Overview

Dataset statistics

Number of variables8
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory69.3 B

Variable types

Categorical2
Text4
Numeric2

Dataset

Description대구광역시 서구_명절 무료개방 주차장 현황_20240131
Author대구광역시 서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3081288&dataSetDetailId=30812881e3a89faf4a35_202001210913&provdMethod=FILE

Alerts

시도 has constant value ""Constant
주차장유형(노상_노외_부설) is highly imbalanced (71.4%)Imbalance
주차장명 has unique valuesUnique
관리기관 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:27:35.605206
Analysis finished2024-03-13 13:27:40.400326
Duration4.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
대구광역시
40 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 40
100.0%

Length

2024-03-13T22:27:40.524568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:27:40.681326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 40
100.0%

주차장명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-13T22:27:41.021791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16.5
Mean length7.125
Min length3

Characters and Unicode

Total characters285
Distinct characters82
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

Unique40 ?
Unique (%)100.0%

Sample

1st row달성초등학교
2nd row중리초등학교
3rd row서구청
4th row이현초등학교
5th row경상여자중학교
ValueCountFrequency (%)
노상공영주차장 2
 
4.5%
비산2,3동복개도로 1
 
2.3%
인지초등학교 1
 
2.3%
서부공업고등학교 1
 
2.3%
서구 1
 
2.3%
구민운동장 1
 
2.3%
서남중학교 1
 
2.3%
서구문화회관 1
 
2.3%
서구청소년수련관 1
 
2.3%
서구국민체육센터 1
 
2.3%
Other values (33) 33
75.0%
2024-03-13T22:27:41.530685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 30
 
10.5%
교 30
 
10.5%
등 22
 
7.7%
서 20
 
7.0%
초 17
 
6.0%
구 12
 
4.2%
중 9
 
3.2%
대 8
 
2.8%
리 5
 
1.8%
부 5
 
1.8%
Other values (72) 127
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
97.2%
Space Separator 4
 
1.4%
Decimal Number 3
 
1.1%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 30
 
10.8%
교 30
 
10.8%
등 22
 
7.9%
서 20
 
7.2%
초 17
 
6.1%
구 12
 
4.3%
중 9
 
3.2%
대 8
 
2.9%
리 5
 
1.8%
부 5
 
1.8%
Other values (67) 119
43.0%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
2 1
33.3%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 277
97.2%
Common 8
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 30
 
10.8%
교 30
 
10.8%
등 22
 
7.9%
서 20
 
7.2%
초 17
 
6.1%
구 12
 
4.3%
중 9
 
3.2%
대 8
 
2.9%
리 5
 
1.8%
부 5
 
1.8%
Other values (67) 119
43.0%
Common
ValueCountFrequency (%)
4
50.0%
3 1
 
12.5%
, 1
 
12.5%
2 1
 
12.5%
6 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 277
97.2%
ASCII 8
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 30
 
10.8%
교 30
 
10.8%
등 22
 
7.9%
서 20
 
7.2%
초 17
 
6.1%
구 12
 
4.3%
중 9
 
3.2%
대 8
 
2.9%
리 5
 
1.8%
부 5
 
1.8%
Other values (67) 119
43.0%
ASCII
ValueCountFrequency (%)
4
50.0%
3 1
 
12.5%
, 1
 
12.5%
2 1
 
12.5%
6 1
 
12.5%

주차장유형(노상_노외_부설)
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
부설
38 
노상
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부설 38
95.0%
노상 2
 
5.0%

Length

2024-03-13T22:27:41.757476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:27:41.906145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부설 38
95.0%
노상 2
 
5.0%

주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-13T22:27:42.158580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length18.775
Min length15

Characters and Unicode

Total characters751
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row대구광역시 서구 고성로 127
2nd row대구광역시 서구 국채보상로 135
3rd row대구광역시 서구 국채보상로 257
4th row대구광역시 서구 국채보상로 37길35
5th row대구광역시 서구 국채보상로 384
ValueCountFrequency (%)
대구광역시 40
23.8%
서구 40
23.8%
국채보상로 9
 
5.4%
당산로 4
 
2.4%
달구벌대로 3
 
1.8%
달서로 2
 
1.2%
문화로 2
 
1.2%
22 2
 
1.2%
35 2
 
1.2%
32 2
 
1.2%
Other values (57) 62
36.9%
2024-03-13T22:27:42.653473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
128
17.0%
구 89
11.9%
서 52
 
6.9%
대 51
 
6.8%
로 40
 
5.3%
광 40
 
5.3%
역 40
 
5.3%
시 40
 
5.3%
3 26
 
3.5%
5 23
 
3.1%
Other values (37) 222
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 480
63.9%
Decimal Number 138
 
