Overview

Dataset statistics

Number of variables12
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory108.5 B

Variable types

Numeric3
Text2
Categorical7

Dataset

Description인천광역시 부평구에 관리하는 게시판 현황 (소재지 주소, 설치장소, 게첩 면수, 광고 수수료 등)에 관한 데이터를 제공합니다.
Author인천광역시부평구시설관리공단
URLhttps://www.data.go.kr/data/15002988/fileData.do

Alerts

포스터 면수 has constant value ""Constant
상단 면수 has constant value ""Constant
포스터광고 수수료 has constant value ""Constant
포스터광고 규격 has constant value ""Constant
상단광고 수수료 has constant value ""Constant
상단광고 규격 has constant value ""Constant
데이터 기준일자 has constant value ""Constant
관리번호 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 관리번호High correlation
관리번호 has unique valuesUnique
설치장소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-11-11 16:36:56.960358
Analysis finished2023-11-11 16:36:59.147939
Duration2.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-11-12T01:36:59.238348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-11-12T01:36:59.420238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

소재지주소
Text

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-11-12T01:36:59.625675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length17.5
Min length13

Characters and Unicode

Total characters420
Distinct characters41
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)66.7%

Sample

1st row인천광역시 부평구 주부토로 206
2nd row인천광역시 부평구 주부토로 193
3rd row인천광역시 부평구 부흥북로 144
4th row인천광역시 부평구 길주남로 166
5th row인천광역시 부평구 부개로 12
ValueCountFrequency (%)
인천광역시 24
24.7%
부평구 23
23.7%
안남로 5
 
5.2%
16 2
 
2.1%
주부토로 2
 
2.1%
길주남로 2
 
2.1%
부흥북로 2
 
2.1%
부영로 2
 
2.1%
165 2
 
2.1%
12 2
 
2.1%
Other values (27) 31
32.0%
2023-11-12T01:37:00.208754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
18.1%
부 32
 
7.6%
천 26
 
6.2%
평 25
 
6.0%
인 24
 
5.7%
광 24
 
5.7%
역 24
 
5.7%
시 24
 
5.7%
로 24
 
5.7%
구 23
 
5.5%
Other values (31) 118
28.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 274
65.2%
Space Separator 76
 
18.1%
Decimal Number 70
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 32
11.7%
천 26
9.5%
평 25
9.1%
인 24
8.8%
광 24
8.8%
역 24
8.8%
시 24
8.8%
로 24
8.8%
구 23
8.4%
남 7
 
2.6%
Other values (20) 41
15.0%
Decimal Number
ValueCountFrequency (%)
1 20
28.6%
2 10
14.3%
6 10
14.3%
3 9
12.9%
5 8
 
11.4%
7 4
 
5.7%
4 4
 
5.7%
0 2
 
2.9%
9 2
 
2.9%
8 1
 
1.4%
Space Separator
ValueCountFrequency (%)
76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 274
65.2%
Common 146
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 32
11.7%
천 26
9.5%
평 25
9.1%
인 24
8.8%
광 24
8.8%
역 24
8.8%
시 24
8.8%
로 24
8.8%
구 23
8.4%
남 7
 
2.6%
Other values (20) 41
15.0%
Common
ValueCountFrequency (%)
76
52.1%
1 20
 
13.7%
2 10
 
6.8%
6 10
 
6.8%
3 9
 
6.2%
5 8
 
5.5%
7 4
 
2.7%
4 4
 
2.7%
0 2
 
1.4%
9 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 274
65.2%
ASCII 146
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
52.1%
1 20
 
13.7%
2 10
 
6.8%
6 10
 
6.8%
3 9
 
6.2%
5 8
 
5.5%
7 4
 
2.7%
4 4
 
2.7%
0 2
 
1.4%
9 2
 
1.4%
Hangul
ValueCountFrequency (%)
부 32
11.7%
천 26
9.5%
평 25
9.1%
인 24
8.8%
광 24
8.8%
역 24
8.8%
시 24
8.8%
로 24
8.8%
구 23
8.4%
남 7
 
