Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

Categorical7
Text1
DateTime1
Numeric2

Dataset

Description제주 신규 공공 와이파이 설치제거를 위한 도내 카테고리별 설치 및 이용 현황 데이터 매쉬업 결과 정보입니다. - 읍면동명, 맥주소, 서비스 사용시간, 사용횟수 등 정보 제공 - 서비스 사용시간 (초), 사용횟수 (건) - 제주빅데이터센터 데이터 활용
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/760

Alerts

서비스 사용시간 has constant value ""Constant
사용 횟수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시도명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
읍면동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 시도명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 읍면동명High correlation

Reproduction

Analysis started2023-12-11 19:30:08.498230
Analysis finished2023-12-11 19:30:09.905229
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2017-01-21
 
472
2017-01-07
 
467
2017-01-19
 
454
2017-01-03
 
445
2017-01-18
 
444
Other values (19)
7718 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-01-08
2nd row2017-01-03
3rd row2017-01-03
4th row2017-01-11
5th row2017-01-03

Common Values

ValueCountFrequency (%)
2017-01-21 472
 
4.7%
2017-01-07 467
 
4.7%
2017-01-19 454
 
4.5%
2017-01-03 445
 
4.5%
2017-01-18 444
 
4.4%
2017-01-08 436
 
4.4%
2017-01-12 435
 
4.3%
2017-01-23 432
 
4.3%
2017-01-06 429
 
4.3%
2017-01-17 424
 
4.2%
Other values (14) 5562
55.6%

Length

2023-12-12T04:30:09.969606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-01-21 472
 
4.7%
2017-01-07 467
 
4.7%
2017-01-19 454
 
4.5%
2017-01-03 445
 
4.5%
2017-01-18 444
 
4.4%
2017-01-08 436
 
4.4%
2017-01-12 435
 
4.3%
2017-01-23 432
 
4.3%
2017-01-06 429
 
4.3%
2017-01-17 424
 
4.2%
Other values (14) 5562
55.6%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5459 
서귀포시
4541 

Length

Max length4
Median length3
Mean length3.4541
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주시
2nd row제주시
3rd row제주시
4th row제주시
5th row서귀포시

Common Values

ValueCountFrequency (%)
제주시 5459
54.6%
서귀포시 4541
45.4%

Length

2023-12-12T04:30:10.093010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:30:10.178177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5459
54.6%
서귀포시 4541
45.4%

읍면동명
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
천지동
 
548
성산읍
 
526
송산동
 
485
조천읍
 
449
구좌읍
 
380
Other values (44)
7612 

Length

Max length4
Median length3
Mean length3.1014
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row외도동
2nd row오라동
3rd row삼도2동
4th row조천읍
5th row천지동

Common Values

ValueCountFrequency (%)
천지동 548
 
5.5%
성산읍 526
 
5.3%
송산동 485
 
4.9%
조천읍 449
 
4.5%
구좌읍 380
 
3.8%
아라동 353
 
3.5%
노형동 351
 
3.5%
애월읍 348
 
3.5%
봉개동 343
 
3.4%
남원읍 334
 
3.3%
Other values (39) 5883
58.8%

Length

2023-12-12T04:30:10.302558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
천지동 548
 
5.5%
성산읍 526
 
5.3%
송산동 485
 
4.9%
조천읍 449
 
4.5%
구좌읍 380
 
3.8%
아라동 353
 
3.5%
노형동 351
 
3.5%
애월읍 348
 
3.5%
봉개동 343
 
3.4%
남원읍 334
 
3.3%
Other values (39) 5883
58.8%

맥주소
Text

Distinct2271
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T04:30:10.544407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters640000
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)1.8%

Sample

1st row62c951766110016b331d420461e2640fdd9c4da65748d47589615e27b2d0a118
2nd rowf50ca6a6fba87e68e848d65b0244bfaa9df059abb810de8a8b0582ff03bedff6
3rd row43ed55ff00f83d1903ae153362acdcdf85ac042f4433745d0a09f188ab0f5c1d
4th row67785ea8a31a943f2b00157ea61426a781648087afb17ce6cc9cac8dba90d80e
5th row67faa69aa19bc56f196f7182f77e575426d83badd7513377013879b97ee2ed8b
ValueCountFrequency (%)
c8dcc32977e4e6b10ca85864365b4119d2035e6b0ac7c3ea0099553c0e0226c9 23
 
