Overview

Dataset statistics

Number of variables11
Number of observations568
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.4 KiB
Average record size in memory96.2 B

Variable types

DateTime1
Numeric6
Categorical4

Dataset

Description경기도 안산시 이동식시료채취시스템의 오염측정값 입니다. 측정일시, 온도, 습도, 암모니아, 황화수소, 총휘발성유기화합물, 풍향, 풍속, 위도, 경도, 데이터기준일자 등의 목록을 제공합니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/15042192/fileData.do

Alerts

위도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
습도 is highly overall correlated with 풍속High correlation
풍속 is highly overall correlated with 습도High correlation
경도 is highly imbalanced (95.2%)Imbalance
총휘발성유기화합물 has 7 (1.2%) zerosZeros
풍속 has 13 (2.3%) zerosZeros

Reproduction

Analysis started2023-12-12 10:05:16.673638
Analysis finished2023-12-12 10:05:22.079083
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정일시
Date

Distinct552
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2020-09-20 07:45:00
Maximum2022-05-20 12:25:00
2023-12-12T19:05:22.147959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:22.278538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

온도
Real number (ℝ)

Distinct132
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.034331
Minimum-0.7
Maximum29.2
Zeros1
Zeros (%)0.2%
Negative2
Negative (%)0.4%
Memory size5.1 KiB
2023-12-12T19:05:22.430418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.7
5-th percentile13.935
Q117.5
median21.9
Q325.2
95-th percentile27.2
Maximum29.2
Range29.9
Interquartile range (IQR)7.7

Descriptive statistics

Standard deviation4.7365889
Coefficient of variation (CV)0.22518372
Kurtosis1.0421894
Mean21.034331
Median Absolute Deviation (MAD)3.6
Skewness-0.70627508
Sum11947.5
Variance22.435274
MonotonicityNot monotonic
2023-12-12T19:05:22.580091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.7 16
 
2.8%
18.3 13
 
2.3%
13.8 12
 
2.1%
18.8 11
 
1.9%
25.5 10
 
1.8%
25.6 10
 
1.8%
14.0 10
 
1.8%
25.0 9
 
1.6%
26.5 9
 
1.6%
14.1 9
 
1.6%
Other values (122) 459
80.8%
ValueCountFrequency (%)
-0.7 1
 
0.2%
-0.2 1
 
0.2%
0.0 1
 
0.2%
0.6 1
 
0.2%
13.6 2
 
0.4%
13.7 3
 
0.5%
13.8 12
2.1%
13.9 8
1.4%
14.0 10
1.8%
14.1 9
1.6%
ValueCountFrequency (%)
29.2 1
 
0.2%
28.2 1
 
0.2%
27.8 2
 
0.4%
27.7 5
0.9%
27.6 2
 
0.4%
27.5 9
1.6%
27.4 1
 
0.2%
27.3 3
 
0.5%
27.2 6
1.1%
27.1 7
1.2%

습도
Real number (ℝ)

HIGH CORRELATION 

Distinct351
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.625176
Minimum30.5
Maximum98.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T19:05:22.715358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30.5
5-th percentile35
Q141.375
median60.9
Q389
95-th percentile95.965
Maximum98.5
Range68
Interquartile range (IQR)47.625

Descriptive statistics

Standard deviation22.582107
Coefficient of variation (CV)0.35492408
Kurtosis-1.5250285
Mean63.625176
Median Absolute Deviation (MAD)20.25
Skewness0.20275094
Sum36139.1
Variance509.95155
MonotonicityNot monotonic
2023-12-12T19:05:22.840117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.8 7
 
1.2%
95.5 5
 
0.9%
95.1 5
 
0.9%
41.3 5
 
0.9%
41.2 5
 
0.9%
40.9 5
 
0.9%
94.1 5
 
0.9%
92.7 5
 
0.9%
35.9 4
 
0.7%
41.0 4
 
0.7%
Other values (341) 518
91.2%
ValueCountFrequency (%)
30.5 1
 
0.2%
30.8 1
 
0.2%
31.1 3
0.5%
31.3 1
 
0.2%
32.1 1
 
0.2%
32.3 1
 
0.2%
32.6 1
 
0.2%
32.8 3
0.5%
32.9 1
 
0.2%
33.1 1
 
0.2%
ValueCountFrequency (%)
98.5 1
 
0.2%
98.4 1
 
0.2%
98.3 2
0.4%
98.1 2
0.4%
97.9 2
0.4%
97.8 2
0.4%
97.7 3
0.5%
97.6 1
 
0.2%
97.5 1
 
0.2%
97.4 1
 
0.2%

암모니아
Real number (ℝ)

