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

DateTime3
Categorical3
Text1
Numeric4

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

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
서비스 사용시간 is highly overall correlated with 사용 횟수High correlation
사용 횟수 is highly overall correlated with 서비스 사용시간High correlation
서비스 사용시간 has 5831 (58.3%) zerosZeros
사용 횟수 has 5831 (58.3%) zerosZeros

Reproduction

Analysis started2023-12-11 19:29:44.364017
Analysis finished2023-12-11 19:29:48.387821
Duration4.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-01-01 00:00:00
Maximum2019-01-24 00:00:00
2023-12-12T04:29:48.456518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:48.596916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
5414 
서귀포시
4586 

Length

Max length4
Median length3
Mean length3.4586
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 5414
54.1%
서귀포시 4586
45.9%

Length

2023-12-12T04:29:48.746424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:29:48.877898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 5414
54.1%
서귀포시 4586
45.9%

읍면동명
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
성산읍
 
534
천지동
 
528
송산동
 
519
조천읍
 
436
구좌읍
 
376
Other values (44)
7607 

Length

Max length4
Median length3
Mean length3.1003
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한림읍
2nd row조천읍
3rd row이도1동
4th row성산읍
5th row성산읍

Common Values

ValueCountFrequency (%)
성산읍 534
 
5.3%
천지동 528
 
5.3%
송산동 519
 
5.2%
조천읍 436
 
4.4%
구좌읍 376
 
3.8%
봉개동 371
 
3.7%
애월읍 362
 
3.6%
노형동 354
 
3.5%
남원읍 343
 
3.4%
중앙동 330
 
3.3%
Other values (39) 5847
58.5%

Length

2023-12-12T04:29:48.979507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성산읍 534
 
5.3%
천지동 528
 
5.3%
송산동 519
 
5.2%
조천읍 436
 
4.4%
구좌읍 376
 
3.8%
봉개동 371
 
3.7%
애월읍 362
 
3.6%
노형동 354
 
3.5%
남원읍 343
 
3.4%
중앙동 330
 
3.3%
Other values (39) 5847
58.5%

맥주소
Text

Distinct2260
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T04:29:49.273510image/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

Unique184 ?
Unique (%)1.8%

Sample

1st rowe283c08bfc633c84a717109719fff3d8d07d506749ce8216078a283df4672de1
2nd row74f177d96ffe36bc04cc397a51f4ded4e7e534b572d2afcb96d487bfadcd228e
3rd rowc0bfe04aae6761bd6ce582f2cec3852680e07f211a12fcb91d7a57cb40cc034f
4th rowe662f7411c0f447cac309416f6c064137f45758c4e3211698c1a679004922bf5
5th row2001ca23cdfa889e33c45033a926229ea9a97fc310f74b40e85b03c499e06774
ValueCountFrequency (%)
c8dcc32977e4e6b10ca85864365b4119d2035e6b0ac7c3ea0099553c0e0226c9 30
 
0.3%
f4d46b85de3205cf8ae81676348d25ed2cb23995abb25afb775641e33f619e01 21
 
0.2%
345ffe27527df917cfe41636009d361e362247dda8d7fb1473fda88423d76325 21
 
0.2%
7f86ca2d5e165f62a60fa7760b7ec826712f358b9af78dcbf9b084dc8e0ee931 21
 
0.2%
1ba16b33ed29206cf29950b8586dc90674e04701e29b2e2cd127dd9f06e254c6 21
 
0.2%
949a573dc2ac1090c30918dd159b4bcba6672d894a5e33d53bec0f6e674efb7d 21
 
0.2%
c6f80221071453fad1c882ae5456d6eb035527c1035e6bf70e1041cb65a0bb79 20
 
0.2%
060cb9fd667e67cc11f3047edc32716f7a630f918055e5828d316cb78d7794d3 20
 
0.2%
83dc393e25cbc6ee683b536df45837199df86264ad701832bd5a00631ae8471c 20
 
0.2%
1a413f41f6df4f24fefd1f563fb21e33f96f4dca0d1be3c6d444be1a3b356ed2 20
 
0.2%
Other values (2250) 9785
97.9%
2023-12-12T04:29:49.663636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 40973
 
