Overview

Dataset statistics

Number of variables8
Number of observations144
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.6 KiB
Average record size in memory67.9 B

Variable types

Categorical3
Numeric3
Text2

Dataset

Description인천광역시 미추홀구 관내에 위치한 그늘막 설치현황에 대한 데이터로 설치장소명,주소, 위도, 경도 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15100671&srcSe=7661IVAWM27C61E190

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
위도 is highly overall correlated with 읍면동High correlation
경도 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:02:06.372087
Analysis finished2024-03-18 05:02:09.066288
Duration2.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
인천광역시
144 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 144
100.0%

Length

2024-03-18T14:02:09.118473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:02:09.212989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 144
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
미추홀구
144 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미추홀구 144
100.0%

Length

2024-03-18T14:02:09.300197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:02:09.396983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미추홀구 144
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
도화2.3동
23 
학익1동
13 
용현5동
12 
숭의1.3동
9 
용현1.4동
8 
Other values (16)
79 

Length

Max length6
Median length4
Mean length4.4722222
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용현5동
2nd row학익1동
3rd row도화1동
4th row도화2.3동
5th row주안1동

Common Values

ValueCountFrequency (%)
도화2.3동 23
16.0%
학익1동 13
 
9.0%
용현5동 12
 
8.3%
숭의1.3동 9
 
6.2%
용현1.4동 8
 
5.6%
주안8동 8
 
5.6%
도화1동 7
 
4.9%
주안6동 7
 
4.9%
관교동 7
 
4.9%
주안7동 6
 
4.2%
Other values (11) 44
30.6%

Length

2024-03-18T14:02:09.482169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도화2.3동 23
16.0%
학익1동 13
 
9.0%
용현5동 12
 
8.3%
숭의1.3동 9
 
6.2%
용현1.4동 8
 
5.6%
주안8동 8
 
5.6%
도화1동 7
 
4.9%
주안6동 7
 
4.9%
관교동 7
 
4.9%
용현2동 6
 
4.2%
Other values (11) 44
30.6%

관리번호
Real number (ℝ)

UNIQUE 

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.5
Minimum1
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-18T14:02:09.601769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.15
Q136.75
median72.5
Q3108.25
95-th percentile136.85
Maximum144
Range143
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation41.713307
Coefficient of variation (CV)0.57535596
Kurtosis-1.2
Mean72.5
Median Absolute Deviation (MAD)36
Skewness0
Sum10440
Variance1740
MonotonicityStrictly increasing
2024-03-18T14:02:09.740011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
74 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
Other values (134) 134
93.1%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%

설치장소명
Text

Distinct140
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-18T14:02:10.004526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length23
Mean length12.909722
Min length5

Characters and Unicode

Total characters1859
Distinct characters257
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)94.4%

Sample

1st row인하대역 앞 교통섬
2nd row학산사거리
3rd row도화초교 사거리
4th row도화사거리
5th row교통방송사거리 lg베스트샵 앞
ValueCountFrequency (%)
앞 71
 
17.4%
횡단보도 35
 
8.6%
교통섬 14
 
3.4%
사거리 11
 
2.7%
건너편 8
 
2.0%
삼거리 6
 
1.5%
정문 5
 
1.2%
숭의역 4
 
1.0%
인천 4
 
1.0%
행정복지센터 4
 
1.0%
Other values (204) 245
60.2%
2024-03-18T14:02:10.380337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
14.3%
앞 83
 
4.5%
리 71
 
3.8%
거 62
 
3.3%
사 52
 
2.8%
도 45
 
2.4%
단 39
 
2.1%
보 38
 
2.0%
횡 36
 
1.9%
교 31
 
1.7%
Other values (247) 1137
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1423
76.5%
Space Separator 265
 
14.3%
Decimal Number 74
 
4.0%
Close Punctuation 27
 
1.5%
Open Punctuation 27
 
1.5%
Uppercase Letter 23
 
1.2%
Lowercase Letter 11
 
0.6%
Dash Punctuation 3
 
0.2%
Other Punctuation 3
 
0.2%
Other Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 83
 
5.8%
리 71
 
5.0%
거 62
 
4.4%
사 52
 
3.7%
도 45
 
3.2%
단 39
 
2.7%
보 38
 
2.7%
횡 36
 
2.5%
교 31
 
2.2%
인 26
 
1.8%
Other values (210) 940
66.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
17.4%
K 3
13.0%
U 3
13.0%
L 3
13.0%
G 3
13.0%
C 2
8.7%
H 2
8.7%
N 1
 
