Overview

Dataset statistics

Number of variables8
Number of observations32
Missing cells25
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory68.1 B

Variable types

Categorical2
DateTime2
Text4

Dataset

Description경기도 용인시 이사화물업체 현황입니다. 인허가일자, 업종구분, 업체명, 주소, 연락처 등의 데이터를 제공합니다. ※ 데이터기준일자 : 2023-04-25
URLhttps://www.data.go.kr/data/15113538/fileData.do

Alerts

시군명 has constant value ""Constant
업종구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
도로명주소 has 1 (3.1%) missing valuesMissing
지번주소 has 1 (3.1%) missing valuesMissing
연락처 has 23 (71.9%) missing valuesMissing
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:52:52.210188
Analysis finished2023-12-12 20:52:52.954453
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
용인시
32 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 32
100.0%

Length

2023-12-13T05:52:53.013849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:52:53.111748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 32
100.0%
Distinct31
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum1989-06-07 00:00:00
Maximum2020-04-10 00:00:00
2023-12-13T05:52:53.219026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:52:53.347349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

업종구분
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
이사화물
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이사화물 32
100.0%

Length

2023-12-13T05:52:53.485081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:52:53.573534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이사화물 32
100.0%

업체명
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-13T05:52:53.750928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.09375
Min length3

Characters and Unicode

Total characters227
Distinct characters89
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

Unique32 ?
Unique (%)100.0%

Sample

1st row(주)로지스프랜드
2nd row(주)무버
3rd row사이버익스프레스
4th row(주)에이플랜로지스틱
5th row(주)하람운수
ValueCountFrequency (%)
주)로지스프랜드 1
 
2.9%
나래익스프레스 1
 
2.9%
태극익스프레스 1
 
2.9%
씰리프로모션 1
 
2.9%
통인익스프레스 1
 
2.9%
정자점 1
 
2.9%
삼성월드트렌스 1
 
2.9%
예은익스프레스 1
 
2.9%
중앙익스프레스 1
 
2.9%
kgb용인 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T05:52:54.127301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
13.2%
14
 
6.2%
12
 
5.3%
12
 
5.3%
10
 
4.4%
8
 
3.5%
( 6
 
2.6%
6
 
2.6%
) 6
 
2.6%
4
 
1.8%
Other values (79) 119
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 205
90.3%
Uppercase Letter 7
 
3.1%
Open Punctuation 6
 
2.6%
Close Punctuation 6
 
2.6%
Space Separator 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
30
 
14.6%
14
 
6.8%
12
 
5.9%
12
 
5.9%
10
 
4.9%
8
 
3.9%
6
 
2.9%
4
 
2.0%
4
 
2.0%
4
 
2.0%
Other values (70) 101
49.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
B 1
14.3%
T 1
14.3%
Y 1
14.3%
L 1
14.3%
K 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 205
90.3%
Common 15
 
6.6%
Latin 7
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
30
 
14.6%
14
 
6.8%
12
 
5.9%
12
 
5.9%
10
 
4.9%
8
 
3.9%
6
 
2.9%
4
 
2.0%
4
 
2.0%
4
 
2.0%
Other values (70) 101
49.3%
Latin
ValueCountFrequency (%)
G 2
28.6%
B 1
14.3%
T 1
14.3%
Y 1
14.3%
L 1
14.3%
K 1
14.3%
Common
ValueCountFrequency (%)
( 6
40.0%
) 6
40.0%
3
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 205
90.3%
ASCII 22
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
30
 
14.6%
14
 
6.8%
12
 
5.9%
12
 
5.9%
10
 
4.9%
8
 
3.9%
6
 
2.9%
4
 
2.0%
4
 
2.0%
4
 
2.0%
Other values (70) 101
49.3%
ASCII
ValueCountFrequency (%)
( 6
27.3%
) 6
27.3%
3
13.6%
G 2
 
9.1%
B 1
 
4.5%
T 1
 
4.5%
Y 1
 
4.5%
L 1
 
4.5%
K 1
 
4.5%

도로명주소
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-13T05:52:54.430193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length31.225806
Min length23

Characters and Unicode

Total characters968
Distinct characters110
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

