Overview

Dataset statistics

Number of variables4
Number of observations40
Missing cells23
Missing cells (%)14.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory35.3 B

Variable types

Text3
DateTime1

Dataset

Description부산광역시 북구 관내에 있는 소독업소 현황에 관한 데이터로 연번, 업소명, 주소, 전화번호 등의 항목을 제공하고 있습니다.공란은 개인정보로 삭제된 데이터입니다.
Author부산광역시 북구
URLhttps://www.data.go.kr/data/3069563/fileData.do

Alerts

전화 has 23 (57.5%) missing valuesMissing
업소명 has unique valuesUnique
주소 has unique valuesUnique
신고일 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:12:47.042007
Analysis finished2023-12-12 02:12:47.440009
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T11:12:47.620437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length8.5
Mean length6.6
Min length3

Characters and Unicode

Total characters264
Distinct characters118
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row 제일방역공사
2nd row 태화환경공사
3rd row해충방역 캐치원
4th row ㈜성아종합관리
5th row 배성산업㈜
ValueCountFrequency (%)
제일방역공사 1
 
2.4%
에코맨즈 1
 
2.4%
㈜비뉴 1
 
2.4%
에코그린 1
 
2.4%
무지개환경 1
 
2.4%
㈜대성종합환경 1
 
2.4%
㈜크린코리아에스엔 1
 
2.4%
청소야닷컴 1
 
2.4%
버그잡스 1
 
2.4%
부경종합환경 1
 
2.4%
Other values (31) 31
75.6%
2023-12-12T11:12:48.038954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
4.5%
10
 
3.8%
10
 
3.8%
9
 
3.4%
8
 
3.0%
7
 
2.7%
7
 
2.7%
7
 
2.7%
6
 
2.3%
6
 
2.3%
Other values (108) 182
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 237
89.8%
Other Symbol 10
 
3.8%
Space Separator 6
 
2.3%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%
Uppercase Letter 2
 
0.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12
 
5.1%
10
 
4.2%
9
 
3.8%
8
 
3.4%
7
 
3.0%
7
 
3.0%
7
 
3.0%
6
 
2.5%
5
 
2.1%
5
 
2.1%
Other values (101) 161
67.9%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
S 1
50.0%
Other Symbol
ValueCountFrequency (%)
10
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 247
93.6%
Common 15
 
5.7%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12
 
4.9%
10
 
4.0%
10
 
4.0%
9
 
3.6%
8
 
3.2%
7
 
2.8%
7
 
2.8%
7
 
2.8%
6
 
2.4%
5
 
2.0%
Other values (102) 166
67.2%
Common
ValueCountFrequency (%)
6
40.0%
( 4
26.7%
) 4
26.7%
/ 1
 
6.7%
Latin
ValueCountFrequency (%)
T 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 237
89.8%
ASCII 17
 
6.4%
None 10
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12
 
5.1%
10
 
4.2%
9
 
3.8%
8
 
3.4%
7
 
3.0%
7
 
3.0%
7
 
3.0%
6
 
2.5%
5
 
2.1%
5
 
2.1%
Other values (101) 161
67.9%
None
ValueCountFrequency (%)
10
100.0%
ASCII
ValueCountFrequency (%)
6
35.3%
( 4
23.5%
) 4
23.5%
T 1
 
5.9%
/ 1
 
5.9%
S 1
 
5.9%

주소
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T11:12:48.281862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length29
Mean length22.125
Min length15

Characters and Unicode

Total characters885
Distinct characters78
Distinct categories7 ?
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 (%)100.0%

Sample

1st row 북구 낙동북로681번길 28(구포동)
2nd row 북구 금곡대로 616번길 10-5(금곡동) 주공2단지 상가207호
3rd row북구 시랑로 79번길 18(구포동)
4th row 북구 시랑로 62(구포동)
5th row 북구 사상로 588(구포동)
ValueCountFrequency (%)
북구 40
27.6%
금곡대로 7
 
4.8%
시랑로 4
 
2.8%
616번길 4
 
2.8%
사상로 3
 
2.1%
만덕2로 3
 
2.1%
학사로 2
 
1.4%
금곡대로616번길 2
 
1.4%
142(금곡동 2
 
1.4%
의성로109번길 2
 
1.4%
Other values (75) 76
52.4%
2023-12-12T11:12:48.656267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
17.2%
58
 
6.6%
1 50
 
5.6%
42
 
4.7%
41
 
4.6%
) 40
 
4.5%
40
 
4.5%
( 40
 
4.5%
2 32
 
3.6%
6 25
 
2.8%
Other values (68) 365
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
50.1%
Decimal Number 201
22.7%
Space Separator 152
 
17.2%
Close Punctuation 40
 
4.5%
Open Punctuation 40
 
4.5%
Dash Punctuation 6
 
0.7%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
58
13.1%
42
 
9.5%
41
 
9.3%
40
 
9.0%
25
 
5.6%
25
 
5.6%
24
 
5.4%
17
 
3.8%
17
 
3.8%
16
 
3.6%
Other values (53) 138
31.2%
Decimal Number
ValueCountFrequency (%)
1 50
24.9%
2 32
15.9%
6 25
12.4%
0 19
 
9.5%
4 18
 
9.0%
5 14
 
7.0%
8 14
 
7.0%
7 12
 
6.0%
3 10
 
5.0%
9 7
 
3.5%
Space Separator
ValueCountFrequency (%)
152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 443
50.1%
Common 442
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
58
13.1%
42
 
