Overview

Dataset statistics

Number of variables13
Number of observations2367
Missing cells8820
Missing cells (%)28.7%
Duplicate rows7
Duplicate rows (%)0.3%
Total size in memory242.8 KiB
Average record size in memory105.1 B

Variable types

Text10
DateTime1
Categorical1
Unsupported1

Dataset

Description대기질 예보통보 조회
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=2866

Alerts

Dataset has 7 (0.3%) duplicate rowsDuplicates
행동요령 has 2367 (100.0%) missing valuesMissing
첨부파일명1 has 1086 (45.9%) missing valuesMissing
첨부파일명2 has 1093 (46.2%) missing valuesMissing
첨부파일명3 has 1086 (45.9%) missing valuesMissing
첨부파일명4 has 1086 (45.9%) missing valuesMissing
첨부파일명5 has 968 (40.9%) missing valuesMissing
첨부파일명6 has 1086 (45.9%) missing valuesMissing
행동요령 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 11:51:58.024764
Analysis finished2024-03-13 11:51:59.581685
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct376
Distinct (%)16.0%
Missing23
Missing (%)1.0%
Memory size18.6 KiB
2024-03-13T20:51:59.936903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length250
Median length160
Mean length60.258532
Min length40

Characters and Unicode

Total characters141246
Distinct characters193
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)2.0%

Sample

1st row○ [미세먼지] 대부분 중서부지역과 일부 남부지역은 전일 미세먼지가 잔류하고 대기 정체와 기류 수렴으로 국내 발생 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.
2nd row○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.
3rd row○ [미세먼지] 대부분 중서부지역과 일부 남부지역은 전일 미세먼지가 잔류하고 대기 정체와 기류 수렴으로 국내 발생 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.
4th row○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.
5th row○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.
ValueCountFrequency (%)
대기 2482
 
7.6%
것으로 2340
 
7.2%
예상됩니다 2332
 
7.2%
2319
 
7.1%
미세먼지 1952
 
6.0%
원활한 1484
 
4.6%
청정할 1104
 
3.4%
대체로 1012
 
3.1%
농도가 980
 
3.0%
확산으로 978
 
3.0%
Other values (287) 15620
47.9%
2024-03-13T20:52:00.623968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30368
21.5%
5900
 
4.2%
5194
 
3.7%
4784
 
3.4%
4073
 
2.9%
3817
 
2.7%
3068
 
2.2%
2776
 
2.0%
2774
 
2.0%
2774
 
2.0%
Other values (183) 75718
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100237
71.0%
Space Separator 30368
 
21.5%
Other Punctuation 3340
 
2.4%
Close Punctuation 2378
 
1.7%
Open Punctuation 2378
 
1.7%
Other Symbol 2319
 
1.6%
Decimal Number 152
 
0.1%
Uppercase Letter 52
 
< 0.1%
Dash Punctuation 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5900
 
5.9%
5194
 
5.2%
4784
 
4.8%
4073
 
4.1%
3817
 
3.8%
3068
 
3.1%
2776
 
2.8%
2774
 
2.8%
2774
 
2.8%
2622
 
2.6%
Other values (162) 62455
62.3%
Decimal Number
ValueCountFrequency (%)
1 56
36.8%
0 32
21.1%
2 30
19.7%
8 8
 
5.3%
7 6
 
3.9%
5 6
 
3.9%
3 6
 
3.9%
4 4
 
2.6%
9 4
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 2376
71.1%
' 944
 
28.3%
20
 
0.6%
Close Punctuation
ValueCountFrequency (%)
] 2324
97.7%
) 54
 
2.3%
Open Punctuation
ValueCountFrequency (%)
[ 2324
97.7%
( 54
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
P 26
50.0%
M 26
50.0%
Space Separator
ValueCountFrequency (%)
30368
100.0%
Other Symbol
ValueCountFrequency (%)
2319
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100237
71.0%
Common 40957
29.0%
Latin 52
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5900
 
5.9%
5194
 
5.2%
4784
 
4.8%
4073
 
4.1%
3817
 
3.8%
3068
 
3.1%
2776
 
2.8%
2774
 
2.8%
2774
 
2.8%
2622
 
2.6%
Other values (162) 62455
62.3%
Common
ValueCountFrequency (%)
30368
74.1%
. 2376
 
5.8%
] 2324
 
5.7%
[ 2324
 
5.7%
2319
 
5.7%
' 944
 
2.3%
1 56
 
0.1%
( 54
 
0.1%
) 54
 
0.1%
0 32
 
0.1%
Other values (9) 106
 
0.3%
Latin
ValueCountFrequency (%)
P 26
50.0%
M 26
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100232
71.0%
ASCII 38670
 
27.4%
Geometric Shapes 2319
 
1.6%
Punctuation 20
 
< 0.1%
Compat Jamo 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30368
78.5%
. 2376
 
6.1%
] 2324
 
6.0%
[ 2324
 
6.0%
' 944
 
2.4%
1 56
 
0.1%
( 54
 
0.1%
) 54
 
0.1%
0 32
 
0.1%
2 30
 
0.1%
Other values (9) 108
 
0.3%
Hangul
ValueCountFrequency (%)
5900
 
5.9%
5194
 
5.2%
4784
 
4.8%
4073
 
4.1%
3817
 
3.8%
3068
 
3.1%
2776
 
2.8%
2774
 
2.8%
2774
 
2.8%
2622
 
2.6%
Other values (161) 62450
62.3%
Geometric Shapes
ValueCountFrequency (%)
2319
100.0%
Punctuation
ValueCountFrequency (%)
20
100.0%
Compat Jamo
ValueCountFrequency (%)
5
100.0%
Distinct546
Distinct (%)23.1%
Missing6
Missing (%)0.3%
Memory size18.6 KiB
Minimum2022-03-11 00:00:00
Maximum2024-01-07 00:00:00
2024-03-13T20:52:00.808073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:52:00.971030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct715
Distinct (%)30.3%
Missing6
Missing (%)0.3%
Memory size18.6 KiB
2024-03-13T20:52:01.245614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length175
Median length137
Mean length137.4515
Min length137

Characters and Unicode

Total characters324523
Distinct characters33
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

