Overview

Dataset statistics

Number of variables7
Number of observations25
Missing cells9
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory63.3 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description제주특별자치도 서귀포시 관내 휴양업에 관한 데이터로 구분, 상호명, 소재지, 연락처, 위도, 경도 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15056050/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 is highly imbalanced (75.8%)Imbalance
연락처 has 9 (36.0%) missing valuesMissing
상호명 has unique valuesUnique
소재지 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:23:36.426743
Analysis finished2024-04-21 01:23:39.106112
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
전문휴양업
24 
종합휴양업
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row종합휴양업
2nd row전문휴양업
3rd row전문휴양업
4th row전문휴양업
5th row전문휴양업

Common Values

ValueCountFrequency (%)
전문휴양업 24
96.0%
종합휴양업 1
 
4.0%

Length

2024-04-21T10:23:39.171090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:23:39.262311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문휴양업 24
96.0%
종합휴양업 1
 
4.0%

상호명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-21T10:23:39.430621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.56
Min length3

Characters and Unicode

Total characters214
Distinct characters104
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

Unique25 ?
Unique (%)100.0%

Sample

1st row휘닉스제주섭지코지
2nd row삼매봉밸리 유원지개발사업
3rd row야크마을
4th row루체빌리조트
5th row(주)꿈
ValueCountFrequency (%)
주식회사 2
 
5.4%
휘닉스제주섭지코지 1
 
2.7%
더베니스랜드 1
 
2.7%
제주해양과학관 1
 
2.7%
상효원 1
 
2.7%
박물관은 1
 
2.7%
살아있다 1
 
2.7%
제주허브동산 1
 
2.7%
세계성문화박물관 1
 
2.7%
제주민속촌 1
 
2.7%
Other values (26) 26
70.3%
2024-04-21T10:23:39.758333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 15
 
7.0%
12
 
5.6%
관 9
 
4.2%
물 8
 
3.7%
박 7
 
3.3%
제 7
 
3.3%
지 6
 
2.8%
리 6
 
2.8%
( 5
 
2.3%
) 5
 
2.3%
Other values (94) 134
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
89.7%
Space Separator 12
 
5.6%
Open Punctuation 5
 
2.3%
Close Punctuation 5
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 15
 
7.8%
관 9
 
4.7%
물 8
 
4.2%
박 7
 
3.6%
제 7
 
3.6%
지 6
 
3.1%
리 6
 
3.1%
식 4
 
2.1%
사 4
 
2.1%
회 3
 
1.6%
Other values (91) 123
64.1%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
89.7%
Common 22
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 15
 
7.8%
관 9
 
4.7%
물 8
 
4.2%
박 7
 
3.6%
제 7
 
3.6%
지 6
 
3.1%
리 6
 
3.1%
식 4
 
2.1%
사 4
 
2.1%
회 3
 
1.6%
Other values (91) 123
64.1%
Common
ValueCountFrequency (%)
12
54.5%
( 5
22.7%
) 5
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
89.7%
ASCII 22
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 15
 
7.8%
관 9
 
4.7%
물 8
 
4.2%
박 7
 
3.6%
제 7
 
3.6%
지 6
 
3.1%
리 6
 
3.1%
식 4
 
2.1%
사 4
 
2.1%
회 3
 
1.6%
Other values (91) 123
64.1%
ASCII
ValueCountFrequency (%)
12
54.5%
( 5
22.7%
) 5
22.7%

소재지
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-21T10:23:39.944870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length25.72
Min length21

Characters and Unicode

Total characters643
Distinct characters69
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

Unique25 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 서귀포시 성산읍 섭지코지로 93-66
2nd row제주특별자치도 서귀포시 호근동 2163
3rd row제주특별자치도 서귀포시 색달동 1045
4th row제주특별자치도 서귀포시 안덕면 상천리 산 78-1 루체빌리조트
5th row제주특별자치도 서귀포시 안덕면 상창리 79번지
ValueCountFrequency (%)
제주특별자치도 25
21.7%
서귀포시 25
21.7%
성산읍 5
 
