Overview

Dataset statistics

Number of variables7
Number of observations50
Missing cells7
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory61.6 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description경상남도 김해시 나들가게 현황에 대한 데이터로 매장명,소재지도로명주소,소재지연락처,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15092790

Alerts

데이터기준일자 has constant value ""Constant
소재지연락번호 has 7 (14.0%) missing valuesMissing
연번 has unique valuesUnique
소재지 도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 00:13:57.389837
Analysis finished2024-03-13 00:13:58.484103
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T09:13:58.542665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-13T09:13:58.658160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

매장명
Text

Distinct47
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-13T09:13:58.845405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.52
Min length3

Characters and Unicode

Total characters276
Distinct characters87
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)88.0%

Sample

1st row동원마트
2nd row이안할인마트
3rd row한아름슈퍼
4th row나들가게칠산점
5th rowe그린마트
ValueCountFrequency (%)
나들가게 3
 
5.4%
더조은마트 2
 
3.6%
주공할인마트 2
 
3.6%
마트 2
 
3.6%
삼방럭키마트 1
 
1.8%
탑플러스마트 1
 
1.8%
대동상회 1
 
1.8%
동원마트 1
 
1.8%
슈퍼맨마트 1
 
1.8%
한강슈퍼마켓 1
 
1.8%
Other values (41) 41
73.2%
2024-03-13T09:13:59.137983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 37
 
13.4%
트 34
 
12.3%
할 13
 
4.7%
인 13
 
4.7%
동 8
 
2.9%
슈 7
 
2.5%
가 7
 
2.5%
퍼 7
 
2.5%
한 7
 
2.5%
나 6
 
2.2%
Other values (77) 137
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
91.3%
Lowercase Letter 8
 
2.9%
Space Separator 6
 
2.2%
Decimal Number 5
 
1.8%
Uppercase Letter 5
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 37
 
14.7%
트 34
 
13.5%
할 13
 
5.2%
인 13
 
5.2%
동 8
 
3.2%
슈 7
 
2.8%
가 7
 
2.8%
퍼 7
 
2.8%
한 7
 
2.8%
나 6
 
2.4%
Other values (61) 113
44.8%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
w 1
 
12.5%
r 1
 
12.5%
i 1
 
12.5%
m 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
3 1
20.0%
6 1
20.0%
5 1
20.0%
9 1
20.0%
1 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
20.0%
L 1
20.0%
G 1
20.0%
F 1
20.0%
T 1
20.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
91.3%
Latin 13
 
4.7%
Common 11
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 37
 
14.7%
트 34
 
13.5%
할 13
 
5.2%
인 13
 
5.2%
동 8
 
3.2%
슈 7
 
2.8%
가 7
 
2.8%
퍼 7
 
2.8%
한 7
 
2.8%
나 6
 
2.4%
Other values (61) 113
44.8%
Latin
ValueCountFrequency (%)
e 4
30.8%
K 1
 
7.7%
L 1
 
7.7%
G 1
 
7.7%
w 1
 
7.7%
F 1
 
7.7%
r 1
 
7.7%
T 1
 
7.7%
i 1
 
7.7%
m 1
 
7.7%
Common
ValueCountFrequency (%)
6
54.5%
3 1
 
9.1%
6 1
 
9.1%
5 1
 
9.1%
9 1
 
9.1%
1 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
91.3%
ASCII 24
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 37
 
14.7%
트 34
 
13.5%
할 13
 
5.2%
인 13
 
5.2%
동 8
 
3.2%
슈 7
 
2.8%
가 7
 
2.8%
퍼 7
 
2.8%
한 7
 
2.8%
나 6
 
2.4%
Other values (61) 113
44.8%
ASCII
ValueCountFrequency (%)
6
25.0%
e 4
16.7%
3 1
 
4.2%
K 1
 
4.2%
L 1
 
4.2%
G 1
 
4.2%
w 1
 
4.2%
6 1
 
4.2%
F 1
 
4.2%
r 1
 
4.2%
Other values (6) 6
25.0%

소재지 도로명주소
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-13T09:13:59.562962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length39
Mean length28.22
Min length16

Characters and Unicode

Total characters1411
Distinct characters123
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