Unique498 ?
Unique (%)21.1%

Sample

1st row서울 : 보통제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 나쁨세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 보통인천 : 나쁨
2nd row서울 : 보통제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통
3rd row서울 : 나쁨제주 : 보통전남 : 보통전북 : 나쁨광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 나쁨부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 나쁨대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨
4th row서울 : 나쁨제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 나쁨세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨
5th row서울 : 보통제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통
ValueCountFrequency (%)
44859
48.7%
서울 2361
 
2.6%
좋음전남 1531
 
1.7%
좋음영서 1511
 
1.6%
좋음경북 1431
 
1.6%
좋음전북 1412
 
1.5%
좋음충남 1351
 
1.5%
좋음경남 1285
 
1.4%
좋음대구 1284
 
1.4%
좋음울산 1278
 
1.4%
Other values (87) 33776
36.7%
2024-03-13T20:52:01.699280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89718
27.6%
: 44859
13.8%
23040
 
7.1%
22603
 
7.0%
18515
 
5.7%
18078
 
5.6%
9444
 
2.9%
9444
 
2.9%
9444
 
2.9%
7083
 
2.2%
Other values (23) 72295
22.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189946
58.5%
Space Separator 89718
27.6%
Other Punctuation 44859
 
13.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23040
 
12.1%
22603
 
11.9%
18515
 
9.7%
18078
 
9.5%
9444
 
5.0%
9444
 
5.0%
9444
 
5.0%
7083
 
3.7%
7083
 
3.7%
4722
 
2.5%
Other values (21) 60490
31.8%
Space Separator
ValueCountFrequency (%)
89718
100.0%
Other Punctuation
ValueCountFrequency (%)
: 44859
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189946
58.5%
Common 134577
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23040
 
12.1%
22603
 
11.9%
18515
 
9.7%
18078
 
9.5%
9444
 
5.0%
9444
 
5.0%
9444
 
5.0%
7083
 
3.7%
7083
 
3.7%
4722
 
2.5%
Other values (21) 60490
31.8%
Common
ValueCountFrequency (%)
89718
66.7%
: 44859
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189946
58.5%
ASCII 134577
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89718
66.7%
: 44859
33.3%
Hangul
ValueCountFrequency (%)
23040
 
12.1%
22603
 
11.9%
18515
 
9.7%
18078
 
9.5%
9444
 
5.0%
9444
 
5.0%
9444
 
5.0%
7083
 
3.7%
7083
 
3.7%
4722
 
2.5%
Other values (21) 60490
31.8%

통보코드
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.6 KiB
PM10
983 
PM25
983 
O3
395 
<NA>
 
6

Length

Max length4
Median length4
Mean length3.6662442
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPM10
2nd rowPM10
3rd rowPM25
4th rowPM25
5th rowPM10

Common Values

ValueCountFrequency (%)
PM10 983
41.5%
PM25 983
41.5%
O3 395
16.7%
<NA> 6
 
0.3%

Length

2024-03-13T20:52:01.860446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:52:01.988611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pm10 983
41.5%
pm25 983
41.5%
o3 395
16.7%
na 6
 
0.3%
Distinct486
Distinct (%)20.6%
Missing7
Missing (%)0.3%
Memory size18.6 KiB
2024-03-13T20:52:02.228045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length151
Median length140
Mean length47.460169
Min length25

Characters and Unicode

Total characters112006
Distinct characters118
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)6.6%

Sample

1st row○ [미세먼지] 수도권·세종·충북·충남·전북·대구는 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 대전·부산·울산·경북은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.
2nd row○ [미세먼지] 수도권·충북은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 대전·세종·충남은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.
3rd row○ [미세먼지] 수도권·세종·충북·충남·전북·대구는 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 대전·부산·울산·경북은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.
4th row○ [미세먼지] 수도권·충북은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 대전·세종·충남은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.
5th row○ [미세먼지] 수도권·충북·충남은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 세종·전북·대구는 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.
ValueCountFrequency (%)
예상됩니다 2900
14.0%
2351
11.4%
미세먼지 1964
 
9.5%
1760
 
8.5%
권역이 1752
 
8.5%
좋음'∼'보통'으로 1156
 
5.6%
나쁨 1103
 
5.3%
보통'으로 676
 
3.3%
권역은 571
 
2.8%
밖의 571
 
2.8%
Other values (510) 5842
28.3%
2024-03-13T20:52:02.683525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18338
 
16.4%
' 9338
 
8.3%
3472
 
3.1%
3416
 
3.0%
3396
 
3.0%
3396
 
3.0%
· 3236
 
2.9%
2932
 
2.6%
. 2912
 
2.6%
2912
 
2.6%
Other values (108) 58658
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69790
62.3%
Space Separator 18338
 
16.4%
Other Punctuation 15486
 
13.8%
Open Punctuation 2386
 
2.1%
Close Punctuation 2386
 
2.1%
Other Symbol 2351
 
2.1%
Math Symbol 1163
 
1.0%
Decimal Number 60
 
0.1%
Uppercase Letter 16
 
< 0.1%
Final Punctuation 14
 
< 0.1%
Other values (2) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3472
 
5.0%
3416
 
4.9%
3396
 
4.9%
3396
 
4.9%
2932
 
4.2%
2912
 
4.2%
2902
 
4.2%
2900
 
4.2%
2784
 
4.0%
2333
 
3.3%
Other values (87) 39347
56.4%
Decimal Number
ValueCountFrequency (%)
1 20
33.3%
7 12
20.0%
4 10
16.7%
2 10
16.7%
0 8
 
13.3%
Other Punctuation
ValueCountFrequency (%)
' 9338
60.3%
· 3236
 
20.9%
. 2912
 
18.8%
Open Punctuation
ValueCountFrequency (%)
[ 2360
98.9%
( 26
 
1.1%
Close Punctuation
ValueCountFrequency (%)
] 2360
98.9%
) 26
 
1.1%
Math Symbol
ValueCountFrequency (%)
1162
99.9%
~ 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
P 8
50.0%
M 8
50.0%
Space Separator
ValueCountFrequency (%)
18338
100.0%
Other Symbol
ValueCountFrequency (%)
2351
100.0%
Final Punctuation
ValueCountFrequency (%)
14
100.0%
Initial Punctuation
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69790
62.3%
Common 42200
37.7%
Latin 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3472
 
