Overview

Dataset statistics

Number of variables14
Number of observations46
Missing cells63
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory114.9 B

Variable types

Unsupported3
Categorical5
Text6

Dataset

Description우수숙박시설굿스테이현황20167
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201455

Alerts

Unnamed: 12 has constant value ""Constant
Unnamed: 1 is highly overall correlated with Unnamed: 4 and 1 other fieldsHigh correlation
Unnamed: 3 is highly overall correlated with Unnamed: 4 and 1 other fieldsHigh correlation
Unnamed: 4 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 9 is highly overall correlated with Unnamed: 1 and 2 other fieldsHigh correlation
Unnamed: 10 is highly overall correlated with Unnamed: 4 and 1 other fieldsHigh correlation
Unnamed: 1 is highly imbalanced (81.0%)Imbalance
Unnamed: 3 is highly imbalanced (81.0%)Imbalance
Unnamed: 10 is highly imbalanced (81.0%)Imbalance
우수숙박시설(굿스테이) 현황(2016년 7월) has 1 (2.2%) missing valuesMissing
Unnamed: 2 has 1 (2.2%) missing valuesMissing
Unnamed: 5 has 1 (2.2%) missing valuesMissing
Unnamed: 6 has 1 (2.2%) missing valuesMissing
Unnamed: 7 has 1 (2.2%) missing valuesMissing
Unnamed: 8 has 1 (2.2%) missing valuesMissing
Unnamed: 11 has 11 (23.9%) missing valuesMissing
Unnamed: 12 has 45 (97.8%) missing valuesMissing
Unnamed: 13 has 1 (2.2%) missing valuesMissing
우수숙박시설(굿스테이) 현황(2016년 7월) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:43:42.512931
Analysis finished2024-03-14 00:43:43.508862
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

우수숙박시설(굿스테이) 현황(2016년 7월)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.2%
Memory size500.0 B

Unnamed: 1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
숙박업
44 
업종명
 
1
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0217391
Min length3

Unique

Unique2 ?
Unique (%)4.3%

Sample

1st row업종명
2nd row<NA>
3rd row숙박업
4th row숙박업
5th row숙박업

Common Values

ValueCountFrequency (%)
숙박업 44
95.7%
업종명 1
 
2.2%
<NA> 1
 
2.2%

Length

2024-03-14T09:43:43.558586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:43:43.641290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업 44
95.7%
업종명 1
 
2.2%
na 1
 
2.2%

Unnamed: 2
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T09:43:43.820058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.7555556
Min length3

Characters and Unicode

Total characters259
Distinct characters118
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

Unique45 ?
Unique (%)100.0%

Sample

1st row영업소명(공식상)
2nd row무주이리스모텔
3rd row세르빌호텔
4th row제일산장
5th row채석리조텔오크빌
ValueCountFrequency (%)
영업소명(공식상 1
 
1.9%
로베펜션 1
 
1.9%
그린토피아 1
 
1.9%
그린피아모텔 1
 
1.9%
샤르모텔 1
 
1.9%
s모텔(구 1
 
1.9%
금수장 1
 
1.9%
왕궁온천 1
 
1.9%
전주호텔(구 1
 
1.9%
아테네 1
 
1.9%
Other values (44) 44
81.5%
2024-03-14T09:43:44.113153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 28
 
10.8%
호 16
 
6.2%
모 11
 
4.2%
9
 
3.5%
스 8
 
3.1%
리 7
 
2.7%
산 6
 
2.3%
( 5
 
1.9%
아 5
 
1.9%
) 5
 
1.9%
Other values (108) 159
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 233
90.0%
Space Separator 9
 
3.5%
Open Punctuation 5
 
1.9%
Close Punctuation 5
 
1.9%
Decimal Number 3
 
1.2%
Uppercase Letter 3
 
1.2%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 28
 
12.0%
호 16
 
6.9%
모 11
 
4.7%
스 8
 
3.4%
리 7
 
3.0%
산 6
 
2.6%
아 5
 
2.1%
빌 4
 
1.7%
우 4
 
1.7%
크 3
 
1.3%
Other values (99) 141
60.5%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
W 1
33.3%
H 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
5 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 233
90.0%
Common 23
 
