Overview

Dataset statistics

Number of variables10
Number of observations33
Missing cells22
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory86.0 B

Variable types

Numeric2
Categorical1
Text6
DateTime1

Alerts

연번 is highly overall correlated with 구분High correlation
객실수 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
홈페이지 has 10 (30.3%) missing valuesMissing
부대시설 has 12 (36.4%) missing valuesMissing
연번 has unique valuesUnique
시 설 명 has unique valuesUnique
소 재 지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:31:17.495488
Analysis finished2024-03-14 01:31:18.506426
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-14T10:31:18.583789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2024-03-14T10:31:18.691901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
굿스테이
26 
관광호텔
7 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
굿스테이 26
78.8%
관광호텔 7
 
21.2%

Length

2024-03-14T10:31:18.796898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:31:18.878866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
굿스테이 26
78.8%
관광호텔 7
 
21.2%

시 설 명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:31:19.046194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length6.1818182
Min length3

Characters and Unicode

Total characters204
Distinct characters84
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

Unique33 ?
Unique (%)100.0%

Sample

1st row전주호텔한성
2nd row화이트관광호텔
3rd row궁관광호텔
4th row풍남관광호텔
5th row전주관광호텔
ValueCountFrequency (%)
전주호텔한성 1
 
2.6%
무주이리스모텔 1
 
2.6%
지리산칸호텔(구 1
 
2.6%
지리산파크텔 1
 
2.6%
남원 1
 
2.6%
한일파크 1
 
2.6%
남원호텔 1
 
2.6%
마이산콘도빌(구 1
 
2.6%
마이산모텔 1
 
2.6%
장수온천호텔 1
 
2.6%
Other values (28) 28
73.7%
2024-03-14T10:31:19.340869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 29
 
14.2%
호 19
 
9.3%
스 8
 
3.9%
모 8
 
3.9%
리 7
 
3.4%
산 6
 
2.9%
관 6
 
2.9%
이 5
 
2.5%
광 5
 
2.5%
5
 
2.5%
Other values (74) 106
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
95.1%
Space Separator 5
 
2.5%
Open Punctuation 2
 
1.0%
Close Punctuation 2
 
1.0%
Uppercase Letter 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 29
 
14.9%
호 19
 
9.8%
스 8
 
4.1%
모 8
 
4.1%
리 7
 
3.6%
산 6
 
3.1%
관 6
 
3.1%
이 5
 
2.6%
광 5
 
2.6%
주 4
 
2.1%
Other values (70) 97
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
95.1%
Common 9
 
4.4%
Latin 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 29
 
14.9%
호 19
 
9.8%
스 8
 
4.1%
모 8
 
4.1%
리 7
 
3.6%
산 6
 
3.1%
관 6
 
3.1%
이 5
 
2.6%
광 5
 
2.6%
주 4
 
2.1%
Other values (70) 97
50.0%
Common
ValueCountFrequency (%)
5
55.6%
( 2
 
22.2%
) 2
 
22.2%
Latin
ValueCountFrequency (%)
S 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 194
95.1%
ASCII 10
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 29
 
14.9%
호 19
 
9.8%
스 8
 
4.1%
모 8
 
4.1%
리 7
 
3.6%
산 6
 
3.1%
관 6
 
3.1%
이 5
 
2.6%
광 5
 
2.6%
주 4
 
2.1%
Other values (70) 97
50.0%
ASCII
ValueCountFrequency (%)
5
50.0%
( 2
 
20.0%
) 2
 
20.0%
S 1
 
10.0%

소 재 지
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:31:19.556380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length15.151515
Min length10

Characters and Unicode

Total characters500
Distinct characters80
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

Unique33 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 전주객사5길 44-5
2nd row전주시 덕진구 전주천동로 501
3rd row전주시 덕진구 용산1길 17-4
4th row전주시 완산구 객사2길 45-7
5th row전주시 완산구 객사5길 44-5
ValueCountFrequency (%)
전주시 11
 
