Overview

Dataset statistics

Number of variables7
Number of observations489
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.3 KiB
Average record size in memory61.3 B

Variable types

Numeric5
Text2

Dataset

Description["국립공원공단에서 운영하고 있는 통합방재시스템 내 기상관측장비 관련 데이터로서, 긱 기상관측장비에 대한 주소, 위도, 경도, 높이값을 포함하고 있습니다."]
Author국립공원공단
URLhttps://www.data.go.kr/data/15090557/fileData.do

Alerts

번호(NO) is highly overall correlated with 아이디(STN_ID)High correlation
아이디(STN_ID) is highly overall correlated with 번호(NO)High correlation
번호(NO) has unique valuesUnique
아이디(STN_ID) has unique valuesUnique
주소(ADDRESS) has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:44:09.733288
Analysis finished2023-12-12 21:44:13.218030
Duration3.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호(NO)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct489
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean285.47853
Minimum1
Maximum572
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-13T06:44:13.305223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.4
Q1130
median291
Q3433
95-th percentile543.2
Maximum572
Range571
Interquartile range (IQR)303

Descriptive statistics

Standard deviation168.95433
Coefficient of variation (CV)0.5918285
Kurtosis-1.2642664
Mean285.47853
Median Absolute Deviation (MAD)151
Skewness-0.039907379
Sum139599
Variance28545.566
MonotonicityNot monotonic
2023-12-13T06:44:13.472414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 1
 
0.2%
378 1
 
0.2%
382 1
 
0.2%
13 1
 
0.2%
11 1
 
0.2%
15 1
 
0.2%
12 1
 
0.2%
10 1
 
0.2%
376 1
 
0.2%
381 1
 
0.2%
Other values (479) 479
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
572 1
0.2%
571 1
0.2%
568 1
0.2%
567 1
0.2%
566 1
0.2%
565 1
0.2%
564 1
0.2%
563 1
0.2%
562 1
0.2%
561 1
0.2%

소속위치(STN_NAME)
Text

Distinct484
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:44:13.918186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.3087935
Min length2

Characters and Unicode

Total characters1129
Distinct characters228
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique479 ?
Unique (%)98.0%

Sample

1st row청주
2nd row고산
3rd row제주
4th row서귀포
5th row강화
ValueCountFrequency (%)
대덕 2
 
0.4%
금천 2
 
0.4%
주천 2
 
0.4%
남원 2
 
0.4%
광주 2
 
0.4%
심원 1
 
0.2%
보길도 1
 
0.2%
선유도 1
 
0.2%
상조도 1
 
0.2%
조선대 1
 
0.2%
Other values (474) 474
96.9%
2023-12-13T06:44:14.484089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 66
 
5.8%
산 57
 
5.0%
천 33
 
2.9%
성 23
 
2.0%
주 22
 
1.9%
양 22
 
1.9%
청 21
 
1.9%
동 21
 
1.9%
서 20
 
1.8%
대 18
 
1.6%
Other values (218) 826
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1127
99.8%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 66
 
5.9%
산 57
 
5.1%
천 33
 
2.9%
성 23
 
2.0%
주 22
 
2.0%
양 22
 
2.0%
청 21
 
1.9%
동 21
 
1.9%
서 20
 
1.8%
대 18
 
1.6%
Other values (216) 824
73.1%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1127
99.8%
Common 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 66
 
5.9%
산 57
 
5.1%
천 33
 
2.9%
성 23
 
2.0%
주 22
 
2.0%
양 22
 
2.0%
청 21
 
1.9%
동 21
 
1.9%
서 20
 
1.8%
대 18
 
1.6%
Other values (216) 824
73.1%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1127
99.8%
ASCII 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 66
 
5.9%
산 57
 
5.1%
천 33
 
2.9%
성 23
 
2.0%
주 22
 
2.0%
양 22
 
2.0%
청 21
 
1.9%
동 21
 
1.9%
서 20
 
1.8%
대 18
 
1.6%
Other values (216) 824
73.1%
ASCII
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

아이디(STN_ID)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct489
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean590.27607
Minimum90
Maximum953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-13T06:44:14.630538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90
5-th percentile137.4
Q1403
median637
Q3792
95-th percentile923.2
Maximum953
Range863
Interquartile range (IQR)389

Descriptive statistics

Standard deviation247.01131
Coefficient of variation (CV)0.41846742
Kurtosis-0.94124403
Mean590.27607
Median Absolute Deviation (MAD)172
Skewness-0.49560831
Sum288645
Variance61014.586
MonotonicityNot monotonic
2023-12-13T06:44:14.763205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131 1
 
