Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells20000
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory134.0 B

Variable types

Numeric10
Categorical2
Unsupported2

Dataset

Description충청남도 재난안전포털에서 제공하는 초단기 기상실황 데이터입니다.(발표일자,발표시각, 기온, 1시간 강수량 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=32&beforeMenuCd=DOM_000000201001001000&publicdatapk=15118435

Alerts

생활기상 발표시각 is highly overall correlated with 기온High correlation
기온 is highly overall correlated with 생활기상 발표시각 and 1 other fieldsHigh correlation
동서바람성분 is highly overall correlated with 풍속High correlation
습도 is highly overall correlated with 기온High correlation
풍속 is highly overall correlated with 동서바람성분High correlation
강수형태 is highly imbalanced (90.5%)Imbalance
하늘상태 has 10000 (100.0%) missing valuesMissing
낙뢰 has 10000 (100.0%) missing valuesMissing
1시간 강수량 is highly skewed (γ1 = 21.4043154)Skewed
하늘상태 is an unsupported type, check if it needs cleaning or further analysisUnsupported
낙뢰 is an unsupported type, check if it needs cleaning or further analysisUnsupported
생활기상 발표시각 has 461 (4.6%) zerosZeros
1시간 강수량 has 9895 (99.0%) zerosZeros
동서바람성분 has 4584 (45.8%) zerosZeros
남북바람성분 has 6032 (60.3%) zerosZeros
풍향 has 202 (2.0%) zerosZeros
풍속 has 2614 (26.1%) zerosZeros

Reproduction

Analysis started2024-01-09 21:31:32.837902
Analysis finished2024-01-09 21:31:43.794119
Duration10.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

X좌표
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.9376
Minimum46
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:43.843900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile50
Q154
median57
Q362
95-th percentile68
Maximum70
Range24
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.2854423
Coefficient of variation (CV)0.091226462
Kurtosis-0.47412877
Mean57.9376
Median Absolute Deviation (MAD)4
Skewness0.20119682
Sum579376
Variance27.9359
MonotonicityNot monotonic
2024-01-10T06:31:43.941614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
55 1064
 
10.6%
57 924
 
9.2%
63 810
 
8.1%
53 687
 
6.9%
61 679
 
6.8%
56 620
 
6.2%
60 502
 
5.0%
58 497
 
5.0%
54 494
 
4.9%
65 491
 
4.9%
Other values (15) 3232
32.3%
ValueCountFrequency (%)
46 62
 
0.6%
47 60
 
0.6%
48 248
 
2.5%
49 125
 
1.2%
50 188
 
1.9%
51 316
 
3.2%
52 434
4.3%
53 687
6.9%
54 494
4.9%
55 1064
10.6%
ValueCountFrequency (%)
70 188
 
1.9%
69 183
 
1.8%
68 183
 
1.8%
67 62
 
0.6%
66 125
 
1.2%
65 491
4.9%
64 189
 
1.9%
63 810
8.1%
62 428
4.3%
61 679
6.8%

Y좌표
Real number (ℝ)

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.6215
Minimum93
Maximum114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:44.032146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum93
5-th percentile95
Q198
median104
Q3109
95-th percentile112
Maximum114
Range21
Interquartile range (IQR)11

Descriptive statistics

Standard deviation5.9810212
Coefficient of variation (CV)0.057719887
Kurtosis-1.359674
Mean103.6215
Median Absolute Deviation (MAD)6
Skewness-0.054906685
Sum1036215
Variance35.772615
MonotonicityNot monotonic
2024-01-10T06:31:44.115434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
110 1001
 
10.0%
96 866
 
8.7%
109 684
 
6.8%
97 676
 
6.8%
104 559
 
5.6%
102 555
 
5.5%
111 509
 
5.1%
99 497
 
5.0%
108 493
 
4.9%
112 437
 
4.4%
Other values (12) 3723
37.2%
ValueCountFrequency (%)
93 124
 
1.2%
94 308
 
3.1%
95 376
3.8%
96 866
8.7%
97 676
6.8%
98 368
3.7%
99 497
5.0%
100 434
4.3%
101 377
3.8%
102 555
5.5%
ValueCountFrequency (%)
114 63
 