5.0%
3416
 
4.9%
3396
 
4.9%
3396
 
4.9%
2932
 
4.2%
2912
 
4.2%
2902
 
4.2%
2900
 
4.2%
2784
 
4.0%
2333
 
3.3%
Other values (87) 39347
56.4%
Common
ValueCountFrequency (%)
18338
43.5%
' 9338
22.1%
· 3236
 
7.7%
. 2912
 
6.9%
[ 2360
 
5.6%
] 2360
 
5.6%
2351
 
5.6%
1162
 
2.8%
) 26
 
0.1%
( 26
 
0.1%
Other values (9) 91
 
0.2%
Latin
ValueCountFrequency (%)
P 8
50.0%
M 8
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69781
62.3%
ASCII 35439
31.6%
None 3236
 
2.9%
Geometric Shapes 2351
 
2.1%
Math Operators 1162
 
1.0%
Punctuation 28
 
< 0.1%
Compat Jamo 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18338
51.7%
' 9338
26.3%
. 2912
 
8.2%
[ 2360
 
6.7%
] 2360
 
6.7%
) 26
 
0.1%
( 26
 
0.1%
1 20
 
0.1%
7 12
 
< 0.1%
4 10
 
< 0.1%
Other values (6) 37
 
0.1%
Hangul
ValueCountFrequency (%)
3472
 
5.0%
3416
 
4.9%
3396
 
4.9%
3396
 
4.9%
2932
 
4.2%
2912
 
4.2%
2902
 
4.2%
2900
 
4.2%
2784
 
4.0%
2333
 
3.3%
Other values (86) 39338
56.4%
None
ValueCountFrequency (%)
· 3236
100.0%
Geometric Shapes
ValueCountFrequency (%)
2351
100.0%
Math Operators
ValueCountFrequency (%)
1162
100.0%
Punctuation
ValueCountFrequency (%)
14
50.0%
14
50.0%
Compat Jamo
ValueCountFrequency (%)
9
100.0%
Distinct487
Distinct (%)20.6%
Missing6
Missing (%)0.3%
Memory size18.6 KiB
2024-03-13T20:52:02.989187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters40137
Distinct characters15
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

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-03-11 05시 발표
2nd row2022-03-11 05시 발표
3rd row2022-03-11 05시 발표
4th row2022-03-11 05시 발표
5th row2022-03-12 05시 발표
ValueCountFrequency (%)
발표 2361
33.3%
05시 2322
32.8%
11시 32
 
0.5%
2022-07-12 17
 
0.2%
2022-04-11 12
 
0.2%
2022-05-09 10
 
0.1%
2022-06-30 9
 
0.1%
2022-10-10 9
 
0.1%
2022-05-05 9
 
0.1%
2022-05-23 9
 
0.1%
Other values (476) 2293
32.4%
2024-03-13T20:52:03.459341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7555
18.8%
2 7099
17.7%
- 4722
11.8%
4722
11.8%
5 2783
 
6.9%
2361
 
5.9%
2361
 
5.9%
2361
 
5.9%
1 2075
 
5.2%
3 1735
 
4.3%
Other values (5) 2363
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23610
58.8%
Other Letter 7083
 
17.6%
Dash Punctuation 4722
 
11.8%
Space Separator 4722
 
11.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7555
32.0%
2 7099
30.1%
5 2783
 
11.8%
1 2075
 
8.8%
3 1735
 
7.3%
6 512
 
2.2%
8 509
 
2.2%
7 499
 
2.1%
9 456
 
1.9%
4 387
 
1.6%
Other Letter
ValueCountFrequency (%)
2361
33.3%
2361
33.3%
2361
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 4722
100.0%
Space Separator
ValueCountFrequency (%)
4722
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33054
82.4%
Hangul 7083
 
17.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7555
22.9%
2 7099
21.5%
- 4722
14.3%
4722
14.3%
5 2783
 
8.4%
1 2075
 
6.3%
3 1735
 
5.2%
6 512
 
1.5%
8 509
 
1.5%
7 499
 
1.5%
Other values (2) 843
 
2.6%
Hangul
ValueCountFrequency (%)
2361
33.3%
2361
33.3%
2361
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33054
82.4%
Hangul 7083
 
17.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7555
22.9%
2 7099
21.5%
- 4722
14.3%
4722
14.3%
5 2783
 
8.4%
1 2075
 
6.3%
3 1735
 
5.2%
6 512
 
1.5%
8 509
 
1.5%
7 499
 
1.5%
Other values (2) 843
 
2.6%
Hangul
ValueCountFrequency (%)
2361
33.3%
2361
33.3%
2361
33.3%

행동요령
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2367
Missing (%)100.0%
Memory size20.9 KiB

첨부파일명1
Text

MISSING 

Distinct761
Distinct (%)59.4%
Missing1086
Missing (%)45.9%
Memory size18.6 KiB
2024-03-13T20:52:03.812206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length116
Mean length114.98439
Min length52

Characters and Unicode

Total characters147295
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)20.5%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031100.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031100.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031200.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031200.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032400.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm10.1hsp.2022050521.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm10.1hsp.2022063021.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm10.1hsp.2022041100.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm10.1hsp.2022101021.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.pm10.1hsp.2022050421.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.pm10.1hsp.2022052321.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm10.1hsp.2022071221.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm10.1hsp.2022110821.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022063003.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052303.png 3
 
0.2%
Other values (751) 1243
97.0%
2024-03-13T20:52:04.301201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14465
 
9.8%
2 12727
 
8.6%
. 11523
 
7.8%
/ 8964
 
6.1%
1 8922
 
6.1%
r 6405
 
4.3%
e 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 63795
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61206
41.6%
Decimal Number 45393
30.8%
Other Punctuation 23049
 
15.6%
Uppercase Letter 12663
 
8.6%
Connector Punctuation 3703
 
2.5%
Math Symbol 1281
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 6405
 
10.5%
e 6405
 
10.5%
a 5124
 
8.4%
p 5122
 
8.4%
o 3843
 
6.3%
i 3843
 
6.3%
w 3843
 
6.3%
h 3704
 
6.1%
k 2562
 
4.2%
f 2562
 
4.2%
Other values (9) 17793
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2561
20.2%
I 1418
11.2%
Q 1280
10.1%
F 1280
10.1%
A 1280
10.1%
K 1143
9.0%
U 1143
9.0%
P 1004
 
