Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory45.5 B

Variable types

Text3
Categorical2

Dataset

Description부산광역시 서구 내에 등록되어 있는 여행업의 상호명, 업종(국내, 국내외, 종합), 주소, 행정동, 연락처의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15007168/fileData.do

Reproduction

Analysis started2023-12-12 20:52:13.415574
Analysis finished2023-12-12 20:52:13.941828
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct17
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T05:52:14.100706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length10
Mean length9.7916667
Min length4

Characters and Unicode

Total characters235
Distinct characters88
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)50.0%

Sample

1st row트레블 고고
2nd row장토푸컴퍼니(Jangtofu Company)
3rd row위드트래블(WITH TRAVEL)
4th row주식회사 모두모아
5th row파란투어
ValueCountFrequency (%)
위드트래블(with 4
 
12.1%
travel 4
 
12.1%
주)미래트레블 2
 
6.1%
곰두리투어 2
 
6.1%
당신이통일입니다 2
 
6.1%
퍼펙트투어 2
 
6.1%
주식회사 2
 
6.1%
동아트래블 1
 
3.0%
세계투어 1
 
3.0%
엠케이마린주식회사 1
 
3.0%
Other values (12) 12
36.4%
2023-12-13T05:52:14.456060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 10
 
4.3%
9
 
3.8%
투 9
 
3.8%
어 9
 
3.8%
블 8
 
3.4%
( 8
 
3.4%
) 8
 
3.4%
T 8
 
3.4%
래 7
 
3.0%
주 6
 
2.6%
Other values (78) 153
65.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
61.3%
Uppercase Letter 44
 
18.7%
Lowercase Letter 21
 
8.9%
Space Separator 9
 
3.8%
Open Punctuation 8
 
3.4%
Close Punctuation 8
 
3.4%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 10
 
6.9%
투 9
 
6.2%
어 9
 
6.2%
블 8
 
5.6%
래 7
 
4.9%
주 6
 
4.2%
사 5
 
3.5%
드 4
 
2.8%
식 4
 
2.8%
회 4
 
2.8%
Other values (50) 78
54.2%
Uppercase Letter
ValueCountFrequency (%)
T 8
18.2%
H 5
11.4%
E 4
9.1%
L 4
9.1%
V 4
9.1%
A 4
9.1%
R 4
9.1%
I 4
9.1%
W 4
9.1%
J 1
 
2.3%
Other values (2) 2
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
a 5
23.8%
n 3
14.3%
o 3
14.3%
l 2
 
9.5%
p 1
 
4.8%
y 1
 
4.8%
m 1
 
4.8%
b 1
 
4.8%
g 1
 
4.8%
t 1
 
4.8%
Other values (2) 2
 
9.5%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
61.7%
Latin 65
27.7%
Common 25
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 10
 
6.9%
투 9
 
6.2%
어 9
 
6.2%
블 8
 
5.5%
래 7
 
4.8%
주 6
 
4.1%
사 5
 
3.4%
드 4
 
2.8%
식 4
 
2.8%
회 4
 
2.8%
Other values (51) 79
54.5%
Latin
ValueCountFrequency (%)
T 8
12.3%
H 5
 
7.7%
a 5
 
7.7%
E 4
 
6.2%
L 4
 
6.2%
V 4
 
6.2%
A 4
 
6.2%
R 4
 
6.2%
I 4
 
6.2%
W 4
 
6.2%
Other values (14) 19
29.2%
Common
ValueCountFrequency (%)
9
36.0%
( 8
32.0%
) 8
32.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
61.3%
ASCII 90
38.3%
None 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 10
 
6.9%
투 9
 
6.2%
어 9
 
6.2%
블 8
 
5.6%
래 7
 
4.9%
주 6
 
4.2%
사 5
 
3.5%
드 4
 
2.8%
식 4
 
2.8%
회 4
 
2.8%
Other values (50) 78
54.2%
ASCII
ValueCountFrequency (%)
9
 
10.0%
( 8
 
8.9%
) 8
 
8.9%
T 8
 
8.9%
H 5
 
5.6%
a 5
 
5.6%
E 4
 
4.4%
L 4
 
4.4%
V 4
 
4.4%
A 4
 
4.4%
Other values (17) 31
34.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업종
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
국내외여행업
10 
종합여행업
8 
국내여행업
6 

Length

Max length6
Median length5
Mean length5.4166667
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합여행업
2nd row종합여행업
3rd row종합여행업
4th row종합여행업
5th row국내여행업

