Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory45.5 B

Variable types

Text4
Unsupported1

Alerts

관광펜션업 현황 (2013년12월) has unique valuesUnique
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:06:15.104568
Analysis finished2024-03-14 01:06:15.397040
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관광펜션업 현황 (2013년12월)
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T10:06:15.511194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5
Min length2

Characters and Unicode

Total characters120
Distinct characters69
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row상호
2nd row구름채펜션
3rd row펜션무주네버랜드
4th row반송펜션
5th row리틀프린스
ValueCountFrequency (%)
상호 1
 
3.8%
구름채펜션 1
 
3.8%
솔섬펜션 1
 
3.8%
소리섬펜션 1
 
3.8%
노을빛언덕 1
 
3.8%
해조음 1
 
3.8%
아모르펜션 1
 
3.8%
땅 1
 
3.8%
우리 1
 
3.8%
독도는 1
 
3.8%
Other values (16) 16
61.5%
2024-03-14T10:06:15.777524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
펜 14
 
11.7%
션 14
 
11.7%
리 8
 
6.7%
스 4
 
3.3%
우 3
 
2.5%
모 3
 
2.5%
드 2
 
1.7%
2
 
1.7%
음 2
 
1.7%
마 2
 
1.7%
Other values (59) 66
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
98.3%
Space Separator 2
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
펜 14
 
11.9%
션 14
 
11.9%
리 8
 
6.8%
스 4
 
3.4%
우 3
 
2.5%
모 3
 
2.5%
드 2
 
1.7%
음 2
 
1.7%
마 2
 
1.7%
덕 2
 
1.7%
Other values (58) 64
54.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
98.3%
Common 2
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
펜 14
 
11.9%
션 14
 
11.9%
리 8
 
6.8%
스 4
 
3.4%
우 3
 
2.5%
모 3
 
2.5%
드 2
 
1.7%
음 2
 
1.7%
마 2
 
1.7%
덕 2
 
1.7%
Other values (58) 64
54.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
98.3%
ASCII 2
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
펜 14
 
11.9%
션 14
 
11.9%
리 8
 
6.8%
스 4
 
3.4%
우 3
 
2.5%
모 3
 
2.5%
드 2
 
1.7%
음 2
 
1.7%
마 2
 
1.7%
덕 2
 
1.7%
Other values (58) 64
54.2%
ASCII
ValueCountFrequency (%)
2
100.0%

Unnamed: 1
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T10:06:15.931232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters72
Distinct characters48
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row대표자
2nd row신선자
3rd row현형태
4th row문현미
5th row우종인
ValueCountFrequency (%)
송주호 2
 
8.0%
신선자 1
 
4.0%
임영신 1
 
4.0%
나경순 1
 
4.0%
이계환 1
 
4.0%
순 1
 
4.0%
허 1
 
4.0%
김정애 1
 
4.0%
박성숙 1
 
4.0%
이윤희 1
 
4.0%
Other values (14) 14
56.0%
2024-03-14T10:06:16.181460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 4
 
5.6%
신 4
 
5.6%
현 3
 
4.2%
순 3
 
4.2%
주 3
 
4.2%
송 2
 
2.8%
애 2
 
2.8%
이 2
 
2.8%
숙 2
 
2.8%
희 2
 
2.8%
Other values (38) 45
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
98.6%
Space Separator 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 4
 
5.6%
신 4
 
5.6%
현 3
 
4.2%
순 3
 
4.2%
주 3
 
4.2%
송 2
 
2.8%
애 2
 
2.8%
이 2
 
2.8%
숙 2
 
2.8%
희 2
 
2.8%
Other values (37) 44
62.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71
98.6%
Common 1
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 4
 
5.6%
신 4
 
5.6%
현 3
 
4.2%
순 3
 
4.2%
주 3
 
4.2%
송 2
 
2.8%
애 2
 
2.8%
이 2
 
2.8%
숙 2
 
2.8%
희 2
 
2.8%
Other values (37) 44
62.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71
98.6%
ASCII 1
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 4
 
