Overview

Dataset statistics

Number of variables7
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory63.7 B

Variable types

Text3
Categorical1
Numeric3

Dataset

Description대구광역시 북구 전통시장 현황에 대한 데이터로 전통시장명, 주소, 영업일, 영업시간, 점포수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15095881/fileData.do

Alerts

영업일 has constant value ""Constant
전통시장명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:02:10.494036
Analysis finished2023-12-12 20:02:11.775189
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

전통시장명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-13T05:02:11.903214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12.5
Mean length7.25
Min length4

Characters and Unicode

Total characters203
Distinct characters59
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

Unique28 ?
Unique (%)100.0%

Sample

1st row칠성시장
2nd row칠성상가시장
3rd row삼성시장
4th row경명시장
5th row팔달시장
ValueCountFrequency (%)
대구종합유통단지 6
 
17.6%
칠성시장 1
 
2.9%
관음시장 1
 
2.9%
전기재료관 1
 
2.9%
전기조명관 1
 
2.9%
전자상가 1
 
2.9%
산업용재관 1
 
2.9%
전자관 1
 
2.9%
섬유제품관 1
 
2.9%
칠성본시장 1
 
2.9%
Other values (19) 19
55.9%
2023-12-13T05:02:12.643723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 23
 
11.3%
장 23
 
11.3%
구 11
 
5.4%
대 10
 
4.9%
종 8
 
3.9%
합 8
 
3.9%
유 7
 
3.4%
전 7
 
3.4%
성 7
 
3.4%
통 7
 
3.4%
Other values (49) 92
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195
96.1%
Space Separator 6
 
3.0%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 23
 
11.8%
장 23
 
11.8%
구 11
 
5.6%
대 10
 
5.1%
종 8
 
4.1%
합 8
 
4.1%
유 7
 
3.6%
전 7
 
3.6%
성 7
 
3.6%
통 7
 
3.6%
Other values (46) 84
43.1%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 195
96.1%
Common 8
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 23
 
11.8%
장 23
 
11.8%
구 11
 
5.6%
대 10
 
5.1%
종 8
 
4.1%
합 8
 
4.1%
유 7
 
3.6%
전 7
 
3.6%
성 7
 
3.6%
통 7
 
3.6%
Other values (46) 84
43.1%
Common
ValueCountFrequency (%)
6
75.0%
( 1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 195
96.1%
ASCII 8
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 23
 
11.8%
장 23
 
11.8%
구 11
 
5.6%
대 10
 
5.1%
종 8
 
4.1%
합 8
 
4.1%
유 7
 
3.6%
전 7
 
3.6%
성 7
 
3.6%
통 7
 
3.6%
Other values (46) 84
43.1%
ASCII
ValueCountFrequency (%)
6
75.0%
( 1
 
12.5%
) 1
 
12.5%

주소
Text

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-13T05:02:12.897104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length23.785714
Min length20

Characters and Unicode

Total characters666
Distinct characters60
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

Unique26 ?
Unique (%)92.9%

Sample

1st row대구광역시 북구 칠성남로 229(칠성동1가)
2nd row대구광역시 북구 칠성남로 230(칠성동1가)
3rd row대구광역시 북구 칠성시장로 42(칠성동1가)
4th row대구광역시 북구 칠성시장로 19(칠성동1가)
5th row대구광역시 북구 팔달로37길 11(노원동2가)
ValueCountFrequency (%)
대구광역시 28
24.8%
북구 28
24.8%
칠성시장로 6
 
5.3%
유통단지로 6
 
5.3%
칠성남로 3
 
2.7%
19(칠성동1가 2
 
1.8%
경진로1길 2
 
1.8%
68(복현동 1
 
0.9%
1(관음동 1
 
0.9%
229(칠성동1가 1
 
0.9%
Other values (35) 35
31.0%
2023-12-13T05:02:13.239295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
12.8%
구 57
 
8.6%
시 36
 
5.4%
대 34
 
5.1%
동 30
 
4.5%
역 28
 
4.2%
광 28
 
4.2%
북 28
 
4.2%
로 28
 
4.2%
( 28
 
4.2%
Other values (50) 284
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
64.6%
Decimal Number 91
 
13.7%
Space Separator 85
 
12.8%
Open Punctuation 28
 
4.2%
Close Punctuation 28
 
4.2%
Dash Punctuation 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 57
13.3%
시 36
 
