Overview

Dataset statistics

Number of variables13
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory111.7 B

Variable types

Numeric2
Text4
Categorical6
Boolean1

Dataset

Description부산광역시해운대구_호텔업현황_20220808
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075749

Alerts

서비스대상구분 has constant value ""Constant
외국어안내서비스 has constant value ""Constant
주차장보유여부 has constant value ""Constant
결제방법 has constant value ""Constant
업종명 is highly imbalanced (67.6%)Imbalance
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique
연락처 has unique valuesUnique
객실수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:31:16.177915
Analysis finished2023-12-10 16:31:17.786496
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T01:31:17.883252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-11T01:31:18.029703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

업소명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:31:18.286863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.4347826
Min length4

Characters and Unicode

Total characters194
Distinct characters75
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row웨스틴조선 부산
2nd row파라다이스호텔 부산
3rd row파크하얏트부산
4th row리베로호텔
5th row(주)호텔일루아
ValueCountFrequency (%)
부산 5
 
12.2%
해운대 5
 
12.2%
호텔 2
 
4.9%
앰배서더 2
 
4.9%
이비스 2
 
4.9%
호텔라온 1
 
2.4%
해운대호텔 1
 
2.4%
브라운도트호텔 1
 
2.4%
웨스틴조선 1
 
2.4%
1
 
2.4%
Other values (20) 20
48.8%
2023-12-11T01:31:18.729264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
9.8%
15
 
7.7%
15
 
7.7%
8
 
4.1%
8
 
4.1%
7
 
3.6%
6
 
3.1%
6
 
3.1%
6
 
3.1%
6
 
3.1%
Other values (65) 98
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
88.7%
Space Separator 19
 
9.8%
Letter Number 1
 
0.5%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
8.7%
15
 
8.7%
8
 
4.7%
8
 
4.7%
7
 
4.1%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
5
 
2.9%
Other values (61) 90
52.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
88.7%
Common 21
 
10.8%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
8.7%
15
 
8.7%
8
 
4.7%
8
 
4.7%
7
 
4.1%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
5
 
2.9%
Other values (61) 90
52.3%
Common
ValueCountFrequency (%)
19
90.5%
( 1
 
4.8%
) 1
 
4.8%
Latin
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
88.7%
ASCII 21
 
10.8%
Number Forms 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
90.5%
( 1
 
4.8%
) 1
 
4.8%
Hangul
ValueCountFrequency (%)
15
 
8.7%
15
 
8.7%
8
 
4.7%
8
 
4.7%
7
 
4.1%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
5
 
2.9%
Other values (61) 90
52.3%
Number Forms
ValueCountFrequency (%)
1
100.0%

업종명
Categorical

IMBALANCE 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
관광호텔
21 
가족호텔
 
1
소규모호텔
 
1

Length

Max length5
Median length4
Mean length4.0434783
Min length4

Unique

Unique2 ?
Unique (%)8.7%

Sample

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

Common Values

ValueCountFrequency (%)
관광호텔 21
91.3%
가족호텔 1
 
4.3%
소규모호텔 1
 
4.3%

Length

2023-12-11T01:31:18.914710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:19.049493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광호텔 21
91.3%
가족호텔 1
 
4.3%
소규모호텔 1
 
4.3%

서비스대상구분
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
관광객
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광객 23
100.0%

Length

2023-12-11T01:31:19.172690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:19.285829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광객 23
100.0%

외국어안내서비스
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
가능
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가능 23
100.0%

Length

2023-12-11T01:31:19.400624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:19.509296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가능 23
100.0%

소재지
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:31:19.696525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length22.869565
Min length17

Characters and Unicode

Total characters526
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row부산광역시 해운대구 동백로 67(중동)
2nd row부산광역시 해운대구 해운대해변로 296(중동)
3rd row부산광역시 해운대구 마린시티1로 51
4th row부산광역시 해운대구 구남로 29번길 21
5th row부산광역시 해운대구 달맞이길 97
ValueCountFrequency (%)
부산광역시 23
24.0%
해운대구 22
22.9%
해운대해변로 5
 
5.2%
송정광어골로 4
 
4.2%
구남로 3
 
3.1%
달맞이길 3
 
3.1%
해운대해변로237번길 2
 
2.1%
8-17(송정동 1
 
1.0%
해운대로570번길46 1
 
1.0%
달맞이길62번길 1
 
1.0%
Other values (31) 31
32.3%
2023-12-11T01:31:20.081315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
13.9%
40
 