6.4%
6 40867
 
6.4%
7 40696
 
6.4%
f 40624
 
6.3%
4 40411
 
6.3%
e 40103
 
6.3%
a 39894
 
6.2%
d 39889
 
6.2%
0 39814
 
6.2%
1 39793
 
6.2%
Other values (6) 236936
37.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400671
62.6%
Lowercase Letter 239329
37.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 40973
10.2%
6 40867
10.2%
7 40696
10.2%
4 40411
10.1%
0 39814
9.9%
1 39793
9.9%
9 39559
9.9%
8 39542
9.9%
5 39536
9.9%
2 39480
9.9%
Lowercase Letter
ValueCountFrequency (%)
f 40624
17.0%
e 40103
16.8%
a 39894
16.7%
d 39889
16.7%
c 39549
16.5%
b 39270
16.4%

Most occurring scripts

ValueCountFrequency (%)
Common 400671
62.6%
Latin 239329
37.4%

Most frequent character per script

Common
ValueCountFrequency (%)
3 40973
10.2%
6 40867
10.2%
7 40696
10.2%
4 40411
10.1%
0 39814
9.9%
1 39793
9.9%
9 39559
9.9%
8 39542
9.9%
5 39536
9.9%
2 39480
9.9%
Latin
ValueCountFrequency (%)
f 40624
17.0%
e 40103
16.8%
a 39894
16.7%
d 39889
16.7%
c 39549
16.5%
b 39270
16.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 640000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 40973
 
6.4%
6 40867
 
6.4%
7 40696
 
6.4%
f 40624
 
6.3%
4 40411
 
6.3%
e 40103
 
6.3%
a 39894
 
6.2%
d 39889
 
6.2%
0 39814
 
6.2%
1 39793
 
6.2%
Other values (6) 236936
37.0%

개통일
Date

Distinct242
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-07-19 00:00:00
Maximum2020-04-27 00:00:00
2023-12-12T04:29:49.804002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:49.941517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1512
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.389815
Minimum33.166454
Maximum33.559583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:50.079743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.166454
5-th percentile33.240385
Q133.254129
median33.434112
Q333.49675
95-th percentile33.526807
Maximum33.559583
Range0.393129
Interquartile range (IQR)0.242621

Descriptive statistics

Standard deviation0.11438286
Coefficient of variation (CV)0.0034256813
Kurtosis-1.6603967
Mean33.389815
Median Absolute Deviation (MAD)0.0838785
Skewness-0.19226278
Sum333898.15
Variance0.013083439
MonotonicityNot monotonic
2023-12-12T04:29:50.225107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.437048 57
 
0.6%
33.248697 57
 
0.6%
33.247744 54
 
0.5%
33.243868 50
 
0.5%
33.244669 46
 
0.5%
33.249836 46
 
0.5%
33.511806 44
 
0.4%
33.246184 42
 
0.4%
33.2495 42
 
0.4%
33.249299 39
 
0.4%
Other values (1502) 9523
95.2%
ValueCountFrequency (%)
33.166453999999995 9
0.1%
33.199104 9
0.1%
33.205119 3
 
< 0.1%
33.2059 2
 
< 0.1%
33.205906 5
0.1%
33.206792 4
< 0.1%
33.207068 6
0.1%
33.208525 2
 
< 0.1%
33.208902 4
< 0.1%
33.209822 3
 
< 0.1%
ValueCountFrequency (%)
33.559583 6
0.1%
33.558634999999995 14
0.1%
33.557889 5
 
0.1%
33.557666 7
0.1%
33.55761 8
0.1%
33.557227000000005 12
0.1%
33.557167 4
 
< 0.1%
33.556926000000004 8
0.1%
33.556553 5
 
0.1%
33.556414000000004 4
 
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1521
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.55736
Minimum126.16361
Maximum126.96873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:50.385505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16361
5-th percentile126.25904
Q1126.49127
median126.55407
Q3126.60844
95-th percentile126.90835
Maximum126.96873
Range0.805128
Interquartile range (IQR)0.117174

