Overview

Dataset statistics

Number of variables14
Number of observations2710
Missing cells2892
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.8 KiB
Average record size in memory114.0 B

Variable types

Text6
Categorical4
Numeric2
Boolean1
DateTime1

Dataset

Description행정사사무소 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=G51IQOGVR4DU7PQ1JBID26789679&infSeq=1

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 관리기관명High correlation
경도 is highly overall correlated with 관리기관명High correlation
관리기관명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
행정사종류 is highly imbalanced (93.7%)Imbalance
대표행정사여부 is highly imbalanced (83.7%)Imbalance
운영상태 is highly imbalanced (68.4%)Imbalance
소재지도로명주소 has 203 (7.5%) missing valuesMissing
소재지지번주소 has 1213 (44.8%) missing valuesMissing
행정사사무소전화번호 has 1476 (54.5%) missing valuesMissing

Reproduction

Analysis started2024-05-17 18:36:19.746443
Analysis finished2024-05-17 18:36:30.089126
Duration10.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

Distinct2485
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-05-18T03:36:30.542481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length9.3730627
Min length2

Characters and Unicode

Total characters25401
Distinct characters533
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2337 ?
Unique (%)86.2%

Sample

1st row1004 행정사 사무소
2nd row101 행정사사무소
3rd row109행정사사무소
4th row119행정사사무소
5th row237 행정사 사무소
ValueCountFrequency (%)
행정사 692
 
14.1%
사무소 617
 
12.5%
행정사사무소 488
 
9.9%
행정사법인 34
 
0.7%
행정사합동사무소 29
 
0.6%
합동사무소 23
 
0.5%
행정사무소 20
 
0.4%
일반행정사 12
 
0.2%
컨설팅 10
 
0.2%
글로벌 10
 
0.2%
Other values (2555) 2986
60.7%
2024-05-18T03:36:31.438069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 4795
18.9%
정 2819
 
11.1%
행 2700
 
10.6%
2212
 
8.7%
무 2167
 
8.5%
소 2153
 
8.5%
이 293
 
1.2%
김 203
 
0.8%
인 181
 
0.7%
한 153
 
0.6%
Other values (523) 7725
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22614
89.0%
Space Separator 2212
 
8.7%
Uppercase Letter 405
 
1.6%
Lowercase Letter 91
 
0.4%
Decimal Number 72
 
0.3%
Open Punctuation 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4795
21.2%
정 2819
12.5%
행 2700
 
11.9%
무 2167
 
9.6%
소 2153
 
9.5%
이 293
 
1.3%
김 203
 
0.9%
인 181
 
0.8%
한 153
 
0.7%
동 140
 
0.6%
Other values (461) 7010
31.0%
Uppercase Letter
ValueCountFrequency (%)
K 46
 
11.4%
S 44
 
10.9%
O 26
 
6.4%
A 26
 
6.4%
L 24
 
5.9%
H 22
 
5.4%
C 20
 
4.9%
M 20
 
4.9%
G 20
 
4.9%
J 18
 
4.4%
Other values (15) 139
34.3%
Lowercase Letter
ValueCountFrequency (%)
n 12
13.2%
e 11
12.1%
a 10
11.0%
l 9
9.9%
o 7
 
7.7%
k 5
 
5.5%
s 5
 
5.5%
r 4
 
4.4%
t 4
 
4.4%
h 3
 
3.3%
Other values (12) 21
23.1%
Decimal Number
ValueCountFrequency (%)
1 24
33.3%
8 12
16.7%
2 9
 
12.5%
9 7
 
9.7%
4 7
 
9.7%
0 4
 
5.6%
3 3
 
4.2%
5 3
 
4.2%
6 2
 
2.8%
7 1
 
1.4%
Space Separator
ValueCountFrequency (%)
2212
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22586
88.9%
Common 2291
 
9.0%
Latin 496
 
2.0%
Han 28
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4795
21.2%
정 2819
12.5%
행 2700
 
12.0%
무 2167
 
9.6%
소 2153
 
9.5%
이 293
 
1.3%
김 203
 
0.9%
인 181
 
0.8%
한 153
 
0.7%
동 140
 
0.6%
Other values (439) 6982
30.9%
Latin
ValueCountFrequency (%)
K 46
 
9.3%
S 44
 
8.9%
O 26
 
5.2%
A 26
 
5.2%
L 24
 
4.8%
H 22
 
4.4%
C 20
 
4.0%
M 20
 
4.0%
G 20
 
4.0%
J 18
 
3.6%
Other values (37) 230
46.4%
Han
ValueCountFrequency (%)
正 4
 
14.3%
道 3
 
10.7%
大 2
 
7.1%
丘 1
 
3.6%
靑 1
 
3.6%
平 1
 
3.6%
通 1
 
3.6%
利 1
 
3.6%
友 1
 
3.6%
行 1
 
3.6%
Other values (12) 12
42.9%
Common
ValueCountFrequency (%)
2212
96.6%
1 24
 
1.0%
8 12
 
0.5%
2 9
 
0.4%
9 7
 
0.3%
4 7
 
0.3%
0 4
 
0.2%
( 3
 
0.1%
3 3
 
0.1%
5 3
 
0.1%
Other values (5) 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22586
88.9%
ASCII 2787
 
