Overview

Dataset statistics

Number of variables5
Number of observations90
Missing cells56
Missing cells (%)12.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory41.5 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description부산광역시 서구 내에 위치한 프랜차이즈 카페에 대한 데이터업종명, 업소명, 소재지의 도로명 주소, 전화번호에 대한 데이터
Author부산광역시 서구
URLhttps://www.data.go.kr/data/15094648/fileData.do

Alerts

데이터기준일 has constant value ""Constant
소재지전화 has 56 (62.2%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:42:27.390056
Analysis finished2023-12-12 15:42:28.003065
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
휴게음식점
77 
일반음식점
13 

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 77
85.6%
일반음식점 13
 
14.4%

Length

2023-12-13T00:42:28.076589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:28.202328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 77
85.6%
일반음식점 13
 
14.4%

업소명
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T00:42:28.485742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length11.233333
Min length3

Characters and Unicode

Total characters1011
Distinct characters167
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st row(주)이디야 부산송도해상케이블카점
2nd rowcafe051 부산대학병원점
3rd rowCU 서구대신협성점
4th row감성커피 충무대로점
5th row고더커피 동아대부민캠퍼스점
ValueCountFrequency (%)
컴포즈 5
 
2.8%
동아대병원점 5
 
2.8%
서대신점 4
 
2.2%
부산대병원점 4
 
2.2%
투썸플레이스 4
 
2.2%
동대신점 4
 
2.2%
블루샥 3
 
1.7%
부산송도점 3
 
1.7%
하삼동커피 3
 
1.7%
이디야 3
 
1.7%
Other values (118) 143
79.0%
2023-12-13T00:42:29.008361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
9.1%
점 87
 
8.6%
대 52
 
5.1%
부 41
 
4.1%
스 33
 
3.3%
동 33
 
3.3%
피 32
 
3.2%
커 31
 
3.1%
신 30
 
3.0%
산 28
 
2.8%
Other values (157) 552
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 884
87.4%
Space Separator 92
 
9.1%
Decimal Number 15
 
1.5%
Open Punctuation 7
 
0.7%
Close Punctuation 7
 
0.7%
Lowercase Letter 4
 
0.4%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 87
 
9.8%
대 52
 
5.9%
부 41
 
4.6%
스 33
 
3.7%
동 33
 
3.7%
피 32
 
3.6%
커 31
 
3.5%
신 30
 
3.4%
산 28
 
3.2%
도 21
 
2.4%
Other values (141) 496
56.1%
Decimal Number
ValueCountFrequency (%)
0 5
33.3%
5 3
20.0%
1 3
20.0%
8 1
 
6.7%
9 1
 
6.7%
4 1
 
6.7%
2 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
f 1
25.0%
a 1
25.0%
c 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
U 1
50.0%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 884
87.4%
Common 121
 
12.0%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 87
 
9.8%
대 52
 
5.9%
부 41
 
4.6%
스 33
 
3.7%
동 33
 
3.7%
피 32
 
3.6%
커 31
 
3.5%
신 30
 
3.4%
산 28
 
3.2%
도 21
 
2.4%
Other values (141) 496
56.1%
Common
ValueCountFrequency (%)
92
76.0%
( 7
 
5.8%
) 7
 
5.8%
0 5
 
4.1%
5 3
 
2.5%
1 3
 
2.5%
8 1
 
0.8%
9 1
 
0.8%
4 1
 
0.8%
2 1
 
0.8%
Latin
ValueCountFrequency (%)
e 1
16.7%
f 1
16.7%
a 1
16.7%
c 1
16.7%
C 1
16.7%
U 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 884
87.4%
ASCII 127
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
72.4%
( 7
 
5.5%
) 7
 
5.5%
0 5
 
3.9%
5 3
 
2.4%
1 3
 
2.4%
8 1
 
0.8%
e 1
 
0.8%
f 1
 
0.8%
a 1
 
0.8%
Other values (6) 6
 
4.7%
Hangul
ValueCountFrequency (%)
점 87
 
9.8%
대 52
 
5.9%
부 41
 
4.6%
스 33
 
3.7%
동 33
 
3.7%
피 32
 
3.6%
커 31
 
3.5%
신 30
 
3.4%
산 28
 
3.2%
도 21
 
2.4%
Other values (141) 496
56.1%

소재지(도로명)
Text

Distinct89
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-13T00:42:29.425343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length35.744444
Min length24

Characters and Unicode

Total characters3217
Distinct characters155
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

