Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory761.7 KiB
Average record size in memory78.0 B

Variable types

DateTime2
Numeric6

Dataset

Description한국공항공사(KAC)가 제공하는 항로 기상관측 정보로 상공의 항공기로부터 정보를 받아 항로의 기상정보로 변환하여 제공합니다.
Author한국공항공사
URLhttps://www.data.go.kr/data/15110012/fileData.do

Alerts

고도(m) is highly overall correlated with 온도(섭씨) and 1 other fieldsHigh correlation
온도(섭씨) is highly overall correlated with 고도(m) and 1 other fieldsHigh correlation
풍속(kn) is highly overall correlated with 고도(m) and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-12 15:05:25.232078
Analysis finished2023-12-12 15:05:31.725781
Duration6.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜(KST)
Date

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-10-12 00:00:00
Maximum2022-10-21 00:00:00
2023-12-13T00:05:31.770571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.879234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

시간(KST)
Date

Distinct9315
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-13 00:00:05
Maximum2023-12-13 23:59:46
2023-12-13T00:05:31.998291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:32.108675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위도
Real number (ℝ)

Distinct6169
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.138409
Minimum35.4526
Maximum39.1513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:05:32.247165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.4526
5-th percentile36.43407
Q136.982275
median37.20235
Q337.3618
95-th percentile37.55331
Maximum39.1513
Range3.6987
Interquartile range (IQR)0.379525

Descriptive statistics

Standard deviation0.34730523
Coefficient of variation (CV)0.0093516454
Kurtosis2.6354267
Mean37.138409
Median Absolute Deviation (MAD)0.18055
Skewness-0.7997582
Sum371384.09
Variance0.12062092
MonotonicityNot monotonic
2023-12-13T00:05:32.375899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3253 12
 
0.1%
37.1949 11
 
0.1%
37.3254 10
 
0.1%
37.1996 10
 
0.1%
37.1866 10
 
0.1%
37.209 9
 
0.1%
37.5061 9
 
0.1%
37.1924 8
 
0.1%
37.1938 8
 
0.1%
37.2014 8
 
0.1%
Other values (6159) 9905
99.1%
ValueCountFrequency (%)
35.4526 1
< 0.1%
35.6072 1
< 0.1%
35.6661 1
< 0.1%
35.8481 1
< 0.1%
35.8568 1
< 0.1%
35.8613 1
< 0.1%
35.8634 1
< 0.1%
35.8645 1
< 0.1%
35.8659 1
< 0.1%
35.8684 1
< 0.1%
ValueCountFrequency (%)
39.1513 1
< 0.1%
39.148 2
< 0.1%
39.1479 1
< 0.1%
39.1367 1
< 0.1%
39.1274 1
< 0.1%
39.1232 1
< 0.1%
39.12 1
< 0.1%
39.1056 1
< 0.1%
39.1032 1
< 0.1%
39.098 1
< 0.1%

경도
Real number (ℝ)

Distinct8022
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.91923
Minimum123.3549
Maximum130.5705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:05:32.500896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123.3549
5-th percentile125.21594
Q1126.4033
median126.9953
Q3127.36165
95-th percentile128.47211
Maximum130.5705
Range7.2156
Interquartile range (IQR)0.95835

Descriptive statistics

Standard deviation0.93626351
Coefficient of variation (CV)0.0073768449
Kurtosis1.3778006
Mean126.91923
Median Absolute Deviation (MAD)0.44725
Skewness-0.15538041
Sum1269192.3
Variance0.87658937
MonotonicityNot monotonic
2023-12-13T00:05:32.627262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9979 13
 
0.1%
126.9977 12
 
0.1%
126.9973 12
 
0.1%
127.0001 11
 
0.1%
126.9967 10
 
0.1%
126.9976 9
 
0.1%
126.9963 9
 
0.1%
126.9959 8
 
0.1%
126.9933 8
 
0.1%
127.001 8
 
0.1%
Other values (8012) 9900
99.0%
ValueCountFrequency (%)
123.3549 1
< 0.1%
123.518 1
< 0.1%
123.5273 1
< 0.1%
123.5375 1
< 0.1%
123.555 1
< 0.1%
123.5618 1
< 0.1%
123.565 1
< 0.1%
123.5811 1
< 0.1%
123.586 1
< 0.1%
123.5881 1
< 0.1%
ValueCountFrequency (%)
130.5705 1
< 0.1%
130.322 1
< 0.1%
130.2367 1
< 0.1%
130.202 1
< 0.1%
130.1547 1
< 0.1%
130.1337 1
< 0.1%
130.101 1
< 0.1%
130.088 1
< 0.1%
130.0744 1
< 0.1%
130.0326 1
< 0.1%

고도(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct2180
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5651.8563
Minimum1604
Maximum14207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:05:32.813864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1604
5-th percentile1992
Q13280
median4876
Q37475
95-th percentile11582
Maximum14207
Range12603
Interquartile range (IQR)4195