11.0%
CJK 28
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 4795
21.2%
정 2819
12.5%
행 2700
 
12.0%
무 2167
 
9.6%
소 2153
 
9.5%
이 293
 
1.3%
김 203
 
0.9%
인 181
 
0.8%
한 153
 
0.7%
동 140
 
0.6%
Other values (439) 6982
30.9%
ASCII
ValueCountFrequency (%)
2212
79.4%
K 46
 
1.7%
S 44
 
1.6%
O 26
 
0.9%
A 26
 
0.9%
L 24
 
0.9%
1 24
 
0.9%
H 22
 
0.8%
C 20
 
0.7%
M 20
 
0.7%
Other values (52) 323
 
11.6%
CJK
ValueCountFrequency (%)
正 4
 
14.3%
道 3
 
10.7%
大 2
 
7.1%
丘 1
 
3.6%
靑 1
 
3.6%
平 1
 
3.6%
通 1
 
3.6%
利 1
 
3.6%
友 1
 
3.6%
行 1
 
3.6%
Other values (12) 12
42.9%

행정사종류
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
일반행정사
2651 
외국어번역행정사(영어)
 
39
외국어번역행정사(일본어)
 
6
외국어번역행정사(중국어)
 
6
해사행정사
 
4
Other values (3)
 
4

Length

Max length14
Median length5
Mean length5.1494465
Min length5

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 2651
97.8%
외국어번역행정사(영어) 39
 
1.4%
외국어번역행정사(일본어) 6
 
0.2%
외국어번역행정사(중국어) 6
 
0.2%
해사행정사 4
 
0.1%
외국어번역행정사(프랑스어) 2
 
0.1%
외국어번역행정사(스페인어) 1
 
< 0.1%
외국어번역행정사(러시아어) 1
 
< 0.1%

Length

2024-05-18T03:36:31.833753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:36:32.144514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 2651
97.8%
외국어번역행정사(영어 39
 
1.4%
외국어번역행정사(일본어 6
 
0.2%
외국어번역행정사(중국어 6
 
0.2%
해사행정사 4
 
0.1%
외국어번역행정사(프랑스어 2
 
0.1%
외국어번역행정사(스페인어 1
 
< 0.1%
외국어번역행정사(러시아어 1
 
< 0.1%

행정사자격증번호
Text

Distinct2705
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-05-18T03:36:32.529863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length11
Mean length12.098155
Min length11

Characters and Unicode

Total characters32786
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2700 ?
Unique (%)99.6%

Sample

1st row15102050876
2nd row20102017268
3rd row19101005453
4th row14101001224
5th row16101009476
ValueCountFrequency (%)
14101055053 2
 
0.1%
14101025027 2
 
0.1%
13101006604 2
 
0.1%
22110009075 2
 
0.1%
20101009702 2
 
0.1%
13101014418 1
 
< 0.1%
t397000013100000010 1
 
< 0.1%
15101034126 1
 
< 0.1%
18100000016 1
 
< 0.1%
20100000031 1
 
< 0.1%
Other values (2695) 2695
99.4%
2024-05-18T03:36:33.414865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11773
35.9%
1 8033
24.5%
3 2365
 
7.2%
2 2052
 
6.3%
4 1796
 
5.5%
5 1490
 
4.5%
6 1373
 
4.2%
7 1255
 
3.8%
8 1191
 
3.6%
9 1086
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32414
98.9%
Uppercase Letter 372
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11773
36.3%
1 8033
24.8%
3 2365
 
7.3%
2 2052
 
6.3%
4 1796
 
5.5%
5 1490
 
4.6%
6 1373
 
4.2%
7 1255
 
3.9%
8 1191
 
3.7%
9 1086
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
T 372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32414
98.9%
Latin 372
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11773
36.3%
1 8033
24.8%
3 2365
 
7.3%
2 2052
 
6.3%
4 1796
 
5.5%
5 1490
 
4.6%
6 1373
 
4.2%
7 1255
 
3.9%
8 1191
 
3.7%
9 1086
 
3.4%
Latin
ValueCountFrequency (%)
T 372
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11773
35.9%
1 8033
24.5%
3 2365
 
7.2%
2 2052
 
6.3%
4 1796
 
5.5%
5 1490
 
4.5%
6 1373
 
4.2%
7 1255
 
3.8%
8 1191
 
3.6%
9 1086
 
3.3%

소재지도로명주소
Text

MISSING 

Distinct2368
Distinct (%)94.5%
Missing203
Missing (%)7.5%
Memory size21.3 KiB
2024-05-18T03:36:34.007474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length33.869565
Min length17

