Overview

Dataset statistics

Number of variables4
Number of observations27
Missing cells3
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory992.0 B
Average record size in memory36.7 B

Variable types

Text4

Dataset

Description울산광역시 남구 모범부동산중개업소 정보에 대한 데이터로 사무소명, 대표, 연락처, 소재지도로명주소의 항목을 제공합니다.
Author울산광역시 남구
URLhttps://www.data.go.kr/data/3069043/fileData.do

Alerts

연락처 has 3 (11.1%) missing valuesMissing
사무소명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:12:34.775228
Analysis finished2024-03-15 00:12:35.561258
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T09:12:36.162670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.259259
Min length10

Characters and Unicode

Total characters304
Distinct characters66
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowMK공인중개사사무소
2nd row현대뜰공인중개사사무소
3rd row어울림공인중개사사무소
4th row신정미소공인중개사사무소
5th row태경공인중개사사무소
ValueCountFrequency (%)
mk공인중개사사무소 1
 
3.7%
무궁화공인중개사사무소 1
 
3.7%
롯데사랑공인중개사사무소 1
 
3.7%
권민조공인중개사사무소 1
 
3.7%
그린공인중개사사무소 1
 
3.7%
뉴삼산공인중개사사무소 1
 
3.7%
새)희망공인중개사사무소 1
 
3.7%
동원공인중개사사무소 1
 
3.7%
태양공인중개사사무소 1
 
3.7%
키움부동산공인중개사사무소 1
 
3.7%
Other values (17) 17
63.0%
2024-03-15T09:12:37.427826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 55
18.1%
소 30
9.9%
무 29
9.5%
개 28
9.2%
인 27
8.9%
중 27
8.9%
공 26
 
8.6%
동 8
 
2.6%
산 5
 
1.6%
부 4
 
1.3%
Other values (56) 65
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
96.4%
Uppercase Letter 5
 
1.6%
Decimal Number 4
 
1.3%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 55
18.8%
소 30
10.2%
무 29
9.9%
개 28
9.6%
인 27
9.2%
중 27
9.2%
공 26
8.9%
동 8
 
2.7%
산 5
 
1.7%
부 4
 
1.4%
Other values (46) 54
18.4%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
L 1
20.0%
B 1
20.0%
A 1
20.0%
K 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 1
25.0%
4 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
96.4%
Common 6
 
2.0%
Latin 5
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 55
18.8%
소 30
10.2%
무 29
9.9%
개 28
9.6%
인 27
9.2%
중 27
9.2%
공 26
8.9%
동 8
 
2.7%
산 5
 
1.7%
부 4
 
1.4%
Other values (46) 54
18.4%
Common
ValueCountFrequency (%)
1 2
33.3%
( 1
16.7%
2 1
16.7%
) 1
16.7%
4 1
16.7%
Latin
ValueCountFrequency (%)
M 1
20.0%
L 1
20.0%
B 1
20.0%
A 1
20.0%
K 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
96.4%
ASCII 11
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 55
18.8%
소 30
10.2%
무 29
9.9%
개 28
9.6%
인 27
9.2%
중 27
9.2%
공 26
8.9%
동 8
 
2.7%
산 5
 
1.7%
부 4
 
1.4%
Other values (46) 54
18.4%
ASCII
ValueCountFrequency (%)
1 2
18.2%
( 1
9.1%
2 1
9.1%
) 1
9.1%
M 1
9.1%
4 1
9.1%
L 1
9.1%
B 1
9.1%
A 1
9.1%
K 1
9.1%

대표
Text

Distinct14
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T09:12:37.934003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.962963
Min length2

Characters and Unicode

Total characters80
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)33.3%

Sample

1st row천**
2nd row김**
3rd row오**
4th row권**
5th row장**
ValueCountFrequency (%)
김 5
18.5%
이 4
14.8%
권 3
11.1%
장 3
11.1%
한 3
11.1%
박 2
 
7.4%
천 1
 
3.7%
오 1
 
3.7%
원 1
 
3.7%
진 1
 
3.7%
Other values (3) 3
11.1%
2024-03-15T09:12:38.594030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 53
66.2%
김 5
 
6.2%
이 4
 
5.0%
권 3
 
3.8%
장 3
 
3.8%
한 3
 
3.8%
박 2
 
2.5%
천 1
 
1.2%
오 1
 
1.2%
원 1
 
1.2%
Other values (4) 4
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 53
66.2%
Other Letter 27
33.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 5
18.5%
이 4
14.8%
권 3
11.1%
장 3
11.1%
한 3
11.1%
박 2
 