0.2%
736 1
 
0.2%
741 1
 
0.2%
112 1
 
0.2%
106 1
 
0.2%
115 1
 
0.2%
108 1
 
0.2%
105 1
 
0.2%
734 1
 
0.2%
739 1
 
0.2%
Other values (479) 479
98.0%
ValueCountFrequency (%)
90 1
0.2%
95 1
0.2%
96 1
0.2%
98 1
0.2%
99 1
0.2%
100 1
0.2%
101 1
0.2%
102 1
0.2%
104 1
0.2%
105 1
0.2%
ValueCountFrequency (%)
953 1
0.2%
951 1
0.2%
948 1
0.2%
947 1
0.2%
946 1
0.2%
945 1
0.2%
944 1
0.2%
943 1
0.2%
942 1
0.2%
941 1
0.2%

위도(LAT)
Real number (ℝ)

Distinct485
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.127839
Minimum33.117
Maximum38.5439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-13T06:44:14.894988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.117
5-th percentile33.97186
Q135.1993
median36.1319
Q337.264
95-th percentile37.9338
Maximum38.5439
Range5.4269
Interquartile range (IQR)2.0647

Descriptive statistics

Standard deviation1.2678875
Coefficient of variation (CV)0.035094474
Kurtosis-0.70982947
Mean36.127839
Median Absolute Deviation (MAD)1.0274
Skewness-0.28670604
Sum17666.513
Variance1.6075387
MonotonicityNot monotonic
2023-12-13T06:44:15.056723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.8167 2
 
0.4%
35.7295 2
 
0.4%
37.5822 2
 
0.4%
37.5455 2
 
0.4%
36.6392 1
 
0.2%
35.809 1
 
0.2%
35.8468 1
 
0.2%
34.7728 1
 
0.2%
35.0568 1
 
0.2%
37.4776 1
 
0.2%
Other values (475) 475
97.1%
ValueCountFrequency (%)
33.117 1
0.2%
33.1664 1
0.2%
33.2462 1
0.2%
33.2494 1
0.2%
33.2593 1
0.2%
33.2613 1
0.2%
33.2727 1
0.2%
33.2772 1
0.2%
33.2938 1
0.2%
33.3046 1
0.2%
ValueCountFrequency (%)
38.5439 1
0.2%
38.5038 1
0.2%
38.3854 1
0.2%
38.2852 1
0.2%
38.2641 1
0.2%
38.2509 1
0.2%
38.2144 1
0.2%
38.2127 1
0.2%
38.1909 1
0.2%
38.1725 1
0.2%

경도(LON)
Real number (ℝ)

Distinct487
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.60464
Minimum124.6305
Maximum131.8698
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-13T06:44:15.194856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124.6305
5-th percentile126.165
Q1126.8387
median127.512
Q3128.4356
95-th percentile129.20594
Maximum131.8698
Range7.2393
Interquartile range (IQR)1.5969

Descriptive statistics

Standard deviation1.0315391
Coefficient of variation (CV)0.0080838687
Kurtosis0.16080129
Mean127.60464
Median Absolute Deviation (MAD)0.7865
Skewness0.24813716
Sum62398.668
Variance1.064073
MonotonicityNot monotonic
2023-12-13T06:44:15.370405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8777 2
 
0.4%
128.8214 2
 
0.4%
127.0282 1
 
0.2%
126.9843 1
 
0.2%
126.6244 1
 
0.2%
129.1243 1
 
0.2%
130.8986 1
 
0.2%
126.9658 1
 
0.2%
128.891 1
 
0.2%
127.1657 1
 
0.2%
Other values (477) 477
97.5%
ValueCountFrequency (%)
124.6305 1
0.2%
124.7124 1
0.2%
124.7291 1
0.2%
125.1264 1
0.2%
125.1923 1
0.2%
125.2995 1
0.2%
125.451 1
0.2%
125.5595 1
0.2%
125.7023 1
0.2%
125.7869 1
0.2%
ValueCountFrequency (%)
131.8698 1
0.2%
130.8986 1
0.2%
130.8706 1
0.2%
130.8118 1
0.2%
129.5667 1
0.2%
129.5475 1
0.2%
129.4906 1
0.2%
129.4309 1
0.2%
129.4128 1
0.2%
129.4093 1
0.2%

높이(HT)
Real number (ℝ)

Distinct436
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.75624
Minimum1
Maximum1668.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-13T06:44:15.500021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.76
Q124.8
median63
Q3144.2
95-th percentile581.02
Maximum1668.3
Range1667.3
Interquartile range (IQR)119.4

