Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells20000
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory888.9 KiB
Average record size in memory91.0 B

Variable types

Numeric7
DateTime1
Unsupported2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20464/S/1/datasetView.do

Alerts

모델명 is highly overall correlated with 시리얼High correlation
시리얼 is highly overall correlated with 모델명High correlation
온도(℃) is highly overall correlated with 습도(%)High correlation
습도(%) is highly overall correlated with 온도(℃)High correlation
이산화탄소 has 10000 (100.0%) missing valuesMissing
등록일시 has 10000 (100.0%) missing valuesMissing
모델명 is highly skewed (γ1 = 47.61498743)Skewed
시리얼 is highly skewed (γ1 = 46.85315405)Skewed
이산화탄소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등록일시 is an unsupported type, check if it needs cleaning or further analysisUnsupported
모델명 has 1026 (10.3%) zerosZeros
시리얼 has 972 (9.7%) zerosZeros

Reproduction

Analysis started2023-12-11 06:36:06.520068
Analysis finished2023-12-11 06:36:13.381267
Duration6.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관 명
Real number (ℝ)

Distinct281
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean308.2755
Minimum76
Maximum607
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:13.452945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum76
5-th percentile91
Q1182
median308
Q3418
95-th percentile524
Maximum607
Range531
Interquartile range (IQR)236

Descriptive statistics

Standard deviation141.09417
Coefficient of variation (CV)0.45768857
Kurtosis-0.97985419
Mean308.2755
Median Absolute Deviation (MAD)122
Skewness0.11453536
Sum3082755
Variance19907.566
MonotonicityNot monotonic
2023-12-11T15:36:13.585705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
254 48
 
0.5%
393 48
 
0.5%
447 47
 
0.5%
512 47
 
0.5%
467 46
 
0.5%
390 46
 
0.5%
282 46
 
0.5%
342 46
 
0.5%
497 45
 
0.4%
388 45
 
0.4%
Other values (271) 9536
95.4%
ValueCountFrequency (%)
76 22
0.2%
77 34
0.3%
78 34
0.3%
79 43
0.4%
80 36
0.4%
82 44
0.4%
83 41
0.4%
84 43
0.4%
85 42
0.4%
86 44
0.4%
ValueCountFrequency (%)
607 29
0.3%
606 39
0.4%
605 35
0.4%
604 40
0.4%
603 40
0.4%
602 34
0.3%
601 44
0.4%
600 35
0.4%
599 40
0.4%
532 15
 
0.1%

모델명
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct129
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.4056
Minimum0
Maximum4820
Zeros1026
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:13.968956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median15
Q327
95-th percentile48
Maximum4820
Range4820
Interquartile range (IQR)21

Descriptive statistics

Standard deviation96.435523
Coefficient of variation (CV)4.7259342
Kurtosis2340.7788
Mean20.4056
Median Absolute Deviation (MAD)10
Skewness47.614987
Sum204056
Variance9299.8101
MonotonicityNot monotonic
2023-12-11T15:36:14.131567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1026
 
10.3%
7 315
 
3.1%
11 309
 
3.1%
12 303
 
3.0%
2 301
 
3.0%
8 297
 
3.0%
4 297
 
3.0%
9 292
 
2.9%
14 288
 
2.9%
6 281
 
2.8%
Other values (119) 6291
62.9%
ValueCountFrequency (%)
0 1026
10.3%
1 198
 
2.0%
2 301
 
3.0%
3 247
 
2.5%
4 297
 
3.0%
5 247
 
2.5%
6 281
 
2.8%
7 315
 
3.1%
8 297
 
3.0%
9 292
 
2.9%
ValueCountFrequency (%)
4820 1
< 0.1%
4816 1
< 0.1%
4809 1
< 0.1%
4601 1
< 0.1%
331 1
< 0.1%
263 1
< 0.1%
235 1
< 0.1%
222 1
< 0.1%
174 1
< 0.1%
172 2
< 0.1%

