Overview

Dataset statistics

Number of variables8
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory74.4 B

Variable types

Categorical2
Numeric6

Dataset

Description발전소 주변의 대기환경 정보이며, 주요 항목으로 연도, 기준항목, 초미세먼지, 오존, 이산화질소, 일산화탄소, 아황산가스의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3071439/fileData.do

Alerts

미세먼지 is highly overall correlated with 초미세먼지 and 3 other fieldsHigh correlation
초미세먼지 is highly overall correlated with 미세먼지 and 3 other fieldsHigh correlation
오존(ppb) is highly overall correlated with 미세먼지 and 3 other fieldsHigh correlation
이산화질소(ppb) is highly overall correlated with 미세먼지 and 3 other fieldsHigh correlation
일산화탄소(ppb) is highly overall correlated with 미세먼지 and 2 other fieldsHigh correlation
아황산가스(ppb) is highly overall correlated with 이산화질소(ppb)High correlation
미세먼지 has 6 (15.4%) zerosZeros
일산화탄소(ppb) has 12 (30.8%) zerosZeros
아황산가스(ppb) has 4 (10.3%) zerosZeros

Reproduction

Analysis started2023-12-12 09:41:04.683734
Analysis finished2023-12-12 09:41:09.631568
Duration4.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
2020
14 
2021
14 
2022
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 14
35.9%
2021 14
35.9%
2022 11
28.2%

Length

2023-12-12T18:41:09.714749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:41:09.864307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 14
35.9%
2021 14
35.9%
2022 11
28.2%

기준항목
Categorical

Distinct14
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
당진발전본부(교로)
3 
석문중(삼봉)
3 
석문면(통정)
3 
당진에코파워
3 
변전소(사관)
3 
Other values (9)
24 

Length

Max length10
Median length7
Mean length6.3846154
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row당진발전본부(교로)
2nd row석문중(삼봉)
3rd row석문면(통정)
4th row당진에코파워
5th row변전소(사관)

Common Values

ValueCountFrequency (%)
당진발전본부(교로) 3
 
7.7%
석문중(삼봉) 3
 
7.7%
석문면(통정) 3
 
7.7%
당진에코파워 3
 
7.7%
변전소(사관) 3
 
7.7%
종합운동장(진관) 3
 
7.7%
적서리 3
 
7.7%
송악초(중흥) 3
 
7.7%
면천면(성상) 3
 
7.7%
합덕읍(운산) 3
 
7.7%
Other values (4) 9
23.1%

Length

2023-12-12T18:41:10.013968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당진발전본부(교로 3
 
7.7%
석문중(삼봉 3
 
7.7%
석문면(통정 3
 
7.7%
당진에코파워 3
 
7.7%
변전소(사관 3
 
7.7%
종합운동장(진관 3
 
7.7%
적서리 3
 
7.7%
송악초(중흥 3
 
7.7%
면천면(성상 3
 
7.7%
합덕읍(운산 3
 
7.7%
Other values (4) 9
23.1%

미세먼지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.66667
Minimum0
Maximum959
Zeros6
Zeros (%)15.4%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:10.199089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.5
median36
Q3123
95-th percentile297.5
Maximum959
Range959
Interquartile range (IQR)96.5

Descriptive statistics

Standard deviation168.30179
Coefficient of variation (CV)1.6554274
Kurtosis17.783881
Mean101.66667
Median Absolute Deviation (MAD)36
Skewness3.7833348
Sum3965
Variance28325.491
MonotonicityNot monotonic
2023-12-12T18:41:10.386358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 6
 
15.4%
26 2
 
5.1%
39 2
 
5.1%
30 2
 
5.1%
29 2
 
5.1%
41 1
 
2.6%
135 1
 
2.6%
33 1
 
2.6%
32 1
 
2.6%
38 1
 
2.6%
Other values (20) 20
51.3%
ValueCountFrequency (%)
0 6
15.4%
17 1
 
2.6%
22 1
 
2.6%
26 2
 
5.1%
27 1
 
2.6%
28 1
 
2.6%
29 2
 
5.1%
30 2
 
5.1%
31 1
 
2.6%
32 1
 
2.6%
ValueCountFrequency (%)
959 1
2.6%
320 1
2.6%
295 1
2.6%
278 1
2.6%
273 1
2.6%
264 1
2.6%
178 1
2.6%
163 1
2.6%
135 1
2.6%
126 1
2.6%

