Overview

Dataset statistics

Number of variables5
Number of observations52
Missing cells50
Missing cells (%)19.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory42.5 B

Variable types

Text4
Unsupported1

Alerts

※ 관광숙박업 현황(2018년) has 45 (86.5%) missing valuesMissing
Unnamed: 1 has 1 (1.9%) missing valuesMissing
Unnamed: 2 has 1 (1.9%) missing valuesMissing
Unnamed: 3 has 1 (1.9%) missing valuesMissing
Unnamed: 4 has 2 (3.8%) missing valuesMissing
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:36:23.515900
Analysis finished2024-03-14 02:36:24.033224
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

※ 관광숙박업 현황(2018년)
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing45
Missing (%)86.5%
Memory size548.0 B
2024-03-14T11:36:24.117723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4
Min length3

Characters and Unicode

Total characters28
Distinct characters20
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

Unique7 ?
Unique (%)100.0%

Sample

1st row업종별
2nd row관광호텔
3rd row한국전통호텔
4th row가족호텔
5th row소형호텔
ValueCountFrequency (%)
업종별 1
14.3%
관광호텔 1
14.3%
한국전통호텔 1
14.3%
가족호텔 1
14.3%
소형호텔 1
14.3%
호스텔 1
14.3%
휴양콘도 1
14.3%
2024-03-14T11:36:24.367041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 5
17.9%
텔 5
17.9%
업 1
 
3.6%
가 1
 
3.6%
콘 1
 
3.6%
양 1
 
3.6%
휴 1
 
3.6%
스 1
 
3.6%
형 1
 
3.6%
소 1
 
3.6%
Other values (10) 10
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 5
17.9%
텔 5
17.9%
업 1
 
3.6%
가 1
 
3.6%
콘 1
 
3.6%
양 1
 
3.6%
휴 1
 
3.6%
스 1
 
3.6%
형 1
 
3.6%
소 1
 
3.6%
Other values (10) 10
35.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 5
17.9%
텔 5
17.9%
업 1
 
3.6%
가 1
 
3.6%
콘 1
 
3.6%
양 1
 
3.6%
휴 1
 
3.6%
스 1
 
3.6%
형 1
 
3.6%
소 1
 
3.6%
Other values (10) 10
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 5
17.9%
텔 5
17.9%
업 1
 
3.6%
가 1
 
3.6%
콘 1
 
3.6%
양 1
 
3.6%
휴 1
 
3.6%
스 1
 
3.6%
형 1
 
3.6%
소 1
 
3.6%
Other values (10) 10
35.7%

Unnamed: 1
Text

MISSING 

Distinct51
Distinct (%)100.0%
Missing1
Missing (%)1.9%
Memory size548.0 B
2024-03-14T11:36:24.603365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.7647059
Min length4

Characters and Unicode

Total characters396
Distinct characters126
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

Unique51 ?
Unique (%)100.0%

Sample

1st row상 호 명
2nd row풍남관광호텔
3rd row전주코아호텔
4th row㈜호텔르윈
5th row전주호텔한성
ValueCountFrequency (%)
호텔 3
 
4.8%
익산 2
 
3.2%
일성무주콘도 1
 
1.6%
스위트관광호텔 1
 
1.6%
호텔티롤 1
 
1.6%
채석강스타힐스 1
 
1.6%
나비잠 1
 
1.6%
한옥호텔 1
 
1.6%
호텔마음 1
 
1.6%
무주덕유산리조트가족호텔 1
 
1.6%
Other values (50) 50
79.4%
2024-03-14T11:36:24.944892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 38
 
9.6%
텔 37
 
9.3%
스 22
 
5.6%
산 14
 
3.5%
리 14
 
3.5%
13
 
3.3%
관 13
 
3.3%
광 13
 
3.3%
트 11
 
2.8%
주 10
 
2.5%
Other values (116) 211
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 378
95.5%
Space Separator 13
 
3.3%
Decimal Number 2
 
0.5%
Uppercase Letter 2
 
0.5%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 38
 
10.1%
텔 37
 
9.8%
스 22
 
5.8%
산 14
 
3.7%
리 14
 
3.7%
관 13
 
3.4%
광 13
 
3.4%
트 11
 
2.9%
주 10
 
2.6%
군 6
 
1.6%
Other values (110) 200
52.9%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 379
95.7%
Common 15
 
3.8%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 38
 
10.0%
텔 37
 
9.8%
스 22
 
5.8%
산 14
 
3.7%
리 14
 
3.7%
관 13
 
3.4%
광 13
 
3.4%
트 11
 
2.9%
주 10
 
2.6%
군 6
 
1.6%
Other values (111) 201
53.0%
Common
ValueCountFrequency (%)
13
86.7%
4 1
 
6.7%
2 1
 
6.7%
Latin
ValueCountFrequency (%)
S 1
50.0%
J 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 378
95.5%
ASCII 17
 