시리얼
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct136
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.3268
Minimum0
Maximum4820
Zeros972
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:14.275901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median17
Q331
95-th percentile57
Maximum4820
Range4820
Interquartile range (IQR)24

Descriptive statistics

Standard deviation96.900379
Coefficient of variation (CV)4.1540365
Kurtosis2290.4874
Mean23.3268
Median Absolute Deviation (MAD)11
Skewness46.853154
Sum233268
Variance9389.6834
MonotonicityNot monotonic
2023-12-11T15:36:14.432323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 972
 
9.7%
8 267
 
2.7%
10 264
 
2.6%
5 260
 
2.6%
12 259
 
2.6%
11 255
 
2.5%
13 255
 
2.5%
7 254
 
2.5%
3 254
 
2.5%
9 252
 
2.5%
Other values (126) 6708
67.1%
ValueCountFrequency (%)
0 972
9.7%
1 168
 
1.7%
2 221
 
2.2%
3 254
 
2.5%
4 206
 
2.1%
5 260
 
2.6%
6 239
 
2.4%
7 254
 
2.5%
8 267
 
2.7%
9 252
 
2.5%
ValueCountFrequency (%)
4820 1
< 0.1%
4816 1
< 0.1%
4809 1
< 0.1%
4601 1
< 0.1%
370 1
< 0.1%
297 1
< 0.1%
261 1
< 0.1%
239 1
< 0.1%
191 1
< 0.1%
190 2
< 0.1%

초미세먼지(㎍/㎥)
Real number (ℝ)

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.6358
Minimum0
Maximum36
Zeros18
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:14.574497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q118
median21
Q324
95-th percentile28
Maximum36
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.7605448
Coefficient of variation (CV)0.27915297
Kurtosis1.2313728
Mean20.6358
Median Absolute Deviation (MAD)3
Skewness-0.92907346
Sum206358
Variance33.183877
MonotonicityNot monotonic
2023-12-11T15:36:14.707296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
22 915
 
9.2%
21 859
 
8.6%
23 849
 
8.5%
24 772
 
7.7%
20 700
 
7.0%
25 625
 
6.2%
19 618
 
6.2%
18 565
 
5.7%
26 562
 
5.6%
27 493
 
4.9%
Other values (27) 3042
30.4%
ValueCountFrequency (%)
0 18
 
0.2%
1 45
0.4%
2 44
 
0.4%
3 46
0.5%
4 55
0.5%
5 43
 
0.4%
6 57
0.6%
7 57
0.6%
8 70
0.7%
9 112
1.1%
ValueCountFrequency (%)
36 5
 
0.1%
35 6
 
0.1%
34 7
 
0.1%
33 24
 
0.2%
32 30
 
0.3%
31 74
 
0.7%
30 151
 
1.5%
29 172
 
1.7%
28 301
3.0%
27 493
4.9%

미세먼지(㎍/㎥)
Real number (ℝ)

Distinct58
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.7533
Minimum4
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:14.873331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile14
Q120
median25
Q331
95-th percentile41
Maximum62
Range58
Interquartile range (IQR)11

Descriptive statistics

Standard deviation8.2427564
Coefficient of variation (CV)0.32006603
Kurtosis0.52550719
Mean25.7533
Median Absolute Deviation (MAD)5
Skewness0.66081163
Sum257533
Variance67.943033
MonotonicityNot monotonic
2023-12-11T15:36:15.049456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 552
 
5.5%
25 521
 
5.2%
20 506
 
5.1%
26 497
 
5.0%
19 485
 
4.9%
22 484
 
4.8%
28 472
 
4.7%
21 462
 
4.6%
23 448
 
4.5%
27 442
 
4.4%
Other values (48) 5131
51.3%
ValueCountFrequency (%)
4 1
 
< 0.1%
5 2
 
< 0.1%
6 6
 
0.1%
7 5
 
0.1%
8 5
 
0.1%
9 38
 
0.4%
10 45
 
0.4%
11 69
0.7%
12 99
1.0%
13 133
1.3%
ValueCountFrequency (%)
62 1
 
< 0.1%
61 1
 
< 0.1%
59 2
 
< 0.1%
58 3
 
< 0.1%
57 7
0.1%
56 4
 
< 0.1%
55 1
 
< 0.1%
54 6
0.1%
53 12
0.1%
52 11
0.1%

온도(℃)
Real number (ℝ)