18.4%
Space Separator 128
 
17.0%
Dash Punctuation 2
 
0.3%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 89
18.5%
서 52
10.8%
대 51
10.6%
로 40
8.3%
광 40
8.3%
역 40
8.3%
시 40
8.3%
길 23
 
4.8%
보 14
 
2.9%
채 14
 
2.9%
Other values (22) 77
16.0%
Decimal Number
ValueCountFrequency (%)
3 26
18.8%
5 23
16.7%
2 23
16.7%
4 15
10.9%
1 14
10.1%
7 12
8.7%
6 10
 
7.2%
8 6
 
4.3%
0 6
 
4.3%
9 3
 
2.2%
Space Separator
ValueCountFrequency (%)
128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 480
63.9%
Common 271
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 89
18.5%
서 52
10.8%
대 51
10.6%
로 40
8.3%
광 40
8.3%
역 40
8.3%
시 40
8.3%
길 23
 
4.8%
보 14
 
2.9%
채 14
 
2.9%
Other values (22) 77
16.0%
Common
ValueCountFrequency (%)
128
47.2%
3 26
 
9.6%
5 23
 
8.5%
2 23
 
8.5%
4 15
 
5.5%
1 14
 
5.2%
7 12
 
4.4%
6 10
 
3.7%
8 6
 
2.2%
0 6
 
2.2%
Other values (5) 8
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 480
63.9%
ASCII 271
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
128
47.2%
3 26
 
9.6%
5 23
 
8.5%
2 23
 
8.5%
4 15
 
5.5%
1 14
 
5.2%
7 12
 
4.4%
6 10
 
3.7%
8 6
 
2.2%
0 6
 
2.2%
Other values (5) 8
 
3.0%
Hangul
ValueCountFrequency (%)
구 89
18.5%
서 52
10.8%
대 51
10.6%
로 40
8.3%
광 40
8.3%
역 40
8.3%
시 40
8.3%
길 23
 
4.8%
보 14
 
2.9%
채 14
 
2.9%
Other values (22) 77
16.0%

위도
Real number (ℝ)

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.872198
Minimum35.857488
Maximum35.889713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-03-13T22:27:42.865125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.857488
5-th percentile35.85893
Q135.867163
median35.872989
Q335.876124
95-th percentile35.883016
Maximum35.889713
Range0.03222478
Interquartile range (IQR)0.00896078

Descriptive statistics

Standard deviation0.0077650811
Coefficient of variation (CV)0.00021646516
Kurtosis-0.31432992
Mean35.872198
Median Absolute Deviation (MAD)0.00424866
Skewness-0.072704325
Sum1434.8879
Variance6.0296485 × 10-5
MonotonicityNot monotonic
2024-03-13T22:27:43.061981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
35.87612373 4
 
10.0%
35.87068147 2
 
5.0%
35.87871467 1
 
2.5%
35.85748835 1
 
2.5%
35.87274213 1
 
2.5%
35.87610575 1
 
2.5%
35.8736259 1
 
2.5%
35.88617922 1
 
2.5%
35.85972649 1
 
2.5%
35.85885744 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
35.85748835 1
2.5%
35.85885744 1
2.5%
35.85893406 1
2.5%
35.85972649 1
2.5%
35.86088403 1
2.5%
35.86161678 1
2.5%
35.86356938 1
2.5%
35.86373839 1
2.5%
35.86471134 1
2.5%
35.86684294 1
2.5%
ValueCountFrequency (%)
35.88971313 1
 
2.5%
35.88617922 1
 
2.5%
35.88284967 1
 
2.5%
35.88278375 1
 
2.5%
35.88139499 1
 
2.5%
35.8813608 1
 
2.5%
35.87900942 1
 
2.5%
35.87871467 1
 
2.5%
35.8782117 1
 
2.5%
35.87612373 4
10.0%

경도
Real number (ℝ)

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.55978
Minimum128.54543
Maximum128.57936
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-03-13T22:27:43.262089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54543
5-th percentile128.54558
Q1128.55259
median128.55892
Q3128.56572
95-th percentile128.5764
Maximum128.57936
Range0.0339258
Interquartile range (IQR)0.013128975

Descriptive statistics

Standard deviation0.0093574432
Coefficient of variation (CV)7.2786706 × 10-5
Kurtosis-0.6557997
Mean128.55978
Median Absolute Deviation (MAD)0.0065765
Skewness0.38933421
Sum5142.3914
Variance8.7561744 × 10-5
MonotonicityNot monotonic
2024-03-13T22:27:43.434086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
128.5589214 4
 