0.6%
113 377
 
3.8%
112 437
4.4%
111 509
5.1%
110 1001
10.0%
109 684
6.8%
108 493
4.9%
107 364
 
3.6%
106 369
 
3.7%
105 313
 
3.1%

발표일자
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20230807
3699 
20230808
3693 
20230809
2608 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20230808
2nd row20230808
3rd row20230807
4th row20230808
5th row20230808

Common Values

ValueCountFrequency (%)
20230807 3699
37.0%
20230808 3693
36.9%
20230809 2608
26.1%

Length

2024-01-10T06:31:44.203890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:31:44.274969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20230807 3699
37.0%
20230808 3693
36.9%
20230809 2608
26.1%

생활기상 발표시각
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1057.68
Minimum0
Maximum2300
Zeros461
Zeros (%)4.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:44.349047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile100
Q1500
median1000
Q31600
95-th percentile2200
Maximum2300
Range2300
Interquartile range (IQR)1100

Descriptive statistics

Standard deviation663.692
Coefficient of variation (CV)0.62749792
Kurtosis-1.0637309
Mean1057.68
Median Absolute Deviation (MAD)500
Skewness0.15507642
Sum10576800
Variance440487.07
MonotonicityNot monotonic
2024-01-10T06:31:44.434445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
800 470
 
4.7%
200 468
 
4.7%
600 468
 
4.7%
1100 464
 
4.6%
500 463
 
4.6%
400 463
 
4.6%
1300 461
 
4.6%
0 461
 
4.6%
1000 461
 
4.6%
1500 461
 
4.6%
Other values (14) 5360
53.6%
ValueCountFrequency (%)
0 461
4.6%
100 459
4.6%
200 468
4.7%
300 459
4.6%
400 463
4.6%
500 463
4.6%
600 468
4.7%
700 458
4.6%
800 470
4.7%
900 455
4.5%
ValueCountFrequency (%)
2300 303
3.0%
2200 312
3.1%
2100 306
3.1%
2000 314
3.1%
1900 304
3.0%
1800 312
3.1%
1700 305
3.0%
1600 457
4.6%
1500 461
4.6%
1400 459
4.6%

기온
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.6645
Minimum23
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:44.515851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile25
Q126
median28
Q331
95-th percentile34
Maximum36
Range13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0366201
Coefficient of variation (CV)0.10593662
Kurtosis-0.87000089
Mean28.6645
Median Absolute Deviation (MAD)2
Skewness0.3929463
Sum286645
Variance9.2210619
MonotonicityNot monotonic
2024-01-10T06:31:44.604754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
26 1535
15.3%
27 1269
12.7%
25 1060
10.6%
30 1047
10.5%
28 959
9.6%
29 824
8.2%
31 760
7.6%
32 612
 
6.1%
34 598
 
6.0%
33 597
 
6.0%
Other values (4) 739
7.4%
ValueCountFrequency (%)
23 34
 
0.3%
24 443
 
4.4%
25 1060
10.6%
26 1535
15.3%
27 1269
12.7%
28 959
9.6%
29 824
8.2%
30 1047
10.5%
31 760
7.6%
32 612
 
6.1%
ValueCountFrequency (%)
36 53
 
0.5%
35 209
 
2.1%
34 598
6.0%
33 597
6.0%
32 612
6.1%
31 760
7.6%
30 1047
10.5%
29 824
8.2%
28 959
9.6%
27 1269
12.7%

1시간 강수량
Real number (ℝ)

SKEWED  ZEROS 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0675
Minimum0
Maximum33
Zeros9895
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:44.699359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0295872
Coefficient of variation (CV)15.253143
Kurtosis537.42622
Mean0.0675
Median Absolute Deviation (MAD)0
Skewness21.404315
Sum675
Variance1.0600498
MonotonicityNot monotonic
2024-01-10T06:31:44.801712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 9895
99.0%
1 39
 