8.9%
덕진구 8
 
6.5%
남원시 5
 
4.0%
군산시 5
 
4.0%
산정2길 3
 
2.4%
부안군 3
 
2.4%
완산구 3
 
2.4%
진안군 2
 
1.6%
33 2
 
1.6%
변산면 2
 
1.6%
Other values (73) 80
64.5%
2024-03-14T10:31:19.869697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
18.2%
1 29
 
5.8%
시 24
 
4.8%
산 21
 
4.2%
2 20
 
4.0%
길 17
 
3.4%
주 16
 
3.2%
- 15
 
3.0%
군 14
 
2.8%
로 14
 
2.8%
Other values (70) 239
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
57.0%
Decimal Number 109
 
21.8%
Space Separator 91
 
18.2%
Dash Punctuation 15
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 24
 
8.4%
산 21
 
7.4%
길 17
 
6.0%
주 16
 
5.6%
군 14
 
4.9%
로 14
 
4.9%
진 13
 
4.6%
전 13
 
4.6%
구 11
 
3.9%
정 9
 
3.2%
Other values (58) 133
46.7%
Decimal Number
ValueCountFrequency (%)
1 29
26.6%
2 20
18.3%
3 12
11.0%
4 11
 
10.1%
5 9
 
8.3%
7 9
 
8.3%
6 7
 
6.4%
9 5
 
4.6%
8 4
 
3.7%
0 3
 
2.8%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
57.0%
Common 215
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 24
 
8.4%
산 21
 
7.4%
길 17
 
6.0%
주 16
 
5.6%
군 14
 
4.9%
로 14
 
4.9%
진 13
 
4.6%
전 13
 
4.6%
구 11
 
3.9%
정 9
 
3.2%
Other values (58) 133
46.7%
Common
ValueCountFrequency (%)
91
42.3%
1 29
 
13.5%
2 20
 
9.3%
- 15
 
7.0%
3 12
 
5.6%
4 11
 
5.1%
5 9
 
4.2%
7 9
 
4.2%
6 7
 
3.3%
9 5
 
2.3%
Other values (2) 7
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
57.0%
ASCII 215
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
42.3%
1 29
 
13.5%
2 20
 
9.3%
- 15
 
7.0%
3 12
 
5.6%
4 11
 
5.1%
5 9
 
4.2%
7 9
 
4.2%
6 7
 
3.3%
9 5
 
2.3%
Other values (2) 7
 
3.3%
Hangul
ValueCountFrequency (%)
시 24
 
8.4%
산 21
 
7.4%
길 17
 
6.0%
주 16
 
5.6%
군 14
 
4.9%
로 14
 
4.9%
진 13
 
4.6%
전 13
 
4.6%
구 11
 
3.9%
정 9
 
3.2%
Other values (58) 133
46.7%

객실수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.575758
Minimum30
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2024-03-14T10:31:19.961831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile30
Q132
median33
Q336
95-th percentile48.8
Maximum63
Range33
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.141561
Coefficient of variation (CV)0.20074235
Kurtosis6.1717489
Mean35.575758
Median Absolute Deviation (MAD)3
Skewness2.3121316
Sum1174
Variance51.001894
MonotonicityNot monotonic
2024-03-14T10:31:20.053989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
32 7
21.2%
30 6
18.2%
33 4
12.1%
40 3
9.1%
36 3
9.1%
35 2
 
6.1%
31 2
 
6.1%
63 1
 
3.0%
46 1
 
3.0%
48 1
 
3.0%
Other values (3) 3
9.1%
ValueCountFrequency (%)
30 6
18.2%
31 2
 
6.1%
32 7
21.2%
33 4
12.1%
34 1
 
3.0%
35 2
 
6.1%
36 3
9.1%
37 1
 
3.0%
40 3
9.1%
46 1
 
3.0%
ValueCountFrequency (%)
63 1
 
3.0%
50 1
 
3.0%
48 1
 
3.0%
46 1
 
3.0%
40 3
9.1%
37 1
 
3.0%
36 3
9.1%
35 2
6.1%
34 1
 
3.0%
33 4
12.1%

전화번호
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:31:20.285885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters396
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