7.4%
천 1
 
3.7%
오 1
 
3.7%
원 1
 
3.7%
진 1
 
3.7%
Other values (3) 3
11.1%
Other Punctuation
ValueCountFrequency (%)
* 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53
66.2%
Hangul 27
33.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 5
18.5%
이 4
14.8%
권 3
11.1%
장 3
11.1%
한 3
11.1%
박 2
 
7.4%
천 1
 
3.7%
오 1
 
3.7%
원 1
 
3.7%
진 1
 
3.7%
Other values (3) 3
11.1%
Common
ValueCountFrequency (%)
* 53
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
66.2%
Hangul 27
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 53
100.0%
Hangul
ValueCountFrequency (%)
김 5
18.5%
이 4
14.8%
권 3
11.1%
장 3
11.1%
한 3
11.1%
박 2
 
7.4%
천 1
 
3.7%
오 1
 
3.7%
원 1
 
3.7%
진 1
 
3.7%
Other values (3) 3
11.1%

연락처
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing3
Missing (%)11.1%
Memory size344.0 B
2024-03-15T09:12:39.364505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row052-227-0055
2nd row052-285-3600
3rd row052-260-0408
4th row052-272-4433
5th row052-221-1737
ValueCountFrequency (%)
052-224-1388 1
 
4.2%
052-260-0408 1
 
4.2%
052-260-8040 1
 
4.2%
052-227-3324 1
 
4.2%
052-249-0088 1
 
4.2%
052-273-8998 1
 
4.2%
052-288-4013 1
 
4.2%
052-227-8289 1
 
4.2%
052-258-7177 1
 
4.2%
052-267-6601 1
 
4.2%
Other values (14) 14
58.3%
2024-03-15T09:12:40.540271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 55
19.1%
0 49
17.0%
- 48
16.7%
5 36
12.5%
8 20
 
6.9%
7 17
 
5.9%
3 14
 
4.9%
9 14
 
4.9%
4 13
 
4.5%
6 13
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 55
22.9%
0 49
20.4%
5 36
15.0%
8 20
 
8.3%
7 17
 
7.1%
3 14
 
5.8%
9 14
 
5.8%
4 13
 
5.4%
6 13
 
5.4%
1 9
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 55
19.1%
0 49
17.0%
- 48
16.7%
5 36
12.5%
8 20
 
6.9%
7 17
 
5.9%
3 14
 
4.9%
9 14
 
4.9%
4 13
 
4.5%
6 13
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 55
19.1%
0 49
17.0%
- 48
16.7%
5 36
12.5%
8 20
 
6.9%
7 17
 
5.9%
3 14
 
4.9%
9 14
 
4.9%
4 13
 
4.5%
6 13
 
4.5%

소재지도로명주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T09:12:41.305766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length24.518519
Min length20

Characters and Unicode

Total characters662
Distinct characters56
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

Unique27 ?
Unique (%)100.0%

Sample

1st row울산광역시 남구 문수로314번길 7(옥동)
2nd row울산광역시 남구 신남로 34(신정동)
3rd row울산광역시 남구 도산로77번길16(달동)
4th row울산광역시 남구 대암로 20, 상가102호(신정동)
5th row울산광역시 남구 신복로72번길 28-35(무거동)
ValueCountFrequency (%)
울산광역시 27
22.7%
남구 27
22.7%
대암로 3
 
2.5%
동산로 2
 
1.7%
중앙로 2
 
1.7%
1층(야음동 2
 
1.7%
봉월로59번길 2
 
1.7%
신선로 1
 
0.8%
중앙로156번길 1
 
0.8%
팔등로 1
 
0.8%
Other values (51) 51
42.9%
2024-03-15T09:12:42.457894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
 
13.9%
산 32
 
4.8%
동 31
 
4.7%
남 28
 
4.2%
울 27
 
4.1%
( 27
 
4.1%
광 27
 
4.1%
역 27
 
4.1%
시 27
 
4.1%
구 27
 
4.1%
Other values (46) 317
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
58.6%
Decimal Number 118
 
