Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells5
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory89.5 B

Variable types

Numeric4
Text2
Categorical2
Boolean2

Dataset

Description칠머리당터와건입동벽화거리의 위치와 관련된 정보로 위도, 경도, 구분, 설명, 포인트, 추천 코스 등의 정보를 제공합니다.
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/1092

Alerts

전체코스여부 has constant value ""Constant
추천코스여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
순서 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 순서 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 순서 and 2 other fieldsHigh correlation
포인트 is highly overall correlated with 순서 and 3 other fieldsHigh correlation
상세정보 is highly overall correlated with 순서 and 3 other fieldsHigh correlation
설명 has 5 (20.8%) missing valuesMissing
순서 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
포인트 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:51:39.125525
Analysis finished2023-12-11 19:51:45.251862
Duration6.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순서
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
2023-12-12T04:51:45.363620image/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
2023-12-12T04:51:45.592114image/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%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.518252
Minimum33.517682
Maximum33.518792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T04:51:45.800563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.517682
5-th percentile33.517797
Q133.517899
median33.518202
Q333.518639
95-th percentile33.518768
Maximum33.518792
Range0.00111002
Interquartile range (IQR)0.000740275

Descriptive statistics

Standard deviation0.00036891458
Coefficient of variation (CV)1.1006379 × 10-5
Kurtosis-1.4936899
Mean33.518252
Median Absolute Deviation (MAD)0.000349485
Skewness0.149179
Sum804.43806
Variance1.3609797 × 10-7
MonotonicityNot monotonic
2023-12-12T04:51:46.010195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
33.51832797 1
 
4.2%
33.51805698 1
 
4.2%
33.51863299 1
 
4.2%
33.51845202 1
 
4.2%
33.51785104 1
 
4.2%
33.517845 1
 
4.2%
33.51785397 1
 
4.2%
33.51778801 1
 
4.2%
33.51791197 1
 
4.2%
33.51817802 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
33.51768197 1
4.2%
33.51778801 1
4.2%
33.517845 1
4.2%
33.51785104 1
4.2%
33.51785397 1
4.2%
33.517859 1
4.2%
33.51791197 1
4.2%
33.51802597 1
4.2%
33.51805103 1
4.2%
33.51805698 1
4.2%
ValueCountFrequency (%)
33.51879199 1
4.2%
33.51877296 1
4.2%
33.51873701 1
4.2%
33.51872804 1
4.2%
33.51868697 1
4.2%
33.51865704 1
4.2%
33.51863299 1
4.2%
33.51858797 1
4.2%
33.51845202 1
4.2%
33.51832797 1
4.2%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.53683
Minimum126.53567
Maximum126.53909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T04:51:46.214658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53567
5-th percentile126.53572
Q1126.53616
median126.53636
Q3126.53744
95-th percentile126.53869
Maximum126.53909
Range0.003412
Interquartile range (IQR)0.0012755

Descriptive statistics

Standard deviation0.0010389575
Coefficient of variation (CV)8.2107118 × 10-6
Kurtosis-0.33746515
Mean126.53683
Median Absolute Deviation (MAD)0.0004875
Skewness0.96788653
Sum3036.884
Variance1.0794326 × 10-6
MonotonicityNot monotonic
2023-12-12T04:51:46.421150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
126.536078 1
 
4.2%
126.537309 1
 
4.2%
126.536208 1
 
4.2%
126.536371 1
 
4.2%
126.536357 1
 
4.2%
126.537174 1
 
4.2%
126.537814 1
 
4.2%
126.538363 1
 
4.2%
126.538696 1
 
4.2%
126.539085 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
126.535673 1
4.2%
126.535704 1
4.2%
126.535812 1
4.2%
126.535874 1
4.2%
126.536077 1
4.2%
126.536078 1
4.2%
126.536187 1
4.2%
126.536194 1
4.2%
126.536208 1
4.2%
126.536324 1
4.2%
ValueCountFrequency (%)
126.539085 1
4.2%
126.538696 1
4.2%
126.538681 1
4.2%
126.538363 1
4.2%
126.537857 1
4.2%
126.537814 1
4.2%
126.537309 1
4.2%
126.537174 1
4.2%
126.536849 1
4.2%
126.536571 1
4.2%

구분
Text

Distinct14
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T04:51:46.670855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.5
Min length2

Characters and Unicode

Total characters180
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)41.7%

Sample

1st row주차장
2nd row오르막 시작점
3rd row오르막 끝지점(내리막 시작점)
4th row내리막 끝지점
5th row보도블럭길 시작점
ValueCountFrequency (%)
시작점 11
23.9%
오르막 8
17.4%
내리막 7
15.2%
끝지점 6
13.0%
끝지점(내리막 3
 
6.5%
보도블럭길 2
 
4.3%
주차장 1
 
2.2%
배수구 1
 
2.2%
입항로 1
 
2.2%
내려가는 1
 
2.2%
Other values (5) 5
10.9%
2023-12-12T04:51:47.101506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
12.2%
점 20
11.1%
막 18
 