8.4%
대 34
 
7.9%
동 30
 
7.0%
역 28
 
6.5%
광 28
 
6.5%
북 28
 
6.5%
로 28
 
6.5%
칠 21
 
4.9%
성 20
 
4.7%
Other values (35) 120
27.9%
Decimal Number
ValueCountFrequency (%)
1 24
26.4%
2 14
15.4%
3 12
13.2%
5 11
12.1%
4 6
 
6.6%
9 5
 
5.5%
7 5
 
5.5%
8 5
 
5.5%
0 5
 
5.5%
6 4
 
4.4%
Space Separator
ValueCountFrequency (%)
85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 430
64.6%
Common 236
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 57
13.3%
시 36
 
8.4%
대 34
 
7.9%
동 30
 
7.0%
역 28
 
6.5%
광 28
 
6.5%
북 28
 
6.5%
로 28
 
6.5%
칠 21
 
4.9%
성 20
 
4.7%
Other values (35) 120
27.9%
Common
ValueCountFrequency (%)
85
36.0%
( 28
 
11.9%
) 28
 
11.9%
1 24
 
10.2%
2 14
 
5.9%
3 12
 
5.1%
5 11
 
4.7%
4 6
 
2.5%
9 5
 
2.1%
7 5
 
2.1%
Other values (5) 18
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 430
64.6%
ASCII 236
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
36.0%
( 28
 
11.9%
) 28
 
11.9%
1 24
 
10.2%
2 14
 
5.9%
3 12
 
5.1%
5 11
 
4.7%
4 6
 
2.5%
9 5
 
2.1%
7 5
 
2.1%
Other values (5) 18
 
7.6%
Hangul
ValueCountFrequency (%)
구 57
13.3%
시 36
 
8.4%
대 34
 
7.9%
동 30
 
7.0%
역 28
 
6.5%
광 28
 
6.5%
북 28
 
6.5%
로 28
 
6.5%
칠 21
 
4.9%
성 20
 
4.7%
Other values (35) 120
27.9%

영업일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
상설시장
28 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설시장 28
100.0%

Length

2023-12-13T05:02:13.359663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:02:13.443578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설시장 28
100.0%

영업시간
Text

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-13T05:02:13.551795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.464286
Min length5

Characters and Unicode

Total characters349
Distinct characters17
Distinct categories5 ?
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 (%)75.0%

Sample

1st row10:00 - 17:00
2nd row06:00 - 19:00
3rd row05:30 - 19:00
4th row자료 없음
5th row07:00 - 21:00
ValueCountFrequency (%)
26
31.7%
21:00 5
 
6.1%
19:00 5
 
6.1%
18:00 5
 
6.1%
09:00 5
 
6.1%
08:00 4
 
4.9%
06:00 4
 
4.9%
07:00 3
 
3.7%
22:00 3
 
3.7%
05:00 3
 
3.7%
Other values (13) 19
23.2%
2023-12-13T05:02:13.825658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 130
37.2%
55
15.8%
: 52
 
14.9%
- 26
 
7.4%
1 21
 
6.0%
2 17
 
4.9%
9 11
 
3.2%
8 9
 
2.6%
7 5
 
1.4%
3 5
 
1.4%
Other values (7) 18
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
59.6%
Space Separator 55
 
15.8%
Other Punctuation 52
 
14.9%
Dash Punctuation 26
 
7.4%
Other Letter 8
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 130
62.5%
1 21
 
10.1%
2 17
 
8.2%
9 11
 
5.3%
8 9
 
4.3%
7 5
 
2.4%
3 5
 
2.4%
6 4
 
1.9%
5 4
 
1.9%
4 2
 
1.0%
Other Letter
ValueCountFrequency (%)
료 2
25.0%
음 2
25.0%
없 2
25.0%
자 2
25.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Other Punctuation
ValueCountFrequency (%)
: 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 341
97.7%
Hangul 8
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 130
38.1%
55
16.1%
: 52
 
15.2%
- 26
 
7.6%
1 21
 
6.2%
2 17
 
5.0%
9 11
 
3.2%
8 9
 
2.6%
7 5
 
1.5%
3 5
 
1.5%
Other values (3) 10
 
2.9%
Hangul
ValueCountFrequency (%)
료 2
25.0%
음 2
25.0%
없 2
25.0%
자 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 341
97.7%
Hangul 8
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 130
38.1%
55
16.1%
: 52
 
