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src/preprocess.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Thu Jun  1 14:14:59 2023
+
+@author: ME
+"""
+
+from datetime import datetime
+import pandas as pd
+import joblib
+
+#load json file
+json_path = r"C:/Users/ME/Desktop/Blessing_AI/Weather_Prediction/Artifacts/feature_dict.joblib"
+loaded_data = joblib.load(json_path)
+
+def preprocess_data(start_d,end_d,airport_name):
+    y, m , d = start_d
+    y2 , m2, d2 = end_d
+    start_date = datetime(y,m,d)
+    end_date = datetime(y2,m2,d2)
+    
+    date_range = pd.date_range(start=start_date, end=end_date, freq='D')
+    df_pred = pd.DataFrame(columns=["ds","NAME","ELEVATION","month","day"])
+    airport_encoded = loaded_data["Airport_name"][airport_name]
+    elevation = loaded_data["elevation"][airport_name]
+    for date in date_range:
+        day = date.day
+        month = date.month
+        df_pred = df_pred.append({'ds':date,"NAME":airport_encoded,"ELEVATION":elevation, 'month': month, 'day': day}, ignore_index=True)
+    return df_pred