Overview

Dataset statistics

Number of variables7
Number of observations105
Missing cells13
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory60.3 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description대구광역시_북구_안경업소현황_20190906
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15030482&dataSetDetailId=150304822f6dbc2007f12_201909061041&provdMethod=FILE

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 13 (12.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:40:46.054782
Analysis finished2024-04-19 05:40:47.268253
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-19T14:40:47.365602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q127
median53
Q379
95-th percentile99.8
Maximum105
Range104
Interquartile range (IQR)52

Descriptive statistics

Standard deviation30.454885
Coefficient of variation (CV)0.57462047
Kurtosis-1.2
Mean53
Median Absolute Deviation (MAD)26
Skewness0
Sum5565
Variance927.5
MonotonicityStrictly increasing
2024-04-19T14:40:47.501910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
80 1
 
1.0%
78 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
Other values (95) 95
90.5%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
105 1
1.0%
104 1
1.0%
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%

업소명
Text

Distinct103
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size972.0 B
2024-04-19T14:40:47.762488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.6
Min length4

Characters and Unicode

Total characters798
Distinct characters178
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)96.2%

Sample

1st row1001동변점안경원
2nd row1001안경원경대점
3rd row1001안경콘택트 침산점
4th row1001안경콘택트산격점
5th row강북안경원
ValueCountFrequency (%)
안경원 8
 
6.1%
아이젠트리 3
 
2.3%
라디오아이즈 2
 
1.5%
동천점 2
 
1.5%
칠곡점 2
 
1.5%
씨채널 2
 
1.5%
안경매니져 2
 
1.5%
침산점 2
 
1.5%
왕눈이안경타운 2
 
1.5%
칠곡안경원 1
 
0.8%
Other values (105) 105
80.2%
2024-04-19T14:40:48.163740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 96
 
12.0%
안 94
 
11.8%
원 47
 
5.9%
점 30
 
3.8%
이 29
 
3.6%
아 29
 
3.6%
26
 
3.3%
트 24
 
3.0%
콘 16
 
2.0%
스 15
 
1.9%
Other values (168) 392
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 729
91.4%
Space Separator 26
 
3.3%
Decimal Number 18
 
2.3%
Lowercase Letter 7
 
0.9%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%
Uppercase Letter 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 96
 
13.2%
안 94
 
12.9%
원 47
 
6.4%
점 30
 
4.1%
이 29
 
4.0%
아 29
 
4.0%
트 24
 
3.3%
콘 16
 
2.2%
스 15
 
2.1%
택 15
 
2.1%
Other values (151) 334
45.8%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
k 1
 
14.3%
e 1
 
14.3%
r 1
 
14.3%
t 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
I 1
20.0%
N 1
20.0%
S 1
20.0%
L 1
20.0%
G 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
0 8
44.4%
2 2
 
11.1%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 729
91.4%
Common 57
 
7.1%
Latin 12
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 96
 
13.2%
안 94
 
12.9%
원 47
 
6.4%
점 30
 
4.1%
이 29
 
4.0%
아 29
 
4.0%
트 24
 
3.3%
콘 16
 
2.2%
스 15
 
2.1%
택 15
 
2.1%
Other values (151) 334
45.8%
Latin
ValueCountFrequency (%)
o 3
25.0%
I 1
 
8.3%
N 1
 
8.3%
k 1
 
8.3%
e 1
 
8.3%
r 1
 
8.3%
t 1
 
8.3%
S 1
 
8.3%
L 1
 
8.3%
G 1
 
8.3%
Common
ValueCountFrequency (%)
26
45.6%
1 8
 
14.0%
0 8
 
14.0%
( 6
 
10.5%
) 6
 
10.5%
2 2
 
3.5%
/ 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 729
91.4%
ASCII 69
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 96
 
13.2%
안 94
 
12.9%
원 47
 
6.4%
점 30
 
4.1%
이 29
 
4.0%
아 29
 
4.0%
트 24
 
3.3%
콘 16
 
2.2%
스 15
 
2.1%
택 15
 
2.1%
Other values (151) 334
45.8%
ASCII
ValueCountFrequency (%)
26
37.7%
1 8
 
11.6%
0 8
 
11.6%
( 6
 
8.7%
) 6
 
8.7%
o 3
 
4.3%
2 2
 
2.9%
I 1
 
1.4%
N 1
 
1.4%
k 1
 
1.4%
Other values (7) 7
 
10.1%

소재지도로명주소
Text

Distinct104
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2024-04-19T14:40:48.471146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length25.961905
Min length20

