Overview

Dataset statistics

Number of variables10
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory87.3 B

Variable types

Text3
Categorical5
Numeric2

Dataset

Description경기도 구리시 소재의 모든 행정관련 사무소 업체에 대한 현황 정보를 제공 (상호명, 신고일자, 위치, 전화번호 등)합니다.
URLhttps://www.data.go.kr/data/15029572/fileData.do

Alerts

기업형태구분명 has constant value ""Constant
행정사인원수 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전문분야내용 is highly imbalanced (74.2%)Imbalance
사무소명 has unique valuesUnique
대표자명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:24:13.651092
Analysis finished2023-12-12 18:24:14.753884
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:24:14.903307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length9
Mean length9.0322581
Min length5

Characters and Unicode

Total characters280
Distinct characters81
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row가나행정사사무소
2nd row굿프렌드행정사
3rd row김경식행정사사무소
4th row김동원행정사
5th row김만종행정사사무소
ValueCountFrequency (%)
사무소 3
 
7.9%
행정사 2
 
5.3%
가나행정사사무소 1
 
2.6%
윤원섭행정사사무소 1
 
2.6%
이레 1
 
2.6%
이선갑 1
 
2.6%
행정사사무소 1
 
2.6%
이종수행정사사무소 1
 
2.6%
장동욱행정사사무소 1
 
2.6%
천진우 1
 
2.6%
Other values (25) 25
65.8%
2023-12-13T03:24:15.268203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 59
21.1%
정 33
11.8%
행 31
 
11.1%
무 27
 
9.6%
소 27
 
9.6%
7
 
2.5%
김 6
 
2.1%
이 4
 
1.4%
동 3
 
1.1%
원 3
 
1.1%
Other values (71) 80
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 263
93.9%
Space Separator 7
 
2.5%
Lowercase Letter 6
 
2.1%
Uppercase Letter 2
 
0.7%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 59
22.4%
정 33
12.5%
행 31
11.8%
무 27
10.3%
소 27
10.3%
김 6
 
2.3%
이 4
 
1.5%
동 3
 
1.1%
원 3
 
1.1%
한 3
 
1.1%
Other values (60) 67
25.5%
Lowercase Letter
ValueCountFrequency (%)
r 1
16.7%
z 1
16.7%
k 1
16.7%
o 1
16.7%
e 1
16.7%
a 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 263
93.9%
Common 9
 
3.2%
Latin 8
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 59
22.4%
정 33
12.5%
행 31
11.8%
무 27
10.3%
소 27
10.3%
김 6
 
2.3%
이 4
 
1.5%
동 3
 
1.1%
원 3
 
1.1%
한 3
 
1.1%
Other values (60) 67
25.5%
Latin
ValueCountFrequency (%)
r 1
12.5%
B 1
12.5%
I 1
12.5%
z 1
12.5%
k 1
12.5%
o 1
12.5%
e 1
12.5%
a 1
12.5%
Common
ValueCountFrequency (%)
7
77.8%
( 1
 
11.1%
) 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 263
93.9%
ASCII 17
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 59
22.4%
정 33
12.5%
행 31
11.8%
무 27
10.3%
소 27
10.3%
김 6
 
2.3%
이 4
 
1.5%
동 3
 
1.1%
원 3
 
1.1%
한 3
 
1.1%
Other values (60) 67
25.5%
ASCII
ValueCountFrequency (%)
7
41.2%
r 1
 
5.9%
( 1
 
5.9%
B 1
 
5.9%
I 1
 
5.9%
z 1
 
5.9%
k 1
 
5.9%
o 1
 
5.9%
e 1
 
5.9%
a 1
 
5.9%

기업형태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
개인
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 31
100.0%

Length

2023-12-13T03:24:15.408802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:15.517555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 31
100.0%

소재지도로명주소
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:24:15.772265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length35
Mean length28.096774
Min length21

Characters and Unicode

Total characters871
Distinct characters104
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 구리시 안골로30번길 46，102호 (교문동)
2nd row경기도 구리시 검배로 36，1003-3호 (수택동， 현주Ifriend빌딩)
3rd row경기도 구리시 이문안로 101 (수택동)
4th row경기도 구리시 수택천로33번길 49 (수택동)
5th row경기도 구리시 건원대로76번길 34 (인창동， 삼보아파트상가 304호)
ValueCountFrequency (%)
경기도 31
18.6%
구리시 31
18.6%
교문동 12
 
7.2%
인창동 6
 
3.6%
건원대로34번길 4
 
2.4%
수택동 3
 
1.8%
안골로 3
 
1.8%
장자대로 3
 
1.8%
건원대로76번길 2
 
1.2%
27 2
 
1.2%
Other values (65) 70
41.9%
2023-12-13T03:24:16.191510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
 