Unique29 ?
Unique (%)93.5%

Sample

1st row경기도 용인시 기흥구 강남로 6, 605-5호 (구갈동)
2nd row경기도 용인시 기흥구 덕영대로1814번길 3 (하갈동)
3rd row경기도 용인시 처인구 남사읍 원암로 481, 델리후레쉬 2층 1호
4th row경기도 용인시 처인구 양지면 주북로5번길 139
5th row경기도 용인시 처인구 남사읍 천덕산로428번길 63
ValueCountFrequency (%)
경기도 31
 
14.8%
용인시 31
 
14.8%
처인구 15
 
7.2%
기흥구 12
 
5.7%
양지면 4
 
1.9%
수지구 4
 
1.9%
중부대로 4
 
1.9%
신갈동 3
 
1.4%
52 2
 
1.0%
201호 2
 
1.0%
Other values (91) 101
48.3%
2023-12-13T05:52:54.963091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
18.5%
50
 
5.2%
44
 
4.5%
1 34
 
3.5%
32
 
3.3%
32
 
3.3%
32
 
3.3%
32
 
3.3%
32
 
3.3%
31
 
3.2%
Other values (100) 470
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 575
59.4%
Space Separator 179
 
18.5%
Decimal Number 148
 
15.3%
Close Punctuation 22
 
2.3%
Open Punctuation 22
 
2.3%
Other Punctuation 14
 
1.4%
Dash Punctuation 7
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
8.7%
44
 
7.7%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
31
 
5.4%
24
 
4.2%
15
 
2.6%
Other values (84) 251
43.7%
Decimal Number
ValueCountFrequency (%)
1 34
23.0%
2 18
12.2%
0 17
11.5%
3 17
11.5%
4 14
9.5%
5 11
 
7.4%
6 11
 
7.4%
7 10
 
6.8%
9 9
 
6.1%
8 7
 
4.7%
Space Separator
ValueCountFrequency (%)
179
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 575
59.4%
Common 392
40.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
8.7%
44
 
7.7%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
31
 
5.4%
24
 
4.2%
15
 
2.6%
Other values (84) 251
43.7%
Common
ValueCountFrequency (%)
179
45.7%
1 34
 
8.7%
) 22
 
5.6%
( 22
 
5.6%
2 18
 
4.6%
0 17
 
4.3%
3 17
 
4.3%
4 14
 
3.6%
, 14
 
3.6%
5 11
 
2.8%
Other values (5) 44
 
11.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 575
59.4%
ASCII 393
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
45.5%
1 34
 
8.7%
) 22
 
5.6%
( 22
 
5.6%
2 18
 
4.6%
0 17
 
4.3%
3 17
 
4.3%
4 14
 
3.6%
, 14
 
3.6%
5 11
 
2.8%
Other values (6) 45
 
11.5%
Hangul
ValueCountFrequency (%)
50
 
8.7%
44
 
7.7%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
32
 
5.6%
31
 
5.4%
24
 
4.2%
15
 
2.6%
Other values (84) 251
43.7%

지번주소
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing1
Missing (%)3.1%
Memory size388.0 B
2023-12-13T05:52:55.250483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length35
Mean length25.580645
Min length19

Characters and Unicode

Total characters793
Distinct characters99
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

Unique29 ?
Unique (%)93.5%

Sample

1st row경기도 용인시 기흥구 구갈동 595-1 605-5호
2nd row경기도 용인시 처인구 남사읍 방아리 980 델리후레쉬
3rd row경기도 용인시 처인구 양지면 주북리 735-2
4th row경기도 용인시 처인구 남사읍 진목리 267-8
5th row경기도 용인시 처인구 고림동 519-29
ValueCountFrequency (%)
경기도 31
16.9%
용인시 31
16.9%
처인구 16
 
8.7%
기흥구 11
 
6.0%
양지면 4
 
2.2%
수지구 4
 
2.2%
신갈동 3
 
1.6%
삼가동 2
 
1.1%
풍덕천동 2
 
1.1%
포곡읍 2
 
1.1%
Other values (71) 77
42.1%
2023-12-13T05:52:55.805423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
19.2%
50
 
6.3%
42
 
5.3%
33
 
4.2%
32
 
4.0%
31
 
3.9%
31
 
3.9%
31
 
3.9%
1 27
 
3.4%
- 25
 
3.2%
Other values (89) 339
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
59.4%
Space Separator 152
 
19.2%
Decimal Number 145
 
18.3%
Dash Punctuation 25
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
50
 