4.3%
P 1
 
4.3%
T 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 18
24.3%
1 17
23.0%
4 11
14.9%
9 7
 
9.5%
8 5
 
6.8%
7 5
 
6.8%
6 4
 
5.4%
5 4
 
5.4%
3 3
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
18.2%
e 2
18.2%
k 1
9.1%
s 1
9.1%
d 1
9.1%
r 1
9.1%
o 1
9.1%
w 1
9.1%
g 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1423
76.5%
Common 402
 
21.6%
Latin 34
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 83
 
5.8%
리 71
 
5.0%
거 62
 
4.4%
사 52
 
3.7%
도 45
 
3.2%
단 39
 
2.7%
보 38
 
2.7%
횡 36
 
2.5%
교 31
 
2.2%
인 26
 
1.8%
Other values (210) 940
66.1%
Latin
ValueCountFrequency (%)
S 4
11.8%
K 3
 
8.8%
U 3
 
8.8%
L 3
 
8.8%
G 3
 
8.8%
C 2
 
5.9%
H 2
 
5.9%
l 2
 
5.9%
e 2
 
5.9%
k 1
 
2.9%
Other values (9) 9
26.5%
Common
ValueCountFrequency (%)
265
65.9%
) 27
 
6.7%
( 27
 
6.7%
2 18
 
4.5%
1 17
 
4.2%
4 11
 
2.7%
9 7
 
1.7%
8 5
 
1.2%
7 5
 
1.2%
6 4
 
1.0%
Other values (8) 16
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1423
76.5%
ASCII 434
 
23.3%
Enclosed Alphanum 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
61.1%
) 27
 
6.2%
( 27
 
6.2%
2 18
 
4.1%
1 17
 
3.9%
4 11
 
2.5%
9 7
 
1.6%
8 5
 
1.2%
7 5
 
1.2%
S 4
 
0.9%
Other values (25) 48
 
11.1%
Hangul
ValueCountFrequency (%)
앞 83
 
5.8%
리 71
 
5.0%
거 62
 
4.4%
사 52
 
3.7%
도 45
 
3.2%
단 39
 
2.7%
보 38
 
2.7%
횡 36
 
2.5%
교 31
 
2.2%
인 26
 
1.8%
Other values (210) 940
66.1%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

주소
Text

Distinct131
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-03-18T14:02:10.637315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length19.506944
Min length16

Characters and Unicode

Total characters2809
Distinct characters112
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)83.3%

Sample

1st row인천광역시 미추홀구 독배로 313
2nd row인천광역시 미추홀구 한나루로 364
3rd row인천광역시 미추홀구 도화동 546
4th row인천광역시 미추홀구 도화동 255
5th row인천광역시 미추홀구 매소홀로 247
ValueCountFrequency (%)
인천광역시 144
24.4%
미추홀구 144
24.4%
인주대로 10
 
1.7%
도화동 10
 
1.7%
매소홀로 10
 
1.7%
용현동 9
 
1.5%
경원대로 7
 
1.2%
인하로 7
 
1.2%
석정로 7
 
1.2%
경인로 7
 
1.2%
Other values (172) 235
39.8%
2024-03-18T14:02:10.988048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
448
15.9%
인 173
 
6.2%
홀 158
 
5.6%
미 149
 
5.3%
추 148
 
5.3%
천 147
 
5.2%
광 144
 
5.1%
역 144
 
5.1%
시 144
 
5.1%
구 144
 
5.1%
Other values (102) 1010
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1866
66.4%
Decimal Number 451
 
16.1%
Space Separator 448
 
15.9%
Dash Punctuation 35
 
1.2%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 173
9.3%
홀 158
 
8.5%
미 149
 
8.0%
추 148
 
7.9%
천 147
 
7.9%
광 144
 
7.7%
역 144
 
7.7%
시 144
 
7.7%
구 144
 
7.7%
로 101
 
5.4%
Other values (85) 414
22.2%
Decimal Number
ValueCountFrequency (%)
1 78
17.3%
2 71
15.7%
4 53
11.8%
5 44
9.8%
3 44
9.8%
7 41
9.1%
8 37
8.2%
9 31
 
6.9%
6 29
 
6.4%
0 23
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
448
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1866
66.4%
Common 941
33.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 173
9.3%
홀 158
 
