Overview

Dataset statistics

Number of variables5
Number of observations93
Missing cells62
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory41.4 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description부산광역시서구_개인카페_20221116
Author부산광역시 서구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15094645

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 62 (66.7%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:47:47.679198
Analysis finished2023-12-10 16:47:48.287135
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
휴게음식점
93 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 93
100.0%

Length

2023-12-11T01:47:48.381187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:47:48.569778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 93
100.0%

업소명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-11T01:47:48.874389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length7.3333333
Min length2

Characters and Unicode

Total characters682
Distinct characters253
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

Unique93 ?
Unique (%)100.0%

Sample

1st row스칼렛커피숖
2nd row휴고
3rd row커피지연
4th row종합강의동 커피점
5th row본(BORN) 95
ValueCountFrequency (%)
카페 8
 
5.8%
커피점 2
 
1.4%
coffee 2
 
1.4%
커피 2
 
1.4%
헬로우(hello 1
 
0.7%
커피나라 1
 
0.7%
커랜 1
 
0.7%
샌치하다 1
 
0.7%
디아펠리즈 1
 
0.7%
윙고(wingo 1
 
0.7%
Other values (119) 119
85.6%
2023-12-11T01:47:49.438910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
6.7%
커 23
 
3.4%
피 23
 
3.4%
페 21
 
3.1%
카 21
 
3.1%
) 17
 
2.5%
( 17
 
2.5%
e 14
 
2.1%
스 11
 
1.6%
이 10
 
1.5%
Other values (243) 479
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 448
65.7%
Lowercase Letter 81
 
11.9%
Uppercase Letter 57
 
8.4%
Space Separator 46
 
6.7%
Close Punctuation 17
 
2.5%
Open Punctuation 17
 
2.5%
Decimal Number 11
 
1.6%
Other Punctuation 4
 
0.6%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
커 23
 
5.1%
피 23
 
5.1%
페 21
 
4.7%
카 21
 
4.7%
스 11
 
2.5%
이 10
 
2.2%
라 9
 
2.0%
리 7
 
1.6%
드 5
 
1.1%
나 5
 
1.1%
Other values (194) 313
69.9%
Lowercase Letter
ValueCountFrequency (%)
e 14
17.3%
f 9
11.1%
a 8
9.9%
i 7
8.6%
l 6
 
7.4%
s 5
 
6.2%
g 5
 
6.2%
n 4
 
4.9%
c 4
 
4.9%
o 3
 
3.7%
Other values (9) 16
19.8%
Uppercase Letter
ValueCountFrequency (%)
O 8
14.0%
C 6
10.5%
E 6
10.5%
A 5
8.8%
N 5
8.8%
G 4
 
7.0%
L 3
 
5.3%
T 3
 
5.3%
U 3
 
5.3%
R 3
 
5.3%
Other values (7) 11
19.3%
Decimal Number
ValueCountFrequency (%)
5 3
27.3%
1 3
27.3%
4 2
18.2%
2 1
 
9.1%
6 1
 
9.1%
9 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
& 1
25.0%
. 1
25.0%
Space Separator
ValueCountFrequency (%)
46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 448
65.7%
Latin 138
 
20.2%
Common 96
 
14.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
커 23
 
5.1%
피 23
 
5.1%
페 21
 
4.7%
카 21
 
4.7%
스 11
 
2.5%
이 10
 
2.2%
라 9
 
2.0%
리 7
 
1.6%
드 5
 
1.1%
나 5
 
1.1%
Other values (194) 313
69.9%
Latin
ValueCountFrequency (%)
e 14
 
10.1%
f 9
 
6.5%
O 8
 
5.8%
a 8
 
5.8%
i 7
 
5.1%
C 6
 
4.3%
l 6
 
4.3%
E 6
 
4.3%
A 5
 
3.6%
s 5
 
3.6%
Other values (26) 64
46.4%
Common
ValueCountFrequency (%)
46
47.9%
) 17
 
17.7%
( 17
 
17.7%
5 3
 
3.1%
1 3
 
3.1%
4 2
 
2.1%
, 2
 
2.1%
& 1
 
1.0%
2 1
 
1.0%
. 1
 
1.0%
Other values (3) 3
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 448
65.7%
ASCII 234
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
19.7%
) 17
 
