Overview

Dataset statistics

Number of variables16
Number of observations167
Missing cells1672
Missing cells (%)62.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.8 KiB
Average record size in memory139.8 B

Variable types

Text2
Categorical3
Unsupported10
Numeric1

Dataset

Description전라북도_민박펜션업소_2017930
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202950

Alerts

데이터기준일자 has constant value ""Constant
업종명 is highly overall correlated with 객실수 and 1 other fieldsHigh correlation
서비스대상구분 is highly overall correlated with 객실수 and 1 other fieldsHigh correlation
객실수 is highly overall correlated with 업종명 and 1 other fieldsHigh correlation
외국어안내서비스 has 167 (100.0%) missing valuesMissing
소재지지번주소 has 167 (100.0%) missing valuesMissing
전화번호 has 167 (100.0%) missing valuesMissing
부대시설 has 167 (100.0%) missing valuesMissing
주차장보유여부 has 167 (100.0%) missing valuesMissing
결제방법 has 167 (100.0%) missing valuesMissing
홈페이지주소 has 167 (100.0%) missing valuesMissing
주변관광정보 has 167 (100.0%) missing valuesMissing
위도 has 167 (100.0%) missing valuesMissing
경도 has 167 (100.0%) missing valuesMissing
업소명 has unique valuesUnique
외국어안내서비스 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
부대시설 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주차장보유여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
결제방법 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주변관광정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
위도 is an unsupported type, check if it needs cleaning or further analysisUnsupported
경도 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 03:04:59.563240
Analysis finished2024-03-14 03:05:00.220815
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct167
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-14T12:05:00.430536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length5.7305389
Min length1

Characters and Unicode

Total characters957
Distinct characters255
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)100.0%

Sample

1st row구름채펜션
2nd row펜션무주네버랜드
3rd row리틀프로망스
4th row리틀프린스
5th row설인펜션
ValueCountFrequency (%)
게스트하우스 21
 
9.8%
집 2
 
0.9%
전주게스트하우스 2
 
0.9%
가득한 2
 
0.9%
소설여행 2
 
0.9%
구름채펜션 1
 
0.5%
옥상달빛 1
 
0.5%
소담소담 1
 
0.5%
앤 1
 
0.5%
쵸코 1
 
0.5%
Other values (181) 181
84.2%
2024-03-14T12:05:00.894187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 98
 
10.2%
하 53
 
5.5%
우 48
 
5.0%
47
 
4.9%
트 46
 
4.8%
게 42
 
4.4%
리 19
 
2.0%
펜 15
 
1.6%
션 15
 
1.6%
이 14
 
1.5%
Other values (245) 560
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 869
90.8%
Space Separator 47
 
4.9%
Lowercase Letter 15
 
1.6%
Decimal Number 8
 
0.8%
Uppercase Letter 8
 
0.8%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Other Punctuation 2
 
0.2%
Control 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 98
 
11.3%
하 53
 
6.1%
우 48
 
5.5%
트 46
 
5.3%
게 42
 
4.8%
리 19
 
2.2%
펜 15
 
1.7%
션 15
 
1.7%
이 14
 
1.6%
주 10
 
1.2%
Other values (219) 509
58.6%
Lowercase Letter
ValueCountFrequency (%)
e 3
20.0%
s 2
13.3%
u 2
13.3%
n 2
13.3%
i 1
 
6.7%
d 1
 
6.7%
t 1
 
6.7%
o 1
 
6.7%
a 1
 
6.7%
r 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
25.0%
G 2
25.0%
J 2
25.0%
D 1
12.5%
H 1
12.5%
Decimal Number
ValueCountFrequency (%)
3 3
37.5%
6 2
25.0%
2 2
25.0%
0 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
& 1
50.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 869
90.8%
Common 65
 