15.2%
- 26
 
7.6%
1 21
 
6.2%
2 17
 
5.0%
9 11
 
3.2%
8 9
 
2.6%
7 5
 
1.5%
3 5
 
1.5%
Other values (3) 10
 
2.9%
Hangul
ValueCountFrequency (%)
료 2
25.0%
음 2
25.0%
없 2
25.0%
자 2
25.0%

점포수
Real number (ℝ)

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean238.75
Minimum6
Maximum1649
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T05:02:13.955643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile38.05
Q161.5
median95
Q3227.5
95-th percentile901.8
Maximum1649
Range1643
Interquartile range (IQR)166

Descriptive statistics

Standard deviation353.39052
Coefficient of variation (CV)1.4801697
Kurtosis9.6094576
Mean238.75
Median Absolute Deviation (MAD)41
Skewness2.9682329
Sum6685
Variance124884.86
MonotonicityNot monotonic
2023-12-13T05:02:14.075430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
60 2
 
7.1%
215 1
 
3.6%
120 1
 
3.6%
360 1
 
3.6%
82 1
 
3.6%
369 1
 
3.6%
1649 1
 
3.6%
1011 1
 
3.6%
699 1
 
3.6%
79 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
6 1
3.6%
30 1
3.6%
53 1
3.6%
55 1
3.6%
58 1
3.6%
60 2
7.1%
62 1
3.6%
66 1
3.6%
79 1
3.6%
80 1
3.6%
ValueCountFrequency (%)
1649 1
3.6%
1011 1
3.6%
699 1
3.6%
420 1
3.6%
369 1
3.6%
360 1
3.6%
265 1
3.6%
215 1
3.6%
180 1
3.6%
161 1
3.6%

경도
Real number (ℝ)

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59573
Minimum128.5449
Maximum128.61977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T05:02:14.204368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5449
5-th percentile128.54862
Q1128.60021
median128.60422
Q3128.60786
95-th percentile128.61609
Maximum128.61977
Range0.074869
Interquartile range (IQR)0.0076431

Descriptive statistics

Standard deviation0.022238293
Coefficient of variation (CV)0.00017293182
Kurtosis0.64857734
Mean128.59573
Median Absolute Deviation (MAD)0.00377185
Skewness-1.4392899
Sum3600.6804
Variance0.0004945417
MonotonicityNot monotonic
2023-12-13T05:02:14.384397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
128.6040691 2
 
7.1%
128.6054247 1
 
3.6%
128.5472252 1
 
3.6%
128.6015562 1
 
3.6%
128.6077158 1
 
3.6%
128.6082746 1
 
3.6%
128.6049824 1
 
3.6%
128.6063967 1
 
3.6%
128.6070231 1
 
3.6%
128.6096639 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
128.5449038 1
3.6%
128.5472252 1
3.6%
128.551221 1
3.6%
128.5541346 1
3.6%
128.565958 1
3.6%
128.570853 1
3.6%
128.596181 1
3.6%
128.6015562 1
3.6%
128.6019647 1
3.6%
128.603476 1
3.6%
ValueCountFrequency (%)
128.6197728 1
3.6%
128.6191898 1
3.6%
128.6103474 1
3.6%
128.6098705 1
3.6%
128.6096639 1
3.6%
128.6089392 1
3.6%
128.6082746 1
3.6%
128.6077158 1
3.6%
128.6070231 1
3.6%
128.6063967 1
3.6%

위도
Real number (ℝ)

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.895872
Minimum35.875276
Maximum35.944921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-13T05:02:14.538492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.875276
5-th percentile35.87553
Q135.877121
median35.891731
Q335.905844
95-th percentile35.936907
Maximum35.944921
Range0.06964522
Interquartile range (IQR)0.028723147

Descriptive statistics

Standard deviation0.020778428
Coefficient of variation (CV)0.00057885286
Kurtosis0.063563302
Mean35.895872
Median Absolute Deviation (MAD)0.014563875
Skewness0.92473552
Sum1005.0844
Variance0.00043174309
MonotonicityNot monotonic
2023-12-13T05:02:14.705918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
35.87571538 2
 
