Overview

Dataset statistics

Number of variables6
Number of observations67
Missing cells5
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory50.0 B

Variable types

Categorical2
Text3
DateTime1

Dataset

Description제주특별자치도에 소재하고 있는 유원시설업과 관련한 데이터로 구분, 상호명, 소재지, 연락처 등의 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15045875/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
비고 is highly imbalanced (72.6%)Imbalance
연락처 has 5 (7.5%) missing valuesMissing
상호명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:52:35.067834
Analysis finished2023-12-12 23:52:35.502614
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
기타유원시설업
55 
일반유원시설업
8 
종합유원시설업
 
4

Length

Max length8
Median length8
Mean length7.8208955
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합유원시설업
2nd row종합유원시설업
3rd row종합유원시설업
4th row종합유원시설업
5th row일반유원시설업

Common Values

ValueCountFrequency (%)
기타유원시설업 55
82.1%
일반유원시설업 8
 
11.9%
종합유원시설업 4
 
6.0%

Length

2023-12-13T08:52:35.551998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:35.630698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타유원시설업 55
82.1%
일반유원시설업 8
 
11.9%
종합유원시설업 4
 
6.0%

상호명
Text

UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-13T08:52:35.828640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length8.4925373
Min length3

Characters and Unicode

Total characters569
Distinct characters193
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)100.0%

Sample

1st row9.81 PARK JEJU
2nd row신화테마파크
3rd row신화워터파크
4th row뽀로로&타요 테마파크 제주
5th row㈜대한항공 정석비행장
ValueCountFrequency (%)
키즈카페 9
 
8.1%
노리파크 3
 
2.7%
헬로방방 2
 
1.8%
리틀비틀 2
 
1.8%
제주 2
 
1.8%
서귀포점 2
 
1.8%
9.81 1
 
0.9%
까꿍베베 1
 
0.9%
대빵오락실 1
 
0.9%
트램플린 1
 
0.9%
Other values (87) 87
78.4%
2023-12-13T08:52:36.182600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
7.7%
주 20
 
3.5%
제 16
 
2.8%
점 16
 
2.8%
키 15
 
2.6%
이 14
 
2.5%
즈 13
 
2.3%
방 13
 
2.3%
카 12
 
2.1%
페 12
 
2.1%
Other values (183) 394
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 492
86.5%
Space Separator 44
 
7.7%
Uppercase Letter 11
 
1.9%
Close Punctuation 5
 
0.9%
Other Symbol 5
 
0.9%
Open Punctuation 5
 
0.9%
Decimal Number 4
 
0.7%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 20
 
4.1%
제 16
 
3.3%
점 16
 
3.3%
키 15
 
3.0%
이 14
 
2.8%
즈 13
 
2.6%
방 13
 
2.6%
카 12
 
2.4%
페 12
 
2.4%
리 12
 
2.4%
Other values (167) 349
70.9%
Uppercase Letter
ValueCountFrequency (%)
J 3
27.3%
R 2
18.2%
P 2
18.2%
U 1
 
9.1%
E 1
 
9.1%
K 1
 
9.1%
A 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
8 1
25.0%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 497
87.3%
Common 61
 
10.7%
Latin 11
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 20
 
4.0%
제 16
 
3.2%
점 16
 
3.2%
키 15
 
3.0%
이 14
 
2.8%
즈 13
 
2.6%
방 13
 
2.6%
카 12
 
2.4%
페 12
 
2.4%
리 12
 
2.4%
Other values (168) 354
71.2%
Common
ValueCountFrequency (%)
44
72.1%
) 5
 
8.2%
( 5
 
8.2%
& 2
 
3.3%
1 2
 
3.3%
9 1
 
1.6%
8 1
 
1.6%
. 1
 
1.6%
Latin
ValueCountFrequency (%)
J 3
27.3%
R 2
18.2%
P 2
18.2%
U 1
 
9.1%
E 1
 
9.1%
K 1
 
9.1%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 492
86.5%
ASCII 72
 
12.7%
None 5
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
61.1%
) 5
 
6.9%
( 5
 
6.9%
J 3
 
4.2%
& 2
 
2.8%
R 2
 
2.8%
P 2
 
2.8%
1 2
 
2.8%
9 1
 
1.4%
U 1
 
1.4%
Other values (5) 5
 
6.9%
Hangul
ValueCountFrequency (%)
주 20
 
4.1%
제 16
 
3.3%
점 16
 
3.3%
키 15
 
3.0%
이 14
 
2.8%
즈 13
 
2.6%
방 13
 
2.6%
카 12
 
2.4%
페 12
 
2.4%
리 12
 
2.4%
Other values (167) 349
70.9%
None
ValueCountFrequency (%)
㈜ 5
100.0%

소재지
Text

UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-13T08:52:36.449135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length23.059701
Min length18