6.8%
Latin 23
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 98
 
11.3%
하 53
 
6.1%
우 48
 
5.5%
트 46
 
5.3%
게 42
 
4.8%
리 19
 
2.2%
펜 15
 
1.7%
션 15
 
1.7%
이 14
 
1.6%
주 10
 
1.2%
Other values (219) 509
58.6%
Latin
ValueCountFrequency (%)
e 3
13.0%
s 2
 
8.7%
u 2
 
8.7%
P 2
 
8.7%
n 2
 
8.7%
G 2
 
8.7%
J 2
 
8.7%
D 1
 
4.3%
i 1
 
4.3%
d 1
 
4.3%
Other values (5) 5
21.7%
Common
ValueCountFrequency (%)
47
72.3%
) 3
 
4.6%
( 3
 
4.6%
3 3
 
4.6%
6 2
 
3.1%
2 2
 
3.1%
, 1
 
1.5%
& 1
 
1.5%
1
 
1.5%
- 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 869
90.8%
ASCII 88
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 98
 
11.3%
하 53
 
6.1%
우 48
 
5.5%
트 46
 
5.3%
게 42
 
4.8%
리 19
 
2.2%
펜 15
 
1.7%
션 15
 
1.7%
이 14
 
1.6%
주 10
 
1.2%
Other values (219) 509
58.6%
ASCII
ValueCountFrequency (%)
47
53.4%
) 3
 
3.4%
( 3
 
3.4%
e 3
 
3.4%
3 3
 
3.4%
s 2
 
2.3%
u 2
 
2.3%
P 2
 
2.3%
n 2
 
2.3%
G 2
 
2.3%
Other values (16) 19
21.6%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
민박
138 
펜션
29 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row펜션
2nd row펜션
3rd row펜션
4th row펜션
5th row펜션

Common Values

ValueCountFrequency (%)
민박 138
82.6%
펜션 29
 
17.4%

Length

2024-03-14T12:05:01.003860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:05:01.085329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민박 138
82.6%
펜션 29
 
17.4%

서비스대상구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
외국인
138 
내국인+외국인
29 

Length

Max length7
Median length3
Mean length3.6946108
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내국인+외국인
2nd row내국인+외국인
3rd row내국인+외국인
4th row내국인+외국인
5th row내국인+외국인

Common Values

ValueCountFrequency (%)
외국인 138
82.6%
내국인+외국인 29
 
17.4%

Length

2024-03-14T12:05:01.177172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:05:01.279134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인 138
82.6%
내국인+외국인 29
 
17.4%

외국어안내서비스
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

소재지도로명주소
Text

Distinct165
Distinct (%)99.4%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2024-03-14T12:05:01.512146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25.5
Mean length21.216867
Min length15

Characters and Unicode

Total characters3522
Distinct characters131
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

Unique164 ?
Unique (%)98.8%

Sample

1st row전라북도 무주군 설천면 구천동로962
2nd row전라북도 무주군 설천면 구천동로289-55
3rd row전라북도 무주군 설천면 구천동로930-8
4th row전라북도 무주군 설천면 만선로34-1
5th row전라북도 무주군 설천면 삼공2길4
ValueCountFrequency (%)
전라북도 165
21.1%
전주시 114
 
14.6%
완산구 107
 
13.7%
군산시 22
 
2.8%
무주군 19
 
2.4%
설천면 17
 
2.2%
향교길 10
 
1.3%
오목대길 7
 
0.9%
경기전길 7
 
0.9%
어진길 7
 
0.9%
Other values (226) 306
39.2%
2024-03-14T12:05:01.961104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
706
20.0%
전 303
 
8.6%
라 168
 
4.8%
북 165
 
4.7%
도 165
 
4.7%
산 143
 
4.1%
시 142
 
4.0%
주 140
 
4.0%
구 136
 
3.9%
길 114
 
3.2%
Other values (121) 1340
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2190
62.2%
Space Separator 706
 
20.0%
Decimal Number 535
 
15.2%
Dash Punctuation 87
 
2.5%
Uppercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 303
13.8%
라 168
 
7.7%
북 165
 
7.5%
도 165
 
7.5%
산 143
 
6.5%
시 142
 
6.5%
주 140
 
6.4%
구 136
 
6.2%
길 114
 
5.2%
완 109
 
5.0%
Other values (105) 605
27.6%
Decimal Number
ValueCountFrequency (%)
1 114
21.3%
2 77
14.4%
3 67
12.5%
5 53
9.9%
4 44
 