Unique33 ?
Unique (%)100.0%

Sample

1st row063-288-0014
2nd row063-271-0123
3rd row063-255-3311
4th row063-231-7900
5th row063-280-7700
ValueCountFrequency (%)
063-288-0014 1
 
3.0%
063-538-9487 1
 
3.0%
063-631-2536 1
 
3.0%
063-452-3388 1
 
3.0%
063-433-6776 1
 
3.0%
063-584-9931 1
 
3.0%
063-583-8046 1
 
3.0%
063-653-3960 1
 
3.0%
063-653-6060 1
 
3.0%
063-353-5555 1
 
3.0%
Other values (23) 23
69.7%
2024-03-14T10:31:20.593206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 66
16.7%
- 66
16.7%
0 59
14.9%
6 54
13.6%
2 28
7.1%
4 28
7.1%
5 27
6.8%
1 21
 
5.3%
8 18
 
4.5%
7 17
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
83.3%
Dash Punctuation 66
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 66
20.0%
0 59
17.9%
6 54
16.4%
2 28
8.5%
4 28
8.5%
5 27
8.2%
1 21
 
6.4%
8 18
 
5.5%
7 17
 
5.2%
9 12
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 66
16.7%
- 66
16.7%
0 59
14.9%
6 54
13.6%
2 28
7.1%
4 28
7.1%
5 27
6.8%
1 21
 
5.3%
8 18
 
4.5%
7 17
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 66
16.7%
- 66
16.7%
0 59
14.9%
6 54
13.6%
2 28
7.1%
4 28
7.1%
5 27
6.8%
1 21
 
5.3%
8 18
 
4.5%
7 17
 
4.3%

홈페이지
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing10
Missing (%)30.3%
Memory size396.0 B
2024-03-14T10:31:20.779815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length17.826087
Min length8

Characters and Unicode

Total characters410
Distinct characters37
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

Unique23 ?
Unique (%)100.0%

Sample

1st rowhansunghotel.alltheway.kr
2nd rowwhitehotel.kr
3rd rowwww.jjgung.co.kr
4th rowwww.pungnamhotel.com
5th rowjeonjuhotel.co.kr
ValueCountFrequency (%)
hansunghotel.alltheway.kr 1
 
4.3%
www.western-inn.kr 1
 
4.3%
whitehotel.kr 1
 
4.3%
www.jangsuhotel.com 1
 
4.3%
마이산펜션.kr 1
 
4.3%
www.namwonhotel.com 1
 
4.3%
www.jirisankhanhotel.com 1
 
4.3%
www.내장산펜션.kr 1
 
4.3%
www.wgspa.co.kr 1
 
4.3%
blog.naver.com/newgrand1 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T10:31:21.081305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 57
13.9%
. 51
12.4%
o 34
 
8.3%
r 25
 
6.1%
e 24
 
5.9%
l 24
 
5.9%
n 23
 
5.6%
c 19
 
4.6%
a 18
 
4.4%
t 18
 
4.4%
Other values (27) 117
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 342
83.4%
Other Punctuation 52
 
12.7%
Other Letter 10
 
2.4%
Decimal Number 4
 
1.0%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 57
16.7%
o 34
9.9%
r 25
 
7.3%
e 24
 
7.0%
l 24
 
7.0%
n 23
 
6.7%
c 19
 
5.6%
a 18
 
5.3%
t 18
 
5.3%
h 17
 
5.0%
Other values (13) 83
24.3%
Other Letter
ValueCountFrequency (%)
산 2
20.0%
션 2
20.0%
펜 2
20.0%
이 1
10.0%
마 1
10.0%
장 1
10.0%
내 1
10.0%
Decimal Number
ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
1 1
25.0%
3 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 51
98.1%
/ 1
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 342
83.4%
Common 58
 
14.1%
Hangul 10
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 57
16.7%
o 34
9.9%
r 25
 