8.9%
Latin 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 28
 
12.0%
호 16
 
6.9%
모 11
 
4.7%
스 8
 
3.4%
리 7
 
3.0%
산 6
 
2.6%
아 5
 
2.1%
빌 4
 
1.7%
우 4
 
1.7%
크 3
 
1.3%
Other values (99) 141
60.5%
Common
ValueCountFrequency (%)
9
39.1%
( 5
21.7%
) 5
21.7%
1 2
 
8.7%
5 1
 
4.3%
~ 1
 
4.3%
Latin
ValueCountFrequency (%)
S 1
33.3%
W 1
33.3%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 233
90.0%
ASCII 26
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 28
 
12.0%
호 16
 
6.9%
모 11
 
4.7%
스 8
 
3.4%
리 7
 
3.0%
산 6
 
2.6%
아 5
 
2.1%
빌 4
 
1.7%
우 4
 
1.7%
크 3
 
1.3%
Other values (99) 141
60.5%
ASCII
ValueCountFrequency (%)
9
34.6%
( 5
19.2%
) 5
19.2%
1 2
 
7.7%
S 1
 
3.8%
W 1
 
3.8%
5 1
 
3.8%
~ 1
 
3.8%
H 1
 
3.8%

Unnamed: 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
전북
44 
광역시/도
 
1
<NA>
 
1

Length

Max length5
Median length2
Mean length2.1086957
Min length2

Unique

Unique2 ?
Unique (%)4.3%

Sample

1st row광역시/도
2nd row<NA>
3rd row전북
4th row전북
5th row전북

Common Values

ValueCountFrequency (%)
전북 44
95.7%
광역시/도 1
 
2.2%
<NA> 1
 
2.2%

Length

2024-03-14T09:43:44.237713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:43:44.364470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북 44
95.7%
광역시/도 1
 
2.2%
na 1
 
2.2%

Unnamed: 4
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size500.0 B
전주시
9 
무주군
7 
군산시
6 
남원시
6 
고창군
4 
Other values (9)
14 

Length

Max length4
Median length3
Mean length3.0217391
Min length3

Unique

Unique5 ?
Unique (%)10.9%

Sample

1st row시군구
2nd row<NA>
3rd row무주군
4th row정읍시
5th row무주군

Common Values

ValueCountFrequency (%)
전주시 9
19.6%
무주군 7
15.2%
군산시 6
13.0%
남원시 6
13.0%
고창군 4
8.7%
부안군 3
 
6.5%
정읍시 2
 
4.3%
진안군 2
 
4.3%
장수군 2
 
4.3%
시군구 1
 
2.2%
Other values (4) 4
8.7%

Length

2024-03-14T09:43:44.460899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 9
19.6%
무주군 7
15.2%
군산시 6
13.0%
남원시 6
13.0%
고창군 4
8.7%
부안군 3
 
6.5%
정읍시 2
 
4.3%
진안군 2
 
4.3%
장수군 2
 
4.3%
시군구 1
 
2.2%
Other values (4) 4
8.7%

Unnamed: 5
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T09:43:44.692464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length22.555556
Min length2

Characters and Unicode

Total characters1015
Distinct characters112
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row주소
2nd row전라북도 무주군 무주읍 한풍루로 381-7
3rd row전라북도 정읍시 내장산로 937
4th row전라북도 무주군 설천면 구천동1로 156
5th row전라북도 부안군 변산면 격포로 196
ValueCountFrequency (%)
전라북도 44
 
19.5%
전주시 9
 
4.0%
덕진구 7
 
3.1%
무주군 7
 
3.1%
군산시 6
 
2.7%
남원시 6
 
2.7%
설천면 4
 
1.8%
고창군 4
 
1.8%
고창읍 4
 
1.8%
산정2길 3
 
1.3%
Other values (117) 132
58.4%
2024-03-14T09:43:45.078084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
17.5%
전 55
 
