Overview

Dataset statistics

Number of variables7
Number of observations748
Missing cells35
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.5 KiB
Average record size in memory58.2 B

Variable types

Numeric2
Categorical1
DateTime1
Text3

Dataset

Description김해시 관내 읍면동의 유흥단란주점에 대한 업종명, 인허가일자, 업소명, 도로명주소, 지번주소, 면적, 전화번호 등의 자료를 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15124188

Alerts

번호 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 번호High correlation
소재지(지번) has 26 (3.5%) missing valuesMissing
영업장면적 has 8 (1.1%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:36:33.170309
Analysis finished2023-12-11 00:36:34.208399
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct748
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean374.5
Minimum1
Maximum748
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T09:36:34.267837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.35
Q1187.75
median374.5
Q3561.25
95-th percentile710.65
Maximum748
Range747
Interquartile range (IQR)373.5

Descriptive statistics

Standard deviation216.07329
Coefficient of variation (CV)0.57696473
Kurtosis-1.2
Mean374.5
Median Absolute Deviation (MAD)187
Skewness0
Sum280126
Variance46687.667
MonotonicityStrictly increasing
2023-12-11T09:36:34.382589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
504 1
 
0.1%
495 1
 
0.1%
496 1
 
0.1%
497 1
 
0.1%
498 1
 
0.1%
499 1
 
0.1%
500 1
 
0.1%
501 1
 
0.1%
502 1
 
0.1%
Other values (738) 738
98.7%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
748 1
0.1%
747 1
0.1%
746 1
0.1%
745 1
0.1%
744 1
0.1%
743 1
0.1%
742 1
0.1%
741 1
0.1%
740 1
0.1%
739 1
0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
유흥주점영업
652 
단란주점영업
96 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유흥주점영업 652
87.2%
단란주점영업 96
 
12.8%

Length

2023-12-11T09:36:34.495166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:34.591107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥주점영업 652
87.2%
단란주점영업 96
 
12.8%

인허가일자
Date

Distinct638
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum1968-01-19 00:00:00
Maximum2023-08-30 00:00:00
2023-12-11T09:36:34.680483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:34.793973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct690
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T09:36:34.989893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length6.0855615
Min length1

Characters and Unicode

Total characters4552
Distinct characters462
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

Unique641 ?
Unique (%)85.7%

Sample

1st row에덴(Eden)
2nd row전국노래자랑
3rd row강강노래주점
4th row바라조
5th row뉴케이
ValueCountFrequency (%)
노래주점 19
 
2.3%
노래타운 5
 
0.6%
귀빈노래주점 4
 
0.5%
황제노래주점 4
 
0.5%
팡팡노래주점 3
 
0.4%
월드노래주점 3
 
0.4%
코끼리 3
 
0.4%
친구노래주점 3
 
0.4%
가고파 3
 
0.4%
국빈노래주점 3
 
0.4%
Other values (709) 760
93.8%
2023-12-11T09:36:35.339765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 406
 
8.9%
점 406
 
8.9%
노 385
 
8.5%
래 384
 
8.4%
이 103
 
2.3%
라 76
 
1.7%
스 64
 
1.4%
63
 
1.4%
타 59
 
1.3%
란 47
 
1.0%
Other values (452) 2559
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4164
91.5%
Uppercase Letter 124
 
2.7%
Decimal Number 108
 
2.4%
Space Separator 63
 
1.4%
Open Punctuation 32
 
0.7%
Close Punctuation 32
 
0.7%
Lowercase Letter 24
 
0.5%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 406
 
9.8%
점 406
 
9.8%
노 385
 
9.2%
래 384
 
9.2%
이 103
 
2.5%
라 76
 
1.8%
스 64
 
1.5%
타 59
 
1.4%
란 47
 
1.1%
단 46
 
1.1%
Other values (401) 2188
52.5%
Uppercase Letter
ValueCountFrequency (%)
I 12
 
9.7%
A 11
 
8.9%
M 11
 
8.9%
E 9
 
7.3%
V 9
 
7.3%
B 9
 
7.3%
N 6
 
4.8%
P 6
 
4.8%
L 5
 
4.0%
T 5
 
4.0%
Other values (13) 41
33.1%
Lowercase Letter
ValueCountFrequency (%)
o 5
20.8%
a 3
12.5%
s 3
12.5%
n 3
12.5%
l 2
 