7.9%
M 1004
 
7.9%
O 276
 
2.2%
Other values (2) 274
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 14465
31.9%
2 12727
28.0%
1 8922
19.7%
3 3251
 
7.2%
9 2090
 
4.6%
5 838
 
1.8%
8 835
 
1.8%
6 820
 
1.8%
7 805
 
1.8%
4 640
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11523
50.0%
/ 8964
38.9%
? 1281
 
5.6%
: 1281
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 3703
100.0%
Math Symbol
ValueCountFrequency (%)
= 1281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73869
50.2%
Common 73426
49.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 6405
 
8.7%
e 6405
 
8.7%
a 5124
 
6.9%
p 5122
 
6.9%
o 3843
 
5.2%
i 3843
 
5.2%
w 3843
 
5.2%
h 3704
 
5.0%
k 2562
 
3.5%
f 2562
 
3.5%
Other values (21) 30456
41.2%
Common
ValueCountFrequency (%)
0 14465
19.7%
2 12727
17.3%
. 11523
15.7%
/ 8964
12.2%
1 8922
12.2%
_ 3703
 
5.0%
3 3251
 
4.4%
9 2090
 
2.8%
= 1281
 
1.7%
? 1281
 
1.7%
Other values (6) 5219
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14465
 
9.8%
2 12727
 
8.6%
. 11523
 
7.8%
/ 8964
 
6.1%
1 8922
 
6.1%
r 6405
 
4.3%
e 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 63795
43.3%

첨부파일명2
Text

MISSING 

Distinct761
Distinct (%)59.7%
Missing1093
Missing (%)46.2%
Memory size18.6 KiB
2024-03-13T20:52:04.670237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length116
Mean length114.97881
Min length52

Characters and Unicode

Total characters146483
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)20.6%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031106.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031106.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031206.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031206.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032406.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm10.1hsp.2022041106.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm10.1hsp.2022050603.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022063006.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm10.1hsp.2022070103.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052306.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm10.1hsp.2022071303.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm10.1hsp.2022101103.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.o3.1hsp.2022050406.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm10.1hsp.2022110903.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.o3.1hsp.2022101006.png 3
 
0.2%
Other values (751) 1243
97.6%
2024-03-13T20:52:05.180582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13450
 
9.2%
2 12617
 
8.6%
. 11460
 
7.8%
/ 8915
 
6.1%
1 8850
 
6.0%
r 6370
 
4.3%
e 6370
 
4.3%
a 5096
 
3.5%
p 5094
 
3.5%
w 3822
 
2.6%
Other values (37) 64439
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60870
41.6%
Decimal Number 45141
30.8%
Other Punctuation 22923
 
15.6%
Uppercase Letter 12593
 
8.6%
Connector Punctuation 3682
 
2.5%
Math Symbol 1274
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 6370
 
10.5%
e 6370
 
10.5%
a 5096
 
8.4%
p 5094
 
8.4%
w 3822
 
6.3%
o 3822
 
6.3%
i 3822
 
6.3%
h 3683
 
6.1%
f 2548
 
4.2%
l 2548
 
4.2%
Other values (9) 17695
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2547
20.2%
I 1411
11.2%
Q 1273
10.1%
F 1273
10.1%
A 1273
10.1%
K 1136
9.0%
U 1136
9.0%
M 997
 
7.9%
P 997
 
7.9%
O 276
 
2.2%
Other values (2) 274
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 13450
29.8%
2 12617
28.0%
1 8850
19.6%
3 2974
 
6.6%
9 2097
 
4.6%
6 2053
 
4.5%
8 830
 
1.8%
5 827
 
1.8%
7 804
 
1.8%
4 639
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11460
50.0%
/ 8915
38.9%
? 1274
 
5.6%
: 1274
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 3682
100.0%
Math Symbol
ValueCountFrequency (%)
= 1274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73463
50.2%
Common 73020
49.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 6370
 
8.7%
e 6370
 
8.7%
a 5096
 
6.9%
p 5094
 
6.9%
w 3822
 
5.2%
o 3822
 
5.2%
i 3822
 
5.2%
h 3683
 
5.0%
f 2548
 
3.5%
l 2548
 
3.5%
Other values (21) 30288
41.2%
Common
ValueCountFrequency (%)
0 13450
18.4%
2 12617
17.3%
. 11460
15.7%
/ 8915
12.2%
1 8850
12.1%
_ 3682
 
5.0%
3 2974
 
4.1%
9 2097
 
2.9%
6 2053
 
2.8%
= 1274
 
1.7%
Other values (6) 5648
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146483
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13450
 
9.2%
2 12617
 
8.6%
. 11460
 
7.8%
/ 8915
 
6.1%
1 8850
 
6.0%
r 6370
 
4.3%
e 6370
 
4.3%
a 5096
 
3.5%
p 5094
 
3.5%
w 3822
 
2.6%
Other values (37) 64439
44.0%

첨부파일명3
Text

MISSING 

Distinct761
Distinct (%)59.4%
Missing1086
Missing (%)45.9%
Memory size18.6 KiB
2024-03-13T20:52:05.509498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length116
Mean length114.98439
Min length52

Characters and Unicode

Total characters147295
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)20.5%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031112.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031112.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031212.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031212.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032412.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm10.1hsp.2022050609.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm10.1hsp.2022070109.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm10.1hsp.2022041112.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm10.1hsp.2022101109.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.pm10.1hsp.2022050509.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.pm10.1hsp.2022052409.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm10.1hsp.2022071309.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm10.1hsp.2022110909.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022063009.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052309.png 3
 
0.2%
Other values (751) 1243
97.0%
2024-03-13T20:52:06.169261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13653
 
9.3%
0 12557
 
8.5%
. 11523
 
7.8%
1 9874
 
6.7%
/ 8964
 
6.1%
r 6405
 
4.3%
e 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 63825
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61206
41.6%
Decimal Number 45393
30.8%
Other Punctuation 23049
 
15.6%
Uppercase Letter 12663
 
8.6%
Connector Punctuation 3703
 
2.5%
Math Symbol 1281
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 6405
 
10.5%
e 6405
 
10.5%
a 5124
 
8.4%
p 5122
 
8.4%
o 3843
 
6.3%
i 3843
 
6.3%
w 3843
 
6.3%
h 3704
 
6.1%
k 2562
 
4.2%
f 2562
 
4.2%
Other values (9) 17793
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2561
20.2%
I 1418
11.2%
Q 1280
10.1%
F 1280
10.1%
A 1280
10.1%
K 1143
9.0%
U 1143
9.0%
P 1004
 