10.0%
128.5738105 2
 
5.0%
128.552195 1
 
2.5%
128.548294 1
 
2.5%
128.5455866 1
 
2.5%
128.5589102 1
 
2.5%
128.5454819 1
 
2.5%
128.5672881 1
 
2.5%
128.5535577 1
 
2.5%
128.5563197 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
128.5454329 1
2.5%
128.5454819 1
2.5%
128.5455866 1
2.5%
128.5478834 1
2.5%
128.548294 1
2.5%
128.548934 1
2.5%
128.5504091 1
2.5%
128.5505179 1
2.5%
128.5514886 1
2.5%
128.552195 1
2.5%
ValueCountFrequency (%)
128.5793587 1
2.5%
128.577262 1
2.5%
128.5763577 1
2.5%
128.5738105 2
5.0%
128.5737118 1
2.5%
128.5705489 1
2.5%
128.5686593 1
2.5%
128.5672881 1
2.5%
128.5668398 1
2.5%
128.565348 1
2.5%

관리기관
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-13T22:27:43.741226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11.5
Mean length6.725
Min length3

Characters and Unicode

Total characters269
Distinct characters78
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

Unique40 ?
Unique (%)100.0%

Sample

1st row달성초등학교
2nd row중리초등학교
3rd row서구청
4th row이현초등학교
5th row경상여자중학교
ValueCountFrequency (%)
달성초등학교 1
 
2.4%
비산2,3동복개도로 1
 
2.4%
인지초등학교 1
 
2.4%
서부공업고등학교 1
 
2.4%
서구 1
 
2.4%
구민운동장 1
 
2.4%
서남중학교 1
 
2.4%
서구문화회관 1
 
2.4%
서구청소년수련관 1
 
2.4%
서구국민체육센터 1
 
2.4%
Other values (32) 32
76.2%
2024-03-13T22:27:44.264283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 30
 
11.2%
교 30
 
11.2%
등 22
 
8.2%
서 20
 
7.4%
초 17
 
6.3%
구 12
 
4.5%
중 9
 
3.3%
대 8
 
3.0%
부 5
 
1.9%
리 5
 
1.9%
Other values (68) 111
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
97.8%
Decimal Number 3
 
1.1%
Space Separator 2
 
0.7%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 30
 
11.4%
교 30
 
11.4%
등 22
 
8.4%
서 20
 
7.6%
초 17
 
6.5%
구 12
 
4.6%
중 9
 
3.4%
대 8
 
3.0%
부 5
 
1.9%
리 5
 
1.9%
Other values (63) 105
39.9%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
97.8%
Common 6
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 30
 
11.4%
교 30
 
11.4%
등 22
 
8.4%
서 20
 
7.6%
초 17
 
6.5%
구 12
 
4.6%
중 9
 
3.4%
대 8
 
3.0%
부 5
 
1.9%
리 5
 
1.9%
Other values (63) 105
39.9%
Common
ValueCountFrequency (%)
2
33.3%
2 1
16.7%
, 1
16.7%
3 1
16.7%
6 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
97.8%
ASCII 6
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 30
 
11.4%
교 30
 
11.4%
등 22
 
8.4%
서 20
 
7.6%
초 17
 
6.5%
구 12
 
4.6%
중 9
 
3.4%
대 8
 
3.0%
부 5
 
1.9%
리 5
 
1.9%
Other values (63) 105
39.9%
ASCII
ValueCountFrequency (%)
2
33.3%
2 1
16.7%
, 1
16.7%
3 1
16.7%
6 1
16.7%

전화번호(주차장관리자)
Text

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-03-13T22:27:44.579250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters480
Distinct characters11
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

Unique37 ?
Unique (%)92.5%

Sample

1st row053-233-0296
2nd row053-233-0755
3rd row053-663-3013
4th row053-233-1608
5th row053-233-8515
ValueCountFrequency (%)
053-663-3013 3
 
7.5%
053-233-0504 1
 
2.5%
053-233-1706 1
 
2.5%
053-233-0180 1
 
2.5%
053-663-3081 1
 
2.5%
053-233-7831 1
 
2.5%
053-663-3091 1
 
2.5%
053-572-2451 1
 
2.5%
053-663-3663 1
 
2.5%
053-233-6083 1
 
2.5%
Other values (28) 28
70.0%
2024-03-13T22:27:45.109639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 124
25.8%
- 80
16.7%
0 67
14.0%
5 56
11.7%
2 48
 
10.0%
1 31
 
6.5%
6 27
 
5.6%
7 14
 
2.9%
8 13
 
2.7%
4 13
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
83.3%
Dash Punctuation 80
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 124
31.0%
0 67
16.8%
5 56
14.0%
2 48
 