5.6%
신 4
 
5.6%
현 3
 
4.2%
순 3
 
4.2%
주 3
 
4.2%
송 2
 
2.8%
애 2
 
2.8%
이 2
 
2.8%
숙 2
 
2.8%
희 2
 
2.8%
Other values (37) 44
62.0%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 2
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T10:06:16.343996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length16
Min length3

Characters and Unicode

Total characters384
Distinct characters50
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

Unique22 ?
Unique (%)91.7%

Sample

1st row소재지
2nd row무주군 설천면 삼공리 820-5
3rd row무주군 설천면 삼공리 366-4
4th row무주군 설천면 삼공리 728-1
5th row무주군 설천면 심곡리 646
ValueCountFrequency (%)
무주군 17
18.3%
설천면 16
17.2%
삼공리 8
 
8.6%
심곡리 7
 
7.5%
부안군 5
 
5.4%
변산면 4
 
4.3%
668-1 2
 
2.2%
격포리 2
 
2.2%
359-17 1
 
1.1%
고창읍 1
 
1.1%
Other values (30) 30
32.3%
2024-03-14T10:06:16.609730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
69
18.0%
군 23
 
6.0%
면 22
 
5.7%
리 20
 
5.2%
무 18
 
4.7%
- 18
 
4.7%
주 17
 
4.4%
설 16
 
4.2%
천 16
 
4.2%
6 13
 
3.4%
Other values (40) 152
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
55.2%
Decimal Number 85
22.1%
Space Separator 69
 
18.0%
Dash Punctuation 18
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 23
10.8%
면 22
 
10.4%
리 20
 
9.4%
무 18
 
8.5%
주 17
 
8.0%
설 16
 
7.5%
천 16
 
7.5%
삼 9
 
4.2%
공 8
 
3.8%
곡 7
 
3.3%
Other values (28) 56
26.4%
Decimal Number
ValueCountFrequency (%)
6 13
15.3%
1 11
12.9%
3 11
12.9%
8 10
11.8%
7 10
11.8%
4 8
9.4%
2 8
9.4%
5 7
8.2%
9 4
 
4.7%
0 3
 
3.5%
Space Separator
ValueCountFrequency (%)
69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
55.2%
Common 172
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 23
10.8%
면 22
 
10.4%
리 20
 
9.4%
무 18
 
8.5%
주 17
 
8.0%
설 16
 
7.5%
천 16
 
7.5%
삼 9
 
4.2%
공 8
 
3.8%
곡 7
 
3.3%
Other values (28) 56
26.4%
Common
ValueCountFrequency (%)
69
40.1%
- 18
 
10.5%
6 13
 
7.6%
1 11
 
6.4%
3 11
 
6.4%
8 10
 
5.8%
7 10
 
5.8%
4 8
 
4.7%
2 8
 
4.7%
5 7
 
4.1%
Other values (2) 7
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
55.2%
ASCII 172
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
69
40.1%
- 18
 
10.5%
6 13
 
7.6%
1 11
 
6.4%
3 11
 
6.4%
8 10
 
5.8%
7 10
 
5.8%
4 8
 
4.7%
2 8
 
4.7%
5 7
 
4.1%
Other values (2) 7
 
4.1%
Hangul
ValueCountFrequency (%)
군 23
10.8%
면 22
 
10.4%
리 20
 
9.4%
무 18
 
8.5%
주 17
 
8.0%
설 16
 
7.5%
천 16
 
7.5%
삼 9
 
4.2%
공 8
 
3.8%
곡 7
 
3.3%
Other values (28) 56
26.4%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size324.0 B

Unnamed: 4
Text

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-03-14T10:06:16.770502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.583333
Min length4

Characters and Unicode

Total characters254
Distinct characters16
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