7.6%
31
 
5.9%
31
 
5.9%
27
 
5.1%
25
 
4.8%
24
 
4.6%
23
 
4.4%
23
 
4.4%
23
 
4.4%
Other values (31) 206
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
68.1%
Decimal Number 74
 
14.1%
Space Separator 73
 
13.9%
Open Punctuation 10
 
1.9%
Close Punctuation 10
 
1.9%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
40
11.2%
31
 
8.7%
31
 
8.7%
27
 
7.5%
25
 
7.0%
24
 
6.7%
23
 
6.4%
23
 
6.4%
23
 
6.4%
19
 
5.3%
Other values (17) 92
25.7%
Decimal Number
ValueCountFrequency (%)
2 15
20.3%
3 10
13.5%
1 10
13.5%
9 9
12.2%
7 8
10.8%
0 7
9.5%
6 5
 
6.8%
8 4
 
5.4%
5 3
 
4.1%
4 3
 
4.1%
Space Separator
ValueCountFrequency (%)
73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 358
68.1%
Common 168
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
40
11.2%
31
 
8.7%
31
 
8.7%
27
 
7.5%
25
 
7.0%
24
 
6.7%
23
 
6.4%
23
 
6.4%
23
 
6.4%
19
 
5.3%
Other values (17) 92
25.7%
Common
ValueCountFrequency (%)
73
43.5%
2 15
 
8.9%
3 10
 
6.0%
( 10
 
6.0%
1 10
 
6.0%
) 10
 
6.0%
9 9
 
5.4%
7 8
 
4.8%
0 7
 
4.2%
6 5
 
3.0%
Other values (4) 11
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
68.1%
ASCII 168
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
43.5%
2 15
 
8.9%
3 10
 
6.0%
( 10
 
6.0%
1 10
 
6.0%
) 10
 
6.0%
9 9
 
5.4%
7 8
 
4.8%
0 7
 
4.2%
6 5
 
3.0%
Other values (4) 11
 
6.5%
Hangul
ValueCountFrequency (%)
40
11.2%
31
 
8.7%
31
 
8.7%
27
 
7.5%
25
 
7.0%
24
 
6.7%
23
 
6.4%
23
 
6.4%
23
 
6.4%
19
 
5.3%
Other values (17) 92
25.7%

연락처
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:31:20.298554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters276
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

Unique23 ?
Unique (%)100.0%

Sample

1st row051-749-7000
2nd row051-742-2121
3rd row051-990-1234
4th row051-740-2111
5th row051-744-1331
ValueCountFrequency (%)
051-749-7000 1
 
4.3%
051-630-1100 1
 
4.3%
051-702-1928 1
 
4.3%
051-742-9309 1
 
4.3%
051-760-9001 1
 
4.3%
051-922-5000 1
 
4.3%
051-922-1000 1
 
4.3%
051-742-0021 1
 
4.3%
051-714-0003 1
 
4.3%
051-702-0090 1
 
4.3%
Other values (13) 13
56.5%
2023-12-11T01:31:20.955985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76
27.5%
1 51
18.5%
- 46
16.7%
5 26
 
9.4%
7 18
 
6.5%
2 15
 
5.4%
9 14
 
5.1%
4 13
 
4.7%
6 8
 
2.9%
3 7
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.3%
Dash Punctuation 46
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 76
33.0%
1 51
22.2%
5 26
 
11.3%
7 18
 
7.8%
2 15
 
6.5%
9 14
 
6.1%
4 13
 
5.7%
6 8
 
3.5%
3 7
 
3.0%
8 2
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 76
27.5%
1 51
18.5%
- 46
16.7%
5 26
 
9.4%
7 18
 
6.5%
2 15
 
5.4%
9 14
 
5.1%
4 13
 
4.7%
6 8
 
2.9%
3 7
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 76
27.5%
1 51
18.5%
- 46
16.7%
5 26
 
9.4%
7 18
 
6.5%
2 15
 
5.4%
9 14
 
5.1%
4 13
 
4.7%
6 8
 
2.9%
3 7
 
2.5%

객실수
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.78261
Minimum28
Maximum528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T01:31:21.087675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile32.5
Q149
median127
Q3264.5
95-th percentile499.7
Maximum528
Range500
Interquartile range (IQR)215.5

Descriptive statistics

Standard deviation154.23004
Coefficient of variation (CV)0.88748834
Kurtosis0.25847256
Mean173.78261
Median Absolute Deviation (MAD)89
Skewness1.0951606
Sum3997
Variance23786.905
MonotonicityNot monotonic
2023-12-11T01:31:21.222719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
290 1
 
