Overview

Dataset statistics

Number of variables9
Number of observations531
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)0.4%
Total size in memory39.5 KiB
Average record size in memory76.2 B

Variable types

Categorical4
Text2
Numeric3

Dataset

Description전북특별자치도 전주시 쓰레기 불법투기 단속 CCTV을 제공하며, 도로명주소, 지번주소, 위도, 경도 설치년도 등을 제공합니다.항목 : 구분, 도로명주소, 지번주소, 위도, 경도, 설치년도, 수량, 담당부서, 연락처제공부서 : 구청 청소위생과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15112948/fileData.do

Alerts

수량 has constant value ""Constant
Dataset has 2 (0.4%) duplicate rowsDuplicates
구분 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
연락처 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
담당부서 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 구분 and 2 other fieldsHigh correlation

Reproduction

Analysis started2024-03-14 10:01:47.247112
Analysis finished2024-03-14 10:01:51.297637
Duration4.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
덕진구
295 
완산구
236 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
덕진구 295
55.6%
완산구 236
44.4%

Length

2024-03-14T19:01:51.488824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:01:51.657387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
덕진구 295
55.6%
완산구 236
44.4%

도로명 주소
Text

Distinct462
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-03-14T19:01:52.766013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length33.222222
Min length1

Characters and Unicode

Total characters17641
Distinct characters359
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

Unique456 ?
Unique (%)85.9%

Sample

1st row전북특별자치도 전주시 덕진구 금암5길 11, 탑하우스 건물앞(금암동)
2nd row전북특별자치도 전주시 덕진구 금암5길 26-2, (금암동)
3rd row전북특별자치도 전주시 덕진구 권삼득로 211-29, (금암동)
4th row전북특별자치도 전주시 덕진구 삼송3길 30, (금암동)
5th row전북특별자치도 전주시 덕진구 삼송1길 10, (금암동, 보보스)
ValueCountFrequency (%)
전주시 467
 
14.8%
전북특별자치도 466
 
14.8%
덕진구 256
 
8.1%
완산구 211
 
6.7%
금암동 32
 
1.0%
인후동1가 25
 
0.8%
삼천동1가 25
 
0.8%
인후동2가 23
 
0.7%
효자동1가 20
 
0.6%
중화산동2가 18
 
0.6%
Other values (1010) 1606
51.0%
2024-03-14T19:01:54.096493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2998
 
17.0%
전 976
 
5.5%
동 543
 
3.1%
1 525
 
3.0%
주 520
 
2.9%
자 520
 
2.9%
구 500
 
2.8%
, 497
 
2.8%
북 491
 
2.8%
도 490
 
2.8%
Other values (349) 9581
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11319
64.2%
Space Separator 2998
 
17.0%
Decimal Number 1760
 
10.0%
Other Punctuation 498
 
2.8%
Close Punctuation 466
 
2.6%
Open Punctuation 466
 
2.6%
Dash Punctuation 129
 
0.7%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 976
 
8.6%
동 543
 
4.8%
주 520
 
4.6%
자 520
 
4.6%
구 500
 
4.4%
북 491
 
4.3%
도 490
 
4.3%
치 471
 
4.2%
시 470
 
4.2%
별 466
 
4.1%
Other values (331) 5872
51.9%
Decimal Number
ValueCountFrequency (%)
1 525
29.8%
2 318
18.1%
3 264
15.0%
4 143
 
8.1%
5 109
 
6.2%
6 98
 
5.6%
7 83
 
4.7%
0 81
 
4.6%
9 78
 
4.4%
8 61
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 497
99.8%
/ 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
80.0%
C 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2998
100.0%
Close Punctuation
ValueCountFrequency (%)
) 466
100.0%
Open Punctuation
ValueCountFrequency (%)
( 466
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11319
64.2%
Common 6317
35.8%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 976
 
8.6%
동 543
 
4.8%
주 520
 
4.6%
자 520
 
4.6%
구 500
 
4.4%
북 491
 
4.3%
도 490
 
4.3%
치 471
 
4.2%
시 470
 
4.2%
별 466
 
4.1%
Other values (331) 5872
51.9%
Common
ValueCountFrequency (%)
2998
47.5%
1 525
 
