Overview

Dataset statistics

Number of variables4
Number of observations118
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory35.1 B

Variable types

Numeric2
Text2

Dataset

Description외국인관광도시민박업현황20167
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201866

Alerts

시 설 명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:29:33.408422
Analysis finished2024-03-14 01:29:33.982603
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

Distinct117
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.745763
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-14T10:29:34.039342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.85
Q129.25
median58.5
Q387.75
95-th percentile111.15
Maximum117
Range116
Interquartile range (IQR)58.5

Descriptive statistics

Standard deviation33.886484
Coefficient of variation (CV)0.57683282
Kurtosis-1.2033368
Mean58.745763
Median Absolute Deviation (MAD)29.5
Skewness0.016863501
Sum6932
Variance1148.2938
MonotonicityIncreasing
2024-03-14T10:29:34.154598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29 2
 
1.7%
1 1
 
0.8%
90 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
Other values (107) 107
90.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%
109 1
0.8%
108 1
0.8%

시 설 명
Text

UNIQUE 

Distinct118
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T10:29:34.414263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11.5
Mean length5.3305085
Min length1

Characters and Unicode

Total characters629
Distinct characters205
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)100.0%

Sample

1st row전주게스트하우스
2nd row해달별
3rd row천년마루
4th row마르타숙소
5th row60-6 게스트하우스
ValueCountFrequency (%)
게스트하우스 13
 
8.8%
전주게스트하우스 2
 
1.4%
아침정원 1
 
0.7%
guest 1
 
0.7%
house 1
 
0.7%
쉼 1
 
0.7%
전주 1
 
0.7%
어린왕자 1
 
0.7%
별헤는집 1
 
0.7%
민트 1
 
0.7%
Other values (125) 125
84.5%
2024-03-14T10:29:34.759472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 66
 
10.5%
하 39
 
6.2%
우 33
 
5.2%
트 31
 
4.9%
30
 
4.8%
게 29
 
4.6%
전 10
 
1.6%
이 9
 
1.4%
주 8
 
1.3%
마 8
 
1.3%
Other values (195) 366
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 564
89.7%
Space Separator 30
 
4.8%
Lowercase Letter 15
 
2.4%
Uppercase Letter 8
 
1.3%
Decimal Number 7
 
1.1%
Other Punctuation 2
 
0.3%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 66
 
11.7%
하 39
 
6.9%
우 33
 
5.9%
트 31
 
5.5%
게 29
 
5.1%
전 10
 
1.8%
이 9
 
1.6%
주 8
 
1.4%
마 8
 
1.4%
한 6
 
1.1%
Other values (170) 325
57.6%
Lowercase Letter
ValueCountFrequency (%)
e 3
20.0%
n 2
13.3%
s 2
13.3%
u 2
13.3%
i 1
 
6.7%
d 1
 
6.7%
a 1
 
6.7%
r 1
 
6.7%
o 1
 
6.7%
t 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
G 2
25.0%
J 2
25.0%
P 2
25.0%
H 1
12.5%
D 1
12.5%
Decimal Number
ValueCountFrequency (%)
3 3
42.9%
6 2
28.6%
2 1
 
14.3%
0 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
& 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 564
89.7%
Common 42
 
6.7%
Latin 23
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 66
 
11.7%
하 39
 
6.9%
우 33
 
5.9%
트 31
 
5.5%
게 29
 
5.1%
전 10
 
1.8%
이 9
 
1.6%
주 8
 
1.4%
마 8
 
1.4%
한 6
 
1.1%
Other values (170) 325
57.6%
Latin
ValueCountFrequency (%)
e 3
13.0%
n 2
 
8.7%
G 2
 
8.7%
s 2
 
8.7%
u 2
 
8.7%
J 2
 
8.7%
P 2
 
8.7%
i 1
 
4.3%
d 1
 
4.3%
a 1
 
4.3%
Other values (5) 5
21.7%
Common
ValueCountFrequency (%)
30
71.4%
3 3
 
7.1%
6 2
 
4.8%
( 1
 
2.4%
2 1
 
2.4%
) 1
 
2.4%
& 1
 
2.4%
, 1
 
2.4%
- 1
 
2.4%
0 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 564
89.7%
ASCII 65
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 66
 
11.7%
하 39
 
6.9%
우 33
 
5.9%
트 31
 
5.5%
게 29
 
5.1%
전 10
 
1.8%
이 9
 
1.6%
주 8
 
1.4%
마 8
 
1.4%
한 6
 
1.1%
Other values (170) 325
57.6%
ASCII
ValueCountFrequency (%)
30
46.2%
3 3
 
4.6%
e 3
 
4.6%
n 2
 
3.1%
6 2
 
3.1%
G 2
 
3.1%
s 2
 
3.1%
u 2
 
3.1%
J 2
 
3.1%
P 2
 
3.1%
Other values (15) 15
23.1%

소 재 지
Text

Distinct117
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-14T10:29:35.041312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length21.957627
Min length15

Characters and Unicode

Total characters2591
Distinct characters104
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

Unique116 ?
Unique (%)98.3%

Sample

1st row전주시 완산구 경기전길 44 (경원동2가)
2nd row전주시 완산구 어진길 33-9 (풍남동3가)
3rd row전주시 완산구 경기전길 186 (교동)
4th row전주시 완산구 오목대길 52 (교동)
5th row전주시 완산구 오목대길 49-1 (교동)
ValueCountFrequency (%)
전주시 100
 
18.0%
완산구 96
 
17.3%
교동 28
 
5.0%
군산시 17
 
3.1%
풍남동3가 12
 
2.2%
경원동2가 10
 
1.8%
향교길 9
 
1.6%
서서학동 7
 
1.3%
오목대길 7
 
1.3%
어진길 7
 
1.3%
Other values (185) 262
47.2%
2024-03-14T10:29:35.530202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
437
 