8.2%
6 43
 
8.0%
8 37
 
6.9%
9 34
 
6.4%
7 33
 
6.2%
0 33
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2190
62.2%
Common 1329
37.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 303
13.8%
라 168
 
7.7%
북 165
 
7.5%
도 165
 
7.5%
산 143
 
6.5%
시 142
 
6.5%
주 140
 
6.4%
구 136
 
6.2%
길 114
 
5.2%
완 109
 
5.0%
Other values (105) 605
27.6%
Common
ValueCountFrequency (%)
706
53.1%
1 114
 
8.6%
- 87
 
6.5%
2 77
 
5.8%
3 67
 
5.0%
5 53
 
4.0%
4 44
 
3.3%
6 43
 
3.2%
8 37
 
2.8%
9 34
 
2.6%
Other values (3) 67
 
5.0%
Latin
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2190
62.2%
ASCII 1332
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
706
53.0%
1 114
 
8.6%
- 87
 
6.5%
2 77
 
5.8%
3 67
 
5.0%
5 53
 
4.0%
4 44
 
3.3%
6 43
 
3.2%
8 37
 
2.8%
9 34
 
2.6%
Other values (6) 70
 
5.3%
Hangul
ValueCountFrequency (%)
전 303
13.8%
라 168
 
7.7%
북 165
 
7.5%
도 165
 
7.5%
산 143
 
6.5%
시 142
 
6.5%
주 140
 
6.4%
구 136
 
6.2%
길 114
 
5.2%
완 109
 
5.0%
Other values (105) 605
27.6%

소재지지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

객실수
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)11.4%
Missing1
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean5.4578313
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-03-14T12:05:02.117146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q36
95-th percentile15.5
Maximum27
Range26
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.725947
Coefficient of variation (CV)0.86590198
Kurtosis8.6691969
Mean5.4578313
Median Absolute Deviation (MAD)2
Skewness2.7842477
Sum906
Variance22.334575
MonotonicityNot monotonic
2024-03-14T12:05:02.240049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4 33
19.8%
2 29
17.4%
3 22
13.2%
5 20
12.0%
6 19
11.4%
7 11
 
6.6%
1 7
 
4.2%
8 6
 
3.6%
9 5
 
3.0%
27 2
 
1.2%
Other values (9) 12
 
7.2%
ValueCountFrequency (%)
1 7
 
4.2%
2 29
17.4%
3 22
13.2%
4 33
19.8%
5 20
12.0%
6 19
11.4%
7 11
 
6.6%
8 6
 
3.6%
9 5
 
3.0%
10 2
 
1.2%
ValueCountFrequency (%)
27 2
1.2%
25 1
0.6%
24 1
0.6%
22 2
1.2%
19 1
0.6%
17 1
0.6%
16 1
0.6%
14 2
1.2%
12 1
0.6%
10 2
1.2%

부대시설
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

주차장보유여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

결제방법
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

홈페이지주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

주변관광정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

위도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

경도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing167
Missing (%)100.0%
Memory size1.6 KiB

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2017-09-30
167 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-09-30
2nd row2017-09-30
3rd row2017-09-30
4th row2017-09-30
5th row2017-09-30

Common Values

ValueCountFrequency (%)
2017-09-30 167
100.0%

Length

2024-03-14T12:05:02.368454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T12:05:02.477071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-09-30 167
100.0%

Interactions

2024-03-14T12:04:59.818801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T12:05:02.556166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명서비스대상구분객실수
업종명1.0000.9990.632
서비스대상구분0.9991.0000.632
객실수0.6320.6321.000
2024-03-14T12:05:02.667460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명서비스대상구분
업종명1.0000.979
서비스대상구분0.9791.000
2024-03-14T12:05:02.766781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수업종명서비스대상구분
객실수1.0000.6250.625
업종명0.6251.0000.979
서비스대상구분0.6250.9791.000

Missing values

2024-03-14T12:04:59.926517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:05:00.081858image/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.
2024-03-14T12:05:00.184347image/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

