1
4.2%
35.89187948 1
4.2%
35.89227144 1
4.2%
35.89365682 1
4.2%
35.89376687 1
4.2%
35.90039343 1
4.2%
35.90086498 1
4.2%
ValueCountFrequency (%)
35.94802493 1
 
4.2%
35.94592467 1
 
4.2%
35.93864195 1
 
4.2%
35.93732675 2
8.3%
35.92684647 3
12.5%
35.92412735 1
 
4.2%
35.92148905 1
 
4.2%
35.92134826 1
 
4.2%
35.91346979 1
 
4.2%
35.9105075 1
 
4.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.5769
Minimum128.54325
Maximum128.62723
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:46:13.232765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54325
5-th percentile128.5435
Q1128.55009
median128.5763
Q3128.59779
95-th percentile128.61732
Maximum128.62723
Range0.0839709
Interquartile range (IQR)0.047705375

Descriptive statistics

Standard deviation0.026805834
Coefficient of variation (CV)0.00020848095
Kurtosis-1.2082456
Mean128.5769
Median Absolute Deviation (MAD)0.024748
Skewness0.20785995
Sum3085.8457
Variance0.00071855275
MonotonicityNot monotonic
2023-12-13T08:46:13.342359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
128.5440308 3
 
12.5%
128.5581782 2
 
8.3%
128.5888952 1
 
4.2%
128.6185844 1
 
4.2%
128.5813516 1
 
4.2%
128.5762219 1
 
4.2%
128.6272251 1
 
4.2%
128.6000202 1
 
4.2%
128.5754014 1
 
4.2%
128.5505242 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
128.5432542 1
 
4.2%
128.5434026 1
 
4.2%
128.5440308 3
12.5%
128.5487698 1
 
4.2%
128.5505242 1
 
4.2%
128.5581782 2
8.3%
128.5660123 1
 
4.2%
128.5754014 1
 
4.2%
128.5762219 1
 
4.2%
128.576381 1
 
4.2%
ValueCountFrequency (%)
128.6272251 1
4.2%
128.6185844 1
4.2%
128.610165 1
4.2%
128.6092522 1
4.2%
128.6043059 1
4.2%
128.6000202 1
4.2%
128.5970479 1
4.2%
128.5968902 1
4.2%
128.5888952 1
4.2%
128.5835046 1
4.2%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum2023-03-17 00:00:00
Maximum2023-03-17 00:00:00
2023-12-13T08:46:13.429529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:13.504216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:46:10.260861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:09.734459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:10.008784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:10.330758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:09.821006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:10.085982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:10.433128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:09.918737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:46:10.171519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:46:13.576161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치기관명도로명주소설치상세위치전화번호위도경도
연번1.0000.9350.8880.0000.9350.7230.693
설치기관명0.9351.0001.0000.0001.0001.0001.000
도로명주소0.8881.0001.0000.0001.0001.0001.000
설치상세위치0.0000.0000.0001.0000.0000.0000.000
전화번호0.9351.0001.0000.0001.0001.0001.000
위도0.7231.0001.0000.0001.0001.0000.725
경도0.6931.0001.0000.0001.0000.7251.000
2023-12-13T08:46:13.669299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도설치상세위치
연번1.000-0.016-0.0040.000
위도-0.0161.000-0.5450.000
경도-0.004-0.5451.0000.000
설치상세위치0.0000.0000.0001.000

Missing values

2023-12-13T08:46:10.531073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:46:10.636223image/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

연번설치기관명도로명주소설치상세위치전화번호위도경도데이터 기준일자
01북구보건소대구광역시 북구 성북로 49(침산동)1층 민원실053-665-321135.891879128.5888952023-03-17
12강북보건지소대구광역시 북구 대천로 81(동천동)2층 민원실053-665-420035.937327128.5581782023-03-17
23관문동행정복지센터대구광역시 북구 매천로18길 34(매천동)1층 민원실053-665-375635.900865128.5432542023-03-17
34동천동 행정복지센터대구광역시 북구 대천로 81(동천동)1층 민원실053-665-332435.937327128.5581782023-03-17
45구암건강생활지원센터대구광역시 북구 구암서로 30(구암동)1층 민원실053-665-428135.938642128.5660122023-03-17
56산격1동행정복지센터대구광역시 북구 연암로36길 6(산격동)1층 민원실053-665-330835.900393128.596892023-03-17
67산격2동행정복지센터대구광역시 북구 동북로31길 30(산격동)1층 민원실053-665-356535.901728128.6092522023-03-17
78산격3동 행정복지센터대구광역시 북구 대학로 95(산격동)1층 민원실053-665-358635.893657128.6101652023-03-17
89산격4동 행정복지센터대구광역시 북구 대구체육관로 48(산격동)1층 민원실053-665-360435.892271128.6043062023-03-17
910고성동 행정복지센터대구광역시 북구 고성로31길 21(고성동3가)1층 민원실053-665-330135.881847128.5835052023-03-17
연번설치기관명도로명주소설치상세위치전화번호위도경도데이터 기준일자
1415읍내동행정복지센터대구광역시 북구 칠곡중앙대로 561(읍내동)1층 민원실053-665-384535.945925128.5505242023-03-17
1516국우동행정복지센터대구광역시 북구 구리로 188(국우동)1층 민원실053-665-388235.948025128.5754012023-03-17
1617칠성동 행정복지센터대구광역시 북구 칠성로19길 4(칠성동2가)1층 민원실053-665-342835.879224128.600022023-03-17
1718검단동행정복지센터대구광역시 북구 검단로41길 12(검단동)1층 민원실053-665-371035.91347128.6272252023-03-17
1819노원동 행정복지센터대구광역시 북구 노원로10길 166(노원동2가)1층 민원실053-665-350535.890147128.5762222023-03-17
1920침산1동행정복지센터대구광역시 북구 침산남로13길 16(침산동)1층 민원실053-665-330335.890321128.5813522023-03-17
2021대구보건대학교대구광역시 북구 영송로 15(태전동)본관 1층 로비053-320-458035.926846128.5440312023-03-17
2122대구보건대학교대구광역시 북구 영송로 15(태전동)연마관 1층 로비053-320-458035.926846128.5440312023-03-17
2223대구보건대학교대구광역시 북구 영송로 15(태전동)인당관 1층 로비053-320-458035.926846128.5440312023-03-17
2324복현1동 행정복지센터대구광역시 북구 동북로52길 7(복현동)1층 민원실053-665-363435.893767128.6185842023-03-17