Characters and Unicode

Total characters2726
Distinct characters126
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

Unique103 ?
Unique (%)98.1%

Sample

1st row대구광역시 북구 동변로18길 2 (동변동)
2nd row대구광역시 북구 대학로 85 (산격동)
3rd row대구광역시 북구 침산남로 153 (침산동)
4th row대구광역시 북구 동북로 154 (산격동)
5th row대구광역시 북구 학정로 421 (동천동, 일도프라자 107)
ValueCountFrequency (%)
대구광역시 105
17.9%
북구 105
17.9%
산격동 24
 
4.1%
침산동 16
 
2.7%
태전동 15
 
2.6%
동천동 15
 
2.6%
동북로 13
 
2.2%
칠곡중앙대로 12
 
2.0%
1층 11
 
1.9%
복현동 9
 
1.5%
Other values (186) 261
44.5%
2024-04-19T14:40:48.953037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
481
17.6%
구 215
 
7.9%
동 153
 
5.6%
대 136
 
5.0%
북 123
 
4.5%
시 106
 
3.9%
역 106
 
3.9%
로 106
 
3.9%
광 105
 
3.9%
( 105
 
3.9%
Other values (116) 1090
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1592
58.4%
Space Separator 481
 
17.6%
Decimal Number 391
 
14.3%
Open Punctuation 105
 
3.9%
Close Punctuation 105
 
3.9%
Other Punctuation 38
 
1.4%
Dash Punctuation 9
 
0.3%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 215
13.5%
동 153
 
9.6%
대 136
 
8.5%
북 123
 
7.7%
시 106
 
6.7%
역 106
 
6.7%
로 106
 
6.7%
광 105
 
6.6%
산 55
 
3.5%
격 28
 
1.8%
Other values (95) 459
28.8%
Decimal Number
ValueCountFrequency (%)
1 99
25.3%
2 59
15.1%
3 47
12.0%
0 35
 
9.0%
4 31
 
7.9%
5 30
 
7.7%
6 28
 
7.2%
7 24
 
6.1%
8 20
 
5.1%
9 18
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
Y 1
25.0%
K 1
25.0%
S 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 37
97.4%
/ 1
 
2.6%
Space Separator
ValueCountFrequency (%)
481
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1592
58.4%
Common 1130
41.5%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 215
13.5%
동 153
 
9.6%
대 136
 
8.5%
북 123
 
7.7%
시 106
 
6.7%
역 106
 
6.7%
로 106
 
6.7%
광 105
 
6.6%
산 55
 
3.5%
격 28
 
1.8%
Other values (95) 459
28.8%
Common
ValueCountFrequency (%)
481
42.6%
( 105
 
9.3%
) 105
 
9.3%
1 99
 
8.8%
2 59
 
5.2%
3 47
 
4.2%
, 37
 
3.3%
0 35
 
3.1%
4 31
 
2.7%
5 30
 
2.7%
Other values (7) 101
 
8.9%
Latin
ValueCountFrequency (%)
B 1
25.0%
Y 1
25.0%
K 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1592
58.4%
ASCII 1134
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
481
42.4%
( 105
 
9.3%
) 105
 
9.3%
1 99
 
8.7%
2 59
 
5.2%
3 47
 
4.1%
, 37
 
3.3%
0 35
 
3.1%
4 31
 
2.7%
5 30
 
2.6%
Other values (11) 105
 
9.3%
Hangul
ValueCountFrequency (%)
구 215
13.5%
동 153
 
9.6%
대 136
 
8.5%
북 123
 
7.7%
시 106
 
6.7%
역 106
 
6.7%
로 106
 
6.7%
광 105
 
6.6%
산 55
 
3.5%
격 28
 
1.8%
Other values (95) 459
28.8%

전화번호
Text

MISSING 

Distinct89
Distinct (%)96.7%
Missing13
Missing (%)12.4%
Memory size972.0 B
2024-04-19T14:40:49.196821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1104
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

Unique86 ?
Unique (%)93.5%

Sample

1st row053-939-1001
2nd row053-958-1002
3rd row053-351-2445
4th row053-954-1001
5th row053-323-0760
ValueCountFrequency (%)
053-955-7525 2
 
