Overview

Dataset statistics

Number of variables4
Number of observations83
Missing cells23
Missing cells (%)6.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory33.6 B

Variable types

Categorical1
Text3

Dataset

Description부산광역시 서구에서 영업중인 유통전문판매업체의 업종에 대한 테이터로 업소명, 주소, 전화번호 정보등의 항목에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15086280/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 23 (27.7%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:05:32.101335
Analysis finished2023-12-12 13:05:32.835576
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
유통전문판매업
83 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 83
100.0%

Length

2023-12-12T22:05:32.927366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:05:33.051162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 83
100.0%

업소명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-12T22:05:33.302394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length7.8433735
Min length3

Characters and Unicode

Total characters651
Distinct characters174
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

Unique83 ?
Unique (%)100.0%

Sample

1st row제일상회
2nd row참손푸드(주)
3rd row희창물산(주)
4th row한림푸드
5th row엠에스 글로벌 바이오 주식회사
ValueCountFrequency (%)
주식회사 9
 
9.4%
제일상회 1
 
1.0%
주)이정푸드 1
 
1.0%
오션트레이딩 1
 
1.0%
주)해청수산 1
 
1.0%
더온푸드 1
 
1.0%
일신수산상사 1
 
1.0%
한수위 1
 
1.0%
주)덕화푸드 1
 
1.0%
송원푸드 1
 
1.0%
Other values (78) 78
81.2%
2023-12-12T22:05:33.707567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 59
 
9.1%
) 50
 
7.7%
( 50
 
7.7%
수 21
 
3.2%
산 21
 
3.2%
푸 20
 
3.1%
드 19
 
2.9%
이 19
 
2.9%
에 15
 
2.3%
사 14
 
2.2%
Other values (164) 363
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 513
78.8%
Close Punctuation 50
 
7.7%
Open Punctuation 50
 
7.7%
Lowercase Letter 15
 
2.3%
Space Separator 13
 
2.0%
Uppercase Letter 7
 
1.1%
Decimal Number 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 59
 
11.5%
수 21
 
4.1%
산 21
 
4.1%
푸 20
 
3.9%
드 19
 
3.7%
이 19
 
3.7%
에 15
 
2.9%
사 14
 
2.7%
회 13
 
2.5%
식 11
 
2.1%
Other values (139) 301
58.7%
Lowercase Letter
ValueCountFrequency (%)
o 3
20.0%
r 2
13.3%
s 1
 
6.7%
u 1
 
6.7%
v 1
 
6.7%
e 1
 
6.7%
t 1
 
6.7%
i 1
 
6.7%
c 1
 
6.7%
d 1
 
6.7%
Other values (2) 2
13.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
14.3%
F 1
14.3%
S 1
14.3%
A 1
14.3%
N 1
14.3%
U 1
14.3%
T 1
14.3%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
5 1
33.3%
1 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
78.8%
Common 116
 
17.8%
Latin 22
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 59
 
11.5%
수 21
 
4.1%
산 21
 
4.1%
푸 20
 
3.9%
드 19
 
3.7%
이 19
 
3.7%
에 15
 
2.9%
사 14
 
2.7%
회 13
 
2.5%
식 11
 
2.1%
Other values (139) 301
58.7%
Latin
ValueCountFrequency (%)
o 3
 
13.6%
r 2
 
9.1%
s 1
 
4.5%
V 1
 
4.5%
F 1
 
4.5%
u 1
 
4.5%
S 1
 
4.5%
v 1
 
4.5%
e 1
 
4.5%
t 1
 
4.5%
Other values (9) 9
40.9%
Common
ValueCountFrequency (%)
) 50
43.1%
( 50
43.1%
13
 
11.2%
3 1
 
0.9%
5 1
 
0.9%
1 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 513
78.8%
ASCII 138
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 59
 
11.5%
수 21
 
4.1%
산 21
 
4.1%
푸 20
 
3.9%
드 19
 
3.7%
이 19
 
3.7%
에 15
 
2.9%
사 14
 
2.7%
회 13
 
2.5%
식 11
 
2.1%
Other values (139) 301
58.7%
ASCII
ValueCountFrequency (%)
) 50
36.2%
( 50
36.2%
13
 
9.4%
o 3
 
2.2%
r 2
 
1.4%
s 1
 
0.7%
V 1
 
0.7%
F 1
 
0.7%
u 1
 
0.7%
S 1
 
0.7%
Other values (15) 15
 
10.9%

소재지(도로명)
Text

Distinct81
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-12T22:05:33.949367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length40
Mean length34.975904
Min length21

