Overview

Dataset statistics

Number of variables7
Number of observations107
Missing cells15
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory60.2 B

Variable types

Numeric3
Text3
Categorical1

Dataset

Description인천광역시 미추홀구에 등록되어 영업중인 행정사 등록현황에 대한 데이터로 상호명, 유형, 도로명주소, 전화번호, 좌표값 등을 제공합니다
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15045489

Alerts

유형 is highly imbalanced (86.7%)Imbalance
전화번호 has 15 (14.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:14:38.644103
Analysis finished2024-01-28 15:14:39.993134
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54
Minimum1
Maximum107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-29T00:14:40.052218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q127.5
median54
Q380.5
95-th percentile101.7
Maximum107
Range106
Interquartile range (IQR)53

Descriptive statistics

Standard deviation31.032241
Coefficient of variation (CV)0.57467114
Kurtosis-1.2
Mean54
Median Absolute Deviation (MAD)27
Skewness0
Sum5778
Variance963
MonotonicityStrictly increasing
2024-01-29T00:14:40.157677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%

상호명
Text

Distinct104
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size988.0 B
2024-01-29T00:14:40.378175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.2242991
Min length5

Characters and Unicode

Total characters987
Distinct characters156
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)95.3%

Sample

1st row대한행정사협회
2nd row다옴 행정사
3rd row열린금융행정사
4th row안암행정사사무소
5th row송비자행정사사무소
ValueCountFrequency (%)
행정사 33
 
19.3%
사무소 12
 
7.0%
행정사사무소 5
 
2.9%
법무사행정사 4
 
2.3%
혜안 3
 
1.8%
법무，행정사 3
 
1.8%
행정사법인 3
 
1.8%
베스트행정사사무소 2
 
1.2%
인천행정사사무소(탐정사 1
 
0.6%
강명구사무소 1
 
0.6%
Other values (104) 104
60.8%
2024-01-29T00:14:40.691819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 193
19.6%
정 113
 
11.4%
행 106
 
10.7%
무 88
 
8.9%
소 80
 
8.1%
65
 
6.6%
이 16
 
1.6%
법 12
 
1.2%
김 12
 
1.2%
인 9
 
0.9%
Other values (146) 293
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 907
91.9%
Space Separator 65
 
6.6%
Uppercase Letter 9
 
0.9%
Other Punctuation 4
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 193
21.3%
정 113
12.5%
행 106
 
11.7%
무 88
 
9.7%
소 80
 
8.8%
이 16
 
1.8%
법 12
 
1.3%
김 12
 
1.3%
인 9
 
1.0%
종 8
 
0.9%
Other values (135) 270
29.8%
Uppercase Letter
ValueCountFrequency (%)
U 2
22.2%
L 2
22.2%
J 1
11.1%
O 1
11.1%
Y 1
11.1%
F 1
11.1%
K 1
11.1%
Space Separator
ValueCountFrequency (%)
65
100.0%
Other Punctuation
ValueCountFrequency (%)
， 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 907
91.9%
Common 71
 
7.2%
Latin 9
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 193
21.3%
정 113
12.5%
행 106
 
11.7%
무 88
 
9.7%
소 80
 
8.8%
이 16
 
1.8%
법 12
 
1.3%
김 12
 
1.3%
인 9
 
1.0%
종 8
 
0.9%
Other values (135) 270
29.8%
Latin
ValueCountFrequency (%)
U 2
22.2%
L 2
22.2%
J 1
11.1%
O 1
11.1%
Y 1
11.1%
F 1
11.1%
K 1
11.1%
Common
ValueCountFrequency (%)
65
91.5%
， 4
 
5.6%
) 1
 
1.4%
( 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 907
91.9%
ASCII 76
 
7.7%
None 4
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 193
21.3%
정 113
12.5%
행 106
 
11.7%
무 88
 
9.7%
소 80
 
8.8%
이 16
 
1.8%
법 12
 
1.3%
김 12
 
1.3%
인 9
 
1.0%
종 8
 
0.9%
Other values (135) 270
29.8%
ASCII
ValueCountFrequency (%)
65
85.5%
U 2
 
2.6%
L 2
 
2.6%
) 1
 
1.3%
( 1
 
1.3%
J 1
 
1.3%
O 1
 
1.3%
Y 1
 
1.3%
F 1
 
1.3%
K 1
 
1.3%
None
ValueCountFrequency (%)
， 4
100.0%

유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
일반행정사
104 
외국어번역행정사(영어)
 
2
해사행정사
 
1

Length

Max length12
Median length5
Mean length5.1308411
Min length5

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
일반행정사 104
97.2%
외국어번역행정사(영어) 2
 
1.9%
해사행정사 1
 
0.9%

Length

2024-01-29T00:14:40.805836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:14:40.884965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반행정사 104
97.2%
외국어번역행정사(영어 2
 