Descriptive statistics

Standard deviation0.16357196
Coefficient of variation (CV)0.0012924729
Kurtosis0.50975136
Mean126.55736
Median Absolute Deviation (MAD)0.062189
Skewness0.28654174
Sum1265573.6
Variance0.026755785
MonotonicityNot monotonic
2023-12-12T04:29:50.536443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.628152 57
 
0.6%
126.564107 57
 
0.6%
126.5603 54
 
0.5%
126.569025 50
 
0.5%
126.559971 46
 
0.5%
126.526056 44
 
0.4%
126.56658600000002 42
 
0.4%
126.557365 42
 
0.4%
126.560763 39
 
0.4%
126.564645 38
 
0.4%
Other values (1511) 9531
95.3%
ValueCountFrequency (%)
126.163606 8
0.1%
126.163778 4
< 0.1%
126.164197 2
 
< 0.1%
126.165759 6
0.1%
126.166233 2
 
< 0.1%
126.166301 4
< 0.1%
126.166819 5
0.1%
126.167783 5
0.1%
126.168003 5
0.1%
126.171035 6
0.1%
ValueCountFrequency (%)
126.968734 13
0.1%
126.967512 4
 
< 0.1%
126.967145 9
0.1%
126.9658 3
 
< 0.1%
126.965055 3
 
< 0.1%
126.964697 9
0.1%
126.963074 4
 
< 0.1%
126.959746 12
0.1%
126.959703 4
 
< 0.1%
126.959575 7
0.1%

카테고리
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
버스정류소
2388 
관광지
1932 
전기차충전소
973 
올레코스
911 
공원
890 
Other values (15)
2906 

Length

Max length13
Median length10
Mean length4.1006
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관광지
2nd row올레코스
3rd row전통시장
4th row공공기관
5th row공공기관

Common Values

ValueCountFrequency (%)
버스정류소 2388
23.9%
관광지 1932
19.3%
전기차충전소 973
9.7%
올레코스 911
 
9.1%
공원 890
 
8.9%
테마거리 869
 
8.7%
해변 448
 
4.5%
전통시장 422
 
4.2%
공공기관 252
 
2.5%
정류소 236
 
2.4%
Other values (10) 679
 
6.8%

Length

2023-12-12T04:29:50.700315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
버스정류소 2388
23.7%
관광지 1932
19.2%
전기차충전소 973
9.7%
올레코스 911
 
9.0%
공원 890
 
8.8%
테마거리 869
 
8.6%
해변 448
 
4.4%
전통시장 422
 
4.2%
공공기관 252
 
2.5%
정류소 236
 
2.3%
Other values (10) 760
 
7.5%

서비스 사용시간
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4139
Distinct (%)41.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79956.013
Minimum0
Maximum5088607
Zeros5831
Zeros (%)58.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:50.855819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q355336
95-th percentile368643.55
Maximum5088607
Range5088607
Interquartile range (IQR)55336

Descriptive statistics

Standard deviation252214.88
Coefficient of variation (CV)3.1544204
Kurtosis96.111724
Mean79956.013
Median Absolute Deviation (MAD)0
Skewness8.0220438
Sum7.9956013 × 108
Variance6.3612344 × 1010
MonotonicityNot monotonic
2023-12-12T04:29:50.992707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5831
58.3%
22 3
 
< 0.1%
3 2
 
< 0.1%
36481 2
 
< 0.1%
25946 2
 
< 0.1%
407 2
 
< 0.1%
90525 2
 
< 0.1%
346 2
 
< 0.1%
43082 2
 
< 0.1%
26 2
 
< 0.1%
Other values (4129) 4150
41.5%
ValueCountFrequency (%)
0 5831
58.3%
1 1
 
< 0.1%
3 2
 
< 0.1%
4 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
13 1
 
< 0.1%
15 1
 
< 0.1%
22 3
 
< 0.1%
26 2
 
< 0.1%
ValueCountFrequency (%)
5088607 1
< 0.1%
4635868 1
< 0.1%
4485733 1
< 0.1%
4277778 1
< 0.1%
4187764 1
< 0.1%
4172933 1
< 0.1%
3974897 1
< 0.1%
3500633 1
< 0.1%
3304207 1
< 0.1%
3164100 1
< 0.1%

