Overview

Dataset statistics

Number of variables6
Number of observations4416
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory224.4 KiB
Average record size in memory52.0 B

Variable types

DateTime1
Categorical1
Numeric4

Dataset

Description광양항 낙포부두 청원경찰 근무초소 대기정보 데이터입니다. 데이터 구성은 시간, 측정소, PM2.5수치, PM10수치, 온도, 습도로 구성되어 있습니다. 데이터 갱신주기는 반기입니다.
Author여수광양항만공사
URLhttps://www.data.go.kr/data/15121194/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
시간 has unique valuesUnique
미세먼지(PM)2_5 has 541 (12.3%) zerosZeros
미세먼지(PM)10 has 329 (7.5%) zerosZeros

Reproduction

Analysis started2024-03-14 18:59:58.918845
Analysis finished2024-03-14 19:00:03.333936
Duration4.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시간
Date

UNIQUE 

Distinct4416
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size34.6 KiB
Minimum2023-07-01 00:00:00
Maximum2023-12-31 23:00:00
2024-03-15T04:00:03.452384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:03.786251image/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 size34.6 KiB
낙포부두 청원경찰 근무초소 실내
4416 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row낙포부두 청원경찰 근무초소 실내
2nd row낙포부두 청원경찰 근무초소 실내
3rd row낙포부두 청원경찰 근무초소 실내
4th row낙포부두 청원경찰 근무초소 실내
5th row낙포부두 청원경찰 근무초소 실내

Common Values

ValueCountFrequency (%)
낙포부두 청원경찰 근무초소 실내 4416
100.0%

Length

2024-03-15T04:00:04.033366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:00:04.200907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
낙포부두 4416
25.0%
청원경찰 4416
25.0%
근무초소 4416
25.0%
실내 4416
25.0%

미세먼지(PM)2_5
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2316576
Minimum0
Maximum228
Zeros541
Zeros (%)12.3%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-03-15T04:00:04.622067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q38
95-th percentile20
Maximum228
Range228
Interquartile range (IQR)7

Descriptive statistics

Standard deviation8.3684682
Coefficient of variation (CV)1.342896
Kurtosis127.515
Mean6.2316576
Median Absolute Deviation (MAD)3
Skewness7.0049698
Sum27519
Variance70.03126
MonotonicityNot monotonic
2024-03-15T04:00:05.046397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 569
12.9%
0 541
12.3%
2 509
11.5%
3 460
10.4%
4 342
 
7.7%
5 320
 
7.2%
6 281
 
6.4%
7 185
 
4.2%
8 178
 
4.0%
9 144
 
3.3%
Other values (52) 887
20.1%
ValueCountFrequency (%)
0 541
12.3%
1 569
12.9%
2 509
11.5%
3 460
10.4%
4 342
7.7%
5 320
7.2%
6 281
6.4%
7 185
 
4.2%
8 178
 
4.0%
9 144
 
3.3%
ValueCountFrequency (%)
228 1
< 0.1%
93 1
< 0.1%
89 1
< 0.1%
84 1
< 0.1%
83 1
< 0.1%
78 1
< 0.1%
73 1
< 0.1%
72 1
< 0.1%
71 1
< 0.1%
66 1
< 0.1%

미세먼지(PM)10
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.2085598
Minimum0
Maximum249
Zeros329
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-03-15T04:00:05.391570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile22
Maximum249
Range249
Interquartile range (IQR)7

Descriptive statistics

Standard deviation9.2732145
Coefficient of variation (CV)1.2864171
Kurtosis119.63447
Mean7.2085598
Median Absolute Deviation (MAD)3
Skewness6.8311516
Sum31833
Variance85.992507
MonotonicityNot monotonic
2024-03-15T04:00:05.648651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 505
11.4%
2 486
11.0%
3 449
10.2%
4 376
 
8.5%
5 342
 
7.7%
0 329
 
7.5%
6 312
 
7.1%
7 212
 
4.8%
8 202
 
4.6%
9 152
 
3.4%
Other values (59) 1051
23.8%
ValueCountFrequency (%)
0 329
7.5%
1 505
11.4%
2 486
11.0%
3 449
10.2%
4 376
8.5%
5 342
7.7%
6 312
7.1%
7 212
4.8%
8 202
 
4.6%
9 152
 
3.4%
ValueCountFrequency (%)
249 1
 
< 0.1%
100 1
 
< 0.1%
87 1
 
< 0.1%
86 1
 
< 0.1%
83 1
 
< 0.1%
82 1
 
< 0.1%
79 2
< 0.1%
77 1
 
< 0.1%
76 1
 
< 0.1%
74 3
0.1%

온도(섭씨)
Real number (ℝ)

Distinct679
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.493745
Minimum24.66
Maximum45.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-03-15T04:00:06.001551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.66
5-th percentile26.8
Q128.1
median29.12
Q330.49
95-th percentile33.44
Maximum45.66
Range21
Interquartile range (IQR)2.39

Descriptive statistics

Standard deviation2.0160749
Coefficient of variation (CV)0.068356016
Kurtosis0.96970746
Mean29.493745
Median Absolute Deviation (MAD)1.13
Skewness0.81131688
Sum130244.38
Variance4.0645582
MonotonicityNot monotonic
2024-03-15T04:00:06.416537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.68 27
 