5.4%
도 47
 
4.6%
라 44
 
4.3%
북 44
 
4.3%
1 37
 
3.6%
2 31
 
3.1%
군 26
 
2.6%
로 24
 
2.4%
시 24
 
2.4%
Other values (102) 505
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
62.0%
Space Separator 181
 
17.8%
Decimal Number 156
 
15.4%
Dash Punctuation 21
 
2.1%
Open Punctuation 14
 
1.4%
Close Punctuation 14
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 55
 
8.7%
도 47
 
7.5%
라 44
 
7.0%
북 44
 
7.0%
군 26
 
4.1%
로 24
 
3.8%
시 24
 
3.8%
주 24
 
3.8%
산 22
 
3.5%
동 18
 
2.9%
Other values (87) 301
47.9%
Decimal Number
ValueCountFrequency (%)
1 37
23.7%
2 31
19.9%
3 17
10.9%
6 16
10.3%
4 14
 
9.0%
9 13
 
8.3%
7 9
 
5.8%
0 7
 
4.5%
8 6
 
3.8%
5 6
 
3.8%
Space Separator
ValueCountFrequency (%)
178
98.3%
  3
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 629
62.0%
Common 386
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 55
 
8.7%
도 47
 
7.5%
라 44
 
7.0%
북 44
 
7.0%
군 26
 
4.1%
로 24
 
3.8%
시 24
 
3.8%
주 24
 
3.8%
산 22
 
3.5%
동 18
 
2.9%
Other values (87) 301
47.9%
Common
ValueCountFrequency (%)
178
46.1%
1 37
 
9.6%
2 31
 
8.0%
- 21
 
5.4%
3 17
 
4.4%
6 16
 
4.1%
( 14
 
3.6%
4 14
 
3.6%
) 14
 
3.6%
9 13
 
3.4%
Other values (5) 31
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 629
62.0%
ASCII 383
37.7%
None 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
46.5%
1 37
 
9.7%
2 31
 
8.1%
- 21
 
5.5%
3 17
 
4.4%
6 16
 
4.2%
( 14
 
3.7%
4 14
 
3.7%
) 14
 
3.7%
9 13
 
3.4%
Other values (4) 28
 
7.3%
Hangul
ValueCountFrequency (%)
전 55
 
8.7%
도 47
 
7.5%
라 44
 
7.0%
북 44
 
7.0%
군 26
 
4.1%
로 24
 
3.8%
시 24
 
3.8%
주 24
 
3.8%
산 22
 
3.5%
동 18
 
2.9%
Other values (87) 301
47.9%
None
ValueCountFrequency (%)
  3
100.0%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.2%
Memory size500.0 B

Unnamed: 7
Text

MISSING 

Distinct45
Distinct (%)100.0%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T09:43:45.294730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length12
Mean length12.266667
Min length4

Characters and Unicode

Total characters552
Distinct characters24
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row063-324-3400
3rd row063-538-9487
4th row063-322-3100
5th row063-583-8046
ValueCountFrequency (%)
전화번호 1
 
2.2%
063-432-4201 1
 
2.2%
063-626-3535 1
 
2.2%
063-232-7123 1
 
2.2%
063-538-5656 1
 
2.2%
063-636-7200 1
 
2.2%
063-584-9931 1
 
2.2%
063-653-3960 1
 
2.2%
063-291-5000 1
 
2.2%
063-291-4747(사무실 1
 
2.2%
Other values (36) 36
78.3%
2024-03-14T09:43:45.602412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 91
16.5%
- 89
16.1%
0 84
15.2%
6 77
13.9%
2 52
9.4%
4 35
 
6.3%
5 33
 
6.0%
1 22
 
4.0%
9 19
 
3.4%
7 18
 
3.3%
Other values (14) 32
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 449
81.3%
Dash Punctuation 89
 
16.1%
Other Letter 7
 
1.3%
Space Separator 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Control 1
 
0.2%
Other Punctuation 1
 
0.2%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 91
20.3%
0 84
18.7%
6 77
17.1%
2 52
11.6%
4 35
 