0.2%
e53ee7e3dd32c69b86a84a19d4b59d1ce390020f2071e1933542cbdf5c00ec5a 23
 
0.2%
3a1ce5a34d05ac70d5cfdd6fdb6e24044e4ba25e5da97aabf261e73692b7524c 22
 
0.2%
a2fdb8319f700a83180b624a83e52d6259ed1b5b616fb4f7da7f319314a5268d 22
 
0.2%
1a413f41f6df4f24fefd1f563fb21e33f96f4dca0d1be3c6d444be1a3b356ed2 22
 
0.2%
8510afbbca0ba51aca24803e6fe252adaa4c419334884b557a067f2736b1b903 22
 
0.2%
4829c048c549d796371745a7152f28182311a0ef15a28244f387b66f3f1e2079 21
 
0.2%
e7bd3191c740beecf041b91bf7eb711ccc4c71fefb3c4633e9f0bfcfe6548260 21
 
0.2%
1ff0f392395436fcf560f2081e0a5ce15ab01e9d20fbc65630ae02b6a5f3ac27 21
 
0.2%
f819871a735dbf8f8bd1dcf3eb8534130cfa817c5a46456c429adb647c4823ac 20
 
0.2%
Other values (2261) 9783
97.8%
2023-12-12T04:30:10.950102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 40943
 
6.4%
f 40735
 
6.4%
7 40731
 
6.4%
6 40545
 
6.3%
e 40110
 
6.3%
4 40090
 
6.3%
a 40000
 
6.2%
0 39898
 
6.2%
b 39769
 
6.2%
5 39686
 
6.2%
Other values (6) 237493
37.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400348
62.6%
Lowercase Letter 239652
37.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 40943
10.2%
7 40731
10.2%
6 40545
10.1%
4 40090
10.0%
0 39898
10.0%
5 39686
9.9%
2 39668
9.9%
1 39648
9.9%
8 39573
9.9%
9 39566
9.9%
Lowercase Letter
ValueCountFrequency (%)
f 40735
17.0%
e 40110
16.7%
a 40000
16.7%
b 39769
16.6%
c 39682
16.6%
d 39356
16.4%

Most occurring scripts

ValueCountFrequency (%)
Common 400348
62.6%
Latin 239652
37.4%

Most frequent character per script

Common
ValueCountFrequency (%)
3 40943
10.2%
7 40731
10.2%
6 40545
10.1%
4 40090
10.0%
0 39898
10.0%
5 39686
9.9%
2 39668
9.9%
1 39648
9.9%
8 39573
9.9%
9 39566
9.9%
Latin
ValueCountFrequency (%)
f 40735
17.0%
e 40110
16.7%
a 40000
16.7%
b 39769
16.6%
c 39682
16.6%
d 39356
16.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 640000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 40943
 
6.4%
f 40735
 
6.4%
7 40731
 
6.4%
6 40545
 
6.3%
e 40110
 
6.3%
4 40090
 
6.3%
a 40000
 
6.2%
0 39898
 
6.2%
b 39769
 
6.2%
5 39686
 
6.2%
Other values (6) 237493
37.1%

개통일
Date

Distinct243
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-07-19 00:00:00
Maximum2020-04-27 00:00:00
2023-12-12T04:30:11.099807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:30:11.236093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1519
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.390569
Minimum33.166454
Maximum33.559583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:30:11.418452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.166454
5-th percentile33.240936
Q133.254841
median33.434496
Q333.497467
95-th percentile33.526917
Maximum33.559583
Range0.393129
Interquartile range (IQR)0.242626

Descriptive statistics

Standard deviation0.11431499
Coefficient of variation (CV)0.0034235712
Kurtosis-1.6585257
Mean33.390569
Median Absolute Deviation (MAD)0.083587
Skewness-0.19616689
Sum333905.69
Variance0.013067917
MonotonicityNot monotonic
2023-12-12T04:30:11.582804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.511806 58
 
0.6%
33.249836 55
 
0.5%
33.2495 51
 
0.5%
33.248697 49
 
0.5%
33.437048 45
 
0.4%
33.246184 44
 
0.4%
33.247744 44
 
0.4%
33.244728 40
 
0.4%
33.243868 40
 
0.4%
33.245962 39
 
0.4%
Other values (1509) 9535
95.3%
ValueCountFrequency (%)
33.166453999999995 6
 
0.1%
33.199104 6
 
0.1%
33.205119 10
0.1%
33.205906 5
 
0.1%
33.206792 2
 
< 0.1%
33.207068 4
 
< 0.1%
33.208525 4
 
< 0.1%
33.208902 4
 
< 0.1%
33.209822 4
 
< 0.1%
33.210076 16
0.2%
ValueCountFrequency (%)
33.559583 5
 
0.1%
33.558634999999995 9
0.1%
33.557889 4
 
< 0.1%
33.557666 9
0.1%
33.55761 5
 
0.1%
33.557227000000005 13
0.1%
33.557167 10
0.1%
33.556926000000004 7
0.1%
33.556553 11
0.1%
33.556414000000004 3
 