16.9%
전 134
 
5.2%
동 134
 
5.2%
시 118
 
4.6%
산 115
 
4.4%
구 112
 
4.3%
주 108
 
4.2%
( 107
 
4.1%
) 107
 
4.1%
완 97
 
3.7%
Other values (94) 1122
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1436
55.4%
Space Separator 437
 
16.9%
Decimal Number 428
 
16.5%
Open Punctuation 107
 
4.1%
Close Punctuation 107
 
4.1%
Dash Punctuation 75
 
2.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 134
 
9.3%
동 134
 
9.3%
시 118
 
8.2%
산 115
 
8.0%
구 112
 
7.8%
주 108
 
7.5%
완 97
 
6.8%
길 81
 
5.6%
가 43
 
3.0%
교 39
 
2.7%
Other values (79) 455
31.7%
Decimal Number
ValueCountFrequency (%)
1 95
22.2%
2 68
15.9%
3 66
15.4%
5 39
9.1%
4 32
 
7.5%
6 29
 
6.8%
8 26
 
6.1%
9 25
 
5.8%
0 25
 
5.8%
7 23
 
5.4%
Space Separator
ValueCountFrequency (%)
437
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1436
55.4%
Common 1155
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 134
 
9.3%
동 134
 
9.3%
시 118
 
8.2%
산 115
 
8.0%
구 112
 
7.8%
주 108
 
7.5%
완 97
 
6.8%
길 81
 
5.6%
가 43
 
3.0%
교 39
 
2.7%
Other values (79) 455
31.7%
Common
ValueCountFrequency (%)
437
37.8%
( 107
 
9.3%
) 107
 
9.3%
1 95
 
8.2%
- 75
 
6.5%
2 68
 
5.9%
3 66
 
5.7%
5 39
 
3.4%
4 32
 
2.8%
6 29
 
2.5%
Other values (5) 100
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1436
55.4%
ASCII 1155
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
437
37.8%
( 107
 
9.3%
) 107
 
9.3%
1 95
 
8.2%
- 75
 
6.5%
2 68
 
5.9%
3 66
 
5.7%
5 39
 
3.4%
4 32
 
2.8%
6 29
 
2.5%
Other values (5) 100
 
8.7%
Hangul
ValueCountFrequency (%)
전 134
 
9.3%
동 134
 
9.3%
시 118
 
8.2%
산 115
 
8.0%
구 112
 
7.8%
주 108
 
7.5%
완 97
 
6.8%
길 81
 
5.6%
가 43
 
3.0%
교 39
 
2.7%
Other values (79) 455
31.7%

객 실 수
Real number (ℝ)

Distinct9
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.279661
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-14T10:29:35.629296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q36
95-th percentile7
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8576964
Coefficient of variation (CV)0.43407559
Kurtosis-0.38888733
Mean4.279661
Median Absolute Deviation (MAD)1
Skewness0.41995399
Sum505
Variance3.4510358
MonotonicityNot monotonic
2024-03-14T10:29:35.711103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 28
23.7%
2 22
18.6%
6 17
14.4%
3 17
14.4%
5 16
13.6%
7 10
 
8.5%
9 3
 
2.5%
1 3
 
2.5%
8 2
 
1.7%
ValueCountFrequency (%)
1 3
 
2.5%
2 22
18.6%
3 17
14.4%
4 28
23.7%
5 16
13.6%
6 17
14.4%
7 10
 
8.5%
8 2
 
1.7%
9 3
 
2.5%
ValueCountFrequency (%)
9 3
 
2.5%
8 2
 
1.7%
7 10
 
8.5%
6 17
14.4%
5 16
13.6%
4 28
23.7%
3 17
14.4%
2 22
18.6%
1 3
 
2.5%

Interactions

2024-03-14T10:29:33.735707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:29:33.576066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:29:33.805642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:29:33.649750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:29:35.786830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객 실 수
연번1.0000.174
객 실 수0.1741.000
2024-03-14T10:29:35.876474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객 실 수
연번1.0000.049
객 실 수0.0491.000

Missing values

2024-03-14T10:29:33.895277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:29:33.957415image/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

연번시 설 명소 재 지객 실 수
01전주게스트하우스전주시 완산구 경기전길 44 (경원동2가)6
12해달별전주시 완산구 어진길 33-9 (풍남동3가)3
23천년마루전주시 완산구 경기전길 186 (교동)4
34마르타숙소전주시 완산구 오목대길 52 (교동)3
4560-6 게스트하우스전주시 완산구 오목대길 49-1 (교동)4
56해밀전주시 완산구 향교길 19-23 (전동)6
67별빛향전주시 완산구 오목대길 27-21 (교동)3
78초정전주시 완산구 향교길 88 (교동)3
89향기나무전주시 완산구 향교길 68 (교동)5
910꽃담전주시 완산구 어진길 38-4 (풍남동2가)3
연번시 설 명소 재 지객 실 수
108108게스트하우스 이웃군산시 구영1길 11-2(신흥동)6
109109하늘군산시 구영3길 72(신창동)4
110110산들 게스트하우스군산시 동국사길 7-3(월명동)6
111111게스트하우스 소설여행군산시 월명로 516-1(신흥동)2
112112다락군산시 절골길 12-4(신흥동)4
113113다호군산시 구영7길 101(영화동)9
114114달군산시 구영3길 21-2(월명동)5
115115나무게스트하우스전라북도 군산시 월명동 22-294
116116행복을 꿈꾸는 게스트하우스군산시 구영7길 7(월명동)8
117117무아게스트하우스남원시 요천로 1501-10(쌍교동)4