Overview

Dataset statistics

Number of variables9
Number of observations368
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.4 KiB
Average record size in memory76.4 B

Variable types

Numeric4
Text2
Categorical3

Dataset

Description제주특별자치도에 소재하고 있는 오름(산 또는 봉우리를 뜻하는 제주도 방언) 관련한 데이터로 오름명, 행정시, 소재지, 비고(m), 표고(m), 면적(㎡), 형태 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15043497/fileData.do

Alerts

비고 is highly overall correlated with 면적High correlation
면적 is highly overall correlated with 비고 and 1 other fieldsHigh correlation
형태 is highly overall correlated with 면적High correlation
데이터기준일자 is highly imbalanced (53.8%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:38:32.316401
Analysis finished2023-12-12 09:38:34.861781
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct368
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.5
Minimum1
Maximum368
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T18:38:34.939782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.35
Q192.75
median184.5
Q3276.25
95-th percentile349.65
Maximum368
Range367
Interquartile range (IQR)183.5

Descriptive statistics

Standard deviation106.37669
Coefficient of variation (CV)0.57656742
Kurtosis-1.2
Mean184.5
Median Absolute Deviation (MAD)92
Skewness0
Sum67896
Variance11316
MonotonicityStrictly increasing
2023-12-12T18:38:35.098316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
244 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
Other values (358) 358
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%

오름명
Text

Distinct339
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:38:35.469636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.951087
Min length2

Characters and Unicode

Total characters1454
Distinct characters261
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique318 ?
Unique (%)86.4%

Sample

1st row가마오름
2nd row가메오름
3rd row가메옥
4th row가메창
5th row가문이오름
ValueCountFrequency (%)
민오름 4
 
1.1%
밝은오름 4
 
1.1%
붉은오름 3
 
0.8%
눈오름 3
 
0.8%
당오름 3
 
0.8%
알오름 3
 
0.8%
천아오름 2
 
0.5%
당산봉 2
 
0.5%
논오름 2
 
0.5%
세미오름 2
 
0.5%
Other values (329) 342
92.4%
2023-12-12T18:38:36.093160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
오 211
 
14.5%
름 203
 
14.0%
이 44
 
3.0%
산 40
 
2.8%
봉 40
 
2.8%
리 39
 
2.7%
은 35
 
2.4%
악 32
 
2.2%
미 17
 
1.2%
족 16
 
1.1%
Other values (251) 777
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1427
98.1%
Open Punctuation 11
 
0.8%
Close Punctuation 11
 
0.8%
Space Separator 2
 
0.1%
Letter Number 2
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
오 211
 
14.8%
름 203
 
14.2%
이 44
 
3.1%
산 40
 
2.8%
봉 40
 
2.8%
리 39
 
2.7%
은 35
 
2.5%
악 32
 
2.2%
미 17
 
1.2%
족 16
 
1.1%
Other values (245) 750
52.6%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1427
98.1%
Common 25
 
1.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
오 211
 
14.8%
름 203
 
14.2%
이 44
 
3.1%
산 40
 
2.8%
봉 40
 
2.8%
리 39
 
2.7%
은 35
 
2.5%
악 32
 
2.2%
미 17
 
1.2%
족 16
 
1.1%
Other values (245) 750
52.6%
Common
ValueCountFrequency (%)
( 11
44.0%
) 11
44.0%
2
 
8.0%
2 1
 
4.0%
Latin
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1427
98.1%
ASCII 25
 
1.7%
Number Forms 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
오 211
 
14.8%
름 203
 
14.2%
이 44
 
3.1%
산 40
 
2.8%
봉 40
 
2.8%
리 39
 
2.7%
은 35
 
2.5%
악 32
 
2.2%
미 17
 
1.2%
족 16
 
1.1%
Other values (245) 750
52.6%
ASCII
ValueCountFrequency (%)
( 11
44.0%
) 11
44.0%
2
 
8.0%
2 1
 
4.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

행정시
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
제주시
210 
서귀포시
158 

Length

Max length4
Median length3
Mean length3.4293478
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 210
57.1%
서귀포시 158
42.9%

Length

2023-12-12T18:38:36.295968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:38:36.437015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 210
57.1%
서귀포시 158
42.9%

소재지
Text

Distinct300
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-12T18:38:36.739416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.557065
Min length18

Characters and Unicode

Total characters8669
Distinct characters138
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