Unique18 ?
Unique (%)75.0%

Sample

1st row등록일자
2nd row2005. 2. 24
3rd row2005. 11. 4
4th row2008. 5. 27
5th row2009. 11. 2
ValueCountFrequency (%)
2010 6
 
9.1%
4 6
 
9.1%
2012 6
 
9.1%
2009 4
 
6.1%
2011 4
 
6.1%
6 3
 
4.5%
27 3
 
4.5%
8 3
 
4.5%
2 3
 
4.5%
5 2
 
3.0%
Other values (20) 26
39.4%
2024-03-14T10:06:17.018025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 46
18.1%
2 42
16.5%
0 42
16.5%
42
16.5%
1 37
14.6%
9 8
 
3.1%
4 7
 
2.8%
8 7
 
2.8%
3 6
 
2.4%
7 6
 
2.4%
Other values (6) 11
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 162
63.8%
Other Punctuation 46
 
18.1%
Space Separator 42
 
16.5%
Other Letter 4
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 42
25.9%
0 42
25.9%
1 37
22.8%
9 8
 
4.9%
4 7
 
4.3%
8 7
 
4.3%
3 6
 
3.7%
7 6
 
3.7%
5 4
 
2.5%
6 3
 
1.9%
Other Letter
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 46
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250
98.4%
Hangul 4
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 46
18.4%
2 42
16.8%
0 42
16.8%
42
16.8%
1 37
14.8%
9 8
 
3.2%
4 7
 
2.8%
8 7
 
2.8%
3 6
 
2.4%
7 6
 
2.4%
Other values (2) 7
 
2.8%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 250
98.4%
Hangul 4
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 46
18.4%
2 42
16.8%
0 42
16.8%
42
16.8%
1 37
14.8%
9 8
 
3.2%
4 7
 
2.8%
8 7
 
2.8%
3 6
 
2.4%
7 6
 
2.4%
Other values (2) 7
 
2.8%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%

Correlations

2024-03-14T10:06:17.128908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관광펜션업 현황 (2013년12월)Unnamed: 1Unnamed: 2Unnamed: 4
관광펜션업 현황 (2013년12월)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

2024-03-14T10:06:15.291135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:06:15.367183image/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

관광펜션업 현황 (2013년12월)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
0상호대표자소재지객실수등록일자
1구름채펜션신선자무주군 설천면 삼공리 820-5102005. 2. 24
2펜션무주네버랜드현형태무주군 설천면 삼공리 366-482005. 11. 4
3반송펜션문현미무주군 설천면 삼공리 728-1192008. 5. 27
4리틀프린스우종인무주군 설천면 심곡리 646102009. 11. 2
5설인펜션신동철무주군 설천면 삼공리 377-1182009. 6. 2
6눈꽃여행김정남무주군 설천면 심곡리 738-7142010. 3. 30
7마법의성강경임무주군 설천면 심곡리 69762010. 3. 30
8반딧불이펜션김건화무주군 설천면 삼공리 318-172010. 8. 4
9체리스펜션박홍식무주군 설천면 삼공리 742-4112010. 8. 5
관광펜션업 현황 (2013년12월)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
14우리두리모텔송주호무주군 설천면 심곡리 668-1172011. 4. 28
15다숲펜션황희숙무주군 설천면 삼공리 530-1212012. 6. 27
16덕유산펜션최대현무주군 설천면 삼공리 524-8202012. 6. 27
17독도는 우리 땅이윤희무주군 설천면 관동길 852012. 11.27
18아모르펜션박성숙고창군 고창읍 월암리 373-1182010. 12. 9
19해조음김정애부안군 변산면 운산리 359-1792009. 7. 13
20노을빛언덕허 순부안군 변산면 격포리 48-252009. 10.23
21소리섬펜션이계환부안군 변산면 격포리 643-882012. 9. 20
22솔섬펜션나경순부안군 변산면 변산로 320972012. 11.19
23생폴드방스펜션신애연부안군 진서면 구름호수길 5242012. 10.17