10.0%
시 11
 
6.1%
작 11
 
6.1%
내 11
 
6.1%
리 11
 
6.1%
오 9
 
5.0%
끝 9
 
5.0%
지 9
 
5.0%
Other values (30) 49
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
84.4%
Space Separator 22
 
12.2%
Close Punctuation 3
 
1.7%
Open Punctuation 3
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 20
13.2%
막 18
11.8%
시 11
 
7.2%
작 11
 
7.2%
내 11
 
7.2%
리 11
 
7.2%
오 9
 
5.9%
끝 9
 
5.9%
지 9
 
5.9%
르 8
 
5.3%
Other values (27) 35
23.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
84.4%
Common 28
 
15.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 20
13.2%
막 18
11.8%
시 11
 
7.2%
작 11
 
7.2%
내 11
 
7.2%
리 11
 
7.2%
오 9
 
5.9%
끝 9
 
5.9%
지 9
 
5.9%
르 8
 
5.3%
Other values (27) 35
23.0%
Common
ValueCountFrequency (%)
22
78.6%
) 3
 
10.7%
( 3
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
84.4%
ASCII 28
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
78.6%
) 3
 
10.7%
( 3
 
10.7%
Hangul
ValueCountFrequency (%)
점 20
13.2%
막 18
11.8%
시 11
 
7.2%
작 11
 
7.2%
내 11
 
7.2%
리 11
 
7.2%
오 9
 
5.9%
끝 9
 
5.9%
지 9
 
5.9%
르 8
 
5.3%
Other values (27) 35
23.0%

설명
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing5
Missing (%)20.8%
Memory size324.0 B
2023-12-12T04:51:47.394768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length12
Mean length10.473684
Min length2

Characters and Unicode

Total characters199
Distinct characters81
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

Unique19 ?
Unique (%)100.0%

Sample

1st row장애인주차구역 3개
2nd row6~13도. 15cm
3rd row칠머리당터 소공원 입구
4th row6~15도. 소공원 내 정자
5th row도로폭 좁아짐(91cm). 뷰 포인트
ValueCountFrequency (%)
뷰 3
 
6.0%
소공원 2
 
4.0%
4~7도 2
 
4.0%
우측 2
 
4.0%
단차 2
 
4.0%
장애인주차구역 1
 
2.0%
18코스 1
 
2.0%
굿 1
 
2.0%
백록 1
 
2.0%
소원 1
 
2.0%
Other values (34) 34
68.0%
2023-12-12T04:51:47.838565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
15.6%
. 12
 
6.0%
도 9
 
4.5%
~ 7
 
3.5%
m 7
 
3.5%
5 7
 
3.5%
1 6
 
3.0%
4 5
 
2.5%
7 4
 
2.0%
c 4
 
2.0%
Other values (71) 107
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100
50.3%
Decimal Number 34
 
17.1%
Space Separator 31
 
15.6%
Other Punctuation 12
 
6.0%
Lowercase Letter 11
 
5.5%
Math Symbol 7
 
3.5%
Close Punctuation 2
 
1.0%
Open Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 9
 
9.0%
차 3
 
3.0%
리 3
 
3.0%
인 3
 
3.0%
소 3
 
3.0%
뷰 3
 
3.0%
원 3
 
3.0%
단 3
 
3.0%
장 2
 
2.0%
포 2
 
2.0%
Other values (55) 66
66.0%
Decimal Number
ValueCountFrequency (%)
5 7
20.6%
1 6
17.6%
4 5
14.7%
7 4
11.8%
2 4
11.8%
3 3
8.8%
9 2
 
5.9%
6 2
 
5.9%
8 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
m 7
63.6%
c 4
36.4%
Space Separator
ValueCountFrequency (%)
31
100.0%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100
50.3%
Common 88
44.2%
Latin 11
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 9
 
9.0%
차 3
 
3.0%
리 3
 
3.0%
인 3
 
3.0%
소 3
 
3.0%
뷰 3
 
3.0%
원 3
 
3.0%
단 3
 
3.0%
장 2
 
2.0%
포 2
 
2.0%
Other values (55) 66
66.0%
Common
ValueCountFrequency (%)
31
35.2%
. 12
 
13.6%
~ 7
 
8.0%
5 7
 
8.0%
1 6
 
6.8%
4 5
 
5.7%
7 4
 
4.5%
2 4
 
4.5%
3 3
 
3.4%
) 2
 
2.3%
Other values (4) 7
 
8.0%
Latin
ValueCountFrequency (%)
m 7
63.6%
c 4
36.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100
50.3%
ASCII 99
49.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
31.3%
. 12
 
