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\n \n \n | \n Status | \n
\n \n | Status | \n | \n
\n \n \n \n | DB | \n 217 | \n
\n \n | ET | \n 152 | \n
\n \n | EX | \n 110 | \n
\n \n | HU | \n 6766 | \n
\n \n | LO | \n 1828 | \n
\n \n | PT | \n 6 | \n
\n \n | SD | \n 4 | \n
\n \n | SS | \n 7 | \n
\n \n | ST | \n 6 | \n
\n \n | TD | \n 6965 | \n
\n \n | TS | \n 10076 | \n
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". With a Weather API From Metomatics You Get: Our weather API as SaaS: we provide the API and the IT infrastructure - you use the API, Fast, direct and easy access to worldwide weather, environmental, climate, ocean and water data, Model data (ECMWF, UKMO, etc. Meteomatics' science and engineering teams are continuously working on comprehensive documentation that ensures users from all industries can leverage the value provided by the API for their purposes. The top-level includes locations and columns information. In your script you may want to extract these as parameters to the script. "text/html": "
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\n \n \n | \n Maximum Wind | \n Minimum Pressure | \n Low Wind NE | \n Low Wind SE | \n Low Wind SW | \n Low Wind NW | \n Moderate Wind NE | \n Moderate Wind SE | \n Moderate Wind SW | \n Moderate Wind NW | \n High Wind NE | \n High Wind SE | \n High Wind SW | \n High Wind NW | \n
\n \n \n \n | 14735 | \n 100 | \n 960 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n
\n \n | 23277 | \n 25 | \n 1010 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n
\n \n | 5563 | \n 35 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n
\n \n | 26134 | \n 30 | \n 1008 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n
\n \n | 6073 | \n 25 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n
\n \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n | \n
\n \n | 23038 | \n 65 | \n 987 | \n 70 | \n 70 | \n 50 | \n 70 | \n 30 | \n 30 | \n 25 | \n 30 | \n 15 | \n 15 | \n 10 | \n 15 | \n
\n \n | 24599 | \n 105 | \n 958 | \n 80 | \n 70 | \n 60 | \n 70 | \n 40 | \n 40 | \n 40 | \n 40 | \n 20 | \n 20 | \n 15 | \n 20 | \n
\n \n | 22508 | \n 25 | \n 1007 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n 0 | \n
\n \n | 18047 | \n 25 | \n 1006 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n
\n \n | 10672 | \n 45 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n -999 | \n
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7842 rows 14 columns
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", "text/plain": " Maximum Wind Minimum Pressure Low Wind NE Low Wind SE Low Wind SW Low Wind NW Moderate Wind NE Moderate Wind SE Moderate Wind SW Moderate Wind NW High Wind NE High Wind SE \\\n14735 100 960 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 \n23277 25 1010 0 0 0 0 0 0 0 0 0 0 \n5563 35 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 \n26134 30 1008 0 0 0 0 0 0 0 0 0 0 \n6073 25 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 \n \n23038 65 987 70 70 50 70 30 30 25 30 15 15 \n24599 105 958 80 70 60 70 40 40 40 40 20 20 \n22508 25 1007 0 0 0 0 0 0 0 0 0 0 \n18047 25 1006 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 \n10672 45 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 -999 \n\n High Wind SW High Wind NW \n14735 -999 -999 \n23277 0 0 \n5563 -999 -999 \n26134 0 0 \n6073 -999 -999 \n \n23038 10 15 \n24599 15 20 \n22508 0 0 \n18047 -999 -999 \n10672 -999 -999 \n\n[7842 rows x 14 columns]", "text": "[10 10 10 4 4 4]\n 0\n0 \n3 6813\n4 2985\n9 5619\n10 10720\n\n Accuracy Score\n0.7632092436010254\n\nClassification Report\n precision recall f1-score support\n\n 0 0.00 0.00 0.00 217\n 1 0.00 0.00 0.00 152\n 2 0.00 0.00 0.00 110\n 3 0.86 0.86 0.86 6766\n 4 0.55 0.91 0.69 1828\n 5 0.00 0.00 0.00 6\n 6 0.00 0.00 0.00 4\n 7 0.00 0.00 0.00 7\n 8 0.00 0.00 0.00 6\n 9 0.76 0.62 0.68 6965\n 10 0.76 0.81 0.78 10076\n\n accuracy 0.76 26137\n macro avg 0.27 0.29 0.27 26137\nweighted avg 0.76 0.76 0.76 26137\n\nConfusion Matrix\n[[ 0 0 0 0 217 0 0 0 0 0 0]\n [ 0 0 0 6 0 0 0 0 0 111 35]\n [ 0 0 0 12 16 0 0 0 0 51 31]\n [ 0 0 0 5847 0 0 0 0 0 0 919]\n [ 0 0 0 22 1655 0 0 0 0 129 22]\n [ 0 0 0 0 4 0 0 0 0 0 2]\n [ 0 0 0 0 4 0 0 0 0 0 0]\n [ 0 0 0 0 0 0 0 0 0 0 7]\n [ 0 0 0 6 0 0 0 0 0 0 0]\n [ 0 0 0 28 1089 0 0 0 0 4295 1553]\n [ 0 0 0 892 0 0 0 0 0 1033 8151]]\n", "text": "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:763: ConvergenceWarning: lbfgs failed to converge (status=1):\nSTOP: TOTAL NO. Setting up the MySQL Database. SQL Server Import and Export Wizard python sql-server import ssms backup Share Improve this question Follow The first part of the sets up some variables to customize the weather data that is entered. In a free test account, we offer you the opportunity to familiarize yourself with the full scope of the weather API.
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