Characters and Unicode

Total characters1545
Distinct characters116
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)100.0%

Sample

1st row제주특별자치도 제주시 애월읍 천덕로 880-24
2nd row제주특별자치도 서귀포시 안덕면 신화역사로 304번길 98
3rd row제주특별자치도 서귀포시 안덕면 신화역사로 304번길 38.98
4th row제주특별자치도 서귀포시 안덕면 상창리 79번지 일원
5th row제주특별자치도 서귀포시 표선면 녹산로 679-11
ValueCountFrequency (%)
제주특별자치도 67
22.6%
제주시 36
 
12.1%
서귀포시 31
 
10.4%
안덕면 6
 
2.0%
조천읍 3
 
1.0%
표선면 3
 
1.0%
이어도로 3
 
1.0%
중산간동로 2
 
0.7%
대정읍 2
 
0.7%
과원북4길 2
 
0.7%
Other values (126) 142
47.8%
2023-12-13T08:52:36.850111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
16.5%
주 106
 
6.9%
제 103
 
6.7%
도 70
 
4.5%
특 67
 
4.3%
별 67
 
4.3%
자 67
 
4.3%
치 67
 
4.3%
시 67
 
4.3%
로 53
 
3.4%
Other values (106) 623
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1044
67.6%
Space Separator 255
 
16.5%
Decimal Number 228
 
14.8%
Dash Punctuation 15
 
1.0%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 106
 
10.2%
제 103
 
9.9%
도 70
 
6.7%
특 67
 
6.4%
별 67
 
6.4%
자 67
 
6.4%
치 67
 
6.4%
시 67
 
6.4%
로 53
 
5.1%
서 34
 
3.3%
Other values (93) 343
32.9%
Decimal Number
ValueCountFrequency (%)
1 37
16.2%
2 33
14.5%
4 27
11.8%
6 22
9.6%
7 21
9.2%
8 20
8.8%
0 19
8.3%
3 18
7.9%
5 17
7.5%
9 14
 
6.1%
Space Separator
ValueCountFrequency (%)
255
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1044
67.6%
Common 501
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 106
 
10.2%
제 103
 
9.9%
도 70
 
6.7%
특 67
 
6.4%
별 67
 
6.4%
자 67
 
6.4%
치 67
 
6.4%
시 67
 
6.4%
로 53
 
5.1%
서 34
 
3.3%
Other values (93) 343
32.9%
Common
ValueCountFrequency (%)
255
50.9%
1 37
 
7.4%
2 33
 
6.6%
4 27
 
5.4%
6 22
 
4.4%
7 21
 
4.2%
8 20
 
4.0%
0 19
 
3.8%
3 18
 
3.6%
5 17
 
3.4%
Other values (3) 32
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1044
67.6%
ASCII 501
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
255
50.9%
1 37
 
7.4%
2 33
 
6.6%
4 27
 
5.4%
6 22
 
4.4%
7 21
 
4.2%
8 20
 
4.0%
0 19
 
3.8%
3 18
 
3.6%
5 17
 
3.4%
Other values (3) 32
 
6.4%
Hangul
ValueCountFrequency (%)
주 106
 
10.2%
제 103
 
9.9%
도 70
 
6.7%
특 67
 
6.4%
별 67
 
6.4%
자 67
 
6.4%
치 67
 
6.4%
시 67
 
6.4%
로 53
 
5.1%
서 34
 
3.3%
Other values (93) 343
32.9%

연락처
Text

MISSING 

Distinct62
Distinct (%)100.0%
Missing5
Missing (%)7.5%
Memory size668.0 B
2023-12-13T08:52:37.054392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032258
Min length9

Characters and Unicode

Total characters746
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

Unique62 ?
Unique (%)100.0%

Sample

1st row1833-9810
2nd row064-908-6100
3rd row064-908-6000
4th row070-8147-3311
5th row064-780-0312
ValueCountFrequency (%)
064-757-0828 1
 
