Overview

Dataset statistics

Number of variables7
Number of observations169
Missing cells117
Missing cells (%)9.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory59.8 B

Variable types

Numeric3
Categorical1
Text3

Dataset

Description인천광역시 미추홀구의 동물관련 영업 현황 데이터로 유형, 상호명,도로명주소,전화번호 등의 자료를 제공합니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15081952

Alerts

연번 is highly overall correlated with 유형High correlation
유형 is highly overall correlated with 연번High correlation
전화번호 has 117 (69.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:46:57.394216
Analysis finished2024-01-28 10:46:58.476088
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct169
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85
Minimum1
Maximum169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:46:58.543293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.4
Q143
median85
Q3127
95-th percentile160.6
Maximum169
Range168
Interquartile range (IQR)84

Descriptive statistics

Standard deviation48.930222
Coefficient of variation (CV)0.57564968
Kurtosis-1.2
Mean85
Median Absolute Deviation (MAD)42
Skewness0
Sum14365
Variance2394.1667
MonotonicityStrictly increasing
2024-01-28T19:46:58.647872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
117 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
Other values (159) 159
94.1%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
169 1
0.6%
168 1
0.6%
167 1
0.6%
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%

유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
동물미용업(일반)
94 
동물위탁관리업
33 
동물판매업(일반)
32 
동물운송업
 
7
동물전시업
 
3

Length

Max length9
Median length9
Mean length8.3727811
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동물판매업(일반)
2nd row동물판매업(일반)
3rd row동물판매업(일반)
4th row동물판매업(일반)
5th row동물판매업(일반)

Common Values

ValueCountFrequency (%)
동물미용업(일반) 94
55.6%
동물위탁관리업 33
 
19.5%
동물판매업(일반) 32
 
18.9%
동물운송업 7
 
4.1%
동물전시업 3
 
1.8%

Length

2024-01-28T19:46:58.970893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:46:59.062302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동물미용업(일반 94
55.6%
동물위탁관리업 33
 
19.5%
동물판매업(일반 32
 
18.9%
동물운송업 7
 
4.1%
동물전시업 3
 
1.8%

상호명
Text

Distinct134
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T19:46:59.317266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length6.3313609
Min length2

Characters and Unicode

Total characters1070
Distinct characters236
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)59.2%

Sample

1st row개팔자 ~ 참
2nd row로얄애견
3rd row둥지애견
4th row토토 애견
5th row멍멍이와야옹이
ValueCountFrequency (%)
강아지 12
 
5.1%
인천점 7
 
3.0%
펫 4
 
1.7%
펫앤펫 3
 
1.3%
강아지의 3
 
1.3%
모든것 3
 
1.3%
러블리 3
 
1.3%
라온캣독 3
 
1.3%
펫싸롱 2
 
0.9%
독특 2
 
0.9%
Other values (153) 193
82.1%
2024-01-28T19:46:59.683065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
 
6.2%
펫 41
 
3.8%
아 40
 
3.7%
지 32
 
3.0%
견 31
 
2.9%
애 28
 
2.6%
강 26
 
2.4%
개 25
 
2.3%
리 24
 
2.2%
이 24
 
2.2%
Other values (226) 733
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 904
84.5%
Space Separator 66
 
6.2%
Lowercase Letter 53
 
5.0%
Uppercase Letter 13
 
1.2%
Close Punctuation 11
 
1.0%
Open Punctuation 11
 
1.0%
Other Punctuation 7
 
0.7%
Decimal Number 4
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
펫 41
 
4.5%
아 40
 
4.4%
지 32
 
3.5%
견 31
 
3.4%
애 28
 
3.1%
강 26
 
2.9%
개 25
 
2.8%
리 24
 
2.7%
이 24
 
2.7%
멍 24
 
2.7%
Other values (193) 609
67.4%
Lowercase Letter
ValueCountFrequency (%)
a 6
11.3%
p 5
9.4%
o 5
9.4%
l 4
 