Characters and Unicode

Total characters84911
Distinct characters536
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2269 ?
Unique (%)90.5%

Sample

1st row경기도 광명시 범안로 1002, 대광프라자 7층(하안동)
2nd row경기도 수원시 영통구 반달로 38, 301호 (영통동)
3rd row경기도 화성시 동탄감배산로 143, 202동 414호 (오산동, 동탄역 유림노르웨이숲)
4th row경기도 고양시 일산서구 강선로 188, 1110동 505호 (일산동, 후곡마을11단지아파트)
5th row경기도 광주시 역동로 5, 709호(역동)
ValueCountFrequency (%)
경기도 2497
 
14.6%
수원시 310
 
1.8%
안산시 170
 
1.0%
부천시 169
 
1.0%
용인시 167
 
1.0%
고양시 139
 
0.8%
화성시 139
 
0.8%
단원구 133
 
0.8%
성남시 131
 
0.8%
영통구 131
 
0.8%
Other values (5000) 13166
76.8%
2024-05-18T03:36:35.088451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14645
 
17.2%
1 3602
 
4.2%
동 3133
 
3.7%
경 2644
 
3.1%
시 2619
 
3.1%
기 2619
 
3.1%
도 2567
 
3.0%
로 2402
 
2.8%
, 2349
 
2.8%
0 2316
 
2.7%
Other values (526) 46015
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46857
55.2%
Decimal Number 15570
 
18.3%
Space Separator 14645
 
17.2%
Other Punctuation 2492
 
2.9%
Open Punctuation 2228
 
2.6%
Close Punctuation 2228
 
2.6%
Dash Punctuation 556
 
0.7%
Uppercase Letter 285
 
0.3%
Lowercase Letter 45
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3133
 
6.7%
경 2644
 
5.6%
시 2619
 
5.6%
기 2619
 
5.6%
도 2567
 
5.5%
로 2402
 
5.1%
호 1620
 
3.5%
구 1304
 
2.8%
원 923
 
2.0%
길 899
 
1.9%
Other values (464) 26127
55.8%
Uppercase Letter
ValueCountFrequency (%)
B 59
20.7%
A 47
16.5%
C 21
 
7.4%
I 18
 
6.3%
S 18
 
6.3%
E 16
 
5.6%
L 14
 
4.9%
D 14
 
4.9%
K 11
 
3.9%
T 9
 
3.2%
Other values (14) 58
20.4%
Lowercase Letter
ValueCountFrequency (%)
e 12
26.7%
i 5
11.1%
a 4
 
8.9%
t 3
 
6.7%
r 3
 
6.7%
c 2
 
4.4%
b 2
 
4.4%
z 2
 
4.4%
k 2
 
4.4%
h 2
 
4.4%
Other values (8) 8
17.8%
Decimal Number
ValueCountFrequency (%)
1 3602
23.1%
0 2316
14.9%
2 2305
14.8%
3 1583
10.2%
4 1334
 
8.6%
5 1165
 
7.5%
6 964
 
6.2%
7 896
 
5.8%
8 705
 
4.5%
9 700
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 2349
94.3%
， 134
 
5.4%
. 9
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
14645
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2228
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2228
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 556
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46857
55.2%
Common 37720
44.4%
Latin 334
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3133
 
6.7%
경 2644
 
5.6%
시 2619
 
5.6%
기 2619
 
5.6%
도 2567
 
5.5%
로 2402
 
5.1%
호 1620
 
3.5%
구 1304
 
2.8%
원 923
 
2.0%
길 899
 
1.9%
Other values (464) 26127
55.8%
Latin
ValueCountFrequency (%)
B 59
17.7%
A 47
14.1%
C 21
 
6.3%
I 18
 
5.4%
S 18
 
5.4%
E 16
 
4.8%
L 14
 
4.2%
D 14
 
4.2%
e 12
 
3.6%
K 11
 
3.3%
Other values (34) 104
31.1%
Common
ValueCountFrequency (%)
14645
38.8%
1 3602
 
9.5%
, 2349
 
6.2%
0 2316
 
6.1%
2 2305
 
6.1%
( 2228
 
5.9%
) 2228
 
5.9%
3 1583
 
4.2%
4 1334
 
3.5%
5 1165
 
3.1%
Other values (8) 3965
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46857
55.2%
ASCII 37916
44.7%
None 134
 
