Overview

Dataset statistics

Number of variables7
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory61.1 B

Variable types

Categorical3
Text3
DateTime1

Dataset

Description제주도 내 특수여객(장의차)의 업체명, 연락처, 차량(승용/승합)보유 대수 등 정보 제공
Author제주특별자치도
URLhttps://www.data.go.kr/data/15056322/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
승용 is highly imbalanced (54.4%)Imbalance
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:21:53.851557
Analysis finished2023-12-12 18:21:54.378924
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
제주시
29 
서귀포시
13 

Length

Max length4
Median length3
Mean length3.3095238
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 29
69.0%
서귀포시 13
31.0%

Length

2023-12-13T03:21:54.435810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:21:54.527626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 29
69.0%
서귀포시 13
31.0%

업체명
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T03:21:54.709925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length7.047619
Min length4

Characters and Unicode

Total characters296
Distinct characters94
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row제일장의 운수사
2nd row중앙장의사
3rd row탐라장의사
4th row씨제이 제주종합상조(주)
5th row강남장의사
ValueCountFrequency (%)
제일장의 1
 
2.1%
동부장의사 1
 
2.1%
ns상조 1
 
2.1%
효돈장의운수사 1
 
2.1%
제주인장례 1
 
2.1%
대일토탈장의서비스 1
 
2.1%
제주영구의전 1
 
2.1%
한림정낭장례식장 1
 
2.1%
주)그랜드중앙 1
 
2.1%
한빛장례문화센타 1
 
2.1%
Other values (37) 37
78.7%
2023-12-13T03:21:55.030327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
12.2%
29
 
9.8%
24
 
8.1%
12
 
4.1%
9
 
3.0%
9
 
3.0%
9
 
3.0%
7
 
2.4%
7
 
2.4%
5
 
1.7%
Other values (84) 149
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 281
94.9%
Space Separator 5
 
1.7%
Open Punctuation 4
 
1.4%
Close Punctuation 4
 
1.4%
Uppercase Letter 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
36
 
12.8%
29
 
10.3%
24
 
8.5%
12
 
4.3%
9
 
3.2%
9
 
3.2%
9
 
3.2%
7
 
2.5%
7
 
2.5%
5
 
1.8%
Other values (79) 134
47.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
N 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 281
94.9%
Common 13
 
4.4%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
36
 
12.8%
29
 
10.3%
24
 
8.5%
12
 
4.3%
9
 
3.2%
9
 
3.2%
9
 
3.2%
7
 
2.5%
7
 
2.5%
5
 
1.8%
Other values (79) 134
47.7%
Common
ValueCountFrequency (%)
5
38.5%
( 4
30.8%
) 4
30.8%
Latin
ValueCountFrequency (%)
S 1
50.0%
N 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 281
94.9%
ASCII 15
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
36
 
12.8%
29
 
10.3%
24
 
8.5%
12
 
4.3%
9
 
3.2%
9
 
3.2%
9
 
3.2%
7
 
2.5%
7
 
2.5%
5
 
1.8%
Other values (79) 134
47.7%
ASCII
ValueCountFrequency (%)
5
33.3%
( 4
26.7%
) 4
26.7%
S 1
 
6.7%
N 1
 
6.7%

승용
Categorical

IMBALANCE 

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
0
36 
1
2
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 36
85.7%
1 4
 
9.5%
2 2
 
4.8%

Length

2023-12-13T03:21:55.148932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:21:55.261355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 36
85.7%
1 4
 
9.5%
2 2
 
4.8%

승합
Categorical

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
28 
2
3
4
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row4
2nd row1
3rd row4
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 28
66.7%
2 6
 
14.3%
3 4
 
9.5%
4 3
 
7.1%
0 1
 
2.4%

Length

2023-12-13T03:21:55.374334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:21:55.483179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
66.7%
2 6
 
14.3%
3 4
 
9.5%
4 3
 
7.1%
0 1
 
2.4%
Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T03:21:55.704684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.571429
Min length18

Characters and Unicode

Total characters864
Distinct characters76
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