Descriptive statistics

Standard deviation222.69003
Coefficient of variation (CV)1.5820971
Kurtosis15.68897
Mean140.75624
Median Absolute Deviation (MAD)48.5
Skewness3.5245263
Sum68829.8
Variance49590.852
MonotonicityNot monotonic
2023-12-13T06:44:15.638723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.7 3
 
0.6%
35.4 3
 
0.6%
10.0 3
 
0.6%
38.0 3
 
0.6%
5.6 3
 
0.6%
4.0 3
 
0.6%
26.0 3
 
0.6%
30.3 3
 
0.6%
63.0 3
 
0.6%
10.9 2
 
0.4%
Other values (426) 460
94.1%
ValueCountFrequency (%)
1.0 1
0.2%
1.1 1
0.2%
2.0 1
0.2%
2.1 1
0.2%
2.2 1
0.2%
2.5 1
0.2%
2.9 1
0.2%
3.0 1
0.2%
3.2 1
0.2%
3.3 1
0.2%
ValueCountFrequency (%)
1668.3 1
0.2%
1595.7 1
0.2%
1518.3 1
0.2%
1488.3 1
0.2%
1088.9 1
0.2%
1050.2 1
0.2%
1015.1 1
0.2%
965.2 1
0.2%
911.8 1
0.2%
864.7 1
0.2%

주소(ADDRESS)
Text

UNIQUE 

Distinct489
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:44:15.941273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length25.552147
Min length16

Characters and Unicode

Total characters12495
Distinct characters367
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

Unique489 ?
Unique (%)100.0%

Sample

1st row충청북도 청주시 흥덕구 공단로76 청주기상지청
2nd row제주특별자치도 제주시 한경면 노을해안로1013-70 고산지역서비스센터
3rd row제주특별자치도 제주시 동문로9길13-1 제주지방기상청
4th row제주특별자치도 서귀포시 태평로439번길17 서귀포지역서비스센터
5th row인천광역시 강화군 불은면 중앙로628 강화자동기상관측소
ValueCountFrequency (%)
전라남도 79
 
3.6%
강원도 67
 
3.1%
경상북도 67
 
3.1%
경상남도 52
 
2.4%
전라북도 39
 
1.8%
경기도 33
 
1.5%
충청북도 30
 
1.4%
충청남도 27
 
1.2%
제주특별자치도 25
 
1.2%
서울특별시 23
 
1.1%
Other values (1331) 1728
79.6%
2023-12-13T06:44:16.335072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1681
 
13.5%
도 514
 
4.1%
1 370
 
3.0%
시 294
 
2.4%
군 292
 
2.3%
면 281
 
2.2%
리 253
 
2.0%
2 230
 
1.8%
- 218
 
1.7%
남 209
 
1.7%
Other values (357) 8153
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8801
70.4%
Decimal Number 1773
 
14.2%
Space Separator 1681
 
13.5%
Dash Punctuation 218
 
1.7%
Uppercase Letter 14
 
0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 514
 
5.8%
시 294
 
3.3%
군 292
 
3.3%
면 281
 
3.2%
리 253
 
2.9%
남 209
 
2.4%
상 208
 
2.4%
산 189
 
2.1%
경 183
 
2.1%
동 176
 
2.0%
Other values (335) 6202
70.5%
Decimal Number
ValueCountFrequency (%)
1 370
20.9%
2 230
13.0%
3 204
11.5%
5 159
9.0%
4 153
8.6%
0 150
8.5%
6 138
 
7.8%
7 137
 
7.7%
9 124
 
7.0%
8 108
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
K 4
28.6%
S 3
21.4%
C 2
14.3%
B 2
14.3%
T 1
 
7.1%
G 1
 
7.1%
I 1
 
7.1%
Space Separator
ValueCountFrequency (%)
1681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8803
70.5%
Common 3678
29.4%
Latin 14
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 514
 
5.8%
시 294
 
3.3%
군 292
 
3.3%
면 281
 
3.2%
리 253
 
2.9%
남 209
 
2.4%
상 208
 
2.4%
산 189
 
2.1%
경 183
 
2.1%
동 176
 
2.0%
Other values (336) 6204
70.5%
Common
ValueCountFrequency (%)
1681
45.7%
1 370
 
10.1%
2 230
 
6.3%
- 218
 
5.9%
3 204
 
5.5%
5 159
 
4.3%
4 153
 
4.2%
0 150
 
4.1%
6 138
 
3.8%
7 137
 
3.7%
Other values (4) 238
 
6.5%
Latin
ValueCountFrequency (%)
K 4
28.6%
S 3
21.4%
C 2
14.3%
B 2
14.3%
T 1
 
7.1%
G 1
 
7.1%
I 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8801
70.4%
ASCII 3692
29.5%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1681
45.5%
1 370
 