2.6%
Other values (20) 41
15.0%

설치장소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-11-12T01:37:00.486868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.583333
Min length6

Characters and Unicode

Total characters254
Distinct characters84
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row갈산주공2단지 정문 앞
2nd row대동@ 103동 앞
3rd row부개주공 3단지 정문
4th row부평기적의도서관 앞
5th row부개주공 503동 앞
ValueCountFrequency (%)
앞 15
23.1%
정문 6
 
9.2%
버스정류장 5
 
7.7%
부개주공 4
 
6.2%
대우 2
 
3.1%
금호 2
 
3.1%
갈산주공2단지 1
 
1.5%
대보 1
 
1.5%
한화2차 1
 
1.5%
우성 1
 
1.5%
Other values (27) 27
41.5%
2023-11-12T01:37:01.054585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
16.1%
앞 15
 
5.9%
동 12
 
4.7%
정 11
 
4.3%
@ 9
 
3.5%
1 8
 
3.1%
부 7
 
2.8%
0 7
 
2.8%
주 6
 
2.4%
3 6
 
2.4%
Other values (74) 132
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
66.9%
Space Separator 41
 
16.1%
Decimal Number 32
 
12.6%
Other Punctuation 9
 
3.5%
Uppercase Letter 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 15
 
8.8%
동 12
 
7.1%
정 11
 
6.5%
부 7
 
4.1%
주 6
 
3.5%
문 6
 
3.5%
류 5
 
2.9%
장 5
 
2.9%
스 5
 
2.9%
버 5
 
2.9%
Other values (61) 93
54.7%
Decimal Number
ValueCountFrequency (%)
1 8
25.0%
0 7
21.9%
3 6
18.8%
2 5
15.6%
5 2
 
6.2%
8 1
 
3.1%
6 1
 
3.1%
4 1
 
3.1%
7 1
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
66.9%
Common 82
32.3%
Latin 2
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 15
 
8.8%
동 12
 
7.1%
정 11
 
6.5%
부 7
 
4.1%
주 6
 
3.5%
문 6
 
3.5%
류 5
 
2.9%
장 5
 
2.9%
스 5
 
2.9%
버 5
 
2.9%
Other values (61) 93
54.7%
Common
ValueCountFrequency (%)
41
50.0%
@ 9
 
11.0%
1 8
 
9.8%
0 7
 
8.5%
3 6
 
7.3%
2 5
 
6.1%
5 2
 
2.4%
8 1
 
1.2%
6 1
 
1.2%
4 1
 
1.2%
Latin
ValueCountFrequency (%)
G 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
66.9%
ASCII 84
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
48.8%
@ 9
 
10.7%
1 8
 
9.5%
0 7
 
8.3%
3 6
 
7.1%
2 5
 
6.0%
5 2
 
2.4%
8 1
 
1.2%
G 1
 
1.2%
M 1
 
1.2%
Other values (3) 3
 
3.6%
Hangul
ValueCountFrequency (%)
앞 15
 
8.8%
동 12
 
7.1%
정 11
 
6.5%
부 7
 
4.1%
주 6
 
3.5%
문 6
 
3.5%
류 5
 
2.9%
장 5
 
2.9%
스 5
 
2.9%
버 5
 
2.9%
Other values (61) 93
54.7%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.50688
Minimum37.495941
Maximum37.519431
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-11-12T01:37:01.232488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.495941
5-th percentile37.499421
Q137.501734
median37.50546
Q337.512448
95-th percentile37.517361
Maximum37.519431
Range0.02349
Interquartile range (IQR)0.0107135

Descriptive statistics

Standard deviation0.0064444854
Coefficient of variation (CV)0.00017182142
Kurtosis-0.9173921
Mean37.50688
Median Absolute Deviation (MAD)0.005149
Skewness0.32232723
Sum900.16513
Variance4.1531392 × 10-5
MonotonicityNot monotonic
2023-11-12T01:37:01.393951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
37.513222 1
 