7.5%
g 4
 
7.5%
y 4
 
7.5%
e 4
 
7.5%
r 4
 
7.5%
d 3
 
5.7%
n 3
 
5.7%
Other values (7) 11
20.8%
Uppercase Letter
ValueCountFrequency (%)
D 4
30.8%
C 2
15.4%
A 2
15.4%
J 2
15.4%
P 2
15.4%
L 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
& 1
 
14.3%
' 1
 
14.3%
# 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
4 2
50.0%
Space Separator
ValueCountFrequency (%)
66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 904
84.5%
Common 100
 
9.3%
Latin 66
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
펫 41
 
4.5%
아 40
 
4.4%
지 32
 
3.5%
견 31
 
3.4%
애 28
 
3.1%
강 26
 
2.9%
개 25
 
2.8%
리 24
 
2.7%
이 24
 
2.7%
멍 24
 
2.7%
Other values (193) 609
67.4%
Latin
ValueCountFrequency (%)
a 6
 
9.1%
p 5
 
7.6%
o 5
 
7.6%
l 4
 
6.1%
g 4
 
6.1%
D 4
 
6.1%
y 4
 
6.1%
e 4
 
6.1%
r 4
 
6.1%
d 3
 
4.5%
Other values (13) 23
34.8%
Common
ValueCountFrequency (%)
66
66.0%
) 11
 
11.0%
( 11
 
11.0%
, 4
 
4.0%
2 2
 
2.0%
4 2
 
2.0%
& 1
 
1.0%
' 1
 
1.0%
# 1
 
1.0%
~ 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 904
84.5%
ASCII 166
 
15.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
39.8%
) 11
 
6.6%
( 11
 
6.6%
a 6
 
3.6%
p 5
 
3.0%
o 5
 
3.0%
l 4
 
2.4%
, 4
 
2.4%
g 4
 
2.4%
D 4
 
2.4%
Other values (23) 46
27.7%
Hangul
ValueCountFrequency (%)
펫 41
 
4.5%
아 40
 
4.4%
지 32
 
3.5%
견 31
 
3.4%
애 28
 
3.1%
강 26
 
2.9%
개 25
 
2.8%
리 24
 
2.7%
이 24
 
2.7%
멍 24
 
2.7%
Other values (193) 609
67.4%

도로명주소
Text

Distinct130
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T19:46:59.903507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length29.87574
Min length22

Characters and Unicode

Total characters5049
Distinct characters175
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)55.6%

Sample

1st row인천광역시 미추홀구 소성로 305 (문학동)
2nd row인천광역시 미추홀구 독배로 415 (용현동)
3rd row인천광역시 미추홀구 인하로164번길 3 (용현동)
4th row인천광역시 미추홀구 제일로 42 (도화동)
5th row인천광역시 미추홀구 인주대로 272-1 (용현동)
ValueCountFrequency (%)
인천광역시 169
17.3%
미추홀구 169
17.3%
주안동 53
 
5.4%
1층 44
 
4.5%
용현동 41
 
4.2%
도화동 24
 
2.5%
숭의동 21
 
2.1%
소성로 17
 
1.7%
학익동 14
 
1.4%
문학동 12
 
1.2%
Other values (225) 413
42.3%
2024-01-28T19:47:00.258777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
808
 
16.0%
인 213
 
4.2%
홀 191
 
3.8%
미 183
 
3.6%
추 182
 
3.6%
천 177
 
3.5%
시 175
 
3.5%
동 175
 
3.5%
구 171
 
3.4%
광 170
 
3.4%
Other values (165) 2604
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3114
61.7%
Space Separator 808
 
16.0%
Decimal Number 643
 
12.7%
Open Punctuation 169
 
3.3%
Close Punctuation 169
 
3.3%
Other Punctuation 104
 
2.1%
Dash Punctuation 23
 
0.5%
Uppercase Letter 14
 
0.3%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 213
 
6.8%
홀 191
 
6.1%
미 183
 
5.9%
추 182
 
5.8%
천 177
 
5.7%
시 175
 
5.6%
동 175
 
5.6%
구 171
 
5.5%
광 170
 
5.5%
역 169
 
5.4%
Other values (141) 1308
42.0%
Decimal Number
ValueCountFrequency (%)
1 137
21.3%
2 95
14.8%
3 82
12.8%
4 68
10.6%
8 55
8.6%
6 51
 