8.3%
, 497
 
7.9%
) 466
 
7.4%
( 466
 
7.4%
2 318
 
5.0%
3 264
 
4.2%
4 143
 
2.3%
- 129
 
2.0%
5 109
 
1.7%
Other values (6) 402
 
6.4%
Latin
ValueCountFrequency (%)
A 4
80.0%
C 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11319
64.2%
ASCII 6322
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2998
47.4%
1 525
 
8.3%
, 497
 
7.9%
) 466
 
7.4%
( 466
 
7.4%
2 318
 
5.0%
3 264
 
4.2%
4 143
 
2.3%
- 129
 
2.0%
5 109
 
1.7%
Other values (8) 407
 
6.4%
Hangul
ValueCountFrequency (%)
전 976
 
8.6%
동 543
 
4.8%
주 520
 
4.6%
자 520
 
4.6%
구 500
 
4.4%
북 491
 
4.3%
도 490
 
4.3%
치 471
 
4.2%
시 470
 
4.2%
별 466
 
4.1%
Other values (331) 5872
51.9%

지번주소
Text

Distinct525
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-03-14T19:01:54.929097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length34.333333
Min length25

Characters and Unicode

Total characters18231
Distinct characters313
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

Unique519 ?
Unique (%)97.7%

Sample

1st row전북특별자치도 전주시 덕진구 금암동 538-4번지 탑하우스 건물앞
2nd row전북특별자치도 전주시 덕진구 금암동 616-4번지
3rd row전북특별자치도 전주시 덕진구 금암동 477-1번지
4th row전북특별자치도 전주시 덕진구 금암동 1544-4번지
5th row전북특별자치도 전주시 덕진구 금암동 666-9번지 보보스
ValueCountFrequency (%)
전주시 532
 
16.9%
전북특별자치도 531
 
16.9%
덕진구 296
 
9.4%
완산구 236
 
7.5%
금암동 39
 
1.2%
인후동1가 35
 
1.1%
인후동2가 35
 
1.1%
삼천동1가 31
 
1.0%
송천동1가 30
 
1.0%
효자동1가 28
 
0.9%
Other values (936) 1351
43.0%
2024-03-14T19:01:56.017166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3029
 
16.6%
전 1082
 
5.9%
1 646
 
3.5%
자 586
 
3.2%
동 581
 
3.2%
주 566
 
3.1%
구 561
 
3.1%
도 556
 
3.0%
북 549
 
3.0%
지 544
 
3.0%
Other values (303) 9531
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12010
65.9%
Space Separator 3029
 
16.6%
Decimal Number 2707
 
14.8%
Dash Punctuation 483
 
2.6%
Uppercase Letter 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 1082
 
9.0%
자 586
 
4.9%
동 581
 
4.8%
주 566
 
4.7%
구 561
 
4.7%
도 556
 
4.6%
북 549
 
4.6%
지 544
 
4.5%
시 537
 
4.5%
치 536
 
4.5%
Other values (289) 5912
49.2%
Decimal Number
ValueCountFrequency (%)
1 646
23.9%
2 403
14.9%
3 290
10.7%
5 253
 
9.3%
6 222
 
8.2%
4 217
 
8.0%
7 216
 
8.0%
8 166
 
6.1%
9 154
 
5.7%
0 140
 
5.2%
Space Separator
ValueCountFrequency (%)
3029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 483
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12010
65.9%
Common 6220
34.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 1082
 
9.0%
자 586
 
4.9%
동 581
 
4.8%
주 566
 
4.7%
구 561
 
4.7%
도 556
 
4.6%
북 549
 
4.6%
지 544
 
4.5%
시 537
 
4.5%
치 536
 
4.5%
Other values (289) 5912
49.2%
Common
ValueCountFrequency (%)
3029
48.7%
1 646
 
10.4%
- 483
 
7.8%
2 403
 
6.5%
3 290
 
4.7%
5 253
 
4.1%
6 222
 
3.6%
4 217
 
3.5%
7 216
 
3.5%
8 166
 
2.7%
Other values (3) 295
 
4.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12010
65.9%
ASCII 6221
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3029
48.7%
1 646
 
