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)
