Overview

Dataset statistics

Number of variables3
Number of observations55
Missing cells27
Missing cells (%)16.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory26.4 B

Variable types

Text3

Dataset

Description부산광역시해운대구_소독업소현황_20230720
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075594

Alerts

주소 has 3 (5.5%) missing valuesMissing
전화번호 has 24 (43.6%) missing valuesMissing
소독업소명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:27:25.799788
Analysis finished2023-12-10 17:27:26.824858
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소독업소명칭
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T02:27:27.165598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.3818182
Min length2

Characters and Unicode

Total characters406
Distinct characters164
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)100.0%

Sample

1st row주식회사 해운대나무병원
2nd row주식회사 씨엠플러스
3rd row해운대에어컨세탁기청소 클린세븐
4th row현대방역솔루션
5th row(주)모든방역
ValueCountFrequency (%)
주식회사 7
 
9.9%
management 1
 
1.4%
피에스제이 1
 
1.4%
주)범경시스템 1
 
1.4%
메이썬에너지 1
 
1.4%
미소 1
 
1.4%
주)대성디엘에스 1
 
1.4%
필그린 1
 
1.4%
주)푸른환경 1
 
1.4%
우리환경테크날리지 1
 
1.4%
Other values (55) 55
77.5%
2023-12-11T02:27:28.143567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 20
 
4.9%
스 17
 
4.2%
16
 
3.9%
) 13
 
3.2%
( 13
 
3.2%
사 12
 
3.0%
방 11
 
2.7%
린 10
 
2.5%
대 10
 
2.5%
역 9
 
2.2%
Other values (154) 275
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
80.3%
Lowercase Letter 18
 
4.4%
Space Separator 16
 
3.9%
Close Punctuation 13
 
3.2%
Open Punctuation 13
 
3.2%
Uppercase Letter 13
 
3.2%
Decimal Number 5
 
1.2%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 20
 
6.1%
스 17
 
5.2%
사 12
 
3.7%
방 11
 
3.4%
린 10
 
3.1%
대 10
 
3.1%
역 9
 
2.8%
이 9
 
2.8%
회 8
 
2.5%
에 7
 
2.1%
Other values (124) 213
65.3%
Lowercase Letter
ValueCountFrequency (%)
n 3
16.7%
a 2
11.1%
m 2
11.1%
e 2
11.1%
t 2
11.1%
o 2
11.1%
g 1
 
5.6%
i 1
 
5.6%
u 1
 
5.6%
l 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
15.4%
O 2
15.4%
K 1
7.7%
N 1
7.7%
U 1
7.7%
D 1
7.7%
A 1
7.7%
C 1
7.7%
V 1
7.7%
P 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
5 1
20.0%
6 1
20.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
80.3%
Common 49
 
12.1%
Latin 31
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 20
 
6.1%
스 17
 
5.2%
사 12
 
3.7%
방 11
 
3.4%
린 10
 
3.1%
대 10
 
3.1%
역 9
 
2.8%
이 9
 
2.8%
회 8
 
2.5%
에 7
 
2.1%
Other values (124) 213
65.3%
Latin
ValueCountFrequency (%)
n 3
 
9.7%
S 2
 
6.5%
a 2
 
6.5%
m 2
 
6.5%
O 2
 
6.5%
e 2
 
6.5%
t 2
 
6.5%
o 2
 
6.5%
K 1
 
3.2%
g 1
 
3.2%
Other values (12) 12
38.7%
Common
ValueCountFrequency (%)
16
32.7%
) 13
26.5%
( 13
26.5%
1 2
 
4.1%
. 2
 
4.1%
5 1
 
2.0%
6 1
 
2.0%
3 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 326
80.3%
ASCII 80
 
19.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 20
 
6.1%
스 17
 
5.2%
사 12
 
3.7%
방 11
 
3.4%
린 10
 
3.1%
대 10
 
3.1%
역 9
 
2.8%
이 9
 
2.8%
회 8
 
2.5%
에 7
 
2.1%
Other values (124) 213
65.3%
ASCII
ValueCountFrequency (%)
16
20.0%
) 13
16.2%
( 13
16.2%
n 3
 
3.8%
1 2
 
2.5%
S 2
 
2.5%
a 2
 
2.5%
m 2
 
2.5%
O 2
 
2.5%
. 2
 
2.5%
Other values (20) 23
28.7%

주소
Text

MISSING 

Distinct52
Distinct (%)100.0%
Missing3
Missing (%)5.5%
Memory size572.0 B
2023-12-11T02:27:28.760028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length35.538462
Min length23

