Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells17048
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory673.8 KiB
Average record size in memory69.0 B

Variable types

Numeric4
Text2
Unsupported1

Dataset

Description경상남도 도립남해대학 우편 DB입니다. (우편번호1, 우편번호2, 주소 )
Author경상남도
URLhttps://www.data.go.kr/data/15039601/fileData.do

Alerts

순번 is highly overall correlated with G|시도구분|시도코드High correlation
우편번호1 is highly overall correlated with G|시도구분|시도코드High correlation
G|시도구분|시도코드 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
번지_APT동 has 7048 (70.5%) missing valuesMissing
사서함등 has 10000 (100.0%) missing valuesMissing
순번 has unique valuesUnique
사서함등 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 23:17:45.913617
Analysis finished2023-12-11 23:17:49.303492
Duration3.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20082.541
Minimum5
Maximum40091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:17:49.379398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile1952.95
Q110167.25
median20022.5
Q330155.5
95-th percentile38036.6
Maximum40091
Range40086
Interquartile range (IQR)19988.25

Descriptive statistics

Standard deviation11584.721
Coefficient of variation (CV)0.57685533
Kurtosis-1.1985176
Mean20082.541
Median Absolute Deviation (MAD)9994
Skewness-0.0083196185
Sum2.0082541 × 108
Variance1.3420576 × 108
MonotonicityNot monotonic
2023-12-12T08:17:49.592649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18424 1
 
< 0.1%
27123 1
 
< 0.1%
29311 1
 
< 0.1%
34307 1
 
< 0.1%
24868 1
 
< 0.1%
27663 1
 
< 0.1%
12115 1
 
< 0.1%
1098 1
 
< 0.1%
25493 1
 
< 0.1%
33733 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
5 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
24 1
< 0.1%
25 1
< 0.1%
30 1
< 0.1%
32 1
< 0.1%
33 1
< 0.1%
ValueCountFrequency (%)
40091 1
< 0.1%
40082 1
< 0.1%
40075 1
< 0.1%
40069 1
< 0.1%
40068 1
< 0.1%
40064 1
< 0.1%
40057 1
< 0.1%
40056 1
< 0.1%
40054 1
< 0.1%
40045 1
< 0.1%

우편번호1
Real number (ℝ)

HIGH CORRELATION 

Distinct248
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean464.7748
Minimum100
Maximum799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:17:49.746572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile134
Q1336
median480
Q3621
95-th percentile755
Maximum799
Range699
Interquartile range (IQR)285

Descriptive statistics

Standard deviation196.79645
Coefficient of variation (CV)0.42342324
Kurtosis-0.9811184
Mean464.7748
Median Absolute Deviation (MAD)142.5
Skewness-0.29832968
Sum4647748
Variance38728.844
MonotonicityNot monotonic
2023-12-12T08:17:49.888246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135 124
 
1.2%
151 98
 
1.0%
540 97
 
1.0%
560 93
 
0.9%
139 87
 
0.9%
150 83
 
0.8%
100 76
 
0.8%
157 75
 
0.8%
641 75
 
0.8%
704 74
 
0.7%
Other values (238) 9118
91.2%
ValueCountFrequency (%)
100 76
0.8%
110 70
0.7%
120 39
0.4%
121 52
0.5%
122 54
0.5%
130 35
0.4%
131 58
0.6%
132 67
0.7%
133 42
0.4%
134 37
0.4%
ValueCountFrequency (%)
799 3
 
< 0.1%
791 45
0.4%
790 44
0.4%
780 72
0.7%
770 51
0.5%
769 48
0.5%
767 31
0.3%
766 38
0.4%
764 21
 
0.2%
763 29
0.3%

우편번호2
Real number (ℝ)

Distinct537
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean752.736
Minimum3
Maximum998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:17:50.019503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile100
Q1768
median823
Q3862
95-th percentile931
Maximum998
Range995
Interquartile range (IQR)94

Descriptive statistics

Standard deviation228.39268
Coefficient of variation (CV)0.30341671
Kurtosis3.7638919
Mean752.736
Median Absolute Deviation (MAD)43
Skewness-2.2309288
Sum7527360
Variance52163.217
MonotonicityNot monotonic
2023-12-12T08:17:50.149559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
821 170
 