7.9%
5 49
 
7.6%
0 46
 
7.2%
7 31
 
4.8%
9 29
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
S 4
28.6%
K 2
14.3%
V 2
14.3%
I 2
14.3%
E 2
14.3%
W 2
14.3%
Lowercase Letter
ValueCountFrequency (%)
k 2
40.0%
y 2
40.0%
e 1
20.0%
Space Separator
ValueCountFrequency (%)
808
100.0%
Open Punctuation
ValueCountFrequency (%)
( 169
100.0%
Close Punctuation
ValueCountFrequency (%)
) 169
100.0%
Other Punctuation
ValueCountFrequency (%)
, 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3114
61.7%
Common 1916
37.9%
Latin 19
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 213
 
6.8%
홀 191
 
6.1%
미 183
 
5.9%
추 182
 
5.8%
천 177
 
5.7%
시 175
 
5.6%
동 175
 
5.6%
구 171
 
5.5%
광 170
 
5.5%
역 169
 
5.4%
Other values (141) 1308
42.0%
Common
ValueCountFrequency (%)
808
42.2%
( 169
 
8.8%
) 169
 
8.8%
1 137
 
7.2%
, 104
 
5.4%
2 95
 
5.0%
3 82
 
4.3%
4 68
 
3.5%
8 55
 
2.9%
6 51
 
2.7%
Other values (5) 178
 
9.3%
Latin
ValueCountFrequency (%)
S 4
21.1%
k 2
10.5%
K 2
10.5%
y 2
10.5%
V 2
10.5%
I 2
10.5%
E 2
10.5%
W 2
10.5%
e 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3114
61.7%
ASCII 1935
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
808
41.8%
( 169
 
8.7%
) 169
 
8.7%
1 137
 
7.1%
, 104
 
5.4%
2 95
 
4.9%
3 82
 
4.2%
4 68
 
3.5%
8 55
 
2.8%
6 51
 
2.6%
Other values (14) 197
 
10.2%
Hangul
ValueCountFrequency (%)
인 213
 
6.8%
홀 191
 
6.1%
미 183
 
5.9%
추 182
 
5.8%
천 177
 
5.7%
시 175
 
5.6%
동 175
 
5.6%
구 171
 
5.5%
광 170
 
5.5%
역 169
 
5.4%
Other values (141) 1308
42.0%

전화번호
Text

MISSING 

Distinct43
Distinct (%)82.7%
Missing117
Missing (%)69.2%
Memory size1.4 KiB
2024-01-28T19:47:00.437795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.096154
Min length12

Characters and Unicode

Total characters629
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

Unique34 ?
Unique (%)65.4%

Sample

1st row032-433-0444
2nd row032-881-0835
3rd row032-874-1555
4th row032-873-8015
5th row032-873-3640
ValueCountFrequency (%)
032-886-0079 2
 
3.8%
032-872-7003 2
 
3.8%
032-875-7566 2
 
3.8%
070-7543-4208 2
 
3.8%
070-4281-0658 2
 
3.8%
032-868-2626 2
 
3.8%
032-875-8707 2
 
3.8%
032-874-1555 2
 
3.8%
032-815-2991 2
 
3.8%
032-889-1909 1
 
1.9%
Other values (33) 33
63.5%
2024-01-28T19:47:00.709112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.5%
0 91
14.5%
8 82
13.0%
2 79
12.6%
3 74
11.8%
7 57
9.1%
5 37
 
5.9%
4 34
 
5.4%
6 28
 
4.5%
9 22
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 525
83.5%
Dash Punctuation 104
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91
17.3%
8 82
15.6%
2 79
15.0%
3 74
14.1%
7 57
10.9%
5 37
7.0%
4 34
 
6.5%
6 28
 
5.3%
9 22
 
4.2%
1 21
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 629
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.5%
0 91
14.5%
8 82
13.0%
2 79
12.6%
3 74
11.8%
7 57
9.1%
5 37
 
