Overview

Dataset statistics

Number of variables5
Number of observations143
Missing cells87
Missing cells (%)12.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory40.9 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description부산광역시 서구 내에 위치한 개인카페에 대한 데이터업종명, 업소명, 소재지의 도로명 주소, 전화번호에 대한 데이터
Author부산광역시 서구
URLhttps://www.data.go.kr/data/15094645/fileData.do

Alerts

업종명 has constant value ""Constant
데이터기준일 has constant value ""Constant
소재지전화 has 87 (60.8%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:34:08.033521
Analysis finished2023-12-12 01:34:08.532201
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
휴게음식점
143 

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 143
100.0%

Length

2023-12-12T10:34:08.607489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:34:08.724593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 143
100.0%

업소명
Text

UNIQUE 

Distinct143
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:34:09.010308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length6.8461538
Min length2

Characters and Unicode

Total characters979
Distinct characters312
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)100.0%

Sample

1st row38도씨
2nd row45번길카페
3rd rowCafe INSTEAD(카페 인스테드)
4th rowEL(이엘)16.52
5th rowmmug ring(엠머그링)
ValueCountFrequency (%)
카페 7
 
3.4%
커피 4
 
1.9%
케이크 2
 
1.0%
커피점 2
 
1.0%
제일통상 2
 
1.0%
라 2
 
1.0%
전차플라워 1
 
0.5%
웨스트사이드 1
 
0.5%
웨슬리 1
 
0.5%
윙고(wingo 1
 
0.5%
Other values (183) 183
88.8%
2023-12-12T10:34:09.514966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
6.4%
피 36
 
3.7%
커 32
 
3.3%
페 26
 
2.7%
카 26
 
2.7%
) 21
 
2.1%
( 21
 
2.1%
이 18
 
1.8%
e 17
 
1.7%
스 16
 
1.6%
Other values (302) 703
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 723
73.9%
Lowercase Letter 85
 
8.7%
Space Separator 63
 
6.4%
Uppercase Letter 49
 
5.0%
Close Punctuation 21
 
2.1%
Open Punctuation 21
 
2.1%
Decimal Number 11
 
1.1%
Other Punctuation 5
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
피 36
 
5.0%
커 32
 
4.4%
페 26
 
3.6%
카 26
 
3.6%
이 18
 
2.5%
스 16
 
2.2%
라 16
 
2.2%
리 14
 
1.9%
다 8
 
1.1%
마 8
 
1.1%
Other values (249) 523
72.3%
Lowercase Letter
ValueCountFrequency (%)
e 17
20.0%
g 6
 
7.1%
i 5
 
5.9%
a 5
 
5.9%
f 5
 
5.9%
r 5
 
5.9%
t 5
 
5.9%
l 4
 
4.7%
s 4
 
4.7%
o 4
 
4.7%
Other values (11) 25
29.4%
Uppercase Letter
ValueCountFrequency (%)
E 7
14.3%
O 6
12.2%
D 4
 
8.2%
A 4
 
8.2%
C 3
 
6.1%
S 3
 
6.1%
N 3
 
6.1%
G 3
 
6.1%
L 3
 
6.1%
U 2
 
4.1%
Other values (8) 11
22.4%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
4 2
18.2%
5 2
18.2%
3 1
 
9.1%
8 1
 
9.1%
6 1
 
9.1%
2 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 2
40.0%
. 2
40.0%
& 1
20.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 721
73.6%
Latin 134
 
13.7%
Common 122
 
12.5%
Han 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
피 36
 
5.0%
커 32
 
4.4%
페 26
 
3.6%
카 26
 
3.6%
이 18
 
2.5%
스 16
 
2.2%
라 16
 
2.2%
리 14
 
1.9%
다 8
 
1.1%
마 8
 
1.1%
Other values (248) 521
72.3%
Latin
ValueCountFrequency (%)
e 17
 
12.7%
E 7
 
5.2%
g 6
 
4.5%
O 6
 
4.5%
i 5
 
3.7%
a 5
 
3.7%
f 5
 
3.7%
r 5
 
3.7%
t 5
 
3.7%
l 4
 
3.0%
Other values (29) 69
51.5%
Common
ValueCountFrequency (%)
63
51.6%
) 21
 
17.2%
( 21
 
17.2%
1 3
 
2.5%
4 2
 
1.6%
, 2
 
1.6%
5 2
 
1.6%
. 2
 
1.6%
- 1
 
0.8%
3 1
 
0.8%
Other values (4) 4
 
3.3%
Han
ValueCountFrequency (%)
如 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 721
73.6%
ASCII 256
 
