Overview

Dataset statistics

Number of variables10
Number of observations26
Missing cells8
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory89.1 B

Variable types

Numeric4
Text2
Categorical2
Boolean2

Dataset

Description대문없는마을상명정낭마을의 위치와 관련된 정보로 위도, 경도, 구분, 설명, 포인트, 추천 코스 등의 정보를 제공합니다.
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/1060

Alerts

전체코스여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
상세정보 is highly overall correlated with 순서 and 4 other fieldsHigh correlation
추천코스여부 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
순서 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
위도 is highly overall correlated with 순서 and 3 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
포인트 is highly overall correlated with 순서 and 2 other fieldsHigh correlation
설명 has 8 (30.8%) missing valuesMissing
순서 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
포인트 has unique valuesUnique

Reproduction

Analysis started2023-12-11 19:43:18.795276
Analysis finished2023-12-11 19:43:21.789039
Duration2.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T04:43:21.895468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-12T04:43:22.117493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.359617
Minimum33.357739
Maximum33.362234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T04:43:22.339397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.357739
5-th percentile33.357773
Q133.358041
median33.359369
Q333.361281
95-th percentile33.36213
Maximum33.362234
Range0.00449496
Interquartile range (IQR)0.0032392925

Descriptive statistics

Standard deviation0.0016791033
Coefficient of variation (CV)5.0333411 × 10-5
Kurtosis-1.5675654
Mean33.359617
Median Absolute Deviation (MAD)0.001518965
Skewness0.34603509
Sum867.35005
Variance2.819388 × 10-6
MonotonicityNot monotonic
2023-12-12T04:43:22.986444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
33.35778904 1
 
3.8%
33.35968201 1
 
3.8%
33.357739 1
 
3.8%
33.35780103 1
 
3.8%
33.35814997 1
 
3.8%
33.35790002 1
 
3.8%
33.35806296 1
 
3.8%
33.35799297 1
 
3.8%
33.35803396 1
 
3.8%
33.35827997 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
33.357739 1
3.8%
33.357768 1
3.8%
33.35778904 1
3.8%
33.35780103 1
3.8%
33.35790002 1
3.8%
33.35799297 1
3.8%
33.35803396 1
3.8%
33.35806296 1
3.8%
33.35814997 1
3.8%
33.35827997 1
3.8%
ValueCountFrequency (%)
33.36223396 1
3.8%
33.36218099 1
3.8%
33.36197899 1
3.8%
33.361866 1
3.8%
33.36174698 1
3.8%
33.36163198 1
3.8%
33.361363 1
3.8%
33.36103301 1
3.8%
33.36100803 1
3.8%
33.36014 1
3.8%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.27186
Minimum126.26993
Maximum126.27429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T04:43:23.178394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.26993
5-th percentile126.27015
Q1126.27108
median126.27153
Q3126.27284
95-th percentile126.27406
Maximum126.27429
Range0.004364
Interquartile range (IQR)0.00175975

Descriptive statistics

Standard deviation0.0012588037
Coefficient of variation (CV)9.9689966 × 10-6
Kurtosis-0.75604609
Mean126.27186
Median Absolute Deviation (MAD)0.000865
Skewness0.5131693
Sum3283.0683
Variance1.5845868 × 10-6
MonotonicityNot monotonic
2023-12-12T04:43:23.358801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
126.274116 1
 
3.8%
126.27111 1
 
3.8%
126.274295 1
 
3.8%
126.273475 1
 
3.8%
126.273376 1
 
3.8%
126.273096 1
 
3.8%
126.272516 1
 
3.8%
126.271661 1
 
3.8%
126.271617 1
 
3.8%
126.271644 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
126.269931 1
3.8%
126.270044 1
3.8%
126.270458 1
3.8%
126.27052 1
3.8%
126.270786 1
3.8%
126.270823 1
3.8%
126.271076 1
3.8%
126.27111 1
3.8%
126.271223 1
3.8%
126.271229 1
3.8%
ValueCountFrequency (%)
126.274295 1
3.8%
126.274116 1
3.8%
126.273899 1
3.8%
126.273475 1
3.8%
126.273376 1
3.8%
126.273096 1
3.8%
126.272941 1
3.8%
126.272554 1
3.8%
126.272516 1
3.8%
126.271837 1
3.8%

