Overview

Dataset statistics

Number of variables4
Number of observations52
Missing cells24
Missing cells (%)11.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory34.5 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시_사상구_제과점현황_20230619
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15025668

Alerts

업종명 has constant value ""Constant
소재지전화 has 24 (46.2%) missing valuesMissing
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:39:16.316324
Analysis finished2023-12-10 16:39:16.715292
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
제과점영업
52 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 52
100.0%

Length

2023-12-11T01:39:16.777257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:39:16.888205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 52
100.0%

업소명
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-11T01:39:17.095588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length13
Mean length9.2115385
Min length3

Characters and Unicode

Total characters479
Distinct characters153
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

Unique50 ?
Unique (%)96.2%

Sample

1st row베리노베이커리
2nd row슈메르브레드
3rd row몽블랑베이커리
4th row케익 하우스 델리
5th row데니쉬제과점
ValueCountFrequency (%)
파리바게뜨 6
 
7.4%
뚜레쥬르 4
 
4.9%
사상점 2
 
2.5%
베이커리(bakery 2
 
2.5%
주)신세계푸드 2
 
2.5%
블랑제리 2
 
2.5%
슈슈베어 2
 
2.5%
무무케이크 1
 
1.2%
학장본점 1
 
1.2%
맷돌방아 1
 
1.2%
Other values (58) 58
71.6%
2023-12-11T01:39:17.512339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
6.1%
리 28
 
5.8%
점 22
 
4.6%
이 17
 
3.5%
파 13
 
2.7%
베 13
 
2.7%
( 12
 
2.5%
) 12
 
2.5%
레 10
 
2.1%
바 9
 
1.9%
Other values (143) 314
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
77.7%
Space Separator 29
 
6.1%
Lowercase Letter 27
 
5.6%
Uppercase Letter 24
 
5.0%
Open Punctuation 12
 
2.5%
Close Punctuation 12
 
2.5%
Other Punctuation 2
 
0.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 28
 
7.5%
점 22
 
5.9%
이 17
 
4.6%
파 13
 
3.5%
베 13
 
3.5%
레 10
 
2.7%
바 9
 
2.4%
게 9
 
2.4%
커 9
 
2.4%
뜨 9
 
2.4%
Other values (113) 233
62.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
20.8%
M 3
12.5%
S 2
 
8.3%
E 2
 
8.3%
Y 2
 
8.3%
A 2
 
8.3%
R 1
 
4.2%
L 1
 
4.2%
Z 1
 
4.2%
D 1
 
4.2%
Other values (4) 4
16.7%
Lowercase Letter
ValueCountFrequency (%)
a 5
18.5%
k 4
14.8%
e 4
14.8%
r 4
14.8%
y 3
11.1%
i 2
 
7.4%
t 1
 
3.7%
n 1
 
3.7%
p 1
 
3.7%
o 1
 
3.7%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
77.7%
Common 56
 
11.7%
Latin 51
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 28
 
7.5%
점 22
 
5.9%
이 17
 
4.6%
파 13
 
3.5%
베 13
 
3.5%
레 10
 
2.7%
바 9
 
2.4%
게 9
 
2.4%
커 9
 
2.4%
뜨 9
 
2.4%
Other values (113) 233
62.6%
Latin
ValueCountFrequency (%)
a 5
 
9.8%
B 5
 
9.8%
k 4
 
7.8%
e 4
 
7.8%
r 4
 
7.8%
y 3
 
5.9%
M 3
 
5.9%
S 2
 
3.9%
E 2
 
3.9%
i 2
 
3.9%
Other values (15) 17
33.3%
Common
ValueCountFrequency (%)
29
51.8%
( 12
21.4%
) 12
21.4%
& 2
 
3.6%
2 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
77.7%
ASCII 107
 
22.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
27.1%
( 12
11.2%
) 12
11.2%
a 5
 
4.7%
B 5
 
4.7%
k 4
 
3.7%
e 4
 
3.7%
r 4
 
3.7%
y 3
 
2.8%
M 3
 
2.8%
Other values (20) 26
24.3%
Hangul
ValueCountFrequency (%)
리 28
 
7.5%
점 22
 
5.9%
이 17
 
4.6%
파 13
 
3.5%
베 13
 
3.5%
레 10
 
2.7%
바 9
 
2.4%
게 9
 
2.4%
커 9
 
2.4%
뜨 9
 
2.4%
Other values (113) 233
62.6%

소재지(도로명)
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-11T01:39:17.802015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length30.826923
Min length23