Unique269 ?
Unique (%)73.1%

Sample

1st row제주특별자치도 제주시 한경면 청수리 1202
2nd row제주특별자치도 제주시 애월읍 봉성리 산124
3rd row제주특별자치도 제주시 구좌읍 송당리 1712
4th row제주특별자치도 제주시 한경면 저지리 1496
5th row제주특별자치도 서귀포시 표선면 가시리 산158-2
ValueCountFrequency (%)
제주특별자치도 368
21.0%
제주시 210
 
12.0%
서귀포시 158
 
9.0%
애월읍 50
 
2.8%
구좌읍 40
 
2.3%
표선면 31
 
1.8%
안덕면 31
 
1.8%
조천읍 30
 
1.7%
남원읍 29
 
1.7%
송당리 24
 
1.4%
Other values (360) 784
44.7%
2023-12-12T18:38:37.217790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1387
 
16.0%
제 578
 
6.7%
주 578
 
6.7%
시 383
 
4.4%
도 373
 
4.3%
특 368
 
4.2%
별 368
 
4.2%
자 368
 
4.2%
치 368
 
4.2%
1 329
 
3.8%
Other values (128) 3569
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5999
69.2%
Space Separator 1387
 
16.0%
Decimal Number 1123
 
13.0%
Dash Punctuation 160
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 578
 
9.6%
주 578
 
9.6%
시 383
 
6.4%
도 373
 
6.2%
특 368
 
6.1%
별 368
 
6.1%
자 368
 
6.1%
치 368
 
6.1%
산 276
 
4.6%
리 272
 
4.5%
Other values (116) 2067
34.5%
Decimal Number
ValueCountFrequency (%)
1 329
29.3%
2 156
13.9%
3 106
 
9.4%
8 92
 
8.2%
5 92
 
8.2%
4 83
 
7.4%
6 80
 
7.1%
7 68
 
6.1%
0 59
 
5.3%
9 58
 
5.2%
Space Separator
ValueCountFrequency (%)
1387
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5999
69.2%
Common 2670
30.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 578
 
9.6%
주 578
 
9.6%
시 383
 
6.4%
도 373
 
6.2%
특 368
 
6.1%
별 368
 
6.1%
자 368
 
6.1%
치 368
 
6.1%
산 276
 
4.6%
리 272
 
4.5%
Other values (116) 2067
34.5%
Common
ValueCountFrequency (%)
1387
51.9%
1 329
 
12.3%
- 160
 
6.0%
2 156
 
5.8%
3 106
 
4.0%
8 92
 
3.4%
5 92
 
3.4%
4 83
 
3.1%
6 80
 
3.0%
7 68
 
2.5%
Other values (2) 117
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5999
69.2%
ASCII 2670
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1387
51.9%
1 329
 
12.3%
- 160
 
6.0%
2 156
 
5.8%
3 106
 
4.0%
8 92
 
3.4%
5 92
 
3.4%
4 83
 
3.1%
6 80
 
3.0%
7 68
 
2.5%
Other values (2) 117
 
4.4%
Hangul
ValueCountFrequency (%)
제 578
 
9.6%
주 578
 
9.6%
시 383
 
6.4%
도 373
 
6.2%
특 368
 
6.1%
별 368
 
6.1%
자 368
 
6.1%
치 368
 
6.1%
산 276
 
4.6%
리 272
 
4.5%
Other values (116) 2067
34.5%

비고
Real number (ℝ)

HIGH CORRELATION 

Distinct145
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.842391
Minimum6
Maximum389
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T18:38:37.424648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile21.35
Q145
median71
Q3109.25
95-th percentile157.9
Maximum389
Range383
Interquartile range (IQR)64.25

Descriptive statistics

Standard deviation51.361063
Coefficient of variation (CV)0.6353234
Kurtosis7.1874328
Mean80.842391
Median Absolute Deviation (MAD)31
Skewness1.9160495
Sum29750
Variance2637.9587
MonotonicityNot monotonic
2023-12-12T18:38:37.595409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 7
 
1.9%
118 7
 
1.9%
51 6
 
1.6%
45 6
 
1.6%
55 6
 
1.6%
30 6
 
1.6%
48 6
 
1.6%
37 6
 
1.6%
49 6
 
1.6%
54 5
 
1.4%
Other values (135) 307
83.4%
ValueCountFrequency (%)
6 1
 
0.3%
8 1
 
0.3%
10 1
 
0.3%
13 3
0.8%
14 2
0.5%
15 2
0.5%
17 2
0.5%
18 1
 
0.3%
20 2
0.5%
21 4
1.1%
ValueCountFrequency (%)
389 1
0.3%
350 1
0.3%
345 1
0.3%
280 1
0.3%
279 1
0.3%
234 1
0.3%
227 1
0.3%
213 1
0.3%
186 1
0.3%
178 1
0.3%

