Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells281
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory595.7 KiB
Average record size in memory61.0 B

Variable types

DateTime1
Numeric5

Dataset

Description부산광역시_대기질진단평가대기질측정소기상정보_20230825
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15120972

Alerts

대기질지점코드 has 256 (2.6%) missing valuesMissing
풍속 is highly skewed (γ1 = 29.58096264)Skewed
풍속 has 198 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 16:26:32.978797
Analysis finished2023-12-10 16:26:37.934152
Duration4.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정날짜
Date

Distinct2048
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2023-08-25 16:00:00
2023-12-11T01:26:38.037270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:38.226145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

대기질지점코드
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)0.3%
Missing256
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean243260.84
Minimum221112
Maximum999913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:26:38.459410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum221112
5-th percentile221131
Q1221172
median221193
Q3221241
95-th percentile221284
Maximum999913
Range778801
Interquartile range (IQR)69

Descriptive statistics

Standard deviation129194.49
Coefficient of variation (CV)0.53109449
Kurtosis30.349677
Mean243260.84
Median Absolute Deviation (MAD)31
Skewness5.6871296
Sum2.3703337 × 109
Variance1.6691217 × 1010
MonotonicityNot monotonic
2023-12-11T01:26:39.106974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
221162 333
 
3.3%
221202 333
 
3.3%
221212 326
 
3.3%
221193 325
 
3.2%
221112 325
 
3.2%
221283 321
 
3.2%
221231 316
 
3.2%
221191 313
 
3.1%
221182 313
 
3.1%
221172 312
 
3.1%
Other values (22) 6527
65.3%
ValueCountFrequency (%)
221112 325
3.2%
221131 312
3.1%
221141 285
2.9%
221142 282
2.8%
221152 308
3.1%
221162 333
3.3%
221163 304
3.0%
221172 312
3.1%
221174 298
3.0%
221181 281
2.8%
ValueCountFrequency (%)
999913 276
2.8%
221284 301
3.0%
221283 321
3.2%
221282 301
3.0%
221281 301
3.0%
221271 312
3.1%
221253 286
2.9%
221251 300
3.0%
221241 283
2.8%
221233 308
3.1%

풍향
Real number (ℝ)

Distinct3028
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.42889
Minimum0
Maximum360
Zeros52
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:26:39.291945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.9
Q193.375
median176.45
Q3241.425
95-th percentile331.605
Maximum360
Range360
Interquartile range (IQR)148.05

Descriptive statistics

Standard deviation95.901756
Coefficient of variation (CV)0.55942587
Kurtosis-0.94191514
Mean171.42889
Median Absolute Deviation (MAD)73.55
Skewness0.014902815
Sum1714288.9
Variance9197.1468
MonotonicityNot monotonic
2023-12-11T01:26:39.511044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 52
 
0.5%
204.0 28
 
0.3%
207.0 26
 
0.3%
187.0 26
 
0.3%
143.0 26
 
0.3%
147.0 25
 
0.2%
203.0 25
 
0.2%
137.0 24
 
0.2%
166.0 21
 
0.2%
193.0 21
 
0.2%
Other values (3018) 9726
97.3%
ValueCountFrequency (%)
0.0 52
0.5%
0.1 2
 
< 0.1%
0.2 1
 
< 0.1%
0.3 1
 
< 0.1%
0.4 3
 
< 0.1%
0.5 4
 
< 0.1%
0.6 1
 
< 0.1%
0.7 1
 
< 0.1%
0.8 2
 
< 0.1%
0.9 1
 
< 0.1%
ValueCountFrequency (%)
360.0 6
0.1%
359.9 3
< 0.1%
359.6 3
< 0.1%
359.5 3
< 0.1%
359.4 2
 
< 0.1%
359.3 3
< 0.1%
359.2 4
< 0.1%
359.1 1
 
< 0.1%
359.0 6
0.1%
358.9 2
 
< 0.1%

풍속
Real number (ℝ)

SKEWED  ZEROS 

Distinct79
Distinct (%)0.8%
Missing25
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean0.95461654
Minimum0
Maximum79.6
Zeros198
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:26:39.735590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.3
median0.7
Q31.3
95-th percentile2.4
Maximum79.6
Range79.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.808128
Coefficient of variation (CV)1.8940882
Kurtosis1116.6145
Mean0.95461654
Median Absolute Deviation (MAD)0.4
Skewness29.580963
Sum9522.3
Variance3.2693267
MonotonicityNot monotonic
2023-12-11T01:26:39.930712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 831
 
8.3%
0.1 810
 
8.1%
0.3 760
 
7.6%
0.4 730
 
7.3%
0.5 712
 
7.1%
0.6 669
 
6.7%
0.7 564
 
5.6%
0.8 563
 
5.6%
0.9 488
 
4.9%
1.0 374
 
3.7%
Other values (69) 3474
34.7%
ValueCountFrequency (%)
0.0 198
 
2.0%
0.1 810
8.1%
0.2 831
8.3%
0.3 760
7.6%
0.4 730
7.3%
0.5 712
7.1%
0.6 669
6.7%
0.7 564
5.6%
0.8 563
5.6%
0.9 488
4.9%
ValueCountFrequency (%)
79.6 1
< 0.1%
74.3 1
< 0.1%
70.1 1
< 0.1%
64.9 1
< 0.1%
52.0 1
< 0.1%
48.9 1
< 0.1%
25.4 1
< 0.1%
14.5 1
< 0.1%
10.0 1
< 0.1%
8.7 1
< 0.1%

기온
Real number (ℝ)