Characters and Unicode

Total characters2903
Distinct characters125
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

Unique79 ?
Unique (%)95.2%

Sample

1st row부산광역시 서구 구덕로295번길 18 (서대신동2가)
2nd row부산광역시 서구 원양로 171 (암남동)
3rd row부산광역시 서구 충무대로 146 (남부민동)
4th row부산광역시 서구 충무대로 146 (남부민동)
5th row부산광역시 서구 구덕로 168 (토성동3가, 소문빌딩 3층)
ValueCountFrequency (%)
부산광역시 83
 
14.2%
서구 83
 
14.2%
암남동 50
 
8.6%
원양로 46
 
7.9%
남부민동 21
 
3.6%
충무대로 19
 
3.3%
1 16
 
2.7%
수산가공선진화단지 15
 
2.6%
35 10
 
1.7%
b동 10
 
1.7%
Other values (148) 230
39.5%
2023-12-12T22:05:34.335986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
501
 
17.3%
동 118
 
4.1%
산 115
 
4.0%
1 113
 
3.9%
부 112
 
3.9%
시 100
 
3.4%
, 100
 
3.4%
서 87
 
3.0%
구 87
 
3.0%
) 84
 
2.9%
Other values (115) 1486
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1659
57.1%
Space Separator 501
 
17.3%
Decimal Number 434
 
15.0%
Other Punctuation 101
 
3.5%
Close Punctuation 84
 
2.9%
Open Punctuation 84
 
2.9%
Uppercase Letter 32
 
1.1%
Dash Punctuation 6
 
0.2%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 118
 
7.1%
산 115
 
6.9%
부 112
 
6.8%
시 100
 
6.0%
서 87
 
5.2%
구 87
 
5.2%
광 83
 
5.0%
역 83
 
5.0%
로 80
 
4.8%
남 72
 
4.3%
Other values (91) 722
43.5%
Decimal Number
ValueCountFrequency (%)
1 113
26.0%
0 64
14.7%
2 59
13.6%
3 48
11.1%
5 43
 
9.9%
4 33
 
7.6%
7 21
 
4.8%
6 21
 
4.8%
9 16
 
3.7%
8 16
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 12
37.5%
A 8
25.0%
G 5
15.6%
L 5
15.6%
H 1
 
3.1%
J 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 100
99.0%
& 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
501
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1659
57.1%
Common 1210
41.7%
Latin 34
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 118
 
7.1%
산 115
 
6.9%
부 112
 
6.8%
시 100
 
6.0%
서 87
 
5.2%
구 87
 
5.2%
광 83
 
5.0%
역 83
 
5.0%
로 80
 
4.8%
남 72
 
4.3%
Other values (91) 722
43.5%
Common
ValueCountFrequency (%)
501
41.4%
1 113
 
9.3%
, 100
 
8.3%
) 84
 
6.9%
( 84
 
6.9%
0 64
 
5.3%
2 59
 
4.9%
3 48
 
4.0%
5 43
 
3.6%
4 33
 
2.7%
Other values (6) 81
 
6.7%
Latin
ValueCountFrequency (%)
B 12
35.3%
A 8
23.5%
G 5
14.7%
L 5
14.7%
i 1
 
2.9%
H 1
 
2.9%
J 1
 
2.9%
o 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1659
57.1%
ASCII 1244
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
501
40.3%
1 113
 
9.1%
, 100
 
8.0%
) 84
 
6.8%
( 84
 
6.8%
0 64
 
5.1%
2 59
 
4.7%
3 48
 
3.9%
5 43
 
3.5%
4 33
 
2.7%
Other values (14) 115
 
9.2%
Hangul
ValueCountFrequency (%)
동 118
 
7.1%
산 115
 
6.9%
부 112
 
6.8%
시 100
 
6.0%
서 87
 
5.2%
구 87
 
5.2%
광 83
 
5.0%
역 83
 
5.0%
로 80
 
4.8%
남 72
 
4.3%
Other values (91) 722
43.5%

소재지전화
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing23
Missing (%)27.7%
Memory size796.0 B
2023-12-12T22:05:34.562161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters840
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

Unique60 ?
Unique (%)100.0%

Sample

1st row 051- 256-8582
2nd row 051- 250-7065
3rd row 051- 254-2065
4th row 051- 247-9595
5th row051 -231 -2727
ValueCountFrequency (%)
051 56
32.9%
231 7
 