5.9%
4 34
 
5.4%
6 28
 
4.5%
9 22
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.5%
0 91
14.5%
8 82
13.0%
2 79
12.6%
3 74
11.8%
7 57
9.1%
5 37
 
5.9%
4 34
 
5.4%
6 28
 
4.5%
9 22
 
3.5%

위도
Real number (ℝ)

Distinct120
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.455843
Minimum37.436615
Maximum37.477988
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:47:00.828463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.436615
5-th percentile37.438885
Q137.448836
median37.456668
Q337.462721
95-th percentile37.472379
Maximum37.477988
Range0.041373034
Interquartile range (IQR)0.013885001

Descriptive statistics

Standard deviation0.010088831
Coefficient of variation (CV)0.00026935267
Kurtosis-0.57311757
Mean37.455843
Median Absolute Deviation (MAD)0.0069793243
Skewness-0.0094058862
Sum6330.0374
Variance0.00010178452
MonotonicityNot monotonic
2024-01-28T19:47:00.934311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4470674411551 4
 
2.4%
37.4403094366971 3
 
1.8%
37.4503767407318 3
 
1.8%
37.4596228422955 3
 
1.8%
37.4598898689648 3
 
1.8%
37.4769856280292 3
 
1.8%
37.4616788951273 3
 
1.8%
37.4779876776446 2
 
1.2%
37.4693146004519 2
 
1.2%
37.4671090312214 2
 
1.2%
Other values (110) 141
83.4%
ValueCountFrequency (%)
37.4366146441081 1
0.6%
37.437375084967 2
1.2%
37.4374800634405 2
1.2%
37.437574784268 2
1.2%
37.4378683413244 1
0.6%
37.438753988699 1
0.6%
37.439081302886 1
0.6%
37.4391324274807 2
1.2%
37.4395101386304 1
0.6%
37.4402765945481 1
0.6%
ValueCountFrequency (%)
37.4779876776446 2
1.2%
37.4769856280292 3
1.8%
37.476260298772 1
 
0.6%
37.4755307105462 1
 
0.6%
37.4750137122294 1
 
0.6%
37.4728699882215 1
 
0.6%
37.4716432651221 2
1.2%
37.4699570154972 2
1.2%
37.4693146004519 2
1.2%
37.4683743623646 1
 
0.6%

경도
Real number (ℝ)

Distinct120
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.66541
Minimum126.63414
Maximum126.69492
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T19:47:01.034694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63414
5-th percentile126.6374
Q1126.65085
median126.66534
Q3126.68011
95-th percentile126.69133
Maximum126.69492
Range0.060781664
Interquartile range (IQR)0.029262661

Descriptive statistics

Standard deviation0.017225925
Coefficient of variation (CV)0.00013599549
Kurtosis-1.2178634
Mean126.66541
Median Absolute Deviation (MAD)0.014757546
Skewness-0.11354293
Sum21406.455
Variance0.00029673248
MonotonicityNot monotonic
2024-01-28T19:47:01.137958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.650849261836 4
 
2.4%
126.679815244717 3
 
1.8%
126.687198743487 3
 
1.8%
126.677688233648 3
 
1.8%
126.694918997797 3
 
1.8%
126.659136628004 3
 
1.8%
126.681391699383 3
 
1.8%
126.655268956144 2
 
1.2%
126.650242435002 2
 
1.2%
126.675673608368 2
 
1.2%
Other values (110) 141
83.4%
ValueCountFrequency (%)
126.634137333891 2
1.2%
126.635358952791 1
0.6%
126.635883710514 2
1.2%
126.636417709146 1
0.6%
126.636669975972 1
0.6%
126.636992675012 2
1.2%
126.638015239648 1
0.6%
126.638603157324 2
1.2%
126.639100443053 1
0.6%
126.63949404783 1
0.6%
ValueCountFrequency (%)
126.694918997797 3
1.8%
126.693934860337 2
1.2%
126.693644557561 2
1.2%
126.693394723683 1
 
