Overview

Dataset statistics

Number of variables6
Number of observations2208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory112.3 KiB
Average record size in memory52.1 B

Variable types

DateTime1
Categorical1
Numeric4

Dataset

Description광양항 낙포부두의 대기정보 데이터입니다. 데이터 구성은 시간, 측정소, PM2.5수치, PM10수치, 온도 습도입니다.데이터 갱신주기는 분기입니다.
Author여수광양항만공사
URLhttps://www.data.go.kr/data/15090369/fileData.do

Alerts

측정소 has constant value ""Constant
미세먼지(PM)2_5 is highly overall correlated with 미세먼지(PM)10High correlation
미세먼지(PM)10 is highly overall correlated with 미세먼지(PM)2_5High correlation
온도(섭씨) is highly overall correlated with 습도(퍼센트)High correlation
습도(퍼센트) is highly overall correlated with 온도(섭씨)High correlation
시간 has unique valuesUnique
미세먼지(PM)2_5 has 44 (2.0%) zerosZeros
미세먼지(PM)10 has 26 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-12 08:19:48.826625
Analysis finished2023-12-12 08:19:51.546238
Duration2.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시간
Date

UNIQUE 

Distinct2208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
Minimum2023-07-01 00:00:00
Maximum2023-09-30 23:00:00
2023-12-12T17:19:51.635279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:51.811086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

측정소
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
낙포부두 실외
2208 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row낙포부두 실외
2nd row낙포부두 실외
3rd row낙포부두 실외
4th row낙포부두 실외
5th row낙포부두 실외

Common Values

ValueCountFrequency (%)
낙포부두 실외 2208
100.0%

Length

2023-12-12T17:19:51.985226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:52.084317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낙포부두 2208
50.0%
실외 2208
50.0%

미세먼지(PM)2_5
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.866848
Minimum0
Maximum72
Zeros44
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2023-12-12T17:19:52.198193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median10
Q316
95-th percentile32
Maximum72
Range72
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.4126286
Coefficient of variation (CV)0.79318693
Kurtosis2.3002058
Mean11.866848
Median Absolute Deviation (MAD)5
Skewness1.3642366
Sum26202
Variance88.597577
MonotonicityNot monotonic
2023-12-12T17:19:52.445270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 143
 
6.5%
3 141
 
6.4%
9 126
 
5.7%
5 126
 
5.7%
6 118
 
5.3%
8 108
 
4.9%
10 107
 
4.8%
2 105
 
4.8%
7 103
 
4.7%
11 99
 
4.5%
Other values (44) 1032
46.7%
ValueCountFrequency (%)
0 44
 
2.0%
1 85
3.8%
2 105
4.8%
3 141
6.4%
4 143
6.5%
5 126
5.7%
6 118
5.3%
7 103
4.7%
8 108
4.9%
9 126
5.7%
ValueCountFrequency (%)
72 1
< 0.1%
60 1
< 0.1%
59 1
< 0.1%
52 1
< 0.1%
51 1
< 0.1%
50 2
0.1%
49 1
< 0.1%
48 1
< 0.1%
45 2
0.1%
44 2
0.1%

미세먼지(PM)10
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct61
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.220562
Minimum0
Maximum79
Zeros26
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2023-12-12T17:19:52.647512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16
median11
Q319
95-th percentile38
Maximum79
Range79
Interquartile range (IQR)13

Descriptive statistics

Standard deviation11.276714
Coefficient of variation (CV)0.79298658
Kurtosis3.402619
Mean14.220562
Median Absolute Deviation (MAD)6
Skewness1.6030496
Sum31399
Variance127.16429
MonotonicityNot monotonic
2023-12-12T17:19:52.837963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 126
 
5.7%
10 125
 
5.7%
5 118
 
5.3%
6 106
 
4.8%
9 105
 
4.8%
12 101
 
4.6%
7 99
 
4.5%
3 97
 
4.4%
8 96
 
4.3%
11 95
 
4.3%
Other values (51) 1140
51.6%
ValueCountFrequency (%)
0 26
 
1.2%
1 48
 
2.2%
2 77
3.5%
3 97
4.4%
4 126
5.7%
5 118
5.3%
6 106
4.8%
7 99
4.5%
8 96
4.3%
9 105
4.8%
ValueCountFrequency (%)
79 2
0.1%
72 2
0.1%
68 1
 
< 0.1%
67 2
0.1%
61 2
0.1%
60 2
0.1%
57 2
0.1%
56 2
0.1%
53 4
0.2%
52 2
0.1%

온도(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct867
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.610457
Minimum22.39
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2023-12-12T17:19:53.050514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.39
5-th percentile24.98
Q126.9775
median29.005
Q331.64
95-th percentile36.5695
Maximum76
Range53.61
Interquartile range (IQR)4.6625

Descriptive statistics

Standard deviation3.645055
Coefficient of variation (CV)0.12310026
Kurtosis11.489466
Mean29.610457
Median Absolute Deviation (MAD)2.225
Skewness1.5273431
Sum65379.89
Variance13.286426
MonotonicityNot monotonic
2023-12-12T17:19:53.245396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.38 11
 