Unique50 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 가야로 58(삼계동) 313동 101호 (삼계동,동원로얄듀크상가)
2nd row경상남도 김해시 해반천로278번길 58(삼계동) 58
3rd row경상남도 김해시 활천로57번길 6(삼정동) 6
4th row경상남도 김해시 칠산로413번길 16-7(화목동) 16-7
5th row경상남도 김해시 삼문로 90(삼문동) 제상가동 104호(삼문동,갑오마을부영그린타운1차)
ValueCountFrequency (%)
경상남도 50
 
18.9%
김해시 50
 
18.9%
1층 5
 
1.9%
상가 4
 
1.5%
101호 3
 
1.1%
가락로 3
 
1.1%
평전로 3
 
1.1%
함박로 3
 
1.1%
101 2
 
0.8%
분성로 2
 
0.8%
Other values (133) 140
52.8%
2024-03-13T09:13:59.927050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
215
 
15.2%
1 83
 
5.9%
상 67
 
4.7%
남 53
 
3.8%
도 51
 
3.6%
해 51
 
3.6%
시 51
 
3.6%
로 51
 
3.6%
경 50
 
3.5%
김 50
 
3.5%
Other values (113) 689
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 830
58.8%
Decimal Number 294
 
20.8%
Space Separator 215
 
15.2%
Close Punctuation 23
 
1.6%
Open Punctuation 23
 
1.6%
Dash Punctuation 16
 
1.1%
Other Punctuation 9
 
0.6%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 67
 
8.1%
남 53
 
6.4%
도 51
 
6.1%
해 51
 
6.1%
시 51
 
6.1%
로 51
 
6.1%
경 50
 
6.0%
김 50
 
6.0%
동 43
 
5.2%
번 25
 
3.0%
Other values (96) 338
40.7%
Decimal Number
ValueCountFrequency (%)
1 83
28.2%
2 44
15.0%
0 35
11.9%
5 25
 
8.5%
4 23
 
7.8%
6 20
 
6.8%
3 17
 
5.8%
7 16
 
5.4%
9 16
 
5.4%
8 15
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
/ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 830
58.8%
Common 580
41.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 67
 
8.1%
남 53
 
6.4%
도 51
 
6.1%
해 51
 
6.1%
시 51
 
6.1%
로 51
 
6.1%
경 50
 
6.0%
김 50
 
6.0%
동 43
 
5.2%
번 25
 
3.0%
Other values (96) 338
40.7%
Common
ValueCountFrequency (%)
215
37.1%
1 83
 
14.3%
2 44
 
7.6%
0 35
 
6.0%
5 25
 
4.3%
) 23
 
4.0%
( 23
 
4.0%
4 23
 
4.0%
6 20
 
3.4%
3 17
 
2.9%
Other values (6) 72
 
12.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 830
58.8%
ASCII 581
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
215
37.0%
1 83
 
14.3%
2 44
 
7.6%
0 35
 
6.0%
5 25
 
4.3%
) 23
 
4.0%
( 23
 
4.0%
4 23
 
4.0%
6 20
 
3.4%
3 17
 
2.9%
Other values (7) 73
 
12.6%
Hangul
ValueCountFrequency (%)
상 67
 
8.1%
남 53
 
6.4%
도 51
 
6.1%
해 51
 
6.1%
시 51
 
6.1%
로 51
 
6.1%
경 50
 
6.0%
김 50
 
6.0%
동 43
 
5.2%
번 25
 
3.0%
Other values (96) 338
40.7%

소재지연락번호
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing7
Missing (%)14.0%
Memory size532.0 B
2024-03-13T09:14:00.126166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters516
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

Unique43 ?
Unique (%)100.0%

Sample

1st row055-311-0089
2nd row055-326-0098
3rd row055-331-3711
4th row055-331-0095
5th row055-338-2246
ValueCountFrequency (%)
055-311-0089 1
 
2.3%
055-337-6568 1
 
2.3%
055-327-8220 1
 
2.3%
055-311-1518 1
 
2.3%
055-324-9881 1
 
2.3%
055-321-6324 1
 
2.3%
055-327-2982 1
 
2.3%
055-322-1182 1
 
2.3%
055-326-1159 1
 
2.3%
055-324-5551 1
 
2.3%
Other values (33) 33
76.7%
2024-03-13T09:14:00.455152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 107
20.7%
- 86
16.7%
3 73
14.1%
0 61
11.8%
2 43
8.3%
1 39
 
