def check_0711(): # conn = uo.connect('interval_ion') # check_match(conn, 'electric') # check_match(conn, 'gas') # conn.close() keys = ['mean', 'std', 'min', '25%', '50%', '75%', 'max', 'overall'] format_dict = {k: lambda x: '{0:.2f}'.format(x) for k in keys} uo.csv2html(os.getcwd() + '/input/FY/interval/ion_0627/cmp_euas/electric_ratio.csv', {'Unnamed: 0': 'Building_Number'}, format_dict) uo.csv2html(os.getcwd() + '/input/FY/interval/ion_0627/cmp_euas/gas_ratio.csv', {'Unnamed: 0': 'Building_Number'}, format_dict) return
def create_summary_daynightlean(): files = glob.glob(os.getcwd() + '/input/FY/interval/ion_0627/table/*.csv') for f in files: df = pd.read_csv(f) df['sortby'] = df['aggregate save%'].map(lambda x: float(x[:-1])) df.sort('sortby', ascending=False, inplace=True) df_out = df.copy() df_out.drop('sortby', axis=1, inplace=True) df_out.to_csv(f, index=False) for f in files: uo.csv2html(f) files = glob.glob(os.getcwd() + '/input/FY/interval/ion_0627/table/*.html') for f in files: shutil.copyfile(f, f.replace('/input/FY/interval/ion_0627/', '/plot_FY_weather/html/interval/')) return