1.6%
064-738-9502 1
 
1.6%
064-732-0020 1
 
1.6%
064-755-5800 1
 
1.6%
064-900-1566 1
 
1.6%
064-784-5600 1
 
1.6%
064-713-9006 1
 
1.6%
064-784-3500 1
 
1.6%
064-805-8660 1
 
1.6%
064-783-0300 1
 
1.6%
Other values (52) 52
83.9%
2023-12-13T08:52:37.593187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 130
17.4%
- 123
16.5%
4 91
12.2%
7 87
11.7%
6 83
11.1%
8 49
 
6.6%
3 47
 
6.3%
2 40
 
5.4%
5 35
 
4.7%
9 34
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 623
83.5%
Dash Punctuation 123
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 130
20.9%
4 91
14.6%
7 87
14.0%
6 83
13.3%
8 49
 
7.9%
3 47
 
7.5%
2 40
 
6.4%
5 35
 
5.6%
9 34
 
5.5%
1 27
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 130
17.4%
- 123
16.5%
4 91
12.2%
7 87
11.7%
6 83
11.1%
8 49
 
6.6%
3 47
 
6.3%
2 40
 
5.4%
5 35
 
4.7%
9 34
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 130
17.4%
- 123
16.5%
4 91
12.2%
7 87
11.7%
6 83
11.1%
8 49
 
6.6%
3 47
 
6.3%
2 40
 
5.4%
5 35
 
4.7%
9 34
 
4.6%

비고
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
특이사항없음
61 
휴업(~2022-06-30)
 
4
휴업(~2023-08-19)
 
1
대승인터컴->JP랜드1으로 수정
 
1

Length

Max length17
Median length6
Mean length6.8358209
Min length6

Unique

Unique2 ?
Unique (%)3.0%

Sample

1st row특이사항없음
2nd row특이사항없음
3rd row특이사항없음
4th row특이사항없음
5th row휴업(~2023-08-19)

Common Values

ValueCountFrequency (%)
특이사항없음 61
91.0%
휴업(~2022-06-30) 4
 
6.0%
휴업(~2023-08-19) 1
 
1.5%
대승인터컴->JP랜드1으로 수정 1
 
1.5%

Length

2023-12-13T08:52:37.705683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:52:37.790122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특이사항없음 61
89.7%
휴업(~2022-06-30 4
 
5.9%
휴업(~2023-08-19 1
 
1.5%
대승인터컴->jp랜드1으로 1
 
1.5%
수정 1
 
1.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
Minimum2021-12-31 00:00:00
Maximum2021-12-31 00:00:00
2023-12-13T08:52:37.872588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:52:37.944034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T08:52:38.001131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상호명소재지연락처비고
구분1.0001.0001.0001.0000.389
상호명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
비고0.3891.0001.0001.0001.000
2023-12-13T08:52:38.077437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분비고
구분1.0000.376
비고0.3761.000
2023-12-13T08:52:38.139213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분비고
구분1.0000.376
비고0.3761.000

Missing values

2023-12-13T08:52:35.389244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:52:35.471554image/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

구분상호명소재지연락처비고데이터기준일자
0종합유원시설업9.81 PARK JEJU제주특별자치도 제주시 애월읍 천덕로 880-241833-9810특이사항없음2021-12-31
1종합유원시설업신화테마파크제주특별자치도 서귀포시 안덕면 신화역사로 304번길 98064-908-6100특이사항없음2021-12-31
2종합유원시설업신화워터파크제주특별자치도 서귀포시 안덕면 신화역사로 304번길 38.98064-908-6000특이사항없음2021-12-31
3종합유원시설업뽀로로&타요 테마파크 제주제주특별자치도 서귀포시 안덕면 상창리 79번지 일원070-8147-3311특이사항없음2021-12-31
4일반유원시설업㈜대한항공 정석비행장제주특별자치도 서귀포시 표선면 녹산로 679-11064-780-0312휴업(~2023-08-19)2021-12-31
5일반유원시설업산지물 물놀이장제주특별자치도 서귀포시 중산간동로 7971<NA>휴업(~2022-06-30)2021-12-31
6일반유원시설업남원용암해수풀장제주특별자치도 서귀포시 남원읍 남태해안로 140064-764-0181휴업(~2022-06-30)2021-12-31
7일반유원시설업생수천 생태문화공원제주특별자치도 서귀포시 색달동 2055064-738-9360휴업(~2022-06-30)2021-12-31
8일반유원시설업크리에이티브통제주제주특별자치도 서귀포시 중문관광로 42064-805-0993특이사항없음2021-12-31
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