26.1%
CJK 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
24.6%
) 21
 
8.2%
( 21
 
8.2%
e 17
 
6.6%
E 7
 
2.7%
g 6
 
2.3%
O 6
 
2.3%
i 5
 
2.0%
a 5
 
2.0%
f 5
 
2.0%
Other values (43) 100
39.1%
Hangul
ValueCountFrequency (%)
피 36
 
5.0%
커 32
 
4.4%
페 26
 
3.6%
카 26
 
3.6%
이 18
 
2.5%
스 16
 
2.2%
라 16
 
2.2%
리 14
 
1.9%
다 8
 
1.1%
마 8
 
1.1%
Other values (248) 521
72.3%
CJK
ValueCountFrequency (%)
如 2
100.0%

소재지(도로명)
Text

Distinct141
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T10:34:09.852761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length44
Mean length31.972028
Min length22

Characters and Unicode

Total characters4572
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

Unique139 ?
Unique (%)97.2%

Sample

1st row부산광역시 서구 송도해변로 21, 301동 102호 (암남동, 송도 서린 엘마르)
2nd row부산광역시 서구 대영로45번길 78, 1층 (서대신동3가)
3rd row부산광역시 서구 보수대로 198, 1층 (동대신동2가)
4th row부산광역시 서구 암남공원로 177, 3-4층 (암남동)
5th row부산광역시 서구 구덕로 230-1, 1층 (부민동1가)
ValueCountFrequency (%)
부산광역시 143
 
16.0%
서구 143
 
16.0%
1층 72
 
8.0%
구덕로 22
 
2.5%
암남동 20
 
2.2%
서대신동3가 18
 
2.0%
동대신동3가 16
 
1.8%
서대신동2가 12
 
1.3%
충무동1가 9
 
1.0%
남부민동 9
 
1.0%
Other values (257) 431
48.2%
2023-12-12T10:34:10.418061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
752
 
16.4%
1 245
 
5.4%
동 197
 
4.3%
부 188
 
4.1%
구 182
 
4.0%
서 181
 
4.0%
산 153
 
3.3%
시 148
 
3.2%
광 146
 
3.2%
) 143
 
3.1%
Other values (143) 2237
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2590
56.6%
Decimal Number 773
 
16.9%
Space Separator 752
 
16.4%
Close Punctuation 143
 
3.1%
Open Punctuation 143
 
3.1%
Other Punctuation 136
 
3.0%
Dash Punctuation 30
 
0.7%
Uppercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 197
 
7.6%
부 188
 
7.3%
구 182
 
7.0%
서 181
 
7.0%
산 153
 
5.9%
시 148
 
5.7%
광 146
 
5.6%
역 143
 
5.5%
로 141
 
5.4%
대 126
 
4.9%
Other values (124) 985
38.0%
Decimal Number
ValueCountFrequency (%)
1 245
31.7%
2 137
17.7%
3 107
13.8%
0 55
 
7.1%
5 52
 
6.7%
4 42
 
5.4%
8 40
 
5.2%
6 35
 
4.5%
7 35
 
4.5%
9 25
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
40.0%
L 1
20.0%
G 1
20.0%
C 1
20.0%
Space Separator
ValueCountFrequency (%)
752
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Other Punctuation
ValueCountFrequency (%)
, 136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2590
56.6%
Common 1977
43.2%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 197
 
7.6%
부 188
 
7.3%
구 182
 
7.0%
서 181
 
7.0%
산 153
 
5.9%
시 148
 
5.7%
광 146
 
5.6%
역 143
 
5.5%
로 141
 
5.4%
대 126
 
4.9%
Other values (124) 985
38.0%
Common
ValueCountFrequency (%)
752
38.0%
1 245
 
12.4%
) 143
 
7.2%
( 143
 
7.2%
2 137
 
6.9%
, 136
 
6.9%
3 107
 
5.4%
0 55
 
2.8%
5 52
 
2.6%
4 42
 
2.1%
Other values (5) 165
 
8.3%
Latin
ValueCountFrequency (%)
B 2
40.0%
L 1
20.0%
G 1
20.0%
C 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2590
56.6%
ASCII 1982
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
752
37.9%
1 245
 
12.4%
) 143
 
7.2%
( 143
 
7.2%
2 137
 
6.9%
, 136
 
6.9%
3 107
 
5.4%
0 55
 
2.8%
5 52
 
2.6%
4 42
 
2.1%
Other values (9) 170
 
8.6%
Hangul
ValueCountFrequency (%)
동 197
 
7.6%
부 188
 
7.3%
구 182
 
7.0%
서 181
 
7.0%
산 153
 
5.9%
시 148
 
5.7%
광 146
 
5.6%
역 143
 
5.5%
로 141
 
5.4%
대 126
 
4.9%
Other values (124) 985
38.0%

소재지전화
Text

MISSING 

Distinct54
Distinct (%)96.4%
Missing87
Missing (%)60.8%
Memory size1.2 KiB
2023-12-12T10:34:10.746250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.089286
Min length11

