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 memory85.9 B

Variable types

Numeric2
Categorical2
Text6

Dataset

Description전북특별자치도 중저가 숙박시설(시설명, 위치, 객실수 등)전북특별자치도 중저가 숙박시설의 객실 개수, 전북특별자치도 중저가 숙박시설의 홈페이지, 전북특별자치도 중저가 숙박시설 데이터를 작성한 날짜 등
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081281/fileData.do

Alerts

연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
객실수 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
데이터기준일 is highly overall correlated with 연번High 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 08:39:29.818956
Analysis finished2024-03-14 08:39:32.281827
Duration2.46 seconds
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 size425.0 B
2024-03-14T17:39:32.392827image/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
2024-03-14T17:39:32.615679image/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 size392.0 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

2024-03-14T17:39:32.858220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:39:33.076949image/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 size392.0 B
2024-03-14T17:39:33.833912image/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%
2024-03-14T17:39:34.939731image/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 size392.0 B
2024-03-14T17:39:35.919245image/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%
2024-03-14T17:39:37.315277image/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 size425.0 B
2024-03-14T17:39:37.518823image/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
2024-03-14T17:39:37.759545image/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 size392.0 B
2024-03-14T17:39:38.605476image/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%
2024-03-14T17:39:39.603322image/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 size392.0 B
2024-03-14T17:39:40.301415image/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%
2024-03-14T17:39:41.611830image/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 size392.0 B
2024-03-14T17:39:42.257335image/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%
2024-03-14T17:39:43.403660image/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 size392.0 B
2024-03-14T17:39:44.270476image/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%
2024-03-14T17:39:45.404934image/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
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size392.0 B
2015-08-30
29 
2016-07-29
4 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-08-30
2nd row2015-08-30
3rd row2015-08-30
4th row2015-08-30
5th row2015-08-30

Common Values

ValueCountFrequency (%)
2015-08-30 29
87.9%
2016-07-29 4
 
12.1%

Length

2024-03-14T17:39:45.839545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:39:46.070638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-08-30 29
87.9%
2016-07-29 4
 
12.1%

Interactions

2024-03-14T17:39:30.990564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:39:30.491502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:39:31.235857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:39:30.742185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:39:46.197668image/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
2024-03-14T17:39:46.414978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분데이터기준일
구분1.0000.000
데이터기준일0.0001.000
2024-03-14T17:39:46.553322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실수구분데이터기준일
연번1.000-0.3390.8610.861
객실수-0.3391.0000.5050.254
구분0.8610.5051.0000.000
데이터기준일0.8610.2540.0001.000

Missing values

2024-03-14T17:39:31.587708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:39:32.019739image/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.
2024-03-14T17:39:32.201515image/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