Distinct188
Distinct (%)33.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.231338
Minimum0.7
Maximum422.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T19:05:22.969148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile2.535
Q14.3
median5.9
Q38.425
95-th percentile357.795
Maximum422.5
Range421.8
Interquartile range (IQR)4.125

Descriptive statistics

Standard deviation104.14869
Coefficient of variation (CV)2.3546358
Kurtosis5.7086094
Mean44.231338
Median Absolute Deviation (MAD)1.9
Skewness2.6753859
Sum25123.4
Variance10846.95
MonotonicityNot monotonic
2023-12-12T19:05:23.088176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 15
 
2.6%
4.1 15
 
2.6%
5.1 14
 
2.5%
6.9 14
 
2.5%
5.3 14
 
2.5%
4.0 12
 
2.1%
7.0 12
 
2.1%
4.4 11
 
1.9%
5.7 11
 
1.9%
5.6 10
 
1.8%
Other values (178) 440
77.5%
ValueCountFrequency (%)
0.7 1
 
0.2%
0.8 1
 
0.2%
0.9 1
 
0.2%
1.0 1
 
0.2%
1.2 1
 
0.2%
1.3 2
 
0.4%
1.4 3
0.5%
1.5 1
 
0.2%
1.9 1
 
0.2%
2.0 6
1.1%
ValueCountFrequency (%)
422.5 1
 
0.2%
420.3 1
 
0.2%
418.7 1
 
0.2%
415.4 1
 
0.2%
415.3 1
 
0.2%
413.7 3
0.5%
412.1 2
0.4%
410.4 1
 
0.2%
410.3 2
0.4%
407.3 1
 
0.2%

황화수소
Real number (ℝ)

Distinct110
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.173768
Minimum0
Maximum494.9
Zeros5
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T19:05:23.208658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11.9
median2.8
Q33.8
95-th percentile33.53
Maximum494.9
Range494.9
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation39.925934
Coefficient of variation (CV)3.9244001
Kurtosis69.944805
Mean10.173768
Median Absolute Deviation (MAD)1
Skewness7.861877
Sum5778.7
Variance1594.0802
MonotonicityNot monotonic
2023-12-12T19:05:23.366801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 29
 
5.1%
3.0 28
 
4.9%
2.3 25
 
4.4%
3.3 24
 
4.2%
2.4 24
 
4.2%
2.8 21
 
3.7%
1.9 16
 
2.8%
1.3 16
 
2.8%
2.9 15
 
2.6%
4.0 15
 
2.6%
Other values (100) 355
62.5%
ValueCountFrequency (%)
0.0 5
 
0.9%
0.3 1
 
0.2%
0.4 3
 
0.5%
0.5 1
 
0.2%
0.6 4
 
0.7%
0.7 5
 
0.9%
0.8 3
 
0.5%
0.9 5
 
0.9%
1.0 12
2.1%
1.1 14
2.5%
ValueCountFrequency (%)
494.9 1
0.2%
334.8 1
0.2%
322.4 1
0.2%
317.8 1
0.2%
311.7 1
0.2%
299.6 1
0.2%
210.2 1
0.2%
202.7 1
0.2%
158.8 1
0.2%
140.1 1
0.2%

총휘발성유기화합물
Real number (ℝ)

ZEROS 

Distinct327
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.51356
Minimum0
Maximum1568
Zeros7
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T19:05:23.521421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.84
Q173.8
median111.3
Q3166.4
95-th percentile317.415
Maximum1568
Range1568
Interquartile range (IQR)92.6

Descriptive statistics

Standard deviation151.9176
Coefficient of variation (CV)1.0889093
Kurtosis31.639097
Mean139.51356
Median Absolute Deviation (MAD)53.2
Skewness4.7713837
Sum79243.7
Variance23078.958
MonotonicityNot monotonic
2023-12-12T19:05:23.664105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 13
 