7.9%
M 1004
 
7.9%
O 276
 
2.2%
Other values (2) 274
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 13653
30.1%
0 12557
27.7%
1 9874
21.8%
3 2955
 
6.5%
9 2400
 
5.3%
5 852
 
1.9%
8 831
 
1.8%
6 820
 
1.8%
7 809
 
1.8%
4 642
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11523
50.0%
/ 8964
38.9%
? 1281
 
5.6%
: 1281
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 3703
100.0%
Math Symbol
ValueCountFrequency (%)
= 1281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 73869
50.2%
Common 73426
49.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 6405
 
8.7%
e 6405
 
8.7%
a 5124
 
6.9%
p 5122
 
6.9%
o 3843
 
5.2%
i 3843
 
5.2%
w 3843
 
5.2%
h 3704
 
5.0%
k 2562
 
3.5%
f 2562
 
3.5%
Other values (21) 30456
41.2%
Common
ValueCountFrequency (%)
2 13653
18.6%
0 12557
17.1%
. 11523
15.7%
1 9874
13.4%
/ 8964
12.2%
_ 3703
 
5.0%
3 2955
 
4.0%
9 2400
 
3.3%
= 1281
 
1.7%
? 1281
 
1.7%
Other values (6) 5235
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13653
 
9.3%
0 12557
 
8.5%
. 11523
 
7.8%
1 9874
 
6.7%
/ 8964
 
6.1%
r 6405
 
4.3%
e 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 63825
43.3%

첨부파일명4
Text

MISSING 

Distinct761
Distinct (%)59.4%
Missing1086
Missing (%)45.9%
Memory size18.6 KiB
2024-03-13T20:52:06.576589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length117
Mean length115.76815
Min length52

Characters and Unicode

Total characters148299
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)20.5%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031100.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031100.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031200.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031200.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032400.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm2p5.1hsp.2022050521.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm2p5.1hsp.2022063021.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm2p5.1hsp.2022041100.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm2p5.1hsp.2022101021.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.pm2p5.1hsp.2022050421.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.pm2p5.1hsp.2022052321.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm2p5.1hsp.2022071221.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm2p5.1hsp.2022110821.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022070103.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052403.png 3
 
0.2%
Other values (751) 1243
97.0%
2024-03-13T20:52:07.203207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13774
 
9.3%
0 13418
 
9.0%
. 11523
 
7.8%
/ 8964
 
6.0%
1 7964
 
5.4%
e 6405
 
4.3%
r 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 65757
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61206
41.3%
Decimal Number 45393
30.6%
Other Punctuation 23049
 
15.5%
Uppercase Letter 13667
 
9.2%
Connector Punctuation 3703
 
2.5%
Math Symbol 1281
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6405
 
10.5%
r 6405
 
10.5%
a 5124
 
8.4%
p 5122
 
8.4%
o 3843
 
6.3%
w 3843
 
6.3%
i 3843
 
6.3%
h 3704
 
6.1%
k 2562
 
4.2%
f 2562
 
4.2%
Other values (9) 17793
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2561
18.7%
P 2008
14.7%
I 1418
10.4%
F 1280
9.4%
Q 1280
9.4%
A 1280
9.4%
U 1143
8.4%
K 1143
8.4%
M 1004
 
7.3%
O 276
 
2.0%
Other values (2) 274
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 13774
30.3%
0 13418
29.6%
1 7964
17.5%
3 3249
 
7.2%
9 2044
 
4.5%
5 1839
 
4.1%
8 835
 
1.8%
6 822
 
1.8%
7 810
 
1.8%
4 638
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11523
50.0%
/ 8964
38.9%
: 1281
 
5.6%
? 1281
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 3703
100.0%
Math Symbol
ValueCountFrequency (%)
= 1281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 74873
50.5%
Common 73426
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6405
 
8.6%
r 6405
 
8.6%
a 5124
 
6.8%
p 5122
 
6.8%
o 3843
 
5.1%
w 3843
 
5.1%
i 3843
 
5.1%
h 3704
 
4.9%
k 2562
 
3.4%
f 2562
 
3.4%
Other values (21) 31460
42.0%
Common
ValueCountFrequency (%)
2 13774
18.8%
0 13418
18.3%
. 11523
15.7%
/ 8964
12.2%
1 7964
10.8%
_ 3703
 
5.0%
3 3249
 
4.4%
9 2044
 
2.8%
5 1839
 
2.5%
= 1281
 
1.7%
Other values (6) 5667
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148299
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13774
 
9.3%
0 13418
 
9.0%
. 11523
 
7.8%
/ 8964
 
6.0%
1 7964
 
5.4%
e 6405
 
4.3%
r 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 65757
44.3%

첨부파일명5
Text

MISSING 

Distinct762
Distinct (%)54.5%
Missing968
Missing (%)40.9%
Memory size18.6 KiB
2024-03-13T20:52:07.518567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length117
Mean length115.60114
Min length52

Characters and Unicode

Total characters161726
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)10.4%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031106.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031106.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031206.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031206.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032406.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm2p5.1hsp.2022101103.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm2p5.1hsp.2022071303.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.pm2p5.1hsp.2022052403.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm2p5.1hsp.2022050603.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm2p5.1hsp.2022110903.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm2p5.1hsp.2022070103.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.pm2p5.1hsp.2022050503.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm2p5.1hsp.2022041106.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022070106.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052406.png 3
 
0.2%
Other values (752) 1361
97.3%
2024-03-13T20:52:08.093787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14703
 
9.1%
0 13669
 
8.5%
. 12585
 
7.8%
/ 9790
 
6.1%
1 8626
 
5.3%
e 6995
 
4.3%
r 6995
 
4.3%
a 5596
 
3.5%
p 5594
 
3.5%
o 4197
 
2.6%
Other values (37) 72976
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 66860
41.3%
Decimal Number 49508
30.6%
Other Punctuation 25173
 