Unique88 ?
Unique (%)97.8%

Sample

1st row부산광역시 서구 송도해변로 171, 3층 (암남동)
2nd row부산광역시 서구 구덕로193번길 12-10 (부민동2가)
3rd row부산광역시 서구 대티로 159, 117동 103,104호 (서대신동3가, 협성르네상스)
4th row부산광역시 서구 충무대로 163-2, 1층 (남부민동)
5th row부산광역시 서구 구덕로 224, 스카이파크 빌딩 102호 (부민동1가)
ValueCountFrequency (%)
부산광역시 90
 
14.5%
서구 90
 
14.5%
1층 45
 
7.3%
암남동 23
 
3.7%
구덕로 20
 
3.2%
송도해변로 12
 
1.9%
동대신동3가 10
 
1.6%
서대신동3가 9
 
1.5%
부민동1가 8
 
1.3%
101호 7
 
1.1%
Other values (203) 305
49.3%
2023-12-13T00:42:30.001174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
529
 
16.4%
1 220
 
6.8%
동 128
 
4.0%
구 122
 
3.8%
부 120
 
3.7%
서 110
 
3.4%
, 107
 
3.3%
시 96
 
3.0%
산 93
 
2.9%
로 92
 
2.9%
Other values (145) 1600
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1827
56.8%
Decimal Number 547
 
17.0%
Space Separator 529
 
16.4%
Other Punctuation 107
 
3.3%
Close Punctuation 90
 
2.8%
Open Punctuation 90
 
2.8%
Dash Punctuation 22
 
0.7%
Uppercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 128
 
7.0%
구 122
 
6.7%
부 120
 
6.6%
서 110
 
6.0%
시 96
 
5.3%
산 93
 
5.1%
로 92
 
5.0%
광 91
 
5.0%
역 90
 
4.9%
대 72
 
3.9%
Other values (127) 813
44.5%
Decimal Number
ValueCountFrequency (%)
1 220
40.2%
2 91
16.6%
3 63
 
11.5%
0 49
 
9.0%
4 23
 
4.2%
9 23
 
4.2%
5 21
 
3.8%
7 21
 
3.8%
8 19
 
3.5%
6 17
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
R 1
 
25.0%
Space Separator
ValueCountFrequency (%)
529
100.0%
Other Punctuation
ValueCountFrequency (%)
, 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1827
56.8%
Common 1386
43.1%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 128
 
7.0%
구 122
 
6.7%
부 120
 
6.6%
서 110
 
6.0%
시 96
 
5.3%
산 93
 
5.1%
로 92
 
5.0%
광 91
 
5.0%
역 90
 
4.9%
대 72
 
3.9%
Other values (127) 813
44.5%
Common
ValueCountFrequency (%)
529
38.2%
1 220
15.9%
, 107
 
7.7%
2 91
 
6.6%
) 90
 
6.5%
( 90
 
6.5%
3 63
 
4.5%
0 49
 
3.5%
4 23
 
1.7%
9 23
 
1.7%
Other values (6) 101
 
7.3%
Latin
ValueCountFrequency (%)
B 3
75.0%
R 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1827
56.8%
ASCII 1390
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
529
38.1%
1 220
15.8%
, 107
 
7.7%
2 91
 
6.5%
) 90
 
6.5%
( 90
 
6.5%
3 63
 
4.5%
0 49
 
3.5%
4 23
 
1.7%
9 23
 
1.7%
Other values (8) 105
 
7.6%
Hangul
ValueCountFrequency (%)
동 128
 
7.0%
구 122
 
6.7%
부 120
 
6.6%
서 110
 
6.0%
시 96
 
5.3%
산 93
 
5.1%
로 92
 
5.0%
광 91
 
5.0%
역 90
 
4.9%
대 72
 
3.9%
Other values (127) 813
44.5%

소재지전화
Text

MISSING 

Distinct34
Distinct (%)100.0%
Missing56
Missing (%)62.2%
Memory size852.0 B
2023-12-13T00:42:30.280233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.147059
Min length12

Characters and Unicode

Total characters413
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

Unique34 ?
Unique (%)100.0%

Sample

1st row051-254-1051
2nd row051-254-3557
3rd row051-207-1544
4th row051-246-5353
5th row051-248-0022
ValueCountFrequency (%)
051-245-3131 1
 
