Overview

Dataset statistics

Number of variables9
Number of observations21
Missing cells22
Missing cells (%)11.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory81.3 B

Variable types

Categorical3
Text3
Unsupported1
Numeric2

Dataset

Description김해시 관광객이용 시설업 현황(영업상태명, 소재지전화, 지번주소, 도로명주소, 사업장명 등)에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033377/fileData.do

Alerts

영업상태명 has constant value ""Constant
개방서비스명 is highly overall correlated with 문화체육업종명High correlation
문화체육업종명 is highly overall correlated with 개방서비스명High correlation
도로명주소 has 1 (4.8%) missing valuesMissing
Unnamed: 6 has 21 (100.0%) missing valuesMissing
사업장명 has unique valuesUnique
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 04:28:20.193980
Analysis finished2023-12-12 04:28:21.709967
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방서비스명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
외국인관광 도시민박업
7 
자동차야영장업
5 
일반야영장업
4 
한옥체험업
3 
전문휴양업
2 

Length

Max length11
Median length7
Mean length7.6666667
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전문휴양업
2nd row전문휴양업
3rd row일반야영장업
4th row일반야영장업
5th row일반야영장업

Common Values

ValueCountFrequency (%)
외국인관광 도시민박업 7
33.3%
자동차야영장업 5
23.8%
일반야영장업 4
19.0%
한옥체험업 3
14.3%
전문휴양업 2
 
9.5%

Length

2023-12-12T13:28:21.828369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:28:21.959501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인관광 7
25.0%
도시민박업 7
25.0%
자동차야영장업 5
17.9%
일반야영장업 4
14.3%
한옥체험업 3
10.7%
전문휴양업 2
 
7.1%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업/정상
21 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 21
100.0%

Length

2023-12-12T13:28:22.085871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:28:22.182725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 21
100.0%

지번주소
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T13:28:22.392056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length25
Mean length22.666667
Min length16

Characters and Unicode

Total characters476
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

Unique19 ?
Unique (%)90.5%

Sample

1st row경상남도 김해시 유하동 88
2nd row경상남도 김해시 대청동 산 63-2
3rd row경상남도 김해시 삼방동 826
4th row경상남도 김해시 상동면 묵방리 산 30-8
5th row경상남도 김해시 삼방동 1086-5
ValueCountFrequency (%)
경상남도 21
20.4%
김해시 21
20.4%
생림면 4
 
3.9%
삼방동 3
 
2.9%
봉황동 3
 
2.9%
121-3 2
 
1.9%
내동 2
 
1.9%
나전리 2
 
1.9%
한진사원아파트 2
 
1.9%
산 2
 
1.9%
Other values (40) 41
39.8%
2023-12-12T13:28:22.856497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
20.8%
상 23
 
4.8%
1 23
 
4.8%
김 22
 
4.6%
해 22
 
4.6%
경 21
 
4.4%
남 21
 
4.4%
도 21
 
4.4%
시 21
 
4.4%
동 20
 
4.2%
Other values (49) 183
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
54.8%
Decimal Number 102
 
21.4%
Space Separator 99
 
20.8%
Dash Punctuation 14
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 23
 
8.8%
김 22
 
8.4%
해 22
 
8.4%
경 21
 
8.0%
남 21
 
8.0%
도 21
 
8.0%
시 21
 
8.0%
동 20
 
7.7%
면 7
 
2.7%
리 7
 
2.7%
Other values (37) 76
29.1%
Decimal Number
ValueCountFrequency (%)
1 23
22.5%
2 18
17.6%
0 13
12.7%
3 12
11.8%
8 10
9.8%
6 9
 
8.8%
5 8
 
7.8%
9 4
 
3.9%
7 4
 
3.9%
4 1
 
1.0%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
54.8%
Common 215
45.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 23
 
8.8%
김 22
 
8.4%
해 22
 
8.4%
경 21
 
8.0%
남 21
 
8.0%
도 21
 
8.0%
시 21
 
8.0%
동 20
 
7.7%
면 7
 
2.7%
리 7
 
2.7%
Other values (37) 76
29.1%
Common
ValueCountFrequency (%)
99
46.0%
1 23
 
10.7%
2 18
 
8.4%
- 14
 
6.5%
0 13
 
6.0%
3 12
 
5.6%
8 10
 
4.7%
6 9
 
4.2%
5 8
 
3.7%
9 4
 
1.9%
Other values (2) 5
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
54.8%
ASCII 215
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
46.0%
1 23
 