0.2%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14645
38.6%
1 3602
 
9.5%
, 2349
 
6.2%
0 2316
 
6.1%
2 2305
 
6.1%
( 2228
 
5.9%
) 2228
 
5.9%
3 1583
 
4.2%
4 1334
 
3.5%
5 1165
 
3.1%
Other values (49) 4161
 
11.0%
Hangul
ValueCountFrequency (%)
동 3133
 
6.7%
경 2644
 
5.6%
시 2619
 
5.6%
기 2619
 
5.6%
도 2567
 
5.5%
로 2402
 
5.1%
호 1620
 
3.5%
구 1304
 
2.8%
원 923
 
2.0%
길 899
 
1.9%
Other values (464) 26127
55.8%
None
ValueCountFrequency (%)
， 134
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%

소재지지번주소
Text

MISSING 

Distinct1403
Distinct (%)93.7%
Missing1213
Missing (%)44.8%
Memory size21.3 KiB
2024-05-18T03:36:35.771355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length42
Mean length26.525718
Min length11

Characters and Unicode

Total characters39709
Distinct characters439
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1330 ?
Unique (%)88.8%

Sample

1st row경기도 고양시 일산서구 일산동 1103번지 후곡마을11단지아파트
2nd row경기도 광주시 태전동 702 힐스테이트 태전
3rd row경기도 고양시 덕양구 행신동 773 무원마을1단지아파트
4th row경기도 화성시 향남읍 평리 81번지 35호
5th row경기도 부천시 소사구 심곡본동 679번지 16호
ValueCountFrequency (%)
경기도 1497
 
16.4%
수원시 180
 
2.0%
성남시 149
 
1.6%
1호 148
 
1.6%
안산시 117
 
1.3%
2호 105
 
1.2%
용인시 103
 
1.1%
단원구 93
 
1.0%
3호 91
 
1.0%
고양시 82
 
0.9%
Other values (2480) 6538
71.8%
2024-05-18T03:36:37.024903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7606
 
19.2%
기 1542
 
3.9%
도 1531
 
3.9%
1 1530
 
3.9%
동 1522
 
3.8%
경 1518
 
3.8%
시 1518
 
3.8%
지 1331
 
3.4%
호 1281
 
3.2%
번 1193
 
3.0%
Other values (429) 19137
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24284
61.2%
Space Separator 7606
 
19.2%
Decimal Number 7456
 
18.8%
Dash Punctuation 210
 
0.5%
Uppercase Letter 94
 
0.2%
Open Punctuation 21
 
0.1%
Close Punctuation 21
 
0.1%
Other Punctuation 9
 
< 0.1%
Lowercase Letter 5
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1542
 
6.3%
도 1531
 
6.3%
동 1522
 
6.3%
경 1518
 
6.3%
시 1518
 
6.3%
지 1331
 
5.5%
호 1281
 
5.3%
번 1193
 
4.9%
구 799
 
3.3%
원 459
 
1.9%
Other values (388) 11590
47.7%
Uppercase Letter
ValueCountFrequency (%)
B 12
12.8%
S 11
11.7%
E 10
10.6%
A 9
9.6%
U 8
8.5%
M 7
 
7.4%
H 6
 
6.4%
D 5
 
5.3%
R 4
 
4.3%
L 4
 
4.3%
Other values (9) 18
19.1%
Decimal Number
ValueCountFrequency (%)
1 1530
20.5%
2 920
12.3%
0 793
10.6%
3 782
10.5%
4 681
9.1%
5 653
8.8%
6 614
8.2%
7 569
 
7.6%
8 496
 
6.7%
9 418
 
5.6%
Other Punctuation
ValueCountFrequency (%)
@ 5
55.6%
. 3
33.3%
, 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
a 2
40.0%
e 2
40.0%
k 1
20.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%
Space Separator
ValueCountFrequency (%)
7606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24284
61.2%
Common 15323
38.6%
Latin 102
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 1542
 
6.3%
도 1531
 
6.3%
동 1522
 
6.3%
경 1518
 
6.3%
시 1518
 
6.3%
지 1331
 
5.5%
호 1281
 
5.3%
번 1193
 
4.9%
구 799
 
3.3%
원 459
 
1.9%
Other values (388) 11590
47.7%
Latin
ValueCountFrequency (%)
B 12
11.8%
S 11
10.8%
E 10
 
9.8%
A 9
 
8.8%
U 8
 
7.8%
M 7
 
6.9%
H 6
 
5.9%
D 5
 
4.9%
R 4
 
3.9%
L 4
 
3.9%
Other values (14) 26
25.5%
Common
ValueCountFrequency (%)
7606
49.6%
1 1530
 
10.0%
2 920
 
6.0%
0 793
 
5.2%
3 782
 
5.1%
4 681
 
4.4%
5 653
 
4.3%
6 614
 
4.0%
7 569
 
3.7%
8 496
 
3.2%
Other values (7) 679
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24284
61.2%
ASCII 15422
38.8%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7606
49.3%
1 1530
 
