cleaning a df for course exam!

# final option for reading and cleaning files!
name=os.path.splitext('coal_consumption_per_capita.xlsx')[0]
g1 =(pd.read_excel("exam/coal_consumption_per_capita.xlsx"))
g2=g1.rename(columns={'value':g1.columns[0],g1.columns[0]:'country'})
g2=pd.melt(g2,id_vars=['country'],var_name='year', value_name=name[:len(name)])
g2=g2[(g2['country'].str.contains("Turkey"))
        | (g2['country'].str.contains("Serbia") == True)
        | (g2['country'].str.contains("Bulgaria") == True)
        | (g2['country'].str.contains("Greece") == True)
        | (g2['country'].str.contains("Turkey") == True)
        | (g2['country'].str.contains("Macedonia") == True)]
g2 =g2.loc[~g2['country'].isin(['Serbia excluding Kosovo','Serbia and Montenegro'])]
g2['year'] = g2['year'].astype('int',errors='ignore')
g2[g2.columns[2]]=g2[g2.columns[2]].astype('float',errors='ignore').round(2)
g2= g2.drop(g2[g2.year <1990].index)
g2.reset_index(drop=True)