7.8%
5 33
 
7.3%
1 22
 
4.9%
9 19
 
4.2%
7 18
 
4.0%
8 18
 
4.0%
Other Letter
ValueCountFrequency (%)
무 1
14.3%
실 1
14.3%
사 1
14.3%
전 1
14.3%
화 1
14.3%
호 1
14.3%
번 1
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 545
98.7%
Hangul 7
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
3 91
16.7%
- 89
16.3%
0 84
15.4%
6 77
14.1%
2 52
9.5%
4 35
 
6.4%
5 33
 
6.1%
1 22
 
4.0%
9 19
 
3.5%
7 18
 
3.3%
Other values (7) 25
 
4.6%
Hangul
ValueCountFrequency (%)
무 1
14.3%
실 1
14.3%
사 1
14.3%
전 1
14.3%
화 1
14.3%
호 1
14.3%
번 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
98.7%
Hangul 7
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 91
16.7%
- 89
16.3%
0 84
15.4%
6 77
14.1%
2 52
9.5%
4 35
 
6.4%
5 33
 
6.1%
1 22
 
4.0%
9 19
 
3.5%
7 18
 
3.3%
Other values (7) 25
 
4.6%
Hangul
ValueCountFrequency (%)
무 1
14.3%
실 1
14.3%
사 1
14.3%
전 1
14.3%
화 1
14.3%
호 1
14.3%
번 1
14.3%

Unnamed: 8
Text

MISSING 

Distinct33
Distinct (%)73.3%
Missing1
Missing (%)2.2%
Memory size500.0 B
2024-03-14T09:43:45.773970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length30
Mean length15.466667
Min length1

Characters and Unicode

Total characters696
Distinct characters44
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)71.1%

Sample

1st row홈페이지
2nd row-
3rd rowhttp://063-538-9487.114service.co.kr
4th rowwww.jlsj.co.kr/
5th rowwww.csr063.com/
ValueCountFrequency (%)
13
28.9%
http://www.063-273-2233.kti114.net/idx.htm 1
 
2.2%
www.mujulaube.com 1
 
2.2%
www.jungeup.com/538-5656 1
 
2.2%
http://cafe.daum.net/charmotel 1
 
2.2%
wgspa.co.kr 1
 
2.2%
www.pensionsulwha.com 1
 
2.2%
www.hhillsresort.co.kr 1
 
2.2%
www.seolguk.com 1
 
2.2%
www.mj1614.com 1
 
2.2%
Other values (23) 23
51.1%
2024-03-14T09:43:46.061804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 83
 
11.9%
. 71
 
10.2%
o 46
 
6.6%
t 42
 
6.0%
c 34
 
4.9%
/ 33
 
4.7%
e 33
 
4.7%
m 28
 
4.0%
r 28
 
4.0%
h 27
 
3.9%
Other values (34) 271
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 512
73.6%
Other Punctuation 115
 
16.5%
Decimal Number 40
 
5.7%
Dash Punctuation 21
 
3.0%
Space Separator 4
 
0.6%
Other Letter 4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 83
16.2%
o 46
 
9.0%
t 42
 
8.2%
c 34
 
6.6%
e 33
 
6.4%
m 28
 
5.5%
r 28
 
5.5%
h 27
 
5.3%
a 26
 
5.1%
n 24
 
4.7%
Other values (15) 141
27.5%
Decimal Number
ValueCountFrequency (%)
3 8
20.0%
1 6
15.0%
6 6
15.0%
5 4
10.0%
4 4
10.0%
2 3
 
7.5%
8 3
 
7.5%
0 3
 
7.5%
7 2
 
5.0%
9 1
 
2.5%
Other Letter
ValueCountFrequency (%)
지 1
25.0%
이 1
25.0%
페 1
25.0%
홈 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 71
61.7%
/ 33
28.7%
: 11
 
9.6%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 512
73.6%
Common 180
 
25.9%
Hangul 4
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 83
16.2%
o 46
 