8.3%
i 2
 
8.3%
e 2
 
8.3%
m 1
 
4.2%
d 1
 
4.2%
v 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
0 36
33.3%
8 20
18.5%
7 19
17.6%
2 10
 
9.3%
1 10
 
9.3%
3 5
 
4.6%
9 3
 
2.8%
4 2
 
1.9%
6 2
 
1.9%
5 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
/ 1
20.0%
? 1
20.0%
& 1
20.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4164
91.5%
Common 240
 
5.3%
Latin 148
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 406
 
9.8%
점 406
 
9.8%
노 385
 
9.2%
래 384
 
9.2%
이 103
 
2.5%
라 76
 
1.8%
스 64
 
1.5%
타 59
 
1.4%
란 47
 
1.1%
단 46
 
1.1%
Other values (401) 2188
52.5%
Latin
ValueCountFrequency (%)
I 12
 
8.1%
A 11
 
7.4%
M 11
 
7.4%
E 9
 
6.1%
V 9
 
6.1%
B 9
 
6.1%
N 6
 
4.1%
P 6
 
4.1%
L 5
 
3.4%
T 5
 
3.4%
Other values (24) 65
43.9%
Common
ValueCountFrequency (%)
63
26.2%
0 36
15.0%
( 32
13.3%
) 32
13.3%
8 20
 
8.3%
7 19
 
7.9%
2 10
 
4.2%
1 10
 
4.2%
3 5
 
2.1%
9 3
 
1.2%
Other values (7) 10
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4164
91.5%
ASCII 388
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 406
 
9.8%
점 406
 
9.8%
노 385
 
9.2%
래 384
 
9.2%
이 103
 
2.5%
라 76
 
1.8%
스 64
 
1.5%
타 59
 
1.4%
란 47
 
1.1%
단 46
 
1.1%
Other values (401) 2188
52.5%
ASCII
ValueCountFrequency (%)
63
16.2%
0 36
 
9.3%
( 32
 
8.2%
) 32
 
8.2%
8 20
 
5.2%
7 19
 
4.9%
I 12
 
3.1%
A 11
 
2.8%
M 11
 
2.8%
2 10
 
2.6%
Other values (41) 142
36.6%

소재지(도로명)
Text

Distinct718
Distinct (%)96.1%
Missing1
Missing (%)0.1%
Memory size6.0 KiB
2023-12-11T09:36:35.661352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length31.1834
Min length16

Characters and Unicode

Total characters23294
Distinct characters193
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

Unique692 ?
Unique (%)92.6%

Sample

1st row경상남도 김해시 내외중앙로 48, 리치빌딩 3층 302호 (외동)
2nd row경상남도 김해시 진영읍 김해대로361번길 2, 진영그랜드프라자 2층 203호
3rd row경상남도 김해시 분성로318번길 17, 2층 (부원동)
4th row경상남도 김해시 삼문로 5, 아모르빌딩 (대청동)
5th row경상남도 김해시 해반천로144번길 35-26, 4층 401호 (삼계동)
ValueCountFrequency (%)
경상남도 747
 
16.9%
김해시 747
 
16.9%
부원동 95
 
2.2%
내외중앙로 83
 
1.9%
진영읍 80
 
1.8%
어방동 68
 
1.5%
대청동 66
 
1.5%
외동 55
 
1.2%
2층 54
 
1.2%
해반천로144번길 46
 
1.0%
Other values (618) 2368
53.7%
2023-12-11T09:36:36.113268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3662
 
15.7%
해 869
 
3.7%
1 850
 
3.6%
김 822
 
3.5%
상 792
 
3.4%
시 760
 
3.3%
남 758
 
3.3%
로 756
 
3.2%
경 748
 
3.2%
도 747
 
3.2%
Other values (183) 12530
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13100
56.2%
Decimal Number 4308
 
18.5%
Space Separator 3662
 
15.7%
Open Punctuation 707
 
3.0%
Close Punctuation 707
 
3.0%
Other Punctuation 650
 
2.8%
Dash Punctuation 124
 
0.5%
Uppercase Letter 36
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 869
 