7.3%
e 24
 
7.0%
l 24
 
7.0%
n 23
 
6.7%
c 19
 
5.6%
a 18
 
5.3%
t 18
 
5.3%
h 17
 
5.0%
Other values (13) 83
24.3%
Common
ValueCountFrequency (%)
. 51
87.9%
- 2
 
3.4%
6 1
 
1.7%
0 1
 
1.7%
1 1
 
1.7%
/ 1
 
1.7%
3 1
 
1.7%
Hangul
ValueCountFrequency (%)
산 2
20.0%
션 2
20.0%
펜 2
20.0%
이 1
10.0%
마 1
10.0%
장 1
10.0%
내 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 400
97.6%
Hangul 10
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 57
14.2%
. 51
12.8%
o 34
 
8.5%
r 25
 
6.2%
e 24
 
6.0%
l 24
 
6.0%
n 23
 
5.8%
c 19
 
4.8%
a 18
 
4.5%
t 18
 
4.5%
Other values (20) 107
26.8%
Hangul
ValueCountFrequency (%)
산 2
20.0%
션 2
20.0%
펜 2
20.0%
이 1
10.0%
마 1
10.0%
장 1
10.0%
내 1
10.0%

부대시설
Text

MISSING 

Distinct17
Distinct (%)81.0%
Missing12
Missing (%)36.4%
Memory size396.0 B
2024-03-14T10:31:21.256188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length10.47619
Min length4

Characters and Unicode

Total characters220
Distinct characters66
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)66.7%

Sample

1st row세미나실, 조식식당
2nd row세미나룸, 브랙퍼스트바
3rd row세미나룸, 비즈니스룸, 한식당
4th row연회장, 커피숍, 인터넷센터
5th row웨딩홀, 연회장, 건식사우나실
ValueCountFrequency (%)
세미나실 5
 
11.4%
식음료장 4
 
9.1%
휴게실 2
 
4.5%
사우나실 2
 
4.5%
비즈니스실 2
 
4.5%
세미나룸 2
 
4.5%
한식당 2
 
4.5%
연회장 2
 
4.5%
비즈니스센터 2
 
4.5%
노래방 1
 
2.3%
Other values (20) 20
45.5%
2024-03-14T10:31:21.524916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
10.5%
, 23
 
10.5%
실 16
 
7.3%
나 11
 
5.0%
식 10
 
4.5%
장 10
 
4.5%
미 7
 
3.2%
세 7
 
3.2%
스 6
 
2.7%
당 5
 
2.3%
Other values (56) 102
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 174
79.1%
Space Separator 23
 
10.5%
Other Punctuation 23
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 16
 
9.2%
나 11
 
6.3%
식 10
 
5.7%
장 10
 
5.7%
미 7
 
4.0%
세 7
 
4.0%
스 6
 
3.4%
당 5
 
2.9%
사 5
 
2.9%
니 5
 
2.9%
Other values (54) 92
52.9%
Space Separator
ValueCountFrequency (%)
23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
79.1%
Common 46
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 16
 
9.2%
나 11
 
6.3%
식 10
 
5.7%
장 10
 
5.7%
미 7
 
4.0%
세 7
 
4.0%
스 6
 
3.4%
당 5
 
2.9%
사 5
 
2.9%
니 5
 
2.9%
Other values (54) 92
52.9%
Common
ValueCountFrequency (%)
23
50.0%
, 23
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 174
79.1%
ASCII 46
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
50.0%
, 23
50.0%
Hangul
ValueCountFrequency (%)
실 16
 
9.2%
나 11
 
6.3%
식 10
 
5.7%
장 10
 
5.7%
미 7
 
4.0%
세 7
 
4.0%
스 6
 
3.4%
당 5
 
2.9%
사 5
 
2.9%
니 5
 
2.9%
Other values (54) 92
52.9%

주변관광지
Text

Distinct25
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2024-03-14T10:31:21.735213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length18.424242
Min length9

Characters and Unicode

Total characters608
Distinct characters130
Distinct categories3 ?
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 (%)57.6%