Characters and Unicode

Total characters1848
Distinct characters121
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row부산광역시 해운대구 대천로67번길 12, 3층 302호 (좌동)
2nd row부산광역시 해운대구 해운대로570번길 17, 한양수자인 마린 오피스텔 1324호 (우동)
3rd row부산광역시 해운대구 해운대해변로357번길 5-1, 205호 (중동)
4th row부산광역시 해운대구 대천로 56, 2층 209호 (좌동, 한일아파트)
5th row부산광역시 해운대구 송정중앙로 19, 302호 (송정동, 코스마아파트)
ValueCountFrequency (%)
부산광역시 52
 
15.3%
해운대구 51
 
15.0%
재송동 11
 
3.2%
반여동 9
 
2.7%
2층 9
 
2.7%
우동 8
 
2.4%
반송동 7
 
2.1%
신반송로 5
 
1.5%
좌동 5
 
1.5%
재반로 4
 
1.2%
Other values (147) 178
52.5%
2023-12-11T02:27:29.632866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
287
 
15.5%
1 69
 
3.7%
대 67
 
3.6%
해 66
 
3.6%
운 63
 
3.4%
동 60
 
3.2%
2 58
 
3.1%
시 56
 
3.0%
산 54
 
2.9%
부 53
 
2.9%
Other values (111) 1015
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1084
58.7%
Decimal Number 304
 
16.5%
Space Separator 287
 
15.5%
Other Punctuation 53
 
2.9%
Close Punctuation 52
 
2.8%
Open Punctuation 52
 
2.8%
Dash Punctuation 10
 
0.5%
Uppercase Letter 5
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 67
 
6.2%
해 66
 
6.1%
운 63
 
5.8%
동 60
 
5.5%
시 56
 
5.2%
산 54
 
5.0%
부 53
 
4.9%
광 53
 
4.9%
로 52
 
4.8%
역 52
 
4.8%
Other values (90) 508
46.9%
Decimal Number
ValueCountFrequency (%)
1 69
22.7%
2 58
19.1%
0 39
12.8%
3 29
9.5%
5 23
 
7.6%
9 18
 
5.9%
6 17
 
5.6%
7 17
 
5.6%
4 17
 
5.6%
8 17
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
E 1
20.0%
P 1
20.0%
A 1
20.0%
C 1
20.0%
B 1
20.0%
Space Separator
ValueCountFrequency (%)
287
100.0%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1084
58.7%
Common 758
41.0%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 67
 
6.2%
해 66
 
6.1%
운 63
 
5.8%
동 60
 
5.5%
시 56
 
5.2%
산 54
 
5.0%
부 53
 
4.9%
광 53
 
4.9%
로 52
 
4.8%
역 52
 
4.8%
Other values (90) 508
46.9%
Common
ValueCountFrequency (%)
287
37.9%
1 69
 
9.1%
2 58
 
7.7%
, 53
 
7.0%
) 52
 
6.9%
( 52
 
6.9%
0 39
 
5.1%
3 29
 
3.8%
5 23
 
3.0%
9 18
 
2.4%
Other values (5) 78
 
10.3%
Latin
ValueCountFrequency (%)
e 1
16.7%
E 1
16.7%
P 1
16.7%
A 1
16.7%
C 1
16.7%
B 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1084
58.7%
ASCII 764
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
287
37.6%
1 69
 
9.0%
2 58
 
7.6%
, 53
 
6.9%
) 52
 
6.8%
( 52
 
6.8%
0 39
 
5.1%
3 29
 
3.8%
5 23
 
3.0%
9 18
 
2.4%
Other values (11) 84
 
11.0%
Hangul
ValueCountFrequency (%)
대 67
 
6.2%
해 66
 
6.1%
운 63
 
5.8%
동 60
 
5.5%
시 56
 
5.2%
산 54
 
5.0%
부 53
 
4.9%
광 53
 
4.9%
로 52
 
4.8%
역 52
 
4.8%
Other values (90) 508
46.9%

전화번호
Text

MISSING 

Distinct31
Distinct (%)100.0%
Missing24
Missing (%)43.6%
Memory size572.0 B
2023-12-11T02:27:30.033922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.451613
Min length8