업소명업종명서비스대상구분외국어안내서비스소재지도로명주소소재지지번주소전화번호객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보위도경도데이터기준일자
0구름채펜션펜션내국인+외국인<NA>전라북도 무주군 설천면 구천동로962<NA><NA>8<NA><NA><NA><NA><NA><NA><NA>2017-09-30
1펜션무주네버랜드펜션내국인+외국인<NA>전라북도 무주군 설천면 구천동로289-55<NA><NA>8<NA><NA><NA><NA><NA><NA><NA>2017-09-30
2리틀프로망스펜션내국인+외국인<NA>전라북도 무주군 설천면 구천동로930-8<NA><NA>17<NA><NA><NA><NA><NA><NA><NA>2017-09-30
3리틀프린스펜션내국인+외국인<NA>전라북도 무주군 설천면 만선로34-1<NA><NA>10<NA><NA><NA><NA><NA><NA><NA>2017-09-30
4설인펜션펜션내국인+외국인<NA>전라북도 무주군 설천면 삼공2길4<NA><NA>19<NA><NA><NA><NA><NA><NA><NA>2017-09-30
5눈꽃여행펜션내국인+외국인<NA>전라북도 무주군 설천면 내배방길22<NA><NA>14<NA><NA><NA><NA><NA><NA><NA>2017-09-30
6마법의성펜션내국인+외국인<NA>전라북도 무주군 설천면 내배방길27-1<NA><NA>4<NA><NA><NA><NA><NA><NA><NA>2017-09-30
7미알레펜션펜션내국인+외국인<NA>전라북도 무주군 무풍면 오두재로96<NA><NA>14<NA><NA><NA><NA><NA><NA><NA>2017-09-30
8한마음콘도펜션내국인+외국인<NA>전라북도 무주군 설천면 외배방길21<NA><NA>12<NA><NA><NA><NA><NA><NA><NA>2017-09-30
9스노우밸리펜션펜션내국인+외국인<NA>전라북도 무주군 설천면 만선로36-37<NA><NA>22<NA><NA><NA><NA><NA><NA><NA>2017-09-30
업소명업종명서비스대상구분외국어안내서비스소재지도로명주소소재지지번주소전화번호객실수부대시설주차장보유여부결제방법홈페이지주소주변관광정보위도경도데이터기준일자
157달민박외국인<NA>전라북도 군산시 구영3길 21-2<NA><NA>5<NA><NA><NA><NA><NA><NA><NA>2017-09-30
158나무게스트하우스민박외국인<NA>전라북도 군산시 월명영3길 9<NA><NA>4<NA><NA><NA><NA><NA><NA><NA>2017-09-30
159행복을 꿈꾸는 게스트하우스민박외국인<NA>전라북도 군산시 구영7길 7<NA><NA>8<NA><NA><NA><NA><NA><NA><NA>2017-09-30
160국일모던 게스트하우스민박외국인<NA>전라북도 군산시 중앙로 183<NA><NA>3<NA><NA><NA><NA><NA><NA><NA>2017-09-30
161게스트하우스 여정민박외국인<NA>전라북도 군산시 구영2길 25<NA><NA>6<NA><NA><NA><NA><NA><NA><NA>2017-09-30
162게스트하우스 동국민박외국인<NA>전라북도 군산시 동국사길 7<NA><NA>7<NA><NA><NA><NA><NA><NA><NA>2017-09-30
163게스트하우스 책방민박외국인<NA>전라북도 군산시 구영5길 100<NA><NA>10<NA><NA><NA><NA><NA><NA><NA>2017-09-30
164게스트하우스 이당민박외국인<NA>전라북도 군산시 구영6길 108 3층<NA><NA>8<NA><NA><NA><NA><NA><NA><NA>2017-09-30
165소설여행 2호점민박외국인<NA>전라북도 군산시 절골길 6 2층<NA><NA>2<NA><NA><NA><NA><NA><NA><NA>2017-09-30
166무아게스트하우스민박외국인<NA>전라북도 남원시 요천로 1501-10<NA><NA>4<NA><NA><NA><NA><NA><NA><NA>2017-09-30