2.2%
053-357-8831 2
 
2.2%
053-384-0767 2
 
2.2%
053-312-1579 1
 
1.1%
053-313-2800 1
 
1.1%
053-326-0100 1
 
1.1%
053-326-3008 1
 
1.1%
053-341-3007 1
 
1.1%
053-955-3369 1
 
1.1%
053-381-8856 1
 
1.1%
Other values (79) 79
85.9%
2024-04-19T14:40:49.566504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 199
18.0%
- 184
16.7%
5 183
16.6%
0 165
14.9%
1 69
 
6.2%
2 68
 
6.2%
9 60
 
5.4%
4 55
 
5.0%
8 47
 
4.3%
6 39
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
83.3%
Dash Punctuation 184
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 199
21.6%
5 183
19.9%
0 165
17.9%
1 69
 
7.5%
2 68
 
7.4%
9 60
 
6.5%
4 55
 
6.0%
8 47
 
5.1%
6 39
 
4.2%
7 35
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 199
18.0%
- 184
16.7%
5 183
16.6%
0 165
14.9%
1 69
 
6.2%
2 68
 
6.2%
9 60
 
5.4%
4 55
 
5.0%
8 47
 
4.3%
6 39
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 199
18.0%
- 184
16.7%
5 183
16.6%
0 165
14.9%
1 69
 
6.2%
2 68
 
6.2%
9 60
 
5.4%
4 55
 
5.0%
8 47
 
4.3%
6 39
 
3.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct104
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.908313
Minimum35.875881
Maximum35.952217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-19T14:40:49.708969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875881
5-th percentile35.8804
Q135.892536
median35.899745
Q335.929129
95-th percentile35.943631
Maximum35.952217
Range0.07633608
Interquartile range (IQR)0.03659282

Descriptive statistics

Standard deviation0.021509637
Coefficient of variation (CV)0.00059901551
Kurtosis-1.1466526
Mean35.908313
Median Absolute Deviation (MAD)0.01349149
Skewness0.49612879
Sum3770.3729
Variance0.00046266447
MonotonicityNot monotonic
2024-04-19T14:40:49.860109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.89890849 2
 
1.9%
35.92114336 1
 
1.0%
35.90005804 1
 
1.0%
35.92924963 1
 
1.0%
35.93273234 1
 
1.0%
35.89966631 1
 
1.0%
35.89253628 1
 
1.0%
35.89935982 1
 
1.0%
35.88368751 1
 
1.0%
35.90156324 1
 
1.0%
Other values (94) 94
89.5%
ValueCountFrequency (%)
35.87588137 1
1.0%
35.87790725 1
1.0%
35.87845591 1
1.0%
35.87850431 1
1.0%
35.8800717 1
1.0%
35.88027798 1
1.0%
35.88089007 1
1.0%
35.88100459 1
1.0%
35.88148035 1
1.0%
35.88368751 1
1.0%
ValueCountFrequency (%)
35.95221745 1
1.0%
35.94484497 1
1.0%
35.94401442 1
1.0%
35.9439295 1
1.0%
35.94376971 1
1.0%
35.94364884 1
1.0%
35.94355794 1
1.0%
35.94336064 1
1.0%
35.94334557 1
1.0%
35.94330564 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct104
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58536
Minimum128.51455
Maximum128.62569
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-19T14:40:50.035687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.51455
5-th percentile128.54693
Q1128.56116
median128.58989
Q3128.60933
95-th percentile128.6187
Maximum128.62569
Range0.1111356
Interquartile range (IQR)0.0481701

Descriptive statistics

Standard deviation0.026618375
Coefficient of variation (CV)0.00020700938
Kurtosis-1.111489
Mean128.58536
Median Absolute Deviation (MAD)0.0226345
Skewness-0.34225184
Sum13501.462
Variance0.00070853786
MonotonicityNot monotonic
2024-04-19T14:40:50.275361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6125207 2
 