Characters and Unicode

Total characters324
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row051-744-5796
2nd row070-4618-6563
3rd row1533-3603
4th row051-782-1795
5th row051-743-7006
ValueCountFrequency (%)
051-744-5796 1
 
3.2%
545-1150 1
 
3.2%
782-1880 1
 
3.2%
747-5404 1
 
3.2%
783-2693 1
 
3.2%
809-2889 1
 
3.2%
051-783-0011 1
 
3.2%
784-2100 1
 
3.2%
743-4999 1
 
3.2%
647-0630 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T02:27:30.762222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
15.4%
- 48
14.8%
1 39
12.0%
5 37
11.4%
7 30
9.3%
4 28
8.6%
6 21
6.5%
2 21
6.5%
8 19
 
5.9%
3 17
 
5.2%
Other values (2) 14
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
84.9%
Dash Punctuation 48
 
14.8%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
18.2%
1 39
14.2%
5 37
13.5%
7 30
10.9%
4 28
10.2%
6 21
7.6%
2 21
7.6%
8 19
 
6.9%
3 17
 
6.2%
9 13
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
15.4%
- 48
14.8%
1 39
12.0%
5 37
11.4%
7 30
9.3%
4 28
8.6%
6 21
6.5%
2 21
6.5%
8 19
 
5.9%
3 17
 
5.2%
Other values (2) 14
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
15.4%
- 48
14.8%
1 39
12.0%
5 37
11.4%
7 30
9.3%
4 28
8.6%
6 21
6.5%
2 21
6.5%
8 19
 
5.9%
3 17
 
5.2%
Other values (2) 14
 
4.3%

Correlations

2023-12-11T02:27:31.018674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소독업소명칭주소전화번호
소독업소명칭1.0001.0001.000
주소1.0001.0001.000
전화번호1.0001.0001.000

Missing values

2023-12-11T02:27:26.324394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:27:26.505159image/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.
2023-12-11T02:27:26.713645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

소독업소명칭주소전화번호
0주식회사 해운대나무병원부산광역시 해운대구 대천로67번길 12, 3층 302호 (좌동)<NA>
1주식회사 씨엠플러스부산광역시 해운대구 해운대로570번길 17, 한양수자인 마린 오피스텔 1324호 (우동)051-744-5796
2해운대에어컨세탁기청소 클린세븐부산광역시 해운대구 해운대해변로357번길 5-1, 205호 (중동)<NA>
3현대방역솔루션부산광역시 해운대구 대천로 56, 2층 209호 (좌동, 한일아파트)<NA>
4(주)모든방역부산광역시 해운대구 송정중앙로 19, 302호 (송정동, 코스마아파트)070-4618-6563
5VIP solution부산광역시 해운대구 윗반송로51번길 59-19(반송동)<NA>
6사회적협동조합 한국클린쿱부산광역시 해운대구 신반송로 151, 반송종합상가 103호 (반송동)<NA>
7에코클린 방역부산광역시 해운대구 해운대로469번가길 91, 상가동 12,13호 (우동, 센텀마리나아파트)1533-3603
8새집줄게 헌집다오부산광역시 해운대구 해운대로61번길 90-1, 샘물교회 2층 (반여동)<NA>
9바이오돔(주)부산광역시 해운대구 해운대로191번길 27, 202호 (재송동)<NA>
소독업소명칭주소전화번호
45(주)에스앤지부산광역시 해운대구 해운대해변로 203, 오션타워 719호 (우동)051-740-5740
46(주)장천<NA>647-0630
47주식회사 동방클린부산광역시 해운대구 우동1로85번길 17, 202호 (우동, 벽산상가)743-4999
48(주)에스지맥스부산광역시 해운대구 재반로112번길 9 (재송동,삼영빌딩 2층)784-2100
49현대종합시스템부산광역시 해운대구 재반로84번길 13, 2층 (재송동)051-783-0011
50보건방역공사부산광역시 해운대구 재송2로28번길 48-5 (재송동)809-2889
51대한환경공사부산광역시 해운대구 재반로 26 (재송동,3층)783-2693
52대영방역공사부산광역시 해운대구 해운대해변로209번나길 12 (우동,세움오피스텔 403호)747-5404
53부일방제부산광역시 해운대구 재반로 162-20 (재송동)782-1880
54(주)부창컨설팅부산광역시 해운대구 좌동순환로433번길 15-1 (중동)051-317-0661