Characters and Unicode

Total characters1603
Distinct characters90
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

Unique52 ?
Unique (%)100.0%

Sample

1st row부산광역시 사상구 사상로 483-1 (모라동)
2nd row부산광역시 사상구 새벽로167번길 5-4 (감전동)
3rd row부산광역시 사상구 사상로531번길 7 (모라동)
4th row부산광역시 사상구 모라로110번길 96, 104호 (모라동, 백양그린@상가)
5th row부산광역시 사상구 학감대로49번길 34 (학장동, 도개공@상가 지하1호)
ValueCountFrequency (%)
부산광역시 52
 
16.2%
사상구 52
 
16.2%
1층 21
 
6.5%
괘법동 12
 
3.7%
주례동 10
 
3.1%
모라동 9
 
2.8%
사상로 7
 
2.2%
엄궁동 7
 
2.2%
덕포동 6
 
1.9%
백양대로 5
 
1.6%
Other values (105) 140
43.6%
2023-12-11T01:39:18.261023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
269
 
16.8%
상 79
 
4.9%
1 70
 
4.4%
사 69
 
4.3%
동 64
 
4.0%
산 58
 
3.6%
광 56
 
3.5%
부 54
 
3.4%
( 53
 
3.3%
) 53
 
3.3%
Other values (80) 778
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 926
57.8%
Space Separator 269
 
16.8%
Decimal Number 246
 
15.3%
Open Punctuation 53
 
3.3%
Close Punctuation 53
 
3.3%
Other Punctuation 46
 
2.9%
Dash Punctuation 7
 
0.4%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 79
 
8.5%
사 69
 
7.5%
동 64
 
6.9%
산 58
 
6.3%
광 56
 
6.0%
부 54
 
5.8%
구 52
 
5.6%
시 52
 
5.6%
역 52
 
5.6%
로 52
 
5.6%
Other values (61) 338
36.5%
Decimal Number
ValueCountFrequency (%)
1 70
28.5%
2 35
14.2%
3 26
 
10.6%
7 24
 
9.8%
4 23
 
9.3%
0 21
 
8.5%
6 15
 
6.1%
5 12
 
4.9%
8 11
 
4.5%
9 9
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 44
95.7%
@ 2
 
4.3%
Space Separator
ValueCountFrequency (%)
269
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 926
57.8%
Common 674
42.0%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 79
 
8.5%
사 69
 
7.5%
동 64
 
6.9%
산 58
 
6.3%
광 56
 
6.0%
부 54
 
5.8%
구 52
 
5.6%
시 52
 
5.6%
역 52
 
5.6%
로 52
 
5.6%
Other values (61) 338
36.5%
Common
ValueCountFrequency (%)
269
39.9%
1 70
 
10.4%
( 53
 
7.9%
) 53
 
7.9%
, 44
 
6.5%
2 35
 
5.2%
3 26
 
3.9%
7 24
 
3.6%
4 23
 
3.4%
0 21
 
3.1%
Other values (6) 56
 
8.3%
Latin
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 926
57.8%
ASCII 677
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
269
39.7%
1 70
 
10.3%
( 53
 
7.8%
) 53
 
7.8%
, 44
 
6.5%
2 35
 
5.2%
3 26
 
3.8%
7 24
 
3.5%
4 23
 
3.4%
0 21
 
3.1%
Other values (9) 59
 
8.7%
Hangul
ValueCountFrequency (%)
상 79
 
8.5%
사 69
 
7.5%
동 64
 
6.9%
산 58
 
6.3%
광 56
 
6.0%
부 54
 
5.8%
구 52
 
5.6%
시 52
 
5.6%
역 52
 
5.6%
로 52
 
5.6%
Other values (61) 338
36.5%

소재지전화
Text

MISSING 

Distinct27
Distinct (%)96.4%
Missing24
Missing (%)46.2%
Memory size548.0 B
2023-12-11T01:39:18.556746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters336
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

Unique26 ?
Unique (%)92.9%

Sample

1st row051-302-1792
2nd row051-323-6206
3rd row051-302-8644
4th row051-304-2925
5th row051-325-8404
ValueCountFrequency (%)
051-754-1554 2
 