Distinct287
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.97924
Minimum-40
Maximum43
Zeros0
Zeros (%)0.0%
Negative128
Negative (%)1.3%
Memory size166.0 KiB
2023-12-11T01:26:40.127428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40
5-th percentile19.6
Q123.3
median25.7
Q327.9
95-th percentile31.9
Maximum43
Range83
Interquartile range (IQR)4.6

Descriptive statistics

Standard deviation7.8914358
Coefficient of variation (CV)0.31591977
Kurtosis47.57277
Mean24.97924
Median Absolute Deviation (MAD)2.3
Skewness-6.1929485
Sum249792.4
Variance62.274758
MonotonicityNot monotonic
2023-12-11T01:26:40.322047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.7 156
 
1.6%
26.4 141
 
1.4%
26.1 139
 
1.4%
25.5 130
 
1.3%
26.2 130
 
1.3%
26.0 129
 
1.3%
26.8 129
 
1.3%
24.8 128
 
1.3%
26.9 123
 
1.2%
25.1 122
 
1.2%
Other values (277) 8673
86.7%
ValueCountFrequency (%)
-40.0 1
 
< 0.1%
-39.9 52
0.5%
-39.8 45
0.4%
-39.3 1
 
< 0.1%
-38.7 1
 
< 0.1%
-38.2 1
 
< 0.1%
-37.5 1
 
< 0.1%
-37.3 1
 
< 0.1%
-37.2 1
 
< 0.1%
-37.0 1
 
< 0.1%
ValueCountFrequency (%)
43.0 1
< 0.1%
37.4 1
< 0.1%
37.2 1
< 0.1%
37.1 2
< 0.1%
37.0 1
< 0.1%
36.9 1
< 0.1%
36.8 2
< 0.1%
36.7 1
< 0.1%
36.6 1
< 0.1%
36.5 1
< 0.1%

상대습도
Real number (ℝ)

Distinct658
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.22216
Minimum0
Maximum100
Zeros25
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T01:26:40.523550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49
Q168.575
median81
Q392
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)23.425

Descriptive statistics

Standard deviation18.186314
Coefficient of variation (CV)0.23249568
Kurtosis3.7009162
Mean78.22216
Median Absolute Deviation (MAD)11.6
Skewness-1.4795519
Sum782221.6
Variance330.74203
MonotonicityNot monotonic
2023-12-11T01:26:40.760468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 750
 
7.5%
99.9 151
 
1.5%
79.0 119
 
1.2%
98.0 117
 
1.2%
86.0 112
 
1.1%
76.0 110
 
1.1%
81.0 105
 
1.1%
82.0 102
 
1.0%
75.0 101
 
1.0%
80.0 100
 
1.0%
Other values (648) 8233
82.3%
ValueCountFrequency (%)
0.0 25
0.2%
0.1 12
 
0.1%
0.2 19
 
0.2%
1.0 56
0.6%
1.1 1
 
< 0.1%
1.2 24
0.2%
1.3 1
 
< 0.1%
1.4 1
 
< 0.1%
1.5 1
 
< 0.1%
1.8 2
 
< 0.1%
ValueCountFrequency (%)
100.0 750
7.5%
99.9 151
 
1.5%
99.8 24
 
0.2%
99.7 9
 
0.1%
99.6 17
 
0.2%
99.5 11
 
0.1%
99.4 14
 
0.1%
99.3 14
 
0.1%
99.2 12
 
0.1%
99.1 22
 
0.2%

Interactions

2023-12-11T01:26:36.839763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:33.945248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.715348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.466774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.231193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.998429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.119254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.883466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.659378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.362371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:37.154258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.273261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.005161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.845223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.481486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:37.317438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.443795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.164091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.983954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.597231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:37.447818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:34.574709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:35.308769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.115561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:26:36.718235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:26:40.905087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대기질지점코드풍향풍속기온상대습도
대기질지점코드1.0000.2040.0000.0650.104
풍향0.2041.0000.0500.0840.132
풍속0.0000.0501.0000.0830.043
기온0.0650.0840.0831.0000.780
상대습도0.1040.1320.0430.7801.000
2023-12-11T01:26:41.047785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대기질지점코드풍향풍속기온상대습도
대기질지점코드1.0000.003-0.0890.018-0.003
풍향0.0031.000-0.001-0.0210.021
풍속-0.089-0.0011.0000.152-0.152
기온0.018-0.0210.1521.000-0.330
상대습도-0.0030.021-0.152-0.3301.000

Missing values

2023-12-11T01:26:37.601231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:26:37.753559image/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.
2023-12-11T01:26:37.869710image/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

측정날짜대기질지점코드풍향풍속기온상대습도
673622023-08-25 15:00221181249.31.326.960.0
132862023-06-17 21:00221213275.01.925.351.0
521312023-08-06 08:0022118418.70.430.071.8
653002023-08-23 00:00221271157.60.728.884.0
457512023-07-29 06:00<NA>144.50.225.089.0
386822023-07-20 06:00221112157.60.422.294.0
455112023-07-28 23:00221241304.01.328.376.9
646402023-08-22 04:002212512.71.025.688.4
252432023-07-03 02:0022116328.00.424.799.0
500572023-08-03 17:00221211254.81.534.356.3
측정날짜대기질지점코드풍향풍속기온상대습도
607512023-08-17 06:0022121183.60.424.9100.0
359992023-07-16 19:00221211241.50.323.8100.0
521982023-08-06 10:00221191121.91.635.464.9
449082023-07-28 05:00221192118.80.627.079.9
111582023-06-15 02:00221241304.01.918.880.2
429672023-07-25 18:00221221160.00.430.667.1
265012023-07-04 17:00221191134.40.428.593.0
178992023-06-23 18:00221213140.51.125.762.6
66822023-06-09 11:00221141192.00.921.380.0
447652023-07-28 01:0022114221.00.129.474.0