9.5%
41
 
9.3%
40
 
9.0%
25
 
5.6%
25
 
5.6%
24
 
5.4%
17
 
3.8%
17
 
3.8%
16
 
3.6%
Other values (53) 138
31.2%
Common
ValueCountFrequency (%)
152
34.4%
1 50
 
11.3%
) 40
 
9.0%
( 40
 
9.0%
2 32
 
7.2%
6 25
 
5.7%
0 19
 
4.3%
4 18
 
4.1%
5 14
 
3.2%
8 14
 
3.2%
Other values (5) 38
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 443
50.1%
ASCII 442
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
34.4%
1 50
 
11.3%
) 40
 
9.0%
( 40
 
9.0%
2 32
 
7.2%
6 25
 
5.7%
0 19
 
4.3%
4 18
 
4.1%
5 14
 
3.2%
8 14
 
3.2%
Other values (5) 38
 
8.6%
Hangul
ValueCountFrequency (%)
58
13.1%
42
 
9.5%
41
 
9.3%
40
 
9.0%
25
 
5.6%
25
 
5.6%
24
 
5.4%
17
 
3.8%
17
 
3.8%
16
 
3.6%
Other values (53) 138
31.2%

전화
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing23
Missing (%)57.5%
Memory size452.0 B
2023-12-12T11:12:48.854341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
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

Unique15 ?
Unique (%)88.2%

Sample

1st row051-334-8300
2nd row051-333-0006
3rd row051-301-1222
4th row051-333-3855
5th row051-365-3341
ValueCountFrequency (%)
051-363-9425 2
 
11.8%
051-327-3113 1
 
5.9%
051-301-1222 1
 
5.9%
051-333-3855 1
 
5.9%
051-365-3341 1
 
5.9%
051-323-4400 1
 
5.9%
051-338-0041 1
 
5.9%
051-333-0006 1
 
5.9%
051-331-9263 1
 
5.9%
051-336-7014 1
 
5.9%
Other values (6) 6
35.3%
2023-12-12T11:12:49.203598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35
17.2%
3 35
17.2%
- 34
16.7%
1 26
12.7%
5 24
11.8%
2 12
 
5.9%
4 10
 
4.9%
6 9
 
4.4%
7 8
 
3.9%
8 7
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
20.6%
3 35
20.6%
1 26
15.3%
5 24
14.1%
2 12
 
7.1%
4 10
 
5.9%
6 9
 
5.3%
7 8
 
4.7%
8 7
 
4.1%
9 4
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35
17.2%
3 35
17.2%
- 34
16.7%
1 26
12.7%
5 24
11.8%
2 12
 
5.9%
4 10
 
4.9%
6 9
 
4.4%
7 8
 
3.9%
8 7
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35
17.2%
3 35
17.2%
- 34
16.7%
1 26
12.7%
5 24
11.8%
2 12
 
5.9%
4 10
 
4.9%
6 9
 
4.4%
7 8
 
3.9%
8 7
 
3.4%

신고일
Date

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum1986-02-13 00:00:00
Maximum2023-07-05 00:00:00
2023-12-12T11:12:49.347734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:12:49.478371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

Correlations

2023-12-12T11:12:49.572642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소전화신고일
업소명1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화1.0001.0001.0001.000
신고일1.0001.0001.0001.000

Missing values

2023-12-12T11:12:47.315147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:12:47.401659image/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

업소명주소전화신고일
0제일방역공사북구 낙동북로681번길 28(구포동)051-334-83001986-02-13
1태화환경공사북구 금곡대로 616번길 10-5(금곡동) 주공2단지 상가207호051-333-00061999-03-17
2해충방역 캐치원북구 시랑로 79번길 18(구포동)051-301-12222003-05-09
3㈜성아종합관리북구 시랑로 62(구포동)051-333-38552005-01-21
4배성산업㈜북구 사상로 588(구포동)051-365-33412006-03-21
5고려용역북구 의성로109번길 63-1(덕천동)051-323-44002006-04-19
6㈜푸른환경시스템북구 금곡대로616번길 106(금곡동)101호051-363-94252008-01-30
7㈜부일환경종합방역북구 백양대로 1078(구포동)051-338-00412008-09-17
8(주)하이종합환경북구 구남언덕로16번길 4(구포동)051-327-31132008-11-17
9씨엠제이환경공사북구 금곡대로616번길 106(금곡동)102호051-363-94252009-02-20
업소명주소전화신고일
30티에스(T/S)솔루션북구 사상로 592(구포동)<NA>2021-08-05
31신화방역북구 금곡대로 458, 금곡월드프라자 240호(금곡동)<NA>2021-11-25
32에코원방역북구 팽나무로 8번길 15(구포동)<NA>2022-07-07
33한솔식물북구 만덕3로 48번다길 20(만덕동)<NA>2022-09-20
34하나방역북부산지점북구 낙동대로 1762번길 63(구포동)<NA>2022-11-10
35좋은방역북구 학사로 132(화명동)<NA>2023-01-02
36부경환경설비북구 구남언덕로 16번길 12(구포동)<NA>2023-01-10
37마리오클린북구 만덕2로29번길 21-7(만덕동)<NA>2023-04-05
38디에이치솔루션북구 모분재로23번길 65(구포동)<NA>2023-06-26
39연화홈케어코리아북구 만덕대로 108(덕천동)<NA>2023-07-05