Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory69.7 B

Variable types

Categorical6
Text2

Dataset

Description부산광역시남구민방위비상급수시설수질검사결과및조치사항(2019년2분기)
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081613

Alerts

주소1 has constant value ""Constant
수질검사일자 has constant value ""Constant
판정결과 is highly overall correlated with 조치내용High correlation
조치내용 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
동명 is highly overall correlated with 조치내용High correlation
구분 is highly overall correlated with 조치내용High correlation
시설명 has unique valuesUnique
주소2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:28:39.021949
Analysis finished2023-12-10 16:28:39.722933
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
음용수
16 
생활용수
7 

Length

Max length4
Median length3
Mean length3.3043478
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
음용수 16
69.6%
생활용수 7
30.4%

Length

2023-12-11T01:28:39.832425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:40.013765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음용수 16
69.6%
생활용수 7
30.4%

동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
용호3동
4 
대연4동
3 
용호2동
3 
용당동
3 
대연3동
2 
Other values (6)
8 

Length

Max length4
Median length4
Mean length3.8695652
Min length3

Unique

Unique4 ?
Unique (%)17.4%

Sample

1st row대연1동
2nd row대연3동
3rd row대연3동
4th row대연4동
5th row대연4동

Common Values

ValueCountFrequency (%)
용호3동 4
17.4%
대연4동 3
13.0%
용호2동 3
13.0%
용당동 3
13.0%
대연3동 2
8.7%
용호1동 2
8.7%
문현1동 2
8.7%
대연1동 1
 
4.3%
용호4동 1
 
4.3%
문현3동 1
 
4.3%

Length

2023-12-11T01:28:40.189142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용호3동 4
17.4%
대연4동 3
13.0%
용호2동 3
13.0%
용당동 3
13.0%
대연3동 2
8.7%
용호1동 2
8.7%
문현1동 2
8.7%
대연1동 1
 
4.3%
용호4동 1
 
4.3%
문현3동 1
 
4.3%

시설명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:28:40.454502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.6521739
Min length3

Characters and Unicode

Total characters153
Distinct characters78
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

Unique23 ?
Unique (%)100.0%

Sample

1st row대연중앙교회
2nd row대우그린아파트
3rd row삼익그린아파트
4th row부산공업고등학교
5th row대호탕
ValueCountFrequency (%)
대연중앙교회 1
 
4.3%
부산인력개발원 1
 
4.3%
한신문화타운 1
 
4.3%
지상태권도장(촌칼국수 1
 
4.3%
등용문학원 1
 
4.3%
용호시장 1
 
4.3%
솔밭놀이터 1
 
4.3%
오양양지아파트 1
 
4.3%
대도라이프타운 1
 
4.3%
인각사 1
 
4.3%
Other values (13) 13
56.5%
2023-12-11T01:28:40.948542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 7
 
4.6%
트 7
 
4.6%
타 6
 
3.9%
파 6
 
3.9%
대 5
 
3.3%
운 5
 
3.3%
용 4
 
2.6%
교 4
 
2.6%
학 4
 
2.6%
등 4
 
2.6%
Other values (68) 101
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
96.1%
Open Punctuation 3
 
2.0%
Close Punctuation 3
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 7
 
4.8%
트 7
 
4.8%
타 6
 
4.1%
파 6
 
4.1%
대 5
 
3.4%
운 5
 
3.4%
용 4
 
2.7%
교 4
 
2.7%
학 4
 
2.7%
등 4
 
2.7%
Other values (66) 95
64.6%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
96.1%
Common 6
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 7
 
4.8%
트 7
 
4.8%
타 6
 
4.1%
파 6
 
4.1%
대 5
 
3.4%
운 5
 
3.4%
용 4
 
2.7%
교 4
 
2.7%
학 4
 
2.7%
등 4
 
2.7%
Other values (66) 95
64.6%
Common
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
96.1%
ASCII 6
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 7
 
4.8%
트 7
 
4.8%
타 6
 
4.1%
파 6
 
4.1%
대 5
 
3.4%
운 5
 
3.4%
용 4
 
2.7%
교 4
 
2.7%
학 4
 
2.7%
등 4
 
2.7%
Other values (66) 95
64.6%
ASCII
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

주소1
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
부산광역시 남구
23 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 남구
2nd row부산광역시 남구
3rd row부산광역시 남구
4th row부산광역시 남구
5th row부산광역시 남구

Common Values

ValueCountFrequency (%)
부산광역시 남구 23
100.0%

Length

2023-12-11T01:28:41.089068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:41.172895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 23
50.0%
남구 23
50.0%

주소2
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T01:28:41.337939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10
Min length6

Characters and Unicode

Total characters230
Distinct characters41
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

Unique23 ?
Unique (%)100.0%

Sample

1st row유엔평화로13번길 33
2nd row황령대로319번가길 190-6
3rd row황령대로319번가길 142
4th row수영로196번길 80
5th row석포로 119
ValueCountFrequency (%)
동명로 5
 
10.9%
황령대로319번가길 2
 
4.3%
진남로 2
 
4.3%
93 2
 
4.3%
유엔평화로13번길 1
 
2.2%
454-20 1
 
2.2%
신선대산복로 1
 
2.2%
105 1
 
2.2%
234 1
 
2.2%
수영로39번가길 1
 
2.2%
Other values (29) 29
63.0%
2023-12-11T01:28:41.646193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 26
 
11.3%
23
 
10.0%
로 23
 
10.0%
9 13
 
5.7%
3 13
 
5.7%
2 11
 
4.8%
번 11
 
4.8%
길 11
 
4.8%
5 8
 
3.5%
동 8
 
3.5%
Other values (31) 83
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
45.2%
Decimal Number 98
42.6%
Space Separator 23
 