Descriptive statistics

Standard deviation2948.6304
Coefficient of variation (CV)0.52171008
Kurtosis-0.50809145
Mean5651.8563
Median Absolute Deviation (MAD)1928
Skewness0.71922138
Sum56518563
Variance8694421.3
MonotonicityNot monotonic
2023-12-13T00:05:32.947931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4876 167
 
1.7%
11277 155
 
1.6%
11887 117
 
1.2%
10972 108
 
1.1%
7010 99
 
1.0%
5486 74
 
0.7%
10058 73
 
0.7%
11582 72
 
0.7%
10668 72
 
0.7%
12192 69
 
0.7%
Other values (2170) 8994
89.9%
ValueCountFrequency (%)
1604 5
0.1%
1607 5
0.1%
1611 1
 
< 0.1%
1615 8
0.1%
1619 2
 
< 0.1%
1623 7
0.1%
1626 4
< 0.1%
1630 7
0.1%
1634 3
 
< 0.1%
1638 7
0.1%
ValueCountFrequency (%)
14207 1
 
< 0.1%
13738 1
 
< 0.1%
13716 2
 
< 0.1%
13106 2
 
< 0.1%
12961 1
 
< 0.1%
12527 2
 
< 0.1%
12523 1
 
< 0.1%
12519 2
 
< 0.1%
12496 57
0.6%
12492 4
 
< 0.1%

온도(섭씨)
Real number (ℝ)

HIGH CORRELATION 

Distinct3198
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-15.28372
Minimum-63.34
Maximum17.15
Zeros0
Zeros (%)0.0%
Negative7972
Negative (%)79.7%
Memory size166.0 KiB
2023-12-13T00:05:33.080364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-63.34
5-th percentile-50.06
Q1-26.9525
median-10.655
Q3-1.89
95-th percentile7.11
Maximum17.15
Range80.49
Interquartile range (IQR)25.0625

Descriptive statistics

Standard deviation17.662847
Coefficient of variation (CV)-1.1556641
Kurtosis-0.56714149
Mean-15.28372
Median Absolute Deviation (MAD)11.105
Skewness-0.67870168
Sum-152837.2
Variance311.97617
MonotonicityNot monotonic
2023-12-13T00:05:33.234354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-16.32 79
 
0.8%
-1.44 65
 
0.7%
4.64 46
 
0.5%
7.93 35
 
0.4%
-6.9 34
 
0.3%
6.68 32
 
0.3%
3.48 31
 
0.3%
2.35 30
 
0.3%
5.81 30
 
0.3%
-5.58 27
 
0.3%
Other values (3188) 9591
95.9%
ValueCountFrequency (%)
-63.34 1
 
< 0.1%
-62.84 1
 
< 0.1%
-62.81 1
 
< 0.1%
-61.55 1
 
< 0.1%
-59.22 1
 
< 0.1%
-58.97 3
< 0.1%
-58.72 1
 
< 0.1%
-57.45 5
0.1%
-57.32 1
 
< 0.1%
-57.19 4
< 0.1%
ValueCountFrequency (%)
17.15 1
< 0.1%
15.66 1
< 0.1%
15.59 1
< 0.1%
15.23 1
< 0.1%
14.0 1
< 0.1%
13.68 2
< 0.1%
13.58 1
< 0.1%
13.52 1
< 0.1%
13.49 1
< 0.1%
13.47 1
< 0.1%

풍향(각도)
Real number (ℝ)

Distinct6248
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean267.7459
Minimum0.27
Maximum357.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:05:33.363701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile188.2995
Q1256.48
median269.64
Q3290.07
95-th percentile331.0235
Maximum357.94
Range357.67
Interquartile range (IQR)33.59

Descriptive statistics

Standard deviation50.009779
Coefficient of variation (CV)0.18678074
Kurtosis10.076866
Mean267.7459
Median Absolute Deviation (MAD)15.63
Skewness-2.6279095
Sum2677459
Variance2500.978
MonotonicityNot monotonic
2023-12-13T00:05:33.490648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
271.19 8
 
0.1%
258.89 8
 
0.1%
259.86 7
 
0.1%
252.41 7
 
0.1%
254.12 7
 
0.1%
269.56 7
 
0.1%
261.63 7
 
0.1%
262.11 7
 
0.1%
260.69 7
 
0.1%
264.38 7
 
0.1%
Other values (6238) 9928
99.3%
ValueCountFrequency (%)
0.27 1
< 0.1%
0.53 1
< 0.1%
0.71 1
< 0.1%
0.76 1
< 0.1%
1.24 1
< 0.1%
2.03 1
< 0.1%
2.29 1
< 0.1%
2.47 1
< 0.1%
2.56 1
< 0.1%
2.77 1
< 0.1%
ValueCountFrequency (%)
357.94 1
< 0.1%
357.86 1
< 0.1%
357.63 1
< 0.1%
357.5 1
< 0.1%
357.37 1
< 0.1%
357.24 1
< 0.1%
355.15 1
< 0.1%
354.51 1
< 0.1%
354.43 1
< 0.1%
354.23 1
< 0.1%

풍속(kn)
Real number (ℝ)