15.6%
경 34
 
3.9%
1 34
 
3.9%
동 33
 
3.8%
구 33
 
3.8%
리 33
 
3.8%
기 32
 
3.7%
시 31
 
3.6%
( 31
 
3.6%
도 31
 
3.6%
Other values (94) 443
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 496
56.9%
Decimal Number 150
 
17.2%
Space Separator 136
 
15.6%
Open Punctuation 31
 
3.6%
Close Punctuation 31
 
3.6%
Other Punctuation 17
 
2.0%
Lowercase Letter 6
 
0.7%
Dash Punctuation 3
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 34
 
6.9%
동 33
 
6.7%
구 33
 
6.7%
리 33
 
6.7%
기 32
 
6.5%
시 31
 
6.2%
도 31
 
6.2%
로 29
 
5.8%
길 18
 
3.6%
번 16
 
3.2%
Other values (71) 206
41.5%
Decimal Number
ValueCountFrequency (%)
1 34
22.7%
3 24
16.0%
0 22
14.7%
4 16
10.7%
2 16
10.7%
9 9
 
6.0%
8 9
 
6.0%
6 9
 
6.0%
7 6
 
4.0%
5 5
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
f 1
16.7%
n 1
16.7%
r 1
16.7%
e 1
16.7%
i 1
16.7%
d 1
16.7%
Other Punctuation
ValueCountFrequency (%)
， 15
88.2%
, 2
 
11.8%
Space Separator
ValueCountFrequency (%)
136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 496
56.9%
Common 368
42.3%
Latin 7
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 34
 
6.9%
동 33
 
6.7%
구 33
 
6.7%
리 33
 
6.7%
기 32
 
6.5%
시 31
 
6.2%
도 31
 
6.2%
로 29
 
5.8%
길 18
 
3.6%
번 16
 
3.2%
Other values (71) 206
41.5%
Common
ValueCountFrequency (%)
136
37.0%
1 34
 
9.2%
( 31
 
8.4%
) 31
 
8.4%
3 24
 
6.5%
0 22
 
6.0%
4 16
 
4.3%
2 16
 
4.3%
， 15
 
4.1%
9 9
 
2.4%
Other values (6) 34
 
9.2%
Latin
ValueCountFrequency (%)
f 1
14.3%
n 1
14.3%
r 1
14.3%
e 1
14.3%
I 1
14.3%
i 1
14.3%
d 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 496
56.9%
ASCII 360
41.3%
None 15
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
37.8%
1 34
 
9.4%
( 31
 
8.6%
) 31
 
8.6%
3 24
 
6.7%
0 22
 
6.1%
4 16
 
4.4%
2 16
 
4.4%
9 9
 
2.5%
8 9
 
2.5%
Other values (12) 32
 
8.9%
Hangul
ValueCountFrequency (%)
경 34
 
6.9%
동 33
 
6.7%
구 33
 
6.7%
리 33
 
6.7%
기 32
 
6.5%
시 31
 
6.2%
도 31
 
6.2%
로 29
 
5.8%
길 18
 
3.6%
번 16
 
3.2%
Other values (71) 206
41.5%
None
ValueCountFrequency (%)
， 15
100.0%

위도
Real number (ℝ)

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.599642
Minimum37.587839
Maximum37.632503
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T03:24:16.336721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.587839
5-th percentile37.58786
Q137.590656
median37.599579
Q337.604516
95-th percentile37.618744
Maximum37.632503
Range0.04466392
Interquartile range (IQR)0.01385997

Descriptive statistics

Standard deviation0.010730966
Coefficient of variation (CV)0.00028540075
Kurtosis3.3510862
Mean37.599642
Median Absolute Deviation (MAD)0.0052445
Skewness1.5214444
Sum1165.5889
Variance0.00011515363
MonotonicityNot monotonic
2023-12-13T03:24:16.488066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.58786028 2
 
6.5%
37.595118 1
 
3.2%
37.58970896 1
 
3.2%
37.60482393 1
 
3.2%
37.60179819 1
 
3.2%
37.5993118 1
 
3.2%
37.604999 1
 
3.2%
37.6007746 1
 
3.2%
37.59756919 1
 
3.2%
37.599577 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
37.587839 1
3.2%
37.58786028 2
6.5%
37.58800774 1
3.2%
37.588012 1
3.2%
37.58815205 1
3.2%
37.58970896 1
3.2%
37.59065037 1
3.2%
37.590662 1
3.2%
37.591919 1
3.2%
37.595118 1
3.2%
ValueCountFrequency (%)
37.63250292 1
3.2%
37.630081 1
3.2%
37.60740688 1
3.2%
37.607065 1
3.2%
37.604999 1
3.2%
37.60482393 1
3.2%
37.604822 1
3.2%
37.604524 1
3.2%
37.60450831 1
3.2%
37.604378 1
3.2%