구분
Text

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T04:43:23.616693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length10
Mean length7.7307692
Min length2

Characters and Unicode

Total characters201
Distinct characters86
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)84.6%

Sample

1st row주차장(상명정낭문화공간)
2nd row퐁낭
3rd row다육이 비닐하우스(담벼락위 다육이들)
4th row시멘트길 시작
5th row갈림길
ValueCountFrequency (%)
입구 4
 
7.8%
앞 3
 
5.9%
주차장(상명정낭문화공간 2
 
3.9%
소리소문 2
 
3.9%
책방 2
 
3.9%
퐁낭 2
 
3.9%
진입로 2
 
3.9%
정자 2
 
3.9%
끝 2
 
3.9%
오르막 2
 
3.9%
Other values (25) 28
54.9%
2023-12-12T04:43:24.067006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
12.4%
소 8
 
4.0%
입 6
 
3.0%
리 6
 
3.0%
( 5
 
2.5%
정 5
 
2.5%
낭 5
 
2.5%
) 5
 
2.5%
구 4
 
2.0%
길 4
 
2.0%
Other values (76) 128
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
81.6%
Space Separator 25
 
12.4%
Open Punctuation 5
 
2.5%
Close Punctuation 5
 
2.5%
Decimal Number 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 8
 
4.9%
입 6
 
3.7%
리 6
 
3.7%
정 5
 
3.0%
낭 5
 
3.0%
구 4
 
2.4%
길 4
 
2.4%
문 4
 
2.4%
단 4
 
2.4%
주 3
 
1.8%
Other values (71) 115
70.1%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
81.6%
Common 37
 
18.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 8
 
4.9%
입 6
 
3.7%
리 6
 
3.7%
정 5
 
3.0%
낭 5
 
3.0%
구 4
 
2.4%
길 4
 
2.4%
문 4
 
2.4%
단 4
 
2.4%
주 3
 
1.8%
Other values (71) 115
70.1%
Common
ValueCountFrequency (%)
25
67.6%
( 5
 
13.5%
) 5
 
13.5%
6 1
 
2.7%
1 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
81.6%
ASCII 37
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
67.6%
( 5
 
13.5%
) 5
 
13.5%
6 1
 
2.7%
1 1
 
2.7%
Hangul
ValueCountFrequency (%)
소 8
 
4.9%
입 6
 
3.7%
리 6
 
3.7%
정 5
 
3.0%
낭 5
 
3.0%
구 4
 
2.4%
길 4
 
2.4%
문 4
 
2.4%
단 4
 
2.4%
주 3
 
1.8%
Other values (71) 115
70.1%

설명
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing8
Missing (%)30.8%
Memory size340.0 B
2023-12-12T04:43:24.341764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length15
Mean length10.555556
Min length2

Characters and Unicode

Total characters190
Distinct characters88
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row장애인주차구역 없음
2nd row13~14구간 꽃길
3rd row계단 30개(비장애인 코스)
4th row양 옆 과수원길
5th row2º~5º
ValueCountFrequency (%)
있음 3
 
5.7%
코스 3
 
5.7%
옆 2
 
3.8%
통로 2
 
3.8%
넓이 2
 
3.8%
비장애인 2
 
3.8%
계단 2
 
3.8%
작은 1
 
1.9%
폭포 1
 
1.9%
없음 1
 
1.9%
Other values (34) 34
64.2%
2023-12-12T04:43:24.848032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
18.4%
길 6
 