1.9%
해사행정사 1
 
0.9%

도로명주소
Text

Distinct92
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2024-01-29T00:14:41.108766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length31.869159
Min length24

Characters and Unicode

Total characters3410
Distinct characters136
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

Unique84 ?
Unique (%)78.5%

Sample

1st row인천광역시 미추홀구 소성로 171， 202호 (학익동)
2nd row인천광역시 미추홀구 토금북로 51-1， 1층 (용현동)
3rd row인천광역시 미추홀구 매소홀로418번길 5， 201동 903호 (학익동， 하나2차아파트)
4th row인천광역시 미추홀구 경원대로 882， 주안더월드스테이트 상가 204호 (주안동)
5th row인천광역시 미추홀구 용정공원로83번길 49， 헤리움메트로타워 1321호 (용현동)
ValueCountFrequency (%)
인천광역시 107
 
16.9%
미추홀구 107
 
16.9%
학익동 48
 
7.6%
주안동 19
 
3.0%
소성로 16
 
2.5%
학익소로 15
 
2.4%
소성로185번길 9
 
1.4%
29 7
 
1.1%
학익동， 7
 
1.1%
숭의동 5
 
0.8%
Other values (209) 293
46.3%
2024-01-29T00:14:41.455645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
529
 
15.5%
1 130
 
3.8%
인 117
 
3.4%
동 115
 
3.4%
홀 113
 
3.3%
미 112
 
3.3%
추 111
 
3.3%
천 110
 
3.2%
시 109
 
3.2%
광 107
 
3.1%
Other values (126) 1857
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2012
59.0%
Decimal Number 577
 
16.9%
Space Separator 529
 
15.5%
Open Punctuation 99
 
2.9%
Close Punctuation 99
 
2.9%
Other Punctuation 69
 
2.0%
Dash Punctuation 18
 
0.5%
Lowercase Letter 4
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 117
 
5.8%
동 115
 
5.7%
홀 113
 
5.6%
미 112
 
5.6%
추 111
 
5.5%
천 110
 
5.5%
시 109
 
5.4%
광 107
 
5.3%
역 107
 
5.3%
구 107
 
5.3%
Other values (104) 904
44.9%
Decimal Number
ValueCountFrequency (%)
1 130
22.5%
2 99
17.2%
0 66
11.4%
3 60
10.4%
5 51
 
8.8%
8 46
 
8.0%
9 36
 
6.2%
4 35
 
6.1%
6 34
 
5.9%
7 20
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
r 1
25.0%
e 1
25.0%
o 1
25.0%
w 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
J 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
529
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Other Punctuation
ValueCountFrequency (%)
， 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2012
59.0%
Common 1391
40.8%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 117
 
5.8%
동 115
 
5.7%
홀 113
 
5.6%
미 112
 
5.6%
추 111
 
5.5%
천 110
 
5.5%
시 109
 
5.4%
광 107
 
5.3%
역 107
 
5.3%
구 107
 
5.3%
Other values (104) 904
44.9%
Common
ValueCountFrequency (%)
529
38.0%
1 130
 
9.3%
( 99
 
7.1%
) 99
 
7.1%
2 99
 
7.1%
， 69
 
5.0%
0 66
 
4.7%
3 60
 
4.3%
5 51
 
3.7%
8 46
 
3.3%
Other values (5) 143
 
10.3%
Latin
ValueCountFrequency (%)
r 1
14.3%
e 1
14.3%
o 1
14.3%
w 1
14.3%
T 1
14.3%
J 1
14.3%
A 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2012
59.0%
ASCII 1329
39.0%
None 69
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
529
39.8%
1 130
 
9.8%
( 99
 
7.4%
) 99
 
7.4%
2 99
 
7.4%
0 66
 
5.0%
3 60
 
4.5%
5 51
 
3.8%
8 46
 
3.5%
9 36
 
2.7%
Other values (11) 114
 
8.6%
Hangul
ValueCountFrequency (%)
인 117
 
5.8%
동 115
 
5.7%
홀 113
 
5.6%
미 112
 
5.6%
추 111
 
5.5%
천 110
 
5.5%
시 109
 
5.4%
광 107
 
5.3%
역 107
 
5.3%
구 107
 
5.3%
Other values (104) 904
44.9%
None
ValueCountFrequency (%)
， 69
100.0%

전화번호
Text

MISSING 

Distinct80
Distinct (%)87.0%
Missing15
Missing (%)14.0%
Memory size988.0 B
2024-01-29T00:14:41.657589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.163043
Min length1

Characters and Unicode

Total characters1027
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)80.4%

Sample

1st row032-872-8848
2nd row0504-158-1874
3rd row0505-815-0070
4th row032-861-5577
5th row032-505-8463
ValueCountFrequency (%)
032-875-0304 3
 