4.3%
528 1
 
4.3%
28 1
 
4.3%
37 1
 
4.3%
50 1
 
4.3%
132 1
 
4.3%
330 1
 
4.3%
260 1
 
4.3%
32 1
 
4.3%
67 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
28 1
4.3%
32 1
4.3%
37 1
4.3%
38 1
4.3%
42 1
4.3%
48 1
4.3%
50 1
4.3%
57 1
4.3%
67 1
4.3%
80 1
4.3%
ValueCountFrequency (%)
528 1
4.3%
510 1
4.3%
407 1
4.3%
330 1
4.3%
290 1
4.3%
269 1
4.3%
260 1
4.3%
237 1
4.3%
181 1
4.3%
156 1
4.3%

부대시설
Categorical

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
레스토랑 등
사우나 등
카페 등
레스토랑, 연회, 웨딩 등
레스토랑, 연회, 온천 등
Other values (6)

Length

Max length14
Median length12
Mean length7.3043478
Min length4

Unique

Unique8 ?
Unique (%)34.8%

Sample

1st row레스토랑, 연회, 웨딩 등
2nd row레스토랑, 연회, 온천 등
3rd row레스토랑, 수영장 등
4th row레스토랑, 연회장 등
5th row레스토랑, 라운지바 등

Common Values

ValueCountFrequency (%)
레스토랑 등 9
39.1%
사우나 등 4
17.4%
카페 등 2
 
8.7%
레스토랑, 연회, 웨딩 등 1
 
4.3%
레스토랑, 연회, 온천 등 1
 
4.3%
레스토랑, 수영장 등 1
 
4.3%
레스토랑, 연회장 등 1
 
4.3%
레스토랑, 라운지바 등 1
 
4.3%
사우나 연회장 등 1
 
4.3%
레스토랑 연회장 등 1
 
4.3%

Length

2023-12-11T01:31:21.380732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23
41.8%
레스토랑 15
27.3%
사우나 5
 
9.1%
연회장 3
 
5.5%
카페 2
 
3.6%
연회 2
 
3.6%
웨딩 1
 
1.8%
온천 1
 
1.8%
수영장 1
 
1.8%
라운지바 1
 
1.8%

주차장보유여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size155.0 B
True
23 
ValueCountFrequency (%)
True 23
100.0%
2023-12-11T01:31:21.505014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

결제방법
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
현금+카드
23 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row현금+카드
2nd row현금+카드
3rd row현금+카드
4th row현금+카드
5th row현금+카드

Common Values

ValueCountFrequency (%)
현금+카드 23
100.0%

Length

2023-12-11T01:31:21.628896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:21.751113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
현금+카드 23
100.0%
Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:31:22.099785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length34
Mean length29
Min length2

Characters and Unicode

Total characters667
Distinct characters31
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)87.0%

Sample

1st rowhttps://www.josunhotel.com/hotel/westinBusan.do
2nd rowhttps://www.busanparadisehotel.co.kr/main.do
3rd rowhttps://busan.park.hyatt.com/ko/hotel/home.html
4th rowhttp://www.liberohotel.co.kr/
5th rowhttps://hotelillua.com/
ValueCountFrequency (%)
없음 3
 
13.0%
https://www.josunhotel.com/hotel/westinbusan.do 1
 
4.3%
http://www.toyoko-inn.kr 1
 
4.3%
http://www.haesurak.com 1
 
4.3%
http://www.centralhotel.kr 1
 
4.3%
https://gjb.josunhotel.com/main.do 1
 
4.3%
https://www.lottehotel.com/busan-signiel/ko.html 1
 
4.3%
http://busan-laon.com 1
 
4.3%
https://sjbrowndt.modoo.at 1
 
4.3%
https://www.shillastay.com/haeundae/index.do 1
 
4.3%
Other values (11) 11
47.8%
2023-12-11T01:31:22.668279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 70
 
10.5%
/ 68
 
10.2%
o 55
 
8.2%
. 48
 
7.2%
h 44
 
6.6%
w 44
 
6.6%
e 34
 
5.1%
a 34
 
5.1%
l 30
 
4.5%
s 26
 
3.9%
Other values (21) 214
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 518
77.7%
Other Punctuation 136
 
20.4%
Other Letter 6
 
0.9%
Dash Punctuation 3
 
0.4%
Decimal Number 2
 
0.3%
Connector Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 70
13.5%
o 55
10.6%
h 44
 