0.4%
2 14
 
0.1%
13 13
 
0.1%
6 13
 
0.1%
16 9
 
0.1%
3 7
 
0.1%
4 4
 
< 0.1%
33 3
 
< 0.1%
27 3
 
< 0.1%
ValueCountFrequency (%)
0 9895
99.0%
1 39
 
0.4%
2 14
 
0.1%
3 7
 
0.1%
4 4
 
< 0.1%
6 13
 
0.1%
13 13
 
0.1%
16 9
 
0.1%
27 3
 
< 0.1%
33 3
 
< 0.1%
ValueCountFrequency (%)
33 3
 
< 0.1%
27 3
 
< 0.1%
16 9
 
0.1%
13 13
 
0.1%
6 13
 
0.1%
4 4
 
< 0.1%
3 7
 
0.1%
2 14
 
0.1%
1 39
 
0.4%
0 9895
99.0%

하늘상태
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

동서바람성분
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.7023
Minimum-8
Maximum5
Zeros4584
Zeros (%)45.8%
Negative4825
Negative (%)48.2%
Memory size166.0 KiB
2024-01-10T06:31:44.884392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8
5-th percentile-3
Q1-1
median0
Q30
95-th percentile1
Maximum5
Range13
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1627596
Coefficient of variation (CV)-1.6556452
Kurtosis3.5285259
Mean-0.7023
Median Absolute Deviation (MAD)1
Skewness-0.97165428
Sum-7023
Variance1.3520099
MonotonicityNot monotonic
2024-01-10T06:31:44.969679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 4584
45.8%
-1 2740
27.4%
-2 1480
 
14.8%
-3 404
 
4.0%
1 391
 
3.9%
2 160
 
1.6%
-4 126
 
1.3%
3 34
 
0.3%
-5 28
 
0.3%
-6 27
 
0.3%
Other values (4) 26
 
0.3%
ValueCountFrequency (%)
-8 3
 
< 0.1%
-7 17
 
0.2%
-6 27
 
0.3%
-5 28
 
0.3%
-4 126
 
1.3%
-3 404
 
4.0%
-2 1480
 
14.8%
-1 2740
27.4%
0 4584
45.8%
1 391
 
3.9%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 5
 
0.1%
3 34
 
0.3%
2 160
 
1.6%
1 391
 
3.9%
0 4584
45.8%
-1 2740
27.4%
-2 1480
 
14.8%
-3 404
 
4.0%
-4 126
 
1.3%

남북바람성분
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.4058
Minimum-6
Maximum5
Zeros6032
Zeros (%)60.3%
Negative3488
Negative (%)34.9%
Memory size166.0 KiB
2024-01-10T06:31:45.060154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6
5-th percentile-2
Q1-1
median0
Q30
95-th percentile0
Maximum5
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83306408
Coefficient of variation (CV)-2.0528932
Kurtosis3.2885823
Mean-0.4058
Median Absolute Deviation (MAD)0
Skewness-0.66126237
Sum-4058
Variance0.69399576
MonotonicityNot monotonic
2024-01-10T06:31:45.171005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 6032
60.3%
-1 2497
25.0%
-2 821
 
8.2%
1 381
 
3.8%
-3 146
 
1.5%
2 63
 
0.6%
3 28
 
0.3%
-4 17
 
0.2%
4 7
 
0.1%
-5 5
 
0.1%
Other values (2) 3
 
< 0.1%
ValueCountFrequency (%)
-6 2
 
< 0.1%
-5 5
 
0.1%
-4 17
 
0.2%
-3 146
 
1.5%
-2 821
 
8.2%
-1 2497
25.0%
0 6032
60.3%
1 381
 
3.8%
2 63
 
0.6%
3 28
 
0.3%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 7
 
0.1%
3 28
 
0.3%
2 63
 
0.6%
1 381
 
3.8%
0 6032
60.3%
-1 2497
25.0%
-2 821
 
8.2%
-3 146
 
1.5%
-4 17
 
0.2%

습도
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.8994
Minimum48
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:45.526997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum48
5-th percentile57
Q167
median77
Q388
95-th percentile97
Maximum100
Range52
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.450011
Coefficient of variation (CV)0.16189998
Kurtosis-0.97339308
Mean76.8994
Median Absolute Deviation (MAD)10
Skewness-0.017971121
Sum768994
Variance155.00278
MonotonicityNot monotonic
2024-01-10T06:31:45.647354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
64 325
 
3.2%
90 313
 
3.1%
79 295
 
2.9%
75 293
 
2.9%
66 288
 
2.9%
82 285
 
2.9%
80 285
 
2.9%
76 280
 
2.8%
71 279
 
2.8%
74 271
 
2.7%
Other values (43) 7086
70.9%
ValueCountFrequency (%)
48 4
 
< 0.1%
49 14
 
0.1%
50 22
 
0.2%
51 19
 
0.2%
52 60
0.6%
53 61
0.6%
54 76
0.8%
55 93
0.9%
56 105
1.1%
57 119
1.2%
ValueCountFrequency (%)
100 35
 