10.0%
2 230
 
6.2%
- 218
 
5.9%
3 204
 
5.5%
5 159
 
4.3%
4 153
 
4.1%
0 150
 
4.1%
6 138
 
3.7%
7 137
 
3.7%
Other values (11) 252
 
6.8%
Hangul
ValueCountFrequency (%)
도 514
 
5.8%
시 294
 
3.3%
군 292
 
3.3%
면 281
 
3.2%
리 253
 
2.9%
남 209
 
2.4%
상 208
 
2.4%
산 189
 
2.1%
경 183
 
2.1%
동 176
 
2.0%
Other values (335) 6202
70.5%
None
ValueCountFrequency (%)
㈜ 2
100.0%

Interactions

2023-12-13T06:44:12.405486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.208699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.663317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.105344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.867778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.534920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.287463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.743454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.195306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.967950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.643064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.357800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.814848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.557623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.074553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.743225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.456186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.903817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.654299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.189138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.858835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.571829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:10.998744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:11.754320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:44:12.308317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:44:16.430802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호(NO)아이디(STN_ID)위도(LAT)경도(LON)높이(HT)
번호(NO)1.0000.9820.7440.4000.086
아이디(STN_ID)0.9821.0000.7400.4410.113
위도(LAT)0.7440.7401.0000.3910.235
경도(LON)0.4000.4410.3911.0000.248
높이(HT)0.0860.1130.2350.2481.000
2023-12-13T06:44:16.537670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호(NO)아이디(STN_ID)위도(LAT)경도(LON)높이(HT)
번호(NO)1.0001.000-0.3430.138-0.042
아이디(STN_ID)1.0001.000-0.3430.138-0.042
위도(LAT)-0.343-0.3431.0000.2660.256
경도(LON)0.1380.1380.2661.0000.341
높이(HT)-0.042-0.0420.2560.3411.000

Missing values

2023-12-13T06:44:13.023777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:44:13.169919image/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

번호(NO)소속위치(STN_NAME)아이디(STN_ID)위도(LAT)경도(LON)높이(HT)주소(ADDRESS)
022청주13136.6392127.440757.2충청북도 청주시 흥덕구 공단로76 청주기상지청
145고산18533.2938126.162871.5제주특별자치도 제주시 한경면 노을해안로1013-70 고산지역서비스센터
244제주18433.5141126.529720.4제주특별자치도 제주시 동문로9길13-1 제주지방기상청
347서귀포18933.2462126.565347.0제주특별자치도 서귀포시 태평로439번길17 서귀포지역서비스센터
449강화20137.7074126.446346.4인천광역시 강화군 불은면 중앙로628 강화자동기상관측소
550양평20237.4886127.494547.9경기도 양평군 양평읍 시민로20번길14-1 양평자동기상관측소
648진주19235.1638128.0430.2경상남도 진주시 남강로43 진주지역서비스센터
723대전13336.372127.372168.9대전광역시 유성구 대학로383 대전지방기상청
840완도17034.3959126.701835.4전라남도 완도군 군외면 청해진로795-3 완도지역서비스센터
921울진13036.9918129.412850.0경상북도 울진군 울진읍 현내항길 울진지역서비스센터
번호(NO)소속위치(STN_NAME)아이디(STN_ID)위도(LAT)경도(LON)높이(HT)주소(ADDRESS)
479559금정구93935.2932129.103553.1부산광역시 금정구 두구동1363
480484울진서84336.9361129.2501219.7경상북도 울진군 서면 불영계곡로1720 왕피천환경출장소
481488소보84736.2763128.466568.3경상북도 군위군 소보면 소보안계로107 국립원예특작과학원
482492소곡85137.0514129.352175.2경상북도 울진군 북면 박금소야로448
483490지보84936.5468128.38780.0경상북도 예천군 지보면 소화1길20-5지 보종합복지회관
484489금천84835.6792128.8953102.9경상북도 청도군 금천면 섶마리1길27 금천초등학교
485497백운산85635.1018127.5981514.9전라남도 광양시 옥룡면 동곡리1105
486477현서83636.2803128.8988321.7경상북도 청송군 현서면 구덕길74 현서중고등학교
487572장목95334.9984128.679830.6경상남도 거제시 장목면 장목리360-12
488571내장산95135.5087126.9073102.6전라북도 정읍시 내장동560 내장산자연생태학습장