10.0%
Dash Punctuation 5
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 23
22.1%
번 11
 
10.6%
길 11
 
10.6%
동 8
 
7.7%
명 7
 
6.7%
대 3
 
2.9%
가 3
 
2.9%
호 3
 
2.9%
용 3
 
2.9%
선 2
 
1.9%
Other values (19) 30
28.8%
Decimal Number
ValueCountFrequency (%)
1 26
26.5%
9 13
13.3%
3 13
13.3%
2 11
11.2%
5 8
 
8.2%
0 7
 
7.1%
8 7
 
7.1%
6 6
 
6.1%
4 5
 
5.1%
7 2
 
2.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 126
54.8%
Hangul 104
45.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 23
22.1%
번 11
 
10.6%
길 11
 
10.6%
동 8
 
7.7%
명 7
 
6.7%
대 3
 
2.9%
가 3
 
2.9%
호 3
 
2.9%
용 3
 
2.9%
선 2
 
1.9%
Other values (19) 30
28.8%
Common
ValueCountFrequency (%)
1 26
20.6%
23
18.3%
9 13
10.3%
3 13
10.3%
2 11
8.7%
5 8
 
6.3%
0 7
 
5.6%
8 7
 
5.6%
6 6
 
4.8%
- 5
 
4.0%
Other values (2) 7
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
54.8%
Hangul 104
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 26
20.6%
23
18.3%
9 13
10.3%
3 13
10.3%
2 11
8.7%
5 8
 
6.3%
0 7
 
5.6%
8 7
 
5.6%
6 6
 
4.8%
- 5
 
4.0%
Other values (2) 7
 
5.6%
Hangul
ValueCountFrequency (%)
로 23
22.1%
번 11
 
10.6%
길 11
 
10.6%
동 8
 
7.7%
명 7
 
6.7%
대 3
 
2.9%
가 3
 
2.9%
호 3
 
2.9%
용 3
 
2.9%
선 2
 
1.9%
Other values (19) 30
28.8%

수질검사일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2019-06-18
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-06-18
2nd row2019-06-18
3rd row2019-06-18
4th row2019-06-18
5th row2019-06-18

Common Values

ValueCountFrequency (%)
2019-06-18 23
100.0%

Length

2023-12-11T01:28:41.761534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:41.859852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-06-18 23
100.0%

판정결과
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
적합
15 
부적합
8 

Length

Max length3
Median length2
Mean length2.3478261
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row적합
3rd row적합
4th row부적합
5th row적합

Common Values

ValueCountFrequency (%)
적합 15
65.2%
부적합 8
34.8%

Length

2023-12-11T01:28:41.951147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:42.053811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 15
65.2%
부적합 8
34.8%

조치내용
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
15 
사용중지
8 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row사용중지
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 15
65.2%
사용중지 8
34.8%

Length

2023-12-11T01:28:42.149279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:28:42.236989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
65.2%
사용중지 8
34.8%

Correlations

2023-12-11T01:28:42.312816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분동명시설명주소2판정결과
구분1.0000.0001.0001.0000.495
동명0.0001.0001.0001.0000.000
시설명1.0001.0001.0001.0001.000
주소21.0001.0001.0001.0001.000
판정결과0.4950.0001.0001.0001.000
2023-12-11T01:28:42.405797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판정결과조치내용동명구분
판정결과1.0001.0000.0000.327
조치내용1.0001.0001.0001.000
동명0.0001.0001.0000.000
구분0.3271.0000.0001.000
2023-12-11T01:28:42.492345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분동명판정결과조치내용
구분1.0000.0000.3271.000
동명0.0001.0000.0001.000
판정결과0.3270.0001.0001.000
조치내용1.0001.0001.0001.000

Missing values

2023-12-11T01:28:39.472004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:28:39.658542image/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

구분동명시설명주소1주소2수질검사일자판정결과조치내용
0음용수대연1동대연중앙교회부산광역시 남구유엔평화로13번길 332019-06-18적합<NA>
1음용수대연3동대우그린아파트부산광역시 남구황령대로319번가길 190-62019-06-18적합<NA>
2음용수대연3동삼익그린아파트부산광역시 남구황령대로319번가길 1422019-06-18적합<NA>
3음용수대연4동부산공업고등학교부산광역시 남구수영로196번길 802019-06-18부적합사용중지
4음용수대연4동대호탕부산광역시 남구석포로 1192019-06-18적합<NA>
5음용수대연4동일반주택(전용)부산광역시 남구홍곡로320번길 1152019-06-18부적합사용중지
6음용수용호1동백운초등학교부산광역시 남구동명로 762019-06-18적합<NA>
7음용수용호2동용호동일타운아파트부산광역시 남구동명로170번길 932019-06-18적합<NA>
8음용수용호2동벽산화이트타워아파트부산광역시 남구용호로269번길 902019-06-18부적합사용중지
9음용수용호3동동보빌라부산광역시 남구용호로159번길 1182019-06-18부적합사용중지
구분동명시설명주소1주소2수질검사일자판정결과조치내용
13음용수용당동신선대(아래솔밭)부산광역시 남구신선대산복로 1052019-06-18부적합사용중지
14음용수문현1동인각사부산광역시 남구진남로 2342019-06-18부적합사용중지
15음용수문현3동대도라이프타운부산광역시 남구수영로39번가길 832019-06-18부적합사용중지
16생활용수대연6동오양양지아파트부산광역시 남구진남로 95-112019-06-18적합<NA>
17생활용수용호1동솔밭놀이터부산광역시 남구동명로 1142019-06-18적합<NA>
18생활용수용호2동용호시장부산광역시 남구동명로152번길 932019-06-18적합<NA>
19생활용수용호3동등용문학원부산광역시 남구동명로 1822019-06-18적합<NA>
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