4.3%
색달동 5
 
4.3%
안덕면 4
 
3.5%
산 2
 
1.7%
표선면 2
 
1.7%
표선리 2
 
1.7%
상예동 2
 
1.7%
고성리 2
 
1.7%
Other values (39) 41
35.7%
2024-04-21T10:23:40.292603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
17.7%
포 26
 
4.0%
제 25
 
3.9%
주 25
 
3.9%
시 25
 
3.9%
서 25
 
3.9%
귀 25
 
3.9%
도 25
 
3.9%
치 25
 
3.9%
자 25
 
3.9%
Other values (59) 303
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 422
65.6%
Space Separator 114
 
17.7%
Decimal Number 97
 
15.1%
Dash Punctuation 10
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 26
 
6.2%
제 25
 
5.9%
주 25
 
5.9%
시 25
 
5.9%
서 25
 
5.9%
귀 25
 
5.9%
도 25
 
5.9%
치 25
 
5.9%
자 25
 
5.9%
별 25
 
5.9%
Other values (47) 171
40.5%
Decimal Number
ValueCountFrequency (%)
1 16
16.5%
2 16
16.5%
0 14
14.4%
4 10
10.3%
9 8
8.2%
3 8
8.2%
6 7
7.2%
5 7
7.2%
8 6
 
6.2%
7 5
 
5.2%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 422
65.6%
Common 221
34.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 26
 
6.2%
제 25
 
5.9%
주 25
 
5.9%
시 25
 
5.9%
서 25
 
5.9%
귀 25
 
5.9%
도 25
 
5.9%
치 25
 
5.9%
자 25
 
5.9%
별 25
 
5.9%
Other values (47) 171
40.5%
Common
ValueCountFrequency (%)
114
51.6%
1 16
 
7.2%
2 16
 
7.2%
0 14
 
6.3%
- 10
 
4.5%
4 10
 
4.5%
9 8
 
3.6%
3 8
 
3.6%
6 7
 
3.2%
5 7
 
3.2%
Other values (2) 11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 422
65.6%
ASCII 221
34.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
51.6%
1 16
 
7.2%
2 16
 
7.2%
0 14
 
6.3%
- 10
 
4.5%
4 10
 
4.5%
9 8
 
3.6%
3 8
 
3.6%
6 7
 
3.2%
5 7
 
3.2%
Other values (2) 11
 
5.0%
Hangul
ValueCountFrequency (%)
포 26
 
6.2%
제 25
 
5.9%
주 25
 
5.9%
시 25
 
5.9%
서 25
 
5.9%
귀 25
 
5.9%
도 25
 
5.9%
치 25
 
5.9%
자 25
 
5.9%
별 25
 
5.9%
Other values (47) 171
40.5%

연락처
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing9
Missing (%)36.0%
Memory size332.0 B
2024-04-21T10:23:40.473299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.0625
Min length12

Characters and Unicode

Total characters193
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)100.0%

Sample

1st row064-731-7000
2nd row064-802-5155
3rd row070-8147-3311
4th row064-792-6262
5th row064-792-5700
ValueCountFrequency (%)
064-784-6565 1
 
6.2%
064-802-5155 1
 
6.2%
070-8147-3311 1
 
6.2%
064-792-6262 1
 
6.2%
064-792-5700 1
 
6.2%
064-738-2888 1
 
6.2%
064-702-9809 1
 
6.2%
064-780-0966 1
 
6.2%
064-731-7000 1
 
6.2%
064-733-2200 1
 
6.2%
Other values (6) 6
37.5%
2024-04-21T10:23:40.793015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
17.6%
- 32
16.6%
6 24
12.4%
4 19
9.8%
7 19
9.8%
3 13
 
6.7%
8 11
 
5.7%
5 11
 
5.7%
1 11
 
5.7%
2 10
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 161
83.4%
Dash Punctuation 32
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
21.1%
6 24
14.9%
4 19
11.8%
7 19
11.8%
3 13
 
