#import dataĭf=pd.read_excel(r'C:\file.xlsx',sheet_name='sheetname')ĭf = df.replace(r'^\s*$', np.nan, regex=True) #converts blank cells to NaNĭf.dropna(subset =, inplace=True) #removing rows where a cell in a given column has a NaN Should be analogous to any other directional data. So, my data are from an offshore buoy which recorded wave heights and directions the waves come from. Well it’s definitely not an optimal code, I am not a programmer.
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