0.4%
99 147
1.5%
98 143
1.4%
97 222
2.2%
96 199
2.0%
95 219
2.2%
94 240
2.4%
93 205
2.1%
92 198
2.0%
91 193
1.9%

강수형태
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9878 
1
 
122

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9878
98.8%
1 122
 
1.2%

Length

2024-01-10T06:31:45.748214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:31:45.822979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9878
98.8%
1 122
 
1.2%

낙뢰
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

풍향
Real number (ℝ)

ZEROS 

Distinct336
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.3067
Minimum0
Maximum360
Zeros202
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:45.906815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q146
median74
Q3140
95-th percentile338.05
Maximum360
Range360
Interquartile range (IQR)94

Descriptive statistics

Standard deviation102.69795
Coefficient of variation (CV)0.89844205
Kurtosis0.084003352
Mean114.3067
Median Absolute Deviation (MAD)33
Skewness1.2069597
Sum1143067
Variance10546.868
MonotonicityNot monotonic
2024-01-10T06:31:46.014198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 202
 
2.0%
54 171
 
1.7%
46 144
 
1.4%
53 132
 
1.3%
74 129
 
1.3%
51 124
 
1.2%
42 117
 
1.2%
65 115
 
1.1%
44 112
 
1.1%
58 111
 
1.1%
Other values (326) 8643
86.4%
ValueCountFrequency (%)
0 202
2.0%
1 16
 
0.2%
2 24
 
0.2%
3 27
 
0.3%
4 18
 
0.2%
5 6
 
0.1%
6 33
 
0.3%
7 27
 
0.3%
8 28
 
0.3%
9 46
 
0.5%
ValueCountFrequency (%)
360 11
 
0.1%
359 54
0.5%
358 56
0.6%
357 15
 
0.1%
356 19
 
0.2%
355 48
0.5%
354 16
 
0.2%
353 21
 
0.2%
352 40
0.4%
351 20
 
0.2%

풍속
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3635
Minimum0
Maximum8
Zeros2614
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:31:46.104975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1885744
Coefficient of variation (CV)0.87170837
Kurtosis1.6362995
Mean1.3635
Median Absolute Deviation (MAD)1
Skewness1.0131411
Sum13635
Variance1.412709
MonotonicityNot monotonic
2024-01-10T06:31:46.195635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 3346
33.5%
0 2614
26.1%
2 2567
25.7%
3 964
 