사용 횟수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1010
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.2774
Minimum0
Maximum3402
Zeros5831
Zeros (%)58.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:29:51.329442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3114
95-th percentile661.05
Maximum3402
Range3402
Interquartile range (IQR)114

Descriptive statistics

Standard deviation286.50028
Coefficient of variation (CV)2.3053289
Kurtosis25.099913
Mean124.2774
Median Absolute Deviation (MAD)0
Skewness4.1913953
Sum1242774
Variance82082.411
MonotonicityNot monotonic
2023-12-12T04:29:51.480458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5831
58.3%
1 43
 
0.4%
4 33
 
0.3%
14 31
 
0.3%
12 29
 
0.3%
21 28
 
0.3%
37 28
 
0.3%
10 27
 
0.3%
16 27
 
0.3%
45 27
 
0.3%
Other values (1000) 3896
39.0%
ValueCountFrequency (%)
0 5831
58.3%
1 43
 
0.4%
2 25
 
0.2%
3 17
 
0.2%
4 33
 
0.3%
5 24
 
0.2%
6 24
 
0.2%
7 23
 
0.2%
8 24
 
0.2%
9 19
 
0.2%
ValueCountFrequency (%)
3402 1
< 0.1%
3350 1
< 0.1%
3349 1
< 0.1%
3285 1
< 0.1%
3168 1
< 0.1%
3027 1
< 0.1%
2947 1
< 0.1%
2881 1
< 0.1%
2783 1
< 0.1%
2776 1
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-12-15 00:00:00
Maximum2020-12-15 00:00:00
2023-12-12T04:29:51.595449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:51.675142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T04:29:47.415499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:45.711645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.288724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.860838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.571683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:45.826981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.432527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.021063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.747040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:45.999339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.566068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.153774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.869966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.157123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:46.707768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:29:47.287067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:29:51.747778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자시도명읍면동명위도경도카테고리서비스 사용시간사용 횟수
일자1.0000.0000.0000.0000.0000.0000.1100.000
시도명0.0001.0001.0000.9770.2630.3470.1740.110
읍면동명0.0001.0001.0000.9130.9600.7780.2250.372
위도0.0000.9770.9131.0000.7760.6330.1710.241
경도0.0000.2630.9600.7761.0000.5780.1160.200
카테고리0.0000.3470.7780.6330.5781.0000.2600.398
서비스 사용시간0.1100.1740.2250.1710.1160.2601.0000.537
사용 횟수0.0000.1100.3720.2410.2000.3980.5371.000
2023-12-12T04:29:51.865301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카테고리시도명읍면동명
카테고리1.0000.2740.298
시도명0.2741.0000.998
읍면동명0.2980.9981.000
2023-12-12T04:29:51.968022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도서비스 사용시간사용 횟수시도명읍면동명카테고리
위도1.0000.1090.1950.1770.8690.6090.251
경도0.1091.000-0.097-0.0860.2020.7520.219
서비스 사용시간0.195-0.0971.0000.9820.1340.0780.085
사용 횟수0.177-0.0860.9821.0000.0840.1350.136
시도명0.8690.2020.1340.0841.0000.9980.274
읍면동명0.6090.7520.0780.1350.9981.0000.298
카테고리0.2510.2190.0850.1360.2740.2981.000