10.7%
2 18
 
8.4%
- 14
 
6.5%
0 13
 
6.0%
3 12
 
5.6%
8 10
 
4.7%
6 9
 
4.2%
5 8
 
3.7%
9 4
 
1.9%
Other values (2) 5
 
2.3%
Hangul
ValueCountFrequency (%)
상 23
 
8.8%
김 22
 
8.4%
해 22
 
8.4%
경 21
 
8.0%
남 21
 
8.0%
도 21
 
8.0%
시 21
 
8.0%
동 20
 
7.7%
면 7
 
2.7%
리 7
 
2.7%
Other values (37) 76
29.1%

도로명주소
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2023-12-12T13:28:23.143387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length29.75
Min length21

Characters and Unicode

Total characters595
Distinct characters83
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

Unique18 ?
Unique (%)90.0%

Sample

1st row경상남도 김해시 유하로226번길 70 (유하동)
2nd row경상남도 김해시 대청계곡길 170-36, 국립용지봉자연휴양림 (대청동)
3rd row경상남도 김해시 신어산길 67 (삼방동, 가야연수원)
4th row경상남도 김해시 상동면 장척로462번길 140
5th row경상남도 김해시 인제로 436 (삼방동)
ValueCountFrequency (%)
경상남도 20
 
17.2%
김해시 20
 
17.2%
인제로 3
 
2.6%
봉황동 3
 
2.6%
삼방동 3
 
2.6%
생림면 3
 
2.6%
한진사원아파트 2
 
1.7%
내동 2
 
1.7%
평전로 2
 
1.7%
219 2
 
1.7%
Other values (53) 56
48.3%
2023-12-12T13:28:23.672910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
16.1%
1 23
 
3.9%
상 22
 
3.7%
김 22
 
3.7%
해 22
 
3.7%
동 21
 
3.5%
도 20
 
3.4%
시 20
 
3.4%
남 20
 
3.4%
경 20
 
3.4%
Other values (73) 309
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
56.6%
Decimal Number 116
 
19.5%
Space Separator 96
 
16.1%
Open Punctuation 14
 
2.4%
Close Punctuation 14
 
2.4%
Other Punctuation 10
 
1.7%
Dash Punctuation 8
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 22
 
6.5%
김 22
 
6.5%
해 22
 
6.5%
동 21
 
6.2%
도 20
 
5.9%
시 20
 
5.9%
남 20
 
5.9%
경 20
 
5.9%
길 15
 
4.5%
로 14
 
4.2%
Other values (58) 141
41.8%
Decimal Number
ValueCountFrequency (%)
1 23
19.8%
2 19
16.4%
0 12
10.3%
9 10
8.6%
5 10
8.6%
6 10
8.6%
3 9
 
7.8%
4 8
 
6.9%
8 8
 
6.9%
7 7
 
6.0%
Space Separator
ValueCountFrequency (%)
96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
56.6%
Common 258
43.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 22
 
6.5%
김 22
 
6.5%
해 22
 
6.5%
동 21
 
6.2%
도 20
 
5.9%
시 20
 
5.9%
남 20
 
5.9%
경 20
 
5.9%
길 15
 
4.5%
로 14
 
4.2%
Other values (58) 141
41.8%
Common
ValueCountFrequency (%)
96
37.2%
1 23
 
8.9%
2 19
 
7.4%
( 14
 
5.4%
) 14
 
5.4%
0 12
 
4.7%
9 10
 
3.9%
, 10
 
3.9%
5 10
 
3.9%
6 10
 
3.9%
Other values (5) 40
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
56.6%
ASCII 258
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
37.2%
1 23
 
8.9%
2 19
 
7.4%
( 14
 
5.4%
) 14
 
5.4%
0 12
 
4.7%
9 10
 
3.9%
, 10
 
3.9%
5 10
 
3.9%
6 10
 
3.9%
Other values (5) 40
15.5%
Hangul
ValueCountFrequency (%)
상 22
 
6.5%
김 22
 
6.5%
해 22
 
6.5%
동 21
 
6.2%
도 20
 
5.9%
시 20
 
5.9%
남 20
 
5.9%
경 20
 
5.9%
길 15
 
4.5%
로 14
 
4.2%
Other values (58) 141
41.8%

사업장명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T13:28:23.927360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.4761905
Min length4