15.6%
Uppercase Letter 14734
 
9.1%
Connector Punctuation 4052
 
2.5%
Math Symbol 1399
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6995
 
10.5%
r 6995
 
10.5%
a 5596
 
8.4%
p 5594
 
8.4%
o 4197
 
6.3%
w 4197
 
6.3%
i 4197
 
6.3%
h 4053
 
6.1%
m 2798
 
4.2%
t 2798
 
4.2%
Other values (9) 19440
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2797
19.0%
P 2008
13.6%
I 1541
10.5%
F 1398
9.5%
A 1398
9.5%
Q 1398
9.5%
U 1256
8.5%
K 1256
8.5%
M 1004
 
6.8%
O 394
 
2.7%
Other values (2) 284
 
1.9%
Decimal Number
ValueCountFrequency (%)
2 14703
29.7%
0 13669
27.6%
1 8626
17.4%
3 3501
 
7.1%
6 2289
 
4.6%
9 2269
 
4.6%
5 1920
 
3.9%
8 937
 
1.9%
7 917
 
1.9%
4 677
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 12585
50.0%
/ 9790
38.9%
? 1399
 
5.6%
: 1399
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 4052
100.0%
Math Symbol
ValueCountFrequency (%)
= 1399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 81594
50.5%
Common 80132
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6995
 
8.6%
r 6995
 
8.6%
a 5596
 
6.9%
p 5594
 
6.9%
o 4197
 
5.1%
w 4197
 
5.1%
i 4197
 
5.1%
h 4053
 
5.0%
m 2798
 
3.4%
t 2798
 
3.4%
Other values (21) 34174
41.9%
Common
ValueCountFrequency (%)
2 14703
18.3%
0 13669
17.1%
. 12585
15.7%
/ 9790
12.2%
1 8626
10.8%
_ 4052
 
5.1%
3 3501
 
4.4%
6 2289
 
2.9%
9 2269
 
2.8%
5 1920
 
2.4%
Other values (6) 6728
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14703
 
9.1%
0 13669
 
8.5%
. 12585
 
7.8%
/ 9790
 
6.1%
1 8626
 
5.3%
e 6995
 
4.3%
r 6995
 
4.3%
a 5596
 
3.5%
p 5594
 
3.5%
o 4197
 
2.6%
Other values (37) 72976
45.1%

첨부파일명6
Text

MISSING 

Distinct761
Distinct (%)59.4%
Missing1086
Missing (%)45.9%
Memory size18.6 KiB
2024-03-13T20:52:08.436536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length117
Mean length115.76815
Min length52

Characters and Unicode

Total characters148299
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique262 ?
Unique (%)20.5%

Sample

1st rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031112.png
2nd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031112.png
3rd rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031212.png
4th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031212.png
5th rowhttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032412.png
ValueCountFrequency (%)
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/05/aqfv1_21h.20220504.knu_09_01.pm2p5.1hsp.2022050609.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.pm2p5.1hsp.2022070109.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/04/11/aqfv1_21h.20220410.knu_09_01.pm2p5.1hsp.2022041112.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/10/10/aqfv1_21h.20221009.knu_09_01.pm2p5.1hsp.2022101109.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/04/aqfv1_21h.20220503.knu_09_01.pm2p5.1hsp.2022050509.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.pm2p5.1hsp.2022052409.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/07/12/aqfv1_09h.20220712.knu_09_01.pm2p5.1hsp.2022071309.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/11/08/aqfv1_21h.20221107.knu_09_01.pm2p5.1hsp.2022110909.png 4
 
0.3%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/06/30/aqfv1_21h.20220629.knu_09_01.o3.1hsp.2022070109.png 3
 
0.2%
https://www.airkorea.or.kr/file/proxyimage?filename=2022/05/23/aqfv1_21h.20220522.knu_09_01.o3.1hsp.2022052409.png 3
 
0.2%
Other values (751) 1243
97.0%
2024-03-13T20:52:08.979614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14700
 
9.9%
. 11523
 
7.8%
0 11510
 
7.8%
/ 8964
 
6.0%
1 8916
 
6.0%
e 6405
 
4.3%
r 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 65787
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 61206
41.3%
Decimal Number 45393
30.6%
Other Punctuation 23049
 
15.5%
Uppercase Letter 13667
 
9.2%
Connector Punctuation 3703
 
2.5%
Math Symbol 1281
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6405
 
10.5%
r 6405
 
10.5%
a 5124
 
8.4%
p 5122
 
8.4%
o 3843
 
6.3%
w 3843
 
6.3%
i 3843
 
6.3%
h 3704
 
6.1%
k 2562
 
4.2%
f 2562
 
4.2%
Other values (9) 17793
29.1%
Uppercase Letter
ValueCountFrequency (%)
N 2561
18.7%
P 2008
14.7%
I 1418
10.4%
F 1280
9.4%
Q 1280
9.4%
A 1280
9.4%
U 1143
8.4%
K 1143
8.4%
M 1004
 
7.3%
O 276
 
2.0%
Other values (2) 274
 
2.0%
Decimal Number
ValueCountFrequency (%)
2 14700
32.4%
0 11510
25.4%
1 8916
19.6%
3 2953
 
6.5%
9 2354
 
5.2%
5 1853
 
4.1%
8 831
 
1.8%
6 822
 
1.8%
7 814
 
1.8%
4 640
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 11523
50.0%
/ 8964
38.9%
: 1281
 
5.6%
? 1281
 
5.6%
Connector Punctuation
ValueCountFrequency (%)
_ 3703
100.0%
Math Symbol
ValueCountFrequency (%)
= 1281
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 74873
50.5%
Common 73426
49.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6405
 
8.6%
r 6405
 
8.6%
a 5124
 
6.8%
p 5122
 
6.8%
o 3843
 
5.1%
w 3843
 
5.1%
i 3843
 
5.1%
h 3704
 
4.9%
k 2562
 
3.4%
f 2562
 
3.4%
Other values (21) 31460
42.0%
Common
ValueCountFrequency (%)
2 14700
20.0%
. 11523
15.7%
0 11510
15.7%
/ 8964
12.2%
1 8916
12.1%
_ 3703
 
5.0%
3 2953
 
4.0%
9 2354
 
3.2%
5 1853
 
2.5%
= 1281
 
1.7%
Other values (6) 5669
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148299
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14700
 
9.9%
. 11523
 
7.8%
0 11510
 
7.8%
/ 8964
 
6.0%
1 8916
 
6.0%
e 6405
 
4.3%
r 6405
 
4.3%
a 5124
 
3.5%
p 5122
 
3.5%
o 3843
 
2.6%
Other values (37) 65787
44.4%

Missing values

2024-03-13T20:51:58.900815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:51:59.163421image/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.
2024-03-13T20:51:59.381406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