9.0%
t 42
 
8.2%
c 34
 
6.6%
e 33
 
6.4%
m 28
 
5.5%
r 28
 
5.5%
h 27
 
5.3%
a 26
 
5.1%
n 24
 
4.7%
Other values (15) 141
27.5%
Common
ValueCountFrequency (%)
. 71
39.4%
/ 33
18.3%
- 21
 
11.7%
: 11
 
6.1%
3 8
 
4.4%
1 6
 
3.3%
6 6
 
3.3%
4
 
2.2%
5 4
 
2.2%
4 4
 
2.2%
Other values (5) 12
 
6.7%
Hangul
ValueCountFrequency (%)
지 1
25.0%
이 1
25.0%
페 1
25.0%
홈 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 692
99.4%
Hangul 4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 83
 
12.0%
. 71
 
10.3%
o 46
 
6.6%
t 42
 
6.1%
c 34
 
4.9%
/ 33
 
4.8%
e 33
 
4.8%
m 28
 
4.0%
r 28
 
4.0%
h 27
 
3.9%
Other values (30) 267
38.6%
Hangul
ValueCountFrequency (%)
지 1
25.0%
이 1
25.0%
페 1
25.0%
홈 1
25.0%

Unnamed: 9
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
30대
7 
20대
6 
40대
5 
50대
4 
25대
4 
Other values (17)
20 

Length

Max length5
Median length3
Mean length3.1956522
Min length3

Unique

Unique14 ?
Unique (%)30.4%

Sample

1st row주차장유무
2nd row<NA>
3rd row40대
4th row50대
5th row20대

Common Values

ValueCountFrequency (%)
30대 7
15.2%
20대 6
13.0%
40대 5
10.9%
50대 4
 
8.7%
25대 4
 
8.7%
15대 2
 
4.3%
100대 2
 
4.3%
120대 2
 
4.3%
36대 1
 
2.2%
17대 1
 
2.2%
Other values (12) 12
26.1%

Length

2024-03-14T09:43:46.182473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30대 7
15.2%
20대 6
13.0%
40대 5
10.9%
50대 4
 
8.7%
25대 4
 
8.7%
15대 2
 
4.3%
100대 2
 
4.3%
120대 2
 
4.3%
500대 1
 
2.2%
주차장유무 1
 
2.2%
Other values (12) 12
26.1%

Unnamed: 10
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
신용카드, 현금
44 
결제방법
 
1
<NA>
 
1

Length

Max length8
Median length8
Mean length7.826087
Min length4

Unique

Unique2 ?
Unique (%)4.3%

Sample

1st row결제방법
2nd row<NA>
3rd row신용카드, 현금
4th row신용카드, 현금
5th row신용카드, 현금

Common Values

ValueCountFrequency (%)
신용카드, 현금 44
95.7%
결제방법 1
 
2.2%
<NA> 1
 
2.2%

Length

2024-03-14T09:43:46.586696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:43:46.684836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신용카드 44
48.9%
현금 44
48.9%
결제방법 1
 
1.1%
na 1
 
1.1%

Unnamed: 11
Text

MISSING 

Distinct22
Distinct (%)62.9%
Missing11
Missing (%)23.9%
Memory size500.0 B
2024-03-14T09:43:46.791821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length6.3714286
Min length2

Characters and Unicode

Total characters223
Distinct characters46
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)37.1%

Sample

1st row부대시설
2nd row한식당
3rd row세미나실, 족구장 등
4th row식당
5th row휴게소
ValueCountFrequency (%)
세미나실 14
25.5%
사우나실 6
10.9%
식음료장 5
 
9.1%
노래방 5
 
9.1%
등 4
 
7.3%
식당 3
 
5.5%
조식 3
 
5.5%
카페 2
 
3.6%
한식당 2
 
3.6%
족구장 2
 
3.6%
Other values (8) 9
16.4%
2024-03-14T09:43:47.038358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 23
 
10.3%
나 20
 
9.0%
20
 
9.0%
, 16
 
7.2%
식 14
 
6.3%
세 14
 
6.3%
미 14
 
6.3%
장 8
 
3.6%
당 6
 
2.7%
사 6
 
2.7%
Other values (36) 82
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
81.2%
Space Separator 20
 