7.1%
35.87631243 1
 
3.6%
35.94492131 1
 
3.6%
35.88023463 1
 
3.6%
35.90506192 1
 
3.6%
35.90569902 1
 
3.6%
35.9054543 1
 
3.6%
35.90496946 1
 
3.6%
35.90720155 1
 
3.6%
35.90627781 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
35.87527609 1
3.6%
35.87551553 1
3.6%
35.8755559 1
3.6%
35.87571538 2
7.1%
35.87631243 1
3.6%
35.8770321 1
3.6%
35.87715006 1
3.6%
35.87781845 1
3.6%
35.88023463 1
3.6%
35.88115274 1
3.6%
ValueCountFrequency (%)
35.94492131 1
3.6%
35.94252351 1
3.6%
35.92647567 1
3.6%
35.92165993 1
3.6%
35.92100106 1
3.6%
35.90720155 1
3.6%
35.90627781 1
3.6%
35.90569902 1
3.6%
35.9054543 1
3.6%
35.90506192 1
3.6%

Interactions

2023-12-13T05:02:11.295381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:10.753893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:11.002504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:11.383820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:10.835211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:11.089071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:11.497524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:10.921245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:02:11.193962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:02:14.812376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전통시장명주소영업시간점포수경도위도
전통시장명1.0001.0001.0001.0001.0001.000
주소1.0001.0000.9771.0001.0001.000
영업시간1.0000.9771.0000.9450.0000.000
점포수1.0001.0000.9451.0000.0000.000
경도1.0001.0000.0000.0001.0000.990
위도1.0001.0000.0000.0000.9901.000
2023-12-13T05:02:14.937593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
점포수경도위도
점포수1.0000.4270.009
경도0.4271.000-0.164
위도0.009-0.1641.000

Missing values

2023-12-13T05:02:11.615199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:02:11.730750image/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

전통시장명주소영업일영업시간점포수경도위도
0칠성시장대구광역시 북구 칠성남로 229(칠성동1가)상설시장10:00 - 17:00215128.60542535.876312
1칠성상가시장대구광역시 북구 칠성남로 230(칠성동1가)상설시장06:00 - 19:0060128.60530835.875556
2삼성시장대구광역시 북구 칠성시장로 42(칠성동1가)상설시장05:30 - 19:0080128.60347635.877818
3경명시장대구광역시 북구 칠성시장로 19(칠성동1가)상설시장자료 없음87128.60406935.875715
4팔달시장대구광역시 북구 팔달로37길 11(노원동2가)상설시장07:00 - 21:0097128.57085335.889047
5팔달신시장대구광역시 북구 팔달로33길 59(노원동3가)상설시장03:00 - 20:00420128.56595835.890701
6복현종합시장대구광역시 북구 경진로1길 78(복현동, 복현시장상가)상설시장09:00 - 23:00265128.61977335.89276
7산격종합시장대구광역시 북구 대동로1길 34(산격동)상설시장09:00 - 21:00161128.61034735.89864
8동대구시장대구광역시 북구 대현로20길 30(대현동)상설시장07:00 - 21:00180128.60893935.881153
9칠곡시장(공설시장)대구광역시 북구 칠곡중앙대로 526(읍내동)상설시장06:00 - 21:0062128.55122135.942524
전통시장명주소영업일영업시간점포수경도위도
18복현전통신시장대구광역시 북구 경진로1길 68(복현동)상설시장자료 없음55128.6191935.893277
19칠성진시장대구광역시 북구 칠성시장로 19(칠성동1가)상설시장05:00 - 20:006128.60406935.875715
20칠성본시장대구광역시 북구 칠성시장로 15-1(칠성동1가)상설시장05:00 - 19:0079128.60437835.875516
21대구종합유통단지 섬유제품관대구광역시 북구 유통단지로 60(산격동)상설시장10:00 - 20:00699128.60966435.906278
22대구종합유통단지 전자관대구광역시 북구 유통단지로 45(산격동)상설시장09:30 - 20:301011128.60702335.907202
23대구종합유통단지 산업용재관대구광역시 북구 유통단지로 16(산격동)상설시장09:00 - 18:001649128.60639735.904969
24대구종합유통단지 전자상가대구광역시 북구 유통단지로 25(산격동)상설시장09:00 - 17:00369128.60498235.905454
25대구종합유통단지 전기조명관대구광역시 북구 유통단지로 50(산격동)상설시장08:00 - 18:0082128.60827535.905699
26대구종합유통단지 전기재료관대구광역시 북구 유통단지로 38(산격동)상설시장08:00 - 19:00360128.60771635.905062
27칠성전자주방시장대구광역시 북구 칠성시장로 73-1(칠성동2가)상설시장08:00 - 19:00120128.60155635.880235