발생원인예측통보시간예보등급통보코드예보개황통보시간행동요령첨부파일명1첨부파일명2첨부파일명3첨부파일명4첨부파일명5첨부파일명6
0○ [미세먼지] 대부분 중서부지역과 일부 남부지역은 전일 미세먼지가 잔류하고 대기 정체와 기류 수렴으로 국내 발생 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-11서울 : 보통제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 나쁨세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 보통인천 : 나쁨PM10○ [미세먼지] 수도권·세종·충북·충남·전북·대구는 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 대전·부산·울산·경북은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-11 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031112.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031112.png
1○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-12서울 : 보통제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 수도권·충북은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 대전·세종·충남은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-11 05시 발표<NA><NA><NA><NA><NA><NA><NA>
2○ [미세먼지] 대부분 중서부지역과 일부 남부지역은 전일 미세먼지가 잔류하고 대기 정체와 기류 수렴으로 국내 발생 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-11서울 : 나쁨제주 : 보통전남 : 보통전북 : 나쁨광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 나쁨부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 나쁨대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·세종·충북·충남·전북·대구는 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 대전·부산·울산·경북은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-11 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM10.1hsp.2022031112.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/11/AQFv1_21h.20220310.KNU_09_01.PM2P5.1hsp.2022031112.png
3○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-12서울 : 나쁨제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 나쁨세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·충북은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 대전·세종·충남은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-11 05시 발표<NA><NA><NA><NA><NA><NA><NA>
4○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-12서울 : 보통제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 수도권·충북·충남은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 세종·전북·대구는 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-12 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031200.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031206.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031212.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031200.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031206.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031212.png
5○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-03-13서울 : 좋음제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 좋음경기북부 : 좋음인천 : 좋음PM10○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-03-12 05시 발표<NA><NA><NA><NA><NA><NA><NA>
6○ [미세먼지] 대부분 중서부지역은 대기 정체로 전일 잔류 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-12서울 : 나쁨제주 : 좋음전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·충북·충남은 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다. 다만 세종·전북·대구는 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-12 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031200.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031206.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM10.1hsp.2022031212.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031200.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031206.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/12/AQFv1_21h.20220311.KNU_09_01.PM2P5.1hsp.2022031212.png
7○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-03-13서울 : 보통제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 보통경기북부 : 보통인천 : 보통PM25○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-03-12 05시 발표<NA><NA><NA><NA><NA><NA><NA>
8○ [미세먼지] 일부 중부지역과 대부분 영남지역은 전일 미세먼지가 잔류하고 대기 정체로 국내 발생 미세먼지가 축적되어 농도가 높을 것으로 예상됩니다.2022-03-24서울 : 보통제주 : 보통전남 : 좋음전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 좋음영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 좋음PM10○ [미세먼지] 강원영동·충북·대구·울산·경북은 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 부산은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2022-03-24 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032400.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032406.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM10.1hsp.2022032412.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032400.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032406.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/03/24/AQFv1_21h.20220323.KNU_09_01.PM2P5.1hsp.2022032412.png
9○ [미세먼지] 일부 내륙지역은 전일 미세먼지가 잔류하고 대기 정체로 국내 발생 미세먼지가 축적되어 농도가 높겠으나 오후부터 원활한 대기 확산과 강수의 영향으로 남쪽지역부터 차차 해소될 것으로 예상됩니다.2022-03-25서울 : 보통제주 : 좋음전남 : 좋음전북 : 보통광주 : 좋음경남 : 좋음경북 : 보통울산 : 좋음대구 : 보통부산 : 좋음충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 강원영서·충북·대구는 '나쁨' 그 밖의 권역은 '좋음'∼'보통'으로 예상됩니다.2022-03-24 05시 발표<NA><NA><NA><NA><NA><NA><NA>
발생원인예측통보시간예보등급통보코드예보개황통보시간행동요령첨부파일명1첨부파일명2첨부파일명3첨부파일명4첨부파일명5첨부파일명6
2357○ [미세먼지] 대부분 지역은 전일 잔류 미세먼지가 대기 정체로 축적되어 농도가 높을 것으로 예상됩니다.2024-01-04서울 : 나쁨제주 : 나쁨전남 : 나쁨전북 : 나쁨광주 : 나쁨경남 : 보통경북 : 나쁨울산 : 보통대구 : 나쁨부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 나쁨대전 : 나쁨영동 : 보통영서 : 나쁨경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·강원영서·충청권·호남권·대구·경북·제주권은 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 부산·울산·경남은 오전에 일시적으로 '나쁨' 수준일 것으로 예상됩니다.2024-01-04 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM10.1hsp.2024010400.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM10.1hsp.2024010406.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM10.1hsp.2024010412.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM2P5.1hsp.2024010400.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM2P5.1hsp.2024010406.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/04/AQF.20240103.NIER_09_01.PM2P5.1hsp.2024010412.png
2358○ [미세먼지] 대부분 지역은 전일 미세먼지가 잔류하고 국외 미세먼지가 유입되어 농도가 높을 것으로 예상됩니다.2024-01-05서울 : 나쁨제주 : 보통전남 : 보통전북 : 나쁨광주 : 나쁨경남 : 보통경북 : 나쁨울산 : 보통대구 : 나쁨부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 나쁨대전 : 나쁨영동 : 보통영서 : 나쁨경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·강원영서·충청권·광주·전북·대구·경북은 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 전남·부산·울산·경남·제주권은 밤에 '나쁨' 수준일 것으로 예상됩니다.2024-01-04 05시 발표<NA><NA><NA><NA><NA><NA><NA>
2359○ [미세먼지] 대부분 지역은 전일 미세먼지가 잔류하고 국외 미세먼지가 유입되어 농도가 높을 것으로 예상됩니다.2024-01-05서울 : 보통제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 수도권·강원영서·충청권·호남권·대구·경북·제주권은 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 부산·울산·경남은 밤에 '나쁨' 수준일 것으로 예상됩니다.2024-01-05 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010500.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010506.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010512.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010500.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010506.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010512.png
2360○ [미세먼지] 대기질이 '보통' 수준이겠으나 대부분 남부 지역은 전일 미세먼지가 잔류하여 오전에 농도가 다소 높을 것으로 예상됩니다.2024-01-06서울 : 보통제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 전 권역이 '보통'으로 예상됩니다. 다만 전남·부산·울산·경남·제주권은 오전에 '나쁨' 수준일 것으로 예상됩니다.2024-01-05 05시 발표<NA><NA><NA><NA><NA><NA><NA>
2361○ [미세먼지] 대부분 지역은 전일 미세먼지가 잔류하고 국외 미세먼지가 유입되어 농도가 높을 것으로 예상됩니다.2024-01-05서울 : 나쁨제주 : 나쁨전남 : 나쁨전북 : 나쁨광주 : 나쁨경남 : 보통경북 : 나쁨울산 : 보통대구 : 나쁨부산 : 보통충남 : 나쁨충북 : 나쁨세종 : 나쁨대전 : 나쁨영동 : 보통영서 : 나쁨경기남부 : 나쁨경기북부 : 나쁨인천 : 나쁨PM25○ [미세먼지] 수도권·강원영서·충청권·호남권·대구·경북·제주권은 '나쁨' 그 밖의 권역은 '보통'으로 예상됩니다. 다만 부산·울산·경남은 밤에 '나쁨' 수준일 것으로 예상됩니다.2024-01-05 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010500.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010506.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM10.1hsp.2024010512.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010500.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010506.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/05/AQF.20240104.NIER_09_01.PM2P5.1hsp.2024010512.png
2362○ [미세먼지] 대기질이 '보통' 수준이겠으나 대부분 남부 지역은 전일 미세먼지가 잔류하여 오전에 농도가 다소 높을 것으로 예상됩니다.2024-01-06서울 : 보통제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 보통PM25○ [미세먼지] 전 권역이 '보통'으로 예상됩니다. 다만 전남·부산·울산·경남·제주권은 오전에 '나쁨' 수준일 것으로 예상됩니다.2024-01-05 05시 발표<NA><NA><NA><NA><NA><NA><NA>
2363○ [미세먼지] 대기질이 대체로 '보통' 수준이겠으나 대부분 지역은 전일 미세먼지가 잔류하여 오전에 농도가 다소 높을 것으로 예상됩니다.2024-01-06서울 : 좋음제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 좋음경기북부 : 보통인천 : 좋음PM10○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다. 다만 강원영서·세종·충북·호남권·영남권·제주권은 오전에 '나쁨' 수준일 것으로 예상됩니다.2024-01-06 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010600.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010606.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010612.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010600.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010606.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010612.png
2364○ [미세먼지] 원활한 대기 확산으로 대기질이 청정할 것으로 예상됩니다.2024-01-07서울 : 좋음제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 좋음경기북부 : 좋음인천 : 좋음PM10○ [미세먼지] 전 권역이 '좋음'으로 예상됩니다.2024-01-06 05시 발표<NA><NA><NA><NA><NA><NA><NA>
2365○ [미세먼지] 대기질이 대체로 '보통' 수준이겠으나 대부분 지역은 전일 미세먼지가 잔류하여 오전에 농도가 다소 높을 것으로 예상됩니다.2024-01-06서울 : 좋음제주 : 보통전남 : 보통전북 : 보통광주 : 보통경남 : 보통경북 : 보통울산 : 보통대구 : 보통부산 : 보통충남 : 보통충북 : 보통세종 : 보통대전 : 보통영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 좋음PM25○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다. 다만 강원영서·세종·충북·호남권·영남권·제주권은 오전에 '나쁨' 수준일 것으로 예상됩니다.2024-01-06 05시 발표<NA>https://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010600.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010606.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM10.1hsp.2024010612.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010600.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010606.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2024/01/06/AQF.20240105.NIER_09_01.PM2P5.1hsp.2024010612.png
2366○ [미세먼지] 원활한 대기 확산으로 대기질이 청정할 것으로 예상됩니다.2024-01-07서울 : 좋음제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 좋음경기북부 : 좋음인천 : 좋음PM25○ [미세먼지] 전 권역이 '좋음'으로 예상됩니다.2024-01-06 05시 발표<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

