Overview

Dataset statistics

Number of variables5
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory42.6 B

Variable types

Text2
Categorical2
DateTime1

Dataset

Description해변, 선착장 등 위험요인이 있는 곳에 로프, 구명동의, 구명환 등 인명구조장비 설치정보
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15024859/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
수량 is highly imbalanced (79.6%)Imbalance
관리번호 has unique valuesUnique
설치장소(위치) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:32:13.765809
Analysis finished2023-12-12 14:32:14.239621
Duration0.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T23:32:14.435405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.5308642
Min length4

Characters and Unicode

Total characters367
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row동홍-1
2nd row동홍-2
3rd row동홍-3
4th row동홍-4
5th row동홍-5
ValueCountFrequency (%)
동홍-1 1
 
1.2%
서귀-3 1
 
1.2%
서귀-21 1
 
1.2%
서귀-20 1
 
1.2%
서귀-19 1
 
1.2%
서귀-18 1
 
1.2%
서귀-17 1
 
1.2%
서귀-16 1
 
1.2%
서귀-15 1
 
1.2%
서귀-14 1
 
1.2%
Other values (71) 71
87.7%
2023-12-12T23:32:14.803070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 81
22.1%
귀 42
11.4%
서 42
11.4%
1 30
 
8.2%
2 21
 
5.7%
3 20
 
5.4%
순 17
 
4.6%
화 17
 
4.6%
4 13
 
3.5%
5 9
 
2.5%
Other values (13) 75
20.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
44.1%
Decimal Number 124
33.8%
Dash Punctuation 81
22.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
귀 42
25.9%
서 42
25.9%
순 17
10.5%
화 17
10.5%
홍 7
 
4.3%
동 7
 
4.3%
대 6
 
3.7%
륜 6
 
3.7%
중 5
 
3.1%
문 5
 
3.1%
Other values (2) 8
 
4.9%
Decimal Number
ValueCountFrequency (%)
1 30
24.2%
2 21
16.9%
3 20
16.1%
4 13
10.5%
5 9
 
7.3%
7 7
 
5.6%
6 7
 
5.6%
9 6
 
4.8%
0 6
 
4.8%
8 5
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 205
55.9%
Hangul 162
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
귀 42
25.9%
서 42
25.9%
순 17
10.5%
화 17
10.5%
홍 7
 
4.3%
동 7
 
4.3%
대 6
 
3.7%
륜 6
 
3.7%
중 5
 
3.1%
문 5
 
3.1%
Other values (2) 8
 
4.9%
Common
ValueCountFrequency (%)
- 81
39.5%
1 30
 
14.6%
2 21
 
10.2%
3 20
 
9.8%
4 13
 
6.3%
5 9
 
4.4%
7 7
 
3.4%
6 7
 
3.4%
9 6
 
2.9%
0 6
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 205
55.9%
Hangul 162
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 81
39.5%
1 30
 
14.6%
2 21
 
10.2%
3 20
 
9.8%
4 13
 
6.3%
5 9
 
4.4%
7 7
 
3.4%
6 7
 
3.4%
9 6
 
2.9%
0 6
 
2.9%
Hangul
ValueCountFrequency (%)
귀 42
25.9%
서 42
25.9%
순 17
10.5%
화 17
10.5%
홍 7
 
4.3%
동 7
 
4.3%
대 6
 
3.7%
륜 6
 
3.7%
중 5
 
3.1%
문 5
 
3.1%
Other values (2) 8
 
4.9%

읍면동
Categorical

Distinct26
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size780.0 B
대정읍
16 
강정동
8 
중문동
6 
서홍동
5 
정방동
5 
Other values (21)
41 

Length

Max length8
Median length3
Mean length3.7777778
Min length3

Unique

Unique11 ?
Unique (%)13.6%

Sample

1st row서홍동
2nd row서홍동
3rd row송산동
4th row서홍동
5th row서홍동

Common Values

ValueCountFrequency (%)
대정읍 16
19.8%
강정동 8
 
9.9%
중문동 6
 
7.4%
서홍동 5
 
6.2%
정방동 5
 
6.2%
하예동 5
 
6.2%
남원읍 위미리 4
 
4.9%
서귀동 4
 
4.9%
토평동 3
 
3.7%
남원읍 태흥리 3
 
3.7%
Other values (16) 22
27.2%

Length

2023-12-12T23:32:14.930509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대정읍 16
16.8%
남원읍 14
14.7%
강정동 8
 
8.4%
중문동 6
 
6.3%
서홍동 6
 
6.3%
정방동 5
 
5.3%
하예동 5
 
5.3%
위미리 4
 
4.2%
서귀동 4
 
4.2%
토평동 3
 
3.2%
Other values (16) 24
25.3%

설치장소(위치)
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T23:32:15.206047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length26
Mean length18.37037
Min length3

Characters and Unicode

Total characters1488
Distinct characters220
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

Unique81 ?
Unique (%)100.0%

Sample

1st row외돌개 산책로 올레길 동측 부근
2nd row서귀포시 새연교 다리밑 방파제
3rd row송산동 천지연폭포 앞
4th row솜반천 공덕사 동측 서홍제 5교 남측
5th row솜반천 다리 북서측 50m 지점
ValueCountFrequency (%)
서귀포 17
 
5.1%
방파제 11
 
3.3%
대포 9
 
2.7%
입구 7
 
2.1%
앞 7
 
2.1%
끝단 6
 
1.8%
위미 6
 
1.8%
주차장 6
 
1.8%
옆 5
 
1.5%
계단 4
 
1.2%
Other values (201) 258
76.8%
2023-12-12T23:32:15.709895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
17.2%
포 53
 