0.6%
126.691665804938 1
 
0.6%
126.690820837071 1
 
0.6%
126.688079338206 1
 
0.6%
126.687289442703 1
 
0.6%
126.687198743487 3
1.8%
126.68657177564 1
 
0.6%

Interactions

2024-01-28T19:46:58.139718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:57.727218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:57.945098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:58.207952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:57.805132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:58.016926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:58.269682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:57.876473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T19:46:58.077467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:47:01.207743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형전화번호위도경도
연번1.0000.9540.0000.2380.000
유형0.9541.0000.0000.2400.000
전화번호0.0000.0001.0001.0001.000
위도0.2380.2401.0001.0000.762
경도0.0000.0001.0000.7621.000
2024-01-28T19:47:01.278445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도유형
연번1.0000.052-0.0550.694
위도0.0521.000-0.0910.099
경도-0.055-0.0911.0000.000
유형0.6940.0990.0001.000

Missing values

2024-01-28T19:46:58.354566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:46:58.439648image/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

연번유형상호명도로명주소전화번호위도경도
01동물판매업(일반)개팔자 ~ 참인천광역시 미추홀구 소성로 305 (문학동)032-433-044437.437868126.681321
12동물판매업(일반)로얄애견인천광역시 미추홀구 독배로 415 (용현동)032-881-083537.456668126.649692
23동물판매업(일반)둥지애견인천광역시 미추홀구 인하로164번길 3 (용현동)032-874-155537.448836126.666175
34동물판매업(일반)토토 애견인천광역시 미추홀구 제일로 42 (도화동)032-873-801537.458596126.67471
45동물판매업(일반)멍멍이와야옹이인천광역시 미추홀구 인주대로 272-1 (용현동)032-873-364037.452361126.666599
56동물판매업(일반)똥강아지인천광역시 미추홀구 소성로 238 (학익동)032-872-070437.438754126.673839
67동물판매업(일반)금자동아, 은자동아인천광역시 미추홀구 소성로 310 (문학동, 희망주택)032-866-331337.437575126.681486
78동물판매업(일반)펫앤펫 인천점 강아지의 모든것인천광역시 미추홀구 경인로 500 (주안동)<NA>37.45989126.694919
89동물판매업(일반)오드리 펫인천광역시 미추홀구 경인로 482 (주안동)<NA>37.459079126.693395
910동물판매업(일반)펫 스토리인천광역시 미추홀구 낙섬중로91번길 28-24 (용현동, 1층)032-888-097937.456926126.639792
연번유형상호명도로명주소전화번호위도경도
159160동물미용업(일반)라온캣독 펫살롱 인천점인천광역시 미추홀구 인주대로458번길 8 (주안동)<NA>37.450377126.687199
160161동물미용업(일반)파트라슈&네로인천광역시 미추홀구 소성로 99 (학익동)032-874-300337.444757126.660212
161162동물미용업(일반)멍블리인천광역시 미추홀구 경인로144번길 10 (숭의동)032-215-474837.465709126.658369
162163동물운송업불티나 펫인천광역시 미추홀구 미추로 5 (숭의동, 진복 행복마을)<NA>37.460724126.647667
163164동물운송업아지냥이콜인천광역시 미추홀구 매소홀로415번길 10 (학익동, 예다움)<NA>37.440552126.668639
164165동물운송업정성카인천광역시 미추홀구 염전로168번길 28, 도화 두손지젤시티 (도화동)<NA>37.476986126.659137
165166동물운송업펫이즈인천광역시 미추홀구 경원대로 717 (주안동, 인천관교 한신휴플러스)<NA>37.447083126.685205
166167동물운송업홍익인용펫인천광역시 미추홀구 매소홀로 143 (용현동, 윤성아파트)<NA>37.445992126.639494
167168동물운송업다솜이펫인천광역시 미추홀구 인주대로11번길 42, 진성투토펠리체 (숭의동)<NA>37.46206126.641016
168169동물운송업카라인천광역시 미추홀구 숙골로88번길 56 (도화동, e편한세상도화 6-2단지)<NA>37.475014126.664942