Overview

Dataset statistics

Number of variables7
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory60.6 B

Variable types

Text2
DateTime3
Categorical2

Dataset

Description제주특별자치도 서귀포시 관내 어린이 놀이시설 안전검사 현황에 관한 데이터로 시설명, 소재지, 검사일 정보 등 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15056054/fileData.do

Alerts

설치검사결과 has constant value ""Constant
검사결과 has constant value ""Constant
공원명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:50:53.473096
Analysis finished2023-12-11 23:50:53.978526
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공원명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T08:50:54.163149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.7241379
Min length4

Characters and Unicode

Total characters137
Distinct characters52
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

Unique29 ?
Unique (%)100.0%

Sample

1st row제석공원
2nd row천지공원
3rd row중앙공원
4th row동홍공원
5th row태양공원
ValueCountFrequency (%)
어린이공원 3
 
9.4%
제석공원 1
 
3.1%
천지공원 1
 
3.1%
2호 1
 
3.1%
1호 1
 
3.1%
문화공원 1
 
3.1%
문부공원 1
 
3.1%
월라봉공원 1
 
3.1%
칠십리공원 1
 
3.1%
사계공원 1
 
3.1%
Other values (20) 20
62.5%
2023-12-12T08:50:54.644262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 29
21.2%
원 29
21.2%
문 4
 
2.9%
이 4
 
2.9%
동 3
 
2.2%
1 3
 
2.2%
2 3
 
2.2%
화 3
 
2.2%
호 3
 
2.2%
3
 
2.2%
Other values (42) 53
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127
92.7%
Decimal Number 7
 
5.1%
Space Separator 3
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 29
22.8%
원 29
22.8%
문 4
 
3.1%
이 4
 
3.1%
동 3
 
2.4%
화 3
 
2.4%
호 3
 
2.4%
어 3
 
2.4%
린 3
 
2.4%
홍 2
 
1.6%
Other values (38) 44
34.6%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
2 3
42.9%
3 1
 
14.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127
92.7%
Common 10
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 29
22.8%
원 29
22.8%
문 4
 
3.1%
이 4
 
3.1%
동 3
 
2.4%
화 3
 
2.4%
호 3
 
2.4%
어 3
 
2.4%
린 3
 
2.4%
홍 2
 
1.6%
Other values (38) 44
34.6%
Common
ValueCountFrequency (%)
1 3
30.0%
2 3
30.0%
3
30.0%
3 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127
92.7%
ASCII 10
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 29
22.8%
원 29
22.8%
문 4
 
3.1%
이 4
 
3.1%
동 3
 
2.4%
화 3
 
2.4%
호 3
 
2.4%
어 3
 
2.4%
린 3
 
2.4%
홍 2
 
1.6%
Other values (38) 44
34.6%
ASCII
ValueCountFrequency (%)
1 3
30.0%
2 3
30.0%
3
30.0%
3 1
 
10.0%

소재지
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T08:50:54.922877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.862069
Min length7

Characters and Unicode

Total characters257
Distinct characters32
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

Unique29 ?
Unique (%)100.0%

Sample

1st row서귀동 166-1
2nd row서귀동 304-4
3rd row서귀동 277-1
4th row동홍동 199-3
5th row동홍동 82-2
ValueCountFrequency (%)
동홍동 7
 
12.1%
서호동 6
 
10.3%
강정동 6
 
10.3%
보성리 3
 
5.2%
서귀동 3
 
5.2%
2399일원 1
 
1.7%
176 1
 
1.7%
646-1 1
 
1.7%
1192-5일원 1
 
1.7%
신효동 1
 
1.7%
Other values (28) 28
48.3%
2023-12-12T08:50:55.290368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 31
 
12.1%
29
 
11.3%
1 29
 
11.3%
- 16
 
6.2%
3 13
 
5.1%
4 13
 
5.1%
5 12
 
4.7%
9 11
 
4.3%
서 10
 
3.9%
2 10
 
3.9%
Other values (22) 83
32.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114
44.4%
Other Letter 98
38.1%
Space Separator 29
 
11.3%
Dash Punctuation 16
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 31
31.6%
서 10
 
10.2%
홍 8
 
8.2%
정 7
 
7.1%
강 6
 
6.1%
호 6
 
6.1%
리 5
 
5.1%
일 4
 
4.1%
원 4
 
4.1%
귀 3
 
3.1%
Other values (10) 14
14.3%
Decimal Number
ValueCountFrequency (%)
1 29
25.4%
3 13
11.4%
4 13
11.4%
5 12
10.5%
9 11
 