HIGH CORRELATION 

Distinct429
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.6665
Minimum0
Maximum499
Zeros87
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:15.212044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q131
median51
Q365
95-th percentile215
Maximum499
Range499
Interquartile range (IQR)34

Descriptive statistics

Standard deviation80.326689
Coefficient of variation (CV)1.1870968
Kurtosis14.647394
Mean67.6665
Median Absolute Deviation (MAD)17
Skewness3.6931127
Sum676665
Variance6452.3769
MonotonicityNot monotonic
2023-12-11T15:36:15.354502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 409
 
4.1%
50 389
 
3.9%
52 283
 
2.8%
53 235
 
2.4%
55 232
 
2.3%
56 230
 
2.3%
57 230
 
2.3%
58 226
 
2.3%
54 209
 
2.1%
59 193
 
1.9%
Other values (419) 7364
73.6%
ValueCountFrequency (%)
0 87
0.9%
1 29
 
0.3%
2 18
 
0.2%
3 37
0.4%
4 27
 
0.3%
5 33
 
0.3%
6 30
 
0.3%
7 29
 
0.3%
8 31
 
0.3%
9 50
0.5%
ValueCountFrequency (%)
499 82
0.8%
498 5
 
0.1%
497 2
 
< 0.1%
496 4
 
< 0.1%
495 5
 
0.1%
494 3
 
< 0.1%
493 2
 
< 0.1%
491 1
 
< 0.1%
490 3
 
< 0.1%
488 4
 
< 0.1%

습도(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct2085
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean977.2943
Minimum0
Maximum9700
Zeros40
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size107.7 KiB
2023-12-11T15:36:15.499902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile429.95
Q1573
median718
Q31101
95-th percentile2471.4
Maximum9700
Range9700
Interquartile range (IQR)528

Descriptive statistics

Standard deviation742.59428
Coefficient of variation (CV)0.75984714
Kurtosis20.915768
Mean977.2943
Median Absolute Deviation (MAD)189
Skewness3.5480313
Sum9772943
Variance551446.26
MonotonicityNot monotonic
2023-12-11T15:36:15.667827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400 151
 
1.5%
0 40
 
0.4%
577 30
 
0.3%
557 29
 
0.3%
631 28
 
0.3%
636 28
 
0.3%
550 26
 
0.3%
589 26
 
0.3%
626 26
 
0.3%
757 26
 
0.3%
Other values (2075) 9590
95.9%
ValueCountFrequency (%)
0 40
0.4%
279 1
 
< 0.1%
320 1
 
< 0.1%
334 1
 
< 0.1%
344 1
 
< 0.1%
364 1
 
< 0.1%
371 1
 
< 0.1%
377 1
 
< 0.1%
378 1
 
< 0.1%
381 1
 
< 0.1%
ValueCountFrequency (%)
9700 1
< 0.1%
9540 1
< 0.1%
9190 1
< 0.1%
9130 1
< 0.1%
9070 1
< 0.1%
8441 1
< 0.1%
8308 1
< 0.1%
8220 1
< 0.1%
7345 1
< 0.1%
7322 1
< 0.1%

총 유기 휘발성 화합물
Date

Distinct2272
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size97.9 KiB
Minimum2022-12-26 00:22:08
Maximum2022-12-28 23:22:43
2023-12-11T15:36:15.807028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:15.944437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