4.2%
37.504293 1
 
4.2%
37.513644 1
 
4.2%
37.513827 1
 
4.2%
37.514739 1
 
4.2%
37.506059 1
 
4.2%
37.507752 1
 
4.2%
37.519431 1
 
4.2%
37.50992 1
 
4.2%
37.517824 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
37.495941 1
4.2%
37.499371 1
4.2%
37.499703 1
4.2%
37.50031 1
4.2%
37.500312 1
4.2%
37.500512 1
4.2%
37.502142 1
4.2%
37.503406 1
4.2%
37.503662 1
4.2%
37.504081 1
4.2%
ValueCountFrequency (%)
37.519431 1
4.2%
37.517824 1
4.2%
37.514739 1
4.2%
37.513827 1
4.2%
37.513644 1
4.2%
37.513222 1
4.2%
37.51219 1
4.2%
37.511869 1
4.2%
37.50992 1
4.2%
37.507752 1
4.2%

경도
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.72593
Minimum126.70596
Maximum126.7421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-11-12T01:37:01.529573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70596
5-th percentile126.70842
Q1126.71343
median126.72571
Q3126.73952
95-th percentile126.74172
Maximum126.7421
Range0.036141
Interquartile range (IQR)0.02608625

Descriptive statistics

Standard deviation0.013733851
Coefficient of variation (CV)0.00010837443
Kurtosis-1.8280874
Mean126.72593
Median Absolute Deviation (MAD)0.01384
Skewness-0.12011291
Sum3041.4224
Variance0.00018861867
MonotonicityNot monotonic
2023-11-12T01:37:01.952789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
126.725742 1
 
4.2%
126.705959 1
 
4.2%
126.72098 1
 
4.2%
126.709527 1
 
4.2%
126.70962 1
 
4.2%
126.714522 1
 
4.2%
126.714662 1
 
4.2%
126.710158 1
 
4.2%
126.741168 1
 
4.2%
126.737741 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
126.705959 1
4.2%
126.70834 1
4.2%
126.7089 1
4.2%
126.709527 1
4.2%
126.70962 1
4.2%
126.710158 1
4.2%
126.714522 1
4.2%
126.714662 1
4.2%
126.715989 1
4.2%
126.716554 1
4.2%
ValueCountFrequency (%)
126.7421 1
4.2%
126.741819 1
4.2%
126.741168 1
4.2%
126.740263 1
4.2%
126.739957 1
4.2%
126.739614 1
4.2%
126.739485 1
4.2%
126.738608 1
4.2%
126.738054 1
4.2%
126.737741 1
4.2%

포스터 면수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
12
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
12 24
100.0%

Length

2023-11-12T01:37:02.084333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:02.189579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 24
100.0%

상단 면수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
1
24 

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 24
100.0%

Length

2023-11-12T01:37:02.303095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:02.391031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
100.0%

포스터광고 수수료
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
26400
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row26400
2nd row26400
3rd row26400
4th row26400
5th row26400

Common Values

ValueCountFrequency (%)
26400 24
100.0%

Length

2023-11-12T01:37:02.483789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:02.571152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
26400 24
100.0%

포스터광고 규격
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
380x530
24 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row380x530
2nd row380x530
3rd row380x530
4th row380x530
5th row380x530

Common Values

ValueCountFrequency (%)
380x530 24
100.0%

Length

2023-11-12T01:37:02.663317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:02.751120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
380x530 24
100.0%

상단광고 수수료
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
31000
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row31000
2nd row31000
3rd row31000
4th row31000
5th row31000

Common Values

ValueCountFrequency (%)
31000 24
100.0%

Length

2023-11-12T01:37:02.835347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:02.917396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31000 24
100.0%

상단광고 규격
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2390x440
24 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2390x440
2nd row2390x440
3rd row2390x440
4th row2390x440
5th row2390x440

Common Values

ValueCountFrequency (%)
2390x440 24
100.0%

Length

2023-11-12T01:37:03.005900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:03.102449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2390x440 24
100.0%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-10-31
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-31
2nd row2023-10-31
3rd row2023-10-31
4th row2023-10-31
5th row2023-10-31