표고
Real number (ℝ)

Distinct357
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean460.86739
Minimum33
Maximum1813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T18:38:37.767058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile84.675
Q1179.45
median350.35
Q3601.6
95-th percentile1336.82
Maximum1813
Range1780
Interquartile range (IQR)422.15

Descriptive statistics

Standard deviation381.89748
Coefficient of variation (CV)0.82864938
Kurtosis2.191277
Mean460.86739
Median Absolute Deviation (MAD)190.95
Skewness1.5548558
Sum169599.2
Variance145845.68
MonotonicityNot monotonic
2023-12-12T18:38:37.938431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
473.0 3
 
0.8%
301.4 2
 
0.5%
342.0 2
 
0.5%
653.3 2
 
0.5%
84.5 2
 
0.5%
186.0 2
 
0.5%
206.2 2
 
0.5%
87.5 2
 
0.5%
158.0 2
 
0.5%
104.0 2
 
0.5%
Other values (347) 347
94.3%
ValueCountFrequency (%)
33.0 1
0.3%
40.7 1
0.3%
41.9 1
0.3%
42.0 1
0.3%
45.0 1
0.3%
48.5 1
0.3%
49.0 1
0.3%
50.1 1
0.3%
52.5 1
0.3%
52.6 1
0.3%
ValueCountFrequency (%)
1813.0 1
0.3%
1747.9 1
0.3%
1740.0 1
0.3%
1711.2 1
0.3%
1699.3 1
0.3%
1698.9 1
0.3%
1695.5 1
0.3%
1666.3 1
0.3%
1639.3 1
0.3%
1628.4 1
0.3%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct362
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278011.17
Minimum0
Maximum2836857
Zeros2
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T18:38:38.139945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22333.05
Q179932.75
median192446
Q3390546.5
95-th percentile719663.05
Maximum2836857
Range2836857
Interquartile range (IQR)310613.75

Descriptive statistics

Standard deviation308582.22
Coefficient of variation (CV)1.1099634
Kurtosis22.428363
Mean278011.17
Median Absolute Deviation (MAD)136842
Skewness3.6823602
Sum1.0230811 × 108
Variance9.522299 × 1010
MonotonicityNot monotonic
2023-12-12T18:38:38.592875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453030 2
 
0.5%
0 2
 
0.5%
192446 2
 
0.5%
152322 2
 
0.5%
72363 2
 
0.5%
144548 2
 
0.5%
298849 1
 
0.3%
66974 1
 
0.3%
139259 1
 
0.3%
53199 1
 
0.3%
Other values (352) 352
95.7%
ValueCountFrequency (%)
0 2
0.5%
5343 1
0.3%
9975 1
0.3%
11449 1
0.3%
14756 1
0.3%
15698 1
0.3%
15717 1
0.3%
16244 1
0.3%
17037 1
0.3%
17198 1
0.3%
ValueCountFrequency (%)
2836857 1
0.3%
2543257 1
0.3%
1932024 1
0.3%
1338920 1
0.3%
1288365 1
0.3%
1266825 1
0.3%
1204428 1
0.3%
1136315 1
0.3%
988332 1
0.3%
951657 1
0.3%

형태
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
원추형
98 
원형
47 
복합형
38 
말굽형(북향)
32 
말굽형(북서향)
28 
Other values (20)
125 

Length

Max length10
Median length8
Mean length5.1304348
Min length2

Unique

Unique9 ?
Unique (%)2.4%

Sample

1st row말굽형(북동향)
2nd row복합형
3rd row복합형
4th row원형
5th row말굽형(남서향)

Common Values

ValueCountFrequency (%)
원추형 98
26.6%
원형 47
12.8%
복합형 38
 
10.3%
말굽형(북향) 32
 
8.7%
말굽형(북서향) 28
 
7.6%
말굽형(북동향) 25
 
6.8%
말굽형(서향) 18
 
4.9%
말굽형(동향) 17
 
4.6%
말굽형(남향) 16
 
4.3%
말굽형(남서향) 12
 
3.3%
Other values (15) 37
 
10.1%

Length

2023-12-12T18:38:38.734738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원추형 98
26.6%
원형 47
12.8%
복합형 38
 
10.3%
말굽형(북향 32
 
8.7%
말굽형(북서향 28
 
7.6%
말굽형(북동향 25
 
6.8%
말굽형(서향 18
 
4.9%
말굽형(동향 17
 
4.6%
말굽형(남향 16
 
4.3%
말굽형(남서향 12
 
3.3%
Other values (15) 37
 
10.1%

데이터기준일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-01-31
332 
2023-05-12
36 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-01-31
2nd row2023-01-31
3rd row2023-01-31
4th row2023-01-31
5th row2023-01-31