9.9%
2 920
 
6.0%
0 793
 
5.1%
3 782
 
5.1%
4 681
 
4.4%
5 653
 
4.2%
6 614
 
4.0%
7 569
 
3.7%
8 496
 
3.2%
Other values (29) 778
 
5.0%
Hangul
ValueCountFrequency (%)
기 1542
 
6.3%
도 1531
 
6.3%
동 1522
 
6.3%
경 1518
 
6.3%
시 1518
 
6.3%
지 1331
 
5.5%
호 1281
 
5.3%
번 1193
 
4.9%
구 799
 
3.3%
원 459
 
1.9%
Other values (388) 11590
47.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
66.7%
Ⅱ 1
33.3%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2333
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.422769
Minimum35.865149
Maximum38.124372
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-05-18T03:36:37.450721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.865149
5-th percentile37.065339
Q137.273044
median37.38884
Q337.601677
95-th percentile37.815097
Maximum38.124372
Range2.2592236
Interquartile range (IQR)0.32863335

Descriptive statistics

Standard deviation0.22137909
Coefficient of variation (CV)0.0059156258
Kurtosis0.53685643
Mean37.422769
Median Absolute Deviation (MAD)0.12671453
Skewness0.24162839
Sum101415.7
Variance0.049008703
MonotonicityNot monotonic
2024-05-18T03:36:37.904220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.45199637 11
 
0.4%
37.31523183 11
 
0.4%
37.266691 9
 
0.3%
37.26212556 8
 
0.3%
37.31162847 7
 
0.3%
37.37353716 6
 
0.2%
37.73933353 5
 
0.2%
37.42003254 5
 
0.2%
37.25177736 5
 
0.2%
37.39253241 5
 
0.2%
Other values (2323) 2638
97.3%
ValueCountFrequency (%)
35.86514871 1
< 0.1%
36.94991936 1
< 0.1%
36.959702 1
< 0.1%
36.96038699 1
< 0.1%
36.96051014 1
< 0.1%
36.96122556 1
< 0.1%
36.97892997 1
< 0.1%
36.98039422 1
< 0.1%
36.98332207 1
< 0.1%
36.98355946 1
< 0.1%
ValueCountFrequency (%)
38.12437226 1
< 0.1%
38.09950186 1
< 0.1%
38.0963136 1
< 0.1%
38.09442798 1
< 0.1%
38.09035621 1
< 0.1%
38.08934865 1
< 0.1%
38.0681024 2
0.1%
38.05324115 1
< 0.1%
38.02912367 1
< 0.1%
38.02641514 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2336
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02041
Minimum126.48744
Maximum128.82528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.9 KiB
2024-05-18T03:36:38.345358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.48744
5-th percentile126.75057
Q1126.845
median127.04264
Q3127.12982
95-th percentile127.31283
Maximum128.82528
Range2.3378447
Interquartile range (IQR)0.28481688

Descriptive statistics

Standard deviation0.19720577
Coefficient of variation (CV)0.0015525519
Kurtosis4.3325427
Mean127.02041
Median Absolute Deviation (MAD)0.1169511
Skewness0.83374947
Sum344225.31
Variance0.038890116
MonotonicityNot monotonic
2024-05-18T03:36:38.762441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.159592 11
 
0.4%
126.8231457 11
 
0.4%
127.025714 9
 
0.3%
127.0315901 8
 
0.3%
126.827782 7
 
0.3%
127.0688883 6
 
0.2%
126.7564272 5
 
0.2%
127.0448627 5
 
0.2%
126.889192 5
 
0.2%
126.7567333 5
 
0.2%
Other values (2326) 2638
97.3%
ValueCountFrequency (%)
126.4874391 1
< 0.1%
126.5620766 1
< 0.1%
126.568918 1
< 0.1%
126.5694893 1
< 0.1%
126.5721567 1
< 0.1%
126.5753871 1
< 0.1%
126.5757493 1
< 0.1%
126.5843452 1
< 0.1%
126.584512 1
< 0.1%
126.5845356 1
< 0.1%
ValueCountFrequency (%)
128.8252838 1
< 0.1%
128.6275009 1
< 0.1%
127.7133384 1
< 0.1%
127.7000497 1
< 0.1%
127.6956849 1
< 0.1%
127.6839594 1
< 0.1%
127.6731335 1
< 0.1%
127.6714653 1
< 0.1%
127.6484545 1
< 0.1%
127.6407538 1
< 0.1%

행정사명
Text

Distinct2539
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-05-18T03:36:39.437673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length2.995572
Min length2

Characters and Unicode

Total characters8118
Distinct characters253
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2382 ?
Unique (%)87.9%

Sample

1st row하재윤
2nd row양승찬
3rd row이주성
4th row최재환
5th row이원
ValueCountFrequency (%)
김정훈 4
 