Characters and Unicode

Total characters178
Distinct characters92
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 (%)100.0%

Sample

1st row부경동물원
2nd row국립용지봉자연휴양림
3rd row(주)가야랜드달빛야영장
4th row(주)신어산 자연숲캠핑장
5th row캠핑가는 날
ValueCountFrequency (%)
부경동물원 1
 
3.0%
플라움 1
 
3.0%
무척산전통한옥 1
 
3.0%
김해한옥체험관 1
 
3.0%
집 1
 
3.0%
작은 1
 
3.0%
그리고 1
 
3.0%
달빛 1
 
3.0%
봉황 1
 
3.0%
머물다 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T13:28:24.327688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
6.7%
스 8
 
4.5%
장 6
 
3.4%
하 6
 
3.4%
우 5
 
2.8%
야 5
 
2.8%
( 4
 
2.2%
핑 4
 
2.2%
캠 4
 
2.2%
) 4
 
2.2%
Other values (82) 120
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
87.1%
Space Separator 12
 
6.7%
Open Punctuation 4
 
2.2%
Close Punctuation 4
 
2.2%
Other Punctuation 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 8
 
5.2%
장 6
 
3.9%
하 6
 
3.9%
우 5
 
3.2%
야 5
 
3.2%
핑 4
 
2.6%
캠 4
 
2.6%
주 4
 
2.6%
가 4
 
2.6%
리 4
 
2.6%
Other values (77) 105
67.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
87.1%
Common 23
 
12.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 8
 
5.2%
장 6
 
3.9%
하 6
 
3.9%
우 5
 
3.2%
야 5
 
3.2%
핑 4
 
2.6%
캠 4
 
2.6%
주 4
 
2.6%
가 4
 
2.6%
리 4
 
2.6%
Other values (77) 105
67.7%
Common
ValueCountFrequency (%)
12
52.2%
( 4
 
17.4%
) 4
 
17.4%
, 2
 
8.7%
. 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
87.1%
ASCII 23
 
12.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
52.2%
( 4
 
17.4%
) 4
 
17.4%
, 2
 
8.7%
. 1
 
4.3%
Hangul
ValueCountFrequency (%)
스 8
 
5.2%
장 6
 
3.9%
하 6
 
3.9%
우 5
 
3.2%
야 5
 
3.2%
핑 4
 
2.6%
캠 4
 
2.6%
주 4
 
2.6%
가 4
 
2.6%
리 4
 
2.6%
Other values (77) 105
67.7%

문화체육업종명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
외국인관광 도시민박업
7 
자동차야영장업
5 
일반야영장업
4 
한옥체험업
3 
전문휴양업
2 

Length

Max length11
Median length7
Mean length7.6666667
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전문휴양업
2nd row전문휴양업
3rd row일반야영장업
4th row일반야영장업
5th row일반야영장업

Common Values

ValueCountFrequency (%)
외국인관광 도시민박업 7
33.3%
자동차야영장업 5
23.8%
일반야영장업 4
19.0%
한옥체험업 3
14.3%
전문휴양업 2
 
9.5%

Length

2023-12-12T13:28:24.483914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:28:24.605911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인관광 7
25.0%
도시민박업 7
25.0%
자동차야영장업 5
17.9%
일반야영장업 4
14.3%
한옥체험업 3
10.7%
전문휴양업 2
 
7.1%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

위도
Real number (ℝ)

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.253233
Minimum35.178569
Maximum35.380669
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T13:28:24.749087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.178569
5-th percentile35.184726
Q135.230344
median35.246751
Q335.275349
95-th percentile35.365344
Maximum35.380669
Range0.20209975
Interquartile range (IQR)0.045005107

Descriptive statistics

Standard deviation0.049767057
Coefficient of variation (CV)0.0014117019
Kurtosis1.9916159
Mean35.253233
Median Absolute Deviation (MAD)0.020323649
Skewness1.0785907
Sum740.31789
Variance0.00247676
MonotonicityNot monotonic
2023-12-12T13:28:24.929548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
35.2467507095 2
 