0.5%
28.67 11
 
0.5%
26.66 10
 
0.5%
27.97 10
 
0.5%
29.2 9
 
0.4%
26.98 9
 
0.4%
26.42 8
 
0.4%
29.9 8
 
0.4%
30.31 8
 
0.4%
27.13 8
 
0.4%
Other values (857) 2116
95.8%
ValueCountFrequency (%)
22.39 1
< 0.1%
22.55 1
< 0.1%
22.65 1
< 0.1%
22.68 1
< 0.1%
22.7 1
< 0.1%
22.79 1
< 0.1%
22.87 1
< 0.1%
22.89 1
< 0.1%
22.9 1
< 0.1%
22.97 1
< 0.1%
ValueCountFrequency (%)
76.0 1
< 0.1%
40.52 1
< 0.1%
40.4 1
< 0.1%
39.83 1
< 0.1%
39.78 1
< 0.1%
39.73 1
< 0.1%
39.72 1
< 0.1%
39.7 1
< 0.1%
39.63 1
< 0.1%
39.56 1
< 0.1%

습도(퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct1708
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.486386
Minimum40.02
Maximum88.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.5 KiB
2023-12-12T17:19:53.441842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40.02
5-th percentile49.1005
Q160.6525
median68.96
Q377.4125
95-th percentile84.476
Maximum88.78
Range48.76
Interquartile range (IQR)16.76

Descriptive statistics

Standard deviation10.837177
Coefficient of variation (CV)0.15823841
Kurtosis-0.74380377
Mean68.486386
Median Absolute Deviation (MAD)8.42
Skewness-0.28393988
Sum151217.94
Variance117.4444
MonotonicityNot monotonic
2023-12-12T17:19:53.591314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.87 5
 
0.2%
62.56 5
 
0.2%
65.5 4
 
0.2%
68.16 4
 
0.2%
58.6 4
 
0.2%
77.38 4
 
0.2%
67.14 4
 
0.2%
68.12 4
 
0.2%
73.24 4
 
0.2%
70.59 4
 
0.2%
Other values (1698) 2166
98.1%
ValueCountFrequency (%)
40.02 1
< 0.1%
40.79 1
< 0.1%
41.72 1
< 0.1%
42.02 1
< 0.1%
42.28 1
< 0.1%
42.32 1
< 0.1%
42.41 1
< 0.1%
42.44 1
< 0.1%
42.56 1
< 0.1%
42.98 1
< 0.1%
ValueCountFrequency (%)
88.78 1
< 0.1%
88.72 1
< 0.1%
88.7 1
< 0.1%
88.48 1
< 0.1%
88.2 1
< 0.1%
87.91 1
< 0.1%
87.78 1
< 0.1%
87.53 1
< 0.1%
87.5 1
< 0.1%
87.47 1
< 0.1%

Interactions

2023-12-12T17:19:50.756762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.089042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.642553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.234019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.892755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.235286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.788523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.381910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:51.010356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.361130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.968099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.522339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:51.137196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:49.500205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.099376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:50.638855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:19:53.686693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
미세먼지(PM)2_51.0000.9780.3160.301
미세먼지(PM)100.9781.0000.2940.312
온도(섭씨)0.3160.2941.0000.802
습도(퍼센트)0.3010.3120.8021.000
2023-12-12T17:19:53.786979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
미세먼지(PM)2_51.0000.9840.255-0.188
미세먼지(PM)100.9841.0000.231-0.157
온도(섭씨)0.2550.2311.000-0.659
습도(퍼센트)-0.188-0.157-0.6591.000

Missing values

2023-12-12T17:19:51.297593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:19:51.480962image/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

시간측정소미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
02023-07-01 00:00낙포부두 실외2225.3383.01
12023-07-01 01:00낙포부두 실외4425.3383.36
22023-07-01 02:00낙포부두 실외61025.3383.83
32023-07-01 03:00낙포부두 실외182525.0684.53
42023-07-01 04:00낙포부두 실외212524.8984.87
52023-07-01 05:00낙포부두 실외233324.9185.55
62023-07-01 06:00낙포부두 실외323724.8585.64
72023-07-01 07:00낙포부두 실외141724.8585.4
82023-07-01 08:00낙포부두 실외4424.7884.64
92023-07-01 09:00낙포부두 실외6725.284.29
시간측정소미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
21982023-09-30 14:00낙포부두 실외161826.3959.73
21992023-09-30 15:00낙포부두 실외111327.0456.16
22002023-09-30 16:00낙포부두 실외101026.9753.72
22012023-09-30 17:00낙포부두 실외5526.7153.58
22022023-09-30 18:00낙포부두 실외6626.2654.52
22032023-09-30 19:00낙포부두 실외111625.4856.3
22042023-09-30 20:00낙포부두 실외71024.8657.42
22052023-09-30 21:00낙포부두 실외101124.3458.4
22062023-09-30 22:00낙포부두 실외91523.9559.6
22072023-09-30 23:00낙포부두 실외91523.9559.6