3.2%
인 5
 
2.6%
음 5
 
2.6%
이 5
 
2.6%
애 4
 
2.1%
7 4
 
2.1%
있 4
 
2.1%
로 4
 
2.1%
장 4
 
2.1%
Other values (78) 114
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
65.8%
Space Separator 35
 
18.4%
Decimal Number 15
 
7.9%
Lowercase Letter 6
 
3.2%
Math Symbol 3
 
1.6%
Other Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%
Close Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 6
 
4.8%
인 5
 
4.0%
음 5
 
4.0%
이 5
 
4.0%
애 4
 
3.2%
있 4
 
3.2%
로 4
 
3.2%
장 4
 
3.2%
비 3
 
2.4%
구 3
 
2.4%
Other values (63) 82
65.6%
Decimal Number
ValueCountFrequency (%)
7 4
26.7%
6 2
13.3%
4 2
13.3%
3 2
13.3%
1 2
13.3%
0 1
 
6.7%
2 1
 
6.7%
5 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
m 3
50.0%
c 3
50.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
64.7%
Common 59
31.1%
Latin 8
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 6
 
4.9%
인 5
 
4.1%
음 5
 
4.1%
이 5
 
4.1%
애 4
 
3.3%
있 4
 
3.3%
로 4
 
3.3%
장 4
 
3.3%
비 3
 
2.4%
구 3
 
2.4%
Other values (62) 80
65.0%
Common
ValueCountFrequency (%)
35
59.3%
7 4
 
6.8%
~ 3
 
5.1%
. 2
 
3.4%
6 2
 
3.4%
( 2
 
3.4%
) 2
 
3.4%
4 2
 
3.4%
3 2
 
3.4%
1 2
 
3.4%
Other values (3) 3
 
5.1%
Latin
ValueCountFrequency (%)
m 3
37.5%
c 3
37.5%
º 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
64.7%
ASCII 65
34.2%
None 2
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
53.8%
7 4
 
6.2%
m 3
 
4.6%
c 3
 
4.6%
~ 3
 
4.6%
. 2
 
3.1%
6 2
 
3.1%
( 2
 
3.1%
) 2
 
3.1%
4 2
 
3.1%
Other values (5) 7
 
10.8%
Hangul
ValueCountFrequency (%)
길 6
 
4.9%
인 5
 
4.1%
음 5
 
4.1%
이 5
 
4.1%
애 4
 
3.3%
있 4
 
3.3%
로 4
 
3.3%
장 4
 
3.3%
비 3
 
2.4%
구 3
 
2.4%
Other values (62) 80
65.0%
None
ValueCountFrequency (%)
º 2
100.0%

포인트
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum12
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-12T04:43:25.016520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13.25
Q118.25
median24.5
Q330.75
95-th percentile35.75
Maximum37
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.31218487
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum637
Variance58.5
MonotonicityStrictly increasing
2023-12-12T04:43:25.185252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
12 1
 
3.8%
26 1
 
3.8%
37 1
 
3.8%
36 1
 
3.8%
35 1
 
3.8%
34 1
 
3.8%
33 1
 
3.8%
32 1
 
3.8%
31 1
 
3.8%
30 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
12 1
3.8%
13 1
3.8%
14 1
3.8%
15 1
3.8%
16 1
3.8%
17 1
3.8%
18 1
3.8%
19 1
3.8%
20 1
3.8%
21 1
3.8%
ValueCountFrequency (%)
37 1
3.8%
36 1
3.8%
35 1
3.8%
34 1
3.8%
33 1
3.8%
32 1
3.8%
31 1
3.8%
30 1
3.8%
29 1
3.8%
28 1
3.8%

상세정보
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
<NA>
13 
접근성정보(*계단. 길 상태. 경사) 있음
13 

Length

Max length23
Median length13.5
Mean length13.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 13
50.0%
접근성정보(*계단. 길 상태. 경사) 있음 13
50.0%

Length

2023-12-12T04:43:25.355680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:43:25.488538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
16.7%
접근성정보(*계단 13
16.7%
길 13
16.7%
상태 13
16.7%
경사 13
16.7%
있음 13
16.7%