Common Values

ValueCountFrequency (%)
국내외여행업 10
41.7%
종합여행업 8
33.3%
국내여행업 6
25.0%

Length

2023-12-13T05:52:14.644958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:52:14.753310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 10
41.7%
종합여행업 8
33.3%
국내여행업 6
25.0%

소재지주소
Text

Distinct17
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T05:52:15.006103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length36.708333
Min length25

Characters and Unicode

Total characters881
Distinct characters78
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)50.0%

Sample

1st row부산광역시 서구 보동길337번길 12-3 (동대신동3가)
2nd row부산광역시 서구 구덕로185번길 15, 2층(토성동3가, 트윈빌딩)
3rd row부산광역시 서구 보수대로 15, 101동 상가106호(토성동1가, 봄여름가을겨울)
4th row부산광역시 서구 구덕로 186번길 13(토성동3가)
5th row부산광역시 서구 충무대로256번길 7, 505호 (충무동1가)
ValueCountFrequency (%)
부산광역시 24
 
15.3%
서구 24
 
15.3%
구덕로 8
 
5.1%
보수대로 5
 
3.2%
15 5
 
3.2%
2층 4
 
2.5%
서대신동3가 4
 
2.5%
봄여름가을겨울 4
 
2.5%
상가106호(토성동1가 4
 
2.5%
101동 4
 
2.5%
Other values (50) 71
45.2%
2023-12-13T05:52:15.395243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
15.3%
1 44
 
5.0%
동 37
 
4.2%
구 33
 
3.7%
가 32
 
3.6%
부 31
 
3.5%
서 30
 
3.4%
, 29
 
3.3%
2 25
 
2.8%
시 25
 
2.8%
Other values (68) 460
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
57.5%
Decimal Number 161
 
18.3%
Space Separator 135
 
15.3%
Other Punctuation 29
 
3.3%
Open Punctuation 23
 
2.6%
Close Punctuation 23
 
2.6%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
7.3%
구 33
 
6.5%
가 32
 
6.3%
부 31
 
6.1%
서 30
 
5.9%
시 25
 
4.9%
대 24
 
4.7%
산 24
 
4.7%
역 24
 
4.7%
광 24
 
4.7%
Other values (53) 223
44.0%
Decimal Number
ValueCountFrequency (%)
1 44
27.3%
2 25
15.5%
5 22
13.7%
3 22
13.7%
0 15
 
9.3%
6 12
 
7.5%
7 6
 
3.7%
4 6
 
3.7%
9 5
 
3.1%
8 4
 
2.5%
Space Separator
ValueCountFrequency (%)
135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
57.5%
Common 374
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
7.3%
구 33
 
6.5%
가 32
 
6.3%
부 31
 
6.1%
서 30
 
5.9%
시 25
 
4.9%
대 24
 
4.7%
산 24
 
4.7%
역 24
 
4.7%
광 24
 
4.7%
Other values (53) 223
44.0%
Common
ValueCountFrequency (%)
135
36.1%
1 44
 
11.8%
, 29
 
7.8%
2 25
 
6.7%
( 23
 
6.1%
) 23
 
6.1%
5 22
 
5.9%
3 22
 
5.9%
0 15
 
4.0%
6 12
 
3.2%
Other values (5) 24
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
57.5%
ASCII 374
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
36.1%
1 44
 
11.8%
, 29
 
7.8%
2 25
 
6.7%
( 23
 
6.1%
) 23
 
6.1%
5 22
 
5.9%
3 22
 
5.9%
0 15
 
4.0%
6 12
 
3.2%
Other values (5) 24
 
6.4%
Hangul
ValueCountFrequency (%)
동 37
 
7.3%
구 33
 
6.5%
가 32
 
6.3%
부 31
 
6.1%
서 30
 
5.9%
시 25
 
4.9%
대 24
 
4.7%
산 24
 
4.7%
역 24
 
4.7%
광 24
 
4.7%
Other values (53) 223
44.0%

행정동
Categorical

Distinct10
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
충무동
7 
서대신3동
4 
동대신3동
3 
부민동
3 
서대신1동
2 
Other values (5)
5 

Length

Max length6
Median length5
Mean length4.125
Min length3

Unique

Unique5 ?
Unique (%)20.8%

Sample

1st row동대신3동
2nd row충무동
3rd row충무동
4th row충무동
5th row충무동

Common Values

ValueCountFrequency (%)
충무동 7
29.2%
서대신3동 4
16.7%
동대신3동 3
12.5%
부민동 3
12.5%
서대신1동 2
 
8.3%
암남동 1
 
4.2%
동대신2동 1
 
4.2%
<NA> 1
 
4.2%
서대신4동 1
 
4.2%
부민동 1
 
4.2%

Length

2023-12-13T05:52:15.562976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:52:15.682409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충무동 7
29.2%
서대신3동 4
16.7%
부민동 4
16.7%
동대신3동 3
12.5%
서대신1동 2
 