8.5%
w 44
 
8.5%
e 34
 
6.6%
a 34
 
6.6%
l 30
 
5.8%
s 26
 
5.0%
n 26
 
5.0%
m 26
 
5.0%
Other values (12) 129
24.9%
Other Punctuation
ValueCountFrequency (%)
/ 68
50.0%
. 48
35.3%
: 20
 
14.7%
Other Letter
ValueCountFrequency (%)
3
50.0%
3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Decimal Number
ValueCountFrequency (%)
0 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 519
77.8%
Common 142
 
21.3%
Hangul 6
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 70
13.5%
o 55
10.6%
h 44
 
8.5%
w 44
 
8.5%
e 34
 
6.6%
a 34
 
6.6%
l 30
 
5.8%
s 26
 
5.0%
n 26
 
5.0%
m 26
 
5.0%
Other values (13) 130
25.0%
Common
ValueCountFrequency (%)
/ 68
47.9%
. 48
33.8%
: 20
 
14.1%
- 3
 
2.1%
0 2
 
1.4%
_ 1
 
0.7%
Hangul
ValueCountFrequency (%)
3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 661
99.1%
Hangul 6
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 70
 
10.6%
/ 68
 
10.3%
o 55
 
8.3%
. 48
 
7.3%
h 44
 
6.7%
w 44
 
6.7%
e 34
 
5.1%
a 34
 
5.1%
l 30
 
4.5%
s 26
 
3.9%
Other values (19) 208
31.5%
Hangul
ValueCountFrequency (%)
3
50.0%
3
50.0%
Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
동백섬, 해운대해수욕장 등
13 
송정해수욕장, 구덕포 등
달맞이언덕, 해운대해수욕장 등
동백섬, 영화의 거리 등
 
1

Length

Max length16
Median length14
Mean length14.086957
Min length13

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row동백섬, 해운대해수욕장 등
2nd row동백섬, 해운대해수욕장 등
3rd row동백섬, 영화의 거리 등
4th row동백섬, 해운대해수욕장 등
5th row달맞이언덕, 해운대해수욕장 등

Common Values

ValueCountFrequency (%)
동백섬, 해운대해수욕장 등 13
56.5%
송정해수욕장, 구덕포 등 5
 
21.7%
달맞이언덕, 해운대해수욕장 등 4
 
17.4%
동백섬, 영화의 거리 등 1
 
4.3%

Length

2023-12-11T01:31:22.851876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:31:22.994508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
23
32.9%
해운대해수욕장 17
24.3%
동백섬 14
20.0%
송정해수욕장 5
 
7.1%
구덕포 5
 
7.1%
달맞이언덕 4
 
5.7%
영화의 1
 
1.4%
거리 1
 
1.4%

Interactions

2023-12-11T01:31:17.088596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:31:16.860463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:31:17.205086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:31:16.977537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:31:23.129725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명업종명소재지연락처객실수부대시설홈페이지주소주변관광정보
연번1.0001.0000.0001.0001.0000.1880.0000.8310.613
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.000
업종명0.0001.0001.0001.0001.0000.0000.7071.0000.269
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.000
객실수0.1881.0000.0001.0001.0001.0000.6200.8500.267
부대시설0.0001.0000.7071.0001.0000.6201.0000.9710.732
홈페이지주소0.8311.0001.0001.0001.0000.8500.9711.0000.861
주변관광정보0.6131.0000.2691.0001.0000.2670.7320.8611.000
2023-12-11T01:31:23.395184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명주변관광정보부대시설
업종명1.0000.2390.410
주변관광정보0.2391.0000.414
부대시설0.4100.4141.000
2023-12-11T01:31:23.551846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수업종명부대시설주변관광정보
연번1.000-0.3810.0000.0000.289
객실수-0.3811.0000.0000.2670.067
업종명0.0000.0001.0000.4100.239
부대시설0.0000.2670.4101.0000.414
주변관광정보0.2890.0670.2390.4141.000

Missing values

2023-12-11T01:31:17.389680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:31:17.681717image/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