Unique40 ?
Unique (%)95.2%

Sample

1st row제주특별자치도 제주시 서광로11길 3
2nd row제주특별자치도 제주시 박성내서길 16-9
3rd row제주특별자치도 제주시 중앙로14길 34
4th row제주특별자치도 제주시 서광로 257
5th row제주특별자치도 제주시 관덕로 2길 15
ValueCountFrequency (%)
제주특별자치도 42
24.6%
제주시 29
17.0%
서귀포시 13
 
7.6%
일주동로 5
 
2.9%
34 3
 
1.8%
1237 2
 
1.2%
서광로 2
 
1.2%
도남동 2
 
1.2%
함덕남2길 2
 
1.2%
14 2
 
1.2%
Other values (68) 69
40.4%
2023-12-13T03:21:56.093802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
15.2%
76
 
8.8%
71
 
8.2%
45
 
5.2%
43
 
5.0%
42
 
4.9%
42
 
4.9%
42
 
4.9%
42
 
4.9%
32
 
3.7%
Other values (66) 298
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 594
68.8%
Decimal Number 134
 
15.5%
Space Separator 131
 
15.2%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
76
12.8%
71
12.0%
45
 
7.6%
43
 
7.2%
42
 
7.1%
42
 
7.1%
42
 
7.1%
42
 
7.1%
32
 
5.4%
20
 
3.4%
Other values (54) 139
23.4%
Decimal Number
ValueCountFrequency (%)
1 29
21.6%
2 21
15.7%
3 18
13.4%
6 12
9.0%
0 11
 
8.2%
5 11
 
8.2%
7 10
 
7.5%
4 10
 
7.5%
9 8
 
6.0%
8 4
 
3.0%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 594
68.8%
Common 270
31.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
76
12.8%
71
12.0%
45
 
7.6%
43
 
7.2%
42
 
7.1%
42
 
7.1%
42
 
7.1%
42
 
7.1%
32
 
5.4%
20
 
3.4%
Other values (54) 139
23.4%
Common
ValueCountFrequency (%)
131
48.5%
1 29
 
10.7%
2 21
 
7.8%
3 18
 
6.7%
6 12
 
4.4%
0 11
 
4.1%
5 11
 
4.1%
7 10
 
3.7%
4 10
 
3.7%
9 8
 
3.0%
Other values (2) 9
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 594
68.8%
ASCII 270
31.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
48.5%
1 29
 
10.7%
2 21
 
7.8%
3 18
 
6.7%
6 12
 
4.4%
0 11
 
4.1%
5 11
 
4.1%
7 10
 
3.7%
4 10
 
3.7%
9 8
 
3.0%
Other values (2) 9
 
3.3%
Hangul
ValueCountFrequency (%)
76
12.8%
71
12.0%
45
 
7.6%
43
 
7.2%
42
 
7.1%
42
 
7.1%
42
 
7.1%
42
 
7.1%
32
 
5.4%
20
 
3.4%
Other values (54) 139
23.4%
Distinct39
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-13T03:21:56.319146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.071429
Min length12

Characters and Unicode

Total characters507
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

Unique37 ?
Unique (%)88.1%

Sample

1st row064-722-7644
2nd row064-725-1024
3rd row064-758-1024
4th row064-723-4291
5th row064-721-4424
ValueCountFrequency (%)
010-0000-0000 3
 
7.1%
064-742-5000 2
 
4.8%
064-738-4333 1
 
2.4%
064-732-5200 1
 
2.4%
064-732-9599 1
 
2.4%
064-762-6646 1
 
2.4%
064-722-7644 1
 
2.4%
064-794-1980 1
 
2.4%
064-753-6100 1
 
2.4%
064-702-4443 1
 
2.4%
Other values (29) 29
69.0%
2023-12-13T03:21:56.696988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 105
20.7%
- 84
16.6%
4 78
15.4%
6 62
12.2%
7 45
8.9%
2 35
 
6.9%
1 30
 
5.9%
3 21
 
4.1%
9 18
 
3.6%
8 15
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 423
83.4%
Dash Punctuation 84
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 105
24.8%
4 78
18.4%
6 62
14.7%
7 45
10.6%
2 35
 