2.3%
20.0 10
 
1.8%
35.0 8
 
1.4%
100.0 7
 
1.2%
0.0 7
 
1.2%
110.0 6
 
1.1%
97.5 6
 
1.1%
113.3 6
 
1.1%
10.0 6
 
1.1%
40.0 6
 
1.1%
Other values (317) 493
86.8%
ValueCountFrequency (%)
0.0 7
1.2%
6.7 1
 
0.2%
7.8 1
 
0.2%
10.0 6
1.1%
11.1 1
 
0.2%
12.2 1
 
0.2%
12.5 2
 
0.4%
13.3 1
 
0.2%
13.6 1
 
0.2%
14.3 1
 
0.2%
ValueCountFrequency (%)
1568.0 1
0.2%
1251.7 1
0.2%
1173.8 1
0.2%
1152.2 1
0.2%
1116.0 1
0.2%
1045.0 1
0.2%
890.0 1
0.2%
840.0 1
0.2%
662.9 1
0.2%
628.9 1
0.2%

풍향
Categorical

Distinct16
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
북서
83 
서
65 
서북서
60 
북북동
56 
북
55 
Other values (11)
249 

Length

Max length3
Median length2
Mean length2.1690141
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row서
2nd row서북서
3rd row서북서
4th row서
5th row서

Common Values

ValueCountFrequency (%)
북서 83
14.6%
서 65
11.4%
서북서 60
10.6%
북북동 56
9.9%
북 55
9.7%
북동 49
8.6%
북북서 45
7.9%
동북동 31
 
5.5%
남동 27
 
4.8%
동남동 27
 
4.8%
Other values (6) 70
12.3%

Length

2023-12-12T19:05:23.801530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
북서 83
14.6%
서 65
11.4%
서북서 60
10.6%
북북동 56
9.9%
북 55
9.7%
북동 49
8.6%
북북서 45
7.9%
동북동 31
 
5.5%
남동 27
 
4.8%
동남동 27
 
4.8%
Other values (6) 70
12.3%

풍속
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.92992958
Minimum0
Maximum6.4
Zeros13
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T19:05:23.969792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.3
median0.7
Q31.2
95-th percentile2.465
Maximum6.4
Range6.4
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.93254993
Coefficient of variation (CV)1.0028178
Kurtosis8.5248475
Mean0.92992958
Median Absolute Deviation (MAD)0.4
Skewness2.4698397
Sum528.2
Variance0.86964938
MonotonicityNot monotonic
2023-12-12T19:05:24.098428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.2 59
 
10.4%
0.3 49
 
8.6%
0.7 47
 
8.3%
0.1 45
 
7.9%
0.6 39
 
6.9%
0.8 37
 
6.5%
0.4 35
 
6.2%
0.9 32
 
5.6%
0.5 27
 
4.8%
1.1 18
 
3.2%
Other values (34) 180
31.7%
ValueCountFrequency (%)
0.0 13
 
2.3%
0.1 45
7.9%
0.2 59
10.4%
0.3 49
8.6%
0.4 35
6.2%
0.5 27
4.8%
0.6 39
6.9%
0.7 47
8.3%
0.8 37
6.5%
0.9 32
5.6%
ValueCountFrequency (%)
6.4 2
0.4%
5.5 1
0.2%
5.4 2
0.4%
4.9 1
0.2%
4.8 1
0.2%
4.7 1
0.2%
4.6 2
0.4%
4.5 1
0.2%
4.3 1
0.2%
4.0 1
0.2%

위도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
37.3
568 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37.3
2nd row37.3
3rd row37.3
4th row37.3
5th row37.3

Common Values

ValueCountFrequency (%)
37.3 568
100.0%

Length

2023-12-12T19:05:24.248905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:05:24.372072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37.3 568
100.0%

경도
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
126.8
565 
126.7
 
3

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row126.8
2nd row126.8
3rd row126.8
4th row126.8
5th row126.8

Common Values

ValueCountFrequency (%)
126.8 565
99.5%
126.7 3
 
0.5%

Length

2023-12-12T19:05:24.472812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:05:24.576288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
126.8 565
99.5%
126.7 3
 
0.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2023-11-03
568 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-03
2nd row2023-11-03
3rd row2023-11-03
4th row2023-11-03
5th row2023-11-03