9.6%
2 10
 
8.8%
6 9
 
7.9%
8 6
 
5.3%
7 6
 
5.3%
0 5
 
4.4%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 159
61.9%
Hangul 98
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 31
31.6%
서 10
 
10.2%
홍 8
 
8.2%
정 7
 
7.1%
강 6
 
6.1%
호 6
 
6.1%
리 5
 
5.1%
일 4
 
4.1%
원 4
 
4.1%
귀 3
 
3.1%
Other values (10) 14
14.3%
Common
ValueCountFrequency (%)
29
18.2%
1 29
18.2%
- 16
10.1%
3 13
8.2%
4 13
8.2%
5 12
7.5%
9 11
 
6.9%
2 10
 
6.3%
6 9
 
5.7%
8 6
 
3.8%
Other values (2) 11
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 159
61.9%
Hangul 98
38.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 31
31.6%
서 10
 
10.2%
홍 8
 
8.2%
정 7
 
7.1%
강 6
 
6.1%
호 6
 
6.1%
리 5
 
5.1%
일 4
 
4.1%
원 4
 
4.1%
귀 3
 
3.1%
Other values (10) 14
14.3%
ASCII
ValueCountFrequency (%)
29
18.2%
1 29
18.2%
- 16
10.1%
3 13
8.2%
4 13
8.2%
5 12
7.5%
9 11
 
6.9%
2 10
 
6.3%
6 9
 
5.7%
8 6
 
3.8%
Other values (2) 11
 
6.9%

설치일
Date

Distinct13
Distinct (%)44.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum1974-05-10 00:00:00
Maximum2014-02-05 00:00:00
2023-12-12T08:50:55.439497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:55.590071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

설치검사일
Date

Distinct9
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2011-12-29 00:00:00
Maximum2014-02-12 00:00:00
2023-12-12T08:50:55.725221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:55.820029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

설치검사결과
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
합격
29 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 29
100.0%

Length

2023-12-12T08:50:55.921631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:55.996181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 29
100.0%

정기검사일
Date

Distinct15
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum2021-07-07 00:00:00
Maximum2023-07-03 00:00:00
2023-12-12T08:50:56.061253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:50:56.144701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

검사결과
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
합격
29 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
합격 29
100.0%

Length

2023-12-12T08:50:56.252154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:50:56.355902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
합격 29
100.0%

Correlations

2023-12-12T08:50:56.420047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공원명소재지설치일설치검사일정기검사일
공원명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
설치일1.0001.0001.0000.8930.830
설치검사일1.0001.0000.8931.0000.949
정기검사일1.0001.0000.8300.9491.000

Missing values

2023-12-12T08:50:53.777484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:50:53.917842image/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

공원명소재지설치일설치검사일설치검사결과정기검사일검사결과
0제석공원서귀동 166-11974-05-102012-07-12합격2022-07-22합격
1천지공원서귀동 304-41987-04-092012-07-12합격2022-10-22합격
2중앙공원서귀동 277-11987-04-092012-07-12합격2021-10-07합격
3동홍공원동홍동 199-31987-04-092012-07-12합격2022-06-22합격
4태양공원동홍동 82-21991-08-192013-07-17합격2023-07-03합격
5희망공원동홍동 87-41991-08-192013-07-17합격2022-07-05합격
6양지공원동홍동 420-11991-08-192013-12-17합격2021-12-09합격
7여명공원동홍동 435-41991-08-192013-12-16합격2021-12-09합격
8미래1공원서호동 11501992-12-312012-07-12합격2022-07-14합격
9문화2공원강정동 1381992-12-312013-12-16합격2021-12-01합격
공원명소재지설치일설치검사일설치검사결과정기검사일검사결과
19바다공원강정동 199-12014-02-052014-02-12합격2022-03-02합격
20숲속공원강정동 191-12014-02-052014-02-12합격2022-03-02합격
21사계공원사계리 35892001-06-122013-12-18합격2021-12-01합격
22칠십리공원서홍동 653-12012-01-012012-07-12합격2022-06-22합격
23월라봉공원신효동 1192-5일원2005-02-252013-12-17합격2021-12-09합격
24문부공원동홍동 646-11986-05-152013-07-17합격2023-07-03합격
25문화공원강정동 1761992-12-312013-07-17합격2023-06-29합격
261호 어린이공원보성리 2399일원2009-01-302013-02-14합격2023-05-10합격
272호 어린이공원보성리 2451일원2009-01-302013-02-14합격2023-05-10합격
283호 어린이공원보성리 2516일원2010-05-192013-02-14합격2023-05-10합격