10.4%
- 483
 
7.8%
2 403
 
6.5%
3 290
 
4.7%
5 253
 
4.1%
6 222
 
3.6%
4 217
 
3.5%
7 216
 
3.5%
8 166
 
2.7%
Other values (4) 296
 
4.8%
Hangul
ValueCountFrequency (%)
전 1082
 
9.0%
자 586
 
4.9%
동 581
 
4.8%
주 566
 
4.7%
구 561
 
4.7%
도 556
 
4.6%
북 549
 
4.6%
지 544
 
4.5%
시 537
 
4.5%
치 536
 
4.5%
Other values (289) 5912
49.2%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct515
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.830254
Minimum35.755
Maximum35.896032
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-03-14T19:01:56.258434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.755
5-th percentile35.791619
Q135.810968
median35.831489
Q335.847245
95-th percentile35.872685
Maximum35.896032
Range0.1410321
Interquartile range (IQR)0.036277245

Descriptive statistics

Standard deviation0.026128015
Coefficient of variation (CV)0.00072921658
Kurtosis-0.21435228
Mean35.830254
Median Absolute Deviation (MAD)0.01830504
Skewness-0.045400858
Sum19025.865
Variance0.00068267318
MonotonicityNot monotonic
2024-03-14T19:01:56.519630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.79403423 4
 
0.8%
35.84662876 2
 
0.4%
35.83132526 2
 
0.4%
35.82512081 2
 
0.4%
35.84080133 2
 
0.4%
35.81295117 2
 
0.4%
35.79439201 2
 
0.4%
35.87258246 2
 
0.4%
35.85703712 2
 
0.4%
35.88483433 2
 
0.4%
Other values (505) 509
95.9%
ValueCountFrequency (%)
35.75500017 1
0.2%
35.76078479 1
0.2%
35.7626508 1
0.2%
35.76319504 1
0.2%
35.76456849 1
0.2%
35.76483279 1
0.2%
35.76626082 1
0.2%
35.76979531 1
0.2%
35.7713323 1
0.2%
35.77268044 1
0.2%
ValueCountFrequency (%)
35.89603227 1
0.2%
35.8944938 1
0.2%
35.89268418 1
0.2%
35.89225697 1
0.2%
35.89177294 1
0.2%
35.88985373 1
0.2%
35.88777132 1
0.2%
35.88738147 1
0.2%
35.88536432 1
0.2%
35.88506076 1
0.2%

경도
Real number (ℝ)

Distinct515
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12877
Minimum127.00477
Maximum127.19696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-03-14T19:01:57.035553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.00477
5-th percentile127.07453
Q1127.11724
median127.13201
Q3127.14795
95-th percentile127.16615
Maximum127.19696
Range0.1921866
Interquartile range (IQR)0.0307128

Descriptive statistics

Standard deviation0.029487564
Coefficient of variation (CV)0.00023195037
Kurtosis2.8629886
Mean127.12877
Median Absolute Deviation (MAD)0.0153609
Skewness-1.2931648
Sum67505.375
Variance0.00086951641
MonotonicityNot monotonic
2024-03-14T19:01:57.354093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1245121 4
 
0.8%
127.1655372 2
 
0.4%
127.1438266 2
 
0.4%
127.1716829 2
 
0.4%
127.1570636 2
 
0.4%
127.1280118 2
 
0.4%
127.0782432 2
 
0.4%
127.1133073 2
 
0.4%
127.1234446 2
 
0.4%
127.0765887 2
 
0.4%
Other values (505) 509
95.9%
ValueCountFrequency (%)
127.0047691 1
0.2%
127.0081133 1
0.2%
127.0111296 1
0.2%
127.0183684 1
0.2%
127.0215084 1
0.2%
127.0218019 1
0.2%
127.0246871 1
0.2%
127.0286626 1
0.2%
127.0306769 1
0.2%
127.0334505 1
0.2%
ValueCountFrequency (%)
127.1969557 1
0.2%
127.1933322 1
0.2%
127.1918835 1
0.2%
127.1900658 1
0.2%
127.1849733 1
0.2%
127.1829243 1
0.2%
127.1823286 1
0.2%
127.1763208 1
0.2%
127.1732593 2
0.4%
127.1729579 1
0.2%

설치년도
Real number (ℝ)