8.1%
8 11
 
6.8%
5 11
 
6.8%
1 11
 
6.8%
2 10
 
6.2%
9 9
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
17.6%
- 32
16.6%
6 24
12.4%
4 19
9.8%
7 19
9.8%
3 13
 
6.7%
8 11
 
5.7%
5 11
 
5.7%
1 11
 
5.7%
2 10
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
17.6%
- 32
16.6%
6 24
12.4%
4 19
9.8%
7 19
9.8%
3 13
 
6.7%
8 11
 
5.7%
5 11
 
5.7%
1 11
 
5.7%
2 10
 
5.2%

위도
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.302354
Minimum33.23998
Maximum33.439873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-21T10:23:40.928107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.23998
5-th percentile33.24216
Q133.250299
median33.278974
Q333.321284
95-th percentile33.434144
Maximum33.439873
Range0.19989324
Interquartile range (IQR)0.0709856

Descriptive statistics

Standard deviation0.066718998
Coefficient of variation (CV)0.0020034319
Kurtosis-0.025094296
Mean33.302354
Median Absolute Deviation (MAD)0.03150558
Skewness1.1362233
Sum832.55885
Variance0.0044514247
MonotonicityNot monotonic
2024-04-21T10:23:41.057391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
33.43264796 1
 
4.0%
33.2434506 1
 
4.0%
33.27897351 1
 
4.0%
33.25471434 1
 
4.0%
33.25029877 1
 
4.0%
33.38500018 1
 
4.0%
33.23997954 1
 
4.0%
33.25029333 1
 
4.0%
33.32128437 1
 
4.0%
33.24746793 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
33.23997954 1
4.0%
33.24183775 1
4.0%
33.2434506 1
4.0%
33.24384628 1
4.0%
33.24746793 1
4.0%
33.25029333 1
4.0%
33.25029877 1
4.0%
33.25471434 1
4.0%
33.25471494 1
4.0%
33.25490241 1
4.0%
ValueCountFrequency (%)
33.43987278 1
4.0%
33.4345174 1
4.0%
33.43264796 1
4.0%
33.41539306 1
4.0%
33.38500018 1
4.0%
33.32912309 1
4.0%
33.32128437 1
4.0%
33.31987799 1
4.0%
33.30721311 1
4.0%
33.29064522 1
4.0%

경도
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0536403 × 108
Minimum126.32219
Maximum1.2634098 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-21T10:23:41.183153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.32219
5-th percentile126.34745
Q1126.41216
median126.50763
Q3126.83986
95-th percentile126.92934
Maximum1.2634098 × 1010
Range1.2634098 × 1010
Interquartile range (IQR)0.4276951

Descriptive statistics

Standard deviation2.5268195 × 109
Coefficient of variation (CV)4.9999987
Kurtosis25
Mean5.0536403 × 108
Median Absolute Deviation (MAD)0.1224634
Skewness5
Sum1.2634101 × 1010
Variance6.3848169 × 1018
MonotonicityNot monotonic
2024-04-21T10:23:41.319602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.9301741 1
 
4.0%
126.5383574 1
 
4.0%
126.394232 1
 
4.0%
126.4176502 1
 
4.0%
126.4121607 1
 
4.0%
126.8398558 1
 
4.0%
126.4288163 1
 
4.0%
126.5360116 1
 
4.0%
126.8430839 1
 
4.0%
126.5076344 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
126.3221948 1
4.0%
126.3462897 1
4.0%
126.3520863 1
4.0%
126.3701538 1
4.0%
126.385171 1
4.0%
126.394232 1
4.0%
126.4121607 1
4.0%
126.414509 1
4.0%
126.4169561 1
4.0%
126.4176502 1
4.0%
ValueCountFrequency (%)
12634097703.0 1
4.0%
126.9301741 1
4.0%
126.9260242 1
4.0%
126.899212 1
4.0%
126.8430839 1
4.0%
126.8406996 1
4.0%
126.8398558 1
4.0%
126.8147216 1
4.0%
126.5860119 1
4.0%
126.5557576 1
4.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-12
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-12
2nd row2024-04-12
3rd row2024-04-12
4th row2024-04-12
5th row2024-04-12