Common Values

ValueCountFrequency (%)
2023-01-31 332
90.2%
2023-05-12 36
 
9.8%

Length

2023-12-12T18:38:38.865638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:38:38.979921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-01-31 332
90.2%
2023-05-12 36
 
9.8%

Interactions

2023-12-12T18:38:34.173793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:32.782183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.189679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.722248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.293317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:32.877154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.352729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.844404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.420410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:32.974414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.500632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.950250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.521351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.090063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:33.613696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:38:34.052839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:38:39.082370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정시비고표고면적형태데이터기준일자
연번1.0000.0000.0000.2020.0000.2240.000
행정시0.0001.0000.0000.1660.0000.2780.000
비고0.0000.0001.0000.4190.7650.7200.048
표고0.2020.1660.4191.0000.2260.0000.314
면적0.0000.0000.7650.2261.0000.8770.075
형태0.2240.2780.7200.0000.8771.0000.000
데이터기준일자0.0000.0000.0480.3140.0750.0001.000
2023-12-12T18:38:39.229913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자행정시형태
데이터기준일자1.0000.0000.000
행정시0.0001.0000.232
형태0.0000.2321.000
2023-12-12T18:38:39.331326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번비고표고면적행정시형태데이터기준일자
연번1.000-0.0650.068-0.0510.0000.0780.000
비고-0.0651.0000.4060.8380.0000.3650.047
표고0.0680.4061.0000.2800.1260.0000.238
면적-0.0510.8380.2801.0000.0000.5820.055
행정시0.0000.0000.1260.0001.0000.2320.000
형태0.0780.3650.0000.5820.2321.0000.000
데이터기준일자0.0000.0470.2380.0550.0000.0001.000

Missing values

2023-12-12T18:38:34.662951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:38:34.806366image/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

연번오름명행정시소재지비고표고면적형태데이터기준일자
01가마오름제주시제주특별자치도 제주시 한경면 청수리 120251140.5154486말굽형(북동향)2023-01-31
12가메오름제주시제주특별자치도 제주시 애월읍 봉성리 산12417372.228371복합형2023-01-31
23가메옥제주시제주특별자치도 제주시 구좌읍 송당리 171228368.022764복합형2023-01-31
34가메창제주시제주특별자치도 제주시 한경면 저지리 14966145.817037원형2023-01-31
45가문이오름서귀포시제주특별자치도 서귀포시 표선면 가시리 산158-2106496.2116176말굽형(남서향)2023-01-31
56가새기오름제주시제주특별자치도 제주시 오라삼동 284520115.017198원추형2023-05-12
67가세오름서귀포시제주특별자치도 서귀포시 표선면 토산리 산2101200.5373099말굽형(서향)2023-01-31
78가시오름서귀포시제주특별자치도 서귀포시 대정읍 동일리 120977106.5263863말굽형(남서향)2023-01-31
89각시바위서귀포시제주특별자치도 서귀포시 호근동 2112140395.0585988원추형2023-01-31
910감낭오름서귀포시제주특별자치도 서귀포시 안덕면 동광리 산4145439.8117413말굽형(북동향)2023-01-31
연번오름명행정시소재지비고표고면적형태데이터기준일자
358359통오름서귀포시제주특별자치도 서귀포시 성산읍 난산리 1976-143143.1258114말굽형(서향)2023-01-31
359360파군봉제주시제주특별자치도 제주시 애월읍 하귀1리 688-15084.559269원추형2023-01-31
360361판포오름제주시제주특별자치도 제주시 한경면 판포리 935-15893.2192446말굽형(동향)2023-01-31
361362폭낭오름제주시제주특별자치도 제주시 애월읍 봉성리 산4376645.5583171복합형2023-01-31
362363하논서귀포시제주특별자치도 서귀포시 호근동 14988143.41266825원형2023-01-31
363364하늬보기서귀포시제주특별자치도 서귀포시 안덕면 상천리 산89-142592.317795원추형2023-05-12
364365한대오름제주시제주특별자치도 제주시 애월읍 봉성리 산136921.4132263원추형2023-01-31
365366후곡악서귀포시제주특별자치도 서귀포시 성산읍 수산리 450436206.254168말굽형(서남향)2023-01-31
366367흑악서귀포시제주특별자치도 서귀포시 남원읍 신례리 산2-140590.132197원추형2023-01-31
367368흙붉은오름제주시제주특별자치도 제주시 아라일동 산671461380.7721090말굽형(동향)2023-01-31