Distinct9
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.0038
Minimum2014
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-03-14T19:01:57.579201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12016
median2018
Q32021
95-th percentile2022
Maximum2022
Range8
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.5073449
Coefficient of variation (CV)0.0012424877
Kurtosis-1.1579429
Mean2018.0038
Median Absolute Deviation (MAD)2
Skewness0.17810316
Sum1071560
Variance6.2867782
MonotonicityNot monotonic
2024-03-14T19:01:57.795278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2017 94
17.7%
2016 78
14.7%
2021 72
13.6%
2022 63
11.9%
2018 63
11.9%
2015 49
9.2%
2014 42
7.9%
2019 41
7.7%
2020 29
 
5.5%
ValueCountFrequency (%)
2014 42
7.9%
2015 49
9.2%
2016 78
14.7%
2017 94
17.7%
2018 63
11.9%
2019 41
7.7%
2020 29
 
5.5%
2021 72
13.6%
2022 63
11.9%
ValueCountFrequency (%)
2022 63
11.9%
2021 72
13.6%
2020 29
 
5.5%
2019 41
7.7%
2018 63
11.9%
2017 94
17.7%
2016 78
14.7%
2015 49
9.2%
2014 42
7.9%

수량
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
1
531 

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 (%)
1 531
100.0%

Length

2024-03-14T19:01:58.029029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:01:58.222870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 531
100.0%

담당부서
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
덕진구 청소위생과
295 
완산구 청소위생과
236 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row덕진구 청소위생과
2nd row덕진구 청소위생과
3rd row덕진구 청소위생과
4th row덕진구 청소위생과
5th row덕진구 청소위생과

Common Values

ValueCountFrequency (%)
덕진구 청소위생과 295
55.6%
완산구 청소위생과 236
44.4%

Length

2024-03-14T19:01:58.438396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:01:58.601220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소위생과 531
50.0%
덕진구 295
27.8%
완산구 236
22.2%

연락처
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
063-270-6378
295 
063-220-5181
236 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row063-270-6378
2nd row063-270-6378
3rd row063-270-6378
4th row063-270-6378
5th row063-270-6378

Common Values

ValueCountFrequency (%)
063-270-6378 295
55.6%
063-220-5181 236
44.4%

Length

2024-03-14T19:01:58.778744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:01:58.944619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
063-270-6378 295
55.6%
063-220-5181 236
44.4%

Interactions

2024-03-14T19:01:49.798258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:48.093335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:48.935365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:50.077745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:48.368015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:49.220879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:50.372983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:48.652870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:01:49.507182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:01:59.061307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분위도경도설치년도담당부서연락처
구분1.0000.9720.4320.0151.0001.000
위도0.9721.0000.7070.2530.9720.972
경도0.4320.7071.0000.2080.4320.432
설치년도0.0150.2530.2081.0000.0150.015
담당부서1.0000.9720.4320.0151.0001.000
연락처1.0000.9720.4320.0151.0001.000
2024-03-14T19:01:59.236844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연락처담당부서
구분1.0000.9960.996
연락처0.9961.0000.996
담당부서0.9960.9961.000
2024-03-14T19:01:59.429794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치년도구분담당부서연락처
위도1.000-0.1210.1230.8490.8490.849
경도-0.1211.000-0.1390.3290.3290.329
설치년도0.123-0.1391.0000.0000.0000.000
구분0.8490.3290.0001.0000.9960.996
담당부서0.8490.3290.0000.9961.0000.996
연락처0.8490.3290.0000.9960.9961.000

Missing values

2024-03-14T19:01:50.756192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:01:51.200444image/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