Sample

1st row전주객사, 영화의 거리, 한옥마을
2nd row전주한옥마을, 덕진공원
3rd row전주한옥마을, 덕진공원
4th row전주한옥마을, 전주객사, 영화의 거리
5th row전주하옥마을, 전동성당, 남부시장
ValueCountFrequency (%)
전주한옥마을 9
 
8.7%
전주덕진공원 6
 
5.8%
군산근대역사박물관 4
 
3.9%
광한루 4
 
3.9%
춘향테마파크 3
 
2.9%
내소사 3
 
2.9%
새만금방조제 3
 
2.9%
무주 2
 
1.9%
진안홍삼 2
 
1.9%
동물원 2
 
1.9%
Other values (52) 65
63.1%
2024-03-14T10:31:22.029186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
 
11.7%
, 58
 
9.5%
마 23
 
3.8%
주 22
 
3.6%
전 22
 
3.6%
산 18
 
3.0%
원 17
 
2.8%
사 15
 
2.5%
을 14
 
2.3%
한 14
 
2.3%
Other values (120) 334
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 479
78.8%
Space Separator 71
 
11.7%
Other Punctuation 58
 
9.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 23
 
4.8%
주 22
 
4.6%
전 22
 
4.6%
산 18
 
3.8%
원 17
 
3.5%
사 15
 
3.1%
을 14
 
2.9%
한 14
 
2.9%
옥 12
 
2.5%
진 12
 
2.5%
Other values (118) 310
64.7%
Space Separator
ValueCountFrequency (%)
71
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 479
78.8%
Common 129
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 23
 
4.8%
주 22
 
4.6%
전 22
 
4.6%
산 18
 
3.8%
원 17
 
3.5%
사 15
 
3.1%
을 14
 
2.9%
한 14
 
2.9%
옥 12
 
2.5%
진 12
 
2.5%
Other values (118) 310
64.7%
Common
ValueCountFrequency (%)
71
55.0%
, 58
45.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 479
78.8%
ASCII 129
 
21.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
55.0%
, 58
45.0%
Hangul
ValueCountFrequency (%)
마 23
 
4.8%
주 22
 
4.6%
전 22
 
4.6%
산 18
 
3.8%
원 17
 
3.5%
사 15
 
3.1%
을 14
 
2.9%
한 14
 
2.9%
옥 12
 
2.5%
진 12
 
2.5%
Other values (118) 310
64.7%

데이터기준일
Date

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
Minimum2015-08-30 00:00:00
Maximum2016-07-29 00:00:00
2024-03-14T10:31:22.113047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:31:22.185060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Interactions

2024-03-14T10:31:18.061447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:31:17.851973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:31:18.150976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:31:17.938400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:31:22.254956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시 설 명소 재 지객실수전화번호홈페이지부대시설주변관광지데이터기준일
연번1.0001.0001.0001.0000.1721.0001.0000.2250.9131.000
구분1.0001.0001.0001.0000.7391.0001.0001.0000.5440.000
시 설 명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소 재 지1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
객실수0.1720.7391.0001.0001.0001.0001.0000.9140.9670.394
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지1.0001.0001.0001.0001.0001.0001.0001.0001.000NaN
부대시설0.2251.0001.0001.0000.9141.0001.0001.0000.767NaN
주변관광지0.9130.5441.0001.0000.9671.0001.0000.7671.0000.630
데이터기준일1.0000.0001.0001.0000.3941.000NaNNaN0.6301.000
2024-03-14T10:31:22.398647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수구분
연번1.000-0.3390.861
객실수-0.3391.0000.505
구분0.8610.5051.000

Missing values

2024-03-14T10:31:18.254381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:31:18.367878image/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.
2024-03-14T10:31:18.456008image/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