4.3%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 38
 
10.1%
텔 37
 
9.8%
스 22
 
5.8%
산 14
 
3.7%
리 14
 
3.7%
관 13
 
3.4%
광 13
 
3.4%
트 11
 
2.9%
주 10
 
2.6%
군 6
 
1.6%
Other values (110) 200
52.9%
ASCII
ValueCountFrequency (%)
13
76.5%
4 1
 
5.9%
2 1
 
5.9%
S 1
 
5.9%
J 1
 
5.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Unnamed: 2
Text

MISSING 

Distinct50
Distinct (%)98.0%
Missing1
Missing (%)1.9%
Memory size548.0 B
2024-03-14T11:36:25.178906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length14.607843
Min length3

Characters and Unicode

Total characters745
Distinct characters102
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

Unique49 ?
Unique (%)96.1%

Sample

1st row소재지
2nd row전주시 완산구 전주객사2길 45-7
3rd row전주시 완산구 노송광장로 51
4th row전주시 완산구 기린대로 81
5th row전주시 완산구 객사5길 43-3
ValueCountFrequency (%)
전주시 19
 
10.3%
완산구 18
 
9.7%
군산시 10
 
5.4%
무주군 6
 
3.2%
남원시 6
 
3.2%
설천면 4
 
2.2%
변산면 3
 
1.6%
부안군 3
 
1.6%
팔달로 3
 
1.6%
익산시 3
 
1.6%
Other values (97) 110
59.5%
2024-03-14T11:36:25.553871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
18.0%
산 40
 
5.4%
시 39
 
5.2%
1 35
 
4.7%
주 33
 
4.4%
전 27
 
3.6%
로 24
 
3.2%
길 24
 
3.2%
2 22
 
3.0%
5 22
 
3.0%
Other values (92) 345
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
59.6%
Decimal Number 151
 
20.3%
Space Separator 134
 
18.0%
Dash Punctuation 16
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 40
 
9.0%
시 39
 
8.8%
주 33
 
7.4%
전 27
 
6.1%
로 24
 
5.4%
길 24
 
5.4%
구 22
 
5.0%
군 20
 
4.5%
완 19
 
4.3%
면 14
 
3.2%
Other values (80) 182
41.0%
Decimal Number
ValueCountFrequency (%)
1 35
23.2%
2 22
14.6%
5 22
14.6%
4 17
11.3%
3 13
 
8.6%
0 13
 
8.6%
7 10
 
6.6%
6 7
 
4.6%
8 7
 
4.6%
9 5
 
3.3%
Space Separator
ValueCountFrequency (%)
134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
59.6%
Common 301
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 40
 
9.0%
시 39
 
8.8%
주 33
 
7.4%
전 27
 
6.1%
로 24
 
5.4%
길 24
 
5.4%
구 22
 
5.0%
군 20
 
4.5%
완 19
 
4.3%
면 14
 
3.2%
Other values (80) 182
41.0%
Common
ValueCountFrequency (%)
134
44.5%
1 35
 
11.6%
2 22
 
7.3%
5 22
 
7.3%
4 17
 
5.6%
- 16
 
5.3%
3 13
 
4.3%
0 13
 
4.3%
7 10
 
3.3%
6 7
 
2.3%
Other values (2) 12
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
59.6%
ASCII 301
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
44.5%
1 35
 
11.6%
2 22
 
7.3%
5 22
 
7.3%
4 17
 
5.6%
- 16
 
5.3%
3 13
 
4.3%
0 13
 
4.3%
7 10
 
3.3%
6 7
 
2.3%
Other values (2) 12
 
4.0%
Hangul
ValueCountFrequency (%)
산 40
 
9.0%
시 39
 
8.8%
주 33
 
7.4%
전 27
 
6.1%
로 24
 
5.4%
길 24
 
5.4%
구 22
 
5.0%
군 20
 
4.5%
완 19
 
4.3%
면 14
 
3.2%
Other values (80) 182
41.0%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)1.9%
Memory size548.0 B

Unnamed: 4
Text

MISSING 

Distinct49
Distinct (%)98.0%
Missing2
Missing (%)3.8%
Memory size548.0 B
2024-03-14T11:36:25.862341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length12.04
Min length3

Characters and Unicode

Total characters602
Distinct characters23
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)96.0%

Sample

1st row비 고
2nd row063-231-7900
3rd row285-1100(14. 3월부터 휴업중)
4th row232-7000
5th row063-288-0014
ValueCountFrequency (%)
063-322-9000 2
 