경도
Real number (ℝ)

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.13605
Minimum127.1121
Maximum127.14477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T03:24:16.615244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.1121
5-th percentile127.12003
Q1127.13161
median127.13985
Q3127.14168
95-th percentile127.14466
Maximum127.14477
Range0.032662
Interquartile range (IQR)0.0100697

Descriptive statistics

Standard deviation0.0080692149
Coefficient of variation (CV)6.3469134 × 10-5
Kurtosis1.5183092
Mean127.13605
Median Absolute Deviation (MAD)0.0049132
Skewness-1.2435386
Sum3941.2175
Variance6.5112228 × 10-5
MonotonicityNot monotonic
2023-12-13T03:24:16.750092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
127.1315949 2
 
6.5%
127.134241 1
 
3.2%
127.132368 1
 
3.2%
127.1415797 1
 
3.2%
127.1213977 1
 
3.2%
127.1186644 1
 
3.2%
127.141586 1
 
3.2%
127.1398531 1
 
3.2%
127.1431969 1
 
3.2%
127.131631 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
127.112105 1
3.2%
127.1186644 1
3.2%
127.1213977 1
3.2%
127.130793 1
3.2%
127.1309801 1
3.2%
127.130983 1
3.2%
127.1315949 2
6.5%
127.131631 1
3.2%
127.1316319 1
3.2%
127.132302 1
3.2%
ValueCountFrequency (%)
127.144767 1
3.2%
127.1447663 1
3.2%
127.1445625 1
3.2%
127.143795 1
3.2%
127.1431969 1
3.2%
127.1430337 1
3.2%
127.142884 1
3.2%
127.1417793 1
3.2%
127.141586 1
3.2%
127.141581 1
3.2%

행정사인원수
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 31
100.0%

Length

2023-12-13T03:24:16.894178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:16.998597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
100.0%

대표자명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:24:17.205626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row임대성
2nd row김종명
3rd row김경식
4th row김동원
5th row김만종
ValueCountFrequency (%)
임대성 1
 
3.2%
윤원섭 1
 
3.2%
이용주 1
 
3.2%
심상환 1
 
3.2%
노재옥 1
 
3.2%
김매동 1
 
3.2%
고준오 1
 
3.2%
함용규 1
 
3.2%
한문순 1
 
3.2%
천진우 1
 
3.2%
Other values (21) 21
67.7%
2023-12-13T03:24:17.536979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
8.6%
이 5
 
5.4%
동 4
 
4.3%
종 4
 
4.3%
정 3
 
3.2%
한 3
 
3.2%
원 3
 
3.2%
성 3
 
3.2%
신 3
 
3.2%
식 2
 
2.2%
Other values (48) 55
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
8.6%
이 5
 
5.4%
동 4
 
4.3%
종 4
 
4.3%
정 3
 
3.2%
한 3
 
3.2%
원 3
 
3.2%
성 3
 
3.2%
신 3
 
3.2%
식 2
 
2.2%
Other values (48) 55
59.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
8.6%
이 5
 
5.4%
동 4
 
4.3%
종 4
 
4.3%
정 3
 
3.2%
한 3
 
3.2%
원 3
 
3.2%
성 3
 
3.2%
신 3
 
3.2%
식 2
 
2.2%
Other values (48) 55
59.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
8.6%
이 5
 
5.4%
동 4
 
4.3%
종 4
 
4.3%
정 3
 
3.2%
한 3
 
3.2%
원 3
 
3.2%
성 3
 
3.2%
신 3
 
3.2%
식 2
 
2.2%
Other values (48) 55
59.1%

전문분야내용
Categorical

IMBALANCE 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
일반
29 
외국어번역(영어)
 
1
해사
 
1

Length

Max length9
Median length2
Mean length2.2258065
Min length2

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
일반 29
93.5%
외국어번역(영어) 1
 
3.2%
해사 1
 
3.2%

Length

2023-12-13T03:24:17.695487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:17.826316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 29
93.5%
외국어번역(영어 1
 
3.2%
해사 1
 
3.2%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
경기도 구리시청
31 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 구리시청
2nd row경기도 구리시청
3rd row경기도 구리시청
4th row경기도 구리시청
5th row경기도 구리시청