9.0%
Other Punctuation 16
 
7.2%
Lowercase Letter 6
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 23
 
12.7%
나 20
 
11.0%
식 14
 
7.7%
세 14
 
7.7%
미 14
 
7.7%
장 8
 
4.4%
당 6
 
3.3%
사 6
 
3.3%
우 6
 
3.3%
래 5
 
2.8%
Other values (32) 65
35.9%
Lowercase Letter
ValueCountFrequency (%)
p 3
50.0%
c 3
50.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 181
81.2%
Common 36
 
16.1%
Latin 6
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 23
 
12.7%
나 20
 
11.0%
식 14
 
7.7%
세 14
 
7.7%
미 14
 
7.7%
장 8
 
4.4%
당 6
 
3.3%
사 6
 
3.3%
우 6
 
3.3%
래 5
 
2.8%
Other values (32) 65
35.9%
Common
ValueCountFrequency (%)
20
55.6%
, 16
44.4%
Latin
ValueCountFrequency (%)
p 3
50.0%
c 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181
81.2%
ASCII 42
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 23
 
12.7%
나 20
 
11.0%
식 14
 
7.7%
세 14
 
7.7%
미 14
 
7.7%
장 8
 
4.4%
당 6
 
3.3%
사 6
 
3.3%
우 6
 
3.3%
래 5
 
2.8%
Other values (32) 65
35.9%
ASCII
ValueCountFrequency (%)
20
47.6%
, 16
38.1%
p 3
 
7.1%
c 3
 
7.1%

Unnamed: 12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing45
Missing (%)97.8%
Memory size500.0 B
2024-03-14T09:43:47.187115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row주변관광정보
ValueCountFrequency (%)
주변관광정보 1
100.0%
2024-03-14T09:43:47.400464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1
16.7%
변 1
16.7%
관 1
16.7%
광 1
16.7%
정 1
16.7%
보 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1
16.7%
변 1
16.7%
관 1
16.7%
광 1
16.7%
정 1
16.7%
보 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1
16.7%
변 1
16.7%
관 1
16.7%
광 1
16.7%
정 1
16.7%
보 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1
16.7%
변 1
16.7%
관 1
16.7%
광 1
16.7%
정 1
16.7%
보 1
16.7%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)2.2%
Memory size500.0 B

Correlations

2024-03-14T09:43:47.504475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11
Unnamed: 11.0001.0000.6741.0001.0001.0001.0001.0000.6741.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 30.6741.0001.0001.0001.0001.0001.0001.0000.6741.000
Unnamed: 41.0001.0001.0001.0001.0001.0000.6950.2261.0000.733
Unnamed: 51.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 71.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 81.0001.0001.0000.6951.0001.0001.0000.7971.0000.837
Unnamed: 91.0001.0001.0000.2261.0001.0000.7971.0001.0000.357
Unnamed: 100.6741.0000.6741.0001.0001.0001.0001.0001.0001.000
Unnamed: 111.0001.0001.0000.7331.0001.0000.8370.3571.0001.000
2024-03-14T09:43:47.615586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 10Unnamed: 9Unnamed: 3Unnamed: 1
Unnamed: 41.0000.8630.0000.8630.863
Unnamed: 100.8631.0000.7470.4700.470
Unnamed: 90.0000.7471.0000.7470.747
Unnamed: 30.8630.4700.7471.0000.470
Unnamed: 10.8630.4700.7470.4701.000
2024-03-14T09:43:47.700005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 3Unnamed: 4Unnamed: 9Unnamed: 10
Unnamed: 11.0000.4700.8630.7470.470
Unnamed: 30.4701.0000.8630.7470.470
Unnamed: 40.8630.8631.0000.0000.863
Unnamed: 90.7470.7470.0001.0000.747
Unnamed: 100.4700.4700.8630.7471.000

Missing values

2024-03-14T09:43:43.045223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:43:43.210243image/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.
2024-03-14T09:43:43.386142image/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

