sort dataframe by column

>>> 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)