연번구분시 설 명소 재 지객실수전화번호홈페이지부대시설주변관광지데이터기준일
01관광호텔전주호텔한성전주시 완산구 전주객사5길 44-540063-288-0014hansunghotel.alltheway.kr세미나실, 조식식당전주객사, 영화의 거리, 한옥마을2015.08.30
12관광호텔화이트관광호텔전주시 덕진구 전주천동로 50135063-271-0123whitehotel.kr세미나룸, 브랙퍼스트바전주한옥마을, 덕진공원2015.08.30
23관광호텔궁관광호텔전주시 덕진구 용산1길 17-430063-255-3311www.jjgung.co.kr세미나룸, 비즈니스룸, 한식당전주한옥마을, 덕진공원2015.08.30
34관광호텔풍남관광호텔전주시 완산구 객사2길 45-763063-231-7900www.pungnamhotel.com연회장, 커피숍, 인터넷센터전주한옥마을, 전주객사, 영화의 거리2015.08.30
45관광호텔전주관광호텔전주시 완산구 객사5길 44-546063-280-7700jeonjuhotel.co.kr웨딩홀, 연회장, 건식사우나실전주하옥마을, 전동성당, 남부시장2015.08.30
56관광호텔해뜨는언덕 관광호텔군산시 부곡3길 640063-468-0707www.fmotel.co.kr비즈니스실, 휴게실군산근대역사박물관, 새만금방조제2015.08.30
67관광호텔채석강스타힐스 호텔부안군 변산면 채석강길 3335063-581-9911www.starhillshotel.com마사지실, 식음료장, 바베큐장, 노래연습장채석강, 내소사, 부안영상테마파크2015.08.30
78굿스테이라뉘호텔전주시 덕진구 송천중앙로 12-432063-253-5707www.lanuit.co.kr<NA>전주덕진공원, 전주한옥마을2015.08.30
89굿스테이르시엘호텔전주시 덕진구 산정2길 2332063-245-4848www.lecielhotel.co.kr<NA>전주한옥마을, 전주덕진공원2015.08.30
910굿스테이아리랑호텔전주시 덕진구 용산2길 17-632063-273-4193www.jj-arirang.co.kr세미나실, 비즈니스실전주덕진공원, 전주한옥마을, 동물원2015.08.30
연번구분시 설 명소 재 지객실수전화번호홈페이지부대시설주변관광지데이터기준일
2324굿스테이무주이리스모텔무주군 무주읍 한풍루로 381-750063-324-3400<NA><NA>무주 반딧불 축제, 무주 전통공예테마파크,2015.08.30
2425굿스테이장수온천호텔장수군 번암면 장수로 673-1430063-353-5555www.jangsuhotel.com식당, 사우나, 다목적실덕유산국립공원, 방화동자연휴양림, 장안산2015.08.30
2526굿스테이영빈호텔순창군 순창읍 순창로 22236063-653-6060<NA><NA>강천산, 회문산, 고추장 민속마을, 섬진강향가유원지2015.08.30
2627굿스테이S모텔순창군 순창읍 옥천로 3330063-653-3960<NA>비즈니스센터강천산, 회문산, 고추장 민속마을, 섬진강향가유원지2015.08.30
2728굿스테이채석리조텔오크빌부안군 변산면 격포로 19630063-583-8046www.csr063.co.kr식음료장내소사, 개암사, 낙조대, 직소폭포, 변산해수욕장2015.08.30
2829굿스테이샤르모텔부안군 부안읍 석정로 199-433063-584-9931<NA><NA>채석강, 내소사, 부안영상테마파크2015.08.30
2930굿스테이진안장여관진안군 진안읍 진무로 1100-631063-433-6776<NA><NA>마이산, 진안홍삼, 운일암 반일암, 풍혈냉천2016.07.29
3031굿스테이파라다이스모텔군산시 조촌1길 2137063-452-3388<NA><NA>경암동 철길마을, 근대역사박물관, 동국사 등2016.07.29
3132굿스테이로망스모텔남원시 옥정5길 12-832063-631-2536<NA><NA>춘향테마파크, 광한루2016.07.29
3233굿스테이발리모텔남원시 향교동 17730063-625-7801<NA><NA>춘향테마파크, 광한루2016.07.29