8.5%
미 149
 
8.0%
추 148
 
7.9%
천 147
 
7.9%
광 144
 
7.7%
역 144
 
7.7%
시 144
 
7.7%
구 144
 
7.7%
로 101
 
5.4%
Other values (85) 414
22.2%
Common
ValueCountFrequency (%)
448
47.6%
1 78
 
8.3%
2 71
 
7.5%
4 53
 
5.6%
5 44
 
4.7%
3 44
 
4.7%
7 41
 
4.4%
8 37
 
3.9%
- 35
 
3.7%
9 31
 
3.3%
Other values (5) 59
 
6.3%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1866
66.4%
ASCII 943
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
448
47.5%
1 78
 
8.3%
2 71
 
7.5%
4 53
 
5.6%
5 44
 
4.7%
3 44
 
4.7%
7 41
 
4.3%
8 37
 
3.9%
- 35
 
3.7%
9 31
 
3.3%
Other values (7) 61
 
6.5%
Hangul
ValueCountFrequency (%)
인 173
9.3%
홀 158
 
8.5%
미 149
 
8.0%
추 148
 
7.9%
천 147
 
7.9%
광 144
 
7.7%
역 144
 
7.7%
시 144
 
7.7%
구 144
 
7.7%
로 101
 
5.4%
Other values (85) 414
22.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)90.2%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean37.455513
Minimum37.436545
Maximum37.476905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-18T14:02:11.156099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.436545
5-th percentile37.439895
Q137.446275
median37.452762
Q337.464519
95-th percentile37.474667
Maximum37.476905
Range0.040359629
Interquartile range (IQR)0.018243972

Descriptive statistics

Standard deviation0.011022796
Coefficient of variation (CV)0.00029429034
Kurtosis-1.1503684
Mean37.455513
Median Absolute Deviation (MAD)0.0088803931
Skewness0.1853847
Sum5356.1383
Variance0.00012150202
MonotonicityNot monotonic
2024-03-18T14:02:11.314004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4675258855587 3
 
2.1%
37.4602401948582 3
 
2.1%
37.4459676101935 2
 
1.4%
37.448246358947 2
 
1.4%
37.474729390613 2
 
1.4%
37.4769047931748 2
 
1.4%
37.4490344823306 2
 
1.4%
37.4520149469249 2
 
1.4%
37.4687833735337 2
 
1.4%
37.4746669122762 2
 
1.4%
Other values (119) 121
84.0%
ValueCountFrequency (%)
37.4365451636913 1
0.7%
37.4387521898928 1
0.7%
37.4387999833368 1
0.7%
37.4391102132307 1
0.7%
37.439350391275 1
0.7%
37.4397231675501 1
0.7%
37.4397512284095 1
0.7%
37.439890403881 1
0.7%
37.4399364399422 1
0.7%
37.4400537896378 1
0.7%
ValueCountFrequency (%)
37.4769047931748 2
1.4%
37.4758784089704 1
0.7%
37.4751883426183 2
1.4%
37.474729390613 2
1.4%
37.4746669122762 2
1.4%
37.4739644136398 1
0.7%
37.4717635032426 1
0.7%
37.4716432651221 1
0.7%
37.4709261054702 2
1.4%
37.4701338984516 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)90.2%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean126.66577
Minimum126.63367
Maximum126.70152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-03-18T14:02:11.447544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.63367
5-th percentile126.63872
Q1126.65089
median126.66586
Q3126.67924
95-th percentile126.69493
Maximum126.70152
Range0.06784729
Interquartile range (IQR)0.028349253

Descriptive statistics

Standard deviation0.017107059
Coefficient of variation (CV)0.00013505668
Kurtosis-0.87244715
Mean126.66577
Median Absolute Deviation (MAD)0.013869425
Skewness0.096354684
Sum18113.205
Variance0.00029265145
MonotonicityNot monotonic
2024-03-18T14:02:11.590001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.66586003162 3
 