9.5%
35.2589748934 2
 
9.5%
35.2203238005 1
 
4.8%
35.2378223238 1
 
4.8%
35.3806688735 1
 
4.8%
35.234362969 1
 
4.8%
35.2303442775 1
 
4.8%
35.2285758158 1
 
4.8%
35.23306757 1
 
4.8%
35.1785691278 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
35.1785691278 1
4.8%
35.1847261638 1
4.8%
35.1854027172 1
4.8%
35.2203238005 1
4.8%
35.2285758158 1
4.8%
35.2303442775 1
4.8%
35.23306757 1
4.8%
35.234362969 1
4.8%
35.2378223238 1
4.8%
35.2467507095 2
9.5%
ValueCountFrequency (%)
35.3806688735 1
4.8%
35.3653439073 1
4.8%
35.28016315 1
4.8%
35.2771489766 1
4.8%
35.2758617386 1
4.8%
35.2753493849 1
4.8%
35.2670743584 1
4.8%
35.2589748934 2
9.5%
35.2516350785 1
4.8%
35.2467507095 2
9.5%

경도
Real number (ℝ)

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.8685
Minimum128.77548
Maximum128.94294
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T13:28:25.084298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.77548
5-th percentile128.80978
Q1128.84169
median128.87688
Q3128.89375
95-th percentile128.92452
Maximum128.94294
Range0.16746561
Interquartile range (IQR)0.052058386

Descriptive statistics

Standard deviation0.040926807
Coefficient of variation (CV)0.00031758582
Kurtosis0.091649615
Mean128.8685
Median Absolute Deviation (MAD)0.024716294
Skewness-0.49086139
Sum2706.2385
Variance0.0016750036
MonotonicityNot monotonic
2023-12-12T13:28:25.235492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
128.8662122117 2
 
9.5%
128.9056119044 2
 
9.5%
128.8197957486 1
 
4.8%
128.942942512 1
 
4.8%
128.8416909976 1
 
4.8%
128.8766847482 1
 
4.8%
128.8793521371 1
 
4.8%
128.8768827885 1
 
4.8%
128.8810212 1
 
4.8%
128.8097844946 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
128.7754768984 1
4.8%
128.8097844946 1
4.8%
128.8120805578 1
4.8%
128.8197957486 1
4.8%
128.8382872 1
4.8%
128.8416909976 1
4.8%
128.8521664948 1
4.8%
128.8662122117 2
9.5%
128.8766847482 1
4.8%
128.8768827885 1
4.8%
ValueCountFrequency (%)
128.942942512 1
4.8%
128.9245240141 1
4.8%
128.9056119044 2
9.5%
128.8957681337 1
4.8%
128.8937493835 1
4.8%
128.8875371877 1
4.8%
128.8870727291 1
4.8%
128.8810212 1
4.8%
128.8793521371 1
4.8%
128.8768827885 1
4.8%

Interactions

2023-12-12T13:28:20.826121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:20.622221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:20.933944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:28:20.727848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:28:25.352665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개방서비스명지번주소도로명주소사업장명문화체육업종명위도경도
개방서비스명1.0000.9090.8401.0001.0000.4530.339
지번주소0.9091.0001.0001.0000.9091.0001.000
도로명주소0.8401.0001.0001.0000.8401.0001.000
사업장명1.0001.0001.0001.0001.0001.0001.000
문화체육업종명1.0000.9090.8401.0001.0000.4530.339
위도0.4531.0001.0001.0000.4531.0000.718
경도0.3391.0001.0001.0000.3390.7181.000
2023-12-12T13:28:25.452324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개방서비스명문화체육업종명
개방서비스명1.0001.000
문화체육업종명1.0001.000
2023-12-12T13:28:25.530768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도개방서비스명문화체육업종명
위도1.0000.2930.2960.296
경도0.2931.0000.2820.282
개방서비스명0.2960.2821.0001.000
문화체육업종명0.2960.2821.0001.000

Missing values

2023-12-12T13:28:21.463848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:28:21.627803image/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