Common Values

ValueCountFrequency (%)
경기도 구리시청 31
100.0%

Length

2023-12-13T03:24:18.304751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:18.426986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 31
50.0%
구리시청 31
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-05-19
31 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-19
2nd row2023-05-19
3rd row2023-05-19
4th row2023-05-19
5th row2023-05-19

Common Values

ValueCountFrequency (%)
2023-05-19 31
100.0%

Length

2023-12-13T03:24:18.681654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:18.809783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-19 31
100.0%

Interactions

2023-12-13T03:24:14.224804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:24:14.043478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:24:14.327562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:24:14.135400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:24:18.897892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사무소명소재지도로명주소위도경도대표자명전문분야내용
사무소명1.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.000
위도1.0001.0001.0000.4591.0000.000
경도1.0001.0000.4591.0001.0000.000
대표자명1.0001.0001.0001.0001.0001.000
전문분야내용1.0001.0000.0000.0001.0001.000
2023-12-13T03:24:19.015220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도전문분야내용
위도1.0000.2410.000
경도0.2411.0000.000
전문분야내용0.0000.0001.000

Missing values

2023-12-13T03:24:14.483074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:24:14.684701image/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

사무소명기업형태구분명소재지도로명주소위도경도행정사인원수대표자명전문분야내용관리기관명데이터기준일자
0가나행정사사무소개인경기도 구리시 안골로30번길 46，102호 (교문동)37.595118127.1342411임대성일반경기도 구리시청2023-05-19
1굿프렌드행정사개인경기도 구리시 검배로 36，1003-3호 (수택동， 현주Ifriend빌딩)37.590662127.1447671김종명일반경기도 구리시청2023-05-19
2김경식행정사사무소개인경기도 구리시 이문안로 101 (수택동)37.591919127.1428841김경식일반경기도 구리시청2023-05-19
3김동원행정사개인경기도 구리시 수택천로33번길 49 (수택동)37.600686127.1445631김동원일반경기도 구리시청2023-05-19
4김만종행정사사무소개인경기도 구리시 건원대로76번길 34 (인창동， 삼보아파트상가 304호)37.607407127.1412081김만종일반경기도 구리시청2023-05-19
5김성화행정사사무소개인경기도 구리시 건원대로34번길 19 (인창동)37.604508127.1413581김성화일반경기도 구리시청2023-05-19
6김정희행정사사무소개인경기도 구리시 건원대로34번길 9 (인창동)37.604378127.1408531김정희외국어번역(영어)경기도 구리시청2023-05-19
7남정위행정사사무소개인경기도 구리시 장자대로1번길 8-4 (교문동)37.588008127.130981남정위일반경기도 구리시청2023-05-19
8다산행정사사무소개인경기도 구리시 건원대로 36, 902호 (교문동)37.604524127.1404791이신웅일반경기도 구리시청2023-05-19
9다원행정사사무소개인경기도 구리시 안골로 48，902호(교문동)37.597106127.1364751이동원일반경기도 구리시청2023-05-19
사무소명기업형태구분명소재지도로명주소위도경도행정사인원수대표자명전문분야내용관리기관명데이터기준일자
21장동욱행정사사무소개인경기도 구리시 아차산로500번길 18 (교문동)37.599579127.1316321장동욱일반경기도 구리시청2023-05-19
22천진우 행정사 사무소개인경기도 구리시 인창2로 13，103동 8층 803호 (인창동，구리 더샵 그린포레1단지)37.599577127.1316311천진우일반경기도 구리시청2023-05-19
23한솔행정사사무소개인경기도 구리시 안골로 108 (수택동)37.597569127.1431971한문순해사경기도 구리시청2023-05-19
24함용규행정사사무소개인경기도 구리시 경춘로 221 (인창동)37.600775127.1398531함용규일반경기도 구리시청2023-05-19
25행정사고준오사무소개인경기도 구리시 장자대로 11 (교문동)37.58786127.1315951고준오일반경기도 구리시청2023-05-19
26행정사김매동사무소개인경기도 구리시 장자대로 11 (교문동)37.58786127.1315951김매동일반경기도 구리시청2023-05-19
27행정사노재옥사무소개인경기도 구리시 건원대로34번길 27，세신인창종합상가 811호 (인창동)37.604999127.1415861노재옥일반경기도 구리시청2023-05-19
28행정사심상환사무소개인경기도 구리시 경춘로20번길 60 (교문동)37.599312127.1186641심상환일반경기도 구리시청2023-05-19
29행정사이용주사무소개인경기도 구리시 딸기원중문길 12 (교문동)37.601798127.1213981이용주일반경기도 구리시청2023-05-19
30행정사황관식사무소개인경기도 구리시 건원대로34번길 27 (인창동)37.604824127.141581황관식일반경기도 구리시청2023-05-19