Characters and Unicode

Total characters677
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

Unique52 ?
Unique (%)92.9%

Sample

1st row051-714-5580
2nd row051-710-4546
3rd row0507-1423-7599
4th row051-200-6152
5th row051-241-4484
ValueCountFrequency (%)
051-255-8448 2
 
3.6%
051-200-6152 2
 
3.6%
051-243-3400 1
 
1.8%
051-242-7454 1
 
1.8%
051-243-6192 1
 
1.8%
070-7576-4992 1
 
1.8%
051-253-1828 1
 
1.8%
02-587-0955 1
 
1.8%
051-242-6777 1
 
1.8%
051-254-1286 1
 
1.8%
Other values (44) 44
78.6%
2023-12-12T10:34:11.286348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 112
16.5%
5 102
15.1%
0 97
14.3%
1 88
13.0%
2 74
10.9%
4 60
8.9%
8 35
 
5.2%
3 31
 
4.6%
7 29
 
4.3%
6 26
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 565
83.5%
Dash Punctuation 112
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 102
18.1%
0 97
17.2%
1 88
15.6%
2 74
13.1%
4 60
10.6%
8 35
 
6.2%
3 31
 
5.5%
7 29
 
5.1%
6 26
 
4.6%
9 23
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 112
16.5%
5 102
15.1%
0 97
14.3%
1 88
13.0%
2 74
10.9%
4 60
8.9%
8 35
 
5.2%
3 31
 
4.6%
7 29
 
4.3%
6 26
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 112
16.5%
5 102
15.1%
0 97
14.3%
1 88
13.0%
2 74
10.9%
4 60
8.9%
8 35
 
5.2%
3 31
 
4.6%
7 29
 
4.3%
6 26
 
3.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-11-14 00:00:00
Maximum2023-11-14 00:00:00
2023-12-12T10:34:11.461736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:34:11.595221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-12T10:34:08.366823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:34:08.482315image/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
0휴게음식점38도씨부산광역시 서구 송도해변로 21, 301동 102호 (암남동, 송도 서린 엘마르)<NA>2023-11-14
1휴게음식점45번길카페부산광역시 서구 대영로45번길 78, 1층 (서대신동3가)<NA>2023-11-14
2휴게음식점Cafe INSTEAD(카페 인스테드)부산광역시 서구 보수대로 198, 1층 (동대신동2가)<NA>2023-11-14
3휴게음식점EL(이엘)16.52부산광역시 서구 암남공원로 177, 3-4층 (암남동)051-714-55802023-11-14
4휴게음식점mmug ring(엠머그링)부산광역시 서구 구덕로 230-1, 1층 (부민동1가)<NA>2023-11-14
5휴게음식점가실당부산광역시 서구 구덕로286번길 36, 1층 (동대신동1가)051-710-45462023-11-14
6휴게음식점가온커피부산광역시 서구 암남공원로 235 (암남동)<NA>2023-11-14
7휴게음식점건강을 주는 드림떡.빵부산광역시 서구 망양로21번길 18-1, 1층 (서대신동3가)0507-1423-75992023-11-14
8휴게음식점고분도리카페부산광역시 서구 해돋이로 416 (서대신동2가)<NA>2023-11-14
9휴게음식점고카롱부산광역시 서구 대신공원로 13-5, 102호 (동대신동3가, 베스트빌라)<NA>2023-11-14
업종명업소명소재지(도로명)소재지전화데이터기준일
133휴게음식점하이오부산광역시 서구 동대로19번길 32, 301동 102호 (동대신동3가, 브라운스톤 하이포레)051-242-31772023-11-14
134휴게음식점하트풀커피부산광역시 서구 대신로 141, 1층 (서대신동3가)051-911-12682023-11-14
135휴게음식점핫도그 스테이츠(HotDog States)부산광역시 서구 대티로 173, 1층 104호 (서대신동3가)051-242-58982023-11-14
136휴게음식점해거름커피숍부산광역시 서구 충무대로276번길 14 (충무동1가)051-242-74542023-11-14
137휴게음식점해돋이 카페부산광역시 서구 해돋이로 357-27, 1층 (서대신동1가)<NA>2023-11-14
138휴게음식점행운다방부산광역시 서구 자갈치로 5-1 (충무동1가)<NA>2023-11-14
139휴게음식점헬로우(HELLO)부산광역시 서구 구덕로157번길 3, 1층 (초장동)<NA>2023-11-14
140휴게음식점혜윰부산광역시 서구 꽃마을로 164-10, 지하1층 (서대신동3가)070-8871-88232023-11-14
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