3.8%
063-281-1000 1
 
1.9%
063-324-3939 1
 
1.9%
063-232-3992 1
 
1.9%
063-720-3000 1
 
1.9%
063-630-7100 1
 
1.9%
063-581-9911 1
 
1.9%
063-287-8877 1
 
1.9%
063-631-9999 1
 
1.9%
063-324-8662 1
 
1.9%
Other values (42) 42
79.2%
2024-03-14T11:36:26.227691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 131
21.8%
- 96
15.9%
3 84
14.0%
6 75
12.5%
2 46
 
7.6%
8 32
 
5.3%
1 32
 
5.3%
7 27
 
4.5%
4 26
 
4.3%
5 18
 
3.0%
Other values (13) 35
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 488
81.1%
Dash Punctuation 96
 
15.9%
Other Letter 10
 
1.7%
Space Separator 3
 
0.5%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 131
26.8%
3 84
17.2%
6 75
15.4%
2 46
 
9.4%
8 32
 
6.6%
1 32
 
6.6%
7 27
 
5.5%
4 26
 
5.3%
5 18
 
3.7%
9 17
 
3.5%
Other Letter
ValueCountFrequency (%)
휴 2
20.0%
업 2
20.0%
터 1
10.0%
부 1
10.0%
월 1
10.0%
중 1
10.0%
비 1
10.0%
고 1
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 592
98.3%
Hangul 10
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 131
22.1%
- 96
16.2%
3 84
14.2%
6 75
12.7%
2 46
 
7.8%
8 32
 
5.4%
1 32
 
5.4%
7 27
 
4.6%
4 26
 
4.4%
5 18
 
3.0%
Other values (5) 25
 
4.2%
Hangul
ValueCountFrequency (%)
휴 2
20.0%
업 2
20.0%
터 1
10.0%
부 1
10.0%
월 1
10.0%
중 1
10.0%
비 1
10.0%
고 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 592
98.3%
Hangul 10
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 131
22.1%
- 96
16.2%
3 84
14.2%
6 75
12.7%
2 46
 
7.8%
8 32
 
5.4%
1 32
 
5.4%
7 27
 
4.6%
4 26
 
4.4%
5 18
 
3.0%
Other values (5) 25
 
4.2%
Hangul
ValueCountFrequency (%)
휴 2
20.0%
업 2
20.0%
터 1
10.0%
부 1
10.0%
월 1
10.0%
중 1
10.0%
비 1
10.0%
고 1
10.0%

Correlations

2024-03-14T11:36:26.311112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
※ 관광숙박업 현황(2018년)Unnamed: 1Unnamed: 2Unnamed: 4
※ 관광숙박업 현황(2018년)1.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.000

Missing values

2024-03-14T11:36:23.815316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:36:23.891135image/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.
2024-03-14T11:36:23.975808image/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

※ 관광숙박업 현황(2018년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
0<NA><NA><NA>NaN<NA>
1업종별상 호 명소재지객실수비 고
2관광호텔풍남관광호텔전주시 완산구 전주객사2길 45-763063-231-7900
3<NA>전주코아호텔전주시 완산구 노송광장로 51111285-1100(14. 3월부터 휴업중)
4<NA>㈜호텔르윈전주시 완산구 기린대로 81166232-7000
5<NA>전주호텔한성전주시 완산구 객사5길 43-340063-288-0014
6<NA>째즈어라운드호텔전주시 덕진구 정언신로 18235063-247-5900
7<NA>화이트관광호텔전주시 덕진구 전주천동로 50135063-271-0123
8<NA>전주한옥태조궁관광호텔전주시 완산구 전라감영로 4030063-287-6400
9<NA>전주관광호텔전주시 완산구 전주객사5길 44-531063-280-7700
※ 관광숙박업 현황(2018년)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
42<NA>24게스트하우스 전주점전주시 완산구 현무3길 5622063-715-1616
43<NA>말마니 게스트하우스전주시 완산구 현무1길 21-279063-288-2466
44<NA>콩쥐팥쥐한옥리조트완주군 이서면 신지앵곡길 23724063-908-2002
45<NA>해바라기펜션 호스텔무주군 설천면 삼공리 522-920010-6533-3631
46휴양콘도켄싱턴리조트지리산남원남원시 소리길 66134063-636-7007
47<NA>중앙하이츠콘도남원시 장승안길 2-9150063-626-8080
48<NA>지리산토비스콘도남원시 산내면 산내원천길 4-560063-636-3663
49<NA>일성지리산콘도남원시 산내면 천왕봉로 626-25167063-636-7000
50<NA>일성무주콘도무주군 무풍면 구천동로 350121063-324-3939
51<NA>무주토비스콘도무주군 무풍면 현내리 산 110106063-322-6411