7.6%
8 29
 
5.6%
6 24
 
4.7%
7 21
 
4.1%
9 18
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 430
83.3%
Dash Punctuation 86
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 107
24.9%
3 73
17.0%
0 61
14.2%
2 43
10.0%
1 39
 
9.1%
8 29
 
6.7%
6 24
 
5.6%
7 21
 
4.9%
9 18
 
4.2%
4 15
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 516
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 107
20.7%
- 86
16.7%
3 73
14.1%
0 61
11.8%
2 43
8.3%
1 39
 
7.6%
8 29
 
5.6%
6 24
 
4.7%
7 21
 
4.1%
9 18
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 107
20.7%
- 86
16.7%
3 73
14.1%
0 61
11.8%
2 43
8.3%
1 39
 
7.6%
8 29
 
5.6%
6 24
 
4.7%
7 21
 
4.1%
9 18
 
3.5%

위도
Real number (ℝ)

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.233093
Minimum35.173545
Maximum35.304828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T09:14:00.573752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.173545
5-th percentile35.180609
Q135.231911
median35.237132
Q335.244202
95-th percentile35.262642
Maximum35.304828
Range0.13128318
Interquartile range (IQR)0.012291133

Descriptive statistics

Standard deviation0.024788759
Coefficient of variation (CV)0.00070356465
Kurtosis1.6431105
Mean35.233093
Median Absolute Deviation (MAD)0.0069257884
Skewness-0.49952819
Sum1761.6547
Variance0.00061448257
MonotonicityNot monotonic
2024-03-13T09:14:00.694673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
35.2325523743 2
 
4.0%
35.2698173576 1
 
2.0%
35.2374920025 1
 
2.0%
35.2295619344 1
 
2.0%
35.2470186845 1
 
2.0%
35.2400147086 1
 
2.0%
35.2022728562 1
 
2.0%
35.1966877531 1
 
2.0%
35.2362265582 1
 
2.0%
35.2514820053 1
 
2.0%
Other values (39) 39
78.0%
ValueCountFrequency (%)
35.1735452961 1
2.0%
35.1737220328 1
2.0%
35.1785220565 1
2.0%
35.1831606357 1
2.0%
35.1914861293 1
2.0%
35.1966877531 1
2.0%
35.2022728562 1
2.0%
35.2055866691 1
2.0%
35.2093116873 1
2.0%
35.2106996032 1
2.0%
ValueCountFrequency (%)
35.304828477 1
2.0%
35.2751515969 1
2.0%
35.2698173576 1
2.0%
35.2538721967 1
2.0%
35.2514820053 1
2.0%
35.2509112578 1
2.0%
35.250739007 1
2.0%
35.250566776 1
2.0%
35.2504168239 1
2.0%
35.2470186845 1
2.0%

경도
Real number (ℝ)

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.86692
Minimum128.71044
Maximum128.97235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T09:14:00.810669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.71044
5-th percentile128.79873
Q1128.85228
median128.87063
Q3128.89888
95-th percentile128.91531
Maximum128.97235
Range0.26191257
Interquartile range (IQR)0.046602942

Descriptive statistics

Standard deviation0.04349975
Coefficient of variation (CV)0.00033755558
Kurtosis2.5053015
Mean128.86692
Median Absolute Deviation (MAD)0.021871439
Skewness-0.90558668
Sum6443.3462
Variance0.0018922282
MonotonicityNot monotonic
2024-03-13T09:14:00.926061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
128.8649996262 2
 
4.0%
128.8667768432 1
 
2.0%
128.915164071 1
 
2.0%
128.8869511909 1
 
2.0%
128.8757422085 1
 
2.0%
128.8795206861 1
 
2.0%
128.8168640552 1
 
2.0%
128.8002693427 1
 
2.0%
128.8983980886 1
 
2.0%
128.8732977114 1
 
2.0%
Other values (39) 39
78.0%
ValueCountFrequency (%)
128.7104377455 1
2.0%
128.7966132494 1
2.0%
128.7974685674 1
2.0%
128.8002693427 1
2.0%
128.8051391261 1
2.0%
128.8084301926 1
2.0%
128.8168640552 1
2.0%
128.8187933645 1
2.0%
128.8190488024 1
2.0%
128.8200798177 1
2.0%
ValueCountFrequency (%)
128.9723503202 1
2.0%
128.9237284677 1
2.0%
128.9154334412 1
2.0%
128.915164071 1
2.0%
128.9127917601 1
2.0%
128.9100767596 1
2.0%
128.9095909811 1
2.0%
128.9076839698 1
2.0%
128.9061144631 1
2.0%
128.9035042897 1
2.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-06-01
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-01
2nd row2023-06-01
3rd row2023-06-01
4th row2023-06-01
5th row2023-06-01