12.0%
1 31
 
7.8%
6 27
 
6.8%
7 14
 
3.5%
8 13
 
3.2%
4 13
 
3.2%
9 7
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 124
25.8%
- 80
16.7%
0 67
14.0%
5 56
11.7%
2 48
 
10.0%
1 31
 
6.5%
6 27
 
5.6%
7 14
 
2.9%
8 13
 
2.7%
4 13
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 124
25.8%
- 80
16.7%
0 67
14.0%
5 56
11.7%
2 48
 
10.0%
1 31
 
6.5%
6 27
 
5.6%
7 14
 
2.9%
8 13
 
2.7%
4 13
 
2.7%

Interactions

2024-03-13T22:27:39.887977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:27:39.576427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:27:40.019573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:27:39.733823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:27:45.257876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차장명주차장유형(노상_노외_부설)주소위도경도관리기관전화번호(주차장관리자)
주차장명1.0001.0001.0001.0001.0001.0001.000
주차장유형(노상_노외_부설)1.0001.0001.0000.0000.0001.0000.000
주소1.0001.0001.0001.0001.0001.0000.983
위도1.0000.0001.0001.0000.7501.0000.985
경도1.0000.0001.0000.7501.0001.0000.974
관리기관1.0001.0001.0001.0001.0001.0001.000
전화번호(주차장관리자)1.0000.0000.9830.9850.9741.0001.000
2024-03-13T22:27:45.402226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도주차장유형(노상_노외_부설)
위도1.0000.2920.000
경도0.2921.0000.000
주차장유형(노상_노외_부설)0.0000.0001.000

Missing values

2024-03-13T22:27:40.176723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:27:40.331455image/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

시도주차장명주차장유형(노상_노외_부설)주소위도경도관리기관전화번호(주차장관리자)
0대구광역시달성초등학교부설대구광역시 서구 고성로 12735.88285128.579359달성초등학교053-233-0296
1대구광역시중리초등학교부설대구광역시 서구 국채보상로 13535.869714128.545433중리초등학교053-233-0755
2대구광역시서구청부설대구광역시 서구 국채보상로 25735.872336128.559282서구청053-663-3013
3대구광역시이현초등학교부설대구광역시 서구 국채보상로 37길3535.873504128.550409이현초등학교053-233-1608
4대구광역시경상여자중학교부설대구광역시 서구 국채보상로 38435.870681128.573811경상여자중학교053-233-8515
5대구광역시제일고등학교부설대구광역시 서구 국채보상로 38435.870681128.573811제일고등학교053-235-6802
6대구광역시폴리텍6대학 대구캠퍼스부설대구광역시 서구 국채보상로 43길 1535.874087128.55306폴리텍6대학 대구캠퍼스053-560-3114
7대구광역시대구광역시립서부도서관부설대구광역시 서구 국채보상로 49길 1235.872443128.557755대구광역시립서부도서관053-231-2412
8대구광역시서부고등학교부설대구광역시 서구 국채보상로 53길 3235.873648128.5602서부고등학교053-231-4543
9대구광역시달서초등학교부설대구광역시 서구 국채보상로34길 3535.866843128.550518달서초등학교053-233-1909
시도주차장명주차장유형(노상_노외_부설)주소위도경도관리기관전화번호(주차장관리자)
30대구광역시경운중학교부설대구광역시 서구 서대구로3길 3235.859726128.553558경운중학교053-233-6083
31대구광역시대구서부교육지원청부설대구광역시 서구 서대구로3길 5(내당동)35.858857128.55632대구서부교육지원청053-233-0180
32대구광역시서대구중학교부설대구광역시 서구 서대구로45길 2235.878715128.552195서대구중학교053-233-7845
33대구광역시서평초등학교부설대구광역시 서구 서대구로45길 6035.878212128.547883서평초등학교053-233-2381
34대구광역시서대구초등학교부설대구광역시 서구 서대구로63길 28-1335.889713128.557533서대구초등학교053-233-1643
35대구광역시비산초등학교부설대구광역시 서구 통학로 20235.879009128.56438비산초등학교053-233-1348
36대구광역시북비산초등학교부설대구광역시 서구 통학로48길 735.881361128.564607북비산초등학교053-233-1508
37대구광역시서도초등학교부설대구광역시 서구 평리로 39535.86727128.565348서도초등학교053-233-1460
38대구광역시경운초등학교부설대구광역시 서구 평리로54길 1635.860884128.552724경운초등학교053-233-1706
39대구광역시대성초등학교부설대구광역시 서구 국채보상로 42635.870628128.577262대성초등학교053-233-0590