구분도로명 주소지번주소위도경도설치년도수량담당부서연락처
0덕진구전북특별자치도 전주시 덕진구 금암5길 11, 탑하우스 건물앞(금암동)전북특별자치도 전주시 덕진구 금암동 538-4번지 탑하우스 건물앞35.838666127.13686320161덕진구 청소위생과063-270-6378
1덕진구전북특별자치도 전주시 덕진구 금암5길 26-2, (금암동)전북특별자치도 전주시 덕진구 금암동 616-4번지35.839442127.13572620221덕진구 청소위생과063-270-6378
2덕진구전북특별자치도 전주시 덕진구 권삼득로 211-29, (금암동)전북특별자치도 전주시 덕진구 금암동 477-1번지35.836487127.13465120151덕진구 청소위생과063-270-6378
3덕진구전북특별자치도 전주시 덕진구 삼송3길 30, (금암동)전북특별자치도 전주시 덕진구 금암동 1544-4번지35.843504127.13650120171덕진구 청소위생과063-270-6378
4덕진구전북특별자치도 전주시 덕진구 삼송1길 10, (금암동, 보보스)전북특별자치도 전주시 덕진구 금암동 666-9번지 보보스35.841476127.13281420171덕진구 청소위생과063-270-6378
5덕진구전북특별자치도 전주시 덕진구 떡전5길 22, 구방송대학교 사거리(금암동)전북특별자치도 전주시 덕진구 금암동 752-6번지 구방송대학교 사거리35.837671127.13005520171덕진구 청소위생과063-270-6378
6덕진구전북특별자치도 전주시 덕진구 금암1길 21, 부근 (금암동)전북특별자치도 전주시 덕진구 금암동 611번지 부근35.839281127.13454320171덕진구 청소위생과063-270-6378
7덕진구전북특별자치도 전주시 덕진구 금암6길 40, (금암동)전북특별자치도 전주시 덕진구 금암동 530-11번지35.8402127.13712320181덕진구 청소위생과063-270-6378
8덕진구전북특별자치도 전주시 덕진구 삼송5길 9, 금암동꾀꼬리공원입구 (금암동)전북특별자치도 전주시 덕진구 금암동 1545-16번지 금암동꾀꼬리공원입구35.842865127.13660720181덕진구 청소위생과063-270-6378
9덕진구전북특별자치도 전주시 덕진구 권삼득로 226, 금암동그랜드마트 맞은편(금암동)전북특별자치도 전주시 덕진구 금암동 563-2번지 금암동그랜드마트 맞은편35.838118127.13452220181덕진구 청소위생과063-270-6378
구분도로명 주소지번주소위도경도설치년도수량담당부서연락처
521완산구전북특별자치도 전주시 완산구 홍산중앙로 33, 놀부보쌈도청 (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1535-5번지 놀부보쌈도청35.816442127.1087320141완산구 청소위생과063-220-5181
522완산구전북특별자치도 전주시 완산구 효자동3가 1098-3번지 선화학교 옆 도로부지35.820416127.08937520151완산구 청소위생과063-220-5181
523완산구전북특별자치도 전주시 완산구 효자동3가 1443-2번지 서곡제 2호공원35.834161127.10257720151완산구 청소위생과063-220-5181
524완산구전북특별자치도 전주시 완산구 효자동3가 1433번지 서중공원앞35.835306127.10019620161완산구 청소위생과063-220-5181
525완산구전북특별자치도 전주시 완산구 만지길 20-7, (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1115-2번지35.821005127.09086220171완산구 청소위생과063-220-5181
526완산구전북특별자치도 전주시 완산구 척동길 19, 뒤편인도가 (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1642-14번지 뒤편인도가35.823426127.10007520171완산구 청소위생과063-220-5181
527완산구전북특별자치도 전주시 완산구 서곡6길 8, (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1420-2번지35.836427127.10296120211완산구 청소위생과063-220-5181
528완산구전북특별자치도 전주시 완산구 서곡2길 16-2, 신덕공원부근 2호 (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1464-2번지 신덕공원부근 2호35.833835127.10228220211완산구 청소위생과063-220-5181
529완산구전북특별자치도 전주시 완산구 문학대6길 14, 문학초인근 (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1613-1번지 문학초인근35.828318127.10336220211완산구 청소위생과063-220-5181
530완산구전북특별자치도 전주시 완산구 황강서원5길 41, 앞헌옷수거함 (효자동3가)전북특별자치도 전주시 완산구 효자동3가 1590-8번지 앞헌옷수거함35.829348127.09890220211완산구 청소위생과063-220-5181

Duplicate rows

Most frequently occurring

구분도로명 주소지번주소위도경도설치년도수량담당부서연락처# duplicates
0덕진구전북특별자치도 전주시 덕진구 반촌1길 21, (진북동)전북특별자치도 전주시 덕진구 진북동 325-19번지35.831325127.14382720141덕진구 청소위생과063-270-63782
1덕진구전북특별자치도 전주시 덕진구 인교6길 13-21, 하인교공원주변 (우아동1가)전북특별자치도 전주시 덕진구 우아동1가 1105-1번지 하인교공원주변35.825121127.17168320161덕진구 청소위생과063-270-63782