Common Values

ValueCountFrequency (%)
2023-10-31 24
100.0%

Length

2023-11-12T01:37:03.212107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-12T01:37:03.317163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-31 24
100.0%

Interactions

2023-11-12T01:36:58.330357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:57.548683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:57.939160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:58.454974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:57.662994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:58.065979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:58.579988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:57.792921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-12T01:36:58.195447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-11-12T01:37:03.394059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호소재지주소설치장소위도경도
관리번호1.0000.9931.0000.5620.677
소재지주소0.9931.0001.0000.9370.961
설치장소1.0001.0001.0001.0001.000
위도0.5620.9371.0001.0000.561
경도0.6770.9611.0000.5611.000
2023-11-12T01:37:03.495636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호위도경도
관리번호1.0000.572-0.495
위도0.5721.000-0.404
경도-0.495-0.4041.000

Missing values

2023-11-12T01:36:58.793045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-11-12T01:36:59.060976image/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

관리번호소재지주소설치장소위도경도포스터 면수상단 면수포스터광고 수수료포스터광고 규격상단광고 수수료상단광고 규격데이터 기준일자
01인천광역시 부평구 주부토로 206갈산주공2단지 정문 앞37.513222126.72574212126400380x530310002390x4402023-10-31
12인천광역시 부평구 주부토로 193대동@ 103동 앞37.511869126.72567712126400380x530310002390x4402023-10-31
23인천광역시 부평구 부흥북로 144부개주공 3단지 정문37.500512126.73805412126400380x530310002390x4402023-10-31
34인천광역시 부평구 길주남로 166부평기적의도서관 앞37.503662126.74026312126400380x530310002390x4402023-10-31
45인천광역시 부평구 부개로 12부개주공 503동 앞37.499703126.73948512126400380x530310002390x4402023-10-31
56인천광역시 부평구 부개로 12부개주공 603동 앞37.499371126.73961412126400380x530310002390x4402023-10-31
67인천광역시 부평구 부흥북로 175부일초등학교 정문 앞37.500312126.74181912126400380x530310002390x4402023-10-31
78인천광역시 부평구 길주남로 143부개주공 204동 앞37.50506126.73995712126400380x530310002390x4402023-10-31
89인천광역시 부평구 수변로 165미래생활고등학교 앞37.50031126.742112126400380x530310002390x4402023-10-31
910인천광역시 부평구 동수천로 118휴먼시아 7단지 입구 앞37.495941126.73693712126400380x530310002390x4402023-10-31
관리번호소재지주소설치장소위도경도포스터 면수상단 면수포스터광고 수수료포스터광고 규격상단광고 수수료상단광고 규격데이터 기준일자
1415인천광역시 부평구 부영로 165우성@ 101동 앞37.502142126.71598912126400380x530310002390x4402023-10-31
1516인천광역시 부평구 굴포로 151부평역사박물관37.51219126.73860812126400380x530310002390x4402023-10-31
1617인천광역시 부평구 후정동로 5대보@ 정문37.517824126.73774112126400380x530310002390x4402023-10-31
1718인천광역시 부평구 동선로 234번길 70진산중학교 삼거리37.50992126.74116812126400380x530310002390x4402023-10-31
1819인천광역시 부평구 평천로 153번길 13광명@ 버스정류장37.519431126.71015812126400380x530310002390x4402023-10-31
1920인천광역시 부평구 안남로 272금호@ 303동 앞37.507752126.71466212126400380x530310002390x4402023-10-31
2021인천광역시 부평구 안남로 272금호@ 버스정류장 앞37.506059126.71452212126400380x530310002390x4402023-10-31
2122인천광역시 부평구 안남로 16대우@ 115동 버스정류장37.514739126.7096212126400380x530310002390x4402023-10-31
2223인천광역시 부평구 안남로 16대우@ 118동 버스정류장37.513827126.70952712126400380x530310002390x4402023-10-31
2324인천광역시 부평구 부평대로 233GM자동차 정문37.513644126.7209812126400380x530310002390x4402023-10-31