10.6%
42
 
8.9%
33
 
7.0%
32
 
6.8%
31
 
6.6%
31
 
6.6%
31
 
6.6%
24
 
5.1%
16
 
3.4%
11
 
2.3%
Other values (77) 170
36.1%
Decimal Number
ValueCountFrequency (%)
1 27
18.6%
2 24
16.6%
0 17
11.7%
5 13
9.0%
7 12
8.3%
6 12
8.3%
9 12
8.3%
3 10
 
6.9%
4 10
 
6.9%
8 8
 
5.5%
Space Separator
ValueCountFrequency (%)
152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
59.4%
Common 322
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
50
 
10.6%
42
 
8.9%
33
 
7.0%
32
 
6.8%
31
 
6.6%
31
 
6.6%
31
 
6.6%
24
 
5.1%
16
 
3.4%
11
 
2.3%
Other values (77) 170
36.1%
Common
ValueCountFrequency (%)
152
47.2%
1 27
 
8.4%
- 25
 
7.8%
2 24
 
7.5%
0 17
 
5.3%
5 13
 
4.0%
7 12
 
3.7%
6 12
 
3.7%
9 12
 
3.7%
3 10
 
3.1%
Other values (2) 18
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
59.4%
ASCII 322
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
47.2%
1 27
 
8.4%
- 25
 
7.8%
2 24
 
7.5%
0 17
 
5.3%
5 13
 
4.0%
7 12
 
3.7%
6 12
 
3.7%
9 12
 
3.7%
3 10
 
3.1%
Other values (2) 18
 
5.6%
Hangul
ValueCountFrequency (%)
50
 
10.6%
42
 
8.9%
33
 
7.0%
32
 
6.8%
31
 
6.6%
31
 
6.6%
31
 
6.6%
24
 
5.1%
16
 
3.4%
11
 
2.3%
Other values (77) 170
36.1%

연락처
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing23
Missing (%)71.9%
Memory size388.0 B
2023-12-13T05:52:56.019361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters108
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

Unique9 ?
Unique (%)100.0%

Sample

1st row031-236-2479
2nd row031-421-4924
3rd row031-264-4123
4th row031-285-2400
5th row031-261-2244
ValueCountFrequency (%)
031-236-2479 1
11.1%
031-421-4924 1
11.1%
031-264-4123 1
11.1%
031-285-2400 1
11.1%
031-261-2244 1
11.1%
031-333-1005 1
11.1%
031-336-2444 1
11.1%
031-976-1234 1
11.1%
031-242-2424 1
11.1%
2023-12-13T05:52:56.390069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 18
16.7%
3 17
15.7%
2 17
15.7%
4 16
14.8%
1 14
13.0%
0 13
12.0%
6 5
 
4.6%
9 3
 
2.8%
7 2
 
1.9%
5 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
83.3%
Dash Punctuation 18
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 17
18.9%
2 17
18.9%
4 16
17.8%
1 14
15.6%
0 13
14.4%
6 5
 
5.6%
9 3
 
3.3%
7 2
 
2.2%
5 2
 
2.2%
8 1
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 18
16.7%
3 17
15.7%
2 17
15.7%
4 16
14.8%
1 14
13.0%
0 13
12.0%
6 5
 
4.6%
9 3
 
2.8%
7 2
 
1.9%
5 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 18
16.7%
3 17
15.7%
2 17
15.7%
4 16
14.8%
1 14
13.0%
0 13
12.0%
6 5
 
4.6%
9 3
 
2.8%
7 2
 
1.9%
5 2
 
1.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
Minimum2023-04-25 00:00:00
Maximum2023-04-25 00:00:00
2023-12-13T05:52:56.532080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:52:56.631728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T05:52:56.727630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자업체명도로명주소지번주소연락처
인허가일자1.0001.0000.9910.9911.000
업체명1.0001.0001.0001.0001.000
도로명주소0.9911.0001.0001.0001.000
지번주소0.9911.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000