초미세먼지
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.898974
Minimum0.01
Maximum312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:10.539410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q114
median18
Q367.5
95-th percentile162.6
Maximum312
Range311.99
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation68.456933
Coefficient of variation (CV)1.3190421
Kurtosis4.4987601
Mean51.898974
Median Absolute Deviation (MAD)17.99
Skewness2.0283228
Sum2024.06
Variance4686.3516
MonotonicityNot monotonic
2023-12-12T18:41:10.695707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.01 6
 
15.4%
17.0 5
 
12.8%
16.0 3
 
7.7%
20.0 2
 
5.1%
52.0 1
 
2.6%
45.0 1
 
2.6%
54.0 1
 
2.6%
27.0 1
 
2.6%
19.0 1
 
2.6%
29.0 1
 
2.6%
Other values (17) 17
43.6%
ValueCountFrequency (%)
0.01 6
15.4%
3.0 1
 
2.6%
9.0 1
 
2.6%
12.0 1
 
2.6%
13.0 1
 
2.6%
15.0 1
 
2.6%
16.0 3
7.7%
17.0 5
12.8%
18.0 1
 
2.6%
19.0 1
 
2.6%
ValueCountFrequency (%)
312.0 1
2.6%
195.0 1
2.6%
159.0 1
2.6%
151.0 1
2.6%
149.0 1
2.6%
144.0 1
2.6%
139.0 1
2.6%
94.0 1
2.6%
77.0 1
2.6%
68.0 1
2.6%

오존(ppb)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.059769
Minimum0.02
Maximum45.836
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:10.843559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.03
Q10.0425
median19.979
Q331.7125
95-th percentile37.7159
Maximum45.836
Range45.816
Interquartile range (IQR)31.67

Descriptive statistics

Standard deviation15.371559
Coefficient of variation (CV)0.85114925
Kurtosis-1.6139823
Mean18.059769
Median Absolute Deviation (MAD)14.355
Skewness0.036340313
Sum704.331
Variance236.28483
MonotonicityNot monotonic
2023-12-12T18:41:10.992459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.03 5
 
12.8%
0.038 2
 
5.1%
26.437 1
 
2.6%
36.686 1
 
2.6%
28.645 1
 
2.6%
17.553 1
 
2.6%
31.499 1
 
2.6%
0.045 1
 
2.6%
0.034 1
 
2.6%
40.253 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
0.02 1
 
2.6%
0.03 5
12.8%
0.034 1
 
2.6%
0.038 2
 
5.1%
0.04 1
 
2.6%
0.045 1
 
2.6%
1.043 1
 
2.6%
2.829 1
 
2.6%
6.134 1
 
2.6%
6.795 1
 
2.6%
ValueCountFrequency (%)
45.836 1
2.6%
40.253 1
2.6%
37.434 1
2.6%
36.686 1
2.6%
35.296 1
2.6%
34.79 1
2.6%
34.334 1
2.6%
34.034 1
2.6%
33.341 1
2.6%
31.833 1
2.6%

이산화질소(ppb)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2838718
Minimum0.005
Maximum40.018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:11.157023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.005
5-th percentile0.006
Q10.077
median2.967
Q38.8725
95-th percentile11.7771
Maximum40.018
Range40.013
Interquartile range (IQR)8.7955

Descriptive statistics

Standard deviation7.256452
Coefficient of variation (CV)1.373321
Kurtosis13.22299
Mean5.2838718
Median Absolute Deviation (MAD)2.958
Skewness3.0181989
Sum206.071
Variance52.656096
MonotonicityNot monotonic
2023-12-12T18:41:11.337786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.42 3
 
