Overview

Dataset statistics

Number of variables12
Number of observations189
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.4 KiB
Average record size in memory99.7 B

Variable types

Numeric3
DateTime5
Categorical4

Dataset

Description미세먼지에 대한 주의보, 경보 발령 이력 을 조회하기 위한 데이터로, 발생_순번,발생_일시,항목_코드,경보 단계,지역명,권역명,발령일자,발령시간,발령농도,해제일자,해제시간,해제농도 정보를 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15106415/fileData.do

Alerts

발생_순번 is highly overall correlated with 발령농도 and 2 other fieldsHigh correlation
발령농도 is highly overall correlated with 발생_순번 and 2 other fieldsHigh correlation
해제농도 is highly overall correlated with 발생_순번 and 2 other fieldsHigh correlation
항목_코드 is highly overall correlated with 발생_순번 and 2 other fieldsHigh correlation
지역명 is highly overall correlated with 권역명High correlation
권역명 is highly overall correlated with 지역명High correlation
경보 단계 is highly imbalanced (95.2%)Imbalance
발생_순번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:29:44.652593
Analysis finished2024-03-23 05:29:51.054626
Duration6.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

발생_순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct189
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean147.26455
Minimum1
Maximum276
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-23T05:29:51.502429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.4
Q182
median151
Q3216
95-th percentile261.6
Maximum276
Range275
Interquartile range (IQR)134

Descriptive statistics

Standard deviation77.448568
Coefficient of variation (CV)0.52591454
Kurtosis-1.1698838
Mean147.26455
Median Absolute Deviation (MAD)67
Skewness-0.12235881
Sum27833
Variance5998.2807
MonotonicityStrictly decreasing
2024-03-23T05:29:52.176367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
276 1
 
0.5%
93 1
 
0.5%
105 1
 
0.5%
103 1
 
0.5%
101 1
 
0.5%
100 1
 
0.5%
99 1
 
0.5%
98 1
 
0.5%
97 1
 
0.5%
96 1
 
0.5%
Other values (179) 179
94.7%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
11 1
0.5%
14 1
0.5%
15 1
0.5%
24 1
0.5%
25 1
0.5%
ValueCountFrequency (%)
276 1
0.5%
273 1
0.5%
272 1
0.5%
270 1
0.5%
268 1
0.5%
267 1
0.5%
266 1
0.5%
264 1
0.5%
263 1
0.5%
262 1
0.5%

발생_일시
Date

Distinct23
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-01-08 00:00:00
Maximum2022-06-01 00:00:00
2024-03-23T05:29:52.567642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:53.102093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

항목_코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
PM25
101 
PM10
88 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PM25 101
53.4%
PM10 88
46.6%

Length

2024-03-23T05:29:53.574434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:29:53.949026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pm25 101
53.4%
pm10 88
46.6%

경보 단계
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
주의보
188 
경보
 
1

Length

Max length3
Median length3
Mean length2.994709
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row주의보
2nd row경보
3rd row주의보
4th row주의보
5th row주의보

Common Values

ValueCountFrequency (%)
주의보 188
99.5%
경보 1
 
0.5%

Length

2024-03-23T05:29:54.420736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:29:54.869286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주의보 188
99.5%
경보 1
 
0.5%

지역명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
경남
30 
인천
24 
경기
23 
강원
18 
충남
16 
Other values (12)
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row경남
2nd row경남
3rd row경남
4th row인천
5th row대전

Common Values

ValueCountFrequency (%)
경남 30
15.9%
인천 24
12.7%
경기 23
12.2%
강원 18
9.5%
충남 16
8.5%
충북 15
7.9%
전북 11
 
5.8%
대전 11
 
5.8%
부산 10
 
5.3%
전남 6
 
3.2%
Other values (7) 25
13.2%

Length

2024-03-23T05:29:55.367952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경남 30
15.9%
인천 24
12.7%
경기 23
12.2%
강원 18
9.5%
충남 16
8.5%
충북 15
7.9%
전북 11
 