Missing values

2023-12-13T05:52:52.643617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:52:52.801216image/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.
2023-12-13T05:52:52.906270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명인허가일자업종구분업체명도로명주소지번주소연락처데이터기준일자
0용인시1995-06-17이사화물(주)로지스프랜드경기도 용인시 기흥구 강남로 6, 605-5호 (구갈동)경기도 용인시 기흥구 구갈동 595-1 605-5호<NA>2023-04-25
1용인시2020-04-10이사화물(주)무버경기도 용인시 기흥구 덕영대로1814번길 3 (하갈동)<NA><NA>2023-04-25
2용인시2000-05-09이사화물사이버익스프레스경기도 용인시 처인구 남사읍 원암로 481, 델리후레쉬 2층 1호경기도 용인시 처인구 남사읍 방아리 980 델리후레쉬031-236-24792023-04-25
3용인시2014-11-13이사화물(주)에이플랜로지스틱경기도 용인시 처인구 양지면 주북로5번길 139경기도 용인시 처인구 양지면 주북리 735-2<NA>2023-04-25
4용인시2014-03-24이사화물(주)하람운수경기도 용인시 처인구 남사읍 천덕산로428번길 63경기도 용인시 처인구 남사읍 진목리 267-8<NA>2023-04-25
5용인시2008-07-28이사화물TY로지스경기도 용인시 처인구 경안천로358번길 30-9 (고림동)경기도 용인시 처인구 고림동 519-29<NA>2023-04-25
6용인시2007-05-16이사화물LG이사플러스경기도 용인시 처인구 포곡읍 포곡로61번길 6, 인정멜로디상가경기도 용인시 처인구 포곡읍 둔전리 406-51 인정멜로디상가031-421-49242023-04-25
7용인시2003-02-12이사화물하하이사(용인점)경기도 용인시 기흥구 신갈로 31 (상갈동)경기도 용인시 기흥구 상갈동 165<NA>2023-04-25
8용인시2003-06-10이사화물처인퀵통합콜센터경기도 용인시 기흥구 신정로41번길 52 (신갈동)경기도 용인시 기흥구 신갈동 402-39<NA>2023-04-25
9용인시2003-11-08이사화물신안전화물경기도 용인시 처인구 양지면 주북로5번길 96경기도 용인시 처인구 양지면 주북리 769-2<NA>2023-04-25
시군명인허가일자업종구분업체명도로명주소지번주소연락처데이터기준일자
22용인시1999-09-28이사화물삼성월드트렌스경기도 용인시 처인구 중부대로 1473, 명빌딩 201호 (김량장동)경기도 용인시 처인구 김량장동 74-13 명빌딩<NA>2023-04-25
23용인시1999-09-02이사화물예은익스프레스경기도 용인시 기흥구 중부대로 777 (상하동)경기도 용인시 기흥구 상하동 244-8<NA>2023-04-25
24용인시1998-01-20이사화물나래익스프레스경기도 용인시 기흥구 고매로43번길 32 (공세동, 성호빌딩)경기도 용인시 기흥구 공세동 159031-285-24002023-04-25
25용인시1997-06-14이사화물중앙익스프레스경기도 용인시 기흥구 마북로247번길 55-6 (마북동)경기도 용인시 기흥구 마북동 23-4<NA>2023-04-25
26용인시1997-03-26이사화물수지익스프레스<NA>경기도 용인시 처인구 마평동 670-6031-261-22442023-04-25
27용인시1995-08-21이사화물천호익스프레스경기도 용인시 처인구 주북로 30-13 (고림동)경기도 용인시 처인구 고림동 88 삼미빌딩 2층031-333-10052023-04-25
28용인시1993-03-25이사화물현대익스프레스경기도 용인시 기흥구 죽전로 10, 장은메디칼프라자 601호 (보정동)경기도 용인시 기흥구 보정동 1261-4 장은메디칼프라자 601호031-336-24442023-04-25
29용인시1993-04-12이사화물에이플러스평화이사경기도 용인시 처인구 양지면 중부대로 2038-8, 용인현대자동차공업 4층 401호경기도 용인시 처인구 양지면 남곡리 251-3 용인현대자동차공업<NA>2023-04-25
30용인시1992-10-08이사화물주식회사 새길경기도 용인시 수지구 문인로31번길 7-19, 102호 (풍덕천동)경기도 용인시 수지구 풍덕천동 671-6 102호031-976-12342023-04-25
31용인시1989-06-07이사화물이김이사랜드경기도 용인시 처인구 양지면 남평로 111-73, 10층경기도 용인시 처인구 양지면 양지리 산 89-7031-242-24242023-04-25