29 lines
931 B
Python
29 lines
931 B
Python
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import Data_Analysis as DA
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import pandas as pd
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import os
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propIds = DA.getuniquePropIdFromDB()
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for propId in propIds:
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name = f"dok/calendarData_prop{propId}.csv"
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if not os.path.exists(name):
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print(propId)
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scrapeDates, calendarData = DA.getDataFromDB(propId)
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if DA.checkForLostProprty(calendarData):
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print(f"Lost Proprty: {propId}")
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else:
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scrapeDates = DA.reformatScrapeDates(scrapeDates)
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HeaderDates = DA.getMinMaxDate(calendarData)
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data = DA.creatDataMatrix(HeaderDates, calendarData)
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# Transform to Dataframe for Plotly
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df = pd.DataFrame(data, columns=HeaderDates)
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df.insert(0, "ScrapeDate", scrapeDates, True)
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df = df.drop(index=0) # Irregulärer Abstand in den Scraping Zeiten (nur 2 Tage)
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df = df.drop(df.columns[[1, 2]], axis=1)
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df.to_csv(name, index=False)
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