1.7%
811 152
 
1.5%
832 150
 
1.5%
831 150
 
1.5%
812 149
 
1.5%
822 144
 
1.4%
841 137
 
1.4%
802 133
 
1.3%
851 133
 
1.3%
861 132
 
1.3%
Other values (527) 8550
85.5%
ValueCountFrequency (%)
3 4
 
< 0.1%
10 30
0.3%
11 16
0.2%
12 13
0.1%
13 11
 
0.1%
14 6
 
0.1%
15 2
 
< 0.1%
16 2
 
< 0.1%
18 1
 
< 0.1%
19 4
 
< 0.1%
ValueCountFrequency (%)
998 1
 
< 0.1%
997 2
< 0.1%
993 1
 
< 0.1%
992 3
< 0.1%
991 3
< 0.1%
990 1
 
< 0.1%
989 1
 
< 0.1%
988 2
< 0.1%
987 1
 
< 0.1%
986 3
< 0.1%

주소
Text

Distinct8346
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T08:17:50.491279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length13.6549
Min length8

Characters and Unicode

Total characters136549
Distinct characters514
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7495 ?
Unique (%)75.0%

Sample

1st row경기 안성시 당왕동 대우1차아파트
2nd row경남 통영시 도산면 저산리
3rd row충북 청원군 북이면 용계리
4th row경북 김천시 어모면 옥률리
5th row충남 연기군 전동면 노장리
ValueCountFrequency (%)
서울 1533
 
4.3%
경기 1351
 
3.7%
경북 1005
 
2.8%
전남 937
 
2.6%
경남 825
 
2.3%
충남 696
 
1.9%
전북 676
 
1.9%
부산 571
 
1.6%
충북 511
 
1.4%
강원 452
 
1.3%
Other values (8183) 27481
76.3%
2023-12-12T08:17:50.980788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26038
 
19.1%
동 6792
 
5.0%
구 5068
 
3.7%
리 4306
 
3.2%
시 3887
 
2.8%
남 3826
 
2.8%
면 3691
 
2.7%
경 3497
 
2.6%
군 3176
 
2.3%
산 2970
 
2.2%
Other values (504) 73298
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105344
77.1%
Space Separator 26038
 
19.1%
Decimal Number 4362
 
3.2%
Math Symbol 322
 
0.2%
Close Punctuation 146
 
0.1%
Open Punctuation 146
 
0.1%
Other Punctuation 135
 
0.1%
Uppercase Letter 55
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6792
 
6.4%
구 5068
 
4.8%
리 4306
 
4.1%
시 3887
 
3.7%
남 3826
 
3.6%
면 3691
 
3.5%
경 3497
 
3.3%
군 3176
 
3.0%
산 2970
 
2.8%
북 2858
 
2.7%
Other values (468) 65273
62.0%
Uppercase Letter
ValueCountFrequency (%)
K 8
14.5%
B 8
14.5%
S 6
10.9%
L 6
10.9%
G 5
9.1%
I 4
7.3%
A 4
7.3%
D 3
 
5.5%
C 2
 
3.6%
P 2
 
3.6%
Other values (7) 7
12.7%
Decimal Number
ValueCountFrequency (%)
1 1508
34.6%
2 1395
32.0%
3 685
15.7%
4 314
 
7.2%
5 156
 
3.6%
6 99
 
2.3%
7 75
 
1.7%
8 62
 
1.4%
9 47
 
1.1%
0 21
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 101
74.8%
· 32
 
23.7%
. 2
 
1.5%
Math Symbol
ValueCountFrequency (%)
∼ 314
97.5%
~ 8
 
2.5%
Space Separator
ValueCountFrequency (%)
26038
100.0%
Close Punctuation
ValueCountFrequency (%)
) 146
100.0%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105335
77.1%
Common 31149
 
22.8%
Latin 56
 
< 0.1%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6792
 
6.4%
구 5068
 
4.8%
리 4306
 
4.1%
시 3887
 
3.7%
남 3826
 
3.6%
면 3691
 
3.5%
경 3497
 
3.3%
군 3176
 
3.0%
산 2970
 
2.8%
북 2858
 
2.7%
Other values (462) 65264
62.0%
Common
ValueCountFrequency (%)
26038
83.6%
1 1508
 
4.8%
2 1395
 
4.5%
3 685
 
2.2%
∼ 314
 
1.0%
4 314
 
1.0%
5 156
 
0.5%
) 146
 
0.5%
( 146
 
0.5%
, 101
 
0.3%
Other values (8) 346
 
1.1%
Latin
ValueCountFrequency (%)
K 8
14.3%
B 8
14.3%
S 6
10.7%
L 6
10.7%
G 5
8.9%
I 4
7.1%
A 4
7.1%
D 3
 