전체코스여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size158.0 B
True
26 
ValueCountFrequency (%)
True 26
100.0%
2023-12-12T04:43:25.613174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

추천코스여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size158.0 B
True
23 
False
3 
ValueCountFrequency (%)
True 23
88.5%
False 3
 
11.5%
2023-12-12T04:43:25.714473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
2021-12-22
26 

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 26
100.0%

Length

2023-12-12T04:43:25.834080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:43:25.957469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-12-22 26
100.0%

Interactions

2023-12-12T04:43:20.920281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.252053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.762713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.405615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:21.033077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.354864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.964922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.536123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:21.147354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.485950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.113312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.664041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:21.283962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:19.612598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.266640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:43:20.800601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:43:26.070486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서위도경도구분설명포인트추천코스여부
순서1.0000.8260.7590.8920.9051.0000.621
위도0.8261.0000.4450.9791.0000.8260.000
경도0.7590.4451.0000.9550.7280.7591.000
구분0.8920.9790.9551.0000.9770.8921.000
설명0.9051.0000.7280.9771.0000.9050.000
포인트1.0000.8260.7590.8920.9051.0000.621
추천코스여부0.6210.0001.0001.0000.0000.6211.000
2023-12-12T04:43:26.217869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세정보추천코스여부
상세정보1.0001.000
추천코스여부1.0001.000
2023-12-12T04:43:26.326362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순서위도경도포인트상세정보추천코스여부
순서1.000-0.5660.1821.0001.0000.457
위도-0.5661.000-0.634-0.5661.0000.000
경도0.182-0.6341.0000.1821.0000.816
포인트1.000-0.5660.1821.0001.0000.457
상세정보1.0001.0001.0001.0001.0001.000
추천코스여부0.4570.0000.8160.4571.0001.000

Missing values

2023-12-12T04:43:21.470114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:43:21.694739image/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
0133.357789126.274116주차장(상명정낭문화공간)장애인주차구역 없음12<NA>YY2021-12-22
1233.357768126.273899퐁낭<NA>13<NA>YY2021-12-22
2333.361008126.272941다육이 비닐하우스(담벼락위 다육이들)13~14구간 꽃길14<NA>YY2021-12-22
3433.361866126.272554시멘트길 시작<NA>15<NA>YY2021-12-22
4533.361979126.271448갈림길<NA>16<NA>YY2021-12-22
5633.362234126.271379할망당 입구<NA>17접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
6733.362181126.271238할망당계단 30개(비장애인 코스)18접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
7833.361747126.271229오르막 시작양 옆 과수원길19접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
8933.361632126.27052오르막 끝2º~5º20접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
91033.361363126.270044정자 앞 삼거리계단 4개21접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
순서위도경도구분설명포인트상세정보전체코스여부추천코스여부데이터기준일자
161733.358832126.271223정낭(제주 전통 올레)길목 안쪽28<NA>YY2021-12-22
171833.358346126.271837횡단보도차량 통행이 많음29접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
181933.35828126.271644소리소문 책방 진입로 입구자갈길 시작30접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
192033.358034126.271617자갈길 끝<NA>31접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
202133.357993126.271661소리소문 책방비장애인 코스32접근성정보(*계단. 길 상태. 경사) 있음YY2021-12-22
212233.358063126.272516인도연결 부분통로 넓이 67cm. 길건너 우측(퐁낭과 작은 폭포 있음)33<NA>YY2021-12-22
222333.3579126.273096포제단 진입로 입구<NA>34접근성정보(*계단. 길 상태. 경사) 있음YN2021-12-22
232433.35815126.273376포제단 계단 16개비장애인 코스35접근성정보(*계단. 길 상태. 경사) 있음YN2021-12-22
242533.357801126.273475우측 길건너(산들휴게소)<NA>36<NA>YN2021-12-22
252633.357739126.274295주차장(상명정낭문화공간)종료37<NA>YY2021-12-22