6.6%
김 822
 
6.3%
상 792
 
6.0%
시 760
 
5.8%
남 758
 
5.8%
로 756
 
5.8%
경 748
 
5.7%
도 747
 
5.7%
동 601
 
4.6%
번 552
 
4.2%
Other values (162) 5695
43.5%
Decimal Number
ValueCountFrequency (%)
1 850
19.7%
2 624
14.5%
0 577
13.4%
3 542
12.6%
5 444
10.3%
4 374
8.7%
6 326
 
7.6%
7 253
 
5.9%
9 167
 
3.9%
8 151
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 14
38.9%
N 10
27.8%
C 10
27.8%
Y 1
 
2.8%
A 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 644
99.1%
/ 6
 
0.9%
Space Separator
ValueCountFrequency (%)
3662
100.0%
Open Punctuation
ValueCountFrequency (%)
( 707
100.0%
Close Punctuation
ValueCountFrequency (%)
) 707
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13100
56.2%
Common 10158
43.6%
Latin 36
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 869
 
6.6%
김 822
 
6.3%
상 792
 
6.0%
시 760
 
5.8%
남 758
 
5.8%
로 756
 
5.8%
경 748
 
5.7%
도 747
 
5.7%
동 601
 
4.6%
번 552
 
4.2%
Other values (162) 5695
43.5%
Common
ValueCountFrequency (%)
3662
36.1%
1 850
 
8.4%
( 707
 
7.0%
) 707
 
7.0%
, 644
 
6.3%
2 624
 
6.1%
0 577
 
5.7%
3 542
 
5.3%
5 444
 
4.4%
4 374
 
3.7%
Other values (6) 1027
 
10.1%
Latin
ValueCountFrequency (%)
B 14
38.9%
N 10
27.8%
C 10
27.8%
Y 1
 
2.8%
A 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13100
56.2%
ASCII 10194
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3662
35.9%
1 850
 
8.3%
( 707
 
6.9%
) 707
 
6.9%
, 644
 
6.3%
2 624
 
6.1%
0 577
 
5.7%
3 542
 
5.3%
5 444
 
4.4%
4 374
 
3.7%
Other values (11) 1063
 
10.4%
Hangul
ValueCountFrequency (%)
해 869
 
6.6%
김 822
 
6.3%
상 792
 
6.0%
시 760
 
5.8%
남 758
 
5.8%
로 756
 
5.8%
경 748
 
5.7%
도 747
 
5.7%
동 601
 
4.6%
번 552
 
4.2%
Other values (162) 5695
43.5%

소재지(지번)
Text

MISSING 

Distinct665
Distinct (%)92.1%
Missing26
Missing (%)3.5%
Memory size6.0 KiB
2023-12-11T09:36:36.415639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length25.588643
Min length17

Characters and Unicode

Total characters18475
Distinct characters174
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique619 ?
Unique (%)85.7%

Sample

1st row경상남도 김해시 외동 1256-2 리치빌딩 3층 302호
2nd row경상남도 김해시 진영읍 진영리 1614-9
3rd row경상남도 김해시 부원동 833-22 2층
4th row경상남도 김해시 대청동 301-3 아모르빌딩 401호
5th row경상남도 김해시 삼계동 1461-6 4층 401호
ValueCountFrequency (%)
경상남도 722
20.0%
김해시 722
20.0%
대청동 130
 
3.6%
부원동 99
 
2.7%
삼계동 98
 
2.7%
어방동 84
 
2.3%
진영읍 79
 
2.2%
외동 73
 
2.0%
진영리 46
 
1.3%
내동 45
 
1.2%
Other values (657) 1508
41.8%
2023-12-11T09:36:36.849929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3464
18.7%
1 975
 
5.3%
상 758
 
4.1%
남 734
 
4.0%
시 731
 
4.0%
경 723
 
3.9%
해 723
 
3.9%
도 722
 
3.9%
김 722
 
3.9%
- 717
 
3.9%
Other values (164) 8206
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9964
53.9%
Decimal Number 4230
22.9%
Space Separator 3464
 