3.5%
032-863-5002 2
 
2.4%
032-420-1336 2
 
2.4%
032-861-4422 2
 
2.4%
032-505-8463 2
 
2.4%
032-872-7200 1
 
1.2%
032-872-8848 1
 
1.2%
032-422-5566 1
 
1.2%
032-207-2322 1
 
1.2%
032-861-2626 1
 
1.2%
Other values (69) 69
81.2%
2024-01-29T00:14:41.959149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 169
16.5%
0 160
15.6%
2 149
14.5%
3 125
12.2%
8 104
10.1%
1 65
 
6.3%
6 59
 
5.7%
7 57
 
5.6%
5 57
 
5.6%
4 52
 
5.1%
Other values (2) 30
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 851
82.9%
Dash Punctuation 169
 
16.5%
Space Separator 7
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 160
18.8%
2 149
17.5%
3 125
14.7%
8 104
12.2%
1 65
7.6%
6 59
 
6.9%
7 57
 
6.7%
5 57
 
6.7%
4 52
 
6.1%
9 23
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1027
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 169
16.5%
0 160
15.6%
2 149
14.5%
3 125
12.2%
8 104
10.1%
1 65
 
6.3%
6 59
 
5.7%
7 57
 
5.6%
5 57
 
5.6%
4 52
 
5.1%
Other values (2) 30
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 169
16.5%
0 160
15.6%
2 149
14.5%
3 125
12.2%
8 104
10.1%
1 65
 
6.3%
6 59
 
5.7%
7 57
 
5.6%
5 57
 
5.6%
4 52
 
5.1%
Other values (2) 30
 
2.9%

위도
Real number (ℝ)

Distinct75
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.449286
Minimum37.438217
Maximum37.470429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-29T00:14:42.072394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.438217
5-th percentile37.441513
Q137.442113
median37.444784
Q337.458177
95-th percentile37.464287
Maximum37.470429
Range0.03221206
Interquartile range (IQR)0.01606467

Descriptive statistics

Standard deviation0.0087032753
Coefficient of variation (CV)0.00023240164
Kurtosis-1.0904743
Mean37.449286
Median Absolute Deviation (MAD)0.00291418
Skewness0.70804803
Sum4007.0736
Variance7.5747002 × 10-5
MonotonicityNot monotonic
2024-01-29T00:14:42.178557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.44478424 9
 
8.4%
37.44196817 4
 
3.7%
37.45984908 4
 
3.7%
37.44195303 4
 
3.7%
37.45666052 3
 
2.8%
37.44301259 3
 
2.8%
37.44162468 3
 
2.8%
37.44294328 3
 
2.8%
37.4431593 2
 
1.9%
37.44215769 2
 
1.9%
Other values (65) 70
65.4%
ValueCountFrequency (%)
37.43821685 1
 
0.9%
37.43965492 1
 
0.9%
37.4413266 1
 
0.9%
37.44138991 1
 
0.9%
37.4414484 1
 
0.9%
37.44146463 1
 
0.9%
37.44162468 3
2.8%
37.44172591 1
 
0.9%
37.44184925 1
 
0.9%
37.44187006 1
 
0.9%
ValueCountFrequency (%)
37.47042891 1
0.9%
37.46748946 1
0.9%
37.46554181 1
0.9%
37.46510171 1
0.9%
37.46439979 1
0.9%
37.46432274 1
0.9%
37.46420286 1
0.9%
37.46361919 1
0.9%
37.46301066 1
0.9%
37.4625705 1
0.9%

경도
Real number (ℝ)

Distinct75
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66972
Minimum126.63802
Maximum126.69726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-29T00:14:42.296307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63802
5-th percentile126.64444
Q1126.66673
median126.66966
Q3126.67324
95-th percentile126.68972
Maximum126.69726
Range0.0592424
Interquartile range (IQR)0.00650485

Descriptive statistics

Standard deviation0.012319264
Coefficient of variation (CV)9.7255003 × 10-5
Kurtosis0.90838912
Mean126.66972
Median Absolute Deviation (MAD)0.0033063
Skewness-0.48420291
Sum13553.66
Variance0.00015176427
MonotonicityNot monotonic
2024-01-29T00:14:42.428054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.670093 9
 
8.4%
126.6676296 4
 
3.7%
126.6729642 4
 
3.7%
126.6686876 4
 
3.7%
126.6380152 3
 
2.8%
126.6710984 3
 
2.8%
126.666916 3
 
2.8%
126.6706044 3
 
2.8%
126.6658371 2
 
1.9%
126.6684789 2
 
1.9%
Other values (65) 70
65.4%
ValueCountFrequency (%)
126.6380152 3
2.8%
126.6397858 1
 