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1529
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.5553
Minimum126.16361
Maximum126.96873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:30:11.770161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16361
5-th percentile126.25855
Q1126.49082
median126.55333
Q3126.60837
95-th percentile126.90284
Maximum126.96873
Range0.805128
Interquartile range (IQR)0.11755

Descriptive statistics

Standard deviation0.16389384
Coefficient of variation (CV)0.0012950373
Kurtosis0.46626962
Mean126.5553
Median Absolute Deviation (MAD)0.061144
Skewness0.26176415
Sum1265553
Variance0.02686119
MonotonicityNot monotonic
2023-12-12T04:30:11.949764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.526056 58
 
0.6%
126.559971 55
 
0.5%
126.56658600000002 51
 
0.5%
126.564107 49
 
0.5%
126.628152 45
 
0.4%
126.557365 44
 
0.4%
126.5603 44
 
0.4%
126.569025 40
 
0.4%
126.563767 40
 
0.4%
126.569931 40
 
0.4%
Other values (1519) 9534
95.3%
ValueCountFrequency (%)
126.163606 1
 
< 0.1%
126.163778 4
< 0.1%
126.164197 5
0.1%
126.165759 5
0.1%
126.166233 1
 
< 0.1%
126.166301 1
 
< 0.1%
126.166819 9
0.1%
126.167783 5
0.1%
126.168003 8
0.1%
126.171035 3
 
< 0.1%
ValueCountFrequency (%)
126.968734 13
0.1%
126.967512 2
 
< 0.1%
126.967145 4
 
< 0.1%
126.9658 2
 
< 0.1%
126.965055 9
0.1%
126.964697 6
0.1%
126.963074 3
 
< 0.1%
126.959746 4
 
< 0.1%
126.959703 5
 
0.1%
126.959575 5
 
0.1%

카테고리
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
버스정류소
2356 
관광지
1982 
전기차충전소
960 
올레코스
895 
공원
876 
Other values (15)
2931 

Length

Max length13
Median length10
Mean length4.0812
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row버스정류소
2nd row전기차충전소
3rd row테마거리
4th row관광지
5th row테마거리

Common Values

ValueCountFrequency (%)
버스정류소 2356
23.6%
관광지 1982
19.8%
전기차충전소 960
9.6%
올레코스 895
 
8.9%
공원 876
 
8.8%
테마거리 835
 
8.3%
해변 488
 
4.9%
전통시장 456
 
4.6%
정류소 258
 
2.6%
공공기관 214
 
2.1%
Other values (10) 680
 
6.8%

Length

2023-12-12T04:30:12.146590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
버스정류소 2356
23.4%
관광지 1982
19.7%
전기차충전소 960
9.5%
올레코스 895
 
8.9%
공원 876
 
8.7%
테마거리 835
 
8.3%
해변 488
 
4.8%
전통시장 456
 
4.5%
정류소 258
 
2.6%
공공기관 214
 
2.1%
Other values (10) 760
 
7.5%

서비스 사용시간
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T04:30:12.291648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:30:12.376855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

사용 횟수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-12T04:30:12.484206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:30:12.577217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-12-15
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-15
2nd row2020-12-15
3rd row2020-12-15
4th row2020-12-15
5th row2020-12-15

Common Values

ValueCountFrequency (%)
2020-12-15 10000
100.0%

Length

2023-12-12T04:30:12.668805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:30:12.762375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-15 10000
100.0%

Interactions

2023-12-12T04:30:09.402910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:30:09.198331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:30:09.528312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:30:09.300915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:30:13.048519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자시도명읍면동명위도경도카테고리
일자1.0000.0110.0000.0000.0000.000
시도명0.0111.0001.0000.9770.2870.348
읍면동명0.0001.0001.0000.9130.9600.789
위도0.0000.9770.9131.0000.7780.629
경도0.0000.2870.9600.7781.0000.582
카테고리0.0000.3480.7890.6290.5821.000
2023-12-12T04:30:13.160429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자시도명읍면동명카테고리
일자1.0000.0090.0000.000
시도명0.0091.0000.9980.275
읍면동명0.0000.9981.0000.308
카테고리0.0000.2750.3081.000
2023-12-12T04:30:13.266614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도일자시도명읍면동명카테고리
위도1.0000.1050.0000.8670.6090.249
경도0.1051.0000.0000.2200.7510.222
일자0.0000.0001.0000.0090.0000.000
시도명0.8670.2200.0091.0000.9980.275
읍면동명0.6090.7510.0000.9981.0000.308
카테고리0.2490.2220.0000.2750.3081.000