이산화탄소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size107.7 KiB

등록일시
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size107.7 KiB

Interactions

2023-12-11T15:36:12.445074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:07.836329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.578657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.351294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.184630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.024502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.764574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.533633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:07.930241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.680766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.518665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.332855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.142313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.862607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.622929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.032691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.789101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.626626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.458247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.236483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.951814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.726949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.140762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.904319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.728815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.582798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.333091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.063695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.821637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.244323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.039679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.857740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.711370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.452264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.173269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.923394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.331676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.162849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.952960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.825129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.575264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.263172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:13.017927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:08.440019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:09.257496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.072910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:10.935277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:11.669826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T15:36:12.350095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T15:36:16.059868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관 명모델명시리얼초미세먼지(㎍/㎥)미세먼지(㎍/㎥)온도(℃)습도(%)
기관 명1.0000.0550.0550.4650.3400.2220.205
모델명0.0551.0000.9810.0680.0000.0000.000
시리얼0.0550.9811.0000.0680.0000.0000.000
초미세먼지(㎍/㎥)0.4650.0680.0681.0000.5400.2810.276
미세먼지(㎍/㎥)0.3400.0000.0000.5401.0000.3100.305
온도(℃)0.2220.0000.0000.2810.3101.0000.709
습도(%)0.2050.0000.0000.2760.3050.7091.000
2023-12-11T15:36:16.193686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관 명모델명시리얼초미세먼지(㎍/㎥)미세먼지(㎍/㎥)온도(℃)습도(%)
기관 명1.0000.0620.053-0.141-0.001-0.149-0.047
모델명0.0621.0000.998-0.283-0.137-0.217-0.154
시리얼0.0530.9981.000-0.296-0.129-0.219-0.157
초미세먼지(㎍/㎥)-0.141-0.283-0.2961.000-0.3830.2510.258
미세먼지(㎍/㎥)-0.001-0.137-0.129-0.3831.0000.2870.278
온도(℃)-0.149-0.217-0.2190.2510.2871.0000.713
습도(%)-0.047-0.154-0.1570.2580.2780.7131.000

Missing values

2023-12-11T15:36:13.141203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T15:36:13.315557image/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

기관 명모델명시리얼초미세먼지(㎍/㎥)미세먼지(㎍/㎥)온도(℃)습도(%)총 유기 휘발성 화합물이산화탄소등록일시
중랑구AN-EMD-TA100L46736402326277152022-12-26 08:22:35<NA><NA>
AN-EMD-TA100L4472225144440115082022-12-27 21:22:36<NA><NA>
AN-EMD-TA100L51112214237232252022-12-27 18:22:40<NA><NA>
AN-EMD-TA100L852730262928923972022-12-26 19:22:10<NA><NA>
AN-EMD-TA100L33334263822616202022-12-27 18:22:29<NA><NA>
AN-EMD-TA100L164232622927282022-12-27 11:22:17<NA><NA>
AN-EMD-TA100L24336401326495672022-12-27 08:22:21<NA><NA>
AN-EMD-TA100L400111225296515582022-12-26 16:22:31<NA><NA>
AN-EMD-TA100L48041462822525292022-12-28 04:23:39<NA><NA>
AN-EMD-TA100L88101125268519902022-12-26 12:22:10<NA><NA>
기관 명모델명시리얼초미세먼지(㎍/㎥)미세먼지(㎍/㎥)온도(℃)습도(%)총 유기 휘발성 화합물이산화탄소등록일시
중랑구AN-EMD-TA100L997921371476642022-12-28 20:22:14<NA><NA>
AN-EMD-TA100L9111263922231522022-12-26 14:22:11<NA><NA>
AN-EMD-TA100L15744512314185572022-12-27 07:22:16<NA><NA>
AN-EMD-TA100L311212527258123502022-12-26 13:22:25<NA><NA>
AN-EMD-TA100L415221630536232022-12-28 05:22:34<NA><NA>
AN-EMD-TA100L12745222813220752022-12-27 15:22:15<NA><NA>
AN-EMD-TA100L33501204020033592022-12-27 16:22:28<NA><NA>
AN-EMD-TA100L4304046631737792022-12-27 23:22:34<NA><NA>
AN-EMD-TA100L21518202027295362022-12-27 06:22:20<NA><NA>
AN-EMD-TA100L3691720927244032022-12-28 17:22:32<NA><NA>