2.1%
126.638622696629 3
 
2.1%
126.650890535445 2
 
1.4%
126.679984163028 2
 
1.4%
126.665622211404 2
 
1.4%
126.654016653853 2
 
1.4%
126.635875711991 2
 
1.4%
126.64506286268 2
 
1.4%
126.661915483713 2
 
1.4%
126.662124580957 2
 
1.4%
Other values (119) 121
84.0%
ValueCountFrequency (%)
126.633671366499 1
 
0.7%
126.635875711991 2
1.4%
126.636390077939 1
 
0.7%
126.638544258203 1
 
0.7%
126.638622696629 3
2.1%
126.639547827708 1
 
0.7%
126.640213114847 1
 
0.7%
126.640670436227 1
 
0.7%
126.641068487263 1
 
0.7%
126.64191677168 1
 
0.7%
ValueCountFrequency (%)
126.701518656221 1
0.7%
126.700397144208 1
0.7%
126.699234722595 1
0.7%
126.698002102329 1
0.7%
126.696986738293 1
0.7%
126.696679296029 1
0.7%
126.695769210281 1
0.7%
126.694945083966 1
0.7%
126.694795067944 1
0.7%
126.690384574125 1
0.7%

Interactions

2024-03-18T14:02:08.515292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:07.963246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.240164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.589566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.085277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.319561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.689641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.166438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:02:08.440166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:02:11.664122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동관리번호위도경도
읍면동1.0000.6710.8720.881
관리번호0.6711.0000.4320.661
위도0.8720.4321.0000.577
경도0.8810.6610.5771.000
2024-03-18T14:02:11.742617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위도경도읍면동
관리번호1.000-0.034-0.0280.305
위도-0.0341.000-0.2300.536
경도-0.028-0.2301.0000.553
읍면동0.3050.5360.5531.000

Missing values

2024-03-18T14:02:08.795842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:02:08.945883image/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.
2024-03-18T14:02:09.029955image/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

시도시군구읍면동관리번호설치장소명주소위도경도
0인천광역시미추홀구용현5동1인하대역 앞 교통섬인천광역시 미추홀구 독배로 31337.448228126.649653
1인천광역시미추홀구학익1동2학산사거리인천광역시 미추홀구 한나루로 36437.440447126.662536
2인천광역시미추홀구도화1동3도화초교 사거리인천광역시 미추홀구 도화동 54637.462115126.671652
3인천광역시미추홀구도화2.3동4도화사거리인천광역시 미추홀구 도화동 25537.467526126.66586
4인천광역시미추홀구주안1동5교통방송사거리 lg베스트샵 앞인천광역시 미추홀구 매소홀로 24737.445968126.650891
5인천광역시미추홀구주안1동6옛 시민회관 사거리인천광역시 미추홀구 경인로 34337.458837126.678195
6인천광역시미추홀구주안6동7석바위 사거리인천광역시 미추홀구 경원대로 84437.458072126.689692
7인천광역시미추홀구주안7동8신기시장 사거리인천광역시 미추홀구 주안동 146337.449381126.679729
8인천광역시미추홀구주안8동9승기사거리인천광역시 미추홀구 주안동 148437.451227126.682563
9인천광역시미추홀구관교동10인천 터미널 사거리인천광역시 미추홀구 관교동 터미널사거리<NA><NA>
시도시군구읍면동관리번호설치장소명주소위도경도
134인천광역시미추홀구관교동135문학경기장 사거리 교통섬인천광역시 미추홀구 관교동 67-437.4388126.694945
135인천광역시미추홀구관교동136교통공원 사거리인천광역시 미추홀구 관교동 565-237.43911126.698002
136인천광역시미추홀구관교동137중앙공원 앞인천광역시 미추홀구 관교동 1437.441669126.699235
137인천광역시미추홀구숭의2동138인주대로45번길 2 숭의커피 앞인천광역시 미추홀구 인주대로45번길 237.459332126.643333
138인천광역시미추홀구도화2.3동139송림로 194 신동아부동산 앞인천광역시 미추홀구 송림로 19437.476905126.654017
139인천광역시미추홀구도화2.3동140송림로 194 정문 앞인천광역시 미추홀구 송림로 19437.476905126.654017
140인천광역시미추홀구도화2.3동141엘리웨이 CU인천광역시 미추홀구 숙골로88번길 1237.46955126.664539
141인천광역시미추홀구도화2.3동142도화2.3동 행정복지센터 앞인천광역시 미추홀구 장고개로 29-137.470926126.666147
142인천광역시미추홀구용현2동143숭의역 4번 출구 앞인천광역시 미추홀구 숭의동 379-2237.461155126.638544
143인천광역시미추홀구학익1동144힐스테이트 학익 쪽문 앞인천광역시 미추홀구 독배로251번길 2437.443762126.648727