7.3%
( 17
 
7.3%
e 14
 
6.0%
f 9
 
3.8%
O 8
 
3.4%
a 8
 
3.4%
i 7
 
3.0%
C 6
 
2.6%
l 6
 
2.6%
Other values (39) 96
41.0%
Hangul
ValueCountFrequency (%)
커 23
 
5.1%
피 23
 
5.1%
페 21
 
4.7%
카 21
 
4.7%
스 11
 
2.5%
이 10
 
2.2%
라 9
 
2.0%
리 7
 
1.6%
드 5
 
1.1%
나 5
 
1.1%
Other values (194) 313
69.9%

소재지(도로명)
Text

Distinct92
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size876.0 B
2023-12-11T01:47:49.779917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length33.172043
Min length23

Characters and Unicode

Total characters3085
Distinct characters149
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

Unique91 ?
Unique (%)97.8%

Sample

1st row부산광역시 서구 보수대로 236 (동대신동3가)
2nd row부산광역시 서구 구덕로 303 (서대신동2가)
3rd row부산광역시 서구 대신공원로 26, 1층 (동대신동3가, 동아대학교의료원 신관 에프동 )
4th row부산광역시 서구 구덕로 225 (부민동2가, 종합강의동 지하 1층)
5th row부산광역시 서구 구덕로 238 (부용동1가)
ValueCountFrequency (%)
부산광역시 93
 
15.4%
서구 93
 
15.4%
1층 46
 
7.6%
서대신동3가 15
 
2.5%
구덕로 14
 
2.3%
암남동 11
 
1.8%
동대신동3가 11
 
1.8%
서대신동2가 7
 
1.2%
암남공원로 6
 
1.0%
남부민동 6
 
1.0%
Other values (200) 301
49.9%
2023-12-11T01:47:50.335558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
510
 
16.5%
1 164
 
5.3%
동 136
 
4.4%
부 122
 
4.0%
서 122
 
4.0%
구 114
 
3.7%
, 103
 
3.3%
산 99
 
3.2%
시 97
 
3.1%
광 94
 
3.0%
Other values (139) 1524
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1740
56.4%
Decimal Number 526
 
17.1%
Space Separator 510
 
16.5%
Other Punctuation 103
 
3.3%
Close Punctuation 93
 
3.0%
Open Punctuation 93
 
3.0%
Dash Punctuation 17
 
0.6%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 136
 
7.8%
부 122
 
7.0%
서 122
 
7.0%
구 114
 
6.6%
산 99
 
5.7%
시 97
 
5.6%
광 94
 
5.4%
역 93
 
5.3%
로 90
 
5.2%
대 89
 
5.1%
Other values (121) 684
39.3%
Decimal Number
ValueCountFrequency (%)
1 164
31.2%
2 93
17.7%
3 76
14.4%
0 40
 
7.6%
5 29
 
5.5%
4 28
 
5.3%
7 26
 
4.9%
8 25
 
4.8%
6 25
 
4.8%
9 20
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
L 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
510
100.0%
Other Punctuation
ValueCountFrequency (%)
, 103
100.0%
Close Punctuation
ValueCountFrequency (%)
) 93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1740
56.4%
Common 1342
43.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 136
 
7.8%
부 122
 
7.0%
서 122
 
7.0%
구 114
 
6.6%
산 99
 
5.7%
시 97
 
5.6%
광 94
 
5.4%
역 93
 
5.3%
로 90
 
5.2%
대 89
 
5.1%
Other values (121) 684
39.3%
Common
ValueCountFrequency (%)
510
38.0%
1 164
 
12.2%
, 103
 
7.7%
2 93
 
6.9%
) 93
 
6.9%
( 93
 
6.9%
3 76
 
5.7%
0 40
 
3.0%
5 29
 
2.2%
4 28
 
2.1%
Other values (5) 113
 
8.4%
Latin
ValueCountFrequency (%)
B 1
33.3%
L 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1740
56.4%
ASCII 1345
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
510
37.9%
1 164
 
12.2%
, 103
 
7.7%
2 93
 
6.9%
) 93
 
6.9%
( 93
 
6.9%
3 76
 
5.7%
0 40
 
3.0%
5 29
 
2.2%
4 28
 
2.1%
Other values (8) 116
 
8.6%
Hangul
ValueCountFrequency (%)
동 136
 
7.8%
부 122
 
7.0%
서 122
 
7.0%
구 114
 
6.6%
산 99
 
5.7%
시 97
 
5.6%
광 94
 
5.4%
역 93
 
5.3%
로 90
 
5.2%
대 89
 
5.1%
Other values (121) 684
39.3%

소재지전화
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing62
Missing (%)66.7%
Memory size876.0 B
2023-12-11T01:47:50.576310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.806452
Min length10