발생원인예측통보시간예보등급통보코드예보개황통보시간첨부파일명1첨부파일명2첨부파일명3첨부파일명4첨부파일명5첨부파일명6# duplicates
0○ [미세먼지] 대부분 지역은 전일 잔류 미세먼지가 대기 정체로 축적되고 국외 미세먼지가 유입되어 농도가 높을 것으로 예상됩니다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
1○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-04-11서울 : 보통제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 보통대구 : 좋음부산 : 보통충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 좋음PM25○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-04-11 05시 발표https://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041112.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041112.png2
2○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-04-11서울 : 보통제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 좋음충북 : 좋음세종 : 좋음대전 : 좋음영동 : 보통영서 : 보통경기남부 : 보통경기북부 : 보통인천 : 좋음PM10○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-04-11 05시 발표https://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM10.1hsp.2022041112.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041100.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041106.pnghttps://www.airkorea.or.kr/file/proxyImage?fileName=2022/04/11/AQFv1_21h.20220410.KNU_09_01.PM2P5.1hsp.2022041112.png2
3○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-04-12서울 : 보통제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 보통충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 보통경기북부 : 보통인천 : 보통PM10○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-04-11 05시 발표<NA><NA><NA><NA><NA><NA>2
4○ [미세먼지] 원활한 대기 확산으로 대기 상태가 대체로 청정할 것으로 예상됩니다.2022-04-12서울 : 보통제주 : 좋음전남 : 좋음전북 : 좋음광주 : 좋음경남 : 좋음경북 : 좋음울산 : 좋음대구 : 좋음부산 : 좋음충남 : 보통충북 : 좋음세종 : 좋음대전 : 좋음영동 : 좋음영서 : 좋음경기남부 : 보통경기북부 : 보통인천 : 보통PM25○ [미세먼지] 전 권역이 '좋음'∼'보통'으로 예상됩니다.2022-04-11 05시 발표<NA><NA><NA><NA><NA><NA>2
5○ [미세먼지] 원활한 대기 확산으로 대기질이 대체로 '보통' 수준일 것으로 예상됩니다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2
6○ [미세먼지] 원활한 대기 확산으로 대기질이 대체로 청정할 것으로 예상됩니다.<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>2