18.7%
Dash Punctuation 717
 
3.9%
Uppercase Letter 31
 
0.2%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%
Other Punctuation 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 758
 
7.6%
남 734
 
7.4%
시 731
 
7.3%
경 723
 
7.3%
해 723
 
7.3%
도 722
 
7.2%
김 722
 
7.2%
동 651
 
6.5%
지 422
 
4.2%
번 397
 
4.0%
Other values (144) 3381
33.9%
Decimal Number
ValueCountFrequency (%)
1 975
23.0%
0 520
12.3%
2 506
12.0%
5 385
 
9.1%
6 384
 
9.1%
4 379
 
9.0%
3 377
 
8.9%
7 258
 
6.1%
8 246
 
5.8%
9 200
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 12
38.7%
N 9
29.0%
C 9
29.0%
A 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 18
78.3%
/ 5
 
21.7%
Space Separator
ValueCountFrequency (%)
3464
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 717
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9964
53.9%
Common 8480
45.9%
Latin 31
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 758
 
7.6%
남 734
 
7.4%
시 731
 
7.3%
경 723
 
7.3%
해 723
 
7.3%
도 722
 
7.2%
김 722
 
7.2%
동 651
 
6.5%
지 422
 
4.2%
번 397
 
4.0%
Other values (144) 3381
33.9%
Common
ValueCountFrequency (%)
3464
40.8%
1 975
 
11.5%
- 717
 
8.5%
0 520
 
6.1%
2 506
 
6.0%
5 385
 
4.5%
6 384
 
4.5%
4 379
 
4.5%
3 377
 
4.4%
7 258
 
3.0%
Other values (6) 515
 
6.1%
Latin
ValueCountFrequency (%)
B 12
38.7%
N 9
29.0%
C 9
29.0%
A 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9963
53.9%
ASCII 8511
46.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3464
40.7%
1 975
 
11.5%
- 717
 
8.4%
0 520
 
6.1%
2 506
 
5.9%
5 385
 
4.5%
6 384
 
4.5%
4 379
 
4.5%
3 377
 
4.4%
7 258
 
3.0%
Other values (10) 546
 
6.4%
Hangul
ValueCountFrequency (%)
상 758
 
7.6%
남 734
 
7.4%
시 731
 
7.3%
경 723
 
7.3%
해 723
 
7.3%
도 722
 
7.2%
김 722
 
7.2%
동 651
 
6.5%
지 422
 
4.2%
번 397
 
4.0%
Other values (143) 3380
33.9%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%

영업장면적
Real number (ℝ)

MISSING 

Distinct676
Distinct (%)91.4%
Missing8
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean129.77091
Minimum0
Maximum1224.91
Zeros2
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T09:36:36.973979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile65.4395
Q196.79
median118.43
Q3130.9525
95-th percentile243.2955
Maximum1224.91
Range1224.91
Interquartile range (IQR)34.1625

Descriptive statistics

Standard deviation85.078228
Coefficient of variation (CV)0.65560325
Kurtosis58.915863
Mean129.77091
Median Absolute Deviation (MAD)17.05
Skewness6.2519717
Sum96030.47
Variance7238.3048
MonotonicityNot monotonic
2023-12-11T09:36:37.095545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120.69 5
 
0.7%
125.24 4
 
0.5%
123.52 4
 
0.5%
105.0 4
 
0.5%
131.89 3
 
0.4%
112.78 3
 
0.4%
128.1 3
 
0.4%
130.77 3
 
0.4%
114.81 3
 
0.4%
123.45 2
 
0.3%
Other values (666) 706
94.4%
(Missing) 8
 
1.1%
ValueCountFrequency (%)
0.0 2
0.3%
12.16 1
0.1%
13.53 1
0.1%
14.52 2
0.3%
17.34 1
0.1%
19.5 1
0.1%
22.4 1
0.1%
23.29 1
0.1%
33.34 1
0.1%
38.38 1
0.1%
ValueCountFrequency (%)
1224.91 1
0.1%
900.55 1
0.1%
849.0 1
0.1%
740.86 1
0.1%
632.0 1
0.1%
560.37 1
0.1%
518.22 1
0.1%
454.09 1
0.1%
419.19 1
0.1%
401.64 1
0.1%

