Overview

Dataset statistics

Number of variables4
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory34.7 B

Variable types

Unsupported2
Text2

Dataset

Description우수숙박시설굿스테이현황20146
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201483

Alerts

Unnamed: 1 has unique valuesUnique
Unnamed: 2 has unique valuesUnique
우수숙박시설(굿스테이)현황(2014년6월) is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:31:01.352950
Analysis finished2024-03-14 00:31:01.588246
Duration0.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

우수숙박시설(굿스테이)현황(2014년6월)
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size524.0 B

Unnamed: 1
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T09:31:01.731700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length5.4489796
Min length3

Characters and Unicode

Total characters267
Distinct characters111
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

Unique49 ?
Unique (%)100.0%

Sample

1st row시 설 명
2nd row61개소
3rd row웨스턴호텔
4th row휴모텔
5th row세르빌호텔
ValueCountFrequency (%)
시 1
 
1.9%
그린토피아 1
 
1.9%
군산뉴그랜드모텔 1
 
1.9%
남원 1
 
1.9%
한일파크 1
 
1.9%
남원호텔 1
 
1.9%
장수온천호텔 1
 
1.9%
영빈호텔 1
 
1.9%
석정힐링카운티 1
 
1.9%
윈호텔 1
 
1.9%
Other values (44) 44
81.5%
2024-03-14T09:31:02.045314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 31
 
11.6%
호 16
 
6.0%
모 13
 
4.9%
산 8
 
3.0%
리 8
 
3.0%
펜 6
 
2.2%
션 6
 
2.2%
스 6
 
2.2%
주 5
 
1.9%
원 5
 
1.9%
Other values (101) 163
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 256
95.9%
Space Separator 5
 
1.9%
Uppercase Letter 2
 
0.7%
Decimal Number 2
 
0.7%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 31
 
12.1%
호 16
 
6.2%
모 13
 
5.1%
산 8
 
3.1%
리 8
 
3.1%
펜 6
 
2.3%
션 6
 
2.3%
스 6
 
2.3%
주 5
 
2.0%
원 5
 
2.0%
Other values (94) 152
59.4%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 256
95.9%
Common 9
 
3.4%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 31
 
12.1%
호 16
 
6.2%
모 13
 
5.1%
산 8
 
3.1%
리 8
 
3.1%
펜 6
 
2.3%
션 6
 
2.3%
스 6
 
2.3%
주 5
 
2.0%
원 5
 
2.0%
Other values (94) 152
59.4%
Common
ValueCountFrequency (%)
5
55.6%
) 1
 
11.1%
( 1
 
11.1%
1 1
 
11.1%
6 1
 
11.1%
Latin
ValueCountFrequency (%)
H 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 256
95.9%
ASCII 11
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 31
 
12.1%
호 16
 
6.2%
모 13
 
5.1%
산 8
 
3.1%
리 8
 
3.1%
펜 6
 
2.3%
션 6
 
2.3%
스 6
 
2.3%
주 5
 
2.0%
원 5
 
2.0%
Other values (94) 152
59.4%
ASCII
ValueCountFrequency (%)
5
45.5%
H 1
 
9.1%
S 1
 
9.1%
) 1
 
9.1%
( 1
 
9.1%
1 1
 
9.1%
6 1
 
9.1%

Unnamed: 2
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-14T09:31:02.300617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length15.428571
Min length1

Characters and Unicode

Total characters756
Distinct characters99
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 (%)100.0%

Sample

1st row소 재 지
2nd row-
3rd row군산시 옥서면 선연길 17
4th row군산시 가도안1길 61
5th row정읍시 내장산로 937
ValueCountFrequency (%)
무주군 12
 
6.5%
전주시 8
 
4.3%
덕진구 6
 
3.3%
설천면 6
 
3.3%
남원시 5
 
2.7%
군산시 5
 
2.7%
무풍면 4
 
2.2%
부안군 4
 
2.2%
구천동로 3
 
1.6%
구천동1로 3
 
1.6%
Other values (110) 128
69.6%
2024-03-14T09:31:02.749377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
17.9%
1 41
 