0.6%
29.31 24
 
0.5%
29.61 24
 
0.5%
28.65 23
 
0.5%
28.18 22
 
0.5%
29.33 22
 
0.5%
28.58 22
 
0.5%
28.28 22
 
0.5%
28.06 21
 
0.5%
29.34 21
 
0.5%
Other values (669) 4188
94.8%
ValueCountFrequency (%)
24.66 2
< 0.1%
24.75 1
< 0.1%
24.89 1
< 0.1%
24.96 1
< 0.1%
25.06 1
< 0.1%
25.12 1
< 0.1%
25.13 1
< 0.1%
25.16 1
< 0.1%
25.17 2
< 0.1%
25.26 1
< 0.1%
ValueCountFrequency (%)
45.66 1
 
< 0.1%
36.06 1
 
< 0.1%
36.0 1
 
< 0.1%
35.98 1
 
< 0.1%
35.96 3
0.1%
35.95 1
 
< 0.1%
35.93 1
 
< 0.1%
35.9 1
 
< 0.1%
35.88 1
 
< 0.1%
35.81 1
 
< 0.1%

습도(퍼센트)
Real number (ℝ)

Distinct2611
Distinct (%)59.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.242652
Minimum11.74
Maximum66.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size38.9 KiB
2024-03-15T04:00:06.837941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.74
5-th percentile16.7975
Q129.81
median37.805
Q343.58
95-th percentile53.225
Maximum66.26
Range54.52
Interquartile range (IQR)13.77

Descriptive statistics

Standard deviation10.867311
Coefficient of variation (CV)0.29984868
Kurtosis-0.58496599
Mean36.242652
Median Absolute Deviation (MAD)6.505
Skewness-0.28233256
Sum160047.55
Variance118.09845
MonotonicityNot monotonic
2024-03-15T04:00:07.287820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.89 9
 
0.2%
39.92 9
 
0.2%
34.52 8
 
0.2%
40.21 7
 
0.2%
34.54 7
 
0.2%
36.8 6
 
0.1%
40.75 6
 
0.1%
36.44 6
 
0.1%
44.31 6
 
0.1%
15.85 6
 
0.1%
Other values (2601) 4346
98.4%
ValueCountFrequency (%)
11.74 1
< 0.1%
12.99 1
< 0.1%
13.1 1
< 0.1%
13.56 1
< 0.1%
13.8 1
< 0.1%
13.82 1
< 0.1%
13.84 1
< 0.1%
13.88 1
< 0.1%
14.01 2
< 0.1%
14.07 1
< 0.1%
ValueCountFrequency (%)
66.26 1
< 0.1%
63.58 1
< 0.1%
63.38 1
< 0.1%
62.05 1
< 0.1%
61.8 1
< 0.1%
61.74 1
< 0.1%
61.73 1
< 0.1%
61.55 1
< 0.1%
61.31 1
< 0.1%
60.88 1
< 0.1%

Interactions

2024-03-15T04:00:02.172644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:59:59.192155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:00.279706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:01.300880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:02.326447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:59:59.442168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:00.533950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:01.554835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:02.594195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:59:59.700711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:00.768164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:01.838923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:02.819727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:59:59.997622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:01.027671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:00:02.017631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:00:07.610687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
미세먼지(PM)2_51.0000.9970.1600.175
미세먼지(PM)100.9971.0000.1550.163
온도(섭씨)0.1600.1551.0000.586
습도(퍼센트)0.1750.1630.5861.000
2024-03-15T04:00:07.859138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
미세먼지(PM)2_51.0000.9780.179-0.176
미세먼지(PM)100.9781.0000.168-0.166
온도(섭씨)0.1790.1681.000-0.405
습도(퍼센트)-0.176-0.166-0.4051.000

Missing values

2024-03-15T04:00:03.064177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:00:03.254792image/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 청원경찰 근무초소 실내0127.5347.23
12023-07-01 01:00낙포부두 청원경찰 근무초소 실내0027.5247.09
22023-07-01 02:00낙포부두 청원경찰 근무초소 실내0027.5647.5
32023-07-01 03:00낙포부두 청원경찰 근무초소 실내0027.6247.59
42023-07-01 04:00낙포부두 청원경찰 근무초소 실내0027.6247.29
52023-07-01 05:00낙포부두 청원경찰 근무초소 실내1327.6247.72
62023-07-01 06:00낙포부두 청원경찰 근무초소 실내3327.649.68
72023-07-01 07:00낙포부두 청원경찰 근무초소 실내2327.5752.56
82023-07-01 08:00낙포부두 청원경찰 근무초소 실내2228.056.1
92023-07-01 09:00낙포부두 청원경찰 근무초소 실내1127.9454.78
시간측정소미세먼지(PM)2_5미세먼지(PM)10온도(섭씨)습도(퍼센트)
44062023-12-31 14:00낙포부두 청원경찰 근무초소 실내7733.9222.53
44072023-12-31 15:00낙포부두 청원경찰 근무초소 실내101233.5820.58
44082023-12-31 16:00낙포부두 청원경찰 근무초소 실내141432.9418.78
44092023-12-31 17:00낙포부두 청원경찰 근무초소 실내161731.9218.84
44102023-12-31 18:00낙포부두 청원경찰 근무초소 실내181831.9519.39
44112023-12-31 19:00낙포부두 청원경찰 근무초소 실내171732.219.34
44122023-12-31 20:00낙포부두 청원경찰 근무초소 실내161632.4319.22
44132023-12-31 21:00낙포부두 청원경찰 근무초소 실내161832.3919.63
44142023-12-31 22:00낙포부두 청원경찰 근무초소 실내171932.4219.82
44152023-12-31 23:00낙포부두 청원경찰 근무초소 실내171932.3719.57