Interactions

2023-12-11T09:36:33.816214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:33.632353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:33.900759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:33.723414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:36:37.168721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명영업장면적
번호1.0000.9880.173
업종명0.9881.0000.087
영업장면적0.1730.0871.000
2023-12-11T09:36:37.243494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호영업장면적업종명
번호1.000-0.2560.899
영업장면적-0.2561.0000.087
업종명0.8990.0871.000

Missing values

2023-12-11T09:36:33.995388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:36:34.083917image/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.
2023-12-11T09:36:34.162024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적
01유흥주점영업2023-08-30에덴(Eden)경상남도 김해시 내외중앙로 48, 리치빌딩 3층 302호 (외동)경상남도 김해시 외동 1256-2 리치빌딩 3층 302호154.58
12유흥주점영업2023-07-27전국노래자랑경상남도 김해시 진영읍 김해대로361번길 2, 진영그랜드프라자 2층 203호경상남도 김해시 진영읍 진영리 1614-9123.52
23유흥주점영업2023-05-30강강노래주점경상남도 김해시 분성로318번길 17, 2층 (부원동)경상남도 김해시 부원동 833-22 2층107.75
34유흥주점영업2023-04-06바라조경상남도 김해시 삼문로 5, 아모르빌딩 (대청동)경상남도 김해시 대청동 301-3 아모르빌딩 401호115.91
45유흥주점영업2023-01-25뉴케이경상남도 김해시 해반천로144번길 35-26, 4층 401호 (삼계동)경상남도 김해시 삼계동 1461-6 4층 401호95.84
56유흥주점영업2023-01-18서영노래방경상남도 김해시 장유로301번길 7, 2층 (무계동)경상남도 김해시 무계동 191-11159.5
67유흥주점영업2022-12-20빙고뮤직타운경상남도 김해시 능동로149번길 8, 일진프라자 304호 (부곡동)경상남도 김해시 부곡동 1161-3 일진프라자 304호125.91
78유흥주점영업2022-11-17애플노래방경상남도 김해시 번화1로 73, 르네상스빌딩 301호 (대청동)경상남도 김해시 대청동 56-7 르네상스빌딩 301호132.2
89유흥주점영업2022-11-10그래이스(GRACE)경상남도 김해시 가락로23번길 8, 1층 (부원동)경상남도 김해시 부원동 602-16 1층160.72
910유흥주점영업2022-07-25룰루랄라 퓨전노래방경상남도 김해시 율하6로 61, 성호루브루 801호 (장유동)경상남도 김해시 장유동 839-1 성호루브루 801호193.1
번호업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적
738739단란주점영업1995-06-02하루방단란주점경상남도 김해시 가락로63번길 2 (부원동)경상남도 김해시 부원동 833-1746.04
739740단란주점영업1994-09-16풍차단란주점경상남도 김해시 한림면 한림로 363경상남도 김해시 한림면 311-9번지<NA>
740741단란주점영업1994-09-09허심청경상남도 김해시 호계로422번길 14 (부원동)경상남도 김해시 부원동 620-4번지146.62
741742단란주점영업1994-08-13월드컵단란주점경상남도 김해시 진영읍 진영로 211경상남도 김해시 진영읍 여래리 711-11번지<NA>
742743단란주점영업1994-05-02비목경상남도 김해시 가락로23번길 11 (부원동)경상남도 김해시 부원동 603-9번지90.09
743744단란주점영업1994-05-02동양단란주점경상남도 김해시 평전로 27 (외동)경상남도 김해시 외동 706-1번지110.46
744745단란주점영업1994-03-07두돌단란주점경상남도 김해시 가락로50번길 8 (부원동)경상남도 김해시 부원동 841-3번지<NA>
745746단란주점영업1994-02-04금바다단란주점경상남도 김해시 가락로50번길 14 (부원동)경상남도 김해시 부원동 760-7번지150.06
746747단란주점영업1993-09-28특급단란주점경상남도 김해시 분성로336번길 32-1 (부원동)경상남도 김해시 부원동 848-1번지90.88
747748단란주점영업1993-09-01사람과세상경상남도 김해시 삼안로195번길 29 (삼방동)경상남도 김해시 삼방동 184-2번지<NA>