3.6%
서 47
 
3.2%
구 37
 
2.5%
동 31
 
2.1%
( 28
 
1.9%
) 28
 
1.9%
방 27
 
1.8%
장 23
 
1.5%
입 22
 
1.5%
Other values (210) 936
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1095
73.6%
Space Separator 256
 
17.2%
Decimal Number 48
 
3.2%
Open Punctuation 28
 
1.9%
Close Punctuation 28
 
1.9%
Lowercase Letter 18
 
1.2%
Dash Punctuation 7
 
0.5%
Other Punctuation 4
 
0.3%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 53
 
4.8%
서 47
 
4.3%
구 37
 
3.4%
동 31
 
2.8%
방 27
 
2.5%
장 23
 
2.1%
입 22
 
2.0%
귀 22
 
2.0%
대 21
 
1.9%
해 21
 
1.9%
Other values (194) 791
72.2%
Decimal Number
ValueCountFrequency (%)
0 15
31.2%
5 11
22.9%
1 9
18.8%
2 8
16.7%
3 4
 
8.3%
6 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
P 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1095
73.6%
Common 372
 
25.0%
Latin 21
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 53
 
4.8%
서 47
 
4.3%
구 37
 
3.4%
동 31
 
2.8%
방 27
 
2.5%
장 23
 
2.1%
입 22
 
2.0%
귀 22
 
2.0%
대 21
 
1.9%
해 21
 
1.9%
Other values (194) 791
72.2%
Common
ValueCountFrequency (%)
256
68.8%
( 28
 
7.5%
) 28
 
7.5%
0 15
 
4.0%
5 11
 
3.0%
1 9
 
2.4%
2 8
 
2.2%
- 7
 
1.9%
3 4
 
1.1%
. 4
 
1.1%
Other values (2) 2
 
0.5%
Latin
ValueCountFrequency (%)
m 18
85.7%
G 1
 
4.8%
P 1
 
4.8%
L 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1095
73.6%
ASCII 393
 
26.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
65.1%
( 28
 
7.1%
) 28
 
7.1%
m 18
 
4.6%
0 15
 
3.8%
5 11
 
2.8%
1 9
 
2.3%
2 8
 
2.0%
- 7
 
1.8%
3 4
 
1.0%
Other values (6) 9
 
2.3%
Hangul
ValueCountFrequency (%)
포 53
 
4.8%
서 47
 
4.3%
구 37
 
3.4%
동 31
 
2.8%
방 27
 
2.5%
장 23
 
2.1%
입 22
 
2.0%
귀 22
 
2.0%
대 21
 
1.9%
해 21
 
1.9%
Other values (194) 791
72.2%

수량
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size780.0 B
1
77 
2
 
3
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 77
95.1%
2 3
 
3.7%
3 1
 
1.2%

Length

2023-12-12T23:32:15.856225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:32:15.969160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 77
95.1%
2 3
 
3.7%
3 1
 
1.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
Minimum2017-06-20 00:00:00
Maximum2017-06-20 00:00:00
2023-12-12T23:32:16.064158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:32:16.184125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T23:32:16.276413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호읍면동설치장소(위치)수량
관리번호1.0001.0001.0001.000
읍면동1.0001.0001.0000.000
설치장소(위치)1.0001.0001.0001.000
수량1.0000.0001.0001.000
2023-12-12T23:32:16.404572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량읍면동
수량1.0000.000
읍면동0.0001.000
2023-12-12T23:32:16.530174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동수량
읍면동1.0000.000
수량0.0001.000

Missing values

2023-12-12T23:32:14.122776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:32:14.206884image/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

관리번호읍면동설치장소(위치)수량데이터기준일자
0동홍-1서홍동외돌개 산책로 올레길 동측 부근12017-06-20
1동홍-2서홍동서귀포시 새연교 다리밑 방파제12017-06-20
2동홍-3송산동송산동 천지연폭포 앞12017-06-20
3동홍-4서홍동솜반천 공덕사 동측 서홍제 5교 남측12017-06-20
4동홍-5서홍동솜반천 다리 북서측 50m 지점12017-06-20
5동홍-6서홍동서홍동 솜반천 서홍2교 남측(오리꼴까닭 뒤편)12017-06-20
6동홍-7동홍동동홍천 산짓물(동홍LPG주유소 맞은편 다리밑)12017-06-20
7중문-1중문동중문 색달해변 서측(하얏트호텔앞)12017-06-20
8중문-2중문동중문색달해변 동측(입구)12017-06-20
9중문-3중문동중문 천제연 폭포12017-06-20
관리번호읍면동설치장소(위치)수량데이터기준일자
71서귀-33남원읍 태흥리위미 태흥1리 방파제 입구 오른쪽으로 5m12017-06-20
72서귀-34남원읍 태흥리위미 태흥3리 하얀등대 방파제 입구에서 20m12017-06-20
73서귀-35남원읍 신흥1리위미 신흥포구 입구(유류저장고 옆)12017-06-20
74서귀-36월평동월평포구 입구-서귀포소방서12017-06-20
75서귀-37강정동강정 켄싱턴호텔 해상방향(구 풍림콘도)-서귀포소방서12017-06-20
76서귀-38남원읍 위미리신우지 서쪽 방파제 입구에서 5m-동부소방12017-06-20
77서귀-39남원읍 위미리위미 2.3 동쪽 방파제 입구 계단(안내판) 옆-동부소방서12017-06-20
78서귀-40남원읍 위미2리중정포구 주차장 정자에서 해상으로 2m-동부소방서12017-06-20
79서귀-41남원읍 남원리큰엉 주차장 정자에서 해상으로 5m-동부소방서12017-06-20
80서귀-42남원읍 태흥리태흥2리 포구 입구 해신탕 앞 5m-동부소방서12017-06-20