Common Values

ValueCountFrequency (%)
2023-11-03 568
100.0%

Length

2023-12-12T19:05:24.689783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:05:24.800495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-03 568
100.0%

Interactions

2023-12-12T19:05:21.330244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.184033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.936295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.794298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.459928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.191114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:21.428365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.307576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.071468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.946608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.584953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.311471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:21.528818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.459774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.227288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.078551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.698898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.466510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:21.605314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.565099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.330942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.175132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.793928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.599447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:21.681047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.670536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.472936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.267437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.921436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.735264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:21.763879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:17.813734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:18.644334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:19.370117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.057719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:05:20.867185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:05:24.886087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도습도암모니아황화수소총휘발성유기화합물풍향풍속경도
온도1.0000.7050.3630.2220.4270.4570.5240.088
습도0.7051.0000.6070.1440.3610.4850.6050.228
암모니아0.3630.6071.0000.0000.0000.0000.3800.000
황화수소0.2220.1440.0001.0000.6160.2220.0000.000
총휘발성유기화합물0.4270.3610.0000.6161.0000.3130.3660.000
풍향0.4570.4850.0000.2220.3131.0000.5830.096
풍속0.5240.6050.3800.0000.3660.5831.0000.423
경도0.0880.2280.0000.0000.0000.0960.4231.000
2023-12-12T19:05:25.040805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
풍향경도
풍향1.0000.074
경도0.0741.000
2023-12-12T19:05:25.139403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
온도습도암모니아황화수소총휘발성유기화합물풍속풍향경도
온도1.000-0.2930.3270.1460.0160.4820.2270.094
습도-0.2931.0000.310-0.028-0.447-0.5720.2130.171
암모니아0.3270.3101.0000.117-0.4010.0040.0000.000
황화수소0.146-0.0280.1171.0000.107-0.0260.1020.000
총휘발성유기화합물0.016-0.447-0.4010.1071.0000.0320.1330.000
풍속0.482-0.5720.004-0.0260.0321.0000.2690.323
풍향0.2270.2130.0000.1020.1330.2691.0000.074
경도0.0940.1710.0000.0000.0000.3230.0741.000

Missing values

2023-12-12T19:05:21.875093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:05:22.022639image/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

측정일시온도습도암모니아황화수소총휘발성유기화합물풍향풍속위도경도데이터기준일자
02020-09-21 2:0025.590.693.64.040.0서1.537.3126.82023-11-03
12020-09-21 1:5525.590.9109.02.922.9서북서2.137.3126.82023-11-03
22020-09-21 1:5025.591.0117.32.020.0서북서2.437.3126.82023-11-03
32020-09-21 1:4525.690.8122.22.020.0서2.137.3126.82023-11-03
42020-09-21 1:4025.691.6145.32.020.0서1.737.3126.82023-11-03
52020-09-21 1:3525.591.9159.94.346.3서북서2.537.3126.82023-11-03
62020-09-21 1:3025.691.8168.05.050.0서2.837.3126.82023-11-03
72020-09-21 1:2525.792.2187.75.050.0서북서2.737.3126.82023-11-03
82020-09-21 1:2025.792.0192.73.934.4서4.637.3126.82023-11-03
92020-09-21 1:1525.893.0204.33.030.0서2.337.3126.82023-11-03
측정일시온도습도암모니아황화수소총휘발성유기화합물풍향풍속위도경도데이터기준일자
5582022-05-02 12:2518.741.35.91.185.0서북서2.137.3126.82023-11-03
5592022-05-02 12:2019.240.85.02.484.3북서2.337.3126.82023-11-03
5602022-05-02 12:1518.741.52.42.390.0서북서1.637.3126.82023-11-03
5612022-05-02 12:1019.240.22.93.387.5북서1.537.3126.82023-11-03
5622022-05-02 12:0519.438.75.03.987.5북서1.937.3126.82023-11-03
5632022-05-02 12:0018.938.95.32.391.4서북서2.037.3126.82023-11-03
5642022-05-02 11:5518.837.65.12.585.0서북서1.837.3126.82023-11-03
5652022-05-02 11:5018.739.83.32.490.0북서1.537.3126.82023-11-03
5662022-05-02 11:4517.945.93.22.3103.3북서2.037.3126.82023-11-03
5672022-05-02 11:0017.952.61.00.0250.0서북서1.837.3126.82023-11-03