<jupyter_start><jupyter_text>Loading and preparing dataget raw data from ASCII file<jupyter_code>fn = 'raw_Blankenese_WL.txt'
df = pd.read_csv(fn, sep='\s+', header=0, names=['Date', 'Time', 'WL [cm]'], usecols= [0,1,2], 
    parse_dates=[['Date', 'Time']], index_col='Date_Time')
df.plot();<jupyter_output><empty_output><jupyter_text>select daterange and make sure it comprises only equidistant timesteps of 5 mins<jupyter_code>df_cut = df['2016':'2017']
df_cut = df_cut.resample('5T').mean()
df_cut.plot();<jupyter_output><empty_output><jupyter_text>convert from cm to m<jupyter_code>df_cut = df_cut/100
df_cut.plot();<jupyter_output><empty_output>
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{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '525635', 'license': 'MIT', 'n_tokens_mistral': 275, 'n_tokens_neox': 260, 'n_words': 46, 'path': 'talk_5_notebooks_vs_scripts/notebooks_project_work/data.ipynb', 'repo_name': 'DHI/datatalks', 'size': '650'}