0.1%
이재호 3
 
0.1%
이상기 3
 
0.1%
이재용 3
 
0.1%
김명수 3
 
0.1%
이종철 3
 
0.1%
김범수 3
 
0.1%
이부영 3
 
0.1%
김재훈 3
 
0.1%
김광현 3
 
0.1%
Other values (2532) 2682
98.9%
2024-05-18T03:36:40.553810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 509
 
6.3%
이 472
 
5.8%
박 240
 
3.0%
정 225
 
2.8%
영 203
 
2.5%
성 178
 
2.2%
수 169
 
2.1%
재 142
 
1.7%
호 136
 
1.7%
상 135
 
1.7%
Other values (243) 5709
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8097
99.7%
Uppercase Letter 9
 
0.1%
Lowercase Letter 9
 
0.1%
Space Separator 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 509
 
6.3%
이 472
 
5.8%
박 240
 
3.0%
정 225
 
2.8%
영 203
 
2.5%
성 178
 
2.2%
수 169
 
2.1%
재 142
 
1.8%
호 136
 
1.7%
상 135
 
1.7%
Other values (227) 5688
70.2%
Lowercase Letter
ValueCountFrequency (%)
g 1
11.1%
u 1
11.1%
e 1
11.1%
b 1
11.1%
o 1
11.1%
n 1
11.1%
a 1
11.1%
f 1
11.1%
x 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
N 2
22.2%
I 2
22.2%
J 2
22.2%
S 1
11.1%
H 1
11.1%
A 1
11.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8097
99.7%
Latin 18
 
0.2%
Common 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 509
 
6.3%
이 472
 
5.8%
박 240
 
3.0%
정 225
 
2.8%
영 203
 
2.5%
성 178
 
2.2%
수 169
 
2.1%
재 142
 
1.8%
호 136
 
1.7%
상 135
 
1.7%
Other values (227) 5688
70.2%
Latin
ValueCountFrequency (%)
N 2
 
11.1%
I 2
 
11.1%
J 2
 
11.1%
g 1
 
5.6%
S 1
 
5.6%
H 1
 
5.6%
A 1
 
5.6%
u 1
 
5.6%
e 1
 
5.6%
b 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8097
99.7%
ASCII 21
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 509
 
6.3%
이 472
 
5.8%
박 240
 
3.0%
정 225
 
2.8%
영 203
 
2.5%
성 178
 
2.2%
수 169
 
2.1%
재 142
 
1.8%
호 136
 
1.7%
상 135
 
1.7%
Other values (227) 5688
70.2%
ASCII
ValueCountFrequency (%)
3
14.3%
N 2
 
9.5%
I 2
 
9.5%
J 2
 
9.5%
g 1
 
4.8%
S 1
 
4.8%
H 1
 
4.8%
A 1
 
4.8%
u 1
 
4.8%
e 1
 
4.8%
Other values (6) 6
28.6%

대표행정사여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
True
2645 
False
 
65
ValueCountFrequency (%)
True 2645
97.6%
False 65
 
2.4%
2024-05-18T03:36:40.888485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

행정사사무소전화번호
Text

MISSING 

Distinct1167
Distinct (%)94.6%
Missing1476
Missing (%)54.5%
Memory size21.3 KiB
2024-05-18T03:36:41.364649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.996759
Min length11

Characters and Unicode

Total characters14804
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

Unique1119 ?
Unique (%)90.7%

Sample

1st row031-203-8676
2nd row031-905-4807
3rd row031-362-5734
4th row031-352-5132
5th row032-663-8899
ValueCountFrequency (%)
031-224-2001 9
 
0.7%
031-8067-5770 4
 
0.3%
031-592-3533 4
 
0.3%
031-204-0503 3
 
0.2%
031-942-8585 3
 
0.2%
031-492-5922 3
 
0.2%
031-241-8828 3
 
0.2%
031-528-5479 3
 
0.2%
031-704-1948 3
 
0.2%
031-282-7895 3
 
0.2%
Other values (1157) 1196
96.9%
2024-05-18T03:36:42.408630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2468
16.7%
3 2148
14.5%
0 2093
14.1%
1 1926
13.0%
2 1091
7.4%
5 901
 
6.1%
7 892
 
6.0%
8 890
 
6.0%
6 828
 
5.6%
4 801
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12336
83.3%
Dash Punctuation 2468
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2148
17.4%
0 2093
17.0%
1 1926
15.6%
2 1091
8.8%
5 901
7.3%
7 892
7.2%
8 890
7.2%
6 828
 
6.7%
4 801
 
6.5%
9 766
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 2468
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2468
16.7%
3 2148
14.5%
0 2093
14.1%
1 1926
13.0%
2 1091
7.4%
5 901
 
6.1%
7 892
 
6.0%
8 890
 
6.0%
6 828
 
5.6%
4 801
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2468
16.7%
3 2148
14.5%
0 2093
14.1%
1 1926
13.0%
2 1091
7.4%
5 901
 