4.1%
256 6
 
3.5%
254 4
 
2.4%
714 4
 
2.4%
253 4
 
2.4%
244 4
 
2.4%
243 3
 
1.8%
070 3
 
1.8%
265 2
 
1.2%
Other values (74) 77
45.3%
2023-12-12T22:05:34.974341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
14.3%
116
13.8%
5 110
13.1%
1 110
13.1%
0 104
12.4%
2 79
9.4%
3 49
5.8%
4 46
 
5.5%
7 42
 
5.0%
6 26
 
3.1%
Other values (2) 38
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 604
71.9%
Dash Punctuation 120
 
14.3%
Space Separator 116
 
13.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 110
18.2%
1 110
18.2%
0 104
17.2%
2 79
13.1%
3 49
8.1%
4 46
7.6%
7 42
 
7.0%
6 26
 
4.3%
8 23
 
3.8%
9 15
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
14.3%
116
13.8%
5 110
13.1%
1 110
13.1%
0 104
12.4%
2 79
9.4%
3 49
5.8%
4 46
 
5.5%
7 42
 
5.0%
6 26
 
3.1%
Other values (2) 38
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
14.3%
116
13.8%
5 110
13.1%
1 110
13.1%
0 104
12.4%
2 79
9.4%
3 49
5.8%
4 46
 
5.5%
7 42
 
5.0%
6 26
 
3.1%
Other values (2) 38
 
4.5%

Correlations

2023-12-12T22:05:35.114757image/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

2023-12-12T22:05:32.460316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:05:32.778244image/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
0유통전문판매업제일상회부산광역시 서구 구덕로295번길 18 (서대신동2가)051- 256-8582
1유통전문판매업참손푸드(주)부산광역시 서구 원양로 171 (암남동)051- 250-7065
2유통전문판매업희창물산(주)부산광역시 서구 충무대로 146 (남부민동)<NA>
3유통전문판매업한림푸드부산광역시 서구 충무대로 146 (남부민동)051- 254-2065
4유통전문판매업엠에스 글로벌 바이오 주식회사부산광역시 서구 구덕로 168 (토성동3가, 소문빌딩 3층)051- 247-9595
5유통전문판매업유명동수산(주)부산광역시 서구 원양로 310, 702호 (암남동, 동영빌딩)051 -231 -2727
6유통전문판매업(주)블루씨푸드부산광역시 서구 원양로 35, 시장회관동 602호 (암남동, 부산국제수산물도매시장)<NA>
7유통전문판매업(주)백경마린부산광역시 서구 충무대로 181, 304호 (남부민동, LG마린타워)051 -242 -5771
8유통전문판매업(주)폰토스부산광역시 서구 원양로 35, 시장회관동 602호 (암남동, 국제수산물도매시장)051 -256 -7014
9유통전문판매업(주)지엔케이부산광역시 서구 충무대로 146, 704호 (남부민동, 희창물산)051 -231 -1552
업종명업소명소재지(도로명)소재지전화
73유통전문판매업(주)사서삼경부산광역시 서구 보수대로194번길 13, 1층 (동대신동2가)<NA>
74유통전문판매업(주)아토코리아부산광역시 서구 원양로 125, 306호 (암남동)070 -8850-1441
75유통전문판매업주식회사 남선에프에스부산광역시 서구 충무대로 202, 부산공동어시장, 본관 508호 (남부민동)<NA>
76유통전문판매업(주)에프앤티부산광역시 서구 송도해변로 197, 2층 1호 (암남동)<NA>
77유통전문판매업(주)제이앤에이치바이오부산광역시 서구 대영로 79-2, J&H Bio 빌딩 4,6층 (동대신동2가)051 -460 -0431
78유통전문판매업주식회사 아토무역부산광역시 서구 원양로 310, 1001호 (암남동)051 -256 -3100
79유통전문판매업(주)등푸른식품부산광역시 서구 원양로 1, 수산가공선진화단지 A동 402호 (암남동)051 -263 -6363
80유통전문판매업순수네이처부산광역시 서구 해돋이로171번길 17-4, 1층 (초장동)<NA>
81유통전문판매업주식회사 밝은무역부산광역시 서구 원양로 310, 9층 901호 (암남동)051 -256 -0377
82유통전문판매업153구포국수부산광역시 서구 꽃마을로 57, 103동 1904호 (서대신동3가, 서대신금호어울림아파트)051 -315 -0153