>>> df.sort_values(by=['col1']) col1 col2 col3 0 A 2 0 1 A 1 1 2 B 9 9 5 C 4 3 4 D 7 2 3 NaN 8 4
df.sort_values(by='col1', ascending=False)
#Python, Pandas #Sorting dataframe df on the values of a column col1 #Temporary df.sort_values(by=["col1"]) #Permanent df.sort_values(by=["col1"], inplace = True)
final_df = df.sort_values(by=['2'], ascending=False)
df.sort_values(by='col1', ascending=False, na_position='first', inplace=True)
df.rename(columns={1:'month'},inplace=True) df['month'] = pd.Categorical(df['month'],categories=['December','November','October','September','August','July','June','May','April','March','February','January'],ordered=True) df = df.sort_values('month',ascending=False)
sorted = df.sort_values('column-to-sort-on', ascending=False) #or df.sort_values('name', inplace=True)
df = df.reindex(sorted(df.columns), axis=1)