9.6%
4 371
 
3.7%
5 77
 
0.8%
6 36
 
0.4%
7 22
 
0.2%
8 3
 
< 0.1%
ValueCountFrequency (%)
0 2614
26.1%
1 3346
33.5%
2 2567
25.7%
3 964
 
9.6%
4 371
 
3.7%
5 77
 
0.8%
6 36
 
0.4%
7 22
 
0.2%
8 3
 
< 0.1%
ValueCountFrequency (%)
8 3
 
< 0.1%
7 22
 
0.2%
6 36
 
0.4%
5 77
 
0.8%
4 371
 
3.7%
3 964
 
9.6%
2 2567
25.7%
1 3346
33.5%
0 2614
26.1%

Interactions

2024-01-10T06:31:42.483171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:34.818297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.551805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.467654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.259422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.985050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.791229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.659932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.610924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.512786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.578695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:34.896321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.626753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.560945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.330813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.056407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.887257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.752008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.679434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.611445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.676741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:34.965025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.716355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.651470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.400882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.128689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.978650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.820611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.748256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.706620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.771131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.032160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.801641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.737300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.469915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.197663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.070189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.885338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.825952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.781070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.874938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.107006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.898275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.813127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.540769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.278907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.166607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.956823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.920862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.880024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.973855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.183452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.993107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.884495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.620389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.359332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.270425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.242927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.025786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.979199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:43.077560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.254411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.086139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.957879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.691786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.441803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.348236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.314724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.120371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.081033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:43.173301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.323268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.177699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.026154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.760417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.518480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.419107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.382076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.215030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.175250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:43.272402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.392733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.266489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.098760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.832263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.590314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.492121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.456026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.306104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.272988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:43.376672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:35.465100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:36.365996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.181412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:37.906435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:38.687381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:39.568320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:40.533505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:41.411108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:31:42.373800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:31:46.273243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X좌표Y좌표발표일자생활기상 발표시각기온1시간 강수량동서바람성분남북바람성분습도강수형태풍향풍속
X좌표1.0000.6440.0000.0000.2420.0850.2900.2900.2490.1430.3920.204
Y좌표0.6441.0000.0000.0000.2270.0800.2390.2550.1800.0340.3090.168
발표일자0.0000.0001.0000.3420.3980.0880.5110.3390.4700.0200.4350.605
생활기상 발표시각0.0000.0000.3421.0000.7980.1580.3920.3560.7420.2170.3250.321
기온0.2420.2270.3980.7981.0000.0990.4010.3510.8800.1150.3740.376
1시간 강수량0.0850.0800.0880.1580.0991.0000.1290.2040.1310.6730.1910.074
동서바람성분0.2900.2390.5110.3920.4010.1291.0000.3770.4830.0000.6770.843
남북바람성분0.2900.2550.3390.3560.3510.2040.3771.0000.3730.1520.6930.613
습도0.2490.1800.4700.7420.8800.1310.4830.3731.0000.1560.3940.426
강수형태0.1430.0340.0200.2170.1150.6730.0000.1520.1561.0000.1050.050
풍향0.3920.3090.4350.3250.3740.1910.6770.6930.3940.1051.0000.314
풍속0.2040.1680.6050.3210.3760.0740.8430.6130.4260.0500.3141.000
2024-01-10T06:31:46.374317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발표일자강수형태
발표일자1.0000.033
강수형태0.0331.000
2024-01-10T06:31:46.444535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
X좌표Y좌표생활기상 발표시각기온1시간 강수량동서바람성분남북바람성분습도풍향풍속발표일자강수형태
X좌표1.000-0.2410.002-0.0180.026-0.0020.046-0.063-0.071-0.1220.0000.109
Y좌표-0.2411.0000.0030.0590.054-0.0540.067-0.0530.016-0.0140.0000.026
생활기상 발표시각0.0020.0031.0000.5180.115-0.046-0.102-0.3960.0090.2100.2180.167
기온-0.0180.0590.5181.000-0.064-0.189-0.225-0.905-0.1020.3670.2610.089
1시간 강수량0.0260.0540.115-0.0641.0000.0410.0510.1150.0570.0050.0360.494
동서바람성분-0.002-0.054-0.046-0.1890.0411.0000.2020.3660.249-0.6490.3570.000
남북바람성분0.0460.067-0.102-0.2250.0510.2021.0000.2590.383-0.4860.2160.117
습도-0.063-0.053-0.396-0.9050.1150.3660.2591.0000.151-0.4670.3210.120
풍향-0.0710.0160.009-0.1020.0570.2490.3830.1511.000-0.1630.2900.081
풍속-0.122-0.0140.2100.3670.005-0.649-0.486-0.467-0.1631.0000.3290.049
발표일자0.0000.0000.2180.2610.0360.3570.2160.3210.2900.3291.0000.033
강수형태0.1090.0260.1670.0890.4940.0000.1170.1200.0810.0490.0331.000

Missing values

2024-01-10T06:31:43.529594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:31:43.718635image/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

X좌표Y좌표발표일자생활기상 발표시각기온1시간 강수량하늘상태동서바람성분남북바람성분습도강수형태낙뢰풍향풍속
42285611220230808200270<NA>-20910<NA>802
11175793202308081700350<NA>00560<NA>421
967356107202308071700290<NA>01840<NA>1491
29054610920230808300250<NA>01840<NA>1401
751162110202308081100310<NA>-10650<NA>742
59054811120230807300260<NA>0-1880<NA>3401
272255106202308072300250<NA>-10870<NA>1001
86544811020230808900300<NA>-10720<NA>991
2335998202308091600290<NA>00710<NA>511
372160100202308081400340<NA>00570<NA>381
X좌표Y좌표발표일자생활기상 발표시각기온1시간 강수량하늘상태동서바람성분남북바람성분습도강수형태낙뢰풍향풍속
14306110320230809600250<NA>-1-2850<NA>213
36176997202308081000310<NA>-20640<NA>892
63874811020230807600240<NA>00930<NA>60
44456211020230808400260<NA>00820<NA>1930
45075310120230808500270<NA>00790<NA>491
998955108202308071200330<NA>-10700<NA>671
1486629720230809900290<NA>-4-2690<NA>614
85916010420230808600260<NA>00910<NA>2460
48985996202308080260<NA>00950<NA>2970
947653108202308071600300<NA>03760<NA>1743