7.7%
0.006 2
 
5.1%
0.009 2
 
5.1%
0.013 2
 
5.1%
6.348 1
 
2.6%
9.872 1
 
2.6%
8.679 1
 
2.6%
11.404 1
 
2.6%
0.51 1
 
2.6%
0.01 1
 
2.6%
Other values (24) 24
61.5%
ValueCountFrequency (%)
0.005 1
 
2.6%
0.006 2
5.1%
0.007 1
 
2.6%
0.009 2
5.1%
0.01 1
 
2.6%
0.011 1
 
2.6%
0.013 2
5.1%
0.141 1
 
2.6%
0.38 1
 
2.6%
0.42 3
7.7%
ValueCountFrequency (%)
40.018 1
2.6%
15.135 1
2.6%
11.404 1
2.6%
10.707 1
2.6%
10.572 1
2.6%
10.262 1
2.6%
9.872 1
2.6%
9.535 1
2.6%
9.259 1
2.6%
9.066 1
2.6%

일산화탄소(ppb)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7115385
Minimum0
Maximum76.41
Zeros12
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:11.511896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.36
Q30.465
95-th percentile50.39
Maximum76.41
Range76.41
Interquartile range (IQR)0.465

Descriptive statistics

Standard deviation18.605507
Coefficient of variation (CV)2.4126842
Kurtosis5.1445067
Mean7.7115385
Median Absolute Deviation (MAD)0.24
Skewness2.4373002
Sum300.75
Variance346.16489
MonotonicityNot monotonic
2023-12-12T18:41:11.687436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 12
30.8%
0.35 3
 
7.7%
0.48 2
 
5.1%
0.45 2
 
5.1%
0.36 2
 
5.1%
37.83 1
 
2.6%
0.41 1
 
2.6%
0.37 1
 
2.6%
0.32 1
 
2.6%
0.43 1
 
2.6%
Other values (13) 13
33.3%
ValueCountFrequency (%)
0.0 12
30.8%
0.12 1
 
2.6%
0.23 1
 
2.6%
0.32 1
 
2.6%
0.34 1
 
2.6%
0.35 3
 
7.7%
0.36 2
 
5.1%
0.37 1
 
2.6%
0.38 1
 
2.6%
0.39 1
 
2.6%
ValueCountFrequency (%)
76.41 1
2.6%
54.35 1
2.6%
49.95 1
2.6%
39.4 1
2.6%
37.83 1
2.6%
34.63 1
2.6%
0.62 1
2.6%
0.5 1
2.6%
0.48 2
5.1%
0.45 2
5.1%

아황산가스(ppb)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.2849487
Minimum0
Maximum82.02
Zeros4
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T18:41:11.898233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.073
median2.142
Q33.735
95-th percentile24.8598
Maximum82.02
Range82.02
Interquartile range (IQR)3.662

Descriptive statistics

Standard deviation14.819798
Coefficient of variation (CV)2.0343037
Kurtosis17.296487
Mean7.2849487
Median Absolute Deviation (MAD)1.998
Skewness3.8056918
Sum284.113
Variance219.62642
MonotonicityNot monotonic
2023-12-12T18:41:12.073239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.002 5
 
12.8%
0.0 4
 
10.3%
17.96 1
 
2.6%
2.932 1
 
2.6%
3.588 1
 
2.6%
37.188 1
 
2.6%
18.37 1
 
2.6%
16.03 1
 
2.6%
2.099 1
 
2.6%
3.13 1
 
2.6%
Other values (22) 22
56.4%
ValueCountFrequency (%)
0.0 4
10.3%
0.001 1
 
2.6%
0.002 5
12.8%
0.144 1
 
2.6%
0.44 1
 
2.6%
0.647 1
 
2.6%
1.045 1
 
2.6%
1.476 1
 
2.6%
1.815 1
 
2.6%
1.96 1
 
2.6%
ValueCountFrequency (%)
82.02 1
2.6%
37.188 1
2.6%
23.49 1
2.6%
18.37 1
2.6%
17.96 1
2.6%
16.91 1
2.6%
16.161 1
2.6%
16.03 1
2.6%
13.37 1
2.6%
3.794 1
2.6%