8.3%
1 30
 
7.1%
3 21
 
5.0%
9 18
 
4.3%
8 15
 
3.5%
5 14
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 507
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 105
20.7%
- 84
16.6%
4 78
15.4%
6 62
12.2%
7 45
8.9%
2 35
 
6.9%
1 30
 
5.9%
3 21
 
4.1%
9 18
 
3.6%
8 15
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 507
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 105
20.7%
- 84
16.6%
4 78
15.4%
6 62
12.2%
7 45
8.9%
2 35
 
6.9%
1 30
 
5.9%
3 21
 
4.1%
9 18
 
3.6%
8 15
 
3.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2017-05-30 00:00:00
Maximum2017-05-30 00:00:00
2023-12-13T03:21:56.832619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:21:56.937792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T03:21:57.028543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업체명승용승합사업장소재지연락처
지역1.0001.0000.0000.0951.0000.554
업체명1.0001.0001.0001.0001.0001.000
승용0.0001.0001.0000.4411.0000.000
승합0.0951.0000.4411.0000.9040.954
사업장소재지1.0001.0001.0000.9041.0000.991
연락처0.5541.0000.0000.9540.9911.000
2023-12-13T03:21:57.200127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역승용승합
지역1.0000.0000.101
승용0.0001.0000.359
승합0.1010.3591.000
2023-12-13T03:21:57.364300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역승용승합
지역1.0000.0000.101
승용0.0001.0000.359
승합0.1010.3591.000

Missing values

2023-12-13T03:21:54.248412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:21:54.343300image/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

지역업체명승용승합사업장소재지연락처데이터기준일자
0제주시제일장의 운수사04제주특별자치도 제주시 서광로11길 3064-722-76442017-05-30
1제주시중앙장의사01제주특별자치도 제주시 박성내서길 16-9064-725-10242017-05-30
2제주시탐라장의사04제주특별자치도 제주시 중앙로14길 34064-758-10242017-05-30
3제주시씨제이 제주종합상조(주)01제주특별자치도 제주시 서광로 257064-723-42912017-05-30
4제주시강남장의사13제주특별자치도 제주시 관덕로 2길 15064-721-44242017-05-30
5제주시(주)그랜드부민02제주특별자치도 제주시 연북로 378064-742-50002017-05-30
6제주시제주천국의전24제주특별자치도 제주시 월랑로 10길 25064-712-10412017-05-30
7제주시효진장의사02제주특별자치도 제주시 오남로6길 2-1064-727-00842017-05-30
8제주시다음장의운수01제주특별자치도 제주시 수정2길 1064-713-24162017-05-30
9제주시한라장의상조운수사01제주특별자치도 제주시 도령로 65064-749-26002017-05-30
지역업체명승용승합사업장소재지연락처데이터기준일자
32서귀포시모슬포한마음 장의사01제주특별자치도 서귀포시 상모로 227064-794-66112017-05-30
33서귀포시서귀포장의사01제주특별자치도 서귀포시 일주동로 8496064-732-22142017-05-30
34서귀포시성심장의운수사01제주특별자치도 서귀포시 동홍로 32-19064-733-01022017-05-30
35서귀포시소망장의사01제주특별자치도 서귀포시 대정읍 인성리 1634064-794-30312017-05-30
36서귀포시시민장의운수사01제주특별자치도 서귀포시 일주동로 8512064-732-52002017-05-30
37서귀포시영신장의사01제주특별자치도 서귀포시 고성동서로 45010-0000-00002017-05-30
38서귀포시중문장의사12제주특별자치도 서귀포시 1100로 105064-738-43332017-05-30
39서귀포시현대장의운수사02제주특별자치도 서귀포시 일주동로 8502064-762-66462017-05-30
40서귀포시효돈장의운수사01제주특별자치도 서귀포시 돈내코로70번길 61064-732-95992017-05-30
41서귀포시하나로장의사01제주특별자치도 서귀포시 일주동로 7115064-764-10092017-05-30