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"""Download latest time series data from MHL website and update local copy.
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D. Howe
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2019-08-30
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"""
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import os
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import pandas as pd
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# Set output directory
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output_dir = 'csv'
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# Define data URLs
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url = 'http://www.mhl.nsw.gov.au/data/realtime/timeseries/'
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txt_names = [
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'SYDDOW.WaveHeight.csv.dat.txt',
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'SYDDOW.WavePeriod.csv.dat.txt',
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]
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for txt_name in txt_names:
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# Read text file from MHL website
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df = pd.read_csv(url + txt_name, index_col=0, parse_dates=True)
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# Create name for exported data
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csv_name = os.path.join(input_dir, txt_name.replace('.dat.txt', ''))
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try:
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# Load local master table
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master = pd.read_csv(csv_name, index_col=0, parse_dates=True)
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# Only include timestamps that do not already exist
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df = df[~df.index.isin(master.index)]
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# Update master
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master = master.append(df)
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except FileNotFoundError:
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# Create new master table if none exists
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master = df
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# Export master table
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master.to_csv(csv_name)
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