0.9%
126.6403122 1
 
0.9%
126.6435849 1
 
0.9%
126.6464519 1
 
0.9%
126.6466511 1
 
0.9%
126.6485366 1
 
0.9%
126.6505184 1
 
0.9%
126.6506179 1
 
0.9%
126.6513565 1
 
0.9%
ValueCountFrequency (%)
126.6972576 1
0.9%
126.6938552 1
0.9%
126.6918224 1
0.9%
126.6911188 1
0.9%
126.6907994 1
0.9%
126.6899169 1
0.9%
126.6892625 1
0.9%
126.6892542 1
0.9%
126.6891379 1
0.9%
126.6891141 2
1.9%

Interactions

2024-01-29T00:14:39.618685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.199187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.386105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.697889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.257249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.450706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.787008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.322018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:14:39.531194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:14:42.500073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형도로명주소전화번호위도경도
연번1.0000.3450.8820.9270.5240.368
유형0.3451.0000.0000.0000.0000.326
도로명주소0.8820.0001.0000.9951.0001.000
전화번호0.9270.0000.9951.0000.0000.968
위도0.5240.0001.0000.0001.0000.854
경도0.3680.3261.0000.9680.8541.000
2024-01-29T00:14:42.578338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도유형
연번1.0000.1040.2550.211
위도0.1041.0000.2750.000
경도0.2550.2751.0000.198
유형0.2110.0000.1981.000

Missing values

2024-01-29T00:14:39.878105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:14:39.959355image/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

연번상호명유형도로명주소전화번호위도경도
01대한행정사협회일반행정사인천광역시 미추홀구 소성로 171， 202호 (학익동)032-872-884837.441968126.66763
12다옴 행정사일반행정사인천광역시 미추홀구 토금북로 51-1， 1층 (용현동)<NA>37.45335126.639786
23열린금융행정사일반행정사인천광역시 미추홀구 매소홀로418번길 5， 201동 903호 (학익동， 하나2차아파트)0504-158-187437.439655126.668723
34안암행정사사무소일반행정사인천광역시 미추홀구 경원대로 882， 주안더월드스테이트 상가 204호 (주안동)<NA>37.461322126.689917
45송비자행정사사무소일반행정사인천광역시 미추홀구 용정공원로83번길 49， 헤리움메트로타워 1321호 (용현동)0505-815-007037.447606126.648537
56행정사윤희범사무소일반행정사인천광역시 미추홀구 소성로 183-12， 흥일빌딩 4층 (학익동)032-861-557737.441465126.668861
67법친구 행정사 사무소일반행정사인천광역시 미추홀구 재넘이길9번길 15， 205호 (학익동)<NA>37.446382126.666236
78에스에이치 행정사사무소일반행정사인천광역시 미추홀구 낙섬중로 78-15， 가득주택 501호 (용현동)<NA>37.454547126.640312
89동아행정사 사무소일반행정사인천광역시 미추홀구 문화로 23， 201동 4층 2호 (관교동， 삼환아파트)<NA>37.441327126.697258
910베스트행정사사무소외국어번역행정사(영어)인천광역시 미추홀구 소성로 171， 로시스빌딩 102호 (학익동)032-505-846337.441968126.66763
연번상호명유형도로명주소전화번호위도경도
9798행정사법인 혜안일반행정사인천광역시 미추홀구 학익소로 53， 502호(학익동)032-875-030437.442943126.670604
9899인천부광행정사사무소일반행정사인천광역시 미추홀구 주승로 22， 508호(학익동)37.443654126.67278
99100행정사최태범사무소일반행정사인천광역시 미추홀구 소성로185번길 16-20， 409호(학익동)032-874-011337.44139126.669658
100101행정사 권호석 사무소일반행정사인천광역시 미추홀구 학익소로 66， 702호(학익동)032-822-780137.441849126.670338
101102김현숙 행정사사무소일반행정사인천광역시 미추홀구 한나루로412번길 58， 3층(학익동)032-861-211137.442506126.665968
102103윤상호행정사사무소일반행정사인천광역시 미추홀구 미추로58번길 12， 203호(숭의동， 메트로칸)37.465102126.646651
103104행정사 이승재 사무소일반행정사인천광역시 미추홀구 소성로 183-39， 2층 201호(학익동)032-424-100137.441953126.668688
104105인천행정사사무소(탐정사)일반행정사인천광역시 미추홀구 염창로 58， 아이죤상가 A동 1층 17호，18호(주안동)37.465542126.680465
105106행정사 함성수 사무소일반행정사인천광역시 미추홀구 경원대로 873， 102호(주안동)032-713-833837.460765126.689254
106107다니엘 탐정행정사사무소일반행정사인천광역시 미추홀구 미추홀대로646번길 14-18(주안동)37.454535126.680534