Characters and Unicode

Total characters428
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

Unique29 ?
Unique (%)93.5%

Sample

1st row051-244-2816
2nd row051 -256 -0258
3rd row 051- 582-4232
4th row051 -200 -6152
5th row051 -996 -0027
ValueCountFrequency (%)
051 25
31.6%
6152 2
 
2.5%
200 2
 
2.5%
254 2
 
2.5%
255 2
 
2.5%
241 2
 
2.5%
070 2
 
2.5%
244 1
 
1.3%
8888 1
 
1.3%
4484 1
 
1.3%
Other values (39) 39
49.4%
2023-12-11T01:47:51.042385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
14.5%
1 56
13.1%
5 55
12.9%
0 54
12.6%
54
12.6%
2 37
8.6%
4 24
 
5.6%
8 20
 
4.7%
6 18
 
4.2%
9 18
 
4.2%
Other values (2) 30
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 312
72.9%
Dash Punctuation 62
 
14.5%
Space Separator 54
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 56
17.9%
5 55
17.6%
0 54
17.3%
2 37
11.9%
4 24
7.7%
8 20
 
6.4%
6 18
 
5.8%
9 18
 
5.8%
7 15
 
4.8%
3 15
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 428
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
14.5%
1 56
13.1%
5 55
12.9%
0 54
12.6%
54
12.6%
2 37
8.6%
4 24
 
5.6%
8 20
 
4.7%
6 18
 
4.2%
9 18
 
4.2%
Other values (2) 30
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 428
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
14.5%
1 56
13.1%
5 55
12.9%
0 54
12.6%
54
12.6%
2 37
8.6%
4 24
 
5.6%
8 20
 
4.7%
6 18
 
4.2%
9 18
 
4.2%
Other values (2) 30
7.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
Minimum2022-11-16 00:00:00
Maximum2022-11-16 00:00:00
2023-12-11T01:47:51.162842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:47:51.277249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T01:47:51.380444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지전화
업소명1.0001.0001.000
소재지(도로명)1.0001.0000.991
소재지전화1.0000.9911.000

Missing values

2023-12-11T01:47:48.096638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:47:48.234114image/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)소재지전화데이터기준일
0휴게음식점스칼렛커피숖부산광역시 서구 보수대로 236 (동대신동3가)051-244-28162022-11-16
1휴게음식점휴고부산광역시 서구 구덕로 303 (서대신동2가)051 -256 -02582022-11-16
2휴게음식점커피지연부산광역시 서구 대신공원로 26, 1층 (동대신동3가, 동아대학교의료원 신관 에프동 )051- 582-42322022-11-16
3휴게음식점종합강의동 커피점부산광역시 서구 구덕로 225 (부민동2가, 종합강의동 지하 1층)051 -200 -61522022-11-16
4휴게음식점본(BORN) 95부산광역시 서구 구덕로 238 (부용동1가)<NA>2022-11-16
5휴게음식점웨슬리부산광역시 서구 구덕로 236-1, 1층 (부용동1가, 1층일부)051 -996 -00272022-11-16
6휴게음식점전차플라워부산광역시 서구 꽃마을로163번길 25 (서대신동3가)051 -241 -66482022-11-16
7휴게음식점혜윰부산광역시 서구 꽃마을로 164-10, 지하1층 (서대신동3가)070 -8871-88232022-11-16
8휴게음식점커피라이터부산광역시 서구 대영로 78 (동대신동1가, 동대신동시장 1층 일부)<NA>2022-11-16
9휴게음식점미엘부산광역시 서구 임시수도기념로 13 (부민동2가)<NA>2022-11-16
업종명업소명소재지(도로명)소재지전화데이터기준일
83휴게음식점그린하이 커피부산광역시 서구 원양로 1, 수산가공선진화단지 B동 6층 607호 (암남동)<NA>2022-11-16
84휴게음식점mmug ring(엠머그링)부산광역시 서구 구덕로 230-1, 1층 (부민동1가)<NA>2022-11-16
85휴게음식점매일봄부산광역시 서구 꽃마을로 48, 301동 205호 (서대신동3가, 대신 더샵)<NA>2022-11-16
86휴게음식점어르미 눈꽃빙수&커피부산광역시 서구 보수대로280번길 24, 101호 (동대신동3가, 산호오피스텔)<NA>2022-11-16
87휴게음식점쿠앤키부산광역시 서구 고운들로 41, 1층 (부민동3가)<NA>2022-11-16
88휴게음식점카페 데이지민부산광역시 서구 대신로 48, 1층 (서대신동3가)<NA>2022-11-16
89휴게음식점아띠부산광역시 서구 충무대로267번길 4, 1층 (충무동1가)<NA>2022-11-16
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