5.4%
C 2
 
3.6%
P 2
 
3.6%
Other values (8) 8
14.3%
Han
ValueCountFrequency (%)
里 3
33.3%
山 2
22.2%
岩 1
 
11.1%
基 1
 
11.1%
華 1
 
11.1%
花 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105335
77.1%
ASCII 30859
 
22.6%
Math Operators 314
 
0.2%
None 32
 
< 0.1%
CJK 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26038
84.4%
1 1508
 
4.9%
2 1395
 
4.5%
3 685
 
2.2%
4 314
 
1.0%
5 156
 
0.5%
) 146
 
0.5%
( 146
 
0.5%
, 101
 
0.3%
6 99
 
0.3%
Other values (24) 271
 
0.9%
Hangul
ValueCountFrequency (%)
동 6792
 
6.4%
구 5068
 
4.8%
리 4306
 
4.1%
시 3887
 
3.7%
남 3826
 
3.6%
면 3691
 
3.5%
경 3497
 
3.3%
군 3176
 
3.0%
산 2970
 
2.8%
북 2858
 
2.7%
Other values (462) 65264
62.0%
Math Operators
ValueCountFrequency (%)
∼ 314
100.0%
None
ValueCountFrequency (%)
· 32
100.0%
CJK
ValueCountFrequency (%)
里 3
33.3%
山 2
22.2%
岩 1
 
11.1%
基 1
 
11.1%
華 1
 
11.1%
花 1
 
11.1%

G|시도구분|시도코드
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.3979
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T08:17:51.098935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median12
Q316
95-th percentile18
Maximum19
Range18
Interquartile range (IQR)13

Descriptive statistics

Standard deviation6.1666992
Coefficient of variation (CV)0.5930716
Kurtosis-1.3695059
Mean10.3979
Median Absolute Deviation (MAD)5
Skewness-0.40305411
Sum103979
Variance38.028178
MonotonicityNot monotonic
2023-12-12T08:17:51.196482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 1533
15.3%
11 1351
13.5%
18 1005
10.1%
15 937
9.4%
17 825
8.2%
13 696
7.0%
16 676
6.8%
2 571
 
5.7%
14 511
 
5.1%
12 452
 
4.5%
Other values (6) 1443
14.4%
ValueCountFrequency (%)
1 1533
15.3%
2 571
 
5.7%
3 423
 
4.2%
4 348
 
3.5%
5 228
 
2.3%
6 194
 
1.9%
7 157
 
1.6%
11 1351
13.5%
12 452
 
4.5%
13 696
7.0%
ValueCountFrequency (%)
19 93
 
0.9%
18 1005
10.1%
17 825
8.2%
16 676
6.8%
15 937
9.4%
14 511
 
5.1%
13 696
7.0%
12 452
 
4.5%
11 1351
13.5%
7 157
 
1.6%

번지_APT동
Text

MISSING 

Distinct2700
Distinct (%)91.5%
Missing7048
Missing (%)70.5%
Memory size156.2 KiB
2023-12-12T08:17:51.465922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length7
Mean length7.0599593
Min length1

Characters and Unicode

Total characters20841
Distinct characters45
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2543 ?
Unique (%)86.1%

Sample

1st row(101108동)
2nd row330
3rd row1∼113번지
4th row151∼627
5th row262∼294
ValueCountFrequency (%)
1∼200번지 9
 
0.3%
1∼299번지 7
 
0.2%
101105동 7
 
0.2%
101104동 7
 
0.2%
101103동 7
 
0.2%
101107동 6
 
0.2%
1∼300번지 6
 
0.2%
201210동 5
 
0.2%
101112동 5
 
0.2%
201204동 5
 
0.2%
Other values (2690) 2888
97.8%
2023-12-12T08:17:51.896104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3197
15.3%
∼ 2418
11.6%
0 2267
10.9%
2 1677
8.0%
3 1445
6.9%
4 1430
6.9%
9 1422
6.8%
5 1364
6.5%
6 1305
6.3%
7 1194
 
5.7%
Other values (35) 3122
15.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16357
78.5%
Math Symbol 2422
 
11.6%
Other Letter 1453
 
7.0%
Close Punctuation 297
 
1.4%
Open Punctuation 297
 
1.4%
Other Punctuation 7
 
< 0.1%
Uppercase Letter 6
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 490
33.7%
번 485
33.4%
동 279
19.2%
산 167
 