17.8%
Space Separator 92
 
13.9%
Open Punctuation 27
 
4.1%
Close Punctuation 27
 
4.1%
Other Punctuation 6
 
0.9%
Dash Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
 
8.2%
동 31
 
8.0%
남 28
 
7.2%
울 27
 
7.0%
광 27
 
7.0%
역 27
 
7.0%
시 27
 
7.0%
구 27
 
7.0%
로 27
 
7.0%
신 16
 
4.1%
Other values (31) 119
30.7%
Decimal Number
ValueCountFrequency (%)
1 27
22.9%
2 17
14.4%
0 13
11.0%
3 13
11.0%
5 11
9.3%
4 10
 
8.5%
6 8
 
6.8%
7 8
 
6.8%
9 7
 
5.9%
8 4
 
3.4%
Space Separator
ValueCountFrequency (%)
92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
58.6%
Common 274
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
 
8.2%
동 31
 
8.0%
남 28
 
7.2%
울 27
 
7.0%
광 27
 
7.0%
역 27
 
7.0%
시 27
 
7.0%
구 27
 
7.0%
로 27
 
7.0%
신 16
 
4.1%
Other values (31) 119
30.7%
Common
ValueCountFrequency (%)
92
33.6%
( 27
 
9.9%
) 27
 
9.9%
1 27
 
9.9%
2 17
 
6.2%
0 13
 
4.7%
3 13
 
4.7%
5 11
 
4.0%
4 10
 
3.6%
6 8
 
2.9%
Other values (5) 29
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
58.6%
ASCII 274
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
33.6%
( 27
 
9.9%
) 27
 
9.9%
1 27
 
9.9%
2 17
 
6.2%
0 13
 
4.7%
3 13
 
4.7%
5 11
 
4.0%
4 10
 
3.6%
6 8
 
2.9%
Other values (5) 29
 
10.6%
Hangul
ValueCountFrequency (%)
산 32
 
8.2%
동 31
 
8.0%
남 28
 
7.2%
울 27
 
7.0%
광 27
 
7.0%
역 27
 
7.0%
시 27
 
7.0%
구 27
 
7.0%
로 27
 
7.0%
신 16
 
4.1%
Other values (31) 119
30.7%

Correlations

2024-03-15T09:12:42.723059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사무소명대표연락처소재지도로명주소
사무소명1.0001.0001.0001.000
대표1.0001.0001.0001.000
연락처1.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.000

Missing values

2024-03-15T09:12:35.162233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:12:35.453237image/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

사무소명대표연락처소재지도로명주소
0MK공인중개사사무소천**052-227-0055울산광역시 남구 문수로314번길 7(옥동)
1현대뜰공인중개사사무소김**052-285-3600울산광역시 남구 신남로 34(신정동)
2어울림공인중개사사무소오**052-260-0408울산광역시 남구 도산로77번길16(달동)
3신정미소공인중개사사무소권**052-272-4433울산광역시 남구 대암로 20, 상가102호(신정동)
4태경공인중개사사무소장**052-221-1737울산광역시 남구 신복로72번길 28-35(무거동)
5옥동인벤스공인중개사사무소김**052-227-8555울산광역시 남구 문수로335번길 6 104호(옥동)
6미소사랑공인중개사사무소김**052-900-8949울산광역시 남구 대암로 19(신정동)
7114부동산공인중개사사무소한**052-260-3440울산광역시 남구 봉월로59번길 18(신정동)
8LBA옥동공인중개사사무소김**052-265-1334울산광역시 남구 거마로30번길 20(신정동)
9킹덤공인중개사사무소원**052-276-0087울산광역시 남구 문수로 471(신정동)
사무소명대표연락처소재지도로명주소
17번개공인중개사사무소남**<NA>울산광역시 남구 수암로 276 1층(야음동)
18키움부동산공인중개사사무소한**<NA>울산광역시 남구 중앙로156번길 33(달동)
19태양공인중개사사무소이**052-267-6601울산광역시 남구 봉월로59번길 18, 1층(신정동)
20동원공인중개사사무소어**052-258-7177울산광역시 남구 수암로155번길 29(야음동)
21(새)희망공인중개사사무소한**052-227-8289울산광역시 남구 동산로 56(신정동)
22뉴삼산공인중개사사무소권**052-288-4013울산광역시 남구 삼산중로131번길 21-2(삼산동)
23그린공인중개사사무소장**052-273-8998울산광역시 남구 중앙로 29, 1층(야음동)
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25롯데사랑공인중개사사무소박**052-227-3324울산광역시 남구 신선로 45, 상가 102호(야음동)
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