개방서비스명영업상태명지번주소도로명주소사업장명문화체육업종명Unnamed: 6위도경도
0전문휴양업영업/정상경상남도 김해시 유하동 88경상남도 김해시 유하로226번길 70 (유하동)부경동물원전문휴양업<NA>35.220324128.819796
1전문휴양업영업/정상경상남도 김해시 대청동 산 63-2경상남도 김해시 대청계곡길 170-36, 국립용지봉자연휴양림 (대청동)국립용지봉자연휴양림전문휴양업<NA>35.185403128.775477
2일반야영장업영업/정상경상남도 김해시 삼방동 826경상남도 김해시 신어산길 67 (삼방동, 가야연수원)(주)가야랜드달빛야영장일반야영장업<NA>35.258975128.905612
3일반야영장업영업/정상경상남도 김해시 상동면 묵방리 산 30-8경상남도 김해시 상동면 장척로462번길 140(주)신어산 자연숲캠핑장일반야영장업<NA>35.277149128.924524
4일반야영장업영업/정상경상남도 김해시 삼방동 1086-5경상남도 김해시 인제로 436 (삼방동)캠핑가는 날일반야영장업<NA>35.267074128.895768
5일반야영장업영업/정상경상남도 김해시 생림면 나전리 30-5경상남도 김해시 생림면 인제로 545-61필립스가든일반야영장업<NA>35.275862128.887073
6자동차야영장업영업/정상경상남도 김해시 생림면 마사리 1322-6<NA>김해생림오토캠핑장자동차야영장업<NA>35.365344128.812081
7자동차야영장업영업/정상경상남도 김해시 어방동 993경상남도 김해시 가야테마길 161 (어방동)카라반 르 몽드자동차야영장업<NA>35.251635128.893749
8자동차야영장업영업/정상경상남도 김해시 생림면 나전리 30-6경상남도 김해시 생림면 인제로 545-59천문대오토캠핑장자동차야영장업<NA>35.275349128.887537
9자동차야영장업영업/정상경상남도 김해시 삼방동 826경상남도 김해시 신어산길 67 (삼방동, 가야연수원)(주)가야랜드 달빛야영장자동차야영장업<NA>35.258975128.905612
개방서비스명영업상태명지번주소도로명주소사업장명문화체육업종명Unnamed: 6위도경도
11외국인관광 도시민박업영업/정상경상남도 김해시 이동 155-8경상남도 김해시 칠산로210번길 128-6 (이동)곤지하우스외국인관광 도시민박업<NA>35.184726128.852166
12외국인관광 도시민박업영업/정상경상남도 김해시 내동 121-3 한진사원아파트 202동 1507호경상남도 김해시 평전로 219, 202동 15층 1507호 (내동, 한진사원아파트)벧엘하우스외국인관광 도시민박업<NA>35.246751128.866212
13외국인관광 도시민박업영업/정상경상남도 김해시 내동 121-3 한진사원아파트 201동 207호경상남도 김해시 평전로 219, 201동 2층 207호 (내동, 한진사원아파트)쑤하우스외국인관광 도시민박업<NA>35.246751128.866212
14외국인관광 도시민박업영업/정상경상남도 김해시 관동동 1169 힐스테이트김해아파트 106동 1201호경상남도 김해시 관동로27번길 39, 106동 12층 1201호 (관동동, 힐스테이트김해아파트)율하카페거리하우스외국인관광 도시민박업<NA>35.178569128.809784
15외국인관광 도시민박업영업/정상경상남도 김해시 서상동 152-36 1502호경상남도 김해시 분성로318번길 3, 1502호 (서상동)더리치하우스외국인관광 도시민박업<NA>35.233068128.881021
16외국인관광 도시민박업영업/정상경상남도 김해시 봉황동 118-20경상남도 김해시 봉황대길 29-1 (봉황동)느리게 머물다, 봉황외국인관광 도시민박업<NA>35.228576128.876883
17외국인관광 도시민박업영업/정상경상남도 김해시 봉황동 278-1경상남도 김해시 분성로288번길 41-13 (봉황동)달빛, 그리고 작은 집.외국인관광 도시민박업<NA>35.230344128.879352
18한옥체험업영업/정상경상남도 김해시 봉황동 425-13경상남도 김해시 가락로93번길 40 (봉황동)김해한옥체험관한옥체험업<NA>35.234363128.876685
19한옥체험업영업/정상경상남도 김해시 생림면 안양리 817경상남도 김해시 생림면 안양로358번길 38무척산전통한옥한옥체험업<NA>35.380669128.841691
20한옥체험업영업/정상경상남도 김해시 대동면 주중리 303경상남도 김해시 대동면 주중길 98-8정감한옥스테이한옥체험업<NA>35.237822128.942943