11.5%
가 4
 
0.3%
단 3
 
0.2%
법 2
 
0.1%
마 2
 
0.1%
하 2
 
0.1%
고 2
 
0.1%
Other values (16) 17
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 3197
19.5%
0 2267
13.9%
2 1677
10.3%
3 1445
8.8%
4 1430
8.7%
9 1422
8.7%
5 1364
8.3%
6 1305
8.0%
7 1194
 
7.3%
8 1056
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
F 1
 
16.7%
Math Symbol
ValueCountFrequency (%)
∼ 2418
99.8%
~ 4
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 297
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19382
93.0%
Hangul 1453
 
7.0%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 490
33.7%
번 485
33.4%
동 279
19.2%
산 167
 
11.5%
가 4
 
0.3%
단 3
 
0.2%
법 2
 
0.1%
마 2
 
0.1%
하 2
 
0.1%
고 2
 
0.1%
Other values (16) 17
 
1.2%
Common
ValueCountFrequency (%)
1 3197
16.5%
∼ 2418
12.5%
0 2267
11.7%
2 1677
8.7%
3 1445
7.5%
4 1430
7.4%
9 1422
7.3%
5 1364
7.0%
6 1305
6.7%
7 1194
 
6.2%
Other values (6) 1663
8.6%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
F 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16970
81.4%
Math Operators 2418
 
11.6%
Hangul 1453
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3197
18.8%
0 2267
13.4%
2 1677
9.9%
3 1445
8.5%
4 1430
8.4%
9 1422
8.4%
5 1364
8.0%
6 1305
7.7%
7 1194
 
7.0%
8 1056
 
6.2%
Other values (8) 613
 
3.6%
Math Operators
ValueCountFrequency (%)
∼ 2418
100.0%
Hangul
ValueCountFrequency (%)
지 490
33.7%
번 485
33.4%
동 279
19.2%
산 167
 
11.5%
가 4
 
0.3%
단 3
 
0.2%
법 2
 
0.1%
마 2
 
0.1%
하 2
 
0.1%
고 2
 
0.1%
Other values (16) 17
 
1.2%

사서함등
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Interactions

2023-12-12T08:17:48.772302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:46.969510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.444910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.094332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.859221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.094576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.620524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.241221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.958623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.202106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.746212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.597347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:49.037905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.318183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:47.904567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:48.689623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:17:51.988611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호1우편번호2G|시도구분|시도코드
순번1.0000.9610.3910.923
우편번호10.9611.0000.3380.890
우편번호20.3910.3381.0000.301
G|시도구분|시도코드0.9230.8900.3011.000
2023-12-12T08:17:52.103683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호1우편번호2G|시도구분|시도코드
순번1.0000.3180.2700.805
우편번호10.3181.0000.0680.640
우편번호20.2700.0681.0000.253
G|시도구분|시도코드0.8050.6400.2531.000

Missing values

2023-12-12T08:17:49.143715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:17:49.246316image/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

순번우편번호1우편번호2주소G|시도구분|시도코드번지_APT동사서함등
1838518424456705경기 안성시 당왕동 대우1차아파트11(101108동)<NA>
2287422917650814경남 통영시 도산면 저산리17<NA><NA>
3996640016363923충북 청원군 북이면 용계리14<NA><NA>
2533125378740832경북 김천시 어모면 옥률리18<NA><NA>
3730837358339841충남 연기군 전동면 노장리13<NA><NA>
65716605601806부산 동구 범일5동2330<NA>
3931439364370823충북 영동군 학산면 서곡리14<NA><NA>
2749927546766872경북 영덕군 창수면 갈천리18<NA><NA>
3634636396330833충남 천안시 성거읍 삼곡리13<NA><NA>
1849018529456380경기 안성시 신소현동11<NA><NA>
순번우편번호1우편번호2주소G|시도구분|시도코드번지_APT동사서함등
87118749705828대구 남구 봉덕2동31501∼1618<NA>
23282341132820서울 도봉구 도봉1동1605∼620<NA>
61656197618722부산 강서구 신호동 삼성자동차(주)2<NA><NA>
6691672760114부산 동구 초량4동2<NA><NA>
1740017439461811경기 성남시 수정구신흥3동112468∼3304번지<NA>
892896157803서울 강서구 가양1동1276∼447<NA>
1202412062501703광주 동구 지산2동 광주법원청사5(지법,고법)<NA>
2268122724641170경남 창원시 반지동17<NA><NA>
1147011508417832인천 강화군 불은면 오두리4<NA><NA>
166861672547270경기 남양주시 수석동11<NA><NA>