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