2.9%
051-253-0401 1
 
2.9%
070-7537-3631 1
 
2.9%
051-241-5334 1
 
2.9%
051-992-3696 1
 
2.9%
051-917-9000 1
 
2.9%
051-247-2388 1
 
2.9%
051-248-8497 1
 
2.9%
051-936-0369 1
 
2.9%
051-254-3557 1
 
2.9%
Other values (24) 24
70.6%
2023-12-13T00:42:30.834528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 68
16.5%
1 63
15.3%
0 58
14.0%
5 56
13.6%
2 37
9.0%
4 34
8.2%
3 25
 
6.1%
7 23
 
5.6%
8 22
 
5.3%
9 14
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 345
83.5%
Dash Punctuation 68
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 63
18.3%
0 58
16.8%
5 56
16.2%
2 37
10.7%
4 34
9.9%
3 25
 
7.2%
7 23
 
6.7%
8 22
 
6.4%
9 14
 
4.1%
6 13
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 413
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 68
16.5%
1 63
15.3%
0 58
14.0%
5 56
13.6%
2 37
9.0%
4 34
8.2%
3 25
 
6.1%
7 23
 
5.6%
8 22
 
5.3%
9 14
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 68
16.5%
1 63
15.3%
0 58
14.0%
5 56
13.6%
2 37
9.0%
4 34
8.2%
3 25
 
6.1%
7 23
 
5.6%
8 22
 
5.3%
9 14
 
3.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2023-11-14 00:00:00
Maximum2023-11-14 00:00:00
2023-12-13T00:42:30.997924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:31.119766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T00:42:31.193897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업소명소재지(도로명)소재지전화
업종1.0001.0000.0001.000
업소명1.0001.0001.0001.000
소재지(도로명)0.0001.0001.0001.000
소재지전화1.0001.0001.0001.000

Missing values

2023-12-13T00:42:27.842121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:42:27.956222image/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

업종업소명소재지(도로명)소재지전화데이터기준일
0휴게음식점(주)이디야 부산송도해상케이블카점부산광역시 서구 송도해변로 171, 3층 (암남동)<NA>2023-11-14
1휴게음식점cafe051 부산대학병원점부산광역시 서구 구덕로193번길 12-10 (부민동2가)051-254-10512023-11-14
2휴게음식점CU 서구대신협성점부산광역시 서구 대티로 159, 117동 103,104호 (서대신동3가, 협성르네상스)<NA>2023-11-14
3휴게음식점감성커피 충무대로점부산광역시 서구 충무대로 163-2, 1층 (남부민동)051-254-35572023-11-14
4휴게음식점고더커피 동아대부민캠퍼스점부산광역시 서구 구덕로 224, 스카이파크 빌딩 102호 (부민동1가)<NA>2023-11-14
5휴게음식점공차 부산동대신점부산광역시 서구 구덕로 316 (동대신동2가)<NA>2023-11-14
6휴게음식점공차 부산동아대부민점부산광역시 서구 구덕로 220, 한웅캠퍼스타워 1층 101호 (부민동1가)<NA>2023-11-14
7휴게음식점공차 부산송도점부산광역시 서구 송도해변로 81, 2,3층 (암남동)<NA>2023-11-14
8휴게음식점그릭하다부산광역시 서구 대청로 3, 1층 (부민동1가)<NA>2023-11-14
9휴게음식점김준호의 대단한커피 부산토성점부산광역시 서구 구덕로 지하 170 (토성동3가)<NA>2023-11-14
업종업소명소재지(도로명)소재지전화데이터기준일
80휴게음식점하삼동 대신푸르지오점부산광역시 서구 고운들로 142, 1층 (서대신동1가)051-911-11762023-11-14
81휴게음식점하삼동 커피 동대신동점부산광역시 서구 구덕로334번길 6 (동대신동3가)051-243-14542023-11-14
82휴게음식점하삼동커피 동아대병원점부산광역시 서구 동대로19번길 32, 301동 103호 (동대신동3가, 브라운스톤 하이포레)051-231-22662023-11-14
83휴게음식점하삼동커피 송도이진베이시티점부산광역시 서구 송도해변로 192, 부대복리시설B동 110호 (암남동, 송도힐스테이트이진베이시티아파트)051-256-15772023-11-14
84휴게음식점하삼동커피 자갈치역점부산광역시 서구 구덕로 102-1, 1층 (충무동1가)<NA>2023-11-14
85휴게음식점하삼동커피(동아대부민캠퍼스점)부산광역시 서구 구덕로 224, 스카이파크 빌딩 106호 (부민동1가)070-8822-13112023-11-14
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