5.8%
대전 11
 
5.8%
부산 10
 
5.3%
전남 6
 
3.2%
Other values (7) 25
13.2%

권역명
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
서부권역
25 
중부권역
 
12
동부권역
 
11
북부권역
 
11
동남부권역
 
10
Other values (35)
120 

Length

Max length7
Median length4
Mean length4.042328
Min length3

Unique

Unique11 ?
Unique (%)5.8%

Sample

1st row밀양권역
2nd row밀양권역
3rd row밀양권역
4th row강화권역
5th row서부권역

Common Values

ValueCountFrequency (%)
서부권역 25
 
13.2%
중부권역 12
 
6.3%
동부권역 11
 
5.8%
북부권역 11
 
5.8%
동남부권역 10
 
5.3%
영종·영흥권역 9
 
4.8%
남부권 8
 
4.2%
동부권 8
 
4.2%
남부권역 7
 
3.7%
영서북부 6
 
3.2%
Other values (30) 82
43.4%

Length

2024-03-23T05:29:55.961472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서부권역 25
 
13.2%
중부권역 12
 
6.3%
동부권역 11
 
5.8%
북부권역 11
 
5.8%
동남부권역 10
 
5.3%
영종·영흥권역 9
 
4.8%
남부권 8
 
4.2%
동부권 8
 
4.2%
남부권역 7
 
3.7%
중부권 6
 
3.2%
Other values (30) 82
43.4%

발령일자
Date

Distinct22
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-01-08 00:00:00
Maximum2022-06-01 00:00:00
2024-03-23T05:29:56.329959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:56.953771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

발령시간
Date

Distinct23
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2024-03-23 00:00:00
Maximum2024-03-23 23:00:00
2024-03-23T05:29:57.442128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:57.830815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

발령농도
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132.46032
Minimum69
Maximum287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-23T05:29:58.345494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile75
Q180
median93
Q3178
95-th percentile241.6
Maximum287
Range218
Interquartile range (IQR)98

Descriptive statistics

Standard deviation59.366915
Coefficient of variation (CV)0.44818642
Kurtosis-0.74456725
Mean132.46032
Median Absolute Deviation (MAD)18
Skewness0.62864263
Sum25035
Variance3524.4306
MonotonicityNot monotonic
2024-03-23T05:29:58.761738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 13
 
6.9%
76 10
 
5.3%
80 10
 
5.3%
81 9
 
4.8%
79 8
 
4.2%
82 8
 
4.2%
78 7
 
3.7%
77 7
 
3.7%
176 5
 
2.6%
160 4
 
2.1%
Other values (64) 108
57.1%
ValueCountFrequency (%)
69 1
 
0.5%
75 13
6.9%
76 10
5.3%
77 7
3.7%
78 7
3.7%
79 8
4.2%
80 10
5.3%
81 9
4.8%
82 8
4.2%
83 4
 
2.1%
ValueCountFrequency (%)
287 1
0.5%
284 1
0.5%
278 1
0.5%
277 1
0.5%
275 1
0.5%
271 1
0.5%
256 1
0.5%
247 1
0.5%
246 2
1.1%
235 1
0.5%

해제일자
Date

Distinct23
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-01-10 00:00:00
Maximum2022-06-01 00:00:00
2024-03-23T05:29:59.191938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:59.669377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

해제시간
Date

Distinct24
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2024-03-23 00:00:00
Maximum2024-03-23 23:00:00
2024-03-23T05:30:00.019641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:30:00.483305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

해제농도
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.05291
Minimum7
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-03-23T05:30:00.945665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile23
Q131
median34
Q390
95-th percentile98
Maximum99
Range92
Interquartile range (IQR)59

Descriptive statistics

Standard deviation30.306718
Coefficient of variation (CV)0.53120373
Kurtosis-1.7804695
Mean57.05291
Median Absolute Deviation (MAD)13
Skewness0.21836824
Sum10783
Variance918.49719
MonotonicityNot monotonic
2024-03-23T05:30:01.455989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33 26
 
13.8%
32 14
 
7.4%
30 13
 
6.9%
31 13
 
6.9%
34 9
 
4.8%
98 7
 
3.7%
99 6
 
3.2%
93 6
 
3.2%
97 6
 
3.2%
88 5
 
2.6%
Other values (40) 84
44.4%
ValueCountFrequency (%)
7 1
 
0.5%
13 1
 
0.5%
15 1
 
0.5%
16 2
 
1.1%
19 1
 
0.5%
21 2
 
1.1%
22 1
 
0.5%
23 2
 
1.1%
25 1
 
0.5%
26 5
2.6%
ValueCountFrequency (%)
99 6
3.2%
98 7
3.7%
97 6
3.2%
96 5
2.6%
95 5
2.6%
94 4
2.1%
93 6
3.2%
92 3
1.6%
91 4
2.1%
90 3
1.6%