Common Values

ValueCountFrequency (%)
2024-04-12 25
100.0%

Length

2024-04-21T10:23:41.451747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:23:41.548778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-12 25
100.0%

Interactions

2024-04-21T10:23:38.723502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:23:38.496027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:23:38.803036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:23:38.635954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:23:41.613911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상호명소재지연락처위도경도
구분1.0001.0001.0001.0000.2510.000
상호명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000NaN
위도0.2511.0001.0001.0001.0000.000
경도0.0001.0001.000NaN0.0001.000
2024-04-21T10:23:41.705503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도구분
위도1.0000.4410.120
경도0.4411.0000.000
구분0.1200.0001.000

Missing values

2024-04-21T10:23:38.922158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:23:39.049753image/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

구분상호명소재지연락처위도경도데이터기준일자
0종합휴양업휘닉스제주섭지코지제주특별자치도 서귀포시 성산읍 섭지코지로 93-66064-731-700033.432648126.9301742024-04-12
1전문휴양업삼매봉밸리 유원지개발사업제주특별자치도 서귀포시 호근동 2163<NA>33.243451126.5383572024-04-12
2전문휴양업야크마을제주특별자치도 서귀포시 색달동 1045<NA>33.26941126.4169562024-04-12
3전문휴양업루체빌리조트제주특별자치도 서귀포시 안덕면 상천리 산 78-1 루체빌리조트064-802-515533.319878126.3851712024-04-12
4전문휴양업(주)꿈제주특별자치도 서귀포시 안덕면 상창리 79번지070-8147-331133.290645126.3221952024-04-12
5전문휴양업제주커피박물관 바움제주특별자치도 서귀포시 성산읍 고성리 2040-1번지<NA>33.439873126.8992122024-04-12
6전문휴양업제주유리박물관제주특별자치도 서귀포시 상예동 4303번지064-792-626233.278516126.3701542024-04-12
7전문휴양업건강과 성 박물관제주특별자치도 서귀포시 안덕면 감산리 1405번지064-792-570033.254715126.346292024-04-12
8전문휴양업주식회사 호반호텔앤리조트제주특별자치도 서귀포시 색달동 2950-4064-738-288833.243846126.4145092024-04-12
9전문휴양업녹지 한라산타운 콘도미니엄제주특별자치도 서귀포시 동홍동 2051064-702-980933.284776126.5557582024-04-12
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15전문휴양업박물관은 살아있다제주특별자치도 서귀포시 색달동 2629<NA>33.25490212634097703.02024-04-12
16전문휴양업제주허브동산제주특별자치도 서귀포시 표선면 표선리 2608번지<NA>33.329123126.8147222024-04-12
17전문휴양업세계성문화박물관제주특별자치도 서귀포시 법환동 914번지064-739-005933.247468126.5076342024-04-12
18전문휴양업제주민속촌제주특별자치도 서귀포시 표선면 표선리 40-1064-787-450133.321284126.8430842024-04-12
19전문휴양업석부작박물관제주특별자치도 서귀포시 호근동 569-2번지064-739-333133.250293126.5360122024-04-12
20전문휴양업(주)아프리카박물관제주특별자치도 서귀포시 대포동 1833064-738-656533.23998126.4288162024-04-12
21전문휴양업(주)삼영관광 일출랜드제주특별자치도 서귀포시 성산읍 삼달리 1010<NA>33.385126.8398562024-04-12
22전문휴양업(주)테디베어뮤지엄제주특별자치도 서귀포시 색달동 2889 테디베어박물관<NA>33.250299126.4121612024-04-12
23전문휴양업부국개발주식회사 여미지식물원제주특별자치도 서귀포시 색달동 2482-1번지064-735-110033.254714126.417652024-04-12
24전문휴양업(주)대유산업제주특별자치도 서귀포시 상예동 144<NA>33.278974126.3942322024-04-12