Interactions

2023-12-12T18:41:08.687744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.034969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.620279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.584080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.210916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.838242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.786859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.122970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.720320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.676486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.308161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.948646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.890759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.229338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.817487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.787577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.418613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.079593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:09.001262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.320663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.928816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.871777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.515237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.266827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:09.131428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.439104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.031602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.998832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.623436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.454691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:09.247930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:05.536359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:06.486240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.114744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:07.740199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:41:08.577875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:41:12.172800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도기준항목미세먼지초미세먼지오존(ppb)이산화질소(ppb)일산화탄소(ppb)아황산가스(ppb)
연도1.0000.0000.4620.5100.6530.3490.0000.000
기준항목0.0001.0000.0000.0000.1610.2660.7560.601
미세먼지0.4620.0001.0000.9250.4210.7080.0000.000
초미세먼지0.5100.0000.9251.0000.5770.1450.0000.000
오존(ppb)0.6530.1610.4210.5771.0000.9230.0000.000
이산화질소(ppb)0.3490.2660.7080.1450.9231.0000.0000.000
일산화탄소(ppb)0.0000.7560.0000.0000.0000.0001.0000.787
아황산가스(ppb)0.0000.6010.0000.0000.0000.0000.7871.000
2023-12-12T18:41:12.337084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준항목연도
기준항목1.0000.000
연도0.0001.000
2023-12-12T18:41:12.467019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지초미세먼지오존(ppb)이산화질소(ppb)일산화탄소(ppb)아황산가스(ppb)연도기준항목
미세먼지1.0000.9300.5880.627-0.5290.0160.3800.000
초미세먼지0.9301.0000.6150.691-0.5910.0720.3430.000
오존(ppb)0.5880.6151.0000.615-0.688-0.0260.4450.000
이산화질소(ppb)0.6270.6910.6151.000-0.4740.5540.2690.072
일산화탄소(ppb)-0.529-0.591-0.688-0.4741.0000.2210.0000.426
아황산가스(ppb)0.0160.072-0.0260.5540.2211.0000.0000.301
연도0.3800.3430.4450.2690.0000.0001.0000.000
기준항목0.0000.0000.0000.0720.4260.3010.0001.000

Missing values

2023-12-12T18:41:09.410790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:41:09.564676image/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

연도기준항목미세먼지초미세먼지오존(ppb)이산화질소(ppb)일산화탄소(ppb)아황산가스(ppb)
02020당진발전본부(교로)4117.040.25340.0180.02.099
12020석문중(삼봉)3020.045.83615.1350.03.794
22020석문면(통정)2618.034.799.0660.02.2
32020당진에코파워3920.033.34110.5720.02.312
42020변전소(사관)3013.034.0345.7250.02.47
52020종합운동장(진관)278149.027.2947.6780.01.815
62020적서리264139.037.4345.8010.02.353
72020송악초(중흥)120195.035.2969.2590.02.362
82020면천면(성상)273144.031.2019.5350.02.018
92020합덕읍(운산)320151.031.8338.2960.02.142
연도기준항목미세먼지초미세먼지오존(ppb)이산화질소(ppb)일산화탄소(ppb)아황산가스(ppb)
292022석문중(삼봉)3216.00.0340.0090.380.002
302022석문면(통정)2917.00.0380.010.390.002
312022당진에코파워2917.00.0380.0130.350.002
322022변전소(사관)2816.00.040.0070.360.002
332022종합운동장(진관)3829.06.1342.5180.230.44
342022적서리3119.012.2522.2620.4316.161
352022송악초(중흥)7517.01.0430.1410.320.144
362022면천면(성상)4527.011.8964.4730.371.476
372022합덕읍(운산)3954.010.2652.9670.350.647
382022신평면(금천)7645.06.7954.1210.411.045