우수숙박시설(굿스테이) 현황(2016년 7월)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
0연번업종명영업소명(공식상)광역시/도시군구주소총객실수전화번호홈페이지주차장유무결제방법부대시설주변관광정보데이터기준일자
1NaN<NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA>NaN
21숙박업무주이리스모텔전북무주군전라북도 무주군 무주읍 한풍루로 381-750063-324-3400-40대신용카드, 현금<NA><NA>2015. 8.
32숙박업세르빌호텔전북정읍시전라북도 정읍시 내장산로 93732063-538-9487http://063-538-9487.114service.co.kr50대신용카드, 현금한식당<NA>2015. 8.
43숙박업제일산장전북무주군전라북도 무주군 설천면 구천동1로 15620063-322-3100www.jlsj.co.kr/20대신용카드, 현금세미나실, 족구장 등<NA>2015. 8.
54숙박업채석리조텔오크빌전북부안군전라북도 부안군 변산면 격포로 19630063-583-8046www.csr063.com/15대신용카드, 현금식당<NA>2015. 8.
65숙박업모악산모텔전북완주군전라북도 완주군 구이면 모악산길 104-1026063-222-2023http://www.moakmotel.com30대신용카드, 현금<NA><NA>2015. 8.
76숙박업웨스턴호텔전북군산시전라북도 군산시 옥서면 선연길 1733063-471-0715www.western-inn.kr/30대신용카드, 현금휴게소<NA>2015. 8.
87숙박업지리산칸호텔전북남원시전라북도 남원시 산내면 지리산로 81536063-626-2114http://www.jirisankhanhotel.com40대신용카드, 현금세미나실, 노래방<NA>2015. 8.
98숙박업휴모텔(군산)전북군산시전라북도 군산시 가도안1길 6140063-464-6081-40대신용카드, 현금<NA><NA>2015. 8.
우수숙박시설(굿스테이) 현황(2016년 7월)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
3649숙박업로베펜션전북무주군전라북도 무주군 설천면 구천동1로 12910063-322-9914www.mujulaube.com18대신용카드, 현금세미나실, 노래방<NA>2015. 8.
3750숙박업무주 덕유산 레저바이크텔전북무주군전라북도 무주군 설천면 구천동로 9686063-320-2575www.mj1614.com40대신용카드, 현금세미나실, 사우나실, 노래방 등<NA>2015. 8.
3851숙박업타코마 팜 리조트전북장수군전라북도 장수군 계남면 장수로 2662-1150063-353-8200www.tacomaresort.co.kr200대신용카드, 현금세미나실, 사우나실, 노래방 등<NA>2015. 8.
3952숙박업넥스텔전북고창군전라북도 고창군 고창읍 월암수월길 112 (월암리)38063-564-8999-45대신용카드, 현금<NA><NA>2015. 8.
4053숙박업자라게스트하우스전북남원시전라북도 남원시 인월면 인월장터로 6 (인월리)7063-626-2129www.zaraguest.com20대신용카드, 현금조식<NA>2015. 8.
4154숙박업W 호텔전북군산시전라북도 군산시 소룡1길 58 (소룡동)41063-464-6205~6-32대신용카드, 현금공공pc실, 카페<NA>2015. 8.
4255숙박업솔호텔전북전주시전라북도 전주시 덕진구 아중2길 22-4 (우아동2가 928-5번지)30063-261-7000www.hotelsol.co.kr25대신용카드, 현금<NA><NA>2015. 8.
4356숙박업르시엘전북전주시전라북도 전주시 덕진구 산정2길 23(산정동)31063-245-4848http://www.lecielhotel.com50대신용카드, 현금노래방<NA>2015. 8.
4457숙박업남원호텔전북남원시전라북도 남원시 주천면 정령치로 122-11(주천면)35063-626-3535www.namwonhotel.com100대신용카드, 현금뷔폐식당<NA>2015. 8.
4558숙박업호텔석정힐전북고창군전라북도 고창군 고창읍 방장로 1228063-563-7711www.hillcc.com60대신용카드, 현금세미나실<NA>2016.07