Missing values

2023-12-12T04:29:48.050251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:29:48.274577image/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
501562019-01-19제주시한림읍e283c08bfc633c84a717109719fff3d8d07d506749ce8216078a283df4672de12017-09-0433.389694126.239639관광지2852142020-12-15
615452019-01-23제주시조천읍74f177d96ffe36bc04cc397a51f4ded4e7e534b572d2afcb96d487bfadcd228e2019-07-3133.535756126.633095올레코스002020-12-15
253182019-01-10제주시이도1동c0bfe04aae6761bd6ce582f2cec3852680e07f211a12fcb91d7a57cb40cc034f2017-08-2333.511806126.526056전통시장1520264832020-12-15
513152019-01-19서귀포시성산읍e662f7411c0f447cac309416f6c064137f45758c4e3211698c1a679004922bf52018-10-3033.442917126.910982공공기관714341102020-12-15
296452019-01-11서귀포시성산읍2001ca23cdfa889e33c45033a926229ea9a97fc310f74b40e85b03c499e067742018-10-3033.442917126.910982공공기관486672122020-12-15
581122019-01-22서귀포시송산동1ba16b33ed29206cf29950b8586dc90674e04701e29b2e2cd127dd9f06e254c62018-05-1433.248491126.559383테마거리002020-12-15
627422019-01-24서귀포시남원읍cb846a036f30af8a758ae65570e9e5c0b94920a82d5781e49028d0e5bbdbe8a02019-09-1933.279254126.730558올레코스002020-12-15
2302019-01-01제주시아라동a9f260a70589ffbcb5b6c58bd4717c3565d31e2193e12fb88f56fefbbcb922922018-05-0333.460553126.561891버스정류소1840773932020-12-15
461172019-01-18서귀포시안덕면c4d3e1d73a2229a3aed64523870e92108481036dbb07dae835b3bd6f0601fb082017-08-1433.289146126.37011관광지810871522020-12-15
227982019-01-09제주시구좌읍3f22057a04717f935aed77cb42ee8615e66e1d83855bdc073fddbd6e906e22242019-06-1533.550461126.750545전기차충전소002020-12-15
일자시도명읍면동명맥주소개통일위도경도카테고리서비스 사용시간사용 횟수데이터기준일자
93032019-01-04서귀포시표선면25cb7804c3e1bf6dff92387d4240a4c8028e0915e6c7e9c6f10109882d33a5272019-06-2533.323283126.831517버스정류소002020-12-15
584612019-01-22서귀포시송산동18c297917620bd124b10406370818a0baba5bff05288515c09528f0956ea935b2019-10-2033.239544126.563564테마거리002020-12-15
422742019-01-16제주시용담2동c47c4690696781ba175932a63af582bce0abc98a6772b2c34e3f0e262d35fd282018-04-0333.513061126.506439버스정류소002020-12-15
78532019-01-03제주시한림읍6837a7634eb482fc0d1daa54e1d3c37ae944d34db55c32e2e03764d24c862cd62017-09-0533.347944126.356806관광지31352662020-12-15
507732019-01-19서귀포시대정읍17d874dd1d49f07aa9b9a8ddf087b7d2bd660d3b03d7203548eac77658e5500a2019-07-1833.226474126.247864공원002020-12-15
520302019-01-20제주시연동326da3479ec7e58163da603e806de44c14f19c3764b347545dcd074f43a8c9aa2019-07-1733.491432126.489119버스정류소002020-12-15
24292019-01-01서귀포시송산동c9bcdcde091f2d75fb6c8c40f95f8c2a7127184120a370bcafbd661004a145cd2017-10-2733.24997126.563154전기차충전소002020-12-15
210092019-01-08서귀포시예래동08a4dbf2ddceba6a7982a1d28fe0d3f2f19b0122716faaf8ad401d3812bf260e2017-08-3133.244447126.416191관광지002020-12-15
265132019-01-10제주시삼양동7d5a4d050f9b20b3ff303c1cb71fdcf3bd4354d19049d6a1375693cffe4a32402019-10-2033.520215126.584185공원002020-12-15
62012019-01-03제주시한림읍8b2137514768f6b5b3eec9e532e07dc9e0a1d59424d0d8b24340a06004a6c52c2017-11-1033.338473126.269308전기차충전소26982392020-12-15