df_sym_col[cmp['symbol']] = cmp['df_name'] # Solve each row of the dataframe for idx, row in df.iterrows(): eqns_tosolve = eqns[:] # add equation of symbol and its values from provided df for col in df_sym_col: eqns_tosolve.append(sp.Eq(col, row[df_sym_col[col]])) soln = sp.solve(eqns_tosolve) if soln: print idx, eqns_tosolve, soln df.loc[idx, "Calculated Poisson's ratio"] = round( soln[0][sp.S('nu')], 2) return df if __name__ == '__main__': pd.set_option('display.width', 1000) # df1 = pd.read_pickle('39135_BMG.pkl') df = CitrineDataRetrieval().get_dataframe(data_set_id=150628, max_results=50) df = df.groupby(['chemicalFormula'], as_index=False).sum() print df new_df = decorate_dataframe(df) print new_df
if cmp['catalog_name'] in mech_props: eqns.append(sp.Eq(mech_props[cmp['catalog_name']]().equation())) df_sym_col[cmp['symbol']] = cmp['df_name'] # Solve each row of the dataframe for idx, row in df.iterrows(): eqns_tosolve = eqns[:] # add equation of symbol and its values from provided df for col in df_sym_col: eqns_tosolve.append(sp.Eq(col, row[df_sym_col[col]])) soln = sp.solve(eqns_tosolve) if soln: print(idx, eqns_tosolve, soln) df.loc[idx, "Calculated Poisson's ratio"] = round(soln[0][sp.S('nu')], 2) return df if __name__ == '__main__': pd.set_option('display.width', 1000) # df1 = pd.read_pickle('39135_BMG.pkl') df = CitrineDataRetrieval().get_dataframe(data_set_id=150628, max_results=50) df = df.groupby(['chemicalFormula'], as_index=False).sum() print(df) new_df = decorate_dataframe(df) print(new_df)