6.1%
7 892
 
6.0%
8 890
 
6.0%
6 828
 
5.6%
4 801
 
5.4%

운영상태
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
영업중
2555 
휴업
 
155

Length

Max length3
Median length3
Mean length2.9428044
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2555
94.3%
휴업 155
 
5.7%

Length

2024-05-18T03:36:42.874919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:36:43.197988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2555
94.3%
휴업 155
 
5.7%

신고일자
Date

Distinct1620
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
Minimum1980-09-20 00:00:00
Maximum2024-01-19 00:00:00
2024-05-18T03:36:43.529395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:36:43.956107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관명
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
경기도 수원시청
356 
경기도 성남시청
215 
경기도 부천시청
176 
경기도 안산시청
172 
경기도 용인시청
171 
Other values (36)
1620 

Length

Max length12
Median length8
Mean length8.1095941
Min length8

Unique

Unique9 ?
Unique (%)0.3%

Sample

1st row경기도 광명시청
2nd row경기도 수원시청
3rd row경기도 화성시청
4th row경기도 고양시청
5th row경기도 광주시청

Common Values

ValueCountFrequency (%)
경기도 수원시청 356
 
13.1%
경기도 성남시청 215
 
7.9%
경기도 부천시청 176
 
6.5%
경기도 안산시청 172
 
6.3%
경기도 용인시청 171
 
6.3%
경기도 화성시청 148
 
5.5%
경기도 남양주시청 141
 
5.2%
경기도 고양시청 141
 
5.2%
경기도 의정부시청 113
 
4.2%
경기도 안양시청 109
 
4.0%
Other values (31) 968
35.7%

Length

2024-05-18T03:36:44.422247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 2698
49.8%
수원시청 356
 
6.6%
성남시청 215
 
4.0%
부천시청 176
 
3.2%
안산시청 172
 
3.2%
용인시청 171
 
3.2%
화성시청 148
 
2.7%
남양주시청 141
 
2.6%
고양시청 141
 
2.6%
의정부시청 113
 
2.1%
Other values (36) 1089
20.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
2024-01-19
2710 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-19
2nd row2024-01-19
3rd row2024-01-19
4th row2024-01-19
5th row2024-01-19

Common Values

ValueCountFrequency (%)
2024-01-19 2710
100.0%

Length

2024-05-18T03:36:44.834864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T03:36:45.188637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-19 2710
100.0%

Interactions

2024-05-18T03:36:28.049479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:36:27.419325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:36:28.367812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T03:36:27.779219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T03:36:45.370927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정사종류위도경도대표행정사여부운영상태관리기관명
행정사종류1.0000.0000.0000.0950.0000.000
위도0.0001.0000.7160.0650.0970.976
경도0.0000.7161.0000.0420.0370.971
대표행정사여부0.0950.0650.0421.0000.0430.141
운영상태0.0000.0970.0370.0431.0000.157
관리기관명0.0000.9760.9710.1410.1571.000
2024-05-18T03:36:45.663582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표행정사여부운영상태관리기관명행정사종류
대표행정사여부1.0000.0270.1180.071
운영상태0.0271.0000.1310.000
관리기관명0.1180.1311.0000.000
행정사종류0.0710.0000.0001.000
2024-05-18T03:36:45.910721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정사종류대표행정사여부운영상태관리기관명
위도1.000-0.1260.0000.0700.1040.849
경도-0.1261.0000.0000.0450.0400.828
행정사종류0.0000.0001.0000.0710.0000.000
대표행정사여부0.0700.0450.0711.0000.0270.118
운영상태0.1040.0400.0000.0271.0000.131
관리기관명0.8490.8280.0000.1180.1311.000

Missing values

2024-05-18T03:36:28.843483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T03:36:29.510736image/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.
2024-05-18T03:36:29.910735image/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