5.4%
2 33
 
4.4%
군 30
 
4.0%
로 28
 
3.7%
주 27
 
3.6%
- 23
 
3.0%
시 22
 
2.9%
면 22
 
2.9%
산 21
 
2.8%
Other values (89) 374
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 430
56.9%
Decimal Number 168
 
22.2%
Space Separator 135
 
17.9%
Dash Punctuation 23
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 30
 
7.0%
로 28
 
6.5%
주 27
 
6.3%
시 22
 
5.1%
면 22
 
5.1%
산 21
 
4.9%
무 18
 
4.2%
천 18
 
4.2%
길 18
 
4.2%
구 16
 
3.7%
Other values (77) 210
48.8%
Decimal Number
ValueCountFrequency (%)
1 41
24.4%
2 33
19.6%
3 18
10.7%
6 16
 
9.5%
9 14
 
8.3%
4 13
 
7.7%
7 10
 
6.0%
5 10
 
6.0%
0 8
 
4.8%
8 5
 
3.0%
Space Separator
ValueCountFrequency (%)
135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 430
56.9%
Common 326
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 30
 
7.0%
로 28
 
6.5%
주 27
 
6.3%
시 22
 
5.1%
면 22
 
5.1%
산 21
 
4.9%
무 18
 
4.2%
천 18
 
4.2%
길 18
 
4.2%
구 16
 
3.7%
Other values (77) 210
48.8%
Common
ValueCountFrequency (%)
135
41.4%
1 41
 
12.6%
2 33
 
10.1%
- 23
 
7.1%
3 18
 
5.5%
6 16
 
4.9%
9 14
 
4.3%
4 13
 
4.0%
7 10
 
3.1%
5 10
 
3.1%
Other values (2) 13
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 430
56.9%
ASCII 326
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
41.4%
1 41
 
12.6%
2 33
 
10.1%
- 23
 
7.1%
3 18
 
5.5%
6 16
 
4.9%
9 14
 
4.3%
4 13
 
4.0%
7 10
 
3.1%
5 10
 
3.1%
Other values (2) 13
 
4.0%
Hangul
ValueCountFrequency (%)
군 30
 
7.0%
로 28
 
6.5%
주 27
 
6.3%
시 22
 
5.1%
면 22
 
5.1%
산 21
 
4.9%
무 18
 
4.2%
천 18
 
4.2%
길 18
 
4.2%
구 16
 
3.7%
Other values (77) 210
48.8%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size524.0 B

Correlations

2024-03-14T09:31:02.842675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2
Unnamed: 11.0001.000
Unnamed: 21.0001.000

Missing values

2024-03-14T09:31:01.495310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:31:01.561506image/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

우수숙박시설(굿스테이)현황(2014년6월)Unnamed: 1Unnamed: 2Unnamed: 3
0연번시 설 명소 재 지객실수
1계61개소-1540
21웨스턴호텔군산시 옥서면 선연길 1733
32휴모텔군산시 가도안1길 6140
43세르빌호텔정읍시 내장산로 93740
54산정호텔정읍시 태인면 정읍북로 1291-2037
65그린피아모텔남원시 주천면 제바위길 3633
76지리산칸호텔(구 지리산파크텔)남원시 산내면 지리산로 81564
87운호관광농원부안군 진서면 청자로 44929
98모악산모텔완주군 구이면 모악산길 104-1024
우수숙박시설(굿스테이)현황(2014년6월)Unnamed: 1Unnamed: 2Unnamed: 3
3952왕궁온천장익산시 왕궁면 온천길 3831
4053전주호텔전주시 덕진구 산정2길 3135
4154마이산모텔진안군 진안읍 마이산로 26334
4255덕화리버사이드모텔무주군 무주읍 당산강변로 14634
4356H힐스리조트무주군 무풍면 구천동로 266-752
4457펜션설화무주군 무풍면 구천동로 32313
4558로베펜션무주군 무풍면 라제통문로 45510
4659무주덕유산레저바이크텔무주군 설천면 구천동1로 1296
4760설국펜션무주군 설천면 원삼공2길 9-715
4861타코마장수관광농원장수군 계남면 장수로 2662-1150