1.9%
128.6037614 1
 
1.0%
128.6150885 1
 
1.0%
128.5427839 1
 
1.0%
128.5498895 1
 
1.0%
128.5816306 1
 
1.0%
128.6212553 1
 
1.0%
128.6228818 1
 
1.0%
128.5959781 1
 
1.0%
128.6185898 1
 
1.0%
Other values (94) 94
89.5%
ValueCountFrequency (%)
128.5145534 1
1.0%
128.5427839 1
1.0%
128.5445637 1
1.0%
128.5463065 1
1.0%
128.5467777 1
1.0%
128.5468626 1
1.0%
128.5471984 1
1.0%
128.5472702 1
1.0%
128.5474818 1
1.0%
128.547749 1
1.0%
ValueCountFrequency (%)
128.625689 1
1.0%
128.6250017 1
1.0%
128.6228818 1
1.0%
128.6226079 1
1.0%
128.6212553 1
1.0%
128.6187321 1
1.0%
128.6185898 1
1.0%
128.6180955 1
1.0%
128.6177526 1
1.0%
128.6175103 1
1.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2019-09-06
105 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-09-06
2nd row2019-09-06
3rd row2019-09-06
4th row2019-09-06
5th row2019-09-06

Common Values

ValueCountFrequency (%)
2019-09-06 105
100.0%

Length

2024-04-19T14:40:50.418318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:40:50.511294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-09-06 105
100.0%

Interactions

2024-04-19T14:40:46.831805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.311733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.568151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.916053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.392040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.654965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.999914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.477815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:40:46.743233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:40:50.577043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호위도경도
연번1.0000.9860.0000.101
전화번호0.9861.0000.9860.983
위도0.0000.9861.0000.797
경도0.1010.9830.7971.000
2024-04-19T14:40:50.675100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.083-0.028
위도-0.0831.000-0.574
경도-0.028-0.5741.000

Missing values

2024-04-19T14:40:47.116231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:40:47.221437image/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

연번업소명소재지도로명주소전화번호위도경도데이터기준일자
011001동변점안경원대구광역시 북구 동변로18길 2 (동변동)053-939-100135.921143128.6037612019-09-06
121001안경원경대점대구광역시 북구 대학로 85 (산격동)053-958-100235.892859128.6093282019-09-06
231001안경콘택트 침산점대구광역시 북구 침산남로 153 (침산동)053-351-244535.888202128.5925232019-09-06
341001안경콘택트산격점대구광역시 북구 동북로 154 (산격동)053-954-100135.899745128.6093922019-09-06
45강북안경원대구광역시 북구 학정로 421 (동천동, 일도프라자 107)053-323-076035.942378128.5630912019-09-06
56경대구내안경원대구광역시 북구 대학로 80, 경북대학교 복지관 1층 (산격동)<NA>35.889011128.6145162019-09-06
67경북안경원대구광역시 북구 노원로 226 (침산동)053-959-005235.900472128.5846282019-09-06
78고고고안경대구광역시 북구 노원로 45 (노원동3가)053-356-789035.892804128.5672582019-09-06
89귀빈당 안경원대구광역시 북구 동북로 246 (복현동)053-952-022235.89506128.6177532019-09-06
910글라스스토리 안경원대구광역시 북구 칠곡중앙대로 403 (태전동)053-314-314835.931867128.5480222019-09-06
연번업소명소재지도로명주소전화번호위도경도데이터기준일자
9596자이스안경대구광역시 북구 성북로 36, 2층 216,217,218호 (침산동)053-353-767035.890831128.5875922019-09-06
9697제누네안경대구광역시 북구 칠성로 102 (칠성동2가)053-426-247335.878456128.600382019-09-06
9798제일밝은안경콘택트대구광역시 북구 옥산로17길 50 (침산동, 침산제일아파트 101동 상가 4호 1층)<NA>35.888932128.5870242019-09-06
9899좋은안경원대구광역시 북구 칠곡중앙대로 411 (태전동)<NA>35.932525128.5479932019-09-06
99100채널아이안경대구광역시 북구 학정로 39 (태전동)053-313-238935.913772128.5471982019-09-06
100101칠곡안경원대구광역시 북구 동천로 37 (동천동)053-321-008835.935206128.5586732019-09-06
101102침산가톨릭안경원대구광역시 북구 침산로 138 (침산동)053-359-111035.888809128.5918742019-09-06
102103코스트코안경대구광역시 북구 검단로 97, 코스트코코리아 지하2층 (산격동)053-352-575935.90637128.6180962019-09-06
103104팔레스안경원대구광역시 북구 칠곡중앙대로 404 (태전동)053-323-969235.931792128.5486092019-09-06
104105피플안경원대구광역시 북구 칠곡중앙대로 355 (태전동)053-325-599535.927363128.547272019-09-06