사무소명행정사종류행정사자격증번호소재지도로명주소소재지지번주소위도경도행정사명대표행정사여부행정사사무소전화번호운영상태신고일자관리기관명데이터기준일자
01004 행정사 사무소일반행정사15102050876경기도 광명시 범안로 1002, 대광프라자 7층(하안동)<NA>37.459692126.875291하재윤Y<NA>영업중2021-12-01경기도 광명시청2024-01-19
1101 행정사사무소일반행정사20102017268경기도 수원시 영통구 반달로 38, 301호 (영통동)<NA>37.250532127.07606양승찬Y031-203-8676영업중2023-08-08경기도 수원시청2024-01-19
2109행정사사무소일반행정사19101005453경기도 화성시 동탄감배산로 143, 202동 414호 (오산동, 동탄역 유림노르웨이숲)<NA>37.198722127.089308이주성Y<NA>영업중2023-06-20경기도 화성시청2024-01-19
3119행정사사무소일반행정사14101001224경기도 고양시 일산서구 강선로 188, 1110동 505호 (일산동, 후곡마을11단지아파트)경기도 고양시 일산서구 일산동 1103번지 후곡마을11단지아파트37.679136126.771978최재환Y031-905-4807영업중2017-12-14경기도 고양시청2024-01-19
4237 행정사 사무소일반행정사16101009476경기도 광주시 역동로 5, 709호(역동)경기도 광주시 태전동 702 힐스테이트 태전37.406202127.260295이원Y<NA>영업중2022-02-09경기도 광주시청2024-01-19
525행정사사무소일반행정사13101060942경기도 고양시 덕양구 화신로 47, 104동 1005호 (행신동, 무원마을1단지아파트)경기도 고양시 덕양구 행신동 773 무원마을1단지아파트37.617256126.838318문이호Y<NA>영업중2021-01-28경기도 고양시청2024-01-19
6365행정사 사무소일반행정사13100000075경기도 안산시 단원구 광덕4로 96, 부일프라자114호(고잔동)<NA>37.315232126.823146안효은Y031-362-5734휴업2022-12-26경기도 안산시청2024-01-19
782 행정사 사무소일반행정사14101056748경기도 화성시 향남읍 평6길 58경기도 화성시 향남읍 평리 81번지 35호37.131205126.908053정인숙Y031-352-5132영업중2019-12-26경기도 화성시청2024-01-19
888 행정사 사무소일반행정사13101024802경기도 부천시 소사구 경인로234번길 22 (심곡본동)경기도 부천시 소사구 심곡본동 679번지 16호37.482152126.781324김영길Y032-663-8899영업중2019-01-22경기도 부천시청2024-01-19
988국제행정사 사무소일반행정사14101009928경기도 안산시 단원구 원곡로3길 18, 1층(원곡동)경기도 안산시 단원구 원곡동 786번지 17호37.330587126.795453장의용Y<NA>영업중2022-01-03경기도 안산시청2024-01-19
사무소명행정사종류행정사자격증번호소재지도로명주소소재지지번주소위도경도행정사명대표행정사여부행정사사무소전화번호운영상태신고일자관리기관명데이터기준일자
2700효원사행정사무소일반행정사13101014709경기도 수원시 권선구 서부로 1610, 2층 203호 (고색동)경기도 수원시 권선구 고색동 886-5037.252862126.975763김익중Y031-295-7004영업중2020-09-15경기도 수원시청2024-01-19
2701희망 꿈 행정사사무소/직업상담소일반행정사14101014017경기도 부천시 원미구 부천로122번길 43(원미동)<NA>37.494913126.787665김흥수Y<NA>영업중2022-05-19경기도 부천시청2024-01-19
2702희망 인력 행정사사무소일반행정사14101013367경기도 부천시 소사구 부천로10번길 19, 부천종합상가 4층 415-1호(심곡동)경기도 부천시 소사구 소사본동 160번지 29호37.485323126.783896박용인Y032-566-0200영업중2022-09-01경기도 부천시청2024-01-19
2703희망 행정사 사무소일반행정사15100000069경기도 오산시 원동로 6 (원동)경기도 오산시 원동 841번지 파크스퀘어 301호37.142034127.069636기인서Y031-372-4494영업중2012-12-31경기도 오산시청2024-01-19
2704희망행정사일반행정사17102044549경기도 수원시 장안구 정조로1074번길 28, A동 302호 (송죽동, 공신그린빌)경기도 수원시 장안구 송죽동 460 공신그린빌37.302294127.005189유기천Y<NA>영업중2018-10-11경기도 수원시청2024-01-19
2705희망행정사 사무소일반행정사13100002580경기도 안산시 단원구 부부로 4, 3층(원곡동)<NA>37.32912126.788559최성길Y<NA>영업중2022-08-19경기도 안산시청2024-01-19
2706희망행정사사무소일반행정사17101027724경기도 화성시 봉담읍 흰돌산길 159-3경기도 화성시 봉담읍 세곡리 197번지37.187273126.927071정역호Y<NA>영업중2018-12-10경기도 화성시청2024-01-19
2707희망행정사사무소일반행정사13101004757경기도 이천시 장호원읍 서동대로8880번길 47-37, 407호(로얄맨숀)<NA>37.11421127.62297정상수Y<NA>영업중2022-06-21경기도 이천시청2024-01-19
2708희망행정심판전문사무소 행정사 박춘경일반행정사13100000071경기도 안산시 상록구 한양대학1길 61, 301호 (사동)<NA>37.300489126.843099박춘경Y031-480-5900휴업2023-10-13경기도 안산시청2024-01-19
2709힘찬행정사일반행정사13100001491경기도 부천시 원미구 소향로13번길 14-23, 401호 (상동, 삼성프라자)<NA>37.504481126.750334박영규Y<NA>영업중2012-12-24경기도 부천시청2024-01-19