HIGH CORRELATION 

Distinct5970
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.981012
Minimum0.05
Maximum157.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:05:33.621443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile5.32
Q118.71
median35.15
Q360.64
95-th percentile109.0605
Maximum157.35
Range157.3
Interquartile range (IQR)41.93

Descriptive statistics

Standard deviation31.538357
Coefficient of variation (CV)0.73377418
Kurtosis0.5171095
Mean42.981012
Median Absolute Deviation (MAD)19.06
Skewness1.0131555
Sum429810.12
Variance994.66796
MonotonicityNot monotonic
2023-12-13T00:05:33.765554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 11
 
0.1%
16.03 10
 
0.1%
4.0 10
 
0.1%
4.14 9
 
0.1%
6.24 9
 
0.1%
4.12 8
 
0.1%
2.25 8
 
0.1%
8.0 8
 
0.1%
8.04 8
 
0.1%
21.39 7
 
0.1%
Other values (5960) 9912
99.1%
ValueCountFrequency (%)
0.05 1
< 0.1%
0.6 1
< 0.1%
0.63 1
< 0.1%
0.64 1
< 0.1%
0.82 1
< 0.1%
0.86 1
< 0.1%
0.95 1
< 0.1%
0.97 1
< 0.1%
0.99 1
< 0.1%
1.17 1
< 0.1%
ValueCountFrequency (%)
157.35 1
< 0.1%
155.58 1
< 0.1%
155.07 1
< 0.1%
154.57 1
< 0.1%
153.91 1
< 0.1%
153.88 1
< 0.1%
153.25 1
< 0.1%
153.06 1
< 0.1%
152.43 1
< 0.1%
152.21 1
< 0.1%

Interactions

2023-12-13T00:05:30.815413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.872948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.477962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.177277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.915152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.052541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.946441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:26.963413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.582404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.305699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:29.079286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.179870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.050118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.063443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.704716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.439615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:29.214507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.309818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.150780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.165942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.807110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.548913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:29.668193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.420681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.270143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.266320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.917343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.669000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:29.779950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.544100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:31.398865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:27.380444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.059539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:28.788462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:29.913581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:05:30.679331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:05:33.856720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜(KST)위도경도고도(m)온도(섭씨)풍향(각도)풍속(kn)
날짜(KST)1.0000.0690.0740.1050.3760.7170.628
위도0.0691.0000.6620.4000.3590.1190.320
경도0.0740.6621.0000.6810.6570.2250.547
고도(m)0.1050.4000.6811.0000.9330.3940.780
온도(섭씨)0.3760.3590.6570.9331.0000.3960.761
풍향(각도)0.7170.1190.2250.3940.3961.0000.506
풍속(kn)0.6280.3200.5470.7800.7610.5061.000
2023-12-13T00:05:34.259249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도고도(m)온도(섭씨)풍향(각도)풍속(kn)
위도1.000-0.282-0.2140.1780.009-0.150
경도-0.2821.0000.251-0.244-0.0190.199
고도(m)-0.2140.2511.000-0.947-0.0030.782
온도(섭씨)0.178-0.244-0.9471.000-0.155-0.773
풍향(각도)0.009-0.019-0.003-0.1551.000-0.056
풍속(kn)-0.1500.1990.782-0.773-0.0561.000

Missing values

2023-12-13T00:05:31.544229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:05:31.667740image/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

날짜(KST)시간(KST)위도경도고도(m)온도(섭씨)풍향(각도)풍속(kn)
66512022-10-1216:55:3537.4541126.578931240.36172.634.12
345572022-10-1512:32:4436.1131126.97327322-20.45273.4360.78
476862022-10-1615:32:1836.9966127.70315817-9.96251.2962.89
726842022-10-1908:26:1337.2012126.234219690.84335.6921.26
182832022-10-1319:01:3837.0367127.038829671.23244.498.43
924292022-10-2106:38:0537.2025125.60511887-52.49274.18112.58
292732022-10-1421:45:0437.0306126.76365368-8.21266.5743.77
181342022-10-1318:32:2137.3091127.0999189311.18300.534.06
67832022-10-1217:06:2737.06127.44514537-9.62341.864.84
245892022-10-1413:35:1837.5567126.596221334.03205.5646.13
날짜(KST)시간(KST)위도경도고도(m)온도(섭씨)풍향(각도)풍속(kn)
161062022-10-1315:04:0437.6429128.413710668-46.01291.3663.51
755062022-10-1913:37:3037.5061126.267619460.27331.1624.82
45552022-10-1213:16:0637.3463125.38397559-30.41319.189.19
720872022-10-1907:16:0937.0447127.23453364-9.06307.6923.31
78512022-10-1218:51:5935.8634126.94547307-28.41320.0724.86
505422022-10-1619:40:0137.2427127.190225032.29287.7321.89
88162022-10-1220:47:4436.0783126.96967585-28.14322.220.23
24072022-10-1209:28:1737.3194126.9566435-23.61325.9612.81
497692022-10-1618:22:5137.0571127.57285478-12.54255.162.98
783392022-10-1918:14:1437.3204126.59563962-4.3333.4128.53