Missing values

2023-12-12T04:30:09.692322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:30:09.839138image/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

일자시도명읍면동명맥주소개통일위도경도카테고리서비스 사용시간사용 횟수데이터기준일자
206102017-01-08제주시외도동62c951766110016b331d420461e2640fdd9c4da65748d47589615e27b2d0a1182018-04-0233.493144126.434315버스정류소002020-12-15
66272017-01-03제주시오라동f50ca6a6fba87e68e848d65b0244bfaa9df059abb810de8a8b0582ff03bedff62017-11-1533.491891126.519879전기차충전소002020-12-15
75022017-01-03제주시삼도2동43ed55ff00f83d1903ae153362acdcdf85ac042f4433745d0a09f188ab0f5c1d2017-08-1433.512306126.52225테마거리002020-12-15
295452017-01-11제주시조천읍67785ea8a31a943f2b00157ea61426a781648087afb17ce6cc9cac8dba90d80e2017-08-2933.44211126.666717관광지002020-12-15
54782017-01-03서귀포시천지동67faa69aa19bc56f196f7182f77e575426d83badd7513377013879b97ee2ed8b2017-08-3033.241969126.563098테마거리002020-12-15
305412017-01-12서귀포시안덕면782fd0425cbbab83eafb6fbb1c241650ee4646945deab5e35c949c8d5bb0247a2020-04-1633.251022126.330798전기차충전소002020-12-15
562822017-01-21서귀포시천지동bb6ec9a47a178c3f13cd7182a3f6751c5a9efd5208c90e780d11317a12cbb1d52017-08-3033.245962126.563879테마거리002020-12-15
261932017-01-10서귀포시표선면c175b36ce659d3c2342f2067a4e90a6f5ef1ad6145af77446447ac21e6a083dc2017-08-2733.326813126.833486버스정류소002020-12-15
159062017-01-06서귀포시성산읍98b0f5a794f33e5165be3d50cd43db562f35e84c9e4f3b7a7f1be8151a60a22c2017-12-0833.472483126.933529공항/터미널/대합실002020-12-15
66042017-01-03서귀포시송산동68f7572914e4499a19c96f9d37e69f8e996f6304019d677a9a505791f94034082019-11-1933.246549126.556824관광지002020-12-15
일자시도명읍면동명맥주소개통일위도경도카테고리서비스 사용시간사용 횟수데이터기준일자
436492017-01-17제주시이도2동f50ca6a6fba87e68e848d65b0244bfaa9df059abb810de8a8b0582ff03bedff62017-11-1533.491703126.520286전기차충전소002020-12-15
176542017-01-07제주시조천읍c163ff208f3bd23b5732ab21648dc606a6c900a9049e7a0afe73adc43f80e53a2017-12-1333.443945126.664925관광지002020-12-15
40502017-01-02제주시도두동d2c0997a9fa4ec04a5f4c18a6e3f1a05cb78768cee29c0681e99b97ef4c934d12020-04-0833.504969126.46674공원002020-12-15
538242017-01-20제주시아라동d6c6312d0babc184cd23f069b117c0951cce5dc20a3e63ec22fec6137666b0472017-11-2333.445271126.560145의료시설002020-12-15
98612017-01-04서귀포시남원읍681aadba338e3e4e9ad8968faae99f8c80de28b761e5c748c58a662f45d610332017-10-3033.277861126.705268전기차충전소002020-12-15
120922017-01-05서귀포시천지동507737113ef1d78329ba8ec376c3187d44218e7da06c457db9e17efe4d104ed12017-08-3033.242155126.566953테마거리002020-12-15
54252017-01-03서귀포시성산읍50c8273a702dd408977b43994af73ddc36c60ad7ceecfa8b410f2b12e708322c2017-08-1433.423688126.929771관광지002020-12-15
290542017-01-11서귀포시정방동8b4b5a30e2a7da46ee293585647ef06b90ce61caa6da01dd38cb52bd13add6d32019-06-2033.247685126.565855전기차충전소002020-12-15
330682017-01-13제주시삼양동f494e0f2fb52097b7fac3c8d223b912404cd63f3f95e1657c120c2f266c9d6142019-06-2633.529311126.592588버스정류소002020-12-15
297412017-01-11제주시구좌읍9b18abb3d640c03f79ebf6c34e92cc8def1a4934873562dc35f60fa12de583662017-10-2433.556414126.761678전기차충전소002020-12-15