7.1%
051-312-1934 1
 
3.6%
051-302-1792 1
 
3.6%
051-326-7444 1
 
3.6%
051-319-9216 1
 
3.6%
051-316-0388 1
 
3.6%
051-282-3136 1
 
3.6%
051-305-4110 1
 
3.6%
051-311-4290 1
 
3.6%
051-916-8000 1
 
3.6%
Other values (17) 17
60.7%
2023-12-11T01:39:19.049902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 56
16.7%
- 56
16.7%
0 46
13.7%
5 42
12.5%
3 41
12.2%
2 30
8.9%
4 20
 
6.0%
6 16
 
4.8%
8 12
 
3.6%
7 9
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
83.3%
Dash Punctuation 56
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 56
20.0%
0 46
16.4%
5 42
15.0%
3 41
14.6%
2 30
10.7%
4 20
 
7.1%
6 16
 
5.7%
8 12
 
4.3%
7 9
 
3.2%
9 8
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 336
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 56
16.7%
- 56
16.7%
0 46
13.7%
5 42
12.5%
3 41
12.2%
2 30
8.9%
4 20
 
6.0%
6 16
 
4.8%
8 12
 
3.6%
7 9
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 56
16.7%
- 56
16.7%
0 46
13.7%
5 42
12.5%
3 41
12.2%
2 30
8.9%
4 20
 
6.0%
6 16
 
4.8%
8 12
 
3.6%
7 9
 
2.7%

Correlations

2023-12-11T01:39:19.211991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지전화
업소명1.0001.0001.000
소재지(도로명)1.0001.0001.000
소재지전화1.0001.0001.000

Missing values

2023-12-11T01:39:16.596978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:39:16.682615image/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

업종명업소명소재지(도로명)소재지전화
0제과점영업베리노베이커리부산광역시 사상구 사상로 483-1 (모라동)051-302-1792
1제과점영업슈메르브레드부산광역시 사상구 새벽로167번길 5-4 (감전동)051-323-6206
2제과점영업몽블랑베이커리부산광역시 사상구 사상로531번길 7 (모라동)051-302-8644
3제과점영업케익 하우스 델리부산광역시 사상구 모라로110번길 96, 104호 (모라동, 백양그린@상가)051-304-2925
4제과점영업데니쉬제과점부산광역시 사상구 학감대로49번길 34 (학장동, 도개공@상가 지하1호)051-325-8404
5제과점영업파란풍차제과점부산광역시 사상구 사상로309번길 7 (덕포동)051-301-5372
6제과점영업파밀리아제과점부산광역시 사상구 대동로 101, 1층 (학장동)051-326-7671
7제과점영업파리바게뜨(주례점)부산광역시 사상구 가야대로282번길 1 (주례동)051-324-7016
8제과점영업델리파티세리부산광역시 사상구 낙동대로 770 (엄궁동)051-328-8054
9제과점영업파레토네제과점부산광역시 사상구 사상로342번길 27, 2동 105호 (덕포동, 벽산늘푸른APT상가)051-304-5232
업종명업소명소재지(도로명)소재지전화
42제과점영업최고다꽈배기부산광역시 사상구 사상로293번길 14, 1층 (덕포동)<NA>
43제과점영업알앤비(R&B)부산광역시 사상구 백양대로 930, 우성모라아파트 상가3동 105호 (모라동)<NA>
44제과점영업파리바게뜨 부산덕포신익부산광역시 사상구 덕상로 16, 벽산신익타운 상가동 101호 (덕포동)<NA>
45제과점영업하리다부산광역시 사상구 운산로 74-1, 1층 (괘법동)<NA>
46제과점영업케이크구나부산광역시 사상구 가야대로284번길 11, 2층 (주례동)<NA>
47제과점영업무무케이크부산광역시 사상구 주례로34번길 43, 1층 (주례동)<NA>
48제과점영업레이지데이(LAZY DAY)부산광역시 사상구 운산로 22, 괘법2차한신아파트 상가12동 2층 203호 (괘법동)<NA>
49제과점영업동백베이커리부산광역시 사상구 사상로 475-14, 1층 (모라동)<NA>
50제과점영업주식회사 마중피엔에프부산광역시 사상구 백양대로 987, 5층 (모라동)051-322-4656
51제과점영업쌀앓이부산광역시 사상구 모라로37번길 28, 1층 (모라동)<NA>