12.1%
~ 7
 
7.1%
m 7
 
7.1%
5 7
 
7.1%
1 6
 
6.1%
4 5
 
5.1%
7 4
 
4.0%
c 4
 
4.0%
2 4
 
4.0%
Other values (6) 12
 
12.1%
Hangul
ValueCountFrequency (%)
도 9
 
9.0%
차 3
 
3.0%
리 3
 
3.0%
인 3
 
3.0%
소 3
 
3.0%
뷰 3
 
3.0%
원 3
 
3.0%
단 3
 
3.0%
장 2
 
2.0%
포 2
 
2.0%
Other values (55) 66
66.0%

포인트
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
2023-12-12T04:51:48.044200image/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
2023-12-12T04:51:48.199995image/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%

상세정보
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
접근성정보(*계단. 길 상태. 경사) 있음
19 
<NA>
5 

Length

Max length23
Median length23
Mean length19.041667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row접근성정보(*계단. 길 상태. 경사) 있음
3rd row<NA>
4th row접근성정보(*계단. 길 상태. 경사) 있음
5th row접근성정보(*계단. 길 상태. 경사) 있음

Common Values

ValueCountFrequency (%)
접근성정보(*계단. 길 상태. 경사) 있음 19
79.2%
<NA> 5
 
20.8%

Length

2023-12-12T04:51:48.389093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:51:48.554950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
접근성정보(*계단 19
19.0%
길 19
19.0%
상태 19
19.0%
경사 19
19.0%
있음 19
19.0%
na 5
 
5.0%

전체코스여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.0 B
True
24 
ValueCountFrequency (%)
True 24
100.0%
2023-12-12T04:51:48.671098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

추천코스여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size156.0 B
True
24 
ValueCountFrequency (%)
True 24
100.0%
2023-12-12T04:51:48.807439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2021-12-22
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-12-22
2nd row2021-12-22
3rd row2021-12-22
4th row2021-12-22
5th row2021-12-22

Common Values

ValueCountFrequency (%)
2021-12-22 24
100.0%

Length

2023-12-12T04:51:48.945864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:51:49.062230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-22 24
100.0%

Interactions

2023-12-12T04:51:44.236405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:42.264247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:42.982753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.602273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:44.379551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:42.501652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.140491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.764856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:44.530773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:42.702843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.286967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.926013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:44.692606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:42.863784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:43.452703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:51:44.089633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:51:49.134415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서위도경도구분설명포인트
순서1.0000.7290.7720.5311.0001.000
위도0.7291.0000.6650.6111.0000.729
경도0.7720.6651.0000.6021.0000.772
구분0.5310.6110.6021.0001.0000.531
설명1.0001.0001.0001.0001.0001.000
포인트1.0000.7290.7720.5311.0001.000
2023-12-12T04:51:49.286150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서위도경도포인트상세정보
순서1.000-0.5560.5971.0001.000
위도-0.5561.000-0.463-0.5561.000
경도0.597-0.4631.0000.5971.000
포인트1.000-0.5560.5971.0001.000
상세정보1.0001.0001.0001.0001.000

Missing values

2023-12-12T04:51:44.899297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:51:45.155751image/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

순서위도경도구분설명포인트상세정보전체코스여부추천코스여부데이터기준일자
0133.518328126.536078주차장장애인주차구역 3개1<NA>YY2021-12-22
1233.518657126.536194오르막 시작점6~13도. 15cm2접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
2333.518588126.536324오르막 끝지점(내리막 시작점)칠머리당터 소공원 입구3<NA>YY2021-12-22
3433.518737126.536341내리막 끝지점6~15도. 소공원 내 정자4접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
4533.518792126.536187보도블럭길 시작점도로폭 좁아짐(91cm). 뷰 포인트5접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
5633.518773126.536077배수구작은 단차. 칠머리당 영등굿 장면 그림6<NA>YY2021-12-22
6733.518728126.535874보도블럭길 끝지점단차 5cm7접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
7833.518687126.535812입항로 내려가는 길계단 앞8접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
8933.518226126.535673오르막 시작점4~7도9접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
91033.517682126.535704오르막 끝지점(내리막 시작점)<NA>10접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
순서위도경도구분설명포인트상세정보전체코스여부추천코스여부데이터기준일자
141533.518121126.537857안전비상벨우측15접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
151633.518232126.538681오르막 시작점4~7도. 35cm16접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
161733.518178126.539085오르막 끝지점뷰 포인트(제주항 뷰). 건입동 올레 18코스 간판17<NA>YY2021-12-22
171833.517912126.538696횡단보도<NA>18접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
181933.517788126.538363내리막 시작점4~5도. 52m. 하버호텔19접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
192033.517854126.537814내리막 끝지점<NA>20접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
202133.517845126.537174내리막 시작점2~7도. 74m21접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
212233.517851126.536357내리막 끝지점오거리22접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
222333.518452126.536371내리막 시작점14도. 25m23접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
232433.518633126.536208내리막 끝지점<NA>24접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22