Common Values

ValueCountFrequency (%)
2023-06-01 50
100.0%

Length

2024-03-13T09:14:01.029557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:14:01.101176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-01 50
100.0%

Interactions

2024-03-13T09:13:58.098810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:57.633913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:57.857022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:58.191344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:57.712072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:57.926469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:58.266983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:57.790606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:13:58.003999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T09:14:01.145646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번매장명소재지 도로명주소소재지연락번호위도경도
연번1.0000.7881.0001.0000.4250.430
매장명0.7881.0001.0001.0000.7150.905
소재지 도로명주소1.0001.0001.0001.0001.0001.000
소재지연락번호1.0001.0001.0001.0001.0001.000
위도0.4250.7151.0001.0001.0000.690
경도0.4300.9051.0001.0000.6901.000
2024-03-13T09:14:01.226586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.1750.038
위도0.1751.0000.461
경도0.0380.4611.000

Missing values

2024-03-13T09:13:58.358598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:13:58.449967image/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

연번매장명소재지 도로명주소소재지연락번호위도경도데이터기준일자
01동원마트경상남도 김해시 가야로 58(삼계동) 313동 101호 (삼계동,동원로얄듀크상가)055-311-008935.269817128.8667772023-06-01
12이안할인마트경상남도 김해시 해반천로278번길 58(삼계동) 58<NA>35.275152128.8674452023-06-01
23한아름슈퍼경상남도 김해시 활천로57번길 6(삼정동) 6<NA>35.232762128.8926692023-06-01
34나들가게칠산점경상남도 김해시 칠산로413번길 16-7(화목동) 16-7055-326-009835.209312128.8513812023-06-01
45e그린마트경상남도 김해시 삼문로 90(삼문동) 제상가동 104호(삼문동,갑오마을부영그린타운1차)055-331-371135.191486128.808432023-06-01
56서원탑할인마트경상남도 김해시 삼안로111번길 10(안동) 한일아파트상가동101,102호055-331-009535.238568128.9154332023-06-01
67이화상회경상남도 김해시 칠산로425번길 22-8(흥동) 이화마트055-338-224635.2107128.8517182023-06-01
78어방할인마트경상남도 김해시 인제로169번길 16(어방동) 어방할인마트055-324-073035.244971128.9035042023-06-01
89가야할인마트경상남도 김해시 분성로261번길 22(봉황동) 1층055-334-377235.234394128.8747882023-06-01
91019차 마트경상남도 김해시 부곡로 12(부곡동) 상가동 1층 101호<NA>35.205587128.7974692023-06-01
연번매장명소재지 도로명주소소재지연락번호위도경도데이터기준일자
4041주공할인마트경상남도 김해시 가락로 222(구산동) 구산영구임대아파트 상가 102호055-338-381635.246612128.8768352023-06-01
4142대동슈퍼경상남도 김해시 함박로 101 대동주상가 122,123호<NA>35.232552128.8652023-06-01
4243한신마트경상남도 김해시 분성로 14 일동한신아파트 상가2동 105,106호055-311-886835.229165128.8489262023-06-01
4344주공마트경상남도 김해시 가락로294번길 16-1055-328-100135.250567128.8740942023-06-01
4445청안슈퍼경상남도 김해시 호계로 518-44055-333-678835.236509128.8856082023-06-01
4546w마트경상남도 김해시 평전로 190 24시마트055-327-858735.244345128.8642352023-06-01
4647한마음할인슈퍼경상남도 김해시 함박로 101055-324-790735.232552128.8652023-06-01
4748따봉슈퍼경상남도 김해시 평전로155번길 3-1055-336-562135.243073128.8604462023-06-01
4849대동상회경상남도 김해시 활천로285번길 8055-332-359735.243771128.9100772023-06-01
4950나들가게삼방점경상남도 김해시 삼안로297번길 12055-331-252235.250911128.9061142023-06-01