Interactions

2024-03-23T05:29:48.758696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:46.848599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:47.689085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:49.123846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:47.198800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:48.048974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:49.492577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:47.422642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T05:29:48.427494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:30:01.841534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생_순번발생_일시항목_코드경보 단계지역명권역명발령일자발령시간발령농도해제일자해제시간해제농도
발생_순번1.0000.9280.9580.0000.5190.0000.9220.7680.7010.9080.6630.612
발생_일시0.9281.0000.9610.5600.5080.0000.9980.8690.6880.9960.6000.803
항목_코드0.9580.9611.0000.0000.0000.0000.9940.5450.9990.9670.5360.956
경보 단계0.0000.5600.0001.0000.0000.2810.6190.0000.1330.5600.0000.354
지역명0.5190.5080.0000.0001.0000.9810.4740.4840.0000.2800.3810.373
권역명0.0000.0000.0000.2810.9811.0000.0000.0000.7200.0000.7060.000
발령일자0.9220.9980.9940.6190.4740.0001.0000.7990.7020.9880.6190.802
발령시간0.7680.8690.5450.0000.4840.0000.7991.0000.3700.7960.4370.401
발령농도0.7010.6880.9990.1330.0000.7200.7020.3701.0000.7810.3920.702
해제일자0.9080.9960.9670.5600.2800.0000.9880.7960.7811.0000.7340.809
해제시간0.6630.6000.5360.0000.3810.7060.6190.4370.3920.7341.0000.310
해제농도0.6120.8030.9560.3540.3730.0000.8020.4010.7020.8090.3101.000
2024-03-23T05:30:02.436566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목_코드경보 단계지역명권역명
항목_코드1.0000.0000.0000.000
경보 단계0.0001.0000.0000.197
지역명0.0000.0001.0000.741
권역명0.0000.1970.7411.000
2024-03-23T05:30:02.719364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생_순번발령농도해제농도항목_코드경보 단계지역명권역명
발생_순번1.0000.5400.5330.8080.0000.2240.000
발령농도0.5401.0000.7290.9590.0980.0000.287
해제농도0.5330.7291.0000.9720.3470.1530.000
항목_코드0.8080.9590.9721.0000.0000.0000.000
경보 단계0.0000.0980.3470.0001.0000.0000.197
지역명0.2240.0000.1530.0000.0001.0000.741
권역명0.0000.2870.0000.0000.1970.7411.000

Missing values

2024-03-23T05:29:50.111895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:29:50.795097image/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

발생_순번발생_일시항목_코드경보 단계지역명권역명발령일자발령시간발령농도해제일자해제시간해제농도
02762022-06-01PM25주의보경남밀양권역2022-06-0113:00692022-06-0114:0013
12732022-06-01PM25경보경남밀양권역2022-06-0111:002192022-06-0113:0069
22722022-06-01PM10주의보경남밀양권역2022-06-0111:002712022-06-0114:0036
32702022-05-23PM25주의보인천강화권역2022-05-2312:00822022-05-2318:0033
42682022-04-27PM10주의보대전서부권역2022-04-2722:001592022-04-2805:0099
52672022-04-27PM10주의보대전동부권역2022-04-2722:001772022-04-2807:0093
62662022-04-27PM10주의보세종세종권역2022-04-2721:001602022-04-2806:0093
72642022-04-27PM10주의보충북중부권역2022-04-2721:001722022-04-2802:0098
82632022-04-27PM10주의보광주광주권역2022-04-2721:001652022-04-2807:0094
92622022-04-27PM10주의보전남서부권2022-04-2714:001762022-04-2804:0097
발생_순번발생_일시항목_코드경보 단계지역명권역명발령일자발령시간발령농도해제일자해제시간해제농도
179252022-01-09PM25주의보경기동부권2022-01-0902:00802022-01-1022:0033
180242022-01-09PM25주의보경기중부권2022-01-0901:00842022-01-1022:0032
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