연번업소명업종명서비스대상구분외국어안내서비스소재지연락처객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보
01웨스틴조선 부산관광호텔관광객가능부산광역시 해운대구 동백로 67(중동)051-749-7000290레스토랑, 연회, 웨딩 등Y현금+카드https://www.josunhotel.com/hotel/westinBusan.do동백섬, 해운대해수욕장 등
12파라다이스호텔 부산관광호텔관광객가능부산광역시 해운대구 해운대해변로 296(중동)051-742-2121528레스토랑, 연회, 온천 등Y현금+카드https://www.busanparadisehotel.co.kr/main.do동백섬, 해운대해수욕장 등
23파크하얏트부산관광호텔관광객가능부산광역시 해운대구 마린시티1로 51051-990-1234269레스토랑, 수영장 등Y현금+카드https://busan.park.hyatt.com/ko/hotel/home.html동백섬, 영화의 거리 등
34리베로호텔관광호텔관광객가능부산광역시 해운대구 구남로 29번길 21051-740-211191레스토랑, 연회장 등Y현금+카드http://www.liberohotel.co.kr/동백섬, 해운대해수욕장 등
45(주)호텔일루아관광호텔관광객가능부산광역시 해운대구 달맞이길 97051-744-133157레스토랑, 라운지바 등Y현금+카드https://hotelillua.com/달맞이언덕, 해운대해수욕장 등
56제이비디자인호텔관광호텔관광객가능부산광역시 해운대구 구남로 12번길 31051-750-900080레스토랑 등Y현금+카드http://www.jbdesignhotel.com/html/00_main/동백섬, 해운대해수욕장 등
67플레르 호텔관광호텔관광객가능부산광역시 해운대구 송정광어골로 70051-701-760148레스토랑 등Y현금+카드https://plaire.modoo.at/송정해수욕장, 구덕포 등
78베니키아 해운대 호텔마리안느관광호텔관광객가능부산광역시 해운대구 해운대해변로 310051-606-0600127레스토랑 등Y현금+카드http://www.mariannehotel.net동백섬, 해운대해수욕장 등
89이비스 버젯 앰배서더 해운대관광호텔관광객가능부산광역시 해운대구 해운대해변로 209번길 8051-901-1100181레스토랑 등Y현금+카드없음동백섬, 해운대해수욕장 등
910올라호텔관광호텔관광객가능부산광역시 해운대구 송정광어골로 49051-704-000142레스토랑 등Y현금+카드http://www.ollahotel.com/송정해수욕장, 구덕포 등
연번업소명업종명서비스대상구분외국어안내서비스소재지연락처객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보
1314신라스테이 해운대호텔관광호텔관광객가능부산광역시 해운대로570번길46051-911-9181407레스토랑 연회장 등Y현금+카드https://www.shillastay.com/haeundae/index.do동백섬, 해운대해수욕장 등
1415브라운도트호텔관광호텔관광객가능부산광역시 해운대구 송정광어골로 30(송정동)051-702-009038카페 등Y현금+카드https://sjbrowndt.modoo.at/송정해수욕장, 구덕포 등
1516호텔라온관광호텔관광객가능부산광역시 해운대구 송정광어골로 39 (송정동)051-714-000367레스토랑 등Y현금+카드http://busan-laon.com/송정해수욕장, 구덕포 등
1617선트리 호텔관광호텔관광객가능부산광역시 해운대구 달맞이길 209 (중동)051-742-002132카페 등Y현금+카드없음달맞이언덕, 해운대해수욕장 등
1718시그니엘 부산관광호텔관광객가능부산광역시 해운대구 달맞이길 30(중동)051-922-1000260사우나 등Y현금+카드https://www.lottehotel.com/busan-signiel/ko.html달맞이언덕, 해운대해수욕장 등
1819그랜드조선 부산관광호텔관광객가능부산광역시 해운대구 해운대해변로 292(중동)051-922-5000330사우나 등Y현금+카드https://gjb.josunhotel.com/main.do동백섬, 해운대해수욕장 등
1920해운대센트럴호텔관광호텔관광객가능부산광역시 해운대구 해운대해변로298번길 33(중동)051-760-9001132레스토랑 등Y현금+카드http://www.centralhotel.kr/동백섬, 해운대해수욕장 등
2021인더스트리호텔관광호텔관광객가능부산광역시 해운대구 구남로 24번길 16051-742-930950레스토랑 등Y현금+카드없음동백섬, 해운대해수욕장 등
2122송정해수락가족호텔관광객가능부산광역시 해운대구 송정해변로 8-17(송정동)051-702-192837사우나 등Y현금+카드http://www.haesurak.com/송정해수욕장, 구덕포 등
2223미포오션사이드호텔소규모호텔관광객가능부산광역시 해운대구 달맞이길62번길 28(중동)051-601-430028음식점 등Y현금+카드http://www.mipohotel.com/달맞이언덕, 해운대해수욕장 등