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37 def readcsv(filename, header=True): 38 return pd.read_csv(filename, header=None) if not header else pd.read_csv(filename)
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10 def __read(filename): 11 field_names = ['date', 'value', 'metaID'] 12 entry_format = '<qdi' # long, double, int; See field names above. 13 entry_size = calcsize(entry_format) 14 15 if not os.path.exists(filename): 16 return pd.DataFrame(None, columns = ['date', 'value', 'metaID']) 17 18 records = np.fromfile(filename, dtype=np.dtype({'names':field_names, 'formats': entry_format[1:]})) 19 20 if len(records) == 0: return pd.DataFrame(None, columns = ['date', 'value', 'metaID']) 21 22 df = pd.DataFrame(records, columns = field_names) 23 df['date'] = pd.to_datetime(df['date'], unit='s') 24 df = df.set_index('date') 25 26 meta_ids = df.metaID 27 df.loc[df.metaID == METADATA_MISSING_VALUE] = np.nan 28 df.metaID = meta_ids 29 30 return df
8 def read_txt(txt): 9 f = open(txt, 'r') 10 lines = f.readlines() 11 f.close() 12 return [tmp.strip() for tmp in lines]