8.3%
암남동 1
 
4.2%
동대신2동 1
 
4.2%
na 1
 
4.2%
서대신4동 1
 
4.2%

전화번호
Text

Distinct12
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T05:52:15.866286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.916667
Min length7

Characters and Unicode

Total characters262
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)16.7%

Sample

1st row070-7561-4763
2nd row051-951-1220
3rd row051-984-0909
4th row051-240-4081
5th row051-248-3666
ValueCountFrequency (%)
개인정보 6
20.0%
포함 6
20.0%
051-984-0909 3
10.0%
051-240-4081 3
10.0%
051-463-0051 2
 
6.7%
051-242-9450 2
 
6.7%
051-441-1444 2
 
6.7%
051-256-5990 2
 
6.7%
070-7561-4763 1
 
3.3%
051-951-1220 1
 
3.3%
Other values (2) 2
 
6.7%
2023-12-13T05:52:16.164260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42
16.0%
- 36
13.7%
1 29
11.1%
4 29
11.1%
5 27
10.3%
9 16
 
6.1%
2 13
 
5.0%
6 9
 
3.4%
9
 
3.4%
8 7
 
2.7%
Other values (8) 45
17.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 181
69.1%
Dash Punctuation 36
 
13.7%
Other Letter 36
 
13.7%
Space Separator 9
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42
23.2%
1 29
16.0%
4 29
16.0%
5 27
14.9%
9 16
 
8.8%
2 13
 
7.2%
6 9
 
5.0%
8 7
 
3.9%
3 6
 
3.3%
7 3
 
1.7%
Other Letter
ValueCountFrequency (%)
포 6
16.7%
함 6
16.7%
인 6
16.7%
보 6
16.7%
정 6
16.7%
개 6
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 226
86.3%
Hangul 36
 
13.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42
18.6%
- 36
15.9%
1 29
12.8%
4 29
12.8%
5 27
11.9%
9 16
 
7.1%
2 13
 
5.8%
6 9
 
4.0%
9
 
4.0%
8 7
 
3.1%
Other values (2) 9
 
4.0%
Hangul
ValueCountFrequency (%)
포 6
16.7%
함 6
16.7%
인 6
16.7%
보 6
16.7%
정 6
16.7%
개 6
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 226
86.3%
Hangul 36
 
13.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42
18.6%
- 36
15.9%
1 29
12.8%
4 29
12.8%
5 27
11.9%
9 16
 
7.1%
2 13
 
5.8%
6 9
 
4.0%
9
 
4.0%
8 7
 
3.1%
Other values (2) 9
 
4.0%
Hangul
ValueCountFrequency (%)
포 6
16.7%
함 6
16.7%
인 6
16.7%
보 6
16.7%
정 6
16.7%
개 6
16.7%

Correlations

2023-12-13T05:52:16.265175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호업종소재지주소행정동전화번호
상호1.0000.0001.0001.0000.987
업종0.0001.0000.0000.0000.000
소재지주소1.0000.0001.0001.0000.987
행정동1.0000.0001.0001.0000.853
전화번호0.9870.0000.9870.8531.000
2023-12-13T05:52:16.368590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종행정동
업종1.0000.000
행정동0.0001.000
2023-12-13T05:52:16.454009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종행정동
업종1.0000.000
행정동0.0001.000

Missing values

2023-12-13T05:52:13.779767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:52:13.895148image/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

상호업종소재지주소행정동전화번호
0트레블 고고종합여행업부산광역시 서구 보동길337번길 12-3 (동대신동3가)동대신3동070-7561-4763
1장토푸컴퍼니(Jangtofu Company)종합여행업부산광역시 서구 구덕로185번길 15, 2층(토성동3가, 트윈빌딩)충무동051-951-1220
2위드트래블(WITH TRAVEL)종합여행업부산광역시 서구 보수대로 15, 101동 상가106호(토성동1가, 봄여름가을겨울)충무동051-984-0909
3주식회사 모두모아종합여행업부산광역시 서구 구덕로 186번길 13(토성동3가)충무동051-240-4081
4파란투어국내여행업부산광역시 서구 충무대로256번길 7, 505호 (충무동1가)충무동051-248-3666
5청춘투어국내외여행업부산광역시 서구 충무대로82번길 27-1, 3층(암남동)암남동051-240-4081
6(주)미래트레블국내여행업부산광역시 서구 망양로 54, 2층 (서대신동3가)서대신3동051-463-0051
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